Unpacking the Climate Change Policy Regime: Adaptation and Mitigation policies in US Cities

Transcription

1 Unpacking the Climate Change Policy Regime: Adaptation and Mitigation policies in US Cities Authors: Robert S. Wood * Andy Hultquist * Rebecca J. Romsdahl ** * Dept of Political Science and Public Administration University of North Dakota 293 Centennial Drive, Stop 8379 Grand Forks, ND USA rwood@business.und.edu andy.hultquist@business.und.edu ** Department of Earth System Science and Policy University of North Dakota 4149 University Avenue, Stop 9011 Grand Forks, ND USA romsdahl@aero.und.edu 1

2 Abstract: As the United States continues to struggle with national solutions to climate change, states and local governments have emerged as leaders in this area and a significant body of research has developed to study why some jurisdictions adopt climate change policies while others do not. One strand of interdisciplinary research has focused on distinguishing between mitigation and adaptation policies, yet thus far relatively little attention has been given to the ideas, institutions, and interests that underlie these sets of policies. Much of the research to date assumes that the factors motivating adaptation policies are similar to those that motivate mitigation policies. This paper applies a policy regimes perspective to test the notion that they are not the same, but that competing problem definitions lead to different sets of policies with different feedback processes and distinct governing structures supported by different sets of interests. The paper uses unique data from a new survey of local climate change policies gathered from over 200 local governments in 11 states of the Great Plains region. The data include direct measures that distinguish between mitigation and adaptation policies, and indicators of whether each policy was framed as a climate change policy or not. Data was also collected about the local atmosphere with regard to climate change policies, the role of government, and the perceived vulnerability to climate change. 2

3 Unpacking the Climate Change Policy Regime: Adaptation and Mitigation policies in US Cities Introduction A substantial body of interesting research has emerged over the last several years on the efforts of state and local actors in addressing climate change, and it has become clear that in the United States, state and local governments are directing the lion s share of climate change regulatory efforts. It remains far less clear why some (cities, in particular) are far more active than others, which policies are more widely adopted than others, and whether their actions are part of a coordinated effort to combat climate change impacts or simply a series of unrelated policies that all happen to reduce potential impacts from climate change. For at least the past decade, cities and states have been at the heart of climate change policy, addressing a fundamentally global problem through a patchwork of collaborative network associations and voluntary measures. A number of scholars have noted this peculiar byproduct of the political gridlock in Washington, and the climate actions of states are well established (Rabe 2008; 2004; Carley 2011). In our view, a promising strand of research that has received somewhat less attention examines the development of climate change policy initiatives at the municipal level. Initially, the bulk of these studies focused on the how, the when, and the why cities adopt various mitigation measures, especially the low hanging fruit items such as energy efficiency (Bulkely & Betsill 2003; Rabe 2004). But other studies have examined how climate policies can be achieved in cities aiming for broader sustainability goals (Portney et al. 2010; Wang et al. 2012). Most recently, studies using surveys and quantitative 3

4 models have begun to identify the distribution of mitigation policies in major US cities as well as the factors that motivate municipalities to take action on climate change (Feiock & Bae 2011; Krause 2012; Sharp et al. 2011; Zahran et al. 2008; ). Despite these efforts, significant gaps in the literature remain. For instance, we know far more about cities who have made explicit commitments to climate networks than we do about those who have not. We also know significantly more about mitigation than we do about adaptation. And to this point, very little has been done to explain these policies in the context of the policy studies literature, which we argue is an essential element to understanding the motivations behind these actions. For example, as it becomes clear that the target reductions of GHG emissions advocated by the IPCC (Pachauri & Reisinger 2007) will not be met in time to avoid major climactic impacts, policymakers have begun to discuss the role of adaptation policies in combatting climate change and researchers have begun to include adaptation measures in their models. Drought, floods, increased soil erosion, degradation of water quality and species loss are less commonly associated with climate change than record- breaking storms or heat, but policies to adapt to each of these impacts are important components of municipal governance. Many, if not most communities in the United States have had policies in place for each of these issues for many years, but how many have been updated to account for potential climate impacts? And how many of those were framed to citizens as explicitly addressing climate risks? While the literature on adaptation has grown significantly in recent years, much of the focus to this point has been on adaptation in places where impacts are already substantial (see Adger et al 2013). We still know little about the how, the when, and the why of adaptation 4

5 policies in ordinary cities and towns. Are there meaningful differences between cities that implement adaptation activities and those who adopt mitigation activities? Can we combine the two for purposes of evaluating a city s commitment to climate change, or are they fundamentally distinct? This paper responds to these questions in several ways. First, we provide a new quantitative data set gathered for this project from 232 municipalities distributed across ten states in the central United States. The sample frame was designed to include cities of all sizes within a smaller geographic region (the Great Plains), distinguishing it from previous studies that have targeted all cities over 100,000 in population nationally (see Krause 2012; Wang et al 2012 for examples). Second, for each city, we use hard counts of the number of specific mitigation and adaptation policies in place and are able to distinguish between those that were framed as climate change policies and those that were not. And third, we model a range of influences to test whether mitigation and adaptation are shaped by the same forces or are fundamentally different. We distinguish between mitigation and adaptation for several reasons. First, among climate policy scholars, the number of policies adopted by a local government has been widely used as an indicator of commitment to climate protection (Krause 2011; 2012; Romsdahl et. al 2012). Yet it is not immediately clear to us whether adaptation policies should be included in these measures. It is possible that these policies are used to soften up citizens and increase support for other climate protection measures, but it is equally possible that they remain substantially unrelated to climate protection efforts. We see this as an empirical question that 5

6 is addressed in our model by distinguishing between influences from the policy environment, the attitudes of local leaders, and the atmosphere in the community. Second, the policy studies literature has long depicted the subsystem as the primary unit of analysis for studying policy change, but the concept of a policy subsystem loses traction in the context of local government where the same actors are directly involved in nearly all policy decisions. At the federal level, climate change mitigation policies operate in a different subsystem than policies to promote adaptation planning. At the municipal level, both types of policy are decided by the same actors in the same room, in competition with any number of other issues. We believe that at this level, shared ideas matter, and can drive policy development across an array of otherwise distinct subsystems. Recent research has introduced a new theoretical construct the policy regime that conceptualizes connections between and across subsystems based on the ideas, institutions and interests they share (Jochim and May 2010). We find this to be a useful way to think about local climate change policies, and by comparing the influences that shape adaptation and mitigation in our analysis, we will explore the possibility that a set of underlying ideas a climate change regime is present that connects these policies and makes sense of actions that can be difficult to otherwise explain in the context of subsystem dynamics. The paper is organized as follows: In the first section we outline briefly the theoretical underpinnings of our research approach. This is followed in the second section by the formal presentation of the regression model used to determine the impact of elements of the policy environment, government attitudes toward climate change, and community atmosphere on adaptation and mitigation policy adoption. A discussion of the data collection process and the 6

