Ammonia and Methane Dairy Emission Plumes in the San Joaquin Valley of California from Individual Feedlot to Regional Scales
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 ppmv−1. 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.