The thesis is related with the development of a fully functional, modular Decision Support System (DSS) for performing Probabilistic Ecological Risk Assessment (PERA) of pollutants in aquatic environments. The Decision Support System is a 3‐module software, which integrates the use of Multi‐Criteria Decision Analysis (MCDA) methods for the quantitative assessment of the reliability and relevance of ecotoxicological data. Ecotoxicological data are vital components of the Ecological Risk Assessment processes and specifically the Effect assessment part. A MCDA based methodology (i.e. from the definition of the conceptual framework to the software implementation in collaboration with an experienced programmer) has been fully developed for the assessment of ecotoxicological data, which are used for the creation of weighted Species Sensitivity Distribution (SSWD) graphs. The innovative MCDA based methodology allows the assessment of ecotoxicological data based on a set of 57 distinctive criteria and gives the possibility to researchers to classify and rank ecotoxicological data, based on their various characteristics. As part of the research project, a case study application has been performed for the analysis of the ecological risk from the presence of cyanide in the Sélune watershed, at the Manche region of the Lower Normandy in the north‐west part of France. Environmental exposure data of cyanide (CN) have been collected from the Water Agency of ‘Seine‐Normandie’ and used in the Exposure Assessment module, while ecotoxicological data for cyanide gathered from peer‐reviewed publications have been analysed with the use of the proposed MCDA based methodology, in the Effect Assessment module. The ecological risk assessment process was concluded with the calculation of the risk indices in the last module of the DSS.

A decision support system for probabilistic ecological risk assessment (PERA) of pollutants on aquatic ecosystems / Isigonis, Panagiotis. - (2015 Feb 13).

A decision support system for probabilistic ecological risk assessment (PERA) of pollutants on aquatic ecosystems

Isigonis, Panagiotis
2015-02-13

Abstract

The thesis is related with the development of a fully functional, modular Decision Support System (DSS) for performing Probabilistic Ecological Risk Assessment (PERA) of pollutants in aquatic environments. The Decision Support System is a 3‐module software, which integrates the use of Multi‐Criteria Decision Analysis (MCDA) methods for the quantitative assessment of the reliability and relevance of ecotoxicological data. Ecotoxicological data are vital components of the Ecological Risk Assessment processes and specifically the Effect assessment part. A MCDA based methodology (i.e. from the definition of the conceptual framework to the software implementation in collaboration with an experienced programmer) has been fully developed for the assessment of ecotoxicological data, which are used for the creation of weighted Species Sensitivity Distribution (SSWD) graphs. The innovative MCDA based methodology allows the assessment of ecotoxicological data based on a set of 57 distinctive criteria and gives the possibility to researchers to classify and rank ecotoxicological data, based on their various characteristics. As part of the research project, a case study application has been performed for the analysis of the ecological risk from the presence of cyanide in the Sélune watershed, at the Manche region of the Lower Normandy in the north‐west part of France. Environmental exposure data of cyanide (CN) have been collected from the Water Agency of ‘Seine‐Normandie’ and used in the Exposure Assessment module, while ecotoxicological data for cyanide gathered from peer‐reviewed publications have been analysed with the use of the proposed MCDA based methodology, in the Effect Assessment module. The ecological risk assessment process was concluded with the calculation of the risk indices in the last module of the DSS.
13-feb-2015
27
Scienze ambientali
Critto, Andrea
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10579/5636
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