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A step towards urban building information modeling: measuring design and field variables for an urban heat island analysis

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A step towards urban building information modeling: measuring design and field variables for an urban heat island analysis

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Content A STEP TOWARDS URBAN BUILDING INFORMATION MODELING: MEASURING DESIGN AND FIELD VARIABLES FOR AN URBAN HEAT ISLAND ANALYSIS by Anupam Jain A Thesis Presented to the FACULTY OF THE SCHOOL OF ARCHITECTURE UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree MASTER OF BUILDING SCIENCE August 2009 Copyright 2009 Anupam Jain ii DEDICATION To my parents iii ACKNOWLEDGMENTS I would like to thank my thesis committee members: Prof. Thomas Spiegelhalter (Co- Chair), Prof. Karen Kensek (Co-Chair), Dr. Farnoush Banaei-Kashani, and Prof. Douglas Noble for their invaluable guidance and insight throughout. Special thanks are due to Prof. Marc Schiler for his expert knowledge with which he enriched this thesis. I would like to thank Leyla Kazemi and Songhua Xing of the Viterbi School of Engineering for their generous help with GeoDec. I would also like to thank Prof. Cyrus Shahabi for developing GeoDec in the first place. And finally, I would like to thank my classmates in building science for all the fun times and support throughout the two years in building science. iv TABLE OF CONTENTS DEDICATION II ACKNOWLEDGMENTS III LIST OF TABLES X LIST OF FIGURES XI GLOSSARY XXV ABSTRACT XXVII CHAPTER ONE: URBAN HEAT ISLANDS 1 1.1 Introduction 1 1.2 Urban Heat Islands 2 1.3 Relevance of the study 13 1.4 Mitigation measures: cool roofs 15 1.5 Mitigation measures: cool pavements 16 1.6 Mitigation measures: trees and vegetation 18 1.7 Mitigation measures: green roofs 24 1.8 Cost wise comparison of mitigation strategies 28 1.8.1 Cool roofs 28 1.8.2 Cool pavements 28 1.8.3 Trees and vegetation 30 1.8.4 Green roofs 30 CHAPTER TWO: LITERATURE AND BACKGROUND STUDY 32 2.1 Several leading UHI researchers 32 v 2.2 Understanding heat islands 36 2.3 Mathematical models for heat islands 41 2.3.1 Urban design-oriented heat-island models 41 2.3.2 Calculation of heat island effects 43 2.3.3 Albedo calculations 46 2.3.4 Effects of plants and vegetation 47 2.3.5 Water budget of plants 51 2.3.6 Evapotranspiration in a multi-layered canopy 56 2.4 Traditional wisdom supported by recent findings 62 CHAPTER THREE: GEOSPATIAL DECISION MAKING (GEODEC) 64 3.1 Need for urban building information modeling 64 3.2 Introduction to GeoDec 68 3.3 Development of a heat island extension to GeoDec 70 3.3.1 Current Status 70 3.3.2 Proposed 72 3.4 Learning from existing tools 76 CHAPTER FOUR: METHODOLOGY 78 4.1 Methodology 78 4.2 The physics behind the process 79 4.3 Scope of Work 84 4.3.1 Domain of study 84 4.3.2 Not included in the domain of study 84 4.3.3 Study Boundary 85 4.4 Deduction 86 4.5 Hypothesis Statement 89 4.5.1 Problem 89 4.5.2 Purpose/Objective 89 4.5.3 Hypothesis 90 vi 4.6 Elaboration of Hypothesis: Terms 90 4.6.1 Three most important terms: 90 4.6.2 Next three most important terms: 93 4.6 Methodology for new and existing buildings 96 4.6.1 New buildings 96 4.6.2 Existing buildings 96 CHAPTER FIVE: DATA MEASUREMENT DEVICES 98 5.1 Field Measurements 98 5.2 Digital Infrared Camera 99 5.2.1 Usefulness to study 99 5.2.2 Technical Specifications 99 5.3 Luminance Meter 106 5.3.1 Usefulness to study 107 5.3.2 Technical Specifications 108 5.4 Digital Environment Meter 108 5.4.1 Usefulness to study 108 5.4.2 Technical Specifications 109 5.5 GE Illuminance Meter 113 5.5.1 Usefulness to study 113 5.5.2 Technical Specifications 114 5.6 Temperature Gun 116 5.6.1 Usefulness to study 116 5.6.2 Technical Specifications 116 CHAPTER SIX: SITE SELECTION AND ANALYSIS 119 6.1 Heat island analysis for site in downtown Los Angeles 119 6.2 Site Selection and Analysis 120 6.3 Site I: Downtown Los Angeles 120 6.4 Site II: Downtown Los Angeles 122 vii 6.5 Conclusions 132 CHAPTER SEVEN: FIELD MEASUREMENTS 133 7.1 Heat island analysis for site on USC campus 133 7.1.1 Why this site? 133 7.1.2 Specifically: 133 7.2 Infrared Images of different surfaces on site 140 CHAPTER EIGHT: SOFTWARE RESULTS 173 8.1 Ecotect Studies 173 8.2 Ecotect Simulations for Site III on USC campus 174 8.2.1 For December 21 at 12:00 pm at the point indicated (lying in the parking lot) 176 8.2.2 For June 21 at 12:00 pm at the point indicated (lying in the parking lot) 178 8.2.3 For March 21 at 12:00 pm at the point indicated (lying in the parking lot) 180 8.2.4 For September 21 at 12:00 pm at the point indicated (lying in the parking lot) 182 8.3 Ecotect simulations for an additional set of buildings on USC campus 183 8.3.1 Shadow Range 184 8.3.2 Shadows on 07/01 at 3:00 pm: 185 8.3.3 Shadow on 06/21 at 12:00 pm (noon): 185 8.3.4 Shadow on 03/21 at 12:00 pm (noon): 186 8.3.5 Shadow on 09/21 at 12:00 pm (noon): 186 8.3.6 Shadow on 12/21 at 12:00 pm (noon): 187 8.3.7 Shading Potential 187 8.3.8 Solar Exposure on 07/01 (Single Day): 190 8.3.9 Solar Access Analysis 1: Incident Solar Radiation for Current Date and Time 191 8.3.10 Solar Access Analysis 2: Incident Solar Radiation for Specified Period (Summer and from 5:00 am to 6:00 pm) 192 8.3.11 Solar Access Analysis 2a: Incident Solar Radiation for Specified Period (Winter and from 5:00 am to 6:00 pm) 193 8.3.12 Solar Access Analysis 3: Shading, Overshadowing and Sunlight Hours for current date and time 194 viii 8.3.13 Solar Access Analysis 4: Shading, Overshadowing and Sunlight Hours for Specified Period (Summer and from 5:00 am to 6:00 pm) 195 8.3.14 Solar Access Analysis 4a: Shading, Overshadowing and Sunlight Hours for Specified Period (Winter and from 5:00 am to 6:00 pm) 196 8.3.15 Solar Access Analysis 5: Sky Factor & Photo-synthetically Active Radiation (PAR) for current date and time 197 8.3.16 Solar Access Analysis 6: Sky Factor & Photo-synthetically Active Radiation (PAR) for Specified Period (Summer and from 5:00 am to 6:00 pm) 198 8.3.17 Solar Access Analysis 6a: Sky Factor & Photo-synthetically Active Radiation (PAR) for Specified Period (Winter and from 5:00 am to 6:00 pm) 199 8.3.18 Lighting Analysis 1: Natural Light Levels – Daylight Factors and Levels on 07/01 at 3:00 pm 200 8.3.19 Lighting Analysis 2: Natural Light Levels – Daylight Factors and Levels on 12/21 at 1:00 pm 201 8.3.20 Lighting Analysis 3: Natural Light Levels – Overall Daylight and Electric Light Levels on 12/21 at 1:00 pm 202 8.3.21 Lighting Analysis 4: Natural Light Levels – Overall Daylight and Electric Light Levels on 12/21 at 1:00 pm 203 CHAPTER NINE: CONCLUSIONS 205 9.1 Field Studies 205 9.2 Calculations for Solar Reflectance Index (SRI) 212 9.3 Data Analysis & Recommendations 220 9.4 Results from software analysis 222 9.5 Conclusions 223 9.6 Geospatial Decision-making 224 CHAPTER TEN: FUTURE WORK 228 10.1 Incorporate the idea of a “building” 229 10.2 Attach material data attributes 230 10.3 Library of materials 230 ix 10.4 Solar analysis 231 10.5 Add visualization tools for temporal viewing 232 10.6 Importing weather data 232 10.7 Photovoltaics 233 10.8 Analyze time lag due to differences in thermal mass 234 10.9 Internal load calculations 235 10.10 CFD simulation 236 10.11 Create a library of vegetation types for analysis 236 10.12 Other functionalities and extensions 237 10.13 Final Thoughts 238 BIBLIOGRAPHY 239 APPENDICES: APPENDIX I: FIELD DATA MEASUREMENTS 246 APPENDIX II: “MITIGATION STRATEGY TYPES” 247 x LIST OF TABLES Table 1: Comparative Costs of Various Pavements 29 Table 2: Solar Reflectance Index (SRI) of typical roofing materials 94 Table 3: Solar Reflectance Index (SRI) of standard paving materials 95 Table 4: Field of view for different target distances 106 Table 5: Albedos, Emissivities, and Thermal Conductivities of elements often found in the landscape 213 Table 6: Radiative properties of natural materials 214 Table 7: Radiative properties of typical urban materials and areas 215 Table 8: Table showing the final results of calculations based on field measurements 217 xi LIST OF FIGURES Figure 1: A generalized cross-section of a typical urban heat island 2 Figure 2: The effect of built areas over air temperatures 3 Figure 3: Trees in rural areas are not impervious like built surfaces in urban areas. The tree canopy keeps the area beneath it cool 4 Figure 4: A dome of smog over urban areas due to urban activities persists until wind or rain disperses it 5 Figure 5: Typical wind profiles over urban areas, fringe areas and open sea. Due to roughness of built surfaces, wind velocities are greatly reduced 5 Figure 6: Urban canyons trap solar radiation, which gets absorbed by the impervious horizontal and vertical surfaces. 8 Figure 7: The effects of sky view factor on heat islands 8 Figure 8: Electrical load can increase steadily once temperatures begin to exceed about 68–77°F (20–25°C) as shown by this example from New Orleans 10 Figure 9: Increasing urban temperature trends over the last 3–8 decades in selected cities 10 Figure 10: Annual average temperatures from 1878 to 2007 as measured at the Los Angeles Civic Center, University of Southern California Campus 12 Figure 11: Land surface temperature image of Southern California obtained during a record-breaking spring 2004 heat wave 12 Figure 12: Grass pavers in parking lots 17 Figure 13: Surface temperature of materials. The different physical characteristics of the various surfaces exposed to radiation give rise to a very contrasting temperature regime. 17 Figure 14: Leaves absorb and use a large portion of the visible solar radiation, but reflect and transmit a large portion of the invisible solar infrared radiation. 19 xii Figure 15: The hydrologic cascade in a soil-plant-atmosphere system. At the right is an electrical analogue of the flow of water from the soil moisture store to the atmospheric sink via the plant system. 20 Figure 16: Landscaping techniques for a temperate climate. The windbreak on the north side of the building should be no farther away than four times its height. 22 Figure 17: Planting design - Minneapolis, Minnesota 22 Figure 18: Picking the right trees and putting them in the right location will maximize their ability to shade buildings and block winds throughout the year 23 Figure 19: Greenery for rooftops 25 Figure 20: Green roofs with regular roofs 26 Figure 21: Infrared image of temperatures 26 Figure 22: Factors affecting the Heat Island effect in an urban area 38 Figure 23: View of downtown Sacramento, CA 65 Figure 24: Urban analysis using ArcGIS 66 Figure 25: Scatter Plot - Diffuse Horizontal Irradiance x Global Horizontal Irradiance 67 Figure 26: Queries displayed in this figure include those for line of sight, GIS road network, GPS based tracking of trams, nomenclature for buildings and points of interest for a site on the USC campus. 69 Figure 27: A model of USC campus with shadows and a sample solar envelope calculation in GeoDec. 71 Figure 28: Four different types of interaction are possible between energy and matter 85 Figure 29: The type of interaction depends not only on the nature of the material but also on the wavelength of the radiation 81 Figure 30: Effects of absorptance and the emittance characteristics of a material on the equilibrium temperature 81 xiii Figure 31: The top graph shows that glass transmits about 90 percent of both the visible and short-wave infrared portions of sunlight and that it does not transmit any of the long-wave infrared radiation emitted by objects at room temperature 83 Figure 32: Factors affecting an urban heat island analysis 85 Figure 33: A sample extracted from a table showing insolation values at 32 ° N latitude at different times of the day for two sample months. 91 Figure 34: Surface albedo values in the urban external environment. 92 Figure 35: Historical evapotranspiration rates for Los Angeles. 93 Figure 36: Rear View 98 Figure 37: Front View 100 Figure 38: Relationship between the field of view and distance. 1: Distance to target; 2: VFOV = vertical field of view; 3: HFOV = horizontal field of view, 4: IFOV = instantaneous field of view (size of one detector element). 105 Figure 39: Side View Figure 40: Side View 107 Figure 41: CEM Digital Environment Meter 110 Figure 42: Light Meter 114 Figure 43: Infrared temperature gun (side view) Figure 44: Infrared temperature gun (side view) 117 Figure 45: Site of first attempted study in downtown Los Angeles. 121 Figure 46: Urban typology at the site. 122 Figure 47: Site of second attempted study in downtown Los Angeles. 122 xiv Figure 48: Urban typology at the site. 126 Figure 49: VRML Model imported from GeoDec into Ecotect. 127 Figure 50: The VRML model is composed of triangular surfaces. 127 Figure 51: Volumetric composition of the site in Google SketchUp 128 Figure 52: Photograph of site 124 Figure 53: Photograph of site 128 Figure 54: Photograph of site 124 Figure 55: Photograph of site 129 Figure 56: Photograph of site 124 Figure 57: Photograph of site 129 Figure 58: Photograph of site – the access to roofs was not granted as the occupants of the building bear legal liability in case of an accident – a risk they did not want to take. 130 Figure 59: Photograph of site 125 Figure 60: Photograph of site 130 Figure 61: Wooden edge of door. 125 Figure 62: Infrared photo of glass door. 131 Figure 63: Photograph of rooftop 126 Figure 64: Infrared photo through glass. 131 Figure 65: Site on USC Campus 134 Figure 66: Site as seen in GeoDec 130 Figure 67: Site as seen in Google Earth 135 xv Figure 68: Site Plan with points indicating locations where measurements were taken and arrows indicating the direction of photographs as given below. 137 Figure 69: At Point P1 - From roof of KAP. 133 Figure 70: At Point P2 - KAP and MCB 138 Figure 71: At Point P3 - MCB and KAP 133 Figure 72: At Point P4 - Area in front of DRB 138 Figure 73: View of MCB from PSA 133 Figure 74: Parking lot from roof of PSA 139 Figure 75: Photograph of site 134 Figure 76: CWO and CWT 139 Figure 77: View from roof of DRB 134 Figure 78: View from roof of KAP 139 Figure 79: MCB roof with pea grave 134 Figure 80: Paving between DRB and PSA 140 Figure 81: Photograph of site 135 Figure 82: Infrared Measurement 141 Figure 83: Photograph of site 136 Figure 84: Infrared Measurement 141 Figure 85: Photograph of site 136 Figure 86: Infrared Measurement 142 Figure 87: Photograph of site 137 xvi Figure 88: Infrared Measurement 142 Figure 89: Photograph of site 137 Figure 90: Infrared Measurement 143 Figure 91: Photograph of site 137 Figure 92: Infrared Measurement 143 Figure 93: Photograph of site 138 Figure 94: Infrared Measurement 144 Figure 95: Photograph of site 138 Figure 96: Infrared Measurement 144 Figure 97: Photograph of site 139 Figure 98: Infrared Measurement 145 Figure 99: Photograph of site 139 Figure 100: Infrared Measurement 145 Figure 101: Photograph of site 139 Figure 102: Infrared Measurement 146 Figure 103: Photograph of site 140 Figure 104: Infrared Measurement 146 Figure 105: Photograph of site 140 Figure 106: Infrared Measurement 147 Figure 107: Photograph of site 140 xvii Figure 108: Infrared Measurement 147 Figure 109: Photograph of site 141 Figure 110: Infrared Measurement 148 Figure 111: Photograph of site 141 Figure 112: Infrared Measurement 148 Figure 113: Infrared Measurement 142 Figure 114: Infrared Measurement 149 Figure 115: Photograph of site 142 Figure 116: Infrared Measurement 149 Figure 117: Photograph of site 143 Figure 118: Infrared Measurement 150 Figure 119: Photograph of site 143 Figure 120: Infrared Measurement 150 Figure 121: Photograph of site 143 Figure 122: Infrared Measurement 151 Figure 123: Photograph of site 144 Figure 124: Infrared Measurement 151 Figure 125: Infrared Measurement 144 Figure 126: Infrared Measurement 152 Figure 127: Photograph of site 145 xviii Figure 128: Infrared Measurement 152 Figure 129: Photograph of site 145 Figure 130: Infrared Measurement 153 Figure 131: Photograph of site 145 Figure 132: Infrared Measurement 153 Figure 133: Photograph of site 146 Figure 134: Infrared Measurement 154 Figure 135: Concrete floor of PSA 146 Figure 136: Light meter reading 155 Figure 137: Methods for calculating reflectance of a given surface 155 Figure 138: Concrete floor of PSA 148 Figure 139: Light meter reading 156 Figure 140: Concrete floor of PSA 148 Figure 141: Light meter reading 156 Figure 142: Green patch in between DRB and PSA 149 Figure 143: Light meter reading 157 Figure 144: Brick tile pavement in between DRB and PSA 149 Figure 145: Light meter reading 157 Figure 146: Concrete floor of PSA roof 150 Figure 147: Concrete floor of PSA roof 158 Figure 148: Concrete floor of PSA roof: point 1 150 xix Figure 149: Concrete floor of PSA roof: point 2 158 Figure 150: Concrete floor of PSA roof: point 3 150 Figure 151: Grass patch in front of DRB 158 Figure 152: Roof of MCB 151 Figure 153: Roof of MCB 159 Figure 154: Roof of MCB 151 Figure 155: Infrared Photo 160 Figure 156: Roof of MCB 152 Figure 157: Infrared Photo 160 Figure 158: Roof of MCB 152 Figure 159: Infrared Photo 161 Figure 160: Roof of MCB 152 Figure 161: Infrared Photo 161 Figure 162: Roof of MCB 153 Figure 163: Infrared Photo 162 Figure 164: Roof of KAP 153 Figure 165: Roof of KAP 162 Figure 166: DRB roof 154 Figure 167: DRB roof 163 Figure 168: Light meter reading 154 Figure 169: 18% gray surface 163 xx Figure 170: Pea gravel over roof of KAP 154 Figure 171: Infrared photograph 163 Figure 172: Pea gravel over roof of KAP 155 Figure 173: Infrared photograph 164 Figure 174: Pea gravel over roof of KAP 155 Figure 175: Infrared photograph 164 Figure 176: View from roof of KAP 156 Figure 177: Infrared photograph 165 Figure 178: View of MCB 156 Figure 179: Infrared photograph 165 Figure 180: View of MCB 157 Figure 181: Infrared photograph 166 Figure 182: Seeley G. Mudd building 157 Figure 183: Infrared photograph 166 Figure 184: Roof of DRB 158 Figure 185: Infrared photograph 167 Figure 186: Roof of DRB 158 Figure 187: Infrared photograph 167 Figure 188: Roof of DRB 159 Figure 189: Infrared photograph 168 Figure 190: Roof of DRB 159 xxi Figure 191: Infrared photograph 168 Figure 192: Roof of DRB 160 Figure 193: Infrared photograph 169 Figure 194: Roof of DRB 160 Figure 195: Infrared photograph 169 Figure 196: Tar felt roof surface of DRB 161 Figure 197: Infrared photograph 170 Figure 198: Roof of DRB 161 Figure 199: Infrared photograph 170 Figure 200: Roof of DRB 161 Figure 201: Infrared photograph 171 Figure 202: Ecotect result for insolation on a simple cuboid for an entire day 173 Figure 203: Rooftop insolation calculation using example file from Ecotect 174 Figure 204: Shadows and availability of direct radiation at the given point 176 Figure 205: Sky view overlaid on the Sun Path diagram as seen from that point 176 Figure 206: Calculated solar stress (direct radiation) for the given point 177 Figure 207: Shadows and availability of direct radiation at the given point 178 Figure 208: Sky view overlaid on the Sun Path diagram as seen from that point 178 Figure 209: Calculated solar stress (direct radiation) for the given point 179 Figure 210: Shadows and availability of direct radiation at the given point 180 Figure 211: Sky view overlaid on the Sun Path diagram as seen from that point 180 xxii Figure 212: Calculated solar stress (direct radiation) for the given point 181 Figure 213: Shadows and availability of direct radiation at the given point 182 Figure 214: Sky view overlaid on the Sun Path diagram as seen from that point 182 Figure 215: Calculated solar stress (direct radiation) for the given point 183 Figure 216: Shadow range: plan 184 Figure 217: Shadow range: 3D 184 Figure 218: Simulated length of shadows 185 Figure 219: Simulated length of shadows 185 Figure 220: Simulated length of shadows 186 Figure 221: Simulated length of shadows 186 Figure 222: Simulated length of shadows 187 Figure 223: Input screen 187 Figure 224: Output screen 1 188 Figure 225: Output screen 2 188 Figure 226: output screen 3 - plan 189 Figure 227: Output Screen 4 - Side View 189 Figure 228: Output Screen 5 - Front View 190 Figure 229: Graph showing solar exposure 190 Figure 230: Input Screen 191 Figure 231: Output Screen 191 Figure 232: Input Screen 192 xxiii Figure 233: Output Screen 192 Figure 234: Input Screen 193 Figure 235: Output Screen 193 Figure 236: Input Screen 194 Figure 237: Output Screen 194 Figure 238: Input Screen 195 Figure 239: Output Screen 195 Figure 240: Input Screen 196 Figure 241: Output Screen 196 Figure 242: Input Screen 197 Figure 243: Output Screen 197 Figure 244: Input Screen 198 Figure 245: Output Screen 198 Figure 246: Input Screen 199 Figure 247: Output Screen 199 Figure 248: Input Screen 200 Figure 249: Output Screen 200 Figure 250: Input Screen 201 Figure 251: Output Screen 201 Figure 252: Input Screen 202 Figure 253: Output Screen 202 xxiv Figure 254: Input Screen 203 Figure 255: Output Screen 203 Figure 256: Pea gravel roof (MCB): Temperatures range between 46-56 °F for the roof and between 90-107 °F for the dark colored brick tile façade. 207 Figure 257: Asphalt and Concrete Paving (Parking Lot 6 in front of MCB): Temperature of asphalt paving is approx. 108 °F and of concrete paving is approx. 96 °F. 207 Figure 258: Tar and gravel roof (DRB): Temperature of roof is between approx. 50-57 °F. 208 Figure 259: Brick tile and concrete pavements: Temperatures range from 80-84 °F for the brick tiles and approx. 74 °F for the concrete. However, under shade both are between 64-67 °F. 208 Figure 260: Sunlit patch of grass (outside DRB): Temperatures range from 43-58 °F for the grass. Compare with temperature of asphalt paving that is approx. 108 °F (as seen earlier). 211 Figure 261: Shaded patch of grass (outside PSA): Temperatures range from 50-55°F for the grass and between 80-82 °F for the brick tile paving in the background. 211 xxv GLOSSARY Albedo is synonymous with solar reflectance. Heat Island Effects occur when warmer temperatures are experienced in urban landscapes compared to adjacent rural areas as a result of solar energy retention on constructed surfaces. Principal surfaces that contribute to the heat island effect include streets, sidewalks, parking lots and buildings. Infrared or Thermal Emittance is a parameter between 0 and 1 (or 0% and 100%) that indicates the ability of a material to shed infrared radiation (heat). The wavelength range for this radiant energy is roughly 3 to 40 micrometers. Most building materials (including glass) are opaque in this part of the spectrum, and have an emittance of roughly 0.9. Materials such as clean, bare metals are the most important exceptions to the 0.9 rule. Thus clean, untarnished galvanized steel has low emittance, and aluminum roof coatings have intermediate emittance levels. Solar Reflectance (albedo) is the ratio of the reflected solar energy to the incoming solar energy over wavelengths of approximately 0.3 to 2.5 micrometers. A reflectance of 100% means that all of the energy striking a reflecting surface is reflected back into the atmosphere, and none of the energy is absorbed by the surface. The best standard technique for its determination uses spectro-photometric measurements with an integrating sphere to determine the reflectance at each different wavelength. An averaging process using a standard solar spectrum then determines the average reflectance (see ASTM Standard E903). Solar Reflectance Index (SRI) is a measure of a material’s ability to reject solar heat, as shown by a small temperature rise. It is defined so that a standard black (reflectance 0.05, emittance 0.90) is 0 and a standard white (reflectance 0.80, emittance 0.900 is 100. For example, a standard black surface has a temperature rise of 90 F (50 C) in full sun, and a standard white surface has a temperature rise of 14.6 F (8.1 C). Once the maximum temperature rise of a given material has been computed, the SRI can be computed by interpolating between the values for white and black. Materials with the highest SRI values are the coolest choices for roofing. Due to the way SRI is defined, particularly hot materials can even take slightly negative values, and particularly cool materials can even exceed 100. 1 Advection describes predominantly horizontal motion in the atmosphere. 2 The motion is usually of some property of the atmosphere, such as heat, humidity, or salinity. BIM is an acronym that stands for the activity of Building Information Modeling. One of its definitions describes it as the creation and use of coordinated, consistent, computable 1 Lawrence Berkeley National Laboratory Cool Roofing Materials Database 2 Oke, T.R., 1978. Boundary Layer Climates 1st ed., Routledge. Pp. 339 xxvi information about a building project in design - parametric information used for design decision making, production of high-quality construction documents, prediction of building performance, cost estimating, and construction planning. 3 Not all software tools are BIM tools. Tools that are not a part of the BIM family produce models with the following characteristics: 1. Models containing only 3D data, but no object attributes. These models can only be used for graphic visualizations and do not provide any support for data integration and design analysis. 2. Models that do not support the behavior of objects in them. For example here it is possible to define objects, but not to adjust their positioning of proportions. This is because they do not utilize parametric intelligence. Changes to such models are extremely labor intensive and there is no protection against creating inconsistent or inaccurate views of the model. 3. Models composed of multiple 2D CAD files that must be combined to define the building. The 3D model in such a case is not guaranteed to be feasible, consistent, countable, or to display intelligence with respect to the objects contained within it. 4. Models that allow changes to object dimensions in one view that are not automatically updated in other views of the model. Not only is this inconvenient, this makes the model erroneous as small changes can go undetected. 4 3 Krygiel, E. & Nies, B., 2008. Green BIM: Successful Sustainable Design with Building Information Modeling, Sybex. Pp. 27 4 Eastman, C. et al., 2008. BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors, Wiley. Pp. 15-16 xxvii ABSTRACT Digital simulation methods are important for analyzing energy flows. They inform the design and help determine what methods are useful for the remediation of built form to enable energy conservation. The logical requirement therefore is to develop sophisticated energy modeling tools for mitigating some of the most pressing urban problems. Urban areas have a greater density of buildings and paved surfaces that absorb and retain heat from the sun. Typically overall, the relative air temperature is lower in rural areas, increases over suburban districts, and then peaks over urban areas. These higher temperatures increase the need for cooling, especially in summer, making buildings consume more electricity. These are characteristics of the urban heat island effect. Urban scale computer modeling for incident solar radiation can aid in learning about mitigation of the heat island effect through albedo modification and increased vegetation, among other solutions. 1 CHAPTER ONE: URBAN HEAT ISLANDS 1.1 Introduction We all use energy in many forms in our day to day lives. Our understanding of its forms and conversions can be instrumental in determining how we harness it in future. The building sector is a major energy consumer. It is therefore imperative that we make the built environment energy efficient. While there has been a lot of analysis done at the building scale by architects and engineers, there is a growing need for analysis at the urban scale as well. Currently, the efforts to make individual buildings energy efficient are growing in visibility and productivity, but a large amount of energy is lost in urban areas. The collective mass in a city needs to be made energy efficient to prevent losses. We have to consider built form as a whole and use software to predict performance, suggest design changes, and help overall in making cities more energy efficient. This objective of conducting analysis for energy flows can be achieved through digital simulation methods. Computer software and simulation packages are important tools for such analyses. They can inform the design and remediation of built form to enable energy conservation. The logical requirement therefore is to develop sophisticated energy modeling tools for mitigating some of the most pressing urban problems. Architects and city planners can then use these tools to inform energy efficiency issues in their designs. 2 1.2 Urban Heat Islands The issue of Urban Heat Islands (UHI) is of prime concern to architects and urban planners. A built area needs to be studied as a group of buildings, a collective, which has a combined effect on the microclimate of the area. It is for the purpose of such a study that a set of visualization and analysis tools becomes useful. Figure 1: A generalized cross-section of a typical urban heat island 5 Urban areas have more paved areas than rural areas. As the sun rises in the morning, it is low in the sky and hits the east facing walls of buildings. In densely urbanized areas with tall buildings, the wall surface area that is exposed to this early morning warming is much greater than in rural areas that have fewer tall buildings. At noon, the sun’s rays are perpendicular to the horizontal surfaces below. These surfaces in urban areas include rooftops, roads, freeways, parking lots, and other hard paved surfaces that retain heat and warm up much more rapidly than soft surfaces such as parks and trees. 