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Modular shading: using design to mitigate bus rider thermal heat stress

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Modular shading: using design to mitigate bus rider thermal heat stress

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Content Modular Shading:
Using Design to Mitigate Bus Rider Thermal Heat Stress
A Thesis Presented to the
FACULTY OF THE USC SCHOOL OF ARCHITECTURE
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
MASTER OF BUILDING SCIENCE
May 2024

ii
ACKNOWLEDGEMENTS
Kyle Konis, Ph.D., AIA
Director, Chase L. Leavitt Graduate Building Science Program
Associate Professor
USC, School of Architecture
Email: kkonis@usc.edu
Rob Ley
Adjunct Professor
USC, School of Architecture
Email: rley@usc.edu
Lauren Dandridge, LC, IES
Adjunct Associate Professor
USC, School of Architecture
Email: ldandrid@usc.edu

iii
TABLE OF CONTENTS
ACKNOWLEDGEMENTS............................................................................................................ ii
LIST OF TABLES......................................................................................................................... vi
LIST OF FIGURES ...................................................................................................................... vii
ABSTRACT................................................................................................................................... xi
KEYWORDS................................................................................................................................. xi
HYPOTHESIS ............................................................................................................................... xi
RESEARCH OBJECTIVES ......................................................................................................... xii
1 CHAPTER ONE: INTRODUCTION ..................................................................................... 1
1.1 Site Background ............................................................................................................... 2
1.1.1 Los Angeles .............................................................................................................. 2
1.1.2 Los Angeles Climate................................................................................................. 4
1.1.3 Los Angeles Population ............................................................................................ 5
1.1.4 Los Angeles Crime Rate ........................................................................................... 6
1.1.6 Los Angeles Public Transportation ................................................................................ 8
1.2 Issues Facing Transit Riders .......................................................................................... 10
1.3.1 Heat Stress and The Vulnerability of L.A. Bus Riders ................................................ 10
1.3.2 UV Exposure of LA Transit Riders.............................................................................. 12
1.3.3 Lack of Safety Provided by Current Bus Stops............................................................ 13
1.3 Software Utilized for Research Modeling and Simulation ............................................ 13
1.3.1 Rhino3D.................................................................................................................. 13
1.3.2 Grasshopper ............................................................................................................ 14
1.3.2.1 Ladybug............................................................................................................... 14
1.3.2.2 Honeybee............................................................................................................. 15
1.4 Design Thinking............................................................................................................. 16
1.5 Modular Design.............................................................................................................. 17
1.6 Summary ........................................................................................................................ 17
2 CHAPTER TWO: LITERATURE REVIEW........................................................................ 19
2.1 Introduction ......................................................................................................................... 19
2.2 The Heat Vulnerability of L.A. Bus Riders ........................................................................ 19
2.3 Urban Geometry’s Effect on Thermal Comfort in Outdoor Spaces............................... 21

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2.3.1 Urban Geometry and Radiation: ............................................................................. 22
2.3.2 Urban Geometry and Air Temperature:.................................................................. 23
2.3.3 Urban Geometry and Thermal Comfort:................................................................. 23
2.4 Role of Shading in Enhancing Thermal Comfort and User Experience ............................. 23
2.4.1 Shading Effects on Park Attendance - Taiwan, China............................................ 24
2.4.2 Equitable Shading - El Paso, Texas........................................................................ 24
2.5 Lack of Safety Provided by Current Bus Stops.............................................................. 25
2.6 Inequity of Bus Shelter Distribution .............................................................................. 26
2.6 Bus Shelter Case Studies: Strength and Weaknesses.......................................................... 28
2.6.1 La Sombrita Bus Shade: ............................................................................................... 28
2.6.2 Big Blue Bus Stops – Santa Monica:............................................................................ 31
2.6.3 SOM Bus Shelter:......................................................................................................... 33
2.7 Summary ........................................................................................................................ 35
3 CHAPTER THREE: METHODOLOGY.............................................................................. 36
3.1 Introduction .................................................................................................................... 36
3.2 Methodology Diagram: .................................................................................................. 37
3.3 Identify Problem............................................................................................................. 38
3.4 Design............................................................................................................................. 38
3.4.1 Define Design Criteria ............................................................................................ 39
3.4.2 Design and Development........................................................................................ 46
3.4.3 Design Testing ........................................................................................................ 47
3.5 Construction ................................................................................................................... 48
3.5.1 Details and Construction Drawings........................................................................ 48
3.5.2 Building Large Scale Model ................................................................................... 49
3.6 Summary ........................................................................................................................ 49
4 CHAPTER FOUR: RESULTS.............................................................................................. 51
4.1 Introduction .................................................................................................................... 51
4.2 Creating Rhino Model.................................................................................................... 51
4.3 Universal Thermal Climate Index & Shade Benefit ...................................................... 53
4.3.1 UTCI – No Shading ................................................................................................ 54
4.3.2 UTCI – Under South Facing Shading..................................................................... 55
4.3.3 UTCI – Under North Facing Shading..................................................................... 57

v
4.3.4 UTCI – Under East Facing Shading ....................................................................... 59
4.3.5 UTCI – Under West Facing Shading...................................................................... 61
4.3.6 UTCI – Under North/East 30º Facing Shading....................................................... 63
4.3.7 UTCI – Under North/West 30º Facing Shading ..................................................... 65
4.3.8 UTCI – Under South/East 30º Facing Shading....................................................... 67
4.3.9 UTCI – Under South/West 30º Facing Shading ..................................................... 69
4.4 Surface Temperature & Shading Study.......................................................................... 71
4.4.1 Surface temperature study – No shading ................................................................ 71
4.4.2 Surface temperature & shading studies – South Facing ......................................... 73
4.4.3 Surface temperature & shading studies – North Facing ......................................... 76
4.4.4 Surface temperature & shading studies – East Facing............................................ 79
4.4.5 Surface temperature & shading studies – West Facing .......................................... 82
4.4.6 Surface temperature & shading studies – 30º North-East Facing........................... 84
4.4.7 Surface temperature & shading studies – 30º North-West Facing.......................... 87
4.4.8 Surface temperature & shading studies – 30º South-East Facing........................... 90
4.4.9 Surface temperature & shading studies – 30º South-West Facing.......................... 93
4.5 Conclusion...................................................................................................................... 96
5 CHAPTER FIVE: DESIGN .................................................................................................. 97
5.1 Introduction .................................................................................................................... 97
5.2 Design Concepts............................................................................................................. 97
5.2.1 Concept 1 ................................................................................................................ 97
5.2.2 Concept 2 .............................................................................................................. 101
5.2.3 Concept 3 .............................................................................................................. 105
5.3 Digital and Physical Modeling..................................................................................... 108
5.4 Building Large Scale Model ........................................................................................ 111
5.5 Conclusion.................................................................................................................... 119
6 CHAPTER SIX: CONCLUSION AND FUTURE WORK ................................................ 120
6.1 Summary ...................................................................................................................... 120
6.2 Future Work ................................................................................................................. 125
6.3 Conclusion.................................................................................................................... 125
AI DISCLAIMER....................................................................................................................... 126
REFERENCES ........................................................................................................................... 127

vi
LIST OF TABLES
Table 1: Shading Design Criteria………………………………………………………………48
Table 2: Percentage of UTCI Improvement……………………………………………………71
Table 3: Percentage of Surface Temperature Improvement………………………………........96
Table 4: Percentage of UTCI Improvement…………………………………………………..122
Table 5: Percentage of Surface Temperature Improvement…………………………………..123

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LIST OF FIGURES
Figure 1: Map of Los Angeles County – (Wikimedia Commons, 2013)........................................ 3
Figure 2: Downtown Los Angeles – (Gary Coronado/Los Angeles Times) .................................. 4
Figure 3: Figure 1.2: Downtown Los Angeles – (Gary Coronado/Los Angeles Times)................ 5
Figure 4: Average monthly high and low temperatures in Los Angeles – (Weather Spark, n.d.).. 5
Figure 5: Racial breakdown of Los Angeles City Population - (United States Census Bureau,
2022) ............................................................................................................................................... 6
Figure 6: Safety scale of different Los Angeles Cities– Neighborhood Scout, Security Gauge .... 7
Figure 7: Change in Crime Rates - (Newton, 2023)....................................................................... 7
Figure 8: 2020 Map of Los Angeles Metro System - (Susaneck, 2020)......................................... 9
Figure 9: 2060 Map of Los Angeles Metro System - (Susaneck, 2020)......................................... 9
Figure 10: Los Angeles Metro Demographics - (Los Angeles Metro, 2022)............................... 11
Figure 11: NURBS curve - (Anon., 2023).................................................................................... 13
Figure 12: NURBS surface - (Anon., 2023) ................................................................................. 13
Figure 13: : Grasshopper visual code and Rhino representation – (Grasshopper - Making a
Parametric Bench, 2016)............................................................................................................... 14
Figure 14: Web of interoperability of Ladybug tools - (Ladybug Tools, n.d.)............................. 15
Figure 15: Design Thinking Process - (Friis Dam & Yu Siang, 2023)......................................... 16
Figure 16: Land surface temperature ranges across Los Angeles County – (Brozen, et al., 2023)
....................................................................................................................................................... 20
Figure 17: Distribution of bus stops and shelters by heat band – (Brozen, et al., 2023).............. 21
Figure 18: Rendering of Outdoor Classroom prototype for Insights Science by Kripa and Mueller
– (Bentancourt, 2023) ................................................................................................................... 25
Figure 19: Criteria for Shelter Location Selection in Los Angeles – UC Berkely: Shelter from the
Storm (Law & Taylor, 2010) ........................................................................................................ 27
Figure 20: La Sombrita Bus Shade – Kounkuey Design Initiative (Capps, 2023)....................... 29
Figure 21: La Sombrita Bus Shade – Kounkuey Design Initiative (Capps, 2023)....................... 30
Figure 22: La Sombrita Bus Shade – x: @LADOTofficial (Los Angeles Department of
Transportation, 2023).................................................................................................................... 31
Figure 23: Big Blue Bus Stop – (Lorcan O’Herlihy Architects, 2016) ........................................ 32
Figure 24: Big Blue Bus Stop – (Lorcan O’Herlihy Architects, 2016) ........................................ 32
Figure 25: Big Blue Bus Stops – (Lorcan O’Herlihy Architects, 2016)....................................... 33
Figure 26: SOM Bus Shelter – (Volpi, 2023)............................................................................... 34
Figure 27: SOM Bus Shelter – (Volpi, 2023)............................................................................... 34
Figure 28: International Conde Council Digital Codes - (Anon., 2022) ...................................... 39
Figure 29: Climate Resolve Hottest in LA Bus Stop Map - (Anon., n.d.).................................... 40
Figure 30: Ladybug Tools EPW Map - (Anon., n.d.)................................................................... 41
Figure 31: Climate Consultant Results......................................................................................... 42
Figure 32: Ladybug shade benefit analysis................................................................................... 43
Figure 33: Ladybug hourly plot.................................................................................................... 44
Figure 34: MatWeb website for material properties. (MatWeb, n.d.) .......................................... 45

viii
Figure 35: Ladybug shading study example - (Interactive Shadow Study and animation in
Ladybug Rhino 004 mp4, 2020)................................................................................................... 45
Figure 36: Erwin Hauer shading screens - (filzfelt, n.d.).............................................................. 47
Figure 37: Isometric view of bus shelter model............................................................................ 52
Figure 38: Front view of bus shelter model.................................................................................. 52
Figure 39: Side view of bus shelter model.................................................................................... 53
Figure 40: Ladybug hourly plot.................................................................................................... 54
Figure 41: UTCI Results – No Shading........................................................................................ 55
Figure 42: Optimal shading layout – South facing ....................................................................... 56
Figure 43: Designed shading layout – South facing ..................................................................... 56
Figure 44: UTCI Results – South facing....................................................................................... 57
Figure 45: Optimal shading layout – North facing ....................................................................... 57
Figure 46: Designed shading layout (front) – North facing bench ............................................... 58
Figure 47: Designed shading layout (back) – North facing.......................................................... 58
Figure 48: UTCI Results – North facing....................................................................................... 59
Figure 49: Optimal shading layout – East facing.......................................................................... 59
Figure 50: Designed shading layout (front) – East facing ............................................................ 60
Figure 51: Optimal shading layout (Back) – East facing.............................................................. 60
Figure 52: UTCI Results – East facing......................................................................................... 61
Figure 53: Optimal shading layout – West facing ........................................................................ 61
Figure 54: Designed shading layout (front) – West facing........................................................... 62
Figure 55: Designed shading layout (back) – West facing........................................................... 62
Figure 56: UTCI Results – West facing........................................................................................ 63
Figure 57: Optimal shading layout – North-east facing................................................................ 63
Figure 58: Designed shading layout (front) – North-east facing .................................................. 64
Figure 59: Designed shading layout (back) – North-east facing .................................................. 64
Figure 60: UTCI Results – North-east facing............................................................................... 65
Figure 61: Optimal shading layout – North-west facing .............................................................. 65
Figure 62: Designed shading layout (front) – North-west facing................................................. 66
Figure 63: Designed shading layout (back) – North-west facing ................................................. 66
Figure 64: UTCI Results – North-west facing.............................................................................. 67
Figure 65: Optimal shading layout – South-east facing................................................................ 67
Figure 66: Designed shading layout (front) – South-east facing .................................................. 68
Figure 67: Designed shading layout (back) – South-east facing .................................................. 68
Figure 68: UTCI Results – South-east facing............................................................................... 69
Figure 69: Optimal shading layout – South-west facin ................................................................ 69
Figure 70: Designed shading layout (front) – South-west facing................................................. 70
Figure 71: UTCI Results – South-west facing.............................................................................. 70
Figure 72: Hourly plot of bench seating surface in ℃ ................................................................. 72
Figure 73: Surface temperature hourly plot – South facing.......................................................... 73
Figure 74: Surface temperature hourly plot – South facing.......................................................... 74
Figure 75: Shade pattern – South facing existing condition......................................................... 75
Figure 76: Shade pattern – South facing designed condition ....................................................... 75

ix
Figure 77: Surface temperature results – South facing................................................................. 76
Figure 78: Hourly plot of bench seating surface in ℃ ................................................................. 76
Figure 79: Shade pattern – North facing existing condition......................................................... 78
Figure 80: Shade pattern – North facing designed........................................................................ 78
Figure 81: Surface temperature results – North facing................................................................. 79
Figure 82: Hourly plot of bench seating surface in ℃ ................................................................. 79
Figure 83: Shade pattern – East facing existing condition ........................................................... 80
Figure 84: Shade pattern – East facing designed condition.......................................................... 81
Figure 85: Surface temperature results – East facing condition ................................................... 81
Figure 86: Hourly plot of bench seating surface in ℃ ................................................................. 82
Figure 87: Shade pattern – West facing existing condition .......................................................... 83
Figure 88: Shade pattern – West facing design condition ............................................................ 83
Figure 89: Surface temperature results – West facing condition.................................................. 84
Figure 90: Surface temperature results – North-east facing condition ......................................... 84
Figure 91: Shade pattern – North-East facing existing condition................................................. 86
Figure 92: Shade pattern – North-East facing designed condition ............................................... 86
Figure 93: Surface temperature results – North-East facing condition......................................... 87
Figure 94: Hourly plot of bench seating surface in ℃ ................................................................. 87
Figure 95: Shade pattern – North-west facing existing condition ................................................ 88
Figure 96: Shade pattern – North-west facing designed condition............................................... 89
Figure 97: Surface temperature results – North-west facing condition ........................................ 89
Figure 98: Hourly plot of bench seating surface in ℃ ................................................................. 90
Figure 99: Shade pattern – South-east facing existing condition ................................................. 91
Figure 100: Shade pattern – South-east facing designed condition.............................................. 92
Figure 101: Surface temperature results – South-east facing condition ....................................... 92
Figure 102: Hourly plot of bench seating surface in ℃ ............................................................... 93
Figure 103: Shade pattern – South-west facing existing condition .............................................. 94
Figure 104: Shade pattern – South-west facing designed condition............................................. 94
Figure 105: Surface temperature results – South-west facing condition ...................................... 95
Figure 106: Clouds by Ronan and Erwan Bouroullec - (Etherington, 2009) .............................. 98
Figure 107: Clouds by Ronan and Erwan Bouroullec - (Etherington, 2009) .............................. 98
Figure 108: Concept 1 development – Digital model................................................................... 99
Figure 109: Concept 1 development – 1:1 Physical model ........................................................ 100
Figure 110: Concept 1 development – 1:1 Physical model ........................................................ 101
Figure 111: Concept 2 development – Working models............................................................ 102
Figure 112: Concept 2 development – Working models............................................................ 103
Figure 113: Concept 2 development – Digital model................................................................. 104
Figure 114: Concept 2 development – 1:1 Physical model ........................................................ 104
Figure 115: Concept 2 development – 1:1 Physical model ........................................................ 105
Figure 116: Erwin Hauer modular shading screen - (Waddoups, 2018) .................................... 106
Figure 117: Erwin Hauer suiter curve reference - (Hauer, 2017)............................................... 107
Figure 118: Iron door curves of Los Angeles home ................................................................... 107
Figure 119: Curve experimentation ............................................................................................ 108

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Figure 120: Curve experimentation ............................................................................................ 109
Figure 121: 3D printed working model ...................................................................................... 110
Figure 122: 3D printed working model ...................................................................................... 111
Figure 123: 1:1 scale working model – Front............................................................................. 112
Figure 124: 1:1 scale working model - Back.............................................................................. 113
Figure 125: 1:1 scale working model - Back.............................................................................. 114
Figure 126: 1:1 scale model........................................................................................................ 115
Figure 127: 1:1 scale model........................................................................................................ 116
Figure 128: 1:1 scale model........................................................................................................ 117
Figure 129: 1:1 scale model........................................................................................................ 118
Figure 130: Methodology diagram ............................................................................................. 121
Figure 131: Bus shelter rendering............................................................................................... 124
Figure 132: 1:1 scale final model................................................................................................ 124

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ABSTRACT
This thesis explores the development of modular shading solutions for existing bus shelters in
Los Angeles, aiming to enhance commuter comfort through improved shading during the city's
extreme heat days. The research highlights gaps in the current bus shelter infrastructure, with an
emphasis on the inadequate shade and cooling provisions that disproportionately affect
vulnerable populations.
Using design thinking, the study evaluates eight bus shelter orientations (South, North, East,
West, South-East, South-West, North-East, North-West) against variables such as the Universal
Thermal Climate Index (UTCI) beneath the shelter as well as the surface temperature and
shading quality at bench surface. Simulations are conducted using the Grasshopper tools
Ladybug, Honeybee, and EnergyPlus to help inform the design of the modular shading elements.
Success metrics for these designs include achieving at least a 20% improvement in UTCI
readings and a reduction in bench surface temperatures, both of which were surpassed in test
results.
The research advances with a modular shading system tailored for diverse bus stop orientations,
hypothesizing that this system significantly boosts thermal comfort and user satisfaction. The
study culminates in constructing a large-scale prototype to be tested under real-world conditions,
confirming the practical benefits of the proposed solutions. This work contributes to urban
design by offering a scalable, adaptable method for improving public transportation
infrastructure in hot climates.
KEYWORDS
Los Angeles, Bus Shelter, Heat Stress, Thermal Comfort, Shading, Modular Design
HYPOTHESIS
The implementation of a modular bus shelter shade will improve the thermal comfort of different
bus shelter orientations and overall satisfaction of bus shelter users in Los Angeles. The modular
shades are expected to reduce the UTCI high temperature readings by 20% and improve surface
temperature and shading quality of bench surface.

xii
RESEARCH OBJECTIVES
- To Analyze Current Bus Shelter Conditions in Los Angeles: Objective is to
comprehensively assess the existing state of bus shelters, focusing on their design, the
level of shade they provide, and their overall safety.
- To Develop and Test Modular Shading Designs: Aim to design and develop a range of
modular shading solutions that can be adapted to various bus stop orientations. This
includes creating iterative design models using simulation tools and testing these models
for their effectiveness in providing adequate shade, reducing surface temperatures, and
enhancing user comfort.
- To Evaluate the Impact of Shading Solutions on User Comfort and Safety: This
objective seeks to measure the effectiveness of the new shading designs in improving
thermal comfort and perceived safety for bus shelter users. It involves conducting
simulations to assess the impact of shading solutions on temperature reduction and user
satisfaction.

