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Major factors influencing the health impacts from controlling air pollutants with nonlinear chemistry : an application to China

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      <subfield code="a">Major factors influencing the health impacts from controlling air pollutants with nonlinear chemistry</subfield>
      <subfield code="b">: an application to China</subfield>
      <subfield code="c">Ying Zhou...[et.al]</subfield>
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      <subfield code="a">Predicting the human-health effects of reducing atmospheric emissions of nitrogen oxide (NOx) emissions from power plants, motor vehicles, and other sources is complex because of nonlinearity in the relevant atmospheric processes. We estimate the health impacts of changes in fine particulate matter (PM2.5) and ozone concentrations that result from control of NOx emissions alone and in conjunction with other pollutants in and outside the mega-city of Shanghai, China. The Community Multiscale Air Quality (CMAQ) Modeling System is applied to model the effects on atmospheric concentrations of emissions from different economic sectors and geographic locations. Health impacts are quantified by combining concentration-response functions from the epidemiological literature with pollutant concentration and population distributions. We find that the health benefits per ton of emission reduction are more sensitive to the location (i.e., inside vs. outside of Shanghai) than to the sectors that are controlled. For eastern China, we predict between 1 and 20 fewer premature deaths per year per 1,000 tons of NOx emission reductions, valued at $300$6,000 per ton. Health benefits are sensitive to seasonal variation in emission controls. Policies to control NOx emissions need to consider emission location, season, and simultaneous control of other pollutants to avoid unintended consequences.</subfield>
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      <subfield code="a">Control ambiental</subfield>
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      <subfield code="a">Contaminación del aire</subfield>
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      <subfield code="w">MAP20077000345</subfield>
      <subfield code="t">Risk analysis : an international journal</subfield>
      <subfield code="d">McLean, Virginia : Society for Risk Analysis, 1987-2015</subfield>
      <subfield code="x">0272-4332</subfield>
      <subfield code="g">07/04/2014 Volumen 34 Número 4 - abril 2014 , p. 683-697</subfield>
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