Transportation, land use, and environmental planning 9780128151679, 0128151676

Table of contents :
PART I MOTIVATIONS 1. The changing nature of work and time use: implications for travel demand 2. Integrating health into metropolitan transportation planning 3. Transportation and land use as social determinants of health: the case of arterial roads 4. Transit-oriented displacement: the role of transit access in the housing market PART II STRATEGIES 5. Urban design for sustainable and livable communities: the case of Vancouver 6. Measuring land use performance: from policy to plan to outcome 7. The transit metropolis: a 21st century perspective 8. Livability as a framework for understanding and guiding transportation and land use integration 9. Making US cities pedestrian- and bicycle-friendly 10. Parking: not as bad as you think, worse than you realize 11. Traffi c management strategies for urban networks: smart city mobility technologies 12. Vehicle technologies for achieving near and longer term fuel economy and climate goals 13. Sharing strategies: carsharing, shared micromobility (bikesharing and scooter sharing), transportation network companies, microtransit, and other innovative mobility modes 14. The role of behavioral economics and social nudges in sustainable travel behavior Part III BROADENING THE SCOPE 15. Energy sources for sustainable transportation and urban development 16. Balancing education opportunities with sustainable travel and development 17. Planners' presence in planning for water quality and availability PART IV IMPLEMENTATION ISSUES: THE CASE OF CALIFORNIA 18. Integrated transport and land use planning aiming to reduce GHG emissions: International comparisons 19. Defi ning TOD: learning from California law 20. Sustainability planning by Metropolitan Planning Organizations: California and national trends 21. The role of county-level agencies in coordinating local climate planning in California 22. California's SB 375 and the pursuit of sustainable and affordable development 23. Citizen mobilization in digital and analog: when regional planning lands in Marin County, California, is it a carrot or a stick painted orange? PART V CONCLUSIONS 24. The role of modern research universities in advancing innovative transportation infrastructure renewal

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Transportation, Land Use, and Environmental Planning

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Transportation, Land Use, and Environmental Planning

Edited by

Elizabeth Deakin Professor Emerita of City and Regional Planning and Urban Design, University of California-Berkeley, USA

Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States Copyright © 2020 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein). Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library ISBN: 978-0-12-815167-9 For information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Joe Hayton Acquisition Editor: Brian Romer Editorial Project Manager: Emily Thomson Production Project Manager: Paul Prasad Chandramohan Designer: Greg Harris

Typeset by Thomson Digital

Contents Contributors xvii Introduction xix

Part I Motivations 1.

The changing nature of work and time use: implications for travel demand Noreen McDonald, Ke Peng

1 Introduction 2 Background 2.1 Changing young adult labor market 2.2 Changing young adult travel 3 Research questions 4 Data and methods 4.1 Segmentation 4.2 Sample characteristics 5 Results 5.1 Employment and economic characteristics, 2003–15 5.2 Work time use segmentation 5.3 Commuting in peak periods 6 Discussion and conclusions References

2.

3 4 4 5 5 6 6 8 9 9 9 11 12 14

Integrating health into metropolitan transportation planning Catherine Ross, Peter Hylton, Farran (Fangru) Wang

1 Overview 2 Previous work 2.1 Health and the built environment 2.2 Health in the planning process 2.3 Health impact assessment (HIA) 3 Methodology 4 Findings 4.1 Target areas 4.2 Project selection 4.3 Organizational structure

17 18 18 19 20 21 22 23 24 26 v

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5 Policy implications 6 Conclusions References

3.

30 31 33

Transportation and land use as social determinants of health: the case of arterial roads Carolyn McAndrews

1 Introduction 35 2 Neighborhoods and health 36 2.1 Poverty and segregation 36 2.2 Neighborhood physical and social environments 37 3 Transportation and land use as social determinants of health in neighborhood 39 3.1 Chronic stress 39 3.2 Behavior 41 4 The case of major arterial roads 41 4.1 Streets and land uses that associate with neglect and physical decay 42 4.2 Barriers that lead to community severance and social isolation 44 5 Implications for policy, planning, and design 45 5.1 Traffic operations and design strategies 45 5.2 Greening and cues to care 46 5.3 Infill, revitalization, and community development strategies 46 6 Conclusion 47 References 48

4.

Transit-oriented displacement: the role of transit access in the housing market Karen Chapple, Miriam Zuk

1 Introduction 2 TOD and displacement: understanding the relationships 3 Defining and describing TOD and displacement 3.1 Data sources and terms 3.2 TOD areas in the Bay Area 4 Modeling gentrification, exclusion, and displacement 4.1 Gentrification 4.2 Exclusion 4.3 Changes in affordable housing 4.4 Loss of low-income households 5 Anti-displacement and housing affordability policies 5.1 Overview of anti-displacement and housing affordability policies 5.2 Housing affordability and anti-displacement policies in the Bay Area

55 56 57 57 59 60 60 62 62 62 65 66 68

Contents

5.3 Addressing displacement in transit-oriented development 6 Conclusion References

vii 68 77 78

PART II

Strategies 5.

Urban design for sustainable and livable communities: the case of Vancouver Elizabeth Macdonald

1 Introduction 2 Urban context and overview of Vancouver’s plans and policies in the two eras 3 Downtown neighborhood planning in the “Living First” era 3.1 Downtown South 3.2 False Creek North 3.3 Southeast False Creek 3.4 Results 4 Neighborhood planning in outlying areas during the EcoDensity era 5 Vancouver going forward 6 Conclusions References

6.

83 85 90 90 92 95 96 98 101 101 103

Measuring land use performance: from policy to plan to outcome Gian-Claudia Sciara

1 Introduction 2 Government action and land use in the United States 3 The effectiveness of governmental efforts to shape land use in the United States 3.1 State growth management policies 3.2 Regional efforts to influence local land use and development 3.3 Local efforts to influence land use and development 4 Four frameworks for evaluating land use plans and policy 4.1 Process-based frameworks for local plan and policy evaluation 4.2 Goal-based frameworks for local plan and policy evaluation 4.3 Implementation-based frameworks for local plan and policy evaluation 4.4 Outcome-based evaluations: monitoring key variables 5 Discussion and conclusions References

105 106 108 111 114 116 118 118 120 120 121 123 125

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7.

The transit metropolis: a 21st century perspective Robert Cervero

1 Introduction 2 The transit metropolis: core principles 3 Megatrends and shifting lifestyle preferences 3.1 Aging societies 3.2 The Millennials and the shifting economy 4 Transformative technologies and urban futures 4.1 Smart mobility and autonomous vehicles 4.2 Ride-hailing and shared-ride services 4.3 Smart pricing and technologies 4.4 E-commerce 5 21st century transit metropolises as hybrids References

8.

131 131 133 133 134 137 137 138 141 143 144 146

Livability as a framework for understanding and guiding transportation and land use integration Bruce Appleyard, Alexander R. Frost

1 Introduction 2 Background and previous work on the topic 3 Methods and findings 3.1 Definitions, typology, and performance measures 3.2 Data 3.3 Analysis of station area performance using quality of life proxy measures 4 Discussion and policy implications References

9.

151 152 155 156 157 161 163 165

Making US cities pedestrian- and bicycle-friendly Susan Handy

1 Introduction 2 Reworking car-friendly cities 2.1 Distances 2.2 Protection 2.3 Integration 3 Unleashing the potential of bicycling 4 Elevating pedestrians and bicyclists in regional planning 5 Conclusions References

169 170 171 173 175 176 179 181 182

10. Parking: not as bad as you think, worse than you realize Rachel Weinberger

1 Introduction 2 The parking problem

189 190

Contents

Problem: your parking demand impinges my supply and 30% of traffic is searching for parking 4 Solution: provide more off-street parking 5 Impact of more parking 5.1 Developer impacts 5.2 Parking and car ownership 6 The impact of parking on the built environment, travel behavior and downtown economies 7 Is the problem well defined? 8 Is there a parking shortage? 9 How much driving is cruising after all? 10 Parking problem redefined 11 Solutions redefined 11.1 Performance parking 11.2 Controls on supply, unbundled, and shared parking 12 Conclusion References

ix

3

191 193 195 195 195 196 197 197 199 200 200 201 201 202 203

11. Traffic management strategies for urban networks: smart city mobility technologies Alexander Skabardonis

1 2 3

Existing traffic management strategies in urban networks Emerging applications: the promise Emerging applications: the implementation challenge 3.1 Technology requirements 3.2 Traffic analysis tools 3.3 Relationship with transportation planning studies and plans 3.4 Communicating the benefits of new technologies to decision-makers References

207 209 212 212 213 214 214 215

12. Vehicle technologies for achieving near and longer term fuel economy and climate goals Timothy E. Lipman

1 Introduction 2 The global oil supply and demand conundrum 3 Regulatory approaches for reducing motor vehicle emissions and energy use 3.1 Emissions and energy standards in the US 3.2 Motor vehicle emissions and energy programs in other countries 4 Additional strategies for improved fuel economy and reduced GHG emissions

217 218 221 221 225 227

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5 Recent research on zero-tailpipe emission vehicles 6 Conclusions References

229 234 235

13. Sharing strategies: carsharing, shared micromobility (bikesharing and scooter sharing), transportation network companies, microtransit, and other innovative mobility modes Susan Shaheen, Adam Cohen, Nelson Chan, Apaar Bansal

1 Introduction 2 Emerging shared mobility services 3 Carsharing 3.1 Roundtrip carsharing 3.2 One-way carsharing 3.3 Personal vehicle sharing (PVS) 4 Shared micromobility (bikesharing and scooter sharing) 4.1 Scooter sharing (standing electric and moped-style scooters) 4.2 Bikesharing 5 Ridesharing 6 On-demand ride services 6.1 Transportation network company (TNC) services 6.2 Ridesplitting (also known as pooling) 6.3 E-hail services 7 Microtransit 8 Courier network services 8.1 P2P delivery services 8.2 Paired on-demand passenger ride and courier services 9 Trip planning apps 9.1 Single-mode trip planning 9.2 Multi-modal trip aggregators 9.3 Gamification 10 Conclusion References

237 238 240 240 242 243 245 246 246 248 248 248 252 253 253 255 256 256 257 257 257 258 258 259

14. The role of behavioral economics and social nudges in sustainable travel behavior William Riggs

1 Statement of the problem 2 Previous work on the topic 3 Experiments 3.1 Experiment 1: incentives for giving up driving 3.2 Experiment 2: perceptions of street safety for cyclists 4 Findings

263 264 266 267 268 269

Contents

4.1 Findings from experiment 1 4.2 Findings from experiment 2 5 Findings and policy implications References

xi

269 270 272 273

Part III Broadening the scope 15. Energy sources for sustainable transportation and urban development Blas L. Pérez Henríquez

1 2 3

Introduction: the energy outlook and emerging challenges Global decarbonization efforts Subnational and non-governmental action for clean energy and greenhouse gas reductions 4 Case example: California’s emissions and energy policies for a clean future 5 Implications for energy planning References

281 283 286 289 292 297

16. Balancing education opportunities with sustainable travel and development Carrie Makarewicz

1 Introduction 299 2 Country differences in school funding, governance, and assignment policies 302 3 Reasons for differential school outcomes 304 3.1 White flight and urban decline 304 3.2 School siting standards and school travel in the United States 309 4 Attempts to address urban school decline and school sprawl 312 4.1 Addressing school decline through in-school reforms and school choice 312 4.2 Addressing school siting and transportation policies 315 5 Policy implications and alternative approaches 317 5.1 Improving urban schools through community connections 317 5.2 Integrating school planning with land use & transportation planning 320 5.3 Federal opportunity for all policies: a new era of school desegregation? 321 6 Conclusion 322 References 324

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17. Planners’ presence in planning for water quality and availability Caitlin Dyckman

1

Introduction/statement of the problem 1.1 How water is used and monitored 1.2 The water problems: nationally and internationally 1.3 Research objectives 2 Previous work on the topic 2.1 States and planners in US water planning 2.2 Water demand management and devolution in water quality control 2.3 Water management problems, their import for planners, and emerging policy approaches to address them: collaborative watershed management, social-ecological resilience (SER), and sustainable commons management (SCM) 3 Methodology 4 Findings 4.1 Planners’ roles in water conservation 4.2 Planners’ roles in watershed-based planning 4.3 State comprehensive water planning legislation 5 Policy implications 6 Conclusions References

333 334 334 337 338 338 342

344 347 349 350 362 363 386 387 388

Part IV Implementation issues: the case of California 18. Integrated transport and land use planning aiming to reduce GHG emissions: International comparisons Andrea Broaddus

1 Introduction 2 What legal regulatory frameworks for transportation and land use planning are in use? 2.1 Roots of centralized regional land use and transport planning in Europe 2.2 Trends: devolution and regionalism 3 What policies linking transportation and land use planning to CO2 emissions are in place? 4 What types of projects and development have resulted in practice, and what are the barriers to implementation? 4.1 Planning approaches 4.2 Plans and Projects 4.3 Barriers 5 Conclusion References

399 400 400 405 409 411 411 412 413 416 417

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19. Defining TOD: learning from California law Gregory L. Newmark, William L. Kaplowitz

1 Introduction 2 Background 3 Methodology 4 California TOD legislation and state programs 5 Definitional issues 5.1 Defining what qualifies as transit 5.2 Establishing the transit-oriented zone 5.3 What land uses are transit-oriented? 6 Conclusions References

419 420 421 423 427 427 432 435 436 437

20. Sustainability planning by Metropolitan Planning Organizations: California and national trends Elisa Barbour

1 Introduction 2 Sustainability planning by MPOs 2.1 Motives for sustainability planning by MPOs 2.2 MPOs and sustainable development 2.3 Challenges of MPO sustainability planning: ambitious goals, modest means 3 Measures for evaluating MPO sustainability planning 4 Findings on sustainability planning by large US MPOs 5 Sustainability planning by California MPOs 5.1 Has SB 375 made a difference? 5.2 SB 375 comes under scrutiny 6 Conclusion 7 List of RTPs References

439 440 440 443 444 445 447 456 457 460 462 464 465

21. The role of county-level agencies in coordinating local climate planning in California Elizabeth Mattiuzzi

1 Introduction 2 Background 2.1 California’s rapid growth and its jobs-housing mismatch 2.2 SB 375 as a change in direction 3 County-level agencies’ roles in California transportation and housing 3.1 County transportation authorities 3.2 Councils of governments 4 Methodology

469 470 470 472 472 473 474 476

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Contents

5

Evidence for subregional coordination of local climate planning and SB 375 implementation 5.1 Surveying planners on SB 375 implementation 5.2 The relationship between collaboration and implementation 5.3 Case studies of subregional coordination of climate planning 6 Conclusion and policy implications References

477 477 480 481 493 494

22. California’s SB 375 and the pursuit of sustainable and affordable development Sarah Mawhorter, Amy Martin, Carol Galante

1 Introduction 2 Background 2.1 Climate change and housing affordability crises converge 2.2 Overview of SB 375 and housing 2.3 Assessments of SB 375 to date 3 Research approach 4 Analysis 4.1 SB 375 implementation through RHNA has limited potential to increase infill development in most regions 4.2 Incentives for SCS implementation are limited and vary by region 4.3 CEQA streamlining to enable SCS implementation 5 Conclusion 5.1 Alignment of housing and transportation goals 5.2 Need for more enforcement 5.3 Need for more incentives 5.4 Need for more capacity 5.5 Need for more accountability 5.6 Looking ahead References

497 498 498 499 500 501 502 502 505 514 516 516 517 517 518 518 519 519

23. Citizen mobilization in digital and analog: when regional planning lands in Marin County, California, is it a carrot or a stick painted orange? Karen Trapenberg Frick

1 2 3

Statement of the problem Conceptual framework—the (virtual) cycle of organizing and adapting in digital Research design

523 528 531

Contents

4 The opposition to Plan Bay Area in Marin County 5 Planning proponents in response 6 Discussion 6.1 Impacts on planning and projects 6.2 Implications for scholarship and practice References

xv 532 537 540 541 543 546

PART V

Conclusions 24. The role of modern research universities in advancing innovative transportation infrastructure renewal Bjorn Birgisson

1 Background 2 Key trends affecting university-based research on transportation infrastructure renewal 3 Changing nature of research universities 4 Accelerating globalization 5 Accelerating rate of technological change 6 Growth in multidisciplinary research and innovation 6.1 Smart Infrastructure 6.2 Manufacturing and automation for transportation infrastructure renewal 6.3 Resilient and critical infrastructure systems 6.4 Innovative financing and procurement 6.5 New collaboration and societal engagement modes for university-based transportation researchers 6.6 Universities for the new knowledge society 7 Recommendations References

555 556 557 558 559 559 560 562 563 564 565 565 566 567

25. Integrating transportation, land use, and environmental planning Elizabeth Deakin

1

Changing planning practices and challenges for planning 1.1 Transportation challenges 1.2 Land use challenges 1.3 Climate change and the continuing challenges of achieving a healthy environment 2 Identifying successes and learning from shortcomings 3 The case of California 4 Barriers to implementation, and ways to overcome them 5 Steps for integrating transportation, land use, and environmental planning References Index

569 570 571 573 574 577 585 591 596 601

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Contributors Bruce Appleyard  School of Public Administration and Urban affairs, San Diego State University, San Diego, CA, United States Apaar Bansal  Transportation Sustainability Research Center, University of California, Berkeley, CA, United States Elisa Barbour  University of California, Davis, CA, United States Bjorn Birgisson  Zachry Department of Civil and Environmental Engineering, Texas A&M University, College Station, TX, United States Andrea Broaddus  Mineta Transportation Institute, San Jose State University, San Jose, CA, United States Robert Cervero  Department of City and Regional Planning, University of California, Berkeley, CA, United States Nelson Chan  Transportation Sustainability Research Center, University of California, Berkeley, CA, United States Karen Chapple  Department of City and Regional Planning, University of California, Berkeley, University of California, Berkeley, CA, United States Adam Cohen  Transportation Sustainability Research Center, University of California, Berkeley, CA, United States Elizabeth Deakin  Department of City and Regional Planning, University of California, Berkeley, University of California, Berkeley, CA, United States Caitlin Dyckman Department of City and Regional Planning and Real Estate Development, Clemson University, Clemson, SC, United States Karen Trapenberg Frick  Department of City and Regional Planning, University of California Berkeley, Berkeley, CA, United States Alexander R. Frost School of Public Administration and Urban affairs, San Diego State University, San Diego, CA, United States Carol Galante Terner Center for Housing Innovation, University of California, Berkeley, CA, United States Susan Handy Department of Environmental Science and Policy, University of California, Davis, CA, United States Peter Hylton  High Street Consulting, Columbia, SC, United States William L. Kaplowitz  Independent Researcher, Chicago, IL, United States xvii

xviii

Contributors

Timothy E. Lipman Transportation Sustainability Research Center, University of California, Berkeley, CA, United States Elizabeth Macdonald Department of City & Regional Planning, Department of Landscape Architecture & Environmental Planning, University of California, Berkeley, CA, United States Carrie Makarewicz  Urban and Regional Planning Department, University of Colorado Denver, Denver, CO, United States Amy Martin  Terner Center for Housing Innovation, University of California, Berkeley, CA, United States Elizabeth Mattiuzzi Federal Reserve Bank of San Francisco, San Francisco, CA, United States Sarah Mawhorter  University of Southern California, Los Angeles, CA, United States Carolyn McAndrews  Department of Planning and Landscape Architecture, University of Wisconsin, Madison, WI, United States Noreen McDonald Department of City & Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States Gregory L. Newmark Department of Landscape Architecture and Regional and Community Planning, Kansas State University, Manhattan, KS, United States Blas L. Pérez Henríquez  Precourt Energy Scholar, Stanford University, Stanford, CA, United States Ke Peng Department of Urban Planning, School of Architecture, Hunan University, Changsha, China William Riggs Department of Public Administration, School of Management, University of San Francisco, San Francisco, CA, United States Catherine Ross School of City and Regional Planning/Civil and Environmental Engineering; Center for Quality Growth and Regional Development (CQGRD); College of Design, Georgia Institute of Technology, Atlanta, GA, United States Gian-Claudia Sciara  Community and Regional Planning Program, The University of Texas at Austin, Austin, TX, United States Susan Shaheen Department of Civil and Environmental Engineering, University of California, Berkeley; Transportation Sustainability Research Center, Berkeley, CA, United States Alexander Skabardonis  Department of Civil and Environmental Engineering, University of California, Berkeley, CA, United States Farran (Fangru) Wang  Pinterest, San Francisco, CA, United States Rachel Weinberger  Weinberger & Associates, Brooklyn, NY, United States Miriam Zuk Department of City and Regional Planning, University of California, Berkeley, CA, United States

