metadata: authors: 0: author: Jones,Nicholas K.W.
1: author: Tiwari,Asmita
2: author: Kikutake,Natsuko
3: author: Takacs,Sacha
4: author: Souverijns,Niels
count: India
docna: 0: docna: Prioritizing Heat Mitigation Actions in
            Indian Cities : A Cost-Benefit Analysis under Climate Change Scenarios
docty: Policy Research Working Paper
theme: Urban Infrastructure and Service Delivery,Economic Policy,Green Growth,Rural Development,Economic Growth and Planning,Environment and Natural Resource Management,Land Administration and Management,Climate change,Urban and Rural Development,Adaptation,Geospatial Services,Urban Development
abstracts: cdata!: Although deaths and economic losses due
            to extreme heat are rising globally, heatwaves remain a
            "hidden hazard" whose impacts are underrecognized
            due to measurement and valuation challenges. Cities in India
            are developing Heat Action Plans that combine physical
            cooling measures (such as urban greening and reflective
            roofs) with public health measures (such as heat-health
            early warning systems). However, there is a key knowledge
            gap on the relative efficacy of these actions. To inform
            debate on how scarce public funds could most efficiently be
            allocated to reduce deaths and productivity loss due to
            extreme heat, this paper develops spatially explicit heat
            risk maps for Lucknow, Chennai, and Surat under climate
            scenarios; models future health and economic losses under a
            &#x201c;no intervention&#x201d; scenario; and
            estimates the costs and benefits of alternative sets of heat
            mitigation actions. The modeling suggests that by 2050, the
            number of heat-related deaths could rise by one-third for
            the case study cities, while labor productivity losses could
            affect between 2 and 4 percent of their economic output.
            Among the interventions typically considered in city Heat
            Action Plans, benefit-to-cost ratios are favorable but vary
            significantly. Urban greening investments more than cover
            their costs based on the health and labor productivity
            benefits of the heat stress reduction they yield
            (benefit-cost ratio of 3:1). However, heat-health early
            warning systems offer the greatest harm reduction per dollar
            invested (benefit-cost ratios exceeding 50:1), suggesting
            that they are &#x201c;low-hanging fruit&#x201d;
            whose wider implementation across Indian and global cities
            should be prioritized.
display_title: Prioritizing Heat Mitigation Actions
            in Indian Cities : A Cost-Benefit Analysis under Climate
            Change Scenarios
listing_relative_url: /research/2024/10/34412634/prioritizing-heat-mitigation-actions-indian-cities-cost-benefit-analysis-under-climate-change-scenarios
topicv3: Climate Change Adaptation in Urban Areas
            m1326481 810,Urban Development m1327371 699,Urban Poverty m1327411 710,Disaster Resilience m1327651 1709,Heat Wave m1503649 3185
publishtoextweb_dt: 2024-10-28T00:00:00Z
dois: 10.1596/1813-9450-10960
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
no_of_pages: 31
author_keys: 0: author_key: 1125716
1: author_key: 864369
2: author_key: 1517860
3: author_key: NA
4: author_key: NA
model_extractions: Policy Research Working Paper 10960 Prioritizing Heat Mitigation Actions in Indian Cities A Cost-Benefit Analysis under Climate Change Scenarios _Nicholas Jones Asmita Tiwari Natsuko Kikutake Sacha Takacs Niels Souverijns_ Urban, Disaster Risk Management, Resilience and Land Global Practice October 2024
Policy Research Working Paper 10960

# **Abstract**

Although deaths and economic losses due to extreme heat are rising globally, heatwaves remain a “hidden hazard” whose impacts are underrecognized due to measurement and valuation challenges. Cities in India are developing Heat Action Plans that combine physical cooling measures (such as urban greening and reflective roofs) with public health measures (such as heat-health early warning systems). However, there is a key knowledge gap on the relative efficacy of these actions. To inform debate on how scarce public funds could most efficiently be allocated to reduce deaths and productivity loss due to extreme heat, this paper develops spatially explicit heat risk maps for Lucknow, Chennai, and Surat under climate scenarios; models future health and economic losses under a “no intervention” scenario; and estimates the costs and benefits of alternative sets of heat mitigation actions. The modeling suggests that by 2050, the number of heat-related deaths could rise by one-third for the case study cities, while labor productivity losses could affect between 2 and 4 percent of their economic output. Among the interventions typically considered in city Heat Action Plans, benefit-to-cost ratios are favorable but vary significantly. Urban greening investments more than cover their costs based on the health and labor productivity benefits of the heat stress reduction they yield (benefit-cost ratio of 3:1). However, heat-health early warning systems offer the greatest harm reduction per dollar invested (benefit-cost ratios exceeding 50:1), suggesting that they are “low-hanging fruit” whose wider implementation across Indian and global cities should be prioritized.

