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==OPTically-based In-situ Characterization System (OPTICS)==  
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==PFAS Leaching Characterization with the Leaching Environmental Assessment Framework (LEAF)==  
OPTICS combines robust aquatic instrumentation and innovative data processing techniques to measure concentrations of a wide range of dissolved and particulate chemical contaminants in surface water at unprecedented scales. OPTICS is used for a variety of environmental applications including remedial investigation, conceptual site model validation, baseline characterization, source control evaluation, plume characterization, and remedial monitoring.
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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.
 
 
 
<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
 
<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
  
 
'''Related Article(s):'''
 
'''Related Article(s):'''
  
*[[Contaminated Sediments - Introduction]]
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*[[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS)]]
*[[Characterization, Assessment & Monitoring]]
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*[[PFAS Sources]]
*[[Mercury in Sediments]]
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*[[PFAS Transport and Fate]]
 
 
'''Contributor(s):'''
 
  
*Grace Chang, Ph.D.
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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
*Todd Martin, P.E.
 
  
'''Key Resource(s):'''
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'''Key Resources:'''
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*Development of Leaching Tests for Materials Containing SVOCs and PFAS, EPA 600/R-23/382<ref name="GarrabrantsEtAl2024"/>
  
*Optically based quantification of fluxes of mercury, methyl mercury, and polychlorinated biphenyls (PCBs) at Berry’s Creek tidal estuary, New Jersey<ref name="ChangEtAl2019">Chang, G., Martin, T., Whitehead, K., Jones, C., Spada, F., 2019. Optically based quantification of fluxes of mercury, methyl mercury, and polychlorinated biphenyls (PCBs) at Berry’s Creek tidal estuary, New Jersey. Limnology and Oceanography, 64(1), pp. 93-108. [https://doi.org/10.1002/lno.11021 doi: 10.1002/lno.11021]&nbsp;&nbsp; [[Media: ChangEtAl2019.pdf | Open Access Article]]</ref>
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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)
  
*OPTically-based In-situ Characterization System (OPTICS) to quantify concentrations of mass fluxes of mercury and methylmercury in South River, Virginia, USA<ref name="ChangEtAl2018">Chang, G., Martin, T., Spada, F., Sackmann, B., Jones, C., Whitehead, K., 2018. OPTically-based In-situ Characterization System (OPTICS) to quantify concentrations and mass fluxes of mercury and methylmercury in South River, Virginia, USA. River Research and Applications, 34(9), pp. 1132-1141. [https://doi.org/10.1002/rra.3361 doi: 10.1002/rra.3361]</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.
  
*Evaluation of stormwater as a potential source of polychlorinated biphenyls (PCBs) to Pearl Harbor, Hawaii<ref name="ChangEtAl2024">Chang, G., Spada, F., Brodock, K., Hutchings, C., Markillie, K., 2024. Evaluation of stormwater as a potential source of polychlorinated biphenyls (PCBs) to Pearl Harbor, Hawaii. Case Studies in Chemical and Environmental Engineering, 9, Article 100659. [https://doi.org/10.1016/j.cscee.2024.100659 doi: 10.1016/j.cscee.2024.100659]&nbsp;&nbsp; [[Media: ChangEtAl2024.pdf | Open Access Article]]</ref>
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{| class="wikitable" style="float:right; margin-left:10px;"
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|+Table 1. EPA SW-846 methods that comprise the LEAF framework
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|-
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!Method
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!Description
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|-
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| 1313 || Liquid-solid partitioning as a function of '''''extract pH''''' using a parallel batch extraction (i.e., equilibrium) procedure (Figure 1)
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|-
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| 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)
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|-
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| 1315 || '''''Mass transfer rates''''' of constituents in monolithic or compacted granular materials using a semi-dynamic tank leaching procedure
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|-
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| 1316 || Liquid-solid partitioning as a function of '''''L/S''''' using a parallel batch extraction (i.e., '''''equilibrium''''') procedure (Figure 2)
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|-
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| colspan="2" style="background:white;" | Note: Text shown in '''''bold''''' indicates primary condition evaluated in each method.
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|}
  
