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==Abiotic Reduction of Munitions Constituents==
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==PFAS Leaching Characterization with the Leaching Environmental Assessment Framework (LEAF)==  
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Munition compounds (MCs) often contain one or more nitro (-NO<sub>2</sub>) functional groups which makes them susceptible to abiotic reduction, i.e., transformation by accepting electrons from a chemical electron donor. In soil and groundwater, the most prevalent electron donors are natural organic carbon and iron minerals. Understanding the kinetics and mechanisms of abiotic reduction of MCs by carbon and iron constituents in soil is not only essential for evaluating the environmental fate of MCs but also key to developing cost-efficient remediation strategies. This article summarizes the recent advances in our understanding of MC reduction by carbon and iron based reductants.
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[[Wikipedia: Firefighting_foam#Synthetic_foams | Aqueous film-forming foams (AFFFs)]] are a major source of [[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) | per- and poly-fluoroalkyl substances (PFAS)]] impacts in soil and groundwater. Standardized tools are needed to rapidly assess the potential for retention, leaching, and transport of PFAS from the source zone to downgradient regions, so that this information can be applied towards critical facets of site management such as prioritizing PFAS-impacted sites for further investigation and remediation. Existing standard leaching methods were developed prior to concerns regarding PFAS. Therefore, studies are needed to ensure that leaching methods are compatible for use with PFAS and that resulting data are representative of the risk of PFAS leaching at impacted sites.
 
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'''Related Article(s):'''
 
'''Related Article(s):'''
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*[[Munitions Constituents]]
 
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*[[Munitions Constituents - Alkaline Degradation]]
 
  
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'''Contributor(s):'''
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*[[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS)]]
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*Dr. Jimmy Murillo-Gelvez
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*[[PFAS Sources]]
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*Paula Andrea Cárdenas-Hernández
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*[[PFAS Transport and Fate]]
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*Dr. Pei Chiu
 
  
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'''Key Resource(s):'''
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'''Contributors:''' Dr. Jennifer L. Guelfo, Dr. David Kosson, Dr. Andy Garrabrants, Ms. Fangfei Liu, Mr. Darlington Yawson, Dr. Md. Isreq Real
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* Schwarzenbach, Gschwend, and Imboden, 2016. Environmental Organic Chemistry, 3rd ed.<ref name="Schwarzenbach2016">Schwarzenbach, R.P., Gschwend, P.M., and Imboden, D.M., 2016. Environmental Organic Chemistry, 3rd Edition. John Wiley and Sons, Ltd, 1024 pages. ISBN: 978-1-118-76723-8</ref>
 
  
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==Introduction==
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'''Key Resources:'''
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[[File:AbioMCredFig1.PNG | thumb |left|300px|Figure 1. Common munitions compounds. TNT and RDX are legacy explosives. DNAN, NTO, and NQ are insensitive MCs (IMCs) widely used as replacement for legacy explosives.]]
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*Development of Leaching Tests for Materials Containing SVOCs and PFAS, EPA 600/R-23/382<ref name="GarrabrantsEtAl2024"/>
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Legacy and insensitive MCs (Figure 1.) are susceptible to reductive transformation in soil and groundwater. Many redox-active constituents in the subsurface, especially those containing organic carbon, Fe(II), and sulfur can mediate MC reduction. Specific examples include Fe(II)-organic complexes<ref name="Naka2006">Naka, D., Kim, D., and Strathmann, T.J., 2006. Abiotic Reduction of Nitroaromatic Compounds by Aqueous Iron(II)−Catechol Complexes. Environmental Science and Technology 40(9), pp. 3006–3012.  [https://doi.org/10.1021/es060044t DOI: 10.1021/es060044t]</ref><ref name="Naka2008">Naka, D., Kim, D., Carbonaro, R.F., and Strathmann, T.J., 2008. Abiotic reduction of nitroaromatic contaminants by iron(II) complexes with organothiol ligands. Environmental Toxicology and Chemistry, 27(6), pp. 1257–1266.  [https://doi.org/10.1897/07-505.1 DOI: 10.1897/07-505.1]</ref><ref name="Hartenbach2008">Hartenbach, A.E., Hofstetter, T.B., Aeschbacher, M., Sander, M., Kim, D., Strathmann, T.J., Arnold, W.A., Cramer, C.J., and Schwarzenbach, R.P., 2008. Variability of Nitrogen Isotope Fractionation during the Reduction of Nitroaromatic Compounds with Dissolved Reductants. Environmental Science and Technology 42(22), pp. 8352–8359.  [https://doi.org/10.1021/es801063u DOI: 10.1021/es801063u]</ref><ref name="Kim2009">Kim, D., Duckworth, O.W., and Strathmann, T.J., 2009. Hydroxamate siderophore-promoted reactions between iron(II) and nitroaromatic groundwater contaminants. Geochimica et Cosmochimica Acta, 73(5), pp. 1297–1311.  [https://doi.org/10.1016/j.gca.2008.11.039 DOI: 10.1016/j.gca.2008.11.039]</ref><ref name="Kim2007">Kim, D., and Strathmann, T.J., 2007. Role of Organically Complexed Iron(II) Species in the Reductive Transformation of RDX in Anoxic Environments. Environmental Science and Technology, 41(4), pp. 1257–1264.  [https://doi.org/10.1021/es062365a DOI: 10.1021/es062365a]</ref>, iron oxides in the presence of aqueous Fe(II)<ref name="Colón2006">Colón, D., Weber, E.J., and Anderson, J.L., 2006. QSAR Study of the Reduction of Nitroaromatics by Fe(II) Species. Environmental Science and Technology, 40(16), pp. 4976–4982.  [https://doi.org/10.1021/es052425x DOI: 10.1021/es052425x]</ref><ref name="Luan2013">Luan, F., Xie, L., Li, J., and Zhou, Q., 2013. Abiotic reduction of nitroaromatic compounds by Fe(II) associated with iron oxides and humic acid. Chemosphere, 91(7), pp. 1035–1041.  [https://doi.org/10.1016/j.chemosphere.2013.01.070 DOI: 10.1016/j.chemosphere.2013.01.070]</ref><ref name="Gorski2016">Gorski, C.A., Edwards, R., Sander, M., Hofstetter, T.B., and Stewart, S.M., 2016. Thermodynamic Characterization of Iron Oxide–Aqueous Fe<sup>2+</sup> Redox Couples. Environmental Science and Technology, 50(16), pp. 8538–8547.  [https://doi.org/10.1021/acs.est.6b02661 DOI: 10.1021/acs.est.6b02661]</ref><ref name="Fan2016">Fan, D., Bradley, M.J., Hinkle, A.W., Johnson, R.L., and Tratnyek, P.G., 2016. Chemical Reactivity Probes for Assessing Abiotic Natural Attenuation by Reducing Iron Minerals. Environmental Science and Technology, 50(4), pp. 1868–1876.  [https://doi.org/10.1021/acs.est.5b05800 DOI: 10.1021/acs.est.5b05800]</ref><ref name="Jones2016">Jones, A.M., Kinsela, A.S., Collins, R.N., and Waite, T.D., 2016. The reduction of 4-chloronitrobenzene by Fe(II)-Fe(III) oxide systems - correlations with reduction potential and inhibition by silicate. Journal of Hazardous Materials, 320, pp. 143–149.  [https://doi.org/10.1016/j.jhazmat.2016.08.031 DOI: 10.1016/j.jhazmat.2016.08.031]</ref><ref name="Klausen1995">Klausen, J., Troeber, S.P., Haderlein, S.B., and Schwarzenbach, R.P., 1995. Reduction of Substituted Nitrobenzenes by Fe(II) in Aqueous Mineral Suspensions. Environmental Science and Technology, 29(9), pp. 2396–2404.  [https://doi.org/10.1021/es00009a036 DOI: 10.1021/es00009a036]</ref><ref name="Strehlau2016">Strehlau, J.H., Stemig, M.S., Penn, R.L., and Arnold, W.A., 2016. Facet-Dependent Oxidative Goethite Growth As a Function of Aqueous Solution Conditions. Environmental Science and Technology, 50(19), pp. 10406–10412.  [https://doi.org/10.1021/acs.est.6b02436 DOI: 10.1021/acs.est.6b02436]</ref><ref name="Elsner2004">Elsner, M., Schwarzenbach, R.P., and Haderlein, S.B., 2004. Reactivity of Fe(II)-Bearing Minerals toward Reductive Transformation of Organic Contaminants. Environmental Science and Technology, 38(3), pp. 799–807.  [https://doi.org/10.1021/es0345569 DOI: 10.1021/es0345569]</ref><ref name="Colón2008">Colón, D., Weber, E.J., and Anderson, J.L., 2008. Effect of Natural Organic Matter on the Reduction of Nitroaromatics by Fe(II) Species. Environmental Science and Technology, 42(17), pp. 6538–6543.  [https://doi.org/10.1021/es8004249 DOI: 10.1021/es8004249]</ref><ref name="Stewart2018">Stewart, S.M., Hofstetter, T.B., Joshi, P. and Gorski, C.A., 2018. Linking Thermodynamics to Pollutant Reduction Kinetics by Fe<sup>2+</sup> Bound to Iron Oxides. Environmental Science and Technology, 52(10), pp. 5600–5609.  [https://doi.org/10.1021/acs.est.8b00481 DOI: 10.1021/acs.est.8b00481]&nbsp;&nbsp; [https://pubs.acs.org/doi/pdf/10.1021/acs.est.8b00481 Open access article.]</ref><ref name="Klupinski2004">Klupinski, T.P., Chin, Y.P., and Traina, S.J., 2004. Abiotic Degradation of Pentachloronitrobenzene by Fe(II):  Reactions on Goethite and Iron Oxide Nanoparticles. Environmental Science and Technology, 38(16), pp. 4353–4360.  [https://doi.org/10.1021/es035434j DOI: 10.1021/es035434j]</ref>, magnetite<ref name="Klausen1995"/><ref name="Elsner2004"/><ref name="Heijman1993">Heijman, C.G., Holliger, C., Glaus, M.A., Schwarzenbach, R.P., and Zeyer, J., 1993. Abiotic Reduction of 4-Chloronitrobenzene to 4-Chloroaniline in a Dissimilatory Iron-Reducing Enrichment Culture. Applied and Environmental Microbiology, 59(12), pp. 4350–4353. [https://doi.org/10.1128/aem.59.12.4350-4353.1993 DOI: 10.1128/aem.59.12.4350-4353.1993]&nbsp;&nbsp; [https://journals.asm.org/doi/reader/10.1128/aem.59.12.4350-4353.1993 Open access article.]</ref><ref name="Gorski2009">Gorski, C.A., and Scherer, M.M., 2009. Influence of Magnetite Stoichiometry on Fe<sup>II</sup> Uptake and Nitrobenzene Reduction. Environmental Science and Technology, 43(10), pp. 3675–3680.  [https://doi.org/10.1021/es803613a DOI: 10.1021/es803613a]</ref><ref name="Gorski2010">Gorski, C.A., Nurmi, J.T., Tratnyek, P.G., Hofstetter, T.B. and Scherer, M.M., 2010. Redox Behavior of Magnetite: Implications for Contaminant Reduction. Environmental Science and Technology, 44(1), pp. 55–60.  [https://doi.org/10.1021/es9016848 DOI: 10.1021/es9016848]</ref>, Fe(II)-bearing clays<ref name="Hofstetter2006">Hofstetter, T.B., Neumann, A., and Schwarzenbach, R.P., 2006. Reduction of Nitroaromatic Compounds by Fe(II) Species Associated with Iron-Rich Smectites. Environmental Science and Technology, 40(1), pp. 235–242.  [https://doi.org/10.1021/es0515147 DOI: 10.1021/es0515147]</ref><ref name="Schultz2000">Schultz, C. A., and Grundl, T.J., 2000. pH Dependence on Reduction Rate of 4-Cl-Nitrobenzene by Fe(II)/Montmorillonite Systems. Environmental Science and Technology 34(17), pp. 3641–3648.  [https://doi.org/10.1021/es990931e DOI: 10.1021/es990931e]</ref><ref name="Luan2015a">Luan, F., Gorski, C.A., and Burgos, W.D., 2015. Linear Free Energy Relationships for the Biotic and Abiotic Reduction of Nitroaromatic Compounds. Environmental Science and Technology, 49(6), pp. 3557–3565.  [https://doi.org/10.1021/es5060918 DOI: 10.1021/es5060918]</ref><ref name="Luan2015b">Luan, F., Liu, Y., Griffin, A.M., Gorski, C.A. and Burgos, W.D., 2015. Iron(III)-Bearing Clay Minerals Enhance Bioreduction of Nitrobenzene by ''Shewanella putrefaciens'' CN32. Environmental Science and Technology, 49(3), pp. 1418–1426.  [https://doi.org/10.1021/es504149y DOI: 10.1021/es504149y]</ref><ref name="Hofstetter2003">Hofstetter, T.B., Schwarzenbach, R.P. and Haderlein, S.B., 2003. Reactivity of Fe(II) Species Associated with Clay Minerals. Environmental Science and Technology, 37(3), pp. 519–528.  [https://doi.org/10.1021/es025955r DOI: 10.1021/es025955r]</ref><ref name="Neumann2008">Neumann, A., Hofstetter, T.B., Lüssi, M., Cirpka, O.A., Petit, S., and Schwarzenbach, R.P., 2008. Assessing the Redox Reactivity of Structural Iron in Smectites Using Nitroaromatic Compounds As Kinetic Probes. Environmental Science and Technology, 42(22), pp. 8381–8387.  [https://doi.org/10.1021/es801840x DOI: 10.1021/es801840x]</ref><ref name="Hofstetter2008">Hofstetter, T.B., Neumann, A., Arnold, W.A., Hartenbach, A.E., Bolotin, J., Cramer, C.J., and Schwarzenbach, R.P., 2008. Substituent Effects on Nitrogen Isotope Fractionation During Abiotic Reduction of Nitroaromatic Compounds. Environmental Science and Technology, 42(6), pp. 1997–2003.  [https://doi.org/10.1021/es702471k DOI: 10.1021/es702471k]</ref>, hydroquinones (as surrogates of natural organic matter)<ref name="Hartenbach2008"/><ref name="Schwarzenbach1990">Schwarzenbach, R.P., Stierli, R., Lanz, K., and Zeyer, J., 1990. Quinone and Iron Porphyrin Mediated Reduction of Nitroaromatic Compounds in Homogeneous Aqueous Solution. Environmental Science and Technology, 24(10), pp. 1566–1574.  [https://doi.org/10.1021/es00080a017 DOI: 10.1021/es00080a017]</ref><ref name="Tratnyek1989">Tratnyek, P.G., and Macalady, D.L., 1989. Abiotic Reduction of Nitro Aromatic Pesticides in Anaerobic Laboratory Systems. Journal of Agricultural and Food Chemistry, 37(1), pp. 248–254.  [https://doi.org/10.1021/jf00085a058 DOI: 10.1021/jf00085a058]</ref><ref name="Hofstetter1999">Hofstetter, T.B., Heijman, C.G., Haderlein, S.B., Holliger, C. and Schwarzenbach, R.P., 1999. Complete Reduction of TNT and Other (Poly)nitroaromatic Compounds under Iron-Reducing Subsurface Conditions. Environmental Science and Technology, 33(9), pp. 1479–1487.  [https://doi.org/10.1021/es9809760 DOI: 10.1021/es9809760]</ref><ref name="Murillo-Gelvez2019">Murillo-Gelvez, J., Hickey, K.P., Di Toro, D.M., Allen, H.E., Carbonaro, R.F., and Chiu, P.C., 2019. Experimental Validation of Hydrogen Atom Transfer Gibbs Free Energy as a Predictor of Nitroaromatic Reduction Rate Constants. Environmental Science and Technology, 53(10), pp. 5816–5827.  [https://doi.org/10.1021/acs.est.9b00910 DOI: 10.1021/acs.est.9b00910]</ref><ref name="Niedźwiecka2017">Niedźwiecka, J.B., Drew, S.R., Schlautman, M.A., Millerick, K.A., Grubbs, E., Tharayil, N. and Finneran, K.T., 2017. Iron and Electron Shuttle Mediated (Bio)degradation of 2,4-Dinitroanisole (DNAN). Environmental Science and Technology, 51(18), pp. 10729–10735.  [https://doi.org/10.1021/acs.est.7b02433 DOI: 10.1021/acs.est.7b02433]</ref><ref name="Kwon2006">Kwon, M.J., and Finneran, K.T., 2006. Microbially Mediated Biodegradation of Hexahydro-1,3,5-Trinitro-1,3,5- Triazine by Extracellular Electron Shuttling Compounds. Applied and Environmental Microbiology, 72(9), pp. 5933–5941.  [https://doi.org/10.1128/AEM.00660-06 DOI: 10.1128/AEM.00660-06]&nbsp;&nbsp; [https://journals.asm.org/doi/reader/10.1128/AEM.00660-06 Open access article.]</ref>, dissolved organic matter<ref name="Dunnivant1992">Dunnivant, F.M., Schwarzenbach, R.P., and Macalady, D.L., 1992. Reduction of Substituted Nitrobenzenes in Aqueous Solutions Containing Natural Organic Matter. Environmental Science and Technology, 26(11), pp. 2133–2141.  [https://doi.org/10.1021/es00035a010 DOI: 10.1021/es00035a010]</ref><ref name="Luan2010">Luan, F., Burgos, W.D., Xie, L., and Zhou, Q., 2010. Bioreduction of Nitrobenzene, Natural Organic Matter, and Hematite by Shewanella putrefaciens CN32. Environmental Science and Technology, 44(1), pp. 184–190.  [https://doi.org/10.1021/es901585z DOI: 10.1021/es901585z]</ref><ref name="Murillo-Gelvez2021">Murillo-Gelvez, J., di Toro, D.M., Allen, H.E., Carbonaro, R.F., and Chiu, P.C., 2021. Reductive Transformation of 3-Nitro-1,2,4-triazol-5-one (NTO) by Leonardite Humic Acid and Anthraquinone-2,6-disulfonate (AQDS). Environmental Science and Technology, 55(19), pp. 12973–12983.  [https://doi.org/10.1021/acs.est.1c03333 DOI: 10.1021/acs.est.1c03333]</ref>, black carbon<ref name="Oh2013">Oh, S.-Y., Son, J.G., and Chiu, P.C., 2013. Biochar-Mediated Reductive Transformation of Nitro Herbicides and Explosives. Environmental Toxicology and Chemistry, 32(3), pp. 501–508.  [https://doi.org/10.1002/etc.2087 DOI: 10.1002/etc.2087]&nbsp;&nbsp; [https://setac.onlinelibrary.wiley.com/doi/epdf/10.1002/etc.2087 Open access article.]</ref><ref name="Oh2009">Oh, S.-Y., and Chiu, P.C., 2009. Graphite- and Soot-Mediated Reduction of 2,4-Dinitrotoluene and Hexahydro-1,3,5-trinitro-1,3,5-triazine. Environmental Science & Technology, 43(18), pp. 6983–6988.  [https://doi.org/10.1021/es901433m DOI: 10.1021/es901433m]</ref><ref name="Xu2015">Xu, W., Pignatello, J.J., and Mitch, W.A., 2015. Reduction of Nitroaromatics Sorbed to Black Carbon by Direct Reaction with Sorbed Sulfides. Environmental Science and Technology, 49(6), pp. 3419–3426.  [https://doi.org/10.1021/es5045198 DOI: 10.1021/es5045198]</ref><ref name="Oh2002">Oh, S.-Y., Cha, D.K., and Chiu, P.C., 2002. Graphite-Mediated Reduction of 2,4-Dinitrotoluene with Elemental Iron. Environmental Science and Technology, 36(10), pp. 2178–2184.  [https://doi.org/10.1021/es011474g DOI: 10.1021/es011474g]</ref><ref name="Amezquita-Garcia2013">Amezquita-Garcia, H.J., Razo-Flores, E., Cervantes, F.J., and Rangel-Mendez, J.R., 2013.  Activated carbon fibers as redox mediators for the increased reduction of nitroaromatics. Carbon, 55, pp. 276–284. [https://doi.org/10.1016/j.carbon.2012.12.062 DOI: 10.1016/j.carbon.2012.12.062]</ref><ref name="Xin2022">Xin, D., Girón, J., Fuller, M.E., and Chiu, P.C., 2022. Abiotic Reduction of 3-Nitro-1,2,4-triazol-5-one (NTO) and Other Munitions Constituents by Wood-Derived Biochar through Its Rechargeable Electron Storage Capacity. Environmental Science: Processes and Impacts, 24(2), pp. 316-329.  [https://doi.org/10.1039/D1EM00447F DOI: 10.1039/D1EM00447F]</ref>, and sulfides<ref name="Hojo1960">Hojo, M., Takagi, Y. and Ogata, Y., 1960. Kinetics of the Reduction of Nitrobenzenes by Sodium Disulfide. Journal of the American Chemical Society, 82(10), pp. 2459–2462.  [https://doi.org/10.1021/ja01495a017 DOI: 10.1021/ja01495a017]</ref><ref name="Zeng2012">Zeng, T., Chin, Y.P., and Arnold, W.A., 2012. Potential for Abiotic Reduction of Pesticides in Prairie Pothole Porewaters. Environmental Science and Technology, 46(6), pp. 3177–3187.  [https://doi.org/10.1021/es203584d DOI: 10.1021/es203584d]</ref>. These geo-reductants may control the fate and half-lives of MCs in the environment and can be used to promote MC degradation in soil and groundwater through enhanced natural attenuation<ref name="USEPA2012">US EPA, 2012. A Citizen’s Guide to Monitored Natural Attenuation. EPA document 542-F-12-014.  [https://www.epa.gov/sites/default/files/2015-04/documents/a_citizens_guide_to_monitored_natural_attenuation.pdf Free download.]</ref>.
 
