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Deadly Landslides in India Made Worse by Climate Change, Study Finds

Extreme rainfall made 10 percent heavier by human-caused climate change triggered landslides that killed hundreds, according to a new study.

By Austyn Gaffney

A sudden burst of rainfall on July 30 caused a cascade of landslides that buried hundreds of people in the mountainous Kerala region of southern India.

That downpour was 10 percent heavier because of human-caused climate change, according to a study by World Weather Attribution, a group of scientists who quantify how climate change can influence extreme weather. Nearly six inches, or 150 millimeters, of rain fell on soils already highly saturated from two months of monsoon and marked the third highest single-day rain event on record for India.

“The devastation in northern Kerala is concerning not only because of the difficult humanitarian situation faced by thousands today, but also because this disaster occurred in a continually warming world,” said Maja Vahlberg, a climate risk consultant at the Red Cross Red Crescent Climate Centre. “The increase in climate-change-driven rainfall found in this study is likely to increase the number of landslides that could be triggered in the future.”

In a state that is highly prone to landslides, the Wayanad district is considered the riskiest part. As of Tuesday, at least 231 people had died and 100 remained missing.

The Kerala landslides were the second extreme landslide event in July, following one in Ethiopia that killed 257 people. July was the second-worst month on record, after July 2019, with 95 landslide events that caused 1,167 fatalities , according to data maintained by Dave Petley, the vice-chancellor of the University of Hull. Together, they caused roughly one-third of the more than 3,600 deaths resulting from some 429 fatal landslides recorded this year, Dr. Petley said in an email.

Already, 2024 is an outlier, Dr. Petley posted to The Landslide Blog on Tuesday . He wrote that he could “only speculate on the likely underlying reasons for this very high incidence of fatal landslides,” but “the most likely cause continues to be the exceptionally high global surface temperatures, and the resultant increase in high intensity rainfall events.”

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PERSPECTIVE article

Unprecedented climate change in india and a three-pronged method for reliable weather and climate prediction.

• 1 National Institute for Space Research, São José dos Campos, Brazil
• 2 Department of Meteorology and Oceanography, Andhra University, Visakhapatnam, India
• 3 Centre for Earth, Ocean and Atmospheric Sciences, University of Hyderabad, Hyderabad, India

India, one of the most disaster-prone countries in the world, has suffered severe economic losses as well as life losses as per the World Focus report. 1 More than 80% of its land and more than 50 million of its people are affected by weather disasters. Disaster mitigation necessitates reliable future predictions, which need focused climate change research. From the climate change perspective, the summer monsoon, the main lifeline of India, is predicted to change very adversely. The duration of the rainy season is going to shrink, and pre-monsoon drying can also occur. These future changes can impact the increase of vector-borne diseases, such as malaria, dengue, and others. In another recent study, 29 world experts from various institutions found that the largest exposure to disasters, such as tropical cyclones (TCs), river floods, droughts, and heat waves, is over India. For improved and skillful prediction, we suggest a three-stage cumulative method, namely, K is for observational analysis, U is for knowledge and understanding, and M is for modeling and prediction. In this brief note, we report our perspective of imminent weather disasters to India, namely, monsoons and TCs, and how the weather and climate forecasting can be improved, leading to better climate change adaptation.

Introduction

The Indian economy still significantly depends on agriculture, which, in turn, depends on the summer monsoon rains occurring from June to September. In the present scenario of climate change, it is essential to know how the Indian summer monsoon rainfall is going to change in the future. In a recent detailed study with regional climate model projections, Ashfaq et al. (2020) suggest that an important adverse signal of future climate change over the Indian monsoon region in the RCP8.5 scenario ( Krishnan et al., 2020 ; Jyoteeshkumar Reddy et al., 2021 ) can occur. The sinking of the Indian monsoon rainy season onset is projected to delay by five to eight pentads and a shrinking of the monsoon rainy season. India can experience pre-monsoon drying as well.

In a recent innovative study, 29 world experts ( Lange et al., 2020 ) from different institutions and different countries, reached some important conclusions. These inferences deserve urgent attention and action plans by policymakers. They considered six categories of extreme climate impact events, namely, river floods, cyclones, crop failures, wildfires, heat waves, and droughts. These authors ( Lange et al., 2020 ) quantified the pure effect of climate change on the exposure of the global population to the events mentioned. One important conclusion, which is of grave concern to India, is that the largest increase in exposure is projected here. Thus, to avoid huge damages due to these disasters, such as deaths and loss of property, urgent and more reliable predictions are needed. We, however, must clarify that there has been tremendous improvement in numerical prediction of tropical cyclones (TCs) in the last few decades in India [e.g., Pattanaik and Mohapatra, 2021 ; Saranya Ganesh et al., 2021 ; Sarkar et al., 2021 , and all other papers in January 2021 of Mausam, a special issue on the state of the art on TC prediction in the North Indian Ocean (NIO)], but what we claim is that applying theory can enhance the skills from the current day model outputs substantially more as discussed in the following section. To provide an analogy, in a recent study, Rao et al. (2021) attempted to connect observations, theory, and a prediction plan for heat waves. This prediction method can be applied to a numerical weather prediction model to predict deadly heat waves; thus, Rao et al. (2021) used a K, U, and M approach for the prediction of deadly heat waves over India.

From the context of the three-pronged K, U, and M method (hereafter, KUM), there are sufficient observational studies, or K, and also some attempts have been made using highly sophisticated, state-of-the-art (atmosphere and ocean) coupled models for predictions, M. What is most lacking, however, are theoretical studies (U) aiming to find out the causes for disastrous TCs or the highly complex regional monsoons.

According to a recent 2021 overview of current research results by the Geophysical Fluid Dynamics Laboratory of Global Warming and Hurricanes 2 , the severity and frequency of TCs are increasing globally. A recent study ( Balaguru et al., 2015 ) also suggests an increase of TCs globally even over the NIO. Essentially, the increase in the strong TCs has far-reaching implications for society because these include the most harmful aspects, namely, storm surges and heavy rains with intense wind speeds. Indeed, TC rainfall rates will possibly increase in the future due to various anthropogenic effects and accompanying increases in atmospheric moisture. Rapid intensification of TCs poses forecast challenges and increased risks for coastal communities ( Emanuel, 2017 ). Recent modeling studies ( Emanuel, 2020 ) show an increase of 10–15% for precipitation rates averaged within about 100 km of the cyclone for a 2°C global warming scenario. As per IPCC AR5, higher levels of coastal flooding due to TCs are expected to occur, all else assumed to be constant due to rising sea levels. In this situation, together with the rise in sea level, the impact due to the strong TCs deteriorates the conditions of the increasing coastal population across India and the neighborhood. As the NIO is one of the typical regions with a population of 1.353 billion (2018), about 18% of the global population by 2020, it is highly susceptible to strong TCs causing adverse living conditions, and the implication is that stronger TCs will be worse.

According to reports from a respected BBC newspaper 3 , 4 , and a potential report 5 from the Indian Meteorological Department, Amphan is a very severe cyclone that transited the west coast of India in 2020 and also caused a lot of damage. The super cyclonic storm Amphan is the costliest case in the recorded history of TCs with damage of US$15.78 billion and also total fatalities of 269. Similarly, in the year 2019, a loss of US$11 billion occurred due to TCs. In the year 2020, there was a record-breaking occurrence of eight TCs over the NIO: five cyclones and three major cyclones compared to the climatology of 4.9, 1.5, and 0.7. We note a drastic increase in category 3 and beyond hurricanes occurring in the NIO and also a significant increase in the Northern and Southern hemispheres ( Figure 1 ). Also, there is a substantial increase in accumulated cyclone energy (ACE) in the last two decades in the NIO and Northern and Southern hemispheres ( Figure 2 ). In 2019, record-breaking ACE of 85 × 10 4 knots 2 , occurred in the NIO, nearly twice the previous record ( Singh et al., 2021 ; Wang et al., 2021 , BAMS). The decrease in the projected number of TCs found in some studies ( Sugi et al., 2017 ) is overcompensated by the huge increase in intensity similar to that found over the NIO in 2019 and 2020. Furthermore, as if to worsen the situation in a colloquial sense, Wang and Murakami (2020) show that the general atmospheric and ocean parameters, which show a high global correlation with the number of TCs, nevertheless show only a very low correlation with TCs of the NIO. Thus, urgent research should be carried out to understand the causes of the occurrence of TCs over the NIO. Even globally, in the last 39 years (1980–2018), weather disasters caused about 23,000 fatalities and US$100 billion in damages worldwide. Each year, weather events displace huge populations, drive people into poverty, and dampen economic growth globally ( Kousky, 2014 ; Munich, 2020 ; Hoegh-Guldberg et al., in press ). The underlying causes show a marked signal of anthropogenic roots and global warming (e.g., Sobel et al., 2016 ; Im et al., 2017 ).

Figure 1 . The number of category 3+ hurricanes that occurred in the Northern and Southern hemispheres and the NIO (black dotted line indicates a linear trend, and orange line indicates significance at the 95% confidence level) ( http://tropical.atmos.colostate.edu/Realtime/index.php?archandloc=northindian ).

Figure 2 . ACE (in 10 4 Knots 2 ) in the Northern and Southern hemispheres and the NIO (black dotted line indicates a linear trend, and orange line indicates significance at 95% confidence level) ( http://tropical.atmos.colostate.edu/Realtime/index.php?archandloc=northindian ).

Henceforth, we focus on the TCs as well as summer monsoons, which are the two most relevant weather and climate phenomena for the Indian region.

A Three-Stage Method to Study and Plan Reliable Prediction

Because India is rigorously prone to natural disasters as well as impacts due to anticipated changes in the summer monsoon in the future, there is indeed a serious question as to how to study the causal mechanisms of these disasters and plan to mitigate them. In this context, the late Gill (1985) , an accomplished geosciences expert, suggested almost 35 years ago the KUM method, namely, knowledge, understanding, and modeling, a three-pronged approach. The first step (K) is to improve observational knowledge of calamity-causing weather events and next a theoretical understanding to find out the cause of a specific effect, probably utilizing linear analytical mathematical solutions (U). Finally, the third one (M), using the presently available highly complex coupled (atmosphere and ocean) models giving numerical solutions to non-linear equations, pioneered by Phillips (1956) , predicting future occurrences. The order of KUM seems to be important. Although relatively substantial observational results are available in the Indian context for meteorological and oceanographic events, very few theoretical studies have been made delineating the causal mechanisms. Thus, this aspect should be given priority. In a recent comment, Emanuel (2020) also stressed the need for theoretical studies. Finally, only after acquiring the observational, knowledge, and cause-and-effect relationships in theoretical studies, only then , should one embark on numerical or climate modeling to successfully predict the future.

In this context, it is illuminating to recall the comments of Phillips (1970) , one of the founding fathers of theoretical meteorology and numerical weather prediction: “in making a numerical forecast, one takes a set of numbers.regardless of.synoptic structures.by another set of numbers, representing the forecast. The computation of a set of numbers depicting the formation of a front, is of course, not a theory of fronts (unless one is content to point to the equation of motion as theory!!!!!)” Thus, one should be very careful using numerical models to develop a theory of TCs, and in the Indian context, monsoon depressions (MDs) are crucial for monsoon rainfall. Today, many students and scientists worldwide spend most of their valuable time dealing with huge data sets and running numerical models to simulate rather than to develop a theory. Tellingly, Emanuel (2020) , mentions that presently there is “computing too much and thinking too little.” Indeed, there is an urgent need for curiosity-driven theoretical research even in the Indian context. One interesting example to stress the importance of theory is, today, that the best numerical weather prediction is in mid and high latitudes in winter. This is because the basic theory behind the mechanism of winter weather changes, the baroclinic instability, was discovered more than 70 years ago by Charney (1947) , and models and observations evolved accordingly. Thus, it is important to realize, without the correct understanding of the causal mechanisms through theory, one will never be able to predict correctly and completely the required weather or climate or its changes with just the brute force of computers available today!!!

TCs Over the NIO

Regarding the theory of the generation mechanisms of TCs, there are two well-known hypotheses, namely, (a) the conditional instability of the second kind (CISK) and (b) wind-induced surface heat exchange (WISHE) (please refer to Tomassini, 2020 for a comprehensive discussion of these two processes). A detailed discussion of these two is beyond the scope of the present short article. However, the authors quickly discuss these two mechanisms in the context of TCs over NIO.

In the case of TCs, the pre-synoptic disturbances get their energy by the complex interaction of two different horizontal scales, namely, cumulus convection of about 1 km and synoptic systems of about 500 km. How this interaction happens is a topic of debate, though, and most of the research in the published literature is about TCs in tropical ocean basins other than the NIO region.

Briefly, we discuss the basic characteristics of CISK and quasi-equilibrium (or WISHE). In the process of CISK, the buoyant convection can occur only when low-level stability is weakened (see Figure 2 ; Ooyama, 1969 ), and in the other, moist convection is governed by the vertically integrated measure of instability. As noted by Tomassini (2020) , meteorological conditions vary greatly from one region to the other in the tropics and also in the same region from one season to another (see Ashok et al., 2000 ; Rao et al., 2000 ; Raymond et al., 2015 ). Raymond mentions two tropical places, Sahel and the Western Pacific, where conditions are very different. Now, how do the conditions vary, during (i) pre-monsoon, (ii) MDs, and (iii) post-monsoon TCs? Similar to Bony et al. (2017) , we suggest that more detailed observations of both satellite measurements and data developed in field programs should be used to understand the convection and circulation coupling of TCs over NIO. For example, the INCOMPASS IOP field program, which collects data from strategically installed ground-based instruments in India, is one such program ( Fletcher et al., 2018 ).

Another, synoptic disturbance of importance is a MD. Despite several observational and theoretical studies by many authors (for example, Sikka, 1977 ; Mishra and Salvekar, 1979 ; Aravequia et al., 1995 ; Boos et al., 2017 ) trying to understand the basic mechanism of origin, some fundamental questions remain unanswered. Similar to TCs, the lack of understanding of how convection and MD circulation couple hinders the prediction. For both TCs and MDs, we suggest analyzing time vertical sections of potential temperature, equivalent potential temperature, and saturated equivalent potential temperature such that one can get an idea of the relative importance of CISK or the quasi-equilibrium hypothesis discussed briefly above.

Another method for elucidating the study is to examine the system's energetics, i.e., TCs or MDs. Lorenz (1960) mentions, “one enlightening method of studying the behaviour of the atmosphere, or a portion of it, consists of examining the behaviour of the energy involved.” Earlier Mishra and Rao (2001) used limited area energetics to infer the mechanism of generation of Northeast Brazil's upper tropospheric vortices. Also, Rao and Rajamani (1972) examined the energetics of MDs. These methods of energy analysis, for example, can be used to isolate or single out the basic mechanism of generation of TCs or MDs, using more recent well-covered data, such as the INCOMPASS IOP program ( Turner et al., 2019 ). Later, targeted numerical model studies should be used to not only verify the process/processes identified in energetic and diagnostic studies, but to design dynamics-based indices related to TC formation that are relatively easier to predict. For example, a CISK parameter may be easier to predict with a longer lead as compared with the TC rainfall. These methods are again akin to the KUM approach. Such carefully verified and designed indices, when operationalized, will substantially help in extending the lead prediction time. Probabilistic dynamical-statistical downscaling tools can also be developed to relate local rainfall with these indices. This will also potentially enhance the lead time of the TC-related deluge. Similarly, a better understanding of model ability in capturing the conversions between different forms of energy.

Again, several aspects of monsoons, particularly, the Indian Monsoon are still not completely clear and hinder the mechanisms of prediction. In a recent exhaustive study, Geen et al. (2020) , discussed several aspects, primarily from a theoretical standpoint even though this study was developed based on the concept of a global monsoon, Figure 2 of Geen et al. (2020) shows only a very low correlation in interannual variations of rainfall, the main meteorological element that must be predicted. However, the different regions of monsoons with different geographical boundaries raise serious objections about the global monsoon concept.

Several studies exist in the literature regarding the observed aspects of the Indian summer monsoon (the K part of the three-pronged method), and modern numerical models are employed to improve prediction skills ( Sahai et al., 2016 ; Rao et al., 2019 ; Mohanty et al., 2020 ). From an almost zero skill, we have reached a stage at which the skills for predicting the area-averaged Indian summer monsoon are found to be statistically significant. This is great progress. Having said that, there is a great scope for further improvement. Although the broad regionally averaged skills are statistically significant, they are modest. Further, improving the skills such that they are locally useful is the obvious goal but still a long way ahead. Although the prediction skill improved through better methods of, for example, data assimilation and parametrization schemes, to improve the predictions further, we need to diagnose the improved representation (e.g., Halder et al., 2016 ; Saha et al., 2019 ; Hazra et al., 2020 ), better replication of physical processes and scale interactions.

Notwithstanding all these technical improvements, the large-scale physical causal mechanisms are not clear yet. This can only be done with the studies aiming to understand the cause-and-effect relation or the U in the three-pronged method. As mentioned earlier, with more observational studies aiming to identify the correct interaction mechanism over NIO between convection and large-scale monsoon circulation (either CISK or WHISE), then this mechanism can be included in the numerical models. Also, controlled experiments using simple models, such as the one by Rao et al. (2000) , can be used to identify relative roles of mountains and thermal contrast in generating the Indian summer monsoon. In the state-of-the-art coupled models, because of extremely complex non-linear interactions among various physical mechanisms, it is almost impossible to isolate the cause of a specific effect.

