739730 Comprehensive ReportPDBS Comprehensive Report FIGURE 5.2-2 IMPACT OF MISSING WELLS ON PREDICTED STANDARD ERROR 5-12 5-16 5-17 5-18 Title 739730 Comprehensive Report.cdr Author

Defense Logistics Agency

Contract F41624-00-D-8024Task Order 0024

Air Force Center for Environmental ExcellenceScience and Engineering Division (AFCEE/ERS)

and

Air Force Environmental Directorate

and

Air Force Real Property Agency

and

FINAL

August 2003

Prepared For

Comprehensive Results Report for thePassive Diffusion Bag Sampler Demonstration

FINAL COMPREHENSIVE RESULTS REPORT FOR THE PASSIVE

DIFFUSION BAG SAMPLER DEMONSTRATION

Prepared For

Air Force Center for Environmental Excellence Science and Engineering Division

and Air Force Environmental Directorate

and Air Force Real Property Agency

and Defense Logistics Agency

CONTRACT NO. F41624-00-D-8024 TASK ORDER 0024

AUGUST 2003

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EXECUTIVE SUMMARY

This report presents the results of a passive diffusion bag sampling (PDBS) demonstration consisting of groundwater monitoring of volatile organic compounds (VOCs) at 14 Department of Defense (DoD) installations. The demonstration was performed by Parsons Engineering Science, Inc. (Parsons) for the Air Force Center for Environmental Excellence, Technology Transfer Division (AFCEE/ERT, currently part of the Science and Engineering Division [AFCEE/ERS]). The objectives of the PDBS demonstration were to:

• Develop vertical profiles of VOC concentrations across the screened intervals of the sampled monitoring wells;

• Assess the effectiveness of the PDBS method by statistically comparing groundwater analytical results for VOCs obtained using the current (conventional) sampling method (i.e., micropurge/sample or 3-casing-volume purge/sample) during regularly scheduled long-term monitoring (LTM) events with results obtained using the PDBS method; and

• Compare the costs of PDB and conventional sampling.

A secondary objective of this demonstration was to perform monitoring network optimizations (MNOs) at nine of the 14 demonstration installations. The MNO evaluated the adequacy and appropriateness of a portion of the groundwater monitoring program at selected sites using both qualitative assessments and a geographic information system-based algorithm that performs temporal and spatial statistical analyses of monitoring well information. Based on the results of the MNO activities, recommendations were made for optimizing the groundwater monitoring program.

Diffusion sampling is a relatively new technology designed to utilize passive sampling techniques that reduce sampling costs and reduce generation of investigation-derived waste. The PDBS method relies on the natural flow of groundwater through a well screen, and therefore the results obtained from this method will not always be comparable to results obtained using conventional sampling methods which induce groundwater flow into a well by creating a hydraulic gradient through well purging.

A total of 1,199 PDB samples were collected from 332 wells at 14 DoD installations during this demonstration. PDB samplers were deployed in each well at a frequency of 1 PDBS per 3 feet of saturated screened interval to develop vertical profiles of VOC concentrations. The samplers were left in-place for a minimum of 14 days to allow local groundwater conditions to re-equilibrate following PDBS deployment, and to allow adequate time for the diffusion process to occur. PDBS retrieval was timed to coincide with regularly scheduled conventional sampling of the same wells performed by the base environmental sampling contractor. Analytical results of PDB and conventional samples were then compared against a set of five correlation criteria. A positive correlation was demonstrated if any of the five criteria were met.


The degree to which concentrations of benzene and trichloroethene (TCE) varied with depth in the sampled wells was statistically evaluated. Concentrations of these compounds exhibited a relatively low degree of vertical variation in most wells. Overall, the evaluation of the vertical distribution of these compounds provided guidance on the use and placement of PDBSs in wells that are being evaluated for PDBS implementation. For example, the proper placement and vertical distribution of PDBSs in wells with relatively long saturated screen intervals may be more important than the placement and vertical distribution of PDBSs in wells with relatively short saturated screen intervals. Similarly, higher degrees of correlation between PDB and conventional sample results may be realized in certain circumstances (e.g., TCE may correlate better in wells having a high degree of vertical variation in TCE concentrations and that are sampled conventionally following a micropurge). These considerations may be useful when developing a PDBS demonstration, evaluating the results, and discussing with regulators the long-term conversion of sampling methodology from conventional methods to the PDBS method.

Excluding correlation results for compounds that are known to be incompatible with the PDBS method, and compounds for which correlation could not be determined, results for 42 of the 48 VOCs (87.5 percent) detected met the correlation criteria in at least 70 percent of the sampled wells. The six compounds that met the correlation criteria in less than 70 percent of the sampled wells include tert-amyl methyl ether, bromoform, naphthalene, n-propylbenzene, 1,2,4-trimethylbenzene (TMB), and 1,3,5-TMB.

Of the 332 wells included in the demonstration, no VOCs were detected in 12 wells (3.6 percent), correlation could not be determined in 2 wells (0.6 percent), and 6 wells (1.8 percent) contained only concentrations of compounds that are not appropriate for comparison. Of the remaining 312 wells, 34 wells (11 percent) met the correlation criteria for fewer than 70 percent of the compounds detected, and 278 wells (89 percent) met the correlation criteria for at least 70 percent of the compounds detected. Additionally, 239 wells (77 percent of the 312 wells) met the correlation criteria for all detected compounds, and could be candidates for immediate PDBS implementation for VOC monitoring. Correlation criteria were met in 1,411 of 1,614 comparison instances (87.4 percent). This relatively high degree of correlation indicates that the PDBS method is reasonably robust and is capable of accurately monitoring concentrations of VOCs dissolved in groundwater in most instances.

Fifteen reasons were developed to help explain instances where correlation criteria were not met. Of those 15 reasons, the following were deemed to be the most likely causes for instances where correlation criteria were not met.

• Low-magnitude concentrations where a small difference in concentration (i.e., less than 5 micrograms per liter) between PDB and conventional sample results prevented the meeting of correlation criteria, but do not necessarily indicate a failure of the PDB technology.

• The presence of field- or laboratory-introduced contamination that was not indicative of actual site-related contamination.

• Inherent differences in the passive (PDBS) and active (pumping/conventional) sampling approaches.


• The submergence depth of the uppermost PDBS (i.e., PDBSs installed near the water surface in the well tended to have low-based VOC concentrations to a greater extent than deeper PDBSs).

• Laboratory-induced variability (i.e., analysis of PDBS and conventional samples as part of separate sample delivery groups).

• Compound-specific physicochemical properties that are, in some cases, less conducive to the PDBS method than in other cases.

Correlation ratios (defined as the ratio of the instances where correlation criteria were met to the total number of instances of comparison) for compounds that are typical contaminants of concern (i.e., benzene, toluene, ethylbenzene, and xylenes [BTEX], chlorinated ethenes and chlorinated ethanes) were generally between 80 and 100 percent. However, even where correlation criteria were not met for a given compound or well, PDBS may still be a viable alternative to conventional sampling depending on the degree to which concentrations of that particular compound must be quantified to achieve LTM objectives. In these instances, it may be desirable to perform additional evaluations to determine whether the instances of reduced correlation were a one-time occurrence, whether correlation of PDB to conventional samples is even reasonable to expect or appropriate in that instance, or whether the wells or compounds are poorly suited to the PDBS method.

Excluding the costs of additional field testing of PDBSs to clarify outlier (i.e., low-correlation) situations, and disregarding the potential need to analyze samples from a given well for constituents other than VOCs, the PDBS method can provide significant long-term cost savings compared to conventional sampling methods. The median cost to evaluate the implementability of PDBS per well during this demonstration was approximately $2,500. Furthermore, the median estimated cost difference between LTM using the PDBS method as opposed to the conventional method was approximately $250 per well per sampling event. Therefore, even if PDBS was implemented on a limited basis, significant long-term cost savings could be realized. Depending on the number of wells, the frequency of sampling, and the duration of the LTM program, varying returns on investment (ROIs) were achieved. The median ROI calculated for the installations included in this demonstration was 356 percent.

In addition to the PDBS demonstration, MNO evaluations were performed at 10 sites distributed among 9 installations. The MNO evaluations were able to identify opportunities for significant reductions in the scope of monitoring programs at all of the sites that were evaluated for potential reductions. Potential percentage reductions in the average number of well-sampling events per year range from 19.5 percent at Norton Air Force Base (AFB) to 83.9 percent at the Vandenberg AFB Site 25 cluster. The MNO methodology also was flexible enough to be able to identify the optimal locations and numbers of new wells to augment the existing monitoring network at Columbus AFB.

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TABLE OF CONTENTS

Page

EXECUTIVE SUMMARY ...........................................................................................ES-1

ACRONYMS AND ABBREVIATIONS............................................................................v

SECTION 1 - INTRODUCTION .................................................................................... 1-1

1.1 Description of the PDBS Method ........................................................................ 1-1 1.2 Objectives and Scope of Demonstration.............................................................. 1-2

1.2.1 Objectives ................................................................................................ 1-2 1.2.2 Scope........................................................................................................ 1-3

1.3 Report Organization............................................................................................. 1-5

SECTION 2 - SAMPLING, LABORATORY ANALYTICAL, DATA VALIDATION, AND MONITORING NETWORK OPTIMIZATION PROCEDURES......................................................... 2-1

2.1 Field Sampling Procedures .................................................................................. 2-1 2.1.1 Field Equipment....................................................................................... 2-1 2.1.2 PDBS Deployment and Retrieval Methodologies ................................... 2-1

2.2 Laboratory Analysis and Data Validatoin............................................................ 2-5

SECTION 3 - PDBS PERFORMANCE ASSESSMENT ............................................... 3-1

3.1 Vertical Distribution of Contaminants................................................................. 3-1 3.2 Correlation Procedure .......................................................................................... 3-6 3.3 Correlation Summary........................................................................................... 3-9

3.3.1 Correlation Ratio Overview..................................................................... 3-9 3.3.2 Application of New and Revised Correlation Criteria............................. 3-9 3.3.3 Summary of Compound-Specific Correlation Ratios ............................ 3-22 3.3.4 Summary of Well-Specific Correlation Ratios ...................................... 3-24 3.3.5 Summary of Installation-Specific Correlation Ratios............................ 3-25

