Assessing the health benefits of reducing particulate matter air pollution in the United States

Environ Res. 1998 Feb;76(2):94-106. doi: 10.1006/enrs.1997.3799.


Most Americans are exposed daily to airborne particulate matter (PM), a pollutant regulated by the U.S. Environmental Protection Agency. Current national standards are set for PM10 (particles less than 10 microns in diameter) and new standards have been promulgated for PM2.5 (particles less than 2.5 microns in diameter). Both particle sizes have been associated with mortality and morbidity in studies in the United States and elsewhere and an unambiguously safe level of ambient PM has been difficult to identify. PM10 concentrations have been reduced significantly in U.S. cities over the past two decades and relatively few locations continue to exceed national PM10 standards. However, the new PM2.5 standards will require further reductions in PM concentrations and additional expenditures for emission controls. Information about the health and economic benefits of achieving lower PM concentrations is important because: (1) expected costs of further PM reductions rise after the least-cost options are exhausted, and (2) there is uncertainty about the existence of a threshold safe level for PM. This paper develops and applies a methodology for quantifying the health benefits of potential reductions in ambient PM. Although uncertainties exist about several components of the methodology, the results indicate that the annual nationwide health benefits of achieving the new standards for PM2.5 relative to 1994-1996 ambient concentrations are likely to be between $14 billion and $55 billion annually, with a mean estimate of $32 billion.

MeSH terms

  • Adult
  • Air Pollution* / adverse effects
  • Air Pollution* / economics
  • Air Pollution* / prevention & control
  • Asthma / epidemiology
  • Bronchitis / epidemiology
  • Child
  • Cost Savings
  • Cost-Benefit Analysis
  • Environmental Exposure*
  • Forecasting
  • Health Care Costs / statistics & numerical data
  • Hospitalization / statistics & numerical data
  • Humans
  • Models, Theoretical
  • Particle Size
  • Public Health / economics*
  • United States / epidemiology