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Green-roof design decision support: climate specific green roof design recommendations

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Green-roof design decision support: climate specific green roof design recommendations

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Content Green-Roof Design Decision Support:
Climate Specific Green Roof Design Recommendations
By
Spurthy Yogananda
Presented to the
FACULTY OF SCHOOL OF ARCHITECTURE
UNIVERSITY OF SOUTHERN CALIFORNIA
In partial fulfilment of the
Requirements of degree
MASTERS OF BUILDING SCIENCE
AUGUST 2015
ii
THESIS COMMITTEE MEMBERS
COMMITTEE CHAIR.
Dr. JOONHO CHOI
ASSISTANT PROFESSOR
University of Southern California
Building Science, School of Architecture
Watt Hall #318, Los Angeles, CA 90089
Tel: (213)740-4576
Email: joonhoch@usc.edu
Douglas Noble
Director of Building
Science, 204 Watt Hall,
School of Architecture
University of
Southern California
Los Angeles, CA
90089-0291
Tel: (213)740-4589
Email: dnoble@usc.edu
George Ban Weiss
Assistant Professors,
Kaprielian Hall, Room
230 Sonny Astani
Department of Civil and Envi-
ronmental
Engineering
University of
Southern California
3620 S. Vermont
Avenue, Los Angeles,
CA 90089-2531
Tel: (213)740-9124
Email: banweiss@usc.edu
Karen Kensek
Assistant Professor,
204 Watt Hall,
School of Architecture
University of
Southern California
Los Angeles, CA
90089-0291
Tel: (213)740-2081
Email: kensek@usc.edu
iii
DEDICATION
To my family, for being my biggest strength and Prof. Douglas Noble and Prof. Joon Ho
Choi for inspiring me and believing in me throughout my Masters Program.
i
ACKNOWLEDGEMENT
I am using this opportunity to express my gratitude to everyone who supported me through-
out my thesis. I am thankful for their aspiring guidance, invaluably constructive criticism and
friendly advice during the research work. I am sincerely grateful to my committee members
and my dear friends and seniors for sharing their views on a number of issues related to the
research.
I express my thanks to Dr. Joon-Ho Choi, Dr. Douglas Noble and Karen Kensek for their
support and guidance at University of Southern California. I would also like to thank my thesis
external guide Dr. Stuart Baur from Department of Civil, Architectural, and Environmental
Engineering at the Missouri University of Science and Technology. I would also like to extend
my thanks to all the people who provided me with their feedback and constructive criticisms for
my research project. Last but not the least, I would like to thank God almighty and my family
members for their support and encouragement throughout my research.
ii
Green-Roof Design Decision Support:
Climate Specific Green Roof Design Recommendations
ABSTRACT
TIn spite of many design and technical efforts to improve building performance using green
roofs as building enclosure components, the critical uncertainty of existing mechanisms, such
as pre-defined computational modeling and design guidelines, have frequently resulted in lower
building performance efficiency than intended by the design. Examination of many actual green
roof performance cases revealed an even larger energy usage and/or lower environmental per-
formance of the building where implemented, than those of the adopted base cases. To address
this challenge, this research will help develop a better understanding of the various components
involved in the construction of a green roof like the soil, insulation leaf area index based on the
climate zone they are located. Impact of each of the above mentioned component is studied in
various climate zone. The parameter are varied for each component until the lowest energy is
achieved from the Combination of leaf area index, insulation and soil by running the calibrated
model simulation with the help of design builder. Based on integrated principles of design and
building configurations, the green roof design strategies developed by this research can lead to
effective green roof design decisions in an early stage of an individualized project.
Keywords: Green roof, simulations, EUI.
iii
Contents
1 Chapter 1: Introduction 1
1.1 Problem . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Hypothesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.3 Importance of the this research . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.4 What is a green roof? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.5 Importance of green roof. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.6 Technical Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.6.1 Urban Heat Island . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.6.2 Solar Reflectance Index (SRI) . . . . . . . . . . . . . . . . . . . . . . 6
1.6.3 Evapotranspiration . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.6.4 Leaf Area Index (LAI) . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.6.5 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.7 Chapter structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2 Chapter 2: Background studies. 11
2.1 Introduction to Green Roofs . . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.1.1 How do the Green Roofs Work? . . . . . . . . . . . . . . . . . . . . . 11
2.1.2 Overview of Details and Construction of Green Roofs . . . . . . . . . 13
2.2 Green roof systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2.1 Intensive green roof system . . . . . . . . . . . . . . . . . . . . . . . 15
2.2.2 Semi intensive green roof system . . . . . . . . . . . . . . . . . . . . 16
2.2.3 Extensive green roof system . . . . . . . . . . . . . . . . . . . . . . . 17
2.3 Sustainability codes and building rating systems . . . . . . . . . . . . . . . . . 18
2.3.1 Leadership in Energy and Environmental Design (LEED) . . . . . . . . 18
2.4 Lack of green roof design guidelines . . . . . . . . . . . . . . . . . . . . . . . 19
iv
2.4.1 Lack of industry standards and design guidelines and specifications: . . 19
2.4.2 Lack of qualified designers and contractors: . . . . . . . . . . . . . . . 20
2.5 Energy modeling of green roofs . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.6 Field experiments and case studies on the thermal performance of green roofs
across the globe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.6.1 Energy saving . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.6.2 Cooling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3 Chapter 3: Data collection and building energy software. 27
3.1 Data collection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.1.1 Selecting the site to place sensors . . . . . . . . . . . . . . . . . . . . 27
3.1.2 Checking for errors in the sensors . . . . . . . . . . . . . . . . . . . . 28
3.1.3 Placing of sensors and a data collection . . . . . . . . . . . . . . . . . 29
3.2 Simulation model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.3 Simulation engine and Graphic User Interface . . . . . . . . . . . . . . . . . . 32
3.4 Modeling a green roof in Design Builder with EnergyPlus engine . . . . . . . 33
3.4.1 Limitations of modeling a green in Design Builder . . . . . . . . . . . 33
4 Chapter 4: Methodology 35
4.1 Green roof model validation . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
4.2 simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
4.2.1 Parameter 1: Insulation . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.2.2 Parameter 2: Soil depth . . . . . . . . . . . . . . . . . . . . . . . . . . 37
4.2.3 Parameter 3: Vegetation type (based on the Leaf Area Index) . . . . . . 38
4.2.4 Parameter 4: Climate type . . . . . . . . . . . . . . . . . . . . . . . . 39
4.3 Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
5 Chapter 5: Data collection, calibration and validation. 41
v
5.1 Temperature data at Burbank. . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
5.1.1 The green roof measured data. . . . . . . . . . . . . . . . . . . . . . . 42
5.1.2 The non- green roof measured data. . . . . . . . . . . . . . . . . . . . 44
5.2 Temperature data at Rolla. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
5.2.1 Study of ambient temperature in the various roof type. . . . . . . . . . 46
5.2.2 Study of surface temperature in the various roof type . . . . . . . . . . 47
5.2.3 Study of Concrete Temperature in the various roof type . . . . . . . . 48
5.2.4 5.2.4. Study of Precipitation, Temperature, Solar Radiation, Humidity,
Wind Speed. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
5.3 Calibration and validation of the model. . . . . . . . . . . . . . . . . . . . . . 49
5.3.1 Burbank validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.3.2 Rolla validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
6 Chapter 6: Simulations with various parameters. 52
6.1 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
6.1.1 Parameters for Simulation . . . . . . . . . . . . . . . . . . . . . . . . 52
6.2 Results and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
6.2.1 Simulation Results Analysis. . . . . . . . . . . . . . . . . . . . . . . 54
6.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
6.3.1 Analysis for Burbank . . . . . . . . . . . . . . . . . . . . . . . . . . 56
6.3.2 Analysis for Rolla . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
6.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
7 Chapter 7: Limitations and future work and conclusion 61
7.1 imitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
7.2 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
7.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 62
vi
List of Figures
1 Green roof - Eco dome, Seoul. ( Samoo Architects & Engineers. Green Roof -
Eco Dome. Digital image. N.p., n.d. Web) . . . . . . . . . . . . . . . . . . . . 2
2 Temperature differences between the cities and the surrounding area due to the
UHI effect (Shickman 2011) . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
3 Solar Reflectance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
4 Process of Evapotranspiration. . . . . . . . . . . . . . . . . . . . . . . . . . . 8
5 Vegetated roof heat flow (Wark 2010) . . . . . . . . . . . . . . . . . . . . . . 13
6 Energy balance of two different roofing types (Velasco 2011) 2.1.2. Overview
of Details and Construction of Green Roofs. . . . . . . . . . . . . . . . . . . . 14
7 Chicago city hall Building with Intensive green roof (Chicago Department of
Environment, Mark Farina). . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
8 Carnegie Mellon Hamerschlag Hall with semi intensive green roof system (Carnegie
Mellon) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
9 Bronx County Courthouse with Extensive green roof. (New York Times) . . . . 18
10 Green roof module predictions as compared to measured soil surface temper-
atures for green roofs at the University of Central Florida test site. The figure
panels represent two weeks of hourly data within each of four seasons (D. J.
