28 Feb 95
the treatability study. The following factors should be
considered when selecting methods to analyze and appropriate
quality control measures for implementation of the treatability
-stage of project;
-anticipated number of samples;
-likely range of contaminant concentration;
-analytical turnaround time;
-identification or quantification or both required;
-required quantitation limit;
(2) Data Quality Objectives (DQOs). Data Quality Objectives
are defined as an integrated set of thought processes which
define data quality requirements based on the intended use of the
data. All project specific data quality objectives must be
clearly defined within the appropriate project plan. During a
treatability study, the data is used to verify that regulatory
levels can be attained or disposal criteria can be met. Data
errors which occur during a treatability study could have a
considerable impact during later phases of the project. For this
reason, DQOs established are normally quantitative and stringent.
(3) Analytical Protocol. DQOs are established
quantitatively with appropriate ranges. The analytical protocol
used to support these DQOs should require positive identification
standardized test methods should be used.
(4) PARCC Parameters. Precision, accuracy,
parameters must be established for the chemical tests performed
during a treatabilty study.
(a) Precision is the measure of the level of random error
associated with a given set of measurements, calculated using
standard deviation or relative percent difference in replicate
analysis, and is determined by the objectives of the project.
Precision is commonly assessed by taking a sufficient number of
samples, including replicates.
(b) Accuracy is the estimate of the relative agreement of
the measured value with the true or expected value. Accuracy is
controlled by prescribing appropriate sampling procedures, sample
handling (including preservation) and analytical procedures.