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==1,2,3-Trichloropropane (TCP)==
+
==PFAS Leaching Characterization with the Leaching Environmental Assessment Framework (LEAF)==  
[[Wikipedia: 1,2,3-Trichloropropane | 1,2,3-Trichloropropane (TCP)]] is a chlorinated volatile organic compound (CVOC) that has been used in chemical production processes, in agriculture, and as a solvent, resulting in point and non-point source contamination of soil and groundwater.  TCP is mobile and highly persistent in soil and groundwater. TCP is not currently regulated at the national level in the United States, but [[Wikipedia: Maximum contaminant level | maximum contaminant levels (MCLs)]] have been developed by some states.  Current treatment methods for TCP are limited and can be cost prohibitive. However, some treatment approaches, particularly [[Chemical Reduction (In Situ - ISCR) | ''in situ'' chemical reduction (ISCR)]] with [[Wikipedia: In_situ_chemical_reduction#Zero_valent_metals_%28ZVMs%29 | zero valent zinc (ZVZ)]] and [[Bioremediation - Anaerobic | ''in situ'' bioremediation (ISB)]], have recently been shown to have potential as practical remedies for TCP contamination of groundwater.
+
[[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):'''
*[[Bioremediation - Anaerobic | Anaerobic Bioremediation]]
 
*[[Chemical Reduction (In Situ - ISCR) | ''In Situ'' Chemical Reduction (ISCR)]]
 
*[[Chemical Oxidation (In Situ - ISCO) | ''In Situ'' Chemical Oxidation (ISCO)]]
 
  
'''Contributor(s):'''
+
*[[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS)]]
*[[Dr. Alexandra Salter-Blanc | Alexandra J. Salter-Blanc]]
+
*[[PFAS Sources]]
*[[Dr. Paul Tratnyek | Paul G. Tratnyek]]
+
*[[PFAS Transport and Fate]]
*John Merrill
 
*Alyssa Saito
 
*Lea Kane
 
*Eric Suchomel
 
*[[Dr. Rula Deeb | Rula Deeb]]
 
  
'''Key Resource(s):'''
+
'''Contributors:''' Dr. Jennifer L. Guelfo, Dr. David Kosson, Dr. Andy Garrabrants, Ms. Fangfei Liu, Mr. Darlington Yawson, Dr. Md. Isreq Real
*Prospects for Remediation of 1,2,3-Trichloropropane by Natural and Engineered Abiotic Degradation Reactions. Strategic Environmental Research and Development Program (SERDP), Project ER-1457.<ref name="Tratnyek2010">Tratnyek, P.G., Sarathy, V., Salter, A.J., Nurmi, J.T., O’Brien Johnson, G., DeVoe, T., and Lee, P., 2010. Prospects for Remediation of 1,2,3-Trichloropropane by Natural and Engineered Abiotic Degradation Reactions. Strategic Environmental Research and Development Program (SERDP), Project ER-1457. [https://serdp-estcp.org/Program-Areas/Environmental-Restoration/Contaminated-Groundwater/Emerging-Issues/ER-1457/ER-1457/(language)/eng-US  Website]&nbsp;&nbsp; [[Media: ER-1457-FR.pdf | Report.pdf]]</ref>
 
  
*Verification Monitoring for In Situ Chemical Reduction Using Zero-Valent Zinc, A Novel Technology for Remediation of Chlorinated Alkanes. Strategic Environmental Research and Development Program (SERDP), Project ER-201628.<ref name="Kane2020">Kane, L.Z., Suchomel, E.J., and Deeb, R.A., 2020. Verification Monitoring for In Situ Chemical Reduction Using Zero-Valent Zinc, A Novel Technology for Remediation of Chlorinated Alkanes. Strategic Environmental Research and Development Program (SERDP), Project ER-201628. [https://www.serdp-estcp.org/Program-Areas/Environmental-Restoration/Contaminated-Groundwater/Persistent-Contamination/ER-201628  Website]&nbsp;&nbsp; [[Media: ER-201628.pdf | Report.pdf]]</ref>
+
'''Key Resources:'''
 +
*Development of Leaching Tests for Materials Containing SVOCs and PFAS, EPA 600/R-23/382<ref name="GarrabrantsEtAl2024"/>
  