This paper is a product of the Urban, Disaster Risk Management, Resilience and Land Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at njones@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **Prioritizing Heat Mitigation Actions in Indian Cities: A Cost-Benefit Analysis under Climate Change Scenarios**

Nicholas Jones<sup>1</sup> , Asmita Tiwari<sup>2</sup> , Natsuko Kikutani<sup>2,</sup> Sacha Takacs<sup>3</sup> , Niels Souverijns<sup>3</sup> JEL Codes: Q54, Q51, R58, I18, O18 Keywords: Benefit-cost analysis, public health, labor productivity, climate change

> 1 Global Facility for Disaster Reduction and Recovery, World Bank

> 2 Global Practice for Urban, Resilience and Disaster Risk Management, World Bank

> 3 Vlaamse Instelling voor Technologisch Onderzoek (VITO)
# **1. Introduction**

on nearly all aspects of urban life, including health, the economy and infrastructure. Extreme periods of hot temperatures are associated with increased deaths and illnesses (Gasparrini et al, 2017), reduced productivity within heat-exposed sectors of the workforce (Kjellstrom 2016), increased suicide and accident rates (Park, Pankratz, and Behrer 2021), higher operating costs and reduced asset lifespans for energy and transport infrastructure (Chapman et al, 2013) and reduced learning outcomes for schoolchildren (Zivin et al. 2016). Global air temperatures may increase by up to 3.2°C by 2100 depending on global emission trends, but the frequency, duration and intensity of heatwaves is projected to increase even if global warming is limited to 1.5°C (Masson-Delmotte et al 2021). A national assessment conducted by the Indian government on climate change projects increasing temperatures for India through the 21st century, including increasing extreme heat events (Krishnan et al, 2020). India faces particularly acute challenges due to the projected increase in heat stress since limited access to domestic water sources, insulated buildings and air conditioning makes it harder for a significant portion of the 1.4 billion population to cope during periods of high heat stress (Azhar 2019, World Bank 2022).

Since the early 2000s, improved quantification of the losses caused by flooding, seismic risk and landslides have helped strengthen the global disaster risk management agenda and underpin increased investment in measures to reduce the losses they cause. By contrast, heatwaves have been described as a “hidden hazard” whose impacts often remain under-counted (Roberts et al 2023). Whereas storms, floods and earthquakes destroy physical assets such as houses, factories, roads and hospitals whose replacement cost can be quantified quickly, the most important channels through which heat waves cause harm are their impacts on human bodies: either through ill health or loss of productivity at work. Methods to assess heat hazard and quantify its health and economic impacts are well established, but their uptake has remained confined to research settings – such as geography and public health departments of universities – to a greater degree than with flood or seismic risk assessment (property-centered hazards for which the insurance and real estate industries have created a large market for risk assessment services). Mortality related to heat waves is known to be significantly under-counted in official statistics (Azhar et al 2014). This has contributed to a relatively low prioritization of heat risks among scientific stakeholders, policy stakeholders and the public.

With studies suggesting that parts of the Indian subcontinent will increasingly experience heat and humidity conditions that approach limits of human survivability by the late 21<sup>st</sup> century (Im et al 2017), heatwave preparedness and mitigation actions are an increasingly urgent consideration. Fortunately, resilience to heatwaves is a challenge that South Asian cities can address decisively and effectively given policy actions that are feasible at the urban scale. Indeed, focusing on these cities is strategic, as urban regions are more accessible, easier to govern, and efficient for implementing interventions compared to rural areas. India’s first city-level Heat Action Plan was developed in Ahmedabad, a city of 7.6 million people in the western state of Gujarat, where researchers documented a tripling of the daily all-cause mortality rate during the 2
heat wave of May 2010 (Azhar et al 2014). The action plan – which combines short-run actions to prevent deaths during an active heatwave with long-run investments in cooling city spaces through vegetation and building design – was credited with averting some 1,200 deaths per year in the city in the years immediately after its introduction (Hess et al, 2018). Its model of a ‘threshold-based’ heat action plan, in which localized temperature thresholds based on all-cause mortality data are used to trigger sector-specific actions in the health system, labor practices and public communications (among other domains), was recognized by the National Disaster Management Agency (NDMA) as a model for the development of city-wide heat action plans across the country.

