Characterizing CO and NOy 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 NOy relationships to constrain emission inventories. We derive ambient and modeled ΔCO:ΔNOy ratios that have previously been interpreted to represent CO:NOy ratios in emissions from local sources. Modeled and measured ΔCO:ΔNOy are similar; however, measured ΔCO:ΔNOy 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 NOy in the area. The sector mix is important because emitted CO:NOx 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:ΔNOy to emitted CO:NOy is challenged by ambient and modeled evidence that free tropospheric entrainment, and atmospheric processing elevates ambient ΔCO:ΔNOy above emitted ratios. Specifically, modeled ΔCO:ΔNOy 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:ΔNOy suggesting that secondary CO formation plays a role in these elevated ratios. This analysis suggests that ambient urban daytime ΔCO:ΔNOy values are not reflective of emitted ratios from individual sources. Key Points Modeling and ambient analysis suggest that atmospheric processing can impact the ΔCO:ΔNOy measured by aircraft over the Baltimore region For about one third of measurements, NOy values derived from different instruments lead to observed ΔCO:ΔNOy that are statistically inconsistent We urge caution in using ΔCO:ΔNOy derived from aircraft measurement to quantify emissions errors from specific sources