Climatic alignment of architectural design strategies through an analysis of native plants in southern California

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CLIMATIC ALIGNMENT OF ARCHITECTURAL DESIGN STRATEGIES

THROUGH AN ANALYSIS OF NATIVE PLANTS IN SOUTHERN CALIFORNIA

by

Andrew Lee

A Thesis Presented to the
FACULTY OF THE SCHOOL OF ARCHITECTURE
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF BUILDING SCIENCE

August 2008

Copyright 2008 Andrew Lee
ii
DEDICATION
This thesis is dedicated to the memory of Jade Satterthwaite, a knowledgeable and graceful advisor who
inspired me to explore the beauty of our native plant communities.

iii
ACKNOWLEDGEMENTS
I would like to thank the many people who guided and supported this work:
Thanks to my advisors Prof. Marc Schiler and Prof. Doug Noble for their wisdom and patience in guiding
me through my education in Building Science at USC.
Thanks to my parents, Catherine and Cliff, for their love, support, and encouragement to always finish what
I start.
Thanks to Brad Pease, Tom Paladino, and Paul Paladino of Paladino and Company for providing me the
time and tools I needed to succeed.
Thanks to Suzanne Alexander of the USC School of Architecture for her personal attention towards making
this thesis official.
Thanks to my friends Colbi Cannon, Mark Siwek, and Brenna McKay for their constructive criticism and
editing support.
And finally, my greatest gratitude and thanks to my mentor and friend, Thomas Spiegelhalter, for his
inspiring energy, challenging perspectives, and for leading me on the path to a rewarding and meaningful
career.
iv
TABLE OF CONTENTS
Dedication ii
Acknowledgements iii
List Of Tables v
List Of Figures vii
Abstract x
Chapter 1: Research Statement 1
1.1. Introduction 1
1.2. Arguments 5
1.3. Hypothesis 5
1.4. Research Methodology 5
Chapter 2: Selection Of Native Plants 7
2.1. Overview 7
2.2. Data Selection 7
2.3. Preliminary Review Of Data 8
2.4. Plant Selection Methodology 9
2.5. Narrowing The Sampling 9
2.6. Findings 9
2.7. Conclusions 12
Chapter 3: Native Plant Study 13
3.1. Overview 13
3.2. Physical Adaptations 14
3.3. Behavioral Adaptations 18
3.4. Parallels To Building Design 21
3.5. Selected Strategy 23
Chapter 4: Validation Of The Biological Strategy 24
4.1. Overview 24
4.2. Psychrometric Analysis 24
4.3. Ecotect Simulation 26
Chapter 5: Conclusions 40
Chapter 6: Future Work 41
Bibliography 43
Appendices 45
Appendix A: Gis Maps 45
Appendix B: Native Plants 50
Appendix C: Validation Model 54
v
LIST OF TABLES
Table 4.1. Fixed variables used in the comfort calculation. 28
Table 4.2. Summary of baseline model input variables. 29
Table 4.3. Ecotect model configurations. 31
Table 4.4. Cooling degree hours reduced in the four design models. 38
Table 4.5. Summary of cooling, heating, and total degree hours reduced in the four design models. 39
Table B-1. The adaptive traits of plants native to the Desert Scrub plant community. 51
Table C-1. Model geometry calculations – Baseline. 54
Table C-2. Model Geometry Calculations – Design A. 55
Table C-3. Model Geometry Calculations – Design B. 56
Table C-4. Model Geometry Calculations – Design C. 57
Table C-5. Model Geometry Calculations – Design D. 58
Table C-6. Night Ventilation Calculation – Design A (Maximum Capacity). 73
Table C-7. Night Ventilation Calculation – Design A (Adjusted Capacity). 74
Table C-8. Night Ventilation Calculation – Design B (Maximum Capacity). 75
Table C-9. Night Ventilation Calculation – Design B (Adjusted Capacity). 76
Table C-10. Night Ventilation Calculation – Design C (Maximum Capacity). 77
Table C-11. Night Ventilation Calculation – Design C (Adjusted Capacity). 78
Table C-12. Night Ventilation Calculation – Design D (Maximum Capacity). 79
Table C-13. Night Ventilation Calculation – Design D (Adjusted Capacity). 80
Table C-14. Discomfort Period – Baseline. 82
Table C-15. Peak Day Temperatures – Baseline. 83
Table C-16. Peak Day Heat Gain – Baseline. 84
Table C-17. Peak Day Heat Gain – Design A. 85
Table C-18. Peak Day Heat Gain – Design B. 86
Table C-19. Peak Day Heat Gain – Design C. 87
Table C-20. Peak Day Heat Gain – Design D. 88
vi
Table C-21. Discomfort Degree Hours – Baseline Model. 89
Table C-22. Discomfort Degree Hours – Design Model A (Thermal Mass). 90
Table C-23. Discomfort Degree Hours – Design Model A (Thermal Mass + Night Ventilation). 91
Table C-24. Discomfort Degree Hours – Design Model B (Thermal Mass). 92
Table C-25. Discomfort Degree Hours – Design Model B (Thermal Mass + Night Ventilation). 93
Table C-26. Discomfort Degree Hours – Design Model C (Thermal Mass). 94
Table C-27. Discomfort Degree Hours – Design Model C (Thermal Mass + Night Ventilation). 95
Table C-28. Discomfort Degree Hours – Design Model D (Thermal Mass). 96
Table C-29. Discomfort Degree Hours – Design Model D (Thermal Mass + Night Ventilation). 97

vii
LIST OF FIGURES
Fig. 1.1. Photo of rooftop wind scoops in Hyderabad, Pakistan (Behling & Behling, 2000) 1
Fig. 1.2. Resource renewal in plants, animals, and micro-organisms. Image courtesy of Solar Power
(Behling & Behling, 2000) 2
Fig. 1.3. Proposal for circular metabolisms in cities. Image courtesy of Cities for a Small Planet
(Rogers, 1998) 2
Fig. 1.4. The Urban Cactus, a high-rise tower design proposal by UCX Architects. (NK, 2006) 3
Fig. 1.5. Concept of related interface with environmental factors (top) and strategy to draw
comparisons (bottom). 4
Fig. 1.6. Methodology of the study. 5
Fig. 2.1. Aerial photography of reference site 7
Fig. 2.2. Maximum temperature of the 11 plant communities and the Los Angeles site (red). 10
Fig. 2.3. Minimum temperature of the 11 plant communities and the Los Angeles site (red). 10
Fig. 2.4. Annual solar insolation of the 11 plant communities and the reference site (red). 11
Fig. 2.5. Annual precipitation of the 11 plant communities and the reference site (red). 11
Fig. 2.6. Chart of weighted climate factor comparisons. 12
Fig. 3.1. Leafless exterior of the Beavertail Pricklypear. 14
Fig. 3.2. Layered exterior of the Mojave Yucca. 15
Fig. 3.3. Cylindrical form and ribbed exterior of Barrel Cactus. 15
Fig. 3.4. White spines of the Teddy Bear Cholla. 16
Fig. 3.5. Skin of the Desert Agave. 16
Fig. 3.6. Waxy stem of Ocotillo. 17
Fig. 3.7. Homeostatic feedback cycle (Jurd, 1997) 18
Fig. 3.8. Leaf growth of Ocotillo. 19
Fig. 4.1. Psychrometric chart for California Climate Zone 8 showing the passive benefit of utilizing
thermal mass with night purge ventilation. Chart from Weather Tool software. 25
Fig. 4.2. Distribution of annual temperatures in the baseline model. 30
Fig. 4.3. Design A mass configuration 32
Fig. 4.4. Design B mass configuration 32
viii
Fig. 4.5. Design C mass configuration 32
Fig. 4.6. Design D mass configuration 32
Fig. 4.7. Operable elements of the building enclosure 36
Fig. 4.8. Detail of operable air inlet on the south facade 36
Fig. A-1. Land cover distribution over the state of California. 45
Fig. A-2. Areas of agriculture and urban zones that were removed from the sampling. 45
Fig. A-3. Geographical distribution of maximum annual temperatures. 46
Fig. A-4. Geographical distribution of minimum annual temperatures. 46
Fig. A-5. Geographical distribution of average annual solar insolation. 47
Fig. A-6. Geographical distribution of average wind power density. 47
Fig. A-7. Geographical distribution of average annual precipitation. 48
Fig. A-8. Sampling boundary from latitude 33° N to 35° N. 49
Fig. A-9. Plant communities selected for microclimate analysis. White areas denote areas where
data was omitted. 49
Fig. B-1. Observations from the Coastal Sage Scrub plant community. 52
Fig. B-2. Observations from the Southern Oak Woodland plant community. 52
Fig. B-3. Phototropism as a response to environment. 53
Fig. B-4. Example of a nastic response in leaf petals. 53
Fig. C-1. Wall Section – Baseline. 59
Fig. C-2. Roof Section – Baseline. 60
Fig. C-3. Floor Section – Baseline. 61
Fig. C-4. Thermal Mass Roof Section – Design A. 62
Fig. C-5. Thermal Mass Wall Section – Design B. 63
Fig. C-6. Thermal Mass Floor Section – Design C. 64
Fig. C-7. Thermal Mass Wall Section – Design D. 65
Fig. C-8. Thermal Mass Roof Section – Design D. 66
Fig. C-9. Title 24-2001 Sample Wall Construction. 67
Fig. C-10. Title 24-2001 Sample Roof Construction. 67
ix
Fig. C-11. Title 24-2001 Sample Floor Construction. 68
Fig. C-12. Occupancy Schedule – Weekend 69
Fig. C-13. Occupancy Schedule – Weekday. 69
Fig. C-14. Comfort Calculation – Lower Limit. 70
Fig. C-15. Comfort Calculation – Upper Limit. 70
Fig. C-16. Heating Months Infiltration Schedule – Baseline Model. 71
Fig. C-17. Heating Months Infiltration Schedule – Design Models A, B, C & D. 71
Fig. C-18. Cooling Months Infiltration Schedule – Design Models A, B & C. 72
Fig. C-19. Cooling Months Infiltration Schedule – Design Model D. 72
Fig. C-20. Night Time Prevailing Winds – California Zone 8. 81
Fig. C-21. Fabric (Envelope) Gains – Baseline. 98
Fig. C-22. Ventilation Gains – Baseline. 98
Fig. C-23. Fabric (Envelope) Gains – Design A. 99
Fig. C-24. Ventilation Gains – Design A. 99
Fig. C-25. Fabric (Envelope) Gains – Design B. 100
Fig. C-26. Ventilation Gains – Design B. 100
Fig. C-27. Fabric (Envelope) Gains – Design C. 101
Fig. C-28. Ventilation Gains – Design C. 101
Fig. C-29. Fabric (Envelope) Gains – Design D. 102
Fig. C-30. Ventilation Gains – Design D. 102
x
ABSTRACT
This paper presents a method of distilling a climate-specific design approach from the adaptive qualities of
native plant communities. The method is demonstrated through the analysis of plants native to Southern
California and an application of a selected adaptation to the design of a simulated reference building on a
site in Los Angeles. Climate data was analyzed in GIS to select representative plant communities for the
reference site based on a comparison of microclimate conditions. The climate analysis concluded that the
Desert Scrub plant community was most applicable to the reference site. Field research was conducted to
catalog the physiological adaptations of prominent species in desert plant communities. The behavioral
adaptations of desert plants were studied in biological texts. CAM photosynthesis was the adaptive trait that
was applied to the reference building and analyzed through psychrometric study and energy simulation.
1
CHAPTER 1: RESEARCH STATEMENT
1.1. INTRODUCTION
1.1.1. BUILDINGS IN THEIR CLIMATE
Humans began as creatures that adapted to their environment. Throughout the evolution of human
civilizations, the variations in what is now referred to as “architecture” were principally dependent on the
materials and natural forces available on the site. Many early examples of vernacular architecture
demonstrated an instinctual design response to what resources were abundant, and how they could be used
to sustain human life at a basic level. The result of this necessity-
based approach to design was numerous and diverse forms that
reflected their immediate environment – physical expressions of
how man and climate were linked. Some of these historical
examples exist and function to this day, such as the dinstinctive
wind scoops that define the rooftops of Hyderabad, Pakistan (Fig.
1.1). In this example, a simple roof form is utilized to passively
capture prevailing winds and direct airflow through the occupied
spaces that would otherwise overheat. In this way, as with many
other historical vernacular examples, the form of the building very
“honesty” speaks of the resource being utilized, as well as its source.
In many ways this climatically-sensitive, locally-sourced approach to architectural design has faded
through generations of technological advancement. Cities originally limited by the boundaries of locally
available resources are now able to draw resources from further distances through advanced means of
transportation. This concept of “ecological footprint”, first proposed by William Reese in 1992, extends
into many aspects of the building industry. Economic and cultural influences have shifted practices
towards greater consistency of materials and construction techniques that are more universally
applied(Behling & Behling, 2000).
Fig. 1.1. Photo of rooftop wind
scoops in Hyderabad, Pakistan
(Behling & Behling, 2000)
2
Technological evolutions, while beneficial to growth of the built environment, have also resulted in a
growing trend to rely on external energy sources (typically from fossil fuels) rather than the natural
resources available on the site. Studies in recent years have attributed the increase in building energy use to
the effects of global warming, a result of the steadily increasing release of CO
2
to the atmosphere(Energy
Information Administration, 2001). Analyses of diminishing resources and indicators in the earth’s
biosphere (Gore, 2006) have shown that this consumption pattern cannot be sustained. In effect, buildings
have been designed with a trend towards the misalignment with climate.
1.1.2. TOWARDS NATURAL CYCLES
The natural world has provided ideal models of resource balance that have evolved over millions of years.
Native ecosystems are composed of an abundance of life forms that utilize local resources in a way that is
synergistically supportive of each other. In this way, nature has for millions of years demonstrated how
numerous complex systems can work together in
resource cycles that are continuously renewable.
These systems are founded on the basic principle
of climatic alignment, where resources from the
sun, water and earth combine to support life.
Architect Richard Rogers has suggested emulation
of natural relationships at the urban scale,
discussing city resource use as “metabolism”.
“Cities themselves must be viewed as ecological
systems and this attitude must inform our approach
to designing cities and managing their use of
resources.”
Richard Rogers(Rogers, 1998)
Rogers asserts that current consumption patterns,
which are largely linear, must move towards a
circular cycle where waste is recovered as resource.
Fig. 1.2. Resource renewal in plants, animals, and
micro-organisms. Image courtesy of Solar Power
(Behling & Behling, 2000)
Fig. 1.3. Proposal for circular metabolisms in
cities. Image courtesy of Cities for a Small Planet
(Rogers, 1998)
3
Another architect, William McDonough, has proposed this concept more directly as “waste equals food”.
In his book Cradle to Cradle, McDonough explores how a shift towards naturally inspired processes can
create materials that are infinitely recyclable and maintain their value from use to use(McDonough &
Braungart, 2002). The approach of mimicking nature has begun to overlap other fields where biological
research can lead to innovation. Janine Benyus, a natural sciences writer, has explored numerous examples
of hybrid biological research in her book entitled Biomimicry(Benyus, 2002). This seminal text on nature-
inspired design explores numerous examples of evolutionary traits in animals and plants that have been
applied to solutions in fields such as medicine, transportation, and product design.
The Biomimicry Guild, an organization co-founded by Benyus, has in recent years collaborated with the
Rocky Mountain Institute to build a tool to share the lessons learned from natural systems. Their joint
project – the Biomimicry Database – is an online tool in the early stages of development that attempts to
organize and catalogue how biological precedents can be applied across different disciplines(Biomimicry
Guild; Rocky Mountain Institute, 2005). Architectural applications of natural precedents are among the
many ideas presented. However, this tool is limited in its presentation of how or when these strategies
would be appropriate for application.
1.1.3. NATIVE PLANT PRECEDENTS
While numerous designers have studied natural forms, the execution of
biologically-inspired design is sometimes superficial. Living systems
have often inspired form, such as in the Urban Cactus project by UCX
Architects. However, the irony of this project, as in many bio-morphic
designs, is the context. This particular project – an emulation of the
form of a desert succulent plant – is located in Rotterdam, a city in the
Netherlands where no cactus would naturally be found. Thus, the basis
of this design, beyond its programmatical or aesthetic appeal, does not
appear to be founded in the performative relevance of this natural
precedent.
Fig. 1.4. The Urban Cactus, a
high-rise tower design proposal
by UCX Architects. (NK, 2006)
4
Historical vernacular buildings have demonstrated that the most successful passive structures are those that
are uniquely endemic to the site. In this same logic, the most comparable structures in nature are native
plants. In many ways native plants are very similar building. Plants, like buildings, are grounded to a
specific site. Both are subject to an identical range of natural forces and environmental conditions. In this
respect, both plant and building must utilize and respond to what is available on the site.
The key difference between plants and buildings is that plants are living organisms and buildings are not.
Plants that respond poorly to their environment may die, while buildings that are not designed properly may
simply create discomfort for the occupants. However, the occupants – which are living – may indeed die if
conditions are unsuitable for human survival. Architect Werner Lang summarizes this relationship, stating
“the fundamental aim of building is to protect people from external climate conditions, such as intensive
solar radiation, extreme temperatures, precipitation, and wind.”(Lang, 2001). Lang suggests that buildings
are an extension of an occupant’s life support system, like a second skin.
Through associations of living and constructed skins, building enclosure becomes conceptually significant
in the comparison of buildings and plants.
Building designers Hausladen et al have
suggested that the façade, or building
enclosure, is an “interface” between
interior and exterior conditions(Hausladen,
de Saldanha, Liedl, & Sager, 2005). This
concept associates each element of building
enclosure as a means of control for specific
environmental factors. Herein lies the
compelling link to plants; building
enclosure may be compared to plant
physiology through associated climate
resources. From this departure point,
meaningful contexts can be established for applying biological precedents to building design.
Fig. 1.5. Concept of related interface with environmental
factors (top) and strategy to draw comparisons (bottom).
5
1.2. ARGUMENTS
• Buildings designs have gradually misaligned with climate.
• Plants are evolutionary examples of climate adaptation that are relevant to architectural design.
1.3. HYPOTHESIS
Adaptive qualities observed in native plants can be applied as architectural design strategies to enhance
passive building performance.
1.4. RESEARCH METHODOLOGY
This master’s thesis presents a method of distilling a climate-specific architectural design approach from
the adaptive qualities of native plant communities. The context, and focus of this research, was to utilize
the knowledge gained from biological study to maximize the passive performance, or energy effectiveness,
of building enclosures within their climate.
This method is demonstrated through a three-part
analysis and application of biological principles.
The first portion of the research involved the
selection of a native plant community that was
most representative of a reference building site.
Recorded climate variables were compared between the reference site and areas of known native plant
distribution. Geographic Information System (GIS) software was used to assemble and compare the
microclimate profiles for each of the selected plant communities. From this analysis, a representative plant
community was selected based on the most comparable microclimate profile to the reference site.
The second portion of the study involved the observation and research into the adaptive traits of plants.
Prominent species within the selected plant community were targeted for field research. Physiological
traits that were found to be climatically advantageous were catalogued from selected field visits.
Biological texts were reviewed to catalogue the documented adaptive features that are characteristic of
desert plants. Upon review of the findings, an adaptive trait was selected for application as a comparable
architectural design strategy.
Fig. 1.6. Methodology of the study.
6
The third research phase was the architectural application and quantitative validation of the biologically-
inspired design strategy. Psychrometric analysis was conducted to initially assess the climatic relevance
and passive potential of the suggested design strategy. Further validation involved the application of the
design strategy to a theoretical building design on the reference site. Ecotect software was used to quantify
the passive performance benefit of applying the biologically inspired strategy when applied to a
conventionally constructed envelope.

7
CHAPTER 2: SELECTION OF NATIVE PLANTS
2.1. OVERVIEW
The reference site selected for this research was an open plot on the campus of the University of Southern
California, in the Los Angeles basin. This urban site is located approximately 10 miles inland from the
Pacific Ocean and 2.5 miles south-southwest of downtown Los Angeles (Fig. 2.1) at Latitude 34° 1’ N and
Longitude 118° 17’W.
The challenge in selecting this location, as with any other
urban site, is the identification of relevant native species.
The prevalence of native plants in urban environments is
typically diminished by development. Specifically in the
Los Angeles basin, impervious surfaces and irrigated
landscaping are more prevalent than undisturbed area.
In order to select a representative community of native
plants, a microclimate analysis was conducted for both the
reference site and the native plant communities present in
Southern California. This analysis was focused on defining
the conditions that must exist for specific native plant communities to thrive. In order to isolate these
relationships, each plant community was catalogued with a profile of climate factors and compared against
similar factors at the reference site.
2.2. DATA SELECTION
Geo-referenced information was selected based on data sets that were publicly available online for the State
of California. Primary online sources for this data included the California Spatial Information
Library(California Spatial Information Library, 2000), the California Fire and Resource Assessment
Program (California Department of Forestry and Fire Protection, 2002), the National Renewable Energy
Lab (National Renewable Energy Laboratory, 1992) and the PRISM Group at Oregon State
University(Daly, Gibson, Doggett, & Smith, 2004).
Fig. 2.1. Aerial photography of reference site
8
Land cover data published in 2002 by the California Department of Forestry and Fire Protection was used
to define the distribution of California native plant communities. This data set specifies 59 different land
cover types based on the California Wildlife Habitat Relationships (WHR) System. See Fig. A-1.
Areas that were known to include non-native species were removed from the land cover sampling. The
first land cover type omitted from the sampling was irrigated agriculture (AGR). This coverage was
concentrated in the California Central Valley, an area of heavy agriculture. Areas defined as urban (URB)
zones were omitted as well. This coverage was primarily concentrated in San Francisco Bay area,
Sacramento, the Los Angeles metropolitan area, and San Diego. See Fig. A-1.
Climate data used in the analysis included maximum annual temperature, minimum annual temperature,
average annual solar insolation, wind power density, and mean annual precipitation. See Fig. A-3 through
Fig. A-7. It is important to note that the climate variables considered in this analysis were limited to the
scope of the research question; selection was based on the site resources that directly affected the energy
use or metabolic balance of both buildings and plants. Thus, climate factors that were not directly related
to energy, such as soil type or hydrology, were not considered despite the known relationship to native
plant distribution.
2.3. PRELIMINARY REVIEW OF DATA
Preliminary review of the geographical climate data sets revealed several correlations between climate and
geography. Climate variations were clearly affected by topography, specifically in patterns of precipitation
and temperature. Higher rainfall and cooler temperatures were associated to higher elevations along the
Sierra Nevada and coastal mountain ranges. Conversely, lowlands – specifically to the east – had higher
temperatures and scarce rainfall. These conditions existed due to the “rain shadow” effect; ocean air blows
inland and forces the release moisture as relative humidity increases at higher elevations (Baker, 1984).
The distribution of native plant communities was also found to have a strong geographical relationship to
climate variances. Plant communities with tall and dense foliage existed in cool and moist conditions while
communities with low and sparse foliage were located in areas with hot and dry conditions. This result
supported the hypothesis that native plant distribution is clearly linked to specific microclimates.
9
2.4. PLANT SELECTION METHODOLOGY
Microclimates for each plant community were quantitatively profiled through an analysis of georeferenced
data sets in ArcGIS software. ArcGIS, a mapping software, was used to facilitate the analysis of climate
factors for natural areas outside of urban zones. In this analysis, layers containing individual land cover
types were mapped overtop climate data and used as a cropping boundary; this isolated the values specific
to each plant community. Once the resultant cropped layers were produced, the graph analysis feature in
ArcGIS was used to report an upper and lower quartile, median, and range of values for each climate
variable. Together, these values defined the microclimate profile for each plant community.
The Los Angeles site microclimate profile was defined by recording the specific site value from each
climate layer. This profile for the site was then compared against each of the plant community profiles to
determine which had the most similar microclimate conditions.
2.5. NARROWING THE SAMPLING
Of the 59 land cover types available, 10 were selected for detailed analysis based on prevalent distribution
within one degree latitude of the reference site (see Fig. A-8). The native habitat zones included: Annual
Grassland (AGS), Chamise-Redshank Chapparal (CRC), Coastal Scrub (CSC), Desert Scrub (DSC), Desert
Succulent Scrub (DSS), Joshua Tree (JST), Mixed Chapparal (MCH), Sagebrush (SGB), Sierran Mixed
Conifer (SMC), and Valley Oak Woodland (VOW). Land cover type Redwood (RDW) was also included
in the analysis for comparison to a sampling outside of the region.
2.6. FINDINGS
Average annual maximum and minimum temperatures at the reference site were found to be on the warmer
end of the scale, relative to the plant communities reviewed. Whereas the maximum temperature of the site
was comparable to the upper quartile of six plant communities with milder temperatures (Fig. 2.2), the
minimum temperature appeared to be more consistent with the two hottest plant communities: Desert Scrub
and Desert Succulent Shrub (Fig. 2.3). This revealed that the site is slightly warmer than the coastal plant
communities and yet not as warm as the extreme inland desert communities.
10

Fig. 2.2. Maximum temperature of the 11 plant communities and the Los Angeles site (red).