7 operationalization of the measures used in our models follows in the third section of the paper. In the fourth section, we present the descriptive statistics on the distribution of mitigation and adaptation policies followed by the findings from our model. In the final section, we discuss the implications of these findings for policymakers and researchers, as well as the directions they suggest for future research. Theory and Literature Climate change is almost certainly one of the most important policy challenges of this generation. The choices made in the next decade by governments, businesses, and citizens will have profound and lasting impacts that will endure for many generations. As the political polarization of the issue has made national solutions more difficult, the actions of cities have emerged as the focus of a growing body of climate policy literature, one that provides a foundation for this research. In an extensive assessment of sub- national mitigation efforts, (2008) suggest that the rapid proliferation of climate action plans among cities and states has the potential to achieve what the national government has not, and reduce overall U.S. emissions to 2010 levels by Subsequent research has suggested that cities with climate action programs and goals are more successful at reducing emissions than those with no plan, but note that only around 600 local governments have adopted such plans (Millard- Ball 2012). A related strand of research examines the factors that lead local governments to adopt climate action plans (Tang et al. 2010; Tang et al. 2011), how land use planning is impacted by climate change (Tang, Hussey, and Wei 2009), and how local governments are bridging the gap between these efforts (Tang, Wang, and Koperski 2011). Each of these efforts has tended to focus on efforts to mitigate GHG emissions and has confined the analyses to cities in 7

8 environmentally progressive areas that have previously signaled a commitment to climate protection. Adaptation to climate change has also been studied for some time by botanists, ecologists, sociologists, anthropologists, and many others. Only relatively recently, however, have the adaptation policies of local governments drawn the attention of climate scholars (Baker et al. 2012). Many of these have focused on specific cases where impacts from climate change are already occurring or are imminent (Adger et al. 2003; Naess et al. 2005; Roberts 2008; Laukkonen et al. 2009) Our research follows a slightly different trajectory that, we believe, complements the aforementioned work nicely. By focusing on an area of the United States with traditionally low levels of climate protection commitment, we expect to better understand the differences between cities that adopt climate protection policies and those that do not. By conceptualizing climate protection fairly broadly, we expect to capture activities in our data that respondents do not consider to be climate change policies, but that do, nonetheless, reduce the impacts of climate change. And, by disaggregating mitigation and adaptation activities, we expect to better understand the motivations and influences that shape their policy choices. Conceptualizing Local Climate Protection A dominant element in much of the local climate initiative literature springs from the attempt to distinguish cities that are active in climate protection from those that are not. There are many different ways to operationalize this distinction, from membership in climate networks to the completion of a GHG inventory, from the presence of a climate action plan to a budget line- item for climate protection. Each measure has its own strengths and weaknesses, 8

9 yet most are dichotomous. We believe that few cities are either universally in favor of or opposed to climate protection, but rather exist along a continuum of engagement. We hypothesize that by using continuous variables, the influences that shape climate protection policies will be more clearly visible, as well as any differences that may exist between mitigation and adaptation activities. For this reason, we choose to use cumulative counts of adaptation and mitigation activities as dependent variables for the models and analyses that follow. Basing our efforts upon similar efforts by Krause, and our own previous research, we identify 14 widely accepted mitigation activities and 14 widely accepted adaptation activities in our survey instrument (Krause 2011; Romsdahl, Wood and Hultquist 2012). A significant strength of this approach is that hard counts of policies are used in place of estimates or proxies. While many studies have engaged with the fundamental question of whether or not cities are engaged in climate protection, very few have gathered data on the presence or absence of specific measures. And, to our knowledge, we are the first to gather data on climate protection activities from cities with populations of less than 100,000. Explaining Variation in Climate Protection Policies Rationally speaking, local governments should have as little to do with GHG mitigation as possible. A vast literature on public choice theory clearly suggests that, since climate protection is a public good with diffused benefits and concentrated costs, cities will be reluctant to engage in these activities voluntarily all other things being equal. Yet the large number of cities that are active in climate protection suggests that all other things are not equal. The 9

10 excellent discussion paper by Sippel and Jenssen (2009) clarifies how a wide range of co- benefits and challenges might alter the rational cost/benefit calculation for a given city sufficiently to influence policy activities (see also (Urpelainen 2009). While it is beyond the scope of this paper to test all the factors they identify, we suggest below three clusters of variables that might be reasonably expected to shift the cost/benefit calculus in a community, either by increasing the potential costs of inaction or by increasing the potential benefits of action beyond the non- excludable benefits typically associated with climate protection. The Policy Environment The first cluster the policy environment is conceptualized as influences from the physical world, such as vulnerability to climate impacts, previous disaster events, population, resources, and capacity. It would also include external constraints that may be placed upon a city by state or federal governments. It is intuitively reasonable to expect the policy environment to influence the level of climate protection activities in a city. Some cities are highly vulnerable to climate change impacts, perhaps due to geographic features or heavy reliance on weather related industries such as agriculture. This vulnerability may increase the potential costs of inaction, particularly for adaptation activities, sufficiently that it becomes rational for them to act. In general, we would expect policy environment variables to all be positively associated with climate protection activities. That is, those cities with higher levels of vulnerability, resources, population, etc. should also have higher levels of climate protection activities. 10

11 Government Attitude Leadership matters. Mayors set the agenda for their cities by prioritizing and persuading even if they are not in a position to dictate policy over a council. The second cluster the attitude of government is comprised of variables that capture the mayor s attitudes toward the appropriate role of local government with regard to climate change. Key concepts in this cluster are whether responding to climate change is viewed as a global problem, a national problem, or a local problem, and the extent to which the mayor believes that cities have a responsibility to act on climate change if other levels of government do not. An additional, widely used indicator of climate protection commitment is signing the US Mayor s Climate Protection Agreement (USMCPA). To date, over 1,000 U.S. cities have signed this agreement, expressly committing their communities to reducing GHG emissions. In an examination of the USMCPA, Warden (2011) proposes a theory of viral governance to explain the rapid rise in signatories between Warden argues that the combination of a shared mission within the network of concerned mayors, their subsequent interactions through national meetings and other activities, plus a feeling of solidarity among cities and their quest for green capital through friendly competition, combined with an open policy window for action on climate change, combine to produce a pattern of viral governance under the banner of the USMCPA. Warden s work suggests that joining the USMCPA can be expected to have a lasting and significant influence on city policy. Other scholars, in contrast, have found that membership in the USMCPA, in itself, means little. Krause (2012) compares the influence of membership in the two major climate networks (USMCPA and ICLEI) and finds that the Mayor s agreement is 11

