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Chen Y, Lu Y, Qi B, Ma Q, Zang K, Lin Y, Liu S, Pan F, Li S, Guo P, Chen L, Lan W, Fang S. Atmospheric CO 2 in the megacity Hangzhou, China: Urban-suburban differences, sources and impact factors. Sci Total Environ 2024; 926:171635. [PMID: 38490430 DOI: 10.1016/j.scitotenv.2024.171635] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 02/15/2024] [Accepted: 03/08/2024] [Indexed: 03/17/2024]
Abstract
Limited observation sites and insufficient monitoring of atmospheric CO2 in urban areas restrict our comprehension of urban-suburban disparities. This research endeavored to shed light on the urban-suburban differences of atmospheric CO2 in levels, diurnal and seasonal variations as well as the potential sources and impact factors in the megacity of Hangzhou, China, where the economically most developed region in China is. The observations derived from the existing Hangzhou Atmospheric Composition Monitoring Center Station (HZ) and Lin'an Regional Atmospheric Background Station (LAN) and the newly established high-altitude Daming Mountain Atmospheric Observation Station (DMS), were utilized. From November 2020 to October 2021, the annual averages of HZ, LAN and DMS were 446.52 ± 17.01 ppm, 441.56 ± 15.42 ppm, and 422.02 ± 10.67 ppm. The difference in atmospheric CO2 mole fraction between HZ and LAN was lower compared to the urban-suburban differences observed in other major cities in China, such as Shanghai, Nanjing, and Beijing. Simultaneous CO2 enhancements were observed at HZ and LAN, when using DMS observations as background references. The seasonal variations of CO2 at LAN and DMS exhibited a high negative correlation with the normalized difference vegetation index (NDVI) values, indicating the strong regulatory of vegetation canopy. The variations in boundary layer height had a larger influence on the low-altitude HZ and LAN stations than DMS. Compared to HZ and LAN, the atmospheric CO2 at DMS was influenced by emissions and transmissions over a wider range. The potential source area of DMS in autumn covered most areas of the urban agglomeration in eastern China. DMS measurements could provide a reliable representation of the background level of CO2 emissions in the Yangtze River Delta and a broader region. Conventional understanding of regional CO2 level in the Yangtze River Delta through LAN measurements may overestimate background concentration by approximately 10.92 ppm.
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Affiliation(s)
- Yuanyuan Chen
- Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou 310014, China; College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Yanran Lu
- Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou 310014, China; College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Bing Qi
- Hangzhou Meteorological Bureau, Hangzhou 310051, China
| | - Qianli Ma
- Lin'an Regional Background Station, China Meteorological Administration, Zhejiang 314016, China
| | - Kunpeng Zang
- Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou 310014, China; College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Yi Lin
- Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou 310014, China; College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Shuo Liu
- Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou 310014, China; College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Fengmei Pan
- Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou 310014, China; College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Shan Li
- Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou 310014, China; College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Peng Guo
- Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou 310014, China; College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Lihan Chen
- Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou 310014, China; College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Wengang Lan
- Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou 310014, China; College of Environment, Zhejiang University of Technology, Hangzhou 310014, China
| | - Shuangxi Fang
- Zhejiang Carbon Neutral Innovation Institute & Zhejiang International Cooperation Base for Science and Technology on Carbon Emission Reduction and Monitoring, Zhejiang University of Technology, Hangzhou 310014, China; College of Environment, Zhejiang University of Technology, Hangzhou 310014, China; Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China.
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Dong Z, Zhang D, Wang T, Song X, Hao Y, Wang S, Wang S. Sources and environmental impacts of volatile organic components in a street canyon: Implication for vehicle emission. Sci Total Environ 2024; 917:170569. [PMID: 38296102 DOI: 10.1016/j.scitotenv.2024.170569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 01/28/2024] [Accepted: 01/28/2024] [Indexed: 02/03/2024]
Abstract
Street canyons serve as a representative environment that directly reflects the impact of vehicular emissions. Volatile organic compounds (VOCs) sampling during an O3 pollution event and a PM2.5 pollution episode was conducted at an urban site and a street canyon in Zhengzhou, China. It has been determined that street canyons suffer from more severe particle and NOx pollution than the urban site. Additionally, O3 has been identified as a significant or emerging pollutant in street canyon environments. In terms of VOCs, the street canyon exhibits 1.4 and 1.1 times higher total VOC concentrations compared to the urban site during the O3 and PM2.5 pollution episodes, respectively. In the street canyon location, there was a slight increase in the proportion of alkanes and aromatics, while the proportions of oxygenated VOCs and halogenated hydrocarbons decreased. Source apportionment analysis reveals that street canyons were more susceptible to the accumulation of VOCs from coating solvent, liquid petroleum gas (LPG), and gasoline additives. Consequently, the environmental impacts of VOCs originating from coating solvent and LPG were more pronounced in the street canyon location compared to the urban site. The trends of NOx concentration indicate that future continuously stricter vehicle emission standards and control policies can further reduce vehicle exhaust emissions and more attention needs to be focused on the reduction of non-exhaust emissions (i.e., coating solvent) and LPG vehicles.
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Affiliation(s)
- Zhangsen Dong
- College of Chemistry, Zhengzhou University, Zhengzhou 450001, China; Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China
| | - Dong Zhang
- College of Chemistry, Zhengzhou University, Zhengzhou 450001, China; Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China
| | - Tiantian Wang
- Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450000, China
| | - Xinshuai Song
- Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450000, China
| | - Yanyan Hao
- Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450000, China
| | - Shanshan Wang
- Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450000, China
| | - Shenbo Wang
- Research Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450000, China; School of Ecology and Environment, Zhengzhou University, Zhengzhou 450000, China.
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Ren H, Xia Z, Yao L, Qin G, Zhang Y, Xu H, Wang Z, Cheng J. Investigation on ozone formation mechanism and control strategy of VOCs in petrochemical region: Insights from chemical reactivity and photochemical loss. Sci Total Environ 2024; 914:169891. [PMID: 38190918 DOI: 10.1016/j.scitotenv.2024.169891] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 12/11/2023] [Accepted: 01/01/2024] [Indexed: 01/10/2024]
Abstract
To investigate disparities in VOCs pollution characteristics, O3 generation activity, and source apportionment outcomes resulting from photooxidation, online monitoring of 106 VOCs was conducted in Jinshan District, Shanghai from April to October 2020. The observed VOCs concentrations (VOCs-obs) were 47.1 ppbv and 59.2 ppbv for clear days (CD) and O3-polluted days (OPD), respectively. The increase in daytime concentrations of alkenes is a significant factor contributing to the enhanced atmospheric photochemical activity during the OPD period, corroborated by VOCs-loss, ozone formation potential (OFP), propy-equiv concentration, and LOH. The sensitivity analysis of O3-NOx-VOCs indicated that O3 formation was in a transitional regime towards NOx-limited conditions. The results of positive matrix factorization (PMF) demonstrated that refining and petrochemicals (20.8-25.0 %), along with oil and gas evaporation (15.6-16.7 %) were the main sources of VOCs concentrations. Notably, source apportionment based on VOCs-obs underestimated the contributions from sources of reactive components. It is worth highlighting that the sunlight impact & background source was identified as the major contributor to LOH (21.6 %) and OFP (25.3 %), signifying its significant role in O3 formation. This study reiterates the importance of controlling reactive VOC components to mitigate O3 pollution and provides a scientific foundation for air quality management, with emphasis on priority species and controlling sources.
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Affiliation(s)
- Huarui Ren
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Zhongyan Xia
- Fengxian District Environmental Monitoring Station, Shanghai 201400, China
| | - Lingbo Yao
- Fengxian District Environmental Monitoring Station, Shanghai 201400, China
| | - Guimei Qin
- Sinopec Shanghai Petrochemical Co., Ltd., Shanghai 200540, China
| | - Yu Zhang
- Tianjin Product Quality Inspection Technology Research Institute, Tianjin 300384, China
| | - Hui Xu
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Zhuo Wang
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Jinping Cheng
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
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Zuo H, Jiang Y, Yuan J, Wang Z, Zhang P, Guo C, Wang Z, Chen Y, Wen Q, Wei Y, Li X. Pollution characteristics and source differences of VOCs before and after COVID-19 in Beijing. Sci Total Environ 2024; 907:167694. [PMID: 37832670 DOI: 10.1016/j.scitotenv.2023.167694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 09/14/2023] [Accepted: 10/07/2023] [Indexed: 10/15/2023]
Abstract
During the outbreak of the COVID-19, the change in the way of people's living and production provided the opportunity to study the influence of human activity on Volatile organic compounds (VOCs) in the atmosphere. Therefore, this study analyzed VOCs concentration and composition characteristics in urban area of Beijing from 2019 to 2020. The results showed that the concentration of VOCs in Chaoyang district in 2020 was 73.1ppbv, lower than that in 2019 (92.8ppbv), and alkanes (45 % and 47 %) were the most dominant components. The concentrations of isopentane, n-pentane, n-hexane, and OVOCs significantly increased in 2020. According to the results of the PMF model, the contribution of VOCs from vehicle and pharmaceutical-related emissions increased to 45.8 % and 27.1 % in 2020, while coal combustion decreased by 23.7 %. This is likely linked to the strict implementation of the coal conversion policy, as well as the increment in individual travel and pharmaceutical production during the pandemic. The calculation results of OFP and SOAFP indicated that toluene had an increased impact on the formation of O3 and SOA in the Chaoyang district in 2020. Notably, VOCs emitted by vehicles have the highest potential for secondary generation. In addition, VOCs from vehicles and industries pose the greatest health risks, together accounting for 77.4 % and 79.31 % of the total carcinogenic risk in 2019 and 2020. Although industrial emission with the high proportions of halocarbons was controlled to some extent during the pandemic, the carcinogenic risk in 2020 was 3.74 × 10-6, which still exceeded the acceptable level, and more attention and governance efforts should be given to.
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Affiliation(s)
- Hanfei Zuo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; School of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150006, China
| | - Yuchun Jiang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Jing Yuan
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; School of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150006, China
| | - Ziqi Wang
- College of Arts and Sciences, University of Cincinnati, Cincinnati, State of Ohio 45221, USA
| | - Puzhen Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Chen Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Zhanshan Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Ye Chen
- School of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150006, China
| | - Qing Wen
- School of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150006, China
| | - Yongjie Wei
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Xiaoqian Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; School of Materials Science and Chemical Engineering, Harbin Engineering University, Harbin 150006, China.
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Huang H, Wang Z, Dai C, Wu H, Guo J, Wang C, Zhang X. Species profile and reactivity of volatile organic compounds emission in solvent uses, industry activities and from vehicular tunnels. J Environ Sci (China) 2024; 135:546-559. [PMID: 37778826 DOI: 10.1016/j.jes.2022.08.035] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 08/28/2022] [Accepted: 08/30/2022] [Indexed: 10/03/2023]
Abstract
A survey was conducted of the volatile organic compounds (VOCs) released from sources of solvent use, industry activities and vehicle emissions in Guiyang, a capital city of China. Samples were collected by canisters and analyzed by GC-MS-FID. The species profiles of VOCs emitted from sources were obtained. Results showed that xylenes, ethylbenzene, acetone and dichloromethane were the characteristics species for painting, 2-propanol and ethyl acetate for printing, α-pinene for solid wood furniture manufacturing, and 2-butanone for biscuit baking. These characteristics species could be as tracers for the sources respectively. In most of samples from the solvent use, the benzene/toluene (B/T) ratio was less than 0.3, indicating that the ratio could be as the indicator for tracing the solvent use related sources. The results also suggested that the toluene/xylene (T/X) ratio be as the indicator to distinguish the VOCs sources of painting (<2) from the printing (>2). Aromatics contributed the most to ozone formation potential (OFP) of most painting and non-paper printing sources, and oxygen-containing VOCs (OVOCs) were major species contributing to OFP of the sources from food production and paper printing. The OFP of the VOCs emissions from vehicle in tunnels and from other manufactures were dominated by both aromatics and alkenes. The α-pinene could explain 56.94% and 32.54% of total OFP of the VOCs sources from filing cabinet and solid wood furniture manufacturing, which was rarely been involved in previous studies of VOCs source profiles, indicating that the species of concern for VOCs sources are still insufficient at present.
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Affiliation(s)
- Haimei Huang
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhangwei Wang
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Chunhao Dai
- Hunan Agricultural University, Changsha 430106, China
| | - Hai Wu
- National Institute of Metrology, Beijing 100029, China.
| | - Jia Guo
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Chunjie Wang
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoshan Zhang
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China
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Cao L, Men Q, Zhang Z, Yue H, Cui S, Huang X, Zhang Y, Wang J, Chen M, Li H. Significance of Volatile Organic Compounds to Secondary Pollution Formation and Health Risks Observed during a Summer Campaign in an Industrial Urban Area. Toxics 2024; 12:34. [PMID: 38250990 PMCID: PMC10820161 DOI: 10.3390/toxics12010034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 12/20/2023] [Accepted: 12/22/2023] [Indexed: 01/23/2024]
Abstract
The chemical complexity and toxicity of volatile organic compounds (VOCs) are primarily encountered through intensive anthropogenic emissions in suburban areas. Here, pollution characteristics, impacts on secondary pollution formation, and health risks were investigated through continuous in-field measurements from 1-30 June 2020 in suburban Nanjing, adjacent to national petrochemical industrial parks in China. On average, the total VOCs concentration was 34.47 ± 16.08 ppb, which was comprised mostly by alkanes (41.8%) and halogenated hydrocarbons (29.4%). In contrast, aromatics (17.4%) dominated the ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP) with 59.6% and 58.3%, respectively. Approximately 63.5% of VOCs were emitted from the petrochemical industry and from solvent usage based on source apportionment results, followed by biogenic emissions of 22.3% and vehicle emissions of 14.2%. Of the observed 46 VOC species, hexachlorobutadiene, dibromoethane, butadiene, tetrachloroethane, and vinyl chloride contributed as high as 98.8% of total carcinogenic risk, a large fraction of which was ascribed to the high-level emissions during ozone pollution episodes and nighttime. Therefore, the mitigation of VOC emissions from petrochemical industries would be an effective way to reduce secondary pollution and potential health risks in conurbation areas.
