ABSTRACT 
 
 
Title of Thesis: FATE AND TRANSPORT OF NITROGEN AT A DEEP ROW 
BIOSOLIDS APPLICATION HYBRID POPLAR TREE FARM 
 
 Carrie Buswell, Master of Engineering, 2006 
 
 
Thesis Directed By: Dr. Gary Felton 
 Department of Biological Resources Engineering 
 
 
 This study focused on a gravel mine reclamation site using biosolids in deep rows 
as a nutrient source and hybrid poplar trees as the stabilizing crop.  Biosolids application 
rates of 481, 962, and 1443 dry Mg/ha and tree densities of 0, 716, and 1074 trees/ha and 
controls (0 dry Mg/ha ? 0 trees/ha) were studied.  Total nitrogen, ammonium, nitrite and 
nitrate in soil water samples from pan and suction lysimeters under and around the 
biosolids rows were evaluated.  Total nitrogen was predominantly in the form of 
ammonium.  Ammonium concentrations in more than half the samples were above 100 
mg/L, reflecting the average biosolids concentration of 2,300 mg/kg.  No significant 
differences (? = 0.05) were determined between application rates or tree densities, but 
ammonium concentration significantly decreased with distance below the biosolids row.  
Nitrite and nitrate nitrogen concentrations were predominantly non-detects or less than 1 
mg/L, indicating that nitrification was not occurring. 
 
 
 
TRANSPORT AND FATE OF NITROGEN AT A DEEP ROW BIOSOLIDS 
APPLICATION HYBRID POPLAR TREE FARM 
 
 
 
by 
 
 
Carrie U. Buswell 
 
 
 
 
Thesis submitted to the Faculty of the Graduate School of the 
University of Maryland, College Park in partial fulfillment 
of the requirements for the degree of 
Master of Engineering 
2006 
 
 
 
 
 
 
 
 
Advisory Committee: 
 
 Dr. Gary Felton, Chair 
 Dr. Scott Angle 
 Dr. Adel Shirmohammadi 
 
 
 
 ii
TABLE OF CONTENTS 
Chapter 1:  Introduction .................................................................................................. 1 
Chapter 2:  Review of Literature .................................................................................... 6 
The Nitrogen Cycle ......................................................................................................... 6 
Land Application of Sewage Sludge ............................................................................. 15 
Trenching of Sewage Sludge......................................................................................... 17 
Use of Zero-Tension (Pan) Lysimeters and Suction Lysimeters to Collect Soil Water 
Samples ......................................................................................................................... 22 
Hybrid Poplar Trees and Their Use With Pollution Management ............................... 25 
Research at the ERCO Site ........................................................................................... 27 
Chapter 3:  Objectives.................................................................................................... 30 
Chapter 4:  Methods and Materials .............................................................................. 31 
Site Location and Characteristics................................................................................. 31 
Experimental Design..................................................................................................... 34 
Biosolids Characteristics and Application ................................................................... 40 
Planting of Hybrid Poplar Clones ................................................................................ 51 
Pan Lysimeter Installation............................................................................................ 54 
Suction Lysimeter Installation ...................................................................................... 70 
Sample Collection ......................................................................................................... 81 
Soil Water Samples................................................................................................... 81 
Biosolids Samples..................................................................................................... 85 
Soil Core Samples..................................................................................................... 86 
Rain Gauge Data....................................................................................................... 86 
 
 iii
Laboratory Analysis of Soil Water, Biosolids and Soil Samples .................................. 87 
Soil Water Samples................................................................................................... 87 
Biosolids Samples..................................................................................................... 89 
Soil Core Samples..................................................................................................... 89 
Data Analysis................................................................................................................ 93 
Chapter 5.  Results and Discussion ............................................................................... 97 
Biosolids Samples ......................................................................................................... 98 
Hydraulic Conductivity............................................................................................... 101 
Rain Gauge Data ........................................................................................................ 112 
Soil Water Analysis and Results:  Overview............................................................... 119 
Soil Water Results:  Total Nitrogen and Ammonium (NH4+-N) Data ........................ 128 
Pan Lysimeter Samples........................................................................................... 130 
Statistical Analysis.............................................................................................. 137 
Suction Lysimeter Samples..................................................................................... 141 
Rainfall Flushing Effect...................................................................................... 154 
Statistical Analysis.............................................................................................. 156 
Conclusions............................................................................................................. 174 
Soil Water Results:  Nitrite (NO2-) Data..................................................................... 176 
Pan Lysimeter Samples........................................................................................... 176 
Statistical Analysis.............................................................................................. 182 
Suction Lysimeter Samples..................................................................................... 184 
Rainfall Flushing Effect...................................................................................... 192 
Statistical Analysis.............................................................................................. 192 
 
 iv
Conclusions............................................................................................................. 198 
Soil Water Results:  Nitrate (NO3-) Data.................................................................... 200 
Pan Lysimeter Samples........................................................................................... 200 
Statistical Analysis.............................................................................................. 206 
Suction Lysimeter Samples..................................................................................... 209 
Rainfall Flushing Effect...................................................................................... 218 
Statistical Analysis.............................................................................................. 219 
Conclusions............................................................................................................. 222 
Conclusions.................................................................................................................... 224 
Future Work.................................................................................................................. 228 
Appendix 1 ? Pan and Suction Lysimeter Installation Details ....................................... 230 
Pan Installation Diagrams.......................................................................................... 230 
Pan Lysimeter Installation Tables .............................................................................. 260 
Suction Lysimeter Installation Tables......................................................................... 265 
Appendix 2 ? Supplemental Results............................................................................... 277 
Biosolids Supplemental Results .................................................................................. 277 
Hydraulic Conductivity Supplemental Results............................................................ 280 
Total Nitrogen and Ammonium Supplemental Results ............................................... 281 
Nitrate pan lysimeter statistical results:..................................................................... 294 
References...................................................................................................................... 295 
 
 
 
 v
LIST OF TABLES 
Table 1.  Determination of biosolids application rates needed to meet nitrogen loading 
rate design (S.I. Units). ..................................................................................................... 47 
Table 2.  Determination of biosolids application rates needed to meet nitrogen loading 
rate design (non-S.I. Units)............................................................................................... 47 
Table 3.  Determination of wet Mg of biosolids required per 21.3m (70 ft) row (S.I. 
Units)................................................................................................................................. 47 
Table 4.  Determination of wet tons of biosolids required per 70-foot row (non-S.I. 
Units)................................................................................................................................. 48 
Table 5.  Determination of cm of biosolids needed per application rate (S.I. Units). ...... 49 
Table 6.  Determination of inches of biosolids needed per application rate (non-S.I. 
Units)................................................................................................................................. 50 
Table 7.  Back calculation of kg N/ha applied (S.I. Units)............................................... 50 
Table 8.  Back calculation of lbs N/acre applied (non-S.I. Units). ................................... 50 
Table 9.  Quarterly assignments for monthly samples...................................................... 94 
Table 10.  Biosolids analysis results (wet weight basis)................................................... 98 
Table 11.  Biosolids analysis results (dry weight basis). .................................................. 98 
Table 12.  Biosolids results: revised after removal of outliers (dry weight basis)............ 99 
Table 13.  Biosolids leachate travel time calculated for each subplot............................ 110 
Table 14.  Rainfall travel time through soil profile to sampling equipment depth......... 116 
Table 15.  Summary of pan and suction lysimeter sampling activities. ......................... 119 
Table 16.  Overall comparison of total nitrogen and ammonium values........................ 130 
Table 17.  Frequency of pan lysimeter results in successive concentration ranges........ 130 
 
 vi
Table 18.  Frequency of suction lysimeter results in successive concentration ranges. . 141 
Table 19.  Comparison of suction lysimeter positions for results > 100 mg/L............... 153 
Table 20.  Tabulation of control by position results that are less than other treatments. 160 
Table 21.  Application rate-tree density combinations with quarterly differences......... 163 
Table 22.  Nitrate pan lysimeter results close to and greater than 1 mg/L. .................... 203 
Table 23.  Nitrate pan lysimeter: application rate by tree density quarterly differences.208 
Table 24.  Nitrate suction lysimeter results close to and greater than 1 mg/L................ 217 
Table 25.  Pan lysimeter installation information ? all blocks. ...................................... 260 
Table 26.  Pan installation notes ? block 1. .................................................................... 262 
Table 27.  Pan installation notes ? block 2. .................................................................... 263 
Table 28.  Pan installation notes ? block 3. .................................................................... 264 
Table 29.  Suction lysimeter (SL) installation information ? block 1: 39,300 kg N/ha.. 265 
Table 30.  Suction lysimeter (SL) installation information ? block 1: 19,650 kg N/ha.. 266 
Table 31.  Suction lysimeter (SL) installation information ? block 1: 58,900 kg N/ha.. 267 
Table 32.  Suction lysimeter (SL) installation information ? block 1: 0 kg N/ha........... 268 
Table 33.  Suction lysimeter (SL) installation information ? block 2: 58,900 kg N/ha.. 269 
Table 34.  Suction lysimeter (SL) installation information ? block 2: 39,300 kg N/ha.. 270 
Table 35.  Suction lysimeter (SL) installation information ? block 2: 19,650 kg N/ha.. 271 
Table 36.  Suction lysimeter (SL) installation information ? block 2: 0 kg N/ha........... 272 
Table 37.  Suction lysimeter (SL) installation information ? block 3: 19,650 kg N/ha.. 273 
Table 38.  Suction lysimeter (SL) installation information ? block 3: 58,900 kg N/ha.. 274 
Table 39.  Suction lysimeter (SL) installation information ? block 3: 39,300 kg N/ha.. 275 
Table 40.  Suction lysimeter (SL) installation information ? block 3: 0 kg N/ha........... 276 
 
 vii
Table 41.  Biosolids analysis results (wet weight basis)................................................. 277 
Table 42.  Biosolids analysis results (dry weight basis). ................................................ 278 
Table 43.  Biosolids results: revised after removal of outliers (dry weight basis).......... 279 
Table 44.  Hydraulic conductivity by block.................................................................... 280 
Table 45.  Trends for pan lysimeter total N and NH4+ results with values > 100 mg/L. 283 
Table 46.  Trends for suction lysimeter total N and NH4+ results with focus on values > 
100 mg/L......................................................................................................................... 291 
 
 
 viii
 
LIST OF FIGURES 
Figure 1.  The nitrogen cycle (Pidwirny, 2000).................................................................. 7 
Figure 2.  Location of the ERCO tree farm. ..................................................................... 31 
Figure 3.  Experimental layout.......................................................................................... 36 
Figure 4.  Experimental layout showing biosolids rows and subplot IDs. ....................... 37 
Figure 5.  Schematic of pan lysimeter layout. .................................................................. 38 
Figure 6.  Schematic of suction lysimeter layout.............................................................. 40 
Figure 7.  Digging a deep row. ......................................................................................... 43 
Figure 8.  Offloading biosolids. ........................................................................................ 43 
Figure 9.  Pushing biosolids into a deep row.................................................................... 44 
Figure 10.  Covering biosolids with overburden. ............................................................. 44 
Figure 11.  Laborer with dibble bar. ................................................................................. 52 
Figure 12.  Dibble hole and poplar cutting. ...................................................................... 53 
Figure 13.  Cutting in ground............................................................................................ 53 
Figure 14.  Cutting with initial leaf growth. ..................................................................... 54 
Figure 15.  Front view of pan lysimeter............................................................................ 55 
Figure 16.  Side view of pan lysimeter. ............................................................................ 56 
Figure 17.  Pan lysimeter top view. .................................................................................. 56 
Figure 18.  Underside of pan lysimeter and protective wire mesh lid (on left). ............... 57 
Figure 19.  Cross-sectional view of installation trench wall............................................. 59 
Figure 20.  Drill with modified trailer anchor as auger (pan and screening in background).
........................................................................................................................................... 64 
Figure 21.  Installation trench wall with etched outline of pan installation cavity........... 64 
 
 ix
Figure 22.  Drilling out pan outline. ................................................................................. 65 
Figure 23. Drilled hole with fines for repacking............................................................... 65 
Figure 24.  Pan installed with attached PVC piping. ........................................................ 65 
Figure 25.  Front view of PVC piping exiting pan cavity................................................. 65 
Figure 26.  Experimental plot layout with pan and suction lysimeter positions............... 66 
Figure 27.  Block 3 pan and suction lysimeter installation locations. .............................. 67 
Figure 28.  Block 2 pan and suction lysimeter installation locations. .............................. 68 
Figure 29.  Block 1 pan and suction lysimeter installation locations. .............................. 69 
Figure 30.  Suction lysimeter (pressure-vacuum soil water sampler)............................... 71 
Figure 31.  Removing overburden to locate biosolids rows. ............................................ 77 
Figure 32.  Biosolids rows. ............................................................................................... 77 
Figure 33.  Measuring biosolids depth.............................................................................. 77 
Figure 34.  Drilling equipment.......................................................................................... 77 
Figure 35.  Drilling hole.................................................................................................... 78 
Figure 36.  Drilled hole in control subplot........................................................................ 78 
Figure 37.  Laterally placed lysimeter hole (to the side of the biosolids row). ................ 78 
Figure 38.  Vertically placed lysimeter hole (below the biosolids row)........................... 78 
Figure 39.  Measuring depth. ............................................................................................ 79 
Figure 40.  Cleaning out bottom of hole with hand auger. ............................................... 79 
Figure 41.  Sifting drilled soil........................................................................................... 79 
Figure 42.  Sieve used for sifting...................................................................................... 79 
Figure 43.  Placing mudpack around ceramic cup............................................................ 80 
Figure 44.  Pouring bentonite around lysimeter to create a watertight plug..................... 80 
 
 x
Figure 45.  Packing fill around lysimeter.......................................................................... 80 
Figure 46.  Lysimeter lines placed to the side of the installation site............................... 80 
Figure 47.  Hand pump and sample collection flask for the pan lysimeter. ..................... 82 
Figure 48.  Collecting a pan lysimeter sample in the flask............................................... 82 
Figure 49.  Pouring an aliquot of sample into the compositing container. ....................... 82 
Figure 50.  Rinsing the sample collection flask with distilled water................................ 82 
Figure 51.  Rinsing the flask with deionized water. ......................................................... 83 
Figure 52.  Rinsing the stopper and tubing with deionized water. ................................... 83 
Figure 53.  Hand pump next to suction lysimeter vacuum and pressure lines.................. 84 
Figure 54.  Applying suction to the lysimeter vacuum access tube.................................. 84 
Figure 55.  Purging sample by applying pressure............................................................. 84 
Figure 56.  Sample collected in graduated cylinder.......................................................... 84 
Figure 57.  Transferring sample to labeled container. ...................................................... 85 
Figure 58.  Rinsing sampling equipment with deionized water........................................ 85 
Figure 59.  Saturated hydraulic conductivity constant head set up................................... 92 
Figure 60.  Hydraulic conductivity by depth (no significant differences between depths).
......................................................................................................................................... 103 
Figure 61.  Hydraulic conductivity by block. ................................................................. 105 
Figure 62.  Hydraulic conductivity by block (logarithmic scale). .................................. 105 
Figure 63.  Experimental plot color-coded with average hydraulic conductivity 
categories. ....................................................................................................................... 107 
Figure 64.  Leachate travel time from bottom of biosolids row to sampling equipment.111 
Figure 65.  Monthly rainfall totals for December 2002-December 2004. ...................... 113 
 
 xi
Figure 66.  Comparison of rainfall in 2003 and 2004..................................................... 113 
Figure 67.  Number of days for rainfall to reach sampling equipment........................... 117 
Figure 68.  Average pH values for suction lysimeter (SL) and pan lysimeter samples.. 122 
Figure 69.  Pan lysimeter samples from block 1............................................................. 124 
Figure 70.  Pan lysimeter samples from block 2............................................................. 124 
Figure 71.  Pan lysimeter samples from block 3............................................................. 124 
Figure 72.  Pan lysimeter samples from control and equipment blank........................... 124 
Figure 73.  Residue from filtration of pan lysimeter samples......................................... 125 
Figure 74.  Suction lysimeter samples from a block 1 subplot....................................... 126 
Figure 75.  Suction lysimeter samples from a block 2 subplot....................................... 126 
Figure 76.  Suction lysimeter samples from a block 3 subplot....................................... 126 
Figure 77.  Suction lysimeter samples from a control subplot. ...................................... 126 
Figure 78.  Residue from filtration of SL samples.......................................................... 127 
Figure 79.  Ammonium quarterly average concentrations for low-level application rate in 
pan lysimeters. ................................................................................................................ 131 
Figure 80.  Ammonium quarterly average concentrations for mid-level application rate in 
pan lysimeters. ................................................................................................................ 131 
Figure 81.  Ammonium quarterly average concentrations for high-level application rate in 
pan lysimeters. ................................................................................................................ 132 
Figure 82.  Number of ammonium samples > 100 mg/L by application rate and tree 
density............................................................................................................................. 134 
Figure 83.  Ammonium average concentrations across blocks with standard deviation for 
low-level application rate in pan lysimeters. .................................................................. 135 
 
 xii
Figure 84.  Ammonium average concentrations across blocks with standard deviation for 
mid-level application rate in pan lysimeters. .................................................................. 136 
Figure 85.  Ammonium average concentrations across blocks with standard deviation for 
high-level application rate in pan lysimeters. ................................................................. 136 
Figure 86.  Ammonium quarterly average concentrations for low-level application rate in 
suction lysimeter (SL) samples ? all quarters................................................................. 143 
Figure 87.  Ammonium quarterly average concentrations for low-level app. rate in SL 
samples: Q4&5................................................................................................................ 144 
Figure 88.  Ammonium quarterly average concentrations for low-level app. rate in SL 
samples: Q6&7................................................................................................................ 144 
Figure 89.  Ammonium quarterly average concentrations for mid-level application rate in 
suction lysimeter (SL) samples ? all quarters................................................................. 145 
Figure 90.  Ammonium quarterly average concentrations for mid-level app. rate in SL 
samples: Q4&5................................................................................................................ 146 
Figure 91.  Ammonium quarterly average concentrations for mid-level app. rate in SL 
samples: Q6&7................................................................................................................ 146 
Figure 92.  Ammonium quarterly average concentrations for high-level application rate in 
suction lysimeter (SL) samples ? all quarters................................................................. 147 
Figure 93.  Ammonium quarterly average concentrations for high-level app. rate in SL 
samples: Q4&5................................................................................................................ 148 
Figure 94.  Ammonium quarterly average concentrations for high-level app. rate in SL 
samples: Q6&7................................................................................................................ 148 
 
 xiii
Figure 95.  Suction lysimeter ammonium results:  distribution across concentration ranges 
for each application rate.................................................................................................. 150 
Figure 96.  Suction lysimeter ammonium results:  distribution of results >100 mg/L 
across tree densities for each application rate................................................................. 150 
Figure 97.  Suction lysimeter ammonium results:  distribution of results > 100 mg/L 
across lysimeter positions. .............................................................................................. 152 
Figure 98.  Suction lysimeter quarterly average ammonium results:  controls vs. all other 
application rates. ............................................................................................................. 158 
Figure 99.  Suction lysimeter quarterly average ammonium results by position for 
controls............................................................................................................................ 159 
Figure 100.  Suction lysimeter quarterly average ammonium results: comparison of 
application rates for each suction lysimeter position...................................................... 161 
Figure 101.  Suction lysimeter quarterly average ammonium results for 19,650 kg N/ha -
716 trees/ha (application rate * tree density * quarter interaction)................................. 164 
Figure 102.  Suction lysimeter quarterly average ammonium results for 39,300 kg N/ha - 
716 trees/ha (application rate * tree density * quarter interaction)................................. 164 
Figure 103.  Suction lysimeter quarterly average ammonium results for 58,900 kg N/ha - 
0 trees/ha (application rate * tree density * quarter interaction)..................................... 165 
Figure 104.  Suction lysimeter quarterly average ammonium results for 0 trees/ha, PV-
15cm (tree density*position*quarter interaction). .......................................................... 167 
Figure 105.  Suction lysimeter quarterly average ammonium results for 0 trees/ha, PV-
30cm (tree density*position*quarter interaction). .......................................................... 167 
 
 xiv
Figure 106.  Suction lysimeter quarterly average ammonium results for 0 trees/ha, PV-
60cm (tree density*position*quarter interaction). .......................................................... 168 
Figure 107.  Suction lysimeter quarterly average ammonium results for 0 trees/ha, PL-30 
cm (tree density*position*quarter interaction). .............................................................. 168 
Figure 108.  Suction lysimeter total nitrogen results by position for each application rate.
......................................................................................................................................... 170 
Figure 109.  Suction lysimeter quarterly average total nitrogen results for 58,900 kg N/ha, 
PV-15cm (application rate*position*quarter interaction). ............................................. 172 
Figure 110.  Suction lysimeter quarterly average total nitrogen results for 58,900 kg N/ha, 
PV-30cm (application rate*position*quarter interaction). ............................................. 172 
Figure 111.  Suction lysimeter quarterly average total nitrogen results for 58,900 kg N/ha, 
PV-60cm (application rate*position*quarter interaction). ............................................. 173 
Figure 112.  Suction lysimeter quarterly average total nitrogen results for 58,900 kg N/ha, 
PL-15cm (application rate*position*quarter interaction)............................................... 173 
Figure 113.  Nitrite quarterly average concentrations for low-level application rate in pan 
lysimeters. ....................................................................................................................... 177 
Figure 114.  Nitrite quarterly average concentrations for mid-level application rate in pan 
lysimeters. ....................................................................................................................... 177 
Figure 115.  Nitrite quarterly average concentrations for high-level application rate in pan 
lysimeters. ....................................................................................................................... 178 
Figure 116.  Scatter plot of nitrite quarterly average results for pan lysimeters............. 183 
Figure 117.  Nitrite quarterly average concentrations for low-level application rate in 
suction lysimeter (SL) samples ? all quarters................................................................. 185 
 
 xv
Figure 118.  Nitrite quarterly average concentrations for low-level application rate in SL 
samples: Q4&Q5............................................................................................................. 186 
Figure 119.  Nitrite quarterly average concentrations for low-level application rate in SL 
samples: Q6&Q7............................................................................................................. 186 
Figure 120.  Nitrite quarterly average concentrations for mid-level application rate in 
suction lysimeter (SL samples) ? all quarters. ................................................................ 187 
Figure 121.  Nitrite quarterly average concentrations for mid-level app. rate for SL 
samples: Q4&Q5............................................................................................................. 188 
Figure 122.  Nitrite quarterly average concentrations for mid-level app. rate for SL 
samples: Q6&Q7............................................................................................................. 188 
Figure 123.  Nitrite quarterly average concentrations for high-level application rate in 
suction lysimeter (SL) samples ? all quarters................................................................. 189 
Figure 124.  Nitrite quarterly average concentrations for high-level app. rate for SL 
samples: Q4&Q5............................................................................................................. 190 
Figure 125.  Nitrite quarterly average concentrations for high-level app. rate for SL 
samples: Q6&Q7............................................................................................................. 190 
Figure 126.  Nitrite quarterly average results:  Suction lysimeter 15 cm vertical position-
within position differences.............................................................................................. 194 
Figure 127.  Nitrite quarterly average results:  Suction lysimeter 30 cm vertical position-
within position differences.............................................................................................. 194 
Figure 128.  Nitrite quarterly average results:  Suction lysimeter 60 cm vertical position-
within position differences.............................................................................................. 195 
 
 xvi
Figure 129.  Nitrite quarterly average results:  Suction lysimeter 15 cm lateral position-
within position differences.............................................................................................. 195 
Figure 130.  Nitrite quarterly average results: Suction lysimeter 30 cm lateral position-
within position differences.............................................................................................. 196 
Figure 131.  Nitrite suction lysimeter quarterly average results:  comparison of vertical 
positions over time.......................................................................................................... 197 
Figure 132.  Nitrite suction lysimeter quarterly average results:  comparison of vertical 
15cm position to lateral positions over time................................................................... 198 
Figure 133.  Nitrate quarterly average concentrations for low-level application rate in pan 
lysimeters. ....................................................................................................................... 201 
Figure 134.  Nitrate quarterly average concentrations for mid-level application rate in pan 
lysimeters. ....................................................................................................................... 201 
Figure 135.  Nitrate quarterly average concentration for high-level application rate in pan 
lysimeters. ....................................................................................................................... 202 
Figure 136.  Nitrate:  Pan lysimeter average quarterly values for each control subplot. 204 
Figure 137.  Nitrate quarterly average concentrations for low-level application rate in 
suction lysimeter (SL) samples:  all quarters.................................................................. 211 
Figure 138.  Nitrate quarterly average concentrations for low-level application rate in SL 
samples:  Q4&5............................................................................................................... 212 
Figure 139.  Nitrate quarterly average concentrations for low-level application rate in SL 
samples:  Q6&7............................................................................................................... 212 
Figure 140.  Nitrate quarterly average concentrations for mid-level application rate in 
suction lysimeter (SL) samples:  all quarters.................................................................. 213 
 
 xvii
Figure 141.  Nitrate quarterly average concentrations for mid-level application rate in SL 
samples:  Q4&5............................................................................................................... 214 
Figure 142.  Nitrate quarterly average concentrations for mid-level application rate in SL 
samples:  Q6&7............................................................................................................... 214 
Figure 143.  Nitrate quarterly average concentrations for high-level application rate in 
suction lysimeter (SL) samples:  all quarters.................................................................. 215 
Figure 144.  Nitrate quarterly average concentrations for high-level application rate in SL 
samples:  Q4&5............................................................................................................... 216 
Figure 145.  Nitrate quarterly average concentrations for high-level application rate in SL 
samples:  Q6&7............................................................................................................... 216 
Figure 146.  Nitrate quarterly average suction lysimeter results: general differences over 
time (quarter). ................................................................................................................. 220 
Figure 147.  Subplot 1A:  Block 1; 39,300 kg N/ha; 716 trees/ha.................................. 230 
Figure 148.  Subplot 1B:  Block 1; 39,300 kg N/ha; 1074 trees/ha................................ 231 
Figure 149.  Subplot 1C:  Block 1; 39,300 kg N/ha; 0 trees/ha...................................... 232 
Figure 150.  Subplot 1D:  Block 1, 19,650 kg N/ha; 716 trees/ha.................................. 233 
Figure 151.  Subplot 1E:  Block 1; 19,650 kg N/ha; 1074 trees/ha. ............................... 234 
Figure 152.  Subplot 1F:  Block 1; 19,650 kg N/ha; 0 trees/ha. ..................................... 235 
Figure 153.  Subplot 1G:  Block 1; 58,900 kg N/ha; 716 trees/ha.................................. 236 
Figure 154.  Subplot 1H:  Block 1; 58,900 kg N/ha; 1074 trees/ha................................ 237 
Figure 155.  Subplot 1I:  Block 1; 58,900 kg N/ha; 0 trees/ha. ...................................... 238 
Figure 156.  Subplot 4C (Control):  Block 1; 0 kg N/ha; 0 trees/ha. .............................. 239 
Figure 157.  Subplot 2A:  Block 2, 58,900 kg N/ha; 716 trees/ha.................................. 240 
 
 xviii
Figure 158.  Subplot 2B:  Block 2; 58,900 kg N/ha; 1074 trees/ha................................ 241 
Figure 159.  Subplot 2C:  Block 2; 58,900 kg N/ha; 0 trees/ha...................................... 242 
Figure 160.  Subplot 2D:  Block 2; 39,300 kg N/ha; 716 trees/ha.................................. 243 
Figure 161.  Subplot 2E:  Block 2; 39,300 kg N/ha; 1074 trees/ha. ............................... 244 
Figure 162.  Subplot 2F:  Block 2; 39,300 kg N/ha; 0 trees/ha. ..................................... 245 
Figure 163.  Subplot 2G:  Block 2; 19,650 kg N/ha; 716 trees/ha.................................. 246 
Figure 164.  Subplot 2H:  Block 2; 19,650 kg N/ha; 1074 trees/ha................................ 247 
Figure 165.  Subplot 2I:  Block 2; 19,650 kg N/ha; 0 trees/ha. ...................................... 248 
Figure 166.  Subplot 4B (Control):  Block 2; 0 kg N/ha; 0 trees/ha. .............................. 249 
Figure 167.  Subplot 3A:  Block 3; 19,650 kg N/ha; 1074 trees/ha................................ 250 
Figure 168.  Subplot 3B:  Block 3; 19,650 kg N/ha; 716 trees/ha.................................. 251 
Figure 169.  Subplot 3C:  Block 3; 19,650 kg N/ha; 0 trees/ha...................................... 252 
Figure 170.  Subplot 3D:  Block 3; 58,900 kg N/ha; 1074 trees/ha................................ 253 
Figure 171.  Subplot 3E:  Block 3; 58,900 kg N/ha; 716 trees/ha. ................................. 254 
Figure 172.  Subplot 3F:  Block 3; 58,900 kg N/ha; 0 trees/ha. ..................................... 255 
Figure 173.  Subplot 3G:  Block 3; 39,300 kg N/ha; 1074 trees/ha................................ 256 
Figure 174.  Subplot 3H:  Block 3; 39,300 kg N/ha; 716 trees/ha.................................. 257 
Figure 175.  Subplot 3I:  Block 3; 39,300 kg N/ha; 0 trees/ha. ...................................... 258 
Figure 176.  Subplot 4A (Control):  Block 3; 0 kg N/ha;0 trees/ha................................ 259 
Figure 177.  Total nitrogen concentrations for low-level app. rate in pan lysimeters. ... 281 
Figure 178.  Total nitrogen concentrations for mid-level app. rate in pan lysimeters.... 281 
Figure 179.  Total nitrogen concentrations for high-level app. rate in pan lysimeters... 282 
 
 xix
Figure 180.  Total nitrogen concentrations for low-level application rate in suction 
lysimeter (SL) samples ? all quarters.............................................................................. 285 
Figure 181.  Total nitrogen concentrations for low-level app. rate in SL samples: Q4&5.
......................................................................................................................................... 286 
Figure 182.  Total nitrogen concentrations for low-level app. rate in SL samples: Q6&7.
......................................................................................................................................... 286 
Figure 183.  Total nitrogen concentrations for mid-level application rate in suction 
lysimeter (SL) samples ? all quarters.............................................................................. 287 
Figure 184.  Total nitrogen concentrations for mid-level app. rate in SL samples: Q4&5.
......................................................................................................................................... 288 
Figure 185.  Total nitrogen concentrations for mid-level app. rate in SL samples: Q6&7.
......................................................................................................................................... 288 
Figure 186.  Total nitrogen concentrations for high-level application rate in suction 
lysimeter (SL) samples ? all quarters.............................................................................. 289 
Figure 187.  Total nitrogen concentrations for high-level app. rate in SL samples: Q4&5.
......................................................................................................................................... 290 
Figure 188.  Total nitrogen concentrations for high-level app. rate in SL samples: Q6&7.
......................................................................................................................................... 290 
 
 
 
 1
Chapter 1:  Introduction 
Since the advent of civilization, with increasing populations living in fixed 
locations, disposal and treatment of household waste has been a necessity of life.  
Domestic wastewater systems evolved from more rudimentary flushing systems that 
discharged raw waste directly into waterways to the more sophisticated wastewater 
treatment plants in use today.  In current systems, raw sewage enters the facility; is 
treated through physical, chemical, and biological processes to meet regulatory 
requirements; and exits in two forms: 1) as effluent and 2) as sewage sludge (a.k.a., 
biosolids).  Effluent is effectively integrated back to the environment via discharge into 
waterways, or in some cases by ground injection.  Sewage sludge, however, poses a 
greater integration challenge that in many cases proves costly.  It is therefore of interest 
to develop safe, effective, and economical means of sewage sludge disposal. 
Current United States regulations for disposal are delineated in The Standards for 
Use of Disposal of Sewage Sludge (Title 40 of the Code of Regulations{CFR} Part 503).  
In addition to incineration, landfilling, and composting, these Environmental Protection 
Agency (EPA) regulations allow for land application of biosolids, and strongly encourage 
implementation of this technique for beneficial uses.  Most beneficial uses consist of land 
application to agricultural fields and other nutrient-deficient lands to enhance growth of 
vegetation.  In such cases, application must follow the protocols in 40 CFR part 503 to 
ensure that excess nutrients are not transported to surface water or leached to ground 
water. 
Biosolids utilization in forest lands, particularly in silviculture operations, has 
gained increased popularity in the United States.  Surface spraying, spreading and 
 
 2
subsurface mixing in the soil are the primary distribution techniques, with applications 
required each year or multiple times a year to successfully meet the nutrient needs of the 
trees and production goals of the operation.  Because trees are not a food crop, concerns 
related to the potential uptake and ingestion of biosolids contaminants do not exist.  Not 
only do the biosolids provide a nutrient source for the trees, they also build up the topsoil, 
reduce erosion and increase above and under ground ecosystem diversity. 
An alternative land application regimen, referred to as deep row application, has 
been in use on private property owned and managed by the Environmental Reclamation 
Company, Inc. (ERCO, Inc.) since the early 1980s.  This technique was established on an 
abandoned surface gravel mine that, prior to reclamation as a tree farm, consisted of a 
sand and gravel overburden underlain by a clay layer.  As such, it was devoid of organic 
matter and subject to erosion.  In concert with regulatory requirements to reclaim 
abandoned mine sites, ERCO devised a reclamation plan to grow hybrid poplar trees over 
trenches that had been filled with biosolids.  The biosolids would serve as a long-term 
nutrient source for the fast-growing, nutrient-demanding poplars.  The poplars, in turn, 
would provide erosion control, wildlife habitat, and potentially become a marketable 
product. 
Deep row application has several advantages over traditional land application 
techniques.  With deep row application, the biosolids are encased in the mine spoils such 
that odor from and vector attraction to the sludge is controlled.  In addition, this set up 
hinders nitrogen volatilization and prevents biosolids runoff during storm events.  The 
biosolids and tree root remnants from the 6-year tree cycle improve the overall quality of 
the soil and set the stage for more permanent ecological reclamation. The combined 
 
 3
advantages allow for a once-per-cycle application of biosolids at a higher rate than 
traditional at-surface application techniques.  This decreases labor costs and allows for 
disposal of a larger amount of biosolids. 
Of critical importance when establishing this operation was the assurance that the 
application of biosolids would not pose a threat to the environment.  Biosolids contain 
nutrients that, although essential to the production of healthy crops, pose an 
environmental and health risk if they are applied in excess and, as they decompose to 
more soluble forms, leach to the groundwater or surface water.  In addition, biosolids are 
known to contain several metals that, if concentrated, can also pose a health risk if 
introduced to groundwater aquifers.  EPA?s 503 rule allows surface application provided 
the biosolids contain no more than the allowed concentrations of certain metals and 
provided that cumulative loading does not exceed criteria.  Water quality monitoring at 
this site was therefore a key component of permit requirements to ensure the project was 
environmentally sound.  To address this issue, seven groundwater monitoring wells 
ranging in depth from 11-36.5 m (35-120 ft) were installed around the perimeter of the 
36.5 ha farmed site between 1982 and 1990.  Over 15 years of groundwater monitoring 
for nutrients, metals and biological parameters show negligible levels of pollutants. 
Although the groundwater, surface water, and soil sample analyses demonstrated 
that the deep-row application protocols were environmentally sound, it did not provide 
enough detail about the mechanisms by which the nutrients in the biosolids, particularly 
nitrogen, were being utilized.  It was clear that nitrogen had not infiltrated the 
groundwater flow represented by the monitoring wells, but the specific dynamics in close 
proximity to the biosolids rows were only theorized, and did not have quantitative data to 
 
 4
support such theories.  To better understand the interactions amongst the soil, biosolids, 
and trees would require closer investigation of the local ecosystem in and around the deep 
rows, at 1-2 m (3-6ft) depths in the soil profile as opposed to the 11-36 m (35-120 ft) 
depths represented by the groundwater monitoring wells.  Such information would help 
to 1) determine the optimal rate at which biosolids can be applied to promote the most 
effective poplar growth without generating excess nutrients and 2) establish the 
feasibility of applying this technique to other gravel spoils with the ultimate goal of 3) 
providing an alternate and better technique to recycle human waste. 
As stated above, better understanding the fate of nitrogen will more readily 
provide for application of this technique to other gravel sites with similar characteristics.  
This is of particular importance in the Baltimore-Washington area, which produces 
approximately 188,000 dry Mg (207,000 dry tons) of biosolids each year and has over 
2230 ha (5,500 acres) of land permitted for sand and gravel mining (Kays et al., 1999).  
This tree farming technique could therefore prove to be a viable solution for the 
reclamation of mines in concert with biosolids disposal, with the added bonus of 
enhancing carbon sequestration in the trees and producing a marketable wood crop. 
To date, studies at the ERCO tree farm have indicated that this deep-row 
application technique is a favorable alternative for biosolids recycling.  Tree growth, 
however, has not proved optimal, with diameter sizes being less than anticipated after the 
6-9 year growth cycle.  This sub optimal growth is the combined effect of nitrogen 
deficiencies and excessive tree densities.  Consequently, the current study was planned to 
evaluate the following factors:  1) hybrid poplar planting at lower densities (to promote 
increased tree diameters) and 2) several biosolids application rates at levels comparable 
 
 5
to and higher than the standard procedure in use at the ERCO tree farm.  These 
conditions may increase chances for nutrient leaching into the soil should the timing and 
amount of nutrient release exceed the poplar tree uptake rate and microbial 
immobilization activity.  Counteracting this concern, however, is the stipulation that 
conditions within the deep row provide a wet anaerobic environment that facilitates 
denitrification, eliminating the potential for percolation though the soil.  In addition, 
because this site is protected by a natural layer (or layers) of clay soil, vertical water flow 
from the trenches, along with the accompanying excess nitrates, would be impeded. This 
rationale must, however, be clearly and consistently demonstrated. 
The focus of this study is to evaluate nitrogen fate and transport occurring in close 
proximity to the biosolids rows, with particular emphasis on the fate of nitrate, a soluble 
form of nitrogen linked to both health and environmental concerns.  Although 
phosphorus dynamics as well as tree production and associated nutrient content is also a 
focus of the overall experiment, these parameters are beyond the scope of this master?s 
thesis. 
 
 6
Chapter 2:  Review of Literature 
Documented records regarding the utilization of sewage sludge as fertilizer dates 
back to the 1500s in Germany, where sewage was used on croplands.  Under the Federal 
Water Pollution Control Acts of 1972, land application of sewage sludge was recognized 
as a protocol for disposal, provided the disposal was managed in accordance with the 
applicable regulations.  In conjunction with this recognition, experts from the EPA, 
United States Department of Agriculture (USDA), and National Land Grant Universities 
pooled their resources to form a Coordinating Committee on Environmental Quality that 
developed a subcommittee on Recycling Efforts of Sludges on Land.  This subcommittee 
evaluated research that had been conducted on the pros and cons of sewage sludge 
application to provide guidance on the most appropriate protocols for use.  This increased 
interest, along with the ongoing buildup of sewage sludge at wastewater treatment plants, 
sparked a series of research projects that evaluated the impacts of sewage sludge 
application to land (Lue-Hing, et al., 1992). 
The Nitrogen Cycle 
In order to understand the implications of sewage sludge disposal techniques and 
associated scientific studies, the nitrogen cycle must be understood.  Nitrogen is one of 
the most important nutrients for plant growth.  Only certain water-soluble inorganic 
forms, including ammonium (NH4+) and nitrate (NO3-), can be absorbed by higher plants.  
In sewage sludge, the treatment process determines the ratio of organic to inorganic 
forms of nitrogen.  Liquid anaerobically digested sludge may contain a majority of 
nitrogen in the form of ammonium, with lesser amounts as organic nitrogen and 
negligible amounts of nitrate (EPA, 1994; Kelley, et al. 1984).  In undigested lime-
 
 7
stabilized biosolids, however, the majority of nitrogen present is in the form of organic 
nitrogen (Shepherd, 1996; Gshwind and Pietz, 1992).  Several biochemical processes 
must therefore occur before plants benefit from this nutrient source.  A depiction of the 
nitrogen cycle is presented in Figure 1. 
 
Figure 1.  The nitrogen cycle (Pidwirny, 2000) 
 
Mineralization is an enzymatic process in which organic nitrogen is decomposed 
to inorganic forms.  The first step is ammonification, in which microbes break down 
organic nitrogen and produce ammonia, which readily dissolves in water to form the 
ammonium cation (NH4+).  This process occurs in either anaerobic or aerobic conditions 
and is performed by a broad group of heterotrophic organisms.  Many of the organisms 
are thermophilic; hence optimum ammonification occurs at temperatures between 40?C 
and 60?C (Lewis, 1986), though it can occur at lower temperatures, albeit at a slower 
 
 8
rate.  Ammonium adsorbs to cation exchange sites; consequently, those soils with higher 
CEC values (e.g., clays) are more likely to inhibit percolation of ammonium than lower 
CEC soils (e.g., sands).  This adsorption, however, depends upon the prevalence of other 
competing cations in the soil water; the uptake rate of ammonium by plants and 
microbes; and potential oxidation of ammonium as described below (Loehr, 1979). 
Ammonia (NH3, the gas) and ammonium (NH4+, the cation) are in equilibrium 
with one another as represented by the following equation:  NH4+ + OH- ? H2O + NH3?.   
Because this is an equilibrium process, anything that impacts the represented compounds 
will alter the balance, and drive the equation in whichever direction restores the balance.  
Consequently, high pH levels (by definition from higher concentrations of OH- ions) as 
well as a decrease in water content will drive the equation to the right, and more 
ammonia will be produced and available to volatilize.  Volatilization is impacted by 
contact with air and soil. If at the soil surface, more ammonia will volatilize.  When 
placed underground in close contact with the soil, diffusion to the atmosphere is 
inhibited.  In addition, ammonia will be adsorbed by clays and organic materials, further 
diminishing volatilization.  Studies performed clearly demonstrate that placing biosolids 
in the subsurface (as opposed to the surface) significantly decreases ammonia losses 
(Adamsen, 1987; Brady and Weil, 2002). 
The second step of mineralization is nitrification.  It consists of two main 
sequential transformations that include: 1) the oxidation of ammonium to nitrite (NO2-), 
typically performed by the autotrophic Nitrosonomas bacteria; and immediately 
thereafter 2) oxidation of nitrite, typically performed by Nitrobacter bacteria to produce 
nitrate.  Other genera of bacteria that can perform this function do exist (e.g., 
 
 9
Nitrosolobus and Nitrocystis) but, in general, the process is dominated by Nitrosonomas 
and Nitrobacter (Lewis, 1986).  The swift transition from nitrite to nitrate usually 
prevents accumulation of nitrite.  Nitrification is usually performed by autotrophic 
bacteria, which derive their energy from the oxidation of NH4+ and NO2-, as opposed to 
the oxidation of carbonaceous compounds (Haynes, 1986).  Both genera of the nitrifying 
organisms cited (i.e., Nitrosonomas and Nitrobacter) as primarily responsible for this 
reaction sequence are aerobes, requiring the presence of oxygen to perform these 
conversions.  In addition, they favor soils with no more than 60% of pore volume filled 
with water, need a carbon source (i.e., bicarbonates and carbon dioxide) to synthesize 
their cell components, and optimally perform at temperatures between 20-30?C (Brady 
and Weil, 2002; Lewis, 1986). 
Nitrate is an anion that is not readily adsorbed to soil particles, is water soluble 
and therefore highly mobile.  Of the forms of nitrogen described above, it presents the 
highest risk of leaching through the soil profile to the groundwater table.  Additionally, 
nitrate warrants the most concern from a human health and environmental pollution 
perspective.  Most acutely in infants and ruminant animals, ingested nitrate is reduced to 
nitrite, which decreases the oxygen-carrying ability of red blood cells and produces a 
condition known as methemoglobinemia (Brady and Weil, 2002).  Consequently nitrate 
is a regulated pollutant in drinking water with a Maximum Contaminant Level (MCL) of 
10 mg/L for NO3-N (EPA, 1994). 
Nitrate also can have a pronounced impact on aquatic systems.  An influx of 
nitrate promotes algal blooms that, upon dying, are decomposed by oxygen-demanding 
bacteria.  Exponential growth and decay results in exponential demand and depletion of 
 
 10
oxygen.  Hypoxic conditions result that are toxic to many forms of aquatic life.  
Proliferation of this cycle can expand these inhospitable zones on a yearly basis, 
rendering once productive waters lifeless (Brady and Weil, 2002). 
A number of studies have been conducted to determine the most important factors 
impacting mineralization.  Wang, et al. (2003) performed a laboratory incubation study in 
which two different types of biosolids (anaerobically digested and dewatered sludge; 
liquid stabilized sludge from an autothermal thermophillic aerobic digestion) were mixed 
with two representative soils (a stony silt loam and a sandy volcanic soil) and incubated 
at two different temperatures (10?C and 20?C).  As expected, mineralization rates were 
significantly greater at the higher temperature.  A greater percentage of the organic 
nitrogen was mineralized in the aerobic biosolids and, overall, mineralization occurred 
sooner and more rapidly in the sandy volcanic soil.  Wang reasoned that the lower pH of 
the silt loam (4.5 vs. 5.4 for the sandy soil) might have inhibited the microbes.   
Another study focusing on predicting mineralization rates determined that the 
standard classification of biosolids by treatment processes (e.g., primary, aerobically 
digested, anaerobically digested, and composted biosolids) was not a reliable 
differentiating factor to use for mineralization impacts unless extensive stabilization had 
occurred (Gilmour, 2003).  Instead, it was more appropriate to evaluate the organic and 
inorganic N content combined with the decomposability of the biosolids (which would be 
greater for unstabilized biosolids, regardless of the treatment process).  A broader scope 
of factors was considered by Er, et al. (2004), who modeled factors impacting 
mineralization through regression analyses.  Variables considered included: biosolid type, 
biosolid organic N content, biosolid application rate, biosolid carbon to nitrogen (C:N) 
 
 11
ratio, soil organic N content, soil pH, time, and temperature.  The most relevant factors 
elicited from this analysis were biosolid application rate, biosolid C:N ratio, and 
temperature. 
Despite the varying focus of the studies cited above, there is a general consensus 
that the following factors represent the more important conditions impacting the 
degradation of biosolids. 
? The chemical composition of the decomposing material, including: 
a) Nitrogen content (inorganic vs. organic and relative concentrations):  
Some studies have indicated that the presence of inorganic forms of 
nitrogen act as a primer and facilitate more rapid mineralization (Haynes, 
1986).  High concentrations of NH4+, however, may inhibit nitrification 
(Brady and Weil, 2002; Nielsen and Revsbech, 1998). 
b)  The C:N ratio:  A low C:N ratio (< 20) will promote rapid bacterial 
growth and mineralization, due to the high amount of nitrogen present.  
This surplus nitrogen will exceed the nutritional requirements of the 
microbes, and the decomposition products (NH4+ and NO3-) will be 
available in soil solution.  The microbial activity will level off in 
correlation with the decreased availability of carbon.  A high C:N ratio 
(>25) also will prompt an initial surge in microbial activity, but this surge 
will be depressed once the microbes consume the nitrogen.  At this point, 
nitrogen will be immobilized in the microbes and unavailable in the soil 
solution.  The microbe population will stagnate and nitrogen will not 
 
 12
become available until this population dies and decomposes (Haynes, 
1986; Brady and Weil, 2002). 
c) The types of carbon in the biosolids:  Easily decomposed fatty acids, 
amino acids, simple sugars, and starches will initiate faster, more intense 
mineralization (Sylvis Environmental, 2000).  Conversely, lignin 
decomposes more slowly and may override the impact of nitrogen 
mineralization by facilitating the synthesis of stable, nitrogen-containing 
humic polymers (Haynes, 1986). 
d) Moisture Content of the Biosolids and Surrounding Soil:  Dry soils with 
<10-20% of their pore space filled with water are inhospitable to most 
microbes under consideration.  The heterotrophic organisms responsible 
for ammonification can tolerate a wider range of moisture content, 
particularly on the upper end of the scale, enabling decomposition in 
waterlogged conditions.  The more select group of nitrifying bacteria 
operates in a narrower window, with optimum performance when 50-60% 
of pore space is filled with water.  Above 70% water content, nitrification 
decreases significantly.  Some studies have shown that alternate drying 
and wetting conditions promote mineralization.  The wetting process 
promotes release and movement of organic compounds that serve as an 
energy source.  Nitrification occurs as the soil conditions enter the most 
favorable water contents.  As the soil dries, microbes die and the nitrogen 
cycle begins anew (Sylvis Environmental, 2000; Haynes, 1986; Lewis, 
1986). 
 
 13
e) Aeration of the Biosolids and Surrounding Soil:  Aeration complements 
the moisture content.  As stated above, ammonification can occur in the 
absence of oxygen, but nitrification is an aerobic process. 
f) Temperature:  Although microbes can operate at temperatures as low as 
0?C, optimum temperatures for ammonification are in the thermophillic 
range of 45-60?C and optimum temperatures for nitrification are in the 
mesophillic range of 20-35?C (Brady and Weil, 2002; Lewis, 1986; 
Sylvis Environmental, 2000). 
g) pH of the Biosolids and Surrounding Soil:  Neutral to slightly basic pHs 
foster the most effective decomposition.  The microbes responsible for 
nitrification are more sensitive to acidic conditions than ammonification, 
though research has shown that nitrification can occur, although at 
diminished rates, at pH conditions as low as 4.0 (Lewis, 1986; Sylvis 
Environmental, 2000). 
h) Soil Type:  Sandy soils drain easily and are less susceptible to 
waterlogged conditions.  Increasing concentrations of clay impart a more 
significant water holding capacity that can lead to sustained saturated 
conditions.  In addition, the higher CEC capacity of clay soils results in 
adsorption of organic materials and ammonium, which can limit their 
availability to microorganisms. 
The converse of mineralization is immobilization, in which ammonium or nitrate 
is complexed into an organic form via biotic or abiotic means.  Both mineralization and 
immobilization processes occur simultaneously, as microbe populations grow and die, 
 
 14
and rates are dependent upon the composition of the soil (Haynes, 1986; Lewis, 1986).  
Those factors that most influence immobilization include: the carbon to nitrogen ratio, 
with a C:N above 25 leading to a higher immobilization; the inorganic form present, with 
microbes favoring NH4+ over NO3-; competition between microbial populations and 
plants; and those physical and chemical properties that impact the microbial population 
dynamics, as described above. 
Denitrification refers to those processes in which nitrate ions are converted to 
gaseous forms of nitrogen {e.g., nitric oxide gas (NO2+), nitrous oxide gas (N2O+), and 
dinitrogen gas (N2)}.  The order of conversion is as follows:  NO3- ?NO2-?NO (gas) 
?N2O (gas) ?N2 (gas).  In this sequence of reactions, which typically occur under 
oxygen-depleted conditions, nitrogen, as opposed to oxygen, acts as the terminal electron 
acceptor.  The majority of bacteria performing this function are facultative anaerobes that 
can be either heterotrophs (i.e., obtain their energy and carbon from oxidation of organic 
compounds) or autotrophs (i.e., obtain their energy and carbon from carbon dioxide or 
carbonates).  Some organisms are capable of catalyzing the entire sequence of reactions; 
others can only initiate specific steps.  Typical conditions include a mixed community of 
bacteria performing different functions (McEldowney, et al., 1993).  Required 
environmental conditions include:  the presence of nitrate; low soil air content (<10%); 
temperatures between 2-50?C (with an optimum range of 25-35?C); a pH optimally 
between 7-8 (though some bacteria are capable of denitrifying under more acidic 
conditions); and an appropriate energy source (i.e., organic carbon) (Oertel and Nicklow, 
2003; Brady and Weil, 2002; Barber, 1995). 
 
