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==Estimating PCE/TCE Abiotic First-Order Reductive Dechlorination Rate Constants in Clayey Soils Under Anoxic Conditions==
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The U.S. Department of Defense (DoD) faces many challenges in restoring aquifers at contaminated sites, often due to back-diffusion of tetrachloroethene (PCE) and trichloroethene (TCE) from low-permeability clay zones. The uptake, storage, and subsequent long-term release of these dissolved contaminants from clays are key processes in understanding the longevity, intensity, and risks associated with many persistent chlorinated ethene groundwater plumes. Although naturally occurring abiotic and biotic dechlorination processes in clays may reduce stored contaminant mass and significantly aid natural attenuation, no standardized field method currently exists to verify or quantify these reactions. It is critical to remediation design efforts to demonstrate and validate a cost-effective in situ approach for assessing these dechlorination processes using first-order rate constants. An approach was developed and applied across eight DoD sites to support Remedial Project Managers (RPMs) and regulators in evaluating natural attenuation potential in clay-rich environments.
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<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
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'''Related Article(s):'''
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 +
*[[Monitored Natural Attenuation (MNA)]]
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*[[Monitored Natural Attenuation (MNA) of Chlorinated Solvents]]
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*[[Monitored Natural Attenuation - Transitioning from Active Remedies]]
 +
*[[Matrix Diffusion]]
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*[[REMChlor - MD]]
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 +
'''Contributors:''' Dani Tran, Dr. Charles Schaefer, Dr. Charles Werth
  
==Advection-Dispersion-Reaction Equation for Solute Transport==
+
'''Key Resource:'''
 +
*Schaefer, C.E, Tran, D., Nguyen, D., Latta, D.E., Werth, C.J., 2025. Evaluating Mineral and In Situ Indicators of Abiotic Dechlorination in Clayey Soils (3)
  
The transport of dissolved solutes in groundwater is often modeled using the Advection-Dispersion-Reaction (ADR) equation. [[wikipedia:Advection|Advection]] refers to the bulk movement of solutes carried by flowing groundwater. [[wikipedia:Dispersion|Dispersion]] refers to the spreading of the contaminant plume from highly concentrated areas to less concentrated areas. Dispersion coefficients are calculated as the sum of [[wikipedia:Molecular diffusion | molecular diffusion]], mechanical dispersion, and macrodispersion. Reaction refers to changes in the mass of the solute within the system resulting from biotic and abiotic processes.
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==Introduction==
<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
+
Cost-effective methods are needed to verify the occurrence of natural dechlorination processes and quantify their dechlorination rates in clays under ambient in situ conditions in order to reliably predict their long-term influence on plume longevity and mass discharge. However, accurately determining these rates is challenging due to slow reaction kinetics, the transient nature of transformation products, and the interplay of biotic and abiotic mechanisms within the clay matrix or at clay-sand interfaces. Tools capable of quantifying these reactions and assessing their role in mitigating plume persistence would be a significant aid for long-term site management.
  
'''Related Article(s):'''
+
For reductive abiotic dechlorination under anoxic conditions, a 1% hydrochloric acid (HCl) extraction of a sample of native clay coupled with X-ray diffraction (XRD) data can be used as a screening level tool to estimate reductive dechlorination rate constants. These rate constants can be inserted into fate and transport models such as [[REMChlor - MD]]<ref>Falta, R., and Wang, W., 2017. A semi-analytical method for simulating matrix diffusion in numerical transport models. Journal of Contaminant Hydrology, 197, pp. 39-49. [https://doi.org/10.1016/j.jconhyd.2016.12.007 doi: 10.1016/j.jconhyd.2016.12.007]&nbsp; [[Media: FaltaWang2017.pdf | Open Access Manuscript]]</ref><ref>Kulkarni, P.R., Adamson, D.T., Popovic, J., Newell, C.J., 2022. Modeling a well-charactized perfluorooctane sulfate (PFOS) source and plume using the REMChlor-MD model to account for matrix diffusion. Journal of Contaminant Hydrology, 247, Article 103986. [https://doi.org/10.1016/j.jconhyd.2022.103986 doi: 10.1016/j.jconhyd.2022.103986]&nbsp; [[Media: KulkarniEtAl2022.pdf | Open Access Manuscript]]</ref> to quantify abiotic dechlorination impacts within clay aquitards on chlorinated solvent plumes. Thus, determination of the abiotic reductive dechlorination rate constant for a particular clayey soil can be readily utilized to provide a more accurate assessment of aquifer cleanup timeframes for groundwater plumes that are being sustained by contaminant back-diffusion.
*[[Advection and Groundwater Flow]]
 
