Optimal tracer identification for dissolved organic matter (DOM) source tracking in watersheds using point source effluent load data
In this study, we characterized the optical and molecular weight (MW) properties of dissolved organic matter (DOM) with various sources in an agriculture-forestry watershed. We proposed a guideline to identify optimum DOM source tracers for downstream rivers during both rain and non-rain events, uti...
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Veröffentlicht in: | Environmental technology & innovation 2023-11, Vol.32, p.103423, Article 103423 |
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description | In this study, we characterized the optical and molecular weight (MW) properties of dissolved organic matter (DOM) with various sources in an agriculture-forestry watershed. We proposed a guideline to identify optimum DOM source tracers for downstream rivers during both rain and non-rain events, utilizing the load of dissolved organic carbon (DOC) from point sources. Six descriptors were pre-selected based on established criteria in the literature, and fifteen pairs of these descriptors were evaluated for their applicability in end-member mixing analysis (EMMA). The results from EMMA provided inconsistent estimates of relative contributions from DOM sources across the fifteen pairs, with optical descriptors outperforming MW-based descriptors and their combinations. The optimal source tracers were determined by comparing relative contributions of DOM from upstream effluent wastewater using DOC load ratios calculated from on-site monitoring data and predictions based on EMMA. The pair of optical descriptors, HIX (humification index) and BIX (biological index), closely matched the measured load ratios with minimal discrepancies (0.4 ± 0.4 %). According to the EMMA results using pairs of HIX and BIX, non-rain events were primarily influenced by oil-cake fertilizer and treated effluent wastewater, while rain event samples were dominated by manure and soils. These findings offer insights into managing non-point organic pollution sources in agricultural-forestry watersheds, contributing to our understanding of carbon and nutrient cycling in aquatic systems. Notably, this study proposes a validation guideline that employs load ratios of point sources, such as effluent wastewater, to enhance source tracking accuracy.
[Display omitted]
•Optical and MW descriptors used for source tracking during non-rain and rain events.•Point source DOC load data improves identification of optimal DOM tracer pair.•Optical descriptors outperformed MW-based descriptors in tracking DOM sources.•Identified primary sources in downstream stream during non-rain and rain events•Proposed validation guideline enhances accuracy of source tracking. |
doi_str_mv | 10.1016/j.eti.2023.103423 |
format | Article |
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[Display omitted]
•Optical and MW descriptors used for source tracking during non-rain and rain events.•Point source DOC load data improves identification of optimal DOM tracer pair.•Optical descriptors outperformed MW-based descriptors in tracking DOM sources.•Identified primary sources in downstream stream during non-rain and rain events•Proposed validation guideline enhances accuracy of source tracking.</description><identifier>ISSN: 2352-1864</identifier><identifier>EISSN: 2352-1864</identifier><identifier>DOI: 10.1016/j.eti.2023.103423</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>dissolved organic carbon ; Dissolved organic matter ; End-member mixing analysis ; environmental technology ; fertilizers ; Fluorescence ; guidelines ; humification ; molecular weight ; Non-point sources ; pollution ; rain ; Size exclusion chromatography ; Source tracking ; wastewater ; watersheds</subject><ispartof>Environmental technology & innovation, 2023-11, Vol.32, p.103423, Article 103423</ispartof><rights>2023 The Authors</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c325t-73e07014f07a04d25f474f3217e9ff77a09f6375f0d536bae378f7a4078435e73</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,860,27901,27902</link.rule.ids></links><search><creatorcontrib>Oh, Haeseong</creatorcontrib><creatorcontrib>Jung, Ka-Young</creatorcontrib><creatorcontrib>Kim, Bo Young</creatorcontrib><creatorcontrib>Lee, Byung