Introduction 1  How this book came to be This book has been a long time in the making. In 2012, Haris Koutsopoulos, then a professor at the Royal Institute of Technology in Stockholm (KTH), proposed that he and I should organize a small conference at which invited scholars and practitioners would examine alternative pathways for urban transportation. With the support of then-faculty member Jonas Eliasson, then-dean Folke Snickars, and then-vice president for research Bjorn Birgisson, Peter Gudmundson, who was KTH president at the time, agreed to provide funding for the effort from the Swedish Government Transport Strategic Area grant to KTH. Peter Gudmundson served as the overall PI, with Haris Koutsopoulos as a Co-PI and overall academic lead, along with Bjorn Birgisson, Jonas Eliasson, and Annika Stensson Trigell. The conference, which we dubbed the Stockholm Summit, was held that fall. Participants debated the role that new technologies such as electric, automated vehicles, and “smart city” management strategies would play in the cities of the future, and speculated on how they might interact with urban policies emphasizing land use planning to foster trip reduction and walk, bike, and transit modes. The conference participants did not reach agreement on these topics, but they did agree that there was a need for more visible and broadbased examination of transportation, land use, and environmental policies for the future. A second conference was organized for the Spring 2013 and many of the participants shared drafts of work in progress at the conference or gave detailed presentations on topics ranging from prospects for new technologies to the factors changing markets for city living. The meeting concluded with a dozen scholars and practitioners committed to contributing a paper in time for a fall 2013 conference, with the aim of turning the papers into an edited book. That book was not to be. While several of the participants did indeed come to the fall conference with papers in hand, others were unable to find the time to fit this extra writing assignment into their busy schedules. Over the next several months, two of the participants moved to other universities and had to focus their attention on their new jobs; two retired and decided to take time off from scholarly writing; two were appointed to government positions and their new appointments precluded outside pursuits. Two additional participants took on major consulting assignments that left no time for the project. By summer 2014, the KTH team and I concluded that it was best to put the conference materials on a website and put the book project on indefinite hold. Still, the ideas the Stockholm meetings had raised remained salient. In 2015, an opportunity arose to organize a conference at the University of California, xix

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Berkeley, covering many of the same topics the Stockholm Summit had been designed to address, but with a US focus. The Berkeley conference was further broadened to address the problem of housing affordability and additional infrastructure issues, including water availability and quality, power generation, and schools. Case studies of California’s experience with efforts to reduce emissions through land use and transportation strategies were added to the agenda. The conference, held in October 2016, was supported with grants and staffing assistance from UC Berkeley’s Institute of Urban and Regional Development, the Berkeley Institute of Transportation Studies, the UC Transportation Center, and the California Department of Transportation. It was attended by over 100 scholars and practitioners, whose questions and comments further illuminated the issues. This book thus grew out of both the Stockholm and Berkeley conferences. Many of the papers presented in the chapters that follow were originally presented at one or more of those conferences, though several have been substantially revised and updated based on ongoing events. Additional papers inspired by the conference and written specifically for this book have been included as well. All of the papers benefited from presentations and papers on various aspects of transportation, land use, and the environment shared by colleagues who were not able to join the book project: David Banister, Karen Brundell-Freij, Ennio Cascetta, Yves Crozet, Jonas Eliasson, Chris Ferrell, Jonathan Gifford, Mans Lonnroth, Steve Lockwood, Hani Mahmassani, Greg Marsden, Lars-Goran Mattsson, Folke Snickars, and Jinhua Zhang. The papers benefited as well from comments and questions raised by the 100+ scholars and professionals who attended the Berkeley event. Anonymous reviewers of this book proposal made several useful suggestions that are reflected in the text. In addition, two anonymous reviewers gave each paper a careful reading and provided the authors with detailed comments and suggestions. Finally, the staff at Elsevier made sure the text was ready for publication and handled many details that simplified the publication process. Any errors that remain can be laid at my doorstep.

2  Introduction and overview 2.1  Motivations for this book Any book written today about transportation, land use, and environmental policy must address the challenge of global warming. Climate science makes it clear that rapid action is needed to limit damage from rising global temperatures, which are substantially caused by anthropogenic emissions. Literally, every sector of the economy needs to make significant changes to help slow temperature increases. The difficulty in doing so is apparent: a quarter of a century after participants in the 1992 United Nations Framework Convention on Climate Change (UNFCCC) made a commitment to reduce greenhouse gas

Introduction

xxi

(GHG) emissions, 2 decades after the Kyoto Agreement established initial reduction targets, and 2 years after the Paris Agreement broadened and strengthened reduction targets, global emissions of GHGs reached an all-time high in 2018—heading the wrong direction. Yet, failure to moderate-temperature increases could have dire consequences—sea-level rises, heat waves, increased flooding and droughts, disruption of agriculture, loss of habitat, species extinctions, and increased spread of pests and infectious diseases are just some of the impacts that have been predicted. Transportation and buildings are major sources of GHG emissions, together producing about 20% of the global total (not counting their use of electricity and heating, which is tabulated as a separate sector). The specifics vary by country and also by accounting method, but in the United States, after allocating electricity and heating to their end uses, transportation accounts for about 30%–33% of emissions and buildings 30%–39%. Moving away from carbonaceous fuels is a major strategy for reducing GHG emissions, but this appears to be more easily done in the energy sector than in transportation. Greener fuels and more fuel-efficient vehicles are key to cutting emissions, and electric vehicles (EVs) are widely considered the most salutary way forward; but EVs will not solve the climate problem if the electricity with which they are powered comes from burning coal or natural gas. Further, neither decarbonization of electricity nor EV market penetration is occurring fast enough to suffice as the only action taken. Carbon sequestration—capture and storage of carbon emissions in geologic formations, salt water, plants, soils, rocks, and manufactured products—shows promise, but current approaches are small scale, experimental, or costly, and some have potential side effects that are problematic (e.g., ocean acidification, long-term seepage from underground storage, etc.). With the need to do something becoming urgent—every year of delay means that even more would need to be accomplished in later years— transportation and land use strategies that were largely set aside in early discussions as too small to matter are back on the table. Still, global warming is only one of many reasons for better integrating transportation, land use, and environmental planning. Indeed, for many, there are social, economic, and environmental problems that are more immediate. These include impacts of transportation facilities that harm public health and the quality of the environment, divide communities, result in social and economic exclusion, and add to the stress of daily living, as well as land use and urban development policies and practices that result in housing affordability problems, auto-dependence, and limited access to goods and services for those who cannot drive a motor vehicle. Transportation and its environmental impacts are thus intertwined with land use and development patterns. Yet, the issues extend further. The location choices of businesses and firms, and many elements of travel behavior, are shaped by the availability and quality of a broad range of urban development attributes—transportation systems, jobs and housing, schools and libraries, shops

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and personal services, parks and recreation facilities, police, fire, and emergency response units, electric power and other energy supplies, water supply and water quality management, waste water treatment, solid waste disposal, telecommunications, and internet services. These services are in turn intertwined; for example, electric utilities are a major user of water, and energy and telecommunications systems frequently run along or adjacent to transportation rights of way. Today, many of the aspects of these systems and services are changing— new ride matching transportation services are being deployed, green buildings and distributed power systems are being implemented, e-books and e-learning are changing the nature of education, schools, and libraries, and e-commerce is transforming shopping for books, clothing, and even groceries. In turn, cities and towns are increasingly searching for ways to retain, or in some cases to create, a sense of place; they are doing so by redesigning streets to be friendlier to pedestrians and cyclists, adding pocket parks and street trees, and working with merchants to make the shopping street an inviting place to visit and linger. Still, it remains a challenge in most places to change practices, much less fully integrate transportation, land use, and environmental planning. In part this is due to the complex patchwork of specialist organizations involved. Traditionally, transportation—and most other public infrastructure—has been the realm of civil engineers, whereas land use planning and regulation has largely been the responsibility of real-estate experts, city planners, and lawyers. Differences in disciplinary training, experience, and perspectives can lead to conflicting views on what transportation investments are needed and what form urban development should take. In addition, there are many institutional actors involved. For example, transportation facilities and services in the United States are owned and operated by the states, counties, cities, and towns, and occasionally by special districts, the private sector, and the federal government. Funding to build and operate transport can and often does come from any or all of these organizations, usually with strings attached, and from user fees and general taxes, with attendant public expectations. Likewise, urban development involves an array of loosely associated actors: private property owners, developers, builders, public utilities suppliers, as well as local government regulators who in turn must follow federal and state legal requirements. In addition, members of the public—commuters, homeowners, renters, business leaders, environmentalists—want a say on how transportation and urban development is shaped and how it proceeds. Environmental planning, meanwhile, is carried out by scientists and engineers in organizations that typically are specialized by focus area: air quality, water quality, fish and wildlife, forestry, oceanography, agriculture, and so on. In many instances, environmental considerations are treated as an impact of the project, rather than a design consideration. In addition, because environmental impact assessments have been designed to take place after a project proposal is well specified, the consideration of alternatives is often perfunctory or narrowly defined. Concerns raised in environmental reviews can come too late in the

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xxiii

process for the project concept or major design details to be changed in a significant way, except at great cost. One result a tendency to focus on mitigating harm rather than incorporating environmental objectives into project definition and design. With such a complex set of institutional arrangements, reaching agreement on coordinated, consistent policy and action can be an arduous process, even more so if a change in direction is needed. This has been amply evidenced by experience with efforts to calm traffic, charge for parking, implement congestion pricing, reallocate street space to make room for bicycles, pedestrians, and transit, increase building densities in transit-rich urban centers, and include affordable housing in affluent new developments. While other countries may have a different mix of organizations and mandates from that in the United States— in particular, international practice is often more top down than in the United States—the situation is not necessarily any simpler or more transparent, and the need for greater integration of land use, transportation, and environmental considerations is equally high. Global warming greatly raises the stakes because it adds a particular urgency to act quickly. This is on top of existing challenges, felt even in wealthy nations but most acutely in the less affluent ones: infrastructure that is in poor condition or just plain missing, air and water quality problems, traffic congestion, energy shortages, and inadequate schools. Social and economic disparities exacerbate the impacts, with the brunt of most problems falling on the poor. Concerns persist about the potential conflicts between economic growth and environmental protection. In emerging economies, leaders point to the need to increase energy use in order to rise to the ranks of the middle class, while elsewhere concerns are raised about the high costs of change—political as well as social. Still, a growing number of cities, states, and national governments worldwide can list successes. In many places, the energy sector is moving away from coal; motor vehicles are cleaner and more fuel-efficient; progress has been made in making communities more livable as well as more prosperous. These achievements move in the right direction; the issue is whether they can happen faster and in ways that reduce GHGs significantly and benefit everyone, not just the affluent. This book was written to help find ways forward. In this book, authors examine policies and practices linking transportation, land use, and environmental planning with the objective of achieving sustainable development—a healthy environment, a thriving economy, and a more equitable and inclusive society. Contributors examine how regional and local planning practices are changing to reflect new demographic and economic trends and environmental and social challenges. They discuss strategies ranging from investments in transit and nonmotorized travel modes, to mixed use and higher density urban development, to radically transformed vehicles and transportation systems enabled by emerging technological innovations. They also discuss issues associated with other key infrastructure and services linked to transportation and development patterns

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and important for GHG reductions, including water, power, and schools. They review experiences with new policies aiming to reduce GHG emissions through transportation and land use actions and highlight issues that need to be brought into the debate—including unintended consequences and areas needing more research.

2.2  Focus on the United States and on California While this book presents examples from several states and countries, the primary focus is on the US experience and within the United States, on the experience in California. This may strike readers from other locales as an odd choice given the United States’ wavering position on global warming and the fact that California is but one state of 50 (and only half a percent of the world’s population.) However, there are several reasons why the United States and California deserve attention not only at home, but also internationally. One reason that the United States should receive international attention is that its outsized impact and influence demand it. While its population is a fraction of that of China or India, the United States has the largest economy in the world and one of the highest gross domestic products (GDPs) per capita. Much of its population growth and urbanization has occurred in the automobile era, with the population expanding from 106 million, about half in urban places, in 1920 to 327 million, 80% urban by 2018. For nearly 5 decades, the United States has had laws in place addressing transportation, the environment and energy conservation through federal rules and state and metropolitan planning, but many of its initiatives have been contentious—perhaps not surprising in a country that is democratic, diverse, and capitalist, and a major auto-manufacturer and oil producer as well. Regardless, the United States provides a rich context and record of experience for examining many of the policies of concern in this book. Today, according to the International Energy Agency, the United States is the second largest emitter of GHGs, after China, and its per capita GHG emissions from fuel consumption are third highest globally—at 15.5 metric tons per capita per year (2018), 1.5–4 times the per capita emissions of Western European countries or Japan. Given the US role in contributing to global emissions, lack of action by its federal government may well make it more politically difficult for other countries to take vigorous steps to reduce GHG emissions. But within the United States, action is in fact taking place—due to economics-driven fuel switching from coal to natural gas, to regulations on motor vehicle fuel efficiency, in response to actions taken at the state and local level, and through voluntary commitments by the private sector. Currently, 23 US states and the District of Columbia have enacted policies designed to reduce GHG emissions, over 400 US cities and counties have adopted the Paris Agreement goals, and hundreds of businesses, including 57 Fortune 500 companies headquartered in the United States, have committed to science-based GHG reduction targets.

Introduction

xxv

This book gives particular attention to California, not because it is the only state in which important contributions to transportation, land use, and the environment are occurring but because of California’s particular leadership and impact. First, California’s sheer size commands attention. Its economy ranks fifth worldwide in GDP, surpassed only by the United States as a whole, China, Germany, and Japan—slightly ahead of the United Kingdom and France. It is the most populous state in the United States, with nearly 40 million people in 2018—up to 10 million since 1990. This would place it 36th in world population rankings if it were a country. It is the third largest US state by land area (after Alaska and Texas), at 163.7 thousand sq. mi (423,972 km2), about the same physical size as Sweden (450,290 km2). Second, the state is environmentally, socially, and economically diverse, providing insights on how policies play out in different contexts. 800 miles long, California includes vast redwood forests, rugged mountain ranges and deserts, a heavily populated coastal area with a Mediterranean climate, and rural valleys and hillsides that produce over a third of the US’s vegetables and half of its fruits. The state’s population is a mixture of races and ethnicities and over a quarter of California residents are immigrants. The state is a major economic force in agriculture, computers, information technology, gene editing, and the movie industry, but economic conditions are widely varied; despite its high GDP, California ranks only 8th of the 50 states in terms of household income, and it suffers from severe income disparities, claiming some of the wealthiest communities in the nation while 13.3% of the population live in poverty (and almost one household in four is close to poverty if broader measures such as cost of living and social safety net benefits are taken into account). California government is organized into over 500 cities, towns, and counties, with 75 cities of over 100,000 population and 5 metropolitan regions of over a million people (Los Angeles, San Francisco, San Diego, Sacramento, and Fresno.) Two of these are megaregions: some 18.7 million people reside in the greater Los Angeles Combined Statistical Area (CSA) and 9.7 million reside in the San Francisco-Oakland-San Jose Bay Area CSA. While state law shapes transportation and environmental policy, substantial authority is delegated to cities and counties, and increasingly to regional agencies. In addition, voters can place measures on the ballot that, if passed, have the force of law and can overturn unpopular legislative acts. Third, California has been a policy innovator in land use, transportation, and environment protection and has a track record that has been extensively scrutinized. The state has long had requirements for each city and county to develop a general plan (i.e., a comprehensive plan) setting out its long-term policies for physical development and specifically discussing land use, transportation, conservation of natural resources, open space, noise, housing, and environmental justice. However, deference to “home rule” means that, in practice, the state inserts itself into the local planning process in very limited ways. California also has a long history of environmental planning; as just one example, it established

xxvi

Introduction

air pollution control districts in the 1940s and began to regulate emissions from stationary and mobile sources in the 1950s and 1960s. Congress acknowledged California’s leadership when it made provision for California to retain its own, tougher air pollution regulations, and consequently allowed other states to opt into the California vehicle emissions standards—a dozen have done so. California also was an early adopter of energy efficiency policies and energy standards for buildings, electric utilities, and transportation vehicles and fuels. Currently, however, the federal government is proposing to roll back vehicle fuel efficiency standards negotiated only a few years ago, and litigation may be the next step. In the field of transportation, California is known for its extensive freeway system, but it also has invested heavily in transit, particularly in its largest cities. Many local governments, large and small, have implemented traffic-calming measures and directed funds to bicycle lanes and pedestrian facilities. Although the state remains leery about congestion pricing, it has implemented high occupancy toll (HOT) lanes on a number of the state’s limited access highways and has adopted peak-off peak toll differentials as a form of congestion pricing on the San Francisco-Oakland Bay Bridge. Transportation network companies (TNCs) began in California, and have been widely deployed throughout the state, although their impact remains contentious. EVs and automated vehicles are being developed and tested in California, as are a variety of alternative fuels. Finally, California has taken an aggressive stand on reducing GHGs. Many cities and counties in California developed climate action plans in the 1990s, aiming to reduce GHGs while promoting more livable and equitable urban environments. The state committed to GHG reduction in 2006 with the passage of AB 32, the California Global Warming Solutions Act, which calls for the maximum technologically feasible and cost-effective reduction in GHGs. 2 years later, the Legislature added SB 375, the Sustainable Communities and Climate Protection Act, which mandates regional land use and transportation plans aimed at further reducing GHG. Both of these legislative mandates have been supplemented by additional laws and executive orders strengthening emission reduction targets and planning practices. Current state policy calls for a reduction in the state’s GHG emissions to 40% below the 1990 levels by 2030 and 80% below 1990 levels by 2050. In addition, gubernatorial Executive Order B-55-18 establishes a statewide goal for California to achieve carbon neutrality by 2045. For all of these reasons, California offers a rich and complex case of efforts to better align transportation, land use, and environmental planning, and several of the papers included in this book evaluate various aspects of the California experience.

3  How this book is organized This book is an edited collection of essays and research papers, presenting assessments of current policies and best practices, policy debates, and emerging issues in the areas of transportation, land use, and environmental planning.

