Exploring the coherence of urban heat adaptation plans

Introduction: Adaptation to heat is urgent given that the duration, frequency, and intensity of heat waves are increasing rapidly. However, there is a knowledge gap regarding the actions undertaken by cities in terms of heat adaptation and how coherent adaptation is across the stages of the policy cycle.

Methods: By conducting a policy document analysis we analyze how urban heat responses are linked to adaptation scope and beneficiaries and examine how different response types are monitored through indicators by exploring the adaptation policy cycle in four nodes: (i) scoping, (ii) defining measures, (iii) implementation, and (iv) monitoring and evaluation in 10 advanced cities located in heat-prone areas.

Results: Our analysis shows that most of our case cities plan adaptation to increase the population’s adaptive capacity, while the economic sector is prioritized less in adaptation measures. While the policy documents address in detail the implementation of actions; there is less clarity on indicator implementation and targeting of monitoring and evaluation.

Discussion: This study highlights the need for iterative, coherent adaptation policy planning and indicator utilization to enhance adaptation outcomes and guide future research and policy development.

1 Introduction

Urban heat risk is a globally recognized risk with harmful effects on ecosystems, infrastructure, and people (IPCC, 2022). At 1.5 °C warming, more than 200 million people, in particular those already vulnerable, poor, and marginalized, could be exposed to unprecedented mean annual temperatures (Rockström et al., 2023). To respond to this risk, cities and local governments are increasingly preparing and implementing local climate action and adaptation plans (Sethi et al., 2020).

The quality of adaptation plans is increasingly being examined (Fuldauer et al., 2022; Reckien et al., 2023; Olazabal et al., 2019). Adaptation planning approaches should be robust for measuring the progress and effectiveness of implemented interventions (Owen, 2020; Olazabal et al., 2019), such as through analyzing adaptation scope, measures, and the monitoring and evaluation (M&E) process (Reckien et al., 2023). Currently, there is no single set of universally accepted criteria for assessing the quality of adaptation planning. However, several guiding principles and frameworks are widely acknowledged, with coherence often identified as a critical component, as it can help enhance the evaluation of adaptation efforts. Moreover, the mere quantity of adaptation measures undertaken does not necessarily reflect progress toward effective adaptation outcomes (Ford and Berrang-Ford, 2016; Reckien et al., 2023, 2025). Only some studies have examined the ways in which adaptation policy maintains its coherence throughout the policy cycle (Reckien et al., 2025; Ranabhat et al., 2018; Benson and Lorenzoni, 2017). Mechanisms for enhancing coherence remain underdeveloped (Benson and Lorenzoni, 2017), and progress in adaptation M&E continues to be hindered by a lack of coherence, absence of standardized tools, datasets, and baseline research (Ford and Berrang-Ford, 2016).

To respond to this knowledge gap, we develop a framework that connects adaptation policy cycle nodes, drawing on existing approaches: scoping, planned measures, actions, and M&E (Reckien et al., 2023). The adaptation coherence framework explains the content of each node of the adaptation policy cycle through which the internal policy coherence can be examined. We introduce a novel two-tiered coherence typology that divides the adaptation policy cycle into two coherence types: (i) implementation coherence (Is setting scope, defining measures, and planning implementation done in a coherent way?) and (ii) monitoring coherence (Are implementation and M&E planned coherently?). This division allows, on the one hand, to explore the relationship between adaptation scope and response types and, on the other hand, to determine the response types in which indicators are used.

We apply the framework to analyze 10 heat-prone cities (IPCC, 2022) with advanced adaptation plans, focusing on their adaptation actions and indicators. Our results show how the case cities target heat adaptation, how the aimed benefits are distributed, and where the key incoherences are. We discuss the need for further research on barriers to implementing more coherent M&E and iterative policy learning process.

2 Adaptation coherence framework

Adaptation plans identify and prioritize specific adaptation actions and measures aimed at reducing climate risks and enhancing adaptive capacity in the face of climate impacts (IPCC, 2022). They provide detailed information for the implementation of strategic goals to enhance adaptation and are iteratively updated based on M&E feedback within the policy cycle (Climate-ADAPT, 2016).

Adaptation planning usually starts with a risk or vulnerability assessment (Adger et al., 2018), which aids in identifying risk groups and establishing scope for local adaptation and defining specific adaptation goals (IPCC, 2014), which typically includes identifying key climate change adaptation beneficiaries (Scott and Moloney, 2022) and answers the questions ‘why, what, who and how’ (Stafford-Smith et al., 2022). After scoping and defining suitable adaptation measures, the next step is implementation, which means doing activities to deliver climate action (Hale et al., 2021). Following the implementation phase, the adaptation policy cycle ideally incorporates M&E to monitor whether the policy progress is moving toward the desired goals set in the scoping phase (Hale et al., 2021).

To examine the adaptation policy content and coherence, we divide the adaptation policy cycle to four nodes (Figure 1). Each node in the cycle is interconnected, and the precision achieved in the preceding nodes, such as establishing adaptation scope, influences the possibility of precision in the subsequent stages. The accumulation of knowledge (Trein et al., 2023) in each node contributes to the advancement of adaptation during the policy cycle (Reckien et al., 2023).

Figure 1

Figure 1. Adaptation coherence framework. The adaptation policy cycle includes four nodes, the content of which are reflected in adaptation plans. The content and coherence of the nodes in the plan can be tracked. Adapted from Climate-ADAPT (2016).