Sailor 2008) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
11 Percentage of effectiveness achieved by each type of green-roof over the Tradi-
tional and the Un-Isolated roofs in Cairo-Egypt (Kamel, et al. 2012) . . . . . . 23
12 Comparison of interior of buildings with conventional (non-green) and green
roofs from a case study in Pennsylvania . . . . . . . . . . . . . . . . . . . . . 25
13 Represents the various climate zones . . . . . . . . . . . . . . . . . . . . . . . 27
14 Green roof on Burbank Water and Power Building (California). . . . . . . . . . 28
15 Green roof on Emerson Electric Company Hall (Rolla) . . . . . . . . . . . . . 28
16 Section of the green roof showing all the placements of sensors. . . . . . . . . 29
17 Represents the sensor placed to measure ambient temperature and humidity . . 30
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18 Shows the sensors placed below the slab to measure the concrete temperature . 30
19 Shows the sensor placed on the glass material wrapped in aluminium paper . . 31
20 a&b Shows the sensors placed at different levels in the green roof. . . . . . . . 32
21 Thermocouples affixed to the concrete sub-slab beneath each roof section. . . . 32
22 Energy simulation engine and the GUI . . . . . . . . . . . . . . . . . . . . . . 33
23 Flowchart1describing the methodology . . . . . . . . . . . . . . . . . . . . . 35
24 DOE 2 three storey office building. . . . . . . . . . . . . . . . . . . . . . . . . 36
25 Various parameters that would be used in this research is shown in the section
of green roof (Groundworks Sheffield) . . . . . . . . . . . . . . . . . . . . . . 37
26 Different soil depth (Groundworks Sheffield) . . . . . . . . . . . . . . . . . . 38
27 Various LAI in plants. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
28 The green and non- green roof area at the Burbank water plant building. . . . . 41
29 Temperatures at different levels of the green roof. . . . . . . . . . . . . . . . . 42
30 Non green roof area plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
31 Ambient temperature recorded by white, green and black roof . . . . . . . . . 47
32 surface temperature recorded by white, green and black roof . . . . . . . . . . 47
33 Concrete surface temperature recorded by white, green and black roof . . . . . 48
34 Weather data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
35 Roof study model naming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52
36 Best green roof composition in Burbank based on loads . . . . . . . . . . . . . 54
37 Best green roof composition in Burbank based on temperature. . . . . . . . . . 55
38 Best green roof composition in Rolla based on loads. . . . . . . . . . . . . . . 56
39 Best green roof composition in Rolla based on temperature. . . . . . . . . . . . 56
40 Comparison in terms of load in Burbank. . . . . . . . . . . . . . . . . . . . . . 57
41 Comparison with respect to temperature in Burbank. . . . . . . . . . . . . . . 58
42 Comparison in terms of load in Rolla. . . . . . . . . . . . . . . . . . . . . . . 59
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43 Comparison in terms of load in Rolla. . . . . . . . . . . . . . . . . . . . . . . 60
44 Present the simulated data for each roof type on a hot day In Burbank. . . . . . 67
45 Present the simulated data for each roof type on a cold day In Burbank. . . . . 68
46 Present the best 10 green roof composition for Burbank. . . . . . . . . . . . . 68
47 Present the temperature and load of base case model for Burbank . . . . . . . . 68
48 Present the best 10 green roof composition for Burbank. . . . . . . . . . . . . 69
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List of Tables
1 The weight of the green roof components . . . . . . . . . . . . . . . . . . . . 14
2 The below shows the different types of green roof systems and their character-
istics. (Table 2) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3 Mean and maximum indoor air temperature and heating, cooling, and total energy. 22
4 Mean and maximum indoor air temperature and heating, cooling, and total en-
ergy for different insulation levels (Jaffal, Ouldboukhitine and Belarbi 2012) . . 22
5 Ranges of various parameters input for Ecoroof model (The encyclopedic ref-
erence to EnergyPlus input and output 2011) . . . . . . . . . . . . . . . . . . . 34
6 Subset for each parameters for a green roof simulation. . . . . . . . . . . . . . 38
7 Shows the chosen two climate zones and the climatic conditions of the chosen
two place. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
8 Above represents the temperature at different layers of a green at an interval of
30 minutes for 24 hours. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
9 Above represents the temperature at different layers of a glass (which is used
has a part decoration in the green roof) the at an interval of 30 minutes for 24
hours. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
10 Burbank validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
11 indicates the percentage of difference between measured and simulated tem-
perature After the validation of the models for both Burbank and Rolla was
completed and the difference in percentage between measured and simulated
temperature was found to be well within the +/- 20 %. The models were then
used to run the simulations with various different green roof parameters. . . . . 51
12 Important factors considered. . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
13 Best options for Burbank for active system . . . . . . . . . . . . . . . . . . . . 57
14 Best options for Burbank for passive system . . . . . . . . . . . . . . . . . . . 57
15 Best active option for Rolla. . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
16 Best passive option for Rolla. . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
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HYPOTHESIS:
The impact on the efficiency of energy saving of a green roof depends on various compo-
sition parameters involved in construction, which is influenced by the climate zones in which
green roof is built.
1
1 Chapter 1: Introduction
1.1 Problem
According to the U.S. Department of Energy, the average American Household releases about 2
tons of carbon dioxide into the atmosphere each year. It has been reported that the house owners
spend up to 11 billion dollars a year to cool their houses (U.S. Department of Energy 2008).
Many cities including Los Angeles suffer from what is known as Urban Heat Island effect
(UHI). UHI is caused by usage of materials like concrete and asphalt. These materials absorb
the heat from the heat waves and store heat and heat up the building and this heat is released
during the night, making the nights warmer. Due to this heat island effect, the temperature
in the cities is 10 degrees higher than the surrounding suburbs (EPA-RUHI, 2010). One of
the mitigations for the urban heat island effect is the green roof (Government 2011). Green
roofs are roofs that are considerably secured with living plants. Historical and archaeological
proof shows that green roofs have been built for more than three thousand years, although their
use has been restricted by the basic expense of supporting heavy soils and by the specialized
difficulties of low-slant waterproofing (Conservation Technology Inc. 2008). The essential part
of a green rooftop is to protect the structure from warmth, icy, snow, rain and wind. A green
roof is a typical rooftop which comprises of soil and plant layers alongside a waterproofing
film. This type of roof relies on different parameters like leaf area index, insulation, soil depth,
and plant type. They are impacted by the climate zone they are built. Although designers,
contractors and clients can comprehend the potential significance of a green rooftop, they lack
much-needed knowledge regarding the variation of climate-related parameters that will benefit
maximum energy savings. Having the knowledge about these climate zone parameters can have
a positive impact on energy saving, and in turn make the green roofs more economical (Doshi
and Peck 2013). This can increase the growth in the construction of green roofs across the
globe.
1.2 Hypothesis
A green roofs energy-saving impact depends on various composition parameters, is also influ-
enced by the climate zones in which they are built.
2
1.3 Importance of the this research
With the help of a quantitative and physically-based building energy simulation tool that repre-
sents the effects of green roof construction, the process of assessing green roof benefits becomes
much quicker, easier and more accessible. Not only the architects and the developers, but also
the client and the public, can get a better understanding of benefits of installing a green roof and
its impact. Hence the goal of the research was to develop a decision support tool that would
help architects decide upon the composition involved in designing of a green roof, which could
be more accessible to the public and also make it possible to account for green roof benefits in
energy codes, related energy-efficiency standards and rating systems such as LEED.
1.4 What is a green roof?
A green roof is a vegetative layer on top of typical roof, which is otherwise known as an eco-
roof. A green roof consists of plants, soil, water proof membrane and insulation.
1.5 Importance of green roof.
Figure 1: Green roof - Eco dome, Seoul. ( Samoo Architects & Engineers. Green Roof - Eco
Dome. Digital image. N.p., n.d. Web)
Pavements, roads and dark colored roofs absorb and trap heat from the sunlight and increase
the temperatures. Urban zones have a tendency to have more streets, structures, and parking
garages and less green space. The high centralization of these heat absorbing surfaces causes
a temperature raise in urban areas. Studies in these areas have shown an increase in air and
surface temperatures that are, on average, 1.8 5.4F higher than temperatures in surrounding
rural areas. In an extreme situation, there was a potential increase in temperature for up to 22F.
3
The increase in temperature in urban areas when compared to the surrounding rural areas is
known has the urban heat island effect ( UHI) (EPA-RUHI, 2010). The trademark slant towards
warming of urban surfaces is exacerbated amid hot days and warmth waves, which strengthens
the air temperature increment (Getter and Rowe 2006), and this is turn results in high-energy
consumption for cooling loads in the building (Heat, Reduction, and Webcast 2010). One
of the mitigations for UHI is the usage of green roofs in buildings. Green roof can be seen
across various disciplines, with various reasons pertaining to economic, aesthetic, and environ-
mental reasons (William C. 2010). Through green roofs, architects nurture the built environ-
ment around us and simultaneously incorporate high-performance building with environmen-
tally friendly design. Utilizing this strategy helps clean the air and water, and also helps in
promoting energy efficiency, thus creating more balanced and ecologically sustainable sites.
Plants and their growing medium on top of a green roof enhances the environment through the
naturally-occurring processes called evapotranspiration and photosynthesis, thereby making the
surrounding ecosystem much better. Evapotranspiration is a process in which the plant canopies
introduce water vapour into the atmosphere via transpiration and the evaporation of water from
the soil and from leaves and stems (Baldocchi 2003). The specific benefits of green roof are that
of easing environmental stress and to create an eco-friendly society and also to re-establishing
endangered species (Garrison et al. 2012). Some advantages of green roof are: storm water
biodiversity and habitat , economic benefits, recovering waste, increased points in the LEED
rating system, emerging synergy with solar power, noise and sound insulation, fostering a sense
of community and making people happy.
These are explained in detail below:
Storm water management
At the point when contrasting green and ordinary rooftops, storm-water administration devel-
ops as a critical separating element. While customary rooftops simply shed water, green roofs
utilize most occurrence water and gradually discharge the rest. Case in point, in a commonplace
year in the Midwestern United States, 75% of the water is held on a green rooftop by aborption
in plants and the dirt layer, and 25% gets to be spill over. Green roofs control overflow even
in zones with frosty, cold seasons. Again in the Midwest, the normal summer water assimila-
tion rate is 70-100%, with winter retention averaging 40-half. It lives up to expectations along
these lines: when a green rooftop achieves immersion, overabundance water gradually perme-
ates through the vegetation layer. The dirt layer traps silt, leaves, overwhelming metals and
different particles, treating overflow before it achieves the seepage outlet. Other than enhancing
water quality by cleaning overflow, green roofs likewise decline flooding in neighbourhood wa-
4
tersheds by augmenting plant uptake of precipitation and minimizing expenses of storm water
administration. An arrangement of green roofs could be the absolute best way to storm water
administration in urban focuses (Macdonagh 2005) (Fibres 2011).
Heat mitigation
The large-scale use of green roofs cities would help reduce the urban heat island effect by
lowering ambient air temperatures. Green roof plants reduce air temperatures, which could be
due to shade or due to evapotranspiration. This would then reduce the temperature which is
usually higher when compared to the surrounding areas within a city (EPA-RUHI, 2010).
