Quantitative structure–activity relationships (QSARs) for the transformation of organic micropollutants during oxidative water treatment
Various oxidants such as chlorine, chlorine dioxide, ferrateVI, ozone, and hydroxyl radicals can be applied for eliminating organic micropollutant by oxidative transformation during water treatment in systems such as drinking water, wastewater, and water reuse. Over the last decades, many second-ord...
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description | Various oxidants such as chlorine, chlorine dioxide, ferrateVI, ozone, and hydroxyl radicals can be applied for eliminating organic micropollutant by oxidative transformation during water treatment in systems such as drinking water, wastewater, and water reuse. Over the last decades, many second-order rate constants (k) have been determined for the reaction of these oxidants with model compounds and micropollutants. Good correlations (quantitative structure–activity relationships or QSARs) are often found between the k-values for an oxidation reaction of closely related compounds (i.e. having a common organic functional group) and substituent descriptor variables such as Hammett or Taft sigma constants. In this study, we developed QSARs for the oxidation of organic and some inorganic compounds and organic micropollutants transformation during oxidative water treatment. A number of 18 QSARs were developed based on overall 412 k-values for the reaction of chlorine, chlorine dioxide, ferrate, and ozone with organic compounds containing electron-rich moieties such as phenols, anilines, olefins, and amines. On average, 303 out of 412 (74%) k-values were predicted by these QSARs within a factor of 1/3–3 compared to the measured values. For HO reactions, some principles and estimation methods of k-values (e.g. the Group Contribution Method) are discussed. The developed QSARs and the Group Contribution Method could be used to predict the k-values for various emerging organic micropollutants. As a demonstration, 39 out of 45 (87%) predicted k-values were found within a factor 1/3–3 compared to the measured values for the selected emerging micropollutants. Finally, it is discussed how the uncertainty in the predicted k-values using the QSARs affects the accuracy of prediction for micropollutant elimination during oxidative water treatment.
[Display omitted]
► We develop 18 QSARs for reaction of water treatment oxidants with organic compounds. ► Tested oxidants for QSARs include chlorine, chlorine dioxide, ferrate and ozone. ► The developed QSARs predict accurately the k-values for organic micropollutants. ► Predicted k-values are useful to assess the transformation efficiency of micropollutants. |
doi_str_mv | 10.1016/j.watres.2012.06.006 |
format | Article |
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[Display omitted]
► We develop 18 QSARs for reaction of water treatment oxidants with organic compounds. ► Tested oxidants for QSARs include chlorine, chlorine dioxide, ferrate and ozone. ► The developed QSARs predict accurately the k-values for organic micropollutants. ► Predicted k-values are useful to assess the transformation efficiency of micropollutants.</description><identifier>ISSN: 0043-1354</identifier><identifier>EISSN: 1879-2448</identifier><identifier>DOI: 10.1016/j.watres.2012.06.006</identifier><identifier>PMID: 22939392</identifier><identifier>CODEN: WATRAG</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Alkenes - chemistry ; amines ; Amines - chemistry ; Aniline Compounds - chemistry ; Applied sciences ; Benzene - chemistry ; Chlorine ; Chlorine Compounds - chemistry ; Chlorine dioxide ; Drinking water ; Exact sciences and technology ; Ferratevi ; hydroxyl radicals ; Iron - chemistry ; Kinetics ; Mathematical models ; Micropollutant ; Organic Chemicals - chemistry ; Oxidants ; Oxidants - chemistry ; Oxidation ; Oxidation-Reduction ; Oxides - chemistry ; Ozone ; Ozone - chemistry ; phenols ; Phenols - chemistry ; Pollution ; prediction ; QSAR ; Quantitative Structure-Activity Relationship ; quantitative structure-activity relationships ; Transformations ; Uncertainty ; Waste Disposal, Fluid - methods ; wastewater ; Water Pollutants, Chemical - chemistry ; Water Purification - methods ; water reuse ; Water treatment ; Water treatment and pollution</subject><ispartof>Water research (Oxford), 2012-12, Vol.46 (19), p.6177-6195</ispartof><rights>2012 Elsevier Ltd</rights><rights>2014 INIST-CNRS</rights><rights>Copyright © 2012 Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c594t-5114045ee03de1952ea8308bec9e60dad2a94b80b830ebc9b375bf499ff3b8b03</citedby><cites>FETCH-LOGICAL-c594t-5114045ee03de1952ea8308bec9e60dad2a94b80b830ebc9b375bf499ff3b8b03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.watres.2012.06.006$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3548,27923,27924,45994</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=26589467$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22939392$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lee, Yunho</creatorcontrib><creatorcontrib>von Gunten, Urs</creatorcontrib><title>Quantitative structure–activity relationships (QSARs) for the transformation of organic micropollutants during oxidative water treatment</title><title>Water research (Oxford)</title><addtitle>Water Res</addtitle><description>Various oxidants such as chlorine, chlorine dioxide, ferrateVI, ozone, and hydroxyl radicals can be applied for eliminating organic micropollutant by oxidative transformation during water treatment in systems such as drinking water, wastewater, and water reuse. Over the last decades, many second-order rate constants (k) have been determined for the reaction of these oxidants with model compounds and micropollutants. Good correlations (quantitative structure–activity relationships or QSARs) are often found between the k-values for an oxidation reaction of closely related compounds (i.e. having a common organic functional group) and substituent descriptor variables such as Hammett or Taft sigma constants. In this study, we developed QSARs for the oxidation of organic and some inorganic compounds and organic micropollutants transformation during oxidative water treatment. A number of 18 QSARs were developed based on overall 412 k-values for the reaction of chlorine, chlorine dioxide, ferrate, and ozone with organic compounds containing electron-rich moieties such as phenols, anilines, olefins, and amines. On average, 303 out of 412 (74%) k-values were predicted by these QSARs within a factor of 1/3–3 compared to the measured values. For HO reactions, some principles and estimation methods of k-values (e.g. the Group Contribution Method) are discussed. The developed QSARs and the Group Contribution Method could be used to predict the k-values for various emerging organic micropollutants. As a demonstration, 39 out of 45 (87%) predicted k-values were found within a factor 1/3–3 compared to the measured values for the selected emerging micropollutants. Finally, it is discussed how the uncertainty in the predicted k-values using the QSARs affects the accuracy of prediction for micropollutant elimination during oxidative water treatment.