Introduction

xxvii

Examples are provided throughout. While the topics are varied, all of the papers examine planning and implementation experiences and flag issues that demand more attention. Written for both scholars and practitioners, this book presents up-to-date information on “best practices” as well as the new strategies that are just beginning to emerge. Along with this introduction, the first few chapters lay out some of the reasons that transportation, land use, and environmental planning are increasingly being bundled together in urban and metropolitan planning processes, including changing demographics, preferences and needs, concerns about public health, concerns about housing affordability, equity issues, and neighborhood livability. Next a set of policies and planning frameworks are introduced that can be used to jointly plan for more livable and sustainable transportation, land use, and environmental outcomes. The chapters discuss urban design and land use planning, regional and corridor-level transit plans and transit-oriented development, bike and pedestrian improvements, parking management, traffic management, demand management, and emerging technologies and services. Three additional issues that weigh increasingly heavily on urban planning and urban quality of life are also discussed: energy sources for sustainable transportation and urban development, water supply and quality, and schools. This book then turns to experiences with efforts to better integrate transportation, urban development, and environmental goals, first taking a brief look at international experience and then examining US experience, and, in particular, California’s efforts to use integrated planning to reduce GHGs. Both the successes to date and the difficulties that have been revealed are discussed. In the concluding chapters, the authors look at the role of research universities in supporting innovation, and offer some prescriptions on ways forward. Among the questions this book addresses are as follows: As concerns about public health, neighborhood livability, economic opportunity, and equity gain traction as planning issues, how do policies and planning practices need to change? As cities become more attractive places to live and work, how can we avoid displacement of low- and moderate-income households? How can we provide housing that is at once affordable and has access to the services and amenities that make it attractive to a range of households including families? What are the prospects for transit and nonmotorized modes of transportation? How big an impact will new options such as carsharing, bikesharing, and ride matching services have on travel choices? What are the prospects for new vehicles and fuels? As the automobile and the street and highway system are redesigned to become smarter, more automated, and more environmentally friendly, how will travel change? What other infrastructure needs to be considered in order to deliver sustainable cities and regions?

•

• • • • •

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Introduction

• How are regional and local planning practices responding to the challenges •

of sustainable development? How effective are the emerging approaches and what has been the public response? What is needed to move transportation, land use, and environmental planning ahead in productive ways?

Despite its breadth, this book does not cover every issue of relevance. There is more to say about the equity of current and proposed transportation and land use plans, on ways of dealing with places that are in economic decline, on strategies for rural communities. Likewise, attention should be given to the ways various strategies for reducing GHGs interact, and about planning for resilience in the face of rising temperatures and sea levels. We leave those issues to other authors and hope that the materials we present here will be food for thought, discussion, and debate.

Part I

Motivations 1. The changing nature of work and time use: implications for travel demand 3 2. Integrating health into metropolitan transportation planning 17

3. Transportation and land use as social determinants of health: the case of arterial roads 35 4. Transit-oriented displacement: the role of transit access in the housing market 55

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Chapter 1

The changing nature of work and time use: implications for travel demand Noreen McDonalda, Ke Pengb a

Department of City & Regional Planning, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States; bDepartment of Urban Planning, School of Architecture, Hunan University, Changsha, China

1 Introduction Since 1970, the labor market has shifted from one characterized by rising prosperity across income and job types to one characterized by polarization and uncertainty. The past four decades have witnessed an increase in “high-skill, good jobs and low-skill, bad jobs, along with a decline in semiskilled well-paying jobs that has shrunk the size of the middle class” (Kalleberg, 2011, p. 14). The impacts of the changing labor market have been felt by all workers, but its effects have been the most dramatic for young adults. Growth of good jobs has not kept pace with demand resulting in a market characterized by unemployment and underemployment (Furlong, 2015, p. 533). This has forced young people to enter the labor market through “low-skill, low-wage jobs” (Furlong, 2015, p. 533). These jobs have been growing rapidly, but are characterized by the lack of full-time employment and lack of commitment from employers to employees (often through zero-hour or temporary contracts (Furlong, 2015, p. 536). Experts expect this multi-decadal labor market shift to continue (Furlong, 2015, p. 534; Kalleberg, 2011, p. 179). While these societal shifts may seem well away from the world of transport planning, they are central to future travel demand. Currently, much of planning practice implicitly presumes that economic recovery along with low gas prices will bring a return to previously-observed rates of mobility. For example, this is what regions assume when they use trip rates calibrated to older survey data or generate future populations with the employment characteristics of earlier times. However, the labor literature suggests increasing polarity in the economic futures of young people. Some will be lucky enough to gain the skills valued in today’s marketplace and attain the coveted “good jobs.” However, many will Transportation, Land Use, and Environmental Planning. http://dx.doi.org/10.1016/B978-0-12-815167-9.00001-3 Copyright © 2020 Elsevier Inc. All rights reserved.

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PART | I  Motivations

be stuck in “bad jobs,” which provide uncertain income and hours and may be associated with lower mobility. The remainder of this article explores how labor market shifts are reflected in the temporal patterns of work and assesses how these patterns connect to demographics and travel behavior. We conclude with an examination of the policy implications of the work.

2 Background 2.1  Changing young adult labor market Kalleberg (2011) highlights three overarching causes of labor market shifts observed since 1970. Globalization increased price competition for goods and ultimately increased pressure on firms to lower labor costs or greatly increase productivity. Deregulation of many sectors such as aviation and financial services lessened the role of governments in labor markets—a phenomenon which is especially prominent in the United States but is also true, albeit to a lesser degree, in the United Kingdom. This weakened labor unions and enforcement of labor laws. Finally, shifting societal patterns, particularly the rise of the knowledge economy and women’s increased labor force participation, led to a large increase in the service sector. Services previously performed at home such as food preparation, laundry, and childcare began to be outsourced. The impacts of this changing labor market on young adults have been dramatic. Young adult unemployment and underemployment reached all-time high in recent years. In southern European countries such as Greece and Spain, the majority of young people in the labor market are unemployed (Furlong, 2015, p. 533). Rates of 20% are common in the United Kingdom, Sweden, France, and Belgium and 10% in Germany, Austria, and Switzerland (Furlong, 2015, p. 533). These dismal statistics are the product of the global financial crisis and a changing labor market. First, there has been a multi-decade trend of lower labor force participation among young people (Furlong & Kelly, 2005). The prime driver of this trend is increased participation of young adults in higher education resulting from government policy and weakening job prospects for those without college degrees (Furlong, 2015, p. 533). For example, close to 95% of 20–24-year-olds in the United Kingdom were in the labor market in 1950 compared with 80% in 2010. Close to 100% of UK males between 25 and 29 years were employed in 1950 compared to approximately 90% in 2010. Second, when young people do enter the labor market, they are often under- or precariouslyemployed. This type of employment is characterized by the lack of full-time work and lack of commitment from employers to employees (often through zero-hour or temporary contracts (Furlong, 2015, p. 536). The future employment picture for young people is not rosy. Experts in this area predict increased unemployment and under-employment (Furlong, 2015, p. 534). As Kalleberg (2011, p.179) notes, the multi-decadal shifts in the labor market result from “structural modifications rather than simply fluctuations of the business cycle.” Weakened economic prospects for young people have knock-on

The changing nature of work and time use: implications for travel demand Chapter | 1

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effects on where they live as well as decisions about education, partnering, and parenthood. Young adults are increasingly continuing to live with their parents as they enter adulthood or finish university. This trend has continued up to today and did not decrease after the worst of the global financial crisis (Fry and Passel, 2014; Office for National Statistics, 2015). Similarly, median age at first marriage has risen steadily since the late 1960s (U.S. Census Bureau, 2016).

2.2  Changing young adult travel Young adults across Europe and North America are driving less today than at the start of the 21st century. This unanticipated decrease is large with reported annual mileage decline of 1000 in the United Kingdom and 2500 in the United States (Kuhnimhof, Armoogum, Buehler, Dargay, Denstadli, & Yamamoto, 2012). Academic and popular investigations of these trends have identified a complex set of explanatory factors including the global financial crisis, changing lifestyles resulting in delayed attainment of life milestones, lower purchasing power due to increased student debt, technological advances allowing for virtual interaction or use of non-auto modes, and changing attitudes and preferences about travel and residential location (Blumenberg, Taylor, Smart, Ralph, Wander, & Brumbagh, 2012; Delbosc & Currie, 2014; Klein & Smart, 2017; Mcdonald, 2015; Polzin, Chu, & Godfrey, 2014; Vij, Gorripaty, & Walker, 2017). Analyses of the relative influence of these variables have shown that economic and demographic factors explain a substantial portion of the observed declines (though there is debate about the share). Blumenberg et al. (2012, p. 4) state that “employment status, household income, and the like strongly influence the travel behavior of youth and adults” and ultimately conclude the “adage ‘It’s the economy, stupid’ appears to hold.” Klein and Smart (2017) find that “decreased employment, lower incomes and less wealth likely explain the differences in car ownership between millennials and older generations.” Mcdonald(2015) concludes that lifestyle-related demographic shifts combined with the general dampening of travel demand accounts for over half of the decline in daily trip making. These results have led many to presume that travel demand will return to normal as economies rebound from the global financial crisis. There is even evidence of aggregate and per capita auto travel returning to precrisis levels in the United States (Federal Highway Administration, 2016).

3  Research questions Our study links these two works by exploring the time patterns of work for young adults. Our focus is on identifying typologies of work time to understand the implications for work commutes. To do this, we focus on two questions: 1. How have employment and economic characteristics of young adults (18– 34 years) changed from 2003 to 2015? 2. What are the work time use patterns of young adults (18–34 years) and how do these vary by demographic characteristics?

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PART | I  Motivations

4  Data and methods The American Time Use Survey (ATUS) records activity and activity durations in American households and has been conducted annually since 2003 (Bureau of Labor Statistics, 2016; Hofferth, Flood, & Sobek, 2015). The survey is a repeated cross-section with respondents drawn from the sample for the US Census Bureau’s Current Population Survey. The ATUS provides a consistent way to assess work patterns and provides information on time spent in travel as well as occupation and employment patterns and demographics. This analysis uses the ATUS in two ways. First, longitudinal data from 2003 to 2015 on young people (18–34 years) are extracted to provide an overview of shifting labor market and demographic patterns. Second, data from 2012 to 2015 are used to develop a segmentation of work time use patterns among young adults (18–34 years). We focus on young adults because this group has experienced the largest impact of labor market restructuring as well as the largest observed changes in travel behavior.

4.1 Segmentation The goal of the segmentation analysis is to identify groups of young adults sharing similar work time use patterns. To do this we adapt the approach of Lesnard and Kan (2011) and first develop a work time sequence for each respondent; second, quantify differences in work time sequence across respondents; and finally, cluster respondents with the most similar patterns. The ATUS day starts at 4 a.m. and includes data on all activities over the next 24 hours. For each reported activity, a start and end time is recorded. To construct the data for the work time use pattern, we divide the day into 96 15-minute intervals. For each interval, we identify the activity occurring during that 15-minute segment as work (1) or non-work (0). To be included in the analysis, a respondent must record at least one 15-minute work segment. The ATUS defines work as “time spent working, doing activities as part of one’s job, engaging in incomegenerating activities not as part of one’s job, and job search activities... ‘Other income-generating activities’ are those done ‘on the side’ or under informal arrangement and are not part of a regular job. Such activities might include selling homemade crafts, babysitting, maintaining a rental property, or having a yard sale. These activities are those that persons are paid for or will be paid” (Bureau of Labor Statistics, 2016, p. 53). This means that a small fraction of individuals included in our analysis have a work activity but are not employed or looking for work. We quantify the similarity (or dissimilarity) between respondents’ work patterns using dynamic hamming matching (DHM). Like other time sequence analyses techniques, DHM compares the differences in time use pattern between any two respondents in each time segment and aggregates the dissimilarities over the 96 time segments. This results in an overall dissimilarity value between any two respondents and dissimilarity matrix that captures differences in work time for the entire sample.

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The uniqueness of DHM compared to other approaches is that the dissimilarity between activities for any two respondents depends on when the activities occur. If many people begin work activities and many other people begin non-work activities in time segment t, DHM assumes time segment t is a popular time for people switching between activities and therefore the dissimilarity between activities is low in time segment t (Lesnard & Kan, 2011). For example, respondents A and B are considered as having a dissimilar time use pattern between 2:00 and 2:15 a.m., if A does not work and B does work because this is not a popular time that people switch activities. In contrast, respondent A and C are considered as having similar time use pattern between 7:45 and 8:00 a.m. even if A does not work and C does work during this period. This is because many people switch from non-work to work during the period. We conduct the time sequence analysis with the seqcomp plug-in for Stata (Halpin, 2014). We then use agglomerative hierarchical clustering based on the dissimilarity matrix generated by DHM to identify groups of workers with similar work patterns. Agglomerative hierarchical clustering generates a set of nested clusters that are organized as tree, which allows us to compare all possible clustering outcomes simultaneously. This allows us to evaluate whether merging one cluster with the closest one sacrifices information on either group. We employ the method “beta-flexible”a with β = −0.3 to calculate the distance between clusters (Lesnard & Kan, 2011). The beta-flexible method has proved more robust in recovering structure in the presence of outliers and noise than other classical linkages such as Ward’s (Milligan, 1980). We used the package “cluster” in R for the clustering analysis. We adopt the 9-cluster solution as it is most succinct and incorporates all major types of expected work time use patterns. The organization of the ATUS data presents one notable quandary for the current analysis. As the ATUS day begins at 4 a.m., it is difficult to fully capture night shifts. In cases where an individual repeats a night shift, their full work time will be captured, that is, at the start and end of the reporting day. But in cases where individuals vary their schedule day to day, only part of their night shift may be captured. However, because DHM considers the differential in chances of switching between activities at different times across all individuals, it is unlikely DHM will confound the night shift time use pattern with other morning shift time use patterns when creating the dissimilarity matrices. This means our segments are reliable but work time may be underestimated for clusters with large proportions of night shift workers. a. In beta-flexible linkage, the distance between a given cluster k and a new group (i, j), which is formed by merging two clusters i and j, depends on three components: the distance between i and k, the distance between j and k, and the distance between i and j. All three distances depend on a parameter, beta, which is the weight that is assigned to the distance between i and j. Following Lesnard’s method, we use β = −0.3.

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4.2  Sample characteristics We focus on young respondents aged between 18 and 34 years in trend and segmentation analyses. The trend analysis considers all respondents in the age range while the segmentation only includes those who commuted to work on the survey day. Socio-demographic and travel differences between the two samples flow from this. Individuals in the segmentation analysis are more educated, work more, and are less likely to be in school; all expected differences (Table 1.1).

TABLE 1.1 Sample summary statistics for trend and segmentation analysis (unweighted). Characteristics

Trend analysis, 2003–15

Segmentation analysis, 2012–15

N (Standard Error)

38,836

3,944

Age: avg (SE)

27.4 (4.8)

27.9 (4.5)

Age: min

18

18

Age: max

34

34

In school %

20.1

15.6

Employed %

74.9

97.2a

White only %

79.6

78.9

Black only %

13.3

13.9

Hispanic %

19.6

19.2

Never married %

49.0

53.6

Female %

57.6

48.8

Education: some college or college degree %

61.4

68.8

Daily work minutes (SE)

191.5 (250.1)

466.7 (168.4)

Daily travel minutes (SE)

77.7 (78.7)

80.2 (58.3)

Usual hours worked per week (SE)

29.2 (20.6)

39.9 (13.6)c

Weekly earnings (2015$) (SE)

555.5 (589.3)d

725.1 (542.6)e

Number of children in household (SE)

1.0 (1.2)

0.9 (1.1)

a

b

The percent of respondents not employed but worked in the segmentation analysis is 2.8. Selfemployed income-generating activities such as yard sale or maintaining/renovating retail property are also categorized as work activities in the ATUS data. b The number of respondents is 37,572 due to 1264 missing values on usual hours worked per week. c The number of respondents is 3778 due to 166 missing values on usual hours worked per week. d The number of respondents is 37,055 due to 1781 missing values on weekly earnings (2015$). e The number of respondents is 3750 due to 194 missing values on weekly earnings (2015$).

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FIGURE 1.1  Employment patterns of 18–34 years old by sex: 2003–15.

5 Results 5.1  Employment and economic characteristics, 2003–15 Labor statistics from the ATUS reflect the impact of the global financial crisis on young adults. Unemployment and dropping out of the labor force increased for men and women in the late 2000s and only by 2014 or 2015 showed signs of increased employment (Fig. 1.1). Even among those with employment, hours worked and earnings dropped during the GFC and its aftermath (Fig. 1.2). While increase in unemployment affected both men and women during this period, young men showed larger and more sustained impacts. For example, average earnings and hours worked have not markedly changed for employed females, but employed males are earning less today than before the crisis and working fewer hours. These results concord with the literature showing strong gender differences in the impacts of the financial crisis (Albelda, 2013; Bettio and Verashchagina, 2014).

5.2  Work time use segmentation A solution with nine clusters provided the best balance between parsimony and representing behavioral patterns (Fig. 1.3). As expected, a large portion of the sample worked a traditional workday. Clusters 1 and 2 averaged 8 hours of work and differed only slightly in their start time. Cluster 6 worked a long day (9.8 hours) with a median start at 8:15 a.m. and end at 18:30 p.m.

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FIGURE 1.2  Weekly earnings and hours worked, employed of 18–34 years old: 2003–15.

FIGURE 1.3  Work time segments: 18–34 years old.

Together these three clusters represent just over half (51.1%) of the sample. These three clusters share similar characteristics. They have high proportions of full-time workers, those employed in management or professional roles, and, not surprisingly, have the three highest average weekly earnings (Table 1.2).

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TABLE 1.2 Economic characteristics by cluster.

Segment

Usual weekly % In % Emp hours school full-time worked

% Professional, Weekly management, earnings business and (2015 $) financial

% Service, sales and related

1: 8–5

11.7

93.7

42.1

861

45.7

13.8

2: 7–4

10.4

90.0

41.2

820

40.0

17.4

3: 6–2

10.1

85.0

40.9

679

21.4

23.0

4: 11–8

26.9

62.0

38.0

527

29.7

25.3

5: Night

12.9

86.6

43.0

705

19.9

36.6

6: Long

11.3

89.9

45.6

928

48.3

12.5

7: Part (a.m.)

19.3

51.9

31.6

525

36.5

23.4

8: Part (p.m.)

32.0

57.6

35.4

478

19.5

38.0

9: Atypical

13.5

82.2

45.1

739

40.4

21.2

Total

15.6

78.5

39.9

725

37.1

20.8

The remaining clusters differ in the timing and time spent at work. Individuals in cluster 3 and 4 work an average of 8.3 hours and typically start around 7 a.m. (Cluster 4) or 8 a.m. (Cluster 3). Individuals in this cluster have the highest number of children on average (1.2). Clusters 5 and 6 work long hours (9.7 and 9.8 hours respectively) but shifted to the evening and night hours. Individuals in Cluster 4 have the second highest rate of being enrolled in school (26.9%) and low weekly earnings ($527). Cluster 5 works in nights and has the highest proportion of respondents reporting they are African-American (23.4%) (Table 1.3). Clusters 7 and 8 represent part-time work in the morning and afternoon, respectively. Both segments have a higher than average proportion of Hispanics and low weekly earnings. Cluster 8 also has the highest proportion working in service and sales (38.0%). Cluster 9 represents atypical work increments scattered throughout the day and captures many individuals who report work but are not employed or are looking for work.

5.3  Commuting in peak periods Large differences exist across clusters in the concentration of start and end times in traditional peak travel periods. Segments with the highest proportion of workers in retail and sales (Clusters 4, 5, 8) have very few individuals starting or ending work during these periods (Table 1.4). These asynchronous patterns may allow for faster travel for individuals with car access who can avoid the

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TABLE 1.3 Demographic characteristics by segment.

