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Liu B, Yang T, Kang S, Wang F, Zhang H, Xu M, Wang W, Bai J, Song S, Dai Q, Feng Y, Hopke PK. Changes in factor profiles deriving from photochemical losses of volatile organic compounds: Insight from daytime and nighttime positive matrix factorization analyses. J Environ Sci (China) 2025; 151:627-639. [PMID: 39481968 DOI: 10.1016/j.jes.2024.04.032] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 04/14/2024] [Accepted: 04/19/2024] [Indexed: 11/03/2024]
Abstract
Substantial effects of photochemical reaction losses of volatile organic compounds (VOCs) on factor profiles can be investigated by comparing the differences between daytime and nighttime dispersion-normalized VOC data resolved profiles. Hourly speciated VOC data measured in Shijiazhuang, China from May to September 2021 were used to conduct study. The mean VOC concentration in the daytime and at nighttime were 32.8 and 36.0 ppbv, respectively. Alkanes and aromatics concentrations in the daytime (12.9 and 3.08 ppbv) were lower than nighttime (15.5 and 3.63 ppbv), whereas that of alkenes showed the opposite tendency. The concentration differences between daytime and nighttime for alkynes and halogenated hydrocarbons were uniformly small. The reactivities of the dominant species in factor profiles for gasoline emissions, natural gas and diesel vehicles, and liquefied petroleum gas were relatively low and their profiles were less affected by photochemical losses. Photochemical losses produced a substantial impact on the profiles of solvent use, petrochemical industry emissions, combustion sources, and biogenic emissions where the dominant species in these factor profiles had high reactivities. Although the profile of biogenic emissions was substantially affected by photochemical loss of isoprene, the low emissions at nighttime also had an important impact on its profile. Chemical losses of highly active VOC species substantially reduced their concentrations in apportioned factor profiles. This study results were consistent with the analytical results obtained through initial concentration estimation, suggesting that the initial concentration estimation could be the most effective currently available method for the source analyses of active VOCs although with uncertainty.
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Affiliation(s)
- 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.
| | - 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
| | - Sicong Kang
- Beijing Make Environment Science & Technology Co., Ltd., Beijing 100083, China
| | - Fuquan Wang
- Beijing Make Environment Science & Technology Co., Ltd., Beijing 100083, China
| | - Haixu Zhang
- Beijing Make Environment Science & Technology Co., Ltd., Beijing 100083, China
| | - Man Xu
- Shijiazhuang Environmental Prediction Center, Shijiazhuang 050022, China
| | - Wei Wang
- Shijiazhuang Environmental Prediction Center, Shijiazhuang 050022, China
| | - Jinrui Bai
- Shijiazhuang Environmental Prediction Center, Shijiazhuang 050022, China
| | - Shaojie Song
- 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
| | - 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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Cui Y, Liu B, Yang Y, Kang S, Wang F, Xu M, Wang W, Feng Y, Hopke PK. Primary and oxidative source analyses of consumed VOCs in the atmosphere. JOURNAL OF HAZARDOUS MATERIALS 2024; 476:134894. [PMID: 38909463 DOI: 10.1016/j.jhazmat.2024.134894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 05/27/2024] [Accepted: 06/11/2024] [Indexed: 06/25/2024]
Abstract
Consumed VOCs are the compounds that have reacted to form ozone and secondary organic aerosol (SOA) in the atmosphere. An approach that can apportion the contributions of primary sources and reactions to the consumed VOCs was developed in this study and applied to hourly VOCs data from June to August 2022 measured in Shijiazhuang, China. The results showed that petrochemical industries (36.9 % and 51.7 %) and oxidation formation (20.6 % and 35.6 %) provided the largest contributions to consumed VOCs and OVOCs during the study period, whereas natural gas (5.0 % and 7.6 %) and the mixed source of liquefied petroleum gas and solvent use (3.1 % and 4.2 %) had the relatively low contributions. Compared to the non-O3 pollution (NOP) period, the contributions of oxidation formation, petrochemical industries, and the mixed source of gas evaporation and vehicle emissions to the consumed VOCs during the O3 pollution (OP) period increased by 2.8, 3.8, and 9.3 times, respectively. The differences in contributions of liquified petroleum gas and solvent use, natural gas, and combustion sources to consumed VOCs between OP and NOP periods were relatively small. Transport of petrochemical industries emissions from the southeast to the study site was the primary consumed pathway for VOCs emitted from petrochemical industries.
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Affiliation(s)
- Yaqi Cui
- 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.
| | - Yufeng 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
| | - Sicong Kang
- Beijing Make Environment Science & Technology Co., Ltd., Beijing 100083, China
| | - Fuquan Wang
- Beijing Make Environment Science & Technology Co., Ltd., Beijing 100083, China
| | - Man Xu
- Shijiazhuang Environmental Prediction Center, Shijiazhuang 050022, China
| | - Wei Wang
- Shijiazhuang Environmental Prediction Center, Shijiazhuang 050022, 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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Zhang W, Wu F, Luo X, Song L, Wang X, Zhang Y, Wu J, Xiao Z, Cao F, Bi X, Feng Y. Quantification of NO x sources contribution to ambient nitrate aerosol, uncertainty analysis and sensitivity analysis in a megacity. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 926:171583. [PMID: 38461977 DOI: 10.1016/j.scitotenv.2024.171583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 02/06/2024] [Accepted: 03/06/2024] [Indexed: 03/12/2024]
Abstract
Dual isotopes of nitrogen and oxygen of NO3- are crucial tools for quantifying the formation pathways and precursor NOx sources contributing to atmospheric nitrate. However, further research is needed to reduce the uncertainty associated with NOx proportional contributions. The acquisition of nitrogen isotopic composition from NOx emission sources lacks regulation, and its impact on the accuracy of contribution results remains unexplored. This study identifies key influencing factors of source isotopic composition through statistical methods, based on a detailed summary of δ15N-NOx values from various sources. NOx emission sources are classified considering these factors, and representative means, standard deviations, and 95 % confidence intervals are determined using the bootstrap method. During the sampling period in Tianjin in 2022, the proportional nitrate formation pathways varied between sites. For suburban and coastal sites, the ranking was [Formula: see text] (NO2 + OH radical) > [Formula: see text] (N2O5 + H2O) > [Formula: see text] (NO3 + DMS/HC), while the rural site exhibited similar fractional contributions from all three formation pathways. Fossil fuel NOx sources consistently contributed more than non-fossil NOx sources in each season among three sites. The uncertainties in proportional contributions varied among different sources, with coal combustion and biogenic soil emission showing lower uncertainties, suggesting more stable proportional contributions than other sources. The sensitivity analysis clearly identifies that the isotopic composition of 15N-enriched and 15N-reduced sources significantly influences source contribution results, emphasizing the importance of accurately characterizing the localized and time-efficient nitrogen isotopic composition of NOx emission sources. In conclusion, this research sheds light on the importance of addressing uncertainties in NOx proportional contributions and emphasizes the need for further exploration of nitrogen isotopic composition from NOx emission sources for accurate atmospheric nitrate studies.