  
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[[File:AbioMCredFig2.png | thumb |450px|Figure 2. General mechanism for the reduction of NACs/MCs.]]
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*[https://www.epa.gov/hw-sw846/leaching-environmental-assessment-framework-leaf-methods-and-guidance Leaching Environmental Assessment Framework (LEAF) Methods and Guidance] (EPA website)
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[[File:AbioMCredFig3.png | thumb |450px|Figure 3. Schematic of natural attenuation of MCs-impacted soils through chemical reduction.]]
 
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Although the chemical structures of MCs can vary significantly (Figure 1), most of them contain at least one nitro functional group (-NO<sub>2</sub>), which is susceptible to reductive transformation<ref name="Spain2000">Spain, J.C., Hughes, J.B., and Knackmuss, H.J., 2000. Biodegradation of Nitroaromatic Compounds and Explosives. CRC Press, 456 pages. ISBN: 9780367398491</ref>. Of the MCs shown in Figure 1, 2,4,6-trinitrotoluene (TNT), 2,4-dinitroanisole (DNAN), and 3-nitro-1,2,4-triazol-5-one (NTO)<ref name="Harris1996">Harris, N.J., and Lammertsma, K., 1996. Tautomerism, Ionization, and Bond Dissociations of 5-Nitro-2,4-dihydro-3H-1,2,4-triazolone. Journal of the American Chemical Society, 118(34), pp. 8048–8055.  [https://doi.org/10.1021/ja960834a DOI: 10.1021/ja960834a]</ref> are nitroaromatic compounds (NACs) and hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) and nitroguanidine (NQ) are nitramines. The structural differences may result in different reactivities and reaction pathways. Reduction of NACs results in the formation of aromatic amines (i.e., anilines) with nitroso and hydroxylamine compounds as intermediates (Figure 2)<ref name="Schwarzenbach2016"/>.
 
  
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Although the final reduction products are different for non-aromatic MCs, the reduction process often starts with the transformation of the -NO<sub>2</sub> moiety, either through de-nitration (e.g., RDX<ref name="Kwon2008">Kwon, M.J., and Finneran, K.T., 2008. Biotransformation products and mineralization potential for hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) in abiotic versus biological degradation pathways with anthraquinone-2,6-disulfonate (AQDS) and ''Geobacter metallireducens''. Biodegradation, 19(5), pp. 705–715.  [https://doi.org/10.1007/s10532-008-9175-5 DOI: 10.1007/s10532-008-9175-5]</ref><ref name="Halasz2011">Halasz, A., and Hawari, J., 2011. Degradation Routes of RDX in Various Redox Systems. Aquatic Redox Chemistry, American Chemical Society, 1071(20), pp. 441-462.  [https://doi.org/10.1021/bk-2011-1071.ch020 DOI: 10.1021/bk-2011-1071.ch020]</ref>) or reduction to nitroso<ref name="Kwon2006"/><ref name="Tong2021">Tong, Y., Berens, M.J., Ulrich, B.A., Bolotin, J., Strehlau, J.H., Hofstetter, T.B., and Arnold, W.A., 2021. Exploring the Utility of Compound-Specific Isotope Analysis for Assessing Ferrous Iron-Mediated Reduction of RDX in the Subsurface. Environmental Science and Technology, 55(10), pp. 6752–6763.  [https://doi.org/10.1021/acs.est.0c08420 DOI: 10.1021/acs.est.0c08420]</ref> followed by ring cleavage<ref name="Kim2007"/><ref name="Halasz2011"/><ref name="Tong2021"/><ref name="Larese-Casanova2008">Larese-Casanova, P., and Scherer, M.M., 2008. Abiotic Transformation of Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) by Green Rusts. Environmental Science and Technology, 42(11), pp. 3975–3981. [https://doi.org/10.1021/es702390b DOI: 10.1021/es702390b]</ref>.
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==Introduction to LEAF==
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The [https://www.epa.gov/ U.S. Environmental Protection Agency (EPA)] [https://www.epa.gov/hw-sw846/leaching-environmental-assessment-framework-leaf-methods-and-guidance Leaching Environmental Assessment Framework (LEAF)] is a suite of standardized test methods for evaluating contaminant release from solids under environmentally relevant conditions (Table 1). The four leaching methods within LEAF were originally validated for inorganic constituents<ref>Garrabrants, A.C., Kosson, D.S., Stefanski, L., DeLapp, R., Seignette, P.F.A.B., van der Sloot, H.A., Kariher, P., Baldwin, M., 2012. Interlaboratory Validation of the Leaching Environmental Assessment Framework (LEAF) Method 1313 and Method 1316, EPA/600/R-12/623, U.S. Environmental Protection Agency, Air Pollution and Control Division. [[Media: EPA 600_R-12_623.pdf | Free Download EPA 600/R-12/623]]</ref><ref>Garrabrants, A.C., Kosson, D.S., DeLapp, R., Kariher, P., Seignette, P.F.A.B., van der Sloot, H.A., Stefanski, L., Baldwin, M., 2012. Interlaboratory Validation of the Leaching Environmental Assessment Framework (LEAF) Method 1314 and Method 1315, EPA/600/R-12/624, U.S. Environmental Protection Agency, Air Pollution and Control Division. [[Media: EPA 600_R-12_624.pdf | Free Download EPA 600/R-12/624]]</ref> and included as standard leaching methods EPA 1313 – 1316 within Update V of SW-846<ref>USEPA, 2026. Hazardous Waste Test Methods / SW-846. [https://www.epa.gov/hw-sw846 USEPA SW-846 website]</ref>. To address the need for standardized tests to evaluate PFAS leaching and mobility, LEAF methods have been optimized and demonstrated for use with PFAS (Methods 1313A-1316A)<ref name="GarrabrantsEtAl2024">Garrabrants, A.C., Liu, F., Warne, R., DeLapp, R., Brown, L., Rubin, Z., Yawson, D., Kosson, D.S., Guelfo, J.L., Real, M.I., van der Sloot, H.A., Touati, A., Thorneloe, S., 2024. Development of Leaching Tests for Materials Containing SVOCs and PFAS, EPA 600/R-23/382, USEPA, Washington, D.C. [[Media: EPA 600_R-23_382.PDF | Free Download EPA 600/R-23/382]]</ref>. This article will focus on Methods 1313A, 1314A, and 1316A. Demonstration of Method 1315A for compacted granular materials (including concrete and asphalt) is ongoing.
  
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Figure 3 illustrates a typical MC reduction reaction. A redox-active soil constituent, such as organic matter or iron mineral, donates electrons to an MC and transforms the nitro group into an amino group (R-NH<sub>2</sub>). The rate at which an MC is reduced can vary by many orders of magnitude depending on the soil constituent, the MC, the reduction potential (''E<sub>H</sub>'') and other media conditions<ref name="Borch2010">Borch, T., Kretzschmar, R., Kappler, A., Cappellen, P.V., Ginder-Vogel, M., Voegelin, A., and Campbell, K., 2010. Biogeochemical Redox Processes and their Impact on Contaminant Dynamics. Environmental Science and Technology, 44(1), pp. 15–23.  [https://doi.org/10.1021/es9026248 DOI: 10.1021/es9026248]&nbsp;&nbsp; [https://pubs.acs.org/doi/pdf/10.1021/es9026248 Open access article.]</ref>.
+
{| class="wikitable" style="float:right; margin-left:10px;"
−
 
+
|+Table 1. EPA SW-846 methods that comprise the LEAF framework
−
The most prevalent reductants in soils are iron minerals and organic carbon such as that found in natural organic matter. It has been suggested that Fe(II)<sub>aq</sub> and dissolved organic matter concentrations could serve as indicators of NAC reducibility in anaerobic sediments<ref name="Zhang2009">Zhang, H., and Weber, E.J., 2009. Elucidating the Role of Electron Shuttles in Reductive Transformations in Anaerobic Sediments. Environmental Science and Technology, 43(4), pp. 1042–1048.  [https://doi.org/10.1021/es8017072 DOI: 10.1021/es8017072]</ref>. The following sections summarize these two classes of reductants separately and present advances in our understanding of the kinetics of NAC/MC reduction by these geo-reductants.
 
−
 
 
−
==Carbonaceous Reductants==
 
−
[[File:AbioMCredFig4.png | thumb |600px|Figure 4. Chemical structure of commonly used hydroquinones in NACs/MCs kinetic experiments.]]
 
−
The two most predominant forms of organic carbon in natural systems are natural organic matter (NOM) and black carbon (BC)<ref name="Schumacher2002">Schumacher, B.A., 2002. Methods for the Determination of Total Organic Carbon (TOC) in Soils and Sediments. U.S. EPA, Ecological Risk Assessment Support Center. [http://bcodata.whoi.edu/LaurentianGreatLakes_Chemistry/bs116.pdf Free download.]</ref>. Black carbon includes charcoal, soot, graphite, and coal. Until the early 2000s black carbon was considered to be a class of (bio)chemically inert geosorbents<ref name="Schmidt2000">Schmidt, M.W.I., and Noack, A.G., 2000. Black carbon in soils and sediments: Analysis, distribution, implications, and current challenges. Global Biogeochemical Cycles, 14(3), pp. 777–793.  [https://doi.org/10.1029/1999GB001208 DOI: 10.1029/1999GB001208]&nbsp;&nbsp; [https://agupubs.onlinelibrary.wiley.com/doi/epdf/10.1029/1999GB001208 Open access article.]</ref>. However, it has been shown that BC can contain abundant quinone functional groups and thus can store and exchange electrons<ref name="Klüpfel2014">Klüpfel, L., Keiluweit, M., Kleber, M., and Sander, M., 2014. Redox Properties of Plant Biomass-Derived Black Carbon (Biochar). Environmental Science and Technology, 48(10), pp. 5601–5611.  [https://doi.org/10.1021/es500906d DOI: 10.1021/es500906d]</ref> with chemical<ref name="Xin2019">Xin, D., Xian, M., and Chiu, P.C., 2019. New methods for assessing electron storage capacity and redox reversibility of biochar. Chemosphere, 215, 827–834.  [https://doi.org/10.1016/j.chemosphere.2018.10.080 DOI: 10.1016/j.chemosphere.2018.10.080]</ref> and biological<ref name="Saquing2016">Saquing, J.M., Yu, Y.-H., and Chiu, P.C., 2016. Wood-Derived Black Carbon (Biochar) as a Microbial Electron Donor and Acceptor. Environmental Science and Technology Letters, 3(2), pp. 62–66.  [https://doi.org/10.1021/acs.estlett.5b00354 DOI: 10.1021/acs.estlett.5b00354]</ref> agents in the surroundings. Specifically, BC such as biochar has been shown to reductively transform MCs including NTO, DNAN, and RDX<ref name="Xin2022"/>.
 
