Modeling air quality in the San Joaquin valley of California during the 2013 Discover-AQ field campaign

Abstract

The San Joaquin Valley (SJV) of California has one of the nation's most severe wintertime PM2.5 pollution problems. The DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) field campaign took place in the SJV from January 16 to February 6, 2013. It captured two PM2.5 pollution episodes with peak 24-h concentrations approaching 70 μg/m3. Using meteorological fields generated from WRFv3.6, CMAQv5.0.2 was applied to simulate PM2.5 formation in the SJV from January 10 through February 10, 2013. Overall, the model was able to capture the observed accumulation of PM2.5 within the simulation period. The model was able to produce increased concentrations of ammonium nitrate and organic carbon, which are two major components of wintertime PM2.5 in the SJV. Comparison to measurements made by aircraft showed that there was general agreement between observed and modeled daytime vertical distributions of selected gas and particulate species, reflecting the adequacy of modeled daytime mixing layer heights. Excess ammonia predicted by the model implied that ammonium nitrate formation was limited by the availability of nitric acid, consistent with observations. Evaluation of the ammonium nitrate diurnal profile revealed that the observed morning increase of ammonium nitrate was also evident from the model. This paper demonstrates that the CMAQ model is able to simulate elevated wintertime PM2.5 formation observed in the SJV during the DISCOVER-AQ 2013 period, which featured both climatic (i.e., 2011–2014 California Drought) and emissions differences compared to a previous large air quality field campaign in the SJV during 1999–2000. Keywords: CMAQ, DISCOVER-AQ, PM2.5 modeling, San joaquin valley