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Affiliation(s)
- Li Cao
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Qihui Men
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Zihao Zhang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Hao Yue
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Shijie Cui
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Xiangpeng Huang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Yunjiang Zhang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Junfeng Wang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Mindong Chen
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Haiwei Li
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, 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. Sci Total Environ 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] [What about the content of this article? (0)] [Affiliation(s)] [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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Yan M, Zhu H, Luo H, Zhang T, Sun H, Kannan K. Daily Exposure to Environmental Volatile Organic Compounds Triggers Oxidative Damage: Evidence from a Large-Scale Survey in China. Environ Sci Technol 2023; 57:20501-20509. [PMID: 38033144 DOI: 10.1021/acs.est.3c06055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/02/2023]
Abstract
Volatile organic compounds (VOCs) are ubiquitous environmental pollutants and have been implicated in adverse health outcomes. In this study, concentrations of 11 VOC metabolites (mVOCs) and three oxidative stress biomarkers (8-oxo-7,8-dihydro-2'-deoxyguanosine, 8-oxo-7,8-dihydro-guanosine, and dityrosine) were determined in 205 urine samples collected from 12 cities across mainland China. Urinary ∑11mVOC concentrations ranged from 498 to 1660 ng/mL, with a geometric mean (GM) value of 1070 ng/mL. The factorial analysis revealed that cooking, solvents, and vehicle emissions were the three primary sources of VOC exposure. A significant regional variation was clearly found in ∑11mVOC concentrations across four regions in China, with high urine VOC concentrations found in North and South China (GM: 1450 and 1340 ng/mL). The multiple linear regression model revealed that most mVOCs were significantly positively correlated with three oxidative stress markers (β range: 0.06-0.22). Mixture effect regression showed that isoprene, crotonaldehyde, acrolein, and benzene were the strongest contributors to oxidative stress. Approximately 80% of the participants have HQ values greater than 1.0 for 1,3-butadiene and benzene, suggesting that their exposure doses were close to potential adverse health effects. Our findings provide comprehensive information on human exposure and potential health risks of VOCs in China.
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Affiliation(s)
- Mengqi Yan
- MOE Key Laboratory of Pollution Processes and Environmental Criteria, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Hongkai Zhu
- MOE Key Laboratory of Pollution Processes and Environmental Criteria, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Haining Luo
- Center for Reproductive Medicine, Tianjin Central Hospital of Gynecology Obstetrics, Tianjin 300100, China
| | - Tao Zhang
- School of Environmental Science and Engineering, Sun Yat-Sen University, Guangzhou 510275, China
| | - Hongwen Sun
- MOE Key Laboratory of Pollution Processes and Environmental Criteria, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Kurunthachalam Kannan
- Wadsworth Center, New York State Department of Health, Albany, New York 12237, United States
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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. Environ Sci Pollut Res Int 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] [What about the content of this article? (0)] [Affiliation(s)] [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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10
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Ni J, Liu SS, Lang XP, He Z, Yang GP. Sulfur hexafluoride in the marine atmosphere and surface seawater of the Western Pacific and Eastern Indian Ocean. Environ Pollut 2023; 335:122266. [PMID: 37499965 DOI: 10.1016/j.envpol.2023.122266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 07/29/2023]
Abstract
Sulfur hexafluoride (SF6) is a powerful greenhouse gas with a high global warming potential. While SF6 emissions from urban areas have been extensively studied, our knowledge about SF6 concentrations in the oceanic atmosphere and its air-sea exchange remains limited. Herein, the concentrations of SF6 in the atmosphere and surface seawater of the WPO (Western Pacific Ocean) and EIO (Eastern Indian Ocean) were comprehensively characterized from 2019 to 2022 in the first long-term study. The mean mixing ratios of SF6 over the WPO and EIO during 2019-2020 (2021-2022) were 10.9 (11.2) and 10.9 (11.1) ppt, respectively. The atmospheric SF6 concentration over the WPO and EIO increased at rates of 0.40 ± 0.06 and 0.58 ± 0.28 ppt yr-1, respectively, surpassing previously reported annual growth rates. The faster growth was primarily attributed to the influence of polluted air masses originating from eastern Asian countries, particularly Japan, Northeast China, and India. This might explain why the radiative forcing caused by SF6 in the study region was higher than the global average. The concentrations of SF6 in the surface seawater of the WPO and EIO ranged from 0.33 to 2.54 fmol kg-1, and the distribution was affected by atmospheric concentrations and ocean currents. Estimated air-sea fluxes revealed that the ocean acted as a significant sink of atmospheric SF6, and the preliminary estimation suggested oceanic uptake accounts for about 7% of annual global SF6 emissions. Based on these findings, we tentatively suggest that the strength of the ocean as a sink of SF6 may warrant reassessment. The global oceanic uptake of SF6 has the potential to reduce its global abundance and environmental impacts.
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Affiliation(s)
- Jie Ni
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, And Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, And College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao, 266100, China
| | - Shan-Shan Liu
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, And Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, And College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao, 266100, China
| | - Xiao-Ping Lang
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, And Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, And College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao, 266100, China
| | - Zhen He
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, And Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, And College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao, 266100, China; Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China.
| | - Gui-Peng Yang
- Frontiers Science Center for Deep Ocean Multispheres and Earth System, And Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, And College of Chemistry and Chemical Engineering, Ocean University of China, Qingdao, 266100, China; Laboratory for Marine Ecology and Environmental Science, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266237, China; Institute of Marine Chemistry, Ocean University of China, Qingdao, 266100, China
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11
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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. Environ Pollut 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] [What about the content of this article? (0)] [Affiliation(s)] [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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12
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Jang E, Choi S, Yoo E, Hyun S, An J. Impact of shipping emissions regulation on urban aerosol composition changes revealed by receptor and numerical modelling. NPJ Clim Atmos Sci 2023; 6:52. [PMID: 37274460 PMCID: PMC10226717 DOI: 10.1038/s41612-023-00364-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 05/03/2023] [Indexed: 06/06/2023]
Abstract
Various shipping emissions controls have recently been implemented at both local and national scales. However, it is difficult to track the effect of these on PM2.5 levels, owing to the non-linear relationship that exists between changes in precursor emissions and PM components. Positive Matrix Factorisation (PMF) identifies that a switch to cleaner fuels since January 2020 results in considerable reductions in shipping-source-related PM2.5, especially sulphate aerosols and metals (V and Ni), not only at a port site but also at an urban background site. CMAQ sensitivity analysis reveals that the reduction of secondary inorganic aerosols (SIA) further extends to inland areas downwind from ports. In addition, mitigation of secondary organic aerosols (SOA) in coastal urban areas can be anticipated either from the results of receptor modelling or from CMAQ simulations. The results in this study show the possibility of obtaining human health benefits in coastal cities through shipping emission controls.
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Affiliation(s)
- Eunhwa Jang
- Busan Metropolitan City Institute of Health and Environment, 120, Hambakbong-ro, 140beon-gil, Buk-gu, Busan, 46616 Republic of Korea
| | - Seongwoo Choi
- Busan Metropolitan City Institute of Health and Environment, 120, Hambakbong-ro, 140beon-gil, Buk-gu, Busan, 46616 Republic of Korea
| | - Eunchul Yoo
- Busan Metropolitan City Institute of Health and Environment, 120, Hambakbong-ro, 140beon-gil, Buk-gu, Busan, 46616 Republic of Korea
| | - Sangmin Hyun
- Marine Environmental Research Center, Korea Institute of Ocean Science and Technology, 385, Haeyang-ro, Yeongdo-gu, Busan, 49111 Republic of Korea
| | - Joongeon An
- Risk Assessment Research Center, Korea Institute of Ocean Science and Technology, Geoje, 53201 Republic of Korea
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13
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Dai S, Chen X, Liang J, Li X, Li S, Chen G, Chen Z, Bin J, Tang Y, Li X. Response of PM2.5 pollution to meteorological and anthropogenic emissions changes during COVID-19 lockdown in Hunan Province based on WRF-Chem model. Environ Pollut 2023:121886. [PMID: 37236582 DOI: 10.1016/j.envpol.2023.121886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 05/11/2023] [Accepted: 05/23/2023] [Indexed: 05/28/2023]
Abstract
In December 2019, the New Crown Pneumonia (the COVID-19) outbroke around the globe, and China imposed a nationwide lockdown starting as early as January 23, 2020. This decision has significantly impacted China's air quality, especially the sharp decrease in PM2.5 (aerodynamic equivalent diameter of particulate matter less than or equal to 2.5 μm) pollution. Hunan Province is located in the central and eastern part of China, with a "horseshoe basin" topography. The reduction rate of PM2.5 concentrations in Hunan province during the COVID-19 (24.8%) was significantly higher than the national average (20.3%). Through the analysis of the changing character and pollution sources of haze pollution events in Hunan Province, more scientific countermeasures can be provided for the government. We use the Weather Research and Forecasting with Chemistry (WRF-Chem, V4.0) model to predict and simulate the PM2.5 concentrations under seven scenarios before the lockdown (2020.1.1-2020.1.22) and during the lockdown (2020.1.23-2020.2.14). Then, the PM2.5 concentrations under different conditions is compared to differentiate the contribution of meteorological conditions and local human activities to PM2.5 pollution. The results indicate the most important cause of PM2.5 pollution reduction is anthropogenic emissions from the residential sector, followed by the industrial sector, while the influence of meteorological factors contribute only 0.5% to PM2.5. The explanation is that emission reductions from the residential sector contribute the most to the reduction of seven primary contaminants. Finally, we trace the source and transport path of the air mass in Hunan Province through the Concentration Weight Trajectory Analysis (CWT). We found that the external input of PM2.5 in Hunan Province is mainly from the air mass transported from the northeast, accounting for 28.6%-30.0%. To improve future air quality, there is an urgent need to burn clean energy, improve the industrial structure, rationalize energy use, and strengthen cross-regional air pollution synergy control.
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Affiliation(s)
- Simin Dai
- College of Environmental Science and Engineering, Hunan University, Changsha, 410082, PR China
| | - Xuwu Chen
- School of Advanced Interdisciplinary Studies, Hunan University of Technology and Business, Changsha, 410205, PR China
| | - Jie Liang
- College of Environmental Science and Engineering, Hunan University, Changsha, 410082, PR China
| | - Xin Li
- College of Environmental Science and Engineering, Hunan University, Changsha, 410082, PR China
| | - Shuai Li
- College of Environmental Science and Engineering, Hunan University, Changsha, 410082, PR China
| | - Gaojie Chen
- College of Mathematics and Econometrics, Hunan University, Changsha, 410082, PR China
| | - Zuo Chen
- College of Information Science and Technology, Hunan University, Changsha, 410082, PR China
| | - Juan Bin
- College of Environmental Science and Engineering, Hunan University, Changsha, 410082, PR China
| | - Yifan Tang
- College of Environmental Science and Engineering, Hunan University, Changsha, 410082, PR China
| | - Xiaodong Li
- College of Environmental Science and Engineering, Hunan University, Changsha, 410082, PR China.
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14
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Zeng X, Han M, Ren G, Liu G, Wang X, Du K, Zhang X, Lin H. A comprehensive investigation on source apportionment and multi-directional regional transport of volatile organic compounds and ozone in urban Zhengzhou. Chemosphere 2023; 334:139001. [PMID: 37220798 DOI: 10.1016/j.chemosphere.2023.139001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 04/18/2023] [Accepted: 05/20/2023] [Indexed: 05/25/2023]
Abstract
To understand the characteristics, source apportionment, and regional transport of volatile organic compounds (VOCs) and ozone (O3) in a typical city with severe air pollution in central China, we observed and analyzed 115 VOC species at an urban site in Zhengzhou from 29 July to 26 September 2021. During this period, observation- and emission-based approaches revealed that Zhengzhou was in a VOC-limited regime. The average concentration of total VOCs (TVOCs) was 162.25 ± 71.42 μg/m3, dominated by oxygenated VOCs (OVOCs, 34.49%), alkanes (24.29%), and aromatics (19.49%). Six VOC sources were identified using positive matrix factorization (PMF) model, including paint solvent usage (25.32%), secondary production (24.11%), industrial production (19.22%), vehicle exhaust (16.18%), biogenic emission (8.87%), and combustion (6.30%). To assess the regional contribution and source apportionment of VOCs and O3, Comprehensive Air Quality Model with Extensions (CAMx) with the Ozone Source Apportionment Technology (OSAT) was used for simulation. Results showed that the VOCs were significantly affected by local emissions (about 70%), while O3 was mainly attributed to regional and super-regional transport. Regarding multi-directional regional transport of VOCs and O3, dominant contributions were from the northeast and east-northeast directions, and O3 contributions were also predominantly from the east and east-southeast directions. In terms of source apportionment, the transportation and industrial sectors (including solvent usage) were the major contributors to O3 and VOCs. To alleviate VOCs and O3 pollution, transportation and industrial emission reduction should be strengthened, and regional coordination, especially from the northeast to east-southeast directions, should be emphasized in addition to local management.
