Climate change adaptation plans: Inclusion of health, equity, and green space

ABSTRACT

We examined the extent to which cities’ climate change adaptation plans, in U.S. cities broadly and in shrinking cities, discuss health equity/justice, including injustices related to green spaces. Using content analysis of 88 cities’ climate change adaptation plans, we coded for health, equity/justice, parks/green space, and joint usage of these terms. We made comparisons of keyword usage between shrinking and non-shrinking cities to examine how shrinking cities—with overlapping vulnerabilities and industrial legacies—differ from stronger market cities. Although health (97%) and equity/justice (81%) were common, only half of the cities discussed health and equity/justice concurrently, with overrepresentation from shrinking cities. Parks/green space were discussed alongside these themes in 28% of cities. Health equity emerged more in shrinking cities and recent plans (e.g., since 2018), suggesting recent shifts toward equity. Many cities vaguely described health equity solutions, necessitating clearer solutions for injustices, including parks/green space as climate adaptation and health infrastructure.

KEYWORDS:

• City planning
• climate change
• environmental justice
• social equity

Introduction

Cities are responding to the threat of climate change by creating climate adaptation plans, which are typically nonbinding strategic plan documents designed to guide cities’ efforts to adapt to a changing environment and mitigate human health risks (Cole et al., 2017; Long & Rice, 2019). While the focus of these plans tends to be on mitigating impacts from sea level rise, flooding, and drought, climate change also puts many people at risk of health complications and other physical and mental harm (Patz et al., 2014; Swann et al., 2021). Climate change can affect physical and mental health in direct ways, such as respiratory illnesses, heat-related illnesses, and exposure to environmental toxins (Luber et al., 2014; Myers & Patz, 2009; Patz et al., 2014), as well as indirect ways, such as increased vulnerability to disasters and health problems (Barrett et al., 2014; Shokry et al., 2020). As the world increasingly urbanizes, the overall human health impact of climate change could be significant.

Marginalized populations (e.g., low-income and people of color) are disproportionally experiencing the impacts of climate change (Anguelovski et al., 2016; Gutschow et al., 2021). The people most vulnerable to climate change—low-income, elderly, children, people of color, and those with comorbidities (i.e., co-occurring diseases or chronic conditions)—are also often living the lowest carbon lifestyles (Rice et al., 2020). Similarly, areas with the most vulnerability to environmental burdens are sometimes the least likely to get investment in sustainability infrastructure, which may help buffer against climate impacts (Shokry et al., 2020). Such uneven investment widens gaps between those who most need protection against the health harms of climate change and the geographic areas best suited to address climate change (Friel et al., 2011). Inequality in who is vulnerable and exposed to burdens, and who has the means and resources to prepare for climate change, poses a health risk (Morello-Frosch et al., 2018).

Health is addressed in a variety of ways in climate adaptation plans, such as through expansion of healthcare, improving access to healthy food, and implementing heat mitigation infrastructure. Of particular interest, however, are cities that seek to adapt to climate change and address human health concerns simultaneously by building green infrastructure—including parks, green spaces, and trees (Meerow, 2020). Green infrastructure is positively linked to health in numerous ways, including more physical activity, better cardiovascular health, psychological health, and better cognitive functioning, among other benefits (Larson et al., 2016). Green infrastructure can also help purify air and water, mitigate urban heat island effects, and support access to nutritious foods, benefiting human health (Wakefield et al., 2001; Jesdale et al., 2013; S. Wakefield et al., 2007). There are also mental and social health benefits to green infrastructure, particularly those that also serve as sites for recreation, such as parks and trails (Hunter et al., 2019; Keith et al., 2018; Larson et al., 2016). Because many of the benefits to human health provided by green infrastructure also help address impacts from climate change, many cities see such investments as a “win-win” (Meerow, 2020). Specifically, cities build green infrastructure to replace gray infrastructure (e.g., sewers, culverts, and water treatment facilities), as it can perform many of the same functions while also providing additional benefits. Green infrastructure, like parks, greenways, trees, and rain gardens, can filter stormwater, absorb greenhouse gas emissions, and reduce surface heat (Meerow, 2020). Many cities thus recognize the importance of green infrastructure as a component of climate adaptation plans (Choi et al., 2021).

Green infrastructure thus has many benefits and can address a number of climate impacts, though it is important to acknowledge not all aspects of green infrastructure are positive. Although links between nature and health are strong (Han et al., 2014; Larson et al., 2016; Wilhelm; Stanis et al., 2014), access to nature—including green infrastructure—remains inequitable. In many communities, low-income and minority residents have less access to quality green space (Anguelovski et al., 2018; Cole et al., 2017; Kamel et al., 2014; Schultz et al., 2017) and are more vulnerable to climate change impacts (Meerow et al., 2019). Therefore, increasing equitable access to green space is needed to reverse these disparities. Climate adaptation plans are an opportunity to address inequities and corresponding environmental injustices (Malloy & Ashcraft, 2020; Schrock et al., 2015). However, without careful planning building new green amenities may unintendedly introduce new or worsen existing injustices (Anguelovski et al., 2018).