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Affiliation(s)
- Wenhui Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Fuliang Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Xi Luo
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Lilai Song
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Xuehan Wang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Jianhui Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Zhimei Xiao
- Tianjin Eco-Environmental Monitoring Center, Tianjin 300191, China
| | - Fang Cao
- Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Xiaohui Bi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; China Meteorological Administration-Nankai University (CMA-NKU) Cooperative Laboratory for Atmospheric Environment-Health Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
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Jing D, Yang K, Shi Z, Cai X, Li S, Li W, Wang Q. Novel approach for identifying VOC emission characteristics based on mobile monitoring platform data and deep learning: Application of source apportionment in a chemical industrial park. Heliyon 2024; 10:e29077. [PMID: 38628757 PMCID: PMC11019163 DOI: 10.1016/j.heliyon.2024.e29077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2024] [Revised: 03/11/2024] [Accepted: 03/29/2024] [Indexed: 04/19/2024] Open
Abstract
Refined volatile organic compound (VOC) emission characteristics are crucial for accurate source apportionment in chemical industrial parks. The data from mobile monitoring platforms in chemical industrial parks contain pollution information that is not intuitively displayed, requiring further excavation. A novel approach was proposed to identify VOC emission characteristics using the class activation map (CAM) technology of convolutional neural network (CNN), which was applied on the mobile monitoring platform data (MD) derived from a typical fine chemical industrial park. It converts a large amount of monitoring data with high spatiotemporal complexity into simple and interpretable characteristic maps, effectively improving the identification effect of VOC emission characteristics, supporting more accurate source apportionment of VOC pollution around the park. Using this method, the VOC emission characteristics of eight key factories were identified. VOC source apportionment in the park was conducted for one day using a positive matrix factorization (PMF) model and seven combined factor profiles (CFPs) were calculated. Based on the identified VOC emission characteristics, the main pollution sources and their contributions to surrounding schools and residential areas were determined, revealing that one pesticide factory (named LKA) had the highest contribution ratio. The source apportionment results indicated that the impact of the chemical industrial park on the surrounding areas varied from morning to afternoon, which to some extent reflected the intermittent production methods employed for fine chemicals.
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Affiliation(s)
- Deji Jing
- Key Laboratory of Biomass Chemical Engineering of the Ministry of Education, Institute of Industrial Ecology and Environment, College of Chemical and Biological Engineering, Zhejiang University (Zijingang Campus), Hangzhou, 310058, China
| | - Kexuan Yang
- Key Laboratory of Biomass Chemical Engineering of the Ministry of Education, Institute of Industrial Ecology and Environment, College of Chemical and Biological Engineering, Zhejiang University (Zijingang Campus), Hangzhou, 310058, China
| | - Zhanhong Shi
- Key Laboratory of Biomass Chemical Engineering of the Ministry of Education, Institute of Industrial Ecology and Environment, College of Chemical and Biological Engineering, Zhejiang University (Zijingang Campus), Hangzhou, 310058, China
| | - Xingnong Cai
- Key Laboratory of Biomass Chemical Engineering of the Ministry of Education, Institute of Industrial Ecology and Environment, College of Chemical and Biological Engineering, Zhejiang University (Zijingang Campus), Hangzhou, 310058, China
| | - Sujing Li
- Key Laboratory of Biomass Chemical Engineering of the Ministry of Education, Institute of Industrial Ecology and Environment, College of Chemical and Biological Engineering, Zhejiang University (Zijingang Campus), Hangzhou, 310058, China
| | - Wei Li
- Key Laboratory of Biomass Chemical Engineering of the Ministry of Education, Institute of Industrial Ecology and Environment, College of Chemical and Biological Engineering, Zhejiang University (Zijingang Campus), Hangzhou, 310058, China
| | - Qiaoli Wang
- College of Environment, Zhejiang University of Technology, Hangzhou, 310032, China
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Li Q, Gong D, Wang H, Deng S, Zhang C, Mo X, Chen J, Wang B. Tibetan Plateau is vulnerable to aromatic-related photochemical pollution and health threats: A case study in Lhasa. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166494. [PMID: 37659561 DOI: 10.1016/j.scitotenv.2023.166494] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 08/20/2023] [Accepted: 08/20/2023] [Indexed: 09/04/2023]
Abstract
Anthropogenic aromatics play a key role in photochemical pollution and pose a serious threat to human health. Current knowledge on source characteristics of aromatics in the urban region of the Tibetan Plateau (TP), the "Third Pole" and ecologically sensitive area, remains limited. In this study, an intensive observation of 17 aromatic hydrocarbons was conducted in Lhasa, the cultural and economic center of TP, during the second Tibetan Plateau Scientific Expedition and Research in summer 2020. The results showed that the average concentration of aromatics in Lhasa (7.6 ± 7.4 ppbv) was unexpectedly higher than those in megacities such as Beijing, Shanghai, and Guangzhou. Tripled concentrations and corresponding ozone formation potential during pollution episodes were recorded. Further source apportionment using positive matrix factorization revealed that solvent usage (60.0 %) was the dominant source, which may be due to the extremely low atmospheric pressure. Vehicle exhaust (15.4 %), industrial emissions (12.8 %), fuel evaporation (6.2 %), and burning emissions (5.7 %) were also important sources. The concentration weighted trajectory analysis revealed that the observed high levels of aromatics were mainly driven by local anthropogenic emissions, rather than the regional transport by the Indian summer monsoon. Long-term exposure to aromatics in Lhasa was assessed to pose carcinogenic risks to the population, with the risks of benzene and ethylbenzene 5 times the criteria. Our results suggest that, given the magnified emissions of aromatics in this extreme environment (low atmospheric pressure and strong solar radiation), the implementation of targeted pollution controls is urgently needed to mitigate the aromatic-related photochemical pollution and health threats in TP.
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Affiliation(s)
- Qinqin Li
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Daocheng Gong
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong Provincial Observation and Research Station for Atmospheric Environment and Carbon Neutrality in Nanling Forests, China
| | - Hao Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong Provincial Observation and Research Station for Atmospheric Environment and Carbon Neutrality in Nanling Forests, China.