1
1 CHAPTER ONE: INTRODUCTION
In the sprawling urban landscape of Los Angeles, a city renowned for its car-centric culture, the
humble bus stop often fades into the background. Yet, for a significant portion of the city's
residents, these bus stops serve as crucial nodes in their daily commutes, connecting them to
work, school, and other essential destinations. Despite their importance, many of these stops lack
the basic infrastructure of a shelter, leaving commuters exposed to the elements and potential
security risks. This glaring oversight in transit planning not only compromises the comfort and
safety of the city's residents but also underscores a broader neglect of public transportation
infrastructure in favor of private vehicular travel. (Newton, 2023)
Bus stops in Los Angeles have historically been overlooked, resulting in a lack of shelters that
provide shade during the summer months and security during the darker hours. This neglect has
led to a two-fold issue. First, without adequate shelter, commuters are exposed to high heat and
sun exposure during the summer months, making the wait for a bus an uncomfortable, if not
unbearable, experience. This particularly affects riders from low-income communities. Second,
the absence of well-lit, secure shelters can make bus stops areas of perceived insecurity,
especially during the night. This perception is particularly heightened for women, who often
report feeling unsafe while waiting for buses in dimly lit areas.
Addressing the lack of bus shelters is not merely a matter of enhancing commuter comfort; it is a
step towards creating a more inclusive, equitable, and sustainable urban environment. A welldesigned bus shelter can encourage more people to opt for public transportation, reducing the
city's carbon footprint and alleviating traffic congestion. Furthermore, by prioritizing the safety
and comfort of all residents, the city sends a clear message about its commitment to the wellbeing of its citizens.
This research aims to shed light on a pressing urban issue and propose innovative solutions that
prioritize the needs of the community. The primary hypotheses guiding this research is: The
implementation of a modular bus shelter shade will improve the thermal comfort of different bus
shelter orientations and overall satisfaction of bus shelter users in Los Angeles. The modular
shades are expected to reduce the UTCI high temperature readings by 20% and improve surface
temperature and shading quality of bench surface. These enhancements aim to mitigate the risk
of heat stress for riders, improve thermal comfort, and reduce glare by providing effective
protection from direct sunlight. Additional shading will be placed vertically along the shelter's
perimeter where necessary. The shading design is carefully considered to meet the comfort and
safety needs of riders, while also enhancing the overall riding experience with an aesthetically
pleasing element.

2
1.1 Site Background
1.1.1 Los Angeles
Los Angeles is located in Southern California and is the second-most populated metropolitan
area in the United States (Pitt, 2023). It borders the 75-miles Pacific Ocean beaches on one side
and a mountainous range on the other (Pitt, 2023). The city serves as the nucleus of Los Angeles
County, which encompasses an additional 90 incorporated cities, including notable locales such
as Beverly Hills, Pasadena, and Long Beach (Pitt, 2023). The city is characterized by its climate,
extensive outdoor activities, and being the hub of the film industry (Pitt, 2023). Los Angeles is
known for standing as a beacon of opportunity (Pitt, 2023). Its demographic composition
includes a diverse range of races and socio-economic backgrounds, which is tied to the city’s
historical ties to immigration (Pitt, 2023). Geographically, the city is as diverse as its populace,
encompassing mountains, valleys, and distinctive beaches that annually attract millions of
visitors. Presently, Los Angeles is a conglomerate of original city districts and annexed
communities, each retaining its unique identity, thereby contributing to the vibrant and dynamic
essence of this quintessentially American city (Pitt, 2023). Figure 1 below shows a map of Los
Angeles County, which shows the county’s location and the different cities within it. Figure 2 is
an image of Downtown LA which showcases the mountainous terrain by the city.

3
Figure 1: Map of Los Angeles County – (Wikimedia Commons, 2013)

4
Figure 2: Downtown Los Angeles – (Gary Coronado/Los Angeles Times)
1.1.2 Los Angeles Climate
Los Angeles is characterized by its semiarid or Mediterranean climate, a result of its southern
latitude, cooling marine air, and protective mountain ranges (Pitt, 2023). These geographical
features help shield the region from extreme desert temperatures and contribute to the city's
notorious photochemical smog, which has been a persistent issue since the 1940s (Pitt, 2023).
The city experiences two main seasons: a dry, moderately warm period from April to November,
and a wet, moderately cool period from November to April, with a mean temperature of
approximately 64 °F (18 °C) (Pitt, 2023). Temperature variations are notable, with differences of
up to 10 °F (5.5 °C) between areas such as the San Fernando Valley and Santa Monica due to the
change in fog, wind speed, and elevation (Pitt, 2023). August is typically the hottest month, with
downtown temperatures averaging 85 °F (29 °C), while the ocean 15 miles away averages a
temperature of 68 °F (20 °C) (Pitt, 2023). January is the coldest, with temperatures rarely
dropping below 40 °F (4 °C) on the plains (Pitt, 2023). Annual precipitation averages around 15
inches (380 mm), with some rainy seasons almost doubling this amount (Pitt, 2023). Prolonged
rains or intense downpours can trigger mudslides, particularly in areas where vegetation has been
stripped by fires (Pitt, 2023). Figures 3 and 4 below show the average daily and monthly
temperatures of the city of Los Angeles.

5
Figure 3: Figure 1.2: Downtown Los Angeles – (Gary Coronado/Los Angeles Times)
1.1.3 Los Angeles Population
The population of Los Angeles has experienced significant shifts in its ethnic and racial
composition over time, evolving from a predominantly African, Native American, or mixed
ancestry in 1781, to a white majority in the late 19th to early 20th century (Pitt, 2023). After the
Mexican Revolution in 1910 there was an influx of agricultural workers migrating to Los
Angeles, and ultimately transforming it into one of the most diverse metropolises in the country
by the 1970s (Pitt, 2023). Today, Los Angeles County boasts the largest Hispanic, Asian, and
Native American populations of any county in the United States (Pitt, 2023). According to the
US Census Bureau, the population estimate for the city of Los Angeles in 2022 was 3,822,238,
with Hispanics being the majority accounting for 48.4%. African Americans make up one-tenth
of the total population, occupying areas such as Compton and Inglewood (Pitt, 2023). Today,
these areas are mostly Hispanic as African Americans moved into the suburbs (Pitt, 2023).
Figure 4: Average monthly high and low temperatures in Los Angeles – (Weather Spark,
n.d.)

6
Figure 5 below is a US Census breakdown of the different races found in Los Angeles. This
diversity is further reflected in the more than 90 languages spoken in homes across the city,
including Spanish, Vietnamese, Cantonese, and many others (Pitt, 2023).
1.1.4 Los Angeles Crime Rate
2023 has witnessed a notable decrease in violent crime, evidenced by a 24% reduction in
homicides, a 17% decrease in instances of rape, and a 12% decline in reported robberies
(Newton, 2023). Conversely, property-related crimes persist as a prominent challenge within the
city's criminal landscape, with a 14% increase in personal and other thefts in 2023, and a 42%
increase over the past two years (Newton, 2023). The Los Angeles Police Department (LAPD)
grapples with addressing these crimes seemingly due to staffing shortages, with its personnel
having diminished from over 10,000 officers to just over 9,000 (Newton, 2023). This reduction
in law enforcement capacity is acutely felt within units tasked with property crime resolution
(Newton, 2023). Moreover, the LAPD's fiscal year budget request, while highlighting successes
in mitigating violent crime, neglects to delineate the resources for addressing property crime
(Newton, 2023). The discord between law enforcement entities and prosecutorial bodies further
exacerbates the issue (Newton, 2023). Figure 6 below is a map of Los Angeles showing the
safest to most dangerous areas in the city, while Figure 7 is a chart showing the percent change
in different crimes as of 2023. Safety at bus stops has been an ongoing concern for Los Angeles
bus riders, as stated in the 2022 METRO ridership survey. Investing in quality bus shelters can
increase their perceived safety and result in a more comfortable experience for public transit
riders.
Figure 5: Racial breakdown of Los Angeles City Population - (United States Census Bureau, 2022)

7
Figure 6: Safety scale of different Los Angeles Cities– Neighborhood Scout, Security Gauge
Figure 7: Change in Crime Rates - (Newton, 2023)

8
1.1.6 Los Angeles Public Transportation
The Los Angeles public transportation system, historically dominated by an auto-centric
approach, is undergoing a significant transition towards a more sustainable and integrated model
(Scauzillo, 2023). Initially, the city's development trajectory was heavily influenced by the
expansive construction of freeways, which facilitated and encouraged widespread automobile
use (Susaneck, 2020). This approach led to notable environmental issues, urban sprawl, and
socio-economic segregation, with public transportation playing a secondary role in the city's
mobility framework (Susaneck, 2020).
In recent years, however, there has been a conscious shift in focus. Los Angeles is actively
investing in and expanding its public transportation infrastructure, emphasizing both rail and bus
transit systems (Susaneck, 2020). This paradigm shift is evident in the extensive rail projects
underway, aimed at transforming the city's transit landscape (Susaneck, 2020). The expansion
includes notable projects like the Regional Connector, which integrates various rail lines to
create a more cohesive and efficient network (Scauzillo, 2023). This will turn the railway system
from a radial configuration to a more of a grid system, reducing the need for transfers and
enhancing the system's core strength (Susaneck, 2020). Additionally, the city's plan to complete
28 significant transit projects before the 2028 Olympics, under the "Twenty Eight by ‘28"
initiative, underscores the urgency and scale of this transformation (Susaneck, 2020).
The expansion of railway lines is set to provide high-capacity connections across key corridors,
significantly reducing dependency on automobiles (Susaneck, 2020). These developments are
coupled with strategic urban planning initiatives, advocating for densification around transit hubs
to maximize the effectiveness of public transportation (Susaneck, 2020).
In parallel, the bus transit system, a vital component of Los Angeles's transportation network, is
being reimagined and reinforced (Susaneck, 2020). If timed properly, the implementation of the
new Bus Rapid Transit (BRT) routes will allow for a seamless transfer between bus and rail
riders and vice versa (Susaneck, 2020). The integration of buses and rail is seen as a critical
strategy for achieving a more connected, equitable, and environmentally sustainable urban
environment (Susaneck, 2020). This shift from a predominantly car-centric urban model to a
robust public transportation system marks a pivotal moment in Los Angeles's urban
development, setting a precedent for future-oriented urban mobility strategies (Susaneck, 2020).
Below are two maps that showcase the proposed evolution of Los Angeles’ METRO system:

9
Figure 8: 2020 Map of Los Angeles Metro System - (Susaneck, 2020)
Figure 9: 2060 Map of Los Angeles Metro System - (Susaneck, 2020)

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1.2 Issues Facing Transit Riders
1.3.1 Heat Stress and The Vulnerability of L.A. Bus Riders
The University of Iowa's Environmental and Safety Department characterizes heat stress as a
physiological condition where the human body's thermoregulatory mechanism is overwhelmed
by excessive heat, impeding its ability to effectively dissipate the accumulated heat (University
of Iowa Environmental Health and Safety, n.d.). This condition precipitates a rise in core body
temperature, accompanied by an elevated heart rate, diminished concentration, and, in severe
cases, can lead to fainting or fatality (University of Iowa Environmental Health and Safety, n.d.).
Contributing factors to heat stress include elevated ambient temperatures, exposure to radiant
heat sources, high humidity levels, direct contact with heated surfaces, and engaging in
physically demanding activities (University of Iowa Environmental Health and Safety, n.d.). The
pronounced impact of heat stress on laborers has prompted the Occupational Safety and Health
Administration (OSHA) to establish the Heat Stress National Emphasis Program (NEP)
(University of Iowa Environmental Health and Safety, n.d.). The Centers for Disease Control and
Prevention (CDC) issue warnings regarding the potential consequences of heat stress, noting that
exposure to extreme thermal environments can induce conditions such as heat stroke, heat
exhaustion, heat cramps, and heat rashes (Centers for Disease Control and Prevention, n.d.).
Furthermore, the CDC identifies specific demographics at heightened risk for adverse effects
from heat stress, including individuals aged 65 and older, those who are overweight, and those
with pre-existing medical conditions like cardiac disease or hypertension (Centers for Disease
Control and Prevention, n.d.).
Los Angeles faces escalating temperatures, with forecasts suggesting that by 2100, parts of the
county could experience 90 to 100 days of extreme heat (above 95 degrees) annually, up from
the current 30 to 40 days (Brozen, et al., 2023). Extreme heat effects have proven more
dangerous to Americans than any natural disaster as it increases the risk of hospitalization for
those struggling with cardiovascular, kidney, and heart disease (Brozen, et al., 2023). A study
done by the Los Angeles Urban Cooling Collaborative shows that the most affected
demographics by increased temperatures are Black and Latino communities. On average, Latino
communities are 4 degrees warmer than non-Latin areas, while higher temperatures are recorded
in areas with black residents during extreme heat days than areas with no black residents
(Brozen, et al., 2023). A study published in Wilderness and Environmental Medicine showed
that there is an overall increase of heat-related emergency visits between the years of 2005 and
2015, with a 67% increase for African Americans, and 63% increase for Hispanics (Scauzillo,
2023).
Latino and Black Los Angeles residents not only experience high heats in their areas of living
but also during their daily commutes. The 2022 LA Metro Customer Survey shows that 63% and
16% of bus riders are Latino and Black, respectively (Los Angeles Metro, 2022). This shows the
transit-dependency of these communities (Baruchman, 2021).

11
Figure 10: Los Angeles Metro Demographics - (Los Angeles Metro, 2022)
Riders taking the bus in Los Angeles go through a great deal of difficulty during their commutes
as only 46% of all bus stops served by Metro have seating, and only 24% of all bus stops have
shelters (Metro Customer Experience Plan 2022, 2022). Kevin Lanza and Caset P.Durand
analyzed the need for bus shelters to mitigate heat in Austin, Texas. In a 2021 interview they
explained how transportation systems need to be redesigned to be resilient against climate
change. This includes using bus shelters and trees as methods to shade riders during wait times
(Baruchman, 2021). It is important to note that bus shelters do not only serve as protection of
extreme heat, but also from all other natural elements. A study conducted by the UCLA institute

12
of Environment & Sustainability found that with greenhouse gas concentration continuing to
increase California can expect an increase in extreme dry and extreme wet events over the course
of the century. It is expected that extreme wet events will 2.5 times more frequent as they are
today (Haung, et al., 2020). This shows that bus shelters are needed not only to protect riders
from extreme heat but also for increased rain fall in the coming years. A UCLA study shows that
most bus stops in Los Angeles are located within the hottest area of the county reaching 97
degrees or above, and most of these stops do not include bus shelters (Brozen, et al., 2023).
Adding shading to bus stops can reduce surface temperatures by 25 to 40 degrees (Scauzillo,
2023).
1.3.2 UV Exposure of LA Transit Riders
Ultraviolet (UV) radiation, emanating from the sun, is categorized into three types based on
wavelength: Ultraviolet A (UVA: 315 nm – 399 nm), Ultraviolet B (UVB: 280 nm – 314 nm),
and Ultraviolet C (UVC: 100 nm – 279 nm) (Centers for Disease Control and Prevention, n.d.).
While UVC radiation is entirely absorbed by the Earth's atmosphere, UVB radiation is partially
absorbed, and UVA radiation, which is not absorbed, reaches the Earth's surface (Centers for
Disease Control and Prevention, n.d.). Although the atmosphere blocks a significant portion of
the sun's UV radiation, the rays that penetrate can have both positive and negative effects on
human health (Science Learning Hub, n.d.).
The primary beneficial effect of UV radiation is the stimulation of vitamin D production in the
body, which is crucial for the absorption of calcium and phosphorus. These minerals are essential
for strengthening bones, muscles, and the immune system (Science Learning Hub, n.d.). The
World Health Organization recommends moderate sun exposure, approximately 5 to 15 minutes,
2 to 3 times a week, to facilitate adequate vitamin D synthesis (Centers for Disease Control and
Prevention, n.d.).
However, the risks associated with UV exposure often outweigh its benefits. Short-term effects
include sunburns, while prolonged exposure can lead to more serious consequences such as
premature aging and skin cancer, the most common type of cancer in the United States (Centers
for Disease Control and Prevention, n.d.). Notably, basal cell cancer and squamous cell cancer,
predominantly caused by UV radiation, commonly affect areas of the body most exposed to
sunlight, such as the head, face, neck, hands, and arms (Centers for Disease Control and
Prevention, n.d.).
Given the high levels of sun exposure faced by Los Angeles transit riders, there is a heightened
risk of long-term skin damage (Centers for Disease Control and Prevention, n.d.). This
underscores the importance of providing adequate shading at bus shelters to protect commuters
from harmful UV rays and contribute to their overall health and well-being (Centers for Disease
Control and Prevention, n.d.).