12 significantly less influential on policy than the more demanding ICLEI. Yet the characteristics that undermine its effectiveness for Krause no cost, no accountability, and no penalties do not undermine the USMCPA s value for our purposes as a symbolic indicator of a mayor s attitude toward climate change. As with factors from the policy environment, we expect the relationship between government attitude and climate protection activities to be positive. Community Atmosphere In the United States, climate change continues to be a highly politicized issue at all levels. High profile advocates on both sides of the issue routinely use derogatory terms to describe each other and undermine the credibility of their opponents. In many communities across rural America, there is also a great deal of skepticism about the science of climate change and open hostility to proposals that would spend taxpayer dollars to reduce greenhouse gas emissions (Lorenzoni and Pidgeon 2006). Despite this fact, the public atmosphere toward climate change is not monolithic. With the third cluster the public atmosphere we intend to capture the collective position of each community on a multi- dimensional scale. Rather than calculate a simple one- dimensional indicator of support for climate protection, we asked respondents to rate how well each of 12 indicators describes their community. The indicators target the emotional and values elements, such as anger, frustration, confusion, and skepticism that contribute to polarization on this issue. We also include in this cluster an indicator of partisanship in the community. Democrats are generally more supportive of climate protection activities than are 12

13 Republicans, and controlling for this in the model ensures that influences from the dimensions of support and skepticism are distinct from partisanship. Data and Measures This paper s analyses are based primarily on data obtained via a survey of 232 mayors offices in 10 Great Plains states. 1 The data for the project was collected in spring 2012 using an online survey instrument via SurveyMonkey. To create a representative sample frame, a proportion of the 5,000 municipalities identified in the 2010 Census was calculated for the 10 target states. An estimated number of cities to sample from each state was based on an overall sample target of 900. Those cities with populations below 1,000 were excluded and all cities with populations above 100,000 and all signatories to the USMCPA were included. The remainder of the sample in each state was selected randomly from cities with populations between 1,001 and 100,000. Envelopes were mailed to each official city address containing an introductory letter that included an invitation to complete the survey online. A link to SurveyMonkey was included in the letter that was unique for each city, allowing us to track responses and use additional data about the jurisdiction in subsequent analysis. The letters also included a paper copy of the survey and a self- addressed stamped envelope for those who preferred to complete the survey this way. A second mailing was sent out approximately 3 weeks after the initial mailing, followed by phone calls to each non- responding city approximately 3 weeks after the second mailing. In most cases, callers were unable to speak directly with the mayor, but were often 1 Great Plains states included: Montana, Wyoming, Colorado, North & South Dakota, Minnesota, Nebraska, Kansas, Oklahoma, and Texas. 2 Given this low response rate, the question of the sample s representativeness is a valid one. To assess the 13

14 successful in obtaining an address that was later used to follow up with an additional . After repeated contacts and reminders, 232 cities ultimately responded to our survey request, for a response rate of approximately 25 percent 2. While not ideal, this result was not unexpected, given the part- time nature of mayors in smaller communities and the many tasks they must perform. The response rate is consistent with other surveys of a similar nature, but given the political controversy associated with climate change, it may also be that mayors were more reluctant than usual in responding to our request for data. To measure the level of climate protection activity or commitment in a city, we asked mayors to indicate, from a list of 14 mitigation activities, those that have been implemented in their city. A similar list of 14 adaptation activities was also presented in the survey, with mayors asked to identify which of the activities had been implemented or updated within the last 10 years. In addition, in a separate box, Mayors were asked to indicate which of the 14 mitigation and 14 adaption activities in place in their community were framed as a climate change policy or addressing climate change risks. 2 Given this low response rate, the question of the sample s representativeness is a valid one. To assess the representativeness of these responses, we employed a t-test to examine whether responding cities differed from nonrespondents along two dimensions population and political characteristics (percent Democratic vote in the 2012 Presidential election). While the mean population of responding locations was found to be higher than those of nonrespondents, this difference was not statistically significant at the 5% level. Respondents showed slightly more Democratic support (38.3%) than nonrespondents (36.2%), a difference which, while statistically significant at the 5% level, is rather small in terms of practical magnitude. To gauge whether cities in different states responded at different rates, we also used a t-test to compare each state s response rate to that of the sample overall (24.9%). For eight of the ten states in our sample, no significant difference was found at the 5% level. For the two states where a significant difference was found, Texas exhibited a slightly lower response rate (15.8%), while Montana showed a higher response rate (44.4%). While these results do indicate some statistically significant differences between responding cities and our overall sampling frame, at the same time, we feel that these differences are relatively minor in practical terms, and do not impair the ability of our results to be generalized to typical communities in the Great Plains region. 14

15 To gauge individual attitudes toward local climate change vulnerability and the appropriate role of local government in addressing this issue, Mayors were asked to respond to five Likert- scale (strongly disagree strongly agree) questions reflecting their agreement with the following statements: 1. In the absence of national climate change legislation, state and local government should act on their own to reduce the impacts of climate change. 2. State and local government should wait for national climate change legislation before addressing climate change. 3. State and local government should just adapt to climate change impacts as they occur. 4. Government action is not needed to address climate change people will adjust their behaviors as free- market prices change. 5. My community is highly vulnerable to impacts from climate change (see Appendix, Question 1). Mayors were also asked, using the same scale, to indicate how well each of twelve statements reflected their city public atmosphere towards climate change (see Appendix, Question 4). These questions, as well as the principle components analysis used to extract their common factors, are explained in greater detail in the Methods section below. To supplement the data collected from the survey, additional data elements on each community were obtained from the following sources. The U.S. Department of Commerce s Bureau of Economic Analysis data was used to provide per capita income for each location at the county level. The cumulative value of disaster declarations affecting each location over the past ten years was obtained from the Federal Emergency Management Agency (FEMA). Finally, data on whether locations had a Climate Action Plan or a voluntary GHG reporting system at the state level was drawn from the Center for Climate and Energy Solutions (C2ES), and information on cities adoption of the Mayors Climate Protection Agreement was obtained from the United States Conference of Mayors. 15

