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Yong J, Xie Y, Guo H, Li Y, Sun S. Unraveling the influence of biogenic volatile organic compounds and their constituents on ozone and SOA formation within the Yellow River Basin, China. CHEMOSPHERE 2024; 353:141549. [PMID: 38408570 DOI: 10.1016/j.chemosphere.2024.141549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Revised: 01/27/2024] [Accepted: 02/23/2024] [Indexed: 02/28/2024]
Abstract
Biogenic volatile organic compounds (BVOC) assume a pivotal role during the formation stages of ozone (O3) and secondary organic aerosols (SOA), serving as their primary precursors. We used the latest MEGAN3.1 model, updated vegetation data and emission factors, combined with MODIS data analysis to simulate and estimate the integrated emissions of BVOC from nine provinces in China's Yellow River Basin in 2018. Following an extensive evaluation of the WRF-CMAQ model utilizing diverse parameters, the simulated and observed values had correlation coefficients between them that ranged from 0.94 to 0.99, implying a favorable outcome in terms of simulation efficacy. The findings from the simulation analysis reveal that the combined BVOC emissions from the nine provinces in the Yellow River Basin reached a total of 6.51 Tg in 2018. Among these provinces, Sichuan, Henan, and Shaanxi ranked highest, with emissions of 1.28 Tg, 1.04 Tg, and 0.96 Tg, respectively. BVOC emissions led to concentrations of 36.72 μg/m³ in the daily maximum 8-h ozone and 0.59 μg/m³ in the average SOA in nine provinces of the Yellow River Basin in July. Isoprene contributed the most to the O3 production with 6.31 μg/m3, and monoterpenes contributed the most to SOA production with 0.45 μg/m3. ΔSOA and ΔOzone are mainly distributed in the belts of central Sichuan Province, southern Shaanxi Province, western Henan Province, northern Qinghai Province, central Inner Mongolia, and southern Shanxi Province, and most of these areas are located 50 km around the Yellow River. O3 and SOA in Taiyuan, Xi'an, Chengdu, and Zhengzhou cities are strongly influenced by the generation of BVOCs. This study provides a reliable scientific basis for the prevention and control of air pollution in the Yellow River Basin.
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Affiliation(s)
- Jiale Yong
- College of Urban and Environmental Science, Northwest University, Xi'an, 710127, China
| | - Yuanli Xie
- College of Urban and Environmental Science, Northwest University, Xi'an, 710127, China; Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, Northwest University, Xi'an, 710127, China.
| | - Huilin Guo
- College of Urban and Environmental Science, Northwest University, Xi'an, 710127, China
| | - Yunmei Li
- College of Urban and Environmental Science, Northwest University, Xi'an, 710127, China
| | - Shaoqi Sun
- College of Urban and Environmental Science, Northwest University, Xi'an, 710127, China
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Anigilaje EA, Nasir ZA, Walton C. Exposure to benzene, toluene, ethylbenzene, and xylene (BTEX) at Nigeria's petrol stations: a review of current status, challenges and future directions. Front Public Health 2024; 12:1295758. [PMID: 38590813 PMCID: PMC11000709 DOI: 10.3389/fpubh.2024.1295758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Accepted: 02/02/2024] [Indexed: 04/10/2024] Open
Abstract
Introduction In Nigeria, because of increasing population, urbanization, industrialization, and auto-mobilization, petrol is the most everyday non-edible commodity, and it is the leading petroleum product traded at the proliferating Nigeria's petrol stations (NPSs). However, because of inadequate occupational health and safety (OHS) regulatory measures, working at NPSs exposes petrol station workers (PSWs) to a large amount of hazardous benzene, toluene, ethylbenzene, and xylene (BTEX) compounds. Methods Studies on BTEX exposures among Nigerian PSWs are scarce. Thus, constraints in quantifying the health risks of BTEX limit stakeholders' ability to design practical risk assessment and risk control strategies. This paper reviews studies on the OHS of Nigerian PSWs at the NPSs. Results Although knowledge, attitude, and practices on OHS in NPSs vary from one Nigeria's study setting to another, generally, safety practices, awareness about hazards and personal protective equipment (PPE), and the use of PPE among PSWs fell below expectations. Additionally, air quality at NPSs was poor, with a high content of BTEX and levels of carbon monoxide, hydrogen sulfide, particulate matter, and formaldehyde higher than the World Health Organization guideline limits. Discussion Currently, regulatory bodies' effectiveness and accountability in safeguarding OHS at NPSs leave much to be desired. Understanding the OHS of NPSs would inform future initiatives, policies, and regulations that would promote the health and safety of workers at NPSs. However, further studies need to be conducted to describe the vulnerability of PSWs and other Nigerians who are occupationally exposed to BTEX pollution. More importantly, controlling air pollution from hazardous air pollutants like BTEX is an essential component of OHS and integral to attaining the Sustainable Development Goals (SDG) 3, 7, and 11.
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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. THE SCIENCE OF THE TOTAL ENVIRONMENT 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] [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 Z, Tian X, Li J, Wang F, Liang W, Zhao H, Huang B, Wang Z, Feng Y, Shi G. Quantitative evidence from VOCs source apportionment reveals O 3 control strategies in northern and southern China. ENVIRONMENT INTERNATIONAL 2023; 172:107786. [PMID: 36738582 DOI: 10.1016/j.envint.2023.107786] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 01/24/2023] [Accepted: 01/26/2023] [Indexed: 06/18/2023]
Abstract
Ground-level ozone (O3) pollution has received widespread attention because its rising trend and adverse ecological impacts. However, the extremely strong photochemical reactions of its precursor volatile organic compounds (VOCs) increase the difficulty of reducing VOCs emissions to alleviate O3. Here, we carried out a one-year comprehensive observation in two representative cities, Tianjin (TJ, Northern China) and Guangzhou (GZ, Southern China). By revealing the concentration characteristics of three different types of VOCs, i.e., initial VOCs without photochemical reaction (In-VOCs), consumed VOCs (C-VOCs), and measured VOCs after the reaction (M-VOCs), we elucidated the important role of C-VOCs in the formation of O3. Although the overall trends were similar in both cities, the average concentration level of VOCs in GZ was 8.2 ppbv higher than that in TJ, and the photochemical loss of VOCs was greater by 2.2 ppbv. In addition, various drivers affecting O3 generation from C-VOCs were specifically explored, and it was found that most alkenes of TJ were key substances for rapid O3 formation compared to aromatics of GZ. Meanwhile, favorable meteorological conditions such as high temperature (T > 31 °C in TJ, and T > 33 °C in GZ), low relative humidity (56% in TJ and 45% in GZ), and stable atmospheric environment (proper pressure and gentle wind speed) also contribute to the generation of O3. More importantly, we combined chemical kinetics and receptor model to quantify the three-type VOCs source contributions and assess the potential impact of C-VOCs sources on O3 production, thus proposing environmental abatement technologies corresponding to the three types of VOCs. The differences in the comparison results of the three-type VOCs highlight the need to reduce O3 pollution from C-VOCs sources, which provides insights for future clean air policies development.
