Development of a Local-Scale Spatially Refined Multimedia Fate Model (LSRMFM) for Urban-Scale Risk Assessment: Model Formulation, GIS-Based Preprocessing, and Case Study
A local-scale spatially refined multimedia fate model (LSRMFM) was developed to evaluate in detail the multimedia transport of organic compounds at a spatial level. The model was derived using a combination of an advection-dispersion-reaction partial differential equation, a steady-state multimedia...
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creator | Kim, Jong Ho Kwak, Byoung Kyu Shin, Chee Burm Jeon, Won Jin Park, Hyeon-Soo Lee, Sun Woo Choi, Kyunghee Lee, Woon Gi Lee, Jun Hee Baek, Sun Ho Yi, Jongheop |
description | A local-scale spatially refined multimedia fate model (LSRMFM) was developed to evaluate in detail the multimedia transport of organic compounds at a spatial level. The model was derived using a combination of an advection-dispersion-reaction partial differential equation, a steady-state multimedia fugacity model, and a geographical information system. The model was applied to predicting four major volatile organic compounds that are produced as emissions (benzene, toluene, xylene, and styrene) in an urban and industrial area (the 50 × 50-km area was divided into 0.5 × 0.5-km segments) in Korea. To test the accuracy of the model, the LSRMFM was used to predict the extent of dispersion and the data compared with actual measured concentrations and the results of a generic multimedia fate model (GMFM). The results indicated that the method developed herein is appropriate for predicting long-term multimedia pollution. However, the comparison study also illustrated that the developed model has some limitations (e.g., steady-state assumption) in terms of explaining all the observed concentrations, and additional verification and study (e.g., validation using a large observed data set, integration with a more accurate runoff model) would be desirable. In comparing LSRMFM and GMFM, discrepancies between the LSRMFM and GMFM outputs were found, as the result of geographical effects, even though the environmental parameters were identical. The geographical variation for LSRMFM output indicated the existence of considerable local human and ecological risks, whereas the GMFM output indicated less average risk. These results demonstrate that the model has the potential for improving the management of pollutant levels under these refined spatial conditions. |
doi_str_mv | 10.1007/s10666-011-9250-x |
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The model was derived using a combination of an advection-dispersion-reaction partial differential equation, a steady-state multimedia fugacity model, and a geographical information system. The model was applied to predicting four major volatile organic compounds that are produced as emissions (benzene, toluene, xylene, and styrene) in an urban and industrial area (the 50 × 50-km area was divided into 0.5 × 0.5-km segments) in Korea. To test the accuracy of the model, the LSRMFM was used to predict the extent of dispersion and the data compared with actual measured concentrations and the results of a generic multimedia fate model (GMFM). The results indicated that the method developed herein is appropriate for predicting long-term multimedia pollution. However, the comparison study also illustrated that the developed model has some limitations (e.g., steady-state assumption) in terms of explaining all the observed concentrations, and additional verification and study (e.g., validation using a large observed data set, integration with a more accurate runoff model) would be desirable. In comparing LSRMFM and GMFM, discrepancies between the LSRMFM and GMFM outputs were found, as the result of geographical effects, even though the environmental parameters were identical. The geographical variation for LSRMFM output indicated the existence of considerable local human and ecological risks, whereas the GMFM output indicated less average risk. These results demonstrate that the model has the potential for improving the management of pollutant levels under these refined spatial conditions.</description><identifier>ISSN: 1420-2026</identifier><identifier>EISSN: 1573-2967</identifier><identifier>DOI: 10.1007/s10666-011-9250-x</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Applications of Mathematics ; Assessments ; Benzene ; Carcinogens ; Case studies ; Chemical contaminants ; data collection ; Differential equations ; Earth and Environmental Science ; emissions ; Environment ; Environmental impact ; Environmental monitoring ; equations ; Finite volume method ; Fugacity ; Geographic information systems ; geographical variation ; humans ; Hydrocarbons ; hydrologic models ; Hydrology ; Industrial areas ; Math. Appl. in Environmental Science ; Mathematical Modeling and Industrial Mathematics ; Mathematical models ; Multimedia ; Operations Research/Decision Theory ; Organic compounds ; Partial differential equations ; Pollutants ; pollution ; Pollution levels ; prediction ; Risk ; Risk assessment ; Studies ; Styrene ; Styrenes ; Toluene ; Urban areas ; VOCs ; Volatile organic compounds ; Xylene</subject><ispartof>Environmental modeling & assessment, 2011-06, Vol.16 (3), p.265-281</ispartof><rights>Springer Science+Business Media B.V. 2011</rights><rights>COPYRIGHT 2011 Springer</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c443t-55723b1cd0dca36c953aea1a02ca0df553723b29ecfd6cc205acd3e94993b81c3</citedby><cites>FETCH-LOGICAL-c443t-55723b1cd0dca36c953aea1a02ca0df553723b29ecfd6cc205acd3e94993b81c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10666-011-9250-x$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10666-011-9250-x$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Kim, Jong Ho</creatorcontrib><creatorcontrib>Kwak, Byoung Kyu</creatorcontrib><creatorcontrib>Shin, Chee Burm</creatorcontrib><creatorcontrib>Jeon, Won Jin</creatorcontrib><creatorcontrib>Park, Hyeon-Soo</creatorcontrib><creatorcontrib>Lee, Sun Woo</creatorcontrib><creatorcontrib>Choi, Kyunghee</creatorcontrib><creatorcontrib>Lee, Woon Gi</creatorcontrib><creatorcontrib>Lee, Jun Hee</creatorcontrib><creatorcontrib>Baek, Sun Ho</creatorcontrib><creatorcontrib>Yi, Jongheop</creatorcontrib><title>Development of a Local-Scale Spatially Refined Multimedia Fate Model (LSRMFM) for Urban-Scale Risk Assessment: Model Formulation, GIS-Based Preprocessing, and Case Study</title><title>Environmental modeling & assessment</title><addtitle>Environ Model Assess</addtitle><description>A local-scale spatially refined multimedia fate model (LSRMFM) was developed to evaluate in detail the multimedia transport of organic compounds at a spatial level. The model was derived using a combination of an advection-dispersion-reaction partial differential equation, a steady-state multimedia fugacity model, and a geographical information system. The model was applied to predicting four major volatile organic compounds that are produced as emissions (benzene, toluene, xylene, and styrene) in an urban and industrial area (the 50 × 50-km area was divided into 0.5 × 0.5-km segments) in Korea. To test the accuracy of the model, the LSRMFM was used to predict the extent of dispersion and the data compared with actual measured concentrations and the results of a generic multimedia fate model (GMFM). The results indicated that the method developed herein is appropriate for predicting long-term multimedia pollution. However, the comparison study also illustrated that the developed model has some limitations (e.g., steady-state assumption) in terms of explaining all the observed concentrations, and additional verification and study (e.g., validation using a large observed data set, integration with a more accurate runoff model) would be desirable. In comparing LSRMFM and GMFM, discrepancies between the LSRMFM and GMFM outputs were found, as the result of geographical effects, even though the environmental parameters were identical. The geographical variation for LSRMFM output indicated the existence of considerable local human and ecological risks, whereas the GMFM output indicated less average risk. These results demonstrate that the model has the potential for improving the management of pollutant levels under these refined spatial conditions.</description><subject>Applications of Mathematics</subject><subject>Assessments</subject><subject>Benzene</subject><subject>Carcinogens</subject><subject>Case studies</subject><subject>Chemical contaminants</subject><subject>data collection</subject><subject>Differential equations</subject><subject>Earth and Environmental Science</subject><subject>emissions</subject><subject>Environment</subject><subject>Environmental impact</subject><subject>Environmental monitoring</subject><subject>equations</subject><subject>Finite volume method</subject><subject>Fugacity</subject><subject>Geographic information systems</subject><subject>geographical variation</subject><subject>humans</subject><subject>Hydrocarbons</subject><subject>hydrologic models</subject><subject>Hydrology</subject><subject>Industrial areas</subject><subject>Math. Appl. in Environmental Science</subject><subject>Mathematical Modeling and Industrial Mathematics</subject><subject>Mathematical models</subject><subject>Multimedia</subject><subject>Operations Research/Decision Theory</subject><subject>Organic compounds</subject><subject>Partial differential equations</subject><subject>Pollutants</subject><subject>pollution</subject><subject>Pollution levels</subject><subject>prediction</subject><subject>Risk</subject><subject>Risk assessment</subject><subject>Studies</subject><subject>Styrene</subject><subject>Styrenes</subject><subject>Toluene</subject><subject>Urban areas</subject><subject>VOCs</subject><subject>Volatile organic compounds</subject><subject>Xylene</subject><issn>1420-2026</issn><issn>1573-2967</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp9ksGO0zAQhiMEEsvCA3DC4sIibZaxHTsJt1LoslIrUEPPlus4lZfULnaCto_EWzJVKiFxWFmyLc_3_x6PJ8teU7ihAOWHREFKmQOlec0E5A9PsgsqSp6zWpZPcV8wyBkw-Tx7kdI9AOIgLrI_n-1v24fD3vqBhI5osgxG93mDkyXNQQ9O9_2RrG3nvG3JauwHt7et02ShB0tWobU9uVo269Vi9Z50IZJN3Gp_Nli79JPMUrIpnW74eOYXIe7HHr2Dvya3d03-SSc0_x7tIQaDsPO7a6J9S-YYIM0wtseX2bNO98m-Oq-X2Wbx5cf8a778dns3ny1zUxR8yIUoGd9S00JrNJemFlxbTTUwo6HthOCnOKut6VppDAOhTcttXdQ131bU8Mvs3eSLqfwabRrU3iVj-157G8akqrrGwgoOSF49SlJZUg5QVAzRt_-h92GMHt-hKimZ4KKsELqZoB2WTjnfhSFqg6O1e2eCxy_A8xma1mVFpUABnQQmhpSi7dQhur2OR0VBndpCTW2hsC3UqS3UA2rYpEnI-p2N_zJ5TPRmEnU6KL2LLqlNw4AWAFRIyhn_C9GAw4g</recordid><startdate>20110601</startdate><enddate>20110601</enddate><creator>Kim, Jong Ho</creator><creator>Kwak, Byoung Kyu</creator><creator>Shin, Chee Burm</creator><creator>Jeon, Won Jin</creator><creator>Park, Hyeon-Soo</creator><creator>Lee, Sun Woo</creator><creator>Choi, Kyunghee</creator><creator>Lee, Woon Gi</creator><creator>Lee, Jun Hee</creator><creator>Baek, Sun Ho</creator><creator>Yi, Jongheop</creator><general>Springer Netherlands</general><general>Springer</general><general>Springer Nature B.V</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>7SC</scope><scope>7ST</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88I</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>KR7</scope><scope>L.-</scope><scope>L.0</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>M2P</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope><scope>7SU</scope><scope>7TV</scope><scope>7U1</scope><scope>7U2</scope><scope>7U6</scope></search><sort><creationdate>20110601</creationdate><title>Development of a Local-Scale Spatially Refined Multimedia Fate Model (LSRMFM) for Urban-Scale Risk Assessment: Model Formulation, GIS-Based Preprocessing, and Case Study</title><author>Kim, Jong Ho ; Kwak, Byoung Kyu ; Shin, Chee Burm ; Jeon, Won Jin ; Park, Hyeon-Soo ; Lee, Sun Woo ; Choi, Kyunghee ; Lee, Woon Gi ; Lee, Jun Hee ; Baek, Sun Ho ; Yi, Jongheop</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c443t-55723b1cd0dca36c953aea1a02ca0df553723b29ecfd6cc205acd3e94993b81c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Applications of Mathematics</topic><topic>Assessments</topic><topic>Benzene</topic><topic>Carcinogens</topic><topic>Case studies</topic><topic>Chemical contaminants</topic><topic>data collection</topic><topic>Differential equations</topic><topic>Earth and Environmental Science</topic><topic>emissions</topic><topic>Environment</topic><topic>Environmental impact</topic><topic>Environmental monitoring</topic><topic>equations</topic><topic>Finite volume method</topic><topic>Fugacity</topic><topic>Geographic information systems</topic><topic>geographical variation</topic><topic>humans</topic><topic>Hydrocarbons</topic><topic>hydrologic models</topic><topic>Hydrology</topic><topic>Industrial areas</topic><topic>Math. Appl. in Environmental Science</topic><topic>Mathematical Modeling and Industrial Mathematics</topic><topic>Mathematical models</topic><topic>Multimedia</topic><topic>Operations Research/Decision Theory</topic><topic>Organic compounds</topic><topic>Partial differential equations</topic><topic>Pollutants</topic><topic>pollution</topic><topic>Pollution levels</topic><topic>prediction</topic><topic>Risk</topic><topic>Risk assessment</topic><topic>Studies</topic><topic>Styrene</topic><topic>Styrenes</topic><topic>Toluene</topic><topic>Urban areas</topic><topic>VOCs</topic><topic>Volatile organic compounds</topic><topic>Xylene</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Jong Ho</creatorcontrib><creatorcontrib>Kwak, Byoung Kyu</creatorcontrib><creatorcontrib>Shin, Chee Burm</creatorcontrib><creatorcontrib>Jeon, Won Jin</creatorcontrib><creatorcontrib>Park, Hyeon-Soo</creatorcontrib><creatorcontrib>Lee, Sun 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Risk</collection><collection>Sustainability Science Abstracts</collection><jtitle>Environmental modeling & assessment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kim, Jong Ho</au><au>Kwak, Byoung Kyu</au><au>Shin, Chee Burm</au><au>Jeon, Won Jin</au><au>Park, Hyeon-Soo</au><au>Lee, Sun Woo</au><au>Choi, Kyunghee</au><au>Lee, Woon Gi</au><au>Lee, Jun Hee</au><au>Baek, Sun Ho</au><au>Yi, Jongheop</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of a Local-Scale Spatially Refined Multimedia Fate Model (LSRMFM) for Urban-Scale Risk Assessment: Model Formulation, GIS-Based Preprocessing, and Case Study</atitle><jtitle>Environmental modeling & assessment</jtitle><stitle>Environ Model Assess</stitle><date>2011-06-01</date><risdate>2011</risdate><volume>16</volume><issue>3</issue><spage>265</spage><epage>281</epage><pages>265-281</pages><issn>1420-2026</issn><eissn>1573-2967</eissn><abstract>A local-scale spatially refined multimedia fate model (LSRMFM) was developed to evaluate in detail the multimedia transport of organic compounds at a spatial level. The model was derived using a combination of an advection-dispersion-reaction partial differential equation, a steady-state multimedia fugacity model, and a geographical information system. The model was applied to predicting four major volatile organic compounds that are produced as emissions (benzene, toluene, xylene, and styrene) in an urban and industrial area (the 50 × 50-km area was divided into 0.5 × 0.5-km segments) in Korea. To test the accuracy of the model, the LSRMFM was used to predict the extent of dispersion and the data compared with actual measured concentrations and the results of a generic multimedia fate model (GMFM). The results indicated that the method developed herein is appropriate for predicting long-term multimedia pollution. However, the comparison study also illustrated that the developed model has some limitations (e.g., steady-state assumption) in terms of explaining all the observed concentrations, and additional verification and study (e.g., validation using a large observed data set, integration with a more accurate runoff model) would be desirable. In comparing LSRMFM and GMFM, discrepancies between the LSRMFM and GMFM outputs were found, as the result of geographical effects, even though the environmental parameters were identical. The geographical variation for LSRMFM output indicated the existence of considerable local human and ecological risks, whereas the GMFM output indicated less average risk. These results demonstrate that the model has the potential for improving the management of pollutant levels under these refined spatial conditions.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10666-011-9250-x</doi><tpages>17</tpages></addata></record> |
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subjects | Applications of Mathematics Assessments Benzene Carcinogens Case studies Chemical contaminants data collection Differential equations Earth and Environmental Science emissions Environment Environmental impact Environmental monitoring equations Finite volume method Fugacity Geographic information systems geographical variation humans Hydrocarbons hydrologic models Hydrology Industrial areas Math. Appl. in Environmental Science Mathematical Modeling and Industrial Mathematics Mathematical models Multimedia Operations Research/Decision Theory Organic compounds Partial differential equations Pollutants pollution Pollution levels prediction Risk Risk assessment Studies Styrene Styrenes Toluene Urban areas VOCs Volatile organic compounds Xylene |
title | Development of a Local-Scale Spatially Refined Multimedia Fate Model (LSRMFM) for Urban-Scale Risk Assessment: Model Formulation, GIS-Based Preprocessing, and Case Study |
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