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

Abstract

Ammonia (NH₃) 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 NH₃ emissions still have large uncertainties. In this study, an improved inversion estimation of NH₃ emissions in China has been made using an ensemble Kalman filter and the Nested Air Quality Prediction Modeling System. By first assimilating the surface NH₃ 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 NH₃ emissions. More enhanced NH₃ emission hotspots, likely associated with industrial or agricultural sources, were captured in northwest China, where the a posteriori NH₃ emissions were more than twice the a priori emissions. Monthly variations of NH₃ 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 NH₃ and related atmospheric processes. These findings highlighted that the improved inversion estimation can be used to advance our understanding of NH₃ emissions in China and their environmental impacts.