Implementation coherence (Figure 1) examines the alignment of the adaptation plans’ beneficiaries with adaptation benefits (scoping) and how adaptation benefits are distributed across the different response types. Monitoring coherence evaluates the coherence between indicators and response types, scrutinizing both the type of adaptation that employs indicators and the nature of indicators utilized. Assessing the implementation and monitoring coherence within policy cycles aids in comprehending the interactions among the various factors in the cycle and identifying the possible loopholes from scoping to monitoring and evaluation of the adaptation responses.

2.1 Scoping

Urban heat risk impacts the population, ecosystems, infrastructure, and economic sectors (IPCC, 2022). The economic sector, here, implies the set of economic activities and systems that are exposed and vulnerable to heat hazards, including labor, capital assets, services, and supply-chains (IPCC, 2022; Hallegatte et al., 2019) as well as the key actors in the private (households, businesses, insurance companies and financial institutions) and public sector (municipal, regional, and national governments) responsible for delivering public services, managing infrastructure, and executing regulatory or fiscal functions (Zhang and van Valkengoed, 2025; Kreibiehl et al., 2022; IPCC, 2022) that also contribute to adaptation measures and strengthening adaptive capacity (OECD, 2024).

To identify how adaptation is targeted, we apply adaptation benefit categorization (Carr and Nalau, 2023): (i) exposure benefit: the response provides an exposure benefit if it has a positive outcome on the physical environment, which lowers the frequency/magnitude of impacts on population, infrastructure, or ecosystem; (ii) sensitivity benefit: the response provides a sensitivity benefit if it reduces susceptibility of an beneficiary at risk (people, ecosystems, and infrastructure) to adverse outcomes (for people, e.g., pre-existing medical conditions, age, income, education; for ecosystems, e.g., drought tolerance; for infrastructure, e.g., asset material properties, asset usage load); (iii) adaptive capacity benefit: the response provides an adaptive capacity benefit if it increases the ability of people, ecosystems, and infrastructure to prepare, respond, and recover from heat impacts. Adaptive capacity of these beneficiaries can be increased by responses targeting economic sector, e.g., financing incentives (public & private) and via that, impact on people, ecosystems and infrastructure (Owen, 2020; West, 2014); (iv) hazard benefit: the response provides a hazard benefit if it reduces the hazard (i.e., it is a climate change mitigation measure or reduces hazards caused by heat, such as air quality, bush fires, drought, infrastructure damage, pests, power supply, wind).

2.2 Response type

Response types encompass the various measures taken by cities to address anticipated or actual heat events and temperature increases. They may include processes, practices, and structures designed to moderate the adverse effects of heat. The responses can be categorized based on three main types. We use the IPCC (2014) classification of adaptation options: (i) structural/physical: engineered and built environment, technological, and ecosystem-based, such as variations in the number of cooling surfaces and the amount of trees in urban areas; (ii) social: educational, informational, and behavioral, such as tracking the number of volunteers who actively contribute to offer information about heat risk; and (iii) institutional: economic, laws and regulations, and government policies and programs, such as the collection of data on factors influencing the development of plans, legislation, or economic instruments (e.g., insurance, catastrophe bonds, payments for ecosystem services, microfinance, disaster contingency funds).

2.3 Indicators

Policymaking demands insights into the advancement and success of adaptation efforts (Hanger et al., 2013). Establishing benchmarks for adaptation progress and assessing measures accordingly often involves the use of indicators (Jacob et al., 2022). To review how case cities utilize indicators, we categorize indicators into four types (Donatti et al., 2020; Seyisi et al., 2023) to explore what is being followed: (i) input: determines the resources needed for implementation of an activity; (ii) output: measures the quantifiable success of project activities, such as hectares of conservation areas restored or a number of trained healthcare practitioners in heat risk practices, that are necessary for reaching the aimed outcomes; (iii) process: a way to monitor how the adaptation goal is achieved, including, for example, technological, financial, and human resources to monitor the process to achieve the goal; and (iv) outcome: measures the effects resulting from project activities, such as reduced hospital visits or reduced impacts of climate change on urban greenery.

3 Materials and methods

3.1 The sample of city-level adaptation plans

Our sample is 10 advanced cities located in heat-prone areas (IPCC, 2022). Eight of these cities (Buenos Aires, Austin, Tokyo, Miami, Tel Aviv, Sydney, New York, and Philadelphia) are part of a global C40’s Cool Cities network (see Figure 2). One case city (Singapore) is part of C40 but not part of the Cool Cities Network. It’s a fast-growing metropolitan area in Southeast Asia that experiences increased harm from urban heat risk and is advanced in urban heat adaptation by innovative infrastructural and technological measures. C40 is one of the most researched climate networks that, regardless of several pitfalls (see, e.g., Davidson et al., 2019), has been identified to advance the partner cities climate actions (see, e.g., Nguyen et al., 2020). One case city (Vienna) is one of the first European cities to research and develop urban heat risk adaptation and actions and bring geographical diversity to the sample. These cities were purposefully selected because they are frontrunners in urban heat adaptation planning and therefore can have a greater number of adaptation measures and indicators to monitor them, which provides a rich sample to answer the research question. These cities had plans that were either entirely dedicated to heat-risk adaptation or included a specific section addressing heat adaptation. In addition, as these cities are located in different geographical locations and their policy systems vary, they face distinct challenges related to heat risk, leading to various types of adaptation approaches that enhance the diversity of our sample. The selected heat adaptation policy documents also covered different urban governance scales which increased the diversity of the sample: Metropolitan (Tokyo), City-State (Singapore), City (Buenos Aires, Austin, Vienna, New York, Philadelphia, Tel Aviv), and Local (New York, Sydney).

