Summary of Key Elements to the DQO Process
Presented below is a list of key elements that technical reviewers will be looking for when reviewing
DQO process summary reports. Prior to issuing a DQO process summary report for review, the document writer should review the key elements listed
below to ensure they have been adequately addressed.
| Step 1: State the Problem |
Key Elements:
- Comprehensive scoping effort
- Conceptual Site Model based on comprehensive scoping effort
- Concise Statement of the Problem(s), based on the Conceptual Site Model, that provides
unambiguous focus for the Project
General Format:
In order to [show that lead is contributing to the decrease in
duck populations in the wetlands], data regarding [levels of lead in the surface water, sediments, and vegetation
in the marshlands] is needed.
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| Step 2: Identify Decisions |
Key Elements:
- Decision Statement(s) designed to address the concerns highlighted in the problem
statement
- Principle
Study Questions (PSQ) that identify key unknown conditions
or unresolved issues requiring environmental data
- Alternative Actions that state all possible actions that might be taken once
a PSQ has been resolved
General Format:
Determine whether [unknown environmental condition/issue/criterion
from the Problem Statement] requires [choosing between two or more Alternative Actions].
Specific Format:
Determine whether [Principal Study Question #1] requires [Alternative
Action A] or [Alternative Action B].
EXAMPLE:
Determine whether [lead is contributing to the decrease in duck populations]
and requires [remediation by removal of the lead from the bottom of the ponds] or [regulation
on the types of pellets that future hunters may use] or [requires no action].
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Key Elements:
- Informational Inputs required to resolve the PSQs
identified in Step 2
- Environmental variables that require measurements
- Sources for data
- Level of Quality needed for the Decision(s)
- Usability of Existing Data sets
- Quality Assured
- Statistically valid
- Agrees with Conceptual Site Model
- Information needed to establish action levels
- Analytical Methods and Detection Limits
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| Step 4: Specify Boundaries |
Key Elements:
- Scale of decision making
- Population of interest
- Geographical (Spatial) boundaries of the decision statement
- Temporal boundaries of the decision statement
- Constraints to sampling
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| Step 5: Define Decision Rules |
Key Elements:
- Decision Rules (if/then statements) that combine:
- Parameter of interest
- Population Parameter
- Sample Statistic
- Environmental Variable
- Chemical/Physical Attribute in the population
- Quantity
- Scale of Decision Making
- Geographic Area/Volume
- Timeframe
- Population
- Action Level
- Alternative Action(s)
EXAMPLE:
If the [true mean
(as estimated by the 90% UCL of the sample mean) concentration of cadmium]
within [the fly ash leachate in a container truck for a period of 1000 years]
is greater than [1 mg/kg], then [the
fly ash waste will be considered hazardous and will be disposed of in a RCRA facility]; or [the
fly ash waste will be disposed of in a municipal landfill].
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| Step 6: Specify Error Tolerances |
Key Elements:
- Expected Range of data values
- Possible decision errors.
- Null and alternative hypotheses.
- Consequences of decision errors.
- Severity of consequences.
- Tolerable limits on decision errors.
- Gray Region boundaries.
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| Step 7: Optimize Sample Design |
Key Elements:
- Select a statistical
method (equation) based on the frequency distribution of the COPCs.
- Calculate the Number of samples needed to make decision using various tolerable
error limits.
- Develop the AUSCAS (Aggregate Unit Sample Collection and Analysis Cost) equation.
- Develop a Cost of Sampling versus Uncertainty relationship (Table)
- Select the most resource-effective data collection and analysis design that satisfies
the DQOs specified in the proceeding 6 Steps.
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