IJERPH, Vol. 15, Pages 2438: Heat-Related Health Impacts under Scenarios of Climate and Population Change

IJERPH, Vol. 15, Pages 2438: Heat-Related Health Impacts under Scenarios of Climate and Population Change

International Journal of Environmental Research and Public Health doi: 10.3390/ijerph15112438

Authors: Philip E. Morefield Neal Fann Anne Grambsch William Raich Christopher P. Weaver

Recent assessments have found that a warming climate, with associated increases in extreme heat events, could profoundly affect human health. This paper describes a new modeling and analysis framework, built around the Benefits Mapping and Analysis Program—Community Edition (BenMAP), for estimating heat-related mortality as a function of changes in key factors that determine the health impacts of extreme heat. This new framework has the flexibility to integrate these factors within health risk assessments, and to sample across the uncertainties in them, to provide a more comprehensive picture of total health risk from climate-driven increases in extreme heat. We illustrate the framework’s potential with an updated set of projected heat-related mortality estimates for the United States. These projections combine downscaled Coupled Modeling Intercomparison Project 5 (CMIP5) climate model simulations for Representative Concentration Pathway (RCP)4.5 and RCP8.5, using the new Locating and Selecting Scenarios Online (LASSO) tool to select the most relevant downscaled climate realizations for the study, with new population projections from EPA’s Integrated Climate and Land Use Scenarios (ICLUS) project. Results suggest that future changes in climate could cause approximately from 3000 to more than 16,000 heat-related deaths nationally on an annual basis. This work demonstrates that uncertainties associated with both future population and future climate strongly influence projected heat-related mortality. This framework can be used to systematically evaluate the sensitivity of projected future heat-related mortality to the key driving factors and major sources of methodological uncertainty inherent in such calculations, improving the scientific foundations of risk-based assessments of climate change and human health.

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