Integration of microbial biosensors to enhance decision support for remediation strategies for contaminated land

The thesis established the value of empirical data (biological, chemical and physical) in enabling an effective prediction of the potential for biological remediation to take place. While this was calibrated with over forty genuine environmental scenarios, its application to genuine fieldscale opera...

Full description

Bibliographic Details
Main Author: Diplock, E. E.
Published: University of Aberdeen 2011
Subjects:
628
Online Access:http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.540543
id ndltd-bl.uk-oai-ethos.bl.uk-540543
record_format oai_dc
spelling ndltd-bl.uk-oai-ethos.bl.uk-5405432015-03-20T05:24:47ZIntegration of microbial biosensors to enhance decision support for remediation strategies for contaminated landDiplock, E. E.2011The thesis established the value of empirical data (biological, chemical and physical) in enabling an effective prediction of the potential for biological remediation to take place. While this was calibrated with over forty genuine environmental scenarios, its application to genuine fieldscale operations was more limited. Empirical data also underpinned the assessment of a set of low cost ameliorants in complexing heavy metals enabling the protection of controlled waters. In this case the ameliorant calcium polysulphide out-performed the other solid matrices investigated. The commercial sponsor of the project was Remedios Limited who have pioneered the development and environmental applications of microbial biosensors. This project served to audit the current performance of biosensors and consider their future potential. All of the empirical data and the statistically evaluated results were integrated into a tiered decision support tool. This tool: Remediation DST was developed through a series of options that were weighted to reflect the parameters that assist users in reaching and justifying decisions regarding contaminated land remediation. Tier 1 considers generic risk assessment in the context of remediation. Tier 2 is a multi-component correlation matrix that matches soils or water to the available technologies. A weighted scoring system differentiates the relative merit of the selected option. Tier 3 is a manual interface that links the bespoke needs of users to generic strategies for effective remediation. Once test driven, the tiered approach was effective at clearly justifying the best remedial option available. The output from this project makes full use of empirical data to enable end-users to reach clear and well justified decisions.628University of Aberdeenhttp://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.540543Electronic Thesis or Dissertation
collection NDLTD
sources NDLTD
topic 628
spellingShingle 628
Diplock, E. E.
Integration of microbial biosensors to enhance decision support for remediation strategies for contaminated land
description The thesis established the value of empirical data (biological, chemical and physical) in enabling an effective prediction of the potential for biological remediation to take place. While this was calibrated with over forty genuine environmental scenarios, its application to genuine fieldscale operations was more limited. Empirical data also underpinned the assessment of a set of low cost ameliorants in complexing heavy metals enabling the protection of controlled waters. In this case the ameliorant calcium polysulphide out-performed the other solid matrices investigated. The commercial sponsor of the project was Remedios Limited who have pioneered the development and environmental applications of microbial biosensors. This project served to audit the current performance of biosensors and consider their future potential. All of the empirical data and the statistically evaluated results were integrated into a tiered decision support tool. This tool: Remediation DST was developed through a series of options that were weighted to reflect the parameters that assist users in reaching and justifying decisions regarding contaminated land remediation. Tier 1 considers generic risk assessment in the context of remediation. Tier 2 is a multi-component correlation matrix that matches soils or water to the available technologies. A weighted scoring system differentiates the relative merit of the selected option. Tier 3 is a manual interface that links the bespoke needs of users to generic strategies for effective remediation. Once test driven, the tiered approach was effective at clearly justifying the best remedial option available. The output from this project makes full use of empirical data to enable end-users to reach clear and well justified decisions.
author Diplock, E. E.
author_facet Diplock, E. E.
author_sort Diplock, E. E.
title Integration of microbial biosensors to enhance decision support for remediation strategies for contaminated land
title_short Integration of microbial biosensors to enhance decision support for remediation strategies for contaminated land
title_full Integration of microbial biosensors to enhance decision support for remediation strategies for contaminated land
title_fullStr Integration of microbial biosensors to enhance decision support for remediation strategies for contaminated land
title_full_unstemmed Integration of microbial biosensors to enhance decision support for remediation strategies for contaminated land
title_sort integration of microbial biosensors to enhance decision support for remediation strategies for contaminated land
publisher University of Aberdeen
publishDate 2011
url http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.540543
work_keys_str_mv AT diplockee integrationofmicrobialbiosensorstoenhancedecisionsupportforremediationstrategiesforcontaminatedland
_version_ 1716791070869684224