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Cited 29 time in webofscience Cited 33 time in scopus
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Characterization and source identification of pollutants in runoff from a mixed land use watershed using ordination analyses

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dc.contributor.authorLee, Dong Hoon-
dc.contributor.authorKim, Jin Hwi-
dc.contributor.authorMendoza, Joseph A.-
dc.contributor.authorLee, Chang Hee-
dc.contributor.authorKang, Joo-Hyon-
dc.date.accessioned2024-09-25T03:00:39Z-
dc.date.available2024-09-25T03:00:39Z-
dc.date.issued2016-05-
dc.identifier.issn0944-1344-
dc.identifier.issn1614-7499-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/23436-
dc.description.abstractWhile identification of critical pollutant sources is the key initial step for cost-effective runoff management, it is challenging due to the highly uncertain nature of runoff pollution, especially during a storm event. To identify critical sources and their quantitative contributions to runoff pollution (especially focusing on phosphorous), two ordination methods were used in this study: principal component analysis (PCA) and positive matrix factorization (PMF). For the ordination analyses, we used runoff quality data for 14 storm events, including data for phosphorus, 11 heavy metal species, and eight ionic species measured at the outlets of subcatchments with different land use compositions in a mixed land use watershed. Five factors as sources of runoff pollutants were identified by PCA: agrochemicals, groundwater, native soils, domestic sewage, and urban sources (building materials and automotive activities). PMF identified similar factors to those identified by PCA, with more detailed source mechanisms for groundwater (i.e., nitrate leaching and cation exchange) and urban sources (vehicle components/motor oils/building materials and vehicle exhausts), confirming the sources identified by PCA. PMF was further used to quantify contributions of the identified sources to the water quality. Based on the results, agrochemicals and automotive activities were the two dominant and ubiquitous phosphorus sources (39-61 and 16-47 %, respectively) in the study area, regardless of land use types.-
dc.format.extent17-
dc.language영어-
dc.language.isoENG-
dc.publisherSPRINGER HEIDELBERG-
dc.titleCharacterization and source identification of pollutants in runoff from a mixed land use watershed using ordination analyses-
dc.typeArticle-
dc.publisher.location독일-
dc.identifier.doi10.1007/s11356-016-6155-x-
dc.identifier.scopusid2-s2.0-84957542754-
dc.identifier.wosid000376421400049-
dc.identifier.bibliographicCitationENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, v.23, no.10, pp 9774 - 9790-
dc.citation.titleENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH-
dc.citation.volume23-
dc.citation.number10-
dc.citation.startPage9774-
dc.citation.endPage9790-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClasssci-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEnvironmental Sciences & Ecology-
dc.relation.journalWebOfScienceCategoryEnvironmental Sciences-
dc.subject.keywordPlusPOSITIVE MATRIX FACTORIZATION-
dc.subject.keywordPlusPRINCIPAL COMPONENT ANALYSIS-
dc.subject.keywordPlusNONPOINT-SOURCE POLLUTION-
dc.subject.keywordPlusSOURCE APPORTIONMENT-
dc.subject.keywordPlusAGRICULTURAL SOILS-
dc.subject.keywordPlusSTORMWATER RUNOFF-
dc.subject.keywordPlusHEAVY-METALS-
dc.subject.keywordPlusWASTE-WATER-
dc.subject.keywordPlusGROUNDWATER-
dc.subject.keywordPlusQUALITY-
dc.subject.keywordAuthorSource identification-
dc.subject.keywordAuthorOrdination analysis-
dc.subject.keywordAuthorRunoff-
dc.subject.keywordAuthorLand use-
dc.subject.keywordAuthorPrincipal component analysis-
dc.subject.keywordAuthorPositive matrix factorization-
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