Figure 2

Figure 2. Global map of case cities, collected documents, document publication year, and the network cities belong to (C40 and C40 Cool Cities Network). In parentheses, the number of the city’s heat adaptation responses. Data. GISS, GISS surface temperature analysis (v4): Global maps (nasa.gov).

We collected relevant policy documents from each city, including adaptation action plans, mitigation plans, heat action plans, and strategies. Policy documents were all collected from the case cities’ websites with the help of the most common search engines and using the following search commands related to cities’ urban heat adaptation: “urban heat risk,” “heat action plan,” “adaptation,” “urban heat island,” “UHI,” “climate change,” “climate risk,” “response,” “plan,” and “strategy,” along with combinations of these search commands and city names. Initially, there were 33 policy documents, but the sample was limited to documents that were written in English and had clear responses to urban heat risk. After narrowing down the sample, there were 14 policy documents for analysis that were from 2015–2022.

3.2 Analysis method

We conducted a systematic policy document analysis by deductively applying the coherence framework (Figure 1; Cardno, 2018). Case cities’ policy documents were coded (Bingham, 2023) in the Atlas.ti (23.0) qualitative analysis software, first, for each urban heat risk adaptation measure as a response. We excluded all sub-action responses from the policy documents because these responses were not always focused on heat risk adaptation. After the initial coding phase, we conducted a second round of coding to determine the adaptation benefits and beneficiaries associated with each response. For this, we drew upon previous literature, descriptions of responses provided in cities’ policy documents, and finally, the authors’ consensus.

After identifying and classifying the responses, we coded all the indicators from the documents that were targeted to monitor heat adaptation measures. The coded indicators were tabulated alongside the corresponding response. In cases where an indicator was not pre-targeted to a specific response in the document, we inferred the most appropriate indicator based on the response characteristics.

Before the final coding, two co-authors and the corresponding author conducted an inter-coder agreement (ICA) (Appendix B) to avoid biases by confirming that codes mean the same thing for all coders (Krippendorff, 2004). We reviewed each response’s coding and, finally, identified 128 urban heat risk responses (Appendix A) and 75 indicators of which several are employed to monitor multiple responses.

After coding, we conducted a descriptive quantification of the results to identify recurring patterns within the dataset and to streamline the qualitative data into manageable and interpretable units. We employed data aggregation (Clark and Avery, 1976), where individual data points were connected into a collective format, facilitating the analysis of patterns and relationships within the dataset. We explored all the nodes of the adaptation policy cycle (Figure 1) and identified potential patterns. To analyze the content of the first and second nodes, we examined the benefits that responses confer upon the beneficiaries. For the second and third node, we explored which factors frequently co-occurred in adaptation responses and what indicators were targeted. Moreover, we explored the relationships between categorical variables by creating contingency tables through descriptive cross-tabulation. Response types were cross-tabulated with adaptation benefits to identify which response types contributed to each benefit and the number of responses associated with them. Subsequently, adaptation benefits were cross-tabulated with beneficiaries to determine how each adaptation benefit was distributed across different beneficiary groups. However, in the context of the hazard benefit, the analysis was inverted, as the beneficiaries function as active factors in hazard mitigation. The primary objective was to discern recurring patterns within the dataset, thereby elucidating underlying dynamics inherent in the relationship between these two key variables and responses.

In the implementation and M&E nodes, we cross-tabulated response types with indicators to identify which response types case cities monitor and the type of information collected from each response type. After the descriptive cross-tabulation was conducted, the results were presented in aggregated bar charts, enabling an overall assessment of how coherently adaptation benefits, beneficiaries, response types, and indicators are considered in advanced cities’ adaptation planning.

4 Results

4.1 Implementation coherence

4.1.1 Scoping and responses

The policy documents showed variation in both the types of adaptation benefits identified in the responses and the intended beneficiaries of those responses (Figure 3). The most prevalent responses offered adaptive capacity benefits to infrastructure and population, as well as hazard benefits through ecosystem responses. Miami, Austin, New York, and Sydney had the highest number of heat responses affecting population adaptive capacity - these cities were also the only ones considering the economic sector in their responses. Also, New York and Sydney were the only cities that considered population sensitivity benefits in their plans. Philadelphia had only responses that considered population adaptive capacity and did not include any mention, for example, of the implementation of green/blue/gray infrastructure. Vienna had the smallest share of population adaptive capacity responses but had the most significant amount of ecosystem responses that considered hazard mitigation.

Figure 3

Figure 3. Aggregated beneficiaries and adaptation benefits of city responses. HB, hazard benefit; SB, sensitivity benefit; EB, exposure benefit; ACB, adaptive capacity benefit; ES, ecosystem; I, infrastructure; P, population; EC, economic sector. The x-axis indicates how many responses in each category have been identified.