5 Based on: Oke, T.R., 1978. Boundary Layer Climates, 1st ed., Routledge. Pp. 254 3 Figure 2: The effect of built areas over air temperatures 6 During the day, the surfaces in rural areas are also heated by the sun’s radiation. However, taking into account the additional early morning solar gain in urban areas, they are relatively cooler. This temperature differential causes air currents to form from urban areas to rural areas until about the evening time when temperatures begin to balance out and surfaces start re-radiating the heat back to the atmosphere to cool down. “During daylight hours, pollution lowers heat build-up slightly, because it blocks incoming solar energy.” 7 As the day progresses however, the heat, dust and smoke from vehicles, mechanical systems, and other city processes adds particles to the atmosphere. This 6 http://epa.gov/hiri/images/UHI_profile-rev-big.gif 7 Akbari, H. et al. eds., 1992. Cooling Our Communities: A Guidebook on Tree Planting and Light-Colored Surfacing, U.S. Environmental Protection Agency, Office of Policy Analysis, Climate Change Division. Pp. 7. 4 process repeated over time during the day leads to the formation of dome-shaped zones above urban areas that are hotter than the atmosphere around them. During the evening hours, due to the low angle of the sun and corresponding heat gain on west facing walls, temperatures in urban areas do not go down as rapidly as they do in rural areas - which get cooled by unrestricted surface winds. Thus the cycle of hot air currents from urban to rural areas repeats itself. “At night, however, pollution prevents heat from escaping by covering the city like a blanket, and thereby increases the heat island effect.” 8 These heated zones centered over urban areas are identifiable from the rural surroundings and form what are called heat islands in the larger landscape. Figure 3: Trees in rural areas are not impervious like built surfaces in urban areas. The tree canopy keeps the area beneath it cool 9 Another aspect of the heat island effect is the formation of smog. The dust particles, in the dome-shaped zones identified earlier, become heavy due to the deposition of fog on them and move downwards - fusing with other particles on the way, usually in the 8 Ibid. Pp.7. 9 William R. Lowry, ‘The Climate of Cities’, Scientific American, August 1967 as quoted in: Michael Hough, 1995. Cities and Natural Process. London, New York: Routledge. Pp. 192 5 absence of rain or strong winds. This increases the level of ozone formation near the ground and promotes the buildup of smog 10 . Figure 4: A dome of smog over urban areas due to urban activities persists until wind or rain disperses it 11 Figure 5: Typical wind profiles over urban areas, fringe areas and open sea. Due to roughness of built surfaces, wind velocities are greatly reduced 12 During the winter, increased temperatures are beneficial as there is less heating load and the excess heat prolongs the growing season for plants 13 . However, during summers, the demand for electricity to cool buildings is much higher and this forces increased 10 Michael Hough, 1995. Cities and Natural Process. London, New York: Routledge. Pp. 193-194 11 William R. Lowry, ‘The Climate of Cities’, Scientific American, August 1967 as quoted in: Michael Hough, 1995. Cities and Natural Process. London, New York: Routledge. Pp. 194 12 Meiss, M., 1979. The Climate of Cities. In I. C. Laurie, ed. Nature in Cities: Natural Environment in the Design and Development of Urban Green Areas. John Wiley & Sons Ltd. as quoted in: Michael Hough, 1995. Cities and Natural Process. London, New York: Routledge. Pp. 193. 13 http://www.epa.gov/hiri/about/index.htm. Accessed: December 13, 2008. 6 production of electricity – adding to pollution and fossil fuel usage. Thus the summer losses far outweigh winter gains. When the sun is shining, the different thermal processes that lead to a heat island get initiated. By mid-day, the temperature differences between urban and rural areas increase. However, the effect of heat islands is the most pronounced at night when the different surfaces that gained heat during the day start re-radiating it back to the environment. At night, since more of the surfaces in rural areas are able to see the sky (called higher sky view factor), they cool down faster. In urban areas, ground surfaces between tall buildings are not able to “see” the sky as much (lower sky view factor) and do not get enough cooling surface winds. The rooftops of buildings that are closer to the sky cool down faster and before the roads and pavements below. This causes temperature stratification in the air, further inhibiting heat loss from ground surfaces to the atmosphere above. In areas with densely located tall buildings, “urban canyons” are formed that take much more time every night to cool down. Inhibition of the natural flow of cooling air currents due to the orientation and density of buildings in urban areas restricts its flow and traps hot air. This is partially offset by the convection that is created by heat islands. The upward draft draws air in from the surrounding countryside, causing a steady inward breeze. However by morning, urban areas are still not able to lose all their stored heat from the previous day to the environment and already start receiving solar heat gain for the next day. This makes urban areas hotter than rural areas – even before beginning the new day’s cycle. At night, surfaces emit longwave radiation to lose 7 the heat gained during the day. The stronger the wind is near the ground surface, the easier it is for the surface to lose the heat. However, wind velocity can be very low due to stratification of air temperatures from uneven cooling of roof and ground surfaces. The surface characteristics also determine how quickly heat is lost to the environment. 14 For example, a higher emissivity value of the surface material will make the surface lose heat faster. Similarly surface roughness and soil thermal conductivity also affect the rate of heat loss to the environment. Therefore it becomes important to use materials that aid in quicker heat loss in urban areas. This will help pavements and rooftops for example to cool down faster at night, instead of storing heat for prolonged periods. The heat island is particularly strong on calm, clear nights. Figure 7 (a) shows that as the sky view factor (Ψ) is reduced towards the cool night sky, the walls and floors of urban canyons (the right part of the sketch) cannot lose heat as readily as the open countryside or less dense suburban areas can due to easier movement of the cool air over the ground surfaces (the left part of the sketch). Figure 7 (b) shows that as the sky view factor (Ψ) gets narrower, the effect (ΔT) gets more pronounced. 14 Geiger, R., Aron, R.H. & Todhunter, P., 2003. The Climate Near the Ground 6th ed., Rowman & Littlefield Publishers. Pp. 81 8 Figure 6: Urban canyons trap solar radiation, which gets absorbed by the impervious horizontal and vertical surfaces. 15 Figure 7: The effects of sky view factor on heat islands 16 15 William R. Lowry, ‘The Climate of Cities’, Scientific American, August 1967 as quoted in: Michael Hough, 1995. Cities and Natural Process. London, New York: Routledge. Pp. 192. 16 Based on: Lowry, W., 1988. Atmospheric Ecology for Designers and Planners, New York: Van Nostrand Reinhold. as quoted in: Stein, B. et al., 2005. Mechanical and Electrical Equipment for Buildings 10th ed., Wiley. Pp. 53 9 Heat islands have been found linked to the increase in energy consumption in urban areas 17 . At mid day on hot summer days, the cooling load for buildings is usually at its highest. This makes the mechanical equipment work harder to keep the occupants comfortable, which leads to greater electricity and hence energy consumption. Every 1K rise in the daily maximum temperature leads to 2 to 4% increase in peak urban electricity demand for cooling starting from the 15-20 °C (59-68 °F) temperature range 18 . It is documented that before 1940, cities were always cooler than the surrounding rural areas 19 . As built up area increased and replaced vegetation, the urban temperatures began to rise, and from 1965 to 1989, urban temperatures increased by about 1K. Data indicates that temperatures in urban areas are rising. This has been found to be a continuous trend. Akbari et al 20 found that for downtown Los Angeles, the maximum temperatures increased by about 2.5K since 1930. The minimum temperatures were found to be about 4K higher than they were in 1880. Similarly, in Washington D.C., the rise in temperatures was 2K between 1871 and 1987. 17 http://www.epa.gov/hiri/impacts/index.htm 18 Akbari, H., 2001. Energy Saving Potentials and Air Quality Benefits of Urban Heat Island Mitigation. Available at: http://www.osti.gov/bridge/servlets/purl/860475- UlHWIq/860475.PDF. 19 Goodridge, J., 1987. Population and temperature trends in California. In Proceedings of the Pacific Climate Workshop. Pacific Grove CA. and Goodridge, J., 1989. Air temperature trends in California, 1916 to 1987 as referenced in Akbari, H., Energy Saving Potentials and Air Quality Benefits of Urban Heat Island Mitigation. Available at: http://www.osti.gov/bridge/purl.cover.jsp;jsessionid=C2891B392A0734398C81EB323FC12EDF?purl=/86 0475-UlHWIq/ [Accessed February 26, 2009]. 20 Akbari, H., Pomerantz, M. & Taha, H., 2001. Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas. Solar Energy, 70(3), 295-310. 10 Figure 8: Electrical load can increase steadily once temperatures begin to exceed about 68–77°F (20– 25°C) as shown by this example from New Orleans 21 Figure 9: Increasing urban temperature trends over the last 3–8 decades in selected cities 22 21 Sailor, D., 2002. Urban Heat Islands, Opportunities and Challenges for Mitigation and Adaptation. Sample Electric Load Data for New Orleans, LA (NOPSI, 1995). Data courtesy Entergy Corporation. In Toronto, Canada. Available at: http://www.epa.gov/hiri/images/electricdemand-big.gif. 11 Some analysis is required to visualize the effects of temperature, reflectivity of materials, and air movement on and around built and paved surfaces. This will aid in evaluating areas that can be improved by vegetative and other techniques. Simulation of the micro- climate will aid in predicting such energy flows for building clusters in urban areas. As seen in Figure 10, the annual temperatures in Los Angeles are on the rise since first recorded in 1878. Figure 11 shows the land surface temperature of Southern California obtained during a record-breaking spring 2004 heat wave. This kind of analysis is useful in visualizing the effects of heat over urban areas. This image was taken by the Moderate Resolution Imaging Spectroradiometer (MODIS) on board NASA's Aqua satellite and shows extreme high surface temperatures nearing 150°F shown in dark red. 22 Akbari, H., Energy Saving Potentials and Air Quality Benefits of Urban Heat Island Mitigation. Available at: http://www.osti.gov/bridge/purl.cover.jsp;jsessionid=C2891B392A0734398C81EB323FC12EDF?purl=/86 0475-UlHWIq/ [Accessed February 26, 2009]. 12 Figure 10: Annual average temperatures from 1878 to 2007 as measured at the Los Angeles Civic Center, University of Southern California Campus 23 Figure 11: Land surface temperature image of Southern California obtained during a record- breaking spring 2004 heat wave 24 23 Data from NOAA National Weather Service - Los Angeles/Oxnard) as quoted in: http://climate.jpl.nasa.gov/news/index.cfm?FuseAction=ShowNews&NewsID=24. Accessed 2009.03.10. 24 http://climate.jpl.nasa.gov/news/index.cfm?FuseAction=ShowNews&NewsID=24. Accessed 2009.03.10 13 It is important to note that though heat islands are formed over urban areas with typically higher air temperatures, they are not the sole reason for changes in regional weather and hence, climate change. Air pollution is one of the other important considerations. For instance, an industrial area may not be as dense as the downtown of a major city, but still have a finite contribution towards causing pollution without a significant contribution to the heat island. 1.3 Relevance of the study As the temperatures in urban areas rise, the natural cycle of night cooling is diminished. This causes problems associated with pockets of trapped heat. The simple act of walking or driving in an urban area versus a rural area tells us how the air temperature varies. Rural areas have many more trees and are thus cooler as compared to hot urban areas. The temperature of air over urban areas therefore increases much more than in rural areas 25 . Some of the associated effects of heat islands are: 1. Rising temperatures increase the need for cooling. Thus buildings consume more electricity and hence energy to cool down. 2. This also increases the pressure on electricity grids to produce more electricity to meet the increased demand – leading to greater environmental pollution from the electricity production plants. 25 Akbari, H. et al. ed., 1992. Op cited 14 3. There are health concerns, such as respiratory problems, related to the build-up of smog and increased air pollution. Public health hazards of excessive heat are enormous. Every year a large number of heat related illnesses and deaths are reported in urban areas. 4. With an increasing amount of hardscaped areas in the cities, there are fewer softscaped areas with plants and trees for rainwater to percolate into the ground. This causes a significant drop in the water table of the area, depriving residents of clean drinking water. This also hinders the capability of the ground surfaces to cool their surroundings and themselves through evaporation of surface water. 5. Though not a direct effect of heat islands, but tangential to it is the fact that paved surfaces pose other problems as well. For example, increased storm water runoff from paved surfaces washes the oil from automobiles, dirt on the streets and the like through pipes to nearby water bodies – contributing to their pollution. This affects the aquatic ecosystem of these water bodies. With increased understanding of heat islands has come a great ability to find methods to mitigate their effects. Scientists have spent years researching implementable solutions. The mitigation measures for heat islands in urban areas are now known to be spanning mainly: trees and vegetation; green roofs; cool roofs; and cool pavements. 26 Next we will examine each of these measures in detail. 26 http://www.epa.gov/hiri/mitigation/index.htm 15 1.4 Mitigation measures: cool roofs Cool roofing as a term refers to the use of highly reflective and emissive materials. Cool roofs help reduce temperatures in urban areas due to their ability to reflect off a substantial amount of incident solar radiation falling on a roof surface. Roofs are often directly facing the sun and perpendicular to its hot incident rays. They are also often dark in color. They therefore absorb a lot of the heat from the sun and subsequently transmit some heat to the building and emit some heat back to the outdoor environment. The combined effect of a large number of roofs, typical in urban areas, is elevated air temperatures over these surfaces. Cool roofs help get rid of this heat incident on the roof surface. They are light and reflective by nature that allows the roofs to remain cool. The light color reflects light in the visible spectrum, which helps a little. For example, a traditional roof has a low solar reflectance of 5-15%, which means that it absorbs 85-95% of the incident energy. A good cool roof on the other hand can have a solar reflectance of 65% or more, thereby absorbing and transferring just about 35% of the incident energy. 5% of the solar energy is in the ultra-violet spectrum, 43% is in the form of visible light, and 52% of the energy is in the infrared spectrum. The infrared spectrum, which is responsible for heating characteristics, does not get fully reflected. This is the reason why cool roof coatings commercially available exploit the emittance value of materials to further aid in keeping the heat out. Emittance is the property of a material that determines how readily it gives up heat. So while solar reflectance (albedo) is important, a surface will keep emitting heat until it reaches a thermal equilibrium with the outdoor 16 temperature. A higher emittance value makes a material give up heat much faster and thus achieves this equilibrium earlier than traditional materials that tend to store some heat before emitting it back to the environment. There is a drawback of having cool roofs though. In winter periods when the additional solar heat is desirable, a cool roof reflects it away from the building. This can result in higher heating costs. However, this is dependent on the local climatic conditions. In most areas, winter periods are shorter and cloudy as compared to summer periods that are longer and directly exposed to the sun. Here one can argue that since the available sunlight is already less and the sun is at a lower angle, the amount of solar gain is relatively less, and hence the loss is not as big due to cool roofs. Compare this with the hot summer months where the sun is high in the sky and sunlight is available aplenty. Cool roofs in this condition will prevent much of the undesired heat from entering buildings. Also, electricity is the fuel mostly used for cooling and the relatively cheaper natural gas for heating. Therefore the savings in summer would be relatively greater in this case as one would use less electricity for cooling. 1.5 Mitigation measures: cool pavements Horizontal surfaces in urban areas include roofs, pavements, streets, parking lots, and so on. These surfaces are directly exposed to the sun’s radiations and gain the most amount of heat. In this section, let’s look at the non-roof paved areas in the outdoor thermal 17 environment. Roads and parking lots are largely asphalt covered and dark in color. They are also largely unshaded. These factors make them extremely hot and contributors to the rise in air temperatures over a large collection of such areas. Concrete is the other most commonly found pavement material. Though it is better than asphalt as it is lighter in color, it still has a low emittance value. This makes concrete a heat absorber too. Cool pavements and outdoor surfaces are important not only for rising urban temperatures, but also for human comfort in these areas. Imagine walking through a large parking lot in the peak of summer, especially if it is covered in blacktop. It would probably not be the most enjoyable experience for anybody. Now imagine walking through a park. It is definitely a much better experience. Figure 12: Grass pavers in parking lots 27 Figure 13: Surface temperature of materials. The different physical characteristics of the various surfaces exposed to radiation give rise to a very contrasting temperature regime. 28 27 www.soilretention.com. Accessed 2008.09.23 28 Meiss, M., 1979. The Climate of Cities. In I. C. Laurie, ed. Nature in Cities: Natural Environment in the Design and Development of Urban Green Areas. John Wiley & Sons Ltd. As quoted in: Michael Hough, 1995. Cities and Natural Process. London, New York: Routledge. Pp. 192 18 Cool pavements are those that allow the surface to cool down and serve other purposes such as water percolation to the ground beneath and reflectance of incident solar radiation. Open concrete grid pavers are one such type of pavers that allow grass to grow through the voids and are lighter in color. Permeable concrete is another option that allows water to percolate to the ground below and is more reflective than asphalt. Porous asphalt is another paving option available that allows water to percolate, even though it does not provide any relief from the heat absorbed by the dark-colored asphalt itself. Not all these pavement types can be installed everywhere. There may be structural considerations like traffic density and expected foot traffic to determine the feasibility of a particular type. For example, open grid concrete pavers may not be able to take heavy traffic frequency loads. Therefore they cannot be installed on roads and on parking lot aisles – places that have constant movement of traffic. However, they can be installed in parking bays in the parking lots and even in fire lanes that are seldom used for moving traffic. They may still need to be maintained through irrigation and trimming though, as compared to asphalt coatings that require little or no regular maintenance. Similar considerations apply to other paving material assemblies. 1.6 Mitigation measures: trees and vegetation Trees and vegetation are the most effective means of reducing temperatures and cleaning the air in urban areas. They can serve as wind breaks that deflect and reduce wind velocity in the vicinity of built forms. This helps reduce heating losses from buildings in 19 cold climates and protect against harsh winds in hot climates. The choice of vegetation type is important as in cold regions, one would not want the sun to get blocked and in hot regions one would want shade as well as the cool evening breeze to filter through. There are primarily two ways in which trees and vegetation help cool the natural environment: shade and evapotranspiration. Shading of surfaces through trees and vegetation cools them down as re-radiation of heat to the environment is significantly lowered. Only a fraction of the total incident solar radiation is transmitted through the leaves and is able to reach the surfaces below. Most of it is either reflected or absorbed by plants (Fig. 14). This is however dependant on the species and types of trees and vegetation selected keeping in mind the local climate and seasons of the year. Figure 14: Leaves absorb and use a large portion of the visible solar radiation, but reflect and transmit a large portion of the invisible solar infrared radiation. 29 29 Brown, R.D. & Gillespie, T.J., 1995. Microclimatic Landscape Design: Creating Thermal Comfort and Energy Efficiency, Wiley. Pp. 47 20 Figure 15: The hydrologic cascade in a soil-plant-atmosphere system. At the right is an electrical analogue of the flow of water from the soil moisture store to the atmospheric sink via the plant system. 30 Trees and vegetation take moisture from the soil and transport it to their leaves and branches from where it is eventually lost to the environment. This movement of water from the soil to the external environment is called transpiration. Water also gets deposited on these surfaces from external sources such as rainfall and dew, which is evaporated directly from the surface itself. Leaves and other vegetation types significantly increase the exposed surface area for the same amount of land area. Some moisture is evaporated directly from the soil as well. This process of evaporation takes heat from the air and uses it to convert water from its liquid state to its gaseous state using latent heat from the 30 Oke, T.R., 1978. Boundary Layer Climates 1st ed., Routledge. Pp. 105 21 environment and hence causing cooling. This combined process of transpiration and evaporation due to plants is known as evapotranspiration (Fig. 15). The correct location of shading from green cover in the urban environment is of critical importance. It is important to shade the east, west and south sides of a building from the hot summer sun. As discussed above, it is beneficial to shade external surfaces such as roofs, walls, windows, etc. that gain direct solar radiation. Shading these building components helps reduce electricity demand in the building itself, as there is a reduced need for cooling from artificial sources such as conventional air-conditioning. Some examples of design using landscape elements at the site level are given in figures 16, 17 and 18 below. 22 Figure 16: Landscaping techniques for a temperate climate. The windbreak on the north side of the building should be no farther away than four times its height. 31 Figure 17: Planting design - Minneapolis, Minnesota 32 31 Gregory McPherson, E. ed., 1984. Energy-conserving site design, American Society of Landscape Architects. 32 Ibid 1 = 3 trees placed on the E-SE block morning summer sun without blocking solar access or cooling summer breezes. 2 = Shade on the S & SW facing surfaces reduces late afternoon temperatures inside the home. 3 = Trees located S of due W allow sunlight to enter W facing windows during late fall when heating is required. 4 = Low branching conifers intercept late afternoon sunlight & provide wind protection. 23 Figure 18: Picking the right trees and putting them in the right location will maximize their ability to shade buildings and block winds throughout the year 33 This concept can be extrapolated at the urban level to also include dark horizontal surfaces such as in parking lots, streets and pavements. Shading greatly reduces the amount of heat absorbed and subsequently transmitted back to the environment by these surfaces, while also adding pleasant landscape elements to improve the urban aesthetics and air quality. 33 Reducing Urban Heat Islands: Compendium of Strategies - Trees and Vegetation, U.S. Environmental Protection Agency. Available at: http://www.epa.gov/hiri/resources/pdf/TreesandVegCompendium.pdf. 24 1.7 Mitigation measures: green roofs Green roofs can be described as greenery planted on rooftops. The idea is simple: the amount of greenery displaced on the ground due to the erection of a building is returned by creating a rooftop garden. This is often an expensive exercise and due to increased structural loads on the building, is usually not possible in existing buildings without a structural reinforcement. This is one of the reasons why it is an expensive exercise to install a green roof. However, the benefits of installing green roofs are many. For starters, the life of the roof itself increases manifold as the diurnal temperature differential is regulated by the evapotranspiration of the greenery. This causes a reduced expansion and contraction of materials in the roof assembly, thereby increasing the life span of the structure. Secondly, the regulated thermal environment allows a moderation in the extremes of fluctuation in the interior temperatures. This reduces excess heating or cooling of the spaces beneath a green roof, resulting in significant savings on heating and cooling costs. Planting native species on rooftops that require little or no watering can be an effective way to reduce maintenance costs and to better support the local plant species. 25 Figure 19: Greenery for rooftops 34 Green roofs can be of two types: extensive and intensive. The extensive type of roof system is a light weight green roof that can have an approximately two inch thick soil base and can still support plants adapted to extreme climates. It is easier to install this type of a green roof on an existing building as it does not require an extensive structural retrofit. The other system, an intensive green roof system, is represented by a larger green roof more like a full roof garden. It is structurally heavier and requires a retrofit for existing buildings along with a stronger foundation. This type of a green roof can accommodate bigger plants and even trees on it. However, the maintenance costs are higher, and the initial investment in such a roof can be substantial. 34 http://www.mtsd.org/asburywoods/wp-content/uploads/2008/02/green-roof.JPG. Accessed 2009.01.12 26 Figure 20: Green roofs with regular roofs 35 Figure 21: Infrared image of temperatures 36 There are however, many benefits of installing green roofs. Some of the notable ones are: 1. Reduced energy use and increased comfort. As the green roof makes the conventional roof thicker, it also adds more insulation to it, making the thermal performance of the roof better. The evapotranspiration benefits from the greenery further cools down the roof surface. All these measures reduce the temperature of the roof, which translates into lower cooling costs for habitable spaces beneath the roof. This added insulation also prevents the heating in these spaces to escape through the roof plenum during winters. These properties result in electricity and energy savings, which are different for different climate zones. Reduction in diurnal swings and losses through roofs help 35 On a typical day, the Chicago City Hall green roof measures almost 80°F (40°C) cooler than the neighboring conventional roof. As quoted in Reducing Urban Heat Islands: Compendium of Strategies - Green Roofs, U.S. Environmental Protection Agency. Available at: http://www.epa.gov/hiri/resources/pdf/GreenRoofsCompendium.pdf. Pp. 4 36 National Center of Excellence/ASU as quoted in Reducing Urban Heat Islands: Compendium of Strategies - Green Roofs, U.S. Environmental Protection Agency. Available at: http://www.epa.gov/hiri/resources/pdf/GreenRoofsCompendium.pdf. Pp. 4 27 improve human comfort conditions in the habitable spaces, especially in non-air- conditioned buildings. 2. Reduced air pollution. Adding vegetation in the green-starved urban environment helps clean the air through normal plant processes such as photosynthesis and evapotranspiration. Plants help sequester carbon and provide more oxygen to the polluted city areas. 