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==Abiotic Reduction of Munitions Constituents==
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==Assessing Vapor Intrusion (VI) Impacts in Neighborhoods with Groundwater Contaminated by Chlorinated Volatile Organic Chemicals (CVOCs)==  
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Munition compounds (MCs) often contain one or more nitro (-NO<sub>2</sub>) functional groups which makes them susceptible to abiotic reduction, i.e., transformation by accepting electrons from a chemical electron donor. In soil and groundwater, the most prevalent electron donors are natural organic carbon and iron minerals. Understanding the kinetics and mechanisms of abiotic reduction of MCs by carbon and iron constituents in soil is not only essential for evaluating the environmental fate of MCs but also key to developing cost-efficient remediation strategies. This article summarizes the recent advances in our understanding of MC reduction by carbon and iron based reductants.
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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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<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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*[[Munitions Constituents]]  
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*[[Munitions Constituents - Alkaline Degradation]]
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*[[Vapor Intrusion (VI)]]
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*[[Vapor Intrusion – Sewers and Utility Tunnels as Preferential Pathways]]
  
 
'''Contributor(s):'''  
 
'''Contributor(s):'''  
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*Dr. Jimmy Murillo-Gelvez
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*Paula Andrea Cárdenas-Hernández
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*Paul C. Johnson, Ph.D.
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*Dr. Pei Chiu
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*Paul Dahlen, Ph.D.
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*Yuanming Guo, Ph.D.
  
 
'''Key Resource(s):'''
 
'''Key Resource(s):'''
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* Schwarzenbach, Gschwend, and Imboden, 2016. Environmental Organic Chemistry, 3rd ed.<ref name="Schwarzenbach2016">Schwarzenbach, R.P., Gschwend, P.M., and Imboden, D.M., 2016. Environmental Organic Chemistry, 3rd Edition. John Wiley and Sons, Ltd, 1024 pages.  ISBN: 978-1-118-76723-8</ref>
 
  
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==Introduction==
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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"/>
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[[File:AbioMCredFig1.PNG | thumb |left|300px|Figure 1. Common munitions compounds. TNT and RDX are legacy explosives. DNAN, NTO, and NQ are insensitive MCs (IMCs) widely used as replacement for legacy explosives.]]
