Uncertainty and Variability in Social Costs for Air Quality
RFF Academic Seminar
, Assistant Professor
School of Public Policy, University of Maryland, College Park
Choosing between alternative products, processes and policies requires credible information on both their private and social costs. For air quality, an impact pathway approach, which traces the emissions through to the monetization of the associated effects, is frequently employed to estimate this social cost. An important step in this process is transforming the emissions to their equivalent ambient concentrations. The assumptions in the air quality models, however, are rarely evaluated and may introduce error into the reduced form literature values. Here, we develop new estimates of the social cost for air emissions in $/ton for generic area and point sources in US urban and rural locations. We use a ‘state of science’ 3-D chemical transport model, the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx). By using this model, we attempt to better account for variability and inherent uncertainties in the effects of emissions as it relates to precursor species, season, location and source type in the model to better constrain the value of particulate matter control in terms of social cost. We calculate social costs that differ from other literature values by a factor of two to more than ten for both reactive and non-reactive compounds. This suggests that model variability in transport and chemistry can have an important influence on the estimates. Our results recommend caution in the use of literature values for the social cost of air quality emissions for benefit-cost analysis and externality pricing.
Thursday, September 20, 2012
12:00 - 1:30 p.m.
Lunch will be provided.
7th Floor Conference Room
1616 P St. NW
Washington, D.C. 20036
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