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Roofenvelope ratio impact on green roof

energy performance

Ryan Martens &Brad Bass &Susana Saiz Alcazar

Published online: 15 April 2008# Springer Science + Business Media, LLC 2008

Abstract This paper addresses the impact of roof-to-envelope ratio on overall energy savings of

a green roof design over conventional roof designs. Simulations were performed using a

modified version of the Environmental System Performance program simulator, developed at the

University of Strathclyde. The modified design employed a model developed by Columbia

University and the Goddard Institute of Space Science which models the evapotranspiritive

effect of a green roof calculated using the Bowen ratio; that is, the ratio of sensible heat flux to the

surrounding air to the latent heat flux resulting from evapourative energy losses. The resultingheat flux term is proportional to the external surface convection, but inversely proportional to the

surface Bowen ratio, which is held constant and chosen to match experimental results obtained

for a given roof design. The present study performed simulations for the month of July in a

Toronto climate on square warehouse style one, two, and three-story buildings, with windows

occupying 10% of the area of each wall. For the first set of simulations, the internal building load

of each story was set to zero, and the roofenvelope ratio was increased by increasing the

building width and length. For the final simulations, several roofenvelope ratios were chosen,

and the internal load of each story was increased from 0 to 50,000 W. As the roofenvelope ratio

increases, the cooling load of the upper floor for multi-story designs approaches the entire

building cooling load. This indicates the importance of upper zone cooling in total building

energy reductions. Furthermore, the total energy savings of a green-roofed building over a

conventional roofed building were far more significant for single-story structures. A 250 250 m

green-roof design with 50,000 W internal loading was found to have percentage energy savings

of 73%, 29%, and 18%, for a one, two, and three-story design, respectively.

Keywords Green roof. Building energy simulation. ESP-r. Building envelope . Latent flux

Urban Ecosyst (2008) 11:399408

DOI 10.1007/s11252-008-0053-z

R. Martens (*) :B. Bass :S. S. Alcazar

Adaptation and Impacts Research Division, Environment Canada, 33 Willcocks Street, Toronto, ONM5S 3E8, Canada

e-mail: [email protected]

B. Bass


S. S. Alcazar



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Introduction

Historically green roofs have been used as a medium for providing insulation and protection in

cold climates, mainly in northern parts of Europe, while in hot dry climates they have been used

to cool the indoor air and increase its moisture content through evaporative processes.Nowadays, green roofs are being implemented not only due to their thermal insulation

properties, but also because they are considered as a way of recovering the benefits provided by

the lost green space of cities. Various studies which have analyzed the effects of green roofs have

focused on a number of key benefits, including reduction in energy consumption, reduction in

greenhouse gas emissions, reduction in heat island effect, improvement in air quality, reduction

of urban noise, storm water management, and various social and recreational opportunities.

Green roofs reduce the heat transfer through the roof, thus reducing the heating and

cooling energy consumption in the building. The heat transfer processes in a common flat

roof, that is, convection, conduction and radiation, are affected by the green roof not only

through a change in the thermal characteristics of the materials and surface properties, butalso through the evapotranspiration and the plant metabolic processes occurring within the

plant system. It is therefore necessary to analyze the thermal performance of both the soil

and vegetation layers added to a conventional roof design.

Niachou et al. (2001) conducted a measurement of surface and air temperatures on green

roofs to examine their thermal properties and potential energy savings. The authors

analyzed the effect of green roofs with different levels of insulation, reporting reductions in

energy consumption ranging from 40% for the non-insulated roof to 2% for the well

insulated roof (considering roof conductance values of 0.4 W/m2C). This work employed

the green roof mathematical model developed by Palomo del Barrio (1997) to evaluate if agreen roof could provide a cooling effect to the buildings. The conclusion of this study was

that green roofs increase the insulating value of the roof, but do not provide any additional

cooling effect on the building.

In another study, several experiments were conducted comparing insulated and non

insulated green roofs (Eumorfopoulou and Aravantinos 1998). It was concluded that green

roofs must be used as a complementary system to the common insulated roof, and cannot

substitute the insulation layer to achieve thermal comfort inside the buildings. The study

identified the shading effect of the green roof as the main factor in the improvement of the

thermal performance.

Wong et al. (2002) analyzed the effect of different types of green roofs on the energyconsumption of a five storey commercial building in Singapore. They compared different

types of vegetation layers (e.g., shrubs, trees and turfing) and various soil thickness. They

reported total energy savings of 15% in relation to the energy consumption of the building

with a common flat roof when a green roof composed by shrubs and 300 mm of clay soil with

40% moisture content was installed in a building with a roof to wall surface ratio of 0.2.