| | - Shuo Deng
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Chengliang Zhang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong Provincial Observation and Research Station for Atmospheric Environment and Carbon Neutrality in Nanling Forests, China
| | - Xujun Mo
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Jun Chen
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Boguang Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong Provincial Observation and Research Station for Atmospheric Environment and Carbon Neutrality in Nanling Forests, 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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Xu K, Liu Y, Li C, Zhang C, Liu X, Li Q, Xiong M, Zhang Y, Yin S, Ding Y. Enhanced secondary organic aerosol formation during dust episodes by photochemical reactions in the winter in Wuhan. J Environ Sci (China) 2023; 133:70-82. [PMID: 37451790 DOI: 10.1016/j.jes.2022.04.018] [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: 10/29/2021] [Revised: 01/23/2022] [Accepted: 04/10/2022] [Indexed: 07/18/2023]
Abstract
To investigate the effect of frequently occurring mineral dust on the formation of secondary organic aerosol (SOA), 106 volatile organic compounds (VOCs), trace gas pollutants and chemical components of PM2.5 were measured continuously in January 2021 in Wuhan, Central China. The observation period was divided into two stages that included a haze period and a following dust period, based on the ratio of PM2.5 and PM10 concentrations. The average ratio of secondary organic carbon (SOC) to elemental carbon (EC) was 1.98 during the dust period, which was higher than that during the haze period (0.69). The contribution of SOA to PM2.5 also increased from 2.75% to 8.64%. The analysis of the relationships between the SOA and relative humidity (RH) and the odd oxygen (e.g., OX = O3 + NO2) levels suggested that photochemical reactions played a more important role in the enhancement of SOA production during the dust period than the aqueous-phase reactions. The heterogeneous photochemical production of OH radicals in the presence of metal oxides during the dust period was believed to be enhanced. Meanwhile, the ratios of trans-2-butene to cis-2-butene and m-/p-xylene to ethylbenzene (X/E) dropped significantly, confirming that stronger photochemical reactions occurred and SOA precursors formed efficiently. These results verified the laboratory findings that metal oxides in mineral dust could catalyse the oxidation of VOCs and induce higher SOA production.
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Affiliation(s)
- Kai Xu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yafei Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Chenlu Li
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Chen Zhang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Xingang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China.
| | - Qijie Li
- Wuhan Municipality Environmental Monitoring Center, Wuhan 430015, China
| | - Min Xiong
- College of Environment and Ecology, Chongqing University, Chongqing 400030, China
| | - Yujun Zhang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Shijie Yin
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yu Ding
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
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Nelson D, Choi Y, Sadeghi B, Yeganeh AK, Ghahremanloo M, Park J. A comprehensive approach combining positive matrix factorization modeling, meteorology, and machine learning for source apportionment of surface ozone precursors: Underlying factors contributing to ozone formation in Houston, Texas. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 334:122223. [PMID: 37481031 DOI: 10.1016/j.envpol.2023.122223] [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: 04/25/2023] [Revised: 07/13/2023] [Accepted: 07/17/2023] [Indexed: 07/24/2023]
Abstract
Ozone concentrations in Houston, Texas, are among the highest in the United States, posing significant risks to human health. This study aimed to evaluate the impact of various emissions sources and meteorological factors on ozone formation in Houston from 2017 to 2021 using a comprehensive PMF-SHAP approach. First, we distinguished the unique sources of VOCs in each area and identified differences in the local chemistry that affect ozone production. At the urban station, the primary sources were n_decane, biogenic/industrial/fuel evaporation, oil and gas flaring/production, industrial emissions/evaporation, and ethylene/propylene/aromatics. At the industrial site, the main sources were industrial emissions/evaporation, fuel evaporation, vehicle-related sources, oil and gas flaring/production, biogenic, aromatic, and ethylene and propylene. And then, we performed SHAP analysis to determine the importance and impact of each emissions factor and meteorological variables. Shortwave radiation (SHAP values are ∼5.74 and ∼6.3 for Milby Park and Lynchburg, respectively) and humidity (∼4.87 and ∼4.71, respectively) were the most important variables for both sites. For the urban station, the most important emissions sources were n_decane (∼2.96), industrial emissions/evaporation (∼1.89), and ethylene/propylene/aromatics (∼1.57), while for the industrial site, they were oil and gas flaring/production (∼1.38), ethylene/propylene (∼1.26), and industrial emissions/evaporation (∼0.95). NOx had a negative impact on ozone production at the urban station due to the NOx-rich chemical regime, whereas NOx had positive impacts at the industrial site. The study's findings suggest that the PMF-SHAP approach is efficient, inexpensive, and can be applied to other similar applications to identify factors contributing to ozone-exceedance events. The study's results can be used to develop more effective air quality management strategies for Houston and other cities with high levels of ozone.
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Affiliation(s)
- Delaney Nelson
- Department of Earth and Atmospheric Science, University of Houston, Texas, USA
| | - Yunsoo Choi
- Department of Earth and Atmospheric Science, University of Houston, Texas, USA.
| | - Bavand Sadeghi
- Air Resources Laboratory, National Oceanic and Atmospheric Administration, College Park, MD, 20740, USA; Cooperative Institute for Satellite Earth System Studies, University of Maryland, College Park, MD, 20740, USA
| | | | - Masoud Ghahremanloo
- Department of Earth and Atmospheric Science, University of Houston, Texas, USA
| | - Jincheol Park
- Department of Earth and Atmospheric Science, University of Houston, Texas, USA
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9
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Wu Y, Liu Y, Liu P, Sun L, Song P, Peng J, Li R, Wei N, Wu L, Wang T, Zhang L, Yang N, Mao H. Evaluating vehicular exhaust and evaporative emissions via VOC measurement in an underground parking garage. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 333:122022. [PMID: 37315887 DOI: 10.1016/j.envpol.2023.122022] [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: 04/09/2023] [Revised: 05/19/2023] [Accepted: 06/10/2023] [Indexed: 06/16/2023]
Abstract
Vehicular emissions, including both tailpipe exhaust and evaporative emissions, are major anthropogenic sources of volatile organic compounds (VOCs) in urban cities. Current knowledge on vehicle tailpipe and evaporative emissions was mainly obtained via laboratory tests on very few vehicles under experimental conditions. Information on fleet gasoline vehicles emission features under real-world conditions is lacking. Here, VOC measurement was conducted in a large residential underground parking garage in Tianjin, China, to reveal the feature of the exhaust and evaporative emissions from real-world gasoline vehicle fleets. The VOC concentration in the parking garage was on average 362.7 ± 87.7 μg m-3, significantly higher than that in the ambient atmosphere at the same period (63.2 μg m-3). Aromatics and alkanes were the mainly contributors on both weekdays and weekends. A positive correlation between VOCs and traffic flow was observed, especially in the daytime. Source apportionment through the positive matrix factorization model (PMF) revealed that the tailpipe and evaporative emissions accounted for 43.2% and 33.7% of VOCs, respectively. Evaporative emission contributed 69.3% to the VOCs at night due to diurnal breathing loss from numerous parked cars. In contrast, tailpipe emission was most remarkable during morning rush hours. Based on the PMF results, we reconstructed a vehicle-related VOCs profile representing the combination of the tailpipe exhaust and evaporative emission from fleet-average gasoline vehicles, which could benefit future source apportionment studies.