==Introduction==
+
*[https://www.epa.gov/hw-sw846/leaching-environmental-assessment-framework-leaf-methods-and-guidance Leaching Environmental Assessment Framework (LEAF) Methods and Guidance] (EPA website)
[[File:123TCPFig1.png|thumb|left|Figure 1. Ball and stick representation of the molecular structure of TCP (Salter-Blanc and Tratnyek, unpublished)]]
 
1,2,3-Trichloropropane (TCP) (Figure 1) is a man-made chemical that was used in the past primarily as a solvent and extractive agent, as a paint and varnish remover, and as a cleaning and degreasing agent.<ref name="ATSDR2021"> Agency for Toxic Substances and Disease Registry (ATSDR), 2021. Toxicological Profile for 1,2,3-Trichloropropane. Free download from: [https://www.atsdr.cdc.gov/toxprofiles/tp57.pdf ATSDR]&nbsp;&nbsp; [[Media: TCP2021ATSDR.pdf | Report.pdf]]</ref>. Currently, TCP is primarily used in chemical synthesis of compounds such as [[Wikipedia: Polysulfone | polysulfone]] liquid polymers used in the aerospace and automotive industries; [[Wikipedia: Hexafluoropropylene | hexafluoropropylene]] used in the agricultural, electronic, and pharmaceutical industries; [[Wikipedia: Polysulfide | polysulfide]] polymers used as sealants in manufacturing and construction; and [[Wikipedia: 1,3-Dichloropropene | 1,3-dichloropropene]] used in agriculture as a soil fumigant. TCP may also be present in products containing these chemicals as an impurity<ref name="ATSDR2021"/><ref name="CH2M2005">CH2M HILL, 2005. Interim Guidance for Investigating Potential 1,2,3-Trichloropropane Sources in San Gabriel Valley Area 3. [[Media: INTERIM_GUIDANCE_FOR_INVESTIGATING_POTENTIAL_1%2C2%2C3-TRICHLOROPROPANE_SOURCES.pdf | Report.pdf]]&nbsp;&nbsp;  [https://cumulis.epa.gov/supercpad/cursites/csitinfo.cfm?id=0902093  Website]</ref>. For example, the 1,2-dichlropropane/1,3-dichloropropene soil fumigant mixture (trade name D-D), which is no longer sold in the United States, contained TCP as an impurity and has been linked to TCP contamination in groundwater<ref name="OkiGiambelluca1987">Oki, D.S. and Giambelluca, T.W., 1987. DBCP, EDB, and TCP Contamination of Ground Water in Hawaii. Groundwater, 25(6), pp. 693-702.  [https://doi.org/10.1111/j.1745-6584.1987.tb02210.x DOI: 10.1111/j.1745-6584.1987.tb02210.x]</ref><ref name="CH2M2005"/>. Soil fumigants currently in use which are composed primarily of 1,3-dichloropropene may also contain TCP as an impurity, for instance Telone II has been reported to contain up to 0.17 percent TCP by weight<ref name="Kielhorn2003">Kielhorn, J., Könnecker, G., Pohlenz-Michel, C., Schmidt, S. and Mangelsdorf, I., 2003. Concise International Chemical Assessment Document 56: 1,2,3-Trichloropropane. World Health Organization, Geneva.  [http://www.who.int/ipcs/publications/cicad/en/cicad56.pdf Website]&nbsp;&nbsp; [[Media: WHOcicad56TCP.pdf | Report.pdf]]</ref>.
 
  
TCP contamination is problematic because it is “reasonably anticipated to be a human carcinogen” based on evidence of carcinogenicity to animals<ref name="NTP2016"> National Toxicology Program, 2016. Report on Carcinogens, 14th ed. U.S. Department of Health and Human Services, Public Health Service. Free download from: [https://ntp.niehs.nih.gov/ntp/roc/content/profiles/trichloropropane.pdf  NIH]&nbsp;&nbsp; [[Media: NTP2016trichloropropane.pdf | Report.pdf]]</ref>. Toxicity to humans appears to be high relative to other chlorinated solvents<ref name="Kielhorn2003"/>, suggesting that even low-level exposure to TCP could pose a significant human health risk.
+
==Introduction to LEAF==
 +
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.
  
