1. Evaluating the Potential for Justice in Urban Climate Change Adaptation in the U.S.: The role of institutions Sara Hughes, Ph.D. Urban Affairs Association March 21, 2014 ORISE Postdoctoral Research Participant at U.S. EPA

2. Disclaimers The work presented here was carried out both during my postdoctoral appointment with NCAR and as an ORISE postdoctoral research participant at the U.S. EPA. The views expressed herein are those of the author and do not necessarily reflect the views or policies of the U.S. EPA.

3. Outline 1.Cities and climate change adaptation 2.The role of institutions in promoting (just) adaptation 3.Preliminary evaluations of the relationship between urban sustainability institutions and policies 4.Gaps and priority areas for adaptation research

4. 1. Cities and Climate Change Adaptation Cities are sites of climate change impacts Increasing number of 100-degree days Uncertainty in water supplies Source: USGCRP 2009

5. 1. Cities and Climate Change Adaptation Cities are sites of climate change impacts Concentrations of people, economies, and infrastructures Nodes of authority

6. 1. Cities and Climate Change Adaptation Decentralization of climate change response to local level in the U.S. Driven by fiscal and political conditions Driven by local jurisdiction over important policy areas Increases importance of local decision makers and decision making processes in adaptation

7. 1. Cities and Climate Change Adaptation Cities are sources of innovation and policy action

8. 1. Cities and Climate Change Adaptation Adapting cities to climate change engages sustainability goals – realigning urban priorities Reducing urban environmental exposures and vulnerabilities to natural hazards −Protecting coastal ecosystems −Mitigating urban heat islands Reducing consumption of increasingly scarce, expensive, or variable natural resources Enhancing social and economic resilience −Improving health −Educating people about evacuation routes −Providing opportunities to increase personal and community assets and access to resources

9. 2. The Role of Institutions These types of policies have the potential to restructure a city and reallocate environmental burdens and benefits Understanding the implications for disadvantaged populations is a major gap in urban climate change policy research (Bulkeley 2010) Institutional form and capacity frequently cited as a condition of local climate change action (Hughes 2013; Romero-Lankao et al. 2013), but limited empirical work to test this theory

10. 2. The Role of Institutions The role of institutions in promoting (just) adaptation Institutions of local government shape incentives, priorities, and decision making power Allocate money and personnel to programs Hypothesis: Budgets, staff and citizen input specific to sustainability will enhance (just) local adaptation policy action

11. 3. Evaluating Urban Programs in the U.S. Local sustainability plans: indicators of urban adaptation

12. 3. Evaluating Urban Programs in the U.S. Local Government Sustainability Survey 2010 ⁻ International City/County Management Association ⁻ 2,176 responses (25.4% response rate) ⁻ Detailed report of policy initiatives of Chief Administrative Officers in U.S. local governments International City/County Management Association. 2010. Local Government Sustainability Survey. http://bookstore.icma.org/Local_Government_Sustainabilit_P2097C170.cfm Local sustainability plans: indicators of urban adaptation

13. 3. Evaluating Urban Programs in the U.S. Number of cities Adoption of Sustainability Policies by U.S. Cities (N=1,677)

14. 3. Evaluating Urban Programs in the U.S. Number of cities Adoption of Sustainability Institutions by U.S. Cities (N=1,677)

15. 3. Evaluating Urban Programs in the U.S. Is policy action influenced by sustainability institutions?

16. 3. Evaluating Urban Programs in the U.S. Institutions (ICMA) −Citizens committee −Sustainability budget −Sustainability staff −Manager form of govern ment Demographics (Census) −Population −Income −% Democratic voters −% Highly educated Regions (ICMA) −Midwest, Mid-Plains −Southeast, West Coast Independent variablesDependent variables Max. Lik. Probit Models Formal policy GHG reduction targets Impervious surface limits Composting program Bike lane expansions Land conservation Farmer’s markets Low-income energy programs Low-income transportation programs