Segment Age

% % % # of White Black % Never % Children % Some only only Hispanic married Female in HH college+

1: 8–5

29.0

82.0

12.2

16.2

43.9

49.6

1.0

75.5

2: 7–4

28.5

84.7

9.2

21.8

50.3

49.3

0.9

72.0

3: 6–2

28.3

80.2

14.2

24.3

47.6

38.6

1.2

53.6

4: 11–8

26.1

73.1

17.8

17.3

77.4

52.4

0.6

67.8

5: Night

27.3

71.3

23.4

14.4

60.8

36.4

0.9

64.6

6: Long

28.5

76.9

13.1

20.1

50.7

45.0

0.7

75.3

7: Part (a.m.)

27.5

77.7

14.4

19.9

54.0

56.3

0.9

65.1

8: Part (p.m.)

25.4

76.6

15.4

22.4

70.6

52.9

0.6

59.9

9: Atypical

28.0

74.2

18.4

12.3

52.2

42.9

0.8

68.7

Total

27.9

78.9

13.9

19.2

53.6

48.8

0.9

68.8

congestion associated with peak periods. However, for individuals without or with unreliable auto access, traveling outside peak periods often incurs a time penalty or the inability to reach needed destinations (Kaza, 2015). The literature on labor markets suggest these type of work time patterns may be expanding and thereby exacerbating access concerns. Data on modal travel time show high rates of auto usage and access across all clusters (Table 1.4). However, the clusters with non-standard or long work hours (11–8, long and night) have the lowest proportion of trips in autos. The data also reveal an inverse correlation between hours worked and number of daily trips. Presumably those with longer work hours have less time available for other activities and the travel required to undertake those activities.

6  Discussion and conclusions Labor market analyses show a nearly 50-year pattern of increased precarity among young people. While the extreme effects of the GFC on the number of unemployed young people may recede, there is likely to be continued growth in temporary, part-time, low-wage jobs in the clerical and routine sectors. Our analysis showed that many young adults start and end work outside traditional peak periods. In a fully auto-oriented society, this might not be problematic— and even might present the advantage of avoiding congestion. However, those

The changing nature of work and time use: implications for travel demand Chapter | 1 13

TABLE 1.4 Work and travel patterns by cluster.

Segment

%

Work hours

% Work start (6:309:30)

1: 8–5

20.4

8.5

92.8

52.1

4.0

3.7 (92.5)

70.8

66.8 (94.4)

2: 7–4

15.4

8.3

92.4

42.5

3.9

3.7 (94.9)

73.3

69.9 (95.4)

3: 6–2

6.8

8.3

17.6

6.7

3.7

3.6 (97.3)

74.4

71.5 (96.1)

4: 11–8

5.3

7.8

7.2

29.3

3.5

3.1 (88.6)

61.4

56.3 (91.7)

5: Night

5.3

9.7

0.5

0.0

3.5

3.3 (94.3)

67.6

64.2 (95.0)

6: Long

15.3

9.8

68.1

69.6

3.5

3.2 (91.4)

63.1

57.6 (91.3)

7: Part (a.m.)

17.8

4.4

45.7

23.7

4.8

4.4 (91.7)

84.3

76.9 (91.2)

8: Part (p.m.)

9.7

6.8

2.3

4.7

3.8

3.5 (92.1)

69.4

62.3 (89.8)

9: Atypical 4.1

8.4

28.2

2.5

3.9

3.7 (94.9)

71.5

68.4 (95.7)

100.0 7.8

54.6

34.6

4.0

3.7 (92.5)

71.9

66.9 (93.0)

Total

% Work end (16:3019:30)

Daily auto Daily trips (% trips of total)

Auto Daily travel travel time (% time of total)

without reliable car access, will face lower levels of transit service that may in turn restrict their employment options. What do these findings mean for transport planning practice and research? First, they show the need for transport planners to consider how the story of changing labor markets may affect travel patterns and resulting infrastructure needs and infrastructure planning tools. In the short-term, this may require efforts to incorporate time-based accessibility analyses into transit operations planning. These temporal accessibilities could then be compared to the travel patterns of transit-dependent population. If planners observe mismatches, service schedules could be adjusted. In the longer-term, planners need to attend to employment projections in demand forecasting processes. Most modeling efforts require construction of future populations including their employment characteristics. These estimates should account for the literature on labor market restructuring, particularly

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PART | I  Motivations

around increased part-time employment. But changes in the labor market also present fundamental challenges to the ability of demographers and planners to project employment—particularly at the small geographic scales required by travel demand models. This, in turn, highlights the importance of quantifying and communicating uncertainty in demand estimates.

References Albelda, R. (2013). Gender impacts of the ‘great recession’ in the United States. In Maria Karamessini & Jill Rubery (Eds.),Women and austerity: The economic crisis and the future for gender equality. London: Routledge. Bettio, F. & Verashchagina, A. (2014). Women and men in the “Great European Recession.” In Maria Karamessini & Jill Rubery (Eds.) Women and austerity:The economic crisis and the future for gender equality (57–81). London: Routledge. Blumenberg, E., Taylor, B. D., Smart, M., Ralph, K., Wander, M. & Brumbagh, S. (2012). What’s youth got to do with it? Exploring the travel behavior of teens and young adults (UCTCFR-2012-14). Los Angeles: University of California Transportation Center. Bureau of Labor Statistics (2016). American Time Use Survey User’s Guide: Understanding ATUS 2003 to 2015. Delbosc, A., & Currie, G. (2014). Changing demographics and young adult driver license decline in Melbourne, Australia (1994-2009). Transportation, 41, 529–542. Federal Highway Administration (2016). Travel monitoring: Traffic volume trends. Fry, R. & Passel, J. S. (2014). In post-recession era, young adults drive continuing rise in multigenerational living, Washington, DC: Pew Research Center’s Social and Demographic Trends project. Furlong, A. (2015). Unemployment, insecurity, and poor work: young adults in the new economy. In: J. Wyn & H. Cahill (Eds.) Handbook of Children and Youth Studies (p. 531–542). Singapore: Springer. Furlong, A., & Kelly, P. (2005). The Brazilianisation of youth transitions in Australia and the UK? Australian Journal of Social Issues, 40, 207–225. Halpin, B. (2014). SADI: Sequence analysis tools for Stata. The Stata Journal, 7(3). 546–572. Hofferth, S. L., Flood, S. M. & Sobek, M. (2015). American Time Use Survey Data Extract Builder: Version 2.5. College Park, Maryland: University of Maryland and Minneapolis, MN: University of Minnesota. Kalleberg, A. L. (2011). Good Jobs Bad Jobs: The Rise of Polarized and Precarious Employment Systems in the United States 1970s to 2000s. New York: Russell Sage Foundation. Kaza, N. (2015). Time dependent accessibility. Journal of Urban Management, 4, 24–39. Klein, N. J., & Smart, M. J. (2017). Millennials and car ownership: less money, fewer cars. Transport Policy, 53, 20–29. Kuhnimhof, T., Armoogum, J., Buehler, R., Dargay, J., Denstadli, J. M., & Yamamoto, T. (2012). Men shape a downward trend in car use among young adults—evidence from six industrialized countries. Transport Reviews, 32, 761–779. Lesnard, L., & Kan, M. Y. (2011). Investigating scheduling of work: a two-stage optimal matching analysis of workdays and workweeks. Journal of the Royal Statistical Society: Series A (Statistics in Society), 174, 349–368. Mcdonald, N. C. (2015). Are millennials really the “go-nowhere” generation? Journal of the American Planning Association, 81, 90–103.

The changing nature of work and time use: implications for travel demand Chapter | 1 15 Milligan, G. W. (1980). An examination of the effect of six types of error perturbation on fifteen clustering algorithms. Psychometrika, 45, 325–342. Office for National Statistics (2015). Families and Households: 2015. London: Office of National Statistics. Polzin, S. E., Chu, X., & Godfrey, J. (2014). The impact of millennials’ travel behavior on future personal vehicle travel. Energy Strategy Reviews, 5, 59–65. US Census Bureau (2016). Median age at first marriage: 1890 to present. Vij, A., Gorripaty, S., & Walker, J. L. (2017). From trend spotting to trend’s plaining: Understanding modal preference shifts in the San Francisco Bay Area. Transportation Research Part A: Policy and Practice, 95, 238–258.

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Chapter 2

Integrating health into metropolitan transportation planning Catherine Rossa, Peter Hyltonb, Farran (Fangru) Wangc a

School of City and Regional Planning/Civil and Environmental Engineering; Center for Quality Growth and Regional Development (CQGRD); College of Design, Georgia Institute of Technology, Atlanta, GA, United States; bHigh Street Consulting, Columbia, SC, United States; cPinterest, San Francisco, CA, United States

1 Overview An individual’s health is the product of individual choices, genes, and environment overlaid on a backdrop of their social and economic reality. Good health results from the confluence of many factors, only some of which the individual directly controls. In larger populations, it is useful to think of these social, economic, and physical settings that define our health determinants and also underlie our ability or propensity to make healthy choices. The built environment is one of the determinants that influences how people exercise, the quality of the air they breathe, their likelihood of suffering injury and their ability to reach opportunities to maintain or improve their health and resilience. The built environment’s form and transportation networks are very relevant to population health (Frank & Engelke, 2001; Jackson, 2003). Urban planning initially recognized the ways in which its work impacted population health, but it shifted its focus in the middle of the last century in response to a modernist focus on efficiency. While efficiency is a very worthy goal, it is not the entirety of the public good related to the built environment. While the focus was turned to efficiency, a health-promoting built environment emphasizing moderate density, multi-modal transportation and mixed land use was abandoned in many American cities. Today planning faces the challenge of maintaining efficiency while updating planning agency goals, metrics, workflows, and organizational structures to support health through the built environment. This chapter illustrates how health can be incorporated to guide decision making affecting transportation and the built environment through a case study of the Atlanta Regional Commission (ARC) and its PLAN 2040. The chapter Transportation, Land Use, and Environmental Planning. http://dx.doi.org/10.1016/B978-0-12-815167-9.00002-5 Copyright © 2020 Elsevier Inc. All rights reserved.

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PART | I  Motivations

extends the HIA concept into decision making by imagining a framework applicable at ARC or other metropolitan planning organizations (MPOs) that wish to incorporate health into interregional decision making. The goal is not to assert a single structural solution, but to propose metrics, workflows, and frameworks applicable with variations at many transportation agencies that can anchor health in decision making. MPOs are highly diverse in structure, goals, metrics, and decision making methods, but the ARC case study illustrates approaches for how other MPOs or planning organizations might integrate health into their transport planning process.

2  Previous work 2.1  Health and the built environment Health is not just the absence of illness, but a complete physical, mental, and social wellbeing (WHO, 1946). A foundation of urban planning is firmly rooted in public health. Communicable diseases, which are among the greatest threats to health, are often closely related to spatial factors of the city, such as the location of industries that emit pollutants. Early urban planning efforts sought to address poor hygienic conditions, overcrowding, residential proximity to manufacturing plants and many other threats that encouraged the spread of communicable diseases. Now, the conventional low-density, single-use zoning put forward as one attempt to reduce the spread of communicable disease has resulted in the sprawled pattern of urban landscapes. In these landscapes driving replaced walking and transit as the dominant form of transportation, and few destinations were accessible within walking distance. Results of this disconnect include the increase in air pollution from cars, more traffic fatalities, and decline in Americans’ average daily physical activity. This urban form also severely impairs the mobility of families that have limited travel mode choices and their accessibility to jobs and services, exacerbating socio-economic and health disparities. As the health professions advanced and living conditions changed, the planning profession focused more on efficiency, equity, and other very important considerations. However, in addressing these worthy causes, health is often left out of conventional planning practice. The built environment—both transportation and land use patterns—influences health through a variety of vectors. Since the built environment is constructed, there is no need to assume it has to be the way that it is (Jackson, 2003). Without presenting an exhaustive array of evidence, the built environment’s influence on health can be broadly understood through physical activity (Berke, Koepsell, Moudon, Hoskins, & Larson, 2007; Frank, Engelke, & Schmid, 2003; Gordon-Larsen, Nelson, Page, & Popkin, 2006; Handy, Boarnet, Ewing, & Killingsworth, 2002), traffic and accident safety (Ewing & Dumbaugh, 2009; Miranda-Moreno, Morency, & El-Geneidy, 2011), pollution and air quality (Frank et al., 2006; Frank & Engelke, 2005), and accessibility to opportunities (Jones et al., 2008; Preston & Rajé, 2007). There are a myriad of connections between built environment factors, including density, mode split, distance to work, and jobs-housing balance

Integrating health into metropolitan transportation planning Chapter | 2

19

on the one side, and health outcomes to include obesity, heart disease, injury and reduced resilience on the other. This chapter briefly addresses each of these but more comprehensively argues that organizations responsible for shaping the built environment must be aware of these connections and adopt a mission to improve health but, they may be more effective by structuring their workflow and decision making to continuously and cross-functionally address health.

2.2  Health in the planning process Land use and transportation can affect health in unexpected ways that are not typically incorporated into conventional planning practice. In many ways, the built environment results in part from decades of market-driven development framed by planning practice contributing to the degradation of health. As priorities changed overtime, land use and transportation plans resulted in unintended negative consequences for health. The social and economic environment, physical environment, and people’s individual characteristics and behaviors are all determinants of health (WHO, 2017). Now, as the paths from planning and project selection to health, wellbeing, and quality of life are becoming clearer, planners and policymakers at every level have the responsibility to use this information to make better decisions about the built environment. The inclusion of health considerations in regional planning efforts is especially important for improving the health conditions of Americans, as the majority of population and economic output concentrate in the largest 100 metropolitan areas (Metropolitan Policy Program, 2007). Planning goals are changing, but planning practice and techniques are not keeping pace. Even as goals have broadened, the measures used to evaluate progress and guide planning often have not, leading to a situation in which MPOs have stated health related goals but often lack the intent or methods to measure them (Handy, 2008). Of the four large MPOs evaluated by Handy (2008), two have goals that explicitly address health, air quality or related issues. More recent work has shown that health impacts of transportation are normally inadequately captured in long-range transportation plan goals. There is typically the lack of focus on air quality and physical activity compared with traffic safety and accessibility. Performance measures for physical activity and public health are especially lacking (Singleton & Clifton, 2014). According to Handy (2008), goals that have performance measures that can be evaluated in regional travel demand models receive the most weight in decision making, whereas goals without performance measures receive the least (Handy, 2008). Congestion management may be driving transportation planning despite stated attempts to look at health and other quality of life factors. Multiple scales present another challenge to health integration into the planning process. Many health issues are locally concentrated, and can be neglected by regional planning processes unless the regional organizations can integrate local and regional priorities, as well as actions by citizens and other organizations at multiple scales (McAndrews & Marcus, 2014).

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PART | I  Motivations

Health might be better positioned to guide planning by improving public participation (Singleton & Clifton, 2014) since the public is ostensibly aware of its own needs and wellbeing, although public participation will be insufficient if supportive actions are absent (McAndrews & Marcus, 2014). Centering health in planning requires not only stated health goals, but also creating performance measures to support them and structuring organizations to address health with data, analysis and action.

2.3  Health impact assessment (HIA) A health impact assessment (HIA) is a process for determining the potential effects on human health of a policy, plan, or project with data analysis and stakeholder involvement (National Research Council, 2011). HIA connects a decision with changes in health determinants that will affect specific populations, which can be segmented by socioeconomic characteristics (e.g., age, race, income) or location (e.g., neighborhood). A set of recommendations to improve the project’s health impact is the HIA’s main output. It can inform decision makers, stakeholders, and the general public about this specific project or future efforts. HIAs include six sequential steps: (1) screening defines whether a project will have health impacts and whether developing HIA can reveal useful information to the stakeholders and decision makers; (2) scoping delineates the scope of health effects that will be analyzed in the HIA, the focus population, the HIA team, data sources, methods, and alternatives under consideration; (3) assessment has two steps: the first assessment step describes the health status of the populations that may be affected by the decision, and the second step assesses impacts based on changes in the health determinants; (4) recommendations identify design or action alternatives that could be implemented to promote or manage health effects; (5) reporting documents present the findings and recommendations to stakeholders and decision-makers; and 6) monitoring and evaluation take different forms depending on the HIA, but fundamentally they ensure that the HIA tracks and encourages adoption of HIA recommendations, and verifies whether the effects that occur are those identified or predicted by the HIA in order to inform future HIAs and allow new strategies to address emerging and associated health problems. Although HIA is not the only way to promote health in projects and planning, a fairly large and growing list of health departments are accepting it as a model. For one thing, the close linkage between the built environment and physical activity allows HIA to be used as an intuitive and analytical tool to promote active transportation. In addition, HIA can be used to support an array of different types of projects that feature different policy prioritizations. The San Francisco Department of Health uses HIA in project and facility development to promote active transportation modes of walking and biking (Dannenberg et al., 2008). Similarly, London’s health department employs HIA to support active transportation in the city’s transportation planning activities (Mindell, Sheridan, Joffe,

Integrating health into metropolitan transportation planning Chapter | 2

21

Samson-Barry, & Atkinson, 2004). HIA was also used to enhance after-school and walk-to-school programs in California (Dannenberg et al., 2008). The Center for Quality Growth and Regional Development (CQGRD) at the Georgia Institute of Technology used HIA to build the argument for incorporating active living principles into the City of Decatur’s transportation plan (CQGRD, 2007) and again more recently to measure health impacts of freight movement in Chatham County and Atlanta, GA (Ross & Smith, 2016a, 2016b). The HIA of the Atlanta BeltLine, also conducted by CQGRD, has shown the advantage of design and project management principles that promote physical activities (Ross et al., 2007). The Atlanta Regional Commission (ARC) is incorporating health effects on communities into its regional plans, and in a similar vein the Nashville MPO crafted their 2015 Regional Transportation Plan explicitly using HIA to improve health (Nashville Area Metropolitan Planning Organization, 2015). There are other examples of transit agencies leading HIAs including the Massachusetts Bay Transit Authority, Greater Boston’s public transportation system (MAPC, 2012). These are fairly recent examples demonstrating the value of HIA as a policy intervention strategy through its influence on elaborating health targets, revealing health concerns, establishing health criteria, and incorporating health consideration into project selection.