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Affiliation(s)
- Zhenyu Wang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Xiao Tian
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Jie Li
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Feng Wang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Weiqing Liang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Huan Zhao
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Bo Huang
- Guangzhou Hexin Instrument Co., Ltd, Guangzhou 510530, China
| | - Zaihua Wang
- Institute of Resources Utilization and Rare Earth Development, Guangdong Academy of Sciences, Guangzhou 510650, China.
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Guoliang Shi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research (CLAER), College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
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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] [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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Niu Y, Yan Y, Chai J, Zhang X, Xu Y, Duan X, Wu J, Peng L. Effects of regional transport from different potential pollution areas on volatile organic compounds (VOCs) in Northern Beijing during non-heating and heating periods. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 836:155465. [PMID: 35500706 DOI: 10.1016/j.scitotenv.2022.155465] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 04/11/2022] [Accepted: 04/19/2022] [Indexed: 06/14/2023]
Abstract
Despite the adoption of air quality control measures, the influence of regional transport on volatile organic compounds (VOCs) pollution has gradually increased in Beijing. In this study, the whole observation period (September 24 to December 12, 2020) was divided into heating period and non-heating period to explore the impact of changing VOCs sources in different observation periods, and also classified into "Type-N" and "Type-S" periods both in non-heating period and heating period to explore the impact of regional transport from the northern and southern regions of sampling site, respectively. The average VOCs concentrations in northern Beijing during observation period were 22.6 ± 12.6 ppbv, which showed a decrease trend in recent years compared with other studies. And higher VOCs concentrations were observed in Type-S than in Type-N period. The positive matrix factorization results showed that vehicular exhaust dominated VOCs (26.1%-33.7%), but coal combustion could not be ignored in heating period, when it was twice that in non-heating period. In particular, coal combustion dominated VOCs in southern trajectories (30.9%) in heating period. The analysis of concentration weighted trajectory showed that coal combustion was affected by regional transport from the southeast regions of Beijing, while vehicular exhaust was affected by urban and the southeast regions of Beijing. Regarding human health risks, the carcinogenic risks of benzene and ethylbenzene exceeded the acceptable cancer risk value (1 × 10-6), and were higher in Type-S than in Type-N period. The results indicated that regional transport from urban areas and the areas south of Beijing had a significant impact on VOCs in northern Beijing. Thus, targeted control measures for different potential pollution regions are important for controlling VOCs pollution in Beijing.
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Affiliation(s)
- Yueyuan Niu
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Yulong Yan
- Institute of Transport Energy and Environment, Beijing Jiaotong University, Beijing 100044, China; School of Environment, Beijing Jiaotong University, Beijing 100044, China.
| | - Jianwei Chai
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Xiangyu Zhang
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Yang Xu
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Xiaolin Duan
- MOE Key Laboratory of Resources and Environmental System Optimization, College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China
| | - Jing Wu
- Institute of Transport Energy and Environment, Beijing Jiaotong University, Beijing 100044, China; School of Environment, Beijing Jiaotong University, Beijing 100044, China
| | - Lin Peng
- Institute of Transport Energy and Environment, Beijing Jiaotong University, Beijing 100044, China; School of Environment, Beijing Jiaotong University, Beijing 100044, China
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Zhang X, Li H, Wang X, Zhang Y, Bi F, Wu Z, Liu Y, Zhang H, Gao R, Xue L, Zhang Q, Chen Y, Chai F, Wang W. Heavy ozone pollution episodes in urban Beijing during the early summertime from 2014 to 2017: Implications for control strategy. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 285:117162. [PMID: 33965854 DOI: 10.1016/j.envpol.2021.117162] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 04/11/2021] [Accepted: 04/13/2021] [Indexed: 06/12/2023]
Abstract
Ground-level ozone (O3) has become the principal air pollutant in Beijing during recent summers. In this context, an investigation of ambient concentrations and variation characteristics of O3 and its precursors in May and June from 2014 to 2017 in a typical urban area of Beijing was carried out, and the formation sensitivity and different causes of heavy O3 pollution (HOP, daily maximum 8-h O3 (MDA8h O3)>124 ppbv) were analyzed. The results showed that the monthly assessment values of the O3 concentrations (the 90th percentile MDA8h O3 within one month) were highest in May or June from 2014 to 2017, and the values presented an overall increasing trend. During this period, the number of O3 pollution days (MDA8h O3 > 75 ppbv) also showed an increasing trend. During the HOP episodes, the concentrations of volatile organic compounds (VOCs), nitrogen oxides (NOX), and carbon monoxide (CO) were higher than their respective mean values in May and June, and the meteorological conditions were more conducive to atmospheric photochemical reactions. The HOP episodes were mainly caused by local photochemical formation. From 2014 to 2017, O3 formation during the HOP episodes shifted from VOC and NOX mixed-limited to VOC-limited conditions, and O3 formation was most sensitive to anthropogenic VOCs. Six categories of VOC sources were identified, among which vehicular exhaust contributed the most to anthropogenic VOCs. The VOC concentrations and OFPs of anthropogenic sources have decreased significantly in recent years, indicating that VOC control measures have been effective in Beijing. Nevertheless, NOX concentrations did not show an evident decreasing trend in the same period. Therefore, more attention should be devoted to O3 pollution control in May and June; control measure adjustments are needed according to the changes in O3 precursors, and coordinated control of VOCs and NOX should be strengthened in long-term planning.