Again, the diagnostic study based on energetics, such as the generation of available potential energy (PE) by latent heat and the baroclinic conversions, for example, may reveal relative roles of some physical processes, such as convection in the Indian monsoon. In a recent companion study (Rao et al., under review), comparing the South American and Indian monsoons, we found that, in the Indian monsoon, the baroclinic conversions P ¯ (mean available PE) to P ′ (eddy PE) to kinetic energy (KE) is non-existent, and the KE of monsoon is mainly furnished by the generation of perturbation PE by latent heating (rainfall) and subsequent conversion to KE. In contrast, over the South American monsoon, both the baroclinic conversions and generation terms are equally important. This is probably because the Himalayas extend from East to West across the cardinal northern border of the country, which does not allow mid-latitude baroclinic waves to penetrate at lower levels while the Andes mountains in South America extend along North to South, permit these waves to penetrate even as low latitude as Manaus, where even austral summer cold waves (FRAIAGENS) are noted. Furthermore, studies are necessary to verify how energetics vary between wet and dry monsoons in these two regions.

In a review article by Geen et al. (2020) , the authors discuss attempts to understand fundamental dynamics (U in our three-pronged method). Geen et al. (2020) mention a very similar KUM approach for monsoons (their section 3). Such efforts are urgently needed from the context of the Indian monsoon. They even discuss the south Asian monsoon (their section 3.1.2). Although they tried to reconcile between global and regional monsoon features, the differences are more striking as we mentioned earlier, regarding the Indian and South American monsoons. In the case of the East Asian monsoon, at least one author ( Molnar et al., 2010 ) mentions, “‘monsoon' is somewhat of a misnomer.”

Although there are some uncertainties in the methods used by Lange et al. (2020) , the importance of their conclusion is unambiguous. They mention that “anthropogenic” climate change has already substantially increased the exposure to extreme global climatic impacts, and anthropogenic warming is projected to exacerbate the pattern of climate change that we are already noticing nowadays. Thus, it is urgent to restrain the increase in global average temperature well below 2°C, which would significantly reduce the risks and impacts of climate change 6 ( Benitez, 2009 ; Dash et al., 2013 ). All this, therefore, underscores the urgency for climate action expressed in the Paris agreement of 2015. Even in a climate change context, using the KUM approach will help in a better diagnosis of the changes in regional implications for large-scale instabilities to diabatic processes. These can help in design model-based indices that can inform the stakeholders working on climate change mitigation and adaptation.

Recommendations

We are in an era in which observational data availability in the tropics has improved significantly and is going to be further improved. In this context, it is recommended that the forecasters and researchers of Indian weather and climate use this excellent opportunity to build theoretical knowledge unique to the regional weather and climate. The knowledge gained should be translated to identify tangible, large-scale dynamical process indices. Such indices will be very useful to extend the lead prediction skills of important weather and climate phenomenon, such as TCs, MDs, etc. Similarly, (i) evaluating the model capacity in predicting and calibration of association between hindcast perturbation PE, latent heating, and subsequent conversion to KE, and (ii) comparing the observations will potentially provide us with indices that can be directly used to predict subseasonal monsoonal rainfall with longer leads. The above recommendations are just examples. In summary, identifying the key dynamics behind important weather and climate processes at discernible time scales and designing useful dynamical indices that can be used to extend the lead forecast envelope will be the way forward.

Data Availability Statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: http://tropical.atmos.colostate.edu .

Author Contributions

VB conceived the idea. VB wrote the manuscript with inputs from KA and using the results from DG analysis. KA comprehensively revised the article. All authors contributed to the article and approved the submitted version.

The publication charge of this article is fully funded by the Frontiers in Climate Journal.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Acknowledgments

The authors thank Prof. Matthew Collins, Specialty Chief Editor, Frontiers in Climate Journal, and reviewers for their helpful feedback and recommendations in improving the manuscript quality. The authors are grateful to the Frontiers in Climate Journal Committee for waiving the article's publishing fees. We thank the reviewers for their critical comments, which helped to improve the quality of the article.

1. ^ World focus-special issue July 2014, editorial (peer-reviewed, refereed research journal).

2. ^ https://www.gfdl.noaa.gov/global-warming-and-hurricanes/

3. ^ https://www.bbc.com/news/world-asia-india-52749935

4. ^ https://en.wikipedia.org/wiki/2020_North_Indian_Ocean_cyclone_season

5. ^ https://mausam.imd.gov.in/Forecast/marquee_data/indian111.pdf

6. ^ https://unfccc.int/process-and-meetings/the-paris-agreement/the-paris-agreement

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Keywords: KUM method, extreme weather, human suffering, tropical cyclone, monsoon, Indian summer monsoon (ISM)

Citation: Brahmananda Rao V, Ashok K and Govardhan D (2021) Unprecedented Climate Change in India and a Three-Pronged Method for Reliable Weather and Climate Prediction. Front. Clim. 3:716507. doi: 10.3389/fclim.2021.716507

Received: 28 May 2021; Accepted: 04 October 2021; Published: 15 November 2021.

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*Correspondence: Vadlamudi Brahmananda Rao, raovadlamud@gmail.com orcid.org/0000-0001-5905-9806

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• Published: 28 April 2021

Resilience of vernacular and modernising dwellings in three climatic zones to climate change

• Khadeeja Henna 1 ,
• Aysha Saifudeen 1 , 2 &
• Monto Mani 1  

Scientific Reports volume  11 , Article number:  9172 ( 2021 ) Cite this article

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Climate change impacts buildings in multiple ways, including extreme weather events and thermal stresses. Rural India comprising 65% of the population is characterised by vernacular dwellings evolved over time to passively regulate and maintain comfortable indoors. Increasing modernization in rural habitations (transitions) evident from the ingress of modern materials and electro-mechanical appliances undermines the ability of building envelopes to passively regulate and maintain comfortable indoors. While such trends are deemed good for the economy, their underlying implications in terms of climate change have not been adequately examined. The current study evaluates the climate-resilience of vernacular dwellings and those undergoing transitions in response to three climate-change scenarios, viz, A1B (rapid economic growth fuelled by balanced use of energy sources), A2 (regionally sensitive economic development) and B1 (structured economic growth and adoption of clean and resource efficient technologies). The study examines dwellings characteristic to three rural settlements representing three major climate zones in India and involves both real-time monitoring and simulation-based investigation. The study is novel in investigating the impact of climate change on indoor thermal comfort in rural dwellings, adopting vernacular and modern materials. The study revealed higher resilience of vernacular dwellings in response to climate change.

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Introduction.

Climate change and its effect on human health, economy and environment is one of the most widely researched topics in the twenty-first century. Building and construction industry, the highest contributor to global emissions and climate change, is responsible for 39% of the global energy- and process-related emissions, with 17% from residential sector 1 . However, buildings are also the most vulnerable to climate change, especially in progressive and developing regions. Climate change could involve gradual/abrupt changes in temperatures to unprecedented rains, floods and cyclones. It impacts building thermal comfort, alters operating conditions and energy demands while rendering existing appliances inadequate 2 . This impact is evident as altered comfortable temperature conditions and increased heating/cooling energy demand. In 2018, 22% of the global final energy was consumed by residential buildings 1 , with 40% of energy utilization on space conditioning. This is projected to increase by 40% by 2050 over 2010 levels based on International Energy Agency’s (IEA) 6 ºC (6DS) scenario 3 . The energy consumed by buildings varies depending on the climate, lifestyle and building typology. Per capita energy consumed by buildings in prosperous countries in a cold climate zone like the United States or Canada, could be 5–10 times that of low-income countries in a warm climate zone in Africa or Latin America 4 . In 2018, India’s per capita residential energy consumption was less than 0.6 MWh while that of the US was over 10 MWh 5 . While 66% of India’s population resides in rural areas, only 18% of US population is rural 6 . However, unlike in westernised regions, the disparity in energy consumption between rural and urban India is huge (96 kWh in rural areas, 288 kWh in urban areas as in 2009) 7 . A 4 × increase in embodied energy (EE) and a 40 × increase in operational energy (OE) respectively has been observed with buildings transitioning from vernacular to modern 8 . If rural life in India rapidly transitions towards global urban lifestyles, the ecological stresses (resource extraction and greenhouse gas emissions) could exasperate global efforts to mitigate climate change. The national statistics indicate rapid transition from traditional climate-responsive houses constructed using locally available materials towards an urban-like dwellings adopting industry manufactured, energy-intensive materials, disregarding the local climate. In 2001, clay tiles roofs (32.5%) had given way to concrete (29%) by 2011 9 . A growth of 89% in the use of concrete and 76% increase in metal/asbestos roofing sheets has been witnessed between 2001 and 2011.

While vernacular dwellings have evolved to passively maintain comfortable indoors, modern dwellings inevitably rely on energy-intensive appliances for comfort. Modern buildings tend to be energy-intensive and result in huge emissions through their lifecycle. Residential energy consumption in India in 2014 was 50 times that in 1971 10 . Such increase could cripple global efforts to mitigate climate change. On the other hand, vernacular dwellings could hold key solutions for mitigation and adaptation to climate change, given their capability to withstand wider temperature variations with lower lifecycle energy-resource intensity 11 . This study attempts to assess the thermal performance of vernacular dwellings in three climate zones in India and the effect of material transitions on the thermal performance of these dwellings. The study also investigates the impact of climate change on their performance.

Literature review

The effect and severity of climate change on thermal comfort in dwellings can be measured as change in heating and/or cooling demand and resulting energy consumption. Severe cold climates are expected to witness reduction in heating demands, while warmer climates are expected to witness considerable increase in cooling demand 12 . The impact of climate change also varies according to building type. Wang and Chen 13 , studied impact of climate change on seven commercial buildings and two residential buildings in different climate zones across the US and found a net increase in energy consumption in warm and moderate climates while a net decrease in energy consumption in colder climates. Karimpour et al. 14 investigated the impact of different building envelope (insulation and glazing) configurations in mild Australian temperate climate on energy consumption in current and future climates and recommended higher insulation, double glazing and low emittance glass in response to increased cooling energy demand. Huang and Gurney 15 studied US building stock, focusing on commercial building types, across three building age classes- pre-1980, post-1980 and new-2004, to understand their performance under climate change. The buildings equipped with the newest technology with more energy efficient equipment and better insulation exhibited higher efficiency in maintaining comfortable indoor environment.

Naturally ventilated (NV) vernacular dwellings constructed using local materials have lower embodied energy and ecological footprint. Mani et al. 16 estimated the ecological footprint of conventional dwellings to be 2.5 times that of traditional dwellings in West Bengal, India. Vernacular buildings also tend to be resilient in wider range of temperatures in providing comfort when compared to conventional buildings 17 , 18 , 19 . Dili et al. 20 studied vernacular and conventional dwellings in Kerala, India, with warm-humid climate, and confirmed that vernacular dwellings outperformed conventional dwellings in maintaining indoor comfort across seasons. Shastry et al. 21 studied the impact of modern transitions on rural dwellings in West Bengal, India, and found an increase in average indoor temperatures from 7 to 10 °C. Given the lower EE and OE energy and higher resilience to maintain indoor thermal comfort in response to wider variations in weather conditions, vernacular dwellings could hold important insights for mitigation and adaptation to climate change.

Methodology

India is broadly classified into five climatic zones- hot-dry, warm-humid, composite, temperate and cold 22 . In this study, three distinct villages belonging to warm-humid, temperate and cold climate zones have been selected to represent warm, moderate and cold climatic conditions in India, respectively. A typical vernacular dwelling from each village was selected for detailed investigation into climate-resilience. Real-time indoor air temperatures at different locations in the dwellings were recorded at 30-min intervals using calibrated Resistance Temperature Detector (RTD) data loggers (0.05 °C resolution and ± 1 °C accuracy). Real-time measurement of indoor parameters proceeded according to Class III level of detail as defined in 23 , widely adopted in thermal comfort field study research. It was important to prevent the loggers from interfering with the daily lives of the inhabitants as these loggers were being installed in occupied houses for almost a year. Calibrated simulation models of the vernacular dwellings were developed using DesignBuilder (v 3.4), an integrated building performance simulation package 24 . The model calibration essentially involved a correlation with real-time climatic-performance data (see Sect.  4 ). In order to examine performance of vernacular dwellings in response to climate change, weather files for both typical and future climate scenarios were generated using Meteonorm . Meteonorm is a global climatological tool, that derives data from weather stations between 1991 and 2010 and integrates IPCC AR4 (Intergovernmental Panel on Climate Change- Fourth Assessment Report) emission scenarios 25 . Three future scenarios, namely, A1B (rapid economic growth fuelled by balanced fossil/non-fossil energy use), A2 (regionally oriented economic development characterised by less innovation) and B1 (structured economic growth and adoption of clean and resource efficient technologies) are explored in this paper. Both A1B and A2 are high emission scenarios, with A2 resulting in higher global surface warming in the second half of the twenty-first century. B1 on the other hand is one of the scenarios with lowest emissions and global surface warming 26 . Modern transitions in each of the habitations were studied based on trends revealed through satellite imagery, field visits and government reports, and were incorporated in the simulation models to examine the impact of future climate change scenarios.

This study comprises three agrarian rural settlements (Fig.  1 ) namely Suggenahalli, Karnataka (12.816° N, 76.993° E), Dasenahalli, Karnataka (13.146° N, 77.465° E) and Bisoi, Uttarakhand (30.971° N, 77.928° E) belonging to warm-humid, temperate and cold climate zones respectively. In addition to the willingness of the inhabitants, these settlements were identified for unique vernacular architecture (Table 1 ) and an evident trend of modern transitions. The vernacular dwellings in these villages are naturally ventilated and constructed using locally available materials with local traditional know-how passed over generations.

(Adapted from National Building Code of India, 2005 22 ) and selected rural settlements: Figure shows the location of the rural settlements studied in this paper on the climate zone map of India. Suggenahalli lies in Warm-humid zone, Dasenahalli in Temperate zone and Bisoi in Cold zone. The authors used Autodesk AutoCAD 2018 (Product version: O.49.0.0 AutoCAD 2018) https://www.autodesk.com/products/autocad/overview?support=ADVANCED&plc=ACDIST&term=1-YEAR&quantity=1 to draw the map and mark the rural settlements on it.

Climatic zones in India.

The proximity and improved connectivity of Suggenahalli and Dasenahalli to Bengaluru city and Bisoi to Dehradun has helped spur modern lifestyles. Access to electricity and modern construction materials is evident as transitions in the dwellings. These transitions that mimic urban habitations are characteristic to many rural habitation and involve traditional local materials giving way to energy-intensive exotic materials 8 , 27 , 28 .

Transitions in vernacular dwellings were characterised by progressive inclusion of modern materials, while retaining the original form. Newer constructions adopted modern construction materials, seldom carrying a semblance of traditional form and indoor spaces. In Suggenahalli (Fig.  2 a–c), the thick rubble walls were increasingly being replaced by slender brick masonry, the pitched clay-tile roofs were replaced by flat AC sheet roofing and then by reinforced cement concrete (RCC) slabs, and the cool earthen floors have made way to cement flooring. In Dasenahalli (Fig.  2 d–f), clay from the agricultural fields were moulded into mud blocks to construct walls. These walls were increasingly being replaced by cement blocks, pitched clay tiled roof by tin/AC sheets and ultimately by flat RCC roof and the mud flooring by cement and tiles. Bisoi, which once depended on forest-harvested timber for houses, is faced with state regulations restricting the use of forest produce. This also has forced villagers to look for alternate building materials, with the older generation preferring vernacular dwellings, and the younger city-educated/employed generation preferring conventional dwellings. The geographic isolation by mountain ranges has moderated the rate of transitions and helped in higher retention of vernacular dwellings. The transitions in Bisoi (Fig.  2 g–i) mostly involve replacing of timber walls on the first floor by brick walls while retaining the ground floor stone and timber wall construction, the slate roof by metal sheets and pitched RCC roof and mud/timber flooring by cement flooring. Flat RCC roofs originally constructed revealed cracks under heavy snow load and were eventually replaced by sloping RCC roof. In all the three villages, material transitions remained the most prominent and evident type of transition. The current study examines the primary material transition in vernacular dwellings retaining their form and orientation for their thermal performance and resilience to climate change. Table 2 summarises the vernacular and conventional building materials used in constructing the simulation models for the three case studies.

Stages of material transition (from left to right) in vernacular dwellings in the three villages: Stages of transition in the use of construction materials for each rural settlement is shown in the figure. Images in each row from left to right shows transition from traditional materials to conventional materials. ( a ), ( d ) and ( g ) represents the typical vernacular construction using traditional materials in Suggenahalli, Dasenahalli and Bisoi, respectively. ( b ), ( e ) and ( h ) represent a common intermediate stage in the process of transition using conventional but mostly temporary materials in the three villages. ( c ), ( f ) and ( i ) are the final products of transitions in the three villages using conventional factory-made materials which are more permanent in nature.

Studies focusing on naturally ventilated buildings rely on adaptive thermal comfort models to assess building climatic performance. These models more precisely accommodate the natural physiological ability to adapt indoor comfort requirements in response to external climatic (temperature) conditions. The performance of dwellings in this study adopts Adaptive Heating and Cooling Degree Days (AHDD and ACDD) calculated based on the Adaptive thermal comfort model (ATCM) incorporated in the ASHRAE 55 standard, 2010 29 . ATCM takes into account the acceptability of wider range of temperatures by occupants in naturally ventilated buildings, especially in tropical climates 30 . It illustrates a linear dependence of indoor operative temperatures on mean monthly outdoor temperatures and also describes a 90% and 80% acceptability limits indicating the percentage of occupants expressing comfort 31 . The days when indoor temperatures exceed acceptability limits, the corresponding ACDD and AHDD are computed as a measure of the augmented cooling or heating need (see Fig.  3 ):

Representation of ACDD and AHDD based on Adaptive Thermal comfort model, ASHRAE 55: The plot shown in the figure represents the Adaptive thermal comfort model defined in ASHRAE 55. Solid line indicates 80% acceptability limits and dotted line indicates 90% acceptability limits. Figure depicts the method adopted for calculating Adaptive Heating Degree Days (AHDD) and Adaptive Cooling Degree Days (ACDD). Indoor operative temperatures falling above or below the 80% acceptability limits multiplied by the duration for which the temperature lasts are used to calculate ACDD and AHDD, respectively. Duration for which the indoor operative temperatures fall above the 80% acceptability limit will require active cooling to attain comfort. Similarly, duration for which the indoor operative temperatures fall below the 80% acceptability limit will require active heating for comfort.

where \(T_{op.i}\) is the daily operative temperatures and \(T_{b.m}^{ul}\) and \(T_{b.m}^{ll}\) are the upper and lower limits of the monthly base temperature above and below which cooling and heating requirements surface. \(T_{b.m}^{ul}\) and \(T_{b.m}^{ll}\) are calculated based on ATCM for each month using the relation:

where T mm is the mean monthly outdoor temperature and x is the variability based on acceptability limit, which is 3.5 for 80% acceptability and 2.5 for 90% acceptability 31 , 32 .

