Value of Information Analysis for Site Investigations in Remediation Projects

Abstract: Site investigations of contaminated land are associated with high costs. From a societal point of view, just enough economic resources should be spent to allow society?s limited resources to be allocated optimally to sustainable development. The solution is to design cost-effective investigation programmes, which can be performed using Value of Information Analysis (VOIA). The principle is to compare the expected benefit at present state of knowledge with the benefit that is expected after an investigation has been performed. Statistical methods are used to calculate the expected change, i.e. the value of the investigation. The main strength of the VOIA process is that it promotes clear thinking and forces the decision-maker to reflect on issues that otherwise would be ignored. A general framework for VOIA of site investigations is presented. The framework consists of seven modules: (1) the land use scenario, (2) the objective of investigation, (3) a conceptual site model, (4) a data collection module, (5) a prior information module, (6) an uncertainty reduction module, and (7) a decision model. The decision model is based on Bayesian risk-cost-benefit decision analysis. The result is an estimate of the value of an investigation programme, and for specific problems, the optimal number of samples. The framework can be applied on three complexity levels, where the value is expressed as: (a) the uncertainty reduction, (b) the quotient of uncertainty reduction and investigation cost, or (c) the expected monetary value. VOIA models were developed for investigations at early phases of a project, and for sampling during the later remediation phase. The models were applied in case-studies and the applications illustrate that the investigation objective, the land use, and the benefit of remediation have a major impact on the results. The main contributions of this thesis are: (1) a general framework for VOIA of site investigations in remediation projects, (2) a toolkit of VOIA models for practical application, and (3) a knowledge base of strengths and weaknesses of the methodology, including recommendations of development.