Difference between revisions of "User:Jhurley/sandbox"

From Enviro Wiki
Jump to: navigation, search
(→‎Lysimeters for Measuring PFAS Concentrations in the Vadose Zone)
 
(936 intermediate revisions by the same user not shown)
Line 1: Line 1:
−
==1,2,3-Trichloropropane (TCP)==
+
==Lysimeters for Measuring PFAS Concentrations in the Vadose Zone==  
−
[[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.
+
[[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) | PFAS]] are frequently introduced to the environment through soil surface applications which then transport through the vadose zone to reach underlying groundwater receptors. Due to their unique properties and resulting transport and retention behaviors, PFAS in the vadose zone can be a persistent contaminant source to underlying groundwater systems. Determining the fraction of PFAS present in the mobile porewater relative to the total concentrations in soils is critical to understanding the risk posed by PFAS in vadose zone source areas. Lysimeters are instruments that have been used by agronomists and vadose zone researchers for decades to determine water flux and solute concentrations in unsaturated porewater. Lysimeters have recently been developed as a critical tool for field investigations and characterizations of PFAS impacted source zones.  
 
<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 Transport and Fate]]
−
*[[Dr. Paul Tratnyek | Paul G. Tratnyek]]
+
*[[PFAS Toxicology and Risk Assessment]]
−
*John Merrill
+
*[[Mass Flux and Mass Discharge]]
−
*Alyssa Saito
 
−
*Lea Kane
 
−
*Eric Suchomel
 
−
*[[Dr. Rula Deeb | Rula Deeb]]
 
  
−
'''Key Resource(s):'''
+
'''Contributors:''' Dr. John F. Stults, Dr. Charles Schaefer
−
*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:'''
 +
*Assessment of PFAS in Collocated Soil and Porewater Samples at an AFFF-Impacted Source Zone: Field-Scale Validation of Suction Lysimeters<ref name="AndersonEtAl2022"/>
 +
*PFAS Concentrations in Soil versus Soil Porewater: Mass Distributions and the Impact of Adsorption at Air-Water Interfaces<ref name="BrusseauGuo2022"/>
 +
*Using Suction Lysimeters for Determining the Potential of Per- and Polyfluoroalkyl Substances to Leach from Soil to Groundwater: A Review<ref name="CostanzaEtAl2025"/>
 +
*Use of Lysimeters for Monitoring Soil Water Balance Parameters and Nutrient Leaching<ref name="MeissnerEtAl2020"/>
 +
*PFAS Porewater Concentrations in Unsaturated Soil: Field and Laboratory Comparisons Inform on PFAS Accumulation at Air-Water Interfaces<ref name="SchaeferEtAl2024"/>
  