*[[Dispersion and Diffusion]]
 
*[[Sorption of Organic Contaminants]]
 
*[[Plume Response Modeling]]
 
  
'''CONTRIBUTOR(S):'''
+
==Recommended Approach==
*[[Dr. Charles Newell, P.E.]]
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[[File: TranFig1.png | thumb | 600 px | Figure 1: First-order rate constants for abiotic reductive dechlorination of TCE under anaerobic conditions (data from this study and prior research)]]
*[[Dr. Robert Borden, P.E.]]
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[[File: TranFig2.png | thumb | 600 px | Figure 2: Flowchart diagram of field screening procedures]]
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The recommended approach builds upon the methodology and findings of a recent study<ref name="SchaeferEtAl2025">Schaefer, C.E., Tran, D., Nguyen, D., Latta, D.E., Werth, C.J., 2025. Evaluating Mineral and In Situ Indicators of Abiotic Dechlorination in Clayey Soils. Groundwater Monitoring and Remediation, 45(2), pp. 31-39. [https://doi.org/10.1111/gwmr.12709 doi: 10.1111/gwmr.12709]</ref>, emphasizing field-based and analytical techniques to quantify abiotic first-order reductive dechlorination rate constants for PCE and TCE in clayey soils under anoxic conditions. Key components of this evaluation are listed below:
 +
#<u>Zone Identification:</u> The focus of the investigation should be to delineate clayey zones adjacent to hydraulically conductive zones.
 +
#<u>Ferrous Mineral Quantification:</u> Assess ferrous mineral context in clay via 1% HCl extraction at ambient temperature over a 10-minute interval.
 +
#<u>Mineralogical Characterization:</u> Conduct XRD analysis with the specific intent of identifying the presence of pyrite and biotite.
 +
#<u>Reduced Gas Analysis:</u> Measurement of reduced gases such as acetylene, ethene, and ethane concentrations in clay samples. Gas-tight sampling devices (e.g., En Core® soil samplers by En Novative Technologies, Inc.)  should be used to ensure sample integrity during collection and transport.
  
'''Key Resource(s):'''
+
Clay samples should be collected within a few centimeters of the high-permeability interface, with optional additional sampling further inward. For mineralogical analysis, a defined interval may be collected and subsequently subsampled. To preserve sample integrity, exposure to air should be minimized during collection, transport, and handling. Homogenization should occur within an anaerobic chamber, and if subsamples are required for external analysis, they must be shipped in gas-tight, anaerobic containers.
*[http://hydrogeologistswithoutborders.org/wordpress/1979-english/ Groundwater]<ref name="FandC1979">Freeze, A., and Cherry, J., 1979. Groundwater, Prentice-Hall, Englewood Cliffs, New Jersey, 604 pages. Free download from [http://hydrogeologistswithoutborders.org/wordpress/1979-english/ Hydrogeologists Without Borders].</ref>, Freeze and Cherry, 1979.
 
*[https://gw-project.org/books/hydrogeologic-properties-of-earth-materials-and-principles-of-groundwater-flow/ Hydrogeologic Properties of Earth Materials and Principals of Groundwater Flow]<ref name="Woessner2020">Woessner, W.W., and Poeter, E.P., 2020. Properties of Earth Materials and Principals of Groundwater Flow, The Groundwater Project, Guelph, Ontario, 207 pages. Free download from [https://gw-project.org/books/hydrogeologic-properties-of-earth-materials-and-principles-of-groundwater-flow/ The Groundwater Project].</ref>, Woessner and Poeter, 2020.
 
