Adaptive spatial sampling of contaminated soil
Suppose that a residential neighborhood may have been contaminated by a nearby abandoned hazardous waste site. The suspected contamination consists of elevated soil concentrations o chemicals that are also found in the absence of site-related contamination. How should a risk manager decide which residential properties to sample and which ones to clean? This paper introduces an adaptive spatial sampling approach which uses initial observations to guide subsequent search. Unlike some recent model-based spatial data analysis methods, it does not require any specific statistical model for the spatial distribution of hazards, but instead constructs an increasingly accurate nonparametric approximation to it as sampling proceeds. Possible cost-effective sampling and cleanup decision rules are described by decision parameters such as the number of randomly selected locations used to initialize the process, the number of highest-concentration locations searched around, the number of samples taken at each location, a stopping rule, and a remediation action threshold. These decision parameters are optimized by simulating the performance of each decision rule. The simulation is performed using the data collected so far to impute multiple probably values of unknown soil concentration distributions during each simulation run.
- Research Organization:
- Cox Associates, Denver, CO (US)
- OSTI ID:
- 20006166
- Journal Information:
- Risk Analysis, Vol. 19, Issue 6; Other Information: PBD: Dec 1999; ISSN 0272-4332
- Country of Publication:
- United States
- Language:
- English
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