title: Modeling the benefits of power plant emission controls in Massachusetts.
abstract: Older fossil-fueled power plants provide a significant portion of emissions of criteria air pollutants in the United States, in part because these facilities are not required to meet the same emission standards as new sources under the Clean Air Act. Pending regulations for older power plants need information about any potential public health benefits of emission reductions, which can be estimated by combining emissions information, dispersion modeling, and epidemiologic evidence. In this article, we develop an analytical modeling framework that can evaluate health benefits of emission controls, and we apply our model to two power plants in Massachusetts. Using the CALPUFF atmospheric dispersion model, we estimate that use of Best Available Control Technology (BACT) for NOx and SO2 would lead to maximum annual average secondary particulate matter (PM) concentration reductions of 0.2 microg/m3. When we combine concentration reductions with current health evidence, our central estimate is that the secondary PM reductions from these two power plants would avert 70 deaths per year in a population of 33 million individuals. Although benefit estimates could differ substantially with different interpretations of the health literature, parametric perturbations within CALPUFF and other simple model changes have relatively small impacts from an aggregate risk perspective. While further analysis would be required to reduce uncertainties and expand on our analytical model, our framework can help decision-makers evaluate the magnitude and distribution of benefits under different control scenarios.
authors.affiliation: Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA. jilevy@hsph.harvard.edu
authors.forename: Jonathan I
authors.initials: JI
authors.lastname: Levy
authors.forename: John D
authors.initials: JD
authors.lastname: Spengler
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000517:prevention & control*; D004777:Environment; D005544:Forecasting; D008404:Massachusetts; D008962:Models, Theoretical; D011050:Policy Making; D011210:Power Plants
chemical_list: D000393:Air Pollutants