  
==The ADR Equation==
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Estimation of the abiotic reductive first-order rate constant for PCE and TCE is based on the “reactive” ferrous content in the clay. Reactive ferrous content (Fe(II)<sub>r</sub>) is estimated as shown in Equation 1:
[[File:AdvectionFig5.png | thumb | right | 350px | Figure 1. Curves of concentration versus distance (a) and concentration versus time (b) generated by solving the ADR equation for a continuous source of a non-reactive tracer with ''R'' = 1, λ = 0, ''v'' = 5 m/yr, and ''D<sub>x</sub>'' = 10 m<sup>2</sup>/yr.]]
 
[[File:ADRFig2.PNG | thumb | right | 350px | Figure 2. Predicted variation in macrodispersivity with distance for varying ''σ<sup>2</sup>Y'' and correlation length = 3 m.]]
 
In many groundwater transport models, solute transport is described by the advection-dispersion-reaction equation. As shown below (Equation 1), the ADR equation describes the change in dissolved solute concentration (''C'') over time (''t'') where groundwater flow is oriented along the ''x'' direction.
 
  
[[File:AdvectionEq3r.PNG|center|620px]]
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::'''Equation 1:'''&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; <big>''Fe(II)<sub><small>r</small></sub> = DA + XRD<sub><small>pyr</small></sub> - XRD<sub><small>biotite</small></sub>''</big>
:Where:
 
::''R'' is the linear, equilibrium retardation factor (see [[Sorption of Organic Contaminants]])
 
::''D<sub>x</sub>, D<sub>y</sub>, and D<sub>z</sub>''  are hydrodynamic dispersion coefficients in the ''x, y'' and ''z'' directions (L<sup>2</sup>/T),
 
::''v''  is the advective transport or seepage velocity in the ''x'' direction (L/T), and
 
::''λ''  is an effective first order decay rate due to combined biotic and abiotic processes (1/T).
 
The term on the left side of the equation is the rate of mass change per unit volume.  On the right side are terms representing the solute flux due to dispersion in the ''x, y'', and ''z'' directions, the advective flux in the ''x'' direction, and the first order decay due to biotic and abiotic processes. Dispersion coefficients (''D<sub>x,y,z</sub>'') are commonly estimated using the following relationships:
 
  
[[File:AdvectionEq4.PNG|center|360px]]
+
where ''DA'' is the ferrous content from the dilute acid (1% HCl) extraction, ''XRD<sub><small>pyr</small></sub>'' is the pyrite content from XRD analysis, and ''XRD<sub><small>biotite</small></sub>'' is the biotite content from XRD analysis<ref name="SchaeferEtAl2025"/>.
:Where:
 
::''D<sub>m</sub>'' is the molecular diffusion coefficient (L<sup>2</sup>/T), and
 
::''&alpha;<sub>L</sub>, &alpha;<sub>T</sub>'', and ''&alpha;<sub>V</sub>''  are the longitudinal, transverse and vertical dispersivities (L).
 
Figures 1a and 1b were generated using a numerical solution of the ADR equation for a non-reactive tracer (''R'' = 1; λ = 0) with ''v'' = 5 m/yr and ''D<sub>x</sub>'' = 10 m<sup>2</sup>/yr. 
 
Figure 1a shows the predicted change in concentration of the tracer, chloride, versus distance downgradient from the continuous contaminant source at different times (0, 1, 2, and 4 years).  Figure 1b shows the change in concentration versus time (commonly referred to as the breakthrough curve or BTC) at different downgradient distances (10, 20, 30 and 40 m).  At 2 years, the mid-point of the concentration versus distance curve (Figure 1a) is located 10 m downgradient (x = 5 m/yr * 2 yr).  At 20 m downgradient, the mid-point of the concentration versus time curves (Figure 1b) occurs at 4 years (t = 20 m / 5 m/yr).
 