Indeed, a growing body of research has demonstrated that green infrastructure development projects—such as those in climate adaptation plans—can lead to gentrification and displacement, often termed green gentrification or climate gentrification (Gould & Lewis, 2017). Specifically, green infrastructure can sharply increase rent prices and property taxes, which may displace current residents, who often move to areas of fewer health resources and experience worse health outcomes (Bhavsar et al., 2020; Chu & Cannon, 2021; Gould & Lewis, 2018; Jelks et al., 2021; Shokry et al., 2020; Smith et al., 2020). Furthermore, some research has shown that gentrification is contributing to carbon emissions, even in cities with a climate-friendly focus, as gentrifiers bring high consumption lifestyles to previously low-carbon areas (Rice et al., 2020). As such, benefits of green infrastructure are not realized by communities they were intended to benefit, resulting in environmental injustices (Anguelovski et al., 2018). Parks and green space in particular are a critical component of green infrastructure in climate adaptation plans given the wide range of health and environmental benefits they offer communities (Larson et al., 2016), as well as inequities in access and their role in gentrification (Mullenbach & Baker, 2020; Vaughan et al., 2013). The size and impact of parks (positive and negative) illustrate their potential to either provide multiple benefits related to climate adaptation, health, and environmental justice (Brown et al., 2015; Sister et al., 2010), or displace vulnerable residents and exacerbate inequities (Mullenbach & Baker, 2020). As more cities incorporate parks and green space into their climate adaptation plans, the potential to improve human health is high (Larson et al., 2016; Swann et al., 2021), but also the risk of potential injustices rises (Gould & Lewis, 2018; Meerow, 2020). In addition to the social unintended consequences of green infrastructure, there are also ecological unintended consequences that can arise from green infrastructure improvement—particularly when such investments are poorly maintained or include invasive species (Taguchi et al., 2020). It is important to note that although any climate adaptation approach can be implemented poorly, green infrastructure represents an interesting case, as cities frequently tout green infrastructure as a “win-win,” with only positive aspects emphasized, despite the potential for negative implications.

On the other hand, with careful planning, green infrastructure can serve as part of a broader health equity strategy for climate adaptation, especially in cities in need of new green infrastructure, like shrinking cities.

Shrinking cities

Health and climate inequities can be particularly apparent in shrinking cities, which are post-industrial cities that have lost more than half of their population since the decline of economic activity or structural change (Ortiz-Moya, 2020). Shrinking cities are home to disproportionately more low-income and racial/ethnic minority residents, as wealthier residents moved away during periods of decline, making them especially vulnerable to inequities associated with new economic growth (Ehrenfeucht & Nelson, 2020; Silverman, 2020). Concurrently, shrinking cities pose additional health risks, due to high rates of vacant land (i.e., unoccupied with no current structures), many of which contain environmental contaminants (Gulachenski et al., 2016). Given that vacant land is often concentrated in poorer neighborhoods and neighborhoods with high concentrations of racial/ethnic minorities, shrinking cities also experience health disparities (Ehrenfeucht & Nelson, 2020). As such, addressing climate change presents an opportunity for shrinking cities to grow in a sustainable manner, as well as to either fix health disparities or maintain or worsen them (Ortiz-Moya, 2020). These cities face additional burdens that larger, growing cities do not, including scarce government resources from a declining tax base and little support from state governments (Hughes, 2020; Sampson et al., 2014). As such, legacies of their industrial past continue to cause health burdens and stifle social and economic development—such as dilapidated housing, landscape scars, and concentrated poverty (Sampson et al., 2014). To combat these multiple obstacles, shrinking cities pursue creative solutions to their problems, especially those that allow for multiple objectives to be achieved at once, making them an important subject of study in the climate adaptation space (Hughes, 2020). Such cities have similar concerns to non-shrinking cities related to gentrification and climate adaptation. Although the risk of gentrification in shrinking cities is more nuanced, the threat is still present, as new investments are being made, drawing in an influx of higher income, highly educated residents, changing the nature of low-income areas (Swanstrom & Plöger, 2020).

Study need and purpose

Despite the impact climate change has had, and will continue to have, on human health, investigations of climate change adaptation and health equity concurrently remains understudied, and the amount that cities are considering health equity remains unknown (Byskov et al., 2021). Furthermore, prior studies that have analyzed equity and environmental justice within cities’ climate adaptation plans have found that some cities are actively working toward equity and justice (Fiack et al., 2021), though most evidence shows that cities are not doing enough to ensure climate adaptation efforts are equitable and just (Anguelovski et al., 2016; Chu & Cannon, 2021; Hess & McKane, 2021; Meerow et al., 2019).

Researchers have called for more studies assessing the likelihood of achieving health equity from climate adaptation plans (Swann et al., 2021; Venkataramanan et al., 2019). A better understanding of the potential or real impacts of climate adaptation plans on health equity, and how decisions are being made about climate adaptation, can help ensure that health equity is a pillar of city climate change adaptation. This paper contributes to this growing line of work by investigating how human health equity is being considered in climate adaptation plans—in shrinking and non-shrinking cities alike (Hughes, 2020). Thus, the purpose of this study is to explore, document, and understand the extent to which climate change adaptation plans, in U.S. cities broadly and in shrinking cities, are discussing and addressing health equity/justice, including injustices related to green spaces. We pursue this purpose through three research questions:

1. To what extent and how are health equity and justice addressed in cities’ climate change adaptation plans?

2. To what extent are parks and green space discussed in the climate adaptation plans in conjunction with health equity and justice?

