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Shang L, Dong Z, Li Z, Wang M, Kong Z, Li X, Zhang R. Abundance and sources of particulate polycyclic aromatic hydrocarbons and aromatic acids at an urban site in central China. J Environ Sci (China) 2024; 142:155-168. [PMID: 38527881 DOI: 10.1016/j.jes.2023.05.036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 05/26/2023] [Accepted: 05/26/2023] [Indexed: 03/27/2024]
Abstract
We conducted a simultaneous field study of PM2.5-bound particulate polycyclic aromatic hydrocarbons (PAHs) and aromatic acids (AAs) in a polluted city Zhengzhou to explore the concentration, sources and potential conversion pathways between PAHs and AAs in different seasons. The average concentrations of PM2.5, 28PAHs and 8AAs during the sampling period were 77 µg/m3, 75 ng/m3, and 283 ng/m3, respectively. The concentration of both 28PAHs and 8AAs were highest in winter and lowest in summer with ratios of 6.3 and 2.3, respectively. PAHs with 5-7 rings were the main components of PAHs (52%), followed by 4 rings PAHs (30%) and 2-3 rings PAHs (18%). According to the source appointment results obtained by positive matrix factorization, the main sources of PAHs were combustion and vehicle emissions, which account for 37% and 34%, respectively. 8AAs were divided into three groups, including four benzene dicarboxylic acids (B2CAs), three benzene tricarboxylic acids (B3CAs) and one benzene tetracarboxylic acid (B4CA). And interspecies correlation analysis with PM2.5 source markers were used to investigate potential sources. Phthalic acid (o-Ph) was the most abundant specie of 8AAs (157 ng/m3, 55% of 8AAs), which was well correlated with sulfate. Meanwhile, B3CAs and B4CA were highly correlated with sulfate and weakly correlated with levoglucosan, suggesting that secondary formation was their main source. As logical oxidation products of PAHs, o-Ph and B3CAs showed good correlations with a number of PAHs, indicating possible photochemical oxidation pathway by PAHs. In addition, O3, NO2, temperature and relative humidity have positive effects on the secondary formation of B3CAs.
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Affiliation(s)
- Luqi Shang
- School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China; Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Zhe Dong
- College of Chemistry, Zhengzhou University, Zhengzhou 450001, China; Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Zihan Li
- School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China; Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Mingkai Wang
- School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China; Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Zihan Kong
- School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China; Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450001, China
| | - Xiao Li
- School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China; Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450001, China.
| | - Ruiqin Zhang
- School of Ecology and Environment, Zhengzhou University, Zhengzhou 450001, China; Institute of Environmental Sciences, Zhengzhou University, Zhengzhou 450001, China.
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Yadav K, Bhardwaj A, Sunder Raman R. Chemical characterization, source identification and potential health effects of PM 2.5-bound non-polar organic compounds over a COALESCE network site - Bhopal, India. Sci Total Environ 2024; 920:170957. [PMID: 38365037 DOI: 10.1016/j.scitotenv.2024.170957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 02/09/2024] [Accepted: 02/11/2024] [Indexed: 02/18/2024]
Abstract
Year-long (2019) measurements of carbonaceous aerosols were performed at Bhopal, a regionally representative site as a part of the COALESCE (Carbonaceous Aerosol Emissions, Source apportionment and Climate Impacts) campaign. Aerosol-associated non-polar organic compounds (NPOCs) were analysed using thermal desorption (TD) Gas chromatography/Mass spectrometry (TD-GC/MS). The annual average of the total organic carbon (OC), elemental carbon (EC), and analysed PAHs (Polycyclic Aromatic Hydrocarbons), and n-alkanes were, 9.74 ± 9.47 μg m-3, 2.13 ± 3.12 μg m-3, 10.43 ± 5.49 ng m-3, and 114.93 ± 49.24 ng m-3, respectively. PAHs diagnostic ratios suggested emissions from petroleum, grass, wood, and coal combustion. Combustion derived PAHs (CombPAHs) accounted for 72.5 % of the total measured PAHs. During wintertime, based on Pyr/BaP ratio (∼0.6), gasoline exhaust emissions were higher compared to diesel exhaust emissions. The weak correlations between PAHs and meteorological parameters suggested that variations in PAH levels are primarily driven by alterations in emission sources. Total PAHs were correlated moderately with BrC (r2 = 0.60). The estimated lifetime lung cancer risk (LLCR) values on exposure to 16 USEPA priority PAHs (5 × 10-5) demonstrated that PAH levels in this region pose moderate health risks. Given observations from only campaign mode short-term measurements of NPOCs over India, this work provides a more comprehensive understanding of the concentrations, seasonal variations, and sources of n-alkanes and health risk associated with particle bound PAHs over the data-poor central Indian region.
