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Zhang Z, Zhu W, Hu M, Wang H, Tang L, Hu S, Shen R, Yu Y, Song K, Tan R, Chen Z, Chen S, Canonaco F, Prévôt ASH, Guo S. Secondary organic aerosol formation in China from urban-lifestyle sources: Vehicle exhaust and cooking emission. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159340. [PMID: 36228803 DOI: 10.1016/j.scitotenv.2022.159340] [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: 08/22/2022] [Revised: 10/05/2022] [Accepted: 10/06/2022] [Indexed: 06/16/2023]
Abstract
An increasing number of people tend to live in cities, where they suffer from serious air pollution from anthropogenic sources. Vehicle exhaust and cooking emission are closely related to daily life of urban residents, and could be defined as "urban-lifestyle sources". The primary emissions of urban-lifestyle sources tend to form abundant secondary organic aerosols (SOA) through complicated atmospheric chemistry processes. The newly formed SOA is a kind of complex mixture and causes considerable health effects with high uncertainty. Most studies focus on formation pathway, mass growth potential and chemical feature of urban-lifestyle SOA under simple laboratory conditions. Few studies have measured the urban-lifestyle SOA in ambient air, let alone verified laboratory findings under complicated atmospheric conditions. In this work, we established a new method that combined laboratory simulation and field observation, which quantified the urban-lifestyle SOA with high time resolution under the real atmospheric condition. The complex SOA was measured and resolved by a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS). The multilinear engine model (ME-2) and multilinear correction methods were used to apply laboratory results into ambient SOA apportionment. It was found that the vehicle source dominated the SOA formation during the diurnal photochemical process, and the SOA:POA ratio of vehicle source was about 1.4 times larger than that of cooking source. The vehicle emission may undergo an alcohol/peroxide & carboxylic acid oxidation pathway and form higher oxidized SOA, while the cooking emission may undergo an alcohol/peroxide oxidation pathway and form relatively lower oxidized SOA. The vehicle SOA and cooking SOA contributed 45.6 % and 24.8 % of OA during a local episode in 2021 winter of downtown Beijing. Our findings could not only provide a new way to quantify urban SOA but also demonstrate some laboratory hypotheses, conducing to understand its ambient contributions, chemical features, and environmental effects.
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Affiliation(s)
- Zirui Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Wenfei Zhu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Min Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
| | - Hui Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Lizi Tang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Shuya Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Ruizhe Shen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Ying Yu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Kai Song
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Rui Tan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Zheng Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Shiyi Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Francesco Canonaco
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), Villigen 5232, Switzerland; Datalystica Ltd., Park innovAARE, 5234 Villigen, Switzerland
| | - Andre S H Prévôt
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), Villigen 5232, Switzerland
| | - Song Guo
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
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Zhou X, Li Z, Zhang T, Wang F, Tao Y, Zhang X. Multisize particulate matter and volatile organic compounds in arid and semiarid areas of Northwest China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 300:118875. [PMID: 35074457 DOI: 10.1016/j.envpol.2022.118875] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2021] [Revised: 01/16/2022] [Accepted: 01/18/2022] [Indexed: 06/14/2023]
Abstract
To investigate the chemical components, sources, and interactions of particulate matter (PM) and volatile organic compounds (VOCs), a field campaign was implemented during the spring of 2018 in nine cities in northwestern (NW) China. PM was mainly contributed by organic matter and water-soluble inorganic ions (41% for PM10 and approximately 60% for PM2.5 and PM1). Two typical haze patterns were observed: anthropogenic pollution type (AP-type), wherein contributions of sulfate, nitrate, and ammonium (SNA) increased, and dust pollution type (DP-type), wherein contributions of Ca2+ increased and SNA decreased. Source appointment suggested that regional sources contributed close to half to PM2.5 pollution (40% for AP-type and 50% for DP-type). Thus, sources from regional transport are also important for haze and dust pollution. The ranking of VOC concentrations was methanol > acetaldehyde > formic acid + ethanol > acetone. Compared with other cities, there are higher oxygenated VOCs (OVOCs) and lower aromatics in NW China. The relationships between VOCs and PM were discussed. The dominating secondary organic aerosols (SOA) formation potential precursors were C10-aromatics, xylene, and styrene under low-nitrogen oxide (NOx) conditions, and benzene, C10-aromatics, and toluene dominated under high-NOx conditions. The quadratic polynomial was the most suitable fitting model for their correlation, and the results suggested that VOC oxidations explained 6.1-10.8% and 9.9-20.7% of SOA formation under high-NOx and low-NOx conditions, respectively.