Model calibration

ASHRAE Guideline 14 suggest use of Mean Bias Error (MBE) and Coefficient of Variation of Root Mean Square Error (CV RMSE) for calibration of simulation model based on measured performance data 33 , 34 , 35 . MBE and CV RMSE indicate the relative and accumulated divergences between measured and simulated value, respectively. According to the guideline, for an acceptable calibrated simulation model, MBE hourly data should lie within ± 10% and CV RMSE hourly data should not exceed 30%. For this study, the simulated indoor air temperatures were calibrated based on real time measurements. Royapoor and Roskilly 36 in their study on performance of an office building had validated their EnergyPlus virtual building model by calculating MBE and CV RMSE. For better reliability, ASHRAE recommends using both statistical and graphical approaches to model calibration 33 , 37 , which has been adopted in this study: firstly, by graphically comparing the measured and simulated indoor air temperatures, and secondly, by calculating the MBE and CV RMSE. Figure  4 illustrates the concurrence between measured and simulated weeklong summer and winter temperatures for the three case studies. Since summer data for Bisoi was not accessible, a warm week in October was relied on as representative for summer. A one-on-one match between real-time and simulated temperature is rarely feasible given the variability in the external climatic data between the simulation model and on-site conditions. Also, variations attributed to non-routine indoor occupancy are difficult to precisely predict and include in the simulation model 38 , 39 . This approach to calibration has been adopted for reliable building performance studies 36 , 37 , 39 , 40 . Figure  5 illustrates the MBE and CV RMSE for the three simulation models being well within recommended favourable limits for calibration. Moreover, the lower error values indicate improved reliability of the simulation results 33 , 35 . MBE and CV RMSE between measured and simulation data are calculated using Eqs. ( 5 ) and ( 6 ):

where m i and s i are measured and simulated data points for i th hour, \(\overline{m}\) is the average of measured data points and N is the total number of data points.

Comparison of simulated and measured temperature data for a representative week-long period in Summer and Winter for the dwellings studied in the three settlements: Figure shows comparison of measured and simulated hourly indoor air temperatures (in °C) for a representative week in winter and summer for the three dwellings to understand how the simulation model has been able to represent the actual indoor operating conditions prevailing in the dwellings. Solid blue line shows the real-time temperature measurements recorded by the loggers, while the dotted orange line shows the simulated data. The simulation models tend to closely imitate real-time operating conditions, suggesting that the models are representative enough to be used for studying the behaviour of the original dwellings.

MBE and CV RMSE between measured and simulated temperature data for the dwellings in the three settlements: Figure shows the Mean Bias Error (MBE) and Coefficient of Variation of Root Mean Square Error (CV RMSE) in percentage calculated between the measured and simulated indoor air temperature data for the dwellings studied in each of the three settlements. The blue coloured solid bar shows MBE, while orange coloured bar with diagonal stripes shows CV RMSE. Both MBE and CV RMSE for all the three settlements are within the limits prescribed by ASHRAE 14 guideline.

With regards to climate change scenarios, for both Dasenahalli and Suggenahalli, the likely outdoor temperatures are much higher than the prevalent trends for all the three scenarios, with a steady decadal increase (see Fig.  6 a, b, d and e). A1B witnesses the highest increase in temperature across the years while B1 had the lowest. Notably, increase in summer (March–May) temperatures are higher than increase in winter (December–February) temperatures. In Bisoi (Fig.  6 c and f), the prevalent mean monthly temperatures ranging from 6 to 22 °C narrowed to 8–21 °C in the future years, while also registering a decadal increase. Here, while future winter temperatures are likely to increase, summer temperatures are likely to decrease.

( a )–( c ) Mean monthly outdoor air temperatures for typical and A1B scenario for 2030, 2040 and 2050 and ( d ), ( e ) the range of daily outdoor air temperatures for the three settlements for typical scenario and all future scenarios: ( a ), ( b ) and ( c ) shows the mean monthly outdoor air temperature (in °C) for typical scenario and A1B scenario for the years 2030, 2040 and 2050 for the rural settlements Suggenahalli, Dasenahalli and Bisoi, respectively. The same is not shown for A2 and B1 scenarios but they show similar trend with increasing temperatures with each passing decade. ( d ), ( e ) and ( f ) show the range of outdoor air temperatures (in °C) for typical and all three scenarios for future years 2030, 2040 and 2050 for the rural settlements Suggenahalli, Dasenahalli and Bisoi, respectively. The temperatures tend to increase with each decade with the highest increase in A1B scenario and lowest in B1 scenario for both Suggenahalli and Dasenahalli. In case of Bisoi winters tend to get warmer than typical conditions while summers tend to get cooler than typical conditions. The decadal increase in temperature can be witnessed here as well.

Figure  7 shows daily indoor temperature distribution in the vernacular and conventional dwelling in both typical and future A1B climate scenario for the three cases. The graphs reveal the % days/year with an average daily temperature greater than the value on the abscissa. In the vernacular dwelling in Suggenahalli (Fig.  7 a), climate change tends to increase indoor temperatures in the future. When the indoor temperatures exceeded 30 °C for only 2% of days in a normal year, in 2030, 16% of the days revealed temperature above 30 °C. A similar trend can also be noted in the conventional dwelling (Fig.  7 b). In typical climate the indoor temperatures in conventional dwelling exceeded 30 °C for 24% of the days and 34 °C for 2% of the days. By 2030, indoor temperatures exceeded 30 °C for 34% of the days and 34 °C for 8% of the days. The persistence of higher temperatures in conventional dwelling shows the effect of material transitions. Dasenahalli (Fig.  7 c and d) also shows a similar trend, though the difference between vernacular and conventional dwelling is not as high. In typical climate, average daily indoor temperatures exceed 26 °C, 17% of the days in vernacular dwelling and 18% in conventional dwelling. Climate change does influence the thermal environment in the dwellings and tends to increase the daily indoor temperatures as is evident from the figure. The temperature in both the dwellings does not exceed 32 °C in any case. Bisoi (Fig.  7 e and f) recorded a wider temperature range from 8 to 28 °C. Even though there is a general increase in temperatures due to climate change, at higher temperatures the trend reverses. Future years does not witness an increase in higher temperatures compared to typical climate. The daily indoor temperature in both the dwellings does not exceed 28 °C. Bisoi being in cold climate zone, the concern should be on the persistence of lower temperatures. In vernacular dwelling, temperature falls below 16 °C, 24% of the time in typical climate while in 2030 A1B scenario it falls below 16 °C for 22% of the time. While in conventional dwelling, temperature falls below 16 °C, 13% of the time in typical climate while in 2030 A1B scenario it falls below 16 °C for 23% of the time. Transitions and climate change seem to maintain comfortable temperature range indoors.

Percentage of days above a daily temperature given on abscissa for vernacular and conventional dwelling in the three settlements for typical scenario and future years under A1B scenario: Each bar in the plot shows the percentage of days in a year for which the mean daily indoor air temperature (in °C) is greater than the corresponding temperature (in °C) given on the abscissa. The plot helps to understand the range of temperatures and extent to which those temperatures prevail inside a dwelling throughout the year. This is shown for typical scenario and future years for A1B scenario. ( a ) and ( b ) shows the same for vernacular and conventional dwelling in Suggenahalli, ( c ) and ( d ) for dwellings in Dasenahalli and ( e ) and ( f ) for dwellings in Bisoi. Higher temperatures tend to persist in the dwellings in future years compared to typical conditions especially for conventional dwelling in case of both Suggenahalli and Dasenahalli. This is more evident in Suggenahalli than Dasenahalli. In the case of Bisoi, the frequency of lower temperatures in higher in the future compared to typical conditions, while frequency of higher temperature is higher in typical conditions than future years.

In Fig.  8 , the daily operative temperatures for each dwelling in the three villages are plotted against mean monthly daily temperatures for typical climate and future years for A1B scenario. It also shows the 80% acceptability limits as prescribed by ASHRAE 55. This figure forms the basis for the calculation of ACDD and AHDD. The vernacular dwelling in Suggenahalli (Fig.  8 a) maintains an indoor operative temperature within the acceptability limits for most part of the year for typical climate but exceeds the upper limit for future years at higher outdoor temperatures. On the other hand, the conventional dwelling (Fig.  8 b) fails to maintain indoor temperatures within the acceptability limits for both typical as well as future years for large part of the year. This shows that transitions hugely impact the indoor operative conditions in the dwelling. In the case of Dasenahalli (Fig.  8 c and d), the indoor operative temperatures are maintained within the acceptability limits for both vernacular and conventional dwellings for typical climate and future years. In Bisoi (Fig.  8 e and f), for both the dwellings, the temperatures fall below the lower acceptability limit for a large part of the year for typical climate and future years.

Indoor operative temperature against mean monthly outdoor air temperature for vernacular and conventional dwellings in the three settlements in typical and future climate for A1B scenario: Each plot shows the daily indoor operative temperatures (in °C) inside the dwelling throughout a year plotted against mean outdoor air temperature (in °C) for the corresponding month. The two dotted lines shown in each figure indicates the 80% acceptability limits prescribed by ASHRAE 55 Adaptive thermal comfort model. The points lying within the 80% acceptability limit band are considered to be comfortable by at least 80% of the inhabitants, while those lying outside indicate thermal discomfort. Higher number of points lying outside the band indicate higher discomfort in the given dwelling. Comparing ( a ) and ( b ), conventional dwelling tends to be highly uncomfortable throughout the year for typical as well as future scenarios. Comparing ( c ) and ( d ), there is only marginal difference between vernacular and conventional dwelling in Dasenahalli. Comparing ( e ) and ( f ), though both vernacular and conventional dwelling tend to be uncomfortable at lower outdoor temperatures, vernacular dwelling seems to be warmer than conventional dwelling providing better comfort in cold weather.

As followed in the comparative evaluation of vernacular buildings under climate change, AHDD and ACDD were computed for the material transitions in dwellings under typical and future (A1B, A2 and B1) climate scenarios. The dwelling in Suggenahalli (Fig.  9 a–c), being in a warm-humid climate zone, do not require any heating throughout the year for all scenarios alike. For the vernacular dwelling, ACDD tend to be quite low in typical climate with small increase in future years. Both climate change and transitions tend to have a serious effect on thermal comfort inside the dwelling in warm-humid climate zone. When the building materials changed from vernacular to modern, ACDD increased from 4 to 246 in typical climate condition (4 to 167 in summer and 0 to 36 in winter). This high difference in degree days between vernacular and conventional dwelling is evident from Fig.  8 a and b shows that a large number of data points lie above the acceptability limit in conventional dwelling compared to vernacular dwelling. Climate change further increased ACDD in the future years with highest increase in A1B scenario and lowest in A2 scenario. Cooling requirement increases considerably due to climate change and transitions especially in summer. In the case of Dasenahalli (Fig.  9 d–f), both AHDD and ACDD are very low in both vernacular and conventional dwelling in typical climate. ACDD is zero in all future years while AHDD, though small, steadily increases in future years, especially for A1B scenario. Transition also affects the thermal comfort in the dwellings where transitions increased both ACDD and AHDD in typical climate, marking an increase in cooling as well as heating demand. In all future years across scenarios, transitions increase ACDD in the dwelling. In Dasenahalli, ACDD and AHDD are not severe enough to require cooling or heating appliances. Bisoi (Fig.  9 g–i) being in cold climate zone, does not require cooling throughout the year for both typical as well as future climatic conditions. The warming climate in Bisoi tend to decrease heating demand in the dwelling in both vernacular and conventional dwelling. Transitions have an adverse effect on the thermal comfort in the dwelling as it increases heating demand in the dwelling by an average of 25% compared to the vernacular dwelling in winter. This shows the effectiveness of insulation provided by the timber walls and the timber and slate roofing in vernacular dwelling over conventional materials.

All year, summer and winter AHDD and ACDD for the dwellings in the three villages for typical and future climate scenarios: Each plot depicts the Adaptive heating degree days (AHDD) and Adaptive cooling degree days (ACDD) calculated for vernacular and conventional dwelling for typical scenario and future years 2030, 2040 and 2050 for A1B, A2 and B1 scenarios. Plots from left to right shows typical and future ACDD and AHDD calculated for the entire year, for summer and winter for each rural settlement for both vernacular and conventional dwelling. From ( a ), ( b ) and ( c ) conventional dwelling in Suggenahalli tend to demand active cooling for most part of the year compared to vernacular dwelling. In case of Dasenahalli ( d ), ( e ) and ( f ), it can be seen that demand for heating or cooling is fairly low, cooling demand is slightly higher in conventional dwelling. From ( g ), ( h ) and ( i ), heating demand is high in both dwellings in Bisoi, especially in winter, with heating demand higher in conventional dwelling than vernacular dwelling.

The study investigated the effect of climate change and material transitions (replacing local traditional materials with conventional materials) on vernacular dwellings in three villages in India across three different climate zones. The impact of climate change on the dwellings were examined for the years 2030, 2040 and 2050 under the IPCC SRES scenarios A1B, A2 and B1 and compared with typical climate which is an average of 20 years of recorded weather data. In both Suggenahalli and Dasenahalli, climate change increased the outdoor temperatures throughout the year affecting the indoor environment as well. The effect of climate change was more pronounced in the case of Suggenahalli located in warm-humid climate zone, making the indoors warmer than the typical, climate demanding the use of cooling appliances. Due to climate change, winter outdoor temperatures increased while summer temperatures decreased in Bisoi. Summer temperatures can be expected to increase further in the second half of the century. Climate change has helped increase indoor temperatures which reduced heating demand in the dwellings. In warm climates, A1B scenario had the worst impact on the weather and the indoor temperatures, while B1 scenario which was a low emission scenario had comparatively lower impact on the temperatures. On the other hand, in cold climates A1B helped reduce the heating demand much better than A2 and B1 scenarios.

For both Suggenahalli and Dasenahalli, the vernacular dwelling maintained comfortable indoor operating conditions for most part of the year. The conventional dwelling in Dasenahalli also was able to maintain comfortable indoor conditions. Transitions in Suggenahalli led to warmer indoor environment pushing it beyond the acceptability limits. In case of Bisoi, indoor temperatures fall below acceptability limit for both vernacular and conventional dwelling. The thermal insulation provided by the traditional materials in the vernacular dwelling helped it to perform better than the conventional dwelling in maintaining warmer indoors. Vernacular dwellings seem to perform better than the conventional dwellings in all the three cases for typical as well as future climate. Conventional dwelling that replaced the traditional materials with modern materials failed to adequately respond to changes in climate, compromising indoor thermal comfort and necessitating dependence on active space conditioning.

Modern material transitions in dwellings compromised the thermal comfort in the dwellings across all climate zones, though the effect was not severe in Temperate climate as it was in Warm-humid and  Cold climates. Climate change further exasperated the thermal comfort in dwellings in warm climates but seemed favourable in cold climates. The study helps to verify the climate-resilience of vernacular dwellings to perform in the context of much imminent climate change and shows that modern dwellings constructed using modern industry manufactured materials, to meet the modern aspirations of inhabitants may not perform in the event of climate change. This confirms the need for reinterpretation in design of houses that meet the modern aspirations of the people and perform in the future climate scenarios. The study indicates that vernacular dwellings hold key answers in the direction of mitigation and adaptation strategies in response to climate change and advocates designers to understand the present and future climatic conditions and future demands in the local context, to appreciate and scientifically validate traditional wisdom while designing buildings for the future. Designers must ensure that the dwellings they construct not only meet the aspirations of the modern inhabitant but also perform under future climatic pressures.

Limitations of the study and scope for future work

A country like India is home to diverse vernacular architecture which varies with climate, culture, customs, and available resources. This paper studies three rural settlements with unique vernacular architecture and evident transitions in three different climate zones in India. The authors have selected the settlements such that the vernacular architecture is representative of the climate zone they are in. Inclusion of more case studies and other climate zones would increase the scope of the paper and present a better estimate on the nature of transitions and their ramifications on resource and energy requirement and vulnerabilities to climate change. The current study is a step in this direction and is also a methodological contribution for such studies, tested for three diverse settlements. The selection of settlements for the study was difficult as it required a combination of both vernacular and modern dwellings and those that are in transition. Overcoming scepticism of villagers and gaining their trust was an important requirement to ensure the corporation of the villagers as the study extended for more than a year in each of the villages. Extending this study to cover the diversity of habitations in India, would require networking with local academic institutions, a larger group and a longer time to identify appropriate interventions/mitigation measures in response to climate change.

Understanding the contribution of each stage of transition on the thermal performance of the dwelling is also important to identify critical stages of transition and adopt preventive or adaptive strategies to improve thermal comfort in the dwelling without compromising the requirements of the inhabitants. Future work will involve investigation of individual stages of transitions and their effects on thermal comfort in the dwelling to assess the contribution of each transition on the performance of the dwellings. The study could subsequently evolve into regional building codes and recommendations for interventions in response to climate change, and the revalidation of vernacular building typologies for their relevance in the modern world. Further, the study could promote dependence on local decentralized circular economies that rely on local resources and skill, thereby lowering the global carbon footprint.

