Improving the spatial and temporal variability of ammonia emissions from agriculture in Western Europe

Abstract

allocation was improved by the implementation of the TIMELINES module, which correlates the timing of manure and fertilizer application with meteorology. The method produced an annual emission map and spatially explicit time profiles for Germany and the Benelux for 2010. The newly derived emission information was imported into LOTOS-EUROS to model the ammonia surface concentration and total column distributions. The validation with in situ measurements showed that the model performance improves significantly with respect to the temporal variation of ammonia concentrations in comparison to the simulation with static emission profiles. The comparison with satellite observations confirmed these results and identified an overestimation of ammonia concentrations in Southern Germany and an underestimation in Northern Germany. The conclusion was that the spatial details on the data input needed to be refined further, including crop and livestock distributions, excretion rates, emissions fractions, and the locations of animal houses.Chapter 3 builds on the work described in Chapter 2 and assesses how the spatial allocation in the ammonia emission modeling can be improved by using publicly available crop maps with higher spatial resolution and livestock number data from national registries for the Netherlands, Denmark, and Portugal. Livestock distributions affect the spatial distribution of excreted N and thus ammonia emission, while detailing the crop distribution affects both the spatial and temporal distributions of application emissions. Emission fractions were also updated using the results of local experiments. The differences in the spatial distribution of ammonia emissions are more evident in the animal housing and manure sectors than in the manure and fertilizer application sectors because the changes in animal number data were greater than that in crop distribution. At the same time, the adapted emission distributions show more spatial details because emissions from manure and fertilizer application to crops are only allocated to where the respective crops are grown. The emissions from the standard INTEGRATOR model and the adapted approaches were validated by comparing surface concentrations predicted with LOTOS-EUROS with in situ observations. The validation was made for springtime and wintertime separately to investigate the improvements brought by crop maps and livestock information. The results show that the inclusion of such data has improved both the spatial and temporal distribution of ammonia emissions. However, uncertainties in the spatial and temporal distribution of ammonia emissions remain, which are caused by not accounting for the exact locations of animal houses and the spatial variation in meteorological conditions, application techniques, manure composition, and soil properties. Moreover, the lack of in situ measurement data only allowed model validation for the Netherlands. Last, it has to be noted that crop maps are not always publicly available for other countries, which means that crop mappi...