Organic Micropollutants Removal from Water by Oxidation and Other Processes:QSAR Models, Decision Support System and Hybrids of Processes

Handle URI:
http://hdl.handle.net/10754/303061
Title:
Organic Micropollutants Removal from Water by Oxidation and Other Processes:QSAR Models, Decision Support System and Hybrids of Processes
Authors:
Sudhakaran, Sairam
Abstract:
The presence of organic micropollutants (OMPs) in water is of great environmental concern. OMPs such as endocrine disruptors and certain pharmaceuticals have shown alarming effects on aquatic life. OMPs are included in the priority list of contaminants in several government directorate frameworks. The low levels of OMPs concentration (ng/L to μg/L) force the use of sophisticated analytical instruments. Although, the techniques to detect OMPs are progressing, the focus of current research is only on limited, important OMPs due to the high amount of time, cost and effort involved in analyzing them. Alternatively, quantitative structure activity relationship (QSAR) models help to screen processes and propose appropriate options without considerable experimental effort. QSAR models are well-established in regulatory bodies as a method to screen toxic chemicals. The goal of the present thesis was to develop QSAR models for OMPs removal by oxidation. Apart from the QSAR models, a decision support system (DSS) based on multi-criteria analysis (MCA) involving socio-economic-technical and sustainability aspects was developed. Also, hybrids of different water treatment processes were studied to propose a sustainable water treatment train for OMPs removal. In order to build the QSAR models, the ozone/hydroxyl radical rate constants or percent removals of the OMPs were compiled. Several software packages were used to 5 compute the chemical properties of OMPs and perform statistical analyses. For DSS, MCA was used since it allows the comparison of qualitative (non-monetary, non-metric) and quantitative criteria (e.g., costs). Quadrant plots were developed to study the hybrid of natural and advanced water treatment processes. The QSAR models satisfied both chemical and statistical criteria. The DSS resulted in natural treatment and ozonation as the preferred processes for OMPs removal. The QSAR models can be used as a screening tool for OMPs removal by oxidation. Moreover, the QSAR - defining molecular descriptors help in detailed understanding of oxidation. The DSS can be considered as an aid in assessing a multi-barrier approach to remove OMPs. Hybrids of natural and advanced treatment processes help to develop a more sustainable multi-barrier approach for OMPs removal.
Advisors:
Amy, Gary L.
Committee Member:
Khashab, Niveen M.; Lattemann, Sabine; Nunes, Suzana Pereira ( 0000-0002-3669-138X ) ; Snyder, Shane ( 0000-0003-2709-9840 )
KAUST Department:
Biological and Environmental Sciences and Engineering (BESE) Division
Program:
Environmental Science and Engineering
Issue Date:
Aug-2013
Type:
Dissertation
Appears in Collections:
Environmental Science and Engineering Program; Dissertations; Biological and Environmental Sciences and Engineering (BESE) Division

Full metadata record

DC FieldValue Language
dc.contributor.advisorAmy, Gary L.en
dc.contributor.authorSudhakaran, Sairamen
dc.date.accessioned2013-10-09T07:42:04Z-
dc.date.available2013-10-09T07:42:04Z-
dc.date.issued2013-08en
dc.identifier.urihttp://hdl.handle.net/10754/303061en
dc.description.abstractThe presence of organic micropollutants (OMPs) in water is of great environmental concern. OMPs such as endocrine disruptors and certain pharmaceuticals have shown alarming effects on aquatic life. OMPs are included in the priority list of contaminants in several government directorate frameworks. The low levels of OMPs concentration (ng/L to μg/L) force the use of sophisticated analytical instruments. Although, the techniques to detect OMPs are progressing, the focus of current research is only on limited, important OMPs due to the high amount of time, cost and effort involved in analyzing them. Alternatively, quantitative structure activity relationship (QSAR) models help to screen processes and propose appropriate options without considerable experimental effort. QSAR models are well-established in regulatory bodies as a method to screen toxic chemicals. The goal of the present thesis was to develop QSAR models for OMPs removal by oxidation. Apart from the QSAR models, a decision support system (DSS) based on multi-criteria analysis (MCA) involving socio-economic-technical and sustainability aspects was developed. Also, hybrids of different water treatment processes were studied to propose a sustainable water treatment train for OMPs removal. In order to build the QSAR models, the ozone/hydroxyl radical rate constants or percent removals of the OMPs were compiled. Several software packages were used to 5 compute the chemical properties of OMPs and perform statistical analyses. For DSS, MCA was used since it allows the comparison of qualitative (non-monetary, non-metric) and quantitative criteria (e.g., costs). Quadrant plots were developed to study the hybrid of natural and advanced water treatment processes. The QSAR models satisfied both chemical and statistical criteria. The DSS resulted in natural treatment and ozonation as the preferred processes for OMPs removal. The QSAR models can be used as a screening tool for OMPs removal by oxidation. Moreover, the QSAR - defining molecular descriptors help in detailed understanding of oxidation. The DSS can be considered as an aid in assessing a multi-barrier approach to remove OMPs. Hybrids of natural and advanced treatment processes help to develop a more sustainable multi-barrier approach for OMPs removal.en
dc.language.isoenen
dc.subjectQSAR'sen
dc.subjecthybridsen
dc.subjectmicropolluntantsen
dc.subjectwater qualityen
dc.titleOrganic Micropollutants Removal from Water by Oxidation and Other Processes:QSAR Models, Decision Support System and Hybrids of Processesen
dc.typeDissertationen
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Divisionen
thesis.degree.grantorKing Abdullah University of Science and Technologyen_GB
dc.contributor.committeememberKhashab, Niveen M.en
dc.contributor.committeememberLattemann, Sabineen
dc.contributor.committeememberNunes, Suzana Pereiraen
dc.contributor.committeememberSnyder, Shaneen
thesis.degree.disciplineEnvironmental Science and Engineeringen
thesis.degree.nameDoctor of Philosophyen
dc.person.id102039en
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