Ammonia emissions from a dairy housing and wastewater treatment plant quantified with an inverse dispersion method accounting for deposition loss

Ammonia (NH3) emissions negatively impact air, soil, and water quality, hence human health and biodiversity. Significant emissions, including the largest sources, originate from single or multiple structures, such as livestock facilities and wastewater treatment plants (WWTPs). The inverse dispersion method (IDM) is effective in measuring total emissions from such sources, although depositional loss between the source and point of measurement is often not accounted for. We applied IDM with a deposition correction to determine total emissions from a representative dairy housing and WWTP during several months in autumn and winter in Switzerland. Total emissions were 1.19 +/- 0.48 and 2.27 +/- 1.53 kg NH3 d(-1) for the dairy housing and WWTP, respectively, which compared well with literature values, despite the paucity of WWTP data. A concurrent comparison with an inhouse tracer ratio method at the dairy housing indicated an offset of the IDM emissions by < 20%. Diurnal emission patterns were evident at both sites mostly driven by changes in air temperature with potential lag effects such as following sludge agitation. Modeled deposition corrections to adjust the concentration loss detected at the measurement point with the associated footprint were 22-28% of the total emissions and the cumulative fraction of deposition to emission modeled with distance from the source was between 7% and 12% for the measurement distances (60-150 m). Although estimates of depositional loss were plausible, the approach is still connected with substantial uncertainty, which calls for future validation measurements. Longer measurement periods encompassing more management activities and environmental conditions are required to assess predictor variable importance on emission dynamics. Combined, IDM with deposition correction will allow the determination of emission factors at reduced efforts and costs, thereby supporting the development and assessment of emission reducing methods and expand the data availability for emission inventories.