Closing Remarks
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1 of 37 Closing Remarks Presenter: Sebastian Tindall 15 minutes DQO Training Course Day 3 Module 23
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DQO Training Course Day 3 Module 23. Closing Remarks. Presenter: Sebastian Tindall. 15 minutes. Module 25 Closing Remarks & Final Exam. Objectives: To summarize key points made today To answer the “How many samples” question “Final Exam” Questions/feedback from the audience. - PowerPoint PPT Presentation
Transcript of Closing Remarks
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Closing Remarks
Presenter: Sebastian Tindall
15 minutes
DQO Training CourseDay 3
Module 23
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Module 25Closing Remarks & Final Exam
Objectives:
To summarize key points made today To answer the “How many samples” question “Final Exam” Questions/feedback from the audience
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The DQO Process“A systematic planning process based on the scientific method for the unambiguous defining of
Environmental decision criteria
Data requirements
Error tolerances
and the documentation / preservation of these details in a consistent, standardized format providing a defensible record of the decision”
Merrick “Rick” BlancqUS Army Corps of Engineers Portland District
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Systematic Planning Doesn’t Just “Happen”
Haphazard approaches yield haphazard results Decision makers must provide input early &
often Need an implementation process Successful implementation model evolved as the
DQO Process was used
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Tools Make the Job Easier
Scoping Checklist DQO e-Workbook (electronic template)
– Standardized DQO Report format DQO Web Site
– DQO tools and materials– Latest version of all of today’s slides
Visual Sample Plan (VSP)– Download free software
Data Quality Assessment tools (coming!)
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Managing Uncertainty We are forced to make environmental decisions
based on estimates Estimates always involve errors Errors in estimates are not mistakes If unmanaged, errors in estimates CAN lead to
Decision Errors which ARE MISTAKES Decision Errors must be managed
– Identify– Quantify
Severe consequences of decision errors mandate a statistical basis
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Defensibility
S ampling and A nalys is P lan
Sc oping
Data QualityA ssessment
Dec is ion
Sampling&
A nalys is
Data Quality Objec tives
(DQO)
L aboratory Data Verific ation /
Validation
F ie l d S a mpl ingP l a n(F S P )
Qua l it y A s sura nc e P ro je c t P l a n
(Q A P j P )
H e a lt h a ndSa fe t y P l a n
(H S P )
Comes from doing good science
Requires documentation– “If it isn’t written down, it
didn’t happen” Use a standardized format We must employ the
scientific method to make defensible decisions
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How Many Samples do I Need?
REMEMBER:
HETEROGENEITY
IS THE RULE!
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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
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Logic to Assess Distribution and Calculate Number of Samples
SkewedCalculate the number of
samples based on skeweddistributions (e.g.,
nonparametric tests suchas WSR or WRS)
Is frequencydistribution fromeach populationsymmetrical orapproximatelysymmetrical?
YesSymmetrical
Use equations based onsymmetrical distribution.
No
Option 1 Option 2
Badly SkewedBadly skewed or for any
distribution, use computersimulations
(e.g.,Monte Carlo) to performcalculations to estimate the
number of samples
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A Visual Decision Strategy
StartGetData
CheckData
Fit Data
DoHypothesis
TestStop
Data
Visual Fit
Visual DQA
Visual Test Clean
Dirty
GetSample
Size
GetSamplingLocations
VSP VESA
NeedMoreDatan x, y
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Project Planning Documents
Work Plan DQO Report FSP Quality Assurance Project Plan HSP
Must contain a clear presentation of (and the reasoning behind):
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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
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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
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Keys to success– Sound technical basis– Complete and thorough documentation
Do it!Do it!(Get the job done - right)
Prove it!Prove it!(Document what/why/how)
SiteClosed
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Managing UncertaintyManaging Uncertainty
Systematic Planning
Dynamic Work Plan
Real-Time Measurement Technologies
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Systematic PlanningManaging Uncertainty with Systematic Planning
for Environmental Decision Making
http://www.doe.hanford.gov/dqo
Sebastian Tindall
Bechtel Hanford Inc. 3190 George Washington Way
MS H9-03; Room 49Richland, WA 99352
(509) [email protected]
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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)
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Managing Uncertainty with Systematic Planning for Environmental Decision-
Making
• Visual DQO: TBD• Visual DQA: ver 2.0
-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
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Brent Pulsipher, ManagerStatistical & Quantitative SciencesPacific Northwest National LaboratoryRichland, WA 99354(509) [email protected]
John Wilson, ProgrammerStatistical & Quantitative Sciences Pacific Northwest National LaboratoryGrand Junction, CO 81503 (970) 270-2998 [email protected]
VSP Contacts
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Sampling for
Environmental ActivitiesChuck RamseyEnviroStat, Inc.
