AT AST AND WITHIN THE RPI GROUP, THE COLLECTION OF SUPPLEMENTAL SAMPLES AND DATA ANALYSIS FOR REMEDIATION PURPOSES IS REFERRED TO AS THE REMEDIAL DESIGN CHARACTERIZATIONAbbreviated as RDC. One of the most common mistakes that leads to an unsuccessful remediation program is an inaccurate and... (RDC). In collaboration with our client the consultant, the robust RDC data set is incorporated with historical site information to develop a quantitative high-resolution Conceptual Site ModelAbbreviated as CSM. The conceptual site model (CSM) is the communication tool that presents the understanding of the fate and... (CSM). The CSM is then used to develop a precise in-situ surgical remediation plan.
One of the most common mistakes that leads to an unsuccessful remediation program is an inaccurate and generalized CSM. These generalized CSMs often rely on composite groundwater samples from the entire saturated water column and limited or aged soil analytical data. AST’s approach to successful remediation in unconsolidated media (overburden) is to conduct an RDC to obtain both spatially and vertically dense soil and groundwater analytical data to increase resolution, determine contaminant gradients, and variability in aquifer properties due to geologic heterogeneity.
Similar data gaps in consolidated media (bedrock) must also be filled in order to effectively mitigate contaminant risk in these regimes. Accurate assessment of the aquifer matrix and discrete interrogation of transmissive features is critical to surgically emplacement of amendments to contact contaminant transport and storage zones. AST combines geological interpretation of the aquifer matrix, well-established geophysical tools and techniques, and unique groundwater sampling methods developed in-house to gain a deeper understanding of site-specific contaminant fate and transport.
Finally, AST utilizes the RPI Project Support Laboratory located in Golden, Colorado to provide no-cost analytical support for domestic and international projects. This remarkable resource eliminates traditional limitations of finite analytical data acquisition.
