A nested semi-mechanistic model to predict the temporal dynamics of ammonia emissions from a solid floor naturally ventilated dairy cattle building Parameter estimation and associated uncertainties

The estimation of emission rates from naturally ventilated housing systems can be realized based on two types of approaches: A top-down approach with intermittent volume flow and concentration measurements at the building scale to train regression models or a bottom-up approach to scale-up mechanistic modelling results. Both approaches have merits, drawbacks and uncertainties. We investigated the potential of coupling different mechanistic modelling approaches towards an overarching barn scale ammonia emission model, which permits ammonia emission projections for naturally ventilated housing systems with minimal measurement efforts. As test case, a dataset with about ten months of on-farm measurements in a naturally ventilated dairy cattle building with scraped solid floor in Northern Germany was used. Data on climate and feed composition were included. A sensitivity study indicated that the urine puddle alkalizing dynamics play a key role in the overall model accuracy in order to capture seasonal and diurnal variability. We present here a set of approaches for the estimation of the crucial input parameters for the nested model related to pH and the resulting model deviations and uncertainties. © 2022, VDI Verlag GMBH. All rights reserved.