This document discusses producing legally defensible environmental data. It begins with an introduction to the author, Christina Hiegel, who has over 11 years of experience in the environmental field. The rest of the document outlines the six key steps to producing defensible data: define the problem and goals, plan the study, prepare for sample collection and analysis, execute the sample collection and analysis, review the results, and manage the data. It provides guidance on each step, emphasizing the importance of planning, proper sampling techniques, quality assurance protocols, data validation, and data management to ensure data defensibility.

1. Data Defensibility
The Data User’s Guide to Producing
Legally Defensible Environmental Data
By Christina Hiegel, P.E.
Civil/Environmental Engineer

2. Introduction
Christina has over 11 years’ experience
in the environmental industry. She is a
registered Civil/Environmental Engineer
and manages the chemistry group at
Trihydro. Her primary responsibilities
include providing technical support for
projects in data defensibility, data quality,
and leading data quality efforts.
Christina Hiegel

3. Overview
Define
Plan
Prepare
Execute
Review
Manage

4. Definition of Defensible Data
Define
Plan
Prepare
Execute
Review
Manage

5. What is Your Final Goal?
Short
Term
To reach your “Final Goal”, the supporting
data will have to be measured in both
extent and quality.
Long
Term

6. Developing Data Quality Objectives
Step 1: State the Problem
Step 2: Identify the Decision
Step 3: Identify Information Inputs
Step 4: Define the Boundaries of the Study
Step 5: Develop the Analytical Approach
Step 6: Specify the Performance or Acceptance Criteria
Step 7: Develop the Plan for Obtaining Data
USEPA. 2006a. Guidance on Systematic Planning Using the Data Quality Objectives Process (EPA QA/G‐4). (EPA/240/B‐06/001). Available from:
http://www.epa.gov/QUALITY/qs‐docs/g4‐final.pdf

7. Planning Defensible Data
Define
Plan
Prepare
Execute
Review
Bad Idea – Spending money without a plan
Manage

8. Choose Your Resources Wisely

9. Organizational Chart

10. Contracting with the Laboratory
-
Certifications
Capabilities
Capacities
Methodology
Reporting
Limits

11. Plans for the Future – Looking Ahead





QAPP
DMP
SAP
SMP
DQO

12. Preparing
Define
Plan
Prepare
Execute
Review
Manage

13. Collecting Defensible Data
Define
Plan
Prepare
Execute
Review
Manage
BAD DATA
Bad Idea – Collecting
data that is not usable

14. Laboratory Preparation

15. Field Preparation
•
•
•
•
•
•
•
Collection Methods
Collection Order
Decontamination
Quality Assurance
Samples
Documentation
Sample Custody
Packing/Shipping

16. Quality Assurance Samples
HOW MANY SHOULD I COLLECT??
Check your sample plans!
RULE OF THUMB
QA Sample
How Many
Percentage
Field Duplicate
1 per 10
10%
Field Blank
1 per day
--
Equipment Blank
1 per day
--
Trip Blank
1 per cooler with VOCs
--
MS/MSD
1 per 20
5%

17. Chain-of-Custody
Trihydro and
laboratories
have tools to
help you make
your data
defensible.
Trihydro’s
Generic CoC

18. Why Validate Data?
Define
Plan
Prepare
Execute
Review
Manage

19. Choosing Validation Levels

20. Tiered Validation
TIER IV
TIER III
TIER II
TIER I

21. Tiered Validation
TIER IV
TIER III
TIER II
Data
Verification

22. Data Verification

23. Tiered Validation
TIER IV
TIER III
TIER II
Data
Verification

24. Tiered Validation
TIER IV
TIER III
TIER II
Data
Verification

25. Data Validation

26. Maintaining Defensible Data
Define







Plan
Prepare
Execute
Use a database to manage your data
Complete validations
Check produced reports, limits, and
constituents
Understand what data are qualified
and why
Check against previous data
Work with laboratory and your team
to make changes, as needed
Read your data reports and validation
reports and ask questions
Review
Manage

27. I Messed Up! What Do I Do?


Don’t panic
Don’t cover-up or
hide your mistake

28. Defensible Data
Define
Plan
Prepare
Execute
Review
Manage