Tracking daily NO x emissions from an urban agglomeration based on TROPOMI NO 2 and a local ensemble transform Kalman filter

作者：Yawen Kong, Bo Zheng, Yuxi Liu · 发表于：Atmospheric chemistry and physics · 年份：2025 · DOI：10.5194/acp-25-5959-2025 · 被引用次数：7 · 研究领域：Atmospheric chemistry and aerosols、Air Quality Monitoring and Forecasting、Atmospheric and Environmental Gas Dynamics

Abstract. Accurate, timely, and high-resolution NOx emissions are essential for formulating pollution control strategies and improving the accuracy of air quality modeling at fine scales. Since late 2018, the Tropospheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (S5P) satellite has been providing daily monitoring of NO2 column concentrations with global coverage and a small footprint of 5.5 km × 3.5 km, offering great potential for tracking daily high-resolution NOx emissions. In this study, we develop a data assimilation and emission inversion framework that couples an ensemble Kalman filter with the Community Multiscale Air Quality (CMAQ) model to estimate daily NOx emissions at 3 km scales in Beijing and surrounding areas in 2020. By assimilating the TROPOMI NO2 tropospheric vertical column densities (TVCDs) and taking the bottom-up inventory as prior emissions, we produce a posterior NOx emission dataset with a reasonable spatial distribution and daily variations at the 3 km scale. The proxy-based bottom-up emission mapping method at fine scales overestimates NOx emissions in densely populated urban areas, whereas our posterior emissions improve this mapping by reducing the overestimation of urban emissions and increasing emissions in rural areas. The posterior NOx emissions show considerable seasonal variations and provide a more timely insight into NOx emission fluctuations, such as those caused by the COVID-19 lockdown measures. Evaluations using...