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Jia Z, Yin J, Cao Z, Wei N, Jiang Z, Zhang Y, Wu L, Zhang Q, Mao H. Large-scale deployment of intelligent transportation to help achieve low-carbon and clean sustainable transportation. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 949:174724. [PMID: 39059649 DOI: 10.1016/j.scitotenv.2024.174724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 06/27/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024]
Abstract
Sustained deep emission reduction in road transportation is encountering bottleneck. The Intelligent Transportation-Speed Guidance System (ITSGS) is anticipated to overcome this challenge and facilitate the achievement of low-carbon and clean transportation. Here, we compiled vehicle emission datasets collected from real-world road experiments and identified the mapping relationships between four pollutants (CO2, CO, NOx, and THC) and their influencing factors through machine learning. We developed random forest models for each pollutant and achieved strong predictive performance, with an R2 exceeding 0.85 on the test dataset for all models. The environmental benefits of ITSGS at the urban scale were quantified by combining emission models with large-scale real trajectory data from Zibo, Shandong Province. Based on temporal and spatial analyses, we found that ITSGS has varying degrees of emission reduction potential during the morning peak, flat peak, and evening peak hours. Values can range from 5.71 %-8.16 % for CO2 emissions, 13.63 %-16.25 % for NOx emissions, 13.69 %-16.45 % for CO emissions, and 4.84-7.07 % for THC emissions, respectively. Additionally, ITSGS can significantly expand the area of low transient emission zones. The best time for achieving maximum environmental benefits from ITSGS is during the workday flat peak. ITSGS limits high-speed and aggressive driving behavior, thereby smoothing the driving trajectory, reducing the frequency of speed switches, and lowering road traffic emissions. The results of the ITSGS environmental benefits evaluation will provide new insights and solutions for sustainable road traffic emission reduction. SYNOPSIS: Large-scale deployment of Intelligent Transportation - Speed Guidance System is a sustainable solution to help achieve low-carbon and clean transportation.
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Affiliation(s)
- Zhenyu Jia
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Jiawei Yin
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Zeping Cao
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Ning Wei
- Jinchuan Group Information and Automation Engineering Co. Ltd., Jinchang 737100, China
| | - Zhiwen Jiang
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Yanjie Zhang
- Tianjin Youmei Environment Technology, Ltd., Tianjin 300380, China
| | - Lin Wu
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Qijun Zhang
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China.
| | - Hongjun Mao
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
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Goel V, Tripathi N, Gupta M, Sahu LK, Singh V, Kumar M. Study of secondary organic aerosol formation and aging using ambient air in an oxidation flow reactor during high pollution events over Delhi. ENVIRONMENTAL RESEARCH 2024; 251:118542. [PMID: 38403149 DOI: 10.1016/j.envres.2024.118542] [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: 11/26/2023] [Revised: 02/15/2024] [Accepted: 02/22/2024] [Indexed: 02/27/2024]
Abstract
Secondary aerosols constitute a significant fraction of atmospheric aerosols, yet our understanding of their formation mechanism and fate is very limited. In this work, the secondary organic aerosol (SOA) formation and aging of ambient air of Delhi are studied using a potential aerosol mass (PAM) reactor, an oxidation flow reactor (OFR), coupled with aerosol chemical speciation monitor (ACSM), proton transfer reaction time of flight mass spectrometer (PTR-ToF-MS), and scanning mobility particle sizer with counter (SMPS + C). The setup mimics atmospheric aging of up to several days with the generation of OH radicals. Variations in primary volatile organic compounds (VOCs) and oxygenated volatile organic compounds (OVOCs) as a function of photochemical age were investigated. Primary VOCs such as benzene, toluene, xylene, trimethyl benzene, etc. decrease and OVOCs like formic acid, formaldehyde, acetone, ethanol, etc. increase substantially upon oxidation in OFR. The highest organic aerosol (OA) enhancement was observed for the 4.2 equivalent photochemical days of aging i.e., 1.84 times the ambient concentration, and net OA loss was observed at very high OH exposure, typically after 8.4 days of photochemical aging due to heterogeneous oxidation followed by fragmentation/evaporation. In ambient air, OA enhancement is highest during nighttime due to the high concentrations of precursor VOCs in the atmosphere. SMPS + C results demonstrated substantial new particle formation upon aging and decrement in preexisting aerosol mass. This is the first experimental study conducting an in-situ evaluation of potential SOA mass generated from the ambient aerosols in India.
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Affiliation(s)
- Vikas Goel
- School of Interdisciplinary Research, Indian Institute of Technology Delhi, Delhi, 110016, India; Department of Mechanical Engineering, Indian Institute of Technology Delhi, Delhi, 110016, India.
| | - Nidhi Tripathi
- Atmospheric Chemistry Department, Max Planck Institute for Chemistry, Mainz, 55128, Germany; Physical Research Laboratory, Navrangpura, Ahmedabad, 380009, India
| | - Mansi Gupta
- Physical Research Laboratory, Navrangpura, Ahmedabad, 380009, India; Indian Institute of Technology Gandhinagar, Palaj, Gandhinagar, 382355, India
| | | | - Vikram Singh
- Department of Chemical Engineering, Indian Institute of Technology Delhi, Delhi, 110016, India
| | - Mayank Kumar
- Department of Mechanical Engineering, Indian Institute of Technology Delhi, Delhi, 110016, India.
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Yao PT, Peng X, Cao LM, Zeng LW, Feng N, He LY, Huang XF. Evaluation of a new real-time source apportionment system of PM 2.5 and its implication on rapid aging of vehicle exhaust. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 937:173449. [PMID: 38797425 DOI: 10.1016/j.scitotenv.2024.173449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/16/2024] [Revised: 05/07/2024] [Accepted: 05/20/2024] [Indexed: 05/29/2024]
Abstract
Accurate identification and rapid analysis of PM2.5 sources and formation mechanisms are essential to mitigate PM2.5 pollution. However, studies were limited in developing a method to apportion sources to the total PM2.5 mass in real-time. In this study, we developed a real-time source apportionment method based on chemical mass balance (CMB) modeling and a mass-closure PM2.5 composition online monitoring system in Shenzhen, China. Results showed that secondary sulfate, secondary organic aerosol (SOA), vehicle emissions and secondary nitrate were the four major PM2.5 sources during autumn 2019 in Shenzhen, together contributed 76 % of PM2.5 mass. The novel method was verified by comparing with other source apportionment methods, including offline filter analysis, aerosol mass spectrometry, and carbon isotopic analysis. The comparison of these methods showed that the new real-time method obtained results generally consistent with the others, and the differences were interpretable and implicative. SOA and vehicle emissions were the major PM2.5 and OA contributors by all methods. Further investigation on the OA sources indicated that vehicle emissions were not only the main source of primary organic aerosol (POA), but also the main contributor to SOA by rapid aging of the exhaust in the atmosphere. Our results demonstrated the great potential of the new real-time source apportionment method for aerosol pollution control and deep understandings on emission sources.
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Affiliation(s)
- Pei-Ting Yao
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Xing Peng
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China.
| | - Li-Ming Cao
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Li-Wu Zeng
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Ning Feng
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Ling-Yan He
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Xiao-Feng Huang
- Laboratory of Atmospheric Observation Supersite, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China.
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Zhang J, Peng J, Song A, Du Z, Guo J, Liu Y, Yang Y, Wu L, Wang T, Song K, Guo S, Collins D, Mao H. Secondary Organic Aerosol Formation Potential from Vehicular Non-tailpipe Emissions under Real-World Driving Conditions. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:5419-5429. [PMID: 38390902 DOI: 10.1021/acs.est.3c06475] [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: 02/24/2024]
Abstract
Traffic emissions are a dominant source of secondary organic aerosol (SOA) in urban environments. Though tailpipe exhaust has drawn extensive attention, the impact of non-tailpipe emissions on atmospheric SOA has not been well studied. Here, a closure study was performed combining urban tunnel experiments and dynamometer tests using an oxidation flow reactor in situ photo-oxidation. Results show a significant gap between field and laboratory research; the average SOA formation potential from real-world fleet is 639 ± 156 mg kg fuel-1, higher than the reconstructed result (188 mg kg fuel-1) based on dynamometer tests coupled with fleet composition inside the tunnel. Considering the minimal variation of SOA/CO in emission standards, we also reconstruct CO and find the critical role of high-emitting events in the real-world SOA burden. Different profiles of organic gases are detected inside the tunnel than tailpipe exhaust, such as more abundant C6-C9 aromatics, C11-C16 species, and benzothiazoles, denoting contributions from non-tailpipe emissions to SOA formation. Using these surrogate chemical compounds, we roughly estimate that high-emitting, evaporative emission, and asphalt-related and tire sublimation share 14, 20, and 10% of the SOA budget, respectively, partially explaining the gap between field and laboratory research. These experimental results highlight the importance of non-tailpipe emissions to atmospheric SOA.