−
 
 
−
NOM encompasses all the organic compounds present in terrestrial and aquatic environments and can be classified into two groups, non-humic and humic substances. Humic substances (HS) contain a wide array of functional groups including carboxyl, enol, ether, ketone, ester, amide, (hydro)quinone, and phenol<ref name="Sparks2003">Sparks, D.L., 2003. Environmental Soil Chemistry, 2nd Edition. Elsevier Science and Technology Books.  [https://doi.org/10.1016/B978-0-12-656446-4.X5000-2 DOI: 10.1016/B978-0-12-656446-4.X5000-2]</ref>. Quinone and hydroquinone groups are believed to be the predominant redox moieties responsible for the capacity of HS and BC to store and reversibly accept and donate electrons (i.e., through reduction and oxidation of HS/BC, respectively)<ref name="Schwarzenbach1990"/><ref name="Dunnivant1992"/><ref name="Klüpfel2014"/><ref name="Scott1998">Scott, D.T., McKnight, D.M., Blunt-Harris, E.L., Kolesar, S.E., and Lovley, D.R., 1998. Quinone Moieties Act as Electron Acceptors in the Reduction of Humic Substances by Humics-Reducing Microorganisms. Environmental Science and Technology, 32(19), pp. 2984–2989.  [https://doi.org/10.1021/es980272q DOI: 10.1021/es980272q]</ref><ref name="Cory2005">Cory, R.M., and McKnight, D.M., 2005. Fluorescence Spectroscopy Reveals Ubiquitous Presence of Oxidized and Reduced Quinones in Dissolved Organic Matter. Environmental Science & Technology, 39(21), pp 8142–8149.  [https://doi.org/10.1021/es0506962 DOI: 10.1021/es0506962]</ref><ref name="Fimmen2007">Fimmen, R.L., Cory, R.M., Chin, Y.P., Trouts, T.D., and McKnight, D.M., 2007. Probing the oxidation–reduction properties of terrestrially and microbially derived dissolved organic matter. Geochimica et Cosmochimica Acta, 71(12), pp. 3003–3015.  [https://doi.org/10.1016/j.gca.2007.04.009 DOI: 10.1016/j.gca.2007.04.009]</ref><ref name="Struyk2001">Struyk, Z., and Sposito, G., 2001. Redox properties of standard humic acids. Geoderma, 102(3-4), pp. 329–346.  [https://doi.org/10.1016/S0016-7061(01)00040-4 DOI: 10.1016/S0016-7061(01)00040-4]</ref><ref name="Ratasuk2007">Ratasuk, N., and Nanny, M.A., 2007. Characterization and Quantification of Reversible Redox Sites in Humic Substances. Environmental Science and Technology, 41(22), pp. 7844–7850.  [https://doi.org/10.1021/es071389u DOI: 10.1021/es071389u]</ref><ref name="Aeschbacher2010">Aeschbacher, M., Sander, M., and Schwarzenbach, R.P., 2010. Novel Electrochemical Approach to Assess the Redox Properties of Humic Substances. Environmental Science and Technology, 44(1), pp. 87–93.  [https://doi.org/10.1021/es902627p DOI: 10.1021/es902627p]</ref><ref name="Aeschbacher2011">Aeschbacher, M., Vergari, D., Schwarzenbach, R.P., and Sander, M., 2011. Electrochemical Analysis of Proton and Electron Transfer Equilibria of the Reducible Moieties in Humic Acids. Environmental Science and Technology, 45(19), pp. 8385–8394.  [https://doi.org/10.1021/es201981g DOI: 10.1021/es201981g]</ref><ref name="Bauer2009">Bauer, I., and Kappler, A., 2009. Rates and Extent of Reduction of Fe(III) Compounds and O<sub>2</sub> by Humic Substances. Environmental Science and Technology, 43(13), pp. 4902–4908.  [https://doi.org/10.1021/es900179s DOI: 10.1021/es900179s]</ref><ref name="Maurer2010">Maurer, F., Christl, I. and Kretzschmar, R., 2010. Reduction and Reoxidation of Humic Acid: Influence on Spectroscopic Properties and Proton Binding. Environmental Science and Technology, 44(15), pp. 5787–5792.  [https://doi.org/10.1021/es100594t DOI: 10.1021/es100594t]</ref><ref name="Walpen2016">Walpen, N., Schroth, M.H., and Sander, M., 2016. Quantification of Phenolic Antioxidant Moieties in Dissolved Organic Matter by Flow-Injection Analysis with Electrochemical Detection. Environmental Science and Technology, 50(12), pp. 6423–6432.  [https://doi.org/10.1021/acs.est.6b01120 DOI: 10.1021/acs.est.6b01120]&nbsp;&nbsp; [https://pubs.acs.org/doi/pdf/10.1021/acs.est.6b01120 Open access article.]</ref><ref name="Aeschbacher2012">Aeschbacher, M., Graf, C., Schwarzenbach, R.P., and Sander, M., 2012.  Antioxidant Properties of Humic Substances. Environmental Science and Technology, 46(9), pp. 4916–4925.  [https://doi.org/10.1021/es300039h DOI: 10.1021/es300039h]</ref><ref name="Nurmi2002">Nurmi, J.T., and Tratnyek, P.G., 2002. Electrochemical Properties of Natural Organic Matter (NOM), Fractions of NOM, and Model Biogeochemical Electron Shuttles. Environmental Science and Technology, 36(4), pp. 617–624.  [https://doi.org/10.1021/es0110731 DOI: 10.1021/es0110731]</ref>.
 
−
 
 
−
Hydroquinones have been widely used as surrogates to understand the reductive transformation of NACs and MCs by NOM. Figure 4 shows the chemical structures of the singly deprotonated forms of four hydroquinone species previously used to study NAC/MC reduction. The second-order rate constants (''k<sub>R</sub>'') for the reduction of NACs/MCs by these hydroquinone species are listed in Table 1, along with the aqueous-phase one electron reduction potentials of the NACs/MCs (''E<sub>H</sub><sup>1’</sup>'') where available. ''E<sub>H</sub><sup>1’</sup>'' is an experimentally measurable thermodynamic property that reflects the propensity of a given NAC/MC to accept an electron in water (''E<sub>H</sub><sup>1</sup>''(R-NO<sub>2</sub>)):
 
−
 
 
−
:::::<big>'''Equation 1:'''&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;''R-NO<sub>2</sub> + e<sup>-</sup> ⇔ R-NO<sub>2</sub><sup>•-</sup>''</big>
 
−
 
 
−
Knowing the identity of and reaction order in the reductant is required to derive the second-order rate constants listed in Table 1. This same reason limits the utility of reduction rate constants measured with complex carbonaceous reductants such as NOM<ref name="Dunnivant1992"/>, BC<ref name="Oh2013"/><ref name="Oh2009"/><ref name="Xu2015"/><ref name="Xin2021">Xin, D., 2021. Understanding the Electron Storage Capacity of Pyrogenic Black Carbon: Origin, Redox Reversibility, Spatial Distribution, and Environmental Applications. Doctoral Thesis, University of Delaware.  [https://udspace.udel.edu/bitstream/handle/19716/30105/Xin_udel_0060D_14728.pdf?sequence=1 Free download.]</ref>, and HS<ref name="Luan2010"/><ref name="Murillo-Gelvez2021"/>, whose chemical structures and redox moieties responsible for the reduction, as well as their abundance, are not clearly defined or known. In other words, the observed rate constants in those studies are specific to the experimental conditions (e.g., pH and NOM source and concentration), and may not be easily comparable to other studies.
 
−
 
 
−
{| class="wikitable mw-collapsible" style="float:left; margin-right:40px; text-align:center;"
 
−
|+ Table&nbsp;1.&nbsp;Aqueous&nbsp;phase one electron reduction potentials and logarithm of second-order rate constants for the reduction of NACs and MCs by the singly deprotonated form of the hydroquinones lawsone, juglone, AHQDS and AHQS, with the second-order rate constants for the deprotonated NAC/MC species (i.e., nitrophenolates and NTO<sup>–</sup>) in parentheses.
 
 
|-
 
|-
−
! Compound 
+
!Method
−
! rowspan="2" |''E<sub>H</sub><sup>1'</sup>'' (V)
+
!Description
−
! colspan="4"| Hydroquinone (log ''k<sub>R</sub>''&nbsp;(M<sup>-1</sup>s<sup>-1</sup>))
 
 
|-
 
|-
−
! (NAC/MC)
+
| 1313 || Liquid-solid partitioning as a function of '''''extract pH''''' using a parallel batch extraction (i.e., equilibrium) procedure (Figure 1)
−
! LAW<sup>-</sup>
 
−
! JUG<sup>-</sup>
 
−
! AHQDS<sup>-</sup>
 
−
! AHQS<sup>-</sup>
 
 
|-
 
|-
−
| Nitrobenzene (NB) || -0.485<ref name="Schwarzenbach1990"/> || 0.380<ref name="Schwarzenbach1990"/> || -1.102<ref name="Schwarzenbach1990"/> || 2.050<ref name="Murillo-Gelvez2019"/> || 3.060<ref name="Murillo-Gelvez2019"/>
+
| 1314 || Liquid-solid partitioning as a function of '''''liquid-solid ratio (L/S)''''' for constituents in solid materials using an up-flow '''''percolation''''' column procedure (Figure 3)
 
|-
 
|-
−
| 2-nitrotoluene (2-NT) || -0.590<ref name="Schwarzenbach1990"/> || -1.432<ref name="Schwarzenbach1990"/> || -2.523<ref name="Schwarzenbach1990"/> || 0.775<ref name="Hartenbach2008"/> ||
+
| 1315 || '''''Mass transfer rates''''' of constituents in monolithic or compacted granular materials using a semi-dynamic tank leaching procedure
−
|-
 
−
| 3-nitrotoluene (3-NT) || -0.475<ref name="Schwarzenbach1990"/> || 0.462<ref name="Schwarzenbach1990"/> || -0.921<ref name="Schwarzenbach1990"/> ||  ||
 
 
|-
 
|-
−
| 4-nitrotoluene (4-NT) || -0.500<ref name="Schwarzenbach1990"/> || 0.041<ref name="Schwarzenbach1990"/> || -1.292<ref name="Schwarzenbach1990"/> || 1.822<ref name="Hartenbach2008"/> || 2.610<ref name="Murillo-Gelvez2019"/>
+
| 1316 || Liquid-solid partitioning as a function of '''''L/S''''' using a parallel batch extraction (i.e., '''''equilibrium''''') procedure (Figure 2)
 
|-
 
|-
−
| 2-chloronitrobenzene (2-ClNB) || -0.485<ref name="Schwarzenbach1990"/> || 0.342<ref name="Schwarzenbach1990"/> || -0.824<ref name="Schwarzenbach1990"/> ||2.412<ref name="Hartenbach2008"/> ||
+
| colspan="2" style="background:white;" | Note: Text shown in '''''bold''''' indicates primary condition evaluated in each method.
−
|-
 
−
| 3-chloronitrobenzene (3-ClNB) || -0.405<ref name="Schwarzenbach1990"/> || 1.491<ref name="Schwarzenbach1990"/> || 0.114<ref name="Schwarzenbach1990"/> || ||
 
−
|-
 
−
| 4-chloronitrobenzene (4-ClNB) || -0.450<ref name="Schwarzenbach1990"/> || 1.041<ref name="Schwarzenbach1990"/> || -0.301<ref name="Schwarzenbach1990"/> || 2.988<ref name="Hartenbach2008"/> ||
 
−
|-
 
−
| 2-acetylnitrobenzene (2-AcNB) || -0.470<ref name="Schwarzenbach1990"/> || 0.519<ref name="Schwarzenbach1990"/> || -0.456<ref name="Schwarzenbach1990"/> || ||
 
−
|-
 
−
| 3-acetylnitrobenzene (3-AcNB) || -0.405<ref name="Schwarzenbach1990"/> || 1.663<ref name="Schwarzenbach1990"/> || 0.398<ref name="Schwarzenbach1990"/> || ||
 
−
|-
 
−
| 4-acetylnitrobenzene (4-AcNB) || -0.360<ref name="Schwarzenbach1990"/> || 2.519<ref name="Schwarzenbach1990"/> || 1.477<ref name="Schwarzenbach1990"/> || ||
 
−
|-
 
−
| 2-nitrophenol (2-NP) || || 0.568 (0.079)<ref name="Schwarzenbach1990"/> || || ||
 
−
|-
 
−
| 4-nitrophenol (4-NP) || || -0.699 (-1.301)<ref name="Schwarzenbach1990"/> || || ||
 
−
|-
 
−
| 4-methyl-2-nitrophenol (4-Me-2-NP) || || 0.748 (0.176)<ref name="Schwarzenbach1990"/> || || ||
 
−
|-
 
−
| 4-chloro-2-nitrophenol (4-Cl-2-NP) || || 1.602 (1.114)<ref name="Schwarzenbach1990"/> || || ||
 
−
|-
 
−
| 5-fluoro-2-nitrophenol (5-Cl-2-NP) || || 0.447 (-0.155)<ref name="Schwarzenbach1990"/> || || ||
 
−
|-
 
−
| 2,4,6-trinitrotoluene (TNT) || -0.280<ref name="Schwarzenbach2016"/> || || 2.869<ref name="Hofstetter1999"/> || 5.204<ref name="Hartenbach2008"/> ||
 
−
|-
 
−
| 2-amino-4,6-dinitrotoluene (2-A-4,6-DNT) || -0.400<ref name="Schwarzenbach2016"/> || || 0.987<ref name="Hofstetter1999"/> || ||
 
−
|-
 
−
| 4-amino-2,6-dinitrotoluene (4-A-2,6-DNT) || -0.440<ref name="Schwarzenbach2016"/>  || || 0.079<ref name="Hofstetter1999"/> || ||
 
−
|-
 
−
| 2,4-diamino-6-nitrotoluene (2,4-DA-6-NT) || -0.505<ref name="Schwarzenbach2016"/> || || -1.678<ref name="Hofstetter1999"/> || ||
 
−
|-
 
−
| 2,6-diamino-4-nitrotoluene (2,6-DA-4-NT) || -0.495<ref name="Schwarzenbach2016"/> || || -1.252<ref name="Hofstetter1999"/> || ||
 
−
|-
 
−
| 1,3-dinitrobenzene (1,3-DNB) || -0.345<ref name="Hofstetter1999"/> || || 1.785<ref name="Hofstetter1999"/> || ||
 
−
|-
 
−
| 1,4-dinitrobenzene (1,4-DNB) || -0.257<ref name="Hofstetter1999"/> || || 3.839<ref name="Hofstetter1999"/> || ||
 
−
|-
 
−
| 2-nitroaniline (2-NANE) || < -0.560<ref name="Hofstetter1999"/> || || -2.638<ref name="Hofstetter1999"/> || ||
 
−
|-
 
−
| 3-nitroaniline (3-NANE) || -0.500<ref name="Hofstetter1999"/> || || -1.367<ref name="Hofstetter1999"/> || ||
 
−
|-
 
−
| 1,2-dinitrobenzene (1,2-DNB) || -0.290<ref name="Hofstetter1999"/> || || || 5.407<ref name="Hartenbach2008"/> ||
 
−
|-
 
−
| 4-nitroanisole (4-NAN) || || -0.661<ref name="Murillo-Gelvez2019"/> || || 1.220<ref name="Murillo-Gelvez2019"/> ||
 
−
|-
 
−
| 2-amino-4-nitroanisole (2-A-4-NAN) || || -0.924<ref name="Murillo-Gelvez2019"/> || || 1.150<ref name="Murillo-Gelvez2019"/> || 2.190<ref name="Murillo-Gelvez2019"/>
 
−
|-
 
−
| 4-amino-2-nitroanisole (4-A-2-NAN) || || || ||1.610<ref name="Murillo-Gelvez2019"/> || 2.360<ref name="Murillo-Gelvez2019"/>
 
−
|-
 
−
| 2-chloro-4-nitroaniline (2-Cl-5-NANE) || || -0.863<ref name="Murillo-Gelvez2019"/> || || 1.250<ref name="Murillo-Gelvez2019"/> || 2.210<ref name="Murillo-Gelvez2019"/>
 
−
|-
 
−
| N-methyl-4-nitroaniline (MNA) || || -1.740<ref name="Murillo-Gelvez2019"/> || || -0.260<ref name="Murillo-Gelvez2019"/> || 0.692<ref name="Murillo-Gelvez2019"/>
 
−
|-
 
−
| 3-nitro-1,2,4-triazol-5-one (NTO) || || || || 5.701 (1.914)<ref name="Murillo-Gelvez2021"/> ||
 
−
|-
 
−
| Hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) || || || || -0.349<ref name="Kwon2008"/> ||
 
 
|}
 
|}
  
−
[[File:AbioMCredFig5.png | thumb |500px|Figure 5. Relative reduction rate constants of the NACs/MCs listed in Table 1 for AHQDS<sup>–</sup>. Rate constants are compared with respect to RDX. Abbreviations of NACs/MCs as listed in Table 1.]]
+
==Method Development for PFAS==
−
Most of the current knowledge about MC degradation is derived from studies using NACs. The reduction kinetics of only four MCs, namely TNT, N-methyl-4-nitroaniline (MNA), NTO, and RDX, have been investigated with hydroquinones. Of these four MCs, only the reduction rates of MNA and TNT have been modeled<ref name="Hofstetter1999"/><ref name="Murillo-Gelvez2019"/><ref name="Riefler2000">Riefler, R.G., and Smets, B.F., 2000. Enzymatic Reduction of 2,4,6-Trinitrotoluene and Related Nitroarenes: Kinetics Linked to One-Electron Redox Potentials. Environmental Science and Technology, 34(18), pp. 3900–3906. [https://doi.org/10.1021/es991422f DOI: 10.1021/es991422f]</ref><ref name="Salter-Blanc2015">Salter-Blanc, A.J., Bylaska, E.J., Johnston, H.J., and Tratnyek, P.G., 2015. Predicting Reduction Rates of Energetic Nitroaromatic Compounds Using Calculated One-Electron Reduction Potentials. Environmental Science and Technology, 49(6), pp. 3778–3786. [https://doi.org/10.1021/es505092s DOI: 10.1021/es505092s]&nbsp;&nbsp; [https://pubs.acs.org/doi/pdf/10.1021/es505092s Open access article.]</ref>.  
+
Complete details of the development of LEAF Methods 1313A, 1314A, and 1316A for use with PFAS are available in Garrabrants ''et al.'', 2024<ref name="GarrabrantsEtAl2024"/>. Representative method modifications include:
 +
* Materials of construction for experimental apparatus: containers used for leaching vessels (Methods 1313A, 1316A) and column construction materials (Method 1314A) evaluated for background PFAS and PFAS uptake.
 +
* Reagents and eluant composition: eluant composition was optimized to use 1 mM CaCl2 to reduce formation of colloidal matter; Method 1313A pH adjustment now conducted with nonoxidizing HCl.
 +
* Experimental conditions: Longer equilibration times (e.g., Method 1313, 1316) may be required due to slow desorption kinetics of certain PFAS from soil and organic matrices, implementation of settling to facilitate separation of solids from eluates.
 +
* Eluate processing (all methods): Use of centrifugation in lieu of eluate filtering, sonication of bottle prior to eluate subsampling.
 +
 
