CO UNT RY S NA P SHO T India s Hotspots The Impact of Temperature and Precipitation Changes on Living Standards Climate change is already a pressing issue for India. Temperatures have risen considerably and will continue increasing. Precipitation patterns will become less predictable. These changes will negatively impact living standards in India. Increasing average temperatures and changes in seasonal rainfall patterns are already having an impact on agriculture Figure 1. Temperatures Are Projected to Continue Rising in India across India. Low-lying coastal areas are at risk from sea-level 29 rise and tropical storms, while mountain areas are at risk due 28 India also contains hidden hotspots areas that are economically at risk from climate change but that are not often discussed. This country snapshot summarizes the drivers, impacts, and policy implications of these hotspots Temperature ( C) to changes in snow, melting glaciers, and natural disasters. 27 26 25 in India.1 24 By 2050, annual average temperatures in India are projected 23 to increase 1 C to 2 C under the climate-sensitive scenario and 1.5 C to 3 C under the carbon-intensive scenario (figure 1 and map 1).2 Historic time series Historic average (1981 2010) Climate-sensitive (RCP 4.5) Carbon-intensive (RCP 8.5) Historic trend (0.11 C/decade) 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050 Sources: Mani et al. 2018; data from Harris et al. (2014) and 11 climate models. Note: RCP = representative concentration pathway. Map 1. Annual Temperatures Are Projected to Increase Dramatically by 2050 a. Climate-sensitive scenario Temperature change ( C) 0.0 1.0 1.0 1.5 1.5 2.0 2.0 2.5 b. Carbon-intensive scenario Temperature change ( C) 0.0 1.0 1.0 1.5 1.5 2.0 2.0 2.5 2.5 3.0 Source: Mani et al. 2018. Note: Changes are for 2036 through 2065 relative to averages for 1981 through 2010. The boundaries, colors, denominations, and any other information shown on these maps do not imply, on the part of the World Bank Group, any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries.
The climate-sensitive scenario corresponds to representative concentration pathway (RCP) 4.5, which represents a future Figure 2. Temperature and Consumption Have an Inverted U Shaped Relationship in India in which some collective action is taken to limit greenhouse 0 increase 2.4 C (range of 1.7 C to 3.2 C) by 2100 relative to preindustrial levels. The carbon-intensive scenario corresponds to RCP 8.5, which represents a future in which no actions are taken to reduce emissions and global annual average temperatures increase 4.3 C (range of 3.2 C to 5.4 C) by 2100 relative to preindustrial levels. Most of India is already experiencing negative effects of temperature on living standards Consumption change gas emissions and global annual average temperatures 10 20 temperature 30 40 50 0 5 10 15 20 25 Annual average temperature ( C) 30 Note: Blue shaded region indicates 90 percent confidence interval. The climate is changing and will continue to do so under a range of scenarios, but what impact will this have on living standards? Addressing this question requires understanding the relationship between today s weather and living standards and then applying this relationship to (figure 2). This shape means that cold areas benefit from temperature increases (to a point), and hot areas are negatively affected. look at future climatic conditions. This is done by In this country snapshot and in the full book, a hotspot is estimating between defined as a location where changes in average temperature consumption expenditures (a proxy for living standards) the empirical relationship and precipitation will have a negative effect on living and climate, controlling for household, district, and standards. To qualify hotspots, mild refers to changes of geospatial characteristics. Using this formulation, it is 0 percent to 4 percent, moderate to changes of found that there is an inverted U shaped relationship 4 percent to 8 percent, and severe to changes larger between temperature and living standards for India than 8 percent. Map 2. The Carbon-Intensive Climate Scenario Leads to More Severe Hotspots by 2050 a. Climate-sensitive scenario Hotspots Severe Moderate Mild Non-Hotspots No data b. Carbon-intensive scenario Hotspots Severe Moderate Mild Non-Hotspots No data Source: Mani et al. 2018. The boundaries, colors, denominations, and any other information shown on these maps do not imply, on the part of the World Bank Group, any judgment on the legal status of any territory, or any endorsement or acceptance of such boundaries. 2 INDIA S HOTSPOTS COUNTRY SNAPSHOT