==Environmental Fate==
+
{| class="wikitable" style="float:right; margin-left:10px;"
TCP’s fate in the environment is governed by its physical and chemical properties (Table 1). TCP does not adsorb strongly to soil, making it likely to leach into groundwater and exhibit high mobility. In addition, TCP is moderately volatile and can partition from surface water and moist soil into the atmosphere. Because TCP is only slightly soluble and denser than water, it can form a [[Wikipedia: Dense non-aqueous phase liquid | dense non-aqueous phase liquid (DNAPL)]] as observed at the Tyson’s Dump Superfund Site<ref name="USEPA2019"> United States Environmental Protection Agency (USEPA), 2019. Fifth Five-year Review Report, Tyson’s Dump Superfund Site, Upper Merion Township, Montgomery County, Pennsylvania. Free download from: [https://semspub.epa.gov/work/03/2282817.pdf USEPA]&nbsp;&nbsp; [[Media: USEPA2019.pdf | Report.pdf]]</ref>. TCP is generally resistant to aerobic biodegradation, hydrolysis, oxidation, and reduction under naturally occurring conditions making it persistent in the environment<ref name="Tratnyek2010"/>.
+
|+Table 1. EPA SW-846 methods that comprise the LEAF framework
 
 
{| class="wikitable" style="float:right; margin-left:10px;text-align:center;"
 
|+Table 1.  Physical and chemical properties of TCP<ref name="USEPA2017">United States Environmental Protection Agency (USEPA), 2017. Technical Fact Sheet—1,2,3-Trichloropropane (TCP). EPA Project 505-F-17-007. 6 pp.  Free download from: [https://www.epa.gov/sites/production/files/2017-10/documents/ffrrofactsheet_contaminants_tcp_9-15-17_508.pdf  USEPA]&nbsp;&nbsp; [[Media: epa_tcp_2017.pdf | Report.pdf]]</ref>
 
|-
 
!Property
 
!Value
 
|-
 
| Chemical Abstracts Service (CAS) Number || 96-18-4
 
|-
 
| Physical Description</br>(at room temperature) || Colorless to straw-colored liquid
 
|-
 
| Molecular weight</br>(g/mol) || 147.43
 
|-
 
| Water solubility at 25°C</br>(mg/L)|| 1,750 (slightly soluble)
 
|-
 
| Melting point</br>(°C)|| -14.7
 
 
|-
 
|-
| Boiling point</br>(°C) || 156.8
+
!Method
 +
!Description
 
|-
 
|-
| Vapor pressure at 25°C</br>(mm Hg) || 3.10 to 3.69
+
| 1313 || Liquid-solid partitioning as a function of '''''extract pH''''' using a parallel batch extraction (i.e., equilibrium) procedure (Figure 1)
 
|-
 
|-
| Density at 20°C (g/cm<sup>3</sup>) || 1.3889
+
| 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)
 
|-
 
|-
| Octanol-water partition coefficient</br>(log''K<sub>ow</sub>'') || 1.98 to 2.27</br>(temperature dependent)
+
| 1315 || '''''Mass transfer rates''''' of constituents in monolithic or compacted granular materials using a semi-dynamic tank leaching procedure
 
|-
 
|-
| Organic carbon-water partition coefficient</br>(log''K<sub>oc</sub>'') || 1.70 to 1.99</br>(temperature dependent)
+
| 1316 || Liquid-solid partitioning as a function of '''''L/S''''' using a parallel batch extraction (i.e., '''''equilibrium''''') procedure (Figure 2)
 
|-
 
|-
| Henry’s Law constant at 25°C</br>(atm-m<sup>3</sup>/mol) || 3.17x10<sup>-4</sup><ref name="ATSDR2021"/> to 3.43x10<sup>-4</sup><ref name="LeightonCalo1981">Leighton Jr, D.T. and Calo, J.M., 1981. Distribution Coefficients of Chlorinated Hydrocarbons in Dilute Air-Water Systems for Groundwater Contamination Applications. Journal of Chemical and Engineering Data, 26(4), pp. 382-385.  [https://doi.org/10.1021/je00026a010 DOI: 10.1021/je00026a010]</ref>
+
| colspan="2" style="background:white;" | Note: Text shown in '''''bold''''' indicates primary condition evaluated in each method.
 