==Background==
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==Method Development for PFAS==
Nationwide, the liability due to contaminated sediments is estimated in the trillions of dollars. Stakeholders are assessing and developing remedial strategies for contaminated sediment sites in major harbors and waterways throughout the U.S. The mobility of contaminants in surface water is a primary transport and risk mechanism<ref>Thibodeaux, L.J., 1996. Environmental Chemodynamics: Movement of Chemicals in Air, Water, and Soil, 2nd Edition, Volume 110 of Environmental Science and Technology: A Wiley-Interscience Series of Texts and Monographs. John Wiley & Sons, Inc. 624 pages. ISBN: 0-471-61295-2</ref><ref>United States Environmental Protection Agency (USEPA), 2005. Contaminated Sediment Remediation Guidance for Hazardous Waste Sites. Office of Superfund Remediation and Technology Innovation Report, EPA-540-R-05-012. [[Media: 2005-USEPA-Contaminated_Sediment_Remediation_Guidance.pdf | Report.pdf]]</ref><ref>Lick, W., 2008. Sediment and Contaminant Transport in Surface Waters. CRC Press. 416 pages. [https://doi.org/10.1201/9781420059885 doi:  10.1201/9781420059885]</ref>; therefore, long-term monitoring of both particulate- and dissolved-phase contaminant concentration prior to, during, and following remedial action is necessary to ensure remedy effectiveness. Source control and total maximum daily load (TMDL) actions generally require costly manual monitoring of dissolved and particulate contaminant concentrations in surface water. The magnitude of cost for these actions is a strong motivation to implement efficient methods for long-term source control and remedial monitoring.  
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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:
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* 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.
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* 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.
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* 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.
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* Eluate processing (all methods): Use of centrifugation in lieu of eluate filtering, sonication of bottle prior to eluate subsampling.
  
Traditional surface water monitoring requires mobilization of field teams to manually collect discrete water samples, send samples to laboratories, and await laboratory analysis so that a site evaluation can be conducted. These traditional methods are well known to have inherent cost and safety concerns and are of limited use in capturing episodic events (e.g., storms) important to site risk and remedy due to safety concerns and standby requirements for resources. Automated water samplers are commercially available but still require significant field support and costly laboratory analysis. Further, automated samplers may not be suitable for analytes with short hold-times and temperature requirements.  
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==Batch Test Demonstration Studies==
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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.
  
