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==OPTically-based In-situ Characterization System (OPTICS)==  
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==Lysimeters for Measuring PFAS Concentrations in the Vadose Zone==  
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OPTICS combines robust aquatic instrumentation and innovative data processing techniques to measure concentrations of a wide range of dissolved and particulate chemical contaminants in surface water at unprecedented scales. OPTICS is used for a variety of environmental applications including remedial investigation, conceptual site model validation, baseline characterization, source control evaluation, plume characterization, and remedial monitoring.
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[[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.  
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<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):'''
  
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*[[Contaminated Sediments - Introduction]]
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*[[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS)]]
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*[[Characterization, Assessment & Monitoring]]
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*[[PFAS Transport and Fate]]
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*[[Mercury in Sediments]]
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*[[PFAS Toxicology and Risk Assessment]]
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*[[Mass Flux and Mass Discharge]]
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'''Contributor(s):'''
 
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*Grace Chang, Ph.D.
 
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*Todd Martin, P.E.
 
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'''Key Resource(s):'''
 
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*Optically based quantification of fluxes of mercury, methyl mercury, and polychlorinated biphenyls (PCBs) at Berry’s Creek tidal estuary, New Jersey<ref name="ChangEtAl2019">Chang, G., Martin, T., Whitehead, K., Jones, C., Spada, F., 2019. Optically based quantification of fluxes of mercury, methyl mercury, and polychlorinated biphenyls (PCBs) at Berry’s Creek tidal estuary, New Jersey. Limnology and Oceanography, 64(1), pp. 93-108. [https://doi.org/10.1002/lno.11021 doi: 10.1002/lno.11021]&nbsp;&nbsp; [[Media: ChangEtAl2019.pdf | Open Access Article]]</ref>
 
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*OPTically-based In-situ Characterization System (OPTICS) to quantify concentrations of mass fluxes of mercury and methylmercury in South River, Virginia, USA<ref name="ChangEtAl2018">Chang, G., Martin, T., Spada, F., Sackmann, B., Jones, C., Whitehead, K., 2018. OPTically-based In-situ Characterization System (OPTICS) to quantify concentrations and mass fluxes of mercury and methylmercury in South River, Virginia, USA. River Research and Applications, 34(9), pp.  1132-1141. [https://doi.org/10.1002/rra.3361 doi: 10.1002/rra.3361]</ref>
 
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*Evaluation of stormwater as a potential source of polychlorinated biphenyls (PCBs) to Pearl Harbor, Hawaii<ref name="ChangEtAl2024">Chang, G., Spada, F., Brodock, K., Hutchings, C., Markillie, K., 2024. Evaluation of stormwater as a potential source of polychlorinated biphenyls (PCBs) to Pearl Harbor, Hawaii. Case Studies in Chemical and Environmental Engineering, 9, Article 100659. [https://doi.org/10.1016/j.cscee.2024.100659 doi: 10.1016/j.cscee.2024.100659]&nbsp;&nbsp; [[Media: ChangEtAl2024.pdf | Open Access Article]]</ref>
 
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==Background==
 
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Nationwide, the liability due to contaminated sediments is estimated in the trillions of dollars. Stakeholders are assessing and developing remedial strategies for contaminated sediment sites in major harbors and waterways throughout the U.S. The mobility of contaminants in surface water is a primary transport and risk mechanism<ref>Thibodeaux, L.J., 1996. Environmental Chemodynamics: Movement of Chemicals in Air, Water, and Soil, 2nd Edition, Volume 110 of Environmental Science and Technology: A Wiley-Interscience Series of Texts and Monographs. John Wiley & Sons, Inc. 624 pages. ISBN: 0-471-61295-2</ref><ref>United States Environmental Protection Agency (USEPA), 2005. Contaminated Sediment Remediation Guidance for Hazardous Waste Sites. Office of Superfund Remediation and Technology Innovation Report, EPA-540-R-05-012. [[Media: EPA-540-R-05-012.pdf | Report.pdf]]</ref><ref>Lick, W., 2008. Sediment and Contaminant Transport in Surface Waters. CRC Press. 416 pages. [https://doi.org/10.1201/9781420059885 doi:  10.1201/9781420059885]</ref>; therefore, long-term monitoring of both particulate- and dissolved-phase contaminant concentration prior to, during, and following remedial action is necessary to ensure remedy effectiveness. Source control and total maximum daily load (TMDL) actions generally require costly manual monitoring of dissolved and particulate contaminant concentrations in surface water. The magnitude of cost for these actions is a strong motivation to implement efficient methods for long-term source control and remedial monitoring.
 
