Quality Assurance Project Plan Including Sampling And Analysis Plan (Page 52 of 67) in pdf

Hunters Point Shipyard Parcel F ESTCP Demonstration Plan

Appendix A: Quality Assurance Project Plan

A.5.2

Data Quality Assessment Reconciliation with Planning Objectives

DQA is a data analysis and interpretation process involving scientific and statistical evaluation of data

sets to determine if they are sufficient to support specific decisions. To implement the DQA process, the

analyst will work closely with a multidisciplinary team, potentially including the Principal Investigator,

Project Manager, Research Studies Leaders, and statistician. The overall assessment of the ESTCP DP is

the responsibility of the Stanford University Principal Investigator.

Upon receipt of the laboratory analytical chemistry data, the data analyst shall assemble the data set,

including field information such as sample coordinates and descriptions and associated field measure-

ments, and review any additional reports (e.g., survey and validation reports). The DQA shall begin with

exploratory data analysis, including a significant graphical component. Standard data assessment tools

will be used, such as histograms, q-q plots, cumulative frequency distributions, and box plots. Because

the DQA process evaluates individual data points within the context of entire data sets, it will identify

both “suspect” data (probable outliers to the actual data distribution) and critical observations that could

affect decisions based on these data. As necessary, “suspect” data will be submitted for “focused

validation” to determine whether the “suspect” data resulted from errors in the data generation process.

“Suspect” and other unusual observations will be reviewed by experts on the natural environment and the

measurement process to determine if there are scientific explanations and if data can be corrected or need

to be rejected. If observations are not corrected or rejected by the above process and are therefore

determined to represent variability inherent in the measurement process or the environment, these data

shall be retained within the data set. Any changes made to the data set shall be fully documented.

The DQA process addresses the questions “Did we get what we asked for?” and “Did we ask for what we

need?” The standards which will be used to evaluate the adequacy of the study findings from the actual

data received are the original DQO specifications for the HPS ESTCP DP survey design, which will be

reviewed for continued relevance to the ecological risk decisions being made. To assess the adequacy of

this sampling design to support the study questions, the data analyst must work with other members of the

project team to determine if the number, type, and quality of samples as specified in the Demonstration

Plan and QAPP and as actually collected, were appropriate. This includes: determining if the correct

number and location of samples were taken; determining if the appropriate media were sampled; judging

the adequacy of the sample number and locations, given the updated understanding of the problem; and

determining if the understanding of the problem changed since the QAPP was prepared because of

observations made by the field team.

For critical data, the BDO project manager will implement the DQA process as described in U.S. EPA

guidance (U.S. EPA QA/G-9, 2000a) to determine adequacy of the critical data to support a decision. The

ESTCP DP will generate data to support evaluation of remedial alternatives in the HPS Parcel F FS, as

described in the DQOs. The DQA will start by determining if these critical assumptions held true, and

whether the sampling design provided data of adequate quality to support the decision. The ESTCP DP

Demonstration Plan describes data analysis procedures.

Assuming that the sampling design was adequate to support the decision, the evaluation of data adequacy

to support that decision may terminate after the initial exploratory analysis, and the site should move

forward in the decision-making process. This determination will be made based on the observed

chemistry, the variability of these measurements, and a determination of the uncertainty associated with

the types of comparisons that are being made with the data.

If an adequate level of confidence was achieved with the chemical constituent concentrations actually

observed, this observation supports the case that data are sufficient to be incorporated into the FS.

Page A-

of A-67

Quality Assurance Project Plan Including Sampling And Analysis Plan Page 52

Related Articles

Related forms

Related Categories