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==PFAS Treatment by Anion Exchange==  
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==Assessing Vapor Intrusion (VI) Impacts in Neighborhoods with Groundwater Contaminated by Chlorinated Volatile Organic Chemicals (CVOCs)==  
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The VI Diagnosis Toolkit<ref name="JohnsonEtAl2020">Johnson, P.C., Guo, Y., Dahlen, P., 2020.  The VI Diagnosis Toolkit for Assessing Vapor Intrusion Pathways and Mitigating Impacts in Neighborhoods Overlying Dissolved Chlorinated Solvent Plumes.  ESTCP Project ER-201501, Final Report. [https://serdp-estcp.mil/projects/details/a0d8bafd-c158-4742-b9fe-5f03d002af71 Project Website]&nbsp;&nbsp; [[Media: ER-201501.pdf | Final Report.pdf]]</ref> is a set of tools that can be used individually or in combination to assess vapor intrusion (VI) impacts at one or more buildings overlying regional-scale dissolved chlorinated solvent-impacted groundwater plumes. The strategic use of these tools can lead to confident and efficient neighborhood-scale VI pathway assessments. 
  
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| style="padding:2px; width:100%" |<h2 id="mp-otd-h2" style="margin:3px; background:#cedff2; font-family:inherit; font-size:120%; font-weight:bold; border:1px solid #a3b0bf; text-align:left; color:#000; padding:0.2em 0.4em;">Editorial Board</h2>
 
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| colspan="3" | <span style="line-height: 1em;">'''Editor-in-Chief'''<br /><span style="line-height: 1.2em;">[[Dr. Robert Borden, P.E.|Robert C. Borden, PhD, PE]]
 
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|| '''Editors'''
 
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|| <span style="line-height: 1.1em;">[[Dr. Jason Barnes|Jason Barnes, PhD]]<br/>Cascadia College || || [[Dr. Samuel Beal|Samuel Beal, PhD]]<br /> CRREL Research and Development Center
 
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|| <span style="line-height: 1.1em;">[[Craig E. Divine, Ph.D., PG|Craig E. Divine, PhD, PG]]<br /> Arcadis || || [[Dr. Kevin Finneran|Kevin Finneran, PhD]] <br /> Finneran Environmental, LLC
 
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|| <span style="line-height: 1.1em;">[[Dr. Upal Ghosh|Upal Ghosh, PhD]] <br/> University of Maryland, Baltimore County || || [[Dr. Rao Kotamarthi| Rao Kotamarthi, PhD]]<br /> Argonne National Lab
 
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|| <span style="line-height: 1.1em;">[[Kim Matthews| Kim Matthews]] <br /> RTI International || || [[Dr. Charles Newell, P.E.|Charles Newell, PhD, PE]] <br/> GSI Environmental
 
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|| <span style="line-height: 1.1em;"> [[Dr. Alexandra Salter-Blanc|Alexandra Salter-Blanc, PhD]] <br/> Jacobs || || [[Dr. John Wilson|John Wilson, PhD]] <br/> Scissortail Environmental Solutions, LLC
 
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[[Wikipedia: Ion exchange | Anion exchange]] has emerged as one of the most effective and economical technologies for treatment of water contaminated by [[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) | per- and polyfluoroalkyl substances (PFAS)]]. Anion exchange resins (AERs) are polymer beads (0.5–1 mm diameter) incorporating cationic adsorption sites that attract anionic PFAS by a combination of electrostatic and hydrophobic mechanisms. Both regenerable and single-use resin treatment systems are being investigated, and results from pilot-scale studies show that AERs can treat much greater volumes of PFAS-contaminated water than comparable amounts of [[Wikipedia: Activated carbon | granular activated carbon (GAC)]] adsorbent media. Life cycle treatment costs and environmental impacts of anion exchange and other adsorbent technologies are highly dependent upon the treatment criteria selected by site managers to determine when media is exhausted and requires replacement or regeneration.
 
 
<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):'''
*[[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS)]]  
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*[[PFAS Sources]]
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*[[Vapor Intrusion (VI)]]
*[[PFAS Transport and Fate]]
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*[[Vapor Intrusion – Sewers and Utility Tunnels as Preferential Pathways]]
*[[PFAS Ex Situ Water Treatment]]
 
*[[Supercritical Water Oxidation (SCWO)]]
 
*[[PFAS Treatment by Electrical Discharge Plasma]]
 
  
 
'''Contributor(s):'''  
 
'''Contributor(s):'''  
*Dr. Timothy J. Strathmann
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*Dr. Anderson Ellis
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*Paul C. Johnson, Ph.D.
*Dr. Treavor H. Boyer
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*Paul Dahlen, Ph.D.
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*Yuanming Guo, Ph.D.
  
 
'''Key Resource(s):'''
 
'''Key Resource(s):'''
*Anion Exchange Resin Removal of Per- and Polyfluoroalkyl Substances (PFAS) from Impacted Water: A Critical Review<ref name="BoyerEtAl2021a">Boyer, T.H., Fang, Y., Ellis, A., Dietz, R., Choi, Y.J., Schaefer, C.E., Higgins, C.P., Strathmann, T.J., 2021. Anion Exchange Resin Removal of Per- and Polyfluoroalkyl Substances (PFAS) from Impacted Water: A Critical Review. Water Research, 200, Article 117244. [https://doi.org/10.1016/j.watres.2021.117244 doi: 10.1016/j.watres.2021.117244]&nbsp;&nbsp; [[Media: BoyerEtAl2021a.pdf | Open Access Manuscript.pdf]]</ref>
 
 
*Regenerable Resin Sorbent Technologies with Regenerant Solution Recycling for Sustainable Treatment of PFAS; SERDP Project ER18-1063 Final Report<ref>Strathmann, T.J., Higgins, C.P., Boyer, T., Schaefer, C., Ellis, A., Fang, Y., del Moral, L., Dietz, R., Kassar, C., Graham, C, 2023. Regenerable Resin Sorbent Technologies with Regenerant Solution Recycling for Sustainable Treatment of PFAS; SERDP Project ER18-1063 Final Report. 285 pages. [https://serdp-estcp.org/projects/details/d3ede38b-9f24-4b22-91c9-1ad634aa5384 Project Website]&nbsp;&nbsp; [[Media: ER18-1063.pdf | Report.pdf]]</ref>
 
 
==Introduction==
 
[[File:StrathmannFig1.png | thumb |300px|Figure 1. Illustration of PFAS adsorption by anion exchange resins (AERs). Incorporation of longer alkyl group side chains on the cationic quaternary amine functional groups leads to PFAS-resin hydrophobic interactions that increase resin selectivity for PFAS over inorganic anions like Cl<sup>-</sup>.]]
 