3.4 Scatter Plots of PDB versus Conventional Sample Results............................... 3-25 3.5 Additional Statistics ........................................................................................... 3-40

3.5.1 Test Description ..................................................................................... 3-40 3.5.2 Population Comparison Tests and Results............................................. 3-40

3.6 Discussion of Low Correlations......................................................................... 3-42 3.6.1 Low-Magnitude Concentrations (Reason 1).......................................... 3-43 3.6.2 PDBS Deployment Time (Reason 2)..................................................... 3-44 3.6.3 Time Lag Between PDB and Conventional Sampling Events

(Reason 3) .............................................................................................. 3-44

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TABLE OF CONTENTS (Continued)

Page 3.6.4 Laboratory and/or Field Introduced Contamination (Reason 4)............ 3-44 3.6.5 Sampling Method Differences (Reason 5)............................................. 3-49 3.6.6 Water Table Above Top of Well Screen (Reason 6) ............................. 3-51 3.6.7 Non-Uniform Vertical Distribution of Contamination (Reason 7)........ 3-53 3.6.8 PDBS Submergence Depth (Reason 8).................................................. 3-53 3.6.9 PDBS Deployed Outside of Screened Interval (Reason 9).................... 3-55 3.6.10 Vertical Groundwater Flow (Reason 10)............................................... 3-55 3.6.11 Hydrogeologic Conditions (Reason 11)................................................. 3-57 3.6.12 Well-Specific Conditions (Reason 12) .................................................. 3-57 3.6.13 Incompatible Compounds (Reason 13).................................................. 3-63 3.6.14 Compound Physicochemical Properties (Reason 14) ............................ 3-63 3.6.15 Laboratory Induced Variability (Reason 15) ......................................... 3-72 3.6.16 Overview of Potential Reasons for Low Correlation............................. 3-72

3.7 Comparison of Results from EON Products and Columbia Analytical PDBSs 3-76

SECTION 4 - COST ANALYSIS ................................................................................... 4-1

4.1 Estimate of Implementation Costs ....................................................................... 4-1 4.2 PDB and Conventional Sampling Cost Comparison ........................................... 4-3

4.2.1 Long-Term PDB Sampling Costs ............................................................ 4-3 4.2.2 Long-Term Conventional Sampling Costs .............................................. 4-4

4.3 Sampling Cost Avoidance.................................................................................... 4-4 4.4 Return on Investment........................................................................................... 4-5

SECTION 5 - MONITORING NETWORK OPTIMIZATION...................................... 5-1

5.1 Objectives ............................................................................................................ 5-1 5.2 Methodology........................................................................................................ 5-3

5.2.1 Site Identification & Data Compilation ................................................... 5-3 5.2.2 Three-Tiered Evaluation .......................................................................... 5-4

5.2.2.1 Qualitative Evaluation............................................................. 5-4 5.2.2.2 Temporal Statistical Evaluation .............................................. 5-5 5.2.2.3 Spatial Statistical Analysis...................................................... 5-7 5.2.2.4 Combined Evaluation Summary ........................................... 5-10

5.2.3 MAROS Evaluation ............................................................................... 5-11 5.3 MNO Results ..................................................................................................... 5-11

5.3.1 Three-Tiered and MAROS Comparison................................................ 5-11 5.3.2 Summary of MNO Recommendations................................................... 5-14

SECTION 6 - CONCLUSIONS AND RECOMMENDATIONS................................... 6-1

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TABLE OF CONTENTS (Continued)

Page

SECTION 7 - REFERENCES ......................................................................................... 7-1

APPENDICES

A Field Data Table B Supporting Documentation for the Vertical Contaminant Distribution

Evaluation C Comprehensive Correlation Ratio Summary Tables D Supporting Documentation for the Lithology, Hydraulic Conductivity, and

Velocity Evaluation E Comments on Draft Report and Responses.

LIST OF TABLES

No. Title Page 1.2-1 Summary of PDBS Demonstration Scope ........................................................... 1-3 3.1-1 Summary of Spearman’s Rank-Order Correlation Coefficient Results for

Benzene................................................................................................................ 3-4 3.1-2 Summary of Spearman’s Rank-Order Correlation Coefficient Results for

TCE...................................................................................................................... 3-5 3.3-1 Correlation Ratio Overview by Well ................................................................. 3-10 3.3-2 Correlation Ratio Overview by Analyte ............................................................ 3-19 3.3-3 Summary of Correlation for Typical Contaminants of Concern ....................... 3-23 3.3-4 Summary of Installation-Specific Correlation ................................................... 3-27 3.4-1 Summary of Correlation Plot Best-Fit Trend Line Statistics............................. 3-37 3.5-1 PDBS Versus Conventional Results Population Comparison ........................... 3-41 3.6-1 Potential Reasons for Low Correlation Between PDB and Conventional

Samples .............................................................................................................. 3-42 3.6-2 Summary of Suspected Blank Sample Contamination Introduced During

Either Field or Laboratory Activities................................................................. 3-50 3.6-3 Summary of Conventional Sampling Purge Methods ....................................... 3-51 3.6-4 Correlation of Correlation Ratio to Physical Properties .................................... 3-72 3.6-5 Correlation Summay for Wells Where Both PDB and Conventional

Samples Were Analyzed in the Same SDG ....................................................... 3-72 3.6-6 Potential Reasons for Low Correlation Between PDB and Conventional

Samples .............................................................................................................. 3-74 3.7-1 Results Comparison for Eon Products and Columbia Analytical Services

PDBS.................................................................................................................. 3-77 4.1-1 Cost Analysis Summary....................................................................................... 4-2 5.1-1 Monitoring Network Sites and Analyses ............................................................. 5-2

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TABLE OF CONTENTS (CONTINUED)

LIST OF TABLES (Continued)

No. Title Page 5.2-1 Monitoring Network Optimization Qualitative Evaluation Decision

Logic .................................................................................................................... 5-4 5.2-2 Qualitative Evaluation Monitoring Frequency Decision Logic........................... 5-5 5.2-3 Example of Qualitative Evaluation of Groundwater Monitoring Program ......... 5-6 5.2-4 Example of 3-Tiered Summary Evaluation of Current Groundwater

Monitoring Program........................................................................................... 5-12 5.3-1 Comparison of MAROS with Three-Tiered Monitoring Network

Optimization Approach...................................................................................... 5-13 5.3-2 Potential Reduction in Monitoring Events Identified By MNO Analysis ......... 5-16 5.3-3 Summary of 3-Tiered MNO Results.................................................................. 5-17 5.3-4 Summary of 3-Tiered MNO and MAROS results ............................................. 5-18

LIST OF FIGURES

No. Title Page 1.2-1 Locations of Installations Included in PDBS Demonstration .............................. 1-4 2.1-1 Standard Diffusion Sampler ................................................................................. 2-2 2.1-2 Example PDBS Placement Form......................................................................... 2-4 3.1-1 Vertical Distribution Coefficient Versus Percent of Wells in Category.............. 3-2 3.3-1 Correlation Overview for Analytes Detected More Than Ten Times ............... 3-23 3.3-2 Correlation Overview for Wells Where Fewer Than Five Compounds

Were Detected and the Correlation Ratio Was Less Than 70 Percent .............. 3-26 3.4-1 PDBS Versus Conventional Results - All Compounds ..................................... 3-28 3.4-2 PDBS Versus Conventional Results - PCE ....................................................... 3-29 3.4-3 PDBS Versus Conventional Results - TCE ....................................................... 3-30 3.4-4 PDBS Versus Conventional Results - cis-1,2-DCE........................................... 3-31 3.4-5 PDBS Versus Conventional Results - Vinyl Chloride...................................... 3-32 3.4-6 PDBS Versus Conventional Results - Benzene ................................................. 3-33 3.4-7 PDBS Versus Conventional Results - Ethylbenzene ......................................... 3-34 3.4-8 PDBS Versus Conventional Results - Toluene.................................................. 3-35 3.4-9 PDBS Versus Conventional Results - Xylenes.................................................. 3-36 3.4-10 PDBS Versus Conventional Results - PCE Sub Groups ................................... 3-38 3.4-11 PDBS Versus Conventional Results - Vinyl Chloride Sub Groups................... 3-39 3.6-1 Correlation Ratio Versus Deployment Time ..................................................... 3-45 3.6-2 Average Correlation Ratio Per Deployment Period Length .............................. 3-46 3.6-3 Correlation Ratio Versus Time Lag Between PDB and Conventional

Sampling Events ................................................................................................ 3-47

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TABLE OF CONTENTS (CONTINUED)

LIST OF FIGURES (Continued)

No. Title Page 3.6-4 Correlation Ratio Versus Time Lag Between PDB and Conventional

Sampling Events ................................................................................................ 3-48 3.6-5 Correlation Ratio Versus Water Level Above Top of Screen and

Compound Density ............................................................................................ 3-52 3.6-6 Correlation Ratio Versus PDBS Submergence Depth ....................................... 3-54 3.6-7 Correlation Ratio Versus Saturated Screen Length ........................................... 3-56 3.6-8 Correlation Ratio Versus Lithology................................................................... 3-58 3.6-9 Correlation Ratio Versus Groundwater Velocity by Site .................................. 3-59 3.6-10 Correlation Ratio Versus Groundwater Velocity by Installation....................... 3-60 3.6-11 Correlation Ratio Versus Hydraulic Conductivity by Site ................................ 3-61 3.6-12 Correlation Ratio Versus Hydraulic Conductivity by Installation..................... 3-62 3.6-13 Correlation Ratio Versus Compound Density ................................................... 3-64 3.6-14 Correlation Ratio Versus Compound Henry's Law Constant ............................ 3-65 3.6-15 Correlation Ratio Versus Compound Organic Carbon Partitioning