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Affiliation(s)
- Xiaoxi Zeng
- Division of Thermophysics Metrology, National Institute of Metrology, Beijing, 100029, China; Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
| | - Mengjuan Han
- Division of Thermophysics Metrology, National Institute of Metrology, Beijing, 100029, China; Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
| | - Ge Ren
- Division of Thermophysics Metrology, National Institute of Metrology, Beijing, 100029, China; Zhengzhou Institute of Metrology, Zhengzhou, 450001, China.
| | - Gege Liu
- Division of Thermophysics Metrology, National Institute of Metrology, Beijing, 100029, China; Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
| | - Xiaoning Wang
- Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
| | - Kailun Du
- Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
| | - Xiaodong Zhang
- Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
| | - Hong Lin
- Division of Thermophysics Metrology, National Institute of Metrology, Beijing, 100029, China; Zhengzhou Institute of Metrology, Zhengzhou, 450001, China
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Qin Z, Xu B, Zheng Z, Li L, Zhang G, Li S, Geng C, Bai Z, Yang W. Integrating ambient carbonyl compounds provides insight into the constrained ozone formation chemistry in Zibo city of the North China Plain. Environ Pollut 2023; 324:121294. [PMID: 36796669 DOI: 10.1016/j.envpol.2023.121294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 01/25/2023] [Accepted: 02/13/2023] [Indexed: 06/18/2023]
Abstract
Quantifying the impact of carbonyl compounds (carbonyls) on ozone (O3) photochemical formation is crucial to formulating targeted O3 mitigation strategies. To investigate the emission source of ambient carbonyls and their integrated observational constraint on the impact of O3 formation chemistry, a field campaign was conducted in an industrial city (Zibo) of the North China Plain from August to September 2020. The site-to-site variations of OH reactivity for carbonyls were in accordance with the sequence of Beijiao (BJ, urban, 4.4 s-1) > Xindian (XD, suburban, 4.2 s-1) > Tianzhen (TZ, suburban, 1.6 s-1). A 0-D box model (MCMv3.3.1) was applied to assess the O3-precursor relationship influenced by measured carbonyls. It was found that without carbonyls constraint, the O3 photochemical production of the three sites was underestimated to varying degrees, and the biases of overestimating the VOC-limited degree were also identified through a sensitivity test to NOx emission changes, which may be associated with the reactivity of carbonyls. In addition, the results of the positive matrix factorization (PMF) model indicated that the main source of aldehydes and ketones was secondary formation and background (81.6% for aldehydes, 76.8% for ketones), followed by traffic emission (11.0% for aldehydes, 14.0% for ketones). Incorporated with the box model, we found that biogenic emission contributed the most to the O3 production at the three sites, followed by traffic emission as well as industry and solvent usage. Meanwhile, the relative incremental reactivity (RIR) values of O3 precursor groups from diverse VOC emission sources featured consistencies and differences at the three sites, which further highlights the importance of the synergetic mitigation of target O3 precursors at regional and local scales. This study will help to provide targeted policy-guiding O3 control strategies for other regions.
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Affiliation(s)
- Ze Qin
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Bo Xu
- Shandong Zibo Eco-Environmental Monitoring Center, Zibo, 255040, China
| | - Zhensen Zheng
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Liming Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Guotao Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Shijie Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Chunmei Geng
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Zhipeng Bai
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Wen Yang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
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Wang S, Li Q, Duan K, Wang B, Zhu X, Wang X, Shen Y, Liu H, Ma Y. Profile of atmospheric VOC over the Yellow Sea, China: A tale of distribution, constraints, and sources. Sci Total Environ 2023; 868:161634. [PMID: 36669669 DOI: 10.1016/j.scitotenv.2023.161634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 01/09/2023] [Accepted: 01/12/2023] [Indexed: 06/17/2023]
Abstract
In the winter of 2018-2019, 75 air samples were collected through four ship-borne measurements in the Yellow Sea (YS) to assess the levels, confinement processes, and source distribution of volatile organic compounds (VOCs). A total of 41 were eventually detected, which mainly were non-methane hydrocarbons (NMHCs), volatile halogenated hydrocarbons (VHCs), oxygenated volatile organic compounds (OVOCs), and volatile organic sulfur compounds (VSCs). Aromatics (31.93 %) and alkenes (11.04 %) in the atmosphere of the YS accounted for a larger proportion of NMHCs compared with the coastal areas. C3-C5 alkanes, propylene, and chloroform exhibited strong latitudinal gradients and opposite latitudinal distributions in the North and South YS, highlighting the strong contribution of regional outflow to YS's atmosphere. The level of Σ41VOCs increased significantly during the heavy pollution period with some chemical monomers detected, which was further enhanced by the emissions from industrial parks near the Liaodong Peninsula and the Shandong Peninsula. Five main VOC sources were identified by the Positive matrix factorization (PMF) model, which were industrial emissions (13.33 %), fuel use and volatilization (6.67 %), Freon R-22 emissions (33.33 %), oil and gas production (20.00 %), and solvent volatilization (26.67 %). These observations revealed the strong causal relationship between coastal air mass transport and the atmosphere in the marginal sea and emphasized that full attention should be paid to the unintentional and unorganized emission of chemical monomers in the industrial process.
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Affiliation(s)
- Shuang Wang
- Green Shipping and Carbon Neutrality Laboratory, College of Environmental Science and Engineering, Dalian Maritime University, 116026, No. 1 Linghai Road, Dalian, Liaoning Province, China
| | - Qingbo Li
- Green Shipping and Carbon Neutrality Laboratory, College of Environmental Science and Engineering, Dalian Maritime University, 116026, No. 1 Linghai Road, Dalian, Liaoning Province, China.
| | - Kuiquan Duan
- Green Shipping and Carbon Neutrality Laboratory, College of Environmental Science and Engineering, Dalian Maritime University, 116026, No. 1 Linghai Road, Dalian, Liaoning Province, China
| | - Baopeng Wang
- Green Shipping and Carbon Neutrality Laboratory, College of Environmental Science and Engineering, Dalian Maritime University, 116026, No. 1 Linghai Road, Dalian, Liaoning Province, China
| | - Xinyu Zhu
- Dalian Eco-environmental Affairs Service Center, 116026, No. 58 Lianshan Street, Shahekou District, Dalian, China
| | - Xuanya Wang
- China Academy of Transportation Science, 10029, No. 240, Huixinli, Chaoyang District, Beijing, China
| | - Yuxin Shen
- Green Shipping and Carbon Neutrality Laboratory, College of Environmental Science and Engineering, Dalian Maritime University, 116026, No. 1 Linghai Road, Dalian, Liaoning Province, China
| | - Hui Liu
- Green Shipping and Carbon Neutrality Laboratory, College of Environmental Science and Engineering, Dalian Maritime University, 116026, No. 1 Linghai Road, Dalian, Liaoning Province, China
| | - Ye Ma
- Green Shipping and Carbon Neutrality Laboratory, College of Environmental Science and Engineering, Dalian Maritime University, 116026, No. 1 Linghai Road, Dalian, Liaoning Province, China
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Wang Y, Song H, Li L, Ma J, Yu F. Generation characteristics and spreading risk of VOCs released from a biological fermentation pharmaceutical factory. Environ Sci Process Impacts 2023; 25:507-518. [PMID: 36606575 DOI: 10.1039/d2em00378c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Pharmaceutical factories produce a large amount of volatile organic compounds (VOCs), which may pose a potential health threat to the environment, workers, and nearby residents. Sampling points were set up in the tylosin biological fermentation workshop (FW) and sewage treatment station (STS) of a pharmaceutical factory in a central city in northern China to collect VOCs and study their generation characteristics and diffusion. The results indicated that with the increase in fermentation time, VOC production decreased gradually, and the decline was rapid. The main VOCs produced by the FW are oxygen-containing organics and nitrogen-containing organics including 1-heptyladehyde (8.86 × 102 mg m-3), 1-methyl-2-pyrrolidone (6.36 × 102 mg m-3) and benzene (5.85 × 102 mg m-3). The STS mainly produces nitrogen-containing organics and oxygen-containing organics including 1-methyl-2-pyrrolidone (3.38 × 103 mg m-3), diethyl amine (9.60 × 102 mg m-3) and methyl ethyl ketone (2.98 × 102 mg m-3). VOCs produced by biopharmaceutical factories can diffuse for a long distance in the atmosphere. The highest concentration of chlorinated organic compounds can spread to 11.43 kilometers in the horizontal direction and 3 kilometers in the vertical direction. Acetaldehyde, butyraldehyde, diethylamine, butyl acetate and methyl ethyl ketone are odorous gases detected in the FW and STS, respectively. Benzene, carbon tetrachloride and acetaldehyde are the main carcinogenic VOCs produced in the fermentation process of tylosin. The research elucidated production characteristics, diffusion and health risks of VOCs in the FW, which provided a reference for the control of VOCs.
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Affiliation(s)
- Yanjie Wang
- College of Public Health, Zhengzhou University, Zhengzhou, 450000, P. R. China
- State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, P. R China
| | - Huiling Song
- College of Public Health, Zhengzhou University, Zhengzhou, 450000, P. R. China
- Department of Medical, Xi'an Gem Flower Changqing Hospitals, Xi'an, 710000, P. R. China
| | - Lin Li
- State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, P. R China
| | - Jiawei Ma
- State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, P. R China
| | - Fangfang Yu
- College of Public Health, Zhengzhou University, Zhengzhou, 450000, P. R. China
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Yao W, Zhao Y, Chen R, Wang M, Song W, Yu D. Emissions of Toxic Substances from Biomass Burning: A Review of Methods and Technical Influencing Factors. Processes (Basel) 2023; 11:853. [DOI: 10.3390/pr11030853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/16/2023] Open
Abstract
In the perspective of energy sustainability, biomass is the widely used renewable domestic energy with low cost and easy availability. Increasing studies have reported the health impacts of toxic substances from biomass burning emissions. To make proper use of biomass as residential solid energy, the evaluation of its health risks and environmental impacts is of necessity. Empirical studies on the characteristics of toxic emissions from biomass burning would provide scientific data and drive the development of advanced technologies. This review focuses on the emission of four toxic substances, including heavy metals, polycyclic aromatic hydrocarbons (PAHs), elemental carbon (EC), and volatile organic compounds (VOCs) emitted from biomass burning, which have received increasing attention in recent studies worldwide. We focus on the developments in empirical studies, methods of measurements, and technical factors. The influences of key technical factors on biomass burning emissions are combustion technology and the type of biomass. The methods of sampling and testing are summarized and associated with various corresponding parameters, as there are no standard sampling methods for the biomass burning sector. Integration of the findings from previous studies indicated that modern combustion technologies result in a 2–4 times reduction, compared with traditional stoves. Types of biomass burning are dominant contributors to certain toxic substances, which may help with the invention or implementation of targeted control technologies. The implications of previous studies would provide scientific evidence to push the improvements of control technologies and establish appropriate strategies to improve the prevention of health hazards.
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Cui X, Peng L, Guo Y, Zhang G, Liu H, Wen Y, Zhang G, Sun J. Distribution, source identification and ecological effects of aerosol dissolved nutrients in the Bohai Bay. Environ Pollut 2023; 320:121069. [PMID: 36639046 DOI: 10.1016/j.envpol.2023.121069] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/17/2022] [Revised: 12/27/2022] [Accepted: 01/10/2023] [Indexed: 06/17/2023]
Abstract
The atmospheric aerosols around the Bohai Bay are affected intensively by the surrounding industrial, shipping and other human activities. Although atmospheric dry deposition is an important way for nutrients to enter the Bohai Bay, few studies explore the distribution patterns, source and deposition fluxes of typical nutrients in aerosols and their impacts on the marine ecosystem. This paper explored the spatial-temporal distribution of typical aerosol nutrients in summer and autumn, and their source and ecological effects were illustrated further. The mean concentration of dissolved total phosphorus (DTP), dissolved total nitrogen (DTN), dissolved organic nitrogen (DON), dissolved inorganic nitrogen (DIN), ammonium (NH4-N), nitrate (NO3-N), nitrite (NO2-N), silicate (SiO3-Si), phosphate (PO4-P), and dissolved organic phosphorus (DOP) were 31.22, 847.22, 288.19, 559.77, 288.19, 304.00, 253.65, 2.12, 15.74 and 15.48 nmol/m3, respectively, while their fluxes were corresponding to 0.61, 8.36, 2.52, 4.90, 1.41, 2.49, 0.02, 0.04, 0.19 and 0.26 mmol/(m2 month). Typical aerosol nutrient concentrations in autumn were mostly higher than those in summer, with high values occurring mainly in the central region. The potential sources of pollution were mainly concentrated in Shandong and Mongolia, and the sources of pollution were mainly agriculture, dust and industry. The large N:P and N:Si ratios in the dry deposition likely exacerbated Si and P limitation in the water column. These results provided the data basis for evaluating the pollution status and revealed that the dry deposition of aerosol nutrients should not be neglected by the ecological environment in the Bohai Bay.
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Affiliation(s)
- Xudong Cui
- Research Centre for Indian Ocean Ecosystem, Tianjin University of Science and Technology, Tianjin, 300457, China
| | - Liying Peng
- Research Centre for Indian Ocean Ecosystem, Tianjin University of Science and Technology, Tianjin, 300457, China
| | - Yu Guo
- Research Centre for Indian Ocean Ecosystem, Tianjin University of Science and Technology, Tianjin, 300457, China
| | - Guicheng Zhang
- Research Centre for Indian Ocean Ecosystem, Tianjin University of Science and Technology, Tianjin, 300457, China
| | - Haijiao Liu
- Research Centre for Indian Ocean Ecosystem, Tianjin University of Science and Technology, Tianjin, 300457, China
| | - Yujian Wen
- Research Centre for Indian Ocean Ecosystem, Tianjin University of Science and Technology, Tianjin, 300457, China
| | - Guodong Zhang
- Research Centre for Indian Ocean Ecosystem, Tianjin University of Science and Technology, Tianjin, 300457, China
| | - Jun Sun
- Research Centre for Indian Ocean Ecosystem, Tianjin University of Science and Technology, Tianjin, 300457, China; Institute for Advanced Marine Research, China University of Geosciences, Guangzhou, 511462, China; State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences (Wuhan), Wuhan, 430074, China.