The current study is limited to understanding the thermal performance of the dwellings to changing climate. Studies have reported increased discomfort among occupants due to transitions 20 , 21 as well as climate change 2 . The response of the occupants to changing climate and performance of dwellings should shed light on possible adaptation strategies since rural population tend to be proactive in responding to change. Research reveals increased dependence on electro-mechanical equipment for thermal comfort, clothing adjustments and window operation as some of the major adaptation strategies 41 , 42 . Future work should aim to explore adaptation and mitigation strategies adopted in form, materials, or surface treatments in the dwelling elements and in clothing, window operation and use of spaces by the occupants.

However, understanding how people are going to change as climate warms, would involve intergenerational attitude and physiological studies, as current forecasts rely on thermal comfort responses valid for the current (adult) generation. Attitude is a critical determinant of sustainablity in human settlements and determines how the built environment evolves, with forcasting models relying on current generation attitudes 45 . In 2050, the present-day infants and youth would be the adults responsible for affecting changes or responses to climate change vulnerabilities. Given the diversity in ethnicity and other physiological differences, such studies on human exposure to climatic variations are extremely challenging in providing the causal basis required for forecasting 43 , 44 .

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Acknowledgements

We thank the Centre for Sustainable Technologies, Indian Institute of Science for providing the unwavering academic support and freedom to purse this valuable research. The current work has relied on and continued the sustained research by our SuDesi (Sustainability and Design) Lab in studying diverse building typologies. Thanks also to the SPARC (Scheme for Promotion of Academic and Research Collaboration) initiative, which has been instrumental in our access to the dwellings in Bisoi.

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K.H., A.S., M.M., All authors were part of the conception of the paper, data collection, and real-time monitoring of the houses. K.H. and A.S. built the simulation models. K.H. performed the simulation, calibration, and analysis. K.H. wrote the main manuscript and prepared the figures and tables. M.M. further edited the manuscript. All authors reviewed the manuscript.

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Henna, K., Saifudeen, A. & Mani, M. Resilience of vernacular and modernising dwellings in three climatic zones to climate change. Sci Rep 11 , 9172 (2021). https://doi.org/10.1038/s41598-021-87772-0

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The costs of climate change in india: a review of the climate-related risks facing india, and their economic and social costs.

Literature review

Written by Angela Picciariello, Sarah Colenbrander, Rathin Roy

India is already feeling the impacts of climate change. Heatwaves are becoming more common and severe; heavy rain events have increased threefold since 1950; and rising sea levels are posing new risks as a third of India’s population live along the coast. Low-income and other marginalised groups are most vulnerable to these hazards.

This literature review finds that the economic costs of climate impacts in India are already immense. In 2020, a single event – Cyclone Amphan – affected 13 million people and caused over $13 billion in damage after it made landfall. One study suggests that declining agricultural productivity and rising cereal prices could increase India’s national poverty rate by 3.5% by 2040 compared to a zero-warming scenario; this equates to around 50 million more poor people that year.

Lower-carbon development could yield immediate benefits such as cleaner air, greater energy security and rapid job creation. India’s climate targets are considered to be ‘2°C compatible’, i.e. a fair share of global effort. However, pursuing a cleaner, more resource-efficient path could stimulate a faster, fairer economic recovery and secure India’s prosperity and competitiveness in the long term.

Authors: Angela Picciariello, Sarah Colenbrander, Amir Bazaz and Rathin Roy

Angela Picciariello

Sarah Colenbrander

Director, Climate and Sustainability programme

Visiting Senior Fellow

Will India get too hot to work?

While India is managing the COVID-19 pandemic, it cannot lose sight of climate risk, which is rising. The coronavirus crisis holds profound lessons that can help us address climate risk — if we make greater economic and environmental resiliency core to our planning for the recovery ahead. Indeed, economic stimulus  in the wake of the pandemic can help restore growth, while also addressing climate risk.

India faces a rapidly changing and degrading physical environment. The challenges of water scarcity and air pollution are well known. Less well appreciated is the impact extreme heat and humidity will likely have on the economy and the toll it could take on human life. In this case study we analyze the direct impact of climate change-driven heat and humidity extremes on India.

We first analyze the “inherent risk,” absent adaptation and mitigation, to assess the magnitude of the challenge and highlight the case for action. We assess inherent risk over the next decade, and then examine the evolution of that risk through to 2050. To assess inherent risk, we relied on the RCP 8.5 scenario (see sidebar, “ An overview of the case study analysis ” ).

An overview of the case study analysis

In Climate risk and response: Physical hazards and socioeconomic impacts , we measured the impact of climate change by the extent to which it could affect human beings, human-made physical assets, and the natural world. We explored risks today and over the next three decades and examined specific cases to understand the mechanisms through which climate change leads to increased socioeconomic risk.

In order to link physical climate risk to socioeconomic impact, we investigated cases that illustrated exposure to climate change extremes and proximity to physical thresholds. These cover a range of sectors and geographies and provide the basis of a “micro-to-macro” approach that is a characteristic of McKinsey Global Institute research. To inform our selection of cases, we considered over 30 potential combinations of climate hazards, sectors, and geographies based on a review of the literature and expert interviews on the potential direct impacts of physical climate hazards. We found these hazards affect five different key socioeconomic systems: livability and workability, food systems, physical assets, infrastructure services, and natural capital.

We ultimately chose nine cases to reflect these systems and to represent leading-edge examples of climate change risk. Each case is specific to a geography and an exposed system, and thus is not representative of an “average” environment or level of risk across the world. Our cases show that the direct risk from climate hazards is determined by the severity of the hazard and its likelihood, the exposure of various “stocks” of capital (people, physical capital, and natural capital) to these hazards, and the resilience of these stocks to the hazards (for example, the ability of physical assets to withstand flooding). We typically define the climate state today as the average conditions between 1998 and 2017, in 2030 as the average between 2021 and 2040, and in 2050 between 2041 and 2060. Through our case studies, we also assess the knock-on effects that could occur, for example to downstream sectors or consumers. We primarily rely on past examples and empirical estimates for this assessment of knock-on effects, which is likely not exhaustive given the complexities associated with socioeconomic systems. Through this “micro” approach, we offer decision makers a methodology by which to assess direct physical climate risk, its characteristics, and its potential knock-on impacts.

Climate science makes extensive use of scenarios ranging from lower (Representative Concentration Pathway 2.6) to higher (RCP 8.5) CO2 concentrations. We have chosen to focus on RCP 8.5, because the higher-emission scenario it portrays enables us to assess physical risk in the absence of further decarbonization. (We also choose a sea level rise scenario for one of our cases that is consistent with the RCP 8.5 trajectory). Such an "inherent risk" assessment allows us to understand the magnitude of the challenge and highlight the case for action. For a detailed description of the reason for this choice, see the technical appendix of the full report.

Our case studies cover each of the five systems we assess to be directly affected by physical climate risk, across geographies and sectors. While climate change will have an economic impact across many sectors, our cases highlight the impact on construction, agriculture, finance, fishing, tourism, manufacturing, real estate, and a range of infrastructure-based sectors. The cases include the following:

• For livability and workability, we look at the risk of exposure to extreme heat and humidity in India and what that could mean for that country’s urban population and outdoor-based sectors, as well as at the changing Mediterranean climate and how that could affect sectors such as wine and tourism.
• For food systems, we focus on the likelihood of a multiple-breadbasket failure affecting wheat, corn, rice, and soy, as well as, specifically in Africa, the impact on wheat and coffee production in Ethiopia and cotton and corn production in Mozambique.
• For physical assets, we look at the potential impact of storm surge and tidal flooding on Florida real estate and the extent to which global supply chains, including for semiconductors and rare earths, could be vulnerable to the changing climate.
• For infrastructure services, we examine 17 types of infrastructure assets, including the potential impact on coastal cities such as Bristol in England and Ho Chi Minh City in Vietnam.
• Finally, for natural capital, we examine the potential impacts of glacial melt and runoff in the Hindu Kush region of the Himalayas; what ocean warming and acidification could mean for global fishing and the people whose livelihoods depend on it; as well as potential disturbance to forests, which cover nearly one-third of the world’s land and are key to the way of life for 2.4 billion people.

We find that India could become one of the first places in the world to experience heat waves that cross the survivability limit for a healthy human being resting in the shade, and this could occur as early as next decade. Moreover, rising heat and humidity levels will impact labor productivity and economic growth in an economy that relies substantially on outdoor work.

How big is the threat of extreme heat and humidity in India?

While the hottest air temperatures ever recorded have been in places like Saudi Arabia, the Sahara Desert, and Death Valley, California, in the United States, the north of India has historically exhibited some of the world’s hottest wet-bulb temperatures. Wet-bulb temperature is an indicator that combines air temperature and relative humidity and provides a more accurate measure of heat stress on the human body than air temperature alone (see sidebar, “ Understanding wet-bulb temperatures ” ).  According to the scientific literature , 35 degrees wet-bulb temperature is commonly regarded as the heat-stress limit for human survival. At 35°C wet-bulb a healthy human being can survive, resting in the shade, for approximately five hours.

Understanding wet-bulb temperatures

High wet-bulb temperatures, a function of both air temperature and relative humidity, are more dangerous to human beings than extreme air temperatures . Wet-bulb temperature is technically defined as the minimum temperature to which a parcel of air can be cooled by evaporation at a constant pressure. Human beings are able to acclimatize to extreme temperatures by increasing the volume of sweat that their bodies process. With the introduction of humidity, however, the ability of air to hold additional water decreases, and the evaporation of sweat becomes more difficult, making heat stress harder to bear. At a wet-bulb temperature of 35 degrees, healthy, well-hydrated human beings resting in the shade would see core temperatures rise to lethal levels after roughly four to five hours of exposure. Any introduction of direct sunlight, activity, or dehydration would shorten this period. In order to better conceptualize this threshold, 35-degree wet-bulb temperature can be roughly defined as a convex line on a temperature/humidity axis, running between 35-degree air temperature with 100 percent relative humidity, and 50-degree air temperature with 40 percent relative humidity.

While wet-bulb temperatures during the worst heat waves in India today rarely, if ever, exceed 32 degrees, the climatological analysis conducted for this case study indicates that temperatures during the most severe heat waves in the hottest parts of India could begin to breach 34 degrees wet-bulb by 2030. Such high temperatures have been recorded only a couple of times on Earth , including a 34.6-degree wet-bulb measurement on the coast of the Persian Gulf in July of 2015, and a later 35.4-degree wet-bulb measurement in the same region. Exposure to 34-degree wet-bulb temperatures will increase mortality risk for the sick and elderly, but more importantly, due to the amplifying urban heat-island effect which can raise temperatures in urban areas, for example, due to the presence of concrete buildings and limited green spaces, urban or peri-urban centers exposed to these temperatures may cross the 35-degree survivability threshold for healthy adults. By 2050, portions of northern India could begin to experience heat waves that cross the 35-degree wet-bulb survivability with a probability of occurrence at least once in the decade centered on 2050 approaching 80 percent (Exhibit 1). As heat and humidity increase, this could also affect labor productivity in outdoor work. This phenomenon occurs not only due to the need to take breaks to avoid dangerous core temperature rise, but also because the body will fatigue to reduce the amount of work (and therefore heat) that it is able to produce.

Millions of lives and billions of dollars are at risk.

Based on a district-by-district geospatial analysis of population urbanicity, we estimate that, under our “inherent risk” scenario, 160–200 million people could be living in urban areas in India with a non-zero annual probability of experiencing a lethal heatwave as soon as 2030. Today, air conditioner penetration in India is about 10 percent. Under business as usual air conditioning growth, only about half will have protection from air conditioning. The average annual probability of a lethal heatwave in those regions is projected to be about 5 percent, meaning the probability of at least one heatwave occurring during the decade centered around 2030 could be about 40 percent. By 2050, the number of people living in at-risk regions will increase to 310–480 million. If historical growth rates continue, it is expected that most people in India will own an air conditioning unit by 2050, and so will have a degree of protection against this risk. It is important that ways to reduce air conditioner carbon footprint are identified in the near term, to prevent large-scale air conditioner growth from exacerbating underlying climate risk.

Climate risk and response

Another consequence of chronic exposure to extreme heat is a rapid decrease in the capacity for outdoor work. We estimate that the number of daylight hours during which outdoor work is unsafe will increase approximately 15 percent by 2030, compared with today’s levels (Exhibit 2).

This is significant because India’s economy is highly dependent on heat-exposed labor. As of 2017, heat-exposed work produces about 50 percent of GDP, drives about 30 percent of GDP growth, and employs about 75 percent of the labor force, some 380 million people. Based on a geospatial, district-by-district analysis of exposed GDP and projected lost working hours, as well as considering effects on other sectors that exchange inputs and outputs with sectors exposed to outdoor heat and the expected transition out of outdoor work over time, we calculate that lost labor hours due to increasing heat and humidity could put approximately 2.5–4.5 percent of GDP at risk by 2030, equivalent to roughly $150–250 billion.

What would it take to reduce the risk from extreme heat and humidity in India?

Given the inherent risk of rising wet-bulb temperatures, adaptation is likely to happen in India but may need to be accelerated. For example, by shifting working hours for outdoor workers, undertaking albedo heat management efforts in cities, establishing early-warning systems and cooling shelters to protect people, and also considering movement of people and capital from high-risk areas. Investing in heat management will be critical, and stakeholders will also need to consider approaches to accelerate the transition out of outdoor work already underway.

Adaptation in general will be challenging because heat is a pervasive risk and involves fundamental changes in how people conduct their daily lives (for example, shifting work hours may entail potential cultural and economic difficulties). Adaptation will be particularly challenging for the urban poor, who will likely require public support, for example in the form of emergency shelters.

We calculate that addressing the risk of lethal heat waves by 2030, using air-conditioning, could come with capital costs of up to $110 billion. Both public- and private-sector stakeholders have an important role to play in developing and delivering the necessary technological and regulatory solutions.

For additional details, download the case study, Will India get too hot to work?  (PDF–2MB).

About this case study:

In January 2020, the McKinsey Global Institute published Climate risk and response: Physical hazards and socioeconomic impacts . In that report, we measured the impact of climate change by the extent to which it could affect human beings, human-made physical assets, and the natural world over the next three decades. In order to link physical climate risk to socioeconomic impact, we investigated nine specific cases that illustrated exposure to climate change extremes and proximity to physical thresholds.

Lola Woetzel is a director of the McKinsey Global Institute, where Mekala Krishnan is a senior fellow. Dickon Pinner is a senior partner in McKinsey’s San Francisco office. Hamid Samandari is a senior partner in the New York office. Rajat Gupta is a senior partner in the Mumbai office.  Hauke Engel is a partner in the Frankfurt office. Carter Powis is a consultant in the Toronto office.

This article was edited by Lauren Meling, a digital editor in the Washington, DC, office.

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Research Article

Lethal heatwaves are challenging India’s sustainable development

Roles Conceptualization, Formal analysis, Funding acquisition, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing

* E-mail: [email protected]

Affiliations Cambridge Zero, University of Cambridge, Cambridge, United Kingdom, Division of Humanities and Social Science, California Institute of Technology, Pasadena, CA, United States of America

Roles Conceptualization, Formal analysis, Funding acquisition, Project administration, Visualization, Writing – original draft, Writing – review & editing

Affiliation Department of Architecture, University of Cambridge, Cambridge, United Kingdom

Roles Conceptualization, Validation, Writing – original draft, Writing – review & editing

Affiliation School of the Environment, Yale University, New Haven, CT, United States of America

• Ramit Debnath, 
• Ronita Bardhan, 
• Michelle L. Bell

• Published: April 19, 2023
• https://doi.org/10.1371/journal.pclm.0000156
• Peer Review
• Reader Comments

Due to the unprecedented burdens on public health, agriculture, and other socio-economic and cultural systems, climate change-induced heatwaves in India can hinder or reverse the country’s progress in fulfilling the sustainable development goals (SDGs). Moreover, the Indian government’s reliance on its Climate Vulnerability Index (CVI), which may underestimate the impact of heatwaves on the country’s developmental efforts. An analytical evaluation of heat index (HI) with CVI shows that more than 90% of the country is at extremely cautious or dangerous levels of adversely impacting adaptive livelihood capacity, food grains yield, vector-borne disease spread and urban sustainability. The results also show by examining Delhi’s urban heat risk that heatwaves will critically hamper SDG progress at the urban scale. Linking HI with CVI identifies more of India’s vulnerability and provides an opportunity to rethink India’s climate adaptation policies through international cooperation in designing holistic vulnerability assessment methodologies. The conclusion emphasizes the urgent need to improve extreme weather impact assessment by combining multiple layers of information within the existing climate vulnerability measurement frameworks that can account for the co-occurrence and collision of climate change events and non-climate structural SDG interventions.

Citation: Debnath R, Bardhan R, Bell ML (2023) Lethal heatwaves are challenging India’s sustainable development. PLOS Clim 2(4): e0000156. https://doi.org/10.1371/journal.pclm.0000156

Editor: Bidhubhusan Mahapatra, Norwegian Refugee Council, JORDAN

Received: September 1, 2022; Accepted: March 12, 2023; Published: April 19, 2023

Copyright: © 2023 Debnath et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The materials and data used in this paper are based on the Government of India's public repository, available at the National Data \& Analytics Platform (NDAP) { https://ndap.niti.gov.in/ }.

Funding: This work was supported by the Bill and Melinda Gates Foundation (OPP1144 to RD), Laudes Foundation (G111269 to RD), the Quadrature Climate Foundation (01-21-000149 to RD), Keynes Fund, Faculty of Economics (JHVH to RD and RB), and the Africa Albarado Grant (G115009 to RB). RD received salary from the Quadrature Climate Foundation, the Laudes Foundation, and the Keynes Fund. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

April 2022 in India was the hottest in 122 years and followed the hottest March on record, reportedly killing at least 25 people [ 1 , 2 ]. The cumulative heatwave-related mortality in India is over 24,000 deaths since 1992 [ 3 ]. Moreover, the heatwave in the Indian subcontinent has had critical impacts on a broad range of interconnected systems of the built environment, health, etc., including frequent and more extended power outages, an increase in dust and ozone levels leading to spikes in air pollution and accelerated melting of glacier snow in the northern regions. At the same time, economic recovery from the Covid-19 pandemic is further hampering the response to the ongoing lethal heatwave [ 2 , 4 ]. Thus, such heatwaves’ public health and economic burdens are incredibly high.