 
[[File:StrathmannFig2.png | thumb | 300px| Figure 2. Effect of perfluoroalkyl carbon chain length on the estimated bed volumes (BVs) to 50% breakthrough of PFCAs and PFSAs observed in a pilot study<ref name="StrathmannEtAl2020">Strathmann, T.J., Higgins, C., Deeb, R., 2020. Hydrothermal Technologies for On-Site Destruction of Site Investigation Wastes Impacted by PFAS, Final Report - Phase I. SERDP Project ER18-1501. [https://serdp-estcp.mil/projects/details/b34d6396-6b6d-44d0-a89e-6b22522e6e9c Project Website]&nbsp;&nbsp; [[Media: ER18-1501.pdf | Report.pdf]]</ref> treating PFAS-contaminated groundwater with the PFAS-selective AER (Purolite PFA694E) ]]
 
 
Anion exchange is an adsorptive treatment technology that uses polymeric resin beads (0.5–1 mm diameter) that incorporate cationic adsorption sites to remove anionic pollutants from water<ref>SenGupta, A.K., 2017. Ion Exchange in Environmental Processes: Fundamentals, Applications and Sustainable Technology. Wiley. ISBN:9781119157397  [https://onlinelibrary.wiley.com/doi/book/10.1002/9781119421252 Wiley Online Library]</ref>. Anions (e.g., NO<sub>3</sub><sup>-</sup>) are adsorbed by an ion exchange reaction with anions that are initially bound to the adsorption sites (e.g., Cl<sup>-</sup>) during resin preparation. Many per- and polyfluoroalkyl substances (PFAS) of concern, including [[Wikipedia: Perfluorooctanoic acid | perfluorooctanoic acid (PFOA)]] and [[Wikipedia: Perfluorooctanesulfonic acid | perfluorooctane sulfonate (PFOS)]], are present in contaminated water as anionic species that can be adsorbed by anion exchange reactions<ref name="BoyerEtAl2021a"/><ref name="DixitEtAl2021">Dixit, F., Dutta, R., Barbeau, B., Berube, P., Mohseni, M., 2021. PFAS Removal by Ion Exchange Resins: A Review. Chemosphere, 272, Article 129777. [https://doi.org/10.1016/j.chemosphere.2021.129777 doi: 10.1016/j.chemosphere.2021.129777]</ref><ref name="RahmanEtAl2014">Rahman, M.F., Peldszus, S., Anderson, W.B., 2014. Behaviour and Fate of Perfluoroalkyl and Polyfluoroalkyl Substances (PFASs) in Drinking Water Treatment: A Review. Water Research, 50, pp. 318–340. [https://doi.org/10.1016/j.watres.2013.10.045 doi: 10.1016/j.watres.2013.10.045]</ref>.
 
</br>
 
<center><big>Anion Exchange Reaction:&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;'''PFAS<sup>-</sup></big><sub>(aq)</sub><big>&nbsp;+&nbsp;Cl<sup>-</sup></big><sub>(resin bound)</sub><big>&nbsp;&nbsp;&rArr;&nbsp;&nbsp;PFAS<sup>-</sup></big><sub>(resin bound)</sub><big>&nbsp;+&nbsp;Cl<sup>-</sup></big><sub>(aq)</sub>'''</center>
 
Resins most commonly applied for PFAS treatment are strong base anion exchange resins (SB-AERs) that incorporate [[Wikipedia: Quaternary ammonium cation | quaternary ammonium]] cationic functional groups with hydrocarbon side chains (R-groups) that promote PFAS adsorption by a combination of electrostatic and hydrophobic mechanisms (Figure 1)<ref name="BoyerEtAl2021a"/><ref>Fuller, Mark. Ex Situ Treatment of PFAS-Impacted Groundwater Using Ion Exchange with Regeneration; ER18-1027. [https://serdp-estcp.mil/projects/details/af660326-56e0-4d3c-b80a-1d8a2d613724 Project Website].</ref>. SB-AERs maintain cationic functional groups independent of water pH. Recently introduced ‘PFAS-selective’ AERs show >1,000,000-fold greater selectivity for some PFAS over the Cl<sup>-</sup> initially loaded onto resins<ref name="FangEtAl2021">Fang, Y., Ellis, A., Choi, Y.J., Boyer, T.H., Higgins, C.P., Schaefer, C.E., Strathmann, T.J., 2021. Removal of Per- and Polyfluoroalkyl Substances (PFASs) in Aqueous Film-Forming Foam (AFFF) Using Ion-Exchange and Nonionic Resins. Environmental Science and Technology, 55(8), pp. 5001–5011. [https://doi.org/10.1021/acs.est.1c00769 doi: 10.1021/acs.est.1c00769]</ref>. These resins also show much higher adsorption capacities for PFAS (mg PFAS adsorbed per gram of adsorbent media) than granular activated carbon (GAC) adsorbents.
 