Coefficient.......................................................................................................... 3-66 3.6-16 Correlation Ratio Versus Compound Molecular Weight................................... 3-67 3.6-17 Correlation Ratio Versus Compound Solubility ................................................ 3-68 3.6-18 Correlation Ratio Versus Compound Water-Liquid Diffusion Coefficient....... 3-69 3.6-19 Correlation Ratio Versus Compound Vapor-Air Diffusion Coefficient............ 3-70 3.6-20 Correlation Ratio Versus Compound Vapor Pressure ....................................... 3-71 5.2-1 Temporal Chemical Concentration Trend Decision Rationale Flow Chart......... 5-8 5.2-2 Impact of Missing Wells on Predicted Standard Error ........................................ 5-9

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LIST OF ACRONYMS AND ABBREVIATIONS

µg/L micrograms per liter AFB Air Force Base AFBCA Air Force Base Conversion Agency AFCEE Air Force Center for Environmental Excellence AFCEE/ERS Air Force Center for Environmental Excellence, Science and

Engineering Division AFCEE/ERT Air Force Center for Environmental Excellence, Technology

Transfer Division AFILEV Air Force Environmental Directorate AFRPA Air Force Real Property Agency ARB Air Reserve Base BRAC Base Realignment and Closure BTEX benzene, toluene, ethylbenzene, and xylenes CAD computer-aided design CAS Columbia Analytical Services CLDW contaminant less dense than water cm centimeter CMDW contaminant more dense than water COC contaminant of concern DCA dichloroethane DCE dichloroethene DDJC Defense Distribution Depot San Joaquin - California DLA Defense Logistics Agency DoD Department of Defense ESRI Environmental Systems Research Institute, Inc. GIS geographical information system GSI Groundwater Services, Inc. ITRC Interstate Technology Regulatory Council Koc organic carbon partitioning coefficient LCS laboratory control sample LDPE low-density polyethylene LTM long-term monitoring MAROS Monitoring and Remediation Optimization System MCL maximum contaminant level MDL method detection limit MIBK 4-methyl-2-pentanone mL milliliter MNO monitoring network optimization MS/MSD matrix spike/matrix spike duplicate MTBE methyl tert-butyl ether Parsons Parsons Engineering Science, Inc. PCE tetrachloroethene PDBS Passive Diffusion Bag Sampler pdf portable document format PPF PDBS Placement Form PQL practical quantitation limit PVC polyvinyl chloride QA quality assurance QC quality Control rs Spearman’s correlation corefficient RL reporting limit

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ROI return on investment RPD relative-percent-difference SAP Sampling and Analysis Plan SDG sample delivery group SOP Standard Operating Procedure SROCC Spearman’s Rank-Order Correlation Coefficient SVOC semivolatile organic compound TCA trichloroethane TCE trichloroethene TMB trimethylbenzene TO task order USEPA US Environmental Protection Agency USGS US Geological Survey VC vinyl chloride VD vertical distribution coefficient VOA volatile organics analysis VOC volatile organic compound

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SECTION 1

INTRODUCTION

On 27 February 2001, Parsons Engineering Science, Inc. (Parsons) was awarded a task order (TO24) under Air Force Center for Environmental Excellence (AFCEE) contract F41624-00-D-8024 to demonstrate the use of passive diffusion bag samplers (PDBSs) in existing groundwater monitoring programs at selected Air Force and Defense Logistics Agency (DLA) installations. The Air Force installations include those managed by the Air Force Environmental Directorate (AFILEV) and the Air Force Real Property Agency (AFRPA), formerly known as the Air Force Base Conversion Agency (AFBCA). The Technology Transfer Division of AFCEE (AFCEE/ERT) (currently part of the Science and Engineering Division [AFCEE/ERS] initiated the PDBS demonstration to introduce this technology to multiple Department of Defense (DoD) installations and to improve the cost effectiveness of groundwater monitoring programs for volatile organic compounds (VOCs). The PDBSs used during this demonstration are designed solely for VOC sampling, and cannot be used for sampling other, non-volatile constituents (e.g., metals, semivolatile organic compounds [SVOCs], and natural attenuation indicator parameters).

This report summarizes results of the groundwater sampling and analysis activities that were performed as part of the PDBS demonstration. In addition, the results of monitoring network optimization (MNO) activities performed for selected sites are presented. The activities described in this report were performed in accordance with procedures outlined in the Umbrella Work Plans (Parsons, 2001a, 2001b, and 2001c), and the site-specific work plans prepared for each sampled installation (Parsons, 2001d through 2001p and 2002).

1.1 DESCRIPTION OF THE PDBS METHOD

Diffusion sampling is a relatively new technology designed to utilize passive sampling techniques that eliminate the need for well purging. Specifically, a diffusive-membrane capsule is filled with deionized/distilled water, sealed, suspended in a well-installation device, and lowered to a specified depth below the water level in a monitoring well. Over time, the VOCs in the groundwater diffuse across the membrane, and the water inside the sampler reaches equilibrium with groundwater in the surrounding formation. The sampler is subsequently removed from the well, and the water in the diffusion sampler is transferred to a sample container and submitted for laboratory analysis of VOCs. Benefits of diffusion sampling include reduced sampling costs and reduced generation of investigation-derived waste.

Once a diffusion sampler is placed in a well, it remains in place until chemical (i.e., VOC) equilibrium is achieved between the water in the well casing and the water in the


diffusion sampler. Depending on the hydrogeologic characteristics of the aquifer, the diffusion samplers can reach equilibrium within 3 to 4 days (Vroblesky, 2001). Groundwater samples collected using the diffusion samplers are thought to be representative of water present within the well during the previous 24 to 72 hours.

PDBS relies on the natural flow of groundwater through a well screen, and therefore the results obtained from this method will not always be comparable to results obtained using conventional sampling methods which induce groundwater flow into a well by creating a hydraulic gradient through well purging. In the absence of vertical flow, the PDBS will primarily monitor VOCs migrating through the well screen at the discrete depth interval at which the sampler is placed. If vertical flow exists in the well, PDBS results likely will be representative of the aquifer zone with the highest hydraulic head. Groundwater flows from high- to low-head zones, and the zone with the highest hydraulic head will be the source for groundwater flowing vertically through the well, and will therefore be the zone monitored by the PDBS. PDB samples are not susceptible to matrix interferences caused by turbidity because the PDB membrane is not permeable to colloids or other particles larger in diameter than approximately 10 angstroms.

The technology has been validated through various studies (Vroblesky and Hyde, 1997; Parsons, 1999; Church, 2000; Hare, 2000; McClellan AFB, 2000; Vroblesky et al., 2000; Vroblesky and Peters, 2000; Vroblesky and Petkewich, 2000), and a guidance document for their use has been developed (Vroblesky, 2001). The Interstate Technology and Regulatory Council (ITRC) has formed a workgroup to expand on the PDBS guidance document and to address technical and regulatory implementation issues as they arise.

1.2 OBJECTIVES AND SCOPE OF DEMONSTRATION

1.2.1 Objectives

The PDBS demonstration had three primary objectives:

• Develop vertical profiles of VOC concentrations across the screened intervals of the sampled monitoring wells;

• Assess the effectiveness of the PDBS method by statistically comparing groundwater analytical results for VOCs obtained using the current (conventional) sampling method (i.e., micropurge/sample or 3-casing-volume purge/sample) during regularly scheduled long-term monitoring (LTM) events with results obtained using the PDBS method; and

• Compare the costs of PDB and conventional sampling.

Vertical contaminant profiles were developed for those wells in which dedicated pumps were not installed and which had a sufficient saturated screen length to support placement of multiple PDBSs by placing multiple PDBSs at discrete depths within the screened interval of the monitoring well, depending on the length of the saturated screened interval, and analyzing the resulting samples for VOCs. The comparison of the conventional and diffusion sampling results was used to assess the appropriateness of implementing diffusion sampling for VOCs at the sampled sites.


A secondary objective of this project was to evaluate the adequacy and appropriateness of a portion of the groundwater monitoring program at selected sites using both qualitative assessments and a geographic information system (GIS)-based algorithm that performs temporal and spatial statistical analyses of monitoring well information. Based on the results of these MNO activities, recommendations were made for optimizing the groundwater monitoring program.

1.2.2 Scope

The PDBS method was demonstrated at nine AFILEV installations, four Base Realignment and Closure (BRAC) installations, and one DLA installation. The sampled installations are summarized in Table 1.2-1, and their locations are shown on Figure 1.2-1.

TABLE 1.2-1 SUMMARY OF PDBS DEMONSTRATION SCOPE

PDBS COMPREHENSIVE REPORT

Installation Number of Wells Sampled

Number of Diffusion Samples Collected

Monitoring Network

Optimization Performed?

AFILEV INSTALLATIONS

Andrews AFB, MD 26 80 No Bolling AFB, Washington, DC 10 26 Yes Buckley AFB, CO 16 28 No Columbus AFB, MS 20 56 Yes Dover AFB, DE 20 47 Yes Edwards AFB, CAa/ 38/14 (38) 109/36 (115) Yes Keesler AFB, MS 17 42 Yes Shaw AFB, SC 24 61 Yes Vandenberg AFB, CAa/ 56/13 (56) 179/35 (181) Yes Totals for AFILEV 227 636 BRAC INSTALLATIONS George AFB, CA 34 174 No March ARB, CA 20 103 No Norton AFB, CA 17 94 Yes Williams AFB, AZ 10 126 Yes Totals for BRAC 81 497 DLA INSTALLATION DDJC-Sharpe, CA 24 66 No Totals for Project 332 1,199 Notes: AFB = Air Force Base; ARB = Air Reserve Base; DDJC= Defense Distribution Depot San Joaquin, California. a/ Resampling was performed at Edwards AFB and Vandenberg AFB. Values presented in Table 1.2-1 are: ORIGINAL SAMPLING/RESAMPLING (TOTAL FINAL)

Draw\739732 map.cdr ma 3/17/03

FIGURE 1.2-1

LOCATIONS OF INSTALLATIONSINCLUDED IN PDBS DEMONSTRATION

PDBS Comprehensive Report

George AFB

Edwards AFB

MarchARB

DDJC-Sharpe

Buckley AFB

KeeslerAFB

Dover AFB

Andrews AFB

Bolling AFB

ColumbusAFB

Shaw AFB

Williams AFB

VandenbergAFB

Norton AFB

10

403141-4


A total of 1,199 PDB samples were collected from 332 wells during this demonstration project as follows:

• 636 samples from 227 wells at AFILEV installations;

• 497 samples from 81 wells at BRAC installations; and

• 66 samples from 24 wells at DLA installations.

