Tracking daily NO_x emissions from an urban agglomeration based on TROPOMI NO₂ and a local ensemble transform Kalman filter

Abstract. Accurate, timely, and high-resolution NO_x emissions are essential for formulating pollution control strategies and improving the accuracy of air quality modelling at fine scales. Since late 2018, the Tropospheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (S5P) satellite has provided 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 NO_x 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 model (CMAQ), to estimate daily NO_x 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 NO_x 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 NO_x 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 NO_x emissions show considerable seasonal variations and provide more timely insight into NO_x emission fluctuations, such as those caused by the COVID-19 lockdown measures. Evaluations using the TROPOMI NO₂ column retrievals and ground-based observations demonstrate that the posterior emissions substantially improved the accuracy of 3-km CMAQ simulations of the NO₂ TVCDs, as well as the daily surface NO₂ and O₃ concentrations in 2020. However, during the summer, despite notable improvements in surface NO₂ and O₃ simulations, positive biases in the posterior model simulations persist, indicating weaker constraints on surface emissions from satellite NO₂ column retrievals in summer. The posterior daily emissions on the 3-km scale estimated by our inversion system not only provide insights into the fine-scale emission dynamic patterns but also improve air quality modelling on the kilometer scale.