3. Enhanced storm water management and water quality. A normal roof collects dirt and debris that is washed into the storm water pipes during rains. Being hard paved, the runoff is very high and all the water that falls on the roof is drained away from the site through piped connections. These two issues deteriorate the water quality and prevent the site from a natural water recharge. A green roof does not solve these problems completely, but aids greatly in their mitigation. As the roof is now vegetated, water is continuously filtered through layers of plant and soil matter. It no longer collects residual dirt and debris on the roof surface. Being a soft surface, green roofs slow down the water runoff, absorbing water throughout, for they need irrigation as well. Therefore, rainwater is not completely lost to storm water pipelines and is retained on the site. This reduces load on the pipelines themselves and help maintain the natural ecology of the place. Reduced runoff rates and absorption also help contain flooding and overflowing sewers in communities. All these factors help alleviate the quality of life in urban neighborhoods. 28 1.8 Cost wise comparison of mitigation strategies 1.8.1 Cool roofs Cool roof coatings can cost between $0.75 and $1.50 per square foot for materials and labor. Single ply membranes can cost between $1.50 and $3.00 per square foot, including materials, installation and some base preparation work. This is the least expensive improvement measure that can be used on existing rooftops. 1.8.2 Cool pavements The costs of cool pavements can vary widely based on the location and terrain conditions on site. Some of the factors involved are the region, local climate, contractor, time of the year, accessibility of the site, underlying soils, project size, expected traffic, and the desired life of the pavement. The table below compares the estimated costs of a conventional paving type with alternate paving types. 29 Table 1: Comparative Costs of Various Pavements 37 37 “Figures are taken from multiples sources and express the maximum range of the values: 1) Cambridge Systematics. 2005. Cool Pavement Draft Report. Prepared for U.S. EPA. 2) ASU’s draft of the Phoenix Energy and Climate Guidebook. 3) Center for Watershed Protection. 2007. Redevelopment Projects. New York State Stormwater Management Design Manual. Prepared for New York State Department of Environmental Conservation. Retrieved June 13, 2008, from <www.dec.ny.gov/docs/water_pdf/swdmredevelop.pdf>. 4) Bean, E.Z.,W.F. Hunt, D.A. Bidelspach, and J.T. Smith. 2004. Study on the Surface Infiltration Rate of Permeable Pavements. Prepared for Interlocking Concrete Pavement Institute. 5) Interlocking Concrete Pavement Institute. 2008. Permeable Interlocking Concrete Pavements: A Comparison Guide to Porous Asphalt and Pervious Concrete. 6) Pratt, C.J. 2004. Sustainable Drainage: A Review of Published Material on the Performance of Various SUDS Components. Prepared for The Environment Agency. Retrieved June 13, 2008, from <www.ciria.org/suds/pdf/suds_lit_review_04.pdf>. 7) NDS, Inc. Technical Specifications for Grass Pavers. Retrieved June 13, 2008, from <www.ndspro.com/cms/index. php/Engineers-and-Architects.html>. 8) Tran, N., B. Powell, H. Marks, R. West, and A. Kvasnak. 2008. Strategies for Design and Construction of High-Reflectance Asphalt Pavements. Under review for the 2009 Transportation Research Board Annual Meeting.” As quoted in Reducing Urban Heat Islands: Compendium of Strategies - Cool Pavements, U.S. Environmental Protection Agency. Available at: http://www.epa.gov/hiri/resources/pdf/CoolPavesCompendium.pdf. 30 1.8.3 Trees and vegetation The cost related to trees and vegetation is dependent on the scale of the project, species being planted, labor rates, and similar factors. In general planting more trees would require more maintenance in the form of irrigation, pest control, and so on. However, the benefits of plants are much more than their associated costs. A five-city study found that by spending about $15-65 annually, the benefits were in the range of $30-90 per tree. 38 In California, the benefits have been found to range from $0-85 per tree. 39, 40, 41 Also, this is perhaps one measure that can be adopted by anybody, beginning from an individual to a large corporation. 1.8.4 Green roofs The cost of installing a green roof is relatively higher than the cost for a conventional roof or a cool roof. The cost is also dependent on the type of green roof selected for installation. An extensive green roof will be relatively cheaper than an intensive green roof. The cost usually is dependent on the additional structural reinforcement required for the building, waterproofing, cost of growing medium, irrigation, maintenance, labor, etc. Also, depending on where the green roof is being installed, there may not be an 38 McPherson, E.G. et al., 2005. Municipal Forest Benefits and Costs in Five US Cities. Journal of Forestry, 103(8), 411-416. 39 McPherson, E.G. et al., 2000. Tree Guidelines for Coastal Southern California Communities. 40 McPherson, E.G. et al., 1999. Benefit-Cost Analysis of Modesto’s Municipal Urban Forest. Journal of Arboriculture, 25(5), 235-248. 41 McPherson, E.G. et al., 2001. Tree Guidelines for Inland Empire Communities. 31 abundance of skilled labor in the locale to execute the job. To give an example of the numbers, for a simple extensive roof the costs start from $10 per square foot, and for an intensive roof the costs start from $25 per square foot. 42 This makes green roofs a high initial investment strategy for mitigating urban heat islands. However, a green roof has many more environmental advantages as outlined in the respective section above. In order to incorporate the mitigation measures identified in this chapter, it is helpful to conduct the following analyses: • Modeling the effects of green roofs, cool roofs, concrete grass pavers, and other alternatives to the regular surface and paving options available for heat island mitigation. • Comparing positive effects of trees and vegetation to the negative effects of hard- paved surfaces in an urban environment. We have now been introduced to the issue of urban heat islands and its importance for urban areas. Next, we will look at what others have done in the past in order to study the effect and what their findings have been. 42 Peck, S. & Kuhn, M., 2001. Design Guidelines for Green Roofs, Toronto, Canada: National Research Council Canada. 32 CHAPTER TWO: LITERATURE AND BACKGROUND STUDY 2.1 Several leading UHI researchers Air temperatures over cities are higher than those over rural areas. This has led many researchers to investigate the causes. Heat islands have been well documented in different books and other literature sources. Air temperature measurements and graphs, along with satellite imagery have been used to compare hot urban areas to cooler rural areas. The following is a list of agencies that have been researching this phenomenon: 1. The Urban Heat Island group 43 in the Lawrence Berkeley National Laboratory has been proactive in heat island research. Hashem Akbari, Joe Huang, Susan Davis and Haider Taha at the group have been instrumental in propagating heat island research across the world. Their collaborations with some of the agencies listed below have triggered other researchers’ interest as well. Their publication, Cooling Our Communities” (1992) in collaboration with the US Environmental Protection Agency was much ahead of its time and identified important mitigation measures almost fifteen years ago. Mr. Akbari is the group leader of the Heat Island group and has been actively involved in heat island related research. He is the author of multiple publications and an international expert on heat islands and cool roofs. 43 http://eetd.lbl.gov/HeatIsland. Accessed 2008.02.18 33 2. Heat Island Reduction Initiative (HIRI) at the US Environmental Protection Agency 44 . This agency has often funded and collaborated with researchers in educational institutions to dig deeper into the impacts of this urban phenomenon. 3. Research facilitated by the California Energy Commission 45 on heat islands and cool roofs 46 . 4. Research at Arizona State University 47 . The engineering school at ASU has developed a permeable concrete composition that has a low albedo value and is almost totally permeable to water. This has been well documented by them and the technique is also available commercially. This research in materials has provided an alternative for paving in urban areas where rainwater percolation to the water table below is restricted by non-porous surfaces with a high runoff coefficient. 5. Work done by the National Aeronautics and Space Administration (NASA) on Urban Heat Islands has used satellite thermal image mapping 48 for studying temperature differences at a macro scale 49 . 6. In terms of software development, Arup, in collaboration with UK’s University of Reading has developed a computer model that makes some quantitative predictions of the urban heat island effect. 50 44 http://www.epa.gov/heatisland/index.htm. Accessed 2008.10.12 45 www.energy.ca.gov Accessed 2009.02.12 46 www.consumerenergycenter.org/coolroof. Accessed 2009.02.25 47 http://caplter.asu.edu/home/capltertour/heat_island.htm Accessed 2009.02.23 48 http://science.nasa.gov/newhome/headlines/essd21apr99_1.htm. Accessed 2009.02.23 49 http://www.nasa.gov/centers/goddard/news/topstory/2004/0801uhigreen.html. Accessed 2009.02.23 50 Sustainable Buildings brochure. Arup. 34 7. Prof. Matheos Santamouris 51 at the University of Athens, Greece, is the editor of several books including “Santamouris, M. ed., 2001. Energy and Climate in the Urban Built Environment, Earthscan Publications Ltd.”, and “Santamouris, M. ed., 2006. Environmental Design of Urban Buildings: An Integrated Approach, Earthscan Publications Ltd.”. He is also the author of numerous journal articles related to the topic. 8. Prof. Nyuk Hien Wong 52 at the National University of Singapore 53 is the co-author of “Wong, N.H. & Chen, Y., 2008. Tropical Urban Heat Islands: Climate, buildings and greenery 1st ed., Taylor & Francis” among numerous other publications and journal articles related to the topic. 9. Prof. Akashi Mochida 54 at the Tohoku University in Japan is the author of numerous journal articles and research papers on the topic. He has been involved in the development of the Comprehensive Assessment System for Building Environmental Efficiency 55 (CASBEE) standard on heat islands for the Japan GreenBuild Council (JaGBC) and Japan Sustainable Building Consortium (JSBC). 10. Prof. Qihao Weng 56 at the Center for Urban and Environmental Change, Indiana State University, is working on projects related to the heat island from a remote sensing perspective. He is the principal investigator of a project funded by the National Science Foundation, and is also working with the city of Indiana, NASA Indiana 51 http://grbes.phys.uoa.gr/SANTAMOURIS%20MATHEOS.htm. Accessed. 2009.02.25 52 http://courses.nus.edu.sg/course/bdgwnh/www/. Accessed 2008.11.08 53 http://www.bdg.nus.edu.sg/staff_bdgwnh.htm. Accessed 2009.11.08 54 http://db.tohoku.ac.jp/whois/e_detail/5ff24bfc08439ce1e953b5a0b036b666.html. Accessed 2009.02.25 55 http://www.ibec.or.jp/CASBEE/english/index.htm. Accessed 2009.02.25 56 http://isu.indstate.edu/qweng. Accessed 2009.02.25 35 Space Grant Consortium, and the U.S. Geological Survey IndianaView Consortium on similar projects. He is the author and editor of several books including “Weng, Q. & Quattrochi, D.A. eds., 2006. Urban Remote Sensing 1st ed., CRC” and “Weng, Q. ed., 2007. Remote Sensing of Impervious Surfaces 1st ed., CRC”; and has authored several journal publications. 11. Prof. C.J.G. (Jon) Morris 57 at the School of Earth Sciences, University of Melbourne, has studied the heat island in Melbourne and examined the spatial and synoptic influences on it, along with an analysis of effects of wind and cloud conditions. 12. Ecotect (a computer program) developed by Dr. Andrew J.Marsh 58 does analysis for two important factors to consider for mitigating heat islands: shading, and insolation, which is the amount of solar radiation reaching the Earth by latitude and by season. 59 The program has recently been acquired by Autodesk Inc. 60 13. Prof. Luo Qing at Chongqing University in China has also been working on the issue. Some examples of his research include the use of an image processing technology that changes an RGB image to a “gray image” and is used to study the Outdoor Thermal Environment (OTE) by analyzing the pixels of the image for their numeric data structure. He studies the network of air flow models to derive mathematical relations. Together, he uses the analysis of images and mathematical models to derive output images that are classified as “specific heat images”, “density images”, and “conduction images”. He calculates building and ground temperature based on these 57 http://www.earthsci.unimelb.edu.au/~jon. Accessed 2009.02.25 58 http://www.ecotect.com/andrew Accessed 2009.03.22 59 http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-annexes.pdf. Accessed: 2009.01.16. 60 http://www.autodesk.com. Accessed 2009.03.22 36 images and studies air flow zones around buildings. His other areas of interest include Phase Changing Materials (PCM) and thermal testing of urban permeable pavements. The latter examines water content of materials, effect of air temperatures, and porosity of pavements using a latent heat analysis. 14. Most of the past work on insolation also considers the possibility of using photovoltaic systems for renewable energy. This is because insolation analysis is the first that needs to be done in order to determine the effectiveness of photovoltaic panels in a given geographic location. 2.2 Understanding heat islands More than half of the world’s population now lives in cities. This trend is still on the rise, and more and more people are migrating to urban centers in search of jobs and better living conditions. This, however, has led to the increase in size of urban areas in order to accommodate the growing influx of population. With an increase in the extents of urban and suburban boundaries comes the increase in area of paved surfaces that absorb and retain heat much more than unpaved surfaces in rural areas. This wide scale transformation of non-urban areas to urban areas has caused significant changes in the surface energy and water budgets for microclimates due to surface alterations. 61 The increase in areas with paved surfaces has also reduced the water permeability of these surfaces. Now, more and more of the rain water runs off these paved surfaces into storm 61 Aron, R.H., Todhunter, P. & Geiger, R., 2003. The Climate Near the Ground 6th ed., Rowman & Littlefield Publishers, Inc. pp. 447 37 water sewers, carrying with it all the surface pollutants and spilling it all into the oceans. The paved surfaces do not cool down via gradual evaporative cooling as is characteristic of green areas with soil and plant moisture. Studies show that long wave emissions from surfaces in urban areas (L↑) are 5-12 percent greater at night, and as much as 20 percent greater during the day. 62 This contributes to the buildup of heat over urban areas much quickly than over rural areas during a 24-hour period. Some of the factors to consider for studying urban heat islands are 63 : 1. Canyon geometry: This is an issue especially in downtown areas where there are tall buildings. Long rows of tall buildings on both sides of a street form what is known as an urban canyon. Due to the height of the buildings, lower angle sunlight does not reach the street itself. Also, as the heights increase, the sky view factor (described in chapter 1) decreases and surfaces near the ground are able to see less and less of the sky. These “urban canyons” serve as heat traps that reflect the sun’s rays from upper parts of vertical faces of buildings down to the lower parts – heating up the lower horizontal surfaces. Usually when a surface absorbs heat from the sun during the day, the night breeze is able to take away the re-radiating heat away from it. In this case however, the flow of wind is restricted by the canyon geometry and the velocity of air near the ground surfaces becomes weak, decreasing its potential to flush out the re- radiating heat. Also, due to the tall nature of buildings, the horizontal surfaces closer 62 Ibid. Pp. 454 63 Wong, N.H. & Chen, Y., 2008. Tropical Urban Heat Islands: Climate, buildings and greenery 1st ed., Taylor & Francis. Pp. 53-55. 38 to the sky, viz. the roofs cool off faster than the lower surfaces such as pavements. This causes a temperature stratification that even further reduces the wind flow near the ground. Therefore the heat does not fully escape from the material surfaces and contributes to rise in temperatures in these microclimates. Figure 22: Factors affecting the Heat Island effect in an urban area 64 2. Building materials: Paved surfaces, both horizontal and vertical, store heat from the sun during the day. Urban areas have more built and paved surfaces and hence the amount of heat stored is greater. Rural areas have more vegetative cover that cools 64 Wong, N.H. & Chen, Y., 2008. Pp. 55 39 down on account of evapotranspiration from plants. The stored heat in the material surfaces is re-radiated back to the external environment at night. This accounts for more heat being emitted over urban areas than rural areas. 3. Greenhouse effect: The incoming solar radiation from the sun is shortwave radiation. When this is absorbed by material surfaces and re-emitted after a certain time lag, this radiation loses some of its energy in the process and gets converted to long wave radiation. This weaker radiation is unable to escape the environment of the earth because a) it does not have enough energy to penetrate it, and b) it gets absorbed on its way by greenhouse gases like water vapor and carbon dioxide. Due to the temperature stratification in urban canyons and increase particulate matter in urban areas due to pollution, the long wave radiation is trapped by these greenhouse gases closer to the surface of the paved areas. This causes higher temperatures to build up near these surfaces and even lesser heat to escape back to the further external environment. This again causes increased temperatures in the microclimate of these areas. 4. Anthropogenic heat source: Urban areas have more buildings, cars, air-conditioners and machinery. These are anthropogenic sources of heat that are not so abundant in non-urban areas. While buildings contribute heat gain to the external environment due to the surface characteristics of their external surfaces, they also contribute heat due to internal loads such as electric lighting, human body heat, cooking, etc. This internally generated heat is expelled to the external environment through air- conditioning, which adds even more heat to the external environment. Similarly, 40 exposed machinery like cars, industrial machines, etc. contribute heat to the external environment. 5. Evaporative cooling source: This is actually one of the rare things that take heat away from the external environment. Trees, vegetation, water bodies are all examples of evaporative cooling sources that convert the incident energy to latent heat instead of sensible heat, which leads to lower temperatures around them. This is an important factor to consider in the mitigation process of heat islands as this is one of the solutions that can be implemented in urban areas. Greenery is particularly lacking in urban areas and with it being supplemented through tree programs and vegetation drives, urban air temperatures can improve. Trees in rural areas are less effective than they are in urban areas. The reason being that in rural areas, there are more trees than paved surfaces, so the net cooling effect per tree for the microclimate is lower. However, in urban areas, there are more paved surfaces than there are vegetated surfaces. Therefore, the net cooling effect per tree will be much higher in urban areas, and which is why it is important to introduce more trees and vegetation there. 6. Wind pattern: As described above in the case of urban canyons, the wind velocity near the ground greatly reduces. This, along with the direction and speed of prevalent winds is influenced by the geometry of the urban fabric – the network of streets, orientation with regard to incoming winds and so on. These factors limit the ability of the wind to advect the re-radiating heat away from the surface materials. This emphasizes the importance of ventilation in urban areas. 41 2.3 Mathematical models for heat islands There are many mathematical models that are available for calculating the different aspects related to heat islands and their mitigation. Researchers from different fields have been working on the issue for decades and have produced equations that explain several of the natural processes that we see in our study of heat islands. The equations applicable to the methodology of this thesis are described below along with their associated aspects. As part of future work, these equations will be helpful for normalizing the results from software tools. 2.3.1 Urban design-oriented heat-island models • From Oke (1982), 65 heat island intensity near sunset and under cloudless skies by taking wind effect into consideration, is given by the following equation: dT = P 0.25 / (4 x V) 0.5 where dT = heat island intensity in degrees Celsius, P = population, and V = regional non-urban wind speed at a height of 10m in meters per second 65 Oke, T.R., 1982. Overview of interactions between settlements and their environments. In WCP-37. WMO, Geneva. As quoted in Santamouris, M. ed., 2001. Energy and Climate in the Urban Built Environment, Earthscan Publications Ltd. pp. 50 42 • From Oke (1981), 66 maximum heat island intensity can be correlated with the geometry of the “urban canyon”: dT = 7.54 + 3.97 ln (H/W) where H = building height W = distance between the buildings • This formula in terms of the “sky view factor” of the middle of the canyon floor, Y sky is as follows: dT = 115.27 – 13.88 Y sky “[T]he urban hemispheric height-to-distance ratio, as seen from a given point, can be expressed by the sky view factor. For an unobstructed horizontal area the sky view factor 66 Oke, T.R., 1981. Canyon geometry and the nocturnal urban heat island: comparison of scale model and field observations. Journal of Climatology, 1. Pp. 237-254. As quoted in Santamouris, M. ed., 2001. Energy and Climate in the Urban Built Environment, Earthscan Publications Ltd. pp. 52. 43 is equal to 1.0. For a point surrounded by close, very high buildings, or for a very narrow street, it may be about 0.1.” 67 2.3.2 Calculation of heat island effects Scientists have been working on the issue of urban heat islands in different fields as well. The following are examples of mathematical equations related to meteorology: • Heat island prediction: Ludwig’s (1970) 68 formula predicts the heat island as a function of the lapse rate: dT = 1.85 – 7.4 Y where dT = urban-rural temperature difference Y = the corresponding lapse rate (in degrees Celsius per millibar) over the rural area 67 Santamouris, M. ed., 2006. Environmental Design of Urban Buildings: An Integrated Approach, Earthscan Publications Ltd. Pp. 100. 68 Ludwig, F.L., 1970. Urban temperature fields in urban climates. Pp. 80-107. As quoted in Santamouris, M. ed., 2006. Environmental Design of Urban Buildings: An Integrated Approach, Earthscan Publications Ltd. pp. 98. 44 • Night time intensity of heat islands: Sundborg’s (1950) 69 model relates the nocturnal heat island of Uppsala, Sweden: dT = 2.8 – 0.1N – 0.38V – 0.02T + 0.03q where N = cloudiness V = wind speed T = temperature q = specific humidity • Effect of wind speed on heat island intensity: Summers’ (1964) 70 model correlates wind speed with heat island intensity: DT = 2r (∂T/∂z)Qu ρc p u 69 Sundborg, A., 1950. Local climatological studies of the temperature conditions in an urban area. Tellus, 2. Pp. 222-232. As quoted in Santamouris, M. ed., 2006. Environmental Design of Urban Buildings: An Integrated Approach, Earthscan Publications Ltd. pp. 98. 70 Summers, P.W., 1964. An urban ventilation model applied to Montreal. PhD thesis. McGill University, Montreal. As quoted in Santamouris, M. ed., 2006. Environmental Design of Urban Buildings: An Integrated Approach, Earthscan Publications Ltd. pp. 98. 45 where r = upwind edge of the city to the center, (∂T/∂z) = potential temperature increase with height z, Qu = urban excessive heat per unit area, ρ = air density, c p = specific heat, and u = wind speed Santamouris, et al (2006) argue that these models are not applicable to the urban design and energy efficiency concerns as “they primarily deal with the maximum urban temperature elevation on a given night, [and] these models cannot be applied when estimating the heat island effect on energy use for heating or cooling, which is related to the diurnal average temperature instead of nocturnal conditions. 71 ” According to them, to estimate the cooling energy consumption in summers and peak load demand, the knowledge of extreme conditions at night is not helpful as what is required is the knowledge of the daytime average and maximum temperatures. 71 Santamouris, M. ed., 2006. Environmental Design of Urban Buildings: An Integrated Approach, Earthscan Publications Ltd. Pp. 99. 46 2.3.3 Albedo calculations The albedo of a surface is the reflected solar radiation divided by the incident solar radiation. The albedo is given by the following equation on a spherical coordinate system: 72 λ 2 2π ∫ ∫ I ↑ cosθdωdλ a = λ 1 0 λ 2 2π ∫ ∫ I ↓ cosθdωdλ λ 1 0 where I = radiant intensity (W/m 2 ), θ = zenith angle defined as the angle between the normal to a surface and the incident beam, λ = wavelength, 72 Santamouris, M. ed., 2006. Environmental Design of Urban Buildings: An Integrated Approach, Earthscan Publications Ltd. Pp. 111. 47 ω = solid angle defined as the ratio of a partial spherical area of interest to the square of the sphere radius, ↑ = reflected radiation, ↓ = incident radiation In order to find an average albedo, an additional integral time should be added to this equation. 2.3.4 Effects of plants and vegetation Plants have many benefits for modification of the microclimate for our benefit. For example, they provide shade, wind shielding, cooling through evapotranspiration, and do photosynthesis. They use a very small percentage of the total incident solar radiation for their photosynthetic processes, and intercept the most of it through dense foliage, converting it to latent heat rather than sensible heat. This latent heat transforms water from the liquid state to the gaseous state, causing evapotranspirative cooling, lower leaf 48 temperatures and higher humidity in the microclimate around them. The energy budget of a plant is described by 73 : Ф n – C – λE = M + S where: Ф n = net heat gain from radiation (short-wave radiation and long-wave radiation). This is often the largest and it drives many other energy fluxes. C = sensible heat loss, which is the sum of all heat loss to the surroundings by conduction or convection λE = net latent heat loss, which is that required to convert all water evaporated from the liquid to the vapor state and is given by the product of the evaporation rate and the latent heat of vaporization of water (λ = 2.454 MJ kg -1 at 20° C) M = net heat stored in biochemical reactions, which represents the storage of heat energy as chemical bond energy and is dominated by photosynthesis and respiration S = net physical storage of thermal energy, which includes energy used in heating the plant material as well as heat used to raise the temperature of the air. Plants convert a large amount of incident solar energy to latent heat. For example, an average tree during a sunny day can evaporate 1460 kg of water and consume 860 MJ of 73 Jones, H.G., 1992. Plants and Microclimate: A Quantitative Approach to Environmental Plant Physiology 2nd ed., Cambridge University Press. As quoted in Wong, N.H. & Chen, Y., 2008. Tropical Urban Heat Islands: Climate, buildings and greenery 1st ed., Taylor & Francis. Pp. 83-85 49 energy. 74 This can also be understood in terms of the Bowen ratio for surfaces. Bowen ratio is defined as the ratio of sensible heating flux to latent heating flux. B = Q h / Q e where B = Bowen’s ratio Q h = Sensible heating Q e = Latent heating Therefore if the value for Bowen ratio is less than 1, a greater amount of incident energy is transferred to the external environment as latent energy and when it exceeds 1, the majority of energy transferred is sensible energy 75 . Applied to the case of plants, it ranges from 0.5 to 2, whereas it can be typically around 5 in the built environment and up to 110 in a desert. 76 This means that planted surfaces would be cooler than their surroundings as they are actually a) not returning as much sensible heat to the external environment as the other surfaces are, and b) they cool down the surface through evaporative cooling (conversion of sensible heat to latent heat). The reason why trees are so effective as compared to other surfaces is the large amount of exposed surface area that leaves on the trees possess. The Leaf Area Index (LAI) can be 74 Moffat, A.S. & Schiler, M., 1981. Landscape Design That Saves Energy, William Morrow 75 http://en.wikipedia.org/wiki/Bowen_ratio Accessed 2009.03.22 76 Santamouris, M. ed., 2001. Energy and Climate in the Urban Built Environment, Earthscan Publications Ltd. 50 up to ten times that of a comparable surface. 