|}
 
|}
  
==Occurrence==
+
==Method Development for PFAS==
TCP has been detected in approximately 1% of public water supply and domestic well samples tested by the United States Geological Survey. More specifically, TCP was detected in 1.2% of public supply well samples collected between 1993 and 2007 by Toccalino and Hopple<ref name="ToccalinoHopple2010">Toccalino, P.L., Norman, J.E., Hitt, K.J., 2010. Quality of Source Water from Public-Supply Wells in the United States, 1993–2007. Scientific Investigations Report 2010-5024. U.S. Geological Survey. [https://doi.org/10.3133/sir20105024 DOI: 10.3133/sir20105024]  Free download from: [https://pubs.er.usgs.gov/publication/sir20105024 USGS]&nbsp;&nbsp; [[Media: Quality_of_source_water_from_public-supply_wells_in_the_United_States%2C_1993-2007.pdf | Report.pdf]]</ref> and 0.66% of domestic supply well samples collected between 1991 and 2004 by DeSimone<ref name="DeSimone2009">DeSimone, L.A., 2009. Quality of Water from Domestic Wells in Principal Aquifers of the United States, 1991–2004. U.S. Geological Survey, Scientific Investigations Report 2008–5227. 139 pp. Free download from: [http://pubs.usgs.gov/sir/2008/5227 USGS]&nbsp;&nbsp; [[Media: DeSimone2009.pdf | Report.pdf]]</ref>. TCP was detected at a higher rate in domestic supply well samples associated with agricultural land-use studies than samples associated with studies comparing primary aquifers (3.5% versus 0.2%)<ref name="DeSimone2009"/>.  
+
Complete details of the development of LEAF Methods 1313A, 1314A, and 1316A for use with PFAS are available in Garrabrants ''et al.'', 2025<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.
==Regulation==
+
* 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.
The United States Environmental Protection Agency (USEPA) has not established an MCL for TCP, although guidelines and health standards are in place<ref name="USEPA2017"/>. TCP was included in the Contaminant Candidate List 3<ref name="USEPA2009">United States Environmental Protection Agency (US EPA), 2009. Drinking Water Contaminant Candidate List 3-Final. Federal Register 74(194), pp. 51850–51862, Document E9-24287. [https://www.federalregister.gov/documents/2009/10/08/E9-24287/drinking-water-contaminant-candidate-list-3-final Website]&nbsp;&nbsp; [[Media: FR74-194DWCCL3.pdf | Report.pdf]]</ref> and the Unregulated Contaminant Monitoring Rule 3 (UCMR 3)<ref name="USEPA2012">United States Environmental Protection Agency (US EPA), 2012. Revisions to the Unregulated Contaminant Mentoring Regulation (UCMR 3) for Public Water Systems. Federal Register 77(85) pp. 26072-26101. [https://www.federalregister.gov/documents/2012/05/02/2012-9978/revisions-to-the-unregulated-contaminant-monitoring-regulation-ucmr-3-for-public-water-systems  Website]&nbsp;&nbsp; [[Media: FR77-85UCMR3.pdf | Report.pdf]]</ref>. The UCMR 3 specified that data be collected on TCP occurrence in public water systems over the period of January 2013 through December 2015 against a reference concentration range of 0.0004 to 0.04 μg/L<ref name="USEPA2017a">United States Environmental Protection Agency (USEPA), 2017. The Third Unregulated Contaminant Monitoring Rule (UCMR 3): Data Summary. EPA 815-S-17-001. [https://www.epa.gov/dwucmr/data-summary-third-unregulated-contaminant-monitoring-rule  Website]&nbsp;&nbsp; [[Media: ucmr3-data-summary-january-2017.pdf | Report.pdf]]</ref>. The reference concentration range was determined based on a cancer risk of 10-6 to 10-4 and derived from an oral slope factor of 30 mg/kg-day, which was determined by the EPA’s Integrated Risk Information System<ref name="IRIS2009">USEPA Integrated Risk Information System (IRIS), 2009. 1,2,3-Trichloropropane (CASRN 96-18-4). [https://cfpub.epa.gov/ncea/iris2/chemicalLanding.cfm?substance_nmbr=200 Website]&nbsp;&nbsp; [[Media: TCPsummaryIRIS.pdf | Summary.pdf]]</ref>. Of 36,848 samples collected during UCMR 3, 0.67% exceeded the minimum reporting level of 0.03 µg/L. 1.4% of public water systems had at least one detection over the minimum reporting level, corresponding to 2.5% of the population<ref name="USEPA2017a"/>. While these occurrence percentages are relatively low, the minimum reporting level of 0.03 µg/L is more than 75 times the USEPA-calculated Health Reference Level of 0.0004 µg/L. Because of this, TCP may occur in public water systems at concentrations that exceed the Health Reference Level but are below the minimum reporting level used during UCMR 3 data collection. These analytical limitations and lack of lower-level occurrence data have prevented the USEPA from making a preliminary regulatory determination for TCP<ref name="USEPA2021">USEPA, 2021. Announcement of Final Regulatory Determinations for Contaminants on the Fourth Drinking Water Contaminant Candidate List. Free download from: [https://www.epa.gov/sites/default/files/2021-01/documents/10019.70.ow_ccl_reg_det_4.final_web.pdf USEPA]&nbsp;&nbsp; [[Media: CCL4.pdf | Report.pdf]]</ref>.  
+
* 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.
Some US states have established their own standards including Hawaii which has established an MCL of 0.6 μg/L<ref name="HDOH2013">Hawaii Department of Health, 2013. Amendment and Compilation of Chapter 11-20 Hawaii Administrative Rules. Free download from: [http://health.hawaii.gov/sdwb/files/2016/06/combodOPPPD.pdf Hawaii Department of Health]&nbsp;&nbsp; [[Media: Amendment_and_Compilation_of_Chapter_11-20_Hawaii_Administrative_Rules.pdf | Report.pdf]]</ref>. California has established an MCL of 0.005 μg/L<ref name="CCR2021">California Code of Regulations, 2021. Section 64444 Maximum Contaminant Levels – Organic Chemicals (22 CA ADC § 64444). [https://govt.westlaw.com/calregs/Document/IA7B3800D18654ABD9E2D24A445A66CB9 Website]</ref>,  a notification level of 0.005 μg/L, and a public health goal of 0.0007 μg/L<ref name="OEHHA2009">Office of Environmental Health Hazard Assessment (OEHHA), California Environmental Protection Agency, 2009. Final Public Health Goal for 1,2,3-Trichloropropane in Drinking Water. [https://oehha.ca.gov/water/public-health-goal/final-public-health-goal-123-trichloropropane-drinking-water Website]</ref>, and New Jersey has established an MCL of 0.03 μg/L<ref name="NJAC2020">New Jersey Administrative Code 7:10, 2020. Safe Drinking Water Act Rules. Free download from: [https://www.nj.gov/dep/rules/rules/njac7_10.pdf  New Jersey Department of Environmental Protection]</ref>.  
 