−
==Downscaling of Global Climate Models==
+
==Introduction==
−
Some communities and businesses have begun to improve their resilience to climate change by building adaptation plans based on national scale climate datatsets ([https://unfccc.int/topics/adaptation-and-resilience/workstreams/national-adaptation-plans National Adaptation Plans]), regional datasets ([https://www.dec.ny.gov/docs/administration_pdf/crrafloodriskmgmtgdnc.pdf New York State Flood Risk Management Guidance]<ref name="NYDEC2020">New York State Department of Environmental Conservation, 2020. New York State Flood Risk Management Guidance for Implementation of the Community Risk and Resiliency Act. Free download from: [https://www.dec.ny.gov/docs/administration_pdf/crrafloodriskmgmtgdnc.pdf New York State]&nbsp;&nbsp; [[Media: NewYorkState2020.pdf | Report.pdf]]</ref>), and datasets generated at local spatial resolutions. Resilience to the changing climate has also been identified by the US Department of Defense (DoD) as a necessary part of the installation planning and basing process ([https://media.defense.gov/2019/Jan/29/2002084200/-1/-1/1/CLIMATE-CHANGE-REPORT-2019.PDF DoD Report on Effects of a Changing Climate]<ref name="DoD2019">US Department of Defense, 2019. Report on Effects of a Changing Climate to the Department of Defense. Free download from: [https://media.defense.gov/2019/Jan/29/2002084200/-1/-1/1/CLIMATE-CHANGE-REPORT-2019.PDF DoD]&nbsp;&nbsp; [[Media: DoD2019.PDF | Report.pdf]]</ref>). More than 79 installations were identified as facing potential threats from climate change. The threats faced due to changing climate include recurrent flooding, droughts, desertification, wildfires and thawing permafrost.  
+
Lysimeters are devices that are placed in the subsurface above the groundwater table to monitor the movement of water through the soil<ref name="GossEhlers2009">Goss, M.J., Ehlers, W., 2009. The Role of Lysimeters in the Development of Our Understanding of Soil Water and Nutrient Dynamics in Ecosystems. Soil Use and Management, 25(3), pp. 213–223. [https://doi.org/10.1111/j.1475-2743.2009.00230.x doi: 10.1111/j.1475-2743.2009.00230.x]</ref><ref>Pütz, T., Fank, J., Flury, M., 2018. Lysimeters in Vadose Zone Research. Vadose Zone Journal, 17 (1), pp. 1-4. [https://doi.org/10.2136/vzj2018.02.0035 doi: 10.2136/vzj2018.02.0035]&nbsp; [[Media: PutzEtAl2018.pdf | Open Access Article]]</ref><ref name="CostanzaEtAl2025">Costanza, J., Clabaugh, C.D., Leibli, C., Ferreira, J., Wilkin, R.T., 2025. Using Suction Lysimeters for Determining the Potential of Per- and Polyfluoroalkyl Substances to Leach from Soil to Groundwater: A Review. Environmental Science and Technology, 59(9), pp. 4215-4229. [https://doi.org/10.1021/acs.est.4c10246 doi: 10.1021/acs.est.4c10246]</ref>. Lysimeters have historically been used in agricultural sciences for monitoring nutrient or contaminant movement, soil moisture release curves, natural drainage patterns, and dynamics of plant-water interactions<ref name="GossEhlers2009"/><ref>Bergström, L., 1990. Use of Lysimeters to Estimate Leaching of Pesticides in Agricultural Soils. Environmental Pollution, 67 (4), 325–347. [https://doi.org/10.1016/0269-7491(90)90070-S doi: 10.1016/0269-7491(90)90070-S]</ref><ref>Dabrowska, D., Rykala, W., 2021. A Review of Lysimeter Experiments Carried Out on Municipal Landfill Waste. Toxics, 9(2), Article 26. [https://doi.org/10.3390/toxics9020026 doi: 10.3390/toxics9020026]&nbsp; [[Media: Dabrowska Rykala2021.pdf | Open Access Article]]</ref><ref>Fernando, S.U., Galagedara, L., Krishnapillai, M., Cuss, C.W., 2023. Lysimeter Sampling System for Optimal Determination of Trace Elements in Soil Solutions. Water, 15(18), Article 3277. [https://doi.org/10.3390/w15183277 doi: 10.3390/w15183277]&nbsp; [[Media: FernandoEtAl2023.pdf | Open Access Article]]</ref><ref name="MeissnerEtAl2020">Meissner, R., Rupp, H., Haselow, L., 2020. Use of Lysimeters for Monitoring Soil Water Balance Parameters and Nutrient Leaching. In: Climate Change and Soil Interactions. Elsevier, pp. 171-205. [https://doi.org/10.1016/B978-0-12-818032-7.00007-2 doi: 10.1016/B978-0-12-818032-7.00007-2]</ref><ref name="RogersMcConnell1993">Rogers, R.D., McConnell, J.W. Jr., 1993. Lysimeter Literature Review, Nuclear Regulatory Commission Report Numbers: NUREG/CR--6073, EGG--2706. [https://www.osti.gov/] ID: 10183270. [https://doi.org/10.2172/10183270 doi: 10.2172/10183270]&nbsp; [[Media: RogersMcConnell1993.pdf | Open  Access Article]]</ref><ref>Sołtysiak, M., Rakoczy, M., 2019. An Overview of the Experimental Research Use of Lysimeters. Environmental and Socio-Economic Studies, 7(2), pp. 49-56. [https://doi.org/10.2478/environ-2019-0012 doi: 10.2478/environ-2019-0012]&nbsp; [[Media: SołtysiakRakoczy2019.pdf | Open Access Article]]</ref><ref name="Stannard1992">Stannard, D.I., 1992. Tensiometers—Theory, Construction, and Use. Geotechnical Testing Journal, 15(1), pp. 48-58. [https://doi.org/10.1520/GTJ10224J doi: 10.1520/GTJ10224J]</ref><ref name="WintonWeber1996">Winton, K., Weber, J.B., 1996. A Review of Field Lysimeter Studies to Describe the Environmental Fate of Pesticides. Weed Technology, 10(1), pp. 202-209. [https://doi.org/10.1017/S0890037X00045929 doi: 10.1017/S0890037X00045929]</ref>. Recently, there has been strong interest in the use of lysimeters to measure and monitor movement of per- and polyfluoroalkyl substances (PFAS) through the vadose zone<ref name="Anderson2021">Anderson, R.H., 2021. The Case for Direct Measures of Soil-to-Groundwater Contaminant Mass Discharge at AFFF-Impacted Sites. Environmental Science and Technology, 55(10), pp. 6580-6583. [https://doi.org/10.1021/acs.est.1c01543 doi: 10.1021/acs.est.1c01543]</ref><ref name="AndersonEtAl2022">Anderson, R.H., Feild, J.B., Dieffenbach-Carle, H., Elsharnouby, O., Krebs, R.K., 2022. Assessment of PFAS in Collocated Soil and Porewater Samples at an AFFF-Impacted Source Zone: Field-Scale Validation of Suction Lysimeters. Chemosphere, 308(1), Article 136247. [https://doi.org/10.1016/j.chemosphere.2022.136247 doi: 10.1016/j.chemosphere.2022.136247]</ref><ref name="SchaeferEtAl2024">Schaefer, C.E., Nguyen, D., Fang, Y., Gonda, N., Zhang, C., Shea, S., Higgins, C.P., 2024. PFAS Porewater Concentrations in Unsaturated Soil: Field and Laboratory Comparisons Inform on PFAS Accumulation at Air-Water Interfaces. Journal of Contaminant Hydrology, 264, Article 104359. [https://doi.org/10.1016/j.jconhyd.2024.104359 doi: 10.1016/j.jconhyd.2024.104359]&nbsp; [[Media: SchaeferEtAl2024.pdf | Open Access Manuscript]]</ref><ref name="SchaeferEtAl2023">Schaefer, C.E., Lavorgna, G.M., Lippincott, D.R., Nguyen, D., Schaum, A., Higgins, C.P., Field, J., 2023. Leaching of Perfluoroalkyl Acids During Unsaturated Zone Flushing at a Field Site Impacted with Aqueous Film Forming Foam. Environmental Science and Technology, 57(5), pp. 1940-1948. [https://doi.org/10.1021/acs.est.2c06903 doi: 10.1021/acs.est.2c06903]</ref><ref name="SchaeferEtAl2022">Schaefer, C.E., Lavorgna, G.M., Lippincott, D.R., Nguyen, D., Christie, E., Shea, S., O’Hare, S., Lemes, M.C.S., Higgins, C.P., Field, J., 2022. A Field Study to Assess the Role of Air-Water Interfacial Sorption on PFAS Leaching in an AFFF Source Area. Journal of Contaminant Hydrology, 248, Article 104001. [https://doi.org/10.1016/j.jconhyd.2022.104001 doi: 10.1016/j.jconhyd.2022.104001]&nbsp; [[Media: SchaeferEtAl2022.pdf | Open Access Manuscript]]</ref><ref name="QuinnanEtAl2021">Quinnan, J., Rossi, M., Curry, P., Lupo, M., Miller, M., Korb, H., Orth, C., Hasbrouck, K., 2021. Application of PFAS-Mobile Lab to Support Adaptive Characterization and Flux-Based Conceptual Site Models at AFFF Releases. Remediation, 31(3), pp. 7-26. [https://doi.org/10.1002/rem.21680 doi: 10.1002/rem.21680]</ref>. PFAS are frequently introduced to the environment through land surface application and have been found to be strongly retained within the upper 5 feet of soil<ref name="BrusseauEtAl2020">Brusseau, M.L., Anderson, R.H., Guo, B., 2020. PFAS Concentrations in Soils: Background Levels versus Contaminated Sites. Science of The Total Environment, 740, Article 140017. [https://doi.org/10.1016/j.scitotenv.2020.140017 doi: 10.1016/j.scitotenv.2020.140017]</ref><ref name="BiglerEtAl2024">Bigler, M.C., Brusseau, M.L., Guo, B., Jones, S.L., Pritchard, J.C., Higgins, C.P., Hatton, J., 2024. High-Resolution Depth-Discrete Analysis of PFAS Distribution and Leaching for a Vadose-Zone Source at an AFFF-Impacted Site. Environmental Science and Technology, 58(22), pp. 9863-9874. [https://doi.org/10.1021/acs.est.4c01615 doi: 10.1021/acs.est.4c01615]</ref>. PFAS recalcitrance in the vadose zone means that environmental program managers and consultants need a cost-effective way of monitoring concentration conditions within the vadose zone. Repeated soil sampling and extraction processes are time consuming and only give a representative concentration of total PFAS in the matrix<ref name="NickersonEtAl2020">Nickerson, A., Maizel, A.C., Kulkarni, P.R., Adamson, D.T., Kornuc, J. J., Higgins, C.P., 2020. Enhanced Extraction of AFFF-Associated PFASs from Source Zone Soils. Environmental Science and Technology, 54(8), pp. 4952-4962. [https://doi.org/10.1021/acs.est.0c00792 doi: 10.1021/acs.est.0c00792]</ref>, not what is readily transportable in mobile porewater<ref name="SchaeferEtAl2023"/><ref name="StultsEtAl2024">Stults, J.F., Schaefer, C.E., Fang, Y., Devon, J., Nguyen, D., Real, I., Hao, S., Guelfo, J.L., 2024. Air-Water Interfacial Collapse and Rate-Limited Solid Desorption Control Perfluoroalkyl Acid Leaching from the Vadose Zone. Journal of Contaminant Hydrology, 265, Article 104382. [https://doi.org/10.1016/j.jconhyd.2024.104382 doi: 10.1016/j.jconhyd.2024.104382]&nbsp; [[Media: StultsEtAl2024.pdf | Open Access Manuscript]]</ref><ref name="StultsEtAl2023">Stults, J.F., Choi, Y.J., Rockwell, C., Schaefer, C.E., Nguyen, D.D., Knappe, D.R.U., Illangasekare, T.H., Higgins, C.P., 2023. Predicting Concentration- and Ionic-Strength-Dependent Air–Water Interfacial Partitioning Parameters of PFASs Using Quantitative Structure–Property Relationships (QSPRs). Environmental Science and Technology, 57(13), pp. 5203-5215. [https://doi.org/10.1021/acs.est.2c07316 doi: 10.1021/acs.est.2c07316]</ref><ref name="BrusseauGuo2022">Brusseau, M.L., Guo, B., 2022. PFAS Concentrations in Soil versus Soil Porewater: Mass Distributions and the Impact of Adsorption at Air-Water Interfaces. Chemosphere, 302, Article 134938. [https://doi.org/10.1016/j.chemosphere.2022.134938 doi: 10.1016/j.chemosphere.2022.134938]&nbsp; [[Media: BrusseauGuo2022.pdf | Open Access Manuscript]]</ref>. Fortunately, lysimeters have been found to be a viable option for monitoring the concentration of PFAS in the mobile porewater phase in the vadose zone<ref name="Anderson2021"/><ref name="AndersonEtAl2022"/>. Note that while some lysimeters, known as weighing lysimeters, can directly measure water flux, the most commonly utilized lysimeters in PFAS investigations only provide measurements of porewater concentrations.
  