Although green roof technology has been under development for some time, a reliable and

general-purpose model does not yet exist for performing energy-based simulations of a generic

green roof. Such a model would allow simulations to be performed on a variety of design

alternatives, allowing intelligent design decisions to be made without the high cost of obtaining

experimental data on a given design alternative. In many fields of study, computer modeling

and simulation has proven to be a low-cost means of obtaining a wealth of information quickly

and efficiently. What would previously require considerable effort and cost in construction,

instrumentation, and time for monitoring data, can now be performed and analysed in minutes

on a typical computer of today. In order to perform this work, however, a numerical model must

be developed and fully validated under a variety of circumstances.

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Although this study does not develop a general-purpose model of a green roof for use with

energy-based building simulation, it does demonstrate the ease in which a great deal of data

may be obtained efficiently and easily using a building energy simulation tool, Environmental

System Performance program (ESP-r; Energy Systems Research Unit (ESRU)). In this study, a

rooftop energy balance model for a green roof is integrated into an existing full building-energy simulation tool in order to determine the performance of a simple green roof model.

In a study conducted by Gaffin et al. (2005, 2006), based on experimental results

obtained from test buildings at Pennsylvania State University (DeNardo 2003), a rooftop

energy balance model was used to model the thermal characteristics of a green roof. The

evaporative heat loss from a green roof, or latent heat, was modeled as proportional to the

convective heat transfer from the rooftop surface to the surrounding air. This factor of

proportionality, the Bowen ratio, is the ratio of the sensible heat flux to the latent heat flux.

Thus the latent heat flux from a green roof, may be expressed as:

Qlatent Qconvectionb

whereis the Bowen ratio. For a control roof, this term is assumed to be zero. Unlike the

previous study, however, no equilibrium conditions have been assumed, resulting from the

ability of ESP-r to simulate transient heat transfer. Furthermore, the entire test-building was

modeled in ESP-r, rather than just the roof.

The base-case model was then extended to model a larger warehouse-style building in a

Toronto climate. Various sized buildings were simulated, with varying internal loading, in

order to determine various trends in the overall green roof energy savings over a

conventional roof design. It is important to note that not all components of a green roof,such as heat storage and insulation from the soil medium, were accurately modeled, as the

green roof improvements were captured simply by adding the latent heat flux term

containing the pre-determined Bowen ratio value.

Implementation in ESP-r

ESP-r is a general-purpose, transient building simulation tool developed at the University of

Strathclyde in Glasgow, Scotland, which accurately models the heat, air, moisture, and

electrical power flows of a building under the control of a plant system (ESRU). This multi-domain problem is solved at user-configurable time-steps. ESP-r is an open-source project,

which allows the implementation of new features, as well as a full understanding of the

theory and assumptions made in the simulation. Further information on the theoretical

formulation of ESP-r is documented by Clarke (Clarke 2001).

In order to perform the present study, the simple one-dimensional model employed in

(Gaffin et al. 2005,2006) was integrated in ESP-r. A full validation was performed using

data obtained from (Gaffin et al. 2005, 2006), as well as experimental data used in

(DeNardo 2003). Several complications arose in this comparison, namely due to

inconsistent climate data. A larger set of climate data was required for the full building

model used by ESP-r, as compared to the one-dimensional model of the roof. Not all of the

required data was logged at the Pennsylvania State test site. As a result, it was necessary to

obtain some of the required solar radiation data from logging performed at a nearby site.

This inconsistency, as well as the inability to obtain full thermal properties of all portions of

the building modeled, proved problematic, and many assumptions were made in the

comparison. The building modeled in this study maintains only the same roof properties as

Urban Ecosyst (2008) 11:399408 401


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those used in the Pennsylvania State test building, which were in fact known. The wall

properties were changed to account for requirements of the new building design, discussed later.

Furthermore, the climate data used was that for the city of Toronto (43 N, 79 W). This climate

is similar to the Pennsylvania State (40 N, 77 W) climate, and all quantities in this data set are

in fact consistent, eliminating the problems previously discussed. The climate for Toronto andPennsylvania State are shown in Tables1 and2, respectively (Weatherbase2007).

The convection model employed was the same as used in (Gaffin et al. 2005, 2006),

based on a model by Terjung and ORourke (Terjung and ORourke1980b), but modified

at low wind speeds to prevent the convection term from vanishing.

