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Wu Q, Li R, Chen J, Yang Z, Li S, Yang Z, Liang Z, Gao L. Historical construction, quantitative source identification and risk assessment of heavy metals contamination in sediments from the Pearl River Estuary, South China. J Environ Manage 2024; 359:120943. [PMID: 38701583 DOI: 10.1016/j.jenvman.2024.120943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2024] [Revised: 03/25/2024] [Accepted: 04/16/2024] [Indexed: 05/05/2024]
Abstract
Historical reconstruction of heavy metals (HMs) contamination in sediments is a key for understanding the effects of anthropogenic stresses on water bodies and predicting the variation trends of environmental state. In this work, eighteen sediment cores from the Pearl River Estuary (PRE) were collected to determine concentrations and geochemical fractions of HMs. Then, their potential sources and the relative contributions during different time periods were quantitatively identified by integrating lead-210 (210Pb) radioisotope dating technique into positive matrix factorisation (PMF) method. Pollution levels and potential ecological risks (PERs) caused by HMs were accurately assessed by enrichment factors (EF) based on establishment of their geochemical baselines (GCBs) and multiparameter evaluation index (MPE). HMs concentrations generally showed a particle size- and organic matter-dependent distribution pattern. During the period of 1958-1978, HMs concentrations remained at low levels with agricultural activities and natural processes being identified as the predominant sources and averagely contributing >60%. Since the reform and opening-up in 1978, industrial and traffic factors become the primary anthropogenic sources of HMs (such as Cu, Zn, Cd, Pb, Cr, and Ni), averagely increasing from 22.1% to 28.1% and from 11.6% to 23.4%, respectively. Conversely, the contributions of agricultural and natural factors decreased from 37.0% to 28.5% and from 29.3% to 20.0%, respectively. Subsequently, implementation of environmental preservation policies was mainly responsible for the declining trend of HMs after 2010. Little enrichment of sediment Cu, Zn, Pb, Cr and Ni with EFs (0.15-1.43) was found in the PRE, whereas EFs of Cd (1.16-2.70) demonstrated a slight to moderate enrichment. MPE indices of Cu (50.7-252), Pb (52.0-147), Zn (35.5-130), Ni (19.6-71.5), Cr (14.2-68.8) and Cd (0-9.90) highlighted their potential ecological hazards due to their non-residual fractions and anthropogenic sources.
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Affiliation(s)
- Qirui Wu
- Carbon-Water Research Station in Karst Regions of Northern Guangdong, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
| | - Rui Li
- Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China
| | - Jianyao Chen
- Carbon-Water Research Station in Karst Regions of Northern Guangdong, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
| | - Zhigang Yang
- Carbon-Water Research Station in Karst Regions of Northern Guangdong, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
| | - Shaoheng Li
- Carbon-Water Research Station in Karst Regions of Northern Guangdong, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
| | - Zaizhi Yang
- Carbon-Water Research Station in Karst Regions of Northern Guangdong, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China
| | - Zuobing Liang
- Carbon-Water Research Station in Karst Regions of Northern Guangdong, School of Geography and Planning, Sun Yat-sen University, Guangzhou, 510275, China.
| | - Lei Gao
- Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems, South China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China.
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Via M, Yus-Díez J, Canonaco F, Petit JE, Hopke P, Reche C, Pandolfi M, Ivančič M, Rigler M, Prevôt ASH, Querol X, Alastuey A, Minguillón MC. Towards a better understanding of fine PM sources: Online and offline datasets combination in a single PMF. Environ Int 2023; 177:108006. [PMID: 37285710 DOI: 10.1016/j.envint.2023.108006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 05/09/2023] [Accepted: 05/29/2023] [Indexed: 06/09/2023]
Abstract
Source apportionment (SA) techniques allocate the measured ambient pollutants with their potential source origin; thus, they are a powerful tool for designing air pollution mitigation strategies. Positive Matrix Factorization (PMF) is one of the most widely used SA approaches, and its multi-time resolution (MTR) methodology, which enables mixing different instrument data in their original time resolution, was the focus of this study. One year of co-located measurements in Barcelona, Spain, of non-refractory submicronic particulate matter (NR-PM1), black carbon (BC) and metals were obtained by a Q-ACSM (Aerodyne Research Inc.), an aethalometer (Aerosol d.o.o.) and fine offline quartz-fibre filters, respectively. These data were combined in a MTR PMF analysis preserving the high time resolution (30 min for the NR-PM1 and BC, and 24 h every 4th day for the offline samples). The MTR-PMF outcomes were assessed varying the time resolution of the high-resolution data subset and exploring the error weightings of both subsets. The time resolution assessment revealed that averaging the high-resolution data was disadvantageous in terms of model residuals and environmental interpretability. The MTR-PMF resolved eight PM1 sources: ammonium sulphate + heavy oil combustion (25%), ammonium nitrate + ammonium chloride (17%), aged secondary organic aerosol (SOA) (16%), traffic (14%), biomass burning (9%), fresh SOA (8%), cooking-like organic aerosol (5%), and industry (4%). The MTR-PMF technique identified two more sources relative to the 24 h base case data subset using the same species and four more with respect to the pseudo-conventional approach mimicking offline PMF, indicating that the combination of both high and low TR data is significantly beneficial for SA. Besides the higher number of sources, the MTR-PMF technique has enabled some sources disentanglement compared to the pseudo-conventional and base case PMF as well as the characterisation of their intra-day patterns.