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Affiliation(s)
- Jinsheng Zhang
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Jianfei Peng
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Ainan Song
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Zhuofei Du
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
- School of Environmental Science and Safety Engineering, Tianjin University of Technology, Tianjin 300382, China
| | - Jiliang Guo
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Yan Liu
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Yicheng Yang
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Lin Wu
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Ting Wang
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Kai Song
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Song Guo
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Don Collins
- Bourns College of Engineering, Center for Environmental Research and Technology (CE-CERT), University of California, 1084 Columbia Avenue, Riverside, California 92507, United States
- Department of Chemical and Environmental Engineering, University of California Riverside, Riverside, California 92521, United States
| | - Hongjun Mao
- Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
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Singh R, Sinha B, Hakkim H, Sinha V. Source apportionment of volatile organic compounds during paddy-residue burning season in north-west India reveals large pool of photochemically formed air toxics. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 338:122656. [PMID: 37793541 DOI: 10.1016/j.envpol.2023.122656] [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: 07/16/2023] [Revised: 09/11/2023] [Accepted: 09/28/2023] [Indexed: 10/06/2023]
Abstract
Paddy-residue burning is associated with poor air quality in north-west India during October-November every year. However, till date a quantitative study of its contribution to ambient volatile organic compounds (VOCs) using highly time-resolved measurements within the region has been lacking. Several VOCs like benzene are carcinogenic and also fuel formation of secondary pollutants such as secondary organic aerosol (SOA) and ozone. Here, we undertake quantitative source-apportionment using a PMF source-receptor model on a high-quality in-situ measured dataset of 54 VOCs in Punjab, India, and validate the model results using source profiles. The contribution of the seven most dominant sources to the total VOC mass concentrations were: daytime photochemistry and biogenic VOCs (BVOCs) (26%), followed by solid-fuel usage and waste-disposal (18%), traffic (two-wheeler 14% and four-wheeler 10%), photochemically aged biomass burning (17%), industries and solvent usage (9%), and fresh paddy residue burning (6%). Ozone production potential was dominated by solid fuel usage and waste disposal (25%), followed by traffic (two-wheeler 11% and four-wheeler 12%), BVOCs and photooxidation products (21%), photochemically aged biomass burning (16%), industries & solvent usage (9%) and fresh paddy residue burning (6%). SOA production was dominated by traffic (two-wheeler 26% and four-wheeler 28%) followed by solid fuel usage and waste disposal (22%), photochemically aged biomass burning emissions (15%) with minor contribution from industries & solvents (6%), fresh paddy residue burning (2%) and photochemistry and biogenic VOCs (1%). Comparisons with global emission inventories REASv3.2.1 and EDGARv4.3.2, showed both overestimate the industry and solvent source. Further, EDGARv4.3.2 underestimated the traffic source whereas paddy residue burning emissions are absent in REASv3.2.1. Although the overall mass contribution of paddy-residue burning emissions isn't high, our results show that health-relevant compounds emitted directly and formed photochemically from biomass burning sources active at this time are majorly responsible for the unhealthy air.
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Affiliation(s)
- Raj Singh
- Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Mohali, Sector 81, S.A.S Nagar, Manauli PO, Punjab, 140306, India
| | - Baerbel Sinha
- Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Mohali, Sector 81, S.A.S Nagar, Manauli PO, Punjab, 140306, India
| | - Haseeb Hakkim
- Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Mohali, Sector 81, S.A.S Nagar, Manauli PO, Punjab, 140306, India
| | - Vinayak Sinha
- Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Mohali, Sector 81, S.A.S Nagar, Manauli PO, Punjab, 140306, India.
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Chen T, Liu J, Chu B, Ge Y, Zhang P, Ma Q, He H. Combined Smog Chamber/Oxidation Flow Reactor Study on Aging of Secondary Organic Aerosol from Photooxidation of Aromatic Hydrocarbons. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:13937-13947. [PMID: 37691473 DOI: 10.1021/acs.est.3c04089] [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: 09/12/2023]
Abstract
Secondary organic aerosol (SOA) is a significant component of atmospheric fine particulate matter (PM2.5), and their physicochemical properties can be significantly changed in the aging process. In this study, we used a combination consisting of a smog chamber (SC) and oxidation flow reactor (OFR) to investigate the continuous aging process of gas-phase organic intermediates and SOA formed from the photooxidation of toluene, a typical aromatic hydrocarbon. Our results showed that as the OH exposure increased from 2.6 × 1011 to 6.3 × 1011 molecules cm-3 s (equivalent aging time of 2.01-4.85 days), the SOA mass concentration (2.9 ± 0.05-28.7 ± 0.6 μg cm-3) and corrected SOA yield (0.073-0.26) were significantly enhanced. As the aging process proceeds, organic acids and multiple oxygen-containing oxidation products are continuously produced from the photochemical aging process of gas-phase organic intermediates (mainly semi-volatile and intermediate volatility species, S/IVOCs). The multigeneration oxidation products then partition to the aerosol phase, while functionalization of SOA rather than fragmentation dominated in the photochemical aging process, resulting in much higher SOA yield after aging compared to that in the SC. Our study indicates that SOA yields as a function of OH exposure should be considered in air quality models to improve SOA simulation, and thus accurately assess the impact on SOA properties and regional air quality.
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Affiliation(s)
- Tianzeng Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Jun Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Biwu Chu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanli Ge
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, Beijing Innovation Center for Engineering Science and Advanced Technology, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Peng Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qingxin Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hong He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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Park Y, Kim H. Real time measurements of the secondary organic aerosol formation and aging from ambient air using an oxidation flow reactor in seoul during winter. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 327:121464. [PMID: 36963451 DOI: 10.1016/j.envpol.2023.121464] [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: 01/11/2023] [Revised: 02/28/2023] [Accepted: 03/19/2023] [Indexed: 06/18/2023]
Abstract
Herein, the formation and aging processes of organic aerosol (OA) in urban Seoul, Korea, during winter were investigated using a high-resolution aerosol mass spectrometer (HR-ToF-AMS) and an oxidation flow reactor (OFR). The results demonstrated that the highest secondary OA (SOA) production (ΔOA = 3.44 μg m-3 with a relative OA enhancement ratio (EROA) = 1.40) occurred at ∼2 eq. days of OH exposure. Particularly, higher SOA production was observed under the following atmospheric conditions: high relative humidity (RH) (>70%) and high PM1 mass concentration (>50 μg m-3), demonstrating that oxidation capacity, heterogeneous and aqueous phase reactions are important for further oxidation. Additionally, increased SOA formation occurs under both higher hydrocarbon-like OA and more oxidized OOA conditions. Further oxidation of both freshly emitted and aged and/or transported OA can be a remarkable further source of SOA in winter in Seoul and further downwind areas. In particular, the high mass concentration of MO-OOA in high total PM1 would be an important indication that SOA formation could be accelerated by a heterogeneous reaction, necessitating additional investigations on the haze formation process.
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Affiliation(s)
- Yoojin Park
- Department of Environmental Science and Engineering, Ewha Womans University, Seoul, 03760, Republic of Korea
| | - Hwajin Kim
- Graduate School of Public Health, Seoul National University, Seoul, 08826, Republic of Korea.
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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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Lin Y, Wu Y, Lin JJ. Building an oxidation reactor in Taiwan: From volatile organic compounds to secondary organic aerosols. J CHIN CHEM SOC-TAIP 2022. [DOI: 10.1002/jccs.202200470] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Yen‐Hsiu Lin
- Institute of Atomic and Molecular Sciences, Academia Sinica Taipei Taiwan
- Department of Chemistry National Taiwan University Taipei Taiwan
| | - Yen‐Ju Wu
- Institute of Atomic and Molecular Sciences, Academia Sinica Taipei Taiwan
- Department of Chemistry National Taiwan University Taipei Taiwan
| | - Jim Jr‐Min Lin
- Institute of Atomic and Molecular Sciences, Academia Sinica Taipei Taiwan
- Department of Chemistry National Taiwan University Taipei Taiwan
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10
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Yao D, Guo H, Lyu X, Lu H, Huo Y. Secondary organic aerosol formation at an urban background site on the coastline of South China: Precursors and aging processes. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 309:119778. [PMID: 35841994 DOI: 10.1016/j.envpol.2022.119778] [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: 05/12/2022] [Revised: 07/02/2022] [Accepted: 07/11/2022] [Indexed: 06/15/2023]
Abstract
Understanding the formation mechanisms of secondary organic aerosols (SOA) is an arduous task in atmospheric chemistry. In November 2018, a sampling campaign was conducted at an urban background site in Hong Kong for characterization of secondary air pollution. A high-resolution time-of-flight aerosol mass spectrometer was used to monitor the compositions of non-refractory submicron particulate matters (NR-PM1), and multiple online instruments provided us with comprehensive auxiliary data. Organic aerosol (OA) constituted the largest fraction (43.8%) of NR-PM1, and 86.5% of the organics was contributed by the oxygenated OA (OOA, secondary components). Formation mechanisms of a dominant and more variable component of the less-oxidized OOA (labelled as LO-OOA1 in this study) and the more-oxidized OOA (MO-OOA) were explored. Based on the multilinear regression with molecular markers of OA (e.g., hydroxybenzonic acids and 2,3-dihydroxy-4-oxopentanoic acid), we presumed that anthropogenic organic compounds, especially aromatics, were the most likely precursors of LO-OOA1. MO-OOA correlated well with odd oxygen (Ox), and its concentration responded positively to the increase of liquid water content (LWC) in NR-PM1, indicating that the formation of MO-OOA involved photochemical oxidation and aqueous processes. It exhibited the best correlation with malic acid which can be formed through the oxidation of various precursors. Moreover, it was plausible that LO-OOA1 was further oxidized to MO-OOA through aqueous processes, as indicated by the consistent diurnal variations of MO-OOA to LO-OOA1 ratio and LWC. This study highlights the important roles of anthropogenic emissions and aqueous processes in SOA formation in coastal areas downwind of cities.