Air quality improvement
The vertical building massing of downtown zones regularly restrains ventilation, diminishing
wind speed and creating pockets of warmth. Toxins can stay suspended for drawn out stretches
of time. Green roofs assimilate carbon dioxide, a noteworthy car outflow, through foliage,
continually purging the air. The air-purging limit of green roofs has direct profits for individuals
who experience the ill effects of asthma and other respiratory infirmities. (Macdonagh 2005)
(Fibres 2011)
Erosion and sedimentation control
Green roof act as erosion barriers and reduce the soil erosion since a thick cover of plants
hold soil in place in case of dust storm or flooring. (Fibres 2011)
Biodiversity and habitat
Green roofs give new natural surroundings to gainful plants and creatures in urban zones,
serving to expand biodiversity. Expanded biodiversity can help environments continue to func-
tion even when they are aggravated by advancement in other ways. Green roofs, especially
escalated ones, can be planned to coordinate numerous living spaces and micro atmospheres,
hence giving suitable conditions to a mixture of plants and creatures to flourish. They can
likewise be intended to copy neighbourhood local natural surroundings, amplifying the range
accessible for local species to colonize. They can also reproduce early progression examples of
ground-level environments, which can permit increases in biodiversity over a longer period of
time (U.S. General Services Administration 2011).
5
Economic benefits
Economic benefits start with comparing the Costs versus Life-Cycle Costs. Despite the nu-
merous profits of green roofs, their constrained utilization is attributable to their higher first
expenses. Commonly, a regular rooftop costs 1012 every square foot. The starting expense
for a green rooftop can potentially cost twice that much. An existence cycle point of view,
nonetheless, uncovers the financial profits of green roofs. Since they protect materials against
ultraviolet radiation and compelling temperature variances as well as cut physical harm from
entertainment or support, the green rooftop delays the potential material degradation of the base
rooftop up to three times longer than a standard rooftop. (Arrowstreet 2009) As an illustration,
a London retail chain that introduced a rooftop layer under a planting in 1938 discovered the
film still in astounding condition after fifty years. In England’s downpour splashed atmosphere,
most traditional level rooftops have a normal lifespan of just 10-15 years (Velazquez 2005,
Macdonagh 2005).
Recovering waste
Green roofs have the ability to collect waste and convert it to valuable item. A Belgian
production line that produces biodegradable clothing items has two sections of land of local
grasses and wildflowers on its rooftop. The results of their assembling procedure are dealt with
in an on location sewage lake and afterward separated through the green rooftop, simultaneously
going about as watering system and a supplement hotspot for the plants (Macdonagh 2005).
Increased points in the LEED rating system
Green roofs can earn at least six points in three categories, and more points are possible under
specific conditions. It can score up to 15 points overall. (Larsen et al. 2011) (Velazquez 2005)
Emerging synergy with solar power
The fundamental standard of the solar garden roof is that it offers a completely coordinated
arrangement that weds photovoltaic panels with a broad green rooftop framework. In that capac-
ity, the sun-root module is exceptional not just in its capacity to join two developing economical
practices sun based and current green rooftop innovation but additionally in the way in which
every innovation complements the other. The living green rooftop layer supports the photo-
voltaic panels and expands their effectiveness, while the planted vegetative material is both
secured and inundated by the sun (Breuning, Tryba, and Miller 2013) (Garrison et al. 2012).
Noise and sound insulation Controlling clamour is an alternate motivation to pick green roofs.
Soil, plants, and the air layer caught between the green rooftop and the building surface give
6
sound protection. The substrate pieces lower frequencies, while the plants square higher fre-
quencies. This can mean a lessening in indoor sound levels of as much as 40 decibels, when
compared to a typical roof. This has the most potential benefit to individuals who live close
air terminals, major expressways, or different types of modern related clamor contamination.
Moreover, wind traveling through the stems and leaves on green roofs can give concealing
clamor or make an advantageous soundscape (Macdonough 2005) (Garrison et al. 2012). Fos-
tering a sense of community and making people happy
Prosperity is broadly recognized to be upgraded by green spaces and connection with na-
ture. As Frederick Law Olmsted put it, ”People have physiological responses to characteristic
excellence and differences, to the shapes and shades of nature, particularly to green, and to
the movements and resonances of different creatures.” (Harvard 2011) In urban settings, green
rooftop perspectives offer an appreciated relief from the urban material palette of rock, black-
top, and cement. Research in the US demonstrate that butterflies visit green roofs up to 20
stories high and fowls visit up to 19 stories high. To foster social connection, numerous green
rooftop are planned with seating regions arranged into conversational groupings, giving chances
to socialization and reclamation. At the Gap Headquarters in San Bruno, California, truancy
was diminished and benefits expanded within a year of introducing a green rooftop. A feeling
of community can likewise be cultivated through green rooftop arrangements (Velazquez 2005).
1.6 Technical Terms
1.6.1 Urban Heat Island
Urban heat islands occur when the air temperature in urban areas are much higher than the
surrounding rural areas. The pavements, roads, dark roofing materials absorb and trap heat
from the sun during the day and radiate it during the night. Due to this effect, temperatures are
even higher during the night. The annual mean air temperature difference between the urban
areas and surrounding rural areas ranges from 1.85.4F (13C). In the evening, the difference can
be as high as 22F (12C). The following figure shows the difference in temperature between the
urban and the surrounding areas (Figure 2).
1.6.2 Solar Reflectance Index (SRI)
The Solar Reflectance Index (SRI) is a measure of the roof’s ability to reject solar heat, as shown
by a small temperature rise. It is defined so that a standard black (reflectance 0.05, emittance
0.90) is 0 and a standard white (reflectance 0.80, emittance 0.90) is 100. For example, the
7
Figure 2: Temperature differences between the cities and the surrounding area due to the UHI
effect (Shickman 2011)
standard black has a temperature rise of 90 deg. F (50 deg. C) in full sun, and the standard
white has a temperature rise of 14.6 deg. F (8.1 deg. C). Once the maximum temperature rise
of a given material has been computed, the SRI can be computed by interpolating between the
values for white and black (Akbari et al. 1994) . Solar radiations and reflectance on a roof is
shown in the figure below (Figure 3).
Figure 3: Solar Reflectance.
1.6.3 Evapotranspiration
Evapotranspiration is the process in which water is lost to the atmosphere by two different
processes: evaporation and transpiration. Water from the soil is lost due to evaporation, and
water from leaves and stems is lost due to transpiration. The figure below explains the process
of evapotranspiration (Figure 4).
8
Figure 4: Process of Evapotranspiration.
1.6.4 Leaf Area Index (LAI)
Leaf Area Index (LAI) is the proportion of aggregate upper leaf surface of vegetation divided
by the surface area on which it is grown. LAI is a dimensionless quality, normally running from
0 for uncovered ground to 6 for a thick woodland.
1.6.5 Objectives
Federal and building rating organizations have begun to promote high performance and en-
ergy efficiency in buildings by adopting more stringent energy and environmental measures in
building standards and assessment categories. Further, communities demand innovative green
engineering technologies and designs that will enhance the environment, occupant health, and
quality of life. In recent years, there has been great interest in the potential of green roofs as
an alternative roofing option to reduce the energy consumed by individual buildings as well
as to mitigate large-scale scale urban environmental problems such as the heat island effect.
(EPA-RUHI,2010).
Rise in energy costs of a building give rise to increased need of green roofing systems.
Although green roofs have many advantages such as reducing UHI, improving air quality and
storm water runoff, the aim of this research is to study the effect of climate zone-based con-
9
struction parameters of green roofs. 1.8. Scope of work
The focus of the research was to first study the temperature and energy benefits of using
a green roof in terms of load reduction through calibration and computer simulation, then to
compare them to a base case roof with respect to chosen climate zones. Buildings with installed
green roofs were chosen in the different climate zones and the data collected over two weeks
were recorded. They were then modeled in the Design Builder modeling environment so that
the accuracy of the model could be checked by validating the computer simulated data.
With respect to the obtained field experiment data of such a model, the same roof model was
then used for the parametric simulation studies. In each simulation, one parameter of the green
roof was changed and its thermal performance was recorded with respect to the chosen climatic
zone. The parameters that were taken into consideration in the green roof were the following:
insulation, vegetation type and growing medium depth or soil depth. Each of these parameters
have their own variables. The thermal performance analysis is done taking into consideration
the roof of the building. These simulation exercises was carried out for different climate zones.
1.7 Chapter structure
Chapter One deals with the problems dealt with green roof, the hypothesis of this project, im-
portance of green roof, the importance of this research in terms of green roof, some terms
related to green roofs, followed by the objectives and scope of work. Chapter Two deals with
the literature and background study on green roofs in general, and also with studies about green
roofs pertaining to different climates of the world. Chapter Two also deals with understand-
ing the importance of green roofs and how well they perform in different climates, as well as
their performance in terms of heat exchange. It also discusses field studies done on the green
roofs in different climate zones and energy modeling/simulation studies done so far. Chapter
Three includes an overview of the energy modeling software that was being used for the study
and discusses the limitations of the model and also data collection. Chapter Four focuses on
methodology and gives a detailed explanation of different phases of the research used to obtain
the ultimate goal of the research. Chapter Five comprises of the results obtained from the cal-
ibration and validation study of modeled green roof assembly. The field data was compared to
the simulated data to determine the accuracy of the model. Chapter Six contains data analysis
and some conclusions resulting from the studies carried out on different green roof assemblies
with respect to different climate zones. The analyses all of the performance metrics and how
they are affected by the different test parameters with respect to the climate in detail is ex-
plained. This is followed by an overall conclusion and also a web-based decision support tool
10
that is accessible to the public is developed. Chapter Seven discusses the limitations of the study
and scope for future work.
11
2 Chapter 2: Background studies.
2.1 Introduction to Green Roofs
A green roof, or rooftop garden, is a vegetative layer grown on a rooftop. Green roofs provide
shade and remove heat from the air through evapotranspiration, reducing temperatures of the
roof surface and the surrounding air. On hot summer days, the surface temperature of a green
roof can be cooler than the air temperature, whereas the surface of a conventional rooftop can
be up to 90F (50C) warmer.( Liu, K. and B. Baskaran. 2003)
2.1.1 How do the Green Roofs Work?
It is vital to comprehend the working of a green roof to outline a superior and proficient green
rooftop. Higher temperatures in the earth prompt high surface temperature of rooftops and even
higher temperatures in buildings, which implies that the structures devour more vitality through
cooling to cool the building. Green roofs on structures work effectively in keeping the rooftops
cooler, by exchanging warmth through diverse layers of the rooftop gatherings. Every layer of
the green rooftop plays an imperative and diverse part in exchanging the warmth stream. Figure
below shows the diverse layers in a green roof (figure 5).
