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Wu Y, Liu B, Meng H, Wang F, Li S, Xu M, Shi L, Zhang S, Feng Y, Hopke PK. Unexpected changes in source apportioned results derived from different ambient VOC metrics. ENVIRONMENT INTERNATIONAL 2024; 190:108910. [PMID: 39094407 DOI: 10.1016/j.envint.2024.108910] [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: 03/09/2024] [Revised: 07/17/2024] [Accepted: 07/23/2024] [Indexed: 08/04/2024]
Abstract
Although most source apportionments of VOCs use mixing ratios, about 23 % of published studies use mass concentrations. Thus, systematically exploring the changes in VOC source apportioned results caused by metric differences is important to assess the differences in key precursor apportionment results given the observed increases in O3 pollution situation. Different monitoring instruments measured hourly VOC volumetric concentrations in three typical Chinese cities (i.e., Qingdao, Shijiazhuang, and Zhumadian). Converting volumetric to mass concentrations under standard and/or actual temperature-pressure conditions, VOC values with different metrics were obtained. The impacts of different metrics on the source apportionments were then investigated. Compared to the positive matrix factorization of the volumetric data (VC-PMF), the VOC species concentrations with low relative molecular mass (RMM) in the factor profiles substantially decreased in mass data analyses (MC-PMF). However, those species with high RMM substantially increased. There were no substantial differences in the apportioned source contributions based on standard and actual condition mass concentrations. However, the high-low rankings of percent contributions apportioned using the volumetric and mass data produced substantial differences. Compared with the VC-PMF results, the percent contributions of sources dominated by species with low RMM (e.g., natural gas usage and mixed sources containing natural gas usage) apportioned by MC-PMF decreased, while those of sources that emitted high RMM species (e.g., solvent usage and mixed sources containing solvent usage) increased. Source apportionments based on the volumetric concentration data had more practical significance compared to the mass concentration data results for control strategy development since the mass data analyses created issues.
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Affiliation(s)
- Yutong Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China.
| | - He Meng
- Qingdao Eco-environment Monitoring Center of Shandong Province, Qingdao 266003, China
| | - Fuquan Wang
- Beijing Make Environment Science & Technology Co., Ltd., Beijing 100083, China
| | - Sen Li
- Zhumadian Ecological and Environmental Monitoring Center of Henan Province, Zhumadian 463000, China
| | - Man Xu
- Shijiazhuang Environmental Prediction Center, Shijiazhuang 050022, China
| | - Laiyuan Shi
- Qingdao Eco-environment Monitoring Center of Shandong Province, Qingdao 266003, China
| | - Songfeng Zhang
- Zhumadian Municipal Ecology and Environment Bureau, Zhumadian 463000, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Philip K Hopke
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA; Institute for a Sustainable Environment, Clarkson University, Potsdam, NY 13699, USA
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Li Y, Wu Z, Ji Y, Chen T, Li H, Gao R, Xue L, Wang Y, Zhao Y, Yang X. Comparison of the ozone formation mechanisms and VOCs apportionment in different ozone pollution episodes in urban Beijing in 2019 and 2020: Insights for ozone pollution control strategies. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:168332. [PMID: 37949143 DOI: 10.1016/j.scitotenv.2023.168332] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Revised: 11/02/2023] [Accepted: 11/02/2023] [Indexed: 11/12/2023]
Abstract
Ground-level ozone (O3) pollution has been a tough issue in urban areas of China in the past decade. Clarifying the formation mechanisms of O3 and the sources of its precursors is necessary for the effective prevention of O3 pollution. In this study, a comparative analysis of O3 formation mechanisms and VOCs apportionment for five O3 pollution episodes was carried out at two urban sites (CRAES and CGZ) in Beijing in 2019 and 2020 by applying an observation-based modeling approach in order to obtain insights into O3 pollution control strategies. Results indicated that O3 pollution levels were generally more severe in 2019 than in 2020 during the observation periods. O3 formation at the two sites was both VOCs-limited on O3 polluted days and non-O3 polluted days. Stronger atmospheric oxidation capacity and ROx radicals cycling processes were found on O3 polluted days which could accelerate the local production of O3, and local photochemical production dominated the observed O3 concentrations at the two sites even on non-O3 polluted days. Emission reduction of VOCs should be a priority for mitigating O3 pollution, and alkenes and biogenic VOCs was the priority species at the CRAES and CGZ sites, respectively. Additionally, the reduction of oxygenated VOCs should also be important for the ozone control. Gasoline exhaust at the CRAES site, and solvent utilization and fuel evaporation at the CGZ site were main anthropogenic sources of VOCs. Therefore, local control measures should be further strengthened and differentiated control strategies of VOCs in the aspects of area, time, sources and species should be adopted in urban Beijing in the future. Overall, the findings of this study could provide a scientific understanding of the causes of O3 pollution and significant guidelines for formulating O3 control strategies from the perspective of different ozone pollution episodes in urban Beijing.