Fig. 2.3. Minimum temperature of the 11 plant communities and the Los Angeles site (red).

Site insolation levels at the site were found to be lower on the relative scale at 5.2 W/m
2
, comparable to the
lower quartile of the two Chapparal plant communities (Fig. 2.4).
11

Fig. 2.4. Annual solar insolation of the 11 plant communities and the reference site (red).
Site precipitation was found to be characteristically low compared to the plant communities. At 14 inches
per year, the site was comparable to the lower quartile of Sagebrush as well as the upper quartile of Desert
Scrub, Desert Succulent Scrub, and Joshua Tree (Fig. 2.5), which are characteristically dry communities.

Fig. 2.5. Annual precipitation of the 11 plant communities and the reference site (red).
12
Results of the climate factor comparisons were used to assign a weighting to each plant community based
on the strength of association. A weighting of 0.5 was assigned to each plant community in which the Los
Angeles climate value fell within the highest and lowest observed values. A weighting of 1 was assigned to
each plant community in which the Los
Angeles climate value fell within the upper
and lower quartile. The total of the
weighted comparisons (Fig. 2.6) revealed
that Desert Scrub (DSC) had the greatest
association to the Los Angeles site.
Conversely, the community with the lowest
association was Redwood (RDW); this was
the only plant community selected from
outside the sampling boundary.
2.7. CONCLUSIONS
Results from the microclimate analysis revealed two conclusions. First, plant community distribution was
found to clearly relate to distinct variations in climate conditions. For example, Desert Scrub, Desert
Succulent Shrub, and Joshua Tree plant communities all showed the consistently low moisture, high
insolation, and high temperatures that are expected in a desert setting. These findings supported the earlier
observation that plant distribution and climate conditions are inherently linked. Furthermore, this
supported the relevance of selecting a representative plant community – in this case Desert Scrub – based
on a comparison of climate factors.
Second, the findings confirmed the validity of sampling from plant communities within adjacent latitudes.
As expected, the Redwood community had the lowest association to the reference site due to the greatest
distance from its latitude. This finding also supported the effectiveness of this selection methodology to
quantitatively exclude plant communities that are clearly not comparable to the reference site.
Based on the conclusions, Desert Scrub was selected for further study of the adaptive traits of native plants.
Fig. 2.6. Chart of weighted climate factor comparisons.
13
CHAPTER 3: NATIVE PLANT STUDY
3.1. OVERVIEW
Prominent species of the Desert Scrub plant community were identified from narratives provided by the
California Department of Fish and Game (see Appendix B). Research of plants was conducted to identify
climate adaptive traits with potential application as energy efficiency strategies in buildings. Field
observation and literature review revealed key physiological and behavioral adaptations of plant species
that were perceived to be advantageous in a desert environment. Crassulacean Acid Metabolism (CAM)
photosynthesis was selected for further exploration as a desert plant adaptation with potential application as
a building design strategy.
Field Observations
The purpose of field observation was to collect first-hand information on the physiological traits of plants
in a desert environment. Field visits were conducted over a six month period within Southern California
Desert Scrub plant communities. Selected locations for plant observation included Topanga State Park,
Rancho Santa Ana Botanical Gardens, Santa Barbara Botanical Gardens, the Theodore Payne Foundation,
and Joshua Tree National Park. Collective observations and online research by graduate students of the
USC School of Landscape Architecture and department of Building Science was compiled into a catalog of
physiological traits for over 200 native plant species. A summary table of the adaptive traits identified for
Desert Scrub plants is provided in Table B-1.
Literature Review
The purpose of a literary review was to research the climatic and environmentally adaptive traits compiled
by third-party plant specialists. Biological, botanical, and ecological texts were reviewed to identify how
desert plants respond to harsh environmental conditions. Through this research, it was found that key
adaptive traits are organized under how desert plants either escape or tolerate drought conditions(Gibson,
1996). Principle findings were organized by physical adaptations and behavioral adaptations, respectively.
Form and surface conditions were discussed under physical adaptations, while metabolic and growth cycles
were explored under behavioral adaptations.
14
3.2. PHYSICAL ADAPTATIONS
3.2.1. FORM
Desert Scrub environments were generally observed to contain low clusters of shrub vegetation and small
trees. Plant species tended towards one of two forms: dense, bristly shrubs or clusters of thick succulents.
Reduced Leaves
Nearly all of the plant species observed in the Desert Scrub
community exhibited form adaptations related to leaf size and
prevalence. Small and simple leaf structure was most common to
woody shrubs. Examples include the clusters of pinnate rounded
leaves (1-1.5cm in size) in the Catclaw Acacia (Acacia greggii) as
well as the narrow petiole leaves (1-4cm in size) in the Wiggins
Croton (Croton wigginsii)(University of California, Berkeley,
2007). In cactus species (Opuntia genus), plant appendages were
limited to thin, needle-like spines; and in the Beavertail Pricklypear
(Opuntia basilaris), the plant exhibited a complete absence of
leaves or spines.
Small size or absence of leaves in desert plants has been attributed to an adaptive means to reduce the
metabolically active surfaces of a plant (Gibson, 1996). Leaves typically contain the light-absorbing
chloroplasts as well as the stomata (pores) that facilitate transpiration of moisture from the plant. By
reducing the surface area of leaves, water loss through transpiration is respectively limited. Plants that lack
leaves, such as cacti, instead use the less photosynthetically active surface of stems(Desert Plant Survival).
Stems of succulents contain much fewer stomata per area relative to leaves (Cactus Survival), which
reduces moisture loss through these surfaces.
Rounded forms
Succulent, or water-storing, species of the Desert Scrub commonly exhibited thick, rounded forms. These
formal characteristics were particularly evident in examples such as the rounded stem structure of the
Fig. 3.1. Leafless exterior of the
Beavertail Pricklypear.
15
Branched Pencil Cholla (Opuntia ramosissima) or the cylindrical structure (Fig. 3.3) of the Barrel Cactus
(Ferocactus cylindraceus).
Rounded forms in succulent plants have been attributed to an
efficient means of water storage. Rounded forms naturally provide
the greatest volume per surface area. Thus, rounded forms reduce
the surface area that is exposed to direct solar gain or air movement.
By minimizing this exposure, plants effectively limit the attributed
evaporative losses and overheating of the stem (Cactus Survival).
Protected Structures
As a reflection of a resource competitive environment, numerous
Desert Scrub varietals exhibited adaptive means of protection from
both animals and natural elements. Examples most evident in the
desert landscape included the spine-covered forms of the Teddy
Bear Cholla (Cylindropuntia bigelovii) or the dagger-like leaves that
layer the stalk (Fig. 3.2) of the Mojave Yucca (Yucca schidigera).
While these sharp elements create a treacherous barrier to animals
foraging for water, botanists have suggested that these elements also
serve as critical protection from the harsh desert sun. Layers of
spines or leaves self-shade the central stem of the plants, as well as
trap a layer of cool, moist air near the surface (Cactus Survival).
Similar self-shading characteristics were observed in the structure of
plants, such as vertical ribs (Fig. 3.3) that characterize the Barrel Cactus (Ferocactus cylindraceus). In this
cactus, a folded enclosure structure allows the core to swell and retract with the availability of water
resources. When the stored volume of water is drawn down and the inner core shrinks, the ribs become
more pronounced as vertical shading devices. Moist air that is kept cool from shade and shielded by the
ridges is held near the surface. Here again, the adaptive elements reduce surface temperatures and
minimize evapotranspiration losses through the plant skin.
Fig. 3.3. Cylindrical form and
ribbed exterior of Barrel Cactus.
Fig. 3.2. Layered exterior of the
Mojave Yucca.
16
3.2.2. SURFACE CHARACTERISTICS
Light Color
Light color was a characteristic most commonly observed in plant species of the Desert Scrub plant
community. Numerous woody shrubs exhibited white or grayish-green color in the surface of leaves.
Several species such as Littleleaf Ratany (Krameria erecta) and
Palmers Coldenia (Tiquilia palmeri) exhibited a white that color was
attributed to small hairs over the surface of leaves. In other shrubs,
such as the White Bursage (Ambrosia dumosa) or Rabbit
Rubberbrush (Chrysothamnus nauseosus), a white color was most
evident in the stem. Light color was prevalent in succulents as well,
exhibited in the dense coat of white spines (Fig. 3.4) that covered the
Teddy Bear Cholla (Cylindropuntia bigelovii) or the light purple
skin of the Beavertail Pricklypear (Opuntia basilaris).
Botanists have suggested that light color in desert plants is a simple adaptive means of reflecting sunlight
(Dalhousie University). A reflective surface minimizes the damaging effects of heat absorption attributed
to direct solar exposure. Small hairs, called trichomes, create this same reflective quality on an external
layer with the additional benefit of lessening air movement across the surface. Accordingly, trichomes
retain moisture at the surface and minimize the evaporative losses through the stomata (pores) of leaves and
stems (Lack & Evans, 2001).
Fleshy Skin
Skin characteristics of cacti and agave represented some of the most
physiologically unique traits observed in desert plants. Fleshy skin
was found to be typical to many succulent species, such as that
which coated the thick, smooth leaves (Fig. 3.5) of the Desert Agave
(Agave desertii). Accordingly, biologists have documented how the
adaptive qualities of this type of skin structure facilitate water
Fig. 3.4. White spines of the
Teddy Bear Cholla.
Fig. 3.5. Skin of the Desert Agave.
st
st
th
th
pa
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Se
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ob
th
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Fi
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mitt, 1997). Cre
Thus, this wax
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17
er
ve to
s limit
h
eosote
xy
af
n

18
3.3. BEHAVIORAL ADAPTATIONS
3.3.1. RESPONSE PATTERNS
Homeostasis
Homeostasis is a term that describes the
process by which living organisms respond
to their environment. The key concept
behind homeostasis is the continuous and
dynamic regulation of conditions around a
set-point. This process requires a sensor to
detect a variance, an interpreter to compare
against the set-point, and an effector to
correct the condition (Fig. 3.7). These elements are the foundation of behavioral adaptations that are
inherent to the survival of desert plants. In these plants, homeostatic responses occur through the
adjustment of structure, growth patterns, and metabolism (Gibson, 1996).
Nastic Responses
Plant responses to a unilateral stimulus, particularly through movement, are known as nastic responses
(Lack & Evans, 2001). In desert plants, nastic responses are most often triggered by high temperatures
(thermonasty), scarcity of water, or diurnal cycles (nyctinasty). Specific examples of these nastic responses
include leaves turning on edge, rolling up, or folding to reduce surface exposure to direct sunlight. These
responses are common to shrubs of the Desert Scrub community, such as the vertical orientation of Jojoba
(Simmondsia chinensis) leaves to reduce exposure during the hotter hours of mid-day.

Fig. 3.7. Homeostatic feedback cycle (Jurd, 1997)
3.
P
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fo
th
te
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ad
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.3.2. GROWTH
erennials
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orm and metab
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emperature and
rowth or dorma
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Annuals
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H PATTERNS
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year by respond
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Plant Survival)
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.
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es (Dimmitt, 19
Fig. 3.8. Leaf gr
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rowth of Ocotill
19
By
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20
3.3.3. METABOLIC CYCLES
C4 Photosynthesis
Some desert plants have adapted to conditions of high light intensity and high temperatures by utilizing an
alternative metabolic cycle called C4 photosynthesis. This altered chemical process utilizes a 4-carbon
acid (oxaloacetate) to concentrate CO
2
that is delivered to the carbon-fixing enzyme (rubisco). This
process improves photosynthetic efficiency by 30% or more, and drops day time respiration to almost
undetectable levels(Lack & Evans, 2001). While not as prevalent as other types of photosynthesis, C4 is
attributed to several summer annuals that are native to the desert environment.
CAM Photosynthesis
A third variation of photosynthesis utilizes an adjustment of the respiration cycle to minimize moisture
loss. This metabolic cycle, known as Crassulacean Acid Metabolism (CAM), involves an adjustment of
stomatal action to exchange CO
2
at night when temperatures are cooler and relative humidity is
higher(Lack & Evans, 2001). Absorbed CO
2
is converted to a malic acid for short-term storage within the
cell structure rather than being processed directly. The stored acid is later processed during the day when
sunlight is available to initiate the Calvin Cycle. While this process is less efficient in energy
conversion(Lack & Evans, 2001), it allows a delayed photosynthetic cycle that is aligned to the diurnal
temperature swing of the desert.
This adaptive cycle requires plants to nearly eliminate day time transpiration through the surface.
Accordingly, this type of photosynthesis is most common to plants with thick, fleshy, and highly sealed
skins, such as those of Opuntia, Agave, Yucca, and other succulent species(Lack & Evans, 2001).
21
3.4. PARALLELS TO BUILDING DESIGN
Findings from the native plant research revealed the collective ability of desert plants to avoid and tolerate
drought. In order to sustain these conditions, plant enclosures were found to be principally adaptive in the
control of light exposure, temperature, and air exchange. These control measures in plant enclosure were
reviewed against building enclosure in order to establish a framework for comparison. Drawing from the
same climate resource parallels used to link building sites and plant communities, the three elements of
light, temperature, and air were utilized to organize relationships.
Comparisons between building and plant enclosure prompted a revisit of the enclosure as “interface”
concept proposed by Hausladen et al (2005). In this model, building enclosure parameters were shown to
be specified in order to control the interior environment. These assumptions were based on the required
conditions to sustain the comfort and well-being of human occupants. Alternatively, plants were found to
set enclosure parameters based on metabolic processes to sustain growth and reproduction. These two
variations of purpose revealed both challenges and opportunities in comparing environmental control
through enclosure.
Light
In general, plant adaptations to control light exposure were found to mitigate overheating from solar gain.
These traits exhibited clear relationships to building measures that control direct solar exposure. However,
the properties of glazing were identified to be particularly problematic in comparisons to plants. As a
transparent element, glazing permits the transfer of direct solar radiation to the interior space. In certain
climates and seasons, this property is advantageous to passively heat interior surfaces and enhance thermal
comfort. Further, buildings are designed to permit light transfer through the enclosure in order to provide
occupants with visible light for activity and visual connection to the exterior environment. However, plants
lack the metabolic requirement or physiology to transmit solar radiation to the interior. Instead, plants
absorb sunlight at the exterior skin or surface of leaves, where the chemical processes of photosynthesis
occur. In this respect, no comparable controls for transparent elements were identified in plant enclosure.

22
Aside from the issues identified with interior solar exposure, plant enclosures revealed several comparable
elements for exterior solar control. Incoming solar radiation was controlled through protective elements
(spines, leaves) that shaded to the skin or stem of plants, similar to external shading devices on buildings.
Form efficiency was identified as a plant adaptation to reduce the surface area exposed to sunlight. This
had clear relationship to appropriate building massing to limit external wall exposure. Reflective surface
characteristics of leaves and stems further limited the affects of absorbed solar gain, similar to how
reflective roofing and shading elements limit exterior surface heat buildup in buildings.
Temperature
Temperature control in plants was chiefly exhibited through the skin. Thick cuticle layers of succulent
plants were found to provide effective air sealing from the high temperatures of the desert climate. These
characteristics were found to relate to building air sealing techniques and massive materials with thermal
lag. Numerous other properties of desert plant enclosures were found to create pockets of air or self-shaded
layers that significantly dropped surface temperatures. These elements controlled conductive heat transfer
through the plant skin, similar to ventilated enclosure structures applied to the exterior of buildings.
Air
The climate adaptive processes of CAM photosynthesis established another compelling link to buildings in
terms of air control. This specialized metabolic cycle in desert plants limited stomatal activity to night
hours when air temperatures were lower. This limited moisture loss from plants that would otherwise result
from the exchange of hotter air during the day. Similarly, passive building ventilation aligned to diurnal
temperature swings is a comparable strategy that could yield significant efficiencies in temperature control.

23
3.5. SELECTED STRATEGY
Of the numerous traits identified in the Desert Scrub community, Crassulacean Acid Metabolism (CAM)
photosynthesis was selected for further study as an applied building design strategy. This adaptive trait was
selected for its synergistic link between physical and behavioral adaptations, as well as its relationship to
readily quantifiable architectural design strategies.
CAM photosynthesis requires a targeted night-time exchange of CO
2
supported by an elimination of
daytime transpiration through the surface. In buildings, this relates to a tightly sealed enclosure that is
designed with the option for passive ventilation. These criteria suggest an enclosure system with reduced
thermal bridges and air leakage, combined with operable façade elements. Further, the building ventilation
strategy should reflect a targeted approach to take advantage of diurnal temperature swing.
CAM photosynthesis also requires the plant to limit overheating. As observed, desert plants limit
overheating through optimized form, reduction of metabolically active surfaces, reflective surfaces, and
self-shading exterior elements. This suggests architectural design strategies such as massing to reduce
surface area and optimized solar orientation. At the building enclosure, window to wall ratios should be
balanced with the requirement for daylight, supported by exterior shading to minimize direct solar gain.
Finally, CAM photosynthesis requires the plant to have a cell structure that supports the storage of a malic
acid. When portrayed as the storage of an energy source, this suggests a building enclosure system with
thermal capacity. Enclosure materials that satisfy this criterion include those that are thick and massive,
such as masonry or concrete.
Together, these traits gleaned from CAM photosynthesis were composed into a combined design strategy
for passive night ventilation combined with thermal mass.

24
CHAPTER 4: VALIDATION OF THE BIOLOGICAL STRATEGY
4.1. OVERVIEW
Two studies were used to evaluate the passive cooling benefit of applying building design strategies
comparable to CAM photosynthesis. First, a psychrometric analysis was conducted for the selected climate
to gauge the potential to capture additional cooling hours through the use of thermal mass and night
ventilation. Second, an energy simulation model was tested with and without these passive design
strategies, using conventional construction as a baseline for comparison. It was hypothesized that these
studies would demonstrate a clear passive cooling benefit of utilizing CAM photosynthesis in the climate.
4.2. PSYCHROMETRIC ANALYSIS
The psychrometric analysis of utilizing thermal mass with night ventilation at the Los Angeles site was
conducted using the Weather Tool software by Square One Research (www.squ1.com). Hourly climate
data for California Climate Zone 8 was imported from an EPV weather file downloaded from the
EnergyPlus website (U.S. Department of Energy, 2006) rather than using the default data for Los Angeles
that is based on measurements from LAX airport, a coastal location. Activity levels were assumed to be
sedentary, reflecting a living and working space with light activity.
4.2.1. CLIMATE ZONE ANALYSIS
Analysis of the Climate Zone 8 weather data revealed that a significant number of hours were outside of the
comfort zone, as shown in Fig. 4.1. Surprisingly, the majority of these hours were shown as heating hours,
where outside temperatures are too cool for most occupants. When combined with cooling hours, it was
found that approximately 12% of the yearly hours are perceived to be comfortable.

25
4.2.2. PASSIVE STRATEGY ANALYSIS
The effects of thermal mass with night purge ventilation were overlaid on the psychrometric chart to reveal
a significant expansion of the comfort hours. Thermal mass was found to increase the perceived comfort to
45% of the year, capturing hours in both heating and cooling conditions (Fig. 4.1). Night purge ventilation
captured an additional 2% of yearly hours, specifically during cooling conditions. In comparison to this
combined strategy, the potential increase in yearly comfort hours for other passive strategies was found to
be 22% of hours for indirect evaporative cooling, 21% for natural ventilation, and 16% for direct
evaporative cooling. These results supported the hypothesis that the combined strategy of thermal mass
and night ventilation was an appropriate selection for the Los Angeles climate.

