Quantifying daily NO_x and CO₂ emissions from Wuhan using satellite observations from TROPOMI and OCO-2

Abstract. Quantification and control of NO_x and CO₂ emissions are important across the world to limit adverse climate change. We present a new top-down method, an improved superposition column model to estimate day-to-day NO_x and CO₂ emissions from the large city of Wuhan, China, located in a polluted background. The lasted released version 2.3.1 TROPOMI NO2 columns and the version 10r of the OCO-2 observed CO₂ mixing ratio are employed. Our estimated NO_x and CO₂ emissions from Wuhan are verified against bottom-up inventories with small deviations (< 3 %). Based on the estimated CO₂ emissions, we also predicted daily CO₂ column mixing ratio enhancements, which match well with OCO-2 observations (< 5 % bias, within ±0.3 ppm). We capture the day-to-day variation of NO_x and CO₂ emissions from Wuhan in 2019–2020, which does not reveal a substantial ‘weekend reduction’ but does show a clear ‘holiday reduction’ in the NO_x and CO₂ emissions. Our method also quantifies the abrupt decrease and slow rebound of NO_x and CO₂ emissions due to the Wuhan lockdown in early 2020. This work demonstrates the improved superposition model to be a promising new tool for the quantification of city NO_x and CO₂ emissions, allowing policy makers to gain real-time information into spatial-temporal emission patterns and the effectiveness of carbon and nitrogen regulation in urban environments.