  
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Traditional surface water monitoring requires mobilization of field teams to manually collect discrete water samples, send samples to laboratories, and await laboratory analysis so that a site evaluation can be conducted. These traditional methods are well known to have inherent cost and safety concerns and are of limited use in capturing episodic events (e.g., storms) important to site risk and remedy due to safety concerns and standby requirements for resources. Automated water samplers are commercially available but still require significant field support and costly laboratory analysis. Further, automated samplers may not be suitable for analytes with short hold-times and temperature requirements.  
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'''Contributors:''' Dr. John F. Stults, Dr. Charles Schaefer
  
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Optically-based characterization of surface water contaminants is a cost-effective alternative to traditional discrete water sampling methods. Unlike discrete water sampling, which typically results in sparse data at low resolution, and therefore, is of limited use in determining mass loading, OPTICS (OPTically-based In-situ Characterization System) provides continuous data and allows for a complete understanding of water quality and contaminant transport in response to natural processes and human impacts<ref name="ChangEtAl2019"/><ref name="ChangEtAl2018"/><ref name="ChangEtAl2024"/><ref>Bergamaschi, B.A., Fleck, J.A., Downing, B.D., Boss, E., Pellerin, B., Ganju, N.K., Schoellhamer, D.H., Byington, A.A., Heim, W.A., Stephenson, M., Fujii, R., 2011. Methyl mercury dynamics in a tidal wetland quantified using in situ optical measurements. Limnology and Oceanography, 56(4), pp. 1355-1371. [https://doi.org/10.4319/lo.2011.56.4.1355 doi: 10.4319/lo.2011.56.4.1355]&nbsp;&nbsp; [[Media: BergamaschiEtAl2011.pdf | Open Access Article]]</ref><ref>Bergamaschi, B.A., Fleck, J.A., Downing, B.D., Boss, E., Pellerin, B.A., Ganju, N.K., Schoellhamer, D.H., Byington, A.A., Heim, W.A., Stephenson, M., Fujii, R., 2012. Mercury Dynamics in a San Francisco Estuary Tidal Wetland: Assessing Dynamics Using In Situ Measurements. Estuaries and Coasts, 35, pp. 1036-1048. [https://doi.org/10.1007/s12237-012-9501-3 doi: 10.1007/s12237-012-9501-3]&nbsp;&nbsp; [[Media: BergamaschiEtAl2012a.pdf | Open Access Article]]</ref><ref>Bergamaschi, B.A., Krabbenhoft, D.P., Aiken, G.R., Patino, E., Rumbold, D.G., Orem, W.H., 2012. Tidally driven export of dissolved organic carbon, total mercury, and methylmercury from a mangrove-dominated estuary. Environmental Science and Technology, 46(3), pp. 1371-1378. [https://doi.org/10.1021/es2029137 doi: 10.1021/es2029137]&nbsp;&nbsp; [[Media: BergamaschiEtAl2012b.pdf | Open Access Article]]</ref>. The OPTICS tool integrates commercial off-the-shelf in-situ aquatic sensors, periodic discrete surface water sample collection, and a multi-parameter statistical prediction model<ref name="deJong1993">de Jong, S., 1993. SIMPLS: an alternative approach to partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 18(3), pp. 251-263. [https://doi.org/10.1016/0169-7439(93)85002-X doi: 10.1016/0169-7439(93)85002-X]</ref><ref name="RosipalKramer2006">Rosipal, R. and Krämer, N., 2006. Overview and Recent Advances in Partial Least Squares, In: Subspace, Latent Structure, and Feature Selection: Statistical and Optimization Perspectives Workshop, Revised Selected Papers (Lecture Notes in Computer Science, Volume 3940), Springer-Verlag, Berlin, Germany. pp. 34-51. [https://doi.org/10.1007/11752790_2 doi: 10.1007/11752790_2]</ref> to provide high temporal and/or spatial resolution characterization of surface water chemicals of potential concern (COPCs).
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'''Key Resources:'''
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*Assessment of PFAS in Collocated Soil and Porewater Samples at an AFFF-Impacted Source Zone: Field-Scale Validation of Suction Lysimeters<ref name="AndersonEtAl2022"/>
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*PFAS Concentrations in Soil versus Soil Porewater: Mass Distributions and the Impact of Adsorption at Air-Water Interfaces<ref name="BrusseauGuo2022"/>
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*Using Suction Lysimeters for Determining the Potential of Per- and Polyfluoroalkyl Substances to Leach from Soil to Groundwater: A Review<ref name="CostanzaEtAl2025"/>
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*Use of Lysimeters for Monitoring Soil Water Balance Parameters and Nutrient Leaching<ref name="MeissnerEtAl2020"/>
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*PFAS Porewater Concentrations in Unsaturated Soil: Field and Laboratory Comparisons Inform on PFAS Accumulation at Air-Water Interfaces<ref name="SchaeferEtAl2024"/>
  