  
==Transformation Processes==
+
==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.
  
 +
'''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: 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)]]
  
{| class="wikitable" style="float:right; margin-left:10px;text-align:center;"
+
'''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>.
|+Table 2.  Advantages and limitations of TCP treatment technologies
+
[[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"/>]]
|-
 
! Technology
 
! Advantages
 
! Limitations
 
|-
 
| ZVZ
 
| style="text-align:left;" |
 
* Can degrade TCP at relatively high and low concentrations
 
* Faster reaction rates than ZVI
 
* Material is commercially available
 
| style="text-align:left;" |
 
* Higher cost than ZVI
 
* Difficult to distribute in subsurface ''in situ'' applications
 
|-
 
| Groundwater</br>Extraction and</br>Treatment
 
| style="text-align:left;" |
 
* Can cost-effectively capture and treat larger, more dilute</br>groundwater plumes than ''in situ'' technologies
 
* Well understood and widely applied technology
 
| style="text-align:left;" |
 
* Requires construction, operation and maintenance of</br>aboveground treatment infrastructure
 
* Typical technologies (e.g. GAC) may be expensive due</br>to treatment inefficiencies
 
|-
 
| ZVI
 
| style="text-align:left;" |
 
* Can degrade TCP at relatively high and low concentrations
 
* Lower cost than ZVZ
 
* Material is commercially available
 
| style="text-align:left;" |
 
* Lower reactivity than ZVZ, therefore may require higher</br>ZVI volumes or thicker PRBs
 
* Difficult to distribute in subsurface ''in situ'' applications
 
|-
 
| ISCO
 
| style="text-align:left;" |
 
* Can degrade TCP at relatively high and low concentrations
 
* Strategies to distribute amendments ''in situ'' are well established
 
* Material is commercially available
 
| style="text-align:left;" |
 
* Most effective oxidants (e.g., base-activated or heat-activated</br>persulfate) are complex to implement
 
* Secondary water quality impacts (e.g., high pH, sulfate, </br>hexavalent chromium) may limit ability to implement
 
|-
 
| ''In Situ''</br>Bioremediation
 
| style="text-align:left;" |
 
* Can degrade TCP at moderate to high concentrations
 
* Strategies to distribute amendments ''in situ'' are well established
 
* Materials are commercially available and inexpensive
 
| style="text-align:left;" |
 
* Slower reaction rates than ZVZ or ISCO
 
|}
 
  
 +
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.
  