Fig. 4.1. Psychrometric chart for California Climate Zone 8 showing the passive benefit of
utilizing thermal mass with night purge ventilation. Chart from Weather Tool software.
26
4.3. ECOTECT SIMULATION
Ecotect software was used to quantitatively evaluate the passive effects of emulating CAM photosynthesis
by simulating as the use of thermal mass with nigh ventilation. This analysis differed from the
psychrometric study in that the application of the passive strategy was compared against a baseline building
of conventional construction. In doing so, the purpose of this evaluation was twofold; first, to assess the
baseline climatic “alignment” of a typical new building in Los Angeles, and second, to reveal the passive
cooling benefit of utilizing the biologically inspired design strategy. To isolate these comparisons, only the
passive performance of the structure was evaluated; no active systems were considered in the model.
4.3.1. BASELINE MODEL INPUTS
Site and Climate
The site chosen for the simulation was downtown Los Angeles, on the campus of the University of
Southern California. Climate data for California Climate Zone 8 was imported from hourly data
downloaded the EnergyPlus Weather Data website.
Geometry
The building model used for this study was based on a Solar Prototype Building designed by undergraduate
and graduate students of the University of Southern California School of Architecture between spring 2003
and fall 2006. This hypothetical building was selected as the reference model for this study due to parallel
research into its development as a zero net energy building in the Los Angeles climate.
The program for this project was a 1400 square foot structure for two living and working adults that must
maintain comfort with a minimum of active systems and energy use. The form of the building was a two-
story low-rise structure with a vertical wall on the north and a continuously curved roof that meets a glazed
southern façade with exterior shading. East and west walls were vertical projections off of the rectangular
footprint. This geometry was used for both baseline and design models for the Ecotect simulation. For full
specifications of model geometry, see Table C-1 through Table C-5.
27
Materials
The baseline model used for the analysis was configured with a construction based on the minimal
performance standards of Title 24-2001, per the Package D prescriptive envelope requirements for a
residential structure (California Energy Commission, 2001). Wall, roof, and floor sections were based on
sample light wood construction assemblies provided in Appendix H of the Title 24-2001 Residential
Manual.
The baseline wall configuration was a stucco-faced 2x4 wood frame filled with 3 ½” R-13 batt insulation
and gypsum board interior. The baseline roof configuration was an asphalt shingle coated 2x10 wood
frame filled with 8½” R-30 batt insulation and a gypsum board interior. The baseline floor configuration
was a vented 2x8 wood frame filled with 6 1/4” R-19 batt insulation under a plywood floor. For sections of
each construction, see Fig. C-1 through Fig. C-3. For sample sections that were referenced from the Title 24-
2001 Residential Package, see Fig. C-9 through Fig. C-11.
Occupancy and Internal Gains
Internal gains were specified for two adults with three different activity levels of sleep at MET 0.7 (40W),
seated activity at MET 1.0 (60W), and light office work at MET 1.2 (70W)(Stein, Reynolds, Grondzilk, &
Kwok, 2006). These values were input into the Ecotect Schedule Editor as hourly wattage per meter
squared values for internal gain contribution. See Fig. C-12 and Fig. C-13 for full occupancy schedules.
Comfort Ranges
The comfort range that was used for the model was determined using the Predicted Mean Vote (PMV) Tool
from Square One Research. This calculator is based on the ISO 7730-1993 (E) standard for analytical
determination of comfort ranges. The variables of comfort that were considered for this calculation
included air temperature, radiant temperature, relative humidity, air velocity, activity rate (MET), and
clothing level (CLO). Fixed variables used for this calculation are shown in Table 4.1.

28
Variable Value Assumed Basis of Assumption
Relative Humidity 60% The Los Angeles climate has an average relative humidity
of 60%.
Activity Rate 1.2 MET The highest activity level for the space – light office work –
was assumed.
Clothing Level 0.6 CLO - Summer
1.0 CLO - Winter
Clothing was assumed to be a short sleeve shirt and trousers
during warmer periods and long-sleeve shirt and trousers
during cooler periods.
Air Velocity 0.4 m/s Air movement was assumed at a rate that would be pleasant
but not enough to disturb office related activities.
Table 4.1. Fixed variables used in the comfort calculation.
With these four variables fixed, the remaining two variables that were adjusted included the air temperature
and radiant temperature. Based on the relatively low mass of the baseline structure, the air and radiant
temperatures were assumed to be comparable. Both temperatures were adjusted concurrently to the
temperature where a maximum dissatisfaction rate of 20% would be observed. This 80% rate of
acceptability was selected to be consistent with the recommendations published in ASHRAE 55-2004, the
current U.S. standard for acceptable comfort ranges. Lower and upper temperature limits were found to be
67°F and 82°F, respectively. See Fig. C-14 and Fig. C-15 for full PMV Calculator results.
Infiltration Rate
Title 24-2001 standards did not specify a minimum or maximum infiltration rate. For residential buildings,
Title 24 provides only the requirement that all exterior joints or openings be caulked, gasketed, weather-
stripped, or otherwise sealed. However, Section 4.2.4 stated that approved computer programs use a
default envelope air leakage, expressed as a Specified Leakage Area (SLA) of 4.9. This value was
converted to approximate air changes per hour (ACH) using the following equations(Sherman, 1998):

Æ

The converted value of 0.49 air changes per hour was input into the Ecotect model as a fixed value for the
baseline model.

29
Active Systems
Mechanical conditioning systems were not reported in the model in order to isolate the passive performance
of the building envelope. Lighting systems were specified to meet the illumination requirements of the
most demanding occupancy type – office – at 400 lux (37.2 fc). Hours of operation were specified from
8am-10pm to assume the hours when occupants would be actively utilizing the space.
Summary of Baseline Input Variables
Baseline input variables are summarized in Table 4.2. Values are shown for the baseline model inputs as
well as the prescriptive requirements of Title 24-2001, Package D for Climate Zone 8.
Reference:
Title 24 – 2001, Package D, Climate Zone 8
Baseline Scheme:
Title 24-2001 Compliant
BUILDING ENVELOPE
Roof: R-30 insulation min Roof:
Asphalt shingle, 2x10 wood frame,
8.5” batt insulation (R-30)
U-factor: 0.02466
Walls: R-13 insulation min Wall:
Stucco-faced 2x4 wood frame,
3.5” batt insulation (R-13)
U-factor: 0.05812
Floors: R-19 insulation min Floor:
Carpet, plywood subfloor, 2x8 wood frame,
6.25” batt insulation (R-19)
U-factor: 0.03170
U-factor: 0.75 max
SHGC: 0.40 max (all orientations)
Glazing: 20% of total surface area

Glazing:
Wood frame, Low-E IG with 2.5mm glass
U-factor: 0.37
SHGC: 0.31
Glazing Ratio: 20% of total surface area
SCHEDULES
Occupancy: Not specified Occupancy: 2 people
Activity:
Seated Rest (MET 1.0) – 8am-10pm, Mon-Sun
Light Office Work (MET 1.2) – 9am-5pm, Mon-Fri
Sleep (MET 0.7) – 11pm-7am, Mon-Sun
Infiltration: Caulked, gasketed, weather-
stripped, or sealed exterior joints and
protrusions -or-
Continuous stucco, caulked & taped wall
joints, building wrap, or rigid insulation
Infiltration: 0.49 air change/hour (ACH)
Table 4.2. Summary of baseline model input variables.
30
4.3.2. BASELINE MODEL ANALYSIS
Analysis of the baseline model revealed conditions where the Title 24 envelope was not able to passively
provide internal temperatures within the specified comfort range. Assuming the comfort range of 67-82ºF,
the baseline simulation results showed that internal temperatures were comfortable for approximately
45.1% of the year. Of the remaining 54.9% of the year that would require additional energy to maintain
comfort, heating demand was found to be most significant. Hours where internal temperatures were too
cool represented approximately 51.2% of the yearly hours. These heating days were present from October
through June and most prominent from October to May. The remaining periods of discomfort were found
to be too hot, representing approximately 3.8% of the yearly hours. These cooling days existed from May
through October, and were most predominant in the months of July, August, and September. On the hottest
day, September 24
th
, internal temperatures peaked at 90.8ºF and daily gains from the envelope, solar,
ventilation and internal loads totaled to approximately 20,330 Btu.

Fig. 4.2. Distribution of annual temperatures in the baseline model.
The hourly distribution of temperature in the baseline model revealed several key findings. Cooler outside
temperatures were significantly shifted into the comfort zone by the Title 24 envelope (Fig. 4.2). Warmer
temperatures were somewhat reduced at their peak, but did not significantly shift towards the comfort zone.
This showed that the Title 24-2001 compliant envelope was able to mitigate cooler outside temperatures
more effectively than warmer outside temperatures. Overall, the baseline results revealed opportunities to
31
improve the passive performance of the Title 24 envelope by mitigating peak internal temperatures and
further consolidating temperature distribution within the comfort zone.
4.3.3. DESIGN MODEL INPUTS
Design models were configured with the same geometry and occupancy patterns as the baseline model,
with several adjustments to materials and infiltration. To emulate a CAM plant’s internal storage structure,
thermal mass was added to the internal layers of the building envelope. To emulate the restricted moisture
loss through the skin of succulent CAM plants, infiltration rates were adjusted to reflect a tighter building
envelope. To emulate the offset respiration of CAM plants, infiltration rates were increased during night
hours to act as a night ventilation scheme. Four design models were simulated with variations in the
configuration of thermal mass, as well as the hours of night ventilation (Table 4.3).
Model Envelope Thermal Mass
Configuration
Mass
Area
Mass
Volume
Heat
Capacity
Infiltration Rates
Baseline Title 24-2001
compliant
No thermal mass
added
N/A N/A N/A 0.49 ACH (24 hours)
Design A Title 24-2001
compliant
4” concrete panels
on ceiling
995 ft
2

330 ft
3
13450
Btu/°F
0.35 ACH (3am-8pm)
0.99 ACH (9pm-2am)
Design B Title 24-2001
compliant
4” concrete panels
on E & W walls
1180 ft
2

395 ft
3
15930
Btu/°F
0.35 ACH (3am-8pm)
0.99 ACH (9pm-2am)
Design C Title 24-2001
compliant
4” concrete floor
slab
1470 ft
2

490 ft
3
19850
Btu/°F
0.35 ACH (3am-8pm)
0.99 ACH (9pm-2am)
Design D Title 24-2001
compliant
2” concrete panels
on walls & ceiling
3120 ft
2

520 ft
3
21080
Btu/°F
0.35 ACH (5am-8pm)
0.99 ACH (9pm-4am)
Table 4.3. Ecotect model configurations.

32
Thermal Mass Placement
Four different configurations of thermal mass placement were applied to the design models. Two common
thicknesses of concrete (2” and 4”) were assumed for the supplemental thermal mass layer applied to the
interior of the Title 24-2001 compliant baseline envelope.
The first model, Design A, incorporated 4-inch thick concrete
panels attached to the ceiling. This was selected to test mass placed
high in the space, where heat absorption was assumed to be most
effective. See Fig. 4.3.
The second model, Design B, incorporated 4-inch thick concrete
panels along the walls. East and west walls were selected to test a
vertical mass configuration with maximum exposure to cross
ventilation. See Fig. 4.4.
The third model, Design C, incorporated a 4-inch thick concrete
floor slab as the only mass element. This was selected to test a
horizontal only configuration in a more conventional application of
thermally massive material. Additionally, this configuration was
selected to test a configuration that would be subject to increased
direct solar gain, compared to the previous two configurations that
were not significantly exposed to direct sunlight. See Fig. 4.5.
The fourth model, Design D, incorporated 2-inch thick concrete
panels on the east, west, and south interior walls as well as the
ceiling. The south wall was not included, as it was primarily
glazed. This variation was intended to simulate a thinner, more
disbursed storage layer across the entire enclosure, similar to the
interior skin structure of a succulent CAM plant. See Fig. 4.6.
Wall, roof, and floor constructions used in the design models are shown in Fig. C-4 through Fig. C-8.
Fig. 4.3. Design A mass configuration
Fig. 4.4. Design B mass configuration
Fig. 4.5. Design C mass configuration
Fig. 4.6. Design D mass configuration
33
Thermal Mass Cooling Capacity
Cooling capacity of the thermal mass was calculated in order to configure each of the four selected design
schemes. The calculation methodology used for this study was adapted from the Passive Cooling
Calculation Procedures outlined in Mechanical and Electrical Equipment for Buildings(Stein, Reynolds,
Grondzilk, & Kwok, 2006). The procedure in this text outlines a method to determine cooling capacity and
mass temperature for each hour of the night using a combination of calculated values and guideline factors.
The purpose of the calculation was to determine thermal mass and night ventilation configurations that
could effectively exchange enough heat to mitigate the worst case cooling conditions. Peak conditions
were determined from the results of the baseline model analysis; internal and external temperatures from
September 24
th
were chosen due to the designation as the “hottest day” within the climate zone.
Heat gains reported from the Ecotect baseline model included fabric (envelope) gains, solar gains,
ventilation gains and internal gains (combination of people, lights and equipment). The sum value of daily
heat gain on the peak day was 20,328 Btu (see Step 2 of Table C-6 through Table C-13). As alternative
confirmation of this value, individual gains were calculated from guideline factors from Stern (2006).
Hand calculations revealed relative consistency between the internal gains of people, lights, equipment.
However, the calculated envelope gains were found to be much higher – by a factor of 3.5x – compared to
the Ecotect results. This raised question as to the basis of the two envelope gains reported. The value from
the Ecotect simulation was ultimately selected due to the utilization of actual material values and solar
positioning in the simulation engine, rather than the use of estimated design factors in the hand calculation.
Heat capacity of the four thermal mass configurations thermal mass was determined through a simple
calculation of the material properties. Area calculations and material properties were taken directly from
the Ecotect model and inserted into Equation 1(Stein, Reynolds, Grondzik, & Kwok, 2006).
Equation 1:

/ // °
The mass heat capacity was utilized to calculate the maximum cooling capacity for each of the four thermal
mass configurations. The purpose of the calculation was to assess whether or not each scheme had enough
34
cooling potential to overcome the peak daily heat gains. To inform this assessment, the maximum cooling
capacity was summed from the hourly cooling capacities throughout the night. Two formulas - Equation 2
and Equation 3 – were utilized to set up a cascading calculation of hourly values (Stein, Reynolds,
Grondzik, & Kwok, 2006).
Equation 2:


Equation 3:

Two assumptions were made for the initial set points of the hourly calculation. First, the boundary of night
ventilation hours was assumed to be 6pm-6am. These values were within one hour of the respective sunset
and sunrise times for Los Angeles in September, and were also consistent with the hours of night
respiration observed in CAM plants(Taiz & Zeiger, 1991). Second, internal temperatures observed on the
peak cooling day were assumed for the initial thermal mass temperature. This selection was based on a
conservative estimate of worse case conditions where the thermal mass would be in temperature
equilibrium with the interior air volume.
Calculations of the hourly values for each configuration revealed several findings. All four mass
configurations provided enough cooling capacity to meet the peak daily heat gains. In fact, maximum
cooling capacities exceeded peak daily heat gain by a factor of 5x in Design A and as much as 12.6x in
Design D. On first assessment, this was perceived as an “over-design” of thermal mass for this relatively
small building volume. However, tests of alternative mass configurations revealed an inherent compromise
in thermal mass sizing. Lowering the thermal mass capacity would allow more rapid cooling of the mass at
night, but would also result in more rapid warming of the mass during the day. An extension of the time
required to reach equilibrium (also known as “thermal lag”) was perceived to be beneficial in this climate;
temperatures peak at mid-day, when a cooled mass would be most beneficial. Thus, it was determined that
lowering heating capacity through the adjustment of night ventilation hours would yield the most beneficial
results.
35
Infiltration
Infiltration rates were specified for the design models to account for both the envelope leakage and night
ventilation. Envelope leakage was based on minimum allowable fresh air rates for residential occupancy.
While a comparable CAM plant can completely eliminate skin respiration during the day, buildings must
provide a minimum volume of fresh air to sustain the continuous breathing of occupants. Recommended
fresh air rates were sourced from ASHRAE 62.1-2004, a standard which allows several compliance paths
for calculating fresh air allowance. The calculated allowance for two residential occupants was found to be
0.19 ACH. However, it was asserted in the standard that 0.35 ACH is the minimum allowable rate for an
occupied space. Thus, the default value of 0.35 ACH was assumed as the minimum ventilation rate.
The night ventilation rate was based on the passive air flow through the building enclosure. Volume flow
rate through the building enclosure during the night hours was determined through Equation 4 (Stein,
Reynolds, Grondzik, & Kwok, 2006).
Equation 4:

where:

Prevailing winds were analyzed in Ecotect to determine wind velocity during the hours of potential night
ventilation. Wind rose plots from late-afternoon to morning hours (6pm-6am) as well as night-time hours
(9pm-3am) revealed that prevailing wind came from the northwest and east/southeast orientations (see
Fig. C-20). Wind velocity during these hours was shown to most frequently range from 10-15 kilometers
per hour (6-9 miles/hour). From the wind plots a conservative estimate of average wind velocity of 10
kilometers/hour (6 miles/hour), prevalent from the SE direction, was assumed. This value was converted to
546.8 fpm for use as the wind velocity ( value.
Due to the north-south orientation of the building model, a reduced effectiveness factor ( was used in
the flow rate calculation to account for non-perpendicular wind direction. Prevailing southeast wind would
strike the southern façade diagonally, and thus an effectiveness factor of 0.35 was assumed (Stein,
Reynolds, Grondzik, & Kwok, 2006).
36
Area of the opening ( ) was fixed based on the
building model design. Operable elements of the
enclosure included swinging doors on the southern
façade, operable skylights, operable windows, and
inlet vents on the southern façade and northern
wall (Fig. 4.7). Swinging doors and operable
windows were design elements intended to support
passive cross-ventilation. However, high air flow rates from cross-ventilation would create discomfort at
night, when air is too cool. Therefore, operable inlets were chosen for low-volume night ventilation.
Inlets on the southern façade were assumed to be
the primary openings for incoming air flow. The
enclosure design included 10 southern air inlets
distributed across five structural bays. Gross
opening size per inlet was 1’-4” x 3’-0”, or 4 ft
2
.
The net free area per inlet was prorated to account
for a louvered rain vent and fine mesh screen to
protect openings from rain and pests (Fig. 4.8).
The combination of elements reduced net free area
of the opening to one third(American Plywood
Association, 1991), or approximately 1.33 ft
2
. The net opening area ( ) of two inlets – 2.67 ft
2
– was
assumed for Equation 4 as a factor of safety. Although average conditions were assumed for wind
velocity, some night hours would exhibit lower wind velocities. Thus, the assumption of utilizing one bay
(2 inlets) included a safety factor of up to 10 inlets to provide similar airflow during low wind conditions.
The volume flow rate ( ) calculated from Equation 4 was found to be 510.4 cfm through two inlets during
average wind conditions. A similar flow rate was found to be accomplished through the opening of all 10
inlets with an available wind velocity of only 2 kilometers/hour (1.2 miles/hour). This value was converted
to 1.0 ACH for use as the night ventilation rate. See Fig. C-16 through Fig. C-19for infiltration schedules.
Fig. 4.8. Detail of operable air inlet on the south facade
Fig. 4.7. Operable elements of the building enclosure
37
Night Ventilation Hours
Night ventilation hours were determined by using the assumed ventilation rate of 1.0 ACH. Appropriate
night ventilation hours were selected to reduce the maximum cooling capacities of the four design models
to more closely align to the peak daily heat gain. This process required two adjustments: reduction of
hourly heat capacity to account for a ventilation rate of 1.0 ACH, and reduction of night ventilation hours.
The night ventilation rate required to achieve maximum cooling capacity was based on the hour of peak
cooling capacity (determined from Equation 2). The cooling capacity and temperature delta from this hour
was inserted into Equation 5(Stein, Reynolds, Grondzik, & Kwok, 2006).
Equation 5:

  /
0.018
In each of the four design models, the required flow rate to achieve maximum cooling varied based on the
different mass cooling capacities (see Step 14 in Table C-6 through Table C-13). Required night
ventilation rates ranged from 59,698 cfm (1.95 ACH) in Design A to 203,388 cfm (6.63 ACH) in Design D.
In lieu of assigning the required rates, a ventilation rate of 1.0 ACH was applied to all four design models
to be consistent with the calculated value achieved through the enclosure inlets. It was assumed that this
adjusted night ventilation rate reduced the hourly cooling capacity based on a ratio of the required air
change rate to the assumed air change rate. The multiplier (see Step 14 in Table C-6 through Table C-13)
was applied to hourly heat capacities calculated in Equation 2: to determine “adjusted cooling capacity”.
Night ventilation hours were adjusted to reduce total cooling capacity to meet peak heat gains. Midnight
was assumed as the median hour of low temperatures, so night ventilation hours were adjusted with equal
distribution before and after 12am. Note that in adjusting the starting hour of night ventilation, the starting
mass temperature was also adjusted to reflect the indoor air temperature from that same hour (see Table
C-15). Night ventilation between 9pm-2am was found to mitigate peak daily heat gain in Design Models
A, B, and C. Design Model D, which had a higher cooling capacity, required ventilation for an additional
two hours. These values were assumed for the night infiltration rates inserted into Ecotect. For full
infiltration schedules, see Fig. C-16 through Fig. C-19.
38
4.3.4. DESIGN MODEL ANALYSIS
Each of the design models was simulated in two phases; first with thermal mass, and second with thermal
mass and night ventilation. This allowed an isolated review of both parts of the passive cooling strategy.
Passive cooling Effects
In all four design models, the addition of thermal mass resulted in significant reduction of cooling degree
hours in all design models; Design A exhibited 37-45% reductions, Design B exhibited 65-78% reductions,
Design C exhibited 49-61% reductions, and Design D exhibited 67-81% reductions. Analysis of heat gains
revealed that these reductions were a result of a mitigation of envelope and ventilation gains. On the peak
day, the hours of envelope gain began at 7am and the ending hour was extended from 6pm in the Baseline
to 9pm in Designs A and B, and 8pm in Design D. In all four Design models, envelope heat gains were
reduced overall. These results show the “thermal lag” affects of thermal mass to mitigate and extend heat
gain throughout the day.
Analysis of ventilation gains revealed identical reductions from the Baseline in Design Models A, B, and C,
and the most significant reduction shown in Design Model D (See Table C-20). These results were
consistent with the number of night ventilation hours assigned. Design A was found to benefit most from
night ventilation, with an additional reduction of 49 degree hours (8.7%) over the thermal mass scheme.
However, night ventilation effects in Design Model D were found to exhibit the most significant heat
reduction in summer months, suggesting that it was the most effective passive cooling scheme (Table 4.4).
Model Thermal Mass
Configuration
Mass
Area
Mass
Volume
Degree Hours Reduced
from Thermal Mass
Degree Hours Reduced
from Thermal Mass &
Night Ventilation
Design A 4” concrete panels
on ceiling
995 ft
2

330 ft
3
251 cooling degree hours
(-44.0%)
300 cooling degree hours
(-52.7%)
Design B 4” concrete panels
on E & W walls
1180 ft
2

395 ft
3
418 cooling degree hours.
(-73.4%)
447 cooling degree hours
(-78.5%)
Design C 4” concrete floor
slab
1470 ft
2

490 ft
3
326 cooling degree hours
(-57.3%)
364 cooling degree hours
(-63.9%)
Design D 2” concrete panels
on walls & ceiling
3120 ft
2

520 ft
3
433 cooling degree hours
(-76.0%)
469 cooling degree hours
(-82.3%)
Table 4.4. Cooling degree hours reduced in the four design models.
39
Annual Passive Benefits
Overall, the thermal mass and night ventilation scheme in all four models exhibited notable cooling degree
hour and heating degree hour reductions over the entire year. However, analysis of the isolated effects of
thermal mass revealed mixed passive benefit, specifically in the heating months. The thermal mass only
schemes of two design models – Design Model B and D – exhibited small increases in heating degree days
during the months of January through March. Conversely, Design Model C exhibited decreases in heating
degree hours in all heating months (see Table C-26). This suggested that thermal mass on the floor was an
advantageous placement during winter months, when greater exposure to direct sunlight could be utilized
for passive heating. However, in the schemes where mass was limited to walls, and solar exposure was
minimal, the thermal lag effects of mass was actually found to be a detriment to passive performance.
When night ventilation was applied, all four design models exhibited a reduction of heating degree hours
during the winter months. This result was assumed to be attributed to the day-long restriction of infiltration
to 0.35 ACH, compared to 0.49 ACH in the Baseline scheme. Because winter months had no night
ventilation component, this infiltration setting was also found to accentuate the affects of thermal mass.
Accordingly, Design C benefitted the most from a reduced infiltration rate, which further demonstrated the
advantage of a floor-based mass placement in winter months. In fact, these reductions of winter heating
degree hours were significant enough to demonstrate that Design C exhibited the greatest overall passive
benefit throughout the year (Table 4.5).
Model Thermal Mass
Configuration
Mass
Area
Mass
Volume
Cooling Degree
Hours Reduced
Heating Degree
Hours Reduced
Total Degree
Hours Reduced
Design A 4” concrete panels
on ceiling
995 ft
2

330 ft
3
300 degree hrs
(-52.7%)
1378 degree hrs
(-8.5%)
1678 degree hrs
(-10.0%)
Design B 4” concrete panels
on E & W walls
1180 ft
2

395 ft
3
447 degree hrs
(-78.5%)
1161 degree hrs
(-7.2%)
1608 degree hrs
(-9.6%)
Design C 4” concrete floor
slab
1470 ft
2

490 ft
3
364 degree hrs
(-63.9%)
1696 degree hrs
(-10.5%)
2060 degree hrs
(-12.3%)
Design D 2” concrete panels
on walls & ceiling
3120 ft
2

520 ft
3
469 degree hrs
(-82.3%)
1475 degree hrs
(-9.1%)
1944 degree hrs
(-11.6%)
Table 4.5. Summary of cooling, heating, and total degree hours reduced in the four design models.

