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      Projections of heatwave-attributable mortality under climate change and future population scenarios in China

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          Summary

          Background

          In China, most previous projections of heat-related mortality have been based on modeling studies using global climate models (GCMs), which can help to elucidate the risks of extreme heat events in a changing climate. However, spatiotemporal changes in the health effects of climate change considering specific regional characteristics remain poorly understood. We aimed to use credible climate and population projections to estimate future heatwave-attributable deaths under different emission scenarios and to explore the drivers underlying these patterns of changes.

          Methods

          We derived climate data from a regional climate model driven by three CMIP5 GCM models and calculated future heatwaves in China under Representative Concentration Pathway (RCP) 2.6, RCP4.5, and RCP8.5. The future gridded population data were based on Shared Socioeconomic Pathway 2 assumption with different fertility rates. By applying climate zone-specific exposure-response functions to mortality during heatwave events, we projected the scale of heatwave-attributable deaths under each RCP scenario. We further analyzed the factors driving changes in heatwave-related deaths and main sources of uncertainty using a decomposition method. We compared differences in death burden under the 1.5°C target, which is closely related to achieving carbon neutrality by mid-century.

          Findings

          The number of heatwave-related deaths will increase continuously to the mid-century even under RCP2.6 and RCP4.5 scenarios, and will continue increasing throughout the century under RCP8.5. There will be 20,303 deaths caused by heatwaves in 2090 under RCP2.6, 35,025 under RCP4.5, and 72,260 under RCP8.5, with half of all heatwave-related deaths in any scenario concentrated in east and central China. Climate effects are the main driver for the increase in attributable deaths in the near future till 2060, explaining 78% of the total change. Subsequent population decline cannot offset the losses caused by higher incidence of heatwaves and an aging population under RCP8.5. Although health loss under the 1.5°C warming scenario is 1.6-fold higher than the baseline period 1986–2005, limiting the temperature rise to 1.5°C can reduce the annual mortality burden in China by 3,534 deaths in 2090 compared with RCP2.6 scenarios.

          Interpretation

          With accelerating climate change and population aging, the effects of future heatwaves on human health in China are likely to increase continuously even under a low emission scenario. Significant health benefits are expected if the optimistic 1.5°C goal is achieved, suggesting that carbon neutrality by mid-century is a critical target for China's sustainable development. Policymakers need to tighten climate mitigation policies tailored to local conditions while enhancing climate resilience technically and infrastructurally, especially for vulnerable elderly people.

          Funding

          National Key R&D Program of China (2018YFA0606200), Wellcome Trust (209734/Z/17/Z), Natural Science Foundation of China (41790471), and Guangdong Major Project of Basic and Applied Basic Research (2020B0301030004).

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          Most cited references36

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          The ERA5 Global Reanalysis

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            The representative concentration pathways: an overview

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                Author and article information

                Contributors
                Journal
                Lancet Reg Health West Pac
                Lancet Reg Health West Pac
                The Lancet Regional Health: Western Pacific
                Elsevier
                2666-6065
                05 September 2022
                November 2022
                05 September 2022
                : 28
                : 100582
                Affiliations
                [a ]Vanke School of Public Health, Tsinghua University, Beijing, China
                [b ]School of Public Health, Sun Yat-sen University, Guangzhou, China
                [c ]Shanghai Typhoon Institute, China Meteorological Administration & Shanghai Key Laboratory of Meteorology and Health, Shanghai Meteorological Service, Shanghai, China
                [d ]The State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
                [e ]School of Public Health, Zhengzhou University, Zhengzhou, China
                [f ]School of Public Health, Guangzhou Medical University, Guangzhou, China
                [g ]School of Linkong Economics and Management, Beijing Institute of Economics and Management, Beijing, China
                [h ]Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing, China
                [i ]State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC), School of Environment, Tsinghua University, Beijing, China
                [j ]College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
                [k ]Climate Change Research Center, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
                [l ]National Climate Center, China Meteorological Administration, Beijing, China
                [m ]Department of Earth Sciences and Geography, University of Hong Kong, Hong Kong Special Administrative Region, China
                [n ]Institute of Healthy China, Tsinghua University, Beijing, China
                Author notes
                [* ]Corresponding author at: Vanke School of Public Health, Tsinghua University, Beijing 100084, China. huangcunrui@ 123456mail.tsinghua.edu.cn
                [1]

                The authors contributed equally to the work

                Article
                S2666-6065(22)00197-3 100582
                10.1016/j.lanwpc.2022.100582
                9465423
                36105236
                a836a9b7-5dc5-4fca-998a-06815b472849
                © 2022 The Author(s)

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

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                climate change,heatwave,attributable death,projection,china
                climate change, heatwave, attributable death, projection, china

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