Ammonia emissions produce negative environmental and human health impacts with largest emissions originating from agriculture. Especially in countries with high livestock density, the majority originate from animal housing and application to fields. Measuring total emissions from multiple heterogenous source structures such as farms and waste treatment facilities can be challenging due to losses from transport, deposition, and chemical transformation. Previous studies have shown that quantifying net fluxes at this scale can be achieved by combining concentration measurements up- and downwind of the structures with inverse dispersion modelling to calculate the emissions from a defined source area. However, this method underestimates total emissions, as it does not account for deposition loss, which must be modelled and can introduce large uncertainties (<40%). Here we present results from several emission measurements of ammonia from cattle housing and the first such measurements from a wastewater treatment plant in Switzerland using miniDOAS concentrations and a backward Lagrangian Stochastic model. Instead of applying a complex resistance model which relies on parameterizations with high uncertainties, we instead constrained the upper and lower limits of deposition loss to correct the modelled emissions using a simplified resistance approach. Compared with a reference in-house tracer ratio method conducted at the dairy housing, mean corrected emissions differed <20 %, while the overall uncertainty of the corrected emissions was approx. 25%. Reducing the high uncertainty of deposition corrections for the inverse dispersion method will promote its application to determine emission factors from buildings. Moreover, it will improve capabilities to assess and implement much needed emission reducing methods on farms and industrial plants.