Joon</creatorcontrib><creatorcontrib>Shin, Hyun-Sang</creatorcontrib><creatorcontrib>Hur, Jin</creatorcontrib><title>Optimal tracer identification for dissolved organic matter (DOM) source tracking in watersheds using point source effluent load data</title><title>Environmental technology & innovation</title><description>In this study, we characterized the optical and molecular weight (MW) properties of dissolved organic matter (DOM) with various sources in an agriculture-forestry watershed. We proposed a guideline to identify optimum DOM source tracers for downstream rivers during both rain and non-rain events, utilizing the load of dissolved organic carbon (DOC) from point sources. Six descriptors were pre-selected based on established criteria in the literature, and fifteen pairs of these descriptors were evaluated for their applicability in end-member mixing analysis (EMMA). The results from EMMA provided inconsistent estimates of relative contributions from DOM sources across the fifteen pairs, with optical descriptors outperforming MW-based descriptors and their combinations. The optimal source tracers were determined by comparing relative contributions of DOM from upstream effluent wastewater using DOC load ratios calculated from on-site monitoring data and predictions based on EMMA. The pair of optical descriptors, HIX (humification index) and BIX (biological index), closely matched the measured load ratios with minimal discrepancies (0.4 ± 0.4 %). According to the EMMA results using pairs of HIX and BIX, non-rain events were primarily influenced by oil-cake fertilizer and treated effluent wastewater, while rain event samples were dominated by manure and soils. These findings offer insights into managing non-point organic pollution sources in agricultural-forestry watersheds, contributing to our understanding of carbon and nutrient cycling in aquatic systems. Notably, this study proposes a validation guideline that employs load ratios of point sources, such as effluent wastewater, to enhance source tracking accuracy.
[Display omitted]
•Optical and MW descriptors used for source tracking during non-rain and rain events.•Point source DOC load data improves identification of optimal DOM tracer pair.•Optical descriptors outperformed MW-based descriptors in tracking DOM sources.•Identified primary sources in downstream stream during non-rain and rain events•Proposed validation guideline enhances accuracy of source tracking.</description><subject>dissolved organic carbon</subject><subject>Dissolved organic matter</subject><subject>End-member mixing analysis</subject><subject>environmental technology</subject><subject>fertilizers</subject><subject>Fluorescence</subject><subject>guidelines</subject><subject>humification</subject><subject>molecular weight</subject><subject>Non-point sources</subject><subject>pollution</subject><subject>rain</subject><subject>Size exclusion chromatography</subject><subject>Source tracking</subject><subject>wastewater</subject><subject>watersheds</subject><issn>2352-1864</issn><issn>2352-1864</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kE1PAyEQhjdGE5vaH-CNYz1shQWWbTyZ-pnU9KJngjBU6napwNZ494dLrSaePAHD885knqI4JXhCMKnPVxNIblLhiuY3ZRU9KAYV5VVJmpod_rkfF6MYVxhnkvCa14Pic7FJbq1alILSEJAz0CVnnVbJ-Q5ZH5BxMfp2Cwb5sFSd02itUsrs-GrxcIai74OG7_yr65bIdehd5e_4AiaiPu5qG--69EuCtW2fp6DWK4OMSuqkOLKqjTD6OYfF08314-yunC9u72eX81LTiqdSUMACE2axUJiZilsmmKUVETC1VuTi1NZUcIsNp_WzAioaKxTDomGUg6DDYrzvuwn-rYeY5NpFDW2rOvB9lBQzTDmdNk1GyR7VwccYwMpNyJ7ChyRY7qTLlczS5U663EvPmYt9BvIOWwdBRu2g02BcAJ2k8e6f9Bfse4rp</recordid><startdate>202311</startdate><enddate>202311</enddate><creator>Oh, Haeseong</creator><creator>Jung, Ka-Young</creator><creator>Kim, Bo Young</creator><creator>Lee, Byung Joon</creator><creator>Shin, Hyun-Sang</creator><creator>Hur, Jin</creator><general>Elsevier B.V</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7S9</scope><scope>L.6</scope></search><sort><creationdate>202311</creationdate><title>Optimal tracer identification for dissolved organic matter (DOM) source tracking in watersheds using point source effluent load data</title><author>Oh, Haeseong ; Jung, Ka-Young ; Kim, Bo Young ; Lee, Byung Joon ; Shin, Hyun-Sang ; Hur, Jin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c325t-73e07014f07a04d25f474f3217e9ff77a09f6375f0d536bae378f7a4078435e73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>dissolved