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

Ecological Risk Assessment (ERA) is a process undertaken for estimating the environmental harms caused by human activities. The assessment is based on three components: effect assessment, exposure assessment, and risk characterisation. The latter is a combination of the former two. Various methodologies can be used for performing ERA, which can be categorised into deterministic and probabilistic. Probabilistic techniques have been at the focus of research the last years, due to their elaborated character and the possibilities they offer for more refined risk assessments. Despite their obvious advantages, probabilistic techniques present also disadvantages and challenges that need to be tackled. In the thesis, the possibility of exploring further the concept of Probabilistic Ecological Risk Assessment (PERA) is addressed. The main motivation of the thesis is identified in the effort to combine various well known concepts and methods for Ecological Risk Assessment, while enhancing them with new features and functionalities to serve the current needs of Risk Assessors. Therefore, providing a complete software package that allows performing efficient Propabilistic ERA (PERA) and offers related functionalities, all gathered in one place. The proposed software is developed as part of the research project AMORE (funded by the National French Research Academy – ANR). A proposal for a Decision Support System (DSS), named AMORE DSS, supporting Probabilistic ERA is described in detail and validated through the application of the proposed DSS to a case study for assessing the effects and risks posed by the presence of cyanide in a river in north-western France. The AMORE DSS aims at allowing efficient Probabilistic ERA and tackles issues related with PERA and the concept of weighted Species Sensitivity Distributions (SSWD) such as the handling of uncertainty in PERA, the production of reliable SSWD graphs and the assessment of the quality of ecotoxicological data. The theoretical section of the thesis is split into two main parts. In the first, the concept of Ecological Risk Assessment is introduced and the principal methods of interest are described. It is followed by the presentation of the concepts of Multi-Criteria Decision Analysis (MCDA) and Decision Support Systems (DSS), which are important aspects of the developed research. The methodological developments of the thesis are based on a proposal for the estimation of the reliability and relevance of ecotoxicological data used in ERA, which is presented in detail and evaluated. The proposed methodology is based on Multi-Criteria Decision Analysis and allows the assessment of ecotoxicological data on the basis of a fixed set of criteria and mathematically stable and robust aggregation techniques. Therefore, the methodology suggests the production of reliable weighted Species Sensitivity Distributions, a vital component of the probabilistic ERA and the calculation of risk probabilities. The proposal allows incorporating in the risk assessment the knowledge gathered from an expert panel and gives significant strength to the risk assessors for the performed assessments, through the use of previously not widely available information and expertise. The proposed DSS is built on the three components (exposure, effects, risk) of ERA and provides a complete set of functionalities to the risk assessors, enhanced with unique features. The thesis describes in detail the development of the software and the functionalities of each of its modules. The Exposure Assessment module aims at providing to the Decision Maker/Risk Assessor a collection of tools for the statistical analysis of environmental exposure data, through the concept of Predicted Environmental Concentration. The Effect Assessment module is based on the concept of weighted Species Sensitivity Distributions (SSWD) and incorporates the proposed methodology for the assessment of the reliability and relevance of ecotoxicological data. The Risk Assessment module is based on the concept of Potentially Affected Fraction (PAF) and aims at synthesising the results of the previous two modules for the estimation of risks, in an efficient and easy to present way. The last part of the thesis is dedicated to the application of the DSS to a real life case study. A Risk Assessment process is performed for estimating the sensitivity of species to the presence of Cyanide (CN) in the environment, for estimating Environmental Quality Criteria (EQC) for the assessed case and for estimating the level of risk posed from Cyanide at the ecosystem. The assessed area is the Selune rivershed in the Manche department of the lower Normandy region in France, where four sampling stations have been identified with records of Cyanide presence for the period 2005-2014. Regarding the ecotoxicological data of the case study, 26 scientific articles on cyanide toxicity, published in the period 1965-2011, have been analysed for the extraction and assessment of 46 toxicological endpoints for the aquatic environment. The case study is firstly based on all the available ecotoxicological data and secondly based on data split per taxonomic groups (i.e vertebrates, invertebrates) and trophic levels (i.e. primary producers, primary/secondary consumers). Specifically, six (6) sets of SSWD graphs are produced (i.e. All data, Vertebrates, Invertebrates, Primary producers, Primary consumers, Secondary consumers) with the use of two weighting options: (i) the weighting coefficients that are produced with the application of the MCDA based methodology and (ii) equal weighting coefficients for all the data. A comprehensive comparison of the two types of SSWD is performed and discussed in detail for the identification of the appropriateness of the fitting of the SSD curves to the experimental data. Hazardous concentrations (HCx) are estimated and presented for all the taxonomic groups and trophic levels. In addition, in combination with the results of the statistical analysis of the environmental exposure data, the risk is estimated for the assessed stations in the case study area. The results of the case study show that the primary producers are found to be the most sensitive trophic level while Invertebrates are more sensitive as a taxonomic group for low cyanide concentrations and Vertebrates are more sensitive for higher concentrations. Regarding the calculated risk indices, station 3 (L’Yvrande) of the Manche region is the area with the higher estimated risk. The performed application of the DSS in the cyanide case study demonstrates a complete probabilistic Ecological Risk Assessment process with the use of Species Sensitivity Distributions and the utilisation of Multi-Criteria Decision Analysis. The case study, alongside with the validation of the developed DSS, demonstrates the performance of the proposed MCDA-based WoE framework for the analysis of ecotoxicological data, based on three distinctive Lines of Evidence (Experimental Reliability, Statistical Reliability, Biological Relevance). The framework and the related MCDA methodology constitute an innovative development in the field of quantitative ecotoxicological data assessment frameworks. Furthermore, a robust performance of the DSS has been identified, which allows potential for adoption within the risk assessment research fields.The thesis is concluded with future considerations for the developed DSS, which could provide interesting functionalities and extensions of the capabilities of the software.