ABSTRACT
Title of Document: GREEN FA?ADE ENERGETICS
Jeffrey W. Price, Master of Science, 2010
Directed By: Associate Professor David R. Tilley, Department
of Environmental Science and Technology
Rising energy costs and a warming climate create the need for innovative, low-
carbon technologies that help cool buildings. We constructed four small buildings and
instrumented them to measure the cooling effect of a green fa?ade on their south and west
walls. The green fa?ade significantly reduced the temperature of the building?s ambient
air, exterior surface, and interior air, and the heat flux through the vegetated wall. Using
a mathematical model, we determined that the whole-building cooling load reduction (1.4
to 28.4%) depended on building construction, green fa?ade placement, and especially
whether the windows were covered. An emergy analysis of a south-facing green fa?ade
revealed that the total emergy consumed could be balanced by the electricity saved from
reduced air conditioning if the cooling load was reduced by at least 14%. With
thoughtful design and placement of a green fa?ade it can sustainably and effectively help
cool buildings.
GREEN FA?ADE ENERGETICS
By
Jeffrey W. Price
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 Science
2010
Advisory Committee:
Associate Professor David R. Tilley, Chair
Associate Professor Patrick C. Kangas
Principle Agent and Specialist in Fruit Joseph A. Fiola
? Copyright by
Jeffrey W. Price
2010
ii
Dedication
I would like to dedicate this thesis to my grandmother, Donna Cooper, who taught
me the value of hard work, to be curious about the world around me, and to always ask
questions.
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Acknowledgements
I am very grateful to all those who helped me with this project and thesis. First
and foremost, it would not have happened without the hard work and dedication of my
advisor, Dr. David Tilley. I would also like to thank my committee members Dr. Joseph
Fiola and Dr. Patrick Kangas for their helpful advice, edits, and guidance throughout the
project.
Thank you to my department, Environmental Science and Technology, for
supporting my work throughout my time at Maryland. Thanks to the gentlemen in the
ENST Project Development Center for their hard work and for making the project a
reality. I would like to thank Brandon Winfrey in particular for helping out on those
grueling Friday evenings and so much more. Also, thank you to the undergraduate
researchers, Wenjie Li and Audrey Varner and others for their data collection and
analysis and for an extra set of hands. Without the support at home and hard work from
my loving fianc?e, Melissa Burns, the project would have never happened.
Finally, I would like to thank Green Roofs for Healthy Cities and the Green Walls
Research Committee for funding the project and for providing guidance on the needs of
the industry.
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Table of Contents
Dedication ........................................................................................................................................ ii
Acknowledgements......................................................................................................................... iii
Table of Contents............................................................................................................................ iv
List of Tables .................................................................................................................................. vi
List of Figures ................................................................................................................................ vii
Chapter 1: Introduction .................................................................................................................... 1
Green Fa?ade Research ............................................................................................................... 2
Objectives .................................................................................................................................. 10
Plan of Study ............................................................................................................................. 10
Chapter 2: Cooling effects of a green fa?ade................................................................................. 12
Objectives .................................................................................................................................. 13
Methods ..................................................................................................................................... 13
Results and Discussion .............................................................................................................. 24
Interior Temperature ............................................................................................................. 25
Exterior Surface Temperature ............................................................................................... 25
Building Ambient Air Temperature ...................................................................................... 27
Heat Flux to Building Interior Air ........................................................................................ 31
Evapotranspiration ................................................................................................................ 31
Plant Growth ......................................................................................................................... 32
Conclusions ............................................................................................................................... 36
Chapter 3: Modeled cooling load reduction using a green fa?ade................................................. 38
Objectives .................................................................................................................................. 40
Methods ..................................................................................................................................... 40
Experimental Buildings......................................................................................................... 40
ASHRAE Cooling Load Modeling ....................................................................................... 43
Results and Discussion .............................................................................................................. 51
Experimental Buildings......................................................................................................... 51
Simulation of the Square Building........................................................................................ 55
Simulation of the Rectangular Building................................................................................ 57
Conclusions ............................................................................................................................... 59
Chapter 4: Emergy evaluation of a green fa?ade ........................................................................... 61
Objectives .................................................................................................................................. 63
Methods ..................................................................................................................................... 64
Results ....................................................................................................................................... 66
Discussion.................................................................................................................................. 68
Conclusions ............................................................................................................................... 72
Calculations ............................................................................................................................... 74
Footnotes to Table 7 Calculations ............................................................................................. 76
Chapter 5: Conclusions ................................................................................................................. 82
Future Work............................................................................................................................... 84
References...................................................................................................................................... 87
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List of Tables
Table 1 Because the instrumentation was fixed on one wall, each building was
rotated 90? to switch the vegetated wall from south to west and back. The
instrumented wall was built opposite the wall with the door.
Table 2 Summary of the peak cooling effects of the green fa?ade during the early
summer 2010 in Maryland, USA.
Table 3 Because the instrumentation was fixed on one wall, each building was
rotated 90? to switch the vegetated wall from south to west and back. The
instrumented wall was built opposite the wall with the door.
Table 4 Climatic characteristics for the days chosen for the study. July 4th was
slightly warmer and drier than June 12th. Temperature data were as
measured by our thermistors, solar data were calculated using solar
geometry.
Table 5 Convective and radiant percentages of total sensible heat gain (ASHRAE
2001).
Table 6 Summary of ASHRAE cooling load model simulations.
Table 7 Emergy required to manufacture, install, maintain, and decommission a 50
m2 green fa?ade during its expected 25-year lifetime. Benefits percentage
is shown for Total Emergy with services.
Table 8 Summary of emergy table.
Table 9 Stainless steel transformity calculation.
Table 10 Stainless steel lifetime corrosion calculation.
Table 11 Stainless steel recycling calculation.
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List of Figures
Figure 1 Vegetated experimental buildings with west-facing green facades mid-
summer 2010.
Figure 2 The green fa?ades growing in the UM Research Greenhouse in mid-March
2010. Supplemental lighting was provided during the early morning and
late evening to extend the day length to 16 hours to encourage faster
growth.
Figure 3 There were a total of sixteen green fa?ades. Three, one of each
commercial product, remained un-vegetated to serve as controls.
Figure 4 Cross-section diagram of the sensor layout. This profile of thermistors
was installed in three locations across the surface of the wall to calculate a
representative mean temperature for each of the measurements.
Figure 5 Approximate locations of each profile of thermistors as they were installed
in the experimental buildings. The black lines represent a drawing of the
wall framing including the studs, header, and footer.
Figure 6 Shadow projected by the green fa?ade. The area within the wood frame
was cropped and processed in Adobe Photoshop to estimate percent cover.
Figure 7 Green fa?ade rotation schedule. On June 18th, the buildings were rotated
90? clockwise such that for the second half of the experiment, the green
fa?ades and instrumented walls faced west.
Figure 8 Mean interior air and exterior surface temperatures for the control
buildings on hot, sunny days.
Figure 9 Reduction in building interior air temperature due to vegetation on the
south or west building wall during either (a) hot, sunny or (b) cool, cloudy
days.
Figure 10 Reduction in the experimental building?s exterior surface due to green
fa?ade vegetation during either (a) hot, sunny or (b) cool, cloudy days.
Figure 11 Reduction in ambient air temperature 10 cm from south and west walls
due to a green fa?ade for (a) hot, sunny and (b) for cool, cloudy days.
Figure 12 Reduction in heat flux into the building?s interior air due to green fa?ade
vegetation during either (a) hot, sunny or (b) cool, cloudy days.
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Figure 13 Observed solar irradiance and estimated evapotranspiration of the (a)
south-facing vegetation for hot, sunny days and of the (b) west-facing
vegetation for hot, sunny days.
Figure 14 Plant growth measurements of experimental green fa?ade vegetation. Leaf
area index (a) represented the number of leaf layers per unit area of wall
covered and percent cover (b) represented the amount of wall space
covered with vegetation. Data were presented as means of each green
fa?ade type.
Figure 15 a) Cross-sectional diagram of profile of thermistors located across the
instrumented wall from exterior (10 cm from vegetation surface) to the
interior wall surface. b) Diagonal pattern of sensor profile locations
evenly spaced across wall
Figure 16 Modeled building sketches of a) the experimental building, b) the square
building, and c) the rectangular building. Note: in (c) the north arrow
points in two directions, one depicting the Rectangle-EW orientation
simulation and the other the Rectangle-NS simulation.
Figure 17 Comparison of mean observed and modeled cooling load for south and
west-facing walls on the experimental buildings.
Figure 18 ASHRAE cooling load model output for the experimental building
without a green fa?ade in June.
Figure 19 Observed heat flux through a) the south wall for three days including June
12th and b) the west wall for three days including July 4th on experimental
buildings. Dotted lines denote buildings with green fa?ades; solid lines
denote buildings without a green fa?ade.
Figure 20 Sources for the cooling load of the square building. ?Other? included
outside air infiltration, occupants, and the floor.
Figure 21 Systems diagram for the green fa?ade.
Figure 22 A/C electricity saved due to a green fa?ade is not well known but has been
estimated to be up to 70%. Not considering human services yields more
than twice the benefit-cost ratio than if they are considered.
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Chapter 1: Introduction
Between 1980 and 2001, the number of U.S. households with central air
conditioning increased from 27 to 55 percent (?South Atlantic?? 2006). They consumed
183 billion kWh of electricity for air conditioning in 2001, comprising 16% of their total
electricity consumption (?South Atlantic?? 2006). With rising energy costs and a
warming climate, there is an increased need for innovative, low-carbon technologies that
help cool buildings. Research done in the U.S. has shown increases in summertime urban
air temperatures due to the urban heat island effect of between 0.5?C ? 3.0?C. Much of
this may be mitigated by the addition of living vegetation and high-albedo surfaces
(Akbari et al. 2001). British meteorologist Luke Howard first observed and documented
the urban heat island effect in The Climate of London (1818). In his original publication,
he outlined the three main differences between the city and countryside: the city has a
more complicated geometry of many vertical surfaces, buildings impede wind circulation,
and the city lacks a store of moisture available for evaporation and hence energy
dissipation (Howard 1818). Strategies to mitigate the urban heat island effect include
reducing energy consumption of buildings, cars, and other heat dissipating entities within
the city, changing the albedo of the urban surfaces, and incorporating vegetation into the
built environment.
Research on the incorporation of vegetation into the urban environment has
shown positive results not just in terms of urban heat island effect mitigation, but also in
reducing air pollution, improving quality of life, and mitigating stormwater runoff.
Researchers in Toronto (Currie and Bass 2008) used the Urban Forest Effects Model
(UFORE; developed by the US Forest Service) to estimate air pollution retention in an
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urban area under various vegetative scenarios. They found that trees are very effective at
removing airborne pollutants and that the installation of green roofs on all downtown
buildings would significantly enhance that removal. Experimentally, Thoennessen
(2002) in Germany found high rates of air pollution deposition and retention on Boston
ivy-vegetated green fa?ades, particularly in the first meter above street-level. Ulrich
(1984) found that patients with a window view of a natural scene versus a brick wall
healed faster, took fewer potent analgesics, and received fewer negative evaluative
comments in nurse?s notes. While researchers have found green roofs to reduce total
stormwater runoff by approximately 50% (Dunnett and Kingsbury 2008), a small-scale
experiment by Schumann (2007) as well as modeling work done by Roehr et al. (2008)
showed potential reductions in stormwater runoff from green fa?ade systems as well.
Growing vegetation on building walls has potential to positively affect the urban
environment, primarily because in most instances, there are four walls to every roof. A
green fa?ade is a trellis system for supporting climbing plants most commonly on
building walls or other man-made structures. In most instances, the plants are rooted in
the ground or in planter boxes at ground level.
Green Fa?ade Research
K?hler (2008) published an article that summarized the history of and current and
ongoing research efforts on green fa?ades in Germany. He stated that over 770 articles
had been published on green fa?ades. Most of the articles were published in the 1980s
and 1990s, when many green fa?ades were installed in Germany.
In North America, green walls are one of the fastest growing green building
technologies being installed today. Green Roofs for Healthy Cities, a non-profit industry
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association representing North America was founded as a direct result of a research
project entitled Greenbacks from green roofs by Peck et al. (1999). While the majority of
the paper outlined the history, benefits, and barriers to a flourishing green roof industry in
Canada, there was also discussion on green walls. There was little detail on the thermal
benefits of green walls in the paper. This, in part, stems from the uncertainty of research
data on the topic. The technology has a significantly longer modern history in Central
Europe and the vast majority of published papers are not available in English.
Peck et al. (1999) were able to find and cite one resource that is particularly
relevant. Gaudet (1985) published an article in Harrowsmith magazine entitled
?Sunspots: landscaping for energy efficiency.? It is from this source that Peck et al.
(1999) drew the following data; ??every degree (F) of summer heat requires an
additional 5-7% of cooling energy. Hence, a 10 F reduction in the outside air
temperature achieved through the judicious arrangement of shade trees (green roofs and
vertical gardens), can reduce energy consumption for air-conditioning by 50-70%.?
Dunnett and Kingbury (2008) cited the Peck et al. (1999) article numerous times in
their book about planting green roofs and living walls. This book has made its way into
mainstream media and has perhaps become the most popular source for information on
the technologies, certainly one of the few on green fa?ades. The authors in this case
again presented the data on potential energy saved by the technology (50-70%).
Unfortunately, these data come from books that are out-of-print so it is hard to know if
the numbers were actually found through peer-reviewed researched or research at all.
Because of these types of references, more thorough and citable research needs to be
made available to industry.
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Hoyano (1988) published an article in English that summarizes research that had
only been published in Japanese. The study consisted of measuring thermal parameters
through the west ivy-covered wall of a residential home near Tokyo.
He first measured the solar transmittance through green fa?ades covered in
Japanese ivy (assumed to be Parthenocissus tricuspidata) at numerous sites around
Tokyo and found the mean to be 2-7%. In other words, only 2-7% of the energy reaching
the top of the plant canopy was transmitted to the underside of the canopy and
subsequently reached the building exterior. He also found a strong inverse correlation
between canopy thickness and transmittance and also between leaf area index (LAI) and
transmittance. Plant canopy thickness ranged from 15-35 cm while LAI ranged from 2-
4.5. The ivy-covered wall at the home where the rest of the study was conducted was
considered to have an average plant canopy. Similar plant canopy growth was observed
on dilapidated tobacco barns in Southern Maryland (Schumann 2007).
Using measured temperatures of the interior and exterior wall surfaces, Hoyano
calculated heat flow on the interior and exterior surface of the wall. He found a
maximum of 232 W m-2 entering the bare wall and that the ivy covering reduced that by
75% down to around 58 Wm-2. He also found that the ivy reduced the heat flux from the
interior surface to the interior air to around zero and concluded that the ivy layer mostly
eliminated the influence of solar radiation on the indoor environment.