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1.3.3 Lack of Safety Provided by Current Bus Stops
One of the main issues stated about the current bus stops in LA is how they feel unsafe. Having
bus shelters not only help decrease heat at bus stops but studies show that they decrease
perceived wait times and increase women’s perception of safety (Brozen, et al., 2023). Currently,
bus stops have no lighting on them leaving them to be very dark at night. The Los Angeles
Department of Transportation released a report that states women of color are more likely to face
harassment in public transportation (Jimenez & Albeck-Ripka, 2023). A 2001 study by UC
Berkley examined the crime rate around bus stops in Los Angeles. The study explored how
environmental variables contributed to bus stop crimes. An older study found that crime rates
were higher for bus stops near alleys, multifamily housing, liquor stores, and check-cashing
establishments, vacant buildings, and areas with graffiti (Liggett, et al., 2003). The study also
found that bus stops with shelters and clear visibility contributed to lower crime rates (Liggett, et
al., 2003).
1.3 Software Utilized for Research Modeling and Simulation
1.3.1 Rhino3D
Rhino, a computer-aided design (CAD) software, excels in creating three-dimensional models. It
employs the Non-Uniform Rational Basis Spline (NURBS) mathematical model, a sophisticated
method for rendering curves and surfaces with high precision (Anon., 2023). NURBS is
particularly adept at producing mathematically accurate representations of complex shapes and
forms (Anon., 2023). Rhino's robust capabilities make it a versatile tool widely adopted across
various sectors, including architecture, product design, and automotive design (Anon., 2023). Its
core strength lies in enabling users to achieve precise and detailed modeling, essential for
professional design and engineering applications.
Figure 11: NURBS curve - (Anon., 2023) Figure 12: NURBS surface - (Anon., 2023)

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1.3.2 Grasshopper
Grasshopper serves as a visual programming interface specifically tailored for Rhino3D. In
Grasshopper, geometry is generated algorithmically through visual programming, which
involves constructing flowcharts that connect data points to specific functions (Harmon, n.d.).
This method empowers designers to craft intricate shapes and quickly explore a variety of design
alternatives, leveraging the algorithmic process to expand creative possibilities (Harmon, n.d.).
Grasshopper is advanced by a plethora of user created plug-ins that allow
Figure 13: : Grasshopper visual code and Rhino representation – (Grasshopper - Making a Parametric Bench, 2016)
1.3.2.1 Ladybug
Ladybug is a plugin for Grasshopper that stands as an initial offering from Ladybug Tools, a
suite designed to aid in environmental design. This interface integrates multiple simulation
engines focused on sustainable design methodologies. Primarily, Ladybug specializes in the
analysis and visualization of climate data. It leverages climate data files to generate detailed
visual representations, facilitating a deeper understanding of the environmental conditions
specific to a location (Ladybug Tools, n.d.).

15
1.3.2.2 Honeybee
Honeybee, another plugin in the Ladybug Tools suite for Grasshopper, is used for conducting
daylight and energy modeling simulations. It functions by bridging Rhino/Grasshopper with
specialized engines, namely Radiance and EnergyPlus. Radiance is employed primarily for
simulations related to lighting and daylight, offering detailed insights into light interactions
within spaces. On the other hand, EnergyPlus serves as a comprehensive simulation engine,
adept at modeling various energy consumptions including heating, cooling, ventilation, lighting,
electrical loads, and water usage, thereby providing an extensive analysis of a building's energy
dynamics (Ladybug Tools, n.d.).
Figure 14: Web of interoperability of Ladybug tools - (Ladybug Tools, n.d.)

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1.4 Design Thinking
Design thinking represents an iterative methodology employed by designers, engineers, and
artists to develop innovative solutions for user-centric challenges, while also questioning and
reevaluating prevailing assumptions (Friis Dam & Yu Siang, 2023). This approach helps to
uncover solutions that are not immediately apparent. Central to design thinking is empathy for
the user experience, fostering a deeper comprehension of unmet needs or areas for enhancement
(Friis Dam & Yu Siang, 2023).
The methodology enhances the practitioner’s capacity to redefine both the problems at hand and
their potential solutions through iterative prototyping and testing (Friis Dam & Yu Siang, 2023).
Design thinking is structured around five critical stages (Friis Dam & Yu Siang, 2023):
1) Empathize: Gaining an insightful understanding of the users' needs and the context in
which these needs arise, identifying areas lacking in fulfillment or requiring
enhancement.
2) Define: Clearly articulating the problem to be addressed, ensuring a focused and
actionable path forward.
3) Ideate: Engaging in a creative process to generate a diverse array of potential solutions.
4) Prototype: Constructing tangible representations of solutions, allowing for the physical
manifestation of ideas to assess their viability.
5) Test: Evaluating the effectiveness of the solution in a real-world context, gathering
feedback to refine and improve the design iteratively.
By systematically following these stages, design thinking empowers individuals and teams to
approach complex problems with a fresh perspective, driving innovation through a user-centered
lens (Friis Dam & Yu Siang, 2023).
Figure 15: Design Thinking Process - (Friis Dam & Yu Siang, 2023)

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1.5 Modular Design
Modular design is a design approach that enhances flexibility and adaptability through the use of
interchangeable modules or parts (Friedman, 2020). A prime example of this is fractal
modularity, exemplified by LEGO bricks, where each individual piece can integrate seamlessly
into larger systems, maintaining a consistent interface regardless of the structure's overall
complexity. This same principle is echoed in slot modularity, which involves components
specifically designed to fit into certain slots within a system (Friedman, 2020). As such, while
parts can be replaced or exchanged, they must correspond to the designated slot type, thereby
enabling customization within a pre-established framework (Friedman, 2020).
Bus modularity represents another variant, characterized by interchangeable modules that share
identical interfaces, thereby facilitating easy rearrangement or replacement (Friedman, 2020).
Each module, unique in content or function, is designed to fit into any position within the
system, thanks to this uniform interface (Friedman, 2020). This form of modularity is
particularly prevalent in systems where the order of components can be altered without
impacting the overall functionality, a common feature in layouts involving text and images
(Friedman, 2020).
Overall, modular design's reliance on similar, attachable parts brings multiple benefits. These
include heightened flexibility, simplified customization, and the capability to update or modify a
system without necessitating a complete overhaul, making it an invaluable tool in modern design
practices (Friedman, 2020).
Adopting modularity in design offers a practical and economical solution. A significant barrier to
the implementation of new infrastructure in urban areas is the associated cost. Municipalities
often face high initial expenses for acquisition and ongoing costs for maintenance, which can
deter the deployment of essential improvements like bus shelters. Modular elements, being
uniform and replicable, streamline the fabrication and installation processes, which contributes to
reduced costs. Additionally, the use of standardized components simplifies maintenance
procedures. Maintenance crews can quickly become proficient in repairing or replacing these
elements, which leads to lower costs over time due to increased efficiency and reduced training
needs. By promoting modularity, cities can achieve a balance between enhancing public
infrastructure and managing budget constraints effectively. This design approach not only
improves the comfort and safety of bus riders but also ensures that the infrastructure is
financially sustainable for the long term.
1.6 Summary
This chapter of the thesis delves into the urban context of Los Angeles and provides a detailed
background highlighting its climate, population, and crime rate. The chapter also discusses the
city's ongoing transition from an auto-centric approach to a more sustainable and integrated

18
public transportation system. A key issue identified is the vulnerability of bus riders, especially
in minority communities, to extreme heat and safety concerns due to inadequately equipped bus
stops. To address these challenges, the thesis proposes using advanced software tools like
Rhino3D and Grasshopper, along with plugins such as Ladybug and Honeybee, for accurate
modeling and simulation in the design process. The chapter introduces the concept of modular
design as a flexible and adaptable solution for the bus shelters, aligning with modern urban
design practices and aiming to improve the overall public transportation experience in Los
Angeles.

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2 CHAPTER TWO: LITERATURE REVIEW
2.1 Introduction
In the sprawling urban landscape of Los Angeles, the design and functionality of bus shelters
play a pivotal role in shaping the daily experience of public transit users. This literature review
examines the various factors influencing bus shelter accessibility in L.A., particularly focusing
on the pressing challenges such as heat vulnerability, the necessity for adequate shading, and
concerns regarding safety and equitable distribution. By analyzing studies from several different
sources, the review highlights the critical intersection of urban planning, environmental stressors,
and public health. Additionally, it delves into an array of bus shelter case studies, shedding light
on different attempts at design solutions and their impact on communities. This comprehensive
overview aims to provide a nuanced understanding of the current state of bus shelter
infrastructure in Los Angeles, offering insights into how these essential elements of urban transit
can be optimized for the benefit of the city's population.
While existing studies extensively document the shortcomings of bus shelters in Los Angeles,
including their scarcity and inadequacy, there remains a noticeable gap in research pertaining to
the enhancement of these shelters. Current literature predominantly concentrates on identifying
problems, such as heat vulnerability and safety concerns, but falls short in exploring potential
solutions or design improvements. This lack of comprehensive research on actionable strategies
for enhancing existing bus shelters underscores the need for innovative approaches that address
both the functional and environmental challenges faced by public transit users. Bridging this gap
with research focused on practical, user-centric design solutions is crucial for elevating the
effectiveness and appeal of Los Angeles' bus shelter infrastructure.
2.2 The Heat Vulnerability of L.A. Bus Riders
The UCLA Lewis Center for Regional Policy Studies has highlighted the significant issue of
extreme heat at Los Angeles bus shelters. Their study reveals that parts of LA County currently
experience 30 – 40 days of extreme heat, exceeding 95 degrees Fahrenheit, a number projected
to rise to 90 – 100 days by the century's end (Brozen, et al., 2023). This extreme heat has
correlated with an increase in hospitalizations, particularly among individuals with pre-existing
cardiovascular, kidney, or respiratory conditions (Brozen, et al., 2023).
The LA Metro bus system, spanning over 1,000 square miles, is the second-largest in the United
States, consisting of over 10,527 bus stops. However, only 26% of these stops are equipped with
shelters, leaving the 560,000 daily riders exposed to the elements and lacking basic amenities
such as shade, seating, and trash bins (Brozen, et al., 2023). The study utilized ECOSTRESS
data from Climate Resolve to analyze average daily surface temperatures across Los Angeles
County from June to September 2022. This data revealed that a significant portion of the county

20
experiences average daily surface temperatures above 90 degrees Fahrenheit (Brozen, et al.,
2023). Figure 1 below is a diagram showing the land surface temperatures across LA county by
UCLA Lewis Center for Regional Policy.
Figure 16: Land surface temperature ranges across Los Angeles County – (Brozen, et al., 2023)
When comparing the surface temperature data with LA Metro's location management system
data, a clear correlation emerges. Most LA bus stops are situated in areas where the average daily
temperature is 97 degrees or higher (Brozen, et al., 2023). Figure 2 below is a graph created as a
part of UCLA’s study, which shows the number of bus stops located in different temperature
categories and the percentage of them with bus shelters. This lack of shade is exacerbated by the
fact that Los Angeles' tree coverage is only 18%, below the national average of 27% (Brozen, et
al., 2023).
A study conducted in Austin, Texas, further supports these findings, demonstrating that weather
conditions, including temperature extremes, significantly impact bus ridership (Lanza & Durand,
2021). For instance, Lane County, Oregon, experienced a 0.3% decrease in daily bus riders when
temperatures exceeded 84.2 degrees Fahrenheit, while Salt Lake City, Utah, saw a 0.4% decrease
when temperatures surpassed 73.4 degrees Fahrenheit (Lanza & Durand, 2021). These findings
highlight the threat that high temperatures pose to the resiliency of public transit systems,
particularly in cities experiencing urban heat island effects.
The Austin study focused on bus ridership between April 1st, 2019, and September 30th, 2019,
in a city characterized by hot summers and cold winters. The public transit system serves

21
approximately 1,300,518 riders over a 1409 km2 area. The study found a slight decrease in
ridership on high-temperature days, attributing the lack of a more significant decrease to riders'
dependency on public transportation (Lanza & Durand, 2021). The study concluded that
combining trees and bus shelters can significantly improve thermal comfort while also providing
environmental and health benefits (Lanza & Durand, 2021).
Figure 17: Distribution of bus stops and shelters by heat band – (Brozen, et al., 2023)
In addition to shade-providing elements, some studies have explored adaptive transit scheduling
as a means to reduce riders' exposure to extreme heat. One such study highlighted that extreme
heat is responsible for approximately 480,000 global deaths annually (Rosenthal, et al., 2022).
The study found that over 75% of heat exposure occurs during wait times at bus stops, with
ingress and egress accounting for a smaller fraction of exposure time (Rosenthal, et al., 2022).
While decreasing wait times could theoretically reduce heat exposure, the study concluded that
the practical limitations of bus fleet sizes and the diminishing returns of adding additional buses
make this solution challenging. As a result, the study advocates for direct heat mitigating
solutions, such as bus shelters and tree planting, as more effective means of protecting riders
from extreme heat (Rosenthal, et al., 2022).
2.3 Urban Geometry’s Effect on Thermal Comfort in Outdoor Spaces
Researchers affiliated with the Department of Architecture at Shanghai Jiao Tong University, the
School of Architecture at Tianjin University, and the School of Mechanical Engineering at
Purdue University conducted a comprehensive study aimed at analyzing the impact of various
factors on the urban thermal environment in outdoor spaces (Lai, et al., 2019). The study's
objective was to enhance the appeal of urban outdoor areas by mitigating thermal discomfort,
thereby encouraging greater public use of these spaces (Lai, et al., 2019). To achieve this, the

22
research team examined four primary mitigation strategies: optimizing urban geometry,
increasing vegetation cover, implementing cool surface materials, and integrating bodies of
water.
The findings from the study revealed that on summer days, adjustments to urban geometry led to
the most significant median air temperature reduction of 2.1 Kelvin (K), closely followed by the
introduction of vegetation and cool surfaces, which resulted in reductions of 2.0 K and 1.9 K,
respectively (Lai, et al., 2019). The addition of water bodies contributed to a median temperature
decrease of 1.8 K. Notably, altering urban geometry was identified as the most effective method
for enhancing thermal comfort, demonstrating a median reduction in physiologically equivalent
temperature (PET) of 18.0 K during summer months (Lai, et al., 2019). The incorporation of
vegetation and water bodies also proved beneficial, reducing median PET by 13.0 K and 4.6 K,
respectively (Lai, et al., 2019).
These empirical results provide critical insights for urban designers and planners focused on
developing thermally comfortable urban open spaces. By strategically employing these
mitigation strategies, it is possible to create more inviting and habitable outdoor environments
for the public (Lai, et al., 2019).
2.3.1 Urban Geometry and Radiation:
The relationship between urban spaces and solar radiation is a critical aspect of urban planning,
particularly with respect to achieving optimal thermal comfort in densely populated areas.
Compact urban environments, characterized by low Sky View Factors (SVF) or elevated Heightto-Width (H/W) ratios, are markedly less exposed to solar radiation (Lai, et al., 2019). This
diminished exposure significantly reduces heat stress and mean radiant temperature (Tmrt),
thereby enhancing thermal comfort during the warmer months (Lai, et al., 2019).
Moreover, the concentration of solar and long-wave radiation in these compact settings is lower
compared to more expansive, open spaces—a consequence attributed to the limited number of
solid surfaces available to emit long-wave radiation (Lai, et al., 2019). Notably, the influence of
long-wave radiation on Tmrt becomes especially pronounced at night, leading to a decrease in
temperature with increased spatial openness (Lai, et al., 2019).
The research also shows the significant role of street orientation in determining solar radiation
exposure and, consequently, its impact on thermal comfort within urban settings (Lai, et al.,
2019). Streets that are aligned on an East-West (E-W) axis are notably subjected to extended
periods of solar exposure compared to their North-South (N-S) counterparts, intensifying the
thermal load experienced in these areas (Lai, et al., 2019). They found that N-S oriented streets,
particularly those with a Height-to-Width (H/W) ratio exceeding 0.8, can maintain thermally
comfortable conditions for most of the day (Lai, et al., 2019). This is contrasted with E-W
oriented streets, where even an increase in H/W ratio to 3.0 does not necessarily improve the
thermal environment (Lai, et al., 2019).