  
==Modeling Dispersion==
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Abiotic dechlorination is unlikely to contribute to mitigating contaminant back-diffusion when reactive ferrous iron (Fe(II)<sub><small>r</small></sub>) concentrations are below 100 mg/kg (Figure 1). For Fe(II)<sub><small>r</small></sub> above 100 mg/kg, the first-order rate constant for PCE and TCE reductive dechlorination can be estimated using the correlation shown in Figure 1<ref name="SchaeferEtAl2018">Schaefer, C.E., Ho, P., Berns, E., Werth, C., 2018. Mechanisms for abiotic dechlorination of trichloroethene by ferrous minerals under oxic and anoxic conditions in natural sediments. Environmental Science and Technology, 52(23), pp.13747-13755. [https://doi.org/10.1021/acs.est.8b04108 doi: 10.1021/acs.est.8b04108]</ref><ref>Borden, R.C., Cha, K.Y., 2021. Evaluating the impact of back diffusion on groundwater cleanup time. Journal of Contaminant Hydrology, 243, Article 103889. [https://doi.org/10.1016/j.jconhyd.2021.103889 doi: 10.1016/j.jconhyd.2021]&nbsp; [[Media: BordenCha2021.pdf | Open Access Manuscript]]</ref>. The rate constant exhibits a strong positive correlation with the logarithm of reactive Fe(II) content (Pearson’s ''r'' = 0.82), with a slope of 4.7 × 10⁻⁸ L g⁻¹ d⁻¹ (log mg kg⁻¹)⁻¹.
The dispersion coefficient in the ADR equation accounts for the combined effects of molecular diffusion and mechanical dispersion, both of which cause spreading of the contaminant plume from highly concentrated areas toward less concentrated areas.  [[wikipedia:Molecular diffusion | Molecular diffusion]] is the result of the thermal motion of individual molecules which causes a flux of dissolved solutes from areas of higher concentration to areas of lower concentration. Mechanical dispersion (hydrodynamic dispersion) results from groundwater moving at rates that vary from the average linear velocity. Because the invading solute-containing water does not travel at the same velocity everywhere, mixing occurs along flow paths. Typical values of the mechanical dispersivity measured in laboratory column tests are on the order of 0.01 to 1 cm<ref name="Anderson1979">Anderson, M.P. and Cherry, J.A., 1979. Using models to simulate the movement of contaminants through groundwater flow systems. Critical Reviews in Environmental Science and Technology, 9(2), pp.97-156. [https://doi.org/10.1080/10643387909381669 DOI: 10.1080/10643387909381669]</ref>.
 
  
Spatial variations in hydraulic conductivity can increase the apparent spreading of solute plumes observed in groundwater monitoring wells. This spreading of the solute caused by large-scale heterogeneities in the aquifer and the associated spatial variations in advective transport velocity is referred to as macrodispersion. In some groundwater modeling projects, large values of dispersivity are used as an adjustment factor to better represent the observed large-scale spreading of plumes <ref name="ITRC2015">Interstate Technology and Regulatory Council (ITRC), 2015. Integrated DNAPL Site Characterization and Tools Selection (ISC-1), DNAPL Site Characterization Team, ITRC, Washington, DC. Free download from: [https://www.itrcweb.org/DNAPL-ISC_tools-selection/Content/Resources/DNAPLPDF.pdf ITRC]</ref>. Theoretical studies (Gelhar et al. 1979; Gelhar and Axness,1983; Dagan 1988) suggest that macrodispersivity will increase with distance near the source, and then increase more slowly farther downgradient, eventually approaching an asymptotic value.  Figure 2 shows values of macrodispersivity calculated using the theory of Dagan (1986) with an autocorrelation length of 3 m and several different values of the variance of ''Y'' (σ<sup>2</sup><sub>Y</sub>) where ''Y'' = Log ''K''. The calculated macrodispersivity increases more rapidly and reaches higher asymptotic values for more heterogeneous aquifers with greater variations in ''K'' (larger σ<sup>2</sup><sub>Y</sub>).  The maximum predicted dispersivity values are in the range of 0.5 to 5 m.
+
Figure 2 presents a decision flowchart designed to evaluate the significance and extent of abiotic reductive dechlorination. By applying Equation 1 to the dilute acid extractable Fe(II) plus measured mineral species data from clay samples, the reactive ferrous iron content (Fe(II)<sub><small>r</small></sub>) can be quantified, enabling a streamlined assessment of the extent to which abiotic processes are contributing to the mitigation of contaminant back-diffusion.
  