There&nbsp;are&nbsp;two&nbsp;main&nbsp;approaches to downscaling. One method, commonly referred to as “statistical downscaling”, uses the empirical-statistical relationships between large-scale weather phenomena and historical local weather data. In this method, these statistical relationships are applied to output generated by global climate models. A second method uses physics-based numerical models (regional-scale climate models or RCMs) of weather and climate that operate over a limited region of the earth (e.g., North America) and at spatial resolutions that are typically 3 to 10 times finer than the global-scale climate models. This method is known as “dynamical downscaling”.  These regional-scale climate models are similar to the global models with respect to their reliance on the principles of physics, but because they operate over only part of the earth, they require information about what is coming in from the rest of the earth as well as what is going out of the limited region of the model. This is generally obtained from a global model.  The primary differences between statistical and dynamical downscaling methods are summarized in Table 1.
+
==Column Test Demonstration Studies==
 +
PFAS-specific adaptations were tested in column test demonstration studies, which included triplicate implementation of Method 1314A in three AFFF-impacted site soils.
 +
[[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.]]
  
It&nbsp;is&nbsp;important&nbsp;to&nbsp;realize that there is no “best” downscaling method or dataset, and that the best method/dataset for a given problem depends on that problem’s specific needs. Several data products based on downscaling higher level spatial data are available ([https://cida.usgs.gov/gdp/ USGS], [http://maca.northwestknowledge.net/ MACA], [https://www.narccap.ucar.edu/ NARCCAP], [https://na-cordex.org/ CORDEX-NA]). The appropriate method and dataset to use depends on the intended application. The method selected should be able to credibly resolve spatial and temporal scales relevant for the application. For example, to develop a risk analysis of frequent flooding, the data product chosen should include precipitation at greater than a diurnal frequency and over multi-decadal timescales. This kind of product is most likely to be available using the dynamical downscaling method.  SERDP reviewed the various advantages and disadvantages of using each type of downscaling method and downscaling dataset, and developed a recommended process that is publicly available<ref name="Kotamarthi2016"/>. In general, the following recommendations should be considered in order to pick the right downscaled dataset for a given analysis:
+
'''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.
  
* When a problem depends on using a large number of climate models and emission scenarios to perform preliminary assessments and to understand the uncertainty range of projections, then using a statistical downscaled dataset is recommended.
+
==LEAF Screening Evaluations==
* When the assessment needs a more extensive parameter list or is analyzing a region with few long-term observational data, dynamically downscaled climate change projections are recommended.
+
[[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.
  
==Uncertainty in Projections==
+
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 leachingExample 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.  
{| class="wikitable" style="float:right; margin-left:10px;text-align:center;"
 
|+Table 2.  Downscaling model characteristics and output<ref name="Kotamarthi2016"/>
 
|-
 
!Model or</br>Dataset Name
 
!Model<br />Method
 
!Output<br />Variables
 
!Output<br />Format
 
!Spatial</br>Resolution
 
!Time</br>Resolution
 
|-
 
| colspan="6" style="text-align: left; background-color:white;" |'''Statistical Downscaled Datasets'''
 
|-
 
| [https://worldclim.org/data/index.html WorldClim]<ref name="Hijmans2005">Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. and Jarvis, A., 2005. Very High Resolution Interpolated Climate Surfaces for Global Land Areas. International Journal of Climatology: A Journal of the Royal Meteorological Society, 25(15), pp 1965-1978. [https://doi.org/10.1002/joc.1276 DOI: 10.1002/joc.1276]</ref>
 
|Delta||T(min, max,</br>avg), Pr||NetCDF||grid: 30 arc sec to</br>10 arc min||month
 
|-
 
| Bias Corrected / Spatial</br>Disaggregation (BCSD)<ref name="Wood2002">Wood, A.W., Maurer, E.P., Kumar, A. and Lettenmaier, D.P., 2002. Long‐range experimental hydrologic forecasting for the eastern United States. Journal of Geophysical Research: Atmospheres, 107(D20), 4429, pp. ACL6 1-15. [https://doi.org/10.1029/2001JD000659 DOI:10.1029/2001JD000659]&nbsp;&nbsp; Free access article available from: [https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2001JD000659 American Geophysical Union]&nbsp;&nbsp; [[Media: Wood2002.pdf | Report.pdf ]]</ref>
 