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Affiliation(s)
- Dawen Yao
- Air Quality Studies, Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Hai Guo
- Air Quality Studies, Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
| | - Xiaopu Lyu
- Air Quality Studies, Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Haoxian Lu
- Air Quality Studies, Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Yunxi Huo
- Air Quality Studies, Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
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Liu J, Chu B, Jia Y, Cao Q, Zhang H, Chen T, Ma Q, Ma J, Wang Y, Zhang P, He H. Dramatic decrease of secondary organic aerosol formation potential in Beijing: Important contribution from reduction of coal combustion emission. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 832:155045. [PMID: 35398421 DOI: 10.1016/j.scitotenv.2022.155045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Revised: 03/23/2022] [Accepted: 04/01/2022] [Indexed: 06/14/2023]
Abstract
Secondary organic aerosol (SOA) formation originating from the emission of anthropogenic volatile organic compounds (VOCs) makes a significant contribution to fine particulate matter (PM2.5) pollution in urban areas. Investigation on the SOA formation potential (SOAFP) can help us understand the contribution of different sources to SOA formation. To characterize the SOAFP of ambient air from anthropogenic VOCs in the urban area of Beijing, field observation was implemented using a twin oxidation flow reactor (Twin-OFRs) system in the winters of 2016 and 2017. Compared to the winter of 2016, the seasonal-average SOAFP in the winter of 2017 was found to decrease by about 74% (18.6 to 4.9 μg/m3), which is more than that of PM1 (59%, 48.7 to 20.2 μg/m3), PM2.5 (61%, 114.4 to 44.8 μg/m3) and CO (57%, 2.1 to 0.9 mg/m3) that mainly comes from the combustion of fossil fuels, suggesting complex affecting factors on SOAFP. The results of wind decomposition mathematical modeling showed that anthropogenic factors and favorable meteorological conditions both contributed significantly to the decrease in SOAFP. The reduction of emissions from scatter coal combustion, which is the key VOCs source for SOAFP, is probably the most important anthropogenic factor affecting SOAFP. In the winter of 2016, the ratio of benzene to toluene is 1.45 that was close to 1.54 representing coal combustion emission; however, it decreased dramatically to 1.05 in the winter of 2017, suggesting considerable reduction of VOC emissions from scatter coal combustion in the latter year due to the coal-to-gas transition in Beijing and surrounding regions. The SOAFP measured in this study considers all ambient VOCs that can react with OH radical, providing another representative method for estimating it. These results could be beneficial to understanding the factors driving SOAFP and its contribution to PM2.5, especially in regions with high-intensity anthropogenic emissions. Synopsis: This study reported the sharp decline of secondary organic aerosol formation potential (SOAFP) between two consecutive winters in Beijing and analyzed the reasons.
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Affiliation(s)
- Jun Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Biwu Chu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Yongcheng Jia
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Qing Cao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Hong Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Beijing Key Lab for Source Control Technology of Water Pollution, College of Environmental Science and Engineering, Beijing Forestry University, Beijing 100083, China; Engineering Research Center for Water Pollution Source Control & Eco-remediation, College of Environmental Science and Engineering, Beijing Forestry University, Beijing 100083, China
| | - Tianzeng Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Qingxin Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinzhu Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yonghong Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Peng Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Hong He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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12
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Hu W, Zhou H, Chen W, Ye Y, Pan T, Wang Y, Song W, Zhang H, Deng W, Zhu M, Wang C, Wu C, Ye C, Wang Z, Yuan B, Huang S, Shao M, Peng Z, Day DA, Campuzano-Jost P, Lambe AT, Worsnop DR, Jimenez JL, Wang X. Oxidation Flow Reactor Results in a Chinese Megacity Emphasize the Important Contribution of S/IVOCs to Ambient SOA Formation. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:6880-6893. [PMID: 34898185 DOI: 10.1021/acs.est.1c03155] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Oxygenated volatile organic compounds (OVOCs) and secondary organic aerosol (SOA) formation potential of ambient air in Guangzhou, China was investigated using a field-deployed oxidation flow reactor (OFR). The OFR was used to mimic hours to weeks of atmospheric exposure to hydroxyl (OH) radicals within the 2-3 min residence time. A comprehensive investigation on the variation of VOCs and OVOCs as a function of OH exposure is shown. Substantial formation of organic acids and nitrogen-containing OVOC species were observed. Maximum SOA formation in the OFR was observed following 1-4 equiv days' OH exposure. SOA produced from known/measured VOC/IVOC precursors such as single-ring aromatics and long-chain alkanes can account for 52-75% of measured SOA under low NOx and 26-60% under high NOx conditions based on laboratory SOA yield parametrizations. To our knowledge, this is the first time that the contribution (8-20%) of long-chain (C8-C20) alkane oxidation to OFR SOA formation was quantified from direct measurement. By additionally estimating contribution from unmeasured semivolatile and intermediate volatility compounds (S/IVOCs) that are committed with C8-C20 alkanes, 64-100% of the SOA formation observed in the OFR can be explained, signifying the important contribution of S/IVOCs such as large cyclic alkanes to ambient SOA.
