1
|
Cui Y, Liu B, Yang Y, Kang S, Wang F, Xu M, Wang W, Feng Y, Hopke PK. Primary and oxidative source analyses of consumed VOCs in the atmosphere. JOURNAL OF HAZARDOUS MATERIALS 2024; 476:134894. [PMID: 38909463 DOI: 10.1016/j.jhazmat.2024.134894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2024] [Revised: 05/27/2024] [Accepted: 06/11/2024] [Indexed: 06/25/2024]
Abstract
Consumed VOCs are the compounds that have reacted to form ozone and secondary organic aerosol (SOA) in the atmosphere. An approach that can apportion the contributions of primary sources and reactions to the consumed VOCs was developed in this study and applied to hourly VOCs data from June to August 2022 measured in Shijiazhuang, China. The results showed that petrochemical industries (36.9 % and 51.7 %) and oxidation formation (20.6 % and 35.6 %) provided the largest contributions to consumed VOCs and OVOCs during the study period, whereas natural gas (5.0 % and 7.6 %) and the mixed source of liquefied petroleum gas and solvent use (3.1 % and 4.2 %) had the relatively low contributions. Compared to the non-O3 pollution (NOP) period, the contributions of oxidation formation, petrochemical industries, and the mixed source of gas evaporation and vehicle emissions to the consumed VOCs during the O3 pollution (OP) period increased by 2.8, 3.8, and 9.3 times, respectively. The differences in contributions of liquified petroleum gas and solvent use, natural gas, and combustion sources to consumed VOCs between OP and NOP periods were relatively small. Transport of petrochemical industries emissions from the southeast to the study site was the primary consumed pathway for VOCs emitted from petrochemical industries.
Collapse
Affiliation(s)
- Yaqi Cui
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China.
| | - Yufeng Yang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Sicong Kang
- Beijing Make Environment Science & Technology Co., Ltd., Beijing 100083, China
| | - Fuquan Wang
- Beijing Make Environment Science & Technology Co., Ltd., Beijing 100083, China
| | - Man Xu
- Shijiazhuang Environmental Prediction Center, Shijiazhuang 050022, China
| | - Wei Wang
- Shijiazhuang Environmental Prediction Center, Shijiazhuang 050022, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Philip K Hopke
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA; Institute for a Sustainable Environment, Clarkson University, Potsdam, NY 13699, USA
| |
Collapse
|
2
|
Wu Y, Liu B, Meng H, Wang F, Li S, Xu M, Shi L, Zhang S, Feng Y, Hopke PK. Unexpected changes in source apportioned results derived from different ambient VOC metrics. ENVIRONMENT INTERNATIONAL 2024; 190:108910. [PMID: 39094407 DOI: 10.1016/j.envint.2024.108910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Revised: 07/17/2024] [Accepted: 07/23/2024] [Indexed: 08/04/2024]
Abstract
Although most source apportionments of VOCs use mixing ratios, about 23 % of published studies use mass concentrations. Thus, systematically exploring the changes in VOC source apportioned results caused by metric differences is important to assess the differences in key precursor apportionment results given the observed increases in O3 pollution situation. Different monitoring instruments measured hourly VOC volumetric concentrations in three typical Chinese cities (i.e., Qingdao, Shijiazhuang, and Zhumadian). Converting volumetric to mass concentrations under standard and/or actual temperature-pressure conditions, VOC values with different metrics were obtained. The impacts of different metrics on the source apportionments were then investigated. Compared to the positive matrix factorization of the volumetric data (VC-PMF), the VOC species concentrations with low relative molecular mass (RMM) in the factor profiles substantially decreased in mass data analyses (MC-PMF). However, those species with high RMM substantially increased. There were no substantial differences in the apportioned source contributions based on standard and actual condition mass concentrations. However, the high-low rankings of percent contributions apportioned using the volumetric and mass data produced substantial differences. Compared with the VC-PMF results, the percent contributions of sources dominated by species with low RMM (e.g., natural gas usage and mixed sources containing natural gas usage) apportioned by MC-PMF decreased, while those of sources that emitted high RMM species (e.g., solvent usage and mixed sources containing solvent usage) increased. Source apportionments based on the volumetric concentration data had more practical significance compared to the mass concentration data results for control strategy development since the mass data analyses created issues.
Collapse
Affiliation(s)
- Yutong Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China.
