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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.

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closing remarks

DQO Training Course

Day 3Module 23

Closing Remarks

Presenter: Sebastian Tindall

15 minutes

module 25 closing remarks final exam

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
the dqo process
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” Blancq

US Army Corps of Engineers Portland District

Merrick.P.Blancq@nwp01.usace.army.mil

systematic planning doesn t just happen
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
tools make the job easier
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!)
managing uncertainty
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
defensibility
Defensibility
  • 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
how many samples do i need
How Many Samples do I Need?

REMEMBER:

HETEROGENEITY

IS THE RULE!

begin with the end in mind
Begin With the End in Mind

DATA

Contaminant Concentrations in the Spatial Distribution of the Population

Population Frequency Distribution

Correct Equation for n (Statistical Method)

, , , 

Alternative Sample Designs

Optimal Sampling Design

How many samples do I need?

The end

project planning documents

Must contain a clear presentation of (and the reasoning behind):

Project Planning Documents
  • Work Plan
  • DQO Report
  • FSP
  • Quality Assurance Project Plan
  • HSP
project planning documents1
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
analytical sampling sub sampling natural heterogeneity of the site total uncertainty

Uncertainty is Additive!

Analytical + Sampling & Sub-sampling +Natural heterogeneity of the site=Total Uncertainty

Remember the uncertainty is additive for all steps in sampling and analysis

keys to success

Do it!

(Get the job done - right)

Site

Closed

Prove it!

(Document what/why/how)

Keys to success
  • Sound technical basis
  • Complete and thorough documentation
slide16

SystematicPlanning

Dynamic Work Plan

Real-TimeMeasurementTechnologies

Managing Uncertainty

systematic planning
Systematic Planning

Managing 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 49

Richland, WA 99352

(509) 372-9195

sctindal@mail.bhi-erc.com

managing uncertainty with systematic planning for environmental decision making
Managing Uncertainty with Systematic Planning for Environmental Decision-Making

BHI Training Courses:

  • DQO Training: 3 days
  • DQA Training: 1 day
  • Visual Sample Plan Primer: 3 hours
  • DQO Applications
  • PNNL Training Course:
    • Visual Sample Plan: 2.5 days (20 hours)
managing uncertainty with systematic planning for environmental decision making1
Managing Uncertainty with Systematic Planning for Environmental Decision-Making

BHI Software Tools:

  • 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)
  • PNNL Software Tools:
    • Visual Sample Plan: ver 4.0
slide20

VSP Contacts

Brent Pulsipher,ManagerStatistical & Quantitative SciencesPacific Northwest National LaboratoryRichland, WA 99354(509) 375-3989brent.pulsipher@pnl.gov

John Wilson, ProgrammerStatistical & Quantitative SciencesPacific Northwest National LaboratoryGrand Junction, CO 81503 (970) 270-2998 john.wilson@pnl.gov

sampling for environmental activities
Sampling for Environmental Activities

Chuck RamseyEnviroStat, Inc.PO Box 636Fort Collins, CO 80522970-689-5700970-229-9977 fax

chuck@envirostat.org

www.envirostat.org

multi increment sub sampling and analyses
Multi-Increment Sub-Sampling and Analyses

Mark Boedigheimer

CH2M HILL

Applied Sciences Laboratory

2300 NW Walnut Blvd.,

Corvallis, OR 97330

541-752-4271

541-758-0245 Ext. 3125

Fax: 541-752-0276

mboedigh@ch2m.com

dqo consultants software for environmental statistics
DQO Consultants: Software for Environmental Statistics

Jim Davidson

Davidson and Davidson, Inc.

8390 Gage Blvd., Suite 205

Kennewick, WA 99336

(509) 374-4498;

davidson@owt.com

on site environmental sampling analyses
On-Site Environmental Sampling & Analyses

J. Edward “Ned” Tillman

Columbia Technologies

1450 So Rolling Rd

Baltimore, MD 21227

410-536-9911

410-536-0222 (Fax)

ntillman@columbiadata.com

http://www.smart.columbiadata.com

http://www.columbiadata.com

dynamic work plans
Dynamic Work Plans

A 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

dqo consultants preparation facilitation
DQO Consultants:Preparation & Facilitation

Mitzi Miller

Environmental Quality Management (EQM), Inc.

1777 Terminal Drive

Richland, WA 99352

(509) 946-4985; Fax: (509) 946-4595

mitzim@eqminc.com

doe sponsored web pages
DOE Sponsored Web Pages

http:/www.hanford.gov/dqo/

http://dqo.pnl.gov/

program pocs
Program POCs

Sebastian Tindall

Bechtel Hanford Inc.

3190 George Washington Way

MS H9-03; Room 49

Richland, WA 99354

(509) 372-9195

sctindal@mail.bhi-erc.com

Brent PulsipherManager

Statistical & Quantitative SciencesPacific Northwest National Laboratories3180 George Washington Way

K6-08Richland, WA 99354(509) 375-3989 brent.pulsipher@pnl.gov

Dr. Jeffrey W DayDepartment of Energy

Office of Science

Laboratory Management DivisionEMSLRichland, WA 99354(509) 372-4629Jeffrey_W_Day@rl.govGeorge DetsisDepartment of Energy

EM-3119901 Germantown RoadBuilding 270

Germantown, MD 20874-1290(301) 903-1488 george.detsis@hq.doe.gov

funding pocs
Funding POCs

Jo Ann Griffith

Assistant Director OSWERUSEPA Headquarters

Ariel Rios Building; 5202G

1200 Pennsylvania Avenue, N. W. Washington, DC 20460

703-603-8774

griffith.joann@epa.gov

Ken SkahnContract Manager OSWER

USEPA Headquarters

Ariel Rios Building; 5202G

1200 Pennsylvania Avenue, N. W. Washington, DC 20460

703-603-8801

skahn.ken@epa.gov

Dr. Jeffrey W DayDepartment of Energy

Office of Science

Laboratory Management DivisionEMSLRichland, WA 99352(509) 372-4629Jeffrey_W_Day@rl.govGeorge DetsisDepartment of Energy

EM-3119901 Germantown RoadBuilding 270

Germantown, MD 20874-1290(301) 903-1488 george.detsis@hq.doe.gov

credits
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
credits1
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
final exam
FINAL EXAM
  • What is the Question?
  • What is the Population?
  • What is the Confidence required?

What is the DQO Process in a Nutshell?

how many samples do i need1
How Many Samples do I Need?

REMEMBER:

HETEROGENEITY

IS THE RULE!

slide34
“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”

summary
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

class feedback discussion
Class Feedback & Discussion

What are your thoughts about the course?

  • Feedback
  • Questions
  • Concerns
  • Impressions
  • Suggestions
end of course
End of Course

Thank you

This concludes our presentation for Day 3

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.