Finally, he calculated what he called the equivalent shading coefficient. It was
defined as the ratio of the incident solar radiation on the wall to the heat flux at the
exterior surface. The ratio ranged between 6-16% when the weather was clear. He also
states that a transmittance of 5% corresponded to an equivalent shading coefficient of
5
12% (Hoyano 1988). While this study was comprehensive, it dealt with only one
building and one green fa?ade in one part of the world. More intensive, experimental
research in North America is needed to compare and hopefully confirm his results.
The following year, Holm (1989) published an article summarizing his work on
green fa?ades in South Africa. In the first part of the study, he looked at thermal
properties of plant leaves. Using relatively simple calculations, he found that a single
plant layer should transmit 12.8%, while two leaf layers would transmit around 5% of the
incident solar energy. He also stated that the spectral and thermal properties of the five
species he tested were no different beyond a canopy thickness of 20cm. Leaf
transmittance and canopy characteristics are important in modeling heat transfer
reduction and will be looked at more thoroughly in the following chapters.
Holm?s main conclusion was that green fa?ades are most effective when placed on
the equator-facing wall of a low thermal mass building in a hot-arid climate. A passive
building of this type in this climate would experience 4 K lower maximum indoor air
temperatures during the day and 1 K higher minimum indoor air temperatures. One
factor omitted from all modeling in his research was the effect of transpiration.
Di and Wang (1999) published an article entitled Cooling effect of ivy on a wall. In
this study, they were able to show a 28% reduction in peak cooling load through the
west-facing wall of a large brick building. They also found that the leaf layer insulated
the building wall at night thereby increasing the nighttime temperature of that wall. And
finally, they found the cooling effect to be much greater in July and August versus June,
when the outdoor temperature was much higher. During June the green fa?ade may have
actually increased the building interior temperature. While this article was also quite
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comprehensive, there was still no experimental replication, and it took place in Beijing.
Stec, Van Paassen, and Maziarz published an article on green fa?ades entitled
Modelling the double skin fa?ade with plants in 2005. A double skin fa?ade is a glass
layer placed outside the building exterior to add insulation and create a ventilated cavity
that may contain shading devices to block solar insolation during the cooling season. The
researchers compared the effect of the blinds, the shading device typically used, to live
plants. They found the cavity air temperature to be lower in the cavity with plants than
with blinds. They also concluded that the building?s cooling load was reduced by nearly
20% and expected a similar reduction in energy consumption by the cooling system.
Laura Schumann (2007) published her thesis on ?Green Cloaks,? an innovative
green roof retrofit technology that utilized a lightweight frame with vines growing on it
suspended over the roof and walls of a building. She found that the green cloak reduced
the peak indoor air temperature of a small-scale un-cooled building in July by 11.3 ?C
saving an estimated 73% in cooling energy costs. Further, for every one point increase in
LAI the building?s indoor temperature was reduced by 1 ?C. Finally, she measured plant
canopy characteristics on dilapidated barns in Southern Maryland, USA and found a
mean LAI of 3.14 and canopy thickness of 70 cm.
Alexandri and Jones (2008) modeled the effect of green walls and roofs on the
urban canyon. Using rudimentary equations, they calculated cooling load reductions due
to both technologies and just green walls alone in cities across the globe. Their
reductions, however, were simply calculated from reduced urban canyon air temperatures
and cannot be directly compared to other papers on the topic. One interesting conclusion
they made was that adding vegetation to cool an urban area was more effective the hotter
7
and drier the climate was, though still effective in humid areas, which reinforced the
modeling work done by Holm (1989). Cooling load reduction of the buildings within the
canyon ranged from 35% to 68%.
In the article entitled Energy simulation of vertical greenery systems, Wong et al.
(2009) explore the thermal effects of green fa?ades on a hypothetical 10-story building in
Singapore. They completed a number of simulations looking at the effect of the greenery
on the interior mean radiant temperature (MRT), and then through the model, applied that
to cooling load energy reduction. Under scenario one, the building was made entirely of
opaque surfaces (i.e. no windows). After being entirely covered (i.e., roof + walls) in
vegetation they observed a 74% reduction in energy use for cooling. For scenario two the
building had windows on each level of the building while only the opaque surfaces were
covered with vegetation. Under this scenario, the effect was much less pronounced at
10% reduction in cooling load. Under the final MRT scenario, all building fa?ades had
windows and were subsequently covered with 50% vegetation for one simulation and
then 100% for the second. Here, the cooling load was reduced by 12% and 32%,
respectively. The major limitations to this study were that they modeled only one
building shape and did not incorporate any experimental data. Also, the modeling was
performed for a building in a tropical climate.
Two recent papers have come from an engineering lab in Greece. Both address the
cooling effect of climbing plants on both passive and climate-controlled buildings in the
northern Mediterranean. In the first paper (Eumorfopoulou and Kontoleon 2009), they
showed significant reductions in both exterior and interior building surface temperatures
when they added a layer of Boston Ivy to the east wall of a passive building. On many
8
days in July and August, they found the vegetation reduced exterior wall temperatures by
around 6-8 ?C and the interior wall surface temperature by about 1 ?C. They also
calculated daily mean heat flow into the building interior air. While the bare wall section
allowed on average between 4 and 13 W m-2 into the building interior air, the vegetated
wall averaged -1 to -11 W m-2. This means that the green fa?ade converted the east wall
in this experiment, on average, from a source of heat to a flow-path for heat dissipation.
Results from this study are similar to Hoyano (1988) where he found the vegetation to
eliminate the covered building wall as a heat source. Unfortunately, there was still no
experimental replication in the study and it took place in a Mediterranean climate.
A second paper by Kontoleon and Eumorfopoulou (2010) was quite similar and
probably came out of the same thesis. In this, they assembled a model to address the
above variables on a simple climate-controlled building. The major findings were that
the exterior surface temperature was reduced highest to lowest in the following order:
west > east > south > north. For their windowless cubical building, they found that
completely covering the west wall in vegetation reduced the cooling load by 20%, and for
the other walls: 18%, 8%, and 5% for the east, south, and north walls, respectively. This
study and the Wong et al. (2009) study were the only two I could find that discussed the
effect of green fa?ade vegetation on the cooling load of the whole building.
Unfortunately, neither study was performed in North America and neither investigated
residential buildings.
Wong et al. (2010) discussed an experimental approach to investigating the thermal
benefits of what they call ?vertical greenery systems.? In this experiment, they placed 8
different types of green walls each in front of their own concrete wall in a park in
9
Singapore. The predominant results they showed were surface temperature reductions of
the concrete wall behind each green wall. All but one of the green walls were living
walls, with small compartments of soil at elevation and plants rooted into the wall?s
medium. The vine-based green fa?ade cooled the concrete the least out of all 8 systems
showing at most a 4.35?C reduction while the best living wall system reduced the
concrete wall temperature by 11.58 ?C. These results only reinforce what had been
reported before, but although they are specific to that climate, the numbers match other
studies reasonably well (Hoyano 1988, Di and Wang 1999, Eumorfopoulou and
Kontoleon 2009).
Ip, Lam, and Miller (2010) performed an experiment to describe the Shading
performance of a deciduous climbing plant canopy. They grew Virginia creeper
(Parthenocissus quinquefolia) on small trellises in front of a building?s southwest
windows in South Britain and measured the incident and transmitted solar radiation
extensively. The main goal of the paper was to define what they call the ?Bioshading
Coefficient,? which was simply a ratio of the transmitted solar irradiance over the solar
irradiance above the canopy. They found that a leaf area index of 5 resulted in a
Bioshading Coefficient of 12%. Wong et al. (2010) used 10% transmittance in their
model but this was not nearly as low as others (Hoyano 1988, Holm 1989) have found,
especially for an LAI of 5.
Based on this comprehensive review of the literature on the thermal performance
of green fa?ades, no studies have been conducted in North America nor have any
simulated a North American climate. Given the prospects of incorporating green fa?ades
into North American buildings and the lack of geographically-focused research, there is a
10
strong need for research to be performed in the temperate climate of North America,
using adapted plants in typical installations to understand the thermal effects of a green
fa?ade.
In addition, only two studies (Wong et al. 2009, Kontoleon and Eumorfopoulou
2010) considered the effects of vegetation on the energy budget of the whole building. In
other studies (Hoyano 1988, Di and Wang 1999, Peck et al. 1999 (research summarized),
Eumorfopoulou and Kontoleon 2009) researchers simply determined the reduction in heat
flux through the wall covered with vegetation.
Objectives
1. Determine the cooling effect of a green fa?ade on the building?s ambient
environment, exterior wall surface, interior air, and heat flux to the interior air.
2. Build a cooling load model to translate the heat flux reduction of one building
wall due to a green fa?ade to the whole-building cooling load.
3. Determine the environmental benefits and embodied energy consumption required
to manufacture, install, maintain, and decommission a green fa?ade over its
lifetime.
Plan of Study
1. To determine the cooling effect of a green fa?ade, we constructed four small-scale
wood-framed buildings with multiple-species green fa?ades and measured
temperature and other environmental conditions extensively through the 2010
growing season.
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2. To determine the effect of a green fa?ade on the whole-building cooling load, we
used an ASHRAE cooling load model under several scenarios. First we simulated
our own experimental buildings using real data. Then we modeled whole-
building cooling load reduction under several scenarios on two hypothetical
residential buildings.
3. To determine the environmental benefits and embodied energy consumed in the
lifetime of a green fa?ade, we completed an emergy analysis of a green fa?ade on
a hypothetical residential home in College Park, MD, USA.
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Chapter 2: Cooling effects of a green fa?ade
Living vegetation that covers building walls reduces solar radiant heating during
the summer decreasing mechanical cooling demand, electricity consumption, and
greenhouse gas emissions (Peck et al. 1999). Other significant benefits to adding
vegetation include: slowing storm runoff (Tilley and Schumann 2008), creating urban
wildlife habitat (Lundholm 2006), lowering environmental noise (Kohler 2008),
improving air quality (Currie and Bass 2008), and mitigating the urban heat island effect
(Bass 2001). Green fa?ades predominantly affect the thermal environment of buildings
by shading them. In addition to this, they act as an insulating layer for the building wall
increasing its R-value by trapping a pocket of air between the vegetation and building
wall, as a radiant barrier attenuating radiant heat loss at night, and as a physical obstacle
impeding air flow across the building wall surface limiting convective heat exchange
with the ambient environment. Much of the solar energy absorbed by the plant and its
leaves can be lost through transpiration as latent energy. This solar energy dissipation
pathway is very important to maintaining a comfortable ambient environment and is often
missing or severely reduced in urban environments. The lack of this cooling mechanism
and the enormous solar heat storage of man-made building materials ubiquitous in urban
environments (such as concrete) are the primary causes of the urban heat island effect.
Several studies to date have documented the cooling effects of a green fa?ade. A
mature Boston Ivy canopy attached to the west-facing wall of a building near Tokyo
reduced the exterior wall surface temperature by 18 ?C and the daily heat flux into the
building?s interior to nearly zero, which eliminated the west wall as a heat source
(Hoyano 1988). A thick canopy of English Ivy attached to the west wall of a large brick
13
building in Beijing reduced the exterior surface temperature by 18 ?C and the peak heat
flux into the building?s interior by 28% (Di and Wang 1999). In a experiment,
Eumorfopoulou and Kontoleon (2009) determined that a thick layer of Boston Ivy cooled
the exterior surface of a multi-story building on average by 5.7 ?C and to a daily
maximum of 8.3 ?C. The un-vegetated wall allowed between 4 and 13 W m-2 of heat into
the building interior while the vegetated wall allowed between 1 and 11 W m-2 to leave
the building. Thus, adding a green fa?ade changed the east wall of the building from a
source of heat into a pathway for interior air heat dissipation to the exterior.
Objectives
The aims of this study were to experimentally measure the effect of a green fa?ade
on the 1) building interior air temperature, 2) building exterior surface temperature, 3)
building ambient air temperature, and 4) heat flux into the building interior air. We
constructed four small wooden buildings and placed green fa?ades with commercially
available trellises and a mix of plant species on two of them, the other two serving as
control buildings, to measure the cooling effects of adding vegetation to a building?s
exterior wall.
Methods
Experimental Building Construction
Four buildings of dimensions 2.5 meters (8ft) long by 2.5 meters (8ft) wide by 3.5
meters (11ft) high were constructed and placed on a concrete pad at the University of
Maryland Central Research and Education Center in Clarksville, MD (approx. 30km
north of Washington, D.C.) on July 8th, 2009. The buildings consisted of a 4-sided
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square-hip 4/12-pitch roof with three-tab charcoal asphalt shingles (GAF Materials
Corporation) and 5cm x 15cm (2x6 in.) wood rafters, a ceiling hung from 5cm x 10cm
(2x4 in.) joists, 5cm x 10cm (2x4 in.) wood framed walls, and a 5cm x 15cm (2x6 in.)
wood floor all at a 40cm (16 in.) center spacing. R-13 fiberglass insulation (CertainTeed
Corporation), 9cm (3-1/2 in.) thick, was installed on the ceiling, walls and floor. The
interior walls and ceiling were covered with 1.6 cm (5/8 in.) thick gypsum drywall. The
buildings were wrapped in a vapor barrier material (Dupont Tyvek HomeWrap) and then
sided with Georgia-Pacific T1-11 1.5cm (19/32 in.) thick pine wood siding. The
buildings were spray painted blue-grey slate (Glidden Premium Latex Exterior Paint-Flat)
in May 2010 for the growing season (Figure 1). The buildings had no windows and a
single door was installed on the wall opposite the vegetation. The buildings were neither
cooled nor heated during any part of the experiment. Thermal resistances (R-values) of
each building surface are summarized in Table 1.
Figure 1. Vegetated experimental buildings with west-facing green
fa?ades mid-summer 2010.
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Green Fa?ade Construction
Sixteen 1.25m wide by 2.5m tall (4 x 8 ft) green fa?ades were constructed for the
experiment. Twelve of the fa?ades were constructed with a wood frame made from 5cm
x 10cm (2x4 in.) boards and either a commercially available trellis system (Carl Stahl?
DecorCable Innovations, LLC or Jakob-USA) or a trellis made from 3/4-inch manila rope
designed and built in our lab. The other four green fa?ades were rigid panels
(greenscreen). Two of these green fa?ades covered an entire wall of the experimental
buildings. At all times, the non-vegetated control buildings had just the wood frame
component of the green fa?ade on their instrumented wall. We mounted the green
fa?ades to wood frames and potted them to reserve the flexibility of applying various
treatments and types of green fa?ades in the experiment. In real-world installations, the
wood frames are not present, so we accounted for their effects by placing them on the
non-vegetated control buildings as well.
The commercially available green fa?ades were covered with a mix of nine
climbing plant species adapted to the United States Mid-Atlantic region (Richter-110
Building Surface
Composite R-Value,
m2 K W-1 (ft2 ?F h Btu-1)
Walls without door 2.27 (12.9)
Wall with door 1.72 (9.77)
Roof 3.21 (18.2)
Floor 2.45 (13.9)
Table 1. Because the instrumentation was fixed on one
wall, each building was rotated 90? to switch the
vegetated wall from south to west and back. The
instrumented wall was built opposite the wall with the
door.