17. 3. Evaluating Urban Programs in the U.S. Independent Variable PolicyGHG Target Imp. Surf. CompostBike Lanes Land Cons. Citizens committee -0.0761 (0.153) -0.0820 (0.170) 0.608*** (0.131) 0.296* (0.127) 0.00794 (0.132) 0.267. (0.139) Sust. Budget 0.0952** (0.0332) 0.132*** (0.0369) 0.0743** (0.0286) 0.0639* (0.0280) 0.223*** (0.0299) 0.0222 (0.0303) Sust. Staff 0.551 (0.387) 1.246** (0.414) 0.125 (0.336) 0.173 (0.330) 0.804* (0.343) 0.309 (0.357) Manager FOG 0.00370 (0.00371) 0.0184*** (0.00435) -0.0000439 (0.00302) -0.00269 (0.00298) 0.00637* (0.00308) 0.00354 (0.00326) (log)Income 0.0352 (0.141) 0.204 (0.161) 0.0883 (0.116) 0.531*** (0.118) -0.256* (0.124) 0.00690 (0.120) (log)Pop. -0.00835 (0.148) 0.365* (0.166) -0.328** (0.126) 0.476*** (0.125) 0.657*** (0.126) -0.321* (0.134) % Highly ed. -0.0319 (0.142) -0.0116 (0.179) -0.283* (0.116) 0.0961 (0.118) 0.0307 (0.118) -0.459*** (0.127) % Democratic -0.188 (0.128) -0.258. (0.157) -0.136 (0.102) 0.514*** (0.104) -0.00926 (0.105) -0.344** (0.108) West Coast 0.522*** (0.0930) 0.546*** (0.104) 0.218** (0.0845) 0.0400 (0.0835) 0.168. (0.0871) 0.189* (0.0893) Mid-plains 0.617*** (0.105) 0.422*** (0.118) -0.0432 (0.103) 0.0809 (0.0998) 0.207* (0.104) 0.198. (0.105) Midwest 0.660*** (0.060) 0.378*** (0.111) 0.0243 (0.0896) 0.161. (0.0872) 0.289** (0.0897) 0.303** (0.0934) Southeast 0.0100 (0.0858) -0.201* (0.101) 0.384*** (0.0696) 0.136* (0.0677) 0.164* (0.0715) -0.197** (0.0756) Numbers = Regression Coefficient (Standard Error). = 90% confidence * = 95% confidence ** = 99% confidence *** = 99.9% confidence Preliminary results

18. 3. Evaluating Urban Programs in the U.S. Independent Variable PolicyGHG Target Imp. Surf. CompostBike Lanes Land Cons. Citizens committee -0.0761 (0.153) -0.0820 (0.170) 0.608*** (0.131) 0.296* (0.127) 0.00794 (0.132) 0.267. (0.139) Sust. Budget 0.0952** (0.0332) 0.132*** (0.0369) 0.0743** (0.0286) 0.0639* (0.0280) 0.223*** (0.0299) 0.0222 (0.0303) Sust. Staff 0.551 (0.387) 1.246** (0.414) 0.125 (0.336) 0.173 (0.330) 0.804* (0.343) 0.309 (0.357) Manager FOG 0.00370 (0.00371) 0.0184*** (0.00435) -0.0000439 (0.00302) -0.00269 (0.00298) 0.00637* (0.00308) 0.00354 (0.00326) (log)Income 0.0352 (0.141) 0.204 (0.161) 0.0883 (0.116) 0.531*** (0.118) -0.256* (0.124) 0.00690 (0.120) (log)Pop. -0.00835 (0.148) 0.365* (0.166) -0.328** (0.126) 0.476*** (0.125) 0.657*** (0.126) -0.321* (0.134) % Highly ed. -0.0319 (0.142) -0.0116 (0.179) -0.283* (0.116) 0.0961 (0.118) 0.0307 (0.118) -0.459*** (0.127) % Democratic -0.188 (0.128) -0.258. (0.157) -0.136 (0.102) 0.514*** (0.104) -0.00926 (0.105) -0.344** (0.108) West Coast 0.522*** (0.0930) 0.546*** (0.104) 0.218** (0.0845) 0.0400 (0.0835) 0.168. (0.0871) 0.189* (0.0893) Mid-plains 0.617*** (0.105) 0.422*** (0.118) -0.0432 (0.103) 0.0809 (0.0998) 0.207* (0.104) 0.198. (0.105) Midwest 0.660*** (0.060) 0.378*** (0.111) 0.0243 (0.0896) 0.161. (0.0872) 0.289** (0.0897) 0.303** (0.0934) Southeast 0.0100 (0.0858) -0.201* (0.101) 0.384*** (0.0696) 0.136* (0.0677) 0.164* (0.0715) -0.197** (0.0756) Numbers = Regression Coefficient (Standard Error). = 90% confidence * = 95% confidence ** = 99% confidence *** = 99.9% confidence Preliminary results