16 Methods To model the impact of these three clusters of influences on the number of climate change policies that a jurisdiction has implemented or updated in the past ten years, we employ ordinary least squares (OLS) regression analysis to estimate three models, each of which adopts the following basic form: #ClimatePolicies! = β! + β! POLICY! + β! GOV T! + β! COMMUNITY! + e! The dependent variable in the equation is the number of climate change policies implemented or updated by a given city in the past ten year period. Using the three vectors of independent variables discussed below, we run three models with three separate measures for the dependent variable. In our first model, the dependent variable is expressed as all climate change policies, both mitigation and adaptation, which the ith city has implemented or updated over the past decade. The second and third models disaggregate the dependent variable, and measure the impact of the equation s independent variables on the number of mitigation and adaptation policies, respective, adopted by a given city. This allows us to directly address the question of whether the same factors play a role in the local adoption of both mitigation and adaptation policies, or whether there are important differences between the elements leading to mitigation policies and those linked to adaptation. The explanatory factors include three vectors intended to model the three clusters of influences policy environment, government attitude, and community atmosphere discussed 16

17 in the previous section. Each of these vectors in turn contains several independent variables. The vector representing the impact of elements contained in the policy environment, POLICY!, consists of six measures, including the city s population as of 2005, per- capita income at the county level (in 2011 dollars), the cumulative value (in billions of 2011 dollars) of FEMA disaster assistance disbursed to the county in the past ten years, the mayor s perceived vulnerability of the community to climate change (survey Question 1, part e ), a dummy equaling 1 if the city s state had a climate action plan, and an additional dummy variable indicating whether the city s state had a voluntary GHG reporting system in place. The second vector, GOV T!, consists of five variables intended to capture the attitude of local government towards climate change policy. The first of these variables is a dichotomous measure of whether or not the city had signed the USMCPA. The remaining four variables are each drawn from our survey instrument s measures of mayoral attitudes towards the role of local governments in addressing climate change (Question 1, parts a through d ), each of which was measured using a five- point Likert scale, as described in the previous section. We use the model s final vector, COMMUNITY!, to capture a city s community atmosphere towards climate change through five variables. The first of these, intended to capture local political affiliation or sentiment, is the percent of the county which voted Democratic in the 2012 Presidential election. The remaining four variables are the product of a factor analysis using responses from the 12 survey questions asking mayors to rate their community s attitude towards climate change. Though each of the twelve questions captures a distinct and useful aspect of local attitudes, for the purposes of this analysis we are concerned with capturing the broader characteristics of the community atmosphere that might shape or 17

18 influence the options available to policymakers. To explore this possibility, we perform a principle components analysis (with varimax rotation), both to reduce the number of variables in the model and to reveal underlying dimensions in the data. The results of this analysis are presented in Table 1. *Table 1 about here* Based on the results of the extraction, we identify four distinct dimensions that comprise the public atmosphere in our data. Inferring their names from their loadings, we label these factors Support, Skepticism, Confusion, and Apathy. We are intrigued by the possibilities suggested by the factor analysis, and particularly by the factors we label Confusion and Apathy. The presence of these two distinct dimensions suggests a complexity of local views on climate change that extends beyond the traditional support/skepticism dichotomy. In our view, it is interesting to note the clear distinctions between the four latent variables produced by the factor analysis. Each component question clearly loads at high levels with respect to a single factor (0.609 or higher), and loads at low levels with respect to the other three, suggesting that each of these four factors captures a separate piece of local public sentiment on the issue of climate change policy. It is also clear that conceptualizing the public atmosphere as a multi- dimensional construct permits a more nuanced modeling of local attitudes, and opens the door to a number of surprising possibilities in the results. One might imagine a highly contentious atmosphere characterized by high levels of support, opposition, and confusion. One might imagine another place with low support, moderate opposition, and high apathy where climate change is simply never discussed. Our expectations for the direction of influence from these variables are thus 18

19 more complicated than for the other clusters. Generally, we expect support and partisanship to be positively associated with climate protection activities, and Skepticism, Confusion, and Apathy to produce negative associations. * Tables 2 and 3 about here * Findings Before turning to the results of our regression analysis, as described above it is interesting to note a number of important findings which become apparent from a simple examination of the number and types of mitigation and adaptation activities which the respondent communities to our survey engage in. Tables 2 and 3 present distributions of the number of mitigation and adaptation activities, respectively, engaged in by cities in our sample, while Tables 4 and 5 detail the number and percent of cities engaging in each of the 14 individual mitigation and 14 adaptation activities, as well as the percent of cities explicitly framing each of those activities as climate change policy. Perhaps the most notable pattern in this data is the wide variation present in local mitigation and adaptation policy adoption. The distribution of mitigation activities in the data, displayed in Table 2, ranged from 0 to 14, with a mean score of Most communities in the sample had implemented some degree of mitigation policy, with 90 percent of cities reporting at least one such policy in place, but only 10.9% percent reported implementing more than 7 of the 14 activities and only 3 cities reported implementation of all 14. * Table 4 about here * Mitigation Activities 19

20 Among mitigation activities, as shown in Table 4, only four of the fourteen policies community- wide hiking and/or bike trails, efficient lighting in city streetlights, ordinances for developers regarding tree planting and/or removal, and provision of information to residents on energy efficiency were adopted in roughly half or more of the 211 communities responding to our survey, with the most widely- occurring among these, hiking and biking trails, still present in less than 60% of locations. Four of the fourteen policies GHG emission inventories, incentives for efficient commuting by city employees, adoption of formal GHG reduction plans, and dedicated municipal budget lines for climate protection activities were present in less than ten percent of the cities in our sample, with the least frequent of these, a dedicated budget item for climate protection, appearing in only 12 (5.7%) communities total. Also of interest is that those mitigation policies which are implemented the most frequently are ones that are less likely to be framed explicitly as addressing climate change. The most frequently adopted activity, hiking and biking trails, is framed as climate change- related in only 10.5% of the cities in which it is adopted, and none of the top five most common mitigation policies are framed as climate change in more than a quarter of the jurisdictions in which they occur. Conversely, while appearing in less than ten percent of responding jurisdictions, the four least common mitigation activities are those which are framed most often as climate change, with three of those four being identified as explicitly climate change- related policies in 44% or more of the cities in which they are in place. * Table 5 about here * Adaptation Activities 20

