Temperature ( C) Map 1. Annual Average Temperatures Are Projected to Increase Dramatically by 2050

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1 CO UNT RY S NA P SHO T Sri Lanka s Hotspots The Impact of Temperature and Precipitation Changes on Living Standards Climate change is already a pressing issue for Sri Lanka. Temperatures have risen considerably and will continue increasing. Precipitation patterns will become less predictable. These changes will negatively impact living standards in Sri Lanka. Sri Lanka is at risk from a variety of climate-related factors. Increasing average temperatures and changes in seasonal Figure 1. Temperatures Are Projected to Continue Rising in Sri Lanka 31 Furthermore, Sri Lanka s proximity to the ocean makes it 30 vulnerable to increases in extreme topical storms and sealevel rise. Yet, Sri Lanka 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 Temperature ( C) rainfall patterns are already having a negative impact. 29 Historic time series Historic average ( ) Climate-sensitive (RCP 4.5) Carbon-intensive (RCP 8.5) Historic trend (0.17 C/decade) these hotspots in Sri Lanka.1 By 2050, annual average temperatures in Sri Lanka are projected to increase 1.0 C to 1.5 C under the climatesensitive scenario and 1.0 C to 2.0 C under the carbonintensive scenario (figure 1 and map 1) 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) b. Carbon-intensive scenario Temperature change ( C) Source: Mani et al Note: Changes are for 2036 through 2065 relative to averages for 1981 through 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 The climate-sensitive scenario corresponds to representative concentration pathway (RCP) 4.5, which represents a future in which some collective action is taken to limit greenhouse gas emissions and global annual average temperatures 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 Sri Lanka is already experiencing negative effects of temperature on living standards 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 look at future climatic conditions. This is done by estimating the empirical relationship between consumption expenditures (a proxy for living standards) and climate, controlling for household, district, and geospatial characteristics (figure 2). Using this formulation, it is found that there is an inverted U shaped relationship between temperature and living standards in Sri Lanka. This shape means that cold areas benefit from temperature increases (to a point) and hot areas are negatively affected (see figure 2). In this country snapshot and in the full book, a hotspot is defined as a location where changes in average temperature and precipitation will have a negative effect on living standards. To qualify hotspots, mild refers to changes of 0 percent to 4 percent, moderate to changes of 4 percent to 8 percent, and severe to changes larger than 8 percent. Overall, projected changes in average temperature and precipitation will have a negative impact on living standards in Sri Lanka (table 1 and map 2). Under the climate-sensitive scenario, the change in living standards is 4.9 percent by 2050; and under the carbon-intensive scenario, the change is 7.0 percent. Figure 2. Temperature and Consumption Have an Inverted U Shaped Relationship in Sri Lanka Consumption change Table 1. Living Standards Are More Affected under the Carbon-Intensive Climate Scenario Scenario Climate-sensitive Carbon-intensive Although the conditions leading to hotspots may vary, the estimated effects are unambiguous: approximately 19 million people in Sri Lanka today live in locations that would become moderate or severe hotspots by 2050 under the carbon-intensive scenario (table 2). This is equivalent to more than 90 percent of the country s population. Living standards are less affected under the climate-sensitive scenario At the provincial level, the spatial distribution of hotspots in Sri Lanka is relatively similar under the carbon-intensive Table 2. Around 19 Million People Live in Areas That Are Projected to Become Moderate or Severe Hotspots under the Carbon-Intensive Climate Scenario by 2050 Hotspot Type 24 No. of People Affected (millions) temperature Annual average temperature ( C) Note: Blue shaded region indicates 90 percent confidence interval. Change in Living Standards Severe Moderate Mild Overall SRI LANKA S HOTSPOTS COUNTRY SNAPSHOT