| | - He Meng
- Qingdao Eco-environment Monitoring Center of Shandong Province, Qingdao 266003, China
| | - Fuquan Wang
- Beijing Make Environment Science & Technology Co., Ltd., Beijing 100083, China
| | - Sen Li
- Zhumadian Ecological and Environmental Monitoring Center of Henan Province, Zhumadian 463000, China
| | - Man Xu
- Shijiazhuang Environmental Prediction Center, Shijiazhuang 050022, China
| | - Laiyuan Shi
- Qingdao Eco-environment Monitoring Center of Shandong Province, Qingdao 266003, China
| | - Songfeng Zhang
- Zhumadian Municipal Ecology and Environment Bureau, Zhumadian 463000, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Philip K Hopke
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY 14642, USA; Institute for a Sustainable Environment, Clarkson University, Potsdam, NY 13699, USA
| |
Collapse
|
3
|
Pan L, Cai J, Liu L, Liu Z, Chen K, Gao P, Jiang X, Ren J. Ambient air pollution decreased normal fertilization rate via the mediation of seminal prosaposin. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 282:116713. [PMID: 39002374 DOI: 10.1016/j.ecoenv.2024.116713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Revised: 06/07/2024] [Accepted: 07/08/2024] [Indexed: 07/15/2024]
Abstract
OBJECTIVE This study focuses on the association between seminal concentration of prosaposin and ambient air pollutants and whether the association affects the normal fertilization rate in vitro fertilization (IVF) treatment. METHODS The cohort of 323 couple participants aged 22-46 was recruited from Jan. 2013 to Jun. 2018. At enrollment, resident address information was obtained and semen parameters of male counterparts were evaluated according to WHO criteria. We used inverse distance weighting interpolation to estimate the levels of ambient pollutants (SO2, O3, CO, NO2, PM2.5, and PM10) in the surrounding area. The exposure of each participant was estimated based on the data gathered from air quality monitoring stations and their home address over various periods (0-9, 10-14, and 0-90 days) before semen sampling. The generalized linear regression model (GLM) and the Bayesian kernel machine regression (BKMR) were used to analyze the associations between pollutants, semen parameters, prosaposin, and normal fertilization. Additionally, the mediating effect of prosaposin and semen parameters on the link between pollutants and normal fertilization was investigated. RESULTS GLM and BKMR showed exposure to ambient air pollutants was all associated with the concentration of seminal prosaposin, among them, O3 and CO were also associated with normal fertilization (-0.10, 95 %CI: -0.13, -0.06; -26.43, 95 %CI: -33.79, -19.07). Among the semen parameters, only the concentration of prosaposin and total motile sperm count (TMC) was associated with normal fertilization (0.059, 95 %CI: 0.047, 0.071; 0.016, 95 %CI: 0.012, 0.020). Mediation analysis showed that prosaposin played a stronger mediating role than TMC in the relationship between short-term exposure to O3 and fertilization (66.83 %, P<0.001 versus 3.05 %, P>0.05). CONCLUSION Seminal plasma prosaposin showed a stronger meditating effect reflect the correlation between ambient air pollutants and normal fertilization rate than conventional semen parameters, which may be used as one of the indicators between pollution and fertilization in IVF.
Collapse
Affiliation(s)
- Luxiang Pan
- Reproductive Medicine Center, Xiamen University Affiliated Chenggong Hospital, Xiamen, Fujian, China
| | - Jiali Cai
- Reproductive Medicine Center, Xiamen University Affiliated Chenggong Hospital, Xiamen, Fujian, China; School of Medicine, Xiamen University, Xiamen, Fujian, China
| | - Lanlan Liu
- Reproductive Medicine Center, Xiamen University Affiliated Chenggong Hospital, Xiamen, Fujian, China
| | - Zhenfang Liu
- Reproductive Medicine Center, Xiamen University Affiliated Chenggong Hospital, Xiamen, Fujian, China
| | - Kaijie Chen
- Reproductive Medicine Center, Xiamen University Affiliated Chenggong Hospital, Xiamen, Fujian, China
| | - Peng Gao
- Medical Quality Management Department, Xiamen University Affiliated Chenggong Hospital, Xiamen, Fujian, China
| | - Xiaoming Jiang
- Reproductive Medicine Center, Xiamen University Affiliated Chenggong Hospital, Xiamen, Fujian, China.
| | - Jianzhi Ren
- Reproductive Medicine Center, Xiamen University Affiliated Chenggong Hospital, Xiamen, Fujian, China.
| |
Collapse
|
4
|
Besis A, Margaritis D, Samara C, Bekiaris E. Volatile Organic Compounds on Rhodes Island, Greece: Implications for Outdoor and Indoor Human Exposure. TOXICS 2024; 12:486. [PMID: 39058138 PMCID: PMC11280855 DOI: 10.3390/toxics12070486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Revised: 06/13/2024] [Accepted: 06/20/2024] [Indexed: 07/28/2024]
Abstract
Volatile organic compounds (VOC) are considered a class of pollutants with a significant presence in indoor and outdoor air and serious health effects. The aim of this study was to measure and evaluate the levels of outdoor and indoor VOCs at selected sites on Rhodes Island, Greece, during the cold and warm periods of 2023. Spatial and seasonal variations were evaluated; moreover, cancer and non-cancer inhalation risks were assessed. For this purpose, simultaneous indoor-outdoor air sampling was carried out on the island of Rhodes. VOCs were determined by Thermal Desorption-Gas Chromatography/Mass Spectroscopy (TD-GC/MS). Fifty-six VOCs with frequencies ≥ 50% were further considered. VOC concentrations (∑56VOCs) at all sites were found to be higher in the warm period. In the warm and cold sampling periods, the highest concentrations were found at the port of Rhodes City, while total VOC concentrations were dominated by alkanes. The Positive Matrix Factorization (PMF) model was applied to identify the VOC emission sources. Non-cancer and cancer risks for adults were within the safe levels.