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Affiliation(s)
- Yunfeng Li
- School of Mechanical Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China
| | - Zhenhai Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yuanyuan Ji
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Tianshu Chen
- Environment Research Institute, Shandong University, Qingdao 266237, China
| | - Hong Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Rui Gao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Likun Xue
- Environment Research Institute, Shandong University, Qingdao 266237, China
| | - Yafei Wang
- School of Mechanical Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China
| | - Yuxi Zhao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Xin Yang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
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Kim SJ, Lee HY, Lee SJ, Choi SD. Passive air sampling of VOCs, O 3, NO 2, and SO 2 in the large industrial city of Ulsan, South Korea: spatial-temporal variations, source identification, and ozone formation potential. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:125478-125491. [PMID: 37999843 DOI: 10.1007/s11356-023-31109-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 11/15/2023] [Indexed: 11/25/2023]
Abstract
Concerns about volatile organic compounds (VOCs) have increased due to their toxicity and secondary reaction with nitrogen oxides (NOX) to form ozone (O3). In this study, passive air sampling of VOCs, O3, NO2, and SO2 was conducted in summer, fall, winter, and spring from 2019 to 2020 at six industrial and ten urban sites in Ulsan, the largest industrial city in South Korea. Over the entire sampling period, the concentration of toluene (mean: 8.75 μg/m3) was the highest of the 50 target VOCs, followed by m,p-xylenes (4.52 μg/m3), ethylbenzene (4.48 μg/m3), 3-methylpentane (4.40 μg/m3), and n-octane (4.26 μg/m3). Total (Σ50) VOC levels did not statistically differ between seasons, indicating that large amounts of VOCs are emitted into the atmosphere throughout the year. On the other hand, O3, NO2, and SO2 exhibited strong seasonal variation depending on the meteorological conditions and emission sources. The spatial distribution of Σ50 VOCs, NO2, and SO2 indicated that industrial complexes were major sources in Ulsan, while O3 had the opposite spatial distribution. Using a positive matrix factorization model, five major sources were identified, with industrial effects dominant. Aromatic compounds, such as m,p,o-xylenes, toluene, and 1,2,4-trimethylbenzene, significantly contributed to O3 formation. The VOC/NO2 ratio and O3 concentrations suggested that reducing VOC emissions is more effective than reducing NO2 emissions in terms of preventing the secondary formation of O3. The findings of this study allow for a better understanding of the relationship between VOCs, O3, NO2, and SO2 in industrial cities.
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Affiliation(s)
- Seong-Joon Kim
- Department of Civil, Urban, Earth, and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea
| | - Ho-Young Lee
- Department of Civil, Urban, Earth, and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea
| | - Sang-Jin Lee
- Department of Civil, Urban, Earth, and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea
| | - Sung-Deuk Choi
- Department of Civil, Urban, Earth, and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan, 44919, Republic of Korea.
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4
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Zeng X, Han M, Ren G, Liu G, Wang X, Du K, Zhang X, Lin H. A comprehensive investigation on source apportionment and multi-directional regional transport of volatile organic compounds and ozone in urban Zhengzhou. CHEMOSPHERE 2023; 334:139001. [PMID: 37220798 DOI: 10.1016/j.chemosphere.2023.139001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 04/18/2023] [Accepted: 05/20/2023] [Indexed: 05/25/2023]
Abstract
To understand the characteristics, source apportionment, and regional transport of volatile organic compounds (VOCs) and ozone (O3) in a typical city with severe air pollution in central China, we observed and analyzed 115 VOC species at an urban site in Zhengzhou from 29 July to 26 September 2021. During this period, observation- and emission-based approaches revealed that Zhengzhou was in a VOC-limited regime. The average concentration of total VOCs (TVOCs) was 162.25 ± 71.42 μg/m3, dominated by oxygenated VOCs (OVOCs, 34.49%), alkanes (24.29%), and aromatics (19.49%). Six VOC sources were identified using positive matrix factorization (PMF) model, including paint solvent usage (25.32%), secondary production (24.11%), industrial production (19.22%), vehicle exhaust (16.18%), biogenic emission (8.87%), and combustion (6.30%). To assess the regional contribution and source apportionment of VOCs and O3, Comprehensive Air Quality Model with Extensions (CAMx) with the Ozone Source Apportionment Technology (OSAT) was used for simulation. Results showed that the VOCs were significantly affected by local emissions (about 70%), while O3 was mainly attributed to regional and super-regional transport. Regarding multi-directional regional transport of VOCs and O3, dominant contributions were from the northeast and east-northeast directions, and O3 contributions were also predominantly from the east and east-southeast directions. In terms of source apportionment, the transportation and industrial sectors (including solvent usage) were the major contributors to O3 and VOCs. To alleviate VOCs and O3 pollution, transportation and industrial emission reduction should be strengthened, and regional coordination, especially from the northeast to east-southeast directions, should be emphasized in addition to local management.