21 Adaptation policy adoption was somewhat stronger in our sample when compared to mitigation, with a mean number of 6.6 such policies adopted per city. Yet again, the variation in adaptation policy adoption is the most striking aspect of Table3. While over 95 percent of respondents engage in at least one adaptation policy, and 42.6% have adopted half or more of the fourteen policies, only a very small number again, three cities out of 211 have all fourteen adaptation policies in place. Likewise, when one considers the implementation of individual adaptation policies, as presented in Table 5, the finding of a greater penetration of adaptation activity adoption in our sample relative to mitigation activities appears to be upheld. While only four mitigation activities were adopted in more than half of the 211 responding locations, a full half of the fourteen adaptation activities in our study were implemented and/or updated in the last decade, with the most common of these, community warning systems for events such as storms and fires, present in over three quarters (77.7%) of cities. Presenting another contrast with mitigation activities, the least common adaptation policy, species/habitat protection plans, was present in 12.3% of cities, and no other adaptation activity appeared in less than a quarter of responding jurisdictions whereas, by comparison, a full eight of the fourteen mitigation activities were present in less than a quarter of the 211 cities in our sample. However, while adaptation activities were implemented more often than mitigation activities, both on average and when examined in terms of individual policy adoption rates, those adaptation policies were framed as climate change- related far less frequently than mitigation activities. Despite the frequency of its adoption, only six locations (3.7%) of the 164 implementing the most common adaptation activity, community warning systems, framed this 21

22 policy in terms of climate change, and for no adaptation activity did more than 16% of adopting jurisdictions express the policy in question as explicitly climate change- related. Likewise, while our summary statistics showed the least common mitigation activities to be the ones framed by the greatest percentage of adopting jurisdictions as climate change policy, all adaptation policies appear to be universally unlikely to be framed in such a manner, regardless of their degree (or lack thereof) of adoption. * Table 6 about here * Influences on Mitigation and Adaptation Policy Adoption Model I All Climate Policies Table 6 presents the results of the paper s primary regression analyses, modeling the number of climate change policies adopted as a function of the three groups of variables describing the policy environment, government attitudes, and community atmosphere. Turning first to the results contained in the column for All Climate Policies, which takes the model s dependent variable as the total number of mitigation and adaptation activities engaged in by a jurisdiction, several interesting results are apparent. First, among factors in the policy environment, population is significantly and positively correlated with climate change policy adoption at the 10% level, with each additional 100,000 residents associated with an additional 6/10ths of an adaptation or mitigation policy. Examination of the variables associated with government attitudes shows that mayoral agreement with the statement that cities and states should act on climate change if federal actors do not is correlated with higher levels of policy implementation at the 5% level here, for each additional level of agreement on the five- point Likert scale, cities display an additional 1.3 adaptation or mitigation policies on average. 22

23 The greatest, and perhaps most interesting, number of results from the model describing aggregate adaptation and mitigation policy adoption appear in the group of variables related to community atmosphere. Here, the percent of the county voting democratic in the 2012 Presidential election, the degree of ideological opposition to climate change (Factor 2) and the degree of confusion about climate change (Factor 3) are each positively and significantly associated with the number of combined adaptation and mitigation policies being implemented in a given city. Model II Mitigation Policies However, when policies are disaggregated and a distinction is made between mitigation and adaptation policies, a somewhat different set of results emerges. The second column of Table 6 presents results from regression Model II, when the equation s dependent variable is taken as the number of mitigation policies only. Whereas population appeared to have a significant influence on the total number of adaptation and mitigation policies combined, when the outcome is differentiated by type of policy, for mitigation activities, population no longer appears as a statistically significant influence. However, the location s exposure to, and severity of, weather- related incidents now does seem to matter, with the incremental $1 billion in FEMA disaster aid over the last decade linked to an additional 0.51 mitigation policies at the 10% significance level. Interesting differences also arise between the aggregate model and Model II s examination of mitigation policies only when one examines the impact of governmental attitudes. Here, while a mayor s agreement with the sentiment that local actors should take action on climate change in the absence of federal policy is still positively linked to 23

24 mitigation policy implementation at the 5% level, with each additional degree of agreement associated with an additional 0.63 mitigation activities, locations that are a signatory of the Mayors Compact on Climate Change now also display a significant, positive association with mitigation actions, implementing 1.73 more policies than location which are not a part of that agreement. As was the case with Model I s analysis of the influence on the total number of adaptation and mitigation policies adopted, Model II s examination also shows statistically significant impacts of community atmosphere- related variables on the number of mitigation activities engaged in by cities. However, while the percent of the county voting democratic in the 2012 Presidential election is still statistically significant, the degree of ideological opposition to climate change (Factor 2) and the degree of confusion about climate change (Factor 3) are no longer so. Instead, Factor 4, capturing community apathy towards climate change, is negatively linked to mitigation policy adoption at the 5% level, with each increasing degree of apathy tied to 0.52 fewer mitigation policies implemented in that community. Model III Adaptation Policies Just as Model II s examination of the influences on mitigation policies alone produced interesting differences when compared to Model I s examination of the influences on aggregate mitigation and adaptation policy adoption, so too does analysis of the factors influencing implementation of adaptation policy, as depicted in the Model III column of Table 6, display its own set of distinct and interesting patterns. While at least one factor classified as part of the policy environment appeared as significant in Models I and II, for adaptation policy, our results suggest that none of the six variables which we term policy environment plays a statistically 24

25 significant role in influencing the number of adaptation policies adopted by a city. Yet, while adaptation policy appears to differ from mitigation policy in terms of the impact of policy influences, in terms of the impact of governmental attitudes on the number of policies implemented, the story for mitigation appears quite similar to that for adaptation. Examining the influence of governmental attitude variables on the number of adaptation policies in place, once again, mayoral agreement that local actors should act on climate change if their federal counterparts do not is again positively and significantly associated with mitigation policy, with the incremental degree of agreement linked to an additional 0.05 adaptation activities. Another interesting contrast between the factors influencing mitigation and adaptation activities becomes apparent when Model III s results for the five community atmosphere variables are considered. While Democratic affiliation is, as in Models I and II, again found to be a statistically significant influence on adaptation policy implementation as it was with mitigation and total policies, examination of the influence of the four community atmosphere Factors shows Model III differing markedly from Model II. Whereas apathy has a statistically significant and negative link to mitigation policy implementation, no such relationship is in evidence with respect to adaptation policy. Instead, adaptation policy exhibits the same community factor- based influences as the number of overall policies in Model I, with Factor 2 (ideological opposition to climate change) and Factor 3 (confusion about climate change) showing a significant and positive association with the number of adaptation policies implemented or updated in jurisdiction in the last ten years. Finally, while individual examination of the three Models and the individual variables which are observed to influence the adoption of adaptation and mitigation activities are 25

