On Uncertainty and Data Worth in Decision Analysis for Contaminated Land
A methodology for including sample uncertainty in data worth analysis is presented. It is based on a Bayesian approach to data worth. The sampling objective is to estimate the mean concentration at a site. A MathCad computer application for the calculations is supplied. An application of the data worth estimation procedure is presented for a sampling problem at a former Ferro-alloy work in Gullspång, Sweden. A conclusion is that prior estimates of contaminant concentrations may have a significant impact on the result, as well as estimates of failure cost. It is recommended to use different estimates of failure cost to study its influence. Results also indicate that when sample uncertainty is increased, the expected net value of the sampling program will decrease moderately and relatively constant.
In situations where contamination has not yet occurred, cost-efficient protective actions need to be identified to combat environmental risks. A methodology for selecting costefficient protective actions for water supplies along railways has been developed. The risk object is railway transport of dangerous goods. Also for this problem, estimation of failure cost is believed to be important for the result.
The need for additional development of the methodology is identified. Estimation of uncertainty in soil sampling can be improved and the described theory extended. The methodology for data worth analysis for contaminated land should be extended to take additional sampling objectives into account.
contaminated land, data worth, decision analysis, risk, sampling, uncertainty
Statens Geotekniska Institut (SGI)
Miljö- och naturvårdsvetenskap
Chalmers tekniska högskola