In addition, MNO evaluations were performed for nine installations (seven AFILEV and two BRAC). For the MNO, locations and completion intervals of individual monitoring wells and sampling points were examined, and the informational contribution of each well or sampling point to the network was weighed against the cost of monitoring at that point. Monitoring protocols and analytical methods also were evaluated. Where warranted, recommendations were developed for optimization of the portion of the monitoring network that was evaluated. Methods used in the evaluation include qualitative hydrogeologic and hydrochemical analyses, application of statistical optimization techniques, and application of decision-logic structures. Additional details regarding the MNO procedures and results are provided in Section 5.

1.3 REPORT ORGANIZATION

This report is organized into seven sections, including this introduction, five appendices, and one attachment. A summary of the field, laboratory analytical, data validation, and MNO procedures used during the execution of this project is provided in Section 2. A PDBS performance assessment is provided in Section 3, and a summary of the cost analyses is provided Section 4. A discussion of the MNO analyses is provided in Section 5. Section 6 contains conclusions and recommendations. References cited in this report are contained in Section 7. Appendix A is a table of field data collected during this demonstration. Appendix B is comprised of tables generated during the vertical contaminant distribution evaluation discussed in Section 3.1. Appendix C includes tables that list the results of the application of various correlation criteria to each well and compound, and Appendix D contains supporting notes, assumptions, and references used in the lithology, hydraulic conductivity, and velocity evaluation presented in Section 3.6. Appendix E is a table listing all comments received on the draft version of this report as well as AFCEE/Parsons’ responses to those comments. Attachment 1 contains electronic copies of the final site-specific PDBS results reports prepared for each of the 14 installations included in this demonstration in portable document format (pdf).


SECTION 2

SAMPLING, LABORATORY ANALYTICAL, DATA VALIDATION, AND MONITORING NETWORK OPTIMIZATION PROCEDURES

2.1 FIELD SAMPLING PROCEDURES

2.1.1 Field Equipment

The standard diffusion sampler used in this demonstration, shown on Figure 2.1-1, is constructed of a 45-centimeter (cm)-long section of 5.08-cm-diameter, 4-mil-thick, low-density polyethylene (LDPE) tubing that is permanently sealed on one end and sealed on the other end with a polyvinyl chloride (PVC) cap. The sampler holds approximately 350 milliliters (mL) of purified water. Samplers of different length and radius can be constructed for specific purposes. The sampler is placed in “flex-guard” polyethylene mesh tubing for abrasion protection, attached to a weighted rope, and lowered to a predetermined depth within the screened interval of a well. The rope is weighted to ensure that the sampling devices are positioned at the correct depth and that they do not float upward through the water column. The samplers were purchased from Eon Products, Inc. in Snellville, Georgia.

Six PDBSs manufactured by Columbia Analytical Services (CAS) also were deployed at Defense Distribution Depot San Joaquin (DDJC)-Sharpe. The CAS PDBSs were installed adjacent to PDBSs manufactured by Eon Products to obtain a side-by-side comparison of results from each manufacturer’s samplers. Comparison results are presented in Section 3.7.

2.1.2 PDBS Deployment and Retrieval Methodologies

Typically, two mobilizations were required to achieve the objectives identified for this demonstration, including one for sampler deployment and one for sampler retrieval. At some sites, additional mobilizations were required for various reasons. Field measurement data collected from each well during this demonstration included water levels in sampled wells (during PDBS deployment and retrieval), total well depth, and PDBS deployment depths. PDBS deployment and retrieval generally followed the procedures described in Standard Operating Procedures (SOPs) #1 and #2; these SOPs were published in Appendix B (Sampling and Analysis Plan [SAP]) of the Umbrella Work Plans (Parsons, 2001a, 2001b, and 2001c). Equipment decontamination procedures used are described in SOP #4 of the SAP. However, these procedures were occasionally modified on a site-specific basis when the procedures used by the incumbent conventional sampling contractor (e.g., for decontamination of the water-level probe) differed from those described in the Parsons SOP. In this case, the PDBS field team followed the same procedures as the conventional sampling contractor to maintain

Draw\739732 map.cdr ma 3/17/03

FIGURE 2.1-1

STANDARD DIFFUSION SAMPLER


A

B

LEGEND

Polyethylene bag without protective mesh covering

Polyethylene bag with protective mesh coveringA

B

11

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consistency. Sample handling and documentation procedures used are described in SOP #5 of the SAP. SOP #3 describes field screening procedures (i.e., use of field test kits to obtain screening-level concentrations of selected analytes). This SOP was not used because all samples were submitted to a fixed-base laboratory for definitive analysis, and field test kits were not used.

At all of the sites except for Columbus Air Force Base (AFB), the PDBSs were filled in the field shortly before their placement in the wells. Typically, grocery-store-grade distilled water was used; however, reagent-grade water was purchased for use at Keesler and Shaw AFBs. At Columbus AFB, which was the first installation sampled, the PDBSs were filled with reagent-grade water by Eon Products, Inc. prior to their shipment to the site. The use of different grades of water to fill the diffusion samplers permitted an evaluation of the importance of the type of source water used (see Section 3.6.4). In order to address data quality issues resulting from the various types of source water used (e.g., source-water contamination), samples of the source water were analyzed for VOCs as discussed in each Site-Specific Results Report (Attachment 1).

As described in Section 1, all PDBS strings were deployed in a manner that was consistent with the vertical profiling requirement of one PDBS per three feet of saturated well screen as specified in the Umbrella Work Plans (Parsons, 2001a, 2001B, and 2001c). PDBSs were installed throughout the saturated screened interval of each of the selected wells.

During the deployment mobilizations, groundwater elevations and total well depths were measured. The PDBS deployment depths were then automatically calculated using an electronic (Microsoft Excel®-based) PDBS Placement Form (PPF) (Figure 2.1-2). Sample strings were assembled using 0.125-inch-diameter braided polypropylene rope, stainless steel weights, 18-inch-long PDBSs, and nylon cable ties (zip-ties). In some cases, longer, larger-volume PDBSs (2 feet long) were used to facilitate collection of both primary and field quality control (QC) samples. A length of rope that would be needed for each well was cut, and a stainless steel weight was attached to one end of the rope with a knot.

Once filled and capped, the PDBSs were attached with zip-ties to the rope at intervals that corresponded to the predetermined spacing interval. After all the required PDBSs were attached to the rope, the sampling string was lowered into the well until the weight was just resting on the well bottom. For wells with dedicated pumps (i.e., selected wells at Edwards AFB), the stainless steel weight was attached directly to the bottom of a PDBS, which was suspended from the bottom of the rope. Dedicated pump depths were not known during PDBS deployment at Edwards AFB, so each PDBS string was lowered into the well until the weight was presumed to be just touching the top of the pump. After lowering each PDBS string, the top of the rope was attached to the well cap to fix the PDBSs at the proper depths. After PDBS deployment, well covers were replaced and locked (if a lock was provided for the well). This procedure was performed independently at each well.

According to Vroblesky (2001), laboratory and field data suggest that 2 weeks of equilibration probably is adequate for many applications. As shown in Appendix A, PDBSs were left in the wells from 13 to 149 days (average 29 days) to allow local groundwater conditions to re-equilibrate following PDBS deployment, and to allow adequate time for the diffusion process to occur.

draw\739732 PDBS Placement Form.ai ma 3/17/03

FIGURE 2.1-2

EXAMPLE PDBS PLACEMENT FORM


PRE-MOBILIZATION DATA PDBS RETRIEVAL DATAInstallation: 8 PDBS retrieval date: 5/13/02

Installation abbreviation: EDWD PDBS retrieval time: 0736Project Number: 739732 Sampler(s) initials: JPT/LRTWBS: 08000Well ID (exclude dashes and slashes): N3DEW1 Sampler #1 ID EDWD\N3DEW1\49.2\01 Matrix Spike #1 ID EDWD\N3DEW1\49.2\MSWell diameter (in): 6 Sampler #2 ID EDWD\N3DEW1\46.3\01 Matrix Spike #2 ID EDWD\N3DEW1\46.3\MSWell scheduled for QC sample collection (dup, MS, MSD)? Sampler #3 ID EDWD\N3DEW1\43.3\01 Matrix Spike #3 ID EDWD\N3DEW1\43.3\MSElevation of TOC (ft amsl): 2280.52 Sampler #4 ID EDWD\N3DEW1\40.4\01 Matrix Spike #4 ID EDWD\N3DEW1\40.4\MSElevation of ground surface (ft amsl): Sampler #5 ID EDWD\N3DEW1\37.4\01 Matrix Spike #5 ID EDWD\N3DEW1\37.4\MSHistorical maximum groundwater depth (ft btoc): Sampler #6 ID EDWD\N3DEW1\34.5\01 Matrix Spike #6 ID EDWD\N3DEW1\34.5\MSHistorical minimum groundwater depth (ft btoc): Sampler #7 ID EDWD\N3DEW1\31.5\01 Matrix Spike #7 ID EDWD\N3DEW1\31.5\MSTop of screen depth (ft btoc): 5.70 Sampler #8 ID EDWD\N3DEW1\28.5\01 Matrix Spike #8 ID EDWD\N3DEW1\28.5\MSBottom of screen depth (ft btoc): 50.70 Sampler #9 ID EDWD\N3DEW1\25.6\01 Matrix Spike #9 ID EDWD\N3DEW1\25.6\MSAnalytical method: 8260B Sampler #10 ID EDWD\N3DEW1\22.6\01 Matrix Spike #10 ID EDWD\N3DEW1\22.6\MS