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Affiliation(s)
- Xiaoxi Zeng
- Division of Thermophysics Metrology, National Institute of Metrology, Beijing, 100029, China; Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
| | - Mengjuan Han
- Division of Thermophysics Metrology, National Institute of Metrology, Beijing, 100029, China; Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
| | - Ge Ren
- Division of Thermophysics Metrology, National Institute of Metrology, Beijing, 100029, China; Zhengzhou Institute of Metrology, Zhengzhou, 450001, China.
| | - Gege Liu
- Division of Thermophysics Metrology, National Institute of Metrology, Beijing, 100029, China; Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
| | - Xiaoning Wang
- Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
| | - Kailun Du
- Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
| | - Xiaodong Zhang
- Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
| | - Hong Lin
- Division of Thermophysics Metrology, National Institute of Metrology, Beijing, 100029, China; Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
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Shi Y, Liu C, Zhang B, Simayi M, Xi Z, Ren J, Xie S. Accurate identification of key VOCs sources contributing to O 3 formation along the Liaodong Bay based on emission inventories and ambient observations. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 844:156998. [PMID: 35787908 DOI: 10.1016/j.scitotenv.2022.156998] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 06/20/2022] [Accepted: 06/23/2022] [Indexed: 06/15/2023]
Abstract
In order to achieve the precise control of the volatile organic compounds (VOCs) species with high ozone (O3) formation contribution from key sources in Panjin and Yingkou, two coastal industrial cities with severe O3 pollution along the Liaodong Bay, northeast China, the ambient concentrations of 99 VOCs species were measured online at urban-petrochemical (XLT), suburban-industrial (PP), and rural (XRD) sites in July 2019, contemporary monthly anthropogenic VOCs emission inventories were developed. The source contribution of ambient VOCs resolved by positive matrix factorization (PMF) model was comparable with emission inventories, and the location of VOCs sources were speculated by potential source contribution function (PSCF). 17.5 Gg anthropogenic VOCs was emitted in Panjin and Yingkou in July 2019 with potential to form 54.7 Gg-O3 estimated by emission inventories. The average VOC mixing ratios of 47.1, 26.7, and 16.5 ppbv was observed at XLT, PP, and XRD sites, respectively. Petroleum industry (22 %), organic chemical industry (21 %), and mobile vehicle emission (19 %) were identified to be the main sources contributing to O3 formation at XLT site by PMF, while it is organic chemical industry (33 %) and solvent utilization (28 %) contributed the most at PP site. Taking the subdivided source contributions of emission inventories and source locations speculated by PSCF into full consideration, organic raw chemicals manufacturing, structural steel coating, petroleum refining process, petroleum products storage and transport, off-shore vessels, and passenger cars were identified as the key anthropogenic sources. High O3-formation contribution sources, organic chemical industry and solvent utilization were located in the industrial parks at the junction of the two cities and the southeast of Panjin, and petroleum industry distributed in the whole Panjin and offshore areas. These results identify the key VOCs species and sources and speculate the potential geographical location of sources for precisely controlling ground-level O3 along the Liaodong Bay.