26 certainly of interest in and of themselves, comparison of the three models also reveals a number of additional, important insights which merit comment before we proceed. First, disaggregation matters. The results of Models II and III confirm our general expectation that, as different types of policy responses to climate change, the adoption of policies of each type is likely to be linked to different factors in the local policy environment, government, and/or community attitudes. While our models did reveal two very important, and arguably intuitive, factors percent Democratic vote and mayoral sentiment towards local action in the face of federal inaction on climate change - which displayed a statistically significant and positive link to mitigation and/or adaptation policy adoption across all three models, other significant variables in all three groups of influences varied significantly across the three models. Along similar lines, while examination of the F- statistic for each regression indicates that all three models have a statistically significant degree of power in terms of explaining the amount of variation in their respective dependent variables, comparison of the Adjusted R 2 of each model also indicated another interesting finding. Specifically, the sixteen independent variables which we chose to include in our regression models, and which we hypothesized to have a potential role in determining the local adoption of mitigation and adaptation activities, do a decidedly better job in accounting for the observed variation in the former than they do in the latter. Our model s variables can be seen to explain roughly 27% of the variation in the number of local mitigation activities implemented, while accounting for barely 10% of the variation in the number of adaptation policies. This itself provides another confirmation that local- level adaptation and mitigation policies are likely to result from two sets of influences which, while sharing some common elements, are also likely to depend on different factors, as 26

27 well. These key differences, and thus the differences in the behavior of local governments with respect to mitigation and adaptation policy, would have been completely missed were the two types of policies inappropriately aggregated, and the results of Model I relied on alone. Implications As time passes without significant reductions in greenhouse gas emissions, what was once a single policy area has now become two. Increasingly, adaptation policies are becoming as much a part of the discussion about climate change as mitigation policies. Yet unlike many mitigation policies, which really only make sense when framed as combatting climate change, almost all adaptive measures a city might take can be adopted without a single reference to climate change. For researchers examining planned adaptation, this can be problematic for capacity building and mainstreaming climate policy. One of our explicit objectives in this project was to get a sense of how often policies were framed as climate change. Given the characteristics of this population, our expectations were low, and they were, for the most part, confirmed. In an open- ended question asking how climate change is framed (for policy and planning purposes), again and again respondents confirmed the use of alternate frames 3. Some examples include: in terms of economic benefit & resource protection. This framing was deliberate to garner support from residents who did not agree with climate change. It is framed as sustainability and sustainable development. Our city focuses on the benefits resource conservation can have on economic strength. When climate change has been mentioned historically, it was done so in the vein of even if 3 Question wording: In your city's policy and planning activities (for energy, conservation, natural resources management, land use, or emergency planning, etc.) how is climate change framed? 27

28 99% of the world's scientists are wrong, making changes to benefit the future of our city make sense. For the most part it is not. All of our actions are framed as environmental without defining climate change as part of the environment. We frame the initiative as: energy savings (=$ savings), as smart growth/good planning, and as common sense natural resource management. Climate change is only explicitly referenced in our Climate Protection Plan adopted in Most initiatives fall under the sustainability umbrella term. We are sensitive to conservation in all areas. However, the climate change movement is destructive as a policy and allocation of scarce resources and is not supported by valid science. Climate change is framed as one of several benefits of conservation measures. Other benefits of conservation, recycling, walking, etc. include it's good for the earth (regardless of climate change), healthful, economical, etc. (Great Plains survey respondents, 2012) Common sense. Economic development. Energy savings. Conservation. Sustainability. Though the frames have nothing to do with climate change, the policies do. A key implication here is that cities are enacting policies that address climate change even though they are reluctant to frame them as such. There is also a sense among a majority of mayors of a responsibility to act on climate change. When asked if cities have a responsibility, in the absence of national legislation, to act on their own to reduce the impacts of climate change, 57 percent either agreed or agreed strongly. When asked if cities and states should wait for national climate legislation before acting, 49 percent either disagreed or disagreed strongly. Moreover, more than 90 percent of cities report at least one mitigation measure and more than 95 percent report at least one adaptation activity. It is not reasonable therefore, to paint local governments, even in the deeply conservative states of the Great Plains, as refusing to take even the smallest steps to 28

29 reduce the impacts of climate change. It is reasonable to conclude that at least some policymakers feel a sense of responsibility in this area, but are substantially limited by low support for aggressive policies that have no alternate framing. For climate protection advocates, the implications should be clear. Focus on identifying and/or increasing the number of mitigation activities that have co- benefits and can be framed exclusively in terms of those benefits. The natural desire to persuade climate skeptics with scientific evidence of climate change has not typically been a successful strategy to this point. The politicization of the issue and the nature of the modern media environment have transformed climate change from a policy issue to a values issue, and values are not often altered through intellectual appeals. A second implication of the model is that apathy not skepticism is the enemy of mitigation policies. Places where no one talks about climate change are substantially less likely to adopt mitigation policies than those places where conversations about climate change are taking place. Among some climate protection advocates, there has been a tendency to avoid stirring up the hornet s nest in places where substantial opposition to their efforts is expected. Our data suggest that, when it comes to mitigation policies, controversy is better than apathy, even if opposition is substantial. Interestingly, this relationship is not present for adaptation policies, which provides a nice illustration of our third set of implications. Our findings suggest that the community atmosphere is a key ingredient for both mitigation and adaptation policies, but the dimensions that influence each are clearly different. In a model where adaptation and mitigation policies are combined, the coefficients suggest that as the levels of skepticism and confusion in a 29

