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DNAPL Source Zones. Mark L. Brusseau University of Arizona. Superfund Basic Research Program University of Arizona. Funded and administered by the National Institute of Environmental Health Sciences (NIEHS), an institute of the National Institutes of Health (NIH) - PowerPoint PPT Presentation
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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
7
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
11
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)
14
NAPL Distribution
In-situ Measurement of NAPL Saturation
[dual-energy gamma]
15
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
17
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
20
Source-Zone Remediation
To Remediate or Not To Remediate---that is the question…
21
Source-zone Remediation
• Complete Mass Removal Not Possible
• Is Partial Removal [Mass Reduction] Beneficial?
• Need To Define Objectives
• Cost/Benefit Analysis
• Need Metrics
22
Mass Flux Reduction vs Mass Removal
A key metric for assessing remediation-system effectiveness
23
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)
24
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
25
Key Questions
• Expected Degree of Mass Removal?
• Impact of Specified MR on Mass Flux?
• Impact of Mass Flux Reduction on Risk?
26
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
27
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
?
28
29
-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
29
30
Answer
• Need to Understand the Impact of Source-zone Architecture and Mass-transfer Dynamics on Mass Flux Behavior
31
Predicting MFR-MR Relationships
• Simplified Mathematical Modeling
• Systems Indicator Parameters• (e.g., Ganglia:Pool Ratio)
• Mass-removal Functions• MFR = MRn
32
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
33
Example: Field Data
34
Example: TIAA Data
n=0.1
n=2
35
Summary: Part 2
• MFR-MR Relationship Useful for
Evaluating Behavior
• How to Predict– need more data
• What Site Information can Support Application
36
Acknowledgements
• NIEHS SBRP, US Air Force, EPA
• Erica DiFilippo, Justin Marble, Ann Russo, Greg Schnaar, Nicole Nelson, Mart Oostrom
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