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Affiliation(s)
- Kajal Yadav
- Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Bhopal, Bhopal by-pass road, Bhauri, Bhopal 462066, Madhya Pradesh, India
| | - Ankur Bhardwaj
- Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Bhopal, Bhopal by-pass road, Bhauri, Bhopal 462066, Madhya Pradesh, India
| | - Ramya Sunder Raman
- Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Bhopal, Bhopal by-pass road, Bhauri, Bhopal 462066, Madhya Pradesh, India.
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Yen PH, Yuan CS, Soong KY, Jeng MS, Cheng WH. Identification of potential source regions and long-range transport routes/channels of marine PM 2.5 at remote sites in East Asia. Sci Total Environ 2024; 915:170110. [PMID: 38232833 DOI: 10.1016/j.scitotenv.2024.170110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 12/25/2023] [Accepted: 01/10/2024] [Indexed: 01/19/2024]
Abstract
Long-range transport (LRT) of air masses in East Asia and their impacts on marine PM2.5 were explored. Situated in the leeward region of East Asia, Taiwan Island marked by its elevated Central Mountain Range (CMR) separates air masses into two distinct air currents. This study aims to investigate the transport of PM2.5 from the north to the leeward region. Six transport routes (A-F) were identified and further classified them into three main channels (i.e. East, West, and South Channels) based on their transport routes and potential sources. Green Island (Site GR) and Hengchun Peninsula (Site HC) exhibited similarities in their transport routes, with Central China, North China, and Korean Peninsula being the major source regions of PM2.5, particularly during the Asian Northeastern Monsoons (ANMs). Dongsha Island (Site DS) was influenced by both Central China and coastal regions of East China, indicating Asian continental outflow (ACO) as the major source of PM2.5. The positive matrix factorization (PMF) analysis of PM2.5 resolved that soil dust, sea salts, biomass burning, ship emissions, and secondary aerosols were the major sources. Northerly Channels (i.e. East and West Channels) were primarily influenced by ship emissions and secondary aerosols, while South Channel was dominated by oceanic spray and soil dust. The results of W-PSCF and W-CWT analysis indicated that three remote sites experienced significant contributions from Central China in the highest PM2.5 concentration range (75-100%). In contrast, PM2.5 in the 0-25% and 25-50% ranges primarily originated from the open seas, with ship emissions being the prominent source. It suggested that northern regions with heavy industrialization and urbanization have impacts on high PM2.5 concentrations, while open seas are the main sources of low PM2.5 concentrations.
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Affiliation(s)
- Po-Hsuan Yen
- Institute of Environmental Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan, ROC
| | - Chung-Shin Yuan
- Institute of Environmental Engineering, National Sun Yat-sen University, Kaohsiung, Taiwan, ROC; Aerosol Science Research Center, National Sun Yat-sen University, Kaohsiung, Taiwan, ROC.
| | - Ker-Yea Soong
- Institute of Marine Biology, National Sun Yat-sen University, Kaohsiung City, Taiwan, ROC
| | - Ming-Shiou Jeng
- Biodiversity Research Center, Academia Sinica, Nangang, Taipei, Taiwan, ROC; Green Island Marine Research Station, Biodiversity Research Center, Academia Sinica, Green Island, Taitung, Taiwan, ROC
| | - Wen-Hsi Cheng
- Ph.D. Program in Maritime Science and Technology, College of Maritime, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan, ROC
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Guo W, Li Z, Zhang Z, Zhu R, Xiao H, Xiao H. Sources and influences of atmospheric nonpolar organic compounds in Nanchang, central China: Full-year monitoring with a focus on winter pollution episodes. Sci Total Environ 2024; 912:169216. [PMID: 38092198 DOI: 10.1016/j.scitotenv.2023.169216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 12/05/2023] [Accepted: 12/06/2023] [Indexed: 12/17/2023]
Abstract
