Spatially resolved estimation of ozone-related mortality in the United States under two representative concentration pathways (RCPs) and their uncertainty
Abstract
We report that 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 and 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 1312 deaths/year under RCP8.5 (95 % confidence interval (CI): 427 to 2198) and ₋2118 deaths/year under RCP4.5 (95 % CI: ₋3021 to ₋1216), when allowing for climate change and emissions reduction. The uncertainty of O3-related excess mortality estimates was mainly caused by RCP emissions pathways. Finally,more »
- Authors:
-
- Emory Univ., Atlanta, GA (United States). Rollins School of Public Health, Dept. of Environmental Health
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Atmospheric Science and Global Change Div. (ASGC)
- Univ. of Tennessee, Knoxville, TN (United States). Dept. of Civil and Environmental Engineering
- Univ. of Rochester, NY (United States). Dept. of Biostatistics and Computational Biology
- George Washington Univ., Washington, DC (United States). Milken Inst. School of Public Health, Dept. of Global Health and Department of Environmental and Occupational Health
- Publication Date:
- Research Org.:
- Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC)
- OSTI Identifier:
- 1188883
- Report Number(s):
- PNNL-SA-97819
Journal ID: ISSN 0165-0009; KP1703010
- Grant/Contract Number:
- AC05-76RL01830; AC05-00OR22725; U01 EH000405; 1R21ES020225; TG-ATM110009; UT-TENN0006
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Climatic Change
- Additional Journal Information:
- Journal Volume: 128; Journal Issue: 1-2; Journal ID: ISSN 0165-0009
- Publisher:
- Springer
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 54 ENVIRONMENTAL SCIENCES; 29 ENERGY PLANNING, POLICY, AND ECONOMY; climate change; ozone; mortality; uncertainty; Representative Concentration Pathways (RCPs); spatial variation
Citation Formats
Kim, Young-Min, Zhou, Ying, Gao, Yang, Fu, Joshua S., Johnson, Brent A., Huang, Cheng, and Liu, Yang. Spatially resolved estimation of ozone-related mortality in the United States under two representative concentration pathways (RCPs) and their uncertainty. United States: N. p., 2014.
Web. doi:10.1007/s10584-014-1290-1.
Kim, Young-Min, Zhou, Ying, Gao, Yang, Fu, Joshua S., Johnson, Brent A., Huang, Cheng, & Liu, Yang. Spatially resolved estimation of ozone-related mortality in the United States under two representative concentration pathways (RCPs) and their uncertainty. United States. https://doi.org/10.1007/s10584-014-1290-1
Kim, Young-Min, Zhou, Ying, Gao, Yang, Fu, Joshua S., Johnson, Brent A., Huang, Cheng, and Liu, Yang. Sun .
"Spatially resolved estimation of ozone-related mortality in the United States under two representative concentration pathways (RCPs) and their uncertainty". United States. https://doi.org/10.1007/s10584-014-1290-1. https://www.osti.gov/servlets/purl/1188883.
@article{osti_1188883,
title = {Spatially resolved estimation of ozone-related mortality in the United States under two representative concentration pathways (RCPs) and their uncertainty},
author = {Kim, Young-Min and Zhou, Ying and Gao, Yang and Fu, Joshua S. and Johnson, Brent A. and Huang, Cheng and Liu, Yang},
abstractNote = {We report that 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 and 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 1312 deaths/year under RCP8.5 (95 % confidence interval (CI): 427 to 2198) and ₋2118 deaths/year under RCP4.5 (95 % CI: ₋3021 to ₋1216), when allowing for climate change and emissions reduction. The uncertainty of O3-related excess mortality estimates was mainly caused by RCP emissions pathways. Finally, 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.},
doi = {10.1007/s10584-014-1290-1},
journal = {Climatic Change},
number = 1-2,
volume = 128,
place = {United States},
year = {Sun Nov 16 00:00:00 EST 2014},
month = {Sun Nov 16 00:00:00 EST 2014}
}
Web of Science
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