==Modeling Diffusion==
+
If Fe(II)r is ≥ 100 mg/kg, a first-order dechlorination rate constant can be estimated and subsequently used within a contaminant fate and transport model. However, if acetylene is detected in the clay, even with Fe(II)r less than 100 mg/kg, then bench-scale testing using methods similar to those described in a recent study<ref name="SchaeferEtAl2025"/> is recommended, as such results would likely be inconsistent with those shown in Figure 1, suggesting some other mechanism might be involved, or that the system mineralogy might be more complex than anticipated. Even if Fe(II)r ≥ 100 mg/kg, confirmatory bench-scale testing may be conducted for additional verification and to refine estimation of the abiotic dechlorination rate constant.
[[File:ADRFig3.png | thumb| 350px| Figure 3.  Comparison of tracer breakthrough (upper graph) and cleanup curves (lower graph) from advection-dispersion based (gray lines) and advection-diffusion based (black lines) solute transport<ref name="ITRC2011">Interstate Technology and Regulatory Council (ITRC), 2011. Integrated DNAPL Site Strategy (IDSS-1), Integrated DNAPL Site Strategy Team, ITRC, Washington, DC. Free download from:
 
[https://itrcweb.org/GuidanceDocuments/IntegratedDNAPLStrategy_IDSSDoc/IDSS-1.pdf ITRC]</ref>.]]
 
[[Matrix Diffusion]] describes the gradual transport  of dissolved contaminants from higher concentration and higher hydraulic conductivity (''K'') zones into low ''K'' zones by [[wikipedia:Molecular diffusion | molecular diffusion]]. The contaminants can then diffuse back out of these low ''K'' zones once the contaminant source is removed and the high ''K'' zone contaminant concentration decreases.  In some cases, matrix diffusion can maintain contaminant concentrations in more permeable zones above target cleanup goals for decades or even centuries after the primary sources have been addressed<ref name="Chapman2005">Chapman, S.W. and Parker, B.L., 2005. Plume persistence due to aquitard back diffusion following dense nonaqueous phase liquid source removal or isolation. Water Resources Research, 41(12).  [https://doi.org/10.1029/2005WR004224 DOI: 10.1029/2005WR004224] Free access article from [https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2005WR004224 American Geophysical Union]</ref>. (See also [[Matrix Diffusion]].)
 
  
===Impacts on Breakthrough Curves===
+
==Summary and Recommendations==
The impacts of matrix diffusion on the initial breakthrough of the solute plume and later cleanup are illustrated in Figure 3<ref name="ITRC2011"/>. Using a traditional advection-dispersion model, the breakthrough curve for a pulse tracer injection appears as a bell-shaped (Gaussian) curve (gray line on the right side of the upper graph) where the peak arrival time corresponds to the average groundwater velocity.  Using an advection-diffusion approach, the breakthrough curve for a pulse injection is asymmetric (solid black line) with the peak tracer concentration arriving earlier than would be expected based on the average groundwater velocity, but with a long extended tail to the flushout curve.
 
  
The lower graph shows the predicted cleanup concentration profiles following complete elimination of a source area.  The advection-dispersion model (gray line) predicts a clean-water front arriving at a time corresponding to the average groundwater velocity.  The advection-diffusion model (black line) predicts that concentrations will start to decline more rapidly than expected (based on the average groundwater velocity) as clean water rapidly migrates through the highest-permeability strata. However, low but significant contaminant concentrations linger much longer (tailing) due to diffusive contaminant mass exchange between zones of high and low permeability.
 