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Yao Y, Ma K, He C, Zhang Y, Lin Y, Fang F, Li S, He H. Urban Surface Ozone Concentration in Mainland China during 2015-2020: Spatial Clustering and Temporal Dynamics. Int J Environ Res Public Health 2023; 20:3810. [PMID: 36900822 PMCID: PMC10001023 DOI: 10.3390/ijerph20053810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 02/15/2023] [Accepted: 02/17/2023] [Indexed: 06/18/2023]
Abstract
Urban ozone (O3) pollution in the atmosphere has become increasingly prominent on a national scale in mainland China, although the atmospheric particulate matter pollution has been significantly reduced in recent years. The clustering and dynamic variation characteristics of the O3 concentrations in cities across the country, however, have not been accurately explored at relevant spatiotemporal scales. In this study, a standard deviational ellipse analysis and multiscale geographically weighted regression models were applied to explore the migration process and influencing factors of O3 pollution based on measured data from urban monitoring sites in mainland China. The results suggested that the urban O3 concentration in mainland China reached its peak in 2018, and the annual O3 concentration reached 157 ± 27 μg/m3 from 2015 to 2020. On the scale of the whole Chinese mainland, the distribution of O3 exhibited spatial dependence and aggregation. On the regional scale, the areas of high O3 concentrations were mainly concentrated in Beijing-Tianjin-Hebei, Shandong, Jiangsu, Henan, and other regions. In addition, the standard deviation ellipse of the urban O3 concentration covered the entire eastern part of mainland China. Overall, the geographic center of ozone pollution has a tendency to move to the south with the time variation. The interaction between sunshine hours and other factors (precipitation, NO2, DEM, SO2, PM2.5) significantly affected the variation of urban O3 concentration. In Southwest China, Northwest China, and Central China, the suppression effect of vegetation on local O3 was more obvious than that in other regions. Therefore, this study clarified for the first time the migration path of the gravity center of the urban O3 pollution and identified the key areas for the prevention and control of O3 pollution in mainland China.
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Affiliation(s)
- Youru Yao
- Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China
| | - Kang Ma
- Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China
| | - Cheng He
- Helmholtz Zentrum München–German Research Center for Environmental Health (GmbH), Institute of Epidemiology, 85764 Neuherberg, Germany
| | - Yong Zhang
- Department of Geological Sciences, University of Alabama, Tuscaloosa, AL 35487, USA
| | - Yuesheng Lin
- Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China
| | - Fengman Fang
- Key Laboratory of Earth Surface Processes and Regional Response in the Yangtze-Huaihe River Basin, School of Geography and Tourism, Anhui Normal University, Wuhu 241002, China
| | - Shiyin Li
- School of Environment, Nanjing Normal University, Nanjing 210023, China
| | - Huan He
- School of Environment, Nanjing Normal University, Nanjing 210023, China
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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. Environ Int 2023; 172:107766. [PMID: 36706584 DOI: 10.1016/j.envint.2023.107766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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22
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Peng Y, Wang H, Wang Q, Jing S, An J, Gao Y, Huang C, Yan R, Dai H, Cheng T, Zhang Q, Li M, Hu J, Shi Z, Li L, Lou S, Tao S, Hu Q, Lu J, Chen C. Observation-based sources evolution of non-methane hydrocarbons (NMHCs) in a megacity of China. J Environ Sci (China) 2023; 124:794-805. [PMID: 36182184 DOI: 10.1016/j.jes.2022.01.040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 01/24/2022] [Accepted: 01/24/2022] [Indexed: 06/16/2023]
Abstract
Both concentrations and emissions of many air pollutants have been decreasing due to implement of control measures in China, in contrast to the fact that an increase in emissions of non-methane hydrocarbons (NMHCs) has been reported. This study employed seven years continuous NMHCs measurements and the related activities data of Shanghai, a megacity in China, to explore evolution of emissions and effectiveness of air pollution control measures. The mixing ratio of NMHCs showed no statistical interannual changes, of which their compositions exhibited marked changes. This resulted in a decreasing trend of ozone formation potential by 3.8%/year (p < 0.05, the same below), which should be beneficial to ozone pollution mitigation as its production in Shanghai is in the NMHCs-limited regime. Observed alkanes, aromatics and acetylene changed by +3.7%/year, -5.9%/year and -7.4%/year, respectively, and alkenes showed no apparent trend. NMHCs sources were apportioned by a positive matrix factorization model. Accordingly, vehicular emissions (-5.9%/year) and petrochemical industry emissions (-7.1%/year) decreased significantly, but the decrease slowed down; significant reduction in solvent usage (-9.0%/year) appeared after 2010; however, emissions of natural gas (+12.6%/year) and fuel evaporation (with an increasing fraction) became more important. The inconsistency between observations and inventories was found in interannual trend and speciation as well as source contributions, emphasizing the need for further validation in NMHCs emission inventory. Our study confirms the effectiveness of measures targeting mobile and centralized emissions from industrial sources and reveals a need focusing on fugitive emissions, which provided new insights into future air policies in polluted region.
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Affiliation(s)
- Yarong Peng
- Department of Environmental Science and Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China; State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Hongli Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China.
| | - Qian Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Shengao Jing
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Jingyu An
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Yaqin Gao
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China.
| | - Rusha Yan
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Haixia Dai
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Tiantao Cheng
- Department of Environmental Science and Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China; Department of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan University, Shanghai 200438, China; Big Data Institute for Carbon Emission and Environmental Pollution, Fudan University, Shanghai 200438, China.
| | - Qiang Zhang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Tsinghua University, Beijing 100084, China
| | - Meng Li
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Tsinghua University, Beijing 100084, China
| | - Jianlin Hu
- School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Zhihao Shi
- School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Li Li
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Shengrong Lou
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Shikang Tao
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Qinyao Hu
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Jun Lu
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Changhong Chen
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
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Liu C, Xin Y, Zhang C, Liu J, Liu P, He X, Mu Y. Ambient volatile organic compounds in urban and industrial regions in Beijing: Characteristics, source apportionment, secondary transformation and health risk assessment. Sci Total Environ 2023; 855:158873. [PMID: 36126704 DOI: 10.1016/j.scitotenv.2022.158873] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 09/09/2022] [Accepted: 09/15/2022] [Indexed: 06/15/2023]
Abstract
Field measurements of volatile organic compounds (VOCs) were conducted simultaneously at an urban site and one industrial park site in Beijing in summer. The VOCs concentrations were 94.3 ± 157.8 ppbv and 20.7 ± 8.9 ppbv for industrial and urban sites, respectively. Alkanes and aromatics were the major contributors to VOCs in industrial site, while oxygenated volatile organic compounds (OVOCs) contributed most in urban site. The most abundant VOC species were n-pentane and formaldehyde for industrial site and urban site, respectively. The calculated ozone formation potential (OFP) and OH loss rates (LOH) were 621.1 ± 1491.9 ppbv (industrial site), 102.9 ± 37.3 ppbv (urban site), 22.0 ± 39.0 s-1 (industrial site) and 5.3 ± 2.2 s-1 (urban site), respectively. Based on the positive matrix factorization (PMF) model, solvent utilization I (34.1 %), solvent utilization II (27.9 %), mixture combustion source (19.3 %), OVOCs related source (9.6 %) and biogenic source (9.1 %) were identified in the industrial site, while OVOCs related source (27.8 %), vehicle exhaust (22.1 %), solvent utilization (19.3 %), coal combustion (16.0 %) and biogenic source (14.8 %) were identified in the urban site. The results of O3-VOCs-NOx sensitivity indicated that O3 formation were respectively under the VOC-limited and NOx-limited conditions in Beijing urban and industrial regions. Additionally, aromatics accounted remarkable SOA formation ability both in the two sites, and SOA potentials of xylene, toluene and ethylbenzene as the indicator species for the solvent utilization in industrial site were remarkable higher than those obtained in urban regions. The hazard index values in the industrial and urban sites were 1.72 and 3.39, respectively, suggesting a high non-carcinogenic risks to the exposed population. Formaldehyde had the highest carcinogenic risks in the two sites, and the cumulative carcinogenic risks in the industrial site and urban site were 1.95 × 10-5 and 1.21 × 10-5, respectively.
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Affiliation(s)
- Chengtang Liu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100085, China
| | - Yanyan Xin
- College of Environmental Engineering, Beijing Forestry University, Beijing 100083, China
| | - Chenglong Zhang
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100085, China
| | - Junfeng Liu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100085, China
| | - Pengfei Liu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100085, China
| | - Xiaowei He
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100085, China
| | - Yujing Mu
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100085, China.
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Cao X, Xing Q, Hu S, Xu W, Xie R, Xian A, Xie W, Yang Z, Wu X. Characterization, reactivity, source apportionment, and potential source areas of ambient volatile organic compounds in a typical tropical city. J Environ Sci (China) 2023; 123:417-429. [PMID: 36522003 DOI: 10.1016/j.jes.2022.08.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Revised: 07/11/2022] [Accepted: 08/01/2022] [Indexed: 06/17/2023]
Abstract
Based on one-year observation, the concentration, sources, and potential source areas of volatile organic compounds (VOCs) were comprehensively analyzed to investigate the pollution characteristics of ambient VOCs in Haikou, China. The results showed that the annual average concentration of total VOCs (TVOCs) was 11.4 ppbV, and the composition was dominated by alkanes (8.2 ppbV, 71.4%) and alkenes (1.3 ppbV, 20.5%). The diurnal variation in the concentration of dominant VOC species showed a distinct bimodal distribution with peaks in the morning and evening. The greatest contribution to ozone formation potential (OFP) was made by alkenes (51.6%), followed by alkanes (27.2%). The concentrations of VOCs and nitrogen dioxide (NO2) in spring and summer were low, and it was difficult to generate high ozone (O3) concentrations through photochemical reactions. The significant increase in O3 concentrations in autumn and winter was mainly related to the transmission of pollutants from the northeast. Traffic sources (40.1%), industrial sources (19.4%), combustion sources (18.6%), solvent usage sources (15.5%) and plant sources (6.4%) were identified as major sources of VOCs through the positive matrix factorization (PMF) model. The southeastern coastal areas of China were identified as major potential source areas of VOCs through the potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models. Overall, the concentration of ambient VOCs in Haikou was strongly influenced by traffic sources and long-distance transport, and the control of VOCs emitted from vehicles should be strengthened to reduce the active species of ambient VOCs in Haikou, thereby reducing the generation of O3.
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Affiliation(s)
- Xiaocong Cao
- Hainan Research Academy of Environmental Sciences, Haikou 571126, China; National Pilot Zone for Ecological Conservation (Hainan) Research Center, Haikou 571126, China
| | - Qiao Xing
- Hainan Research Academy of Environmental Sciences, Haikou 571126, China; National Pilot Zone for Ecological Conservation (Hainan) Research Center, Haikou 571126, China
| | - Shanhu Hu
- Hainan Research Academy of Environmental Sciences, Haikou 571126, China; National Pilot Zone for Ecological Conservation (Hainan) Research Center, Haikou 571126, China
| | - Wenshuai Xu
- Hainan Research Academy of Environmental Sciences, Haikou 571126, China; National Pilot Zone for Ecological Conservation (Hainan) Research Center, Haikou 571126, China.
| | - Rongfu Xie
- Hainan Research Academy of Environmental Sciences, Haikou 571126, China; National Pilot Zone for Ecological Conservation (Hainan) Research Center, Haikou 571126, China
| | - Aidan Xian
- Hainan Research Academy of Environmental Sciences, Haikou 571126, China; National Pilot Zone for Ecological Conservation (Hainan) Research Center, Haikou 571126, China
| | - Wenjing Xie
- Hainan Research Academy of Environmental Sciences, Haikou 571126, China; National Pilot Zone for Ecological Conservation (Hainan) Research Center, Haikou 571126, China
| | - Zhaohui Yang
- Hainan Research Academy of Environmental Sciences, Haikou 571126, China; National Pilot Zone for Ecological Conservation (Hainan) Research Center, Haikou 571126, China
| | - Xiaochen Wu
- Hainan Research Academy of Environmental Sciences, Haikou 571126, China; National Pilot Zone for Ecological Conservation (Hainan) Research Center, Haikou 571126, China.
