Persistent Groundwater Contaminant Plumes: Processes, - - PowerPoint PPT Presentation

Persistent Groundwater Contaminant Plumes: Processes, Characterization, and Case Studies

UA-SRP & USEPA Seminar Series- Webinar February 24, 2014

Mark L. Brusseau School of Earth & Environmental Sciences University of Arizona

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Constrained Mass Removal & Plume Persistence

“significant limitations with currently available remedial technologies persist that make achievement of MCLs throughout the aquifer unlikely at most complex groundwater sites in a time frame of 50-100 years.”* “Complex” groundwater sites are defined as those that have DNAPL present (e.g., chlorinated solvents) and that have substantial subsurface heterogeneity, including the presence of extensive lower-permeability units or fractured media.

• Why does this situation exist?
• What options are available?

*National Research Council (NRC). 2013. Alternatives for

Managing the Nation's Complex Contaminated Groundwater

• Sites. Wash., DC

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Outline

• Chlorinated-solvent sites- prevalence and issues
• Constrained mass removal and plume persistence: Impact of

DNAPL source zones

• Constrained mass removal and plume persistence: Impact of

mass storage in lower-K zones & hydraulic factors

• Constrained mass removal and plume persistence: Impact of

sorbed mass

• Summary

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~1600 SUPERFUND Sites ~80% have Chlorinated-Solvent Contaminants

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Arizona Sites

Chlorinated- Solvents Presence: State: 31/35 Federal: 13/15

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Groundwater Contamination Sites in Tucson

Chlorinated-Solvent Contaminants are Primary Concern

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at all 9 Sites

Groundwater Remediation

Standard Method = Pump and Treat Very effective for plume containment

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Impact of P&T on Water Resources

• Analysis for Tucson [Brusseau & Narter, 2013]- year 2010
• Compare aggregate volume of groundwater extracted for all P&T

systems to total metropolitan groundwater withdrawal

• Total groundwater withdrawal for all P&T systems = 16.6 M m3
• This is ~20% of the total groundwater withdrawal in Tucson
• Treated water used primarily for potable water or re-injection
• Represents ~6% of total potable water supply

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Three Chlorinated-Solvent Sites in Arizona

• TCE is Primary COC
• Very Low Retardation (R<2)
• No Measurable Transformation Processes
• V. Low Biogeochemical Attenuation Capacity

Large Plumes

(several km long)

11 KM 4.5 KM

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9 KM

Pump & Treat CMD Data

Composite Measure:

CMD = Q * C

• OU1

Q = pumping rate C = concentration ~90% Reduction Currently ~ 1 kg/d Asymptotic conditions

~2 equivalent pore volumes displaced 10

Constrained Mass Removal & Plume Persistence

Potential Factors:

• Uncontrolled DNAPL Sources
• Plume-scale Lower-K Zones and Mass Storage (diffusive mass

transfer- “back diffusion”)

• Plume-scale Sorbed-phase Mass Storage

(sorption/desorption processes)

• Hydraulic Factors (P&T well-field, etc)
• Low Attenuation Capacity
• Other (Institutional, Analytical, etc)

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Constrained Mass Removal & Plume Persistence

Need to Determine Relative Significance of Each Factor, and Site-dependent Functionality Long Known:

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1989

Tucson International Airport Area Superfund Site

• TCE/DCE Contamination

Identified in 1981

• Site Placed on Superfund

NPL in 1983

• Pump and Treat started in

1987 (south plume)

• Source-zone Remediation

efforts [SVE, ISCO]

• UA Collaboration since 1993

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Composite CMD: AFP44

1987

High-resolution Temporal Data set

Asymptotic conditions Start Pump & Treat

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Constrained Mass Removal & Plume Persistence

Question: What is the relative significance of each of the various Persistence/Attenuation factors for this site? Conducted an integrated Laboratory, Field, and Modeling study

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Plume-scale Modeling Effort ~50 km2

Known Inputs Conduct series of scenario-testing sensitivity analyses

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Impact of Transport Processes

K Variability & Diffusive Mass Transfer (back diffusion)