−
Assessing the threats climate change poses at regional and local scales requires data with higher spatial resolution than is currently available from global climate models. Global-scale climate models typically have spatial resolutions of 100 to 300 km, and output from these models needs to be spatially and/or temporally disaggregated in order to be useful in performing assessments at smaller scales. The process of producing higher spatial-temporal resolution climate model output from coarser global climate model outputs is referred to as “downscaling” and results in climate change projections (datasets) at scales that are useful for evaluating potential threats to regional and local communities and businesses. These datasets provide information on temperature, precipitation and a variety of other climate variables for current and future climate conditions under various greenhouse gas (GHG) emission scenarios. There are a variety of web-based tools available for accessing these datasets to evaluate potential climate change impacts at regional and local scales.
+
==PFAS Background==
 +
PFAS are a broad class of chemicals with highly variable chemical structures<ref>Moody, C.A., Field, J.A., 1999. Determination of Perfluorocarboxylates in Groundwater Impacted by Fire-Fighting Activity. Environmental Science and Technology, 33(16), pp. 2800-2806. [https://doi.org/10.1021/es981355+ doi: 10.1021/es981355+]</ref><ref name="MoodyField2000">Moody, C.A., Field, J.A., 2000. Perfluorinated Surfactants and the Environmental Implications of Their Use in Fire-Fighting Foams. Environmental Science and Technology, 34(18), pp. 3864-3870. [https://doi.org/10.1021/es991359u doi: 10.1021/es991359u]</ref><ref name="GlügeEtAl2020">Glüge, J., Scheringer, M., Cousins, I.T., DeWitt, J.C., Goldenman, G., Herzke, D., Lohmann, R., Ng, C.A., Trier, X., Wang, Z., 2020. An Overview of the Uses of Per- and Polyfluoroalkyl Substances (PFAS). Environmental Science: Processes and Impacts, 22(12), pp. 2345-2373. [https://doi.org/10.1039/D0EM00291G doi: 10.1039/D0EM00291G]&nbsp; [[Media: GlügeEtAl2020.pdf | Open Access Article]]</ref>. One characteristic feature of PFAS is that they are fluorosurfactants, distinct from more traditional hydrocarbon surfactants<ref name="MoodyField2000"/><ref name="Brusseau2018">Brusseau, M.L., 2018. Assessing the Potential Contributions of Additional Retention Processes to PFAS Retardation in the Subsurface. Science of The Total Environment, 613-614, pp. 176-185. [https://doi.org/10.1016/j.scitotenv.2017.09.065 doi: 10.1016/j.scitotenv.2017.09.065]&nbsp; [[Media: Brusseau2018.pdf | Open Access Manuscript]]</ref><ref>Dave, N., Joshi, T., 2017. A Concise Review on Surfactants and Its Significance. International Journal of Applied Chemistry, 13(3), pp. 663-672. [https://doi.org/10.37622/IJAC/13.3.2017.663-672 doi: 10.37622/IJAC/13.3.2017.663-672]&nbsp; [[Media: DaveJoshi2017.pdf  | Open Access Article]]</ref><ref>García, R.A., Chiaia-Hernández, A.C., Lara-Martin, P.A., Loos, M., Hollender, J., Oetjen, K., Higgins, C.P., Field, J.A., 2019. Suspect Screening of Hydrocarbon Surfactants in Afffs and Afff-Contaminated Groundwater by High-Resolution Mass Spectrometry. Environmental Science and Technology, 53(14), pp. 8068-8077. [https://doi.org/10.1021/acs.est.9b01895 doi: 10.1021/acs.est.9b01895]</ref>. Fluorosurfactants typically have a fully or partially fluorinated, hydrophobic tail with ionic (cationic, zwitterionic, or anionic) head group that is hydrophilic<ref name="MoodyField2000"/><ref name="GlügeEtAl2020"/>. The hydrophobic tail and ionic head group mean PFAS are very stable at hydrophobic adsorption interfaces when present in the aqueous phase<ref>Krafft, M.P., Riess, J.G., 2015. Per- and Polyfluorinated Substances (PFASs): Environmental Challenges. Current Opinion in Colloid and Interface Science, 20(3), pp. 192-212. [https://doi.org/10.1016/j.cocis.2015.07.004 doi: 10.1016/j.cocis.2015.07.004]</ref>. Examples of these interfaces include naturally occurring organic matter in soils and the air-water interface in the vadose zone<ref>Schaefer, C.E., Culina, V., Nguyen, D., Field, J., 2019. Uptake of Poly- and Perfluoroalkyl Substances at the Air–Water Interface. Environmental Science and Technology, 53(21), pp. 12442-12448. [https://doi.org/10.1021/acs.est.9b04008 doi: 10.1021/acs.est.9b04008]</ref><ref>Lyu, Y., Brusseau, M.L., Chen, W., Yan, N., Fu, X., Lin, X., 2018. Adsorption of PFOA at the Air–Water Interface during Transport in Unsaturated Porous Media. Environmental Science and Technology, 52(14), pp. 7745-7753. [https://doi.org/10.1021/acs.est.8b02348 doi: 10.1021/acs.est.8b02348]</ref><ref>Costanza, J., Arshadi, M., Abriola, L.M., Pennell, K.D., 2019. Accumulation of PFOA and PFOS at the Air-Water Interface. Environmental Science and Technology Letters, 6(8), pp. 487-491. [https://doi.org/10.1021/acs.estlett.9b00355 doi: 10.1021/acs.estlett.9b00355]</ref><ref>Li, F., Fang, X., Zhou, Z., Liao, X., Zou, J., Yuan, B., Sun, W., 2019. Adsorption of Perfluorinated Acids onto Soils: Kinetics, Isotherms, and Influences of Soil Properties. Science of The Total Environment, 649, pp. 504-514. [https://doi.org/10.1016/j.scitotenv.2018.08.209 doi: 10.1016/j.scitotenv.2018.08.209]</ref><ref>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>. Their strong adsorption to both soil organic matter and the air-water interface is a major contributor to elevated concentrations of PFAS observed in the upper 5 feet of the soil column<ref name="BrusseauEtAl2020"/><ref name="BiglerEtAl2024"/>. While several other PFAS partitioning processes exist<ref name="Brusseau2018"/>, adsorption to solid phase soils and air-water interfaces are the two primary processes present at nearly all PFAS sites<ref>Brusseau, M.L., Yan, N., Van Glubt, S., Wang, Y., Chen, W., Lyu, Y., Dungan, B., Carroll, K.C., Holguin, F.O., 2019. Comprehensive Retention Model for PFAS Transport in Subsurface Systems. Water Research, 148, pp. 41-50. [https://doi.org/10.1016/j.watres.2018.10.035 doi: 10.1016/j.watres.2018.10.035]</ref>. The total PFAS mass obtained from a vadose zone soil sample contains the solid phase, air-water interfacial, and aqueous phase PFAS mass, which can be converted to porewater concentrations using Equation 1<ref name="BrusseauGuo2022"/>.</br>
 +
:: <big>'''Equation 1:'''</big>&nbsp;&nbsp; [[File: StultsEq1.png | 400 px]]</br>
 +
Where ''C<sub>p</sub>'' is the porewater concentration, ''C<sub>t</sub>'' is the total PFAS concentration, ''ρ<sub>b</sub>'' is the bulk density of the soil, ''θ<sub>w</sub>'' is the volumetric water content, ''R<sub>d</sub>'' is the PFAS retardation factor, ''K<sub>d</sub>'' is the solid phase adsorption coefficient, ''K<sub>ia</sub>'' is the air-water interfacial adsorption coefficient, and ''A<sub>aw</sub>'' is the air-water interfacial area. The air-water interfacial area of the soil is primarily a function of both the soil properties and the degree of volumetric water saturation in the soil. There are several methods of estimating air-water interfacial areas including thermodynamic functions based on the soil moisture retention curve. However, the thermodynamic function has been shown to underestimate air-water interfacial area<ref name="Brusseau2023">Brusseau, M.L., 2023. Determining Air-Water Interfacial Areas for the Retention and Transport of PFAS and Other Interfacially Active Solutes in Unsaturated Porous Media. Science of The Total Environment, 884, Article 163730. [https://doi.org/10.1016/j.scitotenv.2023.163730 doi: 10.1016/j.scitotenv.2023.163730]&nbsp; [[Media: Brusseau2023.pdf  | Open Access Article]]</ref>, and must typically be scaled using empirical scaling factors. An empirical method recently developed to estimate air-water interfacial area is presented in Equation 2<ref name="Brusseau2023"/>.</br>
 +
:: <big>'''Equation 2:'''</big>&nbsp;&nbsp; [[File: StultsEq2.png | 400 px]]</br>
 +
Where ''S<sub>w</sub>'' is the water phase saturation as a ratio of the water content over the volumetric soil porosity, and ''d<sub>50</sub>'' is the median grain diameter.
  