 
PFAS of concern include a wide range of structures, including [[Wikipedia: Perfluoroalkyl carboxylic acids | perfluoroalkyl carboxylic acids (PFCAs)]] and [[Wikipedia: Perfluorosulfonic acids | perfluoroalkyl sulfonic acids (PFSAs)]] of varying carbon chain length<ref>Interstate Technology Regulatory Council (ITRC), 2023. Technical Resources for Addressing Environmental Releases of Per- and Polyfluoroalkyl Substances (PFAS). [https://pfas-1.itrcweb.org/ ITRC PFAS Website]</ref>. As such, affinity for adsorption to AERs is heavily dependent upon PFAS structure<ref name="BoyerEtAl2021a"/><ref name="DixitEtAl2021"/>. In general, it has been found that the extent of adsorption increases with increasing chain length, and that PFSAs adsorb more strongly than PFCAs of similar chain length (Figure 2)<ref name="FangEtAl2021"/><ref>Gagliano, E., Sgroi, M., Falciglia, P.P., Vagliasindi, F.G.A., Roccaro, P., 2020. Removal of Poly- and Perfluoroalkyl Substances (PFAS) from Water by Adsorption: Role of PFAS Chain Length, Effect of Organic Matter and Challenges in Adsorbent Regeneration. Water Research, 171, Article 115381. [https://doi.org/10.1016/j.watres.2019.115381 doi: 10.1016/j.watres.2019.115381]</ref>. The chain length-dependence supports the conclusion that PFAS-resin hydrophobic mechanisms contribute to adsorption. Adsorption of polyfluorinated structures also depend on structure and prevailing charge, with adsorption of zwitterionic species (containing both anionic and cationic groups in the same structure) to AERs being documented despite having a net neutral charge<ref name="FangEtAl2021"/>.
 
  
==Reactors for Treatment of PFAS-Contaminated Water==
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*The VI Diagnosis Toolkit for Assessing Vapor Intrusion Pathways and Impacts in Neighborhoods Overlying Dissolved Chlorinated Solvent Plumes, ESTCP Project ER-201501, Final Report<ref name="JohnsonEtAl2020"/>
Anion exchange treatment of water is accomplished by pumping contaminated water through fixed bed reactors filled with AERs (Figure 3). A common configuration involves flowing water through two reactors arranged in a lead-lag configuration<ref name="WoodardEtAl2017">Woodard, S., Berry, J., Newman, B., 2017. Ion Exchange Resin for PFAS Removal and Pilot Test Comparison to GAC. Remediation, 27(3), pp. 19–27. [https://doi.org/10.1002/rem.21515 doi: 10.1002/rem.21515]</ref>. Water flows through the pore spaces in close contact with resin beads. Sufficient contact time needs to be provided, referred to as empty bed contact time (EBCT), to allow PFAS to diffuse from the water into the resin structure and adsorb to exchange sites. Typical EBCTs for AER treatment of PFAS are 2-5 min, shorter than contact times recommended for granular activated carbon (GAC) adsorbents (≥10 min)<ref name="LiuEtAl2022">Liu, C. J., Murray, C.C., Marshall, R.E., Strathmann, T.J., Bellona, C., 2022. Removal of Per- and Polyfluoroalkyl Substances from Contaminated Groundwater by Granular Activated Carbon and Anion Exchange Resins: A Pilot-Scale Comparative Assessment. Environmental Science: Water Research and Technology, 8(10), pp. 2245–2253. [https://doi.org/10.1039/D2EW00080F doi: 10.1039/D2EW00080F]</ref><ref>Liu, C.J., Werner, D., Bellona, C., 2019. Removal of Per- and Polyfluoroalkyl Substances (PFASs) from Contaminated Groundwater Using Granular Activated Carbon: A Pilot-Scale Study with Breakthrough Modeling. Environmental Science: Water Research and Technology, 5(11), pp. 1844–1853. [https://doi.org/10.1039/C9EW00349E doi: 10.1039/C9EW00349E]</ref>. The higher adsorption capacities and shorter EBCTs of AERs enable use of much less media and smaller vessels than GAC, reducing expected capital costs for AER treatment systems<ref name="EllisEtAl2023">Ellis, A.C., Boyer, T.H., Fang, Y., Liu, C.J., Strathmann, T.J., 2023. Life Cycle Assessment and Life Cycle Cost Analysis of Anion Exchange and Granular Activated Carbon Systems for Remediation of Groundwater Contaminated by Per- and Polyfluoroalkyl Substances (PFASs). Water Research, 243, Article 120324. [https://doi.org/10.1016/j.watres.2023.120324 doi: 10.1016/j.watres.2023.120324]</ref>.
 
  
Like other adsorption media, PFAS will initially adsorb to media encountered near the inlet side of the reactor, but as ion exchange sites become saturated with PFAS, the active zone of adsorption will begin to migrate through the packed bed with increasing volume of water treated. Moreover, some PFAS with lower affinity for exchange sites (e.g., shorter-chain PFAS that are less hydrophobic) will be displaced by competition from other PFAS (e.g., longer-chain PFAS that are more hydrophobic) and move further along the bed to occupy open sites<ref name="EllisEtAl2022">Ellis, A.C., Liu, C.J., Fang, Y., Boyer, T.H., Schaefer, C.E., Higgins, C.P., Strathmann, T.J., 2022. Pilot Study Comparison of Regenerable and Emerging Single-Use Anion Exchange Resins for Treatment of Groundwater Contaminated by per- and Polyfluoroalkyl Substances (PFASs). Water Research, 223, Article 119019. [https://doi.org/10.1016/j.watres.2022.119019 doi: 10.1016/j.watres.2022.119019]&nbsp;&nbsp; [[Media: EllisEtAl2022.pdf | Open Access Manuscript]]</ref>. Eventually, PFAS will start to breakthrough into the effluent from the reactor, typically beginning with the shorter-chain compounds. The initial breakthrough of shorter-chain PFAS is similar to the behavior observed for AER treatment of inorganic contaminants.
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*CPM Test Guidelines: Use of Controlled Pressure Method Testing for Vapor Intrusion Pathway Assessment, ESTCP Project ER-201501, Technical Report<ref name="JohnsonEtAl2021">Johnson, P.C., Guo, Y., Dahlen, P., 2021. CPM Test Guidelines: Use of Controlled Pressure Method Testing for Vapor Intrusion Pathway Assessment.  ESTCP ER-201501, Technical Report. [https://serdp-estcp.mil/projects/details/a0d8bafd-c158-4742-b9fe-5f03d002af71 Project Website]&nbsp;&nbsp; [[Media: ER-201501_Technical_Report.pdf | Technical_Report.pdf]]</ref>    
  