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Affiliation(s)
- Xi Zhou
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China; State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources; Tianshan Glaciological Station, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Zhongqin Li
- State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources; Tianshan Glaciological Station, Chinese Academy of Sciences, Lanzhou, 730000, China; College of Sciences, Shihezi University, Xinjiang, 832000, China; College of Geography and Environmental Science, Northwest Normal University, Lanzhou, 730000, China.
| | - Tingjun Zhang
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Feiteng Wang
- State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources; Tianshan Glaciological Station, Chinese Academy of Sciences, Lanzhou, 730000, China
| | - Yan Tao
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China
| | - Xin Zhang
- State Key Laboratory of Cryospheric Sciences, Northwest Institute of Eco-Environment and Resources; Tianshan Glaciological Station, Chinese Academy of Sciences, Lanzhou, 730000, China
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3
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Li J, Sakamoto Y, Kohno N, Fujii T, Matsuoka K, Takemura M, Zhou J, Nakagawa M, Murano K, Sadanaga Y, Nakashima Y, Sato K, Takami A, Yoshino A, Nakayama T, Kato S, Kajii Y. Total hydroxyl radical reactivity measurements in a suburban area during AQUAS-Tsukuba campaign in summer 2017. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 740:139897. [PMID: 32563867 DOI: 10.1016/j.scitotenv.2020.139897] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 05/19/2020] [Accepted: 05/31/2020] [Indexed: 06/11/2023]
Abstract
Missing hydroxyl radical (OH) reactivity from unknown/unmeasured trace species empirically accounts for 10%-30% of total OH reactivity and may cause significant uncertainty regarding estimation of photochemical ozone production. Thus, it is essential to unveil the missing OH reactivity for developing an effective ozone mitigation strategy. In this study, we conducted simultaneous observations of total OH reactivity and 54 reactive trace species in a suburban area as part of the Air QUAlity Study (AQUAS)-Tsukuba campaign for the summer of 2017 to gain in-depth insight into total OH reactivity in an area that experienced relatively high contributions of secondary pollutants. The campaign identified on average 35.3% of missing OH reactivity among total OH reactivity (12.9 s-1). In general, ozone-production potential estimation categorized ozone formation in this area as volatile organic compound (VOC)-limited conditions, and missing OH reactivity may increase ozone production potential 40% on average if considered. Our results suggest the importance of photochemical processes of both AVOCs and BVOCs for the production of missing OH reactivity and that we may underestimate the importance of reducing precursors in approach to suppressing ozone production if we ignore the contribution of their photochemical products.
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Affiliation(s)
- Jiaru Li
- Graduate School of Global Environmental Studies, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan
| | - Yosuke Sakamoto
- Graduate School of Global Environmental Studies, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan; Graduate School of Human and Environmental Studies, Kyoto University, Yoshida-Nihonmatsucho, Sakyo-ku, Kyoto 606-8316, Japan; Center for Regional Environmental Research, National Institute for Environmental Studies, Tsukuba City, Ibaraki 305-8506, Japan.
