RESUMEN
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 O3 pollution in 27 major Chinese cities during lockdowns. We found that there was an increase in O3 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 O3 in most cities. In cities with over 80% transportation reductions and temperature fluctuations within -2 to 2 °C, the increases in O3 concentrations were mainly attributable to reductions in nitrogen oxide (NOx) emissions. In cities that experienced heatwaves and droughts, increases in the O3 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 O3 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 O3 pollution.
RESUMEN
Nitrate (NO3-) has been identified as a key component of particulate matter (PM2.5) in China. However, there is still a lack of understanding regarding its sources and how it forms, especially in the context of high-frequency and long-term data. In this study, NO3- levels were observed on an hourly basis over an almost three-year period at an urban site in the Pearl River Delta (PRD) region, China, from January 2019 to December 2021. The results reveal an average daily NO3- concentration ranging from 0.08 µg m-3 to 61.69 µg m-3, constituting 11.9 ± 12.5 % of PM2.5. This percentage rose to as high as 57 % during pollution episodes, highlighting NO3-'s significant role in pollution formation. The ammonia-rich environment was found to be the most important factor in promoting NO3- formation. Positive Matrix Factorization (PMF) analysis indicates that the primary sources of NO3- in the PRD region were vehicle emissions (43.8 ± 21.2 %) and coal combustion (39.1 ± 21.5 %), with shipping emissions, sea salt, soil dust and industrial emissions + biomass burning following in importance. Regarding source areas, the primary contributor of vehicle emissions was predominantly from the PRD region, whereas the coal combustion, aside from local contributions, also originates from the northern region. From a long-term perspective, NO3- pollution has remained relatively stable since the summer of 2020. Concurrently, coal combustion source has shown a localization trend. These insights derived from the extensive, high-frequency observation presented in this study serve as a valuable reference for devising strategies to control NO3- and PM2.5 in the PRD region and China.