A key feature of city Heat Action Plans as implemented in India and internationally is the large number of stakeholders that need to be involved for their successful implementation. Given the diverse physical and social settings in which heat stress affects humans – including homes, workplaces, streetscapes, transport settings, and public amenities such as hospitals and schools – agencies responsible for city planning, transportation and buildings management may have capacity to reduce heat within their sphere of influence. During a heat emergency, stakeholders that have points of contact with vulnerable individuals include city health departments, health care providers, employers, labor unions, community associations, NGOs and media (Knowlton et al. 2014). Adding complexity to the development of Heat Action Plans is the range of policy instruments that vary from direct governmental interventions (e.g., publicly funded heat wave alert system, provision of emergency medical care, green spaces) to mandatory regulations (e.g., building code amendments) as well as incentive-based and information-based interventions (e.g., subsidies for cool roofs and public awareness campaigns on staying healthy during extreme heat).

Studies have established heat mitigation benefits of (i) ‘place-based’ interventions such as urban greening and cool building materials, (ii) ‘people-based’ interventions such as heat health early warning systems as well as (iii) ‘resource-based’ interventions such as additional water and electrical power during heat waves (Roberts et al, ibid). A review of 220 studies of vegetation, water or cool building material-based interventions found that temperatures at project sites fell by up to 2°C in approximately two-thirds of cases and by more than 2°C in the remaining cases (Santamouris et al, 2017). Introduction of heat health warning systems in Asian, North American and European settings have shown reduction in excess mortality of 30% or more vis-à-vis expected levels (see studies of Hong Kong SAR, China; Ahmedabad; Florence; and Milwaukee, respectively: Chau, Chan and Woo 2009, Hess et al, 2018, Morabito et al. 2012, Weisskopf et al, 2002). However, while existing studies have created a rich evidence base on the efficacy of individual heat mitigation actions, less research has been conducted on their relative costs and benefits. This is an important gap since city leaders face resource constraints and a consequent need to prioritize among heat mitigation options.

This paper contributes to the literature in two ways. First, we estimate impacts of extreme heat for Indian cities in a no-intervention scenario. Second, we identify feasible packages of heat mitigation interventions that could feasibly be adopted by Indian cities. We introduce two intervention packages, namely 'medium ambition' and 'high ambition,' which vary in terms of resource requirements (see Table 1). We then assess the potential costs and benefits of these 3
intervention packages through two impact channels: health and labor productivity. The analysis is performed by means of an urban climate model that simulates expected future heat stress conditions with and without interventions combined with quantitative methods utilized in the public health and labor productivity impacts literature. We conducted simulations in three 'deep dive' cities: Surat, Chennai, and Lucknow. These cities were chosen as intervention areas due to their diverse climatic regions and regional importance. The findings are further generalized to the wider setting of large cities in India. The work is intended to provide an order-of-magnitude understanding of heat impacts and adaptation financing needs, and to support prioritization of measures within Heat Action Plans.

_Table 1: City heat action: Intervention packages_

|**Category of intervention**|**‘Medium ambition’ package**|**‘High ambition’ package**|**Impacts quantified**|
|---|---|---|---|
|**Urban greening**|Increase tree cover by 10%<br>from by 2050|Increase tree cover by<br>30% by 2050|Averted mortality<br>Averted<br>labor<br>productivity loss|
|**Heatwave early warnings**|Introduce heatwave early<br>warnings<br>reducing<br>heat<br>related excess mortality by<br>20%|Introduce<br>heatwave<br>early warnings reducing<br>heat<br>related<br>excess<br>mortality by 40%|Averted mortality|
|**Working hours shift**|Shift working hours towards<br>early<br>morning<br>and<br>late<br>afternoon<br>for<br>25%<br>of<br>outdoor workers|Shift<br>working<br>hours<br>towards early morning<br>and late afternoon for<br>50% of outdoor workers|Averted<br>labor<br>productivity loss<br>|
|**Cool**<br>**roofs**<br>**program**<br>**(homes/workplaces/public**<br>**buildings)**|Introduce cool roofs on<br>representing 12.5% of the<br>total roof area of the city|Introduce cool roofs on<br>representing 25% of the<br>total roof area of the city|Avoided cooling costs|

# **2. Methods**

# **2.1 Heat hazard for three Indian cities under climate scenarios up to 2050**

Heat hazard was modeled for Chennai, Surat and Lucknow using UrbClim, a computer-based framework for modeling climate variables and high spatial resolution (De Ridder et al. 2015). A detailed representation of each city’s surface including land cover, built-up and vegetated area, terrain, and human-generated heat were constructed using remote sensing datasets (see Supplementary Figures - Table 1); this information was combined with data on the historical and projected future climate from the ERA-5 and CMIP-6 datasets respectively. For future periods, urban growth was incorporated into the modeling through use of projected population extents corresponding to future Shared Socioeconomic Pathway (SSP) scenarios calculated in a separate study (Wang et al. 2022). Model runs were performed for a present-day reference period and two 4
future time periods. For the future time periods, separate model runs were conducted under lowand high-emission scenarios (SSPs 1-1.7 and 3-3.7 respectively). Urbclim temperature output was then used to calculate Wet Bulb Globe Temperature (WBGT), a heat stress index that takes not just temperature into account but also humidity and radiation from the sun and nearby surfaces. Model outputs included a suite of climate variables at 30-meter horizontal resolution including expected daily air temperature values (daily minimum, mean and maximums); number of days per year exceeding temperature thresholds; and WBGT heat stress values.