Long-term projections indicate that Indian heatwaves could cross the survivability limit for a healthy human resting in the shade by 2050 [ 5 , 6 ]. Moreover, they will impact the labour productivity, economic growth, and quality of life of around 310–480 million people [ 6 ]. Estimates show a 15% decrease in outdoor working capacity (i.e., working outdoors in high temperatures, e.g., construction worker) during daylight hours due to extreme heat by 2050 [ 5 ]. Furthermore, a Lancet Report projected heatwaves will intensify from these 2050 baseline estimates, affecting around 600 million Indians by 2100 [ 7 ]. The increased heat is expected to cost India 2.8%, and 8.7% of its Gross Domestic Product (GDP) and depressed living standards by 2050 and 2100, respectively [ 5 , 8 ]. Furthermore, a recent report by the World Meteorological Organization demonstrated the interconnections between lethal heatwaves and the Sustainable Development Goals (SDGs), implying that global mean surface temperature rise will affect all the 17 SDGs [ 9 ]. The impact of heatwaves on sustainability transition is especially concerning for India as the country is yet to achieve its developmental goals, despite recent strides in its self-reported SDG India Index (2020–21) [ 10 ].

India is currently facing a collision of multiple cumulative climate hazards co-occurring due to its size, urbanisation rate, and biophysical characteristics, significantly influencing the hydrological cycle and consequently affecting the behaviour of climate extremes [ 11 ]. In 2022 from January to October, India recorded 242 of 273 days of extreme weather events, making it nearly one extreme event daily. These include co-occurrence of extreme heatwaves and coldwaves in the north and western parts, drought in central India [ 12 ], and high flooding in the coastal plains along with landslides in north-eastern region [ 12 , 13 ]. By 2100 India will have more frequent precipitation and consequent floods, cyclonic storms, warming, heatwaves, and sea-level rise concurrently. To comprehensively understand India’s climate vulnerability, a cumulative representative index is imperative that accounts for the co-occurrence and collision of climate events. At present, India assesses its climate vulnerability through a national Climate Vulnerability Index (CVI), designed by the federal government’s Department of Science and Technology [ 14 ], based on the Intergovernmental Panel on Climate Change (IPCC)’s SREX framework. The concept of vulnerability used by the Government of India is adopted from the IPCC AR5 [ 15 ] where it is conceptualised as an ‘internal property of a system’ that represents the propensity or predisposition of the system to be adversely affected, independent of hazard and exposure [ 15 ]. The CVI is a composite index that uses various indicators to account for India’s socio-economic features and livelihood, biophysical, institutional and infrastructural characteristics (see Table 2, pp. 11–12 in [ 14 ]). These indicators were further mapped to related SDG indicators [ 16 ], as presented in Table 1 . The mapping of the CVI indicators with the SDG was performed based on (i) key domain of impact, (ii) keywords that match the SDG, and (iii) based on the Government of India’s SDG indicators. When all these criteria matched for a CVI indicator, it was assigned to the specific SDG. For example indicator–“Percentage of households below the poverty line as of 2011” is related to reducing poverty or SDG1- No Poverty.

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While there are few methodological and sensitivity analyses for CVI [ 17 – 19 ], it is the only official federal measure available for the country’s climate adaptation planning [ 14 ]. Therefore, we use it to analyse how lethal waves can challenge the progress in the nation’s SDGs and the implications of heatwave impacts on India’s climate vulnerability assessments—at the same time, examining the missed opportunity of not having heat-related policy measures in its current CVI-led assessment.

There is a knowledge gap in the literature evaluating the appropriateness of CVI as a holistic vulnerability measure [ 17 – 19 ]. Contributing to this measurement gap, Edmonds, Lovell and Lovell [ 20 ] proposed a multiple climate vulnerability index to make it a comprehensive measure for empirically estimating the exposure, mitigation and adaptive capacity [ 20 ]. However, the authors did not mention how such an index-based measure can be used as an effective decision-making tool to ensure that progress in SDGs is not reversed. This gap is persistent in the current literature as climate vulnerability indices like India’s CVI use socio-economic indicators to measure vulnerability, which links it with SDG indicators. Whereas, in the case of extreme weather events, the measures are primarily based on hazard probabilities (like the Heat Index (HI). Using these measures as overlapping information layers can improve the overall climate vulnerability assessment. This shapes the paper’s motivation, which is not to compare CVI and HI for India, but instead to provide an empirical basis for evaluating and rethinking India’s approach to vulnerability measurement, especially when the impact of an extreme weather event like heatwaves challenges its development goals and climate adaptation policies [ 3 ].

This paper uniquely contributes to the above gap by examining the following questions: (1) What does India’s current climate vulnerability assessment miss in terms of identifying the vulnerability caused by the heatwaves? (2) To what extent is SDG progress impacted by the absence of a holistic vulnerability measurement? Furthermore, (3) How to co-design policies for improving climate vulnerability assessment in India?

Using the 2022 heatwaves across India as a case study, this paper analyses its vulnerability impact using Heat Index (HI). It discusses this impact assessment with the latest CVI-led SDG ranking across the Indian states and the national capital using publicly available federal data (see Methods section).

This study is designed in two stages to demonstrate that a holistic climate measurement is important across different spatial scales for India. Here, we set the scope of study at a state level and an urban scale. Due to a lack of data, we could not evaluate a more granular scale (like at the district level). The first stage analyses CVI in the country using the latest publicly available government data. The next step estimates the HI and temperature anomaly across India for April 2022. It performs a normative heatwave impact assessment on India’s SDG progress. In the second stage, a scaled-down analysis was performed at an urban scale for Delhi to evaluate its HI and assess its impact on the national capital’s urban sustainability. This was done as a case study to show the severity of heatwaves at an urban scale, especially emphasising the need for contextualised heatwave impact studies.

The case of Delhi is interesting because it is the largest city and the capital of India, with a population of 32,065,760 [ 21 ], which is at high risk from heatwaves [ 22 ] and was the first to draft a State Action Plan on Climate Change (SAPCC). The SAPCC was recently updated with 17 climate risks (see Methods ), including urban heat islands but without considering heatwaves. This paper argues that such state-level vulnerability assessment methodology can be improved by considering the heatwave impacts and upgrading its climate adaptation policies. Finally, broader implications were drawn from international efforts on heatwave adaptation at the national climate vulnerability scale and shaped the discussion on the urgency of similar policy action for India and its neighbouring nations.

Materials and methods

State-level cvi and hi estimation.

This paper used a publicly available dataset on state-level climate vulnerability indicators from the Indian Government’s National Data & Analytics Platform (NDAP) [ 23 ]. The first step was to reference this data with the National Climate Vulnerability Assessment Framework by the Department of Science and Technology [ 14 ] to classify the severity categories (Low, Moderate and High). Then, India’s 2019 Climate Vulnerability Index (CVI) map was constructed using this dataset. In subsequent steps, we evaluated the Heat Index (HI) for April 2022 for India at a state level. Here we assume that exposure to a hazard like extreme heat (measured through HI) can significantly impact climate vulnerability. This impact measurement is currently missing in the Indian Government’s vulnerability assessment through CVI.

HI measures how hot it feels when relative humidity is factored in with actual air temperature. It is a widely used heat exposure metric in environmental health research [ 24 ]. A similar approach was used for estimating district-level HI for Delhi to understand the effects of urbanisation on heat risks [ 25 ].

The T and R values were extracted from publicly available Indian Meteorological Department (IMD) April 2022 temperature profiles [ 27 ]. The temperature anomaly data for the same month was obtained from the IMD. The Sustainable Development Goal (SDG) interconnection with CVI is established as per the ‘indicator rationale’ presented in Table 2 (pages 11–12) of [ 14 ] and Government of India’s SDG Index Dashboard 2020–21 [ 16 ]. The CVI indicators were mapped to the corresponding UN SDG. The resultant value of the indicator was then plotted using the colour of the SDG, where the colour gradient represents the rank of the CVI. Thus, the higher the value of an indicator, the deeper the colour of the box. For example, a deeper colour gradient was used if a CVI indicator conforms to a particular SDG and has a high value for a specific state. The colour was related to the corresponding SDG to which the indicator belonged. CVI and HI spatial maps representing the state-wise severity levels were constructed through spatial analysis in ArcGIS v10.8.1. The GIS shapefiles were adapted from open repositories like github, respective licenses are mentioned in Figs 1 and 4 .

(A) CVI illustrated as Low, Moderate and High levels across states.; (B) Estimated heatwave impact (HI) in April 2022 using data from the India Meteorological Department (IMD) (data source: [ 27 ]). (C) Temperature anomaly caused in India due to heatwaves in April 2022, estimated using the IMD data (source: [ 27 ]) [Note: Due to lack of data, the Union Territories of India (except 30.Ladakh) are excluded from our analysis. The GIS shapefile for the spatial analysis is adopted from [ 33 ] under MIT License].

https://doi.org/10.1371/journal.pclm.0000156.g001

The Government of India’s classification [ 23 ] was used to rank the CVI scores across states as Low, Moderate and High. Low levels show less climate vulnerability. Moderate indicates medium and high levels indicate high levels of climate vulnerability. Similarly, for the HI, NOAA’s classification standards [ 26 ] as Low Risk, Caution, Extreme Caution, Danger and Extreme Danger was used. This HI categorisation refers to the effects of heat on the human body, i.e., Caution: fatigue is possible with prolonged exposure and activity. Continuing activity could result in heat cramps; Extreme Caution: heat cramps and heat exhaustion are likely. Continuing activity could result in heat stroke; Danger: heat cramps and heat exhaustion are likely; heat stroke is probable with continued activity; Extreme danger: heat stroke is imminent [ 26 ].

State-level CVI and HI impact on the UN SDGs

A trend analysis was conducted to map India’s progress in UN SDGs over 20 years (2001–2021) using United Nation’s SDG Index Score [ 28 ], with extreme weather-related mortality from 2001–2021. The trend data was taken from Mahapatra, Walia and Saggurti (2018) [ 29 ] and the Indian Government’s National Crime Record Bureau data on accidental deaths by natural causes [ 30 ]. Next, the severity categories of the states for CVI and HI were mapped to judge the relative position of SDG vulnerability. For example, suppose a state receives a low rank in CVI but a high rank in HI. The relative positioning of the SDG vulnerability will imply that the SDG indicators respective to the low-CVI scores will not be prioritised. However, specific SDG indicators will be over-stressed due to a high HI-score, which needs to be highlighted in the state’s vulnerability assessment. We present this contrasting analysis in the state-level CVI and HI analysis.

Urban-level CVI and HI estimation

In the next step, the case of heatwaves in New Delhi was studied as a scaled-down analysis to discuss heat risks on its urban sustainability. As a baseline, Delhi Government’s latest vulnerability assessment measure through the State Action Plan on Climate Change (SAPCC) [ 31 , 32 ] was used. The SAPCC also classifies vulnerability into three categories: Low, Medium and High. Finally, the vulnerability score is estimated based on 17 risks: migrant population, rate of urbanisation, disabled population, the area under forest cover, total vehicle, solid waste generation, water vulnerable areas, water bodies, parks and tree canopy, tap water connection, sewage treatment plants, effluent treatment plants, stormwater drainage, below-poverty-line families, rooftop solar power and registered electric vehicles and urban heat islands (source: [ 31 , 32 ]).

Increase in heatwave-related vulnerability

Fig 1 captures the extent of heatwave-related vulnerabilities in India, which is missed by the present CVI assessment. It shows the current status of India’s climate vulnerability in Fig 1A ; based on 2019 CVI estimates, the eastern states (except West Bengal) have high climate vulnerability. However, when CVI scores with the HI levels were compared, West Bengal and Andhra Pradesh (a southern state) fall in the ‘extreme danger’ category (see Fig 1B ). Similarly, almost 45% of the country is at moderate CVI levels (see Fig 1A ). However, HI estimates show that more than 90% of India is in the ‘extremely cautious’ or ‘danger’ range (see Fig 1B for this categorisation). Furthermore, the states categorised as’ low’ in CVI rankings are in danger’ Heat Index categories, demonstrating that heatwaves put more people at extreme climate risk across India than estimated by CVI.

Results also show that April 2022 temperature anomalies were exceptionally high (above 4°C) in the northern regions classified as ‘moderate’ in the CVI scores. In addition, states like Punjab and Haryana have experienced a temperature anomaly of 6–7°C, otherwise classified as ‘low’ CVI areas. This high-temperature anomaly zone also includes Delhi, making it most prone to future heatwaves (see Fig 1A and 1C ).

Heatwaves weakening SDG progress across Indian states

The different implications of HI on India’s SDG indicators are shown in Fig 2 . Results indicate that the use of CVI may underestimate the actual burden of climate change concerning heat, suggesting India’s need to reconsider its assessment of climate vulnerabilities to meet the SDGs. This is more so because a CVI that does not include measures of the primary climate change risks/threats (in this study, heatwaves) may fail to identify regions of greatest vulnerability to climate change at the intersection of climate extremes and non-climate, structural and social-economic factors that increase sensitivity. Missing the primary extreme events in conjunction with the contextual factors like differential adaptive capacity that fosters resilience may underestimate the vulnerability [ 34 ] and its subsequent undermining of the sustainable development goals.

The y-axis represents the state-wise HI categories (extreme danger, danger, extreme caution, caution and low risk). The x-axis represents the state-wise CVI categories per UN SDGs. States with blank CVI scores for corresponding SDGs is due to missing data (source: [ 16 ]).

https://doi.org/10.1371/journal.pclm.0000156.g002

Considering the multi-dimensional and cross-sectional nature of climate vulnerability, it is imperative to reflect on the social, cultural, economic, and structural development factors, their inter-relationships, and environmental vulnerabilities. For example, Andhra Pradesh is in extreme danger in HI, affecting SDG-3 (Good health and well-being) and SDG-15 (Life on land). However, these SDGs are considered moderate in the CVI classification (see [ 8 ] and Fig 1A ). For West Bengal, in the same extreme danger HI range (see Fig 2 ), the SDGs that are most critical and will be severely affected are SDG-3 (Good health and well-being), SDG-5 (Gender equality), SDG-8 (Decent work and economic growth) and SDG-15 (Life on land). In this case, the CVI Range for these SDG were also in the high values indicating these SDGs were already stressed in the state. With heatwaves, their fulfilment can further get challenging. Apart from heatwaves, this state is highly vulnerable to flooding and tropical cyclones [ 35 , 36 ].

The trend analysis of the last 20 years from 2001–2021 (see Fig 3 ) on the SDG progress with the mortality due to extreme weather events shows that while the effect of extreme weather events has intensified, the pace of SDG progress is slower. In the last three years (2019–2021), India’s Global SDG rank has declined due to failure in achieving the targets for 11 of the 17 SDGs [ 28 ]. Most of the 11 SDGs India lags on are critically related to climate action. India’s preparedness and performance on SDG 11 (Sustainable Cities and Communities) and SDG 13 (Climate Action) has declined significantly [ 28 ]. This becomes severe due to the strong correlation between these SDGs [ 37 , 38 ]. Thus, in terms of urban sustainability (SDG-11), the failure to develop appropriate low-income housing leaves a significant proportion of the population vulnerable to extreme weather events like heatwaves [ 39 , 40 ].

(source: SDG Index score [ 28 ], Death: [ 29 , 30 ]).

https://doi.org/10.1371/journal.pclm.0000156.g003

The ‘danger’ HI range covers over 80% of Indian states (see Fig 1B ). However, in Fig 2 , many states are classified as moderate or low in the CVI ranking (see Fig 1A ). Highlighting such measurement discrepancies is especially important as the lack of HI accountability in vulnerability mapping can slow down SDG progress and climate adaptation capabilities (supporting the conclusion of [ 41 , 42 ]). For example, Tamil Nadu is assigned a low CVI score reflected across its SDG targets (SDG-2, 8 and 15), implying that even though it has a low climate vulnerability across this sector, heatwaves can significantly impact its socio-economic, livelihood and biophysical quality.

As shown in Fig 1C , northern states are particularly prone to higher temperature anomalies, which supports the latest heatwave pattern across the Indian subcontinent [ 43 , 44 ]. While almost 95% of northern India is under extreme caution and danger HI ranges, ensuring SDG progress becomes even more critical. For example, the most common factors under high climate vulnerability in these states are associated with SDG-2,3, 8 and 15 (see Fig 2 ), which includes agricultural production, employment security and health (as per the Government of India’s CVI estimation, see [ 14 ]). In addition, its sub-indicators include income shares from natural resources, marginal and small landholdings, adaptive livelihood capacity through the MGNREGA program, yield variability of food grains, vector-borne diseases and water-borne diseases (see Table 2 in [ 14 ]). Our findings show that heatwaves will impact all of the above at a grander scale than previously estimated with CVI.

Low HI-risk states also have climate vulnerabilities that will not be affected by heatwaves as much as the states mentioned above. However, Ladakh has a high CVI range impacting SDG-3,5, 8 and 9, implying that the government must continue progress on these SDGs to mitigate its climate vulnerability.

Heatwaves threatening national capital’s urban sustainability

Delhi government’s latest iteration of the State Action Plan on Climate Change (SAPCC) [ 31 ] found high inter-district variability among the standard critical drivers of vulnerability (discussed in Methods) in Delhi, as shown in Fig 4A .