23
Furthermore, streets with intermediate orientations, such as Northeast-Southwest (NE-SW) and
Northwest-Southeast (NW-SE), were found to be beneficial alternatives by providing partial
shading, which significantly mitigates discomfort durations (Lai, et al., 2019).. This analysis of
the dynamics between urban form, street orientation, and solar exposure showcases the need for
strategic urban design (Lai, et al., 2019).
2.3.2 Urban Geometry and Air Temperature:
The research indicates that compact urban spaces, which limit direct solar radiation through
strategic configurations, significantly reduce air temperatures compared to their more expansive
counterparts (Lai, et al., 2019). This is shown in the lower temperatures within deep urban
canyons, such as those observed in Fez, Morocco, Dhaka, and Bangladesh, where high Heightto-Width (H/W) ratios and low Sky View Factors (SVF) have led to temperature differentials as
substantial as 6.6 K when compared to shallower urban formations (Lai, et al., 2019). This
relationship changes during the night hours, where open spaces achieve greater thermal reduction
through enhanced long-wave radiation dissipation (Lai, et al., 2019).
2.3.3 Urban Geometry and Thermal Comfort:
In hot climates, the thermal comfort of urban spaces is significantly influenced by integrated
environmental factors such as radiation levels, air temperature, and wind speed (Lai, et al.,
2019). Compact urban forms, characterized by their ability to lower these factors, generally
provide enhanced thermal comfort through reduced radiation and cooler ambient temperatures
(Lai, et al., 2019). However, the resultant decrease in wind speed can potentially detract from
comfort levels during summer months (Lai, et al., 2019). To quantify thermal comfort, indices
like the Physiologically Equivalent Temperature (PET) are employed, with research consistently
demonstrating that the cooling benefits afforded by shade in densely built environments
outweigh the negative impacts of diminished wind speed (Lai, et al., 2019). Seasonal variations
further complicate urban design considerations, as the thermal advantages of compact urban
morphology are more evident in summer than in winter (Lai, et al., 2019). Conversely, during
winter, open spaces that allow greater solar access can prove more comfortable. This dichotomy
underscores the necessity for a balanced urban design strategy that accommodates the divergent
thermal comfort needs of both warmer and cooler seasons, particularly in temperate regions
where seasonal climate fluctuations are significant (Lai, et al., 2019).
2.4 Role of Shading in Enhancing Thermal Comfort and User Experience

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2.4.1 Shading Effects on Park Attendance - Taiwan, China
In their study examining the impact of shading on public park attendance and thermal comfort in
southern Taiwan, researchers sought to understand how thermal comfort and adaptation
influence the utilization of outdoor spaces, with a particular focus on the effects of varying
shading levels (Lin, et al., 2013). Utilizing a comprehensive methodology that included field
investigations, micrometeorological measurements, park attendance estimations, and thermal
comfort questionnaire surveys, the study provided significant insights into the role of shading in
public spaces (Lin, et al., 2013).
The research found that during cooler seasons, visitor numbers in unshaded areas of the park
increased with rising thermal conditions, whereas in hot seasons, attendance in these areas
decreased (Lin, et al., 2013). In contrast, shaded areas witnessed an increase in attendance
regardless of the season, highlighting the universal appeal of shaded spaces in mitigating thermal
discomfort (Lin, et al., 2013). This pattern underscores the tendency of individuals to migrate
from unshaded to shaded areas as a behavioral adaptation to thermal conditions, including
adjustments in clothing or actively seeking shaded spots (Lin, et al., 2013).
Further, the study revealed that the range of thermal comfort deemed acceptable by participants
significantly influenced overall park attendance across different seasons (Lin, et al., 2013). It
also highlighted how individual differences in thermal adaptation affected the use of varied
spaces within the park (Lin, et al., 2013). In doing so, the research filled a gap in existing
literature that predominantly focused on unshaded sites, offering comparative insights into user
behavior in both shaded and unshaded areas (Lin, et al., 2013).
The findings of this study are particularly relevant for urban planning and design. In hot
climates, such as Taiwan's, the importance of shading in public spaces becomes paramount in
enhancing comfort and increasing utilization (Lin, et al., 2013). This is evident from the
increased use of shaded areas in the park during both cool and hot seasons (Lin, et al., 2013). The
study not only affirms the significance of shading in public spaces but also contributes to a
nuanced understanding of how thermal comfort and adaptation shape space utilization (Lin, et
al., 2013).
2.4.2 Equitable Shading - El Paso, Texas
Architects Ersela Kripa and Stephen Mueller's work in El Paso, Texas, focuses on addressing
shade inequity and the associated health risks due to UV exposure (Bentancourt, 2023). After
their relocation to teach at Texas Tech University, Kripa and Mueller quickly identified the
critical lack of shade in El Paso's desert environment and its impact on pedestrian comfort and
safety (Bentancourt, 2023). At the Project for Operative Spatial Technologies (POST), they
embarked on a study to map shade inequity, correlating it with income levels and ZIP codes
(Bentancourt, 2023). Their research revealed that lower-income areas and high-traffic locations

25
like border crossings suffered from a significant lack of shade compared to more affluent
neighborhoods (Bentancourt, 2023). This disparity in shade access not only leads to discomfort
but also exposes individuals to health risks, such as skin damage from UV radiation
(Bentancourt, 2023). To tackle this issue, the duo began to assess and visualize areas of shade
inequity by constructing maps using satellites that highlight areas with high outdoor activity
(Bentancourt, 2023). After that, they run the collected data through their own algorithm that can
detect if these areas are subject to high levels of UV radiation (Bentancourt, 2023). They then
applied this research to design practical solutions and started with creating a prototype for a steel
shade structure for an outdoor classroom for Insight Science (Bentancourt, 2023). The structure
is aimed at providing the same benefits as trees but in a water-scarce desert setting (Bentancourt,
2023). The goal of this structure is to serve as prototypes for similar urban implementations,
potentially transforming the way cities like El Paso approach public space design to combat
environmental challenges (Bentancourt, 2023). This body of work by Kripa and Mueller stands
as a testament to the importance of shade in urban planning, especially in areas with harsh
environmental conditions, and underscores the need for innovative, sustainable solutions to
enhance public health and comfort (Bentancourt, 2023).
Figure 18: Rendering of Outdoor Classroom prototype for Insights Science by Kripa and Mueller – (Bentancourt, 2023)
2.5 Lack of Safety Provided by Current Bus Stops
A 2001 study conducted by UC Berkeley delved into the crime rates at bus stops in Los Angeles,
examining the impact of various environmental factors on bus stop crimes. The researchers
discovered that bus stops situated near alleys, multifamily housing, liquor stores, check-cashing

26
establishments, vacant buildings, and graffiti-ridden areas experienced higher crime rates.
Conversely, bus stops equipped with shelters and clear visibility had lower crime rates (Liggett,
et al., 2003).
These findings are particularly pertinent given the current state of bus stops in Los Angeles,
many of which are inadequately lit, rendering them dark and potentially unsafe at night. A report
by the Los Angeles Department of Transportation further highlighted the heightened risk of
harassment faced by women of color in public transportation (Jimenez & Albeck-Ripka, 2023).
Bus shelters have been proven to alleviate these safety concerns, as they not only provide respite
from the heat but also enhance women's perception of safety and reduce perceived wait times
(Brozen, et al., 2023). These studies collectively emphasize the critical need for infrastructure
improvements at bus stops to bolster the safety and well-being of public transportation users in
Los Angeles.
A 2010 study surveyed 749 transit users at 12 transit stops around Los Angeles, revealing that
user satisfaction at a transit stop is predominantly influenced by reliable service and a sense of
personal safety (Iseki & Taylor, 2010). The study identified several factors that contribute to
rider satisfaction at transit stations, including on-time performance, security presence, adequate
lighting, safety during the daytime, ease of movement, and clear signage (Iseki & Taylor, 2010).
2.6 Inequity of Bus Shelter Distribution
Los Angeles, revealing that cities within the "2nd District" account for 35% of the total bus
ridership in Los Angeles County. These areas, characterized by higher socioeconomic and transit
needs, include Carson, Compton, Culver City, El Segundo, Gardena, Hawthorne, Hermosa
Beach, Inglewood, Lawndale, Los Angeles (portion), Manhattan Beach, and Redondo Beach.
Notably, these areas also represent one-third of the county's unsheltered bus stops (Yoon, 2023).
The lack of bus shelters disproportionately affects Black and Hispanic riders, exacerbating the
disparities in temperature experienced by different communities in Los Angeles. A study by the
Los Angeles Urban Cooling Collaborative found that Black and Latino communities are most
impacted by increased temperatures, with Latino communities experiencing temperatures that
are, on average, 4 degrees warmer than predominantly non-Latino areas. Similarly, areas with
Black residents record higher temperatures during extreme heat days compared to areas without
Black residents (Brozen, et al., 2023). Additionally, the urban heat island effect, which results in
higher temperatures in cities, disproportionately affects low-income, low-education, and highpoverty communities, which also have a higher percentage of public transit riders (Lanza &
Durand, 2021).
A 2010 study by Berkeley researchers aimed to optimize bus shelter distribution in Los Angeles,
analyzing the functions of shelters and factors influencing their placement. Traditionally, bus
shelter placement has been influenced by potential advertising revenue, political concerns for
geographic equity, and bus rider usage (Law & Taylor, 2010). In 1980, the Los Angeles

27
Department of Transportation (LADOT) developed criteria for planning bus shelter placement,
considering factors such as passenger volume, pedestrian congestion, space availability, and
employment levels in an area (Law & Taylor, 2010). The study identified 249 locations where
bus shelters would significantly improve the user experience. In 1981 and 1982, LADOT
awarded contracts to a private firm for the addition of 500 shelters, granting the firm rights to
place advertisements on the shelters and maintain them. The city would receive a percentage of
annual gross advertisement revenue, starting at 8% and increasing to 13% in 2010 (Law &
Taylor, 2010). However, as of 2010, none of the top 26 bus stops for daily riders had a bus
shelter, highlighting the prioritization of advertising revenue over rider needs (Law & Taylor,
2010). The 1987 bus shelter contract stipulated that shelters would be placed based on "city
request, bus service data, and program revenue considerations," with the vague requirements
often resulting in an emphasis on revenue generation rather than rider comfort. Figure 3 below
illustrates the Los Angeles City Bureau of Engineering’s point system for determining bus
shelter placement (Law & Taylor, 2010).
Figure 19: Criteria for Shelter Location Selection in Los Angeles – UC Berkely: Shelter from the Storm (Law & Taylor, 2010)
This approach has led to a disproportionate number of bus shelters being placed in high-income,
low-ridership areas such as the San Fernando Valley, as opposed to high-ridership, low-income
areas like South-Central LA (Law & Taylor, 2010).

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2.6 Bus Shelter Case Studies: Strength and Weaknesses
2.6.1 La Sombrita Bus Shade:
Over the years, numerous efforts have been made to address the challenge of providing adequate
shade at bus stops, with varying degrees of success. One notable attempt was the "La Sombrita
Bus Shade" project. Initiated as a collaboration between the Los Angeles Department of
Transportation and the Kounkuey Design Initiative, La Sombrita aimed to offer shade during the
day and illumination at night (Jimenez & Albeck-Ripka, 2023). Specifically tailored for women
riders, the project addressed concerns about nighttime safety (Carpenter, 2023). However, after
the installation of four La Sombrita shades, the initiative faced significant public and critical
backlash. Critics argued that the perforated metal structure, with its short overhang, failed to
provide sufficient shade, an irony given that "La Sombrita" translates to "little shadow" in
Spanish (Jimenez & Albeck-Ripka, 2023). This was seen as a failed attempt in the eyes of the
public. These shades were strategically placed in low-income communities with above-average
ridership as part of a pilot program to explore minimalistic shading solutions (Jimenez &
Albeck-Ripka, 2023). The compact design allowed for attachment to existing LADOT signs
without the need for permits, making it a simpler alternative to larger bus shelters or planting
sizable trees on narrow sidewalks (Carpenter, 2023) (Jimenez & Albeck-Ripka, 2023).
Defending the design, the Kounkuey Design Initiative highlighted the shade's quick installation
time (under 30 minutes), lack of permit requirements, and cost-effectiveness, being just 15% of
the price of conventional bus shelters (Jimenez & Albeck-Ripka, 2023). Additionally, each La
Sombrita shade featured a QR code linking to a feedback survey (Carpenter, 2023). Importantly,
the project was entirely grant-funded, ensuring no city tax dollars were expended on the shades
(Miranda, 2023). This thesis is dedicated to the development of shading structures designed to
offer effective and consistent shading for users, irrespective of the bus shelter's orientation.
While the La Sombrita project presented an innovative concept, its implementation fell short in
providing sufficient shade coverage, a key aspect this research aims to enhance.

29
Figure 20: La Sombrita Bus Shade – Kounkuey Design Initiative (Capps, 2023)

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Figure 21: La Sombrita Bus Shade – Kounkuey Design Initiative (Capps, 2023)

31
Figure 22: La Sombrita Bus Shade – x: @LADOTofficial (Los Angeles Department of Transportation, 2023)
2.6.2 Big Blue Bus Stops – Santa Monica:
In 2016, Santa Monica unveiled its innovative Big Blue Bus Stops, a collaborative design effort
by Lorcan O’Herlihy Architects and Bruce Mau Design, commissioned by the City of Santa
Monica (Lorcan O’Herlihy Architects, 2016). The design vision was to establish a "continuous
visual identity" throughout the Santa Monica Big Blue Bus route. These bus stops features
include flexible seating, solar panels, clear signage, an ADA-compliant area with a loading zone,
LED downlighting, and provisions for both shade and rain protection. Additionally, they are
equipped with recycling and trash receptacles. Notably, the construction material for these bus
stops is environmentally conscious, utilizing 100% recycled steel (Lorcan O’Herlihy Architects,
2016). The Big Blue Bus Stops received favorable feedback from the community due to
significant enhancements over existing bus shelters, including the addition of a bus route map
and improved lighting. However, akin to the previous case study, these shelters fall short in
offering sufficient shade coverage, an essential aspect for user comfort.

32
Figure 23: Big Blue Bus Stop – (Lorcan O’Herlihy Architects, 2016)
Figure 24: Big Blue Bus Stop – (Lorcan O’Herlihy Architects, 2016)

33
Figure 25: Big Blue Bus Stops – (Lorcan O’Herlihy Architects, 2016)
2.6.3 SOM Bus Shelter:
In 2022 a new bus shelter contract was signed between Tanzito-Vector and the city of Los
Angeles (Tu, 2023). As part of the Sidewalk and Transit Amenities Program (STAP) The new
contract promises to take the number of bus shelters from 1,870 to 3,000 by 2028 (Tu, 2023).
However, the funds are still needed to fulfill this goal. The program currently has over $114
million to invest in the project and hope to collect more funding through advertising revenue
after installing the first 180 shelters (Tu, 2023). Most of the project budget will not go to design
or construction of the shelters themselves, but to rebuild sidewalks to make them ADA
compliant (Tu, 2023). These shelters were designed by SOM in collaboration with Fehr & Peers,
Studio 111, Designworks, and Tolar Manufacturing (Volpi, 2023). The intent of the design is to
provide shade and enhances safety while incorporating technology, art, and transit information
(Volpi, 2023). Some special features include scooter docking stations, e-lockers, and information
wayfinding kiosks (Volpi, 2023). The design is inspired by “California Modernism” and aims to
be both visually cohesive and community tailored. They are designed as a kit of parts and allow
for flexibility through the ability to be expanded in areas that need it (Volpi, 2023). The SOM
bus shelters represent the most advanced and promising design solution to date, yet their

34
installation is still pending. However, as illustrated in the figures below, there is a concern that
these shelters might provide insufficient shading, due to their design lacking a back wall.
Figure 26: SOM Bus Shelter – (Volpi, 2023)
Figure 27: SOM Bus Shelter – (Volpi, 2023)

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2.7 Summary
This literature review reveals the challenges in designing and installing bus shelters in Los
Angeles as well as several attempts to help solve the problem. The analysis of various studies
paints a comprehensive picture of the hardships of daily transit users, particularly in the areas of
heat stress, equity, and safety. Research also highlights how urban geometry affects the thermal
comfort of outdoor spaces, demonstrating how the size and depth of urban areas influence
radiation levels, air temperature, and overall thermal comfort. The exploration of different bus
shelter designs, ranging from the simple yet controversial La Sombrita Bus Shade to the
sophisticated and multifunctional SOM Bus Shelter, showcases a spectrum of creative responses
to these urban challenges, and demonstrates numerous design philosophies and their practical
implications. The key takeaway from this review is the critical role of thoughtful, user-centric
design in enhancing the efficiency and appeal of public transit systems. As urban areas like Los
Angeles continue to grow and evolve, the insights from this body of work provide valuable
guidance for the development of public transit infrastructure.