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Affiliation(s)
- Xin Zhang
- Environment Research Institute, Shandong University, Qingdao, 266237, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Hong Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Xuezhong Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Yujie Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Fang Bi
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Zhenhai Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Yuhong Liu
- Environment Research Institute, Shandong University, Qingdao, 266237, China
| | - Hao Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Rui Gao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Likun Xue
- Environment Research Institute, Shandong University, Qingdao, 266237, China
| | - Qingzhu Zhang
- Environment Research Institute, Shandong University, Qingdao, 266237, China
| | - Yizhen Chen
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Fahe Chai
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Wenxing Wang
- Environment Research Institute, Shandong University, Qingdao, 266237, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
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Zhang H, Chen C, Yan W, Wu N, Bo Y, Zhang Q, He K. Characteristics and sources of non-methane VOCs and their roles in SOA formation during autumn in a central Chinese city. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 782:146802. [PMID: 33838366 DOI: 10.1016/j.scitotenv.2021.146802] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Revised: 03/19/2021] [Accepted: 03/24/2021] [Indexed: 06/12/2023]
Abstract
Volatile organic compounds (VOCs) are essential in secondary organic aerosol (SOA) formation due to their dual roles as precursors and oxidant producers. In order to explore the dominant contributions of SOA formation from VOCs in central China, 53 VOC species were observed with proton transfer reaction-mass spectrometry (PTR-MS) and canister grab samples in Xinxiang, a mid-sized city located in Henan Province, from November 5th to December 3rd, 2018. The result showed that anthropogenic emissions were intensive compared with many studies in the world. Among the observed VOCs, benzene and toluene had the largest SOA formation potential (SOAFP), and their contributions in SOA formation kept stable with the aggravation of pollution. Among VOCs, formaldehyde was the strongest radical contributor, and the contribution of acetaldehyde was also found significant in this study, especially in polluted periods. Based on the positive matrix factorization (PMF) model, benzenoids (mainly single-ring aromatics) were majorly emitted from chemical process, solvent evaporation, and residential heating, with a total fraction of 75%, and these sources were estimated to have largest SOAFP. However, thermal power generation, chemical process, and solvent evaporation had highest radical contribution rates. According to the backward trajectory analysis, the VOC concentrations were dominated by local emissions. Emissions in the surrounding provinces occupied fractions of 33%-42% in the five sources. Therefore, regional collaborative emission reduction is also important.
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Affiliation(s)
- Haixu Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
| | - Chunrong Chen
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Weijia Yan
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Nana Wu
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Yu Bo
- RCE-TEA, Institute of Atmospheric Physics, Chinese Academy of Science, Beijing 100029, China.
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modelling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Kebin He
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Tsinghua University, Beijing 100084, China
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Wang X, Fu TM, Zhang L, Cao H, Zhang Q, Ma H, Shen L, Evans MJ, Ivatt PD, Lu X, Chen Y, Zhang L, Feng X, Yang X, Zhu L, Henze DK. Sensitivities of Ozone Air Pollution in the Beijing-Tianjin-Hebei Area to Local and Upwind Precursor Emissions Using Adjoint Modeling. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:5752-5762. [PMID: 33890767 DOI: 10.1021/acs.est.1c00131] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Effective mitigation of surface ozone pollution entails detailed knowledge of the contributing precursors' sources. We use the GEOS-Chem adjoint model to analyze the precursors contributing to surface ozone in the Beijing-Tianjin-Hebei area (BTH) of China on days of different ozone pollution severities in June 2019. We find that BTH ozone on heavily polluted days is sensitive to local emissions, as well as to precursors emitted from the provinces south of BTH (Shandong, Henan, and Jiangsu, collectively the SHJ area). Heavy ozone pollution in BTH can be mitigated effectively by reducing NOx (from industrial processes and transportation), ≥C3 alkenes (from on-road gasoline vehicles and industrial processes), and xylenes (from paint use) emitted from both BTH and SHJ, as well as by reducing CO (from industrial processes, transportation, and power generation) and ≥C4 alkanes (from industrial processes, paint and solvent use, and on-road gasoline vehicles) emissions from SHJ. In addition, reduction of NOx, xylene, and ≥C3 alkene emissions within BTH would effectively decrease the number of BTH ozone-exceedance days. Our analysis pinpoint the key areas and activities for locally and regionally coordinated emission control efforts to improve surface ozone air quality in BTH.
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Affiliation(s)
- Xiaolin Wang
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Tzung-May Fu
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
- Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Lin Zhang
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Hansen Cao
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder, Colorado 80309, United States
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China
| | - Hanchen Ma
- Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China
| | - Lu Shen
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Mathew J Evans
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York YO10 5DD, U.K
- National Centre for Atmospheric Science, Department of Chemistry, University of York, York YO10 5DD, U.K
| | - Peter D Ivatt
- Wolfson Atmospheric Chemistry Laboratories, Department of Chemistry, University of York, York YO10 5DD, U.K
- National Centre for Atmospheric Science, Department of Chemistry, University of York, York YO10 5DD, U.K
| | - Xiao Lu
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Youfan Chen
- Sichuan Academy of Environmental policy and planning, Chengdu, Sichuan 610041, China
| | - Lijuan Zhang
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
- Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
- Shanghai Central Meteorological Observatory, Shanghai 200030, China
| | - Xu Feng
- Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing 100871, China
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
- Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Xin Yang
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
- Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Lei Zhu
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
- Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Daven K Henze
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder, Colorado 80309, United States
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10
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Hui L, Ma T, Gao Z, Gao J, Wang Z, Xue L, Liu H, Liu J. Characteristics and sources of volatile organic compounds during high ozone episodes: A case study at a site in the eastern Guanzhong Plain, China. CHEMOSPHERE 2021; 265:129072. [PMID: 33302209 DOI: 10.1016/j.chemosphere.2020.129072] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 10/29/2020] [Accepted: 11/17/2020] [Indexed: 06/12/2023]
Abstract
This study performed continuous measurements of 105 volatile organic compounds (VOCs) in Weinan in the eastern Guanzhong Plain from 1 July to September 19, 2019. Ozone (O3) episode and non-episode days were identified according to China Ambient Air Quality Standard, and the concentrations of total quantified VOCs (TVOCs) were 33.43 ± 13.64 ppbv and 29.13 ± 14.31 ppbv, respectively. During different O3 pollution episodes, alkanes comprised the highest proportion to TVOC concentrations, while alkenes contributed the most to ozone formation potential (OFP). In addition, O3 episode days were mainly caused by enhanced emissions of precursors and meteorological conditions favorable to O3 production. Based on Empirical Kinetic Modelling Approach (EKMA), the O3 formation in Weinan was found in the transitional regime, in which the synergistic reduction of VOCs and nitrogen oxide (NOx) would be more effective for O3 reduction. Eight sources were identified by positive matrix factorization (PMF) model, with natural gas (NG)/liquefied petroleum gas (LPG) usage as the most significant contributor to VOC concentration, followed by vehicle exhaust, biomass burning, solvent usage, fuel evaporation, rubber/plastic industrial emissions, biogenic source, and mixed industrial emissions. Furthermore, rubber/plastic industrial emissions, solvent usage, fuel evaporation, and vehicle exhaust were the most significant sources to O3 formation. Based on conditional bivariate probability function (CBPF), vehicle exhaust, fuel evaporation, and solvent usage were mainly local emissions, while other sources were mainly affected by regional transport. This study provides useful reference for research on the atmospheric photochemical formation of O3 and evidence for regional O3 reduction strategies.
