Because of the significance of CERCLA risk assessments for site decision-making, data must be of sufficient quality to meet risk assessment needs. From an analytical perspective, this means that detection limits should be below levels that would be of concern, that the method has sufficient specificity and selectivity to provide results for the contaminants of concern, that sampling is representative of the exposure unit under consideration, and that QA/QC protocols are sufficient to support analytical quality. These requirements are usually met by using standard fixed-laboratory methods. However, in many cases the same instrumentation that is used at the fixed laboratory can be used in or near the field (e.g., a mobile laboratory) to support dynamic work strategies. In these situations, with the proper QA/QC protocols, data produced by these methods may be as good as or better than what a fixed laboratory would produce.

In other cases, the measurement techniques used to produce real-time measurements may not be of the quality associated with fixed laboratory techniques because of potential interference issues, lack of specificity or selectivity, insufficient detection capabilities, etc. While these data may not be useful for directly supporting risk calculations, they can still be important to the overall quality of the risk assessment. For example, they can provide a much greater density of information about the spatial distribution of contamination and the presence of localized, highly elevated areas of special concern. They can be used to assist in the selection of sampling locations for more definitive analyses via standard fixed-laboratory techniques. They can also be used to verify assumptions about the conceptual site model that may be critical to the risk assessment (e.g., the vertical distribution of contamination in a soil or sediment profile). In other words, they can support development of the CSM that determines the representativeness of the high analytical quality data points, which are invariably taken at spatial densities too low to define the spatial scales of contaminant heterogeneity. The CSM developed from these less rigorous measurements is critical to support correct interpretation of low-density fixed laboratory data.