 15
Land Application of Sewage Sludge  
Land application of sewage sludge to improve soil conditions, enhance crop 
production, improve silviculture operations, and reclaim mined land has been extensively 
studied.  Sludge is either applied 1) on the surface, 2) by disking or plowing into the soil 
to a prescribed depth (usually no more than 15 cm) or 3) via injection underneath the 
surface.  Nitrogen requirements of the crop and background soil concentration dictate 
application rates, with seasonal or yearly applications of the sludge often being 
performed.  Site and crop specific management are the key to optimizing growth while 
preventing nitrogen loss from the system (Ritter and Bergstrom, 2001; EPA, 1994; 
Outwater, 1994; Granato and Pietz, 1992). 
Numerous examples of nitrate leaching under biosolids-amended agricultural land 
have been reported in the literature (Ritter and Bergstrom, 2001; Shepherd, 1996; Clapp, 
et al., 1994).  In these studies, the timing and rate of application, type of sludge used, 
nutrient demands of the crop, and soil conditions influenced the loss of nutrients.  Often, 
a majority of the leaching could have been prevented through more careful management.  
Evanylo (2003) evaluated the impacts of biosolids application at two different times of 
the year (winter and spring) and at three different application rates bracketing the 
agronomic rate of corn crops planted at experimental sites in Virginia.  Results showed 
that leaching loss of nitrogen (as nitrate) was:  greater in the winter than in the summer; 
greater in coarser (sandier) soils than finer textured (higher silt and clay content) soils; 
and was more pronounced during periods of higher rainfall. 
Currie et al (2003) monitored nitrogen mineralization and leaching after 
application of lime-stabilized biosolids to soybean fields.  Results indicated that a surplus 
 
 16
of nitrogen was available in the soil because the soybeans continued to fix nitrogen.  
Despite this, nitrate concentrations in the groundwater were below 10 mg/L, indicating 
the possibility of denitrification. 
Lee (2004) evaluated the impact of three different field management practices on 
soil nitrate distribution in clay soils that were amended with biosolids and planted with 
wheat.  Biosolids were applied to exceed the agronomic rate.  One management practice 
consisted of leaving the field fallow for a year followed by cropping with wheat on an 
annual basis; the second immediately cropped the wheat and continued to do so on an 
annual basis; the third was the same as the second, except commercial fertilizer was 
applied in addition to the biosolids.  Results from soil samples collected  two years after 
biosolids application showed that the maximum nitrate content in the soil was directly 
related to the amount of biosolids applied.  In addition, the fallow treatment had a higher 
concentration of nitrate deeper in the soil profile than the other treatments, indicating that 
more leaching occurred in the absence of wheat crops.  For all treatments, nitrate 
decreased significantly past depths of 100cm.  Because clay soils tend to hold moisture 
longer than sandy soils (i.e., they do not drain as easily), it was reasoned that conditions 
were likely appropriate for denitrification to occur at these depths. 
Mitchell, et al (2000) evaluated the cycling of nitrogen on a small stand of Scots 
pine that received an application of anaerobically digested biosolids.  This traditionally 
nutrient poor ecosystem initially responded with fluxes of nitrogen in the upper soil 
profile, mainly in the form of ammonium, an order of magnitude above that of the control 
plot.  After 17 months, some nitrate leaching was observed, but all were below 10 mg/L, 
demonstrating an effective use of biosolids that results in minimal leaching of nitrogen. 
 
 17
Other studies that demonstrate the ability to minimize nitrate leaching have been 
performed on land reclamation projects.  Larger scale reclamation operations presented 
by Van Ham, et al. (2000), Sopper (1993) and Lue-Hing (1992) show that with 
appropriate biosolids type, application rates, and conditions, nitrogen from the biosolids 
can be preserved and recycled in the upper layers of the soil profile.  A reclamation 
project in British Columbia (Van Ham, et al., 2000) transformed nutrient depleted gravel 
mines into self-sustaining tracts of vegetation that increased the environmental quality of 
the site.  The vegetation not only enhanced the aesthetic and ecological value of the site, 
but actually reduced nitrogen movement that previously migrated to a nearby aquifer.  
When properly used, biosolids are an environmentally safe and effective nutrient source 
that greatly improves soil condition, optimizes crop production, and enhances the soil and 
land ecosystem into which it is introduced. 
 
Trenching of Sewage Sludge 
The majority of land application is in the form of surface spreading or subsurface 
incorporation, both of which evenly spread the biosolids across the parcel being 
fertilized.  Trenching, on the other hand, refers to filling excavated rows with large 
volumes of sludge that are subsequently covered with overburden.  This technique was 
studied in the 1970s and focused on the entrenchment of sewage sludge as a disposal 
option, as opposed to reintegration of biosolids as a beneficial reuse protocol.  An added 
benefit (though not the primary objective of these biosolids disposal efforts) was the 
reintroduction of nutrients into the land, particularly land that had been over farmed. 
 
 18
Walker (1974) summarized the results of studies conducted on sewage sludge 
from the Blue Plains Wastewater Treatment Plant that services the Washington, D.C. 
metro area.  In this study, dewatered raw-limed sludge was applied to trenches 0.6 m 
wide by 0.6 - 1.2 m deep.  A variety of crops such as fescue, alfalfa, rye and trees were 
grown.  Underground and surface drainage water, as well as groundwater from the site 
was monitored.  Results from 19 months of data gathering demonstrated that 
entrenchment prevented contamination of surface water, promoted slow nitrogen release, 
and created an unfavorable environment for pathogens.  An increase in nitrate levels was 
observed in the soil under the trenches and in subsurface drainage water, but not in 
groundwater samples.  No metals movement was observed in the substrate.  Increases in 
chloride were observed in groundwater samples, but this was the only migration of 
significance. 
Nineteen months after entrenchment, sludge dewatered from the top down and 
between one-fifth to one-half of the trench progressed from its original 20% solids 
gelatinous mass to a peat-like consistency.  The rate at which weathering occurred 
depended on the type of sludge used (e.g., digested sludges degraded faster than raw-
limed sludges) and the extent of plant root penetration.  This study indicated that 
entrenchment was a suitable procedure, but longer-term studies were recommended to 
determine the full effect of this practice. 
Similar research was conducted by Sikora, et al. (1978) over a four-year period 
(1972-1976) to evaluate water quality at a sludge entrenchment site consisting of sandy 
soils with an underlying clay layer.  In this study, lime-stabilized sludge was placed in 
0.6m x 0.6m trenches and covered with 0.15 ? 0.30 m of subsoil. Crops and fescue were 
 
 19
grown over the entrenchment area, though again vegetation was a secondary 
consideration.  Water samples were collected from drainage tile lines, a catchment pond, 
and monitoring wells within and around the trenched plot.  These studies showed a peak 
in chloride levels 18 months after entrenchment and a peak in nitrate concentration a year 
after the chloride peak (i.e., 30 months after entrenchment).  Nitrate concentrations were 
below the EPA MCL of 10 mg/L nitrate-N in wells above and below the trench plot.  
Though a high nitrate concentration of 60 mg/L occurred during November 1974 in one 
well within the trench plot, most concentrations (>85%) were below 10 mg/L.  Tile drains 
exhibited a high nitrate-N concentration of 32 mg/L.  Other observations of note were 
that metals did not migrate and pathogens were significantly reduced. 
Sikora et al. (1980) further evaluated the trenching technique with particular focus 
on the dynamics within and below the trench over a four-year period (1974 ?1978).  
Observations included an analysis of the original sludge sample and then the progression 
of the sludge starting at 22 months after entrenchment.  Results showed the following 
patterns: 
? After 22 months of entrenchment, the top portion of the sludge 5-20 cm (2-8 
inches) from the top of the trench had dried out and was densely penetrated 
with roots.  The middle and bottom portions of the trench did not dewater 
until 49 months after entrenchment.  After this four-year period, the entire 
trench contents appeared to have stabilized.  Similar to Walker?s observations, 
dewatering occurred from the top down. 
? A majority of chloride leached through the trench within the first year of 
application.  Chloride, a water-soluble anion commonly found in biosolids, 
 
 20
does not interact chemically with most soils and provides an indication of 
water flow and maximum leaching potential through the biosolids and soil 
profile.  The first reading at day 655 showed that chloride concentration was 
highest in the bottom of the trench, moderate in the middle of the trench, and 
lowest in the top of the trench.  At the inception of this experiment, chloride 
originally present in the biosolids already had migrated through the trench. 
? Organic nitrogen and ammonium leached through the soil profile.  
Distribution patterns at the beginning of the experiment (day 655) were 
similar to that of chloride.  Ammonium in particular was present at much 
higher concentrations in the bottom of the trench compared to the middle and 
top.  After 4 years, concentrations below the trenches returned to low or 
background levels for both parameters. 
? Nitrate, an anion with the same water-soluble properties and leaching 
potential as chloride, exhibited a pattern different from chloride and 
ammonium.  At day 655, the highest concentration was in the top of the 
trench, with lower levels in the middle and very low amounts at the bottom.  
With time, samples showed a progressive increase in the middle of the trench 
that eclipsed the top of the trench at day 998.  This progression of nitrate 
concentration is consistent with the conditions in the trench at these dates.  
The production of nitrate via mineralization of ammonium requires an aerobic 
environment, which only existed in the top of the trench at the beginning of 
the experiment.  Subsequent dewatering of the trench fostered conditions for 
additional mineralization to occur deeper in the trench. 
 
 21
Also important to note is that once produced, nitrate will either 1) be taken up 
by plants or microorganisms or 2) leach further down the trench with the 
water flow and/or 3) undergo denitrification.  The fact that nitrate 
concentrations do not correspond to the timing patterns exhibited by the 
equally water soluble chloride indicates that 1) nitrate production via 
mineralization was delayed for months after biosolids entrenchment and 2) 
once produced, though some nitrate may have leached to the bottom of the 
trench, the waterlogged, anaerobic conditions were optimal for denitrification.  
This theory is supported by the fact that concentrations in the bottom of the 
trench did not reach the levels in the upper portions.  Additionally, 
concentrations in the soil below the trenches, though elevated for a time to a 
maximum of 54 mg/kg, decreased to low levels (2-6 mg/kg) by the end of the 
experiment. 
This and subsequent evaluations of the entrenchment technique (Sikora, et al., 
1982; Sikora and Colacicco, 1980) led to the conclusion that contamination of the 
groundwater could occur dependent upon the soil characteristics and depth to the 
groundwater table.  Experiments provided evidence, however, that recharge would likely 
dilute the nutrients.  Consequently, the specific characteristics of an individual site would 
need to be evaluated to determine if groundwater contamination posed too much risk for 
this technique.  It is important to note, however, that these experiments did not attempt to 
utilize a deep-rooted crop or plant a specific crop density that could reach and utilize the 
nutrient reservoir supplied by the biosolids. 
 
 22
Use of Zero-Tension (Pan) Lysimeters and Suction Lysimeters to Collect Soil Water 
Samples 
A number of studies have been conducted to determine differences in the chemical 
constituents of soil water captured by zero-tension pan lysimeters versus suction 
lysimeters.  Barbee and Brown (1986) evaluated the ability of zero-tension pan and 
suction lysimeters to track chloride movement through three soils of differing texture.  
The suction lysimeters were not able to sample well-structured clay soils, the soil water 
from which was postulated to have bypassed the smaller suction lysimeters.  Soil water 
from the clay was, however, captured by the pan lysimeters.  What samples were 
collected by both lysimeters produced equivalent results without statistically significant 
differences.  The authors concluded that, despite the differing soil water collection 
techniques of the two pieces of equipment, both were able to accurately characterize the 
flow of chloride, with reservations for the use of suction lysimeters in soils with high clay 
content. 
Haines, et. al. (1982) compared nutrient concentrations collected using tension and 
zero-tension lysimeters.  The tension lysimeters used in this experiment were plates, as 
opposed to cups, but operate on the same collection principle.  Results for samples 
collected from two positions in the soil profile, one at the soil-litter interface and another 
30-cm below the soil-litter interface, showed differences between the chemical 
constituents collected by the two types of sampling equipment.  Specifically, zero-tension 
lysimeter results were higher than suction lysimeter results for both ammonium and 
nitrate.  For the soil-litter interface, results for the zero-tension lysimeter were higher than 
the suction lysimeter by a factor of 1.5 for both ammonium and nitrate, which was not 
 
 23
statistically significant.  At 30-cm below the soil-litter interface, results for the zero-
tension lysimeter were higher than the suction lysimeter by a factor of 5.1 and 3.4, 
respectively, which was statistically significant.  Also important to note is that the zero-
tension lysimeters collected 7 times more water than the suction lysimeter at the upper 
position, but 2.1 times less water than the suction lysimeter at the deeper position.  The 
authors reason that the higher concentrations in the zero-tension lysimeters were a 
product of a pulsed element input to saturated flow, which the zero-tension lysimeter 
captured more efficiently than the suction lysimeter. 
In contrast, Hendershot and Courchesne (1991), found consistently lower 
concentrations of nitrate in zero-tension lysimeters versus suction cup tension lysimeters 
in a comparative assessment of the collection equipment in a sugar-maple stand.  Pairs of 
the samplers were installed at 25 and 75 cm depths in the soil.  Samples were analyzed 
for a number of nutrients, including ammonium and nitrate.  Ammonium was present in 
higher concentrations in the suction lysimeter at the 25cm depth, but not enough to be 
statistically significant.  At 75 cm, ammonium concentrations between the two lysimeters 
were equivalent.  The absence of nitrate in the zero-tension lysimeter samples and 
presence in the suction lysimeter samples could not be satisfactorily explained, but was 
postulated to be the result of either: 1) uptake by microorganisms, which could have 
preferentially occurred in the zero-tension lysimeters because more suspended material 
(including microbes) enters the sampler with the soil water or 2) denitrification, which 
occurs in an anaerobic environment consistent with the saturated soil conditions required 
for collection by the zero-tension lysimeters.  This experiment presents a scenario in 
which the zero-tension lysimeter collection conditions, as opposed to those of the suction 
 
 24
lysimeter, are more predominantly associated with chemical and biological 
transformations. 
Yet another perspective is offered in experiments conducted by Marques, et al. 
(1996) at four different depths under a forest soil.  Solutions collected by zero-tension 
plate lysimeters and ceramic-cup tension lysimeters were compared for various nutrients.  
One major difference to note from other studies presented (and the one conducted for this 
thesis) is that the suction cup lysimeters were placed under constant suction, as opposed 
to a limited time period of suction.  Tension lysimeter solutions contained higher 
concentrations of nitrate and ammonium across all depths.  The authors concluded that 
the two types of equipment represented the soil water differently.  Zero-tension 
lysimeters collected the flux solution governed by gravitational forces, which had a 
shorter residence time in the soil and was primarily related to chemical and biological 
processes occurring in the upper soil horizon, after which the swift vertical migration 
would inhibit interaction of the solution with the soil.  Tension lysimeters, however, 
collect fixed phase soil water that more closely represents longer-term biogeochemical 
processes throughout the soil profile including mineralization, ion-exchange, mineral 
weathering and ion uptake.  For this reason, the breakdown products of organic nitrogen 
were more prevalent in the tension lysimeter solutions. 
From all of these studies, it is apparent that, with the exception of the known fact that 
zero-tension lysimeters capture saturated flow and suction lyismeters capture both 
saturated and more predominantly unsaturated flow, no one physical, chemical, or 
biological process can be selectively linked to either collection apparatus.  Rather, the 
soil water collected by either of these lysimeters is a product of the specific 
 
 25
circumstances governing the experimental set up and environmental conditions.  Using 
both types of sampling equipment does, however, ensure that a comprehensive 
representation of the soil solution in the soil profile will be obtained. 
Hybrid Poplar Trees and Their Use With Pollution Management 
The genus Populus includes those trees commonly referred to as poplars, aspen, and 
cottonwood.  They are part of the botanical family Salicaceae, which also includes 
willow trees.  Hybrid poplars are crosses of two different species that are often developed 
to enhance desirable traits, such as hardiness, nutrient uptake, or salinity tolerance.  
Clones are a group of genetically identical plants that result from vegetative production 
of a single tree. 
Hybrid poplars are well known for their high water uptake and transpiration rates and 
have been used for the containment and remediation of nutrients, explosives such as 
TNT, trichloroethylene, and a variety of other organics (Pivetz, 2001; Newman, et al., 
1999; Burken and Schnoor, 1998). Specific studies evaluating groundwater capture and 
hydrologic flow have recorded water use between 1.2 and 25 gallons/day/tree (Ferro, et 
al., 2001).  Other studies in which root growth was directed to an aquifer 25 feet below 
the surface estimated even higher uptake rates between 8-50 gallons/tree/day dependent 
upon the month and age of the tree. (Quinn, et al., 2001).  Such high water use supports 
the potential to provide a large degree of leachate containment, though results vary 
according to the specific site characteristics, density of trees planted, and climatic 
conditions. 
Licht (1990) evaluated the effectiveness of poplar tree buffer strips to control 
nonpoint source pollution, particularly nitrogen.  He concluded that hybrid poplars 1) 
 
 26
naturally form extensive rooting systems that can be further enhanced using deep planting 
techniques; 2) significantly reduce nitrate concentrations in the soil profile as well as in 
near-surface groundwater from 90 mg/L levels to 2 mg/L (well below the drinking water 
MCL of 10 mg/L), and 3) are capable of surviving in both waterlogged and drought 
conditions. 
Haycock and Pinay (1993) performed a comparison of nitrate reduction in grass and 
poplar vegetated riparian buffer strips in winter months and found that the poplar zone 
exhibited 99% retention of nitrate compared to 84% retention in the grass zone.  Though 
active plant uptake of nitrate was reasoned to be low in the dormant season, the high 
carbon contribution of the poplar trees at deeper levels in the soil likely provided a better 
substrate for denitrifying microbes. 
O?Neil and Gordon (1994) performed a controlled bench study in which an artificial 
riparian zone was created using Carolina poplars.  The experimental chambers were 
fertilized with nitrate solutions, irrigated, and the leachate was collected on a weekly 
basis.  The plots with trees removed a significantly larger amount of nitrate than the 
control plots and provided further evidence that poplar trees are capable of removing 
nitrate from soil water over time. 
In summary, characteristics that favor use of hybrid poplar trees in nutrient recycling 
and land reclamation activities include: 
? They are nutrient demanding, with an average uptake range of 91-163 kg (200-
360 lbs) of nitrogen per acre per year (National Agroforestry Center, 2000), and 
the ability to utilize as much as 225 kg (500 lbs) of nitrogen per acre per year as 
estimated from other studies (Murray, 2003). 
 
 27
? They are phreatophytes, will extend roots to the capillary fringe, and can survive 
periods with their roots in the saturated zone of an aquifer 
? The fibrous nature of the roots enables penetration of both highly permeable and 
less permeable soils. 
? Impressive growth rates produce large amounts of biomass that act as a 
significant carbon sink. 
? They are hardy, with high survival rates and can withstand high planting 
densities. 
Studies performed at the ERCO Tree Farm on over 11 clones have demonstrated that the 
OP376 variety (a Populus deltoides x P. nigra clone) is the overall best performer, 
exhibiting superior survival and growth in Maryland sites (Kays, 2002). 
Research at the ERCO Site 
Techniques implemented at the ERCO Tree Farm represent a confluence of 
trenching, reclamation of mine spoils, and poplar tree cultivation.  Research conducted at 
ERCO prior to this thesis experiment has focused on 1) groundwater monitoring, 2) 
nitrogen budgets and 3) hybrid poplar growth and survival.  Pepperman (1995) performed 
a review of data collected over the course of operations at the ERCO Tree Farm.  
Evaluation of soils collected during well drilling and placement of test pits provided an 
overview of the geological stratification at the site.  General observations included: 
1) Sand, gravel and some clay comprised the upper surface to depths of 0.91-1.22 m 
(3-4 ft). 
2) Silts with clay and traces of sand were present between 0.91-2.44 m (3-8 ft). 
3) Clays dominated depths from 2.44-5.49 m (8-18 ft). 
 
 28
4) Depths of 5.49-24.4 m (18-80 ft) consisted of fine sand, some clay and a little 
silt. 
The overriding conclusion was that a slowly permeable layer exists below the remnants 
of the mining operation.  This layer is situated at a depth below that of the biosolids rows. 
Seven groundwater wells installed up gradient, down gradient, and within the site 
provide information on background levels of pollutants and groundwater conditions after 
placement of biosolids.  A background sample collected in 1982 had a nitrate-N 
concentration of 1.5 mg/L and pH of 7.8.  Twelve years of subsequent monitoring after 
biosolids application showed the following trends. 
? Little change in overall water quality 
? No increase in chloride concentration.  As previously explained, chloride is a 
good indicator of water flow from the biosolids.  This demonstrates that water 
leaching from the biosolids is not percolating to the aquifer from which the 
groundwater samples are collected. 
? Nitrate concentrations were mostly nondetects.  The two highest readings of 1.5 
mg/L and 1.9 mg/L came from the same well, with the 1.5 mg/L reading 
occurring prior to application of biosolids (i.e., it represented background 
levels). 
? Metal concentrations, with particular focus on lead and cadmium, were near or 
below detection limits.  None of the detects exceeded the drinking water MCLs. 
? Fecal coliform levels were generally low, with some increased readings in 
November and August. 
 
 29
Pepperman also evaluated the nitrogen balance in this farming operation.  Inputs 
consist of the biosolids, atmospheric deposition, leaf litter and background soil 
concentration.  Outputs and/or storage vehicles include: the poplar trees; storage in the 
soil matrix; losses as leachate; and gaseous losses through volatilization and 
denitrification.  The greatest challenge in estimating the balance was determining an 
accurate degradation rate for the biosolids.  Most quantitative information on degradation 
comes from land application practices.  The deep row technique, however, creates a 
unique environment that hinders mineralization for the following reasons: 1) 
temperatures in the deep rows are lower than those near the surface, such that microbial 
activity is slower; 2) until tree roots permeate the soil and the biosolids begin to dewater, 
oxygen, which is necessary for nitrification, will be scarce; and 3) the high pH of the 
limed biosolids, along with the accompanying high salt concentrations, are adverse 
environments for some of the microbes that perform these nitrogen conversions. 
Using information derived from the literature and ongoing studies, including 
information on less than optimal growth of trees at the ERCO farm, Pepperman 
determined that the permitted rate of application was at least 25% less than that necessary 
for the specific operations at the ERCO site.  Results of this evaluation and other studies 
has led to the testing of increased application rates performed as part of this thesis 
project. 
As noted in the prior section on hybrid poplars, other studies at the ERCO tree farm 
tested the survival and growth of 11 different hybrids, and determined that the OP367 
variety was the most appropriate for use at the farm (Kays, 2002). 
 
 30
Chapter 3:  Objectives 
Primary objectives are as follows: 
? Evaluate the fate and transport of nitrate in biosolids and the surrounding soil 
profile over time. 
? Develop an overview of the water quality associated with the new crop of poplar 
trees that are being planted at a lower density with higher biosolids application 
rates through the analysis of soil leachate and soil water samples. 
 
 31
Chapter 4:  Methods and Materials 
Site Location and Characteristics 
The ERCO Tree Farm is a privately-owned tract of land in Brandywine, Maryland, 
situated on the southern edge of Prince George?s county (see Figure 2).  The former sand 
and gravel mine spans approximately 49 ha (122 acres) and has been subjected to 
reclamation efforts since 1983. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 2.  Location of the ERCO tree farm. 
 
The general technique employed at the ERCO site consists of applying biosolids 
in deep rows (approximately 0.76m deep x 1.0m wide) at a rate of either 383 or 658 dry 
Mg/ha (171 or 294 dry tons/acre).  Rows are dug with a backhoe and approximately ? of 
the trench depth is filled with biosolids.  The row is then covered with backfill from the 
subsequently dug row to produce an overburden cap approximately 0.3-0.6 m deep, 
effectively sealing the biosolids underground.  In the spring, hybrid poplar stem cuttings 
are planted on the treated field.  This one-time bulk application of biosolids acts as a 
nutrient source for the 6-year growing cycle, at which point the trees are harvested (Kays 
ERCO Tree Farm 
 
 32
et al., 1999).  Following harvest, the cycle is repeated, with new biosolids rows 
perpendicular to the prior rotation, facilitating a long-term operation that can ultimately 
produce a viable, permanent ecosystem. 
Approximately 36.5 ha (90 acres) of the gravel spoil is actively farmed at the 
ERCO site, with each 4.05-ha (10-acre) parcel in different phases of production.  Earlier 
rotations of tree crops were planted at densities as high as 1215 ? 2430 trees/ha (3000 ? 
6000 trees/acre), which resulted in crowding and stunted tree growth.  Beginning in 2000, 
however, crops of 202 trees/ha (500 trees/acre) have been planted in an attempt to 
produce a more marketable wood product. 
The site is topographically characterized as a plateau with steep forested banks 
that fall away to a stream incision.  Vegetated berms 0.6 ? 0.9 m (2-3 ft) high surround 
the plateaued areas to control runoff, and runoff is routed to four detention ponds.  Seven 
monitoring wells ranging in depth from 6.1-30 m (20-100 ft) were installed around the 
perimeter and within the plateaued area from 1982-1990. 
Background groundwater and soil samples were collected prior to the application 
of biosolids to establish baseline conditions.  During and subsequent to biosolids 
application, groundwater was evaluated from the monitoring wells on a biannual basis.  
Between 1988 and 1998, samples were collected and tested for:  fecal coliform, pH, 
color, chloride, turbidity, total residue, ammonia, nitrite, nitrate, total alkalinity, hardness, 
sulfate, arsenic, barium, cadmium, chromium, copper, fluoride, iron, lead, manganese, 
mercury, nickel, selenium, silver, sodium, and zinc.  Surface water samples also were 
collected from creeks upstream and downstream of the site as were soil samples before 
and after the biosolids application process.  Of particular interest were the fecal coliform, 
 
 33
chloride, nitrate, cadmium and lead results, due to their potential presence in biosolids 
and possible adverse health and environmental impacts.   
Analytical results demonstrated that the pollutants were not present in appreciable 
quantities in the water samples {i.e., concentrations were either nondetects, below the 
EPA drinking water maximum contaminant levels (MCLs), and/or below the Cumulative 
Pollutant Loading Rates as specified in 40 CFR 503}.  These results, collected over 10 
years of the farming operation, definitively indicated that the tree farm was not having 
adverse effects on the water supplies of the area (Pepperman, 1995).  Based on this well-
established trend of low metals concentrations, the Maryland Department of Environment 
(MDE), the regulatory authority overseeing ERCO?s permit, stipulated that metals and 
some of the wet chemistry parameters no longer needed to be determined.  Subsequent 
groundwater monitoring has focused on the shorter list of parameters and continues to 
date under the conditions of the current permit.  Overall, results continue to demonstrate 
that groundwater sources have not been adversely impacted by this beneficial reuse 
operation. 
Mining activities have destroyed and removed any semblance of an organized soil 
profile.  What remains are the mining spoils and an underlying 1.5-21.3 m (5-70 ft) 
clayey layer.  A more specific description of the soil presented in Wilson and Fleck 
(1990), which evaluated soil borings in Prince George?s County close to the Tree Farm 
site, is as follows. 
? The uppermost layer, which was removed during mining operations in the 1960s and 
70s, is described as Pliocene Upland Deposits.  These deposits, which ranged from 
6.1-15 m (20-50 ft) thick, consist of silty, fine to very course sand and gravels, as 
 
 34
well as some yellow or orange silty clays.  Though a majority of this layer was 
mined, remains of these deposits still exist throughout the farm. 
? The next layer down, which is what is now predominantly at the surface of the 
graded farming areas, is the lower Miocene Calvert Formation.  These marine shelf 
environment deposits are a micaceous, clayey silt approximately 27-30 m (90-100 ft) 
deep. 
? Underneath the Miocene is the lower Eocene Nanjemoy Formation, which consists 
of fine to medium glauconite-bearing sands and ranges from 27-38 m (90 ? 125 ft) in 
thickness. 
? Underneath all of the above is the Marlboro Clay Formation, a hydrologically 
confining unit between 4.6-9.1 m (15-30 ft) deep. 
? Multiple aquifers are located below the Marlboro Clay Formation. 
On-site soil sampling from well drilling and trenching activities have delineated a 
more site-specific geological stratification pattern, which was presented by Pepperman 
(1995) and is summarized in the literature review above.  One of the more important 
conclusions of this evaluation was that the site contained a confining, very slowly 
permeable layer situated below the deepest biosolids row depth (i.e., deeper than 0.8m) 
that would significantly hinder leachate flow to groundwater.  This is consistent with the 
findings of the Maryland Geologic Survey described above. 
Experimental Design 
This section provides a general overview of the experimental setup.  Details 
regarding implementation of each facet are provided in subsequent sections.  The 1.2-ha 
(3-acre) research site is located within a 3.65-ha (9-acre) parcel in the southeast corner of 
 
 35
the farm.  The entire 3.65-ha (9-acre) parcel has been subject to a prior round of biosolids 
application and tree cultivation under ERCO?s standard farming conditions.  The 1.2-ha 
(3-acre) experimental site was partitioned into three blocks based on a north-south 
gradient of changing soil composition and slope.  For this experiment, three biosolids 
application rates of 481, 962, and 1443 dry Mg/ha (215, 430, 645 dry tons/acre), which 
provided approximately 19,650, 39,300, and 58,900 kg N/ha (17,400, 34,800, and 52,000 
lbs N/acre), respectively and three tree densities of 0, 716, and 1074 trees/ha (0, 290, and 
435 trees/acre) were tested.  Each biosolids application rate/tree density combination was 
replicated three times.  Three controls, positioned on the west end of each block, 
contained no biosolids or trees.  Biosolids application rates were randomly assigned but, 
due to logistical considerations, tree densities were not. 
A total of 30 different subplots resulted from this set up with the layout representing 
a split-block design.  Each subplot extends approximately 22m (72 ft) in an east-west 
direction and either 32m (105 ft), 21.3m (70 ft), or 10.7m (35 ft) in a north-south 
direction to accommodate the tree densities of 0, 716, and 1074 trees/ha (0, 290, and 435 
trees/acre), respectively.  Within each subplot containing trees, an outer perimeter of two 
rows of trees (6.1m, or 20ft) was designated as a buffer to isolate treatments and potential 
edge effects.  All soil water collection equipment was installed in the inner rectangle 
delineated by this outer perimeter.  The general experimental layout is depicted in Figures 
3 and 4. 
 
 36
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 3.  Experimental layout. 
SOUTH 
NORTH 
Control
Control 
Control 
BLOCK 3
BLOCK 2
BLOCK 1
21.3m 
(70')
10.7m 
(35')
 32m 
(105')
21.3m 
(70')
21.3m 
(70')
10.7m 
(35')
10.7m 
(35')
 32m 
(105')
 32m 
(105')
22m (72') 22m (72') 22m (72')
Legend
19,650 kg N/ha
58,950 kg N/ha
39,300 kg N/ha
716 trees/ha
1074 trees/ha
0 kg N/ha
 
 37
SOUTH 
NORTH 
Control
Control 
Control 
BLOCK 3
BLOCK 2
BLOCK 1
21.3m 
(70')
10.7m 
(35')
 32m 
(105')
21.3m 
(70')
21.3m 
(70')
10.7m 
(35')
10.7m 
(35')
 32m 
(105')
 32m 
(105')
22m (72') 22m (72') 22m (72')
Legend
19,650 kg N/ha
58,950 kg N/ha
39,300 kg N/ha
716 trees/ha
1074 trees/ha
0 kg N/ha
Biosolids Row
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 4.  Experimental layout showing biosolids rows and subplot IDs. 
3A 3G 
3H 
3I 3F 
3E 
3D 
3C 
3B 
2A 
2C 
2B 
2F 
2E 
2D 
2I 
2G 
2H 
1A 
1B 
1C 1F 
1E 
1D 
1I 
1H 
1G 
4A 
4B 
4C 
 
 38
A set of sampling equipment designed to capture soil water under and around the 
deep rows was installed in each of the 30 subplots.  Each set of equipment consisted of 
the following: 
1) One pan lysimeter installed 0.3m (12 inches) under a deep row to collect 
leachate from saturated flow transport due to gravimetric forces.  Pan 
lysimeters were installed as biosolids rows were being filled.  A graphical 
depiction is provided in Figure 5. 
 
Figure 5.  Schematic of pan lysimeter layout. 
 
 
2) Five suction lysimeters installed under and around the deep row to collect soil 
water either flowing past due to gravimetric forces or, more predominantly, 
held in the soil profile by matric forces.  Three of the lysimeters were 
positioned 0.15m (6 in), 0.30m (12 in), and 0.60m (24 in) underneath the row 
Backfill
Biosolids
PVC pipe
Pan Lysimeter
30 cm (12 in.)
1 pan per subplot x 30 subplots = 30 pan lysimeters
 
 39
to capture vertical flow.  The other two were positioned to capture lateral 
flow, one at 0.15 m (6 in) and the other at 0.30m (12 in) from the side of the 
deep row in the soil profile.  Both were positioned at a depth equal to that of 
the bottom of the trench.  The lateral flow lysimeters were installed around 
the same biosolids row.  Suction lysimeters were installed after all biosolids 
rows were filled and the field was leveled.  Figure 6 shows the positions of 
the lysimeters relative to the biosolids row, though it is important to note that 
not all of the lysimeters were installed under the same row.  For more details 
regarding the requirements for suction lysimeter location, see the forthcoming 
section on suction lysimeter installation. 
When installing pan lysimeters, soil core samples were collected at and above the 
pan installation depth to evaluate hydraulic conductivity of the soil.  In addition, on a 
monthly basis as biosolids rows were being filled, a composite sample of the biosolids 
was collected upon delivery at the farm and analyzed for macro-and micro- nutrients as 
well as basic soil properties. 
A rain gauge was installed at the farm and rainfall data were collected over the 
course of the project to evaluate overall atmospheric input of water as well as isolated 
storm events. 
 
 40
 
 
 
Figure 6.  Schematic of suction lysimeter layout. 
 
 
Biosolids Characteristics and Application 
Biosolids currently used at the ERCO Tree Farm are from the Blue Plains 
Wastewater Treatment Plant in Washington, D.C.  These are dewatered, lime-stabilized 
sludges that, although categorized as Class B biosolids, have markedly low metals 
concentrations.  Lime stabilization is the addition of calcium oxide (CaO?quicklime) or 
calcium hydroxide (Ca [OH]2?hydrated lime) to sludge to elevate the pH to a level for 
an appropriate period of time to inactivate microorganisms.  Lime reacts with water to 
produce hydroxides that, in appropriate amounts, elevate the pH to 11 or 12, creating an 
environment inhospitable to the microbes.  In addition, when quicklime (CaO) is used, an 
Backfill
Biosolids
30 cm
15 cm
30 cm
60 cm
15 cm
5 lysimeters per subplot x 30 subplots = 150 lysimeters
 
 41
exothermic reaction occurs that elevates the temperature to fatal levels in the biosolids, 
further insuring the destruction of pathogens (EPA, 2000). 
During the design stage of the research project, several samples of the dewatered, 
lime-stabilized biosolids were collected upon drop off at the tree farm and showed, on a 
wet weight basis, an organic nitrogen concentration of 1.16% (11,600 mg/kg), total 
phosphorus content of 0.38% (3800 mg/kg), pH values between 11-12, and percent solids 
content of 20-25%.  Ammonia volatilization was evident from the distinct odor exiting 
the biosolids pile.  Throughout construction of the deep rows, biosolids samples were 
collected on a monthly basis to assess physical and chemical properties over time. 
Deep rows were constructed in a north-south direction (perpendicular to the prior set 
of deep rows) on 1.8?2.0 m (6-6.5 ft) centers with a width of 1.07 m (42 inches) and a 
total trench depth of either 0.61 m (24 inches), 0.94m (37 inches), or 1.24 m (49 inches), 
dependent upon the required application rate.  With these dimensions, rows were 
separated by approximately 0.93m of gravel spoils.  Rows were filled with biosolids to a 
depth of either 0.32 m (12.5 inches), 0.64 m (25 inches), or 0.96 m (37.5 inches) to 
achieve application rates of 1694, 3388, and 5082 wet Mg/ha (757, 1515, and 2277 wet 
tons/acre).  With an average percent solids of 28%, this converts to 481, 962, and 1443 
dry Mg/ha (215, 430, and 645 dry tons/acre).  These biosolids loading rates resulted in 
total nitrogen applications of approximately 19,650, 39,300, and 58,900 kg N/ha (17,418, 
34,837, and 52,255 lbs N/acre). 
As biosolids were applied to the appropriate depths, they were covered with an initial 
layer of overburden.  Then, as the next row was dug, the excavated overburden was 
placed on top of the previously filled row.  This excavated layer, combined with the 
 
 42
initial layer of overburden, produced a cap over the biosolids approximately 0.46 ? 0.76 
m (1.5-2.5 ft) thick, effectively sealing the biosolids within the mine spoils.  This process 
is shown in the pictures below (Figures 7-10). 
 
 43
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 7.  Digging a deep row. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 8.  Offloading biosolids. 
 
 
 44
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 9.  Pushing biosolids into a deep row. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 10.  Covering biosolids with overburden. 
 
 45
The basis of the experimental application rates were a combined evaluation of 1) the 
standard application rate of 383 dry Mg/ha (171 dry tons/acre) used at the tree farm 2) the 
demonstration plot application rate of 658 dry Mg/ha (294 dry tons/acre) used at the tree 
farm, 3) studies on the foliar nutrient content of the trees at the farm as well as 4) 
nitrogen mass balance estimates for the operation.  With past total nitrogen contents of 
approximately 3.5% (dry weight), the standard 383 dry Mg/ha (171 dry tons/acre) 
biosolids application rate provided approximately 13,400 kg N/ha (12,000 lbs N/acre) 
and the 658 dry Mg/ha (294 dry tons/acre) rate provided approximately 23,070 kg N/ha 
(20,600 lbs N/acre).  Nitrogen budget evaluations and foliar nutrient data collected from 
past rotations indicated that trees at the farm were not being supplied with enough 
nitrogen (Pepperman, 1995).  After four to six years of growth, foliar nitrogen 
concentrations dropped below the optimal 3.5% level and in some plots foliar 
concentrations diminished to the point that trees were considered nutrient deficient. 
Consequently the biosolids rates used in this experiment were designed to test rates 
similar to and greater than those in operation at the farm.  Initial design planned for 
application rates of 20,160, 40,320, and 60,480 kg N/ha (18,000, 36,000 and 54,000 lbs 
N/acre).  Slightly lower rates of 19,650, 39,300, and 58,954 kg N/ha were actually 
applied once it was determined that the substrate was too unstable to incorporate 12 
biosolids rows within a 21.3m subplot width, and 11 rows were instead applied.   
The biosolids distribution required for a given application rate is dependent upon the 
dimensions of the deep rows and how closely spaced the deep rows can be placed, among 
other factors.  The procedure used to determine the amount of biosolids needed for each 
application rate is itemized below, with detailed calculations following in table format.  
 
 46
Note that each set of calculations is presented twice; first in S.I. Units, followed by a 
second table with the same information in non-S.I. Units to facilitate comparison to other 
studies. 
1) Based on the wet weight nitrogen content of the biosolids being used, 
calculate the amount of biosolids (wet weight, Mg/ha) required for each 
given kg N/ha application rate (see Table 1 for SI units and Table 2 for non-
SI units). 
2) Given a subplot with a set length and width, and given a set number of 
biosolids rows that can be incorporated into the subplot, determine the 
amount of biosolids (wet weight, Mg/ha) that needs to be placed into each 
row of a given length to meet the application rate (see Table 3 for SI units 
and Table 4 for non-SI units). 
3) Given a set length and width for each row, determine how many wet Mg of 
biosolids will be included for each unit depth (i.e., 1 cm) of a row. 
4) Based on the calculations performed in Steps 2 and 3, determine the depth of 
biosolids needed in each row, regardless of row length, for each application 
rate (see Table 5 for SI units and Table 6 for non-SI units).  Note:  It is 
important to determine the required depth of biosolids independent of row 
length because the length of the subplots will be different depending upon the 
tree density being used. 
5) Based on the actual depths of biosolids applied and the number of biosolids 
rows used in each subplot, back-calculate the actual application rate used in 
this experiment (see Table 7 for SI units and Table 8 for non-SI units). 
 
 47
Table 1.  Determination of biosolids application rates needed to meet nitrogen loading 
rate design (S.I. Units). 
Required 
N loading 
rate (kg 
N/ha) 
% N  
(wet 
weight) 
Mg N/wet Mg 
Biosolids 
= (1.16 ? 100) 
kg N/wet Mg Biosolids 
= (0.0116*1000kg N/Mg 
N) 
Wet Mg/ha needed for 
required N loading rate  
= {kg N/ha required ? 
kg N/wet Mg biosolids} 
20,160 1.16 0.0116 11.6 20,160 ? 11.6 = 1738 
40,320 1.16 0.0116 11.6 40,320 ? 11.6 = 3476 
60,480 1.16 0.0116 11.6 60,480 ? 11.6 = 5214 
N=total nitrogen; ha = hectare; Mg = megagram = 1000 kg = metric tonne 
 
 
Table 2.  Determination of biosolids application rates needed to meet nitrogen loading 
rate design (non-S.I. Units). 
Required 
N loading 
rate (lbs 
N/acre) 
% N  
(wet 
weight) 
Tons N/WT Biosolids  
= (1.16 ? 100) 
lbs N/WT Biosolids = 
(0.0116*2000lbs/ton) 
WT/Acre Needed for 
required N loading rate  
= {lbs N/acre required ? 
lbs N/WT biosolids} 
18,000 1.16 0.0116 23 18,000 ? 23 = 783 
36,000 1.16 0.0116 23 36,000 ? 23 = 1565  
54,000 1.16 0.0116 23 54,000 ? 23 = 2348  
lbs = pounds;  N=total nitrogen; WT = wet tons (i.e., U.S. Ton = 2000 lbs) 
 
 
With these wet Mg/ha (and wet tons/acre) values and a subplot area 21.9m (72 ft) 
wide by 21.3m (70 ft) long, the wet Mg needed per 21.3m row based on a set number of 
rows can be estimated (see Table 3 for data in S.I. units and Table 4 for non-S.I. units).  
Although the original plan was to install 12 biosolids rows within each 21.9m (72ft) 
width plot, it also was recognized that soil stability issues might require wider row 
spacing.  For this reason, the calculations below consider both 11 and 12 rows per 21.9m 
plot width. 
Table 3.  Determination of wet Mg of biosolids required per 21.3m (70 ft) row (S.I. 
Units). 
Required 
N 
loading 
rate (kg 
N/ha) 
Wet Mg/ha 
needed for 
required N 
loading rate 
21.3m x 
21.9m 
Sample 
Plot Area 
(m2) 
Sample 
Plot Area 
(ha) = 
m2*1.0E-4 
ha/m2 
Wet Mg/Plot = 
(wet 
Mg/ha*ha/Plot) 
Number of 
21.3m Rows 
Anticipated 
per 21.9m 
width plot 
Wet Mg 
Needed Per 
21.3m Row 
(wet Mg/Plot ? 
#rows/plot) 
20,460 1738 468 0.0468 81.3 11 or 12 7.4 or 6.8 
40,320 3476 468 0.0468 162.7 11 or 12 14.8 or 13.6 
60,480 5214 468 0.0468 244 11 or 12 22.2 or 20.4 
N=total nitrogen; ha = hectare; Mg = megagram = 1000 kg = metric tonne 
 
 48
 
Table 4.  Determination of wet tons of biosolids required per 70-foot row (non-S.I. 
Units). 
Required 
N loading 
Rate (lbs 
N/acre) 
Wet 
Tons/acre 
needed for 
required N 
loading rate 
70' x 72' 
Sample 
Plot Area 
(ft2) 
Sample Plot 
Area (acres) 
=ft2*22.9E-6 
acres/ft2 
Wet Tons/Plot = 
(WT/acre*acres/Plot) 
Number of 
70' Rows 
Anticipated 
per 72' 
width plot 
Wet Tons 
Needed Per 
70' Row 
18,000 783 5040 0.1157 90.6 11 or 12  8.2 or 7.5 
36,000 1565 5040 0.1157 181.0 11 or 12 16.5 or 15.1 
54,000 2348 5040 0.1157 271.6 11 or 12 24.7 or 22.6 
lbs = pounds;  N=total nitrogen; WT = wet tons  
 
 
The next step is to determine the number of wet Mg that each cm depth of the trench 
can hold.  From this calculation, the required depth of biosolids needed for each 
application rate can be determined.  With a trench width of 1.067m, length of 21.3m, and 
0.01m-unit depth, the unit volume is 0.2272m3.  This volume can be converted to a 
weight measurement with the following conversion factors (University of Missouri 
Extension, 2006; EPA, 1995; Knute, 1986). 
Given: 1 ft3 = 62.4 lbs of biosolids (Note:  this assumes the biosolids density is 
similar to that of water.  Biosolids density estimates range from approximately 62.4 ? 
75 lbs/ft3, dependent upon percent moisture and other factors.) 
Given: 1 ft3 = 0.0283 m3 
Then: 0.0283 m3 = 62.4 lbs of biosolids 
Then: 1 m3 = 2,205 lbs of biosolids 
Given: 1 Mg = 2,205 lbs 
Then: 1 m3 biosolids = 1 Mg biosolids 
Using the 0.2272m3 volume determined above for a one-cm depth of a biosolids row: 
0.2272m3 *1 Mg biosolids/m3 biosolids = 0.2272 Mg biosolids per cm of a 21.3m 
length row. 
 
 49
Using the wet tons needed per 21.3m row (from the last column of Table 3) for each of 
the three application rates, the depth of biosolids in each row (regardless of row length) 
can be determined as shown in Table 5. 
 
Table 5.  Determination of cm of biosolids needed per application rate (S.I. Units). 
 Wet Mg Needed 
per 21.3m row 
Wet Mg Biosolids 
per 1cm unit depth 
of 21.3m length row 
Cm of biosolids needed =  
Wet Mg needed ? Wet Mg per cm 
6.8 0.2272 6.8 ? 0.2272 = 30.0 
13.6 0.2272 13.6 ? 0.2272 = 59.8 
12 rows 
20.4 0.2272 20.4 ? 0.2272 = 89.8 
7.4 0.2272 7.4 ? 0.2272 = 32.7 
14.8 0.2272 14.8 ? 0.2272 = 65.3 
11 rows 
22.2 0.2272 22.2 ? 0.2272 = 98.0 
 
 
To determine this same information in non-S.I. units, a one-inch biosolids depth is 
used as the standard unit. With a trench width of 3.5ft, length of 70ft and 0.0833ft (1-
inch) unit depth, the unit volume is 20.42ft3.  This volume can be converted to a weight 
measurement with the conversion factors listed previously. 
Given: 1 ft3 = 62.4 lbs of biosolids 
Then: 20.42 ft3 * 62.4 lbs biosolids/ ft3 = 1274 lbs biosolids  
per 1-inch depth of a 70ft row. 
1274 lbs biosolids * 1Ton/2000lbs = 0.637 wet tons biosolids  
per 1-inch depth of a 70 ft row.   
Using the wet tons needed per 70ft row (from the last column of Table 4) 
for each of the three application rates, the depth of the biosolids in each row 
(regardless of row length) can be determined as shown in Table 6. 
 
 50
Table 6.  Determination of inches of biosolids needed per application rate (non-S.I. 
Units). 
 Wet Tons Needed per 
70ft row 
Wet Tons Biosolids 
per 1-inch unit 
depth of 70ft row 
Inches of biosolids needed =  
WT needed ? WT per inch 
7.5 0.637 7.5 ? 0.637 = 11.8 
15.1 0.637 15.1 ? 0.637 = 23.7 
12 rows 
22.6 0.637 22.6 ? 0.637 = 35.5 
8.2 0.637 8.2 ? 0.637 = 12.9 
16.5 0.637 16.5 ? 0.637 = 25.8 
11 rows 
24.7 0.637 24.7 ? 0.637 = 38.7 
 
 
Although it was originally anticipated that 12 rows could be installed within each 21.9m 
(72ft) subplot width, once installation commenced, it proved to difficult to maintain 
stability between rows at this density.  Consequently 11 rows were installed within each 
21.9m subplot width.  Actual depths of biosolids installed, and the adjusted actual 
nitrogen application rates are provided in Tables 7 and 8 below. 
 
