Air quality in the United States has dramatically improved, yet exposure to air pollution is still associated with 100000-200000 deaths annually. Reducing the number of deaths effectively, efficiently, and equitably relies on attributing them to specific emission sources, but so far, this has been done for only highly aggregated groups of sources, or a select few sources of interest. Here, we estimate mortality in the United States attributable to all domestic, human-caused emissions of primary PM2.5 and secondary PM2.5 precursors. We present detailed source-specific attributions in four alternate groupings relevant for identifying promising ways to reduce mortality. We find that nearly half of the deaths can be attributed to just five activities, all in different sectors. Around half of the deaths can be attributed to fossil fuel combustion, with the remainder attributable to combustion of nonfossil fuels, agricultural processes, and other noncombustion processes. Both primary and secondary PM2.5 are important, including PM2.5 from currently unregulated precursor pollutants such as ammonia. We suggest improvements in air quality can be realized by continued reductions of emissions from traditionally important sources and by novel strategies for reducing emissions from sources of emerging relative importance and research focus. Such changes can contribute to improved health outcomes and other environmental goals.
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The authors thank Nina Domingo, Neil Donahue, Eladio Knipping, Jacob Adenbaum, Madisen Gittlin, and members of the Center for Air, Climate and Energy Solutions (CACES) Science Advisory Committee. This publication was developed as part of CACES, which was supported under Assistance Agreement R835873 awarded by the U.S. Environmental Protection Agency (EPA). It has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. S.K.T. acknowledges the William F. Wilcke Fellowship Fund, and J.D.H. acknowledges USDA/NIFA Project MIN-12-083.
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