1

DNAPL Source Zones

Mark L. Brusseau

University of Arizona

2

Superfund Basic Research ProgramUniversity of Arizona

• Funded and administered by the National Institute of Environmental Health Sciences (NIEHS), an institute of the National Institutes of Health (NIH)

• Hazardous wastes investigated include: arsenic, chlorinated hydrocarbons, and mine tailings contamination

3

Recent Studies

• Interstate Technology and Regulatory Council. 2002. DNAPL Source Reduction: Facing the Challenge.

• Environmental Protection Agency. 2003. The DNAPL Remediation Challenge: Is There a Case for Source Depletion?

• National Research Council. 2004. Contaminants in the Subsurface: Source Zone Assessment and Remediation.

• Strategic Environmental Research & Development Program. 2006. Reducing the Uncertainty of DNAPL Source Zone Remediation.

4

The DNAPL Problem

• Long-term Source of Contamination

• Accurate risk assessment and effective remediation of DNAPL sites requires understanding of source-zone architecture, mass-transfer dynamics, and mass-flux response

• Current Understanding is Insufficient

5

UA DNAPL Research

• Three Major Aspects:

– Fundamentals of Source-zone Architectures and Mass-transfer Dynamics

– Source-zone Characterization Technologies

– Source-zone Remediation Methods

6

Source-zone Architecture & Mass-transfer Dynamics

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Source-zone Mass Flux

Source Zone

ContaminantFlux

High Concentration

Low Concentration

Source Zone

ContaminantFlux

High Concentration

Low Concentration

High Concentration

Low Concentration

Input for dissolved-phase groundwater plume

(Which is usually primary risk driver for site)

(Figure adapted from EPA)

8

Field-scale Research: TIAA Study

• Site Characterization• Source-Zone TCE Mass Flux• TCE Spatial Distribution (areal, vertical) • DNAPL presence• Advective, Diffusive, Dispersive Transport

• Laboratory Experiments--- Mass Transfer Processes

• Mathematical Modeling--- Plume Behavior

• Pilot Source-zone Remediation Projects

9

TIAA Site

• Site Remediation under Superfund and DOD-IR

• Multiple source zones and PRPs

• 14 years of research at portions of the complex

10

Contaminant Elution

0 500 1000 1500 2000 2500 3000 3500 4000

time (day)

0

100

200

300

400

TCE

Conce

ntrat

ion

(ug/L

)

simulated (w/o NAPL)

simulated (w/ NAPL)

observed

effect of NAPL dissolution

1988 1990 1992 1994 1996

Comparison of the Simulated Influent TCE Conc. at Treatment Plant with the Observed Data

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Intermediate-scale Research

• Conducted with Flow Cells– Well-defined conditions

• Develop DNAPL Source Zone

• Characterize Architecture

(Imaging; Tracer Tests)

• Water Flush

(Monitor Q, C)

• Simulate w/ Model

12

Contaminant Elution: Data

0.001

0.01

0.1

1

0 50 100 150 200 250 300

Pore Volumes

Rela

tive C

on

cen

trati

on

Lower-K-1

Lower-K-2

Lower-K-3

Pool

Control

13

Contaminant Elution: Modeling

0

100

200

300

400

500

600

700

0 50 100 150 200 250 300 350

Pore Volumes

Measured data

Prediction

Con

cent

ratio

n (m

g/L)

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NAPL Distribution

In-situ Measurement of NAPL Saturation

[dual-energy gamma]

