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dc.contributor.author김용표*
dc.contributor.author이지이*
dc.date.accessioned2019-05-03T16:30:06Z-
dc.date.available2019-05-03T16:30:06Z-
dc.date.issued2019*
dc.identifier.issn2076-3417*
dc.identifier.otherOAK-24705*
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/249717-
dc.description.abstractWe estimated source-based aerosol optical properties for polydisperse aerosols according to a chemical-species-resolved mass contribution method based on source apportionment. We investigated the sensitivity of aerosol optical properties based on PM2.5 (particulate matter that have a diameter of less than 2.5 micrometers) monitoring results. These aerosols were composed of ions, metals, elemental carbon, and water-soluble organic carbon which includes humic-like carbon substances and water-soluble organic carbon. We calculated aerosols' extinction coefficients based on the PM2.5 composition data and the results of a multivariate receptor model (Solver for Mixture Problem model, SMP). Based on the mass concentration of chemical composition and nine sources calculated with the SMP receptor model, we estimated the size-resolved mass extinction efficiencies for each aerosol source using a multilinear regression model. Consequently, this study quantitatively determined the size resolved sources contributing to the apportionment-based aerosol optical properties and calculated their respective contributions. The results show that source-resolved mass concentrations and extinction coefficients had varying contributions. This discrepancy between the source-based mass concentration and extinction coefficient was mainly due to differences between the source-dependent aerosol size distribution and the aerosol optical properties from different sources.*
dc.languageEnglish*
dc.publisherMDPI*
dc.subjectmass extinction efficiency*
dc.subjectSMP receptor model*
dc.subjectsize- and source-resolved aerosol optical properties*
dc.subjectpolydispersity*
dc.titleEstimation of Source-Based Aerosol Optical Properties for Polydisperse Aerosols from Receptor Models*
dc.typeArticle*
dc.relation.issue7*
dc.relation.volume9*
dc.relation.indexSCIE*
dc.relation.indexSCOPUS*
dc.relation.journaltitleAPPLIED SCIENCES-BASEL*
dc.identifier.doi10.3390/app9071443*
dc.identifier.wosidWOS:000466547500178*
dc.identifier.scopusid2-s2.0-85064079181*
dc.author.googleJung, Chang Hoon*
dc.author.googleLee, Ji Yi*
dc.author.googleUm, Junshik*
dc.author.googleLee, Seoung Soo*
dc.author.googleYoon, Young Jun*
dc.author.googleKim, Yong Pyo*
dc.contributor.scopusid김용표(8721787200)*
dc.contributor.scopusid이지이(27167796600)*
dc.date.modifydate20240415142127*


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