Collapse
Affiliation(s)
- Athanasios Besis
- Centre for Research and Technology Hellas (CERTH)/Hellenic Institute of Transport (HIT), GR-57001 Thessaloniki, Greece; (D.M.); (E.B.)
- Environmental Pollution Control Laboratory, Department of Chemistry, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece;
| | - Dimitrios Margaritis
- Centre for Research and Technology Hellas (CERTH)/Hellenic Institute of Transport (HIT), GR-57001 Thessaloniki, Greece; (D.M.); (E.B.)
| | - Constantini Samara
- Environmental Pollution Control Laboratory, Department of Chemistry, Aristotle University of Thessaloniki, GR-54124 Thessaloniki, Greece;
| | - Evangelos Bekiaris
- Centre for Research and Technology Hellas (CERTH)/Hellenic Institute of Transport (HIT), GR-57001 Thessaloniki, Greece; (D.M.); (E.B.)
| |
Collapse
|
5
|
Wang Y, Meng Z, Wei S, Li X, Su Z, Jiang Y, Wu H, Pan H, Wang J, Zhou Q, Qiao Y, Fan Y. Urinary volatile organic compound metabolites and COPD among US adults: mixture, interaction and mediation analysis. Environ Health 2024; 23:45. [PMID: 38702703 PMCID: PMC11067234 DOI: 10.1186/s12940-024-01086-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 04/29/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND Volatile organic compounds (VOCs) encompass hundreds of high production volume chemicals and have been reported to be associated with adverse respiratory outcomes such as chronic obstructive pulmonary disease (COPD). However, research on the combined toxic effects of exposure to various VOCs on COPD is lacking. We aimed to assess the effect of VOC metabolite mixture on COPD risk in a large population sample. METHODS We assessed the effect of VOC metabolite mixture on COPD risk in 5997 adults from the National Health and Nutrition Examination Survey (NHANES) from 2011 to 2020 (pre-pandemic) using multivariate logistic regression, Bayesian weighted quantile sum regression (BWQS), quantile-based g-Computation method (Qgcomp), and Bayesian kernel machine regression (BKMR). We explored whether these associations were mediated by white blood cell (WBC) count and total bilirubin. RESULTS In the logistic regression model, we observed a significantly increased risk of COPD associated with 9 VOC metabolites. Conversely, N-acetyl-S-(benzyl)-L-cysteine (BMA) and N-acetyl-S-(n-propyl)-L-cysteine (BPMA) showed insignificant negative correlations with COPD risk. The overall mixture exposure demonstrated a significant positive relationship with COPD in both the BWQS model (adjusted odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.06, 1.58) and BKMR model, and with marginal significance in the Qgcomp model (adjusted OR = 1.22, 95% CI: 0.98, 1.52). All three models indicated a significant effect of the VOC metabolite mixture on COPD in non-current smokers. WBC count mediated 7.1% of the VOC mixture associated-COPD in non-current smokers. CONCLUSIONS Our findings provide novel evidence suggesting that VOCs may have adverse associations with COPD in the general population, with N, N- Dimethylformamide and 1,3-Butadiene contributing most. These findings underscore the significance of understanding the potential health risks associated with VOC mixture and emphasize the need for targeted interventions to mitigate the adverse effects on COPD risk.
Collapse
Affiliation(s)
- Ying Wang
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Zhaowei Meng
- Department of Nuclear Medicine, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Sen Wei
- Department of Lung Cancer Surgery, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Xuebing Li
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Department of Lung Cancer Surgery, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Zheng Su
- Department of Tobacco Control and Prevention of Respiratory Disease, Center of Respiratory Medicine, China-Japan Friendship Hospital, Beijing, China
| | - Yong Jiang
- National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China
| | - Heng Wu
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Department of Lung Cancer Surgery, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Hongli Pan
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Department of Lung Cancer Surgery, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jing Wang
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Department of Lung Cancer Surgery, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Qinghua Zhou
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Department of Lung Cancer Surgery, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China
- Sichuan Lung Cancer Institute, Sichuan Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Youlin Qiao
- National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, 100021, Beijing, China
- Center of Global Health, School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, 100730, Beijing, China
| | - Yaguang Fan
- Tianjin Key Laboratory of Lung Cancer Metastasis and Tumor Microenvironment, Department of Lung Cancer Surgery, Tianjin Lung Cancer Institute, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| |
Collapse
|
6
|
Frischmon C, Hannigan M. VOC source apportionment: How monitoring characteristics influence positive matrix factorization (PMF) solutions. ATMOSPHERIC ENVIRONMENT: X 2024; 21:100230. [PMID: 38577261 PMCID: PMC10993988 DOI: 10.1016/j.aeaoa.2023.100230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Abstract
Positive matrix factorization (PMF) can be used to develop more targeted air quality mitigation strategies by identifying major sources of a pollutant in an area. This technique is dependent, however, on the ability of PMF to resolve factors that accurately represent all sources of that pollutant in an area. We investigated how the accuracy of PMF solutions might be influenced by monitoring data characteristics, such as temporal resolution, monitoring location, and species composition, to better inform the use of PMF in VOC mitigation strategies. We applied PMF to five VOC monitoring programs collected within a four-year period in Colorado and found generally consistent factors, which we identified as oil extraction, processing, and evaporation; natural gas; vehicle exhaust; and liquid gasoline/short-lived oil and gas. The main determinant influencing whether or not a dataset resolved each of these sources was whether the dataset had a comprehensive list of VOC species covering key species of each source. Pollution spikes were not well-modeled in any of the solutions. Hyperlocal and volatile chemical product factors expected to be resolved in the industrialized, urban location were also missing, highlighting three limitations of PMF analysis. Wind direction dependence and diurnal trends aided in source identification, suggesting that high-time resolution data is important for developing actionable PMF results. Based on these findings, we recommend that air monitoring for PMF-informed VOC mitigation efforts include high temporal resolution and a comprehensive array of VOC species.
