Improved Inversion of Monthly Ammonia Emissions in China Based on the Chinese Ammonia Monitoring Network and Ensemble Kalman Filter.

Ammonia (NH) emission inventories are an essential input in chemical transport models and are helpful for policy-makers to refine mitigation strategies. However, current estimates of Chinese NH emissions still have large uncertainties. In this study, an improved inversion estimation of NH emissions in China has been made using an ensemble Kalman filter and the Nested Air Quality Prediction Modeling System. By first assimilating the surface NH observations from the Ammonia Monitoring Network in China at a high resolution of 15 km, our inversion results have provided new insights into the spatial and temporal patterns of Chinese NH emissions. More enhanced NH emission hotspots, likely associated with industrial or agricultural sources, were captured in northwest China, where the a posteriori NH emissions were more than twice the a priori emissions. Monthly variations of NH emissions were optimized in different regions of China and exhibited a more distinct seasonality, with the emissions in summer being twice those in winter. The inversion results were well-validated by several independent datasets that traced gaseous NH and related atmospheric processes. These findings highlighted that the improved inversion estimation can be used to advance our understanding of NH emissions in China and their environmental impacts.