−
[[File: Kotamarthi2w2Fig1.jpg | thumb |left| 450px | Figure 1. Typical processes and spatial scales of Regional scale Climate Models. The models may calculate circulation in the atmosphere, cloud processes, precipitation, and land-atmospheric and ocean-atmospheric processes on a limited portion of the Earth, with boundary conditions provided by a Global Climate Model.<ref name="Kotamarthi2016"/>]]
+
==Lysimeters Background==
−
==Methods for Downscaling==
+
[[File: StultsFig1.png |thumb|600 px|Figure 1. (a) A field suction lysimeter with labeled parts typically used in field settings – Credit: Bibek Acharya and Dr. Vivek Sharma, UF/IFAS, https://edis.ifas.ufl.edu/publication/AE581. (b) Laboratory suction lysimeters used in Schaefer ''et al.'' 2024<ref name="SchaeferEtAl2024"/>, which employed the use of micro-sampling suction lysimeters. (c) A field lysimeter used in Schaefer ''et al.'' 2023<ref name="SchaeferEtAl2023"/>. (d) Diagram of a drainage wicking lysimeter – Credit: Edaphic Scientific, https://edaphic.com.au/products/water/lysimeter-wick-for-drainage/]]
 +
Lysimeters,&nbsp;generally&nbsp;speaking, refer to instruments which collect water from unsaturated soils<ref name="MeissnerEtAl2020"/><ref name="RogersMcConnell1993"/>. However, there are multiple types of lysimeters which can be employed in field or laboratory settings. There are three primary types of lysimeters relevant to PFAS listed here and shown in Figure 1a-d.
 +
# <u>Suction Lysimeters (Figure 1a,b):</u> These lysimeters are the most relevant for PFAS sampling and are the majority of discussion in this article. These lysimeters operate by extracting liquid from the unsaturated vadose zone by applying negative suction pressure at the sampling head<ref name="CostanzaEtAl2025"/><ref name="SchaeferEtAl2024"/><ref name="QuinnanEtAl2021"/>. The sampling head is typically constructed of porous ceramic or stainless steel. A PVC case or stainless-steel case is attached to the sampling head and extends upward above the ground surface. Suction lysimeters are typically installed between 1 and 9 feet below ground surface, but can extend as deep as 40-60 feet in some cases<ref name="CostanzaEtAl2025"/>. Shallow lysimeters (< 10 feet) are typically installed using a hand auger. For ceramic lysimeters, a silica flour slurry should be placed at the base of the bore hole and allowed to cover the ceramic head before backfilling the hole partially with natural soil. Once the hole is partially backfilled with soil to cover the sampling head, the remainder of the casing should be sealed with hydrated bentonite chips. When sampling events occur, suction is applied at the ground surface using a rubber gasket seal and a hand pump or electric pump. After sufficient porewater is collected (the time for which can vary greatly based on the soil permeability and moisture content), the seal can be removed and a peristaltic pump used to extract liquid from the lysimeter.
 +
# <u>Field Lysimeters (Figure 1c):</u> These large lysimeters can be constructed from plastic or metal sidings. They can range from approximately 2 feet in diameter to as large as several meters in diameter<ref name="MeissnerEtAl2020"/>. Instrumentation such as soil moisture probes and tensiometers, or even multiple suction lysimeters, are typically placed throughout the lysimeter to measure the movement of water and determine characteristic soil moisture release curves<ref name="Stannard1992"/><ref name="WintonWeber1996"/><ref name="SchaeferEtAl2023"/><ref name="SchaeferEtAl2022"/><ref>van Genuchten, M.Th. , 1980. A Closed‐form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils. Soil Science Society of America Journal, 44(5), pp. 892-898. [https://doi.org/10.2136/sssaj1980.03615995004400050002x doi: 10.2136/sssaj1980.03615995004400050002x]</ref>. Water is typically collected at the base of the field lysimeter to determine net recharge through the system. These field lysimeters are intended to represent more realistic, intermediate scale conditions of field systems.
 +
# <u>Drainage Lysimeters (Figure 1d):</u>  Also known as a “wick” lysimeter, these lysimeters typically consist of a hollow cup attached to a spout which protrudes above ground to relieve air pressure from the system and act as a sampling port. The hollow cup typically has filters and wicking devices at the base to collect water from the soil. The cup is filled with natural soil and collects water as it percolates through the vadose zone. These lysimeters are used to directly monitor net recharge from the vadose zone to the groundwater table and could be useful in determining PFAS mass flux.
  
−
{| class="wikitable" style="float:right; margin-left:10px;text-align:center;"
+
==Analysis of PFAS Concentrations in Soil and Porewater==
−
|+Table 1. Physical and chemical properties of TCP
+
{| class="wikitable mw-collapsible" style="float:left; margin-right:20px; text-align:center;"
 +
|+Table 1. Measured and Predicted PFAS Concentrations in Porewater for Select PFAS in Three Different Soils
 
|-
 
|-
−
!Property
+
!Site
−
!Value
+
!PFAS
 +
!Field</br>Porewater</br>Concentration</br>(&mu;g/L)
 +
!Lab Core</br>Porewater</br>Concentration</br>(&mu;g/L)
 +
!Predicted</br>Porewater</br>Concentration</br>(&mu;g/L)
 
|-
 
|-
−
| Chemical Abstracts Service (CAS) Number || 96-18-4
+
|Site A||PFOS||6.2 ± 3.4||3.0 ± 0.37||6.6 ± 3.3
 
|-
 
|-
−
| Physical Description</br>(at room temperature) || Colorless to straw-colored liquid
+
|Site B||PFOS||2.2 ± 2.0||0.78 ± 0.38||2.8
 
|-
 
|-
−
| Molecular weight</br>(g/mol) || 147.43
+
|rowspan="3"|Site C||PFOS||13 ± 4.1||680 ± 460||164 ± 75
 
|-
 
|-
−
| Water solubility at 25°C</br>(mg/L)|| 1,750 (slightly soluble)
+
|8:2 FTS||1.2 ± 0.46||52 ± 13||16 ± 6.0
 
|-
 
|-
−
| Melting point</br>(°C)|| -14.7
+
|PFHpS||0.36 ± 0.051||2.9 ± 2.0||5.9 ± 3.4
−
|-
 
−
| Boiling point</br>(°C) || 156.8
 
−
|-
 
−
| Vapor pressure at 25°C</br>(mm Hg) || 3.10 to 3.69
 
−
|-
 
−
| Density at 20°C (g/cm<sup>3</sup>) || 1.3889
 
−
|-
 
−
| Octanol-water partition coefficient</br>(log''K<sub>ow</sub>'') || 1.98 to 2.27</br>(temperature dependent)
 
−
|-
 
−
| Organic carbon-water partition coefficient</br>(log''K<sub>oc</sub>'') || 1.70 to 1.99</br>(temperature dependent)
 
−
|-
 
−
| Henry’s Law constant at 25°C</br>(atm-m<sup>3</sup>/mol) || 3.17x10<sup>-4</sup> to 3.43x10<sup>-4</sup>
 
 
|}
 
|}
 +
[[File: StultsFig2.png | thumb | 600 px | Figure 2. Field Measured PFAS concentration Data (Orange) and Lab Core Measured Concentration Data (Blue) for four PFAS impacted sites<ref name="AndersonEtAl2022"/>]]
 +
[[File: StultsFig3.png | thumb | 400 px | Figure 3. Measured and predicted data for PFAS concentrations from a single site field lysimeter study. Model predictions both with and without PFAS sorption to the air-water interface were considered<ref name="SchaeferEtAl2023"/>.]]
 +
Schaefer&nbsp;''et&nbsp;al.''<ref name="SchaeferEtAl2024"/>&nbsp;measured&nbsp;PFAS porewater concentrations with field and laboratory suction lysimeters across several sites. Intact cores from the site were collected for soil water extraction using laboratory lysimeters. The lysimeters were used to directly compare field derived measurements of PFAS concentration in the mobile porewater phase. Results from measurements are for four sites presented in Figure 2.
  
−
{| class="wikitable" style="float:right; margin-left:10px;text-align:center;"
+
Data from sites A and B showed reasonably good agreement (within ½ order of magnitude) for most PFAS measured in the systems. At site C, more hydrophobic constituents (> C6 PFAS) tended to have higher concentrations in the lab core than the field site while less hydrophobic constituents (< C6) had higher concentrations in the field than lab cores. Site D showed substantially greater (1 order of magnitude or more) PFAS concentrations measured in the laboratory-collected porewater sample compared to what was measured in the field lysimeters. This discrepancy for the Site D soil can likely be attributed to soil heterogeneity (as indicated by ground penetrating radar) and the fact that the soil consisted of back-filled materials rather than undisturbed native soils.
−
|+Table 2.  Advantages and limitations of TCP treatment technologies
+
−
|-
+
Site&nbsp;C&nbsp;showed&nbsp;elevated PFAS concentrations in the laboratory collected porewater for the more surface-active compounds. This increase was attributed to the soil wetting that occurred at the bench scale, which was reasonably described by the model shown in Equations 1 and 2 (see Table 1<ref name="AndersonEtAl2022"/>). Equations 1 and 2 were also used to predict PFAS porewater concentrations (using porous cup lysimeters) in a highly instrumented test cell<ref name="SchaeferEtAl2023"/>(Figure 3). The ability to predict soil concentrations from recurring porewater samples is critical to the practical application of lysimeters in field settings<ref name="AndersonEtAl2022"/>.
−
! 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
 
−
|}
 
−
 
 
−
 
 
−
 
 
−
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.
 
