| Title: | Multi-factor reconciliation of discrepancies in ozone-precursor sensitivity retrieved from observation- and emission-based models |
| Author(s): | Xu D; Yuan Z; Wang M; Zhao K; Liu X; Duan Y; Fu Q; Wang Q; Jing S; Wang H; Zhao X; |
| Address: | "School of Environment and Energy, South China University of Technology, Guangzhou 510006, China. School of Environment and Energy, South China University of Technology, Guangzhou 510006, China. Electronic address: zibing@scut.edu.cn. Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China. Electronic address: wangming@nuist.edu.cn. Shanghai Environmental Monitoring Center, Shanghai 200235, China. State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China. Nanjing Intelligent Environmental Science and Technology Co., Ltd., Nanjing 211800, China" |
| DOI: | 10.1016/j.envint.2021.106952 |
| ISSN/ISBN: | 1873-6750 (Electronic) 0160-4120 (Linking) |
| Abstract: | "Ground-level O(3) pollution has been continuously worsening in China despite gradual improvement in other major pollutant levels. Understanding the sensitivity of O(3) production to its precursors (OPS) is a prerequisite for formulating effective O(3) control measures, but this has been hampered by significant discrepancies in OPS produced by traditional identification approaches using observation-based models (OBM) and emission-based models (EBM). In this study, by applying OBM and EBM in parallel within a month having significant O(3) pollution in Shanghai, China, we demonstrated that a lack of carbonyl input, overestimation in NO(2) monitoring data, and differences in simulation period and emission reduction area were the core factors leading to OPS discrepancies, and that a reliable OPS cannot be obtained unless these factors are reconciled. By collectively addressing these factors, the number of days with a consistent OPS from both models increased from 6-7 to 20-21 in a month, and the R value defined to quantify the discrepancy decreased by approximately 55%. The contributions of these factors to OPS discrepancy differed greatly in urban and suburban settings, mainly caused by differences in pollutant emission and transport characteristics. Overall, OPS identified solely by OBM or EBM is associated with great uncertainty, while reliable OPS estimation can be achieved by a collective application of OBM and EBM with consensus on the above factors. The method demonstrated here could be applied to other photo-chemically active regions worldwide as part of efforts to address ozone pollution" |
| Keywords: | *Air Pollutants/analysis *Air Pollution China Environmental Monitoring *Ozone/analysis *Volatile Organic Compounds/analysis Discrepancy reconciliation Emission-based model O(3) precursor sensitivity Observation-based model Ozone; |
| Notes: | "MedlineXu, Danni Yuan, Zibing Wang, Ming Zhao, Kaihui Liu, Xuehui Duan, Yusen Fu, Qingyan Wang, Qian Jing, Shengao Wang, Hongli Zhao, Xin eng Research Support, Non-U.S. Gov't Netherlands 2021/10/31 Environ Int. 2022 Jan; 158:106952. doi: 10.1016/j.envint.2021.106952. Epub 2021 Oct 28" |
