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Zhao Y, Song Y, Zhang L, Zhao B, Lu M, Cui J, Tang W. Source apportionment and specific-source-site risk of quinolone antibiotics for effluent-receiving urban rivers and groundwater in a city, China. J Environ Sci (China) 2024; 144:185-198. [PMID: 38802230 DOI: 10.1016/j.jes.2023.08.012] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 08/13/2023] [Accepted: 08/14/2023] [Indexed: 05/29/2024]
Abstract
There is a large surface-groundwater exchange downstream of wastewater treatment plants (WWTPs), and antibiotics upstream may influence sites downstream of rivers. Thus, samples from 9 effluent-receiving urban rivers (ERURs) and 12 groundwater sites were collected in Shijiazhuang City in December 2020 and April 2021. For ERURs, 8 out of 13 target quinolone antibiotics (QNs) were detected, and the total concentration of QNs in December and April were 100.6-4,398 ng/L and 8.02-2,476 ng/L, respectively. For groundwater, all target QNs were detected, and the total QNs concentration was 1.09-23.03 ng/L for December and 4.54-170.3 ng/L for April. The distribution of QNs was dissimilar between ERURs and groundwater. Most QN concentrations were weakly correlated with land use types in the system. The results of a positive matrix factorization model (PMF) indicated four potential sources of QNs in both ERURs and groundwater, and WWTP effluents were the main source of QNs. From December to April, the contribution of WWTP effluents and agricultural emissions increased, while livestock activities decreased. Singular value decomposition (SVD) results showed that the spatial variation of most QNs was mainly contributed by sites downstream (7.09%-88.86%) of ERURs. Then, a new method that combined the results of SVD and PMF was developed for a specific-source-site risk quotient (SRQ), and the SRQ for QNs was at high level, especially for the sites downstream of WWTPs. Regarding temporal variation, the SRQ for WWTP effluents, aquaculture, and agricultural emissions increased. Therefore, in order to control the antibiotic pollution, more attention should be paid to WWTP effluents, aquaculture, and agricultural emission sources for the benefit of sites downstream of WWTPs.
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Affiliation(s)
- Yu Zhao
- State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Science, Beijing 100085, China
| | - Yuanmeng Song
- State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Science, Beijing 100085, China; College of Environment Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050000, China
| | - Lulu Zhang
- College of Environment Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050000, China.
| | - Bo Zhao
- College of Environment Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050000, China
| | - Mengqi Lu
- College of Environment Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050000, China
| | - Jiansheng Cui
- College of Environment Science and Engineering, Hebei University of Science and Technology, Shijiazhuang 050000, China
| | - Wenzhong Tang
- State Key Laboratory of Environmental Aquatic Chemistry, Research Center for Eco-Environmental Sciences, Chinese Academy of Science, Beijing 100085, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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Zhu Q, Liu Y, Hasheminassab S. Long-term source apportionment of PM 2.5 across the contiguous United States (2000-2019) using a multilinear engine model. JOURNAL OF HAZARDOUS MATERIALS 2024; 472:134550. [PMID: 38728865 PMCID: PMC11136591 DOI: 10.1016/j.jhazmat.2024.134550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Revised: 05/02/2024] [Accepted: 05/03/2024] [Indexed: 05/12/2024]
Abstract
Identifying PM2.5 sources is crucial for effective air quality management and public health. This research used the Multilinear Engine (ME-2) model to analyze PM2.5 from 515 EPA Chemical Speciation Network (CSN) and Interagency Monitoring of Protected Visual Environments (IMPROVE) sites across the U.S. from 2000 to 2019. The U.S. was divided into nine regions for detailed analysis. A total of seven source types (tracers) were resolved across the country: (1) Soil/Dust (Si, Al, Ca and Fe); (2) Vehicle emissions (EC, OC, Cu and Zn); (3) Biomass/wood burning (K); (4) Heavy oil/coal combustion (Ni, V, Cl and As); (5) Secondary sulfate (SO42-); (6) Secondary nitrate (NO3-) and (7) Sea salt (Mg, Na, Cl and SO42-). Furthermore, we extracted and calculated secondary organic aerosols (SOA) based on the secondary sulfate and nitrate factors. Notably, significant reductions in secondary sulfate, nitrate, and heavy oil/coal combustion emissions reflect recent cuts in fossil-fueled power sector emissions. A decline in SOA suggests effective mitigation of their formation conditions or precursors. Despite these improvements, vehicle emissions and biomass burning show no significant decrease, highlighting the need for focused control on these persistent pollution sources for future air quality management.
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Affiliation(s)
- Qiao Zhu
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Yang Liu
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA.
| | - Sina Hasheminassab
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
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Shi B, Yang X, Liang T, Liu S, Yan X, Li J, Liu Z. Source apportionment of soil PTE in a northern industrial county using PMF model: Partitioning strategies and uncertainty analysis. ENVIRONMENTAL RESEARCH 2024; 252:118855. [PMID: 38588909 DOI: 10.1016/j.envres.2024.118855] [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: 01/31/2024] [Revised: 03/16/2024] [Accepted: 03/31/2024] [Indexed: 04/10/2024]
Abstract
Positive matrix factorization (PMF) has commonly been applied for source apportionment of potentially toxic elements (PTE) in agricultural soil, however, spatial heterogeneity of PTE significantly undermines the accuracy and reliability of PMF results. In this study, a representative industrial-agricultural hub in North China (Xuanhua district, Zhangjiakou City) was selected as the research subject, multiple partition processing (PP) strategies and uncertainty analyses were integrated to advance the PMF modeling and associated algorithm mechanisms were comparatively discussed. Specifically, we adopted three methods to split the research area into several subzones according to industrial density (PP-1), population density (PP-2), and the ecological risk index (PP-3) respectively, to rectify the spatial bias phenomenon of PTE concentrations and to achieve a more interpretable result. Our results indicated that the obvious enrichment of Cd, Pb, and Zn was found in the agricultural soil, with Hg and Cd accounted for 83.49% of the overall potential ecological risk. Combining proper PP with PMF can significantly improve the modelling accuracy. Uncertainty analysis showed that interval ratios of tracer species (Cd, Pb, Hg, and Zn) calculated by PP-3 were consistently lower than that of PP-1 and PP-2, indicating that PP-3 coupled PMF can afford the optimal modeling results. It suggested that natural sources, fertilizers and pesticides, atmosphere deposition, mining, and smelting were recognized as the major contributor for the soil PTE contamination. The contribution of anthropogenic activities, specifically fertilizers and pesticides, and atmosphere deposition, increased by 1.64% and 5.91% compared to PMF results. These findings demonstrate that integration of proper partitioning processing into PMF can effectively improve the accuracy of the model even at the case of soil PTE contamination with high heterogeneity, offering support to subsequently implement directional control strategies.
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Affiliation(s)
- Biling Shi
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Xiao Yang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Tao Liang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Siyan Liu
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Xiulan Yan
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Junchun Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; Guangdong Key Laboratory of Contaminated Environmental Management and Remediation, Guangdong Provincial Academy of Environmental Science, Guangdong, 510045, China
| | - Zhaoshu Liu
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
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Haghi B, Cheraghi M, Sobhanardakani S, Lorestani B, Kiani Sadr M. Assessment of potentially toxic elements (PTEs) in atmospheric dry deposition of Hamedan Metropolis, west of Iran: pollution status, spatiotemporal variation, health risk implications, and source identification. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:252. [PMID: 38879860 DOI: 10.1007/s10653-024-02074-4] [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: 05/01/2024] [Accepted: 06/09/2024] [Indexed: 07/09/2024]
Abstract
The present study was designed to assess concentrations, contamination levels, spatiotemporal variations, health hazards and source apportionment of potentially toxic elements (As, Cd, Co, Cr, Cu, Mn, Ni, Pb, Zn, and V) of atmospheric dry deposition (ADD) in Hamedan Metropolis. In so doing, a total of 144 atmospheric dry deposition samples were collected from 12 sites during four seasons in 2023. The concentrations of the analyzed PTEs in dry deposition samples were determined using ICP-OES after samples were digested with acid. The results illustrated that the average contents of As, Cd, Cr, Cu, Ni, Pb, and Zn with 4.52, 0.591, 4.01, 36.5, 42.5, 10.9, 84.6, 69.6, 178, and 3.91 mg/kg, respectively, were higher than those in the background samples reported for Iran, which could indicate the anthropogenic origin of these PTEs. The highest quantities of the tested PTEs in various seasons were observed in summer and/or fall samples and their highest amount in various functional regions pertained to the samples collected from the commercial or industrial regions, showing the effect of seasonal changes on emission sources and human inputs. Values of average contamination factor (CF), geo-accumulation index (I-geo), and enrichment factor (EF) ranged from 0.013 to 4.45, - 7.07 to 1.56, and 0.120 to 41.3, respectively, showing 'slight to high' pollution, 'unpolluted to moderately polluted', and 'no enrichment to very severe enrichment' levels, respectively. The pollution load index (PLI) with an average value of 0.680 reflected slight pollution levels in the entire study area. The average hazard index (HI) values of the tested PTEs for the residents were all within the safe limit (< 1). Additionally, the total carcinogenic risk (TCR) values showed that the carcinogenic risk of As, Cr and Ni for both target groups were at an acceptable level. Based on the positive matrix factorization (PMF) model, non-exhaust emissions and natural sources, fossil fuel combustion and industrial emissions, and traffic sources were identified as the primary contributors to ADD pollution, accounting for 26%, 38%, and 36%, of the total pollution respectively. In conclusion, further research is recommended to investigate the source-oriented ecological and health risks associated with atmospheric dry deposition pollution.
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Affiliation(s)
- Bijan Haghi
- Department of the Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran
| | - Mehrdad Cheraghi
- Department of the Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran.
| | - Soheil Sobhanardakani
- Department of the Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran
| | - Bahareh Lorestani
- Department of the Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran
| | - Maryam Kiani Sadr
- Department of the Environment, College of Basic Sciences, Hamedan Branch, Islamic Azad University, Hamedan, Iran
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Papagiannis S, Abdullaev SF, Vasilatou V, Manousakas MI, Eleftheriadis K, Diapouli E. Air quality challenges in Central Asian urban areas: a PM 2.5 source apportionment analysis in Dushanbe, Tajikistan. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:39588-39601. [PMID: 38822961 DOI: 10.1007/s11356-024-33833-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 05/23/2024] [Indexed: 06/03/2024]
Abstract
This work presents the first comprehensive assessment of PM pollution sources in Dushanbe, Tajikistan. A total of 138 PM2.5 samples were collected during 2015-2016 and 2018-2019 and were analyzed through gravimetric, ED-XRF, and multi-wavelength absorption techniques. The results show that PM2.5 concentrations were substantially higher than the European annual limit value and WHO Air Quality Guidelines annual average value, with an average of 90.9 ± 68.5 μg m-3. The PMF application identified eight sources of pollution that influenced PM2.5 concentration levels in the area. Coal burning (21.3%) and biomass burning (22.3%) were the dominant sources during the winter, while vehicular traffic (7.7%) contributed more during the warm season. Power plant emissions (17.5%) showed enhanced contributions during the warm months, likely due to high energy demand. Cement industry emissions (6.9%) exhibited significant contribution during the cold period of 2018-2019, while soil dust (11.3%) and secondary sulphates (11.5%) displayed increased contribution during the warm and cold months, respectively. Finally, waste burning (1.5%) displayed the lowest contribution, with no significant temporal variation. Our results highlight the significant impact of anthropogenic activities, and especially the use of coal burning for energy production (both in power plants and for residential heating), and the significant contribution of biomass burning during both warm and cold seasons.
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Affiliation(s)
- Stefanos Papagiannis
- EΝvironmental Radioactivity & Aerosol Technology for Atmospheric & Climate ImpacT Lab (ENRACT), Institute of Nuclear and Radiological Science & Technology, Energy & Safety, NCSR Demokritos, 15310, Athens, Greece.
- Institute of Nuclear & Particle Physics, NCSR Demokritos, 15310, Athens, Greece.
- Department of Materials Science & Engineering, University of Ioannina, 45110, Ioannina, Greece.
| | - Sabur Fuzaylovich Abdullaev
- S.U.Umarov Physical Technical Institute National Academy of Sciences of Tajikistan, 734063, Dushanbe, Tajikistan
| | - Vasiliki Vasilatou
- EΝvironmental Radioactivity & Aerosol Technology for Atmospheric & Climate ImpacT Lab (ENRACT), Institute of Nuclear and Radiological Science & Technology, Energy & Safety, NCSR Demokritos, 15310, Athens, Greece
| | - Manousos Ioannis Manousakas
- EΝvironmental Radioactivity & Aerosol Technology for Atmospheric & Climate ImpacT Lab (ENRACT), Institute of Nuclear and Radiological Science & Technology, Energy & Safety, NCSR Demokritos, 15310, Athens, Greece
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232, Villigen, PSI, Switzerland
| | - Konstantinos Eleftheriadis
- EΝvironmental Radioactivity & Aerosol Technology for Atmospheric & Climate ImpacT Lab (ENRACT), Institute of Nuclear and Radiological Science & Technology, Energy & Safety, NCSR Demokritos, 15310, Athens, Greece
| | - Evangelia Diapouli
- EΝvironmental Radioactivity & Aerosol Technology for Atmospheric & Climate ImpacT Lab (ENRACT), Institute of Nuclear and Radiological Science & Technology, Energy & Safety, NCSR Demokritos, 15310, Athens, Greece
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Ouyang X, Wang Z, Liu X. Distribution patterns, risk assessment and potential sources of heavy metals in sediment in the Qiongzhou Strait, China. MARINE POLLUTION BULLETIN 2024; 203:116481. [PMID: 38733891 DOI: 10.1016/j.marpolbul.2024.116481] [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: 03/10/2024] [Revised: 05/05/2024] [Accepted: 05/06/2024] [Indexed: 05/13/2024]
Abstract
Risk assessment and pollutant source analysis are crucial tools for the management and protection of coastal ecosystems. The distribution patterns, risk assessment, and potential sources of heavy metals (Cd, Cr, Fe, Ni, Cu, Zn, As, Hg, and Pb) in surface sediment were analyzed in the Qiongzhou Strait, China, in summer and autumn of 2022. Heavy metals in autumn showed higher ecological risk than that in summer. Seasonal shifts in ocean currents may result in variations in heavy metal accumulation and dispersion. Cd and Hg were the priority heavy metals found, and according to the Positive Matrix Factorization results, the study area contains five sources of pollution, with natural sources, shipping-related activities, and industrial activities being the primary contributors. This study indicated that pollutants from adjacent areas should be considered for managing the environmental quality of Qiongzhou Strait.
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Affiliation(s)
- Xiayu Ouyang
- College of Marine Life Sciences and Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ocean University of China, Qingdao 266003, China; Key Laboratory of Evolution and Marine Biodiversity, Ministry of Education of China, Ocean University of China, Qingdao 266003, China
| | - Zhe Wang
- College of Marine Life Sciences and Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ocean University of China, Qingdao 266003, China; Key Laboratory of Evolution and Marine Biodiversity, Ministry of Education of China, Ocean University of China, Qingdao 266003, China
| | - Xiaoshou Liu
- College of Marine Life Sciences and Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ocean University of China, Qingdao 266003, China; Key Laboratory of Evolution and Marine Biodiversity, Ministry of Education of China, Ocean University of China, Qingdao 266003, China.