Overall, projected changes in average temperature and precipitation will have a negative impact on living standards in India (map 2). Under the climate-sensitive scenario, the change in living standards is 2.0 percent by 2050; and under the carbon-intensive scenario, the change is 2.8 percent (map 2 and table 1). Although the conditions leading to hotspots may vary, the estimated effects are unambiguous: approximately 600 million people in India today live in locations that would become moderate or severe hotspots by 2050 under the carbon-intensive scenario (table 2). This is equivalent to almost 50 percent of the country s population. Table 1. Living Standards Are More Affected under the Carbon-Intensive Climate Scenario Scenario 2030 2050 Climate-sensitive 1.3 2.0 Carbon-intensive 1.5 2.8 Table 2. Around 600 Million People Live in Areas That Are Projected to Become Moderate or Severe Hotspots under the Carbon-Intensive Climate Scenario by 2050 Hotspot Type No. of People Affected (millions) Change in Living Standards Severe 148 9.8 Moderate 441 5.6 Mild 400 2.3 Overall 1,324 2.8 Under the climate-sensitive scenario, severe hotspots are largely avoided By 2050, many severe hotspots emerge under the carbonintensive scenario, while the climate-sensitive scenario primarily leads to moderate hotspots (map 2 and table 3). Under both scenarios, moderate and severe hotspots are present predominantly in central India. The avoidance of most severe hotspots under the climate-sensitive scenario suggests that proactive global climate action would significantly benefit India. The most vulnerable households are engaged in agriculture While the hotspot analysis investigates the overall relationship between household living standards and changes in average temperature and precipitation, understanding the characteristics of vulnerable households can be informative for developing targeted policies. The households most affected in India are also more likely to be engaged in agriculture as their main livelihood (table 4). Inland areas will be most affected States in the Central, Northern, and Northwestern parts of India emerge as the most vulnerable to changes in average temperature and precipitation (map 2). Chhattisgarh and Madhya Pradesh, which are predicted to experience living standards declines of more than 9 percent, are the top two hotspot states, followed by Rajasthan, Uttar Pradesh, and Maharashtra (table 5). In addition to having higher poverty rates, Chhattisgarh and Madhya Pradesh are also home to large indigenous populations. Climate change therefore has important implications from socioeconomic and equity perspectives. Coastal areas in India receive a lot of attention with respect to extreme events. However, the Table 3. Characteristics of Hotspot s Hotspot Type s Road Density (km/10 km 2 ) Population (per km 2 ) Travel Time to Market (hours) Female Years of Education Electricity Severe 11.2 0.8 231.3 2.7 7.4 51.0 5.7 91.3 Moderate 33.3 1.7 1,005.8 2.1 9.4 41.4 5.5 72.1 Mild 30.2 1.6 1,119.1 2.7 10.8 39.5 5.6 76.3 Overall 100.0 1.6 840.7 2.7 10.8 39.8 5.7 79.8 INDIA S HOTSPOTS COUNTRY SNAPSHOT 3
inland areas emerge as hotspots from the perspective of changes in average temperature and precipitation. Seven out of the top 10 most affected hotspot districts belong to the Vidarbha region of Maharashtra State The remaining three districts are located in Chhattisgarh and Madhya Pradesh (table 6). Table 4. More Than Half of s in Severe Hotspots Are in Hotspot Type Change in Living Standards Head Severe 9.8 51.0 Overall 2.8 39.8 Targeted policies can promote development and reduce hotspots The analysis indicates that enhancing educational attainment, reducing water stress, and improving opportunities in the nonagricultural sector is projected