16
grapevine (Vitis berlandieri x V. rupestris); Paulson 1103 grapevine (Vitis berlandieri x
V. rupestris); Dogridge grapevine (Vitis champini); Crossvine (Bignonia capreolata);
Coral Honeysuckle (Lonicera sempervirens); Carolina Jessamine (Gelsemium
sempervirens); American Bittersweet (Celastrus scandens); American Wisteria (Wisteria
frutescens); and Purple Passionflower (Passiflora incarnata). These plants were placed
under their corresponding fa?ade in early January 2010 and grown in the UM Research
Greenhouse until they were moved to Clarksville in May 2010. One of each type of
commercially available green fa?ade served as a control and was not vegetated. Three
Riparia Gloire (Vitis riparia) plants were placed under each manila rope green fa?ade in
March 2010 and grown in the greenhouse until being placed outside in May (Figure 2).
The plants for the nine-species mix were potted in 6-liter (1.5-gallon) plastic pots
in a hand-mixed medium. The medium consisted of equal parts Leafgro compost
(Maryland Environmental Service, Millersville, MD), Fafard topsoil (Conrad Fafard,
Inc., Agawam, MA), and all-purpose sand. The Riparia Gloire plants for the manila rope
fa?ades were potted in the same medium but in 12-liter (3-gallon) plastic pots. See
Figure 3 for a diagram of the green fa?ade planting scheme. While in the greenhouse
during the winter and spring, all plants were irrigated as needed to maintain a moist
growing medium. Outside at Clarksville, during the experiment, the plants were irrigated
every eight hours for 30 minutes starting at each day at 4am. The irrigation system
consisted of a Vigoro Electronic AquaTimer (Melnor, Inc., Winchester, VA) and soaker
hose (Teknor Apex Company, Pawtucket, RI) sections suspended over the pots at the
base of each green fa?ade. Under these conditions, each plant received nearly 3 liters (95
17
ounces) of water per day. Excess irrigation water was allowed to drain from the bottom of
each pot.
Figure 2. The green fa?ades growing in the UM Research Greenhouse in mid-March
2010. Supplemental lighting was provided during the early morning and late evening to
effectively extend the day length to 16 hours and encourage faster growth.
Figure 3. There were a total of sixteen green fa?ades. Three, one of each commercial product,
remained un-vegetated to serve as controls.
18
Thermal Instrumentation and Data Collection
A single wall of each building was outfitted with instrumentation to gather
continuous measurement of temperatures, including those to calculate heat flux, and solar
irradiance. A CS300 silicon pyranometer (Campbell Scientific, Inc., Logan, UT, 300-
1000nm) measured solar irradiance on the instrumented wall. Interior temperature was
measured with three evenly spaced, thermistors (#44006, Omega Engineering, Inc.,
Stamford, CT) mounted vertically on a column located in the center of each building.
Each instrumented wall had three horizontal profiles of thermistors (Figure 4) arranged in
a diagonal pattern across the wall (Figure 5). Exterior surface temperature referred to
measurements from thermistors mounted directly to the exterior wall surfaces, which
were painted to match the building exterior color. Building ambient air temperature
sensors referred to measurements from shaded but open-air thermistors that were
mounted approximately 10 cm from the building surface, or in the case of the buildings
with a green fa?ade, 10 cm above the plant layer surface. A CR1000 data logger
(Campbell Scientific, Inc., Logan, UT) controlled the sensors and logged their data every
10 minutes during the experimental period. All sensors in each building were connected
to an AM16/32B multiplexer (Campbell Scientific, Inc., Logan, UT) and each
multiplexer was connected to the datalogger located in one of the experimental buildings.
A 12-Volt RV/Marine deep-cycle battery (Interstate Batteries, Dallas, TX) powered the
instrumentation and data-logging system.
Soil Moisture Measurements
Soil moisture data from a single Vitis riparia plant were logged every 10 minutes
19
Figure 4. Cross-section diagram of the sensor layout. This
profile of thermistors was installed in three locations across the
surface of the wall to calculate a representative mean
temperature for each of the measurements.
Figure 5. Approximate locations of each profile of
thermistors as they were installed in the experimental
buildings. The black lines represent a drawing of the wall
framing including the studs, header, and footer.
20
during the experimental period using a CS616 Water Content Reflectometer (Campbell
Scientific, Inc., Logan, UT) and were used to calculate evapotranspiration. We were
limited to a single pot due to financial constraints and chose to measure a Vitis riparia
plant because we assumed it would grow to represent a large portion of its green fa?ade.
Also, it remained in-place for the duration of the experiment giving us a constant
measurement and way to compare data through the season. The instrument output data as
percent water content. We multiplied the water content by the volume of the pot to get
the mass of water and calculated ET using the following equation:
?
ET = mw * Hw
A
where the mass of water, mw (kg), was multiplied by the enthalpy of vaporization of
water, Hw (kJ kg
-1), and divided by the area of the wall that the plant covered, A (m2).
We used the change in water mass over the previous hour as the input for the current data
point. The ET curves were interpolated to smooth over the irrigation events that occurred
at 4:00am, 12:00pm, and 8:00pm each day.
Plant Growth Measurements
Growth measurements were taken on the green fa?ades through the duration of
the experiment. Leaf area index was measured at six evenly spaced points on each wall
using a thin 12 mm (0.5 inch) PVC pipe. We counted the number of contacts the
vegetation had with the pipe after being inserted perpendicularly into the plant canopy at
each measurement point. The value recorded for each fa?ade was taken as the mean of
these six measurements. Percent plant cover was calculated digitally from a photograph
of the shadow projected by each wall. We tilted each fa?ade perpendicular to the sun to
project a shadow of the leaf cover onto the ground (Figure 6). This photograph was then
21
processed in Adobe Photoshop (Adobe Systems Inc., San Jose, CA) using the threshold
function, which converted the image to black and white, and a pixel count calculated
percent leaf cover.
Experiment Duration
The experiment took place from May 25th to July 12th, 2010. The instrumented
and vegetated wall faced south for the first half of the experiment and then the buildings
were rotated on June 18th such that the vegetation and instrumented wall faced west.
Every third day, a randomly chosen green fa?ade was placed on a randomly chosen
vegetated building. The other half of the instrumented building wall was covered by one
Figure 6. Shadow projected by the green fa?ade. The area within the wood frame was
cropped and processed in Adobe Photoshop to estimate percent cover.
22
manila green fa?ade for the duration of the experiment. Each green fa?ade type received
four rotations of 3-days each (Figure 7).
Data Analysis
The effect of the green fa?ade on the building?s interior air temperature, exterior
surface temperature, ambient air temperature, and heat gain on the interior air were all
analyzed on a 24-hour basis. The effect of the green fa?ade on these variables was based
on the mean difference between the control buildings and the vegetated buildings.
We categorized each day during the experimental period as sunny or cloudy and
as hot or cool, giving four possible classifications. The mean value of either the outdoor
temperature or solar radiation for the day served as the threshold for whether the day was
hot or cool and sunny or cloudy, respectively. We analyzed the effects of the green
Figure 7. Green fa?ade rotation schedule. On June 18th, the buildings were rotated 90? clockwise such
that for the second half of the experiment, the green fa?ades and instrumented walls faced west.
23
fa?ade only when the weather was classified as either hot, sunny or cool, cloudy.
Evapotranspiration data were analyzed only for hot, sunny days.
Interior air temperature difference was calculated as the mean of six interior
temperature sensors, three from each control building subtracted from the six from the
vegetated buildings. Likewise, the exterior surface temperature difference was calculated
as the mean of the six exterior wall surface sensors from the control buildings subtracted
from the six on the vegetated buildings. Heat flux to the interior air was calculated using
the mean of the interior air temperature and the interior wall surface temperature of the
instrumented wall using the following equation:
Where the heat flux (q) in W m-2 was equal to the sum of the convective and radiative
energy exchange between the interior wall surface (Ts) and interior air (Ti), both in
Kelvin. The convective heat transfer coefficient (h) was 8.29 W m-2 K (McQuiston and
Parker 1994). We assumed an interior wall surface emissivity (?) of 0.90 and sigma (?)
was the Stefan-Boltzmann constant approximately equal to 5.67x10-8 W m-2 K-4
(McQuiston and Parker 1994). Positive values indicated heat flux into the building.
We generated 95% confidence intervals for each curve using temperature
reductions from each 10 minute interval from each day. For example, if there were 10
hot, sunny days, the reduction was the mean of those ten days, and the confidence
interval was generated from the variation in the means from those same ten days.
!
q = h * (Ts " Ti) + #$ * (Ts4 " Ti4 )
24
Results and Discussion
Figure 8 shows the mean interior and exterior temperatures for hot, sunny days for
the control buildings. The south exterior wall reached a maximum temperature of 43 ?C
around noon DST on hot, sunny days. The west exterior wall reached a maximum
temperature of 56 ?C around 5:00pm DST on hot, sunny days. The control buildings?
interior temperatures were higher during the second part of the experiment when the
green buildings? vegetation faced west. The interior temperature reached a maximum of
35 ?C during the south-facing vegetation period and 38 ?C during the west-facing
vegetation period for hot, sunny days. The maximum interior temperature for the south-
facing period occurred around 7:00pm DST and about an hour later for the west-facing
period (Figure 8).
15
20
25
30
35
40
45
50
55
60
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
T
em
pe
rat
ur
e (
?C
)
Time of Day
Exterior, South
Exterior, West
Interior, South
Interior, West
Figure 8. Mean interior air and exterior surface temperatures for the control buildings
on hot, sunny days.
25
Interior Temperature
Figure 9 shows the 24-hr cooling effect that the green fa?ade had on interior
temperatures when the weather was either hot, sunny (Figure 9a) or cool, cloudy (Figure
9b) for south and west-facing walls. The south-facing green fa?ade reduced the interior
air temperature by at most an average of 1.04 ?C at 3:30pm DST on hot, sunny days
(Figure 9a). When they were on the west side, they cooled the interior air temperature by
1.75 ?C at 8:10pm DST for hot, sunny days (Figure 9a). Due to the high variability and
small sample size for west-facing, cool, cloudy days (n=3), the 95% CI included zero
(Figure 9b), indicating that the experiment could not conclusively ascertain a cooling
effect for west-facing green fa?ades on cool, cloudy days.
Due to financial constraints, the experimental buildings were not mechanically
cooled, nor were they designed and built to be passively cooled. Because of this, the
analysis of the green fa?ade?s effect on interior temperature is limited. The range of
indoor air temperatures experienced during the study far exceeded acceptable levels for
human comfort even in a passively cooled building (17 to 37 ?C (62 to 99 ?F) with south-
facing vegetation and 18 to 41 ?C (65 to 106 ?F) with west-facing vegetation).
Exterior Surface Temperature
On hot, sunny days, the green fa?ade on the south and west sides cooled their
respective exterior walls by a maximum of 6.42 and 11.30 ?C (Figure 10a), respectively.
The green fa?ade cooled the south wall from dawn to dusk and was nearly symmetrical
about 12:00pm DST. The west-facing green fa?ade cooled the exterior surface beginning
at dawn, continued into dusk, and was heavily skewed toward late afternoon (Figure 10a).
The west-facing green fa?ade was particularly effective after 1:00pm DST when it began
26
to receive direct irradiance.
During cool, cloudy days the south green fa?ades cooled their exterior walls by on
average as much as 2.38 ?C at 11:20am DST (Figure 10b). Vegetation on the west-facing
wall cooled by as much as 6.17 ?C at 4:30pm DST on cool, cloudy days but frequently
had a confidence interval below zero which indicated a non-significant reduction (Figure
10b). Similar to detecting an effect of the west green fa?ades on the interior temperature
described above, there were only three cool, cloudy days during the west wall
experimental period. A larger sample size would perhaps remedy the inability to detect
the cooling effect of west-facing vegetation on cool, cloudy days. Furthermore, some of
the variability may also come from the fact that the cutoff for what made a day cloudy
versus sunny and cool versus hot was made at the average value. This means that two
very similar days, one with slightly above average solar irradiance and air temperature
versus another with slightly below average solar irradiance and air temperature could
have been assigned opposite categories when in fact they were quite similar days.
The effect of the green fa?ade on exterior surface temperature is perhaps the most
straightforward to analyze. Adding vegetation can reduce the daily exterior surface
temperature range of a wall from 10 to 60 ?C to between 5 and 30 ?C (Peck et al. 1999).
This magnitude of reduction in temperature swing of the building surface can have
profound effect on the longevity of building materials and exterior waterproofing. The
other more immediate benefit of reducing the exterior surface temperature daily range is
the reduction of heat flux through the building wall due to less of a temperature gradient
between the interior and exterior surfaces. Unfortunately, the green fa?ades in this study
were relatively immature with a thin canopy that did not completely cover the
27
experimental building walls. Because of this, the experimental buildings only
experienced exterior surface temperature range reductions of from between 10 to 50 ?C
down to between 11 to 46 ?C when south-facing vegetation was added and from between
11 to 64 ?C down to between 12 to 53 ?C when west-facing vegetation was added.
Building Ambient Air Temperature
On hot, sunny days, the green fa?ade on the south and west sides cooled their
respective ambient air temperatures by as much as 1.12 ?C at 12:00pm DST and 2.97 ?C
at 7:50pm DST (Figure 11a), respectively. The south-facing green fa?ade was most
effective around 12:00pm DST but maintained a small but significant effect from mid-
morning through sunset. The west-facing green fa?ade was particularly effective after
1:00 DST, when it began to receive direct irradiance. While it is difficult to extrapolate
these data to specifically quantify any effects the green fa?ade vegetation have on the
urban heat island effect, it is clear that the air surrounding the living vegetation is cooler
than the air in front of the bare building surface.
During cool, cloudy days the variability in the data for both south and west green
fa?ades was very high and the confidence intervals frequently included zero, indicating
that a significant effect could not be detected. The west-facing green fa?ade, for several
brief periods during the evening, did however cool the building ambient air by around 0.5
?C (Figure 11b).
28
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
T
em
pe
rat
ur
e
R
ed
uc
ti
on
(
K
)
Time of Day
a) Hot, Sunny mean, South
95% CI, South
mean, West
95% CI, West
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
T
em
pe
rat
ur
e
R
ed
uc
ti
on
(
K
)
Time of Day
b) Cool, Cloudy mean, South
95% CI, South
mean, West
95% CI, West
Figure 9. Reduction in building interior air temperature due to vegetation on the south or
west building wall during either (a) hot, sunny or (b) cool, cloudy days.
