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Welcome to ITRC’s Internet Training. Historical Case Analysis of Chlorinated Volatile Organic Compound Plumes March 1999. Sponsored by the ITRC, EPA-TIO & Lawrence Livermore National Laboratory. Today’s Presenters. Greg Bartow, R.G., CH.g. California RWQCB [email protected]

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Welcome to itrc s internet training

Welcome to ITRC’s Internet Training

Historical Case Analysis of Chlorinated Volatile Organic Compound Plumes

March 1999

Sponsored by the ITRC, EPA-TIO

&

Lawrence Livermore National Laboratory


Today s presenters

Today’s Presenters

  • Greg Bartow, R.G., CH.g.

    • California RWQCB

    • [email protected]

  • Walt McNab

    • Environmental Protection Department, Lawrence Livermore National Lab

    • [email protected]

  • David Rice

    • Environmental Protection Department, Lawrence Livermore National Lab

    • [email protected]


Presentation overview

Presentation Overview

  • About the ITRC

  • Description of the methodology and results of a statistical evaluation of hydrologic and contaminant data from chlorinated compound contaminated plumes

  • Questions and Answers

  • Wrap-up and Links to additional

  • information and resources


Who s involved

Who’s Involved?

STATE-LED INITIATIVE WITH:

  • 38 States (and growing)

  • Sponsoring State Organizations

    Environmental Western Southern States

    Council of Governors’ Energy Board

    the States Association

  • Public/Tribal Stakeholders

  • Industry Representatives

  • DOEUS EPADOD


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Creating Tools and Strategies to Reduce Technical and Regulatory Barriers to the Deployment of Innovative Environmental Technologies

Active ITRC States

  • In Situ Bioremediation

  • DNAPLs/In Situ Chemical Oxidation

  • Permeable Reactive Walls

  • Radionuclides

  • Unexploded Ordnance

  • In Situ Biodenitrification

  • Phytoremediation

  • Verification

  • Diffusion Sampler


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Purpose of this Training

  • Understand the factors affecting behavior of the CVOC plumes in ground water from a broad, statistically oriented perspective

  • Enhance your understanding of plume behavior through examination of data from many sites

  • Allow you to focus on the major factors influencing plume behavior increase the efficiency of planning site investigations and cleanup


Cvoc historical case analysis goals

CVOC Historical Case Analysis — Goals

  • Gather case information from over 200 VOC plumes

    • Nation-wide “plumathon”

    • DOE, DOD, Industry, ITRC States, EPA

  • Perform analysis that is defensible and peer reviewed

    • Expert Working Task Force

    • Expert Peer Review Panel

  • Findings and Conclusions based on case analysis

    • Working Task Force prepares

    • Peer Review Panel reviews

  • Recommendations for Policy Change

    • Interstate Technology and Regulatory Cooperation Task Force (ITRC) prepares

    • Peer Review Panel reviews


Working task force

Working Task Force

  • Greg Bartow—California RWQCB

  • Jacob Bear—Technion Institute of Technology

  • Mike Brown/Paul Zielinski—DOE

  • Patrick Haas—DOD/USAF

  • Herb Levine—EPA

  • Curt Oldenburg/Tom McKone—LBL

  • Mike Kavanaugh—Industry

  • Bill Mason/Paul Hadley—ITRC

  • Doug Mackay/Christina Hubbard—University of Waterloo

  • Mohammad Kolhadooz—Industry

  • Mike Pound—DOD/USN

  • Dave Rice (Initiative Coordinator)—LLNL

  • Heidi Temko—California SWRCB

  • Cary Tuckfield—Savannah River Technology Center

  • Walt McNab (Data Analysis Team Leader)—LLNL

  • Richard Ragaini (Data Collection Team Leader)—LLNL


Peer review panel

Peer Review Panel

  • David Ellis–Dupont

  • Lorne Everett–UC Santa Barbara/Geraghty & Miller

  • Marty Faile–USAFCEE

  • William Kastenberg–University of California, Berkeley

  • Perry McCarty–Stanford University

  • Hanadi Rifai–Rice University

  • Lenny Siegel—Pacific Studies Center

  • Todd Wiedemeier–Parson’s Engineering

  • John Wilson–U.S. EPA, ORD


Cvoc historical case analysis potential benefits to nation

CVOC Historical Case Analysis — Potential Benefits to Nation

  • What are the advantages to looking at CVOC plumes nationwide?