77 This causes an effect that is the reverse of the heat island effect and is called the oasis effect – whereby the temperature of the air above these planted surfaces is actually lower than that of the surrounding surfaces. This explains why we feel a temperature drop in heavily planted areas. Some of the major contributions of plants to the urban thermal environment are 78 : 1. Through shading, they reduce the amount of solar heat gain of surfaces 2. This reduces the amount of long wave radiation exchanged by the shaded surface with the external environment. 3. Through evapotranspiration, they reduce the sensible heat gain and hence the conductive and convective heat gain of surfaces 4. They convert the incident solar energy to latent energy and cause cooling through evaporation. Shading by plants implies lower temperatures of surfaces. If planting is placed in the right places, the internal cooling requirements can be greatly reduced. For example, researchers have shown that about 25% to 80% savings can be achieved on air- conditioning through strategic placement of plants around buildings (DeWalle et al., 77 Wilmers, F., 1990. Effects of vegetation on urban climate and buildings. Energy and Buildings, 15-16. As quoted in Wong, N.H. & Chen, Y., 2008. Tropical Urban Heat Islands: Climate, buildings and greenery 1st ed., Taylor & Francis. Pp. 85 78 Geiger, R., Aron, R.H. & Todhunter, P., 2009. The Climate Near the Ground 7th ed., Rowman & Littlefield Publishers. 51 1983 79 ; McPherson et al., 1988 80 ; McPherson and Simpson, 1998 81 ; McPherson et al., 1989 82 ; Parker, 1983 83 ; Raeissi and Taheri, 1999 84 ; Simpson, 2002 85 ) 86 . Therefore, placing plants near the east, west, and south walls makes sense as these facades would receive the maximum amount of solar radiation during a day. If possible, shading roofs is the best bet as a roof would still receive the maximum amount of solar radiation as it is directly exposed to the sun at most times 87 . The savings in energy could be increased by shading the air-conditioning and cooling machinery from direct sunlight in addition to measures such as cool roofs and green roofs (Petit et al., 1995 88 ). 2.3.5 Water budget of plants It is important to study the water budget of plants that are to be considered for the urban landscape. The water budget helps determine the water requirements of plants and 79 DeWalle, D.R., Heilser, G.M. & Jacobs, R.E., 1983. Forest home sites influence heating and cooling energy. Journal of Forestry, 84(3), 84-88 80 McPherson, E.G., Herrington, L.P. & Heisler, G.M., 1988. Impacts of vegetation on residential heating and cooling. Energy and Buildings, 12, 41-51 81 McPherson, E.G. & Simpson, J.R., 1998. Simulation of tree shade impacts on residential energy use for space conditioning in Sacramento. Atmospheric Environment, 32, 69-74 82 McPherson, E.G., Simpson, J.R. & Livingston, M., 1989. Effects of three landscapes on residential energy and water use in Tucson, Arizona. Energy and Buildings, 13, 127-138. 83 Parker, J.H., 1983. Landscaping to reduce the energy used in cooling buildings. Journal of Forestry, 81(2), 82-105. 84 Raeissi, S. & Taheri, M., 1999. Energy saving by proper tree plantation. Building and Environment, 34, 565-570. 85 Simpson, J.R., 2002. Improved estimates of tree-shading effects on residential energy use. Energy and Buildings, 34, 1067-1076. 86 As quoted in Wong, N.H. & Chen, Y., 2008. Tropical Urban Heat Islands: Climate, buildings and greenery 1st ed., Taylor & Francis. Pp. 87 87 Wong, N.H. & Chen, Y., 2008. Tropical Urban Heat Islands: Climate, buildings and greenery 1st ed., Taylor & Francis. Pp. 86-87. 88 Petit, J., Bassert, D.L. & Kollin, C., 1995. Building greener neighborhoods: trees as part of the plan, Washington, D.C.: Home Builder Press. 52 directly influences the evapotranspiration rates and hence the moisture available in the air surrounding them. In case of green roofs, the water budget of plants helps determine the water supply and drainage requirements for buildings, in addition to the structural loads due to additional weight of water held by plants. According to the report Cooling Our Communities 89 , the following equations are helpful in determining the water use by landscape plants: • Calculating evapotranspiration: The relative water use of different crops can be determined by using crop coefficients with a reference evapotranspiration rate. Evapotranspiration for a particular crop (ET c ) is given by: ET c = K c ET o where K c = crop coefficient ET o = reference evapotranspiration defined as the ET (in, for example, mm per day) of a 4 to 7 inch tall, cool-season grass that is not water-stressed, and that is in a large field, rendering boundary effects negligible 90 . ET = evapotranspiration • Evapotranspiration: Further, volumetric evapotranspiration rate (V ET ) can be determined by: 89 Akbari, H. et al. eds., 1992. Cooling Our Communities: A Guidebook on Tree Planting and Light- Colored Surfacing, U.S. Environmental Protection Agency, Office of Policy Analysis, Climate Change Division. 90 UC Cooperative Extension, Leaflet 21426 53 V ET = ET c A c = K c ET o A c where A c = crop area • Equation for a single tree: V ET = A crown ET tree where V ET = volumetric rate of water usage for tree A crown = crown area of tree ET tree = total water transpired and evaporated in the area covered by the tree • Irrigation requirement: The irrigation requirement, I r , for a homogeneous crop under constant environmental conditions is given by: 91 I r η = K c ET o - P where “Ir = irrigation water (mm/day) required to make up for ET losses from the previous period which were not replaced by precipitation (P).” 92 91 Akbari, H. et al. eds., 1992. Cooling Our Communities: A Guidebook on Tree Planting and Light- Colored Surfacing, U.S. Environmental Protection Agency, Office of Policy Analysis, Climate Change Division. Pp. 170 endnote no. 2 54 η = irrigation efficiency (to account for losses due to runoff and percolation out of the plant root zone) P = precipitation • Irrigation requirement: As vegetation changes in type and cover characteristics, the irrigation water requirement changes. This is expressed by: n n ∆I r = (Σ Kc, finali ffinal i - Σ Kc, initiali finitial i ) ET o / η i=1 i=1 where ffinal i = final fraction of the total urban area covered by the ith crop finitial i = initial fraction of the total urban area covered by the ith crop Kc, finali = final crop coefficient of the ith “crop” Kc, initiali = initial crop coefficient of the ith “crop” n = total number of “crops” or plant classifications Notes: 1. The precipitation term is assumed unchanged and hence dropped out. 92 A more sophisticated model would include returns of water by condensation (dew) which might be important in areas with high atmospheric moisture content and large diurnal temperature swings. 55 2. Kc, finali and Kc, initiali are coefficients that allow for changes in water use due to selection of either high or low water use plants. These are based on the specific plants selected and their water budget. • Net crop coefficient: The summed terms in the formula above can be expressed as a net crop coefficient (K n ) for the region of interest. This can be for either the initial or final distribution and expressed as: n K n = Σ Kc i f i i=1 • Water usage: From the above representation of a net crop coefficient, the percent change in water use may be determined by: ∆K n (%) = Kn, final – Kn, initial x 100 Kn, initial • Adjusted crop coefficient: An adjusted crop coefficient (AK c ) that allows basic minimum irrigation of plants while maintaining an acceptable appearance 56 incorporates an allowable level of water stress for the plants. This is important as it provides the minimum water requirements for plants in areas of water scarcity. This quantity can be especially used for green roofs. Used by the California Department of Water Resources for calculating turf irrigation requirements, it is given by (Walker and Kay, 1989 93 ): AK c = 0.8 K c where K c = crop coefficient of the plant Note: When this adjusted crop coefficient is used to estimate the water usage requirements, the equations above are to replace K c with AK c . 2.3.6 Evapotranspiration in a multi-layered canopy This evapotranspiration is different from that for plant matter directly exposed to the sun. This is given by the following equations: 93 Walker, R.E. & Kay, G.F., 1989. Landscape water management handbook, version 4.1, Office of Water Conservation, Department of Water Resources, State of California. As quoted in Akbari, H. et al. eds., 1992. Cooling Our Communities: A Guidebook on Tree Planting and Light-Colored Surfacing, U.S. Environmental Protection Agency, Office of Policy Analysis, Climate Change Division. Pp. 159 57 • Developed by Jensen and Haise (1963) 94 , the model assumes that the environment seen by the tree is essentially unchanged to calculate the additional ET of the shaded lawn. ET p = (0.0252 T – 0.078) R n where ET p = potential ET defined as the rate of ET of plants experiencing no water stress (given in cm of water per day) T = dry-bulb temperature (given in degrees Celsius) R n = short wave radiation at the grass surface (given by equivalent cm of evaporated water per day) • Modified equation: Taking R n as: R n = I(1-a) where I = incident solar radiation a = albedo of the grass 94 Jensen, M.E. & Haise, H.R., 1963. Estimating evapotranspiration from solar radiation. Journal of the Irrigation and Drainage Division (Proceedings of the American Society of Civil Engineers), 89, 15-41. As quoted in Akbari, H. et al. eds., 1992. Cooling Our Communities: A Guidebook on Tree Planting and Light- Colored Surfacing, U.S. Environmental Protection Agency, Office of Policy Analysis, Climate Change Division. Pp. 166 58 and using an average value of a = 0.2 (Oke 1987) 95 , we substitute it in the equation given by Jensen and Haise (1963) above to achieve the following result: ETp = 0.8 (0.0252 T – 0.078) I • Differential model: Taking the total differential of ET p and dividing by ET p gives: dET p /ET p = dI/I + (0.0252 dT)/(0.0252 T – 0.078) • Light filtration: Light, as it filers down through the tree canopy is given by (Jones 1983) 96 : I/I o = e -kL where I o = intensity of light at the top of the tree canopy L = Leaf Area Index. Values of 10 trees listed by Kittredge (1948) 97 range from 2.8 to 10.7. k = attenuation factor dependant on canopy structure and sun angle. Observed values of k range from 0.3 to 1.5 (Jones 1983) 95 Oke, T.R., 1988. Boundary Layer Climates 2nd ed., Routledge. 96 Jones, H.G., 1992. Plants and Microclimate: A Quantitative Approach to Environmental Plant Physiology 2nd ed., Cambridge University Press. 97 Kittredge, J., 1948. Forest Influences, Dover, New York, NY. 59 2.3.7 Transpiration Rate from Trees 98 • For analyzing any decrease in temperature due to evapotranspiration, the latent heat absorbed by ambient air needs to be known during the evaporation of water by a tree. Kjelgren and Montague (1998) 99 proposed a model to calculate the total transpiration rate (E tot in mm) of a tree, based on an energy-balance model proposed by Green (1993) 100 : E tot = E s (LAI s /LAI tot ) + E sh (LAI sh /LAI tot ) where E s = transpiration rate for sunlit portion of the canopy E sh = transpiration rate for the shaded portion of the canopy LAI = Leaf Area Index defined as the area under the crown dripline LAI s = sunlit leaf area index LAI tot = total leaf area index Note: “The model assumes an isolated two-layer tree crown suspended over a surface unshaded by surrounding objects. The tree crown is classified into sunlit and shaded layers, each 98 Santamouris, M. ed., 2001. Energy and Climate in the Urban Built Environment, Earthscan Publications Ltd. Pp. 148-149. 99 Kjelgren, R. & Montague, T., 1998. Urban Tree Transpiration over Turf and Asphalt Surfaces. Atmospheric Environment, 32(1), 35-41. 100 Green, S., 1993. Radiation Balance, Transpiration and Photosynthesis of an Isolated Tree. Agricultural and Forest Meteorology, 64, 201-221. 60 with a separate energy balance. No energy exchange is assumed between the two layers.” 101 • Leaf Area Index: As per a model given by Monteith and Unsworth (1990) 102 , the sunlit leaf area index LAI s can be calculated as: LAI s = (1 – e -kLAI ) / k where k = transmissivity or porousness of a tree crown to light and is a function of the leaf orientation relative to the ground surface and the solar elevation. • Therefore, the amount of shaded leaf area is: LAI sh = LAI tot - LAI s • Transpiration rate for each layer is given by 103 : λE = ( R n s,sh + ρc p e a / r a ) / ( + γ(2 + r s s,sh / r a ) 101 Santamouris, M., 2001. Energy and Climate in the Urban Built Environment, Earthscan Publications Ltd. Pp. 148. 102 Monteith, J. & Unsworth, M., 1990. Principles of Environmental Physics 2nd ed., London: Edward Arnold. Pp. 58-73. 103 Green, S., 1993. Radiation Balance, Transpiration and Photosynthesis of an Isolated Tree. Agricultural and Forest Meteorology, 64, 201-221. 61 where λ = latent heat of vaporization (J/g) E = transpiration rate (g/sm 2 per unit leaf area) R n s,sh = net radiation flux density retained by sunlit and shaded layers (W/m 2 ), respectively e a = canopy-level vapor pressure deficit of air (Pa) r a = total tree leaf boundary layer resistance (s/m 2 ) to vapor and heat movement, which are assumed to be equivalent 104 r s s,sh = average leaf stomatal resistances (s/m) for the sunlit and shaded layers = slope of the saturation vapor pressure curve (Pa/K) at T a γ = psychrometric constant (66.2 Pa/K) r = density of air (g/m 3 ) c p = specific heat capacity of air at constant pressure (J/(gK)) • The variables r s , (1/g s ), and e a can be measured directly. The net radiation R n s may be calculated from the global short-wave radiation for sunlit and shaded layers separately 105 , while r a can be calculated using the following empirical formula proposed by Landsberg and Powell (1973) 106 : 104 Jones, H.G., 1992. Plants and Microclimate: A Quantitative Approach to Environmental Plant Physiology 2nd ed., Cambridge University Press. Pp. 9-44. 105 Kjelgren, R. & Montague, T., 1998. Urban Tree Transpiration over Turf and Asphalt Surfaces. Atmospheric Environment, 32(1), 35-41. 106 Landsberg, J. & Powell, D., 1973. Surface Exchange Characteristics of Leaves Subject to Mutual Interference. Agricultural Meteorology, 13, 169-184. 62 r a = 59 p 0.56 (d/u) 0.5 where d = characteristic dimension of a leaf u = canopy-level wind speed p = a dimensionless number derived from the ratio of total to crown silhouette area perpendicular to the horizontal wind flow 107 . 2.4 Traditional wisdom supported by recent findings The impact of the heat island effect is the most pronounced on the dark colored horizontal surfaces in urban areas. These are the areas that absorb most amount of heat and store it. This is a function of the material properties of that surface. Traditional wisdom suggests that we use light colored roofing to reflect most of the incident solar radiation back without the surfaces being able to absorb much heat. For example, people in the tropical and sub-tropical communities like Greece and North Africa for centuries whitewashed the walls of their buildings and even streets to make them highly reflective and thus keep temperatures low. These albedo modification measures go a long way in energy savings. Lower heating of the built environment would mean lesser energy requirements for cooling and the savings could add up pretty fast when we consider large 107 Kjelgren, R. & Montague, T., 1998. Urban Tree Transpiration over Turf and Asphalt Surfaces. Atmospheric Environment, 32(1), 35-41. 63 clusters of buildings. Akbari et al. 108 simulated the energy savings due to direct and indirect effects of albedo modification and found them to be close to 50% during average hours and 30% during peak cooling periods. Most measures are cost effective and can be actively implemented without incurring any significant changes to the structure of the buildings. They can also be easily integrated into the regular maintenance cycle to further lower costs. This chapter summarizes what has already been done in the past and the work in progress around the world, including the collective work of organizations that are approaching the issue from multiple perspectives. In the next chapter, we will look at a software platform called Geospatial Decision Making (GeoDec) and its capabilities for visualization and analysis. We will subsequently see how GeoDec can help us analyze heat islands in chapters ahead. 108 Akbari, H. et al. eds., 1992. Cooling Our Communities: A Guidebook on Tree Planting and Light- Colored Surfacing, U.S. Environmental Protection Agency, Office of Policy Analysis, Climate Change Division. Pp. xxii-xxiv. 64 CHAPTER THREE: GEOSPATIAL DECISION MAKING (GEODEC) 3.1 Need for urban building information modeling From the previous chapter we have an understanding of the breadth of research that is involved in analyzing urban heat islands. It is also evident that the research is interdisciplinary and has a worldwide impact. There have been many attempts to quantify the causes and effects of heat islands. Many of them use computer simulation programs to analyze urban phenomenon. However, much of the work is restricted to experienced researchers and other technical personnel. Due to the interdisciplinary overlap of the research, it is often not possible to apply all the findings by one particular branch of science to an actual project. While this is still an elusive concept, this thesis is an attempt to take a step towards integration of approaches. The building industry today recognizes the importance of the integrative design process, where specialists from different disciplines are able to collaborate on a project seamlessly through digital tools. Much of the credit is attributable to Building Information Modeling or BIM as it is widely known. Taking this as the inspiration, a similar approach is being taken towards an integration of the interdisciplinary research at the urban scale, where a similar approach can help solve urban problems through a collaborative approach. This has defined the need for Urban Building Information Modeling or U-BIM as we shall now call it. If we look around, there are computer programs of varying complexity already in use that analyze urban 65 conditions. For example, they can be as simple as Google Earth 109 or as complex as ArcGIS 110 and other similar programs. There are other programs as well, but these two are the most commonly used by the author and have therefore been used as examples here. Figure 23: View of downtown Sacramento, CA 111 109 www.earth.google.com. Accessed 2008.09.29 110 www.esri.com. Accessed 2008.09.29 111 Generated using Google Earth 66 Figure 24: Urban analysis using ArcGIS 67 Figure 25: Scatter Plot - Diffuse Horizontal Irradiance x Global Horizontal Irradiance 112 Urban heat island research can benefit from an integrative software platform where it would be possible to integrate the research and technology from different disciplines. There have been isolated advances in the different fields conducting analysis and the need is for a platform that can integrate most of them. This is where Geospatial Decision Making or GeoDec comes in. The system is described in some detail in the following sections. Subsequent chapters will demonstrate the analyses required for heat island analysis and present a roadmap of how GeoDec can adapt to incorporate them. 112 Generated using ArcGIS 68 3.2 Introduction to GeoDec Computer software tools currently available to us allow better understanding of how a building will function once built. Parametric analysis can be used by designers to help determine better solutions before a building is constructed or suggest alternatives for remodeling in existing conditions. GeoDec 113 stands for Geospatial Decision Making. It is a system developed by the Integrated Media Systems Center, Viterbi School of Engineering at the University of Southern California. This system uses an interface that is similar to what we see in other web based applications like Google Earth or Microsoft Virtual Earth. What set GeoDec apart are its capabilities for data analysis. The following are the main components of GeoDec: 1. Rapid Construction of 3D models 2. Geospatial Data Integration a. Road Network and Map Fusion b. Data Integration and Efficient Geospatial Querying c. Temporal Data Fusion 3. 3D Visualization a. Texture Mapping and Video Fusion b. Glove-based user interface 113 GeoDec (Geospatial Decision Making) is a collaborative software development project with Dr. Cyrus Shahabi, Dr. Craig Knoblock, Dr. Ulrich Neumann and Dr. Ramakant Nevatia under the Integrated Media Systems Center at the University Of Southern California Viterbi School Of Engineering, to build an information-rich and realistic geospatial space (e.g., a city) with temporal dimension rapidly and accurately, which supports visualization, querying and data analysis capabilities. (http://infolab.usc.edu/projects/geodec/) Retrieved on 2008-03-17. 69 Figure 26: Queries displayed in this figure include those for line of sight, GIS road network, GPS based tracking of trams, nomenclature for buildings and points of interest for a site on the USC campus. GeoDec is a software platform that uses advancements in the fields of Geographic Information Systems (GIS), Global Positioning Systems (GPS), and satellite imagery to present elements and objects including buildings 114 . It has a strong graphics engine that can be expanded for doing multiple functions. For example, a user can click on a point on a map and run the function for “line of sight” for that point. The software then displays all the points and surfaces in that urban space from where that point is visible. There is 114 Shahabi, C. et al., 2006. GeoDec: Enabling Geospatial Decision Making. In Toronto, Canada. Available at: http://infolab.usc.edu/projects/geodec/publications.php [Accessed August 29, 2008]. Pp 1-3 70 other similar analysis and querying possible. These capabilities make GeoDec a useful system for many applications such as in security surveillance, GPS tracking, and so on. These can all be developed as independent extensions to the system on a common platform. This is one of the reasons why GeoDec is a promising technology in integrating the specialized work of different disciplines. Though there are many extensions possible for GeoDec, we shall be looking at the development of an extension that helps us study heat islands. However, new features for simulation and design analysis needed to be added to make GeoDec useful for this analysis. As development continues, these capabilities are also to be validated through other software programs. 3.3 Development of a heat island extension to GeoDec 3.3.1 Current Status The GeoDec team of computer scientists is currently developing a capability to visualize insolation on building surfaces as well as on pavements and other horizontal surfaces. Ecotect is to be used to validate some of the results generated by GeoDec. During the time this thesis was written, the system was developed to do some basic analysis by this team. An example is a basic solar envelope generation technique being added to the system, as shown in figure 27. 71 Figure 27: A model of USC campus with shadows and a sample solar envelope calculation in GeoDec. 115 The process for developing a heat island extension has been identified to have the following four phases: 1. Development of a shadow casting capability in GeoDec. 2. Integration of solar envelope and inverse solar envelope calculations. 3. Development of capability for calculating solar insolation. 4. Analysis with respect to urban heat islands. 115 IMSC Lab, USC Viterbi School of Engineering 72 Below are some intermediate steps and features that need to be accomplished before a heat island analysis would be possible. The program has other features as well but they are not applicable to this thesis. 1. Build site geometry. GeoDec is to import a VRML file into an exact geographic location of the site in a photorealistic environment. It does not yet import other common formats. 2. Determine location. Calculate solar position and cast shadows. This has already been accomplished, but the model does not take into account the relative “blackness” of shadows due to available ambient light. 3. Create solar envelopes. The program will do this for certain dates and times. This is only tangentially related to this project, but is important for urban solar policy and to aide design for daylighting and to determine the locations for placement of solar photovoltaic panels. 4. Create inverse solar envelopes. Almost done. The program first calculates a daily and yearly shadow volume associated with the buildings. This is then used to create a volume on a specific site that is not currently shadowed by its neighbors. Once again, tangential to the study, but useful for designers. 3.3.2 Proposed The final outcome is expected to be a visualization and analysis capability developed inside of GeoDec. The purpose of this capability will be to visualize the solar insolation on a given surface. Architects can benefit from such a visual representation of solar 73 insolation on surfaces such as building rooftops and façades. This can be extended to include SRI (Solar Reflectance Index) calculations and insolation analysis including the generation of sky maps. This unique capability will allow a heat island analysis for new and existing built form and aid in its mitigation. Some intermediate steps include: 1. Creation of an analysis grid that is overlaid on built surfaces for visualizing the results of analysis done by GeoDec. 2. Calculating insolation for different surfaces of the model. This enables the user to determine the amount of solar radiation that is incident on the project site and to quantify the heating potential of the site. 3. Assigning material data and other values to surfaces. This is what would make GeoDec a BIM tool and would allow analysis using different values embedded inside of surfaces, for example albedo information stored in the attributes of different surfaces of a model can allow an overall surface reflectance calculation. The end result will be a visualization and analysis capability in GeoDec. Through such a study, it will be possible to: 1. Identify the worst heat-polluting components in a given urban environment. 2. Look at mitigation strategies like albedo modification and increased vegetation. 3. Get suggestive answers to mitigate the Heat Island effect. 74 The last area is currently out of the scope, but can be attempted as part of future work. A notable thing here is that the idea is not to develop a list of possible solutions for architects when they insert their design scheme into the GeoDec model. The system will rather allow one to plug in the design scheme and look at the insolation effects with respect to the neighbors in a graphic representation for example. Its interpretations or recommendations are not provided. Though GeoDec will not be giving any design recommendations, architects with this information available to them will be able to: 1. Test insolation effects on different materials in their design and look for reducing the heat gain for that surface. 2. Select the correct glass type for handling the incoming solar radiation according to the climatic conditions, i.e. either low-e glass or higher solar heat gain coefficient glass types. 3. Design shading devices 4. Determine the placement of solar photovoltaic panels for maximum benefit. 5. Design the landscape and vegetative shading options near the building. 6. Select an appropriate roofing material and assembly. If for example the roof of a building is totally shaded by the neighboring buildings, the owner can protect his building by a relatively low cost measure such as a cool roof. If however the roof is gaining a high amount of solar radiation, the owner can invest in strategies such as a 75 green roof or a roof garden to cut down on the interior temperatures and to increase the life span of the roof itself. If the surface is a pavement or a road surface, the visualization capability will help city managers to take specific measures for improving the performance characteristics of the identified surfaces. For example: 1. For big parking lots that are usually covered with asphalt, there is a large amount of heat gain. These open surfaces absorb a large amount of heat and do not let any rainfall permeate through them, leading to increased temperatures and runoffs. The visualization tool can help the parking lot owners or the city to identify these lots and replace the surface with Concrete Grid Pavers (CGP’s). This introduces pleasing softscape as well as lowers the temperature and promotes water infiltration through the ground. 2. For vehicular roads and pavements, a similar strategy can be adopted once it is identified which segments are actually the worst affected. The visualization tool will be able to accurately define the extents of such segments that need to be treated for improving the material surfaces. This will contribute significantly in lowering the temperature of the outdoor paved areas and aid in Urban Heat Island reduction. 