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==Technology Overview==
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==Introduction==
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[[File:ChangFig1.png | thumb | 300px| Figure 1. Schematic diagram illustrating the OPTICS methodology. High resolution in-situ data are integrated with traditional discrete sample analytical data using partial least-square regression to derive high resolution chemical contaminant concentration data series.]]
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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.
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[[File:ChangFig2.png | thumb | 300px| Figure 2. Example of instrumentation used for OPTICS monitoring.]]
 
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The principle behind OPTICS is based on the relationship between optical properties of natural waters and the particles and dissolved material contained within them<ref>Boss, E. and Pegau, W.S., 2001. Relationship of light scattering at an angle in the backward direction to the backscattering coefficient. Applied Optics, 40(30), pp. 5503-5507. [https://doi.org/10.1364/AO.40.005503 doi: 10.1364/AO.40.005503]</ref><ref>Boss, E., Twardowski, M.S., Herring, S., 2001. Shape of the particulate beam spectrum and its inversion to obtain the shape of the particle size distribution. Applied Optics, 40(27), pp. 4884-4893. [https://doi.org/10.1364/AO.40.004885 doi:10/1364/AO.40.004885]</ref><ref>Babin, M., Morel, A., Fournier-Sicre, V., Fell, F., Stramski, D., 2003. Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration. Limnology and Oceanography, 48(2), pp. 843-859. [https://doi.org/10.4319/lo.2003.48.2.0843 doi: 10.4319/lo.2003.48.2.0843]&nbsp;&nbsp; [[Media: BabinEtAl2003.pdf | Open Access Article]]</ref><ref>Coble, P., Hu, C., Gould, R., Chang, G., Wood, M., 2004. Colored dissolved organic matter in the coastal ocean: An optical tool for coastal zone environmental assessment and management. Oceanography, 17(2), pp. 50-59. [https://doi.org/10.5670/oceanog.2004.47 doi: 10.5670/oceanog.2004.47]&nbsp;&nbsp; [[Media: CobleEtAl2004.pdf | Open Access Article]]</ref><ref>Sullivan, J.M., Twardowski, M.S., Donaghay, P.L., Freeman, S.A., 2005. Use of optical scattering to discriminate particle types in coastal waters. Applied Optics, 44(9), pp. 1667–1680. [https://doi.org/10.1364/AO.44.001667 doi: 10.1364/AO.44.001667]</ref><ref>Twardowski, M.S., Boss, E., Macdonald, J.B., Pegau, W.S., Barnard, A.H., Zaneveld, J.R.V., 2001. A model for estimating bulk refractive index from the optical backscattering ratio and the implications for understanding particle composition in case I and case