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dc.contributor.convenorZhiguo Yuanen_AU
dc.contributor.authorBlumenstein, Michaelen_US
dc.contributor.authorFogelman, Shoshanaen_US
dc.contributor.authorZhao, Huijunen_US
dc.contributor.editorZhiguo Yuanen_US
dc.date.accessioned2017-04-04T17:02:59Z
dc.date.available2017-04-04T17:02:59Z
dc.date.issued2009en_US
dc.date.modified2010-08-05T07:17:25Z
dc.identifier.urihttp://hdl.handle.net/10072/31927
dc.description.abstractReliable, continuous on-line water quality monitoring technology is becoming vital in the drive to ensure sustainable, safe supplies of freshwater resources in light of climate change, increased industrialisation and water scarcity (Schwarzenbach et al 2006; Diamond 2004; Allan et al. 2006). This is because currently, accurate and costeffective on-line monitoring of various water quality parameters has proven difficult to achieve, as direct sensor deployment often means most sensors are unavoidably exposed to a wide range of varied and extreme measurement conditions (Diamond 2004; Allan et al. 2006, Frey and Sullivan 2004). The majority of on-line monitoring technologies currently employed are based on direct adaptations of traditional laboratory-based analytical methods, which were not originally designed for continuous or field based monitoring applications (Frey and Sullivan 2004; Danszer and Currie 1998). As the calibration models are based on Gauss's theory of least squares, they have the inherent flaw requiring strictly defined physicochemical measurement conditions in order to obtain quantitative results (Danszer and Currie 1998). This is because most sensors are not entirely selective towards one specific analyte and tend to suffer cross responses from the sample matrix. As ideal measurement conditions are rarely present in the natural environment, this invalidates the operating conditions required for reliable performance and hence leads to measurement errors. Consequently, these methods require frequent calibration, maintenance, complicated sample pre-treatment and consume large quantities of reagents in order to try and maintain their reliable performance (Frey and Sullivan 2004). However, the cost associated with maintaining instruments based on this measurement principle has greatly reduced their wide spread application, especially for remote, large-scale environmental water quality monitoring in places like the European Union (Allan et al. 2006). Therefore, simple methods that can improve the reliability, accuracy and economic costs associated with on-line monitoring such as maintenance and reagent consumption would be of great benefit to industry, government and research organisations. The aim of this research was to develop a generic new analytical method specifically developed for continuous on-line monitoring in a diversified range of non-ideal measurement conditions. This is becoming increasingly important as we produce potable water from more impaired or novel water resources and ensure that traditional water resources such as rivers and catchments are not contaminated. Hence in this paper we present a new analytical method that can enable a traditional laboratorybased sensor to intelligently respond in-situ to its measurement environment, negating the need for conventional calibration, reagents, sample pre-treatment or strictly controlled measurement conditions.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_AU
dc.format.extent191976 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.language.isoen_AU
dc.publisherInternational water Associationen_US
dc.publisher.placeQueensland, Australiaen_US
dc.publisher.urihttp://www.iwa-ica2009.org/en_AU
dc.relation.ispartofstudentpublicationYen_AU
dc.relation.ispartofconferencename10th IWA Conference on Instrumentation Control and Automationen_US
dc.relation.ispartofconferencetitleProceedings of the 10th IWA Conference on Instrumentation Control and Automationen_US
dc.relation.ispartofdatefrom2009-06-14en_US
dc.relation.ispartofdateto2009-06-17en_US
dc.relation.ispartoflocationCairns, Queensland, Australiaen_US
dc.rights.retentionYen_AU
dc.subject.fieldofresearchInstrumental Methods (excl. Immunological and Bioassay Methods)en_US
dc.subject.fieldofresearchNeural, Evolutionary and Fuzzy Computationen_US
dc.subject.fieldofresearchcode030105en_US
dc.subject.fieldofresearchcode080108en_US
dc.titleDevelopment of a new analytical method for continuous on-line and in-situ monitoring in real world non-ideal environmentsen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.facultyGriffith Sciences, Griffith School of Environmenten_US
gro.rights.copyrightCopyright remains with the authors 2009. The attached file is posted here with permission of the copyright owners for your personal use only. No further distribution permitted. For information about this conference please refer to the publisher's website or contact the authors.en_AU
gro.date.issued2009
gro.hasfulltextFull Text


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