1. Foliage (plants or leaves) Vegetation
The vegetation performs a comparative capacity as a ”cool” rooftop by exchanging sun based
vitality to the environment. On a late spring day, leaf temperatures of any plant are normally
under 5 C (9 F) higher than the encompassing air temperature, making aggregate leaf scope
and rough plant tallness the main noteworthy outline criteria for cooling properties. Another
consideration is leaf maintenance. Numerous plants have an extra preference over cool rooftops
in that they lose their leaves in the winter, permitting the sun to warm the rooftop. Selecting
plants for most extreme warm profit is area-specific. ASHRAE 90.1-99, Energy Standard for
Buildings except Low-Rise Residential Structures, takes into account a decreased protection
in rooftop frameworks utilizing an intelligent cool rooftop in warm atmospheres. However, it
ought to be extended to incorporate vegetation in a more extensive territory of atmospheres.
This is most eccentric in light of the fact that it uses all systems for warmth control gave by na-
ture convection, dissemination, conduction, sun controlled reflectivity, radiative warmth spread,
warm mass. Plants can similarly utilize extra warmth directing methodology, for instance, by
defoliation in winter. (Wark and Wark 2003)
12
2. Stem Gap
The air caught between the foliage and the highest point of the planting medium gives re-
stricted conduction. The stem itself conducts a little amount of heat between the foliage and the
roots. A a result, the air temperature between the planting medium and the plants are much less
when compared to the air temperature above the plants (Wark and Wark 2003).
3. Medium
The warm mass of the planting medium assumes a noteworthy part in losing the effect of sur-
rounding temperature variances. This property can drastically influence heat exchange through
rooftop frameworks in atmospheres where the outside air temperature has a tendency to wa-
ver about the set indoor temperature. ASHRAE has been constantly enhancing its tables for
modifying R-values for high-mass dividers, yet construction standards still have a tendency to
utilize straight R-values as a result of the trouble in applying warm mass to particular cases.
With planting media, the circumstance is further muddled by the following occurrence: as the
dampness of a substance builds, their warm mass increases but their R-esteem diminishes. Wa-
ter maintenance is an alternate imperative parameter which can fluctuate with the sort and sum
of vegetation, medium organization, and atmosphere. Assimilation and stream rates are site-
related.
Furthermore, particularly in framework, estimations of water maintenance attributes must be
ascertained for individual cases. Planting medium profundity and organization should likewise
be suitable for the chosen vegetation. (Wark and Wark 2003)
4. Drain layer
The drain layer is the layer through which water flows to the drainage system of the building.
This layer lies between the planting medium and the roof membrane. The thickness of this
layer is 20mm but thicker mats can be provided which could perform as root barriers and act as
additional insulation (Wark and Wark 2003).
5. Insulation
Results from a study done on commercial structures in Northern California utilizing DOE-2
have been done. Furthermore, a restrictive rooftop warmth exchange model grown by Shade
Consulting demonstrate that an uninsulated green rooftop could lessen the building warm-
ing/cooling framework interest for most of the year by 30 percent more than an ordinary rooftop
with R-18 unbending protection without a radiation boundary (Wark and Wark 2003).
13
6. Membrane
A membrane layer is necessary in a green rooftop. Without one, a layer is subjected to
UV radiation, great warmth cycling, wind, downpour, and contamination (particularly when
ponding happens). With a legitimately composed green rooftop fusing a defensive layer, the
film is subjected to just a little measure of dampness. Since a green rooftop keeps the film
surface temperature much closer to the rooftop deck temperature, mechanical stretch inside the
film is colossally diminished. This helps keep up joint trustworthiness, adherence to the deck,
and diminishes water vapor exchange (Wark and Wark 2003).
7.Roof Deck The rooftop deck gives basic conduction yet can have critical mass. Making
sense of how to streamline every layer is just an issue of being more brilliant than the roof.
(Wark and Wark 2003). The figure below explains the difference in energy balance between
Figure 5: Vegetated roof heat flow (Wark 2010)
traditional roofs and green roof due to the lack of evaporative cooling (Figure 6).
2.1.2 Overview of Details and Construction of Green Roofs
The designing of a green roof requires a joint effort between designers, structural architects and
scene engineers. Green roofs add extra load the structure, subsequently the structural framework
ought to be outlined considering the extra weight of the green rooftop on the building. Live loads
14
Figure 6: Energy balance of two different roofing types (Velasco 2011) 2.1.2. Overview of
Details and Construction of Green Roofs.
that must be added to the figuring of the heap include the weights of vegetation, soil profundity
and base. The extra load on the structure by the green rooftop brings about a more prominent
expense. The weights of soil thickness, vegetation and soaked soil are significant. The weight
of the green roof components varies depending on material (Table 1).
Table 1: The weight of the green roof components
The construction of green rooftop is multidisciplinary. It includes designers, scene plan-
ners, mechanical specialists, structural architects, and foremen that tend to all the parts of green
rooftop. The tasks of projecting the cost, setting particular objectives, and arranging compo-
nents to a successful result requires coordination. A few states and cities like New York, Mary-
15
land, Chicago, Pennsylvania, Portland, Seattle, and Washington D.C in the U.S give motivating
forces and bring down the extremely practical charges (Protection, Programs, and Usepa 2012).
The expenditure on green rooftop development when contrasted with conventional rooftop de-
velopment assesses for the life cycle cost of building. The life cycle cost covers the purchase
price, installation cost, operating costs, maintenance and upgrade costs, and residual or salvage
value at the end of ownership or its useful life. (LEED 2009) The construction of green roofs
also involves thermal insulation, although the green roof itself acts as a thermal mass. Insulation
reduces the heat flow between the inside and outside of the building envelope. Insulation helps
in keeping the building warmer in the heating season, and cooler in the cooling season. This
helps in reducing the energy consumption in a building. Thermal insulation is mandatory by
building codes and varies with the climate zone they are located in. The most common thermal
insulation seen in the construction industry is the fiberglass batts and injected polyurethane.
Green roofs, especially in low rise buildings. can be an efficient design strategy because of
the heat transfer that occurs through the roof. The r-value of the green roof is directly dependent
upon the depth and amount of moisture in growing medium. The r-value is much higher in drier
soil and much lower than the wetter soil. The r-value in a green roof can never be constant,
since the factors like the moisture content of the growing medium constantly vary. The type of
vegetation and the location of the insulation also influence the thermal insulation of the green
roof.
2.2 Green roof systems
A green rooftop is a green space made by including layers of developing medium and plants
on top of a customary material framework. This ought not to be mistaken for the conventional
rooftop garden, where planting is carried out in unattached compartments and grower, and found
on an available rooftop patios or decks. Construction of a green roof involves taking into con-
sideration various parameters such as vegetation type, strength of the structure, maintenance,
irrigation system and cost. Based on all these parameters, green roofs have been mainly classi-
fied into three categories by the green roof association. The classifications are Intensive Green
Roof, Semi-Intensive and Extensive Green Roof.
2.2.1 Intensive green roof system
A green roof that can be described by its extensive variety of vegetation from herbaceous plants
to little trees. Escalated green roofs oblige proficient upkeep and propelled green roof watering
16
system frameworks. The developing medium profundity of a concentrated green roof is 6 inches
or more. Serious green roofs offer an extraordinary potential for biodiversity. This sort of green
roof framework underpins little gardens to full scale open parks. Plant choice and outlines
assume an imperative part in this green roof. Intensive green roofs require higher supplement
applications and centered support. The figure below is an example of intensive green roof
(Figure 7).
Figure 7: Chicago city hall Building with Intensive green roof (Chicago Department of Envi-
ronment, Mark Farina).
2.2.2 Semi intensive green roof system
A semi- intensive green roof system is portrayed by vegetation that ranges from little herbaceous
plants, ground covers, grasses and little bushes. This sort of green roof obliges moderate upkeep
and an intermittent watering system. A developing medium profundity for a semi-escalated
green rooftop is 6 to 12 inches. This framework has the capacity hold storm water with serious
framework, and gives more diverse biology. Aoncentrated framework obliges high support, and
the semi-serious green roof framework gives possibility to a formal greenhouse. The following
figure is an example of semi intensive green roof (Figure 8)
17
Figure 8: Carnegie Mellon Hamerschlag Hall with semi intensive green roof system (Carnegie
Mellon)
2.2.3 Extensive green roof system
An extensive green rooftop system is described by vegetation, running from sedums to little
grasses, herbs and blossoming herbaceous plants. This kind of system obliges little support and
no perpetual watering system framework. The developing medium profundity for vegetation in
a broad green rooftop framework is normally 6 inches or less. These frameworks are perfect for
low upkeep. The figure below is an example of extensive green roof (Figure 9).
18
Figure 9: Bronx County Courthouse with Extensive green roof. (New York Times)
Table 2: The below shows the different types of green roof systems and their characteristics.
(Table 2)
2.3 Sustainability codes and building rating systems
2.3.1 Leadership in Energy and Environmental Design (LEED)
Leadership in Energy and Environmental Design (LEED) is the green building rating system
which was developed by the United States Green Building Council (USGBC). The purpose
is to give a standard affirmation handle that registers structures developed with natural execu-
tion, effectiveness, and inhabitant well being and prosperity as essential objectives. Structures
have focuses towards differing levels of accreditation taking into account the arrangement of
19
classifications created by the USGBC. Green Roofs can contribute to LEED Certification. The
wide variety of benefits associated with green roofs is captured to varying degrees in the U.S.
Green Building Councils LEED rating system. While each green rooftop undertaking is in-
teresting, and the degree to which a green rooftop on any building can help procure credits
differs. This aid offers essential knowledge in augmenting the green roof outline to help attain
LEED-accreditation.
Sustainable Sites
SS Credit 5.1 Site Development Protect or Restore Habitat (1 point)
SS Credit 5.2 Site Development Maximize Open Space (1 point)
SS Credit 6.1 Storm Water Design: Quantity Control (1 point)
SS Credit 7.2 Heat Island Effect: Roof (1 point)
SS Credit 7.2 Heat Island Effect: Roof (1 point)
Water Efficiency
WE Credit 1 Water Efficient Landscaping (Potential: 2-4 Points)
Energy and Optimization
EA Prerequisite 2: Minimum Energy Performance (Required)
EA Credit 1 Optimize Energy Performance (Potential: Up to 19 Points)
Materials and Resources
MR Credit 3 Material Reuse (Potential: 1-2 Points)
MR Credit 4 Recycled Content (Potential: 1-2 Points)
MR Credit 5.1 Regional Material (Potential: 1-2 points)
Green Roof systems installed on 50% or more of the roof surface virtually guarantees 2
LEED points and can contribute an additional 7+ points toward LEED-certification, which al-
most 20% of the total needed for a project to be LEED-certified.
