This study investigates the trends and drivers of anthropogenic nitrogen oxide (NOx) emissions in China from 2020 to 2022. Using satellite observations and atmospheric inversion techniques, the research reveals a consistent decline in NOx emissions during this period, despite increased fossil fuel consumption. The reduction is supported by data from two independent spaceborne instruments: TROPOMI and OMI. In 2020, the decline was partly due to the impact of the COVID-19 lockdowns, while in 2021 and 2022, it was driven by stringent air pollution controls in the industry and transport sectors. The satellite-based inversion system developed in this study represents a significant advancement in real-time monitoring of regional air pollution emissions from space. The study also examines the spatial and temporal variations in NOx emissions across different provinces in China, highlighting the impact of socio-economic factors and air pollution control measures. Provinces with high levels of industrialization and population saw substantial reductions in NOx emissions, while others experienced increases. The findings indicate that air pollution control measures have been effective in reducing NOx emissions, although the reduction in CO2 emissions has not been as pronounced due to increased fossil fuel consumption. The study acknowledges uncertainties and limitations in the NOx emission estimation, including potential errors from satellite data and model simulations. Despite these challenges, the results are robust and consistent across different methods and data sources. The study concludes that China's ongoing clean air measures have led to significant reductions in NOx emissions, offering a viable blueprint for other countries facing similar air quality challenges. However, achieving coordinated governance of air quality and climate pollutants remains a challenge under the current energy structure. The satellite-based inversion system developed in this study could be a crucial tool for tracking air pollutant emissions by sector with low latency.This study investigates the trends and drivers of anthropogenic nitrogen oxide (NOx) emissions in China from 2020 to 2022. Using satellite observations and atmospheric inversion techniques, the research reveals a consistent decline in NOx emissions during this period, despite increased fossil fuel consumption. The reduction is supported by data from two independent spaceborne instruments: TROPOMI and OMI. In 2020, the decline was partly due to the impact of the COVID-19 lockdowns, while in 2021 and 2022, it was driven by stringent air pollution controls in the industry and transport sectors. The satellite-based inversion system developed in this study represents a significant advancement in real-time monitoring of regional air pollution emissions from space. The study also examines the spatial and temporal variations in NOx emissions across different provinces in China, highlighting the impact of socio-economic factors and air pollution control measures. Provinces with high levels of industrialization and population saw substantial reductions in NOx emissions, while others experienced increases. The findings indicate that air pollution control measures have been effective in reducing NOx emissions, although the reduction in CO2 emissions has not been as pronounced due to increased fossil fuel consumption. The study acknowledges uncertainties and limitations in the NOx emission estimation, including potential errors from satellite data and model simulations. Despite these challenges, the results are robust and consistent across different methods and data sources. The study concludes that China's ongoing clean air measures have led to significant reductions in NOx emissions, offering a viable blueprint for other countries facing similar air quality challenges. However, achieving coordinated governance of air quality and climate pollutants remains a challenge under the current energy structure. The satellite-based inversion system developed in this study could be a crucial tool for tracking air pollutant emissions by sector with low latency.