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Affiliation(s)
- Marta Via
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain; Department of applied physics, Faculty of Physics, University of Barcelona, Barcelona 08028, Spain.
| | - Jesús Yus-Díez
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain; Department of applied physics, Faculty of Physics, University of Barcelona, Barcelona 08028, Spain
| | - Francesco Canonaco
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland; Datalystica Ltd., Park innovAARE, 5234 Villigen, Switzerland
| | - Jean-Eudes Petit
- Laboratoire des Sciences du Climat et de l'Environnement (CNRS-CEA-UVSQ), Gif-sur-Yvette, France
| | - Philip Hopke
- Institute for a Sustainable Environment, Clarkson University, Potsdam NY13699, USA; Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester NY14642, USA
| | - Cristina Reche
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain
| | - Marco Pandolfi
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain
| | - Matic Ivančič
- Aerosol d.o.o., Kamniška 39a, 1000 Ljubljana, Slovenia
| | - Martin Rigler
- Aerosol d.o.o., Kamniška 39a, 1000 Ljubljana, Slovenia
| | - André S H Prevôt
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland
| | - Xavier Querol
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain
| | - Andrés Alastuey
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain
| | - María Cruz Minguillón
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain
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Gu Y, Liu B, Li Y, Zhang Y, Bi X, Wu J, Song C, Dai Q, Han Y, Ren G, Feng Y. Multi-scale volatile organic compound (VOC) source apportionment in Tianjin, China, using a receptor model coupled with 1-hr resolution data. Environ Pollut 2020; 265:115023. [PMID: 32593924 DOI: 10.1016/j.envpol.2020.115023] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2020] [Revised: 05/27/2020] [Accepted: 06/10/2020] [Indexed: 06/11/2023]
Abstract
The multi-scale chemical characteristics and source apportionment of volatile organic compounds (VOCs) were analysed in Tianjin, China, using 1-hr resolution VOC-species data between November 1, 2018 and March 15, 2019. The average total VOC (TVOC) concentration was 30.6 ppbv during the heating season. The alkanes accounted for highest proportion of the TVOC, while the alkenes were the predominant species forming ozone, especially ethylene. Compared to the clean period, the concentration of acetylene during the haze events showed highest increase rate, followed by the ethane; and the concentrations and proportions of alkanes and alkenes were highest during the growth stage (GS) of haze events. The multi-scale apportionment results suggested petrochemical industry and solvent usage (PI/SU, 31.2%), vehicle emissions and liquefied petroleum gas (VE/LPG, 20.5%), and combustion emissions (CE, 19.1%) were the main VOC sources during the heating season. Compared to the clean period, the contributions of PI/SU, VE/LPG, CE, and refinery emissions notably increased during the haze events, while that of gasoline evaporation decreased. The contributions of PI/SU and RPI showed significantly increase during the GS of haze events, whereas most sources decreased during the dissipation stage of haze events. Diurnal-variations in source contributions during the haze events were clearer than the clean period, and the contributions of PI/SU, VE/LPG, and CE during the haze events were markedly higher at night. These findings provide valuable information to inform effective VOC control and prevention measures with specific relevance for the control of ozone pollution in Tianjin.