3 Map 2. The Carbon-Intensive Climate Scenario Leads to More Severe Hotspots by 2050 a. Climate-sensitive scenario b. Carbon-intensive scenario Hotspots Severe Moderate Mild Non-Hotspots No data Hotspots Severe Moderate Mild Non-Hotspots No data Source: Mani et al 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. and climate-sensitive scenarios (map 2). However, at the The highly urbanized and densely populated Western household level, the effects of climate change are weaker province also includes Colombo, which is a critical under the climate-sensitive scenario (table 3). This suggests economic hub that contributes more than 40 percent of the that proactive global climate action would significantly country s GDP. benefit Sri Lanka. Among the districts, Jaffna emerges as the top hotspot, North and North Western areas will be the most affected followed by Puttalam in North Western province and Mannar and Kilinochchi in Northern province (table 5). Given that 5 of the top 10 vulnerable districts of Sri Lanka The North and North Western provinces of Sri Lanka are in Northern province, it is very important that changes emerge as the top two hotspots (table 4). Northern in average temperature and precipitation be considered province is home to a large number of poor and displaced for the future planning and development activities of people, and the effects of climate change will add a further Northern province. Gampaha, which is among the top challenge to this long-term recovery. North Central and 10 most vulnerable districts, is also the second most Western provinces are also heavily affected, with living populous district in the country and has been heavily standard declines of 8.0 and 7.5 percent, respectively. affected by recent droughts. Table 3. Characteristics of Hotspot Households Hotspot Type Households Road Density (km/10 km2) Population (per km2) Travel Time to Market (hours) Female Household Agriculture Years of Education Electricity Severe Moderate Mild Overall SRI LANKA S HOTSPOTS COUNTRY SNAPSHOT 3

4 Table 4. Predicted Change in Living Standards and Characteristics of Provinces in Sri Lanka under the Carbon-Intensive Scenario in 2050 Province 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 Household Agriculture Overall Northern North Western North Central Western , Eastern Southern Sabaragamuwa Uva Central 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. Table 5. Predicted Change in Living Standards and Characteristics of the Top 10 District Hotspots in Sri Lanka under the Carbon-Intensive Scenario in 2050 District Province 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 Household Agriculture Years of Education Electricity Overall Jaffna Northern Puttalam North Western Mannar Northern Kilinochchi Northern Kurunegala North Western Trincomalee Eastern Gampaha Western , Kegalle Sabaragamuwa Mullaitivu Northern Vavuniya Northern a. Water availability refers to the ratio of surface water use to groundwater use. A large value is good because it indicates that water is use more likely to be sustainable. Targeted policies can promote development and reduce hotspots The analysis suggests that increasing nonagricultural jobs by 30 percent relative to current levels could reduce the living standards burden from 7.0 to 0.1 percent (figure 3). Reducing the time to reach a market by 3 percent could reduce the consumption burden from 7.0 to 2.1 percent. Increasing average educational 4 SRI LANKA S HOTSPOTS COUNTRY SNAPSHOT

5 Figure 3. Good Development Outcomes Reduce Hotspots in Sri Lanka Change in living standards Status quo 7.0 Educational attainment 2.6 Market access 2.1 Nonagricultural jobs 0.1 Note: The impact of all development outcomes (except market access) is calculated using a 30 percent positive increase in the indicator. Market access is calculated using a 3 percent increase. attainment by 30 percent could also reduce the overall severity of climate-related living standards impacts from 7.0 to 2.6 percent. If these interventions were implemented together, they would likely yield greater benefits than if implemented individually. Notes 1. Data and analysis are provided in Mani and others 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 Updated High-Resolution Grids of Monthly Climatic Observations The CRU TS3.10 Dataset. International Journal of Climatology 34 (3): Mani, M., S. Bandyopadhyay, S. Chonabayashi, A. Markandya, and T. Mosier 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 An Overview of CMIP5 and the Experiment Design. Bulletin of the American Meteorological Society 93 (4): SRI LANKA S HOTSPOTS COUNTRY SNAPSHOT 5

6 worldbank.org/southasiahotspots SKU 33204