3. Are these patterns similar when looking specifically at shrinking cities?

Materials and methods

We conducted content analysis on climate change adaptation plans from cities across the U.S. to understand how cities were approaching human health, specifically the extent to which their approaches address and seek to advance equity and justice.

Data

The dataset comprised publicly available documents of U.S. cities’ climate change adaptation or sustainability plans. A total of 88 cities’ plans were identified through the Georgetown University Climate Center’s State and Local Adaptation Plan clearinghouse¹ which provided scope and boundaries around our analysis. We ensured that plans were up-to-date by checking that each plan was the most recent one for each city, and if it was not we obtained the most recent plan as of the download date (February 2021). To ensure that every state plus DC was represented, we obtained the most recent plan for the largest city in the state if a state did not have a plan in the clearinghouse. There were six exceptions: Alabama, Idaho, Kansas, North Dakota, South Dakota, and Wyoming do not have any cities with climate change adaptation plans or sustainability plans at the time of this analysis. Plan documents were either downloaded from the clearinghouse or from the cities’ government websites. County-level, state-level, and town plans were excluded, to keep the city as the unit of analysis.

Content analysis

We used summative content analysis, based on guidelines described by Hsieh and Shannon (2005). Content analysis is “a systematic, replicable technique for compressing many words of text into fewer content categories based on explicit rules of coding” and is a popular method for summarizing information from large amounts of qualitative data in quantitative terms (Stemler, 2001). We chose summative content analysis, which is a type of content analysis that uses keyword searches of text to seek an understanding of the frequency of those keywords, the context words were used in, and in what way (Hsieh & Shannon, 2005).

We used NVivo version 12 to manage our analysis. First, text searches were conducted for keywords related to health (e.g., asthma, cancer, physical activity), equity and justice (e.g., environmental justice, climate justice, social equity), and parks/green space (e.g., parks, recreation, green space; complete list of words is available in Table 2). All search results were screened for relevance. Text searches were then conducted on these search results such that health-related results were searched for equity/justice-related content, and equity/justice-related results were searched for health-related content. Statements that appeared in both of these two searches were only coded once. A master health/justice/equity code was created, with results from each of these searches stored within it. Statements were considered to have a “co-occurrence” of both health and equity/justice if the health topic and the equity/justice topic occurred in the same sentence, using a feature within NVivo. We flagged content that specifically related to provision of green spaces, parks, and recreational facilities/resources as climate change adaptation strategies intended to provide co-benefits of environmental and human health (see Step 5 in Figure 1). Although other outputs from programs or policies can provide co-benefits—such as greenhouse gas emission targets—these types of outputs were beyond the scope of our study. Text fragments within the master code were coded in two waves: once to identify the types of statements (i.e., framing) being made in the plan documents, and once to identify specific content and topics areas. Subsequent codes were created as analysis proceeded to represent the types of statements and types of content/topics discovered within the text. This process is shown in Figure 1. We reviewed and discussed these thematic findings together, created and clarified definitions, and combined categories as necessary to come to consensus on the types of statements and content/topic.

Figure 1. Search, coding, and analysis process for climate adaptation plans and health equity.

Step 1: Create keywords from the literature related to justice/equity, health, and parks/green space. Step 2: Search data corpus using keywords. Step 3: Perform text searches on the health keyword results for justice/equity, and vice versa. Step 4: Combine results into master code related to health equity/justice. Step 5: Code results from Step 3 to identify types of statements, content and topic areas, & co-occurrence with parks/green space. Step 6: Analyze coded data from Step 5, with separate analysis for shrinking cities.

We established word counts for keywords to ascertain the extent to which the keywords were mentioned across the plans (spread) and within the plans (density). We also collected meta-data on average year of the plans, size of the cities, and climatic region of the country. Next, we conducted a sub-analysis, which looked descriptively at how shrinking cities address health equity/justice in their plans in comparison to strong-market cities, given their unique opportunity to either “re-grow” in a more equitable manner or continue or worsen environmental injustices (e.g., gentrification) affecting vulnerable populations (Ehrenfeucht & Nelson, 2020; Hollander & Németh, 2011). We used the list of shrinking cities from Ganning and Tighe (2021) to determine which of the cities in our dataset met criteria for “shrinking city.” A chi-square test was used to examine differences in the distribution of word counts across shrinking and non-shrinking cities.

Results

Our data included 88 climate change adaptation plans from 88 cities, representing 44 states plus DC Data on the cities and plans are displayed in Table 1. The plans range in age from 14 years old (2007; Homer, Alaska) to less than a year old (2021; Lincoln, Nebraska; Philadelphia, Pennsylvania; Portland, Maine), and the cities range in population size from 3,322 (Lewes, Delaware) to 8,336,817 (New York City). Of these 88 cities, 15 (17%) are classified as shrinking (Tighe & Ganning, 2015). The cities represent all climatic regions in the U.S.: the Northeast (21 cities), Northern Rockies (3 cities), Northwest (3 cities), Ohio Valley (11 cities), South (9 cities), Southeast (10 cities), Southwest (9 cities), Upper Midwest (8 cities) and West (12 cities).² More details on individual cities are available in Table A1 in the Appendix.

