1 of 37 Closing Remarks Presenter: Sebastian Tindall 15 minutes DQO Training Course Day 3 Module 23
2 of 37 Module 25 Closing Remarks & Final Exam Objectives: n To summarize key points made today n To answer the “How many samples” question n “Final Exam” n Questions/feedback from the audience
3 of 37 The DQO Process “A systematic planning process based on the scientific method for the unambiguous defining of n Environmental decision criteria n Data requirements n Error tolerances and the documentation / preservation of these details in a consistent, standardized format providing a defensible record of the decision” Merrick “Rick” Blancq US Army Corps of Engineers Portland District
4 of 37 Systematic Planning Doesn’t Just “Happen” n Haphazard approaches yield haphazard results n Decision makers must provide input early & often n Need an implementation process n Successful implementation model evolved as the DQO Process was used
5 of 37 Tools Make the Job Easier n Scoping Checklist n DQO e-Workbook (electronic template) –Standardized DQO Report format n DQO Web Site –DQO tools and materials –Latest version of all of today’s slides n Visual Sample Plan (VSP) –Download free software n Data Quality Assessment tools (coming!)
6 of 37 Managing Uncertainty n We are forced to make environmental decisions based on estimates n Estimates always involve errors n Errors in estimates are not mistakes n If unmanaged, errors in estimates CAN lead to Decision Errors which ARE MISTAKES n Decision Errors must be managed –Identify –Quantify n Severe consequences of decision errors mandate a statistical basis
7 of 37 Defensibility n Comes from doing good science n Requires documentation –“If it isn’t written down, it didn’t happen” n Use a standardized format n We must employ the scientific method to make defensible decisions
8 of 37 How Many Samples do I Need? REMEMBER: HETEROGENEITY IS THE RULE!
9 of 37 How many samples do I need? Begin With the End in Mind Optimal Sampling Design Alternative Sample Designs , , , Correct Equation for n (Statistical Method) Population Frequency Distribution Contaminant Concentrations in the Spatial Distribution of the Population The end DATA
10 of 37 Logic to Assess Distribution and Calculate Number of Samples
11 of 37 A Visual Decision Strategy
12 of 37 Project Planning Documents n Work Plan n DQO Report n FSP n Quality Assurance Project Plan n HSP Must contain a clear presentation of (and the reasoning behind):
13 of 37 Project Planning Documents General project decision goals More detailed, technical project goals/decision rules (DQOs), that will guide project decision-making Goals for data quality (MQOs) How sampling representativeness will be ensured, and how sampling uncertainty will be controlled List of analytical technologies and methods QC protocols and criteria to demonstrate that data of known quality will be generated Description how data will be assessed and interpreted according to the decision rules
14 of 37 Analytical + Sampling & Sub-sampling + Natural heterogeneity of the site = Total Uncertainty Uncertainty is Additive! Remember the uncertainty is additive for all steps in sampling and analysis
15 of 37 Keys to success –Sound technical basis –Complete and thorough documentation Do it! (Get the job done - right) Prove it! (Document what/why/how) Site Closed
16 of 37 Managing Uncertainty Systematic Planning Dynamic Work Plan Real-Time Measurement Technologies
17 of 37 Systematic Planning Managing Uncertainty with Systematic Planning for Environmental Decision Making Sebastian Tindall Bechtel Hanford Inc George Washington Way MS H9-03; Room 49 Richland, WA (509)
18 of 37 Managing Uncertainty with Systematic Planning for Environmental Decision- Making DQO Training: 3 days DQA Training: 1 day Visual Sample Plan Primer: 3 hours DQO Applications BHI Training Courses: PNNL Training Course: Visual Sample Plan: 2.5 days (20 hours)
19 of 37 Managing Uncertainty with Systematic Planning for Environmental Decision- Making Visual DQO: TBD Visual DQA: ver Visual Decision Suite (VDS) -Visual Decision Tutor (VDT) -Visual Population Creator (VPC) -Hands-On Statistics Toolbox (HOST) BHI Software Tools: PNNL Software Tools: Visual Sample Plan: ver 4.0
