Assimilating surface PM2.5 and ozone measurements to improve health exposure assessment and air quality forecasting in South China
Project Description
This proposal requests support for research on the development of a system to assimilate surface measurements of PM2.5, ozone (O3) and nitrogen dioxide (NO2) simultaneously to obtain better spatiotemporal variations of PM2.5 and O3 concentrations, to reduce uncertainties in health exposure assessment, and to improve the accuracy of air quality forecasting in South China. Chemical data assimilation with advanced coupled meteorology-chemistry models has recently been developed and applied as a useful approach to reduce model errors in both aerosols and meteorological variables, due to the nature of coupled models that treat aerosol-weather interactions. Aerosol data assimilation with coupled models over China has been investigated by several studies, while the exploration of O3 assimilation is still limited. However, O3 pollution is also a prominent environmental issue in China, especially in South China, posing a great threat to human health and vegetation growth. Estimating the impacts of air pollution on health, climate and ecosystem, and implementing emergency responses to air pollution episodes require better representations of the spatiotemporal variations of air pollutants and accurate air quality forecasts.
Based on our previous extension to assimilate PM2.5 measurements, two additional control variables (O3 and NO2) are proposed to be included in the Gridpoint Statistical Interpolation (GSI) data assimilation system. The developed system will be applied in South China with the WRF- Chem model (Weather Research and Forecasting model coupled with Chemistry) and CNEMC (China National Environmental Modeling Center) surface measurements to obtain spatiotemporal variations of PM2.5 and O3 concentrations, to estimate health exposure, and to demonstrate the improvements in air quality forecasts. The methodology and findings from this project can be applied easily to other regions.
Project Investigator
Professor GAO Meng (Academy of Geography, Sociology and International Studies)
Publications
- Wang, F., Xu, Y., Patel, P. N., Gautam, R., Gao, M., Liu, C., ... & McElroy, M. B. (2024). Arctic amplification–induced decline in West and South Asia dust warrants stronger antidesertification toward carbon neutrality. Proceedings of the National Academy of Sciences, 121(14), e2317444121. https://www.pnas.org/doi/abs/10.1073/pnas.2317444121
- Wang, F., Gao, M., Liu, C., Zhao, R., & McElroy, M. B. (2024). Uniformly elevated future heat stress in China driven by spatially heterogeneous water vapor changes. Nature Communications, 15(1), 4522. https://www.nature.com/articles/s41467-024-48895-w
- Gao, M., Wang, F., Ding, Y., Wu, Z., Xu, Y., Lu, X., ... & McElroy, M. B. (2023). Large-scale climate patterns offer preseasonal hints on the co-occurrence of heat wave and O3 pollution in China. Proceedings of the National Academy of Sciences, 120(26), e2218274120. https://www.pnas.org/doi/abs/10.1073/pnas.2218274120
- Xiao, X., Xu, Y., Zhang, X., Wang, F., Lu, X., Cai, Z., ... & Gao, M. (2022). Amplified upward trend of the joint occurrences of heat and ozone extremes in China over 2013–20. Bulletin of the American Meteorological Society, 103(5), E1330-E1342. https://journals.ametsoc.org/view/journals/bams/103/5/BAMS-D-21-0222.1.xml
- Wang, F., Carmichael, G. R., Zhang, X., Xiao, X., & Gao, M. (2022). Pollution severity-regulated effects of roof strategies on China’s winter PM2. 5. npj Climate and Atmospheric Science, 5(1), 55. https://www.nature.com/articles/s41612-022-00278-y
- Zhang, X., Xiao, X., Wang, F., Brasseur, G., Chen, S., Wang, J., & Gao, M. (2022). Observed sensitivities of PM2. 5 and O3 extremes to meteorological conditions in China and implications for the future. Environment International, 168, 107428. https://www.sciencedirect.com/science/article/pii/S0160412022003555
- Wang, F., Carmichael, G. R., Wang, J., Chen, B., Huang, B., Li, Y., ... & Gao, M. (2022). Circulation-regulated impacts of aerosol pollution on urban heat island in Beijing. Atmospheric Chemistry and Physics, 22(20), 13341-13353. https://acp.copernicus.org/articles/22/13341/2022/acp-22-13341-2022.html
- Zhang, X., Xiao, X., Wang, F., Yang, Y., Liao, H., Wang, S., & Gao, M. (2023). Discordant future climate-driven changes in winter PM2. 5 pollution across India under a warming climate. Elementa: Science of the Anthropocene, 11(1). https://online.ucpress.edu/elementa/article/11/1/00149/196804
- Zhang, X., Zhou, C., Zhang, Y., Lu, X., Xiao, X., Wang, F., ... & Gao, M. (2023). Where to place methane monitoring sites in China to better assist carbon management. npj Climate and Atmospheric Science, 6(1), 32. https://www.nature.com/articles/s41612-023-00359-6
- Yang, Q., Kim, J., Cho, Y., Lee, W. J., Lee, D. W., Yuan, Q., ... & Gao, M. (2023). A synchronized estimation of hourly surface concentrations of six criteria air pollutants with GEMS data. npj Climate and Atmospheric Science, 6(1), 94. https://www.nature.com/articles/s41612-023-00407-1
- Zhang, X., Lu, X., Wang, F., Zhou, W., Wang, P., & Gao, M. (2024). Enhanced late spring ozone in Southern China by early onset of the South China Sea summer monsoon. Journal of Geophysical Research: Atmospheres, 129(4), e2023JD039029. https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2023JD039029