40
CHAPTER 5: CONCLUSIONS
Through analysis it was concluded that the application of CAM photosynthesis as a design strategy had
passive cooling benefit in the reference building. While numerous studies have proven the effectiveness of
thermal mass and night ventilation as a cooling strategy in arid climates, the significance of this conclusion
was in the method that was used to select this design strategy. Night ventilation was selected in observance
of a comparable trait in a native plant, rather than from building precedents within the region. This
supported the hypothesis that native plants can in fact reveal adaptations that are climatologically
appropriate for building design.
One caveat of this conclusion is the comparison of mass configuration in the Ecotect validation models.
The Design model most consistent with structure of a CAM plant skin – Design D – was most
advantageous during periods of overheating. Conversely, Design C, a scheme that benefitted from passive
solar gain in the winter, was more advantageous over the entire year. This difference in annual
performance was principally due to the abundance of heating degree hours observed in the Baseline model;
greater performance gains were available for passive heating strategies. However, context is important in
this situation to interpret the results. CAM photosynthesis was applied to the reference building for the
specific purpose of passive cooling. As an isolated cooling strategy, it was indeed effective. Alternatively,
if the goal of the study was to achieve passive heating, selection of a difference plant strategy would have
more appropriate.
In conclusion, not all of the adaptive strategies observed in the representative plant community will be
relevant to every building type. The most beneficial application of this research is the selective application
of plant strategies in order to achieve a specific design goal. Determination of appropriate goals, with
specific intent to improve passive performance, will depend on the professional experience and level of
baseline evaluation undertaken by each designer that chooses to apply this approach to architectural design.

41
CHAPTER 6: FUTURE WORK
This study was focused to the evaluation of a single passive design strategy adapted from a focused review
of native plants in the Southern California area. Future work related to this topic would involve the
enhancement of comparison relevance and the extension of research scope.
Detailed Site Data
This study relied on interpolated GIS climate data for the site analysis and approximated weather data for
the simulation model, which may not accurately reflect conditions at the reference site. Utilizing data with
greater accuracy – perhaps from site measurement – would yield a more relevant microclimate analysis.
This is particularly important for urban sites, where heat islands and building adjacency can create
localized variances in temperature and airflow patterns. Thus, greater granularity in site data would allow
more meaningful comparisons of microclimate conditions.
Alternative Materials
While the purpose of the validation model was to isolate the effects of thermal mass and night ventilation,
alternative enclosure materials could be investigated to enhance passive performance. For instance, using
SIP panels – a product with more homogenous materials and lower u-values – would likely enhance the
thermal storage effects of the thermal mass and thus increase the passive performance of the enclosure.
This type of construction may also better represent an enclosure system that yields a tighter building
envelope with a reduced infiltration rate.
Additionally, other materials with thermal mass capacity may be investigated in order to simulate a more
integrated enclosure system. Phase change materials, for example, may better emulate the dynamic
properties of an integrated material structure and distributed storage capacity that is characteristic of the
membrane of a CAM plant.
Dynamic Envelope Characteristics
The majority of commercially available simulation software tools limit building studies to the evaluation of
a static envelope. The nature of plants and other living systems is that they have the ability to change their
enclosure characteristics to adapt to variable weather conditions throughout the year. Therefore,
42
opportunities for building innovation may exist through investigation of “responsive” building skins that
change with seasonal conditions. This may extend beyond simple operable elements to more dynamic
building elements such as enclosures with variable surface area or multi-purpose composite skins.
Simulations that accommodate these studies may require a split modeling procedure to isolate seasonal
performance, or new modeling tools to reflect enclosure systems with variable properties.
Alternative Locations
This methodology was limited to a single location in Southern California using readily available data and
individual observation. To extend the relevance of this study, similar research at other locations would
provide additional insight into how this methodology can be applied to other climate zones. Given the
attention and resources necessary to develop this as a design framework, there is great opportunity to take
advantage of diverse and collaborative interpretations of biological precedents for application to
architectural design.
Studies Beyond Energy
This study focused on passive envelope performance in order to optimize energy use in providing comfort.
However, the study of native plants can inform many other adaptive design strategies that are not energy
focused. For example, this study may have alternatively focused on water capture as a desired design
strategy. Numerous elements that were observed in the plant physiology, such as optimized root structures
or drainage from leaf structures, may have informed an investigation into water harvesting. Thus, this
method of bioclimatic investigation to inform architectural design has nearly limitless opportunity given the
focus of the research scope.

43
BIBLIOGRAPHY
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Baker, E. (1984). An Island Called California. Berkeley and Los Angeles, California: University of
California Press.
Behling, S., & Behling, S. (2000). Solar Power: The Evolution of Sustainable Architecture. Munich: Prestel
Verlag.
Benyus, J. M. (2002). Biomimicry: Innovation Inspired by Nature. New York: Harper Perennial.
Biomimicry Guild; Rocky Mountain Institute. (2005). Welcome to Biomimicry Database. Retrieved August
15, 2005, from Biomimicry Institute: http://database.portal.modwest.com/
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http://www.cactusmuseum.com/survival.asp
California Department of Forestry and Fire Protection. (2002). FRAP - Fire and Resource Assessment
Program. Retrieved May 8, 2005, from CA.gov: http://frap.cdf.ca.gov
California Energy Commission. (2001, June 1). California's 2001 Energy Efficiency Building Standards.
Retrieved January 18, 2008, from Residential Manual For Compliance with California's 2001 Energy
Efficiency Standards: http://www.energy.ca.gov/title24/2001standards/residential_manual/index.html
California Spatial Information Library. (2000). Retrieved May 6, 2005, from The State of California:
http://gis.ca.gov
Dalhousie University. (n.d.). Biology of Cacti. Retrieved February 13, 2005, from Dalhousie Collection of
Cacti & Other Succulents: http://www.dal.ca/~dp/cactus/biology.html
Daly, C., Gibson, W., Doggett, M., & Smith, J. (2004). Near-Real-Time High-Resolution Monthly Average
Maximum/Minimum Temperature for the Conterminous United States. Corvallis, Oregon, USA: Spatial
Climate Analysis Service, Oregon.
Desert Plant Survival. (n.d.). Retrieved February 13, 2005, from DesertUSA:
http://www.desertusa.com/du_plantsurv.html
Dimmitt, M. A. (1997, Spring). How Plants Cope with the Desert Climate. Sonorensis , 17 (1).
Energy Information Administration. (2001). Annual Energy Review 2001. Pittsburgh, Pennsylvania: U.S.
Government Printing Office.
Gibson, A. C. (1996). Structure-Function Relations of Warm Desert Plants. Berlin: Springer-Verlag.
Gore, A. (2006). An Inconvenient Truth. New York: Rodale.
Gutterman, Y. (2002). Survival Strategies of Annual Desert Plants. Berlin: Springer.
44
Hausladen, G., de Saldanha, M., Liedl, P., & Sager, C. (2005). Climate Design: Solutions for Buildings that
Can Do More with Less Technology. Basel: Birkhäuser.
Jurd, R. D. (1997). Animal Biology. New York: Springer-Verlag.
Lack, A. J., & Evans, D. E. (2001). Instant Notes in Plant Biology. New York: Springer-Verlag.
Lang, W. (2001). In C. Schittich (Ed.), In Detail: Building Skins (p. 29). Basel, Switzerland: Birkhauser.
McDonough, W., & Braungart, M. (2002). Cradle to Cradle: Remaking the Way We Make Things. North
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http://ucjeps.berkeley.edu/interchange.html

45
APPENDIX A: GIS MAPS

Fig. A-1. Land cover distribution over the state of California.

Fig. A-2. Areas of agriculture and urban zones that were removed from the sampling.
46

Fig. A-3. Geographical distribution of maximum annual temperatures.

Fig. A-4. Geographical distribution of minimum annual temperatures.
47

Fig. A-5. Geographical distribution of average annual solar insolation.

Fig. A-6. Geographical distribution of average wind power density.
48

Fig. A-7. Geographical distribution of average annual precipitation.

Fi
Fi
om

ig. A-8. Sampli
ig. A-9. Plant co
mitted.
ing boundary fr
ommunities sele
rom latitude 33
ected for micro

° N to 35° N.
climate analysi is. White areas denote areas w where data was
49

50
APPENDIX B: NATIVE PLANTS
REPRESENTATIVE PLANT SPECIES
Source: California Department of Fish and Game
http://www.dfg.ca.gov/biogeodata/cwhr/wildlife_habitats.asp
Desert Scrub Habitat
Desert Scrub habitats typically are open, scattered assemblages of broadleaved evergreen or deciduous
microphyll shrubs usually between 0.5 and 2 m (1.5 and 6.5 ft) in height; desert scrub plants rarely exceed
3 m (10 ft) in height.
Prevalent species
- Creosote Bush (dominant)
- Catclaw Acacia
- Desert agave
- Coastal Bladderpool
- White Brittlebush
- Burrobush
- White Bursage
- Barrel and Hedgehog Cactus
- Branched Pencil
- Teddy Bear Cholla
- Palmer's Coldenia
- Wiggin’s Croton

- Desert Globemallow
- Jojoba
- Littleleaf Ratany
- Ocotillo
- Beavertail Pricklypear
- Douglas and Rubber Rabbitbrush
- Desert Sand Verbena
- Desert Senna
- Squaw Waterweed
- Anderson's Wolfberry
- Mojave Yucca.
51
DESERT SCRUB PLANTS

Table B-1. The adaptive traits of plants native to the Desert Scrub plant community.

Common Name Species
No Leaves
Small Leaves
Rounded Forms
Self-Shading Form
Light Color
Fuzzy Coating
Fleshy Skin
Scaled/Waxy surface
Woody, Dry Stems
Desert Sand Verbena Abronia villosa xxx
Catclaw Acacia Acacia greggii xx x
Desert Agave Agave desertii xxx
Burrobush Ambrosia dumosa xxx
White bursage Ambrosia dumosa xxx
Squaw Waterweed Baccharis sergiloides xx
Desert Senna Calochortus splendens xx x
Rubber Rabbitbrush Chrysothamnus nauseosus xx
Douglas Rabbitbrush Chrysothamnus viscidiflorus ssp. viscidiflorus xx x
Wiggins croton Croton wigginsii xx x
Teddybear Cholla Cylindropuntia bigelovii xxx
White Brittlebush Encelia farinosa xx x
Barrel Cactus Ferocactus cylindraceus xxx x
Ocotillo Fouquieria splendens xx x
Coastal Bladderpod Isomeris arborea xx
Littleleaf Ratany Krameria erecta xxx x
Creosote Bush Larrea tridentate xxx
Anderson Wolfberry Lycium andersonii xx x x
Beavertail Pricklypear Opuntia basilaris xx xx
Branched Pencil Cholla Opuntia ramosissima xxxx
Jojoba Simmondsia chinensis xxx xx
Desert Globemallow Sphaeralcea ambigua xxx x
Palmer's Coldenia Tiquilia palmeri xxx
Mojave Yucca Yucca schidigera xx x
SURFACE FORM
SK
Fi
Fi
KETCHES FR
ig. B-1. Observ
ig. B-2. Observ
ROM SITE O
vations from the
vations from the
OBSERVATIO
e Coastal Sage S
e Southern Oak
ON
Scrub plant com
k Woodland pla
mmunity.
ant community. .

52
53
SKETCHES FROM LITERATURE STUDY
Sketched from content in Solar Power(Behling & Behling, 2000)

Fig. B-3. Phototropism as a response to environment.

Fig. B-4. Example of a nastic response in leaf petals.
54
APPENDIX C: VALIDATION MODEL

Table C-1. Model geometry calculations – Baseline.
SOUTH EAST
Area U-factor DETD DCLF Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Wall: 0.00 sf 0.05636 9 0.00
Title24 Wall: 489.44 sf 0.05812 9 256.02 Title24 Wall: 589.17 sf 0.05812 9 308.18
Window: 897.89 sf 12.6 11313.41 Window: 90.50 sf 43.6 3945.80
TOTAL: 1387.33 sf TOTAL: 679.67 sf
NORTH WEST
Area U-factor DETD DCLF Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Wall: 0.00 sf 0.05636 9 0.00 Mass Wall: 0.00 sf 0.05636 9 0.00
Title24 Wall: 945.73 sf 0.05812 9 494.69 Title24 Wall: 589.17 sf 0.05812 9 308.18
Window: 120.00 sf 13.6 1632.00 Window: 90.50 sf 43.6 3945.80
TOTAL: 1065.73 sf TOTAL: 679.67 sf
FLOOR ROOF
Area U-factor DETD Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Floor 0 0.03346 9 0.00 Mass Roof 0.00 sf 0.05636 30 0.00
Floor 1468.27 sf 0.03346 9 442.15 Roof: 995.07 sf 0.02466 30 736.15
0.00 Skylight: 48.00 sf 90.6 4348.80
TOTAL: 1468.27 sf TOTAL: 1043.07 sf
30672.81
6323.74
DETD and DCLF factors from MEEB Tables F.5 & F.6. 1246.89
Assumes mean daily rande of 20 (M), Design Temp at 89°F. 19.7%
Total Volume:
Total Surface Area:
Total Window Area:
Window % Surface:
55

Table C-2. Model Geometry Calculations – Design A.

SOUTH EAST
Area U-factor DETD DCLF Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Wall: 0.00 sf 0.05636 9 0.00
Title24 Wall: 489.44 sf 0.05812 9 256.02 Title24 Wall: 589.17 sf 0.05812 9 308.18
Window: 897.89 sf 12.6 11313.41 Window: 90.50 sf 43.6 3945.80
TOTAL: 1387.33 sf TOTAL: 679.67 sf
NORTH WEST
Area U-factor DETD DCLF Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Wall: 0.00 sf 0.05636 9 0.00 Mass Wall: 0.00 sf 0.05636 9 0.00
Title24 Wall: 945.73 sf 0.05812 9 494.69 Title24 Wall: 589.17 sf 0.05812 9 308.18
Window: 120.00 sf 13.6 1632.00 Window: 90.50 sf 43.6 3945.80
TOTAL: 1065.73 sf TOTAL: 679.67 sf
FLOOR ROOF
Area U-factor DETD Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Floor 0 0.03346 9 0.00 Mass Roof 995.07 sf 0.05636 30 1682.46
Floor 1468.27 sf 0.03346 9 442.15 Roof: 0.00 sf 0.02466 30 0.00
0.00 Skylight: 48.00 sf 90.6 4348.80
TOTAL: 1468.27 sf TOTAL: 1043.07 sf
= Enclosure area with addition of thermal mass 30672.81
6323.74
DETD and DCLF factors from MEEB Tables F.5 & F.6. 1246.89
Assumes mean daily rande of 20 (M), Design Temp at 89°F. 19.7%
Total Volume:
Total Surface Area:
Total Window Area:
Window % Surface:
56

Table C-3. Model Geometry Calculations – Design B.

SOUTH EAST
Area U-factor DETD DCLF Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Wall: 589.17 sf 0.05636 9 298.85
Title24 Wall: 489.44 sf 0.05812 9 256.02 Title24 Wall: 0.00 sf 0.05812 9 0.00
Window: 897.89 sf 12.6 11313.41 Window: 90.50 sf 43.6 3945.80
TOTAL: 1387.33 sf TOTAL: 679.67 sf
NORTH WEST
Area U-factor DETD DCLF Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Wall: 0.00 sf 0.05636 9 0.00 Mass Wall: 589.17 sf 0.05636 9 298.85
Title24 Wall: 945.73 sf 0.05812 9 494.69 Title24 Wall: 0.00 sf 0.05812 9 0.00
Window: 120.00 sf 13.6 1632.00 Window: 90.50 sf 43.6 3945.80
TOTAL: 1065.73 sf TOTAL: 679.67 sf
FLOOR ROOF
Area U-factor DETD Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Floor 0 0.03346 9 0.00 Mass Roof 0.00 sf 0.05636 30 0.00
Floor 1468.27 sf 0.03346 9 442.15 Roof: 995.07 sf 0.02466 30 736.15
0.00 Skylight: 48.00 sf 90.6 4348.80
TOTAL: 1468.27 sf TOTAL: 1043.07 sf
= Enclosure area with addition of thermal mass 30672.81
6323.74
DETD and DCLF factors from MEEB Tables F.5 & F.6. 1246.89
Assumes mean daily rande of 20 (M), Design Temp at 89°F. 19.7%
Total Volume:
Total Surface Area:
Total Window Area:
Window % Surface:
57

Table C-4. Model Geometry Calculations – Design C.

SOUTH EAST
Area U-factor DETD DCLF Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Wall: 0.00 sf 0.05636 9 0.00
Title24 Wall: 489.44 sf 0.05812 9 256.02 Title24 Wall: 589.17 sf 0.05812 9 308.18
Window: 897.89 sf 12.6 11313.41 Window: 90.50 sf 43.6 3945.80
TOTAL: 1387.33 sf TOTAL: 679.67 sf
NORTH WEST
Area U-factor DETD DCLF Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Wall: 0.00 sf 0.05636 9 0.00 Mass Wall: 0.00 sf 0.05636 9 0.00
Title24 Wall: 945.73 sf 0.05812 9 494.69 Title24 Wall: 589.17 sf 0.05812 9 308.18
Window: 120.00 sf 13.6 1632.00 Window: 90.50 sf 43.6 3945.80
TOTAL: 1065.73 sf TOTAL: 679.67 sf
FLOOR ROOF
Area U-factor DETD Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Floor 1468.27 0.03346 9 442.15 Mass Roof 0.00 sf 0.05636 30 0.00
Floor 0.00 sf 0.03346 9 0.00 Roof: 995.07 sf 0.02466 30 736.15
0.00 Skylight: 48.00 sf 90.6 4348.80
TOTAL: 1468.27 sf TOTAL: 1043.07 sf
= Enclosure area with addition of thermal mass 30672.81
6323.74
DETD and DCLF factors from MEEB Tables F.5 & F.6. 1246.89
Assumes mean daily rande of 20 (M), Design Temp at 89°F. 19.7%
Total Volume:
Total Surface Area:
Total Window Area:
Window % Surface:
58

Table C-5. Model Geometry Calculations – Design D.

SOUTH EAST
Area U-factor DETD DCLF Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Wall: 589.17 sf 0.05636 9 298.85
Title24 Wall: 489.44 sf 0.05812 9 256.02 Title24 Wall: 0.00 sf 0.05812 9 0.00
Window: 897.89 sf 12.6 11313.41 Window: 90.50 sf 43.6 3945.80
TOTAL: 1387.33 sf TOTAL: 679.67 sf
NORTH WEST
Area U-factor DETD DCLF Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Wall: 945.73 sf 0.05636 9 479.71 Mass Wall: 589.17 sf 0.05636 9 298.85
Title24 Wall: 0.00 sf 0.05812 9 0.00 Title24 Wall: 0.00 sf 0.05812 9 0.00
Window: 120.00 sf 13.6 1632.00 Window: 90.50 sf 43.6 3945.80
TOTAL: 1065.73 sf TOTAL: 679.67 sf
FLOOR ROOF
Area U-factor DETD Heat Gain Area U-factor DETD DCLF Heat Gain
Mass Floor 0 0.03346 9 0.00 Mass Roof 995.07 sf 0.05636 30 1682.46
Floor 1468.27 sf 0.03346 9 442.15 Roof: 0.00 sf 0.02466 30 0.00
0.00 Skylight: 48.00 sf 90.6 4348.80
TOTAL: 1468.27 sf TOTAL: 1043.07 sf
= Enclosure area with addition of thermal mass 30672.81
6323.74
DETD and DCLF factors from MEEB Tables F.5 & F.6. 1246.89
Assumes mean daily rande of 20 (M), Design Temp at 89°F. 19.7%
Total Volume:
Total Surface Area:
Total Window Area:
Window % Surface:
59
Title 24-2001 Compliant Construction

Fig. C-1. Wall Section – Baseline.

60
Title 24-2001 Compliant Construction

Fig. C-2. Roof Section – Baseline.

61
Title 24-2001 Compliant Construction

Fig. C-3. Floor Section – Baseline.

62
Title 24-2001 Compliant Construction + 4” Concrete Panel

Fig. C-4. Thermal Mass Roof Section – Design A.

63
Title 24-2001 Compliant Construction + 4” Concrete Panel

Fig. C-5. Thermal Mass Wall Section – Design B.

64
Title 24-2001 Compliant Construction + 4” Concrete Slab

Fig. C-6. Thermal Mass Floor Section – Design C.

65
Title 24-2001 Compliant Construction + 2” Concrete Panel

Fig. C-7. Thermal Mass Wall Section – Design D.

66
Title 24-2001 Compliant Construction + 2” Concrete Panel

Fig. C-8. Thermal Mass Roof Section – Design D.

67

Fig. C-9. Title 24-2001 Sample Wall Construction.

Fig. C-10. Title 24-2001 Sample Roof Construction.
68

Fig. C-11. Title 24-2001 Sample Floor Construction.

69
Saturday, Sunday

Fig. C-12. Occupancy Schedule – Weekend
Occupancy was set at two people in a live/work environment. Activity was assumed to be sitting/rest
(60W) from 8am-10pm, when occupants were assumed to be awake, and sleep (40W) from 11pm-7am.
Monday, Tuesday, Wednesday, Thursday, Friday

Fig. C-13. Occupancy Schedule – Weekday.
During weekday working hours, activity levels were elevated to light office work (70W) from 9am-5pm.

%
10
20
30
40
50
60
70
80
90
0 2 4 6 8 10 12 14 16 18 20 22 24
Hourly Operational Profile W eekend
%
10
20
30
40
50
60
70
80
90
0 2 4 6 8 10 12 14 16 18 20 22 24
Hourly Operational Profile W eekday
70

Fig. C-14. Comfort Calculation – Lower Limit.
Adjustment of the lower comfort band revealed that dissatisfaction rates exceeded 20% between 19°C and
20°C. When converted to Imperial units the lower temperature was rounded to the nearest value of 67°F.