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Wang J, Yue H, Cui S, Zhang Y, Li H, Wang J, Ge X. Chemical Characteristics and Source-Specific Health Risks of the Volatile Organic Compounds in Urban Nanjing, China. Toxics 2022; 10:722. [PMID: 36548555 PMCID: PMC9783090 DOI: 10.3390/toxics10120722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 11/16/2022] [Accepted: 11/22/2022] [Indexed: 06/17/2023]
Abstract
This work comprehensively investigated the constituents, sources, and associated health risks of ambient volatile organic compounds (VOCs) sampled during the autumn of 2020 in urban Nanjing, a megacity in the densely populated Yangtze River Delta region in China. The total VOC (TVOC, sum of 108 species) concentration was determined to be 29.04 ± 14.89 ppb, and it was consisted of alkanes (36.9%), oxygenated VOCs (19.9%), halogens (19.1%), aromatics (9.9%), alkenes (8.9%), alkynes (4.9%), and others (0.4%). The mean TVOC/NOx (ppbC/ppbv) ratio was only 3.32, indicating the ozone control is overall VOC-limited. In terms of the ozone formation potential (OFP), however, the largest contributor became aromatics (41.9%), followed by alkenes (27.6%), and alkanes (16.9%); aromatics were also the dominant species in secondary organic aerosol (SOA) formation, indicative of the critical importance of aromatics reduction to the coordinated control of ozone and fine particulate matter (PM2.5). Mass ratios of ethylbenzene/xylene (E/X), isopentane/n--pentane (I/N), and toluene/benzene (T/B) ratios all pointed to the significant influence of traffic on VOCs. Positive matrix factorization (PMF) revealed five sources showing that traffic was the largest contributor (29.2%), particularly in the morning. A biogenic source, however, became the most important source in the afternoon (31.3%). The calculated noncarcinogenic risk (NCR) and lifetime carcinogenic risk (LCR) of the VOCs were low, but four species, acrolein, benzene, 1,2-dichloroethane, and 1,2-dibromoethane, were found to possess risks exceeding the thresholds. Furthermore, we conducted a multilinear regression to apportion the health risks to the PMF-resolved sources. Results show that the biogenic source instead of traffic became the most prominent contributor to the TVOC NCR and its contribution in the afternoon even outpaced the sum of all other sources. In summary, our analysis reveals the priority of controls of aromatics and traffic/industrial emissions to the efficient coreduction of O3 and PM2.5; our analysis also underscores that biogenic emissions should be paid special attention if considering the direct health risks of VOCs.
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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. Environ Sci Process Impacts 2022; 24:1968-1981. [PMID: 36000414 DOI: 10.1039/d2em00175f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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Hsu CY, Chang YT, Lin CJ. How a winding-down oil refinery park impacts air quality nearby? Environ Int 2022; 169:107533. [PMID: 36150296 DOI: 10.1016/j.envint.2022.107533] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 09/12/2022] [Accepted: 09/16/2022] [Indexed: 06/16/2023]
Abstract
It is always difficult to compare, let alone estimate, the difference of air pollutant concentrations before and after closure of a major source because the pollutants cannot be traced or predicted after entering the ambient. Indeed, we are not aware of any studies specifically related to the air pollutants impacted by a winding-down source. In this work, we applied nine years (2010-2018) online measurement of air pollutants (including PM10, PM2.5, NO2, SO2, O3 and VOCs) to investigate (i) the temporal behavior of air pollutants before and after closure of an oil refinery park by using pair-wise statistics and correlations between wind speed and direction, and (ii) the source impacts on O3 concentrations using PMF coupled with multiple linear regression (MLR) analysis (PMF-MLR). Example applications are presented at two monitoring sites (A and B) close to the Kaohsiung Oil Refinery (KOR), located in the southern industrial city of Taiwan. The results show that the KOR shutdown changed air pollutant concentrations to a certain extent in these study areas. We also conclude that, instead of using propylene-equivalent and ozone formation potential (OFP) concentrations, it is better to estimate the formation of O3 based on PMF-MLR analysis as developed in this study. The PMF analysis has identified various VOCs sources at both sites including solvent usage, petrochemical industrial sources, industrial emissions, vehicle-related sources, vegetation emissions and aged air-masses. Also, the MLR model shows that both the background sources and petrochemical industrial sources may significantly change O3 concentrations.
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Affiliation(s)
- Chin-Yu Hsu
- Department of Safety, Health and Environmental Engineering, Ming Chi University of Technology, 84 Gungjuan Rd., Taishan Dist, New Taipei City 24301, Taiwan; Center for Environmental Sustainability and Human Health, Ming Chi University of Technology, 84 Gungjuan Rd., Taishan Dist, New Taipei City 24301, Taiwan.
| | - Yu-Tzu Chang
- Department of Safety, Health and Environmental Engineering, Ming Chi University of Technology, 84 Gungjuan Rd., Taishan Dist, New Taipei City 24301, Taiwan
| | - Cheng-Ju Lin
- Department of Safety, Health and Environmental Engineering, Ming Chi University of Technology, 84 Gungjuan Rd., Taishan Dist, New Taipei City 24301, Taiwan
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Shi Y, Liu C, Zhang B, Simayi M, Xi Z, Ren J, Xie S. Accurate identification of key VOCs sources contributing to O 3 formation along the Liaodong Bay based on emission inventories and ambient observations. Sci Total Environ 2022; 844:156998. [PMID: 35787908 DOI: 10.1016/j.scitotenv.2022.156998] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 06/20/2022] [Accepted: 06/23/2022] [Indexed: 06/15/2023]
Abstract
In order to achieve the precise control of the volatile organic compounds (VOCs) species with high ozone (O3) formation contribution from key sources in Panjin and Yingkou, two coastal industrial cities with severe O3 pollution along the Liaodong Bay, northeast China, the ambient concentrations of 99 VOCs species were measured online at urban-petrochemical (XLT), suburban-industrial (PP), and rural (XRD) sites in July 2019, contemporary monthly anthropogenic VOCs emission inventories were developed. The source contribution of ambient VOCs resolved by positive matrix factorization (PMF) model was comparable with emission inventories, and the location of VOCs sources were speculated by potential source contribution function (PSCF). 17.5 Gg anthropogenic VOCs was emitted in Panjin and Yingkou in July 2019 with potential to form 54.7 Gg-O3 estimated by emission inventories. The average VOC mixing ratios of 47.1, 26.7, and 16.5 ppbv was observed at XLT, PP, and XRD sites, respectively. Petroleum industry (22 %), organic chemical industry (21 %), and mobile vehicle emission (19 %) were identified to be the main sources contributing to O3 formation at XLT site by PMF, while it is organic chemical industry (33 %) and solvent utilization (28 %) contributed the most at PP site. Taking the subdivided source contributions of emission inventories and source locations speculated by PSCF into full consideration, organic raw chemicals manufacturing, structural steel coating, petroleum refining process, petroleum products storage and transport, off-shore vessels, and passenger cars were identified as the key anthropogenic sources. High O3-formation contribution sources, organic chemical industry and solvent utilization were located in the industrial parks at the junction of the two cities and the southeast of Panjin, and petroleum industry distributed in the whole Panjin and offshore areas. These results identify the key VOCs species and sources and speculate the potential geographical location of sources for precisely controlling ground-level O3 along the Liaodong Bay.
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Affiliation(s)
- Yuqi Shi
- College of Environmental Sciences and Engineering, State Key Joint Laboratory of Environmental Simulation and Pollution Control, Peking University, Beijing 100871, PR China
| | - Chang Liu
- Liaoning Ecological and Environmental Service Center, Shenyang, Liaoning 110161, PR China
| | - Baosheng Zhang
- Department of Ecology and Environment of Liaoning Province, Shenyang, Liaoning 110161, PR China
| | - Maimaiti Simayi
- College of Resources and Environments, Xinjiang Agricultural University, Urumqi, Xinjiang 830052, PR China
| | - Ziyan Xi
- College of Environmental Sciences and Engineering, State Key Joint Laboratory of Environmental Simulation and Pollution Control, Peking University, Beijing 100871, PR China
| | - Jie Ren
- College of Environmental Sciences and Engineering, State Key Joint Laboratory of Environmental Simulation and Pollution Control, Peking University, Beijing 100871, PR China
| | - Shaodong Xie
- College of Environmental Sciences and Engineering, State Key Joint Laboratory of Environmental Simulation and Pollution Control, Peking University, Beijing 100871, PR China.
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Ren H, Su P, Kang W, Ge X, Ma S, Shen G, Chen Q, Yu Y, An T. Heterologous spatial distribution of soil polycyclic aromatic hydrocarbons and the primary influencing factors in three industrial parks. Environ Pollut 2022; 310:119912. [PMID: 35961570 DOI: 10.1016/j.envpol.2022.119912] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 06/13/2022] [Accepted: 07/29/2022] [Indexed: 06/15/2023]
Abstract
Soil polycyclic aromatic hydrocarbons (PAHs) generated from industrial processes are highly spatially heterologous, with limited quantitative studies on their main influencing factors. The present study evaluated the soil PAHs in three types of industrial parks (a petrochemical industrial park, a brominated flame retardant manufacturing park, and an e-waste dismantling park) and their surroundings. The total concentrations of 16 PAHs in the parks were 340-2.43 × 103, 26.2-2.63 × 103, and 394-2.01 × 104 ng/g, which were significantly higher than those in the surrounding areas by 1-2 orders of magnitude, respectively. The highest soil PAH contamination was observed in the e-waste dismantling park. Nap can be considered as characteristic pollutant in the petrochemical industrial park, while Phe in the flame retardant manufacturing park and e-waste dismantling park. Low molecular weight PAHs (2-3 rings) predominated in the petrochemical industrial park (73.0%) and the surrounding area of brominated flame retardant manufacturing park (80.3%). However, high molecular weight PAHs (4-6 rings) were enriched in the other sampling sites, indicating distinct sources and determinants of soil PAHs. Source apportionment results suggested that PAHs in the parks were mainly derived from the leakage of petroleum products in the petroleum manufacturing process and pyrolysis or combustion of fossil fuels. Contrarily, the PAHs in the surrounding areas could have been derived from the historical coal combustion and traffic emissions. Source emissions, wind direction, and local topography influenced the PAH spatial distributions.
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Affiliation(s)
- Helong Ren
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou, 510006, PR China; Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Key Laboratory of City Cluster Environmental Safety and Green Development, School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou, 510006, PR China
| | - Peixin Su
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou, 510006, PR China; Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Key Laboratory of City Cluster Environmental Safety and Green Development, School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou, 510006, PR China
| | - Wei Kang
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou, 510006, PR China; Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Key Laboratory of City Cluster Environmental Safety and Green Development, School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou, 510006, PR China
| | - Xiang Ge
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou, 510006, PR China; Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Key Laboratory of City Cluster Environmental Safety and Green Development, School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou, 510006, PR China
| | - Shengtao Ma
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou, 510006, PR China
| | - Guofeng Shen
- College of Urban and Environmental Sciences, Peking University, Beijing, 100871, PR China
| | - Qiang Chen
- College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, PR China
| | - Yingxin Yu
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou, 510006, PR China; Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Key Laboratory of City Cluster Environmental Safety and Green Development, School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou, 510006, PR China.
| | - Taicheng An
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control, Institute of Environmental Health and Pollution Control, Guangdong University of Technology, Guangzhou, 510006, PR China; Guangzhou Key Laboratory of Environmental Catalysis and Pollution Control, Key Laboratory of City Cluster Environmental Safety and Green Development, School of Environmental Science and Engineering, Guangdong University of Technology, Guangzhou, 510006, PR China
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Jookjantra P, Thepanondh S, Keawboonchu J, Kultan V, Laowagul W. Formation potential and source contribution of secondary organic aerosol from volatile organic compounds. J Environ Qual 2022; 51:1016-1034. [PMID: 35751911 DOI: 10.1002/jeq2.20381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Accepted: 05/31/2022] [Indexed: 06/15/2023]
Abstract
Secondary organic aerosol (SOA), a key constituent of fine particulate matter, can be formed through the oxidation of volatile organic compounds (VOCs). However, information on its relevant emission sources remains limited in many cities, especially concerning different types of land use. In this study, VOC concentration in Bangkok Metropolitan Region (BMR), Thailand, was continuously collected for 24 h by 6-L evacuated canister and analyzed by gas chromatography/mass spectrophotometry following USEPA TO15, and the formation of SOA was evaluated through the comprehensive direct measurements and speciation of ambient VOCs. Finally, source contribution of VOCs to SOA formation was characterized using the Positive Matrix Factorization (PMF) model. The results revealed the abundant group of VOCs species in the overall BMR was oxygenated VOCs, accounting for 49.97-57.37%. The SOA formation potential (SOAP) ranged from 1,134.33 to 3,143.74 μg m-3 . The VOC species contributing to the highest SOAP was toluene. Results from the PMF model revealed the dominant emission source of VOCs that greatly contributed to SOA was vehicle exhaust emission. Industrial combustion was the main source of VOC emission contributing to SOA in industrial areas. Sources of fuel evaporation, biomass burning, and cooking were also found in the study areas but in small quantities. The results of this study elucidated that different emission sources of VOCs contribute to SOA with respect to different types of land use. Findings of this study highlight the necessity to identify the contribution of potential emission sources of SOA precursors to effectively manage urban air pollution.