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Affiliation(s)
- Yajun Wu
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Yan Liu
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Peiji Liu
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Luna Sun
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Pengfei Song
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Jianfei Peng
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.
| | - Ruikang Li
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Ning Wei
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Lin Wu
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Ting Wang
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Lina Zhang
- Tianjin Academy of Eco-Environmental Sciences, Tianjin, 300071, China
| | - Ning Yang
- Tianjin Eco-Environmental Monitoring Center, Tianjin, 300192, China
| | - Hongjun Mao
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
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10
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Liu B, Yang Y, Yang T, Dai Q, Zhang Y, Feng Y, Hopke PK. Effect of photochemical losses of ambient volatile organic compounds on their source apportionment. ENVIRONMENT INTERNATIONAL 2023; 172:107766. [PMID: 36706584 DOI: 10.1016/j.envint.2023.107766] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 12/19/2022] [Accepted: 01/17/2023] [Indexed: 06/18/2023]
Abstract
Photochemical losses of ambient volatile organic compounds (VOCs) substantially affect source apportionment analysis. Hourly speciated VOC data measured from April to August 2020 in Tianjin, China were used to analyze the photochemical losses of VOC species and assess the impacts of photochemical losses on source apportionment by comparing the positive matrix factorization (PMF) results based on observed and initial concentration data (OC-PMF and IC-PMF). The initial concentrations of the VOC species were estimated using a photochemical age-based parameterization method. The results suggest that the average photochemical loss of total VOCs (TVOCs) during the ozone pollution period was 2.4 times higher than that during the non-ozone pollution period. The photochemical loss of alkenes was more significant than that of the other VOC species. Temperature has an important effect on photochemical losses, and different VOC species have different sensitivities to temperature; high photochemical losses mainly occurred at temperatures between 25 °C and 35 °C. Photochemical losses reduced the concentrations of highly reactive species in the OC-PMF factor profile. Compared with the IC-PMF results, the OC-PMF contributions of biogenic emissions and polymer production-related industrial sources were underestimated by 73 % and 50 %, respectively, likely due to the oxidation of isoprene and propene, respectively. The contribution of diesel and gasoline evaporation was underestimated by 39 %, which was likely due to the loss of m,p-xylene. Additionally, the contributions of liquefied petroleum gas, vehicle emissions, natural gas, and oil refinery were underestimated by 31 %, 29 %, 23 %, and 13 %, respectively. When the O3 concentrations were higher than 140 μg m-3 or the temperatures were higher than 30 °C, the photochemical losses from most sources increased substantially. Additionally, solar radiation produced different photochemical losses for different source types.
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Affiliation(s)
- 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
| | - 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
| | - 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
| | - Yufen Zhang
- 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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11
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Li B, Ho SSH, Li X, Guo L, Feng R, Fang X. Pioneering observation of atmospheric volatile organic compounds in Hangzhou in eastern China and implications for upcoming 2022 Asian Games. J Environ Sci (China) 2023; 124:723-734. [PMID: 36182177 DOI: 10.1016/j.jes.2021.12.029] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 12/16/2021] [Accepted: 12/19/2021] [Indexed: 06/16/2023]
Abstract
Understanding the emission sources of volatile organic compounds (VOCs) is critical for air pollution mitigation. Continuous measurements of atmospheric VOCs were conducted from January to February in Hangzhou in 2021. The average measured concentration of total VOCs (TVOCs) was 38.2 ± 20.9 ppb, > 42% lower than that reported by previous studies at the urban center in Hangzhou. The VOC concentrations and proportions were similar between weekdays and weekends. During the long holidays of the Spring Festival in China, the concentrations of TVOCs were ∼50% lower than those during the regular days, but their profiles showed no significant difference (p > 0.05). Further, we deduced that aromatics and alkenes were the most crucial chemicals promoting the formation of O3 and secondary organic aerosol (SOA) in Hangzhou. According to interspecies correlations, combustion processes and solvent use were inferred as major VOC emission sources. This study provides implications for air quality improvements before and during the upcoming Asian Games that will be hosted in Hangzhou in 2022.
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Affiliation(s)
- Bowei Li
- College of Environmental & Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Steven Sai Hang Ho
- Division of Atmospheric Sciences, Desert Research Institute, Reno, Nevada, 89512, USA
| | - Xinhe Li
- College of Environmental & Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Liya Guo
- College of Environmental & Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Rui Feng
- College of Environmental & Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Xuekun Fang
- College of Environmental & Resource Sciences, Zhejiang University, Hangzhou 310058, China; Center for Global Change Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
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12
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Li X, Li B, Guo L, Feng R, Fang X. Research progresses on VOCs emission investigations via surface and satellite observations in China. ENVIRONMENTAL SCIENCE. PROCESSES & IMPACTS 2022; 24:1968-1981. [PMID: 36000414 DOI: 10.1039/d2em00175f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Volatile organic compounds (VOCs) are important precursors of severe pollution of ozone (O3) and secondary organic aerosols in China. Fully understanding the VOCs emission is crucial for making regulations to improve air quality. This study reviews the published studies on atmospheric VOCs concentration observations in China and observation-based estimation of China's VOCs emission strengths and emission source structures. The results reveal that direct sampling and stainless-steel-tank sampling are the most commonly used methods for online and offline observations in China, respectively. The GC-MS/FID is the most commonly used VOCs measuring instrument in China (in 60.8% of the studies we summarized). Numerous studies conducted observation campaigns in urban areas (76.2%) than in suburban (17.1%), rural (18.1%), and background areas (14.3%) in China. Moreover, observation sites are largely set in eastern China (83.8%). Though there are published studies reporting observation-based China's VOCs emission investigation, these kinds of studies are still limited, and gaps are found between the results of top-down investigation and bottom-up inventories of VOCs emissions in China. In order to enhance the observation-based VOCs emission investigations in China, this study suggests future improvements including: (1) development of VOCs detection techniques, (2) strengthening of atmospheric VOCs observations, (3) improvement of the accuracy of observation-based VOCs emission estimations, and (4) facilitation of better VOCs emission inventories in China.
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Affiliation(s)
- Xinhe Li
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P. R. China.
| | - Bowei Li
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P. R. China.
| | - Liya Guo
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P. R. China.
| | - Rui Feng
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P. R. China.
| | - Xuekun Fang
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, Zhejiang 310058, P. R. China.
- State Key Joint Laboratory for Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, 100871, China
- Center for Global Change Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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13
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Niu Y, Yan Y, Chai J, Zhang X, Xu Y, Duan X, Wu J, Peng L. Effects of regional transport from different potential pollution areas on volatile organic compounds (VOCs) in Northern Beijing during non-heating and heating periods. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 836:155465. [PMID: 35500706 DOI: 10.1016/j.scitotenv.2022.155465] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/11/2022] [Accepted: 04/19/2022] [Indexed: 06/14/2023]
Abstract
Despite the adoption of air quality control measures, the influence of regional transport on volatile organic compounds (VOCs) pollution has gradually increased in Beijing. In this study, the whole observation period (September 24 to December 12, 2020) was divided into heating period and non-heating period to explore the impact of changing VOCs sources in different observation periods, and also classified into "Type-N" and "Type-S" periods both in non-heating period and heating period to explore the impact of regional transport from the northern and southern regions of sampling site, respectively. The average VOCs concentrations in northern Beijing during observation period were 22.6 ± 12.6 ppbv, which showed a decrease trend in recent years compared with other studies. And higher VOCs concentrations were observed in Type-S than in Type-N period. The positive matrix factorization results showed that vehicular exhaust dominated VOCs (26.1%-33.7%), but coal combustion could not be ignored in heating period, when it was twice that in non-heating period. In particular, coal combustion dominated VOCs in southern trajectories (30.9%) in heating period. The analysis of concentration weighted trajectory showed that coal combustion was affected by regional transport from the southeast regions of Beijing, while vehicular exhaust was affected by urban and the southeast regions of Beijing. Regarding human health risks, the carcinogenic risks of benzene and ethylbenzene exceeded the acceptable cancer risk value (1 × 10-6), and were higher in Type-S than in Type-N period. The results indicated that regional transport from urban areas and the areas south of Beijing had a significant impact on VOCs in northern Beijing. Thus, targeted control measures for different potential pollution regions are important for controlling VOCs pollution in Beijing.