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Affiliation(s)
- Yao Gu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.
| | - Yafei Li
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Xiaohui Bi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Jianhui Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Congbo Song
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Yan Han
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Ge Ren
- Ying Da Chang An Insurance Brokers Group CO., LTD, Beijing, 100052, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
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Li Y, Liu B, Xue Z, Zhang Y, Sun X, Song C, Dai Q, Fu R, Tai Y, Gao J, Zheng Y, Feng Y. Chemical characteristics and source apportionment of PM 2.5 using PMF modelling coupled with 1-hr resolution online air pollutant dataset for Linfen, China. Environ Pollut 2020; 263:114532. [PMID: 32311623 DOI: 10.1016/j.envpol.2020.114532] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Revised: 03/26/2020] [Accepted: 04/03/2020] [Indexed: 05/10/2023]
Abstract
The chemical species in PM2.5 and air pollutant concentration data with 1-hr resolution were monitored synchronously between 15 November 2018 and 20 January 2019 in Linfen, China, which were analysed for multiple temporal patterns, and PM2.5 source apportionment using positive matrix factorisation (PMF) modelling coupled with online chemical species data was conducted to obtain the apportionment results of distinct temporal patterns. The mean concentration of PM2.5 was 124 μg/m3 during the heating period, and NO3- and organic carbon (OC) were the dominant species. The concentrations and percentages of NO3-, SO42-, and OC increased notably during the growth periods of haze events, thereby indicating secondary particle formation. Six factors were identified by the PMF model during the heating period, including vehicular emissions (VE: 26.5%), secondary nitrate (SN: 16.5%), coal combustion and industrial emissions (CC&IE: 25.7%), secondary sulfate and secondary organic carbon (SS&SOC: 24.4%), biomass burning (BB: 1.0%), and crustal dust (CD: 5.9%). The primary sources of PM2.5 on clean days were CD (33.3%), VE (23.1%), and SS&SOC (20.6%), while they were CC&IE (32.9%) and SS&SOC (28.3%) during the haze events. The contributions of secondary sources and CC&IE increased rapidly during the growth periods of haze events, while that of CD increased during the dissipation period. Diurnal variations in the contribution of secondary sources were mainly related to the accumulation and transformation of corresponding gaseous precursors. In comparison, contributions of CC&IE and VE varied as a function of the domestic heating load and peak levels occurred during the morning and evening rush hours. High contributions of major sources (CC&IE and SS&SOC) during haze events originated mainly from the north and south, while high contribution of a major source (CD) on clean days was from the northwest.
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Affiliation(s)
- Yafei Li
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
| | - Zhigang Xue
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Xiaoyun Sun
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Congbo Song
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China; School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
| | - Ruichen Fu
- Linfen Eco-Environmental Bureau, Linfen, Shanxi, 041000, China
| | - Yonggang Tai
- Linfen Eco-Environmental Bureau, Linfen, Shanxi, 041000, China
| | - Jinyu Gao
- Linfen Eco-Environmental Bureau, Linfen, Shanxi, 041000, China
| | - Yajun Zheng
- Linfen Eco-Environmental Bureau, Linfen, Shanxi, 041000, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Center for Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China
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Tadros CV, Crawford J, Treble PC, Baker A, Cohen DD, Atanacio AJ, Hankin S, Roach R. Chemical characterisation and source identification of atmospheric aerosols in the Snowy Mountains, south-eastern Australia. Sci Total Environ 2018; 630:432-443. [PMID: 29486437 DOI: 10.1016/j.scitotenv.2018.02.231] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2018] [Revised: 02/19/2018] [Accepted: 02/19/2018] [Indexed: 06/08/2023]
Abstract
Characterisation of atmospheric aerosols is of major importance for: climate, the hydrological cycle, human health and policymaking, biogeochemical and palaeo-climatological studies. In this study, the chemical composition and source apportionment of PM2.5 (particulate matter with aerodynamic diameters less than 2.5μm) at Yarrangobilly, in the Snowy Mountains, SE Australia are examined and quantified. A new aerosol monitoring network was deployed in June 2013 and aerosol samples collected during the period July 2013 to July 2017 were analysed for 22 trace elements and black carbon by ion beam analysis techniques. Positive matrix factorisation and back trajectory analysis and trajectory clustering methods were employed for source apportionment and to isolate source areas and air mass travel pathways, respectively. This study identified the mean atmospheric PM2.5 mass concentration for the study period was (3.3±2.5)μgm-3. It is shown that automobile (44.9±0.8)%, secondary sulfate (21.4±0.9)%, smoke (12.3±0.6)%, soil (11.3±0.5)% and aged sea salt (10.1±0.4)% were the five PM2.5 source types, each with its own distinctive trends. The automobile and smoke sources were ascribed to a significant local influence from the road network and bushfire and hazard reduction burns, respectively. Long-range transport are the dominant sources for secondary sulfate from coal-fired power stations, windblown soil from the inland saline regions of the Lake Eyre and Murray-Darling Basins, and aged sea salt from the Southern Ocean to the remote alpine study site. The impact of recent climate change was recognised, as elevated smoke and windblown soil events correlated with drought and El Niño periods. Finally, the overall implications including potential aerosol derived proxies for interpreting palaeo-archives are discussed. To our knowledge, this is the first long-term detailed temporal and spatial characterisation of PM2.5 aerosols for the region and provides a crucial dataset for a range of multidisciplinary research.