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Affiliation(s)
- Peemapat Jookjantra
- Dep. of Sanitary Engineering, Faculty of Public Health, Mahidol Univ., Bangkok, 10400, Thailand
| | - Sarawut Thepanondh
- Dep. of Sanitary Engineering, Faculty of Public Health, Mahidol Univ., Bangkok, 10400, Thailand
- Center of Excellence on Environmental Health and Toxicology (EHT), OPS, MHESI, Thailand
| | - Jutarat Keawboonchu
- Dep. of Sanitary Engineering, Faculty of Public Health, Mahidol Univ., Bangkok, 10400, Thailand
| | - Vanitchaya Kultan
- Dep. of Sanitary Engineering, Faculty of Public Health, Mahidol Univ., Bangkok, 10400, Thailand
| | - Wanna Laowagul
- Dep. of Environmental Quality Promotion, Environmental Research and Training Center, Pathumthani, Thailand
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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. Sci Total Environ 2022; 836:155465. [PMID: 35500706 DOI: 10.1016/j.scitotenv.2022.155465] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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Ding S, Chen Y, Devineni SR, Pavuluri CM, Li XD. Distribution characteristics of organosulfates (OSs) in PM 2.5 in Tianjin, Northern China: Quantitative analysis of total and three OS species. Sci Total Environ 2022; 834:155314. [PMID: 35447194 DOI: 10.1016/j.scitotenv.2022.155314] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 04/09/2022] [Accepted: 04/12/2022] [Indexed: 06/14/2023]
Abstract
Organosulfates (OSs) are important secondary organic aerosol (SOA) species in atmospheric fine particles (PM2.5) and can be considered as molecular indicators of SOA. To understand their seasonal and diurnal distribution characteristics and formation mechanism in northern China, PM2.5 samples collected in daytime and nighttime in winter and summer 2019 in Tianjin, China were studied for total OSs and three OS species (methyl sulfate (MS), glycolic acid sulfate (GAS), benzyl sulfate (BS)). The S contents of total OSs (SOSs) in winter and summer were 0.6 ± 1 μg m-3 and 0.4 ± 0.3 μg m-3, respectively, in PM2.5. BS found to be less abundant among the measured species, and accounted for only 0.8%-4.8% of methyl sulfate (MS), and 0.01%-0.3% of glycolic acid sulfate (GAS). Average content of GAS was higher in summer than in winter, while that of MS and BS were opposite. The fractions of MS, GAS, and BS in SOSs were higher in daytime than that in night during winter, despite their concentrations were higher in nighttime, indicating that the concentrations of unidentified OS species were much higher in nighttime than in daytime. Such diurnal variations implied that relative humidity (RH) played a major role in the formation processes of OSs, especially biogenic OSs and the acid catalyzed reaction of SO42- might be a main pathway of OSs formation during winter. High T, RH and O3 determined biological GAS in summer, while NO2 and SO2 determined anthropogenic OSs in winter. We also found that the fractions of SOSs in S contents of organic sulfur (SOS) and the S contents of MS + GAS+BS (SMS+GAS+BS) in SOSs were accounted for only less than 10% and 5%, respectively. Therefore, this study suggests the components of OS and OSs in PM2.5 have not been discovered fully yet and needs further research.
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Affiliation(s)
- Shiyuan Ding
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China
| | - Yingying Chen
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China
| | - Subba Rao Devineni
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China
| | - Chandra Mouli Pavuluri
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China
| | - Xiao-Dong Li
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China.
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Li J, Deng S, Tohti A, Li G, Yi X, Lu Z, Liu J, Zhang S. Spatial characteristics of VOCs and their ozone and secondary organic aerosol formation potentials in autumn and winter in the Guanzhong Plain, China. Environ Res 2022; 211:113036. [PMID: 35283079 DOI: 10.1016/j.envres.2022.113036] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 01/20/2022] [Accepted: 02/24/2022] [Indexed: 06/14/2023]
Abstract
As critical precursors of tropospheric ozone (O3) and secondary organic aerosol (SOA), volatile organic compounds (VOCs) largely influence air quality in urban environments. In this study, measurements of 102 VOCs at all five major cities in the Guanzhong Plain (GZP) were conducted during Sep.09-Oct. 13, 2017 (autumn) and Nov. 14, 2017-Jan. 19, 2018 (winter) to investigate the characteristics of VOCs and their roles in O3 and SOA formation. The average concentrations of total VOCs (TVOCs) at Xi'an (XA), Weinan (WN), Xianyang (XY), Tongchuan (TC), and Baoji (BJ) sites were in the range of 55.2-110.2 ppbv in autumn and 42.4-74.3 ppbv in winter. TVOCs concentrations were reduced by 22.4%-43.5% from autumn to winter at XA, WN and BJ. Comparatively low concentrations of TVOCs were observed in XY and TC, ranging from 53.5 to 62.7 ppbv across the sampling period. Alkanes were the major components at all sites, accounting for 26.4%-48.9% of the TVOCs during the sampling campaign, followed by aromatics (4.2%-26.4%). The average concentration of acetylene increased by a factor of up to 4.8 from autumn to winter, indicating the fuel combustion in winter heating period significantly impacted on VOCs composition in the GZP. The OH radical loss rate and maximum incremental reactivity method were employed to determine photochemical reactivities and ozone formation potentials (OFPs) of VOCs, respectively. The VOCs in XA and WN exhibited the highest reactivities in O3 formation, with the OFP of 168-273 ppbv and the OH loss rates of 19.3-40.8 s-1. Alkenes and aromatics primarily related to on-road and industrial emissions contributed 57.8%-76.3% to the total OFP. The contribution of aromatics to the SOA formation at all sites reached 94.1%-98.6%. Considering the potential source-area of VOCs, regional transport of VOCs occurred within the GZP cities.
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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.
| | - Abla Tohti
- School of Water and Environment, Chang'an University, Xi'an, 710064, China
| | - Guanghua Li
- School of Water and Environment, Chang'an University, Xi'an, 710064, China
| | - Xiaoxiao Yi
- School of Water and Environment, Chang'an University, Xi'an, 710064, China
| | - Zhenzhen Lu
- School of Water and Environment, Chang'an University, Xi'an, 710064, China
| | - Jiayao Liu
- School of Water and Environment, Chang'an University, Xi'an, 710064, China
| | - Shuai Zhang
- School of Water and Environment, Chang'an University, Xi'an, 710064, China
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Qin G, Gao S, Fu Q, Fu S, Jia H, Zeng Q, Fan L, Ren H, Cheng J. Investigation of VOC characteristics, source analysis, and chemical conversions in a typical petrochemical area through 1-year monitoring and emission inventory. Environ Sci Pollut Res Int 2022; 29:51635-51650. [PMID: 35247176 DOI: 10.1007/s11356-022-19145-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/06/2022] [Indexed: 06/14/2023]
Abstract
To effectively investigate the characteristics, source analysis, and chemical conversions of volatile organic compounds (VOCs) pollution in a typical petrochemical area, 81 VOC species from nine sampling sites were collected from 1st January to 31th December 2019 in Jinshan District. Results showed the concentration of VOCs was 51.63 ± 36.05 ppbv, and VOCs were dominated by alkane (40.10%) and alkenes (39.91%). The temporal variations of VOCs showed that the highest average VOC concentration appeared in July, and the lowest concentration of VOCs was in February. The concentration of VOCs was mainly connected with industrial processes and was transported to other areas through the downwind direction. Six PMF-derived sources including petrochemical industry, solvent utilization, vehicle exhaust, fuel evaporation, combustion, and other industry processes, contributing 37.08%, 16.74%, 16.69%, 14.99%, 9.53%, and 4.97%, respectively. Meanwhile, an anthropogenic VOC emission inventory was established by emission factors and the activity statistics for 2019, results indicated that the total emission of VOCs was estimated as 6.22 kt, petrochemical industry was the most important contributor of human-produced VOCs. The LOH concentration was 396.12 ppbv via OH radical loss rate method, and the OFP was 210.44 ppbv based on the MIR factor. Alkenes and aromatics were the important components of O3 formation. This study provides effective information for corresponding governments to establish VOCs contamination control directives.
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Affiliation(s)
- Guimei Qin
- China-UK Low Carbon College, Shanghai Jiao Tong University, 3 Yinlian Road, Shanghai, 201306, China
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Song Gao
- Shanghai Environmental Monitor Center, Shanghai, 200235, China
| | - Qingyan Fu
- Shanghai Environmental Monitor Center, Shanghai, 200235, China
| | - Shuang Fu
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Haohao Jia
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Qingrui Zeng
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Linping Fan
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Huarui Ren
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jinping Cheng
- China-UK Low Carbon College, Shanghai Jiao Tong University, 3 Yinlian Road, Shanghai, 201306, China.
- School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
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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. Environ Int 2022; 165:107330. [PMID: 35671590 DOI: 10.1016/j.envint.2022.107330] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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Li Q, Gong D, Wang H, Wang Y, Han S, Wu G, Deng S, Yu P, Wang W, Wang B. Rapid increase in atmospheric glyoxal and methylglyoxal concentrations in Lhasa, Tibetan Plateau: Potential sources and implications. Sci Total Environ 2022; 824:153782. [PMID: 35183643 DOI: 10.1016/j.scitotenv.2022.153782] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 02/06/2022] [Accepted: 02/06/2022] [Indexed: 06/14/2023]
Abstract
Glyoxal (Gly) and methylglyoxal (Mgly) are the intermediate products of several volatile organic compounds (VOCs) as well as the precursors of brown carbon and may play key roles in photochemical pollution and regional climate change in the Tibetan Plateau (TP). However, their sources and atmospheric behaviors in the TP remain unclear. During the second Tibetan Plateau Scientific Expedition and Research in the summer of 2020, the concentrations of Gly (0.40 ± 0.30 ppbv) and Mgly (0.57 ± 0.16 ppbv) observed in Lhasa, the most densely populated city in the TP, had increased by 20 and 15 times, respectively, compared to those measured a decade previously. Owing to the strong solar radiation, secondary formations are the dominant sources of both Gly (71%) and Mgly (62%) in Lhasa. In addition, primary anthropogenic sources also play important roles by emitting Gly and Mgly directly and providing abundant precursors (e.g., aromatics). During ozone pollution episodes, local anthropogenic sources (industries, vehicles, solvent usage, and combustion activities) contributed up to 41% and 45% in Gly and Mgly levels, respectively. During non-episode periods, anthropogenic emissions originating from the south of Himalayas also have non-negligible contributions. Our results suggest that in the previous decade, anthropogenic emissions have elevated the levels of Gly and Mgly in the TP dramatically. This study has important implications for understanding the impact of human activities on air quality and climate change in this ecologically fragile area.
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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-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China; Australia-China Centre for Air Quality Science and Management (Guangdong), Guangzhou 511443, China
| | - Hao Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China; Australia-China Centre for Air Quality Science and Management (Guangdong), Guangzhou 511443, China.
| | - Yu Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Shijie Han
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Australia-China Centre for Air Quality Science and Management (Guangdong), Guangzhou 511443, China
| | - Gengchen Wu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Australia-China Centre for Air Quality Science and Management (Guangdong), Guangzhou 511443, China
| | - Shuo Deng
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China; Australia-China Centre for Air Quality Science and Management (Guangdong), Guangzhou 511443, China
| | - Pengfei Yu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China
| | - Wenlu Wang
- 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-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China; Australia-China Centre for Air Quality Science and Management (Guangdong), Guangzhou 511443, China.
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Chen R, Zhao Y, Tian Y, Feng X, Feng Y. Sources and uncertainties of health risks for PM 2.5-bound heavy metals based on synchronous online and offline filter-based measurements in a Chinese megacity. Environ Int 2022; 164:107236. [PMID: 35447425 DOI: 10.1016/j.envint.2022.107236] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 03/13/2022] [Accepted: 04/07/2022] [Indexed: 06/14/2023]
Abstract
Accurate measurements of PM2.5 related heavy metals (HMs) and some components are critical to better understanding the sources and health risks of PM2.5. HMs and other components in PM2.5 were simultaneously measured using online and offline filter-based methods in a Chinese megacity. Online Mn, Pb, Cu, and Zn concentrations exhibited good correspondence with offline results (R2 ≥ 0.7, relative biases = -3%-22%). Some differences were observed for Cr, As, Co, and V. The assessment of online and offline probabilistic health risks indicated that non-cancer and total cancer risks were higher than the acceptable limits. Different analytical methods of As may result in different uncertainties in risk analysis. The positive matrix factorization model (PMF) was used to perform online and offline source apportionment. Five sources (coal combustion, vehicle source, industrial source, secondary source, and resuspended dust) were identified. Lower online percentage contribution of resuspended dust (8%) might relate to the lack of Si and Al measurements. The different rate contributions of vehicle source were potentially linked to the different time resolutions of the online and offline data. The assessment of online and offline source-specific health risks revealed that industrial source and coal combustion were the most important sources. Online and offline source-specific risks were not significantly different (P > 0.05). This contrastive study not only helps decision makers to manage health risk more effectively, but also provides insights into the applicability of online and offline measurements for quantifying source-specific risks.
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Affiliation(s)
- Rui Chen
- 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
| | - Yehui Zhao
- 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
| | - Yingze Tian
- 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; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China.
| | - Xin 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
| | - 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; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
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Feng Y, Ding D, Xiao A, Li B, Jia R, Guo Y. Characteristics, influence factors, and health risk assessment of volatile organic compounds through one year of high-resolution measurement at a refinery. Chemosphere 2022; 296:134004. [PMID: 35181418 DOI: 10.1016/j.chemosphere.2022.134004] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2021] [Revised: 02/08/2022] [Accepted: 02/13/2022] [Indexed: 06/14/2023]
Abstract
From January 2020 to December 2020, high-resolution data of volatile organic compound (VOC) concentrations were monitored by online instruments at a petroleum refinery. The measurement results showed that the external contaminants, meteorological conditions and photochemical reactions had a great influence on the VOC data measured in the petroleum refineries. Some significant differences were observed in the emission composition of different refineries, while propene (34.2%), propane (10.2%), n-butane (5.6%), i-pentane (5.0%) were the dominant species emitted from the refinery in this study. The correlations between compounds with similar atmospheric lifetimes were strong (R2 > 0.9), which indicated that the diagnostic ratios of these compounds could be used as indicators to identify the refinery emission source. Chronic health effects of non-carcinogenic risk results showed that acrolein had the highest non-carcinogenic risk and other compound-specific health risks may be of less concern in the refining area. Halogenates and aromatics accounted for 97.4% of the total carcinogenic risk values, while 1,2-dibromoethane, chloromethane, benzene, trichloromethane, 1,2-dichloroethane contributed approximately 80% of the total carcinogenic risk assessment values. This research has recorded valuable data about the VOC emission characteristics from the perspective of the high-resolution monitoring of the petroleum refinery. The results of this work will provide a reference to accurately quantify and identify the emission of petroleum refineries and further throw some light on effective VOC abatement strategies.