Sampler #11 ID EDWD\N3DEW1\19.7\01 Matrix Spike #11 ID EDWD\N3DEW1\19.7\MS

FIELD MEASUREMENTS/PDBS PLACEMENT DATA Sampler #12 ID EDWD\N3DEW1\16.7\01 Matrix Spike #12 ID EDWD\N3DEW1\16.7\MSDepth to water (ft btoc): 8.35 Sampler #13 ID EDWD\N3DEW1\13.8\01 Matrix Spike #13 ID EDWD\N3DEW1\13.8\MSTotal well depth (ft btoc): 52.95 Sampler #14 ID EDWD\N3DEW1\10.8\01 Matrix Spike #14 ID EDWD\N3DEW1\10.8\MSLength of saturated screen (ft): 42.35 Sampler #15 ID NA Matrix Spike #15 ID NACalculated saturated screened interval (ft btoc): 8.35 - 50.70 Duplicate #1 ID EDWD\N3DEW1\49.2\10 MS Duplicate #1 ID EDWD\N3DEW1\49.2\MDNumber of PDB samplers to deploy: 14 Duplicate #2 ID EDWD\N3DEW1\46.3\10 MS Duplicate #2 ID EDWD\N3DEW1\46.3\MDPlace bottom of sampler at the following depths (ft from bottom of weight) Duplicate #3 ID EDWD\N3DEW1\43.3\10 MS Duplicate #3 ID EDWD\N3DEW1\43.3\MD (deeper) Sampler #1 2.98 Duplicate #4 ID EDWD\N3DEW1\40.4\10 MS Duplicate #4 ID EDWD\N3DEW1\40.4\MD

Sampler #2 5.93 Duplicate #5 ID EDWD\N3DEW1\37.4\10 MS Duplicate #5 ID EDWD\N3DEW1\37.4\MDSampler #3 8.88 Duplicate #6 ID EDWD\N3DEW1\34.5\10 MS Duplicate #6 ID EDWD\N3DEW1\34.5\MDSampler #4 11.84 Duplicate #7 ID EDWD\N3DEW1\31.5\10 MS Duplicate #7 ID EDWD\N3DEW1\31.5\MDSampler #5 14.79 Duplicate #8 ID EDWD\N3DEW1\28.5\10 MS Duplicate #8 ID EDWD\N3DEW1\28.5\MD

Sampler #6 17.74 Duplicate #9 ID EDWD\N3DEW1\25.6\10 MS Duplicate #9 ID EDWD\N3DEW1\25.6\MDSampler #7 20.70 Duplicate #10 ID EDWD\N3DEW1\22.6\10 MS Duplicate #10 ID EDWD\N3DEW1\22.6\MDSampler #8 23.65 Duplicate #11 ID EDWD\N3DEW1\19.7\10 MS Duplicate #11 ID EDWD\N3DEW1\19.7\MDSampler #9 26.61 Duplicate #12 ID EDWD\N3DEW1\16.7\10 MS Duplicate #12 ID EDWD\N3DEW1\16.7\MD

Sampler #10 29.56 Duplicate #13 ID EDWD\N3DEW1\13.8\10 MS Duplicate #13 ID EDWD\N3DEW1\13.8\MDSampler #11 32.51 Duplicate #14 ID EDWD\N3DEW1\10.8\10 MS Duplicate #14 ID EDWD\N3DEW1\10.8\MDSampler #12 35.47 Duplicate #15 ID NA MS Duplicate #15 ID NASampler #13 38.42Sampler #14 41.37Sampler #15 NA

PDBS deployment date:

Edwards AFB

Yes

04/21/021615PDBS deployment date:

12

403142-4


Parsons coordinated with the conventional sampling contractor to retrieve the PDBSs as close in time to the conventional sampling of the same well as feasible. The incumbent environmental monitoring contractor typically performed the conventional sampling as part of their regularly scheduled LTM program.

Because the conventional sampling typically was not performed by Parsons, and because of concerns that the wells be allowed to equilibrate in terms of water level and turbidity following PDBS retrieval and prior to conventional sampling, lag times between the two sampling events of at least one to two days typically occurred. As shown in Appendix A, lag times ranged from 0 (conventional samples collected the same day as PDBS retrieval) to 49 days. Lag times often were relatively large on very large sites containing many wells (e.g., Vandenberg AFB) because the conventional sampling events at these sites took up to a few weeks to complete. As a result, PDBS retrieval at wells sampled toward the end of the conventional sampling event occurred weeks prior to the conventional sampling of the same wells. The effect of time lag between sampling events on the comparability of the PDB and conventional sampling data sets is discussed in Section 3.6.3. Parsons did perform both the PDB sampling and at least a portion of the conventional sampling at Bolling, Buckley, Andrews, and Dover AFBs because the regularly scheduled conventional sampling events at these installations were relatively limited in scope.

Upon retrieval, the end cap on the samplers was removed, and water samples were transferred into 40-mL volatile organics analysis (VOA) vials. Sample transfer for 45 wells at 3 installations (Columbus AFB, Keesler AFB, and March ARB) was performed using a straw provided by the PDBS vendor. Sample transfer for the remaining wells was performed by removing the end cap and pouring the water directly into the sample container. As indicated by data presented in Section 3.3.5, the sample transfer method did not significantly affect the correlation between PDBS and conventional results. The samples were preserved on ice and submitted to a fixed-base laboratory for analysis (see Section 2.2).

Conventional purging and sampling techniques varied by installation and included 3-casing-volume purge and sample using a bailer, submersible pump, or peristaltic pump, and low-flow (i.e., micropurge) techniques using either peristaltic or submersible pumps. The conventional sampling methodology and equipment used at each installation are summarized in Appendix A.

A portion of the PDB sampling at Edwards and Vandenberg AFBs had to be repeated at a later date due to the use of improper field procedures during the initial PDBS retrieval event at these installations. Details regarding the scope of these resampling events are contained in the site-specific reports for these installations (Attachment 1). At Vandenberg AFB, the PDB resampling event was performed immediately prior to initiation of a regularly-scheduled conventional sampling event. At Edwards AFB, the PDB resampling was performed approximately 26 days following the conclusion of a regularly scheduled conventional sampling event.

2.2 LABORATORY ANALYSIS AND DATA VALIDATOIN

In order to minimize variability between sample populations (i.e., conventional and PDB samples), the same laboratory and analytical protocol that were used for


conventional sample analysis also were used for PDB sample analysis. For each sampled installation, the laboratory was instructed to handle the PDB and conventional samples identically to the extent feasible to minimize analytical variability as a source of variation between the two sets of results.

A Level III validation was performed for a minimum of 10 percent of the PDBS analytical results for each installation. In some cases, the conventional results were received from the conventional sampling contractor in a validated format. In cases where unvalidated conventional data were received, Parsons performed a Level III validation on a minimum of 10 percent of these data also. Validation consisted of examining data deliverables to determine data quality. This included application of data qualifiers to the analytical results based on adherence to method protocols and project-specific quality assurance (QA)/QC limits. Method protocols reviewed included:

• analytical holding times,

• method blanks,

• trip blanks,

• surrogate spikes,

• internal standards,

• matrix spikes/matrix spike duplicates (MS/MSDs),

• laboratory control samples (LCSs), and

• hardcopy data review.

Data qualifiers were applied to analytical results during the data validation process. All data were validated using method-applicable guidelines and in accordance with the National Functional Guidelines for Organic Data Review (US Environmental Protection Agency [USEPA], 1996) as modified for SW8260B requirements.


SECTION 3

PDBS PERFORMANCE ASSESSMENT

3.1 VERTICAL DISTRIBUTION OF CONTAMINANTS

A vertical distribution coefficient (VD) was calculated to quantify the degree of vertical variation in contaminant concentrations measured with PDBSs placed at different depths within a well. The VD for each well was computed using the following formula:

X

X

PDB

xPDBPDB

MedianMinMax −

where ( xPDBPDB MinMax X − ) is the range of measured values of a specific chemical at a given well, and

XPDBMedian is the median of measured values of a specific chemical at

the same well. A higher VD corresponds to a greater degree of variability of measurements of a chemical at a given well; likewise, a lower VD corresponds to low variability of measurements at a well. The VD is the non-parametric equivalent of the coefficient of variation, or the standard deviation divided by the mean of a set of values, a measure of variability for normally-distributed populations.

Vertical distribution coefficients were calculated for benzene and trichloroethene (TCE). Wells for which there were no detections of these analytes in the PDB samples, or for which only one PDB sample was acquired, were excluded from the analysis. In the case where one or more of the PDB concentrations was below the method detection limit (MDL) (i.e., non-detect), two VDs were calculated:

1. VD0: Non-detect values were assigned a value of 0.

2. VDMDL: Non-detect values were assigned the value of the MDL.

The VDs for benzene and TCE for both non-detect cases are presented in Appendix B. In the case where the median of the group of measurements at a well was zero, a VD0 could not be calculated (e.g., the benzene VD0 for well W9). Figure 3.1-1 is a plot of eight different VD0 and VDMDL groupings for both benzene and TCE versus the percentage of wells that had VDs within each group. The majority (76 to 83 percent) of VDs in the data set were less than 1, suggesting a relatively low degree of vertical variation in TCE and benzene concentrations.

A statistical test of correlation, the Spearman’s Rank-Order Correlation Coefficient (SROCC) test, was applied to the VDMDL populations of both benzene and TCE as compared to several other parameters including:

FIGURE 3.1-1VERTICAL DISTRIBUTION COEFFICIENT VERSUS PERCENT OF WELLS IN

CATEGORYPDBS COMPREHENSIVE REPORT

0%

5%

10%

15%

20%

25%

0 to 0.050 0.051 to 0.100 0.101 to 0.150 0.151 to 0.300 0.301 to 0.500 0.501 to 1.000 1.001 to 5.000 > 5.001

Vertical Distribution Coefficient Group

Perc

ent o

f Wel

ls p

er C

ateg

ory

TCE where non-detects were assigned method detection limit value TCE where non-detects were assigned a value of zeroBenzene where non-detects were assigned method detection limit value Benzene where non-detects were assigned a value of zero

Number of Wells per Category:VDMDL TCE = 151VD0 TCE = 148VDMDL Benzene = 74VD0 Benzene = 72

403143-2


• VDMDL of benzene to VDMDL of TCE,

• VDMDL of benzene and TCE to the length of the screened interval of each well,

• VDMDL of benzene and TCE to the minimum head of water that was above the top of the well screen during the PDBS deployment period,

• VDMDL of benzene and TCE to the correlation ratio (a comparison of the PDB and conventional sampling results which is introduced and discussed in Section 3.2) for all samples,

• VDMDL of benzene and TCE to the correlation ratio for wells where the conventional sample was collected following a 3-casing-volume purge, and

• VDMDL of benzene and TCE to the correlation ratio for wells where the conventional sample was collected following a micropurge.