|Empirical Quantile</br>Mapping||Runoff,</br>Streamflow||NetCDF||grid: 7.5 arc min||day
 
|-
 
| [https://cida.usgs.gov/thredds/catalog.html?dataset=dcp Asynchronous Regional Regression</br>Model (ARRM v.1)]<ref name="Stoner2013">Stoner, A.M., Hayhoe, K., Yang, X., and Wuebbles, D.J., 2013. An Asynchronous Regional Regression Model for Statistical Downscaling of Daily Climate Variables. International Journal of Climatology, 33(11), pp. 2473-2494[https://doi.org/10.1002/joc.3603 DOI:10.1002/joc.3603]</ref>
 
|Parameterized</br>Quantile Mapping||T(min, max), Pr||NetCDF||stations plus</br>grid: 7.5 arc min||day
 
|-
 
| [https://sdsm.org.uk/ Statistical Downscaling Model (SDSM)]<ref name="Wilby2013">Wilby, R.L., and Dawson, C.W., 2013. The Statistical DownScaling Model: insights from one decade of application. International Journal of Climatology, 33(7), pp. 1707-1719. [https://doi.org/10.1002/joc.3544 DOI: 10.1002/joc.3544]</ref>
 
|Weather Generator||T(min, max), Pr||PC Code||stations||day
 
|-
 
| [https://climate.northwestknowledge.net/MACA/ Multivariate Adaptive</br>Constructed Analogs (MACA)]<ref name="Hidalgo2008">Hidalgo, H.G., Dettinger, M.D. and Cayan, D.R., 2008. Downscaling with Constructed Analogues: Daily Precipitation and Temperature Fields Over the United States. California Energy Commission PIER Final Project, Report CEC-500-2007-123. [[Media: Hidalgo2008.PDF | Report.pdf]]</ref>
 
|Constructed Analogues||10 Variables||NetCDF||grid: 2.5 arc min||day
 
|-
 
| [http://loca.ucsd.edu/ Localized Constructed Analogs (LOCA)]<ref name="Pierce2013">Pierce, D.W., Cayan, D.R. and Thrasher, B.L., 2014. Statistical Downscaling Using Localized Constructed Analogs (LOCA). Journal of Hydrometeorology, 15(6), pp. 2558-2585. [https://doi.org/10.1175/JHM-D-14-0082.1 DOI: 10.1175/JHM-D-14-0082.1]&nbsp;&nbsp; Free access article available from: [https://journals.ametsoc.org/view/journals/hydr/15/6/jhm-d-14-0082_1.xml American Meteorological Society].&nbsp;&nbsp; [[Media: Pierce2014.pdf | Report.pdf]]</ref>
 
|Constructed Analogues||T(min, max), Pr||NetCDF||grid: 3.75 arc min||day
 
|-
 
| [https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-dcp30 NASA Earth Exchange Downscaled</br>Climate Projections (NEX-DCP30)]<ref name="Wood2002"/>
 
|Bias Correction /</br>Spatial Disaggregation||T(min, max), Pr||NetCDF||grid: 30 arc sec||month
 
|-
 
| colspan="6" style="text-align: left; background-color:white;" |'''Dynamical Downscaled Datasets'''
 
|-
 
| [http://www.narccap.ucar.edu/index.html North American Regional Climate</br>Change Assessment Program (NARCCAP)]<ref name="Mearns2009">Mearns, L.O., Gutowski, W., Jones, R., Leung, R., McGinnis, S., Nunes, A. and Qian, Y., 2009. A Regional Climate Change Assessment Program for North America. Eos, Transactions, American Geophysical Union, 90(36), p.311.  [https://doi.org/10.1029/2009EO360002 DOI: 10.1029/2009EO360002]&nbsp;&nbsp; Free access article from: [https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2009EO360002 American Geophysical Union]&nbsp;&nbsp; [[Media: Mearns2009.pdf  | Report.pdf]]</ref>
 
|Multiple Models||49 Variables||NetCDF||grid: 30 arc min||3 hours
 
|-
 
| [https://cordex.org/about/ Coordinated Regional Climate</br>Downscaling Experiment (CORDEX)]<ref name="Giorgi2009">Giorgi, F., Jones, C., and Asrar, G.R., 2009. Addressing climate information needs at the regional level: the CORDEX framework. World Meteorological Organization (WMO) Bulletin, 58(3), pp. 175-183. Free access article from: [https://public.wmo.int/en/bulletin/addressing-climate-information-needs-regional-level-cordex-framework World Meteorological Organization]&nbsp;&nbsp; [[Media: Giorgi2009.pdf | Report.pdf]]</ref>
 
