title: A case study of surface ozone source apportionment during a high concentration episode, under frequent shifting wind conditions over the Yangtze River Delta, China.
abstract: Surface ozone is an environmental issue occurring at several scales, ranging from local to continental. One of the most developed regions in China, the Yangtze River Delta (YRD), experiences severe tropospheric ozone problem. Hence, quantifying the contributions from various geographical source regions is helpful for better understanding the regional ozone problem. Ozone source apportionment studies can provide relevant information for designing suitable air pollution protection strategies. In the present work, the WRF-Chem model coupled with an online ozone tagging method is applied to a case study, with the objective of exploring the ozone contributions to the surface ozone from different source regions over the YRD region, during a frequent wind-shifting period. Our results show that the YRD was highly affected by the upwind source regions bearing high values both ozone and its precursors. The contribution from the source region outside the main air pollution zones in the Central Eastern China (super regional contribution) was also important, accounting for more than 30 ppb of daytime maximum mean ozone concentrations. Ozone arising from increased local and regional emissions during high-concentration events was more significant than super regional contribution. It reveals that the ozone from Anhui region was transported through vertical mixing and horizontal advection to receptor areas in the YRD during the study time focus. Chemical process contributed significantly at ground and high altitude levels of 500 and 1000 m. However, most of the ozone from the remote regions of Henan and Hubei provinces was transported to the receptor of Nanjing through physical processes. The vertical mixing process played a crucial positive role at super regional scales, with regard to the formation of surface ozone over the YRD region during the addressed time interval.
authors.affiliation: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China; Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, China.
authors.forename: Jinhui
authors.initials: J
authors.lastname: Gao
authors.affiliation: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China; Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, China. Electronic address: binzhu@nuist.edu.cn.
authors.forename: Bin
authors.initials: B
authors.lastname: Zhu
authors.affiliation: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China; Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Xiao
authors.affiliation: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China; Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, China.
authors.forename: Hanqing
authors.initials: H
authors.lastname: Kang
authors.affiliation: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China; Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, China.
authors.forename: Xuewei
authors.initials: X
authors.lastname: Hou
authors.affiliation: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China; Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, China.
authors.forename: Ping
authors.initials: P
authors.lastname: Shao
keywords: Ozone tagging method; Source apportionment; WRF-Chem; YRD