Upon breakthrough, treatment is halted, and the exhausted resins are either replaced with fresh media or regenerated before continuing treatment. Most vendors are currently operating AER treatment systems for PFAS in single-use mode where virgin media is delivered to replace exhausted resins, which are transported off-site for disposal or incineration<ref name="BoyerEtAl2021a"/>. As an alternative, some providers are developing regenerable AER treatment systems, where exhausted resins are regenerated on-site by desorbing PFAS from the resins using a combination of salt brine (typically ≥1 wt% NaCl) and cosolvent (typically ≥70 vol% methanol)<ref name="BoyerEtAl2021a"/><ref name="BoyerEtAl2021b">Boyer, T.H., Ellis, A., Fang, Y., Schaefer, C.E., Higgins, C.P., Strathmann, T.J., 2021. Life Cycle Environmental Impacts of Regeneration Options for Anion Exchange Resin Remediation of PFAS Impacted Water. Water Research, 207, Article 117798. [https://doi.org/10.1016/j.watres.2021.117798 doi: 10.1016/j.watres.2021.117798]&nbsp;&nbsp; [[Media: BoyerEtAl2021b.pdf | Open Access Manuscript]]</ref><ref>Houtz, E., (projected completion 2025). Treatment of PFAS in Groundwater with Regenerable Anion Exchange Resin as a Bridge to PFAS Destruction, Project ER23-8391. [https://serdp-estcp.mil/projects/details/a12b603d-0d4a-4473-bf5b-069313a348ba/treatment-of-pfas-in-groundwater-with-regenerable-anion-exchange-resin-as-a-bridge-to-pfas-destruction Project Website].</ref>. This mode of operation allows for longer term use of resins before replacement, but requires more complex and extensive site infrastructure. Cosolvent in the resulting waste regenerant can be recycled by distillation, which reduces chemical inputs and lowers the volume of PFAS-contaminated still bottoms requiring further treatment or disposal<ref name="BoyerEtAl2021b"/>. Currently, there is active research on various technologies for destruction of PFAS concentrates in AER still bottoms residuals<ref name="StrathmannEtAl2020">Strathmann, T.J., Higgins, C., Deeb, R., 2020. Hydrothermal Technologies for On-Site Destruction of Site Investigation Wastes Impacted by PFAS, Final Report - Phase I. SERDP Project ER18-1501. [https://serdp-estcp.mil/projects/details/b34d6396-6b6d-44d0-a89e-6b22522e6e9c Project Website]&nbsp;&nbsp; [[Media: ER18-1501.pdf | Report.pdf]]</ref><ref name="HuangEtAl2021">Huang, Q., Woodard, S., Nickleson, M., Chiang, D., Liang, S., Mora, R., 2021. Electrochemical Oxidation of Perfluoroalkyl Acids in Still Bottoms from Regeneration of Ion Exchange Resins Phase I - Final Report. SERDP Project ER18-1320. [https://serdp-estcp.mil/projects/details/ccaa70c4-b40a-4520-ba17-14db2cd98e8f Project Website]&nbsp;&nbsp; [[Media: ER18-1320.pdf | Report.pdf]]</ref>.
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*VI Diagnosis Toolkit User Guide, ESTCP Project ER-201501<ref name="JohnsonEtAl2022">Johnson, P.C., Guo, Y., and Dahlen, P., 2022. VI Diagnosis Toolkit User Guide, ESTCP ER-201501, User Guide. [https://serdp-estcp.mil/projects/details/a0d8bafd-c158-4742-b9fe-5f03d002af71 Project Website]&nbsp;&nbsp; [[Media: ER-201501_User_Guide.pdf | User_Guide.pdf]]</ref>
  
==Field Demonstrations==
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==Background==
Field pilot studies are critical to demonstrating the effectiveness and expected costs of PFAS treatment technologies. A growing number of pilot studies testing the performance of commercially available AERs to treat PFAS-contaminated groundwater, including sites impacted by historical use of aqueous film-forming foam (AFFF), have been published recently (Figure 4)
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[[File:ChangFig2.png | thumb | 400px| Figure 1. Example of instrumentation used for OPTICS monitoring.]]
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[[File:ChangFig1.png | thumb | 400px| Figure 2. 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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Nationwide, the liability due to contaminated sediments is estimated in the trillions of dollars. Stakeholders are assessing and developing remedial strategies for contaminated sediment sites in major harbors and waterways throughout the U.S. The mobility of contaminants in surface water is a primary transport and risk mechanism<ref>Thibodeaux, L.J., 1996. Environmental Chemodynamics: Movement of Chemicals in Air, Water, and Soil, 2nd Edition, Volume 110 of Environmental Science and Technology: A Wiley-Interscience Series of Texts and Monographs. John Wiley & Sons, Inc. 624 pages. ISBN: 0-471-61295-2</ref><ref>United States Environmental Protection Agency (USEPA), 2005. Contaminated Sediment Remediation Guidance for Hazardous Waste Sites. Office of Superfund Remediation and Technology Innovation Report, EPA-540-R-05-012. [[Media: 2005-USEPA-Contaminated_Sediment_Remediation_Guidance.pdf | Report.pdf]]</ref><ref>Lick, W., 2008. Sediment and Contaminant Transport in Surface Waters. CRC Press. 416 pages. [https://doi.org/10.1201/9781420059885 doi:  10.1201/9781420059885]</ref>; therefore, long-term monitoring of both particulate- and dissolved-phase contaminant concentration prior to, during, and following remedial action is necessary to document 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 (due to safety concerns and standby requirements for resources) in capturing the effects of episodic events (e.g., storms) that are important to consider in site risk assessment and remedy selection. 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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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 (Figure 1), 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) (Figure 2).
  