Table 1. Summary information from 88 cities in analysis, including median age of climate adaptation plans, population size, city-wide median income, and racial/ethnic makeup.

Summary data	Median	Range
Age of climate adaptation plans	4 years (2017)	2007–2021
City population size	221,877	3,322–8,336,817
City median income	$60,208	$28,834-$147,620
% white	67.5%	14.7%-97.4%
% Black or African American	8.3%	0%-78.3%
% Asian	4.3%	.3%-34.4%
% Hispanic/Latino of any race	10.5%	1.2%-72.7%

Table 2. Keyword counts and spread across cities’ climate change adaptation plans for keywords related to equity/justice, health, and green space (total N = 88, shrinking cities n = 15 [17%]).

Keyword	Total count	Total no. of cities	Count in shrinking cities (% of total count)	No. of shrinking cities (% of total cities)
Equity/Justice*	1,132	71	596 (25%)	13 (18%)
Disproportionate	230	54	38 (17%)	10 (19%)
Diversity, equity, and inclusion (DEI)	58	15	18 (31%)	2 (13%)
Inequity	371	37	69 (19%)	9 (24%)
Social equity	173	36	66 (38%)	8 (22%)
Climate justice	86	9	61 (71%)	3 (33%)
Environmental justice	149	31	50 (34%)	8 (26%)
Racial justice	2	2	1 (50%)	1 (50%)
Social justice	35	20	2 (6%)	1 (5%)
Gentrification	28	11	5 (18%)	2 (18%)
Health*	4,173	85	830 (23%)	13 (15%)
Active transportation	1,173	75	261 (22%)	11 (15%)
Asthma	175	44	65 (37%)	10 (23%)
Cancer/carcinogen	32	19	7 (22%)	3 (16%)
Cardiovascular	52	24	7 (13%)	5 (21%)
Cognitive health/ADHD	9	8	3 (33%)	3 (38%)
Diabetes	33	16	11 (33%)	2 (13%)
Health outcomes	109	24	15 (14%)	5 (21%)
Heart disease	32	17	6 (19%)	3 (18%)
Human health	141	46	33 (23%)	7 (15%)
Mental health	200	33	12 (6%)	4 (12%)
Obesity	60	17	14 (23%)	4 (24%)
Physical activity	66	20	19 (29%)	4 (20%)
Pollution/pollute	1,105	79	266 (24%)	14 (18%)
Public health	895	77	171 (19%)	12 (16%)
Wellbeing	91	27	36 (40%)	5 (19%)
Parks/Green Space*	2,415	83	790 (33%)	15 (17%)
Green space	182	42	65 (36%)	10 (24%)
Park/parks	1,457	79	503 (35%)	15 (17%)
Recreation facilities/resources	776	73	222 (29%)	14 (19%)

*Sum of counts in keywords.

Word counts for the first sets of keywords (health-related, equity/justice-related, and green space-related) are displayed in Table 2. Codes from analysis Step 5 (i.e., types of statements, content/topic areas, and co-occurrence of green space with health equity/justice) are displayed in Table 3.

Table 3. Topics related to health equity/justice—counts and spread across cities’ climate change adaptation plans (total N = 88, shrinking cities n = 15 [17%]).

Topics	Total count	Total no. of cities	Count in shrinking cities (% of total count)	No. of shrinking cities (% of total cities)
Health Equity/Justice	268	44	73 (27%)	10 (23%)
Types of Statements
Co-benefits	24	14	4 (17%)	4 (29%)
Goals	95	32	29 (31%)	8 (25%)
Past successes	19	13	7 (37%)	3 (23%)
Problem-framing	99	37	26 (26%)	10 (27%)
Solutions	65	21	18 (28%)	6 (29%)
Planning process	5	4	1 (20%)	1 (25%)
Content/Topic
Absence of amenity/necessity	47	21	19 (40%)	6 (29%)
General health disparities	64	25	19 (30%)	7 (28%)
General environmental/health solutions	59	26	19 (32%)	8 (31%)
General health consequences	38	23	7 (18%)	5 (22%)
Populations affected	68	31	19 (28%)	8 (26%)
Presence of harm/burden/hazard	62	28	17 (27%)	7 (25%)
Specific environmental/health solutions	30	12	10 (33%)	5 (42%)
Specific health consequences	42	21	17 (40%)	6 (29%)
Co-Occurrence with Parks/Green Space	88	25	31 (35%)	7 (28%)

To what extent and how are health equity and justice addressed in cities’ climate change adaptation plans?

The majority of plans mentioned either health (n = 85, 97%) or equity/justice (n = 71 cities, 81% of total cities) keywords in their plans (Table 2). Half of the city plans (n = 44, 50%) mentioned health and equity/justice concurrently (Table 3). This followed a temporal trend, in that cities that mentioned health and equity concurrently had, on average, more recent plans (mean year = 2017) than cities that did not (mean year = 2014).

