1 of 39 The EPA 7-Step DQO Process Step 7 - Optimize Sample Design DQO Case Study 45 minutes Presenter: Sebastian Tindall DQO Training Course Day 3 Module.

Slides:



Advertisements
Similar presentations
Day 2 DQO Training Course Module 9 The EPA 7-Step DQO Process
Advertisements

Quality is a Lousy Idea-
Chapter 9 Introduction to the t-statistic
Day 2 DQO Training Course Module 3 The EPA 7-Step DQO Process
Lessons Learned Multi Incremental Sampling Alaska Forum on the Environment February, 2009 Alaska Department of Environmental Conservation.
1 1 Slide © 2008 Thomson South-Western. All Rights Reserved Slides by JOHN LOUCKS St. Edward’s University.
Sensitivity Analysis In deterministic analysis, single fixed values (typically, mean values) of representative samples or strength parameters or slope.
Significance Testing Chapter 13 Victor Katch Kinesiology.
HYPOTHESIS TESTING Four Steps Statistical Significance Outcomes Sampling Distributions.
Hypothesis Testing: Type II Error and Power.
Sampling Methods and Sampling Distributions Chapter.
Testing the Difference Between Means (Small Independent Samples)
Chapter 9 Hypothesis Testing.
DQOs and the Development of MQOs Carl V. Gogolak USDOE Environmental Measurements Lab.
Decision analysis and Risk Management course in Kuopio
Copyright © 2007 Pearson Education Canada 1 Chapter 12: Audit Sampling Concepts.
1 of 39 DQO Implementation Process: Flow Chart and Wall Charts 30 minutes DQO Training Course Day 2 Module 8 Presenter: Sebastian Tindall.
Overview Definition Hypothesis
1 of 25 The EPA 7-Step DQO Process Step 5 - Define Decision Rules 15 minutes Presenter: Sebastian Tindall DQO Training Course Day 2 Module 14.
1 of 55 The EPA 7-Step DQO Process Step 1 - State the Problem Presenter: Sebastian Tindall 60 minutes DQO Training Course Day 2 Module 9.
1 of 35 The EPA 7-Step DQO Process Step 4 - Specify Boundaries (30 minutes) Presenter: Sebastian Tindall Day 2 DQO Training Course Module 4.
1 MARLAP SCIENCE ADVISORY BOARD CHAPTERS 6 & 7 Stan Morton DOE-RESL April 2002.
Week 10 Chapter 10 - Hypothesis Testing III : The Analysis of Variance
Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Section 7-3 Estimating a Population Mean:  Known.
14 Elements of Nonparametric Statistics
1 of 63 The EPA 7-Step DQO Process Step 1 – Problem Statement DQO Case Study Presenter: Sebastian Tindall 45 minutes DQO Training Course Day 3 Module 18.
1 of 21 Introduction to the EPA 7-Step DQO Process DQO Training Course Day 1 Module 7 (30 minutes) Steps Presenter: Sebastian Tindall.
1 of 49 Key Concepts Underlying DQOs and VSP DQO Training Course Day 1 Module minutes (75 minute lunch break) Presenter: Sebastian Tindall.
Audit Sampling: An Overview and Application to Tests of Controls
1 of 45 How Many Samples do I Need? Part 1 Presenter: Sebastian Tindall 60 minutes (15 minute 1st Afternoon Break) DQO Training Course Day 1 Module 4.
1 of 40 The EPA 7-Step DQO Process Step 2 - Identify the Decisions Presenter: Sebastian Tindall (30 minutes) DQO Training Course Day 2 Module 12.
1 of 32 Systematic Planning for Environmental Decision-Making DOE EM-3 Day 2 DQO Training Colorado Department of Public Health & Environment EPA Conference.
1 of 37 Key Concepts Underlying DQOs and VSP DQO Training Course Day 1 Module 4 (60 minutes) (75 minute lunch break) Presenter: Sebastian Tindall.
1 of 50 The EPA 7-Step DQO Process Step 7 - Optimize Sample Design 60 minutes Presenter: Sebastian Tindall DQO Training Course Day 3 Module 16.