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Affiliation(s)
- Carol V Tadros
- Australian Nuclear Science and Technology Organisation, Locked Bag 2001, Kirrawee DC, NSW 2232, Australia; Connected Waters Initiative Research Centre, UNSW Australia, Sydney, NSW, Australia.
| | - Jagoda Crawford
- Australian Nuclear Science and Technology Organisation, Locked Bag 2001, Kirrawee DC, NSW 2232, Australia
| | - Pauline C Treble
- Australian Nuclear Science and Technology Organisation, Locked Bag 2001, Kirrawee DC, NSW 2232, Australia; Connected Waters Initiative Research Centre, UNSW Australia, Sydney, NSW, Australia
| | - Andy Baker
- Connected Waters Initiative Research Centre, UNSW Australia, Sydney, NSW, Australia
| | - David D Cohen
- Australian Nuclear Science and Technology Organisation, Locked Bag 2001, Kirrawee DC, NSW 2232, Australia
| | - Armand J Atanacio
- Australian Nuclear Science and Technology Organisation, Locked Bag 2001, Kirrawee DC, NSW 2232, Australia
| | - Stuart Hankin
- Australian Nuclear Science and Technology Organisation, Locked Bag 2001, Kirrawee DC, NSW 2232, Australia
| | - Regina Roach
- NSW National Parks and Wildlife Service, Sydney, NSW, Australia
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Khan MF, Maulud KNA, Latif MT, Chung JX, Amil N, Alias A, Nadzir MSM, Sahani M, Mohammad M, Jahaya MF, Hassan H, Jeba F, Tahir NM, Abdullah SMS. Physicochemical factors and their potential sources inferred from long-term rainfall measurements at an urban and a remote rural site in tropical areas. Sci Total Environ 2018; 613-614:1401-1416. [PMID: 29898507 DOI: 10.1016/j.scitotenv.2017.08.025] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2017] [Revised: 07/26/2017] [Accepted: 08/02/2017] [Indexed: 06/08/2023]
Abstract
Air pollution can be detected through rainwater composition. In this study, long-term measurements (2000-2014) of wet deposition were made to evaluate the physicochemical interaction and the potential sources of pollution due to changes of land use. The rainwater samples were obtained from an urban site in Kuala Lumpur and a highland-rural site in the middle of Peninsular Malaysia. The compositions of rainwater were obtained from the Malaysian Meteorological Department. The results showed that the urban site experienced more acidity in rainwater (avg=277mm, range of 13.8 to 841mm; pH=4.37) than the rural background site (avg=245mm, range of 2.90 to 598mm; pH=4.97) due to higher anthropogenic input of acid precursors. The enrichment factor (EF) analysis showed that at both sites, SO42-, Ca2+ and K+ were less sensitive to seawater but were greatly influenced by soil dust. NH4+ and Ca2+ can neutralise a larger fraction of the available acid ions in the rainwater at the urban and rural background sites. However, acidifying potential was dominant at urban site compared to rural site. Source-receptor relationship via positive matrix factorisation (PMF 5.0) revealed four similar major sources at both sites with a large variation of the contribution proportions. For urban, the major sources influence on the rainwater chemistry were in the order of secondary nitrates and sulfates>ammonium-rich/agricultural farming>soil components>marine sea salt and biomass burning, while at the background site the order was secondary nitrates and sulfates>marine sea salt and biomass burning=soil components>ammonia-rich/agricultural farming. The long-term trend showed that anthropogenic activities and land use changes have greatly altered the rainwater compositions in the urban environment while the seasonality strongly affected the contribution of sources in the background environment.