(A) District-level climate change vulnerability assessment as per the Delhi Government classification.; (B) Air temperature during heatwaves, and (C) Estimated heat index (HI) at district-level. The GIS shapefile for the spatial analysis is adopted from [ 45 ] under the CC BY-SA 2.5 IN license.

https://doi.org/10.1371/journal.pclm.0000156.g004

The Delhi government’s assessment shows that the South and North-East Delhi are most vulnerable to climate change impacts (see Fig 4A ), which are also the most affluent areas [ 32 ]. However, our estimation shows that 100% of the city is at ‘Danger’ HI levels (see Fig 1B and 1C ). In addition, by downscaling the HI to the district level in Fig 4C , results show that even the ‘low’ climate-vulnerable areas in Delhi are at high heatwave risks. This is concerning as the current heat-action plans [ 46 ] are designed and implemented per the Delhi government’s vulnerability assessment, which does not include HI estimations. In addition, the high intensity of development in Central, East, West and North-East districts (i.e., the old Delhi area) can further elevate the HI risks through heat island formation. (supporting the findings of [ 47 , 48 ]).

Lack of holistic vulnerability measurements impact India’s SDGs

This study shows that heatwaves make more Indian states vulnerable to climate change than previously estimated with the CVI. Our results show that more than 90% of India is in the ‘extremely cautious’ or ‘danger’ range of heatwave impacts through Heat Index (HI), which is otherwise considered as ‘low’ or ‘moderate’ vulnerability (through CVI, see Figs 1 and 2 ). As the heatwaves in India and the Indian subcontinent become recurrent and long-lasting, it is high time that climate experts and policymakers reevaluate the metrics for assessing the country’s climate vulnerability.

In addition, the findings uniquely reveal that the state-level SDGs in India, considered the basis for CVI, suffer extensive vulnerability due to a lack of consideration of heat impacts at the policy level. It is to be noted that India is already very selective of SDGs in its CVI estimation (see Table 1 ). Such extreme weather events can have spillover effects on SDGs that are not considered. For example, urban India is already very vulnerable to climate change impacts due to its proximity to coastal areas and topological factors in general, resource dependence and existing environmental risks [ 49 ]. By 2025, 70 Indian cities are expected to have more than 1 million inhabitants [ 50 ]. A lack of a holistic climate vulnerability assessment process will slow progress towards meeting SDG-11 (sustainable cities and communities). Such under-reporting of legacy vulnerabilities can severely affect its urban sustainability, as more than 70% of India’s building stock is yet to be built [ 51 ].

Heatwave challenging India’s urban sustainability

In Fig 3 , a trend analysis showed India’s preparedness and performance of SDG 11 (Sustainable Cities and Communities) and SDG 13 (Climate Action) had declined significantly [ 28 ]. Furthermore, regional analysis in the SDG-11 context showed that Delhi’s urban sustainability is severely challenged as its current district-level climate change vulnerability measurements (through SAPCC) do not factor in heatwave impacts (see Fig 4 ). The results emphasise that Delhi’s vulnerability assessment does not consider the variables the national CVI estimation considers, supporting our argument that there needs to be more standardisation for vulnerability assessment in India across federal, state and local levels. Additionally, CVI does not account for the structural sustainable development interventions that are not often related to climate but might impact the coping capacity thresholds for the population. For example, affordable housing is mainly developed to close the housing deficit in the low-income population. However, it can act as a coping mechanism to climate-related heat stress if it is designed to allow better ventilation for heat removal or provides open spaces that encourage community networking. Such networks can then act as mechanisms to build climate resilience. Thus, fulfilling the SDG-11 and SDG-13 agendas. Therefore, vulnerability assessments must account for the interaction between primary climate events and non-climate interventions to progress interdependent SDG goals.

Our results showed that Delhi lies in the 6–7°C temperature anomaly zone, with HI in the danger category (see Figs 1 and 4 ). Some of the critical variables in Delhi that will aggravate heat-related vulnerabilities are like concentration of slum population and overcrowding in high HI areas, lack of access to basic amenities like electricity, water and sanitation, non-availability of immediate healthcare and health insurance, poor condition of housing and dirty cooking fuel (traditional biomass, kerosene and coal). Reducing these vulnerabilities needs structural interventions through the fulfilment of SDG 3, 9, 11 and 10, which are currently missing in India’s SDG focus areas (see Fig 2 ). While some of these variables are considered by the Delhi government in their vulnerability assessment of a small sample of slum households (n = 392) in high-temperature hotspot zones [ 52 ], a significant gap remains in scaling and implementation as heat-action policy frameworks do not exist in practice. The HI analysis for Delhi also supports the existing SAPCC’s vulnerability assessment that affluent areas are at high risk (see Fig 4 ). Since in Delhi, most of the slum settlements co-exist near affluent neighbourhoods [ 47 ], it will have unprecedented consequences on the low-income population. It will pose a threat to energy security (SDG—7), public health and well-being (SDG—3) and reverse progress in reduced inequality (SDG—10) and poverty action (SDG—1). Furthermore, as a rapidly urbanising city, Delhi has a high level of construction activities, mostly involving a low-income labour force, who are also at severe risk from heatwave impacts.

India ranks Delhi as the second-best performer in terms of UN-SDG progress [ 16 ]. It ranks highest in SDG-7 (clean and affordable energy) and has made positive progress towards SDG-1 (no poverty), SDG-3 (good health and well-being), SDG-4 (quality education), SDG-8 (decent work and growth), SDG-10 (reduced inequality), and SDG-11 (sustainable cities and communities) [ 16 ]. However, with the unaccounted HI risk, this ranking is threatened even with its bespoke climate vulnerability assessment using the 17 risk indicators (see Fig 4A ). Moreover, it pressures the adaptive capacity of the migrant population, below-poverty-line families, disabled people, and slum population, severely challenging Delhi’s urban sustainability.

The case of Delhi emphasises that heat is an urban killer and can be modulated through artificial interventions. How we design our cities strongly determines heatwave impacts, eventually affecting the SDGs. Therefore, most urgently, upcoming heat-action policies need to standardise and streamline vulnerability assessments in India.

Emphasizing the multidimensional nature of CVI and its policy

India has demonstrated tremendous leadership in scaling up heat action plans in the last five years by declaring heatwaves a natural disaster and mobilising appropriate relief resources [ 53 ]. In addition, the states have begun adopting the newly launched national guidelines for prevention and management of heatwave [ 54 ], a one-of-a-kind heat action plan in practice only for the city of Ahmedabad since 2013. There are also plans to improve heatwave nowcasting and vulnerability mapping [ 3 ]. However, it is high time that due attention is given to how India assesses its climate vulnerabilities while progressing in its SDGs in the recurring extreme weather context.

The United Nations Framework Convention on Climate Change (UNFCCC) has long recognised the importance of international cooperation and knowledge transfer to improve climate vulnerability assessment while fulfilling global climate objectives [ 55 ]. The results further emphasise the need for India to rethink its vulnerability assessment strategies at a national sustainability policy scale with the increasing severity of heatwaves. International lessons can help in its reevaluation as well [ 56 ]. While there is yet to be a globally accepted universal climate vulnerability index, this study showed the need to incorporate the multidimensional aspects of vulnerability while capturing the co-occurrence and interactions of the climate events capturing the co-occurrence and interactions of the climate events with economic and structural development changes primarily related to SDGs. It further emphasises UN SDG-17 (Partnership for the goals), which is not present in its current CVI methodologies. For example, Bhutan aims to integrate heat risk in an all-hazards risk management system with specific emphasis on improving SDG-4 (Quality Education) through a climate-resilient education system [ 57 ]; however, at present, no information exists on heat vulnerability for Bhutan [ 3 ].

Similarly, Pakistan plans to strengthen extreme heat risk management in the southern region close to India’s highest temperature anomaly zones (see Fig 1C ). Nonetheless, it lacks risk sensitisation and local heat health action plans [ 3 ]. Bangladesh has limited knowledge of heat hotspots and vulnerability mapping across areas within Indian borders. There is a real opportunity for regional partnerships across the Indian subcontinent.

Lessons can also be learnt from global heat preparedness leaders like Australia, the US, the UK and the European Union (EU). For example, the Australian government is set to use the Integrated Heat Vulnerability Assessment Toolkit to measure heat sensitivity and heat adaptive capability indicators at national, regional and city scales [ 58 ]. It is built on the successful Heat Vulnerability Index (HVI), already in use across Melbourne, Dandenong, and Bendigo [ 59 ]. The UK Health Security Agency (UKHSA) and Met Office have recently launched their comprehensive Heatwave plan for England with detailed heatwave alert levels (see pp 13 in [ 60 ]). As a policy, it is designed to work with UK’s existing climate vulnerability measurements [ 60 ]. In the US, the Centre for Disease Control (CDC) releases guides for health departments to assess health vulnerabilities to climate change through a federal Climate and Health program that helps local authorities holistically track climate-related health vulnerabilities (along with heat effects) [ 61 ]. The EU has strategically identified that long-term intersectoral cooperation, surveillance, and plan evaluation can build resilience towards heatwave impacts [ 62 ].

This paper consistently emphasises that there are opportunities for upgrading existing vulnerability assessments for future lethal heatwaves, which is critical to preventing the reversal of India’s SDG progress.

Heatwaves around the globe are getting recurrent, intense and lethal due to climate change. The 2022 Indian heatwave was severe. This paper shows that for India, a vulnerability index (CVI) that does not include measures of the primary climate change risks/threats (like heatwaves) may fail to identify regions of greatest vulnerability to climate change, especially those at the intersection of climate extremes and non-climate, structural and social-economic factors (indicated through SDGs) that increase sensitivity. Results showed that combining HI with CVI can identify practical climate vulnerability impacts that account for extreme weather events at the state level. This, in turn, aids in developing a better understanding of India’s SDG progress. This paper advocates the urgency of improving India’s extreme weather vulnerability assessment while supporting its developmental needs. The same empirical viewpoint can be valid for other weather-related parameters like temperature, precipitation, humidity, etc., to cover extreme weather events, which remain a future work, along with the need for standardization of India’s climate vulnerability assessment at a granular level.

The analysis presented in this paper is limited in its scope to prescribe methods for improving India’s (or any nation’s) CVI estimations across the spectrum of extreme weather events. Due to a lack of data, there was a time lag between the CVI (2019–2020) and HI (2022) estimates that affected the accuracy of CVI vs HI categorization in Figs 1 and 2 . A more updated CVI dataset could provide a more realistic state vulnerability ranking to the HI scores. This study assumed that the hazard probability measured through HI could represent the climate vulnerability measured through CVI. The vulnerability paradox suggests that long-term exposure to elevated levels of climate extremes generate asymmetry in coping capacity and can foster short-term resilience [ 34 ]. Hence, future work would need to derive a composite index with its vulnerability, hazard, adaptive/coping capacity of the population and exposure level at a national and urban scale to compare CVI with heatwave risks for assessing SDG progress.

Further studies should be conducted to evaluate the sensitivity of indices like CVI and HI across different climatic conditions across local, national and international scales to understand their usefulness in the climate change context. Moreover, the two scales presented in this study pave the way for India’s district-level heatwave impact analysis. Small area estimation results can help gross root-level climate change preparedness planning.

This paper shows evidence from the 2022 incidences of severe heatwaves in India (based on April 2022) that abnormal temperature rises from climate change could severely impact over 90% of the country. More accurate estimates can be derived with more data points and macro trend analysis. This lack of data infrastructure must be mitigated for better climate vulnerability assessment. However, the core implication of this paper is that such extreme weather events will intensify the adverse effects on productivity, health, and well-being, potentially slowing down SDG progress. While India can gain from global partnerships on mitigation and adaptation to heatwave impacts, the neighbouring nations can learn from India’s capacity building to a holistic climate vulnerability assessment. India can begin appropriate adaptation planning only with a whole-system treatment of its climate vulnerabilities.

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• 38. Stapleton SO, Nadin R, Watson C, Kellett J. Climate change, migration and displacement -The need for a risk-informed and coherent approach. Shaping Policy for Development by Overseas Development Institute, United Nations Development Programme. 2017;.

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Physical Risk - Risk Management - Transition Risk

India: A Case Study in Climate Mitigation and Adaptation

This article explores the difficult trade-offs that need to be made between the competing claims of climate mitigation, adaptation, and economic development..

Thursday, September 14, 2023

By Maxine Nelson

This article has been extensively updated, incorporating new COP 27 commitments, Reserve Bank of India (RBI) statements and current green bond issuance. It was originally published Oct. 18, 2021.

After decades of population growth and economic development, India is now the third largest emitter of greenhouse gases in the world. In addition, India is among the countries most vulnerable to climate change due to its geography and dependence on agriculture.

It has been estimated that if emissions are not significantly reduced, India could suffer economic losses of USD 35 trillion . Indeed, much of India has been experiencing annual heatwaves followed by intense flooding, and in 2021 alone it experienced even more  extreme weather events — including cyclones and a glacier collapse. Thus, India makes a thought-provoking case study for policymakers and risk professionals given the difficult trade-offs that need to be made between the competing claims of climate mitigation, adaptation and economic development.

Climate Change’s Effect on India

The banking regulator, Reserve Bank of India (RBI) , explains that “India has witnessed changes in climatic patterns in line with the rest of the world… the rainfall pattern, particularly with respect to the [south west monsoon] SWM, which provides around 75 percent of the annual rainfall, has undergone significant changes. Moreover, the occurrence of extreme weather events like floods/unseasonal rainfall, heat waves and cyclones has increased during the past two decades, and data reveal that some of the key agricultural states in India have been the most affected by such events.”

A more recent, detailed RBI study points out that “it is the increased frequency of extreme weather occurrences that is breaking the back of our capability to cope with natural disasters.” As shown by India’s nationally determined contributions (NDCs) — the actions it has committed to take to reduce its emissions and adapt to the impacts of climate change — it is among the most vulnerable countries in the world to the impact of accelerated sea level rise from global warming. This is due to its long coastline, large number of islands and population of 170 million living in coastal regions.

The RBI also notes that precipitation and temperature — the two key climate indicators — “play a crucial role in the overall health of the Indian economy.” As well as affecting food production, the extreme weather in agricultural states impacts employment and GDP, with approximately 44% of the working population employed in agriculture and allied sectors which contribute about 20% of GDP, according to M.K. Jain, the deputy governor of the Reserve Bank . Several challenges confronting Indian agriculture, including diminishing and degrading natural resources and unprecedented climate change, need to be tackled for the long-term sustainability and viability of Indian agriculture.

However, there is uncertainty over how large the impacts might be. The Swiss Re Institute , for example, estimates a 35% reduction in the level of India’s GDP by 2050 if greenhouse gas emissions are not reduced globally, and approximately a 6% GDP reduction even if the Paris Agreement goals are met. An Oxford Economics report “Estimating the Economic Impact of Global Warming” has framed the impact differently, estimating that India’s GDP could be 90% lower in 2100 than it would be if there was no climate change, suggesting that climate change has the potential to absorb all of India’s future prospective growth in income per capita. And  Deloitte  has estimated USD 35 trillion of economic losses by 2070. While these different approaches produce diverse estimates, they all show that the impact will be big and require additional investments in both mitigation and adaptation.

India’s Effect on Climate Change

Not only will the changing climate have a significant impact on India, but India is also expected to have a significant impact on the climate. Although historically it has not had high emissions, India rose to the number three spot in the national emissions rankings 15 years ago, behind China and the U.S. The RBI noted that “With the increase in population, the cumulative level of greenhouse gas (GHG) emissions has increased, resulting in a rise of average temperature. According to a study by the International Energy Agency (IEA), India emitted 2,299 million tonnes of carbon dioxide (CO 2 ) in 2018, a rise of 4.8% over the previous year.”

Unfortunately, India’s future potential emissions are not yet aligned with the Paris Agreement goals. India’s NDCs currently correspond to temperature increases above 3°C, according to Climate Action Tracker . (You can find out more about NDCs and their place in the Paris Agreement in this  short article . ) India increased its commitment to reduce greenhouse gas emissions at COP 26, the 2021 annual meeting of the signatories of the Paris Agreement, where it pledged to cut its emissions to net zero by 2070. While this was a large increase in commitment, it isn’t yet aligned with the worldwide goal of cutting emissions to net zero by 2050 needed to limit global warming to 1.5°C.

Maxine Nelson

In advance of COP 27, India has again increased its commitment and pledged to a 45% reduction in GDP emissions intensity by 2030 — marking an 10% increase from the previous pledge. Any emissions reduction is helpful to mitigate climate change. However, as the pledge is based on emissions intensity and not absolute emissions, emissions can continue increasing as the economy expands. This pledge, therefore, doesn’t meet the net-zero goal of reducing emissions by 45% by 2030. Still, the effort required to overcome the challenge of rapidly expanding an economy while decreasing emissions intensity needs to be appreciated.

To further mitigate climate change, India may need to agree to reduce its emissions even more — a big task for a developing economy with average annual energy consumption of a third the global average, and per capita emissions already 10 times lower than that of the U.S., four times lower than China, and three times lower than Europe. With IPCC reports highlighting the urgency of tackling climate change quickly to reduce the loss and damage for humans and ecosystems, it is even more important that emissions reductions are ambitious.

Financing Mitigation and Adaptation

A 2021 RBI Financial Stability Report noted that climate change and the associated mitigating policy commitments are “set to reshape the macroeconomic and financial landscape”. Extensive funding is needed both to reduce future emissions and to finance the adaptation needed to manage the impacts of climate change. In their 2016 NDC, India estimated that at least USD 2.5 trillion (at 2014-15 prices) would be required for meeting its climate change actions between 2016 and 2030. And the International Energy Agency estimates that nearly 60% of India’s CO 2 emissions in the late 2030s will be coming from infrastructure and machines that do not exist today. If this investment is to be sustainable, USD 1.4 trillion extra funding (above that required for current policies) is needed over the next 20 years.

