Journal article
Global effect factors for exposure to fine particulate matter
Department of Technology, Management and Economics, Technical University of Denmark1
University of Minnesota Twin Cities2
University of Washington3
Harvard T.H. Chan School of Public Health4
Sustainability, Department of Technology, Management and Economics, Technical University of Denmark5
Quantitative Sustainability Assessment, Sustainability, Society and Economics, Department of Technology, Management and Economics, Technical University of Denmark6
University of California at Berkeley7
Polish Academy of Sciences8
University of Michigan, Ann Arbor9
University of Texas at Austin10
University of Michigan11
Technical University of Denmark12
...and 2 moreWe evaluate fine particulate matter (PM2.5) exposure–response models to propose a consistent set of global effect factors for product and policy assessments across spatial scales and across urban and rural environments. Relationships among exposure concentrations and PM2.5-attributable health effects largely depend on location, population density, and mortality rates.
Existing effect factors build mostly on an essentially linear exposure–response function with coefficients from the American Cancer Society study. In contrast, the Global Burden of Disease analysis offers a nonlinear integrated exposure–response (IER) model with coefficients derived from numerous epidemiological studies covering a wide range of exposure concentrations.
We explore the IER, additionally provide a simplified regression as a function of PM2.5 level, mortality rates, and severity, and compare results with effect factors derived from the recently published global exposure mortality model (GEMM). Uncertainty in effect factors is dominated by the exposure–response shape, background mortality, and geographic variability.
Our central IER-based effect factor estimates for different regions do not differ substantially from previous estimates. However, IER estimates exhibit significant variability between locations as well as between urban and rural environments, driven primarily by variability in PM2.5 concentrations and mortality rates.
Using the IER as the basis for effect factors presents a consistent picture of global PM2.5-related effects for use in product and policy assessment frameworks.
Language: | English |
---|---|
Publisher: | American Chemical Society |
Year: | 2019 |
Pages: | 6855-6868 |
ISSN: | 15205851 , 0013936x and 13823124 |
Types: | Journal article |
DOI: | 10.1021/acs.est.9b01800 |
ORCIDs: | Fantke, Peter , 0000-0001-6955-4210 and 0000-0002-2796-3478 |