2.4 Lack of green roof design guidelines
2.4.1 Lack of industry standards and design guidelines and specifications:
Green roofs are now gaining popularity in the United States. This term has been criticized
as misleading by some GSA consultants (U.S. General Services Administration 2011). Green
roofs has various environmental qualities, green roofs could mean vegetated roofs, roofs with
garden made of recycled materials, reflected roofs, or even known has a sustainable roof. To
address the lack of knowledge regarding the green roofs, a standard guide is being developed
by green roof task group under the American Society for Testing and Materials (ASTM) Sub-
committee E06.71. This guide would include procedures for assessing green roofs and include
technical requirements as well as considerations for sustainable development. A number of or-
ganizations like the Canadian-based green roofs for healthy cities have developed green roof
training seminars to educate and encourage the clients and professionals in the field with con-
20
struction of green roofs.
2.4.2 Lack of qualified designers and contractors:
Green roof designing requires prior knowledge of the complex interactions and performance of
all its layers. Seminars on green roofs would help to educate the designers and clients. How-
ever, the practical skills and knowledge needed to install a green roof are not specialized. The
industry lacks guidelines for green roof installation especially in terms of energy performance
with respect to climate zones in which they are built.
2.5 Energy modeling of green roofs
Energy modeling of green roofs when compared to other energy modeling components is still
unexplored. Energy modeling for green roofs in early times used conventional roofs with cal-
culated Cumulative R-Value on buildings while running the simulations. This was due to the
lack of simulation engines which could not take into account the behavior of vegetation on a
roof of a building. This no longer holds true, since a number of simulation software is avail-
able in the market that can model a green roof. Some lack in certain areas, for example, only
a range of data could be used for a lot of data input. A number of literature papers include
references on research done so far with respect to thermal modeling of green roof using various
energy modeling programs. A Green Roof Model for Building Energy Simulation Programs,
consists of all the studies by Sailor in which he discusses the factors he took into account while
developing the algorithm for green roof (ecoroof) for EnergyPlus simulation engine. In this
green roof module, the energy modeler can explore various green roof design options which
includes growing media, thermal properties and depth, and vegetation characteristics such as
plant type, height and leaf area index. This model that he developed was tested successfully
using observations data that he collected from a monitored green roof in Florida. The following
figure (Figure 10) shows the results from his validation study. A preliminary set of parametric
tests has been conducted on prototypical 4000m office buildings in Chicago, IL and Houston,
TX. These tests focus on evaluating the role of growing media depth, irrigation, and vegetation
density (leaf area index) on both natural gas and electricity consumption. Building energy con-
sumption was found to vary significantly in response to variations in these parameters. Further,
this response depended significantly on building location (climate). Hence, it is evident that the
green roof simulation tool presented by him can serve a valuable role in making informed green
roof design decisions (D. J. Sailor 2008).
21
Figure 10: Green roof module predictions as compared to measured soil surface temperatures
for green roofs at the University of Central Florida test site. The figure panels represent two
weeks of hourly data within each of four seasons (D. J. Sailor 2008)
A Comprehensive Study of the Impact of Green Roofs on Building Energy Performance by
Issa Jaffal, Salah-Eddine Ouldboukhitine and Rafik Belarbi. The paper describes a green roof
model using TRNSYS software that was created. The impact of a green roof on the energy
performance on a single-family house with an area of 96 sq. m. was carried out. Simulations
were conducted for the house with conventional and with green roofs in a temperate French cli-
mate (La Rochelle). Mean and maximum indoor air temperature and heating, cooling, and total
energy demand were studied in three different climates (Athens, La Rochelle and Stockholm).
From the simulations, it was observed that by increasing the LAI, there was a reduction in the
summer indoor air temperature and the cooling demand but an increase in the heating demand.
The table below shows the effect of LAI in terms of energy and temperature (Table 3).
22
Table 3: Mean and maximum indoor air temperature and heating, cooling, and total energy.
Demand in La Rochelle for different LAI levels (Jaffal, Ouldboukhitine and Belarbi 2012)
Different insulation depth was evaluated by La Rochelle. It was observed that the green roof
reduced the mean and maximum indoor air temperature by 6.5 and 9.3 C, respectively, for the
uninsulated roof. However, the research shows that these reductions were both less than 1.0 C
in the case of the 30 cm insulated roof. There was reduction of 48 % in heating demand for
the uninsulated green roof. As the insulation level increased the impact of a green roof on the
cooling demand decreased. The table below shows the effect of insulation in terms of energy
and temperature (Table 4).
Table 4: Mean and maximum indoor air temperature and heating, cooling, and total energy for
different insulation levels (Jaffal, Ouldboukhitine and Belarbi 2012)
In study of green roofs conducted in Cairo, Egypt was to determine the effectiveness of
green roofs in reducing the energy consumption of a residential building. The study was mainly
focused on the impacts of properties of soil like growing media depth, thermal bulk properties
of soil, plant height, stomatal conductance and soil moisture conditions through irrigation. The
energy software used for this research was Design Builder. The study of the green roof was
compared against an uninsulated, traditional roof which was Egyptian code-compliant. Soil
conductivity followed by soil depth was seen to be the two parameters affecting the energy
savings of the building as shown in the figure below. It was observed that as soil conductivity
decreased or soil depth increased, the energy consumption increased (Figure 11).
23
Figure 11: Percentage of effectiveness achieved by each type of green-roof over the Traditional
and the Un-Isolated roofs in Cairo-Egypt (Kamel, et al. 2012)
2.6 Field experiments and case studies on the thermal performance of
green roofs across the globe
The study of green roof assessment on the environmental benets is itself a main research topic,
second only to research on the substrate and plant material. Green roof study assessment on the
environmental benets includes various factors like the assessment of energy-saving and cooling
effectiveness of a building, cost-benet analyses , and storm water management. Among these,
the largest number of studies is on energy saving and cooling effects on a building.
2.6.1 Energy saving
In relation to the studies of the energy-saving effectiveness of green roofs, in buildings the en-
ergy savings in air conditioning for cooling season and the reduction in usage of heater during
the heating season were studied. Due to the various climatic zones and different building ma-
terials in different parts of the world, the study of energy-saving effectiveness of a green roof
on buildings varied from one place to another (Santamouris 2012). Studies were done on the
energy saving and environmental performance of a green roof system which was installed in a
school building in Athens, Greece. The conclusion of the study of green roof on that building
showed signicant decrease in the usage of electricity during the cooling season for air- condi-
tioning by 6-19% for the entire building and by 12-87% for the top oor alone. However, it did
not provide any savings in heating. Another case study on the energy-saving of a green roof on a
24
commercial building in Athens, Greece, showed the reduction in consumption of electricity dur-
ing the cooling season by approximately 40%, by using the green roof. (Sfakianaki et al. 2009).
Studying were done the energy saving effectiveness of a green roof on the residential buildings
in Athens, Greece. The results of this case study showed that a green roof in the Mediterranean
climate provide limited insulation for most buildings. The study also showed that, a green roof
was able to effectively reduce the cooling load of a building by 11% for thermostatically con-
trolled buildings. There was also a temperature drop of approximately 0.6 C between the roof
surface and interior of a green roofed building, which improved the heat comfort in summer in
the ordinary buildings.
Studies on different levels of insulation of the roof slab resulted in the different cooling
effectiveness of the green roof (Theodosiou, 2003; Niachou et al., 2001). Analyzation was
performed on the energy-saving effectiveness of a green roof in a building varied with varying
U-values of the insulating material used in the construction of a green roof. The conclusion of
their studies was that as the degree of insulation of the roof slab decreased, the effectiveness
of the energy-saving after greening increased. Another case study by (Castleton, et al.,2013)on
green roof concluded that the largest energy saving effectiveness derived from roof greening,
was in that of an old buildings with poor insulation received the largest benet from a green roof.
The modern buildings, which are built with a high standard insulation layer, gained very little
benefits from the construction of a green roof. To study the energy-saving effectiveness, a green
roof energy balance model was formed with the help of Energy Plus software simulation(D. J.
Sailor 2008). The study showed that the efciency of energy of a green roof was related to the
location and characteristics of the green roof. Another case study that took place is Pennsylvania
on a one story green roofed building showed results that the energy consumption for cooling
the building was reduced by 75% when compared to a conventional roof building. Modeling
green roof analysis have shown researchers various results based on the location on type of
plants used in the green roof. There was a 17 percent of the cooling load for a hypothetical five-
story commercial building in Singapore which was covered with a turf roof. For a one-story
commercial building there was an over 10 percent reduction in Santa Barbara, California, and
12 percent for a one-story building in Portland, Oregon.
25
Figure 12: Comparison of interior of buildings with conventional (non-green) and green roofs
from a case study in Pennsylvania
2.6.2 Cooling
Cooling is one of the most direct indicators used to assess the energy-saving efciency of a green
roof. Different regions, planting type, plant materials, and substrate all affect the cooling ef-
fectiveness in a building with green roof (Wong, Tan, & Chen, 2007). Studies were done of
the temperature before and after implanting green roof of a Singapore building. The results
showed that the green roof signicantly reduced surface temperature, especially for the roof with
high plant coverage, this resulted in a maximum temperature difference of 18 degree C. Differ-
ent plants may also result in different levels of effectiveness. As the amount of the coverage
increased, the magnitude of the temperature change also increased. The study in Hong Kong
showed that the heat storage of the ordinary roof was higher by 75% than that of the green
roof. In a case study in India, the coverage of an extensive green roof was shown to reduce the
temperature on the roof surface by a maximum temperature difference of 38 degree C, and the
heat ow through the roof was reduced by 51-63%. The study on the thermal effectiveness of
green roofs in northern and central Italy also showed that a green roof could reduce the daily
heat loss through the roof (Tang & Yang, 2009). This study proposed that solar radiation, wind
speed and air temperature had an impact on reducing the internal surface temperature. With the
growth of the urban heat island phenomenon, many mitigations have been developed, including
the invention of cool roofs along with green roof.
Many comparisons between the green roof and cool roof have also been made (D’Orazio et
al.) The effectiveness of the green roof and other various types of cool roof with a high degree
of insulation near Ancona, Italy, was studied. The results showed that the installation of a green
26
roof in DOrazios case study could reduce the surface temperature in the cooling season and
stabilize the daily variation of temperature.