II waters. Journal of Geophysical Research: Oceans, 106(C7), pp. 14,129-14,142. [https://doi.org/10.1029/2000JC000404 doi: 10/1029/2000JC000404]&nbsp;&nbsp; [[Media: TwardowskiEtAl2001.pdf | Open Access Article]]</ref><ref>Chang, G.C., Barnard, A.H., McLean, S., Egli, P.J., Moore, C., Zaneveld, J.R.V., Dickey, T.D., Hanson, A., 2006. In situ optical variability and relationships in the Santa Barbara Channel: implications for remote sensing. Applied Optics, 45(15), pp. 3593–3604. [https://doi.org/10.1364/AO.45.003593 doi: 10.1364/AO.45.003593]</ref><ref>Slade, W.H. and Boss, E., 2015. Spectral attenuation and backscattering as indicators of average particle size. Applied Optics, 54(24), pp. 7264-7277. [https://doi.org/10.1364/AO.54.007264 doi: 10/1364/AO.54.007264]&nbsp;&nbsp; [[Media: SladeBoss2015.pdf | Open Access Article]]</ref>. Surface water COPCs such as heavy metals and polychlorinated biphenyls (PCBs) are hydrophobic in nature and tend to sorb to materials in the water column, which have unique optical signatures that can be measured at high-resolution using in-situ, commercially available aquatic sensors<ref>Agrawal, Y.C. and Pottsmith, H.C., 2000. Instruments for particle size and settling velocity observations in sediment transport. Marine Geology, 168(1-4), pp. 89-114. [https://doi.org/10.1016/S0025-3227(00)00044-X doi: 10.1016/S0025-3227(00)00044-X]</ref><ref>Boss, E., Pegau, W.S., Gardner, W.D., Zaneveld, J.R.V., Barnard, A.H., Twardowski, M.S., Chang, G.C., Dickey, T.D., 2001. Spectral particulate attenuation and particle size distribution in the bottom boundary layer of a continental shelf. Journal of Geophysical Research: Oceans, 106(C5), pp. 9509-9516. [https://doi.org/10.1029/2000JC900077  doi: 10.1029/2000JC900077]&nbsp;&nbsp; [[Media: BossEtAl2001.pdf | Open Access Article]]</ref><ref>Boss, E., Pegau, W.S., Lee, M., Twardowski, M., Shybanov, E., Korotaev, G. Baratange, F., 2004. Particulate backscattering ratio at LEO 15 and its use to study particle composition and distribution. Journal of Geophysical Research: Oceans, 109(C1), Article C01014. [https://doi.org/10.1029/2002JC001514 doi: 10.1029/2002JC001514]&nbsp;&nbsp; [[Media: BossEtAl2004.pdf | Open Access Article]]</ref><ref>Briggs, N.T., Slade, W.H., Boss, E., Perry, M.J., 2013. Method for estimating mean particle size from high-frequency fluctuations in beam attenuation or scattering measurement. Applied Optics, 52(27), pp. 6710-6725. [https://doi.org/10.1364/AO.52.006710 doi: 10.1364/AO.52.006710]&nbsp;&nbsp; [[Media: BriggsEtAl2013.pdf | Open Access Article]]</ref>. Therefore, high-resolution concentrations of COPCs can be accurately and robustly derived from in-situ measurements using statistical methods.
 