  
==ADR Applications==
+
<br clear="right"/>
The ADR equation can be solved to find the spatial and temporal distribution of solutes using a variety of analytical and numerical approaches.  The design tools [https://www.epa.gov/water-research/bioscreen-natural-attenuation-decision-support-system BIOSCREEN]<ref name="Newell1996">Newell, C.J., McLeod, R.K. and Gonzales, J.R., 1996. BIOSCREEN: Natural Attenuation Decision Support System - User's Manual, Version 1.3. US Environmental Protection Agency, EPA/600/R-96/087. [https://www.enviro.wiki/index.php?title=File:Newell-1996-Bioscreen_Natural_Attenuation_Decision_Support_System.pdf Report.pdf]  [https://www.epa.gov/water-research/bioscreen-natural-attenuation-decision-support-system BIOSCREEN website]</ref>, [https://www.epa.gov/water-research/biochlor-natural-attenuation-decision-support-system BIOCHLOR]<ref name="Aziz2000">Aziz, C.E., Newell, C.J., Gonzales, J.R., Haas, P.E., Clement, T.P. and Sun, Y., 2000. BIOCHLOR Natural Attenuation Decision Support System. User’s Manual - Version 1.0. US Environmental Protection Agency, EPA/600/R-00/008.  [https://www.enviro.wiki/index.php?title=File:Aziz-2000-BIOCHLOR-Natural_Attenuation_Dec_Support.pdf Report.pdf]  [https://www.epa.gov/water-research/biochlor-natural-attenuation-decision-support-system BIOCHLOR website]</ref>, and [https://www.epa.gov/water-research/remediation-evaluation-model-chlorinated-solvents-remchlor REMChlor]<ref name="Falta2007">Falta, R.W., Stacy, M.B., Ahsanuzzaman, A.N.M., Wang, M. and Earle, R.C., 2007. REMChlor Remediation Evaluation Model for Chlorinated Solvents - User’s Manual, Version 1.0. US Environmental Protection Agency. Center for Subsurface Modeling Support, Ada, OK.  [[Media:REMChlorUserManual.pdf | Report.pdf]]  [https://www.epa.gov/water-research/remediation-evaluation-model-chlorinated-solvents-remchlor REMChlor website]</ref> employ an analytical solution of the ADR equation.  [https://www.usgs.gov/software/mt3d-usgs-groundwater-solute-transport-simulator-modflow MT3DMS]<ref name="Zheng1999">Zheng, C. and Wang, P.P., 1999. MT3DMS: A Modular Three-Dimensional Multispecies Transport Model for Simulation of Advection, Dispersion, and Chemical Reactions of Contaminants in Groundwater Systems; Documentation and User’s Guide. Contract Report SERDP-99-1 U.S. Army Engineer Research and Development Center, Vicksburg, MS. [[Media:Mt3dmanual.pdf | Report.pdf]]  [https://www.usgs.gov/software/mt3d-usgs-groundwater-solute-transport-simulator-modflow MT3DMS website]</ref> uses a numerical method to solve the ADR equation using the head distribution generated by the groundwater flow model MODFLOW<ref name="McDonald1988">McDonald, M.G. and Harbaugh, A.W., 1988. A Modular Three-dimensional Finite-difference Ground-water Flow Model, Techniques of Water-Resources Investigations, Book 6, Modeling Techniques. U.S. Geological Survey, 586 pages. [https://doi.org/10.3133/twri06A1  DOI: 10.3133/twri06A1]  [[Media: McDonald1988.pdf | Report.pdf]]  Free MODFLOW download from: [https://www.usgs.gov/mission-areas/water-resources/science/modflow-and-related-programs?qt-science_center_objects=0#qt-science_center_objects USGS]</ref>.
 