|Multiple Models||66 Variables||NetCDF||grid: 30 arc min||3 hours
 
|-
 
| [https://esrl.noaa.gov/gsd/wrfportal/ Strategic Environmental Research and</br>Development Program (SERDP)]<ref name="Wang2015">Wang, J., and Kotamarthi, V.R., 2015. High‐resolution dynamically downscaled projections of precipitation in the mid and late 21st century over North America. Earth's Future, 3(7), pp. 268-288.  [https://doi.org/10.1002/2015EF000304 DOI: 10.1002/2015EF000304]&nbsp;&nbsp; Free access article from: [https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2015EF000304 American Geophysical Union]&nbsp;&nbsp; [[Media: Wang2015.pdf | Report.pdf]]</ref>
 
|Weather Research and</br>Forecasting (WRF v3.3)||80+ Variables||NetCDF||grid: 6.5 arc min||3 hours
 
|}
 
A&nbsp;primary&nbsp;cause&nbsp;of&nbsp;uncertainty in climate change projections, especially beyond 30 years into the future, is the uncertainty in the greenhouse gas (GHG) emission scenarios used to make climate model projections. The best method of accounting for this type of uncertainty is to apply a climate change model to multiple GHG emission scenarios (see also: [[Wikipedia: Representative Concentration Pathway]]).  
 
  
The&nbsp;uncertainties&nbsp;in&nbsp;climate&nbsp;projections over shorter timescales, less than 30 years out, are dominated by something known as “internal variability” in the models. Different approaches are used to address the uncertainty from internal variability<ref name="Kotamarthi2021"/>. A third type of uncertainty in climate modeling, known as scientific uncertainty, comes from our inability to numerically solve every aspect of the complex earth system. We expect this scientific uncertainty to decrease as we understand more of the earth system and improve its representation in our numerical modelsAs discussed in [[Climate Change Primer]], numerical experiments based on global climate models are designed to address these uncertainties in various ways. Downscaling methods evaluate this uncertainty by using several independent regional climate models to generate future projections, with the expectation that each of these models will capture some aspects of the physics better than the others, and that by using several different models, we can estimate the range of this uncertainty.  Thus, the commonly accepted methods for accounting for uncertainty in climate model projections are either using projections from one model for several emission scenarios, or applying multiple models to project a single scenario.
+
==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 risksHowever, 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
  
A comparison of the currently available methods and their characteristics is provided in Table 2 (adapted from Kotamarthi et al., 2016<ref name="Kotamarthi2016"/>).  The table lists the various methodologies and models used for producing downscaled data, and the climate variables that these methods produce.  These datasets are mostly available for download from the data servers and websites listed in the table and in a few cases by contacting the respective source organizations. 
+
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
  
The most popular and widely used format for atmospheric and climate science is known as [[Wikipedia:NetCDF | NetCDF]], which stands for Network Common Data Form. NetCDF is a self-describing data format that saves data in a binary format. The format is self-describing in that a metadata listing is part of every file that describes all the data attributes, such as dimensions, units and data size and in principal should not need additional information to extract the required data for analysis with the right software.  However, specially built software for reading and extracting data from these binary files is necessary for making visualizations and further analysis. Software packages for reading and writing NetCDF datasets and for generating visualizations from these datasets are widely available and obtained free of cost ([https://www.unidata.ucar.edu/software/netcdf/docs/ NetCDF-tools]). Popular geospatial analysis tools such as ARC-GIS, statistical packages such as ‘R’ and programming languages such as Fortran, C++, and Python have built in libraries that can be used to directly read NetCDF files for visualization and analysis.
+
==Other LEAF Resources==
<br clear="left" />
+
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==
 
<references />
 
<references />
 +
 
==See Also==
 
==See Also==
 
[https://serdp-estcp.org/Program-Areas/Resource-Conservation-and-Resiliency/Infrastructure-Resiliency/Vulnerability-and-Impact-Assessment/RC-2242/(language)/eng-US Climate Change Impacts to Department of Defense Installations, SERDP Project RC-2242]
 

Latest revision as of 15:25, 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., 2025[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.

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.

File:GuelfoFig1.png
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 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].

File:GuelfoFig2.png
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]

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

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

File:GuelfoFig3.png
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.

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

File:GuelfoFig4.png
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