Optically-based characterization of surface water contaminants is a cost-effective alternative to traditional discrete water sampling methods. Unlike discrete water sampling, which typically results in sparse data at low resolution, and therefore, is of limited use in determining mass loading, OPTICS (OPTically-based In-situ Characterization System) provides continuous data and allows for a complete understanding of water quality and contaminant transport in response to natural processes and human impacts<ref name="ChangEtAl2019"/><ref name="ChangEtAl2018"/><ref name="ChangEtAl2024"/><ref>Bergamaschi, B.A., Fleck, J.A., Downing, B.D., Boss, E., Pellerin, B., Ganju, N.K., Schoellhamer, D.H., Byington, A.A., Heim, W.A., Stephenson, M., Fujii, R., 2011. Methyl mercury dynamics in a tidal wetland quantified using in situ optical measurements. Limnology and Oceanography, 56(4), pp. 1355-1371. [https://doi.org/10.4319/lo.2011.56.4.1355 doi: 10.4319/lo.2011.56.4.1355]&nbsp;&nbsp; [[Media: BergamaschiEtAl2011.pdf | Open Access Article]]</ref><ref>Bergamaschi, B.A., Fleck, J.A., Downing, B.D., Boss, E., Pellerin, B.A., Ganju, N.K., Schoellhamer, D.H., Byington, A.A., Heim, W.A., Stephenson, M., Fujii, R., 2012. Mercury Dynamics in a San Francisco Estuary Tidal Wetland: Assessing Dynamics Using In Situ Measurements. Estuaries and Coasts, 35, pp. 1036-1048. [https://doi.org/10.1007/s12237-012-9501-3 doi: 10.1007/s12237-012-9501-3]&nbsp;&nbsp; [[Media: BergamaschiEtAl2012a.pdf | Open Access Article]]</ref><ref>Bergamaschi, B.A., Krabbenhoft, D.P., Aiken, G.R., Patino, E., Rumbold, D.G., Orem, W.H., 2012. Tidally driven export of dissolved organic carbon, total mercury, and methylmercury from a mangrove-dominated estuary. Environmental Science and Technology, 46(3), pp. 1371-1378. [https://doi.org/10.1021/es2029137 doi: 10.1021/es2029137]&nbsp;&nbsp; [[Media: BergamaschiEtAl2012b.pdf | Open Access Article]]</ref>. The OPTICS tool integrates commercial off-the-shelf ''in situ'' aquatic sensors, periodic discrete surface water sample collection, and a multi-parameter statistical prediction model<ref name="deJong1993">de Jong, S., 1993. SIMPLS: an alternative approach to partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 18(3), pp. 251-263. [https://doi.org/10.1016/0169-7439(93)85002-X doi: 10.1016/0169-7439(93)85002-X]</ref><ref name="RosipalKramer2006">Rosipal, R. and Krämer, N., 2006. Overview and Recent Advances in Partial Least Squares, In: Subspace, Latent Structure, and Feature Selection: Statistical and Optimization Perspectives Workshop, Revised Selected Papers (Lecture Notes in Computer Science, Volume 3940), Springer-Verlag, Berlin, Germany. pp. 34-51. [https://doi.org/10.1007/11752790_2 doi: 10.1007/11752790_2]</ref> to provide high temporal and/or spatial resolution characterization of surface water chemicals of potential concern (COPCs).
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[[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)]]
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'''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.
  
==Technology Overview==
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[[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"/>]]
[[File:ChangFig1.png | thumb | 400px| Figure 1. Schematic diagram illustrating the OPTICS methodology. High resolution in-situ data are integrated with traditional discrete sample analytical data using partial least-square regression to derive high resolution chemical contaminant concentration data series.]]
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'''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>.  
[[File:ChangFig2.png | thumb | 400px| Figure 2. Example of instrumentation used for OPTICS monitoring.]]
 