4.1.1.1 Adaptive capacity benefit

The results indicate that the advanced cities prioritize urban residents’ adaptation to heat as their primary concern, as the cities’ responses offer the most adaptation capacity benefits for the population (n = 85). Such responses are, for example, policies that facilitate the sharing of information, monitoring and evaluation of the progress of adaptation, and improving people’s adaptive capacity, for example, with improved shelter accessibility and cooling devices. In addition, responses oriented toward the formulation of an adaptation program and plan or organizing workshops were systematically categorized for the population beneficiary by advancing knowledge and the ability to adapt. Miami’s adaptation strategy emphasized the importance of communication, training, investments, and community, but it also included infrastructure measures, such as “build on the success of the Heat Season Campaign,” “engage and prepare healthcare practitioners,” and “expand access to water and shade.” Similarly, New York City’s plans prioritize equity in adaptation efforts, ensuring every citizen has access to cooling during heat waves. Responses such as “advocating for reforms to the low-income Home Energy Assistance Program,” “achieve cooling equity and reduce heat-related deaths,” and “continue ways to provide cooling to NYCHA residents and use results to inform future planning” exemplify this commitment.

Examples of responses that considered increasing the adaptive capacity of infrastructure (n = 28) included developing innovative funding models for cooling infrastructure and implementing existing building retrofit programs. Another commonly employed response involved the use of solar heat-blocking pavements, such as painting asphalt, roofs, and walls of buildings with white. Increasing adaptive capacity for infrastructure was particularly prominent in Austin with initiatives like “harden/retrofit critical facilities to hazard-resistant levels” and “acquire and install generators with hard-wired quick connections at all critical facilities, lift stations, and pump stations,” as well as in Miami with actions like “investment in energy resilience at evacuation shelters” and “pilot and scale cool pavements.”

Nineteen responses increasing the adaptive capacity of ecosystems were identified. These types of responses contribute to the ecosystem’s ability to confront and recover from heat-related risks, which impose additional stress on vegetation in urban areas. Examples of such responses include New York’s “fostering partnerships around urban forestry,” Singapore’s “enhancing habitat management and restoration,” and Sydney’s “implementing an urban forest strategy.”

Economic sector was considered the least among the responses aimed at increasing adaptive capacity. Economic sector was identified in 16 of the 128 responses: 14 for the private sector and seven for the public sector, with both sectors explicitly mentioned together in five instances. Austin considered economic sector in response to “evaluating the financial impact of prolonged outages of major utility facilities during and after significant weather events” to better prepare for possible financial impacts of heat events. Various responses were implemented to support the adoption of more energy-resistant technology, such as Miami’s “invest in energy resilience at evacuation shelters.”

4.1.1.2 Sensitivity benefit

Sensitivity benefit was the least considered of all four benefits, and it was least considered in terms of reducing the sensitivity of the population (n = 2). Sydney and New York were the only cities to incorporate responses in their heat plans that considered the population sensitivity benefits. In New York City, the strategy involves expanding green areas, supported by justifications of the positive impact of proximity to trees on mental and physical wellbeing, reduced morbidity and mortality in urban residents (attributed to trees offering psychological relaxation and stress alleviation), promotion of social cohesion, and support for increased physical activity. Meanwhile, Sydney is formulating an urban forest strategy, driven by the understanding that greener cities exhibit lower levels of obesity, higher rates of physical activity, and improved mental health.

Sensitivity decrease as an adaptation benefit was most often identified in responses targeted at infrastructure (n = 17). For example, in Austin, infrastructure’s sensitivity is intended to be reduced by “upgrading aging building systems in accordance with current code requirements, conducting condition assessments, and energy/water audits in critical communities”; and in Tokyo by “implementation of cool coatings”; and in Tel Aviv by “implementing use of climate-adjusted construction and finishing materials.”

Second, the case cities’ responses are targeted at reducing sensitivity of ecosystems (n = 11). Tel Aviv has planned to decrease ecosystem sensitivity by “increasing biodiversity” and “managing urban forests,” and New York has planned to “create and implement an authority-wide tree maintenance plan.”

The limited quantity of the sensitivity benefits may be because people’s sensitivity refers to health, age, and financial status (i.e., factors that are challenging to target directly with adaptation actions). However, some adaptation measures, such as urban green spaces, can reduce people’s sensitivity by promoting citizens’ mental health and physical wellbeing in addition to providing exposure benefits. It is noteworthy that only 2 out of 10 cities explicitly considered this aspect in their responses, despite the multifaceted benefits of green areas.

4.1.1.3 Exposure benefit

Exposure benefit was most often identified in the response within the population (n = 18). The population’s exposure reduction was targeted by creating diverse structures where people can find shade from the sun and cool off, such as shading structures on pedestrian streets in diverse ways. Examples include Singapore’s “strengthening connectivity between green spaces,” Tel Aviv’s “expanding green groundcover in the city,” and Vienna’s “shading open spaces and footpaths.”

Case cities’ plans considered the second-most exposure benefit for the infrastructure (n = 14). The responses that decreased the exposure of infrastructure notably employed green infrastructure, which reduced direct sunlight exposure on building structures, for example. Infrastructure exposure targeted in Singapore by “restoring nature into the built environment,” in Buenos Aires by “100,000 new trees by 2025,” and in New York with “cool the public realm.”