29
-4
1
6
11
16
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
T
em
pe
rat
ur
e
R
ed
uc
ti
on
(
K
)
Time of Day
a) Hot, Sunny mean, South
95% CI, South
mean, West
95% CI, West
-4
1
6
11
16
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
T
em
pe
rat
ur
e
R
ed
uc
ti
on
(
K
)
Time of Day
b) Cool, Cloudy mean, South
95% CI, South
mean, West
95% CI, West
Figure 10. Reduction in the experimental building?s exterior surface due to green fa?ade
vegetation during either (a) hot, sunny or (b) cool, cloudy days.
30
-3
-2
-1
0
1
2
3
4
5
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
T
em
pe
rat
ur
e
R
ed
uc
ti
on
(
K
)
Time of Day
a) Hot, Sunny mean, South
95% CI, South
mean, West
95% CI, West
-3
-2
-1
0
1
2
3
4
5
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
T
em
pe
rat
ur
e
R
ed
uc
ti
on
(
K
)
Time of Day
b) Cool, Cloudy mean, South
95% CI, South
mean, West
95% CI, West
Figure 11. Reduction in ambient air temperature 10 cm from south and west walls due to a
green fa?ade for (a) hot, sunny and (b) for cool, cloudy days.
31
Heat Flux to Building Interior Air
Figure 11 shows heat flux reduction to the building interior due to south and west-
facing green fa?ades on hot, sunny days (Figure 12a) and cool, cloudy days (Figure 12b).
The south-facing green fa?ade reduced heat flux into the building on hot, sunny days by
as much as 3.57 W m-2 at 1:30pm DST from an original peak of 13.0 W m-2. The mean
heat flux reduction for hot, sunny days between 11:00am and 4:00pm DST was 33.7%.
On cool, cloudy days it reduced mean peak heat flux into the building by 2.11 W m-2 at
12:30pm DST.
The west-facing green fa?ade reduced the mean peak heat flux into the building
by 10.65 W m-2 at 5:40pm DST from an original peak of 23.6 W m-2 on hot, sunny days
(Figure 12a) but for cool, cloudy days, variability in the data did not allow us to draw any
conclusions (Figure 12b). On hot, sunny days, the mean heat flux between 2:30pm and
9:30pm was reduced by 47.5% through the west wall.
Evapotranspiration
Total daily ET from a single Vitis riparia plant and its potting mix on the south-
facing green fa?ade for hot, sunny days was estimated to be 47% of the total daily solar
irradiation on those days (Figure 13a). Solar radiation was symmetrical about noon while
ET was approximately symmetrical about 2:00pm and slightly skewed toward the
afternoon. Total daily ET from a single Vitis riparia plant and its potting mix on the
west-facing green fa?ade for hot, sunny days was estimated to be 40% of the total daily
solar irradiation on those days (Figure 13b). West-wall ET was approximately
symmetrical about 2:00pm and was nearly equal to solar irradiance until the wall began
receiving direct sunlight after 1:00pm. These values agree reasonably well with the value
32
reported by Di and Wang (1999), 32%, which was a daily average value from a west-
facing English Ivy canopy in Beijing, China in July.
A building wall can absorb almost all of incoming solar radiation, converting
most of that radiation into stored heat. A typical plant canopy will absorb 75% (Gates
1980) of incoming radiation but instead of storing it, will release it in several forms. One
dominant pathway to release that energy is through transpiration. Heat that the leaf
absorbs is temporarily stored in water contained within the leaf. The water turns to vapor
when its energy content reaches the heat of vaporization, at which point the water exits
the leaf through the stomates. In effect, solar energy was blocked from entering the
building by the leaf, and removed from the system as water vapor. Through this
mechanism, plants cool themselves, the building they are covering, and the urban airshed.
Adding water vapor to an urban environment that lacks vegetation and suffers from the
heat island effect may be an effective way to cool it (Bass 2001).
Plant Growth
Near the end of the experimental period (July 13th, 2010), after approximately six
months of growth, the leaf area index for all green fa?ades was the same, with a mean of
3.07 (p<0.05) (Figure 14a). In addition, the mean plant cover was 80% by July 15th
(Figure 14b) with no significant differences between green fa?ade types (p<0.05). This
rapid first-year growth demonstrated the potential of a new green fa?ade to quickly
establish and cool its building. This may be particularly advantageous in new
construction where newly planted shade trees may take many years to establish.
33
-5
0
5
10
15
20
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
H
eat
G
ai
n
R
ed
uc
ti
on
(
W
m
-2
)
Time of Day
a) Hot, Sunny mean, South
95% CI, South
mean, West
95% CI, West
-5
0
5
10
15
20
0:00 3:00 6:00 9:00 12:00 15:00 18:00 21:00 0:00
H
eat
G
ai
n
R
ed
uc
ti
on
(
W
m
-2
)
Time of Day
b) Cool, Cloudy mean, South
95% CI, South
mean, West
95% CI, West
Figure 12. Reduction in heat flux into the building?s interior air due to green
fa?ade vegetation during either (a) hot, sunny or (b) cool, cloudy days.
34
0
100
200
300
400
500
600
700
800
0:00 6:00 12:00 18:00 0:00
E
ne
rgy
F
lu
x (
W
m
-2
)
Time of Day
a) South
Mean Solar
Mean ET
0
100
200
300
400
500
600
700
800
0:00 6:00 12:00 18:00 0:00
E
ne
rgy
F
lu
x (
W
m
-2
)
Time of Day
b) West
Mean ET
Mean Solar
Figure 13. Observed solar irradiance and estimated evapotranspiration of the (a) south-facing
vegetation for hot, sunny days and of the (b) west-facing vegetation for hot, sunny days.
35
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
2-Jun 7-Jun 12-Jun 17-Jun 22-Jun 27-Jun 2-Jul 7-Jul 12-Jul
L
eaf
A
re
a
In
de
x
a)
greenscreen
Carl Stahl
Jakob
Manila
0
10
20
30
40
50
60
70
80
90
100
24-Feb 16-Mar 5-Apr 25-Apr 15-May 4-Jun 24-Jun 14-Jul
P
er
ce
nt
C
ov
er
(%)
b)
greenscreen
Carl Stahl
Jakob
Manila
Figure 14. Plant growth measurements of experimental green fa?ade vegetation.
Leaf area index (a) represented the number of leaf layers per unit area of wall
covered and percent cover (b) represented the amount of wall space covered with
vegetation. Data were presented as means of each green fa?ade type.
36
Conclusions
The green fa?ade significantly reduced the ambient air temperature, exterior
surface temperature, heat flux through the wall, and interior air temperature of the 8 ft x 8
ft wooden experimental buildings on hot, sunny days in May, June, and July in Maryland,
USA (Table 2).
South West
Ambient air, K 1 3
Exterior surface, K 6 11
Interior air, K 1 2
Heat flux, W m-2 4 11
Heat flux, % 34 48
On cool, cloudy days, which had lower average ambient air temperatures and solar
irradiance, the effects were less detectable due to high variability and a small sample size.
In every comparison, the peak reduction was greater for west-facing vegetation than for
the south. However, the study was conducted in late-May, June, and early-July, when the
sun was at or near its maximum altitude. Later in the summer, when the air temperature
is high but the solar altitude is lower, the effects of the green fa?ade could be different. A
longer experimental period is needed to answer this question.
Evapotranspiration accounted for 47% and 40% of the incoming solar energy on
hot, sunny days for south and west-facing vegetation, respectively. This confirmed that
evapotranspiration was a significant pathway for heat dissipation by the green facade.
Further research needs to address the trade-off between water use and evaporative
cooling, particularly in drier climates.
Table 2. Summary of the peak cooling effects
of the green fa?ade during the early summer
2010 in Maryland, USA.
37
Finally, after approximately six months, the green fa?ades had plant canopies with
a mean leaf area index of three (i.e., LAI = 3) and percent leaf cover of 80%. There were
no differences between commercial trellis products or species configurations. This rapid
first-year growth demonstrated the potential of a new green fa?ade to quickly establish
and cool its building.
Though the results presented in this chapter apply specifically to our small,
wooden experimental buildings in Maryland, they may be used to enhance our general
understanding of green fa?ade energetics. By green fa?ades decreasing ambient air
temperatures, as observed on our experimental buildings, they have the potential to
mitigate the urban heat island effect.
Growing vegetation on the south or west wall of a building may significantly
decrease the need for air conditioning during the cooling season. The green fa?ade
reduced both the interior air temperature of our experimental buildings and the heat flux
from the interior wall surface to the interior air. These effects are further explored in the
next chapter.
38
Chapter 3: Modeled cooling load reduction using a green fa?ade
The number of U.S. households with central air conditioning increased from 27 to
55 percent between 1980 and 2001 (?South Atlantic?? 2006). They consumed 183
billion kWh of electricity for air conditioning in 2001, which was 16% of their total
electricity consumption (?South Atlantic?? 2006). With rising energy costs and a
warming climate, the need for innovative, low-carbon technologies that help cool
buildings is rising. Research done in the U.S. has shown increases in summertime urban
air temperatures due to the urban heat island effect of between 0.5?C ? 3.0?C and that
much of this may be mitigated by the addition of living vegetation and high-albedo
surfaces (Akbari et al. 2001).
One effective technology for cooling the urban environment is to add vegetation
to building fa?ades and roofs. While a growing number of researchers have evaluated the
thermal benefits of green roofs (Palomo Del Barrio 1998, Wong et al. 2003, Kumar and
Kaushik 2005, Hien et al. 2007, Takebayashi and Mariyama 2007, Fang et al. 2008), less
has been written about green fa?ades and most of it is in German and about German
green fa?ades (K?hler 2008). One relevant study by Di and Wang (1999) measured the
cooling effect of a 10 cm thick ivy plant layer on a west-facing brick wall in Beijing. The
researchers measured the thermal properties of the fa?ade and compared those data to a
section of wall where they removed the vegetation. The ivy layer reduced the maximum
exterior wall temperature from approximately 52 ?C (126 ?F) to 36 ?C (97 ?F). They
found that the green fa?ade reduced the peak heat flux from the interior wall surface to
the indoor air by 28% on a clear summer day. Akira Hoyano (1988) measured the heat
39
flux through the vegetated west wall of a residence near Tokyo, Japan. The home had a
15 cm thick bare reinforced concrete wall that was completely covered with Japanese Ivy
(Parthenocissus tricuspidata). He found that the vegetation reduced the heat flux at the
indoor surface from a peak of approximately 58 W m-2, to a fluctuating value just below
zero. Therefore, he concluded that green fa?ade vegetation could effectively eliminate
the influence of solar radiation on the indoor thermal environment (Hoyano 1988).
While the researchers in both of these studies thoroughly quantified the effect of
adding vegetation to a building fa?ade on the heat flux to the interior environment,
neither investigated this effect on the energy budget of the whole building. Wong et al.
(2009) used a computer program to simulate the whole-building cooling load reduction
due to a number of different vegetation scenarios on a 10-story office building. Under
scenario one, the building was made entirely of opaque surfaces (i.e. no windows) and
after being entirely covered in vegetation saw a 74% reduction in energy use for cooling.
In scenario two they added windows to each level of the building and then covered the
opaque surfaces only with greenery. Under this scenario, the effect was much less
pronounced at just over a 10% reduction in cooling load. Under the final scenario, the
building fa?ades were entirely windows and subsequently covered with vegetation to
50% and 100%. Here, the cooling load was reduced by 12% and 32%, respectively.
Kontoleon and Eumorfopoulou (2010) simulated a small, cubic, windowless,
climate-controlled building to which they added vegetation and simulated the cooling
load reduction. They found that completely covering the west wall in vegetation reduced
the cooling load by 20%, and for the other walls: 18%, 8%, and 5% for the east, south,
and north walls, respectively. They also found a linear relationship for percent cover
40
such that 50% plant cover on the west wall resulted in a 10% reduction in cooling load.
There is a need for replicated experimental research that considers the effects of
green fa?ade vegetation on the whole-building cooling load. And furthermore,
acknowledging that every green fa?ade installation and its effects on cooling the building
is unique, Heating, Ventilation, and Air Conditioning (HVAC) Engineers need data on
how to best integrate green fa?ades into their design.
Objectives
The objectives of this study were to 1) determine the reduction in peak heat flux
through south and west walls covered with a green fa?ade on replicated, wood-framed,
experimental buildings, 2) estimate the reduction in whole-building cooling load of the
experimental buildings by incorporating experimental data into a peak cooling load
model, and 3) use the peak cooling load model to estimate the whole-building cooling
load reduction of two simulated, full-scale residential buildings with vegetation covering
either their south or west walls.
Methods
Experimental Buildings
Construction
Four buildings of dimensions 2.5 meters (8 ft) long by 2.5 meters (8 ft) wide by
3.5 meters (11 ft) high were constructed and placed on a concrete pad at the University of
Maryland Central Research and Education Center in Clarksville, MD (approx. 30 km
north of Washington, D.C.) on July 8th, 2009. Each of the buildings consisted of a 4-
sided square-hip 4/12-pitch roof with three-tab charcoal asphalt shingles (GAF Materials
41
Corporation, Wayne, NJ) and 5 cm x 15 cm (2x6 in.) wood rafters, a ceiling hung from 5
cm x 10 cm (2x4 in.) joists, 5 cm x 10 cm (2x4 in.) wood framed walls, and a 5 cm x 15
cm (2x6 in.) wood floor; all at a 40 cm (16 in.) center spacing. There were no windows
and one door, which was centered on the wall opposite the instrumentation wall
(described below). The floor joists rested upon three 10 cm x 10 cm (4 x 4 in.) treated
posts laid flat on the ground, which served as the building?s foundation. R-13 fiberglass
insulation (CertainTeed Corporation, Valley Forge, PA), 9 cm (3-1/2 in.) thick, was
installed on the ceiling, walls, and floor. The interior walls and ceiling were covered with
1.6 cm (5/8 in.) thick gypsum drywall (USG Corporation, Chicago, IL). The buildings
were wrapped with vapor barrier (Dupont Tyvek HomeWrap, Wilmington, DE) and then
covered with 1.5 cm (19/32 in.) thick pine T1-11 (Georgia-Pacific Building Products,
Atlanta, GA). The buildings were first spray painted white (Glidden Premium Flat Latex
Exterior, Akzo Nobel N.V., Amsterdam, Netherlands) in in July 2009 and then blue-grey
slate (Glidden Premium Flat Latex Exterior, Akzo Nobel N.V., Amsterdam, Netherlands)
in May 2010 before the second growing season began. This construction represented a
total heat gain coefficient (Ktot) of 12.9 W/K (24.4 Btu/hr ?F). Table 3 summarizes the
thermal resistances (R-values) of each building surface.
Building Surface
Composite R-Value,
m2K/W (ft2?F h/Btu)
Walls without door 2.27 (12.9)
Wall with door 1.72 (9.77)
Roof 3.21 (18.2)
Floor 2.45 (13.9)
Table 3. Because the instrumentation was fixed on
one wall, each building was rotated 90? to switch the
vegetated wall from south to west and back. The
instrumented wall was built opposite the wall with the
door.