  
 
==References==
 
==References==
 
+
<references />
<references/>
 
  
 
==See Also==
 
==See Also==
*[http://iwmi.dhigroup.com/solute_transport/advection.html International Water Management Institute Animations]
 
*[http://www2.nau.edu/~doetqp-p/courses/env303a/lec32/lec32.htm NAU Lecture Notes on Advective Transport]
 
*[https://www.youtube.com/watch?v=00btLB6u6DY MIT Open CourseWare Solute Transport: Advection with Dispersion Video]
 
*[https://www.youtube.com/watch?v=AtJyKiA1vcY Physical Groundwater Model Video]
 
*[https://www.coursera.org/learn/natural-attenuation-of-groundwater-contaminants/lecture/UzS8q/groundwater-flow-review Online Lecture Course - Groundwater Flow]
 

Latest revision as of 15:51, 27 April 2026

Estimating PCE/TCE Abiotic First-Order Reductive Dechlorination Rate Constants in Clayey Soils Under Anoxic Conditions

The U.S. Department of Defense (DoD) faces many challenges in restoring aquifers at contaminated sites, often due to back-diffusion of tetrachloroethene (PCE) and trichloroethene (TCE) from low-permeability clay zones. The uptake, storage, and subsequent long-term release of these dissolved contaminants from clays are key processes in understanding the longevity, intensity, and risks associated with many persistent chlorinated ethene groundwater plumes. Although naturally occurring abiotic and biotic dechlorination processes in clays may reduce stored contaminant mass and significantly aid natural attenuation, no standardized field method currently exists to verify or quantify these reactions. It is critical to remediation design efforts to demonstrate and validate a cost-effective in situ approach for assessing these dechlorination processes using first-order rate constants. An approach was developed and applied across eight DoD sites to support Remedial Project Managers (RPMs) and regulators in evaluating natural attenuation potential in clay-rich environments.

Related Article(s):

Contributors: Dani Tran, Dr. Charles Schaefer, Dr. Charles Werth

Key Resource:

  • Schaefer, C.E, Tran, D., Nguyen, D., Latta, D.E., Werth, C.J., 2025. Evaluating Mineral and In Situ Indicators of Abiotic Dechlorination in Clayey Soils (3)

Introduction

Cost-effective methods are needed to verify the occurrence of natural dechlorination processes and quantify their dechlorination rates in clays under ambient in situ conditions in order to reliably predict their long-term influence on plume longevity and mass discharge. However, accurately determining these rates is challenging due to slow reaction kinetics, the transient nature of transformation products, and the interplay of biotic and abiotic mechanisms within the clay matrix or at clay-sand interfaces. Tools capable of quantifying these reactions and assessing their role in mitigating plume persistence would be a significant aid for long-term site management.

For reductive abiotic dechlorination under anoxic conditions, a 1% hydrochloric acid (HCl) extraction of a sample of native clay coupled with X-ray diffraction (XRD) data can be used as a screening level tool to estimate reductive dechlorination rate constants. These rate constants can be inserted into fate and transport models such as REMChlor - MD[1][2] to quantify abiotic dechlorination impacts within clay aquitards on chlorinated solvent plumes. Thus, determination of the abiotic reductive dechlorination rate constant for a particular clayey soil can be readily utilized to provide a more accurate assessment of aquifer cleanup timeframes for groundwater plumes that are being sustained by contaminant back-diffusion.

Recommended Approach

File:TranFig1.png
Figure 1: First-order rate constants for abiotic reductive dechlorination of TCE under anaerobic conditions (data from this study and prior research)
File:TranFig2.png
Figure 2: Flowchart diagram of field screening procedures

The recommended approach builds upon the methodology and findings of a recent study[3], emphasizing field-based and analytical techniques to quantify abiotic first-order reductive dechlorination rate constants for PCE and TCE in clayey soils under anoxic conditions. Key components of this evaluation are listed below:

  1. Zone Identification: The focus of the investigation should be to delineate clayey zones adjacent to hydraulically conductive zones.
  2. Ferrous Mineral Quantification: Assess ferrous mineral context in clay via 1% HCl extraction at ambient temperature over a 10-minute interval.
  3. Mineralogical Characterization: Conduct XRD analysis with the specific intent of identifying the presence of pyrite and biotite.
  4. Reduced Gas Analysis: Measurement of reduced gases such as acetylene, ethene, and ethane concentrations in clay samples. Gas-tight sampling devices (e.g., En Core® soil samplers by En Novative Technologies, Inc.) should be used to ensure sample integrity during collection and transport.

