Literature DB >> 26850099

Characterization and source identification of pollutants in runoff from a mixed land use watershed using ordination analyses.

Dong Hoon Lee1, Jin Hwi Kim1, Joseph A Mendoza1, Chang Hee Lee2, Joo-Hyon Kang3.   

Abstract

While 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.

Entities:  

Keywords:  Land use; Ordination analysis; Positive matrix factorization; Principal component analysis; Runoff; Source identification

Mesh:

Substances:

Year:  2016        PMID: 26850099     DOI: 10.1007/s11356-016-6155-x

Source DB:  PubMed          Journal:  Environ Sci Pollut Res Int        ISSN: 0944-1344            Impact factor:   4.223


  20 in total

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Authors:  Terry B Councell; Kea U Duckenfield; Edward R Landa; Edward Callender
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3.  Source apportionment of polychlorinated biphenyls in the New York/New Jersey Harbor.

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Authors:  S S Huang; Q L Liao; M Hua; X M Wu; K S Bi; C Y Yan; B Chen; X Y Zhang
Journal:  Chemosphere       Date:  2007-02-02       Impact factor: 7.086

Review 5.  Receptor modeling of ambient particulate matter data using positive matrix factorization: review of existing methods.

Authors:  Adam Reff; Shelly I Eberly; Prakash V Bhave
Journal:  J Air Waste Manag Assoc       Date:  2007-02       Impact factor: 2.235

6.  Nonpoint source pollution of urban stormwater runoff: a methodology for source analysis.

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Journal:  Environ Sci Pollut Res Int       Date:  2014-04-24       Impact factor: 4.223

Review 7.  The potential for a suite of isotope and chemical markers to differentiate sources of nitrate contamination: a review.

Authors:  C Fenech; L Rock; K Nolan; J Tobin; A Morrissey
Journal:  Water Res       Date:  2012-02-09       Impact factor: 11.236

Review 8.  Cobalt.

Authors:  D G Barceloux
Journal:  J Toxicol Clin Toxicol       Date:  1999

9.  Source apportionment of heavy metals and ionic contaminants in rainwater tanks in a subtropical urban area in Australia.

Authors:  R Huston; Y C Chan; H Chapman; T Gardner; G Shaw
Journal:  Water Res       Date:  2011-12-13       Impact factor: 11.236

10.  Characterization and source identification of stormwater runoff in tropical urban catchments.

Authors:  M F Chow; Z Yusop
Journal:  Water Sci Technol       Date:  2014       Impact factor: 1.915

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  2 in total

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2.  A geostatistical approach to estimating source apportionment in urban and peri-urban soils using the Czech Republic as an example.

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Journal:  Sci Rep       Date:  2021-12-08       Impact factor: 4.379

  2 in total

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