3 Methodology This chapter uses a case study of the Atlanta Regional Commission (ARC) to illustrate how health can be systematically incorporated into its workflow, structure and decision making. The case study approach is appropriate because of the diverse resources, structures, programs and decision making procedures within MPOs and other planning organizations. ARC’s long-range plan, called PLAN 2040, must be central to its health decision making because the plan addresses ARC’s multiple functions. These functions include its MPO-designated transportation planning function as well as its other state or regionally defined roles in land use, housing, greenspace, water, and air quality. Not surprisingly, PLAN 2040 has numerous direct and indirect health implications. The PLAN 2040 includes a Regional Transportation Plan through 2040, a six-year priority Transportation Improvement Program (TIP), and the comprehensive Regional Development Plan (RDP). The HIA evaluates potential effects of the PLAN 2040 on the regional population health via changes in health determinants. Moreover, the HIA is linked to both transportation and the built environment since it can be used as the first tool to review the region’s comprehensive plan. Researchers at CQGRD also identified a set of high-priority health determinants related to planning, land use, and transportation by conducting a thorough review of health-related research (Ross & Elliott, 2012). This chapter also includes an implementation plan to reveal areas of opportunity for incorporating health into MPOs’ transportation decision making

22

PART | I  Motivations

FIGURE 2.1  Connection between PLAN 2040 and ARC implementation opportunities. (Constructed by Author.)

processes and to leverage ancillary organizational functions such as influence over land use to promote health. The implementation plan derives directly from the HIA since it prioritizes the HIA’s 200+ multi-functional recommendations for improving health impacts, and it proposes structures that could assist ARC or other planning organizations to incorporate health considerations into decisions across the organization. Both the PLAN 2040 HIA and the implementation plan were supported by funding from the Health Impact Project, a collaboration of the Robert Wood Johnson Foundation and The Pew Charitable Trusts. Both the HIA and the implementation plan are oriented towards integrating research, analysis, and organizational structures to produce long-term improvements in health and health-related decision making. The PLAN 2040 establishes goals and strategies for health, but the HIA and implementation steps systematically promote health. The region’s health determinants were categorized to include: access, equity, and economy; active living; ecology and environmental quality; and civic life and social connections. There are many links between the different health influences detailed by the PLAN 2040 HIA and the identified implementation opportunities, and these linkages are mediated by vectors that pass through physical activity, pollution, safety, and accessibility, as described in Fig. 2.1 below. Most implementation steps impact several of these vectors and several associated themes. For example, ARC’s Livable Centers Initiative (LCI) promotes dense and ‘centered’ urban development, as well as intersection upgrades. This can improve traffic safety and physical activity locally, while also reducing driving and regional air pollution.

4 Findings We rely heavily on examples from ARC and the PLAN 2040 to illustrate the proposals, but almost all the findings have implications that may be generalized. The findings concentrate on three focus areas: target areas, project selection, and organizational structure. Each of the three is critical for successfully delivering HIA and considered together they reflect the general picture of how health considerations can be incorporated into the planning process.

Integrating health into metropolitan transportation planning Chapter | 2

23

4.1  Target areas Through the review of over 200 recommendations included in the HIA conducted for the PLAN 2040 (Ross & Elliott, 2012), we categorized the planning topics that target health assessment more explicitly or those that have the great opportunities to improve the region’s health into five broad areas as summarized below. 1. Transportation mode share reflects people’s aggregate travel behaviors, and it is influenced by socio-economic status, transportation, land use, and built environment factors. Travel mode shares are highly skewed towards automobiles in most American cities and in the Atlanta region. It is a health priority to diversify mode share to grow physically active transportation modes particularly walking and biking. Given the direct influence of physical activity on long-term health, active transportation could improve health outcomes for large population segments. Moreover, mode shares can be easily quantified via either United States Census Data (USCD), regional travel surveys, or local transit ridership, and can be used as an intuitive metric in project evaluation, selection, and target setting processes. 2. Land use directly influences people’s every-day physical activities. Abundant literature has shown the positive effect of mixed land use and better destination/park accessibility on the individual’s tendency to exercise and choose active travel modes (Heath et al., 2006). The PLAN 2040 HIA recommends targeting developed centers throughout the region to counter the trend of single-use, low-density land development that impedes physical activity, use of alternative modes and pedestrian and/ or bike accessibility. In a more general sense, land use characteristics that encourage people to exercise more by providing accessibility to playgrounds / parks, or those that may encourage a shift to more active travel modes such as transit-oriented development (TOD), can be beneficial. 3. Roadways design has a substantial and direct influence on health because it affects traffic accidents, crashes, and the spatial distribution of emissions and noise. The HIA recommends that roadway design address safety not through separation of modes (e.g., guardrail installation between roadway and sidewalk), which can discourage active transportation, but through design that allows multiple modes and activities to coexist in a single right-ofway. The idea of ‘context sensitive design,’ where the roadway is designed with these different uses in mind, was employed as a banner to allow design specifications to vary based on purpose. For example, higher design speeds are allowable away from centers but where high non-automotive activity is expected low design speeds and traffic-calming devices are encouraged. 4. Connectivity through street network is identified as the fourth health domain that influences positive health outcomes. Most of the Atlanta region has a street network with very low levels of connectivity, which impairs accessibility, especially for non-automotive modes. The PLAN 2040 HIA recommends improving accessibility by enhancing street network connectivity.

24

PART | I  Motivations

5. Finally, parking is another factor that often interlocks with many other built environment factors and has noticeable influence on people’s travel behaviors and life styles. In the Atlanta region, parking is readily available and typically required in local regulations discouraging non-automotive modes. Therefore, evaluating the potential room for parking reduction should be considered as an option for promoting better health outcomes in HIA. These five areas are often included in regional plans and may all positively influence regional health. Incorporating health into the planning of these areas is not only consistent with existing planning, but also helps to comprehensively reveal a project’s potential impacts. ARC presents a good example of an MPO incorporating health considerations into project selection and its other programs. For example, ARC has launched the Livable Centers Initiative (LCI) and encourages transit-oriented development to promote healthy trends in the five mentioned areas. Transfer of Development Rights (TDR), which has been implemented in part of the Atlanta region, also has potential at a regional scale to encourage in-fill development. Although the proposals address specific ARC structures and functions, most planning organizations perform or could perform similar processes; therefore, the proposals could also be valid in other settings with relatively minor adaptation.

4.2  Project selection Project selection is one of the most important activities since it typically encapsulates the largest funding sources and leverages federal and matching funds. We rely heavily on ARC’s project selection process to illustrate how health can be incorporated. The example is generalizable because MPOs’ project selection processes are often quite similar. ARC’s existing project selection process involves four key decision points (KDP), of which two are significant for health: funds are divided among different project types (KDP1); second, projects types are filtered for policy priorities (KDP2); third, projects’ performance is evaluated based on pre-identified metrics (KDP3); and fourth, funds are allocated to top-performing projects (KDP4). Not all steps apply to each project type, so the only project types that apply to a given step are those that are shaded (on the left of Fig. 2.2). Fig. 2.2 also summarizes our proposals. The first decision point of a project selection process is often to divide funds among different project types. Here, it is important that governing boards and upper management periodically re-evaluate the project types to ensure that funding distribution is aligned with health goals. Some organizations are already doing this informally, but in many cases there is room for more formal or more regular review. Analysis of past projects’ observed health effects and the region’s evolving health profile can highlight opportunities for improving health through funding allocation. One of the continuing challenges will be prioritizing health with other policy goals in project selection (e.g., travel time, air

Integrating health into metropolitan transportation planning Chapter | 2

25

FIGURE 2.2  Proposed project selection changes. (Constructed by Author.)

quality). Prioritizations remain inherently political despite data analysis, which is why governing boards ultimately oversee discretionary funding allocations by project type. The second decision point intends to promote projects that align with policy documents. The degree to which health considerations can be incorporated will vary based on previously adopted policies. For example, if a policy goal of maintaining air quality for sensitive uses (e.g., schools, senior facilities, hospitals) has already been established, the projects that would exceed the proscribed pollution concentrations in sensitive areas would be eliminated. The health themes from Fig. 2.1 (active transportation, clean air, and access to social and economic opportunities) should therefore have associated health policies. The third decision point is to evaluate project performance, which at many organizations relies on quantitative performance measures that allow side-by-side comparison of project alternatives. Cost-benefit analysis is a common method used to compare projects. For example, project evaluation in the PLAN 2040 entails calculating transit or road projects’ cost-benefit ratios accounting for mobility, connections, safety, economic growth and environment/community impacts. Project types for which a cost-benefit ratio cannot be reasonably calculated will omit this decision point. Fortunately, though health data are often not publicly available, there are many other data sources that can be used for constructing health-related metrics to be used in a cost-benefit analysis for project evaluation. For example, air pollution (e.g., air emissions per capita derived from the travel demand model and emissions models) and physical activity (e.g., population at risk for low physical activity based on walking, biking, and public transit mode shares) may both be measured and included in cost-benefit calculations. Many regions already have air pollution models, and there is an extensive literature

26

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establishing coefficients that describe the extent to which population exposure to air pollution can be associated with disease. A similar approach can be followed to estimate how changes in physical activity will impact chronic disease. For both air pollution and physical activity the difficulty of establishing strictly causal links between changes in air pollution and physical activity and health outcomes, due to intervening variables, does not negate the benefit by estimating associations that may reflect the direction and scale of impact. After funding is allocated (fourth key decision point), the final retrospective step in project selection is to evaluate the project’s observed impact on health. Retrospective evaluation improves future work because it can reveal discrepancies between predicted and observed health impacts to calibrate future assessments. If a retrospective health evaluation is conducted several years after project implementation, the agency will build a continually improving set of knowledge and metrics linking project selection to health. The retrospective evaluation can reveal health impacts by project type, which the governing board can consider in allocating funding among project types (first decision point). The retrospective evaluation can also calibrate future forecasts in the third decision point. Incorporating retrospective evaluation of health outcomes into the first and third decision points will increase the chance that a project or project type with greater health benefits will be funded in future project selection iterations. The format of the retrospective evaluation will depend on the project types, which are highly varied, and it will be contingent on data resources in health, transportation and land use.

4.3  Organizational structure Health outcomes are shaped by many functions within planning organizations, and the cross-functionality makes it hard to address even in the organizations that have most successfully broken down functional silos. The right structure can ensure that health remains front-and-center on the agenda. Within ARC, at least six of its committees have work that addresses health more or less directly (Aging & Health Resources Committee, Transportation & Air Quality Committee, Regional Transit Committee, Community Resources Committee, Transportation Coordinating Committee, and Land Use Coordinating Committee). ARC’s commitment to health has overcome functional fragmentation, even though coordination around an overarching topic like health could easily forestall even the best intentions. One solution to health’s multi-functionality would be to create a coordinating committee that represents a unified voice of health in the organization. The coordinating committee could provide advice to the governing board and the stakeholders about the likely health impacts of a project or policy. It can also serve as a connection among all other committees. The Health Coordinating Committee as applied to ARC links the six most related committees’ work coherently around health (as shown in Fig. 2.3). The committee’s primary concern

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FIGURE 2.3  Interaction between proposed “Health Coordinating Committee” and existing committees. (Constructed by Author.)

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would be to align different projects’ functions and interactions with the goal of promoting regional health. Health-related coordination can exist not only among committees but also among entire staff or departments that affect functional areas. In the example of ARC, there are three major staff centers (Center for Livable Communities, Center for Community Services, and Center for Strategic Relations), and the first two directly influence the transportation, development and aging decisions that would typically affect health. The Center for Community Services is concerned with the needs of vulnerable populations, economic development, and social health while the Center for Livable Communities focuses more on the built environment. The two centers may influence social health in different ways: the Center for Community Services would directly advocate for improving population health, while the Center for Livable Communities may impact social health through plans surrounding urban form, accessibility, and land development. The Health Coordinating Committee is where these two centers can exchange inputs and build common ground. A Health Coordinating Committee that bridges departments can consistently integrate health into the work of the other units and also synthesize data and analysis. Departments that do not directly address development and urban form can also contribute to supporting health considerations. For example, ARC’s Center for Strategic Relations communicates with community organizations and citizens. It may influence health by connecting grassroots citizens and organizations with ARC’s health planning process and facilitates health considerations by soliciting input as well as data. Fig. 2.4 presents the connections among the

FIGURE 2.4  Internal staff support for Health Coordinating Committee. (Constructed by Author.)

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FIGURE 2.5  Health partner support of Health Coordinating Committee. (Constructed by Author.)

three centers of ARC and the role of the Health Coordinating Committee in connecting them to health promotion. Finally, in our explicit focus on planning’s impact on health, we must not forget that other organizations also affect health. These organization’s knowledge, data, and community relationships can increase planning’s effectiveness just as planning can bring a new spatial urban form approach to their work. Any planning organization with health goals can reach out to establish mutually beneficial long-term partnerships with public health entities including hospitals, non-profits, and other government organizations (e.g., departments of public health; departments of community affairs). Many of these organizations collect data and others serve as gatekeepers for communities that are important to a goal of enhancing stakeholder engagement. Involving different stakeholders in health-related planning processes is critical because in addition to increasing the diversity of input it also builds a foundation for implementing long-term plans. Including stakeholders may start with invitations to them to participate in meetings and discussions about healthrelated topics. In the example of ARC, major organizations not represented on the ARC board have been included in either a voting or non-voting capacity (see Fig. 2.5). For example, the Transportation & Air Quality Committee includes representatives from the transit agencies, the Georgia Department of Transportation (GDOT), and environmental agencies in Georgia. A Health Coordinating Committee can employ a similar approach. Specifically, the Health Coordinating Committee can solicit health advice and insights from major state and county health organizations and communicate the same to the MPO’s staff and board members. The committee can also look for participation from organizations

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such as hospitals, school boards, and non-profits, which could represent additional corporate or grassroots perspectives.

5  Policy implications Within the federal transportation planning process, all MPOs and state Departments of Transportation (DOT) are responsible for transportation project selection and prioritization. Methods for prioritization and improvement range from highly data-driven and formulaic to expert or politics driven. Because project selection is one of the key planning responsibilities that leverages federal, state, and local funding, it presents a key opportunity to shape regional health. Health is not explicitly considered in project selection in many organizations, which means that project health impacts are not considered alongside measurable effects in decision making. Health can be integrated into steps that are commonly found in project selection through ‘health performance measures’ and through periodic review and continual commitment by governing boards. There is great inertia in the post-war technocratic paradigm in planning that divides the built environment into siloed specialties (e.g., land use, transportation, and environment) and most heavily considers measurable phenomena. This paradigm makes inclusion and consideration of health in planning different because health is holistic. Broadly speaking, the solution is not to eliminate the specialties because the built environment is far too complex for generalists. Nor is the solution to discard data in favor of the subjective, which would lose valuable insights. Nor should we aim for heroic feats of individual effort to overcome the institutional current. Rather, we should institutionalize coordination among the specialties, not to reverse them but to link them. Once joined, we require the work of heroic individuals so health will have a voice at the table. Another approach is to quantify the built environment’s effect on health. Other built environment imperatives (e.g., efficiency, air quality) have mobilized research and resources to ultimately produce enduring models evaluating complex phenomena. Travel demand models are among the oldest and best anchored in the planning profession, and air quality, land use, and economic development models are also strong. Health is at least as complex of a phenomenon as travel behavior or air quality, perhaps even more so, because of individual-level impacts and unknown variables. Yet, models need not be perfect to be useful. In fact, all models are approximations, but many represent reality sufficiently to be valuable. It is time to generalize health analysis away from the exclusive domain of HIAs and into planning more broadly with HIAs being a part of the planning process. The technical foundation for quantifying the health contribution of a project already exists in the form of travel demand models with active modes, air quality models and dose-response functions linking pollutant exposure or behaviors with health outcome risks. The profession

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has overcome challenges in integrating similar datasets, and it is appropriate to do so when integrating health into planning practice and the work of MPOs. It will raise health’s prominence in organizational decision making when estimates of health impact are displayed alongside travel time savings or economic impact. As the saying goes, “what gets measured, gets managed.” Health modeling brings health to the decision makers’ table while conforming to the general promotion of the seemingly objective (i.e. data) over the seemingly subjective (which is normally immeasurable or not measured). The ARC example demonstrates that health effects are often quantifiable with valid data, so it is not difficult to incorporate it into metric-based project evaluation and comparison. Many of the necessary models and research present a great opportunity that only needs attention and administration. Health impact is a valid and measurable criteria alongside other considerations in the project selection process. The organizational structure is also critical as the cross-functional nature of planning organizations makes it a challenge to integrate health considerations consistently across functional silos. One immediate step to make the incorporation of health viable is to create a permanent unit charged with promoting regional health by connecting it to the organization’s other planning functions. This coordinating committee provides a unified voice of health in the organization that is built upon comprehensive analysis and input from its functions. The coordinating committee may also involve all health-related stakeholders to integrate their abilities and generate synergies. Finally, the committee can establish two-way communication about health with citizens and community organizations thereby contributing to building a foundation for the design and implementation of future projects and work. The structure of how the Health Coordinating Committee works with other committees within an MPO can be varied, but it should be endowed with the necessary power to influence organizational priorities and outcomes since it is the voice for health. Health in planning requires mobilizing resources and coordinating across functions and stakeholders, so it needs to have an open and inviting venue that connects different parts. It also needs to have tangible criteria and even hierarchical requirements that prioritize health in the conversation even when conflicts appear within the organization.

6 Conclusions There is no one-size-fits-all for the incorporation of health into MPOs, partially because the existing decision making criteria and structures are so different. However, there are broad lessons and guidance for adding health into planning organizations. It is not enough to simply set a goal. Appropriate measures must exist to make an evaluation of progress possible. We proposed measures for periodic evaluation and building some of these measures explicitly into the project

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selection process, which will give them strength. Health is a commonly stated planning goal even if it is not part of the institutional process. There is still exciting planning work occurring around health in many organizations, and where the structure is lacking it is often a credit to the staff’s or leader’s energy and vision to achieve health-related aims despite inertia. This is made easier if planning organizations centralize health in their processes. Planning organizations are typically not designed around health, so the factors influencing health are siloed. Steps have to be taken to cut across the siloes so that the organization can view health holistically and coordinate across programs. The ability to cut across siloes is made more permanent when reflected in the organizational structure. Dramatic restructurings risk disrupting other workflows, so more modest structural changes and coordinating committees may be considered initially. Coordinating committees are attractive because they leave the rest of the structure undisturbed and add little or no staff while still creating an institutional cross-functional unit charged with identifying health synergies among the specialties. Health metrics require data on population wellbeing, the environment, natural resources, travel patterns, and land use. The planning organization may not always have all of the data internally requiring it to develop long-term partnerships with other function-specific organizations. Data is a logical entry point to partner with organizations with explicit health missions such as hospitals, clinics and government health departments. The partnerships can be mutually beneficial since they can better support population health by synchronizing their efforts in medicine, public health, and the construction of the built environment. The goal of planning organizations is not to become health organizations but rather to orient planning so that it supports an array of public health benefits, alongside efficiency, mobility, environmental protection and others. Obtaining these benefits is predicated on having a complete view of health through the conduct of data analysis and stakeholder engagement. Coordinating and sharing data with dedicated health organizations will help all organizations and fill resource gaps. “Health in all policies” can guide the planning profession back to its roots since health exposures have changed but not disappeared. If health becomes a focus in planning organizations, rather than the exception, the future of public health is promising. The health function will be evaluated and considered alongside other indicators in decisions affecting the built environment. With the passage of time, the built environment will be transformed. People will have more choice in travel and opportunities to use muscles instead of motors. Clean and refreshing natural reserves that promote healthy lifestyles will be nearby and accessible to people of all incomes. This new built environment will still be efficient, and dynamic; and it will also support and promote health. This changed built environment is more readily achievable by its integration into the planning profession, its organizations, and related disciplines.