to reduce the impacts of climate change on living standards (figure 3). The analysis predicts that increasing average educational attainment by 30 percent could reduce the living standards burden from 2.8 to 2.4 percent. Reducing water stress and enhancing nonagricultural employment opportunities by 30 percent could yield similar benefits. Therefore, it is recommended that multiple actions be taken to maximize resilience. Conversely, these results also indicate that the wrong policy actions or worsening water stress could exacerbate the impact of climate change. Table 5. Predicted Change in Living Standards and Characteristics of the 10 Most Affected States in India under the Carbon-Intensive Scenario in 2050 State Change in Living Standards Length of Road (km/10 km 2 ) Population Density (per km 2 ) Travel Time to Market (hours) Water Availability a Female Years of Education Electricity Overall 2.8 1.6 840.7 2.7 2.0 10.8 39.8 5.7 79.8 Chhattisgarh 9.4 1.0 212.7 2.9 0.3 6.3 60.7 5.5 89.5 Madhya Pradesh 9.1 1.0 237.0 2.6 0.4 6.0 48.5 5.4 88.4 Rajasthan 6.4 0.7 229.4 2.6 0.1 9.4 36.8 4.8 82.7 Uttar Pradesh 4.9 1.4 801.3 1.9 0.9 10.5 42.9 5.1 51.7 Maharashtra 4.6 1.0 325.6 2.7 0.4 9.4 40.3 7.1 94.2 Jharkhand 4.6 1.6 482.4 2.0 3.5 8.2 30.6 5.2 74.3 Haryana 4.3 2.3 480.5 2.6 0.2 7.4 36.2 6.6 96.6 Andhra Pradesh 3.4 2.1 1,831.3 2.6 2.3 14.3 41.2 5.2 98.2 Punjab 3.3 2.1 464.6 3.5 0.2 12.4 23.5 5.7 98.6 Chandigarh 3.3 5.1 4,529.6 1.5 0.1 6.2 0.2 8.9 97.9 a. Water availability refers to the ratio of surface water use to groundwater use. A large value is good because it indicates that water use is more likely to be sustainable. 4 INDIA S HOTSPOTS COUNTRY SNAPSHOT
Table 6. Predicted Change in Living Standards and Characteristics of the Top 10 District Hotspots in India under the Carbon-Intensive Scenario in 2050 District State Change in Living Standards Length of Road (km/10 km 2 ) Population Density (per km 2 ) Travel Time to Market (hours) Water Availability a Female Head Years of Education Electricity Overall 2.8 1.6 840.7 2.7 2.0 10.8 39.8 5.7 79.8 Chandrapur Maharashtra 12.4 1.2 161.6 1.7 3.1 8.7 50.6 6.8 84.6 Bhandara Maharashtra 11.9 0.8 219.7 2.5 0.3 5.3 51.9 7.2 93.1 Gondiya Maharashtra 11.8 0.8 215.9 2.5 0.2 9.5 51.2 7.0 96.6 Wardha Maharashtra 11.8 0.5 172.0 2.6 0.1 9.8 53.1 8.3 93.6 Nagpur Maharashtra 11.7 0.2 379.9 2.3 0.1 7.7 17.7 8.8 97.2 Raj Nandgaon Chhattisgarh 11.4 1.5 153.0 3.8 0.1 1.8 59.2 4.4 98.0 Durg Chhattisgarh 11.4 0.5 314.4 2.3 0.2 10.6 43.7 7.1 94.3 Hoshangabad Madhya Pradesh 11.3 1.3 144.1 3.6 0.6 0.2 40.0 5.8 91.2 Yavatmal Maharashtra 11.1 0.3 169.3 2.3 0.1 4.4 67.7 5.4 83.0 Gadchiroli Maharashtra 11.1 0.8 61.8 2.5 7.7 9.1 74.0 5.1 81.1 a. Water availability refers to the ratio of surface water use to groundwater use. A large value is good because it indicates that water use is more likely to be sustainable. Figure 3. Good Development Outcomes Reduce the Severity of Hotspots in India Change in living standards 0 0.5 1.0 1.5 2.0 2.5 3.0 Notes Status quo 2.8 Nonagricultural jobs 2.6 Reducing water stress 2.5 Note: The impact of all development outcomes is calculated using a 30 percent positive increase in the indicator. Educational attainment 1. Data and analysis are provided in Mani and others 2018. 2.4 2. Historic climate data are from the Climate Research Unit TS 3.24 (Harris and others 2014). Projected climate data are from an ensemble of climate models participating in CMIP5 (Taylor, Stouffer, and Meehl 2012) selected for use in the full book. References Harris, I. P. D. J., P. D. Jones, T. J. Osborn, and D. H. Lister. 2014. Updated High-Resolution Grids of Monthly Climatic Observations The CRU TS3.10 Dataset. International Journal of Climatology 34 (3): 623 42. Mani, M., S. Bandyopadhyay, S. Chonabayashi, A. Markandya, and T. Mosier. 2018. South Asia s Hotspots: The Impact of Temperature and Precipitation Changes on Living Standards. South Asia Development Matters. Washington, DC: World Bank. Taylor, K. E., R. J. Stouffer, and G. A. Meehl. 2012. An Overview of CMIP5 and the Experiment Design. Bulletin of the American Meteorological Society 93 (4): 485 98. INDIA S HOTSPOTS COUNTRY SNAPSHOT 5
worldbank.org/southasiahotspots SKU 33201