−
 
 
−
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:
 
  
−
* 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.
+
Results from suction lysimeters studies and field lysimeter studies show that PFAS concentrations in porewater predicted from soil concentrations using Equations 1 and 2 generally have reasonable agreement with measured ''in situ'' porewater data when air-water interfacial partitioning is considered. Results show that for less hydrophobic components like PFOA, the impact of air-water interfacial adsorption is less significant than for highly hydrophobic components like PFOS. The soil for the field lysimeter in Figure 3 was a sandy soil with a relatively low air-water interfacial area. The effect of air-water interfacial partitioning is expected to be much more significant for a greater range of PFAS in soils with high capillary pressure (i.e. silts/clays) with higher associated air-water interfacial areas<ref name="Brusseau2023"/><ref>Peng, S., Brusseau, M.L., 2012. Air-Water Interfacial Area and Capillary Pressure: Porous-Medium Texture Effects and an Empirical Function. Journal of Hydrologic Engineering, 17(7), pp. 829-832. [https://doi.org/10.1061/(asce)he.1943-5584.0000515 doi: 10.1061/(asce)he.1943-5584.0000515]</ref><ref>Brusseau, M.L., Peng, S., Schnaar, G., Costanza-Robinson, M.S., 2006. Relationships among Air-Water Interfacial Area, Capillary Pressure, and Water Saturation for a Sandy Porous Medium. Water Resources Research, 42(3), Article W03501, 5 pages. [https://doi.org/10.1029/2005WR004058 doi: 10.1029/2005WR004058]&nbsp; [[Media: BrusseauEtAl2006.pdf | Free Access Article]]</ref>.
−
* 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.
 
  
−
==Uncertainty in Projections==
+
==Summary and Recommendations==
−
{| class="wikitable" style="float:right; margin-left:10px;text-align:center;"
+
The majority of research with lysimeters for PFAS site investigations has been done using porous cup suction lysimeters<ref name="CostanzaEtAl2025"/><ref name="AndersonEtAl2022"/><ref name="SchaeferEtAl2024"/><ref name="QuinnanEtAl2021"/>. Porous cup suction lysimeters are advantageous because they can be routinely sampled or sampled after specific wetting or drying events much like groundwater wells. This sampling is easier and more efficient than routinely collecting soil samples from the same locations. Co-locating lysimeters with soil samples is important for establishing the baseline soil concentration levels at the lysimeter location and developing correlations between the soil concentrations and the mobile porewater concentration<ref name="CostanzaEtAl2025"/>. Appropriate standard operation procedures for lysimeter installation and operation have been established and have been reviewed in recent literature<ref name="CostanzaEtAl2025"/><ref name="SchaeferEtAl2024"/>. Lysimeters should typically be installed near the source area and just above the maximum groundwater level elevation to obtain accurate results of porewater concentrations year round. Depending upon the geology and vertical PFAS distribution in the soil, multilevel lysimeter installations should also be considered.
−
|+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 models.  As 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.  
 
  
−
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.
+
Results from several lysimeters studies across multiple field sites and modelling analysis has shown that lysimeters can produce reasonable results between field and laboratory studies<ref name="SchaeferEtAl2024"/><ref name="SchaeferEtAl2023"/><ref name="SchaeferEtAl2022"/>. Transient effects of wetting and drying as well as media heterogeneity affects appear to be responsible for some variability and uncertainty in lysimeter based PFAS measurements in the vadose zone. These mobile porewater concentrations can be coupled with effective recharge estimates and simplified modelling approaches to determine mass flux from the vadose zone to the underlying groundwater<ref name="Anderson2021"/><ref name="StultsEtAl2024"/><ref name="BrusseauGuo2022"/><ref>Stults, J.F., Schaefer, C.E., MacBeth, T., Fang, Y., Devon, J., Real, I., Liu, F., Kosson, D., Guelfo, J.L., 2025. Laboratory Validation of a Simplified Model for Estimating Equilibrium PFAS Mass Leaching from Unsaturated Soils. Science of The Total Environment, 970, Article 179036. [https://doi.org/10.1016/j.scitotenv.2025.179036 doi: 10.1016/j.scitotenv.2025.179036]</ref><ref>Smith, J. Brusseau, M.L., Guo, B., 2024. An Integrated Analytical Modeling Framework for Determining Site-Specific Soil Screening Levels for PFAS. Water Research, 252, Article121236. [https://doi.org/10.1016/j.watres.2024.121236 doi: 10.1016/j.watres.2024.121236]</ref>.
  
−
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.  
+
Future research opportunities should address the current key uncertainties related to the use of lysimeters for PFAS investigations, including:
−
<br clear="left" />
+
#<u>Collect larger datasets of PFAS concentrations</u> to determine how transient wetting or drying periods and media type affect PFAS concentrations in the mobile porewater. Some research has shown that non-equilibrium processes can occur in the vadose zone, which can affect grab sample concentration in the porewater at specific time periods.
 +
#<u>More work should be done with flux averaging lysimeters</u> like the drainage cup or wicking lysimeter. These lysimeters can directly measure net recharge and provide time averaged concentrations of PFAS in water over the sampling period. However, there is little work detailing their potential applications in PFAS research, or operational considerations for their use in remedial investigations for PFAS.
 +
#<u>Lysimeters should be coupled with monitoring of wetting and drying</u> in the vadose zone using ''in situ'' soil moisture sensors or tensiometers and groundwater levels. Direct measurements of soil saturation at field sites are vital to directly correlate porewater concentrations with soil concentrations. Similarly, groundwater level fluctuations can inform net recharge estimates. By collecting these data we can continue to improve partitioning and leaching models which can relate porewater concentrations to total PFAS mass in soils and PFAS leaching at field sites.
 +
#<u>Comparisons of various bench-scale leaching or desorption tests to field-based lysimeter data</u> are recommended. The ability to correlate field measurements of PFAS concentrations with estimates of leaching from laboratory studies would provide a powerful method to empirically estimate PFAS leaching from field sites.
  
 
==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 15:50, 15 January 2026

Lysimeters for Measuring PFAS Concentrations in the Vadose Zone

PFAS are frequently introduced to the environment through soil surface applications which then transport through the vadose zone to reach underlying groundwater receptors. Due to their unique properties and resulting transport and retention behaviors, PFAS in the vadose zone can be a persistent contaminant source to underlying groundwater systems. Determining the fraction of PFAS present in the mobile porewater relative to the total concentrations in soils is critical to understanding the risk posed by PFAS in vadose zone source areas. Lysimeters are instruments that have been used by agronomists and vadose zone researchers for decades to determine water flux and solute concentrations in unsaturated porewater. Lysimeters have recently been developed as a critical tool for field investigations and characterizations of PFAS impacted source zones.

Related Article(s):

Contributors: Dr. John F. Stults, Dr. Charles Schaefer

Key Resources:

  • Assessment of PFAS in Collocated Soil and Porewater Samples at an AFFF-Impacted Source Zone: Field-Scale Validation of Suction Lysimeters[1]
  • PFAS Concentrations in Soil versus Soil Porewater: Mass Distributions and the Impact of Adsorption at Air-Water Interfaces[2]
  • Using Suction Lysimeters for Determining the Potential of Per- and Polyfluoroalkyl Substances to Leach from Soil to Groundwater: A Review[3]
  • Use of Lysimeters for Monitoring Soil Water Balance Parameters and Nutrient Leaching[4]
  • PFAS Porewater Concentrations in Unsaturated Soil: Field and Laboratory Comparisons Inform on PFAS Accumulation at Air-Water Interfaces[5]

Introduction

Lysimeters are devices that are placed in the subsurface above the groundwater table to monitor the movement of water through the soil[6][7][3]. Lysimeters have historically been used in agricultural sciences for monitoring nutrient or contaminant movement, soil moisture release curves, natural drainage patterns, and dynamics of plant-water interactions[6][8][9][10][4][11][12][13][14]. Recently, there has been strong interest in the use of lysimeters to measure and monitor movement of per- and polyfluoroalkyl substances (PFAS) through the vadose zone[15][1][5][16][17][18]. PFAS are frequently introduced to the environment through land surface application and have been found to be strongly retained within the upper 5 feet of soil[19][20]. PFAS recalcitrance in the vadose zone means that environmental program managers and consultants need a cost-effective way of monitoring concentration conditions within the vadose zone. Repeated soil sampling and extraction processes are time consuming and only give a representative concentration of total PFAS in the matrix[21], not what is readily transportable in mobile porewater[16][22][23][2]. Fortunately, lysimeters have been found to be a viable option for monitoring the concentration of PFAS in the mobile porewater phase in the vadose zone[15][1]. Note that while some lysimeters, known as weighing lysimeters, can directly measure water flux, the most commonly utilized lysimeters in PFAS investigations only provide measurements of porewater concentrations.