  
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The OPTICS method is analogous to the commonly used empirical derivation of total suspended solids concentration (TSS) from optical turbidity using linear regression<ref>Rasmussen, P.P., Gray, J.R., Glysson, G.D., Ziegler, A.C., 2009. Guidelines and procedures for computing time-series suspended-sediment concentrations and loads from in-stream turbidity-sensor and streamflow data. In: Techniques and Methods, Book 3: Applications of Hydraulics, Section C: Sediment and Erosion Techniques, Ch. 4. 52 pages. U.S. Geological Survey.&nbsp;&nbsp; [[Media: RasmussenEtAl2009.pdf | Open Access Article]]</ref>. However, rather than deriving one response variable (TSS) from one predictor variable (turbidity), OPTICS involves derivation of one response variable (e.g., PCB concentration) from a suite of predictor variables (e.g., turbidity, temperature, salinity, and fluorescence of chlorophyll-a) using multi-parameter statistical regression. OPTICS is based on statistical correlation – similar to the turbidity-to-TSS regression technique; the method does not rely on interpolation or extrapolation.  
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==PFAS Background==
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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.
  
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The OPTICS technique utilizes partial least-squares (PLS) regression to determine a combination of physical, optical, and water quality properties that best predicts chemical contaminant concentrations with high variance. PLS regression is a statistically based method combining multiple linear regression and principal component analysis (PCA), where multiple linear regression finds a combination of predictors that best fit a response and PCA finds combinations of predictors with large variance<ref name="deJong1993"/><ref name="RosipalKramer2006"/>. Therefore, PLS identifies combinations of multi-collinear predictors (in situ, high-resolution physical, optical, and water quality measurements) that have large covariance with the response values (discrete surface water chemical contaminant concentration data from samples that are collected periodically, coincident with in situ measurements). PLS combines information about the variances of both the predictors and the responses, while also considering the correlations among them. PLS therefore provides a model with reliable predictive power.
+
==Lysimeters Background==
 +
[[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.
  
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OPTICS in situ measurement parameters include, but are not limited to current velocity, conductivity, temperature, depth, turbidity, dissolved oxygen, and fluorescence of chlorophyll-a and dissolved organic matter. Instrumentation for these measurements is commercially available, robust, deployable in a wide variety of configurations (e.g., moored, vessel-mounted, etc.), powered by batteries, and records data internally and/or transmits data in real-time. The physical, optical, and water quality instrumentation is compact and self-contained. The modularity and automated nature of the OPTICS measurement system enable robust, long-term, autonomous data collection for near-continuous monitoring.  
+
==Analysis of PFAS Concentrations in Soil and Porewater==
 +
{| 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
 +
|-
 +
!Site
 +
!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)
 +
|-
 +
|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
 +
|-
 +
|rowspan="3"|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
 +
|}
 +
[[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.
  
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OPTICS measurements are provided at a significantly reduced cost relative to traditional monitoring techniques used within the environmental industry. Cost performance analysis shows that monitoring costs are reduced by more than 85% while significantly increasing the temporal and spatial resolution of sampling. The reduced cost of monitoring makes this technology suitable for a number of environmental applications including, but not limited to site baseline characterization, source control evaluation, dredge or stormflow plume characterization, and remedy performance monitoring. OPTICS has been successfully demonstrated for characterizing a wide variety of COPCs: mercury, methylmercury, copper, lead, PCBs, dichlorodiphenyltrichloroethane (DDT) and its related compounds (collectively, DDX), and 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD or dioxin) in a number of different environmental systems ranging from inland lakes and rivers to the coastal ocean. To date, OPTICS has been limited to surface water applications; additional applications, e.g., groundwater, would require further research and development.  
+
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.  
 
   
 
   
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==Applications==
+
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"/>.
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[[File:ChangFig3.png | thumb | 300px| Figure 3. OPTICS to characterize COPC variability in the context of site processes at BCSA. (A) Tidal oscillations (Elev.<sub>MSL</sub>) and precipitation (Precip.). (B) – (D) OPTICS-derived particulate mercury (PHg) and methylmercury (PMeHg) and total PCBs (TPCBs). Open circles represent discrete water sample data.]]
 
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[[File:ChangFig4.png | thumb | 300px| Figure 4. OPTICS reveals baseflow daily cycling and confirms storm-induced particle-bound COPC resuspension and mobilization through bank interaction. (A) Flow rate (Q) and precipitation (Precip). (B) – (C) OPTICS-derived particulate mercury (PHg) and methylmercury (PMeHg). Open circles represent discrete water sample data.]]
 