When examining the types of concurrent health equity/justice statements, six categories emerged: problem-framing (n = 37 cities, 42% of total cities), goals (n = 32, 36%), solutions (n = 21, 24%), co-benefits (n = 14, 16%), past successes (n = 13, 15%), and planning process (n = 4, 5%). Eight cities included five of these six in their climate plans, and an additional six cities included four. Problem-framing statements were those that described the health and equity problems facing cities currently, in the future, or that will be exacerbated by climate change. These problem-framing statements were the most common type of statement for health equity to be discussed. For instance, the Flint sustainability plan notes the following: “Environmental issues such as pollution, crime, property abandonment, lack of areas to exercise outdoors, and poor access to healthy foods disproportionately impact residents who are low income, minority, or uninsured.” Goal statements expressed the goals or objectives that the plan worked toward, such as reductions in air pollution in high-minority neighborhoods, expansion of bus routes to low-income neighborhoods, or tree canopy cover goals in historically polluted neighborhoods, among others. An example statement from the Cincinnati Green Plan says, “The City of Cincinnati strives to provide equal opportunity and protection for all of its residents. Therefore, there is a need for an environmental justice program in the City.” Solutions statements described solutions to health inequities as they will be addressed through implementation of the plan, such as in the Portland, Oregon, Climate Action Plan, which states “Invest in neighborhood accessibility by bringing services to underserved neighborhoods and supporting equitable expansions of public transit and active transportation infrastructure.” Co-benefits statements mentioned how climate adaptation strategies would perform the twin duties of alleviating health burdens and moving cities further toward equity and justice. These statements did not necessarily discuss health disparities or achieving health equity, but rather that the two outcomes could both be addressed through actions toward climate change adaptation, such as in the following statement from the Minneapolis Climate Action Plan, “Many of the strategies in this plan will reduce greenhouse gas emissions while also reducing these existing disparities and creating other co-benefits, such as improved public health.” Past successes were statements describing existing programs, policies, or initiatives that would remain or expand in the plan that have already seen success, such as New York City’s acceptance of EBT at all farmer’s markets. Finally, statements about the planning process described ways the cities addressed health and equity/justice concerns through the creation of the plan itself, as seen in the following statement from the Somerville, Massachusetts, plan, “All of the actions in this plan were designed with equity in mind.”

For the content of the concurrent health equity/justice statements, eight categories emerged: absence of amenities/necessities (n = 21 cities, 24% of total cities), presence of a harm/burden/hazard (n = 28, 32%), general health disparities (n = 25, 28%), populations affected (n = 31, 35%), general health consequences (n = 23, 28%), specific health consequences (n = 21, 24%), general environmental/health solutions (n = 26, 30%), and specific environmental/health solutions (n = 12, 14%). Absence of amenities/necessities statements described health equity issues associated with resident populations and/or geographic areas with a disproportionate lack of access to amenities or necessities, such as green space or fresh food. For instance, the Dallas Climate Action Plan states the following: “Lower income populations and communities of color often have less access to adequate and energy efficient housing, transit, or safe bicycling and walking routes.” Presence of a harm/burden/hazard statements described health equity issues associated with resident groups living with disproportionate exposure to such burdens as air pollution, water pollution, and toxic waste, as in the following statement from Louisville, Kentucky: “Neighborhoods with factories and chemical plants, such as Rubbertown, are often populated with lower-income residents and people of color, creating inequities around race and income. Pollutants released into the air, onto the land, and into the Ohio River create significant health and safety impacts.” General health disparities statements described existing disparities in the health of the population but did not detail which health conditions are experienced disparately across subpopulations, nor were they attributed to climate change, as in this statement from the Flint Sustainability Plan: “Children and young adults are disproportionately affected by unsafe and unhealthy environments.” Rather, such statements mentioned that health disparities that already exist must be addressed through the climate change adaptation plan.

Populations affected statements described who will feel the effects of climate change. Populations mentioned included Black residents, children, communities of color, the elderly, Hispanic/Latino residents, immigrant groups, Indigenous residents, low-income residents, outdoor workers, people with chronic or preexisting illnesses, people with disabilities, and pregnant women. General health consequences statements mentioned that climate change will impact health, but without providing detail, such as mentioning that hotter temperatures will disproportionately impact vulnerable populations, or the following statement from Madison, Wisconsin’s plan: “people of color, non-English speakers, indigenous groups and those facing discrimination due to gender or religion … are at increased health risk, in part, because they have fewer resources to adapt to climate change impacts.” Specific health consequences statements included ways that climate change can worsen an existing disparity for certain conditions among certain populations, or ways that climate change can cause health disparities/inequities. For instance, Columbia, Missouri, listed the specific health impacts they refer to when discussing implications of climate change: “Health, safety and well-being includes addressing impacts of climate change, such as heat stress, air quality, allergens, food security, vector-borne disease and mental health.” General environmental/health solutions statements contained references to solutions to health inequities but did not provide details, such as: “the City will work with partners to develop equitable planning and land-use policies around clean air, clean drinking water, and pollution free waterways” (Houston, Texas). Finally, specific environmental/health solutions statements described ways that cities plan to address health and environmental issues using specific strategies, such as plans to expand parks and recreation resources in concert with residents across the city.