The reduction of ecosystems’ exposure was identified in cities’ responses four times. Only Austin, Sydney, and Vienna took into account the exposure of green areas. Ecosystem exposure is reduced in Austin by “building on the Austin Forest Climate Vulnerability Assessment, developing an urban forest climate change adaptation strategy for the Austin area”; in Sydney by “recognition of trees and green infrastructure as critical urban infrastructure”; and in Vienna by “adaptation of the urban structure and development.”

4.1.1.4 Hazard reduction benefit

Hazard reduction benefits were identified most often in responses targeted at ecosystems (n = 28). Vegetation actively cools the environment by evaporation, transpiration, and shading surfaces such as asphalt that would otherwise have absorbed shortwave radiation. Cities considered the hazard benefit by implementing various green infrastructure responses. Singapore is planting one million trees by 2030, Sydney is acknowledging the importance of trees and green infrastructure as critical urban infrastructure, and Buenos Aires is developing “green streets” where the road’s main material includes absorbent and biologically active surfaces in areas of the city where access to public green space is more restricted.

Second-most often, hazard benefits were identified in responses related to infrastructure (n = 18). Cities have employed diverse measures that consider the infrastructure’s impact on heat hazard. Miami seeks “increased support for efficiency and cooling upgrades” and “piloting and scaling cool pavements”; Vienna promotes “lighter colored buildings and surface materials as well as increasing permeability”; Tokyo is applying a “green building program for new buildings”; and Buenos Aires is developing its “meeting streets,” which are built in such a way that they cool the area and reduce traffic, reducing the amount of emissions.

4.1.2 Response types and adaptation benefits

4.1.2.1 Social

Our analysis showed that most of the social response types included educational and informational responses that offer adaptive capacity benefits (Figure 4). The measures identified in this category are designed to proactively equip individuals to cope with heat-related risks by enhancing their knowledge and awareness. Additionally, these responses encompass provisions for the wellbeing of vulnerable populations during periods of heightened heat risk. Most of the social responses were educational, including workshops and training programs. For example, Austin included hazard training to provide climate and weather hazard identification, response, and safety training to the City of Austin staff, especially staff working outside, as well as workshops on ways to retrofit historical homes to mitigate weather-related hazards. Miami County engages and prepares healthcare practitioners for heat risks and leverages the urban heat research group for continued learning. Also, Austin includes a response that uses participation to gain new knowledge on heat risks. Austin coordinates local volunteers to help collect environmental data about the hottest and coolest places in the region during a heat wave.

Figure 4

Figure 4. Distribution of coded adaptation benefits in response types. HB, hazard reduction benefit; SB, sensitivity benefit; EB, exposure benefit; ACB, adaptive capacity benefit.

4.1.2.2 Institutional

Most of the institutional responses were plans, strategies, assessments, laws, and regulations to foster adaptation to heat-related risks. These initiatives primarily involve enhancing current assessments, securing funding, and implementing regulations that promote heat adaptation measures. Institutional responses provide a distinct adaptive capacity benefit, and this was the most common benefit in institutional responses. For example, Austin creates and implements an Extreme Event Recovery Plan that includes a social capital component.

Adaptive capacity benefits arise from the institutional responses through the enhancement of knowledge and facilitation of proactive risk preparation. Furthermore, institutional responses influence sensitivity benefits, as evidenced by regulations mandating building retrofits that effectively diminish the sensitivity of structures to risks. For example, Sydney is developing an innovative funding model for cooling infrastructure.

4.1.2.3 Structural/physical

Most of the case cities’ responses were structural/physical. Structural/physical response types of measures offered the most adaptive capacity and hazard reduction benefits. Adaptive capacity benefits occurred in responses that increased the ability of people, ecosystems, and infrastructure to prepare and respond to, and recover from heat impacts. For example, a backup site for workers during an extreme heat wave offers tools for the population to survive the heat with fewer disadvantages. Hazard benefits were often identified in infrastructure responses, such as shading and greening, because these structures reduce the severity of the Urban Heat Island phenomenon (UHI). For example, Singapore, New York, and Miami are integrating cool surfaces into existing infrastructure.

4.2 Monitoring coherence

4.2.1 Indicators and response types

4.2.1.1 General aspects

Of a total of 128 responses, only 37 (Table 1) apply indicators to track implementation. Indicators are utilized in Buenos Aires, Miami, New York, Philadelphia, Tel Aviv, Singapore, and Vienna. Austin, Tokyo, and Sydney do not use/do not publicly mention that they utilize indicators to monitor their urban heat risk responses. However, Sydney has mentioned in its 2018 heat adaptation plan that their next step is to develop an M&E system for urban heat risk responses. Austin has named designated planning team members who are responsible for monitoring, updating, and reviewing the plan update, but indicators are not mentioned. Tokyo’s plans do not mention monitoring or indicators.

Table 1

Table 1. Cities’ responses, response type, utilized indicators, and indicator type.

Tel Aviv’s Climate Adaptation Action Plan (2020) and Miami’s Extreme Heat Action Plan (2022) had some responses that were open to interpretation. In addition, Tel Aviv’s plan reported all urban heat risk indicators (9) at the end of the document and did not link them to any individual responses, thus we used our judgment to link the indicators to relevant responses. Miami’s indicators were reported after each goal with responses, and the indicators were expressed in a detailed way. This made it feasible to link indicators specifically to individual responses.