The principle behind OPTICS is based on the relationship between optical properties of natural waters and the particles and dissolved material contained within them<ref>Boss, E. and Pegau, W.S., 2001. Relationship of light scattering at an angle in the backward direction to the backscattering coefficient. Applied Optics, 40(30), pp. 5503-5507. [https://doi.org/10.1364/AO.40.005503 doi: 10.1364/AO.40.005503]</ref><ref>Boss, E., Twardowski, M.S., Herring, S., 2001. Shape of the particulate beam spectrum and its inversion to obtain the shape of the particle size distribution. Applied Optics, 40(27), pp. 4884-4893. [https://doi.org/10.1364/AO.40.004885 doi:10/1364/AO.40.004885]</ref><ref>Babin, M., Morel, A., Fournier-Sicre, V., Fell, F., Stramski, D., 2003. Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration. Limnology and Oceanography, 48(2), pp. 843-859. [https://doi.org/10.4319/lo.2003.48.2.0843 doi: 10.4319/lo.2003.48.2.0843]&nbsp;&nbsp; [[Media: BabinEtAl2003.pdf | Open Access Article]]</ref><ref>Coble, P., Hu, C., Gould, R., Chang, G., Wood, M., 2004. Colored dissolved organic matter in the coastal ocean: An optical tool for coastal zone environmental assessment and management. Oceanography, 17(2), pp. 50-59. [https://doi.org/10.5670/oceanog.2004.47 doi: 10.5670/oceanog.2004.47]&nbsp;&nbsp; [[Media: CobleEtAl2004.pdf | Open Access Article]]</ref><ref>Sullivan, J.M., Twardowski, M.S., Donaghay, P.L., Freeman, S.A., 2005. Use of optical scattering to discriminate particle types in coastal waters. Applied Optics, 44(9), pp. 1667–1680. [https://doi.org/10.1364/AO.44.001667 doi: 10.1364/AO.44.001667]</ref><ref>Twardowski, M.S., Boss, E., Macdonald, J.B., Pegau, W.S., Barnard, A.H., Zaneveld, J.R.V., 2001. A model for estimating bulk refractive index from the optical backscattering ratio and the implications for understanding particle composition in case I and case II waters. Journal of Geophysical Research: Oceans, 106(C7), pp. 14,129-14,142. [https://doi.org/10.1029/2000JC000404 doi: 10/1029/2000JC000404]&nbsp;&nbsp; [[Media: TwardowskiEtAl2001.pdf | Open Access Article]]</ref><ref>Chang, G.C., Barnard, A.H., McLean, S., Egli, P.J., Moore, C., Zaneveld, J.R.V., Dickey, T.D., Hanson, A., 2006. In situ optical variability and relationships in the Santa Barbara Channel: implications for remote sensing. Applied Optics, 45(15), pp. 3593–3604. [https://doi.org/10.1364/AO.45.003593 doi: 10.1364/AO.45.003593]</ref><ref>Slade, W.H. and Boss, E., 2015. Spectral attenuation and backscattering as indicators of average particle size. Applied Optics, 54(24), pp. 7264-7277. [https://doi.org/10.1364/AO.54.007264 doi: 10/1364/AO.54.007264]&nbsp;&nbsp; [[Media: SladeBoss2015.pdf | Open Access Article]]</ref>. Surface water COPCs such as heavy metals and polychlorinated biphenyls (PCBs) are hydrophobic in nature and tend to sorb to materials in the water column, which have unique optical signatures that can be measured at high-resolution using ''in situ'', commercially available aquatic sensors<ref>Agrawal, Y.C. and Pottsmith, H.C., 2000. Instruments for particle size and settling velocity observations in sediment transport. Marine Geology, 168(1-4), pp. 89-114. [https://doi.org/10.1016/S0025-3227(00)00044-X doi: 10.1016/S0025-3227(00)00044-X]</ref><ref>Boss, E., Pegau, W.S., Gardner, W.D., Zaneveld, J.R.V., Barnard, A.H., Twardowski, M.S., Chang, G.C., Dickey, T.D., 2001. Spectral particulate attenuation and particle size distribution in the bottom boundary layer of a continental shelf. Journal of Geophysical Research: Oceans, 106(C5), pp. 9509-9516. [https://doi.org/10.1029/2000JC900077  doi: 10.1029/2000JC900077]&nbsp;&nbsp; [[Media: BossEtAl2001.pdf | Open Access Article]]</ref><ref>Boss, E., Pegau, W.S., Lee, M., Twardowski, M., Shybanov, E., Korotaev, G. Baratange, F., 2004. Particulate backscattering ratio at LEO 15 and its use to study particle composition and distribution. Journal of Geophysical Research: Oceans, 109(C1), Article C01014. [https://doi.org/10.1029/2002JC001514 doi: 10.1029/2002JC001514]&nbsp;&nbsp; [[Media: BossEtAl2004.pdf | Open Access Article]]</ref><ref>Briggs, N.T., Slade, W.H., Boss, E., Perry, M.J., 2013. Method for estimating mean particle size from high-frequency fluctuations in beam attenuation or scattering measurement. Applied Optics, 52(27), pp. 6710-6725. [https://doi.org/10.1364/AO.52.006710 doi: 10.1364/AO.52.006710]&nbsp;&nbsp; [[Media: BriggsEtAl2013.pdf | Open Access Article]]</ref>. Therefore, high-resolution concentrations of COPCs can be accurately and robustly derived from ''in situ'' measurements using statistical methods.
 