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Affiliation(s)
- Weiwei Hu
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, Guangdong 510640. China
- CAS Center for Excellence in Deep Earth Science, Guangzhou, Guangdong 510640, China
- Guangdong-Hong Kong-Macao, Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Science, Guangzhou, Guangdong 510640. China
- Guangdong Provincial Key Laboratory of Environmental Protection and Resources Utilization, Chinese Academy of Science, Guangzhou, Guangdong 510640. China
| | - Huaishan Zhou
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, Guangdong 510640. China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Chen
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, Guangdong 510640. China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuqing Ye
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, Guangdong 510640. China
| | - Tianle Pan
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, Guangdong 510640. China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yingkun Wang
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, Guangdong 510640. China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Song
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, Guangdong 510640. China
- CAS Center for Excellence in Deep Earth Science, Guangzhou, Guangdong 510640, China
- Guangdong-Hong Kong-Macao, Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Science, Guangzhou, Guangdong 510640. China
- Guangdong Provincial Key Laboratory of Environmental Protection and Resources Utilization, Chinese Academy of Science, Guangzhou, Guangdong 510640. China
| | - Huina Zhang
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, Guangdong 510640. China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Deng
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, Guangdong 510640. China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Ming Zhu
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, Guangdong 510640. China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chaomin Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, Guangdong 511443, China
| | - Caihong Wu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, Guangdong 511443, China
| | - Chenshuo Ye
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, Guangdong 511443, China
| | - Zelong Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, Guangdong 511443, China
| | - Bin Yuan
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, Guangdong 511443, China
| | - Shan Huang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, Guangdong 511443, China
| | - Min Shao
- Institute for Environmental and Climate Research, Jinan University, Guangzhou, Guangdong 511443, China
| | - Zhe Peng
- Cooperative Institute for Research in the Environmental Sciences (CIRES), University of Colorado at Boulder, Boulder, Colorado 80309, United States
- Department of Chemistry, University of Colorado at Boulder, Boulder, Colorado 80309, United States
| | - Douglas A Day
- Cooperative Institute for Research in the Environmental Sciences (CIRES), University of Colorado at Boulder, Boulder, Colorado 80309, United States
- Department of Chemistry, University of Colorado at Boulder, Boulder, Colorado 80309, United States
| | - Pedro Campuzano-Jost
- Cooperative Institute for Research in the Environmental Sciences (CIRES), University of Colorado at Boulder, Boulder, Colorado 80309, United States
- Department of Chemistry, University of Colorado at Boulder, Boulder, Colorado 80309, United States
| | - Andrew T Lambe
- Aerodyne Research Inc., Billerica, Massachusetts 01821, United States
| | - Douglas R Worsnop
- Aerodyne Research Inc., Billerica, Massachusetts 01821, United States
| | - Jose L Jimenez
- Cooperative Institute for Research in the Environmental Sciences (CIRES), University of Colorado at Boulder, Boulder, Colorado 80309, United States
- Department of Chemistry, University of Colorado at Boulder, Boulder, Colorado 80309, United States
| | - Xinming Wang
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou, Guangdong 510640. China
- CAS Center for Excellence in Deep Earth Science, Guangzhou, Guangdong 510640, China
- Guangdong-Hong Kong-Macao, Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Science, Guangzhou, Guangdong 510640. China
- Guangdong Provincial Key Laboratory of Environmental Protection and Resources Utilization, Chinese Academy of Science, Guangzhou, Guangdong 510640. China
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13
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Xu W, Li Z, Lambe AT, Li J, Liu T, Du A, Zhang Z, Zhou W, Sun Y. Secondary organic aerosol formation and aging from ambient air in an oxidation flow reactor during wintertime in Beijing, China. ENVIRONMENTAL RESEARCH 2022; 209:112751. [PMID: 35077717 DOI: 10.1016/j.envres.2022.112751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 01/05/2022] [Accepted: 01/14/2022] [Indexed: 06/14/2023]
Abstract
Secondary organic aerosols (SOA) constitute a large fraction of atmospheric aerosols, yet our knowledge of the formation and aging processes of SOA in megacities of China is still limited. In this work, the formation and aging processes of SOA in winter in Beijing was investigated using a high-resolution aerosol mass spectrometer (AMS) and an oxidation flow reactor (OFR). Our results showed that the OA enhancement from OH aging peaked at ∼3.9 equivalent days with an average enhancement of 0.9 (±0.3) μg m-3. Positive matrix factorization analysis of AMS-OFR data identified three primary OA (POA) and two SOA factors. While the concentrations of POA factors decreased as a function of photochemical age, the two SOA factors showed clear enhancements by 2.5 and 4.3 μg m-3 at ∼3.9 and ∼2.6 days of equivalent photochemical age, respectively. The average contribution of SOA to the total OA was 47% in ambient air and 87% in OFR-oxidized ambient air. The elevated oxygen-to-carbon (O/C) ratio from 0.49 to 0.77-0.82 and the decreased hydrogen-to-carbon (H/C) from 1.37 to ∼1.1 highlighted the formation of more oxidized SOA during photochemical aging in winter in Beijing. The ubiquitous SOA enhancement as a function of OA levels indicated the significant formation potential of SOA in winter, and it varied differently among different episodes. In particular, we observed a maximum SOA enhancement of 38.6 μg m-3 during a biomass burning event. This result demonstrates that photochemical oxidation of ubiquitous biomass burning emissions can be a large source of SOA in winter in North China Plain.
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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
| | - Zhijie Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | | | - Jinjian Li
- Division of Environment and Sustainability, Hong Kong University of Science and Technology, Hong Kong, China
| | - Tengyu Liu
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
| | - Aodong Du
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhiqiang Zhang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Wei Zhou
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China; College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China; Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China.
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14
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Wang H, Guo S, Wu Z, Qiao K, Tang R, Yu Y, Xu W, Zhu W, Zeng L, Huang X, He L, Hallquist M. Secondary organic aerosol formation from straw burning using an oxidation flow reactor. J Environ Sci (China) 2022; 114:249-258. [PMID: 35459490 DOI: 10.1016/j.jes.2021.08.049] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Revised: 08/22/2021] [Accepted: 08/25/2021] [Indexed: 06/14/2023]
Abstract
Herein, we use an oxidation flow reactor, Gothenburg: Potential Aerosol Mass (Go: PAM) reactor, to investigate the secondary organic aerosol (SOA) formation from wheat straw burning. Biomass burning emissions are exposed to high concentrations of hydroxyl radicals (OH) to simulate processes equivalent to atmospheric oxidation of 0-2.55 days. Primary volatile organic compounds (VOCs) were investigated, and particles were measured before and after the Go: PAM reactor. The influence of water content (i.e. 5% and 11%) in wheat straw was also explored. Two burning stages, the flaming stage, and non-flaming stages, were identified. Primary particle emission factors (EFs) at a water content of 11% (∼3.89 g/kg-fuel) are significantly higher than those at a water content of 5% (∼2.26 g/kg-fuel) during the flaming stage. However, the water content showed no significant influence at the non-flaming stage. EFs of aromatics at a non-flaming stage (321.8±46.2 mg/kg-fuel) are larger than that at a flaming stage (130.9±37.1 mg/kg-fuel). The OA enhancement ratios increased with the increase in OH exposure at first and decreased with the additional increment of OH exposure. The maximum OA enhancement ratio is ∼12 during the non-flaming stages, which is much higher than ∼ 1.7 during the flaming stages. The mass spectrum of the primary wheat burning organic aerosols closely resembles that of resolved biomass burning organic aerosols (BBOA) based on measurements in ambient air. Our results show that large gap (∼60%-90%) still remains to estimate biomass burning SOA if only the oxidation of VOCs were included.
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Affiliation(s)
- 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
| | - 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; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 10044, China.
| | - Zhijun Wu
- 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; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 10044, China.
| | - Kai Qiao
- 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
| | - Rongzhi 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
| | - 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
| | - Weizhao Xu
- 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
| | - Liwu Zeng
- Key Laboratory for Urban Habitat Environmental Science and Technology, College of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Xiaofeng Huang
- Key Laboratory for Urban Habitat Environmental Science and Technology, College of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Lingyan He
- Key Laboratory for Urban Habitat Environmental Science and Technology, College of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Mattias Hallquist
- Department of Chemistry and Molecular Biology, Atmospheric Science, University of Gothenburg, SE-412 96 Gothenburg, Sweden
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15
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Sahu LK, Tripathi N, Gupta M, Singh V, Yadav R, Patel K. Impact of COVID-19 Pandemic Lockdown in Ambient Concentrations of Aromatic Volatile Organic Compounds in a Metropolitan City of Western India. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2022; 127:e2022JD036628. [PMID: 35602912 PMCID: PMC9111284 DOI: 10.1029/2022jd036628] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 03/06/2022] [Indexed: 06/15/2023]
Abstract
The real-time Benzene, Toluene, Ethylbenzene, and Xylenes (BTEX) concentrations were measured in a metropolitan city of India during January to May of 2020 and 2014-2015-2018 to assess the impact of emission reduction during the COVID-19 lockdown. The total BTEX (∑BTEX) concentrations were 11.5 ± 9.0, 15.7 ± 16, 5.3 ± 5.0, 2.9 ± 2.0, and 0.93 ± 1.2 ppbv in January-May 2020, respectively. The evening rush hour peaks of BTEX during lockdown decreased by 4-5 times from the same period of years 2014-2015-2018. A significant decline in background concentrations suggests a regional-scale reduction in anthropogenic emissions. The contributions of ∑TEX compounds to ∑BTEX increased from 42% to 59% in winter to 64%-75% during the lockdown under hot summer conditions. While emission reductions dominated during the lockdown period, the meteorological and photochemical factors may also have contributed. Meteorological influence on actual observed BTEX data was removed by normalizing with ventilation coefficient (VC). The actual ambient air reductions of 85%-90% and VC-normalized reductions of 54%-88% of the BTEX concentrations during lockdown were estimated compared to those during the same period of 2014-2015-2018. The estimated changes using nighttime data, which take into account BTEX photooxidation removal, are ∼8% lower than the VC-normalized estimates using all data. These significant reductions in BTEX concentrations are consistent with the change in people's movement as inferred from mobility data during the lockdown. Although enforced, the significant decline in ambient BTEX levels during lockdown was a good change for the air quality. The study suggests a need for more effective science-based policies that consider local and regional factors.