Fig. C-15. Comfort Calculation – Upper Limit.
Adjustment of the upper comfort band revealed that dissatisfaction rates exceeded 20% at just below 28°C.
When converted to Imperial units the upper temperature was rounded to the nearest value of 82°F.
71
All Months

Fig. C-16. Heating Months Infiltration Schedule – Baseline Model.
Infiltration was set to a continuous 0.49 ACH throughout the day during all months.
Heating Months – October to June

Fig. C-17. Heating Months Infiltration Schedule – Design Models A, B, C & D.
Infiltration was set to a continuous 0.35 ACH throughout the day during the months of October to June.
The restricted infiltration rate is intended to represent a better sealed enclosure.

%
10
20
30
40
50
60
70
80
90
0 2 4 6 8 10 12 14 16 18 20 22 24
Hourly Operational Profile All Season Infiltration
%
10
20
30
40
50
60
70
80
90
0 2 4 6 8 10 12 14 16 18 20 22 24
Hourly Operational Profile H eating Season Infiltration
72
Cooling Months – July to September

Fig. C-18. Cooling Months Infiltration Schedule – Design Models A, B & C.
During the months of July to September, infiltration was set to 0.35 ACH from 3am-8pm and increased to
1.00 ACH from 9pm-2am. This reflects the night ventilation strategy for Design A, B, and C models.
Cooling Months – July to September

Fig. C-19. Cooling Months Infiltration Schedule – Design Model D.
During the months of July to September, infiltration was set to 0.35 ACH from 5am-8pm and increased to
1.00 ACH from 9pm-4am. This reflects the night ventilation strategy for the Design D model.
%
10
20
30
40
50
60
70
80
90
0 2 4 6 8 10 12 14 16 18 20 22 24
Hourly Operational Profile Cooling Season Infiltration
%
10
20
30
40
50
60
70
80
90
0 2 4 6 8 10 12 14 16 18 20 22 24
Hourly Operational Profile Cooling Season Infiltration
73

Table C-6. Night Ventilation Calculation – Design A (Maximum Capacity).
STEP 1STEP 7STEP 6
OA Temp Cooling Btu/h Mass Temp
Hour Outdoor Air
Temp
(II)
Cooling
Capacity
(Btu/h)
(III)
Mass
Temp
(IV)
6pm 73.4 °F 82.2 °F starting mass temp
7pm 73.4 °F 8756.6 81.5 °F
8pm 73.4 °F 8108.8 80.9 °F
9pm 71.2 °F 9658.2 80.2 °F
10pm 69.1 °F 11093.0 79.4 °F
11pm 67.5 °F 11884.3 78.5 °F
12am 68.9 °F 9572.2 77.8 °F
1am 69.3 °F 8505.8 77.2 °F
2am 70.3 °F 6801.8 76.7 °F
3am 71.2 °F 5403.1 76.3 °F
4am 64.0 °F 12167.8 75.4 °F peak cooling hour
5am 66.4 °F 8939.1 74.7 °F
6am 73.4 °F 1292.4 74.6 °F final mass temp
MAX COOLING CAPACITY: 102,183.2 Btu
STEP 2
24-hour Heat Gain
ECOTECT MEEB
Heat Gain
per day (Btu)
Heat Gain
per day (Btu)
Heat Gain
per sf (Btu)
MEEB Table Factors Value
Envelope 7698.96 28677.51 19.53 F.5, F.6 DETD, DCLF See Geometry
Solar 178.77 included
Ventilation 5922.06 3812.40 2.60 F.7 Infiltration Factor 1
People - Res - Sensible 6527.82 490.00 0.33 F.8 Sensible heat/person 245
People - Res - Latent included 310.00 0.21 F.8 Latent heat/person 155
Lights included 2936.54 2.00 F.3 Sens. heat/sf 2.0
Equipment included 1468.27 1.00 F.3 Sens. heat/sf 1.0
Sensible 20,327.6 37384.72 25.46
Sensible (Lights & Equip) 4404.81 3.00
Latent (People) 310.00 0.21
TOTAL: 20,327.6 37,694.72 Btu
STEP 3 Surface Surface Area
Mass Surface Area (sf) Surface Area Conductance 1.00
E Wall 0.00
N Wall 0.00 Material Density
W Wall 0.00
Floor 0.00 Lightweight Concrete 59.31
Roof 995.07 Concrete Stone 143.58
TOTAL: 995.07 sf
STEP 4 Thickness Thickness Volume Density Specific Heat
Mass Heat Capacity (in) (ft) (cu.ft) (lb/cuft) (Btu/lb/°F)
4 inches .33 feet 331.69 143.58 0.28242 13449.98
STEP 14
Flow Rate Requirement
Max Cooling ΔTemp Flow Rate
Night Vent
Air Changes
(Btu/h) (cfh) (ACH)
12167.8 11.3 59698.3 1.95
ASHRAE 62.1-2004
cfm/person
ASHRAE
cfm/sf
ASHRAE
Total cfm
Air Changes
(ACH)
5 0.06 98.1 0.19 Calculated requirement
0.35 Minimum allowable
Heat Capacity
(Btu/lb/°F)
74

Table C-7. Night Ventilation Calculation – Design A (Adjusted Capacity).
STEP 1STEP 7STEP 6
OA Temp Cooling Btu/h Mass Temp
Hour Outdoor Air
Temp
(II)
Cooling
Capacity
(Btu/h)
(III)
Mass
Temp
(IV)
Adjusted Cooling
Capacity
(Btu/h)
Adjusted Mass
Temp
6pm 73.4 °F
7pm 73.4 °F
8pm 73.4 °F
9pm 71.2 °F 79.5 °F starting mass temp 79.5 °F
10pm 69.1 °F 10368.6 78.7 °F 5327.4 79.1 °F
11pm 67.5 °F 11213.5 77.9 °F peak cooling hour 5761.5 78.7 °F
12am 68.9 °F 8951.0 77.2 °F 4599.0 78.3 °F
1am 69.3 °F 7930.6 76.6 °F 4074.7 78.0 °F
2am 70.3 °F 6269.2 76.2 °F final mass temp 3221.1 77.8 °F
3am 71.2 °F
4am 64.0 °F
5am 66.4 °F
6am 73.4 °F
MAX COOLING CAPACITY: 44,733.0 Btu ADJ CAPACITY: 22,983.6 Btu
STEP 2
24-hour Heat Gain
ECOTECT MEEB
Heat Gain per
day (Btu)
Heat Gain per
day
Heat Gain per sf
(Btu)
MEEB Table Factors Value
Envelope 7697.44 28677.51 19.53 F.5, F.6 DETD, DCLF See Geometry
Solar 178.77 included
Ventilation 5922.06 3812.40 2.60 F.7 Infiltration Factor 1
People - Res - Sensible 6527.82 490.00 0.33 F.8 Sensible heat/person 245
People - Res - Latent included 310.00 0.21 F.8 Latent heat/person 155
Lights included 2936.54 2.00 F.3 Sens. heat/sf 2.0
Equipment included 1468.27 1.00 F.3 Sens. heat/sf 1.0
Sensible 20,326.1 37384.72 25.46
Sensible (Lights & Equip) 4404.81 3.00
Latent (People) 310.00 0.21
TOTAL: 20,326.1 37,694.72 Btu
STEP 3 Surface Surface Area
Mass Surface Area (sf) Surface Area Conductance 1.00
E Wall 0.00
N Wall 0.00 Material Density
W Wall 0.00
Floor 0.00 Lightweight Concrete 59.31
Roof 995.07 Concrete Stone 143.58
TOTAL: 995.07 sf
STEP 4 Thickness Thickness Volume Density Specific Heat
Mass Heat Capacity (in) (ft) (cu.ft) (lb/cuft) (Btu/lb/°F)
4 inches .33 feet 331.69 143.58 0.28242 13449.98
STEP 14
Flow Rate Requirement
Max Cooling ΔTemp Flow Rate
Night Vent
Air Changes
Reduced Air
Change Rate Multiplier
(Btu/h) (cfh) (ACH) (ACH)
11213.5 10.4 59698.3 1.95 1.00 0.51
ASHRAE 62.1-2004
cfm/person
ASHRAE
cfm/sf
ASHRAE
Total cfm
Air Changes
(ACH)
5 0.06 98.1 0.19 Calculated requirement
0.35 Minimum allowable
Heat Capacity
(Btu/°F)
75

Table C-8. Night Ventilation Calculation – Design B (Maximum Capacity).
STEP 1STEP 7STEP 6
OA Temp Cooling Btu/h Mass Temp
Hour Outdoor Air
Temp
(II)
Cooling
Capacity
(Btu/h)
(III)
Mass
Temp
(IV)
6pm 73.4 °F 82.2 °F starting mass temp
7pm 73.4 °F 10369.4 81.5 °F
8pm 73.4 °F 9602.2 80.9 °F
9pm 71.2 °F 11437.0 80.2 °F
10pm 69.1 °F 13136.1 79.4 °F
11pm 67.5 °F 14073.2 78.5 °F
12am 68.9 °F 11335.2 77.8 °F
1am 69.3 °F 10072.4 77.2 °F
2am 70.3 °F 8054.6 76.7 °F
3am 71.2 °F 6445.3 76.3 °F
4am 64.0 °F 14405.4 75.4 °F peak cooling hour
5am 66.4 °F 10582.3 74.7 °F
6am 73.4 °F 1527.5 74.6 °F final mass temp
MAX COOLING CAPACITY: 121,040.6 Btu
STEP 2
24-hour Heat Gain
ECOTECT MEEB
Heat Gain per
day (Btu)
Heat Gain per
day (Btu)
Heat Gain per sf
(Btu)
MEEB Table Factors Value
Envelope 7698.96 27712.53 18.87 F.5, F.6 DETD, DCLF See Geometry
Solar 178.77 included
Ventilation 5922.06 3812.40 2.60 F.7 Infiltration Factor 1
People - Res - Sensible 6527.82 490.00 0.33 F.8 Sensible heat/person 245
People - Res - Latent included 310.00 0.21 F.8 Latent heat/person 155
Lights included 2936.54 2.00 F.3 Sens. heat/sf 2.0
Equipment included 1468.27 1.00 F.3 Sens. heat/sf 1.0
Sensible 20,327.6 36419.74 24.80
Sensible (Lights & Equip) 4404.81 3.00
Latent (People) 310.00 0.21
TOTAL: 20,327.6 36,729.74 Btu
STEP 3 Surface Surface Area
Mass Surface Area (sf) Surface Area Conductance 1.00
E Wall 589.17
N Wall 0.00 Material Density
W Wall 589.17
Floor 0.00 Lightweight Concrete 59.31
Roof 0.00 Concrete Stone 143.58
TOTAL: 1178.34 sf
STEP 4 Thickness Thickness Volume Density Specific Heat
Mass Heat Capacity (in) (ft) (cu.ft) (lb/cuft) (Btu/lb/°F)
4 inches .33 feet 392.78 143.58 0.28242 15927.18
STEP 14
Flow Rate Requirement
Max Cooling ΔTemp Flow Rate
Night Vent
Air Changes
(Btu/h) (cfh) (ACH)
14405.4 11.3 70693.4 2.30
ASHRAE 62.1-2004
cfm/person
ASHRAE
cfm/sf
ASHRAE
Total cfm
Air Changes
(ACH)
5 0.06 98.1 0.19 Calculated requirement
0.35 Minimum allowable
Heat Capacity
(Btu/°F)
76

Table C-9. Night Ventilation Calculation – Design B (Adjusted Capacity).
STEP 1STEP 7STEP 6
OA Temp Cooling Btu/h Mass Temp
Hour Outdoor Air
Temp
(II)
Cooling
Capacity
(Btu/h)
(III)
Mass
Temp
(IV)
Adjusted Cooling
Capacity
(Btu/h)
Adjusted Mass
Temp
6pm 73.4 °F
7pm 73.4 °F
8pm 73.4 °F
9pm 71.2 °F 79.5 °F starting mass temp 79.5 °F
10pm 69.1 °F 12278.3 78.7 °F 5327.4 79.2 °F
11pm 67.5 °F 13278.8 77.9 °F peak cooling hour 5761.5 78.8 °F
12am 68.9 °F 10599.6 77.2 °F 4599.0 78.5 °F
1am 69.3 °F 9391.2 76.6 °F 4074.7 78.3 °F
2am 70.3 °F 7423.8 76.2 °F final mass temp 3221.1 78.1 °F
3am 71.2 °F
4am 64.0 °F
5am 66.4 °F
6am 73.4 °F
MAX COOLING CAPACITY: 52,971.8 Btu ADJ CAPACITY: 22,983.6 Btu
STEP 2
24-hour Heat Gain
ECOTECT MEEB
Heat Gain per
day (Btu)
Heat Gain per
day (Btu)
Heat Gain per sf
(Btu)
MEEB Table Factors Value
Envelope 7697.44 27712.53 18.87 F.5, F.6 DETD, DCLF See Geometry
Solar 178.77 included
Ventilation 5922.06 3812.40 2.60 F.7 Infiltration Factor 1
People - Res - Sensible 6527.82 490.00 0.33 F.8 Sensible heat/person 245
People - Res - Latent included 310.00 0.21 F.8 Latent heat/person 155
Lights included 2936.54 2.00 F.3 Sens. heat/sf 2.0
Equipment included 1468.27 1.00 F.3 Sens. heat/sf 1.0
Sensible 20,326.1 36419.74 24.80
Sensible (Lights & Equip) 4404.81 3.00
Latent (People) 310.00 0.21
TOTAL: 20,326.1 36,729.74 Btu
STEP 3 Surface Surface Area
Mass Surface Area (sf) Surface Area Conductance 1.00
E Wall 589.17
N Wall 0.00 Material Density
W Wall 589.17
Floor 0.00 Lightweight Concrete 59.31
Roof 0.00 Concrete Stone 143.58
TOTAL: 1178.34 sf
STEP 4 Thickness Thickness Volume Density Specific Heat
Mass Heat Capacity (in) (ft) (cu.ft) (lb/cuft) (Btu/lb/°F)
4 inches .33 feet 392.78 143.58 0.28242 15927.18
STEP 14
Flow Rate Requirement
Max Cooling ΔTemp Flow Rate
Night Vent
Air Changes
Reduced Air
Change Rate Multiplier
(Btu/h) (cfh) (ACH) (ACH)
13278.8 10.4 70693.4 2.30 1.00 0.43
ASHRAE 62.1-2004
cfm/person
ASHRAE
cfm/sf
ASHRAE
Total cfm
Air Changes
(ACH)
5 0.06 98.1 0.19 Calculated requirement
0.35 Minimum allowable
Heat Capacity
(Btu/°F)
77

Table C-10. Night Ventilation Calculation – Design C (Maximum Capacity).
STEP 1STEP 7STEP 6
OA Temp Cooling Btu/h Mass Temp
Hour Outdoor Air
Temp
(II)
Cooling
Capacity
(Btu/h)
(III)
Mass
Temp
(IV)
6pm 73.4 °F 83.3 °F starting mass temp
7pm 73.4 °F 14535.9 82.6 °F
8pm 73.4 °F 13460.5 81.9 °F
9pm 71.2 °F 15636.1 81.1 °F
10pm 69.1 °F 17650.7 80.2 °F
11pm 67.5 °F 18723.5 79.3 °F
12am 68.9 °F 15224.0 78.5 °F
1am 69.3 °F 13569.1 77.8 °F
2am 70.3 °F 10979.5 77.3 °F
3am 71.2 °F 8845.7 76.8 °F
4am 64.0 °F 18762.8 75.9 °F peak cooling hour
5am 66.4 °F 13938.9 75.2 °F
6am 73.4 °F 2600.4 75.0 °F final mass temp
MAX COOLING CAPACITY: 163,927.1 Btu
STEP 2
24-hour Heat Gain
ECOTECT MEEB
Heat Gain per
day (Btu)
Heat Gain per
day (Btu)
Heat Gain per sf
(Btu)
MEEB Table Factors Value
Envelope 7698.96 27731.20 18.89 F.5, F.6 DETD, DCLF See Geometry
Solar 178.77 included
Ventilation 5922.06 3812.40 2.60 F.7 Infiltration Factor 1
People - Res - Sensible 6527.82 490.00 0.33 F.8 Sensible heat/person 245
People - Res - Latent included 310.00 0.21 F.8 Latent heat/person 155
Lights included 2936.54 2.00 F.3 Sens. heat/sf 2.0
Equipment included 1468.27 1.00 F.3 Sens. heat/sf 1.0
Sensible 20,327.6 36438.41 24.82
Sensible (Lights & Equip) 4404.81 3.00
Latent (People) 310.00 0.21
TOTAL: 20,327.6 36,748.41 Btu
STEP 3 Surface Surface Area
Mass Surface Area (sf) Surface Area Conductance 1.00
E Wall 0.00
N Wall 0.00 Material Density
W Wall 0.00
Floor 1468.27 Lightweight Concrete 59.31
Roof 0.00 Concrete Stone 143.58
TOTAL: 1468.27 sf
STEP 4 Thickness Thickness Volume Density Specific Heat
Mass Heat Capacity (in) (ft) (cu.ft) (lb/cuft) (Btu/lb/°F)
4 inches .33 feet 489.42 143.58 0.28242 19846.05
STEP 14
Flow Rate Requirement
Max Cooling ΔTemp Flow Rate
Night Vent
Air Changes
(Btu/h) (cfh) (ACH)
18762.8 11.8 88087.5 2.87
ASHRAE 62.1-2004
cfm/person
ASHRAE
cfm/sf
ASHRAE
Total cfm
Air Changes
(ACH)
5 0.06 98.1 0.19 Calculated requirement
0.35 Minimum allowable
Heat Capacity
(Btu/°F)
78

Table C-11. Night Ventilation Calculation – Design C (Adjusted Capacity).
STEP 1STEP 7STEP 6
OA Temp Cooling Btu/h Mass Temp
Hour Outdoor Air
Temp
(II)
Cooling
Capacity
(Btu/h)
(III)
Mass
Temp
(IV)
Adjusted Cooling
Capacity
(Btu/h)
Adjusted Mass
Temp
6pm 73.4 °F
7pm 73.4 °F
8pm 73.4 °F
9pm 71.2 °F 79.5 °F starting mass temp 79.5 °F
10pm 69.1 °F 15299.4 78.7 °F 5327.4 79.2 °F
11pm 67.5 °F 16546.1 77.9 °F peak cooling hour 5761.5 78.9 °F
12am 68.9 °F 13207.6 77.2 °F 4599.0 78.7 °F
1am 69.3 °F 11701.9 76.6 °F 4074.7 78.5 °F
2am 70.3 °F 9250.4 76.2 °F final mass temp 3221.1 78.3 °F
3am 71.2 °F
4am 64.0 °F
5am 66.4 °F
6am 73.4 °F
MAX COOLING CAPACITY: 66,005.5 Btu USTED CAPACITY: 22,983.6 Btu
STEP 2
24-hour Heat Gain
ECOTECT MEEB
Heat Gain per
day (Btu)
Heat Gain per
day (Btu)
Heat Gain per sf
(Btu)
MEEB Table Factors Value
Envelope 7697.44 27731.20 18.89 F.5, F.6 DETD, DCLF See Geometry
Solar 178.77 included
Ventilation 5922.06 3812.40 2.60 F.7 Infiltration Factor 1
People - Res - Sensible 6527.82 490.00 0.33 F.8 Sensible heat/person 245
People - Res - Latent included 310.00 0.21 F.8 Latent heat/person 155
Lights included 2936.54 2.00 F.3 Sens. heat/sf 2.0
Equipment included 1468.27 1.00 F.3 Sens. heat/sf 1.0
Sensible 20,326.1 36438.41 24.82
Sensible (Lights & Equip) 4404.81 3.00
Latent (People) 310.00 0.21
TOTAL: 20,326.1 36,748.41 Btu
STEP 3 Surface Surface Area
Mass Surface Area (sf) Surface Area Conductance 1.00
E Wall 0.00
N Wall 0.00 Material Density
W Wall 0.00
Floor 1468.27 Lightweight Concrete 59.31
Roof 0.00 Concrete Stone 143.58
TOTAL: 1468.27 sf
STEP 4 Thickness Thickness Volume Density Specific Heat
Mass Heat Capacity (in) (ft) (cu.ft) (lb/cuft) (Btu/lb/°F)
4 inches .33 feet 489.42 143.58 0.28242 19846.05
STEP 14
Flow Rate Requirement
Max Cooling ΔTemp Flow Rate
Night Vent
Air Changes
Reduced Air
Change Rate Multiplier
(Btu/h) (cfh) (ACH) (ACH)
16546.1 10.4 88087.5 2.87 1.00 0.35
ASHRAE 62.1-2004
cfm/person
ASHRAE
cfm/sf
ASHRAE
Total cfm
Air Changes
(ACH)
5 0.06 98.1 0.19 Calculated requirement
0.35 Minimum allowable
Heat Capacity
(Btu/°F)
79

Table C-12. Night Ventilation Calculation – Design D (Maximum Capacity).
STEP 1STEP 7STEP 6
OA Temp Cooling Btu/h Mass Temp
Hour Outdoor Air
Temp
(II)
Cooling
Capacity
(Btu/h)
(III)
Mass
Temp
(IV)
6pm 73.4 °F 83.3 °F starting mass temp
7pm 73.4 °F 30879.5 81.8 °F
8pm 73.4 °F 26310.4 80.6 °F
9pm 71.2 °F 29154.7 79.2 °F
10pm 69.1 °F 31578.1 77.7 °F
11pm 67.5 °F 31958.6 76.2 °F peak cooling hour
12am 68.9 °F 22738.3 75.1 °F
1am 69.3 °F 18250.9 74.2 °F
2am 70.3 °F 12181.7 73.7 °F
3am 71.2 °F 7572.0 73.3 °F
4am 64.0 °F 28909.4 71.9 °F
5am 66.4 °F 17333.0 71.1 °F final mass temp
6am 73.4 °F
MAX COOLING CAPACITY: 256,866.7 Btu
STEP 2
24-hour Heat Gain
ECOTECT MEEB
Heat Gain per
day (Btu)
Heat Gain per
day (Btu)
Heat Gain per sf
(Btu)
MEEB Table Factors Value
Envelope 7698.96 28643.86 19.51 F.5, F.6 DETD, DCLF See Geometry
Solar 178.77 included
Ventilation 5922.06 3812.40 2.60 F.7 Infiltration Factor 1
People - Res - Sensible 6527.82 490.00 0.33 F.8 Sensible heat/person 245
People - Res - Latent included 310.00 0.21 F.8 Latent heat/person 155
Lights included 2936.54 2.00 F.3 Sens. heat/sf 2.0
Equipment included 1468.27 1.00 F.3 Sens. heat/sf 1.0
Sensible 20,327.6 37351.07 25.44
Sensible (Lights & Equip) 4404.81 3.00
Latent (People) 310.00 0.21
TOTAL: 20,327.6 37,661.07 Btu
STEP 3 Surface Surface Area
Mass Surface Area (sf) Surface Area Conductance 1.00
E Wall 589.17
N Wall 945.73 Material Density
W Wall 589.17
Floor 0.00 Lightweight Concrete 59.31
Roof 995.07 Concrete Stone 143.58
TOTAL: 3119.14 sf
STEP 4 Thickness Thickness Volume Density Specific Heat
Mass Heat Capacity (in) (ft) (cu.ft) (lb/cuft) (Btu/lb/°F)
2 inches .17 feet 519.86 143.58 0.28242 21080.12
STEP 14
Flow Rate Requirement
Max Cooling ΔTemp Flow Rate
Night Vent
Air Changes
(Btu/h) (cfh) (ACH)
31958.6 8.7 203378.7 6.63
ASHRAE 62.1-2004
cfm/person
ASHRAE
cfm/sf
ASHRAE
Total cfm
Air Changes
(ACH)
5 0.06 98.1 0.19 Calculated requirement
0.35 Minimum allowable
Heat Capacity
(Btu/°F)
80