30 community rise, so too does the number of policies adopted. This is exactly the opposite of the relationship we would expect, and has no easy explanation. When the policy types are considered separately, on the other hand, the story becomes easier to understand. A key point in the climate change debate is the fact that the skeptics principal objection to climate change policy is the assertion that it is caused by human activities. At this point, many skeptics concede that the climate is changing, but contend that this is a natural cycle which has occurred many times in the past and human efforts at greenhouse gas reduction are both expensive and futile. In this context, increasing skepticism and confusion are excellent motivators for a community to increase adaptation activities while simultaneously resisting mitigation policies, particularly when framed as mitigating climate change. The implication for climate policy researchers is that the aggregation of mitigation and adaptation policies into a combined total indicator of climate engagement may be unwise. In some ways this is surprising, particularly since cities with many mitigation policies also tend to have many adaptation policies. Yet despite a standard Pearson s correlation between the two of.59 (p=.000), they appear to be distinct sets of policies with distinct frames and distinct motivations. Conclusions An increasingly accepted view among climate scientists is that on the current trajectory, the average global temperature could increase 4 C before the end of the 21 st Century. Nnimmo Bassey, Chair of Friends of the Earth International, called this a death sentence for Africa, Small Island States, and the poor and vulnerable worldwide (Gerhardt 2011). The 2011 Durban platform is the first international agreement in more than a decade with the potential to 30

31 change this trajectory, though many details and opportunities for failure remain. In the United States, the issue has become highly politicized at the national level, and has been largely supplanted by the great recession, healthcare reform, and most recently, immigration reform. Despite President Obama s rhetoric to the contrary, the likelihood of a comprehensive national climate change policy remains somewhere between slim and none. In this policy vacuum, cities (and states) have emerged as unlikely, but effective leaders in climate protection activities. A viral governance movement has developed as a variety of state and local governments have signed agreements signifying efforts to address climate change planning from the bottom- up. Although these agreements are popular, the reality of local climate protection is less ambitious, due in part to the complex interactions of the many influential factors that shape local government policy- making. Understanding why cities do or do not develop climate change policies continues to be of considerable interest to scholars. The literature on this phenomenon has grown rapidly and continues to develop as circumstances evolve, and this study contributes to this effort in several meaningful ways. First, we present hard counts of the number of policies for each city as well as information on how issues were framed, thereby increasing our understanding of the situation on the ground in the communities of the Great Plains. Second, we develop and test three clusters of variables that have been related to the adoption of climate protection policies in previous research. And third, we disaggregate mitigation and adaptation activities, testing the extent to which the factors that shape them are similar. The findings suggest some similarities but also identify some differences that may be of use to both scholars and policymakers. 31

32 Ultimately, climate protection activities at the local level are complicated too. In their diagnostic framework for identifying challenging but malleable barriers to adaptation planning, Moser & Ekstrom (2010) contend that detecting climate change as a problem may be the first barrier that communities face in establishing proactive planning. Our findings suggest that many communities are bypassing this barrier by framing climate change policies as something else. Since adaptation policies are more amenable to alternative frames than mitigation measures, we expect that even highly skeptical cities will adopt nearly all our adaptation measures in the years to come. We believe it would be a mistake, however, to assume that these actions alone will serve as a bridge to greater mitigation activities. Framing matters. Leadership matters. And if cities wish to be successful at reducing their greenhouse gas emissions, mayors and other civic leaders must move beyond the values- based divide that has defined this issue and produced a political stalemate at the national level. Common sense, sustainability, economic development, conservation, and energy savings are all excellent alternate frames that generate support for climate protection activities without ever mentioning climate change. The good news is that, based on the open- ended comments we received, the mayors of the Great Plains are well aware of this fact and actively working to solve the problem. 32

33 Bibliography Adger, W. N., S. Dessai, M. Goulden, M. Hulme, I. Lorenzoni, D. R. Nelson, L. O. Naess, J. Wolf, and A. Wreford Are there social limits to adaptation to climate change? Climatic Change 93 (3): Adger, W. Neil, Saleemul Huq, Katrina Brown, Declan Conway, and Mike Hulme "Adaptation to Climate Change in the Developing World." Progress in Development Studies 3 (3): Baker, Ingrid, Ann Peterson, Greg Brown, and Clive McAlpine "Local Government Response to the Impacts of Climate Change: An Evaluation of Local Climate Adaptation Plans." Landscape and Urban Planning 107 (2): doi: /j.landurbplan Bulkeley, H., and M. M. Betsill Cities and climate change: Urban sustainability and global environmental governance. New York: Routledge. Carley, S. (2011). The era of state energy policy innovation: A review of policy instruments. Review of Policy Research, 28(3), Feiock, R. C., and J. Bae Politics, institutions and entrepreneurship: City decisions leading to inventoried GHG emissions. Carbon Management 2 (4): Gerhardt, T Get it Done! Youth to UN on Climate Treaty The Progressive, December 11, IPCC (Intergovernmental Panel on Climate Change Climate Change 2007: Synthesis Report of the IPCC Fourth Assessment Report Summary for Policy Makers. Geneva, Switzerland: IPCC Jochim, Ashley E. and Peter J. May "Beyond Subsystems: Policy Regimes and Governance." Policy Studies Journal 38 (2): Krause, R. M An assessment of the greenhouse gas reducing activities being implemented in US cities. Local Environment 16 (2): Krause, R. M An assessment of the impact that participation in local climate networks has on cities implementation of climate, energy, and transportation policies. Review of Policy Research 29 (5):

34 Laukkonen, Julia, Paola Kim Blanco, Jennifer Lenhart, Marco Keiner, Branko Cavric, and Cecilia Kinuthia- Njenga "Combining Climate Change Adaptation and Mitigation Measures at the Local Level." Habitat International 33 (3): Lorenzoni, Irene and Nick F. Pidgeon "Public Views on Climate Change: European and USA Perspectives." Climatic Change 77 (1-2): Lutsey, Nicholas and Daniel Sperling "America's Bottom- Up Climate Change Mitigation Policy." Energy Policy 36 (2): doi: /j.enpol Millard- Ball, Adam "Do City Climate Plans Reduce Emissions?" Journal of Urban Economics 71 (3): Moser, S. C., and J. A. Ekstrom A framework to diagnose barriers to climate change adaptation. Proceedings of the National Academy of Sciences 107 (51): Naess, Lars Otto, Guri Bang, Siri Eriksen, and Jonas Vevatne "Institutional Adaptation to Climate Change: Flood Responses at the Municipal Level in Norway." Global Environmental Change 15 (2): Romsdahl, R.J., Wood, R. and A. Hultquist. (in- review) Planning for Climate Change Adaptation in Natural Resources Management: Challenges to Policy- making in the US Great Plains. Journal of Environmental Planning & Policy. Roberts, Debra "Thinking Globally, Acting Locally institutionalizing Climate Change at the Local Government Level in Durban, South Africa." Environment and Urbanization 20 (2): Sharp, E. B., D. M. Dale, and M. S. Lynch Understanding local adoption and implementation of climate change policy. Urban Affairs Review 47 (3) Sippel, M. and Jennsen, T What about local climate governance? A review of promis and problems. Social Science Research Network. Tang, Zhenghong, Samuel D. Brody, Ruopu Li, Courtney Quinn, and Nan Zhao "Examining Locally Driven Climate Change Policy Efforts in Three Pacific States." Ocean & Coastal Management 54 (5): Tang, Zhenghong, Samuel D. Brody, Courtney Quinn, Liang Chang, and Ting Wei "Moving from Agenda to Action: Evaluating Local Climate Change Action Plans." Journal of Environmental Planning and Management 53 (1):