Clay samples should be collected within a few centimeters of the high-permeability interface, with optional additional sampling further inward. For mineralogical analysis, a defined interval may be collected and subsequently subsampled. To preserve sample integrity, exposure to air should be minimized during collection, transport, and handling. Homogenization should occur within an anaerobic chamber, and if subsamples are required for external analysis, they must be shipped in gas-tight, anaerobic containers.

Estimation of the abiotic reductive first-order rate constant for PCE and TCE is based on the “reactive” ferrous content in the clay. Reactive ferrous content (Fe(II)r) is estimated as shown in Equation 1:

Equation 1:       Fe(II)r = DA + XRDpyr - XRDbiotite

where DA is the ferrous content from the dilute acid (1% HCl) extraction, XRDpyr is the pyrite content from XRD analysis, and XRDbiotite is the biotite content from XRD analysis[3].

Abiotic dechlorination is unlikely to contribute to mitigating contaminant back-diffusion when reactive ferrous iron (Fe(II)r) concentrations are below 100 mg/kg (Figure 1). For Fe(II)r above 100 mg/kg, the first-order rate constant for PCE and TCE reductive dechlorination can be estimated using the correlation shown in Figure 1[4][5]. The rate constant exhibits a strong positive correlation with the logarithm of reactive Fe(II) content (Pearson’s r = 0.82), with a slope of 4.7 × 10⁻⁸ L g⁻¹ d⁻¹ (log mg kg⁻¹)⁻¹.

Figure 2 presents a decision flowchart designed to evaluate the significance and extent of abiotic reductive dechlorination. By applying Equation 1 to the dilute acid extractable Fe(II) plus measured mineral species data from clay samples, the reactive ferrous iron content (Fe(II)r) can be quantified, enabling a streamlined assessment of the extent to which abiotic processes are contributing to the mitigation of contaminant back-diffusion.

If Fe(II)r is ≥ 100 mg/kg, a first-order dechlorination rate constant can be estimated and subsequently used within a contaminant fate and transport model. However, if acetylene is detected in the clay, even with Fe(II)r less than 100 mg/kg, then bench-scale testing using methods similar to those described in a recent study[3] is recommended, as such results would likely be inconsistent with those shown in Figure 1, suggesting some other mechanism might be involved, or that the system mineralogy might be more complex than anticipated. Even if Fe(II)r ≥ 100 mg/kg, confirmatory bench-scale testing may be conducted for additional verification and to refine estimation of the abiotic dechlorination rate constant.

Summary and Recommendations


References

  1. ^ Falta, R., and Wang, W., 2017. A semi-analytical method for simulating matrix diffusion in numerical transport models. Journal of Contaminant Hydrology, 197, pp. 39-49. doi: 10.1016/j.jconhyd.2016.12.007  Open Access Manuscript
  2. ^ Kulkarni, P.R., Adamson, D.T., Popovic, J., Newell, C.J., 2022. Modeling a well-charactized perfluorooctane sulfate (PFOS) source and plume using the REMChlor-MD model to account for matrix diffusion. Journal of Contaminant Hydrology, 247, Article 103986. doi: 10.1016/j.jconhyd.2022.103986  Open Access Manuscript
  3. ^ 3.0 3.1 3.2 Schaefer, C.E., Tran, D., Nguyen, D., Latta, D.E., Werth, C.J., 2025. Evaluating Mineral and In Situ Indicators of Abiotic Dechlorination in Clayey Soils. Groundwater Monitoring and Remediation, 45(2), pp. 31-39. doi: 10.1111/gwmr.12709
  4. ^ Schaefer, C.E., Ho, P., Berns, E., Werth, C., 2018. Mechanisms for abiotic dechlorination of trichloroethene by ferrous minerals under oxic and anoxic conditions in natural sediments. Environmental Science and Technology, 52(23), pp.13747-13755. doi: 10.1021/acs.est.8b04108
  5. ^ Borden, R.C., Cha, K.Y., 2021. Evaluating the impact of back diffusion on groundwater cleanup time. Journal of Contaminant Hydrology, 243, Article 103889. doi: 10.1016/j.jconhyd.2021  Open Access Manuscript

See Also