Literature DB >> 16869441

Decision support-oriented selection of remediation technologies to rehabilitate contaminated sites.

Andrea Critto1, Lisa Cantarella, Claudio Carlon, Silvio Giove, Gianniantonio Petruzzelli, Antonio Marcomini.   

Abstract

A methodology for selecting remediation technologies is presented as part of a decision support system for the rehabilitation of contaminated sites. It includes 2 steps: In the 1st step, a pool of suitable technologies is selected within a technologies database according to their applicability to site-specific conditions; in the 2nd step, the selected technologies: are ranked according to a multicriteria decision analysis (MCDA) approach. The MCDA was applied to allow for a transparent procedure and for the integration of expert analyses. The methodology was implemented in a previously developed georeferenced information system-based decision support system for the rehabilitation of contaminated sites and then applied to a case study (Porto Marghera, Venice, Italy). On the basis of the obtained results, the proposed methodology appeared suitable to select remediation technologies according to both technical features and requirements of available technologies, as well as site-specific environmental conditions of the site of concern, such as chemical contamination levels and remediation objectives.

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Year:  2006        PMID: 16869441

Source DB:  PubMed          Journal:  Integr Environ Assess Manag        ISSN: 1551-3777            Impact factor:   2.992


  2 in total

1.  Using multiple indices to evaluate scenarios for the remediation of contaminated land: the Porto Marghera (Venice, Italy) contaminated site.

Authors:  Andrea Critto; Paola Agostini
Journal:  Environ Sci Pollut Res Int       Date:  2009-07-02       Impact factor: 4.223

2.  Screening of groundwater remedial alternatives for brownfield sites: a comprehensive method integrated MCDA with numerical simulation.

Authors:  Wei Li; Min Zhang; Mingyu Wang; Zhantao Han; Jiankai Liu; Zhezhou Chen; Bo Liu; Yan Yan; Zhu Liu
Journal:  Environ Sci Pollut Res Int       Date:  2018-03-26       Impact factor: 4.223

  2 in total

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