Table 7.  Back calculation of kg N/ha applied (S.I. Units). 
A B C D E F G H 
Actual 
Depth 
Used 
(cm) 
Wet Mg 
Biosolids 
per cm of 
21.9m row 
Wet Mg 
per 
21.9m 
Row = 
A*B 
# Rows 
per 
subplot 
Back 
calculated 
Wet 
Mg/subplot 
= C*D 
Subplot 
Area 
(ha/subplot) 
Back 
calculated 
Wet Mg/ha 
= E/F 
Back 
calculated 
kg N/ha 
= 11.6*G 
31.7 0.2272 7.20 11 79.4 0.0468 1694 19,650 
63.5 0.2272 14.39 11 158.7 0.0468 3388 39,300 
95.2 0.2272 21.59 11 238.1 0.0468 5082 58,954 
 
 
Table 8.  Back calculation of lbs N/acre applied (non-S.I. Units). 
A B C D E F G H 
Actual 
Depth 
Used 
(in.) 
Wet Tons 
Biosolids 
per inch of 
70 ft row 
Wet 
Tons per 
70ft 
Row = 
A*B 
# 
Rows 
per 
subplo
t 
Back 
calculated 
Wet 
Tons/subplot 
= C*D 
Subplot 
Area 
(acres/subpl
ot) 
Back 
calculated 
Wet 
Tons/acre 
= E/F 
Back 
calculated 
lbs N/acre 
= 23*G 
12.5 0.64 7.96 11 79.4 0.1157 757 17,418 
25.0 0.64 15.93 11 158.7 0.1157 1515 34,837 
37.5 0.64 23.89 11 238.1 0.1157 2272 52,255 
 
 
 
 51
The average percent solids in the biosolids over the course of application averaged 
28.4%.  The Wet Mg/ha (wet tons/acre) specified in Tables 7 and 8 produces application 
rates of 481, 962, and 1443 dry Mg/ha (215, 430, 645 dry tons/acre).  Nitrogen content 
averaged 1.16% wet weight, consistent with values obtained during the design phase of 
the experiment. 
Planting of Hybrid Poplar Clones 
Due to an extremely wet spring, planting was delayed from the usual April/May 
schedule until June 2003.  Unrooted cuttings of the OP367 cultivar of hybrid poplar clone 
(Populus deltoides x Populus nigra) were obtained from Broadacres Nursery in Hubbard, 
Oregon.  When refrigerated, they can be maintained in a dormant state until planting 
time.  Cuttings were prepared for planting by removing them from refrigerated conditions 
and soaking in water for several hours.  Trees were planted on 3m x 3m (10 ft x 10 ft) 
spacing for 435 trees/acre and 3m x 4.6 m (10 ft x 15 ft) spacing for 290 trees/acre.  Each 
experimental subplot extends approximately 22m (72 ft) in an east-west direction and 
either 32m (105 ft), 21.3m (70 ft), or 10.7m (35 ft) in a north south direction for the 435, 
290 and 0 trees/acre densities, respectively (see Figure 4). 
The standard planting technique used at ERCO consists of attaching a subsoiling bar 
to a bulldozer and etching a set of 0.3m deep lines that are 3m (10 feet) apart and parallel 
to one another in one direction of the field, followed by etching a similar set of lines 
perpendicular to the first set.  This creates a square grid over the field.  At the intersection 
of the lines, a tree cutting is planted by hand, resulting in 3m x 3m spacing (i.e., 1074 
trees/ha or 435 trees/acre).  Tree rows are not intentionally situated directly over the 
biosolids rows, though in some instances this may occur by coincidence.  Over 20 years 
 
 52
of experience at the ERCO site definitively shows that tree roots will naturally grow 
towards the water and nutrient source.  Consequently, positioning trees over the biosolids 
would incorporate an unnecessary layer of planning into the planting process.  In 
addition, it would only be possible if the tree row spacing were the same as the biosolids 
row spacing. 
Because some of the soil water sampling equipment had been installed prior to 
planting, it was not possible to use a tractor or bulldozer to cultivate the field with a 
subsoiling bar as described above.  Instead, rows were delineated by hand with a tape 
measure and the planting locations were marked with spray paint.  A dibble bar was used 
to create a hole for the approximately 0.3m long cutting.  Between 2/3 to 3/4 of the 
cutting length was placed in the hole, which was then packed with dirt to seal out air and 
create close contact between the surface of the tree cutting and the soil.  Figures 11 ? 14 
depict the planting procedure. 
 
  
 
 
Figure 11.  Laborer with dibble bar. 
 
 
 
 53
  
 
Figure 12.  Dibble hole and poplar cutting. 
 
 
 
 
 
 
  
Figure 13.  Cutting in ground. 
 
 
 
 54
  
Figure 14.  Cutting with initial leaf growth. 
 
 
In summer 2003 and spring 2004, pre-emergent herbicides were applied in 3-foot 
strips along each side of the trees to reduce competition from weeds.  In spring 2004, tree 
mortality was assessed.  Any trees that had died were removed and replaced with new 
cuttings. 
Pan Lysimeter Installation 
Pan lysimeters were assembled at the University of Maryland Biological Resources 
Engineering machine shop.  Pans were constructed from stainless steel sheets (ASTM-
176-B7) to form a container with a square, open top and sloping underside to deliver 
collected soil water to one point underneath the pan.  Stainless steel sheets were welded 
to the interior of the pan across the length and width to provide structural support.  A cast 
stainless steel threaded T-fitting was attached under the deep end of the bottom of the pan 
to provide an access port for the sampling line positioned below the bottom of the pan.  A 
 
 55
stainless steel wire mesh lid (304 stainless steel 0.120 inch diameter, woven plain square 
weave, 2x2 inch mesh, 0.380 inch opening) was placed over the top of the pan to provide 
additional structural support.  Nylon window screening was sewn on top of the wire mesh 
lid to filter out smaller particulates.   
Prior to installation, pans and screens were cleaned by wiping them down with 
isopropyl rubbing alcohol, followed by a distilled water rinse and then a deionized water 
rinse.  Pan lysimeters were determined to be capable of holding approximately 10 liters 
of liquid.  Overall shape and dimensions of the pan (not drawn to scale) are shown in 
Figures 15 and 16.  Pictures of the pans are provided in Figures 17 and 18. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 15.  Front view of pan lysimeter. 
 
 
 
 
 
 
 
 
Sampling outlet 
Plugged outlet 
26.6 cm 26.6 cm 
13 cm 
53.3 cm 
5 cm 
 
 56
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 16.  Side view of pan lysimeter. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 17.  Pan lysimeter top view. 
 
 
 
 
Sampling outlet 
Plugged outlet 
13 cm 
53.3 cm 
Interior Structural Supports 
53.3 cm 
53.3 cm 
 
 57
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 18.  Underside of pan lysimeter and protective wire mesh lid (on left). 
 
 
Pan lysimeters were installed between July 2002 and March 2003, concurrent with 
the construction of biosolids rows at the research plot.  Details of each installation 
process are provided in Appendix 1.  Once the requisite length of biosolids row was 
complete, a measuring wheel was used to determine the appropriate section of the row 
under which the pan needed to be located (i.e., the interior zone of the subplot, inside the 
buffer perimeter as discussed in the Experimental Design section).  An installation trench 
was dug using a backhoe to a depth sufficient for workers to comfortably stand while 
drilling 0.3m below the bottom of the biosolids row.  The installation trench was dug 
parallel to the biosolids row as close to it as possible without compromising the integrity 
of the installation trench wall (approximately 0.61m (2 feet)). 
Wire Mesh Lid 
Underside of Pan 
 
 58
The specific depth of the biosolids row at the installation location was determined by 
sinking a steel T-handled point bar into the biosolids row until it reached the bottom of 
the row.  The overburden covering the biosolids row was loosened from digging and was 
easily penetrated, as was the biosolids.  The resistance to movement upon reaching the 
bottom of the biosolids row/mine spoil interface, however, was markedly higher than 
when the point bar was sliding through the biosolids.  The bar depth at this interface was 
marked, measured, and used as the basis for calculating pan installation depth.  These 
measurements also served as a comprehensive quality control check for the biosolids row 
construction process, and demonstrated good agreement with the designed depths. 
For the control subplots, the depth of installation was the same as the design depth 
for the lowest application rate.  Using a designed row depth of 0.61m, plus the 0.30m 
distance between the bottom of the row and the pan, pans were installed at a depth of 
0.91m under the surface. 
As stated in the Experimental Design section, the research plot and surrounding 
acreage had previously received an application of biosolids under the standard ERCO 
regimen.  Consequently, old biosolids rows ran perpendicular to (though not necessarily 
at the same depth as) the new rows being laid out for this experiment.  The old biosolids 
rows had been subject to years of dewatering, microbial conversion, and tree root 
infiltration.  In this decomposed state, they often served as preferential flow paths for 
subsurface flow.  Dependent upon the application rate and corresponding depth of the 
new row, the old rows could be either above, at the same level as, or below the vertical 
position of the pan.  It was therefore important to horizontally position each pan lysimeter 
 
 59
equidistant from the two bracketing old rows to ensure the pans captured flow migrating 
from and around the new biosolids rows.  Figure 19 graphically depicts this concept. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 19.  Cross-sectional view of installation trench wall. 
 
 
Upon determining the pan installation depth with regard to the new biosolids row 
and horizontal pan position with regard to old biosolids rows, a rectangle 0.56m wide x 
0.15m tall was etched into the installation trench wall to guide drilling.  Drilling distance 
into the trench wall was calculated as the distance between the installation trench wall 
Pan Installation Opening (equidistant 
from old biosolids rows) 
Old row Old row 
New Biosolids Row 
Note:  The new biosolids row is not visible from the installation 
trench (it is 0.6m away from the installation trench wall) 
Installation Trench Surface 
Leachate Flow 
 
 60
and biosolids trench wall (usually 0.6m) plus the length of the pan lysimeter (0.53m), for 
a total drilling distance of approximately 1.13m.  Basic installation steps are as follows. 
? Drill the pan installation cavity.  The drill used was a Milwaukee 350 rpm, ? 
inch Super Hole Shooter with pipe handle (Catalog No. 1854-1).  A generator 
provided the electrical power.  The original drill bit used was a modified bulb 
and plant auger with 6.35cm (2.5 inch) diameter flights and 61cm (24 inch) 
length.  This broke within a minute of drilling.  Trailer anchors with 15.24cm (6 
inch) flights were then used.  The end of the anchors with the bolt bracket was 
cut off so it would fit in the drill bit.  This modified auger proved much more 
sturdy and could withstand the drilling pressure.  Prior to subsequent 
installations, teeth were welded onto the first flight in the auger to give it more 
cutting power. 
? Clean out and shape the cavity using shovels to fit the dimensions of the pan 
lysimeter. 
? Test the pan fit by sliding the pan into the cavity and ensuring that the ceiling 
wall of the cavity allows for a flat, level placement of the top of the pan. 
? Rinse the pan to remove any mine spoils and other particulates that may have 
entered the pan while out in the field.  Fit the wire mesh and window screening 
(which was previously sewn to the wire mesh) into the top lip of the pan 
lysimeter.  Collect an equipment blank on the pan and screens by rinsing with 
deionized water.  Permanently plug the bottom opening of the pan with a 
2.66cm (? inch) threaded PVC plug using PVC primer and glue.  Screw another 
 
 61
2.66cm (? inch) threaded PVC plug into the sampling portal to temporarily 
cover the opening. 
? Slide the pan into the cavity until it reaches the back wall.  In some installations, 
a layer of playground sand was placed on the bottom of the cavity to facilitate 
sliding of the pan into the cavity. 
? One person would hold the top of the pan flush against the ceiling of the cavity 
while another person would use the previously removed cavity contents to 
tightly repack the cavity and hold the pan in place. 
? Once the back end of the pan was secure enough to remain flush against the 
ceiling without assistance, the plug was removed from the sampling portal and 
permanently replaced by gluing a 2.66 cm (? inch) threaded PVC coupling.  A 
length of 2.66cm (? inch) straight PVC pipe measured to reach a couple of 
inches from the installation trench wall was then glued into the PVC coupling.  
The pipe was propped level with packed mine spoils (and in some cases a 
crushed soda can) to ensure it did not have a downward slope in the direction of 
the trench wall. 
? A 2.66cm (? inch) 45? PVC elbow joint was glued to the end of the PVC pipe. 
? Another, usually smaller length of straight PVC pipe was cut and glued to the 
other end of the 45? elbow.  Another 45? elbow was glued to the other end of the 
shorter PVC pipe.  At this point, the PVC pipe and connections reached out of 
the installation cavity next to the wall, and the second 45? elbow was pointing 
straight up. 
 
 62
? A final 3.05m (10 ft) straight PVC pipe was glued to the second 45? elbow to 
provide a continuous, protected watertight conduit through which sampling line 
could be threaded into the pan lysimeter for sample collection. 
? A 2.66cm (? inch) PVC cap was placed on top of the pipe to close the pipe 
network. 
? The remainder of the pan installation opening was tightly repacked with the 
native soil that had been drilled out to make the opening.  The remainder of the 
installation trench was then refilled and tightly packed with the original 
contents. 
? Soil core samples were collected along the installation trench wall (or along the 
opposite side of the installation trench if space constraints necessitated).  One 
core was collected in line with the pan lysimeter location; one core was 
collected 30cm (12 inches) above the first soil core; the third core was collected 
60 cm above (24 inches) above the first soil core.  These were used to evaluate 
soil properties, specifically hydraulic conductivity. 
? The installation trench was filled with the previously excavated mine spoils.  As 
the trench was refilled, the ground was tamped with both the backhoe bucket 
and a hand tamper to ensure the soil around the opening of the pan cavity would 
not be looser than the surrounding soil. 
A pictorial layout of the pan installation is provided in Figures 20-25.  While some 
installations were completed with relative ease within 4 hours, others proved more 
problematic.  In some cases, heavy subsurface water flow into the trench from the old 
biosolids rows flooded the bottom of the installation trench.  Submersible pumps were 
 
 63
installed to clear out the water, though regardless installations were more complicated 
given the wet conditions.  In other instances, soil instability and texture made drilling 
difficult.  In a few cases, the integrity of the pan lysimeter cavity or the installation trench 
could not be maintained during the drilling process and the site had to be abandoned, at 
which point a new installation location was determined under a different biosolids row 
within the subplot. Figures 26-29 depict the pan positions as well as the suction lysimeter 
positions at the experimental site. 
Each installation trench provided insight into the varying soil profile in each of the 
subplots.  As previously stated, the southernmost experimental area (Block 3) was 
characterized by higher clay content, with increasing sand and gravel present from Block 
2 to Block 1.  While in general this overall trend was representative, the soil profile 
within each installation trench was variable.  Block 3 subplots had pockets of sandier 
soils and Block 1 subplots contained pockets of clay soils.  In addition, the old 
decomposed biosolids rows introduced yet another soil characteristic into the profile.  
These observations demonstrate that soil composition varies with depth at this site, and 
encompasses a wide range of characteristics. All installation measurements and 
conditions were recorded and transferred to installation diagrams and a summary table.  
These pan-specific installation diagrams and the accompanying table with details about 
the installations are provided in Appendix 1.  
 
 64
 
Figure 20.  Drill with modified trailer anchor as auger (pan and screening in background). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 21.  Installation trench wall with etched outline of pan installation cavity. 
 
 
Old Biosolids 
Rows 
Pooled Water 
Exiting from 
Old Biosolids 
Row 
Etched 
Pan 
Outline 
 
 65
 
 
 
 
 
 
 
 
Figure 22.  Drilling out pan outline. 
Figure 23. Drilled hole with 
fines for repacking. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 24.  Pan installed with attached PVC piping. 
Figure 25.  Front view of PVC 
piping exiting pan cavity. 
Soil Core 
Sampling Sites 
Pan 
Installation 
Cavity 
PVC Pipe 
 
 66
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 26.  Experimental plot layout with pan and suction lysimeter positions. 
2m = 6.5 ft
BL
OC
K 
3
21.9m (72 ft)
43
0 t
ree
s/a
cre
    
 (2
1.3
m 
= 7
0 f
t)
29
0 t
ree
s/a
cre
    
 (3
2m
 = 
10
5 f
t)
 0 
tre
es/
acr
e  
 
(10
.7m
 = 
35
 ft)
Subplot 3A
Subplot 3B
Subplot 3C
BL
OC
K 
2
29
0 t
ree
s/a
cre
    
 (3
2m
 = 
10
5 f
t)
43
0 t
ree
s/a
cre
    
 (2
1.3
m 
= 7
0 f
t)
 0 
tre
es/
acr
e  
 
(10
.7m
 = 
35
 ft)
Subplot 2A
Subplot 2B
Subplot 2C
2m = 6.5 ft 2m = 6.5 ft
21.9m (72 ft)
Subplot 3D
Subplot 3E
Subplot 3F
2m = 6.5 ft
2  = 6.5 ft
43
0 t
ree
s/a
cre
 (2
1.3
m 
= 7
0 f
t)
29
0 t
ree
s/a
cre
  (3
2m
 = 
10
5 f
t)
21.9m (72 ft)
Subplots shifted 12.2m (40 ft) south due to 
unstable soil in Block 1
0 t
ree
s/a
cre
    
   
(10
.7m
 = 
35
ft)
Subplot 3I
Subplot 3H
Subplot 3G
BL
OC
K 
1
 0 
tre
es/
acr
e  
 
(10
.7m
 = 
35
 ft)
29
0 t
ree
s/a
cre
    
 (3
2m
 = 
10
5 f
t)
43
0 t
ree
s/a
cre
    
 (2
1.3
m 
= 7
0 f
t)
Subplot 1A
Subplot 1B
Subplot 1C
Subplot 2D
Subplot 2E
Subplot 2F
Subplot 1D
Subplot 1E
Subplot 1F
43
0 t
ree
s/a
cre
 (2
1.3
m 
= 7
0 f
t)
29
0 t
ree
s/a
cre
  (3
2m
 = 
10
5 f
t)
0 t
ree
s/a
cre
    
   
(10
.7m
 = 
35
ft)
Subplot 1G
Subplot 1H
Subplot 1I
29
0 t
ree
s/a
cre
  (3
2m
 = 
10
5 f
t)
43
0 t
ree
s/a
cre
 (2
1.3
m 
= 7
0 f
t)
0 t
ree
s/a
cre
    
   
(10
.7m
 = 
35
ft)
Subplot 2G
Subplot 2H
Subplot 2I
0 trees/acre    
(6.1m = 20ft)
Subplot 4A
x
0 trees/acre    
(6.1m = 20ft)
Subplot 4B
x
0 trees/acre    
(6.1m = 20ft)
Subplot 4C
Legend
19,650 kg N/ha
58,950 kg N/ha
39,300 kg N/ha
30cm vertical SL
30cm lateral SL
0 kg N/ha
Biosolids Row
Pan Lysimeter
60cm vertical SL
15cm vertical SL
15cm lateral SL
 
 67
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 27.  Block 3 pan and suction lysimeter installation locations. 
Subplot 3C 
Subplot 3B 
Subplot 3A 
Subplot 3F 
Subplot 3E 
Subplot 3D 
Subplot 3I 
Subplot 3H 
Subplot 3G 
Note: For the first 5 rows, the 58,900 
kgN/ha application rate was stopped 
6.1m (20ft) too soon and 39,300 kg N/ha 
started up 6.1m (20ft) above where it 
2m = 6.5 ft 2m = 6.5 ft
21.9m (72 ft)21.9m (72 ft)
4 3
0  t
r e e
s / a
c r e
 ( 2
1 . 3
m  
=  7
0  f
t )
2 9
0  t
r e e
s / a
c r e
    
 ( 3
2 m
 =  
1 0
5  f
t )
 0  
t r e
e s /
a c r
e   
 
( 1 0
. 7 m
 =  
3 5
 f t )
0 trees/acre    
(6.1m = 20ft)
NORTH 
2m = 6.5 ft
43
0 t
ree
s/a
cre
 (2
1.3
m 
= 7
0 f
t)
29
0 t
ree
s/a
cre
  (3
2m
 = 
10
5 f
t)
21.9m (72 ft)
Subplots below shifted 12.2m (40 ft) south due to 
unstable soil in Block 1
0 t
ree
s/a
cre
    
   
(10
.7m
 = 
35
ft)
Subplot 4A 
Subplot 3C 
Subplot 3B 
Subplot 3A Subplot 3D 
Subplot 3E 
Subplot 3F 
Subplot 3G 
Subplot 3H 
Subplot 3I 
Legend
19,650 kg N/ha
58,950 kg N/ha
39,300 kg N/ha
30cm vertical SL
30cm lateral SL
0 kg N/ha
Biosolids Row
Pan Lysimeter
60cm vertical SL
15cm vertical SL
15cm lateral SL
1 0
7 4
 t r e
e s /
h a
 =  
7 1
6  t
r e e
s / h
a  =
 
10
74
 tre
es/
ha
 = 
71
6 t
ree
s/h
a =
 
 
 68
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 28.  Block 2 pan and suction lysimeter installation locations. 
2m = 6.5 ft 2m = 6.5 ft
21.9m (72 ft) 21.9m (72 ft)
2 9
0  t
r e e
s / a
c r e
    
 ( 3
2 m
 =  
1 0
5  f
t )
4 3
0  t
r e e
s / a
c r e
 ( 2
1 . 3
m  
=  7
0  f
t )
 0  
t r e
e s /
a c r
e   
 
( 1 0
. 7 m
 =  
3 5
 f t )
x
0 trees/acre    
(6.1m = 20ft)
2m = 6.5 ft
Subplots shifted 12.2m (40 ft) south due to 
unstable soil in Block 1
21.9m (72 ft)
43
0 t
ree
s/a
cre
 (2
1.3
m 
= 7
0 f
t)
0 t
ree
s/a
cre
    
   
(10
.7m
 = 
35
ft)
29
0 t
ree
s/a
cre
  (3
2m
 = 
10
5 f
t)
NORTH 
Subplot 2A 
Subplot 2C 
Subplot 2B 
Subplot 2F 
Subplot 2E 
Subplot 2D 
Subplot 2I 
Subplot 2H 
Subplot 2G 
Subplot 4B 
Legend
19,650 kg N/ha
58,950 kg N/ha
39,300 kg N/ha
30cm vertical SL
30cm lateral SL
0 kg N/ha
Biosolids Row
Pan Lysimeter
60cm vertical SL
15cm vertical SL
15cm lateral SL
1 0
7 4
 t r e
e s /
h a
 =  
7 1
6  t
r e e
s / h
a  =
 107
4 t
ree
s/h
a =
 
71
6 t
ree
s/h
a =
 
 
 69
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 29.  Block 1 pan and suction lysimeter installation locations. 
NORTH 
x
0 trees/acre    
(6.1m = 20ft)
2m = 6.5 ft 2m = 6.5 ft
 0  
t r e
e s /
a c r
e   
 
( 1 0
. 7 m
 =  
3 5
 f t )
21.9m (72 ft) 21.9m (72 ft)
2 9
0  t
r e e
s / a
c r e
    
 ( 3
2 m
 =  
1 0
5  f
t )
4 3
0  t
r e e
s / a
c r e
 ( 2
1 . 3
m  
=  7
0  f
t )
2m = 6.5 ft
0 t
ree
s/a
cre
    
   
(10
.7m
 = 
35
ft)
43
0 t
ree
s/a
cre
 (2
1.3
m=
70
 ft)
29
0 t
ree
s/a
cre
  (3
2m
 = 
10
5 f
t)
21.9m (72 ft)
Subplots below shifted 12.2m (40 ft) south due to 
unstable soil in Block 1
Subplot 1A 
Subplot 1B 
Subplot 1C Subplot 1F 
Subplot 1E 
Subplot 1D 
Subplot 1G 
Subplot 1H 
Subplot 1I 
Subplot 4C 
Legend
19,650 kg N/ha
58,950 kg N/ha
39,300 kg N/ha
30cm vertical SL
30cm lateral SL
0 kg N/ha
Biosolids Row
Pan Lysimeter
60cm vertical SL
15cm vertical SL
15cm lateral SL
71
6 t
ree
s/h
a =
 
10
74
 tre
es/
ha
 = 
1 0
7 4
 t r e
e s /
h a
 =  
7 1
6  t
r e e
s / h
a  =
 
 
 70
Suction Lysimeter Installation 
Suction lysimeters were installed from July-August 2003, after all biosolids had been 
applied to the experimental site and trees had been planted.  An itemized listing of 
installation dates and conditions is provided in Appendix 1.  The pressure/vacuum soil 
water sampler (a.k.a., suction lysimeter) used in this experiment was obtained from 
Soilmoisture Equipment Corp. (product no. 1920F1L12B02M2).  The sampler was 30cm 
(12 inch) long, with a 4.83cm (1.9 inch) outer diameter PVC body and an epoxy bonded 
200kPa (2 bar) porous ceramic cup (1.1um pore size) on one end.  The other end of the 
PVC body was capped and threaded with nylon compression fittings through which 
customized lengths of access tubes (0.64cm {0.25 inch} outer diameter polyethylene 
tubing) were attached.  A plastic dip tube inside the sampler was attached to the 
underside of the cap directly under the one of the nylon fittings and extends down the 
PVC body into the ceramic cup. 
The suction lysimeter collects soil water held in the soil profile under matric forces 
by pulling the water through the ceramic cup while under tension.  After a requisite 
period of time, the tension is discontinued.  The collected soil water is then purged from 
the sampler by applying pressure to the access tube, which pushes the collected sample 
out through the sample recovery tube.  A diagram of the suction lysimeter is provided in 
Figure 30. 
 
 71
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 30.  Suction lysimeter (pressure-vacuum soil water sampler). 
 
 
Suction lysimeters were obtained from the vendor assembled; only the access tubes 
needed to be attached.  Green medium density polyethylene (MDPE) tubing (0.65cm 
outer diameter) was used for the sampling access line and black MDPE tubing was used 
for the vacuum/pressure line.  Approximately 2.4-3.6m lengths of the MDPE tubing were 
connected to each lysimeter.  Neoprene tubing, cut into 10-15cm lengths was placed over 
the exposed end of the access lines, bent in half, and held in position with a clamping 
ring.  This effectively sealed the access lines until pressure or tension needed to be 
applied.  After attaching access tubes, all suction lysimeters were soaked in water for 
several hours to prime the ceramic cup.  Pressure was then applied with a hand pump 
through the pressure access tube while clamping off the sample recovery tube.  The entire 
Porous Ceramic Cup 
PVC Tube 
Nylon Compression Fitting 
Pressure/Vacuum Access Tube 
Nylon Compression Fitting 
Sample Recovery Access Tube 
Dip Tube (inside sampler) 
 
 72
submerged apparatus was observed to determine if any bubbles were escaping, which 
would indicate the presence of an unwanted leak.  Particular attention was paid to the 
interface of the PVC tube and ceramic cup as well as the nylon compression fittings.  
Leaks in the nylon compression fittings were the most common, and were eliminated by 
adjusting the tightness of the fittings. 
As previously noted, installations occurred during the summer of 2003.  Installations 
needed to be within the interior zone of each subplot, inside the buffer perimeter.  In 
addition, suction lysimeters needed to be 3.05m (10 feet) from both the pan lysimeter and 
the former pan installation trench to prevent any interactions amongst equipment.  
Typically, four different biosolids rows were needed for the five suction lysimeters 
required per subplot.  One row was used for the two lateral flow lysimeters, which were 
positioned on either side of a biosolids row.  A separate biosolids row was then used for 
each of the three vertical flow lysimeters. 
Lateral flow lysimeter installations required that both edges of the biosolids be 
delineated.  One lysimeter was then installed 0.15m (6 inches) from one side and the 
other lysimeter was installed 0.3m (12 inches) from the other side to evaluate lateral flow 
over two distances.  The two distances were randomly assigned to the east and west sides 
of the biosolids row.  These lysimeters were installed on either side of the biosolids row 
in the mine spoils at a depth equal to that of the bottom of the biosolids row. Diagrams of 
the suction lysimeter positions within each subplot are provided in Figures 26-29 in the 
prior section on Pan Lysimeter Installation.  Details regarding the individual installations 
are provided in tabular format in Appendix 1. 
 
 73
Suction lysimeters were soaked in water for several hours right before installation 
and tested a second time to ensure no leaks were present.  The standard protocol for 
installation of the suction lysimeter was consistent with that provided in the 
1920F1/1920F1K1 Pressure-Vacuum Soil Water Samplers Operating Instructions 
Manual (Soilmoisture Equipment Corporation, 1997) and is summarized below.  The 
installation process at the site is depicted in Figures 31-46. 
? Identify the appropriate area within which installations are to be performed (within 
inner subplot). 
? Place plastic tube protectors over trees in the delineated area. 
? Using a backhoe, carefully uncover between 0.3-0.6m of overburden in an east-west 
direction within a subplot until the top of one or two biosolids rows can be identified 
with a point bar.  Note:  Because installations took place in the summer, the 
experimental area contained a natural cover crop of native grasses and weeds that 
were dug up during this process. 
? Determine the specific depth of the biosolids row at the installation location by 
sinking a steel T-handled point bar into the biosolids row until it reaches the bottom 
of the row.  Evaluate whether or not an old biosolids row is underneath the new 
biosolids row.  Given that the old biosolids rows are often less dense than the new 
biosolids row, the point bar will sink significantly deeper than the designated depth 
of the new biosolids row.  Move to a different location in the biosolids row if this 
occurs because the suction lysimeters are not to be installed within an old row. 
? If the lateral flow suction lysimeters are being installed, the east and west edges of 
the biosolids trench also need to be delineated using the point bar.  Measure 0.15m 
 
 74
and 0.30m from the designated east and west side of the trench walls to identify the 
installation locations. 
? If the vertical flow suction lysimeters are being installed, only the depth to the 
bottom of the biosolids row needs to be determined. 
? Note:  The equipment used to drill the installation hole included 1) a Little Beaver
 
11 hp hydraulic earth drill with a 2-man handle as well as 2) a hand auger with a 9-
10cm diameter.  A level was periodically placed on top of the hydraulic drill handle 
to ensure a vertical hole was being drilled. 
? Excavate a hole to the appropriate depth with the hydraulic drill.  Periodically pull up 
the auger and empty the residue out of the hole.  Save it for repacking the cavity. 
  When installing the lateral flow lysimeters, drill in the mine spoils to a 
depth equal to the bottom of the biosolids row. 
  When installing the vertical flow lysimeters, drill through the biosolids 
row and then either 0.15m, 0.30m, or 0.60m beneath the row. 
Note:  The excavated holes from both the mine spoils and biosolids material 
remained intact during the drilling and installation process and did not require 
additional wall support to prevent collapse.  This made the installation process much 
simpler than originally anticipated, especially with regard to the vertical installations 
directly underneath the biosolids rows. 
? Approximately 5-10 cm before reaching the bottom of the lysimeter cavity, switch 
over to a hand auger to reach the final depth and to better clean out the bottom of the 
cavity.  Monitor depth periodically throughout the drilling process with a tape 
measure. 
 
 75
? Sift the overburden drilled from the installation cavity through a sieve to remove 
particles >2mm and to produce a relatively uniform backfill soil. 
? Pour approximately 200mL of distilled water down the hole and, using a wooden 
stake (or similar implement), mix the water with backfill soil to make some mud at 
the bottom of hole. 
? Make some mud in a bucket by mixing screened spoil that was excavated from the 
hole with distilled water. 
? Pack the mud in the bucket around the ceramic cup of the suction lysimeter.  This 
will create a hydraulic seal that will promote good flow of soil water through the 
ceramic cup. 
? Taking care to keep the mudpack around the ceramic cup, lower the suction 
lysimeter into the installation hole.  Push the lysimeter into the mud at the bottom of 
the hole.  The mud should fill the hole slightly above the ceramic cup. 
? Fill the hole around the lysimeter with more mud and backfill to between one-third 
to halfway up the lysimeter. 
? Take approximately 3-5 handfuls of dry bentonite and deposit in the hole to make a 
ring around the lysimeter.  The bentonite will expand as it makes contact with the 
mud and absorbs moisture.  It will expand and form an impermeable collar around 
the lysimeter column. 
? Backfill the hole with native soil, packing the soil while filling.  When the level of 
packed backfill is just under the top cap of the lysimeter, pour more dry bentonite 
around the lysimeter to make a second bentonite plug at the top of the lysimeter.  
These bentonite plugs will seal the area around the lysimeter to prevent water from 
 
 76
selectively passing down the drilled hole through any fissures that could not be 
completely packed up.  This will ensure that the soil water collected through the 
ceramic cup is representative of the leachate that percolated through the biosolids 
and soil profile to the depth of the lysimeter. 
? Fill the remainder of the hole with backfill, carefully packing it around the lysimeter 
to prevent the creation of preferential flow paths. 
? Move the lysimeter access hoses to the sides of the trench and fill in the trench with 
the backhoe.  Tamp the trench as it is being filled.   
? Use plastic cable ties to attach the exposed portions of the access tubes to wooden 
stakes that are securely hammered into the soil. 
? After each installation, remove any remaining residue from the augers used in the 
drilling process. 
As with the pan lysimeters, for the Control subplots, the depth of installation was the 
same as the design depth for the lowest application rate.  Using a designed row depth of 
0.61m, suction lysimeters were installed at the appropriate depths in relation to the 
theoretical biosolids row. 
 
 77
 
 
Figure 31.  Removing overburden to 
locate biosolids rows. 
Figure 32.  Biosolids rows. 
 
 
 
Figure 33.  Measuring biosolids depth. 
Figure 34.  Drilling equipment. 
 
 
Biosolids 
Row 
Biosolids 
Row 
 
 78
 
 
Figure 35.  Drilling hole. 
Figure 36.  Drilled hole in control 
subplot. 
 
 
 
Figure 37.  Laterally placed lysimeter hole 
(to the side of the biosolids row). 
Figure 38.  Vertically placed lysimeter 
hole (below the biosolids row). 
 
 
 
 
 
 79
 
Figure 39.  Measuring depth. 
Figure 40.  Cleaning out bottom of hole 
with hand auger. 
 
 
 
 
 
 
Figure 41.  Sifting drilled soil. 
Figure 42.  Sieve used for sifting. 
 
 
 
 
 80
 
 
 
Figure 43.  Placing mudpack around 
ceramic cup. 
Figure 44.  Pouring bentonite around 
lysimeter to create a watertight plug. 
 
 
Figure 45.  Packing fill around lysimeter. 
Figure 46.  Lysimeter lines placed to the 
side of the installation site. 
 
 
 
 
 
 
 
 
 
 81
 
Sample Collection 
Soil Water Samples 
On a monthly basis, soil water samples were collected from the 30 pan lysimeters 
and 150 suction lysimeters for testing at a water quality lab.  The experimental site was 
divided into three sets of subplots running in a north-south direction.  Each of the three 
sets was sampled in a given week within the same month.  Within a sampling week, pan 
lysimeters were collected on one day and suction lysimeters were usually collected on a 
different day.  Sample collection for pan lysimeters commenced in April 2003.  Sample 
collection for suction lysimeters commenced in November 2003.  This thesis addresses 
samples collected through December 2004. 
Each pan lysimeter was fitted with a dedicated line of polyethylene tubing running 
down the inside of the PVC pipe that was connected to the pan lysimeter.  Samples were 
drawn out of the polyethylene tubing into a 1-L filtration flask by applying suction on the 
arm of the flask with a vacuum hand pump.  Water was withdrawn until the pan emptied 
or the estimated volume of the pan (i.e., 10-L) was extracted, whichever occurred first.  
In some instances, volumes greater than 10-L could be extracted, due to the fact that 
water recharged more quickly than sample could be removed.  In other instances, pans 
did not contain leachate and a sample could not be collected.  For each 1-L of volume 
collected, 100-mL was sub-sampled and placed in a 1-L high-density polyethylene 
container to produce a composite sample representative of the contents of the pan.  This 
composite sample was transferred to a smaller, high-density polyethylene (HDPE) 125 or 
200mL container for delivery to and processing at the laboratory.  The total volume and 
appearance of the sample purged from the pan was recorded.  Samples were stored on ice 
 
 82
in a cooler until delivery at the laboratory.  Figures 47-52 show the pan lysimeter sample 
collection process. 
Figure 47.  Hand pump and sample 
collection flask for the pan lysimeter. 
Figure 48.  Collecting a pan lysimeter 
sample in the flask. 
 
 
 
 
Figure 49.  Pouring an aliquot of sample 
into the compositing container. 
Figure 50.  Rinsing the sample collection 
flask with distilled water. 
 
Suction Line 
Line from 
Pan 
Lysimeter 
 
 83
 
 
 
 
Figure 51.  Rinsing the flask with 
deionized water. 
Figure 52.  Rinsing the stopper and tubing 
with deionized water. 
 
As previously shown in Figure 30 above, each suction lysimeter apparatus contains a 
dedicated pressure-vacuum access tube and discharge access tube.  Approximately three 
to four days prior to the collection date, 60-70 centibars of suction was applied to the 
vacuum access tube with a hand pump while keeping the discharge access tube closed.  
The vacuum tube was then closed to maintain suction and draw sample from the soil 
matrix through the porous ceramic cup of the suction lysimeter.  Sample was then 
recovered from the suction lysimeter by opening both lines, applying pressure to the 
pressure-vacuum tube, and collecting the sample that ejected from the discharge access 
tube in a graduated cylinder.  The volume and appearance of the sample collected was 
recorded, and transferred into pre-labeled 125mL HDPE bottles.  Samples were stored on 
ice in a cooler until delivery at the laboratory.  Figures 53-58 show the sample collection 
process. 
 
 84
 
Figure 53.  Hand pump next to suction 
lysimeter vacuum and pressure lines. 
Figure 54.  Applying suction to the 
lysimeter vacuum access tube. 
 
 
 
 
Figure 55.  Purging sample by applying 
pressure. 
Figure 56.  Sample collected in graduated 
cylinder. 
 
 
 
 
 
 
 
 
 85
 
 
Figure 57.  Transferring sample to 
labeled container. 
Figure 58.  Rinsing sampling equipment 
with deionized water. 
 
Both pan and suction lysimeter samples were transported in coolers on ice to the 
laboratory for further processing.  Samples were measured for pH and an aliquot was 
vacuum filtered through a 0.45um nylon membrane filter to remove particulates.  A 
separate aliquot was preserved with sulfuric acid to pH < 2.  All samples were frozen 
until analyzed. 
Biosolids Samples 
As mentioned in the experimental design section, during the construction of the 
biosolids rows in the experimental plot, biosolids samples were collected on a monthly 
basis to evaluate nutrient and other parameters over time.  After being offloaded from the 
delivery truck, a composite sample was obtained by taking five to seven aliquots from 
different parts of the biosolids pile and mixing them together in a HDPE sampling 
container.  Biosolids samples were placed on ice and frozen, then delivered to the 
laboratory for analysis. 
 
 86
Soil Core Samples 
During the installation of pan lysimeters, soil core samples representative of the soil 
profile at and above the pan installation location were collected along the installation 
trench wall.  Soil cores were collected in either 5.4cm diameter, 6cm length brass 
cylinders with beveled ends or 4.7cm diameter, 5cm length aluminum cylinders.  One end 
of the cylinder was placed on the surface of the soil site to be collected and a wooden 
block was placed over the other end of the cylinder.  The cylinder was driven into the soil 
by hammering on the wooden block.  The filled cylinder was carefully removed from the 
soil and covered with plastic caps on both ends.  
Soil cores were obtained from three different depths in the soil profile for 28 of the 
30 subplots.  For the remaining two subplots (subplots 3B and 2B), one and two soil 
cores were collected, respectively.  The depth of sample collection was in relation to the 
position of the pan lysimeter (and therefore the depth of the biosolids row, which 
correlates to the application rate).  Soil cores were collected at 1) the depth of the pan 
lysimeter installation, 2) 30 cm above the pan depth, and 3) 60 cm above the pan depth.  
Diagrams depicting the collection location at each installation subplot are provided in 
Appendix 1.   
Rain Gauge Data 
A tipping bucket rain gauge connected to a HOBO
 Event data logger from Onset 
Computer Corporation was installed on an open rooftop of a trailer adjacent to the west 
side of the experimental plot.  This site was equal to or higher than all other trailers in 
near proximity and devoid of trees.  On a biweekly basis, data from the rain gauge was 
downloaded in accordance with the protocols for the Onset Computer Corporation?s 
 
 87
Boxcar
 software.  Each event recorded by the logger was equivalent to 0.025cm 
(0.01inch) of rainfall, and was associated with a specific date and time.  Rainfall event 
files from the data logger were imported to excel spreadsheets, converted to cm of 
rainfall and summed to determine daily totals. 
The rain gauge was physically inspected on a monthly basis to ensure all components 
were unencumbered by insects, spider webs, or debris and that all parts were in working 
order.  When temperatures were below freezing, the heating component of the rain gauge 
was turned on to ensure any frozen precipitation would be melted and properly recorded 
Laboratory Analysis of Soil Water, Biosolids and Soil Samples 
Soil Water Samples 
Pan and suction lysimeter samples were transported to the laboratory after collection.  
Samples were analyzed for pH on a Fisher Scientific accumet Basic AB15 pH meter.  An 
aliquot of sample was vacuum filtered through a 0.45um pore size nylon membrane filter 
(Whatman part no. 7404-004) and frozen until analyzed.  Original, unfiltered aliquots 
were frozen and placed in storage.  Filtered samples were analyzed for total nitrogen, 
ammonium, nitrite, and nitrate.  With the exception of some nitrate and nitrate analyses 
noted below, all analyses were performed by the Appalachian Laboratory at the 
University of Maryland Center for Environmental Studies in Frostburg, MD.  Analytical 
methods/protocols used included the following. 
? Total nitrogen:  Standard Methods, Method 4500-N B.  In-Line UV/Persulfate 
Digestion and Oxidation with Flow Injection Analysis (APHA, 1998) 
? Ammonium nitrogen:  Lachet QuickChem Method 10-107-06-3-D, Revision 
Date August 26, 2003 (Sodium salicylate ?based method). 
 
 88
? Nitrite/nitrate:   
a) Methods for Chemical Analysis of Water and Wastes (MCAWW) 
Method 353.2 Determination of Nitrate-Nitrite Nitrogen by 
Automated Colorimetry (using a Lachet Quick Chem 8000 Flow 
Injection Analyzer) (EPA, 1983).  Both nitrite and nitrite+nitrate are 
determined; nitrate is then mathematically calculated as the 
difference. 
OR 
b) Bran and Luebbe Method 696E-82W (nitrite) and 696F-82W 
(nitrite+nitrate).  These methods are based on Methods 4500-NO2 B. 
and 4500-NO3 H, respectively, from Standard Methods for the 
Examination of Water and Wastewater (APHA, 1998).  Nitrate is 
mathematically calculated as the difference between Nitrite+nitrate 
and nitrite. 
Note:  The Braun and Luebbe method was used for samples collected prior 
to March 2004, which were analyzed at the University of Maryland?s 
Water Quality Laboratory in the Biological Resources Engineering 
Department in College Park, MD.  Samples collected during and after 
March 2004 were analyzed using MCAWW Method 353.2 by the 
Appalachian Laboratory at the University of Maryland Center for 
Environmental Studies in Frostburg, MD. 
 
 89
Biosolids Samples 
Biosolids samples collected on a monthly basis during set up of the experimental plot 
were delivered to the University of Maryland?s Maryland Cooperative Extension 
Laboratory in College Park, MD.  Analytical methods/protocols used included the 
following. 
? A sample aliquot is analyzed for moisture content. 
? Ammonium nitrogen:  A representative fresh (not dried) aliquot is distilled using 
MgO (Association of Official Analytical Chemists {AOAC} Section #2.057. 
? For all remaining analyses, a sample aliquot is dried at 80?C and ground in a Wiley 
Mill to pass through a 20 Mesh sieve. 
? Organic nitrogen:  Leco CHN combustion determination (Campbell, C.R. 1992.  In 
Plant analysis reference procedures for the southern region of the U.S.  Southern 
Cooperative Research Ser. Bulletin 368. USDA, Washington, D.C. pp. 21-23). 
? Total nitrogen:  The sum of ammonium and organic nitrogen. 
? Magnesium, phosphorus, potassium and calcium:  Perchloric/Nitric acid digestion 
followed by Technicon AutoAnalyzer determination (Walsh, L.M., 1971). 
? Manganese, zinc, and copper:  Perchloric/Nitric acid digestion followed by Atomic 
Absorption determination (Gorsuch, 1970). 
? Sulfur:  Leco S132 combustion determination (Leco Application Bulletin 203-601-
073). 
Soil Core Samples 
Hydraulic conductivity was determined on soil cores collected concurrent with the pan 
lysimeter installations.  Analyses were performed in-house at the University of Maryland 
 
 90
Biological Resources Engineering Soil Water Laboratory using an adaptation of the 
constant head protocol delineated in Methods of Soil Analysis (Knute, A. 1986).  The 
protocol is based on Darcy?s Law, in which: 
q = Q/A = -k(?h/?l)        (1) 
where: 
q = hydraulic flux 
Q = volumetric flow rate = volume of water flowing through core sample (V) 
for a given time (t) = V/t 
A = cross sectional area of the core sample (cylinder).  Determine from pid2/4. 
k = hydraulic conductivity 
?h = the hydraulic head difference imposed across a sample of length ?l? 
{i.e., difference in height between the bottom of the Mariotte air tube (i.e., 
bottom of copper tubing) and bottom of brass soil core cylinder} 
?l = length of the core sample (distance through which the water flows) 
t = time 
For these experiments, ?h/?l was approximately 10. 
Solving for k = hydraulic conductivity: 
-k = (V*?l)/(A*?h*t)        (2) 
In summary, a soil core sample is placed in a Tempe Cell and saturated with water from 
the bottom up.  The Tempe Cell set up was modified to replace the ceramic disk that is 
normally placed in the bottom of the cell underneath the soil core with a thin, porous 
hydrophobic polypropylene material made by Porex Corporation.  The resistance of the 
 
 91
material is orders of magnitude less than the soil samples and hence is neglected in the 
hydraulic conductivity calculation. 
A Mariotte reservoir is filled with water and flushed until air bubbles exit the 
Mariotte air tube within the reservoir.  The Mariotte tube is used to deliver water to a soil 
column at a constant outlet pressure.  Tygon tubing extending from the bottom opening 
of the Mariotte reservoir is filled with water in the process of flushing.  This tubing is 
then attached to the upper opening of the Tempe Cell without introducing air bubbles to 
the system.  A known pressure head is consequently established with the Mariotte air 
tube positioned at a known height above the core sample that sits in the Tempe Cell.  The 
spigot at the bottom of the Mariotte reservoir is opened.  A steady stream of water from 
the Mariotte reservoir flows to the Tempe Cell and through the soil core sample.  The 
volume of water flowing through the core sample for a known amount of time is used to 
determine the hydraulic conductivity based on the equation provided above.  The general 
set-up is shown in Figure 59. 
 
 
 92
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 59.  Saturated hydraulic conductivity constant head set up. 
 
Tygon Tubing carrying water 
Tempe Cell 
Saturated Soil Core 
in Brass Cylinder 
Tempe Cell 
Inlet 
Graduated Cylinder 
Tempe Cell Outlet 
Mariotte Reservoir  
(filled with water) 
Mariotte Air Tube 
Air Bubbles from Air Tube 
?h = Hydraulic 
head difference.  
Distance between 
air tube outlet and 
Tempe Cell 
outlet. ?l = length 
of soil 
cylinder 
 
 93
Data Analysis 
Data were statistically analyzed using analysis of variance (ANOVA) techniques 
(Kuehl, 2000) to evaluate trends in hydraulic conductivity with depth and location, water 
quality over time, and whether differences exist in water quality between biosolids 
application rates and tree densities.  SAS 9.1.  2002-2003 (SAS Institute, Inc., Cary, 
North Carolina) was used to perform these analyses. 
Hydraulic conductivity and nitrogen data were statistically analyzed using analysis 
of variance (ANOVA) techniques with SAS statistical software (v. 9.1).  Hydraulic 
conductivity results were examined in terms of block and depth.  This factorial treatment 
design was evaluated using PROC Mixed.  Significant fixed effects (?=0.05) were then 
subjected to Least Squares Means evaluation to isolate which interactions were 
responsible. 
Water quality data from the pan and suction lysimeter soil water samples were 
subjected to the following procedures.  The monthly measurements were averaged on a 
quarterly basis for each subplot.  Seasonal quarters were similar, but not exact for the pan 
lysimeters and suction lysimeters, due to the different start dates for collection activities 
and the need to have a data set complete enough to successfully run through the statistical 
procedures.  Table 9 identifies which months were consolidated into the seasonal 
quarters. 
 
 94
Table 9.  Quarterly assignments for monthly samples. 
Pan Lysimeter Suction Lysimeter 
Month-Year Quarter Month-Year Quarter* 
April-2003 1 N/A  
May-2003 1 N/A  
June-2003 2 N/A  
July-2003 2 N/A  
August-2003 2 N/A  
September-2003 3 N/A  
October-2003 3 N/A  
November-2003 3 November-2003 4 
December-2003 4 December-2003 4 
January-2004 4 January-2004 4 
February-2004 4 February-2004 4 
March-2004 5 March-2004 5 
April-2004 5 April-2004 5 
May-2004 5 May-2004 5 
June-2004 6 June-2004 6 
August-2004 6 August-2004 6 
October-2004 7 October-2004 7 
December-2004 8 December-2004 7 
 
 
As is shown in Table 9, suction lysimeter samples could not be separated into as 
many quarters as the pan lysimeters for the November 2003 to December 2004 time 
period.  Specifically, the averaging of suction lysimeter (SL) results over more months 
for quarters 1 and 4 was necessitated by the fact that for each subplot, 5 different 
positions/depths were represented by the SLs.  Samples were not always present each 
month (or for several months) at a particular lysimeter, and data were therefore not 
generated during those times.  If the data set was not complete enough for a particular 
position, statistical analyses were in some cases compromised and usable results could 
not be generated.  This necessitated the consolidation of more of the monthly results than 
with the pan lysimeters. 
Non-detect results were set to a value equal to 2/3 of the detection limit (Douglass, 
L., personal communication, 2005).  Data for each analyte were then evaluated to 
 
 95
determine if they met the normal distribution and homogeneity of residuals assumptions 
of ANOVA.  Upon determining that they did not, data were log transformed and again 
evaluated.  Log transformation produced data sets that met the assumptions for ANOVA. 
The split plot experimental design and collection of data over time provides a 
repeated measures data set best analyzed using the Mixed procedure with repeated 
measures analysis techniques that: 1) estimate the covariance residuals and 2) use the 
variance and covariance estimates to determine appropriate standard errors and test 
hypotheses (Douglass, 2005).  Six different covariance structures were evaluated to 
determine which structure best described the random variances and covariances among 
the repeated measures.  These included: compound symmetry (CS), heterogeneous 
compound symmetry (CSH), first-order autoregressive {AR(1)}, heterogeneous first-
order autoregressive {ARH(1)}, spatial power{SP(power)}, first-order ante-dependence 
{ANTE(1)}, unstructured (UN) (Littel, R.C., et. al., 1996). 
Upon determining the most appropriate structure for the data set (i.e., the one with 
the best goodness of fit measurement), the program was run to evaluate whether or not 
the null hypothesis was rejected.  The null hypothesis and alternate hypothesis were: 
Ho = Treatment effects means and interaction effects means are equal 
Ha = Treatment effect means and/or interaction effects means are not equal 
 
 96
Tests of fixed effects showed which null hypotheses were rejected based on a 
probability level of 0.05.  Those rejected null hypotheses were further evaluated by the 
least squares difference (LSD) procedure to compare individual treatment means.  
Significant differences (p < 0.05) from the LSD analysis were then studied to determine 
if any differences were important in the context of the experiment (Kuehl, 2000; Littel, 
R.C., et. al., 1996). 
 