To what extent are parks and green space discussed in the climate adaptation plans in conjunction with health equity and justice?

Approximately a quarter of cities discussed parks/green space in a health equity/justice context (n = 25, 28%; Table 3), and parks/green space was frequently discussed in the climate plans in a general sense (n = 83, 94%; Table 2). Similar to the overall health and equity/justice trend, cities where health equity/justice was mentioned concurrently with parks/green space were more recent (mean year = 2018) than those that did not (mean year = 2015; see Table 4). Although an encouraging finding, the number of instances of parks/green space being discussed concurrently with health equity/justice precluded us from examining this topic further in the manner of research question 1 (i.e., looking into types of statements and content areas).

Table 4. Average age of climate adaptation plans by concurrent discussion of health/justice and health/equity (n = 88).

	Justice/Health Intersection	Equity/Health Intersection
Does mention concurrently	Mean year = 2018 (n = 23)	Mean year = 2018 (n = 44)
Does not mention concurrently	Mean year = 2015 (n = 64)	Mean year = 2014 (n = 44)

Are these patterns similar when looking specifically at shrinking cities?

The proportion of shrinking cities discussing equity/justice broadly (χ² = 2.01; p= .156), or health/equity/justice in combination (χ² = 2.96; p= .085) were not statistically different than cities not designated as shrinking. However, descriptively, shrinking cities comprised a larger share of the discussion of both, when examining the counts (frequency) of the statements. Shrinking cities only made up 17% of the sample but comprised 27% of the counts discussing health equity/justice, and 35% of the counts examining the intersection of health equity/justice with parks/green space (Table 3)—which is disproportionate, though not significantly.

Discussion and conclusions

Our findings demonstrate that cities are discussing health and equity/justice topics in climate adaptation plans. Indeed, it is promising to see how many cities are discussing justice and equity given that the consequences of climate change on the health of vulnerable populations could be vast (Myers & Patz, 2009; Swann et al., 2021). However, the number of cities making efforts toward equity and justice in health effects of climate change was smaller, highlighting a need for consideration in this area (Swann et al., 2021). The finding that newer plans were more attentive to these issues signals the trend may grow.

When examining when this intersection occurred, we found that cities most often were focused on laying out the problems their cities will or are facing, and their goals for adapting to those problems. Substantially less attention was directed toward discussing solutions, and when solutions were discussed, they focused on more general than specific solutions. While this may give flexibility for cities to identify the best solutions during the implementation of the plans, and leaves room to include citizens in that decision making process (Anguelovski et al., 2016), it may also result in vague or ineffective solutions (Fiack et al., 2021). Similarly, fewer cities discussed their planning process, preventing analysis of the equity of those processes and any improvements that could be made to environmental justice. These findings are noteworthy because they point out that even with increased discussion of health equity/justice, cities may need to spend more time detailing specific solutions to these complex health equity/justice consequences from climate change or risk seeing the problems come to light in the face of overly general action plans.

Our findings align with Meerow and colleagues (Meerow et al., 2019), who found that attention to equity varied widely across the cities in their study. We also found variability in attention paid to equity/justice, with shrinking cities discussing justice disproportionately. Shrinking cities also focused on green space, parks, and recreation as climate solutions disproportionately more than their share of cities would suggest. Green space is often included in environmental and economic revitalization initiatives, particularly in shrinking cities (Ortiz-Moya, 2020). Many plans mentioned parks, green space, and recreation as an element of climate adaptation, but few made the connection to health equity/justice issues, despite the potential (Maibach et al., 2009; Swann et al., 2021; Venkataramanan et al., 2019). Given the amount of co-benefits that cities identified in their climate change plans, more cities should recognize the many co-benefits that green spaces, parks, and recreational amenities provide for both climate adaptation and health equity (Shokry et al., 2020).

This study’s investigation of green infrastructure focused on parks and green spaces, which are part of green infrastructure broadly, to understand how these sites of multiple co-benefits (e.g., physical activity, social interaction, and mental health) and inequity risk (e.g., gentrification, inequitable access) are used and conceived of in climate change adaptation planning. However, to further benefit public health, future research could expand to look at green infrastructure more broadly, as it relates to health equity in climate adaptation planning. Additionally, research should also expand outside the U.S., and especially to the Global South, where issues such as land grabbing in the name of sustainability is displacing populations already vulnerable to climate change effects (Anguelovski et al., 2019).

Although this study cannot speak for all shrinking cities, shrinking cities in this study approached climate adaptation equitably at a higher rate than non-shrinking cities. Given that shrinking cities have high concentrations of vulnerable populations, this emphasis on equity can make a large difference in environmental justice (Ehrenfeucht & Nelson, 2020; Silverman, 2020). Furthermore, given that many shrinking cities use multi-benefit strategies, such as green infrastructure, to adapt to climate change (in which green infrastructure is used to accomplish more than one objective), an equity approach can lead to the many health benefits for vulnerable and marginalized residents that green spaces provide (Hughes, 2020; Sampson et al., 2014; Schilling & Logan, 2008). Shrinking cities are not unique in their use of multi-benefit strategies, but may differ from non-shrinking cities in their necessity to stretch public dollars further (Hughes, 2020).

