期刊
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
卷 116, 期 18, 页码 8775-8780出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1816102116
关键词
air pollution; environmental economics; marginal damages; particulate matter
资金
- US EPA [R835873]
- University of Minnesota IREE Grants [RL-0026-09, RO-0002-11]
- US Department of Energy [DE-EE0004397]
- US Department of Agriculture NIFA/AFRI Grant [2011-68005-30411]
- EPA [R835873, 909425] Funding Source: Federal RePORTER
- NIFA [579559, 2011-68005-30411] Funding Source: Federal RePORTER
Fine particulate matter (PM2.5) air pollution has been recognized as a major source of mortality in the United States for at least 25 years, yet much remains unknown about which sources are the most harmful, let alone how best to target policies to mitigate them. Such efforts can be improved by employing high-resolution geographically explicit methods for quantifying human health impacts of emissions of PM2.5 and its precursors. Here, we provide a detailed examination of the health and economic impacts of PM2.5 pollution in the United States by linking emission sources with resulting pollution concentrations. We estimate that anthropogenic PM2.5 was responsible for 107,000 premature deaths in 2011, at a cost to society of $886 billion. Of these deaths, 57% were associated with pollution caused by energy consumption [e.g., transportation (28%) and electricity generation (14%)]; another 15% with pollution caused by agricultural activities. A small fraction of emissions, concentrated in or near densely populated areas, plays an outsized role in damaging human health with the most damaging 10% of total emissions accounting for 40% of total damages. We find that 33% of damages occur within 8 km of emission sources, but 25% occur more than 256 km away, emphasizing the importance of tracking both local and long-range impacts. Our paper highlights the importance of a fine-scale approach as marginal damages can vary by over an order of magnitude within a single county. Information presented here can assist mitigation efforts by identifying those sources with the greatest health effects.
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