In comparison to other reported PFAS destruction techniques, PRD offers several advantages:  
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==Technology Overview==
*Relative to UV/sodium sulfite and UV/sodium iodide systems, the fitted degradation rates in the micelle-accelerated PRD reaction system were ~18 and ~36 times higher, indicating the key role of the self-assembled micelle in creating a confined space for rapid PFAS destruction<ref name="ChenEtAl2020"/>. The negatively charged hydrated electron associated with the positively charged cetyltrimethylammonium ion (CTA<sup>+</sup>) forms the surfactant micelle to trap molecules with similar structures, selectively mineralizing compounds with both hydrophobic and hydrophilic groups (e.g., PFAS).
+
The principle behind OPTICS is based on the relationship between optical properties of natural waters and the particles and dissolved material contained within them<ref>Boss, E. and Pegau, W.S., 2001. Relationship of light scattering at an angle in the backward direction to the backscattering coefficient. Applied Optics, 40(30), pp. 5503-5507. [https://doi.org/10.1364/AO.40.005503 doi: 10.1364/AO.40.005503]</ref><ref>Boss, E., Twardowski, M.S., Herring, S., 2001. Shape of the particulate beam spectrum and its inversion to obtain the shape of the particle size distribution. Applied Optics, 40(27), pp. 4884-4893. [https://doi.org/10.1364/AO.40.004885 doi:10/1364/AO.40.004885]</ref><ref>Babin, M., Morel, A., Fournier-Sicre, V., Fell, F., Stramski, D., 2003. Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration. Limnology and Oceanography, 48(2), pp. 843-859. [https://doi.org/10.4319/lo.2003.48.2.0843 doi: 10.4319/lo.2003.48.2.0843]&nbsp;&nbsp; [[Media: BabinEtAl2003.pdf | Open Access Article]]</ref><ref>Coble, P., Hu, C., Gould, R., Chang, G., Wood, M., 2004. Colored dissolved organic matter in the coastal ocean: An optical tool for coastal zone environmental assessment and management. Oceanography, 17(2), pp. 50-59. [https://doi.org/10.5670/oceanog.2004.47 doi: 10.5670/oceanog.2004.47]&nbsp;&nbsp; [[Media: CobleEtAl2004.pdf | Open Access Article]]</ref><ref>Sullivan, J.M., Twardowski, M.S., Donaghay, P.L., Freeman, S.A., 2005. Use of optical scattering to discriminate particle types in coastal waters. Applied Optics, 44(9), pp. 1667–1680. [https://doi.org/10.1364/AO.44.001667 doi: 10.1364/AO.44.001667]</ref><ref>Twardowski, M.S., Boss, E., Macdonald, J.B., Pegau, W.S., Barnard, A.H., Zaneveld, J.R.V., 2001. A model for estimating bulk refractive index from the optical backscattering ratio and the implications for understanding particle composition in case I and case II waters. Journal of Geophysical Research: Oceans, 106(C7), pp. 14,129-14,142. [https://doi.org/10.1029/2000JC000404 doi: 10/1029/2000JC000404]&nbsp;&nbsp; [[Media: TwardowskiEtAl2001.pdf | Open Access Article]]</ref><ref>Chang, G.C., Barnard, A.H., McLean, S., Egli, P.J., Moore, C., Zaneveld, J.R.V., Dickey, T.D., Hanson, A., 2006. In situ optical variability and relationships in the Santa Barbara Channel: implications for remote sensing. Applied Optics, 45(15), pp. 3593–3604. [https://doi.org/10.1364/AO.45.003593 doi: 10.1364/AO.45.003593]</ref><ref>Slade, W.H. and Boss, E., 2015. Spectral attenuation and backscattering as indicators of average particle size. Applied Optics, 54(24), pp. 7264-7277. [https://doi.org/10.1364/AO.54.007264 doi: 10/1364/AO.54.007264]&nbsp;&nbsp; [[Media: SladeBoss2015.pdf | Open Access Article]]</ref>. Surface water COPCs such as heavy metals and polychlorinated biphenyls (PCBs) are hydrophobic in nature and tend to sorb to materials in the water column, which have unique optical signatures that can be measured at high-resolution using ''in situ'', commercially available aquatic sensors<ref>Agrawal, Y.C. and Pottsmith, H.C., 2000. Instruments for particle size and settling velocity observations in sediment transport. Marine Geology, 168(1-4), pp. 89-114. [https://doi.org/10.1016/S0025-3227(00)00044-X doi: 10.1016/S0025-3227(00)00044-X]</ref><ref>Boss, E., Pegau, W.S., Gardner, W.D., Zaneveld, J.R.V., Barnard, A.H., Twardowski, M.S., Chang, G.C., Dickey, T.D., 2001. Spectral particulate attenuation and particle size distribution in the bottom boundary layer of a continental shelf. Journal of Geophysical Research: Oceans, 106(C5), pp. 9509-9516. [https://doi.org/10.1029/2000JC900077  doi: 10.1029/2000JC900077]&nbsp;&nbsp; [[Media: BossEtAl2001.pdf | Open Access Article]]</ref><ref>Boss, E., Pegau, W.S., Lee, M., Twardowski, M., Shybanov, E., Korotaev, G. Baratange, F., 2004. Particulate backscattering ratio at LEO 15 and its use to study particle composition and distribution. Journal of Geophysical Research: Oceans, 109(C1), Article C01014. [https://doi.org/10.1029/2002JC001514 doi: 10.1029/2002JC001514]&nbsp;&nbsp; [[Media: BossEtAl2004.pdf | Open Access Article]]</ref><ref>Briggs, N.T., Slade, W.H., Boss, E., Perry, M.J., 2013. Method for estimating mean particle size from high-frequency fluctuations in beam attenuation or scattering measurement. Applied Optics, 52(27), pp. 6710-6725. [https://doi.org/10.1364/AO.52.006710 doi: 10.1364/AO.52.006710]&nbsp;&nbsp; [[Media: BriggsEtAl2013.pdf | Open Access Article]]</ref>. Therefore, high-resolution concentrations of COPCs can be accurately and robustly derived from ''in situ'' measurements using statistical methods.
*The PRD reaction does not require solid catalysts or electrodes, which can be expensive to acquire and difficult to regenerate or dispose.  
 
*The aqueous solution is not heated or pressurized, and the UV wavelength used does not cause direct water [[Wikipedia: Photodissociation | photolysis]], therefore the energy input to the system is more directly employed to destroy PFAS, resulting in greater energy efficiency.
 
*Since the reaction is performed at ambient temperature and pressure, there are limited concerns regarding environmental health and safety or volatilization of PFAS compared to heated and pressurized systems.  
 