| | - Nanase Kohno
- Graduate School of Global Environmental Studies, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan
| | - Tomihide Fujii
- Graduate School of Global Environmental Studies, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan
| | - Kohei Matsuoka
- Graduate School of Global Environmental Studies, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan
| | - Marina Takemura
- Graduate School of Human and Environmental Studies, Kyoto University, Yoshida-Nihonmatsucho, Sakyo-ku, Kyoto 606-8316, Japan
| | - Jun Zhou
- Graduate School of Global Environmental Studies, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan
| | - Maho Nakagawa
- Graduate School of Global Environmental Studies, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan; National Institute of Information and Communications Technology, 4-2-1 Nukui-kita, Koganei, Tokyo 184-8795, Japan
| | - Kentaro Murano
- Graduate School of Global Environmental Studies, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan
| | - Yasuhiro Sadanaga
- Graduate School of Engineering, Osaka Prefecture University, 1-1 Gakuen-cho, Naka-ku, Sakai, Osaka 599-8531, Japan
| | - Yoshihiro Nakashima
- Graduate School of Agriculture, Tokyo University of Agriculture and Technology, 3-5-8 Saiwai-cho, Fuchu, Tokyo 183-8538, Japan
| | - Kei Sato
- Center for Regional Environmental Research, National Institute for Environmental Studies, Tsukuba City, Ibaraki 305-8506, Japan
| | - Akinori Takami
- Center for Regional Environmental Research, National Institute for Environmental Studies, Tsukuba City, Ibaraki 305-8506, Japan
| | - Ayako Yoshino
- Center for Regional Environmental Research, National Institute for Environmental Studies, Tsukuba City, Ibaraki 305-8506, Japan
| | - Tomoki Nakayama
- Institute for Space-Earth Environmental Research, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan; Graduate School of Fisheries and Environmental Sciences, Nagasaki University, 1-14, Bunkyo-machi, Nagasaki 852-8521, Japan
| | - Shungo Kato
- Graduate School of Urban Environmental Sciences, Tokyo Metropolitan University, Tokyo 192-0397, Japan
| | - Yoshizumi Kajii
- Graduate School of Global Environmental Studies, Kyoto University, Yoshida-Honmachi, Sakyo-ku, Kyoto 606-8501, Japan; Graduate School of Human and Environmental Studies, Kyoto University, Yoshida-Nihonmatsucho, Sakyo-ku, Kyoto 606-8316, Japan; Center for Regional Environmental Research, National Institute for Environmental Studies, Tsukuba City, Ibaraki 305-8506, Japan.
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4
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Chang D, Wang Z, Guo J, Li T, Liang Y, Kang L, Xia M, Wang Y, Yu C, Yun H, Yue D, Wang T. Characterization of organic aerosols and their precursors in southern China during a severe haze episode in January 2017. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 691:101-111. [PMID: 31319248 DOI: 10.1016/j.scitotenv.2019.07.123] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2019] [Revised: 07/07/2019] [Accepted: 07/08/2019] [Indexed: 06/10/2023]
Abstract
The rapid industrialization and economic development in the Pearl River Delta (PRD) region of southern China have led to a substantial increase in anthropogenic emissions and hence frequent haze pollution over the past two decades. In early January 2017, a severe regional haze pollution episode was captured in the PRD region, with a peak PM2.5 concentration of around 400μgm-3, the highest value ever reported at this site. During the haze episode, elevated concentrations of oxygenated volatile organic compounds (OVOCs, 33±16 ppbv) and organic matter (41±15μg m-3) were observed, indicating the enhanced roles of secondary organic aerosols (SOAs) in the formation of haze pollution. Water-soluble organic carbon (WSOC, 12.8±5.5μg C m-3) dominated the organic aerosols, with a WSOC/OC ratio of 0.63±0.12 and high correlation (R=0.85) with estimated secondary organic carbon (SOC), suggesting the predominance of a secondary origin of the measured organic aerosols during the haze episode. Four carboxylic acids (oxalic, acetic, formic, and pyruvic acids) were characterized in the aerosols (1.30±0.38μgm-3) and accounted for 3.6±1.2% of WSOC in carbon mass, with oxalic acid as the most abundant species. The simultaneous measurements of volatile organic compounds (VOCs), OVOCs, and organic acids in aerosols at this site provided an opportunity to investigate the relationship between the precursors and the products, as well as the potential formation pathways. Water-soluble aldehydes and ketones, predominantly produced via the oxidation of anthropogenic VOCs (mainly propane, toluene, n-butane, and m, p-xylene), were the main contributors of the organic acids. The formation of OVOCs is largely attributed to gas-phase photochemical oxidation, whereas the WSOC and dicarboxylic acids were produced from both photochemistry and nocturnal heterogeneous reactions. These findings provided further insights into the oxidation and evolution of organic compounds during the haze pollution episode.
