How we build scientific Heat Action Plans with Indian cities

Good HAPs could benefit 76 per cent of Indians living in high to very high heat-risk districts.

Summers in India have undergone a transformation. Increased hot days are now accompanied by warmer nights and higher humidity — conditions that prevent the body from recovering from heat exposure. Analysis by the Council on Energy, Environment and Water (CEEW) shows that an increase in relative humidity is especially pronounced in North India. Cities such as Delhi, Chandigarh, Jaipur, and Lucknow are experiencing a six to nine per cent rise in relative humidity over the past decade (1982–2011), while 70 per cent of India's districts recorded more very warm nights. About 57 per cent of India's districts, home to 76 per cent of the total population, now fall into the high- to very-high heat-risk categories. Rising temperatures have now become a public health emergency.

India’s primary institutional response has been through city, district, and state-level Heat Action Plans (HAPs). It is a formally adopted, multi-agency framework that defines in advance how a city or district will detect, communicate, and respond to extreme heat events, as per the National Disaster Management (NDMA) guidelines. However, while approximately 300 cities have some form of  HAP today, more than 4,400 urban local bodies (ULBs) remain without one. Even among cities that do have HAPs, the scientific robustness varies significantly: a review of 38 HAPs in 2023 found that most contain blanket advisories not calibrated to local climate conditions, local health data, or population vulnerabilities. A city in coastal Odisha and a city in arid Rajasthan face fundamentally different heat risk profiles, and their HAPs must reflect that.

This blog draws on emerging evidence and implementation experience across Indian cities as well as CEEW’s own research in developing evidence-based, locally calibrated HAPs across 140 cities and districts in eight states to outline what an effective HAP actually requires.

A well-designed HAP answers four fundamental questions: when to act, where to act, what actions, and who will take responsibility for implementation. What follows is a practical guide to each.

When to act

The first decision in a HAP is also the most consequential: at what threshold does a city shift from routine preparedness to active response? In India, most HAPs currently rely on the India Meteorological Department’s (IMD) standard heatwave definition as a trigger. While these thresholds vary by region (coasts, plains, hills) and serve meteorological purposes well, they are not designed for public health. As a result, cities may respond too late or base actions on threshold levels that do not actually reflect health risks in their local context.

A better starting point is a heat-health threshold. This is a locally derived trigger point anchored in the relationship between temperature and health outcomes in that city, not merely in atmospheric conditions. Recognising this, the World Meteorological Organization (WMO) and the World Health Organization (WHO) jointly issued guidelines for Heat Health Warning Systems (HHWS) in 2015, placing localised, impact-based thresholds at the heart of effective heat governance.

These guidelines identify two primary methodologies:

• Biostatistical analysis establishes the statistical relationship between extreme temperature conditions and health outcomes in a specific location. It uses all-cause daily mortality adjusted for seasonal variability, cause-specific mortality, and emergency service call volumes. Thresholds can be derived from a single meteorological variable, such as daily maximum temperature, or from a composite index like the Heat Index, which integrates temperature and humidity. An example of this is the Ahmedabad HAP which used a dose-response relationship between daily maximum temperature and all-cause mortality to arrive at a temperature threshold for active response. The figure below visualises how as temperatures (or dose), rise, the response (or health risks such as heat-related illnesses or deaths), also increase measurably.

Image 1: Temperature-mortality curve: Daily deaths in Ahmedabad rise sharply once temperatures exceed 41°C, validating heat-warning thresholds (2001–2016).
Source: Developing local thresholds for heat health warning systems, NDMA

• Biometeorological indices are a practical alternative when reliable long-term health data are unavailable. Here, the 90th or 95th percentile of a city's historical daily maximum temperature serves as the warning trigger, meaning the threshold reflects conditions that have historically been exceeded on only 5–10 per cent of days. This WHO-WMO-endorsed approach grounds the threshold in local climatological reality rather than a national benchmark with no necessary connection to local health experience.

Given the lack of long-term data on mortality and morbidity, CEEW employed a hybrid framework for its HAP analysis of the 140 cities and districts, developing month-wise localised thresholds that reflect both the city's climatic baseline and the physiological realities of heat stress in a hot, humid environment. The approach goes beyond daytime extreme dry temperatures to incorporate felt temperatures, utilising the heat index, which is a composite of relative humidity and temperature. This is especially important in humid coastal cities, where felt heat can significantly exceed air temperature and where the physiological burden on residents is correspondingly greater (Image 2).

Image 2: An ice cream vendor at Miramar Beach continues work under intense coastal heat, where high humidity amplifies the body’s thermal stress.
Source: CEEW

This example from Cuttack city in Odisha illustrates how this plays out. Tables 1 and 2 show month-wise thresholds for yellow, orange, and red alerts derived from both dry temperatures and felt heat for the summer season. Two points are worth noting: first, thresholds rise consistently between March and May and fall in June, reflecting the city’s actual climatic seasonality rather than a constant national standard; second, felt-heat thresholds are consistently higher than dry-temperature thresholds in the later months, indicating the compounding effect of humidity. This enables more accurate risk assessment and better protection of vulnerable communities such as women, children, the elderly, people living with chronic health diseases and outdoor workers.