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3 CHAPTER THREE: METHODOLOGY
3.1 Introduction
This chapter outlines the methodology adopted for addressing the challenges associated with bus
shelters in Los Angeles, particularly focusing on aspects of temperature control and shading. The
chosen design-oriented methodology aims to offer a pragmatic solution, addressing the problems
identified in earlier sections of this thesis. This approach is important in fostering a
comprehensive understanding of the existing inadequacies in Los Angeles bus shelters, and it
establishes a structured framework for devising a solution centered on enhancing passenger
comfort and satisfaction.
In contrast to alternative research methodologies such as case studies or surveys, this study
employs a solution-focused strategy lead by design thinking principles. The rationale behind this
choice is to directly engage with the problem through creative and practical solutions, rather than
purely analytical or observational methods.
The core of this methodology is the development of a versatile, modular bus shelter shade
system. This system is designed to be adaptable to varying orientations of bus stops, thereby
maximizing its effectiveness and applicability across different settings within Los Angeles. The
subsequent sections detail a systematic plan encompassing research, design, and construction
phases, all aimed at fulfilling the objectives of this project. This structured approach ensures a
methodical progression from conceptualization to real-world implementation, facilitating a
thorough evaluation of the proposed solution in practical scenarios

37
3.2 Methodology Diagram:

38
3.3 Identify Problem
The research will begin with a comprehensive evaluation of existing literature and datasets,
focusing on the challenges and conditions of bus stop shelters in Los Angeles, particularly
regarding temperature fluctuations and passenger safety. This evaluation will encompass two
principal investigative aspects:
o Analysis of Bus Temperature Data: This stage will involve a detailed scrutiny of
temperature data related to bus stops. The aim will be to identify patterns and highlight
bus stops that are exceptionally susceptible to extreme heat. Identifying these critical
points will direct the research toward areas where interventions are most urgently
required.
o Assessment of METRO Ridership Surveys: In this phase, METRO ridership surveys
will be thoroughly reviewed to ascertain user experiences and needs. This analysis will be
pivotal in measuring user satisfaction and pinpointing specific requirements for
improvement. Furthermore, this survey review will also yield valuable insights into the
demographics of the passengers who frequent these high-heat-risk stops, facilitating a
more focused and effective design strategy.
These initial steps will be fundamental in laying a robust empirical groundwork for the project.
By comprehensively understanding the current challenges and conditions, the research will
ensure that the proposed design solutions are not only based on factual evidence but are also
finely tuned to address the specific needs of bus stop users effectively. This methodology,
centered on data-driven analysis and user-focused insights, will position the research to develop
solutions that are both pertinent and impactful in enhancing the safety and comfort of bus shelter
users in Los Angeles.
3.4 Design
During the design phase, this project will utilize software simulation tools to conduct a thorough
analysis of current bus shelters. This analysis will serve as the foundation for developing
iterative bus shading solutions. The simulations will not only evaluate the efficacy of existing
shelter designs but also investigate potential enhancements.
This phase will be structured into three primary stages:
o Defining design criteria: A set of design criteria will be established, which will guide
the design and development process. These criteria will be based on the insights gathered
from reviewing code requirements, reviewing city requirements, and testing existing
solutions and identifying areas of improvement.
o Design and development: Building upon the established criteria, a series of shading
solutions will be conceptualized and developed. This process will involve iterative
design, where multiple prototypes will be created, evaluated, and refined. The aim is to

39
explore a range of designs that can be adapted to different orientations and configurations
of bus stops.
o Design testing: Each shading solution will undergo testing through simulations. These
tests will assess the solutions' performance and their ability to meet the established design
criteria. The testing process will be crucial in identifying the most effective and practical
solutions suitable for implementation in real-world scenarios.
3.4.1 Define Design Criteria
The design criteria will be established by conducting a thorough examination of the 2023
California Building Code found in the International Code Council digital library. The focus will
be on sections that dictate the design and functionality of transportation facilities. These sections
include:
o Section 11B – 810.0: This section outlines the requirements for accessibility in
transportation facilities, ensuring that shelters are accessible to all, including individuals
with disabilities.
o Section 11B – 810.2: This section details the standards for boarding and alighting areas,
which will dictate the spatial layout and the flow of commuter traffic in and around the
shelters.
o Section 11B – 305: This section provides specifications for clear floor or ground space,
which will be crucial for determining the footprint of the shelter and ensuring it provides
sufficient space for a wheelchair to maneuver.
o Section 11B – 402: This section describes the requirements for accessible routes,
informing pathways to and from the shelters.
Figure 28: International Conde Council Digital Codes - (Anon., 2022)

40
Furthermore, requirements from the Valley Transportation Authority and the Foothill Extension
Bus Interface Plan will be reviewed to ensure that the designs conform to a broad range of
operational standards and community expectations.
After that, existing conditions will be tested, with the site being chosen based on existing
temperature data, specifically targeting the hottest bus stop areas in Los Angeles. The site
location will be chosen based on the bus stop temperature and rider density studies done by
Climate Resolve. This study analyzed the hottest bus stops in Los Angeles with the highest
average daily rider numbers in the county.
After a location is chosen, the weather data for the specific location will be downloaded through
the Ladybug EPW map. This website is a global map with weather data for different locations.
The weather files downloaded provides weather data in several different formats. Our desired
simulations will use the “.epw” and “.stat” files.
Figure 29: Climate Resolve Hottest in LA Bus Stop Map - (Anon., n.d.)

41
Climate Consultant will be utilized to analyze site conditions. This will help generate graphs like
what is shown in the figure below. This will help understand the relevant conditions that can
influence design, such as but not limited to:
o Sun Chart & Sun Shading Chart: South facing orthographic projection of the sun’s
trajectory. The chart will represent the sun patterns from due west to due east
horizontally, and from zero to 90 degrees vertically. These charts will show the sun path
from sunrise to sunset throughout the year, with color coding to indicate daily
temperatures and specific times when shade is most needed
o Temperature Range: A chart that will display the comfort zone level in a specific
location. This will include temperature ranges below the comfort zone, indicating a
heating-dominated climate, and ranges above the comfort zone, suggesting a coolingdominated climate. This analysis will be crucial in understanding and addressing the
thermal comfort requirements of the bus shelter users.
Figure 30: Ladybug Tools EPW Map - (Anon., n.d.)

42
o Monthly Diural Averages: This component will compile and chart several daily
variables, such as dry bulb temperature, wet bulb temperature, and solar radiation. The
chart will also highlight the ideal comfort zone levels, offering a comprehensive view of
the environmental conditions and how they align with or deviate from the desired
comfort standards.
Several simulations will be done to test existing and improved bus shelter conditions, and each of
the simulations will test bus shelters in following orientations:
o North facing
o South facing
o East facing
o West facing
o North-West facing (30º)
o North-East facing (30º)
o South-West facing (30º)
o South-East facing (30º)
Figure 31: Climate Consultant Results

43
First, this research will conduct a simulation to determine the Universal Thermal Climate Index
(UTCI) simulation will be initiated. This simulation will be done using components in Ladybug.
This will involve the 3D modeling of an existing bus shelter in Rhino, employing photographs
and measurements of current structures to guarantee model accuracy. The aim is to simulate realworld conditions as accurately as possible to ensure the validity of the simulation results. The
primary objective of this simulation is to determine the optimal amount of shading for differently
oriented bus shelters to optimize the thermal comfort for bus riders. The UTCI is instrumental in
evaluating the perceived "feels like" temperature experienced by individuals awaiting transit
services under these shelters. To accurately determine the UTCI, the initial step involves
calculating the Mean Radiant Temperature (Tmrt). This is calculated by examining the human to
sky relation of individual stationed under the bus shelter. This systematic approach ensures a
comprehensive understanding of the thermal environment, facilitating the design of the bus
shelter shading extensions that will enhance the comfort levels of public transit users. The
optimal shading pattern for each bus shelter orientation will be identified utilizing Ladybug's
Thermal Shade Benefit component. This component is designed to analyze a specific shading
area —in this instance, the bench surface—and generate an optimal shading pattern, similar to
what is shown below. This pattern aims to ensure that individuals waiting under the shelter
experience the desired UTCI conditions. This simulation will produce hourly temperature
readings for the months of April – October. The temperature readings will be filtered into three
batches. Batch 1 is for readings between 0℃-19℃. Batch 2 is for readings between 20℃-26℃
which is considered the ideal thermal comfort temperature. Batch 3 is for readings between
27℃-45+℃. The objective is to decrease the number of temperature readings falling in the third
batch, which are high temperatures that can subject riders to thermal heat stress. An analysis for
the existing condition will be done and compared to that of the designed condition.
Figure 32: Ladybug shade benefit analysis
For data visualization, several simulations in this study will utilize hourly plots. These plots are
typically used to display readings for every hour throughout the year. However, to align with the
specific aims of this research, the analysis will be limited to the daylight hours in Los Angeles,
from 05:00 to 20:00 and between the months of April - August. This approach allows for a
focused examination of the thermal comfort conditions experienced by transit riders in Los

44
Angeles during periods of solar exposure. Below is an example of the hourly plot that will be
employed:
Figure 33: Ladybug hourly plot
The second set of simulations involve a surface temperature study using the Grasshopper plugins
Honeybee and EnergyPlus. This is done to investigate the thermal impact of prolonged solar
exposure on bus shelters in Los Angeles. The objective is to understand the heating effect on the
seating surfaces utilized by passengers as they wait. The primary focus of this simulation is to
calculate the hourly surface temperature of the seating surfaces. This is a critical aspect of the
study based on the assumption that the temperature experienced by these surfaces accurately
reflects the thermal conditions to which bus riders are subjected while seated.
Since Honeybee was used for the surface temperature simulations, it is important to assign
material properties to each surface to reflect the thermodynamic responses of the bus shelters and
their components under solar exposure. For the purpose of this study, the shelters and seating
were assumed to be aluminum and positioned atop sidewalks composed of cement. Accordingly,
aluminum's material properties were attributed to all surfaces of the bus shelter, encompassing
both the seating and shading elements, while cement properties were designated for the sidewalk
surface. These material characteristics were sourced from the MatWeb material property
database. The specific construction data incorporated into the simulation encompassed the
following parameters:
• Thickness [m]
• Conductivity [W/m-K]
• Density [kg/m3
]
• Specific heat [J/kg-K]

45
Figure 34: MatWeb website for material properties. (MatWeb, n.d.)
The surface temperature data is analyzed in the same manner as the previous simulation, where
hourly temperature readings are sorted into categories. The goal is to reduce the number of
readings in the third category, which represents high, uncomfortable temperatures.
The third simulation done is the shading study using Rhino along with the Grasshopper plugins
Ladybug and Honeybee. This study will utilize the date, time, and sun orientation of the highest
temperature reading found in the temperature study. This will be crucial in understanding how
shading patterns differ with each orientation and how they can affect bench seating surface
temperature. Assuming the high temperature on the seating surface is caused by inadequate
shading the temperature data will be used to analyze shading patterns. The intention is to
improve shading quality. For the purpose of this research good shading quality is measured by
have shading that covers the full bench surface during the time of the hottest temperature
reading.
Figure 35: Ladybug shading study example - (Interactive Shadow Study and animation in Ladybug Rhino 004 mp4, 2020)

46
3.4.2 Design and Development
With the foundational data established, the research will proceed to explore additional shading
design and placement for each bus shelter orientation and assessing the resultant performance
improvements. The design iterations will depend on four key performance metrics:
o Temperature Performance: The effectiveness of the shading will also be measured in
terms of its ability to reduce high hourly UTCI and surface temperatures. This analysis
will determine the most efficacious shade location and size for each orientation.
o Shading Performance: This will be analyzed based on the interplay between the shade
provided and the bus shelter seating. The objective is to maximize shaded hours on the
bench surface during the peak summer months, enhancing user comfort and safety.
o Safety: The design will also prioritize the safety of bus shelter users by maintaining clear
visibility and situational awareness through the shading structures. Ensuring that riders
can see their surroundings reduces the risk of accidents and enhances the sense of
security, particularly important in urban environments where safety concerns are
prevalent.
o Aesthetic Appeal: The aesthetic aspect of the shading is significant. The design aims to
integrate with the urban landscape, providing not only functional benefits but also
enhancing the visual appeal of the bus shelters. By creating an attractive design, the
project seeks to contribute to the overall urban aesthetic and user experience, making the
bus shelters inviting and pleasant for daily commuters.
While an entirely opaque shading system would indeed maximize temperature reduction and
shading performance, the design of the shading screen intentionally includes openings for several
important reasons. These perforations are crucial to achieving a balance between all the
performance metrics stated above:
o Visual Connection and Safety: Openings in the shading screen allow users to maintain a
visual connection with their surroundings, enhancing the feeling of safety and awareness.
This is particularly important in urban settings where situational awareness can
significantly contribute to the comfort and security of the riders.
o Aesthetic Appeal: The design incorporates aesthetic considerations in both its form and
its performance. It uses perforations to create visually appealing patterns that can
transform a functional element into a piece of urban art. Openings enable a dynamic
interplay of light and shadow, which can create a more engaging and less monotonous
environment. This not only improves the visual landscape but also fosters a more pleasant
waiting experience for bus riders.
o Ventilation and Airflow: The openings help facilitate ventilation, allowing air to
circulate freely through the shelter.
o Seasonal Performance: The shading is designed to reduce temperatures during the
summer months, improving thermal comfort. The openings allow sunlight to penetrate
during cooler months, maintaining thermal comfort and preventing the area beneath the

47
shelter from becoming too cold. This balance ensures year-round usability and comfort
for shelter users.
Similar to the president shown below, the innovative aspect of this design will be its modularity.
The shading for each orientation will be conceptualized to be assembled using interchangeable
parts, which can be rearranged to suit different configurations.
Figure 36: Erwin Hauer shading screens - (filzfelt, n.d.)
The next stage will involve extracting the surface area of the additional shading structure
required and embarking on an iterative design process. This process will be conducted using
Rhino/Grasshopper, with the aim of developing a modular shading system adaptable to various
orientations.
This iterative design phase will start with the development of one or more core modules, forming
the base of the design. This will involve selecting a general form and exploring various
panelization methods or starting with a base shape and refining it. Throughout this process,
small-scale models and prototypes will be created to evaluate design concepts. These iterations
will undergo multiple rounds of reviews and critiques, ultimately culminating in the selection of
the final design.
3.4.3 Design Testing
To assess the improvements in temperature control and shading efficiency, the newly developed
design will undergo a testing process using the same simulation tools previously applied to
analyze existing solutions, specifically employing Ladybug, Honeybee, and EnergyPlus for this

48
purpose. Such a consistent approach in testing both the existing and proposed designs ensures a
reliable comparison of their respective performances.
This meticulous testing process will be pivotal in validating the effectiveness of the new design,
ensuring it aligns with the predefined criteria. It will also provide an opportunity to identify and
rectify any aspects of the design that may require further refinement, thereby ensuring the
development of a well-considered and efficient shading solution.
The selection of the final design will be based on its performance in several key areas, as
determined by the following criteria:
Criteria
Temperature Reduction
Quality Shading
Aesthetically Pleasing
Cost Effective
Ease of Maintenance
Replicable
Ease of Construction
Ease of transport
Low Site Impact
3.5 Construction
3.5.1 Details and Construction Drawings
The progression from the design phase to the actual construction phase will necessitate the
production of detailed construction drawings. These drawings, which will be created using Rhino
and Revit, are intended to serve as a thorough blueprint for the fabrication of the shelter
Table 1: Shading Design Criteria

49
components. The creation of small-scale models will be a crucial step in this process, providing a
tangible understanding of the joinery and assembly techniques required.
A focus will be placed on developing intricate details for how the modules will interconnect with
each other and attach to the base of the bus shelter. These construction documents will
encompass exact measurements, material specifications, and step-by-step assembly instructions.
This level of detail is essential to ensure that the construction process accurately reflects the
design vision and maintains fidelity to the intended specifications.
After the completion of the construction drawings and detail plans, a comprehensive spreadsheet
will be compiled using Excel. This spreadsheet will be instrumental in managing the
procurement process, detailing the materials required, and monitoring costs and material usage.
This organized approach will facilitate effective resource management, ensuring that all
materials are acquired efficiently and within budget.
This revision aims to clearly articulate the transition from design to construction, emphasizing
the importance of detailed planning and effective resource management in realizing the design.
3.5.2 Building Large Scale Model
The final phase of the project's methodology entails the construction of a 1:1 scale prototype, an
essential step in translating the theoretical design into a physical manifestation. This stage is
critical in evaluating the design's functionality and structural integrity in a realistic setting.
The construction process will commence with the procurement of materials, as detailed in the
construction documents. The assembly of the prototype will adhere strictly to the specifications
and guidelines outlined in the detailed plans, ensuring accuracy and fidelity to the design intent.
3.6 Summary
A systematic and detailed approach has been outlined for designing and constructing a modular
bus shelter shade adaptable to various orientations in Los Angeles. It will commence with an
extensive review of existing conditions, including an analysis of bus temperature data and
METRO ridership surveys, to define the scope and nature of the problem. The design phase will
utilize advanced simulation tools such as Rhino, Grasshopper, Ladybug, and Honeybee to study
shading and temperature dynamics, ensuring that the shading solutions are versatile for different
bus shelter orientations. Detailed construction drawings, to be developed using Rhino and
AutoCAD, will guide the fabrication process of the shelter components, emphasizing modularity
and adaptability. The designs will then undergo rigorous testing through simulations to evaluate
their shading effectiveness and temperature control capabilities. Material procurement will be
managed efficiently using Excel spreadsheets. The methodology will culminate in the
construction of a 1:1 scale prototype. This prototype will serve as a tangible demonstration of the

50
design’s functionality and practicality. This methodology ensures that each phase, from initial
concept to real-world application, is planned and executed to enhance the comfort and safety of
bus shelter users in Los Angeles.

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4 CHAPTER FOUR: RESULTS
4.1 Introduction
This chapter presents the results of the simulations conducted to evaluate the effectiveness of
modular shading solutions designed for bus shelters in Los Angeles. Building upon the
methodologies outlined in Chapter 3, this section analyzes the impact of various shading designs
on Universal Thermal Climate Index (UTCI), bench seating surface temperature, and bench
seating shading quality. These indicators were selected to assess the potential improvements in
thermal comfort provided by the newly designed shading elements compared to existing
conditions. The findings are crucial for developing a scalable and versatile modular bus shelter
system that can adapt to different orientations and locations across the city, significantly
enhancing the usability and comfort of public transit amenities in urban heat environments.
4.2 Creating Rhino Model
The digital representation of the bus shelter was developed within Rhino based on an existing
shelter located in Los Angeles. This process involved field measurements of the bus shelter using
a tape measure to ensure accuracy. The dimensions recorded for the construction of the model
were as follows:
For the bus shelter shading canopy:
• Height: 96 inches
• Length: 156 inches
• Width: 52 inches
For the bus shelter bench:
• Height: 44 inches
• Width: 18 inches
• Length: 72 inches
Photos of the bus shelter were also used to create the model, supplementing the dimensions
taking. The model serves as a foundational element for subsequent analyses in this research.

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Figure 37: Isometric view of bus shelter model
Figure 38: Front view of bus shelter model
156”
96”
44”
72”

53
Figure 39: Side view of bus shelter model
4.3 Universal Thermal Climate Index & Shade Benefit
The initial simulation deployed the Universal Thermal Climate Index (UTCI) to assess comfort
levels at bus shelters for individuals waiting at benches. This assessment involved comparing
UTCI readings under three different shading conditions alongside a control scenario with no
shade. The conditions examined included: existing bus shelter shading, optimal shading as
generated by the Ladybug tool's "Shade Benefit Analysis," and a custom-designed shading
configuration proposed for real-world application. The existing shading condition utilized
current bus shelter designs, while the optimal shading condition was generated through the
Ladybug tool to create the most effective shading pattern for maintaining a specified mean
radiant temperature. The designed shading condition was based on practical, deployable shading
structures. For the purposes of this simulation, a comfort temperature of 26℃ was targeted. The
Ladybug tool facilitated the addition of specified work areas where shading would be optimal,
automatically generating a shading pattern that best fit these designated zones as discussed in
Chapter 3. The results indicated that the UTCI readings under the designed shading conditions
52”
18”

54
closely matched those achieved by the optimal shading, demonstrating the effectiveness of the
proposed designs in mimicking ideal shading conditions.
4.3.1 UTCI – No Shading
The UTCI analysis without shading provided crucial baseline data, which was segmented into
three temperature ranges:
1) 0°C to 19°C,
2) 20°C to 26°C (considered the comfort range),
3) 27°C to 45°C.
The primary objective of this part of the study was to reduce the frequency of readings within the
third group, particularly during the daylight hours from April to October, which are critical
periods of higher temperatures. This data helps to establish a benchmark against which the
effectiveness of the proposed shading solutions can be measured, aiming to enhance comfort
levels by minimizing exposure to excessively high temperatures.
Figure 40: Ladybug hourly plot
The accompanying chart categorizes the hourly UTCI readings into three distinct temperature
ranges, highlighting the distribution across each category. These readings, recorded with no
shade, reveal a predominance of readings in the third group (27°C to 45°C), which falls into the
uncomfortable temperature range, potentially leading to heat stress during the hot summer
months. This analysis sets the stage for a detailed comparison of UTCI readings across different
bus shelter orientations. By contrasting these no-shade readings with scenarios of optimal
shading and specifically designed shading, the study evaluates the effectiveness of each shading
solution in mitigating extreme heat and enhancing passenger comfort at bus stops.