 +
==Batch Test Demonstration Studies==
 +
PFAS-specific adaptations were tested in batch test demonstration studies, which included triplicate implementation of Methods 1313A and 1316A in four AFFF-impacted site soils.
 +
 
 +
[[File: GuelfoFig1.png | thumb | 500 px | Figure 1: Figure 1. a) Overview of LEAF Method 1313A and b) PFHxS leaching as a function of pH<ref name="GarrabrantsEtAl2024"/>. Definitions: lower limit of quantification (LLOQ) and method detection limit (MDL)]]
 +
'''Draft Method 1313A''' was used to evaluate pH-dependent leaching in PFAS-contaminated soils in parallel batch extractions where each set of batch reactors is prepared and equilibrated at different pH (Figure 1). Short-chain PFAS (≤6 fluorinated carbons) generally showed little to no variation in leaching across the tested pH range of 2-13 (e.g., [[Wikipedia: Perfluorohexanesulfonic acid | PFHxS]], Figure 1), whereas long-chain PFAS exhibited increased leaching at higher pH<ref name="GarrabrantsEtAl2024"/>. This trend is consistent with previous findings showing that soil-water partitioning coefficients (''K<sub>d</sub>'') decrease as pH increases (e.g., Higgins and Luthy 2006)<ref name="HigginsLuthy2006">Higgins, C.P., Luthy, R.G., 2006. Sorption of Perfluorinated Surfactants on Sediments. Environmental Science and Technology, 40(23), pp. 7251–7256. [https://doi.org/10.1021/es061000n doi: 10.1021/es061000n]</ref>. The most pronounced pH effects were observed for perfluoroalkyl sulfonamides (FASAs) such as [[Wikipedia: Perfluorooctanesulfonamide | perfluorooctane sulfonamide (FOSA)]], which transition from neutral to anionic forms within the circumneutral pH range (~pH 6). The anionic form has a lower ''K<sub>d</sub>'' and results in higher leaching concentrations<ref name="GarrabrantsEtAl2024"/><ref name="NguyenEtAl2020">Nguyen, T.M.H., Bräunig, J., Thompson, K., Thompson, J., Kabiri, S., Navarro, D.A., Kookana, R.S., Grimison, C., Barnes, C.M., Higgins, C.P., McLaughlin, M.J., Mueller, J.F., 2020. Influences of Chemical Properties, Soil Properties, and Solution pH on Soil–Water Partitioning Coefficients of Per- and Polyfluoroalkyl Substances (PFASs). Environmental Science and Technology, 54(24), pp. 15883–15892. [https://doi.org/10.1021/acs.est.0c05705 doi: 10.1021/acs.est.0c05705]&nbsp; [[Media: NguyenEtAl2020.pdf | Open Access Article]]</ref>. For many site management scenarios where pH is circumneutral, variations in anionic PFAS leaching are expected to be small over the relevant pH range. In such cases, when testing time and costs are primary considerations, Method 1313A may be a lower priority relative to evaluating leaching as a function of L/S (Method 1316A, Method 1314A).  Different considerations may be needed where FASAs or PFAS with multiple, ionizable functional groups (i.e., [[Wikipedia: Zwitterion | zwitterions]]) are of concern.
 +
 
 +
[[File: GuelfoFig2.png | thumb | 500 px | Figure 2: a) Overview of LEAF Method 1316A and b) PFHxS leaching as a function of L/S ratio evaluated in parallel batch leaching vessels<ref name="GarrabrantsEtAl2024"/>]]
 +
'''Draft Method 1316A''' was used to evaluate L/S-dependent leaching of PFAS in impacted soils using parallel batch extractions where each set of batch reactors is prepared and equilibrated at a different L/S. (Figure 2).  Methods 1314A and 1316A are similar in intent as they both evaluate leaching as a function of L/S; however, the experimental approach differs.  Method 1314A uses a flow-through column configuration (Figure 3; discussed further below).  Method 1314A may better simulate field conditions, but Method 1316A is simpler and less costly to implement.  Trends in Method 1314A and 1316A are expected to be qualitatively similar but leaching concentrations are expected to exhibit differences. Despite this, leaching studies comparing Methods 1314A and 1316A for inorganics showed that cumulative release results were within one order of magnitude<ref>Lopez Meza, S., Garrabrants, A.C., van der Sloot, H., Kosson, D.S., 2008. Comparison of the Release of Constituents from Granular Materials under Batch and Column Testing. Waste Management, 28(10), pp. 1853–1867. [https://doi.org/10.1016/j.wasman.2007.11.009 doi: 10.1016/j.wasman.2007.11.009]</ref>.
 +
 
 +
Method 1316A and Method 1314A may also provide different insights into transport mechanisms. Because Method 1316A is performed using equilibrated batch reactors at varying L/S, results can be used to develop equilibrium desorption isotherms and calculate desorption coefficients (e.g., ''K<sub><small>d,desorption</small></sub>''). Studies have shown that ''K<sub><small>d,desorption</small></sub>'' values for PFAS may be greater than ''K<sub><small>d</small></sub>'', an effect often attributed to desorption hysteresis<ref>Schaefer, C.E., Nguyen, D., Christie, E., Shea, S., Higgins, C.P., Field, J., 2022. Desorption Isotherms for Poly- and Perfluoroalkyl Substances in Soil Collected from an Aqueous Film-Forming Foam Source Area. Journal of Environmental Engineering, 148(1), Article 04021074. [https://doi.org/10.1061/(ASCE)EE.1943-7870.0001952 doi: 10.1061/(ASCE)EE.1943-7870.0001952]</ref>. Consequently Method 1316A provides a straightforward method to estimate site-specific desorption parameters. Although sorption parameters can also be inferred from column (Method 1314A) data, interpretation is often complicated by nonequilibrium processes.  Conversely, the column data can be valuable for quantifying those additional mechanisms providing transport parameters that can describe rate-limited transport (e.g., fraction of non-equilibrium sorption sites and sorption rates) and other dynamic behavior.
 +
 
 +
As anticipated, trends in PFAS leaching obtained during the Method 1316A and Method 1314A demonstrations were qualitatively similar. These are further discussed below.
  
−
Using the rate constants obtained with AHQDS<sup>–</sup>, a relative reactivity trend can be obtained (Figure 5). RDX is the slowest reacting MC in Table 1, hence it was selected to calculate the relative rates of reaction (i.e., log ''k<sub>NAC/MC</sub>'' – log ''k<sub>RDX</sub>''). If only the MCs in Figure 5 are considered, the reactivity spans 6 orders of magnitude following the trend: RDX ≈ MNA < NTO<sup>–</sup> < DNAN < TNT < NTO. The rate constant for DNAN reduction by AHQDS<sup>–</sup> is not yet published and hence not included in Table 1. Note that speciation of NACs/MCs can significantly affect their reduction rates. Upon deprotonation, the NAC/MC becomes negatively charged and less reactive as an oxidant (i.e., less prone to accept an electron). As a result, the second-order rate constant can decrease by 0.5-0.6 log unit in the case of nitrophenols and approximately 4 log units in the case of NTO (numbers in parentheses in Table 1)<ref name="Schwarzenbach1990"/><ref name="Murillo-Gelvez2021"/>.
+
==Column Test Demonstration Studies==
 +
[[File: GuelfoFig3.png | thumb | 500 px | Figure 3. a) Overview of LEAF Method 1314A and b) PFHxS leaching as a function of ∑(L/S) evaluated in saturated up-flow column tests<ref name="GarrabrantsEtAl2024"/>. Note that acrylic here simply refers to the column material of construction used in this round of Method 1314 testing.]]
 +
PFAS-specific adaptations were tested in column test demonstration studies, which included triplicate implementation of Method 1314A in three AFFF-impacted site soils.
  
−
==Ferruginous Reductants==
+
'''Draft Method 1314A''' was implemented in saturated, up-flow columns to evaluate leaching of PFAS as a function of cumulative L/S (∑(L/S)); Figure 3; total volume of water that has passed through the column divided by the soil mass in the column). As noted, the intent of Method 1314a and 1316a is similar, and in both tests, similar qualitative results were observed. For example, short-chain PFAS exhibited high initial concentrations that decreased rapidly. However, in Method 1314a, these rapid drops in short-chain PFAS tended to occur by ∑(L/S) ≈  2 (e.g., Site 1 and 3 soils, Figure 3) whereas in some cases, such as for PFHxS, Method 1316A produced slightly flatter elution curves than Method 1314A (Figures 2b and 3b). Long-chain PFAS generally displayed flatter elution profiles than short-chain PFAS across both methods. These trends are consistent with chain length dependent sorption documented in the literature<ref name="HigginsLuthy2006"/><ref name="NguyenEtAl2020"/><ref>Guelfo, J.L., Higgins, C.P., 2013. Subsurface Transport Potential of Perfluoroalkyl Acids at Aqueous Film-Forming Foam (AFFF)-Impacted Sites. Environmental Science and Technology, 47(9), pp. 4164–4171. [https://doi.org/10.1021/es3048043 doi: 10.1021/es3048043]</ref>. Although column modeling is beyond the scope of this article, prior studies have shown that saturated transport can be influenced by rate-limited desorption, particularly for long-chain PFAS<ref>Doria-Manzur, A., Gray, E.P., Streets, S.S., Guelfo, J.L., 2025. Per- and Polyfluoroalkyl Substances (PFAS) Transport from Biosolids-Amended Soils: An Experimental and Numerical Approach. Water Research, 288(Part B), Article 124674. [https://doi.org/10.1016/j.watres.2025.124674 doi: 10.1016/j.watres.2025.124674]&nbsp; [[Media: Doria-ManzurEtAl2026.pdf | Open Access Article]]</ref><ref>Guelfo, J.L., Wunsch, A., McCray, J., Stults, J.F., Higgins, C.P., 2020. Subsurface Transport Potential of Perfluoroalkyl Acids (PFAAs): Column Experiments and Modeling. Journal of Contaminant Hydrology, 233, Article 103661. [https://doi.org/10.1016/j.jconhyd.2020.103661 doi: 10.1016/j.jconhyd.2020.103661]&nbsp; [[Media: GuelfoEtAl2020.pdf | Open Access Manuscript]]</ref>. As noted, data from Methods 1316A and 1314A can support estimation of transport parameters representing equilibrium and nonequilibrium behavior, respectively.
−
{| class="wikitable mw-collapsible" style="float:right; margin-left:40px; text-align:center;"
 
−
|+ Table&nbsp;2.&nbsp;Logarithm&nbsp;of&nbsp;second-order rate constants for reduction of NACs and MCs by dissolved Fe(II) complexes with the stoichiometry of ligand and iron in square brackets
 
−
|-
 
−
! rowspan="2" | Compound
 
−
! rowspan="2" | E<sub>H</sub><sup>1'</sup>  (V)
 
−
! Cysteine<ref name="Naka2008"/></br>[FeL<sub>2</sub>]<sup>2-</sup>
 
−
! Thioglycolic acid<ref name="Naka2008"/></br>[FeL<sub>2</sub>]<sup>2-</sup>
 
−
! DFOB<ref name="Kim2009"/></br>[FeHL]<sup>0</sup>
 
−
! AcHA<ref name="Kim2009"/></br>[FeL<sub>3</sub>]<sup>-</sup>
 
−
! Tiron <sup>a</sup></br>[FeL<sub>2</sub>]<sup>6-</sup>
 
−
! Fe-Porphyrin <sup>b</sup>
 
−
|-
 
−
! colspan="6" | Fe(II)-Ligand [log ''k<sub>R</sub>'' (M<sup>-1</sup>s<sup>-1</sup>)]
 
−
|-
 
−
| Nitrobenzene || -0.485<ref name="Schwarzenbach1990"/> || -0.347 || 0.874 || 2.235 || -0.136 || 1.424<ref name="Gao2021">Gao, Y., Zhong, S., Torralba-Sanchez, T.L., Tratnyek, P.G., Weber, E.J., Chen, Y., and Zhang, H., 2021. Quantitative structure activity relationships (QSARs) and machine learning models for abiotic reduction of organic compounds by an aqueous Fe(II) complex. Water Research, 192, p. 116843.  [https://doi.org/10.1016/j.watres.2021.116843 DOI: 10.1016/j.watres.2021.116843]</ref></br>4.000<ref name="Salter-Blanc2015"/> || -0.018<ref name="Schwarzenbach1990"/></br>0.026<ref name="Salter-Blanc2015"/>
 
−
|-
 
−
| 2-nitrotoluene || -0.590<ref name="Schwarzenbach1990"/> || || || || || || -0.602<ref name="Schwarzenbach1990"/>
 
−
|-
 
−
| 3-nitrotoluene || -0.475<ref name="Schwarzenbach1990"/> || -0.434 || 0.767 || 2.106 || -0.229 || 1.999<ref name="Gao2021"/></br>3.800<ref name="Salter-Blanc2015"/> || 0.041<ref name="Schwarzenbach1990"/>
 
−
|-
 
−
| 4-nitrotoluene || -0.500<ref name="Schwarzenbach1990"/> || -0.652 || 0.528 || 2.013 || -0.402 || 1.446<ref name="Gao2021"/></br>3.500<ref name="Salter-Blanc2015"/> || -0.174<ref name="Schwarzenbach1990"/>
 
−
|-
 
−
| 2-chloronitrobenzene || -0.485<ref name="Schwarzenbach1990"/> || || || || || || 0.944<ref name="Schwarzenbach1990"/>
 
−
|-
 
−
| 3-chloronitrobenzene || -0.405<ref name="Schwarzenbach1990"/> || 0.360 || 1.810 || 2.888 || 0.691 || 2.882<ref name="Gao2021"/></br>4.900<ref name="Salter-Blanc2015"/> || 0.724<ref name="Schwarzenbach1990"/>
 
−
|-
 
−
| 4-chloronitrobenzene || -0.450<ref name="Schwarzenbach1990"/> || 0.230 || 1.415 || 2.512 || 0.375 || 3.937<ref name="Gao2021"/></br>4.581<ref name="Naka2006"/> || 0.431<ref name="Schwarzenbach1990"/></br>0.289<ref name="Salter-Blanc2015"/>
 
−
|-
 
−
| 2-acetylnitrobenzene || -0.470<ref name="Schwarzenbach1990"/> || || || || || || 1.377<ref name="Schwarzenbach1990"/>
 
−
|-
 
−
| 3-acetylnitrobenzene || -0.405<ref name="Schwarzenbach1990"/> || || || || || || 0.799<ref name="Schwarzenbach1990"/>
 
−
|-
 
−
| 4-acetylnitrobenzene || -0.360<ref name="Schwarzenbach1990"/> || 0.965 || 2.771 || || 1.872 || 5.028<ref name="Gao2021"/></br>6.300<ref name="Salter-Blanc2015"/> || 1.693<ref name="Schwarzenbach1990"/>
 
−
|-
 
−
| RDX || -0.550<ref name="Uchimiya2010">Uchimiya, M., Gorb, L., Isayev, O., Qasim, M.M., and Leszczynski, J., 2010.  One-electron standard reduction potentials of nitroaromatic and cyclic nitramine explosives. Environmental Pollution, 158(10), pp. 3048–3053.  [https://doi.org/10.1016/j.envpol.2010.06.033 DOI: 10.1016/j.envpol.2010.06.033]</ref> || || || || || 2.212<ref name="Gao2021"/></br>2.864<ref name="Kim2007"/> ||
 
−
|-
 
−
| HMX || -0.660<ref name="Uchimiya2010"/> || || || || || -2.762<ref name="Gao2021"/> ||
 
−
|-
 
−
| TNT || -0.280<ref name="Schwarzenbach2016"/> || || || || || 7.427<ref name="Gao2021"/> || 2.050<ref name="Salter-Blanc2015"/>
 
−
|-
 
−
| 1,3-dinitrobenzene || -0.345<ref name="Hofstetter1999"/> || || || || || || 1.220<ref name="Salter-Blanc2015"/>
 
−
|-
 
−
| 2,4-dinitrotoluene || -0.380<ref name="Schwarzenbach2016"/> || || || || || 5.319<ref name="Gao2021"/> || 1.156<ref name="Salter-Blanc2015"/>
 
−
|-
 
−
| Nitroguanidine (NQ) || -0.700<ref name="Uchimiya2010"/> || || || || || -0.185<ref name="Gao2021"/> ||
 
−
|-
 
−
| 2,4-dinitroanisole (DNAN) || -0.400<ref name="Uchimiya2010"/> || || || || || || 1.243<ref name="Salter-Blanc2015"/>
 
−
|-
 
−
| colspan="8" style="text-align:left; background-color:white;" | Notes:</br>''<sup>a</sup>'' 4,5-dihydroxybenzene-1,3-disulfonate (Tiron). ''<sup>b</sup>'' meso-tetra(N-methyl-pyridyl)iron porphin in cysteine.
 