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Affiliation(s)
- Lirong Hui
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Tong Ma
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Zongjiang Gao
- Nanjing Intelligent Environmental Science and Technology Co., Ltd., Nanjing, 211800, China
| | - Jian Gao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
| | - Zhe Wang
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Likun Xue
- Environment Research Institute, Shandong University, Ji'nan, 250013, China
| | - Hanqing Liu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Jiayuan Liu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
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11
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Sun J, Shen Z, Wang R, Li G, Zhang Y, Zhang B, He K, Tang Z, Xu H, Qu L, Sai Hang Ho S, Liu S, Cao J. A comprehensive study on ozone pollution in a megacity in North China Plain during summertime: Observations, source attributions and ozone sensitivity. ENVIRONMENT INTERNATIONAL 2021; 146:106279. [PMID: 33276317 DOI: 10.1016/j.envint.2020.106279] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 11/04/2020] [Accepted: 11/09/2020] [Indexed: 06/12/2023]
Abstract
Tropospheric ozone (O3) pollution has been becoming prominent in North China Plain (NCP) in China since last decade. In order to clarify the source contribution and formation mechanism of O3, the critical precursors of volatile organic compounds (VOCs) were measured with both on-line and off-line methods in Luoyang City in summer of 2019. The concentrations of nitrogen oxides (NOx, sum of NO and NO2) and O3 were simultaneously monitored. Fifty-seven VOCs measured in U.S. Photochemical Assessment Monitoring Station (PAMS) showed daily concentrations in a range of 14.5 ± 5.33 to 29.2 ± 11.2 ppbv in Luoyang, which were comparable with those in other Chinese megacities. The mass compositions of VOCs were determined, with comparatively low proportions of alkanes (<50%) but high fractions of photoreactive alkenes and alkyne. Source apportionment of VOCs was conducted by Hybrid Environmental Receptor Model (HERM). The results indicated that industrial (38.5%) and traffic (32.0%) were the two dominated pollution sources of VOCs in the urban, while the biogenic and residential sources had contributions of 15.8% and 13.8%, respectively. To further measure the O3 formation sensitivity and its source attribution, the WRF-CHEM model was adopted in this study. The variation of O3 between the observation and the stimulation using the local emission inventory showed an index of agreement (IOA) of 0.85. The simulation conducted by WRF-CHEM indicated an average of 43.5% of the O3 was associated with the regional transportation, revealing the importance of inter-regional prevention and control policy. Traffic and biogenic emissions were the two major pollution sources to an O3 episode occurred from July 21 to July 27, 2019 (when O3 concentration over 150 μg m-3) in Luoyang, with average contributions of 22.9% and 18.3%, respectively. The O3 isopleths proved that its formation in the atmosphere of Luoyang was in transitional regime and collectively controlled by both VOCs and NOx. This was different from the observations in main cities of NCP before implantations of strict emission controls. The isopleths additionally designated that the O3 formation regime would move forward or shift to NOx regime after a reduction of over 45% during the episode. Similar patterns were also reported in other Chinese megacities such as Beijing and Shanghai, due to the tightening of the NOx control policies. Our results do support that the simultaneous controls of NOx and VOCs were effective in reductions of tropospheric O3 in Luoyang. Meanwhile, joint regional control policies on the emissions of NOx and VOCs can potentially overwhelm the current O3 pollutions in China.
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Affiliation(s)
- Jian Sun
- Department of Environmental Science and Engineering, Xi'an Jiaotong University, Xi'an 710049, China; Key Lab of Aerosol Chemistry & Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710049, China
| | - Zhenxing Shen
- Department of Environmental Science and Engineering, Xi'an Jiaotong University, Xi'an 710049, China; Key Lab of Aerosol Chemistry & Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710049, China.
| | - Ruonan Wang
- Key Lab of Aerosol Chemistry & Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710049, China
| | - Guohui Li
- Key Lab of Aerosol Chemistry & Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710049, China
| | - Yue Zhang
- Department of Environmental Science and Engineering, Xi'an Jiaotong University, Xi'an 710049, China
| | - Bin Zhang
- Department of Environmental Science and Engineering, Xi'an Jiaotong University, Xi'an 710049, China
| | - Kun He
- Department of Environmental Science and Engineering, Xi'an Jiaotong University, Xi'an 710049, China
| | - Zhuoyue Tang
- Department of Environmental Science and Engineering, Xi'an Jiaotong University, Xi'an 710049, China
| | - Hongmei Xu
- Department of Environmental Science and Engineering, Xi'an Jiaotong University, Xi'an 710049, China
| | - Linli Qu
- Hong Kong Premium Services and Research Laboratory, Kowloon, Hong Kong Special Administrative Region
| | - Steven Sai Hang Ho
- Divison of Atmospheric Sciences, Desert Research Institute, Reno NV89512, United States
| | - Suixin Liu
- Key Lab of Aerosol Chemistry & Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710049, China
| | - Junji Cao
- Key Lab of Aerosol Chemistry & Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710049, China
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12
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Zhang L, Li H, Wu Z, Zhang W, Liu K, Cheng X, Zhang Y, Li B, Chen Y. Characteristics of atmospheric volatile organic compounds in urban area of Beijing: Variations, photochemical reactivity and source apportionment. J Environ Sci (China) 2020; 95:190-200. [PMID: 32653179 DOI: 10.1016/j.jes.2020.03.023] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 03/11/2020] [Accepted: 03/17/2020] [Indexed: 05/22/2023]
Abstract
Atmospheric volatile organic compounds (VOCs) were observed by an on-line gas chromatography-flame ionization detector monitoring system from November 2016 to August 2017 in Beijing. The average concentrations were winter (40.27 ± 25.25 μg/m3) > autumn (34.25 ± 19.90 µg/m3) > summer (32.53 ± 17.39 µg/m3) > spring (24.72 ± 17.22 µg/m3). Although benzene (15.70%), propane (11.02%), ethane (9.32%) and n-butane (6.77%) were the most abundant species, ethylene (14.07%) and propene (11.20%) were the key reactive species to ozone formation potential (OFP), and benzene, toluene, ethylbenzene, m-xylene + p-xylene and o-xylene (54.13%) were the most reactive species to secondary organic aerosol formation potential (SOAFP). The diurnal and seasonal variations indicated that diesel vehicle emission during early morning, gasoline vehicle emission at the traffic rush hours and coal burning during the heating period might be important sources. Five major sources were further identified by positive matrix factorization (PMF). The vehicle exhaust (gasoline exhaust and diesel exhaust) was found to be contributed most to atmospheric VOCs, with 43.59%, 41.91%, 50.45% and 43.91%, respectively in spring, summer, autumn and winter; while solvent usage contributed least, with 11.10%, 7.13%, 14.00% and 19.87%, respectively. Biogenic emission sources (13.11%) were only identified in summer. However, both vehicle exhaust and solvent usage were identified to be the key sources considering contributions to the OFP and SOAFP. Besides, the contributions of combustion during heating period and gasoline evaporation source during warm seasons to OFP and SOAFP should not be overlooked.