27
3 Chapter 3: Data collection and building energy software.
3.1 Data collection
Two climate zones in the United States were chosen to study the green roofs with respect to
climate. The chosen climate zones were climate zone 3, which is hot dry, and climate zone 4,
which is humid. Two places in the chosen two climate zones were selected, namely California
and Missouri. The reason for choosing two different climate zones was to study the factors
affecting the performance of the green roof based on the parameters involved in the construction
of the green roof. Temperatures at different levels of green roofs in the selected climate zones
were collected over a period of 4 to 15 days in both California and Missouri, using various
sensors and the data as recorded.
Figure 13: Represents the various climate zones
3.1.1 Selecting the site to place sensors
Selecting the building with green roof, for the research was based on the green roof type in the
two different climate zones. The characteristics of the green roof including plant type, depth
of the soil, and insulation, had to be similar in order to study and compare in the two climate
zones.
Site in California
The site chosen in California was the Burbank Water and Power Building. Burbank has a
Mediterranean climate. The building was two story, constructed in 2012.It is LEED Platinum
certified building.
28
Figure 14: Green roof on Burbank Water and Power Building (California).
Site in Missouri
The site chosen in Missouri was, Emerson Electric Company Hall at the Missouri University
of Science and Technology in Rolla, Missouri. The climate is humid subtropical, with 1227
mm average annual rainfall. As part of the roof renovation, a GAF Gardenscapes green roofing
system with an area of 3,245 sq. ft was installed in the year 2013.
Figure 15: Green roof on Emerson Electric Company Hall (Rolla)
3.1.2 Checking for errors in the sensors
The sensors used in collecting the data in Burbank were the HOBO. It was important to check
for the errors in the sensors before placing them to record data. Hence, all the HOBOs used
for recording the data were placed together, and the data was recorded every 10 minutes over
a period of 48 hours and then checked for errors. The graphs of the data showed uniform
temperature and humidity reading. The maximum temperature difference between the sensors
was .02 degree F, proving that the sensors could be used, since none of them showed errors and
the temperatures recorded by them were almost constant. The sensors used in collecting data in
Rolla were Thermocouples. The thermocouples were prepared by exposing an inch of wire at
one end, wrapping the two metals together, binding them with a blow torch, and then covering
the probe tip with plastic dip paint. Due to the large scale of the project and varying locations
29
of the probes, the lengths of thermocouple wire used vary from 25 to 235. In total, around
half a mile of thermocouple wire was used. The wide variety of lengths necessitated that the
measurements be calibrated so as to eliminate any inconsistencies in the temperature readings
resulting from the differences in wire lengths. To do this, the wires were left overnight while
a data logger recorded temperature data at 3-second intervals. A graph of this data showed the
thermocouples slowly approach a uniform temperature reading. Once this uniform reading was
reached, the small differences among each thermocouple were taken as offset values (Stuart
Baur 2013)
3.1.3 Placing of sensors and a data collection
Placing the sensors in Burbank, California
Firstly, the green roof in the Burbank was divided into two parts the vegetative and the non-
vegetative part. The non-vegetative part consisted of the glass decoration that was placed on the
roof. The sensors were placed at various levels of both the vegetative and non-vegetative part
of the green roofs. In the vegetative part of the roof the HOBOs were placed 2 feet above the
green roof surface, to capture ambient air temperature on the surface of the green roof, beneath
the soil at a depth of 4 inches and another HOBO was placed below the concrete surface from
inside of the building has shown in the figure below (Figure 16) . Another censor was placed at
the working level inside the building. The HOBOs used on the surface of the soil and green roof
were covered with aluminium papers to reduce the impact of solar radiations on the temperature
reading (Figure 17). The HOBO under the soil was placed in a plastic bag, with holes for the
air to pass. In the non-vegetative part of the green roof, HOBO was placed on top of the glass
Figure 16: Section of the green roof showing all the placements of sensors.
30
Figure 17: Represents the sensor placed to measure ambient temperature and humidity
Figure 18: Shows the sensors placed below the slab to measure the concrete temperature
decorations which was again covered with aluminium paper (Figure 19) for the same reasons as
mentioned above, below the glass decorations again placed in a plastic bag with holes for the air
to pass and to the concrete surface beneath the green roof area from inside of the building.The
sensors recorded the Temperature and Humidity over the next 15 days for every 30 minutes.
31
Figure 19: Shows the sensor placed on the glass material wrapped in aluminium paper
Placing the sensors in Rolla, Missouri
The experimental setup in Rolla consisted of three primary sources of data collection: The
thermocouples for temperature measurement, a heat flux sensor, and a weather station. Two
probes were placed at each levels of a green roof, 2 above the black roof, 4 beneath the green
roof soil, and 2 above the green roof. One probe was placed at the remaining locations: the
surface of the green roof, and on the underside of the concrete slab beneath, the green, roof
sections (Figure 20b). To capture the ambient air temperature 2 above each roof surface, three
identical stands were built out of pressure treated 2x4 and weighed down with either sandbags
or concrete blocks (Figure 20a ). To isolate the thermocouples from wind and solar radiation,
they were placed inside a double layer of plastic containers. The inner layer protects the ther-
mocouple from the wind whilst allowing some airflow through small openings. The larger outer
layer is spray painted white to so as to reduce the impact of solar radiation on the temperature
reading. (Stuart Baur 2013) For the temperature readings on the underside of the concrete roof
slab, the thermocouple probes were placed directly on the concrete. A 6 square piece of one
inch thick r-board was pressed up against the probe to isolate it from the temperature of the air
space below. The blocks and probes are affixed to the concrete with high-strength adhesive tape
(Figure 21). In the case of the green roof, a location was chosen where the vegetation cover
was an average representation of the whole roof. Thermocouple wires from each location were
run into a watertight box on the black section of the roof that held the data logging equipment.
(Stuart Baur, 2013)
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Figure 20: a&b Shows the sensors placed at different levels in the green roof.
Figure 21: Thermocouples affixed to the concrete sub-slab beneath each roof section.
3.2 Simulation model
After the collection of data from the green roof in both Burbank and Rolla, the next step was to
model the green roof on a building with the obtained data from the sensors.
3.3 Simulation engine and Graphic User Interface
Energy simulation software have what is known has graphic user interface (GUI) and a simu-
lation engine. The GUI is used to input files for simulations and also to display the simulation
results. There can be multiple GUI for one simulation engine. For this research, 3D graphical
design modeling software called Design Builder, with EnergyPlus has its simulation engine is
used.
33
Figure 22: Energy simulation engine and the GUI
3.4 Modeling a green roof in Design Builder with EnergyPlus engine
Lack of green roof design energy modeling tool lead Dr.David J. Sailor to develop a compu-
tational model of green roof which involved heat transfer process in them. In EnergyPlus the
user can specify the eco roof as the outer layer for the roof construction options. The user must
also specify other parameters involving the green roof construction which includes parameters
like soil moisture conditions (including irrigation) , plant height, growing media depth, plant
canopy density, thermal properties and stomatal conductance (ability to transpire moisture) (The
Encyclopedic Reference to EnergyPlus 2011). The green roof model takes into account the fol-
lowing:
Conduction of heat in the different layers of the soil.
Evapotranspiration from the plants and soil.
Convective heat transfer due to the plant canopy.
Radioactive exchange within the plant canopy, due to long and short wave of the sun.
3.4.1 Limitations of modeling a green in Design Builder
For the Conduction Transfer Function (CTF) algorithm to work, it requires to input specific
parameters with respect to the soil and plants. The parameters have specific ranges for the data
inputs beyond which, we cannot input the data. The ranges for the various parameter is shown
in table below (Table 5).
34
Table 5: Ranges of various parameters input for Ecoroof model (The encyclopedic reference to
EnergyPlus input and output 2011)
35
4 Chapter 4: Methodology
The research methodology consists of various phase, each phase dependent on the other and
followed in the order of green roof model validation, simulation and analysis as shown in the
flowchart below
Figure 23: Flowchart1describing the methodology
4.1 Green roof model validation
The research focuses on green roof modeling, a DOE2 model of three storey office building
(Figure 25) was considered. The roof of this building was modeled to be eco roof using the
design builder software. The eco roof was modeled accurately enough to match the real case
scenario.
This was done by modeling the roof assemblies on the DOE2 model from the data obtained
(as mentioned in chapter 3) from the buildings with green roof in both Burbank and Rolla. The
simulations are run to determine the performance of the green roof with the respect to climate
zones and construction type. The simulation results are then compared to the green roof data
that was collected. Changes were made to the model in terms of the parameters involved until a
benchmark of +/- 20% difference between the actual field data and simulated data was obtained.
36
Figure 24: DOE 2 three storey office building.
4.2 simulation
Simulation phase was that phase in which the DOE2 building was modeled with the green
roof from the field data collected. Once the accuracy of the model against the field data was
achieved by changing the parameters which were the LAI, soil depth and insulation, the model
was then used for various parametric simulation study, which means, the model was tested with
various varying parameters as mentioned above in the chosen two climate zones. The main
purpose of simulation running over various parameters was to study the impact of energy load
of a green roof on the building with respect to the climate zones they are located in and help
user understand the thermal performance of the green roof with varying parameters involved the
green roof. The simulation studies also helped in understanding the varying surface temperature
of a green roof with respect to varying parameters. There are various parameters on which the
performance the green roof can depend on they are orientation, insulation, climate, height of the
building, roof slope, soil depth, vegetation type, Irrigation, building function, drainage system,
thickness of drainage system etc. The figure below shows the parameters that were considered
simulation (Figure 25).
The four testing parameters was insulation, soil depth, vegetation type and climate type.
Since the efficiency of energy saving of a green roof varies depending on the composition pa-
rameters like the insulation, soil depth, and vegetation type and the climate zone they are built
in, these four parameters play a major role hence these three parameters have been chosen. The
table below shows following subset of variables of each parameters (Table 6).
37
Figure 25: Various parameters that would be used in this research is shown in the section of
green roof (Groundworks Sheffield)
4.2.1 Parameter 1: Insulation
In any kind of a roof an insulation layer is optional, the same holds true even in the case of
green roof. The Green roof itself acts like insulation, due to the soil layer and vegetation.
Insulation boards in a green roof provide extra protection as they are placed under the water
proofing member. The different subsets under the insulation that was be studied are: the green
roof without insulation and green roof with 4,6 ,8 thick insulation.
4.2.2 Parameter 2: Soil depth
Soil depth in a green roof varies based on the type of the green roof being constructed. Based
on the type of vegetation used for the green roof, they are classified into three categories of
green roof with varying soil depth, intensive, extensive and semi- intensive green roof. For the
construction of Intensive types of a green roof, the soil depth usually needs to be 12 inches or
deeper. Green roofs with soil depth 2 inches to 6 inches, lie under the category of Extensive
green roof type. Semi-Intensive green roof is one, where the soil depth lies between 6 inches to
12 inches.