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References Berke, E. M., Koepsell, T. D., Moudon, A. V., Hoskins, R. E., & Larson, E. B. (2007). Association of the built environment with physical activity and obesity in older persons. American Journal of Public Health, 97, 486–492. doi: 10.2105/AJPH.2006.085837. CQGRD (2007). Pathways to a Healthy Decatur: A Rapid Health Impact Assessment of the City of Decatur Community Transportation Plan. Atlanta: Georgia Institute of Technology, Center for Quality Growth and Regional Development. Dannenberg, A. L., Bhatia, R., Cole, B. L., Heaton, S. K., Feldman, J. D., & Rutt, C. D. (2008). Use of health impact assessment in the U.S. American Journal of Preventive Medicine, 34, 241–256. doi: 10.1016/j.amepre.2007.11.015. Ewing, R., & Dumbaugh, E. (2009). The built environment and traffic safety: A review of empirical evidence. Journal of Planning Literature, 23, 347–367. doi: 10.1177/0885412209335553. Frank, L. D., & Engelke, P. (2005). Multiple impacts of the built environment on public health: Walkable places and the exposure to air pollution. International Regional Science Review, 28, 193–216. doi: 10.1177/0160017604273853. Frank, L. D., Engelke, P., & Schmid, T. (2003). Health and community design: The impact of the built environment on physical activity. Island Press. Frank, L. D., & Engelke, P. O. (2001). The built environment and human activity patterns: Exploring the impacts of urban form on public health. Journal of Planning Literature, 16, 202–218. doi: 10.1177/08854120122093339. Frank, L. D., Sallis, J. F., Conway, T. L., Chapman, J. E., Saelens, B. E., & Bachman, W. (2006). Many pathways from land use to health: Associations between neighborhood walkability and active transportation, body mass index, and air quality. Journal of the American Planning Association, 72, 75–87. doi: 10.1080/01944360608976725. Gordon-Larsen, P., Nelson, M. C., Page, P., & Popkin, B. M. (2006). Inequality in the built environment underlies key health disparities in physical activity and obesity. Pediatrics, 117, 417–424. doi: 10.1542/peds.2005-0058. Handy, S. (2008). Regional transportation planning in the US: An examination of changes in technical aspects of the planning process in response to changing goals. Transport Policy, 15(2), 113-126. https://doi.org/10.1016/j.tranpol.2007.10.006 Handy, S., Boarnet, M. G., Ewing, R., Killingsworth, R. E. (2002). How the built environment affects physical activity: Views from urban planning. American Journal of Preventive Medicine, 23, 64-73. doi:10.1016/S0749-3797(02)00475-0. Heath, G. W., Brownson, R. C., Kruger, J., Miles, R., Powell, K. E., & Ramsey, L. T. (2006). The Effectiveness of Urban Design and Land Use and Transport Policies and Practices to Increase Physical Activity: A Systematic Review. Journal of Physical Activity and Health, 3, S55–S76. doi: 10.1123/jpah.3.s1.s55. Jackson, R. J. (2003). The impact of the built environment on health: an emerging field. Journal of Physical Activity & Health Impact, 93, 1382. Jones, A. P., Haynes, R., Sauerzapf, V., Crawford, S. M., Zhao, H., & Forman, D. (2008). Travel times to health care and survival from cancers in Northern England. European Journal of Cancer, 44, 269–274. doi: 10.1016/j.ejca.2007.07.028. MAPC. (2012). A healthy T for a healthy region. Boston, Massachusetts: Metropolitan Area Planning Council. McAndrews, C., & Marcus, J. (2014). Community-based advocacy at the intersection of public health and transportation: The challenges of addressing local health impacts within a regional policy process. Journal of Planning Education and Research, 34, 190–202. doi: 10.1177/0739456X14531624.

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Metropolitan Policy Program (2007). MetroNation: How U.S. metropolitan areas fuel American prosperity. The Brookings Institution. Mindell, J., Sheridan, L., Joffe, M., Samson-Barry, H., & Atkinson, S. (2004). Health impact assessment as an agent of policy change: improving the health impacts of the mayor of London’s draft transport strategy. Journal of Epidemiology and Community Health, 58, 169–174. doi: 10.1136/ jech.2003.012385. Miranda-Moreno, L. F., Morency, P., & El-Geneidy, A. M. (2011). The link between built environment, pedestrian activity and pedestrian–vehicle collision occurrence at signalized intersections. Accident Analysis & Prevention, 43, 1624–1634. doi: 10.1016/j.aap.2011.02.005. Nashville Area Metropolitan Planning Organization. (2015). 2040 regional transportation plan: Increased policy for health. Nashville, Tennessee. Preston, J., & Rajé, F. (2007). Accessibility, mobility and transport-related social exclusion. Journal of Transport Geography, 15, 151–160. doi: 10.1016/j.jtrangeo.2006.05.002. Ross, C. L., Elliott, M. L. (2012). Health impact assessment: Atlanta regional PLAN 2040. Center for Quality Growth and Regional Development, Final Report. Atlanta, Georgia. Ross, C. L., Nie, K. L. de, Barringer, J., Hashas, M., Benjamin, S., Doyle, J. H., Pierce, D. (2007). Atlanta BeltLine Health Impact Assessment. Atlanta: Center for Quality Growth and Regional Development. Ross, C. L., & Smith, S. (2016a). Health impact assessment: Coastal Region Metropolitan Planning Organization (CORE MPO) freight study. Atlanta: Center for Quality Growth and Regional Development. Ross, C. L., & Smith, S. (2016b). Health impact assessment: Cargo Atlanta, a citywide freight study. Atlanta: Center for Quality Growth and Regional Development. Singleton, P. A., & Clifton, K. J. (2014). Incorporating public health in US long-range metropolitan transportation planning: A review of guidance statements and performance measures. Presented at the 94th Annual Meeting of the Transportation Research Board (p. 43). Washington, D.C. WHO (2017). The determinants of health. World Health Organ. Available from http://www.who. int/hia/evidence/doh/en/. WHO. (1946). Preamble to the Constitution of the World Health Organization as adopted by the International Health Conference. New York:World Health Organization.

Chapter 3

Transportation and land use as social determinants of health: the case of arterial roads Carolyn McAndrews Department of Planning and Landscape Architecture, University of Wisconsin, Madison, WI, United States

1 Introduction There are several points of entry into the question of how transportation and land use affect health behaviors and outcomes. Among the most discussed are physical activity, injury, exposure to air pollution, and noise. To understand these issues, research has usually defined transportation and land use as part of the physical environment. This chapter focuses on an aspect of the problem that has received relatively less attention: how motorized traffic, streets, and surrounding land uses are also social determinants of health. The social impact of transportation is important for health, equity, and policy formulation. Streets are among the most important forms of public space in cities, serving the manifold demands of mobility and social life. As such, they display the material signs of social problems and neglect such as graffiti, drug and alcohol use, and squalor. These exposures are known social-ecological pathways that affect health and health disparities. The aim of this chapter is to provide a critical summary of how transportation and land use can be understood as part of these pathways. This is an interdisciplinary problem that requires forging understanding of physical design, behavior, psychosocial, and institutional factors. It is also a problem that can be mapped onto specific types of infrastructure such as major arterial roads and freeways, which are used as a case for this chapter. Equity implications arise because the negative social impacts of transport­ ation and land use disproportionately affect economically deprived neighborhoods and certain racial and ethnic groups. This occurs through higher exposure to traffic along arterials, arterials functioning as accessibility barriers, and disinvestment and physical decay along commercial strips, even if formal processes exist to prevent these impacts. From a policy perspective, cities and regions Transportation, Land Use, and Environmental Planning. http://dx.doi.org/10.1016/B978-0-12-815167-9.00003-7 Copyright © 2020 Elsevier Inc. All rights reserved.

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increasingly locate infill and transit-oriented development along arterials and the health effects of these changes, positive and negative, are mostly unknown. The next sections situate transportation and land use, arterials in particular, in the broader field of health and place, and outline how stress associated with streets and traffic translates into health behaviors and outcomes. The final sections highlight key areas of prior investigation relating arterials to social factors, suggesting new challenges for research, policy, and practice.

2  Neighborhoods and health I locate this exploration of streets, traffic, and neighborhood social environments within the larger discussion of health and place. The field of population health investigates neighborhood-level social and physical determinants of health because personal characteristics, health behaviors, and access to quality healthcare do not sufficiently explain the causes and distribution of disease (Diez Roux & Mair, 2010; Evans & Stoddart, 1990; Frumkin, 2005). In particular, the social, economic, and built environments of neighborhoods—as well as the broader regional processes that shape them—influence health inequities by race, ethnicity, and socio-economic status in the short run and over a lifetime of exposure (Adler & Newman, 2002; Cummins, Curtis, Diez Roux, & Macintyre, 2007; Diez Roux & Mair, 2010; Do, 2009; Hedman, Manley, Van Ham, & Östh, 2013; Osypuk & Acevedo-Garcia, 2010). Three major areas of research are relevant to the role of transportation and land use as social determinants of health: (1) poverty, (2) segregation, and (3) the interaction between social and physical environments in neighborhoods.

2.1  Poverty and segregation At an upstream level, neighborhoods contribute to health and health disparities because they are the physical manifestation of resource distribution (Ellen, Mijanovich, & Dillman, 2001). Individuals and families realize the advantages of education, income, and occupation through privileged access to protective social and physical environments (Adler & Newman, 2002; Angell, 1993). In general, people who experience poverty live, work, and carry out activities in places with relatively poor environmental quality, and this pathway leads to poorer health outcomes (Cushing, Morello-Frosch, Wander, & Pastor, 2015). Yet, the specific mechanisms of the neighborhood-health relationship, such as the role of transportation and land use, are not fully understood. Nor is it understood how the neighborhood-health relationship varies by gender, race, ethnicity, occupation, and other personal characteristics. In addition to health disparities by socioeconomic status, neighborhoods contribute to racial and ethnic health disparities (Acevedo-Garcia, Lochner, Osypuk, & Subramanian, 2003; Cummins et al., 2007). Specifically, segregation makes it difficult to use residential sorting to invest in health through the

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selection of residential location (Hipp, 2011; Massey & Denton, 1993). The chronic exposure to neighborhood poverty caused by racial and ethnic segregation is a major cause of health disparities in United States and it is associated with mortality, teenage childbearing, tuberculosis, cardiovascular disease, lack of access to healthy food, and exposure to air pollution and toxics(AcevedoGarcia et al., 2003; Do, 2009). Transportation and land use together shape the landscape of poverty and segregation through inter-governmental policies that determine infrastructure investment, employment and housing patterns in regional economies, and local land use decisions (Hayden, 2009; Jackson, 1985; Liebs, 1995; Logan & Molotch, 1987; Loukaitou-Sideris, 1997; Mollenkopf, 1983; Thompson Fullilove, 2004). Transportation’s relationship to racial, ethnic, and socioeconomic inequalities have been direct, such as through higher investment in public transit for higher income riders, as well as indirect, such as through differential access to education, employment, and other opportunities (Golub, Marcantonio, & Sanchez, 2013; Sanchez, Stolz, & Ma, 2004; Bullard, 2004).

2.2  Neighborhood physical and social environments It is well known that exposure to traffic is a significant health burden because of externalities such as air pollution, noise, and safety hazards. For example, extensive public health literature has established the connection between air pollution and respiratory disease, certain types of cancer, cardiovascular disease, and adverse birth outcomes (Anderson, Thundiyil, & Stolbach, 2012; Babisch, 2014; Sapkota, Chelikowsky, Nachman, Cohen, Ritz, 2012). Heavy traffic is also associated with higher injury rates, especially on arterial roads and in lower income neighborhoods (Morency, Gauvin, Plante, Fournier, & Morency, 2012). Persistent racial and socioeconomic inequalities in exposure to heavy traffic is yet another challenge. Estimates of the proportion of the US population living close to high-traffic roads range from 4% to 19%, depending on the definition of the road type and assumptions about distance. These proportions are higher for people of color and low-income households, as well as for people who are foreign born and people who do not speak English at home (Boehmer, Foster, Henry, Woghiten-Akinnifesi, & Yip, 2013; Rowangould, 2013). In California, children of color are three times as likely to live close to heavy traffic as white children, and minority and low-income neighborhoods have twice the traffic density of the regional average (Gunier, Hertz, Von Behren, & Reynolds, 2003; Houston, Wu, Ong, & Winer, 2004; Tian, Xue, & Barzyk, 2013). Research on transportation and health has captured these physical pathways, but the social pathways through which traffic, streets, and land use influence health are not well understood. Based on the public health literature, we know that the interconnected social and physical environments of neighborhoods are necessary for health promotion (Cummins et al., 2007; Diez Roux & Mair, 2010; Winkel, Saegert, & Evans, 2009; Yen & Syme, 1999). We also know that

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place-based community factors such as social cohesion, collective efficacy, social networks, physical and relational accessibility, and the maintenance of social norms are related to health (Diez Roux & Mair, 2010; Ellen et al., 2001; Sampson & Raudenbush, 1999; Yen & Syme, 1999). What is not yet known is how transportation and land use operate as neighborhood-level social and physical factors that influence health outcomes. The presence of neglect and physical decay in neighborhoods—as well as the perception of neglect and physical decay—may be a critical social pathway for transportation and land use. For instance, bus stops, residential back alleys, commercial strips, and arterial roads with heavy traffic have all been associated with neglect and physical decay (Appleyard, 1981; Liggett, Loukaitou-Sideris, & Iseki, 2001; Loukaitou-Sideris, 1999; McAndrews, Flórez, & Deakin, 2006; McAndrews & Marcus, 2014; Wolch et al., 2010). Evidence of neglect and physical decay is part of a larger “broken windows” theory that litter, graffiti, abandoned lots, and blight represent diminished social control in public spaces, which, in turn, invites more neglect, physical decay, and even crime. What is important for transportation-health relationship is that these incivilities in neighborhoods are sources of chronic stress, and they shape health-related behaviors in both urban and nonmetropolitan places (Ellaway et al., 2009; Frumkin, 2005; Reisig & Cancino, 2004; Ross & Mirowsky, 1999; Ross & Mirowsky, 2001; Skogan, 2012; Wilson & Kelling, 1982). Nevertheless, it is not clear whether actions to improve quality of life through “broken windows policing” or other methods is effective in reducing felony crime or even street-level incivilities. Its effectiveness depends on the type of police enforcement used, and the negative consequences of zero-tolerance policing can have serious negative effects on community cohesion (Braga & Bond, 2008). Interpreting neglect and physical decay in transportation environments requires a nuanced understanding of public space and how norms operate in transportation environments. Thinking of Jakarta, Indonesia, Lo (2009) understands the public space of streets, as well as transit networks, as the coincidence of two things: the flows of global networks and places for everyday life. The public spaces of streets serve as the place where global flows and the places of everyday life intersect. Therefore, streets are also places that reflect resistance to the spatial logic of global development and the consequences of being excluded from this global development. This is why the material traces of street-level poverty can also be understood as markers of political conflict, the source of which is an ongoing contest about the distribution of the costs and benefits of road networks, information networks, and other material and nonmaterial engagement with global flows. Pedestrians are a case in point. In some contexts, walking is a symbol of health and economic vitality. Cities conduct analyses of the economic benefit of pedestrian spaces. In other contexts, walking is a symbol of poverty, where walking is not considered a problem of mobility or transportation but rather a problem of the poor. In a similar way, we can

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read signs of neglect and decay in the public space offered by streets as part of these larger social, economic, and political struggles.

3  Transportation and land use as social determinants of health in neighborhood Transportation has a strong social framework. Understood with a first-order perspective, travel is inherently social because it captures the geography of daily life in time and space. Travel behavior is influenced by social and ecological factors such as family, work, and infrastructure. Understood with a second-order perspective, the provision and consumption of transportation services, including infrastructure, vehicles, operations, and programming, results in social and economic impacts such as changes in travel time, cost, and options; accessibility; and community cohesion (Geurs, Boon, & Van Wee, 2009; Forkenbrock, Benshoff, & Weisbrod, 2001; FHWA, 1996). In many instances, formal analysis of the social impacts of transportation projects is legally mandated, for example by Title VI of the 1964 Civil Rights Act, the 1969 National Environmental Policy Act, the 1991 Intermodal Surface Transportation Efficiency Act, and the 1994 Executive Order 12898 on Environmental Justice. However, practitioners in transportation work with “insufficient methods, tools, and techniques” to fully assess the social impact of transportation projects (Forkenbrock et al., 2001). One of the missing tools is fundamental knowledge of how the social impact of transportation interacts with its health impact. Two potential pathways that link the social impact of transportation to health impact are chronic stress and behavior, which are proposed causal pathways between neighborhood and health (Ellen et al., 2001).

3.1  Chronic stress Chronic stress is a potential mechanism relating neighborhood and health, particularly mental health and depressive symptoms (Aneshensel, 2010; Gilster, 2014; Kim, 2008; Mair, Roux, & Galea, 2008). Chronic stress results from the perception that aspects of the physical and social environment are exceedingly burdensome (Cohen, Janicki-Deverts, & Miller, 2007; Pearlin, Menaghan, Lieberman, & Mullan, 1981). It is associated with diseases such as clinical depression, cardiovascular disease, human immunodeficiency virus, and cancer (Cohen et al., 2007), and it affects people differentially by individual characteristics such as race (Gilster, 2014). For instance, people who live close to sources of pollution (e.g., toxic waste sites, refineries, and incinerators) have two problems. First, they suffer exposure to harmful chemicals. Second, they suffer chronic stress caused by their awareness of this exposure, and this chronic stress results in additional adverse mental health outcomes (Neutra, Lipscomb, Satin, & Shusterman, 1991; Yang & Matthews, 2010). In Philadelphia, Kondo et al. (2014) conducted focus group

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discussions with neighbors of a refinery and found that their awareness of the pollution, the sense of stigma that they experienced because of living in a polluted neighborhood, and their fear of displacement contributed to chronic stress. This is one example of emerging research on the effects of non-chemical pathways associated with environmental hazards, and it could serve as a model for understanding the impact of transportation and land use. Exposure to motorized traffic has been included among the various aspects of the physical environment that may contribute to stress. Gee and Takeuchi (2004) and Song, Gee, Fan, and Takeuchi (2007) used multi-level statistical models to investigate how traffic stress and objective measures of the transportation environment affected general health and depressive symptoms. Traffic stress was self-reported and centered on the degree to which one was bothered by traffic, auto maintenance, and traffic crashes. Environmental stress was also self-reported and centered on physical conditions of the neighborhood, noise, pollution, and crime. Vehicular burden in the neighborhood was measured as the percent of persons age 16 or older who drive or take public transportation to work in a given census tract, but no measure of on-street traffic volumes was included. The study found that those who reported traffic stress and who also lived in neighborhood with a high vehicular burden had significantly lower well-being than those living in areas with a lower vehicular burden, as measured by both general health status and for depressive symptoms. The perception of poor neighborhood conditions was associated with depression, but this association was no longer significant after traffic stress was included in the model. Song et al. (2007) replicated the original study with more detailed information about the built environment. This second study’s results were consistent with those of the first study, and they found that the ratio of land area devoted to parks moderated the relationship between traffic stress and well-being. In addition, neighborhoods with more major streets were more problematic, and the presence of restorative green spaces may mitigate these negative traffic and roadway externalities. In both of these studies, the constructs of people suffering from traffic stress and environmental stress may suffer from problems of construct validity because it is unclear whether the stress results from exposure to vehicular traffic, from traveling in motor vehicles, or some other combination of traffic and travel-related exposure. Using traffic volume measures in multi-level models, Yang and Matthews (2010) and Matthews and Yang (2010) found that two explanatory variables— heavy traffic and a composite measure of the physical environment—were associated with higher self-reported stress. They also found that neighborhood-level socioeconomic status and crime did not associate with self-reported stress after controlling for the built environment. With respect to the study’s design, it is possible that survey respondents found it easier to respond to visual cues of social threats than to other representations of social threats, and therefore these methods could overstate the effect of the built environment on stress (Yang & Matthews, 2010). These studies did not report specific thresholds for traffic volumes that associate with higher stress.

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In addition to chronic stress, relationships between personality and neighborhood environment might be meaningful for health. A multi-level study investigating the relationship between physical environment and psychological wellbeing found an association between the ambient stressors of neighborhoods (air pollution, noise, and traffic) and cynical hostility, which is a personality trait associated with heart disease and depression (King, 2012). Thus, there are a number of ways that everyday exposure to traffic and streets could influence individual-level health and health behaviors.