 
 97
Chapter 5.  Results and Discussion 
Results and the accompanying discussion are presented in the following order: 
? Biosolids analysis 
? Hydraulic conductivity 
? Rain gauge data 
? Soil water analysis and results:  overview 
? Soil water results:  total nitrogen and ammonium (NH4+-N) data 
? Soil water results:  nitrite (NO2-) data 
? Soil water results:  nitrate (NO3-) data. 
Biosolids analysis results provide information about the nutrient content applied 
during the course of the experimental set up.  Hydraulic conductivity values offer insight 
to the potential flux of water throughout the experimental plot at different depths within 
the soil profile.  Precipitation values from the rain gauge provide further information on 
hydrologic conditions impacting water percolation in the soil profile.  Soil water results 
are the main focus of this thesis.  These include results from the pan and suction 
lysimeter samples collected to ascertain nitrogen concentrations in close proximity to the 
biosolids rows. 
 
 
 98
Biosolids Samples 
As stated in the Chapter 4, biosolids were dewatered and lime-stabilized with a pH of 
approximately 12.  Samples were collected on a monthly basis during application to the 
experimental site to monitor the concentrations of macro and micronutrients.  Summary 
results from the analysis of these samples are presented in Table 10. 
Table 10.  Biosolids analysis results (wet weight basis). 
 
 
 
 
 
 
 
 
 
These data were reported by the laboratory on a wet weight basis.  Because moisture 
content varies amongst biosolids, it is useful to report results on a dry weight basis to 
allow for comparisons with other biosolids.  Conversion is performed using the formula:  
Cdry = Cwet (100/%solids), where C = concentration of the parameter.  Dry weight 
conversions are presented in Table 11.  For reference, those results reported in percent 
(%) units can be converted to mg/kg units by multiplying the % value by 10,000. 
Table 11.  Biosolids analysis results (dry weight basis). 
 
 
 
 
 
 
 
 
 
Results demonstrated relatively consistent values over time, with magnesium (Mg) 
and ammonium (NH4+) exhibiting the highest relative variability.  In both instances, the 
Descriptive 
Statistic N (%)
NH4-N 
(%)
P2O5 
(%)
K2O 
(%) Ca (%) Mg (%) S (%)
Mn 
(ppm)
Zn 
(ppm)
Cu 
(ppm)
Moisture 
(%)
Mean 1.15 0.073 0.84 0.12 3.42 0.09 0.19 49.16 111.04 58.53 71.76
Standard 
Deviation 0.12 0.05 0.11 0.04 1.25 0.14 0.06 16.70 38.40 11.19 3.55
Coefficient of 
Variation 10.57 69.66 12.78 35.49 36.67 155.85 31.73 33.96 34.58 19.11 4.94
Descriptive 
Statistic
Moisture 
(% )
Solids (% )                
= 100-% M N (% )
NH4-N 
(% )
P2O5 
(% )
K2O 
(% ) Ca (% )
Mg 
(% ) S (% )
Mn 
(ppm)
Zn 
(ppm)
Cu 
(ppm)
Mean 71.76 28.24 4.12 0.27 2.99 0.41 11.94 0.31 0.66 173.55 394.20 207.42
Standard 
Deviation 3.55 3.55 0.43 0.22 0.36 0.14 3.39 0.43 0.17 53.57 139.15 29.54
Coefficient of 
Variation 4.94 12.56 10.37 83.19 12.16 33.89 28.42 140.58 26.42 30.87 35.30 14.24
 
 99
high variability is attributed to a single outlier value.  For ammonium, a markedly high 
value of 1.51% (15,100 mg/kg) dry weight was reported for the 3/26/2003 sample, 
compared to an average value of 0.27% dry weight.  For magnesium, a notably high 
value of 2.85% (28,500 mg/kg) dry weight was reported for the second of two samples 
collected on 11/27/2003, compared to an average value of 0.31% dry weight.  These 
individual sample results (as opposed to the mean values shown in this section) are 
presented in Appendix 2.  When these outliers were removed, the coefficient of variation 
decreased significantly for both parameters, becoming comparable to those values 
reported for other parameters (see Table 12). 
Table 12.  Biosolids results: revised after removal of outliers (dry weight basis). 
 
 
 
 
 
 
 
 
 
A specific explanation could not be obtained for the two unusually high values.  The 
consistency of all other values indicates that they could be the result of a calculation or 
transcription error.  Another possibility for the outlier ammonium value could be 
explained by its transient nature under certain conditions.  The high pH conditions of the 
biosolids (pH=11-12) drive the conversion of ammonium to gaseous ammonia (NH3).  
Wherever the biosolids are in contact with air, ammonia can escape into the atmosphere. 
Adamsen and Sabey (1987) conducted studies in which the ammonia content of 
surface-applied biosolids was measured at the time of application and at various intervals 
thereafter.  Results showed that 40% of ammonium can be lost via conversion to gaseous 
Descriptive 
Statistic NH4-N (%) Mg (%)
Mean 0.23 0.24
Standard Deviation 0.07 0.04
Coefficient of 
Variation 29.94 17.35
 
 100
ammonia within 2 weeks.  Because the biosolids from the ERCO study are stored in a 
yard at the wastewater treatment plant and moved frequently with a front-end loader, 
variable amounts of ammonium could be lost during storage or transport of the biosolids.  
Despite the ammonium and magnesium anomalies, the overriding conclusion is that 
biosolids of consistent composition and nutrient content were applied to the site 
throughout the experimental setup. 
 
 101
 
Hydraulic Conductivity 
Soil core results show a wide range in saturated hydraulic conductivity from 
1.40x10-7 ? 1.84x10-2 cm/sec, reflecting varied soil composition, some with high clay 
content and others dominated by sand and gravel.  This range is consistent with visual 
observations during equipment installations at the site.  Visual observations indicated 
higher sand and gravel contents in Block 1, with successive transition over to higher silt 
and clay content through Blocks 2 and 3.  Also noted, however, during equipment 
installations was the fact that some subplots with sandy soil at the surface had clay layers 
or pockets further in the soil profile.  Similarly, the higher clay content surface in Block 3 
would sometimes contain sandier layers and pockets at different depths.  Thus, the soil 
composition was reflective of the extensive disturbance and mixing of overburden that 
would occur during excavation operations at a gravel mine. 
A fresh sample of biosolids was also subjected to the hydraulic conductivity analysis.  
The hydraulic conductivity measured was 2.55x10-6 cm/sec, reflecting properties similar 
to silty and clay soils.  If the soil surrounding the biosolids row has a higher conductivity 
value than the biosolids, water entering the subsoil system via precipitation will likely 
travel around the biosolids row.  Conversely, if the soil has a lower conductivity value, 
water will choose the path of least resistance and percolate through the biosolids row.  It 
is also important to note that within the biosolids row the hydraulic conductivity value 
will change over time as biosolids dewater and decompose.  Based on observations of 
decomposed biosolids at the tree farm as well as the actual water flow in and around old 
biosolids rows, the conductivity increases as the biosolids age and the old rows serve as 
conduits. 
 
 102
To better quantify these visual observations, the hydraulic conductivity data were 
evaluated and subjected to statistical analyses to determine if:  1) significant differences 
(? = 0.05) occurred between the three blocks at the experimental site and 2) significant 
differences (? = 0.05) existed at different depths in the soil profile.  Although soil cores 
were collected at three different depths within each subplot, because those depths varied 
with biosolids application rate and variances in the topography of the site, the range of 
depths over which soil cores were collected were separated into four different levels.  
This allowed for a more consistent comparison across the experimental area based on the 
standard datum of depth from the surface.  The four depth levels consisted of:  30-60cm; 
61-94cm; 95-129cm; and 130-168cm.  The shallower depths were typically associated 
with the lowest and middle application rates; the highest depths were almost exclusively 
associated with the highest application rate.  The middle depths included samples 
associated with all application rates. 
The two factors under consideration were block (i.e., areas of the experimental plot 
with differing topographic features and soil composition) and depth.  This constitutes a 
factorial treatment design with three levels of the block factor and four levels of the depth 
factor.  PROC Mixed was used to perform a factorial analysis of variance.  Results 
showed statistically significant differences (? = 0.05) between blocks (Pr<0.0001), but 
not between depths or block*depth interactions.  Least Squares Means evaluation showed 
all three blocks to be significantly different from one another (Pr <0.0031 for Blocks 1 
and 2; Pr<0.0001 for Blocks 1 and 3; Pr<0.0038 for Blocks 2 and 3).  These results are 
reflected in plots of the data as shown in Figures 60-62. 
 
 
 
 103
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 60.  Hydraulic conductivity by depth (no significant differences between depths). 
 
 
As can be seen from Figure 60, as depth increases, hydraulic conductivity neither 
increases nor decreases in a consistent trend.  Higher and lower values exist at both 
shallow and deep locations within the soil profile.  What this demonstrates is the varying 
nature of the soil composition within the evaluated profile depth.  The subsurface 
stratigraphy of this region indicates that underneath the gravel and sand formations 
(Upland Deposits and Calvert Formation) there exist the silty clays and clayey sands of 
the Nanjemoy Formation followed by a confining unit of clays known as the Marlboro 
Clay (see Chapter 4, Site Location and Characteristics; Wilson and Fleck, 1990).  It was 
originally reasoned that the mining operations would have removed most of the gravel 
and sand formations, leaving the silty clays and clays exposed at the experimental site, 
0
20
40
60
80
100
120
140
160
180
1.00E-07 1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00
Hydraulic Conductivity (cm/sec) 
Logarithmic Scale
De
pth
 fr
om
 Su
rfa
ce 
(cm
)
 
 104
such that with increasing depth, a higher proportion of clays would be encountered in the 
soil profile. 
Mining operations, however, will only remove what is economically feasible, and it 
is obvious from the visual inspection and soil core analyses that pockets of sand and 
gravel remain at the mined site, particularly in the north end of the experimental site 
(Block 1).  The range of depths examined in this experiment encompassed the upper four 
meters of the soil profile (i.e., was limited to the soil profile in proximity to the biosolids 
rows).  The relatively shallow profile considered likely did not cross over different 
geographic formations within each subplot considered.  Furthermore, with all of the soil 
disturbance inherent to the mining operations, and the fact that this experimental site had 
previously been subjected to a round of biosolids application, significant alteration of the 
profile had already occurred.  Were there originally a trend of increasing clay content 
with depth reflecting different stratigraphic regions in the upper 4m of the profile, they 
may have been mixed enough to render them indistinguishable. 
Figures 61 and 62 show hydraulic conductivity by block.  Figure 61 emphasizes the 
marked differences between blocks, the most notable difference belonging to Block1, 
with the highest overall values.  Block 1 is located on the north end of the experimental 
plot, is approximately 10-15 feet lower in elevation than Block 3, and is characterized by 
high sand and gravel content.  Figure 62 shows the same data, but with a log transformed 
scale to make the lower end of the scale more visible. 
 
 
 
 
 
 
 
 105
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 61.  Hydraulic conductivity by block. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 62.  Hydraulic conductivity by block (logarithmic scale). 
0
10
20
30
40
50
60
70
0.00E+00 2.00E-03 4.00E-03 6.00E-03 8.00E-03 1.00E-02 1.20E-02 1.40E-02 1.60E-02 1.80E-02 2.00E-02
Hydraulic Conductivity (cm/sec)
De
pth
 fr
om
 Su
rfa
ce 
(cm
)
Block 1
Block 2
Block 3
0
10
20
30
40
50
60
70
1.00E-07 1.00E-06 1.00E-05 1.00E-04 1.00E-03 1.00E-02 1.00E-01 1.00E+00
Hydraulic Conductivity 
Logarithmic Scale (cm/sec) 
De
pth
 fr
om
 Su
rfa
ce 
(cm
)  
Block 1
Block 2
Block 3
 
 106
Though not a specific goal during the design of the experiment, the vast range of soil 
conditions encountered has expanded the scope to examine nutrient fate and transport in a 
much wider variety of soil types.  Consequently, results will provide valuable information 
about whether or not this reclamation technique is environmentally feasible not only in 
high clay content soils, but in sandier soils as well. 
To put the hydraulic conductivity measurements in perspective with the experimental 
layout, the average hydraulic conductivity was computed for each subplot, and the 
subplots were color coded to reflect ranges in values, as shown in Figure 63.  Individual 
hydraulic conductivity results are provided in Appendix 2. 
 
 107
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 63.  Experimental plot color-coded with average hydraulic conductivity 
categories. 
 
 
 
3A 3D 3G
3B 3E 3H 4A
3C 3F 3I Control
2A 2D 2G
2B 2E 2H 4B
2C 2F 2I Control 
1A 1D 1G
1B 1E 1H 4C
1C 1F 1I Control 
BLOCK 3
BLOCK 2
BLOCK 1
21.3m 
(70')
10.7m 
(35')
 32m 
(105')
21.3m 
(70')
21.3m 
(70')
10.7m 
(35')
10.7m 
(35')
 32m 
(105')
 32m 
(105')
22m (72') 22m (72') 22m (72')
10-5 cm/sec
10-6 cm/sec
716 trees/ha
1074 trees/ha
10-4 cm/sec
10-3 cm/sec
10-2 cm/sec
Legend
 
 108
Hydraulic conductivity values provide insight into the amount of time it would take 
for water leaching from the biosolids to reach sampling equipment.  Using the results 
from the deep soil core from each subplot, which represent the soil conditions under the 
biosolids row in the vicinity of the pan and suction lysimeters, it is possible to estimate 
leachate travel time.  Transmission of water through porous media is described using 
Darcy?s Law: 
q = -K dH/dx        (3) 
where, 
q = volume flux density of water, i.e., the volume of water V passing through a unit 
cross sectional area A, that is perpendicular to the flow direction (L/T), 
dH/dx = hydraulic head gradient (L/L), and 
K = hydraulic conductivity, i.e., the ability of the conducting medium to transmit the 
liquid (L/T). 
 
Hydraulic conductivity is directly proportional to flux and is dependent upon pore 
size, tortuosity, and fluid properties including viscosity and density.  It can be used to 
estimate the rate of soil water flow if 1) seepage through the soil is assumed to be due to 
gravimetric forces alone and 2) saturated flow conditions are represented (Hillel, 1998).  
It also assumes that no preferential flow exists.  Using the measured hydraulic 
conductivities and the 30 cm distance between the bottom of the biosolids row and the 
pan lysimeter (as well as the mid-depth vertically positioned suction lysimeter), leachate 
travel times were determined for each subplot and are presented in Table 13 (in subplot 
ID and travel time order) and Figure 64 (in travel time order). 
 
 109
The assumptions inherent to this analysis are not unreasonable for the study period 
under consideration.  Past studies on biosolids trenching and deep row application show 
that biosolids rows actively dewater, especially during the first two years after application 
(Sikora, et al., 1982).  Therefore, the soil directly underneath the trenches would likely 
become saturated.  Whether or not the soil remains continuously saturated, though, would 
be dependent upon the rate of leaching from the biosolids versus the rate of travel 
through the soil.  Although matric forces will be present in concert with gravimetric 
forces, given the documented observations of downward dewatering occurring in 
biosolids trenching studies, gravimetric forces likely dominate, at least initially.  It is 
important to note that these assumptions will become less valid over time as the most 
intense biosolids dewatering subsides, and as tree roots infiltrate the area around the 
biosolids rows and actively divert gravimetric flow.  The estimates presented could be 
skewed if preferential flow paths existed when the soil samples were collected (which 
would impact the hydraulic conductivity values).  For example, the fissures created when 
the clay-dominated soil dried would serve as conduits for rainfall infiltration until the 
clay swelled from moisture absorption. 
Conversely, the estimates may not represent future travel times, given that the 
hydraulic conductivy values used do not account for preferential flow paths that may 
develop over time.  As a result, these are crude approximations of travel time.  
Regardless, the hydraulic conductivity values provide a basis for comparing the 
differences in transport over the experimental site. 
 
 110
 
 
Table 13.  Biosolids leachate travel time calculated for each subplot. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
These results show a wide range in travel times, and slightly more overlap between 
blocks (i.e., Blocks 1, 2, and 3 as denoted by the first character in the subplot ID, with the 
exception of the controls, which have block designations after the ID) than was observed 
Subplot ID
Time required to 
travel 30 cm from 
bottom of 
biosolids row to 
lysimeter (hour)
Time 
(days)
1A 2.78 0.12
1B 888.63 37.03
1C 2.90 0.12
1D 0.47 0.02
1E 54.02 2.25
1F 110.82 4.62
1G 3.36 0.14
1H 27.33 1.14
1I 2.12 0.09
2A 113.33 4.72
2B 92.29 3.85
2C 3.80 0.16
2D 194.31 8.10
2E 9354.81 389.78
2F 159.89 6.66
2G 184.49 7.69
2H 178.59 7.44
2I 18.14 0.76
3A 653.59 27.23
3B 829.06 34.54
3C 89.72 3.74
3D 2708.36 112.85
3E 84.79 3.53
3F 1544.84 64.37
3G 50.66 2.11
3H 14.70 0.61
3I 55.61 2.32
4A (Block 3) 63.96 2.66
4B (Block 2) 64.60 2.69
4C (Block 1) 4.40 0.18
Sorted by Subplot ID
Subplot ID
Time required to 
travel 30 cm from 
bottom of 
biosolids row to 
lysimeter (hour)
Time 
(days)
1D 0.47 0.02
1I 2.12 0.09
1A 2.78 0.12
1C 2.90 0.12
1G 3.36 0.14
2C 3.80 0.16
4C (Block 1) 4.40 0.18
3H 14.70 0.61
2I 18.14 0.76
1H 27.33 1.14
3G 50.66 2.11
1E 54.02 2.25
3I 55.61 2.32
4A (Block 3) 63.96 2.66
4B (Block 2) 64.60 2.69
3E 84.79 3.53
3C 89.72 3.74
2B 92.29 3.85
1F 110.82 4.62
2A 113.33 4.72
2F 159.89 6.66
2H 178.59 7.44
2G 184.49 7.69
2D 194.31 8.10
3A 653.59 27.23
3B 829.06 34.54
1B 888.63 37.03
3F 1544.84 64.37
3D 2708.36 112.85
2E 9354.81 389.78
Sorted by Travel Time
 
 111
in computations of average hydraulic conductivity across all depths for each subplot.  
This reflects the fact that some of the hydraulic conductivity values from the deepest 
layer (as opposed to the average of values across all layers) were lower in Block 1 than 
Blocks 2 and 3.  The trend of notable differences between blocks, however, is still 
evident. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 64.  Leachate travel time from bottom of biosolids row to sampling equipment. 
 
 
As can be more readily seen from Figure 64 above, in 80% of the subplots, biosolids 
leachate will reach the collection equipment within 8 days.  The other 20%, however, will 
take a minimum of one month to travel 30 cm.  Longer travel times will result in more 
time for diffusion, interaction with soil particulates and microbes, and other processes 
occurring in the soil profile, which could result in compositional changes in the leachate.  
Short travel times, however, may allow for intervals in which some portions of the soil 
0.01
0.10
1.00
10.00
100.00
1000.00
1D 1I 1A 1C 1G 2C 4C 3H 2I 1H 3G 1E 3I 4A 4B 3E 3C 2B 1F 2A 2F 2H 2G 2D 3A 3B 1B 3F 3D 2E
Sample ID
Nu
mb
er 
of 
Da
ys 
(L
og
ar
ith
mi
c S
ca
le)
0.5 - 4 hours
0.6 - 8 days
0.91 - 3.8 months
13 
months
 
 112
are drained and left unsaturated, thereby altering the physical and chemical conditions in 
the soil. 
Rain Gauge Data 
Rain gauge data collection began in December 2002.  Data were downloaded 
approximately every two weeks from the data logger.  Routine physical inspection of the 
rain gauge showed it to be in good working condition over most of the course of data 
collection activities.  Between May 12?30, 2003 and June 20-23, 2003, malfunctions 
resulted in the loss of data from these time periods.  Values for these time periods were 
estimated using rain gauge data collected from three other sites in Maryland and applying 
the U.S. National Weather Service?s inverse square distance weighting method.  This 
technique uses the formula: 
           (4) 
Px = {(1/dax)2 * Pa + (1/dbx)2 * Pb + (1/dcx)2 *Pc +?}/{(1/dax)2 + (1/dbx)2 + (1/dcx)2?} 
where: 
Px = estimated precipitation at gauge x, 
Pa, b or c = known precipitation at gauge a, b, or c, and 
dax, bx, or cx = distance between rain gauge x and rain gauge a, b, or c. 
 
On another occasion in June 2003, bird droppings had plugged the hole at the bottom 
of the rainwater collection funnel and, upon release of the plug, the rain collected from 
the prior day?s storm was consequently recorded in the data logger as occurring over a 
much smaller time frame on the day after the actual storm event.  This did not adversely 
 
 113
impact use of the data.  Monthly totals are presented in Figure 65 and a side-by-side 
comparison of 2003 to 2004 rainfall is provided in Figure 66. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 65.  Monthly rainfall totals for December 2002-December 2004. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 66.  Comparison of rainfall in 2003 and 2004. 
0.0
5.0
10.0
15.0
20.0
25.0
De
c-0
2
Jan
-03
Feb
-03
Ma
r-0
3
Ap
r-0
3
Ma
y-0
3
Jun
-03
Jul
-03
Au
g-0
3
Sep
-03
Oc
t-0
3
No
v-0
3
De
c-0
3
Jan
-04
Feb
-04
Ma
r-0
4
Ap
r-0
4
Ma
y-0
4
Jun
-04
Jul
-04
Au
g-0
4
Sep
-04
Oc
t-0
4
No
v-0
4
De
c-0
4
Month
Ra
inf
all
 (c
m)
0.0
5.0
10.0
15.0
20.0
25.0
Jan
uar
y
Feb
rua
ry
Ma
rch April May June July
Aug
ust
Sep
tem
ber
Oct
obe
r
Nov
emb
er
Dec
emb
er
Month
Ra
inf
all
 (c
m)
2003:  Total = 141 cm
2004:  Total = 108 cm
 
 114
From these figures, it is evident that 2003 had more precipitation than 2004, with 
particularly high rainfall in May and June.  In 2003 this high rainfall delayed the planting 
of trees at the experimental site from early May until mid-June 2003.  In both years, May 
through September were marked by greater precipitation than other months.  Dependent 
upon surface and soil conditions as well as the intensity and duration of precipitation, 
rainfall can impart an intense, immediate influence on subsurface flow or, conversely, a 
more diffuse, delayed effect. 
In those soils with higher hydraulic conductivity values (>10-4 cm/sec) the travel 
time for infiltrating rainfall to reach sampling equipment can be rapid.  The rate at which 
rainfall would flow directly through the biosolids row, however, would be much slower 
given that the measured hydraulic conductivity for the biosolids at time of application 
was 2.55x10-6 cm/sec.  In such cases rainfall will take the path of least resistance and 
flow around the edges of the trench to then proceed underneath the row and into the 
sampling equipment.  For those soils with hydraulic conductivity comparable to the 
biosolids, flow may be more evenly distributed amongst biosolids and surrounding soil. 
As biosolids rows drain and loose moisture content, they will have the capacity to 
absorb more of the infiltrating rainfall.  In fact, the resulting gravimetric and matric 
potential combined with chemical forces from the high organic content facilitates water 
infiltration into the biosolids rows (Sikora and Colacicco, 1980).  Trenching studies 
conducted in the 1970s showed that gravimetric flow prevailed, and biosolids rows 
dewater from the top down.  In fact, 19 months after biosolids placement in a row 
surrounded by sandy soil, the top 20% of a row of raw, limed sludge had weathered to a 
peat like consistency (Walker, 1974).  Another trenching study conducted between 1977-
 
 115
1980 (Sikora, et al., 1982) in well-drained silt loam soils similarly found the largest 
amount of biosolids dewatering to occur in the first 20 months, but overall, the amount of 
dewatering that occurred was less than that observed in sandy soils due to the slower 
percolation through silty soils.  Regardless, the biosolids pack dewatered from the top 
down. 
These varying soil conditions will impact the transport of rainfall and, by 
association, those compounds soluble in water that will accompany the flow of water 
through the soil profile.  The effects will likely be most immediate and pronounced in the 
sandier soils with high hydraulic conductivities.  In such cases rainfall may flush soil 
water and accompanying solutes through the soil.  Flushing could also result in the 
mixing of rainfall with the existing soil water to dilute solute concentrations. 
To better evaluate the time for rainfall to percolate through the soil profile to the 
depth of the sampling equipment, hydraulic conductivity values were used to estimate 
travel time using the same technique as that previously presented in the hydraulic 
conductivity results section.  In this instance, however, the entire soil profile was 
considered, as opposed to just the 30 cm layer between the biosolids row bottom and the 
equipment.  The deep core sample provided an estimate of hydraulic conductivity for the 
30 cm directly above the pan lysimeter; the middle core sample provided an estimate for 
the 30 cm above the deep layer, and the shallow core provided an estimate for the 
remaining upper profile (i.e., to the surface).  The upper profile layer varied in length 
dependent upon the biosolids application rate and changes in elevation. 
For a given subplot, the hydraulic conductivity value for each layer was divided by 
the respective depth of that layer to determine the travel time through the layer.  These 
 
 116
three time lengths were then summed to determine the total time for rainfall to travel 
from the surface to the sampling equipment (Schwab, et al., 1993).  Results are shown in 
Table 14 and Figure 67. 
Table 14.  Rainfall travel time through soil profile to sampling equipment depth. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Subplot 
ID
Rainfall travel 
time from surface 
to sampling 
equipment (hour) Time (days)
1A 12.08 0.50
1B 1010.27 42.09
1C 37.86 1.58
1D 1.88 0.08
1E 92.85 3.87
1F 216.72 9.03
1G 113.26 4.72
1H 157.05 6.54
1I 270.16 11.26
2A 189.39 7.89
2B 145.94 6.08
2C 908.24 37.84
2D 827.37 34.47
2E 9925.39 413.56
2F 350.76 14.62
2G 691.63 28.82
2H 1272.95 53.04
2I 138.52 5.77
3A 92499.96 3854.17
3B 3316.25 138.18
3C 445.80 18.58
3D 26594.83 1108.12
3E 20356.17 848.17
3F 4037.95 168.25
3G 8049.82 335.41
3H 681.66 28.40
3I 393.53 16.40
4A 971.75 40.49
4B 149.98 6.25
4C 15188.68 632.86
Sorted by Subplot ID
Subplot 
ID
Rainfall travel 
time from surface 
to sampling 
equipment (hour) Time (days)
Time 
(months)
1D 1.88 0.08
1A 12.08 0.50
1C 37.86 1.58
1E 92.85 3.87
1G 113.26 4.72
2I 138.52 5.77
2B 145.94 6.08
4B 149.98 6.25
1H 157.05 6.54
2A 189.39 7.89
1F 216.72 9.03
1I 270.16 11.26
2F 350.76 14.62 0.49
3I 393.53 16.40 0.55
3C 445.80 18.58 0.62
3H 681.66 28.40 0.95
2G 691.63 28.82 0.96
2D 827.37 34.47 1.15
2C 908.24 37.84 1.26
4A 971.75 40.49 1.35
1B 1010.27 42.09 1.40
2H 1272.95 53.04 1.77
3B 3316.25 138.18 4.61
3F 4037.95 168.25 5.61
3G 8049.82 335.41 11.18
2E 9925.39 413.56 13.79
4C 15188.68 632.86 21.10
3E 20356.17 848.17 28.27
3D 26594.83 1108.12 36.94
3A 92499.96 3854.17 128.47
Sorted by Travel Time
 
 117
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 67.  Number of days for rainfall to reach sampling equipment. 
 
 
Results encompass a broad range of time, reflecting the differing soil properties over 
the experimental site.  It is more likely that those subplots with travel times less than two 
weeks will be susceptible to a flushing effect from the rainfall.  Those soil properties that 
inhibit rainfall flow and produce longer travel times will dissipate the flushing potential 
of the rainfall.  Subplot order in Figure 67 is similar to the biosolids leachate travel time 
previously presented in Figure 64, but in some instances subplot order has changed.  Such 
changes reflect the more marked effect of certain hydraulic conductivity levels from the 
middle and shallow depth levels.  In addition, some of the shallow depth level hydraulic 
conductivity values had greater influence on the travel time due to the greater length 
0.01
0.10
1.00
10.00
100.00
1000.00
10000.00
1D 1A 1C 1E 1G 2I 2B 4B 1H 2A 1F 1I 2F 3I 3C 3H 2G 2D 2C 4A 1B 2H 3B 3F 3G 2E 4C 3E 3D 3A
Subplot ID
Nu
mb
er 
of 
Da
ys 
(L
og
ar
ith
mi
c S
ca
le)
.   
 
< 2 weeks
0.5 - 2 
months
0.9 - 3 years
10 years
4.5 - 6 
months
 
 118
associated with that layer (i.e., greater than the 30 cm lengths associated with the middle 
and deep layers).  These travel estimates will be used in subsequent sections to evaluate 
whether or not analytical results indicate that a flushing effect may have occurred. 
 
 119
Soil Water Analysis and Results:  Overview 
Pan lysimeter soil water sample collection began in April 2003, upon completion of 
biosolids application to the experimental plot.  Suction lysimeters were installed in July 
and August 2003 and sample collection began in November 2003.  Results presented 
encompass sample collection activities through December 2004.  Table 15 documents the 
dates of collection and number of samples collected. 
Table 15.  Summary of pan and suction lysimeter sampling activities. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Sampling 
Date
Number of 
samples 
collected 
(n)
Sampling 
Date
Number of 
samples 
collected 
(n)
4/23/2003 10 1/7/2004 10
5/7/2003 8 1/13/2004 8
5/28/2003 9 1/31/2004 4
6/4/2003 8 2/10/2004 8
6/17/2003 9 2/17/2004 9
6/23/2003 9 2/25/2004 7
7/8/2003 11 3/8/2004 9
7/16/2003 9 3/19/2004 8
7/23/2003 10 3/26/2004 7
8/6/2003 8 4/9/2004 10
8/13/2003 11 4/23/2004 9
8/20/2003 11 4/30/2004 6
9/3/2003 8 5/13/2004 9
9/10/2003 10 5/21/2004 9
9/22/2003 11 5/27/2004 10
10/14/2003 10 6/16/2004 10
10/20/2003 11 6/23/2004 11
10/29/2003 10 6/29/2004 12
11/9/2003 9 8/17/2004 11
11/16/2003 8 8/23/2004 11
11/24/2003 11 8/30/2004 11
12/3/2003 10 10/15/2004 10
12/10/2003 9 10/22/2004 11
12/18/2003 9 10/29/2004 11
12/3/2004 11
12/12/2004 5
12/21/2004 11
2003 2004
Pan Lysimeter Samples
Sampling 
Date
Number of 
samples 
collected 
(n)
Sampling 
Date
Number of 
samples 
collected 
(n)
1/6/2004 45
1/12/2004 42
1/30/2004 31
2/11/2004 47
2/18/2004 46
2/26/2004 45
3/10/2004 46
3/19/2004 47
3/26/2004 45
4/9/2004 45
4/23/2004 45
4/30/2004 43
5/14/2004 48
5/21/2004 44
5/27/2004 45
6/16/2004 50
6/23/2004 47
6/30/2004 47
11/10/2003 43 8/18/2004 50
11/18/2003 44 8/25/2004 49
11/23/2003 44 8/31/2004 44
11/30/2003 46 10/16/2004 49
12/8/2003 44 10/23/2004 47
12/21/2003 47 10/30/2004 44
12/4/2004 49
12/13/2004 47
12/22/2004 44
Suction Lysimeter Samples
2003 2004
 
 120
Provided every pan produced a sample, each sampling date should have produced 
11-12 samples (10 pans plus one or two equipment blanks).  Similarly, for suction 
lysimeters, each collection date should have produced 51 samples (50 suction lysimeters 
plus one equipment blank).  As shown in Table 15 above, however, not all sampling 
events produced these numbers.  Recall that pan lysimeters capture saturated flow.  
Consequently, once gravimetric flow ceases, or other potentials and preferential flow 
paths in the soil override the gravimetric potential, flow to the pan lysimeters will be 
reduced.  For suction lysimeters, which capture both saturated and unsaturated flow, the 
matric forces in the subsurface around the equipment will determine whether or not the 
suction placed on the lysimeter will be strong enough to pull soil water into the 
equipment.  Therefore, if the soil is extremely dry, it will be difficult to capture any 
sample.  In addition, equipment malfunctions (e.g., plugs in the sampling lines from 
particulates or frozen sample) also prevented collection on several occasions. 
Samples varied in appearance (e.g., color, clarity, types of particulates) and 
properties, with pH ranging from 5.03-8.20 for pan lysimeters and 4.82 ? 11.33 for 
suction lysimeters.  Figure 68 below shows the average pH in relation to each equipment 
type and position for subplots with biosolids and without biosolids (i.e., controls).  For 
subplots with biosolids, notable trends shown in this graphic include:  1) for vertical flow 
suction lysimeters, pH decreased with increasing distance from the biosolids row; 2) 
vertical flow suction lysimeters produced values greater than lateral flow suction 
lysimeters; 3) the pan lysimeters (all of which were positioned at the same 30 cm depth 
below the biosolids row) produced samples with lower pH values than any of the 
vertically placed suction lysimeter samples.  In addition, with the exception of the lateral 
 
 121
flow suction lysimeter placed 30cm from the biosolids row (i.e., SL-PL-30cm), all 
control values were less than those subplots with biosolids. 
These trends reflect a number of influences to which the soil water is subject, 
including travel time and soil interaction.  Equipment closest to the biosolids row will 
likely contain the most unaltered leachate from the biosolids because the shorter flow 
path means it has contact with less soil as well as less time in contact with this soil.  
Given the high pH level of the biosolids, those samples closest to the flow path from the 
biosolids will likely have higher pH values.  For this reason as well, it is not surprising 
that the vertical flow suction lysimeters would have higher pH values than the lateral 
flow samples, because the lateral flow samples are not directly underneath the biosolids 
rows, but rather to the side of the rows.  This suggests that lateral flow is not a major 
factor in transport from the biosolids pack. 
This trend in vertical flow vs. lateral flow of suction lysimeters, as well as the 
difference between the suction lysimeters and the pan lysimeters, also reflects the manner 
in which equipment was installed.  Pan lysimeter installation was performed underneath 
the biosolids row, and did not directly disturb the biosolids.  Lateral flow suction 
lysimeters required drilling to either side of the biosolids row, and also did not disturb the 
biosolids rows.  For the those suction lysimeters designed to capture vertical flow, 
however, installation required drilling directly through and underneath the biosolids row 
to appropriately position the suction lysimeter.  Although bentonite plugs around the 
suction lysimeter prevent a preferential flow path from forming along the wall of the 
lysimeter, the initial drilling process was often accompanied by some leachate flow into 
the lysimeter hole.  This, and the disturbance of the biosolids itself, likely contributed to 
 
 122
the higher pH values in the suction lysimeter samples.  Finally, the lower pH values 
associated with the controls are consistent with the fact that the controls do not contain a 
recent application of high-pH biosolids. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 68.  Average pH values for suction lysimeter (SL) and pan lysimeter samples. 
 
 
The 2-bar ceramic cup of the suction lysimeter had a pore size of 1um.  As a result, 
suction lysimeter samples were subjected to an initial filtration during the collection 
process.  Pan samples, however, were not initially filtered and remained that way in the 
pan between collection dates.  As would be expected, pan samples contained more 
particulates than the suction lysimeters.  In general, pan samples tended to become 
clearer after several months of collection (though most still contained particulates).  Both 
4.00
4.50
5.00
5.50
6.00
6.50
7.00
7.50
8.00
8.50
SL-PV-15cm SL-PV-30cm SL-PV-60cm SL-PL-15cm SL-PL-30cm Pan-PV-30cm
Sampling Equipment ID:  SL = suction lysimeter 
PV=vertical placement below biosolids row; PL=lateral placement from edge of biosolids row
Av
era
ge
 pH
All non-zero application rates
Controls
 
 123
pan and suction lysimeter samples from many of the subplots contained small rust-
colored flakes that are speculated to be an iron precipitate.  Within 30 minutes of 
collection, the precipitate became more prevalent, and precipitate settled to the bottom of 
the collection container.  Figures 69-72 and 74-77 show samples from multiple subplots, 
demonstrating the varied appearance.  Figures 73 and 78 show the residue captured by 
the filter paper for a set of pan and suction lysimeter samples. 
 
 
 124
 
Figure 69.  Pan lysimeter samples from 
block 1. 
Figure 70.  Pan lysimeter samples from 
block 2. 
 
 
 
 
Figure 71.  Pan lysimeter samples from 
block 3. 
Figure 72.  Pan lysimeter samples from 
control and equipment blank. 
 
 
 
 
 
 
 
 
 
 
 
 
 125
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 73.  Residue from filtration of pan lysimeter samples. 
 
 
Block 1 
Block 2 
Block 3 
Control Equipment Blanks 
 
 126
 
 
Figure 74.  Suction lysimeter samples from a 
block 1 subplot. 
Figure 75.  Suction lysimeter samples 
from a block 2 subplot. 
 
 
 
 
 
Figure 76.  Suction lysimeter samples from a 
block 3 subplot. 
Figure 77.  Suction lysimeter samples 
from a control subplot. 
 
 
 
 
 
 
 
 
 
 
 
 127
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 78.  Residue from filtration of SL samples. 
 
 
Block 1 
Block 2 
Block 3 
Control 
 
 128
 
Soil Water Results:  Total Nitrogen and Ammonium (NH4+-N) Data 
Biosolids applied to the experimental plot contained on average 41,200 mg/kg total 
nitrogen and 2,700 mg/kg of ammonium nitrogen.  The cation ammonium represents the 
inorganic portion of total nitrogen.  By simple calculation, inorganic nitrogen constitutes 
7% of the total nitrogen.  Consequently, a majority of the nitrogen applied (93%) was in 
the form of organic nitrogen.  Unless this organic nitrogen exists in dissolved form, 
movement into the soil profile will be limited. 
Ammonification is the first step in the decomposition of organic nitrogen, and is 
performed by a variety of heterotrophic organisms in both aerobic and anaerobic 
environments.  The product, ammonium, is soluble in water and easily infiltrates the soil 
profile, though movement is often limited by the cation?s attraction to negatively charged 
particles in the soil (Haynes, 1986).  As stated above, ammonium was already present in 
the applied biosolids in notable quantities.  Therefore, notwithstanding ammonium 
production from organic nitrogen that could have occurred over time, an ample supply 
existed at the start of the experiment. 
Soil water samples were analyzed for both total nitrogen and ammonium nitrogen.  
For the pan lysimeters, 427 samples were analyzed.  When these individual subplot 
values were averaged within each quarter, the 427 results were consolidated to 222 
average values.  For the suction lysimeters, 1450 samples were analyzed.  When these 
individual lysimeter results were averaged within each quarter, the 1450 results were 
consolidated to 562 average values.  Unless otherwise stated, the data presented and 
discussed below represent the quarterly averages of the individual monthly values. 
 
 129
Results show that a majority of the total nitrogen measured in the samples was in the 
form of ammonium.  In theory, ammonium values should be less than or equal to total 
nitrogen values.  Field and analytical variability, however, is a standard component of 
any experiment and must be considered in the interpretation of results.  Therefore, 
ammonium values less than or equal to 120% of total nitrogen values were considered 
within the range of acceptable analytic variability.  All ammonium values that were 
greater than total nitrogen values for the same sample were reanalyzed multiple times at 
the laboratory to provide the most representative results possible.  The high total nitrogen 
and ammonium concentrations in some of these samples, as well as other components of 
the sample matrix, were likely responsible for the analytical variability.  Despite these 
analytical challenges, only an extremely small portion of the samples (4 from the pan 
lysimeters) exhibited ammonium values greater than 120% of total nitrogen values. 
The information in Table 16 indicates that 88% of the pan results and 78% of the 
suction lysimeter results contain ammonium concentrations equivalent to total nitrogen 
(i.e., those NH4+ values within 80-120% of total N).  Pan lysimeters generated more 
results within this range and a smaller percentage of samples below this range compared 
to the suction lysimeters.  Due to the similarity in values and patterns between total N and 
ammonium, it would be redundant to present both sets of results.  Consequently, 
ammonium results are presented in this section, and total nitrogen results are provided in 
Appendix 2 for reference.  Ammonium results are the primary focus of this discussion, 
with some supplemental discussion of total nitrogen where appropriate.  Pan lysimeter 
results will be presented first, followed by suction lysimeter results. 
 
 130
 
Table 16.  Overall comparison of total nitrogen and ammonium values. 
Pan Lysimeter Samples Suction Lysimeter Samples 
22 of 222 NH4+ values = 10% were  
< 80% of the total N values. 
122 of 562 NH4+ values = 22% were  
< 80% of the total N values. 
196 of 222 NH4+ values = 88% were  
> 80% and < 120% of total N values 
440 of 562 NH4+ values = 78% were  
> 80% and < 120% of total N values 
4 of 222 NH4+ values = 2% were  
> 120% of total N values. 
0 of 562 NH4+ values = 0% were  
> 120% of total N values. 
 
 
Pan Lysimeter Samples 
Total N and ammonium results showed appreciable concentrations across application 
rates, with controls exhibiting the lowest values.  A summary of the concentration ranges 
is presented in Table 17. 
Table 17.  Frequency of pan lysimeter results in successive concentration ranges. 
 Total N NH4+ 
Values < 10 mg/L 34 of 222 = 15% 33 of 222 = 15% 
Values from 10-20 mg/L 15 of 222 =   7% 18 of 222 =   8% 
Values from 20-50 mg/L 25 of 222 = 11% 25 of 222 = 11% 
Values from 50-100 mg/L 33 of 222 = 15% 30 of 222 = 13% 
Values from 100-500 mg/L 81 of 222 = 36% 80 of 222 = 36% 
Values from 500-1000 mg/L 15 of 222 =   7% 17 of 222 =   8% 
Values > 1000 mg/L 19 of 222 =   9% 19 of 222 =   9% 
 
 
Though 34% of results were less than 50 mg/L, within the general range of the 
control results, an equally high percentage of results had more significant values between 
100-500 mg/L.  Distribution of values was essentially the same between total nitrogen 
and ammonium.  Ammonium results are presented by each application rate in Figures 79-
81 below.  Total nitrogen results are included in Appendix 2.  Due to the wide range in 
concentrations, results are presented in a logarithmic scale. 
 
 
 
 
 131
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 79.  Ammonium quarterly average concentrations for low-level application rate in 
pan lysimeters. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 80.  Ammonium quarterly average concentrations for mid-level application rate in 
pan lysimeters. 
1
10
100
1000
10000
Q1-
B1
Q1-
B2
Q1-
B3
Q2-
B1
Q2-
B2
Q2-
B3
Q3-
B1
Q3-
B2
Q3-
B3
Q4-
B1
Q4-
B2
Q4-
B3
Q5-
B1
Q5-
B2
Q5-
B3
Q6-
B1
Q6-
B2
Q6-
B3
Q7-
B1
Q7-
B2
Q7-
B3
Q8-
B1
Q8-
B2
Q8-
B3
Quarter-Block ID
NH
4+
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
0 kgN/ha; 0 trees/ha 19,650 kgN/ha; 0 trees/ha
19,650 kgN/ha; 716 trees/ha 19,650 kgN/ha; 1074 trees/ha
Apr-May-03 Jun-Aug-03 Sept-Nov-03 Dec-03, 
Jan/Feb-04
Mar-May-04 Jun/Aug 
04
Oct-04 Dec-04
1
10
100
1000
10000
Q1-
B1
Q1-
B2
Q1-
B3
Q2-
B1
Q2-
B2
Q2-
B3
Q3-
B1
Q3-
B2
Q3-
B3
Q4-
B1
Q4-
B2
Q4-
B3
Q5-
B1
Q5-
B2
Q5-
B3
Q6-
B1
Q6-
B2
Q6-
B3
Q7-
B1
Q7-
B2
Q7-
B3
Q8-
B1
Q8-
B2
Q8-
B3
Quarter-Block ID
NH
4+
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
0 kgN/ha; 0 trees/ha 39,300 kgN/ha; 0 trees/ha
39,300 kgN/ha; 716 trees/ha 39,300 kgN/ha; 1074 trees/ha
Apr-May-03 Jun-Aug-03 Sept-Nov-03 Dec-03, 
Jan/Feb-04
Mar-May-04 Jun/Aug 
04
Oct-04 Dec-04
 
 132
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 81.  Ammonium quarterly average concentrations for high-level application rate in 
pan lysimeters. 
 
 
Results from the controls (0 kgN/ha; 0 trees/ha) ranged between 3.2 ? 43 mg/L for 
total N and 1.1 ? 44 mg/L for ammonium; approximately 60% of these values were 
greater than 10 mg/L.  Prior testing of untreated soil at the tree farm showed total 
nitrogen values of 100 mg/kg and ammonium values of 1.2 mg/kg (Pepperman, 1995).  
These values, which represent the amount in one kilogram of soil, can be used to estimate 
the amount in the aqueous portion of the soil based on several soil property assumptions. 
Assuming an average bulk density for subsoil samples ranging between 1.6-1.9 
g/cm3, each kg (1000g) of soil would provide:  1000g/(1.6g/cm3) = 625 cm3 to 
1000g/(1.9g/ cm3) = 526 cm3 of soil volume.  Given this range in soil volume of 526-625 
cm3, and assuming a volumetric water content between 25-50%, we can estimate the 
0.1
1
10
100
1000
10000
Q1-
B1
Q1-
B2
Q1-
B3
Q2-
B1
Q2-
B2
Q2-
B3
Q3-
B1
Q3-
B2
Q3-
B3
Q4-
B1
Q4-
B2
Q4-
B3
Q5-
B1
Q5-
B2
Q5-
B3
Q6-
B1
Q6-
B2
Q6-
B3
Q7-
B1
Q7-
B2
Q7-
B3
Q8-
B1
Q8-
B2
Q8-
B3
Quarter-Block ID
NH
4+
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
0 kgN/ha; 0 trees/ha 58,900 kgN/ha; 0 trees/ha
58,900 kgN/ha; 716 trees/ha 58,900 kgN/ha; 1074 trees/ha
Apr-May-03 Jun-Aug-03 Sept-Nov-03 Dec-03, 
Jan/Feb-04
Mar-May-04 Jun/Aug 
04
Oct-04 Dec-04
 
 133
volume of water present in this given volume of soil.  For these volumetric water 
contents:  (0.25 cm3 water/ 1 cm3 soil) * 526 cm3 soil = 131 cm3 water = 131 mL water. 
Similarly, 625 cm3 of soil would generate 156 mL water; 0.50 cm3 water/ 1 cm3 soil and 
526 cm3 soil would generate 263 mL water; and 0.50 cm3 water/ 1 cm3 soil and 625 cm3 
soil would generate 312 mL water. 
Not all of the total nitrogen will be soluble in water.  Based on information regarding 
the soluble nitrogen content in plant matter (Haynes, 1986), it is reasonable to assume 
that no more than 10% will be in solution.  The 100 mg/kg of total nitrogen measured in 
the soil sample therefore provides a maximum of 10 mg of nitrate in 131-312 mL of soil 
water, or a range of 32-76 mg/L.  This range in value of 32 - 76 mg/L for background 
levels of total nitrogen is comparable to the values seen in the samples collected during 
this experiment. 
Assuming most of the measured ammonium in the soil sample will be in solution, the 
1.2 mg/kg of ammonium measured in the soil sample is equal to 1.2 mg of ammonium in 
131-312 mL of soil water.  This range of 4-9 mg/L represents the lower levels of 
ammonium found in the control samples.  The higher values found in the controls could 
be a result of residual ammonium from prior biosolids applications or decomposition of 
vegetation with subsequent percolation through the subsurface. 
Using the 1-45 mg/L control results as background levels, sample values greater than 
100 mg/L will be more closely examined.  Figure 82 provides a breakdown of the number 
of samples from each application rate with values greater than 100 mg/L. 
 
 
 134
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 82.  Number of ammonium samples > 100 mg/L by application rate and tree 
density. 
 
Comparing application rates, 19,650 kg N/ha and 39,300 kg N/ha produced the same 
number of results with values greater than 100 mg/L (i.e., 47 results), whereas 58,900 kg 
N/ha produced a markedly lower number of these higher values (22 results).  A 
breakdown of these total numbers by the three tree densities shows that 0 trees/ha 
contained the most numerous greater than 100 mg/L results for all three application rates.  
The differences between 716 and 1074 trees/ha were less consistent across application 
rates.  Not shown in this figure but also worth noting is the fact that although the 0 
trees/ha density exhibited the greater number of values above 100 mg/L, this tree density 
was not always associated with the highest ammonium concentrations.  From Figures 79-
81, it is evident that for19,650 kg N/ha application rate, the 716 trees/ha density had 
0
5
10
15
20
25
30
35
40
45
50
19,650 kg N/ha 39,300 kg N/ha 58,900 kg N/ha
Application Rate
Nu
mb
er 
of 
sam
ple
s w
ith
 N
H4+
 >1
00
 m
g/L
All tree densities
0 trees/ha
716 trees/ha
1074 trees/ha
43%
50%
38%
38%
30%32%
19% 36%
14%
 
 135
much higher values than either the 0 trees/ha or 1074 trees/ha densities.  For both 39,300 
kg N/ha and 58,900 kg N/ha, both 0 trees/ha and 1074 trees/ha shared the highest values, 
all of which shows that the highest concentrations were spread across all tree densities. 
An overview of variability within each quarter is presented in Figures 83-85, in 
which the results for the three blocks within a particular treatment were averaged and 
standard deviation determined.  Visual inspection shows no definitive trend in standard 
deviation over time. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 83.  Ammonium average concentrations across blocks with standard deviation for 
low-level application rate in pan lysimeters. 
 