Like most of the world, green bond issuance in India — which could provide some of this funding — is currently a small proportion of all bond issuance.  The rate of issuance is increasing, however, with USD 21.6 billion of green, sustainable or social bonds issued in 2022. And in 2023, the Government of India entered the green finance market issuing USD 2 billion of green bonds to finance their spending on a range of projects including solar power, green hydrogen and afforestation. As they obtained a greenium (lower financing costs than other equivalent bonds), we should expect to see more of these issued in the future.

There are also substantial opportunities in other financial markets, such as the  development of a derivatives market   to aid adaptation via products such as:

• agricultural commodity derivatives, which can help reduce risks by enabling continuous price discovery and providing hedging
• weather derivatives, which can hedge the risks of high-probability, low-risk events

Of course, meeting the needs of climate change financing carries the usual financial risk implications of any lending. An RBI analysis shows that banks’ direct exposure to fossil fuels (through electricity, chemicals and cars) is 10% of total outstanding non-retail bank credit, so it should have a limited impact on the banking system. However, it notes that many other industries indirectly use fossil fuels and their impacts also need to be closely monitored.

Regulatory Response

The RBI has noted that policy measures such as a deepening of the corporate bond market, standardization of green investment terminology, consistent corporate reporting and removing information asymmetry between investors and recipients can make a significant contribution in addressing some of the shortcomings of the green finance market.

Like in most of the rest of the world, there is an increasing regulatory focus on climate risk. The RBI Governor has stated that guidelines will be issued about disclosure of climate-related risks, and also scenario analysis and stress testing. This followed last year’s RBI consultation which asked for inputs on a comprehensive range of topics from climate risk governance to strategy, and risk monitoring, management and mitigation at regulated entities. This consultation, in turn, built on the results of an RBI survey of banks that was also published last year. The survey found that “although banks have begun taking steps in the area of climate risk and sustainable finance, there remains a need for concerted effort and further action in this regard.” It also found that board-level engagement is inadequate, and few banks had a strategy for incorporating climate risk into their risk management framework. To see what leading climate risk firms are doing globally look at GARP’s whitepaper: “ Climate Risk Leadership: Lessons From 4 Annual Surveys .”

Given the widespread impact of climate change, it isn’t just the banking regulator that is looking at how climate risk will affect firms in its jurisdiction. In 2021, the Securities and Exchange Board of India (SEBI) mandated that the largest 1,000 listed firms complete a Business Responsibility and Sustainability Report . The report asks for information like material ESG risks and opportunities and their financial implications; sustainability related targets and performance; and their greenhouse gas emissions. Companies’ value chains also need to be assessed. This requirement is being progressively rolled out from 2023 to 2027, with the largest companies also required to get assurance of their disclosures.

In addition, SEBI has altered the rules for mutual funds , allowing them to have multiple ESG schemes with different strategies; in the past, a mutual fund could only have one ESG fund. This increase in scope follows one for green debt securities , which was expanded to include bonds such as blue bonds (sustainable water management and marine sector), yellow bonds (solar energy generation and transmission), transition bonds and adaptation bonds. Both of these expansions in scope should increase financing for sustainability related initiatives.

Reflecting the fact that addressing climate change is a global problem, needing both local and global solutions, the RBI joined the Network for Greening the Financial System (NGFS) in April 2021. The NGFS’s purpose is to strengthen the global response required to meet the goals of the Paris Agreement and to enhance the role of the financial system to manage risks and to mobilize capital for green and low-carbon investments. These goals align very well with the work India needs to undertake to make not just its financial system resilient to the risks from climate change, but to balance mitigation, adaptation, and economic development across the country.

Maxine Nelson , Ph.D, Senior Vice President, GARP Risk Institute, currently focusses on sustainability and climate risk management. She has extensive experience in risk, capital and regulation gained from a wide variety of roles across firms including Head of Wholesale Credit Analytics at HSBC. She also worked at the U.K. Financial Services Authority, where she was responsible for counterparty credit risk during the last financial crisis.

ESG Explained: What It Is and Why It Matters Jun 30, 2023

The 4 Main Drivers of Transition Risk, and Why the Risks Are Increasing Apr 12, 2022

Understanding the Physical Risks Associated with Climate Change Apr 27, 2022

India: A Case Study in Climate Mitigation and Adaptation Sep 14, 2023

ESG: Risks, Opportunities and Benefits Jul 26, 2019

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India: Climate Change Impacts

To better understand the risks of climate change to development, the World Bank Group commissioned the Potsdam Institute for Climate Impact Research and Climate Analytics to look at the likely impacts of temperature increases from 2ºC to 4ºC in three regions. The scientists used the best available evidence and supplemented it with advanced computer simulations to arrive at likely impacts on agriculture, water resources, cities and coastal ecosystems in South Asia, South East Asia and Sub-Saharan Africa. Some of their findings for India include:

Extreme Heat

Changing Rainfall Patterns

Groundwater

Glacier Melt

Sea level rise

Agriculture and food security

Energy Security

Water Security

Migration and conflict

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Mainstreaming Adaptation in Action: Case Studies from Two States in India

India will face considerable and varied climate change impacts in the coming decades. The country has a large population with high poverty and low adaptive capacity, heavy dependence on climate-sensitive sectors, and is likely to face negative climate change impacts. These factors make adaptation critical. Integrating, or mainstreaming, adaptation into development plans, programs, and projects is an important strategy to ensure that adaptation can match the scale and urgency of the climate change problem. In India, states are key players on adaptation, and several vulnerable sectors are the responsibility of the state. Some sectors in a few states have begun mainstreaming adaptation into their sectoral programs and projects. This paper highlights two case studies of adaptation being integrated into sectoral development programs and projects, in the states of Madhya Pradesh and Uttarakhand. Ideally, the findings from analyzing these case studies will accelerate and scale mainstreaming efforts in India.

Key Findings

• Programmatic mainstreaming may be more financially sustainable than project-specific mainstreaming
• Funding streams can be used to intentionally support mainstreaming; having supportive policy frameworks in place can support mainstreaming
• Both political and administrative leaders play important and complementary roles in enabling mainstreaming
• Building capacity and improving institutional memory are key elements of mainstreaming
• Persistent communication and coordination among sectors is critical for managing climate risks.

Executive Summary

• India will face considerable and varied climate change impacts in the coming decades. The country’s large population with high poverty and low adaptive capacity, dependence on climate-sensitive sectors, and negative climate change projections make adaptation critical.
• Integrating, or mainstreaming, adaptation into development plans, programs, and projects is an important strategy to ensure that adaptation can match the scale and urgency of the climate change problem.
• In India, states are key players on adaptation, and several vulnerable sectors are the responsibility of the state. Although some sectors in a few states have begun mainstreaming adaptation into their sectoral programs and projects, there is much more opportunity to integrate climate risks into development.
• This paper describes how sectoral departments in two states have sought to manage climate risks and incorporate adaptation into their sector plans, budgets, and programs, as well as why this was necessary, what it looked like, and how this mainstreaming of adaptation was possible. 
• In doing so, the paper provides findings that may be relevant to other sectoral departments and states: Programmatic mainstreaming may be more financially sustainable than project-specific mainstreaming; funding streams can be used to intentionally support mainstreaming; having supportive policy frameworks in place can support mainstreaming; both political and administrative leaders play important and complementary roles in enabling mainstreaming; building capacity and improving institutional memory are key elements of mainstreaming; and persistent communication and coordination among sectors is critical for managing climate risks.

Integrating adaptation into sectoral programs, policies, and projects is an effective way to address the magnitude of climate change. India’s large population is highly vulnerable to climate change impacts, and it is important for communities and sectors to adapt rapidly, at scale, in a way that is sustainable over time. One way to achieve this is to integrate adaptation into the day-to-day functioning of relevant sectors, such as agriculture and water, upon which large sections of the population depend for their livelihoods.

In India, these key sectors are the responsibility of states, and states are expected to incorporate climate change into their regular functioning. To prioritize adaptation activities, states have developed and implemented State Action Plans on Climate Change (SAPCCs). These plans have resulted in some interventions being implemented, but there is much more opportunity for progress. Through the upcoming revision of the SAPCCs, states have an opportunity to accelerate and deepen efforts to get climate-sensitive sectors to identify and address climate change risks and impacts in their day-to-day operations, programs, and budgets.

However, there are institutional and financing dynamics that challenge integration of adaptation into sectoral strategies at the state level. For instance, in 2014, the Planning Commission, which was the central body that guided planning and development in India, was dissolved and replaced with National Institution for Transforming India (NITI Aayog). NITI Aayog is a policy think tank that aims to increase the involvement of the states in policymaking. While decentralization of power to the states will be beneficial in some ways, there is a need for centralized planning guidance, directives, and financial support to enable state-level adaptation policymaking. This institutional decentralization has been coupled with financial decentralization, which has resulted in states needing funding for their SAPCCs at a time when they have potentially less access to financial support from the central government. The SAPCC has no dedicated funding mechanism for adaptation, and the link between the SAPCCs and India’s Nationally Determined Contribution (NDC) to the United Nations Framework Convention on Climate Change (UNFCCC), which is the country’s most recent climate plan, is weak.

Despite these challenging dynamics, there is scope for more and better adaptation to be integrated into sectoral programs and projects. This paper provides findings from two case studies to enable and encourage this, by showcasing mainstreamed adaptation that has been done: what it looks like, and how and why it was achieved. One case study looks into how the Department of Animal Husbandry (DoAH) in Madhya Pradesh integrated adaptation into its programs, and the other looks into how a multisectoral project was implemented by the Forest Department in Uttarakhand.

About This Working Paper

This paper provides two in-depth examples of how adaptation is integrated into sectoral programs, projects, and budgets in order to highlight what mainstreamed adaptation looks like and also what is necessary for integrating adaptation into development. Ideally, these findings will enable sectors, departments, and states to accelerate and scale their efforts at integrating adaptation into their day-to-day functioning. Doing so will help India adapt to the negative impacts of climate change more rapidly and at scale. The findings are also relevant to stakeholders who can support the rapid uptake of mainstreamed adaptation in India, such as the Ministry of Environment, Forest and Climate Change (MoEFCC) and state climate change cells.

• Programmatic mainstreaming may be more financially sustainable than project-based mainstreaming. Programmatic mainstreaming has occurred when adaptation is integrated into a department’s programs and budgets and can be seen in its day-to-day work. Using the program’s budget for making the department’s day-to-day work resilient to climate change can be challenging because sectors usually have constrained budgets. However, the benefit of this type of mainstreaming is that it may be more financially sustainable over time because program budgets are always accessible (if adequate) to support adaptation. This is in contrast to stand-alone adaptation interventions that are time-bound, after which there is no option of accessing funds for further adaptation activities.
• Funding streams can be used to intentionally support mainstreaming.  It is especially strategic to use sectoral funds to integrate adaptation into a department’s work when it does not require an overhaul of the existing program being implemented by the department. For instance, in the Madhya Pradesh case study, the Department of Animal Husbandry was able to use sectoral funds by retaining the way it delivered its program but changing the species of cows it was promoting to a more climate-resilient species. In the case of project mainstreaming or when sectoral funds are inadequate to accommodate expenditure of adaptation, other sources may provide an opportunity to adapt. For instance in the Uttarakhand case study, 40 percent of the project was funded by cofinancing from the departments involved, and this cofinancing was dovetailed with budgets from relevant government schemes. The Mission for Integrated Development of Horticulture (MIDH) provided a subsidy for constructing the polyhouses that provided an alternative to rain-fed farming that is vulnerable to increased drought and erratic rainfall.
• Policy frameworks are important, especially at the early stages of mainstreaming.  Although the SAPCC recommendations are not mandates and cannot ensure that adaptation takes place, the two case studies showcase the different but important roles that the SAPCCs played in both states at the beginning of the mainstreaming process. In Madhya Pradesh it was not the final SAPCC document that spurred and enabled integration of adaptation into the DoAH as much as the process of developing the SAPCC, with the working groups and access to experts being critical elements that enabled mainstreaming. In Uttarakhand, the Forest Department prepared the SAPCC with support from the United Nations Development Programme (UNDP), which seemed to enable the Forest Department to lead the project highlighted in the case study. The SAPCC itself was helpful in guiding selection of the location and activities of the project implemented by the Forest Department. 
• Both political and administrative leaders have different yet complementary influences on the mainstreaming process. Political leaders have the ability to share high-level messages from state or sectoral plans with communities at local levels. For instance, in Madhya Pradesh, political leaders promoted incentive schemes at the village level to increase the uptake of the DoAH’s revised programs. Administrative leaders are government officials who allocate funds for various state-level programs and can influence the strategic use of funds for mainstreaming. In the case of Madhya Pradesh, the chief secretary of DoAH was able to approve the well-documented case for amending the DoAH’s programs and budgets to integrate climate risks. Both these forms of support and influence are required for successful mainstreaming of adaptation.
• Building capacity and institutional memory enables implementation and sustained action.  Both case studies highlight how a commitment to engaging individuals and building their capacity to engage further enables implementation of adaptation interventions within a sector. Building capacity and institutional memory can also enable sustained action over time, despite turnover in personnel. The process of developing the SAPCC was critical for building the capacity of sectoral department staff in Madhya Pradesh, and both of the case studies show that an investment in information-sharing and training can ensure institutional memory.
• Persistent communication and coordination across sectors are critical for managing climate risks.  In cases where multiple sectors are involved, as in the Uttarakhand project, persistent communication and ongoing coordination between sectors and other key entities—in this case the State Climate Change Cell and UNDP—were critical to engage other departments and sustain the momentum of the project. As described further in the Uttarakhand case study and in the Findings and Conclusions, having persistent communication and coordination is feasible for projects with a clear lead implementer, which was the Forest Department in this case. However, in cases of inter-sectoral programmatic mainstreaming where there is no lead organization, it will be critical to agree upon distinct roles and responsibilities.

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Climate change: The challenges for public health preparedness and response- An Indian case study

Rajan r. patil.

Dept. of Health, UNDP, UN-House-II, Orissa, India

T. M. Deepa

Extremes weather changes surpassing their usual statistical ranges and tumbling records in India could be an early warning bell of global warming. Extreme weather events like the recent record setting in western Indian city of Mumbai or all time high fatalities due to the heat wave in southern Indian states or increasing vulnerability of easten Indian states to flood could all be a manifestation of climate change in the Asian subcontinent. While the skeptics may be inclined to dismiss these events as simple local aberrations, when viewed in an epidemiological paradigm in terms of person, time and space couple with frequency, intensity and fatalities, it could well be an early manifestation of climate change. Global warming poses serious challenge to the health sector and hence warrants emergency health preparedness and response. Climate-sensitive diseases are among the largest global killers, hence major brunt of global climate change in terms of adverse health impact will be mostly borne by poor and developing countries in Asia, given the levels of poverty, nutional levels and poor public health infrastructure.

INDIAN CASE STUDY

The Indian metropolitan city of Mumbai was besieged with India's heaviest downpour of the century in July 2005, killing nearly 600 people. According to the Indian Meteorological department, was the heaviest ever rainfall received in a single day, any where in India recording 94.4 cm in the last 100 years. It broke the record of previous highest rainfall at one place in India at Cherrapunjee in Meghalaya of 83.82 cm recorded on July 12 th , 1910.[ 1 ] Cherrapunjee in the North Eastern state of Meghalaya is a generally wellknown for being the wettest place in the world.

In the same year, there was another record broken in Eastern Indian state of Orissa, for unusual mercurial rise in summer, June 2005 recorded the highest temperature of 46.3 degree Celsius in Bhubaneswar of the last 33 years which is 10 degrees above normal,[ 1 ] leading to a heatwave. Speaking of heat wave, the 1998 heat wave in Orissa was recorded as one of the worst, claiming more than 2000 lives.[ 2 ] 1998 was the warmest year globally.[ 3 ]

Extremes of climatic changes surpassing their usual statistical ranges and tumbling records in India should be an early alarm to all of us to sit back and take notice. Extreme weather could be a manifestation of global climate change and global warming.

We are not insisting that the record-breaking Mumbai rain or heat waves in Orissa have a direct causal association with global warming /global climate change but at the same time, we should also not ignore them as “simple local aberrations”. Extreme weather events such as severe storms, floods and drought have claimed thousands of lives during last few years and have adversely affected the lives of millions and cost significantly in terms of economic losses and damage to property. Just to take few examples: Floods are an annual feature in Bihar, but the 2004 floods were unique for its severity. Andhra Pradesh reeled under heat wave in 2003 killing 1,421 people, which is an all-time high in the history of Andhra Pradesh.[ 4 ] Orissa is no stranger to cyclones but the 1999 cyclone was again unprecedented for the sheer severity with wind speed reaching over 300 km per hour leaving nearly 10000 dead and has gone down in history as the Super cyclone.[ 5 ] Cheerrapunjee, the world's wettest place is going through a rare rain crisis and is experiencing dry spells. This year while Mumbai was being flooded, Cherrapunjee received less than average rain fall in June and July with distressing situation subsequently. According to the meteorological department officials the unusual pattern of rainfall can be attributed to the monsoon trough moving southwards from normal position of the Cherrpunjee-Assam-Bihar belt. The shift has caused more rains in Orissa and Maharashtra belt.[ 1 ]

In addition to changing weather patterns, climatic conditions affect diseases transmitted through water and via vectors such as mosquitoes. Climate-sensitive diseases are among the largest global killers. Diarrhoea, malaria and protein-energy malnutrition alone caused more than 3.3 million deaths globally in 2002, with 29% of these deaths occurring in the Region of Africa.[ 3 ]

No, we are not even saying that India is the only country taking the entire brunt of global warming. Of course all the countries are facing it, e.g., the 1995 Chicago heat wave killed nearly 600 people, French heat wave of 2004 killed 15, 000 people in a matter of a weeks.[ 6 ] Like-wise in Fiji, the 1998 Dengue outbreaks are again said to be an evidence of global climate change, as the distribution of the vector (Aedes polyneiensis) is said to be affected by rise in the sea level, since it breeds in brackish water.[ 7 ]

Recognition of the existence of the problem is the first step towards solution, rather than dismissing global climate change as conspiracy theory or hype created by environmentalists. It is important that we have these extreme events on our surveillance radar and verify them for being potential pieces of evidence from India for global climate change. Extreme climate events are expected to become more frequent in the coming years with climate change.