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[[File:ChangFig5.png | thumb | 300px| Figure 5. Three-dimensional volume plot of high spatial resolution OPTICS-derived PCBs in exceedance of baseline showing that PCBs were discharged from the outfall (yellow arrow), remained in suspension, and dispersed elsewhere before settling.]]
 
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An OPTICS study was conducted at Berry’s Creek Study Area (BCSA), New Jersey in 2014 and 2015 to understand COPC sources and transport mechanisms for development of an effective remediation plan. OPTICS successfully extended periodic discrete surface water samples to continuous, high-resolution measurements of PCBs, mercury, and methylmercury to elucidate COPC sources and transport throughout the BCSA tidal estuary system. OPTICS provided data at resolution sufficient to investigate COC variability in the context of physical processes. The results facilitated focused and effective site remediation and management decisions that could not be determined based on periodic discrete samples alone, despite over seven years of monitoring at different locations throughout the system over a range of different seasons, tidal phases, and environmental conditions. The BCSA OPTICS methodology and results have undergone official peer review overseen by the U.S. Environmental Protection Agency (USEPA) and results have been published in peer-reviewed literature<ref name="ChangEtAl2019"/>.  
 
  
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OPTICS was applied at the South River, Virginia in 2016 to quantify sources of legacy mercury in the system that are contributing to recontamination and continued elevated mercury concentrations in fish tissue. OPTICS provided information necessary to identify mechanisms for COPC redistribution and to quantify the relative contribution of each mechanism to total mass transport of mercury and methylmercury in the system. Continuous, high-resolution COPC data afforded by OPTICS helped resolve baseflow daily cycling that had never before been observed at the South River and provided data at temporal resolution necessary to verify storm-induced particle-bound COC resuspension and mobilization through bank interaction. The results informed source control and remedy design and monitoring efforts. Methodology and results from the South River have been published in peer-reviewed literature<ref name="ChangEtAl2018"/>.  
+
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>.
  
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The U.S. Department of Defense’s Environmental Security Technology Certification Program (ESTCP) supported an OPTICS demonstration study at the Pearl Harbor Sediment Site, Hawaii, to determine whether stormwater from Oscar 1 Pier outfall is a contributing source of PCBs to Decision Unit (DU) N-2 (ESTCP Project ER21-5021). High spatial resolution results afforded by ship-based, mobile OPTICS monitoring suggested that PCBs were discharged from the outfall, remained in suspension, and dispersed elsewhere before settling. More details regarding this study were presented by Chang et al. in 2024<ref name="ChangEtAl2024"/>.  
+
==Summary and Recommendations==
 +
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.
  
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==Summary==
+
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>.
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OPTICS provides:
 
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*High resolution surface water chemical contaminant characterization
 
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*Cost-effective monitoring and assessment
 
−
*Versatile and modular monitoring with capability for real-time telemetry
 
−
*Data necessary for development and validation of conceptual site models
 
−
*A key line of evidence for designing and evaluating remedies.
 
  
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Because OPTICS monitoring involves deployment of autonomous sampling instrumentation, a substantially greater volume of data can be collected using this technique compared to traditional sampling, and at a far lower cost. A large volume of data supports evaluation of chemical contaminant concentrations over a range of spatial and temporal scales, and the system can be customized for a variety of environmental applications. OPTICS helps quantify contaminant mass flux and the relative contribution of local transport and source areas to net contaminant transport. OPTICS delivers a strong line of evidence for evaluating contaminant sources, fate, and transport, and for supporting the design of a remedy tailored to address site-specific, risk-driving conditions. The improved understanding of site processes aids in the development of mitigation measures that minimize site risks.  
+
Future research opportunities should address the current key uncertainties related to the use of lysimeters for PFAS investigations, including:
 +
#<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==

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.

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See Also

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