CAS-TWAS Center of Excellence for Climate and Environment Sciences (ICCES), Institute of Atmospheric Physics , Chinese Academy of Sciences , Beijing 100029 , China.
University of Chinese Academy of Sciences , Beijing 100049 , China.
Environ Sci Technol. 2019 Nov 5;53(21):12529-12538. doi: 10.1021/acs.est.9b02701. Epub 2019 Oct 16.
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.
氨气（NH）排放清单是化学传输模型的重要输入，有助于政策制定者完善减排策略。然而，目前对中国 NH 排放的估计仍存在很大的不确定性。在本研究中，我们使用集合卡尔曼滤波和嵌套空气质量预测建模系统对中国的 NH 排放进行了改进的反演估计。通过首先同化中国氨监测网络的表面 NH 观测数据，分辨率高达 15 公里，我们的反演结果提供了对中国 NH 排放的时空模式的新见解。在中国西北部，可能与工业或农业源有关的 NH 排放热点得到了更多的增强，这些地区的事后 NH 排放是先验排放的两倍以上。中国不同地区的 NH 排放的月变化得到了优化，并表现出更明显的季节性，夏季排放是冬季的两倍。反演结果得到了跟踪气态 NH 和相关大气过程的几个独立数据集的很好验证。这些发现强调了改进的反演估计可以用于提高我们对中国 NH 排放及其环境影响的认识。