55
Figure 41: UTCI Results – No Shading
4.3.2 UTCI – Under South Facing Shading
Below are images comparing the optimal shading and the specifically designed shading for a
south-facing bus shelter bench. These renderings help illustrate the differences in shading
patterns and layouts, highlighting how each perform in terms of providing effective shade. The
images serve as a practical reference to evaluate the functional aspects of both shading solutions,
while embracing the aesthetic qualities of the designed solution. This helps envision the designed
shading’s potential impact on enhancing commuter comfort in a real-world setting. 670757 1571
0℃ - 1 9℃ 2 0℃ - 2 6℃ 2 7℃ - 4 5℃
# OF TEMP READINGS
TEMPERATURE (℃)
UTCI - NO SHADING

56
Figure 42: Optimal shading layout – South facing
Figure 43: Designed shading layout – South facing

57
Figure 44: UTCI Results – South facing
Comparing the UTCI readings for the south-facing shelters reveals a significant improvement in
thermal comfort with the designed shading. Initially, the existing shading recorded 381 instances
of uncomfortable temperatures. After implementing the designed shading, this number was
reduced to 265, marking a 30% decrease in uncomfortable temperature recordings. This
substantial reduction demonstrates the effectiveness of the designed shading in enhancing
comfort levels at south-facing bus shelters.
4.3.3 UTCI – Under North Facing Shading
Figure 45: Optimal shading layout – North facing
670
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1112
757
1461
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217
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N O S H A D I N G E X I S T I N G S H A D I N G O P T I M A L S H A D I N G D E S I G N E D S H A D I N G
# OF TEMP READINGS
UTCI CHANGES - SOUTH FACING
0℃ - 19℃ 20℃ - 26℃ 27℃ - 45℃

58
Figure 46: Designed shading layout (front) – North facing bench
Figure 47: Designed shading layout (back) – North facing

59
Figure 48: UTCI Results – North facing
For the north-facing shelters, the UTCI analysis highlights a notable improvement in thermal
comfort with the implementation of the designed shading. Originally, the existing shading was
associated with 337 instances of uncomfortable temperatures. With the introduction of the
designed shading, this figure dropped to 250, equating to a 26% reduction in the number of
uncomfortable temperature readings. This result underscores the effectiveness of the newly
designed shading in enhancing comfort at north-facing bus shelters.
4.3.4 UTCI – Under East Facing Shading
Figure 49: Optimal shading layout – East facing
670
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N O S H A D I N G E X I S T I N G S H A D I N G O P T I M A L S H A D I N G D E S I G N E D S H A D I N G
# OF TEMP READINGS
UTCI CHANGES - NORTH FACING
0℃ - 19℃ 20℃ - 26℃ 27℃ - 45℃

60
Figure 50: Designed shading layout (front) – East facing
Figure 51: Optimal shading layout (Back) – East facing

61
Figure 52: UTCI Results – East facing
In the case of east-facing shelters, the UTCI readings show a significant reduction in
uncomfortable temperatures due to the implementation of the designed shading. Initially, there
were 360 recorded instances of discomfort under the existing shading conditions. After applying
the designed shading, these instances decreased to 271, representing a 25% reduction in
uncomfortable temperature readings. This demonstrates the effectiveness of the new shading
design in improving thermal comfort for east-facing bus shelters.
4.3.5 UTCI – Under West Facing Shading
Figure 53: Optimal shading layout – West facing
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N O S H A D I N G E X I S T I N G S H A D I N G O P T I M A L S H A D I N G D E S I G N E D S H A D I N G
# OF TEMP READINGS
UTCI CHANGES - EAST FACING
0℃ - 19℃ 20℃ - 26℃ 27℃ - 45℃

62
Figure 54: Designed shading layout (front) – West facing
Figure 55: Designed shading layout (back) – West facing

63
Figure 56: UTCI Results – West facing
For the west-facing shelters, the UTCI readings indicate a significant improvement in thermal
comfort following the implementation of the designed shading. Initially, the existing shading
configuration resulted in 416 instances of uncomfortable temperatures. With the new designed
shading in place, this number was reduced to 308, marking a 26% decrease in the number of
uncomfortable temperature readings. This data highlights the effectiveness of the newly designed
shading in enhancing comfort levels at west-facing bus shelters.
4.3.6 UTCI – Under North/East 30º Facing Shading
Figure 57: Optimal shading layout – North-east facing
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N O S H A D I N G E X I S T I N G S H A D I N G O P T I M A L S H A D I N G D E S I G N E D S H A D I N G
# OF TEMP READINGS
UTCI CHANGES - WEST FACING
0℃ - 19℃ 20℃ - 26℃ 27℃ - 45℃

64
Figure 58: Designed shading layout (front) – North-east facing
Figure 59: Designed shading layout (back) – North-east facing

65
Figure 60: UTCI Results – North-east facing
For the north-east facing shelters, the UTCI analysis demonstrates a noticeable enhancement in
thermal comfort with the implementation of the designed shading. Originally, there were 278
uncomfortable temperature recordings under the existing shading. After introducing the designed
shading, this number decreased to 217, reflecting a 22% reduction in uncomfortable
temperature readings. This significant improvement underscores the effectiveness of the
designed shading in increasing comfort levels at north-east facing bus shelters.
4.3.7 UTCI – Under North/West 30º Facing Shading
Figure 61: Optimal shading layout – North-west facing
670
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1032
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N O S H A D I N G E X I S T I N G S H A D I N G O P T I M A L S H A D I N G D E S I G N E D S H A D I N G
# OF TEMP READINGS
UTCI CHANGES - NORTH EAST FACING
0℃ - 19℃ 20℃ - 26℃ 27℃ - 45℃

66
Figure 62: Designed shading layout (front) – North-west facing
Figure 63: Designed shading layout (back) – North-west facing

67
Figure 64: UTCI Results – North-west facing
For the north-west facing shelters, the UTCI readings highlight a substantial improvement in
comfort with the application of the designed shading. Initially, there were 363 instances of
uncomfortable temperatures recorded under the existing shading conditions. With the
implementation of the designed shading, this number was reduced to 258, resulting in a 30%
decrease in uncomfortable temperature readings. This demonstrates the effectiveness of the new
shading design in significantly enhancing thermal comfort for north-west facing bus shelters.
4.3.8 UTCI – Under South/East 30º Facing Shading
Figure 65: Optimal shading layout – South-east facing
670
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1095
1088
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1429
1455
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1571
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N O S H A D I N G E X I S T I N G S H A D I N G O P T I M A L S H A D I N G D E S I G N E D S H A D I N G
# OF TEMP READINGS
UTCI CHANGES - NORTH WEST FACING
0℃ - 19℃ 20℃ - 26℃ 27℃ - 45℃

68
Figure 66: Designed shading layout (front) – South-east facing
Figure 67: Designed shading layout (back) – South-east facing

69
Figure 68: UTCI Results – South-east facing
For the south-east facing shelters, the UTCI analysis indicates a marked improvement in comfort
with the implementation of the designed shading. Initially, under existing shading conditions,
there were 383 uncomfortable temperature recordings. After the introduction of the designed
shading, this number was significantly reduced to 247, reflecting a 36% decrease in
uncomfortable temperature readings. This substantial reduction highlights the effectiveness of
the newly implemented shading in enhancing thermal comfort at south-east facing bus shelters
4.3.9 UTCI – Under South/West 30º Facing Shading
Figure 69: Optimal shading layout – South-west facin
670
929
1103
1082
757
1457
1486
1451
1571
383
220
247
N O S H A D I N G E X I S T I N G S H A D I N G O P T I M A L S H A D I N G D E S I G N E D S H A D I N G
# OF TEMP READINGS
UTCI CHANGES - SOUTH EAST FACING
0℃ - 19℃ 20℃ - 26℃ 27℃ - 45℃

70
Figure 71: UTCI Results – South-west facing
For the south-west facing shelters, the UTCI readings reveal a significant enhancement in
thermal comfort due to the implementation of the designed shading. Originally, there were 456
instances of uncomfortable temperatures recorded under existing shading conditions. With the
deployment of the designed shading, this figure was reduced to 293, translating to a 36% 670 988 1225 1140 757 1351 1349 1323 1571 456 212293
N O S H A D I N G E X I S T I N G S H A D I N G O P T I M A L S H A D I N G D E S I G N E D S H A D I N G
# OF TEMP READINGS
UTCI CHANGES - SOUTH WEST FACING
0℃ - 19℃ 20℃ - 26℃ 27℃ - 45℃
Figure 70: Designed shading layout (front) – South-west facing

71
decrease in uncomfortable temperature readings. This demonstrates the considerable
effectiveness of the newly designed shading in improving comfort levels at south-west facing
bus shelters.
Orientation % Improvement
South 30%
North 26%
East 25%
West 26%
North-East 22%
North-West 30%
South-East 36%
South-West 36%
The table demonstrates that implementing carefully designed shading across various bus shelter
orientations consistently achieves greater than a 20% improvement in UTCI readings in all
cases.
4.4 Surface Temperature & Shading Study
4.4.1 Surface temperature study – No shading
Table 2: Percentage of UTCI Improvement

72
The objective of the surface temperature study was to analyze the temperature variations of bus
stop seating surfaces across different bus shelter orientations, with a particular focus on assessing
the effects of shading on the temperature readings. First, a simulation was done to examine
bench surface temperatures in the absence of any shading. The simulation yielded the hourly
temperature readings with the top 15 exterior surface temperature readings analyzed as follows:
• The highest recorded temperature was 62.94°C (145.29°F) on September 01, 2023, at
12:00.
• Subsequent temperatures marginally decreased, with the second highest being 62.43°C
(144.37°F) recorded an hour earlier on the same day.
• The temperatures continued to fluctuate slightly with changes in date and time, yet
consistently remained above 60°C (140°F), illustrating significant heat exposure.
The fluctuating temperature readings hovered around 61.81°C (143.26°F) and 61.69°C
(143.03°F) for other peak times during July and September. The lowest of these top readings was
observed as 60.57°C (141.03°F) on July 09, 2023, at 12:00. Below is an hourly plot depicting the
temperature readings for a bench’s seating surface without any shading:
To justify the simulation data's reliability, empirical temperature readings were obtained from
existing aluminum benches in Los Angeles on October 20th, 2024, at 14:55. The measurements
revealed that a bench in direct sunlight reached a temperature of 134℉, whereas a bench situated
in the shade registered a significantly cooler temperature of 85.3℉. These real-world
observations closely align with the simulated data, affirming the accuracy and relevance of the
simulated temperature findings for understanding the thermal conditions at bus stop seating
areas.
Figure 72: Hourly plot of bench seating surface in ℃

73
After understanding the surface temperature of the bench without shading it was time to analyze
the shadings effects on the seating surface when oriented in different orientations. Similar to the
UTCI simulation the different readings will be compared for temperature readings of bench
surface under existing shading, optimal shading, and designed shading.
4.4.2 Surface temperature & shading studies – South Facing
Figure 73: Surface temperature hourly plot – South facing
The orientation of the bus shelter towards the south was analyzed to evaluate its impact on the
temperature of the seating surface, particularly during the months of April through October. This
period, encompassing the summer months, is characterized by the sun’s higher position in the
sky. Observations revealed that during the hours of 10:00 AM to 4:00 PM, the seating surface
temperatures ideally ranged between 20°C and 25°C. Contrarily, the morning hours from 7:00
AM to 10:00 AM registered undesirably high temperatures between 35°C and 40°C.
Additionally, instances of extremely elevated temperatures, ranging from 50°C to in excess of
55°C, were recorded. These higher temperature ranges, while less concerning during the
Figure 4.37: Existing bench temperature reading

74
November to March winter months, due to Los Angeles’s cooler climate and the desirability of
sunlight. The high temperatures pose a significant comfort challenge during the periods of early
and late September, as well as in October. During these times, temperatures are high and exceed
comfortable thresholds, suggesting the need for optimized shading solutions. The analysis further
identified the 15 highest temperature readings for south-facing bus shelter orientations,
highlighting peak temperatures that significantly surpassed comfort levels, such as 58.70°C
(137.67°F) on October 06 at 1:00 PM.
Figure 74: Surface temperature hourly plot – South facing
Top 15 hourly surface temperature readings for south facing bus shelters:
1. October 06, 2023 - Hour: 13, Temperature: 58.70°C / 137.67°F
2. October 14, 2023 - Hour: 12, Temperature: 58.61°C / 137.49°F
3. October 06, 2023 - Hour: 12, Temperature: 58.55°C / 137.40°F
4. October 05, 2023 - Hour: 12, Temperature: 57.89°C / 136.21°F
5. October 14, 2023 - Hour: 13, Temperature: 57.64°C / 135.76°F
6. October 05, 2023 - Hour: 13, Temperature: 57.36°C / 135.25°F
7. October 13, 2023 - Hour: 12, Temperature: 57.35°C / 135.23°F
8. October 13, 2023 - Hour: 13, Temperature: 56.93°C / 134.47°F
9. October 14, 2023 - Hour: 11, Temperature: 56.91°C / 134.44°F
10. October 06, 2023 - Hour: 11, Temperature: 56.90°C / 134.42°F
11. October 05, 2023 - Hour: 11, Temperature: 56.42°C / 133.55°F
12. October 13, 2023 - Hour: 11, Temperature: 56.39°C / 133.50°F
13. October 07, 2023 - Hour: 13, Temperature: 55.99°C / 132.78°F

75
14. October 07, 2023 - Hour: 12, Temperature: 55.91°C / 132.64°F
15. October 13, 2023 - Hour: 14, Temperature: 55.89°C / 132.60°F
Below is a visual representation of a shading study conducted on the date with the highest
recorded surface temperature. It compares the shading patterns between the existing conditions
and the newly designed shading, highlighting the quality of shading provided on the hottest
recorded day.
Figure 75: Shade pattern – South facing existing condition
Figure 76: Shade pattern – South facing designed condition

76
For the south-facing shelters, the analysis shows that the number of uncomfortable temperature
readings under existing shading was 1,317. With the implementation of the designed shading,
this number was reduced to 1,275, resulting in a 5% decrease in uncomfortable temperature
readings.
Figure 77: Surface temperature results – South facing
4.4.3 Surface temperature & shading studies – North Facing
Figure 78: Hourly plot of bench seating surface in ℃
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1016
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2058
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690
1275
N O S H A D I N G E X I S T I N G S H A D I N G O P T I M A L S H A D I N G D E S I G N E D S H A D I N G
# OF TEMP. READINGS
BENCH SURFACE TEMP. READINGS
SOUTH FACING
0℃-19℃ 20℃-26℃ 27℃-70℃

77
When looking at the data for the northward orientation of the bus shelter, undesirable surface
temperatures are predominantly seen in the afternoon hours from April to October, with higher
temperature spikes observed during May, June, and July. Morning periods also exhibited
elevated temperatures, but it is less frequent. The peak temperature was recorded on July 24,
2023, at 16:00, reaching 42.97°C (109.34°F). The top 15 temperatures consistently hovered
above 40°C (104°F) in the late afternoon, with July and June presenting the highest frequencies
of such conditions.
This pattern indicates a thermal challenge for north-facing bus shelters during the hot summer
months. The consistent occurrence of temperatures in the range of 40.96°C (105.73°F) to
42.97°C (109.34°F) during the late afternoon underscores the necessity for targeted mitigation
strategies to address the heat gain in these shelters, enhancing the overall thermal comfort for
users.
Top 15 hourly surface temperature readings for North facing bus shelters:
1. July 24, 2023 - Hour: 16, Temperature: 42.97°C / 109.34°F
2. July 15, 2023 - Hour: 16, Temperature: 42.09°C / 107.75°F
3. June 16, 2023 - Hour: 16, Temperature: 41.82°C / 107.27°F
4. July 25, 2023 - Hour: 16, Temperature: 41.71°C / 107.08°F
5. June 05, 2023 - Hour: 16, Temperature: 41.56°C / 106.80°F
6. July 14, 2023 - Hour: 16, Temperature: 41.54°C / 106.77°F
7. June 17, 2023 - Hour: 16, Temperature: 41.52°C / 106.74°F
8. June 15, 2023 - Hour: 16, Temperature: 41.44°C / 106.59°F
9. June 04, 2023 - Hour: 16, Temperature: 41.41°C / 106.54°F
10. July 23, 2023 - Hour: 16, Temperature: 41.31°C / 106.36°F
11. June 18, 2023 - Hour: 16, Temperature: 41.16°C / 106.09°F
12. July 13, 2023 - Hour: 16, Temperature: 41.15°C / 106.07°F
13. June 06, 2023 - Hour: 16, Temperature: 41.11°C / 105.99°F
14. June 03, 2023 - Hour: 16, Temperature: 40.97°C / 105.75°F
15. July 22, 2023 - Hour: 16, Temperature: 40.96°C / 105.73°F

78
Figure 79: Shade pattern – North facing existing condition
Figure 80: Shade pattern – North facing designed
For the north-facing shelters, surface temperature analysis revealed that existing shading resulted
in 1,360 uncomfortable temperature readings. The implementation of the designed shading
reduced this to 1,351, marking a 1% decrease in uncomfortable temperature readings.