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Affiliation(s)
- Lihui Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; School of Environment and Safety Engineering, North University of China, Taiyuan 030051, China
| | - Hong Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; Collaborative Innovation Center on Atmospheric Environment and Equipment Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
| | - Zhenhai Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Weiqi Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Kankan Liu
- School of Environment and Safety Engineering, North University of China, Taiyuan 030051, China
| | - Xi Cheng
- Shenhua Group Zhungeer Energy Co., Ltd, Gangue Power Company, Ordos 017100, China
| | - Yujie Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Bin Li
- School of Environment and Safety Engineering, North University of China, Taiyuan 030051, China
| | - Yizhen Chen
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
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13
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Ding Y, Lu J, Liu Z, Li W, Chen J. Volatile organic compounds in Shihezi, China, during the heating season: pollution characteristics, source apportionment, and health risk assessment. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2020; 27:16439-16450. [PMID: 32124278 DOI: 10.1007/s11356-020-08132-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Accepted: 02/17/2020] [Indexed: 06/10/2023]
Abstract
From November 2018 to March 2019, the mixing ratios of 57 types of volatile organic compounds (VOCs) were measured using gas chromatography-mass spectrometry in Shihezi. The results depicted that the average mixing ratios of VOCs were 58.48 ppbv and alkanes (34.15 ppbv) showed the largest contribution, followed by ethyne (20.16 ppbv), alkenes (2.62 ppbv), and aromatics (1.55 ppbv). Based on the positive matrix factorization (PMF) model result, coal burning (39.83%), traffic-related exhaust (26.87%), liquefied petroleum gas/natural gas usage (LPG/NG) (17.32%), fuel evaporation and paint usage (9.02%), and industrial emission (6.96%) were distinguished. Secondary formation potential was applied to demonstrate the probability of secondary pollution; the results indicated that alkanes (27.30 ppbv) and alkenes (21.42 ppbv) played leading roles in ozone formation potential (OFP) and the contributions of alkanes (1.05 μg/m3) and aromatics (0.99 μg/m3) were nearly equal for secondary organic aerosol formation potential (SOAFP) under high-NOx condition. However, under a low-NOx condition, aromatics (2.12 μg/m3) dominated, and the contribution of alkanes (1.05 μg/m3) was lower. Monte Carlo simulation results showed that exposure to 1,3-butadiene and benzene may contribute potential carcinogenic risks to local residents; PMF results showed that reducing traffic-related and industrial emissions as well as coal burning was more effective in controlling carcinogenic risks. This study provides a crucial theoretical basis for decision-makers to minimize local air pollution more effectively.
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Affiliation(s)
- Yanzhou Ding
- Key Laboratory for Green Processing of Chemical Engineering of Xinjiang Production and Construction Corps/School of Chemistry and Chemical Engineering, Shihezi University, Shihezi, 832003, China
| | - Jianjiang Lu
- Key Laboratory for Green Processing of Chemical Engineering of Xinjiang Production and Construction Corps/School of Chemistry and Chemical Engineering, Shihezi University, Shihezi, 832003, China.
| | - Zilong Liu
- Key Laboratory for Green Processing of Chemical Engineering of Xinjiang Production and Construction Corps/School of Chemistry and Chemical Engineering, Shihezi University, Shihezi, 832003, China
| | - Weijun Li
- Shihezi Environmental Monitoring Station, Shihezi, 832000, China
| | - Jiadeng Chen
- Key Laboratory for Green Processing of Chemical Engineering of Xinjiang Production and Construction Corps/School of Chemistry and Chemical Engineering, Shihezi University, Shihezi, 832003, China
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14
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Han T, Ma Z, Xu W, Qiao L, Li Y, He D, Wang Y. Characteristics and source implications of aromatic hydrocarbons at urban and background areas in Beijing, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 707:136083. [PMID: 31863975 DOI: 10.1016/j.scitotenv.2019.136083] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 12/09/2019] [Accepted: 12/10/2019] [Indexed: 05/22/2023]
Abstract
The characteristics of benzene, toluene, ethylbenzene, and xylene (BTEX) concentrations, their temporal and spatial variations, and their source origins from September-December 2017 at an urban and a background site in Beijing, China were investigated. The averaged (±σ) total mixing ratios of benzene, toluene, ethylbenzene, m, p-xylenes, and o-xylene were 0.40 ± 0.39 ppbv, 0.31 ± 0.34 ppbv, 0.08 ± 0.07 ppbv, 0.08 ± 0.08 ppbv, and 0.05 ± 0.05 ppbv at the SDZ site, which were 63%, 79%, 83%, 85%, and 89% lower than those at the Chinese Academy of Meteorological Sciences site (CMA). It is worth noting that the average mixing ratios of BTEX at SDZ and CMA were 0.86 ± 1.03 ppbv and 3.38 ± 2.80 ppbv during the heating period (HP), which were 2.3% and 21.9% lower than those before the HP, a decrease that was mainly related to the frequent occurrence of strong northerly and northwesterly winds and low relative humidity (RH) during the HP. Obvious differences were also observed between the BTEX composition proportions at the SDZ and CMA sites. On average, benzene comprised 44% of the total BTEX at SDZ, whereas toluene was the largest contributor to the total BTEX at CMA, accounting for 37%. In addition, the contributions of C8 aromatics (the sum of ethylbenzene, m, p-xylenes, and o-xylene) at CMA (36%) were also higher than those at SDZ (21%), reflecting the different emission sources of the two sites. In addition, the BTEX species showed similar and pronounced diurnal profiles at SDZ and CMA, all characterized by much higher values at night than during the day. Diagnostic ratios and source implications suggested that SDZ was affected mainly by biomass/biofuel/coal burning, with substantially elevated benzene levels during the winter HP, whereas CMA was affected both by traffic-related emissions and biomass/biofuel/coal burning emissions. These findings suggest the necessity of regionally-tailored control strategies both to reduce BTEX levels and to mitigate their environmental impact. Further analysis of the backward trajectories revealed that the BTEX compounds varied greatly in terms of air mass origins, but generally exhibited high values for slow air masses passing over areas south of Beijing, with dominant contributions from benzene, toluene, and m, p-xylenes.