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Impact of Transport Processes

Sorption-desorption (nonlinear, rate limited)

[Sims include physical heterogeneity] 19

Impact of Transport Processes

Controlling Factor for Early Phase

DNAPL in Source zones

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Source-zone Architecture, DNAPL Dissolution, and Mass Removal

Multi-scale Investigations of Systems

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APS ~6 mm ~10 cm ~2 m

Pore Core Intermediate

DNAPL Source Behavior

Pore-scale Imaging: 10 um resolution 1 2 3 4 1 2 3 4

Desorption Control NAPL Dissolution Control [1-4]: Non-uniform accessibility No-NAPL Expt

2 3 4 2 3 4 Column Experiments

Relative Concentration

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DNAPL Source Behavior

Flow-cell Experiments DNAPL Sn Imaging

1 10 100 1000 10000 100000 20 40 60 80 100 120 140 160 180

Concentration (mg/L) Pore Volume

Control- Homogeneous Mixed Source Heterogeneous Heterogeneous-2

Laboratory Experiments

• Known DNAPL distributions
• Permeability variability
• Measure DNAPL in situ

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DNAPL Source Behavior

Variables:

• Domain size

[20 vs 10,000 m2]

• Gradient & Q

[natural vs induced]

• Initial DNAPL Mass

Field Data

0.0001 0.001 0.01 0.1 1 10 50 100 150 200 CMD (Kg/d) Time (month) AFP44- 3 3 Hangers Dover- Surf

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Difficult to conduct comparative analysis

Data Analysis & Interpretation

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Fractional Mass Discharge Reduction Fractional Mass Reduction

1:1 (First order) Minimal Reduction (efficient mass removal) Maximal Reduction (inefficient mass removal)

0.001 0.01 0.1 1 5 10 15 20

Relative Concentration or Relative CMD Relative Time

1:1 Minimal Reduction Maximal Reduction

• Employ contaminant mass discharge (CMD)

metric

• Determine relationship between reduction in

mass discharge and reduction in mass

• Enhances comparative analysis

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DNAPL Source Behavior

Contaminant Mass Distribution [Accessibility] {source architecture, site age (mass removed)} Field Data Flow-cell Experiments

0.2 0.4 0.6 0.8 1 0.2 0.4 0.6 0.8 1

Fraction Reduction in CMD Fraction Reduction in Mass

TIAA-1 TIAA-2 Visualiz. Dover-CSF Dover-Surf Borden-1 Borden-2

Increasing fraction

• f poorly accessible

mass)

0.2 0.4 0.6 0.8 1 0.2 0.4 0.6 0.8 1

Fractional Reduction in CMD Fractional Reduction in Mass

Control-homogeneous Mixed Source Heterogeneous-1 Heterogeneous-2

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Post Source-zone Remediation

Persistence Factors:

• Residual DNAPL Sources (incomplete removal/containment)
• Plume-scale Lower-K Zones and Mass Storage (diffusive mass

transfer- “back diffusion”)

• Plume-scale Sorbed-phase Mass Storage

(sorption/desorption processes)

• Hydraulic Factors (P&T well-field, etc)
• Other (Institutional, Analytical, etc)

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Composite CMD: AFP44

SVE Start ISCO Start

1987

Impacts from Source Remediation efforts

Current CMD = 0.2 kg/d Pre SZR CMD = 2 kg/d ~90% Reduction

ISCO End SVE End

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Plume Persistence after Source Remediation

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Contaminant Mass Discharge (Kg/d)

Simulated- Remediation Simulated- No Remediation Measured

Non-source Factors: *Plume-scale*

• 1. Mass in Lower-K Zones
• 2. Sorbed Mass
• 3. Hydraulic Factors (well field)

*Ideal case- all source mass removed

Predictions for AFP44 Site

2 4 6 8 10 12 14

Time (Y)

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Lower-permeability Zones & Diffusion

0.001 0.01 0.1 1 10 100 5 10 15 20 25

Mass Remaining (%) Relative Time

1 3.5 Modflow: Clay-Sand-Clay

Mass Removed (%)