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Affiliation(s)
- Di Chang
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Zhe Wang
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
| | - Jia Guo
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Tao Li
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China; School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China
| | - Yiheng Liang
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Lingyan Kang
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Men Xia
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Yaru Wang
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Chuan Yu
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China; School of Environmental Science and Engineering, Shandong University, Qingdao 266237, China
| | - Hui Yun
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Dingli Yue
- Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangzhou 510308, China
| | - Tao Wang
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
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5
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Effects of a Detailed Vegetation Database on Simulated Meteorological Fields, Biogenic VOC Emissions, and Ambient Pollutant Concentrations over Japan. ATMOSPHERE 2018. [DOI: 10.3390/atmos9050179] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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6
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Xu W, Han T, Du W, Wang Q, Chen C, Zhao J, Zhang Y, Li J, Fu P, Wang Z, Worsnop DR, Sun Y. Effects of Aqueous-Phase and Photochemical Processing on Secondary Organic Aerosol Formation and Evolution in Beijing, China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2017; 51:762-770. [PMID: 28035819 DOI: 10.1021/acs.est.6b04498] [Citation(s) in RCA: 99] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Secondary organic aerosol (SOA) constitutes a large fraction of OA, yet remains a source of significant uncertainties in climate models due to incomplete understanding of its formation mechanisms and evolutionary processes. Here we evaluated the effects of photochemical and aqueous-phase processing on SOA composition and oxidation degrees in three seasons in Beijing, China, using high-resolution aerosol mass spectrometer measurements along with positive matrix factorization. Our results show that aqueous-phase processing has a dominant impact on the formation of more oxidized SOA (MO-OOA), and the contribution of MO-OOA to OA increases substantially as a function of relative humidity or liquid water content. In contrast, photochemical processing plays a major role in the formation of less oxidized SOA (LO-OOA), as indicated by the strong correlations between LO-OOA and odd oxygen (Ox = O3 + NO2) during periods of photochemical production (R2 = 0.59-0.80). Higher oxygen-to-carbon ratios of SOA during periods with higher RH were also found indicating a major role of aqueous-phase processing in changing the oxidation degree of SOA in Beijing. Episodes analyses further highlight that LO-OOA plays a more important role during the early stage of the formation of autumn/winter haze episodes while MO-OOA is more significant during the later evolution period.
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Affiliation(s)
- Weiqi Xu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences , Beijing 100029, China
- University of Chinese Academy of Sciences , Beijing 100049, China
| | - Tingting Han
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences , Beijing 100029, China
- University of Chinese Academy of Sciences , Beijing 100049, China
| | - Wei Du
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences , Beijing 100029, China
- University of Chinese Academy of Sciences , Beijing 100049, China
| | - Qingqing Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences , Beijing 100029, China
| | - Chen Chen
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences , Beijing 100029, China
| | - Jian Zhao
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences , Beijing 100029, China
- University of Chinese Academy of Sciences , Beijing 100049, China
| | - Yingjie Zhang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences , Beijing 100029, China
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology , Nanjing 210044, China
| | - Jie Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences , Beijing 100029, China
| | - Pingqing Fu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences , Beijing 100029, China
| | - Zifa Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences , Beijing 100029, China
| | - Douglas R Worsnop
- Aerodyne Research, Inc. , Billerica, Massachusetts 01821, United States
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences , Beijing 100029, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences , Xiamen 361021, China
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology , Nanjing 210044, China
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Li L, Tang P, Nakao S, Kacarab M, Cocker DR. Novel Approach for Evaluating Secondary Organic Aerosol from Aromatic Hydrocarbons: Unified Method for Predicting Aerosol Composition and Formation. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2016; 50:6249-6256. [PMID: 27177154 DOI: 10.1021/acs.est.5b05778] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Innovative secondary organic aerosol (SOA) composition analysis methods normalizing aerosol yield and chemical composition on an aromatic ring basis are developed and utilized to explore aerosol formation from oxidation of aromatic hydrocarbons. SOA yield and chemical composition are revisited using 15 years of University of California, Riverside/CE-CERT environmental chamber data on 17 aromatic hydrocarbons with HC:NO ranging from 11.1 to 171 ppbC:ppb. SOA yield is redefined in this work by normalizing the molecular weight of all aromatic precursors to the molecular weight of the aromatic ring [Formula: see text], where i is the aromatic hydrocarbon precursor. The yield normalization process demonstrates that the amount of aromatic rings present is a more significant driver of aerosol formation than the vapor pressure of the precursor aromatic. Yield normalization also provided a basis to evaluate isomer impacts on SOA formation. Further, SOA elemental composition is explored relative to the aromatic ring rather than on a classical mole basis. Generally, four oxygens per aromatic ring are observed in SOA, regardless of the alkyl substitutes attached to the ring. Besides the observed SOA oxygen to ring ratio (O/R ∼ 4), a hydrogen to ring ratio (H/R) of 6 + 2n is observed, where n is the number of nonaromatic carbons. Normalization of yield and composition to the aromatic ring clearly demonstrates the greater significance of aromatic ring carbons compared with alkyl carbon substituents in determining SOA formation and composition.