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7
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Dar T, Rai N, Jahan A, Kumar S, Bhat MA, Ahmad R. Uncovering sources, distribution, and seasonal patterns of trace element deposition: the elemental puzzle of the western Himalayas. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:37196-37214. [PMID: 38764085 DOI: 10.1007/s11356-024-33601-6] [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: 11/16/2023] [Accepted: 05/03/2024] [Indexed: 05/21/2024]
Abstract
The transport and deposition of atmospheric pollutants in the Himalayas have a adverse impact on the climate, cryosphere, ecosystem, and monsoon patterns. Unfortunately, there is a insufficiency of data on trace element concentrations and behaviors in the high-altitude Himalayan region, leading to limited research in this area. This study presents a comprehensive and detailed comprehension of trace element deposition, its spatial distribution, seasonal variations, and anthropogenic signals in the high-altitude Kashmir region of the Western Himalayas. Our investigation involved the analysis of 10 trace elements (Al, Cr, Mn, Fe, Co, Ni, Cu, Zn, Cd, and Pb) in glacier ice, snow pits, surface snow, and rainwater collected at various sites including Kolahoi, Thajwas, Pahalgam (Greater Himalayan ranges), and Kongdori and Shopian (Pir Panjal Ranges) during 2021. The study reveals distinct ranges of concentrations for the trace elements at different sampling sites. Our analysis of trace element concentration depth profiles in snow pits reveals seasonal fluctuations during the deposition year. The highest concentrations were found in the autumn (below 20 cm) and summer (top layer), compared to the winter concentration (10-20 cm). The high enrichment factors (EFs) suggest the severity of human-induced trace metal deposition in the western Himalayan region, relative to surrounding regions. Surprisingly, the concentrations and EFs of trace elements showed seasonal contradictions, with lower concentration values and higher EFs during the non-monsoon season and vice versa. A source apportionment analysis using the positive matrix factorization (PMF) technique identified five sources of trace element deposition in the region, including crustal sources (32.33%), coal combustion (15.62%), biomass burning (17.63%), traffic emission (18.8%), and industrial sources (15.6%). Additionally, the study incorporated backward trajectories coupled with δ18O using the NOAA HYSPLIT model to estimate moisture sources in the region, which suggests atmospheric pollutants predominately deposited from the large-scale atmospheric circulation from westerlies (75%) during non-monsoon season. These findings underscore the urgent need for enhanced monitoring and research efforts in the future.
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Affiliation(s)
- Tanveer Dar
- Department of Earth Sciences, Indian Institute of Technology, Roorkee, 247667, India.
| | - Nachiketa Rai
- Department of Earth Sciences, Indian Institute of Technology, Roorkee, 247667, India
| | - Akhtar Jahan
- Department of Earth Sciences, Indian Institute of Technology, Roorkee, 247667, India
| | - Sudhir Kumar
- Hydrological Investigations Division, National Institute of Hydrology, Roorkee, 247667, India
| | - Mohd Aadil Bhat
- State Key Laboratory of Marine Geology, Tongji University, Shanghai, 200092, China
| | - Rayees Ahmad
- Department of Geography and Disaster Management, School of Earth and Environmental Sciences, University of Kashmir, Srinagar, 190006, India
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Yang Y, Sun M, Wu G, Qi Y, Zhu W, Zhao Y, Zhu Y, Li W, Zhang Y, Wang N, Sheng L, Wang W, Yu X, Yu J, Yao X, Zhou Y. Characteristics of aerosol aminiums over a coastal city in North China: Insights from the divergent impacts of marine and terrestrial influences. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 918:170672. [PMID: 38316306 DOI: 10.1016/j.scitotenv.2024.170672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 02/01/2024] [Accepted: 02/02/2024] [Indexed: 02/07/2024]
Abstract
Aminium ions, as crucial alkaline components within fine atmospheric particles, have a notable influence on new particle formation and haze occurrence. Their concentrations within coastal atmosphere depict considerable variation due to the interplay of distinctive marine and terrestrial sources, further complicated by dynamic meteorological conditions. This study conducted a comprehensive examination of aminiums ions concentrations, with a particular focus on methylaminium (MMAH+), dimethylaminium (DMAH+), trimethylaminium (TMAH+), and triethylaminium (TEAH+) within PM2.5, over varying seasons (summer, autumn, and winter of 2019 and summer of 2021), at an urban site in the coastal megacity of Qingdao, Northern China. The investigations revealed that the total concentration of particulate aminium ions (∑Aminium) was 21.6 ± 23.6 ng/m3, exhibiting higher values in the autumn and winter compared to the two summer periods. Considering diurnal variations during autumn and winter, concentrations of particulate aminium ions (excluding TEAH+) exhibited a slight increase during the day compared to night, with a notable peak during the morning hours. However, it was not the case for TEAH+, which was argued to be readily oxidized by ambient oxidants in the afternoon. Additionally, the ∑Aminium within the summer demonstrated markedly elevated levels during the day compared to night, potentially attributed to daytime sea fog associated with sea-land breeze interactions. Positive matrix factorization results indicate terrestrial anthropogenic emissions, including vehicle emission mixed with road dust and primary pollution, as the primary sources of MMAH+ and DMAH+. Conversely, TMAH+ was predominantly emitted from agricultural and marine sources. With the dominance of sea breeze in summer, TMAH+ was identified as a primary marine emission correlated with sea salt, while MMAH+, DMAH+, and TEAH+ were postulated to undergo secondary formation. Furthermore, a notable inverse correlation was observed between TMAH+ and methanesulfonate in PM2.5, consistent with dynamic emissions of sulfur-content and nitrogen-content gases reported in the literature.
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Affiliation(s)
- Yiyan Yang
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Mingge Sun
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Guanru Wu
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Yuxuan Qi
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Wenqing Zhu
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Yunhui Zhao
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Yujiao Zhu
- Environment Research Institute, Shandong University, Qingdao 266237, China
| | - Wenshuai Li
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Yanjing Zhang
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Nana Wang
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China; Jiaozhou Meteorological Bureau, Qingdao Meteorological Bureau, Qingdao 266300, China
| | - Lifang Sheng
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Wencai Wang
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
| | - Xu Yu
- Division of Environment and Sustainability, Hong Kong University of Science and Technology, 999077, Hong Kong
| | - Jianzhen Yu
- Division of Environment and Sustainability, Hong Kong University of Science and Technology, 999077, Hong Kong; Department of Chemistry, Hong Kong University of Science and Technology, 999077, Hong Kong
| | - Xiaohong Yao
- Key Laboratory of Marine Environment and Ecology (MoE), Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ministry of Education, Ocean University of China, Qingdao 266100, China; Laboratory for Marine Ecology and Environmental Sciences, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China
| | - Yang Zhou
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao 266100, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China.
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Attri P, Mani D, Satyanarayanan M, Reddy D, Kumar D, Sarkar S, Kumar S, Hegde P. Atmospheric aerosol chemistry and source apportionment of PM10 using stable carbon isotopes and PMF modelling during fireworks over Hyderabad, southern India. Heliyon 2024; 10:e26746. [PMID: 38495155 PMCID: PMC10943357 DOI: 10.1016/j.heliyon.2024.e26746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 02/11/2024] [Accepted: 02/19/2024] [Indexed: 03/19/2024] Open
Abstract
This study examined the influence of fireworks on atmospheric aerosols over the Southern Indian city of Hyderabad during festival of Diwali using mass closure, stable carbon isotopes and the EPA-PMF model. Identification of chemical species in day and night time aerosol samples for 2019 and 2020 Diwali weeks showed increased concentrations of NH4+, NO3-, SO42-, K+, organic carbon (OC), Ba, Pb and Li, which were considered as tracers for fireworks. PM10 source apportionment was done using inorganic (trace elements, major ions) and carbonaceous (organic and elemental carbon; OC & EC) constituents, along with stable isotopic compositions of TC and EC. K+/Na+ ∼1 and K+nss/OC > 0.5 indicated contribution from fireworks. High NO3-, NH4+, Na+, Cl- and SO42- suggested the presence of deliquescent salts NaCl, NH4NO3 and (NH4)2SO4. TAE/TCE >1 suggested H+ exclusion, indicating possible presence of H2SO4 and NH4HSO4 in the aerosols. Ba, Pb, Sb, Sr and Fe increased by 305 (87), 12 (11), 12 (3), 3 (2) and 3 (4) times on Diwali nights, compared to pre-Diwali of 2019 (2020), and are considered as metallic tracers of fireworks. δ13CTC and δ13CEC in aerosols closely resembled that of diesel and C3 plant burning emissions, with meagre contribution from firecrackers during Diwali period. The δ13CEC was relatively depleted than δ13CTC and δ13COC. For both years, δ13COC-EC (δ13COC - δ13CEC) were positive, suggesting photochemical aging of aerosols during long-range transport, while for pre-Diwali 2019 and post-Diwali 2020, δ13COC-EC were negative with high OC/EC ratio, implying secondary organic aerosols formation. High toluene during Diwali week contributed to fresh SOA formation, which reacted with precursor 12C, leading to 13C depletions. Eight-factored EPA-PMF source apportionment indicated highest contribution from residue/waste burning, followed by marine/dust soil and fireworks, while least was contributed from solid fuel/coal combustion.
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Affiliation(s)
- Pradeep Attri
- Centre for Earth, Ocean and Atmospheric Sciences, University of Hyderabad, Telangana 500046, India
| | - Devleena Mani
- Centre for Earth, Ocean and Atmospheric Sciences, University of Hyderabad, Telangana 500046, India
| | - M. Satyanarayanan
- CSIR-National Geophysical Research Institute, Hyderabad, Telangana 500007, India
| | - D.V. Reddy
- CSIR-National Geophysical Research Institute, Hyderabad, Telangana 500007, India
| | - Devender Kumar
- CSIR-National Geophysical Research Institute, Hyderabad, Telangana 500007, India
| | | | - Sanjeev Kumar
- Physical Research Laboratory, Ahmedabad, Gujarat 380009, India
| | - Prashant Hegde
- Space Physics Laboratory, Vikram Sarabhai Space Centre, Thiruvananthapuram, Kerala 695021, India
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Adeniran JA, Ogunlade BT, Abdulraheem KA, Odediran ET, Atanda AS, Oyeneye AK, Yusuf RO. Concentration and sources of persistent organic pollutants within the vicinity of a scrap-iron smelting plant: Seasonal pattern and health risk assessment. JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH. PART C, TOXICOLOGY AND CARCINOGENESIS 2024; 42:16-32. [PMID: 38060326 DOI: 10.1080/26896583.2023.2286863] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/23/2024]
Abstract
Polychlorinated biphenyls (PCBs) are a class of ubiquitous and significant synthetic organic chemicals that pose deleterious threats to the environment and human health. This study examined the concentration, indoor-outdoor and seasonal change, sources, and health effects of PCBs in particulate-bound dust near a scrap iron recycling plant. PCBs levels were determined in samples using gas chromatograph mass spectrometer. The results indicated that 5 Cl atoms PCB constituted the majority of PCBs (41% overall), contributing 43% during the rainy season and 39% during the dry season. Dioxin-like PCBs (DLPCBs) contributed 38% during the rainy season and 33% during the dry season. In addition, DLPCB accounted for 26% and 40% of indoor and outdoor PCB emissions, respectively. Iron and steel production were identified as the highest identified contributing sources, accounting for 76% of PCB emissions in the rainy season, while plastic combustion had the highest contribution in the dry season, accounting for 44% of PCB emissions. Incremental Lifetime Cancer Risk assessment showed ingestion as the main exposure pathway for children and adults during the two seasons (74.42% and 58.24%, respectively), followed by dermal exposure, while inhalation had the least contribution. A multifaced approach involving relevant agencies, the industry, and the community is required to reduce exposure.
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Ding S, Jiang J, Li Y. Quercetin alleviates PM 2.5-induced chronic lung injury in mice by targeting ferroptosis. PeerJ 2024; 12:e16703. [PMID: 38188138 PMCID: PMC10768656 DOI: 10.7717/peerj.16703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 11/29/2023] [Indexed: 01/09/2024] Open
Abstract
Background PM2.5 is a well-known harmful air pollutant that can lead to acute exacerbation and aggravation of respiratory diseases. Although ferroptosis is involves in the pathological process of pulmonary disease, the potential mechanism of ferroptosis in PM2.5-caused lung inflammation and fibrosis need to be further clarified. Quercetin is a phenolic compound that can inhibit ferroptosis in various diseases. Hence, this study explores the role of ferroptosis in lung injury induced by PM2.5 in order to further elucidate the beneficial effect of quercetin and its underlying mechanism. Methods C57BL/6J mice were treated with either saline or PM2.5 by intratracheal instillation 20 times (once every two days). Additionally, PM2.5-treated mice were supplemented with two doses of quercetin. Lung injury, lipid peroxidation, iron content and ferroptosis marker protein expression and the Nrf2 signaling pathway were evaluated. In vitro, cell experiments were applied to verify the mechanisms underlying the links between Nrf2 signaling pathway activation and ferroptosis as well as between ferroptosis and inflammation. Results In vivo, PM2.5 increased lung inflammation and caused lung fibrosis and increased lipid peroxidation contents, iron contents and ferroptosis markers in lung tissues; these effects were significantly reversed by quercetin. Additionally, quercetin upregulated the nuclear Nrf2 expression and downregulated Keap1 expression in lung tissues of PM2.5-exposed mice. Quercetin decreased lipid peroxidation products, iron contents and ferroptosis levels and increased the nuclear translocation of Nrf2 and the degradation of Keap1 in PM2.5-exposed BEAS-2B cells. Moreover, we found that quercetin and dimethyl fumarate markedly decreased lipid peroxidation production and ferroptosis by activating the Nrf2-Keap1 pathway in PM2.5-exposed cells. Furthermore, quercetin reduced inflammatory cytokines and TGF-β1 in PM2.5-exposed cells. Conclusion Our data suggested that Nrf2 is involved in ferroptosis in PM2.5-induced lung injury, and quercetin can alleviate these adverse effects via activating Nrf2-Keap1 signaling pathway.
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Affiliation(s)
- Shibin Ding
- Public Health and Management, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, China
| | - Jinjin Jiang
- Public Health and Management, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, China
| | - Yang Li
- Public Health and Management, Jiangsu Vocational College of Medicine, Yancheng, Jiangsu, China
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Wang J, Yuan J, Hou Q, Yang Z, You Y, Yu T, Ji J, Dou L, Ha X, Sheng W, Liu X. Distribution of potentially toxic elements in soils and sediments in Pearl River Delta, China: Natural versus anthropogenic source discrimination. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 903:166573. [PMID: 37633402 DOI: 10.1016/j.scitotenv.2023.166573] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 08/08/2023] [Accepted: 08/23/2023] [Indexed: 08/28/2023]
Abstract
Although anthropogenic contamination has been regarded as the most important source of potentially toxic elements (PTEs) in soils of large river delta plains, the extent to which human activities affect PTEs in soils is worth exploring. This study used high density geochemical data to distinguish source patterns of PTEs in soils of the Pearl River Delta Economic Zone, a large industrialized and urbanized area in China. Enrichment factor, discriminant analysis, principal components analysis, cumulative distribution function, and positive matrix factorization were used to identify sources of PTEs in soils. The results indicated that parent material was the most significant factor affecting geochemical characteristics of PTEs in soils. Median concentrations of Cd, Cr, Cu, Hg, Pb, and Zn were 0.400, 88.5, 40.5, 0.143, 43.0, and 116.0 mg/kg for stream sediments, 0.333, 75.7, 39.0, 0.121, 42.6, and 98.5 mg/kg for deep soils, and 0.365, 74.0, 45.1, 0.143, 44.6, and 119.5 mg/kg for surface soils, respectively, all of which exceed relevant reference standards. Compared with stream sediments and deep soils, surface soils exhibit substantial concentrations of PTEs. Chemical weathering and erosion of parent materials distributed in the Pearl River Delta were the main sources of PTEs in soils. Diffuse contamination and many small local contamination sources distributed throughout the study area were the most significant anthropogenic sources of PTEs in surface soils. Intensive human activities failed to change the soil geochemical characteristics derived from the parent material at the regional scale. However, it could induce non-point source pollution and local severe PTEs pollution in surface soils.