[Display omitted]
► We develop 18 QSARs for reaction of water treatment oxidants with organic compounds. ► Tested oxidants for QSARs include chlorine, chlorine dioxide, ferrate and ozone. ► The developed QSARs predict accurately the k-values for organic micropollutants. ► Predicted k-values are useful to assess the transformation efficiency of micropollutants.</description><subject>Alkenes - chemistry</subject><subject>amines</subject><subject>Amines - chemistry</subject><subject>Aniline Compounds - chemistry</subject><subject>Applied sciences</subject><subject>Benzene - chemistry</subject><subject>Chlorine</subject><subject>Chlorine Compounds - chemistry</subject><subject>Chlorine dioxide</subject><subject>Drinking water</subject><subject>Exact sciences and technology</subject><subject>Ferratevi</subject><subject>hydroxyl radicals</subject><subject>Iron - chemistry</subject><subject>Kinetics</subject><subject>Mathematical models</subject><subject>Micropollutant</subject><subject>Organic Chemicals - chemistry</subject><subject>Oxidants</subject><subject>Oxidants - chemistry</subject><subject>Oxidation</subject><subject>Oxidation-Reduction</subject><subject>Oxides - chemistry</subject><subject>Ozone</subject><subject>Ozone - chemistry</subject><subject>phenols</subject><subject>Phenols - chemistry</subject><subject>Pollution</subject><subject>prediction</subject><subject>QSAR</subject><subject>Quantitative Structure-Activity Relationship</subject><subject>quantitative structure-activity relationships</subject><subject>Transformations</subject><subject>Uncertainty</subject><subject>Waste Disposal, Fluid - methods</subject><subject>wastewater</subject><subject>Water Pollutants, Chemical - chemistry</subject><subject>Water Purification - methods</subject><subject>water reuse</subject><subject>Water treatment</subject><subject>Water treatment and pollution</subject><issn>0043-1354</issn><issn>1879-2448</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkk1v1DAQhiMEotvCP0DgC1I5ZPFXsvalUlXxJVVCpfRsOc5k61USL7ZT6K1nrvxDfgmzZIEbIB9GHj8z72heF8UTRpeMsvrlZvnZ5ghpySnjS1ovKa3vFQumVrrkUqr7xYJSKUomKnlQHKa0oZRyLvTD4oBzLfDwRfH1YrJj9tlmfwMk5Ti5PEX4fvfNOkz5fEsi9PgaxnTtt4kcX1yefkgvSBciyddAcrRjwsvwkyGhIyGu7egdGbyLYRv6fsookUg7RT-uSfji21kN5wdsEsHmAcb8qHjQ2T7B4308Kq5ev_p49rY8f__m3dnpeekqLXNZMSaprACoaIHpioNVgqoGnIaatrblVstG0Qaz0DjdiFXVdFLrrhONaqg4Ko7nvtsYPk2Qshl8ctD3doQwJcPqChXqSsh_o2zFlBIY_gMVumYKF4-onFHcT0oROrONfrDx1jBqdt6ajZm9NTtvDa0NeotlT_cKUzNA-7vol5kIPN8DNjnbd-iM8-kPV1dKy3o36rOZ62wwdh2RubpEpQo_CNWc71Z0MhOAPtx4iCY5D6OD1kdw2bTB_33WHzeW0as</recordid><startdate>20121201</startdate><enddate>20121201</enddate><creator>Lee, Yunho</creator><creator>von Gunten, Urs</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>FBQ</scope><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7QH</scope><scope>7ST</scope><scope>7TV</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H97</scope><scope>L.G</scope><scope>SOI</scope><scope>7SU</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>20121201</creationdate><title>Quantitative structure–activity relationships (QSARs) for the transformation of organic micropollutants during oxidative water treatment</title><author>Lee, Yunho ; von Gunten, Urs</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c594t-5114045ee03de1952ea8308bec9e60dad2a94b80b830ebc9b375bf499ff3b8b03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Alkenes - chemistry</topic><topic>amines</topic><topic>Amines - chemistry</topic><topic>Aniline Compounds - chemistry</topic><topic>Applied sciences</topic><topic>Benzene - chemistry</topic><topic>Chlorine</topic><topic>Chlorine Compounds - chemistry</topic><topic>Chlorine dioxide</topic><topic>Drinking water</topic><topic>Exact sciences and technology</topic><topic>Ferratevi</topic><topic>hydroxyl radicals</topic><topic>Iron - chemistry</topic><topic>Kinetics</topic><topic>Mathematical models</topic><topic>Micropollutant</topic><topic>Organic Chemicals - chemistry</topic><topic>Oxidants</topic><topic>Oxidants - chemistry</topic><topic>Oxidation</topic><topic>Oxidation-Reduction</topic><topic>Oxides - chemistry</topic><topic>Ozone</topic><topic>Ozone - chemistry</topic><topic>phenols</topic><topic>Phenols - chemistry</topic><topic>Pollution</topic><topic>prediction</topic><topic>QSAR</topic><topic>Quantitative Structure-Activity Relationship</topic><topic>quantitative structure-activity relationships</topic><topic>Transformations</topic><topic>Uncertainty</topic><topic>Waste Disposal, Fluid - methods</topic><topic>wastewater</topic><topic>Water Pollutants, Chemical - chemistry</topic><topic>Water Purification - methods</topic><topic>water reuse</topic><topic>Water treatment</topic><topic>Water treatment and pollution</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lee, Yunho</creatorcontrib><creatorcontrib>von Gunten, Urs</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Pollution Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><collection>Environmental Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Water research (Oxford)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lee, Yunho</au><au>von Gunten, Urs</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantitative structure–activity relationships (QSARs) for the transformation of organic micropollutants during oxidative water treatment</atitle><jtitle>Water research (Oxford)</jtitle><addtitle>Water Res</addtitle><date>2012-12-01</date><risdate>2012</risdate><volume>46</volume><issue>19</issue><spage>6177</spage><epage>6195</epage><pages>6177-6195</pages><issn>0043-1354</issn><eissn>1879-2448</eissn><coden>WATRAG</coden><abstract>Various oxidants such as chlorine, chlorine dioxide, ferrateVI, ozone, and hydroxyl radicals can be applied for eliminating organic micropollutant by oxidative transformation during water treatment in systems such as drinking water, wastewater, and water reuse. Over the last decades, many second-order rate constants (k) have been determined for the reaction of these oxidants with model compounds and micropollutants. Good correlations (quantitative structure–activity relationships or QSARs) are often found between the k-values for an oxidation reaction of closely related compounds (i.e. having a common organic functional group) and substituent descriptor variables such as Hammett or Taft sigma constants. In this study, we developed QSARs for the oxidation of organic and some inorganic compounds and organic micropollutants transformation during oxidative water treatment. A number of 18 QSARs were developed based on overall 412 k-values for the reaction of chlorine, chlorine dioxide, ferrate, and ozone with organic compounds containing electron-rich moieties such as phenols, anilines, olefins, and amines. On average, 303 out of 412 (74%) k-values were predicted by these QSARs within a factor of 1/3–3 compared to the measured values. For HO reactions, some principles and estimation methods of k-values (e.g. the Group Contribution Method) are discussed. The developed QSARs and the Group Contribution Method could be used to predict the k-values for various emerging organic micropollutants. As a demonstration, 39 out of 45 (87%) predicted k-values were found within a factor 1/3–3 compared to the measured values for the selected emerging micropollutants. Finally, it is discussed how the uncertainty in the predicted k-values using the QSARs affects the accuracy of prediction for micropollutant elimination during oxidative water treatment.
[Display omitted]
► We develop 18 QSARs for reaction of water treatment oxidants with organic compounds. ► Tested oxidants for QSARs include chlorine, chlorine dioxide, ferrate and ozone. ► The developed QSARs predict accurately the k-values for organic micropollutants. ► Predicted k-values are useful to assess the transformation efficiency of micropollutants.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>22939392</pmid><doi>10.1016/j.watres.2012.06.006</doi><tpages>19</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Alkenes - chemistry amines Amines - chemistry Aniline Compounds - chemistry Applied sciences Benzene - chemistry Chlorine Chlorine Compounds - chemistry Chlorine dioxide Drinking water Exact sciences and technology Ferratevi hydroxyl radicals Iron - chemistry Kinetics Mathematical models Micropollutant Organic Chemicals - chemistry Oxidants Oxidants - chemistry Oxidation Oxidation-Reduction Oxides - chemistry Ozone Ozone - chemistry phenols Phenols - chemistry Pollution prediction QSAR Quantitative Structure-Activity Relationship quantitative structure-activity relationships Transformations Uncertainty Waste Disposal, Fluid - methods wastewater Water Pollutants, Chemical - chemistry Water Purification - methods water reuse Water treatment Water treatment and pollution |
title | Quantitative structure–activity relationships (QSARs) for the transformation of organic micropollutants during oxidative water treatment |
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