Loading…

Source apportionment of heavy metals in farmland soil of Wuwei, China: Comparison of three receptor models

Receptor models are, rarely utilized in soil but are often used to identify pollutant sources and quantify their contribution. This paper focuses on the soil in oasis farmland. A geochemical baseline is used to assess the pollution of the soil, and then three models are tentatively utilized to appor...

Full description

Saved in:
Bibliographic Details
Published in:Journal of cleaner production 2019-11, Vol.237, p.117792, Article 117792
Main Authors: Guan, Qingyu, Zhao, Rui, Pan, Ninghui, Wang, Feifei, Yang, Yanyan, Luo, Haiping
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c367t-96075a0eead9449bea623fffe841290550f3e4cbb4220db27e3ef88242b0e2763
cites cdi_FETCH-LOGICAL-c367t-96075a0eead9449bea623fffe841290550f3e4cbb4220db27e3ef88242b0e2763
container_end_page
container_issue
container_start_page 117792
container_title Journal of cleaner production
container_volume 237
creator Guan, Qingyu
Zhao, Rui
Pan, Ninghui
Wang, Feifei
Yang, Yanyan
Luo, Haiping
description Receptor models are, rarely utilized in soil but are often used to identify pollutant sources and quantify their contribution. This paper focuses on the soil in oasis farmland. A geochemical baseline is used to assess the pollution of the soil, and then three models are tentatively utilized to apportion heavy metals and compare the sources, the contributions and the operation effects. Pollution assessment indicated that the farmland soil of Wuwei was lightly contaminated by heavy metals. Source apportionments suggested that atmospheric deposition contributed the most pollution (53.95%–65.35%). The three models supplemented each other, and the grouped principal component analysis/absolute principal component scores (GPCA/APCS) was outstanding. GPCA/APCS and UNMIX suggested that agricultural activities were the prime anthropogenic source (51.06%–61.56%), followed by the combustion of fossil fuels (coal and oil) (27.92%–28.66%) and building materials-related activities source (10.52%–20.29%). Fertilizers and pesticides (67.88%–74.81%) contributed more than traffic emissions (25.19%–32.12%) in agricultural activities. Similar results were acquired via positive matrix factorization (PMF), while industrial activity was the highest individual contributor (29.91%). Therefore, combining these three models was the most effective approach, and more attention should be paid to mitigating the pollution caused by the use of fertilizers and pesticides as well as the industrial activities in Wuwei. The results of this study could provide reference in reduction of heavy metal pollution in farmland soil. [Display omitted] •Evaluating pollution by background values based on geochemical baseline.•Apportioning heavy metal source by GPCA/APCS, PMF and UNMIX.•GPCA/APCS model was optimal.•Fertilizers, pesticides and industrial activities were large contributor.
doi_str_mv 10.1016/j.jclepro.2019.117792
format article
fullrecord <record><control><sourceid>elsevier_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1016_j_jclepro_2019_117792</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0959652619326526</els_id><sourcerecordid>S0959652619326526</sourcerecordid><originalsourceid>FETCH-LOGICAL-c367t-96075a0eead9449bea623fffe841290550f3e4cbb4220db27e3ef88242b0e2763</originalsourceid><addsrcrecordid>eNqFkM1KxDAURoMoOI4-gpAHsDVJ26RxI1L8gwEXKi5Dmt4wKW1Tks7IvL0tM3tXd_Hd73DvQeiWkpQSyu_btDUdjMGnjFCZUiqEZGdoRUshEypKfo5WRBYy4QXjl-gqxpYQKojIV6j99LtgAOtx9GFyfuhhmLC3eAt6f8A9TLqL2A3Y6tB3emhw9K5bFn52v-DucLV1g37Ale9HHVz0w5JN2wCAAxgYJx9w7xvo4jW6sDMMbk5zjb5fnr-qt2Tz8fpePW0Sk3ExJZITUWgCoBuZ57IGzVlmrYUyp0ySoiA2g9zUdc4YaWomIANblixnNQEmeLZGxZFrgo8xgFVjcL0OB0WJWoSpVp2EqUWYOgqbe4_H3nwr7B0EFY2DwUDj5k8m1Xj3D-EPOkx4qQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Source apportionment of heavy metals in farmland soil of Wuwei, China: Comparison of three receptor models</title><source>ScienceDirect Freedom Collection</source><creator>Guan, Qingyu ; Zhao, Rui ; Pan, Ninghui ; Wang, Feifei ; Yang, Yanyan ; Luo, Haiping</creator><creatorcontrib>Guan, Qingyu ; Zhao, Rui ; Pan, Ninghui ; Wang, Feifei ; Yang, Yanyan ; Luo, Haiping</creatorcontrib><description>Receptor models are, rarely utilized in soil but are often used to identify pollutant sources and quantify their contribution. This paper focuses on the soil in oasis farmland. A geochemical baseline is used to assess the pollution of the soil, and then three models are tentatively utilized to apportion heavy metals and compare the sources, the contributions and the operation effects. Pollution assessment indicated that the farmland soil of Wuwei was lightly contaminated by heavy metals. Source apportionments suggested that atmospheric deposition contributed the most pollution (53.95%–65.35%). The three models supplemented each other, and the grouped