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Affiliation(s)
- Tingting Han
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China; Beijing Shangdianzi Regional Atmosphere Watch Station, Beijing 101507, China
| | - Zhiqiang Ma
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China; Beijing Shangdianzi Regional Atmosphere Watch Station, Beijing 101507, China.
| | - Wanyun Xu
- State Key Laboratory of Severe Weather &Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Lin Qiao
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China; Beijing Shangdianzi Regional Atmosphere Watch Station, Beijing 101507, China
| | - Yingruo Li
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China; Beijing Shangdianzi Regional Atmosphere Watch Station, Beijing 101507, China
| | - Di He
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China; Beijing Shangdianzi Regional Atmosphere Watch Station, Beijing 101507, China
| | - Ying Wang
- State Key Laboratory of Severe Weather &Key Laboratory for Atmospheric Chemistry, Institute of Atmospheric Composition, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
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15
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Liu Y, Song M, Liu X, Zhang Y, Hui L, Kong L, Zhang Y, Zhang C, Qu Y, An J, Ma D, Tan Q, Feng M. Characterization and sources of volatile organic compounds (VOCs) and their related changes during ozone pollution days in 2016 in Beijing, China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 257:113599. [PMID: 31796324 DOI: 10.1016/j.envpol.2019.113599] [Citation(s) in RCA: 81] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Revised: 11/07/2019] [Accepted: 11/08/2019] [Indexed: 06/10/2023]
Abstract
Concentrations of 99 volatile organic compounds (VOCs) were continuously measured online at an urban site in Beijing, China, in January, April, July, and October 2016. Characterization and sources of VOCs and their related changes during days with heavy ozone (O3) pollution were analysed. The total observed concentration of VOCs (TVOCs) was 44.0 ± 28.9 ppbv. The VOC pollution level has decreased in Beijing but remains higher than in other Chinese cities. Alkanes comprised the highest proportion among seven major sampled VOC groups. The concentrations and sources of ambient VOCs showed obvious temporal variations. Six emission sources were identified by the positive matrix factorization (PMF), including biomass burning, coal combustion, gasoline vehicles, diesel vehicles, solvent usage, and biogenic + secondary emissions. The combustion source was the key control factor for VOC reduction in Beijing. From the potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) model, Beijing, Tianjin, Hebei, Shanxi, Inner Mongolia, Shandong, and Henan were identified as major potential source regions of ambient VOCs. O3 formation was sensitive to VOCs in Beijing according to the VOC/NOx ratio (ppbC/ppbv, 8:1 threshold). High- and low-O3 days in July were identified, and high O3 levels were due to both enhanced VOC emission levels and meteorological conditions favourable to the production of O3. These findings provide evidence that the fuel combustion and regional transport have a great impact on concentrations and sources of VOCs in urban Beijing.
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Affiliation(s)
- Yafei Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Mengdi Song
- 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.
| | - Yuepeng Zhang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Lirong Hui
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, 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
| | - 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
| | - Depeng Ma
- Appraisal Center for Environment & Engineering, Ministry of Environment and Ecology, Beijing 100012, 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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16
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Source Apportionment of Volatile Organic Compounds (VOCs) during Ozone Polluted Days in Hangzhou, China. ATMOSPHERE 2019. [DOI: 10.3390/atmos10120780] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
A field sampling campaign of volatile organic compounds (VOCs) was conducted during ozone polluted days at three sites of botanic gardens (HP), industrial areas (XS), and traffic residential mixed areas (ZH) in Hangzhou. The sampling was performed using stainless steel canisters from 6:00 to 20:00 synchronously with a time interval of 2 h on 17 May, 26 June, 20 July, 24 August, and 26 September 2018. A total of 107 species of VOCs for each sample were quantified using two standard gases with a pre-concentrator coupled by GC/MS. The Positive Matrix Factorization (PMF) model was used to identify the major VOC sources and assess their contribution to VOC concentrations. The effects of VOCs on O3 formation were investigated, based on propylene-equivalent concentrations (Prop-E), ozone formation potential (OFP), and Smog Production Model (SPM). It was found that the concentration of ozone during the sampling days tended to be highest in the downwind area while the concentrations of VOCs and NO2 in HP were rather low. The most reactive species were isoprene, ethylene, m-xylene, toluene, and propylene. The average total VOC volume mixing ratios in HP, XS, and ZH were 32.00, 36.63, and 50.34 ppbv, respectively. Bimodal profiles of propane and n-butane were exhibited in ZH while unimodal diurnal variation of isoprene was performed in HP. Liquefied petroleum gas/natural gas (LPG/NG) usage, aged background, and secondary source were identified as the major contributors to total VOCs in Hangzhou, accounting for 19.65%, 15.53%, and 18.93%, respectively.
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Yang Y, Liu X, Zheng J, Tan Q, Feng M, Qu Y, An J, Cheng N. Characteristics of one-year observation of VOCs, NOx, and O 3 at an urban site in Wuhan, China. J Environ Sci (China) 2019; 79:297-310. [PMID: 30784453 DOI: 10.1016/j.jes.2018.12.002] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Revised: 11/27/2018] [Accepted: 12/05/2018] [Indexed: 05/22/2023]
Abstract
A continuous online observation of ozone and its precursors (NOx, VOCs) was carried out in central urban Wuhan from September 2016 to August 2017. The concentration levels of ozone, NOx, VOCs and their variations in urban Wuhan were analyzed, as well as effects of VOCs on ozone photochemical generation and the main controlling factors for ozone production. During the observation period, the average concentrations of ozone and NOx in Wuhan was 22.63 and 30.14 ppbv, respectively, and the average concentration of VOCs was 32.61 ppbv (42.3% alkanes, 13.0% alkenes, 10.0% aromatics, 7.3% acetylene, 9.9% OVOCs, and 10.5% halohydrocarbons). Ozone concentration was higher in spring and summer as compared with autumn and winter, wheras VOCs and NOx concentratios were lower in spring and summer but higher in autumn and winter. Aromatics and alkenes, two of VOCs species, showed the highest contributions to ozone formation potential in Wuhan (35.7% alkenes, 35.4 aromatics, 17.5% alkanes, 8.6% OVOCs, 1.6% halogenated hydrocarbons, and 1.4% acetylene). Among all VOCs species, those with the highest contribution were ethylene, m-xylene, toluene, propylene and o-xylene. The contribution of these five compounds to the total ozone formation potential concentration was 43.90%. Ozone-controlling factors in Wuhan changed within one day; during the early morning hours (6:00-9:00), VOCs/NOx was low, and ozone generation followed a VOCs-limited regime. However, during the peak time of ozone concentration (12:00-16:00), the ratio of VOCs/NOx was relatively high, suggesting that ozone generation followed a NOx-limited regime.