90 99 99.9 99.99

0.2 0.4 0.6 0.8 1 0.2 0.4 0.6 0.8 1

Fraction Reduction in Mass Discharge Fraction Mass Reduction

Model Simulations

Stochastic (random K fields) vs. Discrete (homogeneous, orthogonal) layers (MODFLOW)

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1 3.5 Modflow: Clay-Sand-Clay

Variance of lnK

Well-field Configuration

0.001 0.01 0.1 1 5 10 15 20 25

Relative Concentration Relative Time

3 longitudinal wells 3 downgradient (transverse) wells 9 uniform-dist wells Natural gradient (equiv Q)

Model Simulations

3–Layer system (Clay-Sand-Clay) [MODFLOW]

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Sorption-Desorption Processes

Extensive Elution Tailing

• Observed for all media
• Occurs with short contact times
• Need continuous-distribution

domain model Causative Mechanisms?

0.0000001 0.000001 0.00001 0.0001 0.001 0.01 0.1 1 500 1000 1500 2000 2500 3000 3500 4000

Relative Concentration Pore Volumes

Non-Linear, Rate-Limited Sorption Linear, Rate-Limited Sorption Non-Linear, Equilibrium Sorption Measured

RLS >> NLS Column Experiments

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Sorption-Desorption Processes

1

Eustis

0.1 0.01

Progressive increase

0.001

in resistance with increasing contact

0.0001

time

0.00001 0.000001 0.0000001 2 PV 4 PV 8 PV 20 PV 100 PV 1000 PV Aged 30 days Aged 420 days Aged 4 years

Interaction with Hard Carbon [sorbate permeation within, and sorbate-induced deformation of, the HC matrix]

1 0.1

Replication

Exp 1 Exp 2 Exp 3

Relative Concentration

1000 2000 3000 4000 5000 6000 7000 8000 9000

Pore Volumes

98% quartz sand 2% clay (kaolinite- non-expanding) 0.38% organic carbon 0.14% hard carbon (kerogen, bc)

Relative Concentration

Exp 4

0.01

Simulation

0.001 0.0001 0.00001 0.000001

Non-linear sorption Competitive sorption

0.0000001 500 1000 1500 2000 2500 3000 3500 4000

Pore Volumes

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Sorption-Desorption Processes

98-80% quartz, feldspars 2-20% clay (montmorillonite- expanding) 0.03% organic carbon 0.02% hard carbon (kerogen, bc) Non-linear sorption

Peak Shift = change in d-spacing

AFP 44 Sediment XRD Analysis: several AFP44 samples and 2 (mont) specimen controls Clay inter-layer d-spacing = ~0.3-0.6 nm TCE thickness = ~0.3 nm Increase in d-spacing for TCE treatment = ~0.4 nm TCE Intercalation [+ HCI]

No apparent aging effect 34

Summary: 3 Hanger Site at TIAA

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 10 20 30 40 50 60 Contaminant Mass Discharge (kg/d) Elapsed Time (month)

Hydraulic Source Control

Plume Reduction = ~50% Identify Relevant Factors:

• 1. Low-K Zones and DMT
• 2. Source Residual
• 3. Well-field Configuration

[~2-3 pore volumes]

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Measured Model Simulation

Summary: continued

• Source Zones- incomplete removal/containment of

contamination, continuing source

• Large, Persistent Plumes- contributing factors
• Site “Architecture” and “Age” key factors

– Subsurface properties (permeability field, flow field) – Contaminant distribution (phases, relative accessibility) – Change in contaminant distributions and accessibility as sites age

• Alternatives to P&T ?
• Long-term Site Management

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Acknowledgements

• The many students and post-docs who have contributed

to this research; our collaborators and partners with EPA, AECOM, US Air Force, CRA, Tucson Airport Authority, ADEQ.

• Financial support provided by the National Institute of

Environmental Health Sciences Superfund Research Program (ES04940), the US Department of Defense Strategic Environmental Research and Development Program (ER-1614), the US Air Force, and the Tucson Airport Authority

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References

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