Previous discussions in this newsletter have covered the need for high density data, as well as the tools and methods for collecting these data. We have also discussed the need for quality assurance procedures for all tools that provide data, both semi-quantitative and quantitative. This discussion contrasts the data quality objectives (DQOs) for methods we use in the field (US EPA Method 8265) with off-site analyses (US EPA Method 8260). This illustrates why the use of both methods improves the management of sampling uncertainty due to site heterogeneity, as well as the success of site remediation.
The use of on-site, real-time, and high-density data has a different purpose from samples collected for off-site analysis, and the DQOs support these project needs. Real-time data collected using Method 8265 assists project managers in addressing the effects of site heterogeneity on sample representativeness. The ability to collect and analyze large numbers of samples allows project managers to make quick, informed decisions about where additional sampling locations are needed to accurately define the source and plume. Data from samples analyzed in a certified laboratory using Method 8260 are usually required to make decisions about site remediation actions.
DQOs for samples analyzed by Method 8260 support risk assessment and remedial e actions based on the risk assessment. Although quantitative and applied in the field using a full QA/QC program, DQOs for on-site, high-density data from samples analyzed using Method 8265 support the construction of an accurate conceptual site model that can be used to select a limited number of sampling locations for off-site analysis by Method 8260.
The combination of methods is powerful, because project managers can be assured that the final conceptual site model is based on complementary types of data that accurately represent site conditions. This process significantly reduces the uncertainty in site decisions required to manage the identified risks. Site characterization is more efficient and total project costs are reduced.