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Affiliation(s)
- Md Firoz Khan
- Centre for Tropical Climate Change System, Institute of Climate Change, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia.
| | - Khairul Nizam Abdul Maulud
- Earth Observation Centre, Institute of Climate Change, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia; Department of Civil and Structural Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
| | - Mohd Talib Latif
- School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia; Institute for Environment and Development (Lestari), Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
| | - Jing Xiang Chung
- School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
| | - Norhaniza Amil
- Environmental Technology Division, School of Industrial Technology, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia
| | - Azwani Alias
- School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
| | - Mohd Shahrul Mohd Nadzir
- Centre for Tropical Climate Change System, Institute of Climate Change, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia; School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
| | - Mazrura Sahani
- Environmental Health and Industrial Safety Program, School of Diagnostic and Applied Health Sciences, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Jalan Raja Muda Abdul Aziz, 50300 Kuala Lumpur, Malaysia
| | - Maznorizan Mohammad
- Malaysian Meteorological Department, Jalan Sultan, 46667 Petaling Jaya, Selangor, Malaysia
| | - Mohd Firdaus Jahaya
- Malaysian Meteorological Department, Jalan Sultan, 46667 Petaling Jaya, Selangor, Malaysia
| | - Hanashriah Hassan
- School of Environmental and Natural Resource Sciences, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia; Malaysian Meteorological Department, Jalan Sultan, 46667 Petaling Jaya, Selangor, Malaysia
| | - Farah Jeba
- Department of Chemistry, University of Dhaka, Dhaka 1000, Bangladesh
| | - Norhayati Md Tahir
- Environmental Research Group, School of Marine and Environment Sciences, Universiti Malaysia Terengganu, 21030 Kuala Terengganu, Terengganu, Malaysia; Institute of Oceanography, Universiti Malaysia Terengganu, 21030 Kuala Terengganu, Terengganu, Malaysia
| | - Sharifah Mastura Syed Abdullah
- Social, Environmental and Developmental Sustainability Research Centre (SEEDS), Faculty of Social Sciences and Humanities, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia; Institute of Climate Change, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
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Lan Z, Zhang B, Huang X, Zhu Q, Yuan J, Zeng L, Hu M, He L. Source apportionment of PM 2.5 light extinction in an urban atmosphere in China. J Environ Sci (China) 2018; 63:277-284. [PMID: 29406110 DOI: 10.1016/j.jes.2017.07.016] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2017] [Revised: 06/01/2017] [Accepted: 07/20/2017] [Indexed: 06/07/2023]
Abstract
Haze in China is primarily caused by high pollution of atmospheric fine particulates (PM2.5). However, the detailed source structures of PM2.5 light extinction have not been well established, especially for the roles of various organic aerosols, which makes haze management lack specified targets. This study obtained the mass concentrations of the chemical compositions and the light extinction coefficients of fine particles in the winter in Dongguan, Guangdong Province, using high time resolution aerosol observation instruments. We combined the positive matrix factor (PMF) analysis model of organic aerosols and the multiple linear regression method to establish a quantitative relationship model between the main chemical components, in particular the different sources of organic aerosols and the extinction coefficients of fine particles with a high goodness of fit (R2=0.953). The results show that the contribution rates of ammonium sulphate, ammonium nitrate, biomass burning organic aerosol (BBOA), secondary organic aerosol (SOA) and black carbon (BC) were 48.1%, 20.7%, 15.0%, 10.6%, and 5.6%, respectively. It can be seen that the contribution of the secondary aerosols is much higher than that of the primary aerosols (79.4% versus 20.6%) and are a major factor in the visibility decline. BBOA is found to have a high visibility destroying potential, with a high mass extinction coefficient, and was the largest contributor during some high pollution periods. A more detailed analysis indicates that the contribution of the enhanced absorption caused by BC mixing state was approximately 37.7% of the total particle absorption and should not be neglected.
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Affiliation(s)
- Zijuan Lan
- Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China; Shenzhen Research Academy of Environmental Sciences, Shenzhen 518001, China
| | - Bin Zhang
- Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Xiaofeng Huang
- Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China.
