ALBERT

Description: Agricultural ammonia (NH3) emissions are highly uncertain, with high spatiotemporal variability and a lack of widespread in situ measurements. Regional NH3 emission estimates using mass balance or emission ratio approaches are uncertain due to variable NH3 sources and sinks as well as unknown plume correlations with other dairy source tracers. We characterize the spatial distributions of NH3 and methane (CH4) dairy plumes using in situ surface and airborne measurements in the Tulare dairy feedlot region of the San Joaquin Valley, California, during the NASA Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality 2013 field campaign. Surface NH3 and CH4 mixing ratios exhibit large variability with maxima localized downwind of individual dairy feedlots. The geometric mean NH3:CH4 enhancement ratio derived from surface measurements is 0.15 +/- 0.03 ppmv ppmv1. Individual dairy feedlots with spatially distinct NH3 and CH4 source pathways led to statistically significant correlations between NH3 and CH4 in 68% of the 69 downwind plumes sampled. At longer sampling distances, the NH3:CH4 enhancement ratio decreases 20-30%, suggesting the potential for NH3 deposition as a loss term for plumes within a few kilometers downwind of feedlots. Aircraft boundary layer transect measurements directly above surface mobile measurements in the dairy region show comparable gradients and geometric mean enhancement ratios within measurement uncertainties, even when including NH3 partitioning to submicron particles. Individual NH3 and CH4 plumes sampled at close proximity where losses are minimal are not necessarily correlated due to lack of mixing and distinct source pathways. Our analyses have important implications for constraining NH3 sink and plume variability influences on regional NH3 emission estimates and for improving NH3 emission inventory spatial allocations.

Description: The San Joaquin Valley (SJV) of California experiences high concentrations of PM2.5 (particulate matter with aerodynamic diameter 2.5 m) during episodes of meteorological stagnation in winter. Modeling PM2.5 NH4NO3 during these episodes is challenging because it involves simulating meteorology in complex terrain under low wind speed and vertically stratified conditions, representing complex pollutant emissions distributions, and simulating daytime and nighttime chemistry that can be influenced by the mixing of urban and rural air masses. A rich dataset of observations related to NH4NO3 formation was acquired during multiple periods of elevated NH4NO3 during the DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) field campaign in SJV in January and February 2013. Here, NH4NO3 is simulated during the SJV DISCOVER-AQ study period with the Community Multiscale Air Quality (CMAQ) model version 5.1, predictions are evaluated with the DISCOVER-AQ dataset, and process analysis modeling is used to quantify HNO3 production rates. Simulated NO3- generally agrees well with routine monitoring of 24-h average NO3-, but comparisons with hourly average NO3- measurements in Fresno revealed differences at higher time resolution. Predictions of gas-particle partitioning of total nitrate (HNO3 + NO3-) and NHx (NH3 + NH4+) generally agreed well with measurements in Fresno, although partitioning of total nitrate to HNO3 was sometimes overestimated at low relative humidity in afternoon. Gas-particle partitioning results indicate that NH4NO3 formation is limited by HNO3 availability in both the model and ambient. NH3 mixing ratios are underestimated, particularly in areas with large agricultural activity, and the spatial allocation of NH3 emissions could benefit from additional work, especially near Hanford. HNO3 production via daytime and nighttime pathways is reasonably consistent with the conceptual model of NH4NO3 formation in SJV, and production peaked aloft between about 160 and 240 m in the model. During a period of elevated NH4NO3, the model predicted that the OH + NO2 pathway contributed 46% to total HNO3 production in SJV and the N2O5 heterogeneous hydrolysis pathway contributed 54%. The relative importance of the OH + NO2 pathway for HNO3 production is predicted to increase as NOx emissions decrease.