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Affiliation(s)
- Lijie Li
- Department of Chemical and Environmental Engineering, University of California, Riverside , Riverside, California 92521, United States
- College of Engineering, Center for Environmental Research and Technology (CE-CERT), University of California, Riverside , Riverside, California 92507, United States
| | - Ping Tang
- Department of Chemical and Environmental Engineering, University of California, Riverside , Riverside, California 92521, United States
- College of Engineering, Center for Environmental Research and Technology (CE-CERT), University of California, Riverside , Riverside, California 92507, United States
| | - Shunsuke Nakao
- Department of Chemical and Environmental Engineering, University of California, Riverside , Riverside, California 92521, United States
- College of Engineering, Center for Environmental Research and Technology (CE-CERT), University of California, Riverside , Riverside, California 92507, United States
| | - Mary Kacarab
- Department of Chemical and Environmental Engineering, University of California, Riverside , Riverside, California 92521, United States
- College of Engineering, Center for Environmental Research and Technology (CE-CERT), University of California, Riverside , Riverside, California 92507, United States
| | - David R Cocker
- Department of Chemical and Environmental Engineering, University of California, Riverside , Riverside, California 92521, United States
- College of Engineering, Center for Environmental Research and Technology (CE-CERT), University of California, Riverside , Riverside, California 92507, United States
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Pipal AS, Tiwari S, Satsangi PG, Taneja A, Bisht DS, Srivastava AK, Srivastava MK. Sources and characteristics of carbonaceous aerosols at Agra "World heritage site" and Delhi "capital city of India". ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2014; 21:8678-8691. [PMID: 24723344 DOI: 10.1007/s11356-014-2768-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2013] [Accepted: 03/10/2014] [Indexed: 06/03/2023]
Abstract
Agra, one of the oldest cities "World Heritage site", and Delhi, the capital city of India are both located in the border of Indo-Gangetic Plains (IGP) and heavily loaded with atmospheric aerosols due to tourist place, anthropogenic activities, and its topography, respectively. Therefore, there is need for monitoring of atmospheric aerosols to perceive the scenario and effects of particles over northern part of India. The present study was carried out at Agra (AGR) as well as Delhi (DEL) during winter period from November 2011 to February 2012 of fine particulate (PM₂.₅: d < 2.5 μm) as well as associated carbonaceous aerosols. PM₂.₅ was collected at both places using medium volume air sampler (offline measurement) and analyzed for organic carbon (OC) and elemental carbon (EC). Also, simultaneously, black carbon (BC) was measured (online) at DEL. The average mass concentration of PM₂.₅ was 165.42 ± 119.46 μg m(-3) at AGR while at DEL it was 211.67 ± 41.94 μg m(-3) which is ~27% higher at DEL than AGR whereas the BC mass concentration was 10.60 μg m(-3). The PM₂.₅ was substantially higher than the annual standard stipulated by central pollution control board and United States Environmental Protection Agency standards. The average concentrations of OC and EC were 69.96 ± 34.42 and 9.53 ± 7.27 μm m(-3), respectively. Total carbon (TC) was 79.01 ± 38.98 μg m(-3) at AGR, while it was 50.11 ± 11.93 (OC), 10.67 ± 3.56 μg m(-3) (EC), and 60.78 ± 14.56 μg m(-3) (TC) at DEL. The OC/EC ratio was 13.75 at (AGR) and 5.45 at (DEL). The higher OC/EC ratio at Agra indicates that the formation of secondary organic aerosol which emitted from variable primary sources. Significant correlation between PM₂.₅ and its carbonaceous species were observed indicating similarity in sources at both sites. The average concentrations of secondary organic carbon (SOC) and primary organic carbon (POC) at AGR were 48.16 and 26.52 μg m(-3) while at DEL it was 38.78 and 27.55 μg m(-3), respectively. In the case of POC, similar concentrations were observed at both places but in the case of SOC higher over AGR by 24 in comparison to DEL, it is due to the high concentration of OC over AGR. Secondary organic aerosol (SOA) was 42% higher at AGR than DEL which confirms the formation of secondary aerosol at AGR due to rural environment with higher concentrations of coarse mode particles. The SOA contribution in PM₂.₅ was also estimated and was ~32 and 12% at AGR and DEL respectively. Being high loading of fine particles along with carbonaceous aerosol, it is suggested to take necessary and immediate action in mitigation of the emission of carbonaceous aerosol in the northern part of India.