Nonpolar organic compounds (NPOCs) are found in atmospheric aerosols and have significant implications for environmental and human health. Although many studies have quantitatively estimated the sources of NPOCs in different cities, few have evaluated their main influencing factors (e.g., emissions and meteorological conditions) at relatively long (e.g., different seasons) and short timescales (e.g., several days during pollution episodes). A better understanding of this issue could optimise strategies for dealing with organic contamination in atmospheric particulate matter. NPOCs (including n-alkanes, PAHs and hopanes) in fine particulate matter (PM2.5) were sampled daily at Nanchang, China, from 1 November 2020 to 31 October 2021. Analyses of specific biomarkers and diagnostic ratios indicate that the NPOCs mainly had anthropogenic sources. The quantitative estimates of a positive matrix factorization model show that fossil fuel and biomass combustion were the main sources of n-alkanes (contributing 64.8 %), while vehicle exhaust was the main source of PAHs (47.0 %) and hopanes (52.3 %). Seasonally, the contributions from coal and/or biomass combustion were higher in autumn and winter (40.2-56.3 %) than in spring and summer (25.7-44.3 %), while contributions from natural plants, petroleum volatilization and vehicle exhaust were higher in spring and summer (14.7-63.5 %) than in autumn and winter (8.1-48.9 %). Redundancy analysis shows that increased emissions, especially from coal and/or biomass combustion, are the main cause of increases in NPOCs, during both annual sampling periods and winter pollution episodes. Over the year, higher temperature and longer sunshine hours correspond to lower NPOC concentrations. In winter pollution episodes, increases in temperature and relative humidity correspond to increases in NPOC concentrations. Our results suggest that controlling primary emissions, especially from coal and biomass combustion, may be an effective way to prevent increases in NPOC concentrations.
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Affiliation(s)
- Wei Guo
- School of Water Resources and environmental Engineering, East China University of Technology, Nanchang 330013, China; Jiangxi Province Key Laboratory of the Causes and Control of Atmospheric Pollution, East China University of Technology, Nanchang 330013, China
| | - Zicong Li
- School of Water Resources and environmental Engineering, East China University of Technology, Nanchang 330013, China; Jiangxi Province Key Laboratory of the Causes and Control of Atmospheric Pollution, East China University of Technology, Nanchang 330013, China
| | - Ziyue Zhang
- School of Water Resources and environmental Engineering, East China University of Technology, Nanchang 330013, China; Jiangxi Province Key Laboratory of the Causes and Control of Atmospheric Pollution, East China University of Technology, Nanchang 330013, China
| | - Renguo Zhu
- School of Water Resources and environmental Engineering, East China University of Technology, Nanchang 330013, China; Jiangxi Province Key Laboratory of the Causes and Control of Atmospheric Pollution, East China University of Technology, Nanchang 330013, China
| | - Hongwei Xiao
- School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Huayun Xiao
- School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, China.
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Duan L, Yu H, Wang Q, Wang F, Lin T, Cao Y, Guo Z. A comprehensive exploration of characteristics and source attribution of carbonaceous aerosols in PM 2.5 in an East China megacity. Environ Pollut 2024; 343:123239. [PMID: 38154782 DOI: 10.1016/j.envpol.2023.123239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2023] [Revised: 12/15/2023] [Accepted: 12/25/2023] [Indexed: 12/30/2023]
Abstract
A total of 84 PM2.5 (fine particulate matter) aerosol samples were collected between October 2020 and August 2021 within an urban site in Hangzhou, an East China megacity. Chemical species, such as organic carbon (OC), elemental carbon (EC), as well as char, soot, and n-alkanes, were analyzed to determine their pollution characteristics and source contributions. The mean yearly concentrations of OC, EC, char, soot, and total n-alkanes (∑n-alkane) were 8.76 ± 3.61 μg/m3, 1.44 ± 0.76 μg/m3, 1.21 ± 0.69 μg/m3, 0.3 ± 0.1 μg/m3, and 24.2 ± 10.6 ng/m3. The OC, EC, and ∑n-alkanes were found in the highest levels during winter and lowest during summer. There were strong correlations between OC and EC in both winter and spring, suggesting similar potential sources for these carbonaceous components in both seasons. There were poor correlations among the target pollutants due to summertime secondary organic carbon formation. Potential source contribution functions analysis showed that local pollution levels in winter and autumn were likely influenced by long-range transportation from the Plain of North China. Source index and positive matrix factorization models provided insights into the complex sources of n-alkanes in Hangzhou. Their major contributors were identified as terrestrial plant releases (32.7%), traffic emissions (28.8%), coal combustion (27.3%), and microbial activity (11.2%). Thus, controlling vehicular emissions and coal burning could be key measures to alleviate n-alkane concentrations in the atmosphere of Hangzhou, as well as other Chinese urban centers.