The three sub parameters under soil depth for a green roof construction are green roofs with
38
Table 6: Subset for each parameters for a green roof simulation.
3 thick soil (extensive), 6 thick soil (semi-intensive), 12 thick soil (intensive). The following
figure explains the 3 classification of green roof based on the soil depth.
Figure 26: Different soil depth (Groundworks Sheffield)
4.2.3 Parameter 3: Vegetation type (based on the Leaf Area Index)
Types of plants used on the green roof vary with geographical location. Not all plants can
survive in varying climates of the United States. Soil depth in the green roof, depends on
the type of plants used. Plant type used on the green roof also has an effect on the thermal
performance of the roof. Plants have different leaf area Index (LAI), LAI is defined as the
amount of leaf area in a vegetation canopy per unit land area (Scurlock et al. 2001). LAI is
one of the most important parameter in green roof, since it affects the heat flux between the
plants and atmosphere. In other words, LAI provides solar shading on the roof surface. The sub
variables used for LAI are 1, 3, 5 . The figure below explains the LAI studied (Figure 27)
39
Figure 27: Various LAI in plants.
4.2.4 Parameter 4: Climate type
Two climate zones are selected to study the thermal performance of the green roof with respect
to various parameters. The climate zones chosen were climate zone 3 which is hot dry climate
zone and California was the state that was chosen in that climate zone, Burbank was the city
and the other climate zone was climate zone 4 which is humid, the state that was chosen under
this climate zone was Missouri and the city was Rolla. The table below shows the chosen two
climate zones and the climatic conditions (Table 7).
Table 7: Shows the chosen two climate zones and the climatic conditions of the chosen two
place.
40
4.3 Analysis
On completion of all the simulation, the energy loads on the building were calculated and ana-
lyzed. The hypothesis that impact of the efficiency of energy saving of a green roof depends on
various composition parameters and the climate zone they are located in is tested. A part from
that, the best combination of green roof parameters, with respect to the climate zone, to obtain a
maximum thermal efficiency of the green roof is studied. Once this is completed, guidelines for
designing a green roof to obtain the best thermal performance in the chosen two climate zones
is developed, which could be possible by studying all the chart in details.
41
5 Chapter 5: Data collection, calibration and validation.
With the help of the sensors temperature and weather files were collected in Rolla and Burbank
for over a period of 15 days. Temperatures at different levels of a green roof was collected has
mentioned in chapter 4.
5.1 Temperature data at Burbank.
The green roof at Burbank was be divided into two zones: the green roof area which was the
vegetative layer and the non-green roof area. As shown in the figure below (Figure 28). The
green roof area is that area in which the plants have been grown and the non-green roof area is
that part of the roof where the colored glass piece blue and green were used for the purpose of
decoration. The green roof consists of up to 90 % of the roof while the rest 10 % is by the non-
green roof area
Figure 28: The green and non- green roof area at the Burbank water plant building.
The temperatures at different levels of green roof were collected using HOBOs. Temper-
ature was collected over a period of 15 days from 10/1/2015 to10/15/2015, every 10 minutes
for 24 hours a day. The HOBOS were collected at the end of 15 days and the temperature at
different layers of the green roof was plotted. According to the graphs generated temperature
varied from each layer as expected in a green roof. The temperatures were collected by placing
the HOBOs at different layers of a green roof. The temperature recorded were the ambient
temperature, the temperature at top layer of the plant, temperature at 4 inches deep in the soil,
the temperature of the concrete from inside of the building and also the temperature from the
conditioned space. There are variations in temperature between different layers of the green
42
roof (Figure 29). The roof is also acting as insulation
Figure 29: Temperatures at different levels of the green roof.
Due to the green roof, the temperature at the surface of the roof is much cooler than com-
pared to the ambient temperature. This helps in reducing the transfer of heat from the outside
to the inside, keeping the temperature of the room much cooler during the day. At night the
temperature of the room is much higher, which in other words the temperature inside the space
is much warmer than the outside temperature. This in green roof is mostly caused due to the
time lag in the building.
5.1.1 The green roof measured data.
43
Table 8: Above represents the temperature at different layers of a green at an interval of 30
minutes for 24 hours.
The graph above represents the difference in temperature at different layers in the green
area of the roof. This gives us a clear understanding of heat transfer between each layer. The
maximum difference in temperature was seen between the ambient temperature and the top
layer of the soil. The difference in temperature could be because of the evapotranspiration by
the leaves and also due to the shade of the plant on the top surface of the soil. Furthermore the
temperature is reduce from top most layer of the soil to the temperature within the soil is could
be because of the moisture content in the soil and soil also acts has a very good insulation. The
temperature of the top surface of concrete is further decreased while the temperature of concrete
on the bottom surface is a little higher compared to the top surface this could be due to the return
air in the conditioned space. The temperature inside the building was seen to be constant since
44
the building is a conditioned space, where the temperature is almost always constant.
5.1.2 The non- green roof measured data.
The figure below represents the difference in temperature in the non-green area of the roof
(Figure 30).
Figure 30: Non green roof area plot
In this chart we can see that the heat is unevenly distributed.
45
Table 9: Above represents the temperature at different layers of a glass (which is used has a
part decoration in the green roof) the at an interval of 30 minutes for 24 hours.
The temperature in the top most layer of the concrete is higher than the outside ambient tem-
perature, while the temperature of inside surface of the concrete is much reduce considerably.
This could be because of the conditioned space of the building.
46
5.2 Temperature data at Rolla.
Unlike the green roof in Burbank, the green roof here consists of complete green roof area.
Thermocouples were used to record temperature at various layers of the green roof. Also, heat
transfer were studied in different kinds roof, namely; green roof, white roof and black roof.
The data was recorded for a very short period of time. (includes everything except heat flux
data)). The data spans roughly four days: from 9:00 AM on July 25, 2013 to 11:00 AM on July
29, 2013. There was one rain event during this time period, on the 26th. All of the days were
unusually cool for the end of July, which is typically the hottest time of the year.
5.2.1 Study of ambient temperature in the various roof type.
From the graph below we can know that the ambient air temperature recorded on the white roof
is consistently higher than that recorded on the green or black sections. (Figure 31)
The black and green roofs appear to closely follow each other. The outer white solar radia-
tion shield is designed to prevent solar radiation entering through the top and sides. It does not
protect from radiation that reflects off the white roof surface. As a result, extra radiation may
hit the probe from the bottom, skewing the temperature measurement.
47
Figure 31: Ambient temperature recorded by white, green and black roof
5.2.2 Study of surface temperature in the various roof type
. The graph below shows the surface temperatures on all three roof types appear to be as
expected. (Figure 32) The black section is the hottest, regularly peaking to almost 70 C. The
Figure 32: surface temperature recorded by white, green and black roof
green roof is consistently the coolest, and the white roof is slightly warmer. The data for the
sensors buried beneath the green roof soil medium reveals an interesting phenomenon. The
four inches of soil serves as a large thermal mass that evens out much of the temperature spikes
observed on the surface. Additionally, the soil appears to gain heat energy at a much slower
48
rate, and reaches its peak temperature several hours after the peak temperature is observed on
the surface.
5.2.3 Study of Concrete Temperature in the various roof type
. The below graph represents the comparative studies of the temperature difference beneath the
surface of concrete among the green roof, white roof and dark roof. (Figure 33)
Figure 33: Concrete surface temperature recorded by white, green and black roof
Graph 3: Concrete surface temperature recorded by white, green and black roof Temperature
measurements from 9:00 AM on 7/25/13 to 11:00 AM on 7/29/13. Note the large fluctuations
( 2.5 C) in the black roof sub slab temperature. The temperature of the concrete surface beneath
the green roof seems to be much higher when compared to the dark roof or white roof.
5.2.4 5.2.4. Study of Precipitation, Temperature, Solar Radiation, Humidity, Wind Speed.
The graphs below were the weather data from 9:00 AM on 7/25/13 to 11:00 AM on 7/29/13.
One rain event occurred during this period. Note the correlation between precipitation, solar
radiation, and the roof temperatures graphs below. (Figure 34)
49
Figure 34: Weather data
5.3 Calibration and validation of the model.
The green roof model was built in Design Builder with the exact same parameters that were
used in both Burbank and Rolla. The green roof in Design Builder was built by first choosing
a flat roof and then by adding each layer to the flat roof, green roof was modeled in Design
Builder. Once the green roof model was created the model had to be calibrated. For the purpose
of calibration measured hourly data was used. The hourly measured data in this case the tem-
perature at different layers of the green roof. According to ASHRAE Guidelines- Measurement
of energy and demand savings (Gillespie et al. 2002) the acceptable calibration for an hourly
collected data model has been declared when the model matches to +/- 20% of the measured
data. Based on this, ambient temperature, top surface temperature, inside surface temperature
of the space was taken into account.
5.3.1 Burbank validation
The chart below explain the Burbank green roof validation, wherein the temperature difference
between different layers of the roof between measured and simulated are well within the range
of +/- 20% . According to the model calibration the difference in percentage of temperature at
50
each different
layers of green roof are shown in Table 10 below
Table 10: Burbank validation
5.3.2 Rolla validation
The chart below is the result from validation of the green roof in Rolla. The temperature differ-
ence between the measured and simulated data are well within the scope of +/- 20% . It has been
observed that the temperature difference although is within the scope of +/-20%, the percentage
difference between the two is high when compared to that Burbank. The table below shows us
the difference in percentage between simulated and measured data
51
Table 11: indicates the percentage of difference between measured and simulated temperature
After the validation of the models for both Burbank and Rolla was completed and the difference
in percentage between measured and simulated temperature was found to be well within the +/-
20 %. The models were then used to run the simulations with various different green roof
parameters.
52
6 Chapter 6: Simulations with various parameters.
Once the models were validated the next step was to change the various parameters and run
simulations to check for the effect on green roof in terms of energy and temperature.
6.1 Simulations
Once the process of calibration was completed, the green roof of the model was varied based
on different parameter and simulated.
6.1.1 Parameters for Simulation
The parameters that were considered for simulation in both case of Burbank and Rolla were:
LEAF AREA INDEX 1, 3, 5
SOIL DEPTH- 3, 6, 12
INSULATION- 0, 4, 6, 8
A combination of the above three parameters were chosen for the simulations. A combina-
tion of 36 different roof type was tested. The roofs were named after the composition of the
parameters in the green roof. They were in the order of Leaf Area Index-Soil Depth- Insulation.