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Affiliation(s)
- L. K. Sahu
- Physical Research Laboratory (PRL)AhmedabadIndia
| | | | - Mansi Gupta
- Physical Research Laboratory (PRL)AhmedabadIndia
- Indian Institute of Technology GandhinagarGandhinagarIndia
| | - Vikas Singh
- National Atmospheric Research Laboratory (NARL)GadankiIndia
| | - Ravi Yadav
- Indian Institute of Tropical Meteorology (IITM)PuneIndia
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16
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Xing L, Fu TM, Liu T, Qin Y, Zhou L, Chan CK, Guo H, Yao D, Duan K. Estimating organic aerosol emissions from cooking in winter over the Pearl River Delta region, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 292:118266. [PMID: 34610414 DOI: 10.1016/j.envpol.2021.118266] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 09/09/2021] [Accepted: 09/29/2021] [Indexed: 06/13/2023]
Abstract
Cooking is an important source of organic aerosols (OA), particularly in urban areas, but it has not been explicitly included in current emission inventories in China. This study estimated the organic aerosol emissions from cooking during winter over the Pearl River Delta (PRD) region, China. Using the retrieved hourly cooking organic aerosol (COA) concentrations at two sites in Hong Kong and Guangzhou, population density, and daily per capita COA emissions, we determined the spatial and temporal distribution of COA emissions over the PRD region based on two approaches by treating COA as non-volatile (NVCOA) and semi-volatile (SVCOA), respectively. By using the estimated COA emissions and the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) model, we reproduced the diurnal cycles of COA concentrations at the PolyU site in Hong Kong and Panyu site in Guangzhou. We also resolved the different patterns of COA between weekdays and weekends. The mean COA concentration during wintertime over the urban areas of the PRD region was 0.7 μg m-3 and 0.9 μg m-3 for the NVCOA and SVCOA cases, respectively, contributing 5.1% and 6.9% to the urban OA concentrations. The total COA emissions in winter over the PRD region were estimated to be 3.5 × 108 g month-1 and 3.8 × 108 g month-1 for the NVCOA and SVCOA cases, respectively, adding 34.8% and 37.8% to the total primary organic aerosol emissions. Considering COA emissions in the model increased the mean regional OA concentrations by 4.6% and 7.4% for the NVCOA and SVCOA cases, respectively. Our study therefore highlights the importance of cooking activities to OA concentrations in winter over the PRD region.
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Affiliation(s)
- Li Xing
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, Shaanxi, China.
| | - Tzung-May Fu
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; Shenzhen Institute of Sustainable Development, Southern University of Science and Technology, Shenzhen, Guangdong, China
| | - Tengyu Liu
- School of Energy and Environment, City University of Hong Kong, Hong Kong, China
| | - Yiming Qin
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, United States
| | - Liyuan Zhou
- School of Energy and Environment, City University of Hong Kong, Hong Kong, China
| | - Chak K Chan
- School of Energy and Environment, City University of Hong Kong, Hong Kong, China
| | - Hai Guo
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Dawen Yao
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Keqin Duan
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, Shaanxi, China
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17
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Wang H, Guo S, Yu Y, Shen R, Zhu W, Tang R, Tan R, Liu K, Song K, Zhang W, Zhang Z, Shuai S, Xu H, Zheng J, Chen S, Li S, Zeng L, Wu Z. Secondary aerosol formation from a Chinese gasoline vehicle: Impacts of fuel (E10, gasoline) and driving conditions (idling, cruising). THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 795:148809. [PMID: 34328915 DOI: 10.1016/j.scitotenv.2021.148809] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 06/16/2021] [Accepted: 06/29/2021] [Indexed: 06/13/2023]
Abstract
Chassis dynamometer experiments were conducted to investigate the effect of vehicle speed and usage of ethanol-blended gasoline (E10) on formation and evolution of gasoline vehicular secondary organic aerosol (SOA) using a Gothenburg Potential Aerosol Mass (Go: PAM) reactor. The SOA forms rapidly, and its concentration exceeds that of primary organic aerosol (POA) at an equivalent photochemical age (EPA) of ~1 day. The particle effective densities grow from 0.62 ± 0.02 g cm-3 to 1.43 ± 0.07 g cm-3 with increased hydroxyl radical (OH) exposure. The maximum SOA production under idling conditions (4259-7394 mg kg-fuel-1) is ~20 times greater than under cruising conditions. There was no statistical difference between SOA formation from pure gasoline and its formation from E10. The slopes in Van Krevelen diagram indicate that the formation pathways of bulk SOA includes the addition of both alcohol/peroxide functional groups and carboxylic acid formation from fragmentation. A closure estimation of SOA based on bottom-up and top-down methods shows that only 16%-38% of the measured SOA can be explained by the oxidation of measured volatile organic compounds (VOCs), suggesting the existence of missing precursors, e.g. unmeasured VOCs and probably semivolatile or intermediate volatile organic compounds (S/IVOCs). Our results suggest that applying parameters obtained from unified driving cycles to model SOA concentrations may lead to large discrepancies between modeled and ambient vehicular SOA. No reduction in vehicular `SOA production is realized by replacing normal gasoline with E10.
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Affiliation(s)
- 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, PR China
| | - 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, PR China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, PR 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, PR 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, PR 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, PR China
| | - Rongzhi 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, PR 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, PR China
| | - Kefan Liu
- 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, PR 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, PR China
| | - Wenbin Zhang
- State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100871, PR China
| | - Zhou Zhang
- State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100871, PR China
| | - Shijin Shuai
- State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100871, PR China
| | - Hongming Xu
- State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100871, PR China
| | - Jing Zheng
- Chinese Academy of Meteorological Science, Beijing 100871, PR 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, PR China
| | - Shaomeng Li
- 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, PR China
| | - Limin Zeng
- 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, PR China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, PR China
| | - Zhijun Wu
- 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, PR China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, PR China
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18
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Zhou L, Liu T, Yao D, Guo H, Cheng C, Chan CK. Primary emissions and secondary production of organic aerosols from heated animal fats. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 794:148638. [PMID: 34217089 DOI: 10.1016/j.scitotenv.2021.148638] [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: 04/18/2021] [Revised: 06/17/2021] [Accepted: 06/20/2021] [Indexed: 06/13/2023]
Abstract
Cooking is an important source of primary organic aerosol (POA) in urban areas, and it may also generate abundant non-methane organic gases (NMOGs), which form oxidized organic aerosol (OOA) after atmospheric oxidation. Edible fats play an important role in a balanced diet and are part of various types of cooking. We conducted laboratory studies to examine the primary emissions of POA and NMOGs and OOA formation using an oxidation flow reactor (OFR) for three animal fats (i.e., lard, beef and chicken fats) heated at two different temperatures (160 and 180 °C). Positive matrix factorization (PMF) revealed that OOA formed together with POA loss after photochemical aging, suggesting the conversion of some POA to OOA. The maximum OOA production rates (PRs) from heated animal fats, occurring under OH exposures (OHexp) of 8.3-15 × 1010 molecules cm-3 s, ranged from 8.9 to 24.7 μg min-1, 1.6-14.5 times as high as initial POA emission rates (ERs). NMOG emissions from heated animal fats were dominated by aldehydes, which contributed 14-71% of the observed OOA. We estimated that cooking-related OOA could contribute to as high as ~10% of total organic aerosol (OA) in an urban area in Hong Kong, where cooking OA (COA) dominated the POA. This study provides insights into the potential contribution of cooking to urban OOA, which might be especially pronounced when cooking contributions dominate the primary emissions.
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Affiliation(s)
- Liyuan Zhou
- School of Energy and Environment, City University of Hong Kong, Hong Kong, China
| | - Tengyu Liu
- Joint International Research Laboratory of Atmospheric and Earth System Sciences, School of Atmospheric Sciences, Nanjing University, Nanjing, China.
| | - Dawen Yao
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Hai Guo
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, 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, China
| | - Chak K Chan
- School of Energy and Environment, City University of Hong Kong, Hong Kong, China.
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19
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Zhou L, Salvador CM, Priestley M, Hallquist M, Liu Q, Chan CK, Hallquist ÅM. Emissions and Secondary Formation of Air Pollutants from Modern Heavy-Duty Trucks in Real-World Traffic-Chemical Characteristics Using On-Line Mass Spectrometry. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:14515-14525. [PMID: 34652131 PMCID: PMC8567417 DOI: 10.1021/acs.est.1c00412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 08/02/2021] [Accepted: 09/09/2021] [Indexed: 06/13/2023]
Abstract
Complying with stricter emissions standards, a new generation of heavy-duty trucks (HDTs) has gradually increased its market share and now accounts for a large percentage of on-road mileage. The potential to improve air quality depends on an actual reduction in both emissions and subsequent formation of secondary pollutants. In this study, the emissions in real-world traffic from Euro VI-compliant HDTs were compared to those from older classes, represented by Euro V, using high-resolution time-of-flight chemical ionization mass spectrometry. Gas-phase primary emissions of several hundred species were observed for 70 HDTs. Furthermore, the particle phase and secondary pollutant formation (gas and particle phase) were evaluated for a number of HDTs. The reduction in primary emission factors (EFs) was evident (∼90%) and in line with a reduction of 28-97% for the typical regulated pollutants. Secondary production of most gas- and particle-phase compounds, for example, nitric acid, organic acids, and carbonyls, after photochemical aging in an oxidation flow reactor exceeded the primary emissions (EFAged/EFFresh ratio ≥2). Byproducts from urea-selective catalytic reduction systems had both primary and secondary sources. A non-negative matrix factorization analysis highlighted the issue of vehicle maintenance as a remaining concern. However, the adoption of Euro VI has a significant positive effect on emissions in real-world traffic and should be considered in, for example, urban air quality assessments.
