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https://doi.org/10.5194/egusphere-2024-1903
https://doi.org/10.5194/egusphere-2024-1903
22 Jul 2024
 | 22 Jul 2024

Identifying Missing Sources and Reducing NOx Emissions Uncertainty over China using Daily Satellite Data and a Mass-Conserving Method

Lingxiao Lu, Jason Blake Cohen, Kai Qin, Xiaolu Li, and Qin He

Abstract. This study applies a mass-conserving model-free analytical approach to daily observations on a grid-by-grid basis of NO2 from TROPOMI, to rapidly and flexibly quantify changing and emerging sources of NOx emissions at high spatial and daily temporal resolution. The inverted NOx emissions and optimized underlying ranges include quantification of the underlying atmospheric in-situ processing, transport and physics. The results are presented over three changing regions in China, including Shandong and Hubei which are rapidly urbanizing and not frequently addressed in the global literature. The day-to-day and grid-by-grid emissions are found to be 1.96±0.27 µg/m2/s on pixels with available priori values (1.94 µg/m2/s), while 1.22±0.63 µg/m2/s extra emissions are found on pixels in which the a priori inventory is lower than 0.3 µg/m2/s. Source attribution based on thermodynamics of combustion temperature, atmospheric transport, and in-situ atmospheric processing successfully identify 5 different industrial source types. Emissions from these industrial sites adjacent to the Yangtze River are found to be 160.5±68.9 Kton/yr (163 % higher than the a priori) consistent with missing light and medium industry located along the river, contradicting previous studies attributing the water as the source of NOx emissions. Finally, the results demonstrate those pixels with an uncertainty larger than day-to-day variability, providing quantitative information for placement of future monitoring stations. It is hoped that these findings will drive a new approach to top-down emissions estimates, in which emissions are quantified and updated continuously based consistently on remotely sensed measurements and associated uncertainties that actively reflect land-use changes and quantify misidentified emissions, while quantifying new datasets to inform the bottom-up emissions community.

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Lingxiao Lu, Jason Blake Cohen, Kai Qin, Xiaolu Li, and Qin He

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-1903', Anonymous Referee #1, 09 Aug 2024
  • RC2: 'Comment on egusphere-2024-1903', Anonymous Referee #2, 28 Aug 2024
Lingxiao Lu, Jason Blake Cohen, Kai Qin, Xiaolu Li, and Qin He
Lingxiao Lu, Jason Blake Cohen, Kai Qin, Xiaolu Li, and Qin He

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Short summary
This study assimilates NO2 observations from TROPOMI in a mass-conserving manner and inverts daily NOx emissions. The results are presented over rapidly changing regions in China. Attribution is quantified using local observations and inverted proxy of combustion temperature. There are significant sources identified in some areas which are not in existing databases, especially small and medium industries along the Yangtze River. We also demonstrate which emissions are robust and which are not.