Qconvection g1 u0:8 TsurfTair ; u >1:75

Qconvection +2 Tsurf Tair ; u e1:75

In the above,g1and g2were set to 6.5 and 10.3, respectively, as obtained for the control

roof using statistical analysis (Gaffin et al. 2005,2006). Convective heat-transfer from the

green roof was assumed to be similar to that of the control roof. Any changes in heat-

transfer for the green roof will be caused by the latent transfer, which as previously

discussed, is proportional to the convective transfer.

The zone air temperature was assumed well-mixed and held constant at 22C through

the use of an ideal air-conditioning and heating model. A control time-step of 2 min was

chosen to ensure that the zone air temperature remained constant at all times. As the

simulations were performed during the month of July, the focus of analysis was on total

cooling loads. It should be noted that on some nights, a small amount of heating wasrequired to maintain this fixed internal air temperature. The effect of heating on building

energy consumption was ignored in this study.

Model of a simple warehouse

A simple warehouse building was modeled using ESP-r. As previously noted, the roof

properties of the green roof used were identical to that of the Pennsylvania test site to

maintain compatibility with the parameters used in the model. All other properties were

Table 1 Average climate for Toronto, ON

Quantity Units Annual Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Average temperature C 7 6 5 6 12 17 21 20 15 8 3 2

Average high

temperature

C 12 2 1 3 11 18 22 26 25 20 13 6

Average low

temperature

C 2 9 9 4 1 7 12 15 14 10 3 6

Average precipitation Cm 76 4 4 5 6 6 6 7 8 7 6 6 6Average relative

humidity (morning)

% 83 83 83 82 78 76 78 79 86 89 87 86 84

Average relative

humidity (evening)

% 64 76 73 68 58 55 54 54 57 61 65 74 78

All simulations in this study were performed using climate data from Toronto. A summary of the Toronto

climate is provided for comparison with State College, PA, USA

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modified, but were consistent between the green-roofed building and the control building.

For all cases, the height of each story was fixed to 3.0 m, and windows were assumed to

occupy 10% of the total area of each wall, except the north wall, which contained a single

door.

Table 3 shows the material properties used in the simulated buildings. The individual

materials for each construction are specified from the outside to the inside. With the

exception of the roof, which is based on Pennsylvania test site constructions, the properties

were obtained from the ESP-r construction database. As a result, some of the materials usedmay not be familiar to North American readers.

It is important to note that the green roof model does not contain any material for

increasing the thermal capacitance. The sole effect of the green roof is obtained through the

latent heat loss term, resulting from water vapour evaporation. Further experimental

comparisons should be performed to examine the effect of including thermal capacitance in

the model. Since the soil medium employed at the test site studied was quite thin, the

overall effect is expected to be small. Although simple to add in the simulations performed,

this was not modeled to maintain consistency with the parameters obtained at the

Pennsylvania State test site.

The study was performed for the month of July in a Toronto climate. It should be notedthat the chosen Bowen ratio, 0.12, is highly dependent on the green roof itself, as well as

the climate in which the roof is implemented. The previous study (Gaffin et al. 2006) used

Bowen ratios ranging from 0.21 to 0.35. The lower value was chosen as the simulated

model is already somewhat conservative in nature. As mentioned previously, no thermal

capacitance was modeled for the roof. Also, the model calculates the temperature of the

roof-top surface, not the temperature below the soil surface in contact with the roof

insulation, which is slightly cooler. The combination of the above factors justifies the

selection of 0.12 for the Bowen ratio. Although the Bowen ratio employed was determined

for a Pennsylvania climate, the Toronto climate should result in similar values. A Toronto

climate was chosen for several reasons. First, and most important, is the fact that the Penn-

state data obtained was pieced together from several sources. Inconsistencies in data sets

proved problematic in ESP-r simulations. In addition, the Toronto climate proved of

immediate interest for other research, although it would be beneficial to repeat the study

under other climates. Recall, however, that the Bowen ratio is strongly dependant on

humidity, and other climatic factors.