principal component analysis/absolute principal component scores (GPCA/APCS) was outstanding. GPCA/APCS and UNMIX suggested that agricultural activities were the prime anthropogenic source (51.06%–61.56%), followed by the combustion of fossil fuels (coal and oil) (27.92%–28.66%) and building materials-related activities source (10.52%–20.29%). Fertilizers and pesticides (67.88%–74.81%) contributed more than traffic emissions (25.19%–32.12%) in agricultural activities. Similar results were acquired via positive matrix factorization (PMF), while industrial activity was the highest individual contributor (29.91%). Therefore, combining these three models was the most effective approach, and more attention should be paid to mitigating the pollution caused by the use of fertilizers and pesticides as well as the industrial activities in Wuwei. The results of this study could provide reference in reduction of heavy metal pollution in farmland soil. [Display omitted] •Evaluating pollution by background values based on geochemical baseline.•Apportioning heavy metal source by GPCA/APCS, PMF and UNMIX.•GPCA/APCS model was optimal.•Fertilizers, pesticides and industrial activities were large contributor.</description><identifier>ISSN: 0959-6526</identifier><identifier>EISSN: 1879-1786</identifier><identifier>DOI: 10.1016/j.jclepro.2019.117792</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Farmland soil heavy metals ; GPCA/APCS ; PMF ; Source apportionment ; UNMIX</subject><ispartof>Journal of cleaner production, 2019-11, Vol.237, p.117792, Article 117792</ispartof><rights>2019 Elsevier Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c367t-96075a0eead9449bea623fffe841290550f3e4cbb4220db27e3ef88242b0e2763</citedby><cites>FETCH-LOGICAL-c367t-96075a0eead9449bea623fffe841290550f3e4cbb4220db27e3ef88242b0e2763</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Guan, Qingyu</creatorcontrib><creatorcontrib>Zhao, Rui</creatorcontrib><creatorcontrib>Pan, Ninghui</creatorcontrib><creatorcontrib>Wang, Feifei</creatorcontrib><creatorcontrib>Yang, Yanyan</creatorcontrib><creatorcontrib>Luo, Haiping</creatorcontrib><title>Source apportionment of heavy metals in farmland soil of Wuwei, China: Comparison of three receptor models</title><title>Journal of cleaner production</title><description>Receptor models are, rarely utilized in soil but are often used to identify pollutant sources and quantify their contribution. This paper focuses on the soil in oasis farmland. A geochemical baseline is used to assess the pollution of the soil, and then three models are tentatively utilized to apportion heavy metals and compare the sources, the contributions and the operation effects. Pollution assessment indicated that the farmland soil of Wuwei was lightly contaminated by heavy metals. Source apportionments suggested that atmospheric deposition contributed the most pollution (53.95%–65.35%). The three models supplemented each other, and the grouped principal component analysis/absolute principal component scores (GPCA/APCS) was outstanding. GPCA/APCS and UNMIX suggested that agricultural activities were the prime anthropogenic source (51.06%–61.56%), followed by the combustion of fossil fuels (coal and oil) (27.92%–28.66%) and building materials-related activities source (10.52%–20.29%). Fertilizers and pesticides (67.88%–74.81%) contributed more than traffic emissions (25.19%–32.12%) in agricultural activities. Similar results were acquired via positive matrix factorization (PMF), while industrial activity was the highest individual contributor (29.91%). Therefore, combining these three models was the most effective approach, and more attention should be paid to mitigating the pollution caused by the use of fertilizers and pesticides as well as the industrial activities in Wuwei. The results of this study could provide reference in reduction of heavy metal pollution in farmland soil. [Display omitted] •Evaluating pollution by background values based on geochemical baseline.•Apportioning heavy metal source by GPCA/APCS, PMF and UNMIX.•GPCA/APCS model was optimal.•Fertilizers, pesticides and industrial activities were large contributor.</description><subject>Farmland soil heavy metals</subject><subject>GPCA/APCS</subject><subject>PMF</subject><subject>Source apportionment</subject><subject>UNMIX</subject><issn>0959-6526</issn><issn>1879-1786</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNqFkM1KxDAURoMoOI4-gpAHsDVJ26RxI1L8gwEXKi5Dmt4wKW1Tks7IvL0tM3tXd_Hd73DvQeiWkpQSyu_btDUdjMGnjFCZUiqEZGdoRUshEypKfo5WRBYy4QXjl-gqxpYQKojIV6j99LtgAOtx9GFyfuhhmLC3eAt6f8A9TLqL2A3Y6tB3emhw9K5bFn52v-DucLV1g37Ale9HHVz0w5JN2wCAAxgYJx9w7xvo4jW6sDMMbk5zjb5fnr-qt2Tz8fpePW0Sk3ExJZITUWgCoBuZ57IGzVlmrYUyp0ySoiA2g9zUdc4YaWomIANblixnNQEmeLZGxZFrgo8xgFVjcL0OB0WJWoSpVp2EqUWYOgqbe4_H3nwr7B0EFY2DwUDj5k8m1Xj3D-EPOkx4qQ</recordid><startdate>20191110</startdate><enddate>20191110</enddate><creator>Guan, Qingyu</creator><creator>Zhao, Rui</creator><creator>Pan, Ninghui</creator><creator>Wang, Feifei</creator><creator>Yang, Yanyan</creator><creator>Luo, Haiping</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20191110</creationdate><title>Source