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Column-scale Experiments

0.001

0.01

0.1

1

10

0 100 200 300 400 500 600 700 800 900

Pore Volumes

Rel

ativ

e C

once

ntra

tion

Well-sorted Sand

Hayhook Soil

Mt Lemmon Soil

Ideal mass transfer = maintain max C

Efficient mass removal

Most prior research = well-sorted sands

16

Pore Scale Research: Synchrotron X-ray microtomography

DOE APS facility

5 mm

NAPL = white

Water = Black

Solid = Gray

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NAPL Blob Morphology

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NAPL Dissolution Dynamics

Initial Time Step 1 Time Step 2

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Summary: Part 1

• NAPL configuration and flow-field dynamics are key

– Hydraulic Accessibility of NAPL

• Constraints to full characterization at the field scale

• Need methods for profiling general behavior

– Up-scaled Modeling

– MFR-MR Assessment

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Source-Zone Remediation

To Remediate or Not To Remediate---that is the question…

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Source-zone Remediation

• Complete Mass Removal Not Possible

• Is Partial Removal [Mass Reduction] Beneficial?

• Need To Define Objectives

• Cost/Benefit Analysis

• Need Metrics

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Mass Flux Reduction vs Mass Removal

A key metric for assessing remediation-system effectiveness

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MFR-MR Relationship

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Fractional Mass Removed

Frac

tiona

l Mas

s Fl

ux R

educ

tion

1:1

Minimal Reduction (efficient mass removal)

Maximal Reduction (inefficient mass removal)

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Mass Removal Behavior

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 50 100 150 200 250 300 350 400

Time

Rel

ativ

e C

once

ntra

tion

1:1

Efficient Mass RemovalInefficient Mass Removal

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Key Questions

• Expected Degree of Mass Removal?

• Impact of Specified MR on Mass Flux?

• Impact of Mass Flux Reduction on Risk?

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Column Data

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Fractional Mass Removed

Frac

tion

al M

ass

Flux

Red

ucti

on

Well-sorted Sand

Hayhook Soil

Mt. Lemmon Soil

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Flow-cell Data

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Fractional Mass Removed

Frac

tiona

l Mas

s Fl

ux R

educ

tion

Lower-K-1 (residual)Lower-K-2 (residual)PoolPool & ResidualControl

2828

Field Data: End-Point Analysis of MFR-MR

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Fractional Mass Removed

Fra

cti

on

al

Ma

ss

Flu

x R

ed

uc

tio

n

Borden, Canada

Hill AFB, UT

Dover AFB, DE

Cape Canaveral, FL

Fort Worth, TX

AFP44, AZ

Paducah, KY

Camp Leguene, NC

Savannah River, SC

Pinellas Plant, FL

Sages, FL

Former SolventRecycling Facility

More Common Data Type

Missing early stages

Not continuous

Many uncertainties

?

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-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Fractional Mass Removed

Fra

cti

on

al M

ass F

lux R

ed

ucti

on

TIAA

Borden

TIAA-EndPointBorden-End Point

Field Data: Time-Continuous Analysis of MFR-MR

TIAA

Borden Very different mass-flux reductions for similar

% mass removed

Rare data type

Impact of source-zone architecture

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Answer

• Need to Understand the Impact of Source-zone Architecture and Mass-transfer Dynamics on Mass Flux Behavior

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Predicting MFR-MR Relationships

• Simplified Mathematical Modeling

• Systems Indicator Parameters• (e.g., Ganglia:Pool Ratio)

• Mass-removal Functions• MFR = MRn

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Example: Flow-cell Data

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Fractional Mass Removed

Frac

tiona

l Mas

s Fl

ux R

educ

tion

Lower-K-1

Lower-K-2

Lower-K-3

Pool

Control

Function,1/n=1Function,1/n=1.2Function,1/n=2Function,1/n=15Function,1/n=0.5

n=15

n=2

n=1.2

n=1

n=0.6

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Example: Field Data

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Example: TIAA Data

n=0.1

n=2

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Summary: Part 2

• MFR-MR Relationship Useful for

Evaluating Behavior

• How to Predict– need more data

• What Site Information can Support Application

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Acknowledgements

• NIEHS SBRP, US Air Force, EPA

• Erica DiFilippo, Justin Marble, Ann Russo, Greg Schnaar, Nicole Nelson, Mart Oostrom

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