Table 1: Heat thresholds based on dry temperature for March–June (summer season) in degrees Celsius (°C)

Month	Yellow alert	Orange alert	Red alert
March	37	39	40
April	40	42	43
May	42	43	44
June	40	41	42

Source: Authors’ analysis

Table 2: Heat thresholds based on felt heat, which includes temperature plus humidity for March–June (summer season) in degrees Celsius (°C)

Month	Yellow alert	Orange alert	Red alert
March	37	39	41
April	40	42	44
May	42	45	46
June	42	44	46

Source: Authors’ analysis

Where to act

Once a city knows when to act, it needs to know where to direct that action. While many HAPs have strengthened city-level preparedness for extreme heat, heat risk is not distributed uniformly across a city. Significant variations in exposure, vulnerability, and adaptive capacity exist between neighbourhoods, shaped by differences in the built environment, socio-economic conditions, and population composition. Two neighbourhoods separated by a few kilometres can experience very different levels of risk.

The answer to this question can be found in a ward heat risk index. This index can be built using frameworks such as the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), which quantifies risk as a function of hazard (the intensity of heat exposure), exposure (the extent to which the built environment amplifies that heat), and vulnerability (the capacity of residents to cope). Each component can be measured using a combination of ward-level datasets spanning climate, socioeconomic, biophysical, and land-use and land-cover data.

• Measuring hazard and exposure: High-resolution climate datasets capture spatial variations in heat exposure and surface temperatures across cities. Such analyses can include indicators such as the number of hot days and warm nights, as well as measures of felt heat that combine temperature and humidity. Alongside this, Landsat 8 satellite imagery is used to measure Land Surface Temperature (LST) at 30 m resolution — enough to distinguish a park from a parking lot — across every ward. LST captures how hot the ground, rooftops, and roads actually get.  It helps identify areas that are consistently hotter than their surroundings, typically due to dense construction and poor green cover.
• Measuring vulnerability
  Vulnerability is assessed across three broad dimensions:
  • Physical environment: share of built-up land, building density, parks per square kilometre, and extent of green cover.
  • Population composition: proportion of elderly residents and young children, both of whom are physiologically less able to regulate body temperature, proportion of people with chronic health conditions or disabilities, sex ratio, and overall population density.
  • Socio-economic and infrastructural vulnerability: proportion of residents living in slums, illiteracy rates, health centres per thousand residents, and access to road networks and water sources.

Combining these dimensions into a composite ward-level heat risk index produces a map that helps administrators identify priority areas for action. In Cuttack, CEEW’s analysis identified Wards 12 and 26 as falling into the very high-risk category (Figure 2). Importantly, even neighbouring wards such as Ward 12 and Ward 11 fall into different risk categories. Ward 12 has a higher built-up density, with closely-packed structures and limited open spaces that trap heat, along with lower vegetation cover that reduces natural cooling. It also has a higher concentration of socio-economically vulnerable populations. 

Figure 1: Heat risk assessment under CEEW's HAP highlights Wards 12 and 26 as most at risk in Cuttack

But the index is most useful when disaggregated: two wards can carry the same overall risk score for entirely different reasons. One may be at risk primarily because of extreme surface heat and dense construction; another because it has fewer health centres per thousand population. The intervention required in each case is different, and a composite score alone cannot reveal this. This is what makes the index a decision tool rather than a ranking exercise. It tells us which neighbourhoods to prioritise for cooling centres, where early warning outreach must reach first, and where the health system’s capacity must be strengthened before a heatwave arrives. 

What action to take

Knowing when and where to act raises the question: what should the line departments actually do? Effective HAPs identify and prioritise short-, medium-, and long-term actions. This ranges from early warning systems, public awareness campaigns, and emergency response measures to urban greening, cool roofs, climate-responsive infrastructure, and heat-resilient urban planning. To strengthen their effectiveness as long-term adaptation tools, current HAPs need to incorporate a clearer implementation roadmap, including phased interventions, defined institutional responsibilities, financing mechanisms, and monitoring frameworks.

• Short-term measures are the first line of defence against extreme heat. They activate actions when thresholds are crossed and must be pre-positioned. They include strengthening heat early warning systems, disseminating timely public advisories, conducting awareness campaigns, preparing healthcare facilities for heat-related illnesses, ensuring access to drinking water, and establishing cooling centres or shaded public spaces.
  
  On early warning, the IMD’s comprehensive heatwave guidance system provides daily impact-based warnings, district-level forecasts, heat indices, and public advisories. State governments are increasingly integrating these heat warnings into public communication systems, using local-language messaging through SMS, mass media, and community networks to ensure that risk information reaches vulnerable populations in a timely and accessible manner. This last-mile dissemination of heat alerts is a critical component of effective HAPs, helping convert early warnings into early action.
  