apportionment of heavy metals in farmland soil of Wuwei, China: Comparison of three receptor models</title><author>Guan, Qingyu ; Zhao, Rui ; Pan, Ninghui ; Wang, Feifei ; Yang, Yanyan ; Luo, Haiping</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c367t-96075a0eead9449bea623fffe841290550f3e4cbb4220db27e3ef88242b0e2763</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Farmland soil heavy metals</topic><topic>GPCA/APCS</topic><topic>PMF</topic><topic>Source apportionment</topic><topic>UNMIX</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guan, Qingyu</creatorcontrib><creatorcontrib>Zhao, Rui</creatorcontrib><creatorcontrib>Pan, Ninghui</creatorcontrib><creatorcontrib>Wang, Feifei</creatorcontrib><creatorcontrib>Yang, Yanyan</creatorcontrib><creatorcontrib>Luo, Haiping</creatorcontrib><collection>CrossRef</collection><jtitle>Journal of cleaner production</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guan, Qingyu</au><au>Zhao, Rui</au><au>Pan, Ninghui</au><au>Wang, Feifei</au><au>Yang, Yanyan</au><au>Luo, Haiping</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Source apportionment of heavy metals in farmland soil of Wuwei, China: Comparison of three receptor models</atitle><jtitle>Journal of cleaner production</jtitle><date>2019-11-10</date><risdate>2019</risdate><volume>237</volume><spage>117792</spage><pages>117792-</pages><artnum>117792</artnum><issn>0959-6526</issn><eissn>1879-1786</eissn><abstract>Receptor models are, rarely utilized in soil but are often used to identify pollutant sources and quantify their contribution. This paper focuses on the soil in oasis farmland. A geochemical baseline is used to assess the pollution of the soil, and then three models are tentatively utilized to apportion heavy metals and compare the sources, the contributions and the operation effects. Pollution assessment indicated that the farmland soil of Wuwei was lightly contaminated by heavy metals. Source apportionments suggested that atmospheric deposition contributed the most pollution (53.95%–65.35%). The three models supplemented each other, and the grouped principal component analysis/absolute principal component scores (GPCA/APCS) was outstanding. GPCA/APCS and UNMIX suggested that agricultural activities were the prime anthropogenic source (51.06%–61.56%), followed by the combustion of fossil fuels (coal and oil) (27.92%–28.66%) and building materials-related activities source (10.52%–20.29%). Fertilizers and pesticides (67.88%–74.81%) contributed more than traffic emissions (25.19%–32.12%) in agricultural activities. Similar results were acquired via positive matrix factorization (PMF), while industrial activity was the highest individual contributor (29.91%). Therefore, combining these three models was the most effective approach, and more attention should be paid to mitigating the pollution caused by the use of fertilizers and pesticides as well as the industrial activities in Wuwei. The results of this study could provide reference in reduction of heavy metal pollution in farmland soil. [Display omitted] •Evaluating pollution by background values based on geochemical baseline.•Apportioning heavy metal source by GPCA/APCS, PMF and UNMIX.•GPCA/APCS model was optimal.•Fertilizers, pesticides and industrial activities were large contributor.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.jclepro.2019.117792</doi></addata></record>
fulltext fulltext
identifier ISSN: 0959-6526
ispartof Journal of cleaner production, 2019-11, Vol.237, p.117792, Article 117792
issn 0959-6526
1879-1786
language eng
recordid cdi_crossref_primary_10_1016_j_jclepro_2019_117792
source ScienceDirect Freedom Collection
subjects Farmland soil heavy metals
GPCA/APCS
PMF
Source apportionment
UNMIX
title Source apportionment of heavy metals in farmland soil of Wuwei, China: Comparison of three receptor models
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-12T20%3A08%3A19IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-elsevier_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Source%20apportionment%20of%20heavy%20metals%20in%20farmland%20soil%20of%20Wuwei,%20China:%20Comparison%20of%20three%20receptor%20models&rft.jtitle=Journal%20of%20cleaner%20production&rft.au=Guan,%20Qingyu&rft.date=2019-11-10&rft.volume=237&rft.spage=117792&rft.pages=117792-&rft.artnum=117792&rft.issn=0959-6526&rft.eissn=1879-1786&rft_id=info:doi/10.1016/j.jclepro.2019.117792&rft_dat=%3Celsevier_cross%3ES0959652619326526%3C/elsevier_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c367t-96075a0eead9449bea623fffe841290550f3e4cbb4220db27e3ef88242b0e2763%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true