. "Appendix C: Description of the Air Pollution Emission Experiments and Policy (APEEP) Model and Its Application." Hidden Costs of Energy: Unpriced Consequences of Energy Production and Use. Washington, DC: The National Academies Press, 2010.
The following HTML text is provided to enhance online
readability. Many aspects of typography translate only awkwardly to HTML.
Please use the page image
as the authoritative form to ensure accuracy.
Hidden Costs of Energy: Unpriced Consequences of Energy Production and Use
After computing the marginal damage of emissions for a specific pollutant from source i, this experiment can be repeated for each of the six pollutants covered in APEEP and the approximately 10,000 distinct (individual and grouped) sources in the United States. The total 10,000 sources encompass all anthropogenic emissions of these six pollutants in the lower 48 states. It is important to note that the APEEP model, in its current form, does not test for interactions among emissions of multiple pollutants in terms of the damages that such emissions cause. The model is designed to simulate the emissions of 1 ton of one specific pollutant from a particular source and to estimate its impact rather than the emissions of multiple pollutants from a source and estimating their cumulative impact.
The following section briefly highlights the basic structure of the model and some of its most important assumptions. The model uses data on emissions (excluding carbon monoxide and lead and including ammonia) that contribute to the formation of criteria air pollutants. The data were provided by EPA’s 2002 National Emission Inventory (EPA 2009). Concentrations due to the baseline levels of emissions are estimated by the air-quality models in APEEP. The air-quality modeling module makes use of a source-receptor matrix framework. That is, the marginal contribution of emissions in a source county (s) to the ambient concentration in a receptor county (r) is represented as the s,r element in a matrix. Using a linear algebraic approach, APEEP multiplies the matrix times an emission vector to generate a vector of predicted ambient concentrations. When the emission vectors represent changes to existing emissions, the corresponding estimated concentrations reflect changes to the baseline levels, or existing concentrations. When the emission vectors represent the emission rates, then predicted concentrations reflect those rates, not changes to concentrations.
The model contains source-receptor matrices for the following pollutants in both summer and winter: NOx → NOx, SO2 → SO2. The matrix governing the relationship between NOx emissions, VOC emissions, and O3 concentrations is calibrated to the summer season. The matrices representing formation and transport of particles (PM2.5 → PM2.5, PM10 → PM10, NOx → PM, SO2 → PM, NH3 → NH4, VOC → PM) produce annual means.2 There is a specific matrix in APEEP for each of the emission-concentration relationships shown above.
The particulate matter source-receptor matrices compute the ammonium-sulfate-nitrate equilibrium, which determines the amount of ambient ammonium sulfate (NH4)2, SO4, and ammonium nitrate (NH4NO3) at each receptor county. The equilibrium computations reflect several fundamental
PM indicates that the contribution of NOx, VOCs, and SO2 is counted to both PM2.5 and PM10. Parameterization of the relationship between VOC emissions and the formation of PM is based on the work of Grosjean and Seinfeld (1989).