The simulations highlight the presence of significant Urban Heat Island (UHI) effects for the three cities as well as significant expected increases in heat exposure in future. Lucknow, with its inland location, experiences a stronger UHI effect than do the coastal cities of Chennai and Surat (Figure 1). The night-time UHI effect for Lucknow reaches as high as 5°C. UHI intensity is seen to increase with proximity to the dense urban core; the satellite city of Barabanki, with its lower density of buildings and sealed surfaces, also experiences a UHI intensity some 2°C lower than central Lucknow does. The spatially explicit estimates of future heat stress variables are a key input for the modeling conducted under this paper, while the significant increase in heat exposure – the magnitude of which differs depending upon global emissions scenarios – are themselves informative results for adaptation planning (see Section 3).

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periods. Crude death rates were obtained from state data (urban area crude death rate – NITI Aayong, 2022).

_Figure 2: Relationships between temperature and all-cause mortality for demographic groups in India_ Note: Relative risk describes the ratio of excess mortality compared to the mortality rate prevailing at the Optimal Temperature (OT). The Optimal Temperature is defined as the temperature at which mortality rates are lowest. Source: Adapted from Fu et al (2018).

We adopt a Value of Life Years (VOLY) approach to translate mortality impacts into economic terms <mark>(Desaigues et al 2011). This economic term has been employed in prior studies to illustrate the overall expenses associated with premature deaths resultng from excessive heat (as demonstrated in studies by Ebi et al., 2004, and Chiabai et al., 2018).</mark> Previous studies we examined indicated that each heatwave-related death was estimated to result in a loss of life years ranging from 6 to 9. For example, the 2003 heatwave in France, which led to approximately 15,000 excess deaths, was associated with an estimated 100,000 lost life years, equivalent to an average of 6.7 lost life years per excess death (Keller 2015). In contrast, Bosello and Schechter (2013) adopted a fixed value of 8 years for their calculations for the Mediterranean region. When determining the value for lost life years in our study, we considered the fact that India's overall life expectancy is lower than that of France and the demographic structure of India is characterized by a predominantly young population. We calculated the total cost of heat-related impacts by multiplying the 8 lost years by the VOLY metric for India.

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- (ii) Labor productivity channel

High temperature and humidity place the human body under strain, resulting in health risks to workers (particularly those in high physical exertion roles) and reduced physical and cognitive performance.

We utilize heat stress threshold values based upon the US Association Advancing Occupational and Environmental Health non-acclimatized standard by the National Institute for Occupational Safety and Health (NIOSH) and measured on the WBGT scale (Centers For Disease Control, 2018). We derive lost working hours (LWH) by applying productivity loss functions to WBGT heat stress values modeled through the UrbClim simulations. Separate productivity loss functions are applied for occupations with low, medium and high physical intensity (Figure 3).

We model labor productivity loss under climate scenarios in several steps. The working-age population for each city is divided into occupational sector based on the Periodic Labor Force Survey (PLFS, 2023). Sectors are categorized into low, medium and high work intensity (see Supplementary Figures – SF3). Average daily earnings by category are identified from the PLFS (2023) and city-specific sources. Foregone work output is calculated by applying productivity loss functions to sector-wise economic output and expected future losses are adjusted to present-day real prices to account for inflation.

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_Figure 3: Loss of work capacity at varying heat stress levels for occupations of light, moderate and high physical intensity._ <u>Note: The figure presents the relationship of labor productivity (y-axis) with heat stress (x-axis) for occupations</u> of differing physical intensities. As heat stress increases, work capacity decreases. Heat stress is measured in degrees Centigrade on the Wet Bulb Globe Temperature (WBGT) scale. Background colors denote heat stress categories varying from “no heat stress” (green background) to “extreme heat stress” (dark red background). The blue curve denotes light-intensity activities such as office work (physical effort of 180 Watts); the green curve denotes moderate-intensity activities such as retailing and light manual work (300 Watts); the red curve denotes high-intensity activities such as construction labor (415 Watts).

