1 / 18

WVONGA Annual Fall Meeting Wheeling, West Virginia September 11, 2013

The Dirty Dozen 12 Ways Your Environmental Data Might be Flawed . WVONGA Annual Fall Meeting Wheeling, West Virginia September 11, 2013 Gerald L. Kirkpatrick, P.G. Bryce E. Stearns. Six Bad Field Team Habits. Poorly Designed Sampling Programs

decima
Télécharger la présentation

WVONGA Annual Fall Meeting Wheeling, West Virginia September 11, 2013

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. The Dirty Dozen 12 Ways Your Environmental Data Might be Flawed WVONGA Annual Fall Meeting Wheeling, West Virginia September 11, 2013 Gerald L. Kirkpatrick, P.G. Bryce E. Stearns

  2. Six Bad Field Team Habits • Poorly Designed Sampling Programs • Inconsistent Sample Collection Procedures • Improper Sampling Equipment • Untrained and Inexperienced Field Personnel • Absence of Documentation • Inadequate QA/QC Sampling 2

  3. 1. Poorly Designed Sampling Programs • What’s your objective in collecting the data? • What do you want to know? • Who wants to know it? Thoughtful analysis up-front saves problems out-back 3

  4. 2. Inconsistent Sample Collection Procedures • Multiple sampling contractors result in multiple ways of collecting a sample. • Some of those ways are wrong and lead to litigation . Prepare Standard Operating Procedures and train field people 4

  5. 3. Improper Sampling Equipment • Using the proper equipment is critical to producing reliable sampling data. • Just because a sample was collected, doesn’t mean it was collected well. Prepare Sampling and Analysis Plans Follow-up With Field Audits 5

  6. 4. Untrained and Inexperienced Field Personnel • Watching contractor minions in the field is entertaining, but can be scary. • Training field personnel on how to collect a sample is not bizarre and experience indicates it is badly needed. Training and field audits are critical to the health of your sample data 6

  7. 5. Absence of Documentation • Document, document, document! • Be careful of what you write • Be careful of what you don’t write Prepare a Quality Assurance Project Plan and use it 7

  8. 6. Inadequate QA/QC Sampilng • Not that hard • Not that expensive • Data can solve your worst nightmares • “QA/QC Insurance” Submit some sort of QA/QC samples with your field samples 8

  9. Six Laboratory Pitfalls • Lack of Traceability • Not Adhering to the Method • Failure to Calibrate Instrumentation • Inadequate Quality Control • Poor Documentation Practices • Insufficient Training 9

  10. 1. Lack of Traceability You do not want your data generated “blind.” • Everything that comes in contact with the sample… • Materials • Reagents • Standards • Solvents • Sample Jars, etc. Traceability is a key component to Quality Control 10

  11. 2. Not Adhering to the Method Failure to follow the approved method or internal SOP • Provides a basis of how the result was generated 11

  12. 3. Failure to Calibrate Instruments Failure to adequately calibrate monitoring and measuring devices used in the analytical processimpacts data quality. Examples: Balances, thermometers, pipettes Crucial to ensure measurement accuracy 12

  13. 4. Inadequate Quality Control • Basic Error Checking • Failure to review or verify results • Requires a formal and documented procedure • Vital for minimizing reporting errors 13

  14. 5. Poor Documentation Practices • Required information isn’t recorded or it’s recorded incorrectly. • Everything from SOPs, bench sheets, log books, to actual lab measurements. • If it’s not documented, it didn’t happen. 14

  15. 6. Insufficient Training • The devil is in the details. • Depth of understanding is required to produce accurate and precise data. • Fundamental need for the generation of viable results 15

  16. Conclusion • Analytical work is complex and requires significant effort to be accurate and precise. • Demands are high and there can be a lot at stake. • Need data that will stand the test of time. • Because…In the end, all you have are data. 16

  17. Q&A ? 17

  18. Contact Environmental Standards, Inc. “Setting the Standards for Innovative Environmental Solutions” Headquarters 1140 Valley Forge Road | PO Box 810 | Valley Forge, PA 19482 | 610.935.5577 Virginia 1208 East Market Street | Charlottesville, VA 22902 | 434.293.4039 Tennessee 8331 East Walker Springs Lane, Suite 402 | Knoxville, TN 37923 | 865.376.7590 Texas 11200 Richmond Avenue, Suite 350 | Houston, TX 77082 | 281.752.9782 Web www.envstd.com | E-mail solutions@envstd.com 18

More Related