PFAS Background

PFAS are a broad class of chemicals with highly variable chemical structures[24][25][26]. One characteristic feature of PFAS is that they are fluorosurfactants, distinct from more traditional hydrocarbon surfactants[25][27][28][29]. Fluorosurfactants typically have a fully or partially fluorinated, hydrophobic tail with ionic (cationic, zwitterionic, or anionic) head group that is hydrophilic[25][26]. The hydrophobic tail and ionic head group mean PFAS are very stable at hydrophobic adsorption interfaces when present in the aqueous phase[30]. Examples of these interfaces include naturally occurring organic matter in soils and the air-water interface in the vadose zone[31][32][33][34][35]. Their strong adsorption to both soil organic matter and the air-water interface is a major contributor to elevated concentrations of PFAS observed in the upper 5 feet of the soil column[19][20]. While several other PFAS partitioning processes exist[27], adsorption to solid phase soils and air-water interfaces are the two primary processes present at nearly all PFAS sites[36]. The total PFAS mass obtained from a vadose zone soil sample contains the solid phase, air-water interfacial, and aqueous phase PFAS mass, which can be converted to porewater concentrations using Equation 1[2].

Equation 1:   StultsEq1.png

Where Cp is the porewater concentration, Ct is the total PFAS concentration, ρb is the bulk density of the soil, θw is the volumetric water content, Rd is the PFAS retardation factor, Kd is the solid phase adsorption coefficient, Kia is the air-water interfacial adsorption coefficient, and Aaw is the air-water interfacial area. The air-water interfacial area of the soil is primarily a function of both the soil properties and the degree of volumetric water saturation in the soil. There are several methods of estimating air-water interfacial areas including thermodynamic functions based on the soil moisture retention curve. However, the thermodynamic function has been shown to underestimate air-water interfacial area[37], and must typically be scaled using empirical scaling factors. An empirical method recently developed to estimate air-water interfacial area is presented in Equation 2[37].

Equation 2:   StultsEq2.png

Where Sw is the water phase saturation as a ratio of the water content over the volumetric soil porosity, and d50 is the median grain diameter.

Lysimeters Background

Figure 1. (a) A field suction lysimeter with labeled parts typically used in field settings – Credit: Bibek Acharya and Dr. Vivek Sharma, UF/IFAS, https://edis.ifas.ufl.edu/publication/AE581. (b) Laboratory suction lysimeters used in Schaefer et al. 2024[5], which employed the use of micro-sampling suction lysimeters. (c) A field lysimeter used in Schaefer et al. 2023[16]. (d) Diagram of a drainage wicking lysimeter – Credit: Edaphic Scientific, https://edaphic.com.au/products/water/lysimeter-wick-for-drainage/

Lysimeters, generally speaking, refer to instruments which collect water from unsaturated soils[4][11]. However, there are multiple types of lysimeters which can be employed in field or laboratory settings. There are three primary types of lysimeters relevant to PFAS listed here and shown in Figure 1a-d.

  1. Suction Lysimeters (Figure 1a,b): These lysimeters are the most relevant for PFAS sampling and are the majority of discussion in this article. These lysimeters operate by extracting liquid from the unsaturated vadose zone by applying negative suction pressure at the sampling head[3][5][18]. The sampling head is typically constructed of porous ceramic or stainless steel. A PVC case or stainless-steel case is attached to the sampling head and extends upward above the ground surface. Suction lysimeters are typically installed between 1 and 9 feet below ground surface, but can extend as deep as 40-60 feet in some cases[3]. Shallow lysimeters (< 10 feet) are typically installed using a hand auger. For ceramic lysimeters, a silica flour slurry should be placed at the base of the bore hole and allowed to cover the ceramic head before backfilling the hole partially with natural soil. Once the hole is partially backfilled with soil to cover the sampling head, the remainder of the casing should be sealed with hydrated bentonite chips. When sampling events occur, suction is applied at the ground surface using a rubber gasket seal and a hand pump or electric pump. After sufficient porewater is collected (the time for which can vary greatly based on the soil permeability and moisture content), the seal can be removed and a peristaltic pump used to extract liquid from the lysimeter.
  2. Field Lysimeters (Figure 1c): These large lysimeters can be constructed from plastic or metal sidings. They can range from approximately 2 feet in diameter to as large as several meters in diameter[4]. Instrumentation such as soil moisture probes and tensiometers, or even multiple suction lysimeters, are typically placed throughout the lysimeter to measure the movement of water and determine characteristic soil moisture release curves[13][14][16][17][38]. Water is typically collected at the base of the field lysimeter to determine net recharge through the system. These field lysimeters are intended to represent more realistic, intermediate scale conditions of field systems.
  3. Drainage Lysimeters (Figure 1d): Also known as a “wick” lysimeter, these lysimeters typically consist of a hollow cup attached to a spout which protrudes above ground to relieve air pressure from the system and act as a sampling port. The hollow cup typically has filters and wicking devices at the base to collect water from the soil. The cup is filled with natural soil and collects water as it percolates through the vadose zone. These lysimeters are used to directly monitor net recharge from the vadose zone to the groundwater table and could be useful in determining PFAS mass flux.

Analysis of PFAS Concentrations in Soil and Porewater

Table 1. Measured and Predicted PFAS Concentrations in Porewater for Select PFAS in Three Different Soils
Site PFAS Field
Porewater
Concentration
(μg/L) 		Lab Core
Porewater
Concentration
(μg/L) 		Predicted
Porewater
Concentration
(μg/L)
Site A PFOS 6.2 ± 3.4 3.0 ± 0.37 6.6 ± 3.3
Site B PFOS 2.2 ± 2.0 0.78 ± 0.38 2.8
Site C PFOS 13 ± 4.1 680 ± 460 164 ± 75
8:2 FTS 1.2 ± 0.46 52 ± 13 16 ± 6.0
PFHpS 0.36 ± 0.051 2.9 ± 2.0 5.9 ± 3.4
Figure 2. Field Measured PFAS concentration Data (Orange) and Lab Core Measured Concentration Data (Blue) for four PFAS impacted sites[1]
Figure 3. Measured and predicted data for PFAS concentrations from a single site field lysimeter study. Model predictions both with and without PFAS sorption to the air-water interface were considered[16].

Schaefer et al.[5] measured PFAS porewater concentrations with field and laboratory suction lysimeters across several sites. Intact cores from the site were collected for soil water extraction using laboratory lysimeters. The lysimeters were used to directly compare field derived measurements of PFAS concentration in the mobile porewater phase. Results from measurements are for four sites presented in Figure 2.

Data from sites A and B showed reasonably good agreement (within ½ order of magnitude) for most PFAS measured in the systems. At site C, more hydrophobic constituents (> C6 PFAS) tended to have higher concentrations in the lab core than the field site while less hydrophobic constituents (< C6) had higher concentrations in the field than lab cores. Site D showed substantially greater (1 order of magnitude or more) PFAS concentrations measured in the laboratory-collected porewater sample compared to what was measured in the field lysimeters. This discrepancy for the Site D soil can likely be attributed to soil heterogeneity (as indicated by ground penetrating radar) and the fact that the soil consisted of back-filled materials rather than undisturbed native soils.

Site C showed elevated PFAS concentrations in the laboratory collected porewater for the more surface-active compounds. This increase was attributed to the soil wetting that occurred at the bench scale, which was reasonably described by the model shown in Equations 1 and 2 (see Table 1[1]). Equations 1 and 2 were also used to predict PFAS porewater concentrations (using porous cup lysimeters) in a highly instrumented test cell[16](Figure 3). The ability to predict soil concentrations from recurring porewater samples is critical to the practical application of lysimeters in field settings[1].

Results from suction lysimeters studies and field lysimeter studies show that PFAS concentrations in porewater predicted from soil concentrations using Equations 1 and 2 generally have reasonable agreement with measured in situ porewater data when air-water interfacial partitioning is considered. Results show that for less hydrophobic components like PFOA, the impact of air-water interfacial adsorption is less significant than for highly hydrophobic components like PFOS. The soil for the field lysimeter in Figure 3 was a sandy soil with a relatively low air-water interfacial area. The effect of air-water interfacial partitioning is expected to be much more significant for a greater range of PFAS in soils with high capillary pressure (i.e. silts/clays) with higher associated air-water interfacial areas[37][39][40].