42
Instrumentation
A single wall of each building was outfitted with instrumentation to gather
continuous measurement of temperatures, including those to calculate heat flux, and solar
irradiance. A CS300 silicon pyranometer (Campbell Scientific, Inc., Logan, UT, 300-
1000nm) measured solar irradiance on the instrumented wall. Each instrumented wall
had three horizontal profiles of thermistors (#44006, Omega Engineering, Inc., Stamford,
CT) (Figure 15a) arranged in a diagonal pattern across the wall (Figure 15b). Interior
temperature was measured with three evenly spaced thermistors mounted vertically on a
column located in the center of each building. A CR1000 data logger (Campbell
Scientific, Inc., Logan, UT) controlled the sensors and logged their data every 10 minutes
when the system was powered. All sensors in each building were connected to an
AM16/32B multiplexer (Campbell Scientific, Inc., Logan, UT) and each multiplexer was
Figure 15. a) Cross-sectional diagram of profile of thermistors located across the instrumented wall
from exterior (10 cm from vegetation surface) to the interior wall surface. b) Diagonal pattern of sensor
profile locations evenly spaced across wall
a) b)
43
connected to the datalogger, which was located in one of the experimental buildings. A
12-Volt RV/Marine deep-cycle battery (Interstate Batteries, Dallas, TX) powered the
instrumentation and data-logging system.
Experimental Data Analysis
Heat flux through the instrumented wall was calculated by the following equation:
Where heat flux (Q) in W m-2 was equal to the sum of the convective and radiative flux
from the interior wall surface to the interior air. Tw was the interior wall surface
temperature and Ti was interior air temperature, both were in units of Kelvin. The
convective heat transfer coefficient (hwi) was assumed to be 8.29 W m
-2 K-1 (1.46 Btu h-1
ft-2 ?F-1) based on a vertical surface in still air (McQuiston and Parker 1994, pg. 157).
Interior wall surface emissivity (?) was assumed to be 0.90 and sigma (?) was the
Stefan-Boltzmann constant, approximately equal to 5.673x10-8 W m-2 K-4 (McQuiston
and Parker 1994). Positive values indicated heat flux into the building.
Two days with similar climatic conditions were chosen to compare the effects of a
south and west green fa?ade on our experimental buildings. The climatic characteristics
of these days are summarized in Table 4.
ASHRAE Cooling Load Modeling
Calculation Methods
We used the ?radiant time series? method as described in Chapter 29 of the 2001
ASHRAE Fundamentals Handbook (ASHRAE 2001) to generate hourly peak cooling
loads for each opaque building surface. The method began by calculating the hourly
!
Q = hwi(Tw " Ti) + #$ (Tw4 " Ti4 )
44
solar loading, including direct and diffuse irradiance, on each building surface, which
was used to calculate a ?Sol-air? temperature of that building surface. The Sol-air
temperature was defined as:
??the temperature of the outdoor air that in the absence of all radiation changes gives
the same rate of heat entry into the surface as would the combination of incident solar
radiation, radiant energy exchange with the sky and other outdoor surroundings, and
convective heat exchange with the outdoor air? (ASHRAE 2001).
The next step was to calculate the heat input, which was the conduction through the wall
surface based on the temperature gradient between the Sol-air temperature and the indoor
June 12, 2010 July 4, 2010
Mean Temperature, ?C (?F) 27 (80) 26 (79)
Max Temperature, ?C (?F) 33 (92) 37 (98)
Min Temperature, ?C (?F) 19 (67) 15 (59)
Mean Humidity, % 70 51
Max Humidity, % 90 84
Min Humidity, % 49 18
Mean Insolation on horiz.
surface, W m-2
616 610
Max Insolation on horiz.
surface, W m-2
1000 998
Table 4. Climatic characteristics for the days chosen for the study. July
4th was slightly warmer and drier than June 12th. Temperature data were
as measured by our thermistors, solar data were calculated using solar
geometry.
45
air temperature. The conduction time series (CTS) method redistributed this heat input
temporally based on physical properties of the specific building materials, i.e. the
material stored heat and released it with a time delay. Next, the energy was divided into
radiant and convective components based on source of heat gain (Table 5). These values
did not vary based on differences in construction materials.
For opaque surfaces like walls, convective heat (Table 5) contributed to the
cooling load instantaneously, while radiant heat (Table 4) was transformed by a radiant
time series (RTS) distribution also based on wall construction characteristics. The
convective and transformed radiant heat gains were then added to derive the total cooling
load for each hour for the wall surface.
For transparent surfaces, like windows, transmission of solar radiation into the
building interior often accounts for a large proportion of the total cooling load. For these
surfaces, the previously calculated hourly direct solar load was multiplied by the window
area of the corresponding building fa?ade and then transformed by a representative solar
RTS where 100% of the gain was radiant. Prior to being processed by the RTS, the heat
gain was reduced by a solar heat gain coefficient (SHGC), which was defined as the
fraction of incident irradiance that entered through the glazing and became heat gain
(ASHRAE 2001). Also prior to multiplying by the RTS, any shading devices, both
Heat Gain Source Radiant heat, % Convective heat, %
Transmitted Solar 100 0
Absorbed Solar (by fenestration) 63 37
Conduction, exterior walls 63 37
Conduction, exterior roofs 84 16
Table 5. Convective and radiant percentages of total sensible heat gain (ASHRAE 2001).
46
exterior and interior, were accounted for accordingly. The next step was to multiply the
ground and sky diffuse solar irradiance by the window area and corresponding SHGC to
get the diffuse solar heat gain. After these values were added to the conductive heat gain,
which was equal to the window area multiplied by the inverse R-value of the window and
the temperature difference between the inside and outside air, they were split where 37%
of the gain is convective and 63% is radiant. The radiant heat gain was then transformed
by the corresponding RTS and finally added to the direct solar cooling load to get the
total window cooling load for that fa?ade.
Heat gain due to household appliances, occupancy by people, and air infiltration
can also be added. Household appliances were assumed to add 469 W (1600 Btu/hr). An
adult male occupant added 161 W (550 Btu/hr), an adult female added 132 W (450
Btu/hr), and each child was assigned a heat gain of 121 W (413 Btu/hr) (ASHRAE 2001).
Heat gain due to air infiltration was calculated for each hour using the temperature
difference between the indoor and outdoor air, a tabulated value for the air exchange rate
based on tightness of building construction, and the necessary unit conversion factors
(Bobenhausen 1994).
Annual Energy Savings Calculations
Use of the degree-day method for energy analysis remains simple and accurate
even today in an age of complex computer modeling (ASHRAE 2001). The degree-day
concept accurately describes the severity of a given climate. Cooling degree-days are
standard tabulated values generally available for major cities across the world. We used
the book value for Washington, D.C., which was 1430 ?F days (Bobenhausen 1994). A
cooling degree-day (CDD) is ?the difference between a particular base temperature and
47
the mean outdoor temperature, in degrees Fahrenheit, on that day? (Bobenhausen 1994).
The typically used base temperature is 65 ?F, which refers to the lowest outdoor
temperature at which mechanical cooling is required to maintain indoor comfort. When
estimating the quantity of electricity consumed by the air conditioning equipment during
the cooling season, the cooling degree-day value must be converted to cooling load-hours
(CLH) using the formula (Bobenhausen 1994):
where Tstd is the outside summer design temperature in ?F. Once the CLH is calculated,
the electricity consumption is calculated using the following formula (Bobenhausen
1994):
where the electricity consumption is in kilowatt hours, the CLH is in hours, the design
cooling load (qc) is in Btu hour
-1, and the Seasonal Energy Efficiency Ratio (SEER) is in
Btu hour-1 W-1. The SEER ratio is a measure of cooling efficiency per input Watt over
the entire cooling season. We used a SEER ratio of 10, which was appropriate for an
older average home (?Central Air Conditioners? 2010). The design cooling load (qc) was
the hourly peak cooling load that we estimated as explained above. As is common
practice, we used the outside summer design temperature for Washington D.C. at the
2.5% design condition (91 ?F), which meant our system was capable of cooling 97.5% of
summer hours (Bobenhausen 1994). This practice is used to avoid excessive over sizing
of equipment, which would lead to an overall decrease in system efficiency
!
CLH = CDD65 "24(Tstd # 65)
!
kWhc"yr =
CLH # qc
1000# SEER
48
(Bobenhausen 1994). Finally, cost savings were calculated for each hypothetical full-
scale building scenario. The cost of electricity used in the calculations was $0.1502 kWh-
1, the average retail price for the residential market in Maryland as of July 2010
(?Average retail price?? 2010).
Modeling the Green Fa?ade
The green fa?ade vegetation serves primarily as an external shading device for the
building wall. External shading devices are accounted for in ASHRAE modeling by
tracking the shadow throughout the day and reducing the direct irradiance on any surface
behind it to zero. However, the solar irradiance penetrating a vegetative canopy will
never be zero and may vary considerably. One study in Britain found a shading
coefficient (i.e., ratio of solar irradiance below a canopy to above it, SC) of 12% through
a thick canopy of Virginia creeper with a leaf area index (LAI) of 5 (Ip et al. 2010).
Hoyano (1988) measured the solar transmittance (SC) under a large number of green
fa?ades in Tokyo and found it to range from 2-7%. Schumann (2007) found the
transmittance through a thick canopy (LAI 3.17) of Virginia creeper using a
hyperspectral radiometer to be 9.3% (Schumann 2007). For the purposes of this study,
we used 12% in our modeling and considered the effect of using 2%. To model the
reduction in solar irradiance by the green fa?ade, we reduced both the direct and diffuse
solar irradiances before the Sol-air calculation for the affected surface. This is not the
same as the traditional definition of the shading coefficient. ASHRAE (2001, pg. 30.38)
defines the shading coefficient as ?the ratio of the solar heat gain coefficient of a glazing
system at a particular angle of incidence and incident solar spectrum to that for standard
reference glazing at the same angle of incidence and spectral distribution.? Because our
49
model was in spreadsheet form and we had access to each component, we were able to
account explicitly for the transmitted irradiance.
Simulation of the Experimental Building
Simulation of the experimental buildings used the observed indoor and outdoor
temperatures from July 4th, 2010, and assumed Wall Number 6 (Wood siding, sheathing,
R-11 batt insulation, gyp board) for the wall CTS, and Roof Number 4 (Asphalt shingles,
wood sheathing, R-19 batt insulation, gyp board) for the roof CTS. The representative
non-solar RTS used was under the conditions of the interior zone, light construction, and
no carpet. The representative solar RTS used was under the conditions of light
construction, no carpet, and 10% glass (ASHRAE 2001, Chapter 29). All building
surfaces had an area of 4.83 m2 (52 ft2). The experimental building simulation contained
cooling loads for the roof, walls, floor, and infiltration. The geographic coordinates used
were 39? North, 77? West, which was the approximate location of Washington, D.C.,
USA. All simulations were performed using June solar geometry. See Figure 16a for a
sketch of the experimental building.
Simulation of the Full-Scale Buildings
The first simulation of a full-scale building was of a 2-story building that had a
square floor-plan 10.7 m (35 ft) on each side and a flat roof 6.1 m (20 ft) off the ground
for a total floor area of 228 m2 (2450 ft2) (Fig. 16b). The walls consisted of 5x15 cm
(2x6 in) wood studs filled with R-19 fiberglass insulation, and covered with wood siding
with gypsum on the interior walls. Each wall had 10% window area, and the door was
located on the north wall. The windows were double paned operable vinyl windows with
an R-value of 0.53 m2 K W-1 (3.0 ft2 ?F hr Btu-1). The total heat gain coefficient for the
50
building was 189 W/K (359 Btu/hr ?F). Observed data from July 4th were used for the
outdoor temperature, but the interior temperature was held constant at 23.9 ?C (75 ?F) to
simulate an air-conditioned interior. This simulation had four trials; two with vegetation
on the south wall and the other two with just the west wall covered. One simulation for
each orientation had the vegetation covering just the opaque wall surfaces, while a second
had both the wall and windows covered.
The second full-scale building simulation was for a rectangular building 10.7 m
(35 ft) wide by 6.1 m (20 ft) long by 9.1 m (30 ft) high for a total floor area of 195 m2
(2100 ft2) (Figure 16c). Construction was the same as in the first full-scale simulation
except windows were placed only on the two smaller walls. Interior temperature was
also held constant at 23.9 ?C (75 ?F) for this simulation. The simulation was performed
in two sets, once with the small surface area of the building facing west and once with it
facing south. Vegetation was placed on either the south or west wall for both building
orientations. In the two cases where the vegetation was placed on the wall with windows,
an extra simulation was done covering both walls and windows. These configurations
yielded a total of six scenarios for the rectangular building.
Figure 16. Modeled building sketches of a) the experimental building, b) the square building, and c) the
rectangular building. Note: in (c) the north arrow points in two directions, one depicts the Rectangle-EW
orientation simulation and the other the Rectangle-NS simulation.
51
Results and Discussion
Experimental Buildings
Validation that the ASHRAE cooling load model could reproduce the heat flux of
the experimental buildings when there was no green fa?ade was satisfactory, but not
perfect (Figure 17). The modeled cooling load for the south wall fit reasonably well,
especially from midnight to 2:00 pm. The largest error for the south wall occurred during
the afternoon and into the evening (Figure 17). However, the modeled cooling load for
the west wall was overestimated during the morning and early afternoon, and grossly
underestimated during the late afternoon and evening. One reason for the differences
may have been that the ASHRAE cooling load model was meant for climate-controlled
buildings, which the experimental buildings in this study were not. Since the inside
temperatures of the experimental buildings rose to 27.4 ?C (81.4 ?F) before 12:00 pm,
when the west wall started to receive direct irradiance, heat flux was likely directed from
the indoor air to the west-facing interior wall. This reversal of the temperature gradient
would not occur in a climate-controlled building.
The cooling load contributed by each building surface of the experimental
building without a green fa?ade is shown in Figure 18. The east-facing wall included the
door in this simulation and was responsible for nearly the entire building?s cooling load
from sunrise until mid-morning. Although the total daily cooling load for the east-facing
wall was the highest of any surface (120 W m-2), the hourly peak cooling load for the
entire building occurred at 3:00 pm when the other building surfaces each contributed to
an overall higher hourly peak (62.5 W m-2).
52
-10
-5
0
5
10
15
20
25
30
-1 4 9 14 19 24
C
oo
lin
g
loa
d (
W
m
-2
)
Time (Hour of the Day)
Modeled South
Modeled West
Observed South
Observed West
-40
-20
0
20
40
60
0 4 8 12 16 20
C
oo
lin
g Loa
d (
W
m
-2
)
Time of Day
Whole-bldg.
Roof
North
East
South
West
Floor
Infiltration
Figure 17. Comparison of mean observed and modeled cooling load for south and
west-facing walls on the experimental buildings.
Figure 18. ASHRAE cooling load model output for the experimental building
without a green fa?ade in June.