Collapse
Affiliation(s)
- Caroline Frischmon
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, 80309, USA
| | - Michael Hannigan
- Department of Mechanical Engineering, University of Colorado Boulder, Boulder, CO, 80309, USA
| |
Collapse
|
7
|
Yuan Q, Zhang Z, Chen Y, Hui L, Wang M, Xia M, Zou Z, Wei W, Ho KF, Wang Z, Lai S, Zhang Y, Wang T, Lee S. Origin and transformation of volatile organic compounds at a regional background site in Hong Kong: Varied photochemical processes from different source regions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 908:168316. [PMID: 37949123 DOI: 10.1016/j.scitotenv.2023.168316] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 10/29/2023] [Accepted: 11/01/2023] [Indexed: 11/12/2023]
Abstract
Volatile organic compounds (VOCs) are important gaseous constituents in the troposphere, impacting local and regional air quality, human health, and climate. Oxidation of VOCs, with the participation of nitrogen oxides (NOx), leads to the formation of tropospheric ozone (O3). Accurately apportioning the emission sources and transformation processes of ambient VOCs, and effectively estimation of OH reactivity and ozone formation potential (OFP) will play an important role in reducing O3 pollution in the atmosphere and improving public health. In this study, field measurements were conducted at a regional background site (Hok Tsui; HT) in Hong Kong from October to November 2020 with proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS). VOC data coupled with air mass back trajectory cluster analysis and receptor modelling were applied to reveal the pollution pattern, emission sources and transformation of ambient VOCs at HT in autumn 2020. Seven sources were identified by positive matrix factorization (PMF) analysis, namely vehicular + industrial, solvent usage, primary oxygenated VOCs (OVOCs), secondary OVOCs 1, secondary OVOCs 2 (aged), biogenic emissions, and background + biomass burning. Secondary formation and vehicular + industrial emissions are the vital sources of ambient VOCs at HT supersite, contributing to 20.8 % and 46.7 % of total VOC mixing ratios, respectively. Integrated with backward trajectory analysis and correlations of VOCs with their oxidation products, short-range transport of air masses from inland regions of southeast China brought high levels of total VOCs but longer-range transport of air masses brought more secondary OVOCs in aged air masses. Photolysis of OVOCs was the most important contributor to OH reactivity and OFP, among which aldehyde was the dominant contributor. The results of this study highlight the photochemical processing of VOCs from different source regions which should be considered in strategy making for pollution reduction.
Collapse
Affiliation(s)
- Qi Yuan
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, Hong Kong
| | - Zhuozhi Zhang
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, Hong Kong
| | - Yi Chen
- Department of Chemistry, The Hong Kong University of Science and Technology, Hong Kong 999077, Hong Kong
| | - Lirong Hui
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong 999077, Hong Kong
| | - Meng Wang
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, Hong Kong
| | - Men Xia
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, Hong Kong; Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki 00014, Finland
| | - Zhouxing Zou
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, Hong Kong
| | - Wan Wei
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, Hong Kong
| | - Kin Fai Ho
- School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong 999077, Hong Kong
| | - Zhe Wang
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Hong Kong 999077, Hong Kong
| | - Senchao Lai
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Yingyi Zhang
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Tao Wang
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, Hong Kong
| | - Shuncheng Lee
- Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, Hong Kong.
