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Liu S, Yang S, Chen D, Mao L, Cheng X, Zhou Z, Pei C, Li M, Cheng C. Influence of ozone pollution on the mixing state and formation of oxygenated organics containing single particles. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:171880. [PMID: 38531461 DOI: 10.1016/j.scitotenv.2024.171880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/17/2024] [Accepted: 03/20/2024] [Indexed: 03/28/2024]
Abstract
The formation and aging processes of oxygenated organic molecules (OOMs) are important for understanding the formation mechanisms of secondary organic aerosols (SOAs) in the field. In this study, we investigated the mixing states of OOM particles by identifying several oxygenated species along with the distributions of secondary organic carbon (SOC) during both clean and ozone (O3)-polluted periods in July and September of 2022 in Guangzhou, China. OOM-containing particles accounted for 57 % and 49 % of the total detected single particles in July and September, respectively. Most of the OOM particles were internally mixed with sulfate and nitrate, while elemental carbon and hydrocarbon species were absent. Despite the higher SOC/OC ratio in September (81 %) than it in July (72 %), comparative investigations of the mass spectra, diurnal patterns, and distributions of OOM particles revealed the same composition and aging states of OOMs in two O3 pollution periods. As the O3 concentration increased from the clean to the polluted periods, the ratio of SOC to OC increased along with the relative abundance of secondary OOM particles among total OOM particles. In contrast, the relative abundance of OC-type OOM particles gradually decreased, indicating the conversion of hydrocarbon species into OOMs as the SOC/OC ratio increased. Both the bulk analysis of SOC from filter measurement and the mixing states of OOM particles suggested that OOM production and degree of oxidation were higher in the O3-polluted periods than in the clean periods. These results elucidate the effects of O3 pollution on the OOM formation process and offer new perspectives for the joint investigation of SOA production based on filter sampling and single-particle measurements.
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Affiliation(s)
- Sulin Liu
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Suxia Yang
- Guangzhou Research Institute of Environment Protection Co., Ltd, Guangzhou 510620, China
| | - Duanying Chen
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Liyuan Mao
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Xiaoya Cheng
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Zhen Zhou
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Chenglei Pei
- Guangzhou Ecological and Environmental Monitoring Center of Guangdong Province, Guangzhou 510030, China
| | - Mei Li
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China.
| | - Chunlei Cheng
- Institute of Mass Spectrometry and Atmospheric Environment, Guangdong Provincial Engineering Research Center for on-line source apportionment system of air pollution, Jinan University, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China; State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University, Haikou 570228, China; State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy Science, Xi'an 710061, China.
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Li J, Hua C, Ma L, Chen K, Zheng F, Chen Q, Bao X, Sun J, Xie R, Bianchi F, Kerminen VM, Petäjä T, Kulmala M, Liu Y. Key drivers of the oxidative potential of PM 2.5 in Beijing in the context of air quality improvement from 2018 to 2022. ENVIRONMENT INTERNATIONAL 2024; 187:108724. [PMID: 38735076 DOI: 10.1016/j.envint.2024.108724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 04/30/2024] [Accepted: 05/06/2024] [Indexed: 05/14/2024]
Abstract
The mass concentration of atmospheric particulate matter (PM) has been continuously decreasing in the Beijing-Tianjin-Hebei region. However, health endpoints do not exhibit a linear correlation with PM mass concentrations. Thus, it is urgent to clarify the prior toxicological components of PM to further improve air quality. In this study, we analyzed the long-term oxidative potential (OP) of water-soluble PM2.5, which is generally considered more effective in assessing hazardous exposure to PM in Beijing from 2018 to 2022 based on the dithiothreitol assay and identified the crucial drivers of the OP of PM2.5 based on online monitoring of air pollutants, receptor model, and random forest (RF) model. Our results indicate that dust, traffic, and biomass combustion are the main sources of the OP of PM2.5 in Beijing. The complex interactions of dust particles, black carbon, and gaseous pollutants (nitrogen dioxide and sulfur dioxide) are the main factors driving the OP evolution, in particular, leading to the abnormal rise of OP in Beijing in 2022. Our data shows that a higher OP is observed in winter and spring compared to summer and autumn. The diurnal variation of the OP is characterized by a declining trend from 0:00 to 14:00 and an increasing trend from 14:00 to 23:00. The spatial variation in OP of PM2.5 was observed as the OP in Beijing is lower than that in Shijiazhuang, while it is higher than that in Zhenjiang and Haikou, which is primarily influenced by the distribution of black carbon. Our results are of significance in identifying the key drivers influencing the OP of PM2.5 and provide new insights for advancing air quality improvement efforts with a focus on safeguarding human health in Beijing.