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Affiliation(s)
- Yueyuan Niu
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Yulong Yan
- Institute of Transport Energy and Environment, Beijing Jiaotong University, Beijing 100044, China; School of Environment, Beijing Jiaotong University, Beijing 100044, China.
| | - Jianwei Chai
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Xiangyu Zhang
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Yang Xu
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Xiaolin Duan
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Jing Wu
- Institute of Transport Energy and Environment, Beijing Jiaotong University, Beijing 100044, China; School of Environment, Beijing Jiaotong University, Beijing 100044, China
| | - Lin Peng
- Institute of Transport Energy and Environment, Beijing Jiaotong University, Beijing 100044, China; School of Environment, Beijing Jiaotong University, Beijing 100044, China
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14
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Characteristics and Sources of Volatile Organic Compounds in the Nanjing Industrial Area. ATMOSPHERE 2022. [DOI: 10.3390/atmos13071136] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
In this study, 56 volatile organic compounds species (VOCs) and other pollutants (NO, NO2, SO2, O3, CO and PM2.5) were measured in the northern suburbs of Nanjing from September 2014 to August 2015. The total volatile organic compound (TVOC) concentrations were higher in the autumn (40.6 ± 23.8 ppbv) and winter (41.1 ± 21.7 ppbv) and alkanes were the most abundant species among the VOCs (18.4 ± 10.0 ppbv). According to the positive matrix factorization (PMF) model, the VOCs were found to be from seven sources in the northern suburbs of Nanjing, including liquefied petroleum gas (LPG) sources, gasoline vehicle emissions, iron and steel industry sources, industrial refining coke sources, solvent sources and petrochemical industry sources. One of the sources was influenced by seasonal variations: it was a diesel vehicle emission source in the spring, while it was a coal combustion source in the winter. According to the conditional probability function (CPF) method, it was found that the main contribution areas of each source were located in the easterly direction (mainly residential areas, industrial areas, major traffic routes, etc.). There were also seasonal differences in concentration, ozone formation potential (OFP), OH radical loss rate (LOH) and secondary organic aerosols potential (SOAP) for each source due to the high volatility of the summer and autumn temperatures, while combustion increases in the winter. Finally, the time series of O3 and OFP was compared to that PM2.5 and SOAP and then they were combined with the wind rose figure. It was found that O3 corresponded poorly to the OFP, while PM2.5 corresponded well to the SOAP. The reason for this was that the O3 generation was influenced by several factors (NOx concentration, solar radiation and non-local transport), among which the influence of non-local transport could not be ignored.
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15
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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: 23] [Impact Index Per Article: 7.7] [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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16
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Yang T, Liu B, Yang Y, Dai Q, Zhang Y, Feng Y, Hopke PK. Improved positive matrix factorization for source apportionment of volatile organic compounds in vehicular emissions during the Spring Festival in Tianjin, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 303:119122. [PMID: 35276248 DOI: 10.1016/j.envpol.2022.119122] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/25/2021] [Revised: 02/26/2022] [Accepted: 03/07/2022] [Indexed: 06/14/2023]
Abstract
Photochemical losses of volatile organic compounds (VOCs) and uncertainties in calculated factor profiles can reduce the accuracy of source apportionment by positive matrix factorization (PMF). We developed an improved PMF method (termed ICLP-PMF) that estimated the reaction-corrected ("initial") concentrations of VOCs. Source profiles from literature provided constraints. ICLP-PMF evaluated the vehicular emission contributions to hourly speciated VOC data from December 2020 to March 2021 and estimated gasoline and diesel vehicles contributions to Tianjin's VOC concentrations around the Chinese Spring Festival (SF). The average observed and initial total VOCs (TVOCs) concentrations were 24.2 and 42.9 ppbv, respectively. Alkanes were the highest concentration VOCs while aromatics showed the largest photochemical losses during the study period. Literature gasoline and diesel profiles from representative Chinese cities were constructed and provided constraints. Source apportionment was performed using ICLP-PMF method and three other PMF approaches. Photochemical losses of alkenes and aromatic hydrocarbons induced differences between calculated factor profiles and literature profiles. Using observed concentrations and unconstrained profiles produced underestimated SF contributions (∼121% and 72% for gasoline and diesel vehicles, respectively). According to the ICLP-PMF results, the contributions of gasoline and diesel vehicles during the SF were 25.6% and 23.2%, respectively, lower than those before and after the SF. No diel diesel vehicle contribution variations were found during the SF likely due to the decline in truck activity north of the study site during the holiday period.
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Affiliation(s)
- 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
| | - 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.
| | - 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
| | - 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
| | - Yufen Zhang
- 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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17
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Luo W, Deng Z, Zhong S, Deng M. Trends, Issues and Future Directions of Urban Health Impact Assessment Research: A Systematic Review and Bibliometric Analysis. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19105957. [PMID: 35627492 PMCID: PMC9141375 DOI: 10.3390/ijerph19105957] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 05/11/2022] [Accepted: 05/12/2022] [Indexed: 02/06/2023]
Abstract
Health impact assessment (HIA) has been regarded as an important means and tool for urban planning to promote public health and further promote the integration of health concept. This paper aimed to help scientifically to understand the current situation of urban HIA research, analyze its discipline co-occurrence, publication characteristics, partnership, influence, keyword co-occurrence, co-citation, and structural variation. Based on the ISI Web database, this paper used a bibliometric method to analyze 2215 articles related to urban HIA published from 2012 to 2021. We found that the main research directions in the field were Environmental Sciences and Public Environmental Occupational Health; China contributed most articles, the Tehran University of Medical Sciences was the most influential institution, Science of the Total Environment was the most influential journal, Yousefi M was the most influential author. The main hotspots include health risk assessment, source appointment, contamination, exposure, particulate matter, heavy metals and urban soils in 2012–2021; road dust, source apposition, polycyclic aromatic hydrocarbons, air pollution, urban topsoil and the north China plain were always hot research topics in 2012–2021, drinking water and water quality became research topics of great concern in 2017–2021. There were 25 articles with strong transformation potential during 2020–2021, but most papers carried out research on the health risk assessment of toxic elements in soil and dust. Finally, we also discussed the limitations of this paper and the direction of bibliometric analysis of urban HIA in the future.
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Affiliation(s)
- Wenbing Luo
- School of Business, Hunan University of Science and Technology, Xiangtan 411201, China; (W.L.); (Z.D.)