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Affiliation(s)
- Jiaxin Wang
- School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China.
| | - Jiaxin Yuan
- Tianjin Research Institute for Water Transport Engineering, M.O.T, Tianjin, 300456, China
| | - Qingye Hou
- School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China.
| | - Zhongfang Yang
- School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China.
| | - Yuanhang You
- 3rd Geological Team, Guangdong Geological Bureau, Shaoguan 512030, China
| | - Tao Yu
- School of sciences, China University of Geosciences, Beijing 100083, China.
| | - Junfeng Ji
- School of Earth Sciences and Engineering, Nanjing University, Nanjing 210093, China.
| | - Lei Dou
- Institute of Guangdong Geological Survey, Guangdong Geological Bureau, Guangzhou 510080, China
| | - Xianrui Ha
- School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China.
| | - Weikang Sheng
- School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China
| | - Xu Liu
- School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China
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Liu R, Wang Y, Wang L, Wang Y, Peng X, Cao L, Liu Y. Spatio-temporal distribution and source identification of antibiotics in suspended matter in the Fen River Basin. CHEMOSPHERE 2023; 345:140497. [PMID: 37866500 DOI: 10.1016/j.chemosphere.2023.140497] [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: 03/26/2023] [Revised: 10/18/2023] [Accepted: 10/19/2023] [Indexed: 10/24/2023]
Abstract
In this study, 26 typical antibiotics in the suspended matter of the Fen River basin were analyzed during the wet and dry seasons, and the main sources of antibiotic contamination were further identified. The results showed that the concentrations of antibiotics in the suspended matter varied seasonally. Sixteen antibiotics were detected in the suspended matter during the wet season with an average concentration of 463.56 ng/L. However, a total of 21 antibiotics were detected in the dry season, with an average concentration of 106.00 ng/L. The concentration of chloramphenicol antibiotics was outstanding in the wet season and dry season. The spatial distribution of the antibiotics in suspended matter showed little spatial discrepancy during the wet season. During the dry season, nevertheless, the concentration was higher upstream than midstream and downstream. The main sources of antibiotics in the Fen River Basin were livestock and poultry breeding, wastewater from wastewater treatment plants (WWTPs), agricultural drainage, domestic sewage, and pharmaceutical wastewater. Wastewater from WWTPs and domestic sewage were identified as two primary sources in the suspended matter during the wet season, with wastewater from WWTPs contributing the most accounting for 37%. While the most significant source of antibiotics in the suspended matter in the dry season was pharmaceutical wastewater, accounting for 36%. In addition, the contribution proportion of sources for antibiotics exhibited discrepant spatial distribution characteristics. In the wet season, wastewater from WWTPs dominated in the upstream and midstream, and livestock and poultry breeding was prominent in the midstream and downstream. Pharmaceutical wastewater was the main source in the midstream and downstream regions during the dry season.
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Affiliation(s)
- Ruimin Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Yunan Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Linfang Wang
- Sorghum Research Institute, Shanxi Agricultural University/Shanxi Academy of Agricultural Sciences, No.238, Yuhuaxi Street, Jinzhong, 030600, China.
| | - Yifan Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Xinyuan Peng
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Leiping Cao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Yue Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
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Bai Z, Shao J, Xu W, Zhu K, Zhao L, Wang L, Chen J. An unneglected source to ambient brown carbon and VOCs at harbor area: LNG tractor truck. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 900:165575. [PMID: 37499815 DOI: 10.1016/j.scitotenv.2023.165575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 06/23/2023] [Accepted: 07/14/2023] [Indexed: 07/29/2023]
Abstract
The ambient air quality of harbors area in Asia is commonly more polluted compared to other continents. The airborne pollutant is directly or indirectly related to a significant impact of traffic emissions. This study for the first time assessed the impacts on brown carbon (BrC) and volatile organic compounds (VOCs) from in-port liquid natural gas (LNG) tractor truck at harbor areas, via conducting real-time monitoring of VOCs characteristic and sampling for ambient air at a harbor (named as W harbor) in Shanghai, China, collecting emissions of in-port LNG tractor truck and miniCast in laboratory, as well as statistics of external container diesel trucks in the port for further validation. HPLC/DAD/Q-Tof MS was adopted for sample analysis. Results showed that many CHO compounds were associated with vehicle exhausts. Among of them, aliphatic CHO compounds with low degree of unsaturation were identified as fatty acids and fatty acid methyl esters extensively existing in fuel combustion emissions. And non-aliphatic CHO compounds characterized by low O/C ratios (<0.17) identified for the harbor air came from the emissions of in-port LNG power trucks with low-speed driving and idling. The ambient average non-methane total hydrocarbons (NMHC) concentration (0.59 ppm) at W harbor was much greater than that for other areas in Shanghai. The higher ratios of toluene/benzene (3.30) and m/p-xylene/ethylbenzene (3.11) observed at W harbor implied instead of external container diesel trucks, the dominating contributing of internal LNG tractor trucks to ambient VOCs cannot be neglected. This study concluded that LNG is not as clean as it was expected. The LNG-fueled vehicles can produce strong light-absorption chromophores as well as high concentration of VOCs.
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Affiliation(s)
- Zhe Bai
- School of Ecology and Environment, Inner Mongolia University, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Institute of Eco-Chongming (IEC), Shanghai, China
| | - Jiantao Shao
- China Construction Eighth Engineering Division Corp., Ltd., Shanghai 200112, China
| | - Wei Xu
- Shanghai Jianke Environmental Techonology Co., Ltd, China
| | - Ke Zhu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Institute of Eco-Chongming (IEC), Shanghai, China
| | - Ling Zhao
- School of Ecology and Environment, Inner Mongolia University, China
| | - Lina Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Institute of Eco-Chongming (IEC), Shanghai, China.
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Institute of Eco-Chongming (IEC), Shanghai, China
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15
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Sun P, Yang J, Wu Y, Liu X, Huang Y, He EK, He TH, Liu M. Spatial modeling and source identification of PAHs in soils and roadside dusts from Hangzhou, a new first-tier megcity of China. JOURNAL OF HAZARDOUS MATERIALS 2023; 460:132366. [PMID: 37634381 DOI: 10.1016/j.jhazmat.2023.132366] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/16/2023] [Accepted: 08/20/2023] [Indexed: 08/29/2023]
Abstract
Soil (n = 100) and roadside dust (n = 97) samples across a new first-tier megacity (Hangzhou, East China) were collected to systematically survey the spatial patterns and sources of 16 priority Polycyclic aromatic hydrocarbons (PAHs). The total PAH (Σ16PAH) concentrations in the surface soils exhibited an average of 329 ± 168 ng/g with a range of 67.7-2950 ng/g. 45 % of soils suffered from the weak - heavy PAH contaminations. By contrast, the average concentration of Σ16PAHs in roadside dusts was approximately three times higher than that found in the soils. Within both soil and dust samples, PAHs with a high molecular weight (HMW, 4-6 rings) were the dominant homologs. Spatial lag models revealed that industrial and traffic-related variables significantly influenced the spatial distribution of PAHs in dusts. Furthermore, a positive matrix factorization model indicated that Σ16PAHs in soils and dusts mainly derived from coal-related production/combustion and automobile exhaust emission (65.0 % and 77.9 %, respectively). The isotopic composition analysis conducted on heavily polluted samples further demonstrated that HMW PAHs in these soils and dusts predominantly originated from coal processing and liquid fossil fuel combustion. Overall, the findings of this study suggest that the intensive urban construction and human activities strongly stimulated PAH accumulations in soils and dusts during the rapid urbanization of Hangzhou.
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Affiliation(s)
- Pei Sun
- 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
| | - Jing Yang
- 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.
| | - Yan Wu
- 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
| | - Xia 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
| | - 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
| | - Er-Kai 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
| | - Tian-Hao 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
| | - 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.
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16
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Ghosh S, Banerjee S, Mukherjee A, Bhattacharyya P. Appraise potassium chemistry and distribution patterns in tailing soil, India: Through quantity - Intensity relations and multi model statistical methods. CHEMOSPHERE 2023:139184. [PMID: 37302492 DOI: 10.1016/j.chemosphere.2023.139184] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 06/07/2023] [Accepted: 06/09/2023] [Indexed: 06/13/2023]
Abstract
Tailings are waste materials left behind after mineral extraction. Giridih district of Jharkhand, India has the second largest ore of mica mines in the country. This study evaluated the forms of potassium (K+) and quantity-intensity relationships in soils contaminated by tailings around the abundant mica mines. A total of 63 rice rhizosphere soil samples (8-10 cm depth) were collected from agricultural fields near 21 mica mines in the Giridih district at different distances: 10 m (zone 1), 50 m (zone 2), and 100 m (zone 3). The samples were collected to quantify various forms of potassium in the soil and characterize non-exchangeable K (NEK) reserves and Q/I isotherms. The semi-logarithmic release of NEK with continuous extractions suggests a decrease in release over time. Significant values of threshold K+ levels were observed in zone 1 samples. As K+ concentrations increased, the activity ratio (AReK) and its corresponding labile K+ (KL) concentrations decreased. The AReK, KL, and fixed K+ (KX) values were higher in zone 1 [AReK: 3.2 (mol L-1)1/2 × 10-4, KL: 0.058 cmol kg-1, and KX: 0.038 cmol kg-1), except for readily available K+ (K0) for zone 2 (0.028 cmol kg-1). The potential buffering capacity and K+ potential values were higher in zone 2 soils. In zone 1, Vanselow selectivity coefficients (KV) and Krishnamoorthy-Davis-Overstreet selectivity coefficients (KKDO) were higher, while Gapon constants were higher in zone 3. It was found that AReK was significantly correlated with K0, KL, K+ saturation, -ΔG, KV, and KKDO. Different statistical methods such as positive matrix factorization, self-organizing maps, geostatistics, and Monte Carlo simulation approaches were employed to predict soil K+ enrichment, source apportionment, distribution patterns, availability for plants, and contribution to soil K+ maintenance. Thus, this study significantly contributes to understanding K+ dynamics in mica mine soils and operational K+ management.
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Affiliation(s)
- Saibal Ghosh
- Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, 815301, Jharkhand, India
| | - Sonali Banerjee
- Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, 815301, Jharkhand, India
| | - Abhishek Mukherjee
- Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, 815301, Jharkhand, India
| | - Pradip Bhattacharyya
- Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, 815301, Jharkhand, India.
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Jang E, Choi S, Yoo E, Hyun S, An J. Impact of shipping emissions regulation on urban aerosol composition changes revealed by receptor and numerical modelling. NPJ CLIMATE AND ATMOSPHERIC SCIENCE 2023; 6:52. [PMID: 37274460 PMCID: PMC10226717 DOI: 10.1038/s41612-023-00364-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 05/03/2023] [Indexed: 06/06/2023]
Abstract
Various shipping emissions controls have recently been implemented at both local and national scales. However, it is difficult to track the effect of these on PM2.5 levels, owing to the non-linear relationship that exists between changes in precursor emissions and PM components. Positive Matrix Factorisation (PMF) identifies that a switch to cleaner fuels since January 2020 results in considerable reductions in shipping-source-related PM2.5, especially sulphate aerosols and metals (V and Ni), not only at a port site but also at an urban background site. CMAQ sensitivity analysis reveals that the reduction of secondary inorganic aerosols (SIA) further extends to inland areas downwind from ports. In addition, mitigation of secondary organic aerosols (SOA) in coastal urban areas can be anticipated either from the results of receptor modelling or from CMAQ simulations. The results in this study show the possibility of obtaining human health benefits in coastal cities through shipping emission controls.
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Affiliation(s)
- Eunhwa Jang
- Busan Metropolitan City Institute of Health and Environment, 120, Hambakbong-ro, 140beon-gil, Buk-gu, Busan, 46616 Republic of Korea
| | - Seongwoo Choi
- Busan Metropolitan City Institute of Health and Environment, 120, Hambakbong-ro, 140beon-gil, Buk-gu, Busan, 46616 Republic of Korea
| | - Eunchul Yoo
- Busan Metropolitan City Institute of Health and Environment, 120, Hambakbong-ro, 140beon-gil, Buk-gu, Busan, 46616 Republic of Korea
| | - Sangmin Hyun
- Marine Environmental Research Center, Korea Institute of Ocean Science and Technology, 385, Haeyang-ro, Yeongdo-gu, Busan, 49111 Republic of Korea
| | - Joongeon An
- Risk Assessment Research Center, Korea Institute of Ocean Science and Technology, Geoje, 53201 Republic of Korea
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18
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Gamelas CA, Canha N, Vicente A, Silva A, Borges S, Alves C, Kertesz Z, Almeida SM. Source apportionment of PM 2.5 before and after COVID-19 lockdown in an urban-industrial area of the Lisbon metropolitan area, Portugal. URBAN CLIMATE 2023; 49:101446. [PMID: 36820273 PMCID: PMC9932663 DOI: 10.1016/j.uclim.2023.101446] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 01/06/2023] [Accepted: 02/11/2023] [Indexed: 06/18/2023]
Abstract
The lockdowns held due to the COVID-19 pandemic conducted to changes in air quality. This study aimed to understand the variability of PM2.5 levels and composition in an urban-industrial area of the Lisbon Metropolitan Area and to identify the contribution of the different sources. The composition of PM2.5 was assessed for 24 elements (by PIXE), secondary inorganic ions and black carbon. The PM2.5 mean concentration for the period (December 2019 to November 2020) was 13 ± 11 μg.m-3. The most abundant species in PM2.5 were BC (19.9%), SO4 2- (15.4%), NO3 - (11.6%) and NH4 + (5.3%). The impact of the restrictions imposed by the COVID-19 pandemic on the PM levels was found by comparison with the previous six years. The concentrations of all the PM2.5 components, except Al, Ba, Ca, Si and SO4 2-, were significantly higher in the winter/pre-confinement than in post-confinement period. A total of seven sources were identified by Positive Matrix Factorisation (PMF): soil, secondary sulphate, fuel-oil combustion, sea, vehicle non-exhaust, vehicle exhaust, and industry. Sources were greatly influenced by the restrictions imposed by the COVID-19 pandemic, with vehicle exhaust showing the sharpest decrease. Secondary sulphate predominated in summer/post-confinement. PM2.5 levels and composition also varied with the types of air mass trajectories.
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Affiliation(s)
- Carla A Gamelas
- Centro de Ciências e Tecnologias Nucleares, Instituto Superior Técnico, Universidade de Lisboa, Estrada Nacional 10, 2695-066 Bobadela, Portugal
- Instituto Politécnico de Setúbal, Escola Superior de Tecnologia de Setúbal, Centro de Investigação em Energia e Ambiente, IPS Campus, 2914-508 Setúbal, Portugal
| | - Nuno Canha
- Centro de Ciências e Tecnologias Nucleares, Instituto Superior Técnico, Universidade de Lisboa, Estrada Nacional 10, 2695-066 Bobadela, Portugal
| | - Ana Vicente
- CESAM-Centre for Environmental and Marine Studies, Department of Environment and Planning, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Anabela Silva
- Câmara Municipal do Seixal, Divisão de Desenvolvimento Estratégico, Gabinete Seixal Sustentável e Inovação, 2844-001 Seixal, Portugal
| | - Sónia Borges
- Câmara Municipal do Seixal, Divisão de Desenvolvimento Estratégico, Gabinete Seixal Sustentável e Inovação, 2844-001 Seixal, Portugal
| | - Célia Alves
- CESAM-Centre for Environmental and Marine Studies, Department of Environment and Planning, University of Aveiro, 3810-193 Aveiro, Portugal
| | - Zsofia Kertesz
- Laboratory for Heritage Science, Institute for Nuclear Research, H-4026 Debrecen, Hungary
| | - Susana Marta Almeida
- Centro de Ciências e Tecnologias Nucleares, Instituto Superior Técnico, Universidade de Lisboa, Estrada Nacional 10, 2695-066 Bobadela, Portugal
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Liu W, Yu Y, Li M, Yu H, Shi M, Cheng C, Hu T, Mao Y, Zhang J, Liang L, Qi S, Xing X. Bioavailability and regional transport of PM 2.5 during heavy haze episode in typical coal city site of Fenwei Plain, China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2023; 45:1933-1949. [PMID: 35752731 DOI: 10.1007/s10653-022-01310-z] [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: 11/22/2021] [Accepted: 05/15/2022] [Indexed: 06/15/2023]
Abstract
Despite the decrease in anthropogenic emissions, haze episodes were still frequent in the Fenwei Plain, which was identified as one of the three key areas for air pollution control. Herein, PM2.5 samples were collected to investigate the influence of festival effect during the Chinese Spring Festival from February 2rd to 13th, 2019, in Linfen on the Fenwei Plain. The characteristics of element pollution, enrichment factor, source apportionment, regional transport of PM2.5, and health risk assessment were discussed. Meanwhile, the simulated lung fluid method (SLF) was carried out to accurately assess the inhalation risks of heavy metals (HMs). Results indicated that the average concentration of PM2.5 was 195.6 μg·m-3 during the studying period. Road fugitive dust (15.6%), firework burning source (25.6%), industrial emission (30.5%), and coal combustion (28.3%) were identified by positive matrix factorization (PMF) modeling. Using the HYSPLIT trajectory model, air masses from the central Shaanxi, southern Hebei, and northern Henan were the dominant transport paths during the Spring Festival, which contributed 21.9 and 41.2% of total trajectories, respectively. The findings that high PSCF and CWT levels were found in central Shaanxi, southern Hebei, and northern Henan were confirmed. The SLF mean bioaccessibility (%) of the solubility of particulate metals was in order of Mn > Ni > Sb > Ba > Zn > Pb > Cr. However, the carcinogenic risk value of Cr was the highest, exceeding the maximum acceptable risk. The present study provided important information for further analyzing the air pollution cause of Fenwei Plain.