−
|}
 
−
{| class="wikitable mw-collapsible" style="float:left; margin-right:40px; text-align:center;"
 
−
|+ Table&nbsp;3.&nbsp;Rate constants for the reduction of MCs by iron minerals
 
−
|-
 
−
! MC
 
−
! Iron Mineral
 
−
! Iron mineral loading</br>(g/L)
 
−
! Surface area</br>(m<sup>2</sup>/g)
 
−
! Fe(II)<sub>aq</sub> initial</br>(mM) ''<sup>b</sup>''
 
−
! Fe(II)<sub>aq</sub> after 24 h</br>(mM) ''<sup>c</sup>''
 
−
! Fe(II)<sub>aq</sub> sorbed</br>(mM) ''<sup>d</sup>''
 
−
! pH
 
−
! Buffer
 
−
! Buffer</br>(mM)
 
−
! MC initial</br>(&mu;M) ''<sup>e</sup>''
 
−
! log ''k<sub>obs</sub>''</br>(h<sup>-1</sup>) ''<sup>f</sup>''
 
−
! log ''k<sub>SA</sub>''</br>(Lh<sup>-1</sup>m<sup>-2</sup>) ''<sup>g</sup>''
 
−
|-
 
−
| TNT 29 || Goethite || 0.64 || 17.5 || 1.5 || || || 7.0 || MOPS || 25 || 50 || 1.200 || 0.170
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 0.1 || 0 || 0.10 || 7.0 || HEPES || 50 || 50 || -3.500 || -5.200
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 0.2 || 0.02 || 0.18 || 7.0 || HEPES || 50 || 50 || -2.900 || -4.500
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 0.5 || 0.23 || 0.27 || 7.0 || HEPES || 50 || 50 || -1.900 || -3.600
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 1.5 || 0.94 || 0.56 || 7.0 || HEPES || 50 || 50 || -1.400 || -3.100
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 3.0 || 1.74 || 1.26 || 7.0 || HEPES || 50 || 50 || -1.200 || -2.900
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 5.0 || 3.38 || 1.62 || 7.0 || HEPES || 50 || 50 || -1.100 || -2.800
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 10.0 || 7.77 || 2.23 || 7.0 || HEPES || 50 || 50 || -1.000 || -2.600
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 1.6 || 1.42 || 0.16 || 6.0 || MES || 50 || 50 || -2.700 || -4.300
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 1.6 || 1.34 || 0.24 || 6.5 || MOPS || 50 || 50 || -1.800 || -3.400
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 1.6 || 1.21 || 0.37 || 7.0 || MOPS || 50 || 50 || -1.200 || -2.900
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 1.6 || 1.01 || 0.57 || 7.0 || HEPES || 50 || 50 || -1.200 || -2.800
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 1.6 || 0.76 || 0.82 || 7.5 || HEPES || 50 || 50 || -0.490 || -2.100
 
−
|-
 
−
| RDX 80 || Magnetite || 1.00 || 44 || 1.6 || 0.56 || 1.01 || 8.0 || HEPES || 50 || 50 || -0.590 || -2.200
 
−
|-
 
−
| NG 82 || Magnetite || 4.00 || 0.56|| 4.0 || || || 7.4 || HEPES || 90 || 226 || ||
 
−
|-
 
−
| NG 85 || Pyrite || 20.00 || 0.53 || || || || 7.4 || HEPES || 100 || 307 || -2.213 || -3.238
 
−
|-
 
−
| TNT 85 || Pyrite || 20.00 || 0.53 ||  || || || 7.4 || HEPES || 100 || 242 || -2.812 || -3.837
 
−
|-
 
−
| RDX 85 || Pyrite || 20.00 || 0.53 || || ||  || 7.4 || HEPES || 100 || 201 || -3.058 || -4.083
 
−
|-
 
−
| RDX 51 || Carbonate Green Rust || 5.00 || 36 || || || || 7.0 || || || 100 || ||
 
−
|-
 
−
| RDX 51 || Sulfate Green Rust || 5.00 || 20 || || || || 7.0 || || || 100 || ||
 
−
|-
 
−
| DNAN 83 || Sulfate Green Rust || 10.00 || || || || || 8.4 || || || 500 || ||
 
−
|-
 
−
| NTO 83 || Sulfate Green Rust || 10.00 || || || || || 8.4 || || || 500 || ||
 
−
|-
 
−
| DNAN 81 || Magnetite || 2.00 || 17.8 || 1.0 || || || 7.0 || NaHCO<sub>3</sub> || 10 || 200 || -0.100 || -1.700
 
−
|-
 
−
| DNAN 81 || Mackinawite || 1.50 || || || || || 7.0 || NaHCO<sub>3</sub> || 10 || 200 || 0.061 ||
 
−
|-
 
−
| DNAN 81 || Goethite || 1.00 || 103.8 || 1.0 || || || 7.0 || NaHCO<sub>3</sub> || 10 || 200 || 0.410 || -1.600
 
−
|-
 
−
| RDX 88 || Magnetite || 0.62 ||  || 1.0 ||  ||  || 7.0 || NaHCO<sub>3</sub> || 10 || 17.5 || -1.100 ||
 
−
|-
 
−
| RDX 88 || Magnetite || 0.62 ||  ||  ||  ||  || 7.0 || MOPS || 50 || 17.5 || -0.270 ||
 
−
|-
 
−
| RDX 88 || Magnetite || 0.62 ||  || 1.0 ||  ||  || 7.0 || MOPS || 10 || 17.6 || -0.480 ||
 
−
|-
 
−
| NTO 89 || Hematite || 1.00 || 5.7 || 1.0 || 0.92 || 0.08 || 5.5 || MES || 50 || 30 || -0.550 || -1.308
 
−
|-
 
−
| NTO 89 || Hematite || 1.00 || 5.7 || 1.0 || 0.85 || 0.15 || 6.0 || MES || 50 || 30 || 0.619 || -0.140
 
−
|-
 
−
| NTO 89 || Hematite || 1.00 || 5.7 || 1.0 || 0.9 || 0.10 || 6.5 || MES || 50 || 30 || 1.348 || 0.590
 
−
|-
 
−
| NTO 89 || Hematite || 1.00 || 5.7 || 1.0 || 0.77 || 0.23 || 7.0 || MOPS || 50 || 30 || 2.167 || 1.408
 
−
|-
 
−
| NTO 89 || Hematite ''<sup>a</sup>'' || 1.00 || 5.7 ||  || 1.01 ||  || 5.5 || MES || 50 || 30 || -1.444 || -2.200
 
−
|-
 
−
| NTO 89 || Hematite ''<sup>a</sup>'' || 1.00 || 5.7 ||  || 0.97 ||  || 6.0 || MES || 50 || 30 || -0.658 || -1.413
 
−
|-
 
−
| NTO 89 || Hematite ''<sup>a</sup>'' || 1.00 || 5.7 ||  || 0.87 ||  || 6.5 || MES || 50 || 30 || 0.068 || -0.688
 
−
|-
 
−
| NTO 89 || Hematite ''<sup>a</sup>'' || 1.00 || 5.7 ||  || 0.79 ||  || 7.0 || MOPS || 50 || 30 || 1.210 || 0.456
 
−
|-
 
−
| RDX 50 || Mackinawite || 0.45 ||  ||  ||  ||  || 6.5 || NaHCO<sub>3</sub> || 10 || 250 || -0.092 ||
 
−
|-
 
−
| RDX 50 || Mackinawite || 0.45 ||  ||  ||  ||  || 7.0 || NaHCO<sub>3</sub> || 10 || 250 || 0.009 ||
 
−
|-
 
−
| RDX 50 || Mackinawite || 0.45 ||  ||  ||  ||  || 7.5 || NaHCO<sub>3</sub> || 10 || 250 || 0.158 ||
 
−
|-
 
−
| RDX 50 || Green Rust || 5 ||  ||  ||  ||  || 6.5 || NaHCO<sub>3</sub> || 10 || 250 || -1.301 ||
 
−
|-
 
−
| RDX 50 || Green Rust || 5 ||  ||  ||  ||  || 7.0 || NaHCO<sub>3</sub> || 10 || 250 || -1.097 ||
 
−
|-
 
−
| RDX 50 || Green Rust || 5 ||  ||  ||  ||  || 7.5 || NaHCO<sub>3</sub> || 10 || 250 || -0.745 ||
 
−
|-
 
−
| RDX 50 || Goethite || 0.5 ||  || 1 || 1 ||  || 6.5 || NaHCO<sub>3</sub> || 10 || 250 || -0.921 ||
 
−
|-
 
−
| RDX 50 || Goethite || 0.5 ||  || 1 || 1 ||  || 7.0 || NaHCO<sub>3</sub> || 10 || 250 || -0.347 ||
 
−
|-
 
−
| RDX 50 || Goethite || 0.5 ||  || 1 || 1 ||  || 7.5 || NaHCO<sub>3</sub> || 10 || 250 || 0.009 ||
 
−
|-
 
−
| RDX 50 || Hematite || 0.5 ||  || 1 || 1 ||  || 6.5 || NaHCO<sub>3</sub> || 10 || 250 || -0.824 ||
 
−
|-
 
−
| RDX 50 || Hematite || 0.5 ||  || 1 || 1 ||  || 7.0 || NaHCO<sub>3</sub> || 10 || 250 || -0.456 ||
 
−
|-
 
−
| RDX 50 || Hematite || 0.5 ||  || 1 || 1 ||  || 7.5 || NaHCO<sub>3</sub> || 10 || 250 || -0.237 ||
 
−
|-
 
−
| RDX 50 || Magnetite || 2 ||  || 1 || 1 ||  || 6.5 || NaHCO<sub>3</sub> || 10 || 250 || -1.523 ||
 
−
|-
 
−
| RDX 50 || Magnetite || 2 ||  || 1 || 1 ||  || 7.0 || NaHCO<sub>3</sub> || 10 || 250 || -0.824 ||
 
−
|-
 
−
| RDX 50 || Magnetite || 2 || || 1 || 1 ||  || 7.5 || NaHCO<sub>3</sub> || 10 || 250 || -0.229 ||
 
−
|-
 
−
| DNAN 84 || Mackinawite || 4.28 || 0.25 ||  ||  ||  || 6.5 || NaHCO<sub>3</sub> || 8.5 + 20% CO<sub>2</sub>(g) || 400 || 0.836 || 0.806
 
−
|-
 
−
| DNAN 84 || Mackinawite || 4.28 || 0.25 ||  ||  ||  || 7.6 || NaHCO<sub>3</sub> || 95.2 + 20% CO<sub>2</sub>(g) || 400 || 0.762 || 0.732
 
−
|-
 
−
| DNAN 84 || Commercial FeS || 5.00 || 0.214 ||  ||  ||  || 6.5 || NaHCO<sub>3</sub> || 8.5 + 20% CO<sub>2</sub>(g) || 400 || 0.477 || 0.447
 
−
|-
 
−
| DNAN 84 || Commercial FeS || 5.00 || 0.214 ||  ||  ||  || 7.6 || NaHCO<sub>3</sub> || 95.2 + 20% CO<sub>2</sub>(g) || 400 || 0.745 || 0.716
 
−
|-
 
−
| NTO 84 || Mackinawite || 4.28 || 0.25 ||  ||  ||  || 6.5 || NaHCO<sub>3</sub> || 8.5 + 20% CO<sub>2</sub>(g) || 1000 || 0.663 || 0.633
 
−
|-
 
−
| NTO 84 || Mackinawite || 4.28 || 0.25 ||  ||  ||  || 7.6 || NaHCO<sub>3</sub> || 95.2 + 20% CO<sub>2</sub>(g) || 1000 || 0.521 || 0.491
 
−
|-
 
−
| NTO 84 || Commercial FeS || 5.00 || 0.214 ||  ||  ||  || 6.5 || NaHCO<sub>3</sub> || 8.5 + 20% CO<sub>2</sub>(g) || 1000 || 0.492 || 0.462
 
−
|-
 
−
| NTO 84 || Commercial FeS || 5.00 || 0.214 ||  ||  ||  || 7.6 || NaHCO<sub>3</sub> || 95.2 + 20% CO<sub>2</sub>(g) || 1000 || 0.427 || 0.398
 
−
|-
 
−
| colspan="13" style="text-align:left; background-color:white;" | Notes:</br>''<sup>a</sup>'' Dithionite-reduced hematite; experiments conducted in the presence of 1 mM sulfite. ''<sup>b</sup>'' Initial aqueous Fe(II); not added for Fe(II) bearing minerals. ''<sup>c</sup>'' Aqueous Fe(II) after 24h of equilibration. ''<sup>d</sup>'' Difference between b and c. ''<sup>e</sup>'' Initial nominal MC concentration. ''<sup>f</sup>'' Pseudo-first order rate constant. ''<sup>g</sup>'' Surface area normalized rate constant calculated as ''k<sub>Obs</sub>'' '''/''' (surface area concentration) or ''k<sub>Obs</sub>'' '''/''' (surface area × mineral loading).
 
−
|}
 
−
{| class="wikitable mw-collapsible" style="float:right; margin-left:40px; text-align:center;"
 
−
|+ Table&nbsp;4.&nbsp;Rate constants for the reduction of NACs by iron oxides in the presence of aqueous Fe(II)
 
−
|-
 
−
! NAC ''<sup>a</sup>''
 
−
! Iron Oxide
 
−
! Iron oxide loading</br>(g/L)
 
−
! Surface area</br>(m<sup>2</sup>/g)
 
−
! Fe(II)<sub>aq</sub> initial</br>(mM) ''<sup>b</sup>''
 
−
! Fe(II)<sub>aq</sub> after 24 h</br>(mM) ''<sup>c</sup>''
 
−
! Fe(II)<sub>aq</sub> sorbed</br>(mM) ''<sup>d</sup>''
 
−
! pH
 
−
! Buffer
 
−
! Buffer</br>(mM)
 
−
! NAC initial</br>(μM) ''<sup>e</sup>''
 
−
! log ''k<sub>obs</sub>''</br>(h<sup>-1</sup>) ''<sup>f</sup>''
 
−
! log ''k<sub>SA</sub>''</br>(Lh<sup>-1</sup>m<sup>-2</sup>) ''<sup>g</sup>''
 
−
|-
 
−
| NB 11 || Magnetite || 0.200 || 56.00 || 1.5000 ||  ||  || 7.00 || Phosphate || 10 || 50 || 1.05E+00 || 7.75E-04
 
−
|-
 
−
| 4-ClNB 11 || Magnetite || 0.200 || 56.00 || 1.5000 ||  ||  || 7.00 || Phosphate || 10 || 50 || 1.14E+00 || 8.69E-02
 
−
|-
 
−
| 4-ClNB 29 || Goethite || 0.640 || 17.50 || 1.5000 ||  ||  || 7.00 || MOPS || 25 || 50 || -1.01E-01 || -1.15E+00
 
−
|-
 
−
| 4-ClNB 13 || Goethite || 1.500 || 16.20 || 1.2400 || 0.9600 || 0.2800 || 7.20 || MOPS || 1.2 || 0.5 - 3 || 1.68E+00 || 2.80E-01
 
−
|-
 
−
| 4-ClNB 13 || Hematite || 1.800 || 13.70 || 1.0400 || 1.0100 || 0.0300 || 7.20 || MOPS || 1.2 || 0.5 - 3 || -2.32E+00 || -3.72E+00
 
−
|-
 
−
| 4-ClNB 13 || Lepidocrocite || 1.400 || 17.60 || 1.1400 || 1.0000 || 0.1400 || 7.20 || MOPS || 1.2 || 0.5 - 3 || 1.51E+00 || 1.20E-01
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3500 || 0.0300 || 7.97 || HEPES || 25 || 15 || -7.47E-01 || -8.61E-01
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3700 || 0.0079 || 7.67 || HEPES || 25 || 15 || -1.51E+00 || -1.62E+00
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3600 || 0.0200 || 7.50 || MOPS || 25 || 15 || -2.15E+00 || -2.26E+00
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3600 || 0.0120 || 7.28 || MOPS || 25 || 15 || -3.08E+00 || -3.19E+00
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3700 || 0.0004 || 7.00 || MOPS || 25 || 15 || -3.22E+00 || -3.34E+00
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3700 || 0.0024 || 6.80 || MOPSO || 25 || 15 || -3.72E+00 || -3.83E+00
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 0.004 || 292.00 || 0.3750 || 0.3700 || 0.0031 || 6.60 || MES || 25 || 15 || -3.83E+00 || -3.94E+00
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 0.020 || 292.00 || 0.3750 || 0.3700 || 0.0031 || 6.60 || MES || 25 || 15 || -3.83E+00 || -4.60E+00
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 0.110 || 292.00 || 0.3750 || 0.3700 || 0.0032 || 6.60 || MES || 25 || 15 || -1.57E+00 || -3.08E+00
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 0.220 || 292.00 || 0.3750 || 0.3700 || 0.0040 || 6.60 || MES || 25 || 15 || -1.12E+00 || -2.93E+00
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 0.551 || 292.00 || 0.3750 || 0.3700 || 0.0092 || 6.60 || MES || 25 || 15 || -6.18E-01 || -2.82E+00
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 1.099 || 292.00 || 0.3750 || 0.3500 || 0.0240 || 6.60 || MES || 25 || 15 || -3.66E-01 || -2.87E+00
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 1.651 || 292.00 || 0.3750 || 0.3400 || 0.0340 || 6.60 || MES || 25 || 15 || -8.35E-02 || -2.77E+00
 