Most indicators are utilized in Buenos Aires (9 indicators for 6 responses), Miami (23 indicators for 10 responses), New York City (15 indicators for 4 responses), and Tel Aviv (8 indicators for 4 responses). Miami utilizes all four indicator types, Buenos Aires uses only input and output indicators, and Tel Aviv and New York have not included process indicators in monitoring. In Singapore, two indicators (input and output) are utilized for two responses. In Vienna, four indicators are utilized for two responses, exclusively focusing on process indicators. Philadelphia applies four indicators, encompassing both process and outcome indicators for a single response. See Appendix C for details on how case cities utilize indicators for adaptation beneficiaries.

4.2.1.2 Indicator targeting for response types

4.2.1.2.1 Structural/physical

Monitoring structural/physical adaptation responses involves assessing changes in the city’s infrastructure. Output indicators (n = 18) were utilized the most in structural/physical responses. Output indicators quantify the short-term success of project activities, making them well-suited for assessing structural changes in urban areas, such as variations in the number of cooling surfaces, the number of trees in urban areas, and vegetative cover compared to surface temperature. These indicators provide valuable insights into the implementation of responses; however, they do not convey any information regarding the potential impact of these structural changes, such as their effectiveness in controlling urban heat.

Input (n = 15) and outcome (n = 15) indicators were second-most often utilized in case cities. Input indicators, focusing on structural or physical responses, gauge the required resources for activity implementation. For instance, in the context of the response “building new meeting streets,” inputs can be monitored by tracking the location and quantity of these meeting streets. The response to expanding green groundcover in the city to moderate the urban heat island phenomenon is monitored by an input indicator that calculates the number of days in which the temperature exceeds 32 °C. Outcome indicators were used to measure changes achieved through implemented structural/physical actions. For example, the outcome of New York City’s green infrastructure project is monitored by temperature variation across New York City.

Process indicators (n = 4) were the least utilized indicators in structural/physical responses, and were included, for example, for technological, financial, and human resources to monitor the process to achieve the goal. There was a higher prevalence of process indicators in comparison to other response types. In Vienna, process indicators were exclusively employed for monitoring structural and physical responses. This monitoring focused on tracking the augmentation and preservation of green areas, open spaces, and trees. Indicators included measures such as the green and open space factor, mapping green roof potential, and green space monitoring.

4.2.1.2.2 Institutional

The advancement of institutional responses is often gauged through the collection of data on factors influencing the development of plans, legislation, or economic aspects. Input (15) and outcome (15) indicators were most utilized in institutional responses. Input indicators monitored, for example, completion of a countywide resilience hub plan to track if the incorporation of an extreme heat plan was successful and the capacity of accessible emergency shelters to achieve cooling equity and reduce heat-related deaths. Input indicators tracked resources needed to achieve response goals. Outcome indicators measured the effects of implemented plan/strategies, for example, monitoring the number of trees planted on public lands through greening program.

Output indicators (14) monitor the implementation of the stages of laws and plans. The response “cooling the public realm” includes, for example, carbon reduction. This is monitored by following the amount of carbon reduced, calculated from the square footage of roofs coated. The response “seek increased support for efficiency and cooling upgrades” is monitored by tracking the number of single and multifamily housing unit retrofits.

Process indicators (1) were only used in Philadelphia. An indicator monitored the “updating the community health assessment” response by tracking heat vulnerability maps. This indicator informs the extent to which sufficient human and financial resources are available to support updating assessment.

4.2.1.2.3 Social

Social responses are systematically monitored through indicators that offer insights into individuals’ contributions to adaptation efforts. Alternatively, these indicators can gather pertinent information regarding, for example, vulnerable groups within the adaptation domain. Input indicators (14) were the most utilized indicators, and they identify geographic areas and populations most vulnerable to heat risks. Outcome indicators (9) offer insights into the effectiveness of adaptation responses. They furnish information on various outcomes such as the reach of heat risk knowledge, reductions in heat-related illnesses and deaths achieved through improved healthcare, and the provision of protective measures against heat. Output indicators (8) track the tangible efforts made in social responses, aiming to enhance people’s adaptability while minimizing exposure and vulnerability. For instance, these indicators monitor the installation of air conditioning systems and quantify the establishment of energy-redundant or resilient emergency facilities.

Process indicators (2) were the least utilized in social responses. The first indicator tracked the number of municipalities and community-based organizations involved in outreach and training to build on the success of the Heat Season Campaign. The second indicator tracked the number of professionals and volunteers trained to monitor the engagement and preparation of healthcare practitioners.

5 Discussion

Our framework addresses the issue of adaptation policy coherence across the implementation and monitoring of 10 advanced cities’ heat adaptation plans. Previous studies have mostly focused on only one part of the policy cycle (Reckien et al., 2023; Ranabhat et al., 2018; Benson and Lorenzoni, 2017), while our document analysis covers the policy cycle from scoping to responses and M&E. The purpose of the conceptual framework we introduce in this study is twofold: first, to advance adaptation policy research by contributing to the policy coherence literature from an internal adaptation policy coherence perspective, and second, to provide a practical tool for practitioners to consider coherence in planning adaptation policies. The framework supports the assessment of whether heat risks in cities are coherently considered in adaptation responses, whether these responses are monitored evenly, and whether different phases of adaptation are systematically assessed. Furthermore, the framework supports the use of outcome indicators, as outcome monitoring requires clear objectives and coherent policy design (Carr and Nalau, 2023; Fopa Tchinda and Talbot, 2024; Goonesekera and Olazabal, 2022). When adaptation responses fail to achieve their intended outcomes, this approach facilitates the systematic identification of gaps or incoherences in the policy cycle, thereby enabling targeted adjustments to enhance adaptation effectiveness (Reckien et al., 2023).