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Affiliation(s)
- Weijie Liu
- School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430074, China
- Hubei Key Laboratory of Mine Environmental Pollution Control and Remediation, School of Environmental Science and Engineering, Hubei Polytechnic University, Huangshi, 435003, China
| | - Yue Yu
- School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430074, China
| | - Miao Li
- School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430074, China
- Hubei Key Laboratory of Mine Environmental Pollution Control and Remediation, School of Environmental Science and Engineering, Hubei Polytechnic University, Huangshi, 435003, China
| | - Haikuo Yu
- School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430074, China
| | - Mingming Shi
- School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430074, China
| | - Cheng Cheng
- School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430074, China
| | - Tianpeng Hu
- School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430074, China
| | - Yao Mao
- School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430074, China
| | - Jiaquan Zhang
- Hubei Key Laboratory of Mine Environmental Pollution Control and Remediation, School of Environmental Science and Engineering, Hubei Polytechnic University, Huangshi, 435003, China
| | - Lili Liang
- School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430074, China
| | - Shihua Qi
- School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430074, China
| | - Xinli Xing
- School of Environmental Studies & State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan, 430074, China.
- Hubei Key Laboratory of Mine Environmental Pollution Control and Remediation, School of Environmental Science and Engineering, Hubei Polytechnic University, Huangshi, 435003, China.
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20
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Ghosh S, Banerjee S, Prajapati J, Mandal J, Mukherjee A, Bhattacharyya P. Pollution and health risk assessment of mine tailings contaminated soils in India from toxic elements with statistical approaches. CHEMOSPHERE 2023; 324:138267. [PMID: 36871802 DOI: 10.1016/j.chemosphere.2023.138267] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 02/09/2023] [Accepted: 02/26/2023] [Indexed: 06/18/2023]
Abstract
The rapid mining activities of mica mines in Giridih district, India, have led to toxic metal pollution of agricultural soil. This is a key concern for environmental risk and human health. 63 top soil samples were collected at a distance of 10 m (Zone 1), 50 m (Zone 2), and 100 m (Zone 3) from near 21 mica mines with agriculture fields. The mean concentration of total and bio-available toxic elements (TEs - Cr, Ni, Pb, Cu, Zn, and Cd) was higher in zone 1 across three zones. The Positive matrix factorization model (PMF) and Pearson Correlation analysis were used to identify waste mica soils with TEs. Based on PMF results, Ni, Cr, Cd, and Pb were the most promising pollutants and carried higher environmental risks than the other TEs. Using the self-organizing map (SOM), zone 1 was identified as a high-potential source of TEs. Soil quality indexes for TEs risk zone 1 were found to be higher across three zones. Based on the health risk index (HI), children are more adversely affected than adults. Monte Carlo simulations (MCS) model and sensitivity analysis of total carcinogenic risk (TCR), children were more affected by Cr and Ni than adults through ingestion exposure pathways. Finally, a geostatistical tool was developed to predict the spatial distribution patterns of TEs contributed by mica mines. In a probabilistic assessment of all populations, non-carcinogenic risks appeared to be negligible. The fact that there is a TCR can't be ignored, and children are more likely to develop it than adults. Mica mines with TEs contamination were found to be the most significant anthropogenic contributor to health risks based on source-oriented risk assessment.
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Affiliation(s)
- Saibal Ghosh
- Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, Jharkhand, 815301, India
| | - Sonali Banerjee
- Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, Jharkhand, 815301, India
| | - Jyoti Prajapati
- Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, Jharkhand, 815301, India; Department of Mathematics, Institute of Chemical Technology, Mumbai, India
| | - Jajati Mandal
- School of Science, Engineering & Environment, University of Sulford, Manchester, M5 4WT, UK
| | - Abhishek Mukherjee
- Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, Jharkhand, 815301, India
| | - Pradip Bhattacharyya
- Agricultural and Ecological Research Unit, Indian Statistical Institute, Giridih, Jharkhand, 815301, India.
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21
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Fakhri N, Fadel M, Pikridas M, Sciare J, Hayes PL, Afif C. Source apportionment of PM 2.5 using organic/inorganic markers and emission inventory evaluation in the East Mediterranean-Middle East city of Beirut. ENVIRONMENTAL RESEARCH 2023; 223:115446. [PMID: 36758920 DOI: 10.1016/j.envres.2023.115446] [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: 11/28/2022] [Revised: 01/21/2023] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
Source contributions to PM2.5 concentrations were evaluated in Greater Beirut (Lebanon), a typical East Mediterranean-Middle East (EMME) city, using Positive Matrix Factorization with two approaches. The first approach included only inorganic species (PMF-trad) and the other approach added organic markers (PMF-org). PMF-org identified 4 additional sources, and large discrepancies in contributions were observed for some major sources found in both approaches, highlighting the importance of including organic markers. The traffic factor was underestimated in PMF-trad by 2 to 7 folds. Moreover, results showed that this city is prone to high desert dust concentrations originating from uncontrollable dust storm events, like all cities in the Middle East. A PM2.5 mitigation plan taking into account the potency of the identified sources was developed. Sources like diesel generators or traffic presented smaller contributions in term of mass compared to desert dust, however the health impact of the latter is relatively small and actions should target sources with the highest potency. Local emission inventories in the EMME region are scarce and studies typically rely on global emission inventories for local air quality management plans, but these inventories significantly underestimate Beirut's road transport emissions by more than an order of magnitude.
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Affiliation(s)
- Nansi Fakhri
- EMMA Research Group, Centre d'Analyses et de Recherche, Faculty of Sciences, Université Saint-Joseph, Beirut, Lebanon; Department of Chemistry, Faculty of Arts and Sciences, Université de Montréal, Montréal, Québec, Canada
| | - Marc Fadel
- EMMA Research Group, Centre d'Analyses et de Recherche, Faculty of Sciences, Université Saint-Joseph, Beirut, Lebanon
| | - Michael Pikridas
- Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus
| | - Jean Sciare
- Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus
| | - Patrick L Hayes
- Department of Chemistry, Faculty of Arts and Sciences, Université de Montréal, Montréal, Québec, Canada.
| | - Charbel Afif
- EMMA Research Group, Centre d'Analyses et de Recherche, Faculty of Sciences, Université Saint-Joseph, Beirut, Lebanon; Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus.
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22
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Cai P, Cai G, Yang J, Li X, Lin J, Li S, Zhao L. Distribution, risk assessment, and quantitative source apportionment of heavy metals in surface sediments from the shelf of the northern South China Sea. MARINE POLLUTION BULLETIN 2023; 187:114589. [PMID: 36646001 DOI: 10.1016/j.marpolbul.2023.114589] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 12/08/2022] [Accepted: 01/04/2023] [Indexed: 05/15/2023]
Abstract
The concentration of heavy metals (Cu, Pb, Zn, Cr, Co, and Ni) from 421 sediment samples from the shelf of the northern margin of the South China Sea (SNSCS) was analyzed. The heavy metal content and calculated potential ecological indicators (Eri < 40 and RI < 160) indicate that there is low potential ecological risk of heavy metal pollution in the SNSCS. The mean effects range-median quotient (M-ERM-Q) and hazard quotient (HQ) values of sediment toxicological characteristics indicate that heavy metals are a potential toxicological risk. The high-risk area is mainly distributed in the southwest of the nearshore SNSCS. The positive matrix factorization (PMF) analysis results showed that major contributors to heavy metal pollution were natural sources and anthropogenic activities in the SNSCS. The government should pay particular attention to the monitoring of heavy metals in the nearshore southwest of the SNSCS.
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Affiliation(s)
- Pengjie Cai
- Guangzhou Marine Geological Survey, China Geological Survey, 510760 Guangzhou, China; State Key Laboratory for Mineral Deposits Research, School of Earth Sciences and Engineering, Nanjing University, 210023 Nanjing, China.
| | - Guanqiang Cai
- Guangzhou Marine Geological Survey, China Geological Survey, 510760 Guangzhou, China; Southern Marine Science and Engineering Guangdong Laboratory (Guang Zhou), 511458 Guangzhou, China.
| | - Jingsui Yang
- Guangzhou Marine Geological Survey, China Geological Survey, 510760 Guangzhou, China; State Key Laboratory for Mineral Deposits Research, School of Earth Sciences and Engineering, Nanjing University, 210023 Nanjing, China; Southern Marine Science and Engineering Guangdong Laboratory (Guang Zhou), 511458 Guangzhou, China
| | - Xuejie Li
- Guangzhou Marine Geological Survey, China Geological Survey, 510760 Guangzhou, China; Southern Marine Science and Engineering Guangdong Laboratory (Guang Zhou), 511458 Guangzhou, China
| | - Jie Lin
- Guangzhou Marine Geological Survey, China Geological Survey, 510760 Guangzhou, China
| | - Shun Li
- Guangzhou Marine Geological Survey, China Geological Survey, 510760 Guangzhou, China
| | - Li Zhao
- Guangzhou Marine Geological Survey, China Geological Survey, 510760 Guangzhou, China
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23
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Li W, Qi Y, Qu W, Qu W, Shi J, Zhang D, Liu Y, Zhang Y, Zhang W, Ren D, Ma Y, Wang X, Yi L, Sheng L, Zhou Y. PM 2.5 source apportionment identified with total and soluble elements in positive matrix factorization. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 858:159948. [PMID: 36336053 DOI: 10.1016/j.scitotenv.2022.159948] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 10/19/2022] [Accepted: 10/31/2022] [Indexed: 06/16/2023]
Abstract
Source apportionments of urban aerosols identified with positive matrix factorization (PMF) are sensitive to input variables. So far, total elements were frequently included as effective factors in PMF-based source apportionment. We investigated the advances to involve soluble parts of elements in the source apportionment with four data sets of PM2.5 composition observed at a coastal city (Qingdao) in northern China: water-soluble ions plus organic and elemental carbon (IC set), the IC set plus total elements (ICTE set), the IC set plus soluble elements (ICSE set), and the IC set plus both total elements and soluble elements (ICAE set). The apportionments of six sources, including secondary sulfate, secondary nitrate, secondary oxalate, sea salt, biomass burning and dust, were identified with the IC set. In comparison, pollutants from vehicle + coal combustion, ship emissions, waste incineration and industrial activities were also identified with the ICTE, ICSE, or ICAE sets. We found that the PMF solutions of the ICAE set could distinguish aged and fresh dust, and identify fly ash and aged pollutants from industrial sources. The profiles and corresponding time series of vehicle + coal combustion, secondary aerosols, ship emissions, sea salt, and biomass burning emissions identified with the four data sets were very similar, while discrepancies were encountered for waste incineration, dust, and industrial sources. These results indicate the benefits and potentials with total and soluble elements involved in PMF-based source apportionments.
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Affiliation(s)
- Wenshuai Li
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Yuxuan Qi
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Wen Qu
- North China Sea Marine Forecasting Center of State Ocean Administration, Qingdao, Shandong, China
| | - Wenjun Qu
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Jinhui Shi
- College of Environmental Science and Engineering, Ocean University of China, Qingdao, Shandong, China
| | - Daizhou Zhang
- Faculty of Environmental and Symbiotic Sciences, Prefectural University of Kumamoto, Kumamoto 862-8502, Japan
| | - Yingchen Liu
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Yanjing Zhang
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Weihang Zhang
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Danyang Ren
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Yuanyuan Ma
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Xinfeng Wang
- Environment Research Institute, Shandong University, Qingdao, Shandong, China
| | - Li Yi
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China
| | - Lifang Sheng
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China.
| | - Yang Zhou
- Frontier Science Center for Deep Ocean Multispheres and Earth System (FDOMES) and Physical Oceanography Laboratory, Ocean University of China, Qingdao, Shandong, China; College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, Shandong, China.
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24
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Die Feinstaubbelastung Radfahrender im innerstädtischen Straßenverkehr. ZENTRALBLATT FÜR ARBEITSMEDIZIN, ARBEITSSCHUTZ UND ERGONOMIE 2023. [DOI: 10.1007/s40664-023-00494-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
ZusammenfassungFahrradfahren als Form der aktiven Fortbewegung bietet viele gesundheitliche Vorteile durch eine gesteigerte körperliche Aktivität. In städtischer Umgebung können diese Vorteile aufgrund der intensivierten Respiration beim Radfahren und der Nähe zum Fahrzeugverkehr mit einer assoziierten Exposition von verkehrsbedingter partikulärer Luftverschmutzung durch Feinstaub beeinträchtigt werden. Das Ziel dieser Übersichtsarbeit ist, eine Darstellung der aktuellen Literatur mit mobil erhobenen Daten zur Feinstaubbelastung Radfahrender im urbanen Raum zu geben sowie die darin beschriebenen Einflussfaktoren der Feinstaubkonzentrationen aus Meteorologie, Verkehr, Architektur und zeitlichen Bedingungen zu beschreiben. Fahrradfahren repräsentiert diesbezüglich eine effiziente Vorgehensweise zur Charakterisierung individueller Feinstaubbelastungen mit der Möglichkeit einer hohen räumlich-zeitlichen Auflösung. Unter Beachtung der Hintergrundkonzentration können Aussagen zur relativen Schadstoffexposition und des einhergehenden Gesundheitsrisikos mit Erkenntnissen zugunsten einer umweltverträglichen innerstädtischen Verkehrsplanung getroffen werden.
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25
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Yang Y, Lu X, Fan P, Yu B, Wang L, Lei K, Zuo L. Multi-element features and trace metal sources of road sediment from a mega heavy industrial city in North China. CHEMOSPHERE 2023; 311:137093. [PMID: 36332740 DOI: 10.1016/j.chemosphere.2022.137093] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 09/28/2022] [Accepted: 10/30/2022] [Indexed: 06/16/2023]
Abstract
As the primary carrier of harmful elements, road sediment poses severe hazards to human health and ecological environment, especially in megacities. Based on the industrial cities in North China, this research focused on the multi-element features and the pollution levels, sources, and spatial distributions of trace metals in road sediment of Shijiazhuang. The mean levels of P (928.4 mg kg-1), S (1446.2 mg kg-1), Cl (783.9 mg kg-1), Br (5.3 mg kg-1), Na2O (2.0%), CaO (9.9%), Co (36.0 mg kg-1), Pb (38.0 mg kg-1), Cu (34.7 mg g-1), Zn (149.1 mg kg-1), Ba (518.1 mg kg-1), and Sr (224.9 mg kg-1) in road sediment were greater than their soil background values. Trace metals in most samples was moderately (75%) and heavily contaminated (15.6%). The industrial areas, congested roads, and residential areas in the northeast, middle and south of Shijiazhuang are the hotspots of trace metals pollution. A comprehensive analysis of trace metals sources indicated that Ni, V, Ga, Rb, Y, Sc, La, Ce, Zr, and Hf were mainly from natural source, which contributed to 34.2% of the total trace metals concentrations. Cu, Pb, Zn, Cr, Ba, Sr, and Mn primarily originated from mixed source, which accounted for 46.5%. Co principally came from building source, which accounted for 19.3%. This study shows that industrial discharges, construction dust and traffic emissions are the primary anthropogenic sources of trace metals in road sediment in the study area.