3.2 Behavior Walkability is another field that has adopted a social-ecological framing of transportation environments. Land use, connectivity, and the density of activities are known to influence mode choice and therefore physical activity through active modes of travel (Ding, Sallis, Kerr, Lee, & Rosenberg, 2011). In addition, environmental qualities such as aesthetics, naturalness and presence of vegetation, and perceived safety influence active travel (Nasar, 2015). In addition to features of the physical environment, a variety of social factors influence the propensity to walk. For instance, perceived safety is important, and the construct of safety often takes two meanings. One meaning is fear of traffic. A second meaning is fear of crime. Fear of crime and social disorder are cited as factors that are central to individuals’ decisions to walk (Griffin, Wilson, Wilcox, Buck, & Ainsworth, 2007; Roman & Chalfin, 2008 ). If disorder in the built and social environments leads to stress and fear, this may affect health directly through stress mechanisms, as well as indirectly by discouraging health-promoting behavior such as walking or using parks and playgrounds (Loukaitou-Sideris, 2006; Ross & Mirowsky, 2001). However, empirical evidence about the crime-physical activity connection is mixed, potentially because of different constructs and methodologies used (Loukaitou-Sideris, 2006; Saelens & Handy, 2008).

4  The case of major arterial roads If streets, traffic, and land use combine into an important social-ecological pathway that influences individual and community health, then major arterial roads may be a critical type of infrastructure implicated in this relationship. Arterial roads are streets that carry high volumes of fast traffic. Urban transportation systems depend on them for everyday travel, serving transit routes, facilitating goods distribution, and connecting local traffic to regional expressways. They are an important case for both research and intervention in the transportationhealth relationship. First, arterial roads carry high volumes of traffic, which means that they are corridors of concentrated negative externalities such as noise, pollution, and safety hazards. Second, in addition to their mobility function, arterials also serve as commercial strip developments that mark the edges

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of residential neighborhoods, which implies that they also concentrate exposure to the negative externalities of traffic as well as the potential benefits of this proximity. Third, arterial roads are associated with neglect and physical decay in cities and they are public spaces where road users of all types can be exposed to such incivilities. This section focuses on how arterial roads are a useful case example of the interaction of social and physical factors in the context of transportation and land use. We know that arterial roads—their traffic, design, and surrounding land use contexts—associate with neglect and physical decay. But which features of arterials matter most? Is it the land use context, the heavy traffic, or the interaction of these and other factors? Similarly, do the traffic, street design, and land uses only reflect surrounding social contexts, or can they influence social contexts? How could interventions in the street design, traffic operations, and land use of arterial roads be used as a tool for addressing the perception of crime? The following sections explore two social dimensions of arterial roads that plausibly relate to health behaviors and outcomes: the presence of neglect and physical decay along arterials and their role as accessibility barrier that leads to community severance and social isolation.

4.1  Streets and land uses that associate with neglect and physical decay Major arterial roads are a specific type of infrastructure developed within the highway paradigm of transportation planning and they are a landscape in their own right. In the early 20th century, urban planners and traffic engineers promoted arterial roads as a way to channel motorized traffic away from residential subdivisions, therefore minimizing traffic exposure to protected residential neighborhoods. At the same time, this strategy accommodated increasing demand for regional mobility as jobs and housing located farther away from city centers (Buchanan, 1963; FHWA, 1997). In the inner suburbs, many arterial roads are configured as main streets because they were created along the rightof-way of former streetcar lines, surrounded by neighborhood-serving retail. In contemporary settings, arterials function as highways with larger-scale strip development. A key feature of arterial roads is that they provide access to surrounding land uses, which compromises their ideal-type mobility function and distinguishes them from freeways. In practice, arterials serve multiple types of road users and multiple transportation modes. However, because they have been designed with modified highway standards that allow for heavy, fast traffic, this combination of mobility and access results in conflicts. Some of the conflicts are physical, such as the problem of pedestrian safety. Other conflicts are discursive, such as debate about their design and which users should be prioritized. Arterial roads are also social places. Older main streets were locations for commerce as well as churches, theaters, memorials, libraries and they were “the

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ideal setting for speeches, parades, and celebrations” (Liebs, 1985, p. 8). However, when freeway bypasses were built, inner suburb and downtown arterials lost traffic and business declined. At the same time, new development occurred farther in the suburbs and inner suburbs and downtowns faced the dual-impact of decline and urban renewal, leaving many arterial roads and commercial strips empty, boarded up, and decaying (Liebs, 1985; Loukaitou-Sideris, 1997). Today, some of these strips have been revitalized, but the vast majority continue to serve primarily as traffic and fast-food corridors with mixed reputations as unsavory but useful for travel and consumption (Hurvitz, Moudon, Rehm, Streichert, & Drewnowski, 2009). At the same time, they serve essential neighborhood functions such as providing access to retail and transportation services, particularly in places where nearby residents have limited access to automobiles (Loukaitou-Sideris, 1997). Although not all arterial roads are characterized by the presence of neglect and physical decay, these social problems associate with arterial roads and specifically with commercial strip development in inner cities and suburbs. Surveys of nearby residents, business owners, and developers have been a main source for data about the nature of arterial roads and what characteristics of these places influence neighbors’ and users’ quality of life. Survey respondents and focus group participants discuss the presence of gangs, drug dealing, and prostitution as well as needles, graffiti, litter, and a lack of maintenance as problems that negatively affect their neighborhoods (Loukaitou-Sideris, 1997, 2000; McAndrews et al., 2006; Mejias & Deakin, 2005). Business owners call attention to surrounding poverty as a challenge (Loukaitou-Sideris, 2000). In addition to social problems, neighbors are also concerned about traditional transportation issues such as the speed of traffic, pedestrian safety, and parking. Bus stops and residential back alleys are two additional examples of transportation environments that have been framed as both social and physical environments. Research about crime around bus stops using multivariate statistical models found that a mix of locational, land use, and design features associate with higher police-reported crime rates at bus stops. Higher crime rates at bus stops associate with specific bus stop locations, undesirable establishments such as liquor stores, and the presence of litter. Lower crime rates are associated with pedestrian presence and good visibility of the bus stop from nearby establishments (Liggett et al., 2001). Traffic volumes on the streets did not affect crime rates. These findings about bus stops are consistent with research about undesirable land uses, and they support the idea that certain non-residential land uses elevate the perception of crime (McCord, Ratcliffe, Garcia, & Taylor, 2007). Residential back alleys are a second context in which land use, design, and social disorder intersect. Residential back alleys, similar to arterials, serve a utility function. They are places for residential storage, waste pick-up, and driveways and garages that offer access. They are only semi-public spaces, and they are somewhat hidden (Martin, 1996, 2000). As such, they also have problems such as litter and graffiti. In focus group discussions, residents associated

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their back alleys with illicit activities (Wolch et al., 2010). Municipalities and neighborhood organizations have used clean-up and greening programs to improve the conditions of back alleys, but these revitalization programs face limitations. For example, alley programs that emphasized green infrastructure did not easily adopt social equity goals as part of their agendas, and the signs of disorder that had once been located on alleys that received revitalization treatments simply moved to nearby alleys that had not received the interventions (Newell et al., 2013; Seymour, Wolch, Reynolds, & Bradbury, 2010). The literature on neglect and physical decay in neighborhood has often relied on observation of streets, traffic, and land use, but, with the exception of investigations of bus stops and residential back alleys, it has not been concerned with transportation environments per se. How does the heavy traffic on arterial roads influence the social norms of public space on streets, and how are operations and design strategies used to shape social norms even in the presence of heavy traffic (Appleyard, 1981)? Could street design and infrastructure improvements prevent incivilities, or are these interventions limited to changing perceptions of incivilities?

4.2  Barriers that lead to community severance and social isolation Arterial roads are social barriers because of the presence of neglect and physical decay as well as physical barriers because of their design and traffic. Their function as a barrier is another potential pathway through which they affect individual and community health. The phrase community severance refers to these barriers, and is defined as the “…cumulative impact of psychological and physical barriers to movement and social participation, created by the transport infrastructure…” (James, Millington, & Tomlinson, 2005). Community severance is associated with a larger problem of social and economic isolation in communities, resulting from the combination of heavy traffic and poor accessibility (Geurs et al., 2009). Accessibility is a critical metric for evaluating the fundamental benefits offered by transportation systems, particularly for elderly and people with disabilities (Decker, 2006; Golub & Martens, 2014). It is not clear if mainstream transportation planning practice has the tools, methods, and resources to engage with this problem (James et al., 2005). Community severance is directly linked to well-being as it affects accessibility and physical mobility, which are health promoting aspects of well-being (Delbosc, 2012). Heavy traffic, in particular, is a known contributor to community severance and diminished social capital (Anciaes, Boniface, Dhanani, Mindell, & Groce, 2016; Appleyard, 1981). In a qualitative community-based study of arterials and health, McAndrews and Marcus (2014) found that accessibility barriers, along with social disorder and direct exposure to hazards, were central to residents’ perception of the negative externalities of the large arterial road.

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5  Implications for policy, planning, and design The conflicts present for the case of arterial roads resemble a larger problem in urban design: how streets and other transportation infrastructure contribute to a sense of place while at the same time functioning as part of a regional network (Belzer, Autler, Espinosa, Feigon, & Ohland, 2004; Bertolini, 1996). For the case of arterial roads, this means asking how to combine street design, land use, and other programming to create streets with significant traffic capacity accompanied by significant social capacity. Arterials may be a critical element for urban policies such as infill housing, enhanced transit service, and transit-oriented development, particularly as growth continues in central cities and inner suburbs (Beyard, Pawlukiewicz, & Bond, 2003; Cherry, Deakin, Higgins, & Huey, 2006; Mejias & Deakin, 2005). But each of these initiatives requires both a high quality of place and a high level of mobility, which are competing demands.

5.1  Traffic operations and design strategies The difficulties of urban arterial roads have been documented in planning, engineering, urban design, and public health literature (Dowling, Flannery, Landis, Petritsch, Rouphail, & Ryus, 2008; Dumbaugh & Rae, 2009; Hebbert, 2005; Miles-Doan & Thompson, 1999; Mindell & Karlsen, 2012). These difficulties range from travel delay and travel time unreliability to exposure to traffic safety hazards, direct exposure to noise and near-roadway pollution, and physical barriers that limit access and lead to community severance. With respect to the physical aspects of street, traffic volumes, traffic speed, noise levels, the potential to support transit, and the attractiveness of the streetscape are all important characteristics (McAndrews et al., 2006; Mejias & Deakin 2005; Seto, Holt, Rivard, & Bhatia, 2007). Research about arterials has focused on two aspects of design. The first emphasizes the multi-modal boulevard; the second emphasizes design and operations for public transit. Research about boulevards and other multi-use streets accepts that traffic and livability are reconcilable through design (Jacobs, 1993; Jacobs, Macdonald, & Rofe, 2002). In fact, traffic can make certain streets dynamic and interesting, despite also being a source of noise and pollution. In particular, street design can be used to buffer neighbors and road users from noise, pollution, and other negative effects of traffic. Research about boulevard designs found that residents living along them are happy despite the traffic, and that these major roads can be more livable than nearby streets with lower traffic volumes (Bosselmann, Macdonald, & Kronemeyer, 1999). In this way, accepting car traffic as an element of neighborhood vitality allows one to ask questions that are critical for contemporary transportation policy, such as how to design for transit-oriented and residential infill development in settings where cars remain a priority. A second approach has focused on the design and operations strategies that make major arterial roads successful transit streets (Cherry et al., 2006). These

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strategies include transit operations, traffic operations, geometric design, pedestrian improvements, as well as land use strategies. Design can be a successful technique, but it needs a strong urban design, land use, and transit service framework, not only a complete streets design template.

5.2  Greening and cues to care Beautification, specifically greening of vacant lots, has been another response to crime and social disorder in neighborhoods. Greening has been associated with reductions in gun assault incidents in Philadelphia and lower crime rates in Baltimore (Branas et al., 2011; Troy, Grove, & O’Neil-Dunne, 2012). One potential mechanism causing the decreases in crime may be that surveillance is easier in places that are more tidy and transparent. A second mechanism may be that greening is an expression of care and that a green, maintained landscape is a cultural sign that cultivates trust (Nassauer, 1995). There are several proposed pathways between greening and health, including physical activity, reducing stress, and increasing social contact. Contact with nature is considered protective against adverse mental health outcomes, cardiovascular disease, and overall mortality (James et al., 2015; Hartig et al., 2015). Contact with nature in urban settings is usually framed as access to parks and community gardens, but green streets may have health co-benefits if they are well maintained (EPA, 2008). For example, residential arterials designed as boulevards were used for exercise such as walking, jogging, and bicycling, and they were used as parks where people would walk dogs, interact, or sit and watch the activity (Bosselmann et al., 1999).

5.3  Infill, revitalization, and community development strategies Urban revitalization is a key strategy for dealing with social disorder along commercial strips. For example, during a period of economic revitalization along an arterial in the San Francisco Bay Area in California, street activity increased and criminal activity decreased. This decline in criminal activity was favorable for infill housing and commercial development because lenders were more willing to finance projects as the neighborhoods became safer (Mejias & Deakin, 2005). However, the transformation of commercial strips is also part of the gentrification process that affects businesses and residents alike, and these changes may be contested (Loukaitou-Sideris, 2002; Minner, 2013). For instance, an Urban Land Institute report about revitalization of neighborhood retail suggested that “high-quality” residents can help turn around a neighborhood (Beyard et al., 2003). This framing seems to suggest that place-based public health practices are speculative processes whereby cities attract healthy people with relatively higher incomes to changing neighborhoods. Instead, future practice needs to be explicit about how it includes the needs of current residents.

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Supporting retail and land uses that are active at night are typical goals of revitalization strategies for arterial roads, but even in places where active land uses are strong, retail and other active land uses cannot be located continuously along every road. This is a challenge for neighborhoods of all income levels, and the problem has voluntary, market, regulatory aspects. One approach is to support the formation of merchant associations that serve the important role of community building among business and other groups (Loukaitou-Sideris, 2000). Local governments can help by creating policies that support local retail, such as tax rebates for improvements, access to financing, programs to facilitate storefront façade improvements, and zoning that concentrates retail development at nodes instead of all along a corridor (Loukaitou-Sideris, 2000).

6 Conclusion Transportation and land use should be understood as social determinants of health, not only physical determinants of health. This is because social pathways are primary mechanisms through which built environments affect individual and community health. Transportation and land use can be conceptualized in a social-ecological framework that is consistent with the nature of travel as well as the nature of population health. These social determinants of health may operate at multiple scales. Through investments in transportation services, the siting of infrastructure, and the standards for development, transportation and land use relate to poverty and segregation, which are upstream social processes that influence health and health disparities at a regional level. At the site level, the combination of streets, traffic, and land use are social environments and, as such, they display social problems such as crime, disorder, and physical decay. These multi-scalar social exposures work in combination, and may “get under the skin” through mechanisms such as chronic stress and behavior. Arterial roads are a case example that exemplifies both the physical and social dimensions of the transportation-health relationship. Arterial roads carry high volumes of fast traffic, and they concentrate exposure to air pollution, noise, and safety hazards. The difficult aspects of high traffic volumes can be mitigated through built-environment and traffic-related interventions—or by reducing traffic altogether—but the social aspects of arterial roads are equally important. In addition to their role as travel corridors, arterial roads are also important neighborhood assets. In particular, they are places that nearby residents use with some frequency, despite their traffic and related hazards. However, arterial roads, particularly those with commercial strip development, are prone to concentrate social disorder such as graffiti, litter, and alcohol and drug use. Actual and perceived social disorder is a source of stress for neighbors and it may create a barrier that diminishes social cohesion and increases social isolation. Therefore, arterials also serve as an opportunity to develop transportationhealth interventions within a social-ecological model. Potential interventions

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include transportation design and operations strategies, land use strategies and revitalization, and greening and maintenance programs that express cues to care. These interventions are not traditional “transportation” projects and they will typically fall outside the scope of mainstream transportation planning activities, particularly on state-owned roads. In addition, working within a socialecological model of transportation and land use will also require an expanded set of partners, including social work, law enforcement, and the maintenance function of public works departments and their contractors. Economic growth and demographic change in cities has prompted infill development and neighborhood change along arterial corridors. The effects of these changes on individual and community health are unknown. A next step for future research is to use experimental research designs, as well as qualitative and environmental design methods, to evaluate the causal effects of livability interventions on arterials to better understand the interdependence of the quantity and quality of traffic, the social features of arterials, and the impacts on individual and community health.

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Minner, J.S. (2013). Landscapes of thrift and choreographies of change: reinvestment and adaptation along Austin's commercial strips. (Dissertation). Austin: University of Texas Mollenkopf, J. H. (1983). The contested city. Princeton NJ: Princeton University Press. Morency, P., Gauvin, L., Plante, C., Fournier, M., & Morency, C. (2012). Neighborhood social inequalities in road traffic injuries: the influence of traffic volume and road design. American Journal of Public Health, 102(6), 1112–1119. Nasar, J.L. (2015). Creating places that promote physical activity: Perceiving is believing. Robert Wood Johnson Foundation Research Review. Nassauer, J. I. (1995). Messy ecosystems, orderly frames. Landscape Journal, 14(2), 161–170. Neutra, R., Lipscomb, J., Satin, K., & Shusterman, D. (1991). Hypotheses to explain the higher symptom rates observed around hazardous waste sites. Environmental Health Perspectives, 94, 31–38. Newell, J. P., Seymour, M., Yee, T., Renteria, J., Longcore, T., Wolch, J. R., & Shishkovsky, A. (2013). Green Alley programs: planning for a sustainable urban infrastructure? Cities, 31, 144–155. Osypuk, T. L., & Acevedo-Garcia, D. (2010). Beyond individual neighborhoods: a geography of opportunity perspective for understanding racial/ethnic health disparities. Health & Place, 16(6), 1113–1123. Pearlin, L. I., Menaghan, E. G., Lieberman, M. A., & Mullan, J. T. (1981). The stress process. Journal of Health and Social Behavior, 337–356. Reisig, M. D., & Cancino, J. M. (2004). Incivilities in nonmetropolitan communities: the effects of structural constraints, social conditions, and crime. Journal of Criminal Justice, 32(1), 15–29. Roman, C. G., & Chalfin, A. (2008). Fear of walking outdoors: a multilevel ecologic analysis of crime and disorder. American Journal of Preventive Medicine, 34(4), 306–312. Ross, C. E., & Mirowsky, J. (1999). Disorder and decay the concept and measurement of perceived neighborhood disorder. Urban Affairs Review, 34(3), 412–432. Ross, C. E., & Mirowsky, J. (2001). Neighborhood disadvantage, disorder, and health. Journal of Health and Social Behavior, 258–276. Rowangould, G.M. (2013). A census of the US near-roadway population: public health and environmental justice considerations. Transportation Research Part D: Transport and Environment, 25, 59–67. Saelens, B. E., & Handy, S. L. (2008). Built environment correlates of walking: a review. Medicine and science in sports and exercise, 40(7 Suppl), S550–S566. Sampson, R. J., & Raudenbush, S. W. (1999). Systematic social observation of public spaces: a new look at disorder in urban neighborhoods. American Journal of Sociology, 105(3), 603–651. Sanchez, T.W., Stolz, R. and Ma, J.S., 2004. Moving to equity: Addressing inequitable effects of transportation policies on minorities. Transportation Research Record: Journal of the Transportation Research Board, No. 1885,TRB, National Research Council, Washington, D.C., pp. 104–110. Sapkota, A., Chelikowsky, A. P., Nachman, K. E., Cohen, A. J., & Ritz, B. (2012). Exposure to particulate matter and adverse birth outcomes: a comprehensive review and meta-analysis. Air Quality, Atmosphere & Health, 5(4), 369–381. Seto, E. Y. W., Holt, A., Rivard, T., & Bhatia, R. (2007). Spatial distribution of traffic induced noise exposures in a US city: an analytic tool for assessing the health impacts of urban planning decisions. International Journal of Health Geographics, 6(1), 1. Seymour, M., Wolch, J., Reynolds, K. D., & Bradbury, H. (2010). Resident perceptions of urban alleys and alley greening. Applied Geography, 30(3), 380–393. Skogan, W.G. (2012). Disorder and crime. B. Welsh & DP Farrington. The Oxford handbook of crime prevention (pp. 173–188).

