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E.. Stockton 99 Speedway Quality Assurance Project Plan April 12,2007 F 3.0 DATA QUALITY OBJECTIVES 3.1 Data Quality Objective Process The Data Quality Objectives (DQO) process is a planning process from which qualitative and quantitative statements are derived in relation to a particular data collection event (or group of events). Performing the DQO process is generally one of the prerequisite steps to data collection. The DQO process is described in EPA guidance (EPA, 2000). The steps of the DQO process are: • State the Problem; • Identify the Decision; • Identify Inputs to the Decision; • Define the Study Boundaries; • Develop a Decision Rule; • Specify Tolerable Limits on Decision Errors; and • Optimize the Design for Obtaining Data; The steps of the DQO process are summarized below for the Stockton 99 Speedway project. Step 1: State the Problem: • In order to evaluate whether contaminants of potential concern (COPCs) and other contaminants pose a potential risk to human health and/or the environment, data regarding concentrations and distributions of COPCs and other contaminants in the soil is needed. Step 2: Identify-the Decision: • Determine whether COPCs, and other contaminants, present at the Site pose an unacceptable risk to human health and/or the environment, and require development of remedial alternatives to mitigate the risks. I Step 3: Identify Inputs to the Decision: Soil samples will be collected and analyzed for COPCs, and other contaminants, from areas of the Site. Step 4: Define the Study Boundaries: • The boundaries of this study are limited to the Stockton 99 Speedway property and immediate vicinity where samples will be colle(;ted. € Qualty_AssLra)ce_ProjeIX Plan.Rnal.doc 3-1 The Source Group,Inc.