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Affiliation(s)
- Yufan Yang
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Xinwei Lu
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China.
| | - Peng Fan
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Bo Yu
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
| | - Lingqing Wang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China.
| | - Kai Lei
- School of Biological and Environmental Engineering, Xi'an University, Xi'an 710065, China
| | - Ling Zuo
- Department of Environmental Science, School of Geography and Tourism, Shaanxi Normal University, Xi'an 710119, China
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26
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Scerri MM, Weinbruch S, Delmaire G, Mercieca N, Nolle M, Prati P, Massabò D. Exhaust and non-exhaust contributions from road transport to PM 10 at a Southern European traffic site. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 316:120569. [PMID: 36347413 DOI: 10.1016/j.envpol.2022.120569] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 10/27/2022] [Accepted: 10/30/2022] [Indexed: 06/16/2023]
Abstract
It is a well - established fact that road traffic is one of the main contributors to ambient levels of airborne particulate matter (APM). This study was carried out at a traffic site in which the PM10 levels are monitored all year round. A trend analysis of these levels revealed that over a decade there was no discernible trend, with the PM10 concentrations normally hovering around the EU limit values. In 2018, one of these limit values was exceeded. The contribution of traffic at the site was therefore investigated through a chemical speciation of 209 PM10 samples collected throughout this year. The speciation data were used in a source apportionment exercise in which the output of the PMF model was further refined using the lesser-known, constraint weighted non - negative matrix factorization (CW - NMF) model. This technique enabled the isolation of two factors clearly related to traffic, which were labelled as "exhaust contribution" (responsible for 3.4% of the PM10), "tire/brake wear contribution" (contributing 17% of the PM10). Additionally, a factor including both traffic resuspended dust and crustal material was also isolated and labelled "road dust/crustal" factor. The two contributors to the factor jointly contribute 18% to the PM10 and the contribution of the traffic resuspended dust was estimated at 7.3%. The traffic resuspended component of this factor together with the "tire/brake wear contribution" jointly make up the non-exhaust contribution of traffic - derived dust. Consonant with what has been known for quite some time, the exhaust fraction is the minor component of traffic PM10. It is therefore, clear that policies aimed at controlling traffic derived PM10 pollution at the receptor will have a minimal effect unless the non - exhaust emissions are adequately controlled.
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Affiliation(s)
- Mark M Scerri
- Institute of Earth Systems, University of Malta, Tal-Qroqq, Msida, MSD2080, Malta.
| | - Stephan Weinbruch
- Institute of Applied Geosciences, Technical University Darmstadt, Schnittspahnstraße 9, 64287, Darmstadt, Germany
| | - Gilles Delmaire
- Laboratoire d'Informatique Signal et Image de la Côte d'Opale (LISIC), Université du Littoral Côte d'Opale, F62228, Calais, France
| | - Nadine Mercieca
- Environment and Resources Authority, Hexagon House, Spencer Hill, Marsa, MRS1441, Malta
| | - Michael Nolle
- Environment and Resources Authority, Hexagon House, Spencer Hill, Marsa, MRS1441, Malta
| | - Paolo Prati
- Physics Department & INFN, Università degli studi di Genova, Via Dodecaneso 33, 16146, Genova, Italy
| | - Dario Massabò
- Physics Department & INFN, Università degli studi di Genova, Via Dodecaneso 33, 16146, Genova, Italy
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27
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Goswami AP, Kalamdhad AS. Mobility and risk assessment of heavy metals in benthic sediments using contamination factors, positive matrix factorisation (PMF) receptor model, and human health risk assessment. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:7056-7074. [PMID: 36029450 DOI: 10.1007/s11356-022-22707-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 08/20/2022] [Indexed: 06/15/2023]
Abstract
Metal pollution in benthic sediments was fractionated and modelled to quantify the risk of anthropogenic activities on river ecosystems. In this study, the individual contamination factor (ICF) and the global contamination factor (GCF) were used to measure the contamination levels in the sediments. On the other hand, the mobility factor (MF) was used to quantify the mobility of heavy metals in benthic river sediments. The factors used to assess pollution in benthic sediments employ bioavailable fractions of heavy metals, which have a greater chance of release into aquatic sediments and hence are more dangerous to the environment. Heavy metal mobility (MF) is highest in the post-monsoon season for Zn, Pb, Cu, and Co; Fe in winter; Mn in pre-monsoon; and Cd in monsoon. This means that heavy metals accumulate in benthic sediments during the post-monsoon season when river flows are less turbulent. ICF and GCF data show that pollution levels are higher post-monsoon than the rest season levels. Sediment samples were further subjected to the positive matrix factorization (PMF) model, which identified four factors that explained the variation in the study: factor 1 is concerned with anthropogenic Cu, Cd, and Co pollution, while factors 2, 3, and 4 are concerned with Fe, Mn, and Zn pollution. Finally, the total cancer risk (TCR) and hazard index (HI) are employed to quantify the risk to human health from accidental ingestion and dermal exposure. According to the risk outcomes from probabilistic and deterministic approaches, river exposure is dangerous to human health, with dermal absorption being the most significant concern of the exposure paths.
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Affiliation(s)
- Ankit Pratim Goswami
- Department of Civil Engineering, Indian Institute of Technology Guwahati, Guwahati, 781039, Assam, India.
| | - Ajay S Kalamdhad
- Department of Civil Engineering, Indian Institute of Technology Guwahati, Guwahati, 781039, Assam, India
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Bao Q, Liu C, Friese K, Dadi T, Yu J, Fan C, Shen Q. Understanding the Heavy Metal Pollution Pattern in Sediments of a Typical Small- and Medium-Sized Reservoir in China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 20:708. [PMID: 36613029 PMCID: PMC9819956 DOI: 10.3390/ijerph20010708] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 12/25/2022] [Accepted: 12/29/2022] [Indexed: 06/17/2023]
Abstract
Heavy metal pollution in sediments is a common environmental issue in small- and medium-sized reservoirs not only in China but also worldwide; however, few interpretations of the pollution pattern exist. Based on the analyses of accumulation characteristics, ecological risks, and source apportionments of eight heavy metals (As, Cd, Cr, Cu, Hg, Pb, Ni, and Zn) in sediments, we derived a paradigm to describe the pollution pattern of heavy metals in sediments of a typical small- and medium-sized Tongjiqiao Reservoir. The results showed high levels of Cd, Hg, and As pollutants in the surface and upper sediment layers of the pre-dam area. Additionally, As, Cd, Hg, and Pb pollutants peaked in the middle layers of the inflow area, indicating a high ecological risk in these areas. The positive matrix factorization results implied that industrial, agricultural, and transportation activities were the main sources of heavy metals. The heavy metal pollution pattern exhibited three distinct stages: low contamination, rapid pollution, and pollution control. This pattern explains the heavy metal pollution process in the sediments and will provide scientific guidance for realizing the green and sustainable operation and development of the reservoir.
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Affiliation(s)
- Qibei Bao
- Ningbo College of Health Sciences, Ningbo 315100, China
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
| | - Cheng Liu
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
| | - Kurt Friese
- UFZ-Helmholtz Centre for Environmental Research, Department of Lake Research, 39114 Magdeburg, Germany
| | - Tallent Dadi
- UFZ-Helmholtz Centre for Environmental Research, Department of Lake Research, 39114 Magdeburg, Germany
| | - Juhua Yu
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
- Fujian Academy of Agricultural Sciences, Institute of Soil and Fertilizer, Fuzhou 350013, China
| | - Chengxin Fan
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
| | - Qiushi Shen
- State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
- UFZ-Helmholtz Centre for Environmental Research, Department of Lake Research, 39114 Magdeburg, Germany
- Sino-Africa Joint Research Center, Chinese Academy of Sciences, Wuhan 430070, China
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Yi Y, Li Q, Zhang K, Li R, Yang L, Liu Z, Zhang X, Wang S, Wang Y, Chen H, Huang L, Yu JZ, Li L. Highly time-resolved measurements of elements in PM 2.5 in Changzhou, China: Temporal variation, source identification and health risks. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 853:158450. [PMID: 36058329 DOI: 10.1016/j.scitotenv.2022.158450] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 08/28/2022] [Accepted: 08/28/2022] [Indexed: 06/15/2023]
Abstract
The temporal variation, sources, and health risks of elemental composition in fine particles (PM2.5) were explored using online measurements of 19 elements with a time resolution of 1 h at an urban location in Changzhou, China, from December 10, 2020 to March 31, 2021. The mass concentration of PM2.5 was 50.1 ± 32.6 μg m-3, with a range of 3-218 μg m-3. The total concentration of 19 elements (2568 ± 1839 ng m-3) accounted for 5.1 % of PM2.5 mass concentration. S, Cl, Si, and Fe were the dominant elementary species, accounting for 90 % of total element mass concentrations during the whole campaign. Positive matrix factorization (PMF) model was applied to identify the major emission sources of elements in PM2.5. Seven factors, named secondary sulfate mixed with coal combustion, Cl-rich, traffic, iron and steel industry, soil dust, fireworks, and shipping, were identified. The major sources for elements were iron and steel industry, followed by soil dust and secondary sulfate mixed with coal combustion, explaining 32.0 %, 23.5 % and 16.7 % of the total source contribution, respectively. The total hazard index (HI) of elements was 3.01 for children and 1.18 for adults, much greater than the admissible level (HI = 1). The total carcinogenic risk (CR) in Changzhou was estimated to be 5.87 × 10-5, which was above the acceptable CR level (1 × 10-6). Among the calculated metal elements, Cr, Co and As have higher carcinogenic risk, and Co was found to trigger the highest noncarcinogenic risk to Children. Our results indicate that industrial emission is the dominant CR contributor, emphasizing the necessity for stringent regulation of industry sources. Overall, our study provides useful information for policymakers to reduce emissions and health risks from elements in the Yangtze River Delta region.
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Affiliation(s)
- Yanan Yi
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Qing Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, 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 200444, 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 200444, 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 200444, 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 200444, China; Jiangsu Changhuan Environment Technology Co., Ltd., Changzhou 213002, China
| | - Xiaojuan Zhang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China; Jiangsu Changhuan Environment Technology Co., Ltd., Changzhou 213002, China
| | - Shunyao Wang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, 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 200444, 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 200444, 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 200444, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China
| | - Jian Zhen 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 200444, China; Key Laboratory of Organic Compound Pollution Control Engineering (MOE), Shanghai University, Shanghai, China.
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Fan J, Deng L, Wang W, Yi X, Yang Z. Contamination, Source Identification, Ecological and Human Health Risks Assessment of Potentially Toxic-Elements in Soils of Typical Rare-Earth Mining Areas. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:15105. [PMID: 36429823 PMCID: PMC9690513 DOI: 10.3390/ijerph192215105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 11/12/2022] [Accepted: 11/14/2022] [Indexed: 06/16/2023]
Abstract
The mining and leaching processes of rare-earth mines can include the entry of potentially toxic elements (PTEs) into the environment, causing ecological risks and endangering human health. However, the identification of ecological risks and sources of PTEs in rare-earth mining areas is less comprehensive. Hence, we determine the PTE (Co, Cr, Cu, Mn, Ni, Pb, Zn, V) content in soils around rare-earth mining areas in the south and analyze the ecological health risks, distribution characteristics, and sources of PTEs in the study area using various indices and models. The results showed that the average concentrations of Co, Mn, Ni, Pb and Zn were higher than the soil background values, with a maximum of 1.62 times. The spatial distribution of PTEs was not homogeneous and the hot spots were mostly located near roads and mining areas. The ecological risk index and the non-carcinogenic index showed that the contribution was mainly from Co, Pb, and Cr, which accounted for more than 90%. Correlation analysis and PMF models indicated that eight PTEs were positively correlated, and rare-earth mining operations (concentration of 22.85%) may have caused Pb and Cu enrichment in soils in the area, while other anthropogenic sources of pollution were industrial emissions and agricultural pollution. The results of the study can provide a scientific basis for environmental-pollution assessment and prevention in rare-earth mining cities.
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Affiliation(s)
- Jiajia Fan
- Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region, Ministry of Education, Chang’an University, Xi’an 710064, China
| | - Li Deng
- Ecological Environment Planning and Environmental Protection Technology Center of Qinghai Province, Xining 810007, China
| | - Weili Wang
- Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China
| | - Xiu Yi
- Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region, Ministry of Education, Chang’an University, Xi’an 710064, China
| | - Zhiping Yang
- Jiangxi Research Academy of Ecological Civilization, Nanchang 330036, China
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Li W, Zuo Y, Wang L, Wan X, Yang J, Liang T, Song H, Weihrauch C, Rinklebe J. Abundance, spatial variation, and sources of rare earth elements in soils around ion-adsorbed rare earth mining areas. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 313:120099. [PMID: 36084740 DOI: 10.1016/j.envpol.2022.120099] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/23/2022] [Accepted: 08/27/2022] [Indexed: 06/15/2023]
Abstract
Rare earth elements (REEs) concentrated in soils have attracted increasing attention about their impact on soil health as emerging contaminants. However, the sources of REEs enriched in soils are diverse and need to be further investigated. Here, surface soil samples were collected from southern Jiangxi Province, China. REEs contents and soil physicochemical properties were determined, and cerium (Ce) and europium (Eu) anomalies were calculated. Moreover, we established a model to further identify the main sources of REEs accumulation in the studied soils. Results show that the abundance of soil REEs reveals larger spatial variation, suggesting spatially heterogeneous distribution of REEs. The median content of light REEs in soils (154.5 mg kg-1) of the study area was higher than that of heavy REEs and yttrium (35.8 mg kg-1). In addition, most of the soil samples present negative Ce anomalies and all the soil samples present negative Eu anomalies implying the combined effect of weathering and potential exogenous inputs on soil REEs. Positive matrix factorization modeling reveals that soil REEs content is primarily influenced by soil parent materials. Potential anthropogenic sources include mining-related leachate, traffic exhaust, and industrial dust. These results demonstrate that the identification of sources of soil REEs is an important starting point for targeted REEs sources management and regulation of excessive and potentially harmful REEs levels in the soil.
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Affiliation(s)
- Wanshu Li
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Yiping Zuo
- Foreign Environmental Cooperation Center, Ministry of Ecology and Environment, Beijing, 100035, China
| | - Lingqing Wang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China; University of Wuppertal, School of Architecture and Civil Engineering, Institute of Foundation Engineering, Water- and Waste-Management, Soil- and Groundwater-Management, Pauluskirchstraße 7, 42285, Wuppertal, Germany.
| | - Xiaoming Wan
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Jun Yang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Tao Liang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hocheol Song
- Department of Environment, Department of Environment and Energy, Sejong University, Seoul, 05006, Republic of Korea
| | - Christoph Weihrauch
- University of Wuppertal, School of Architecture and Civil Engineering, Institute of Foundation Engineering, Water- and Waste-Management, Soil- and Groundwater-Management, Pauluskirchstraße 7, 42285, Wuppertal, Germany
| | - Jörg Rinklebe
- University of Wuppertal, School of Architecture and Civil Engineering, Institute of Foundation Engineering, Water- and Waste-Management, Soil- and Groundwater-Management, Pauluskirchstraße 7, 42285, Wuppertal, Germany; Department of Environment, Department of Environment and Energy, Sejong University, Seoul, 05006, Republic of Korea
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32
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Kim S, Yang J, Park J, Song I, Kim DG, Jeon K, Kim H, Yi SM. Health effects of PM 2.5 constituents and source contributions in major metropolitan cities, South Korea. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:82873-82887. [PMID: 35761136 DOI: 10.1007/s11356-022-21592-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 06/16/2022] [Indexed: 06/15/2023]
Abstract
Ambient PM2.5 is one of the major risk factors for human health, and is not fully explained solely by mass concentration. We examined the short-term associations of cause-specific mortality (i.e., all-cause, cardiovascular, and respiratory mortality) with the 15 chemical constituents and sources of PM2.5 in four metropolitan cities of South Korea during 2014-2018. We found transition metals consistently showed significant associations with all-cause mortality, while the effects of other constituents varied across the cities and for cause of death. Carbonaceous components strongly affected the all-cause, cardiovascular, and respiratory mortality in Daejeon. Secondary inorganic aerosols, SO42- and NH4+, showed significant associations with respiratory mortality in Gwangju. We also found the sources from which species closely linked to mortality generally increased the relative mortality risks. Heavy metal markers from soil or industrial sources were significantly associated with mortality in all cities. However, several sources influenced mortality despite their marker species not being significantly associated with it. Secondary nitrate and secondary sulfate sources were linked to mortality in DJ. This could be attributed to the deep inland location, which might have facilitated formation of secondary inorganic aerosols. In addition, primary sources including mobile and coal combustion seemed to have acute impacts on respiratory mortality in Gwangju. Our findings suggest the necessity of positive matrix factorization (PMF)-based approaches for evaluating health effects of PM2.5 while considering the spatial heterogeneity in the compositions and source contributions of PM2.5.