35 Tang, Zhenghong, Christopher M. Hussey, and Ting Wei "Assessing Local Land use Planning's Awareness, Analysis, and Actions for Climate Change." International Journal of Climate Change Strategies and Management 1 (4): Tang, Zhenghong, Zijia Wang, and Thomas Koperski "Measuring Local Climate Change Response Capacity and Bridging Gaps between Local Action Plans and Land use Plans." International Journal of Climate Change Strategies and Management 3 (1): Urpelainen, Johannes "Explaining the Schwarzenegger Phenomenon: Local Frontrunners in Climate Policy." Global Environmental Politics 9 (3): Wang, X. H., C. V. Hawkins, N. Lebredo, and E. M. Berman Capacity to sustain sustainability: A study of US cities. Public Administration Review. Warden, T Viral governance and mixed motivations: How and why U.S. cities engaged on the climate change issue, In Cities and climate change: Responding to an urgent agenda., eds. D. Hoornweg, M. Freire, M. J. Lee, P. Bhada- Tata and B. Yuen. Vol , World Bank. Zahran, S., G. Himanshu, S. D. Brody, and A. Vedlitz Risk, stress, and capacity: Explaining metropolitan commitment to climate protection. Urban Affairs Review 43 (4):

36 Table 1: Factor Analysis Public Atmosphere toward Climate Change Rotated Component Matrix Factor 1: Support Factor 2: Skepticism Factor 3: Confusion Public Support for policies to address CC Public demands action on CC Concern about CC Anger about CC Frustration about CC Our city is vulnerable to CC impacts CC is a natural cycle CC is exaggerated by the media CC science is uncertain The feeling that CC is not relevant Confusion about CC Nobody talks about it (not aware of CC) Notes: Principal Components extraction with Varimax Rotation and Kaiser Normalization. Rotation converged in 5 iterations. Factor 4: Apathy 36

37 Table 2: Frequency Distribution, Number of Climate Change Mitigation Activities Engaged in by Local Government No. of Mitigation Activities Frequency Percent Cumulative Percent n=211 Mean = 3.88 s.d. = 2.85 Table 3: Frequency Distribution, Number of Climate Change Adaptation Activities Engaged in by Local Government No. of Adaptation Activities Frequency Percent Cumulative Percent n=211 Mean = 6.60 s.d. =

38 Mitigation Activity Table 4: Local Government Implementation and Framing of Selected Climate Change Mitigation Activities No. of governments implementing Pct. Of governments implementing No. Implementing and framing as climate change policy Pct. of those Implementing Framing as climate change policy Community- wide hike and bike trails in place Efficient lighting installed in city streetlights Tree ordinance adopted specifying planting/removal requirements for developers City provides information to residents on energy efficiency Residential yard waste is composted Policy for city equipment and appliances, purchase only EnergyStar labeled City provides residents or developers incentives for energy efficiency building/improvements City has regulations requiring private/commercial buildings to meet efficiency standards Vehicle fleet being made green (i.e converted to hybrids, high efficiency, alternative fuels) Planning and zoning decisions explicitly consider effect on sprawl or greenhouse gas emissions (GHG) Inventory conducted on local GHG emissions City offers incentives to its employees to use methods other than single occupancy vehicles to commute to work GHG reduction plan developed and formally adopted by city Climate protection activities have line in municipal budget n=

39 Adaptation Activity Table 5: Local Government Implementation and Framing of Selected Climate Change Adaptation Activities No. of governments implementing Pct. Of governments implementing No. Implementing and framing as climate change policy Pct. of those Implementing Framing as climate change policy Warning System(s) (e.g. storm alerts, fire risk) Flood risk maps Flood management plans Emergency evacuation plans Educational materials/information to public (e.g. tree planting, composting, energy saving tips, etc.) Stormwater pollution prevention plan Drought- dependent water use restrictions Mosquito/ pest control policies Regional cooperation on natural resource management (e.g. river, lake, drought, etc.) Disclosure requirements (e.g. on flooding, erosion risks) Soil erosion management plans Density restrictions in city planning Setbacks along riverbanks Species and/or habitat protection plans (e.g. land trusts) n=

40 Table 6: Influences on Mitigation and Adaptation Policy Adoption (Number of Policies Adopted) Model I: All Climate Policies Model II: Mitigation Policies Model III: Adaptation Policies f Constant The Policy Environment Population (100,000 persons, 2005).617* Per Capita Income ($100,000) a Value of Disaster Assistance ($billion) a,b *.289 Perceived Vulnerability of Community State has a Climate Action Plan c State has Voluntary GHG Reporting System d Attitude of Government Signed Mayor s Compact on CC e **.234 Cities/States should act on CC if feds don t 1.287**.629**.658** Cities/States should wait for feds before acting Cities/States should just adapt to CC impacts Market forces alone will adjust behavior on CC E- 005 Community Atmosphere Percent Democrat Vote: President, *.035*.047* Factor 1: Concern/Support for CC Factor 2: Ideological Skepticism about CC.959* * Factor 3: Confusion about CC.704* * Factor 4: Apathy toward CC **.062 Adjusted R 2 F test *** Notes: *p <.10 ** p <.05 *** p <.01 a : 2011 constant dollars b : total value of county level FEMA disaster declarations over the last 10 years c: states- regions/policy- maps/action- plan (dummy variable) d: states- regions/policy- maps/ghg- reporting (dummy variable) e : (dummy variable) f: implemented or updated in the last 10 years *** *** 40

41 Appendix A: Survey Instrument 41

42 42

43 43