76 3.4 Learning from existing tools This study focuses on informing the development of an extension to GeoDec for heat island analysis utilizing its existing functions. The photorealistic environment of GeoDec provides a life-like representation of results and is a definite advantage over other analysis tools. The development of this extension to GeoDec will take the work of the GeoDec team forward. The functional ability within the system to study the effects of solar insolation on buildings and outdoor surfaces in an urban environment will provide results numerically and graphically. It will take into account albedo values and shadows of neighboring buildings and trees on a particular surface at different times of the day during the year. The existing software tools give a lead to what GeoDec would need to accomplish before specializing in heat island analysis. Ecotect is a software tool that has been used extensively in the academia and the industry for analysis capabilities. The results are presented through compelling graphics that especially appeal to architects. GeoDec would benefit from incorporating such capabilities in its representation of analysis results. This visual representation when set with satellite imagery, which is a hallmark of GeoDec, would be easy to interpret and use in a real world setting. It is important that results from these calculations will be validated with actual field measurements of temperature data on the surfaces on site at different times of the day as has been done in chapter 7. It will ensure the accuracy of the calculations. This is 77 however out of the current scope and is hoped to be accomplished in a future study. The effects of albedo modification through application of alternative materials for pavements, parking lots, and different types of trees in the software model are to be done to achieve the optimum values in the above categories. This method will form the basis for selecting materials for new projects as well as for renovations projects. Also as part of future work, the calculation equations can be programmed into GeoDec so that a comprehensive heat island analysis can be performed on a single platform in a user friendly manner. The graphical capabilities should be carefully integrated into the analysis as well. In this chapter we got a closer look at the GeoDec platform. This completes the background information, where we looked at a review of existing literature on heat islands in chapter 2 and in this chapter, at GeoDec, which is a step towards achieving a feasible heat island analysis. Chapter 10 describes in detail the future work required to adapt GeoDec to conduct an urban heat island analysis as identified by this thesis. In the next chapter we will look at the methodology adopted for the analyzing heat islands and the boundaries for this research. 78 CHAPTER FOUR: METHODOLOGY 4.1 Methodology Mitigation of the heat island effect requires code compliance and participation from the community in addition to steps taken by city planners and owners of buildings. There are many ways this can be accomplished. This thesis will concentrate on two - albedo modification and increasing the planting in urban areas: 1. Albedo modification: Albedo is the ratio of reflected solar energy to the incoming solar energy. Some examples of albedo values are: concrete = 10% to 50%, asphalt = 5% to 15% and vegetation = 5% to 30%. 116 Black asphalt roads and pavements need to be converted to surfaces with material having higher albedo values as dark colored surfaces will absorb more heat than lighter colored ones. When the amount of sunshine absorbed is less, surfaces would store less heat and reflect more of it back to the environment. This will reduce the amount of heat to be flushed out by the night cooling winds, thereby contributing to reduction in temperatures. As we will see ahead, the Solar Reflectance Index (SRI) value of the individual materials on the surfaces in the external environment is of concern here. 2. Increased vegetation: Increasing the amount of vegetation in urban areas enhances the heat absorbing capabilities of the built environment. Though plants have a low albedo, they’re not contributing to heating up the environment 117 . In fact, their evapotranspiration cycle provides moisture retention and evaporative cooling brings 116 Based on Brown, R.D. & Gillespie, T.J., 1995. Microclimatic Landscape Design: Creating Thermal Comfort and Energy Efficiency, Wiley. Pp. 49 117 Lechner, N., 2000. Heating, Cooling, Lighting: Design Methods for Architects 2nd ed., Wiley. 79 down temperatures. An increase in the area of paved surfaces also causes an increase in the water runoff in urban areas. Plants help contain loss of top soil from the left over unpaved areas by locking moisture in their roots as well as holding the soil together. These soft areas allow the percolation of rainwater back to the ground for rainwater harvesting and recharging of underground aquifers. 4.2 The physics behind the process Transmittance, absorptance, reflectance, and emittance are four critical ways that energy interacts with matter, like for example, solar radiance with the street pavement. For the purposes of this thesis, we shall be considering the reflectance and emittance interactions only as they are more relevant to this study of heat islands. Transmittance and absorptance are not considered as they are influenced by the internal loads and usage characteristics of individual buildings – involving transfer of energy from the inside of the building to the outside, which can vary from building to building. Additionally, this inside to outside transfer is governed by the material properties of the intermediate membranes that include assembly details, overall u-values and thermal mass and associated properties. Description of a few terms is useful at this time: Reflectance: It is the ratio of the amount of light that is reflected off a surface to the incident light on it. 80 Units: It is expressed as a percentage. Thus, if a surface reflects half the light falling on it, its reflectance is 50%. Emittance: It is the ratio of the radiation emitted by a given material to that emitted by a blackbody at the same temperature 118 . Simply, it is the amount of radiation given off by a surface that reduces the sensible heat content of the object. For example, a polished metal surface would have a high emittance value as compared to other materials. Units: Watts per square meters. Albedo: It is used to measure the reflectivity of a surface for solar radiation falling on it. Units: It is expressed as a percentage. Thus, a surface with an albedo of 0% will absorb the entire solar radiation incident on it and a surface with an albedo of 100% will reflect all of it. 118 Stein, B. et al., 2005. Mechanical and Electrical Equipment for Buildings 10th ed., Wiley. Pp. 183 81 Figure 28: Four different types of interaction Figure 29: The type of interaction depends not only are possible between energy and matter. 119 on the nature of the material but also on the wavelength of the radiation. 120 Figure 30: Effects of absorptance and the emittance characteristics of a material on the equilibrium temperature 121 119 Based on Lechner, N., 2000. Heating, Cooling, Lighting: Design Methods for Architects 2nd ed., Wiley. Pp. 46 120 Ibid. Pp. 46 82 The equilibrium temperature is a consequence of both the absorptance and the emittance characteristics of a material. The “selective coating” mentioned in Figure 30 is for solar collectors that have the same high absorptance as black, but do not emit as much as black does. The type of interaction is also dependent on the wavelength of the radiation in question. Some materials like glass are largely opaque to long-wave radiation, but allow shortwave radiation to pass through it (see figures 28, 29 and 31). Different materials have different ways through which they absorb and emit radiant energy. 121 Lechner, N., 2000. Heating, Cooling, Lighting: Design Methods for Architects 2nd ed., Wiley. Pp. 48 83 Figure 31: The top graph shows that glass transmits about 90 percent of both the visible and short- wave infrared portions of sunlight and that it does not transmit any of the long-wave infrared radiation emitted by objects at room temperature 122 122 Lechner, N., 2000. Heating, Cooling, Lighting: Design Methods for Architects 2nd ed., Wiley. Pp. 47 84 Solar radiation is short-wave radiation that is made up of ultraviolet, visible spectrum and solar infrared. The response of materials to the solar infrared range of wavelengths largely decides their heating characteristics. If a material has a higher reflectance and emittance, its contribution to the heat island is less than if it has lower reflectance (e.g. dark roofs, asphalt paving) and emittance. 4.3 Scope of Work 4.3.1 Domain of study The domain of study for this thesis is the development of an analysis methodology for architects to conduct heat island analysis. With this analysis, a landscape or urban designer can modify his or her design for better performance. Special emphasis will be given to the role of a material’s albedo and the use of plants for shadow casting and potential evapotranspiration. Specifically, it will be possible to study the effects of albedo modification on the different surfaces in an architectural scheme. 4.3.2 Not included in the domain of study Other variables affecting heat islands include the movement of air currents in the region and their deflection based upon the formation of hot and cold air pockets in the urban environment; geometry of urban form; public health benefits; air pollution prevention; smog reduction and man-made catastrophes such as heat waves. These variables are out of the scope of the current research and have not yet been investigated for our purposes. 85 4.3.3 Study Boundary The figure below depicts the factors that affect the analysis of urban heat islands in a hypothetical urban boundary. The internal heat gains and losses as well as contribution to the external environment from individual buildings are not included in the scope. This can however, be included for an advanced analysis as part of future work. Figure 32: Factors affecting an urban heat island analysis The area of enquiry for this research therefore does not include the evaluation of individual buildings and their energy consumption, heat transfer due to their respective internal loads, or U-value implications of façade materials. The boundary consists of the spaces between buildings and is not intended to cover entire cities. The mutual effect of buildings on each other has been considered. 86 So, effects like mutual shading and inverse solar envelope have been taken into account. Parking lots, open spaces, roads, pavements, rooftops and vegetation are included. Wind studies are not within the scope of the current investigation, but are hoped to be done as part of future work. 4.4 Deduction The first step is to conduct an accurate analysis of the problem is to simulate effects of the heat island on the building or surface in question. It is therefore important to identify the climatic characteristics of the site under investigation. The analysis starts with a single building in an urban area whose roof absorbs incident solar radiation (insolation) throughout the day and heats up. If it is dark in color, it absorbs much more heat than if it is light in color. As we will see in Chapter 7, the roofs of buildings studied on the USC campus do not exhibit these characteristics as much as the asphalt parking lots that front them. The amount of solar insolation available in an area depends upon the geographic location of the building and the amount of solar radiation available at that time of the day and year. Therefore, it is important to consider the location and reflectivity of the surface (e.g. building roof). A computer simulation tool such as Ecotect 123 allows numerical and graphical analysis to take these factors into account. 123 www.ecotect.com. Accessed 2009.02.12 87 The existing site issues need to be addressed beforehand. There may be existing buildings, monuments, trees, etc. surrounding the building site that would affect the amount of incident solar radiation that directly hits the site at different times of the day and year. The site may also partially or fully be shaded by these external elements. All these variables are influenced by the prevalent weather. Therefore, one should be able to visualize the project in a larger model of the neighboring urban environment for analysis. An important requirement is modeling of the inverse solar envelope for a building (solar envelope is the maximum buildable volume on a site without hindering the solar access of existing neighboring buildings at specified times.). An inverted solar envelope is the maximum build-able volume of neighboring buildings so that they don't obstruct the solar access of the building on site under investigation. The next step is to calculate the Solar Reflectance Index (SRI) of the roofing material. It is important to note that two surfaces may have the same albedo value, but vary considerably in their emittance values. For example, some polished metals can have the same albedo value as a white painted surface. However, the metals have much lower emittance values than the white painted surface – making them hotter 124 . For new buildings, an architect has control over selection of materials that has the highest albedo and emittance values to be used for successfully reflecting sunlight. But for existing buildings, it is important to determine the albedo of the surface under investigation. It may not be possible to test each and every surface that already exists in the surrounding 124 Lechner, N., 2000. Heating, Cooling, Lighting: Design Methods for Architects 2nd ed., Wiley. 88 built environment physically. One has to usually rely on approximation techniques for such situations. The next most important consideration is that of vegetation and its benefits. This introduces the concept of evapotranspiration and how plants have a cooling effect on their surroundings 125,126 . While simulating the benefits of vegetation on the temperature of the horizontal surface under question (e.g. pavements), it becomes important to factor in the effect of shade and cooling provided by vegetation around it. This component has a greater dimension to it as vegetation is not static and changes over time – in different seasons of the year and over the years. 127,128 The type and species of plants is important as different varieties have varying characteristics. Therefore, it is necessary to record the exact type of vegetation in the area of inquiry. That will allow us to examine the area under its shade, and the cooling effect of that particular species of vegetation in addition to other properties identified above. The combined effect of the different considerations identified here allows us to get an accurate picture of the conditions on site due to an existing or proposed design of the built form. At this point, an architect has the option of selecting different mitigation 125 Akbari, H. et al. eds., 1992. Cooling Our Communities: A Guidebook on Tree Planting and Light- Colored Surfacing, U.S. Environmental Protection Agency, Office of Policy Analysis, Climate Change Division. 126 Wong, N.H. & Chen, Y., 2008. Tropical Urban Heat Islands: Climate, buildings and greenery 1st ed., Taylor & Francis. 127 Moffat, A.S. & Schiler, M., 1994. Energy-Efficient and Environmental Landscaping: Cut Your Utility Bills by Up to 30 Percent and Create a Natural Healthy Yard 1st ed., Appropriate Solutions Press. 128 Moffat, A.S. & Schiler, M., 1981. Landscape Design That Saves Energy, William Morrow. 89 measures and using them in permutations and combinations to achieve a harmonious result. For example, if a large building’s roof is partially shaded by surrounding buildings and there is still a large area that is exposed to the sun, one can use a mix of strategies including installation of solar photovoltaic panels, wind turbines, green roofs, cool roofs, after leaving area required for building services, amenities and usable rooftop area for occupants’ use. The combined benefits of these strategies will allow the architect or designer to test different options and achieve an acceptable result that would increase the life of a building, lower energy consumption and contribute to reducing the effects of a heat island. 4.5 Hypothesis Statement 4.5.1 Problem Even though a single building may use technology for the evaluation of its design performance, an entire community needs to harness technology to develop sustainable communities and make a positive and substantial change to global environmental concerns. 4.5.2 Purpose/Objective To study through digital methods, the design strategies that affect communities and how they can be accurately simulated for performance and subsequently better designed. 90 4.5.3 Hypothesis Urban scale computer modeling for solar insolation can aid in learning about mitigation of the heat island effect through albedo modification and increased vegetation, among other solutions. 4.6 Elaboration of Hypothesis: Terms 4.6.1 Three most important terms: 1. Insolation: Insolation is the amount of solar radiation reaching the surface of the earth or a horizontal surface such as rooftops, pavements, etc. This varies by latitude and by season. 129 Usually insolation refers to the radiation arriving at the top of the atmosphere. Units: Btu/h ft 2 or W/m 2 (1 Btu/h ft 2 x 3.152 = 1 W/m 2 ) 129 http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-annexes.pdf. Accessed 2009.01.16 91 Figure 33: A sample extracted from a table showing insolation values at 32 ° N latitude at different times of the day for two sample months. 130 2. Solar Reflectance (albedo): It is simply a ratio of the reflected solar energy to the incoming solar energy over wavelengths of approximately 0.3 to 2.5 micrometers [300 to 2500 nanometers]. 131 A 100% reflectance means that all the energy striking a surface is reflected back into the atmosphere and none of the energy is absorbed. The best standard technique for its determination uses spectro-photometric measurements with an integrating sphere to determine the reflectance at each different wavelength. An averaging process using a standard solar spectrum then determines the average reflectance (see ASTM Standard E903). 130 Lunde, P.J., 1980. Solar Thermal Engineering: Space Heating and Hot Water Systems, John Wiley & Sons Inc. as quoted in: Stein, B. et al., 2005. Mechanical and Electrical Equipment for Buildings 10th ed., Wiley. Pp. 1512 131 US Green Building Council. September 2006. LEED NC 2.2 credit 7.2. Pp. 99-100. 92 Figure 34: Surface albedo values in the urban external environment. 132 3. Evapo-transpiration 133 : Plants absorb water through their roots and emit it through their leaves. This movement of water is called "transpiration." Evaporation, the conversion of water from a liquid to a gas, also occurs from the soil around vegetation and from trees and vegetation as they intercept rainfall on leaves and other surfaces. Together, these processes are referred to as evapotranspiration, which lowers 132 Huang, Y., Akbari, H. & Taha, H., 1990. The Wind-Shielding and Shading Effects of Trees on Residential Heating and Cooling Requirements, Berkeley, CA: Lawrence Berkeley National Laboratory as quoted in Akbari, H. et al. eds., 1992. Cooling Our Communities: A Guidebook on Tree Planting and Light- Colored Surfacing, U.S. Environmental Protection Agency, Office of Policy Analysis, Climate Change Division. Pp. 45. 133 http://www.epa.gov/heatisland/resources/glossary.htm#e. Accessed: 2009.01.16 93 temperatures by using heat from the air to evaporate water. Units: inches or millimeters. Figure 35: Historical evapotranspiration rates for Los Angeles. 134 4.6.2 Next three most important terms: 1. Solar Envelope 135 : It is defined as the maximum built volume on a site such that it does not block direct sun to its neighbors in specified times. As buildings become taller and densities increase, the sun access to buildings decreases and the maximum buildable volume of the site approximates a pyramid. This is important to determine the placement of solar photovoltaic panels on rooftops as well in open areas as this helps determine the area where one gets the most amount of solar radiation to be harnessed. This concept is useful once the mitigation measures for heat islands are 134 Irrisoft, Inc., Rain Bird® ET Manager™ Scheduler Software, Tucson, AZ: Rain Bird Corporation. 135 http://www.usc.edu/dept/architecture/mbs/tools/vrsolar/Help/solar_concepts.html. Accessed 2009.01.16 94 discussed. This is one of the options that can be used in place of albedo modification on rooftops where useful solar radiation is available for generating renewable energy. 2. Solar Reflectance Index (SRI) 136 : It is a measure of a material’s ability to reject solar heat, as shown by a small temperature rise. It is defined so that a standard black (reflectance 0.05, emittance 0.90) is 0 and a standard white (reflectance 0.80, emittance 0.900 is 100. For example, a standard black surface has a temperature rise of 90 °F (50°C) in full sun, and a standard white surface has a temperature rise of 14.6 °F (8.1°C). Once the maximum temperature rise of a given material has been computed, the SRI can be computed by interpolating between the values for white and black. Materials with the highest SRI values are the coolest choices for roofing. Due to the way SRI is defined, particularly hot materials can even take slightly negative values, and particularly cool materials can even exceed 100. 137 Units: Since SRI is a ratio (of temperatures), it has no units. Table 2: Solar Reflectance Index (SRI) of typical roofing materials 138 136 US Green Building Council. September 2006. LEED NC 2.2 credit 7.2. Pp. 99-100. 137 Lawrence Berkeley National Laboratory Cool Roofing Materials Database 138 LBNL Cool Roofing Materials Database as quoted in: LEED NC v.2.2 Pp. 99. These values are for reference only and are not for use as substitutes for actual manufacturer data. Individual products may perform better. 95 Table 3: Solar Reflectance Index (SRI) of standard paving materials 139 3. Infrared or Thermal Emittance: It is a parameter between 0 and 1 (or 0% and 100%) that indicates the ability of a material to shed infrared radiation (heat). The wavelength range for this radiant energy is roughly 3 to 40 micrometers [3000 to 40000 nanometers]. 140 Most building materials (including glass) are opaque in this part of the spectrum, and have an emittance of roughly 0.9. Materials such as clean, 139 Council, U.G.B., 2006. New Construction & Major Renovation Reference Guide 2nd ed. Pp. 93 140 Ibid. 96 bare metals are the most important exceptions to the 0.9 rule. Clean, untarnished galvanized steel has a low emittance, and aluminum roof coatings have intermediate emittance levels. 4.6 Methodology for new and existing buildings 4.6.1 New buildings For new buildings, designers and city planners have the maximum control over the finishes, materials and other design aspects. Analysis for new construction is largely restricted to preliminary simulations using energy modeling tools at the design stage. Therefore a heat island analysis should also be conducted at this stage. The analysis should be doable using a set of goals and criteria in a relatively simple software platform. With increased awareness about heat island mitigation, such analysis will become common for designers. New buildings are currently not analyzed in this thesis as this requires enough development of the GeoDec system to be able to conduct any heat island related analysis. A design model can be imported into the GeoDec platform but without the capabilities for analysis that does not serve any purpose. Therefore we begin with analyzing existing buildings. 4.6.2 Existing buildings 97 For existing buildings, it is important to study the site in detail and conduct field measurements. The text book values or values from manufacturer’s data sheets are not applicable to such situations in determining the best course of action for mitigating heat islands. This is primarily because surfaces in the real world are exposed to the natural elements and significant modifications may occur to surface characteristics based on climatic variables, weathering, discoloration, and so on. Measurements obtained from field data can then be used in software tools to model the existing scenario accurately. This enables an informed intervention to alter existing surfaces to combat the heat island. It is important to note that in such an investigation, one has to consider the effects of neighboring built form, vegetation, and other objects that are in the vicinity of the site. This hold true for analysis in the case of new construction as well. This chapter has defined the approach for studying an urban area in order to suggest guidelines for design decisions which would reduce the impact of that area on the Urban Heat Island effect. The next chapter presents the measurement devices required for the field data collection, their uses and technical specifications. These will be used to study site III on USC campus, the field measurements of which are presented in chapter 7. Subsequent chapters will show the beginning of a study of existing sites, results and modifications to the boundary of the area being tested. 98 CHAPTER FIVE: DATA MEASUREMENT DEVICES 5.1 Field Measurements For conducting a heat island analysis for existing buildings, we need to take field measurements of the variables involved by surveying the site. Below are some quantities that are to be measured: 1. Illuminance for sky and test surfaces Luminance is the luminous intensity per square unit of area that receives it. Simply, it describes the amount of light that passes through or is emitted from a particular area, and falls within a given solid angle. 141 Units: cd/m 2 , cd/ft 2 , Footlambert 2. Luminance for test and reference surfaces Illuminance is the amount of light falling on a given surface area. For example, one lumen of luminous flux, uniformly incident of 1 m (ft 2 ) of area, produces an illuminance of 1 lux (footcandle). 142 Units: lux, footcandle 3. Infrared Photos of test surfaces 4. Surface temperatures of surfaces 5. Air temperature 6. Relative Humidity As we shall see later, existing buildings on the USC campus were studied for this analysis. These quantities were measured by state-of-the-art measurement devices as specified in this chapter. The devices were selected based on the requirements for 141 http://en.wikipedia.org/wiki/Luminance. Accessed 2009.06.08 142 Stein, B. et al., 2005. Mechanical and Electrical Equipment for Buildings 10th ed., Wiley. Pp. 464 99 measurement of incident solar radiation, SRI and the effects of vegetation on the given site. They are now being described in detail here. 5.2 Digital Infrared Camera 5.2.1 Usefulness to study For studying the temperature characteristics of the site, it is important to have measurements regarding surface temperature of the test surfaces and compare them with the surrounding surfaces. This infrared camera allows these measurements to be taken in an easy and efficient manner. On taking these measurements it was revealed how different surfaces behave thermally under the same given environmental conditions. This was also used to determine the points on site where other measurements should be taken and was therefore a valuable tool for the thesis. 5.2.2 Technical Specifications • Manufacturer: Extech Instruments • Make: FLIR Infrared Camera • Model Number: Extech i5 100 Figure 36: Rear View Figure 37: Front View • Technical Specifications: o Imaging and optical data: Field of view (FOV) 17° × 17° Close focus limit 0.6 m (2 ft.) Thermal sensitivity/NETD < 0.1°C (0.18°F) Image frequency 9 Hz Focus Focus free 101 o Detector data: Detector type Focal plane array (FPA), uncooled microbolometer Spectral range 7.5–13 μm Resolution 80 × 80 pixels o Image presentation: Display 2.8 in. color LCD o Measurement: Object temperature range 0°C to +250°C (+32° to +482°F) Accuracy ±2°C (±3.6°F) or ±2% of reading, for ambient temperature 10° to 35°C (+50° to 95°F) 102 o Image storage: Image storage type miniSD™ Card File formats Standard JPEG, 14-bit measurement data included Compatibility ThermaCAM Reporter 8 and ThermaCAM QuickReport compatible o Power system: Battery type Rechargeable Li ion battery Battery voltage 3.6 V Battery operating time Approximately 5 hours at +25°C (+77°F) ambient temperature and typical use Charging system Battery is charged inside the camera Power management Automatic shut-down AC operation AC adapter, 90–260 VAC input. 5 V output to camera 103 o Data Communication Interfaces: Interfaces USB Mini-B: Data transfer to and from PC o Environmental data: Operating temperature range 0°C to +50°C (+32°F to +122°F) Storage temperature −40°C to +70°C (−40°F to +158°F) range Humidity (operating and storage) IEC 60068-2-30/24 h 95% relative humidity EMC • EN 61000-6-2:2005 (Immunity) • EN 61000-6-3:2001 (Emission) • FCC 47 CFR Part 15 Class B (Emission) Encapsulation Camera housing and lens: IP 43 (IEC 60529) Bump 25 g (IEC 60068-2-29) Vibration 2 g (IEC 60068-2-6) 104 o Physical data: Camera weight, incl. battery 0.34 kg (0.75 lb.) Camera size (L × W × H) 223 × 79 × 83 mm (8.8 × 3.1 × 3.3 in.) Material • Polycarbonate + acrylonitrile butadiene styrene (PC-ABS) • Thixomold magnesium • Thermoplastic elastomer (TPE) o Certifications: Certification UL, CSA, CE, PSE and CCC o Field of view and distance 143 : 143 2008. FLIR Systems - User's Manual: FLIR i5, Extech Instruments (A FLIR Company). Available at: http://www.extech.com. Pp. 41 105 Figure 38: Relationship between the field of view and distance. 1: Distance to target; 2: VFOV = vertical field of view; 3: HFOV = horizontal field of view, 4: IFOV = instantaneous field of view (size of one detector element). 