Although all cities in the study are considered as frontrunners in adaptation, their strategies vary, and patterns emerge among cities with similar planning approaches. First, cities with a history of social inequities and severe climate hazards, such as New York, which has concentrated on immediate risk reduction after major hurricanes and heat emergencies, tend to prioritize social and equity-focused measures to protect high-risk populations. Similarly, Austin, Philadelphia, and Miami emphasize social measures. Second, densely built cities or those with older architecture, such as Vienna, Tokyo, Singapore, and Sydney, prioritize structural and NBSs to adapt. They also apply NBSs extensively because each city has a dedicated greening plan: Tokyo’s Green Biz 2023, Singapore’s Green Plan 2030, and Vienna’s multiple greening programs alongside its heat risk strategy, which specifically targets the mitigation of the UHI phenomenon by NBSs. Tel Aviv is planning NBSs in response to intensifying heatwaves that threaten the local ecosystem, alongside social measures aimed at achieving their goal of reducing social inequity. Buenos Aires implements NBSs and energy-efficient measures to reduce heat and energy demand, simultaneously fulfilling its Carbon Neutrality 2050 strategy, enhancing both climate resilience and adaptation to urban heat risk.

With regards to ‘implementation coherence’, we observed disparities in the heat adaptation plans among cities, with varying emphases such as green infrastructure, gray infrastructure, and knowledge sharing. Most responses prioritized enhancing adaptive capacity for the population. Actions classified under social response types were least utilized, although these can effectively influence citizens’ adaptive capacity through knowledge gain (IPCC, 2014). Focus on knowledge sharing (e.g., workshops, mobile apps, flyers, information stands during heat events) is equally important, as adequate preparedness prior to a heat event and social responses during it can significantly influence various outcomes, including a decrease in mortality and morbidity rates (McElroy et al., 2020; Lowe et al., 2011; Matthies and Menne, 2009). Case cities mostly implement structural/physical responses, primarily influencing heat risk through infrastructure. Given cities’ inclination towards responses that modify the physical environment, it becomes important for them to understand the impact of infrastructure on heat hazard, because poorly designed infrastructure can exacerbate heat levels (Min et al., 2019; Qi et al., 2022).

Institutional responses primarily consisted of adaptation strategies and plans, while attention to the economic sector remained secondary. New York City, Miami, Austin and Sydney were the only cities that integrated adaptation measures with economic considerations.

Targeting adaptation of economic sector impacts adaptive capacity ensuring, e.g., equitable adaptation for households by offering support to those who cannot afford essentials (Kaswan, 2012; Chu and Cannon, 2021) like air conditioning for heatwave periods and by enhancing business productivity and economic growth through providing financing for infrastructure advancement. Economic assistance is also necessary to enhance adaptation in the public sectors, e.g., by financing incentives (IPCC, 2014). Despite the diverse benefits, the responses aiding economic sectors received minimal attention in the advanced cities’ plans that are expected to illustrate best practices in the field, while, obviously, acknowledging the potential bias of the small sample and selection criteria excluding cities with heat adaptation plans in languages other than English. Nevertheless, adaptation targeted at economic sectors, including both public and private, should be integrated into the cities’ plans, enabling the policy process to coherently address all beneficiaries of heat adaptation (Kaswan, 2012; Chu and Cannon, 2021).

With regards to ‘monitoring coherence’, our results show that the 10 advanced cities utilize indicators coherently across all response types. Yet, the results show that the utilization of indicators and overall M&E practices is lagging, evident in inadequate targeting and the limited scope of indicators employed. The use of indicators to monitor urban heat risk responses is insufficient, as cities like Austin, Tokyo, and Sydney do not publicly mention utilizing them, and Miami and Tel Aviv include indicators that are open to interpretation. There is also variability in how case cities use different types of indicators. Cities should employ a diverse range of indicators (input, output, outcome, process) to gain a comprehensive and accurate understanding of the impacts and effectiveness of their responses, as each indicator type offers a distinct perspective.

This aligns with the previous research and validates cities’ concerns, highlighting ongoing challenges such as the need for further development of M&E (Bryan et al., 2018; Goonesekera and Olazabal, 2022), as well as the persistence of a fragmented policy process, which undermines overall coherence (Benson and Lorenzoni, 2017).

The vague use of indicators may stem from various factors, such as lack of detailed local adaptation scoping and a poor understanding of adaptation action impacts (Goonesekera and Olazabal, 2022). Therefore, cities must establish clarity regarding the progression of the policy cycle. Consistent utilization of indicators for each response, or at least for every major adaptation goal, is important so that cities can track progress and thereby enhance the adaptation. Overall, the documents had input indicators the most and process indicators the least. This is a positive observation as process indicators have been criticized for their weak ability to describe the effectiveness of adaptation. Process indicators give a simplified view of adaptation that excludes relevant insights of the risk, progress, and other important information that may be necessary for decision-making (Leiter and Pringle, 2018; Chen et al., 2018; Berrang-Ford et al., 2019; de Sainz Murieta et al., 2021).