- School of Accounting, Hunan University of Technology and Business, Changsha 410205, China
| | - Zhongping Deng
- School of Business, Hunan University of Science and Technology, Xiangtan 411201, China; (W.L.); (Z.D.)
| | - Shihu Zhong
- Shanghai National Accounting Institute, Shanghai 201702, China
- Correspondence:
| | - Mingjun Deng
- Big Data and Intelligent Decision Research Center, Hunan University of Science and Technology, Xiangtan 411201, China;
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18
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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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19
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Wang F, Zhang Z, Wang G, Wang Z, Li M, Liang W, Gao J, Wang W, Chen D, Feng Y, Shi G. Machine learning and theoretical analysis release the non-linear relationship among ozone, secondary organic aerosol and volatile organic compounds. J Environ Sci (China) 2022; 114:75-84. [PMID: 35459516 DOI: 10.1016/j.jes.2021.07.026] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 07/22/2021] [Accepted: 07/22/2021] [Indexed: 06/14/2023]
Abstract
Fine particulate matter (PM2.5) and ozone (O3) pollutions are prevalent air quality issues in China. Volatile organic compounds (VOCs) have significant impact on the formation of O3 and secondary organic aerosols (SOA) contributing PM2.5. Herein, we investigated 54 VOCs, O3 and SOA in Tianjin from June 2017 to May 2019 to explore the non-linear relationship among O3, SOA and VOCs. The monthly patterns of VOCs and SOA concentrations were characterized by peak values during October to March and reached a minimum from April to September, but the observed O3 was exactly the opposite. Machine learning methods resolved the importance of individual VOCs on O3 and SOA that alkenes (mainly ethylene, propylene, and isoprene) have the highest importance to O3 formation; alkanes (Cn, n ≥ 6) and aromatics were the main source of SOA formation. Machine learning methods revealed and emphasized the importance of photochemical consumptions of VOCs to O3 and SOA formation. Ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP) calculated by consumed VOCs quantitatively indicated that more than 80% of the consumed VOCs were alkenes which dominated the O3 formation, and the importance of consumed aromatics and alkenes to SOAFP were 40.84% and 56.65%, respectively. Therein, isoprene contributed the most to OFP at 41.45% regardless of the season, while aromatics (58.27%) contributed the most to SOAFP in winter. Collectively, our findings can provide scientific evidence on policymaking for VOCs controls on seasonal scales to achieve effective reduction in both SOA and O3.
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Affiliation(s)
- Feng Wang
- 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 (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Zhongcheng Zhang
- 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 (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Gen Wang
- State Key Laboratory on Odor Pollution Control, Tianjin Academy of Environmental Sciences, Tianjin 300191, China
| | - Zhenyu Wang
- 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 (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Mei Li
- Guangdong Provincial Engineering Research Center for On-line Source Apportionment System of Air Pollution Jinan University, Institute of Mass Spectrometry and Atmospheric Environment, Guangzhou 510632, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 510632, China
| | - Weiqing Liang
- 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 (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Jie Gao
- 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 (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Wei Wang
- Trusted AI System Laboratory, College of Computer Science, Nankai University, Tianjin 300350, China.
| | - Da Chen
- Key Laboratory of Civil Aviation Thermal Hazards Prevention and Emergency Response, Civil Aviation University of China, Tianjin 300300, 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 (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Guoliang Shi
- 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 (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
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20
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Temporal and Spatial Analysis of PM2.5 and O3 Pollution Characteristics and Transmission in Central Liaoning Urban Agglomeration from 2015 to 2020. SUSTAINABILITY 2022. [DOI: 10.3390/su14010511] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The central Liaoning urban agglomeration is an important heavy industry development base in China, and also an important part of the economy in northeast China. The atmospheric environmental problems caused by the development of heavy industry are particularly prominent. Trajectory clustering, potential source contribution (PSCF), and concentration weighted trajectory (CWT) analysis are used to discuss the temporal and spatial pollution characteristics of PM2.5 and ozone concentrations and reveal the regional atmospheric transmission pattern in central Liaoning urban agglomeration from 2015 to 2020. The results show that: (1) PM2.5 in the central Liaoning urban agglomeration showed a decreasing trend from 2015 to 2020. The concentration of PM2.5 is the lowest in 2018. Except for Benxi (34.7 µg/m3), the concentrations of PM2.5 in other cities do not meet the standard in 2020. The ozone concentration in Anshan, Liaoyang, and Shenyang reached the peaks in 2017, which are 68.76 µg/m3, 66.27 µg/m3, and 63.46 µg/m3 respectively. PM2.5 pollution is the highest in winter and the lowest in summer. The daily variation distribution of PM2.5 concentration showed a bimodal pattern. Ozone pollution is the most serious in summer, with the concentration of ozone reaching 131.14 µg/m3 in Shenyang. Fushun is affected by Shenyang intercity pollution, and the ozone concentration is high. (2) In terms of spatial distribution, the high values of PM2.5 are concentrated in monitoring stations in urban areas. On the contrary, the concentration of ozone in suburban stations is higher. The high concentration of ozone in the northeast of Anshan, Liaoyang, Shenyang to Tieling, and Fushun extended in a band distribution. (3) Through cluster analysis, it is found that PM2.5 and ozone in Shenyang are mainly affected by short-distance transport airflow. In winter, the weighted PSCF high-value area of PM2.5 presents as a potential contribution source zone of the northeast trend with wide coverage, in which the contribution value of the weighted CWT in the middle of Heilongjiang is the highest. The main potential source areas of ozone mass concentration in spring and summer are coastal cities and the Bohai Sea and the Yellow Sea. We conclude that the regional transmission of pollutants is an important factor of pollution, so we should pay attention to the supply of industrial sources and marine sources of marine pollution in the surrounding areas of cities, and strengthen the joint prevention and control of air pollution among regions. The research results of this article provide a useful reference for the central Liaoning urban agglomeration to improve air quality.
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Gu Y, Liu B, Dai Q, Zhang Y, Zhou M, Feng Y, Hopke PK. Multiply improved positive matrix factorization for source apportionment of volatile organic compounds during the COVID-19 shutdown in Tianjin, China. ENVIRONMENT INTERNATIONAL 2022; 158:106979. [PMID: 34991244 DOI: 10.1016/j.envint.2021.106979] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 10/13/2021] [Accepted: 11/10/2021] [Indexed: 06/14/2023]
Abstract
Ambient concentrations of volatile organic compounds (VOCs) vary with emission rates, meteorology, and chemistry. Conventional positive matrix factorization (PMF) loses information because of dilution variations and chemical losses. Multiply improved PMF incorporates the ventilation coefficient, and total solar radiation or oxidants to reduce the effects of dispersion and chemical loss. These methods were applied to hourly speciated VOC data from November 2019 to March 2020 including during the COVID-19 shutdown. Various comparisons were made to assess the influences of these fluctuation drivers by time of day. Dispersion normalized PMF (DN-PMF) reduced the dispersion variations. Dispersion-radiation normalized PMF (DRN-PMF) reduced the impact of chemical loss, especially at night, which was better than Dispersion-Ox normalized PMF (DON-PMF). The conditional bivariate probability function (CBPF) plots of DRN-PMF results were consist with actual source locations. The DN-PMF, DRN-PMF, and DON-PMF results were consistent between 10:00 and 15:00, suggesting dispersion was significantly more influential than photochemical reactions during these times. The DRN-PMF results indicated that the highest VOC contributors during the COVID-19 shutdown were liquefied petroleum gas (LPG) (28.8%), natural gas (25.2%), and pulverized coal boilers emissions (19.6%). Except for petrochemical-related enterprises and LPG, the contribution concentrations of all other sources decreased substantially during the COVID-19 shutdown, by 94.7%, 90.6%, and 86.8% for vehicle emissions, gasoline evaporation, and the mixed source of diesel evaporation and solvent use, respectively. Controlling the use of motor vehicles and related volatilization of diesel fuel and gasoline can be effective in controlling VOCs in the future.
