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Improved Anthropogenic SO2 Retrieval from High-Spatial-Resolution Satellite and its Application during the COVID-19 Pandemic.

Congzi XiaCheng LiuZhaonan CaiXiaonan DuanQihou HuFei ZhaoHaoran LiuXiangguang JiChengxin ZhangYi Liu
Published in: Environmental science & technology (2021)
Sulfur dioxide (SO2) measured by satellites is widely used to estimate anthropogenic emissions. The Sentinel-5 Precursor (S-5P) operational SO2 product is overestimated compared to the ground-based multiaxis differential optical absorption spectroscopy (MAX-DOAS) measurements in China and shows an opposite variation to the surface measurements, which limits the application of TROPOspheric monitoring instrument (TROPOMI) products in emissions research. Radiometric calibration, a priori profiles, and fitting windows might cause the overestimation of S-5P operational SO2 product. Here, we improve the optimal-estimation-based algorithm through several calibration methods. The improved retrieval agrees reasonably well with the ground-based measurements (R > 0.70, bias <13.7%) and has smaller biases (-28.9%) with surface measurements over China and India. It revealed that the SO2 column in March 2020 decreased by 51.6% compared to March 2019 due to the lockdown for curbing the spread of the COVID-19 pandemic, and there was a decrease of 50% during the lockdown than those after the lockdown, similar to the surface measurement trend, while S-5P operational SO2 product showed an unrealistic increase of 19%. In India, the improved retrieval identified obvious "hot spots" and observed a 30% decrease of SO2 columns during the lockdown.
Keyphrases
  • high resolution
  • single molecule
  • machine learning
  • liquid chromatography
  • deep learning
  • single cell
  • heavy metals
  • patient reported outcomes
  • life cycle
  • tandem mass spectrometry
  • water quality