 
 
 
 
 
 
 
1
10
100
1000
10000
0 1 2 3 4 5 6 7 8 9
Quarter
NH
4+
 (m
g/L
)  
qu
ar
ter
ly 
av
era
ge
 of
 bl
oc
ks
 1-
3 
wi
th 
sta
nd
ar
d d
ev
iat
ion
{lo
ga
rit
hm
ic 
sca
le}
0 kgN/ha; 0 trees/ha 19,650 kgN/ha; 0 trees/ha
19,650 kgN/ha; 716 trees/ha 19,650 kgN/ha; 1074 trees/ha
 
 136
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 84.  Ammonium average concentrations across blocks with standard deviation for 
mid-level application rate in pan lysimeters. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 85.  Ammonium average concentrations across blocks with standard deviation for 
high-level application rate in pan lysimeters. 
1
10
100
1000
10000
0 1 2 3 4 5 6 7 8 9
Quarter
NH
4+
 (m
g/L
)  
qu
ar
ter
ly 
av
era
ge
 of
 bl
oc
ks
 1-
3 
wi
th 
sta
nd
ar
d d
ev
iat
ion
{lo
ga
rit
hm
ic 
sca
le}
0 kgN/ha; 0 trees/ha 58,900 kgN/ha; 0 trees/ha
58,900 kgN/ha; 716 trees/ha 58,900 kgN/ha; 1074 trees/ha
1
10
100
1000
10000
0 1 2 3 4 5 6 7 8 9
Quarter
NH
4+
 (m
g/L
)  
qu
ar
ter
ly 
av
era
ge
 of
 bl
oc
ks
 1-
3 
wi
th 
sta
nd
ar
d d
ev
iat
ion
{lo
ga
rit
hm
ic 
sca
le}
0 kgN/ha; 0 trees/ha 39,300 kgN/ha; 0 trees/ha
39,300 kgN/ha; 716 trees/ha 39,300 kgN/ha; 1074 trees/ha
 
 137
Statistical Analysis 
Statistical analysis included evaluation of the following interactions for significance: 
? Application rate 
? Tree density 
? Application rate by tree density 
? Quarter 
? Application rate by quarter 
? Tree density by quarter 
? Application rate by tree density by quarter 
When evaluating results, the more complex statistically significant interactions were 
first considered because they impart more detail on what experimental condition is most 
influencing the differences.  In addition, the more complex interaction will capture any of 
the simpler interactions represented by the included conditions. 
Statistical analyses showed no significant differences (? = 0.05) between any 
application rates, tree densities, or time.  This includes the comparison of controls to the 
other treatments.  Though the statistics indicate that the higher values from all three 
biosolids application rates, which ranged from 100 mg/L ? 3178 mg/L, were not 
significantly different from the controls, which exhibited values less than 45 mg/L, it is 
evident from the results that ammonium is leaching from the biosolids to the pan 
lysimeters.  The lack of statistical significance may be related in part to the fact that the 
high results were not consistently reproduced amongst replicates (i.e., blocks), and does 
not negate the fact that these higher concentrations of total nitrogen (mostly in the form 
of ammonium) are present in those samples. 
 
 138
To determine if these high concentration levels are reasonable, the concentrations in 
the biosolids must be revisited.  Recall from the prior biosolids results section that the 
average concentration of ammonium in the biosolids applied to the experimental plot was 
700 mg/kg (0.07%) on a wet weight basis.  Given an average percent moisture content of 
72%, and assuming that water-soluble ammonium would be in the aqueous phase of the 
biosolids, the concentration of ammonium in solution is calculated as follows:  700 
mg/kg of biosolids*1kg of bisolids/0.72 kg water = 972 mg/kg of water.  Assuming a 
water density of 1g/mL (or 1 kg/L), the estimated concentration of ammonium in the 
aqueous phase is 972 mg/L.  This concentration is an estimate, and does not account for 
the fact that ammonium, as a cation, is adsorbed to organic compounds and soil particles 
with negative charges.  This adsorption will impact compartmentalization of ammonium 
in the aqueous versus the solid phase, as well as movement with the water (Sopper and 
Kerr, 1979; Haynes, 1986). 
Regardless, this calculation does support the higher values found in the samples.  
Values above 1000 mg/L can be explained by either the microbial breakdown of total 
nitrogen into ammonium and/or the concentration of ammonium in the soil during dryer 
time periods when water content decreases.  Stednick and Wooldridge?s (1979) lysimeter 
studies evaluating use of liquid digested sludge in a tree stand supports the latter 
condition, noting that high nutrient concentrations in the soil solutions tended to be 
associated with low water flow and soil moisture content.   
Experiments conducted by Brutsaert, et al. (2004) on nitrate leaching from biosolids 
stockpiles showed that leachate samples collected over an eight month time frame in pan 
lysimeters installed in the soil profile one and two feet under the stockpile contained 800-
 
 139
1500 mg/L total Kjeldahl nitrogen (most of which was in the form of ammonium).  
Further down the profile, three feet below the stockpile, a marked decrease in total 
Kjeldahl nitrogen was noted, with values typically below 100 mg/L.  Leachate collected 
directly from the stockpile contained 2,800 ? 4000 mg/L ammonium, demonstrating that 
some attenuation or conversion of ammonium had occurred. 
Based on the fact that ammonium is held in the soil by the reversible process of 
cation exchange, in which ammonium is adsorbed to negatively-charged soil sites, as well 
as the non-exchangeable process of fixation within clay lattices (Haynes, 1986), it may 
have been expected that ammonium would be more selectively absorbed by those 
subplots with higher silt and clay concentrations.  Haynes (1986) and others have noted 
that, barring other factors, leaching losses of ammonium are usually only problematic in 
soils with a low cation exchange capacity (CEC), as is often evidenced in sandy soils.  
Block 3 contained the highest amount of clay in the soils, followed by block 2.  Block 1 
contained the sandiest of the subplots.  Based on this logic, block 1 should allow the 
highest amount of ammonium to flow through the soil profile to the pans, followed by 
block 2, with block 3 hindering flow the most.  It is evident from the results that no single 
block stands out as having predominantly higher results across the treatments. 
This mix of results can be explained by a number of factors.  Note from earlier 
descriptions of the soil that within each of the three blocks, the subsoil profile was not 
well structured, having been disturbed during mining activities and later during previous 
biosolids applications.  Most subplots in block 3 contained pockets of sandier soil, just as 
subplots in blocks 1 and 2 contained pockets of high clay-content soil.  This variation in 
the soil will impact cation exchange capacity and hydraulic conductivities, both of which 
 
 140
will affect the adsorption of ammonium to the soil and rate of soil water flow from the 
biosolids to the pan lysimeters. 
Another important factor impacting the adsorption of ammonium to the soil is the 
presence of other cations.  The biosolids were heavily limed and contained on average 
119,000 mg/kg calcium (11.9%) on a dry weight basis and 34,200 mg/kg (3.42%) on a 
wet weight basis.  Potassium in the biosolids, measured as potash (K2O), was also present 
in appreciable quantities (30,000 mg/kg on a dry weight basis and 1,200 mg/kg on a wet 
weight basis).  Magnesium concentrations were 3,100 mg/kg on a dry weight basis and 
900 mg/kg on a wet weight basis.  These cations will compete with ammonia for 
exchange sites both in the biosolids and in the soil profile.  According to Barber (1995) 
ammonium is similar in size to potassium and will therefore be held on soil exchange 
sites with similar strength.  Haynes (1986) reported the following order of replacing 
power on cation exchange sites in soils: Al3+ > Fe3+ > Ca2+ > Mg2+ > K+ > Na+.  Though 
this lineup does not include ammonium (NH4+), it does include potassium (K+).  As noted 
above, potassium has a similar holding strength to ammonium.  Consequently, 
ammonium will be out competed for exchange sites by elements known to be present in 
large quantities in the biosolids used at the experimental plot.   
Loehr et al (1979) estimated that, within the pH range of most soils (4.5-7.5), the 
presence of calcium, magnesium, and potassium could reduce the amount of CEC 
available for ammonium to approximately 5%.  For a soil with an average CEC value 
(approximately 15 meq/100g), Loehr calculated that the soil?s capacity for ammonium 
would be limited to 112 kg/ha.  The ammonium content of the biosolids used at the 
ERCO site was approximately 7% of the total nitrogen.  The low-level total nitrogen 
 
 141
application rate was 19,650 kg N/ha.  Seven percent of this application rate is 
19,650*0.07 = 1,375 kg NH4+/ha, a 10-fold increase above the cutoff presented by Loehr.  
Leaching of ammonium is therefore not an unexpected occurrence at the ERCO 
experimental plot.  Suction lysimeter results, which evaluated three different distances 
below the biosolids row and two positions lateral to the biosolids row, may provide more 
insight regarding the direction and depth to which ammonium leaching occurred. 
Suction Lysimeter Samples 
As with the pan lysimeters, total N and ammonium results from suction lysimeters 
showed appreciable concentrations across application rates, with controls exhibiting the 
lowest values.  A summary of the frequency of results in successive concentration ranges 
is presented in Table 18. 
 
Table 18.  Frequency of suction lysimeter results in successive concentration ranges. 
 Total N NH4+* 
Values < 10 mg/L 92 of 562 =  16%  108 of 562 = 19% (pan=15%) 
Values from 10-20 mg/L 41 of 562 =    7%  29 of 562 =     5% (pan=8%) 
Values from 20-50 mg/L 56 of 562 =  11%  58 of 562 =   11% (pan=11%) 
Values from 50-100 mg/L 77 of 562 =  14%  69 of 562 =   12% (pan=13%) 
Values from 100-500 mg/L 151 of 562 = 27%  150 of 562 = 27% (pan=36%) 
Values from 500-1000 mg/L 41 of 562 =    7%  45 of 562 =     8% (pan=8%) 
Values > 1000 mg/L 104 of 562 = 18%  103 of 562 = 18% (pan=9%) 
*For comparison, pan lysimeter percentages are included in parentheses (pan=xx%). 
 
 
Though a high percentage of results were less than 50 mg/L, a higher percentage of 
results had more significant values above 100 mg/L.  Distribution of values was 
essentially the same between total nitrogen and ammonium.  Compared to pan lysimeters, 
distribution was the same for values less than 100 mg/L.  A higher percentage of suction 
lysimeter values, however, were distributed in the highest range (i.e., values > 1000 
mg/L), with corresponding lower amounts in the 100-500 mg/L range. 
 
 142
Suction lysimeter results for ammonium are presented by each application rate in 
Figures 86-94 below.  Total nitrogen is presented in Appendix 2.  Data plots show 
quarterly values for each block and depth.  The initial data plot with all four quarters 
represented is included to provide an overall view of results over time.  Because of the 
number of data points, however, the resolution of individual application rate by tree 
density combinations was compromised.  Consequently, this original data plot was 
further separated into two charts, each of which includes two of the four quarters.  Within 
these charts, quarter, block and position designations are noted.  Due to the wide range in 
concentrations, results are plotted on a logarithmic scale. 
Recall that five suction lysimeters were installed within each of the 30 subplots.  
Three capture vertical flow and were positioned 15, 30, and 60 cm underneath the bottom 
of the biosolids rows.  Two capture vertical flow and were positioned 15 and 30cm lateral 
from the edge of a biosolids row at a depth equal to the bottom of the biosolids row 
(Figure 6).  In the bar charts and tables that follow, these positions are indicated as PV15, 
PV30, PV60, PL15, and PL30, respectively.  As a reminder, the time periods associated 
with each of the suction lysimeter quarterly designations include: 
Q4 = November 2003 ? February 2004; Q5 = March 2004 ? May 2004;  
Q6 = June 2004 ? August 2004 (recall that samples were not collected in July); 
Q7 = October 2004 ? December 2004 (recall that samples were not collected in 
November). 
  
143
                             Fig
ure
 86.  A
mm
oni
um
 qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 low
-le
ve
l a
ppl
ica
tion r
ate
 in s
uc
tion l
ysi
me
ter
 (S
L)
 sa
mpl
es ? a
ll 
qua
rte
rs.
 
00110
10
0
10
00
10
00
0
Q4-B1-PV15Q4-B1-PV30
Q4-B1-PV60Q4-B1-PL15
Q4-B1-PL30Q4-B2-PV15
Q4-B2-PV30Q4-B2-PV60
Q4-B2-PL15Q4-B2-PL30
Q4-B3-PV15Q4-B3-PV30
Q4-B3-PV60Q4-B3-PL15
Q4-B3-PL30Q5-B1-PV15
Q5-B1-PV30Q5-B1-PV60
Q5-B1-PL15Q5-B1-PL30
Q5-B2-PV15Q5-B2-PV30
Q5-B2-PV60Q5-B2-PL15
Q5-B2-PL30Q5-B3-PV15
Q5-B3-PV30Q5-B3-PV60
Q5-B3-PL15Q5-B3-PL30
Q6-B1-PV15Q6-B1-PV30
Q6-B1-PV60Q6-B1-PL15
Q6-B1-PL30Q6-B2-PV15
Q6-B2-PV30Q6-B2-PV60
Q6-B2-PL15Q6-B2-PL30
Q6-B3-PV15Q6-B3-PV30
Q6-B3-PV60Q6-B3-PL15
Q6-B3-PL30Q7-B1-PV15
Q7-B1-PV30Q7-B1-PV60
Q7-B1-PL15Q7-B1-PL30
Q7-B2-PV15Q7-B2-PV30
Q7-B2-PV60Q7-B2-PL15
Q7-B2-PL30Q7-B3-PV15
Q7-B3-PV30Q7-B3-PV60
Q7-B3-PL15Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osit
ion
 ID
N H 4 +  ( m g / L )
L o g a r i t h m i c  S c a l e
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 0
 tre
es/h
a
19
,65
0 k
gN
/ha
; 7
16
 tre
es/
ha
19
,65
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
144
                     Fig
ure
 87.  A
mm
oni
um
 qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 low
-le
ve
l a
pp. r
ate
 in S
L 
sam
ple
s: Q
4&
5. 
                     Fig
ure
 88.  A
mm
oni
um
 qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 low
-le
ve
l a
pp. r
ate
 in S
L 
sam
ple
s: Q
6&
7. 
00110
10
0
10
00
10
00
0
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
NH4+ (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 7
16
 tre
es/
ha
19
,65
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
00110
10
0
10
00
10
00
0
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
NH4+ (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 7
16
 tre
es/
ha
19
,65
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
145
                             Fig
ure
 89.  A
mm
oni
um
 qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 m
id-
leve
l a
ppl
ica
tion r
ate
 in s
uc
tion l
ysi
me
ter
 (S
L)
 sa
mpl
es ? a
ll 
qua
rte
rs.
 00110100
10
00
10
00
0
Q4-B1-PV15Q4-B1-PV30
Q4-B1-PV60Q4-B1-PL15
Q4-B1-PL30Q4-B2-PV15
Q4-B2-PV30Q4-B2-PV60
Q4-B2-PL15Q4-B2-PL30
Q4-B3-PV15Q4-B3-PV30
Q4-B3-PV60Q4-B3-PL15
Q4-B3-PL30Q5-B1-PV15
Q5-B1-PV30Q5-B1-PV60
Q5-B1-PL15Q5-B1-PL30
Q5-B2-PV15Q5-B2-PV30
Q5-B2-PV60Q5-B2-PL15
Q5-B2-PL30Q5-B3-PV15
Q5-B3-PV30Q5-B3-PV60
Q5-B3-PL15Q5-B3-PL30
Q6-B1-PV15Q6-B1-PV30
Q6-B1-PV60Q6-B1-PL15
Q6-B1-PL30Q6-B2-PV15
Q6-B2-PV30Q6-B2-PV60
Q6-B2-PL15Q6-B2-PL30
Q6-B3-PV15Q6-B3-PV30
Q6-B3-PV60Q6-B3-PL15
Q6-B3-PL30Q7-B1-PV15
Q7-B1-PV30Q7-B1-PV60
Q7-B1-PL15Q7-B1-PL30
Q7-B2-PV15Q7-B2-PV30
Q7-B2-PV60Q7-B2-PL15
Q7-B2-PL30Q7-B3-PV15
Q7-B3-PV30Q7-B3-PV60
Q7-B3-PL15Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
N H 4 +  ( m g / L )
L o g a r i t h m i c  S c a l e
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 7
16
 tre
es/
ha
39
,30
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
146
                     Fig
ure
 90.  A
mm
oni
um
 qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 m
id-
leve
l a
pp. r
ate
 in S
L 
sam
ple
s: Q
4&
5. 
                     Fig
ure
 91.  A
mm
oni
um
 qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 m
id-
leve
l a
pp. r
ate
 in S
L 
sam
ple
s: Q
6&
7. 
00110
10
0
10
00
10
00
0
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
NH4+ (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 7
16
 tre
es/
ha
39
,30
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
00110
10
0
10
00
10
00
0
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
NH4+ (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 7
16
 tre
es/
ha
39
,30
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
147
                             Fig
ure
 92.  A
mm
oni
um
 qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 hi
gh-
leve
l a
ppl
ica
tion r
ate
 in s
uc
tion l
ysi
me
ter
 (S
L)
 sa
mpl
es ? a
ll 
qua
rte
rs.
 001101001000
10
00
0
Q4-B1-PV15Q4-B1-PV30
Q4-B1-PV60Q4-B1-PL15
Q4-B1-PL30Q4-B2-PV15
Q4-B2-PV30Q4-B2-PV60
Q4-B2-PL15Q4-B2-PL30
Q4-B3-PV15Q4-B3-PV30
Q4-B3-PV60Q4-B3-PL15
Q4-B3-PL30Q5-B1-PV15
Q5-B1-PV30Q5-B1-PV60
Q5-B1-PL15Q5-B1-PL30
Q5-B2-PV15Q5-B2-PV30
Q5-B2-PV60Q5-B2-PL15
Q5-B2-PL30Q5-B3-PV15
Q5-B3-PV30Q5-B3-PV60
Q5-B3-PL15Q5-B3-PL30
Q6-B1-PV15Q6-B1-PV30
Q6-B1-PV60Q6-B1-PL15
Q6-B1-PL30Q6-B2-PV15
Q6-B2-PV30Q6-B2-PV60
Q6-B2-PL15Q6-B2-PL30
Q6-B3-PV15Q6-B3-PV30
Q6-B3-PV60Q6-B3-PL15
Q6-B3-PL30Q7-B1-PV15
Q7-B1-PV30Q7-B1-PV60
Q7-B1-PL15Q7-B1-PL30
Q7-B2-PV15Q7-B2-PV30
Q7-B2-PV60Q7-B2-PL15
Q7-B2-PL30Q7-B3-PV15
Q7-B3-PV30Q7-B3-PV60
Q7-B3-PL15Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
N H 4 +  ( m g / L )
L o g a r i t h m i c  S c a l e
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 7
16
 tre
es/
ha
58
,90
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
148
                    Fig
ure
 93.  A
mm
oni
um
 qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 hi
gh-
leve
l a
pp. r
ate
 in S
L 
sam
ple
s: Q
4&
5. 
                    Fig
ure
 94.  A
mm
oni
um
 qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 hi
gh-
leve
l a
pp. r
ate
 in S
L 
sam
ple
s: Q
6&
7.
00110
10
0
10
00
10
00
0
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Qu
ar
ter
-B
loc
k-
Po
sit
ion
 ID
NH4+ (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 7
16
 tre
es/
ha
58
,90
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
00110
10
0
10
00
10
00
0
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-
Po
sit
ion
 ID
NH4+ (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 7
16
 tre
es/
ha
58
,90
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
 
 149
 
Results from the controls (0 kgN/ha; 0 trees/ha) ranged between 0.91 ? 51 mg/L for 
total N and 0.07 ? 55 mg/L for ammonium, similar to the ranges associated with the pan 
lysimeters.  Of the 28 control values, only four for total nitrogen and three for ammonium 
(11-14%) were greater than 10 mg/L.  The smaller proportion of higher values is different 
from the pan lysimeters, for which 60% of the control results were above 10 mg/L.  As 
noted in the prior discussion on pan lysimeter results, these control values are consistent 
with background level estimates previously determined on untreated soil samples from 
the farm. 
As with the pan lysimeters, the trends for total nitrogen and ammonium coincide.  
Total nitrogen and ammonium results demonstrate essentially the same partitioning into 
concentration ranges as well as distribution over suction lysimeter positions and quarters.  
Using the 0.07 - 55 mg/L control results as background levels, sample values greater than 
100 mg/L will be more closely examined. 
Figure 95 compares the percentages of ammonium results in different concentration 
ranges across application rates.  Figure 96 further examines ammonium results greater 
than 100 mg/L within each application rate by tree density.  Of the three application rates, 
39,300 kg N/ha produced the highest percentage of results greater than 100 mg/L.  
Although 19,650 kg N/ha rate had the highest percentage of results greater than 1,000 
mg/L, it was not notably higher than the other two application rates.  Results greater than 
100 mg/L were distributed evenly across tree densities for all application rates.  
Differences in concentrations over time were not obvious from this general overview, but 
will be presented in more detail when discussing statistical analysis results. 
 
 
 150
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 95.  Suction lysimeter ammonium results:  distribution across concentration ranges 
for each application rate. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 96.  Suction lysimeter ammonium results:  distribution of results >100 mg/L 
across tree densities for each application rate. 
0
20
40
60
80
100
120
19,650 kg N/ha 39,300 kg N/ha 58,900 kg N/ha
Application Rate
Nu
mb
er 
of 
res
ult
s w
ith
 N
H4+
 >1
00
 m
g/L
All tree densities
0 trees/ha
716 trees/ha
1074 trees/ha
35%
32%
38%
37%
30%32%
28%
36%
32%
41
36
45
37
46
34
22
18
21
0
5
10
15
20
25
30
35
40
45
50
19,650 kg N/ha 39,300 kg N/ha 58,900 kg N/ha
Application Rate
%
 N
H4
+  
Re
su
lts
  
% Results < 100 mg/L
% Results 100-1000 mg/L
% Results > 1000 mg/L
 
 151
 
Differences across each application rate are more clearly linked to suction lysimeter 
position.  From the quarterly results presented in Figures 86-94 above, and as more 
clearly shown in summary level in Figure 97 below, a greater concentration of total 
nitrogen and ammonium had traveled with greater frequency directly underneath the 
biosolids rows to the shallowest of the three vertical suction lysimeters, with successively 
lower concentrations by depth.  The highest results (those greater than 1,000 mg/L) are 
associated with the vertical flow lysimeters in closest proximity to the biosolids row (i.e., 
PV15 and PV30) across all quarters, with PV15 standing out amongst all other positions.  
Within the PV15, PV30, and PV60 positions, each application rate produced similar 
numbers of high results, with 19,650 kg N/ha producing slightly more values in the PV15 
position and 58,900 kg N/ha producing more in the PV30 and PV60 positions. 
Compared to the vertical flow positions, the lateral flow positions had a lower 
frequency of soil water with concentrations above 100 mg/L, especially the lysimeter 
positioned furthest from the edge of the biosolids row (PL30), for which the highest 
application rate (58,900 kg N/ha) produced no results greater than 100 mg/L.  This 
supports the postulation that flow of leachate from the biosolids row is predominantly 
downward. 
 
 152
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 97.  Suction lysimeter ammonium results:  distribution of results > 100 mg/L 
across lysimeter positions. 
 
Table 19 provides supporting information to Figure 97, and provides ranges in 
concentrations for each position.  The high end of the concentration range for the suction 
lysimeters (6723 and 5103 mg/L for TN and NH4+, respectively) was considerably higher 
than that of the pan lysimeters (2800 and 3178 mg/L for TN and NH4+, respectively).  
The position of the pan lysimeter, however, is 30 cm below the biosolids trench.  
Therefore, it is most appropriate to compare the pan lysimeter results to those from the 
PV30 suction lysimeters.  The high values of 3875 and 4020 mg/L for the suction 
lysimeters are closer to, but still slightly higher than, those from the pan lysimeter. 
0
5
10
15
20
25
30
35
40
PV-15cm PV-30cm PV-60cm PL-15cm PL-30cm
Suction Lysimeter Position: 
PV=vertical placement below bisolids row; PL= lateral placement from edge of biosolids row
Nu
mb
er 
of 
NH
4+
 re
su
lts
 > 
10
0 m
g/L
19,650 kg N/ha
39,300 kg N/ha
58,900 kg N/ha
 
 153
 
Table 19.  Comparison of suction lysimeter positions for results > 100 mg/L. 
Number of Results > 100 mg/L 
SL 
Position 
TN&NH4+ Concentration 
Range for those values > 
100 mg/L 
19,650 
kgN/ha 
39,300 
kgN/ha 
58,900 
kgN/ha Totals 
PV15 
TN:  124?6273 
NH4+:  113-5103 34 31 31 96 
PV30 
TN:  119?3875 
NH4+:  120-4020 22 19 24 65 
PV60 
TN:  100?2082 
NH4+:  101-2113 18 21 22 61 
PL15 
TN:  102-1247 
NH4+:  104-1221 17 19 16 52 
PL30 
TN:  103?357 
NH4+:  100-350 7 17 0 24 
 
 
It could be reasoned that the slightly higher values for the suction lysimeter are 
logical, given the type of water collected from the suction lysimeter versus that from the 
pan lysimeter.  The pan lysimeter predominantly collects saturated flow due to 
gravimetric forces.  This water travels quickly through the larger pores in the soil with 
less time for soil contact.  The suction lysimeter, however, predominantly collects soil 
water held in the soil by matric forces.  This water is subject to a longer residence time 
that could allow for concentration or conversion of nutrients in the soil (Barbee and 
Brown, 1986; Marques, et. al., 1996).  Conversely, one could argue that saturated flow is 
often associated with a flushing effect that moves nutrients and other water-soluble 
compounds through the soil profile, and can account for elevated concentrations of 
nutrients (Brady and Weil, 2002).  Such flushing effects are more likely to be captured by 
pan lysimeters, which continuously collect sample over time and capture flow from a 
greater cross sectional area, as opposed to suction lysimeters, which capture soil water 
from a smaller area and only during the time that suction is applied (for the purposes of 
this experiment, approximately three days). 
 
 154
When evaluating these conditions, the source of the soil water flowing to the 
equipment must also be considered.  The two main sources of aqueous solution to the soil 
are rainfall and leachate from the biosolids rows.  The elevated ammonium 
concentrations are clearly from the biosolids (given the much lower values in the controls 
and the known amounts from the biosolids analysis).  Provided the biosolids rows are 
continuously dewatering, with a majority of flow in the vertical direction, the pan and 
suction lysimeters will both be capturing soil water introduced from this source.  Dilution 
effects from rainfall and subsequent percolation through the soil as well as concentration 
effects from drier periods will impact the concentration levels captured by both types of 
equipment.  Consequently, a variety of factors influence the type of soil water that is 
collected from the two types of lysimeters. 
Prior studies comparing pan and suction lysimeters (presented in the literature review 
section) as well as observations noted in this thesis study show that, with the exception of 
the known fact that zero-tension lysimeters capture saturated flow and suction lyismeters 
capture both saturated and more predominantly unsaturated flow, no one physical, 
chemical, or biological process can be selectively linked to either collection apparatus.  
Rather, the soil water collected by either of these lysimeters is a product of the specific 
circumstances governing the experimental set up and environmental conditions.  Using 
both types of sampling equipment does, however, ensure that a comprehensive 
representation of the soil solution in the soil profile was obtained. 
Rainfall Flushing Effect 
Another facet of environmental conditions worth considering in the context of these 
results is whether or not storm events influenced the results.  Of particular interest is 
 
 155
whether or not precipitation may have introduced a flushing effect that would have 
produced elevated results in samples collected during the flushing time frame.  Due to the 
nature of the sample collection process, this evaluation can only consider results from 
suction lysimeters, which capture flow from the select period of time (usually 3 days) 
during which suction is placed on the equipment.  Pan lysimeters, on the other hand, 
continuously collect soil water between each monthly collection event.  Consequently, 
and despite the fact that other studies have reasoned that pan lysimeters are more efficient 
at collecting saturated flow, it is not possible to distinguish between what may be a 
combination of storm flow and non-storm flow in the pan lysimeter samples. 
For this evaluation, individual unconsolidated ammonium results (i.e., those results 
produced from each sampling event, as opposed to the quarterly averages used for most 
other evaluations in this discussion) that were greater than 1000 mg/L were identified.  
Over 247 results encompassing 25 of the 30 subplots were included.  Those subplots 
without results greater than 1000 mg/L included the controls (subplots 4A, 4B, and 4C) 
and two subplots from block 3 (3E and 3H).  Based on the hydraulic conductivity values 
collected over the soil profile in each subplot, an estimate of rainfall travel time to the 
equipment was determined (as noted and shown in the previous section on rain gauge 
data, Table 14 and Figure 67).  It is important to note, however that these calculations are 
based on assumptions of saturated flow.  If at any point unsaturated flow conditions exist, 
which is likely, the percolation of precipitation would be much slower. 
Storm events producing greater than 2.54 cm (1 inch) of rainfall were then identified.  
Based on the dates of the storm events and the previously determined soil profile travel 
times, the time frame during which the infiltrated rainfall would reach the suction 
 
 156
lysimeters in each subplot was calculated.  This rainfall arrival time frame was then 
compared to the collection dates for samples with the high ammonium concentrations to 
see if the two time intervals coincided.  Of the 247 results identified, 51 (approximately 
20%) had sample collection dates that matched the intervals during which a precipitation 
event would have reached the equipment.  With only 20% of the results falling in this 
category, it is evident that an overall flush effect was not observed.  The high ammonium 
values are instead more closely tied to the ongoing dewatering of the biosolids. 
 
Statistical Analysis 
Unlike the pan lysimeters, statistical analysis of suction lysimeter results showed 
significant differences (? = 0.05) for a number of treatment interactions for both total 
nitrogen and ammonium.  Because these trends were similar for both nitrogen forms, 
ammonium will be the focus of this discussion, with references to total nitrogen as 
appropriate.  A number of interactions were statistically analyzed and included: 
? Application rate 
? Tree density 
? Application rate by tree density 
? Position 
? Application rate by position 
? Tree density by position 
? Application rate by tree density by position 
? Quarter 
? Application rate by quarter 
? Tree density by quarter 
 
 157
? Application rate by tree density by quarter 
? Position by quarter 
? Application rate by position by quarter 
? Tree density by position by quarter 
? Application rate by tree density by quarter. 
When evaluating the results, the more complex statistically significant interactions 
were first considered because they impart more detail on what experimental condition is 
influencing the differences most.  In addition, the more complex interaction will capture 
any of the simpler interactions represented by the included conditions. 
Controls vs. other application rates 
Comparison of controls (0 kgN/ha and 0 trees/ha) to other application rates and tree 
density combinations showed significant differences (? = 0.05) for time (i.e., quarter) and 
position.  With regard to time, an internal comparison of control results across quarters 
revealed no consistent trends.  Quarter 4 was not significantly different than quarters 6 
and 7, though quarter 5 was less than quarters 4, 6, and 7, and quarter 6 was less than 
quarter 7.   
Comparison of controls to other application rates showed that all control results for 
each of the four quarters (i.e., quarters 4, 5, 6 and 7) were significantly less than almost 
all other quarterly results for all other combinations of application rate and tree density.  
Figure 98 provides a scatter plot of quarterly results by each application rate to 
demonstrate these differences.  Each set of application rate results is offset from the other 
within each quarter designation on the plot to ensure that these values are readily seen for 
comparison. 
 
 158
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 98.  Suction lysimeter quarterly average ammonium results:  controls vs. all other 
application rates. 
 
 
Evaluation of differences between positions (i.e., PV15, PV30, PV60, PL15, and 
PL30) showed an internal control difference as well as differences from other application 
rates.  Comparing control position results to one another, the PV60 position was 
significantly higher than PV15, PV30 and PL30 (though not PL15).  Figure 99 below 
plots the control results across positions, definitively showing that results from the PV60 
position does contain results that are higher than most other positions.  While most results 
from all positions are near or below 10 mg/L, a cluster of results in the PV60 set is 
notably higher with values between 35-55 mg/L.  These values are from the same suction 
lysimeter (and therefore the same control subplot, 4A) over all four quarters.  After 
evaluating the installation notes and sample collection logs, no notable differences 
0.0
0.1
1.0
10.0
100.0
1000.0
10000.0
3 4 5 6 7 8Quarter
NH
4+
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
0 kgN/ha; 0 trees/ha 19,650 kg N/ha; all tree densities
39,300 kg N/ha; all tree densities 58,900 kg N/ha; all tree densities
 
 159
between this suction lysimeter and others was found.  The values from this lysimeter are 
consistent across time and represent the high end of ammonium concentrations found in 
background levels at the site. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 99.  Suction lysimeter quarterly average ammonium results by position for 
controls. 
 
 
Comparison of controls to other application rates again shows a general trend of 
control results being less than results from other application rates across all positions, 
though some positions produced more statistically significant differences (? = 0.05) than 
others.  The number of non-control application rate by tree density by position 
combinations equals 3*3*5 = 45 different combinations against which each of the five 
positions from the controls can be compared.  Table 20 below provides a breakout of the 
number of statistically significant (? = 0.05) differences (evaluated by LSD) associated 
0.01
0.10
1.00
10.00
100.00
Suction Lysimeter Position
NH
4+
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
0 kgN/ha; 0 trees/ha
PV15 PL30PL15PV60PV30
 
 160
with each control position.  In all of the noted instances, the controls were significantly 
less than the other application rates. 
Table 20.  Tabulation of control by position results that are less than other treatments. 
Number of significantly different results (out of 45 possible)  
Control Position Total N NH4+ 
PV15 43 44 
PV30 40 43 
PV60 22 18 
PL15 39 41 
PL30 38 44 
 
 
It is evident that the control values from all but the PV60 control positions were 
significantly less than almost all other application rate-tree density-position 
combinations.  The control PV60 position was significantly lower than most of the PV15 
and PV30 positions from all other application rate-tree density combinations (accounting 
for the 22 and 18 significant differences cited in Table 20).  It was not always different, 
however, from the PV60, PL15 and PL30 positions from the non-control treatments.  
This is consistent with the previously noted trend for the non-control application rates, in 
which vertical flow lysimeter results decreased with distance from the biosolids row, and 
lateral flow lysimeter results were generally lower than all vertical flow lysimeter results.  
For the non-control treatments, these positions produced lower results more likely to 
overlap with the PV60 control values. 
This trend is better depicted in Figure 100 below.  The control values for PV15, 
PV30, PL15, and PL30 all are in a lower range bracket than the corresponding non-
control application rates.  The PV60 control values, however, overlap with the values for 
the other application rates, not only within the PV60 position, but also across the PL15 
and PL30 positions.  Notwithstanding these exceptions, the statistical evaluations 
 
 161
definitively show that the control results were significantly lower than all other 
treatments. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 100.  Suction lysimeter quarterly average ammonium results: comparison of 
application rates for each suction lysimeter position. 
 
 
Differences between and within non-control treatments 
Evaluation of differences for all non-control treatments showed the following 
interactions to be statistically significant: 
? Application rate by tree density by quarter (for both ammonia and total nitrogen) 
? Tree density by position by quarter (for both ammonia and total nitrogen) 
? Application rate by position by quarter (for total nitrogen only) 
0.01
0.10
1.00
10.00
100.00
1000.00
10000.00
Suction Lysimeter Position:
PV=Vertical placement below biosolids row; PL=lateral placement from edge of biosolids row
NH
4+
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
19,650 kgN/ha; all tree densities 39,300 kgN/ha; all tree densities
58,900 kgN/ha; all tree densities 0 kgN/ha; 0 trees/ha
PV-15cm PL-30cmPL-15cmPV-60cmPV-30cm
 
 162
The ?application rate by tree density by quarter? interaction produced significant 
differences (? = 0.05) between quarters within a given application rate-tree density 
combination.  No differences were generated across application rate-tree density 
combinations.  In most cases, quarter 4 (i.e., the first of the four quarters associated with 
suction lysimeter collection) was significantly less than successive quarters 5, 6 and 7.  
Though not as prevalent as with quarter 4, in some instances quarters 5 and 6 were also 
significantly less than successive quarters.  This may indicate an overall trend of an 
increase in concentration with time, but it is important to note that the trend is not 
consistent and is generalized, because it does not differentiate between suction lysimeter 
positions (i.e., the ?application rate by tree density by position by quarter? interaction was 
not significantly different).  In addition, not all application rate-tree density combinations 
exhibited such differences, though a majority did.  With these noted reservations, this 
statistical analysis may indicate an increase in the leaching of total nitrogen and 
ammonium over time.  This would be consistent with the ongoing dewatering of the 
biosolids over time, assuming dewatering had not yet started to decline.  Table 21 
provides a listing of which treatments produced different quarterly results (i.e., those that 
exhibited the general trends in quarterly increases noted above) and which ones did not.  
Figures 101-103 present the results for the three application rate-tree density 
combinations that most clearly show a consistent statistically significant trend over time.  
Given that these differences may not be visually obvious (due to the logarithmic scale 
and variability of the data), the statistically significant differences are noted in the 
figures.  Note that each quarter captures results from the three blocks, each of which 
contain five suction lysimeter positions, for a maximum of 15 results. 
 
 163
 
Table 21.  Application rate-tree density combinations with quarterly differences. 
Treatments with quarterly differences 
(kg N/ha ? trees/ha) 
Treatments without quarterly differences 
(kg N/ha ? trees/ha) 
Total Nitrogen Ammonium Total Nitrogen Ammonium 
19,650 ? 0 19,650 ? 0 19,650 ? 1074 19,650 ? 1074 
19,650 ? 716 19,650 ? 716 39,300 ? 0  
 39,300 ? 0 58,900 ? 716 58,900 ? 716 
39,300 ? 716 39,300 ? 716   
39,300 ? 1074 39,300 ? 1074   
58,900 ? 0 58,900 ? 0   
58,900 ? 1074 58,900 ? 1074   
 
 
 164
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 101.  Suction lysimeter quarterly average ammonium results for 19,650 kg N/ha -
716 trees/ha (application rate * tree density * quarter interaction). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 102.  Suction lysimeter quarterly average ammonium results for 39,300 kg N/ha - 
716 trees/ha (application rate * tree density * quarter interaction). 
1
10
100
1000
10000
3 4 5 6 7 8Quarter
NH
4+
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
19,650 kg N/ha; 716 trees/haS tatistically significant differences:
Q4 and Q5 < Q6 and Q7
Q6 < Q7
1
10
100
1000
10000
3 4 5 6 7 8Quarter
NH
4+
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
39,300 kg N/ha; 716 trees/haStatistically significant differences:
Q4 and Q5 < Q6 and Q7
Q6 < Q7
 
 165
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 103.  Suction lysimeter quarterly average ammonium results for 58,900 kg N/ha - 
0 trees/ha (application rate * tree density * quarter interaction). 
 
 
Both the ?tree density by position by quarter? and ?application rate by position by 
quarter? interactions exhibited some differences over time (i.e., quarters) in specific 
instances, but were dominated more by differences between the suction lysimeter 
positions, with a general pattern of PV15 > PV30 > PV60.  In addition PV15 was almost 
always greater than PL15 and PL30 and PV30 was often greater than PL15 and PL30.  
Differences between PV60, PL15 and PL30 were not as pronounced. 
For the ?tree density by position by quarter? interaction, the PV15 position for each 
tree density across all quarters was significantly greater than some of the PV30 and PV60 
positions, and almost all of the PL15, and PL30 positions for all quarters across all tree 
densities.  PV30 exhibited differences from PL15 and PL30 across many quarters.  
1
10
100
1000
10000
3 4 5 6 7 8Quarter
NH
4+
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
58,900 kg N/ha; 0 trees/haStatistically significant differences:
Q4 < Q5, Q6 and Q7
Q5 < Q6 and Q7
 
 166
Differences between PV30 and PV60 were not pronounced, nor were differences between 
PV60 and PL15 and PL30.  Comparison of each position to itself across the three tree 
densities showed no differences between tree densities (e.g., PV15 quarterly results from 
0 trees/ha, 716 trees/ha and 1074 trees/ha were not different from one another).  
Consequently, no major differences exist between tree densities; it is more a product of 
position. 
Further evaluating results of the ?tree density by position by quarter? interaction, an 
investigation of each position within a tree density across quarters does show some 
instances in which concentrations increase over time.  The following tree density-position 
combinations show an increase in concentrations from quarters 4 and/or 5 to quarters 6 
and/or 7, though in many of these instances, the trend is not completely sequential over 
all quarters:  1)  for the 0 trees/ha tree density, the PV15, PV30, PV60 and PL30 positions 
show increases over time (quarters); 2) for the 716 trees/ha tree density, the PV15 and 
PL15 positions show increases over time (quarters); 3) for the 1074 trees/ha tree density, 
the PV30 and PL15 positions show increases over time (quarters). 
Figures 104-107 present a subset of the data, specifically from the 0 trees/ha tree 
density, to provide examples of the specific statistically significant differences (? = 0.05) 
determined.  Because differences may not be obvious visually (due to the logarithmic 
scale and variability of results), they are noted in each figure.  Note that each quarter 
captures results from the three blocks, each of which contains four application rates, for a 
maximum of twelve results. 
 
 167
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 104.  Suction lysimeter quarterly average ammonium results for 0 trees/ha, PV-
15cm (tree density*position*quarter interaction). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 105.  Suction lysimeter quarterly average ammonium results for 0 trees/ha, PV-
30cm (tree density*position*quarter interaction). 
0.0
0.1
1.0
10.0
100.0
1000.0
10000.0
3 4 5 6 7 8
Quarter
NH
4+
 (m
g/L
) 
Lo
ga
rit
hm
ic 
Sc
ale
0 trees/ha; PV-15cm
Statistically significant differences:
Q4 < Q6 and Q7
0.1
1.0
10.0
100.0
1000.0
10000.0
3 4 5 6 7 8
Quarter
NH
4+
 (m
g/L
) 
Lo
ga
rit
hm
ic 
Sc
ale
0 trees/ha; PV-30cm
Statistically significant differences:
Q5 < Q6 and Q7
 
 168
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 106.  Suction lysimeter quarterly average ammonium results for 0 trees/ha, PV-
60cm (tree density*position*quarter interaction). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 107.  Suction lysimeter quarterly average ammonium results for 0 trees/ha, PL-30 
cm (tree density*position*quarter interaction). 
1.0
10.0
100.0
1000.0
10000.0
3 4 5 6 7
Quarter
NH
4+
 (m
g/L
) 
Lo
ga
rit
hm
ic 
Sc
ale
0 trees/ha; PV-60cm
Statistically significant differences:
Q4 < Q6 and Q7
Q5 and Q6 < Q7
0.0
0.1
1.0
10.0
100.0
1000.0
3 4 5 6 7 8
Quarter
NH
4+
 (m
g/L
) 
Lo
ga
rit
hm
ic 
Sc
ale
0 trees/ha; PL-30cm
Statistically significant differences:
Q4 < Q6 and Q7
Q5 and Q6 < Q7
 
 169
The ?application rate by position by quarter? interaction was significant for total 
nitrogen only, one of the few instances in which the statistical results were not consistent 
between total nitrogen and ammonium.  Because of the similarity in results between the 
two parameters, it may simply be a matter of total nitrogen exhibiting differences slightly 
more pronounced than ammonium such that total nitrogen crossed the threshold of being 
statistically significant. 
Statistical significance was determined between positions.  Similar to findings from 
other interactions, all PV15 values across all quarters for 19,650 kg N/ha, 39,300 kg 
N/ha, and 58,900 kg N/ha were significantly greater than many PV30 and PV60 values 
and almost all PL15 and PL30 values across all quarters and application rates.  PV15 
values from one application rate were not different the other two application rates (i.e., 
differences were not found between application rates). 
PV30 values did not exhibit as pronounced differences from the PV60 position, but 
were often greater than the laterally positioned lysimeters (PL15 and PL30) across 
application rates and quarters.  Figure 108 below shows total nitrogen results for each 
application rate by position.  Figure 100 above, previously presented when evaluating 
control results, shows the same results for ammonium.  Although this interaction for 
ammonium was not statistically significant, it is evident that both sets of results follow a 
similar pattern. 
 
 170
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 108.  Suction lysimeter total nitrogen results by position for each application rate. 
 
 
As with the ?tree by position by quarter? interaction, the ?application rate by position 
by quarter? interaction showed some quarterly trends within a particular application rate-
position combination.  The following application rate-position combinations show an 
increase in concentrations from quarters 4 and/or 5 to quarters 6 and/or 7, though in many 
of these instances, the trend is not completely sequential over all quarters: 
? For the 19,650 kg N/ha application rate, the PV60 and PL30 positions show 
increases over time (quarters). 
? For the 39,300 kg N/ha application rate, the PV15, PV30, PV60, and PL30 
positions show increases over time (quarters). 
? For the 58,900 kg N/ha application rate, the PV15, PV30, PV60, and PL15 
positions show increases over time (quarters). 
0.1
1.0
10.0
100.0
1000.0
10000.0
0 10 20 30 40 50 60
Suction Lysimeter Position
PV=vertical placement below biosolids row; PL=lateral placement from edge of biosolids row
To
tal
 N
 (m
g/L
) 
Lo
ga
rit
hm
ic 
Sc
ale
0 kg N/ha; 0 trees/ha 19,650 kg N/ha; all tree densities
39,300 kg N/ha; all tree densities 58,900 kg N/ha; all tree densities
PV-15cm PV-30cm PV-60cm PL-15cm PL-30cm
 
 171
Figures 109-112 below present a subset of the data, specifically from the 58,900 kg 
N/ha application rate, to provide examples of the specific statistically significant 
differences (? = 0.05) determined.  Because differences may not be obvious visually (due 
to the logarithmic scale and variability of results), they are noted in each figure.  Note 
that each quarter captures results from the three blocks, each of which contains three tree 
densities, for a maximum of nine results. 
 
 
 
 172
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 109.  Suction lysimeter quarterly average total nitrogen results for 58,900 kg N/ha, 
PV-15cm (application rate*position*quarter interaction). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 110.  Suction lysimeter quarterly average total nitrogen results for 58,900 kg N/ha, 
PV-30cm (application rate*position*quarter interaction). 
1
10
100
1000
10000
3 4 5 6 7 8
Quarter
To
tal
 N
 (m
g/L
) 
Lo
ga
rit
hm
ic 
Sc
ale
58,900 kg N/ha; PV-15cm
Statistically significant differences:
Q4 < Q5, Q6, and Q7
Q5 < Q7
1
10
100
1000
10000
3 4 5 6 7 8
Quarter
To
tal
 N
 (m
g/L
) 
Lo
ga
rit
hm
ic 
Sc
ale
58,900 kg N/ha; PV-30cm
Statistically significant differences:
Q4 < Q5, Q6, and Q7
 
 173
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 111.  Suction lysimeter quarterly average total nitrogen results for 58,900 kg N/ha, 
PV-60cm (application rate*position*quarter interaction). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 112.  Suction lysimeter quarterly average total nitrogen results for 58,900 kg N/ha, 
PL-15cm (application rate*position*quarter interaction). 
1
10
100
1000
10000
3 4 5 6 7 8Quarter
To
tal
 N
 (m
g/L
) 
Lo
ga
rit
hm
ic 
Sc
ale
58,900 kg N/ha; PV-60cm
Statistically significant differences:
Q4 < Q6
1
10
100
1000
10000
3 4 5 6 7 8
Quarter
To
tal
 N
 (m
g/L
) 
Lo
ga
rit
hm
ic 
Sc
ale
58,900 kg N/ha; PL-15cm
Statistically significant differences:
Q4 < Q5, Q6, and Q7
Q5 < Q6 and Q7
 
 174
Conclusions 
More than half of both the pan and suction lysimeter samples contained ammonium 
concentrations in excess of 100 mg/L, with some values greater than 1000 mg/L.  For the 
pan lysimeters, the higher concentrations were distributed fairly evenly across application 
rates, but were more prevalent in the 0 trees/ha tree density.  Statistical analysis of the 
pan samples, however, showed no significant differences (?= 0.05) for application rate 
(which included the controls), tree density, or time. 
Suction lysimeters provided more distinct differences.  Unlike the pan lysimeters, 
higher concentrations were not associated with 0 trees/ha, but rather were distributed 
evenly across tree densities.  Comparison of application rates did show the controls to be 
significantly less than other application rates, but no overriding trend was determined 
between the non-control application rates.   
The most notable trend from both observational and statistical analysis is that an 
inverse relationship exists between depth below the biosolids row and ammonium 
concentration.  As depth increases, concentration decreases, suggesting that ammonium is 
leaching out of the biosolids row and, over the course of this experiment, the highest 
concentrations have thus far reached the first suction lysimeter.  An alternative 
explanation for the lower concentrations in the deeper vertical lysimeters could be that 
ammonia is nitrifying to produce nitrate, with subsequent denitrification of nitrate.  This 
explanation is not as plausible, however, given the negligible concentration of nitrite and 
nitrate found in all samples (see subsequent sections for results) and the improbability of 
enough oxygen reaching areas below the biosolids within the first couple of years.  Even 
if nitrate was denitrifying once it presumably was produced and leached to lower, more 
 
 175
oxygen-deprived locations, at some point a sample would be collected that captured 
nitrate before it leached further in the profile and/or was denitrified. 
An overall increase in concentration with time has also been indicated within each 
lysimeter position, though further data collection over time will be necessary to provide 
more insight to the extent of this trend. 
 
 176
 
Soil Water Results:  Nitrite (NO2-) Data 
Nitrite is produced from the breakdown of ammonia in the first part of the two-step 
process of nitrification.  Aerobic conditions, the appropriate microbes, and a carbon 
source for the microbes are required.  Upon application, the biosolids were encased in the 
overburden/soil from the site and were saturated with water, effectively impeding the 
flow of oxygen to the rows.  During design of the experiment it was hypothesized that 
conversions to nitrite would be significantly diminished until water drained from the 
biosolids and oxygen was introduced to deeper layers of the soil via tree roots and drying 
processes.  In addition, physical and chemical conditions in the soil would need to be 
favorable for the growth of the Nitrosonomas and other bacteria responsible for this 
conversion. 
 
Pan Lysimeter Samples 
Pan lysimeter results show consistently low levels of nitrite across all treatments, 
with few exceptions.  Of the 430 results generated, 422 (98%) were less than the EPA 
drinking water MCL of 1.0 mg/L.  The eight remaining results above 1.0 mg/L ranged 
from 1.2-30 mg/L.  When individual subplot values were averaged within each quarter, 
the 430 results were consolidated to 223 results.  Depictions of quarterly results for each 
block are provided in Figures 113-115.  Results are plotted on a logarithmic scale. 
 