20 of 37 Brent Pulsipher, Manager Statistical & Quantitative Sciences Pacific Northwest National Laboratory Richland, WA (509) John Wilson, Programmer Statistical & Quantitative Sciences Pacific Northwest National Laboratory Grand Junction, CO (970) VSP Contacts
21 of 37 Sampling for Environmental Activities Chuck Ramsey EnviroStat, Inc. PO Box 636 Fort Collins, CO fax
22 of 37 Multi-Increment Sub-Sampling and Analyses Mark Boedigheimer CH2M HILL Applied Sciences Laboratory 2300 NW Walnut Blvd., Corvallis, OR Ext Fax:
23 of 37 DQO Consultants: Software for Environmental Statistics Jim Davidson Davidson and Davidson, Inc Gage Blvd., Suite 205 Kennewick, WA (509) ;
24 of 37 On-Site Environmental Sampling & Analyses J. Edward “Ned” Tillman Columbia Technologies 1450 So Rolling Rd Baltimore, MD (Fax)
25 of 37 Dynamic Work Plans A Guideline for Dynamic Workplans and Field Analytics: The Keys to Cost-Effective Site Characterization and Cleanup Albert Robbat, Jr. Tufts University, Chemistry Department Center for Field Analytical Studies and Technology Medford, Massachusetts, tel: and fax:
26 of 37 DQO Consultants: Preparation & Facilitation Mitzi Miller Environmental Quality Management (EQM), Inc Terminal Drive Richland, WA (509) ; Fax: (509)
27 of 37 DOE Sponsored Web Pages
28 of 37 Program POCs Dr. Jeffrey W Day Department of Energy Office of Science Laboratory Management Division EMSL Richland, WA (509) George Detsis Department of Energy EM Germantown Road Building 270 Germantown, MD (301) Sebastian Tindall Bechtel Hanford Inc George Washington Way MS H9-03; Room 49 Richland, WA (509) Brent Pulsipher Manager Statistical & Quantitative Sciences Pacific Northwest National Laboratories 3180 George Washington Way K6-08 Richland, WA (509)
29 of 37 Funding POCs Dr. Jeffrey W Day Department of Energy Office of Science Laboratory Management Division EMSL Richland, WA (509) George Detsis Department of Energy EM Germantown Road Building 270 Germantown, MD (301) Jo Ann Griffith Assistant Director OSWER USEPA Headquarters Ariel Rios Building; 5202G 1200 Pennsylvania Avenue, N. W. Washington, DC Ken Skahn Contract Manager OSWER USEPA Headquarters Ariel Rios Building; 5202G 1200 Pennsylvania Avenue, N. W. Washington, DC
30 of 37 Credits Surajit Amrit, Bechtel-Jacobs, Knoxville, TN Mike Schwab, Bechtel Hanford, RL, WA Mark Byrnes, Fluor Hanford, RL, WA Roy Bauer, Fluor Hanford, Richland, WA Roger Ovink, CH2M Hill, Richland, WA Mitzi Miller, EQM, Richland, TN Debbie Carlson, PNNL, Richland, WA Susan Blackburn, SAIC, Richland, WA Tracy Friend, SAIC, Richland, WA
31 of 37 Credits Dave Blumenkranz, SAIC, Richland, WA Gayelyn Gibson, EQM, Richland, WA Kelly Black, Neptune and Associates, Denver, CO Candy Hawk, Blue Sky Software, Richland, WA Al Robinson, EQM, Richland, WA Jeff Day, DOE-RL, Richland, WA Merrick “Rick” Blancq, USACE, Portland, OR Jim Davidson, D&D Inc., Kennewick, WA Chuck Ramsey, Envirostat, Ft Collins, CO
32 of 37 FINAL EXAM What is the Question? What is the Population? What is the Confidence required? What is the DQO Process in a Nutshell?
33 of 37 How Many Samples do I Need? REMEMBER: HETEROGENEITY IS THE RULE!
34 of 37 “The bitterness of poor quality remains long after the sweetness of low price is forgotten” - Anonymous “If it isn’t written down, it didn’t happen”
35 of 37 Summary Use Classical Statistical sampling approach: Very likely to fail to get representative data in most cases Use Other Statistical sampling approaches: Bayesian Geo-statistics Kriging Use M-Cubed Approach: Based on Massive FAM Use Multi-Increment sampling approach: Can use classical statistics Cheaper Faster Defensible: restricted to surfaces (soils, sediments, etc.) MASSIVE DATA Required
36 of 37 Class Feedback & Discussion What are your thoughts about the course? –Feedback –Questions –Concerns –Impressions –Suggestions
37 of 37 End of Course Please take a few minutes to fill out and turn in all 3 of the course evaluation forms. Thank you for your attention this week. Thank you This concludes our presentation for Day 3