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Affiliation(s)
- Yunxia Feng
- State Key Laboratory of Safety and Control for Chemicals, SINOPEC Research Institute of Safety Engineering Co., Ltd., Qingdao, Shandong, 266071, PR China.
| | - Dewu Ding
- State Key Laboratory of Safety and Control for Chemicals, SINOPEC Research Institute of Safety Engineering Co., Ltd., Qingdao, Shandong, 266071, PR China
| | - Anshan Xiao
- State Key Laboratory of Safety and Control for Chemicals, SINOPEC Research Institute of Safety Engineering Co., Ltd., Qingdao, Shandong, 266071, PR China
| | - Bo Li
- State Key Laboratory of Safety and Control for Chemicals, SINOPEC Research Institute of Safety Engineering Co., Ltd., Qingdao, Shandong, 266071, PR China
| | - Runzhong Jia
- State Key Laboratory of Safety and Control for Chemicals, SINOPEC Research Institute of Safety Engineering Co., Ltd., Qingdao, Shandong, 266071, PR China
| | - Yirong Guo
- State Key Laboratory of Safety and Control for Chemicals, SINOPEC Research Institute of Safety Engineering Co., Ltd., Qingdao, Shandong, 266071, PR China
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Tamilvanan V, Subramani M, Subramani D, Ramasamy S. Probing of sequential atmospheric degradation of chlorine radical initiated 1,8-cineole in the presence of O 2 and NO radical with the emission of secondary pollution. Environ Pollut 2022; 300:118974. [PMID: 35150796 DOI: 10.1016/j.envpol.2022.118974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 01/24/2022] [Accepted: 02/07/2022] [Indexed: 06/14/2023]
Abstract
1,8-cineole is an essential monoterpene cyclic ether which is released into the troposphere by many types of plants. It interacts with several atmospheric oxidants because of which is removed from the troposphere via oxidation. The oxidation of 1,8-cineole with Cl radical and the subsequent addition of atmospheric O2 and NO radical with the intermediates are studied using the quantum chemical method. Further, the thermodynamic parameters of 1,8-cineole, such as enthalpy and Gibbs free energy are calculated for all initial and subsequent reactions to facilitate perspicacity. The dissociation and formation of chemical bonds during H abstraction from 1,8-cineole at C2, C6, and C8 sites are described using Mayer bond order analysis. The reaction force analysis demonstrates that the structural rearrangement is dominant with the yield percentages of 85%, 50.80%, and 96.9% over electron reordering with the yield percentages of 15%, 49.19%, and 3.03% respectively in the H abstraction reaction of 1,8-cineole. In the temperature range of 278-350 K, the total CVT/SCT rate constant is calculated to be 2.94 × 10-12 cm3/molecule/sec, which is consistent with the experimentally available value of 2.2 × 10-10 cm3/molecule/sec. At 298 K, branching ratios of rate constant of alkyl radical intermediates I1A, I1B, and I1C are calculated with the percentage of 42.19%, 21.52%, and 36.29% respectively, which suggest that the Cl addition to the C2 site contributes more to the total rate constant rather than the other two sites (C6 and C8). The lifetime of 1,8-cineole is calculated to be 5.2 weeks, implies that the 1,8-cineole may be readily destroyed in the atmosphere after it is released. Secondary pollutants formed from this degradation mechanism may be harmful to the environment and the living things.
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Affiliation(s)
- Vasuki Tamilvanan
- Department of Physics, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India
| | | | | | - Shankar Ramasamy
- Department of Physics, Bharathiar University, Coimbatore, 641046, Tamil Nadu, India.
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He X, Yuan B, Wu C, Wang S, Wang C, Huangfu Y, Qi J, Ma N, Xu W, Wang M, Chen W, Su H, Cheng Y, Shao M. Volatile organic compounds in wintertime North China Plain: Insights from measurements of proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS). J Environ Sci (China) 2022; 114:98-114. [PMID: 35459518 DOI: 10.1016/j.jes.2021.08.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 08/02/2021] [Accepted: 08/04/2021] [Indexed: 06/14/2023]
Abstract
The characteristics of wintertime volatile organic compounds (VOCs) in the North China Plain (NCP) region are complicated and remain obscure. VOC measurements were conducted by a proton transfer reaction time-of-flight mass spectrometer (PTR-ToF-MS) at a rural site in the NCP from November to December 2018. Uncalibrated ions measured by PTR-ToF-MS were quantified and the overall VOC compositions were investigated by combining the measurements of PTR-ToF-MS and gas chromatography-mass spectrometer/flame ionization detector (GC-MS/FID). The measurement showed that although atmospheric VOCs concentrations are often dominated by primary emissions, the secondary formation of oxygenated VOCs (OVOCs) is non-negligible in the wintertime, i.e., OVOCs accounts for 42% ± 7% in the total VOCs (151.3 ± 75.6 ppbV). We demonstrated that PTR-MS measurements for isoprene are substantially overestimated due to the interferences of cycloalkanes. The chemical changes of organic carbon in a pollution accumulation period were investigated, which suggests an essential role of fragmentation reactions for large, chemically reduced compounds during the heavy-polluted stage in wintertime pollution. The changes of emission ratios of VOCs between winter 2011 and winter 2018 in the NCP support the positive effect of "coal to gas" strategies in curbing air pollutants. The high abundances of some key species (e.g. oxygenated aromatics) indicate the strong emissions of coal combustion in wintertime of NCP. The ratio of naphthalene to C8 aromatics was proposed as a potential indicator of the influence of coal combustion on VOCs.
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Affiliation(s)
- Xianjun He
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Bin Yuan
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China.
| | - Caihong Wu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Sihang Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Chaomin Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Yibo Huangfu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Jipeng Qi
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Nan Ma
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
| | - Wanyun Xu
- State Key Laboratory of Severe Weather & Key Laboratory for Atmospheric Chemistry of China Meteorology Administration, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Ming Wang
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Wentai Chen
- Nanjing Intelligent Environmental Science and Technology Co., Ltd., Nanjing 211800, China
| | - Hang Su
- Max Planck Institute for Chemistry, Mainz 55128, Germany
| | - Yafang Cheng
- Max Planck Institute for Chemistry, Mainz 55128, Germany
| | - Min Shao
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China; Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Guangzhou 511443, China
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Wang J, Zhang Y, Wu Z, Luo S, Song W, Wang X. Ozone episodes during and after the 2018 Chinese National Day holidays in Guangzhou: Implications for the control of precursor VOCs. J Environ Sci (China) 2022; 114:322-333. [PMID: 35459495 DOI: 10.1016/j.jes.2021.09.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Revised: 08/29/2021] [Accepted: 09/06/2021] [Indexed: 06/14/2023]
Abstract
The impact of reducing industrial emissions of volatile organic compounds (VOCs) on ozone (O3) pollution is of wide concern particularly in highly industrialized megacities. In this study, O3, nitrogen oxides (NOx) and VOCs were measured at an urban site in the Pearl River Delta region during the 2018 Chinese National Day Holidays and two after-holiday periods (one with ozone pollution and another without). O3 pollution occurred throughout the 7-day holidays even industrial emissions of VOCs were passively reduced due to temporary factory shutdowns, and the toluene to benzene ratios dropped from ∼10 during non-holidays to ∼5 during the holidays. Box model (AtChem2-MCM) simulations with the input of observation data revealed that O3 formation was all VOC-limited, and alkenes had the highest relative incremental reactivity (RIR) during the holiday and non-holiday O3 episodes while aromatics had the highest RIR during the non-pollution period. Box model also demonstrated that even aromatics decreased proportionally to levels with near-zero contributions of industrial aromatic solvents, O3 concentrations would only decrease by less than 20% during the holiday and non-holiday O3 episodes and ozone pollution in the periods could not be eliminated. The results imply that controlling emissions of industrial aromatic solvents might be not enough to eliminate O3 pollution in the region, and more attention should be paid to anthropogenic reactive alkenes. Isoprene and formaldehyde were among the top 3 species by RIRs in all the three pollution and non-pollution periods, suggesting substantial contribution to O3 formation from biogenic VOCs.
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Affiliation(s)
- Jun Wang
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanli Zhang
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; CAS Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Zhenfeng Wu
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shilu Luo
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Song
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Xinming Wang
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; CAS Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Liu L, Seyler BC, Liu H, Zhou L, Chen D, Liu S, Yan C, Yang F, Song D, Tan Q, Jia F, Feng C, Wang Q, Li Y. Biogenic volatile organic compound emission patterns and secondary pollutant formation potentials of dominant greening trees in Chengdu, southwest China. J Environ Sci (China) 2022; 114:179-193. [PMID: 35459483 DOI: 10.1016/j.jes.2021.08.033] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 08/10/2021] [Accepted: 08/11/2021] [Indexed: 06/14/2023]
Abstract
Integral to the urban ecosystem, greening trees provide many ecological benefits, but the active biogenic volatile organic compounds (BVOCs) they release contribute to the production of ozone and secondary organic aerosols, which harm ambient air quality. It is, therefore, necessary to understand the BVOC emission characteristics of dominant greening tree species and their relative contribution to secondary pollutants in various urban contexts. Consequently, this study utilized a dynamic enclosure system to collect BVOC samples of seven dominant greening tree species in urban Chengdu, Southwest China. Gas chromatography/mass spectrometry was used to analyze the BVOC components and standardized BVOC emission rates of each tree species were then calculated to assess their relative potential to form secondary pollutants. We found obvious differences in the composition of BVOCs emitted by each species. Ficus virens displayed a high isoprene emission rate at 31.472 μgC/(gdw (g dry weight)•hr), while Cinnamomum camphora emitted high volumes of D-Limonene at 93.574 μgC/(gdw•hr). In terms of the BVOC emission rates by leaf area, C. camphora had the highest emission rate of total BVOCs at 13,782.59 μgC/(m2•hr), followed by Cedrus deodara with 5466.86 μgC/(m2•hr). Ginkgo biloba and Osmanthus fragrans mainly emitted oxygenated VOCs with lower overall emission rates. The high BVOC emitters like F. virens, C. camphora, and Magnolia grandiflora have high potential for significantly contributing to environmental secondary pollutants, so should be cautiously considered for future planting. This study provides important implications for improving urban greening efforts for subtropical Chinese urban contexts, like Chengdu.
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Affiliation(s)
- Liping Liu
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China; College of Science, Sichuan Agricultural University, Ya'an 625014, China
| | - Barnabas C Seyler
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China
| | - Hefan Liu
- Chengdu Academy of Environmental Sciences, Chengdu 610000, China
| | - Li Zhou
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China.
| | - Dongyang Chen
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China
| | - Song Liu
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China
| | - Chang Yan
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China
| | - Fumo Yang
- College of Architecture and Environment, Sichuan University, Chengdu 610065, China
| | - Danlin Song
- Chengdu Academy of Environmental Sciences, Chengdu 610000, China
| | - Qinwen Tan
- Chengdu Academy of Environmental Sciences, Chengdu 610000, China
| | - Fengju Jia
- Chengdu Ecological and Environmental Monitoring Center, Chengdu 610000, China
| | - Cheng Feng
- Chengdu Ecological and Environmental Monitoring Center, Chengdu 610000, China
| | - Qiuwei Wang
- Longquanyi Ecology and Environment Bureau, Chengdu 610000, China
| | - Yunchun Li
- College of Science, Sichuan Agricultural University, Ya'an 625014, China
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Zhou B, Zhao T, Ma J, Zhang Y, Zhang L, Huo P, Zhang Y. Characterization of VOCs during Nonheating and Heating Periods in the Typical Suburban Area of Beijing, China: Sources and Health Assessment. Atmosphere 2022; 13:560. [DOI: 10.3390/atmos13040560] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
In recent years, the “coal to electricity” project (CTEP) using clean energy instead of coal for heating has been implemented by Beijing government to cope with air pollution. However, VOC pollution after CTEP was rarely studied in suburbs of Beijing. To fill this exigency, 116 volatile organic compounds (VOCs) were observed during nonheating (P1) and heating (P2) periods in suburban Beijing. The results showed that the total of VOCs (TVOCs) was positively correlated with PM2.5, PM10, NO2, CO, and SO2 but negatively correlated with O3 and wind speed. The average TVOCs concentration was 19.43 ± 12.41 ppbv in P1 and 16.25 ± 8.01 ppbv in P2. Aromatics and oxygenated VOCs (OVOCs) were the main contributors to ozone formation potential (OFP). Seven sources of VOCs identified by the positive matrix factorization (PMF) model were industrial source, coal combustion, fuel evaporation, gasoline vehicle exhaust, diesel vehicle exhaust, background and biogenic sources, and solvent usage. The contribution of coal combustion to VOCs increased significantly during P2, whereas industrial sources, fuel evaporation, and solvent usage exhibited opposite trends. The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) were used to analyze the source distributions. The results showed that VOC pollution was caused mainly by air mass from southern Hebei during P1 but by local emissions during P2. Therefore, although the contribution of coal combustion after heating increased, TVOCs concentration during P2 was lower than that during P1. Chronic noncarcinogenic risks of all selected VOC species were below the safe level, while the carcinogenic risks of most selected VOC species were above the acceptable risk level, especially for tetrachloromethane and 1,2-dichloroethane. The cancer risks posed by gasoline vehicle emissions, industrial enterprises, and coal combustion should be paid more attention.
