relied on conventional well sampling, which is labor intensive and requires costly laboratory analyses. Given that tens to hundreds of monitoring wells are present at most sites, and standard quarterly sampling is often required, estimates of monitoring can exceed $100 million per year at DoD facilities alone, which represents a significant percentage of the financial resources dedicated to remediation efforts. Furthermore, the traditional two-dimensional resolution of monitoring well networks (which produce vertically averaged concentration values) may be insufficient to support an accurate site conceptualization, particularly for highly heterogeneous formations.

Continued development of conventional monitoring techniques has led to more detailed characterization of the distribution of dissolved contaminants, particular in the vertical dimension. However, to support a cost-effective transition to long-term management, additional tools are needed. This section addresses ongoing developments in (1) optimization of conventional monitoring systems, (2) techniques for measuring contaminant flux, (3) sensor technology, and (4) new tools that can be applied to better understand whether MNA is working.

Improved Application of Conventional Monitoring Tools

The deployment of conventional site characterization tools has evolved in a manner that has emphasized greater spatial resolution in regions where contamination is significant. In particular, multi-level monitoring and nested well systems now enable the collection of hydraulic head data and groundwater samples over relatively short vertical intervals (ITRC, 2004; Einarson, 2006; Einarson et al., 2010; Kavanaugh and Deeb, 2011). Although more costly than conventional 2-D monitoring, multi-level monitoring systems can lead to more streamlined and accurate remedial investigations and long-term management.

Formal simulation/optimization techniques have been developed to improve the design of monitoring programs—a process sometimes termed long-term monitoring optimization (LTMO). These applications are in a relatively early stage of development and a variety of approaches are available to formulate and solve the optimization problem. For example, one approach might be to analyze the value of information provided by an existing monitoring network to identify monitoring wells that are spatially redundant and could be removed (e.g., Reed et al., 2000, 2001; Babbar-Sebens and Minsker, 2008). Most work to date has focused on monitoring frequency and spatial resolution of well networks, with less attention given to issues such as the number and selection of analytes, sampling analytical techniques, and data processing. In a pilot study comparing two software-driven LTMO systems, the U.S. Environmental Protection Agency (EPA)



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