−
|-
 
−
| 4-CNNB 6 || Ferrihydrite || 2.199 || 292.00 || 0.3750 || 0.3300 || 0.0430 || 6.60 || MES || 25 || 15 || -3.11E-02 || -2.84E+00
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.038 || 34.00 || 0.3750 || 0.3320 || 0.0430 || 7.97 || HEPES || 25 || 15 || 1.63E+00 || 1.52E+00
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.038 || 34.00 || 0.3750 || 0.3480 || 0.0270 || 7.67 || HEPES || 25 || 15 || 1.26E+00 || 1.15E+00
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.038 || 34.00 || 0.3750 || 0.3470 || 0.0280 || 7.50 || MOPS || 25 || 15 || 7.23E-01 || 6.10E-01
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.038 || 34.00 || 0.3750 || 0.3680 || 0.0066 || 7.28 || MOPS || 25 || 15 || 4.53E-02 || -6.86E-02
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.038 || 34.00 || 0.3750 || 0.3710 || 0.0043 || 7.00 || MOPS || 25 || 15 || -3.12E-01 || -4.26E-01
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.038 || 34.00 || 0.3750 || 0.3710 || 0.0042 || 6.80 || MOPSO || 25 || 15 || -7.75E-01 || -8.89E-01
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.038 || 34.00 || 0.3750 || 0.3680 || 0.0069 || 6.60 || MES || 25 || 15 || -1.39E+00 || -1.50E+00
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.038 || 34.00 || 0.3750 || 0.3750 || 0.0003 || 6.10 || MES || 25 || 15 || -2.77E+00 || -2.88E+00
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.016 || 34.00 || 0.3750 || 0.3730 || 0.0024 || 6.60 || MES || 25 || 15 || -3.20E+00 || -2.95E+00
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.024 || 34.00 || 0.3750 || 0.3690 || 0.0064 || 6.60 || MES || 25 || 15 || -2.74E+00 || -2.66E+00
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.033 || 34.00 || 0.3750 || 0.3680 || 0.0069 || 6.60 || MES || 25 || 15 || -1.39E+00 || -1.43E+00
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.177 || 34.00 || 0.3750 || 0.3640 || 0.0110 || 6.60 || MES || 25 || 15 || 3.58E-01 || -4.22E-01
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.353 || 34.00 || 0.3750 || 0.3630 || 0.0120 || 6.60 || MES || 25 || 15 || 9.97E-01|| -8.27E-02
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 0.885 || 34.00 || 0.3750 || 0.3480 || 0.0270 || 6.60 || MES || 25 || 15 || 1.34E+00 || -1.34E-01
 
−
|-
 
−
| 4-CNNB 6 || Hematite || 1.771 || 34.00 || 0.3750 || 0.3380 || 0.0370 || 6.60 || MES || 25 || 15 || 1.78E+00 || 3.59E-03
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3460 || 0.0290 || 7.97 || HEPES || 25 || 15 || 1.31E+00 || 1.20E+00
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3610 || 0.0140 || 7.67 || HEPES || 25 || 15 || 5.82E-01 || 4.68E-01
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3480 || 0.0270 || 7.50 || MOPS || 25 || 15 || 4.92E-02 || -6.47E-02
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3640 || 0.0110 || 7.28 || MOPS || 25 || 15 || 1.62E+00 || -4.90E-01
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3640 || 0.0110 || 7.00 || MOPS || 25 || 15 || -1.25E+00 || -1.36E+00
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3620 || 0.0130 || 6.80 || MOPSO || 25 || 15 || -1.74E+00 || -1.86E+00
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3740 || 0.0015 || 6.60 || MES || 25 || 15 || -2.58E+00 || -2.69E+00
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 0.027 || 49.00 || 0.3750 || 0.3700 || 0.0046 || 6.10 || MES || 25 || 15 || -3.80E+00 || -3.92E+00
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 0.020 || 49.00 || 0.3750 || 0.3740 || 0.0014 || 6.60 || MES || 25 || 15 || -2.58E+00 || -2.57E+00
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 11.980 || 49.00 || 0.3750 || 0.3620 || 0.0130 || 6.60 || MES || 25 || 15 || -5.78E-01 || -3.35E+00
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 0.239 || 49.00 || 0.3750 || 0.3530 || 0.0220 || 6.60 || MES || 25 || 15 || -2.78E-02 || -1.10E+00
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 0.600 || 49.00 || 0.3750 || 0.3190 || 0.0560 || 6.60 || MES || 25 || 15 || 3.75E-01 || -1.09E+00
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 1.198 || 49.00 || 0.3750 || 0.2700 || 0.1050 || 6.60 || MES || 25 || 15 || 5.05E-01 || -1.26E+00
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 1.798 || 49.00 || 0.3750 || 0.2230 || 0.1520 || 6.60 || MES || 25 || 15 || 5.56E-01 || -1.39E+00
 
−
|-
 
−
| 4-CNNB 6 || Lepidocrocite || 2.388 || 49.00 || 0.3750 || 0.1820 || 0.1930 || 6.60 || MES || 25 || 15 || 5.28E-01 || -1.54E+00
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.025 || 51.00 || 0.3750 || 0.3440 || 0.0310 || 7.97 || HEPES || 25 || 15 || 9.21E-01 || 8.07E-01
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.025 || 51.00 || 0.3750 || 0.3660 || 0.0094 || 7.67 || HEPES || 25 || 15 || 3.05E-01 || 1.91E-01
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.025 || 51.00 || 0.3750 || 0.3570 || 0.0180 || 7.50 || MOPS || 25 || 15 || -9.96E-02 || -2.14E-01
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.025 || 51.00 || 0.3750 || 0.3640 || 0.0110 || 7.28 || MOPS || 25 || 15 || -8.18E-01 || -9.32E-01
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.025 || 51.00 || 0.3750 || 0.3670 || 0.0084 || 7.00 || MOPS || 25 || 15 || -1.61E+00 || -1.73E+00
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.025 || 51.00 || 0.3750 || 0.3750 || 0.0004 || 6.80 || MOPSO || 25 || 15 || -1.82E+00 || -1.93E+00
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.025 || 51.00 || 0.3750 || 0.3730 || 0.0018 || 6.60 || MES || 25 || 15 || -2.26E+00 || -2.37E+00
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.025 || 51.00 || 0.3750 || 0.3670 || 0.0076 || 6.10 || MES || 25 || 15 || -3.56E+00 || -3.67E+00
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.020 || 51.00 || 0.3750 || 0.3680 || 0.0069 || 6.60 || MES || 25 || 15 || -2.26E+00 || -2.27E+00
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.110 || 51.00 || 0.3750 || 0.3660 || 0.0090 || 6.60 || MES || 25 || 15 || -3.19E-01 || -1.07E+00
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.220 || 51.00 || 0.3750 || 0.3540 || 0.0210 || 6.60 || MES || 25 || 15 || 5.00E-01 || -5.50E-01
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.551 || 51.00 || 0.3750 || 0.3220 || 0.0530 || 6.60 || MES || 25 || 15 || 1.03E+00 || -4.15E-01
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 1.100 || 51.00 || 0.3750 || 0.2740 || 0.1010 || 6.60 || MES || 25 || 15 || 1.46E+00 || -2.88E-01
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 1.651 || 51.00 || 0.3750 || 0.2330 || 0.1420 || 6.60 || MES || 25 || 15 || 1.66E+00 || -2.70E-01
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 2.196 || 51.00 || 0.3750 || 0.1910 || 0.1840 || 6.60 || MES || 25 || 15 || 1.83E+00 || -2.19E-01
 
−
|-
 
−
| 4-CNNB 6 || Goethite || 0.142 || 51.00 || 0.3750 ||  ||  || 6.60 || MES || 25 || 15 || 1.99E-01 || -6.61E-01
 
−
|-
 
−
| 4-AcNB 6 || Goethite || 0.142 || 51.00 || 0.3750 ||  ||  || 6.60 || MES || 25 || 15 || -6.85E-02 || -9.28E-01
 
−
|-
 
−
| 4-ClNB 6 || Goethite || 0.142 || 51.00 || 0.3750 ||  ||  || 6.60 || MES || 25 || 15 || -5.47E-01 || -1.41E+00
 
−
|-
 
−
| 4-BrNB 6 || Goethite || 0.142 || 51.00 || 0.3750 ||  ||  || 6.60 || MES || 25 || 15 || -5.73E-01 || -1.43E+00
 
−
|-
 
−
| NB 6 || Goethite || 0.142 || 51.00 || 0.3750 ||  ||  || 6.60 || MES || 25 || 15 || -7.93E-01 || -1.65E+00
 
−
|-
 
−
| 4-MeNB 6 || Goethite || 0.142 || 51.00 || 0.3750 ||  ||  || 6.60 || MES || 25 || 15 || -9.79E-01 || -1.84E+00
 
−
|-
 
−
| 4-ClNB 10 || Goethite || 0.040 || 186.75 || 1.0000 || 0.8050 || 0.1950 || 7.00 ||  ||  ||  || 1.05E+00 || -3.20E-01
 
−
|-
 
−
| 4-ClNB 10 || Goethite || 7.516 || 16.10 || 1.0000 || 0.9260 || 0.0740 || 7.00 ||  ||  ||  || 1.14E+00 || 0.00E+00
 
−
|-
 
−
| 4-ClNB 10 || Ferrihydrite || 0.111 || 252.60 || 1.0000 || 0.6650 || 0.3350 || 7.00 ||  ||  ||  || 1.05E+00 || -1.56E+00
 
−
|-
 
−
| 4-ClNB 10 || Lepidocrocite || 2.384 || 60.40 || 1.0000 || 0.9250 || 0.0750 || 7.00 ||  ||  ||  || 1.14E+00 || -8.60E-01
 
−
|-
 
−
| 4-ClNB 9 || Goethite || 10.000 || 14.90 || 1.0000 ||  ||  || 7.20 || HEPES || 10 || 10 - 50 || 2.26E+00 || 8.00E-02
 
−
|-
 
−
| 4-ClNB 9 || Goethite || 3.000 || 14.90 || 1.0000 ||  ||  || 7.20 || HEPES || 10 || 10 - 50 || 2.38E+00 || 7.30E-01
 
−
|-
 
−
| 4-ClNB 9 || Lepidocrocite || 2.700 || 16.20 || 1.0000 ||  ||  || 7.20 || HEPES || 10 || 10 - 50 || 9.20E-01 || -7.20E-01
 
−
|-
 
−
| 4-ClNB 9 || Lepidocrocite || 10.000 || 16.20 || 1.0000 ||  ||  || 7.20 || HEPES || 10 || 10 - 50 || 1.03E+00 || -1.18E+00
 
−
|-
 
−
| 4-ClNB 12 || Goethite || 0.325 || 140.00 || 1.0000 ||  ||  || 7.00 || Bicarbonate || 10 || 100 || 1.14E+00 || -1.79E+00
 
−
|-
 
−
| 4-ClNB 12 || Goethite || 0.325 || 140.00 || 1.0000 ||  ||  || 6.50 || Bicarbonate || 10 || 100 || 1.11E+00 || -2.10E+00
 
−
|-
 
−
| NB 15 || Goethite || 0.500 || 30.70 || 0.1000 || 0.1120 || 0.0090 || 6.00 || MES || 25 || 12 || -1.42E+00 || -2.61E+00
 
−
|-
 
−
| NB 15 || Goethite || 0.500 || 30.70 || 0.5000 || 0.5150 || 0.0240 || 6.00 || MES || 25 || 15 || -7.45E-01 || -1.93E+00
 
−
|-
 
−
| NB 15 || Goethite || 0.500 || 30.70 || 1.0000 || 1.0280 || 0.0140 || 6.00 || MES || 25 || 19 || -7.45E-01 || -1.93E+00
 
−
|-
 
−
| NB 15 || Goethite || 1.000 || 30.70 || 0.1000 || 0.0960 || 0.0260 || 6.00 || MES || 25 || 13 || -1.12E+00 || -2.61E+00
 
−
|-
 
−
| NB 15 || Goethite || 1.000 || 30.70 || 0.5000 || 0.4890 || 0.0230 || 6.00 || MES || 25 || 14 || -5.53E-01 || -2.04E+00
 
−
|-
 
−
| NB 15 || Goethite || 1.000 || 30.70 || 1.0000 || 0.9870 || 0.0380 || 6.00 || MES || 25 || 19 || -2.52E-01 || -1.74E+00
 
−
|-
 
−
| NB 15 || Goethite || 2.000 || 30.70 || 0.1000 || 0.0800 || 0.0490 || 6.00 || MES || 25 || 11 || -8.86E-01 || -2.67E+00
 
−
|-
 
−
| NB 15 || Goethite || 2.000 || 30.70 || 0.6000 || 0.4890 || 0.0640 || 6.00 || MES || 25 || 14 || -1.08E-01 || -1.90E+00
 
−
|-
 
−
| NB 15 || Goethite || 2.000 || 30.70 || 1.1000 || 0.9870 || 0.0670 || 6.00 || MES || 25 || 14 || 2.30E-01 || -1.56E+00
 
−
|-
 
−
| NB 15 || Goethite || 4.000 || 30.70 || 0.1000 || 0.0600 || 0.0650 || 6.00 || MES || 25 || 11 || -8.89E-01 || -2.98E+00
 
−
|-
 
−
| NB 15 || Goethite || 4.000 || 30.70 || 0.6000 || 0.3960 || 0.1550 || 6.00 || MES || 25 || 17 || 1.43E-01 || -1.95E+00
 
−
|-
 
−
| NB 15 || Goethite || 4.000 || 30.70 || 1.0000 || 0.8360 || 0.1450 || 6.00 || MES || 25 || 16 || 4.80E-01 || -1.61E+00
 
−
|-
 
−
| NB 15 || Goethite || 4.000 || 30.70 || 5.6000 || 5.2110 || 0.3790 || 6.00 || MES || 25 || 15 || 1.17E+00 || -9.19E-01
 
−
|-
 
−
| NB 15 || Goethite || 1.000 || 30.70 || 0.1000 || 0.0870 || 0.0300 || 6.50 || MES || 25 || 5.5 || -1.74E-01 || -1.66E+00
 
−
|-
 
−
| NB 15 || Goethite || 1.000 || 30.70 || 0.5000 || 0.4920 || 0.0300 || 6.50 || MES || 25 || 15 || 3.64E-01 || -1.12E+00
 
−
|-
 
−
| NB 15 || Goethite || 1.000 || 30.70 || 1.0000 || 0.9390 || 0.0650 || 6.50 || MES || 25 || 18 || 6.70E-01 || -8.17E-01
 
−
|-
 
−
| NB 15 || Goethite || 2.000 || 30.70 || 0.1000 || 0.0490 || 0.0730 || 6.50 || MES || 25 || 5.2 || 3.01E-01 || -1.49E+00
 
−
|-
 
−
| NB 15 || Goethite || 2.000 || 30.70 || 0.5000 || 0.4640 || 0.0710 || 6.50 || MES || 25 || 14 || 8.85E-01 || -9.03E-01
 
−
|-
 
−
| NB 15 || Goethite || 2.000 || 30.70 || 1.0000 || 0.9130 || 0.1280 || 6.50 || MES || 25 || 16 || 1.12E+00 || -6.64E-01
 
−
|-
 
−
| NB 15 || Goethite || 1.000 || 30.70 || 0.1000 || 0.0630 || 0.0480 || 7.00 || MOPS || 25 || 5.3 || 6.12E-01 || -8.75E-01
 
−
|-
 
−
| NB 15 || Goethite || 1.000 || 30.70 || 0.5000 || 0.4690 || 0.0520 || 7.00 || MOPS || 25 || 9 || 1.51E+00 || 2.07E-02
 
−
|-
 
−
| NB 15 || Goethite || 1.000 || 30.70 || 1.0000 || 0.9360 || 0.1090 || 7.00 || MOPS || 25 || 18 || 1.33E+00 || -1.53E-01
 
−
|-
 
−
| NB 15 || Goethite || 2.000 || 30.70 || 0.1000 || 0.0290 || 0.0880 || 7.00 || MOPS || 25 || 12 || 6.85E-01 || -1.10E+00
 
−
|-
 
−
| NB 15 || Goethite || 2.000 || 30.70 || 0.5000 || 0.3950 || 0.1450 || 7.00 || MOPS || 25 || 15 || 1.59E+00 || -1.95E-01
 
−
|-
 
−
| colspan="13" style="text-align:left; background-color:white;" | Notes:</br>''<sup>a</sup>'' The NACs are Nitrobenzene (NB), 4-chloronitrobenzene(4-ClNB), 4-cyanonitrobenzene (4-CNNB), 4-acetylnitrobenzene (4-AcNB), 4-bromonitrobenzene (4-BrNB), 4-nitrotoluene (4-MeNB). ''<sup>b</sup>'' Initial aqueous Fe(II). ''<sup>c</sup>'' Aqueous Fe(II) after 24h of equilibration. ''<sup>d</sup>'' Difference between b and c. ''<sup>e</sup>'' Initial nominal NAC concentration. ''<sup>f</sup>'' Pseudo-first order rate constant. ''<sup>g</sup>'' Surface area normalized rate constant calculated as ''k<sub>Obs</sub>'' '''/''' (surface area × mineral loading).
 