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Affiliation(s)
- Yichang Yang
- School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
| | - Xingang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China.
| | - Jun Zheng
- School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.
| | - Qinwen Tan
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Miao Feng
- Chengdu Academy of Environmental Sciences, Chengdu 610072, 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
| | - Nianliang Cheng
- Beijing Municipal Environmental Monitoring Center, 100048 Beijing, ,China
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Zeng P, Lyu XP, Guo H, Cheng HR, Jiang F, Pan WZ, Wang ZW, Liang SW, Hu YQ. Causes of ozone pollution in summer in Wuhan, Central China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2018; 241:852-861. [PMID: 29913412 DOI: 10.1016/j.envpol.2018.05.042] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2017] [Revised: 05/12/2018] [Accepted: 05/14/2018] [Indexed: 05/16/2023]
Abstract
In August 2016, continuous measurements of volatile organic compounds (VOCs) and trace gases were conducted at an urban site in Wuhan. Four high-ozone (O3) days and twenty-seven non-high-O3 days were identified according to the China's National Standard Level II (∼100 ppbv). The occurrence of high-O3 days was accompanied by tropical cyclones. Much higher concentrations of VOCs and carbon monoxide (CO) were observed on the high-O3 days (p < 0.01). Model simulations revealed that vehicle exhausts were the dominant sources of VOCs, contributing 45.4 ± 5.2% and 37.3 ± 2.9% during high-O3 and non-high-O3 days, respectively. Both vehicle exhausts and stationary combustion made significantly larger contributions to O3 production on high-O3 days (p < 0.01). Analysis using a chemical transport model found that local photochemical formation accounted for 74.7 ± 5.8% of the daytime O3, around twice the regional transport (32.2 ± 5.4%), while the nighttime O3 was mainly attributable to regional transport (59.1 ± 9.9%). The local O3 formation was generally limited by VOCs in urban Wuhan. To effectively control O3 pollution, the reduction ratio of VOCs to NOx concentrations should not be lower than 0.73, and the most efficient O3 abatement could be achieved by reducing VOCs from vehicle exhausts. This study contributes to the worldwide database of O3-VOC-NOx sensitivity research. Its findings will be helpful in formulating and implementing emission control strategies for dealing with O3 pollution in Wuhan.
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Affiliation(s)
- P Zeng
- School of Resource and Environmental Sciences, Wuhan University, Wuhan 430072, China; Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - X P Lyu
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - H Guo
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China.
| | - H R Cheng
- School of Resource and Environmental Sciences, Wuhan University, Wuhan 430072, China.
| | - F Jiang
- International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - W Z Pan
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong, China
| | - Z W Wang
- School of Resource and Environmental Sciences, Wuhan University, Wuhan 430072, China
| | - S W Liang
- Wuhan Environment Monitoring Center, Wuhan 430022, China
| | - Y Q Hu
- Wuhan Environment Monitoring Center, Wuhan 430022, China
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Hu R, Liu G, Zhang H, Xue H, Wang X. Levels, characteristics and health risk assessment of VOCs in different functional zones of Hefei. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2018; 160:301-307. [PMID: 29857234 DOI: 10.1016/j.ecoenv.2018.05.056] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Revised: 05/17/2018] [Accepted: 05/22/2018] [Indexed: 06/08/2023]
Abstract
In order to study the characteristics and health risk of VOCs in the ambient air in the typical developing cities in China, the research was conducted in five functional zones in Hefei from September 2016 to January 2017. The average concentrations of total measured VOCs in traffic zone was the largest (85.94 μg m-3), followed by industrial zone (64.84 μg m-3), development zone (58.92 μg m-3), resident zone (57.31 μg m-3), and background zone (54.94 μg m-3). Cl-VOCs were most abundant species in chlorinated VOCs (85.06%), which showed much higher level in industrial zone. the mean value of BTEX found in presented study was 65.19 μg m-3. Based on the specific VOC ratio method (B/T), the observed sites were greatly affected by the traffic emissions. The ratios of T/B, E/B and X/B were 1.15, 1.35 and 0.47, respectively, possibly due to the aging air mass. Carcinogenic risks for benzene, carbon tetrachloride, trichloroethylene, 1, 2-dichloroethane and chloroform were higher than the general acceptable risk level of 1.00 × 10-6. Potential non-carcinogenic risk assessment showed that hazard quotient (HQ) of 10 VOCs not exceeded unity, but the hazard risk index (HI) at site ED, LY, YH and HD were both higher than 1.
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Affiliation(s)
- Ruoyu Hu
- CAS Key Laboratory of Crust-Mantle Materials and Environment, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China; State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, The Chinese Academy of Sciences, Xi'an, Shaanxi 710075, China
| | - Guijian Liu
- CAS Key Laboratory of Crust-Mantle Materials and Environment, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China; State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, The Chinese Academy of Sciences, Xi'an, Shaanxi 710075, China.
| | - Hong Zhang
- CAS Key Laboratory of Crust-Mantle Materials and Environment, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Huaqin Xue
- CAS Key Laboratory of Crust-Mantle Materials and Environment, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
| | - Xin Wang
- CAS Key Laboratory of Crust-Mantle Materials and Environment, School of Earth and Space Sciences, University of Science and Technology of China, Hefei, Anhui 230026, China
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An J, Wang J, Zhang Y, Zhu B. Source Apportionment of Volatile Organic Compounds in an Urban Environment at the Yangtze River Delta, China. ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2017; 72:335-348. [PMID: 28190079 DOI: 10.1007/s00244-017-0371-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2016] [Accepted: 01/20/2017] [Indexed: 06/06/2023]
Abstract
Volatile organic compounds (VOCs) were collected continuously during June-August 2013 and December 2013-February 2014 at an urban site in Nanjing in the Yangtze River Delta. The positive matrix factorization receptor model was used to analyse the sources of VOCs in different seasons. Eight and seven sources were identified in summer and winter, respectively. In summer and winter, the dominant sources of VOCs were vehicular emissions, liquefied petroleum gas/natural gas (LPG/NG) usage, solvent usage, biomass/biofuel burning, and industrial production. In summer, vehicular emissions made the most significant contribution to ambient VOCs (38%), followed by LPG/NG usage (20%), solvent usage (19%), biomass/biofuel burning (13%), and industrial production (10%). In winter, LPG/NG usage accounted for 36% of ambient VOCs, whereas vehicular emissions, biomass/biofuel burning, industrial production and solvent usage contributed 30, 18, 9, and 6%, respectively. The contribution of LPG/NG usage in winter was approximately four times that in summer, whereas the contribution from biomass/biofuel burning in winter was more than twice that in summer. The sources related to vehicular emissions and LPG/NG usages were important. Using conditional probability function analysis, the VOC sources were mainly associated with easterly, northeasterly and southeasterly directions, pointing towards the major expressway and industrial area. Using the propylene-equivalent method, paint and varnish (23%) was the highest source of VOCs in summer and biomass/biofuel burning (36%) in winter. Using the ozone formation potential method, the most important source was biomass/biofuel burning (32% in summer and 47% in winter). The result suggests that the biomass/biofuel burning and paint and varnish play important roles in controlling ozone chemical formation in Nanjing.