53
The green fa?ade reduced the peak heat flux of the south wall on June 12th by
48% at 3:00 pm DST (p<0.05) (Figure 19a) from an original value of 10.9 W m-2 (3.46
Btu hr-1 ft-2). When considering the impact of the south wall?s heat flux reduction on the
cooling load of the entire experimental building, the ASHRAE model estimated that the
peak hourly cooling load would be reduced by 3.4% at 4:00 pm DST from an original
value of 308 W (1052 Btu h-1). The impact of the south wall reduction was diluted
because it was only 17.6% of the total peak cooling load for the whole building.
In order for the ASHRAE model to estimate a similar whole-building peak
cooling load, the shading coefficient needed to be set equal to 0.45. This was the SC that
yielded a peak cooling load reduction most similar to the experimental measurements.
The SC was high because the plant canopy was immature; the mean LAI of the south
wall vegetation was 3.4 and the cover was only 55%. With a plant cover of 55%, almost
half of the building wall was receiving direct irradiance. Within the first few years of
installation, properly designed and maintained green fa?ades should grow a thick, full
canopy that entirely covers their wall. Under these conditions, one can expect a shading
coefficient in the range of 2 to 12% (Hoyano 1988, Schumann 2007, Ip et al. 2010).
The green fa?ade reduced the peak cooling load of the west wall on July 4th by
52% at 5pm DST (p<0.05) (Figure 19b) from an original value of 27 W m-2 (8.57 Btu hr-1
ft-2). When considering the impact of the west wall?s heat flux reduction on the cooling
load of the experimental building in the ASHRAE model, the peak hourly cooling load
was reduced by 4.8% for the entire building at 2:00pm DST from an original value of 308
W (1052 Btu h-1). A shading coefficient of 0.49 achieved a similar cooling load
reduction in this case. On July 4th, the mean LAI of the west wall vegetation was 2.7 and
54
Figure 19. Observed heat flux through a) the south wall for three days including
June 12th and b) the west wall for three days including July 4th on experimental
buildings. Dotted lines denote buildings with green fa?ades; solid lines denote
buildings without a green fa?ade.
a)
b)
55
the cover was about 67%. The green fa?ade canopy at that time was slightly thinner but
covered the wall more. Although the west wall vegetation reduced the cooling load by
approximately the same percentage as the south wall, the amount of reduction was nearly
double that of the south. Because of this, placing the green fa?ade on the west wall was
more effective in reducing the peak cooling load of the experimental buildings in June.
The whole-building cooling load results (3.4 and 4.8% for south and west,
respectively) were considerably less than the 7.6% and 20.08% reduction for the south
and west-facing building walls found in the Kontoleon and Eumorfopoulou (2010) study,
in which they modeled a geometrically-similar, windowless building. However, when we
increased our SC to 12%, an SC closer to what they were probably using, on the
experimental buildings in the cooling load model, the cooling load reductions increased
to 10.2 and 17.3% with the addition of south and west-facing vegetation, respectively.
These results agreed reasonably well with the previous study (Kontoleon and
Eumorfopoulou 2010).
Simulation of the Square Building
The peak cooling load for the square building was 10,975 W (37,449 Btu hr-1) for
a total annual A/C energy cost of $742 (Table 6). Covering the south wall with
vegetation reduced the peak cooling load by 1.4% at 6:00 pm DST with a SC of 12%
resulting in $10 saved in annual A/C energy costs. When the west wall of the square
building was covered with vegetation instead of the south, the peak cooling load was
reduced by 2.8% and $20 was saved. Finally, when the green fa?ade installation included
covering the windows as well as the opaque wall surfaces, the hourly peak cooling loads
56
were decreased by 7.8% and 26.4% for the south and west walls, resulting in $58 and
$196 in annual A/C costs saved, respectively (Table 6).
Peak cooling load of opaque walls in the square building accounted for only 11%
of the total load, while 56% was from the windows (Figure 20). With this type of load
distribution it was clear that shading the windows had a much larger effect on the whole
building?s peak cooling load.
The square building simulated in our study (10.7 m wide x 10.7 m long x 6.1 m
tall, 10% window area) was somewhat similar to one simulated in the Wong et al. (2009)
study though they covered all four of the walls with vegetation. In the Wong et al. (2009)
scenario 2B, they found that adding vegetation to all the opaque surfaces reduced the
whole-building cooling load by 10.35%.
Roof
13%
Walls
11%
Windows
56%
Other
20%
Figure 20. Sources for the cooling load of the square building.
?Other? included outside air infiltration, occupants, and the
floor.
57
Simulation of the Rectangular Building
The hourly peak cooling load for the rectangular building when its long axis was
oriented east-west was 8330 W (28,423 Btu hr-1) for a total annual A/C energy cost of
$564 (Table 6). Covering the south wall with vegetation reduced the peak cooling load
by 2.4% at 6:00 pm DST with a SC of 12% resulting in $14 saved in annual A/C energy
costs. When the west wall of the same building was covered with vegetation instead of
the south, the hourly peak cooling load was reduced by 3.4% and saved $19. Finally,
when the green fa?ade installation included covering the windows as well as the opaque
wall surfaces, the hourly peak cooling load was decreased by 28.4% for the west resulting
in $160 in annual A/C costs saved (Table 6). There were no windows on the south wall
in this scenario.
The hourly peak cooling load for the rectangular building, when its long axis was
oriented north-south, was 6866 W (23,430 Btu hr-1) for a total annual A/C energy cost of
$464 (Table 6). Covering the south wall with vegetation reduced the peak cooling load
by 1.5% at 6:00 pm DST with a SC of 12% resulting in $7 saved in annual A/C energy
costs. When the west wall of the same building was covered with vegetation instead of
the south, the hourly peak cooling load was reduced by 7.9% and saved $37. Finally,
when the green fa?ade installation included covering the windows as well as the opaque
wall surface, the hourly peak cooling load was decreased 8.9% for the south resulting in
$41 in annual A/C costs saved (Table 6). There were no windows on the west wall in this
scenario so no simulation was conducted.
For the north-south oriented rectangular house, opaque walls accounted for 28%
of the peak cooling load while windows accounted for 27%. This scenario was
58
somewhat unique in that it had no east or west-facing windows, which meant the window
cooling load was low. Because of this, covering the opaque west wall surface had a
significant effect and in fact, the largest effect of all scenarios where windows were not
covered (7.9% whole-building cooling load reduction, Table 6).
Decreasing the shading coefficient from 12%, which was used in the square and
rectangular building simulations, to 2%, improved the cooling load reduction for
Building type
(see Fig. 2)
Orientation
of
Vegetation
Original
peak
cooling
load,
W (Btu
hr-1)
Whole
building
cooling
load
reduction,
(%)
Annual
A/C energy
consumed,
($USD)
Annual
A/C energy
saved,
($USD)
Windows
covered?
Experimental South 3.4 N/A N/A N/A
West
308
(1,052)
4.8 N/A N/A N/A
Square South 1.4 $10 No
West 2.8 $20 No
South 7.8 $58 Yes
West
10,975
(37,449)
26.4
$742
$196 Yes
Rectangle-
EW
South 2.4 $14 No
West 3.4 $19 No
West
8,330
(28,423)
28.4
$564
$160 Yes
Rectangle-NS South 1.5 $7 No
West 7.9 $37 No
South
6,866
(23,430)
8.9
$464
$41 Yes
Table 6. Summary of ASHRAE cooling load model simulations.
59
example, in the square building simulation with south-facing vegetation, to 1.5% from
1.4%. Similar reductions were found in each scenario and because of this minor
difference and to simplify presentation of the results, we reported data from the model
using only the 12% SC.
Conclusions
The green facade reduced the peak heat flux through the south and west facing
walls on the experimental buildings by 48% and 52%, respectively on two hot and sunny
days in June and July in Maryland, USA. The ASHRAE (2001) cooling load model
showed that this large reduction in heat flux through one building wall amounted to a
small fraction of the total building cooling load (3.4% and 4.8% for south and west walls,
respectively) because the wall was only one of five solar-exposed heating surfaces. The
un-vegetated north and east walls and the roof continued to receive significant amounts
of solar energy.
Peak cooling load models of two simulated wood-framed residential buildings in
Maryland were then generated in an effort to apply our experimental data to full-scale
buildings that had windows and were climate-controlled. We showed using the model
that the green fa?ade was significantly more effective when it shaded the building?s
windows?particularly those facing west (1.4%-7.9% for opaque walls versus a 7.8 ?
28.4% reduction for walls with windows covered).
Modeling scenarios were restricted to June for simplicity and because this time
period corresponded to the experimental period. Future modeling should assess the
effects of green fa?ade vegetation during other months of the year, in particular, in
August and September when outdoor air temperatures are still high but the solar
60
geometry is different. In late summer, when the solar altitude is lower and the south wall
receives more solar irradiance than the west wall, south-facing vegetation may reduce the
building?s peak cooling load more than the west. Further, even though solar loading may
be at its maximum in June, many buildings? cooling loads peak in late summer when the
lower solar angle allows more sunlight to enter through windows.
There are many factors to consider that can affect cooling load reduction by a
green fa?ade including but certainly not limited to: building and vegetation orientation,
building construction, window placement and total area, climate, presence and condition
of surrounding tree canopy, green fa?ade plant canopy development, and plant species.
We acknowledge the vast amount of variability in the effect each individual installation
may have on cooling load and have presented here a few examples to demonstrate one
way of how users can account for the effect of the green fa?ade in their own specific
model in order to properly design their HVAC equipment accordingly. The results of this
research should be used as guidelines for what to consider when installing a green fa?ade.
It is our hope that the methods discussed here for how to integrate the effect of a green
fa?ade into a cooling load model will be used in future models for real-world
installations.
61
Chapter 4: Emergy evaluation of a green fa?ade
(At the time of thesis submission, this manuscript was In Review for
Emergy Synthesis 6, the conference proceedings for the 6th Biennial
Emergy Systems meeting.)
Abstract
Increased environmental awareness and demand for green space in urban areas
are driving the need to find ecological solutions to environmental problems. Green
fa?ades are a promising eco-technology that can help moderate temperature, create
habitat, attenuate noise pollution, and mitigate stormwater runoff in urban areas. A green
fa?ade is a type of green wall system in which climbing plants or cascading groundcovers
are trained to cover specially designed supporting structures (i.e. a trellis). The aim of
this study was to evaluate the emergy invested in a 50 m2 green fa?ade. The model
system consisted of a stainless steel trellis mounted to the south fa?ade of an existing
building with its plants rooted in the ground. The solar emergy required to manufacture,
install, maintain, and decommission the green fa?ade was 9.8 E12 sej/m2/yr, with nearly
55% embodied in human services, 14% in non-renewable materials, and 31% in
renewable materials. Depending on how much A/C electricity could be saved, the benefit
of the green fa?ade ranged from 0 to 5 times the total solar emergy cost. If 10% of A/C
electricity was saved, the green fa?ade had an emergy return on emergy invested for its
non-renewable materials of five. However, inclusion of the emergy invested as human
services in this ratio reduced it to 1.0, indicating that the ecological benefit was highly
sensitive to the financial cost of the fa?ade. These results suggested that the emergy
62
benefit of a green fa?ade was highly sensitive to its effect on building cooling load and
total lifetime costs.
Introduction
Man-made structures that dominate the urban environment can increase urban
afternoon ambient air temperatures by as much as 8?C (Peck et al. 1999), a phenomenon
known as the urban heat island effect. Urban heat island effect mitigation strategies
strive to create a more natural environment by increasing transpiration, decreasing heat
storage and altering surface albedo. Incorporation of vegetation is a simple way to
achieve this. Much of the research done in the US has shown that significant increases in
urban temperatures over the last 100 years are caused by the absence of urban vegetation
and abundance of low-albedo urban surfaces (Akbari et al. 2001).
While planting trees is probably the most common way to introduce vegetation
into urban areas, planting climbing plants can significantly add to the potential area of
green space in our cities. Green fa?ades have long inhabited our urban areas, dating back
to the Hanging Gardens of Babylon and the middle ages of Europe, lining Mediterranean
villas and castle walls and gardens. Green fa?ades gained their modern momentum in
Central Europe in the 1980s and 1990s when Berlin offered incentives to install them.
The vast majority of those systems used the self-clinging climber Boston Ivy
(Parthenocissus tricuspidata) (K?hler 2008). However, due to the desire for better
growth control and protection of newly constructed buildings, the installation of trellises
and use of non-clinging climbers accounts for the majority of installations today (Dunnett
and Kingsbury 2008).
63
While the exact energy saved by a green fa?ade is not well known, up to 70% was
found in the literature. Peck et al. (1999) suggested that a 10?F reduction in air
temperature outside a building achieved by well-placed shade trees can reduce A/C
energy consumption by 50-70%. A study in Britain showed a 25% reduction in annual
energy costs through deciduous shade trees and wind chill reduction (Peck et al. 1999).
And finally, as a point of comparison, a study in Canada found a 25% reduction in
summer cooling needs with an extensive green roof (Dunnett and Kingsbury 2008, pg.
73). This wide range of estimates and comparisons of the green fa?ade to shade trees and
green roofs reflects the lack of research data on the technology. Preliminary modeling
results from our work suggest that the green fa?ade may only reduce the peak cooling
load by 10-15% when the south or west wall including the windows are covered (Price
and Tilley, unpublished data). Actual reductions will vary considerably due to
geographic location, proportion of fa?ade covering, window placement, existing building
construction and use, and many other factors.
Objectives
Our objectives were to: (1) determine the amount of renewable and non-
renewable emergy required to manufacture, install, maintain, and decommission a green
fa?ade in a temperate climate; (2) estimate the amount of embodied energy saved by a
green fa?ade due to lowered air conditioning (A/C) electricity consumption; (3) estimate
the embodied energy value of the ecological production of the green fa?ade; and (4)
estimate the emergy benefit-cost ratio of the green fa?ade.
64
Methods
System Description
The green fa?ade evaluated in this study completely covered the 50 m2 (10m long
x 5m high) south wall of a two-story residential building. The fa?ade was assumed to
have a 25-year lifetime, which represents the industry average. The trellis consisted of 4
mm diameter stainless steel cable (grade 316) bolted to the building wall on 15 cm long
stainless steel spacer bars. The cables were mounted in a grid pattern with 40 cm vertical
spacing and 30cm horizontal spacing, as recommended by Dunnett and Kingsbury (2008,
pg. 206). The vines were planted in the ground and irrigated with tap water as needed to
make up for rainfall deficiency, fertilized, and sprayed with fungicide during plant
establishment for the first three years. The area used in the rainfall and tap water
calculations was the planting bed dimension, 10 m long by 1 m wide. This was the area
assumed to contain the majority of the root structure. It was assumed that a contractor
installed the system and the homeowner provided the maintenance labor.