    • Similar sites can share common lessons learned

      • High or Low risk VOC release scenarios can be identified

      • Help understand where natural attenuation may be applicable

    • Reduced Cleanup Costs

      • Focus characterization costs on those factors that most influence plume behavior

    • Technology Market Identified

      • Analysis of large number of cases identifies technology needs

      • Defines technology functional requirements


Voc historical case analysis hypothesis questions

VOC Historical Case Analysis — Hypothesis & Questions

  • Hypothesis: Chlorinated solvent cases have natural groupings

  • Hypothesis: These groupings can identify sites that have common predictable characteristics


Cvoc historical case analysis specific questions

CVOC Historical Case Analysis —Specific Questions

  • How often is a dense non-aqueous phase liquid (DNAPL) inferred to be present.

    • Are Plumes with possible DNAPLS longer?

  • How often is there evidence of transformation processes

    • Are plumes with CVOC transformations shorter?

    • Do daughter product plumes behave differently compared to parent CVOC plumes?


Historical case analysis a new data model

Historical Case Analysis: A New Data Model

  • Much of our knowledge of plume behavior comes from well-instrumented research sites.

  • Much of the CVOC groundwater data is collected at poorly-instrumented sites targeted for cleanup.

  • Historical case analyses offers a means for systematically analyzing these data.


Project scope

Project Scope

Source term

  • Collect hydrogeologic and contaminant data from many sites reflecting diverse environmental and release settings.

  • Estimate representative values for key variables.

  • Employ statistical methods to assess relationships between dependent and independent variables.

  • Validate results with probabilistic modeling.

Advection

Transformation


Rules definitions and assumptions

Rules, Definitions, and Assumptions

  • “Plume” defined per CVOC per site.

  • Minimum site characterization requirements.

  • Site exclusion criteria.

    • Daylighting plumes.

    • Plumes undergoing active pump-and-treat.

    • Plumes that were highly complex as a result of unusual conditions.

MW-1

MW-3

MW-2

Plume length (10 ppb)

MW-6

(100 ppb)

MW-4

MW-5

MW-7

Length = Distance from location of max. historical concentration to distal 10-ppb contour.


Definitions of major variables

Definitions of Major Variables

  • Independent variables

    • Source strength

    • Mean groundwater velocity

    • Reductive dehalogenation category assignment

  • Dependent variables

    • Plume length

    • Change in plume length over time (growth rate)


Project data set

Project Data Set

  • 65 sites included in initial study; over 100 in current data set.

  • Data from a variety of release scenarios and sources:

    • D.o.D. and D.O.E. facilities

    • Dry cleaners

    • Commercial industrial sites

    • Landfills


Plume length distributions

Plume Length Distributions


Plume length and source strength

Plume Length and Source Strength

100-ppb plumes

R = 0.40, p = 2 x 10-6


Groundwater velocity

Groundwater Velocity

50th percentile ~ 0.2 ft/day

  • Mean groundwater velocity, v, estimated from Darcy’s law:

    • Geometric mean K estimated from site pumping tests and slug tests.

    • Mean hydraulic gradient from potentiometric surface maps.

    • Mean porosity assumed to be equal to 0.25.

10th percentile ~ 0.005 ft/day

90th percentile ~ 6 ft/day


Plume length and groundwater velocity

Plume Length and Groundwater Velocity

4

R = 0.46, p = 0.006

r = 0.46, p = 0.006

2

0

-2

-4

-6

-8

2.5

2.7

2.9

3.1

3.3

3.5

3.7

3.9

4.1

4.3

Log velocity (ft/day)

Log plume length (ft)


Reductive dehalogenation

Reductive Dehalogenation

No reductive dehalogenation group: 23 sites, no daughter products

Strong reductive dehalogenation group: 20 sites, cis-1,2-DCE and vinyl chloride

Weak reductive dehalogenation group: 18 sites, cis-12,-DCE but no vinyl chloride


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Example: Reductive

Dehalogenation at Site 41350001

Coincident PCE and vinyl chloride plumes

VC and benzene (ppb)

Cl- (ppm)

PCE conc. (ppb)

GW flow direction


Reductive dehalogenation distributions of plume lengths

Reductive Dehalogenation: Distributions of Plume Lengths

No. of plumes

CDF

Plume length (ft)

ANOVA: No significant differences between distributions

Logarithm of plume length (ft)


Where is the reductive dehalogenation effect

Where is the reductive dehalogenation effect?

  • Plume length reduction by reductive dehalogenation is subtle compared to groundwater velocity and source strength effects.

  • Biases in the data collection/analyses processes skew the results between groupings.


Biases in the data set

Biases in the Data Set

100%

90%

80%

70%

60%

Cumulative distribution

50%

40%

Strong RD sites have significantly stronger source terms (p = 0.007).

30%

20%

10%

0%

1.E+00

1.E+02

1.E+04

1.E+06

1.E+08

Max. site concentration (ppb)

No RD

Strong RD

  • Site groundwater velocity contrasts:

    • For Strong-RD group, median groundwater velocity is 0.21 ft/day.