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Affiliation(s)
- Junlin An
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
| | - Junxiu Wang
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Yuxin Zhang
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Bin Zhu
- Key Laboratory of Meteorological Disaster, Ministry of Education (KLME)/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)/Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
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Mehrizadeh H, Niaei A, Tseng HH, Salari D, Khataee A. Synthesis of ZnFe2O4 nanoparticles for photocatalytic removal of toluene from gas phase in the annular reactor. J Photochem Photobiol A Chem 2017. [DOI: 10.1016/j.jphotochem.2016.08.028] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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An J, Shi Y, Wang J, Zhu B. Temporal Variations of O3 and NO x in the Urban Background Atmosphere of Nanjing, East China. ARCHIVES OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2016; 71:224-234. [PMID: 27272535 DOI: 10.1007/s00244-016-0290-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/18/2016] [Accepted: 05/30/2016] [Indexed: 06/06/2023]
Abstract
Rapid economic growth has given rise to a significant increase in ozone (O3)-precursor emissions in many regions of China. An improved understanding of O3 formation in response to different precursor emissions is imperative to address the highly nonlinear O3 problem and to provide a solid scientific basis for efficient O3 abatement in these regions. To this end, this study was performed in Nanjing using a set of observational data from June 1, 2013, to May 31, 2014. The results showed that O3 concentrations were positively correlated with wind speed and temperature and were significantly negatively correlated with relative humidity. The highest monthly daytime, nighttime, and daily average O3 concentrations were observed in summer with values of approximately 46, 18 and 30 ppb, respectively. The lowest O3 concentrations were observed in November through January with values as low as 17, 4, and 9 ppb for the daytime, nighttime, and daily concentrations, respectively. The highest daytime average NO and NO2 concentrations were observed in December, whereas the lowest concentrations were observed in July. A unimodal O3 peak was observed with the highest O3 levels in summer followed by spring and then autumn; the lowest levels observed in the winter. The O3 concentration reached maximum levels at 14:00 to 15:00 h (local standard time). It was found that the crossover occurred with approximately several hours difference with the earliest occurring in summer (06:00 h) followed by spring (08:00 h), autumn (09:00 h), and winter (10:30 h). Furthermore, the highest constant rate of O3 accumulation was observed in summer (5.6 ppb/h) followed by autumn (4.8 ppb/h), spring (4.5 ppb/h), and winter (2.7 ppb/h). The oxidant intercept ranged from 28.4 ppb in January to 58.6 ppb in June, although the slope also shows substantial variation from 0.18 in June to 0.67 in August. The weekend effect is stronger in spring and summer than in autumn and winter and is more intense on Sundays than on Saturdays. Thus, the decrease of O3 levels during weekends suggests that it may be NO x -sensitive.
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Affiliation(s)
- Junlin An
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
| | - Yuanzhe Shi
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Junxiu Wang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Bin Zhu
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
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An J, Zou J, Wang J, Lin X, Zhu B. Differences in ozone photochemical characteristics between the megacity Nanjing and its suburban surroundings, Yangtze River Delta, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2015; 22:19607-17. [PMID: 26272292 DOI: 10.1007/s11356-015-5177-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2015] [Accepted: 08/07/2015] [Indexed: 05/22/2023]
Abstract
Rapid economic growth has led to a significant increase in ozone (O3) precursor emissions in many regions of China. Improved understanding of O3 formation in response to different precursor emissions is imperative to address the highly nonlinear O3 problem and to provide a solid scientific basis for efficient O3 abatement in these regions. A comparative study was conducted in summer using a set of observational data at urban and suburban sites in Nanjing. The results showed that high O3 concentrations were frequently encountered at both sites. The probability distributions of O3 in both sites show a fair resemblance to each other, suggesting strong regional mixing over the polluted Nanjing. A distinction between the characteristics of O3 precursors has been found at different sites. During the observation period, O3 concentrations varied monthly, reaching a minimum in June and peaking in August. The daily maximum O3 concentration was found to exceed 80 ppb for 27 days at residential area (RA), whereas it only exceeded 80 ppb for 22 days at industrial area (IA), 16 days at traffic area (TA), and 14 days at commercial area (CA). This pattern suggests a higher continuous ozone exposure risk at RA. The daily maximum O3 concentrations at different sites were 135.1 ppb (IA), 134.1 ppb (RA), 129.2 ppb (TA), and 110.6 ppb (CA), respectively. The daily maximum O3 concentration occurred at 16:00 in IA, at 17:00 in TA and CA, and at 18:00 in RA. Nitrogen dioxide (NO2) and carbon monoxide (CO) showed similar double-peak diurnal cycles. NO2 showed maximum values in June and minimum values in July. CO showed a similar diurnal variation to NO2. This effect may be explained by their common sources and the similar chemical losses. During the day, O3 tended to rapidly increase during the morning, reaching a maximum value of 9-11 ppb h(-1). The differences in O3 and NO2 between workdays and weekends were small. The CO levels were higher on weekdays than on weekends in urban areas and were higher on weekends than on weekdays in suburban areas. A sensitivity study performed with an observation-based model (OBM) showed alkenes to be the largest contributor to O3 production. The production of O3 in the Nanjing area is generally limited by volatile organic compounds (VOCs), whereas high nitric oxide (NO) concentrations suppress O3 concentrations.
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Affiliation(s)
- Junlin An
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China.
| | - Jianan Zou
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Junxiu Wang
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Xu Lin
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
| | - Bin Zhu
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China
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