Modeling air quality during the California Regional PM10/PM2.5 Air Quality Study (CPRAQS) using the UCD/CIT Source Oriented Air Quality Model – Part II. Regional source apportionment of primary airborne particulate matter

A comprehensive air quality modeling project was carried out to simulate regional source contributions to primary airborne particle concentrations in Californiaʹs central Valley. A 3-week stagnation episode lasting from December 15, 2000 to January 7, 2001, was chosen for study using the air quality and meteorological data collected during the California Regional PM10/PM2.5 Air Quality Study (CRPAQS). The UCD/CIT source oriented air quality model was applied to this episode using both the source-oriented external mixture configuration and an internal mixture with artificial tracers so that source contribution information could be retrieved in less time. The majority of the predicted and measured primary airborne particulate matter mass was composed of elemental carbon (EC) and organic carbon (OC). Previous work has shown that base case EC and OC predictions made by the UCD/CIT model are in good agreement with observations. Model results from the current study show that the highest EC and OC concentrations occur in urban areas and along transportation corridors where primary emissions are largest. Lower concentrations of primary EC and OC are predicted at rural locations in the San Joaquin Valley (SJV). Source contributions predicted by the UCD/CIT air quality model were compared to receptor-oriented source apportionment results produced by the Chemical Mass Balance (CMB) model at Fresno and Angiola. The relative contributions from major sources predicted by the UCD/CIT model agree with the CMB model results, building confidence in the accuracy of the UCD/CIT model predictions at locations where the CMB results are not available. Wood smoke was identified as the major regional source of primary OC in airborne particles in the winter SJV episode, accounting for approximately 50% of the total PM2.5. Diesel engines were also found to be a significant contributor to primary PM2.5 OC and the largest contributor to the predicted PM2.5 EC averaged over a typical day. EC contributions from wood smoke increased at night and sometimes reached as high as 40% of the total PM2.5 EC. The contribution of fugitive dust to primary PM2.5 mass was also predicted to be significant, especially in rural areas, but this result is likely biased high by the lack of an appropriate diurnal profile for dust emissions. The results of the current study suggest that reductions in wood burning and diesel engine activity would reduce the regional concentration of primary PM2.5 during severe winter stagnation events in the SJV.