    • For No-RD group, 9 of 13 sites have mean velocities below the Strong-RD group median.


Biases in data set cont d

Biases in Data Set (cont’d)

No RD

No RD

Strong RD

Strong RD

No.

No.

Plume length

Plume length

  • Site screening process may preferentially exclude certain types of sites:

    • Small source, low velocity, reductive dehalogenation  very small plumes not likely to be well-monitored (excluded).

    • Large source, high velocity, no transformation  very large plumes likely to be subject to early remediation (excluded).


Biases in the data set source strength and groundwater velocity

Biases in the Data Set: Source Strength and Groundwater Velocity

p = 0.018


Analysis of covariance

Analysis of Covariance

Sites with no evidence of reductive dehalogenation

Sites with strong evidence of reductive dehalogenation

Geometric means of raw plume lengths

876ft

872ft

Adjusted geometric means (ANCOVA)

1047ft

510ft


Questions and answers

QUESTIONS AND ANSWERS

C0

R, 

v

Plume length


Probabilistic modeling

Probabilistic Modeling

Groundwater velocity

Sensitivity?

Plume length

Solute transport model

Degradationrate


Simulation overview

Simulation: Overview

C0

R, 

v

Plume length

  • Analytical solute transport solution used as model of “average” plume behavior.

  • Monte Carlo techniques used to generate a synthetic plume set.

  • Probability distributions of input variables developed from project database.

  • Two synthetic populations - one transforming and one stable - used to assess reductive dehalogenation effects.

Monte Carlo analysis with Domenico (1987) model


Plume length as a function of source strength simulation vs observation

Plume Length as a Function of Source Strength: Simulation vs. Observation

Observed Plume Set (10-ppb plumes)

Simulated Plume Set

R = 0.36

R = 0.20


Plume length as a function of ground water velocity simulation vs observation

Plume Length as a Function of Ground Water Velocity: Simulation vs. Observation

Observed Plume Set (10-ppb plumes)

Simulated Plume Set

4

4

R = 0.64

R = 0.46

2

2

0

0

Log velocity (ft/day)

Log velocity (ft/day)

-2

-2

-4

-4

-6

-6

-8

-8

2.0

2.5

3.0

3.5

4.0

4.5

2.0

2.5

3.0

3.5

4.0

4.5

Log plume length (ft)

Log plume length (ft)


Contaminant transformation and plume length simulation vs observation

Contaminant Transformation and Plume Length: Simulation vs. Observation

Observed Plume Lengths

p = 0.91

Cumulative distribution

Simulated Plume Lengths

Plume length (ft)

p = 0.51

Cumulative distribution

Plume length (ft)


Analysis of covariance model output

Analysis of Covariance: Model Output

Stable plumes

Transforming plumes

Geometric means of raw plume lengths

790 ft

884 ft

Adjusted geometric means (ANCOVA)

991 ft

705 ft


Temporal analysis of cvoc measurements in wells

Temporal Analysis of CVOC Measurements in Wells

TCE concentrations in 533 wells from 41 sites

  • Analyze temporal trends in data to discern natural attenuation effects

  • Methodology:

    • Rank-based linear regression with time

    • 5 or more distinct sampling events

    • R < -0.5  declining trend

    • R > 0.5  increasing trend


Temporal trends

Temporal Trends

Compound

No. of wells

No. of sites

Decline: increase

Benzene

35

9

7.0

1,1,1-TCA

134

19

6.5

Toluene

21

8

4.5

TCE (+ vinyl chloride)

74

11

3.9

1,2-DCA

34

10

3.5

Chloroform

55

8

2.7

1,1-DCE

183

20

2.6

TCE

533

41

2.5

1,1-DCA

107

17

2.1

PCE

95

21

2.1

Cis-1,2-DCE

63

11

1.2

Vinyl chloride

125

12

0.9

Carbon tetrachloride

97

4

0.7


Ratio analysis 1 1 1 tca and 1 1 dce

Ratio Analysis: 1,1,1-TCA and 1,1-DCE

Median ratio at source: 0.25

Predicted ratio at 1000 ft, assuming mean groundwater velocity of 0.6 ft/day, reaction half-life of 2 years, and 0.2 mole DCE produced from each mole of TCA.


Principal component analysis and reductive dehalogenation

Principal Component Analysis and Reductive Dehalogenation

Median = 77%

Median = 58%

Median = 74%

  • Results of PCA

    • Variance dominated by a single factor - GW flow regime?

    • Effect of reductive dehalogenation is apparent.

