The current environmental legislation (e.g. WFD, REACH) has increased the demand for ecological risk assessments of chemicals. Challenges emerge in the development of tools for the quantitative assessment of risk, where statistical and mathematical models have to be used, as multiple statistical aspects (e.g. ecotoxicological data analysis, estimation of reliability, uncertainty) have to be analysed. In this context, the European research project “AMORE” (Multi-Criteria Analysis for the Development of a Decision Support Tool for the prevention of Environmental Risks), funded by the National French Research Academy (ANR), aimed at the development of an innovative environmental Decision Support System (DSS) able to perform probabilistic ecological risk assessment. The DSS is based on the use of Multi-Criteria Decision Analysis (MCDA). The objective of the DSS is to support the risk assessment approach in a reliable and reproducible way. It is a tool aiding in increasing the efficiency of risk assessment processes and allows the integration of different experts’ opinions for supporting the process of structuring decisions. The DSS consists of the following three modules: 1. Exposure Assessment – Predicted Environmental Concentration (PEC) graphs 2. Effect Assessment – Species Sensitivity Distribution (SSD) graphs 3. Risk Assessment - Potentially Affected Fraction (PAF) of species The innovative feature of the DSS is the incorporation of a new MCDA based Weight of Evidence (WoE) methodology, which aims to improve the evaluation of ecotoxicological data, through the assessment of their relevance and reliability for the definition of SSDs. The methodology is based on the assessment of a hierarchically structured set of 57 criteria, which is used for assigning a quantitative score to every ecotoxicological datum and was created based on the review of the state of the art frameworks for the assessment of ecotoxicological data. The different endpoints are analysed based on three main aspects: the ‘Experimental Reliability’, the ‘Statistical Reliability’ and the ‘Biological Relevance’ of the experimental protocol used during their production. The platform presentation reports the characteristics and the structure of the PROERA Decision Support System, the main mathematical details of the proposed WoE methodology for the analysis of ecotoxicological data, as well as the results of the application to selected case studies.
PROERA: A Multi-Criteria based Decision Support System for probabilistic ecological risk assessment
ISIGONIS, PANAGIOTIS;ZABEO, Alex;SEMENZIN, Elena;GIOVE, Silvio;CRITTO, Andrea;MARCOMINI, Antonio;
2014-01-01
Abstract
The current environmental legislation (e.g. WFD, REACH) has increased the demand for ecological risk assessments of chemicals. Challenges emerge in the development of tools for the quantitative assessment of risk, where statistical and mathematical models have to be used, as multiple statistical aspects (e.g. ecotoxicological data analysis, estimation of reliability, uncertainty) have to be analysed. In this context, the European research project “AMORE” (Multi-Criteria Analysis for the Development of a Decision Support Tool for the prevention of Environmental Risks), funded by the National French Research Academy (ANR), aimed at the development of an innovative environmental Decision Support System (DSS) able to perform probabilistic ecological risk assessment. The DSS is based on the use of Multi-Criteria Decision Analysis (MCDA). The objective of the DSS is to support the risk assessment approach in a reliable and reproducible way. It is a tool aiding in increasing the efficiency of risk assessment processes and allows the integration of different experts’ opinions for supporting the process of structuring decisions. The DSS consists of the following three modules: 1. Exposure Assessment – Predicted Environmental Concentration (PEC) graphs 2. Effect Assessment – Species Sensitivity Distribution (SSD) graphs 3. Risk Assessment - Potentially Affected Fraction (PAF) of species The innovative feature of the DSS is the incorporation of a new MCDA based Weight of Evidence (WoE) methodology, which aims to improve the evaluation of ecotoxicological data, through the assessment of their relevance and reliability for the definition of SSDs. The methodology is based on the assessment of a hierarchically structured set of 57 criteria, which is used for assigning a quantitative score to every ecotoxicological datum and was created based on the review of the state of the art frameworks for the assessment of ecotoxicological data. The different endpoints are analysed based on three main aspects: the ‘Experimental Reliability’, the ‘Statistical Reliability’ and the ‘Biological Relevance’ of the experimental protocol used during their production. The platform presentation reports the characteristics and the structure of the PROERA Decision Support System, the main mathematical details of the proposed WoE methodology for the analysis of ecotoxicological data, as well as the results of the application to selected case studies.
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