Summary and Recommendations

The majority of research with lysimeters for PFAS site investigations has been done using porous cup suction lysimeters[3][1][5][18]. Porous cup suction lysimeters are advantageous because they can be routinely sampled or sampled after specific wetting or drying events much like groundwater wells. This sampling is easier and more efficient than routinely collecting soil samples from the same locations. Co-locating lysimeters with soil samples is important for establishing the baseline soil concentration levels at the lysimeter location and developing correlations between the soil concentrations and the mobile porewater concentration[3]. Appropriate standard operation procedures for lysimeter installation and operation have been established and have been reviewed in recent literature[3][5]. Lysimeters should typically be installed near the source area and just above the maximum groundwater level elevation to obtain accurate results of porewater concentrations year round. Depending upon the geology and vertical PFAS distribution in the soil, multilevel lysimeter installations should also be considered.

Results from several lysimeters studies across multiple field sites and modelling analysis has shown that lysimeters can produce reasonable results between field and laboratory studies[5][16][17]. Transient effects of wetting and drying as well as media heterogeneity affects appear to be responsible for some variability and uncertainty in lysimeter based PFAS measurements in the vadose zone. These mobile porewater concentrations can be coupled with effective recharge estimates and simplified modelling approaches to determine mass flux from the vadose zone to the underlying groundwater[15][22][2][41][42].

Future research opportunities should address the current key uncertainties related to the use of lysimeters for PFAS investigations, including:

  1. Collect larger datasets of PFAS concentrations to determine how transient wetting or drying periods and media type affect PFAS concentrations in the mobile porewater. Some research has shown that non-equilibrium processes can occur in the vadose zone, which can affect grab sample concentration in the porewater at specific time periods.
  2. More work should be done with flux averaging lysimeters like the drainage cup or wicking lysimeter. These lysimeters can directly measure net recharge and provide time averaged concentrations of PFAS in water over the sampling period. However, there is little work detailing their potential applications in PFAS research, or operational considerations for their use in remedial investigations for PFAS.
  3. Lysimeters should be coupled with monitoring of wetting and drying in the vadose zone using in situ soil moisture sensors or tensiometers and groundwater levels. Direct measurements of soil saturation at field sites are vital to directly correlate porewater concentrations with soil concentrations. Similarly, groundwater level fluctuations can inform net recharge estimates. By collecting these data we can continue to improve partitioning and leaching models which can relate porewater concentrations to total PFAS mass in soils and PFAS leaching at field sites.
  4. Comparisons of various bench-scale leaching or desorption tests to field-based lysimeter data are recommended. The ability to correlate field measurements of PFAS concentrations with estimates of leaching from laboratory studies would provide a powerful method to empirically estimate PFAS leaching from field sites.