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Affiliation(s)
- A S Pipal
- Department of Chemistry, University of Pune, Pune, India, 411007,
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Zhang H, Chen G, Hu J, Chen SH, Wiedinmyer C, Kleeman M, Ying Q. Evaluation of a seven-year air quality simulation using the Weather Research and Forecasting (WRF)/Community Multiscale Air Quality (CMAQ) models in the eastern United States. THE SCIENCE OF THE TOTAL ENVIRONMENT 2014; 473-474:275-85. [PMID: 24374589 DOI: 10.1016/j.scitotenv.2013.11.121] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2013] [Revised: 11/20/2013] [Accepted: 11/20/2013] [Indexed: 04/14/2023]
Abstract
The performance of the Weather Research and Forecasting (WRF)/Community Multi-scale Air Quality (CMAQ) system in the eastern United States is analyzed based on results from a seven-year modeling study with a 4-km spatial resolution. For 2-m temperature, the monthly averaged mean bias (MB) and gross error (GE) values are generally within the recommended performance criteria, although temperature is over-predicted with MB values up to 2K. Water vapor at 2-m is well-predicted but significant biases (>2 g kg(-1)) were observed in wintertime. Predictions for wind speed are satisfactory but biased towards over-prediction with 0<MB<0.5 m s(-1) and root mean square error (RMSE) around 1.5 to 2 m s(-1). Wind direction, predicted without observation nudging, is not well-reproduced with GE values as large as 50° in summertime. Performance in other months is better with RMSE around 20-30° and MB within ± 10°. O3 performance meets the EPA criteria of mean normalized bias (MNB) within ± 0.15 and accuracy of unpaired peak (AUP) within 0.2. Normalized gross error (NGE) is mostly below 0.25, lower than the criteria of 0.35. Performance of PM10 is satisfactory with mean fractional bias (MFB) within ± 0.6, but a large under-prediction in springtime was frequently observed. Performance of PM2.5 and its components is mostly within performance goals except for organic carbon (OC), which is universally under-predicted with MFB values as large as -0.8. The predicted frequency distribution of PM2.5 generally agrees with observations although the predictions are slightly biased towards more frequent high concentrations in most areas. Elemental carbon (EC), nitrate and sulfate concentrations are also well reproduced. The other unresolved PM2.5 components (OTHER) are significantly overestimated by more than a factor of two. No conclusive explanations can be made regarding the possible cause of this universal overestimation, which warrants a follow-up study to better understand this problem.
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Affiliation(s)
- Hongliang Zhang
- Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843, USA
| | - Gang Chen
- Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843, USA
| | - Jianlin Hu
- Department of Civil & Environmental Engineering, University of California, Davis, CA 95616, USA
| | - Shu-Hua Chen
- Department of Land, Air, and Water Resources, University of California, Davis, CA 95616, USA
| | - Christine Wiedinmyer
- Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
| | - Michael Kleeman
- Department of Civil & Environmental Engineering, University of California, Davis, CA 95616, USA
| | - Qi Ying
- Zachry Department of Civil Engineering, Texas A&M University, College Station, TX 77843, USA.