The VDMDL was selected for use in the SROCC test instead of the VD0 because results of both non-detect analyses were similar.

The SROCC test was applied to measure the non-parametric (i.e., no assumptions made involving an estimation of the parameters of a statistic) correlation between variables. Spearman’s correlation coefficient (rs) is the non-parametric analogue to the Pearson product-moment correlation coefficient (the R2 value obtained for a best-fit trend line in Microsoft Excel®). Spearman’s rs was used instead of the Pearson coefficient because the assumptions underlying the Pearson product-moment correlation are violated in that the populations being evaluated are not necessarily normally-distributed and no test was performed to determine what other type(s) of distributions may be present.

rs and other measures of correlation are descriptive statistical measures that represent the degree of relationship between two or more variables. rs is based on an analysis of two sets of ranks. For the PDBS data set, rs is employed to evaluate data for n subjects (i.e., wells), each of whom has an associated value for two variables (e.g., Correlation Ratio and Vapor Pressure). Within each of the variables, the n scores are rank-ordered. Spearman’s rank-order correlation coefficient determines the degree to which a monotonic relationship exists between two variables. A monotonic increasing (associated with positive correlation) relationship exists when an increase in the value of one variable is always accompanied by an increase in the value of the other variable; a monotonic decreasing (associated with a negative correlation) relationship exists if an increase in the value of one variable is always accompanied by a decrease in the value of the other variable.

The same general guidelines that are used to interpret the value of the Pearson product-moment correlation coefficient can be applied to Spearman’s rank-order correlation coefficient. Thus, rs ranges from –1 to +1; the closer |rs| is to 1, the stronger the monotonic relationship, and the closer |rs| is to 0, the weaker the monotonic relationship between the two variables. When rs = 0, no monotonic relationship is present. The sign of rs indicates the direction of the relationship; for example, a positive correlation indicates that an increase of one variable is associated with an increase in the


other value, and a negative correlation indicates than an increase in one variable is associated with a decrease in the other variable.

Once the rs is calculated, it is common practice to determine whether the absolute value of the correlation coefficient is large enough to conclude that the correlation coefficient between the two variables is some value other than zero.

To test the statistical significance of the Spearman’s rank-order correlation coefficient, the t distribution was employed (note that this is the same methodology for testing the significance of the Pearson’s rs value).

This calculated t-value is associated with a p-value based on the Table of Student’s t Distribution. The p-value, or observed level of significance, is the smallest level of significance at which the correlation ratio is not statistically equal to zero. Typical significance levels are α = 0.05, 0.01 and 0.1. The confidence level is the probability value 1-α. For example, a test of significance of a given rs value that resulted in a p-value of 0.03 would correspond to confidence level of 1 minus 0.03, or 97% confidence level that the two test variables have a non-zero correlation.

In the PDBS analysis, rs values and the associated tests for significance were conducted using StatSoft’s Statistica 6.0 software. A detailed explanation of these procedures is provided in Sheskin, 2000.

Table 3.1-1 presents the results of the SROCC analysis of VDMDL for benzene to the six variables listed above. The vertical distribution coefficient for benzene was found to have a non-zero correlation coefficient (with a confidence level greater than 90%) to five of the six variables, with the exception of the correlation ratio (discussed in Section 3.2) for the subset of wells sampled using a micropurge method. In other words, a direct relationship exists between the VDMDL for benzene and:

• The VDMDL for TCE (i.e., the higher the degree of vertical variation in benzene concentrations, the higher the degree of vertical variation in TCE concentrations),

• Length of the well screened interval (i.e., as the length of the well screen increases, so does the degree of vertical variation in benzene concentrations),

• Head above the top of the well screen (i.e., as the head above the top of the well screen increases, so does the degree of vertical variation in benzene concentrations),

• Correlation ratio for wells sampled conventionally following a 3-volume purge (i.e., higher degree of vertical variation in benzene concentrations in a well resulted in higher correlation ratios between PDB and conventional samples when the conventional sample was collected following a 3-casing volume purge), and

• Correlation ratio for all wells (i.e., higher degree of vertical variation in benzene concentrations resulted in higher correlation ratios between PDB and conventional samples, regardless of the conventional sampling method).


TABLE 3.1-1 SUMMARY OF SPEARMAN’S RANK-ORDER CORRELATION COEFFICIENT

RESULTS FOR BENZENE PDBS COMPREHENSIVE REPORT

Benzene Vertical Distribution Correlation To:

Number of Samples

Spearman rs

p-level (2-tailed)

Level of Significance

TCE Vertical Distribution 29 0.60 0.00 99.9% Screened Interval 74 0.43 0.00 100.0% Correlation Ratio, 3-Volume-Purge Sampling

44 0.32 0.04 96.4%

Minimum Head Above Top of Screen 74 0.24 0.04 96.1% Correlation Ratio, All Data 74 0.22 0.06 93.7% Correlation Ratio, Micropurge Sampling

30 0.00 1.00 0.0%

Table 3.1-2 presents the results of the SROCC analysis of VDMDL for TCE to the same five parameters that were examined with VDMDL for benzene (with the exception of TCE VD vs. Benzene VD, which would be redundant). The vertical distribution coefficient for TCE was found to have a non-zero correlation coefficient (with a confidence level of at least 90 percent) to two out of five variables. In other words, a direct relationship exists between the VDMDL for TCE and:

• The length of the well screened interval (i.e., as the length of the well screen increases, so does the degree of vertical variation in TCE concentrations), and

• The correlation ratio for wells sampled conventionally following a micropurge (i.e., higher degree of vertical variation in TCE concentrations resulted in higher correlation ratios between PDB and conventional samples when the conventional sample was collected following a micropurge).

TABLE 3.1-2 SUMMARY OF SPEARMAN’S RANK-ORDER CORRELATION COEFFICIENT

RESULTS FOR TCE PDBS COMPREHENSIVE REPORT

TCE Vertical Distribution Correlation To:

Number of Samples

Spearman rs

p-level (2-tailed)

Level of Significance

Correlation Ratio, Micropurge Sampling

38 0.31 0.05 94.6%

Screened Interval 111 0.16 0.10 89.6% Correlation Ratio, All Data 111 0.10 0.29 71.3% Minimum Head Above Screen 111 -0.05 0.63 36.7% Correlation Ratio, 3-Volume Purge Sampling

73 -0.03 0.79 20.7%

Overall, the evaluation of the vertical distribution of benzene and TCE in the set of wells included in this demonstration can provide guidance on the use and placement of


PDBSs in wells that are being evaluated for PDBS implementation. For example, the proper placement and vertical distribution of PDBSs in wells with relatively long screens may be more important than the placement and vertical distribution of PDBSs in wells with relatively short screens. Similarly, higher degrees of correlation between PDB and conventional sample results may be realized in certain circumstances (e.g., TCE may correlate better in wells with high vertical TCE distribution and that are sampled conventionally following a micropurge). These considerations may be useful when developing a PDBS demonstration, evaluating the results, and discussing with regulators the long-term conversion of sampling methodology from conventional methods to the PDBS method.

3.2 CORRELATION PROCEDURE

In order to ensure that the correlation approach for each site-specific PDBS demonstration was consistent, a standardized approach to data comparison was developed and applied to data sets from each installation. This approach is described below.

If the maximum PDBS analytical result obtained for a well was greater than or equal to the conventional sampling result for that well, the PDBS method was inferred to be appropriate for use in that well (Vroblesky, 2001). Nonetheless, comparison to the conventional sampling results was performed in all instances. Specifically, analytical results for all samples collected using the diffusion samplers were compared to results from the conventional sampling using the following relative-percent-difference (RPD) equation:

RPD = 100*[abs(D-C)]/[(D+C)/2]

Where:

abs = absolute value;

D = diffusion sampler result; and C = conventional sample result.

An RPD less than or equal to 15 was initially proposed as an indicator of comparable data. That is, if the maximum PDBS result was less than the conventional sample result but was within 15 RPD of the conventional result, then acceptable correlation between sample results was demonstrated. However, upon reviewing standard conventions for comparing primary and field duplicate samples (USEPA, 1996, 1999, and 2000; Radian International, 1997 and 1998; EarthTech, 1998; McClellan AFB, 2000; Goad, 2001;), the acceptance criterion of 15 RPD was deemed to be overly conservative. Based on the literature RPD criteria, which ranged from 30 to 50, a revised value of 30 was selected as the criterion for this PDBS demonstration. This value was also used as the comparison criterion for the Base-wide PDBS demonstration performed at McClellan AFB (2000). The revised acceptance criteria used to determine suitability of PDB sampling in the site-specific reports (Attachment 1) are as follow:

• PDBS ≥ Conventional Criterion: If at least one PDBS result for a given well is equal to or greater than the conventional sampling result, PDB sampling was deemed appropriate for use in that well.


• RPD Criterion: If either the PDB or the conventional sample result is greater than three times the laboratory reporting limit (RL), and the PDBS result is less than the conventional result, then an RPD of 30 was used as the acceptance criterion.

• RL Criterion: If both the PDB and conventional sample results are less than or equal to three times the laboratory RL, a value of ± the RL was used as the range of acceptance between the two values. If the RLs for the conventional and PDB samples are different, the lowest RL was used to determine the acceptance range. Use of the lowest RL in these instances made this criterion particularly conservative; use of less restrictive criteria may be justified.

There are many instances where more than one of the correlation criteria were met per PDBS/conventional comparison. However, as long as at least one of the correlation criteria were met per comparison, then PDB sampling was deemed to be an acceptable alternative sampling method for that analyte in that well.

The variance between the results of PDB and conventional samples would be expected to be greater than the variance between a primary and field duplicate sample. This is due in part to the following considerations:

• PDB and conventional sampling was typically performed by different contractors. Although the same SOPs for tasks common to both sampling approaches (e.g., sample handling and preservation) were followed by both sampling teams, some variability is to be expected simply because different individuals were involved. Conversely, primary and field duplicate samples are collected by the same sampling personnel.

