Sampling strategies for contaminated brownfield sites

Abstract

Abstract. Brownfield sites often require a geochemical survey to assess the extent of contamination that is present as a result of previous industrial activities. These measurements are subsequently assessed to ascertain whether the site presents the possibility of causing significant harm to those who may use the site for specified purposes. The measurement process comprises both field sampling and chemical analysis, with sampling being of crucial importance, since previous studies have repeatedly shown that it is the sampling phase that generates the highest component of uncertainty. A variety of methods are currently available for sampling brownfield sites, such as different sampling patterns and the choice of depth and mass recovered. An investigator may also choose to employ more innovative sampling methods, such as in situ measurement strategies that can significantly reduce the overall time taken to complete the survey. The general aim of a sampling strategy is to take representative samples for chemical analysis, although this is rarely achieved due to the inherent heterogeneity of contaminants within any given site. Since it is practically impossible to sample an entire site, and thus achieve a truly representative sample, it is becoming increasingly understood that the uncertainty of the measurements should be estimated, to provide a more reliable interpretation of the survey. Various methods are currently available to estimate the measurement uncertainty that arises from both sampling and analysis, which vary in terms of complexity and cost. The level of uncertainty estimated during a site investigation should also be judged on its fitness‐for‐purpose (i.e. whether subsequent decisions based upon it are acceptable). The ‘optimized contaminated land investigation’ (OCLI) method is a new approach that can be used to balance the site‐specific variables of any given investigation, such as the measurement costs against the level of uncertainty and costs that may arise from misclassification. This provides an objective and traceable judgement of whether the measurements are fit‐for‐purpose.