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Affiliation(s)
- Yao Gu
- 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.
| | - 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
| | - Yufen Zhang
- 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
| | - Ming Zhou
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, 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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22
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Li J, Deng S, Li G, Lu Z, Song H, Gao J, Sun Z, Xu K. VOCs characteristics and their ozone and SOA formation potentials in autumn and winter at Weinan, China. ENVIRONMENTAL RESEARCH 2022; 203:111821. [PMID: 34370988 DOI: 10.1016/j.envres.2021.111821] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2021] [Revised: 07/29/2021] [Accepted: 07/29/2021] [Indexed: 06/13/2023]
Abstract
Frequent ozone and fine particulate matter (PM2.5) pollution have been occurring in the Guanzhong Plain in China. To effectively control the tropospheric ozone and PM2.5 pollution, this study performed measurements of 102 VOCs species from Sep.19-25 (autumn) and Nov.27-Dec. 8, 2017 (winter) at Weinan in the central Guanzhong Plain. The total volatile organic compounds (TVOCs) concentrations were 95.8 ± 30.6 ppbv in autumn and 74.4 ± 37.1 ppbv in winter. Alkanes were the most abundant group in both of autumn and winter, accounting for 33.5% and 39.6% of TVOCs concentrations, respectively. The levels of aromatics and oxygenated VOCs were higher in autumn than in winter, mainly due to changes in industrial activities and combustion strength. Photochemical reactivities and ozone formation potentials (OFPs) of VOCs were calculated by applying the OH radical loss rate (LOH) and maximum incremental reactivity (MIR) method, respectively. Results showed that Alkenes and aromatics were the key VOCs in term ozone formation in Weinan, which together contributed 59.6% ̶ 65.3% to the total LOH and OFP. Secondary organic aerosol formation potentials (SOAFP) of the measured VOCs were investigated by employing the fractional aerosol coefficient (FAC) method. Aromatics contributed 94.9% and 96.2% to the total SOAFP in autumn and winter, respectively. The regional transport effects on VOCs and ozone formation were investigated by using trajectory analysis and potential source contribution function (PSCF). Results showed that regional anthropogenic sources from industrial cities (Tongchuan, Xi'an city) and biogenic sources from Qinling Mountain influenced VOCs levels and OFP at Weinan. Future studies need to emphasize on meteorological factors and sources that impact on VOCs concentrations in Weinan.
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Affiliation(s)
- Jianghao Li
- School of Water and Environment, Chang'an University, Xi'an, 710064, China; Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, 710064, China
| | - Shunxi Deng
- School of Water and Environment, Chang'an University, Xi'an, 710064, China; Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, 710064, China.
| | - Guanghua Li
- School of Water and Environment, Chang'an University, Xi'an, 710064, China; Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, 710064, China
| | - Zhenzhen Lu
- School of Water and Environment, Chang'an University, Xi'an, 710064, China; Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, 710064, China
| | - Hui Song
- School of Water and Environment, Chang'an University, Xi'an, 710064, China; School of Architectural Engineering, Chang'an University, Xi'an, 710064, China
| | - Jian Gao
- Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Zhigang Sun
- School of Water and Environment, Chang'an University, Xi'an, 710064, China; Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, 710064, China
| | - Ke Xu
- School of Water and Environment, Chang'an University, Xi'an, 710064, China; Key Laboratory of Subsurface Hydrology and Ecological Effect in Arid Region of Ministry of Education, Chang'an University, Xi'an, 710064, China
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23
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Xie G, Chen H, Zhang F, Shang X, Zhan B, Zeng L, Mu Y, Mellouki A, Tang X, Chen J. Compositions, sources, and potential health risks of volatile organic compounds in the heavily polluted rural North China Plain during the heating season. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 789:147956. [PMID: 34052493 DOI: 10.1016/j.scitotenv.2021.147956] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 05/17/2021] [Accepted: 05/17/2021] [Indexed: 06/12/2023]
Abstract
Severe volatile organic compound (VOC) pollution has become an urgent problem during the heating season in the North China Plain (NCP), as exposure to hazardous VOCs can lead to chronic or acute diseases. A campaign with online VOC measurements was conducted at a rural site in Wangdu, NCP during the 2018 heating season to characterize the compositions and associated sources of VOCs and to assess their potential health risks. The total concentration of VOCs with 94 identified species was 77.21 ± 54.39 ppb. Seven source factors were identified by non-negative matrix factorization, including coal combustion (36.1%), LPG usage (21.1%), solvent usage (13.9%), biomass burning and secondary formation (14.2%), background (7.0%), industrial emissions (4.5%), and vehicle emissions (3.3%). The point estimate approach and Monte Carlo simulation were used to estimate the carcinogenic and non-carcinogenic risks of harzadous VOCs. The results showed that the cumulative health risk of VOCs was above the safety level. Acrolein, 1.2-dichloroethane, 1,2-dichloropropane, chloroform, 1,3-butadiene, and benzene were identified as the key hazardous VOCs in Wangdu. Benzene had the highest average carcinogenic risk. Solvent usage and secondary formation were the dominant sources of adverse health effects. During the Spring Festival, most sources were sharply reduced; and VOC concentration declined by 49%. However, coal and biomass consumptions remained relatively large, probably due to heating demand. This study provides important references for the control strategies of VOCs during the heating season in heavily polluted rural areas in the NCP.
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Affiliation(s)
- Guangzhao Xie
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China
| | - Hui Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China.
| | - Fei Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China; State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Acadamy of Environment Sciences, Shanghai 200233, China
| | - Xiaona Shang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China
| | - Bixin Zhan
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China
| | - Limin Zeng
- School of Environmental Science & Engineering, Peking University, Beijing 100071, China
| | - Yujing Mu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Abdelwahid Mellouki
- Institut de Combustion, Aerothermique, Reactivite et Environnement, CNRS, 45071 Orleans cedex 02, France
| | - Xu Tang
- IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, China; IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China.