• Logistically, it was not always possible to perform PDB sampling immediately prior to conventional sampling. In some instances, a time lag of several weeks to months occurred between PDB and conventional sampling (Appendix A). Although it is unlikely that groundwater chemistry will change significantly over the course of a few hours, some variability can occur over the course of several days, weeks, or months. In contrast, primary and field duplicate samples are collected at the same time.

• PDB and conventional samples were typically not included in the same laboratory sample delivery group (SDG). Therefore, even though the same laboratory was used, the PDB samples may have been analyzed by different instrument operators, on different days, and potentially using different equipment than the conventional samples. Although laboratory QA/QC practices attempt to achieve temporal consistency for analyses, some variability is to be expected. Conversely, primary and field duplicate samples typically are analyzed as part of the same SDG.

• The PDB and conventional sampling methods are inherently different. For example, different equipment is used for the different methods (e.g., dedicated [PDBS] versus non-dedicated [conventional] equipment), and different sample collection procedures are employed (i.e., passive sample collection [PDBS] versus active sample collection [pumping/conventional]). These differences are likely to introduce variability in the sample results; whereas primary and field duplicate samples are collected using the same sampling equipment and procedures.


Therefore, the selected RPD criterion of 30 is likely conservative.

As described above, if the correlation criteria were met for any PDBS in a well, then PDB sampling was considered to be an acceptable alternative sampling method for that analyte in that well. Conversely, if none of the PDBS results for an analyte in a given well met the conventional sampling result correlation criteria, further review of the well- or sample-specific conditions was recommended, including review of:

• The hydrogeology of the material surrounding the well screen;

• Sample handling differences (e.g., holding times, sample preservation);

• Sample collection differences (e.g., time lag between sampling events);

• Sample analysis differences (e.g., laboratory control sample differences); and/or

• Chemical-specific properties that may impact its compatibility with the PDBS method.

There were instances where results for some of the analytes detected in samples from a well met the correlation criteria while results for other analytes in the same well did not. Similarly, there were instances where results for one analyte met the correlation criteria in samples from several wells but did not in samples from other wells. For each compound and well, a correlation ratio was calculated by dividing the total number of instances where correlation criteria were met by the total number of instances where correlation was evaluated. As described above, even though the correlation criteria may not have been met in every instance for a well or analyte, PDB sampling may still be a viable alternative to conventional sampling for that situation. However, further review of the data sets should be performed prior to a final determination regarding the suitability of PDBS use.

In the site-specific reports, further review of comparative data sets was typically performed when the correlation criteria for a well or analyte were met in fewer than 70 percent of the comparisons (i.e., correlation ratios less than 70 percent). For example, if TCE was detected in samples from 10 wells, and the correlation criteria were met for 9 of these samples (90-percent correlation ratio), typically no further review of TCE results was performed. Conversely, if 10 analytes were detected in a sample, but only one of those analytes met the correlation criteria (10-percent correlation ratio), then the conditions at that well were reviewed further. The 70-percent threshold value was not intended to indicate success or failure of PDB sampling, but rather to focus further review on those wells or analytes for which lower correlation ratios were observed.

The approach described above and used in the site-specific reports has been expanded in this report to consider general trends that appear in the scale of the entire data set, as opposed to the site-specific scale (Section 3.3.2).

Several variables can affect the comparability of PDB and conventional data sets. These variables can be grouped into three categories:

• compound-specific variables,


• well-specific variables, and

• technology-specific variables.

These variables, and their relative influence on the comparability of the data sets, are evaluated in Section 3.3.

3.3 CORRELATION SUMMARY

3.3.1 Correlation Ratio Overview

Summaries of the PDB and conventional sample comparisons are presented in Tables 3.3-1 (by well) and 3.3-2 (by analyte). These tables present the number of comparisons made, the number of instances where correlation criteria were and were not met, the number of instances where correlation could not be determined, and the overall correlation ratio for each well (Table 3.3-1) and analyte (Table 3.3-2). These tables also provide correlation ratio summaries for several different sets of correlation criteria, which are discussed in Section 3.3.2. However, this section focuses exclusively on the original set of correlation criteria described in Section 3.2 and shown in Tables 3.3-1 and 3.3-2 as “PDBS ≥ Conventional, RPD = 30, RL” in the left-most column of correlation criteria.

A total of 320 wells had at least one detected analyte in either the conventional or PDB samples. Of those, the correlation criteria were met for at least 70 percent of the detected compounds in 231 wells; 88 wells met the correlation criteria for fewer than 70 percent of the detected compounds, and correlation could not be determined for one well (Table 3.3-1).

A total of 58 analytes were detected in PDB and/or conventional samples. Of those, results for 37 analytes met the correlation criteria in at least 70 percent of the 320 wells having detections; 20 analytes met the correlation criteria in fewer than 70 percent of the sampled wells having detections, and correlation could not be determined for one analyte (Table 3.3-2).

3.3.2 Application of New and Revised Correlation Criteria

The correlation ratios presented in Tables 3.3-1 and 3.3-2 are based on application of the correlation criteria defined in Section 3.2; these criteria were developed prior to initiation of any data collection for this project. However, during the course of data collection it became evident that two new correlation criteria and one modification to an existing correlation criterion were justified. The new correlation criteria include:

1. Low-Magnitude Concentrations Criterion: Instances where a small difference in concentration (i.e., less than 5 micrograms per liter [µg/L]) between PDB and conventional sample results may prevent the meeting of correlation criteria, but do not necessarily indicate a failure of the PDB technology. For example, in a case where the PDBS result is 3 µg/L with an RL of 1 µg/L, and the corresponding conventional sample result is 6 µg/L with an RL of 5 µg/L, although none of the original correlation criteria are met, application of the low-magnitude concentrations criterion would permit this comparison to demonstrate correlation.

Total Analytes Detected

Total "Yes"

Total "No"

Total "ND"

Correlation Ratio


Total "Yes"

Total "No"

Total "ND"

Correlation Ratio


Total "Yes"

Total "No"

Total "ND"

Correlation Ratio


Total "Yes"

Total "No"

Total "ND"

Correlation Ratio


Total "Yes"

Total "No"

Total "ND"

Correlation Ratio

Andrews H6 7 5 2 1 71% 7 6 1 1 86% 7 6 1 1 86% 6 4 2 0 67% 6 5 1 0 83%Andrews MW02-ST14 8 8 0 0 100% 8 8 0 0 100% 8 8 0 0 100% 7 7 0 0 100% 7 7 0 0 100%Andrews MW04-ST14 6 6 0 0 100% 6 6 0 0 100% 6 6 0 0 100% 6 6 0 0 100% 6 6 0 0 100%Andrews MW10-ST14 5 4 1 0 80% 5 5 0 0 100% 5 4 1 0 80% 5 4 1 0 80% 5 5 0 0 100%Andrews MW11-ST14 3 3 0 0 100% 3 3 0 0 100% 3 3 0 0 100% 2 2 0 0 100% 2 2 0 0 100%Andrews MW12-ST14 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100%Andrews MW19-ST14 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100%Andrews OW2A-SS01 3 3 0 0 100% 3 3 0 0 100% 3 3 0 0 100% 3 3 0 0 100% 3 3 0 0 100%Andrews OW2B-SS01 2 2 0 1 100% 2 2 0 1 100% 2 2 0 1 100% 2 2 0 0 100% 2 2 0 0 100%Andrews OW3A-SS01 9 8 1 1 89% 9 9 0 1 100% 9 8 1 1 89% 8 7 1 0 88% 8 8 0 0 100%Andrews OW3B-SS01 5 4 1 1 80% 5 5 0 1 100% 5 5 0 1 100% 5 4 1 0 80% 5 5 0 0 100%Andrews PW01-SS01 7 5 2 0 71% 7 7 0 0 100% 7 6 1 0 86% 6 4 2 0 67% 6 6 0 0 100%Andrews SS01-DP01 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 1 1 0 0 100% 1 1 0 0 100%Andrews SS01-DP02 7 7 0 1 100% 7 7 0 1 100% 7 7 0 1 100% 6 6 0 0 100% 6 6 0 0 100%Andrews SS01-DP03 6 5 1 1 83% 6 5 1 1 83% 6 5 1 1 83% 6 5 1 0 83% 6 5 1 0 83%Andrews SS01-DP04 5 5 0 1 100% 5 5 0 1 100% 5 5 0 1 100% 4 4 0 0 100% 4 4 0 0 100%Andrews SS01-DP17 8 6 2 1 75% 8 7 1 1 88% 8 6 2 1 75% 7 5 2 0 71% 7 6 1 0 86%Andrews SS01-DP18 6 6 0 1 100% 6 6 0 1 100% 6 6 0 1 100% 5 5 0 0 100% 5 5 0 0 100%Andrews SS01-DP19 4 4 0 1 100% 4 4 0 1 100% 4 4 0 1 100% 3 3 0 0 100% 3 3 0 0 100%Andrews SS01-DP20 5 3 2 0 60% 5 4 1 0 80% 5 3 2 0 60% 5 3 2 0 60% 5 4 1 0 80%Andrews SS01-DP21 8 6 2 1 75% 8 6 2 1 75% 8 6 2 1 75% 7 5 2 0 71% 7 5 2 0 71%Andrews SS01-DP25 4 4 0 1 100% 4 4 0 1 100% 4 4 0 1 100% 3 3 0 0 100% 3 3 0 0 100%Andrews SS01-DP26 3 3 0 1 100% 3 3 0 1 100% 3 3 0 1 100% 2 2 0 0 100% 2 2 0 0 100%Andrews SS01-DP27 7 7 0 1 100% 7 7 0 1 100% 7 7 0 1 100% 6 6 0 0 100% 6 6 0 0 100%Andrews SS01-DP28 2 2 0 1 100% 2 2 0 1 100% 2 2 0 1 100% 1 1 0 0 100% 1 1 0 0 100%Andrews SS01-DP29 1 1 0 1 100% 1 1 0 1 100% 1 1 0 1 100% 0 0 0 0 NA 0 0 0 0 NABolling H2MW01 9 5 4 0 56% 9 5 4 0 56% 9 7 2 0 78% 8 5 3 0 63% 8 7 1 0 88%Bolling H2MW02 6 4 2 0 67% 6 4 2 0 67% 6 5 1 0 83% 6 4 2 0 67% 6 5 1 0 83%Bolling H2MW03 5 4 1 0 80% 5 4 1 0 80% 5 5 0 0 100% 4 4 0 0 100% 4 4 0 0 100%Bolling HPMW11 9 6 3 0 67% 9 6 3 0 67% 9 8 1 0 89% 9 6 3 0 67% 9 8 1 0 89%Bolling MW-11 4 3 1 0 75% 4 3 1 0 75% 4 3 1 0 75% 4 3 1 0 75% 4 3 1 0 75%Bolling MW-15 1 1 0 1 100% 1 1 0 1 100% 1 1 0 1 100% 1 1 0 1 100% 1 1 0 1 100%Bolling MW-3R 1 1 0 0 100% 1 1 0 0 100% 1 1 0 0 100% 1 1 0 0 100% 1 1 0 0 100%Bolling MW-4R 3 2 1 0 67% 3 3 0 0 100% 3 3 0 0 100% 3 2 1 0 67% 3 3 0 0 100%Bolling MW-6R 4 2 2 0 50% 4 2 2 0 50% 4 2 2 0 50% 4 2 2 0 50% 4 2 2 0 50%Buckley FDA-MW11 4 3 1 3 75% 4 3 1 3 75% 4 3 1 3 75% 4 3 1 2 75% 4 3 1 2 75%Buckley FDA-MW11B 4 3 1 4 75% 4 3 1 4 75% 4 3 1 4 75% 4 3 1 3 75% 4 3 1 3 75%Buckley FDA-MW11C 8 7 1 0 88% 8 7 1 0 88% 8 7 1 0 88% 7 6 1 0 86% 7 6 1 0 86%