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Chapter 4

Transit-oriented displacement: the role of transit access in the housing market Karen Chapple, Miriam Zuk Department of City and Regional Planning, University of California, Berkeley, CA, United States

1 Introduction Recognizing the role good planning can play in achieving our AB32 goals, California passed Senate Bill 375, requiring the metropolitan planning organizations (MPOs) to develop Sustainable Communities Strategies (SCSs) as part of their regional transportation planning process to illustrate how integrated land use, transportation, and housing planning will help achieve greenhouse gas reductions targets. Regions are pursuing more compact, transit-oriented development as a key strategy to achieve these reductions. Planning for SCSs across the state has raised awareness of the potential social equity effects of land-use-based greenhouse gas reduction strategies. Locals are likely to benefit from improved mobility, neighborhood revitalization, lower transportation costs, and other amenities that spill over from the new development (Cervero and Duncan, 2004). However, more disadvantaged communities may fail to benefit, if the new development does not bring appropriate housing and job opportunities, or if there is gentrification that displaces low-income and/or minority residents (Chapple, 2009; Pollack et al., 2010). Specifically, there is a concern that new transit investment and development may increase housing costs, forcing low-income communities, often of color, to move to more affordable but less accessible locations and preventing these communities from sharing the benefits of this type of development. This chapter examines the relationship between fixed-rail transit neighborhoods and displacement in California, modeling past patterns of neighborhood change in relation to transit-related investment (also called transit-oriented development, or TOD). We focus on the San Francisco Bay Area, where most transit development occurred with the development of the BART system in the 1970s and 1980s. After describing the relationship between TOD and displacement Transportation, Land Use, and Environmental Planning. http://dx.doi.org/10.1016/B978-0-12-815167-9.00004-9 Copyright © 2020 Elsevier Inc. All rights reserved.

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PART | I  Motivations

established in the literature, the chapter turns to empirical analysis of patterns of neighborhood change, differentiating between gentrification, exclusion, and displacement. The chapter concludes by identifying anti-displacement strategies in use and discussing how they might best be incorporated into regional transportation planning.

2  TOD and displacement: understanding the relationships Surprisingly, little research has addressed the relationship between transit neighborhoods and social equity, outside of an advocacy literature that has focused largely on the importance of affordable housing near transit stations to reduce transportation cost burdens for low-income households (CHPC, 2013; Great Communities Collaborative, 2007). One reason for the relative lack of research on equity issues related to transit neighborhoods is the challenge of operationalizing displacement, due to lack of appropriate data. Further, most studies neglect to examine the role of private or public investment in spurring gentrification, examining it as a purely demographic phenomenon, that is, the influx of higher-income households into low-income neighborhoods. They also generally fail to examine the possibility of displacement via discrimination preventing minority households from moving in, in addition to displacement via rent increases. Studies typically investigate only a 10-year period; however, given the length of time it takes to plan, fund, and build transportation improvements, examining a longer period of time may be more appropriate. However, there is a significant body of literature on the impact of transit on property values. Most of these studies focus on changes in property values rather than land use, household, or racial transition, possibly due to the fact that property value data is more widely available than data such as land use (Landis, Guhathakurta, Huang, Zhang, & Fukuji, 1995). Transit and transit-oriented districts (TODs) are viewed as desirable amenities in urban neighborhoods due to their accessibility, which gets capitalized into property values. However, disamenity effects also exist from being “too close” to transit, which can result in heightened noise, congestion, pollution, and traffic (Cervero, 2006; Kilpatrick, Throupe, Carruthers, Krause, 2007). In general, the literature agrees that transport investments (new stations, TODs) have economic benefits primarily if they improve access significantly. However, findings are inconsistent in part due to differences in research methods and in the local conditions in which transit investments are made; transit systems have an appreciable impact on the accessibility only where road networks are insufficient for handling travel demands (i.e., where congestion is severe) (Giuliano and Agarwal, 2010). Overall, the impact of transit on home values can vary depending on a number of mediating factors. Wardrip (2011) outlines several reasons, which include housing tenure and type, the extent and reliability of the transit system, the strength of the housing market, the nature of the surrounding development, and so on. In an area with a strong housing market and a reliable transit system,

Transit-oriented displacement Chapter | 4

57

the price premium may be much higher than the average. Additionally, effects may vary for different stations within a single market. For instance, averages can hide a lot of variation, and transit stations may have little or no impact on housing prices in some neighborhoods but a significant impact in others (Wardrip, 2011). Some studies have also found that transit expansion plans may drive increases in property values before anything is built (Knaap, Ding, & Hopkins, 2001). Finally, research suggests that heavy rail systems have a greater impact on property values than light rail systems. This is likely due to heavy rail’s greater frequency, speed, and scope of service as compared to most light rail networks (Landis et al., 1995; Lewis-Workman and Brod, 1997; Parsons Brinckerhoff, 2001).

3  Defining and describing TOD and displacement In part due to the lack of appropriate data to measure the phenomenon of interest, researchers have adopted many different approaches to defining and analyzing gentrification and displacement, as well as TOD. The lack of agreement on how to operationalize these terms, as well as the inability to clarify the relationship particularly between gentrification and displacement, has made it difficult for policymakers to design and implement responses. In this section, we develop definitions and begin to describe how gentrification is related to TOD areas.

3.1  Data sources and terms Gentrification: We consider gentrification to be the transformation of a working-class area via an influx of capital and middle- and high-income newcomers. Following Freeman (2005) and Bates (2013), we use the following criteria to define a neighborhood (census tract) as having gentrified between Year 1 and Year 2: A tract was eligible to be classified as gentrified, if it met all of the following criteria: 1. The tract had a population of at least 500 residents in Year 1 2. The tract had at least 3 out of 4 of the following indicators in Year 1 indicating vulnerability to gentrification: a. % low-income households (household income below 80% of the county median) is above the county median b. % college educated (Bachelor’s degree or higher) below county median c. % renters above county median d. % nonwhite above county median A tract is said to be gentrified or gentrifying, if it meets the following criteria: 1. Demographic change between Years 1 and 2 a. Change in % college educated above the county (percentage points) b. Change in median household income above county (absolute value)

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PART | I  Motivations

2. Investment between Years 1 and 2 a. Growth in either: - Single family sales price per square foot > regional median - Multi-family sales price per square foot > regional median - Home value > regional median Using the above criteria for the Bay Area, we find that 83 tracts gentrified between 1990 and 2000 and 85 tracts gentrified between the years 2000 and 2013 (for a total of about 10% of all tracts). Of these 85 that gentrified between 2000 and 2013, 19 were tracts that gentrified between 1990 and 2000 as well. In total, we estimate that 149 tracts gentrified between 1990 and 2013. The fact that a tract has gentrified between 2 decades does not preclude them from continued change. In fact, of the 149 tracts that we estimate to have gentrified between 1990 and 2013, 71 had lower rates of growth of low-income households than the rest of the region, 105 lost naturally occurring affordable housing, and 100 had lower rates of in-migration of low-income residents in 2013 than they did in 2009. Furthermore, 88 of the gentrified tracts continue to have higher proportions of low-income households than the region (39%). Exclusion: Exclusionary displacement creates barriers that make it difficult for disadvantaged residents to move in. To analyze exclusion, we look at the share of in-movers by demographic and socioeconomic characteristics. Specifically, we focus on the share of in-movers who are in poverty (and over age 15), high-income (with household income over 120% of the county median), non-Hispanic white, individuals with less than a high school diploma, and persons with a Bachelor’s degree or higher (persons 25 years or over). In order to calculate the share of in-movers for each characteristic (income, race, and education), we first had to subtract the total number of non-movers or the “stayers” (those who reported living in the same house 1 year ago) in the group from the total mobility universe, which in this case, are persons age 15 years or older. This calculation gives the absolute number of in-movers with each characteristic. We then divide the absolute number by the total in-movers for that tract, and multiplied by 100 to get the share. The following set of calculations shows our process. # In-movers = (TotalPersons Age 15+ − Non-movers) % In-movers = (# In-movers/Total in-movers) × 100 Changes in affordable housing: For this analysis, we look at a more direct measure of displacement by examining the loss of affordable housing as a proxy. This is measured by the change in affordable rental units, Section 8 vouchers, and subsidized units including low-income housing tax credit (LIHTC) units from 2000 to 2013. We define affordable rental units as those where low-income households are paying less than 30% of their income on rent. Data on Section 8 units are derived from the Housing and Urban Development’s (HUD) Picture

Transit-oriented displacement Chapter | 4

59

of subsidized households for years 2000 and 2013. 2000 Section 8 data were adjusted to 2010 boundaries using Brown University’s Longitudinal Tract Data Base’s (LTDB) crosswalks. Data on subsidized units are derived from the California Housing Partnership Corporation that verified HUD and HCD data and includes some non-LIHTC federally and state subsidized housing units (e.g., project based Section 8). The placed-in-service variable was used to identify units constructed up to 2000 and 2014. All units are normalized as fraction of the housing stock (divided by total housing units). The change represents the proportion after minus the proportion before. Loss of low-income households: Another approach to estimating displacement is by using the loss of low-income households as a proxy. Researchers have found that neighborhood composition in the United States is considerably stable (Landis, 2015; Wei and Knox, 2014). In fact, on average Bay Area census tracts’ low-income population grew by 59 households between 2000 and 2013. Therefore, we may assume that any neighborhood that experienced a net loss of low-income households while stable in overall population is a result of displacement pressures. Although the change in low-income households could be due to income mobility (e.g., low-income households moving into middle or upper income categories, or vice versa), from our analysis of data from the Panel Study on Income Dynamics, we estimate that there would have been a net increase in low-income households in most places likely due to the great recession.

3.2  TOD areas in the Bay Area We define TOD here broadly to include any housing within a one-half mile radius of a fixed-rail transit station. This section looks at where TOD areas are located and then creates a typology of TOD areas, as related to gentrification. The number of rail stations in the Bay Area has more than doubled since 1990. Thus, as of 2014, there were 548 census tracts within one-half mile of rail transit in the Bay Area, clustered in heavily populated areas. In 2000, 488 census tracts were near transit, and in 1991, just 418; overall, census tract coverage has only increased by 31%. One way of differentiating between TOD areas is by the amount of development that has occurred, of both housing and transit. Here, we distinguish between areas that have significant subsidized housing development (with existing transit), areas with significant private development near transit, and areas with very little development at all (despite some new transit). Table 4.1 shows the three types and compares the average amount of development in each. The vast majority of tracts have seen little development of any kind. Development and gentrification do not have a clear relationship in TOD areas. Of the 125 Census tracts that gentrified between 2000 and 2013, half (63) were in TOD areas (Table 4.2). Yet, the vast majority of these did not experience much development, either subsidized driven, or mixed between transit and private driven development. While many TOD tracts experienced significant

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PART | I  Motivations

TABLE 4.1 Summary statistics for transit station types (means). Subsidized housing driven

Little development

Private development w/new transit

65.8

109.1

1997.6

Subsidized units, 00-14

417.9

20.8

150.3

New transit stations 00-14

0.3

0.8

2.3

n

24

510

14

New market rate units, 00-13 New and rehabbed

Source: Authors.

TABLE 4.2 TOD tracts, gentrified with/without development for the 9-county Bay Area. Gentrified 00-13

Did not gentrify 00-13

Subsidized housing driven development

2

22

Little development

58

452

Private development w/new transit

3

11

Source: Authors.

development, they did not undergo gentrification either because they were not low income to begin with, or because there was not sufficient demographic change during the time period of analysis. Thus, the relationship between gentrification and development is complex. The vast majority of tracts experienced relatively little development from 2000 to 2013, and most development is occurring in tracts that did not gentrify.

4  Modeling gentrification, exclusion, and displacement We next look at the relationship between TOD and displacement measured several different ways: by gentrification, exclusion, loss of affordable housing, and loss of low-income households.

4.1 Gentrification We begin by modeling gentrification for two individual time periods: 1990–2000 and 2000–13 (Table 4.3). New and established stations appear to positively

TABLE 4.3 Logit regressions of gentrification, 1990–2000 and 2000–13. Dependent variables: gentrified 1990–2000, gentrified 2000–13 Model I BA 1990–2000

Model II BA 1990–2000

Model I 2000–13

Model II 2000–

−7.729

***

−7.04897

***

−6.346

***

−6.235

***

Median household income (/10000)

0.683

**

0.643

**

0.597

**

0.572

*

Income squared

−0.053

**

−0.054

***

−0.053

**

−0.052

**

% Non-hispanic black

0.461

1.095

*

3.593

***

3.590

***

% Asian

1.292

1.646

**

1.652

*

% Hispanic

1.778

**

1.694

***

1.888

***

1.830

**

% Renters

3.757

***

4.242

***

1.586

**

1.539

**

Core city TOD

1.038

***

0.557

*

Non-core city TOD

0.782

**

−0.052

−0.216

New TOD 1990s

0.836

***

0.311

All TOD 1990

0.873

***

0.616

New TOD 2000s n Likelihood Ratio

**

0.344 118.2

1577

1577

***

−381.7

***P < .01, **P < .05, *P < .10 Source: 1990 and 2000 Decennial Censuses, 2009–13, 5-year ACS. Calculations by authors.

***

119.9

1579

1579

***

−270.7

***

Transit-oriented displacement Chapter | 4

Intercept

61

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PART | I  Motivations

influence gentrification between 1990 and 2000, but only established stations seem to have an impact on gentrification from 2000 to 2013. Both Hispanic and African American neighborhoods are more likely to experience gentrification during both time periods, whereas Asian neighborhoods are only susceptible from 2000 to 2013. TODs in the three major cities (Oakland, SF and San Jose, labeled downtown) were more likely to gentrify than TODs in other cities. Furthermore, more established TODs were more likely to gentrify than newer ones.

4.2 Exclusion In our model to predict exclusion, the dependent variable is the share of 1-year in-movers who are in poverty (persons 15 years or older), high-income (with household income over 120% of the county median), non-Hispanic white, individuals with less than a high school diploma, and a Bachelor’s degree or higher (persons 25 years or over). Table 4.4 reports the results of the OLS regressions for each of the subgroups. After accounting for the demographic and socioeconomic characteristic (race/ethnicity and income) of the neighborhood and for core city location, and tenure, individuals in poverty actually make up a higher rate of in-movers into core city TODs; however, not into non-core city TODs. This may be related to the location of housing opportunities for very low income households. Conversely, higher income and better educated persons make up a higher share of in-movers in TOD areas, ceteris paribus. Finally, non-Hispanic whites make up a higher share after adjusting for all other factors.

4.3  Changes in affordable housing Table 4.5 presents the results for the model on change in affordable housing. We begin by first examining what is happening overall with the housing market, which is measured by the first two columns in Table 4.5—the change in affordable rental units and condo conversions. Both include subsidized and unsubsidized housing units. The only finding that is significant is that being in a TOD area in one of the Bay Area’s three major cities—SF, Oakland, and San Jose—positively predicts the addition of federally subsidized housing; however, outside of these three cities being in a TOD neighborhood predicts fewer new subsidized units. For the entire region, an increase in affordable housing is predicted for minority neighborhoods for both naturally occurring rental units and the use of housing choice vouchers, however, only for Hispanic neighborhoods for new federally subsidized units.

4.4  Loss of low-income households The final measure of displacement that we analyze is loss of low-income households. In Table 4.6, we find that TODs outside of the three major cities

TABLE 4.4 Modeling share of in-movers by subgroups, multivariate regressions, 2009–13. High- Income (> 120% County Median Income)

In Poverty

Less than High School

Bachelor Degree or Higher

non- Hispanic white

0.412

***

−0.055

***

0.496

***

0.078

*

0.898

Median household income

−0.053

***

0.013

***

−0.051

***

0.055

***

−0.001

Income squared

0.002

***

0.000

***

0.001

***

−0.001

***

0.000

% Non-Hispanic black

0.171

***

−0.013

*

0.198

***

−0.345

***

−0.794

***

% Asian

0.016

−0.014

***

0.132

***

−0.043

*

−0.933

***

% Hispanic

0.077

***

−0.048

***

0.684

***

−0.671

***

−0.959

***

Core city TOD

0.019

**

0.004

*

−0.024

**

0.045

***

0.048

***

Non-core city TOD

−0.014

0.008

***

−0.015

**

0.048

***

0.002

% Renters

0.020

0.091

***

−0.258

***

0.410

***

0.066

n

1575

1578

1575

1575

1576

Adjusted R-squared

0.3275

0.3922

0.5685

0.579

0.7169

***P < .01, **P < .05, *P < .10 Source: 2009–13 ACS. Calculations by the authors.

***

***

Transit-oriented displacement Chapter | 4

Constant

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PART | I  Motivations

TABLE 4.5 Changes in affordable housing, linear regressions. Model I

Model II

Model III

∆ Affordable

∆ Section 8

∆ Federally

Intercept

−142.541

***

34.043

***

96.23171

***

Median Household Income, 2000

14.112

***

−3.880

***

−14.10548

***

Income Squared, 2000

−0.365

***

0.086

*

0.4715534

***

% Asian, 2000

40.256

***

36.249

***

3.703027

% Non-Hispanic black, 2000

92.624

***

14.739

*

−18.85684

% Hispanic, 2000

95.357

***

16.762

**

43.51598

% Renter, 2000

−119.277

***

−0.453

11.84316

Core city TOD, 2000

−2.978

−0.964

21.08426

***

Non-core city TOD, 2000

−6.507

−2.744

−23.96116

***

Adjusted R-squared

0.189

0.184

0.082

n

1579

1579

1579

***

***P < .01, **P < .05, *P < .10 Source: 2000 Decennial Census, 2006–10 and 2009–13, 5-year ACS, 2000 and 2013 HUD’s Picture of Subsidized Households, CHPC. Calculations by the authors.

TABLE 4.6 Change of low-income households, linear regressions. Change in low income households, 2000–13 Intercept

−33.829

Median household income (/10000), 2000

9.850

*

Income squared, 2000

−0.326

*

% Asian, 2000

108.805

***

% non-Hispanic black, 2000

14.670

% Hispanic, 2000

234.995

***

% Renters, 2000

−74.772

***

Core city TOD, 2000

17.886

Non-core city TOD, 2000

−44.087

Adjusted R-squared

0.065

n

1569

Source: Calculations by the authors.

***

Transit-oriented displacement Chapter | 4

65

TABLE 4.7 Relationship between TOD area type and gentrification, exclusion and displacement.

TOD area

Gentri- Gentrification, fication, 1990s 00s

Change in federally Low