Spatially resolved estimation of ozone-related mortality in the United States under two representative concentration pathways (RCPs) and their uncertainty

Young-Min Kim, Ying Zhou, Yang Gao, Joshua S. Fu, Brent A. Johnson, Cheng Huang, Yang Liu

The spatial pattern of the uncertainty in air pollution-related health impacts due to climate change has rarely been studied due to the lack of high-resolution model simulations, especially under the Representative Concentration Pathways (RCPs), the latest greenhouse gas emission pathways. We estimated future tropospheric ozone (O3) and related excess mortality and evaluated the associated uncertainties in the continental United States under RCPs. Based on dynamically downscaled climate model simulations, we calculated changes in O3 level at 12 km resolution between the future (2057-2059) and base years (2001-2004) under a low-to-medium emission scenario (RCP4.5) and a fossil fuel intensive emission scenario (RCP8.5). We then estimated the excess mortality attributable to changes in O3. Finally, we analyzed the sensitivity of the excess mortality estimates to the input variables and the uncertainty in the excess mortality estimation using Monte Carlo simulations. O3-related premature deaths in the continental U.S. were estimated to be 1,312 deaths/year under RCP8.5 (95% confidence interval (CI): 427 to 2,198) and -2,118 deaths/year under RCP4.5 (95% CI: -3,021 to -1,216), when allowing for climate change and emissions reduction. The uncertainty of O3-related excess mortality estimates was mainly caused by RCP emissions pathways. Excess mortality estimates attributable to the combined effect of climate and emission changes on O3 as well as the associated uncertainties vary substantially in space and so do the most influential input variables. Spatially resolved data is crucial to develop effective community level mitigation and adaptation policy.