  
The OPTICS method is analogous to the commonly used empirical derivation of total suspended solids concentration (TSS) from optical turbidity using linear regression<ref>Rasmussen, P.P., Gray, J.R., Glysson, G.D., Ziegler, A.C., 2009. Guidelines and procedures for computing time-series suspended-sediment concentrations and loads from in-stream turbidity-sensor and streamflow data. In: Techniques and Methods, Book 3: Applications of Hydraulics, Section C: Sediment and Erosion Techniques, Ch. 4. 52 pages. U.S. Geological Survey.&nbsp;&nbsp; [[Media: RasmussenEtAl2009.pdf | Open Access Article]]</ref>. However, rather than deriving one response variable (TSS) from one predictor variable (turbidity), OPTICS involves derivation of one response variable (e.g., PCB concentration) from a suite of predictor variables (e.g., turbidity, temperature, salinity, and fluorescence of chlorophyll-a) using multi-parameter statistical regression. OPTICS is based on statistical correlation – similar to the turbidity-to-TSS regression technique. The method does not rely on interpolation or extrapolation.  
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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.
  
The OPTICS technique utilizes partial least-squares (PLS) regression to determine a combination of physical, optical, and water quality properties that best predicts chemical contaminant concentrations with high variance. PLS regression is a statistically based method combining multiple linear regression and principal component analysis (PCA), where multiple linear regression finds a combination of predictors that best fit a response and PCA finds combinations of predictors with large variance<ref name="deJong1993"/><ref name="RosipalKramer2006"/>. Therefore, PLS identifies combinations of multi-collinear predictors (''in situ'', high-resolution physical, optical, and water quality measurements) that have large covariance with the response values (discrete surface water chemical contaminant concentration data from samples that are collected periodically, coincident with ''in situ'' measurements). PLS combines information about the variances of both the predictors and the responses, while also considering the correlations among them. PLS therefore provides a model with reliable predictive power.
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As anticipated, trends in PFAS leaching obtained during the Method 1316A and Method 1314A demonstrations were qualitatively similar. These are further discussed below.
  
OPTICS ''in situ'' measurement parameters include, but are not limited to current velocity, conductivity, temperature, depth, turbidity, dissolved oxygen, and fluorescence of chlorophyll-a and dissolved organic matter. Instrumentation for these measurements is commercially available, robust, deployable in a wide variety of configurations (e.g., moored, vessel-mounted, etc.), powered by batteries, and records data internally and/or transmits data in real-time. The physical, optical, and water quality instrumentation is compact and self-contained. The modularity and automated nature of the OPTICS measurement system enables robust, long-term, autonomous data collection for near-continuous monitoring.  
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==Column Test Demonstration Studies==
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[[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.]]
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PFAS-specific adaptations were tested in column test demonstration studies, which included triplicate implementation of Method 1314A in three AFFF-impacted site soils.
  
OPTICS measurements are provided at a significantly reduced cost relative to traditional monitoring techniques used within the environmental industry. Cost performance analysis shows that monitoring costs are reduced by more than 85% while significantly increasing the temporal and spatial resolution of sampling. The reduced cost of monitoring makes this technology suitable for a number of environmental applications including, but not limited to site baseline characterization, source control evaluation, dredge or stormflow plume characterization, and remedy performance monitoring. OPTICS has been successfully demonstrated for characterizing a wide variety of COPCs: mercury, methylmercury, copper, lead, PCBs, dichlorodiphenyltrichloroethane (DDT) and its related compounds (collectively, DDX), and 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD or dioxin) in a number of different environmental systems ranging from inland lakes and rivers to the coastal ocean. To date, OPTICS has been limited to surface water applications. Additional applications (e.g., groundwater) would require further research and development.
+
'''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.
  