| |
Collapse
|
8
|
Liu Y, Yin S, Zhang S, Ma W, Zhang X, Qiu P, Li C, Wang G, Hou D, Zhang X, An J, Sun Y, Li J, Zhang Z, Chen J, Tian H, Liu X, Liu L. Drivers and impacts of decreasing concentrations of atmospheric volatile organic compounds (VOCs) in Beijing during 2016-2020. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167847. [PMID: 37844645 DOI: 10.1016/j.scitotenv.2023.167847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 10/06/2023] [Accepted: 10/13/2023] [Indexed: 10/18/2023]
Abstract
China has implemented various policies and measures for controlling air pollutants. However, our knowledge of the long-term trends in ambient volatile organic compounds (VOCs) after the implementation of these action plans in China remains limited. To address this, we conducted a five-year analysis (2016-2020) of VOC compositions and concentrations in Beijing. The annual VOC concentration decreased from 44.0 ± 28.8 to 26.2 ± 16.4 ppbv, with alkanes being the most prevalent group. The annual average concentrations of alkenes, alkynes, and aromatics have experienced a significant decrease of over 50 %. Seasonal variations indicated higher VOC concentrations in winter and autumn, with more significant reductions observed in winter and autumn. The impact of meteorological conditions caused variations in VOC reductions during the Chinese Spring Festival. Satellite-based measurements of formaldehyde (HCHO) columns confirmed the reduction of VOC emissions during the Coronavirus (COVID-19) lockdown. The normalized annual average VOC concentration decreased by 2.9ppbv yr-1 from 2016 to 2020, and emission reduction contributed to 58.8 % of VOC reduction from 2016 to 2020 after meteorological normalization, indicating the effectiveness of implemented control measures. Based on receptor model, vehicle emissions and industrial sources were identified as the largest contributors to VOC concentrations. Vehicle emissions, liquefied petroleum gas/natural gas (LPG/NG) use, and coal combustion were major drivers of VOC reduction. Potential source region analysis revealed that air masses transported from northwestern and southern regions significantly contributed to VOC concentrations in Beijing. The range of source regions shrunk in both northwestern and southern regions with the reduction in VOC concentrations. The annual variations of ozone formation potential indicated a significant decrease in VOC reactivities through emission control. These results could provide insights into future emission control and coordinated efforts to improve PM2.5 and ozone levels in China.
Collapse
Affiliation(s)
- Yafei Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China; Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Shijie Yin
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Siqing Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Wei Ma
- Aerosol and Haze Laboratory, Advanced Innovation Center for Soft Matter Science and Engineering, Beijing University of Chemical Technology, Beijing 100029, China
| | - Xin Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Peipei Qiu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Chenlu Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Guangpeng Wang
- Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China
| | - Dongli Hou
- Ecology Environment Monitoring Center of Hebei Province, Shijiazhuang 050000, China
| | - Xiang Zhang
- Ecology Environment Monitoring Center of Hebei Province, Shijiazhuang 050000, 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
| | - Yele Sun
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Jie Li
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Ziyin Zhang
- Institute of Urban Meteorology, China Meteorological Administration, Beijing 100089, China
| | - Jing Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Hezhong Tian
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Xingang Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China.
| | - Lianyou Liu
- Key Laboratory of Environmental Change and Natural Disaster, Ministry of Education, Beijing Normal University, Beijing 100875, China.
| |
Collapse
|
9
|
Wu Y, Liu B, Meng H, Dai Q, Shi L, Song S, Feng Y, Hopke PK. Changes in source apportioned VOCs during high O 3 periods using initial VOC-concentration-dispersion normalized PMF. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 896:165182. [PMID: 37385502 DOI: 10.1016/j.scitotenv.2023.165182] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 06/11/2023] [Accepted: 06/26/2023] [Indexed: 07/01/2023]
Abstract
Ambient volatile organic compounds (VOCs) concentrations are affected by emissions, dispersion, and chemistry. This work developed an initial concentration-dispersion normalized PMF (ICDN-PMF) to reflect the changes in source emissions. The effects of photochemical losses for VOC species were corrected by estimating the initial data, and then applying dispersion normalization to reduce the impacts of atmospheric dispersion. Hourly speciated VOC data measured in Qingdao from March to May 2020 were utilized to test the method and had assessed its effectiveness. Underestimated solvent use and biogenic emissions contributions due to photochemical losses during the O3 pollution (OP) period reached 4.4 and 3.8 times the non-O3 pollution (NOP) period values, respectively. Increased solvent use contribution due to air dispersion during the OP period was 4.6 times the change in the NOP period. The influence of chemical conversion and air dispersion on the gasoline and diesel vehicle emissions was not apparent during either period. The ICDN-PMF results suggested that biogenic emissions (23.1 %), solvent use (23.0 %), motor-vehicle emissions (17.1 %), and natural gas and diesel evaporation (15.8 %) contributed most to ambient VOCs during the OP period. Biogenic emissions and solvent use contributions during the OP period increased by 187 % and 135 % compared with the NOP period, respectively, whereas that of liquefied petroleum gas substantially decreased during the OP period. Controlling solvent use and motor-vehicles could be effective in controlling VOCs in the OP period.
Collapse
Affiliation(s)
- Yutong Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China.