−
|}
 
  
−
Iron(II)&nbsp;can&nbsp;be&nbsp;complexed by a myriad of organic ligands and may thereby become more reactive towards MCs and other pollutants. The reactivity of an Fe(II)-organic complex depends on the relative preference of the organic ligand for Fe(III) versus Fe(II)<ref name="Kim2009"/>. Since the majority of naturally occurring ligands complex Fe(III) more strongly than Fe(II), the reduction potential of the resulting Fe(III) complex is lower than that of aqueous Fe(III); therefore, complexation by organic ligands often renders Fe(II) a stronger reductant thermodynamically<ref name="Strathmann2011">Strathmann, T.J., 2011. Redox Reactivity of Organically Complexed Iron(II) Species with Aquatic Contaminants. Aquatic Redox Chemistry, American Chemical Society,1071(14), pp. 283-313. [https://doi.org/10.1021/bk-2011-1071.ch014 DOI: 10.1021/bk-2011-1071.ch014]</ref>. The reactivity of dissolved Fe(II)-organic complexes towards NACs/MCs has been investigated. The intrinsic, second-order rate constants and one electron reduction potentials are listed in Table 2.
+
==LEAF Screening Evaluations==
 +
[[File: GuelfoFig4.png | thumb | 500 px | Figure 4. Example screening assessment for perfluorooctane sulfonate (PFOS) using total content and data from Methods 1313A and 1314A.  Figure format adapted from Garrabrants ''et al''. 2021<ref>Garrabrants, A.C., Kosson, D.S., Brown, K.G., Fagnant, D.P., Helms, G., Thorneloe, S.A., 2021. Methodology for Scenario-Based Assessments and Demonstration of Treatment Effectiveness Using the Leaching Environmental Assessment Framework (LEAF). Journal of Hazardous Materials, 406, Article 124635. [https://doi.org/10.1016/j.jhazmat.2020.124635 doi: 10.1016/j.jhazmat.2020.124635]&nbsp; [[Media: GarrabrantsEtAl2021.pdf | Open Access Manuscript]]</ref>.]]
 +
LEAF provides a standardized, robust approach for evaluating PFAS release from impacted granular materials under a range of environmental conditions. The tests are complementary, capture a range of conditions, and vary in ease of implementation. This provides the flexibility for users to select the test or test combinations that best suit their project objectives, timeline, and budget. A common use of LEAF data is in screening level assessments.  These are stepwise assessments that establish increasingly refined maximum leaching concentrations, ''C<sub><small>leach,max</small></sub>'' (Figure 4), which can then be compared to regulatory limits such as maximum contaminant levels, when available. For example, a stepwise screening assessment might include:
 +
#Assume the maximum leaching concentration is represented by the total content (total initial mass of contaminant present) leaching into the first L/S.
 +
#Assume only the available content leaches into the first L/S where available content is the maximum mass released over pH 2-13 measured using Method 1313a. For many PFAS, total content is equal to available content meaning that all of the PFAS mass is available for leaching.
 +
#Assume the leaching concentration at natural pH (measured in Method 1313A at natural pH or Method 1316A at L/S of 10) is maximum leaching concentration adjusted to the first L/S.
 +
#Consider the maximum leaching concentration over the L/S range (Method 1314A or Method 1316A) and the upper estimate of leaching, or ''C<sub><small>leach,max</small></sub>'', is the concentration from either Step 3 or Step 4, whichever is greater.
  
−
In addition to forming organic complexes, iron is ubiquitous in minerals. Iron-bearing minerals play an important role in controlling the environmental fate of contaminants through adsorption<ref name="Linker2015">Linker, B.R., Khatiwada, R., Perdrial, N., Abrell, L., Sierra-Alvarez, R., Field, J.A., and Chorover, J., 2015. Adsorption of novel insensitive munitions compounds at clay mineral and metal oxide surfaces. Environmental Chemistry, 12(1), pp. 74–84.  [https://doi.org/10.1071/EN14065 DOI: 10.1071/EN14065]</ref><ref name="Jenness2020">Jenness, G.R., Giles, S.A., and Shukla, M.K., 2020. Thermodynamic Adsorption States of TNT and DNAN on Corundum and Hematite. The Journal of Physical Chemistry C, 124(25), pp. 13837–13844.  [https://doi.org/10.1021/acs.jpcc.0c04512 DOI: 10.1021/acs.jpcc.0c04512]</ref> and reduction<ref name="Gorski2011">Gorski, C.A., and Scherer, M.M., 2011. Fe<sup>2+</sup> Sorption at the Fe Oxide-Water Interface: A Revised Conceptual Framework. Aquatic Redox Chemistry, American Chemical Society, 1071(15), pp. 315–343.  [https://doi.org/10.1021/bk-2011-1071.ch015 DOI: 10.1021/bk-2011-1071.ch015]</ref> processes. Studies have shown that aqueous Fe(II) itself cannot reduce NACs/MCs at circumneutral pH<ref name="Klausen1995"/><ref name="Gregory2004">Gregory, K.B., Larese-Casanova, P., Parkin, G.F., and Scherer, M.M., 2004. Abiotic Transformation of Hexahydro-1,3,5-trinitro-1,3,5-triazine by Fe<sup>II</sup> Bound to Magnetite. Environmental Science and Technology, 38(5), pp. 1408–1414.  [https://doi.org/10.1021/es034588w DOI: 10.1021/es034588w]</ref> but in the presence of an iron oxide (e.g., goethite, hematite, lepidocrocite, ferrihydrite, or magnetite), NACs<ref name="Colón2006"/><ref name="Klausen1995"/><ref name="Strehlau2016"/><ref name="Elsner2004"/><ref name="Hofstetter2006"/> and MCs such as TNT<ref name="Hofstetter1999"/>, RDX<ref name="Gregory2004"/>, DNAN<ref name="Berens2019">Berens, M.J., Ulrich, B.A., Strehlau, J.H., Hofstetter, T.B., and Arnold, W.A., 2019. Mineral identity, natural organic matter, and repeated contaminant exposures do not affect the carbon and nitrogen isotope fractionation of 2,4-dinitroanisole during abiotic reduction. Environmental Science: Processes and Impacts, 21(1), pp. 51-62.  [https://doi.org/10.1039/C8EM00381E DOI: 10.1039/C8EM00381E]</ref>, and NG<ref name="Oh2004">Oh, S.-Y., Cha, D.K., Kim, B.J., and Chiu, P.C., 2004. Reduction of Nitroglycerin with Elemental Iron:  Pathway, Kinetics, and Mechanisms. Environmental Science and Technology, 38(13), pp. 3723–3730.  [https://doi.org/10.1021/es0354667 DOI: 10.1021/es0354667]</ref> can be rapidly reduced. Unlike ferric oxides, Fe(II)-bearing minerals including clays<ref name="Hofstetter2006"/><ref name="Schultz2000"/><ref name="Luan2015a"/><ref name="Luan2015b"/><ref name="Hofstetter2003"/><ref name="Neumann2008"/><ref name="Hofstetter2008"/>, green rust<ref name="Larese-Casanova2008"/><ref name="Khatiwada2018">Khatiwada, R., Root, R.A., Abrell, L., Sierra-Alvarez, R., Field, J.A., and Chorover, J., 2018. Abiotic reduction of insensitive munition compounds by sulfate green rust. Environmental Chemistry, 15(5), pp. 259–266.  [https://doi.org/10.1071/EN17221 DOI: 10.1071/EN17221]</ref>, mackinawite<ref name="Elsner2004"/><ref name="Berens2019"/><ref name="Menezes2021">Menezes, O., Yu, Y., Root, R.A., Gavazza, S., Chorover, J., Sierra-Alvarez, R., and Field, J.A., 2021. Iron(II) monosulfide (FeS) minerals reductively transform the insensitive munitions compounds 2,4-dinitroanisole (DNAN) and 3-nitro-1,2,4-triazol-5-one (NTO). Chemosphere, 285, p. 131409.  [https://doi.org/10.1016/j.chemosphere.2021.131409 DOI: 10.1016/j.chemosphere.2021.131409]</ref> and pyrite<ref name="Elsner2004"/><ref name="Oh2008">Oh, S.-Y., Chiu, P.C., and Cha, D.K., 2008. Reductive transformation of 2,4,6-trinitrotoluene,  hexahydro-1,3,5-trinitro-1,3,5-triazine, and nitroglycerin by pyrite and magnetite. Journal of hazardous materials, 158(2-3), pp. 652–655.  [https://doi.org/10.1016/j.jhazmat.2008.01.078 DOI: 10.1016/j.jhazmat.2008.01.078]</ref> do not need aqueous Fe(II) to be reactive toward NACs/MCs. However, upon oxidation, sulfate green rust was converted into lepidocrocite<ref name="Khatiwada2018"/>, and mackinawite into goethite<ref name="Menezes2021"/>, suggesting that aqueous Fe(II) coupled to Fe(III) oxides might be at least partially responsible for continued degradation of NACs/MCs in the subsurface once the parent reductant (e.g., green rust or iron sulfide) oxidizes.
+
Screening assessments may be sufficient to meet project goals, but when additional refinements of leaching estimates are needed, site-specific data (e.g., infiltration) can be combined with test data and computational approaches (e.g., fate and transport models) for more site-specific estimates of leaching.  Example scenarios where LEAF may be used to evaluate PFAS-impacted solids include 1) estimating PFAS release from AFFF-impacted soils, 2) estimating PFAS release from biosolids-amended soils at land application sites, 3) providing transport parameters to model PFAS transport from the source zone to the saturated zone, and 4) evaluating PFAS release from treatment residuals such as soils or sediments treated by soil washing or thermal approaches.  
  
−
The reaction conditions and rate constants for a list of studies on MC reduction by iron oxide-aqueous Fe(II)  redox couples and by other Fe(II)-containing minerals are shown in Table 3<ref name="Hofstetter1999"/><ref name="Larese-Casanova2008"/><ref name="Gregory2004"/><ref name="Berens2019"/><ref name="Oh2008"/><ref name="Strehlau2018">Strehlau, J.H., Berens, M.J., and Arnold, W.A., 2018. Mineralogy and buffer identity effects on RDX kinetics and intermediates during reaction with natural and synthetic magnetite. Chemosphere, 213, pp. 602–609.  [https://doi.org/10.1016/j.chemosphere.2018.09.139 DOI: 10.1016/j.chemosphere.2018.09.139]</ref><ref name="Cardenas-Hernandez2020">Cárdenas-Hernandez, P.A., Anderson, K.A., Murillo-Gelvez, J., di Toro, D.M., Allen, H.E., Carbonaro, R.F., and Chiu, P.C., 2020. Reduction of 3-Nitro-1,2,4-Triazol-5-One (NTO) by the Hematite–Aqueous Fe(II) Redox Couple. Environmental Science and Technology, 54(19), pp. 12191–12201.  [https://doi.org/10.1021/acs.est.0c03872 DOI: 10.1021/acs.est.0c03872]</ref>. Unlike hydroquinones and Fe(II) complexes, where second-order rate constants can be readily calculated, the reduction rate constants of NACs/MCs in mineral suspensions are often specific to the experimental conditions used and are usually reported as BET surface area-normalized reduction rate constants (''k<sub>SA</sub>''). In the case of iron oxide-Fe(II) redox couples, reduction rate constants have been shown to increase with pH (specifically, with [OH<sup>– </sup>]<sup>2</sup>) and aqueous Fe(II) concentration, both of which correspond to a decrease in the system's reduction potential<ref name="Colón2006"/><ref name="Gorski2016"/><ref name="Cardenas-Hernandez2020"/>.
+
==Summary and Ongoing Research==
 +
The LEAF framework offers a reliable, replicable approach to evaluating PFAS release from solids. With recent adaptations for PFAS-specific considerations, LEAF methods provide valuable tools for regulators and practitioners in managing PFAS-contaminated materials and assessing long-term environmental risks. However, there are key areas of ongoing research, including:
 +
*An interlab validation of Methods 1313A, 1314A, and 1316A in coordination with the EPA
 +
*Optimization and demonstration of Method 1315A for use with PFAS-impacted solids
 +
*Evaluation of an unsaturated Method 1314A protocol to assess the need for and ability of LEAF testing to capture air-water interfacial partitioning of PFAS
 +
*Application of the total oxidizable precursor (TOP) assay for evaluating the maximum additional PFAS leaching that may occur as a result of polyfluoroalkyl precursor transformation
 +
*Comparison of LEAF testing data to previously collected field-scale enhanced flushing data collected from the same site
  
−
For minerals that contain structural iron(II) and can reduce pollutants in the absence of aqueous Fe(II), the observed rates of reduction increased with increasing structural Fe(II) content, as seen with iron-bearing clays<ref name="Luan2015a"/><ref name="Luan2015b"/> and green rust<ref name="Larese-Casanova2008"/>. This dependency on Fe(II) content allows for the derivation of second-order rate constants, as shown on Table 3 for the reduction of RDX by green rust<ref name="Larese-Casanova2008"/>, and the development of reduction potential (E<sub>H</sub>)-based models<ref name="Luan2015a"/><ref name="Gorski2012a">Gorski, C.A., Aeschbacher, M., Soltermann, D., Voegelin, A., Baeyens, B., Marques Fernandes, M., Hofstetter, T.B., and Sander, M., 2012. Redox Properties of Structural Fe in Clay Minerals. 1. Electrochemical Quantification of Electron-Donating and -Accepting Capacities of Smectites. Environmental Science and Technology, 46(17), pp. 9360–9368.  [https://doi.org/10.1021/es3020138 DOI: 10.1021/es3020138]</ref><ref name="Gorski2012b">Gorski, C.A., Klüpfel, L., Voegelin, A., Sander, M., and Hofstetter, T.B., 2012. Redox Properties of Structural Fe in Clay Minerals. 2. Electrochemical and Spectroscopic Characterization of Electron Transfer Irreversibility in Ferruginous Smectite, SWa-1. Environmental Science and Technology, 46(17), pp. 9369–9377.  [https://doi.org/10.1021/es302014u DOI: 10.1021/es302014u]</ref><ref name="Gorski2013">Gorski, C.A., Klüpfel, L.E., Voegelin, A., Sander, M. and Hofstetter, T.B., 2013. Redox Properties of Structural Fe in Clay Minerals: 3. Relationships between Smectite Redox and Structural Properties. Environmental Science and Technology, 47(23), pp. 13477–13485.  [https://doi.org/10.1021/es403824x DOI: 10.1021/es403824x]</ref>, where E<sub>H</sub> represents the reduction potential of the iron-bearing clays. Iron-bearing expandable clay minerals represent a special case, which in addition to reduction can remove NACs/MCs through adsorption. This is particularly important for planar NACs/MCs that contain multiple electron-withdrawing nitro groups and can form strong electron donor-acceptor (EDA) complexes with the clay surface<ref name="Hofstetter2006"/><ref name="Hofstetter2003"/><ref name="Neumann2008"/>.
+
Additionally, there are key areas for consideration in future research:
 +
*Collection of paired field-laboratory data under ambient conditions to further validate the applicability of LEAF assessments for estimation of field-relevant PFAS leaching and mobility
 +
*Consideration of biotransformation in modeling and interpretation of LEAF data, as the state of the science regarding biotransformation of polyfluoroalkyl substances to terminal perfluoroalkyl acids advances
  
−
Although the second-order rate constants derived for Fe(II)-bearing minerals may allow comparison among different studies, they may not reflect changes in reactivity due to variations in surface area, pH, and the presence of ions. Anions such as bicarbonate<ref name="Larese-Casanova2008"/><ref name="Strehlau2018"/><ref name="Chen2020">Chen, G., Hofstetter, T.B., and Gorski, C.A., 2020. Role of Carbonate in Thermodynamic Relationships Describing Pollutant Reduction Kinetics by Iron Oxide-Bound Fe<sup>2+</sup>. Environmental Science and Technology, 54(16), pp. 10109–10117.  [https://doi.org/10.1021/acs.est.0c02959 DOI: 10.1021/acs.est.0c02959]</ref> and phosphate<ref name="Larese-Casanova2008"/><ref name="Bocher2004">Bocher, F., Géhin, A., Ruby, C., Ghanbaja, J., Abdelmoula, M., and Génin, J.M.R., 2004. Coprecipitation of Fe(II–III) hydroxycarbonate green rust stabilised by phosphate adsorption. Solid State Sciences, 6(1), pp. 117–124.  [https://doi.org/10.1016/j.solidstatesciences.2003.10.004 DOI: 10.1016/j.solidstatesciences.2003.10.004]</ref> are known to decrease the reactivity of iron oxides-Fe(II) redox couples and green rust. Sulfite has also been shown to decrease the reactivity of hematite-Fe(II) towards the deprotonated form of NTO (Table 3)<ref name="Cardenas-Hernandez2020"/>. Exchanging cations in iron-bearing clays can change the reactivity of these minerals by up to 7-fold<ref name="Hofstetter2006"/>. Thus, more comprehensive models are needed to account for the complexities in the subsurface environment.
+
==Other LEAF Resources==
 +
There are numerous  resources describing the development of the LEAF leaching methods for inorganics. They are not specific to PFAS, but are still valuable resources focused on LEAF implementation, applications, and management of LEAF data. They include:
 +
*[https://www.vanderbilt.edu/leaching/leach-xs-lite/ Leach XS Lite] - a tool for LEAF data management and visualization; free to download after registering for a free license key
 +
*[https://www.epa.gov/hw-sw846/how-guide-leaching-environmental-assessment-framework LEAF “How-To” Guide] - guidance on LEAF background, implementation, test result interpretation; includes case studies
 +
*[https://www.epa.gov/hw-sw846/leaching-environmental-assessment-framework-leaf-methods-and-guidance USEPA LEAF Methods and Guidance] homepage
 +
<br clear="right"/>
  
−
The reduction of NACs has been widely studied in the presence of different iron minerals, pH, and Fe(II)<sub>(aq)</sub> concentrations (Table 4)<ref name="Colón2006"/><ref name="Klausen1995"/><ref name="Strehlau2016"/><ref name="Elsner2004"/><ref name="Hofstetter2006"/>. Only selected NACs are included in Table 4. For more information on other NACs and ferruginous reductants, please refer to the cited references.
 