 
 177
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 113.  Nitrite quarterly average concentrations for low-level application rate in pan 
lysimeters. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 114.  Nitrite quarterly average concentrations for mid-level application rate in pan 
lysimeters. 
0.00
0.01
0.10
1.00
10.00
Q1-
B1
Q1-
B2
Q1-
B3
Q2-
B1
Q2-
B2
Q2-
B3
Q3-
B1
Q3-
B2
Q3-
B3
Q4-
B1
Q4-
B2
Q4-
B3
Q5-
B1
Q5-
B2
Q5-
B3
Q6-
B1
Q6-
B2
Q6-
B3
Q7-
B1
Q7-
B2
Q7-
B3
Q8-
B1
Q8-
B2
Q8-
B3
Quarter-Block ID
NO
2-  
(m
g/L
)
Lo
ga
rith
mi
c S
ca
le
0 kgN/ha; 0 trees/ha
39,300 kgN/ha; 0 trees/ha
39,300 kgN/ha; 716 trees/ha
39,300 kgN/ha; 1074 trees/ha
Apr-May-03 Jun-Aug-03 Sept-Nov-03 Dec-03, Jan/Feb-04 Mar-May-04 Jun/Aug 
04
Oct-04 Dec-04
0.00
0.01
0.10
1.00
10.00
Q1-
B1
Q1-
B2
Q1-
B3
Q2-
B1
Q2-
B2
Q2-
B3
Q3-
B1
Q3-
B2
Q3-
B3
Q4-
B1
Q4-
B2
Q4-
B3
Q5-
B1
Q5-
B2
Q5-
B3
Q6-
B1
Q6-
B2
Q6-
B3
Q7-
B1
Q7-
B2
Q7-
B3
Q8-
B1
Q8-
B2
Q8-
B3
Quarter-Block ID
NO
2-  
(m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
0 kgN/ha; 0 trees/ha
19,650 kgN/ha; 0 trees/ha
19,650 kgN/ha; 716 trees/ha
19,650 kgN//ha; 1074 trees/ha
Apr-May-03 Jun-Aug-03 Sept-Nov-03 Dec-03, Jan/Feb-04 Mar-May-04 Jun/Aug 
04
Oct-04 Dec-04
 
 178
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 115.  Nitrite quarterly average concentrations for high-level application rate in pan 
lysimeters. 
 
Three groups of higher values (> 1.0 mg/L) stand out:  (a) the quarter 1 value for the 
control (0 kgN/ha; 0 trees/ha) in Block 2, which is identified as subplot 4B (b) the quarter 
1 value for 19,650 kgN/ha; 0 trees/ha in Block 2, which is identified as subplot 2I and (c) 
quarter 3, 4, 6,7 and 8 values for 58,900 kgN/ha; 0 trees/ha, all in Block 2, which is 
identified as subplot 2C. 
In the case of the control, the high concentration is associated with subplot ID 4B 
(the control in Block 2) and is succeeded in quarter 2 by a lower, though still slightly 
elevated value of 0.44 mg/L (elevated, comparatively speaking, from the rest of the data) 
and a non-detect value in quarter 3.  This indicates that a nitrogen source was present in 
the control at the beginning of collection activities that was also exposed to enough 
oxygen and microbes to facilitate some level of nitrification.  In addition, the nitrification 
0.00
0.01
0.10
1.00
10.00
100.00
Q1-
B1
Q1-
B2
Q1-
B3
Q2-
B1
Q2-
B2
Q2-
B3
Q3-
B1
Q3-
B2
Q3-
B3
Q4-
B1
Q4-
B2
Q4-
B3
Q5-
B1
Q5-
B2
Q5-
B3
Q6-
B1
Q6-
B2
Q6-
B3
Q7-
B1
Q7-
B2
Q7-
B3
Q8-
B1
Q8-
B2
Q8-
B3
Quarter-Block ID
NO
2-  
(m
g/L
)
Lo
ga
rith
mi
c S
ca
le
0 kgN/ha; 0 trees/ha
58,900 kgN/ha; 0 trees/ha
58,900 kgN/ha; 716 trees/ha
58,900 kgN/ha; 1074 trees/ha
Apr-May-03 Jun-Aug-03 Sept-Nov-03 Dec-03, Jan/Feb-04 Mar-May-04 Jun/Aug 
04
Oct-04 Dec-04
 
 179
products were transported approximately 90-100cm through the soil profile (or less if the 
nitrification occurred below the surface) to the pan lysimeter. 
A plausible explanation for this initial spike (albeit a low level spike) in 
concentration and ensuing subsidence would be the disturbance during installation of the 
pan lysimeter of the thick vegetative cover that was established at the control subplot.  
According to a University of Wisconsin-Extension Fact Sheet (Korb, et al., 1999), grass 
clippings are organic fertilizers with 3-4% nitrogen on a dry weight basis, and grass 
clippings from a 1,000ft2 (92.9m2) lawn would supply 0.25 lbs (0.11kg) of nitrogen.  The 
surface area disturbed when the installation trench was dug for the pan lysimeter 
installation was approximately 3m x 1.5 m = 4.5m2.  This represents 5% of the 92.9m2 
surface area that supplied 0.11kg of nitrogen.  Therefore, the disturbed area could supply 
approximately 0.005kg (500mg) of nitrogen.  Dependent upon the rate of decomposition, 
rainfall, flow paths in the subsurface profile, and other environmental factors, it is 
feasible that some portion of this nitrogen could have been converted to water-soluble 
nitrite and been transported to the pan to produce a final concentration level of 1mg/L.  
Because no biosolids were applied to the control site, this initial grass cover would likely 
be the only appreciable source of nitrogen, though other forms of organic matter 
(organisms, etc.) in the vegetative cover or in the disturbed soil profile could also 
contribute nitrogen.  Consequently, the decrease and eventual absence of nitrite in the pan 
lysimeter samples over time is logical. 
Provided conditions were favorable for the Nitrobacter (and other) organisms that 
convert nitrite to nitrate, it is more likely that nitrate would be present in higher 
concentrations than nitrite, since the conversion from nitrite to nitrate is usually rapid.  
 
 180
Therefore, the subsequent section presenting results on nitrate will also examine the 
values for these same samples. 
It is worthwhile to point out that the nitrite results from the other two controls were 
non-detects or near non-detects for quarters 1 and 2, with a slightly higher result for both 
blocks in quarter 3 (0.02mg/L) and oscillations between non-detects and 0.05 mg/L over 
quarters 4-8.  Such low levels are representative of background levels.  It might be 
expected that the same vegetative cover disturbance in these other two controls should 
produce the same spike in concentration.  The hydraulic conductivities in the uppermost 
layer (30-40cm) of these subplot surfaces, however, were 1.0x10-6 cm/sec for control 
block 1 and 1.8x10-5 cm/sec for control block 3, which is much lower than the shallow 
depth conductivity of 2.3x10-4 cm/sec for control block 2.  Consequently, flow through 
these two subplots proceeded at slower rates than in control block 2.  This could allow 
more time for conversion of nitrite to nitrate followed by immobilization or 
denitrification.  It also could be that the disturbed vegetative cover at these control plots 
decomposed at the surface and were washed to another location during a storm event, or 
that any decomposition products percolated outside the pan lysimeter area. 
It is also important to note that although cover vegetation was a potential source of 
nitrogen at the control subplots, a vegetative cover was not present over the plots in 
which the biosolids were applied, because the site had been leveled and any cover 
destroyed months before the biosolids application commenced. 
The second incidence of nitrite values >1.0 mg/L occurred in quarter 1 at one of the 
three 19,650 kgN/ha; 0 trees/ha subplots (the block 2 subplot, subplot ID = 2I).  After this 
initial higher average value of 1.69 mg/L, concentrations oscillated between non-detects 
 
 181
and 0.02 mg/L.  Concentrations in the other two subplots associated with blocks 1 and 3 
oscillated between non-detects and 0.07 mg/L.  This level of nitrogen could be associated 
with nitrite present in the biosolids at the time of application or nitrite that was formed 
from the ammonium present in the biosolids.  Evaluation of pan installation 
documentation indicates nothing out of the ordinary (i.e., no disturbance or difficulty 
during the installation process that could have created an out of the ordinary flow path or 
source of nitrification).  Sample collection was also routine, with approximately 3000mL 
of volume collected for the sample associated with quarter 1.  As with other incidences of 
notable nitrite values, the nitrate concentrations associated with this sample will be 
evaluated. 
The third group of nitrite values > 1.0 mg/L occurred in greater quantity than the 
prior two incidences, and are associated with the 58,900 kgN/ha; 0 trees/ha treatment.  
The highest values (those >1.0 mg/L) are all associated with the block 2 subplot (ID = 
2C).  These high values were as follows:  q3 = 3.8mg/L; q4 = 1.3mg/L; q6 = 4.0mg/L; q7 
= 13.2 mg/L; q8 = 30.2mg/L.  Sample was not available for q5 because no water had 
flowed into the pan during this quarter (i.e., from March-May, 2004).  Pan lysimeter 
collections from this subplot were characterized by low volumes (< 125mL), which could 
result in greater concentration of solutes per unit volume.  Sample pH ranged from 7.5-
8.12, which indicates that some high pH leachate from the limed biosolids reached the 
pan. 
Overall, Figure 115 shows an increase in nitrite concentration over time for the 
interval considered (i.e., Q1-Q8 = April 2003-December 2004).  It is evident that a source 
of nitrite was available to subplot 2C.  The other two subplots associated with this 
 
 182
application rate by tree density combination (1I and 3F) produced lower values that 
ranged between non-detects and 0.5 mg/L.  These subplots also captured larger volumes 
of leachate than subplot 2C (750-10,000mL for 1I; 75-225mL for 3F) and pH levels were 
in a more neutral range (6.91-7.15 for 1I; 6.25-7.0 for 3F).  Nitrate concentrations will be 
evaluated in conjunction to determine if conversion to nitrate is occurring as well. 
Statistical Analysis 
As with ammonium, statistical analysis encompassed evaluation of the following 
interactions for significance: 
? Application rate 
? Tree density 
? Application rate by tree density 
? Quarter 
? Application rate by quarter 
? Tree density by quarter 
? Application rate by tree density by quarter 
When evaluating the results, the more complex statistically significant interactions 
were first considered because they impart more detail on what experimental condition is 
influencing the differences most.  In addition, the more complex interaction will capture 
any of the simpler interactions represented by the included conditions. 
Statistical analysis of pan lysimeter results showed significant effects for 1) 
application rate by tree density interactions and 2) quarterly time intervals.  Further 
evaluation through LSD showed the 58,900 kgN/ha by 0 trees/ha combination to be 
significantly different from all other application rate by tree density combinations, which 
 
 183
is not surprising, given the results shown in Figures 113-115.  No other application rate 
by tree density combinations were different from one another (including controls).  
Quarterly differences were general, and showed quarters 3, 4, 5, and 6 to be lower than 
quarters 7 and 8.  The scatter plot of nitrite results shown in Figure 116 below highlights 
these findings. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 116.  Scatter plot of nitrite quarterly average results for pan lysimeters. 
 
 
The plot clearly demonstrates a trend of 58,900 kgN/ha; 0 Trees/ac results that are 
markedly higher than all other values for most quarters.  It is also apparent that the results 
from all treatments have lower overall values in quarters 3, 4, 5, and 6 compared to 
quarters 1, 2, 7 and 8, with quarters 7 and 8 being different enough the elicit a statistically 
significant response. 
0.00
0.01
0.10
1.00
10.00
100.00
0 1 2 3 4 5 6 7 8 9
Quarter
NO
2-  
(m
g/L
)   
   
Lo
g T
ra
ns
for
me
dn
 n 
  
58,900 kgN/ha; 0 trees/ha 58,900 kgN/ha; 716 trees/ha 58,900 kgN/ha; 1074 trees/ha
19,650 kgN/ha; 0 trees/ha 19,650 kgN/ha; 716 trees/ha 19,650 kgN/ha; 1074 trees/ha
39,300 kgN/ha; 0 trees/ha 39,300 kgN/ha; 716 trees/ha 39,300 kgN/ha; 1074 trees/ha
0 kgN/ha; 0 trees/ha
Q3, 4, 5, and 6 are significantly lower than Q7 and 8
58,900 kgN/ha; 0 Trees/ac is significantly different from all 
other Application Rate/Tree Density Combinations.  No other 
combinations are significantly different.
 
 184
Suction Lysimeter Samples 
Of the 1453 results generated from the suction lysimeters, 1448 (99.6%) were less 
than the EPA NO2-N MCL of 1.0 mg/L.  The six remaining results ranged from 1.0-32 
mg/L, similar to the pans.  All quarterly results are shown in Figures 117-125 below.  
Data plots show quarterly values for each block and depth.  The initial data plot with all 
four quarters represented is included to provide an overall view of results over time.  
Because of the number of data points, however, the resolution of individual application 
rate by tree density combinations was compromised.  Consequently, the bar charts are 
further separated into two charts, each of which includes two quarters.  Within these 
charts, quarter, block and position designations are noted.  Because of the preponderance 
of low-level results, all figures use a logarithmic scale to present the data. 
Recall that five suction lysimeters were installed within each of the 30 subplots.  
Three capture vertical flow and were positioned 15, 30, and 60 cm underneath the bottom 
of the biosolids rows.  Two others were positioned 15 and 30cm lateral from the edge of a 
biosolids row at a depth equal to the bottom of the biosolids row (Figure 6).  In the bar 
charts and tables that follow, these positions are indicated as PV15, PV30, PV60, PL15, 
and PL30, respectively.  As a reminder, the time periods associated with each of the 
suction lysimeter quarterly designations include: 
Q4 = November 2003 ? February 2004 
Q5 = March 2004 ? May 2004 
Q6 = June 2004 ? August 2004 (recall that samples were not collected in July) 
Q7 = October 2004 ? December 2004 (recall that samples were not collected in 
November). 
  
185
  
            
        
        
Fig
ure
 117.  N
itri
te qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 low
-le
ve
l a
ppl
ica
tion r
ate
 in s
uc
tion l
ysi
me
ter
 (S
L)
 sa
mpl
es ? a
ll qua
rte
rs.
 
0.0
0
0.0
1
0.1
0
1.0
0
10
.00
Q4-B1-PV15Q4-B1-PV30
Q4-B1-PV60Q4-B1-PL15
Q4-B1-PL30Q4-B2-PV15
Q4-B2-PV30Q4-B2-PV60
Q4-B2-PL15Q4-B2-PL30
Q4-B3-PV15Q4-B3-PV30
Q4-B3-PV60Q4-B3-PL15
Q4-B3-PL30Q5-B1-PV15
Q5-B1-PV30Q5-B1-PV60
Q5-B1-PL15Q5-B1-PL30
Q5-B2-PV15Q5-B2-PV30
Q5-B2-PV60Q5-B2-PL15
Q5-B2-PL30Q5-B3-PV15
Q5-B3-PV30Q5-B3-PV60
Q5-B3-PL15Q5-B3-PL30
Q6-B1-PV15Q6-B1-PV30
Q6-B1-PV60Q6-B1-PL15
Q6-B1-PL30Q6-B2-PV15
Q6-B2-PV30Q6-B2-PV60
Q6-B2-PL15Q6-B2-PL30
Q6-B3-PV15Q6-B3-PV30
Q6-B3-PV60Q6-B3-PL15
Q6-B3-PL30Q7-B1-PV15
Q7-B1-PV30Q7-B1-PV60
Q7-B1-PL15Q7-B1-PL30
Q7-B2-PV15Q7-B2-PV30
Q7-B2-PV60Q7-B2-PL15
Q7-B2-PL30Q7-B3-PV15
Q7-B3-PV30Q7-B3-PV60
Q7-B3-PL15Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
N O 2 -  ( m g / L )
L o g a r i t h m i c  S c a l e
0 k
gN
/ha
; 0
 tre
es/h
a
19
,65
0 k
gN
/ha
; 0
 tre
es/h
a
19
,65
0 k
gN
/ha
; 7
16
 tre
es/
ha
19
,65
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
186
                    Fig
ure
 118.  N
itri
te qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 low
-le
ve
l a
ppl
ica
tion r
ate
 in S
L 
sam
ple
s: Q
4&
Q5. 
                      Fig
ure
 119.  N
itri
te qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 low
-le
ve
l a
ppl
ica
tion r
ate
 in S
L 
sam
ple
s: Q
6&
Q7.
 
0.0
0
0.0
1
0.1
0
1.0
0
10
.00
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-
Po
sit
ion
 ID
NO2- (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 7
16
 tre
es/
ha
19
,65
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
0.0
0
0.0
1
0.1
0
1.0
0
10
.00
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Qu
ar
ter
-B
loc
k-
Po
sit
ion
 ID
NO2- (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 7
16
 tre
es/
ha
19
,65
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
187
                              Fig
ure
 120.  N
itri
te qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 m
id-
leve
l a
ppl
ica
tion r
ate
 in s
uc
tion l
ysi
me
ter
 (S
L s
am
ple
s) ? a
ll qua
rte
rs.
 
0.0
0
0.0
1
0.1
0
1.0
0
Q4-B1-PV15Q4-B1-PV30
Q4-B1-PV60Q4-B1-PL15
Q4-B1-PL30Q4-B2-PV15
Q4-B2-PV30Q4-B2-PV60
Q4-B2-PL15Q4-B2-PL30
Q4-B3-PV15Q4-B3-PV30
Q4-B3-PV60Q4-B3-PL15
Q4-B3-PL30Q5-B1-PV15
Q5-B1-PV30Q5-B1-PV60
Q5-B1-PL15Q5-B1-PL30
Q5-B2-PV15Q5-B2-PV30
Q5-B2-PV60Q5-B2-PL15
Q5-B2-PL30Q5-B3-PV15
Q5-B3-PV30Q5-B3-PV60
Q5-B3-PL15Q5-B3-PL30
Q6-B1-PV15Q6-B1-PV30
Q6-B1-PV60Q6-B1-PL15
Q6-B1-PL30Q6-B2-PV15
Q6-B2-PV30Q6-B2-PV60
Q6-B2-PL15Q6-B2-PL30
Q6-B3-PV15Q6-B3-PV30
Q6-B3-PV60Q6-B3-PL15
Q6-B3-PL30Q7-B1-PV15
Q7-B1-PV30Q7-B1-PV60
Q7-B1-PL15Q7-B1-PL30
Q7-B2-PV15Q7-B2-PV30
Q7-B2-PV60Q7-B2-PL15
Q7-B2-PL30Q7-B3-PV15
Q7-B3-PV30Q7-B3-PV60
Q7-B3-PL15Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
N O 2 -  ( m g/ L )
L ogar i t h m i c  S c al e
0 k
gN
/ha
; 0
 tre
es/h
a
39
,30
0 k
gN
/ha
; 0
 tre
es/h
a
39
,30
0 k
gN
/ha
; 7
16
 tre
es/
ha
39
,30
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
188
                    Fig
ure
 121.  N
itri
te qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 m
id-
leve
l a
pp. r
ate
 for
 SL
 
sam
ple
s: Q
4&
Q5. 
                     Fig
ure
 122.  N
itri
te qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 m
id-
leve
l a
pp. r
ate
 for
 SL
 
sam
ple
s: Q
6&
Q7. 
 
0.0
0
0.0
1
0.1
0
1.0
0
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
NO2- (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 7
16
 tre
es/
ha
39
,30
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
0.0
0
0.0
1
0.1
0
1.0
0
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
NO2- (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 7
16
 tre
es/
ha
39
,30
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
189
                              Fig
ure
 123.  N
itri
te qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 hi
gh-
leve
l a
ppl
ica
tion r
ate
 in s
uc
tion l
ysi
me
ter
 (S
L)
 sa
mpl
es ? a
ll qua
rte
rs.
 
0.0
0
0.0
1
0.1
0
1.0
0
10
.00
10
0.0
0
Q4-B1-PV15Q4-B1-PV30
Q4-B1-PV60Q4-B1-PL15
Q4-B1-PL30Q4-B2-PV15
Q4-B2-PV30Q4-B2-PV60
Q4-B2-PL15Q4-B2-PL30
Q4-B3-PV15Q4-B3-PV30
Q4-B3-PV60Q4-B3-PL15
Q4-B3-PL30Q5-B1-PV15
Q5-B1-PV30Q5-B1-PV60
Q5-B1-PL15Q5-B1-PL30
Q5-B2-PV15Q5-B2-PV30
Q5-B2-PV60Q5-B2-PL15
Q5-B2-PL30Q5-B3-PV15
Q5-B3-PV30Q5-B3-PV60
Q5-B3-PL15Q5-B3-PL30
Q6-B1-PV15Q6-B1-PV30
Q6-B1-PV60Q6-B1-PL15
Q6-B1-PL30Q6-B2-PV15
Q6-B2-PV30Q6-B2-PV60
Q6-B2-PL15Q6-B2-PL30
Q6-B3-PV15Q6-B3-PV30
Q6-B3-PV60Q6-B3-PL15
Q6-B3-PL30Q7-B1-PV15
Q7-B1-PV30Q7-B1-PV60
Q7-B1-PL15Q7-B1-PL30
Q7-B2-PV15Q7-B2-PV30
Q7-B2-PV60Q7-B2-PL15
Q7-B2-PL30Q7-B3-PV15
Q7-B3-PV30Q7-B3-PV60
Q7-B3-PL15Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
N O 2 -  ( m g/ L )
L ogar i t h m i c  S c al e
0 k
gN
/ha
; 0
 tre
es/h
a
58
,90
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 7
16
 tre
es/h
a
58
,90
0 k
gN
/ha
; 1
07
4 tr
ees
/ha
  
190
                    Fig
ure
 124.  N
itri
te qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 hi
gh-
leve
l a
pp. r
ate
 for
 SL
 
sam
ple
s: Q
4&
Q5. 
                      Fig
ure
 125.  N
itri
te qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 hi
gh-
leve
l a
pp. r
ate
 for
 SL
 
sam
ple
s: Q
6&
Q7. 
0.0
0
0.0
1
0.1
0
1.0
0
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
NO2- (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 7
16
 tre
es/
ha
58
,90
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
0.0
0
0.0
1
0.1
0
1.0
0
10
.00
10
0.0
0
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
os
itio
n I
D
NO2- (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 7
16
 tre
es/
ha
58
,90
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
 
 191
 
When individual position values for each subplot were averaged within each quarter, 
the 1453 results were consolidated to 562 results.  This also resulted in consolidation of 
the initial six values to three values that were greater than 1.0 mg/L.  These three values 
(with accompanying monthly values) included: 
? 1.23 mg/L for 19,650 kgN/ha; 0 trees/ha for Q7-B1-PL15 (quarter 7, block 1, lateral 
SL 15cm from the side of the biosolids row, subplot ID=1F).  Monthly values for 
quarter 7 were 2.37 mg/L for October 2004 and 0.09 mg/L for December 2004. 
? 1.39 mg/L for 19,650 kgN/ha; 716 trees/ha for Q7-B1-PV30 (quarter 7, block1, 
vertical SL 30cm below the biosolids row, subplot ID=1D).  Monthly values for 
quarter 7 were 1.57 mg/L for October 2004 and 1.21 for December 2004. 
? 27.8 mg/L for 58,900 kgN/ha; 716 trees/ha for Q7-B1-PL15 (quarter 7, block 1, 
lateral SL 15cm from the side of the biosolids row, subplot ID=1G).  Monthly values 
were 32.1 mg/L for October 2004 and 23.5 mg/L for December 2004. 
All values are associated with quarter 7.  Individual October and December values 
from quarter 7 were both greater than 1 mg/L with the exception of the December 2004 
value for Q7-B1-PL15.  Values for the prior three quarters were all less than 1 mg/L.  
Values are associated with both laterally and vertically positioned suction lysimeters.  
The only commonality between these results and those from the pan lysimeters is the 
19,650 kgN/ha; 0 trees/ha application, though the quarter and block are different from the 
single pan lysimeter high value from that treatment.  Data from future analyses will need 
to be evaluated to determine whether or not these higher values signal the start of a trend, 
or are isolated incidents.  Due to the fact that these represent an extremely small number 
of values from the experiment, the overriding conclusion is that insignificant amounts of 
 
 192
nitrite are present in the soil profile.  Nitrate values for these samples will also be 
evaluated to determine if complete nitrification occurred. 
Rainfall Flushing Effect 
As with the high concentration ammonium samples, the five monthly nitrite values 
greater than 1 m/L were also evaluated to determine if they reflect a flushing effect from 
storm events.  The protocol used was described in the ammonium results section.  Of the 
five results identified, all of which were from block 1, subplots 1D, 1F and 1G, only 1 
(i.e., 20%) was linked to a storm event.  It therefore does not appear that a flushing effect 
was responsible for the higher nitrite results. 
Statistical Analysis 
As with the ammonium results, the same interactions were statistically analyzed and 
included: 
? Application rate 
? Tree density 
? Application rate by tree density 
? Position 
? Application rate by position 
? Tree density by position 
? Application rate by tree density by position 
? Quarter 
? Application rate by quarter 
? Tree density by quarter 
? Application rate by tree density by quarter 
 
 193
? Position by quarter 
? Application rate by position by quarter 
? Tree density by position by quarter 
? Application rate by tree density by quarter. 
When evaluating the results, the more complex statistically significant interactions 
were first considered because they impart more detail on what experimental condition is 
influencing the differences most.  In addition, the more complex interaction will also 
capture any of the simpler interactions represented by the included conditions. 
Statistical analysis showed no significant differences (? = 0.05) between any of the 
application rate or tree density combinations (including controls) and no significant 
differences for any of these treatments over time.  Statistically significant differences did 
occur, however, for position by quarter interactions both within and between positions.  A 
comparison within each position across quarters does show an increase in concentrations 
from quarters 4 and/or 5 to quarters 6 and/or 7, though in many of these instances, the 
trend is not completely sequential over all quarters.  Within position differences are 
visually depicted in Figures 126-130.  It is important to note that these trends are general 
across all experimental conditions and are not associated with a specific application rate 
or tree density. 
 
 194
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 126.  Nitrite quarterly average results:  Suction lysimeter 15 cm vertical position-
within position differences. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 127.  Nitrite quarterly average results:  Suction lysimeter 30 cm vertical position-
within position differences. 
 
0.00
0.01
0.10
1.00
3 4 5 6 7 8
Quarter
NO
2-
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
Q5 is lower than Q6 and Q7
Q4 is lower than Q5, 6, and 7
(Nov. 2003-
Feb. 2004)
(March-May 
2004)
(June&August 
2004)
(Oct.&Dec. 
2004)
0.00
0.01
0.10
1.00
10.00
3 4 5 6 7 8
Quarter
NO
2-
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
Q4 and Q6 are lower than Q7
Q5 is lower than Q6 and 7
(Nov. 2003-
Feb. 2004)
(March-May 
2004)
(June&Aug. 
2004)
(Oct.&Dec. 
2004)
 
 195
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 128.  Nitrite quarterly average results:  Suction lysimeter 60 cm vertical position-
within position differences. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 129.  Nitrite quarterly average results:  Suction lysimeter 15 cm lateral position-
within position differences. 
0.00
0.01
0.10
1.00
3 4 5 6 7 8
Quarter
NO
2-
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
Q4 is lower than Q7
Q5 is lower than Q6 and Q7
(Nov. 2003-
Feb. 2004)
(March-May 
2004)
(June&Aug. 
2004)
(Oct.&Dec. 
2004)
0.00
0.01
0.10
1.00
10.00
100.00
3 4 5 6 7 8
Quarter
NO
2-
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
Q4 and Q5 are lower than Q7
Q5 is lower than Q6 and Q7
(Nov. 2003-
Feb. 2004)
(March-May 
2004)
(June&Aug. 
2004)
(Oct.&Dec. 
2004)
 
 196
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 130.  Nitrite quarterly average results: Suction lysimeter 30 cm lateral position-
within position differences. 
 
 
Although statistically significant differences (? = 0.05) were noted for each position 
over time, and in general those trends show higher levels in later quarters compared to 
earlier quarters, these charts depict an overriding facet of the data:  comparisons mostly 
involve such low levels that the differences noted are inconsequential.  As previously 
stated, controls were no different than any other application rate and tree density 
combinations.  With the exception of a couple of higher values, all of these results are 
equivalent to background levels. 
Statistically significant differences (? = 0.05) also were established between 
positions over different quarters.  In general, the 15cm vertical position (PV15) values 
across all quarters were greater than many of the values from the other positions over all 
quarters.  The 30 cm vertical position (PV30) values also exhibited some significant 
0.00
0.01
0.10
1.00
3 4 5 6 7 8
Quarter
NO
2-
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
Q4,5 and 6 are lower than Q7
(Nov. 2003-
Feb. 2004)
(March-May 
2004)
(June&Aug. 
2004)
(Oct.&Dec. 
2004)
 
 197
differences (?from the 15cm and 30 cm lateral position (PL15 and PL30) values across 
quarters.  Differences between PV60, PL15 and PL30 were not notable.  What these 
results show is not a particular increase or decrease over time, but more a trend of 
relatively higher values in the suction lysimeters positioned closest to the biosolids rows.  
As was noted above, however, all values were extremely low, such that the differences 
noted do not bear any applied significance.  A comparison of the values for the vertical 
suction lysimeters across quarters is provided in Figure 131 to show the relatively higher 
values of PV15 compared to PV30 and PV60.  Figure 132 provides a comparison of the 
PV15 position to the lateral positions (PL15 and PL30). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 131.  Nitrite suction lysimeter quarterly average results:  comparison of vertical 
positions over time. 
 
 
 
0.00
0.01
0.10
1.00
10.00
3 4 5 6 7 8
Quarter
NO
2-  
(m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
15cm vertical 30cm vertical 60cm vertical
(March-May 
2004)
(Nov. 2003-
Feb. 2004)
(June&Aug. 
2004)
(Oct.&Dec. 
2004)
 
 198
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 132.  Nitrite suction lysimeter quarterly average results:  comparison of vertical 
15cm position to lateral positions over time. 
 
 
The figures above depict trends in which the PV15 values, though not always higher 
than all values from other positions, do show a greater frequency of values in higher 
concentration ranges than the other positions. 
Conclusions 
Overall, nitrite concentrations were low, with suction lysimeter samples exhibiting 
slightly lower values that those from the pan lysimeters.  For pan lysimeters, the 58,900 
kg N/ha-0 trees/ha combination produced significantly higher values than all other 
application rate-tree density combinations, though thus far the high values are associated 
with only one of the three replicates for this treatment.  All other application rate-tree 
0.00
0.01
0.10
1.00
10.00
100.00
3 4 5 6 7 8
Quarter
NO
2-  
(m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
15cm vertical 15cm lateral 30cm lateral
(March-May 
2004)
(Nov. 2003-
Feb. 2004)
(June&Aug. 
2004)
(Oct.&Dec. 
2004)
 
 199
density combinations, including controls, were not statistically different from one 
another.  A very general trend of quarterly results potentially increasing over time was 
determined statistically, but applied to all experimental conditions collectively (i.e., no 
application rate and/or tree density by quarter interactions were significant). 
Suction lysimeter results showed no significant differences (? = 0.05) between or 
within application rate and/or tree density (including controls), nor were differences 
found for application rate and/or tree density over time.  Some differences were noted 
within and between suction lysimeter positions.  Within a position, concentrations from 
earlier quarters (Q4 and Q5) were sometimes different from the latter quarters (Q6 and 
Q7), though not consistently so.  Across positions, differences were more a product of 
position rather than exhibiting a trend over quarters.  In general, PV15 results contained 
the greatest frequency of higher values than other positions.  A spike in values during 
quarter 7 (October-December 2004) for the 15 cm lateral suction lysimeter in one 
replicate of the 58,900 kgN/ha-716 trees/ha treatment may indicate the presence of 
mineralization, though future collection events will need to be evaluated to determine if a 
trend forms. 
Though the above-noted statistical differences were ascertained, the overriding 
conclusion is that nitrite values were so low across all experimental conditions that they 
are not considered to have any applied significance. 
 
 
 200
Soil Water Results:  Nitrate (NO3-) Data 
Nitrate is the final product of the two-step nitrification process that oxidizes 
ammonia to nitrite and then nitrate.  The transition from nitrite to nitrate is usually rapid, 
provided conditions are suitable for the Nitrobacter (and other) bacteria that perform the 
conversions.  Similar to Nitrosonomas, these conditions include:  the presence of nitrite, 
oxygen, a carbon source in the form of carbon dioxide or bicarbonates, appropriate 
temperature, pH, and absence of toxic compounds.  Once nitrate is produced, it can be:  
immobilized by microbes; consumed by the poplar trees; converted to gaseous forms via 
denitrification processes; and/or leach through the soil profile with the flow of water.  
Collection of samples over time from both pan and suction lysimeters in close proximity 
to the biosolids rows provides an evaluation of the occurrence and transport of nitrate in 
the soil at this site. 
Pan Lysimeter Samples 
Pan lysimeter results show consistently low levels of nitrate across all treatments, 
with few exceptions.  Of the 426 results generated, 423 (99%) were less than the EPA 
drinking water MCL of 10 mg/L.  The three remaining results above 10 mg/L ranged 
between 13.7 ? 37.6 mg/L.  When individual subplot values were averaged within each 
quarter, the 426 results were consolidated to 220 results.  Depictions of quarterly results 
for each block are provided in Figures 133-135.  To provide further insight into the lower 
level values, results are plotted on a logarithmic scale. 
 
 201
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 133.  Nitrate quarterly average concentrations for low-level application rate in pan 
lysimeters. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 134.  Nitrate quarterly average concentrations for mid-level application rate in pan 
lysimeters. 
0.00
0.01
0.10
1.00
10.00
100.00
Q1-
B1
Q1-
B2
Q1-
B3
Q2-
B1
Q2-
B2
Q2-
B3
Q3-
B1
Q3-
B2
Q3-
B3
Q4-
B1
Q4-
B2
Q4-
B3
Q5-
B1
Q5-
B2
Q5-
B3
Q6-
B1
Q6-
B2
Q6-
B3
Q7-
B1
Q7-
B2
Q7-
B3
Q8-
B1
Q8-
B2
Q8-
B3
Quarter-Block ID
NO
3-  
(m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
0 kgN/ha; 0 trees/ha
19,650 kgN/ha; 0 trees/ha
19,650 kgN/ha; 716 trees/ha
19,650 kgN/ha; 1074 trees/ha
Dec-04Oct-04Jun/Aug 
04
Mar-May-04Dec-03, Jan/Feb-04Sept-Nov-03Jun-Aug-03Apr-May-03
0.00
0.01
0.10
1.00
10.00
100.00
Q1-
B1
Q1-
B2
Q1-
B3
Q2-
B1
Q2-
B2
Q2-
B3
Q3-
B1
Q3-
B2
Q3-
B3
Q4-
B1
Q4-
B2
Q4-
B3
Q5-
B1
Q5-
B2
Q5-
B3
Q6-
B1
Q6-
B2
Q6-
B3
Q7-
B1
Q7-
B2
Q7-
B3
Q8-
B1
Q8-
B2
Q8-
B3
Quarter-Block ID
NO
3-  
(m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
0 kgN/ha; 0 trees/ha
39,300 kgN/ha; 0 trees/ha
39,300 kgN/ha; 716 trees/ha
39,300 kgN/ha; 1074 trees/ha
Dec-04Oct-04Jun/Aug 
04
Mar-May-04Dec-03, 
Jan/Feb-04
Sept-Nov-03Jun-Aug-03Apr-May-03
 
 202
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 135.  Nitrate quarterly average concentration for high-level application rate in pan 
lysimeters. 
 
 
Focusing on those values close to and greater than 1mg/L, the following results 
shown in Table 22 below, sorted by application rate and tree density, warrant a closer 
look. 
0.00
0.01
0.10
1.00
10.00
100.00
Q1-
B1
Q1-
B2
Q1-
B3
Q2-
B1
Q2-
B2
Q2-
B3
Q3-
B1
Q3-
B2
Q3-
B3
Q4-
B1
Q4-
B2
Q4-
B3
Q5-
B1
Q5-
B2
Q5-
B3
Q6-
B1
Q6-
B2
Q6-
B3
Q7-
B1
Q7-
B2
Q7-
B3
Q8-
B1
Q8-
B2
Q8-
B3
Quarter-Block ID
NO
3-  
(m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
0 kgN/ha; 0 trees/ha
58,900 kgN/ha; 0 trees/ha
58,900 kgN/ha; 716 trees/ha
58,900 kgN/ha; 1074 trees/ha
Apr-May-03 Jun-Aug-03 Sept-Nov-03 Dec-03, Jan/Feb-04 Mar-May-04 Jun/Aug 
04
Oct-04 Dec-04
 
 203
Table 22.  Nitrate pan lysimeter results close to and greater than 1 mg/L. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
The subplot with the highest consecutive results is the control from block 2 (subplot 
ID=4B).  These higher results from quarters 1 and 2 are consistent with those presented 
for nitrite values in the previous section.  As previously explained, because biosolids 
were not applied to the control sites, another source of nitrogen had to account for the 
surge in concentration.  The most likely candidate is the vegetation that covered the 
subplot area prior to installation of the pan lysimeter.  Concentrations continued to 
decline in quarter 3, with a value of 0.05 mg/L, and then oscillated between non-detects 
and 0.03 mg/L during the rest of the time covered, as is shown in either of Figures 133-
135.  Results from controls in the other two blocks ranged between non-detects and a 
maximum of 0.12 mg/L, reflecting low level background concentrations.  Figure 136 
below presents these control values by each block over the eight quarters. 
Subplot 
ID Block
App. 
Rate 
(kgN/ha)
Tree 
Density 
(trees/ha) quarter Time Period
# monthly 
results 
averaged
NO3-N 
Mean
4B 2 0 0 1 April-May 2003 1 37.59
4B 2 0 0 2 June-Aug. 2003 3 6.38
1E 1 19,650 1074 7 October 2004 1 1.20
3I 3 39,300 0 1 April-May 2003 1 0.72
1B 1 39,300 1074 4 Dec. 2003-Feb. 2004 3 0.61
1B 1 39,300 1074 5 March-May 2004 3 0.87
1B 1 39,300 1074 6 June-Aug. 2004 2 0.63
3G 3 39,300 1074 8 December 2004 1 0.65
2C 2 58,900 0 3 Sept.-Nov. 2003 2 0.94
2C 2 58,900 0 4 Dec. 2003-Feb. 2004 2 0.74
2C 2 58,900 0 6 June-Aug. 2004 1 2.54
2C 2 58,900 0 7 October 2004 1 2.16
2C 2 58,900 0 8 December 2004 1 3.50
2A 2 58,900 716 1 April-May 2003 1 3.65
2B 2 58,900 1074 1 April-May 2003 1 13.66
 
 204
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 136.  Nitrate:  Pan lysimeter average quarterly values for each control subplot. 
 
 
Isolated higher-level values were evidenced for subplots 1E, 3I, 2A, and 2B.  Most 
of these values were well below any level of concern, but subplot 2B exhibited a 
concentration of 13.7 mg/L, which exceeds the EPA NO3-N drinking water MCL of 10 
mg/L.  Although it is not a goal of this operation to produce leachate in close proximity to 
the biosolids that meets drinking water standards, such limits are a good benchmark for 
discussing potential environmental concerns.  All other results from both this subplot and 
the other two at the 58,900 kgN/ha-1074 trees/ha treatment produced low-level results 
ranging from non-detects to 0.09 mg/L.  Nitrite values were low for this subplot as well.  
Suction lysimeter results will be evaluated to determine if they reflect this apparent 
isolated event in subplot 2B. 
0.001
0.010
0.100
1.000
10.000
100.000
0 1 2 3 4 5 6 7 8 9
Quarter
NO
3-
 (m
g/L
) 
Lo
ga
rit
hm
ic 
Sc
ale
Control, Block 1 (4C)
Control, Block 2 (4B)
Control, Block 3 (4A)
 
 205
Two application rate/tree density combinations showed slightly elevated results over 
multiple quarters.  The first set includes data from the 39,300 kgN/ha-1074 trees/ha 
treatment (specifically subplots 1B and 3G), which collectively produced nitrate results 
ranging from 0.61-0.87 mg/L during quarters 4, 5, 6, and 8.  All other results for all three 
subplots ranged from non-detects to 0.14 mg/L.  Though not discussed in the nitrite 
section because results were so low, nitrite results did show a similar, though less 
prevalent pattern for this treatment.  In quarters 5 and 6, subplot 1B produced nitrite 
concentrations of 0.14 and 0.20 mg/L, respectively.  Although these levels are not of 
concern, they are slightly higher than the other results for this treatment.  Consequently, 
some nitrification may have occurred. 
The second set includes results from a single subplot associated with the 58,900 
kgN/ha-0 trees/ha treatment (subplot 2C).  As previously shown in Table 22, results 
increased with time from quarters 3 through 8.  This pattern is also similar to those for the 
nitrite results, although in this instance the nitrite values were higher than nitrate.  Given 
the usual rapid conversion of nitrite to nitrate as it is being produced, nitrite is typically 
present at lower levels than nitrate.  This transposition indicates that either 1) the sample 
was collected at the specific time when the nitrite was produced and had not yet been 
converted to nitrate, 2) as soon as nitrate was being produced, it encountered an anaerobic 
microsite and underwent denitrification and/or 3) the conversion of nitrite to nitrate was 
inhibited. 
Inhibition could occur if conditions were more hostile to the Nitrobacter population 
(i.e., the microbes that convert nitrite to nitrate) than the Nitrosonomas population (i.e., 
the microbes that convert ammonium to nitrite).  Elevated salt concentrations, as are 
 
 206
present in the leachate from heavily limed biosolids, are known to inhibit microbial 
growth (Haynes, 1986).  Haynes (1986) also reported that high ammonium 
concentrations have been shown to selectively inhibit Nitrobacter species.  The 
maximum tolerable ammonium concentrations under which nitrification would still occur 
(specifically the conversion of nitrite to nitrate) was 400-800 mg/kg.  As is evident from 
the prior discussion of ammonium results, concentrations in the biosolids as well as the 
leachate traveling to the pan lysimeters exceed these levels.  Consequently, until 
ammonium concentrations decrease either through conversion to nitrite, immobilization 
by microbes, or uptake by trees, production of nitrate will be limited in this region of the 
soil profile. 
The time periods (quarters) associated with these two sets of data cover both active 
and dormant periods in the ecosystem, and therefore do not indicate a cyclical trend.  
Overall, these levels may indicate an extremely low level of leaching nitrate that was 
either 1) present in the biosolids upon application, 2) produced when an extremely low-
level of nitrification occurred or 3) produced when a higher level of nitrification 
occurred, but the resulting nitrate was immobilized in microbial biomass or taken up by 
the poplar trees.  Regardless, these levels are not of concern from an environmental or 
health perspective. 
Statistical Analysis 
Statistical analysis evaluated the same interactions previously presented in the 
ammonium and nitrite sections.  Significant differences (?= 0.05)were determined for the 
application rate by tree density by quarter interaction, both within and between 
 
 207
application rate/tree density combinations for specific quarters.  In most cases, however, 
consistent trends were not demonstrated. 
Controls exhibited statistical differences from other treatments for specific quarters.  
Overall, the quarter 2 control results were significantly greater than multiple (but not all) 
quarters across each of the treatments.  Subsequent (but not all) quarters for the controls 
were significantly less than one or more quarters in all other treatments.  Note that 
multiple quarters for the controls were not significantly different than other treatments.  
Control results from quarter 1, in fact, were not significantly different from any other 
treatment by quarter combinations.  In summary, only isolated instances, and not an 
overall difference between the controls and other treatments, was demonstrated.  This 
supports the overall observation that nitrate concentrations in the treatments were not 
different from the controls. 
Within treatment differences were examined and are summarized in Table 23 below.  
In most instances, differences do not exhibit a repeated, sequential trend over time.  More 
often, the differences oscillate or are attributed to one or two relatively higher 
concentrations that peaked and then diminished in subsequent quarters.  The 58,900 
kgN/ha; 0 trees/ha treatment shows a potential trend towards increasing values with time, 
but additional data from later sampling quarters (beyond the scope of this thesis) would 
need to be evaluated to determine what type of trend was established.  Also note that 
neither of the other tree densities for 58,900 kgN/ha application rate show this pattern. 
 
 208
 
Table 23.  Nitrate pan lysimeter: application rate by tree density quarterly differences. 
Application Rate: Tree Density Significant Quarterly Differences 
0 lbN/ha : 0 trees/ha Q2 is greater than Q3-Q8 
19,650 kgN/ha : 0 trees/ha Q2 and Q3 are greater than Q8 
19,650 kgN/ha : 716 trees/ha Q2 and Q4 are greater than Q5 
19,650 kgN/ha : 1074 trees/ha Q2 is greater than Q4 and Q5 
Q3 is greater than Q5 
Q5 is less than Q7 
39,300 kgN/ha : 0 trees/ha Q3 is less than Q2, Q4, and Q8 
Q4 is greater than Q5, Q6 
Q5 is less than Q8 
Q6 is less than Q7 and Q8 
39,300 kgN/ha : 716 trees/ha Q2 and Q3 are greater than Q5 and Q8 
39,300 kgN/ha : 1074 trees/ha Q5 and Q7 are less than Q8 
58,900 kgN/ha : 0 trees/ha Q1, Q2, Q3, and Q4 are less than Q6 and Q8 
Q7 is less than Q8 
58,900 kgN/ha : 716 trees/ha Q1 is greater than Q3-8 
Q2 is greater than Q4, Q6, Q7, and Q8 
58,900 kgN/ha : 1074 trees/ha Q2 is greater than Q5 
 
 
Within a given application rate, statistically significant differences in tree densities 
for specific quarters were determined.  An itemized list of the differences is provided in 
Appendix 2 for reference.  For the 19,650 kg N/ha application rate, differences between 
tree densities were spotty, and did not show a particular trend.  For the 39,300 kgN/ha 
application rate, the 716 trees/ha density had the preponderance of values less than the 
other tree densities, and 1074 trees/ha were always more than the other densities.  Aside 
from this, no explicit trends were ascertained.  Finally, for the 58,900 kgN/ha application 
rate, the 0 trees/ha density had significantly greater values for multiple quarters compared 
to other densities.  This is consistent with the trend of higher values associated with this 
application rate/tree density combination, particularly in quarters 6-8. 
Between treatment differences were even more convoluted.  In general, the 
previously discussed application rate/tree density/quarter results with relatively higher 
 
 209
values (i.e., > 0.6 mg/L) than general background levels produced significant differences 
greater than the other application/rate/tree density/quarter values.  Beyond this, actual 
nitrate concentrations were so low, and not consistently different from the controls that 
these differences do not warrant further evaluation. 
Suction Lysimeter Samples 
Compared to pan lysimeter results, those from suction lysimeters show even more 
consistently low levels of nitrate across all treatments.  Of the 1454 monthly results 
generated, 1453 (99.9%) were less than the EPA drinking water MCL of 10 mg/L.  The 
one result above 10 mg/L was 12.5 mg/L.  When individual subplot values were averaged 
within each quarter, the 1454 results were consolidated to 563 results.  Results are shown 
in Figures 137-145 below.  Data plots show quarterly values for each block and depth.  
The initial data plot with all four quarters is included to provide an overall view of results 
over time.  Because of the number of data points, however, the resolution of individual 
application rate by tree density combinations was compromised.  Consequently, the bar 
charts are further separated into two charts, each of which includes two quarters.  Within 
these charts, quarter, block and position designations are noted.  Because of the 
preponderance of low-level results, all figures use a logarithmic scale to present the data. 
Recall that five suction lysimeters were installed within each of the 30 subplots.  
Three capture vertical flow and were positioned 15, 30, and 60 cm underneath the bottom 
of the biosolids rows.  Two capture vertical flow and were positioned 15 and 30cm lateral 
from the edge of a biosolids row at a depth equal to the bottom of the biosolids row 
(Figure 6).  In the bar charts and tables that follow, these positions are indicated as PV15, 
PV30, PV60, PL15, and PL30, respectively. 
 
 210
As a reminder, the time periods associated with each of the suction lysimeter 
quarterly designations include: 
Q4 = November 2003 ? February 2004 
Q5 = March 2004 ? May 2004 
Q6 = June 2004 ? August 2004 (recall that samples were not collected in July) 
Q7 = October 2004 ? December 2004 (recall that samples were not collected in 
November). 
 
 
 
 
 
  
211
                              Fig
ure
 137.  N
itra
te qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 low
-le
ve
l a
ppl
ica
tion r
ate
 in s
uc
tion l
ysi
me
ter
 (S
L)
 sa
mpl
es:
  a
ll qua
rte
rs.
 