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Affiliation(s)
- Sangcheol Kim
- Sejong Institute of Health and Environment, Sejong, Republic of Korea
- Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea
| | - Juyeon Yang
- Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea
| | - Jieun Park
- Institute of Health and Environment, Seoul National University, Seoul, Republic of Korea
| | - Inho Song
- Climate and Air Quality Research Department Air Quality Research Division, National Institute of Environmental Research, Incheon, Republic of Korea
| | - Dae-Gon Kim
- Climate and Air Quality Research Department Air Quality Research Division, National Institute of Environmental Research, Incheon, Republic of Korea
| | - Kwonho Jeon
- Climate and Air Quality Research Department Global Environment Research Division, National Institute of Environmental Research, Incheon, Republic of Korea
| | - Ho Kim
- Graduate School of Public Health & Institute of Health and Environment, Seoul National University, 1 Gwanak ro, Gwanak gu, Seoul, 08826, Republic of Korea
| | - Seung-Muk Yi
- Graduate School of Public Health & Institute of Health and Environment, Seoul National University, 1 Gwanak ro, Gwanak gu, Seoul, 08826, Republic of Korea.
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Comparison of concentrations of chemical species and emission sources PM 2.5 before pandemic and during pandemic in Krakow, Poland. Sci Rep 2022; 12:16481. [PMID: 36182965 PMCID: PMC9526202 DOI: 10.1038/s41598-022-21012-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 09/21/2022] [Indexed: 11/08/2022] Open
Abstract
Observations of air pollution in Krakow have shown that air quality has been improved during the last decade. In the presented study two factors affecting the physicochemical characteristic of PM2.5 fraction at AGH station in Krakow were observed. One is the ban of using solid fuels for heating purposes and the second is COVID-19 pandemic in Krakow. The PM2.5 fraction was collected during the whole year every 3rd day between 2nd March 2020 and 28th February 2021 at AGH station in Krakow. In total 110 PM2.5 fraction samples were collected. The chemical composition was determined for these samples. The elemental analysis was performed by energy dispersive X-ray fluorescence (EDXRF) technique, ions analysis was performed by ion chromatography (IC) and black carbon by optical method. In order to identify the emission sources the positive matrix factorization (PMF) was used. The results of such study were compared to similar analysis performed for PM2.5 for the period from June 2018 to May 2019 at AGH station in Krakow. The PM2.5 concentration dropped by 25% in 2020/2021 in comparison to 2018/2019 at this station. The concentrations of Si, K, Fe, Zn and Pb were lowering by 43-64% in the year 2020/2021 in comparison to 2018/2019. Cu, Mn, Zn and Pb come from mechanical abrasion of brakes and tires while Ti, Fe, Mn and Si are crustal species. They are the indicators of road dust (non-exhaust traffic source). Moreover, the annual average contribution of traffic/industrial/soil/construction work source was reduced in 2020/2021 in comparison to 2018/2019. As well the annual average contribution of fuels combustion was declining by 22% in 2020/2021 in comparison to 2018/2019. This study shows that the ban and lockdown, during COVID-19 pandemic, had significant impact on the characteristic of air pollution in Krakow.
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Wang Z, Yan J, Zhang P, Li Z, Guo C, Wu K, Li X, Zhu X, Sun Z, Wei Y. Chemical characterization, source apportionment, and health risk assessment of PM 2.5 in a typical industrial region in North China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:71696-71708. [PMID: 35604610 DOI: 10.1007/s11356-022-19843-2] [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: 11/25/2021] [Accepted: 03/17/2022] [Indexed: 06/15/2023]
Abstract
To clarify the chemical characteristics, source contributions, and health risks of pollution events associated with high PM2.5 in typical industrial areas of North China, manual sampling and analysis of PM2.5 were conducted in the spring, summer, autumn, and winter of 2019 in Pingyin County, Jinan City, Shandong Province. The results showed that the total concentration of 29 components in PM2.5 was 53.4 ± 43.9 μg·m-3, including OC/EC, water-soluble ions, inorganic elements, and metal elements. The largest contribution was from the NO3- ion, at 14.6 ± 14.2 μg·m-3, followed by organic carbon (OC), SO42-, and NH4+, with concentrations of 9.3 ± 5.5, 9.1 ± 6.4, and 8.1 ± 6.8 μg·m-3, respectively. The concentrations of OC, NO3-, and SO42- were highest in winter and lowest in summer, whereas the NH4+ concentration was highest in winter and lowest in spring. Typical heavy metals had higher concentrations in autumn and winter, and lower concentrations in spring and summer. The annual average sulfur oxidation rate (SOR) and nitrogen oxidation rate (NOR) were 0.30 ± 0.14 and 0.21 ± 0.12, respectively, with the highest SO2 emission and conversion rates in winter, resulting in the SO42- concentration being highest in winter. The average concentration of secondary organic carbon in 2019 was 2.8 ± 1.9 μg·m-3, and it comprised approximately 30% of total OC. The concentrations of 18 elements including Na, Mg, and Al were between 2.3 ± 1.6 and 888.1 ± 415.2 ng·m-3, with Ni having the lowest concentration and K the highest. The health risk assessment for typical heavy metals showed that Pb poses a potential carcinogenic risk for adults, whereas As may pose a carcinogenic risk for adults, children, and adolescents. The non-carcinogenic risk coefficients for all heavy metals were lower than 1.0, indicating that the non-carcinogenic risk was negligible. Positive matrix factorization analysis indicated that coal-burning emissions contributed the largest fraction of PM2.5, accounting for 35.9% of the total. The contribution of automotive emissions is similar to that of coal, at 32.1%. The third-largest contributor was industrial sources, which accounted for 17.2%. The contributions of dust and other emissions sources to PM2.5 were 8.4% and 6.4%, respectively. This study provides reference data for policymakers to improve the air quality in the NCP.
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Affiliation(s)
- Zhanshan Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Jiayi Yan
- The Ecological Environment Monitoring Center of Linyi, Shandong province, Linyi, 276000, China
| | - Puzhen Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Zhigang Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Chen Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Kai Wu
- Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, 610225, China
- Department of Land, Air, and Water Resources, University of California, Davis, CA, USA
| | - Xiaoqian Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Xiaojing Zhu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
| | - Zhaobin Sun
- Institute of Urban Meteorology, China Meteorological Administration, Beijing, 100089, China
| | - Yongjie Wei
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.
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35
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Chatoutsidou SE, Lazaridis M. Mass concentrations and elemental analysis of PM 2.5 and PM 10 in a coastal Mediterranean site: A holistic approach to identify contributing sources and varying factors. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 838:155980. [PMID: 35588836 DOI: 10.1016/j.scitotenv.2022.155980] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 04/13/2022] [Accepted: 05/11/2022] [Indexed: 06/15/2023]
Abstract
PM10 and PM2.5 were measured at a suburban coastal Mediterranean site. Daily mass concentrations were generally lower than the WHO air quality limits but showed significant diurnal and seasonal variations, with intensive African dust events and residential heating emissions during wintertime causing the higher % increase of ambient concentrations (32% and 59% respectively). However, analysis of the elemental content revealed intrinsic characteristics. Statistically significant seasonal variability was found for S with higher concentrations during warm seasons directly associated with the formation of secondary sulfates. Increased S was the driving reason for the significant depletion of both Cl and Br. On the other hand, elevated K during wintertime was attributed to biomass burning. Analysis of the mineral content of airborne particles showed that typical soil-derived particles were significantly increased during dust events (Mg, Al, Si, K, Ca, Ti, Mn, Fe) although the corresponding mass concentrations preserved relative low levels (<30 μg m-3). It was also found that dust events contributed to P, S, V, Zn, Sr and Pb with elemental ratios including Si (Si/Al, Si/Fe, Si/Ca) and Ca/Al serving as good markers for African dust. Heavy metals were found to have both direct and indirect influence on PM2.5 and PM10. PM2.5 were primarily enriched with metals produced from motor vehicles (Cu, Zn, Pb) and ships (V, Ni), whilst, PM10 enriched indirectly with Cr, Zn, Br and Pb due to road dust. At the end, source appointment has shown that the dominant contributing factor was mineral dust for both metrics (>30%) but significant contributions arose from secondary sulfates and traffic, (aged) sea salt, biomass burning (only for PM2.5) and road dust (only for PM10). Overall, this work provides a novel insight on the characteristics and chemical profile of atmospheric particles in a suburban environment largely affected by local, regional and long-range sources.
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Affiliation(s)
| | - Mihalis Lazaridis
- School of Chemical and Environmental Engineering, Technical University of Crete, Chania, Greece
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36
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Ma S, Shao M, Zhang Y, Dai Q, Wang L, Wu J, Tian Y, Bi X, Feng Y. Evaluating the performance of chemical transport models for PM 2.5 source apportionment: An integrated application of spectral analysis and grey incidence analysis. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 837:155781. [PMID: 35550897 DOI: 10.1016/j.scitotenv.2022.155781] [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: 01/14/2022] [Revised: 05/03/2022] [Accepted: 05/04/2022] [Indexed: 06/15/2023]
Abstract
Evaluating the performance of source apportionment (SA) models is difficult due to the non-observable nature of source contribution in reality. Here we propose a new approach to assess the performance of Chemical Transport Models (CTMs) for SA based on wavelet time-frequency spectral analysis and Grey Incidence Analysis (GIA). For each source category, certain species that better reflect the periodic characteristics of the emission sources were selected as the chemical tracers. The consistency of the time series between the simulated source contributions and the observed source-specific chemical tracers was then examined using a GIA model based on the perspective of similarity, and characterized by the GIA scores. By applying this method to six typical pollution episodes, we evaluated the performance of the Comprehensive Air Quality Model with Extensions-Particle Source Apportionment Technology (CAMx-PSAT) model for PM2.5 SA from different temporal and spatial scales. The source- and episode-dependent optimal average time and main source regions were obtained. This approach is robust for facilitating a relatively meticulous evaluation of the performance of CTMs for PM2.5 SA, and provides additional insight for decision-making for heavy pollution emergencies.
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Affiliation(s)
- Simeng Ma
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Min Shao
- School of Environment, Nanjing Normal University, Nanjing 210023, China
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Litao Wang
- Department of Environmental Engineering, School of Energy and Environmental Engineering, Hebei University of Engineering, Handan 056038, China; Hebei Key Laboratory of Air Pollution Cause and Impact, Handan, 056038, China
| | - Jianhui Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Yingze Tian
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Xiaohui Bi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
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Zhou B, Wang J, Liu S, Ho SSH, Wu T, Zhang Y, Tian J, Feng Q, Li C, Wang Q. Extrapolation of anthropogenic disturbances on hazard elements in PM 2.5 in a typical heavy industrial city in northwest China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:64582-64596. [PMID: 35471756 PMCID: PMC9039608 DOI: 10.1007/s11356-022-20184-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 04/06/2022] [Indexed: 06/14/2023]
Abstract
Baoji is a typical heavy industrial city in northwest China. Its air quality is greatly impacted by the emission from the factories. Elements in fine particulate matter (PM2.5) that are greatly emitted from anthropogenic sources could pose diverse health impacts on humans. In this study, an online AMMS-100 atmospheric heavy metal analyzer was used to quantify 30 elements in PM2.5 under the weak and strong anthropogenic disturbance scenarios before the city lockdown period (from January 9th to 23rd) and the lockdown period (from January 26th to February 9th) due to the outbreak of COVID-19 in 2020. During the lockdown period, the average total concentration of total quantified elements was 3475.0 ng/m3, which was 28% and 33% lower than that of the week and strong anthropogenic disturbance scenarios during the pre-lockdown period. The greatest reductions were found for the elements of chromium (Cr), titanium (Ti), manganese (Mn), and Zinc (Zn), consistent with the industrial structure of Baoji. The mass concentrations of most elements showed obvious reductions when the government post-alerted the industries to reduce the operations and production. Dust, traffic sources, combustion, non-ferrous metal processing, and Ti-related industrial processing that are the contributors of the elements in the pre-lockdown period were apportioned by the positive matrix factorization (PMF) model. Substantial changes in the quantified elements' compositions and sources were found in the lockdown period. Health assessment was conducted and characterized by apportioned sources. The highest non-carcinogenic risk (HQ) was seen for Zn, demonstrating the high emissions from the related industrial activities. The concentration level of arsenic (As) exceeded the incremental lifetime carcinogenic risk (ILCR) in the lockdown period. This could be attributed to the traditional firework activities for the celebration of the Chinese New Year within the lockdown period.
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Affiliation(s)
- Bianhong Zhou
- Shaanxi Key Laboratory of Disaster Monitoring and Mechanism Simulation, College of Geography & Environment, Baoji University of Arts & Sciences, Baoji, 721013, China
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Jin Wang
- Shaanxi Key Laboratory of Disaster Monitoring and Mechanism Simulation, College of Geography & Environment, Baoji University of Arts & Sciences, Baoji, 721013, China
| | - Suixin Liu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
- CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China
- Shaanxi Key Laboratory of Atmospheric and Haze-fog Pollution Prevention, Xi'an, 710061, China
| | - Steven Sai Hang Ho
- Division of Atmospheric Sciences, Desert Research Institute, Reno, NV, 89512, USA
| | - Tingting Wu
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Yong Zhang
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Jie Tian
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China
| | - Qiao Feng
- Shaanxi Key Laboratory of Disaster Monitoring and Mechanism Simulation, College of Geography & Environment, Baoji University of Arts & Sciences, Baoji, 721013, China
| | - Chunyan Li
- Shaanxi Key Laboratory of Disaster Monitoring and Mechanism Simulation, College of Geography & Environment, Baoji University of Arts & Sciences, Baoji, 721013, China
| | - Qiyuan Wang
- State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an, 710061, China.
- CAS Center for Excellence in Quaternary Science and Global Change, Xi'an, 710061, China.
- Shaanxi Key Laboratory of Atmospheric and Haze-fog Pollution Prevention, Xi'an, 710061, China.