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Affiliation(s)
- Liyuan Zhou
- School
of Energy and Environment, City University
of Hong Kong, Hong Kong, China
| | - Christian M. Salvador
- Department
of Chemistry and Molecular Biology, University
of Gothenburg, 412 96 Gothenburg, Sweden
| | - Michael Priestley
- Department
of Chemistry and Molecular Biology, University
of Gothenburg, 412 96 Gothenburg, Sweden
| | - Mattias Hallquist
- Department
of Chemistry and Molecular Biology, University
of Gothenburg, 412 96 Gothenburg, Sweden
| | - Qianyun Liu
- School
of Energy and Environment, City University
of Hong Kong, Hong Kong, China
| | - Chak K. Chan
- School
of Energy and Environment, City University
of Hong Kong, Hong Kong, China
| | - Åsa M. Hallquist
- IVL
Swedish Environmental Research Institute, 400 14 Gothenburg, Sweden
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20
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Park G, Kim K, Park T, Kang S, Ban J, Choi S, Yu DG, Lee S, Lim Y, Kim S, Mun S, Woo JH, Jeon CS, Lee T. Primary and secondary aerosols in small passenger vehicle emissions: Evaluation of engine technology, driving conditions, and regulatory standards. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 286:117195. [PMID: 33975218 DOI: 10.1016/j.envpol.2021.117195] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 04/01/2021] [Accepted: 04/19/2021] [Indexed: 06/12/2023]
Abstract
The characteristics of primary gas/aerosol and secondary aerosol emissions were identified for small passenger vehicles using typical fuel types in South Korea (gasoline, liquefied petroleum gas (LPG), and diesel). The generation of secondary organic aerosol (SOA) was explored using the potential aerosol mass (PAM) oxidation flow reactor. The primary emissions did not vary significantly between fuel types, combustion technologies, or aftertreatment systems, while the amount of NH3 was higher in gasoline and LPG vehicle emissions than that in diesel vehicle emissions. The SOA emission factor was 11.7-66 mg kg-fuel-1 for gasoline vehicles, 2.4-50 mg kg-fuel-1 for non-diesel particulate filter (non-DPF) diesel vehicles (EURO 2-3), 0.4-40 mg kg-fuel-1 for DPF diesel vehicles (EURO 4-6), and 3-11 mg kg-fuel-1 for LPG vehicles (lowest). The carbonaceous aerosols (equivalent black carbon (eBC) + primary organic aerosol + SOA) of diesel vehicles in EURO 4-6 were reduced by up to 95% compared to those in EURO 2-3. The expected SOA yield increased through the hot-condition combustion section of a vehicle, over the SOA range of 0.2-155 μg m-3. These results provide the necessary data to analyze all types of SOA generated by the gas-phase oxidation in vehicle emissions in metropolitan areas.
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Affiliation(s)
- Gyutae Park
- Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, 17035, South Korea
| | - Kyunghoon Kim
- Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, 17035, South Korea
| | - Taehyun Park
- Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, 17035, South Korea
| | - Seokwon Kang
- Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, 17035, South Korea
| | - Jihee Ban
- Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, 17035, South Korea
| | - Siyoung Choi
- Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, 17035, South Korea
| | - Dong-Gil Yu
- Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, 17035, South Korea
| | - Sanguk Lee
- Transportation Pollution Research Center, National Institute of Environmental Research, Incheon, 22689, South Korea
| | - Yunsung Lim
- Transportation Pollution Research Center, National Institute of Environmental Research, Incheon, 22689, South Korea
| | - Sunmoon Kim
- Transportation Pollution Research Center, National Institute of Environmental Research, Incheon, 22689, South Korea
| | - Sunhee Mun
- Transportation Pollution Research Center, National Institute of Environmental Research, Incheon, 22689, South Korea
| | - Jung-Hun Woo
- Department of Civil and Environmental Engineering, Konkuk University, Seoul, 05029, South Korea
| | - Chan-Soo Jeon
- Korea Institute of Civil Engineering and Building Technology, Goyang, 10223, South Korea
| | - Taehyoung Lee
- Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, 17035, South Korea.
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21
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Liao K, Chen Q, Liu Y, Li YJ, Lambe AT, Zhu T, Huang RJ, Zheng Y, Cheng X, Miao R, Huang G, Khuzestani RB, Jia T. Secondary Organic Aerosol Formation of Fleet Vehicle Emissions in China: Potential Seasonality of Spatial Distributions. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:7276-7286. [PMID: 34009957 DOI: 10.1021/acs.est.0c08591] [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: 06/12/2023]
Abstract
Vehicle emissions are an important source of urban particular matter. To investigate the secondary organic aerosol (SOA) formation potential of real-world vehicle emissions, we exposed on-road air in Beijing to hydroxyl radicals generated in an oxidation flow reactor (OFR) under high-NOx conditions on-board a mobile laboratory and characterized SOA and their precursors with a suite of state-of-the-art instrumentation. The OFR produced 10-170 μg m-3 of SOA with a maximum SOA formation potential of 39-50 μg m-3 ppmv-1 CO that occurred following an integrated OH exposure of (1.3-2.0) × 1011 molecules cm-3 s. The results indicate relatively shorter photochemical ages for maximum SOA production than previous OFR results obtained under low-NOx conditions. Such timescales represent the balance of functionalization and fragmentation, possibly resulting in different spatial distributions of SOA in different seasons as the oxidant level changes. The detected precursors may explain as much as 13% of the observed SOA with the remaining plausibly contributed by the oxidation of undetected intermediate-volatility organic compounds. Extrapolation of the results suggests an annual SOA production rate of 0.78 Tg yr-1 from mobile gasoline sources in China, highlighting the importance of effective regulation of gaseous vehicular precursors to improve air quality in the future.
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Affiliation(s)
- Keren Liao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Qi Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Ying Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Yong Jie Li
- Department of Civil and Environmental Engineering, Faculty of Science and Technology, University of Macau, Taipa, Macau 999078, China
| | - Andrew T Lambe
- Aerodyne Research, Inc., Billerica, Massachusetts 01821, United States
| | - Tong Zhu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Ru-Jin Huang
- State Key Laboratory of Loess and Quaternary Geology, Center for Excellence in Quaternary Science and Global Change, and Key Laboratory of Aerosol Chemistry & Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710075, China
| | - Yan Zheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Xi Cheng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Ruqian Miao
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Guancong Huang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Reza Bashiri Khuzestani
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Tianjiao Jia
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, BIC-ESAT and IJRC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
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22
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Liu J, Chu B, Chen T, Zhong C, Liu C, Ma Q, Ma J, Zhang P, He H. Secondary Organic Aerosol Formation Potential from Ambient Air in Beijing: Effects of Atmospheric Oxidation Capacity at Different Pollution Levels. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:4565-4572. [PMID: 33733751 DOI: 10.1021/acs.est.1c00890] [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] [Indexed: 06/12/2023]
Abstract
Secondary organic aerosol (SOA) plays a critical role in sustained haze pollution in megacities. Traditional observation of atmospheric aerosols usually analyzes the ambient organic aerosol (OA) but neglects the SOA formation potential (SOAFP) of precursors remaining in ambient air. Knowledge on SOAFP is still limited, especially in megacities suffering from frequent haze. In this study, the SOAFP of ambient air in urban Beijing was characterized at different pollution levels based on a two-year field observation using an oxidation flow reactor (OFR) system. Both OA and SOAFP increased as a function of ambient pollution level, in which increasing concentrations of precursor volatile organic compounds (VOCs) and decreasing atmospheric oxidation capacity were found to be the two main influencing factors. To address the role of the atmospheric oxidation capacity in SOAFP, a relative OA enhancement ratio (EROA = 1 + SOAFP/OA) and the elemental composition of the OA were investigated in this study. The results indicated that the atmospheric oxidation capacity was weakened and resulted in higher SOAFP on more polluted days. The relationship found between SOAFP and the atmospheric oxidation capacity could be helpful in understanding changes in SOA pollution with improving air quality in the megacities of developing countries.
