TY - JOUR
T1 - Estimating the variability in NOx emissions from Wuhan with TROPOMI NO2 data during 2018 to 2023
AU - Zhang, Qianqian
AU - Boersma, K.F.
AU - Van Der Laan, Chiel
AU - Mols, Alba
AU - Zhao, Bin
AU - Li, Shengyue
AU - Pan, Yuepeng
PY - 2025/3/19
Y1 - 2025/3/19
N2 - Accurate NOx emission estimates are required to better understand air pollution, investigate the effectiveness of emission restrictions, and develop effective emission control strategies. This study investigates and demonstrates the ability and uncertainty of the superposition column model in combination with the TROPOspheric Monitoring Instrument (TROPOMI) tropospheric NO2 column data to estimate city-scale NOx emissions and chemical lifetimes and their variabilities. Using the recently improved TROPOMI tropospheric NO2 column product (v2.4-2.6), we derive daily NOx emissions and chemical lifetimes over the city of Wuhan for 372 d with full NO2 coverage between May 2018 and December 2023 and validate the results with bottom-up emission inventories. We find an insignificant weekly cycle of NOx emissions for Wuhan. We estimate a summer-to-winter emission ratio of 0.77, which may be overestimated to some extent but is still lower than suggested by the bottom-up inventories. We find a steady decline in NOx emissions from 2019 to 2023 (except for the sudden drop in 2020 caused by the COVID-19 lockdown), indicating the success of the emission control strategy. The superposition model method results in an g15 % lower estimation of NOx emissions when the wind direction is from distinct upwind NO2 hotspots compared to other wind directions, indicating the need to improve the approach for cities that are not relatively isolated pollution hotspots. The method tends to underestimate NOx emissions and lifetimes when the wind speed is > 5-7 m s-1, and, in Wuhan's case, the underestimation is g4 % for the emissions and g 8 % for the chemical lifetime. The results of this work nevertheless confirm the strength of the superposition column model in estimating urban NOx emissions with reasonable accuracy.
AB - Accurate NOx emission estimates are required to better understand air pollution, investigate the effectiveness of emission restrictions, and develop effective emission control strategies. This study investigates and demonstrates the ability and uncertainty of the superposition column model in combination with the TROPOspheric Monitoring Instrument (TROPOMI) tropospheric NO2 column data to estimate city-scale NOx emissions and chemical lifetimes and their variabilities. Using the recently improved TROPOMI tropospheric NO2 column product (v2.4-2.6), we derive daily NOx emissions and chemical lifetimes over the city of Wuhan for 372 d with full NO2 coverage between May 2018 and December 2023 and validate the results with bottom-up emission inventories. We find an insignificant weekly cycle of NOx emissions for Wuhan. We estimate a summer-to-winter emission ratio of 0.77, which may be overestimated to some extent but is still lower than suggested by the bottom-up inventories. We find a steady decline in NOx emissions from 2019 to 2023 (except for the sudden drop in 2020 caused by the COVID-19 lockdown), indicating the success of the emission control strategy. The superposition model method results in an g15 % lower estimation of NOx emissions when the wind direction is from distinct upwind NO2 hotspots compared to other wind directions, indicating the need to improve the approach for cities that are not relatively isolated pollution hotspots. The method tends to underestimate NOx emissions and lifetimes when the wind speed is > 5-7 m s-1, and, in Wuhan's case, the underestimation is g4 % for the emissions and g 8 % for the chemical lifetime. The results of this work nevertheless confirm the strength of the superposition column model in estimating urban NOx emissions with reasonable accuracy.
U2 - 10.5194/acp-25-3313-2025
DO - 10.5194/acp-25-3313-2025
M3 - Article
AN - SCOPUS:105000441509
SN - 1680-7316
VL - 25
SP - 3313
EP - 3326
JO - Atmospheric Chemistry and Physics
JF - Atmospheric Chemistry and Physics
IS - 6
ER -