0.0
0
0.0
1
0.1
0
1.0
0
10
.00
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-
Po
sit
ion
 ID
N O 3 -  ( m g / L )
L o g a r i t h m i c  S c a l e
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 7
16
 tre
es/
ha
19
,65
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
212
                     Fig
ure
 138.  N
itra
te qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 low
-le
ve
l a
ppl
ica
tion r
ate
 in S
L 
sam
ple
s:  Q
4&
5. 
                     Fig
ure
 139.  N
itra
te qua
rte
rly
 ave
rag
e c
onc
ent
rat
ions
 for
 low
-le
ve
l a
ppl
ica
tion r
ate
 in S
L 
sam
ple
s:  Q
6&
7. 
0.0
0
0.0
1
0.1
0
1.0
0
10
.00
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
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                              Fig
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                    Fig
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                              Fig
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                     Fig
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 217
 
As with nitrite results, nitrate values close to and greater than 1mg/L will be more 
closely examined.  The small subset of quarterly results in this category are delineated in 
Table 24 and sorted by application rate, tree density and position.  A discussion of the 
results follows. 
Table 24.  Nitrate suction lysimeter results close to and greater than 1 mg/L. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Two control subplots produced quarterly results greater than 1 mg/L (4B and 4C).  
Control subplot 4B exhibited an elevated level in quarter 5.  Elevated levels for subplot 
4B were also seen in the pan lysimeter, though these occurred in quarters 1 and 2.  
Because suction lysimeters were not yet installed when quarters 1-3 samples were 
collected for the pans, the trends seen in the pan from subplot 4B could not be directly 
compared to the SL samples.  Another control, subplot 4C, showed elevated levels in 
quarters 4 and 6.  In both subplots, concentrations reverted to lower levels (non-detects ? 
0.10 mg/L) in other quarters.  Also note that, although the position designations 
associated with the controls do correlate with specific depths below the surface, the 
lateral and vertical designations are not tied to a particular biosolids row, given that the 
controls do not contain any biosolids rows from this experiment. 
 Subplot 
ID      Block    
Application 
Rate 
(kgN/ha)
Tree 
Density 
(trees/ha) Position    quarter   Time period
# monthly 
results 
averaged
NO3-N 
Mean
SL-4B-2 2 0 0 lateral-15cm 5 March-May 2004 3 1.36
SL-4C-3 1 0 0 lateral-15cm 4 Nov. 2003-Feb. 2004 1 0.94
SL-4C-2 1 0 0 vertical-15cm 6 June-Aug. 2004 2 1.05
SL-1F-1 1 19,650 0 lateral-15cm 6 June-Aug. 2004 2 6.24
SL-1F-1 1 19,650 0 lateral-15cm 7 Oct.-Dec. 2004 2 5.29
SL-1F-2 1 19,650 0 lateral-30cm 5 March-May 2004 2 3.63
SL-1F-2 1 19,650 0 lateral-30cm 6 June-Aug. 2004 2 1.71
SL-1F-2 1 19,650 0 lateral-30cm 7 Oct.-Dec. 2004 2 2.39
SL-1F-4 1 19,650 0 vertical-60cm 7 Oct.-Dec. 2004 2 1.74
 
 218
The remaining higher nitrate values were associated with a single subplot from the 
19,650 kgN/ha-0 trees/ha treatment.  Several of the suction lysimeters in this subplot 
established higher values over quarters 6 and 7.  Although pan results did produce higher 
values for this subplot in quarters 6 and 7 compared to other quarters, values were 0.12 
and 0.35 mg/L, respectively, well under 1 mg/L.  Recall that the suction lysimeter 
samples represent soil water subject to both gravimetric and matric forces, and not just 
the gravimetric forces that primarily govern flow to the pan lysimeters.  Consequently, 
the soil water collected from the suction lysimeters is in contact with soil surfaces for 
longer time periods, potentially facilitating more chemical and biological reactions.   
The laterally positioned lysimeters produced most of these values.  It is logical that 
any mineralization would initially take place from the outermost reaches of the biosolids 
rows.  It is here that tree root systems will first establish themselves and where microbes 
are likely to find a more hospitable environment compared to conditions within the 
highly limed, salt-laden, high-pH biosolids.  The higher values for SL-1F-1 is consistent 
with the nitrite value of 1.23 mg/L previously noted for quarter 7, further indicating that 
some nitrification (albeit likely a small amount) has occurred. 
Rainfall Flushing Effect 
As with the high concentration ammonium and nitrite samples, the 10 monthly 
nitrate values greater than 1 m/L were also evaluated to determine if they reflect a 
flushing effect from storm events.  The protocol used was described in the ammonium 
results section.  Of the ten results identified, which were from subplots 1F, 4B, and 4C, 
only two (i.e., 20%) were linked to storm events.  It therefore does not appear that a 
flushing effect was responsible for the higher nitrate results. 
 
 219
Statistical Analysis 
Statistical analyses evaluated the same interactions as those previously described for 
ammonium and nitrite and showed no significant differences (? = within and between 
any of the application rate/tree density combinations, including the controls.  An overall 
difference between quarters was determined.  Quarter 4 was significantly higher than 
quarters 5-7, and quarters 5 and 7 were significantly higher than quarter 6.  The overall 
trend for quarter 4 being greater than other quarters is counter to results for subplot 1F 
shown in Table 24.  Such a general effect, however, collectively considers values from all 
application rates, tree densities and positions across each quarter.  Consequently, higher 
values from a select subplot (such as those from IF) would be overshadowed by hundreds 
of other values from the other subplots.  A scatter plot of all results by quarters 4-7 is 
presented in Figure 146 below to graphically depict these statistical results.  Results are 
separated by application rate over each quarter designation to provide for a better 
comparison across controls and the other three application rates. 
Those previously mentioned results greater than 1 mg/L stand out against the other 
clusters of results, all of which are similar in value.  Recall that these results were from 
either two replicates of the control (subplots 4B and 4C) or one replicate from the 19,650 
kgN/ha-0 trees/ha treatment (subplot 1F).  As stated above, statistical results do not show 
these treatments to be significantly different from the others.  Data collected in the future, 
however, may provide further insight regarding whether or not these higher levels 
continue. 
 
 220
 
 
 
 
 
 
 
 
 
 
 
Figure 146.  Nitrate quarterly average suction lysimeter results: general differences over 
time (quarter). 
 
 
As with the nitrite data, although data do show statistically significant differences 
(?for time, the overall implications are minimal, given the low nitrate concentrations in 
most samples.  The controls were designed to show typical background levels in soil that 
was not subjected to a recent round of biosolids application.  Control results included 
some of the relatively higher values, demonstrating that the treatment subplots were 
similar to or lower than the controls. 
To put these values in perspective, we can evaluate background nitrogen 
concentration levels previously determined at the ERCO tree farm site.  For nitrate, a 
value of 7 mg/kg was reported (Pepperman, 1995).  Assuming an average bulk density 
0.00
0.01
0.10
1.00
10.00
3 4 5 6 7 8
Quarter
NO
3-
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
19,650 kgN/ha; 0 trees/ha 19,650 kgN/ha; 716 trees/ha 19,650 kgN/ha; 1074 trees/ha
39,300 kgN/ha; 0 trees/ha 39,300 kgN/ha; 716 trees/ha 39,300 kgN/ha; 1074 trees/ha
58,900 kgN/ha; 0 trees/ha 58,900 kgN/ha; 716 trees/ha 58,900 kgN/ha; 1074 trees/ha
0 kgN/ha; 0 trees/ha
Q4 is significantly greater than Q5- Q7
 
 221
for subsoil samples ranging between 1.6-1.9 g/cm3, each kg (1000g) of soil would 
provide:  1000g/(1.6g/cm3) = 625 cm3 to 1000g/(1.9g/ cm3) = 526 cm3 of soil volume. 
Given this range in soil volume of 526-625 cm3, and assuming a volumetric water 
content between 25-50%, we can estimate the volume of water present in this given 
volume of soil.  For these volumetric water contents:   
(0.25 cm3 water/ 1 cm3 soil) * 526 cm3 soil = 131 cm3 water 
(0.25 cm3 water/ 1 cm3 soil) * 625 cm3 soil = 156 cm3 water 
(0.50 cm3 water/ 1 cm3 soil) * 526 cm3 soil = 263 cm3 water 
(0.50 cm3 water/ 1 cm3 soil) * 625 cm3 soil = 312 cm3 water 
Because nitrate is a highly water-soluble anion that is not attracted to soil particles, 
all nitrate measured in the soil sample will likely be in solution.  Consequently, the 
7mg/kg of nitrate in the soil is equal to 7 mg of nitrate in 131-312 mL of soil water. 
7 mg/131mL = 0.05 mg/mL * 1000mL/L = 53 mg/L 
7 mg/312 mL = 0.02 mg/mL * 1000 mL/L = 22 mg/L 
This range in values of 22 ? 53 mg/L for background levels of nitrate is well above 
the values seen in the samples collected during this experiment.  For the time period 
covered in this experiment, it is evident that nitrate concentrations from the leachate in 
close proximity to the biosolids rows are not rising above background levels.  This trend 
is independent of soil type, tree density, and biosolids application rate. 
 
 222
Conclusions 
Pan lysimeter samples contained low-levels of nitrate, with limited exceptions in 
both controls and other treatments.  One replicate from the 58,900 kgN/ha-0 trees/ha 
treatment and two replicates from the 39,300 kgN/ha-1076 trees/ha treatment produced 
results near or slightly above 1 mg/L over multiple quarters.  This may indicate that a 
limited amount of nitrification was occurring.  Statistical analyses showed differences in 
time (quarters) for certain application rate-tree density combinations.  In general, no 
consistent trends were demonstrated from these differences, with the exception of the 
58,900 kgN/ha-0 trees/ha treatment.  Within this treatment, the latter quarters (quarters 6-
8) had higher values than earlier quarters; across treatments, quarters 5-8 were higher 
than a number of other treatments. 
Suction lysimeter samples had a higher percentage of low-level results than pans.  A 
limited subset contained results close to or greater than 1 mg/L.  These included results 
from two control replicates and one 19,650 kgN/ha-0 trees/ha treatment, none of which 
provides enough consistency to indicate a specific trend.  The only statistical difference 
observed was a set of quarterly differences when examining all treatments collectively.  
These differences were inconsistent, with quarter 4 being greater than quarters 5-7, but 
with quarter 6 being less than quarters 5 and 7.  From this a trend cannot be identified. 
In summary, nitrate results were consistently low across application rates, tree 
densities, positions, and time.  These results indicate that nitrification is not occurring.  
Conversely, it could be argued that nitrification is occurring, but is immediately followed 
by denitrification, immobilization, plant uptake, or a combination thereof.  Neither of 
these scenarios, however, could account for such consistently low values of nitrate.  If 
 
 223
nitrification were occurring, one of the many samples collected each month would show 
higher levels of nitrate. 
As with nitrite, the overriding conclusion is that nitrate was not detected in quantities 
that present an environmental or health concern.  In fact, with few exceptions, nitrate is 
present at background levels only across application rates, tree densities, and positions 
around the biosolids rows. 
 
 224
 
Conclusions 
This study has provided valuable insight to the subsoil nitrogen dynamics 
surrounding the biosolids recycling operation at the ERCO Tree Farm.  By closely 
monitoring the breakdown products of organic nitrogen, including ammonium, nitrite, 
and nitrate in the soil water, a better understanding of the fate and transport of these 
nitrogen forms has been obtained in a wide variety of soil types. 
Biosolids 
With the exception of one anomalous result for ammonium and magnesium, all other 
results were consistent across all samples.  Average dry weight concentrations for total 
nitrogen were 4.12% (41,200 mg/kg) and for ammonium (after removal of the one 
outlier) were 0.23% (2,300 mg/kg). 
Hydraulic conductivity 
Saturated hydraulic conductivity (Ksat) values ranging from 1.40x10-7 ? 1.84x10-2 
cm/sec reflected soil composition ranging from those with high clay content to others 
dominated by sand and gravel.  Ksat in Block 1 was significantly greater than Ksat in 
Block 2 and Ksat in Block 2 was significantly greater than Ksat in Block 3.  Statistically 
significant differences were not determined, however, with depth in the soil profile, 
reflecting the varied soil conditions present after mining operations. 
Hydraulic conductivity values were used to estimate soil water travel times in 
saturated conditions for percolation of leachate from the biosolids rows to the sample 
collection equipment (i.e., pan and suction lysimeters).  In 80% of the subplots, biosolids 
leachate was calculated to reach the collection equipment within 8 days.  The other 20%, 
 
 225
however, would take a minimum of one month and maximum of 13 months to travel 30 
cm. 
Rain gauge data 
Rain gauge data were collected to provide insight to the precipitation cycles and 
potential impact on water flow into the soil profile from a source other than the biosolids.  
2003 had more precipitation than 2004, with particularly high rainfall in May and June.  
In 2003 this high rainfall delayed the planting of trees at the experimental site from early 
May until mid-June 2003.  In both years, May through September were marked by 
greater precipitation than other months.   
Ammonium 
As previously noted in the biosolids results, ammonium was already present in the 
biosolids in appreciable amounts (2,300 mg/kg on a dry weight basis).  Because 
ammonium is readily soluble in water, it is not surprising that the biosolids leachate 
would contain comparable amounts that could be transported in the soil profile.  In fact, 
more than half of the pan and suction lysimeter samples contained ammonium 
concentrations in excess of 1000 mg/L.   
For the pan lysimeters, ammonium concentrations were distributed fairly evenly 
across application rates, with more prevalence in the 0 trees/ha tree density compared to 
716 and 1074 trees/ha.  Statistical analysis showed no significant differences (? = 0.05) 
for application rate (including controls), tree density, or time.   
For suction lysimeters, ammonium concentrations from controls were significantly 
less than the other application rates.  The other notable trend in the non-control 
treatments was a decrease in concentration with distance from the biosolids row.  This 
 
 226
supports the observation that more ammonium is reaching the first of the vertical suction 
lysimeters, with attenuation as it travels deeper through the soil profile.  The decrease 
with depth could be due to cation exchange reactions in the soil that hold the ammonium 
and delay movement with soil water, microbial interactions (i.e., immobilization) or, 
though less likely, conversion of ammonium to nitrate with subsequent immediate 
denitrification.  Finally, an overall increase in concentration with time was indicated, 
though more data from later time periods will need to be evaluated in the future to better 
define this trend. 
Nitrite 
Nitrite, the next step of organic nitrogen breakdown, was not detected in a majority 
of the samples, though a couple of exceptions did occur.  Pan lysimeters produced 
significantly higher values for the 58,900 kg N/ha ? 0 trees/ha treatment, though this set 
of higher values was primarily associated with only one of the three replicates.  All other 
treatments, including controls, were not significantly different from one another.  Suction 
lysimeters produced no significant differences (? = 0.05) between application rate, tree 
density (including controls) or time.  Some statistical differences were determined 
between and within positions, with the vertical position closest to the biosolids being 
greater than some of the other positions, though the differences were isolated.  In 
summary, nitrite values were generally so low across experimental conditions that they 
are not considered to have any adverse impact on the recycling process. 
Nitrate 
Nitrate, the final product of nitrification, and the parameter of most concern from an 
environmental and health perspective, was consistently not detected or found in low 
 
 227
concentrations.  Across both pan and suction lysimeters, isolated incidences of values 
between 1-10 mg/L were found in a control subplot and three different non-control 
treatments.  The only notable statistical difference in pan samples pertained to the 58,900 
kg N/ha- 0 trees/ha treatment, for which the later quarters had higher values than the 
earlier quarters within the treatment.  In addition, across treatments quarters 5-8 were 
higher than some other treatments. 
Suction lysimeter results had an even higher percentage of lower level results (< 1 
mg/L) than pans, and showed no statistical differences between application rate, tree 
density, or position (including controls).  Some quarterly differences were detected when 
all results were collectively combined, though these differences did not indicate any 
trend.  As with nitrite, the overriding conclusion is that very little nitrification is 
occurring, and only in very isolated instances if at all.  Values do not differ between 
controls and other application rate-tree densities, clearly demonstrating that nitrate is not 
present in quantities that would adversely impact human health or the environment. 
 
 
 228
Future Work 
Though the data gathering thus far on this project has been extensive, additional data 
and evaluation would provide more insight to the processes occurring in the soil profile.  
Suggestions for further data gathering and study includes: 
? Evaluation of pan lysimeter and suction lysimeter sample volume records over time, 
to determine trends that may provide insight to saturated vs. unsaturated conditions 
in the soil profile. 
? Additional statistical analyses of the data to elicit whether or not certain isolated data 
are impacting the differences noted. 
? Evaluation of data from standpipe wells to determine water level and oxygen content 
trends in the experimental plot.  
? Evaluation of the phosphorus, chloride, and sulfate data being generated on a subset 
of samples from this project. 
? Evaluation of sample results generated subsequent to the December 2004 cutoff for 
this thesis. 
? Obtaining and evaluating monthly biosolids analysis records from the Blue Plains 
Wastewater Treatment Plant for the time period during which the biosolids rows in 
this experiment were installed.  These data would include parameters not determined 
at the University of Maryland lab. 
? Evaluating groundwater data from wells that encompass the perimeter of the ERCO 
tree farm. 
? Analysis of soil cores for cation exchange capacity. 
? Analysis of soil cores for sand, clay and silt content to better define soil texture. 
 
 229
? Collection and analysis of biosolids in the experimental plot on a yearly or twice 
yearly basis to determine decomposition rates at different depths in the row. 
? Analysis of biosolids and soil core samples from the experimental plots for microbial 
activity. 
? Evaluation of nitrogen content in foliar samples from the poplar trees in the 
experimental plot to better understand how much of the biosolids nitrogen is being 
consumed by the trees. 
? On a yearly basis, excavation and examination of root penetration from poplar trees 
into the biosolids at the experimental plot to provide insight into the 1) development 
of channels for oxygen transport to the biosolids and 2) the extent to which the trees 
have enveloped the biosolids and can take up soil water and nitrogen. 
? Collecting pan lysimeter samples designed to isolate storm flow.  The focus of these 
collection efforts would be those subplots with higher hydraulic conductivity. 
? Collection of lysimeter samples earlier in the process of the experimental set up, in 
concert with biosolids application, to capture initial leachate from the biosolids.  
? Installation of tensiometers at depths consistent with sample collection equipment to 
more definitively study soil moisture conditions in the soil profile. 
? Installation of temperature and oxygen probes in the biosolids rows and at the 
lysimeter depths to better monitor temperature and oxygen conditions over time. 
 
 
 230
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 86.4cm 
61 cm 
Installation Measurements 
Appendix 1 ? Pan and Suction Lysimeter Installation Details 
Pan Installation Diagrams 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 147.  Subplot 1A:  Block 1; 39,300 kg N/ha; 716 trees/ha. 
Distance Between Old Biosolids Rows 
63.5cm 
1.57m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter 
positioned equidistant 
from old biosolids rows 
30.5cm 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
30.5cm 
40.6cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
94
cm
 1
24
cm
 
63.5cm 
30.5cm 
Shallow core 
Middle Core 
Deep 
Core 
 
 231
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 148.  Subplot 1B:  Block 1; 39,300 kg N/ha; 1074 trees/ha 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 94cm 
48.3 cm 
59.7cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.12m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
94
cm
 
12
4c
m 
63.5cm 
Shallow core 
Middle Core 
Deep Core 
Note:  Core samples 
taken from installation 
trench wall opposite pan 
installation wall due to 
small dead space 
between old biosolids 
rows. 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
30.5cm 
38.1cm 
 
 232
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 149.  Subplot 1C:  Block 1; 39,300 kg N/ha; 0 trees/ha. 
Distance Between Old Biosolids Rows 
1.22m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
94
cm
 
12
4c
m 
63.5cm 
15.2cm 
Shallow core 
Middle Core 
Deep Core 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 94cm 
55.9cm 
Installation Measurements 
58.4cm 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
25.4cm 
38.1cm 
 
 233
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 150.  Subplot 1D:  Block 1, 19,650 kg N/ha; 716 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 68.9cm 
55.9cm 
58.4cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.52m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
35.6cm 
30.5cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
76
.2c
m 
10
7c
m 
45.7cm 
20.3cm 
Shallow core 
Middle Core 
Deep Core 
 
 234
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 151.  Subplot 1E:  Block 1; 19,650 kg N/ha; 1074 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 76.2cm 
51 cm 
53.3cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.04m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
30.5cm 
30.5cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
78
.7c
m 
10
9c
m 
48.3cm 
15.2cm 
Shallow core 
Middle Core 
Deep Core 
 
 235
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 152.  Subplot 1F:  Block 1; 19,650 kg N/ha; 0 trees/ha. 
53.3cm 
Distance Between Old Biosolids Rows 
1.13m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
30.5cm 
30.5cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
68
.6c
m 9
9c
m 
38.1cm 
Shallow core 
Middle Core 
Deep Core 
Note:  Core samples 
taken from installation 
trench wall opposite pan 
installation wall due to 
small dead space 
between old biosolids 
rows and partial collapse 
of installation wall. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 61cm 
68.6cm 
63.5cm 
Installation Measurements 
53.3c  
 
 236
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 153.  Subplot 1G:  Block 1; 58,900 kg N/ha; 716 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 96.5cm 
50.8cm 
55.9cm 
Installation Measurements 
Distance Between Old Biosolids Rows 
1.52m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
30.5cm 
30.5cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
10
4c
m 
13
5c
m 
73.7cm 
15.2cm 
Shallow core 
Middle Core 
Deep Core 
 
 237
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 154.  Subplot 1H:  Block 1; 58,900 kg N/ha; 1074 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 104cm 
30.5cm 
30.5cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.52m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
15.2cm 
20.3cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
11
8c
m 
14
2c
m 
81.3cm 
Shallow core 
Middle Core 
Deep Core 
Note:  Core samples 
taken from installation 
trench wall opposite pan 
installation wall due to 
small dead space 
between old biosolids 
rows. 
 
 238
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 155.  Subplot 1I:  Block 1; 58,900 kg N/ha; 0 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter 
Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 119cm 
76.2cm 
63.5cm 
Installation Measurements 
Distance Between Old Biosolids Rows 
1.46m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
12
7c
m 
15
7c
m 
96.5cm 
12.7cm 
Shallow core 
Middle Core 
Deep Core 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
17.8cm 
38.1cm 
 
 239
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 156.  Subplot 4C (Control):  Block 1; 0 kg N/ha; 0 trees/ha. 
Surface 
Installation Trench 
Control Area: No 
Biosolids, 
Undisturbed soil 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
theoretical biosolids row and top 
of pan = 30.5cm 
Depth for theoretical 
biosolids row = 61cm 
30.5cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.0m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
71
.1c
m 
10
2c
m 
40.6cm 
20.3cm 
Shallow core 
Middle Core 
Deep Core 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
12.7cm 
20.3cm 
Control Area: No 
Biosolids, 
Undisturbed soil 
107 cm across 
 
 240
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 157.  Subplot 2A:  Block 2, 58,900 kg N/ha; 716 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 124cm 
58.4cm 
61cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.52m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
26.7cm 
40.6cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
12
4c
m 
15
5c
m 
94cm 
19cm 
Shallow core 
Middle Core 
Deep Core 
 
 241
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 158.  Subplot 2B:  Block 2; 58,900 kg N/ha; 1074 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 102cm 
61 cm 
59.7cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.52m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
25.4cm 
40.6cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
13
2c
m 
102cm 
25.4cm 
Middle Core 
Deep Core 
 
 242
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 159.  Subplot 2C:  Block 2; 58,900 kg N/ha; 0 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 107cm 
58.4cm 
66cm 
Installation Measurements 
Distance Between Old Biosolids Rows 
1.22m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
30.5cm 
43.2cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
10
7c
m 
13
7c
m 
76.2m 
15.2cm 
Shallow core 
Middle Core 
Deep Core 
 
 243
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 160.  Subplot 2D:  Block 2; 39,300 kg N/ha; 716 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 99cm 
55.9cm 
53.3cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.4m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
33cm 
30.5cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
10
4c
m 
13
5c
m 
73.7cm 
15.2cm 
Shallow core 
Middle Core 
Deep Core 
 
 244
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 161.  Subplot 2E:  Block 2; 39,300 kg N/ha; 1074 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 94cm 
40.6cm 
48.3cm 
Installation Measurements 
Distance Between Old Biosolids Rows 
1.28m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
30.5cm 
30.5cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
94
cm
 
12
4c
m 
63.5cm 
20.3cm 
Shallow core 
Middle Core 
Deep Core 
 
 245
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 162.  Subplot 2F:  Block 2; 39,300 kg N/ha; 0 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 88.9cm 
55.9cm 
52.1cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.45m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
30.5cm 
30.5cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
99
.1c
m 1
30
cm
 
68.6cm 
20.3cm 
Shallow core 
Middle Core 
Deep Core 
 
 246
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 163.  Subplot 2G:  Block 2; 19,650 kg N/ha; 716 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 63.5cm 
50.8cm 
61cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.88m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
33cm 
33cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
71
.1c
m 
10
2c
m 
40.6cm 
25.4cm 
Shallow core 
Middle Core 
Deep Core 
 
 247
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 164.  Subplot 2H:  Block 2; 19,650 kg N/ha; 1074 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 68.6cm 
53.3cm 
53.3cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.27m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
33cm 
27.9cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
76
.2c
m 
10
7c
m 
45.7cm 
20.3cm 
Shallow core 
Middle Core 
Deep Core 
 
 248
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 165.  Subplot 2I:  Block 2; 19,650 kg N/ha; 0 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 63.5cm 
30.5cm 
33cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.22m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
20.3cm 
15.2cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
71
.1c
m 
10
2c
m 
40.6cm 
Shallow core 
Middle Core 
Deep Core 
Note:  Core samples 
taken from installation 
trench wall opposite pan 
installation wall due to 
small dead space 
between old biosolids 
rows. 
 
 249
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 166.  Subplot 4B (Control):  Block 2; 0 kg N/ha; 0 trees/ha. 
Distance Between Old Biosolids Rows 
1.16m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
71
.1c
m 
10
2c
m 
40.6cm 
20.3cm 
Shallow core 
Middle Core 
Deep Core 
Surface 
Installation Trench 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of  
theoretical biosolids row and top 
of pan = 30.5cm 
Depth for theoretical 
biosolids row = 61cm 
30.5cm 
Installation Measurements 
Control Area: No 
Biosolids, 
Undisturbed soil 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
12.7cm 
22.9cm 
Control Area: No 
Biosolids, 
Undisturbed soil 
107 cm across 
 
 250
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 167.  Subplot 3A:  Block 3; 19,650 kg N/ha; 1074 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 61cm 
40.6cm 
40.6cm 
Installation Measurements 
Distance Between Old Biosolids Rows 
NA 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
33cm 
20.3cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
61
cm
 9
1c
m 
30.5cm 
61cm 
Shallow core 
Middle Core 
Deep Core 
 
 251
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 168.  Subplot 3B:  Block 3; 19,650 kg N/ha; 716 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 61cm 
61 cm 
61cm 
Installation Measurements 
Distance Between Old Biosolids Rows 
2.44m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
40.6cm 
35.6cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
94cm 
15.2cm 
Deep Core 
Note:  Only one core, 
at the deep site (next 
to the pan installation 
depth) was collected. 
 
 252
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 169.  Subplot 3C:  Block 3; 19,650 kg N/ha; 0 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 71.1cm 
40.6cm 
47cm 
Installation Measurements 
Distance Between Old Biosolids Rows 
2.13m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
30.5cm 
25.4cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
71
.1c
m 
10
2c
m 
40.6cm 
45.7cm 
Shallow core 
Middle Core 
Deep Core 
 
 253
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 170.  Subplot 3D:  Block 3; 58,900 kg N/ha; 1074 trees/ha. 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance Between Old Biosolids Rows 
2.13m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
20.3cm 
43.2cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
13
7c
m 
16
8c
m 
107cm 
45.7cm 
Shallow core 
Middle Core 
Deep Core 
Surface 
Installation Trench 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 137cm 
55.9cm 
55.9cm 
Installation Measurements 
Biosolids Row 
107 cm across 
Pan Length 
53.3 cm 
 
 254
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 171.  Subplot 3E:  Block 3; 58,900 kg N/ha; 716 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 129cm 
55.9cm 
58.4cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.68m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to new 
row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
25.4cm 
38.1cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
13
7c
m 
16
8c
m 
107cm 
25.4cm 
Shallow core 
Middle Core 
Deep Core 
 
 255
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 172.  Subplot 3F:  Block 3; 58,900 kg N/ha; 0 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 122cm 
53.3cm 
53.3cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.52m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
13
2c
m 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
30.5cm 
35.6cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
16
3c
m 
102cm 
20.3cm 
Shallow core 
Middle Core 
Deep Core 
Note: Old 
biosolids row 
prevented 
sampling of 
shallow core to 
side of pan, so 
collected directly 
above pan. 
 
 256
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 173.  Subplot 3G:  Block 3; 39,300 kg N/ha; 1074 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 95.2cm 
50.8cm 
58.4cm 
Installation Measurements 
Distance Between Old Biosolids Rows 
1.43m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
30.5cm 
38.1cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
10
3c
m 
13
3c
m 
72.4cm 
20.3cm 
Shallow core 
Middle Core 
Deep Core 
 
 257
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 174.  Subplot 3H:  Block 3; 39,300 kg N/ha; 716 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 78.7cm 
54.6cm 
57.1cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.52m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
30.5cm 
30.5cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
86
.4c
m 
11
7c
m 
55.9cm 
20.3cm 
Shallow core 
Middle Core 
Deep Core 
 
 258
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 175.  Subplot 3I:  Block 3; 39,300 kg N/ha; 0 trees/ha. 
Surface 
Installation Trench 
Biosolids Row 
107 cm across 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Distance from Installation Trench 
Wall to Edge of Biosolids Row 
Pan Lysimeter Depth = 15.2cm 
Depth between bottom of 
biosolids row and top of pan = 
30.5cm 
Measured depth to bottom of 
biosolids row = 76.2cm 
61 cm 
58.4cm 
Installation Measurements Distance Between Old Biosolids Rows 
1.52m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Biosolids Row 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
33cm 
33cm 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
83
.8c
m 
11
4c
m 
53.3cm 
25.4cm 
Shallow core 
Middle Core 
Deep Core 
 
 259
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 176.  Subplot 4A (Control):  Block 3; 0 kg N/ha;0 trees/ha. 
Distance Between Old Biosolids Rows 
1.68m 
Old biosolids row 
(perpendicular to 
new row) 
Old biosolids row 
(perpendicular to 
new row) 
Pan Lysimeter positioned 
equidistant from old 
biosolids rows 
Core Sample Positions 
Surface 
Pan Lysimeter 
(53.3cm across) 
30.5cm 
30.5cm 
71
.1c
m 10
2c
m 
40.6cm 
20.3cm 
Shallow core 
Middle Core 
Deep Core 
Surface 
Installation Trench 
Pan Length 
53.3cm 
Distance from 
Installation 
Trench Wall to 
Installed Pan 
Pan Lysimeter Depth = 15.2cm 
Depth between theoretical 
bottom of biosolids row and top 
of pan = 30.5cm 
Depth for theoretical 
biosolids row = 61cm 
30.5cm 
Installation Measurements 
Control Area: No 
Biosolids, 
Undisturbed soil 
107 cm across 
Surface 
Installation Trench 
PVC Pipe Measurements 
3.05m 
15.2cm 
22.9cm 
Control Area: No 
Biosolids, 
Undisturbed soil 
107 cm across 
 
 260
Pan Lysimeter Installation Tables 
Table 25.  Pan lysimeter installation information ? all blocks. 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which Pan 
Installed 
Pan Position 
(Distance 
from S. End 
of Plot) (m) 
Depth to 
Bottom of Bio. 
Row (m) 
Date 
Installed 
Weather 
1A 39,300 716 6 145.4 0.86 8/1/2002 Sunny, 26.7-29.4?C 
1B 39,300 1074 6 173.1 0.94 8/6/2002 Sunny, breezy, 26.7-29.4?C 
1C 39,300 0 6 186.5 0.94 8/6/2002 Sunny, breezy, 26.7-29.4?C 
1D 19,650 716 19 142.3 0.69 11/8/2002 Sunny, 15.5?C 
1E 19,650 1074 20 168.8 0.76 12/2/2002 Sunny, 4.4?C 
1F 19,650 0 22 186.2 0.61 1/9/2003 Sunny, -1.1 ? 1.7?C 
1G 58,900 716 30 *144.2 0.96 1/21/2003 Partly sunny, -1.1 ? 1.7?C 
1H 58,900 1074 31 *166.1 1.04 2/5/2003 Sunny, breezy, 4.4-7.2?C 
1I 58,900 0 30 *184.4 1.19 1/27/2003 Sunny, breezy, -6.7- -3.9?C 
4C 0 0 NA *178.6 0.61 3/25/2003 Sunny, 21.1-23.9?C 
2A 58,900 716 6 84.1 1.24 7/29/2002 Sunny, humid, 32.2-35?C 
2B 58,900 1074 6 106.7 1.02 7/30/2002 Sunny, humid, 32.2-35?C 
2C 58,900 0 6 125.6 1.07 8/1/2002 Sunny, breezy, 26.7-29.4?C 
2D 39,300 716 17 79.2 0.99 10/23/2002 Sunny, breezy, 16.7?C 
2E 39,300 1074 16 106.7 0.94 10/7/2002 Partly sunny, 21.1?C 
2F 39,300 0 17 122.5 0.89 10/28/2002 Cloudy, showers in AM, 11.1?C 
2G 19,650 716 29 *78.0 0.64 1/10/2003 Sunny, p. cloudy, breezy, 4.4?C 
2H 19,650 1074 29 *106.7 0.69 1/13/2003 Sunny, 4.4?C 
2I 19,650 0 30 *122.5 0.64 1/20/2003 Part cloudy, breezy, -1.1- 1.7?C 
4B 0 0 NA *122.5 0.61 3/19/2003 Overcast, breezy, 10-12.8?C 
3A 19,650 1074 5 10.7 0.61 7/19/2002 Sunny, humid, 32.2-35?C 
3B 19,650 716 4 32.3 0.61 7/16/2002 Sunny, humid, 32.2?C 
3C 19,650 0 5 58.7 0.71 7/25/2002 Partly cloudy, breezy, 29.4?C 
3D 58,900 1074 14 11.9 1.37 10/2/2002 Sunny, 31.1?C 
3E 58,900 716 16 35.7 1.29 10/14/2002 Sunny, breezy, 15.5-18.3?C 
3F 58,900 0 17 55.5 1.22 10/21/2002 Partly cloudy, 10-12.8?C 
3G 39,300 1074 27 *6.10 0.95 12/23/2002 Sunny, 7.22?C 
 
 261
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which Pan 
Installed 
Pan Position 
(Distance 
from S. End 
of Plot) (m) 
Depth to 
Bottom of Bio. 
Row (m) 
Date 
Installed 
Weather 
3H 39,300 716 29 *36.6 0.79 1/7/2003 Partly sunny, breezy, -1.1- 1.7?C 
3I 39,300 0 29 *58.5 0.76 1/8/2003 Overcast, 1.7?C 
4A 0 0 NA *58.5 0.61 2/14/2003 Overcast, 1.7-4.4?C 
*Distance from south end is with respect to the western-most north-south strip of experimental subplots, the entire strip of which is positioned 
12.2m south of the eastern and middle north-south strips of experimental subplots (See Figure 3). 
 
 262
 
Table 26.  Pan installation notes ? block 1. 
Subplot  Notes/Comments 
1A Sandy soil; drilling easier than in eastern subplots of Blocks 2 and 3. 
1B Soil profile had clay on top, but underneath was a sandy lens, so surface clay is not representative of a clay lens.  Water slowly 
streamed in from old biosolids rows. 
1C Soil profile had clay on top, but underneath was a sandy lens, so surface clay is not representative of a clay lens.  Installation 
was problematic.  Unstable soil resulted in a large chunk breaking off from the ceiling of the pan installation cavity.  This 
created an arch of dead space 7.6-10.2cm above the inserted pan.  To fill the gap, two sets of pan screens were placed on top of 
the pan (to provide extra support and filtering capability) and sand was distributed on top of the screens to fill in the void. 
1D Very gravelly, sandy soil.  Water streamed out of old biosolids rows. Drilling relatively easy except when rocks encountered. 
1E Sandier soil.  Relatively easy drilling.  Drill poked into old biosolids row on the south side of the pan wall.  No influx of water 
or dark biosolids was noted.  Readjusted pan installation to the south to avoid having the pan resting against the breach. 
1F Due to the instability of mine spoil/soil and trench wall, left 68.6cm distance between the installation trench and biosolids row 
under which pan was installed.  Final distance between front end of installed pan and installation trench = 63.5cm, leaving 2-
3cm of pan outside biosolids row.  Very wet soil profile.  Water also seeped through soil into pan installation cavity.  After 
positioning pan in the installation cavity, some soil from the ceiling of the cavity fell onto the screen covering the pan.  Sand 
was used to fill the resulting gap in the ceiling,   Water gushed out of old biosolids rows.  Pump required to prevent installation 
trench from filling too much and impeding installation efforts. 
1G Sandy soil.  Frozen ground at top 8-15cm of soil/mine spoil.  Easy drilling.  Small amount of drainage from old biosolids rows. 
1H Installation trench walls unstable; a layer of overburden from wall opposite installation broke off when digging installation 
trench.  Wall supports prevented further breakoff .  Drilling of average difficulty; negligible drainage from old biosolids rows. 
1I Soil consisted of gravelly backfill with < 5cm diameter rocks.  Frozen ground at top 8-15cm of soil/mine spoil.  Drilling 
proceeded quickly.  Due to instability of installation trench, kept distance between installation trench and biosolids row at 
76cm.  With a maximum possible drilling distance of 117cm (due to length of auger), only was able to fit 41cm of the 53.3cm 
pan length under the biosolids row.  Water gushed in from old biosolids rows, requiring pump out. 
4C 
(control) 
Soil was dark brown and contained more clay and less sand than other installations in Block 1. Water streamed in from old 
biosolids rows, which were wider than most.  After pan was installed and soil packed back into the pan installation hole, the 
track loader experienced mechanical problems.  While waiting for the track loader to be repaired, a layer of the installation 
trench wall fell away, but did not interfere with the pan installation hole.  The entire installation trench was then filled.  Note:  
A small fissure/crack was created at the surface over the biosolids row, but was filled when the track loader smoothed over the 
entire installation area. 
 
 263
Table 27.  Pan installation notes ? block 2. 
Subplot 
ID 
Notes/Comments 
2A Drilling of average difficulty.  Soil was dry due to drought. 
2B Drilling of average difficulty.  Soil was dry due to drought. 
2C Soil contains sand and gravel.  Water seeped into the pan installation cavity from the left (north) side.  Odorous water trickled 
out of the old biosolids row on the left (north).  Collected a soil sample directly underneath the old biosolids row to the north 
of the pan.  Laboratory analysis showed negligible amounts of nitrate (< 1 mg/L). 
2D Soil contains pebbles and is crumbly.  Although clay was notably present in different locations of the soil profile, sandier 
patches of soil/overburden existed.  Soil had a variable profile that was difficult to characterize.  Water trickled from old 
biosolids rows. 
2E Average drilling.  Negligible water from old biosolids rows. 
2F Trench walls unstable.  Pan installed 5cm short of originally intended placement due to time constraints imposed by transient 
trench wall conditions.  Odorous water gushed from old biosolids rows. 
2G Soil/overburden consists of grayish/white packed sand and clay mix.  Similar to concrete.  Drilling difficult and slow. 
2H Drilling of average difficulty.  Trickle of water coming from old biosolids rows. 
2I Sandy/clay mix with pebbles.  Frozen ground at top 8-15cm of soil/mine spoil.  Trickle of water coming from old biosolids 
rows.  Drilling of average difficulty. 
4B Sandy clay with pebbles that was difficult to drill.  Soil packed like concrete.  Water trickled in from old biosolids rows. 
 
 
 264
 
Table 28.  Pan installation notes ? block 3. 
Subplot ID Notes/Comments 
3A High clay content.  Soil dry due to drought.  Drilling slow. 
3B High clay content.  Soil dry due to drought.  Drilling slow. 
3C High clay content.  Soil dry due to drought.  Drilling slow. 
3D Drilling of average difficulty.  Negligible water from old biosolids trenches. 
3E Drilling slow.  Shaping of pan cavity took a long time.  Water gushed from old biosolids rows. 
3F Soil/overburden fairly soft and easier to drill through than other pans in Block 3.  Water seeping through soil into ceiling of 
pan installation cavity.  Water also streaming out of old biosolids row on north side of pan installation. 
3G High clay content, wet and packed.  Drilling very slow.  Water gushed out of old biosolids rows.  Pump used to remove water 
from installation trench. 
3H Sandy clay soil.  Smooth drilling.  Water seeped through soil into ceiling of pan installation cavity.  Water trickled from old 
biosolids rows. 
3I Drilling of average difficulty.  Water gushed out of old biosolids rows, and filled installation trench to a 0.3m depth within 10 
minutes.  Used pump to remove water. 
4A Drilling of average difficulty.  Water streamed into installation trench from old biosolids. 
 
 265
 
Suction Lysimeter Installation Tables 
 
Table 29.  Suction lysimeter (SL) installation information ? block 1: 39,300 kg N/ha. 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which SL 
Installed 
SL Position 
in Relation 
to Biosolids 
Row (cm)* 
Biosolids 
Depth 
(m) 
Overburden 
Depth (m) 
Water Seepage 
Into Installation 
Cavity? 
Date 
Installed 
SL-1A-1 39,300 716 5 15 ? v 0.79 0.53 No 8/18/2003 
SL-1A-2 39,300 716 4 60 ? v  0.81 0.48 No 8/18/2003 
SL-1A-3 39,300 716 3 30 ? v  0.91 0.51 No 8/18/2003 
SL-1A-4 39,300 716 2 30 ? west 1.0 0.53 No 8/18/2003 
SL-1A-5 39,300 716 2 15 ? east  1.0 0.53 No 8/18/2003 
SL-1B-1 39,300 1074 7 60 ? v 0.94 0.30 No 8/15/2003 
SL-1B-2 39,300 1074 6 30 ? v 0.76 0.56 Yes ? damp 8/15/2003 
SL-1B-3 39,300 1074 5 15 ? west 0.71 0.53 No 8/15/2003 
SL-1B-4 39,300 1074 5 30 ? east 0.71 0.53 No 8/15/2003 
SL-1B-5 39,300 1074 4 15 ? v  0.68 0.58 Yes ? damp 8/15/2003 
SL-1C-1 39,300 0 9 60 ?v 0.96 0.41 Yes ? pooled high 8/14/2003 
SL-1C-2 39,300 0 8 15 ? west 0.96 0.53 Yes ? pooled high 8/14/2003 
SL-1C-3 39,300 0 8 30 ? east 0.96 0.53 No 8/14/2003 
SL-1C-4 39,300 0 4 15 ?v 0.94 0.41 No 8/14/2003 
SL-1C-5 39,300 0 3 30 ? v 0.94 0.35 No 8/14/2003 
* v = vertically positioned lysimeters; depth = distance below bottom of biosolids row. 
East = laterally positioned lysimeter placed at the specified distance from the east edge of the biosolids row at depth equal to 
the depth of the biosolids row. 
West = laterally positioned lysimeter placed at the specified distance from the west edge of the biosolids row at depth equal to 
the depth of the biosolids row. 
 
 
 266
Table 30.  Suction lysimeter (SL) installation information ? block 1: 19,650 kg N/ha. 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which SL 
Installed 
SL Position 
in Relation 
to Biosolids 
Row (cm)* 
Biosolids 
Depth 
(m) 
Overburden 
Depth (m) 
Water Seepage 
Into 
Installation 
Cavity? 
Date 
Installed 
SL-1D-1 19,650 716 16 30 ? v 0.68 0.56 No 7/30/2003 
SL-1D-2 19,650 716 15 15 ? v 0.48 0.15 No 7/30/2003 
SL-1D-3 19,650 716 14 60 ? v 0.56 0.64 No 7/30/2003 
SL-1D-4 19,650 716 13 15 ? west 0.56 0.53 No 7/30/2003 
SL-1D-5 19,650 716 13 30 ? east 0.56 0.53 No 7/30/2003 
SL-1E-1 19,650 1074 16 60 ? v 0.76 0.41 No 7/30/2003 
SL-1E-2 19,650 1074 15 15 ? v 0.46 0.46 No 7/30/2003 
SL-1E-3 19,650 1074 14 30 ? v 0.51 0.56 No 7/30/2003 
SL-1E-4 19,650 1074 13 30 ? west 0.63 0.61 No 7/30/2003 
SL-1E-5 19,650 1074 13 15 ? east 0.63 0.61 No 7/30/2003 
SL-1F-1 19,650 0 17 15 ? west 0.63 0.35 No 7/31/2003 
SL-1F-2 19,650 0 17 30 ? east 0.63 0.35 No 7/31/2003 
SL-1F-3 19,650 0 16 15 ? v 0.68 0.20 No 7/31/2003 
SL-1F-4 19,650 0 15 60 ? v 0.61 0.45 No 7/31/2003 
SL-1F-5 19,650 0 14 30 ?v  0.71 0.43 No 7/31/2003 
* v = vertically positioned lysimeters; depth = distance below bottom of biosolids row. 
East = laterally positioned lysimeter placed at the specified distance from the east edge of the biosolids row at depth equal to 
the depth of the biosolids row. 
West = laterally positioned lysimeter placed at the specified distance from the west edge of the biosolids row at depth equal to 
the depth of the biosolids row. 
 
 
 
 
 
 
 
 267
Table 31.  Suction lysimeter (SL) installation information ? block 1: 58,900 kg N/ha. 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which SL 
Installed 
SL Position 
in Relation 
to Biosolids 
Row (cm)* 
Biosolids 
Depth 
(m) 
Overburden 
Depth (m) 
Water Seepage 
Into 
Installation 
Cavity? 
Date 
Installed 
SL-1G-1 58,900 716 29 60 ?v 1.04 0.48 No 8/26/2003 
SL-1G-2 58,900 716 28 15 ? v 1.17 0.48 No 8/26/2003 
SL-1G-3 58,900 716 26 30 ? v 1.24 0.51 No 8/26/2003 
SL-1G-4 58,900 716 25 30 ? west 1.19 0.43 No 8/26/2003 
SL-1G-5 58,900 716 25 15 ? east 1.19 0.43 No 8/26/2003 
SL-1H-1 58,900 1074 27 15 ? v 0.94 0.30 No 8/22/2003 
SL-1H-2 58,900 1074 26 30 ?v  0.91 0.33 No 8/22/2003 
SL-1H-3 58,900 1074 25 60 ? v 0.99 0.43 No 8/22/2003 
SL-1H-4 58,900 1074 24 30 ? west 0.96 0.43 No 8/22/2003 
SL-1H-5 58,900 1074 24 15 ? east 0.96 0.43 No 8/22/2003 
SL-1I-1 58,900 0 27 15 ? v 0.89 0.38 No 8/22/2003 
SL-1I-2 58,900 0 27 30 ?v  0.89 0.38 Yes ? pooled 8/22/2003 
SL-1I-3 58,900 0 26 15 ? west 1.0 0.38 No 8/22/2003 
SL-1I-4 58,900 0 26 60 ? v 1.0 0.38 Yes ? damp 8/22/2003 
SL-1I-5 58,900 0 26 30 ? east  1.0 0.38 No 8/22/2003 
 
 
 268
 
Table 32.  Suction lysimeter (SL) installation information ? block 1: 0 kg N/ha. 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which SL 
Installed 
SL Position 
in Relation 
to Biosolids 
Row (cm)* 
Biosolids 
Depth 
(m) 
Overburden 
Depth (m) 
Water Seepage 
Into 
Installation 
Cavity? 
Date 
Installed 
SL-4C-1 0 0 NA 30 ? v 0.32 0.30 No 8/25/2003 
SL-4C-2 0 0 NA 15 ? v 0.32 0.30 No 8/25/2003 
SL-4C-3 0 0 NA 15 ? west 0.32 0.30 No 8/25/2003 
SL-4C-4 0 0 NA 30 ? east 0.32 0.30 No 8/25/2003 
SL-4C-5 0 0 NA 60 ? v  0.32 0.30 No 8/25/2003 
* v = vertically positioned lysimeters; depth = distance below bottom of biosolids row.  East = laterally positioned lysimeter 
placed at the specified distance from the east edge of the biosolids row at depth equal to the depth of the biosolids row.  West = 
laterally positioned lysimeter placed at the specified distance from the west edge of the biosolids row at depth equal to the depth of the 
biosolids row. 
 
 
 269
Table 33.  Suction lysimeter (SL) installation information ? block 2: 58,900 kg N/ha. 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which SL 
Installed 
SL Position 
in Relation 
to Biosolids 
Row (cm)* 
Biosolids 
Depth 
(m) 
Overburden 
Depth (m) 
Water Seepage 
Into 
Installation 
Cavity? 
Date 
Installed 
SL-2A-1 58,900 716 8 15 ? v 1.07 0.58 No 8/24/2003 
SL-2A-2 58,900 716 5 60 ? v 1.17 0.56 No 8/24/2003 
SL-2A-3 58,900 716 4 30 ? west 0.91 0.56 No 8/24/2003 
SL-2A-4 58,900 716 4 15 ? east 0.91 0.56 No 8/24/2003 
SL-2A-5 58,900 716 3 30 ? v  0.96 0.58 No 8/24/2003 
SL-2B-1 58,900 1074 5 15 ? v 0.86 0.51 No 8/19/2003 
SL-2B-2 58,900 1074 4 30 ? v 0.91 0.51 No 8/19/2003 
SL-2B-3 58,900 1074 3 60 ? v 0.91 0.41 No 8/19/2003 
SL-2B-4 58,900 1074 2 15 ? west 0.89 0.43 No 8/19/2003 
SL-2B-5 58,900 1074 2 30 ? east 0.89 0.43 No 8/19/2003 
SL-2C-1 58,900 0 5 30 ?v  0.99 0.41 No 8/19/2003 
SL-2C-2 58,900 0 4 15 ? v 0.91 0.46 No 8/19/2003 
SL-2C-3 58,900 0 3 15 ? west 0.86 0.51 No 8/19/2003 
SL-2C-4 58,900 0 3 30 ? east 0.86 0.51 No 8/19/2003 
SL-2C-5 58,900 0 2 60 ? v  0.91 0.51 No 8/19/2003 
* v = vertically positioned lysimeters; depth = distance below bottom of biosolids row. 
East = laterally positioned lysimeter placed at the specified distance from the east edge of the biosolids row at depth equal to 
the depth of the biosolids row. 
West = laterally positioned lysimeter placed at the specified distance from the west edge of the biosolids row at depth equal to 
the depth of the biosolids row. 
 
 
 270
Table 34.  Suction lysimeter (SL) installation information ? block 2: 39,300 kg N/ha. 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which SL 
Installed 
SL Position 
in Relation 
to Biosolids 
Row (cm)* 
Biosolids 
Depth 
(m) 
Overburden 
Depth (m) 
Water Seepage 
Into Installation 
Cavity? 
Date 
Installed 
SL-2D-1 39,300 716 16 15 ? v 0.76 0.64 No 8/1/2003 
SL-2D-2 39,300 716 15 60 ? v 0.86 0.61 No 8/1/2003 
SL-2D-3 39,300 716 14 15 ? west 0.86 0.56 No 8/1/2003 
SL-2D-4 39,300 716 14 30 ? east 0.86 0.56 No 8/1/2003 
SL-2D-5 39,300 716 13 30 ? v 0.86 0.53 No 8/1/2003 
SL-2E-1 39,300 1074 20 60 ? v 0.74 0.61 Yes ? pooled high 8/1/2003 
SL-2E-2 39,300 1074 19 15 ? v 0.71 0.61 No 8/1/2003 
SL-2E-3 39,300 1074 18 30 ? west 0.76 0.64 Yes ? pooled 8/1/2003 
SL-2E-4 39,300 1074 18 15 ? east 0.76 0.64 Yes ? pooled 8/1/2003 
SL-2E-5 39,300 1074 17 30 ? v 0.76 0.48 No 8/1/2003 
SL-2F-1 39,300 0 19 30 ? v 0.96 0.43 No 7/31/2003 
SL-2F-2 39,300 0 19 60 ? v 0.96 0.43 No 7/31/2003 
SL-2F-3 39,300 0 15 15 ? v 0.86 0.35 Yes ? pooled 7/31/2003 
SL-2F-4 39,300 0 14 15 ? west 0.89 0.45 Yes ? pooled 7/31/2003 
SL-2F-5 39,300 0 14 30 ? east 0.89 0.45 No 7/31/2003 
* v = vertically positioned lysimeters; depth = distance below bottom of biosolids row. 
East = laterally positioned lysimeter placed at the specified distance from the east edge of the biosolids row at depth equal to 
the depth of the biosolids row. 
West = laterally positioned lysimeter placed at the specified distance from the west edge of the biosolids row at depth equal to 
the depth of the biosolids row. 
 