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Affiliation(s)
- Yuqi Shi
- College of Environmental Sciences and Engineering, State Key Joint Laboratory of Environmental Simulation and Pollution Control, Peking University, Beijing 100871, PR China
| | - Chang Liu
- Liaoning Ecological and Environmental Service Center, Shenyang, Liaoning 110161, PR China
| | - Baosheng Zhang
- Department of Ecology and Environment of Liaoning Province, Shenyang, Liaoning 110161, PR China
| | - Maimaiti Simayi
- College of Resources and Environments, Xinjiang Agricultural University, Urumqi, Xinjiang 830052, PR China
| | - Ziyan Xi
- College of Environmental Sciences and Engineering, State Key Joint Laboratory of Environmental Simulation and Pollution Control, Peking University, Beijing 100871, PR China
| | - Jie Ren
- College of Environmental Sciences and Engineering, State Key Joint Laboratory of Environmental Simulation and Pollution Control, Peking University, Beijing 100871, PR China
| | - Shaodong Xie
- College of Environmental Sciences and Engineering, State Key Joint Laboratory of Environmental Simulation and Pollution Control, Peking University, Beijing 100871, PR China.
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Chen T, Huang L, Zhang X, Gao R, Li H, Fan K, Ma D, Ma Z, Xue L, Wang W. Effects of coal chemical industry on atmospheric volatile organic compounds emission and ozone formation in a northwestern Chinese city. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 839:156149. [PMID: 35643128 DOI: 10.1016/j.scitotenv.2022.156149] [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: 03/24/2022] [Revised: 05/16/2022] [Accepted: 05/18/2022] [Indexed: 06/15/2023]
Abstract
Coal is well known as the primary energy consumption in China, and the coal chemical industry (CCI) can serve as an important source of volatile organic compounds (VOCs) emissions. However, the characteristics of VOCs emitted from CCI along with their environmental consequences are still poorly understood. To pin down this, an intensive field campaign was carried out at a typical CCI city in northwestern China (Yulin) from February 26 to March 7, 2021. Results showed that VOC compositions in Yulin were distinct from those in the megacities of China as well as in the typical oilfields over the world. The concentration of naphthalene (1.6 ± 1.1 ppbv), an important byproduct of CCI, was significantly higher than that in other cities (<0.2 ppbv). Positive matrix factorization (PMF) model analysis revealed that the direct contribution of the CCI source for VOC emissions is 8.8 ± 1.8%. More importantly, these VOCs emitted from the CCI can account for 17.9 ± 6.8% of ozone (O3) formation potential and 16.9 ± 7.4% of OH reactivity of VOCs, suggesting the significant impacts of the CCI on the air quality and atmospheric oxidizing capacity. During the observation, a rapid increase in O3 concentration after a snowfall was encountered. The changing rate of O3 concentration in the daytime was significantly higher than in its peripheral cities. The increased O3 formation was partially attributed to the CCI, and this enhancement can be further magnified by snow cover due to the increment of surface albedo. These findings deepen the understanding of the characteristics and air quality impact of VOCs related to the CCI and provide valuable insights for the development of air quality control measures in the region influenced by intensive coal chemical production.
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Affiliation(s)
- Tianshu Chen
- Environment Research Institute, Shandong University, Qingdao 266237, China
| | - Liubin Huang
- Environment Research Institute, Shandong University, Qingdao 266237, China.
| | - Xin Zhang
- Environment Research Institute, Shandong University, Qingdao 266237, China; Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Rui Gao
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Hong Li
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Kai Fan
- Yulin Municipal Ecology and Environment Bureau, Yulin 719000, China
| | - Dun Ma
- Yulin Municipal Ecology and Environment Bureau, Yulin 719000, China
| | - Zhaokun Ma
- Shandong Academy for Environmental Planning, Ji'nan 250101, China
| | - Likun Xue
- Environment Research Institute, Shandong University, Qingdao 266237, China.