# **2.3 Heat mitigation interventions: Definition and costing**

In practice, city action plans to address extreme heat tend to comprise a ‘bundle’ of diverse types of interventions ranging from planting more trees and promoting a cooler built environment to introducing heatwave emergency actions including early warnings and health sector preparedness. Indeed, past studies by the World Bank have advocated a ‘Places, People, Institutions’ approach to city heat action planning in which actions target cooler city spaces, protection of vulnerable groups during heat emergencies, and mainstreaming of extreme heat mitigation across line agencies (Jones et al, 2022; Roberts et al, 2023). Based on desk review of existing Heat Action Plans and other strategy documents, we set out to identify feasible packages of interventions that could be adopted by cities vulnerable to heat in India. For each action area, we identified ‘medium ambition’ and ‘high ambition’ alternatives. The cost of each action was estimated based on local unit costs where available and international unit costs otherwise. All costs and benefits were converted to real 2020 US dollars. International costs were adjusted using Purchasing Power Parity (PPP). Here we focus on four major actions that are widely included in Heat Action Plans: 9
_(i) Urban greening._ Based on review of existing Heat Action Plans and urban greening interventions, we established that a medium-ambition investment involves increasing the city's total tree canopy area by 10%, while a high-ambition investment entails a 30% increase. For example, if the city currently has a 10% tree canopy coverage, the medium-ambition plan aims to raise it to 20%, and the high-ambition plan seeks to raise it to 40% within the city boundaries. It was assumed that two trees can be planted on a 10 x 10-meter square. The unit cost for each additional tree planted was US$ 2.50. Maintenance cost per newly planted tree was estimated at US$ 5 per year based on US reference values with PPP conversion applied (Vogt et al, 2015).

(ii) _Early warning systems_ . Heat health early warning systems are designed to convert weather forecasts of potentially harmful conditions into alerts that prompt individuals and institutions to take action to prevent heat-related illnesses and deaths. In our study, we used international benchmarks to estimate the initial setup and annual operating costs of implementing such a system in a large Indian city. The startup costs were estimated at US$ 150,000, using data from the U.S. city of Philadelphia, adjusted for PPP and inflation (Ebi et al., ibid).

We based the operating costs on a model for managing heatwave alert systems, with cost references from Madrid, Spain. Rather than relying on a fixed annual cost, as done in Toloo et al. (2013), we used a per-heatwave-day cost approach, using data from Chiabai et al. 2018. The operating costs, converted from Spain to India using the PPP index, were approximately US$ 1,800 per heatwave day.

Additionally, some actions, such as operating the public heat advisory service (‘Heatline’) and deploying extra Emergency Medical Service (EMS) crews, incur direct costs, primarily in the form of additional wages. Based on Ebi et al. (2004), we estimated these wage costs to be approximately US$ 4,750 per day, with around 40% allocated to EMS crews, up to 30% for maintaining the Heatline during heatwaves, and the remainder for other medical assistance.

(iii) _Working hours shift_ . One of the most straightforward but challenging adaptation measures to implement is shifting working hours to an "early morning" and "late afternoon" schedule. This change is particularly important for workers engaged in intense outdoor physical activities, who are most affected by excessive heat, leading to reduced productivity, especially during the middle of the day. Assuming current working hours are from 8 AM to 6 PM, including a one-hour break at 1 PM, the proposed adjustment involves shifting to a schedule of 6 AM to 11 AM and 3 PM to 7 PM for 25% (medium-ambition package) and 50% (high-ambition package) of outdoor workers. This shift aims to reduce the loss of working hours due to intense mid-day heat. Although this midday break policy effectively reduces heat-related issues, it can be challenging for workers who have long commutes between home and work. However, the United Arab Emirates has successfully addressed this concern by implementing a break from 12:30 to 3:00 PM from June to September (MoHRE, n.d.).

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_(iv) Cool roofs._ Various cool roof interventions can be adopted, ranging from low-cost to high-cost options. In this context, we focused on the most affordable option. Studies of cool roof treatments in Indian cities provide per-meter unit costs for several treatments, including lime wash—a natural mineral-based paint—and high-density polyethylene (HDPE) cool roof membranes (NRDC, n.d). We applied a unit cost for lime wash of US$ 0.75 per m2 and for HDPE cool roof membrane of US$ 2.10 per m2. Lime wash is assumed to be effective for 2 years, while the HDPE cool roof membrane is expected to last for 5 years. In the medium-ambition package, we assume that 12.5% of buildings' roofs will be treated with cool roof interventions, while in the high-ambition package, we assume 25% coverage of the buildings being covered.

