Fine-scale simulation of ammonium and nitrate over the South Coast Air Basin and San Joaquin Valley of California during CalNex-2010

National ambient air quality standards (NAAQS) have been set for PM_2.5 due to its association with adverse health effects. PM_2.5 design values in the South Coast Air Basin (SoCAB) and San Joaquin Valley of California exceed NAAQS levels, and NH^(+)_(4) and NO^(-)_(3) make up the largest fraction of total PM2.5 mass on polluted days. Here we evaluate fine-scale simulations of PM_(2.5) NH^(+)_(4) and NO^(-)_(3) with the Community Multiscale Air Quality model using measurements from routine networks and the California Research at the Nexus of Air Quality and Climate Change 2010 campaign. The model correctly simulates broad spatial patterns of NH^(+)_(4) and NO^(-)_(3) including the elevated concentrations in eastern SoCAB. However, areas for model improvement have been identified. NH_3 emissions from livestock and dairy facilities appear to be too low, while those related to waste disposal in western SoCAB may be too high. Analyses using measurements from flights over SoCAB suggest that problems with NH3 predictions can influence NO^(-)_(3) predictions there. Offline ISORROPIA II calculations suggest that overpredictions of NH_x in Pasadena cause excessive partitioning of total nitrate to the particle phase overnight, while underpredictions of Na^+ cause too much partitioning to the gas phase during the day. Also, the model seems to underestimate mixing during the evening boundary layer transition leading to excessive nitrate formation on some nights. Overall, the analyses demonstrate fine-scale variations in model performance within and across the air basins. Improvements in inventories and spatial allocations of NH_3 emissions and in parameterizations of sea spray emissions, evening mixing processes, and heterogeneous ClNO_2 chemistry could improve model performance

Characterizing CO and NO y Sources and Relative Ambient Ratios in the Baltimore Area Using Ambient Measurements and Source Attribution Modeling.

Modeled source attribution information from the Community Multiscale Air Quality model was coupled with ambient data from the 2011 Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality Baltimore field study. We assess source contributions and evaluate the utility of using aircraft measured CO and NO y relationships to constrain emission inventories. We derive ambient and modeled ΔCO:ΔNO y ratios that have previously been interpreted to represent CO:NO y ratios in emissions from local sources. Modeled and measured ΔCO:ΔNO y are similar; however, measured ΔCO:ΔNO y has much more daily variability than modeled values. Sector-based tagging shows that regional transport, on-road gasoline vehicles, and nonroad equipment are the major contributors to modeled CO mixing ratios in the Baltimore area. In addition to those sources, on-road diesel vehicles, soil emissions, and power plants also contribute substantially to modeled NO y in the area. The sector mix is important because emitted CO:NO x ratios vary by several orders of magnitude among the emission sources. The model-predicted gasoline/diesel split remains constant across all measurement locations in this study. Comparison of ΔCO:ΔNO y to emitted CO:NO y is challenged by ambient and modeled evidence that free tropospheric entrainment, and atmospheric processing elevates ambient ΔCO:ΔNO y above emitted ratios. Specifically, modeled ΔCO:ΔNO y from tagged mobile source emissions is enhanced 5-50% above the emitted ratios at times and locations of aircraft measurements. We also find a correlation between ambient formaldehyde concentrations and measured ΔCO:ΔNO y suggesting that secondary CO formation plays a role in these elevated ratios. This analysis suggests that ambient urban daytime ΔCO:ΔNO y values are not reflective of emitted ratios from individual sources