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Affiliation(s)
- Jun Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Biwu Chu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tianzeng Chen
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Cheng Zhong
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Changgeng Liu
- School of Biological and Chemical Engineering, Panzhihua University, Panzhihua 617000, China
| | - Qingxin Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinzhu Ma
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Peng Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Hong He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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23
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Gen M, Zhou L, Zhang R, Chan CK. Concluding remarks: Faraday Discussion on air quality in megacities. Faraday Discuss 2021; 226:617-628. [PMID: 33650602 DOI: 10.1039/d0fd90037k] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Megacities are metropolitan areas with populations over 10 million, and many of them are facing significant global environmental challenges such as air pollution. Intense economic and human activities in megacities result in air pollution emissions, inducing high levels of air pollutants in the atmosphere that harm human health, cause regional haze and acid deposition, damage crops, influence regional air quality, and contribute to climate change. Since the Great London Smog and the first recognized episode of Los Angeles photochemical smog seventy years ago, substantial progress has been achieved in improving the scientific understanding of air pollution and in developing emissions reduction technologies and control measures. However, much remains to be understood about the complex processes of atmospheric transport and reaction mechanisms; the formation and evolution of secondary particles, especially those containing organic species; and the influence of emerging emissions sources and changing climate on air quality and health. Molina (DOI: ) has provided an excellent overview of the sources of emissions in megacities, atmospheric physicochemical processes, air quality trends and management, and the impacts on health and climate for the introductory lecture of this Faraday Discussion.
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Affiliation(s)
- Masao Gen
- Faculty of Frontier Engineering, Institute of Science and Engineering, Kanazawa University, Kakuma-machi, Kanazawa 920-1192, Japan
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24
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Meng X, Wu Z, Guo S, Wang H, Liu K, Zong T, Liu Y, Zhang W, Zhang Z, Chen S, Zeng L, Hallquist M, Shuai S, Hu M. Humidity-Dependent Phase State of Gasoline Vehicle Emission-Related Aerosols. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:832-841. [PMID: 33377762 DOI: 10.1021/acs.est.0c05478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
The phase states of primarily emitted and secondarily formed aerosols from gasoline vehicle exhausts were investigated by quantifying the particle rebound fraction (f). The rebound behaviors of gasoline vehicle emission-related aerosols varied with engines, fuel types, and photochemical aging time, showing distinguished differences from biogenic secondary organic aerosols. The nonliquid-to-liquid phase transition of primary aerosols emitted from port fuel injection (PFI) and gasoline direct injection (GDI) vehicles started at a relative humidity (RH) = 50 and 60%, and liquefaction was accomplished at 60 and 70%, respectively. The RH at which f declined to 0.5 decreased from 70 to 65% for the PFI case with 92# fuel, corresponding to the photochemical aging time from 0.37 to 4.62 days. For the GDI case, such RH enhanced from 60 to 65%. Our results can be used to imply the phase state of traffic-related aerosols and further understand their roles in urban atmospheric chemistry. Taking Beijing, China, as an example, traffic-related aerosols were mainly nonliquid during winter with the majority ambient RH below 50%, whereas they were mostly liquid during the morning rush hour of summer, and traffic-related secondary aerosols fluctuated between nonliquid and liquid during the daytime and tended to be liquid at night with increased ambient RH.
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Affiliation(s)
- Xiangxinyue Meng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Zhijun Wu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Song Guo
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Hui Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Kefan Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Taomou Zong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Yuechen Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Wenbin Zhang
- State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
| | - Zhou Zhang
- State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
| | - Shiyi Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Limin Zeng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Mattias Hallquist
- Department of Chemistry and Molecular Biology, Atmospheric Science, University of Gothenburg, Gothenburg SE-412 96, Sweden
| | - Shijin Shuai
- State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
| | - Min Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
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25
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Wang Y, Wang Q, Ye J, Li L, Zhou J, Ran W, Zhang R, Wu Y, Cao J. Chemical composition and sources of submicron aerosols in winter at a regional site in Beijing-Tianjin-Hebei region: Implications for the Joint Action Plan. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 719:137547. [PMID: 32143101 DOI: 10.1016/j.scitotenv.2020.137547] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2019] [Revised: 02/23/2020] [Accepted: 02/24/2020] [Indexed: 06/10/2023]
Abstract
The Ministry of Environmental Protection released a Joint Action Plan for Control of Air Pollution (Hereafter, Joint Action Plan, JAP), to reduce PM2.5 concentrations in the Beijing-Tianjin-Hebei region (BTH) during the winter of 2017. To investigate the effectiveness of the controls, we deployed an aerosol chemical speciation monitor and collected filter samples at Xianghe, a representative site for the BTH, to characterize the aerosol composition during the implementation of the JAP. Those results were compared with earlier data obtained from a literature survey and reanalysis of studies in the BTH. During several pollution episodes in the control period, the major aerosol types changed relative to the earlier studies from sulfate, oxygenated organic aerosol, and coal combustion organic aerosol to nitrate and biomass burning organic aerosol. The dominant secondary inorganic aerosol species during the JAP changed from sulfate to nitrate, and the main source for primary organic aerosol switched from coal combustion to biomass burning. These changes can be explained by the fact that the JAP controls targeted coal combustion and SO2 but not biomass burning or NOx emissions. Our evaluation of the control measures provides a scientific basis for developing new policies in the future.
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Affiliation(s)
- Yichen Wang
- School of Humanities, Economics and Law, Northwestern Polytechnical University, Xi'an 710129, China; Key Laboratory of Aerosol Chemistry and Physics, State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
| | - Qiyuan Wang
- Key Laboratory of Aerosol Chemistry and Physics, State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an 710061, China.
| | - Jianhuai Ye
- School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Li Li
- Key Laboratory of Aerosol Chemistry and Physics, State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
| | - Jun Zhou
- Graduate School of Global Environmental Studies, Kyoto University, Kyoto 6068501, Japan
| | - Weikang Ran
- Key Laboratory of Aerosol Chemistry and Physics, State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China
| | - Renjian Zhang
- Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; Xianghe Observatory of Whole Atmosphere, Institute of Atmospheric Physics, Chinese Academy of Sciences, Xianghe County, Hebei Province 065400, China
| | - Yunfei Wu
- Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Junji Cao
- Key Laboratory of Aerosol Chemistry and Physics, State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710061, China; CAS Center for Excellence in Quaternary Science and Global Change, Xi'an 710061, China.
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26
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Men C, Liu R, Xu L, Wang Q, Guo L, Miao Y, Shen Z. Source-specific ecological risk analysis and critical source identification of heavy metals in road dust in Beijing, China. JOURNAL OF HAZARDOUS MATERIALS 2020; 388:121763. [PMID: 31818668 DOI: 10.1016/j.jhazmat.2019.121763] [Citation(s) in RCA: 125] [Impact Index Per Article: 31.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Revised: 11/24/2019] [Accepted: 11/25/2019] [Indexed: 05/11/2023]
Abstract
To explore the spatial variation of source-specific ecological risks and identify critical sources of heavy metals in road dust, 36 road dust samples collected in Beijing in March 2017 were analyzed for heavy metals. A new method that takes into consideration the heavy-metal toxic response and is flexible to changes in the number of calculated heavy metals, called the Nemerow integrated risk index (NIRI), was developed for ecological risk assessment. The NIRI indicated that heavy metals posed considerable to high risks at the majority of sites, and 22 % of the sites suffered extreme risk in spring (NIRI > 320). Four main sources were identified based on positive matrix factorization (PMF): traffic exhaust, fuel combustion, construction, and use of pesticides and fertilizers. Owing to the lower toxic response factors of representative heavy metals of fuel combustion than those of other sources, although fuel combustion had the highest contribution (34.21 %) to heavy metals in spring, it only contributed 5.57 % to ecological risks. Critical sources and critical source areas were determined by considering the contributions to both heavy metals and ecological risks. The use of pesticide and fertilizer and traffic-related exhaust were identified as critical sources of heavy metals in spring. Source-specific ecological risks and critical sources of heavy metals changed with the changing seasons, which suggests that different strategies should be adopted in different seasons.
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Affiliation(s)
- Cong Men
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Ruimin Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Libing Xu
- College of Agronomy, Nanjing Agricultural University, Nanjing, 210095, China
| | - Qingrui Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Lijia Guo
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Yuexi Miao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Zhenyao Shen
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
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27
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Jorga SD, Kaltsonoudis C, Liangou A, Pandis SN. Measurement of Formation Rates of Secondary Aerosol in the Ambient Urban Atmosphere Using a Dual Smog Chamber System. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:1336-1343. [PMID: 31869213 DOI: 10.1021/acs.est.9b03479] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
A dual smog chamber system was used to quantify the formation rates of secondary organic and inorganic aerosol in an urban environment (Pittsburgh, US). Ambient air was introduced in both chambers, and HONO photolysis was used to produce hydroxyl radicals (OH) in the perturbed chamber. The second chamber was used as a reference. The production rate of secondary organic aerosol (SOA) under typical noon-time OH concentrations ranged from 0.2 to 0.8 μg m-3 h-1. The production rate of sulfate was approximately five times less than that of the SOA. Nucleation and growth of new particles were observed in the perturbation chamber. The produced SOA had a similar composition with the preexisting oxygenated ambient OA. The reacted amounts of the measured VOCs were able to explain 5-50% of the formed SOA in the perturbed chamber. Intermediate volatility organic compounds could be responsible for the rest. The oxygen to carbon ratio (O:C) in the perturbed chamber remained approximately the same during SOA production, while an increase was observed in the control chamber. A possible explanation could be the loss of less oxidized species to the chamber walls. After 2 h, the OA increased by 70% on average and the sulfate by 40%.
