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We developed a new tagged species source apportionment (TSSA) algorithm for tracking the direct mass contributions of selected emissions sources to the formation of particulates such as aerosol sulfate, nitrate, ammonium, elemental carbon, and secondary organic aerosols in the U.S. EPA Community Multiscale Air Quality Model (CMAQ). The focus of this paper is on sulfate, nitrate, and elemental carbon. The objective of the TSSA algorithm is to provide useful results in modeling studies for identifying important emissions categories and identifying possible emissions reduction strategies to attain particulate matter (PM) air quality goals. TSSA differs from model sensitivity approaches because it tracks direct mass contributions from specific emissions sources to the total PM concentration at selected receptor sites, while results from sensitivity approaches are affected by nonlinear chemistry that can change the concentration of sulfate, nitrate, and organic carbon secondary particulates. We evaluated the algorithm by comparing CMAQ/TSSA results with results from zero‐out CMAQ sensitivity simulations. As expected, TSSA results were almost identical to the CMAQ sensitivity results for chemical species that do not undergo nonlinear chemical reactions. For chemical species with nonlinear chemical reaction, the TSSA results are expected to differ from model sensitivity results, but for small emissions changes the results are similar in the two approaches. We also compared CMAQ/TSSA to CAMx/PSAT. Because there are significant differences in the CMAQ and CAMx model predicted concentrations, the source attribution results differed for TSSA and PSAT; however, the rank order of emissions sources were similar for the two approaches at most receptor sites.
Wang et al. (Mon,) studied this question.