Inventory of emergy inputs
An emergy evaluation was completed that accounted for all components needed
to manufacture, install, maintain, and decommission the green fa?ade. Renewable inputs
evaluated were sun, rainfall, transpiration, and recycled stainless steel. Non-renewable
inputs were plants, tap water, fertilizers, fungicide, stainless steel, product services, and
human labor. Product services was the total cost of the system without the cost of labor
and the stainless steel material. The remaining costs were assumed to account for the
emergy of designing and manufacturing the system. Benefits consisted of A/C electricity
65
saved due to reduced heat gain on the interior air and the amount of ecological
production. All calculations were made using the 15.83 E09 sej/y global baseline.
Grade 316 stainless steel was used for the cable trellis, as is the case for
installations where corrosion due to sea spray and/or urban air pollution may be an issue.
We derived a transformity for the stainless steel by incorporating the emergy of other
metals into an existing steel transformity. The alloy composition was simplified to the
following metals: 67% Iron, 17% Chromium, 12% Nickel, 2% Manganese, 2%
Molybdenum (AK Steel 2009). We assumed steel was made entirely of iron, which was
a simplification. We then set up a proportion equation relating the stainless steel metal
composition to the steel composition and the steel transformity to the transformity of
stainless steel (see Table 9).
Since stainless steel can be recycled, we used data given by Buranakarn (1998) to
estimate the proportion of its embodied energy that could be reused. This required
proportioning the emergy among the metals, which could be reused, and the electricity
and fuel, which could not be reused because they were dissipated during primary
manufacturing. It was assumed that the metal of a used trellis was 100% recyclable,
because very little of it was oxidized during its 25-year lifetime (Table 10).
Estimate of emergy of benefits
The main benefit of the green fa?ade considered in this analysis was the
electricity saved from reduced use of air conditioning (A/C). The emergy of ecological
production was assumed to be the same as transpiration, which was calculated using leaf
area from estimates by Dragoni et al. (2006). Transpiration is a good proxy for
ecological production because it is directly related to gas exchange.
66
Data Analysis
The total solar emergy required to manufacture, install, maintain, and
decommission the green fa?ade was the sum of all the renewable and non-renewable
inputs to the system. The total benefits of the system were the sum of the A/C electricity
saved and ecological production. The benefit-cost ratio was the total annualized benefit
divided by the total solar emergy consumed, amortized over the life of the system. We
chose to report the results in Table 7 with 10% A/C electricity saved. Benefit-cost ratios
were calculated over the entire range of expected percent A/C electricity saved both with
consideration for human services and when they were ignored. Human services in this
case encompass product services embodied in the cost of the green fa?ade and both
installation and maintenance labor.
Results
A green fa?ade requires that non-renewable resources be consumed in mining,
manufacturing, installation, and maintenance so the vegetation can control the
microclimate of the building envelope (Figure 21). The vegetation reflects unneeded
near-infrared solar radiation, and absorbs a large fraction of the ultraviolet, visible, and
near-infrared radiation into latent heat via transpiration. The vegetation accumulates
biomass to provide ancillary ecological benefits such as songbird habitat, but through
transpiration requires the consumption of water as a renewable resource for its operation.
By reducing the solar load on a building?s interior air, the green fa?ade reduces the need
for A/C use and thus lowers electricity consumption (Figure 21).
The total annual solar emergy required to manufacture, install, maintain, and
decommission the green fa?ade for the 25-year expected lifetime was 9772 E9 sej/m2/yr
67
(Table 7). Assuming that the stainless steel was recycled, 31% of the total emergy was
from renewable resources. Just over half (55%) of the total emergy was embodied in
human services (items #12, #13, and #14 in Table 7). Approximately 13% of the total
emergy was embodied in the stainless steel and not recyclable (#11 in Table 7).
Transpiration was the second largest renewable input after recycled stainless steel, but
only accounted for 1.2% of the total (item #3 in Table 7). All other inputs combined,
including plants, tap water, fertilizers, and fungicide accounted for less than 1% of the
total (items #4-10 in Table 7). With 10% of A/C electricity saved, the benefit was 6831
E9 sej/m2/y (item #15 in Table 7). The ecological production benefit accounted for 1.2%
Figure 21. Systems diagram for the green fa?ade.
68
of the total solar emergy (item #16 in Table 7). Ignoring all the solar emergy of human
services, the total solar emergy dissipated over the 25-yr life of the green fa?ade was
4357 E9 sej/m2/y (Table 7).
The benefits of the green fa?ade matched the emergy costs (9772 E9 sej/m2/y) at
14.4% A/C electricity saved. Over the range of A/C electricity savings we evaluated, the
emergy benefit-cost ratio was as great as 4.8:1 and as small as 0.012:1 (Figure 22). If the
human services are ignored, then the benefit-cost ratio could be as great as 10.8:1, or at
the conservative estimate of 10% of A/C electricity saved, it would be 1.57:1 (Figure 22).
Comparing non-renewable inputs to benefits, at 10% of A/C electricity saved the green
fa?ade nearly breaks even (0.99, Table 8). If human services are ignored, the ratio of
non-renewable inputs to benefits increases to 4.97 (Table 8).
Discussion
Other environmental benefits provided by the green fa?ade (i.e., in addition to
saving A/C electricity and ecological production) were not evaluated here because they
were considered outside the scope of this study. Therefore, the emergy benefits and
benefit-cost ratios calculated here should be considered minimum values. Other benefits
including: habitat creation, air and noise pollution attenuation, building envelope
weatherization, stormwater flow attenuation, psychological well-being, urban food
production, and winter insulation should be evaluated in future research.
We chose to assess this eco-technology based on its emergy benefit-cost ratio, to
determine how much A/C electricity a green fa?ade would need to save to recoup the
emergy dissipated for its manufacture, installation, maintenance, and decommissioning.
69
Number Item Unit
Value
(unit/yr/
m2)
Solar
Transform
ity
(sej/unit)
Solar
Emergy
(sej/m2/yr)
E09
%
Total
Renewable
1 Sun J 3.68E+09 1.00E+00d 4
2 Rain J 1.05E+06 3.06E+04d 32
3 Transpiration J 4.46E+06 2.59E+04d 116 1.2%
4
Stainless Steel (69%
recycled) g 6.27E+01 4.61E+10% 2890 29.6%
Renewable Subtotal 3005
Non-renewable
5 Plants J 3.08E+05 1.90E+04d 6 0.1%
6 Tap Water J 7.83E+04 3.14E+05f 25 0.3%
7 Potash g 1.12E+00 1.74E+09d 2 0.0%
8 Phosphorus g 1.58E-01 2.20E+10d 3 0.0%
9 Nitrogen g 2.14E-01 2.41E+10d 5 0.1%
10 Fungicide g 5.10E-01 2.49E+10a 13 0.1%
11 Stainless Steel g 2.82E+01 4.61E+10% 1298 13.3%
12 Product Services $ 4.00E+00 8.30E+11c 3324 34.0%
13 Maintenance Labor ind.*year2 9.13E-06 1.55E+17g 1415 14.5%
14 Installation Labor ind*year 2.92E-06 2.31E+17g 676 6.9%
Non-renewable (subtotal w/ services) 6766
Non-renewable (subtotal w/o services) 1352
Total Emergy (w/
services) 9772 100.0%
Total Emergy (w/o
services) 4357
15 A/C Electricity Saved# J 2.50E+07 2.69E+05d 6715 68.7%
16 Ecological Production based on transpiration 116 1.2%
Total Benefits 6831 69.9%
Table 7. Emergy required to manufacture, install, maintain, and decommission a 50 m2 green fa?ade
during its expected 25-year lifetime. Benefits percentage is shown for Total Emergy with services.
aBrown and Arding 1991; bBuranakarn 1998; cCohen et al. 2006; dOdum 1996; eTilley 2006; fBuenfil
2001; gCampbell and Lu 2009.
#Assumed 10% of A/C electricity saved.
%Calculated in this paper.
70
The emergy breakeven point for the recycled green fa?ade is at the low end of the
range with 14.4% of A/C electricity saved. If the A/C electricity saved were to reach the
high end of the range (70%), the green fa?ade benefits would outweigh the costs by
nearly five times (Figure 22). Ignoring human services, the emergy breakeven point
occurred when 6.3% of A/C electricity was saved by the green fa?ade.
0
2
4
6
8
10
0 10 20 30 40 50 60 70
Em
er
gy B
en
ef
it-
C
os
t
R
at
io
% A/C Electricity Saved
w/ services
w/o services
Item Solar Emergy (sej/m2/yr) E09
Renewable Used 3005
Non-renewable Used w/ Services 6766
Non-renewable Used w/o Services 1352
Services Used 5414
Benefit, A/C electricity saved 6715
A/C saved per non-renewable (w/ Services) 1.0
A/C saved per non-renewable (w/o Services) 5.0
Figure 22. A/C electricity saved due to a green fa?ade is not well known but has been estimated to
be up to 70%. Not considering human services yields more than twice the benefit-cost ratio than if
they are considered.
Table 8. Summary of emergy table.
1:1
71
This more than half reduction in the amount of A/C electricity saved necessary to
reach the emergy breakeven point demonstrated the magnitude of the human services
investigated in our study. Efforts to increase the sustainability of the green fa?ade should
be aimed at reducing costs and time spent maintaining it.
Rustagi et al. (2008) recently calculated a benefit-cost ratio of 0.116 for an
extensive green roof with 20% of electricity saved. Our green fa?ade benefit-cost ratio
(1.39 at 20% of A/C electricity saved) was twelve times higher than this. Such a low
benefit-cost ratio for the green roof reflected the high emergy materials that were used to
construct it?they found the highly engineered drainage and growing media to account
for over 90% of the total emergy consumption.
Climate is one of the primary factors affecting the amount of A/C electricity
saved by a green fa?ade due to factors such as solar geometry, cloudiness, and ambient
air temperature. For example, a home in the high latitudes with a south-facing green
fa?ade could experience increased energy bills. These locations may have very few or no
cooling days and the shading provided by the green fa?ade may reduce solar energy
inputs enough to require heat where it was not needed before. However, residents in the
low latitudes, like in the southern US, could conceivably save the estimated maximum of
70% of A/C electricity under optimal conditions. The greatest benefit would most likely
come from shading a very poorly insulated west wall that contains many windows and
represents a large portion of the total cooling load for the home.
The solar orientation of the green fa?ade will also have a large effect on the
amount of A/C electricity saved. The addition of vegetation to the west and/or east wall
or even the roof, as with the Green Cloak (Schumann and Tilley 2008), could further
72
decrease A/C electricity consumption. Green fa?ades may be particularly effective
against west wall heat gain where direct afternoon sun exposure is exacerbated by high
afternoon air temperatures.
A third factor that will affect A/C electricity saved by a green fa?ade is the
proportion of glazing to opaque surface a building has and how much the green fa?ade
shades that glazing. While there is a lack of experimental research on this factor, on-
going research suggests that 10% A/C electricity saved can be achieved, but only when a
significant portion of a building?s heat gain was due to glazing and that glazing is
subsequently shaded by the green fa?ade (Price and Tilley, unpublished data).
A new transformity was derived for stainless steel based on its elemental
concentrations of iron, chromium, nickel, manganese, and molybdenum. The
transformity increased over six times to 4.61E10 sej/g with the addition of these rare
metals (Table 9). Stainless steel compared to steel is extremely resistant to corrosion. In
fact, within its 25-year lifetime the trellis considered in this study only lost 0.0000516%
of its mass (Table 10). The mass lost was considered negligible and thus ignored in the
recycling calculation. It was also calculated that 69% of the total energy was embodied
in the stainless steel material itself and was able to be returned through material recycling
(Table 11).
Conclusions
The emergy analysis of a south-facing green fa?ade revealed that the total emergy
consumed could be balanced by the electricity saved from reduced air conditioning if the
cooling load was reduced by at least 14%. Thus, a green fa?ade can recover the emergy
consumed during its manufacturing, installation, maintenance, and decommissioning
73
simply from saving electricity. Other benefits, such as habitat creation, noise mitigation,
and reduction in the urban heat island effect were not part of the analysis, but would help
to further balance the emergy consumption. Future emergy analyses should consider
these benefits. In addition, the 14% cooling load reduction was specific to our green
fa?ade design and assumptions. For any specific application the breakeven point would
depend on many factors including building size and shape, green fa?ade size and
orientation, and plant canopy thickness and cover.
With 98% of the energy embodied in the human services and stainless steel trellis,
we encourage the use of alternative materials such as wood, natural fibers, or other low-
emergy materials where possible. However, it should be noted that these materials may
not last as long as stainless steel or other metals. Today?s green fa?ades can be made
more eco-friendly by maximizing the emergy in benefits. To do this, learn as much about
the building and site as much as possible. If unable to perform a cooling load calculation,
note visually the parts of the building that receive direct sunlight and concentrate on
shading those areas, particularly the windows.
74
Calculations
TABLE 9. STAINLESS STEEL TRANSFORMITY CALCULATION
Assumed Electric Arc Furnace (EAF) process able to make stainless steel similarly to
regular steel with different alloy composition. Set up proportion equation to scale up the
Steel, EAF process transformity with higher transformity metal elements. Alloy
composition was simplified to the following metals: 67% Iron, 17% Chromium, 12%
Nickel, 2% Manganese, 2% Molybdenum (AK Steel 2009).
Steel, EAF process transformity 4.19E09 sej/g from Buranakarn (1998, pg. 142)
4.19E09*1.68 = 7.04E09 sej/g corrected by a factor of 1.68 (Odum 2000)
Iron (Fe) transformity 1.20E10 sej/g from Cohen et al. (2006, pg. 16.6)
Chromium (Cr) transformity 1.50E11 sej/g ??
Nickel (Ni) transformity 2.0E11 sej/g ??
Manganese (Mn) transformity 3.50E11 sej/g ??
Molybdenum (Mb) transformity 7.0E11 sej/g ??
[ (Fe trans.)(Fe proportion) + (Cr trans.)(Cr prop.) + (Ni trans.)(Ni prop.) + (Mn
trans.)(Mn prop.) + (Mb trans.)(Mb prop.) ] * (steel trans.) / (iron trans.) = (stainless steel
transformity)
[ (1.20E10*0.67 + 1.50E11*0.17 + 2.0E11*0.12 + 3.50E11*0.02 + 7.0E11*0.02)
]*(7.04E09) / (1.20E10) = 4.61E10 sej/g
TABLE 10. STAINLESS STEEL LIFETIME CORROSION CALCULATION
Mass loss from the stainless steel trellis over its lifetime was explored. This value was
then used in the material recycling calculation (see Table 11). The average corrosion rate
75
for grade 316 stainless steel is 0.1 mg/m2/year (Herting et al. 2005). Surface area = 2 * ?
* r * L. Wetted area ratio (WA) for 7x7 (7 braided strands with each strand having 7
wires) stranded wire rope = 7:1 (Pisaturo 2009).