| | - Wenxing Wang
- Environment Research Institute, Shandong University, Qingdao 266237, China; Chinese Research Academy of Environmental Sciences, Beijing 100012, China
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Kim SJ, Lee SJ, Lee HY, Son JM, Lim HB, Kim HW, Shin HJ, Lee JY, Choi SD. Characteristics of volatile organic compounds in the metropolitan city of Seoul, South Korea: Diurnal variation, source identification, secondary formation of organic aerosol, and health risk. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:156344. [PMID: 35654203 DOI: 10.1016/j.scitotenv.2022.156344] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/25/2022] [Accepted: 05/26/2022] [Indexed: 06/15/2023]
Abstract
Atmospheric volatile organic compounds (VOCs) in Seoul, the capital of South Korea, have attracted increased attention owing to their emission, secondary formation, and human health risk. In this study, we collected 24 hourly samples once a month at an urban site in Seoul for a year (a total of 288 samples) using a sequential tube sampler. Analysis results revealed that toluene (9.08 ± 8.99 μg/m3) exhibited the highest annual mean concentration, followed by ethyl acetate (5.55 ± 9.09 μg/m3), m,p-xylenes (2.79 ± 4.57 μg/m3), benzene (2.37 ± 1.55 μg/m3), ethylbenzene (1.81 ± 2.27 μg/m3), and o-xylene (0.91 ± 1.47 μg/m3), indicating that these compounds accounted for 77.8-85.6% of the seasonal mean concentrations of the total (Σ59) VOCs. The concentrations of the Σ59 VOCs were statistically higher in spring and winter than in summer and fall because of meteorological conditions, and the concentrations of individual VOCs were higher during the daytime than nighttime owing to higher human activities during the daytime. The conditional bivariate probability function and concentration weighted trajectory analysis results suggested that domestic effects (e.g., vehicular exhaust and solvents) exhibited a dominant effect on the presence of VOCs in Seoul, as well as long-range atmospheric transport of VOCs. Further, the most important secondary organic aerosol formation potential (SOAFP) compounds included benzene, toluene, ethylbenzene, and m,p,o-xylenes, and the total SOAFP of nine VOCs accounted for 5-29% of the seasonal mean PM2.5 concentrations. The cancer and non-cancer risks of the selected VOCs were below the tolerable (1 × 10-4) and acceptable (Hazard quotient: HQ < 1) levels, respectively. Overall, this study highlighted the feasibility of the sequential sampling of VOCs and hybrid receptor modeling to further understand the source-receptor relationship of VOCs.
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Affiliation(s)
- Seong-Joon Kim
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Sang-Jin Lee
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Ho-Young Lee
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Ji-Min Son
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea
| | - Hyung-Bae Lim
- Air Quality Research Division, National Institute of Environmental Research (NIER), Incheon 22689, Republic of Korea
| | - Hyeon-Woong Kim
- Air Quality Research Division, National Institute of Environmental Research (NIER), Incheon 22689, Republic of Korea
| | - Hye-Jung Shin
- Air Quality Research Division, National Institute of Environmental Research (NIER), Incheon 22689, Republic of Korea
| | - Ji Yi Lee
- Department of Environmental Science and Engineering, Ewha Womans University, Seoul 03760, Republic of Korea
| | - Sung-Deuk Choi
- Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, Republic of Korea.
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Zhang X, Kong Y, Cao J, Li H, Gao R, Zhang Y, Wang K, Li Y, Ren Y, Wang W. A sensitive simultaneous detection approach for the determination of 30 atmospheric carbonyls by 2,4-dinitrophenylhydrazine derivatization with HPLC-MS technique and its preliminary application. CHEMOSPHERE 2022; 303:134985. [PMID: 35588876 DOI: 10.1016/j.chemosphere.2022.134985] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Revised: 05/07/2022] [Accepted: 05/13/2022] [Indexed: 06/15/2023]
Abstract
Atmospheric carbonyls are important precursors of PM2.5 and ground-level ozone, and some carbonyls are toxic and harmful; thus, it is crucial to obtain accurate information on the ambient levels of carbonyls. However, the detection of carbonyls is difficult due to their relatively higher reactivities and chemical instabilities; therefore, accurate determination of atmospheric carbonyls is important. In this study, an analytical method for atmospheric carbonyls with high concentration or reactivity was developed, the precursor ion of each carbonyl compound was selected, and the declustering potential (DP) and entrance potential (EP) for each precursor ion were optimized. A 2,4-dinitrophenylhydrazine cartridge derivatization-high performance liquid chromatography/atmospheric pressure chemical ionization-mass spectrometry (DNPH-HPLC/APCI-MS) method for the determination of 30 carbonyls was established. The results showed that the linear range of 24 carbonyls was 1.2-600 ng/mL, while other 6 carbonyls was 1.2-300 ng/mL, and the detection limits of 30 carbonyls ranged from 0.092 to 0.947 ng/mL (0.005-0.049 μg/m3 with an ambient air sampling volume of 96 L). The intra-day and inter-day repeatability ranges were 0.55-4.20% and 1.40-12.48%, respectively. A preliminary application of the method was carried out in the urban area of Beijing in spring and summer of 2021, and it was found that the mean total mass concentration of 30 carbonyls was 35.894 μg/m3. This study provided additional concentration information for 14 atmospheric carbonyls, including mono-, di-, oxygen-containing and heterocyclic carbonyls, which accounted for 38% and 35% of the total mass concentration and OH radical reactivities of 30 carbonyls, respectively. This is the first investigation of simultaneous quantitative analysis of multiple atmospheric carbonyls based on commercial standard derivatives. The optimized method could provide more comprehensive information for atmospheric carbonyls and further support research concerning the role of chemical reaction processes and health effects than traditional measuring techniques.
