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Understanding End-Users’ Approaches to
Ensuring the Quality of Environmental Data
By Christina Hiegel, P.E.
Civil/Environm...
Introduction
Christina has over 11 years’ experience
in the environmental industry. She is a
registered civil/environmenta...
Importance of Data Quality
Laboratory
• Certification
• Methodology
• Standard
Operating
Procedures
• Legal
Defensibility
...
Importance of Data Quality
Laboratory
• Certification
• Methodology
• Standard
Operating
Procedures
• Legal
Defensibility
...
Importance of Data Quality
Laboratory
• Certification
• Methodology
• Standard
Operating
Procedures
• Legal
Defensibility
...
Differing Quality Standards
Reporting Limits
Holding Times
Preservations
Choosing Analytical Methods
Data Validation Standards
Data Validation Standards

USEPA.  2010. USEPA Contract Laboratory Program National Functional Guidelines for Inorganic Su...
Data Validation Standards
Data Validation Standards

USEPA.  2008. USEPA Contract Laboratory Program National Functional Guidelines for 
Superfund O...
Calibration Standards
Calibration Standards

USEPA.  2008. USEPA Contract Laboratory Program National Functional Guidelines for Superfund Organi...
Precision
Data Reporting
TIER IV

TIER III

TIER II
TIER I
Final Data Management
Electronic 
Data 
Deliverable

Laboratory 
Report

Data 
Validation

Final Reports
Figures
Tables
Meeting Quality Objectives
Communicate:
• General project information
• Regulatory requirements
• Reporting limits and ana...
Understanding End-Users' Approaches to Ensuring the Quality of Environmental Data
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Understanding End-Users' Approaches to Ensuring the Quality of Environmental Data

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Understand how regulations can cause conflicting views between laboratories and end users on the data quality.

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Understanding End-Users' Approaches to Ensuring the Quality of Environmental Data

  1. 1. Understanding End-Users’ Approaches to Ensuring the Quality of Environmental Data By Christina Hiegel, P.E. Civil/Environmental Engineer
  2. 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. 3. Importance of Data Quality Laboratory • Certification • Methodology • Standard Operating Procedures • Legal Defensibility Consultant/ Responsible Party Regulatory Agency
  4. 4. Importance of Data Quality Laboratory • Certification • Methodology • Standard Operating Procedures • Legal Defensibility Consultant/ Responsible Party • Regulatory Requirements • Legal Defensibility • Project Objectives Regulatory Agency
  5. 5. Importance of Data Quality Laboratory • Certification • Methodology • Standard Operating Procedures • Legal Defensibility Consultant/ Responsible Party • Regulatory Requirements • Legal Defensibility • Project Objectives Regulatory Agency • Public Scrutiny • Public Protection • Legal Defensibility
  6. 6. Differing Quality Standards
  7. 7. Reporting Limits
  8. 8. Holding Times
  9. 9. Preservations
  10. 10. Choosing Analytical Methods
  11. 11. Data Validation Standards
  12. 12. Data Validation Standards USEPA.  2010. USEPA Contract Laboratory Program National Functional Guidelines for Inorganic Superfund Data Review (USEPA 540‐ R‐10‐011). Available from: http://www.epa.gov/superfund/programs/clp/download/ism/ism1nfg.pdf.
  13. 13. Data Validation Standards
  14. 14. Data Validation Standards USEPA.  2008. USEPA Contract Laboratory Program National Functional Guidelines for  Superfund Organic Methods Data Review (USEPA‐540‐R‐08‐01). Available from:  http://www.epa.gov/superfund/programs/clp/download/somnfg.pdf.
  15. 15. Calibration Standards
  16. 16. Calibration Standards USEPA.  2008. USEPA Contract Laboratory Program National Functional Guidelines for Superfund Organic  Methods Data Review (USEPA‐540‐R‐08‐01). Available from:  http://www.epa.gov/superfund/programs/clp/download/somnfg.pdf
  17. 17. Precision
  18. 18. Data Reporting TIER IV TIER III TIER II TIER I
  19. 19. Final Data Management Electronic  Data  Deliverable Laboratory  Report Data  Validation Final Reports Figures Tables
  20. 20. Meeting Quality Objectives Communicate: • General project information • Regulatory requirements • Reporting limits and analyses requirements • Analyses, constituents of concern, target analytes • Subcontracting requirements • How to communicate with each other • Validation objectives • Audit changes to the data • Other information (e.g., sampling requirements, blanks, turn, and special reporting packages)

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