Let's face it; the major brunt of global climate change in terms of adverse health impact will be mostly borne by poor and developing countries, even though rich and industrialized countries account for maximum green house gas emission.[ 3 , 8 ] Any region under stress, such as the Indian sub-continent, is likely to experience greater effects from these ‘extreme weather’ events, because of obvious reasons poverty, malnutrition, poor public health infrastructure etc.

In its Third Assessment Report (2001), the United Nation's Intergovernmental Panel on Climate Change (IPCC) stated: “There is new and stronger evidence that most of the warming observed over the last 50 years is attributable to human activities” and concluded that: overall, climate change is projected to increase threats to human health, particularly in lower income populations, predominantly within tropical/subtropical countries.[ 9 ]

A brief overview of likely health effects due to climate change ( Figure 1 ) is discussed here.

Possible health impacts due to climate change[ 11 ]

DIRECT IMPACTS

The weather has a direct impact on our health. If the overall climate becomes warmer, there will be an increase in health problems. It is anticipated that there will be an increase in the number of deaths due to greater frequency and severity of heat waves and other extreme weather events. The elderly, the very young and those suffering from respiratory and cardiovascular disorders will probably be affected by such weather extremes as they have lesser coping capacity. An extreme rise in the temperature will affect people living in the urban areas more than those in the rural areas. This is due to the ‘heat islands’ that develop here owing to the presence of concrete constructions, paved and tarred roads. Higher temperatures in the cities would lead to an increase in the ground-level concentration of ozone thereby increasing air pollution problems.

INDIRECT IMPACTS

Indirectly, changes in weather pattern, can lead to ecological disturbances, changes in food production levels, increase in the distribution of malaria, dengue and other vector-borne diseases. Fluctuation in the climate especially in the temperature, precipitation and humidity can influence biological organisms and the processes linked to the spread of infectious diseases.

The infections that will spread with climate change have some commonalities.[ 10 ] They are focal and their distribution is limited by the ecology of their reservoir, be it arthropod, snail or water. They usually have a two or three-host life cycle, meaning that in addition to infecting people, they infect a vector and frequently also a wild vertebrate animal host. Either the vector or the host or both, are the reservoir. The range of the reservoir is delineated by temperature and sometimes water. If the agent and reservoir are successful in the newly warmer climate, the agent can be expected to multiply more rapidly and if the reservoir is an arthropod or snail, it too will develop more rapidly (it may also have a shorter life).

The risk of explosive epidemics due to vector borne diseases is enhanced because of two main properties of the vector-virus relationship. Firstly, within limits viruses multiply more rapidly in mosquitoes at high temperatures than at low ones. Secondly, the mosquito also develops more rapidly at high temperatures than at low ones. This combination is conducive to a very short incubation period in the mosquito and rapid mosquito population increase. A short incubation period in the mosquito along with rapid population increase in turn can lead to more rapid and sometimes explosive transmission in the human population. This prediction, however, should be accompanied by a caution. Warmer temperatures also lead to a shorter life span of the mosquito and shorter life means less time to transmit the virus to another person.

Among vector-borne diseases in India, malaria is of considerable concern. Periodic epidemics of malaria occur every five to seven years and the World Bank estimates that about 577,000 DALYs (disability-adjusted life years) were lost due to malaria in India in 1998. Climate change could increase the incidence of malaria in areas that are already malaria-prone and also introduce malaria into new areas.

Potential effects on health due to sea level rise include:

• Death and injury due to flooding;
• Reduced availability of fresh water due to saltwater intrusion;
• Contamination of water supply through pollutants from submerged waste dumps;
• Change in the distribution of disease-spreading insects;
• Health effect on the nutrition due to a loss in agriculture land and changes in fish catch; and health impacts associated with population displacement

Source of Support: Nil

Conflict of Interest: None declared.

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Call for case studies on indigenous climate adaptive solutions in India

24 September 2024, 7:10 UTC 3 min read

India is one of the most diverse countries in terms of indigenous communities. This makes it well placed to utilise the rich knowledge and practices of these communities. Indigenous people have, over several decades, used these to design effective climate adaptive solutions to tackle climate change. The significance of indigenous climate adaptable solutions in India stems from the centuries-long cultivation of a profound grasp over local ecosystems. Insights on regional climatic trends, soil composition, and water supplies are included in this traditional knowledge, and these can be helpful in managing and adapting to climate change. In addition, these practices also support the preservation of cultural diversity, sustainable resource management, and biodiversity—all of which are essential to successfully adapt to environmental change. 

To tap into this rich knowledge, Climate Group, as part of its Under2 Coalition sub national work, aims to bring out the best practices and case studies on a national and global platform. We aim to initiate policy advocacy around incorporating these practices into the mainstream policy measures designed to address climate change. 

What kind of case studies are we looking for?  

We are looking for brief, true stories about an advocacy campaign, initiative or a project which highlights local and indigenous work on climate adaptation. Stories which document efforts lowering the impact of climate change, supporting communities and societies as they make the transition to a future that is both just and climate resilient. 

What should an Indigenous climate adaptive solution case study look like?  

Solutions-driven: Ensure that your case study is concrete, real and an existing indigenous climate adaptive solution incorporated by communities or promoted by government authorities or civil society organisations through projects or policy interventions. 

Visually appealing: Do share images, video or graphic elements if possible. 

Highlights stakeholders: The story should underline the involvement of different stakeholders and sectors driving the change. These could be community representatives, local government authorities, civil society organisations, academicians, etc.  

Personal element: Highlight the people behind the initiative. Share their perspective or quote them in the story. Include someone who’s directly involved in the project or an expert in the field. 

Short and concise:  Limit the story within 1200 – 1500 words.  

How to submit the case study?  

The case studies can be submitted via this online form or in text format (1500 words max), following the guiding questions, by email to [email protected] . The guiding questions are meant to help you structure your case study and help ensure all relevant information is present but are not mandatory. Complementing the case studies with visual material, such as photos from the field, would be preferable.  

Interested organisations and individuals are also encouraged to showcase their projects by submitting a short 1-2 minute video footage and testimonials from the field, by email to [email protected] . These recordings could be used to create an advocacy video on “The inclusion of local indigenous climate adaptive solutions in adaptation policy framework for India” that will be projected at the 2025 India State Funder Roundtable event at Delhi. 

The deadline for submitting the case study is 18 October 2024.  

How will the case studies be used?  

A selection of case studies* will be presented at the upcoming national roundtable on climate change involving the government officials, funders, philanthropists, CSOs and representatives from selected communities in January 2025. 

*Selected submissions will be further co-developed into case studies in collaboration with Climate Group’s Governments and Policy team. These case studies highlight the scope and diversity of ongoing indigenous adaptive efforts to tackle climate change, but do not necessarily imply endorsement from Climate Group.  

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Climate Change: A Case Study Over India

• Published: November 1998
• Volume 61 , pages 9–18, ( 1998 )

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• A. K. Sahai 1  

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A brief account of various causes of climate change in recent decades and climate change trends in the Indian region is presented. It is of great importance to determine the influence of human activities on the likely climate change during recent decades. Local temperature is one of the major climatic elements to record the changes in the atmospheric environment caused by industrialization and urbanization. It is mentioned in the literature that there is either a cooling tendency or cessation of warming after the late 1950s at most of the Indian industrial cities. A case study of Nagpur, a centrally located city in India, is done to understand and the possible cause of cooling. Nagpur is the only city in India for which a long-term record of temperature, for urban (Mayo Hospital) and relatively suburban (Sonegaon Airport) area, is available. The study of the diurnal asymmetry in maximum and minimum temperatures indicates that the role of suspended particulate matter dominates over that of increasing greenhouse gases.

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Sahai, A. Climate Change: A Case Study Over India. Theor Appl Climatol 61 , 9–18 (1998). https://doi.org/10.1007/s007040050047

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DOI : https://doi.org/10.1007/s007040050047

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Waaree Energy: Business Case Study on the Underdog of India’s Renewable Energy!

Waaree energies is revolutionizing india's solar industry, outpacing even the biggest players with its innovative strategies and rapid growth. discover how this underdog is set to break china's monopoly and power india's renewable future—read the full story now.

Thursday September 26, 2024 , 4 min Read

In an era where nations are grappling with both climate change and energy dependency, India's resolve to embrace renewable energy shines bright. Amidst the solar power surge, Waaree Energies has emerged as the unlikely hero. With India aiming to become the third-largest economy under the Modi 3.0 government, energy security is paramount, especially as rising inflation, foreign pressures, and fierce global competition loom. At the heart of India's power puzzle is its persistent oil dependency problem, but a hidden gem in the renewable energy sector may just have the answer: Waaree Energies.

The Oil Dependency Problem and India's Renewable Solution

India’s energy demand, coupled with its oil dependency, not only inflates costs but makes it vulnerable to international economic shifts. Renewable energy, particularly solar, offers a clean solution to this growing crisis. However, there’s a catch: India relies heavily on China for solar panel materials, with China monopolising over 80% of the global solar panel production process. For context, China manufactures solar panels at 50% lower cost than Europe and 65% lower than the U.S. In fact, the European Commission's 2023 study revealed that Chinese companies produce solar panels for 16 to 18.9 cents per watt , far cheaper than European ( 24.3 to 30 cents per watt ) and U.S. ( 28 cents per watt ) counterparts.

But here’s the twist: Waaree Energies has risen above the Chinese tide, making waves in India’s solar landscape. By 2024, Waaree boasts a production capacity of 13.35 GW , three times that of Adani’s 4 GW and comfortably surpassing Vikram Solar’s 3.5 GW .

Waaree’s fiscal performance is equally striking. In FY23, where Adani’s Mundra posted a revenue decline of -12% , Vikram Solar dipped by -7% , and Tata Power faced a -19% slump, Waaree surged ahead with a 136% revenue growth and a jaw-dropping 538% net profit growth.

Breaking the Chinese Monopoly: Waaree’s Solar Superpowers

So, how is Waaree Energies outshining even the corporate giants of India, like Adani and Tata? Let’s break down their strategy into three "superpowers":

• Manufacturing Scale : Waaree understands that to compete globally, scale is essential. By ramping up production capacity, the company has achieved cost efficiencies, gradually closing the price gap with Chinese manufacturers. With global solar demand on the rise, Waaree has positioned itself to benefit from this shift.
• Vertical Integration for Supply Chain Security : While many Indian solar companies rely heavily on Chinese imports, Waaree is taking bold steps to vertically integrate its supply chain within India. From producing ingots and wafers to solar cells and modules, Waaree is working towards self-reliance. By building out this domestic infrastructure, Waaree is not only safeguarding itself from the notorious Chinese “dumping” strategy but also aligning itself with government policies aimed at boosting indigenous manufacturing.
• Expansive Distribution Network : A significant aspect of Waaree’s success is its vast distribution network, achieved through a franchise model that spans across India. With over 388 unique franchises , Waaree can reach even the remotest corners of the country, including Tier 2 and Tier 3 cities. This grassroots penetration ensures the company is a household name in both rural and urban settings.

Waaree’s Challenges: Battling Price Drops and Chinese Dumping

Despite its meteoric rise, Waaree faces significant challenges. The price of solar modules has plummeted by 95% from $1.78 per watt in 2010 to $0.096 per watt by 2024, compressing profit margins. Moreover, Waaree still imports 70% of its raw materials from China, which leaves it vulnerable to China’s aggressive dumping strategy.

Government Support: A Ray of Hope for Indian Solar

The Indian government is not leaving its solar champions to fend for themselves. Through initiatives like the Domestic Content Requirement (DCR) mandate, Performance Linked Incentive (PLI) schemes , and imposing 40% import duty on solar modules, India is steadily pushing for more domestic manufacturing. Additionally, subsidies aimed at rooftop solar installations are expected to drive consumer demand, with the government setting an ambitious goal of 1 crore Indian households switching to solar.

In a nutshell, Waaree is the "light at the end of the power tunnel" —and as the underdog continues to rise, it’s a reminder that sometimes, the best stories come from those who are quietly breaking records in the background.

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This is a new section of the Public-Private Partnership Resource Center website and is currently in draft form. Your feedback is welcome: If you would like to comment on the content of this section of the website or if you have suggestions for links or materials that could be included please contact us at [email protected].

EV charging infrastructure, India

I. Innovative Revenues for Infrastructure (IRI)

- Abbreviations

- Executive Summary

1. Overview and Structure

2. Introduction to Commercial Value Capture (CVC)

3. Applying CVC in Infrastructure Projects

4. Roadmap for CVC

II. Annex for IRI Guide

1. Worked Examples on CVC

2. Case Studies in CVC from International Experiences

3.100 Case Studies: Municipal PPP Framework 

Find Full Outline

Photo Credit: Image by frimufilms on Freepik

On this page:  Renewable energy projects can provide governments with an additional source of revenue from leasing land or water bodies to developers.   Find case studies below, or visit the  Guidelines on Innovative Revenues for Infrastructure  section.

Project Summary:

The cost of electric motorbikes and mopeds has now reached parity with the traditional internal combustion motorbikes and mopeds.  Moreover, electric charging costs are relatively cheaper than gasoline.  Consequently, there has been a sharp increase in the uptake of electric vehicles (EV), especially motorbikes and mopeds in Asia, not only in developed countries such as China and Japan but also in emerging markets such as India, Indonesia, and Thailand.

Successful EV adoption requires a change in consumer behavior enabled by public policy to create an EV ecosystem that makes EV use affordable and reliable.

The shift to EV use is imperative for countries with net zero commitments, given that transport is a leading source of greenhouse gas (GHG) emissions. Although a strong push toward EV would also create higher energy demand that could easily offset gains if energy sources are not clean.

The charging infrastructure is the backbone of electric mobility. India perceives key barriers for EVs including high capital investment, lack of affordable land in dense urban areas with public charging seen as a standalone land use requiring dedicated space, limited power distribution capacity, and long charging times. 1

Project Structure

The Government of India supports the EV industry by encouraging electric and hybrid vehicle purchases through its Faster Adoption and Manufacturing of Electric Vehicles (FAME). FAME II is a 3-year program supporting electric and hybrid buses, electric 3W, 2W and 4W passenger vehicles. 2

Under FAME I and II, about 371,000 EVs were supported with total incentive of around Rs. 634 Crore (~USD 79.6 million) as of July 2021, and 427 charging stations have been installed. Under FAME II, Rs. 1000 Crores (~USD 125.6 million) is allocated for the development of charging infrastructure in the country. 3

The Government of India has set a target to electrify 70% of all commercial vehicles, 30% of private cars, 40% of buses, and 80% of two-wheeler and three-wheeler sales by 2030. This target entails simultaneous penetration of charging stations across India. 4

In 2022, Tata Power has installed 150 EV charging points across residential societies, malls, commercial complexes and petrol pumps in Mumbai. The EV charging points are powered by renewable energy sources like wind, solar and hydropower. 5

Key players for delivering improved services

Ministry of Heavy Industries & National Real Estate Development Council assist the development of EV charging to achieve renewable targets.

Tata Power, a subsidiary of Tata Group, has consolidated its position at the top of the sector, accounting for over 50% of PCPs in the country. Even in the home charging and fleet charging verticals, Tata Power’s market share is at ~40%. 6

Mechanism/s for Maximizing Funding for Infrastructure

The Memorandum of Understanding (MoU) between Tata Power and National Real Estate Development Council for 5,000 EV charging points across Maharashtra was signed to boost EV adoption in the state. Tata Power will provide comprehensive EV charging solutions across properties of member developers of National Real Estate Development Council (NAREDCO). 7

While in Gujarat state, Ahmedabad Municipal Corporation (AMC) will lease land at adjusted rates of INR 10 (USD 13 cents) per sqm with an allotment of ~50 sqm for each charging station. The AMC plans to establish 25 charging stations in the first phase. The 10-year contract will be awarded to the bidder offering the highest fee, subject to a mid-term review at the end of five years. The charging rates to be paid by users will soon be decided by the state government. 8

Typical Business Model

Lessons Learned

Implementation

• Subsidies and incentives to grow the value chain for EV such as manufacturing of EV vehicles and installation of EV charging points were applied in India to encourage growth in private sector business.
• However, as demand rises, land can be leased at more commercial rates.

Replicability

• Similar to AMC, governments can consider partnering with private sector to install EV charging points and earn a concession fee or lease payments and a revenue share once utilization goes beyond a certain threshold.

Footnote 1:   India has made the right move on charging infrastructure for electric vehicles

Footnote 2:   Faster Adoption and Manufacturing of Hybrid and Electric Vehicles (FAME) Scheme - Phase I & II

Footnote 3:   Rs.756.66 Crore allocated and Rs.53.27 Crore Utilized till June 2021 under FAME Scheme

Footnote 4:   Tata sets up 150EV charging points with green fuel in Mumbai

Footnote 5: Ibid

Footnote 6:   Low margins, high stakes: The Tata Power foundation to Tata Group’s electric empire

Footnote 7:   Tata Power signs MoU with NAREDCO for 5,000 EV charging points

Footnote 8: https://www.inframationnews.com/news/11917236/indian-municipality-plans-ev-charging-stations-ppp.thtml

The  Guidelines on Innovative Revenues for Infrastructure (IRI)  is intended to be a living document and will be reviewed at regular intervals. They have not been prepared with any specific transaction in mind and are meant to serve only as general guidance. It is therefore critical that the Guidelines be reviewed and adapted for specific transactions . 

To find more, visit the  Innovative Revenues for Infrastructure  section and the   Content Outline , or  Download the Full Report .  For  feedback  on the content of this section of the website or suggestions for links or materials that could be included, please contact the Public-Private Partnership Resource Center at  [email protected] .

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