79
Figure 81: Surface temperature results – North facing
4.4.4 Surface temperature & shading studies – East Facing
Figure 82: Hourly plot of bench seating surface in ℃
The analysis of surface temperature data for east-facing orientations revealed pronounced
temperature elevations during morning hours across the months from March to October, with
mid-high temperatures occurring in the afternoons. Notably, the early afternoons of September
and October also experienced significant high temperatures. The top 15 recorded temperatures
are all within the months of June and July. The highest recorded temperature was observed on
July 25, at 09:00, registering at 49.82°C (121.68°F). A consistent pattern of elevated
temperatures above 48°C (118°F) was noted, predominantly at 09:00 across various dates in June
and July.
This shows that east-facing shelters are particularly susceptible to intense solar radiation during
the morning hours This trend underscores the need for effective thermal management strategies
especially that these are usually hours of commute. 688 628
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S H A D I N G
O P T I M A L S H A D I N G D E S I G N E D
S H A D I N G
# OF TEMP. READINGS
BENCH SURFACE TEMP. READINGS
NORTH FACING
0℃-19℃ 20℃-26℃ 27℃-70℃

80
Top 15 hourly surface temperature readings for East facing bus shelters:
1. July 25, 2023 - Hour: 9, Temperature: 49.82°C / 121.68°F
2. July 10, 2023 - Hour: 9, Temperature: 49.56°C / 121.21°F
3. July 24, 2023 - Hour: 9, Temperature: 49.44°C / 120.99°F
4. July 09, 2023 - Hour: 9, Temperature: 49.16°C / 120.48°F
5. June 16, 2023 - Hour: 9, Temperature: 48.87°C / 119.97°F
6. July 11, 2023 - Hour: 9, Temperature: 48.75°C / 119.75°F
7. July 08, 2023 - Hour: 9, Temperature: 48.74°C / 119.73°F
8. June 15, 2023 - Hour: 9, Temperature: 48.68°C / 119.62°F
9. June 17, 2023 - Hour: 9, Temperature: 48.64°C / 119.55°F
10. July 23, 2023 - Hour: 9, Temperature: 48.56°C / 119.41°F
11. July 07, 2023 - Hour: 9, Temperature: 48.50°C / 119.30°F
12. June 18, 2023 - Hour: 9, Temperature: 48.42°C / 119.16°F
13. July 22, 2023 - Hour: 9, Temperature: 48.41°C / 119.14°F
14. July 12, 2023 - Hour: 9, Temperature: 48.33°C / 118.99°F
15. June 14, 2023 - Hour: 9, Temperature: 48.30°C / 118.94°F
Figure 83: Shade pattern – East facing existing condition

81
Figure 84: Shade pattern – East facing designed condition
For the east-facing shelters, the initial surface temperature analysis showed 1,409 uncomfortable
temperature readings with existing shading. After implementing the designed shading, this
number marginally decreased to 1,408, resulting in a modest 0.1% reduction in uncomfortable
temperature readings.
Figure 85: Surface temperature results – East facing condition
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1408
N O S H A D I N G E X I S T I N G
S H A D I N G
O P T I M A L S H A D I N G D E S I G N E D
S H A D I N G
# OF TEMP. READINGS
BENCH SURFACE TEMP. READINGS
EAST FACING
0℃-19℃ 20℃-26℃ 27℃-70℃

82
4.4.5 Surface temperature & shading studies – West Facing
Figure 86: Hourly plot of bench seating surface in ℃
The analysis of temperatures for west-facing shelters showed high readings in the afternoons, a
pattern attributable to the westward setting of the sun and the lack of effective shading during
these hours. The surface temperature data of the seating area revealed consistently high
temperatures in the afternoon across all months, with particular emphasis on April through
October—the period when Los Angeles encounters its hottest climate. Such conditions pose a
significant risk of heat stress for transit riders. The peak temperature was observed on October
05, 2023, at 13:00, reaching 56.16°C (133.09°F). Looking at the top 15 temperature readings,
temperatures remained above 54°C (129.2°F).
Top 15 hourly surface temperature readings for West facing bus shelters:
1. October 05, 2023 - Hour: 13, Temperature: 56.16°C / 133.09°F
2. September 01, 2023 - Hour: 14, Temperature: 55.92°C / 132.65°F
3. October 06, 2023 - Hour: 12, Temperature: 55.91°C / 132.64°F
4. October 14, 2023 - Hour: 13, Temperature: 55.55°C / 132.00°F
5. October 14, 2023 - Hour: 12, Temperature: 55.25°C / 131.45°F
6. October 05, 2023 - Hour: 14, Temperature: 55.09°C / 131.16°F
7. September 01, 2023 - Hour: 13, Temperature: 55.08°C / 131.14°F
8. October 06, 2023 - Hour: 13, Temperature: 54.98°C / 130.96°F
9. October 07, 2023 - Hour: 13, Temperature: 54.80°C / 130.64°F
10. September 02, 2023 - Hour: 13, Temperature: 54.79°C / 130.62°F
11. October 13, 2023 - Hour: 13, Temperature: 54.77°C / 130.59°F

83
12. October 13, 2023 - Hour: 12, Temperature: 54.75°C / 130.55°F
13. October 14, 2023 - Hour: 14, Temperature: 54.54°C / 130.17°F
14. October 07, 2023 - Hour: 12, Temperature: 54.53°C / 130.15°F
15. September 02, 2023 - Hour: 14, Temperature: 54.51°C / 130.12°F
Figure 87: Shade pattern – West facing existing condition
Figure 88: Shade pattern – West facing design condition

84
For the west-facing shelters, surface temperature analysis indicated that existing shading resulted
in 1,284 uncomfortable temperature readings. The implementation of the designed shading
reduced this figure to 1,248, achieving a 3% decrease in uncomfortable temperature readings.
Figure 89: Surface temperature results – West facing condition
4.4.6 Surface temperature & shading studies – 30º North-East Facing
Figure 90: Surface temperature results – North-east facing condition
The examination of surface temperature data for the north-east facing bus shelter reveals a
comparatively more comfortable thermal profile than that of other orientations investigated in
this study thus far. Notably, sporadic high temperatures were observed in the morning hours
during June to September, with mid-to-high temperatures also occurring in the mornings from 688 552 551 551 331 1014 1481 1053 2058 1284 664 1248
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S H A D I N G
O P T I M A L S H A D I N G D E S I G N E D
S H A D I N G
# OF TEMP. READINGS
BENCH SURFACE TEMP. READINGS
WEST FACING
0℃-19℃ 20℃-26℃ 27℃-70℃

85
May through October. Furthermore, mid-to-high temperatures were observed during the
afternoons of the warm/hot months April through October, predominantly in July and September.
This orientation demonstrates the most consistent shading, thereby contributing to thermal
comfort and reducing the risk of heat stress and overheating for transit users.
However, while the north-east orientation benefits from effective shading during the hot summer
months, there is a potential risk of reducing thermal comfort through excessive shading in the
cooler winter months from November to March. The highest temperature was recorded on
September 01, 2023, at 11:00, at 39.77°C (103.59°F). This was followed by temperatures such as
39.06°C (102.30°F) on July 25, 2023, at 8:00, and 38.89°C (102.00°F) on September 02, 2023, at
11:00, among others. These readings highlight the occurrence of elevated temperatures, though
generally below the extreme highs observed in other orientations. Below are the top 15 recorder
surface temperatures.
Top 15 hourly surface temperature readings for 30º North-East facing bus shelters:
1. September 01, 2023 - Hour: 11, Temperature: 39.77°C / 103.59°F
2. July 25, 2023 - Hour: 8, Temperature: 39.06°C / 102.30°F
3. September 02, 2023 - Hour: 11, Temperature: 38.89°C / 102.00°F
4. June 28, 2023 - Hour: 8, Temperature: 38.71°C / 101.67°F
5. September 01, 2023 - Hour: 12, Temperature: 38.50°C / 101.30°F
6. September 03, 2023 - Hour: 11, Temperature: 38.37°C / 101.07°F
7. June 27, 2023 - Hour: 8, Temperature: 38.34°C / 101.01°F
8. July 26, 2023 - Hour: 8, Temperature: 38.33°C / 100.99°F
9. September 02, 2023 - Hour: 12, Temperature: 38.33°C / 100.99°F
10. August 31, 2023 - Hour: 11, Temperature: 38.23°C / 100.81°F
11. June 29, 2023 - Hour: 8, Temperature: 38.18°C / 100.72°F
12. September 03, 2023 - Hour: 12, Temperature: 38.15°C / 100.67°F
13. August 31, 2023 - Hour: 12, Temperature: 38.14°C / 100.65°F
14. July 24, 2023 - Hour: 8, Temperature: 38.12°C / 100.62°F
15. July 27, 2023 - Hour: 8, Temperature: 38.11°C / 100.60°F

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Figure 91: Shade pattern – North-East facing existing condition
Figure 92: Shade pattern – North-East facing designed condition
For the north-east facing shelters, the analysis showed that existing shading led to 1,068
uncomfortable temperature readings. After introducing the designed shading, this number
slightly decreased to 1,065, resulting in a 0.3% reduction in uncomfortable temperature
readings.

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Figure 93: Surface temperature results – North-East facing condition
4.4.7 Surface temperature & shading studies – 30º North-West Facing
Figure 94: Hourly plot of bench seating surface in ℃
The surface temperature data for bus shelters with a 30º North-West is the inverse of the ideal
thermal pattern sought for year-round comfort. Optimally, one would expect lower temperatures
during the hot summer months to alleviate discomfort and mid-to-high temperatures during the
cooler winter months to maintain warmth. However, the observed data presents a contrary
scenario, with mid-to-high and very high temperatures occurring in the afternoons of summer
months, and mid-to-low temperatures observed during winter. The highest temperature, 49.21°C
(120.58°F), was recorded on September 01, 2023, at 15:00. These temperatures reveal a pattern
of excessive heat during critical periods, notably in the afternoons of both spring and early fall. 688 583 607 581 331 11561419 1161 2058 1068 727 1065
N O S H A D I N G E X I S T I N G
S H A D I N G
O P T I M A L S H A D I N G D E S I G N E D
S H A D I N G
# OF TEMP. READINGS
BENCH SURFACE TEMP. READINGS
NORTH-EAST FACING
0℃-19℃ 20℃-26℃ 27℃-70℃

88
Top 15 hourly surface temperature readings for 30º North-West facing bus shelters:
1. September 01, 2023 - Hour: 15, Temperature: 49.21°C / 120.58°F
2. September 02, 2023 - Hour: 15, Temperature: 47.48°C / 117.46°F
3. April 24, 2023 - Hour: 15, Temperature: 46.94°C / 116.50°F
4. September 03, 2023 - Hour: 15, Temperature: 46.94°C / 116.49°F
5. September 01, 2023 - Hour: 14, Temperature: 46.85°C / 116.33°F
6. April 25, 2023 - Hour: 15, Temperature: 46.74°C / 116.13°F
7. September 02, 2023 - Hour: 14, Temperature: 46.73°C / 116.11°F
8. September 01, 2023 - Hour: 16, Temperature: 46.72°C / 116.10°F
9. April 23, 2023 - Hour: 15, Temperature: 46.61°C / 115.90°F
10. September 02, 2023 - Hour: 16, Temperature: 46.60°C / 115.88°F
11. September 03, 2023 - Hour: 14, Temperature: 46.55°C / 115.79°F
12. April 26, 2023 - Hour: 15, Temperature: 46.53°C / 115.75°F
13. September 03, 2023 - Hour: 16, Temperature: 46.46°C / 115.63°F
14. September 04, 2023 - Hour: 15, Temperature: 46.36°C / 115.45°F
15. April 22, 2023 - Hour: 15, Temperature: 46.35°C / 115.43°F
Figure 95: Shade pattern – North-west facing existing condition

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Figure 96: Shade pattern – North-west facing designed condition
For the north-west facing shelters, initial surface temperature measurements under existing
shading recorded 1,461 uncomfortable temperature readings. With the implementation of the
designed shading, this number was reduced to 1,449, marking a 1% decrease in uncomfortable
temperature readings.
Figure 97: Surface temperature results – North-west facing condition
688
543
582
536
331
874
1314
894
2058
1461
818
1449
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S H A D I N G
# OF TEMP. READINGS
BENCH SURFACE TEMP. READINGS
NORTH-WEST FACING
0℃-19℃ 20℃-26℃ 27℃-70℃

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4.4.8 Surface temperature & shading studies – 30º South-East Facing
Figure 98: Hourly plot of bench seating surface in ℃
The thermal analysis of the south-east orientation for bus shelters reveals a temperature profile
that is closer to optimal conditions when compared to other orientations. During the summer
months, the temperature readings predominantly exhibit mid-to-low ranges, aligning more
closely with thermal comfort requirements. However, notable exceptions include high
temperature spikes observed in the morning hours of August, deviating from the otherwise
comfortable trend.
Throughout the hot summer months, temperature readings in the mornings and late afternoons
tend to fall within mid ranges, while noon and early afternoon periods frequently experience
temperatures conducive to optimal comfort. Additionally, the mornings of April, September, and
October are characterized by high temperatures, with sporadic high readings also recorded in the
afternoons. Conversely, the cool winter months register mid-to-high temperatures, which
potentially enhance thermal comfort for riders. The highest temperature recorded was 56.56°C
(133.81°F) on October 14, 2023, at 11:00. The pattern of temperature distribution suggests that
while afternoons in April, September, and October may experience high temperatures, the
overall thermal profile of the south-east orientation remains comparatively favorable for rider
comfort across different seasons.
Top 15 hourly surface temperature readings for 30º South-East facing bus shelters:
1. October 14, 2023 - Hour: 11, Temperature: 56.56°C / 133.81°F
2. October 06, 2023 - Hour: 11, Temperature: 55.84°C / 132.52°F
3. October 05, 2023 - Hour: 11, Temperature: 55.16°C / 131.29°F
4. October 14, 2023 - Hour: 12, Temperature: 54.89°C / 130.80°F
5. October 06, 2023 - Hour: 12, Temperature: 54.68°C / 130.42°F
6. October 13, 2023 - Hour: 11, Temperature: 54.64°C / 130.35°F
7. October 05, 2023 - Hour: 12, Temperature: 54.39°C / 129.90°F

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8. October 07, 2023 - Hour: 11, Temperature: 54.09°C / 129.36°F
9. October 13, 2023 - Hour: 12, Temperature: 54.06°C / 129.31°F
10. October 14, 2023 - Hour: 13, Temperature: 54.04°C / 129.27°F
11. October 06, 2023 - Hour: 13, Temperature: 53.99°C / 129.18°F
12. October 07, 2023 - Hour: 12, Temperature: 53.88°C / 128.98°F
13. October 05, 2023 - Hour: 13, Temperature: 53.76°C / 128.77°F
14. October 13, 2023 - Hour: 13, Temperature: 53.64°C / 128.55°F
15. October 07, 2023 - Hour: 13, Temperature: 53.51°C / 128.32°F
Figure 99: Shade pattern – South-east facing existing condition

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Figure 100: Shade pattern – South-east facing designed condition
For the south-east facing shelters, surface temperature analysis revealed that existing shading led
to 1,317 uncomfortable temperature readings. After applying the designed shading, this number
decreased to 1,275, resulting in a 3% reduction in uncomfortable temperature readings.
Figure 101: Surface temperature results – South-east facing condition
688
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S H A D I N G
# OF TEMP. READINGS
BENCH SURFACE TEMP READINGS
SOUTH-EAST FACING
0℃-19℃ 20℃-26℃ 27℃-70℃

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4.4.9 Surface temperature & shading studies – 30º South-West Facing
Figure 102: Hourly plot of bench seating surface in ℃
Similarly to south-east orientation, the south west orientation is showing results conducive to
overall thermal comfort. During the summer months, the temperature readings are showing low
ranges throughout May, June, and July. However, high temperature spikes are observed in the
afternoons of April, August, September, and October, which can be reduced with roper shading.
While the ideal temperature levels are observed in the afternoons, mid temperatures are still
observed in the mornings and late afternoons of the summer months, with some high temperature
readings found in late afternoons in May.
Top 15 hourly surface temperature readings for 30º South-West facing bus shelters:
1. October 06, 2023 - Hour: 13, Temperature: 58.45°C / 137.20°F
2. September 01, 2023 - Hour: 15, Temperature: 57.75°C / 135.95°F
3. October 14, 2023 - Hour: 13, Temperature: 57.38°C / 135.29°F
4. October 05, 2023 - Hour: 13, Temperature: 57.21°C / 134.98°F
5. September 01, 2023 - Hour: 14, Temperature: 57.20°C / 134.96°F
6. October 06, 2023 - Hour: 12, Temperature: 57.15°C / 134.87°F
7. September 02, 2023 - Hour: 15, Temperature: 57.14°C / 134.85°F
8. October 14, 2023 - Hour: 12, Temperature: 57.10°C / 134.78°F
9. October 07, 2023 - Hour: 13, Temperature: 57.00°C / 134.60°F
10. September 02, 2023 - Hour: 14, Temperature: 56.93°C / 134.47°F
11. September 01, 2023 - Hour: 16, Temperature: 56.92°C / 134.46°F
12. October 13, 2023 - Hour: 13, Temperature: 56.87°C / 134.37°F

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13. October 05, 2023 - Hour: 12, Temperature: 56.84°C / 134.31°F
14. September 03, 2023 - Hour: 15, Temperature: 56.81°C / 134.26°F
15. October 13, 2023 - Hour: 12, Temperature: 56.80°C / 134.24°F
Figure 103: Shade pattern – South-west facing existing condition
Figure 104: Shade pattern – South-west facing designed condition

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For the south-west facing shelters, the initial surface temperature readings under existing shading
accounted for 1,248 uncomfortable recordings. After implementing the designed shading, this
number was reduced to 1,206, achieving a 3.3% decrease in uncomfortable temperature
readings.
Figure 105: Surface temperature results – South-west facing condition
Orientation % Improvement
South 5.0%
North 1.0%
East 0.1%
West 3.0%
North-East 0.3% 688 583 611 581 331 1005 1617
1042
2058
1248
505
1206
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# OF TEMP READINGS
BENCH SURFACE TEMP. READINGS
SOUTH-WEST FACING
0-19 20-26 27-70

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North-West 1.0%
South-East 3.0%
South-West 3.4%
The table above displays the modest improvements in surface temperature readings. Although
these improvements are not substantial, they still represent a positive trend in reducing surface
temperatures. Coupled with the improvements in UTCI readings, these changes demonstrate that
carefully designed shading can significantly enhance the transit riding experience.
4.5 Conclusion
This chapter details the simulation results of various bus shelter designs in Los Angeles, focusing
on daylight simulation, shading study, and Universal Thermal Climate Index (UTCI) analysis
aimed at improving temperature control and shading. A Rhino model, based on field
measurements of an existing shelter, served as the basis for these simulations. The results
revealed that the designed shading elements significantly outperformed existing conditions,
reducing uncomfortable temperature readings by 22% to 36% across all orientations. Surface
temperature studies further demonstrated that designed shadings modestly decreased bench
surface temperatures, even in the hottest conditions. Empirical validation from actual bus shelters
confirmed the simulation's accuracy, substantiating the effectiveness of the proposed shading
solutions in enhancing commuter comfort and supporting the viability of these designs for
practical implementation.
Table 3: Percentage of Surface Temperature Improvement

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5 CHAPTER FIVE: DESIGN
5.1 Introduction
This chapter delves into the design process of developing modular shading solutions for bus
shelters, presenting an exploration of three distinct design concepts. Each concept was developed
to address the specific criteria established in Chapter 3, showcasing a methodical evolution from
initial ideas to refined solutions. This chapter outlines the creative journey from conceptual
sketches to digital and physical modeling, emphasizing the iterative nature of the design process.
By examining each concept's development, challenges, and adaptations, the chapter provides
insight into the practical and theoretical considerations that shape functional and aesthetic
decisions in architectural design.
5.2 Design Concepts
The design phase of the project involved the development of three distinct concept ideas. Each of
these design concepts represented variations based on the design criteria established in Chapter
3, reflecting a progressive refinement and adaptation to meet the specified requirements
effectively.
5.2.1 Concept 1
The first design concept was centered around flexibility, drawing inspiration from the modular
acoustic panels created by Erwan Bouroullec. The idea was to develop modules that could
independently fold or collapse, allowing them to connect flexibly and form various interesting
patterns. The design aimed to utilize simple geometries with folds that attached at the edges,
enabling a versatile assembly.