Limitations and future research

We made the choice to use the city climate adaptation plans that were available in the Georgetown Climate Center clearinghouse, using one plan per city, representing a snapshot in time. This limits our ability to track cities’ modifications over time but keeps the type of plan consistent across all cities, and enables our research to represent current discourse. An additional limitation of using the clearinghouse is that we could not guarantee a representative subsample of shrinking cities; however in future studies, moving beyond what is listed in this resources could allow for better representation. Related to this is the notion of representing regional variability in city sizes and climate impacts. Our study focused on obtaining representation from as many states as possible, though future research could investigate regional distinctions. Methodologically, we made decisions about our keywords based on our objectives and the literature; however we did not implement strategies to ensure we did not miss important information that could have arisen from choosing additional keywords (e.g., equal and unequal, instead of merely equity and inequity). Scholars continuing this work could consider adding more keywords or performing checks on the text. Since not every city has multiple plans, we restricted the sample to one plan per city. In a future study, we could assess the cities that have had multiple iterations to examine how cities modify their approach over time, including a greater emphasis on equity/justice concerns over time. Similarly, in future research, we can investigate how these climate adaptation plans—sometimes viewed as strategic plans, sometimes as policy prescriptions, sometimes as mere discursive nods to campaign promises—end in policy outcomes. Climate adaptation plans, while important indicators of what cities prioritize, are not necessarily binding commitments, and we should continue monitoring effects as these plans are implemented.

Although the scope of the present paper was limited to descriptive results on health equity in existing climate adaptation plans, it is important to point out the drivers of the inequalities present in the plans. In many U.S. cities, causes of existing health and environmental inequities stem from social structures steeped in racism and classism (Anguelovski et al., 2016; Gutschow et al., 2021; Hughes, 2020). For instance, especially in post-industrial cities, the push for economic growth has left behind vulnerable residents, which has lasting effects on contemporary climate adaptation plans (Sampson et al., 2014). Future research in this area of health equity in climate adaptation can identify solutions to injustice not only in policy prescriptions from climate adaptation plans, but also in alleviating poverty and institutional racism. We are encouraged by the solutions that we did observe in the sample’s climate adaptation plans—the health, social, and economic efforts meant to close environmental injustice, like prioritizing health-promoting infrastructure in marginalized communities—but long-term solutions to health inequities and climate injustice are still nascent in U.S. cities’ climate adaptation plans. Future research should employ a critical lens to the approach of U.S. cities’ climate adaptation to further interrogate the racist and classist structures creating environmental injustice (Anguelovski et al., 2016; Friel et al., 2011). In particular, future research can dive deeper into what leads shrinking cities to be at the forefront of equitable climate adaptation. Lastly, future research should also dive deeper into gentrification—given that 11 of 88 cities mentioned gentrification, even if briefly—and the intersection between gentrification and health equity leaves more to explore.

Cities’ climate adaptation plans represent an opportunity to advance health equity and achieve climate justice. However, without careful attention, present health disparities may only be exacerbated rather than disrupting the causes of those health disparities (Anguelovski et al., 2018). The present study highlights the gap between the number of cities engaging in equitable climate adaptation and the number that are not, as well as future gaps between a plan’s promises for health equity and implementation. Further, this study sheds light on how cities in the U.S.—both non-shrinking and shrinking—conceptualize and plan for health equity in climate adaptation, though we acknowledge more research on the distinction between differently sized cities would further clarify how cities are approaching this issue. Solutions such as investing first in the most health-burdened communities and those with histories of environmental injustice may help reduce health inequities. In shrinking cities—many of which grapple with excessive heat—health equity solutions could involve reducing impacts from heat waves, such as transforming vacant lots into parks, and improving shade (i.e., trees) and cooling resources in low-income and high-minority areas (Jang & Kim, 2021). Beyond the physical solutions mentioned, public health implications include consequences of the politics of urban climate planning. Given the potential role of local politics in facilitating or hamstringing climate adaptation measures (Quastel et al., 2012), health equity/justice may suffer if not championed by city officials (Anguelovski et al., 2016; Fiack et al., 2021).

Acknowledgments

We wish to acknowledge the efforts of Noah Christensen, student at the University of Missouri, for his assistance in compiling the climate plans for this paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Additional information

Notes on contributors

Lauren E. Mullenbach

Lauren E. Mullenbach is an Assistant Professor in the Department of Geography and Environmental Sustainability at the University of Oklahoma. She focuses on urban environmental justice, including issues related to climate justice and adaptation, green infrastructure development, and human health and wellbeing. Her work has also been published in Cities, Landscape and Urban Planning, and Conservation Letters.

