Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.540543
Title: Integration of microbial biosensors to enhance decision support for remediation strategies for contaminated land
Author: Diplock, E. E.
Awarding Body: University of Aberdeen
Current Institution: University of Aberdeen
Date of Award: 2011
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Abstract:
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.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.540543  DOI: Not available
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