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24
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Sun L, Zhong C, Peng J, Wang T, Wu L, Liu Y, Sun S, Li Y, Chen Q, Song P, Mao H. Refueling emission of volatile organic compounds from China 6 gasoline vehicles. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 789:147883. [PMID: 34323824 DOI: 10.1016/j.scitotenv.2021.147883] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 04/22/2021] [Accepted: 05/13/2021] [Indexed: 06/13/2023]
Abstract
Vehicular refueling emission is a potential source of urban atmospheric volatile organic compounds (VOCs) that is not well understood and controlled. China 6 vehicles have been equipped with the onboard refueling vapor recovery (ORVR) system to cut down refueling emissions, while the emission characteristics and reduction effectiveness are rarely reported. In this study, we conducted laboratory tests to measure the refueling emissions from ten China 6 vehicles and three China 5 vehicles (refueling-emission-uncontrolled, REU) and developed an inventory in a typical middle-sized Chinese city (Langfang) to explore the emission reduction resulted from relevant policies. Compared with headspace vapor and refueling vapor from REU vehicles, the emission profiles for China 6 vehicles are consist of considerably higher proportions of small alkanes and alkenes (C2-C3) and lower proportions of C6-C8 hydrocarbons. Such differences indicate that the headspace vapor profiles are incapable of representing the refueling emission for China 6 vehicles. The market-share-weighting emission factors (EFs) of total hydrocarbons (THCs) and total VOCs for China 6 vehicles are 11.2 mg/L and 6.4 mg/L, respectively, corresponding to control efficiency of approximately 98.8% compared with the REU vehicles. Based on the real-world EFs and the fuel consumption in Langfang, a refueling emission inventory with high spatiotemporal resolution is developed. The total refueling emission of THCs in Langfang is approximately 190.6 tons in 2018 and will likely decline to 25.0 tons in 2035. The implementation of the ORVR will contribute to 90% of the refueling emission reduction in 2035.
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Affiliation(s)
- Luna Sun
- Tianjin Key Laboratory of Urban Transport Emission Research, State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Chongzhi Zhong
- China Automotive Technology and Research Center Co., Ltd, Tianjin 300300, China
| | - Jianfei Peng
- Tianjin Key Laboratory of Urban Transport Emission Research, State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China.
| | - Ting Wang
- Tianjin Key Laboratory of Urban Transport Emission Research, State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Lin Wu
- Tianjin Key Laboratory of Urban Transport Emission Research, State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Yan Liu
- Tianjin Key Laboratory of Urban Transport Emission Research, State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Shida Sun
- Tianjin Key Laboratory of Urban Transport Emission Research, State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Yuening Li
- Department of Physical and Environmental Sciences, University of Toronto, 1265 Military Trail, Toronto, Ontario M1C 1A4, Canada
| | - Qiang Chen
- China Automotive Technology and Research Center Co., Ltd, Tianjin 300300, China
| | - Pengfei Song
- Tianjin Key Laboratory of Urban Transport Emission Research, State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China
| | - Hongjun Mao
- Tianjin Key Laboratory of Urban Transport Emission Research, State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300071, China.
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25
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Diao L, Zhang H, Liu B, Dai C, Zhang Y, Dai Q, Bi X, Zhang L, Song C, Feng Y. Health risks of inhaled selected toxic elements during the haze episodes in Shijiazhuang, China: Insight into critical risk sources. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 276:116664. [PMID: 33609903 DOI: 10.1016/j.envpol.2021.116664] [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: 10/27/2020] [Revised: 01/26/2021] [Accepted: 02/02/2021] [Indexed: 06/12/2023]
Abstract
PM2.5 in Shijiazhuang was collected from October 15, 2018 to January 31, 2019, and selected toxic elements were measured. Five typical haze episodes were chosen to analyze the health risks and critical risk sources. Toxic elements during the haze episodes accounted for 0.33% of PM2.5 mass. Non-cancer risk of toxic elements for children was 1.8 times higher than that for adults during the haze episodes, while cancer risk for adults was 2.5 times higher than that for children; cancer and non-cancer risks were primarily attributable to As and Mn, respectively. Health risks of toxic elements increased during the growth and stable periods of haze episodes. Non-cancer and cancer risks of toxic elements during the haze stable periods were higher than other haze stages, and higher for children than for adults during the stable period. Mn was the largest contributor to non-cancer risk during different haze stages, while As was the largest contributor to cancer risk. Crustal dust, vehicle emissions, and industrial emissions were critical sources of cancer risk during the clean-air periods; while vehicle emissions, coal combustion, and crustal dust were key sources of cancer risk during the haze episodes. Cancer risks of crustal dust and vehicle emissions during the haze episodes were 2.0 and 1.7 times higher than those in the clean-air periods. Non-cancer risks from emission sources were not found during different periods. Cancer risks of biomass burning and coal combustion increased rapidly during the haze growth period, while that of coal combustion decreased sharply during the dissipation period. Vehicle emissions, crustal dust, and coal combustion were significant cancer risk sources during different haze stages, cancer risk of each source was the highest during the stable period. Southern Hebei, Northern and central Shaanxi were potential risk regions that affected the health of both adults and children in Shijiazhuang.
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Affiliation(s)
- Liuli Diao
- 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
| | - Huitao Zhang
- 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
| | - 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.
| | - Chunling Dai
- Shijiazhuang Ecological and Environmental Monitoring Center of Hebei Province, Shijiazhuang, 050022, China
| | - Yufen Zhang
- 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
| | - 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
| | - Xiaohui Bi
- 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
| | - Lingzhi Zhang
- Shijiazhuang Ecological and Environmental Monitoring Center of Hebei Province, Shijiazhuang, 050022, China
| | - Congbo Song
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - 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
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Abstract
Pollution prevention is an approach for generating less waste using fewer toxic chemicals while conserving water and energy. Even though pollution prevention practices have been encouraged for over thirty years, many smaller businesses have not considered or adopted such techniques. This study examines the effect of a community-based approach designed to emphasize the benefits to the health and economic well-being of urban communities when source reduction practices are implemented by businesses in the community. Partnering with existing community groups in Newark and Jersey City, NJ, technical assistance was provided to small and medium-sized businesses under grant funding from Region 2 of the US Environmental Protection Agency. In this research, 32 small and medium-sized businesses were evaluated for source reduction opportunities and implementation plans were drawn up. After these businesses implemented operational changes, emission and cost savings were determined and reported back to respective small business owners as well as to the communities during community meetings designed to encourage additional participation. Based on 32 case studies, several measurable benefits were achieved, including the yearly saving of 932 pounds of hazardous waste, 3917 pounds of non-hazardous waste, 13.62 metric tons of carbon equivalent (MTCE) of greenhouse gases and $5335 USD. The initial findings suggest that community-based programs such as this can be beneficial but must be sustained over a period of time. One issue that was repeatedly observed, and is likely widely believed, is the concern of small business operators that cooperation with any group funded by a government program may lead to the assessment of fines or penalties for environmental violations. This concern limits the willingness of many smaller businesses to participate. The findings of this study suggest that a sustained community-based program may overcome that concern through demonstration of the benefit to the business and the community, and through credibility building achieved by regular community reporting and the absence of official intervention.
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