*Due to the reductive nature of the reaction, there is no formation of unwanted byproducts resulting from oxidative processes, such as [[Wikipedia: Perchlorate | perchlorate]] generation during electrochemical oxidation<ref>Veciana, M., Bräunig, J., Farhat, A., Pype, M. L., Freguia, S., Carvalho, G., Keller, J., Ledezma, P., 2022. Electrochemical Oxidation Processes for PFAS Removal from Contaminated Water and Wastewater: Fundamentals, Gaps and Opportunities towards Practical Implementation. Journal of Hazardous Materials, 434, Article 128886. [https://doi.org/10.1016/j.jhazmat.2022.128886 doi: 10.1016/j.jhazmat.2022.128886]</ref><ref>Trojanowicz, M., Bojanowska-Czajka, A., Bartosiewicz, I., Kulisa, K., 2018. Advanced Oxidation/Reduction Processes Treatment for Aqueous Perfluorooctanoate (PFOA) and Perfluorooctanesulfonate (PFOS) – A Review of Recent Advances. Chemical Engineering Journal, 336, pp. 170–199. [https://doi.org/10.1016/j.cej.2017.10.153 doi: 10.1016/j.cej.2017.10.153]</ref><ref>Wanninayake, D.M., 2021. Comparison of Currently Available PFAS Remediation Technologies in Water: A Review. Journal of Environmental Management, 283, Article 111977. [https://doi.org/10.1016/j.jenvman.2021.111977 doi: 10.1016/j.jenvman.2021.111977]</ref>.
 
*Aqueous fluoride ions are the primary end products of PRD, enabling real-time reaction monitoring with a fluoride [[Wikipedia: Ion-selective electrode | ion selective electrode (ISE)]], which is far less expensive and faster than relying on PFAS analytical data alone to monitor system performance.
 
  
===Disadvantages===
+
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.  
*The CTAB additive is only partially consumed during the reaction, and although CTAB is not problematic when discharged to downstream treatment processes that incorporate aerobic digestors, CTAB can be toxic to surface waters and anaerobic digestors. Therefore, disposal options for treated solutions will need to be evaluated on a site-specific basis. Possible options include removal of CTAB from solution for reuse in subsequent PRD treatments, or implementation of an oxidation reaction to degrade CTAB.  
 
*The PRD reaction rate decreases in water matrices with high levels of total dissolved solids (TDS). It is hypothesized that in high TDS solutions (e.g., ion exchange still bottoms with TDS of 200,000 ppm), the presence of ionic species inhibits the association of the electron donor with the micelle, thus decreasing the reaction rate.
 
*The PRD reaction rate decreases in water matrices with very low UV transmissivity. Low UV transmissivity (i.e., < 1 %) prevents the penetration of UV light into the solution, such that the utilization efficiency of UV light decreases.
 
  
==State of the Art==
+
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.
  
===Technical Performance===
+
OPTICS ''in situ'' measurement parameters include, but are not limited to current velocity, conductivity, temperature, depth, turbidity, dissolved oxygen, and fluorescence of chlorophyll-a and dissolved organic matter. Instrumentation for these measurements is commercially available, robust, deployable in a wide variety of configurations (e.g., moored, vessel-mounted, etc.), powered by batteries, and records data internally and/or transmits data in real-time. The physical, optical, and water quality instrumentation is compact and self-contained. The modularity and automated nature of the OPTICS measurement system enables robust, long-term, autonomous data collection for near-continuous monitoring.  
[[File:WittFig2.png | thumb |400px| Figure 2. Enspired Solutions<small><sup>TM</sup></small> commercial PRD PFAS destruction equipment, the PFASigator<small><sup>TM</sup></small>. Dimensions are 8 feet long by 4 feet wide by 9 feet tall.]]
 
  
{| class="wikitable mw-collapsible" style="float:left; margin-right:20px; text-align:center;"
+
[[File:ChangFig3.png | thumb | 400px| Figure 3. OPTICS to characterize COPC variability in the context of site processes at BCSA. (A) Tidal oscillations (Elev.<sub>MSL</sub>) and precipitation (Precip.). (B) (D) OPTICS-derived particulate mercury (PHg) and methylmercury (PMeHg) and total PCBs (TPCBs). Open circles represent discrete water sample data.]] 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.
|+Table 1. Percent decreases from initial PFAS concentrations during benchtop testing of PRD treatment in different water matrices
 
|-
 
! Analytes
 
!
 
! GW
 
! FF
 
! AFFF<br>Rinsate
 
! AFF<br>(diluted 10X)
 
! IDW NF
 
|-
 
| &Sigma; Total PFAS<small><sup>a</sup></small> (ND=0)
 
| rowspan="9" style="background-color:white;" | <p style="writing-mode: vertical-rl">% Decrease<br>(Initial Concentration, &mu;g/L)</p>
 
| 93%<br>(370) || 96%<br>(32,000) || 89%<br>(57,000) || 86 %<br>(770,000) || 84%<br>(82)
 
|-
 
| &Sigma; Total PFAS (ND=MDL) || 93%<br>(400) || 86%<br>(32,000) || 90%<br>(59,000) || 71%<br>(770,000) || 88%<br>(110)
 
|-
 
| &Sigma; Total PFAS (ND=RL) || 94%<br>(460) || 96%<br>(32,000) || 91%<br>(66,000) || 34%<br>(770,000) || 92%<br>(170)
 
|-
 
| &Sigma; Highly Regulated PFAS<small><sup>b</sup></small> (ND=0) || >99%<br>(180) || >99%<br>(20,000) || 95%<br>(20,000) || 92%<br>(390,000) || 95%<br>(50)
 
|-
 
| &Sigma; Highly Regulated PFAS (ND=MDL) || >99%<br>(180) || 98%<br>(20,000) || 95%<br>(20,000) || 88%<br>(390,000) || 95%<br> (52)
 
|-
 
| &Sigma; Highly Regulated PFAS (ND=RL) || >99%<br>(190) || 93%<br>(20,000) || 95%<br>(20,000) || 79%<br>(390,000) || 95%<br>(55)
 
|-
 
| &Sigma; High Priority PFAS<small><sup>c</sup></small> (ND=0) || 91%<br>(180) || 98%<br>(20,000) || 85%<br>(20,000) || 82%<br>(400,000) || 94%<br>(53)
 