Table 2 Average climate for State College, PA, USA

Quantity Units Annual Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Average temperature C 9 2 2 2 8 14 19 21 20 16 10 4 1

Average hightemperature

C 15 1 2 7 14 21 25 27 26 22 16 8 2

Average low

temperature

C 4 6 6 2 3 8 13 16 15 11 5 5

Average precipitation cm 98 7 6 8 8 10 10 9 8 7 7 6 6

Average relative

humidity

% 74 77 73 72 68 72 72 74 76 76 73 75 77

Previous studies developed a green roof model using a test site in Pennsylvania. Due to inconsistencies in

available PA data, and a requirement for results in the city of Toronto, simulations were conducted for a

Toronto climate

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Roof

envelope ratio analysis

In order to assess the impact of roofenvelope ratio on overall energy savings resulting

from a green roof, a variety of simulations were performed on the previously described

warehouse-type building. One, two, and three story buildings were examined in order to

determine the drop in energy savings with increasing building height. Building-envelope

ratio was varied by changing the length of each wall, and the internal loading was assumed

to be zero, unless noted otherwise. The benefit of a green roof over a conventional-roof was

obtained by comparing the total building cooling loads required for each case. The

percentage savings is defined as the ratio of the difference in cooling load required for a

green roof to the total cooling load of the control roof.

Figure1shows the total cooling load for both green and control roofs as a function of

building roofenvelope ratio, for a constant internal loading of both 0 and 5,000 W. It

should be noted that the latter load employed is somewhat low for the building sizes

investigated in this study. Nevertheless, the increase in cooling load required is still

significant, and provides further evidence of the advantage gained through the use of a

Table 3 Summary of simulated building material properties

Thickness Conductivity Density Specific

heat

Longwave

emissivity

Solar

absorptivity

Diffusion

resistance

(m) (W/mC) (kg/m3) (J/kgC)

Wall

Brick 0.100 0.960 2000 650 0.90 0.70 25

Glasswool 0.075 0.040 250 840 0.90 0.30 4

Air 0.050 0.000 0 0 0.99 0.99 1

Breeze block 0.100 0.440 1500 650 0.90 0.65 15

Roof

Aluminum 0.003 210.0 2700 880 0.22 0.20 19200

Air 0.025 0.000 0 0 0.99 0.99 1

Glass fiber quilt 0.080 0.040 12 840 0.90 0.65 30

Aluminum 0.003 210.0 2700 880 0.22 0.20 19200

Green roofPlywood 0.019 0.200 560 1000 0.90 0.70 576

Fiberglass 0.089 0.049 300 1000 0.90 0.50 5

OSB 0.006 0.110 600 1210 0.80 0.65 12

Ground floor

Earth 0.250 1.280 1460 879 0.90 0.85 5

Gravel 0.150 0.520 2050 184 0.90 0.85 2

Heavy-mix concrete 0.150 1.400 2100 653 0.90 0.65 19

Air 0.050 0.000 0 0 0.99 0.99 1

Chipboard 0.019 0.150 800 2093 0.91 0.65 96

Wilton 0.006 0.060 186 1360 0.90 0.60 10

Suspended floor

Wilton 0.006 0.060 186 1360 0.90 0.60 10

Chipboard 0.019 0.150 800 2093 0.91 0.65 96

Air 0.050 0.000 0 0 0.99 0.99 1

Heavy-mix Concrete 0.140 1.400 2100 653 0.90 0.65 19

Steel 0.004 50.000 7800 502 0.12 0.20 19200

Roof properties used in the simulation are identical to those of the Pennsylvania test site. All other properties

used in the simulation are taken from the ESP-r construction database

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green roof. The reduction in cooling load for the 5,000 W case decreases steadily for both

the green and control roof due to the increased total building size required to obtain larger

roofenvelope ratios. What is more important is the increase in savings obtained by a green

roof at these higher ratios.

Figures2and 3extend these findings to a two and three story building, respectively. In

addition, these figures break down the cooling load required into that required to cool only

the upper floor of the building, as well as that required to cool the total building. Again, for

small roofenvelope ratios, the green roof provides no benefit, as expected. At the oppositeend of the spectrum, however, the reduction in cooling load with the use of a green roof is

significant. More importantly, it becomes clear how important a roof is in dictating the

overall energy load of a building. As is clearly shown in Figs. 2and3, the cooling load of

the upper floor alone approaches the total cooling load at higher roofenvelope ratios. In

fact, above a roofenvelope ratio of 0.7 for a two-story building, the upper floor value

equals the total building cooling load. This effect is slightly less pronounced in the three-

story design. In both cases, the increase in cooling load with increasing roofenvelope ratio

Fig. 1 Variations in cooling load

for a single-story building with

the control and green roofs. The

simulations were performed with

a modified version of the ESP-r

model. Each simulation is run

with a constant internal loadingof 0 and 5,000 W, with 0 repre-

senting a baseline situation where

cooling is the only demand for

electricity in an unoccupied

building

Fig. 2 Variations in cooling loadfor a two-story building with the

control and green roofs. Cooling

load is shown for the entire

building, and also for the upper

floor alone, demonstrating that

for large roofenvelope ratios,

cooling of the upper floor

accounts for the entire building

cooling load. Green roofs provide

significant savings over the con-

trol roof with increasing roof

envelope ratios

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is due to the larger building sizes of the high roofenvelope ratio buildings. Of more

importance is the energy savings of the green roof case over the conventional roof design.

