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 Adaptive Remedial Actions

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Adaptive Remedial Actions

Benefits of adaptive remedial actions, and examples of dynamic work strategies applied to adaptive remedial action planning and implementation.

Adaptive remedial actions and associated dynamic work strategies offer the greatest potential for cost savings under the Triad. By this time in the characterization and remediation process, contaminants of concern are identified and action levels established. Site-specific real-time measurement performance has been demonstrated. Per unit cleanup costs are quantifiable allowing for cost-benefit analyses when designing data collection programs. Sampling requirements to support remediation may be significant. The potential for cost savings through waste stream minimization is present.

Adaptive remedial actions leverage adaptive data collection programs to make the remedial action more effective and efficient. The results are remedial action programs that look and operate differently than standard approaches. Examples of dynamic work strategies applied to adaptive remedial action planning and implementation include:

  • Adaptive Pre-Design Data Collection. Remedial investigations rarely result in data sets with sufficient information to adequately design and implement proposed remedial actions. The primary deficiency is usually inadequate information about the location and spatial extent of contamination above cleanup requirements. The uncertainty this introduces can complicate both the engineering design process (e.g., determining excavation footprints or locating injection/extraction wells), and the programmatic planning process (e.g., accurately estimating remediation costs and schedules). Adaptive pre-design data collection programs can be deployed as part of a dynamic work strategy to reduce uncertainty to acceptable levels. If closure plans have already been finalized and pre-design data collection conducted in a manner consistent with closure data needs, this type of data collection can expedite the closure process. In this setting pre-design data serve a dual purpose, supporting remedial design and allowing no further action decisions to be made for portions of a site where nothing above requirements is discovered and no remediation is necessary.

  • Precision Excavation Techniques. Precision excavation techniques refer to the combined use of locational control technologies such as Global Positioning Systems and real-time measurement systems to guide the removal of contaminated soil or sediment. Dynamic work strategies that support precision excavation usually begin with a minimized, highly certain footprint of known contamination, and then progress outwards and downwards in pursuit of contamination above cleanup goals. The ultimate footprint of the work is not specified, although there may be bounds placed on what is expected based on pre-design data collection and analysis. Decisions units take the form of remediation units (i.e., discrete areas treated as a unit for remediation decision purposes). The size of remediation units are functions of technology capabilities, logistics, remediation costs, and final closure requirements. For subsurface contamination, sediment or soil removal usually occurs in "lifts", with exposed surfaces characterized before removal activities continue at that location. The ultimate objective is to minimize total remediation costs while achieving closure goals. A cost-benefit analysis is critical to getting the right mix of real-time measurement systems and in-field decision-logic that will guide work. Sites with relatively inexpensive treatment or disposal options and relatively more expensive sampling and analysis costs will likely de-emphasize significant investments in real-time measurement collection. Conversely, sites where real-time measurements are relatively cheap compared to disposal and/or treatment costs may make significant investments in real-time data collection to make sure the right remediation decisions are made.

  • Adaptive Groundwater Remedial Actions. Groundwater remediation involves contaminated media that is mobile, and includes actions with time horizons that are usually much longer than those associated with contaminated sediment or soil remedial actions. As with soils and sediments, the uncertainty associated with groundwater remedial design stems partly from unknowns about nature and extent of contamination, but also to a large degree from doubt about how the system will respond to the selected remedial approach. Under the Triad, one way to address this uncertainty is to design with change in mind, and to implement the selected strategy with appropriate measurement systems to support change as necessary. For groundwater remedial action support, adaptive analytics selection is key to supporting timely decisions while controlling characterization costs. An example of incorporating flexibility is designing an injection/extraction system with a larger number of smaller capacity injection/extraction points and modifying the operation of the system across the points and over time as necessary. A second example is the use of direct push platforms as a means for cost-effectively identifying the most appropriate locations for more expensive, permanent monitoring wells.

  • Treatment Train Approaches. As discussed earlier, one way to manage both uncertainty in remedial performance and overall costs for complex subsurface environmental systems is through the use of treatment trains. Treatment trains result in an overall remediation process that is comprised of a set of sequential steps. A dynamic work strategy applied to remedial action monitoring as part of the overall treatment train design can provide the information necessary to support decisions about when to adjust existing system parameters to improve performance, and/or when to switch from one intervention (e.g., active pump and treat) to the next phase (e.g., monitored natural attenuation).

  • Adaptive Waste Disposition Support. Remedial actions produce waste streams that must be managed. Management includes determining the appropriate disposition of waste streams, and/or additional treatment required. A Triad-based dynamic work strategy can be used to support alternative disposition and/or treatment decisions. As an example, the excavation of a former burial area may yield four distinctly different waste streams, one that meets site cleanup criteria and can be used as backfill (e.g., clean overburden or layback that must be removed to get at contamination), a second that meets the requirements for solid municipal waste disposal, a third that could be accepted by a properly permitted facility without further treatment, and a fourth that would require treatment to satisfy RCRA treatment standards before disposal. The per-unit treatment/disposal costs associated with each waste stream would be significantly different. The goal of data collection in this instance is to establish compliance with appropriate waste profile characteristics. Real-time measurements could be done in situ before soils are removed, or ex situ as soils are handled to support disposal decisions. In this particular case the dynamic work strategy would require logistical coordination to make sure waste profile data collection did not interfere with overall work flow, and flexibility in the project's capacity to handle a range of waste volumes, since these would likely be uncertain before work began.

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