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Sojka M, Jaskuła J. Heavy Metals in River Sediments: Contamination, Toxicity, and Source Identification-A Case Study from Poland. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph191710502. [PMID: 36078217 PMCID: PMC9518182 DOI: 10.3390/ijerph191710502] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 08/15/2022] [Accepted: 08/17/2022] [Indexed: 05/28/2023]
Abstract
This study investigated the spatial distribution, contamination, potential ecological risks and quantities of pollutant sources of six heavy metals (HMs) in sediments of 47 rivers. The catchments of the investigated rivers are situated in Poland, but some of them are located in Slovakia, the Czech Republic, and Germany. Cluster analysis was applied to analyze the spatial distribution of Cd, Cr, Cu, Ni, Pb, and Zn in river sediments. Moran I and Getis-Ord Gi* statistics were calculated to reveal the distribution pattern and hotspot values. Principal component analysis (PCA) and positive matrix factorization (PMF) were used to identify pollution sources. Furthermore, geochemical indices and sediment quality guidelines allowed us to assess sediment contamination and potential toxic effects on aquatic biota. The results showed that in 1/3rd of the rivers, the HM pattern and concentrations indicate sediment contamination. The EF, PLI, and MPI indices indicate that concentrations were at a rather low level in 2/3rd of the analyzed rivers. Only in individual rivers may the HMs have toxic effects on aquatic biota. Spatial autocorrelation analysis using the Moran I statistic revealed a random and dispersed pattern of HMs in river sediments. PCA analysis identified two sources of HMs' delivery to the aquatic environment. Cr, Cu, Ni, Pb, and Zn originate from point and non-point sources, while Cd concentrations have a dominant natural origin. The PMF identified three sources of pollution. Among them, urban pollution sources are responsible for Cu delivery, agricultural pollution for Zn, and industrial pollution for Ni and Cr. Moreover, the analysis showed no relationship between catchment land-use patterns and HM content in river sediments.
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Huang H, Zhang J, Hu H, Kong S, Qi S, Liu X. On-road emissions of fine particles and associated chemical components from motor vehicles in Wuhan, China. ENVIRONMENTAL RESEARCH 2022; 210:112900. [PMID: 35167853 DOI: 10.1016/j.envres.2022.112900] [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: 08/09/2021] [Revised: 01/01/2022] [Accepted: 02/03/2022] [Indexed: 06/14/2023]
Abstract
Vehicle emission is an important contributor to urban air pollution with the increasing number of motor vehicles. Ten typical vehicles were selected in Wuhan to study the emissions of fine particular matters (PM2.5) and associated chemical components by on-road tests through a Portable Emission Monitoring System (PEMS). The emission factors of PM2.5 and the compositions of it from different types of vehicle were obtained. Results showed that the average emission factors of PM2.5 from gasoline and diesel vehicles were 1.266 and 16.589 mg/km. As the emission standard of vehicles increased from China III to China V, PM2.5 emission factor gradually decreased from 17.385 to 1.520 mg/km. Emission rate of PM2.5 was 0.0384 mg/s under low speed, and it increased to 0.0775 and 0.0964 mg/s under the medium and high speeds. The ratio of organic carbon versus elemental carbon (OC/EC) in PM2.5 from gasoline vehicles was 6.89, which was greater than that of diesel vehicles as 3.12. Because gasoline was made of small molecules and the compression ratio of gasoline engine was relatively low, some OC remained in the area where the ignition failed in the cylinder. The top four water-soluble ions with high emission factors were Cl-, SO42-, Ca2+, and Na+, while K, Na, Ca and Mg had a larger emission factors in the 21 tested inorganic elements. These water-soluble ions and inorganic elements mainly came from the oil burning, fuel additives and engines wear. Results of PM2.5 emission characteristics would help to improve the air quality in Wuhan.
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Affiliation(s)
- Hao Huang
- School of Environmental Science and Engineering, Huazhong University of Science & Technology, Wuhan, 430074, PR China
| | - Jinjie Zhang
- CATARC Automotive Inspection Center (Wuhan) Company, Wuhan, 430056, PR China
| | - Hui Hu
- School of Environmental Science and Engineering, Huazhong University of Science & Technology, Wuhan, 430074, PR China.
| | - Shaofei Kong
- School of Environmental Studies, China University of Geosciences, Wuhan, 430074, PR China
| | - Shihua Qi
- School of Environmental Studies, China University of Geosciences, Wuhan, 430074, PR China
| | - Xiaoyong Liu
- Hubei Academy of Environmental Science, Wuhan, 430072, PR China
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Feng S, Jiang F, Wang H, Shen Y, Zheng Y, Zhang L, Lou C, Ju W. Anthropogenic emissions estimated using surface observations and their impacts on PM 2.5 source apportionment over the Yangtze River Delta, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 828:154522. [PMID: 35288133 DOI: 10.1016/j.scitotenv.2022.154522] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 02/11/2022] [Accepted: 03/08/2022] [Indexed: 06/14/2023]
Abstract
Source-tagged source apportionment (SA) has advantages for quantifying the contribution of various source regions and categories to PM2.5; however, it is highly affected by uncertainty in the emission inventory. In this study, we used a Regional multi-Air Pollutant Assimilation System (RAPAS) to optimize daily SO2, NOx and primary PM2.5 (PPM2.5) emissions in the Yangtze River Delta (YRD) in December 2016 by assimilating hourly in-situ measurements. The CMAQ-ISAM model was implemented with prior and posterior emissions respectively to investigate the impacts of optimizing emissions on PM2.5 SA in the YRD megalopolis (YRDM) and three megacities of Shanghai, Nanjing, and Hangzhou in the YRDM. The results showed that RAPAS significantly improved the simulations and reduced the emission uncertainties of the different pollutants. Compared with prior emissions, the posterior emissions in the YRD decreased by 13% and 11% for SO2 and NOx respectively, and increased by 24% for PPM2.5. Compared with SA using prior emissions, the contributions from Hangzhou, northern Zhejiang, and areas outside of the YRD to the YRDM increased. The local contributions from the YRDM, Nanjing and Shanghai decreased by 1.8%, 9.7%, and 2.3%, respectively, whereas that of Hangzhou increased by 5.6%. The changes in the daily local contributions caused by optimizing emissions ranged from -18.0% to 23.6%. Generally, under stable weather conditions, the local contribution changed the most, whereas under unstable weather conditions, the contribution from upwind areas changed significantly. Overall, with optimized emissions, we found in Nanjing, Shanghai, and Hangzhou, local emissions contributed 18.2%, 39.6% and 36.8% of their PM2.5 concentrations, respectively; long-range transport from outside the YRDM contributed 59.2%, 48.1%, and 48.2%, respectively. This study emphasizes the importance of improving emission estimations for source-tagged SA and provides more reliable SA results for the main cities in the YRD, which will contribute to pollution control in these regions.
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Affiliation(s)
- Shuzhuang Feng
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Fei Jiang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China.
| | - Hengmao Wang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
| | - Yang Shen
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Yanhua Zheng
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Lingyu Zhang
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Chenxi Lou
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China
| | - Weimin Ju
- Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
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Recent Insights into Particulate Matter (PM 2.5)-Mediated Toxicity in Humans: An Overview. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19127511. [PMID: 35742761 PMCID: PMC9223652 DOI: 10.3390/ijerph19127511] [Citation(s) in RCA: 135] [Impact Index Per Article: 67.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 06/16/2022] [Accepted: 06/16/2022] [Indexed: 12/10/2022]
Abstract
Several epidemiologic and toxicological studies have commonly viewed ambient fine particulate matter (PM2.5), defined as particles having an aerodynamic diameter of less than 2.5 µm, as a significant potential danger to human health. PM2.5 is mostly absorbed through the respiratory system, where it can infiltrate the lung alveoli and reach the bloodstream. In the respiratory system, reactive oxygen or nitrogen species (ROS, RNS) and oxidative stress stimulate the generation of mediators of pulmonary inflammation and begin or promote numerous illnesses. According to the most recent data, fine particulate matter, or PM2.5, is responsible for nearly 4 million deaths globally from cardiopulmonary illnesses such as heart disease, respiratory infections, chronic lung disease, cancers, preterm births, and other illnesses. There has been increased worry in recent years about the negative impacts of this worldwide danger. The causal associations between PM2.5 and human health, the toxic effects and potential mechanisms of PM2.5, and molecular pathways have been described in this review.
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Abdulraheem MO, Adeniran JA, Ameen HA, Odediran ET, Yusuf MNO, Abdulraheem KA. Source identification and health risk assessments of heavy metals in indoor dusts of Ilorin, North central Nigeria. JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE & ENGINEERING 2022; 20:315-330. [PMID: 35669800 PMCID: PMC9163253 DOI: 10.1007/s40201-021-00778-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 12/25/2021] [Indexed: 05/06/2023]
Abstract
BACKGROUND AND PURPOSE Exposure to heavy metals (HMs) in indoor dusts is a serious public concern that is linked to a myriad of deleterious health outcomes. The objectives of this study are to estimate the contamination levels of HMs in indoor dusts of different residential areas in Ilorin, Nigeria; identify HMs sources in different residential areas; and evaluate human health risks of HMs in selected residential areas. METHODS Indoor dust sampling was conducted in ten randomly selected from low, medium and high population density residential areas of Ilorin, Nigeria. Ten HMs concentration levels, their health risk implication and the associated potential ecological risks were evaluated. RESULTS The mean concentration levels measured for Fe, Pb, Zn, As, Co, Cr, Cu, Cd, Mn and Ni were 38.99, 5.74, 3.99, 0.08, 2.82, 2.13, 0.47, 0.60, 6.45 and 1.09 mg/kg, respectively. Positive Matrix Factorization (PMF) model was applied to ascertain sources of HMs in sampled indoor dust. Percentage contribution from oil-based cooking (29.82%) and transportation (29.77%) represented the highest source to HM concentrations among the six factors identified. The results of the various pollution indices employed showed that Pb, Zn, As, Co, Cr, Cu, Mn and Ni contributed moderately to HMs concentration levels in the sampled dusts. Cd had highest potential ecological risk factor E r i of between 160 and 320. The average values of Enrichment Factors (EFs) obtained aside from Fe used as the reference metal, ranged between 8.46 (As) and 2521.61(Cd). Health risk assessment results revealed that children are the most susceptible to the risks associated with HMs bound indoor dust than the adults. The percentage risk contributions of Hazard Quotient via ingestion route (HQing) in Hazard Index (HI) for non-cancer risk of indoor HMs were 93.17% and 69.87% in children and adults, respectively. Likewise, the percentage cancer risks contribution through ingestion pathway (CRing) were higher than cancer risks through inhalation and dermal pathways (CRinh and CRdermal), accounting for 99.84% and 97.04% of lifetime cancer risk in children and adults, respectively. The contamination level of Cd recorded is of great concern and signifies very strong contribution from anthropogenic sources. CONCLUSION This study has further revealed the levels of HMs in typical African residential settings that could be used by relevant stakeholders and policy makers in developing lasting control measures. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1007/s40201-021-00778-8.
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Affiliation(s)
| | - Jamiu Adetayo Adeniran
- Environmental Engineering Research Laboratory, Department of Chemical Engineering, University of Ilorin, Ilorin, Nigeria
| | - Hafsat Abolore Ameen
- Department of Epidemiology and Community Health, University of Ilorin, Ilorin, Nigeria
| | - Emmanuel Toluwalope Odediran
- Environmental Engineering Research Laboratory, Department of Chemical Engineering, University of Ilorin, Ilorin, Nigeria
| | - Muhammad-Najeeb O. Yusuf
- Environmental Engineering Research Laboratory, Department of Chemical Engineering, University of Ilorin, Ilorin, Nigeria
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Wang L, Wang Y, Li H, Zhu Y, Liu R. Occurrence, source apportionment and source-specific risk assessment of antibiotics in a typical tributary of the Yellow River basin. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2022; 305:114382. [PMID: 34973559 DOI: 10.1016/j.jenvman.2021.114382] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 12/09/2021] [Accepted: 12/21/2021] [Indexed: 06/14/2023]
Abstract
The spatial distributions, sources, and source-specific risk apportionments of 26 antibiotics (5 categories) in the Fenhe River basin were determined based on sample data. The results showed that antibiotics were widely distributed in the surface water. There were significant differences between the different types of antibiotics, and the highest mean concentration was that of the sulfonamide category (33.74 ng/L), accounting for 36% of the total antibiotic concentration. Spatially, all antibiotics were mainly detected in the middle and downstream areas. The ecological risk assessment results showed that the significant risk rate of antibiotics accounted for 70% and was mainly distributed in the downstream area; however, the risks differed between the 5 categories. Quinolone antibiotics exhibited the highest significant risk rate, reaching 100%. The ecological risk associated with sulfamethoxazole was the highest among all detected antibiotics. The following five main factors influenced the antibiotic concentrations: aquaculture, pharmaceutical wastewater, livestock discharges, domestic sewage, and sewage treatment plants. Among these, pharmaceutical wastewater sources contributed the most (35%) to the total antibiotic concentration, and were distributed throughout the river. Although livestock discharges were not the main reason for the high level of ecological risk, these discharges were highest at certain sites in the midstream region. Different pollution sources posed different levels of ecological risk to the Fenhe River basin, the highest of which was pharmaceutical wastewater with a significant risk rate of 58%.
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Affiliation(s)
- Linfang Wang
- School of Environment and Resources, Shanxi University, Taiyuan, 030006, China; Sorghum Research Institute, Shanxi Agricultural University/Shanxi Academy of Agricultural Sciences, No. 238, Yunhua West Street, Jinzhong Shanxi, 030603, China
| | - Yifan Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
| | - Hua Li
- School of Environment and Resources, Shanxi University, Taiyuan, 030006, China.
| | - Yuen Zhu
- School of Environment and Resources, Shanxi University, Taiyuan, 030006, China
| | - Ruimin Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing 100875, China
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Chianese E, Tirimberio G, Appolloni L, Dinoi A, Contini D, Di Gilio A, Palmisani J, Cotugno P, Miniero DV, Dusek U, Cammino G, Riccio A. Chemical characterisation of PM 10 from ship emissions: a study on samples from hydrofoil exhaust stacks. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:17723-17736. [PMID: 34676477 PMCID: PMC8530373 DOI: 10.1007/s11356-021-17035-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 10/11/2021] [Indexed: 06/13/2023]
Abstract
A chemical characterization of PM10 collected at hydrofoil exhaust stacks was performed conducting two on-board measuring campaigns, with the aim of assessing the ship emission impact on PM10 collected in the coastal area of Naples (Southern Italy) and providing information about the characteristics of this important PM emission source.Samples were analysed determining the contribution of different chemical parameters to PM10's mass, which consisted of polycyclic aromatic hydrocarbons (PAHs) (0.10 ± 0.12%), total carbon (61.9% ± 20.0%, with 40.4% of organic carbon, OC, and 21.5% of elemental carbon, EC) and elemental fraction (0.44% ± 1.00%). Differences in terms of composition and chemical parameter profiles were observed between samples collected during offshore navigation (Off) and samples collected during shunting operations (SO), the latter of higher concern on a local scale. For SO samples, lower contributions of OC and EC were observed (39.7% and 19.6% respectively) compared to Off samples (41.5% and 24.2%), and an increase in terms of elements (from 0.32 to 0.51%) and PAHs (from 0.06 to 0.12%) concentrations was observed. In addition, enrichment factors (EFs) for some elements such as V, Zn, Cd, Cu, Ag and Hg as well as PAHs profile varied significantly between SO and Off. Data presented here were compared with data on chemical composition of PM10 sampled in a tunnel, in a background site and in an urban site in the city of Naples. Results indicated that shipping activities contributed significantly to the emission of V and, in some extent, Zn and Cd; in addition, PAH profiles indicated a greater contribution to urban PM10 from vehicular traffic than shipping emissions. These results can significantly contribute to the correct evaluation of the influence of shipping emission on PM10 generation in urban coastal areas and can be a useful reference for similar studies. The coastal area of Naples is an important example of the coexistence of residential, touristic and natural areas with pollutants emission sources including, among the others, shipping emissions. In this and similar contexts, it is important to distinguish the contribution of each emission source to clearly define environmental control policies.