| | - He Meng
- Qingdao Eco-environment Monitoring Center of Shandong Province, Qingdao 266003, China
| | - 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
| | - Laiyuan Shi
- Qingdao Eco-environment Monitoring Center of Shandong Province, Qingdao 266003, China
| | - Shaojie Song
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - 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
| |
Collapse
|
10
|
Gu Y, Liu B, Meng H, Song S, Dai Q, Shi L, Feng Y, Hopke PK. Source apportionment of consumed volatile organic compounds in the atmosphere. JOURNAL OF HAZARDOUS MATERIALS 2023; 459:132138. [PMID: 37531767 DOI: 10.1016/j.jhazmat.2023.132138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 07/12/2023] [Accepted: 07/23/2023] [Indexed: 08/04/2023]
Abstract
Conventional source apportionments of ambient volatile organic compounds (VOCs) have been based on observed and initial concentrations after photochemical correction. However, these results have not been related to ozone (O3) and secondary organic aerosol (SOA) formation. Thus, the apportioned contributions could not effectively support secondary pollution control development. Source apportionment of the VOCs consumed in forming O3 and SOA is needed. A consumed VOC source apportionment approach was developed and applied to hourly speciated VOCs data from June to August 2022 measured in Laoshan, Qingdao. Biogenic emissions (56.3%), vehicle emissions (17.2%), and gasoline evaporation (9.37%) were the main sources of consumed VOCs. High consumed VOCs from biogenic emissions mainly occurred during transport from parks to the southwest and northwest of study site. During the O3 pollution period, biogenic emissions (46.3%), vehicle emissions (24.2%), and gasoline evaporation (14.3%) provided the largest contributions to the consumed VOCs. However, biogenic emissions contribution increased to 57.1% during the non-O3 pollution period, and vehicle emissions and gasoline evaporation decreased to 16.5% and 9.01%, respectively. Biogenic emissions and the mixed source of combustion sources and solvent use contributed the most to O3 and SOA formation potentials during the O3 pollution period, respectively.
Collapse
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.
| | - He Meng
- Qingdao Eco-environment Monitoring Center of Shandong Province, Qingdao 266003, China
| | - Shaojie Song
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; CMA-NKU Cooperative Laboratory for Atmospheric Environment-Health Research, Tianjin 300350, China
| | - Laiyuan Shi
- Qingdao Eco-environment Monitoring Center of Shandong Province, Qingdao 266003, 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
| |
Collapse
|
11
|
Wang Z, Zhang P, Pan L, Qian Y, Li Z, Li X, Guo C, Zhu X, Xie Y, Wei Y. Ambient Volatile Organic Compound Characterization, Source Apportionment, and Risk Assessment in Three Megacities of China in 2019. TOXICS 2023; 11:651. [PMID: 37624157 PMCID: PMC10458435 DOI: 10.3390/toxics11080651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/26/2023]
Abstract
In order to illustrate pollution characterization, source apportionment, and risk assessment of VOCs in Beijing, Baoding, and Shanghai, field observations of CO, NO, NO2, O3, and volatile organic compounds (VOCs) were conducted in 2019. Concentrations of VOCs were the highest in Beijing (105.4 ± 52.1 ppb), followed by Baoding (97.1 ± 47.5 ppb) and Shanghai (91.1 ± 41.3 ppb). Concentrations of VOCs were the highest in winter (120.3 ± 61.5 ppb) among the three seasons tested, followed by summer (98.1 + 50.8 ppb) and autumn (75.5 + 33.4 ppb). Alkenes were the most reactive VOC species in all cities, accounting for 56.0%, 53.7%, and 39.4% of ozone formation potential in Beijing, Baoding, and Shanghai, respectively. Alkenes and aromatics were the reactive species, particularly ethene, propene, 1,3,5-trimethylbenzene, and m/p-xylene. Vehicular exhaust was the principal source in all three cities, accounting for 27.0%, 30.4%, and 23.3% of VOCs in Beijing, Baoding, and Shanghai, respectively. Industrial manufacturing was the second largest source in Baoding (23.6%) and Shanghai (21.3%), and solvent utilization was the second largest source in Beijing (25.1%). The empirical kinetic modeling approach showed that O3 formation was limited by both VOCs and nitric oxides at Fangshan (the suburban site) and by VOCs at Xuhui (the urban site). Acrolein was the only substance with an average hazard quotient greater than 1, indicating significant non-carcinogenic risk. In Beijing, 1,2-dibromoethane had an R-value of 1.1 × 10-4 and posed a definite carcinogenic risk.
Collapse
Affiliation(s)
- Zhanshan Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (Z.W.)
| | - Puzhen Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (Z.W.)
| | - Libo Pan
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (Z.W.)
| | - Yan Qian
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (Z.W.)
| | - Zhigang Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (Z.W.)
| | - Xiaoqian Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (Z.W.)
| | - Chen Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (Z.W.)
| | - Xiaojing Zhu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (Z.W.)
| | - Yuanyuan Xie
- Foreign Environmental Cooperation Centre, Ministry of Ecology and Environment, Beijing 100035, China
| | - Yongjie Wei
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China; (Z.W.)