Sonja A. Wilhelm Stanis

Sonja A. Wilhelm Stanis is a Professor and Associate Director of the School of Natural Resources at the University of Missouri. Her research is in the human dimensions of natural resource management with an emphasis in the social psychological as well as environmental factors that influence aspects of outdoor recreation. Specifically, her work examines the role of parks and public lands in promoting physical activity and public health, benefits of and constraints to outdoor recreation, and issues in outdoor recreation relating to diversity and youth. Her work has also been published in American Journal of Preventive Medicine, Environmental Management, Environment and Behavior, and Health & Place.

Notes

1. http://www.georgetownclimate.org/adaptation/index.html.

2. Climate regions obtained here: https://www.ncdc.noaa.gov/monitoring-references/maps/us-climate-regions.php.

Appendix

Table A1. Cities included in analysis, their population, year of plan, and climate region.

City	State	Population	Year of plan	Climate region
Albany*	NY	96,460	2014	NE
Albuquerque	NM	560,513	2009	SW
Alexandria	VA	159,428	2012	SE
Annapolis	MD	39,223	2010	NE
Aspen	CO	7,401	2017	SW
Atlanta	GA	506,811	2017	SE
Austin	TX	978,908	2015	S
Baltimore*	MD	593,490	2013	NE
Berkeley	CA	121,363	2016	W
Boston	MA	692,600	2016	NE
Boulder	CO	105,673	2017	SW
Burlington	VT	42,819	2014	NE
Charleston	SC	137,566	2010	SE
Chester*	PA	34,000	2015	NE
Chicago*	IL	2,693,976	2015	OV
Chula Vista	CA	274,492	2011	W
Cincinnati*	OH	303,940	2018	OV
Cleveland*	OH	381,009	2013	OV
Columbia	MO	123,195	2019	OV
Columbus	OH	898,553	2018	OV
Dallas	TX	1,343,573	2020	S
Del Mar	CA	4,340	2016	W
Denver	CO	727,211	2018	SW
Detroit*	MI	670,031	2019	UM
Eugene	OR	172,622	2019	NW
Evanston	IL	73,473	2018	OV
Fayetteville	AR	87,590	2018	S
Flagstaff	AZ	75,038	2018	SW
Flint*	MI	95,538	2013	UM
Fort Collins	CO	170,243	2019	SW
Grand Rapids	MI	201,013	2013	UM
Guilford	CT	22,133	2013	NE
Hampton	NH	15,495	2020	NE
Hoboken	NJ	52,677	2013	NE
Homer	AK	5,922	2007	N/A
Houston	TX	2,320,268	2020	S
Indianapolis	IN	876,384	2019	OV
Iowa City	IA	75,130	2018	UM
Keene	NH	22,786	2007	NE
Lewes	DE	3,322	2011	NE
Lincoln	NE	289,102	2021	NR
Little Rock	AR	197,312	2019	S
Los Angeles	CA	3,979,576	2019	W
Louisville	KY	262,764	2020	OV
Madison	WI	259,680	2020	UM
Memphis	TN	651,073	2020	OV
Miami	FL	467,963	2019	SE
Milwaukee*	WI	590,157	2020	UM
Minneapolis	MN	429,606	2013	UM
Missoula	MT	75,516	2020	NR
Morgantown	WV	30,549	2018	OV
New Orleans*	LA	390,144	2017	S
New York	NY	8,336,817	2019	NE
Norfolk*	VA	242,742	2016	SE
North Kingstown	RI	26,323	2015	NE
Oahu	HI	974,563	2019	N/A
Oklahoma City	OK	655,057	2020	S
Philadelphia*	PA	1,584,064	2021	NE
Phoenix	AZ	1,680,992	2020	SW
Pittsburgh*	PA	300,286	2017	NE
Portland	ME	66,215	2021	NE
Portland	OR	654,741	2015	NW
Portsmouth	NH	21,927	2013	NE
Providence*	RI	179,883	2019	NE
Punta Gorda	FL	20,369	2019	SE
Raleigh	NC	474,069	2012	SE
Reno	NV	255,601	2019	W
Richmond	CA	110,567	2016	W
Rochester	NH	31,526	2013	NE
Sacramento	CA	513,624	2015	W
Salem	MA	43,226	2014	NE
Salt Lake City	UT	200,567	2020	SW
San Antonio	TX	1,547,253	2019	S
San Diego	CA	1,423,851	2016	W
San Francisco	CA	881,549	2016	W
San Rafael	CA	58,440	2019	W
Santa Barbara	CA	91,364	2020	W
Santa Cruz	CA	64,608	2017	W
Seattle	WA	753,675	2018	NW
Somerville	MA	81,360	2018	NE
St. Louis*	MO	300,576	2017	OV
St. Paul	MN	308,096	2019	UM
Tucson	AZ	548,073	2011	SW
Tybee Island	GA	27,669	2016	SE
Virginia Beach	VA	449,974	2020	SE
Washington	DC	705,749	2016	SE**
Waveland	MS	6,302	2013	S
Whitefish	MT	8,295	2018	NR

*Denotes shrinking city. **DC was considered part of Virginia for purposes of climate zone classification. Note: NE = Northeast, NR = Northern Rockies, NW = Northwest, OV = Ohio Valley, S = South, SE = Southeast, SW = Southwest, UM = Upper Midwest, W = West.