A decision support tool to prioritize risk management options for contaminated sites

The decisions on risk management (RM) of contaminated sites in Finland have typically been driven by practical factors such as time and money. However, RM is a multifaceted task that generally involves several additional determinants, e.g. performance and environmental effects of remediation methods, psychological and social factors. Therefore, we adopted a multi-criteria decision analysis approach and developed a decision support tool (DST) that is viable in decision-making in such a complex situation. The basic components of the DST are based on the Dutch REC system. However, our DST is more case-specific and allows the consideration of the type, magnitude and scale of contamination, land use, environmental conditions and socio-cultural aspects (e.g. loss of cultural heritage, image aspects). The construction of the DST was started by structuring the decision problem using a value tree. Based on this work we adopted the Multi-Attribute Value Theory (MAVT) for data aggregation. The final DST was demonstrated by two model sites for which the RM alternatives and site-specific data were created on the basis of factual remediation projects and by interviewing experts. The demonstration of the DST was carried out in a workshop where representatives of different stakeholders were requested to rank and weight the decision criteria involved. To get information on the consistency of the ranking of the RM alternatives, we used different weighting techniques (ratio estimation and pair-wise weighting) and alternative ways to treat individual respondents' weights in calculating the preference scores for each RM alternative. These dissimilar approaches resulted in some differences in the preference order of the RM alternatives. The demonstration showed that attention has to be paid to the proper description of the site, the principles of the procedure and the decision criteria. Nevertheless, the procedure proved to enable efficient communication between different stakeholders and the identification of the preferred RM option.