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Adaptive Sampling and Analysis Programs (ASAPs)

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AR #1728

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Tech ID: 2946
Project Overview
The Adaptive Sampling and Analysis Programs (ASAPs) approach makes use of real-time data collection techniques and in-field decision-making methodologies to guide the progress of data collection activities. The advantages of this approach include reduced analytical costs per sample, a reduction in the number of samples and data collected, and a better characterization survey. Three software products developed to support ASAPs include (1) SitePlanner and SiteView, object-oriented geographic information systems customized for characterization work, (2) the MaD browser (MaDCoW) for dynamic display of maps and data over the Web, and (3) Plume, a Bayesian geostatistical package for designing ASAPs to delineate the extent of contamination. The most recent developments have focused on integrating these technologies into soil remediation actions to make those actions more precise.

Technology Description
The ASAP approach to the sampling strategy problem is based on dynamic work plans which utilize field analytical methods to generate sample results quickly enough to have an impact on the course of the field sampling program, along with decision support mechanisms allowing the field data to be used in a timely and accurate fashion.

There are two components to the decision support system. The first is a Geographical Information System to integrate, manage, and display site characterization information as it is being gathered, such as SitePlanner(TM). Coupled with SitePlanner is Plume(TM), an interactive software package developed by Argonne National Laboratory. Plume uses advanced Bayesian geostatistical techniques to combine `soft' site data with sample results to form updated images of contamination location, providing quantitative measures of the potential benefits from and optimal locations for additional sampling. This approach can readily be applied for soil contamination remediation as well as other types of site characterization.

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