1 of 39 The EPA 7-Step DQO Process Step 3 - Identify Inputs (45 minutes) Presenter: Sebastian Tindall Day 2 DQO Training Course Module 3.
8- 1 Chapter Eight McGraw-Hill/Irwin © 2006 The McGraw-Hill Companies, Inc., All Rights Reserved.
BUS216 Spring  Simple Random Sample  Systematic Random Sampling  Stratified Random Sampling  Cluster Sampling.
1 of 35 The EPA 7-Step DQO Process Step 2 – Identify the Decision Presenter: Sebastian Tindall 15 minutes (75 minute Lunch break) DQO Training Course Day.
Introduction to the EPA 7-Step DQO Process
1 of 36 The EPA 7-Step DQO Process Step 6 - Specify Error Tolerances (60 minutes) (15 minute Morning Break) Presenter: Sebastian Tindall DQO Training Course.
Education 793 Class Notes Decisions, Error and Power Presentation 8.
Estimating a Population Mean
Sampling distributions rule of thumb…. Some important points about sample distributions… If we obtain a sample that meets the rules of thumb, then…
1 of 27 The EPA 7-Step DQO Process Step 5 - Define Decision Rules (15 minutes) Presenter: Sebastian Tindall Day 2 DQO Training Course Module 5.
Auditing: The Art and Science of Assurance Engagements Chapter 13: Audit Sampling Concepts Copyright © 2011 Pearson Canada Inc.
Copyright © Cengage Learning. All rights reserved. 12 Analysis of Variance.
Chapter Eight: Using Statistics to Answer Questions.
1 of 86 The EPA 7-Step DQO Process Step 7 - Optimize Sample Design (70 minutes) Presenter: Sebastian Tindall Day 2 DQO Training Course Module 7.
1 of 10 Introduction to Visual Sample Plan & Applications DQO Training Course Day 3 Module 21 Presenter: Sebastian Tindall (60 minutes)
1 of 39 How Many Samples do I Need? Part 3 Presenter: Sebastian Tindall (50 minutes) (5 minute “stretch” break) DQO Training Course Day 1 Module 6.
Chapter 15 The Chi-Square Statistic: Tests for Goodness of Fit and Independence PowerPoint Lecture Slides Essentials of Statistics for the Behavioral.
Education 793 Class Notes Inference and Hypothesis Testing Using the Normal Distribution 8 October 2003.
1 of 19 Managing Uncertainty with Systematic Planning for Environmental Decision-Making 3-Day DQO Training Day 2.
1 of 27 How Many Samples do I Need? Part 2 Presenter: Sebastian Tindall (60 minutes) (5 minute “stretch” break) DQO Training Course Day 1 Module 5.
1 of 7 Exercise 1 Populations, Histograms, Range & Simulations 45 minutes Presenter: Sebastian Tindall DQO Training Course Day 2.
1 of 31 The EPA 7-Step DQO Process Step 6 - Specify Error Tolerances 60 minutes (15 minute Morning Break) Presenter: Sebastian Tindall DQO Training Course.
8- 1 Chapter Eight McGraw-Hill/Irwin © 2005 The McGraw-Hill Companies, Inc., All Rights Reserved.
LECTURE 13 QUALITY ASSURANCE METHOD VALIDATION
1 of 7 Exercise 4 Hypothesis Testing: Beta Error 30 minutes Presenter: Sebastian Tindall DQO Training Course Day 2.
1 of 48 The EPA 7-Step DQO Process Step 6 - Specify Error Tolerances 3:00 PM - 3:30 PM (30 minutes) Presenter: Sebastian Tindall Day 2 DQO Training Course.
Hypothesis Tests. An Hypothesis is a guess about a situation that can be tested, and the test outcome can be either true or false. –The Null Hypothesis.
1 FORMER COS COB POWER PLANT From Characterization to Redevelopment Brownfields2006 November 14, 2006.
Quality is a Lousy Idea-
Quality is a Lousy Idea-
What it Means, Why it Works, and How to Comply
Why Use Them? By: Marcy Bolek – Alloway
Elementary Statistics
Chapter Nine Part 1 (Sections 9.1 & 9.2) Hypothesis Testing
Estimating a Population Mean:  Known
Chapter Nine: Using Statistics to Answer Questions
Presentation transcript:

1 of 39 The EPA 7-Step DQO Process Step 7 - Optimize Sample Design DQO Case Study 45 minutes Presenter: Sebastian Tindall DQO Training Course Day 3 Module 20

2 of 39 Information INActions Information OUT From Previous Step To Next Step Select the optimal sample size that satisfies the DQOs for each data collection design option For each design option, select needed mathematical expressions Check if number of samples exceeds project resource constraints Decision Error Tolerances Gray Region Optimal Sample Design Go back to Steps 1- 6 and revisit decisions. Yes No Review DQO outputs from Steps 1-6 to be sure they are internally consistent Step 7- Optimize Sample Design Develop alternative sample designs

3 of 39 Terminal Objective To be able to use the output from the previous DQO Process steps to select sampling and analysis designs and understand design alternatives presented to you for a specific project

4 of 39 Sampling Approaches n Sampling Approach 1 –Simple Random –Traditional fixed laboratory analyses n Sampling Approach 2 –Systematic Grid –Field analytical measurements –Computer simulations –Dynamic work plan

5 of 39 Design Approaches Approach 1 Collect samples using Simple Random design. Use predominantly fixed traditional laboratory analyses and specify the method specific details at the beginning of DQO and do not change measurement objectives as more information is obtained

6 of 39 Approach 1 Sample Design Plan View Former Pad Location Runoff Zone ft m Buffer Zone

7 of 39 Histogram

8 of 39 “Normal” Approach Due to using only five samples for initial distribution assessment, one cannot infer a ‘normal’ frequency distribution Reject the ‘Normal’ Approach and Examine ‘Non-Normal’ or ‘Skewed’ Approach

9 of 39 Pb, U, TPH (DRO/GRO) n Because there were multiple COPCs with varied standard deviations, action limits and LBGRs, separate tables for varying alpha, beta, and (LBGR) delta were calculated n For the U, Pb, and TPH, the largest number of samples for a given alpha, beta and delta are presented in the following table

10 of 39 Pb, U, TPH Based on Non-Parametric Test

11 of 39 Aroclor 1260: Non-Parametric Test n For PCBs, the Aroclor 1260 has the greatest variance and using the standard deviation results in a wide gray region n The following table presents the variation of alpha, beta and deltas for Aroclor 1260

12 of 39 Aroclor 1260: Non-Parametric Test

13 of 39 Approach 1 Sampling Design (cont.) Surface Soils S&A Costs

14 of 39 Approach 1 Sampling Design (cont) Sub-surface Soils S&A Costs

15 of 39 Approach 1 Sampling Design (cont.) Surface Soils

16 of 39 Approach 1 Sampling Design (cont.) Sub-surface Soils

17 of 39 Approach 1 Based Sampling Design n Design for Pb, U, TPH –Alpha = 0.05; Beta = 0.2; Delta = total error –The decision makers agreed on collection of 9 surface samples for Pb, U and TPH (GRO & DRO) from each of the two surface strata, for a total of 18 samples using a stratified random design –For the sub-surface, nine borings/probes will be collected from each of the two subsurface stratum at random locations, collected at a random depth down to 10 feet, to assess migration through the vadose zone, for a total of 18 samples n Design for PCBs –Alpha = 0.05; Beta = 0.20; Delta = 0.50 (50% of the AL) –The decision makers agreed on collection of 24 surface samples from each of the two surface strata; total of 48 samples using a stratified random design –For the sub-surface, 24 borings/probes will be collected from each of the two subsurface stratum at random locations, collected at a random depth down to 10 feet for a total of 48 samples (2 X 24)

18 of 39 Approach 1 Sample Locations (Surface Strata) Plan View Former Pad Location Runoff Zone ft m Buffer Zone

19 of 39 Approach 1 Sampling Design (cont.)

20 of 39 Remediation Costs* *Does not include layback area

21 of 39 Approach 1 Based Sampling Design n Compare Approach 1 costs versus remediation costs –Approach 1 S&A costs $11,700 (Pb, U, TPH) + $21,600 (PCBs) = $33,300 –Remediation costs Cost to remediate surface soil under footprint of pad and buffer area: $204,200 Cost to remediate subsurface soil under footprint of pad and buffer area: $3,881,400

22 of 39 Design Approaches Approach 2: Dynamic Work Plan (DWP) & Field Analytical Methods (FAMs) n Manage uncertainty by increasing sample density by using field analytical measurements n Manage uncertainty by including RCRA metals as COPCs n Use DWP to allow more field decisions to meet the measurement objectives and allow the objectives to be refined in the field using DWP

23 of 39 Approach 2 Sampling Design n Phase 1: Pb, U, TPH, PCBs –Perform field analysis of the four strata on-site using XRF (RCRA metals & U), on-site GC (TPH), and Immunoassay (PCBs) methods. Take into account the chance of false positives at the low detection levels –This will produce a worse-case frequency distributions and variance for each COPC that will be used to select the proper statistical method and then calculate the number of confirmatory samples for laboratory analysis for the surface and below grade strata