  Similarly, cities have installed more temporary water kiosks, shaded bus stops, green shade nets in markets and high-footfall areas, and cooling shelters during peak summer months to reduce immediate exposure among outdoor workers and commuters (Image 3 and 4). Delhi has introduced innovative bamboo-based ‘cooling zones’ as part of its Heat Action Plan to provide relief from heatwaves in public spaces. These eco-friendly structures use bamboo, vetiver grass screens, natural ventilation, and mist-based cooling systems to reduce ambient temperatures while offering drinking water, ORS, and shaded resting areas for vulnerable populations. While Ahmedabad's ‘Cool Bus Stop’, developed under the city's HAP, combines khus (vetiver) curtains and a high-pressure mist cooling system to lower ambient temperatures by 6–7°C, providing relief to thousands of daily commuters exposed to extreme heat.

Image 3: Green shade nets installed in high-footfall areas near Kadamba Bus Stand provide low-cost, effective shading to reduce direct heat exposure for pedestrians and vendors.
Source: CEEW

Image 4: Cool Bus Stop at Lal Darwaza Market in Ahmedabad integrates shading and mist-based cooling to lower ambient temperatures and reduce heat exposure for daily commuters.
Source: CEEW

• Medium-term measures institutionalise heat risk management. These interventions move the city from seasonal response to systematic adaptation. They focus on strengthening governance infrastructure that makes heat response reliable: ward-level vulnerability mapping, heat-health surveillance, workforce training, occupational safety protocols, and inter-departmental coordination mechanisms.
  
  The Thane HAP offers an exceptional template: it proposes strengthening departmental coordination, improving hyper-local data systems for ward-level risk assessment, and integrating heat considerations into municipal planning processes. Revised work schedules and mandatory rest-water-shade provisions for outdoor workers, which require coordination between labour departments, employers, local governments, and occupational health authorities, are a further example of medium-term governance interventions that can substantially reduce occupational heat stress.
• Long-term measures address the root causes of heat vulnerability by transforming the built and natural environment. These cannot be delivered in a single budget cycle. They require integration into master plans, municipal budgets, capital investment programmes, and climate finance frameworks. Ahmedabad's HAP exemplifies this. It was launched in 2013 following the devastating heatwave in 2010, initially focusing on early warning systems, public awareness, healthcare preparedness, and emergency response to reduce heat-related mortality. The HAP gradually shifted from a predominantly responsive approach to a broader resilience-building framework to address the underlying drivers of heat vulnerability through heat-resilient infrastructure measures such as cool roofs, improved access to water, capacity building for vulnerable populations, health-sector preparedness through healthcare worker training and integration of heat risk into urban planning including the use of climate vulnerability assessments, urban greening, urban forests, and lake rejuvenation to mitigate heat exposure and strengthen long-term climate resilience.

Who will act

A persistent gap in many HAPs in the past was the lack of clearly defined institutional responsibilities, which weakens implementation on the ground. CEEW addresses this within HAPs by establishing two accountability structures. The first is a dedicated heat-wave task-force committee. The second is a responsibilities matrix that clearly maps every mitigation, preparedness, and response action in the HAP to a named department, specifying supporting roles for each. The matrix should distinguish between actions that are the primary responsibility of city departments, and those of the District Disaster Management Authority (DDMA) or the State Disaster Management Authority (SDMA) that play a supporting or coordinating role. Without this clarity, implementation can become inconsistent.

To ensure that the heat wave task force committees and responsibility matrix are translated into action, capacity-building and awareness sessions could be conducted with relevant stakeholders. These engagements play a critical role in ensuring that the information does not merely remain on paper (Images 5 and 6).

Images 5 and 6: Stakeholder consultations and capacity-building sessions conducted in Bhubhaneswar, Odisha, to operationalise HAPs at the city and district levels.
Source: CEEW

Equally important is a robust monitoring, evaluation, and learning (MEL) framework for every HAP. Implementing a HAP is only half the work. Knowing whether it is actually reducing heat-related illness and mortality and reaching the most vulnerable populations determines its real-world impact. MEL enables cities to track progress against each action, identify implementation gaps in real time, and provides opportunities for course correction before the next heat season. It also generates an evidence base that strengthens plan design, ensuring that each iteration of a city's HAP is more targeted, better resourced, and more effective than the last. Without MEL, HAPs risk becoming static documents rather than living, adaptive tools for building heat resilience.

With extreme heat emerging as a significant climate and public health risk, HAPs will continue to play a central role in advancing heat resilience and safeguarding public health, livelihoods, and economic productivity. Their effectiveness will depend on strong implementation, coordinated institutional action, and continuous monitoring to address evolving heat risks and local vulnerabilities.

Prerna Ojha is a Programme Associate, Anushka Goswami and Divyanshu Sharma are Research Analysts at the Council on Energy, Environment and Water (CEEW). Send your comments to prerna.ojha@ceew.in.

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