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Ranking surface soil pollution potential of chemicals from accidental release by using two indicators calculated with a multimedia model (SoilPCA)

DC Field Value Language
dc.contributor.authorKim, Ki-Eun-
dc.contributor.authorJung, Ja Eun-
dc.contributor.authorLee, Yunah-
dc.contributor.authorLee, Dong Soo-
dc.creator이동수-
dc.date.accessioned2019-04-25T02:09:40Z-
dc.date.available2020-04-05T02:09:40Z-
dc.date.created2018-12-11-
dc.date.created2018-12-11-
dc.date.issued2018-02-
dc.identifier.citationEcological Indicators, Vol.85, pp.664-673-
dc.identifier.issn1470-160X-
dc.identifier.urihttps://hdl.handle.net/10371/150424-
dc.description.abstractAttention should be paid to potential impacts on the soil quality of chemicals initially released into air from accidents as soil pollution by atmospheric deposition can threaten the health of human and ecosystems. The present work aimed to develop and calculate indicators that can be used to score the individual chemicals' surface soil pollution potential which signifies a measure of external exposure incurred from the surface soil pollution. The average concentration over time and space and the characteristic length of polluted area were derived as the two indicators to represent the level and spatial extent of pollution, respectively. The two indicators can commonly be applied to human and ecosystem. A new dynamic multimedia mass balance model, SoilPCA, was developed to quantify the indicators under the standard environmental conditions of South Korea. The final score for the surface soil pollution potential was calculated by taking the logarithm of the product of the two indicator values. The score was calculated for a total of 150 organic chemicals of three groups (i.e., 50 hydrophobic semivolatile organic compounds (SVOCs), 50 non-hydrophobic SVOCs, and 50 volatile organic compounds (VOCs)). The score was found to be dictated essentially by the maximum level of pollution in surface soil that is reached no later than 4 h after a release stops. This indicates that the rank of the chemicals of the surface soil pollution potential is determined principally during this early period and hardly changes afterward in spite of wide differences in the environmental fate properties among the chemicals. The organic-air partition coefficient divided by Henry's law constant (K-oa/K-H) is a useful predictor of the surface soil pollution potential of chemicals for each of the chemical groups, showing a positive relationship with the final score. Contrary to the expectation that hydrophobicity would govern the surface soil pollution potential, the non-hydrophobic SVOCs generally tend to show greater surface soil potential than the hydrophobic SVOCs given K-oa/K-H. This tendency is reinforced if no rain is assumed. The VOCs are largely of the lowest pollution potential as expected.-
dc.language영어-
dc.language.isoenen
dc.publisherElsevier BV-
dc.titleRanking surface soil pollution potential of chemicals from accidental release by using two indicators calculated with a multimedia model (SoilPCA)-
dc.typeArticle-
dc.identifier.doi10.1016/j.ecolind.2017.11.010-
dc.citation.journaltitleEcological Indicators-
dc.identifier.wosid000430634500069-
dc.identifier.scopusid2-s2.0-85034455944-
dc.description.srndOAIID:RECH_ACHV_DSTSH_NO:T201829795-
dc.description.srndRECH_ACHV_FG:RR00200001-
dc.description.srndADJUST_YN:-
dc.description.srndEMP_ID:A003201-
dc.description.srndCITE_RATE:3.983-
dc.description.srndDEPT_NM:환경계획학과-
dc.description.srndEMAIL:leeds@snu.ac.kr-
dc.description.srndSCOPUS_YN:Y-
dc.citation.endpage673-
dc.citation.startpage664-
dc.citation.volume85-
dc.description.isOpenAccessN-
dc.contributor.affiliatedAuthorLee, Dong Soo-
dc.identifier.srndT201829795-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.subject.keywordPlusEUROPEAN-UNION SYSTEM-
dc.subject.keywordPlusDISPERSION MODELS-
dc.subject.keywordPlusFATE-
dc.subject.keywordPlusSUBSTANCES-
dc.subject.keywordAuthorAccidental chemical release-
dc.subject.keywordAuthorSurface soil pollution potential-
dc.subject.keywordAuthorMultimedia model-
dc.subject.keywordAuthorPollution indicators-
dc.subject.keywordAuthorChemical ranking-
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