|-
 
| &Sigma; High Priority PFAS (ND=MDL) || 91%<br>(190) || 94%<br>(20,000) || 85%<br>(20,000) || 79%<br>(400,000) || 86%<br>(58)
 
|-
 
| &Sigma; High Priority PFAS (ND=RL) || 92%<br>(200) || 87%<br>(20,000) || 86%<br>(21,000) || 70%<br>(400,000) || 87%<br>(65)
 
|-
 
| Fluorine mass balance<small><sup>d</sup></small> || ||106% || 109% || 110% || 65% || 98%
 
|-
 
| Sorbed organic fluorine<small><sup>e</sup></small> || || 4% || 4% || 33% || N/A || 31%
 
|-
 
| colspan="7" style="background-color:white; text-align:left" | <small>Notes:<br>GW = groundwater<br>GW FF = groundwater foam fractionate<br>AFFF rinsate = rinsate collected from fire system decontamination<br>AFFF (diluted 10x) = 3M Lightwater AFFF diluted 10x<br>IDW NF = investigation derived waste nanofiltrate<br>ND = non-detect<br>MDL = Method Detection Limit<br>RL = Reporting Limit<br><small><sup>a</sup></small>Total PFAS = 40 analytes + unidentified PFCA precursors<br><small><sup>b</sup></small>Highly regulated PFAS = PFNA, PFOA, PFOS, PFHxS, PFBS, HFPO-DA<br><small><sup>c</sup></small>High priority PFAS = PFNA, PFOA, PFHxA, PFBA, PFOS, PFHxS, PFBS, HFPO-DA<br><small><sup>d</sup></small>Ratio of the final to the initial organic fluorine plus inorganic fluoride concentrations<br><small><sup>e</sup></small>Percent of organic fluorine that sorbed to the reactor walls during treatment<br></small>
 
|}
 
</br>
 
The&nbsp;PRD&nbsp;reaction&nbsp;has&nbsp;been validated at the bench scale for the destruction of PFAS in a variety of environmental samples from Department of Defense sites (Table 1). Enspired Solutions<small><sup>TM</sup></small> has designed and manufactured a fully automatic commercial-scale piece of equipment called PFASigator<small><sup>TM</sup></small>, specializing in PRD PFAS destruction (Figure 2). This equipment is modular and scalable, has a small footprint, and can be used alone or in series with existing water treatment trains. The PFASigator<small><sup>TM</sup></small> employs commercially available UV reactors and monitoring meters that have been used in the water industry for decades. The system has been tested on PRD efficiency operational parameters, and key metrics were proven to be consistent with benchtop studies.  
 
  
Bench scale PRD tests were performed for the following samples collected from Department of Defense sites: groundwater (GW), groundwater foam fractionate (FF), firefighting truck rinsate ([[Wikipedia: Firefighting foam | AFFF]] Rinsate), 3M Lightwater AFFF, investigation derived waste nanofiltrate (IDW NF), [[Wikipedia: Ion exchange | ion exchange]] still bottom (IX SB), and Ansulite AFFF. The PRD treatment was more effective in low conductivity/TDS solutions. Generally, PRD reaction rates decrease for solutions with a TDS > 10,000 ppm, with an upper limit of 30,000 ppm. Ansulite AFFF and IX SB samples showed low destruction efficiencies during initial screening tests, which was primarily attributed to their high TDS concentrations. Benchtop testing data are shown in Table 1 for the remaining five sample matrices.
+
==Applications==
 +
[[File:ChangFig4.png | thumb | 400px| Figure 4. OPTICS reveals baseflow daily cycling and confirms storm-induced particle-bound COPC resuspension and mobilization through bank interaction. (A) Flow rate (Q) and precipitation (Precip). (B) – (C) OPTICS-derived particulate mercury (PHg) and methylmercury (PMeHg). Open circles represent discrete water sample data.]]
 +
[[File:ChangFig5.png | thumb | 400px| Figure 5. Three-dimensional volume plot of high spatial resolution OPTICS-derived PCBs in exceedance of baseline showing that PCBs were discharged from the outfall (yellow arrow), remained in suspension, and dispersed elsewhere before settling.]]  
 +
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 (Figure 3) facilitated focused and effective site remediation and management decisions that could not be determined based on periodic discrete samples alone, despite over seven years of monitoring at different locations throughout the system over a range of different seasons, tidal phases, and environmental conditions. The BCSA OPTICS methodology and its results have undergone official peer review overseen by the U.S. Environmental Protection Agency (USEPA), and those results have been published in peer-reviewed literature<ref name="ChangEtAl2019"/>.  
  
During treatment, PFOS and PFOA concentrations decreased 96% to >99% and 77% to 97%, respectively. For the PFAS with proposed drinking water Maximum Contaminant Levels (MCLs) recently established by the USEPA (PFNA, PFOA, PFOS, PFHxS, PFBS, and HFPO-DA), concentrations decreased >99% for GW, 93% for FF, 95% for AFFF Rinsate and IDW NF, and 79% for AFFF (diluted 10x) during the treatment time allotted. Meanwhile, the total PFAS concentrations, including all 40 known PFAS analytes and unidentified perfluorocarboxylic acid (PFCA) precursors, decreased from 34% to 96% following treatment. All of these concentration reduction values were calculated by using reporting limits (RL) as the concentrations for non-detects.  
+
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 (Figure 4) 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"/>.  
  
Excellent fluorine/fluoride mass balance was achieved. There was nearly a 1:1 conversion of organic fluorine to free inorganic fluoride ion during treatment of GW, FF and AFFF Rinsate. The 3M Lightwater AFFF (diluted 10x) achieved only 65% fluorine mass balance, but this was likely due to high adsorption of PFAS to the reactor.
+
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 (Figure 5). More details regarding this study were presented by Chang et al. in 2024<ref name="ChangEtAl2024"/>.
  