PO Box 636Fort Collins, CO 80522
970-689-5700970-229-9977 fax
www.envirostat.org
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Multi-Increment Sub-Sampling and Analyses
Mark BoedigheimerCH2M HILL
Applied Sciences Laboratory2300 NW Walnut Blvd.,
Corvallis, OR 97330
541-752-4271
541-758-0245 Ext. 3125
Fax: 541-752-0276
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DQO Consultants: Software for Environmental
Statistics
Jim Davidson
Davidson and Davidson, Inc.8390 Gage Blvd., Suite 205
Kennewick, WA 99336
(509) 374-4498;
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On-Site Environmental Sampling & Analyses
J. Edward “Ned” Tillman Columbia Technologies
1450 So Rolling RdBaltimore, MD 21227
410-536-9911410-536-0222 (Fax)
[email protected]://www.smart.columbiadata.com
http://www.columbiadata.com
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Dynamic Work PlansA Guideline
for
Dynamic Workplans and Field Analytics:
The Keys to Cost-Effective Site Characterization and Cleanup
http://cluin.org/char1_edu.cfm#dyna_work
Albert Robbat, Jr.
Tufts University, Chemistry Department
Center for Field Analytical Studies and Technology
Medford, Massachusetts, 02155
tel: 617-627-3474 and fax: 617-627-3443
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DQO Consultants:Preparation & Facilitation
Mitzi Miller
Environmental Quality Management (EQM), Inc.1777 Terminal Drive
Richland, WA 99352
(509) 946-4985; Fax: (509) 946-4595
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DOE Sponsored Web Pages
http:/www.hanford.gov/dqo/
http://dqo.pnl.gov/
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Program POCsDr. Jeffrey W Day
Department of Energy
Office of Science
Laboratory Management DivisionEMSL
Richland, WA 99354(509) 372-4629
George DetsisDepartment of Energy
EM-3119901 Germantown Road
Building 270
Germantown, MD 20874-1290(301) 903-1488
Sebastian Tindall
Bechtel Hanford Inc. 3190 George Washington Way
MS H9-03; Room 49Richland, WA 99354
(509) [email protected]
Brent PulsipherManager
Statistical & Quantitative Sciences Pacific Northwest National
Laboratories3180 George Washington Way
K6-08Richland, WA 99354
(509) 375-3989 [email protected]
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Funding POCsDr. Jeffrey W DayDepartment of Energy
Office of Science
Laboratory Management DivisionEMSL
Richland, WA 99352(509) 372-4629
George DetsisDepartment of Energy
EM-3119901 Germantown Road
Building 270
Germantown, MD 20874-1290(301) 903-1488
Jo Ann Griffith
Assistant Director OSWER USEPA Headquarters
Ariel Rios Building; 5202G1200 Pennsylvania Avenue, N. W.
Washington, DC 20460703-603-8774
Ken SkahnContract Manager OSWER
USEPA Headquarters Ariel Rios Building; 5202G
1200 Pennsylvania Avenue, N. W. Washington, DC 20460
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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
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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
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FINAL EXAM
• What is the Question?
• What is the Population?
• What is the Confidence required?
What is the DQO Process in a Nutshell?
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How Many Samples do I Need?
REMEMBER:
HETEROGENEITY
IS THE RULE!
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“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”
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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
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Class Feedback & Discussion
What are your thoughts about the course?– Feedback– Questions– Concerns– Impressions– Suggestions
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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
