Potential source contributions and risk assessment of PAHs in sediments from Taihu Lake, China: Comparison of three receptor models

In this work, three receptor models (Principal Component Analysis–Multiple Linear Regression (PCA–MLR) model, Unmix model and Positive Matrix Factorization (PMF) model) were employed to investigate potential source apportionment of PAHs in sediments from Taihu Lake, China. A total of 15 priority PAH...

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Veröffentlicht in:Water research (Oxford) 2012-06, Vol.46 (9), p.3065-3073
Hauptverfasser: Zhang, Yuan, Guo, Chang-Sheng, Xu, Jian, Tian, Ying-Ze, Shi, Guo-Liang, Feng, Yin-Chang
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container_end_page 3073
container_issue 9
container_start_page 3065
container_title Water research (Oxford)
container_volume 46
creator Zhang, Yuan
Guo, Chang-Sheng
Xu, Jian
Tian, Ying-Ze
Shi, Guo-Liang
Feng, Yin-Chang
description In this work, three receptor models (Principal Component Analysis–Multiple Linear Regression (PCA–MLR) model, Unmix model and Positive Matrix Factorization (PMF) model) were employed to investigate potential source apportionment of PAHs in sediments from Taihu Lake, China. A total of 15 priority PAHs in 29 sediments from Taihu Lake were measured, with ∑PAHs (sum of 15 PAHs) concentrations ranging from 209 to 1003 ng g−1 dw. Source apportionment results derived from three different models were similar, indicating that the highest contribution to ∑PAHs was from vehicular emission (53.6–54.3%), followed by coal combustion (23.8–28.8%) and wood combustion (11.9–16.0%). The contribution of mixed wood and coal combustion source identified by PCA–MLR was 41.3%. For the first time the risk assessment for each identified source category was quantitatively calculated by combining the BaP equivalents (BaPE) values with estimated source contributions. The results showed that vehicular emission posed the highest toxic risk, with BaPE values of 26.9–31.5 ng g−1 dw, and the BaPE values for coal combustion and wood combustion were 6.56–15.6 ng g−1 dw and 2.94–6.11 ng g−1 dw, respectively. The distributions of contribution and BaPE for each identified source category were studied as well, and showed similar trends among the sampling sites, for each source category. [Display omitted] ► Fifteen PAHs concentration were measured in sediments. ► Source apportionment was study by three receptor models. ► Vehicular emission got the highest contributions: 53.6–54.3%. ► Vehicular emission got the highest toxic risk: 26.9–31.5 ng g−1 dw for BaPE.
doi_str_mv 10.1016/j.watres.2012.03.006
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A total of 15 priority PAHs in 29 sediments from Taihu Lake were measured, with ∑PAHs (sum of 15 PAHs) concentrations ranging from 209 to 1003 ng g−1 dw. Source apportionment results derived from three different models were similar, indicating that the highest contribution to ∑PAHs was from vehicular emission (53.6–54.3%), followed by coal combustion (23.8–28.8%) and wood combustion (11.9–16.0%). The contribution of mixed wood and coal combustion source identified by PCA–MLR was 41.3%. For the first time the risk assessment for each identified source category was quantitatively calculated by combining the BaP equivalents (BaPE) values with estimated source contributions. The results showed that vehicular emission posed the highest toxic risk, with BaPE values of 26.9–31.5 ng g−1 dw, and the BaPE values for coal combustion and wood combustion were 6.56–15.6 ng g−1 dw and 2.94–6.11 ng g−1 dw, respectively. The distributions of contribution and BaPE for each identified source category were studied as well, and showed similar trends among the sampling sites, for each source category. [Display omitted] ► Fifteen PAHs concentration were measured in sediments. ► Source apportionment was study by three receptor models. ► Vehicular emission got the highest contributions: 53.6–54.3%. ► Vehicular emission got the highest toxic risk: 26.9–31.5 ng g−1 dw for BaPE.</description><identifier>ISSN: 0043-1354</identifier><identifier>EISSN: 1879-2448</identifier><identifier>DOI: 10.1016/j.watres.2012.03.006</identifier><identifier>PMID: 22459329</identifier><identifier>CODEN: WATRAG</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Applied sciences ; Categories ; China ; Coal ; Combustion ; Exact sciences and technology ; Geologic Sediments - chemistry ; Lakes ; linear models ; Models, Theoretical ; PAHs ; Pollution ; Polyallylamine hydrochloride ; polycyclic aromatic hydrocarbons ; Polycyclic Compounds - analysis ; Receptor models ; risk ; Risk Assessment ; Sediments ; Source apportionment ; toxicity ; Water Pollutants, Chemical - analysis ; Water treatment and pollution ; Wood</subject><ispartof>Water research (Oxford), 2012-06, Vol.46 (9), p.3065-3073</ispartof><rights>2012 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><rights>Copyright © 2012 Elsevier Ltd. 