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Affiliation(s)
- Lian Duan
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438, China; Institute of Eco-Chongming (IEC), Shanghai, 200062, China
| | - Huimin Yu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438, China
| | - Qiongzhen Wang
- Environmental Science Research & Design Institute of Zhejiang Province, Hangzhou, Zhejiang, 310007, China; Key Laboratory of Environmental Pollution Control Technology of Zhejiang Province, Hangzhou, 310007, China
| | - Fengwen Wang
- Key Laboratory of the Three Gorges Reservoir Region's Eco-Environment, Ministry of Education, College of Environment and Ecology, Chongqing University, Chongqing, 400030, China
| | - Tian Lin
- College of Marine Ecology and Environment, Shanghai Ocean University, Shanghai, 201306, China
| | - Yibo Cao
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438, China
| | - Zhigang Guo
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, 200438, China; Institute of Eco-Chongming (IEC), Shanghai, 200062, China; State Environmental Protection Key Laboratory of Land and Sea Ecological Governance and Systematic Regulation, Shandong Academy for Environmental Planning, Jinan, 250101, China.
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Li Q, Zhang K, Li R, Yang L, Yi Y, Liu Z, Zhang X, Feng J, Wang Q, Wang W, Huang L, Wang Y, Wang S, Chen H, Chan A, Latif MT, Ooi MCG, Manomaiphiboon K, Yu J, Li L. Underestimation of biomass burning contribution to PM 2.5 due to its chemical degradation based on hourly measurements of organic tracers: A case study in the Yangtze River Delta (YRD) region, China. Sci Total Environ 2023; 872:162071. [PMID: 36775179 DOI: 10.1016/j.scitotenv.2023.162071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 02/01/2023] [Accepted: 02/02/2023] [Indexed: 06/18/2023]
Abstract
Biomass burning (BB) has significant impacts on air quality and climate change, especially during harvest seasons. In previous studies, levoglucosan was frequently used for the calculation of BB contribution to PM2.5, however, the degradation of levoglucosan (Lev) could lead to large uncertainties. To quantify the influence of the degradation of Lev on the contribution of BB to PM2.5, PM2.5-bound biomass burning-derived markers were measured in Changzhou from November 2020 to March 2021 using the thermal desorption aerosol gas chromatography-mass spectrometry (TAG-GC/MS) system. Temporal variations of three anhydro-sugar BB tracers (e.g., levoglucosan, mannosan (Man), and galactosan (Gal)) were obtained. During the sampling period, the degradation level of air mass (x) was 0.13, indicating that ~87 % of levoglucosan had degraded before sampling in Changzhou. Without considering the degradation of levoglucosan in the atmosphere, the contribution of BB to OC were 7.8 %, 10.2 %, and 9.3 % in the clean period, BB period, and whole period, respectively, which were 2.4-2.6 times lower than those (20.8 %-25.9 %) considered levoglucosan degradation. This illustrated that the relative contribution of BB to OC could be underestimated (~14.9 %) without considering degradation of levoglucosan. Compared to the traditional method (i.e., only using K+ as BB tracer), organic tracers (Lev, Man, Gal) were put into the Positive Matrix Factorization (PMF) model in this study. With the addition of BB organic tracers and replaced K+ with K+BB (the water-soluble potassium produced by biomass burning), the overall contribution of BB to PM2.5 was enhanced by 3.2 % after accounting for levoglucosan degradation based on the PMF analysis. This study provides useful information to better understand the effect of biomass burning on the air quality in the Yangtze River Delta region.
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Affiliation(s)
- Qing Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Kun Zhang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Rui Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Liumei Yang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Yanan Yi
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Zhiqiang Liu
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China; Jiangsu Changhuan Environment Technology Co., Ltd., Changzhou, Jiangsu, China
| | - Xiaojuan Zhang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China; Jiangsu Changhuan Environment Technology Co., Ltd., Changzhou, Jiangsu, China
| | - Jialiang Feng
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Qiongqiong Wang
- Department of Chemistry, Hong Kong University of Science & Technology, Hong Kong, China
| | - Wu Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Ling Huang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Yangjun Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Shunyao Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Hui Chen
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Andy Chan
- Department of Civil Engineering, University of Nottingham Malaysia, Semenyih, Selangor, Malaysia
| | - Mohd Talib Latif
- Department of Earth Science and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Maggie Chel Gee Ooi
- Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
| | - Kasemsan Manomaiphiboon
- The Joint Graduate School of Energy and Environment, King Mongkut's University of Technology Thonburi, Bangkok, Thailand
| | - Jianzhen Yu
- Department of Chemistry, Hong Kong University of Science & Technology, Hong Kong, China; Division of Environment & Sustainability, Hong Kong University of Science & Technology, Hong Kong, China
| | - Li Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China.