Since the case cities utilize a limited number of indicators, further research should explore cities’ barriers to employing M&E, e.g., targeting indicators and responsible entities. This study builds the ground for systematic coherent adaptation planning, but due to the nature of the data, we were not able to systematically analyze the coherence across all nodes – this would require, for example, a time series approach with several consecutive documents or in-depth interviews with the key actors or both. It would be useful to explore, for example, the coherence of the ‘M&E’ and ‘scoping’ nodes, and the patterns that occur in them, e.g., which beneficiaries are the indicators most targeted at. However, the purpose of this study is not to provide an exhaustive overview or a comparative analysis, but rather to conduct a conceptual analysis of internal adaptation policy cycle coherence and test it empirically. This research is intended as a conceptual advancement that can be further developed by extending the analysis to a larger set of cities. By applying this analysis to a broader sample that also includes cities from the Global South, it could be possible to explore what types of cities have higher coherence. This could reveal correlations between adaptation responses, benefits, and governance or contextual factors, providing additional insights into patterns and drivers of policy coherence. Quantifying coherence or developing indicator quality metrics could provide an opportunity for comparison and improved assessment of coherence. Conceptually, the framework could be expanded to include equity dimensions (e.g., targeting vulnerable groups) and temporal coherence (consistency over time). Methodologically, integrating mixed methods, such as combining policy document analysis with expert interviews, could enhance understanding of the reasons behind the emergence of inconsistencies.

One limitation of this study is its focus solely on English-language documents. This and the limitation of search keywords excluded potentially relevant documents. While we recognize the potential limitations related to selection bias, sample size, and the exclusion of documents in multiple languages, our aim was to provide a focused analysis within the defined scope, rather than an exhaustive dataset. Future research should incorporate a larger dataset to enable the application of large-scale quantitative analysis. Additionally, we employed human coding and did not apply text-mining or NLP approaches, as our study required nuanced, context-sensitive interpretation that automated methods cannot always provide (Macanovic and Przepiorka, 2024; Munnes et al., 2022).

6 Conclusion

We explore what 10 high-risk cities with advanced heat adaptation plans do plan in terms of heat adaptation and how coherent their adaptation policy cycles are. We address this knowledge gap by evaluating the coherence of cities’ heat adaptation processes through an examination of their adaptation plans. We find diversity in the quality of adaptation plans concerning the scope and cohesiveness of heat responses. Most of the 10 advanced cities target heat adaptation for population and their adaptive capacity. Cities increase the adaptive capacity of the population, for example, by building shelters and parks, increasing cooled public transport, and leveraging knowledge sharing. Yet, targeting adaptation to the economic sector is the least considered beneficiary, despite it being essential considering the socio-economic characteristics of the urban heat risks and for enhancing private and public sectors capacity to adapt to heat-related risks.

Responses offering a sensitivity benefit aim mostly to strengthen infrastructure and ecosystem resilience, minimizing their vulnerability to hazards. Their sensitivity is affected by, for example, maintenance of green areas and organizing workshops on building retrofitting. These ecosystem and infrastructure responses also have an impact on the population, reducing their heat exposure by, for example, shading. Cities’ ecosystem responses offer most hazard benefits. Various infrastructural measures are implemented to mitigate heat hazards, such as the incorporation of cool surfaces to maintain lower temperatures.

Case cities’ heat adaptation plans use input indicators the most, while process indicators are utilized the least. While the cities’ indicator use appears to be advanced based on the criteria towards process indicators, our research finds a gap in M&E practices overall. Miami and Tel Aviv do not specifically align their indicators with a singular response. Furthermore, Tel Aviv has indicators not directly linked to a specific response or broader goal. Sydney is planning an M&E system, and Tokyo does not mention indicators in their adaptation plan. While M&E should ideally be planned early in the policy cycle, our observations indicate that policy documents address in detail implementation of actions, and there is less clarity regarding the implementation and targeting of indicators.

Although our case cities are expected to implement their adaptation plans, there is a lack of clear evidence regarding the aimed outcomes in terms of risk reduction. In the future, cities can enhance their approach by making more specific scoping, developing indicators for a broader range of responses, and targeting these indicators more accurately.

Data availability statement

The original contributions presented in the study are included in the article/Supplementary material, further inquiries can be directed to the corresponding author.

Author contributions

JT: Writing – original draft, Software, Visualization, Formal analysis, Conceptualization, Validation, Data curation, Writing – review & editing, Methodology, Investigation. JK: Data curation, Formal analysis, Conceptualization, Validation, Methodology, Writing – review & editing, Software, Investigation, Writing – original draft, Supervision. AM: Formal analysis, Validation, Supervision, Data curation, Methodology, Writing – review & editing, Conceptualization, Writing – original draft, Investigation, Software. SJ: Conceptualization, Resources, Writing – review & editing, Funding acquisition, Validation, Investigation, Project administration, Supervision, Methodology.

Funding

The author(s) declared that financial support was received for this work and/or its publication. This article is a part of the HERCULES project funded by the Academy of Finland within the program “Climate Change and Health” (CLIHE) (grant no. 329239). Open access funded by Helsinki University Library.

Acknowledgements

We thank MSc. Scott Williams for his insightful comments on the manuscript and analysis process.

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Generative AI statement

The author(s) declared that Generative AI was used in the creation of this manuscript. Generative AI was used to assist with language editing. The authors reviewed and approved all AI-supported edits.

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Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fclim.2025.1741647/full#supplementary-material

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