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Affiliation(s)
- Xin Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Environment Research Institute, Shandong University, Qingdao 266237, China
| | - Yuxue Kong
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; College of Science, China University of Petroleum, Beijing 102249, China
| | - Juan Cao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Hong Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Rui Gao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yujie Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Kexin Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; School of Resources and Environment, Yangtze University, Wuhan 430100, China
| | - Yunfeng Li
- School of Mechanical Engineering, Beijing Institute of Petrochemical Technology, Beijing 102617, China
| | - Yanqin Ren
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Wenxing Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Environment Research Institute, Shandong University, Qingdao 266237, China
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9
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Yang Y, Liu B, Hua J, Yang T, Dai Q, Wu J, Feng Y, Hopke PK. Global review of source apportionment of volatile organic compounds based on highly time-resolved data from 2015 to 2021. ENVIRONMENT INTERNATIONAL 2022; 165:107330. [PMID: 35671590 DOI: 10.1016/j.envint.2022.107330] [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: 02/09/2022] [Revised: 05/27/2022] [Accepted: 05/28/2022] [Indexed: 06/15/2023]
Abstract
Highly time-resolved data for volatile organic compounds (VOCs) can now be monitored. Source analyses of such high time-resolved concentrations provides key information for controlling VOC emissions. This work reviewed the literature on VOCs source analyses published from 2015 to 2021, and assesses the state-of-the-art and the existing issues with these studies. Gas chromatography system and direct-inlet mass spectrometry are the main monitoring tools. Quality control (QC) of the monitoring process is critical prior to analysis. QC includes inspection and replacement of instrument consumables, calibration curve corrections, and reviewing the data. Approximately 54% published papers lacked details on the quantitative evaluation of the effectiveness of QC measures. Among the reviewed works, the number of monitored species varied from 5 to 119, and fraction of papers with more than 90 monitored species increased yearly. US EPA PMF v5.0 was the most commonly used (∼86%) for VOC source analyses. However, conventional source apportionment directly uses the measured VOCs and may be problematic given the impacts of dispersion and photochemical losses, uncertainty setting of VOCs data, factor resolution, and factor identification. Excluding species with high-reactivity or estimation of corrected concentrations were often applied to reduce the influence of photochemical reactions on the results. However, most reports did not specify the selection criteria or the specific error fraction values in the uncertainty estimation. Model diagnostic indexes were used in 99% of the reports for PMF analysis to determine the factor resolution. Due to lack of known local source profiles, factor identification was mainly achieved using marker species and characteristic species ratios. However, multiple sources had high-collinearity and the same species were often used to identify different sources. Vehicle emissions and fuel evaporation were the primary contributors to VOCs around the world. Contribution of coal combustion in China was substantially higher than in other countries.
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Affiliation(s)
- Yang Yang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China.
| | - Jing Hua
- Tianjin Ecology and Environment Bureau, Tianjin 300191, China
| | - Tao Yang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Jianhui Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Philip K Hopke
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA; Institute for a Sustainable Environment, Clarkson University, Potsdam, NY 13699, USA
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Abstract
In order to investigate the seasonal variation in chemical characteristics of VOCs in the urban and suburban areas of southwest China, we used SUMMA canister sampling in Jinghong city from October 2016 to June 2017. Forty-eight VOC species concentrations were analyzed using atmospheric preconcentration gas chromatography–mass spectrometry (GC–MS), Then, regional VOC pollution characteristics, ozone formation potentials (OFP), source identity, and health risk assessments were studied. The results showed that the average concentration of total mass was 144.34 μg·m−3 in the urban area and 47.81 μg·m−3 in the suburban area. Alkanes accounted for the highest proportion of VOC groups at 38.11%, followed by olefins (36.60%) and aromatic hydrocarbons (25.28%). Propane and isoprene were the species with the highest mass concentrations in urban and suburban sampling sites. The calculation of OFP showed that the contributions of olefins and aromatic hydrocarbons were higher than those of alkanes. Through the ratio of specific species, the VOCs were mainly affected by motor vehicle exhaust emissions, fuel volatilization, vegetation emissions, and biomass combustion. Combined with the analysis of the backward trajectory model, biomass burning activities in Myanmar influenced the concentration of VOCs in Jinghong. Health risk assessments have shown that the noncarcinogenic risk and hazard index of atmospheric VOCs in Jinghong were low (less than 1). However, the value of the benzene cancer risk to the human body was higher than the safety threshold of 1 × 10−6, showing that benzene has carcinogenic risk. This study provides effective support for local governments formulating air pollution control policies.