−
<br clear="right" />
 
 
==References==
 
==References==
 
<references />
 
<references />
  
 
==See Also==
 
==See Also==
−
[https://www.serdp-estcp.org/Program-Areas/Environmental-Restoration/Contaminated-Groundwater/Persistent-Contamination/ER-2617 Measuring and Predicting the Natural and Enhanced Rate and Capacity of Abiotic Reduction of Munition Constituents]
 
−
[https://www.epa.gov/fedfac/military-munitionsunexploded-ordnance Military Munitions/Unexploded Ordnance - EPA]
 

Latest revision as of 18:39, 13 August 2026

PFAS Leaching Characterization with the Leaching Environmental Assessment Framework (LEAF)

Aqueous film-forming foams (AFFFs) are a major source of per- and poly-fluoroalkyl substances (PFAS) impacts in soil and groundwater. Standardized tools are needed to rapidly assess the potential for retention, leaching, and transport of PFAS from the source zone to downgradient regions, so that this information can be applied towards critical facets of site management such as prioritizing PFAS-impacted sites for further investigation and remediation. Existing standard leaching methods were developed prior to concerns regarding PFAS. Therefore, studies are needed to ensure that leaching methods are compatible for use with PFAS and that resulting data are representative of the risk of PFAS leaching at impacted sites.

Related Article(s):

Contributors: Dr. Jennifer L. Guelfo, Dr. David Kosson, Dr. Andy Garrabrants, Ms. Fangfei Liu, Mr. Darlington Yawson, Dr. Md. Isreq Real

Key Resources:

  • Development of Leaching Tests for Materials Containing SVOCs and PFAS, EPA 600/R-23/382[1]

Introduction to LEAF

The U.S. Environmental Protection Agency (EPA) Leaching Environmental Assessment Framework (LEAF) is a suite of standardized test methods for evaluating contaminant release from solids under environmentally relevant conditions (Table 1). The four leaching methods within LEAF were originally validated for inorganic constituents[2][3] and included as standard leaching methods EPA 1313 – 1316 within Update V of SW-846[4]. To address the need for standardized tests to evaluate PFAS leaching and mobility, LEAF methods have been optimized and demonstrated for use with PFAS (Methods 1313A-1316A)[1]. This article will focus on Methods 1313A, 1314A, and 1316A. Demonstration of Method 1315A for compacted granular materials (including concrete and asphalt) is ongoing.

Table 1. EPA SW-846 methods that comprise the LEAF framework
Method Description
1313 Liquid-solid partitioning as a function of extract pH using a parallel batch extraction (i.e., equilibrium) procedure (Figure 1)
1314 Liquid-solid partitioning as a function of liquid-solid ratio (L/S) for constituents in solid materials using an up-flow percolation column procedure (Figure 3)
1315 Mass transfer rates of constituents in monolithic or compacted granular materials using a semi-dynamic tank leaching procedure
1316 Liquid-solid partitioning as a function of L/S using a parallel batch extraction (i.e., equilibrium) procedure (Figure 2)
Note: Text shown in bold indicates primary condition evaluated in each method.

Method Development for PFAS

Complete details of the development of LEAF Methods 1313A, 1314A, and 1316A for use with PFAS are available in Garrabrants et al., 2024[1]. Representative method modifications include:

  • Materials of construction for experimental apparatus: containers used for leaching vessels (Methods 1313A, 1316A) and column construction materials (Method 1314A) evaluated for background PFAS and PFAS uptake.
  • Reagents and eluant composition: eluant composition was optimized to use 1 mM CaCl2 to reduce formation of colloidal matter; Method 1313A pH adjustment now conducted with nonoxidizing HCl.
  • Experimental conditions: Longer equilibration times (e.g., Method 1313, 1316) may be required due to slow desorption kinetics of certain PFAS from soil and organic matrices, implementation of settling to facilitate separation of solids from eluates.
  • Eluate processing (all methods): Use of centrifugation in lieu of eluate filtering, sonication of bottle prior to eluate subsampling.

Batch Test Demonstration Studies

PFAS-specific adaptations were tested in batch test demonstration studies, which included triplicate implementation of Methods 1313A and 1316A in four AFFF-impacted site soils.

Figure 1: Figure 1. a) Overview of LEAF Method 1313A and b) PFHxS leaching as a function of pH[1]. Definitions: lower limit of quantification (LLOQ) and method detection limit (MDL)

Draft Method 1313A was used to evaluate pH-dependent leaching in PFAS-contaminated soils in parallel batch extractions where each set of batch reactors is prepared and equilibrated at different pH (Figure 1). Short-chain PFAS (≤6 fluorinated carbons) generally showed little to no variation in leaching across the tested pH range of 2-13 (e.g., PFHxS, Figure 1), whereas long-chain PFAS exhibited increased leaching at higher pH[1]. This trend is consistent with previous findings showing that soil-water partitioning coefficients (Kd) decrease as pH increases (e.g., Higgins and Luthy 2006)[5]. The most pronounced pH effects were observed for perfluoroalkyl sulfonamides (FASAs) such as perfluorooctane sulfonamide (FOSA), which transition from neutral to anionic forms within the circumneutral pH range (~pH 6). The anionic form has a lower Kd and results in higher leaching concentrations[1][6]. For many site management scenarios where pH is circumneutral, variations in anionic PFAS leaching are expected to be small over the relevant pH range. In such cases, when testing time and costs are primary considerations, Method 1313A may be a lower priority relative to evaluating leaching as a function of L/S (Method 1316A, Method 1314A). Different considerations may be needed where FASAs or PFAS with multiple, ionizable functional groups (i.e., zwitterions) are of concern.

Figure 2: a) Overview of LEAF Method 1316A and b) PFHxS leaching as a function of L/S ratio evaluated in parallel batch leaching vessels[1]

Draft Method 1316A was used to evaluate L/S-dependent leaching of PFAS in impacted soils using parallel batch extractions where each set of batch reactors is prepared and equilibrated at a different L/S. (Figure 2). Methods 1314A and 1316A are similar in intent as they both evaluate leaching as a function of L/S; however, the experimental approach differs. Method 1314A uses a flow-through column configuration (Figure 3; discussed further below). Method 1314A may better simulate field conditions, but Method 1316A is simpler and less costly to implement. Trends in Method 1314A and 1316A are expected to be qualitatively similar but leaching concentrations are expected to exhibit differences. Despite this, leaching studies comparing Methods 1314A and 1316A for inorganics showed that cumulative release results were within one order of magnitude[7].

Method 1316A and Method 1314A may also provide different insights into transport mechanisms. Because Method 1316A is performed using equilibrated batch reactors at varying L/S, results can be used to develop equilibrium desorption isotherms and calculate desorption coefficients (e.g., Kd,desorption). Studies have shown that Kd,desorption values for PFAS may be greater than Kd, an effect often attributed to desorption hysteresis[8]. Consequently Method 1316A provides a straightforward method to estimate site-specific desorption parameters. Although sorption parameters can also be inferred from column (Method 1314A) data, interpretation is often complicated by nonequilibrium processes. Conversely, the column data can be valuable for quantifying those additional mechanisms providing transport parameters that can describe rate-limited transport (e.g., fraction of non-equilibrium sorption sites and sorption rates) and other dynamic behavior.

As anticipated, trends in PFAS leaching obtained during the Method 1316A and Method 1314A demonstrations were qualitatively similar. These are further discussed below.

Column Test Demonstration Studies

Figure 3. a) Overview of LEAF Method 1314A and b) PFHxS leaching as a function of ∑(L/S) evaluated in saturated up-flow column tests[1]. Note that acrylic here simply refers to the column material of construction used in this round of Method 1314 testing.

PFAS-specific adaptations were tested in column test demonstration studies, which included triplicate implementation of Method 1314A in three AFFF-impacted site soils.

Draft Method 1314A was implemented in saturated, up-flow columns to evaluate leaching of PFAS as a function of cumulative L/S (∑(L/S)); Figure 3; total volume of water that has passed through the column divided by the soil mass in the column). As noted, the intent of Method 1314a and 1316a is similar, and in both tests, similar qualitative results were observed. For example, short-chain PFAS exhibited high initial concentrations that decreased rapidly. However, in Method 1314a, these rapid drops in short-chain PFAS tended to occur by ∑(L/S) ≈ 2 (e.g., Site 1 and 3 soils, Figure 3) whereas in some cases, such as for PFHxS, Method 1316A produced slightly flatter elution curves than Method 1314A (Figures 2b and 3b). Long-chain PFAS generally displayed flatter elution profiles than short-chain PFAS across both methods. These trends are consistent with chain length dependent sorption documented in the literature[5][6][9]. Although column modeling is beyond the scope of this article, prior studies have shown that saturated transport can be influenced by rate-limited desorption, particularly for long-chain PFAS[10][11]. As noted, data from Methods 1316A and 1314A can support estimation of transport parameters representing equilibrium and nonequilibrium behavior, respectively.

LEAF Screening Evaluations

Figure 4. Example screening assessment for perfluorooctane sulfonate (PFOS) using total content and data from Methods 1313A and 1314A. Figure format adapted from Garrabrants et al. 2021[12].

LEAF provides a standardized, robust approach for evaluating PFAS release from impacted granular materials under a range of environmental conditions. The tests are complementary, capture a range of conditions, and vary in ease of implementation. This provides the flexibility for users to select the test or test combinations that best suit their project objectives, timeline, and budget. A common use of LEAF data is in screening level assessments. These are stepwise assessments that establish increasingly refined maximum leaching concentrations, Cleach,max (Figure 4), which can then be compared to regulatory limits such as maximum contaminant levels, when available. For example, a stepwise screening assessment might include:

  1. Assume the maximum leaching concentration is represented by the total content (total initial mass of contaminant present) leaching into the first L/S.
  2. Assume only the available content leaches into the first L/S where available content is the maximum mass released over pH 2-13 measured using Method 1313a. For many PFAS, total content is equal to available content meaning that all of the PFAS mass is available for leaching.
  3. Assume the leaching concentration at natural pH (measured in Method 1313A at natural pH or Method 1316A at L/S of 10) is maximum leaching concentration adjusted to the first L/S.
  4. Consider the maximum leaching concentration over the L/S range (Method 1314A or Method 1316A) and the upper estimate of leaching, or Cleach,max, is the concentration from either Step 3 or Step 4, whichever is greater.

Screening assessments may be sufficient to meet project goals, but when additional refinements of leaching estimates are needed, site-specific data (e.g., infiltration) can be combined with test data and computational approaches (e.g., fate and transport models) for more site-specific estimates of leaching. Example scenarios where LEAF may be used to evaluate PFAS-impacted solids include 1) estimating PFAS release from AFFF-impacted soils, 2) estimating PFAS release from biosolids-amended soils at land application sites, 3) providing transport parameters to model PFAS transport from the source zone to the saturated zone, and 4) evaluating PFAS release from treatment residuals such as soils or sediments treated by soil washing or thermal approaches.

Summary and Ongoing Research

The LEAF framework offers a reliable, replicable approach to evaluating PFAS release from solids. With recent adaptations for PFAS-specific considerations, LEAF methods provide valuable tools for regulators and practitioners in managing PFAS-contaminated materials and assessing long-term environmental risks. However, there are key areas of ongoing research, including:

  • An interlab validation of Methods 1313A, 1314A, and 1316A in coordination with the EPA
  • Optimization and demonstration of Method 1315A for use with PFAS-impacted solids
  • Evaluation of an unsaturated Method 1314A protocol to assess the need for and ability of LEAF testing to capture air-water interfacial partitioning of PFAS
  • Application of the total oxidizable precursor (TOP) assay for evaluating the maximum additional PFAS leaching that may occur as a result of polyfluoroalkyl precursor transformation
  • Comparison of LEAF testing data to previously collected field-scale enhanced flushing data collected from the same site

Additionally, there are key areas for consideration in future research:

  • Collection of paired field-laboratory data under ambient conditions to further validate the applicability of LEAF assessments for estimation of field-relevant PFAS leaching and mobility
  • Consideration of biotransformation in modeling and interpretation of LEAF data, as the state of the science regarding biotransformation of polyfluoroalkyl substances to terminal perfluoroalkyl acids advances

Other LEAF Resources

There are numerous resources describing the development of the LEAF leaching methods for inorganics. They are not specific to PFAS, but are still valuable resources focused on LEAF implementation, applications, and management of LEAF data. They include:


References

  1. ^ 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 Garrabrants, A.C., Liu, F., Warne, R., DeLapp, R., Brown, L., Rubin, Z., Yawson, D., Kosson, D.S., Guelfo, J.L., Real, M.I., van der Sloot, H.A., Touati, A., Thorneloe, S., 2024. Development of Leaching Tests for Materials Containing SVOCs and PFAS, EPA 600/R-23/382, USEPA, Washington, D.C. Free Download EPA 600/R-23/382
  2. ^ Garrabrants, A.C., Kosson, D.S., Stefanski, L., DeLapp, R., Seignette, P.F.A.B., van der Sloot, H.A., Kariher, P., Baldwin, M., 2012. Interlaboratory Validation of the Leaching Environmental Assessment Framework (LEAF) Method 1313 and Method 1316, EPA/600/R-12/623, U.S. Environmental Protection Agency, Air Pollution and Control Division. Free Download EPA 600/R-12/623
  3. ^ Garrabrants, A.C., Kosson, D.S., DeLapp, R., Kariher, P., Seignette, P.F.A.B., van der Sloot, H.A., Stefanski, L., Baldwin, M., 2012. Interlaboratory Validation of the Leaching Environmental Assessment Framework (LEAF) Method 1314 and Method 1315, EPA/600/R-12/624, U.S. Environmental Protection Agency, Air Pollution and Control Division. Free Download EPA 600/R-12/624
  4. ^ USEPA, 2026. Hazardous Waste Test Methods / SW-846. USEPA SW-846 website
  5. ^ 5.0 5.1 Higgins, C.P., Luthy, R.G., 2006. Sorption of Perfluorinated Surfactants on Sediments. Environmental Science and Technology, 40(23), pp. 7251–7256. doi: 10.1021/es061000n
  6. ^ 6.0 6.1 Nguyen, T.M.H., Bräunig, J., Thompson, K., Thompson, J., Kabiri, S., Navarro, D.A., Kookana, R.S., Grimison, C., Barnes, C.M., Higgins, C.P., McLaughlin, M.J., Mueller, J.F., 2020. Influences of Chemical Properties, Soil Properties, and Solution pH on Soil–Water Partitioning Coefficients of Per- and Polyfluoroalkyl Substances (PFASs). Environmental Science and Technology, 54(24), pp. 15883–15892. doi: 10.1021/acs.est.0c05705  Open Access Article
  7. ^ Lopez Meza, S., Garrabrants, A.C., van der Sloot, H., Kosson, D.S., 2008. Comparison of the Release of Constituents from Granular Materials under Batch and Column Testing. Waste Management, 28(10), pp. 1853–1867. doi: 10.1016/j.wasman.2007.11.009
  8. ^ Schaefer, C.E., Nguyen, D., Christie, E., Shea, S., Higgins, C.P., Field, J., 2022. Desorption Isotherms for Poly- and Perfluoroalkyl Substances in Soil Collected from an Aqueous Film-Forming Foam Source Area. Journal of Environmental Engineering, 148(1), Article 04021074. doi: 10.1061/(ASCE)EE.1943-7870.0001952
  9. ^ Guelfo, J.L., Higgins, C.P., 2013. Subsurface Transport Potential of Perfluoroalkyl Acids at Aqueous Film-Forming Foam (AFFF)-Impacted Sites. Environmental Science and Technology, 47(9), pp. 4164–4171. doi: 10.1021/es3048043
  10. ^ Doria-Manzur, A., Gray, E.P., Streets, S.S., Guelfo, J.L., 2025. Per- and Polyfluoroalkyl Substances (PFAS) Transport from Biosolids-Amended Soils: An Experimental and Numerical Approach. Water Research, 288(Part B), Article 124674. doi: 10.1016/j.watres.2025.124674  Open Access Article
  11. ^ Guelfo, J.L., Wunsch, A., McCray, J., Stults, J.F., Higgins, C.P., 2020. Subsurface Transport Potential of Perfluoroalkyl Acids (PFAAs): Column Experiments and Modeling. Journal of Contaminant Hydrology, 233, Article 103661. doi: 10.1016/j.jconhyd.2020.103661  Open Access Manuscript
  12. ^ Garrabrants, A.C., Kosson, D.S., Brown, K.G., Fagnant, D.P., Helms, G., Thorneloe, S.A., 2021. Methodology for Scenario-Based Assessments and Demonstration of Treatment Effectiveness Using the Leaching Environmental Assessment Framework (LEAF). Journal of Hazardous Materials, 406, Article 124635. doi: 10.1016/j.jhazmat.2020.124635  Open Access Manuscript

See Also

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