Table C-13. Night Ventilation Calculation – Design D (Adjusted Capacity).
STEP 1STEP 7STEP 6
OA Temp Cooling Btu/h Mass Temp
Hour Outdoor Air
Temp
(II)
Cooling
Capacity
(Btu/h)
(III)
Mass
Temp
(IV)
Adjusted Cooling
Capacity
(Btu/h)
Adjusted Mass
Temp
6pm 73.4 °F
7pm 73.4 °F
8pm 73.4 °F
9pm 71.2 °F 79.5 °F starting mass temp 79.5 °F
10pm 69.1 °F 32501.4 78.0 °F 4901.7 79.3 °F
11pm 67.5 °F 32745.3 76.4 °F peak cooling hour 4938.5 79.0 °F
12am 68.9 °F 23408.6 75.3 °F 3530.4 78.9 °F
1am 69.3 °F 18822.0 74.4 °F 2838.7 78.7 °F
2am 70.3 °F 12668.3 73.8 °F 1910.6 78.6 °F
3am 71.2 °F 7986.6 73.4 °F 1204.5 78.6 °F
4am 64.0 °F 29262.7 72.0 °F final mass temp 4413.3 78.4 °F
5am 66.4 °F
6am 73.4 °F
MAX COOLING CAPACITY: 157,395.0 Btu ADJ. CAPACITY: 23,737.7 Btu
STEP 2
24-hour Heat Gain
ECOTECT MEEB
Heat Gain per
day (Btu)
Heat Gain per
day (Btu)
Heat Gain per sf
(Btu)
MEEB Table Factors Value
Envelope 7697.44 28643.86 19.51 F.5, F.6 DETD, DCLF See Geometry
Solar 178.77 included
Ventilation 5922.06 3812.40 2.60 F.7 Infiltration Factor 1
People - Res - Sensible 6527.82 490.00 0.33 F.8 Sensible heat/person 245
People - Res - Latent included 310.00 0.21 F.8 Latent heat/person 155
Lights included 2936.54 2.00 F.3 Sens. heat/sf 2.0
Equipment included 1468.27 1.00 F.3 Sens. heat/sf 1.0
Sensible 20,326.1 37351.07 25.44
Sensible (Lights & Equip) 4404.81 3.00
Latent (People) 310.00 0.21
TOTAL: 20,326.1 37,661.07 Btu
STEP 3 Surface Surface Area
Mass Surface Area (sf) Surface Area Conductance 1.00
E Wall 589.17
N Wall 945.73 Material Density
W Wall 589.17
Floor 0.00 Lightweight Concrete 59.31
Roof 995.07 Concrete Stone 143.58
TOTAL: 3119.14 sf
STEP 4 Thickness Thickness Volume Density Specific Heat
Mass Heat Capacity (in) (ft) (cu.ft) (lb/cuft) (Btu/lb/°F)
2 inches .17 feet 519.86 143.58 0.28242 21080.12
STEP 14
Flow Rate Requirement
Max Cooling ΔTemp Flow Rate
Night Vent
Air Changes
Reduced Air
Change Rate Multiplier
(Btu/h) (cfh) (ACH) (ACH)
32745.3 8.9 203378.7 6.63 1.00 0.15
ASHRAE 62.1-2004
cfm/person
ASHRAE
cfm/sf
ASHRAE
Total cfm
Air Changes
(ACH)
5 0.06 98.1 0.19 Calculated requirement
0.35 Minimum allowable
Heat Capacity
(Btu/°F)
81
July 1
st
– September 30
th

6pm – 6am

9pm – 3am

Fig. C-20. Night Time Prevailing Winds – California Zone 8.
82

MONTH
TOO
HOT
TOO
HOT
TOO
COOL
TOO
COOL TOTAL TOTAL
(Hrs) (%) (Hrs) (%) (Hrs) (%)
Jan 0 0.0% 668 89.8% 668 89.8%
Feb 0 0.0% 613 91.2% 613 91.2%
Mar 0 0.0% 642 86.3% 642 86.3%
Apr 0 0.0% 494 68.6% 494 68.6%
May 14 1.9% 384 51.6% 398 53.5%
Jun 12 1.7% 93 12.9% 105 14.6%
Jul 123 16.5% 67 9.0% 190 25.5%
Aug 86 11.6% 19 2.6% 105 14.1%
Sep 92 12.8% 43 6.0% 135 18.8%
Oct 5 0.7% 259 34.8% 264 35.5%
Nov 0 0.0% 545 75.7% 545 75.7%
Dec 0 0.0% 654 87.9% 654 87.9%
TOTAL HOURS OF
DISCOMFORT
332 3.8% 4481 51.2% 4813 54.9%
TOTAL HOURS OF
COMFORT

3947 45.1%

Table C-14. Discomfort Period – Baseline.

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Hrs
0 0
200
200
400
400
600
600
800
800
00 00
14 12
123
86 92
5 00
Too Hot
668
613
642
494
385
93
67
19
43
259
545
654
Too Cool
DISCOMFORT PERIOD - Module California Climate Zone 8, USA
83
Monday, September 24
th
Average Temperature: 76.8 °F (Ground 62.7 °F)
Total Surface Area: 6293.75 ft2 (428.7% flr area).
Total Exposed Area: 4825.48 ft2 (328.7% flr area).
Total South Window: 897.89 ft2 (61.2% flr area).
Total Window Area: 1246.88 ft2 (84.9% flr area).
Total Conductance (AU): 1144.7 Btu/hr/°K
Total Admittance (AY): 3308.5 Btu/hr/°K
Response Factor: 2.02
HOUR INSIDE OUTSIDE TEMP.DIF
(F) (F) (F)
12am 76.3 68.9 7.4
1am 76.4 69.3 7.2
2am 76.8 70.3 6.5
3am 77.2 71.2 6
4am 74.9 64 10.8
5am 75.1 66.4 8.8
6am 77.7 73.4 4.3
7am 81 81.5 -0.5
8am 83.9 86.7 -2.8
9am 88.5 91.8 -3.3
10am 90.3 95.9 -5.6
11am 90.5 95.9 -5.4
12pm 90.8 97.9 -7
1pm 90.2 95.9 -5.7
2pm 89.4 92.8 -3.5
3pm 88.9 91.8 -2.8
4pm 87.3 87.6 -0.3
5pm 83.9 80.4 3.5
6pm 82.2 77.5 4.6
7pm 80.6 73.4 7.2
8pm 80.3 73.4 6.9
9pm 79.5 71.2 8.3
Starting Mass
Temperature
10pm 78.7 69.1 9.6
11pm 75.9 67.5 8.4

Table C-15. Peak Day Temperatures – Baseline.
84
Monday, September 24
th

HOUR HVAC FABRIC SOLAR VENT. INTERN
(Btu) (Btu) (Btu) (Btu) (Btu)
0 0 0 0 0 25.36
1 0 0 0 0 25.36
2 0 0 0 0 25.36
3 0 0 0 0 25.36
4 0 -126.85 0 -172.41 25.36
5 0 -68.94 0 -35.11 25.36
6 0 -8.88 8.3 0 25.36
7 0 35.5 18.15 0 25.36
8 0 373.42 14.78 267.32 38.04
9 0 761.58 14.91 584.47 447.25
10 0 1028.78 18.54 848.63 447.25
11 0 1055.12 23.46 889.68 447.25
12 0 1082.81 19.45 1001.91 447.25
13 0 1000.94 15.82 901.61 447.25
14 0 907.39 13.61 683.92 447.25
15 0 847.32 15.3 624.69 447.25
16 0 618.77 14.39 327.35 447.25
17 0 178.69 2.07 0 447.25
18 0 11.77 0 0 447.25
19 0 0 0 0 447.25
20 0 0 0 0 447.25
21 0 0 0 0 447.25
22 0 0 0 0 447.25
23 0 0 0 0 25.36
TOTAL 0 7697.44 178.77 5922.06 6527.82
Table C-16. Peak Day Heat Gain – Baseline.
0 2 4 6 8 10 12 14 16 18 20 22
0.0 0.0
2500.0
2500.0
5000.0
5000.0
7500.0
7500.0
10000.0
10000.0
Btu/ hr
12500.0
HVAC Load Conduction SolAir Direct Solar Ventilation Internal Inter-Zonal
HOURLY GAINS - Module Monday 24th September (267) - California Climate Zone 8, USA
85
Monday, September 24
th

HOUR HVAC FABRIC SOLAR VENT. INTERN
(Btu) (Btu) (Btu) (Btu) (Btu)
0 0 0 0 0 25.36
1 0 0 0 0 25.36
2 0 0 0 0 25.36
3 0 0 0 0 25.36
4 0 -126.85 0 -123.15 25.36
5 0 -66.25 0 -25.08 25.36
6 0 -8.31 8.3 0 25.36
7 0 35.43 18.15 0 25.36
8 0 364.71 14.78 190.94 38.04
9 0 733.71 14.91 417.48 447.25
10 0 983.91 18.54 606.17 447.25
11 0 1002.48 23.46 635.48 447.25
12 0 1036.55 19.45 715.65 447.25
13 0 957.65 15.82 644.01 447.25
14 0 872.72 13.61 488.52 447.25
15 0 824.07 15.3 446.21 447.25
16 0 613.15 14.39 233.82 447.25
17 0 193.1 2.07 0 447.25
18 0 31.93 0 0 447.25
19 0 13.74 0 0 447.25
20 0 4.61 0 0 447.25
21 0 0.12 0 0 447.25
22 0 0 0 0 447.25
23 0 0 0 0 25.36
TOTAL 0 7466.48 178.77 4230.04 6527.82

Table C-17. Peak Day Heat Gain – Design A.
0 2 4 6 8 10 12 14 16 18 20 22
0.0 0.0
2500.0
2500.0
5000.0
5000.0
7500.0
7500.0
10000.0
10000.0
Btu/ hr
12500.0
HVAC Load Conduction SolAir Direct Solar Ventilation Internal Inter-Zonal
HOURLY GAINS - Module Monday 24th September (267) - California Climate Zone 8, USA
86
Monday, September 24
th

HOUR HVAC FABRIC SOLAR VENT. INTERN
(Btu) (Btu) (Btu) (Btu) (Btu)
0 0 0 0 0 25.36
1 0 0 0 0 25.36
2 0 0 0 0 25.36
3 0 0 0 0 25.36
4 0 -126.85 0 -123.15 25.36
5 0 -51.06 0 -25.08 25.36
6 0 -5.13 8.3 0 25.36
7 0 5.89 18.15 0 25.36
8 0 229.04 14.78 190.94 38.04
9 0 532.02 14.91 417.48 447.25
10 0 801.23 18.54 606.17 447.25
11 0 901.47 23.46 635.48 447.25
12 0 1032.31 19.45 715.65 447.25
13 0 972.98 15.82 644.01 447.25
14 0 811.65 13.61 488.52 447.25
15 0 688.74 15.3 446.21 447.25
16 0 451.73 14.39 233.82 447.25
17 0 145.78 2.07 0 447.25
18 0 90.85 0 0 447.25
19 0 89.25 0 0 447.25
20 0 43.84 0 0 447.25
21 0 3.96 0 0 447.25
22 0 0 0 0 447.25
23 0 0 0 0 25.36
TOTAL 0 6617.72 178.77 4230.04 6527.82
Table C-18. Peak Day Heat Gain – Design B.
0 2 4 6 8 10 12 14 16 18 20 22
0.0 0.0
2500.0
2500.0
5000.0
5000.0
7500.0
7500.0
10000.0
10000.0
Btu/ hr
12500.0
HVAC Load Conduction SolAir Direct Solar Ventilation Internal Inter-Zonal
HOURLY GAINS - Module Monday 24th September (267) - California Climate Zone 8, USA
87
Monday, September 24
th

HOUR HVAC FABRIC SOLAR VENT. INTERN
(Btu) (Btu) (Btu) (Btu) (Btu)
0 0 0 0 0 25.36
1 0 0 0 0 25.36
2 0 0 0 0 25.36
3 0 0 0 0 25.36
4 0 -126.85 0 -123.15 25.36
5 0 -68.94 0 -25.08 25.36
6 0 -8.88 8.3 0 25.36
7 0 35.78 18.15 0 25.36
8 0 373.92 14.78 190.94 38.04
9 0 761.74 14.91 417.48 447.25
10 0 1028.76 18.54 606.17 447.25
11 0 1055.12 23.46 635.48 447.25
12 0 1082.96 19.45 715.65 447.25
13 0 1000.92 15.82 644.01 447.25
14 0 907.35 13.61 488.52 447.25
15 0 847.29 15.3 446.21 447.25
16 0 618.95 14.39 233.82 447.25
17 0 179.1 2.07 0 447.25
18 0 11.84 0 0 447.25
19 0 0 0 0 447.25
20 0 0 0 0 447.25
21 0 0 0 0 447.25
22 0 0 0 0 447.25
23 0 0 0 0 25.36
TOTAL 0 7699.07 178.77 4230.04 6527.82
Table C-19. Peak Day Heat Gain – Design C.
0 2 4 6 8 10 12 14 16 18 20 22
0.0 0.0
2500.0
2500.0
5000.0
5000.0
7500.0
7500.0
10000.0
10000.0
Btu/ hr
12500.0
HVAC Load Conduction SolAir Direct Solar Ventilation Internal Inter-Zonal
HOURLY GAINS - Module Monday 24th September (267) - California Climate Zone 8, USA
88
Monday, September 24
th

HOUR HVAC FABRIC SOLAR VENT. INTERN
(Btu) (Btu) (Btu) (Btu) (Btu)
0 0 0 0 0 25.36
1 0 0 0 0 25.36
2 0 0 0 0 25.36
3 0 0 0 0 25.36
4 0 -126.85 0 -351.86 25.36
5 0 -34 0 -25.08 25.36
6 0 -1.56 8.3 0 25.36
7 0 -21.36 18.15 0 25.36
8 0 216.02 14.78 190.94 38.04
9 0 499.52 14.91 417.48 447.25
10 0 793.74 18.54 606.17 447.25
11 0 906.26 23.46 635.48 447.25
12 0 1031.84 19.45 715.65 447.25
13 0 957.49 15.82 644.01 447.25
14 0 781.71 13.61 488.52 447.25
15 0 708.04 15.3 446.21 447.25
16 0 525.89 14.39 233.82 447.25
17 0 245.69 2.07 0 447.25
18 0 206.14 0 0 447.25
19 0 101.94 0 0 447.25
20 0 7.3 0 0 447.25
21 0 0 0 0 447.25
22 0 0 0 0 447.25
23 0 0 0 0 25.36
TOTAL 0 6797.83 178.77 4001.33 6527.82
Table C-20. Peak Day Heat Gain – Design D.
0 2 4 6 8 10 12 14 16 18 20 22
0.0 0.0
2500.0
2500.0
5000.0
5000.0
7500.0
7500.0
10000.0
10000.0
Btu/ hr
12500.0
HVAC Load Conduction SolAir Direct Solar Ventilation Internal Inter-Zonal
HOURLY GAINS - Module Monday 24th September (267) - California Climate Zone 8, USA
89
Envelope: Title 24-2001 compliant
Infiltration: Jan-Dec: 0.49 ACH – all hours.
Comfort Band: 67.0 – 82.0°F

TOO
HOT
TOO
COOL TOTAL
MONTH (DegHrs) (DegHrs) (DegHrs)
Jan 0 3541 3541
Feb 0 2615 2615
Mar 0 2249 2249
Apr 0 1400 1400
May 10 824 834
Jun 9 90 99
Jul 189 31 220
Aug 160 15 175
Sep 197 31 228
Oct 5 442 447
Nov 0 1863 1863
Dec 0 3111 3111
TOTAL 569.4 16212.3 16781.7
Table C-21. Discomfort Degree Hours – Baseline Model.

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
kDegHr
0.00 0.00
1.00
1.00
2.00
2.00
3.00
3.00
4.00
4.00
0 0 0 0 0.009716980.00900122
0.189345 0.159776 0.196917
0.00461238 0 0
Too Hot
3.54116
2.61487
2.24907
1.40032
0.824132
0.0897301
0.0309157 0.0151812 0.0312297
0.441908
1.86286
3.11091
Too Cool
DISCOMFORT DEGREE HOURS - Module California Climate Zone 8, USA
90
Envelope: Title 24-2001 compliant + 4" concrete ceiling panels
Infiltration: Jan-Dec: 0.49 ACH – all hours.
Comfort Band: 67.0 – 82.0°F

TOO
HOT
TOO
COOL TOTAL
MONTH (DegHrs) (DegHrs) (DegHrs)
Jan 0 3534 3534 -0.2% Heating Degree Hours
Feb 0 2602 2602 -0.5% Heating Degree Hours
Mar 0 2242 2242 -0.3% Heating Degree Hours
Apr 0 1329 1329 -5.1% Heating Degree Hours
May 0 750 750 -9.0% Heating Degree Hours
Jun 0 54 54 -40.0% Heating Degree Hours
Jul 106 6 112 -43.9% Cooling Degree Hours
Aug 88 9 97 -45.0% Cooling Degree Hours
Sep 125 13 138 -36.5% Cooling Degree Hours
Oct 0 345 345 -21.9% Heating Degree Hours
Nov 0 1783 1783 -4.3% Heating Degree Hours
Dec 0 3076 3076 -1.1% Heating Degree Hours
TOTAL 318.7 15743.7 16062.4 -4.3% Total Degree Hours
Table C-22. Discomfort Degree Hours – Design Model A (Thermal Mass).

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
kDegHr
0.00 0.00
1.00
1.00
2.00
2.00
3.00
3.00
4.00
4.00
0 0 0 0 0.000291626 0
0.106023 0.0877447 0.124642
9.45091e-06 0 0
Too Hot
3.53413
2.60197
2.24207
1.3293
0.749923
0.0538338
0.006337190.00879421 0.0131563
0.344658
1.78335
3.07618
Too Cool
DISCOMFORT DEGREE HOURS - Module California Climate Zone 8, USA
91
Envelope: Title 24-2001 compliant + 4" concrete ceiling panels
Infiltration: Oct-Jun: 0.35 ACH – All hours. Jul-Sep: 0.35 ACH – 3am-8pm, 1.00 ACH – 9pm-2am.
Comfort Band: 67.0 – 82.0°F

TOO
HOT
TOO
COOL TOTAL
MONTH (DegHrs) (DegHrs) (DegHrs)
Jan 0 3408 3408 -3.8% Heating Degree Hours
Feb 0 2472 2472 -5.5% Heating Degree Hours
Mar 0 2097 2097 -6.8% Heating Degree Hours
Apr 0 1214 1214 -13.3% Heating Degree Hours
May 1 665 666 -19.3% Heating Degree Hours
Jun 0 40 40 -55.6% Heating Degree Hours
Jul 89 17 106 -52.9% Cooling Degree Hours
Aug 71 12 83 -55.6% Cooling Degree Hours
Sep 109 20 129 -44.7% Cooling Degree Hours
Oct 0 288 288 -34.8% Heating Degree Hours
Nov 0 1663 1663 -10.7% Heating Degree Hours
Dec 0 2939 2939 -5.5% Heating Degree Hours
TOTAL 269.3 14834.8 15104.2 -10.0% Total Degree Hours
Table C-23. Discomfort Degree Hours – Design Model A (Thermal Mass + Night Ventilation).

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
kDegHr
0.00 0.00
1.00
1.00
2.00
2.00
3.00
3.00
4.00
4.00
0 0 0 0 0.00102732 0
0.0885179 0.0712776 0.108506
000
Too Hot
3.40797
2.47229
2.09699
1.21357
0.664854
0.0401685 0.0174832 0.0115838 0.0202536
0.288208
1.6628
2.93867
Too Cool
DISCOMFORT DEGREE HOURS - Module California Climate Zone 8, USA
92
Envelope: Title 24-2001 compliant + 4" concrete wall panels
Infiltration: Jan-Dec: 0.49 ACH – all hours.
Comfort Band: 67.0 – 82.0°F

TOO
HOT
TOO
COOL TOTAL
MONTH (DegHrs) (DegHrs) (DegHrs)
Jan 0 3600 3600 1.7% Heating Degree Hours
Feb 0 2660 2660 1.7% Heating Degree Hours
Mar 0 2348 2348 4.4% Heating Degree Hours
Apr 0 1348 1348 -3.7% Heating Degree Hours
May 0 741 741 -10.1% Heating Degree Hours
Jun 0 41 41 -54.4% Heating Degree Hours
Jul 45 2 47 -76.2% Cooling Degree Hours
Aug 36 5 42 -77.5% Cooling Degree Hours
Sep 70 5 76 -64.5% Cooling Degree Hours
Oct 0 302 302 -31.7% Heating Degree Hours
Nov 0 1768 1768 -5.1% Heating Degree Hours
Dec 0 3117 3117 0.2% Heating Degree Hours
TOTAL 151.7 15937.3 16089.1 -4.1% Total Degree Hours
Table C-24. Discomfort Degree Hours – Design Model B (Thermal Mass).
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
kDegHr
0.00 0.00
1.00
1.00
2.00
2.00
3.00
3.00
4.00
4.00
0 000 0 0 0.0451357 0.0363268 0.0702455
000
Too Hot
3.60037
2.65984
2.34831
1.34777
0.74073
0.0406193 0.001946920.005487270.00527403
0.301708
1.7683
3.117
Too Cool
DISCOMFORT DEGREE HOURS - Module California Climate Zone 8, USA
93
Envelope: Title 24-2001 compliant + 4" concrete wall panels
Infiltration: Oct-Jun: 0.35 ACH – All hours. Jul-Sep: 0.35 ACH – 3am-8pm, 1.00 ACH – 9pm-2am.
Comfort Band: 67.0 – 82.0°F

TOO
HOT
TOO
COOL TOTAL
MONTH (DegHrs) (DegHrs) (DegHrs)
Jan 0 3479 3479 -1.8% Heating Degree Hours
Feb 0 2537 2537 -3.0% Heating Degree Hours
Mar 0 2209 2209 -1.8% Heating Degree Hours
Apr 0 1239 1239 -11.5% Heating Degree Hours
May 0 656 656 -20.4% Heating Degree Hours
Jun 0 29 29 -67.8% Heating Degree Hours
Jul 36 6 41 -81.0% Cooling Degree Hours
Aug 27 7 34 -83.1% Cooling Degree Hours
Sep 60 10 70 -69.5% Cooling Degree Hours
Oct 0 250 250 -43.4% Heating Degree Hours
Nov 0 1650 1650 -11.4% Heating Degree Hours
Dec 0 2981 2981 -4.2% Heating Degree Hours
TOTAL 122.5 15051.5 15174 -9.6% Total Degree Hours
Table C-25. Discomfort Degree Hours – Design Model B (Thermal Mass + Night Ventilation).

