Characterizing the PM₂.₅-related health benefits of emission reductions for 17 industrial, area and mobile emission sectors across the U.S

Environ Int. 2012 Nov 15:49:141-51. doi: 10.1016/j.envint.2012.08.017. Epub 2012 Sep 28.

Abstract

Background: Air pollution benefits assessments tend to be time and resource intensive. Reduced-form approaches offer computational efficiency, but may introduce uncertainty. Some reduced-form approaches apply simplified air quality models, which may not capture the complex non-linear chemistry governing the formation of certain pollutants such as PM₂.₅. Other approaches apply the results of sophisticated photochemical modeling, but characterize only a small number of source types in a limited geographic area.

Methods: We apply CAMx source apportionment photochemical modeling, coupled with a PC-based human health benefits software program, to develop a suite of PM₂.₅ benefit per ton estimates. These per-ton estimates relate emission changes to health impacts and monetized benefits for 17 sectors across the continental U.S., including Electricity Generating Units (EGU), mobile, area and industrial point sources.

Results: The benefit per ton of reducing directly emitted PM₂.₅ is about an order of magnitude larger than reducing emissions of PM₂.₅ precursor emissions. On a per-ton basis, the value of reducing directly emitted PM₂.₅ and PM₂.₅ precursors in 2005 ranges between approximately $1300 (2010$) for reducing a ton of NO(x) from Ocean-Going Vessels to about $450,000 (2010$) for reducing a ton of directly emitted PM₂.₅ from Iron and Steel facilities. The benefit per ton estimates for 2016 are generally higher than the 2005 estimates. The values estimated here are generally comparable with those generated using photochemical modeling, but larger than those calculated using simplified air quality models.

Conclusions: Our approach characterizes well the per-ton benefits of reducing emissions from a broad array of 17 industrial point, EGU and mobile sectors, while our use of photochemical air quality modeling gives us greater confidence that we have accounted for the non-linear chemistry governing PM₂.₅ formation. The resulting benefit per-ton estimates thus represent a compromise between approaches that may simplify the treatment of PM₂.₅ air quality formation and those techniques that are based in photochemical modeling but account for only a small number of emission sources.

MeSH terms

  • Air Pollutants / analysis*
  • Air Pollution / statistics & numerical data*
  • Environmental Monitoring*
  • Health Status
  • Humans
  • Industry / statistics & numerical data
  • Models, Chemical
  • Particle Size
  • Particulate Matter / analysis*
  • United States

Substances

  • Air Pollutants
  • Particulate Matter