===Application===
+
==Summary==
Due to the first-order kinetics of PRD, destruction of PFAS is most energy efficient when paired with a pre-concentration technology, such as foam fractionation (FF), nanofiltration, reverse osmosis, or resin/carbon adsorption, that remove PFAS from water. Application of the PFASigator<small><sup>TM</sup></small> is therefore proposed as a part of a PFAS treatment train that includes a pre-concentration step.
+
OPTICS provides:
 +
*High resolution surface water chemical contaminant characterization
 +
*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.
  
The first pilot study with the PFASigator<small><sup>TM</sup></small> was conducted in late 2023 at an industrial facility in Michigan with PFAS-impacted groundwater. The goal of the pilot study was to treat the groundwater to below the limits for regulatory discharge permits. For the pilot demonstration, the PFASigator<small><sup>TM</sup></small> was paired with an FF unit, which pre-concentrated the PFAS into a foamate that was pumped into the PFASigator<small><sup>TM</sup></small> for batch PFAS destruction. Residual PFAS remaining after the destruction batch was treated by looping back the PFASigator<small><sup>TM</sup></small> effluent to the FF system influent. During the one-month field pilot duration, site-specific discharge limits were met, and steady state operation between the FF unit and PFASigator<small><sup>TM</sup></small> was achieved such that the PFASigator<small><sup>TM</sup></small> destroyed the required concentrated PFAS mass and no off-site disposal of PFAS contaminated waste was required.
+
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.  
  
 
==References==
 
==References==

Latest revision as of 20:39, 15 July 2024

Assessing Vapor Intrusion (VI) Impacts in Neighborhoods with Groundwater Contaminated by Chlorinated Volatile Organic Chemicals (CVOCs)

The VI Diagnosis Toolkit[1] is a set of tools that can be used individually or in combination to assess vapor intrusion (VI) impacts at one or more buildings overlying regional-scale dissolved chlorinated solvent-impacted groundwater plumes. The strategic use of these tools can lead to confident and efficient neighborhood-scale VI pathway assessments.

Related Article(s):

Contributor(s):

  • Paul C. Johnson, Ph.D.
  • Paul Dahlen, Ph.D.
  • Yuanming Guo, Ph.D.

Key Resource(s):

  • The VI Diagnosis Toolkit for Assessing Vapor Intrusion Pathways and Impacts in Neighborhoods Overlying Dissolved Chlorinated Solvent Plumes, ESTCP Project ER-201501, Final Report[1]
  • CPM Test Guidelines: Use of Controlled Pressure Method Testing for Vapor Intrusion Pathway Assessment, ESTCP Project ER-201501, Technical Report[2]
  • VI Diagnosis Toolkit User Guide, ESTCP Project ER-201501[3]

Background

Figure 1. Example of instrumentation used for OPTICS monitoring.
Figure 2. 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.

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[4][5][6]; therefore, long-term monitoring of both particulate- and dissolved-phase contaminant concentration prior to, during, and following remedial action is necessary to document 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.

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 (due to safety concerns and standby requirements for resources) in capturing the effects of episodic events (e.g., storms) that are important to consider in site risk assessment and remedy selection. 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.

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[7][8][9][10][11][12]. The OPTICS tool integrates commercial off-the-shelf in situ aquatic sensors (Figure 1), periodic discrete surface water sample collection, and a multi-parameter statistical prediction model[13][14] to provide high temporal and/or spatial resolution characterization of surface water chemicals of potential concern (COPCs) (Figure 2).

Technology Overview

The principle behind OPTICS is based on the relationship between optical properties of natural waters and the particles and dissolved material contained within them[15][16][17][18][19][20][21][22]. 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[23][24][25][26]. Therefore, high-resolution concentrations of COPCs can be accurately and robustly derived from in situ measurements using statistical methods.

The OPTICS method is analogous to the commonly used empirical derivation of total suspended solids concentration (TSS) from optical turbidity using linear regression[27]. 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.

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[13][14]. 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.

OPTICS in situ measurement parameters include, but are not limited to current velocity, conductivity, temperature, depth, turbidity, dissolved oxygen, and fluorescence of chlorophyll-a and dissolved organic matter. Instrumentation for these measurements is commercially available, robust, deployable in a wide variety of configurations (e.g., moored, vessel-mounted, etc.), powered by batteries, and records data internally and/or transmits data in real-time. The physical, optical, and water quality instrumentation is compact and self-contained. The modularity and automated nature of the OPTICS measurement system enables robust, long-term, autonomous data collection for near-continuous monitoring.

Figure 3. OPTICS to characterize COPC variability in the context of site processes at BCSA. (A) Tidal oscillations (Elev.MSL) and precipitation (Precip.). (B) – (D) OPTICS-derived particulate mercury (PHg) and methylmercury (PMeHg) and total PCBs (TPCBs). Open circles represent discrete water sample data.

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.

Applications

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.
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.

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 (Figure 3) facilitated focused and effective site remediation and management decisions that could not be determined based on periodic discrete samples alone, despite over seven years of monitoring at different locations throughout the system over a range of different seasons, tidal phases, and environmental conditions. The BCSA OPTICS methodology and its results have undergone official peer review overseen by the U.S. Environmental Protection Agency (USEPA), and those results have been published in peer-reviewed literature[7].

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 (Figure 4) 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[8].

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 (Figure 5). More details regarding this study were presented by Chang et al. in 2024[9].

Summary

OPTICS provides:

  • High resolution surface water chemical contaminant characterization
  • Cost-effective monitoring and assessment
  • Versatile and modular monitoring with capability for real-time telemetry
  • Data necessary for development and validation of conceptual site models
  • A key line of evidence for designing and evaluating remedies.

Because OPTICS monitoring involves deployment of autonomous sampling instrumentation, a substantially greater volume of data can be collected using this technique compared to traditional sampling, and at a far lower cost. A large volume of data supports evaluation of chemical contaminant concentrations over a range of spatial and temporal scales, and the system can be customized for a variety of environmental applications. OPTICS helps quantify contaminant mass flux and the relative contribution of local transport and source areas to net contaminant transport. OPTICS delivers a strong line of evidence for evaluating contaminant sources, fate, and transport, and for supporting the design of a remedy tailored to address site-specific, risk-driving conditions. The improved understanding of site processes aids in the development of mitigation measures that minimize site risks.

References

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See Also