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de Gouw JA, Middlebrook AM, Warneke C, Ahmadov R, Atlas EL, Bahreini R, Blake DR, Brock CA, Brioude J, Fahey DW, Fehsenfeld FC, Holloway JS, Le Henaff M, Lueb RA, McKeen SA, Meagher JF, Murphy DM, Paris C, Parrish DD, Perring AE, Pollack IB, Ravishankara AR, Robinson AL, Ryerson TB, Schwarz JP, Spackman JR, Srinivasan A, Watts LA. Organic aerosol formation downwind from the Deepwater Horizon oil spill. Science 2011; 331:1295-9. [PMID: 21393539 DOI: 10.1126/science.1200320] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
A large fraction of atmospheric aerosols are derived from organic compounds with various volatilities. A National Oceanic and Atmospheric Administration (NOAA) WP-3D research aircraft made airborne measurements of the gaseous and aerosol composition of air over the Deepwater Horizon (DWH) oil spill in the Gulf of Mexico that occurred from April to August 2010. A narrow plume of hydrocarbons was observed downwind of DWH that is attributed to the evaporation of fresh oil on the sea surface. A much wider plume with high concentrations of organic aerosol (>25 micrograms per cubic meter) was attributed to the formation of secondary organic aerosol (SOA) from unmeasured, less volatile hydrocarbons that were emitted from a wider area around DWH. These observations provide direct and compelling evidence for the importance of formation of SOA from less volatile hydrocarbons.
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Affiliation(s)
- J A de Gouw
- Chemical Sciences Division, Earth System Research Laboratory, National Oceanic and Atmospheric Administration, Boulder, CO 80305, USA.
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Morino Y, Ohara T, Yokouchi Y, Ooki A. Comprehensive source apportionment of volatile organic compounds using observational data, two receptor models, and an emission inventory in Tokyo metropolitan area. ACTA ACUST UNITED AC 2011. [DOI: 10.1029/2010jd014762] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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12
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Matsui H, Koike M, Kondo Y, Takegawa N, Fast JD, Pöschl U, Garland RM, Andreae MO, Wiedensohler A, Sugimoto N, Zhu T. Spatial and temporal variations of aerosols around Beijing in summer 2006: 2. Local and column aerosol optical properties. ACTA ACUST UNITED AC 2010. [DOI: 10.1029/2010jd013895] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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13
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Partitioning phase preference for secondary organic aerosol in an urban atmosphere. Proc Natl Acad Sci U S A 2010; 107:6705-10. [PMID: 20176970 DOI: 10.1073/pnas.0911244107] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Secondary organic aerosol (SOA) comprises a significant portion of atmospheric particular matter. The impact of particular matter on both human health and global climate has long been recognized. Despite its importance, there are still many unanswered questions regarding the formation and evolution of SOA in the atmosphere. This study uses a modeling approach to understand the preferred partitioning behavior of SOA species into aqueous or organic condensed phases. More specifically, this work uses statistical analyses of approximately 24,000 data values for each variable from a state of the art 3D airshed model. Spatial and temporal distributions of fractions of SOA residing in the aqueous phase (fAQ) in the South Coast Air Basin of California are presented. Typical values of fAQ within the basin near the surface range from 5 to 80%. Results show that the likelihood of large fAQ values is inversely proportional to the total SOA loading. Analysis of various meteorological parameters indicates that large fAQ values are predicted because modeled aqueous-phase SOA formation is less sensitive than that of organic-phase SOA to atmospheric conditions that are not conducive to SOA formation. There is a diurnal variation of fAQ near the surface: It tends to be larger during daytime hours than during nighttime hours. Results also indicate that the largest fAQ values are simulated in layers above ground level at night. In summary, one must consider SOA in both organic and aqueous phases for proper regional and global SOA budget estimation.
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Matsui H, Koike M, Kondo Y, Takegawa N, Kita K, Miyazaki Y, Hu M, Chang SY, Blake DR, Fast JD, Zaveri RA, Streets DG, Zhang Q, Zhu T. Spatial and temporal variations of aerosols around Beijing in summer 2006: Model evaluation and source apportionment. ACTA ACUST UNITED AC 2009. [DOI: 10.1029/2008jd010906] [Citation(s) in RCA: 74] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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15
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Oshima N, Koike M, Zhang Y, Kondo Y, Moteki N, Takegawa N, Miyazaki Y. Aging of black carbon in outflow from anthropogenic sources using a mixing state resolved model: Model development and evaluation. ACTA ACUST UNITED AC 2009. [DOI: 10.1029/2008jd010680] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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