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Affiliation(s)
- Elena Chianese
- Department of Science and Technology, University of Naples 'Parthenope', Centro Direzionale Isola C4, 80143, Napoli, Italy.
| | - Giuseppina Tirimberio
- Department of Science and Technology, University of Naples 'Parthenope', Centro Direzionale Isola C4, 80143, Napoli, Italy
| | - Luca Appolloni
- Department of Science and Technology, University of Naples 'Parthenope', Centro Direzionale Isola C4, 80143, Napoli, Italy
| | - Adelaide Dinoi
- Istituto Di Scienze Dell'Atmosfera E del Clima, ISAC-CNR, 73100, Lecce, Italy
| | - Daniele Contini
- Istituto Di Scienze Dell'Atmosfera E del Clima, ISAC-CNR, 73100, Lecce, Italy
| | - Alessia Di Gilio
- Department of Biology, University of Bari, Via Orabona 4, 70126, Bari, Italy
| | - Jolanda Palmisani
- Department of Biology, University of Bari, Via Orabona 4, 70126, Bari, Italy
| | - Pietro Cotugno
- Department of Biology, University of Bari, Via Orabona 4, 70126, Bari, Italy
| | | | - Ulrike Dusek
- Centre for Isotope Research (CIO) Energy and Sustainability Research Institute Groningen (ESRIG), University of Groningen, 9747 AG, Groningen, Netherlands
| | - Gennaro Cammino
- Autorità Di Sistema Portuale del Mar Tirreno Centrale, Piazzale Pisacane 80133, Napoli, Italy
| | - Angelo Riccio
- Department of Science and Technology, University of Naples 'Parthenope', Centro Direzionale Isola C4, 80143, Napoli, Italy
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Wang Y, Wang L, Liu R, Li L, Cao L, Jiao L, Xia X. Source-specific risk apportionment and critical risk source identification of antibiotic resistance in Fenhe River basin, China. CHEMOSPHERE 2022; 287:131997. [PMID: 34455124 DOI: 10.1016/j.chemosphere.2021.131997] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 08/05/2021] [Accepted: 08/22/2021] [Indexed: 06/13/2023]
Abstract
A comprehensive understanding of the sources and distribution of antibiotic resistance risk is essential for controlling antibiotic pollution and resistance. Based on surface water samples collected from the Fenhe River basin in the flood season, using the positive matrix factorization (PMF) model, the risk quotient (RQ) method and the multiple attribute decision making (MADM) method, the resistance risk and source-specific resistance risk of antibiotics were analyzed in this study. The results showed that sulfonamides (SAs) were the dominant antibiotics with a mean concentration of 118.30 ng/L, whereas tetracyclines (TCs) and macrolides (MLs) had the highest detection frequencies (100%). The significant resistance risk rate of antibiotics in the entire river basin was 48%, but no high risk occurred. The significant resistance risk rate of quinolones (QNs) was the highest (100%), followed by that of MLs and TCs. Owing to human activities, the most serious resistance risk occurred in the midstream of the river basin. The resistance risk was the lowest upstream. The antibiotics were mainly contributed by six sources. Pharmaceutical wastewater was the main source, accounting for 30%, followed by livestock discharge (22%). The resistance risk from the six sources showed clear differences, but none of the sources caused a high risk of antibiotic resistance. Pharmaceutical wastewater poses the greatest risk of antibiotic resistance in the Fenhe River basin and is widely distributed. The second greatest source was livestock discharge, which was mainly concentrated in the upstream and midstream areas. The critical sources upstream, midstream, and downstream were all pharmaceutical wastewater, whereas the sequences of other sources were different because different areas were affected by different human activities. The proposed method might provide an important reference for the identification the key source of antibiotics and management of antibiotic pollution, as well as help for the management of antibiotics in Fenhe and Shanxi Province.
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Affiliation(s)
- Yifan Wang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Linfang Wang
- Shanxi Research Academy of Environmental Science, No. 11, Xinghua Street, Taiyuan, 030027, China
| | - Ruimin Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China.
| | - Lin Li
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Leiping Cao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Lijun Jiao
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
| | - Xinghui Xia
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19, Xinjiekouwai Street, Beijing, 100875, China
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Ou L, Honda A, Miyasaka N, Akaji S, Omori I, Ishikawa R, Li Y, Ueda K, Takano H. Application of three-dimensional Raman imaging to determination of the relationship between cellular localization of diesel exhaust particles and the toxicity. Toxicol Mech Methods 2021; 32:333-340. [PMID: 34794370 DOI: 10.1080/15376516.2021.2008569] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
A diesel exhaust particle (DEP) is a type of particulate matter that is easily produced from combustion in a diesel power engine. It has been reported that DEPs can cause short- and long-term health problems. This is because DEPs are complex mixtures that are highly inhalable through the airways due to their small particle size. However, the relationship between intracellular localization of DEPs after their deposition in the lungs and the subsequent biological responses remains to be clarified. This is due to difficulties in distinguishing particles that are inside the cells from those that are outside. In this study, A549 human lung epithelial cells were exposed to DEPs at concentrations of 0, 25, 75, or 200 µg/mL for different periods, after that particles in the A549 cells were analyzed by three-dimensional (3D) images obtained from a Raman microscope. The cytotoxic effects of DEPs on the A549 cells were investigated by measuring cell viability, the levels of intracellular reactive oxygen species (ROS) and cell death. The Raman microscopy revealed that the particles invaded the A549 cells, and at a concentration of 200 µg/mL, they markedly decreased cell viability, increased intracellular ROS production, triggered late apoptosis/necrosis and induced nuclear damage. These results suggest that intracellular DEPs exposed at a high concentration may be highly toxic and can impair the viability of A549 cells. Furthermore, the 3D images from the Raman microscopy can be used to evaluate intracellular particle dynamics.
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Affiliation(s)
- Langying Ou
- Graduate School of Global Environmental Studies, Kyoto University, Japan
| | - Akiko Honda
- Graduate School of Global Environmental Studies, Kyoto University, Japan.,Graduate School of Engineering, Kyoto University, Japan
| | - Natsuko Miyasaka
- Graduate School of Global Environmental Studies, Kyoto University, Japan
| | - Sakiko Akaji
- Graduate School of Engineering, Kyoto University, Japan
| | - Issei Omori
- Graduate School of Engineering, Kyoto University, Japan
| | - Raga Ishikawa
- Graduate School of Engineering, Kyoto University, Japan
| | - Yinpeng Li
- Graduate School of Engineering, Kyoto University, Japan
| | - Kayo Ueda
- Graduate School of Global Environmental Studies, Kyoto University, Japan.,Graduate School of Engineering, Kyoto University, Japan
| | - Hirohisa Takano
- Graduate School of Global Environmental Studies, Kyoto University, Japan.,Graduate School of Engineering, Kyoto University, Japan
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Wang M, Tian P, Wang L, Yu Z, Du T, Chen Q, Guan X, Guo Y, Zhang M, Tang C, Chang Y, Shi J, Liang J, Cao X, Zhang L. High contribution of vehicle emissions to fine particulate pollutions in Lanzhou, Northwest China based on high-resolution online data source appointment. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 798:149310. [PMID: 34340091 DOI: 10.1016/j.scitotenv.2021.149310] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 07/20/2021] [Accepted: 07/23/2021] [Indexed: 06/13/2023]
Abstract
The quantitative estimation of urban particulate matter (PM) sources is essential but limited because of various reasons. The hourly online data of PM2.5, organic carbon (OC), elemental carbon (EC), water-soluble ions, and elements from December 2019 to November 2020 was used to conduct PM source appointment, with an emphasis on the contribution of vehicle emissions to fine PM pollution in downtown Lanzhou, Northwest China. Vehicle emissions, secondary formation, mineral dust, and coal combustion were found to be the major PM sources using the positive matrix factorization model. The seasonal mean PM2.5 were estimated to be 72.8, 39.2, 24.3, and 43.6 μg·m-3 and vehicle emissions accounted for 35.7%, 25.8%, 30.0%, and 56.6% in winter, spring, summer, and autumn, respectively. Vehicle emissions were the largest source of PM considering the high PM pollution in winter and its significantly large contribution in autumn. Furthermore, the contribution of vehicle emissions increased with increasing PM in winter and autumn. Vehicle emissions were also the most important source of EC, accounting for 70.3%, 91.0%, 83.5%, and 93.7% of the total EC in winter, spring, summer, and autumn, respectively. With the reduction in industrial emissions and increase in vehicle numbers in China in recent years, vehicle emissions are going to be the largest source of urban PM pollution. To sustainably improve air quality in Lanzhou and other Chinese cities, efforts should be made to control vehicle emissions such as promoting clean-energy vehicles and encouraging public transportation.
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Affiliation(s)
- Min Wang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Pengfei Tian
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China.
| | - Ligong Wang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Zeren Yu
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Tao Du
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Qiang Chen
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Xu Guan
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Yumin Guo
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Min Zhang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Chenguang Tang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Yi Chang
- Gansu Province Environmental Monitoring Center, Lanzhou 730020, China
| | - Jinsen Shi
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou 730000, China
| | - Jiening Liang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Xianjie Cao
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China
| | - Lei Zhang
- Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China; Collaborative Innovation Center for Western Ecological Safety, Lanzhou University, Lanzhou 730000, China
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Adeniran JA, Abdulraheem MO, Ameen HA, Odediran ET, Yusuf MNO. Source identification and health risk assessments of polycyclic aromatic hydrocarbons in settled dusts from different population density areas of Ilorin, Nigeria. ENVIRONMENTAL MONITORING AND ASSESSMENT 2021; 193:777. [PMID: 34748100 DOI: 10.1007/s10661-021-09566-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 10/26/2021] [Indexed: 06/13/2023]
Abstract
Polycyclic aromatic hydrocarbons (PAHs) have attracted significant attention in recent times on account of their reasonably high environmental burden and extreme toxicity. Samples of indoor dusts were obtained daily over a period of 2 weeks from 10 residences located within low, medium, and high density residential areas of Ilorin City. The concentration levels, potential sources, and cancer health risks of sixteen polycyclic aromatic hydrocarbons (PAHs) were investigated using gas chromatography/mass spectrometry. PAHs total concentrations varied from 3.95 ± 0.19 to 8.70 ± 0.43 μg/g with arithmetic mean of 6.09 ± 0.46 μg/g. Fluoranthene was the most dominant PAHs congener. High molecular weight (HMW) PAHs (4-6 rings) were the most prevalent PAHs and were responsible for 79.29% of total PAHs in sampled residences. Chrysene (Chry) was the most abundant compound among the 7 carcinogenic PAHs (CPAHs). Moreover, diagnostic ratios and positive matrix factorization (PMF) employed to apportion PAHs suggested that indoor dusts originated from indoor activities and infiltrating outdoor air pollutants. Diagnostic ratios revealed that PAHs are from mixed sources which include coal/wood combustion, non-traffic and traffic emissions, petroleum, petrogenic (gasoline), and petroleum combustion. Similarly, positive matrix factorization (PMF) model suggested five sources (factors) were responsible for PAHs in indoor dusts comprised of petroleum combustion and traffic emissions (60.05%), wood and biomass combustion emissions (20.84%), smoke from cooking, incense burning and tobacco (4.17%), gasoline combustion from non-traffic sources (13.89%), and emissions from coal burning and electronic devices (1.05%). The incremental lifetime carcinogenic risks (ILCR) of PAHs in adults and children estimated by applying benzo(a)pyrene (BaP) equivalent were within the satisfactory risk limits in Ilorin. Indoor PAHs emissions in Ilorin residences could be monitored and controlled by using data provided in this study.
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Affiliation(s)
- Jamiu Adetayo Adeniran
- Environmental Engineering Research Laboratory, Department of Chemical Engineering, University of Ilorin, Ilorin, Nigeria.
| | | | - Hafsat Abolore Ameen
- Department of Epidemiology and Community Health, University of Ilorin, Ilorin, Nigeria
| | - Emmanuel Toluwalope Odediran
- Environmental Engineering Research Laboratory, Department of Chemical Engineering, University of Ilorin, Ilorin, Nigeria
| | - Muhammad-Najeeb O Yusuf
- Environmental Engineering Research Laboratory, Department of Chemical Engineering, University of Ilorin, Ilorin, Nigeria
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Liu J, Han G. Tracing riverine sulfate source in an agricultural watershed: Constraints from stable isotopes. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 288:117740. [PMID: 34265563 DOI: 10.1016/j.envpol.2021.117740] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Revised: 06/25/2021] [Accepted: 07/04/2021] [Indexed: 06/13/2023]
Abstract
The sulfate pollution in water environment gains more and more concerns in recent years. The discharge of domestic, municipal, and industrial wastewaters increases the riverine sulfate concentrations, which may cause local health and ecological problems. To better understand the sources of sulfate, this study collected water samples in a typical agricultural watershed in East Thailand. The source apportionment of sulfide was conducted by using stable isotopes and receptor models. The δ34SSO4 value of river water varied from 1.2‰ to 16.4‰, with a median value of 8.9‰. The hydrochemical data indicated that the chemical compositions of Mun river water were affected by the anthropogenic inputs and natural processes such as halite dissolution, carbonate, and silicate weathering. The positive matrix factorization (PMF) model was not suitable to trace source of riverine sulfate, because the meaning of the extracted factors seems to be vague. Based on the elemental ratio and isotopic composition, the inverse model yielded the relative contribution of sulfide oxidation (approximately 46.5%), anthropogenic input (approximately 41.5%), and gypsum dissolution (approximately 12%) to sulfate in Mun river water. This study indicates that the selection of models for source apportionment should be careful. The large contribution of anthropogenic inputs calls an urgent concern of the Thai government to establish effective management strategies in the Mun River basin.
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Affiliation(s)
- Jinke Liu
- Institute of Earth Sciences, China University of Geosciences (Beijing), Beijing, 100083, China
| | - Guilin Han
- Institute of Earth Sciences, China University of Geosciences (Beijing), Beijing, 100083, China.
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50
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Liu X, Jiang N, Zhang R, Yu X, Li S, Miao Q. Composition analysis of PM 2.5 at multiple sites in Zhengzhou, China: implications for characterization and source apportionment at different pollution levels. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2021; 28:59329-59344. [PMID: 33009610 DOI: 10.1007/s11356-020-10943-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/26/2020] [Accepted: 09/20/2020] [Indexed: 06/11/2023]
Abstract
Zhengzhou is one of the most heavily polluted cities in China. This study collected samples of PM2.5 (atmospheric fine particulate matter with aerodynamic diameter ≤ 2.5 μm) at five sites in different functional areas of Zhengzhou in 2016 to investigate the chemical properties and sources of PM2.5 at three pollution levels, i.e., PM2.5 ≤ 75 μg/m3 (non-pollution, NP), 75 μg/m3 < PM2.5 ≤ 150 μg/m3 (moderate pollution, MP), and PM2.5 > 150 μg/m3 (heavy pollution, HP). Chemical analysis was conducted, and source categories and potential source region were identified for PM2.5 at different pollution levels. The health risks of toxic elements were evaluated. Results showed that the average PM2.5 concentration in Zhengzhou was 119 μg/m3, and the sum of the concentrations of SO42-, NO3-, and NH4+ increased with the aggravation of pollution level (23, 42, and 114 μg/m3 at NP, MP, and HP days, respectively). Positive Matrix Factorization analysis indicated that secondary aerosols, coal combustion, vehicle traffic, industrial processes, biomass burning, and dust were the main sources of PM2.5 at three pollution levels, and accounted for 38.4%, 21.6%, 16.7%, 7.4%, 7.7%, and 8.1% on HP days, respectively. Trajectory clustering analysis showed that close-range transport was one of the dominant factors on HP days in Zhengzhou. The potential source areas were mainly located in Xinxiang, Kaifeng, Xuchang, and Pingdingshan. Significant risks existed in the non-carcinogenic risk of As (1.4-2.3) for children at three pollution levels and the non-carcinogenic risk of Pb (1.0-1.4) for children with NP and MP days.
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Affiliation(s)
- Xiaohan Liu
- College of Chemistry, Zhengzhou University, Zhengzhou, 450001, China
| | - Nan Jiang
- School of Ecology and Environment, Zhengzhou University, Zhengzhou, 450001, China.
| | - Ruiqin Zhang
- School of Ecology and Environment, Zhengzhou University, Zhengzhou, 450001, China
| | - Xue Yu
- College of Chemistry, Zhengzhou University, Zhengzhou, 450001, China
| | - Shengli Li
- School of Ecology and Environment, Zhengzhou University, Zhengzhou, 450001, China
| | - Qingqing Miao
- College of Chemistry, Zhengzhou University, Zhengzhou, 450001, China
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