# **2.4 Benefits of intervention options**

For each action, we identified expected benefits in terms of reducing adverse impacts of urban heat and adopted a suitable approach to value these benefits (see Table 2).

(i) _Urban greening_ . Past studies have estimated heat reduction benefits from tree planting considering the sensitivity of local heat stress metrics to canopy cover (Lonsdorf et al. 2021). We apply a linear regression of tree canopy coverage within the study cities against present-day daily temperatures as well as WBGT temperatures to derive our own local estimates of temperaturetree canopy coverage relationships (see Supplementary Figures – Figure SF2). Temperature reduction benefits from the assumed 10% tree canopy area increase (medium ambition scenario) and 30% increase (high ambition scenario) are derived based on this relationship.

The temperature reductions were used to calculate the decrease in the Relative Risk (RR) of mortality. This reduction in RR was then subtracted from the summed daily relative risks of each city at each timestep (which are calculated when temperatures exceed the optimal level for each city, as illustrated in Figures 5A and 5B). The adjusted RR values were then applied to population distribution maps for each city to estimate the overall impact on mortality rates. Through a similar procedure, predicted heat stress reductions due to the greening interventions were used to derive expected benefits in terms of averted labor productivity loss.

(ii) _Heat-health early warnings_ . A study of the Ahmedabad heat early warning system identified a 23% reduction of heat-related excess mortality in the years immediately following its introduction, while a study of France’s heat early warning system noted a reduction of up to 60% in heat-related excess mortality (Hess et al. 2018, Fouillet et al. 2004). We assume that mortalityreduction efficacy will vary according to the level of effort invested in developing a robust system grounded in extensive stakeholder consultation and supported by proactive communication and outreach efforts to the most vulnerable. Based on the range of mortality reduction benefits reported in the literature, we defined a ‘medium-ambition’ intervention as achieving a 20% reduction in heat-related excess mortality and a ‘high-ambition’ intervention as achieving a 40% reduction. These reduction factors were applied to the projections of heat-related mortality 11
under a 'no intervention' scenario to estimate the benefits of introducing an early warning system by calculating the number of deaths avoided.

(iii) _Working hours shift_ . We apply the shift of working hours to daily modelled heat exposure under future climate scenarios produced through the UrbClim simulations. The number of lost working hours averted through this ‘early mornings/late afternoons’ working regime is quantified and valued based on projected economic output.

(iv) _Cool roofs_ . Evaluation of cool roof interventions in India has shown that indoor air temperatures can be reduced by 2°C-5°C depending on building type and treatment type, resulting in reduced energy needs for air conditioning (NRDC, ibid). In Hyderabad, cool roofs reduced cooling energy usage by 14%-26% for previously black roofs and 10%-19% for previously uncoated concrete roofs, resulting in energy savings of 13-14 kWh per square meter for uncoated concrete roofs and 20-22 kWh per square meter for black roofs annually. We assume an annual energy saving of 17 kWh per square meter.

_Table 2: Heat mitigation interventions, their outputs and outcomes, and valuation approach_

|<br>**Intervention**|<br>**Output**|**Intermediate**<br>**outcome**|<br>**Value metric**||<br>**Valua**|**tion approach**||
|---|---|---|---|---|---|---|---|
|**Urban**<br>**greening**|Increase<br>in<br>tree<br>canopy cover|Temperature<br>reduction|Mortality risk<br>change)<br>Labor<br>productivity<br>change)|(%<br>(%|Relati<br>as<br> <br>tempe<br>Labor<br>as<br> <br>tempe|ve risk of mor<br>a<br>function<br>rature<br>productivity<br>a<br>function<br>rature|tality<br>of<br>loss<br>of|
|**Heat-health**<br>**early warnings**|Heatwave<br>early<br>warnings|Individuals<br>adopt exposure<br>reduction and<br>health-<br>preserving<br>behaviors|Mortality risk<br>change)|(%|Relati<br>as<br> <br>tempe|ve risk of mor<br>a<br>function<br>rature|tality<br>of|
|**Working hours**<br>**shift**|Change in working<br>hours<br>for<br>heat<br>affected workers|Reduced heat<br>exposure<br>of<br>workers|Labor<br>productivity<br>change)|(%|Labor<br>as<br> <br>tempe|productivity<br>a<br>function<br>rature|loss<br>of|
|**Cool roofs**|Increase in building<br>area with cool roof<br>treatments|Reduced<br>cooling energy<br>demand|Private cost<br>cooling<br>change)|of<br>(%|Coolin<br>functi|g expenditure<br>on of tempera|as a<br>ture|

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<u>Note</u> : Heatwave days are defined as days where the highest temperature exceeds the 90<sup>th</sup> percentile of the temperature distribution for a present-day reference period. Shared Socioeconomic Pathways (SSPs) are standardized scenarios developed in connection with the Intergovernmental Panel on Climate Change. SSP11.9 represents a scenario in which global emissions peak early; SSP3-7.0 is a scenario in which emissions remain high until after mid-century.

