Dissecting Drivers of Ozone Pollution during the 2022 Multicity Lockdowns in China Sheds Light on Future Control Direction

ENVIRONMENTAL SCIENCE & TECHNOLOGY(2024)

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摘要
In 2022, many Chinese cities experienced lockdowns and heatwaves. We analyzed ground and satellite data using machine learning to elucidate chemical and meteorological drivers of changes in O-3 pollution in 27 major Chinese cities during lockdowns. We found that there was an increase in O-3 concentrations in 23 out of 27 cities compared with the corresponding period in 2021. Random forest modeling indicates that emission reductions in transportation and other sectors, as well as the changes in meteorology, increased the level of O-3 in most cities. In cities with over 80% transportation reductions and temperature fluctuations within -2 to 2 degrees C, the increases in O-3 concentrations were mainly attributable to reductions in nitrogen oxide (NOx) emissions. In cities that experienced heatwaves and droughts, increases in the O-3 concentrations were primarily driven by increases in temperature and volatile organic compound (VOC) emissions, and reductions in NOx concentrations from ground transport were offset by increases in emissions from coal-fired power generation. Despite 3-99% reduction in passenger volume, most cities remained VOC-limited during lockdowns. These findings demonstrate that to alleviate urban O-3 pollution, it will be necessary to further reduce industrial emissions along with transportation sources and to take into account the climate penalty and the impact of heatwaves on O-3 pollution.
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ozone pollution,machine learning,2022 lockdown,meteorological and chemical driver
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