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Figure 106: Clouds by Ronan and Erwan Bouroullec - (Etherington, 2009)
Figure 107: Clouds by Ronan and Erwan Bouroullec - (Etherington, 2009)

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However, this concept faced significant challenges related to material constraints. The modules
required a rigid material for construction, which limited the potential for inherent flexibility.
Instead, flexibility had to come from additional connections, increasing the risk of module
failure. Given the constraints of module resiliency, creating a truly flexible module proved to be
impractical, offering a high risk with low reward.
Figure 108: Concept 1 development – Digital model

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This realization led to a shift in the design approach. I concluded that the flexibility did not need
to originate from the module itself but could instead be achieved through the scalability of the
system. Thus, the redesigned shading system was conceived to be adaptable, capable of scaling
from individual bus shelters to larger structures like buildings, offering a more feasible and
robust solution.
Figure 109: Concept 1 development – 1:1 Physical model

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Figure 110: Concept 1 development – 1:1 Physical model
5.2.2 Concept 2
For the second concept, I concentrated on the connections and structural integrity of the shading
system, aiming to design a self-supporting structure that interconnected seamlessly. To achieve
this, I innovated beyond a single modular design, proposing a dual-module system comprising a
'space module' and a 'connection module.' The development process involved constructing small
paper models to explore and understand various connection possibilities. Ultimately, I opted for
a design where modules would connect via a slit in one module that a connecting point from
another module could slot into. However, this approach lacked the sophistication and

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architectural depth I envisioned. The design felt overly simple and failed to captivate or engage
visually, leading me to further refine the concept to imbue the structure with greater depth and
intrigue.
Figure 111: Concept 2 development – Working models

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Figure 112: Concept 2 development – Working models

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Figure 113: Concept 2 development – Digital model
Figure 114: Concept 2 development – 1:1 Physical model

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Figure 115: Concept 2 development – 1:1 Physical model
5.2.3 Concept 3
The final design concept drew inspiration from the works of Erwin Hauer, an architect and artist
renowned for his use of modular elements to create aesthetically pleasing, seamless shades and
partitions. Hauer’s methodologies provided a foundational framework for the design, particularly
influencing the approach to modular construction. Although much of Hauer's work involved

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molds for casting concrete or metals, the choice was made to work with stainless steel or
aluminum sheets to maintain material consistency between the bus shelter and the shading
system. The thickness and seamlessness of Hauer’s designs could not be replicated with thin
metal sheets, yet his concept of 'suture curves,' as discussed in his book Still Facing Infinity:
Sculptures by Erwin Hauer, influenced the design direction. Hauer describes these curves as akin
to the stitching on a baseball—a subtle yet essential detail often overlooked but integral to the
object’s function and aesthetics. Hauer wrote: “Many of us have encountered this line in our
daily lives without paying any attention to it. It is the stitching that holds together two pieces of
leather that many of us hold so dear” (Hauer, 2017). This notion led to the incorporation of
similar curves into the design, echoing the iron door curves prevalent in Los Angeles
architecture, thereby making it a symbol of the city and its cultural fabric.
Figure 116: Erwin Hauer modular shading screen - (Waddoups, 2018)

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Figure 117: Erwin Hauer suiter curve reference - (Hauer, 2017)
Figure 118: Iron door curves of Los Angeles home

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5.3 Digital and Physical Modeling
The design process began in Rhino by importing the curve patterns to explore effective
incorporation that highlights their unique features. Various modular configurations were
experimented with, as detailed in the process description. Ultimately, a diagonal arrangement of
the curves was selected, with softened edges to create an intriguing yet gentle aesthetic.
Additionally, the front of the model was curved to enhance interaction with light, producing a
glowing effect rather than merely obstructing it. This approach aimed to leverage the dynamic
interplay between light and shadow, adding functionality and visual appeal to the shading
element.
After determining which modular breakdown was most successful, the design transitioned from
2D to 3D. Thickness was added to the modules, and curvature was applied to both segments to
enhance their interaction with light.
Figure 119: Curve experimentation

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To enhance the visual interest of the design, the orientation of the curves was adjusted by
rotating them 45 degrees, as illustrated above. The next step was to create small-scale 3D printed
models to further understand the object’s physical form. This phase highlighted that having
curved edges introduces significant challenges in attaching a series of modules together. This
Figure 120: Curve experimentation

110
model also further confirmed the need to soften the corners to enhance the overall design and
create a calm human experience.
Figure 121: 3D printed working model

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5.4 Building Large Scale Model
After implementing the necessary design changes, the next step involved constructing a fullscale 1:1 model. Building this large-scale model required a particular focus on connections and
structural integrity. To facilitate this, tabs were designed to be riveted together at the edges,
connecting the two elements and the panels effectively. These tabs also played a crucial role in
attaching the shading to a basic metal structural backing, as shown below.
Figure 122: 3D printed working model

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Figure 123: 1:1 scale working model – Front

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Figure 124: 1:1 scale working model - Back

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Figure 125: 1:1 scale working model - Back

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Figure 126: 1:1 scale model

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Figure 127: 1:1 scale model

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Figure 128: 1:1 scale model

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Figure 129: 1:1 scale model

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5.5 Conclusion
The design exploration detailed in this chapter illustrates a progressive refinement of concepts,
each building on the insights and shortcomings of its predecessors. From the initial flexibilityfocused designs inspired by modular acoustic panels to the structurally cohesive systems
influenced by Erwin Hauer's architectural philosophies, the journey reflects a deep engagement
with both material constraints and aesthetic aspirations. The final concept, which marries
practicality with the subtle elegance of hidden curves, symbolizes a mature integration of form
and function suited to the urban landscape of Los Angeles. This chapter not only captures the
evolution of design ideas but also sets a foundation for the real-world application of these
concepts, culminating in the construction of a full-scale model. Through this iterative process,
the project demonstrates the crucial role of design thinking in addressing urban challenges,
ultimately enhancing the commuter experience through innovative shading solutions.

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6 CHAPTER SIX: CONCLUSION AND FUTURE WORK
6.1 Summary
This thesis explores the development of modular shading solutions for existing bus shelters in
Los Angeles, aiming to enhance commuter comfort through improved shading during the city's
extreme heat days. The research highlights gaps in the current bus shelter infrastructure, with an
emphasis on the inadequate shade and cooling provisions that disproportionately affect
vulnerable populations.
Using design thinking, the study evaluates eight bus shelter orientations (South, North, East,
West, South-East, South-West, North-East, North-West) against variables such as the Universal
Thermal Climate Index (UTCI) beneath the shelter as well as the surface temperature and
shading quality at bench surface. Simulations are conducted using the Grasshopper tools
Ladybug, Honeybee, and EnergyPlus to help inform the design of the modular shading elements.
Success metrics for these designs include achieving at least a 20% improvement in UTCI
readings and a reduction in bench surface temperatures, both of which were surpassed in test
results.
The research advances with a modular shading system tailored for diverse bus stop orientations,
hypothesizing that this system significantly boosts thermal comfort and user satisfaction. The
study culminates in constructing a large-scale prototype to be tested under real-world conditions,
confirming the practical benefits of the proposed solutions. This work contributes to urban
design by offering a scalable, adaptable method for improving public transportation
infrastructure in hot climates.
The first chapter of the thesis delves into the urban context of Los Angeles and provides a
detailed background highlighting its climate, population, and crime rate. The chapter also
discusses the city's ongoing transition from an auto-centric approach to a more sustainable and
integrated public transportation system. A key issue identified is the vulnerability of bus riders,
especially in minority communities, to extreme heat and safety concerns due to inadequately
equipped bus stops. To address these challenges, the thesis proposes using advanced software
tools like Rhino3D and Grasshopper, along with plugins such as Ladybug and Honeybee, for
accurate modeling and simulation in the design process. The chapter introduces the concept of
modular design as a flexible and adaptable solution for the bus shelters, aligning with modern
urban design practices and aiming to improve the overall public transportation experience in Los
Angeles.
This literature review reveals the challenges in designing and installing bus shelters in Los
Angeles as well as several attempts to help solve the problem. The analysis of various studies
paints a comprehensive picture of the hardships of daily transit users, particularly in the areas of
heat stress, equity, and safety. Research also shows the effects of urban geometry on the thermal
comfort of outdoor spaces, and how urban spaces size and depth influence the amount of
radiation, air temperature, and thermal comfort levels in all urban spaces. The exploration of

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different bus shelter designs, ranging from the simple yet controversial La Sombrita Bus Shade
to the sophisticated and multifunctional SOM Bus Shelter, showcases a spectrum of creative
responses to these urban challenges, and demonstrates numerous design philosophies and their
practical implications. The key takeaway from this review is the critical role of thoughtful, usercentric design in enhancing the efficiency and appeal of public transit systems. As urban areas
like Los Angeles continue to grow and evolve, the insights from this body of work provide
valuable guidance for the development of public transit infrastructure.
A systematic and detailed approach has been outlined for designing and constructing a modular
bus shelter shade adaptable to various orientations in Los Angeles. It will commence with an
extensive review of existing conditions, including an analysis of bus temperature data and
METRO ridership surveys, to define the scope and nature of the problem. The design phase will
utilize advanced simulation tools such as Rhino, Grasshopper, Ladybug, and Honeybee to study
shading and temperature dynamics, ensuring that the shading solutions are versatile for different
bus shelter orientations. Detailed construction drawings, to be developed using Rhino and
AutoCAD, will guide the fabrication process of the shelter components, emphasizing modularity
and adaptability. The designs will then undergo rigorous testing through simulations to evaluate
their shading effectiveness and temperature control capabilities. Material procurement will be
managed efficiently using Excel spreadsheets. The methodology will culminate in the
construction of a large-scale prototype within Watt Hall, which will subsequently be installed in
Harris Courtyard. This prototype will serve as a tangible demonstration of the design’s
functionality and practicality. This forward-looking methodology ensures that each phase, from
initial concept to real-world application, is strategically planned and executed to enhance the
comfort and safety of bus shelter users in Los Angeles.
Figure 130: Methodology diagram

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Chapter 4 details the simulation results of various bus shelter designs in Los Angeles, focusing
on daylight simulation, shading study, and Universal Thermal Climate Index (UTCI) analysis
aimed at improving temperature control and shading. A Rhino model, based on field
measurements of an existing shelter, served as the basis for these simulations. The results
revealed that the designed shading elements significantly outperformed existing conditions,
reducing uncomfortable temperature readings by 22% to 36% across all orientations. Surface
temperature studies further demonstrated that designed shadings modestly decreased bench
surface temperatures, even in the hottest conditions. Empirical validation from actual bus shelters
confirmed the simulation's accuracy, substantiating the effectiveness of the proposed shading
solutions in enhancing commuter comfort and supporting the viability of these designs for
practical implementation.
Orientation UTCI Reading % Improvement
South 30%
North 26%
East 25%
West 26%
North-East 22%
North-West 30%
South-East 36%
South-West 36%
Table 4: Percentage of UTCI Improvement

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Orientation Surface Temp % Improvement
South 5.0%
North 1.0%
East 0.1%
West 3.0%
North-East 0.3%
North-West 1.0%
South-East 3.0%
South-West 3.4%
Chapter 5 chronicles the iterative design process that was central to developing the final modular
shading solutions for Los Angeles bus shelters. This chapter detailed the evolution of design
concepts, each iteratively refined to better meet the project's requirements. The design journey
began with a flexible concept inspired by Erwan Bouroullec's modular acoustic panels, which
evolved into a more structurally focused design involving a dual-module system to ensure robust
connections and support. The final design drew inspiration from Erwin Hauer's work, integrating
his principles of modular construction and aesthetic seamlessness into the design of durable,
visually appealing shading systems made from stainless steel or aluminum. This design phase
was characterized by extensive prototyping, from digital simulations in Rhino to physical
models, which helped refine the modules' interaction with light and enhance their visual and
functional integration into urban spaces. Adjustments such as rotating curve orientations and
softening edges were made to optimize light interaction and aesthetic harmony, culminating in
Table 5: Percentage of Surface Temperature Improvement

124
the creation of a large-scale prototype that demonstrated the practical viability of the shading
system in real-world conditions.
Figure 131: Bus shelter rendering
Figure 132: 1:1 scale final model

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6.2 Future Work
- Creating Drawing Details: Detailed drawings will be created to facilitate precise
manufacturing and assembly processes.
- Making Full-Scale Model Out of Aluminum: A full-scale model will be constructed using
aluminum to validate the design in a real-world context due to its durability and aesthetic
qualities.
- Real World Testing: The full-scale model will undergo real-world testing to assess its
performance under various real world environmental conditions and its practical viability
in existing bus shelters.
6.3 Conclusion
This thesis has made a significant contribution to enhancing commuter comfort in bus shelters
across Los Angeles by developing and testing modular shading solutions tailored to the city's
diverse and extreme heat conditions. The research identified critical gaps in the existing
infrastructure, particularly the lack of adequate shade and cooling provisions that
disproportionately affect vulnerable populations. Through a rigorous design and simulation
process using tools such as Grasshopper, Ladybug, and EnergyPlus, the study evaluated eight
different bus shelter orientations. It successfully demonstrated that the newly designed modular
shading elements could significantly improve the Universal Thermal Climate Index (UTCI)
readings and reduce surface temperatures at bus stop benches. Results showed a reduction in
uncomfortable temperature readings by 22% to 36% across various orientations, surpassing the
initial success metrics which aimed for at least a 20% improvement.
The impact of this work extends beyond mere academic inquiry; it contributes practical solutions
to real-world problems. By addressing the thermal comfort issues prevalent in Los Angeles'
public transportation shelters, the study not only enhances the daily commuting experience but
also promotes greater use of public transportation, contributing to environmental sustainability
and urban livability. The construction of a large-scale prototype, tested under real-world
conditions, further validated the effectiveness of the shading solutions, offering a scalable and
adaptable method that can be applied to improve public transportation infrastructure in other hot
climates. This research underscores the importance of user-centric design in urban planning and
provides a robust framework for future enhancements in public transit facilities.

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AI DISCLAIMER
AI played a role in the development of this thesis in the following capacities:
1) Writing Enhancement: AI was employed to refine the thesis by editing paragraphs to
enhance grammar, writing flow, technical writing style, and spelling when needed.
2) Data Analysis: In Chapter 4, AI was utilized to analyze data, specifically to identify and
extract the top 15 hottest surface temperature readings.

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Abstract (if available)

Abstract This thesis explores the development of modular shading solutions for existing bus shelters in Los Angeles, aiming to enhance commuter comfort through improved shading during the city's extreme heat days. The research highlights gaps in the current bus shelter infrastructure, with an emphasis on the inadequate shade and cooling provisions that disproportionately affect vulnerable populations.

Using design thinking, the study evaluates eight bus shelter orientations (South, North, East, West, South-East, South-West, North-East, North-West) against variables such as the Universal Thermal Climate Index (UTCI) beneath the shelter as well as the surface temperature and shading quality at bench surface. Simulations are conducted using the Grasshopper tools Ladybug, Honeybee, and EnergyPlus to help inform the design of the modular shading elements. Success metrics for these designs include achieving at least a 20% improvement in UTCI readings and a reduction in bench surface temperatures, both of which were surpassed in test results.

The research advances with a modular shading system tailored for diverse bus stop orientations, hypothesizing that this system significantly boosts thermal comfort and user satisfaction. The study culminates in constructing a large-scale prototype to be tested under real-world conditions, confirming the practical benefits of the proposed solutions. This work contributes to urban design by offering a scalable, adaptable method for improving public transportation infrastructure in hot climates.

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Asset Metadata

Creator Alawami, Fairooz Amin (author)

Core Title Modular shading: using design to mitigate bus rider thermal heat stress

School School of Architecture

Degree Master of Building Science

Degree Program Building Science

Degree Conferral Date 2024-05

Publication Date 06/05/2024

Defense Date 05/01/2024

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

Tag bus shelter,heat stress,Los Angeles,modular design,OAI-PMH Harvest,shading,thermal comfort

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Konis, Kyle (committee chair), Dandridge, Lauren (committee member), Ley, Rob (committee member)

Creator Email falawami@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113992580

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Legacy Identifier etd-AlawamiFai-13065

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Format theses (aat)

Rights Alawami, Fairooz Amin

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