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Affiliation(s)
- Spiro D Jorga
- Department of Chemical Engineering , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States
| | - Christos Kaltsonoudis
- Department of Chemical Engineering , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States
| | - Aikaterini Liangou
- Institute of Chemical Engineering Sciences, ICE-HT , Patras GR-26504 , Greece
- Department of Chemical Engineering , University of Patras , Patras GR-26504 , Greece
| | - Spyros N Pandis
- Department of Chemical Engineering , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States
- Institute of Chemical Engineering Sciences, ICE-HT , Patras GR-26504 , Greece
- Department of Chemical Engineering , University of Patras , Patras GR-26504 , Greece
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28
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Shah RU, Coggon MM, Gkatzelis GI, McDonald BC, Tasoglou A, Huber H, Gilman J, Warneke C, Robinson AL, Presto AA. Urban Oxidation Flow Reactor Measurements Reveal Significant Secondary Organic Aerosol Contributions from Volatile Emissions of Emerging Importance. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:714-725. [PMID: 31851821 DOI: 10.1021/acs.est.9b06531] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Mobile sampling studies have revealed enhanced levels of secondary organic aerosol (SOA) in source-rich urban environments. While these enhancements can be from rapidly reacting vehicular emissions, it was recently hypothesized that nontraditional emissions (volatile chemical products and upstream emissions) are emerging as important sources of urban SOA. We tested this hypothesis by using gas and aerosol mass spectrometry coupled with an oxidation flow reactor (OFR) to characterize pollution levels and SOA potentials in environments influenced by traditional emissions (vehicular, biogenic), and nontraditional emissions (e.g., paint fumes). We used two SOA models to assess contributions of vehicular and biogenic emissions to our observed SOA. The largest gap between observed and modeled SOA potential occurs in the morning-time urban street canyon environment, for which our model can only explain half of our observation. Contributions from VCP emissions (e.g., personal care products) are highest in this environment, suggesting that VCPs are an important missing source of precursors that would close the gap between modeled and observed SOA potential. Targeted OFR oxidation of nontraditional emissions shows that these emissions have SOA potentials that are similar, if not larger, compared to vehicular emissions. Laboratory experiments reveal large differences in SOA potentials of VCPs, implying the need for further characterization of these nontraditional emissions.
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Affiliation(s)
- Rishabh U Shah
- Center for Atmospheric Particle Studies , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States
- Mechanical Engineering , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States
| | - Matthew M Coggon
- Chemical Sciences Division , National Oceanic and Atmospheric Administration, Earth Systems Research Laboratory , Boulder , Colorado 80305 , United States
- Cooperative Institute for Research in Environmental Sciences , University of Colorado , Boulder , Colorado 80309 , United States
| | - Georgios I Gkatzelis
- Chemical Sciences Division , National Oceanic and Atmospheric Administration, Earth Systems Research Laboratory , Boulder , Colorado 80305 , United States
- Cooperative Institute for Research in Environmental Sciences , University of Colorado , Boulder , Colorado 80309 , United States
| | - Brian C McDonald
- Chemical Sciences Division , National Oceanic and Atmospheric Administration, Earth Systems Research Laboratory , Boulder , Colorado 80305 , United States
- Cooperative Institute for Research in Environmental Sciences , University of Colorado , Boulder , Colorado 80309 , United States
| | - Antonios Tasoglou
- R. J. Lee Group Inc. , Monroeville , Pennsylvania 15146 , United States
| | - Heinz Huber
- R. J. Lee Group Inc. , Monroeville , Pennsylvania 15146 , United States
| | - Jessica Gilman
- Chemical Sciences Division , National Oceanic and Atmospheric Administration, Earth Systems Research Laboratory , Boulder , Colorado 80305 , United States
| | - Carsten Warneke
- Chemical Sciences Division , National Oceanic and Atmospheric Administration, Earth Systems Research Laboratory , Boulder , Colorado 80305 , United States
- Cooperative Institute for Research in Environmental Sciences , University of Colorado , Boulder , Colorado 80309 , United States
| | - Allen L Robinson
- Center for Atmospheric Particle Studies , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States
- Mechanical Engineering , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States
| | - Albert A Presto
- Center for Atmospheric Particle Studies , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States
- Mechanical Engineering , Carnegie Mellon University , Pittsburgh , Pennsylvania 15213 , United States
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29
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Peng Z, Jimenez JL. Radical chemistry in oxidation flow reactors for atmospheric chemistry research. Chem Soc Rev 2020; 49:2570-2616. [DOI: 10.1039/c9cs00766k] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
We summarize the studies on the chemistry in oxidation flow reactor and discuss its atmospheric relevance.
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Affiliation(s)
- Zhe Peng
- Cooperative Institute for Research in Environmental Sciences and Department of Chemistry
- University of Colorado
- Boulder
- USA
| | - Jose L. Jimenez
- Cooperative Institute for Research in Environmental Sciences and Department of Chemistry
- University of Colorado
- Boulder
- USA
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30
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Simonen P, Kalliokoski J, Karjalainen P, Rönkkö T, Timonen H, Saarikoski S, Aurela M, Bloss M, Triantafyllopoulos G, Kontses A, Amanatidis S, Dimaratos A, Samaras Z, Keskinen J, Dal Maso M, Ntziachristos L. Characterization of laboratory and real driving emissions of individual Euro 6 light-duty vehicles - Fresh particles and secondary aerosol formation. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2019; 255:113175. [PMID: 31542669 DOI: 10.1016/j.envpol.2019.113175] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 08/19/2019] [Accepted: 09/03/2019] [Indexed: 06/10/2023]
Abstract
Emissions from passenger cars are one of major sources that deteriorate urban air quality. This study presents characterization of real-drive emissions from three Euro 6 emission level passenger cars (two gasoline and one diesel) in terms of fresh particles and secondary aerosol formation. The gasoline vehicles were also characterized by chassis dynamometer studies. In the real-drive study, the particle number emissions during regular driving were 1.1-12.7 times greater than observed in the laboratory tests (4.8 times greater on average), which may be caused by more effective nucleation process when diluted by real polluted and humid ambient air. However, the emission factors measured in laboratory were still much higher than the regulatory value of 6 × 1011 particles km-1. The higher emission factors measured here result probably from the fact that the regulatory limit considers only non-volatile particles larger than 23 nm, whereas here, all particles (also volatile) larger than 3 nm were measured. Secondary aerosol formation potential was the highest after a vehicle cold start when most of the secondary mass was organics. After the cold start, the relative contributions of ammonium, sulfate and nitrate increased. Using a novel approach to study secondary aerosol formation under real-drive conditions with the chase method resulted mostly in emission factors below detection limit, which was not in disagreement with the laboratory findings.
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Affiliation(s)
- Pauli Simonen
- Aerosol Physics Laboratory, Physics Unit, Faculty of Engineering and Natural Sciences, Tampere University, Tampere, Finland.
| | - Joni Kalliokoski
- Aerosol Physics Laboratory, Physics Unit, Faculty of Engineering and Natural Sciences, Tampere University, Tampere, Finland.
| | - Panu Karjalainen
- Aerosol Physics Laboratory, Physics Unit, Faculty of Engineering and Natural Sciences, Tampere University, Tampere, Finland.
| | - Topi Rönkkö
- Aerosol Physics Laboratory, Physics Unit, Faculty of Engineering and Natural Sciences, Tampere University, Tampere, Finland.
| | - Hilkka Timonen
- Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland.
| | - Sanna Saarikoski
- Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland.
| | - Minna Aurela
- Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland.
| | - Matthew Bloss
- Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland.
| | | | - Anastasios Kontses
- Laboratory of Applied Thermodynamics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
| | - Stavros Amanatidis
- Laboratory of Applied Thermodynamics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
| | - Athanasios Dimaratos
- Laboratory of Applied Thermodynamics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
| | - Zissis Samaras
- Laboratory of Applied Thermodynamics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
| | - Jorma Keskinen
- Aerosol Physics Laboratory, Physics Unit, Faculty of Engineering and Natural Sciences, Tampere University, Tampere, Finland.
| | - Miikka Dal Maso
- Aerosol Physics Laboratory, Physics Unit, Faculty of Engineering and Natural Sciences, Tampere University, Tampere, Finland.
| | - Leonidas Ntziachristos
- Aerosol Physics Laboratory, Physics Unit, Faculty of Engineering and Natural Sciences, Tampere University, Tampere, Finland; Laboratory of Applied Thermodynamics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
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