Looking to future periods, the projections point to significant intensification in heat stress metrics that will affect human health and the economy. Figure 5(A) depicts the expected change in the number of tropical nights (defined as nights where temperature do not fall below 25°C). In Surat, roughly 65% of nights per year currently fall into this category, but this would rise to 82% of nights. In the most densely built neighborhoods, the frequency of hot nights will be even higher with nocturnal temperatures <mark>rarely falling below 25°C. F</mark> igure 5(B) depicts the number of hours per year at high heat stress (>30°C WBGT) across all three cities, where high heat stress is defined using the WBGT metric. At present, we observe that some 25% of working hours in the year meet the high heat stress threshold for the three cities combined. Under a high emissions scenario, the number of high heat stress hours per year would rise by more than two-thirds for all cities amounting to some 40% of annual working hours.

_Figure 5: Projected change in key heat stress metrics for Chennai, Surat and Lucknow (2050 vs. present-day)_ <u>Note: Panel A depicts the expected number of tropical nights (defined as nights where temperatures remain</u> above 25°C). Panel B depicts number of hours per year with very high heat stress (defined as temperatures exceeding 30°C on the Wet Bulb Globe Temperature scale) for Chennai, Surat and Lucknow. SSP1-1.9 refers to a moderate scenario for global greenhouse gas emissions while SSP3-7.0 refers to a high emissions scenario.

# (ii) Impacts under a ‘no intervention’ scenario

# _Health impacts_

Heat-related excess mortality is, at present, estimated to range between 0.2 to 0.4 per 1,000 people for the cities of Lucknow, Chennai and Surat according to our modeling. This translates to approximately 1,000 deaths per year for both Surat and Lucknow and around 2,500 excess deaths per year for Chennai. The heat-related excess mortality rate is roughly 20% higher for individuals aged 70 or above. By 2050, under a low-emissions scenario, our modeling estimates a 30% increase in annual heat-related deaths per 1,000 residents for Chennai and Surat and a 38% increase in the case of Lucknow. The increase is greater in the high-emissions scenario, with each 14
city experiencing a rise of over 50% in the per capita heat-related excess mortality rate. When factoring in urban expansion this results in more than 3,000 heat-related deaths per year for Lucknow and Surat, and approximately 6,500 annual deaths for Chennai (Figure 6).

_Figure 6: Projected rate of heat-related excess mortality for selected cities (present-day and 2050 under moderate and high global emissions scenarios)_ <u>Note</u> a moderate scenario for global greenhouse gas emissions while SSP3-7.0 refers to a high emissions scenario.

# _Labor productivity impacts_

Currently, about 20% of annual working hours in these cities exceed safe heat stress levels, measured by the WBGT over 31°C. Under a high-emission scenario, this could rise to 30%-40%, significantly reducing productivity and causing economic losses of billions of US dollars per year, affecting up to 4% of each city’s GDP. For example, Chennai currently loses about 1.9 billion USD annually, or 2.3% of its GDP, due to extreme heat. By 2050, these losses could increase by 50% under the high-emission scenario. Cities such as Surat and Lucknow, both projected to undergo significant demographic growth, could see their economic losses double (Figure 7).

_Figure 7: Projected economic output loss due to labor productivity effects under climate scenarios for selected cities (present-day and 2050 under alternate moderate and high climate change scenarios)_ 15
# Economic Output at Risk

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impact on cities as global climate change progresses. At present, around one-fifth of working hours per year are currently too hot for high-intensity physical work to be conducted safely based on occupational health and safety standards. The number of lost working hours due to extreme heat is expected to rise by up to 30% in the case of Chennai, putting more than 4% of the city’s economic output at risk. While labor productivity outputs are crucial, it is however important to analyze these alongside expected health impacts, given that heatwaves result in illness and premature death concentrated among vulnerable segments of the population including the elderly. Consistent with existing epidemiological studies of extreme heat in India, our modeling estimates that the crude death rate may rise by 50% by 2050 under high emission scenario assuming a ‘no intervention’ scenario (Zhao et al. 2021).