 
 
 
 
 
 271
Table 35.  Suction lysimeter (SL) installation information ? block 2: 19,650 kg N/ha. 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which SL 
Installed 
SL Position 
in Relation 
to Biosolids 
Row (cm)* 
Biosolids 
Depth 
(m) 
Overburden 
Depth (m) 
Water Seepage 
Into Installation 
Cavity? 
Date 
Installed 
SL-2G-1 19,650 716 27 15 ? v 0.51 0.53 No 7/28/2003 
SL-2G-2 19,650 716 26 60 ? v 0.56 0.63 No 7/28/2003 
SL-2G-3 19,650 716 25 15 ? west 0.51 0.51 No 7/28/2003 
SL-2G-4 19,650 716 25 30 ? east 0.63 0.51 No 7/28/2003 
SL-2G-5 19,650 716 24 30 ? v 0.63 0.51 No 7/28/2003 
SL-2H-1 19,650 1074 28 60 ? v 0.51 0.43 No 7/28/2003 
SL-2H-2 19,650 1074 27 30 ? v 0.51 0.41 No 7/28/2003 
SL-2H-3 19,650 1074 26 15 ? v 0.51 0.51 No 7/28/2003 
SL-2H-4 19,650 1074 25 30 ? west 0.51 0.51 Yes ? pooled 7/28/2003 
SL-2H-5 19,650 1074 25 15 ? east 0.51 0.51 Yes - pooled 7/28/2003 
SL-2I-1 19,650 0 28 15 ? v 0.43 0.51 No 7/29/2003 
SL-2I-2 19,650 0 27 30 ? v 0.51 0.51 No 7/29/2003 
SL-2I-3 19,650 0 26 30 ? west 0.58 0.51 No 7/29/2003 
SL-2I-4 19,650 0 26 15 ? east 0.58 0.51 No 7/29/2003 
SL-2I-5 19,650 0 25 60 - v 0.56 0.51 No 7/29/2003 
 
 
 272
Table 36.  Suction lysimeter (SL) installation information ? block 2: 0 kg N/ha. 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which SL 
Installed 
SL Position 
in Relation 
to Biosolids 
Row (cm)* 
Biosolids 
Depth 
(m) 
Overburden 
Depth (m) 
Water Seepage 
Into Installation 
Cavity? 
Date 
Installed 
SL-4B-1 0 0 NA 30 ? west 0.32 0.30 No 8/21/2003 
SL-4B-2 0 0 NA 15 ? east 0.32 0.30 No 8/21/2003 
SL-4B-3 0 0 NA 30 ? v 0.32 0.30 No 8/21/2003 
SL-4B-4 0 0 NA 60 ? v  0.32 0.30 No 8/21/2003 
SL-4B-5 0 0 NA 15 ? v  0.32 0.30 No 8/21/2003 
* v = vertically positioned lysimeters; depth = distance below bottom of biosolids row.  East = laterally positioned lysimeter 
placed at the specified distance from the east edge of the biosolids row at depth equal to the depth of the biosolids row.  West = 
laterally positioned lysimeter placed at the specified distance from the west edge of the biosolids row at depth equal to the depth of the 
biosolids row. 
 
 273
 
Table 37.  Suction lysimeter (SL) installation information ? block 3: 19,650 kg N/ha. 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which SL 
Installed 
SL Position 
in Relation 
to Biosolids 
Row (cm)* 
Biosolids 
Depth 
(m) 
Overburden 
Depth (m) 
Water Seepage 
Into Installation 
Cavity? 
Date 
Installed 
SL-3A-1 19,650 1074 9 15 ? west 0.63 0.51 No 7/24/2003 
SL-3A-2 19,650 1074 9 15 ? v 0.51 0.51 Yes ? pooled 7/24/2003 
SL-3A-3 19,650 1074 9 30 ? east 0.56 0.76 No 7/24/2003 
SL-3A-4 19,650 1074 7 30 ? v 0.61 0.66 No 7/24/2003 
SL-3A-5 19,650 1074 5 60 ? v 0.61 0.91 No 7/24/2003 
SL-3B-1 19,650 716 7 15 ? west 0.53 0.61 No 7/24/2003 
SL-3B-2 19,650 716 7 30 ? east 0.53 0.61 No 7/24/2003 
SL-3B-3 19,650 716 6 15 ? v 0.41 0.43 No 7/24/2003 
SL-3B-4 19,650 716 4 30 ?v  0.53 0.48 No 7/24/2003 
SL-3B-5 19,650 716 3 60 ? v 0.61 0.61 No 7/24/2003 
SL-3C-1 19,650 0 8 15 ? v 0.58 0.71 No 7/25/2003 
SL-3C-2 19,650 0 7 30 ?v  0.43 0.53 Yes ? pooled 7/25/2003 
SL-3C-3 19,650 0 4 15 ? west 0.53 0.63 No 7/25/2003 
SL-3C-4 19,650 0 4 30 ? east 0.53 0.63 No 7/25/2003 
SL-3C-5 19,650 0 3 60 ? v  0.46 0.76 No 7/25/2003 
* v = vertically positioned lysimeters; depth = distance below bottom of biosolids row. 
East = laterally positioned lysimeter placed at the specified distance from the east edge of the biosolids row at depth equal to 
the depth of the biosolids row. 
West = laterally positioned lysimeter placed at the specified distance from the west edge of the biosolids row at depth equal to 
the depth of the biosolids row. 
 
 
 274
Table 38.  Suction lysimeter (SL) installation information ? block 3: 58,900 kg N/ha. 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which SL 
Installed 
SL Position 
in Relation 
to Biosolids 
Row (cm)* 
Biosolids 
Depth 
(m) 
Overburden 
Depth (m) 
Water Seepage 
Into Installation 
Cavity? 
Date 
Installed 
SL-3D-1 58,900 1074 19 30 ? west 0.91 0.58 Yes - pooled 8/27/2003 
SL-3D-2 58,900 1074 19 15 ? east 0.91 0.58 Yes - pooled 8/27/2003 
SL-3D-3 58,900 1074 18 15 ? v 0.99 0.66 No 8/27/2003 
SL-3D-4 58,900 1074 17 60 ? v 1.17 0.68 No 8/27/2003 
SL-3D-5 58,900 1074 16 30 ? v 1.19 0.68 No 8/27/2003 
SL-3E-1 58,900 716 18 60 ? v 1.19 0.61 No 8/27/2003 
SL-3E-2 58,900 716 17 15 ? v 1.19 0.66 No 8/27/2003 
SL-3E-3 58,900 716 15 30 ? west 1.24 0.68 Yes - pooled 8/27/2003 
SL-3E-4 58,900 716 15 15 ? east 1.24 0.68 No 8/27/2003 
SL-3E-5 58,900 716 14 30 ? v 1.27 0.68 Yes - pooled 8/27/2003 
SL-3F-1 58,900 0 20 15 ? v 0.94 0.48 No 8/26/3003 
SL-3F-2 58,900 0 19 60 ? v 0.94 0.51 No 8/26/3003 
SL-3F-3 58,900 0 16 30 ? v 1.04 0.63 No 8/26/3003 
SL-3F-4 58,900 0 15 30 ? west 0.89 0.68 No 8/26/3003 
SL-3F-5 58,900 0 15 15 ? east  0.89 0.68 No 8/26/3003 
* v = vertically positioned lysimeters; depth = distance below bottom of biosolids row. 
East = laterally positioned lysimeter placed at the specified distance from the east edge of the biosolids row at depth equal to 
the depth of the biosolids row. 
West = laterally positioned lysimeter placed at the specified distance from the west edge of the biosolids row at depth equal to 
the depth of the biosolids row. 
 
 
 
 
 
 
 275
Table 39.  Suction lysimeter (SL) installation information ? block 3: 39,300 kg N/ha. 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which SL 
Installed 
SL Position 
in Relation 
to Biosolids 
Row (cm)* 
Biosolids 
Depth 
(m) 
Overburden 
Depth (m) 
Water Seepage 
Into Installation 
Cavity? 
Date 
Installed 
SL-3G-1 39,300 1074 31 30 ? v 0.94 0.45 No 8/4/2003 
SL-3G-2 39,300 1074 31 15 ? v 0.94 0.45 No 8/4/2003 
SL-3G-3 39,300 1074 30 30 ? west 0.84 0.61 No 8/4/2003 
SL-3G-4 39,300 1074 30 15 ? east 0.84 0.61 No 8/4/2003 
SL-3G-5 39,300 1074 29 60 ? v 0.89 0.45 No 8/4/2003 
SL-3H-1 39,300 716 28 15 ? v 0.76 0.68 No 8/5/2003 
SL-3H-2 39,300 716 27 30 ? v  0.76 0.61 No 8/5/2003 
SL-3H-3 39,300 716 26 60 ? v 0.76 0.61 No 8/5/2003 
SL-3H-4 39,300 716 25 30 ? west 0.81 0.61 No 8/5/2003 
SL-3H-5 39,300 716 25 15 ? east 0.81 0.61 No 8/5/2003 
SL-3I-1 39,300 0 31 15 ? v 0.76 0.38 No 8/5/2003 
SL-3I-2 39,300 0 30 60 ? v 0.68 0.48 No 8/5/2003 
SL-3I-3 39,300 0 27 30 ? west 0.71 0.56 No 8/5/2003 
SL-3I-4 39,300 0 27 15 ? east 0.71 0.56 No 8/5/2003 
SL-3I-5 39,300 0 26 30 ? v  0.71 0.56 No 8/5/2003 
 
 
 276
 
Table 40.  Suction lysimeter (SL) installation information ? block 3: 0 kg N/ha 
Subplot 
ID 
Application 
Rate  
(kg N/ha) 
Tree 
Density 
(trees/ha) 
Biosolids 
Row Under 
Which SL 
Installed 
SL Position 
in Relation 
to Biosolids 
Row (cm)* 
Biosolids 
Depth 
(m) 
Overburden 
Depth (m) 
Water Seepage 
Into Installation 
Cavity? 
Date 
Installed 
SL-4A-1 0 0 NA 30 ? v  0.32 0.30 No 8/18/2003 
SL-4A-2 0 0 NA 60 ? v  0.32 0.30 No 8/18/2003 
SL-4A-3 0 0 NA 30 ? west 0.32 0.30 No 8/18/2003 
SL-4A-4 0 0 NA 15 ? east 0.32 0.30 No 8/18/2003 
SL-4A-5 0 0 NA 15 ? v  0.32 0.30 No 8/18/2003 
* v = vertically positioned lysimeters; depth = distance below bottom of biosolids row.  East = laterally positioned lysimeter 
placed at the specified distance from the east edge of the biosolids row at depth equal to the depth of the biosolids row.  West = 
laterally positioned lysimeter placed at the specified distance from the west edge of the biosolids row at depth equal to the depth of the 
biosolids row.
 
 277
Appendix 2 ? Supplemental Results 
 
Biosolids Supplemental Results 
Table 41.  Biosolids analysis results (wet weight basis). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Sample ID = 
Date of 
Collection N (%)
NH4-N 
(%)
P2O5 
(%)
K2O 
(%) Ca (%) Mg (%) S (%)
Mn 
(ppm)
Zn 
(ppm)
Cu 
(ppm)
Moisture 
(%)
3/7/2002 1.09 0.06 0.80 0.09 3.12 0.06 0.05 29.30 89.00 52.60 74.70
3/18/2002 1.17 0.12 0.69 0.09 2.81 0.05 0.18 30.40 78.70 49.00 74.90
3/15/2002 1.15 0.06 0.80 0.07 2.70 0.05 0.17 29.60 77.00 55.80 77.20
3/13/2002 0.96 0.03 0.75 0.07 3.19 0.07 0.18 44.20 91.10 69.30 65.50
6/25/2002 1.23 0.08 0.82 0.08 3.35 0.06 0.20 64.10 97.50 58.60 69.60
6/26/2002 1.07 0.05 0.75 0.07 2.59 0.05 0.16 56.40 78.70 50.10 74.70
6/28/2002 1.54 0.09 1.02 0.09 2.80 0.06 0.24 71.60 143.30 77.50 67.40
7/26/2002 1.11 0.05 0.77 0.08 2.24 0.05 0.21 38.50 92.90 58.30 74.00
7/29/2002 1.16 0.06 0.78 0.07 2.45 0.05 0.21 28.80 107.60 62.10 73.60
7/30/2002 1.19 0.06 0.76 0.06 2.31 0.05 0.20 39.80 134.90 55.70 73.50
8/23/2002 1.18 0.04 0.82 0.09 2.19 0.06 0.31 48.90 131.40 79.00 71.10
8/27/2002 1.21 0.05 0.74 0.12 3.70 0.07 0.34 42.20 138.50 80.00 68.20
8/28/2002 1.44 0.09 1.07 0.10 3.30 0.06 0.30 74.50 192.00 76.40 68.70
9/27/2002 1.10 0.06 0.85 0.09 2.79 0.07 0.23 79.40 96.40 56.00 73.10
9/30/2002 1.05 0.08 0.83 0.11 2.84 0.08 0.21 72.90 89.40 63.60 74.20
9/30/2002 1.17 0.08 0.91 0.14 4.63 0.10 0.31 81.20 171.50 86.30 63.30
10/25/2002 1.10 0.05 0.91 0.13 2.66 0.07 0.18 70.10 170.50 59.40 75.80
10/28/2002 1.32 0.08 1.04 0.13 4.90 0.08 0.22 71.20 129.90 71.20 68.80
10/28/2002 1.36 0.11 1.08 0.14 6.49 0.08 0.24 77.20 187.30 72.80 66.30
11/27/2002 1.19 0.07 0.89 0.11 2.98 0.07 0.17 60.90 100.80 57.60 72.30
11/27/2002 1.26 0.07 0.87 0.13 4.87 0.91 0.18 64.10 153.50 51.70 68.10
11/27/2002 1.17 0.05 0.78 0.12 2.34 0.06 0.15 46.00 80.60 49.30 74.60
12/23/2002 0.92 0.04 0.66 0.11 2.24 0.05 0.12 39.25 70.69 40.36 77.70
12/23/2002 0.99 0.04 0.70 0.11 2.59 0.06 0.13 43.29 79.33 48.67 76.60
12/23/2002 1.14 0.06 0.87 0.13 6.27 0.08 0.18 48.76 87.46 47.82 68.54
1/20/2003 1.22 0.06 0.97 0.15 6.09 0.09 0.20 46.62 91.60 49.57 67.17
1/21/2003 1.11 0.07 0.83 0.18 3.57 0.06 0.16 42.44 85.67 46.66 73.64
1/24/2003 1.02 0.05 0.90 0.23 3.75 0.08 0.18 45.00 93.05 52.74 72.39
2/25/2003 1.23 0.05 0.87 0.20 3.68 0.08 0.16 40.44 99.51 61.92 68.41
3/10/2003 1.11 0.06 0.82 0.15 3.74 0.07 0.15 35.13 94.76 54.32 70.48
3/4/2003 1.08 0.05 0.77 0.13 3.61 0.07 0.13 30.88 99.44 54.11 71.67
3/25/2003 1.10 0.07 0.81 0.13 5.01 0.08 0.16 41.93 95.47 54.96 71.67
3/25/2003 1.18 0.06 0.92 0.21 5.78 0.11 0.18 55.56 107.53 63.92 70.13
3/26/2003 1.07 0.35 0.93 0.11 2.14 0.06 0.13 41.58 229.51 56.22 76.77
4/25/2003 1.19 0.07 0.83 0.10 2.12 0.06 0.13 32.98 88.39 51.90 72.97
4/30/2003 1.09 0.09 0.64 0.07 2.26 0.05 0.13 25.32 75.18 44.58 73.62
4/30/2003 1.06 0.08 0.74 0.07 2.41 0.05 0.13 28.61 78.49 45.41 73.75
Mean 1.15 0.07 0.84 0.12 3.42 0.09 0.19 49.16 111.04 58.53 71.76
Standard 
Deviation 0.12 0.05 0.11 0.04 1.25 0.14 0.06 16.70 38.40 11.19 3.55
Coefficient of 
Variation 10.57 69.66 12.78 35.49 36.67 155.85 31.73 33.96 34.58 19.11 4.94
 
 278
Table 42.  Biosolids analysis results (dry weight basis). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Sample ID = 
Date of 
Collection
Moisture 
(%)
Solids (%)                
= 100-%M N (%)
NH4-N 
(%)
P2O5 
(%)
K2O 
(%) Ca (%) Mg (%) S (%)
Mn 
(ppm)
Zn 
(ppm)
Cu 
(ppm)
3/7/2002 74.70 25.30 4.31 0.24 3.16 0.36 12.33 0.24 0.20 115.81 351.78 207.91
3/18/2002 74.90 25.10 4.66 0.48 2.75 0.36 11.20 0.20 0.72 121.12 313.55 195.22
3/15/2002 77.20 22.80 5.04 0.26 3.51 0.31 11.84 0.22 0.75 129.82 337.72 244.74
3/13/2002 65.50 34.50 2.78 0.09 2.17 0.20 9.25 0.20 0.52 128.12 264.06 200.87
6/25/2002 69.60 30.40 4.05 0.26 2.70 0.26 11.02 0.20 0.66 210.86 320.72 192.76
6/26/2002 74.70 25.30 4.23 0.20 2.96 0.28 10.24 0.20 0.63 222.92 311.07 198.02
6/28/2002 67.40 32.60 4.72 0.28 3.13 0.28 8.59 0.18 0.74 219.63 439.57 237.73
7/26/2002 74.00 26.00 4.27 0.19 2.96 0.31 8.62 0.19 0.81 148.08 357.31 224.23
7/29/2002 73.60 26.40 4.39 0.23 2.95 0.27 9.28 0.19 0.80 109.09 407.58 235.23
7/30/2002 73.50 26.50 4.49 0.23 2.87 0.23 8.72 0.19 0.75 150.19 509.06 210.19
8/23/2002 71.10 28.90 4.08 0.14 2.84 0.31 7.58 0.21 1.07 169.20 454.67 273.36
8/27/2002 68.20 31.80 3.81 0.16 2.33 0.38 11.64 0.22 1.07 132.70 435.53 251.57
8/28/2002 68.70 31.30 4.60 0.29 3.42 0.32 10.54 0.19 0.96 238.02 613.42 244.09
9/27/2002 73.10 26.90 4.09 0.22 3.16 0.33 10.37 0.26 0.86 295.17 358.36 208.18
9/30/2002 74.20 25.80 4.07 0.31 3.22 0.43 11.01 0.31 0.81 282.56 346.51 246.51
9/30/2002 63.30 36.70 3.19 0.22 2.48 0.38 12.62 0.27 0.84 221.25 467.30 235.15
10/25/2002 75.80 24.20 4.55 0.21 3.76 0.54 10.99 0.29 0.74 289.67 704.55 245.45
10/28/2002 68.80 31.20 4.23 0.26 3.33 0.42 15.71 0.26 0.71 228.21 416.35 228.21
10/28/2002 66.30 33.70 4.04 0.33 3.20 0.42 19.26 0.24 0.71 229.08 555.79 216.02
11/27/2002 72.30 27.70 4.30 0.25 3.21 0.40 10.76 0.25 0.61 219.86 363.90 207.94
11/27/2002 68.10 31.90 3.95 0.22 2.73 0.41 15.27 2.85 0.56 200.94 481.19 162.07
11/27/2002 74.60 25.40 4.61 0.20 3.07 0.47 9.21 0.24 0.59 181.10 317.32 194.09
12/23/2002 77.70 22.30 4.13 0.18 2.96 0.49 10.04 0.22 0.54 176.01 317.00 180.99
12/23/2002 76.60 23.40 4.23 0.17 2.99 0.47 11.07 0.26 0.56 185.00 339.02 207.99
12/23/2002 68.54 31.46 3.62 0.19 2.77 0.41 19.93 0.25 0.57 154.99 278.00 152.00
1/20/2003 67.17 32.83 3.72 0.18 2.95 0.46 18.55 0.27 0.61 142.00 279.01 150.99
1/21/2003 73.64 26.36 4.21 0.27 3.15 0.68 13.54 0.23 0.61 161.00 325.00 177.01
1/24/2003 72.39 27.61 3.69 0.18 3.26 0.83 13.58 0.29 0.65 162.98 337.02 191.02
2/25/2003 68.41 31.59 3.89 0.16 2.75 0.63 11.65 0.25 0.51 128.02 315.00 196.01
3/10/2003 70.48 29.52 3.76 0.20 2.78 0.51 12.67 0.24 0.51 119.00 321.00 184.01
3/4/2003 71.67 28.33 3.81 0.18 2.72 0.46 12.74 0.25 0.46 109.00 351.01 191.00
3/25/2003 71.67 28.33 3.88 0.25 2.86 0.46 17.68 0.28 0.56 148.01 336.99 194.00
3/25/2003 70.13 29.87 3.95 0.20 3.08 0.70 19.35 0.37 0.60 186.01 359.99 213.99
3/26/2003 76.77 23.23 4.61 1.51 4.00 0.47 9.21 0.26 0.56 178.99 987.99 242.01
4/25/2003 72.97 27.03 4.40 0.26 3.07 0.37 7.84 0.22 0.48 122.01 327.01 192.01
4/30/2003 73.62 26.38 4.13 0.34 2.43 0.27 8.57 0.19 0.49 95.98 284.99 168.99
4/30/2003 73.75 26.25 4.04 0.30 2.82 0.27 9.18 0.19 0.50 108.99 299.01 172.99
Mean 71.76 28.24 4.12 0.27 2.99 0.41 11.94 0.31 0.66 173.55 394.20 207.42
Standard 
Deviation 3.55 3.55 0.43 0.22 0.36 0.14 3.39 0.43 0.17 53.57 139.15 29.54
Coefficient of 
Variation 4.94 12.56 10.37 83.19 12.16 33.89 28.42 140.58 26.42 30.87 35.30 14.24
 
 279
Table 43.  Biosolids results: revised after removal of outliers (dry weight basis). 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Sample ID NH4-N (%) Sample ID Mg (%)
3/7/2002 0.24 3/7/2002 0.24
3/18/2002 0.48 3/18/2002 0.20
3/15/2002 0.26 3/15/2002 0.22
3/13/2002 0.09 3/13/2002 0.20
6/25/2002 0.26 6/25/2002 0.20
6/26/2002 0.20 6/26/2002 0.20
6/28/2002 0.28 6/28/2002 0.18
7/26/2002 0.19 7/26/2002 0.19
7/29/2002 0.23 7/29/2002 0.19
7/30/2002 0.23 7/30/2002 0.19
8/23/2002 0.14 8/23/2002 0.21
8/27/2002 0.16 8/27/2002 0.22
8/28/2002 0.29 8/28/2002 0.19
9/27/2002 0.22 9/27/2002 0.26
9/30/2002 0.31 9/30/2002 0.31
9/30/2002 0.22 9/30/2002 0.27
10/25/2002 0.21 10/25/2002 0.29
10/28/2002 0.26 10/28/2002 0.26
10/28/2002 0.33 10/28/2002 0.24
11/27/2002 0.25 11/27/2002 0.25
11/27/2002 0.22 11/27/2002 0.24
11/27/2002 0.20 12/23/2002 0.22
12/23/2002 0.18 12/23/2002 0.26
12/23/2002 0.17 12/23/2002 0.25
12/23/2002 0.19 1/20/2003 0.27
1/20/2003 0.18 1/21/2003 0.23
1/21/2003 0.27 1/24/2003 0.29
1/24/2003 0.18 2/25/2003 0.25
2/25/2003 0.16 3/10/2003 0.24
3/10/2003 0.20 3/4/2003 0.25
3/4/2003 0.18 3/25/2003 0.28
3/25/2003 0.25 3/25/2003 0.37
3/25/2003 0.20 3/26/2003 0.26
4/25/2003 0.26 4/25/2003 0.22
4/30/2003 0.34 4/30/2003 0.19
4/30/2003 0.30 4/30/2003 0.19
Mean 0.23 0.24
Standard Deviation 0.07 0.04
Coefficient of 
Variation 29.94 17.35
 
 280
Hydraulic Conductivity Supplemental Results 
Table 44.  Hydraulic conductivity by block 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Subplot ID
Depth from 
Top of 
Installation 
Trench (cm)
Hydraulic 
Conductivity 
(cm/sec) Subplot ID
Depth from 
Top of 
Installation 
Trench (cm)
Hydraulic 
Conductivity 
(cm/sec) Subplot ID
Depth from 
Top of 
Installation 
Trench (cm)
Hydraulic 
Conductivity 
(cm/sec)
1A-shallow 64 5.27E-03 2A-shallow 94 4.66E-04 3A-shallow 30 4.05E-07
1A-middle 94 1.64E-03 2A-middle 124 7.73E-04 3A-middle 61 1.40E-07
1A-deep 124 3.05E-03 2A-deep 155 7.47E-05 3A-deep 91 1.30E-05
1B-shallow 64 1.71E-03
1B-middle 94 7.78E-05 2B-middle 102 4.73E-04
1B-deep 124 9.53E-06 2B-deep 132 9.17E-05 3B-deep 94 1.02E-05
1C-shallow 64 8.33E-04 2C-shallow 76 2.88E-05 3C-shallow 41 2.68E-04
1C-middle 94 1.67E-03 2C-middle 107 3.60E-04 3C-middle 71 2.84E-05
1C-deep 124 2.92E-03 2C-deep 137 2.23E-03 3C-deep 102 9.44E-05
1D-shallow 46 1.85E-02 2D-shallow 74 1.01E-04 3D-shallow 107 1.48E-06
1D-middle 76 1.71E-02 2D-middle 104 2.18E-05 3D-middle 137 8.91E-06
1D-deep 107 1.81E-02 2D-deep 135 4.36E-05 3D-deep 168 3.13E-06
1E-shallow 48 4.71E-04 2E-shallow 64 1.27E-04 3E-shallow 107 3.81E-06
1E-middle 79 6.03E-03 2E-middle 94 2.12E-05 3E-middle 137 7.44E-07
1E-deep 109 1.57E-04 2E-deep 124 9.05E-07 3E-deep 168 9.99E-05
1F-shallow 38 2.11E-03 2F-shallow 69 1.32E-04 3F-shallow 102 1.41E-04
1F-middle 69 8.56E-05 2F-middle 99 5.77E-04 3F-middle 132 3.74E-06
1F-deep 99 7.64E-05 2F-deep 130 5.30E-05 3F-deep 163 5.48E-06
1G-shallow 74 2.77E-04 2G-shallow 41 4.77E-05 3G-shallow 72 3.24E-06
1G-middle 104 4.10E-04 2G-middle 71 4.67E-05 3G-middle 103 1.77E-05
1G-deep 135 2.52E-03 2G-deep 102 4.59E-05 3G-deep 133 1.67E-04
1H-shallow 81 2.40E-04 2H-shallow 46 9.93E-05 3H-shallow 56 3.80E-04
1H-middle 112 4.75E-04 2H-middle 76 9.16E-06 3H-middle 86 1.38E-05
1H-deep 142 3.10E-04 2H-deep 107 4.74E-05 3H-deep 117 5.76E-04
1I-shallow 97 1.26E-04 2I-shallow 41 1.40E-04 3I-shallow 53 4.04E-04
1I-middle 127 4.00E-04 2I-middle 71 8.74E-04 3I-middle 84 2.91E-05
1I-deep 157 3.99E-03 2I-deep 102 4.67E-04 3I-deep 114 1.52E-04
4C-shallow 41 1.02E-06 4B-shallow 41 2.28E-04 4A-shallow 41 1.79E-05
4C-middle 71 2.03E-03 4B-middle 71 4.89E-04 4A-middle 71 2.07E-04
4C-deep 102 1.92E-03 4B-deep 102 1.31E-04 4A-deep 102 1.32E-04
Block 1 Block 2 Block 3
 
 281
Total Nitrogen and Ammonium Supplemental Results 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 177.  Total nitrogen concentrations for low-level app. rate in pan lysimeters. 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 178.  Total nitrogen concentrations for mid-level app. rate in pan lysimeters. 
1
10
100
1000
10000
Q1-
B1
Q1-
B2
Q1-
B3
Q2-
B1
Q2-
B2
Q2-
B3
Q3-
B1
Q3-
B2
Q3-
B3
Q4-
B1
Q4-
B2
Q4-
B3
Q5-
B1
Q5-
B2
Q5-
B3
Q6-
B1
Q6-
B2
Q6-
B3
Q7-
B1
Q7-
B2
Q7-
B3
Q8-
B1
Q8-
B2
Q8-
B3
Quarter-Block ID
To
tal
 N
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
0 kgN/ha; 0 trees/ha 19,650 kgN/ha; 0 trees/ha
19,650 kgN/ha; 716 trees/ha 19,650 kgN/ha; 1074 trees/ha
Apr-May-03 Jun-Aug-03 Sept-Nov-03
Dec-03, 
Jan/Feb-04
Mar-May-04 Jun/Aug 
04
Oct-04 Dec-04
1
10
100
1000
10000
Q1-
B1
Q1-
B2
Q1-
B3
Q2-
B1
Q2-
B2
Q2-
B3
Q3-
B1
Q3-
B2
Q3-
B3
Q4-
B1
Q4-
B2
Q4-
B3
Q5-
B1
Q5-
B2
Q5-
B3
Q6-
B1
Q6-
B2
Q6-
B3
Q7-
B1
Q7-
B2
Q7-
B3
Q8-
B1
Q8-
B2
Q8-
B3
Quarter-Block ID
To
tal
 N
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
0 kgN/ha; 0 trees/ha 39,300 kgN/ha; 0 trees/ha
39,300 kgN/ha; 716 trees/ha 39,300 kgN/ha; 1074 trees/ha
Apr-May-03 Jun-Aug-03 Sept-Nov-03 Dec-03, 
Jan/Feb-04
Mar-May-04 Jun/Aug 
04
Oct-04 Dec-04
 
 282
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Figure 179.  Total nitrogen concentrations for high-level app. rate in pan lysimeters. 
 
 
 
1
10
100
1000
10000
Q1-
B1
Q1-
B2
Q1-
B3
Q2-
B1
Q2-
B2
Q2-
B3
Q3-
B1
Q3-
B2
Q3-
B3
Q4-
B1
Q4-
B2
Q4-
B3
Q5-
B1
Q5-
B2
Q5-
B3
Q6-
B1
Q6-
B2
Q6-
B3
Q7-
B1
Q7-
B2
Q7-
B3
Q8-
B1
Q8-
B2
Q8-
B3
Quarter-Block ID
To
tal
 N
 (m
g/L
)
Lo
ga
rit
hm
ic 
Sc
ale
0 kgN/ha; 0 trees/ha 58,900 kgN/ha; 0 trees/ha
58,900 kgN/ha; 716 trees/ha 58,900 kgN/ha; 1074 trees/ha
Apr-May-03 Jun-Aug-03 Sept-Nov-03 Dec-03, 
Jan/Feb-04
Mar-May-04 Jun/Aug 
04
Oct-04 Dec-04
 
 283
Table 45.  Trends for pan lysimeter total N and NH4+ results with values > 100 mg/L. 
Application 
Rate Total N Trends 
19,650 kgN/ha 0 trees/ha had the most numerous values greater than 100 mg/L (19).  Values 
ranged from 158-496 mg/L and were distributed amongst all blocks and 
quarters. 
716 trees/ha had 18 values > 100 mg/L, with the consistently highest values 
of the tree densities, as follows: 
? Block 2 had the highest values ranging from 750-2800 mg/L across all 
quarters. 
? Blocks 1 and 3 had lower values between 104-500 mg/L in quarters 3-8. 
1074 trees/ha had the lowest number of values greater than 100 mg/L (8).  
These were associated with blocks 1 and 3 and ranged from 105-184 mg/L 
across most quarters. 
39,300 kgN/ha 0 trees/ha had the most values greater than 100 mg/L (18) and higher values 
with a range between 204 ? 2275 mg/L.  Most values were associated with 
blocks 1 and 3 across all quarters, though several values were from block 2. 
716 trees/ha had the next highest number of values (16), ranging between 147 
? 580 mg/L.  All of these values were associated with blocks 2 and 3.  Block 
1 had many values less than 10 mg/L. 
1074 trees/ha had 14 values ranging from 104-953 mg/L.  All were associated 
with blocks 1 and 2 except one value from block 3. 
58,900 kgN/ha 0 trees/ha had the most values greater than 100 mg/L (11).  Seven values were 
from block 2 across all quarters and were all > 1000 mg/L.  The remaining 
four values were from block 1, quarters 5-8, and ranged from 103 ? 150 
mg/L. 
716 trees/ha had only three values greater than 100 mg/L, ranging from 130-
196 mg/L.  All were associated with block 1, quarters 6-8.  All block 2 and 3 
values were less than 15 mg/L. 
1074 trees/ha had the second highest number of values (8) ranging from 147 - 
2202 mg/L.  Seven values were from block 3 and ranged between 781 - 2202 
mg/L; one value was from block 1 and was 147 mg/L. 
 
 284
 
Application 
Rate NH4+ Trends 
19, 650 kgN/ha 0 trees/ha had the most numerous values greater than 100 mg/L (20).  Values 
ranged from 102-415 mg/L and were distributed amongst all blocks and 
quarters. 
716 trees/ha had 18 values > 100 mg/L, with the consistently highest values 
of the tree densities, as follows: 
? Block 2 had the highest values ranging from 867-3178 mg/L across all 
quarters. 
? Blocks 1 and 3 had lower values between 112-508 mg/L in quarters 3-8. 
1074 trees/ha had the lowest number of values greater than 100 mg/L (9).  
These were associated with blocks 1 and 3 and ranged from 107-188 mg/L 
across most quarters. 
39,300 kgN/ha 0 trees/ha had the most values greater than 100 mg/L (18) and higher values, 
with a range between 214 ? 1272 mg/L.  Most values were associated with 
blocks 1 and 3 across all quarters, though two of the higher values were from 
block 2, quarters 5 and 6. 
716 trees/ha had the next highest number of values (15), ranging from 164-
659 mg/L.  All of these values were associated with blocks 2 and 3.  Block 1 
had one value at 20 mg/L and the rest were less than 10 mg/L. 
1074 trees/ha had 14 values greater than 100 mg/L that spanned all quarters.  
Block 2 had the six highest values, with a range of 681-1073.  Block 1 had 
seven values from 108-241 mg/L.  Block 3 had one value at 138 mg/L. 
58,900 kgN/ha 0 trees/ha had the most values greater than 100 mg/L (11).  Seven values were 
from block 2 across all quarters and were between 982-2321 mg/L.  The 
remaining four values were from block 1, quarters 5-8, and ranged from 108 ? 
158 mg/L. 
716 trees/ha had only three values greater than 100 mg/L, ranging from 123-
208 mg/L.  All were associated with block 1, quarters 6-8.  All block 2 and 3 
values were less than 15 mg/L. 
1074 trees/ha had the second highest number of values (8), seven of which 
were from block 3 and ranged between 654 - 2456 mg/L with a steady 
increase over time.  The other value was from block 1, quarter 8, at a much 
lower value of 144 mg/L. 
 
  
285
 
                       
  
    Fig
ure
 180.  T
ota
l ni
trog
en c
onc
ent
rat
ions
 for
 low
-le
ve
l a
ppl
ica
tion r
ate
 in s
uc
tion l
ysi
me
ter
 (S
L)
 sa
mpl
es ? a
ll qua
rte
rs.
 
0110
10
0
10
00
10
00
0
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
T o t a l  N  ( m g / L )
L o g a r i t h m i c  S c a l e
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 7
16
 tre
es/
ha
19
,65
0 k
gN
/ha
; 1
07
4 tr
ees
/ha
  
286
                      Fig
ure
 181.  T
ota
l ni
trog
en c
onc
ent
rat
ions
 for
 low
-le
ve
l a
pp. r
ate
 in S
L s
am
ple
s: Q
4&
5. 
      
    
            Fig
ure
 182.  T
ota
l ni
trog
en c
onc
ent
rat
ions
 for
 low
-le
ve
l a
pp. r
ate
 in S
L s
am
ple
s: Q
6&
7.
0110
10
0
10
00
10
00
0
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
Total N (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 7
16
 tre
es/
ha
19
,65
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
0110
10
0
10
00
10
00
0
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
Total N (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 0
 tre
es/
ha
19
,65
0 k
gN
/ha
; 7
16
 tre
es/
ha
19
,65
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
287
                              Fig
ure
 183.  T
ota
l ni
trog
en c
onc
ent
rat
ions
 for
 m
id-
leve
l a
ppl
ica
tion r
ate
 in s
uc
tion l
ysi
me
ter
 (S
L)
 sa
mpl
es ? a
ll qua
rte
rs.
 
0110
10
0
10
00
10
00
0
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osit
ion
 ID
T o t a l  N  ( m g / L )
L o g a r i t h m i c  S c a l e
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 0
 tre
es/h
a
39
,30
0 k
gN
/ha
; 7
16
 tre
es/
ha
39
,30
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
288
                      Fig
ure
 184.  T
ota
l ni
trog
en c
onc
ent
rat
ions
 for
 m
id-
leve
l a
pp. r
ate
 in S
L s
am
ple
s: Q
4&
5. 
                      Fig
ure
 185.  T
ota
l ni
trog
en c
onc
ent
rat
ions
 for
 m
id-
leve
l a
pp. r
ate
 in S
L s
am
ple
s: Q
6&
7. 
0110
10
0
10
00
10
00
0
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
Total N (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 7
16
 tre
es/
ha
39
,30
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
0110
10
0
10
00
10
00
0
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
Total N (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 0
 tre
es/
ha
39
,30
0 k
gN
/ha
; 7
16
 tre
es/
ha
39
,30
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
  
289
                              Fig
ure
 186.  T
ota
l ni
trog
en c
onc
ent
rat
ions
 for
 hi
gh-
leve
l a
ppl
ica
tion r
ate
 in s
uc
tion l
ysi
me
ter
 (S
L)
 sa
mpl
es ? a
ll qua
rte
rs.
 
0110
10
0
10
00
10
00
0
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
T o t a l  N  ( m g / L )
L o g a r i t h m i c  S c a l e
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 0
 tre
es/h
a
58
,90
0 k
gN
/ha
; 7
16
 tre
es/
ha
58
,90
0 k
gN
/ha
; 1
07
4 tr
ees
/ha
  
290
                      Fig
ure
 187.  T
ota
l ni
trog
en c
onc
ent
rat
ions
 for
 hi
gh-
leve
l a
pp. r
ate
 in S
L s
am
ple
s: Q
4&
5. 
                     Fig
ure
 188.  T
ota
l ni
trog
en c
onc
ent
rat
ions
 for
 hi
gh-
leve
l a
pp. r
ate
 in S
L s
am
ple
s: Q
6&
7. 
0110
10
0
10
00
10
00
0
Q4-B1-PV15
Q4-B1-PV30
Q4-B1-PV60
Q4-B1-PL15
Q4-B1-PL30
Q4-B2-PV15
Q4-B2-PV30
Q4-B2-PV60
Q4-B2-PL15
Q4-B2-PL30
Q4-B3-PV15
Q4-B3-PV30
Q4-B3-PV60
Q4-B3-PL15
Q4-B3-PL30
Q5-B1-PV15
Q5-B1-PV30
Q5-B1-PV60
Q5-B1-PL15
Q5-B1-PL30
Q5-B2-PV15
Q5-B2-PV30
Q5-B2-PV60
Q5-B2-PL15
Q5-B2-PL30
Q5-B3-PV15
Q5-B3-PV30
Q5-B3-PV60
Q5-B3-PL15
Q5-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
Total N (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 7
16
 tre
es/
ha
58
,90
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
0110
10
0
10
00
10
00
0
Q6-B1-PV15
Q6-B1-PV30
Q6-B1-PV60
Q6-B1-PL15
Q6-B1-PL30
Q6-B2-PV15
Q6-B2-PV30
Q6-B2-PV60
Q6-B2-PL15
Q6-B2-PL30
Q6-B3-PV15
Q6-B3-PV30
Q6-B3-PV60
Q6-B3-PL15
Q6-B3-PL30
Q7-B1-PV15
Q7-B1-PV30
Q7-B1-PV60
Q7-B1-PL15
Q7-B1-PL30
Q7-B2-PV15
Q7-B2-PV30
Q7-B2-PV60
Q7-B2-PL15
Q7-B2-PL30
Q7-B3-PV15
Q7-B3-PV30
Q7-B3-PV60
Q7-B3-PL15
Q7-B3-PL30
Qu
ar
ter
-B
loc
k-P
osi
tio
n I
D
Total N (mg/L)
Logarithmic Scale
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 0
 tre
es/
ha
58
,90
0 k
gN
/ha
; 7
16
 tre
es/
ha
58
,90
0 k
gN
/ha
; 1
07
4 t
ree
s/h
a
 
 291
 
Table 46.  Trends for suction lysimeter total N and NH4+ results with focus on values > 100 mg/L. 
Application 
Rate (kgN/ha) 
Tree 
Density 
(trees/ha) Total Nitrogen Trends* Ammonium Trends* 
0 16 results > 1000 mg/L:   
PV15, all blocks-all Q 
PV30, B3-all Q 
17 results from 100-1000 mg/L:   
PV30, B1&2-all Q 
PV60, B1-Q4,6,7, B3-Q6&7 
several PL15 and PL30 
20 results < 100 mg/L 
16 results > 1000 mg/L:   
PV15, all blocks-all Q 
PV30, B3-all Q 
18 results from 100-1000 mg/L:   
PV30, B1&2-all Q 
PV60, B1-all Q, B3-Q6&7 
several PL15 and PL30 
19 results < 100 mg/L 
716 11 results > 1000 mg/L:   
PV15, B1&3-all Q 
PV30, B1-most Q 
24 results from 100-1000 mg/L:  
PV15, B2-all Q 
PV30, B3 ? all Q 
PV60, all blocks ? most Q 
PL15, B1&2-Q6&7 
25 results < 100 mg/L 
11 results > 1000 mg/L:   
PV15, B1&3-all Q 
PV30, B1-most Q 
25 results from 100-1000 mg/L:  
PV15, B2-all Q 
PV30, B1-Q4, B3 ? all Q 
PV60, all blocks ? all Q 
PL15, B1&2- Q6&7 
24 results < 100 mg/L 
19,650 
1074 10 results > 1000 mg/L: 
PV15, B1-Q6&7, B2&3-all Q 
18 results from 100-1000 mg/L: 
PV30, B1-Q4&5 
PL15, all blocks  - most Q 
PL 30, B2-allQ, B3-Q6 
26 results < 100 mg/L 
10 results > 1000 mg/L: 
PV15, B1-Q6&7, B2&3-all Q 
18 results from 100-1000 mg/L: 
PV30, B1-Q4&5 
PL15, all blocks  - most Q 
PL 30, B2-allQ, B3-Q6 
26 results < 100 mg/L 
 
 292
Application 
Rate (kgN/ha) 
Tree 
Density 
(trees/ha) Total Nitrogen Trends* Ammonium Trends* 
0 13 results > 1000 mg/L 
PV15, all blocks ? all Q 
PV30, B1-Q7 
28 results from 100-1000 mg/L 
PV30, B1&2 - most Q 
PV60, B1&2 ? all Q 
PL15, B1&2 ? all Q 
PL30, B1-Q6&7, B2 ? all Q 
17 results < 100 mg/L 
13 results > 1000 mg/L 
PV15, all blocks ? all Q 
PV30, B1-Q7 
28 results from 100-1000 mg/L 
PV30, B1&2 - most Q 
PV60, B1&2 ? all Q 
PL15, B1&2 ? all Q 
PL30, B1-Q6&7, B2 ? all Q 
17 results < 100 mg/L 
716 10 results > 1000 mg/L 
PV15, B1-all Q, B2-Q6&7 
PV60, B1&2 ? several Q 
25 results from 100-1000 mg/L 
PV15, B2-Q5 
PV30, several results from B1&2 
PV60, several results from all blocks 
PL15, B1&2-all Q 
PL30, B1&2-all Q 
19 results < 100 mg/L 
10 results > 1000 mg/L 
PV15, B1-all Q, B2-Q6&7 
PV60, B1&2 ? several Q 
25 results from 100-1000 mg/L 
PV15, B2-Q5 
PV30, several results from B1&2 
PV60, several results from all blocks 
PL15, B1&2-all Q 
PL30, B1&2-all Q 
19 results < 100 mg/L 
39,300 
1074 7 results > 1000 mg/L 
PV15, B2-Q7, B3-all Q 
PV30, B1-Q6&7 
25 results from 100-1000 mg/L 
PV15, B1&2- most Q 
PV30, B1&3 ? most Q 
PV60, B3-all Q 
PL15, B1&2-Q6&7 
PL30-B2&3-some Q 
25 results < 100 mg/L 
7 results > 1000 mg/L 
PV15, B2-Q7, B3-all Q 
PV30, B1-Q6&7 
25 results from 100-1000 mg/L 
PV15, B1&2- all Q 
PV30, B1-Q4&5, B3 ? Q4, 5, 7 
PV60, B3-all Q 
PL15, B1&2-Q6&7 
PL30-B2&3-Q6&7 
25 results < 100 mg/L 
 
 293
Application 
Rate (kgN/ha) 
Tree 
Density 
(trees/ha) Total Nitrogen Trends* Ammonium Trends* 
0 11 results > 100 mg/L 
PV15, B2-all Q, B3-Q6&7 
PV30, B2 - Q5, 6, 7 
PV60, B1-Q6&7 
18 results from 100-1000 mg/L 
PV15, B1-Q6, B3-Q4&5 
PV30, B1-Q7, B2-Q4 
PV60, B1-Q5, B2-all Q, B3-Q6&7 
PL15, B1-Q6&7, B2-all Q 
30 results < 100 mg/L 
11 results > 100 mg/L 
PV15, B2-all Q, B3-Q6&7 
PV30, B2 - Q5, 6, 7 
PV60, B1-Q6&7 
19 results from 100-1000 mg/L 
PV15, B1-Q6, B3-Q4&5 
PV30, B1-Q7, B2-Q4 
PV60, B1-Q5, B2-all Q, B3-Q5, 6, 7 
PL15, B1-Q6&7, B2-all Q 
29 results < 100 mg/L 
716 13 results > 1000 mg/L 
PV15, B1-all Q 
PV30, B1&2-allQ 
PL15, B2-Q7 
16 results from 100-1000 mg/L 
PV15, B2&3- most Q 
PV60, B1-Q4, B2-all Q 
PL15, B1-all Q 
24 results < 100 mg/L 
13 results > 1000 mg/L 
PV15, B1-all Q 
PV30, B1&2-allQ 
PL15, B2-Q7 
17 results from 100-1000 mg/L 
PV15, B2&3- most Q 
PV60, B1-Q4, B2-all Q 
PL15, B1-all Q 
PL30, B3-Q6 
23 results < 100 mg/L 
58,900 
1074 13 results > 1000 mg/L 
PV15, B1-Q7, B3-all Q 
PV30, B2&3 ? most Q 
PV60, B1-Q4 
22 results from 100-1000 mg/L 
PV15, B1-Q4, 5, 6, B2-Q5, 6, 7 
PV30, B1-all Q 
PV60, B1&B3-most Q 
PL15, B2-Q6&7, B3-Q4, 6, and 7 
23 results < 100 mg/L 
12 results > 1000 mg/L 
PV15, B1-Q7, B3-Q4, 6, 7 
PV30, B2&3 ? most Q 
PV60, B1-Q4 
21 results from 100-1000 mg/L 
PV15, B1-Q4, 5, 6, B2-Q7, B3-Q5 
PV30, B1-all Q 
PV60, B1&B3-most Q 
PL15, B2-Q6&7, B3-Q4, 6, and 7 
25 results < 100 mg/L 
*Key to Abbreviations:  PV# = vertical lysimeter placed # distance (cm) below biosolids row; B = block; Q = quarter 
 
 
 
 294
 
Nitrate pan lysimeter statistical results: 
For each non-control application rate, a list of statistically significant differences in 
tree densities for specific quarters was determined.  These are itemized below. 
 
Application Rate:  19,650 kgN/ha 
0 trees/acre, Q2 is greater than 716 trees/ha, Q5 and Q8 
0 trees/ha, Q2 is greater than 1074 trees/ha, Q5 
0 trees/ha, Q5 and Q8 is less than 716 trees/ha, Q2 
716 trees/ha, Q5, Q6, and Q8 are less than 716 trees/ha, Q2 
For this low-level application rate, differences between tree densities are spotty, and 
do not show a particular trend. 
 
Application Rate:  39,300 kgN/ha 
0 trees/ha, Q2 is greater than 716 trees/ha, Q8 
0 trees/ha, Q4 is greater than 716 trees/ha, Q5 and Q8 
0 trees/ha, Q8 is greater than 716 trees/ha, Q5, Q6 and Q8 
0 trees/ha, Q3, Q5, Q6 is less than 1074trees/ha, Q8 
716 trees/ha, Q3-Q8 are less than 1074 trees/ha, Q8 
716 trees/ha, Q5 is less than 1074 trees/ha, Q2 and Q6 
716 trees/ha, Q8 is less than 1074 trees/ha, Q2-Q6 
Of the differences noted, the 716 trees/ha density has the preponderance of values 
less than the other densities, and 1074 trees/ha are always more than the other densities.  
Aside from this, no explicit trends are noted. 
 
Application Rate:  58,900 kgN/ha 
0 trees/ha, Q1, Q3 and Q4 are less than 716 trees/ha, Q1 
0 trees/ha, Q5 is greater than 716 trees/ha, Q6-Q8 
0 trees/ha, Q6 is greater than 716 trees/ha, Q3-Q8 
0 trees/ha, Q8 is greater than 716 trees/ha, Q2-Q8 
0 trees/ha, Q2 is greater than 1074 trees/ha, Q5 
0 trees/ha, Q5 is greater than 1074 trees/ha, Q5-Q8 
0 trees/ha, Q6 is greater than 1074 trees/ha, Q2-Q8 
0 trees/ha, Q7 is greater than 1074 trees/ha, Q5, Q6, and Q8 
0 trees/ha, Q8 is greater than 1074 trees/ha, Q2-Q8 
716 trees/ha, Q1 is greater than 1074 trees/ha, Q2-Q8 
716 trees/ha, Q2 is greater than 1074 trees/ha, Q4-Q8 
 
 
 
 
 
 
 295
 
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