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Yao D, Tang G, Sun J, Wang Y, Yang Y, Wang Y, Liu B, He H, Wang Y. Annual nonmethane hydrocarbon trends in Beijing from 2000 to 2019. J Environ Sci (China) 2022; 112:210-217. [PMID: 34955205 DOI: 10.1016/j.jes.2021.04.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2021] [Revised: 04/06/2021] [Accepted: 04/16/2021] [Indexed: 06/14/2023]
Abstract
High loads of ground-level ozone have occurred with the implementation of the Air Pollution Prevention and Control Action Plan. However, the long temporal variation in precursor nonmethane hydrocarbons (NMHCs) has rarely been studied. In this study, we examined the evolution of NMHCs in Beijing based on ambient measurements from 2000 to 2019. The results indicated that the annual variation of ambient NMHCs during 2000 and 2019 could be divided into two stages. The mixing ratios of NMHCs rapidly rose during 2000 and 2009 (1.76 ppbv/year) but exhibited a downward trend from 2009 to 2019 at rate of 0.80 ppbv/yr. Moreover, the notable decrease in alkenes and aromatics after 2009 led to a sharp decrease in the propylene-equivalent concentration (PEC) (-0.80 ppbv/year). Implementation of emission reduction measures in Beijing have effectively reduced the contribution of vehicle-related sources, but the contribution of solvent usage and fuel consumption increased, which will become the focus of VOC control in Beijing in the future.
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Affiliation(s)
- Dan Yao
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guiqian Tang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Jie Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Yinghong Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Yuan Yang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yiming Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Baoxian Liu
- School of Environment, Tsinghua University, Beijing 100084, China; Beijing Key Laboratory of Airborne Particulate Matter Monitoring Technology, Beijing Municipal Environmental Monitoring Center, Beijing 100048, China
| | - Hong He
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yuesi Wang
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Yao D, Tang G, Wang Y, Yang Y, Wang L, Chen T, He H, Wang Y. Significant contribution of spring northwest transport to volatile organic compounds in Beijing. J Environ Sci (China) 2021; 104:169-181. [PMID: 33985719 DOI: 10.1016/j.jes.2020.11.023] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 11/09/2020] [Accepted: 11/09/2020] [Indexed: 06/12/2023]
Abstract
High values of ozone (O3) occur frequently in the dry spring season; thus, understanding the evolution characteristics of volatile organic compounds (VOCs) in spring is of great significance for preventing O3 pollution. In this study, a total of 101 VOCs from April 16 to May 21, 2019, were quantified using an online gas chromatography mass spectrometer/flame ionization detector (GCMS/FID). The results indicated that the observed concentration of total VOCs (TVOCs) was 30.4 ± 17.0 ppbv, and it was dominated by alkanes (44.3%), followed by oxygenated VOCs (OVOCs) (17.4%), halocarbons (12.7%), aromatics (9.5%), alkenes (8.2%), acetylene (5.3%) and carbon disulfide (2.5%). The average mixing ratio of VOCs showed obvious diurnal variation (high at night, low during daytime). We conducted a source apportionment study based on 32 major VOCs using positive matrix factorization (PMF), and coal + biomass burning (25.2%), diesel exhaust (16.0%), gasoline exhaust + evaporation (17.4%), secondary + long-lived species (16.7%), biogenic sources (4.3%), industrial emissions (9.3%) and solvent use (11.2%) were identified as major sources of VOCs. In addition to local emissions, most of the atmospheric VOCs were derived from long-distance air masses (65.7%), and the average mixing ratio of VOCs in the northwest direction was 29.4 ppbv. Combined with the results of the potential source contribution function (PSCF) indicate that research should focus on the local emissions of combustion, transportation sources and solvents usage to control atmospheric VOCs. Additionally, transmission of the northwest air mass is an important component that cannot be ignored during spring in Beijing.