If a roof type was named 536, it contained the numbers of the parameters it was composed of.
For example, in case of roof 536, as seen in the figure below (Figure 35) 5 represented the leaf
area Index of the leave, 3 was the soil depth and 6 was the thickness of the insulation used.
Figure 35: Roof study model naming
The other factors considered for simulation was choosing of one hot day and cold day based
on the location. Studying the performance of the green roof in a hot day and a cold day gave a
53
better understanding of the performance of the roof than running the simulation for a year. So in
case of Burbank the Hottest day was considered has August 15, since in Burbank according the
weather station August was to be the hottest month and the coldest month being January. The 15
th of January was used to run simulation to study the performance of green roof on the coldest
day. In case of Rolla, to study the green roof performance in this climate zone the the hottest
day was July 15 th and the coldest was December 15 th was selected to run the simulations.
One other important factor that was considered to study the performance of the roof was, if
the green roof were being used for a passive design house or an active design house. Based on
the design criteria of the house, the factors considered in the deciding the suitable green roof
varied. For an Active Design House (HV AC) Total Load was considered a deciding factor and
for a passive design house with no HV AC or lighting average indoor surface temperature was
the deciding factor, which was mostly dependent on whether or not the houses were located in
the heating dominant or cooling dominant zones. The table below summarizes all the important
factors (Table 12) Once all the data was collected for the 36 different types of green roof based
Table 12: Important factors considered.
on the total load, surface temperature and the location in which the green roofs were located,
the best suitable green roof type pertaining to the climate zone was chosen for the guidelines .
54
6.2 Results and Conclusion
After simulating the green roof based on various parameters has mentioned above best 10 green
roof composition was chosen based on the climate zone and total load and temperature. The
graphs below shows the top 10 best composition for a green roof in Burbank based on the hot
day and cold day for active design house. (Figure 36 )
Figure 36: Best green roof composition in Burbank based on loads
The graph below shows 10 best composition for a green in Burbank based on the hot day
and cold day for a passive design house.((Figure 37 )
The process was repeated in the case of Rolla as mentioned above for Burbank.The graphs
below shows the top 10 best composition for a green roof in Rolla based on the hot day and cold
day for active design house. (Figure 38 )
The graph below shows the top 10 best composition for a green in Rolla based on the hot
day and cold day for a passive design house.(Figure 39 )
6.2.1 Simulation Results Analysis.
The best solution for a green roof with respect to the climate zone was chosen. The final sorting
out the best green roof composition were based on the following criteria
For an active design strategy house total cooling or heating load was considered De-
pending on Whether or not the green roof was located in Heating Dominant or cooling
55
Figure 37: Best green roof composition in Burbank based on temperature.
Dominant climate green roof for active strategy houses were chosen. In the case of Bur-
bank, it is located in the cooling dominant season hence the percentage of reduction in
total cooling load when compared to the base case model played a major role. At the same
time, in a heating dominant climate like Rolla the reduction in percentage with respect to
the heating load was taken in to account when in comparison to the base case model.
For a passive design strategy, the average indoor surface temperature was taken into con-
sideration. One would want the indoor surface temperature to be much lower when com-
pared to the outside surface temperature and outside air temperature in a cooling domi-
nant climate and higher average surface temperature when compared to outside surface
temperature and outside air temperature in a heating dominant climate.
Another factor that was considered during the selection of best green roof composition
was, whether or not the green roof composition performed as expected when in the future
56
Figure 38: Best green roof composition in Rolla based on loads.
Figure 39: Best green roof composition in Rolla based on temperature.
if they happened to change from passive system to active system in the buildings.
6.3 Results
6.3.1 Analysis for Burbank
Based on the above mentioned criteria the best green roof composition for Burbank were as
follows Green roof for an active system is shown in the table 12 below
The graph below shows us the annual load due to the green roof, when compared to the base
case building.(Figure 41 )
57
Table 13: Best options for Burbank for active system
Figure 40: Comparison in terms of load in Burbank.
According to this chart there was a reduction in 66% of the load by using B5126, B568,
B534 and B334, while reduction in load was 64% in B566 and 67% in B138 when compared to
the base case model. Green roof for a passive system is shown in the table 13 below
Table 14: Best options for Burbank for passive system
The graph below represents the reduction in temperature of the indoor surface temperature
when compared to the indoor surface of the base case model. (Figure ?? )
58
Figure 41: Comparison with respect to temperature in Burbank.
The chart above represents the reduction in temperature of the indoor surface temperature
when compared to the indoor surface of the base case model. There was a clear reduction of
up to 1 degree F of temperature in all the green roof composition chosen for the passive design
strategy
6.3.2 Analysis for Rolla
In the case of Rolla, the best green roof composition were as follows:
Green roof for an active system is shown in the table15 below
Table 15: Best active option for Rolla.
The graph below shows us the annual load due to the green roof, when compared to the base
case building when built in Rolla (Figure 42). According to this chart there was a reduction in
11% of the load by using B3124, 6% by using B360, while reduction in load was 4% by using
B1128 and B330, 2% by using B134.
59
Figure 42: Comparison in terms of load in Rolla.
Green roof for a passive system is shown in the table 15 below
Table 16: Best passive option for Rolla.
The graph below represents the reduction in temperature of the indoor surface temperature
when compared to the indoor surface of the base case model for a heating dominant climate
like Rolla in this case (Figure 43). The temperature was higher by almost 3 degree F when
compared to the base case model.
60
Figure 43: Comparison in terms of load in Rolla.
6.4 Conclusion
The impact of the efficiency of energy saving of a green roof depends on various composition
parameters of the green roof and it is also influenced by the climate zones they are built specifi-
cally. was investigated through this research. It effect of the parameters varied based on climate
zone. In a hot dry climate zone vegetation played an important role, this could be due to the
shading and also evapotranspiration of the plants. In hot humid climate the soil depth played an
important role since soil acts has insulation, the effect on the green roof was proportional based
on the increase in soil depth. Green roof was supported to have a bigger on reducing the cooling
loads of a building than on the heating load of a building. Hence they work better in a cooling
dominant climate than a heating dominant climate. It was also observed that in a hot dry climate
like Burbank the larger leaf area index impacted in reducing of the cooling load of the building,
while in case of Rolla the variation in the thickness of soil depth played an important role in
reducing the heating load when compared to the base case model. In terms of the indoor surface
temperature it was observed that the green roof in colder climate zones performed better than
that of the hotter climate zones, wherein the temperature of the indoor surface of the green roof
was increased up to 3 degree F during the heating season when compared to that of the base
case. Overall, green roof based on the composition and climate zone has an effective impact
on the buildings heating or cooling load. A part from contributing to the energy saving of the
building it has many benefits one can benefit from.
61
7 Chapter 7: Limitations and future work and conclusion
7.1 imitations
The limitations with respect to the green roof research involves, the lack of field data for vali-
dation in other climate zone. United States is divided into six main climate zones, but the scope
of the research was limited to two climate zones only. Studying the green roof performance in
other climate zones, would have given much better understanding of the thermal performance
of the green roof pertaining to that climate zones. Parameters like the solar radiation were not
considered by the energy plus software to calculate the surface temperature of the green roof.
It was considered only during the whole building energy simulation. For the research only four
parameters were considered and each parameter had a limit on the number of subset variables.
Various other parameters like orientation, humidity, solar radiation, plant type, other climate
zones, different types of roofing systems apart from the chosen four parameters could have
been tested
7.2 Future Work
Future work could involve considering various other parameters like types of roofing system
(sloped, flat, shaded, non-shaded etc.), different types of building, and also various other cli-
mate zones could be investigated. Not many simulation software can perform green roof energy
analysis, hence it would be interesting to study the comparison between the software with re-
spect to green roof energy performance for better understanding of software. Also, developing
new algorithms for the software without having limited number of subsets would be really use-
ful.
It would be very interesting to study the parameters affecting the air temperature at the
site when compared to the temperature from weather file. The air temperature at site could
vary based on the location, humidity, cloud coverage and the surrounding buildings. Also,
the vegetation has an effect on the site. To study the impact of these on the site would be a
very interesting thesis topic which could help people in calibration for validating a model since
the temperature difference from weather file and the air temperature collected on site could
sometime have large differences.One of the main reasons for Green roof to have not made it to
the top, despite of so many benefits is due to the cost benefits. It would be interesting to study
the cost analysis of green roof based on the composition in different climate zones.
62
7.3 Conclusion
Lack for prior knowledge about the parameters involved in the construction of green roof based
on climate zones led to failures in terms of thermal performance and efficiency in the past. Bet-
ter understanding of the construction and performance of the green roof based on the parameters
would only lead to efficient green roof design across the globe. Green Roofs have turned into
a critical segment of economical urban advancement in recent 30 years. Developing ecological
mindfulness and the striking practical and environmental focal points are the main forces for
this incredible achievement.
63
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67
APPENDIX A: Simulated Data with various roof composition
Figure 44: Present the simulated data for each roof type on a hot day In Burbank.
68
Figure 45: Present the simulated data for each roof type on a cold day In Burbank.
Figure 46: Present the best 10 green roof composition for Burbank.
Figure 47: Present the temperature and load of base case model for Burbank
69
Figure 48: Present the best 10 green roof composition for Burbank.

Abstract (if available)

Abstract In spite of many design and technical efforts to improve building performance using green roofs as building enclosure components, the critical uncertainty of existing mechanisms, such as pre-defined computational modeling and design guidelines, have frequently resulted in lower building performance efficiency than intended by the design. Examination of many actual green roof performance cases revealed an even larger energy usage and/or lower environmental performance of the building where implemented, than those of the adopted base cases. To address this challenge, this research will help develop a better understanding of the various components involved in the construction of a green roof like the soil, insulation leaf area index based on the climate zone they are located. Impact of each of the above mentioned component is studied in various climate zone. The parameter are varied for each component until the lowest energy is achieved from the Combination of leaf area index, insulation and soil by running the calibrated model simulation with the help of design builder. Based on integrated principles of design and building configurations, the green roof design strategies developed by this research can lead to effective green roof design decisions in an early stage of an individualized project,

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Creator Yogananda, Spurthy (author)

Core Title Green-roof design decision support: climate specific green roof design recommendations

School School of Architecture

Degree Master of Building Science

Degree Program Building Science

Publication Date 08/12/2017

Defense Date 05/01/2015

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag EUI,green roof,OAI-PMH Harvest,simulations

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