==Applications==
+
==LEAF Screening Evaluations==
[[File:ChangFig3.png | thumb | 400px| Figure 3. OPTICS to characterize COPC variability in the context of site processes at BCSA. (A) Tidal oscillations (Elev.<sub>MSL</sub>) and precipitation (Precip.). (B) – (D) OPTICS-derived particulate mercury (PHg) and methylmercury (PMeHg) and total PCBs (TPCBs). Open circles represent discrete water sample data.]]
+
[[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>.]]
[[File:ChangFig4.png | thumb | 400px| Figure 4. OPTICS reveals baseflow daily cycling and confirms storm-induced particle-bound COPC resuspension and mobilization through bank interaction. (A) Flow rate (Q) and precipitation (Precip). (B) – (C) OPTICS-derived particulate mercury (PHg) and methylmercury (PMeHg). Open circles represent discrete water sample data.]]
+
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:
[[File:ChangFig5.png | thumb | 400px| Figure 5. Three-dimensional volume plot of high spatial resolution OPTICS-derived PCBs in exceedance of baseline showing that PCBs were discharged from the outfall (yellow arrow), remained in suspension, and dispersed elsewhere before settling.]]  
+
#Assume the maximum leaching concentration is represented by the total content (total initial mass of contaminant present) leaching into the first L/S.
An OPTICS study was conducted at Berry’s Creek Study Area (BCSA), New Jersey in 2014 and 2015 to understand COPC sources and transport mechanisms for development of an effective remediation plan. OPTICS successfully extended periodic discrete surface water samples to continuous, high-resolution measurements of PCBs, mercury, and methylmercury to elucidate COPC sources and transport throughout the BCSA tidal estuary system. OPTICS provided data at resolution sufficient to investigate COC variability in the context of physical processes. The results facilitated focused and effective site remediation and management decisions that could not be determined based on periodic discrete samples alone, despite over seven years of monitoring at different locations throughout the system over a range of different seasons, tidal phases, and environmental conditions. The BCSA OPTICS methodology and its results have undergone official peer review overseen by the U.S. Environmental Protection Agency (USEPA), and those results have been published in peer-reviewed literature<ref name="ChangEtAl2019"/>.  
+
#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.
  
OPTICS was applied at the South River, Virginia in 2016 to quantify sources of legacy mercury in the system that are contributing to recontamination and continued elevated mercury concentrations in fish tissue. OPTICS provided information necessary to identify mechanisms for COPC redistribution and to quantify the relative contribution of each mechanism to total mass transport of mercury and methylmercury in the system. Continuous, high-resolution COPC data afforded by OPTICS helped resolve baseflow daily cycling that had never before been observed at the South River and provided data at temporal resolution necessary to verify storm-induced particle-bound COC resuspension and mobilization through bank interaction. The results informed source control and remedy design and monitoring efforts. Methodology and results from the South River have been published in peer-reviewed literature<ref name="ChangEtAl2018"/>.  
+
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 U.S. Department of Defense’s Environmental Security Technology Certification Program (ESTCP) supported an OPTICS demonstration study at the Pearl Harbor Sediment Site, Hawaii, to determine whether stormwater from Oscar 1 Pier outfall is a contributing source of PCBs to Decision Unit (DU) N-2 (ESTCP Project ER21-5021). High spatial resolution results afforded by ship-based, mobile OPTICS monitoring suggested that PCBs were discharged from the outfall, remained in suspension, and dispersed elsewhere before settling. More details regarding this study were presented by Chang et al. in 2024<ref name="ChangEtAl2024"/>.
+
==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
  
==Summary==
+
Additionally, there are key areas for consideration in future research:
OPTICS provides:
+
*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
*High resolution surface water chemical contaminant characterization
+
*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
*Cost-effective monitoring and assessment
 
*Versatile and modular monitoring with capability for real-time telemetry
 
*Data necessary for development and validation of conceptual site models
 
*A key line of evidence for designing and evaluating remedies.
 
  
Because OPTICS monitoring involves deployment of autonomous sampling instrumentation, a substantially greater volume of data can be collected using this technique compared to traditional sampling, and at a far lower cost. A large volume of data supports evaluation of chemical contaminant concentrations over a range of spatial and temporal scales, and the system can be customized for a variety of environmental applications. OPTICS helps quantify contaminant mass flux and the relative contribution of local transport and source areas to net contaminant transport. OPTICS delivers a strong line of evidence for evaluating contaminant sources, fate, and transport, and for supporting the design of a remedy tailored to address site-specific, risk-driving conditions. The improved understanding of site processes aids in the development of mitigation measures that minimize site risks.  
+
==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"/>
  
 
==References==
 
==References==

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