Figure 4 summarizes the percentage savings in cooling load of a green roof over a

conventional roof for all cases previously considered. The reduction in performance for

multi-story buildings quickly becomes apparent, although the gain in performance for high

roofenvelope ratios is significant in all cases.

The results obtained for the single story building represent an extreme case. The highroofenvelope ratio was obtained for a building of 250 250 m. Although this is not

uncommon with some warehouse building constructions, the convection model employed

may not provide accurate results for a rooftop of this size. Further studies should investigate

the use of other convection models in order to fully understand the flow over such a large

surface. Furthermore, a building with no internal loading does not represent a practical case.

The next section will deal with the addition of internal loading, and the overall effect on

reducing the performance gain of a green roof.

Fig. 3 Variations in cooling load

for a three-story building with the

control and green roofs. Cooling

load is shown for the entire

building, and also for the upper

floor alone. Slightly larger roof

envelope ratios are required forthe upper floor cooling load to

reach the total building cooling

load, when compared to the two-

story building

Fig. 4 Percentage savings in

building energy usage of greenroof design over the control roof

for a one, two, and three-story

structure. Overall savings from a

green roof are reduced for an

increasing number of stories, but

become more substantial for

higher roofenvelope ratios

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Internal load analysis

In addition to examining the impact of roofenvelope ratio, the effect of internal loading

was also examined. For several representative roofenvelope ratios, the internal loading

was varied from 0 to 50,000 W, a load more representative of buildings of this dimension.

Figure5 shows the effect of increasing the internal load for each of the test buildings, with

a roof area of 100 100 m. As shown in the plot, the net energy savings increases

approximately linearly with increased internal loading. This increase, however, reaches amaximum value, after which an increase in internal loading results in a drop in net energy

savings. For a 100100 m square roof, the effect is not noticed for two and three story

buildings.

Similar plots may be generated for larger roof areas. Although the energy savings are

larger, notably a net energy saving of up to 13,000 kW h for the three story building with a

roof area of 250250 m, the plots are considerably more flat, indicating the reduced effect

of total internal load on such a large building. Furthermore, the peak in energy savings is

not present in the case of larger buildings.

Fig. 5 Net energy savings

obtained from a green roof as a

function of internal loading for a

one, two, and three-story ware-

house structure measuring 100

100 m. Energy savings increase

approximately linearly with in-creasing internal load. A maxi-

mum value is shown in the

single-story case, after which net

energy savings decrease with in-

creasing internal load

Fig. 6 Percentage energysavings for a single-story with

varied internal loading. Increased

internal loading results in an

overall reduction in energy

savings, although savings are still

substantial

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Figure 6 demonstrates the percentage energy savings of a single story building with

varying internal loading. As shown in the figure, more realistic values for energy savings

are obtained when realistic internal loading is assumed. The values approaching 100%

obtained for all cases with 0 W internal loading are clearly not obtainable in a practical

structure. For loadings more typical of a practical structure, however, the savings are stillsignificant. A 250250 m green-roof design with 50,000 W internal loading was found to

have percentage energy savings of 73%, 29%, and 18%, for a one, two, and three-story

design, respectively.

In addition to addressing the issue of improved convection modeling, future studies

should investigate several further issues. This model accounts for the evapotranspiration

present on a green roof. The model does not directly account for changes in convection

resulting from the green roof. Furthermore, a green roof with a larger mass should also be

studied using the present model, in order to investigate the effect of thermal capacitance on

energy savings. The present study has assumed a constant value for the Bowen ratio.

Additional studies should identify the Bowen ratio as a function of climate conditions, as

well as any additional required green roof parameters. This would allow an investigation of

green roof performance at other sites and under other climates.

References

Clarke JA (2001) Energy simulation in building design, 2nd edn. Butterworth-Heinemann, Oxford

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