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
kDegHr
0.00 0.00
1.00
1.00
2.00
2.00
3.00
3.00
4.00
4.00
00 00 00 0.0356032 0.0272158 0.0596693
000
Too Hot
3.47851
2.53657
2.20881
1.2385
0.656131
0.0291789 0.005550430.00713093 0.0101686
0.249938
1.64974
2.98125
Too Cool
DISCOMFORT DEGREE HOURS - Module California Climate Zone 8, USA
94
Envelope: Title 24-2001 compliant + 4" concrete floor slab
Infiltration: Jan-Dec: 0.49 ACH – all hours.
Comfort Band: 67.0 – 82.0°F

TOO
HOT
TOO
COOL TOTAL
MONTH (DegHrs) (DegHrs) (DegHrs)
Jan 0 3515 3515 -0.7% Heating Degree Hours
Feb 0 2578 2578 -1.4% Heating Degree Hours
Mar 0 2219 2219 -1.3% Heating Degree Hours
Apr 0 1281 1281 -8.5% Heating Degree Hours
May 0 705 705 -14.4% Heating Degree Hours
Jun 0 39 39 -56.7% Heating Degree Hours
Jul 80 2 82 -57.7% Cooling Degree Hours
Aug 63 6 69 -60.6% Cooling Degree Hours
Sep 100 6 106 -49.2% Cooling Degree Hours
Oct 0 294 294 -33.5% Heating Degree Hours
Nov 0 1734 1734 -6.9% Heating Degree Hours
Dec 0 3052 3052 -1.9% Heating Degree Hours
TOTAL 243.2 15430.1 15673.3 -6.6% Total Degree Hours
Table C-26. Discomfort Degree Hours – Design Model C (Thermal Mass).
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
kDegHr
0.00 0.00
1.00
1.00
2.00
2.00
3.00
3.00
4.00
4.00
00 00 00
0.0798912 0.0631253 0.100193
000
Too Hot
3.51511
2.57781
2.21922
1.28096
0.705442
0.0385214 0.001987050.005584920.00564782
0.294068
1.73412
3.05167
Too Cool
DISCOMFORT DEGREE HOURS - Module California Climate Zone 8, USA
95
Envelope: Title 24-2001 compliant + 4" concrete floor slab
Infiltration: Oct-Jun: 0.35 ACH – All hours. Jul-Sep: 0.35 ACH – 3am-8pm, 1.00 ACH – 9pm-2am.
Comfort Band: 67.0 – 82.0°F

TOO
HOT
TOO
COOL TOTAL
MONTH (DegHrs) (DegHrs) (DegHrs)
Jan 0 3388 3388 -4.3% Heating Degree Hours
Feb 0 2448 2448 -6.4% Heating Degree Hours
Mar 0 2073 2073 -7.8% Heating Degree Hours
Apr 0 1168 1168 -16.6% Heating Degree Hours
May 0 621 621 -24.6% Heating Degree Hours
Jun 0 27 27 -70.0% Heating Degree Hours
Jul 66 5 72 -65.1% Cooling Degree Hours
Aug 52 7 59 -67.5% Cooling Degree Hours
Sep 88 11 99 -55.3% Cooling Degree Hours
Oct 0 242 242 -45.2% Heating Degree Hours
Nov 0 1613 1613 -13.4% Heating Degree Hours
Dec 0 2912 2912 -6.4% Heating Degree Hours
TOTAL 205.8 14516.1 14721.9 -12.3% Total Degree Hours
Table C-27. Discomfort Degree Hours – Design Model C (Thermal Mass + Night Ventilation).

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
kDegHr
0.00 0.00
1.00
1.00
2.00
2.00
3.00
3.00
4.00
4.00
00 00 00
0.0661624 0.0517898 0.0878855
000
Too Hot
3.38801
2.44809
2.0729
1.16825
0.621068
0.0268263 0.005480380.00726294 0.0108878
0.241695
1.61321
2.91243
Too Cool
DISCOMFORT DEGREE HOURS - Module California Climate Zone 8, USA
96
Envelope: Title 24-2001 compliant + 2" concrete ceiling and wall panels
Infiltration: Jan-Dec: 0.49 ACH – all hours.
Comfort Band: 67.0 – 82.0°F

TOO
HOT
TOO
COOL TOTAL
MONTH (DegHrs) (DegHrs) (DegHrs)
Jan 0 3566 3566 0.7% Heating Degree Hours
Feb 0 2623 2623 0.3% Heating Degree Hours
Mar 0 2300 2300 2.3% Heating Degree Hours
Apr 0 1303 1303 -6.9% Heating Degree Hours
May 0 706 706 -14.3% Heating Degree Hours
Jun 0 32 32 -64.4% Heating Degree Hours
Jul 41 1 42 -78.3% Cooling Degree Hours
Aug 31 4 35 -80.6% Cooling Degree Hours
Sep 65 3 68 -67.0% Cooling Degree Hours
Oct 0 274 274 -38.0% Heating Degree Hours
Nov 0 1730 1730 -7.1% Heating Degree Hours
Dec 0 3087 3087 -0.8% Heating Degree Hours
TOTAL 136.9 15628.3 15765.3 -6.1% Total Degree Hours
Table C-28. Discomfort Degree Hours – Design Model D (Thermal Mass).
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
kDegHr
0.00 0.00
1.00
1.00
2.00
2.00
3.00
3.00
4.00
4.00
00 00 00 0.0410928 0.0309941 0.0648439
000
Too Hot
3.5655
2.62331
2.30046
1.30252
0.70569
0.0318138 0.000655729 0.003820940.00305154
0.274248
1.7302
3.08707
Too Cool
DISCOMFORT DEGREE HOURS - Module California Climate Zone 8, USA
97
Envelope: Title 24-2001 compliant + 2" concrete ceiling and wall panels
Infiltration: Oct-Jun: 0.35 ACH – All hours. Jul-Sep: 0.35 ACH – 5am-8pm, 1.00 ACH – 9pm-4am.
Comfort Band: 67.0 – 82.0°F

TOO
HOT
TOO
COOL TOTAL
MONTH (DegHrs) (DegHrs) (DegHrs)
Jan 0 3442 3442 -2.8% Heating Degree Hours
Feb 0 2498 2498 -4.5% Heating Degree Hours
Mar 0 2157 2157 -4.1% Heating Degree Hours
Apr 0 1193 1193 -14.8% Heating Degree Hours
May 0 620 620 -24.8% Heating Degree Hours
Jun 0 21 21 -76.7% Heating Degree Hours
Jul 29 4 33 -84.7% Cooling Degree Hours
Aug 20 7 27 -87.5% Cooling Degree Hours
Sep 52 9 60 -73.6% Cooling Degree Hours
Oct 0 226 226 -48.9% Heating Degree Hours
Nov 0 1611 1611 -13.5% Heating Degree Hours
Dec 0 2950 2950 -5.2% Heating Degree Hours
TOTAL 100.5 14737.7 14838.1 -11.6% Total Degree Hours
Table C-29. Discomfort Degree Hours – Design Model D (Thermal Mass + Night Ventilation).

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
kDegHr
0.00 0.00
1.00
1.00
2.00
2.00
3.00
3.00
4.00
4.00
00 00 00 0.0287192 0.0201806 0.0515663
000
Too Hot
3.4417
2.49804
2.1569
1.19288
0.620467
0.0213485 0.0044821 0.006575120.00851528
0.225623
1.61145
2.94967
Too Cool
DISCOMFORT DEGREE HOURS - Module California Climate Zone 8, USA
98
Envelope: Title 24-2001 compliant

Fig. C-21. Fabric (Envelope) Gains – Baseline.

Infiltration: 0.49 ACH – all hours

Fig. C-22. Ventilation Gains – Baseline.

02
04
06
08
10
12
14
16
18
20
22
Hr
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
-3181.89
-3234.37
-3301.33
-3409.87
-3420.83
-3516.9
-3494.16
-3179.27
-2034.06
-1091.74
-568.44
-229.863
-118.112
-195.403
-81.1276
-218.843
-739.051
-1500.37
-2305.03
-2614.39
-2827.99
-2916.82
-2972.53
-3038.36
-2958.4
-3021.85
-3091.72
-3161.86
-3206.81
-3336.62
-3277.51
-2742.16
-1606.86
-709.184
-226.467
94.1941
167.561
53.4981
213.41
151.471
-173.977
-917.737
-1860.48
-2270.7
-2539.71
-2678.63
-2757.2
-2825.61
-2628.47
-2725.03
-2882.1
-2962.27
-3066.18
-3104.46
-2899.04
-2075.03
-1166.91
-455.42
-22.3547
155.929
185.841
79.2694
281.728
311.048
101.669
-521.854
-1393.35
-2018.04
-2274.38
-2455.34
-2564.54
-2633.15
-2420.16
-2447.74
-2519.42
-2602.75
-2456.51
-2244.12
-1955.92
-1203.04
-486.497
38.7173
322.832
462.413
453.839
328.924
468.602
534.478
355.482
-91.4291
-823.47
-1544.47
-1800.76
-2074.22
-2258.91
-2331.46
-1792.73
-1817.07
-1868.02
-1931
-1813.02
-1619.8
-1355.29
-747.885
-216.294
172.844
422.039
548.405
557.938
493.762
649.407
752.042
621.8
265.986
-401.575
-920.224
-1161.51
-1388.03
-1575.35
-1686.91
-1080.4
-1135.56
-1222.13
-1221.37
-1206.21
-890.281
-522.675
-85.9527
258.457
447.642
619.064
777.364
744.048
676.105
827.189
896.766
869.63
814.917
472.21
-242.555
-649.753
-840.881
-973.213
-1040.33
-746.718
-763.204
-806.393
-861.286
-740.566
-602.621
-462.285
163.422
601.279
887.621
1048.16
1155.65
1173.44
951.574
1035.6
1085.02
994.166
873.918
551.939
1.21439
-256.498
-433.589
-588.751
-676.173
-654.091
-669.007
-669.628
-694.427
-687.497
-681.903
-536.36
-216.511
126.874
518.267
1032.9
1270.07
1203.83
1067.82
1184.12
1142.39
1029.48
749.595
302.996
-201.032
-306.7
-390.869
-490.321
-580.833
-745.155
-782.38
-844.3
-899.768
-918.004
-938.047
-718.322
-286.747
257.001
660.289
983.497
1109.64
1107.24
1050.49
1172.76
1167.89
988.07
463.204
-36.9084
-287.27
-397.636
-517.962
-617.659
-668.003
-1484.94
-1556.38
-1647.76
-1656.97
-1724.3
-1740.43
-1304.55
-618.972
-6.25056
449.68
676.778
719.681
653.486
665.128
754.271
672.123
314.147
-240.008
-777.652
-1001.53
-1174.91
-1286.79
-1369.39
-1433.8
-2539.2
-2609.78
-2723.4
-2768.89
-2752.95
-2767.81
-2530.95
-1661.11
-801.88
-187.655
227.212
407.655
359.53
350.493
362.603
140.945
-433.99
-1110.37
-1747.28
-2071.22
-2282.79
-2430.39
-2513.74
-2561.37
-3156.06
-3245.29
-3359.46
-3487.43
-3541.85
-3567.55
-3596.5
-3017.59
-1973.18
-963.887
-370.153
-16.9899
84.9763
14.0742
87.1046
29.7164
-468.28
-1253.36
-1980.68
-2274.38
-2452.95
-2643.5
-2827.05
-2995.7
Watts
4000
3200
2400
1600
800
0
-800
-1600
-2400
-3200
-4000
Fabric Gains - Qc + Qs - Module California Climate Zone 8, USA
02
04
06
08
10
12
14
16
18
20
22
Hr
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
-3058.89
-3090.39
-3174.6
-3335.51
-3308.77
-3497.92
-3368.95
-2913.87
-2048.72
-1466.3
-1065.03
-781.514
-640.887
-607.235
-649.86
-959.235
-1489.63
-2017.03
-2385.01
-2700.46
-2910.98
-2970.01
-3027.09
-2942.21
-3080.7
-3161.25
-3217.29
-3325.09
-3324
-3543.86
-3391.29
-2667.05
-1874.55
-1244.04
-868.234
-519.785
-429.402
-384.789
-401.005
-659.733
-1039.5
-1586.19
-2139.26
-2476.04
-2725.4
-2831.59
-2902.73
-2966.47
-2591.4
-2740.46
-2960.72
-3015.76
-3141.42
-3144.73
-2766.46
-2064.97
-1474.44
-1010.99
-668.257
-527.339
-401.029
-378.682
-370.894
-514.228
-811.568
-1408.2
-1812.48
-2083.59
-2298.39
-2464.15
-2581.49
-2643.59
-2520.5
-2542.34
-2603.22
-2643.2
-2405.52
-2168.97
-1903.05
-1313.1
-822.898
-465.8
-311.323
-173.678
-99.9424
-144.411
-174.74
-232.961
-530.095
-929.567
-1443.83
-1684.68
-1937.81
-2197.41
-2373.32
-2430.44
-1795.86
-1846.53
-1914.55
-1984.68
-1782.97
-1556.26
-1317.45
-933.753
-552.449
-303.291
-181.053
-91.4548
4.05687
-15.0352
-31.0738
-47.9418
-291.17
-594.813
-953.071
-1084.84
-1252.54
-1445.33
-1620.67
-1719.51
-1117.62
-1182.25
-1265.93
-1226.6
-1238.53
-795.994
-520.124
-306.544
-88.3681
-16.5016
68.9536
130.76
137.163
188.515
110.868
55.4322
-17.958
-88.9469
-323.383
-544.349
-739.278
-920.003
-1018.34
-1104.01
-750.325
-774.517
-823.062
-874.109
-697.789
-573.289
-463.288
-129.567
32.593
220.09
297.012
408.457
588.77
430.478
316.67
241.486
62.6952
10.3858
-68.764
-156.076
-301.657
-477.178
-620.208
-688.4
-625.744
-630.187
-652.296
-697.615
-667.426
-668.463
-520.955
-265.627
-92.4631
96.1722
365.412
552.15
587.294
595.116
466.118
248.458
137.375
13.367
-116.046
-242.518
-329.701
-394.641
-499.87
-583.188
-713.023
-736.49
-825.919
-857.543
-875.286
-908.115
-615.507
-284.947
-23.0102
206.686
448.086
516.324
633.072
625.338
567.996
422.306
271.167
-49.5188
-193.218
-325.423
-428.951
-547.036
-632.833
-653.058
-1509.91
-1603.15
-1695.58
-1689.88
-1790.57
-1767.78
-1192.75
-582.406
-238.013
-12.6678
74.5148
142.003
147.645
205.054
83.3664
-47.9478
-317.827
-586.098
-858.687
-1070.66
-1245.82
-1337.13
-1398.39
-1479.14
-2564.11
-2701.83
-2782.43
-2778.35
-2810.25
-2825.19
-2523.89
-1462.81
-1013.69
-605.851
-316.551
-186.985
-149.347
-136.696
-312.168
-574.857
-1053.34
-1434.96
-1923.35
-2165.05
-2331.11
-2461.06
-2548.01
-2582.8
-3276.14
-3424.94
-3556.22
-3698.68
-3716.53
-3723.91
-3726.98
-2933.05
-2101.11
-1278.91
-856.449
-532.155
-374.917
-431.359
-481.124
-577.473
-1032.06
-1600.73
-2193.31
-2386.57
-2557.19
-2733.45
-2978.5
-3180
Watts
4000
3200
2400
1600
800
0
-800
-1600
-2400
-3200
-4000
Ventilation Gains - Qv - Module California Climate Zone 8, USA
99
Envelope: Title 24-2001 compliant + 4" concrete ceiling panels

Fig. C-23. Fabric (Envelope) Gains – Design A.

Infiltration: Oct-Jun: 0.35 ACH All hours.
Jul-Sep: 0.35 ACH 3am-8pm, 1.00 ACH 9pm-2am.

Fig. C-24. Ventilation Gains – Design A.

02
04
06
08
10
12
14
16
18
20
22
Hr
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
-3151.17
-3204.16
-3270.59
-3378.52
-3387.53
-3484.49
-3460.01
-3147.16
-2010.9
-1105.64
-612.384
-299.953
-192.653
-262.078
-130.133
-247.059
-736.047
-1463.24
-2248.59
-2563.63
-2788.26
-2884.44
-2942.13
-3008.91
-2929.72
-2993.64
-3062.66
-3132.35
-3176.15
-3305.96
-3244.72
-2711.97
-1594.12
-737.081
-290.476
9.84772
77.9518
-23.9607
146.658
106.806
-186.532
-888.012
-1802.16
-2215.48
-2497.54
-2646.77
-2727.97
-2797.25
-2602.95
-2700.09
-2855.46
-2933.46
-3036.55
-3073.76
-2869.31
-2050.57
-1170.46
-497.63
-96.165
64.7697
95.0266
-0.271316
206.432
252.702
70.5164
-510.771
-1340.35
-1957.58
-2225.7
-2422.42
-2536.92
-2606.07
-2396.49
-2425.13
-2496.55
-2578.64
-2431.07
-2222.48
-1938.18
-1193.44
-505.116
-11.6339
244.018
368.273
358.046
244.153
395.003
477.428
322.145
-87.8833
-783.609
-1488.09
-1756.08
-2042.59
-2233.96
-2305.7
-1774.13
-1799.71
-1850.78
-1913.13
-1794.12
-1603.98
-1343.07
-745.994
-234.95
125.893
348.105
452.667
456.536
399.731
564.121
683.223
577.619
264.299
-359.216
-866.158
-1121.52
-1365.36
-1557.83
-1668.04
-1069.13
-1125.01
-1210.78
-1208.84
-1194.18
-878.905
-518.707
-92.054
235.634
405.022
551.277
676.218
627.918
565.486
726.777
817.688
819.644
804.329
497.154
-195.155
-610.781
-815.945
-959.48
-1027.8
-738.188
-755.659
-798.954
-853.286
-731.667
-596.739
-458.736
157.34
568.016
820.049
947.768
1029.96
1044.84
833.01
935.22
1008.3
946.017
865.689
583.375
49.4738
-221.935
-416.47
-580.521
-667.207
-646.444
-662.079
-662.975
-688.204
-680.716
-675.59
-530.019
-214.451
115.036
478.435
941.209
1137.28
1060.96
937.347
1078.88
1063.52
993.847
757.22
347.364
-153.784
-276.785
-378.08
-484.502
-574.17
-737.153
-775.017
-836.393
-891.09
-908.497
-928.766
-709.099
-283.672
239.085
614.083
906.693
1007.19
998.805
949.965
1090.92
1108.47
966.203
483.603
7.49171
-251.218
-378.17
-509.723
-610.174
-659.96
-1469.85
-1541.83
-1632.12
-1640.39
-1708.01
-1723.26
-1288.16
-612.026
-20.4599
404.664
604.156
632.846
561.46
582.02
686.438
635.794
317.267
-202.815
-734.019
-969.327
-1154.93
-1271.23
-1354.24
-1418.79
-2514.92
-2585.91
-2698.28
-2742.19
-2725.92
-2741.86
-2505.35
-1640.89
-803.942
-218.509
167.251
328.321
276.956
278.188
312.977
123.165
-415.15
-1065.82
-1702.05
-2032.96
-2253.13
-2402.49
-2487.16
-2535.5
-3124.15
-3214.46
-3327.7
-3454.79
-3507.09
-3533.15
-3562.47
-2983.97
-1955.32
-978.419
-416.976
-84.728
14.039
-49.3553
42.9637
11.9859
-452.913
-1214.18
-1936.89
-2233.67
-2420.78
-2613.95
-2798.59
-2965.63
Watts
4000
3200
2400
1600
800
0
-800
-1600
-2400
-3200
-4000
Fabric Gains - Qc + Qs - Module California Climate Zone 8, USA
02
04
06
08
10
12
14
16
18
20
22
Hr
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
-2297.86
-2326.22
-2386.68
-2500.08
-2475.47
-2624.84
-2532.74
-2187.26
-1462.1
-1046.52
-759.748
-557.368
-457.249
-432.911
-463.33
-684.116
-1062.65
-1438.85
-1701.58
-1926.65
-2076.89
-2119.5
-2160.28
-2184.62
-2200.5
-2258.04
-2298.06
-2375.07
-2374.29
-2531.33
-2422.35
-1905.04
-1338.96
-888.603
-620.167
-371.275
-306.715
-274.849
-286.432
-471.238
-742.497
-1132.99
-1528.04
-1768.6
-1946.72
-2022.57
-2073.38
-2118.91
-1851
-1957.47
-2114.8
-2154.12
-2243.87
-2246.24
-1976.04
-1474.98
-1053.17
-722.139
-477.326
-376.671
-286.449
-270.487
-264.924
-367.306
-579.691
-1005.86
-1294.63
-1488.28
-1641.71
-1760.11
-1843.92
-1888.28
-1800.36
-1815.96
-1859.44
-1888
-1718.22
-1549.27
-1359.32
-937.925
-587.784
-332.714
-222.373
-124.055
-71.3874
-103.151
-124.814
-166.401
-378.639
-663.976
-1031.31
-1203.34
-1384.15
-1569.58
-1695.23
-1736.03
-1282.76
-1318.95
-1367.53
-1417.63
-1273.55
-1111.61
-941.037
-666.966
-394.606
-216.637
-129.324
-65.3249
2.89777
-10.7394
-22.1956
-34.2441
-207.979
-424.866
-680.765
-774.886
-894.67
-1032.38
-1157.62
-1228.22
-832.05
-880.758
-942.704
-876.14
-884.664
-568.567
-371.517
-218.96
-63.1201
-11.7869
49.2526
93.4001
97.9735
134.653
79.1914
39.5944
-12.8271
-63.5335
-230.988
-388.82
-528.055
-718.052
-795.012
-857.97
-1531.28
-1580.65
-1679.72
-624.364
-498.421
-409.492
-330.92
-92.5476
23.2807
157.207
212.151
291.755
420.55
307.484
226.193
172.49
44.7823
7.41845
-49.1172
-111.483
-215.469
-973.832
-1265.73
-1404.9
-1277.03
-1286.1
-1331.22
-498.296
-476.733
-477.474
-372.111
-189.733
-66.0451
68.6944
261.008
394.393
419.495
425.083
332.942
177.47
98.1252
9.54784
-82.8898
-173.227
-235.501
-805.39
-1020.14
-1190.18
-1433.57
-1479.45
-1661.09
-612.531
-625.204
-648.653
-439.648
-203.534
-16.4359
147.633
320.061
368.803
452.194
446.67
405.711
301.647
193.691
-35.3706
-138.013
-232.445
-306.394
-1116.4
-1291.5
-1332.77
-1078.51
-1145.11
-1211.13
-1207.06
-1278.98
-1262.7
-851.962
-416.004
-170.009
-9.04844
53.2248
101.43
105.461
146.467
59.5474
-34.2484
-227.019
-418.642
-613.348
-764.761
-889.87
-955.09
-998.848
-1056.53
-1831.51
-1929.88
-1987.45
-1984.53
-2007.32
-2017.99
-1802.78
-1044.87
-724.065
-432.75
-226.108
-133.561
-106.677
-97.64
-222.977
-410.612
-752.382
-1024.97
-1373.82
-1546.46
-1665.08
-1757.9
-1820.01
-1844.86
-2340.1
-2446.38
-2540.16
-2641.92
-2654.67
-2659.94
-2662.13
-2095.04
-1500.79
-913.506
-611.749
-380.11
-267.798
-308.113
-343.66
-412.48
-737.183
-1143.38
-1566.65
-1704.7
-1826.56
-1952.46
-2127.5
-2271.43
Watts
4000
3200
2400
1600
800
0
-800
-1600
-2400
-3200
-4000
Ventilation Gains - Qv - Module California Climate Zone 8, USA
100
Envelope: Title 24-2001 compliant + 4" concrete wall panels

Fig. C-25. Fabric (Envelope) Gains – Design B.