24 of 39 n Phase 1: Metals, TPH, PCBs –Provide detailed SOPs for performance of FAMs: XRF, GC, & Immunoassay analysis –Divide both surface strata into triangular grids –Use systematic sampling, w/random start (RS), to locate sample points; sample in center of each grid n Pad & Run-off zone – CSM expects contamination more likely here – 10 ft equilateral triangle: ft 2 – Pad + Run-off zone = 12,272 ft 2 – 283 sample points n Buffer area: – Also 283 sample points – CSM expects contamination less likely here – Thus, grid triangle has larger area Approach 2 Sampling Design (cont.)

25 of 39 n Phase 1: Pb, U, TPH, PCBs –Sub-surface strata: Pad & Run-off zone n Use Direct Push Technology (DPT) to collect n Push at all surface sample points > ALs n Minimum sample locations: 40 (+ 10 >ALs) = ~50 n Collect sub-surface samples at feet n 50 X 3 = 150 sub-surface samples in this strata n Use systematic sampling, w/random start (RS), to locate sample points –Buffer area n CSM expects contamination less likely here n Thus, fewer sample points n Same >ALs rationale as above n 50 X 3 = 150 sub-surface samples in Buffer area n Use systematic sampling, w/RS, to locate sample points Approach 2 Sampling Design (cont.)

26 of 39 Stratified Systematic Grid with Random Start (Surface Strata) Not to scale Triangles will be adjusted according to Step 7 design N Footprint of Concrete Pad (Stratum 1) Runoff Zone (Stratum 1) Buffer Zone (Stratum 2)

27 of 39 n Phase 2: Pb, U, TPH, PCBs –Evaluate the FAM results, calculate variance and construct FDs for each COPC –Using Monte Carlo method, sample the worst case distribution and evaluate the alpha, beta and delta values and resulting n based on the XRF, on-site GC, and Immunoassay data and select a value (worst case) for n to confirm the FAM data, using traditional laboratory analysis for each of the four strata –For this Case Study, we will assume that number came out to be 9 per strata or 36 confirmatory lab samples Approach 2 Sampling Design (cont.)

28 of 39 FAM Procedure SW-846, Draft Update IVA Method 6200 Field portable x-ray fluorescence spectrometry for the determination of elemental concentrations in soil and sediment

29 of 39 FAM Procedure SW-846, Draft Update III Method 4020 Screening for polychlorinated biphenyls by immunoassay

30 of 39 FAM Procedure for GRO SW-846, Draft Update III Preparation Method 5030 or 5035 (purge and trap methods) Followed by Analysis Method 8015 B Non-halogenated organics using GC/FID

31 of 39 FAM Procedure for DRO SW-846, Draft Update III One of Following Extraction Methods: 3540 (soxhlet), 3541(auto-soxhlet), 3550 (ultrasonic), or 3560 (super critical fluid) Followed by Analysis Method 8015 B: Non-halogenated organics using GC/FID

32 of 39 Approach 2 Sampling Design (cont.) Surface Soils SC&SA Costs

33 of 39 Approach 2 Sampling Design (cont) Sub-surface Soils SC&SA Costs

34 of 39 Approach 2 Sampling Design (cont.)

35 of 39 Approach 2 Sampling Design (cont.)

36 of 39 n Evaluate costs of Approach 2 vs. remediation costs –Sampling and analysis (S&A) costs $143,624 –Original budget for S&A $45,000 –Remediation cost n Cost to remediate surface soil under footprint of pad and buffer area: $204,200 n Cost to remediate subsurface soil under footprint of pad and buffer area: $3,881,400 Approach 2 Sampling Design (cont.)

37 of 39 Remediation Costs: Surface - $204,200 Sub-surface - $3,881,400 Approach 2 Sampling Design (cont.)

38 of 39 n Measure gasoline & diesel range organics (GRO/DRO) n Ship & process all samples in one batch to decrease cost. n QC defined per SW 846 [1 MS/MSD, 1 method blank, 1 equipment blank (if equipment is reused), 1 trip blank for GRO only]. n Cool GRO/DRO to 4°C,  2°C. n QAP written and approved before implementation. QC and Analysis Details Used in All Approaches

39 of 39 End of Module 20 Thank you Questions?