| |
Collapse
|
12
|
Wang W, Fang H, Zhang Y, Ding Y, Hua F, Wu T, Yan Y. Characterizing sources and ozone formations of summertime volatile organic compounds observed in a medium-sized city in Yangtze River Delta region. CHEMOSPHERE 2023; 328:138609. [PMID: 37023901 DOI: 10.1016/j.chemosphere.2023.138609] [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: 02/06/2023] [Revised: 03/28/2023] [Accepted: 04/03/2023] [Indexed: 06/19/2023]
Abstract
Volatile organic compounds (VOCs) emitted from various sources into atmosphere could cause serious O3 pollution in urban areas. Although characterizations of ambient VOCs have been extensively studied in megacities, they are scarcely investigated in medium/small-sized cities, which could present different pollution characterizations due to the factors like emission sources and populations. Herein, field campaigns were conducted concurrently at six sites in a medium-sized city of Yangtze River Delta region to determine ambient levels, O3 formations and source contributions of summertime VOCs. During the observation period, the total VOC (TVOCs) mixing ratios ranged from 27.10 ± 3.35 to 39.09 ± 10.84 ppb at six sites. The ozone formation potential (OFP) results showed that alkenes, aromatics and oxygenated VOCs (OVOCs) were dominant contributors, together sharing 81.4% of total calculated OFPs. Ethene ranked the largest OFP contributor at all six sites. A high VOC site, KC, was selected as a case to detailed analyze diurnal variations of VOCs and its relationship with O3. Consequently, diurnal patterns varied with VOC groups, and TVOC concentrations were lowest during strong photochemical period (15:00-18:00 p.m.), opposite to the O3 peak. VOCs/NOx ratios and observation-based model (OBM) analysis revealed that O3 formation sensitivity was primarily in transition regime in summertime and that the reduction of VOCs rather than NOX would be more efficient to suppress O3 peak at KC during pollution episode. Additionally, source apportionment conducted with positive matrix factorization (PMF) indicated that industrial emission (29.2%-51.7%) and gasoline exhaust (22.4%-41.1%) were major sources for VOCs at all six sites, and that VOCs from industrial emissions and gasoline exhaust were the key precursors for ozone formation. Our results shed light on the importance of alkenes, aromatics and OVOCs in forming O3 and propose that preferentially reducing VOCs especially those from industrial emission and gasoline exhaust would benefit alleviating O3 pollution.
Collapse
Affiliation(s)
- Wenjing Wang
- School of Ecology and Environment, Anhui Normal University, Wuhu, 241000, China
| | - Hua Fang
- School of Ecology and Environment, Anhui Normal University, Wuhu, 241000, China; Center of Cooperative Innovation for Recovery and Reconstruction of Degraded Ecosystem in Wanjiang City Belt, Wuhu, 241000, China.
| | - Ying Zhang
- Wuhu Ecological and Environmental Monitoring Center of Anhui Province, Wuhu, 241005, China
| | - Yueyue Ding
- Wuhu Ecological and Environmental Monitoring Center of Anhui Province, Wuhu, 241005, China
| | - Fei Hua
- Wuhu Institute of Technology, Wuhu, 241006, China
| | - Ting Wu
- School of Ecology and Environment, Anhui Normal University, Wuhu, 241000, China; Center of Cooperative Innovation for Recovery and Reconstruction of Degraded Ecosystem in Wanjiang City Belt, Wuhu, 241000, China.
| | - Yunzhi Yan
- School of Ecology and Environment, Anhui Normal University, Wuhu, 241000, China; Center of Cooperative Innovation for Recovery and Reconstruction of Degraded Ecosystem in Wanjiang City Belt, Wuhu, 241000, China.
| |
Collapse
|
13
|
Zeng X, Han M, Ren G, Liu G, Wang X, Du K, Zhang X, Lin H. A comprehensive investigation on source apportionment and multi-directional regional transport of volatile organic compounds and ozone in urban Zhengzhou. CHEMOSPHERE 2023; 334:139001. [PMID: 37220798 DOI: 10.1016/j.chemosphere.2023.139001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 04/18/2023] [Accepted: 05/20/2023] [Indexed: 05/25/2023]
Abstract
To understand the characteristics, source apportionment, and regional transport of volatile organic compounds (VOCs) and ozone (O3) in a typical city with severe air pollution in central China, we observed and analyzed 115 VOC species at an urban site in Zhengzhou from 29 July to 26 September 2021. During this period, observation- and emission-based approaches revealed that Zhengzhou was in a VOC-limited regime. The average concentration of total VOCs (TVOCs) was 162.25 ± 71.42 μg/m3, dominated by oxygenated VOCs (OVOCs, 34.49%), alkanes (24.29%), and aromatics (19.49%). Six VOC sources were identified using positive matrix factorization (PMF) model, including paint solvent usage (25.32%), secondary production (24.11%), industrial production (19.22%), vehicle exhaust (16.18%), biogenic emission (8.87%), and combustion (6.30%). To assess the regional contribution and source apportionment of VOCs and O3, Comprehensive Air Quality Model with Extensions (CAMx) with the Ozone Source Apportionment Technology (OSAT) was used for simulation. Results showed that the VOCs were significantly affected by local emissions (about 70%), while O3 was mainly attributed to regional and super-regional transport. Regarding multi-directional regional transport of VOCs and O3, dominant contributions were from the northeast and east-northeast directions, and O3 contributions were also predominantly from the east and east-southeast directions. In terms of source apportionment, the transportation and industrial sectors (including solvent usage) were the major contributors to O3 and VOCs. To alleviate VOCs and O3 pollution, transportation and industrial emission reduction should be strengthened, and regional coordination, especially from the northeast to east-southeast directions, should be emphasized in addition to local management.