Infiltration: Oct-Jun: 0.35 ACH – All hours.
Jul-Sep: 0.35 ACH – 3am-8pm, 1.00 ACH – 9pm-2am.

Fig. C-26. Ventilation Gains – Design B.

02
04
06
08
10
12
14
16
18
20
22
Hr
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
-2805.38
-2863.74
-2924.07
-3025.2
-3012.78
-3119.31
-3075.6
-2784.76
-1984.06
-1367.69
-946.692
-491.549
-182.718
-95.2405
-116.218
-399.84
-955.171
-1449.23
-1840.92
-2076.3
-2322.77
-2523.62
-2601.65
-2677.97
-2607.07
-2675.93
-2735.35
-2799.8
-2831.05
-2960.6
-2875.83
-2375.37
-1680.28
-1112.67
-718.297
-192.575
75.6102
153.513
157.07
-74.8767
-500.015
-1021.87
-1500.45
-1747.55
-2026.35
-2281.38
-2401.43
-2479.24
-2315.89
-2419.05
-2555.66
-2609.63
-2703.77
-2728.91
-2534.46
-1990.47
-1404.16
-911.942
-431.211
-106.587
120.684
170.062
204.855
30.8741
-314.637
-811.682
-1249.93
-1501.94
-1726.78
-2011.8
-2228.75
-2302.86
-2130.33
-2170.12
-2238.49
-2306.98
-2144.86
-1977.82
-1801.92
-1307.62
-811.262
-397.388
-66.8546
210.399
374.076
367.126
348.777
235.225
-70.3852
-409.77
-863.959
-1093.37
-1324
-1638.63
-1956.51
-2018.55
-1565.83
-1604.42
-1656.45
-1711.8
-1581.44
-1424.88
-1258.98
-908.687
-528.654
-211.555
83.6236
307.416
471.145
500.125
496.779
413.24
151.897
-125.603
-466.806
-602.227
-760.102
-1060.89
-1341.82
-1458.18
-943.005
-1006.33
-1083.17
-1068.21
-1059.03
-750.683
-532.476
-330.784
-111.665
70.4118
314.102
526.308
631.567
689.855
668.004
547.189
370.163
279.996
56.9156
-162.224
-283.341
-463.012
-744.126
-888.995
-643.205
-670.999
-715.239
-763.324
-631.85
-529.896
-446.671
-169.351
56.6093
316.423
616.608
887.787
1074.36
987.15
886.298
726.358
470.697
371.279
239.16
136.744
33.6044
-168.557
-452.666
-568.579
-561.411
-584.584
-588.213
-617.995
-604.39
-604.336
-501.73
-293.899
-98.7718
143.904
541.791
849.299
993.61
1086.47
999.153
739.928
499.717
355.898
196.215
66.1164
-37.2645
-193.315
-420.171
-500.471
-647.723
-692.274
-747.593
-793.71
-802.047
-824.625
-606.297
-322.127
-55.5089
203.162
519.464
773.609
963.601
1005.65
958.119
762.849
526.034
231.483
84.6031
-24.6001
-176.654
-398.901
-527.625
-570.882
-1300.57
-1378.28
-1456.39
-1454.22
-1524.94
-1530.23
-1103.36
-618.938
-291.656
-26.6144
226.527
453.734
592.426
664.134
555.715
336.408
1.28252
-256.528
-499.693
-684.793
-912.242
-1099.01
-1185.71
-1251
-2241.46
-2316.75
-2415.37
-2441.77
-2421.9
-2449.45
-2216.37
-1450.44
-974.51
-568.765
-205.39
147.978
302.244
363.842
219.351
-103.927
-593.406
-949.793
-1365.64
-1633.74
-1900.68
-2092.64
-2190.1
-2245.45
-2766.16
-2867.77
-2970.33
-3087.45
-3116.51
-3146.11
-3179.07
-2604.74
-1921.6
-1210.54
-761.785
-285.441
-0.771901
43.8893
0.246377
-158.257
-612.414
-1104.49
-1602.75
-1805.97
-2047.86
-2285.67
-2480.17
-2628.99
Watts
4000
3200
2400
1600
800
0
-800
-1600
-2400
-3200
-4000
Fabric Gains - Qc + Qs - Module California Climate Zone 8, USA
02
04
06
08
10
12
14
16
18
20
22
Hr
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
-2297.86
-2326.22
-2386.68
-2500.08
-2475.47
-2624.84
-2532.74
-2187.26
-1462.1
-1046.52
-759.748
-557.368
-457.249
-432.911
-463.33
-684.116
-1062.65
-1438.85
-1701.58
-1926.65
-2076.89
-2119.5
-2160.28
-2184.62
-2200.5
-2258.04
-2298.06
-2375.07
-2374.29
-2531.33
-2422.35
-1905.04
-1338.96
-888.603
-620.167
-371.275
-306.715
-274.849
-286.432
-471.238
-742.497
-1132.99
-1528.04
-1768.6
-1946.72
-2022.57
-2073.38
-2118.91
-1851
-1957.47
-2114.8
-2154.12
-2243.87
-2246.24
-1976.04
-1474.98
-1053.17
-722.139
-477.326
-376.671
-286.449
-270.487
-264.924
-367.306
-579.691
-1005.86
-1294.63
-1488.28
-1641.71
-1760.11
-1843.92
-1888.28
-1800.36
-1815.96
-1859.44
-1888
-1718.22
-1549.27
-1359.32
-937.925
-587.784
-332.714
-222.373
-124.055
-71.3874
-103.151
-124.814
-166.401
-378.639
-663.976
-1031.31
-1203.34
-1384.15
-1569.58
-1695.23
-1736.03
-1282.76
-1318.95
-1367.53
-1417.63
-1273.55
-1111.61
-941.037
-666.966
-394.606
-216.637
-129.324
-65.3249
2.89777
-10.7394
-22.1956
-34.2441
-207.979
-424.866
-680.765
-774.886
-894.67
-1032.38
-1157.62
-1228.22
-832.05
-880.758
-942.704
-876.14
-884.664
-568.567
-371.517
-218.96
-63.1201
-11.7869
49.2526
93.4001
97.9735
134.653
79.1914
39.5944
-12.8271
-63.5335
-230.988
-388.82
-528.055
-718.052
-795.012
-857.97
-1531.28
-1580.65
-1679.72
-624.364
-498.421
-409.492
-330.92
-92.5476
23.2807
157.207
212.151
291.755
420.55
307.484
226.193
172.49
44.7823
7.41845
-49.1172
-111.483
-215.469
-973.832
-1265.73
-1404.9
-1277.03
-1286.1
-1331.22
-498.296
-476.733
-477.474
-372.111
-189.733
-66.0451
68.6944
261.008
394.393
419.495
425.083
332.942
177.47
98.1252
9.54784
-82.8898
-173.227
-235.501
-805.39
-1020.14
-1190.18
-1433.57
-1479.45
-1661.09
-612.531
-625.204
-648.653
-439.648
-203.534
-16.4359
147.633
320.061
368.803
452.194
446.67
405.711
301.647
193.691
-35.3706
-138.013
-232.445
-306.394
-1116.4
-1291.5
-1332.77
-1078.51
-1145.11
-1211.13
-1207.06
-1278.98
-1262.7
-851.962
-416.004
-170.009
-9.04844
53.2248
101.43
105.461
146.467
59.5474
-34.2484
-227.019
-418.642
-613.348
-764.761
-889.87
-955.09
-998.848
-1056.53
-1831.51
-1929.88
-1987.45
-1984.53
-2007.32
-2017.99
-1802.78
-1044.87
-724.065
-432.75
-226.108
-133.561
-106.677
-97.64
-222.977
-410.612
-752.382
-1024.97
-1373.82
-1546.46
-1665.08
-1757.9
-1820.01
-1844.86
-2340.1
-2446.38
-2540.16
-2641.92
-2654.67
-2659.94
-2662.13
-2095.04
-1500.79
-913.506
-611.749
-380.11
-267.798
-308.113
-343.66
-412.48
-737.183
-1143.38
-1566.65
-1704.7
-1826.56
-1952.46
-2127.5
-2271.43
Watts
4000
3200
2400
1600
800
0
-800
-1600
-2400
-3200
-4000
Ventilation Gains - Qv - Module California Climate Zone 8, USA
101
Envelope: Title 24-2001 compliant + 4" concrete floor slab

Fig. C-27. Fabric (Envelope) Gains – Design C.

Infiltration: Oct-Jun: 0.35 ACH – All hours.
Jul-Sep: 0.35 ACH – 3am-8pm, 1.00 ACH – 9pm-2am.

Fig. C-28. Ventilation Gains – Design C.

02
04
06
08
10
12
14
16
18
20
22
Hr
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
-3181.89
-3234.37
-3301.33
-3409.87
-3420.83
-3516.9
-3494.16
-3179.27
-2034.03
-1091.48
-568.008
-229.362
-117.703
-194.916
-80.626
-218.653
-738.972
-1500.34
-2305.03
-2614.39
-2827.99
-2916.82
-2972.53
-3038.36
-2958.4
-3021.85
-3091.72
-3161.86
-3206.81
-3336.62
-3277.51
-2742.15
-1606.64
-708.872
-225.902
94.7639
168.135
54.099
213.834
151.73
-173.769
-917.616
-1860.46
-2270.7
-2539.71
-2678.63
-2757.2
-2825.61
-2628.47
-2725.03
-2882.1
-2962.27
-3066.18
-3104.46
-2899.04
-2074.73
-1166.1
-454.258
-21.0949
157.41
187.441
80.9093
282.817
311.739
102.213
-521.513
-1393.17
-2018.04
-2274.38
-2455.34
-2564.54
-2633.15
-2420.16
-2447.74
-2519.42
-2602.75
-2456.51
-2244.12
-1955.81
-1201.97
-484.65
41.4861
326.164
465.981
457.252
332.419
471.561
536.862
357.318
-90.0887
-822.804
-1544.47
-1800.76
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-2331.46
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-1931
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-746.333
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176.282
425.989
552.38
561.742
497.554
652.61
754.542
623.686
267.561
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260.939
450.904
622.826
781.084
747.558
679.438
829.963
898.969
871.438
816.407
473.23
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-602.621
-461.942
164.942
603.492
890.345
1051.31
1158.5
1176.22
954.424
1038.07
1087.18
995.896
875.378
553.221
1.54348
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129.049
521.436
1036.11
1273.08
1206.53
1070.34
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751.014
304.041
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258.732
662.579
985.891
1111.85
1109.14
1052.19
1174.17
1169.02
989.261
464.407
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450.629
677.922
720.712
654.184
665.615
754.536
672.336
314.384
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359.796
350.676
362.798
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85.5277
14.4986
87.4438
29.9207
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-1980.68
-2274.38
-2452.95
-2643.5
-2827.05
-2995.7
Watts
4000
3200
2400
1600
800
0
-800
-1600
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-3200
-4000
Fabric Gains - Qc + Qs - Module California Climate Zone 8, USA
02
04
06
08
10
12
14
16
18
20
22
Hr
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
-2297.86
-2326.22
-2386.68
-2500.08
-2475.47
-2624.84
-2532.74
-2187.26
-1462.1
-1046.52
-759.748
-557.368
-457.249
-432.911
-463.33
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-1701.58
-1926.65
-2076.89
-2119.5
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-2298.06
-2375.07
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-471.238
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-1768.6
-1946.72
-2022.57
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-2118.91
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-1957.47
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-2243.87
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-1474.98
-1053.17
-722.139
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-579.691
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-1718.22
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-1695.23
-1736.03
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-1367.53
-1417.63
-1273.55
-1111.61
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2.89777
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49.2526
93.4001
97.9735
134.653
79.1914
39.5944
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23.2807
157.207
212.151
291.755
420.55
307.484
226.193
172.49
44.7823
7.41845
-49.1172
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-1265.73
-1404.9
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-1331.22
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-372.111
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-66.0451
68.6944
261.008
394.393
419.495
425.083
332.942
177.47
98.1252
9.54784
-82.8898
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-1479.45
-1661.09
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-439.648
-203.534
-16.4359
147.633
320.061
368.803
452.194
446.67
405.711
301.647
193.691
-35.3706
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-1116.4
-1291.5
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-1278.98
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53.2248
101.43
105.461
146.467
59.5474
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-2017.99
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-1373.82
-1546.46
-1665.08
-1757.9
-1820.01
-1844.86
-2340.1
-2446.38
-2540.16
-2641.92
-2654.67
-2659.94
-2662.13
-2095.04
-1500.79
-913.506
-611.749
-380.11
-267.798
-308.113
-343.66
-412.48
-737.183
-1143.38
-1566.65
-1704.7
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-2127.5
-2271.43
Watts
4000
3200
2400
1600
800
0
-800
-1600
-2400
-3200
-4000
Ventilation Gains - Qv - Module California Climate Zone 8, USA
102
Envelope: Title 24-2001 compliant + 2" concrete ceiling and wall panels

Fig. C-29. Fabric (Envelope) Gains – Design D.

Infiltration: Oct-Jun: 0.35 ACH – All hours.
Jul-Sep: 0.35 ACH – 5am-8pm, 1.00 ACH – 9pm-4am.

Fig. C-30. Ventilation Gains – Design D.

02
04
06
08
10
12
14
16
18
20
22
Hr
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
-2946.32
-3010.8
-3072.54
-3167.46
-3162.82
-3273.5
-3239.56
-2936.71
-2166.23
-1564.76
-940.61
-420.174
-166.359
-91.1275
-150.045
-471.171
-853.561
-1299.65
-1744.06
-2131.49
-2551.08
-2658.12
-2740.7
-2821.85
-2737.02
-2810.63
-2874.96
-2931.7
-2973.57
-3105
-3022.61
-2523.68
-1865.42
-1303.65
-651.951
-91.86
117.166
151.367
135.678
-156.272
-390.403
-841.818
-1339.98
-1730.41
-2234.34
-2425.73
-2525.25
-2614.95
-2434.22
-2538.06
-2678.45
-2724.23
-2835.47
-2871.82
-2671.39
-2145.24
-1578.11
-934.382
-371.27
-29.8584
158.72
185.335
157.739
-47.0712
-200.643
-623.814
-1042.18
-1377.14
-1851.59
-2222.99
-2340.35
-2423.73
-2248.64
-2282.84
-2348.8
-2414.92
-2256.59
-2101.83
-1934.38
-1410.14
-887.322
-374.862
1.16213
279.959
424.248
383.247
317.888
196.482
48.044
-228.3
-653.156
-950.514
-1334.4
-1878.58
-2039.54
-2116.71
-1653.17
-1690.48
-1740.56
-1791.74
-1664.87
-1516.58
-1358.5
-988.119
-578.159
-152.694
134.565
354.196
513.943
514.642
457.88
384.452
275.696
68.4053
-228.734
-424.701
-785.022
-1217.43
-1418.55
-1520.91
-994.369
-1057.21
-1134.15
-1114.62
-1116.18
-814.916
-592.061
-401.738
-99.6947
168.51
381.954
561.451
652.028
718.882
632.228
494.493
511.553
477.741
287.151
106.32
-118.781
-599.064
-860.269
-930.567
-682.089
-707.95
-751.552
-796.064
-666.75
-572.949
-495.658
-198.164
22.5847
463.513
757.847
955.661
1130.03
1013.99
856.231
686.509
615.236
582.335
492.475
374.31
138.957
-298.771
-510.039
-587.887
-590.942
-618.017
-621.459
-647.459
-636.065
-633.987
-536.718
-327.291
-118.594
154.726
564.872
895.135
1094.39
1136.61
977.013
690.244
686.544
602.396
436.38
233.477
-24.8472
-337.022
-437.928
-520.19
-684.069
-726.414
-783.85
-825.687
-840.105
-867.894
-651.268
-369.822
-126.387
206.181
631.361
853.414
1033.45
1055.8
940.271
770.089
705.205
469.217
292.214
38.4378
-265.858
-456.759
-548.737
-594.681
-1365.83
-1446.01
-1528.05
-1518.66
-1602.93
-1611.81
-1175.62
-715.476
-399.793
-23.5347
316.359
557.127
658.779
670.592
523.673
357.966
185.329
-63.3559
-375.772
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-1036.06
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-2553.6
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-1577.65
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211.846
350.504
380.037
183.035
-86.5547
-433.197
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-1318.51
-1732.82
-2031.93
-2209.65
-2302.41
-2363.2
-2904.7
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-3122.29
-3227.01
-3270.51
-3306.06
-3348.39
-2767.13
-2100.83
-1424.27
-752.834
-229.259
35.2766
49.9421
-25.8561
-174.415
-494.746
-973.16
-1555.52
-1902.34
-2184.76
-2424.99
-2593.98
-2750.07
Watts
4000
3200
2400
1600
800
0
-800
-1600
-2400
-3200
-4000
Fabric Gains - Qc + Qs - Module California Climate Zone 8, USA
02
04
06
08
10
12
14
16
18
20
22
Hr
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
-2297.86
-2326.22
-2386.68
-2500.08
-2475.47
-2624.84
-2532.74
-2187.26
-1462.1
-1046.52
-759.748
-557.368
-457.249
-432.911
-463.33
-684.116
-1062.65
-1438.85
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-2119.5
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-2200.5
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-2374.29
-2531.33
-2422.35
-1905.04
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-2118.91
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-2114.8
-2154.12
-2243.87
-2246.24
-1976.04
-1474.98
-1053.17
-722.139
-477.326
-376.671
-286.449
-270.487
-264.924
-367.306
-579.691
-1005.86
-1294.63
-1488.28
-1641.71
-1760.11
-1843.92
-1888.28
-1800.36
-1815.96
-1859.44
-1888
-1718.22
-1549.27
-1359.32
-937.925
-587.784
-332.714
-222.373
-124.055
-71.3874
-103.151
-124.814
-166.401
-378.639
-663.976
-1031.31
-1203.34
-1384.15
-1569.58
-1695.23
-1736.03
-1282.76
-1318.95
-1367.53
-1417.63
-1273.55
-1111.61
-941.037
-666.966
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-129.324
-65.3249
2.89777
-10.7394
-22.1956
-34.2441
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-774.886
-894.67
-1032.38
-1157.62
-1228.22
-832.05
-880.758
-942.704
-916.179
-928.271
-568.567
-371.517
-218.96
-63.1201
-11.7869
49.2526
93.4001
97.9735
134.653
79.1914
39.5944
-12.8271
-63.5335
-230.988
-388.82
-528.055
-718.052
-795.012
-857.97
-1531.28
-1580.65
-1679.72
-1783.9
-1424.06
-409.492
-330.92
-92.5476
23.2807
157.207
212.151
291.755
420.55
307.484
226.193
172.49
44.7823
7.41845
-49.1172
-111.483
-215.469
-973.832
-1265.73
-1404.9
-1277.03
-1286.1
-1331.22
-1423.7
-1362.09
-477.474
-372.111
-189.733
-66.0451
68.6944
261.008
394.393
419.495
425.083
332.942
177.47
98.1252
9.54784
-82.8898
-173.227
-235.501
-805.39
-1020.14
-1190.18
-1433.57
-1479.45
-1661.09
-1724.83
-1760.41
-648.653
-439.648
-203.534
-16.4359
147.633
320.061
368.803
452.194
446.67
405.711
301.647
193.691
-35.3706
-138.013
-232.445
-306.394
-1116.4
-1291.5
-1332.77
-1078.51
-1145.11
-1211.13
-1207.06
-1278.98
-1262.7
-851.962
-416.004
-170.009
-9.04844
53.2248
101.43
105.461
146.467
59.5474
-34.2484
-227.019
-418.642
-613.348
-764.761
-889.87
-955.09
-998.848
-1056.53
-1831.51
-1929.88
-1987.45
-1984.53
-2007.32
-2017.99
-1802.78
-1044.87
-724.065
-432.75
-226.108
-133.561
-106.677
-97.64
-222.977
-410.612
-752.382
-1024.97
-1373.82
-1546.46
-1665.08
-1757.9
-1820.01
-1844.86
-2340.1
-2446.38
-2540.16
-2641.92
-2654.67
-2659.94
-2662.13
-2095.04
-1500.79
-913.506
-611.749
-380.11
-267.798
-308.113
-343.66
-412.48
-737.183
-1143.38
-1566.65
-1704.7
-1826.56
-1952.46
-2127.5
-2271.43
Watts
4000
3200
2400
1600
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0
-800
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Ventilation Gains - Qv - Module California Climate Zone 8, USA

Asset Metadata

Creator Lee, Andrew C. (author)

Core Title Climatic alignment of architectural design strategies through an analysis of native plants in southern California

Contributor Electronically uploaded by the author (provenance)

School School of Architecture

Degree Master of Building Science

Degree Program Building Science

Publication Date 08/07/2008

Defense Date 05/07/2008

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

Tag biomimetics,biomimicry,climate design,green building,OAI-PMH Harvest,sustainability

Place Name California (states)

Language English

Advisor Spiegelhalter, Thomas (committee chair), Noble, Douglas (committee member), Schiler, Marc (committee member)

Creator Email andrew.c.lee@gmail.com,leea@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m1557

Unique identifier UC1178286

Identifier etd-Lee-2245 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-106285 (legacy record id),usctheses-m1557 (legacy record id)

Legacy Identifier etd-Lee-2245.pdf

Dmrecord 106285

Document Type Thesis

Rights Lee, Andrew C.

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email uscdl@usc.edu

Abstract (if available)

Abstract This paper presents a method of distilling a climate-specific design approach from the adaptive qualities of native plant communities. The method is demonstrated through the analysis of plants native to Southern California and an application of a selected adaptation to the design of a simulated reference building on a site in Los Angeles. Climate data was analyzed in GIS to select representative plant communities for the reference site based on a comparison of microclimate conditions. The climate analysis concluded that the Desert Scrub plant community was most applicable to the reference site. Field research was conducted to catalog the physiological adaptations of prominent species in desert plant communities. The behavioral adaptations of desert plants were studied in biological texts. CAM photosynthesis was the adaptive trait that was applied to the reference building and analyzed through psychrometric study and energy simulation.