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Zhang X, Yan Y, Duan X, Chai J, Li R, Xu Y, Li Z, Peng L. Sources and Seasonal Variance of Ambient Volatile Organic Compounds in the Typical Industrial City of Changzhi, Northern China. Atmosphere 2022; 13:393. [DOI: 10.3390/atmos13030393] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Volatile organic compounds (VOCs) emitted from industrial processes, which are major emission sources of air pollutants, could cause significant impacts on air quality. However, studies on the comprehensive analysis from sources contributing to the health risk perspective regarding ambient VOCs in industrial cities are limited. In this study, VOC samples were collected from 15 April 2018 to 19 October 2018 in Changzhi, a typical industrial city in northern China, and a total of 57 VOCs were measured for analysis. The average VOC concentrations were 54.4 µg·m−3, with the highest concentrations in autumn (58.4 µg·m−3). Ambient VOCs in spring, summer and autumn were all dominated by alkanes (66.8%), with contributions of 70.3%, 66.3% and 63.8%, respectively. The top five concentrations of total VOCs were isopentane (19.0%), ethane (9.5%), n-butane (8.1%), benzene (7.9%) and propane (5.2%), indicating that vehicle exhaust and coal combustion are the main sources of VOCs. Source apportionment by principal component analysis showed that vehicle exhaust (27.5%) and coal combustion (23.5%) were the main sources of VOCs in Changzhi, followed by industrial production (17.4%), solvent evaporation (13.5%), liquefied petroleum gas/natural gas leaking (9.5%), and biogenic emissions (8.7%). Sources of coal combustion and vehicle exhaust contributed more VOCs than industrial production. The carcinogenic risks of benzene (3.4 × 10−5) and ethylbenzene (2.2 × 10−6) were higher than the limit levels (1 × 10−6). Coal combustion contributed most (25.3%) to the carcinogenic risks because of its high VOC emissions. In an industrial city such as Changzhi, vehicle exhaust and coal combustion have become major sources of ambient air VOCs owing to the increasingly stringent industrial standards. Therefore, VOCs from vehicle exhaust and coal combustion also need to take into account mitigation measures for VOCs from the perspective of source contribution to health risk.
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Li C, Liu Y, Cheng B, Zhang Y, Liu X, Qu Y, An J, Kong L, Zhang Y, Zhang C, Tan Q, Feng M. A comprehensive investigation on volatile organic compounds (VOCs) in 2018 in Beijing, China: Characteristics, sources and behaviours in response to O 3 formation. Sci Total Environ 2022; 806:150247. [PMID: 34562762 DOI: 10.1016/j.scitotenv.2021.150247] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 08/22/2021] [Accepted: 09/05/2021] [Indexed: 06/13/2023]
Abstract
Observations of volatile organic compounds (VOCs) are a prerequisite for evaluating the effectiveness of government efforts targeting VOC pollution. Here, based on the one-year online VOC measurement in 2018 in Beijing, systematic analyses and model simulation were conducted to illuminate VOC characteristics, emission sources, regional hotspots and behaviours in response to O3 formation. The observed mean VOC concentration in 2018 was 29.12 ± 17.64 ppbv declined distinctly compared to that in 2015 and 2016. Vehicle exhaust (39.95%), natural gas/liquefied petroleum gas (22.04%) and industrial sources (20.64%) were the main contributors to VOCs in Beijing. Regional transport, mainly from the south-south-east (SSE) and south-south-west (SSW), quantitatively contributed 36.65%-55.06% to VOCs based on our developed method. O3 sensitivity tended to be in the transition regime in summer identified by ground-based and satellite observations. Strong solar radiation along with high temperature and low humidity aggravated O3 pollution that was further intensified by regional transport from southern polluted regions. The model simulation determined that turning off CH3CHO related reactions brought about the most predominantly short-term and long-run O3 reduction, indicating that control policies in VOC species should be tailored, instead of one-size-fits-all. Overall, region-collaborated and active VOC-species-focused strategies on VOC controls are imperative.
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Affiliation(s)
- Chenlu Li
- 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
| | - Bingfen Cheng
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yuepeng 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.
| | - Yu Qu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China.
| | - Junling An
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Liuwei Kong
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Yingying Zhang
- 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
| | - Qinwen Tan
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Miao Feng
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
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Wang Q, Hou Z, Li L, Guo S, Liang H, Li M, Luo H, Wang L, Luo Y, Ren H. Seasonal disparities and source tracking of airborne antibiotic resistance genes in Handan, China. J Hazard Mater 2022; 422:126844. [PMID: 34399210 DOI: 10.1016/j.jhazmat.2021.126844] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 08/02/2021] [Accepted: 08/04/2021] [Indexed: 06/13/2023]
Abstract
The transmission of airborne antibiotic resistance genes (ARGs) loaded on particle is a significant global public health concern. Up to date, the dispersal pattern of airborne ARGs remains unclear despite their critical role in multiregional transmission. In this study, airborne ARGs loaded on fine particulate matter (PM2.5) and source tracking based on the airflow trajectories were performed by the potential source contribution function (PSCF) and concentration weighted trajectory (CWT) model. The results show that the absolute abundance of ARG subtypes were generally twice times higher in the winter season than that in the summer season, which could be attributable to winter haze events with high particulate matter concentrations in Handan. Exogenous input from serious haze events and local release of ARGs loaded on PM2.5 of air masses may cause higher levels of ARGs in the winter. Moreover, based on the positive correlation between the abundance of ARGs and PM2.5 concentration, a source tracing model of airborne ARGs was proposed to the estimate of ARGs release and dissemination. This study highlights airborne ARGs transmission loaded on PM2.5 of air masses, which facilitating the global spread of antibiotic resistance.
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Affiliation(s)
- Qing Wang
- College of Energy and Environmental Engineering, Hebei Key Laboratory of Air Pollution Cause and Impact, Hebei University of Engineering, Handan 056038, China; State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210093, China
| | - Zelin Hou
- College of Energy and Environmental Engineering, Hebei Key Laboratory of Air Pollution Cause and Impact, Hebei University of Engineering, Handan 056038, China
| | - Linyun Li
- College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Nankai University, Tianjin 300071, China
| | - Shaoyue Guo
- College of Energy and Environmental Engineering, Hebei Key Laboratory of Air Pollution Cause and Impact, Hebei University of Engineering, Handan 056038, China
| | - Haiyin Liang
- College of Energy and Environmental Engineering, Hebei Key Laboratory of Air Pollution Cause and Impact, Hebei University of Engineering, Handan 056038, China
| | - Menghan Li
- College of Energy and Environmental Engineering, Hebei Key Laboratory of Air Pollution Cause and Impact, Hebei University of Engineering, Handan 056038, China
| | - Huixiao Luo
- College of Energy and Environmental Engineering, Hebei Key Laboratory of Air Pollution Cause and Impact, Hebei University of Engineering, Handan 056038, China
| | - Litao Wang
- College of Energy and Environmental Engineering, Hebei Key Laboratory of Air Pollution Cause and Impact, Hebei University of Engineering, Handan 056038, China.
| | - Yi Luo
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210093, China; College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Nankai University, Tianjin 300071, China.
| | - Hongqiang Ren
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210093, China
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47
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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. Environ Int 2022; 158:106979. [PMID: 34991244 DOI: 10.1016/j.envint.2021.106979] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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Meng Y, Song J, Zeng L, Zhang Y, Zhao Y, Liu X, Guo H, Zhong L, Ou Y, Zhou Y, Zhang T, Yue D, Lai S. Ambient volatile organic compounds at a receptor site in the Pearl River Delta region: Variations, source apportionment and effects on ozone formation. J Environ Sci (China) 2022; 111:104-117. [PMID: 34949340 DOI: 10.1016/j.jes.2021.02.024] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Revised: 02/22/2021] [Accepted: 02/22/2021] [Indexed: 06/14/2023]
Abstract
We present the continuously measurements of volatile organic compounds (VOCs) at a receptor site (Wan Qing Sha, WQS) in the Pearl River Delta (PRD) region from September to November of 2017. The average mixing ratios of total VOCs (TVOCs) was 36.3 ± 27.9 ppbv with the dominant contribution from alkanes (55.5%), followed by aromatics (33.3%). The diurnal variation of TVOCs showed a strong photochemical consumption during daytime, resulting in the formation of ozone (O3). Five VOC sources were resolved by the positive matrix factorization (PMF) model, including solvent usage (28.6%), liquid petroleum gas (LPG) usage (24.4%), vehicle exhaust (21.0%), industrial emissions (13.2%) and gasoline evaporation (12.9%). The regional transport air masses from the upwind cities of south China can result in the elevated concentrations of TVOCs. Low ratios of TVOCs/NOx (1.53 ± 0.88) suggested that the O3 formation regime at WQS site was VOC-limited, which also confirmed by a photochemical box model with the master chemical mechanism (PBM-MCM). Furthermore, the observation on high-O3 episode days revealed that frequent O3 outbreaks at WQS were mainly caused by the regional transport of anthropogenic VOCs especially for aromatics and the subsequent photochemical reactions. This study provides valuable information for policymakers to propose the effective control strategies on photochemical pollution in a regional perspective.
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Affiliation(s)
- Yao Meng
- The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, and Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Junwei Song
- Institute of Meteorology and Climate Research, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, Eggenstein-Leopoldshafen 76344, Germany
| | - Lewei Zeng
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Yingyi Zhang
- The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, and Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Yan Zhao
- Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangzhou 510308, China
| | - Xufei Liu
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Hai Guo
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Liuju Zhong
- Guangdong Polytechnic of Environmental Protection Engineering, Foshan 528216, China
| | - Yubo Ou
- Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangzhou 510308, China
| | - Yan Zhou
- Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangzhou 510308, China
| | - Tao Zhang
- Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangzhou 510308, China
| | - Dingli Yue
- Guangdong Environmental Monitoring Center, State Environmental Protection Key Laboratory of Regional Air Quality Monitoring, Guangzhou 510308, China.
| | - Senchao Lai
- The Key Lab of Pollution Control and Ecosystem Restoration in Industry Clusters, Ministry of Education, and Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control, School of Environment and Energy, South China University of Technology, Guangzhou 510006, China.
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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. Environ Res 2022; 203:111821. [PMID: 34370988 DOI: 10.1016/j.envres.2021.111821] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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50
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Panopoulou A, Liakakou E, Sauvage S, Gros V, Locoge N, Bonsang B, Salameh T, Gerasopoulos E, Mihalopoulos N. Variability and sources of non-methane hydrocarbons at a Mediterranean urban atmosphere: The role of biomass burning and traffic emissions. Sci Total Environ 2021; 800:149389. [PMID: 34426353 DOI: 10.1016/j.scitotenv.2021.149389] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/21/2021] [Accepted: 07/28/2021] [Indexed: 06/13/2023]
Abstract
Levels and sources of non-Methane Hydrocarbons (NMHCs) were investigated at the urban background Thissio station, close to the historical center of Athens (Greece) from March 2016 to February 2017 (12 months), by means of an automated GC-FID. Alkanes dominated over aromatics and alkenes, with hourly mean levels ranging from detection limit up to 60 μg m-3 for i-pentane and 90 μg m-3 for toluene. Higher levels were recorded in the cold period relative to the warmer one. In addition, NMHCs seasonal diurnal cycles were characterized by a bimodal pattern, following the trend of tracers of anthropogenic sources. The Positive Matrix Factorization (PMF) was used for the allocation of NMHC to their sources. Five factors were identified and quantified, with traffic-related sources being the main one contributing up to 60% to total NMHCs, while biomass burning contributes up to 19%. A supplementary PMF assimilation was applied on a seasonal basis further including α-pinene, C6-C16 alkanes and aromatics. This PMF resulted to a seven-factor solution that allowed the examination of two additional sources, in addition to five already identified, highlighting the main contribution of anthropogenic sources (70%) to α-pinene.
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Affiliation(s)
- Anastasia Panopoulou
- University of Crete, Department of Chemistry, Environmental Chemical Processes Laboratory (ECPL), 71003 Heraklion, Crete, Greece; National Observatory of Athens, Institute for Environmental Research and Sustainable Development, 15236 P. Penteli, Athens, Greece
| | - Eleni Liakakou
- National Observatory of Athens, Institute for Environmental Research and Sustainable Development, 15236 P. Penteli, Athens, Greece.
| | - Stéphane Sauvage
- IMT Lille Douai, Institut Mines-Télécom, Univ. Lille, Centre for Energy and Environment, F-59000 Lille, France
| | - Valérie Gros
- LSCE, Laboratoire des Sciences Du Climat et de L'Environnement, Unité Mixte CNRS-CEA-UVSQ, CEA/Orme des Merisiers, 91191 Gif-sur-Yvette Cedex, France
| | - Nadine Locoge
- IMT Lille Douai, Institut Mines-Télécom, Univ. Lille, Centre for Energy and Environment, F-59000 Lille, France
| | - Bernard Bonsang
- LSCE, Laboratoire des Sciences Du Climat et de L'Environnement, Unité Mixte CNRS-CEA-UVSQ, CEA/Orme des Merisiers, 91191 Gif-sur-Yvette Cedex, France
| | - Thérèse Salameh
- IMT Lille Douai, Institut Mines-Télécom, Univ. Lille, Centre for Energy and Environment, F-59000 Lille, France
| | - Evangelos Gerasopoulos
- National Observatory of Athens, Institute for Environmental Research and Sustainable Development, 15236 P. Penteli, Athens, Greece
| | - Nikolaos Mihalopoulos
- University of Crete, Department of Chemistry, Environmental Chemical Processes Laboratory (ECPL), 71003 Heraklion, Crete, Greece; National Observatory of Athens, Institute for Environmental Research and Sustainable Development, 15236 P. Penteli, Athens, Greece
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