References

  1. ^ 1.0 1.1 1.2 1.3 1.4 1.5 1.6 Anderson, R.H., Feild, J.B., Dieffenbach-Carle, H., Elsharnouby, O., Krebs, R.K., 2022. Assessment of PFAS in Collocated Soil and Porewater Samples at an AFFF-Impacted Source Zone: Field-Scale Validation of Suction Lysimeters. Chemosphere, 308(1), Article 136247. doi: 10.1016/j.chemosphere.2022.136247
  2. ^ 2.0 2.1 2.2 2.3 Brusseau, M.L., Guo, B., 2022. PFAS Concentrations in Soil versus Soil Porewater: Mass Distributions and the Impact of Adsorption at Air-Water Interfaces. Chemosphere, 302, Article 134938. doi: 10.1016/j.chemosphere.2022.134938  Open Access Manuscript
  3. ^ 3.0 3.1 3.2 3.3 3.4 3.5 3.6 Costanza, J., Clabaugh, C.D., Leibli, C., Ferreira, J., Wilkin, R.T., 2025. Using Suction Lysimeters for Determining the Potential of Per- and Polyfluoroalkyl Substances to Leach from Soil to Groundwater: A Review. Environmental Science and Technology, 59(9), pp. 4215-4229. doi: 10.1021/acs.est.4c10246
  4. ^ 4.0 4.1 4.2 4.3 Meissner, R., Rupp, H., Haselow, L., 2020. Use of Lysimeters for Monitoring Soil Water Balance Parameters and Nutrient Leaching. In: Climate Change and Soil Interactions. Elsevier, pp. 171-205. doi: 10.1016/B978-0-12-818032-7.00007-2
  5. ^ 5.0 5.1 5.2 5.3 5.4 5.5 5.6 5.7 Schaefer, C.E., Nguyen, D., Fang, Y., Gonda, N., Zhang, C., Shea, S., Higgins, C.P., 2024. PFAS Porewater Concentrations in Unsaturated Soil: Field and Laboratory Comparisons Inform on PFAS Accumulation at Air-Water Interfaces. Journal of Contaminant Hydrology, 264, Article 104359. doi: 10.1016/j.jconhyd.2024.104359  Open Access Manuscript
  6. ^ 6.0 6.1 Goss, M.J., Ehlers, W., 2009. The Role of Lysimeters in the Development of Our Understanding of Soil Water and Nutrient Dynamics in Ecosystems. Soil Use and Management, 25(3), pp. 213–223. doi: 10.1111/j.1475-2743.2009.00230.x
  7. ^ Pütz, T., Fank, J., Flury, M., 2018. Lysimeters in Vadose Zone Research. Vadose Zone Journal, 17 (1), pp. 1-4. doi: 10.2136/vzj2018.02.0035  Open Access Article
  8. ^ Bergström, L., 1990. Use of Lysimeters to Estimate Leaching of Pesticides in Agricultural Soils. Environmental Pollution, 67 (4), 325–347. doi: 10.1016/0269-7491(90)90070-S
  9. ^ Dabrowska, D., Rykala, W., 2021. A Review of Lysimeter Experiments Carried Out on Municipal Landfill Waste. Toxics, 9(2), Article 26. doi: 10.3390/toxics9020026  Open Access Article
  10. ^ Fernando, S.U., Galagedara, L., Krishnapillai, M., Cuss, C.W., 2023. Lysimeter Sampling System for Optimal Determination of Trace Elements in Soil Solutions. Water, 15(18), Article 3277. doi: 10.3390/w15183277  Open Access Article
  11. ^ 11.0 11.1 Rogers, R.D., McConnell, J.W. Jr., 1993. Lysimeter Literature Review, Nuclear Regulatory Commission Report Numbers: NUREG/CR--6073, EGG--2706. [1] ID: 10183270. doi: 10.2172/10183270  Open Access Article
  12. ^ Sołtysiak, M., Rakoczy, M., 2019. An Overview of the Experimental Research Use of Lysimeters. Environmental and Socio-Economic Studies, 7(2), pp. 49-56. doi: 10.2478/environ-2019-0012  Open Access Article
  13. ^ 13.0 13.1 Stannard, D.I., 1992. Tensiometers—Theory, Construction, and Use. Geotechnical Testing Journal, 15(1), pp. 48-58. doi: 10.1520/GTJ10224J
  14. ^ 14.0 14.1 Winton, K., Weber, J.B., 1996. A Review of Field Lysimeter Studies to Describe the Environmental Fate of Pesticides. Weed Technology, 10(1), pp. 202-209. doi: 10.1017/S0890037X00045929
  15. ^ 15.0 15.1 15.2 Anderson, R.H., 2021. The Case for Direct Measures of Soil-to-Groundwater Contaminant Mass Discharge at AFFF-Impacted Sites. Environmental Science and Technology, 55(10), pp. 6580-6583. doi: 10.1021/acs.est.1c01543
  16. ^ 16.0 16.1 16.2 16.3 16.4 16.5 16.6 Schaefer, C.E., Lavorgna, G.M., Lippincott, D.R., Nguyen, D., Schaum, A., Higgins, C.P., Field, J., 2023. Leaching of Perfluoroalkyl Acids During Unsaturated Zone Flushing at a Field Site Impacted with Aqueous Film Forming Foam. Environmental Science and Technology, 57(5), pp. 1940-1948. doi: 10.1021/acs.est.2c06903
  17. ^ 17.0 17.1 17.2 Schaefer, C.E., Lavorgna, G.M., Lippincott, D.R., Nguyen, D., Christie, E., Shea, S., O’Hare, S., Lemes, M.C.S., Higgins, C.P., Field, J., 2022. A Field Study to Assess the Role of Air-Water Interfacial Sorption on PFAS Leaching in an AFFF Source Area. Journal of Contaminant Hydrology, 248, Article 104001. doi: 10.1016/j.jconhyd.2022.104001  Open Access Manuscript
  18. ^ 18.0 18.1 18.2 Quinnan, J., Rossi, M., Curry, P., Lupo, M., Miller, M., Korb, H., Orth, C., Hasbrouck, K., 2021. Application of PFAS-Mobile Lab to Support Adaptive Characterization and Flux-Based Conceptual Site Models at AFFF Releases. Remediation, 31(3), pp. 7-26. doi: 10.1002/rem.21680
  19. ^ 19.0 19.1 Brusseau, M.L., Anderson, R.H., Guo, B., 2020. PFAS Concentrations in Soils: Background Levels versus Contaminated Sites. Science of The Total Environment, 740, Article 140017. doi: 10.1016/j.scitotenv.2020.140017
  20. ^ 20.0 20.1 Bigler, M.C., Brusseau, M.L., Guo, B., Jones, S.L., Pritchard, J.C., Higgins, C.P., Hatton, J., 2024. High-Resolution Depth-Discrete Analysis of PFAS Distribution and Leaching for a Vadose-Zone Source at an AFFF-Impacted Site. Environmental Science and Technology, 58(22), pp. 9863-9874. doi: 10.1021/acs.est.4c01615
  21. ^ Nickerson, A., Maizel, A.C., Kulkarni, P.R., Adamson, D.T., Kornuc, J. J., Higgins, C.P., 2020. Enhanced Extraction of AFFF-Associated PFASs from Source Zone Soils. Environmental Science and Technology, 54(8), pp. 4952-4962. doi: 10.1021/acs.est.0c00792
  22. ^ 22.0 22.1 Stults, J.F., Schaefer, C.E., Fang, Y., Devon, J., Nguyen, D., Real, I., Hao, S., Guelfo, J.L., 2024. Air-Water Interfacial Collapse and Rate-Limited Solid Desorption Control Perfluoroalkyl Acid Leaching from the Vadose Zone. Journal of Contaminant Hydrology, 265, Article 104382. doi: 10.1016/j.jconhyd.2024.104382  Open Access Manuscript
  23. ^ Stults, J.F., Choi, Y.J., Rockwell, C., Schaefer, C.E., Nguyen, D.D., Knappe, D.R.U., Illangasekare, T.H., Higgins, C.P., 2023. Predicting Concentration- and Ionic-Strength-Dependent Air–Water Interfacial Partitioning Parameters of PFASs Using Quantitative Structure–Property Relationships (QSPRs). Environmental Science and Technology, 57(13), pp. 5203-5215. doi: 10.1021/acs.est.2c07316
  24. ^ Moody, C.A., Field, J.A., 1999. Determination of Perfluorocarboxylates in Groundwater Impacted by Fire-Fighting Activity. Environmental Science and Technology, 33(16), pp. 2800-2806. doi: 10.1021/es981355+
  25. ^ 25.0 25.1 25.2 Moody, C.A., Field, J.A., 2000. Perfluorinated Surfactants and the Environmental Implications of Their Use in Fire-Fighting Foams. Environmental Science and Technology, 34(18), pp. 3864-3870. doi: 10.1021/es991359u
  26. ^ 26.0 26.1 Glüge, J., Scheringer, M., Cousins, I.T., DeWitt, J.C., Goldenman, G., Herzke, D., Lohmann, R., Ng, C.A., Trier, X., Wang, Z., 2020. An Overview of the Uses of Per- and Polyfluoroalkyl Substances (PFAS). Environmental Science: Processes and Impacts, 22(12), pp. 2345-2373. doi: 10.1039/D0EM00291G  Open Access Article
  27. ^ 27.0 27.1 Brusseau, M.L., 2018. Assessing the Potential Contributions of Additional Retention Processes to PFAS Retardation in the Subsurface. Science of The Total Environment, 613-614, pp. 176-185. doi: 10.1016/j.scitotenv.2017.09.065  Open Access Manuscript
  28. ^ Dave, N., Joshi, T., 2017. A Concise Review on Surfactants and Its Significance. International Journal of Applied Chemistry, 13(3), pp. 663-672. doi: 10.37622/IJAC/13.3.2017.663-672  Open Access Article
  29. ^ García, R.A., Chiaia-Hernández, A.C., Lara-Martin, P.A., Loos, M., Hollender, J., Oetjen, K., Higgins, C.P., Field, J.A., 2019. Suspect Screening of Hydrocarbon Surfactants in Afffs and Afff-Contaminated Groundwater by High-Resolution Mass Spectrometry. Environmental Science and Technology, 53(14), pp. 8068-8077. doi: 10.1021/acs.est.9b01895
  30. ^ Krafft, M.P., Riess, J.G., 2015. Per- and Polyfluorinated Substances (PFASs): Environmental Challenges. Current Opinion in Colloid and Interface Science, 20(3), pp. 192-212. doi: 10.1016/j.cocis.2015.07.004
  31. ^ Schaefer, C.E., Culina, V., Nguyen, D., Field, J., 2019. Uptake of Poly- and Perfluoroalkyl Substances at the Air–Water Interface. Environmental Science and Technology, 53(21), pp. 12442-12448. doi: 10.1021/acs.est.9b04008
  32. ^ Lyu, Y., Brusseau, M.L., Chen, W., Yan, N., Fu, X., Lin, X., 2018. Adsorption of PFOA at the Air–Water Interface during Transport in Unsaturated Porous Media. Environmental Science and Technology, 52(14), pp. 7745-7753. doi: 10.1021/acs.est.8b02348
  33. ^ Costanza, J., Arshadi, M., Abriola, L.M., Pennell, K.D., 2019. Accumulation of PFOA and PFOS at the Air-Water Interface. Environmental Science and Technology Letters, 6(8), pp. 487-491. doi: 10.1021/acs.estlett.9b00355
  34. ^ Li, F., Fang, X., Zhou, Z., Liao, X., Zou, J., Yuan, B., Sun, W., 2019. Adsorption of Perfluorinated Acids onto Soils: Kinetics, Isotherms, and Influences of Soil Properties. Science of The Total Environment, 649, pp. 504-514. doi: 10.1016/j.scitotenv.2018.08.209
  35. ^ 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
  36. ^ Brusseau, M.L., Yan, N., Van Glubt, S., Wang, Y., Chen, W., Lyu, Y., Dungan, B., Carroll, K.C., Holguin, F.O., 2019. Comprehensive Retention Model for PFAS Transport in Subsurface Systems. Water Research, 148, pp. 41-50. doi: 10.1016/j.watres.2018.10.035
  37. ^ 37.0 37.1 37.2 Brusseau, M.L., 2023. Determining Air-Water Interfacial Areas for the Retention and Transport of PFAS and Other Interfacially Active Solutes in Unsaturated Porous Media. Science of The Total Environment, 884, Article 163730. doi: 10.1016/j.scitotenv.2023.163730  Open Access Article
  38. ^ van Genuchten, M.Th. , 1980. A Closed‐form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils. Soil Science Society of America Journal, 44(5), pp. 892-898. doi: 10.2136/sssaj1980.03615995004400050002x
  39. ^ Peng, S., Brusseau, M.L., 2012. Air-Water Interfacial Area and Capillary Pressure: Porous-Medium Texture Effects and an Empirical Function. Journal of Hydrologic Engineering, 17(7), pp. 829-832. doi: 10.1061/(asce)he.1943-5584.0000515
  40. ^ Brusseau, M.L., Peng, S., Schnaar, G., Costanza-Robinson, M.S., 2006. Relationships among Air-Water Interfacial Area, Capillary Pressure, and Water Saturation for a Sandy Porous Medium. Water Resources Research, 42(3), Article W03501, 5 pages. doi: 10.1029/2005WR004058  Free Access Article
  41. ^ Stults, J.F., Schaefer, C.E., MacBeth, T., Fang, Y., Devon, J., Real, I., Liu, F., Kosson, D., Guelfo, J.L., 2025. Laboratory Validation of a Simplified Model for Estimating Equilibrium PFAS Mass Leaching from Unsaturated Soils. Science of The Total Environment, 970, Article 179036. doi: 10.1016/j.scitotenv.2025.179036
  42. ^ Smith, J. Brusseau, M.L., Guo, B., 2024. An Integrated Analytical Modeling Framework for Determining Site-Specific Soil Screening Levels for PFAS. Water Research, 252, Article121236. doi: 10.1016/j.watres.2024.121236

See Also

Retrieved from "https://www.enviro.wiki/index.php?title=User:Jhurley/sandbox&oldid=17811"