144 This table gives examples of the field of view for different target distances: 144 Ibid 106 Table 4: Field of view for different target distances 145 • Made in: European Union • Website: http://www.extech.com/cameras/product.asp?prodid=492 5.3 Luminance Meter 145 2008. FLIR Systems - User's Manual: FLIR i5, Extech Instruments (A FLIR Company). Available at: http://www.extech.com. 107 5.3.1 Usefulness to study This device was needed to measure the luminance of the test surface and the reference surface. As we will see in a later chapter, luminance values of these two surfaces when plugged into an equation, give us the reflectance of the test surface – which is the objective. This meter specifically is handy as it is portable and gives a stable reading for most surfaces. Its adaptability for outdoor surface luminance values was particularly helpful in measurements. Figure 39: Side View Figure 40: Side View 108 5.3.2 Technical Specifications • Manufacturer: Minolta Camera Co., Ltd. • Make: Minolta Luminance Meter 1° (Digital) • Model Serial Number: 301762 • Technical Specifications: o This device provides readings in ft-L o Uses 9V dc battery • Conversion factors: o cd/ft 2 = x (1/π) o cd/m 2 = x (3.43) o asb = x (10.76) • Made in: Japan • Website: http://www.konicaminolta.com/instruments/ 5.4 Digital Environment Meter 5.4.1 Usefulness to study This multi-purpose meter was very helpful in determining the illuminance of the test surface, sky illuminance, air temperature, relative humidity for each case where measurements were taken. 109 These measurements allow the comparison of values later on when doing calculations as the external environmental conditions are now known. If someone desires to take similar measurements for a study in the future, these values become benchmarks for their study as well. Particularly useful was the digital interface of the device and its ability to measure a lot of variables as a single device. 5.4.2 Technical Specifications • Measures: o Illuminance (lux) o Temperature (°C and °F) o Relative Humidity (percent) o Sound Level (dB) • Manufacturer: Shenzhen Everbest Machinery Industry Co., Ltd. • Make: Environment Meter • Model Number: DT-8820 • Serial Number: 02090501 110 Figure 41: CEM Digital Environment Meter • Technical Specifications: o Display: Large 1999 counts LCD display with function of Lux, x10 Lux, °C, °F, % RH and dB, A & dB, C & dB, Lo & dB, Hi & dB, MAX HOLD, DATA HOLD indication. o Polarity: Automatic, (-) negative polarity indication o Over-range: “OL” mark indication o Low Battery Indication: The “BAT” is displayed when the battery voltage drops below the operating level. o Measurement rate: 1.5 times per second, nominal 111 o Storage temperature: -10°C to 60 °C (14 °F to 140 °F) at < 80% relative humidity. o Auto Power Off: Meter automatically shuts down after approx. 10 minutes of inactivity o Power: One standard 9V, NEDA 1604 or 6F22 battery o Dimensions/Wt.: 251.0 (H) x 63.8 (W) x 40 (D) mm/250 g o Photo detector dimensions: 115 x 60 x 27 mm • Sound Level o Measurement range: A LO (low) – Weighting: 35-100 dB A HI (high) – Weighting: 65-130 dB C LO (low) – Weighting: 35-100 dB C HI (high) – Weighting: 65-130 dB Resolution: 0.1 dB o Typical instrument frequency range: 30 Hz-10 kHz o Frequency Weighting: A,C – weighting o Time weighting: Fast o Maximum Hold: Decay<1.5 dB/3 min. o Accuracy: +/- 3.5 dB at 94 dB sound level, 1 kHz sine wave o Microphone: Electric condenser microphone • Light 112 o Measuring range: 20, 200, 2000, 20000 lux (20000 lux range reading x10) o Overrate display: Highest digit of “1” is displayed o Accuracy: +/- 5% rdg + 10 dgts (calibrated to standard incandescent lamp at color temperature 2856 K) o Repeatability: +/- 2% o Temperature Characteristic: +/- 0.1%/°C o Photo detector: One silicon photo diode with filter • Humidity/Temperature o Measurement Range: Humidity: 25% ~ 95% RH Temperature (K-Type) -20.0 °C to +50.0 °C -4°F to +122 °F -20.0 °C to +200.0 °C -20 °C to +750 °C -4.0 °F to +200 °F -4 °F to +1400 °F o Resolution: 0.1% RH, 0.1 °C, 1 °C / 0.1 °F, 1 °F o Accuracy (after calibration): Humidity: +/- 5% RH (at 25°C, 35% ~ 95% RH) 113 Response time of the humidity sensor: approx. 6 min. Temperature: • +/- 3% rdg +/- 2 °C (at -20.0 °C ~ +200.0 °C) • +/- 3.5% rdg +/- 2 °C (at -20.0 °C ~ +750 °C) • +/- 3% rdg +/- 2 °C (at -4.0 °F ~ +200.0 °F) • +/- 3.5% rdg +/- 2 °C (at -4 °F ~ +1400 °F) (Input protection: 60 V dc or 24 V ac rms) • Made in: not specified • Website: http://www.cem-meter.com.cn/DT-8820.htm 5.5 GE Illuminance Meter 5.5.1 Usefulness to study This meter was helpful in determining the light levels for the sky when the digital environment meter described above went out of range. Though most of the measurements were taken on cloudy days, the amount of illuminance available from the sky can be very high. This meter has a cap on it that allows only 10% of the total ambient illuminance to reach the sensor, enabling it to be functional in higher light level environments. This capability was used in instances where the light levels were higher, but still needed to be measured. 114 5.5.2 Technical Specifications • Manufacturer: General Electric Lighting • Make: Type 217 Light Meter • Serial Number: Light Meter MBS 04: USC School of Architecture Figure 42: Light Meter • Technical Specifications: o Three-scale meter capable of directly reading illuminance from 10 footcandles (fc) to 1,000 fc and up to 10,000 fc with the use of the included 10X multiplier. o Color Correction: A special filter mounted over the meter cell matches the color sensitivity of the meter closely to that of the human eye. No correction 115 factors are necessary for measurements involving light sources with different spectral characteristics. Simply read the meter directly. o Cosine Correction: The diffusing plate on top of the meter case is designed to collect light from wide angles so that the cell response will be a function of the cosine of the angle that the incident light makes with the perpendicular. Light reaching the meter from various directions is therefore measured accurately. o Accuracy: The accuracy of a reading with the Type 217 meter depends upon the scale and the part of the scale used. Scale Part-of-scale Accuracy 10-50 fc 10-20 fc +/- 15% 20-50 fc +/- 10% 50-250 fc 50-100 fc +/- 15% 100-250 fc +/- 10% 200-1000 fc All +/- 15% • Website: http://www.gelighting.com/na/ • Made in: not specified 116 5.6 Temperature Gun 5.6.1 Usefulness to study The temperature gun was used to measure the exact surface temperatures of the test surfaces under question. Being an infrared device, it is much more reliable than a mercury thermometer. Also, it is much easier and faster to take measurements with this gun. It is important to use the surface temperature readings in conjunction with the infrared photographs of surfaces in order to study the warming effects of different surfaces as compared to their adjacent surfaces. While an infrared image gives an overall picture of this, this device measures the temperature of the exact point where the rest of the measurements like luminance, and illuminance are taken. Also, it gives a more accurate result. 5.6.2 Technical Specifications • Manufacturer: Raytek • Make: MiniTemp • Model Number: MT 117 Figure 43: Infrared temperature gun (side view) Figure 44: Infrared temperature gun (side view) • Technical Specifications: o Hand held non-contact thermometer using single dot laser sighting system o Output < 1mW o Wavelength: 630 – 670 nm o Class II laser product o Complies with CFR 1040.10 o Uses 9V dc battery • Website: http://www.raytek.com/ • Made in: China 118 In this chapter, we looked at the instruments used to measure data on an existing site. These quantities are important to conduct a heat island analysis. In the following chapter we will look at the site selection procedure that was followed to pick an area for analysis. This is important for researchers as there are many practical problems that can inhibit such analysis procedures, as we will see next. 119 CHAPTER SIX: SITE SELECTION AND ANALYSIS 6.1 Heat island analysis for site in downtown Los Angeles Los Angeles, CA is the second largest city in the United States and has a severe heat island problem. The city is estimated to have the potential for the second largest net annual energy cost savings when compared to eleven US Metropolitan Statistical Areas, which is just less than Phoenix, AZ 146 . This is one of the reasons why a heat island analysis makes sense in Los Angeles. Also, due to the availability of data on the city, it has been chosen for the purposes of this study. Los Angeles contains thousands of offices and other mixed use buildings that make it a guzzler of energy. The downtown area is dotted with tall buildings that heighten the urban canyon effect. As people occupy these buildings, especially during the day time hours, thermal comfort is required, and due to the heat island effect, the demand for cooling in summer months rises drastically. This requires buildings to invest heavily in infrastructural amenities just to keep the places running and comfortable for human habitation. But all this equipment consumes energy, and the energy demand is highest during peak hours. 146 Konopacki, S. et al., 1997. Cooling Energy Savings Potential of Light-colored Roofs for Residential and Commercial Buildings in 11 U.S. Metropolitan Areas, Berkeley, CA: Lawrence Berkeley National Laboratory. 120 6.2 Site Selection and Analysis A generic site should reflect a mix of short and tall buildings, parking lots, narrow streets, patches of green cover, adequate pedestrian footfall, and appropriate solar orientation. The site is to be then analyzed according to the parameters identified in Chapter 3, viz. for inverse solar envelope, albedo, Solar Reflectance Index (SRI), and vegetation to study how insolation affects each of them. Ecotect was used to conduct an insolation analysis. This will enable the numeric quantification of theoretical insolation and shadowing for this specific location. The inverse solar envelope is also simulated through the program by taking into account the mutual shading of buildings during different times of the day and the year. For determining the SRI, the albedo and emittance values of the surfaces are required. These are taken from the respective standard charts for the materials identified and SRI is calculated. For existing buildings some of these values, like reflectance, will have to be calculated based on field measurements. Keeping these factors in mind, the following sites were selected: 6.3 Site I: Downtown Los Angeles Although useful in many regards, this site was eventually not chosen for the study. The amount of information available for this site is very limited. For example, the building heights are not available. 121 It was deemed impractical to spend time trying to measure the heights of the buildings within the study area without proper instruments and even then a long process for seeking permissions rendered this option invalid. Initially it was hoped that one could use Google Earth or GeoDec selecting the heights but Google Earth does not give accurate building heights in their models, and GeoDec does not have a VRML model for this particular area in its database of buildings for downtown Los Angeles. Therefore, I proceeded to consult with the GeoDec team to select Site II as detailed in the next section. Figure 45: Site of first attempted study in downtown Los Angeles. 147 147 http://maps.google.com. Accessed 2008.10.12 122 Figure 46: Urban typology at the site. 148 6.4 Site II: Downtown Los Angeles Figure 47: Site of second attempted study in downtown Los Angeles. 149 148 Google Earth 123 This site was selected from the available area modeled in GeoDec for downtown Los Angeles so that an analysis in GeoDec could be attempted. As it turns out, this site also could not be used for the study. A third site (also available in GeoDec) was selected, but also could not be studied in GeoDec due to time restrictions. As work on GeoDec progresses, this can be attempted in the future. The second site in downtown Los Angeles is a good site to take up for analysis because it has all the essential elements that are required for a study of urban heat islands. Some of the notable features that make this site worthy of investigation are: 1. A large amount of the total horizontal paved area is dedicated to parking lots covered with asphalt. This is an essential component of the urban environment, especially in downtown areas of major cities in the United States that contributes to the heat island effect due to the dark color of asphalt that absorbs and retains a larger amount of solar infrared radiation. 2. There are tall buildings on site that shade the lower buildings adjacent to them. This is important as one of the parameters for analysis is mutual shading of buildings. If an area or building is shaded by an adjoining element for the most part of the heat gain periods, then it may not be financially wise to re-surface it or to attempt albedo modification as the case may be for heat island mitigation. Therefore, mutual shading of buildings can be studied on this site. 149 http://maps.google.com. Accessed 2008.12.23 124 3. There are a couple of trees on the periphery of the site. This gives an opportunity to investigate how urban vegetation can be helpful in lowering the temperatures of horizontal surfaces underneath them and how they regulate the flow of heat in the urban thermal environment. These tree spots can also be used to study evapotranspiration effects of trees and how that contributes to heat island mitigation. The latent heat transfer from vegetation can be compared to the sensible heat transfer of adjacent paved surfaces to make a comparison in cooling and heating contributions to the external thermal environment. 4. The site is surrounded by rows of tall buildings that form urban canyons; with streets of varying widths between buildings. This is important to study the urban canyon effect and the flow of air in the vicinity of the site. While this is currently out of scope for this thesis, the contribution of Computational Fluid Dynamics (CFD) analysis for the fluid studies in urban areas is a documented method for predicting the effectiveness of the orientation of built mass in predicting the advective potential of the night cooling winds. 5. Being in downtown Los Angeles, this site is part of the collective contribution of a large amount of built mass including tall buildings with high HVAC requirements to the urban microclimate that surrounds it. Heat generated by air-conditioning units, vehicles and other external machinery contributes to the heating budget of the area. These individual components contribute to the excess heat contained within this microclimate. Increased pollution from these processes also traps the greenhouse gases and prevents the heat from escaping to the larger external environment, which 125 can result in greater chances of fog and smog build up over downtown areas. This can also be helpful in studying the effects of smog and related health hazards due to air pollution as these are found to be prevalent in such areas. As we have seen in Chapter 1, smog accumulation gets promoted by heat islands. 6. Although I was not able to access the roofs of the buildings on site, one can see from the Google Earth images that the color of roofs is not the same everywhere. A few buildings seem to have really dark colored roofs, while others have lighter colored roofs. One of the buildings also seems to have installed solar photovoltaic panels on its roof for generation of renewable energy. This last part is important as one of the ways rooftops can be utilized if they are not be made more reflective, is to install solar photovoltaic panels on them. Though these are expensive in the initial phase, the payback is relatively short depending upon the type of panels installed and also helps produce clean electricity to meet the demands of the building, thereby reducing the load on the grid that produces electricity from various sources, including some not so clean ones like coal. Important to note here is that even though photovoltaic panels are dark in color and absorb more heat than let’s say a cool roof, they help produce environmentally clean energy. So, even though they may not help mitigate the urban heat island, they offer a tradeoff between leaving empty roofs dark and heat absorbing to using them for installing PV panels. Technology continues to evolve in the production of PV panels and lighter colors are increasingly becoming a viable option in the future. When these are available, PV panel installation and albedo modification will work together for the betterment of the environment. 126 Figure 48: Urban typology at the site. 150 150 Google Earth 127 Figure 49: VRML Model imported from GeoDec into Ecotect. Figure 50: The VRML model is composed of triangular surfaces. 128 Figure 51: Volumetric composition of the site in Google SketchUp Figure 52: Photograph of site Figure 53: Photograph of site 129 Figure 54: Photograph of site Figure 55: Photograph of site Figure 56: Photograph of site Figure 57: Photograph of site 130 Figure 58: Photograph of site – the access to roofs was not granted as the occupants of the building bear legal liability in case of an accident – a risk they did not want to take. Figure 59: Photograph of site Figure 60: Photograph of site 131 Figure 61: Wooden edge of door. Figure 62: Infrared photo of glass door. Figure 63: Photograph of rooftop Figure 64: Infrared photo through glass. 132 6.5 Conclusions After pursuing multiple agencies that are involved on Site II, it was decided not to proceed further with analysis here. Each building and indeed even the parking lot is owned by one agency, and/or leased and operated by another agency and so on. There is a restriction for access to rooftops of buildings as in case of any injury to the field investigator (me), the owners are legally liable. Therefore, there was not much progress in getting access to go to the rooftops, and some agencies refused access. After trying to convince the others to allow access for the sake of an academic project, the chances still seemed slim. And even if they did allow access, data would be required for all the rooftops and not for a few isolated ones. After further consultations with the GeoDec team and availability of permissions and data, a third site was selected on USC campus. In this chapter we saw the problems and issues surrounding the selection and analysis of a case study site. These issues should be addressed early on and an appropriate site selected. People who would like to take up further work on this project may note these difficulties while choosing a site for their own analysis. The third site is on USC campus and exhibits most of the features that are essential to the study of heat islands as identified for Site II above. This site is convenient to study as it is easily accessible and the Facilities Management Services on campus is the sole agency involved in the maintenance of the buildings – that are all owned by USC. The drawings and permissions as well as assistance for clarifications and field visits were available on this site unlike in case of the previous sites. 133 CHAPTER SEVEN: FIELD MEASUREMENTS 7.1 Heat island analysis for site on USC campus 7.1.1 Why this site? 1. Due to its location on the campus of the University of Southern California, there is ease of access and availability of permissions, drawings and data. As noted in Chapter 6, previous efforts to study sites in downtown Los Angeles failed due to these factors. 2. Los Angeles is one of the major cities in US affected by Heat Islands 151 . 7.1.2 Specifically: 1. Large area dedicated to a parking lot. This is asphalt paved and dark in color – absorbs heat. 2. Trees and vegetation on site give an opportunity to study their benefits. 3. Tall buildings shade adjacent low buildings. 4. Roofs of the buildings were found to be light in color – with one already covered with cool-roofing membranes. This presented an opportunity to study heat island mitigation measures as well. 151 Akbari et al., eds., 1992. Op cited 134 Figure 65: Site on USC Campus 152 152 http://web-app.usc.edu/maps/. Accessed 2009.02.04 135 Figure 66: Site as seen in GeoDec 153 Figure 67: Site as seen in Google Earth 154 The selected site is shown in the figures 65, 66 and 67. The area selected on the campus of USC has a parking lot paved with asphalt, a multi-storey parking structure, and three research buildings within the area of investigation. The buildings included in the analysis are: 1. Parking Structure A (PSA) 2. Ray R. Irani Hall (MCB) 3. Kaprilien Hall (KAP) 4. Denny Research Building (DRB) 153 Google Earth 154 GeoDec 136 Parking Lot 6 is one of the major paved areas that are being studied here. Other horizontal surfaces being studied include the pavements and soft surfaces in between the buildings identified above. The site also has a few auxiliary buildings, which are: 1. Child’s Way Building One (CWO) 2. Child’s Way Building Two (CWT) 3. Human Resources Center (HRC) These buildings are not included in the boundary of study due to lack of data for them. Since these are smaller buildings on the site, they can be successfully ignored for the purpose of our analysis. 137 Figure 68: Site Plan with points indicating locations where measurements were taken and arrows indicating the direction of photographs as given below. 155 155 Base drawing: Facilities Management Services, University of Southern California 138 Figure 69: At Point P1 - From roof of KAP. Figure 70: At Point P2 - KAP and MCB Figure 71: At Point P3 - MCB and KAP Figure 72: At Point P4 - Area in front of DRB 139 Figure 73: View of MCB from PSA Figure 74: Parking lot from roof of PSA Figure 75: Photograph of site Figure 76: CWO and CWT Figure 77: View from roof of DRB Figure 78: View from roof of KAP 140 Figure 79: MCB roof with pea gravel Figure 80: Paving between DRB and PSA 7.2 Infrared Images of different surfaces on site The following are infrared images as compared to the actual photograph of the external environment on the site. A variety of different surfaces have been studied here, including: asphalt paving, concrete paving, brick tile paving, metal surfaces, grass and shrubs, trees and other vegetation, soil in different conditions, pea and gravel surfaces, surfaces with Sarnafil 156 coating, and surfaces with Tar and gravel coating. The following are examples of the results achieved through an infrared camera described in Chapter 5 and the comparison with actual photographs taken with a digital camera also described in Chapter 5: 156 http://www.sarnafilus.com/index/roofing/products_rp/membranes_rp.htm. Accessed 2009.02.12. 141 Figure 81: Photograph of site Figure 82: Infrared Measurement Figure 83: Photograph of site Figure 84: Infrared Measurement 142 Figure 85: Photograph of site Figure 86: Infrared Measurement Figure 87: Photograph of site Figure 88: Infrared Measurement 143 Figure 89: Photograph of site Figure 90: Infrared Measurement Figure 91: Photograph of site Figure 92: Infrared Measurement 144 Figure 93: Photograph of site Figure 94: Infrared Measurement Figure 95: Photograph of site Figure 96: Infrared Measurement 145 Figure 97: Photograph of site Figure 98: Infrared Measurement Figure 99: Photograph of site Figure 100: Infrared Measurement 146 Figure 101: Photograph of site Figure 102: Infrared Measurement Figure 103: Photograph of site Figure 104: Infrared Measurement 147 Figure 105: Photograph of site Figure 106: Infrared Measurement Figure 107: Photograph of site Figure 108: Infrared Measurement 148 Figure 109: Photograph of site Figure 110: Infrared Measurement Figure 111: Photograph of site Figure 112: Infrared Measurement 149 Figure 113: Infrared Measurement Figure 114: Infrared Measurement Figure 115: Photograph of site Figure 116: Infrared Measurement 150 Figure 117: Photograph of site Figure 118: Infrared Measurement Figure 119: Photograph of site Figure 120: Infrared Measurement 151 Figure 121: Photograph of site Figure 122: Infrared Measurement Figure 123: Photograph of site Figure 124: Infrared Measurement 152 Figure 125: Infrared Measurement Figure 126: Infrared Measurement Figure 127: Photograph of site Figure 128: Infrared Measurement 153 Figure 129: Photograph of site Figure 130: Infrared Measurement Figure 131: Photograph of site Figure 132: Infrared Measurement 154 Figure 133: Photograph of site Figure 134: Infrared Measurement Illuminance readings were also taken for the sky at the various points where measurements were taken. The following are illuminance readings at those points along with photographs of the surface in question – taken with the GE Illuminance light meter described in chapter 5. These measurements are useful in comparing the type of surface material with the amount of light incident on it under overcast sky conditions. 155 Figure 135: Concrete floor of PSA Figure 136: Light meter reading Figure 137: Methods for calculating reflectance of a given surface 157 157 Stein, B. et al., 2005. Mechanical and Electrical Equipment for Buildings 10th ed., Wiley. Pp. 471 156 Figure 138: Concrete floor of PSA Figure 139: Light meter reading Figure 140: Concrete floor of PSA Figure 141: Light meter reading 157 Figure 142: Green patch in between DRB and PSA Figure 143: Light meter reading Figure 144: Brick tile pavement in between DRB and PSA Figure 145: Light meter reading 158 Figure 146: Concrete floor of PSA roof Figure 147: Concrete floor of PSA roof Figure 148: Concrete floor of PSA roof: point 1 Figure 149: Concrete floor of PSA roof: point 2 Figure 150: Concrete floor of PSA roof: point 3 Figure 151: Grass patch in front of DRB 159 Comparison of horizontal surfaces on the roof of Ray R. Irani Hall (MCB) along with their infrared photographs indicating the temperatures of the surfaces at a given time is done in the images below. The roof was mostly occupied by heavy mechanical equipment and there was barely enough space left to move around for inspection and repair if required. The roof was found to be coated with a cool roofing material called “Sarnafil” and there were black rubber mats placed on top of it to guide movement on the roof. The following images show how dirty the originally white “Sarnafil” coating was found to be and temperature of the roof and mechanical equipment installed on top of it. Figure 152: Roof of MCB Figure 153: Roof of MCB 160 Figure 154: Roof of MCB Figure 155: Infrared Photo Figure 156: Roof of MCB Figure 157: Infrared Photo 161 Figure 158: Roof of MCB Figure 159: Infrared Photo Figure 160: Roof of MCB Figure 161: Infrared Photo 162 Figure 162: Roof of MCB Figure 163: Infrared Photo Photographs of the roof surface and mechanical equipment thereon on the roof on Denny Research Center (DRB) along with comparison photographs with infrared photographs and luminance meter measurements with the type of surface indicated next to it. It is important to note here that a shaded roof is much better than a roof treated with coatings, such as a cool roof coating to begin with. The coating does help, but one should try to shade as much as possible. Figure 164: Roof of KAP Figure 165: Roof of KAP 163 Figure 166: DRB roof Figure 167: DRB roof Figure 168: Light meter reading Figure 169: 18% gray surface Figure 170: Pea gravel over roof of KAP Figure 171: Infrared photograph 164 Figure 172: Pea gravel over roof of KAP Figure 173: Infrared photograph Figure 174: Pea gravel over roof of KAP Figure 175: Infrared photograph 165 Figure 176: View from roof of KAP Figure 177: Infrared photograph Figure 178: View of MCB Figure 179: Infrared photograph 166 Figure 180: View of MCB Figure 181: Infrared photograph Figure 182: Seeley G. Mudd building Figure 183: Infrared photograph 167 Figure 184: Roof of DRB Figure 185: Infrared photograph Figure 186: Roof of DRB Figure 187: Infrared photograph 168 Figure 188: Roof of DRB Figure 189: Infrared photograph Figure 190: Roof of DRB Figure 191: Infrared photograph 169 Figure 192: Roof of DRB Figure 193: Infrared photograph Figure 194: Roof of DRB Figure 195: Infrared photograph 170 Figure 196: Tar felt roof surface of DRB Figure 197: Infrared photograph Figure 198: Roof of DRB Figure 199: Infrared photograph 171 Figure 200: Roof of DRB Figure 201: Infrared photograph The measurements depict how reflectance and emittance can be used to calculate the Solar Reflective Index (SRI) of these materials. The standard ASTM E 1980 (Standard Practice for Calculating Solar Reflectance Index of Horizontal and Low-Sloped Opaque Surfaces) was used to calculate the SRI from those two values. An Excel spreadsheet developed by Akbari 158 for this purpose was used. An alternate method of calculation is through the LEED NC v.2.2 templates 159 for the Sustainable Sites credits 7.1 and 7.2 that have the calculations in built in them. These spreadsheets and calculations are presented in Appendix I. This chapter presents field data collected for the site on the USC campus. This data is helpful in determining the response of different roofing and paving materials to the solar insolation incident on them. Measurements include those for luminance, illuminance, 158 http://coolcolors.lbl.gov. Accessed 2009.02.12 159 www.usgbc.org. Accessed 2008.10.22 172 surface temperature, air temperature, and relative humidity. The illuminance measurements were done in two parts: one measurement was for the sky illuminance and the other was for the illuminance measurement taken parallel to the surface under investigation. The luminance was similarly measured in two parts: one for the surface under investigation and the other for a reference surface with a known reflectance. A white sheet of paper (with reflectance 85%) and an 18% gray surface (with reflectance 18%) were used for this purpose as reference surfaces. This data is further analyzed through software calculations and output in the next chapter along with the analysis of the results in chapter 9. 