Well IDInstallation

TABLE 3.3-1 CORRELATION RATIO OVERVIEW BY WELL


PDBS ≥ Conventional, RPD = 50, RL, Low Magnitude, Inappropriate

Comparisons Removed

CORRELATION CRITERIA APPLIED

PDBS ≥ Conventional, RPD = 30, RL PDBS ≥ Conventional, RPD = 50, RL PDBS ≥ Conventional, RPD = 30, RL, Low Magnitude

PDBS ≥ Conventional, RPD = 30, RL, Inappropriate Comparisons Removed

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Total "Yes"

Total "No"

Total "ND"

Correlation Ratio


Total "Yes"

Total "No"

Total "ND"

Correlation Ratio


Total "Yes"

Total "No"

Total "ND"

Correlation Ratio


Total "Yes"

Total "No"

Total "ND"

Correlation Ratio


Total "Yes"

Total "No"

Total "ND"

Correlation RatioWell IDInstallation

TABLE 3.3-1 (Continued)CORRELATION RATIO OVERVIEW BY WELL



Comparisons Removed




Buckley FDAMW15 3 2 1 0 67% 3 2 1 0 67% 3 2 1 0 67% 3 2 1 0 67% 3 2 1 0 67%Buckley FDAMW16 3 2 1 2 67% 3 2 1 2 67% 3 2 1 2 67% 2 1 1 2 50% 2 1 1 2 50%Buckley FDAMW22 3 2 1 0 67% 3 2 1 0 67% 3 2 1 0 67% 2 1 1 0 50% 2 1 1 0 50%Buckley FDAMW25 3 3 0 0 100% 3 3 0 0 100% 3 3 0 0 100% 2 2 0 0 100% 2 2 0 0 100%Buckley FDAMW26 1 1 0 1 100% 1 1 0 1 100% 1 1 0 1 100% 1 1 0 0 100% 1 1 0 0 100%Buckley FDAMW27 1 1 0 0 100% 1 1 0 0 100% 1 1 0 0 100% 1 1 0 0 100% 1 1 0 0 100%Buckley FDAMW28 2 1 1 0 50% 2 2 0 0 100% 2 1 1 0 50% 2 1 1 0 50% 2 2 0 0 100%Buckley FDAMW32 4 4 0 0 100% 4 4 0 0 100% 4 4 0 0 100% 3 3 0 0 100% 3 3 0 0 100%Buckley FDAMW34 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100%Buckley FDAMW35 4 4 0 0 100% 4 4 0 0 100% 4 4 0 0 100% 2 2 0 0 100% 2 2 0 0 100%Buckley FDAMW36 3 3 0 0 100% 3 3 0 0 100% 3 3 0 0 100% 2 2 0 0 100% 2 2 0 0 100%Buckley FWAMW4 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 1 1 0 0 100% 1 1 0 0 100%Buckley FWAPZ4 1 1 0 0 100% 1 1 0 0 100% 1 1 0 0 100% 1 1 0 0 100% 1 1 0 0 100%Columbus DW16 4 4 0 0 100% 4 4 0 0 100% 4 4 0 0 100% 2 2 0 0 100% 2 2 0 0 100%Columbus DW85 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 0 0 0 0 NA 0 0 0 0 NAColumbus W10 6 6 0 0 100% 6 6 0 0 100% 6 6 0 0 100% 4 4 0 0 100% 4 4 0 0 100%Columbus W104 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 0 0 0 0 NA 0 0 0 0 NAColumbus W105 18 6 12 0 33% 18 9 9 0 50% 18 10 8 0 56% 15 3 12 0 20% 15 9 6 0 60%Columbus W106 20 19 1 0 95% 20 20 0 0 100% 20 19 1 0 95% 17 17 0 0 100% 17 17 0 0 100%Columbus W13 16 5 11 0 31% 16 5 11 0 31% 16 7 9 0 44% 14 3 11 0 21% 14 5 9 0 36%Columbus W18 13 12 1 0 92% 13 12 1 0 92% 13 13 0 0 100% 11 10 1 0 91% 11 11 0 0 100%Columbus W21 18 18 0 0 100% 18 18 0 0 100% 18 18 0 0 100% 15 15 0 0 100% 15 15 0 0 100%Columbus W22 10 8 2 0 80% 10 8 2 0 80% 10 10 0 0 100% 8 6 2 0 75% 8 8 0 0 100%Columbus W35 14 12 2 0 86% 14 12 2 0 86% 14 12 2 0 86% 13 12 1 0 92% 13 12 1 0 92%Columbus W47 8 5 3 0 63% 8 7 1 0 88% 8 7 1 0 88% 6 3 3 0 50% 6 5 1 0 83%Columbus W49 8 7 1 0 88% 8 7 1 0 88% 8 7 1 0 88% 6 6 0 0 100% 6 6 0 0 100%Columbus W8 5 4 1 1 80% 5 4 1 1 80% 6 6 0 0 100% 3 2 1 1 67% 4 4 0 0 100%Columbus W81 11 11 0 0 100% 11 11 0 0 100% 11 11 0 0 100% 9 9 0 0 100% 9 9 0 0 100%Columbus W82 2 2 0 1 100% 2 2 0 1 100% 2 2 0 1 100% 0 0 0 1 ND 0 0 0 1 NDColumbus W84 15 14 1 0 93% 15 15 0 0 100% 15 14 1 0 93% 14 14 0 0 100% 14 14 0 0 100%Columbus W86 4 4 0 0 100% 4 4 0 0 100% 4 4 0 0 100% 2 2 0 0 100% 2 2 0 0 100%Columbus W87 15 14 1 0 93% 15 14 1 0 93% 15 15 0 0 100% 13 12 1 0 92% 13 13 0 0 100%Columbus W9 7 7 0 0 100% 7 7 0 0 100% 7 7 0 0 100% 5 5 0 0 100% 5 5 0 0 100%Dover DM302S 6 5 1 0 83% 6 6 0 0 100% 6 5 1 0 83% 6 5 1 0 83% 6 6 0 0 100%Dover DM303S 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100%Dover DM337S 2 1 1 0 50% 2 1 1 0 50% 2 1 1 0 50% 1 1 0 0 100% 1 1 0 0 100%Dover DM338S 3 0 3 0 0% 3 0 3 0 0% 3 3 0 0 100% 3 0 3 0 0% 3 3 0 0 100%Dover DM343S 1 0 1 0 0% 1 0 1 0 0% 1 0 1 0 0% 0 0 0 0 NA 0 0 0 0 NA

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403143-11


Total "Yes"

Total "No"

Total "ND"

Correlation Ratio


Total "Yes"

Total "No"

Total "ND"

Correlation Ratio


Total "Yes"

Total "No"

Total "ND"

Correlation Ratio


Total "Yes"

Total "No"

Total "ND"

Correlation Ratio


Total "Yes"

Total "No"

Total "ND"

Correlation RatioWell IDInstallation

TABLE 3.3-1 (Continued)CORRELATION RATIO OVERVIEW BY WELL



Comparisons Removed




Dover DM345S 6 5 1 1 83% 6 5 1 1 83% 6 5 1 1 83% 6 5 1 1 83% 6 5 1 1 83%Dover DM381S 6 5 1 0 83% 6 6 0 0 100% 6 5 1 0 83% 6 5 1 0 83% 6 6 0 0 100%Dover DM390S 7 5 2 0 71% 7 5 2 0 71% 7 5 2 0 71% 6 5 1 0 83% 6 5 1 0 83%Dover DM393S 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100% 2 2 0 0 100%Dover DM406S 7 3 4 0 43% 7 3 4 0 43% 7 4 3 0 57% 7 3 4 0 43% 7 4 3 0 57%Dover DM431S 7 7 0 0 100% 7 7 0 0 100% 7 7 0 0 100% 7 7 0 0 100% 7 7 0 0 100%Dover DM432S 6 6 0 0 100% 6 6 0 0 100% 6 6 0 0 100% 6 6 0 0 100% 6 6 0 0 100%Dover MW235D 10 8 2 0 80% 10 8 2 0 80% 10 8 2 0 80% 9 7 2 0 78% 9 7 2 0 78%Dover MW236D 17 15 2 0 88% 17 16 1

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