Collapse
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
| |
Collapse
|
14
|
Hua J, Cui Y, Guo L, Li H, Fan J, Li Y, Wang Y, Liu K, He Q, Wang X. Spatial characterization of HCHO and reapportionment of its secondary sources considering photochemical loss in Taiyuan, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 865:161069. [PMID: 36584945 DOI: 10.1016/j.scitotenv.2022.161069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2022] [Revised: 11/28/2022] [Accepted: 12/16/2022] [Indexed: 06/17/2023]
Abstract
Formaldehyde (HCHO) plays an important role in atmospheric ozone (O3) formation. To accurately identify the sources of HCHO, carbonyls and volatile organic compounds (VOCs) were measured at three urban sites (Taoyuan, TY-U; Jinyuan, JY-U; Xiaodian, XD-U) and a suburban site (Shanglan, SL-B) in Taiyuan during a high O3 period (from July 20 to August 3, 2020). The average mixing ratio of HCHO at XD-U (8.1 ± 2.8 ppbv) was comparable to those at TY-U (7.4 ± 2.1 ppbv) and JY-U (7.0 ± 2.3 ppbv) but higher (p < 0.01) than that at SL-B (4.9 ± 2.3 ppbv). HCHO contributed to 54.3-59.9 % of the total ozone formation potentials (OFPs) of non-methane hydrocarbons (NMHCs) at four sites. The diurnal variation of HCHO concentrations reached a peak value at 12:00-15:00, which may be attributed to the strong photochemical reaction. To obtain more accurate source results of HCHO under the condition of photochemical loss, the initial concentrations of NMHCs were estimated based on photochemical age parameterization and incorporated into the positive matrix factorization (PMF) model (termed IC-PMF). According to the IC-PMF results, secondary formation (SF) contributed the most to HCHO at XD-U (35.6 %) and SL-B (25.1 %), whereas solvent usage (SU) (40.9 %) and coking sources (CS) (36.0 %) were the major sources at TY-U and JY-U, respectively. Compared to the IC-PMF, the conventional PMF analysis based on the observed data underestimated the contributions of SU (100.5-154.2 %) and biogenic sources (BS) (28.5-324.7 %). Further reapportionment of secondary HCHO by multiple linear regression indicated that SU dominated the sources of HCHO at SL-B (28.3 %) and TY-U (41.7 %), while industrial emissions (IE) and CS contributed the most to XD-U (26.6 %) and JY-U (43.0 %) in Taiyuan from north to south, respectively.
Collapse
Affiliation(s)
- Jingya Hua
- School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China
| | - Yang Cui
- School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China.
| | - Lili Guo
- School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China
| | - Hongyan Li
- School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China
| | - Jie Fan
- School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China
| | - Yanan Li
- School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China
| | - Yonghong Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
| | - Kankan Liu
- School of Environment and Safety Engineering, North University of China, Taiyuan 030051, China
| | - Qiusheng He
- School of Environment and Resources, Taiyuan University of Science and Technology, Taiyuan 030024, China
| | - Xinming Wang
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| |
Collapse
|
15
|
Liu B, Yang Y, Yang T, Dai Q, Zhang Y, Feng Y, Hopke PK. Effect of photochemical losses of ambient volatile organic compounds on their source apportionment. ENVIRONMENT INTERNATIONAL 2023; 172:107766. [PMID: 36706584 DOI: 10.1016/j.envint.2023.107766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 12/19/2022] [Accepted: 01/17/2023] [Indexed: 06/18/2023]
Abstract
Photochemical losses of ambient volatile organic compounds (VOCs) substantially affect source apportionment analysis. Hourly speciated VOC data measured from April to August 2020 in Tianjin, China were used to analyze the photochemical losses of VOC species and assess the impacts of photochemical losses on source apportionment by comparing the positive matrix factorization (PMF) results based on observed and initial concentration data (OC-PMF and IC-PMF). The initial concentrations of the VOC species were estimated using a photochemical age-based parameterization method. The results suggest that the average photochemical loss of total VOCs (TVOCs) during the ozone pollution period was 2.4 times higher than that during the non-ozone pollution period. The photochemical loss of alkenes was more significant than that of the other VOC species. Temperature has an important effect on photochemical losses, and different VOC species have different sensitivities to temperature; high photochemical losses mainly occurred at temperatures between 25 °C and 35 °C. Photochemical losses reduced the concentrations of highly reactive species in the OC-PMF factor profile. Compared with the IC-PMF results, the OC-PMF contributions of biogenic emissions and polymer production-related industrial sources were underestimated by 73 % and 50 %, respectively, likely due to the oxidation of isoprene and propene, respectively. The contribution of diesel and gasoline evaporation was underestimated by 39 %, which was likely due to the loss of m,p-xylene. Additionally, the contributions of liquefied petroleum gas, vehicle emissions, natural gas, and oil refinery were underestimated by 31 %, 29 %, 23 %, and 13 %, respectively. When the O3 concentrations were higher than 140 μg m-3 or the temperatures were higher than 30 °C, the photochemical losses from most sources increased substantially. Additionally, solar radiation produced different photochemical losses for different source types.
Collapse
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
| |
Collapse
|