organic carbon</topic><topic>Dissolved organic matter</topic><topic>End-member mixing analysis</topic><topic>environmental technology</topic><topic>fertilizers</topic><topic>Fluorescence</topic><topic>guidelines</topic><topic>humification</topic><topic>molecular weight</topic><topic>Non-point sources</topic><topic>pollution</topic><topic>rain</topic><topic>Size exclusion chromatography</topic><topic>Source tracking</topic><topic>wastewater</topic><topic>watersheds</topic><toplevel>online_resources</toplevel><creatorcontrib>Oh, Haeseong</creatorcontrib><creatorcontrib>Jung, Ka-Young</creatorcontrib><creatorcontrib>Kim, Bo Young</creatorcontrib><creatorcontrib>Lee, Byung Joon</creatorcontrib><creatorcontrib>Shin, Hyun-Sang</creatorcontrib><creatorcontrib>Hur, Jin</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>AGRICOLA</collection><collection>AGRICOLA - Academic</collection><jtitle>Environmental technology & innovation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Oh, Haeseong</au><au>Jung, Ka-Young</au><au>Kim, Bo Young</au><au>Lee, Byung Joon</au><au>Shin, Hyun-Sang</au><au>Hur, Jin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Optimal tracer identification for dissolved organic matter (DOM) source tracking in watersheds using point source effluent load data</atitle><jtitle>Environmental technology & innovation</jtitle><date>2023-11</date><risdate>2023</risdate><volume>32</volume><spage>103423</spage><pages>103423-</pages><artnum>103423</artnum><issn>2352-1864</issn><eissn>2352-1864</eissn><abstract>In this study, we characterized the optical and molecular weight (MW) properties of dissolved organic matter (DOM) with various sources in an agriculture-forestry watershed. We proposed a guideline to identify optimum DOM source tracers for downstream rivers during both rain and non-rain events, utilizing the load of dissolved organic carbon (DOC) from point sources. Six descriptors were pre-selected based on established criteria in the literature, and fifteen pairs of these descriptors were evaluated for their applicability in end-member mixing analysis (EMMA). The results from EMMA provided inconsistent estimates of relative contributions from DOM sources across the fifteen pairs, with optical descriptors outperforming MW-based descriptors and their combinations. The optimal source tracers were determined by comparing relative contributions of DOM from upstream effluent wastewater using DOC load ratios calculated from on-site monitoring data and predictions based on EMMA. The pair of optical descriptors, HIX (humification index) and BIX (biological index), closely matched the measured load ratios with minimal discrepancies (0.4 ± 0.4 %). According to the EMMA results using pairs of HIX and BIX, non-rain events were primarily influenced by oil-cake fertilizer and treated effluent wastewater, while rain event samples were dominated by manure and soils. These findings offer insights into managing non-point organic pollution sources in agricultural-forestry watersheds, contributing to our understanding of carbon and nutrient cycling in aquatic systems. Notably, this study proposes a validation guideline that employs load ratios of point sources, such as effluent wastewater, to enhance source tracking accuracy.
[Display omitted]
•Optical and MW descriptors used for source tracking during non-rain and rain events.•Point source DOC load data improves identification of optimal DOM tracer pair.•Optical descriptors outperformed MW-based descriptors in tracking DOM sources.•Identified primary sources in downstream stream during non-rain and rain events•Proposed validation guideline enhances accuracy of source tracking.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.eti.2023.103423</doi><oa>free_for_read</oa></addata></record> |
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subjects | dissolved organic carbon Dissolved organic matter End-member mixing analysis environmental technology fertilizers Fluorescence guidelines humification molecular weight Non-point sources pollution rain Size exclusion chromatography Source tracking wastewater watersheds |
title | Optimal tracer identification for dissolved organic matter (DOM) source tracking in watersheds using point source effluent load data |
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