173 CHAPTER EIGHT: SOFTWARE RESULTS 8.1 Ecotect Studies Ecotect is a software tool used to simulate building energy performance. It was used to simulate the different scenarios possible for analyzing the site for heat islands. The following figures are examples of a simple box and a simple rooftop shoeing how solar insolation affects different faces: Figure 202: Ecotect result for insolation on a simple cuboid for an entire day 174 Figure 203: Rooftop insolation calculation using example file from Ecotect 8.2 Ecotect Simulations for Site III on USC campus Site III on the USC campus was modeled in Ecotect for analysis. The model included all the buildings on site as well as the surrounding buildings that would affect them by shading. It was found that the parking lot in front of MCB was largely unshaded throughout the year from the surrounding buildings, especially during hours when the site received the maximum amount of solar insolation. This parking lot is paved with black asphalt and has a few trees on the periphery. The trees were also modeled for their effect, which was not found to be of any substantial difference. The rooftops of the buildings on site were physically examined and the surfaces were found to be: 175 1. KAP: Pea gravel 2. DRB: Tar and gravel 3. MCB: “Sarnafil” brand 160 cool roof coating 4. PSA: Exposed concrete 5. CWO: Sloped tile roof 6. CWT: Sloped tile roof 7. HRC: Sloped tile roof Apart from the roofs, the pavements and other horizontal surfaces were covered with the following materials - asphalt: new, asphalt: old, concrete pavements, grass beds, trees, shrubs, brick tiles, dirt, and painted curbs. The illuminance, luminance, surface temperature, and infrared thermographs were taken along with the recording of air temperature, relative humidity, illuminance and luminance of a reference surface at the points shown in Figure. 68 in Chapter 7. These surfaces when modeled in Ecotect, revealed the following results: 160 http://www.sarnafilus.com/index/roofing/products_rp/membranes_rp.htm. Accessed 2009.02.18 176 8.2.1 For December 21 at 12:00 pm at the point indicated (in the parking lot): Figure 204: Shadows and availability of direct radiation at the given point Figure 205: Sky view overlaid on the Sun Path diagram as seen from that point 177 Figure 206: Calculated solar stress (direct radiation) for the given point 178 8.2.2 For June 21 at 12:00 pm at the point indicated (lying in the parking lot): Figure 207: Shadows and availability of direct radiation at the given point Figure 208: Sky view overlaid on the Sun Path diagram as seen from that point 179 Figure 209: Calculated solar stress (direct radiation) for the given point 180 8.2.3 For March 21 at 12:00 pm at the point indicated (in the parking lot): Figure 210: Shadows and availability of direct radiation at the given point Figure 211: Sky view overlaid on the Sun Path diagram as seen from that point 181 Figure 212: Calculated solar stress (direct radiation) for the given point 182 8.2.4 For September 21 at 12:00 pm at the point indicated (in the parking lot): Figure 213: Shadows and availability of direct radiation at the given point Figure 214: Sky view overlaid on the Sun Path diagram as seen from that point 183 Figure 215: Calculated solar stress (direct radiation) for the given point 8.3 Ecotect simulations for an additional set of buildings on USC campus The changing effect of shadows at different times of the year and the incident solar radiation were also simulated. This was done on another set of buildings on the USC campus (Site IV). All calculations were done using the Los Angeles, CA weather file as supported by Autodesk Ecotect 2009. 184 8.3.1 Shadow Range Figure 216: Shadow range: plan Figure 217: Shadow range: 3D 185 8.3.2 Shadows on 07/01 at 3:00 pm: Figure 218: Simulated length of shadows 8.3.3 Shadow on 06/21 at 12:00 pm (noon): Figure 219: Simulated length of shadows 186 8.3.4 Shadow on 03/21 at 12:00 pm (noon): Figure 220: Simulated length of shadows 8.3.5 Shadow on 09/21 at 12:00 pm (noon): Figure 221: Simulated length of shadows 187 8.3.6 Shadow on 12/21 at 12:00 pm (noon): Figure 222: Simulated length of shadows 8.3.7 Shading Potential Figure 223: Input screen 188 Figure 224: Output screen 1 Figure 225: Output screen 2 189 Figure 226: output screen 3 - plan Figure 227: Output Screen 4 - Side View 190 Figure 228: Output Screen 5 - Front View 8.3.8 Solar Exposure on 07/01 (Single Day): Figure 229: Graph showing solar exposure 191 8.3.9 Solar Access Analysis 1: Incident Solar Radiation for Current Date and Time Figure 230: Input Screen Figure 231: Output Screen 192 8.3.10 Solar Access Analysis 2: Incident Solar Radiation for Specified Period (Summer and from 5:00 am to 6:00 pm) Figure 232: Input Screen Figure 233: Output Screen 193 8.3.11 Solar Access Analysis 2a: Incident Solar Radiation for Specified Period (Winter and from 5:00 am to 6:00 pm) Figure 234: Input Screen Figure 235: Output Screen 194 8.3.12 Solar Access Analysis 3: Shading, Overshadowing and Sunlight Hours for current date and time Figure 236: Input Screen Figure 237: Output Screen 195 8.3.13 Solar Access Analysis 4: Shading, Overshadowing and Sunlight Hours for Specified Period (Summer and from 5:00 am to 6:00 pm) Figure 238: Input Screen Figure 239: Output Screen 196 8.3.14 Solar Access Analysis 4a: Shading, Overshadowing and Sunlight Hours for Specified Period (Winter and from 5:00 am to 6:00 pm) Figure 240: Input Screen Figure 241: Output Screen 197 8.3.15 Solar Access Analysis 5: Sky Factor & Photo-synthetically Active Radiation (PAR) for current date and time Figure 242: Input Screen Figure 243: Output Screen 198 8.3.16 Solar Access Analysis 6: Sky Factor & Photo-synthetically Active Radiation (PAR) for Specified Period (Summer and from 5:00 am to 6:00 pm) Figure 244: Input Screen Figure 245: Output Screen 199 8.3.17 Solar Access Analysis 6a: Sky Factor & Photo-synthetically Active Radiation (PAR) for Specified Period (Winter and from 5:00 am to 6:00 pm) Figure 246: Input Screen Figure 247: Output Screen 200 8.3.18 Lighting Analysis 1: Natural Light Levels – Daylight Factors and Levels on 07/01 at 3:00 pm Figure 248: Input Screen Figure 249: Output Screen 201 8.3.19 Lighting Analysis 2: Natural Light Levels – Daylight Factors and Levels on 12/21 at 1:00 pm Figure 250: Input Screen Figure 251: Output Screen 202 8.3.20 Lighting Analysis 3: Natural Light Levels – Overall Daylight and Electric Light Levels on 12/21 at 1:00 pm Figure 252: Input Screen Figure 253: Output Screen 203 8.3.21 Lighting Analysis 4: Natural Light Levels – Overall Daylight and Electric Light Levels on 12/21 at 1:00 pm Figure 254: Input Screen Figure 255: Output Screen 204 In this chapter we saw the simulation results in Ecotect for the parameters that were not measured on site. This analysis provides vital clues to the type of simulation results that are desirable for a heat island analysis. The results of this simulation, along with the results of field measurements are analyzed in the next chapter to provide recommendations as necessary. 205 CHAPTER NINE: CONCLUSIONS 9.1 Field Studies There are many factors that we must know to make a first step in analyzing the problem and understanding the set of criteria that must be present for a simulation program to be useful. The first of those factors is the determination of the incident solar radiation (insolation). The amount of solar insolation available in an area depends upon the geographic location of the building and the amount of solar radiation available at that time of the day and year. Theoretical available insolation can be derived from first principles, quarried from data available on solar radiation sky maps generated by the government, or even pulled from TMY weather data available for thousands of locations collected over many years. The local insolation also heavily depends on the exact site being studied. There may be existing buildings, large signs, monuments, and other obstructions surrounding a building site that will affect the amount of incident solar radiation that directly hits the site at different times of the day and year. The site may be partially or fully shaded by these external elements. These variables are influenced by the prevalent weather – sunny, rainy, partly cloudy etc. Therefore, one should be able to visualize the project in a larger model of the neighboring urban environment for analysis. Insolation and site geometry determine the overall availability of solar radiation. The materials of the buildings, paving, obstructions, etc. influence how it is used. For example, if a roof is dark in color, it absorbs much more heat than if it is light in color. 206 Therefore, it is important to consider the Solar Reflectance Index (SRI) of the surface (e.g. building roof or sidewalk), which can be calculated from the reflectance and emittance for that surface. For new buildings, an architect can greatly influence the selection of materials that have the highest albedo and emittance values to be used for successfully reflecting sunlight. But for existing buildings, it is important to determine the albedo of the surface under investigation. It may not be possible to test each and every surface that already exists in the surrounding built environment physically. One has to usually rely on approximation techniques for such situations. For the purposes of this study, the author calculated the SRI of different surface materials in order to eventually determine their effect on heating up the external environment. Field measurements were taken on a site on the USC campus. Although far from being ideal, this location had some advantages, mainly convenience, that led to it being chosen. Field measurements were taken with a digital infrared camera; digital environment meter that measures air temperature, relative humidity, and illuminance; luminance meter; light meter; and infrared temperature gun. Not all of the measurements turned out to be useful. Several types of surfaces were included in the field measurements: asphalt, concrete, brick tile paving, metal, grass and shrubs, trees and other vegetation, soil in different conditions, pea and gravel surfaces, surfaces with a cool roof coating, and surfaces with tar and gravel coating. An example of infrared comparison of the surfaces with the actual photograph is presented in Fig. 256. 207 The light colored pea and gravel roof was found to be at approx. 46-56°F as compared to the dark colored brick tile façade that is at approx. 90-107°F. Such data is helpful in determining the response of different roofing and paving materials to the solar insolation hitting them even on an overcast day. Figure 256: Pea gravel roof (MCB): Temperatures range between 46-56 °F for the roof and between 90-107 °F for the dark colored brick tile façade. Figure 257: Asphalt and Concrete Paving (Parking Lot 6 in front of MCB): Temperature of asphalt paving is approx. 108 °F and of concrete paving is approx. 96 °F. 208 Figure 258: Tar and gravel roof (DRB): Temperature of roof is between approx. 50-57 °F. Figure 259: Brick tile and concrete pavements: Temperatures range from 80-84 °F for the brick tiles and approx. 74 °F for the concrete. However, under shade both are between 64-67 °F. The heating up of paved surfaces depends on their material properties as well as their shading from on-site elements. For example, in Fig. 257 we see that for the same unshaded outside conditions, the temperature of the asphalt pavement (approx. 108°F) is much higher than the adjacent concrete pavement (approx. 96°F). However, in Fig. 4 we can see how shading makes a difference to surface temperatures. Under unshaded conditions, the brick tile pavement is at approx. 80-84°F as compared to the concrete 209 pavement which is at approx. 74°F. However under shade, the temperature drops to about 64-67°F for both surfaces. The illuminance measurements were done in two parts: one measurement was for the sky illuminance and the other was for the illuminance measurement taken parallel to the surface under investigation. The luminance was similarly measured in two parts: one for the surface under investigation and the other for a reference surface with a known reflectance. The reflectance of the test surface was obtained by the equation: [Luminance of known surface/Luminance of test surface] = [Reflectance of known surface/Reflectance of test surface]. The emittance values of the surface materials were referenced from standard tables. The data depicts how reflectance and emittance values can be measured on site. These can now be used to calculate the Solar Reflective Index (SRI) for the surface materials. The ASTM E 1980 standard (Standard Practice for Calculating Solar Reflectance Index of Horizontal and Low-Sloped Opaque Surfaces) was used to calculate the SRI from those two values. An Excel spreadsheet developed by Akbari 161 for this purpose was used. An alternate method of calculation is through the LEED® NC v.2.2 templates 162 for the Sustainable Sites credits 7.1 and 7.2 for heat island analysis that have the calculations built into them. 161 http://coolcolors.lbl.gov/assets/docs/SRI%20Calculator/SRI-calc10.xls. Accessed. 2009.02.12 162 www.usgbc.org. Accessed 2008.10.22 210 Another important site consideration is vegetation. While simulating the benefits of vegetation on the temperature of the surface under question (e.g. pavements or building facades), in addition to its SRI, it becomes important to factor in the effect of shade and cooling provided by vegetation around it. This component has a greater dimension to it as vegetation is temporally dynamic, for example, leaves may grow and disperse seasonally, and a tree may grow substantially over time. However, there are marked differences in the surface temperatures of vegetated surfaces as compared to paved surfaces. This is one of the reasons why trees and vegetation are desirable in an urban environment full of paved surfaces. Consider a patch of grass exposed to direct sunlight in Fig. 260. We find that its temperature is between 43-58°F. Compare this to the temperatures of paved surfaces that we saw in Fig. 257, which range from 96-113°F. Both measurements were taken at the same date and time and at adjoining locations. Combining shade and vegetation is also an effective strategy for reducing surface temperatures. Consider a patch of grass shaded by a tree in Fig. 261, which is at approx. 50-55°F as compared to the brick tile paving in the background, which is at approx. 80-82°F. 211 Figure 260: Sunlit patch of grass (outside DRB): Temperatures range from 43-58 °F for the grass. Compare with temperature of asphalt paving that is approx. 108 °F (as seen earlier). Figure 261: Shaded patch of grass (outside PSA): Temperatures range from 50-55 °F for the grass and between 80-82 °F for the brick tile paving in the background. The type and species of plants is important as different varieties have varying characteristics. Therefore, it is necessary to record the exact type of vegetation in the area of inquiry. In addition to the SRI of a planted area and the shading potential of the 212 vegetation on neighboring areas, evapotranspiration also plays a role in cooling the environment. 163, 164 This is however, outside the scope of this study. 9.2 Calculations for Solar Reflectance Index (SRI) To determine the Solar Reflectance Index (SRI) of a test surface, we need the: • Emittance, and • Reflectance for the surface. 163 Akbari, H. et al. eds., 1992. Cooling Our Communities: A Guidebook on Tree Planting and Light- Colored Surfacing, U.S. Environmental Protection Agency, Office of Policy Analysis, Climate Change Division. 164 Wong, N.H. & Chen, Y., 2008. Tropical Urban Heat Islands: Climate, buildings and greenery 1st ed., Taylor & Francis. 213 Table 5: Albedos, Emissivities, and Thermal Conductivities of elements often found in the landscape 165 165 Brown, R.D. & Gillespie, T.J., 1995. Microclimatic Landscape Design: Creating Thermal Comfort and Energy Efficiency, Wiley. Pp. 49 214 Table 6: Radiative properties of natural materials 166 166 Sellers (1965), List (1966), Paterson (1969) and Monteith (1973). as quoted in Oke, T.R., 1978. Boundary Layer Climates 1st ed., Routledge. 215 Table 7: Radiative properties of typical urban materials and areas 167 Example Calculation: The test surface here is the Tar and Gravel roof surface of Denny Research Center (DRB) building on USC Campus. The emittance values were taken from standard tables 168 Therefore, the emittance of a Tar and Gravel roof = 0.92 167 Threlkeld (1962); Sellers (1965); van Straaten (1967); Oke (1974) as quoted in Oke, T.R., 1978. Boundary Layer Climates 1st ed., Routledge. Pp. 247 168 Oke, T.R., 1978. Boundary Layer Climates 1st ed., Routledge. Pp. 247 216 To determine the reflectance of a test surface, let’s put the values measured on site in the following equation: Measured values: • Luminance of known surface = 60.1 foot-Lamberts • Luminance of test surface = 143 foot-Lamberts • Reflectance of known surface = 0.18 (using an 18% gray card) Therefore, reflectance of test surface (Tar & Gravel) = 0.4283 or 42.83% The SRI value is then calculated using ASTM standard E 1980 (Standard Practice for Calculating Solar Reflectance Index of Horizontal and Low-Sloped Opaque Surfaces). For this calculation, two options were used: 1. Excel calculator developed by Lawrence Berkeley National Labs. 169 2. LEED® (NC v.2.2) templates for Sustainable Sites credits 7.1 and 7.2. From reflectance and emittance, SRI = 50 169 http://coolcolors.lbl.gov/assets/docs/SRI%20Calculator/SRI-calc10.xls. Accessed. 2009.02.12 217 Note: LEED® (NC v.2.2) requires an SRI of 78 for low sloped roofs and an SRI of 29 for steep sloped roofs for obtaining credits SS 7.1 and 7.2. ADDITIONAL MEASUREMENTS: The measurements were taken on February 12, 2009 at 5:04 pm under the following conditions (also measured): • Outside air temperature = 60.6 °F • Surface temperature = 51 °F • Relative Humidity = 44.8% • Sky Illuminance = 8130 lux (755.30 fc) on a partly cloudy day Table 8: Table showing the final results of calculations based on field measurements FIELD DATA MEASUREMENTS University of Southern California Campus Site Point Air Temperature (°F) Surface Type Material Emissivity Reflectance (%) SRI A - Parking Lot Asphalt 0.95 24.14 27 B - Car on Parking Lot Metal 0.2 44.74 16 218 C - Parking Spot Asphalt - old 0.95 22.46 24 D - Parking Aisle - Not Shaded Asphalt - new 0.95 21.25 23 E - Brick Tile Paving Brick Tile 0.9 22.57 22 F - Shaded Parking Spot Asphalt 0.95 6.82 5 G - Wet grass in front of DBR Grass 0.95 2.55 0 H - Wet grass in sunlight (in front of DBR) Grass 0.95 30.06 34 1 72.6 PSA Concrete 0.91 27.99 30 2 67.2 PSA Concrete 0.88 27.16 27 3 69.5 PSA Concrete 0.88 29.56 30 4 68.4 PSA Concrete 0.88 25.19 25 219 5 68.6 Grass in front of DBR Grass 0.95 4.68 2 6 68.6 Pavement in front of DBR Brick Tiles 0.9 10.65 7 7 70.9 Point 2 Concrete 0.88 29.80 31 8 67.7 Point 3 Concrete 0.88 26.17 26 9 66.9 Point 4 Concrete 0.88 26.44 26 10 67.1 Point 1 Concrete 0.88 24.23 23 11 66.1 Grassy area abutting PSA Grass 0.98 5.46 5 12 66.1 Pavement in between PSA and DBR Brick Tiles 0.9 12.78 10 13 72.2 Rooftop - MCB “Sarnafil” Membrane 0.92 64.68 79 14 75.7 Rooftop - KAP Pea Gravel 0.9 14.01 11 220 15 65.6 Rooftop - KAP Pea Gravel 0.9 23.77 24 16 62.7 Rooftop - KAP Pea Gravel 0.9 27.98 29 17 62.5 Rooftop - KAP Pea Gravel 0.9 - - 18 63.2 Rooftop - DBR Tar and gravel 0.92 28.67 31 19 60.6 Rooftop - DBR Tar and gravel 0.92 42.83 50 20 60.6 Rooftop - DBR Tar and gravel 0.92 37.54 43 9.3 Data Analysis & Recommendations Based on field measurements, calculations and simulations, it was found that the parking lot (with asphalt paving) in front of MCB would be largely unshaded throughout the year. To reduce build up of heat and increase ground water recharge, asphalt paving can be replaced with perforated concrete grid pavers during the next scheduled maintenance. 221 The rooftops of the buildings on site were physically examined and the surfaces were found to be: • KAP: Pea gravel • DRB: Tar and gravel • MCB: Cool-roof coating (“Sarnafil”) – this one is OK (calculated SRI = 79; specified SRI > 104). The reason SRI is lower than specifications is due to dirt accumulation. • PSA: Exposed concrete • CWO: Sloped tile roof • CWT: Sloped tile roof • HRC: Sloped tile roof Since all these roofs are either flat or low sloped roofs, they could be converted to cool- roofs (with a min. SRI = 78) as recommended by LEED® NC v.2.2 or to green roofs during the course of their next scheduled maintenance. As can be seen from the example of MCB, even though a cool roofing membrane is installed on the roof, the effective SRI is much lower than what is specified by the manufacturer. The main reason for this is the accumulation of dirt and grease from the atmosphere and the mechanical equipment that is housed on top of that roof. This emphasizes the importance of self cleanliness of these cool roofing materials. The “Sarnafil” membrane being white in color attracts dirt on the roof of MCB. It is also important to take into account the rainfall characteristics of an area before choosing a 222 particular product. So even though the product is self cleansing, it may be so at minimum rainfall expectancy rates in the area. It seems the product installed does not match the annual precipitation rates in Los Angeles, which can be pretty low. Therefore, while selecting the cool roofing or paving materials, it is important to choose materials with self cleansing characteristics that are low in maintenance and are able to deliver higher performance. 9.4 Results from software analysis The building site needs to be analyzed for the incident solar radiation that is available at that geographic location. Here, the use of software tools like Ecotect becomes important as it allows us to simulate the solar path throughout the year and predict the results immediately rather than wait for an entire year to take field measurements. Analysis for the site on USC campus revealed that the roofs of the buildings became hot during the day and the surface temperature was dependent on the roofing material. This is also true for other horizontal surfaces such as parking lot 6, the grassy areas between PSA and DRB, the brick tile paving, concrete paving and so on. All these surfaces absorbed heat based on the surface characteristics that can be explained through their solar reflectance index (SRI), which incorporates the reflectance and emittance characteristics as well. 223 The solar analysis through the software showed us in particular the effect of mutual shading from buildings, trees and vegetation and other objects in the periphery of the site. This is important as elements in shade have a considerably low surface temperature. Therefore an analysis of the shading patterns throughout the day, season and year becomes important to see the extents of shadows and the percentage of time that they are present. It is logical to conclude that areas that are mostly in shadow throughout the year would absorb lesser heat as compared to those that are relatively less in shadows, which in turn would absorb lesser heat than those that are never in shade. Therefore, a shadow plot was simulated to measure the extents and darkness of shadows for the different horizontal surfaces in Ecotect. When overlaid with the insolation plot, this would reveal the heating potential of specific areas of the site. 9.5 Conclusions Conducting a heat island analysis has several dimensions based on the depth of the analysis. The ability to analyze a model of the proposed design in a simulation program can aid the mitigation process as it enables the designers to address the problem at the drawing board itself. However as this research progressed, it was found that solely conducting a software simulation is not sufficient in doing a comprehensive study, especially for existing buildings. Therefore it is a combination of field studies and software simulation that need to be used to address the problem. This reinforces the hypothesis that we began with, viz. urban scale computer modeling for solar insolation 224 can aid in learning about mitigation of the heat island effect through albedo modification and increased vegetation, among other solutions. The findings also demonstrate that a heat island analysis is possible for the benefit of designers. They can use this analysis for informing their design effectively. For conducting a sample heat island analysis, field data was collected from a site on the USC campus. This was used to determine the reflectance, emittance and thereafter Solar Reflectance Index (SRI) of the materials on horizontal surfaces on the site. The detailed measurements are presented in Appendix I of this thesis and samples of the field data are presented in chapter 6 along with their detailed analysis and interpretations in chapter 9. This site was also modeled in Ecotect and analyzed for the incoming solar radiation effects, shadows and surface properties. The results of these software modeling exercises are presented in chapter 8. These two exercises when combined helped to study the site in theoretical as well as practical ways. 9.6 Geospatial Decision-making The ability to conduct a heat island simulation at the design stage is the first step towards mitigating it as designers have maximum control over a project at this stage. Previous attempts at studying heat islands have overlooked the need for designers to have an integrated tool for the assessment of the effect in order for them to do something about it. The analysis techniques available currently are scattered and require the use of multiple 225 platforms for conducting the analysis. Moreover, this is often understood only by specialists in the field who are then able to do the complex set of analyses. The idea of developing an extension to GeoDec stems from this fact and endeavors to produce a simplified tool that can be used by designers to conduct a preliminary heat island analysis for their design projects, just as they are currently able to do an analysis for the internal performance of a building. It is important to note that since a building level analysis is possible to be conducted at the designer level in a relatively easy manner, it is required by codes such as California Title 24 and independent rating systems such as LEED®. This is not to say that conducting a heat island analysis in GeoDec will guarantee its inclusion as a mandatory code compliance requirement, but it definitely paves the way for it. This is a much more effective way of doing something about the issue of heat islands than to document it and study it in isolated labs or to give generalized recommendations about the mitigation measures. A software simulation will help tailor the recommendations in a cost effective manner for incorporation into the design documents and successful implementation in the field. GeoDec can deliver that ability. It is currently being developed towards that. GeoDec is not nearly complete with regard to these extensions. But when finished, it is hoped that designers can benefit from heat island analysis for surfaces such as building rooftops, façades, pavements, driveways, parking lots, etc. Such analysis can also help them to: 226 7. Test insolation and SRI effects on different surfaces in their design and look for options to reduce heat gain. 8. Test and select appropriate glazing type for handling the incoming solar radiation on a particular façade. 9. Design shading devices. 10. Determine the placement of solar photovoltaic panels. 11. Select vegetation for planting adjacent to built areas. 12. Select appropriate cool/green roofing areas. For example, if the roof of a building is totally shaded by neighbouring buildings, the owner can protect his building by a relatively low cost measure such as a cool roof. If however the roof is gaining a high amount of solar radiation, the owner can invest in strategies such as a green roof to reduce internal heat gain and increase the life of the structure. 13. For horizontal surfaces such as roads and pavements, heat island analysis will help city managers to take specific measures for improving them. Big parking lots that are usually covered with asphalt have a large amount of heat gain. Such surfaces also do not let any rainwater to permeate through them - leading to increased temperatures and surface runoffs. Heat island analysis can help parking lot owners to identify problem areas and resurface them with perforated concrete grid pavers or similar materials during the next scheduled maintenance. Such measures introduce pleasing softscape in the community and lower air temperatures, while promoting rainwater percolation to the ground. 