| | - Qiao Zhu
- Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Jinfeng Yuan
- Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Liwu Zeng
- Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
| | - Min Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Lingyan He
- Key Laboratory for Urban Habitat Environmental Science and Technology, School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
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8
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Alghamdi MA, Alam MS, Yin J, Stark C, Jang E, Harrison RM, Shamy M, Khoder MI, Shabbaj II. Receptor modelling study of polycyclic aromatic hydrocarbons in Jeddah, Saudi Arabia. Sci Total Environ 2015; 506-507:401-408. [PMID: 25460975 DOI: 10.1016/j.scitotenv.2014.10.056] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2014] [Revised: 09/23/2014] [Accepted: 10/17/2014] [Indexed: 06/04/2023]
Abstract
Measurements of 14 polycyclic aromatic hydrocarbons (PAH) have been made in Jeddah, Saudi Arabia, with a view to establishing the concentrations in this major city, and quantifying the contributions of major sources. Particulate and vapour forms have been sampled and analysed separately. The concentrations are compared to measurements from other sites in the Middle Eastern region and are towards the lower end of the range, being far lower than concentrations reported from Riyadh (Saudi Arabia), Assiut (Egypt) and Tehran (Iran) but broadly similar to those measured in Damascus (Syria) and higher than those measured in Kuwait. The partitioning between vapour and particle phases is similar to that in data from Egypt and China, but with many compounds showing a higher particle-associated percentage than in Birmingham (UK) possibly reflecting a higher concentration of airborne particulate matter in the former countries. Concentrations in Jeddah were significantly higher at a site close to the oil refinery and a site close to a major ring road than at a suburban site to the north of the city. Application of positive matrix factorisation to the pooled data elicited three factors accounting respectively for 17%, 33% and 50% of the measured sum of PAH and these are interpreted as arising from gasoline vehicles, industrial sources, particularly the oil refinery, and to diesel/fuel oil combustion.
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Affiliation(s)
- Mansour A Alghamdi
- Department of Environmental Sciences, Faculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Mohammed S Alam
- Division of Environmental Health & Risk Management, School of Geography, Earth & Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom.
| | - Jianxin Yin
- Division of Environmental Health & Risk Management, School of Geography, Earth & Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Christopher Stark
- Division of Environmental Health & Risk Management, School of Geography, Earth & Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Eunhwa Jang
- Division of Environmental Health & Risk Management, School of Geography, Earth & Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Roy M Harrison
- Department of Environmental Sciences, Faculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz University, Jeddah, Saudi Arabia; Division of Environmental Health & Risk Management, School of Geography, Earth & Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom.
| | - Magdy Shamy
- Department of Environmental Sciences, Faculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Mamdouh I Khoder
- Department of Environmental Sciences, Faculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Ibrahim I Shabbaj
- Department of Environmental Sciences, Faculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz University, Jeddah, Saudi Arabia
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9
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Zhang J, Wang J, Hua P, Krebs P. The qualitative and quantitative source apportionments of polycyclic aromatic hydrocarbons in size dependent road deposited sediment. Sci Total Environ 2015; 505:90-101. [PMID: 25310884 DOI: 10.1016/j.scitotenv.2014.09.091] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2014] [Revised: 09/26/2014] [Accepted: 09/26/2014] [Indexed: 06/04/2023]
Abstract
This study showcases the qualitative and quantitative source apportionments of size-dependent polycyclic aromatic hydrocarbons (PAHs) in road deposited sediment by means of molecular diagnostic ratio (MDR) and positive matrix factorisation (PMF) approaches. The MDR was initially used to narrow the PAH source candidates. PMF modelling was subsequently used to provide more precise source apportionment with the assistance of a multiple linear regression analysis. Through a combined qualitative and quantitative source apportionment, different potential source contributors were identified at different size fractions. Explicitly, three major contributors to sorption at the size fraction of 1000-400 μm were tentatively identified as incineration (26%), coal combustion (53%) and gasoline-powered vehicle (20%). Four major contributors to the size fraction of 400-100 μm were identified as gasoline-powered vehicle (25%), surface pavement (15%), diesel-powered vehicle (37%) and industrial boiler (24%). Four major contributors to the size fraction of 100-63 μm were identified as cogeneration emission (13%), diesel-powered vehicle (28%), tire debris (45%) and wood combustion (14%). The potential contributors in the size fraction 63-0.45 μm were identified as diesel-powered vehicle (21%), heterogeneous sources (41%) and biomass burning (38%). In addition, the highest ∑16PAH concentration was found in the smallest size fraction of 63-0.45 μm, which is also where the highest BaPE and TEF values for potential risk assessment occurred.
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Affiliation(s)
- Jin Zhang
- Institute of Urban Water Management, Technische Universität Dresden, 01062 Dresden, Germany.
| | - Jing Wang
- Institute of Urban Water Management, Technische Universität Dresden, 01062 Dresden, Germany
| | - Pei Hua
- Chair of Water Supply Engineering, Institute of Urban Water Management, Technische Universität Dresden, 01062 Dresden, Germany.
| | - Peter Krebs
- Institute of Urban Water Management, Technische Universität Dresden, 01062 Dresden, Germany
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