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Affiliation(s)
- Jinwen Li
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Chenjie Hua
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Li Ma
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Kaiyun Chen
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Feixue Zheng
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Qingcai Chen
- School of Environmental Science and Engineering, Shaanxi University of Science and Technology, Xi'an 710021, China
| | - Xiaolei Bao
- Hebei Chemical & Pharmaceutical College, Shijiazhuang 050026, China
| | - Juan Sun
- Jiangsu Nanjing Environmental Monitoring Center, Nanjing 210019, China
| | - Rongfu Xie
- College of Ecology and Environment, Hainan University, Haikou 570228, China
| | - Federico Bianchi
- Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki 00014, Finland
| | - Veli-Matti Kerminen
- Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki 00014, Finland
| | - Tuukka Petäjä
- Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki 00014, Finland
| | - Markku Kulmala
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China; Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki 00014, Finland
| | - Yongchun Liu
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China.
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Zhang ZE, Li J, Zhang R, Tian C, Sun Z, Li T, Han M, Yu K, Zhang G. Increase in Agricultural-Derived NH x and Decrease in Coal Combustion-Derived NO x Result in Atmospheric Particulate N-NH 4+ Surpassing N-NO 3- in the South China Sea. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:6682-6692. [PMID: 38547356 DOI: 10.1021/acs.est.3c09173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/17/2024]
Abstract
The atmospheric deposition of anthropogenic active nitrogen significantly influences marine primary productivity and contributes to eutrophication. The form of nitrogen deposition has been evolving annually, alongside changes in human activities. A disparity arises between observation results and simulation conclusions due to the limited field observation and research in the ocean. To address this gap, our study undertook three field cruises in the South China Sea in 2021, the largest marginal sea of China. The objective was to investigate the latest atmospheric particulate inorganic nitrogen deposition pattern and changes in nitrogen sources, employing nitrogen-stable isotopes of nitrate (δ15N-NO3-) and ammonia (δ15N-NH4+) linked to a mixing model. The findings reveal that the N-NH4+ deposition generally surpasses N-NO3- deposition, attributed to a decline in the level of NOx emission from coal combustion and an upswing in the level of NHx emission from agricultural sources. The disparity in deposition between N-NH4+ and N-NO3- intensifies from the coast to the offshore, establishing N-NH4+ as the primary contributor to oceanic nitrogen deposition, particularly in ocean background regions. Fertilizer (33 ± 21%) and livestock (20 ± 6%) emerge as the primary sources of N-NH4+. While coal combustion continues to be a significant contributor to marine atmospheric N-NO3-, its proportion has diminished to 22 (Northern Coast)-35% (background area) due to effective NOx emission controls by the countries surrounding the South China Sea, especially the Chinese Government. As coal combustion's contribution dwindles, the significance of vessel and marine biogenic emissions grows. The daytime higher atmospheric N-NO3- concentration and lower δ15N-NO3- compared with nighttime further underscore the substantial role of marine biogenic emissions.
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Affiliation(s)
- Zheng-En Zhang
- State Key Laboratory of Organic Geochemistry, Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, and Guangdong-Hong Kong-Macao Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Jun Li
- State Key Laboratory of Organic Geochemistry, Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, and Guangdong-Hong Kong-Macao Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, P. R. China
| | - Ruijie Zhang
- Guangxi Laboratory on the Study of Coral Reefs in the South China Sea; Coral Reef Research Center of China; School of Marine Sciences, Guangxi University, Nanning 530004, P. R. China
- Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519080, P. R. China
| | - Chongguo Tian
- CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, P. R. China
| | - Zeyu Sun
- CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Tingting Li
- State Key Laboratory of Organic Geochemistry, Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, and Guangdong-Hong Kong-Macao Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
| | - Minwei Han
- Guangxi Laboratory on the Study of Coral Reefs in the South China Sea; Coral Reef Research Center of China; School of Marine Sciences, Guangxi University, Nanning 530004, P. R. China
| | - Kefu Yu
- Guangxi Laboratory on the Study of Coral Reefs in the South China Sea; Coral Reef Research Center of China; School of Marine Sciences, Guangxi University, Nanning 530004, P. R. China
- Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519080, P. R. China
| | - Gan Zhang
- State Key Laboratory of Organic Geochemistry, Guangdong Province Key Laboratory of Environmental Protection and Resources Utilization, and Guangdong-Hong Kong-Macao Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, P. R. China
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Qu Q, Wang S, Zhao B, Hu R, Liang C, Zhang H, Li S, Feng B, Hou X, Yin D, Du J, Chu Y, Zhang Y, Wu Q, Wen Y, Wu X, Hu J, Zhang S, Hao J. Response of organic aerosol in Beijing to emission reductions during the XXIV Olympic Winter Games. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 914:170033. [PMID: 38220000 DOI: 10.1016/j.scitotenv.2024.170033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 01/05/2024] [Accepted: 01/07/2024] [Indexed: 01/16/2024]