227 The combined effect of the different considerations identified above allows us to get an accurate picture of the conditions on site due to an existing or proposed design of the built form, experiment with the different options, and achieve an acceptable result that would increase the life of the building, lower the energy consumption, and contribute to reducing the heat island. For example, if a large building’s roof is partially shaded by surrounding buildings and there is still a large area that is exposed to the sun, one can use a mix of strategies including selecting beneficial locations for the installation of solar photovoltaic panels, wind turbines, green roofs, cool roofs, etc. after leaving area required for building services, amenities and usable rooftop area for occupants’ use. In this chapter we looked at the interpretations of the data collected in the field and the results obtained from software simulation. This has given us a basis for recommendations for improvement to surfaces on USC campus site. This prototype analysis can be extended to other sites and the results can be studied in the framework specified in this thesis. 228 CHAPTER TEN: FUTURE WORK Urban heat island research spans different domains and disciplines, many of which can be seen by the work already been done on it in different parts of the world. Chapter 2 presented a literature review along with a list of researching bodies and individuals that are studying different aspects of it. For the purpose of our analysis, we are concentrating on the usefulness of heat island analysis for its mitigation as can be used by architects and city managers. A study of the United States Green Building Council’s Leadership in Energy and Environmental Design (LEED) rating system was presented in chapter 9. The use and importance of software analysis tools for analysis was discussed in chapter 1 itself. The purpose of this thesis is to identify the characteristics needed for analysis in this framework and to inform the development of a software platform to successfully do the analysis. GeoDec was chosen on the basis of its merits described in chapter 4. Through field measurements and software analysis using other software tools, a framework for the development of GeoDec was developed, which is already being programmed for achieving these capabilities. However, much more can be done to enhance its analysis capabilities. This chapter presents the specific functionalities that can be incorporated within GeoDec to make it an efficient tool for heat island analysis. There are many logical extensions to the work being done for the enhancement of GeoDec. The following are the upcoming steps that are hoped to be incorporated into GeoDec at a later date: 229 10.1 Incorporate the idea of a “building” While it is important to study the individual horizontal surfaces for the purpose of a heat island analysis, a building model is composed of other surfaces as well. These surfaces should also be editable and definable just like the exposed horizontal surfaces in the model. This becomes useful as the complexity of the model and analysis increases. As we are able to study more than just a single building and groups of buildings together as a whole in GeoDec, the effects of vertical surfaces can also be taken into account to get a more accurate analysis. Therefore the individual surfaces should all be editable and definable. Once this is achieved, one should be able to select the whole building as well in one shot. This can be achieved by defining all surfaces of the building to be on a separate layer and creating multiple layers in the model for multiple buildings. This idea is achieved in Ecotect by creating “zones”. All horizontal and vertical surfaces for a building are to lie on a single zone or layer (holding discrete editable values for each surface at the same time), making it possible to select the whole building as a single entity for analysis in an urban environment. This is important as it allows the building to behave as a single entity. For example, when conducting a CFD simulation, it becomes useful to consider the whole building as a single object that deflects the wind around it. 230 10.2 Attach material data attributes Program the ability to attach attributes such as material data to the surfaces in the model. The VRML files imported by GeoDec help create the geometry of the building. However, in order to conduct analysis, it is important to associate the different surfaces with associated properties as would be the case for a building in the real physical world. Thus a capability to store or connect to a database of material properties is necessary for any analysis to inform the real world buildings. 10.3 Library of materials Create a library of materials in GeoDec and store their reflectance and emittance values in a database with them. When a user selects a material, the corresponding reflectance and emittance values should get applied to the model. When studying buildings in the urban environment that have surfaces composed of different materials, we need the same materials simulated in the simulation program where we are simulating the building itself. So, a library of building materials is justified. When a user defines a building in the software, he should be able to select the right material from the library and apply it to the surface under question. This application of the material to the building model should apply at least the emittance and reflectance values to the surface – for heat island analysis. 231 For creating this library of materials, additional field measurements may be required to test existing buildings where the surface characteristics (especially reflectance) may be different due to weathering conditions and would require accurate field data for simulation and getting accurate results. 10.4 Solar analysis Analyzing the built form for its performance under the sun is one of the most important objectives of a heat island analysis. This aspect needs to be studied in detail. While this thesis presents solar analysis in other software packages, GeoDec would also have to incorporate these into its programming setup. The incident solar radiation has direct, diffuse and a global horizontal radiation components. These can be found in the weather data files for any location. Using these, one must calculate the insolation available at the different surfaces in an urban model. There are manual calculation equations that can be used for verifying the calculations made by the software program as well. Therefore, calculate insolation values either from first principles, simplified calculations, sky map data, or TMY weather data (solar availability direct, diffuse, and total insolation). 232 10.5 Add visualization tools for temporal viewing Often times the ability to do calculations in a software program and the ability to present it in graphically pleasing ways are two different aspects. However, one would agree that for non-technical personnel it can be daunting to imagine the effects of numerical calculations without any graphical aids. To visualize the reflectance and emittance values, GeoDec could break down each surface into a grid or create an overlay that can be divided into a grid. This grid will visually and numerically display insolation, surface temperature, and other similar characteristics such as SRI and albedo as well. The data is to be displayed as colored boxes with each color representing a range of values on a graphical scale accompanying each grid analysis. This is achieved to some extent in Ecotect and can be customized for our purposes in GeoDec to display additional characteristics. 10.6 Importing weather data GeoDec should be able to import and then help users visualize other TMY weather data including wind (direction and speed) and rainfall and humidity data. This is the most comprehensive method for conducting an accurate analysis for any part of the globe as these weather data files are available for free download for almost any location. 233 Also, the data contained therein is collected over several years at those locations and is presented in a manner that most accurately represents the climate characteristics of the area. Importing this data into GeoDec can amplify the accuracy levels for real world applications. This is the first step in utilizing this data for analysis within the model. The different categories of data identified above will be useful for several different aspects of the heat island analysis. For example, the wind direction and speed data can facilitate the CFD simulation of a larger urban area so that the wind effects near a particular site can be accurately predicted based upon the deflections and speed changes due to the geometry of the urban fabric and formation of local pockets. 10.7 Photovoltaics Determine placement of solar photovoltaic panels on rooftops and on top of parking structure roofs based on available insolation and types of PV panels available in the market. This is one of the most direct useful outcomes of this analysis. We are already studying the amount of solar radiation incident on different surfaces in an urban model. We also know when and which parts of the site are going to be in shade along with the most effective areas that are exposed to the sun. While this identifies the playing field for testing of strategies for heat island mitigation, it also tells us the boundary area within which solar photovoltaic panels will be most productive. 234 Therefore, this identification of the boundary can be used for installing the PV panels that one desires. A basic PV analysis in supplementary software tools such as Solar Advisor Model (SAM) 170 or the web based California Solar Initiative Incentive Calculator 171 can be used to select the exact product to be installed. A cost-benefit analysis is available within the programs and a host of utility incentives (see the Database of State Incentives for Renewables and Efficiency - DSIRE 172 ) support finance for such installations. At this point, the designer should be able to make rough comparisons between possible solutions. GeoDec can be made a more sophisticated heat model by adding other extensions to it, including: 10.8 Analyze time lag due to differences in thermal mass For example, for a selected time period, the insolation available at that location will hit the model surfaces within the software model – some will be reflected and a part of the heat energy will be absorbed. This will get emitted after a time lag according to the emittance properties of the surfaces. In addition, this emitted heat during the specified time period will affect the external environment. From this one can graph the rate of heating and calculate the total heat contribution of the model surface. Here a simple list 170 https://www.nrel.gov/analysis/sam/ Accessed 2009.03.22 171 http://www.csi-epbb.com/ Accessed 2009.03.22 172 http://www.dsireusa.org/ Accessed 2009.03.22 235 or database of building component assemblies can be helpful to select standard wall and roof constructions. This should however be editable, allowing the user to define custom assemblies. 10.9 Internal load calculations Include calculations for energy losses from buildings based on their usage and associated internal loads. For this, one might use satellite thermal imaging data being independently studied for heat island analysis into the GeoDec model or acquire this information from the building information model for the project, if available. When studying an urban area, it can be very difficult to monitor the energy performance of each and every household and detect the amount of losses due to construction leakages to estimate the heat being emitted by any set of buildings to the external environment. A set of sophisticated tools involving infrared satellite imagery can be really helpful here. An infrared photograph taken from a satellite at different times of the day and year can visually and numerically demonstrate the amount of heat being generated by the set of buildings that gets leaked out to the external environment. This data will be more reliable and measurable for analysis in the urban environment. Using these data sets one can identify the defaulting buildings and surfaces and take action for their mitigation. This method, coupled with remote sensing, is being independently used to study heat islands – identifying how urban areas are hotter than rural areas. 236 GeoDec has the ability to work with satellite imagery and such images should simply become overlays for the model being analyzed. This will greatly enhance the graphical abilities and give a regional perspective to the analysis, wherein field data is used hand- in-hand with the software tool to predict results. 10.10 CFD simulation CFD simulation using wind speed and direction data as identified above. Although vegetation is crucial to this study, it has not yet been incorporated into the study except with regard to the calculation of solar reflection indices. Here is a rough idea of what might be necessary to incorporate calculations for determining the cooling effects due to vegetation into GeoDec: 10.11 Create a library of vegetation types for analysis Create a library of trees and other forms of vegetation. This would have to include at least the following information: a. suitability for a given area (for example, list native plants for a given area) b. shape and transparency (leaf area index) seasonally; rate of growth 237 c. water requirements d. evapotranspiration rate (this is a complex calculation that includes many variables including plant type, rainfall, relative humidity, dew point temperature, watering requirements, etc.) This information can be used for calculating the effects of vegetation using the formulae identified in chapter 2. Programming the formulae inside of GeoDec and extracting information from the library of information identified above, the cooling effects of vegetation can be more accurately simulated and studied. This will allow for potential recommendations for plant species types and their requirements for the given climate according to not only the native plant species available, but also the water budget required for their maintenance. 10.12 Other functionalities and extensions Since GeoDec can be simultaneously adapted for multiple visualization and analysis functions, one of the applications that utilize the information above is the study of building generated glare. Most of the components for this analysis is closely related to the luminance, illuminance, reflectance, transmittance and other properties that are studied for heat island analysis. Using the contrast between light levels incident on urban surfaces, one can predict the amount of glare caused due to them. This can be a helpful extension to GeoDec as urban glare is a well documented phenomenon that needs mitigation. 238 As an example, the external surfaces of the Walt Disney Concert Hall in downtown Los Angeles had to be treated due to the high amount of glare caused due to them 173 that led to traffic hazards and in some cases concentrated solar power was reported to cause melting of plastic dustbins and similar objects. 10.13 Final Thoughts Heat islands are an important factor to consider in the energy budget of our urban built environment. They have been studied over many years by different scientists all over the world. With fast depleting natural resources, there is an urgent need to step up efforts and empower the people who can actually make a difference. Software tools such as GeoDec can greatly help architects, designers, city managers and other specialists to simulate and quantify the effects of the heat island effect and apply the research principles to actual building and urban projects. This thesis is an effort to identify the different factors required for a detailed analysis and to bring together these components through a common platform – laying a roadmap for the development of a software tool such as GeoDec. With accurate analysis available, it is hoped that the harmful effects of urban heat islands would be mitigated by informed and collective actions of individuals. 173 Schiler, M. & Valmont, E., 2005. Microclimatic Impact: Glare around the Walt Disney Concert Hall. In Proceedings of the Solar World Congress 2005 Joint American Solar Energy Society. Orlando. 239 BIBLIOGRAPHY 1. 2008. FLIR Systems - User's Manual: FLIR i5, Extech Instruments (A FLIR Company). Available at: http://www.extech.com. 2. Akbari, H., Energy Saving Potentials and Air Quality Benefits of Urban Heat Island Mitigation. Available at: http://www.osti.gov/bridge/purl.cover.jsp;jsessionid=C2891B392A0734398C81EB32 3FC12EDF?purl=/860475-UlHWIq/ [Accessed February 26, 2009]. 3. Akbari, H. et al. eds., 1992. Cooling Our Communities: A Guidebook on Tree Planting and Light-Colored Surfacing, U.S. Environmental Protection Agency, Office of Policy Analysis, Climate Change Division. 4. Akbari, H., Konopacki, S. & Parker, D., 2000. CUpdates on Revision to ASHRAE Standard 90.2: Including Roof Reflectivity for Residential Buildings, Pacific Grove, CA: Lawrence Berkeley National Laboratory, Berkeley, CA. Available at: http://eetd.lbl.gov/HeatIsland/RECPUB.html [Accessed August 29, 2008]. 5. Akbari, H., Pomerantz, M. & Taha, H., 2001. Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas. Solar Energy, 70(3), 295-310. 6. Akbari, H., Rose, L. & Taha, H., Charaterizing the Fabric of the Urban Environment: A Case Study of Sacramento, CA, Lawrence Berkeley National Laboratory, Berkeley, CA. Available at: http://eetd.lbl.gov/HeatIsland/RECPUB.html [Accessed August 29, 2008]. 7. Aron, R.H., Todhunter, P. & Geiger, R., 2003. The Climate Near the Ground 6th ed., Rowman & Littlefield Publishers, Inc. 8. ASHRAE, 2005. 2005 ASHRAE HANDBOOK : Fundamentals : Inch-Pound Edition, American Society of Heating Refrigerating and Air-conditioning Engineers, Inc. 9. Bolstad, P., 2002. GIS Fundamentals: A First Text on Geographic Information Systems First., White Bear Lake, Minnesota: Eider Press. Available at: http://bolstad.gis.umn.edu/GISbook.html. 10. Browne, N. & Keeley, S.M., 2006. Asking the Right Questions: A Guide to Critical Thinking 8th ed., Prentice Hall. 11. Brown, R.D. & Gillespie, T.J., 1995. Microclimatic Landscape Design: Creating Thermal Comfort and Energy Efficiency, Wiley. 240 12. Council, U.G.B., 2006. New Construction & Major Renovation Reference Guide 2nd ed. 13. DeWalle, D.R., Heilser, G.M. & Jacobs, R.E., 1983. Forest home sites influence heating and cooling energy. Journal of Forestry, 84(3), 84-88. 14. Eastman, C. et al., 2008. BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors, Wiley. 15. Geiger, R., Aron, R.H. & Todhunter, P., 2003. The Climate Near the Ground 6th ed., Rowman & Littlefield Publishers. 16. Goodridge, J., 1987. Population and temperature trends in California. In Proceedings of the Pacific Climate Workshop. Pacific Grove CA. 17. Goodridge, J., 1989. Air temperature trends in California, 1916 to 1987. 18. Green, S., 1993. Radiation Balance, Transpiration and Photosynthesis of an Isolated Tree. Agricultural and Forest Meteorology, 64, 201-221. 19. Gregory McPherson, E. ed., 1984. Energy-conserving site design, American Society of Landscape Architects. 20. Gorsevski, V. et al., Air Pollution Prevention Through Urban Heat Island Mitigation: An Update on the Urban Heat Island Pilot Project. 21. Huang, Y., Akbari, H. & Taha, H., 1990. The Wind-Shielding and Shading Effects of Trees on Residential Heating and Cooling Requirements, Berkeley, CA: Lawrence Berkeley National Laboratory. 22. Huber, A. et al., 2006. Pollution Dispersion in Urban Landscapes. Fluent News (Special Edition) Applied Computational Fluid Dynamics - The Business Benefits of Flow Simulation: manufacturing, healthcare, environment, sports. , Vol XV(2). 23. Irrisoft, Inc., Rain Bird® ET Manager™ Scheduler Software, Tucson, AZ: Rain Bird Corporation. 24. Janis, R.R. & Tao, W.K.Y., 2008. Mechanical & Electrical Systems in Buildings 4th ed., Prentice Hall. 25. Jensen, R., Gatrell, J. & McLean, D. eds., 2007. Geo-Spatial Technologies in Urban Environments: Policy, Practice, and Pixels Second., New York: Springer-Verlag Berlin Heidelberg. 241 26. Jensen, M.E. & Haise, H.R., 1963. Estimating evapotranspiration from solar radiation. Journal of the Irrigation and Drainage Division (Proceedings of the American Society of Civil Engineers), 89, 15-41. 27. Jones, H.G., 1992. Plants and Microclimate: A Quantitative Approach to Environmental Plant Physiology 2nd ed., Cambridge University Press. 28. Kjelgren, R. & Montague, T., 1998. Urban Tree Transpiration over Turf and Asphalt Surfaces. Atmospheric Environment, 32(1), 35-41. 29. Knowles, R.L., 1981. Sun Rhythm Form, MIT. 30. Konopacki, S. et al., 1997. Cooling Energy Savings Potential of Light-colored Roofs for Residential and Commercial Buildings in 11 U.S. Metropolitan Areas, Berkeley, CA: Lawrence Berkeley National Laboratory. 31. Kreith, F. & Kreider, J.F., 1978. Principles of Solar Engineering, Mcgraw-Hill (Tx). 32. Krygiel, E. & Nies, B., 2008. Green BIM: Successful Sustainable Design with Building Information Modeling, Sybex. 33. Landsberg, J. & Powell, D., 1973. Surface Exchange Characteristics of Leaves Subject to Mutual Interference. Agricultural Meteorology, 13, 169-184. 34. Lechner, N., 2008. Heating, Cooling, Lighting: Sustainable Design Methods for Architects 3rd ed., Wiley. 35. Lowry, W., 1988. Atmospheric Ecology for Designers and Planners, New York: Van Nostrand Reinhold. 36. Ludwig, F.L., 1970. Urban temperature fields in urban climates, 37. Lunde, P.J., 1980. Solar Thermal Engineering: Space Heating and Hot Water Systems, John Wiley & Sons Inc. 38. McPherson, E.G. et al., 2005. Municipal Forest Benefits and Costs in Five US Cities. Journal of Forestry, 103(8), 411-416. 39. McPherson, E.G., Herrington, L.P. & Heisler, G.M., 1988. Impacts of vegetation on residential heating and cooling. Energy and Buildings, 12, 41-51. 242 40. McPherson, E.G., Simpson, J.R. & Livingston, M., 1989. Effects of three landscapes on residential energy and water use in Tucson, Arizona. Energy and Buildings, 13, 127-138. 41. McPherson, E.G. et al., 2000. Tree Guidelines for Coastal Southern California Communities. 42. McPherson, E.G. & Simpson, J.R., 1998. Simulation of tree shade impacts on residential energy use for space conditioning in Sacramento. Atmospheric Environment, 32, 69-74. 43. McPherson, E.G. et al., 2001. Tree Guidelines for Inland Empire Communities. 44. Meiss, M., 1979. The Climate of Cities. In I. C. Laurie, ed. Nature in Cities: Natural Environment in the Design and Development of Urban Green Areas. John Wiley & Sons Ltd. 45. Moffat, A.S. & Schiler, M., 1981. Landscape Design That Saves Energy, William Morrow. 46. Moffat, A.S. & Schiler, M., 1994. Energy-Efficient and Environmental Landscaping: Cut Your Utility Bills by Up to 30 Percent and Create a Natural Healthy Yard 1st ed., Appropriate Solutions Press. 47. Monteith, J. & Unsworth, M., 1990. Principles of Environmental Physics 2nd ed., London: Edward Arnold. 48. Oke, T.R., 1981. Canyon geometry and the nocturnal urban heat island: comparison of scale model and field observations. Journal of Climatology, 1. 49. Oke, T.R., 1982. Overview of interactions between settlements and their environments. In WCP-37. WMO, Geneva. 50. Oke, T.R., 1988. Boundary Layer Climates 2nd ed., Routledge. 51. Parker, J.H., 1983. Landscaping to reduce the energy used in cooling buildings. Journal of Forestry, 81(2), 82-105. 52. Peck, S. & Kuhn, M., 2001. Design Guidelines for Green Roofs, Toronto, Canada: National Research Council Canada. 243 53. Petersen, F.F., Insolation and a Method for Its Measurement, M.A. Thesis (USC) CA. Available at: http://eetd.lbl.gov/HeatIsland/RECPUB.html [Accessed August 29, 2008]. 54. Petit, J., Bassert, D.L. & Kollin, C., 1995. Building greener neighborhoods: trees as part of the plan, Washington, D.C.: Home Builder Press. 55. Pomerantz, M. et al., 2000. The Effect of Pavements' Temperatures on Air Temperatures in Large Cities, Lawrence Berkeley National Laboratory, Berkeley, CA. Available at: http://eetd.lbl.gov/HeatIsland/RECPUB.html [Accessed August 29, 2008]. 56. Raeissi, S. & Taheri, M., 1999. Energy saving by proper tree plantation. Building and Environment, 34, 565-570. 57. Reducing Urban Heat Islands: Compendium of Strategies - Cool Pavements, U.S. Environmental Protection Agency. Available at: http://www.epa.gov/hiri/resources/pdf/CoolPavesCompendium.pdf. 58. Reducing Urban Heat Islands: Compendium of Strategies - Cool Roofs, U.S. Environmental Protection Agency. Available at: http://www.epa.gov/hiri/resources/pdf/CoolRoofsCompendium.pdf. 59. Reducing Urban Heat Islands: Compendium of Strategies - Green Roofs, U.S. Environmental Protection Agency. Available at: http://www.epa.gov/hiri/resources/pdf/GreenRoofsCompendium.pdf. 60. Reducing Urban Heat Islands: Compendium of Strategies - Trees and Vegetation, U.S. Environmental Protection Agency. Available at: http://www.epa.gov/hiri/resources/pdf/TreesandVegCompendium.pdf. 61. Rich, P.M., Hetrick, W.A. & Saving, S.C., 1994. Characterization of vegetation properties: Canopy modeling of pinyon-juniper and ponderosa pine woodlands; Final report. Modeling topographic influences on solar radiation: A manual for the SOLARFLUX model, United States. Available at: 10.2172/90166 [Accessed September 28, 2008]. 62. Rich, P.M. et al., 1995. Modeling Topographic Influences on Solar Radiation [microform]: A Manual for the SOLARFLUX Model, Los Alamos, N.M.: Los Alamos National Laboratory. 63. Sailor, D., 2002. Urban Heat Islands, Opportunities and Challenges for Mitigation and Adaptation. Sample Electric Load Data for New Orleans, LA (NOPSI, 1995). 244 Data courtesy Entergy Corporation. In Toronto, Canada. Available at: http://www.epa.gov/hiri/images/electricdemand-big.gif. 64. Santamouris, M. ed., 2001. Energy and Climate in the Urban Built Environment, Earthscan Publications Ltd. 65. Santamouris, M. ed., 2006. Environmental Design of Urban Buildings: An Integrated Approach, Earthscan Publications Ltd. 66. Schiler, M., 2009. Examples of Glare Remediation Techniques: Four Buildings. In Quebec, Canada. 67. Schiler, M. & Valmont, E., 2005. Microclimatic Impact: Glare around the Walt Disney Concert Hall. In Proceedings of the Solar World Congress 2005 Joint American Solar Energy Society. Orlando. 68. Shahabi, C. et al., 2006. GeoDec: Enabling Geospatial Decision Making. In Toronto, Canada. Available at: http://infolab.usc.edu/projects/geodec/publications.php [Accessed August 29, 2008]. 69. Simpson, J.R., 2002. Improved estimates of tree-shading effects on residential energy use. Energy and Buildings, 34, 1067-1076. 70. Stein, B. et al., 2005. Mechanical and Electrical Equipment for Buildings 10th ed., Wiley. 71. Summers, P.W., 1964. An urban ventilation model applied to Montreal. PhD thesis. McGill University, Montreal. 72. Sundborg, A., 1950. Local climatological studies of the temperature conditions in an urban area. Tellus, 2. 73. Szokolay, S., 2008. Introduction to Architectural Science: The Basis of Sustainable Design 2nd ed., Architectural Press. 74. Taha, H., Chang, S. & Akbari, H., 2000. Meteorological And Air Quality Impacts Of Heat Island Mitigation Measures In Three U.S. Cities, Berkely, CA: Lawrence Berkeley National Laboratory. Available at: http://asusmart.com/blog/urban- climate/air-quality-analysis-for-3-cities [Accessed August 31, 2008]. 75. Velazquez-Lozada, A., Gonzalez, J. & Winter, A., Urban heat island effect analysis for San Juan, Puerto Rico [An article from: Atmospheric Environment]. Elsevier. 245 76. Voogt, J.A., 2002. Urban Heat Island. In I. Douglas, ed. Encyclopedia of Global Environmental Change. Causes and consequences of global environmental change. Chichester: John Wiley & Sons, Ltd, pp. 660– 666. 77. Walker, R.E. & Kay, G.F., 1989. Landscape water management handbook, version 4.1, Office of Water Conservation, Department of Water Resources, State of California. 78. Weng, Q. ed., 2007. Remote Sensing of Impervious Surfaces 1st ed., CRC. 79. Weng, Q. & Quattrochi, D.A. eds., 2006. Urban Remote Sensing 1st ed., CRC. 80. Wilmers, F., 1990. Effects of vegetation on urban climate and buildings. Energy and Buildings, 15-16. 81. Wong, N.H. & Chen, Y., 2008. Tropical Urban Heat Islands: Climate, buildings and greenery 1st ed., Taylor & Francis.

Abstract (if available)

Abstract Digital simulation methods are important for analyzing energy flows. They inform the design and help determine what methods are useful for the remediation of built form to enable energy conservation. The logical requirement therefore is to develop sophisticated energy modeling tools for mitigating some of the most pressing urban problems.

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Asset Metadata

Creator Jain, Anupam (author)

Core Title A step towards urban building information modeling: measuring design and field variables for an urban heat island analysis

School School of Architecture

Degree Master of Building Science

Degree Program Building Science

Publication Date 08/07/2009

Defense Date 03/11/2009

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

Tag albedo,computer modeling,cool roof,green roof,insolation,OAI-PMH Harvest,Parking Lot,pavement,urban heat island

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Kensek, Karen (committee chair), Spiegelhalter, Thomas (committee chair), Banaei-Kashani, Farnoush (committee member), Noble, Douglas (committee member)

Creator Email anupam11@gmail.com,anupamj@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m2531

Unique identifier UC1128453

Identifier etd-Jain-3174 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-178515 (legacy record id),usctheses-m2531 (legacy record id)

Legacy Identifier etd-Jain-3174.pdf

Dmrecord 178515

Document Type Thesis

Rights Jain, Anupam

Type texts

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

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu