Application of various cytotoxic endpoints for the toxicity prioritization of fine dust (PM2.5) sources using a multi-criteria decision-making approach
Fine dust (PM2.5) is generated from various sources, and many studies have reported on the sources of PM2.5. However, the current research on PM2.5 toxicity based on its sources is insufficient. In this study, we developed a framework for the prioritization of fine dust (PM2.5) sources on the basis...
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description | Fine dust (PM2.5) is generated from various sources, and many studies have reported on the sources of PM2.5. However, the current research on PM2.5 toxicity based on its sources is insufficient. In this study, we developed a framework for the prioritization of fine dust (PM2.5) sources on the basis of the multi-endpoint toxicities using the multi-criteria decision-making method (MCDM). To obtain the multi-endpoint toxicities of PM2.5 sources, cell mortality, reactive oxygen species (ROS), inflammation and mutagenicity were measured for diesel exhaust particles (DEP), gasoline exhaust particles (GEP), rice straw burning particles (RBP), coal combustion particles (CCP) and tunnel dust particles (TDP). The integrative toxicity score (ITS) of the PM2.5 source was calculated using MCDM, which consist of four steps: (1) defining the decision-making matrix, (2) normalization and weighting, (3) calculating the ITS (linear aggregation) and (4) a global sensitivity analysis. The indicator of cell mortality had the highest weight (0.3780) followed by inflammation (0.2471), ROS (0.2178) and mutagenicity (0.1571). Additionally, the ITS based on the sources contributing to PM2.5 resulted in the following order: DEP (0.89), GEP (0.44), RBP (0.40), CCP (0.23) and TDP (0.06). The relative toxicity index (RTI), which represents the ratio of toxicity due to the difference in sources, increases as the contribution of the highly toxic sources increases. The RTI over 1 is closely associated with an increased contribution from highly toxic sources, such as diesel exhaust, gasoline exhaust and biomass burning. It is necessary to investigate the toxicity of various PM2.5 sources and PM2.5 risk based on the sources. |
doi_str_mv | 10.1007/s10653-019-00469-2 |
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fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2423968425</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2423968425</sourcerecordid><originalsourceid>FETCH-LOGICAL-c418t-c250fa47f9db47ca4da2c50b1f793e297c96bc842a34ee1f605aea41daab74ab3</originalsourceid><addsrcrecordid>eNp9kctOAyEUhonRxHp5AVckbnRBBYaZKcum8ZZodKFrcoaBirbDCIyxvoivK7ZGd65OcvJ955IfoSNGx4zS-iwyWpUFoUwSSkUlCd9CI1bWBeFyUmyjEeW5Kajgu2gvxmdKqazFZIQ-p32_cBqS8x32Fr9BcH6IWK-ST_7daWy6tveuSxFbH3B6Mnjdd2mF-8wGl9zHr25dZ3A7xIRP7m_5uDzF0Q9Bm4iH6Lo5BrwcFskRnTUTHODWaBezTJbwsgb6PnjQTwdox8IimsOfuo8eL84fZlfk5u7yeja9IVqwSSKal9SCqK1sG1FrEC1wXdKG2VoWhstay6rRE8GhEMYwW9ESDAjWAjS1gKbYR8ebuXnt62BiUs_54C6vVFzwQlbZLTPFN5QOPsZgrMqvLyGsFKPqOwC1CUDlANQ6AMWzVGykmOFubsLf6H-sL7G2jNs</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2423968425</pqid></control><display><type>article</type><title>Application of various cytotoxic endpoints for the toxicity prioritization of fine dust (PM2.5) sources using a multi-criteria decision-making approach</title><source>SpringerLink Journals - AutoHoldings</source><creator>Kim, Injeong ; Park, Kihong ; Lee, KwangYul ; Park, Minhan ; Lim, Heungbin ; Shin, Hanjae ; Kim, Sang Don</creator><creatorcontrib>Kim, Injeong ; Park, Kihong ; Lee, KwangYul ; Park, Minhan ; Lim, Heungbin ; Shin, Hanjae ; Kim, Sang Don</creatorcontrib><description>Fine dust (PM2.5) is generated from various sources, and many studies have reported on the sources of PM2.5. However, the current research on PM2.5 toxicity based on its sources is insufficient. In this study, we developed a framework for the prioritization of fine dust (PM2.5) sources on the basis of the multi-endpoint toxicities using the multi-criteria decision-making method (MCDM). To obtain the multi-endpoint toxicities of PM2.5 sources, cell mortality, reactive oxygen species (ROS), inflammation and mutagenicity were measured for diesel exhaust particles (DEP), gasoline exhaust particles (GEP), rice straw burning particles (RBP), coal combustion particles (CCP) and tunnel dust particles (TDP). The integrative toxicity score (ITS) of the PM2.5 source was calculated using MCDM, which consist of four steps: (1) defining the decision-making matrix, (2) normalization and weighting, (3) calculating the ITS (linear aggregation) and (4) a global sensitivity analysis. The indicator of cell mortality had the highest weight (0.3780) followed by inflammation (0.2471), ROS (0.2178) and mutagenicity (0.1571). Additionally, the ITS based on the sources contributing to PM2.5 resulted in the following order: DEP (0.89), GEP (0.44), RBP (0.40), CCP (0.23) and TDP (0.06). The relative toxicity index (RTI), which represents the ratio of toxicity due to the difference in sources, increases as the contribution of the highly toxic sources increases. The RTI over 1 is closely associated with an increased contribution from highly toxic sources, such as diesel exhaust, gasoline exhaust and biomass burning. It is necessary to investigate the toxicity of various PM2.5 sources and PM2.5 risk based on the sources.</description><identifier>ISSN: 0269-4042</identifier><identifier>EISSN: 1573-2983</identifier><identifier>DOI: 10.1007/s10653-019-00469-2</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Aggregation ; Atmospheric particulates ; Biomass burning ; Burning ; Combustion ; Cytotoxicity ; Decision making ; Diesel ; Diesel engines ; Dust ; Dust storms ; Earth and Environmental Science ; Environment ; Environmental Chemistry ; Environmental Health ; Exhaust gases ; Gasoline ; Geochemistry ; Mathematical analysis ; Matrix methods ; Mortality ; Multiple criterion ; Mutagenicity ; Original Paper ; Particulate matter ; Public Health ; Reactive oxygen species ; Rice straw ; Sensitivity analysis ; Soil Science & Conservation ; Terrestrial Pollution ; Toxicity</subject><ispartof>Environmental geochemistry and health, 2020-06, Vol.42 (6), p.1775-1788</ispartof><rights>Springer Nature B.V. 2019</rights><rights>Springer Nature B.V. 2019.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c418t-c250fa47f9db47ca4da2c50b1f793e297c96bc842a34ee1f605aea41daab74ab3</citedby><cites>FETCH-LOGICAL-c418t-c250fa47f9db47ca4da2c50b1f793e297c96bc842a34ee1f605aea41daab74ab3</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/s10653-019-00469-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10653-019-00469-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27923,27924,41487,42556,51318</link.rule.ids></links><search><creatorcontrib>Kim, Injeong</creatorcontrib><creatorcontrib>Park, Kihong</creatorcontrib><creatorcontrib>Lee, KwangYul</creatorcontrib><creatorcontrib>Park, Minhan</creatorcontrib><creatorcontrib>Lim, Heungbin</creatorcontrib><creatorcontrib>Shin, Hanjae</creatorcontrib><creatorcontrib>Kim, Sang Don</creatorcontrib><title>Application of various cytotoxic endpoints for the toxicity prioritization of fine dust (PM2.5) sources using a multi-criteria decision-making approach</title><title>Environmental geochemistry and health</title><addtitle>Environ Geochem Health</addtitle><description>Fine dust (PM2.5) is generated from various sources, and many studies have reported on the sources of PM2.5. However, the current research on PM2.5 toxicity based on its sources is insufficient. In this study, we developed a framework for the prioritization of fine dust (PM2.5) sources on the basis of the multi-endpoint toxicities using the multi-criteria decision-making method (MCDM). To obtain the multi-endpoint toxicities of PM2.5 sources, cell mortality, reactive oxygen species (ROS), inflammation and mutagenicity were measured for diesel exhaust particles (DEP), gasoline exhaust particles (GEP), rice straw burning particles (RBP), coal combustion particles (CCP) and tunnel dust particles (TDP). The integrative toxicity score (ITS) of the PM2.5 source was calculated using MCDM, which consist of four steps: (1) defining the decision-making matrix, (2) normalization and weighting, (3) calculating the ITS (linear aggregation) and (4) a global sensitivity analysis. The indicator of cell mortality had the highest weight (0.3780) followed by inflammation (0.2471), ROS (0.2178) and mutagenicity (0.1571). Additionally, the ITS based on the sources contributing to PM2.5 resulted in the following order: DEP (0.89), GEP (0.44), RBP (0.40), CCP (0.23) and TDP (0.06). The relative toxicity index (RTI), which represents the ratio of toxicity due to the difference in sources, increases as the contribution of the highly toxic sources increases. The RTI over 1 is closely associated with an increased contribution from highly toxic sources, such as diesel exhaust, gasoline exhaust and biomass burning. It is necessary to investigate the toxicity of various PM2.5 sources and PM2.5 risk based on the sources.</description><subject>Aggregation</subject><subject>Atmospheric particulates</subject><subject>Biomass burning</subject><subject>Burning</subject><subject>Combustion</subject><subject>Cytotoxicity</subject><subject>Decision making</subject><subject>Diesel</subject><subject>Diesel engines</subject><subject>Dust</subject><subject>Dust storms</subject><subject>Earth and Environmental Science</subject><subject>Environment</subject><subject>Environmental Chemistry</subject><subject>Environmental Health</subject><subject>Exhaust gases</subject><subject>Gasoline</subject><subject>Geochemistry</subject><subject>Mathematical analysis</subject><subject>Matrix methods</subject><subject>Mortality</subject><subject>Multiple criterion</subject><subject>Mutagenicity</subject><subject>Original Paper</subject><subject>Particulate matter</subject><subject>Public Health</subject><subject>Reactive oxygen species</subject><subject>Rice straw</subject><subject>Sensitivity analysis</subject><subject>Soil Science & Conservation</subject><subject>Terrestrial 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prioritization of fine dust (PM2.5) sources using a multi-criteria decision-making approach</title><author>Kim, Injeong ; Park, Kihong ; Lee, KwangYul ; Park, Minhan ; Lim, Heungbin ; Shin, Hanjae ; Kim, Sang Don</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c418t-c250fa47f9db47ca4da2c50b1f793e297c96bc842a34ee1f605aea41daab74ab3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Aggregation</topic><topic>Atmospheric particulates</topic><topic>Biomass burning</topic><topic>Burning</topic><topic>Combustion</topic><topic>Cytotoxicity</topic><topic>Decision making</topic><topic>Diesel</topic><topic>Diesel engines</topic><topic>Dust</topic><topic>Dust storms</topic><topic>Earth and Environmental Science</topic><topic>Environment</topic><topic>Environmental Chemistry</topic><topic>Environmental Health</topic><topic>Exhaust gases</topic><topic>Gasoline</topic><topic>Geochemistry</topic><topic>Mathematical analysis</topic><topic>Matrix methods</topic><topic>Mortality</topic><topic>Multiple criterion</topic><topic>Mutagenicity</topic><topic>Original Paper</topic><topic>Particulate matter</topic><topic>Public Health</topic><topic>Reactive oxygen species</topic><topic>Rice straw</topic><topic>Sensitivity analysis</topic><topic>Soil Science & Conservation</topic><topic>Terrestrial Pollution</topic><topic>Toxicity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kim, Injeong</creatorcontrib><creatorcontrib>Park, Kihong</creatorcontrib><creatorcontrib>Lee, KwangYul</creatorcontrib><creatorcontrib>Park, Minhan</creatorcontrib><creatorcontrib>Lim, Heungbin</creatorcontrib><creatorcontrib>Shin, Hanjae</creatorcontrib><creatorcontrib>Kim, Sang Don</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Environment 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decision-making approach</atitle><jtitle>Environmental geochemistry and health</jtitle><stitle>Environ Geochem Health</stitle><date>2020-06-01</date><risdate>2020</risdate><volume>42</volume><issue>6</issue><spage>1775</spage><epage>1788</epage><pages>1775-1788</pages><issn>0269-4042</issn><eissn>1573-2983</eissn><abstract>Fine dust (PM2.5) is generated from various sources, and many studies have reported on the sources of PM2.5. However, the current research on PM2.5 toxicity based on its sources is insufficient. In this study, we developed a framework for the prioritization of fine dust (PM2.5) sources on the basis of the multi-endpoint toxicities using the multi-criteria decision-making method (MCDM). To obtain the multi-endpoint toxicities of PM2.5 sources, cell mortality, reactive oxygen species (ROS), inflammation and mutagenicity were measured for diesel exhaust particles (DEP), gasoline exhaust particles (GEP), rice straw burning particles (RBP), coal combustion particles (CCP) and tunnel dust particles (TDP). The integrative toxicity score (ITS) of the PM2.5 source was calculated using MCDM, which consist of four steps: (1) defining the decision-making matrix, (2) normalization and weighting, (3) calculating the ITS (linear aggregation) and (4) a global sensitivity analysis. The indicator of cell mortality had the highest weight (0.3780) followed by inflammation (0.2471), ROS (0.2178) and mutagenicity (0.1571). Additionally, the ITS based on the sources contributing to PM2.5 resulted in the following order: DEP (0.89), GEP (0.44), RBP (0.40), CCP (0.23) and TDP (0.06). The relative toxicity index (RTI), which represents the ratio of toxicity due to the difference in sources, increases as the contribution of the highly toxic sources increases. The RTI over 1 is closely associated with an increased contribution from highly toxic sources, such as diesel exhaust, gasoline exhaust and biomass burning. It is necessary to investigate the toxicity of various PM2.5 sources and PM2.5 risk based on the sources.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10653-019-00469-2</doi><tpages>14</tpages></addata></record> |
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subjects | Aggregation Atmospheric particulates Biomass burning Burning Combustion Cytotoxicity Decision making Diesel Diesel engines Dust Dust storms Earth and Environmental Science Environment Environmental Chemistry Environmental Health Exhaust gases Gasoline Geochemistry Mathematical analysis Matrix methods Mortality Multiple criterion Mutagenicity Original Paper Particulate matter Public Health Reactive oxygen species Rice straw Sensitivity analysis Soil Science & Conservation Terrestrial Pollution Toxicity |
title | Application of various cytotoxic endpoints for the toxicity prioritization of fine dust (PM2.5) sources using a multi-criteria decision-making approach |
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