Abstract
Organic aerosol (OA) serves as a crucial component of fine particulate matter. However, the response of OA to changes in anthropogenic emissions remains unclear due to its complexity. The XXIV Olympic Winter Games (OWG) provided real atmospheric experimental conditions on studying the response of OA to substantial emission reductions in winter. Here, we explored the sources and variations of OA based on the observation of aerosol mass spectrometer (AMS) combined with positive matrix factorization (PMF) analysis in urban Beijing during the 2022 Olympic Winter Games. The influences of meteorological conditions on OA concentrations were corrected by CO and verified by deweathered model. The CO-normalized primary OA (POA) concentrations from traffic, cooking, coal and biomass burning during the OWG decreased by 39.8 %, 23.2 % and 65.0 %, respectively. Measures controlling coal and biomass burning were most effective in reducing POA during the OWG. For the CO-normalized concentration of secondary OA (SOA), aqueous-phase related oxygenated OA decreased by 51.8 % due to the lower relative humidity and emission reduction in precursors, while the less oxidized‑oxygenated OA even slightly increased as the enhanced atmospheric oxidation processes may partially offset the efficacy of emission control. Therefore, more targeted reduction of organic precursors shall be enhanced to lower atmospheric oxidation capacity and mitigate SOA pollution.
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Affiliation(s)
- Qipeng Qu
- 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
| | - Shuxiao Wang
- 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.
| | - Bin Zhao
- 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
| | - Ruolan Hu
- 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
| | - Chengrui Liang
- 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
| | - Haowen Zhang
- 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
| | - Shengyue Li
- 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
| | - Boyang Feng
- 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
| | - Xuan Hou
- 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
| | - Dejia Yin
- 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
| | - Jinhong Du
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yangxi Chu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yanning Zhang
- 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
| | - Qingru Wu
- 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
| | - Yifan Wen
- 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
| | - Xiaomeng Wu
- 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
| | - Jingnan Hu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Shaojun Zhang
- 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
| | - Jiming Hao
- 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
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Yang X, Wang L, Ma P, He Y, Zhao C, Zhao W. Urban and suburban decadal variations in air pollution of Beijing and its meteorological drivers. ENVIRONMENT INTERNATIONAL 2023; 181:108301. [PMID: 37939441 DOI: 10.1016/j.envint.2023.108301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 10/04/2023] [Accepted: 10/31/2023] [Indexed: 11/10/2023]
Abstract
Air pollution is a major threat to human health and ecosystems. Using 10-year (2013-2022) multi-source observations for the Beijing, China, we showed that clean-air actions have significantly reduced PM2.5, PM10, CO, NO2, and SO2 pollution, with an increase in the surface maximum daily 8-h average ozone (MDA8O3) concentrations during autumn and winter, leading to a rapid diminishment of the urban-suburban gap in air pollution. Secondary sources and vehicle emissions were enhanced in both urban and suburban areas in all seasons except summer from 2013 to 2022. By combining statistical analysis with the convergent cross-mapping model, the varying relationships between air pollution and meteorological conditions in the urban and suburban areas were delineated. The results suggested that boundary layer height and relative humidity exerted strong and stable influences on all air pollutants, except for MDA8O3, whose key meteorological driver was temperature. This study showed that increasing O3 trends in autumn and winter and aggravated O3 formation in summer in urban areas in Beijing became non-negligible from 2013 to 2022, despite the declining levels of air pollutants. Meteorological observations suggested that weather patterns in Beijing, characterized by higher temperatures, sunshine hours, and boundary layer height and lower relative humidity, have become more favorable for O3 formation in autumn and winter. Future mitigation efforts should focus on reducing VOC and NOx emissions to avoid further deterioration of O3 pollution under the frequent adverse meteorological conditions predicted under the background of global warming.
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Affiliation(s)
- Xingchuan Yang
- College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
| | - Lili Wang
- College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China
| | - Pengfei Ma
- Ministry of Ecology and Environment Center for Satellite Application on Ecology and Environment/State Environmental Protection Key Laboratory of Satellite Remote Sensing, Beijing 100094, China
| | - Yuling He
- Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department I of Thoracic Oncology, Peking University Cancer Hospital & Institute, Beijing 100142, China
| | - Chuanfeng Zhao
- Department of Atmospheric and Oceanic Sciences, Laboratory for Climate and Ocean-Atmosphere Studies, School of Physics, Peking University, Beijing 100871, China.
| | - Wenji Zhao
- College of Resource Environment and Tourism, Capital Normal University, Beijing 100048, China.
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