    • Results are independent of grouping strategy, i.e. no correlation with:

      • No. of CVOCs

      • No. of samples

No. of sites

No. of sites


Principal component analysis and temporal trends

Principal Component Analysis and Temporal Trends

= site with evidence of reductive dehalogenation

26 sites


Implications

Implications

  • Can historical case data be used to predict plume behavior?

    • Yes: Signals (i.e., expected patterns of plume behavior) can be detected through site-specific noise (i.e., heterogeneities, different disposal histories).


Implications1

Implications

  • What are the key uncertainties associated with evaluating CVOC plume behavior using historical case data and what types of data are needed?

    • Ranges of groundwater velocities at sites (i.e., multiple pumping tests).

    • Geochemical indicator data (redox indicators, total soil organic carbon).


Implications2

Implications

  • How may CVOC historical case analysis be used in CVOC cleanup decision-making?

    • Reference frame for comparative analyses of plumes at individual sites.

    • A set of bounds for typical plume behavior - GIS applications?

    • Prioritization of characterization and remediation.

    • Actuarial data for insurance on monitored natural attenuation.


Basic cvoc plume metrics compared to 1995 llnl luft study

Basic CVOC Plume Metrics*compared to 1995 LLNL LUFT Study

  • Change in Plume Length, minimum 3 yrs of data.

    • 29% increasing plume length (8%)

    • 16% decreasing plume length (33%)

    • 55% no statistically significant trend (59%)

  • Median length 1660 ft (130 ft)

    90% less than 6300 ft (306 ft)

    (*Based on a review of 247 CVOC plumes from 65 sites)


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San Francisco Bay Area

Silicon Valley – About 125 CVOC Plumes including 24 Superfund Sites

San Francisco


Non fuel program s f bay regional water quality control board

Non-Fuel Program:S.F. Bay Regional Water Quality Control Board

There are nearly 600 significant non-fuel cases ranging from Superfund to small dry cleaners (not counting about 900 lower-risk sites)

  • 65% have undertaken source control measures. This includes soil excavation and disposal/treatment, soil venting, soil vapor extraction, free product removal

  • About 36% have active groundwater cleanup in progress. This includes pump and treat systems, sparging, enhanced biodegradation, and innovative methods

  • About 13% have other engineering controls including capping and containment barriers


Overview

Overview

  • Study produces the first ever statistical analysis of data from CVOC sites.

  • More variability than LUFT sites.

  • Don’t look for major changes compared to LLNL LUFT Study.

  • Look for states, rather than authors, to recommend regulatory response.

  • Follow-up analysis to confirm results will likely be needed to increase acceptance.


Potential regulatory response 1

Potential Regulatory Response #1

  • Finding: Unlike Lawrence Livermore 1995 LUFT Study, CVOC plumes show wide variability.

  • Response: Unlikely to see any “global” regulatory changes.


Potential regulatory response 2 plume length

Potential Regulatory Response #2 - Plume Length

  • Finding: Reductive dehalogenation has less impact on plume length than source strength and groundwater velocity.

  • Potential Regulatory Response: Plumes with lower source strength and groundwater velocity may be better candidates for reductive dehalogenation - monitored natural attenuation remedies.


Potential regulatory response 3 transformation processes

Potential Regulatory Response #3 Transformation Processes

  • Findings - Presence of Vinyl Chloride appears to indicate that reductive dehalogenation may be playing a role in reducing the extent of CVOC plumes.

    Presence of cis-1,2 DCE w/out Vinyl Chloride appears to indicate reductive dehalogenation rates that are insufficient to effectively reduce extent of CVOC plumes.

  • Response: Focus Reductive Dehalogenation - Natural Attenuation remedies on sites with Vinyl Chloride.


Best candidates for reductive dehalogenation monitored natural attenuation remedies appear to be

Best Candidates for Reductive Dehalogenation - Monitored Natural Attenuation remedies appear to be:

  • Sites with Vinyl Chloride present,

  • Slow Groundwater Velocity,

  • Low Maximum Concentration.


Other potential regulatory outcomes

Other potential regulatory outcomes:

  • Need greater focus on collecting data on:

    • hydraulic conductivity

    • organic carbon content in soil and groundwater

  • Initiative sites were heavily weighted in western U.S. thus findings may be easier to accept in the western vs. eastern states.

  • Findings of CVOC Initiative will likely need further confirmation prior to gaining wide spread acceptance.


Limitations

Limitations

  • Data set is relatively small and may exhibit pronounced biases.

  • Findings are general and not necessarily applicable to individual sites.


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Historical Analysis of CVOC Plumes


Wrap up

Wrap-up

  • QUESTIONS AND ANSWERS


Thank you

Thank You!

Links to Additional Resources


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