19. 3. Evaluating Urban Programs in the U.S. Independent Variable Low-income energy programs Low-income transportation programs Citizens committee -0.0396 (0.123) 0.106 (0.0947) Sust. Budget 0.533*** (0.130) 0.157 (0.110) Sust. Staff 0.144 (0.127) 0.226* (0.0981) Manager FOG -0.0846 (0.104) -0.114 (0.0764) (log)Income -0.303 (0.194) -0.714*** (0.147) (log)Pop. 0.115** (0.0391) 0.0720* (0.0307) % Highly ed. 0.0107 (0.484) -0.242 (0.386) % Democratic 0.0115* (0.00446) 0.000951 (0.00326) West Coast 0.364* (0.181) 0.0790 (0.134) Mid-plains 0.229 (0.181) 0.0670 (0.119) Midwest 0.153 (0.162) -0.0168 (0.109) Southeast 0.0473 (0.188) -0.415** (0.137) Numbers = Regression Coefficient (Standard Error). = 90% confidence * = 95% confidence ** = 99% confidence *** = 99.9% confidence Preliminary results

20. 3. Evaluating Urban Programs in the U.S. Independent Variable Low-income energy programs Low-income transportation programs Citizens committee -0.0396 (0.123) 0.106 (0.0947) Sust. Budget 0.533*** (0.130) 0.157 (0.110) Sust. Staff 0.144 (0.127) 0.226* (0.0981) Manager FOG -0.0846 (0.104) -0.114 (0.0764) (log)Income -0.303 (0.194) -0.714*** (0.147) (log)Pop. 0.115** (0.0391) 0.0720* (0.0307) % Highly ed. 0.0107 (0.484) -0.242 (0.386) % Democratic 0.0115* (0.00446) 0.000951 (0.00326) West Coast 0.364* (0.181) 0.0790 (0.134) Mid-plains 0.229 (0.181) 0.0670 (0.119) Midwest 0.153 (0.162) -0.0168 (0.109) Southeast 0.0473 (0.188) -0.415** (0.137) Numbers = Regression Coefficient (Standard Error). = 90% confidence * = 95% confidence ** = 99% confidence *** = 99.9% confidence Preliminary results

21. 3. Evaluating Urban Programs in the U.S. Interpretation: Predicted probabilities Sustainability institutions more than double the likelihood that a city has a formal policy, GHG targets Sustainability institutions also increase the likelihood of programs for low-income communities −Budgets increase the likelihood of energy programs from 6% to 16% −Staff increases the likelihood of transportation programs from 17% to 24%

22. 4. Gaps and Priority Areas Implications for (just) adaptation Institutions for sustainability play a consistent and large role in promoting policy action Institutional capacity also increases likelihood of programs for low income communities, but less consistently Politics of promoting sustainability/adaptation really about institutional change, and who institutions are designed to benefit −Getting the institutions “right”

23. 4. Gaps and Priority Areas Number of cities Adoption of Sustainability Institutions by U.S. Cities (N=1,677)

24. 4. Gaps and Priority Areas Priority areas for future research Institutional change is a unique political challenge −Lock-in −Vested interests −Mobilization challenges −Authority vacuums Research: Where does institutional change come from at the local level? Who accomplishes it? Advocacy: Encouraging adaptation/sustainability policy action at the local level starts with institutional change?

25. Thank you hughes.sara@epa.gov