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A total of 15 priority PAHs in 29 sediments from Taihu Lake were measured, with ∑PAHs (sum of 15 PAHs) concentrations ranging from 209 to 1003 ng g−1 dw. Source apportionment results derived from three different models were similar, indicating that the highest contribution to ∑PAHs was from vehicular emission (53.6–54.3%), followed by coal combustion (23.8–28.8%) and wood combustion (11.9–16.0%). The contribution of mixed wood and coal combustion source identified by PCA–MLR was 41.3%. For the first time the risk assessment for each identified source category was quantitatively calculated by combining the BaP equivalents (BaPE) values with estimated source contributions. The results showed that vehicular emission posed the highest toxic risk, with BaPE values of 26.9–31.5 ng g−1 dw, and the BaPE values for coal combustion and wood combustion were 6.56–15.6 ng g−1 dw and 2.94–6.11 ng g−1 dw, respectively. The distributions of contribution and BaPE for each identified source category were studied as well, and showed similar trends among the sampling sites, for each source category. 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Guo, Chang-Sheng ; Xu, Jian ; Tian, Ying-Ze ; Shi, Guo-Liang ; Feng, Yin-Chang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c449t-22be8fcecb0bfae5ac76e9dcc6a9f614ea588961214824baa0c15c3ea5792fdc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Applied sciences</topic><topic>Categories</topic><topic>China</topic><topic>Coal</topic><topic>Combustion</topic><topic>Exact sciences and technology</topic><topic>Geologic Sediments - chemistry</topic><topic>Lakes</topic><topic>linear models</topic><topic>Models, Theoretical</topic><topic>PAHs</topic><topic>Pollution</topic><topic>Polyallylamine hydrochloride</topic><topic>polycyclic aromatic hydrocarbons</topic><topic>Polycyclic Compounds - analysis</topic><topic>Receptor models</topic><topic>risk</topic><topic>Risk Assessment</topic><topic>Sediments</topic><topic>Source apportionment</topic><topic>toxicity</topic><topic>Water Pollutants, Chemical - analysis</topic><topic>Water treatment and pollution</topic><topic>Wood</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Yuan</creatorcontrib><creatorcontrib>Guo, Chang-Sheng</creatorcontrib><creatorcontrib>Xu, Jian</creatorcontrib><creatorcontrib>Tian, Ying-Ze</creatorcontrib><creatorcontrib>Shi, Guo-Liang</creatorcontrib><creatorcontrib>Feng, Yin-Chang</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Water research (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Yuan</au><au>Guo, Chang-Sheng</au><au>Xu, Jian</au><au>Tian, Ying-Ze</au><au>Shi, Guo-Liang</au><au>Feng, Yin-Chang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Potential source contributions and risk assessment of PAHs in sediments from Taihu Lake, China: Comparison of three receptor models</atitle><jtitle>Water research (Oxford)</jtitle><addtitle>Water Res</addtitle><date>2012-06-01</date><risdate>2012</risdate><volume>46</volume><issue>9</issue><spage>3065</spage><epage>3073</epage><pages>3065-3073</pages><issn>0043-1354</issn><eissn>1879-2448</eissn><coden>WATRAG</coden><abstract>In this work, three receptor models (Principal Component Analysis–Multiple Linear Regression (PCA–MLR) model, Unmix model and Positive Matrix Factorization (PMF) model) were employed to investigate potential source apportionment of PAHs in sediments from Taihu Lake, China. A total of 15 priority PAHs in 29 sediments from Taihu Lake were measured, with ∑PAHs (sum of 15 PAHs) concentrations ranging from 209 to 1003 ng g−1 dw. Source apportionment results derived from three different models were similar, indicating that the highest contribution to ∑PAHs was from vehicular emission (53.6–54.3%), followed by coal combustion (23.8–28.8%) and wood combustion (11.9–16.0%). The contribution of mixed wood and coal combustion source identified by PCA–MLR was 41.3%. For the first time the risk assessment for each identified source category was quantitatively calculated by combining the BaP equivalents (BaPE) values with estimated source contributions. The results showed that vehicular emission posed the highest toxic risk, with BaPE values of 26.9–31.5 ng g−1 dw, and the BaPE values for coal combustion and wood combustion were 6.56–15.6 ng g−1 dw and 2.94–6.11 ng g−1 dw, respectively. The distributions of contribution and BaPE for each identified source category were studied as well, and showed similar trends among the sampling sites, for each source category. [Display omitted] ► Fifteen PAHs concentration were measured in sediments. ► Source apportionment was study by three receptor models. ► Vehicular emission got the highest contributions: 53.6–54.3%. ► Vehicular emission got the highest toxic risk: 26.9–31.5 ng g−1 dw for BaPE.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>22459329</pmid><doi>10.1016/j.watres.2012.03.006</doi><tpages>9</tpages></addata></record>
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source MEDLINE; ScienceDirect Journals (5 years ago - present)
subjects Applied sciences
Categories
China
Coal
Combustion
Exact sciences and technology
Geologic Sediments - chemistry
Lakes
linear models
Models, Theoretical
PAHs
Pollution
Polyallylamine hydrochloride
polycyclic aromatic hydrocarbons
Polycyclic Compounds - analysis
Receptor models
risk
Risk Assessment
Sediments
Source apportionment
toxicity
Water Pollutants, Chemical - analysis
Water treatment and pollution
Wood
title Potential source contributions and risk assessment of PAHs in sediments from Taihu Lake, China: Comparison of three receptor models
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