| Title: | "Machine learning and theoretical analysis release the non-linear relationship among ozone, secondary organic aerosol and volatile organic compounds" |
| Author(s): | Wang F; Zhang Z; Wang G; Wang Z; Li M; Liang W; Gao J; Wang W; Chen D; Feng Y; Shi G; |
| Address: | "State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China. State Key Laboratory on Odor Pollution Control, Tianjin Academy of Environmental Sciences, Tianjin 300191, China. Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution Jinan University, Institute of Mass Spectrometry and Atmospheric Environment, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China. Trusted AI System Laboratory, College of Computer Science, Nankai University, Tianjin 300350, China. Electronic address: kevinwangwei@nankai.edu.cn. Key Laboratory of Civil Aviation Thermal Hazards Prevention and Emergency Response, Civil Aviation University of China, Tianjin 300300, China. State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China. Electronic address: nksgl@nankai.edu.cn" |
| DOI: | 10.1016/j.jes.2021.07.026 |
| ISSN/ISBN: | 1001-0742 (Print) 1001-0742 (Linking) |
| Abstract: | "Fine particulate matter (PM(2.5)) and ozone (O(3)) pollutions are prevalent air quality issues in China. Volatile organic compounds (VOCs) have significant impact on the formation of O(3) and secondary organic aerosols (SOA) contributing PM(2.5). Herein, we investigated 54 VOCs, O(3) and SOA in Tianjin from June 2017 to May 2019 to explore the non-linear relationship among O(3), SOA and VOCs. The monthly patterns of VOCs and SOA concentrations were characterized by peak values during October to March and reached a minimum from April to September, but the observed O(3) was exactly the opposite. Machine learning methods resolved the importance of individual VOCs on O(3) and SOA that alkenes (mainly ethylene, propylene, and isoprene) have the highest importance to O(3) formation; alkanes (C(n), n >/= 6) and aromatics were the main source of SOA formation. Machine learning methods revealed and emphasized the importance of photochemical consumptions of VOCs to O(3) and SOA formation. Ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP) calculated by consumed VOCs quantitatively indicated that more than 80% of the consumed VOCs were alkenes which dominated the O(3) formation, and the importance of consumed aromatics and alkenes to SOAFP were 40.84% and 56.65%, respectively. Therein, isoprene contributed the most to OFP at 41.45% regardless of the season, while aromatics (58.27%) contributed the most to SOAFP in winter. Collectively, our findings can provide scientific evidence on policymaking for VOCs controls on seasonal scales to achieve effective reduction in both SOA and O(3)" |
| Keywords: | Aerosols/analysis *Air Pollutants/analysis Alkenes/analysis China Environmental Monitoring Machine Learning *Ozone/analysis Particulate Matter/analysis *Volatile Organic Compounds/analysis Ozone formation potential Photochemical consumption Secondary orga; |
| Notes: | "MedlineWang, Feng Zhang, Zhongcheng Wang, Gen Wang, Zhenyu Li, Mei Liang, Weiqing Gao, Jie Wang, Wei Chen, Da Feng, Yinchang Shi, Guoliang eng Netherlands 2022/04/24 J Environ Sci (China). 2022 Apr; 114:75-84. doi: 10.1016/j.jes.2021.07.026. Epub 2022 Jan 14" |