Exposed area of horizontal cables: (2)(?)(0.002 m)(10 m)(10 cables)(7 WA) =
8.796 m2
Exposed area of vertical cables: (2)(?)(0.002 m)(5 m)(30 cables)(7 WA) = 13.195
m2
Exposed area of posts: (2)(?)(0.015 m)(0.15 m)(40 posts) = 0.565 m2
Exposed area of clamps: (2)(?)(0.02 m)(0.02 m)(300 clamps) = 0.754 m2
Exposed area of bolts: (2)(?)(0.005 m)(0.1 m)(40 bolts) = 0.126 m2
Total exposed surface area = 8.796 + 13.195 + 0.565 + 0.754 + 0.126 = 23.44 m2
Lifetime corrosion = (23.44 m2)(0.1 mg/m2/year)(25 yr) / (1000 mg/g) = 0.0586 g
Percent mass loss = 0.0586 / 113636 = 5.16E-05 %
TABLE 11. STAINLESS STEEL RECYCLING CALCULATION
Calculated recyclable portion of stainless steel using the emergy evaluation of
Conventional Steel Product, EAF process for the entire U.S. from Buranakarn (1998, pg.
52). Assumed no material loss in trellis? 25-year lifetime (see Table 10).
Emergy
Item (sej) 1.0E20
Pig iron 1283.00
Natural gas 152.38
Other fuels 18.51
76
Electricity 319.45
Transport (Railroad) 3.80
Transport (Truck) 72.34
Labor 18.98
Annual Yield (Y) 1867.60
% Recyclable is proportion of Pig Iron to Total Emergy Yield =1283 E20 sej / 1868 E20
sej = 69%
Footnotes to Table 7 Calculations
The following calculations were made for a 50 m2 stainless steel cable trellis green fa?ade
in the US state of Maryland with an expected lifetime of 25 years. The final unit for all
calculations was per unit area per year.
1 Sun: Average annual solar radiation for ?South Facing Vertical Flat Plate? located
in Maryland, 3.50 kWhr/m2/day (Solar Radiation? 2009). Average plant canopy
absorption 80% (Campbell and Norman 1998).
Equation: (average insolation)(plant canopy absorption)
(3500 Whr/m2/day)(60 sec/min)(60 min/hr)(365 day)(80% absorption) = 3.68 E09
J
2 Rain: Average annual precipitation for Baltimore-Washington International
(BWI) Airport (1871-2008), 42 inches (Baltimore Average? 2009). Used 3.06
77
E04 sej/J for the transformity which was 18,199 sej/J corrected by a factor of 1.68
(Odum et al. 2000).
Equation: (rainfall)(affected area)(Gibbs free energy)/(fa?ade area)
(42 in)(0.0254 m/in)(10 m2)(4.94 J/g)(1000 g/L)(1000 L/m3)/(50m2) = 1.05 E06 J
3 Transpiration: Average total daily transpiration per unit leaf area 1.65 liters for
grapevines in New York state (Dragoni et al. 2006). Leaf area for green fa?ade
estimated to be 3 (Schumann and Tilley 2008). We used a six-month growing
season.
Equation: (LAI)(transpiration rate)(Gibbs free energy)(growing season length)
(3 leaf area)(1.65 L/day/m2 leaf area)(4.94 J/g)(182.5 day/yr)(1000 g/L) = 4.46
E06 J
4 Stainless Steel: 69% of value placed here as renewable due to recycling (see
Table 11). The remaining 31% was added to the Non-renewable inputs (see
footnote #11 in Table 7). Density of stainless steel 7.99 g/cm3 (AK Steel 2009).
Mass of stainless steel estimated by volume.
Equation: Volume cylinder = ? r2 h.
Volume of horiz. cables: (?)(0.002 m)2(10 m)(10 cables) = 0.0012566 m3
Volume of vertical cables: (?)(0.002 m)2(5 m)(30 cables) = 0.001885 m3
Volume of posts: (?)(0.015 m)2(0.15 m)(40 posts) = 0.004241 m3
Volume of clamps: (?)(0.02 m)2(0.02 m)(300 clamps) = 0.006524 m3
Volume of bolts: (?)(0.005 m)2(0.1 m)(40 bolts) = 0.000314 m3
78
Total mass = (0.01422 m3)(7990 kg/m3)(1000 g/kg) = 1.14 E05 g
(1.14 E05 g)/(25 yr)/(50m2)(69%) = 6.27 E01 g
5 Plants: Approximated emergy of plants using emergy in organic matter of potting
mix from Leonard and Rangarajan (2007). Planted one plant per foot of wall
length (Dunnett and Kingsbury 2008).
Equation: (mass organic matter)(energy in organic matter)
(1 plant/foot)(30 feet)(1 gal soil/plant)(3785 cm3/gal)(0.3 g/cm3)(0.5 g organic
matter /g mix)(5.4 kcal/g organic matter)(4186 J/kcal)/(25 yr)/(50 m2) = 3.08 E05
J
6 Tap Water: Tap water used for three years after planting to establish root system.
Estimated watering need, 1 inch/week during growing season.
Equation: (water depth)(Gibbs free energy)(ground area watered)/(25 yr)/(50 m2)
(1 in/week)(26 weeks)(0.0254 m/in)(4.94 J/g)(1000 g/L)(1000 L/m3)(10 m2)/(25
yr)/(50 m2) = 2.60 E04 J
7, 8, 9 Fertilizers: Spectrum Analytic (2009) recommends an average annual application
of 100lbs K/acre, 50lbs P/acre, and 75lbs N/acre for grapes. The fertilizer is only
needed for the first three years to establish complete fa?ade coverage. We used a
fa?ade area of 50 m2 instead of ground area to better estimate leaf area since the
green fa?ade is vertical. DAP = Di-ammonium phosphate fertilizer.
Equation: (application rate)(molar mass)(years applied)/(fa?ade lifetime)
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Potash: (1 acre / 4047 m2)(100 lbs K2O/acre/yr)(454 g/lb)(78 g/mol K/94 g/mol
K2O)(3 yr)/(25 yr) = 1.12 g K
Phosphorus: (1 acre / 4047 m2)(50 lbs P/acre/yr)(454 g/lb)(31 g/mol P/132 g/mol
DAP)(3 yr)/(25 yr) = 0.158 g P
Nitrogen: (1 acre / 4047 m2)(75 lbs N/acre/yr)(454 g/lb)(28 g/mol N/132 g/mol
DAP)(3 yr)/(25 yr) = 0.214 g N
10 Fungicide: DeMarsay (2009) from the Maryland Cooperative Extension
recommends roughly four ounces of fungicide per acre every ten days through the
growing season. Transformity from Brandt-Williams (2001), 1.48 E10 sej/J
corrected by 1.68 (Odum et al. 2000) to 2.49 E10 sej/J.
(1 acre/4047 m2)(4 oz/acre/app.)(182.5 days/year)(1 app./10 days)(28.3 g/oz) =
0.510 g
11 Stainless Steel: 31% of the value calculated in footnote #4 of Table 7.
(1.14 E05 g)/(25 yr)/(50m2)(31%) = 2.82 E01 g
12 Services: Total system cost estimated at $12-20 per square foot (Greenscreen
2009). Used low end of range because the system installed was very simple. A
representative from Jakob-USA (pers. comm.), a cable trellis green fa?ade
company, confirmed the pricing estimate. The cost of system was divided into
three parts: installation, product, and raw material. We assumed services needed
to account for product costs only and that they were already embodied in both the
80
raw material and labor costs. We used the current AK Steel Stainless Steel Price
List (2009) to estimate the commercial rate for stainless steel and used the
prevailing wage rate for one general carpenter and one common laborer in Prince
George?s County, Maryland for installation labor rate (?Labor...? 2009).
Total system cost: (12 $/ft2)(10.76 ft2/m2)(50 m2) = $6456
Installation cost: (32 hr)(33.58 $/hr + 21.35 $/hr)/2 = $879
Raw material cost: (1.14E05 g)(1 lb/454 g)($2.28 /lb) = $571
Product cost: ($6456 total) ? ($879 labor) ? ($571 stainless steel) = $5006
($5006)/(25 yr)/(50 m2) = $4.00
13, 14 Labor: Maintenance and installation labor were estimated based on experience.
Labor emergy calculated using EMERGY/individual method from Odum (1996)
and restated in Campbell and Lu (2009). The fa?ade was installed by a local
contractor and his or her general laborer. Maintenance labor by the homeowner
included pruning, applying fertilizer and fungicide, and watering.
Equation: (individuals)(time worked)(fa?ade area)
Maintenance: (1 individual)(4 hr)(1/8760 hours/year)/(50 m2) = 9.13 E-06
ind*yr2
Installation: (2 individuals)(2 days)(8 hours/day)(1/8760 hours/year)/(25
yr)/(50 m2) = 2.92 E-06 ind*yr
15 A/C Electricity Saved: South Atlantic (USA) average A/C electricity consumption
3467 kWh/year (EIA 2009). Used 10% of A/C electricity saved.
Equation: (annual A/C electricity consumption)(% electricity saved)/(fa?ade area)
81
(3467 kWh/year)(10%)(3.6E6 J/kWh)/(50 m2) = 2.5 E07 J
16 Ecological Production: Estimated by transpiration to be 4.46 E06 J (see footnote
3).
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Chapter 5: Conclusions
Growing vegetation on building walls has many benefits including reducing daily
temperature extremes of the building?s exterior surfaces and reducing the need for air
conditioning in the summer. Few researchers have focused on how green fa?ades reduce
the whole-building cooling load and no studies originate from North America. The
objectives of the research were to experimentally reinforce existing research on the
cooling effects of green fa?ades in North America, to model the effect of a green fa?ade
on hypothetical residential buildings? cooling loads, and to account for the sustainability
of a green fa?ade in an emergy analysis.
Based on data gathered from our experimental building, we concluded that adding
vegetation to the south or west-facing wall effectively reduced the building?s interior air
temperature, exterior surface temperature, exterior ambient temperature, and heat flux
through the wall on hot, sunny days (Chapter 2). Each of these values agreed reasonably
well with those found in the literature. Every comparison between the south and west-
facing wall favored the west wall. This was most likely because our measurements were
made around June when the solar loading on the west wall was much higher than on the
south due to a high sun angle. Later in the summer, when the air temperature is still high
but the solar altitude is much lower, the differences due to orientation in the cooling
effect of the green fa?ade vegetation may be more equal.
In Chapter 3 we took experimental data from the building measurements (detailed
in Chapter 2) and applied them to an ASHRAE cooling load model to translate the
cooling effect of one wall covered with vegetation to the energy budget of the whole
building. As modeled, our green fa?ades had a minor effect (3.4 and 4.8% for south and
83
west, respectively) on the peak cooling load of our experimental buildings in June. In
order to further apply the knowledge gained by this model, I then changed the building
characteristics and created new models for two hypothetical residential buildings. These
models were more realistic in that they accounted for heat gains due to people,
appliances, and through windows. The results from these models varied greatly
depending on orientation and whether or not the building?s windows were covered.
Overall, if windows made up a large part of the whole-building cooling load, then
covering the building?s opaque wall surfaces had little effect (1.4 ? 3.4% reduction in
whole-building peak cooling load). However, when we covered the windows with
vegetation, which is very rare in real-world installations, the peak cooling load was
reduced by a much larger amount (7.8 ? 28.4%).
In Chapter 4 we determined the amount of renewable and non-renewable
embodied energy required to manufacture, install, maintain, and decommission a 50 m2
green fa?ade in a temperate climate on a hypothetical residential home. The model
system consisted of a stainless steel trellis mounted to the south fa?ade of an existing
building with its plants rooted in the ground. The solar emergy required to manufacture,
install, maintain, and decommission the green fa?ade was 9.8 E12 sej/m2/yr, with nearly
55% embodied in human services, 14% in non-renewable materials, and 31% in
renewable materials. Depending on how much A/C electricity could be saved, the benefit
of the green fa?ade ranged from 0 to 5 times the total solar emergy cost. If 10% of A/C
electricity was saved, the green fa?ade had an emergy return on emergy invested for its
non-renewable materials of five. However, inclusion of the emergy invested as human
services in this ratio reduced it to 1.0. These results suggested that the emergy benefit of
84
a green fa?ade was highly sensitive to its effect on building cooling load and total
lifetime costs.
Installing a green fa?ade on the south or west-facing wall of a building in North
America has many benefits including cooling the building?s interior and exterior
environment. The whole-building cooling load reduction benefit may vary greatly
depending on the green fa?ade?s placement on the building, geographic location, building
construction, and plant canopy development. Taking into consideration that few new
green fa?ades cover the building?s windows, the whole-building cooling load benefit is
significantly less than previously thought.
It is our hope that the research presented in this thesis contributed valuable new
information to fellow green fa?ade researchers, designers, installers, and proponents. It
was our intention to provide replicated experimental data for a North American climate
and to present models that realistically estimate the whole-building cooling load benefit.
Considering this new information, we challenge designers to find new and innovative
ways to cover the building?s windows while allowing daylight penetration at the right
time and in the right place.
Future Work
A lot of time was spent on the project designing and constructing the buildings
and instrumentation to be flexible so that Dr. Tilley and future students could expand
upon the project. I would like to suggest the following list of topics for future research
using these buildings.
? Add thermistors to every wall surface, at least on the interior walls, to allow
calculation of the heat flux into the building through every surface. These data
85
can be used to validate a model that completely accounts for the heat content and
flow in the building. We were only able to assume that the north wall and floor,
for instance, were letting a significant amount of heat out of the building during
all hours of the day.
? Combine the green fa?ade concept with Dr. Tilley?s green cloak idea that was
discussed in Laura Schumann?s 2007 thesis. There are many ways to incorporate
vegetation onto the experimental buildings, and doing so with the addition of
adding thermistors to every surface could allow for a powerful analysis of heat
flux and the abilities of the green cloak to perhaps eliminate the need for air
conditioning.
? Adding small room-scale air conditioner units to each building and directly
recording energy consumption with a power meter on each building would be the
best way to estimate reduction in energy use due to green fa?ade vegetation. This
would be particularly useful for calculating an annual or whole-season budget and
would help eliminate many of the uncertainties in the ASHRAE cooling load
model. One major limitation of the ASHRAE cooling load model is that it
estimates annual energy consumption from the peak cooling load and the cooling
degree-day method making a number of large assumptions along the way.
? The folks at Green Roofs for Healthy Cities would like to see data on how the
green fa?ade vegetation affects building materials other than those in a wood-
framed house. While brick and concrete are very easy to integrate into the
ASHRAE cooling load model, further funding is needed to actual construct and
test these materials at the experimental building site.
86
? It would be very useful to estimate the thermal resistance (R-value) of the green
fa?ade vegetation. The R-value concept is easily understood and could go a long
way towards communicating the effects of vegetation on a building?s thermal
environment to non-technical audiences.
? Repeating all data analyses for August or September would help further compare
the cooling effects of the vegetation between building orientations. As stated
before, the solar geometry later in the summer is very different while air
temperatures are still high making a south-facing green fa?ade a potentially more
favorable design choice.
87
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