Cities in India, and globally, are increasingly adopting measures to mitigate the diverse adverse impacts of extreme heat upon their citizens, economies, and infrastructure. The Ahmedabad Heat Action Plan has emerged as one ‘best practice’ model that other cities in India and internationally have emulated considering its multi-sectoral actions ranging from measures with a long time horizon that cool the physical spaces of the city (e.g., tree planting and cool roofs) and measures with a short time horizon that seek to save lives during heatwaves (e.g., issuance of color-coded alerts, activation of extreme heat protocols in hospitals, and measures to protect heat-affected workers). In this paper, we set out to model the benefits from adopting multi-sectoral packages of heat mitigation actions in Indian cities and to compare the benefit-cost ratios of the different actions.

We found benefit-cost ratios for the urban greening and heat-health early warning system interventions to be significantly positive. Increasing the area under tree canopy cover by 10% to 30% can be expected to yield air temperature reductions of up to 1.5°C on a localized basis, according to our analysis, which is in line with findings of a meta-analysis from European city-level studies of tree canopy cooling benefits (Iungman et al. 2023). Quantifying benefits of such temperature reduction based on averted mortality and labor productivity loss yields a positive benefit-cost ratio for urban tree planting. It is important to note that increasing tree cover and other natural assets in urban areas offers multiple advantages beyond reducing daily temperatures and heat stress. These enhancements create cooling areas for laborers, street vendors, workers, and commuters during hot days. Secondly, they play a significant role in flood risk management and provide a range of physical and mental health benefits to residents. This would be a significant advantage in labor surplus economies such as India, which are grappling with the challenge of addressing youth unemployment. These broader benefits may be equally or even more substantial in scale compared to the effects discussed here. Our finding that tree planting yields a benefit-cost ratio of 3:1 or higher suggests that such interventions ‘pay for themselves’ through mitigating adverse impacts of extreme heat on health and labor productivity alone, with their real benefit-cost ratios likely to be significantly higher, particularly in cases where tree planting brings significant flood mitigation benefits.

Our analysis also suggests that, among the heat mitigation interventions that cities can adopt, heat-health early warning systems has a particularly high ratio of benefits to costs. Indeed, with a benefit-cost ratio of 50:1 or higher, for heat warning systems – as well as high levels of 18
implementation feasibility – this intervention can be considered ‘low hanging fruit’ that produce strongly beneficial outcomes for limited financial outlays. The finding suggests that cities would be well advised to prioritize heat-health early warning systems.

Implementing heat early warning systems is shown to be a highly effective strategy. Our research, along with other studies, consistently shows a significant reduction in mortality rates and a benefit-cost ratio (BCR) exceeding 50. These findings are not unique; similar BCR values are observed in studies worldwide. For instance, research by Chiabai et al. (2018) and Ebi et al. (2004) revealed BCRs well above 50 for cities like Madrid and Philadelphia.

Our study has several limitations. The health impacts analysis examined mortality without performing estimates of health costs associated with non-fatal illness. The exposure-response curves utilized were derived from all-India mortality data; our analysis could be improved through use of locally derived temperature-mortality relationships that would better characterize heat impacts in India’s varied climatic zones. In future work, labor productivity impacts should be modeled with improved treatment of difference in heat exposure between occupations (eg. indoor vs. outdoor work). Despite these limitations, the present work contributes to advancing modeling approaches for urban heat mitigation and adaptation while pointing to strong policy conclusions about the urgency and efficacy of heat mitigation and adaptation actions that can be championed at the city level. Additional impact channels that could be analyzed would include extreme heat impacts on transport, power and water infrastructure and city services.

# **5. Conclusion**

Indian cities already experience night-time temperatures 5°C or more higher than outlying rural areas due to the urban heat island effect, with densely packed neighborhoods most affected. Combined with impacts of global climate change, cities such as Chennai, Surat and Lucknow will see 30%-50% more heatwave days and hot nights per year. The rise in heat stress will increase the number of working hours per year which are too hot to safely perform work – particularly in high physical-intensity and heat-exposed outdoor sectors such as construction, agricultural work, policing, etc. – putting as much as 4% of economic output in cities such as Lucknow and Chennai at risk by 2050 under a high carbon emissions scenario. In parallel, based on existing heatmortality relationships and accounting for a reasonable degree of additional heat-tolerance as urban Indians acclimatize to hotter conditions, heat-related excess mortality is expected to rise by approximately one-third by 2050, regularly resulting in hundreds of additional excess deaths per city during heatwaves, particularly among elderly and vulnerable populations. Cities are uniquely positioned to address the challenge of urban heat through policy instruments and investments such as tree canopy expansion, cool roofs and heat-health early warning systems. Benefit-cost ratios are particularly high in the case of heat-health early warning systems, suggesting that such measures should be prioritized for more widespread implementation in Indian and global cities.

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