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Affiliation(s)
- Dan Yao
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guiqian Tang
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Yinghong Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Yuan Yang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lili Wang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, 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
| | - Hong He
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yuesi Wang
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Variations in Levels and Sources of Atmospheric VOCs during the Continuous Haze and Non-Haze Episodes in the Urban Area of Beijing: A Case Study in Spring of 2019. ATMOSPHERE 2021. [DOI: 10.3390/atmos12020171] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
To better evaluate the variations in concentration characteristics and source contributions of atmospheric volatile organic compounds (VOCs) during continuous haze days and non-haze days, hourly observations of atmospheric VOCs were conducted using a continuous on-line GC-FID (Airmo VOC GC-866) monitoring system during 1–15 March 2019, in urban areas of Beijing, China. The results showed that the total VOC concentrations during haze days and non-haze days were 59.13 ± 31.08 μg/m3 and 16.91 ± 7.19 μg/m3, respectively. However, the average O3 concentrations during the two haze days were lower than those of non-haze days due to the extremely low concentrations at night instead of the reported lower photochemical reaction in daytime. The ratio of OH radical concentration during haze and non-haze days indicating that the rate of photochemical reaction during haze days was higher than those of non-haze days from 13:00–19:00. The stable air conditions and the local diesel emission at night were the main reasons for the decreased O3 concentrations during haze days. Six major sources were identified by positive matrix factorization (PMF), namely, diesel exhaust, combustion, gasoline evaporation, solvent usage, gasoline exhaust, and the petrochemical industry, contributing 9.93%, 25.29%, 3.90%, 16.88%, 35.59% and 8.41%, respectively, during the whole observation period. The contributions of diesel exhaust and the petrochemical industry emissions decreased from 26.14% and 6.43% during non-haze days to 13.70% and 2.57%, respectively, during haze days. These reductions were mainly ascribed to the emergency measures that the government implemented during haze days. In contrast, the contributions of gasoline exhaust increased from 34.92% during non-haze days to 48.77% during haze days. The ratio of specific VOC species and PMF both showed that the contributions of gasoline exhaust emission increased during haze days. The backward trajectories, potential source contribution function (PSCF) and concentration weighted trajectory (CWT) showed that the air mass of VOCs during haze days was mainly affected by the short-distance transportation from the southwestern of Hebei province. However, the air mass of VOCs during non-haze days was mainly affected by the long-distance transportation from the northwest.
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Wang F, Du W, Lv S, Ding Z, Wang G. Spatial and Temporal Distributions and Sources of Anthropogenic NMVOCs in the Atmosphere of China: A Review. ADVANCES IN ATMOSPHERIC SCIENCES 2021; 38:1085-1100. [PMID: 33948045 PMCID: PMC8085794 DOI: 10.1007/s00376-021-0317-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 01/02/2021] [Accepted: 01/19/2021] [Indexed: 05/06/2023]
Abstract
As the key precursors of O3, anthropogenic non-methane volatile organic compounds (NMVOCs) have been studied intensively. This paper performed a meta-analysis on the spatial and temporal variations of NMVOCs, their roles in photochemical reactions, and their sources in China, based on published research. The results showed that both non-methane hydrocarbons (NMHCs) and oxygenated VOCs (OVOCs) in China have higher mixing ratios in the eastern developed cities compared to those in the central and western areas. Alkanes are the most abundant NMHCs species in all reported sites while formaldehyde is the most abundant among the OVOCs. OVOCs have the highest mixing ratios in summer and the lowest in winter, which is opposite to NMHCs. Among all NMVOCs, the top eight species account for 50%-70% of the total ozone formation potential (OFP) with different compositions and contributions in different areas. In devolved regions, OFP-NMHCs are the highest in winter while OFP-OVOCs are the highest in summer. Based on positive matrix factorization (PMF) analysis, vehicle exhaust, industrial emissions, and solvent usage in China are the main sources for NMHCs. However, the emission trend analysis showed that solvent usage and industrial emissions will exceed vehicle exhaust and become the two major sources of NMVOCs in near future. Based on the meta-analysis conducted in this work, we believe that the spatio-temporal variations and oxidation mechanisms of atmospheric OVOCs, as well as generating a higher spatial resolution of emission inventories of NMVOCs represent an area for future studies on NMVOCs in China.
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Affiliation(s)
- Fanglin Wang
- Key Lab of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, 200241 China
| | - Wei Du
- Key Lab of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, 200241 China
| | - Shaojun Lv
- Key Lab of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, 200241 China
| | - Zhijian Ding
- Key Lab of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, 200241 China
| | - Gehui Wang
- Key Lab of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, Shanghai, 200241 China
- Institute of Eco-Chongming, Shanghai, 200062 China
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