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Environ Sci Technol
Title: | Drivers of High Concentrations of Secondary Organic Aerosols in Northern China during the COVID-19 Lockdowns |
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Author(s): | Chang X; Zheng H; Zhao B; Yan C; Jiang Y; Hu R; Song S; Dong Z; Li S; Li Z; Zhu Y; Shi H; Jiang Z; Xing J; Wang S; |
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Address: | "State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China. State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China. Transport Planning and Research Institute, Ministry of Transport, Laboratory of Transport Pollution Control and Monitoring Technology, Beijing 100028, China. Joint International Research Laboratory of Atmospheric and Earth System Research, School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China. Institute for Atmospheric and Earth System Research/Physics, Faculty of Science, University of Helsinki, Helsinki 00560, Finland. 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. Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, College of Environment and Energy, Guangzhou Higher Education Mega Center, South China University of Technology, Guangzhou 510006, China. Key Laboratory of Middle Atmosphere and Global Environment Observation, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100045, China" |
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Journal Title: | Environ Sci Technol |
Year: | 2023 |
Volume: | 20230331 |
Issue: | 14 |
Page Number: | 5521 - 5531 |
DOI: | 10.1021/acs.est.2c06914 |
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ISSN/ISBN: | 1520-5851 (Electronic) 0013-936X (Linking) |
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Abstract: | "During the COVID-19 lockdown in early 2020, observations in Beijing indicate that secondary organic aerosol (SOA) concentrations increased despite substantial emission reduction, but the reasons are not fully explained. Here, we integrate the two-dimensional volatility basis set into a state-of-the-art chemical transport model, which unprecedentedly reproduces organic aerosol (OA) components resolved by the positive matrix factorization based on aerosol mass spectrometer observations. The model shows that, for Beijing, the emission reduction during the lockdown lowered primary organic aerosol (POA)/SOA concentrations by 50%/18%, while deteriorated meteorological conditions increased them by 30%/119%, resulting in a net decrease in the POA concentration and a net increase in the SOA concentration. Emission reduction and meteorological changes both led to an increased OH concentration, which accounts for their distinct effects on POA and SOA. SOA from anthropogenic volatile organic compounds and organics with lower volatility contributed 28 and 62%, respectively, to the net SOA increase. Different from Beijing, the SOA concentration decreased in southern Hebei during the lockdown because of more favorable meteorology. Our findings confirm the effectiveness of organic emission reductions and meanwhile reveal the challenge in controlling SOA pollution that calls for large organic precursor emission reductions to rival the adverse impact of OH increase" |
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Keywords: | Humans *Air Pollutants/analysis *covid-19 Communicable Disease Control Respiratory Aerosols and Droplets China Cmaq COVID-19 lockdown emission control efficacy organic aerosol two-dimensional volatility basis set; |
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Notes: | "MedlineChang, Xing Zheng, Haotian Zhao, Bin Yan, Chao Jiang, Yueqi Hu, Ruolan Song, Shaojie Dong, Zhaoxin Li, Shengyue Li, Zeqi Zhu, Yun Shi, Hongrong Jiang, Zhe Xing, Jia Wang, Shuxiao eng Research Support, Non-U.S. Gov't 2023/04/01 Environ Sci Technol. 2023 Apr 11; 57(14):5521-5531. doi: 10.1021/acs.est.2c06914. Epub 2023 Mar 31" |
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Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 16-11-2024
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