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Li Y, Huang Y, Yuan L, He Y, Yin G, He T, He E, Ding F, Xia H, Xu H, Liu M, Tao S. The deposition mapping of polycyclic aromatic hydrocarbons in megacity Shanghai, China. Journal of Hazardous Materials 2023; 443:130173. [PMID: 36257109 DOI: 10.1016/j.jhazmat.2022.130173] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 10/03/2022] [Accepted: 10/09/2022] [Indexed: 06/16/2023]
Abstract
The deposition of polycyclic aromatic hydrocarbon (PAHs) has far-reaching impacts on Earth's surface system and human health. However, a comprehensive understanding of PAHs' deposition in a high urbanized area is still lacking because of limited field measurements data and rough resolution of current models. In this research, a deposition map of PAHs with a resolution of 2 × 2 km in megacity Shanghai, China was established. Gridded annual total deposition of PAHs from July 2020 to June 2021 ranged from 385 to 10,631 ng/(m2·d), with a mean value of 2,611 ng/(m2·d). The highest PAHs deposition was found over the downtown Shanghai, which received 4.3 times the deposition flux of outlying areas. About 77 % of area in Shanghai was dominated by wet deposition which accounted for 62 % of total deposition in Shanghai. The total deposition showed a trend of summer>fall>spring>winter, which was similar to that of the amount of rain. Source apportionment and geographically weighted regression analysis showed that built-up land and human activities are key driving factors of PAHs' deposition in Shanghai. Our results suggest that intensive human activities could alter the PAHs deposition distribution in Shanghai, and improve the understanding of PAHs' environmental behavior in high urbanized area.
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Affiliation(s)
- Ye Li
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Ye Huang
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China.
| | - Lina Yuan
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Yue He
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Guoyu Yin
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Tianhao He
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Erkai He
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Fangfang Ding
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Haibin Xia
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China
| | - Haoran Xu
- Laboratory of Earth Surface Processes, College of Urban and Environmental Science, Peking University, Beijing 100871, China
| | - Min Liu
- Key Laboratory of Geographic Information Science of the Ministry of Education, School of Geographic Sciences, East China Normal University, 500 Dongchuan Road, Minhang District, Shanghai 200241, China.
| | - Shu Tao
- Laboratory of Earth Surface Processes, College of Urban and Environmental Science, Peking University, Beijing 100871, China
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An Z, Li X, Yuan Y, Duan F, Jiang J. Large contribution of non-priority PAHs in atmospheric fine particles: Insights from time-resolved measurement and nontarget analysis. Environ Int 2022; 163:107193. [PMID: 35339920 DOI: 10.1016/j.envint.2022.107193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/18/2021] [Revised: 02/11/2022] [Accepted: 03/17/2022] [Indexed: 06/14/2023]
Abstract
Polycyclic aromatic hydrocarbons (PAHs), detrimental to human health, are key components contributing to the carcinogenicity of fine particles. The 16 priority PAHs listed by the United States Environment Protection Agency have been studied extensively. However, other than them, there is a large diversity of PAH species, whose atmospheric concentrations, risks, and variations remain elusive. Here, we carried out a time-resolved nontarget measurement in atmospheric PM2.5 using an improved comprehensive two-dimensional gas chromatography mass spectrometry. The measurement conducted during a 5-day pollution episode at an urban site of Beijing with a time resolution of 2 h. The nontarget analysis of time-resolved chromatographic data was performed for screening PAHs. A total number of 85 PAHs were identified and quantified. We found that other than 16 EPA PAHs, other screened PAHs contributed 43.3% of the total PAH mass concentration and 40.8% poential health risks. Dynamic variations of mass concentrations and their potential health risks of the screened PAHs were captured during a short-term heavy pollution episode, during which the instantaneous PAHs concentrations were much higher than their average concentrations. This study shows the potential for application of nontarget analysis for online comprehensive two-dimensional gas chromatography mass spectrometry and highlights the importance of time-resolved measurement of PAHs in PM2.5 and attention on extended PAHs species other than 16 EPA PAHs.
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Affiliation(s)
- Zhaojin An
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Xue Li
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Yi Yuan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Fengkui Duan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Jingkun Jiang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China.
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