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Legacy and insensitive MCs (Figure 1.) are susceptible to reductive transformation in soil and groundwater. Many redox-active constituents in the subsurface, especially those containing organic carbon, Fe(II), and sulfur can mediate MC reduction. Specific examples include Fe(II)-organic complexes<ref name="Naka2006">Naka, D., Kim, D., and Strathmann, T.J., 2006. Abiotic Reduction of Nitroaromatic Compounds by Aqueous Iron(II)−Catechol Complexes. Environmental Science and Technology 40(9), pp. 3006–3012.  [https://doi.org/10.1021/es060044t DOI: 10.1021/es060044t]</ref><ref name="Naka2008">Naka, D., Kim, D., Carbonaro, R.F., and Strathmann, T.J., 2008. Abiotic reduction of nitroaromatic contaminants by iron(II) complexes with organothiol ligands. Environmental Toxicology and Chemistry, 27(6), pp. 1257–1266.  [https://doi.org/10.1897/07-505.1 DOI: 10.1897/07-505.1]</ref><ref name="Hartenbach2008">Hartenbach, A.E., Hofstetter, T.B., Aeschbacher, M., Sander, M., Kim, D., Strathmann, T.J., Arnold, W.A., Cramer, C.J., and Schwarzenbach, R.P., 2008. Variability of Nitrogen Isotope Fractionation during the Reduction of Nitroaromatic Compounds with Dissolved Reductants. Environmental Science and Technology 42(22), pp. 8352–8359.  [https://doi.org/10.1021/es801063u DOI: 10.1021/es801063u]</ref><ref name="Kim2009">Kim, D., Duckworth, O.W., and Strathmann, T.J., 2009. Hydroxamate siderophore-promoted reactions between iron(II) and nitroaromatic groundwater contaminants. Geochimica et Cosmochimica Acta, 73(5), pp. 1297–1311.  [https://doi.org/10.1016/j.gca.2008.11.039 DOI: 10.1016/j.gca.2008.11.039]</ref><ref name="Kim2007">Kim, D., and Strathmann, T.J., 2007. Role of Organically Complexed Iron(II) Species in the Reductive Transformation of RDX in Anoxic Environments. Environmental Science and Technology, 41(4), pp. 1257–1264.  [https://doi.org/10.1021/es062365a DOI: 10.1021/es062365a]</ref>, iron oxides in the presence of aqueous Fe(II)<ref name="Colón2006">Colón, D., Weber, E.J., and Anderson, J.L., 2006. QSAR Study of the Reduction of Nitroaromatics by Fe(II) Species. Environmental Science and Technology, 40(16), pp. 4976–4982.  [https://doi.org/10.1021/es052425x DOI: 10.1021/es052425x]</ref><ref name="Luan2013">Luan, F., Xie, L., Li, J., and Zhou, Q., 2013. Abiotic reduction of nitroaromatic compounds by Fe(II) associated with iron oxides and humic acid. Chemosphere, 91(7), pp. 1035–1041.  [https://doi.org/10.1016/j.chemosphere.2013.01.070 DOI: 10.1016/j.chemosphere.2013.01.070]</ref><ref name="Gorski2016">Gorski, C.A., Edwards, R., Sander, M., Hofstetter, T.B., and Stewart, S.M., 2016. Thermodynamic Characterization of Iron Oxide–Aqueous Fe<sup>2+</sup> Redox Couples. Environmental Science and Technology, 50(16), pp. 8538–8547.  [https://doi.org/10.1021/acs.est.6b02661 DOI: 10.1021/acs.est.6b02661]</ref><ref name="Fan2016">Fan, D., Bradley, M.J., Hinkle, A.W., Johnson, R.L., and Tratnyek, P.G., 2016. Chemical Reactivity Probes for Assessing Abiotic Natural Attenuation by Reducing Iron Minerals. Environmental Science and Technology, 50(4), pp. 1868–1876.  [https://doi.org/10.1021/acs.est.5b05800 DOI: 10.1021/acs.est.5b05800]</ref><ref name="Jones2016">Jones, A.M., Kinsela, A.S., Collins, R.N., and Waite, T.D., 2016. The reduction of 4-chloronitrobenzene by Fe(II)-Fe(III) oxide systems - correlations with reduction potential and inhibition by silicate. Journal of Hazardous Materials, 320, pp. 143–149.  [https://doi.org/10.1016/j.jhazmat.2016.08.031 DOI: 10.1016/j.jhazmat.2016.08.031]</ref><ref name="Klausen1995">Klausen, J., Troeber, S.P., Haderlein, S.B., and Schwarzenbach, R.P., 1995. Reduction of Substituted Nitrobenzenes by Fe(II) in Aqueous Mineral Suspensions. Environmental Science and Technology, 29(9), pp. 2396–2404.  [https://doi.org/10.1021/es00009a036 DOI: 10.1021/es00009a036]</ref><ref name="Strehlau2016">Strehlau, J.H., Stemig, M.S., Penn, R.L., and Arnold, W.A., 2016. Facet-Dependent Oxidative Goethite Growth As a Function of Aqueous Solution Conditions. Environmental Science and Technology, 50(19), pp. 10406–10412.  [https://doi.org/10.1021/acs.est.6b02436 DOI: 10.1021/acs.est.6b02436]</ref><ref name="Elsner2004">Elsner, M., Schwarzenbach, R.P., and Haderlein, S.B., 2004. Reactivity of Fe(II)-Bearing Minerals toward Reductive Transformation of Organic Contaminants. Environmental Science and Technology, 38(3), pp. 799–807.  [https://doi.org/10.1021/es0345569 DOI: 10.1021/es0345569]</ref><ref name="Colón2008">Colón, D., Weber, E.J., and Anderson, J.L., 2008. Effect of Natural Organic Matter on the Reduction of Nitroaromatics by Fe(II) Species. Environmental Science and Technology, 42(17), pp. 6538–6543.  [https://doi.org/10.1021/es8004249 DOI: 10.1021/es8004249]</ref><ref name="Stewart2018">Stewart, S.M., Hofstetter, T.B., Joshi, P. and Gorski, C.A., 2018. Linking Thermodynamics to Pollutant Reduction Kinetics by Fe<sup>2+</sup> Bound to Iron Oxides. Environmental Science and Technology, 52(10), pp. 5600–5609.  [https://doi.org/10.1021/acs.est.8b00481 DOI: 10.1021/acs.est.8b00481]&nbsp;&nbsp; [https://pubs.acs.org/doi/pdf/10.1021/acs.est.8b00481 Open access article.]</ref><ref name="Klupinski2004">Klupinski, T.P., Chin, Y.P., and Traina, S.J., 2004. Abiotic Degradation of Pentachloronitrobenzene by Fe(II):  Reactions on Goethite and Iron Oxide Nanoparticles. Environmental Science and Technology, 38(16), pp. 4353–4360.  [https://doi.org/10.1021/es035434j DOI: 10.1021/es035434j]</ref>, magnetite<ref name="Klausen1995"/><ref name="Elsner2004"/><ref name="Heijman1993">Heijman, C.G., Holliger, C., Glaus, M.A., Schwarzenbach, R.P., and Zeyer, J., 1993. Abiotic Reduction of 4-Chloronitrobenzene to 4-Chloroaniline in a Dissimilatory Iron-Reducing Enrichment Culture. Applied and Environmental Microbiology, 59(12), pp. 4350–4353. [https://doi.org/10.1128/aem.59.12.4350-4353.1993 DOI: 10.1128/aem.59.12.4350-4353.1993]&nbsp;&nbsp; [https://journals.asm.org/doi/reader/10.1128/aem.59.12.4350-4353.1993 Open access article.]</ref><ref name="Gorski2009">Gorski, C.A., and Scherer, M.M., 2009. Influence of Magnetite Stoichiometry on Fe<sup>II</sup> Uptake and Nitrobenzene Reduction. Environmental Science and Technology, 43(10), pp. 3675–3680.  [https://doi.org/10.1021/es803613a DOI: 10.1021/es803613a]</ref><ref name="Gorski2010">Gorski, C.A., Nurmi, J.T., Tratnyek, P.G., Hofstetter, T.B. and Scherer, M.M., 2010. Redox Behavior of Magnetite: Implications for Contaminant Reduction. Environmental Science and Technology, 44(1), pp. 55–60.  [https://doi.org/10.1021/es9016848 DOI: 10.1021/es9016848]</ref>, Fe(II)-bearing clays<ref name"Hofstetter2006">Hofstetter, T.B., Neumann, A., and Schwarzenbach, R.P., 2006. Reduction of Nitroaromatic Compounds by Fe(II) Species Associated with Iron-Rich Smectites. Environmental Science and Technology, 40(1), pp. 235–242.  [https://doi.org/10.1021/es0515147 DOI: 10.1021/es0515147]</ref><ref name"Schultz2000">Schultz, C. A., and Grundl, T.J., 2000. pH Dependence on Reduction Rate of 4-Cl-Nitrobenzene by Fe(II)/Montmorillonite Systems. Environmental Science and Technology 34(17), pp. 3641–3648. [https://doi.org/10.1021/es990931e DOI: 10.1021/es990931e]</ref><ref name"Luan2015a">Luan, F., Gorski, C.A., and Burgos, W.D., 2015. Linear Free Energy Relationships for the Biotic and Abiotic Reduction of Nitroaromatic Compounds. Environmental Science and Technology, 49(6), pp. 3557–3565.  [https://doi.org/10.1021/es5060918 DOI: 10.1021/es5060918]</ref><ref name"Luan2015b">Luan, F., Liu, Y., Griffin, A.M., Gorski, C.A. and Burgos, W.D., 2015. Iron(III)-Bearing Clay Minerals Enhance Bioreduction of Nitrobenzene by ''Shewanella putrefaciens'' CN32. Environmental Science and Technology, 49(3), pp. 1418–1426.  [https://doi.org/10.1021/es504149y DOI: 10.1021/es504149y]</ref><ref name"Hofstetter2003">Hofstetter, T.B., Schwarzenbach, R.P. and Haderlein, S.B., 2003. Reactivity of Fe(II) Species Associated with Clay Minerals. Environmental Science and Technology, 37(3), pp. 519–528.  [https://doi.org/10.1021/es025955r DOI: 10.1021/es025955r]</ref><ref name"Neumann2008">Neumann, A., Hofstetter, T.B., Lüssi, M., Cirpka, O.A., Petit, S., and Schwarzenbach, R.P., 2008. Assessing the Redox Reactivity of Structural Iron in Smectites Using Nitroaromatic Compounds As Kinetic Probes. Environmental Science and Technology, 42(22), pp. 8381–8387.  [https://doi.org/10.1021/es801840x DOI: 10.1021/es801840x]</ref><ref name"Hofstetter2008">Hofstetter, T.B., Neumann, A., Arnold, W.A., Hartenbach, A.E., Bolotin, J., Cramer, C.J., and Schwarzenbach, R.P., 2008. Substituent Effects on Nitrogen Isotope Fractionation During Abiotic Reduction of Nitroaromatic Compounds. Environmental Science and Technology, 42(6), pp. 1997–2003.  [https://doi.org/10.1021/es702471k DOI: 10.1021/es702471k]</ref>, hydroquinones (as surrogates of natural organic matter)<ref name="Hartenbach2008"/><ref name="Schwarzenbach1990">Schwarzenbach, R.P., Stierli, R., Lanz, K., and Zeyer, J., 1990. Quinone and Iron Porphyrin Mediated Reduction of Nitroaromatic Compounds in Homogeneous Aqueous Solution. Environmental Science and Technology, 24(10), pp. 1566–1574.  [https://doi.org/10.1021/es00080a017 DOI: 10.1021/es00080a017]</ref><ref name="Tratnyek1989">Tratnyek, P.G., and Macalady, D.L., 1989. Abiotic Reduction of Nitro Aromatic Pesticides in Anaerobic Laboratory Systems. Journal of Agricultural and Food Chemistry, 37(1), pp. 248–254.  [https://doi.org/10.1021/jf00085a058 DOI: 10.1021/jf00085a058]</ref><ref name="Hofstetter1999">Hofstetter, T.B., Heijman, C.G., Haderlein, S.B., Holliger, C. and Schwarzenbach, R.P., 1999. Complete Reduction of TNT and Other (Poly)nitroaromatic Compounds under Iron-Reducing Subsurface Conditions. Environmental Science and Technology, 33(9), pp. 1479–1487.  [https://doi.org/10.1021/es9809760 DOI: 10.1021/es9809760]</ref><ref name="Murillo-Gelvez2019">Murillo-Gelvez, J., Hickey, K.P., Di Toro, D.M., Allen, H.E., Carbonaro, R.F., and Chiu, P.C., 2019. Experimental Validation of Hydrogen Atom Transfer Gibbs Free Energy as a Predictor of Nitroaromatic Reduction Rate Constants. Environmental Science and Technology, 53(10), pp. 5816–5827.  [https://doi.org/10.1021/acs.est.9b00910 DOI: 10.1021/acs.est.9b00910]</ref><ref name="Niedźwiecka2017">Niedźwiecka, J.B., Drew, S.R., Schlautman, M.A., Millerick, K.A., Grubbs, E., Tharayil, N. and Finneran, K.T., 2017. Iron and Electron Shuttle Mediated (Bio)degradation of 2,4-Dinitroanisole (DNAN). Environmental Science and Technology, 51(18), pp. 10729–10735.  [https://doi.org/10.1021/acs.est.7b02433 DOI: 10.1021/acs.est.7b02433]</ref><ref name="Kwon2006">Kwon, M.J., and Finneran, K.T., 2006. Microbially Mediated Biodegradation of Hexahydro-1,3,5-Trinitro-1,3,5- Triazine by Extracellular Electron Shuttling Compounds. Applied and Environmental Microbiology, 72(9), pp. 5933–5941.  [https://doi.org/10.1128/AEM.00660-06 DOI: 10.1128/AEM.00660-06]&nbsp;&nbsp; [https://journals.asm.org/doi/reader/10.1128/AEM.00660-06 Open access article.]</ref>, dissolved organic matter<ref name="Dunnivant1992">Dunnivant, F.M., Schwarzenbach, R.P., and Macalady, D.L., 1992. Reduction of Substituted Nitrobenzenes in Aqueous Solutions Containing Natural Organic Matter. Environmental Science and Technology, 26(11), pp. 2133–2141.  [https://doi.org/10.1021/es00035a010 DOI: 10.1021/es00035a010]</ref><ref name="Luan2010">Luan, F., Burgos, W.D., Xie, L., and Zhou, Q., 2010. Bioreduction of Nitrobenzene, Natural Organic Matter, and Hematite by Shewanella putrefaciens CN32. Environmental Science and Technology, 44(1), pp. 184–190.  [https://doi.org/10.1021/es901585z DOI: 10.1021/es901585z]</ref><ref name="Murillo-Gelvez2021">Murillo-Gelvez, J., di Toro, D.M., Allen, H.E., Carbonaro, R.F., and Chiu, P.C., 2021. Reductive Transformation of 3-Nitro-1,2,4-triazol-5-one (NTO) by Leonardite Humic Acid and Anthraquinone-2,6-disulfonate (AQDS). Environmental Science and Technology, 55(19), pp. 12973–12983.  [https://doi.org/10.1021/acs.est.1c03333 DOI: 10.1021/acs.est.1c03333]</ref>, black carbon
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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>    
  
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==Application of Plasma for the Treatment of PFAS-Contaminated Water==
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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>
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Several research groups have investigated the use of plasma to treat and remove PFAS from contaminated water<ref name="Hayashi2015">Hayashi, R., Obo, H., Takeuchi, N., and Yasuoka, K., 2015. Decomposition of Perfluorinated Compounds in Water by DC Plasma within Oxygen Bubbles. Electrical Engineering in Japan, 190(3), pp.9-16. [https://doi.org/10.1002/eej.22499 DOI: 10.1002/eej.22499]&nbsp;&nbsp;  [https://onlinelibrary.wiley.com/doi/full/10.1002/eej.22499 Open access article].</ref><ref name="Matsuya2014">Matsuya, Y., Takeuchi, N., Yasuoka, K., 2014. Relationship Between Reaction Rate of Perfluorocarboxylic Acid Decomposition at a Plasma-Liquid Interface and Adsorbed Amount. Electrical Engineering in Japan, 188(2), pp.1-8. [https://doi.org/10.1002/eej.22526 DOI:  10.1002/eej.22526]&nbsp;&nbsp; [https://onlinelibrary.wiley.com/doi/full/10.1002/eej.22526 Open access article].</ref><ref name="Stratton2017">Stratton, G.R., Dai, F., Bellona, C.L., Holsen, T.M., Dickenson, E.R., and Mededovic Thagard, S., 2017. Plasma-Based Water Treatment: Efficient Transformation of Perfluoroalkyl Substances in Prepared Solutions and Contaminated Groundwater. Environmental Science and Technology, 51(3), pp.1643-1648. [https://doi.org/10.1021/acs.est.6b04215 DOI: 10.1021/acs.est.6b04215]</ref><ref name="Takeuchi2013">Takeuchi, N., Kitagawa, Y., Kosugi, A., Tachibana, K., Obo, H., and Yasuoka, K., 2013. Plasma-Liquid Interfacial Reaction in Decomposition of Perfluoro Surfactants. Journal of Physics D: Applied Physics, 47(4), p.045203. [https://doi.org/10.1088/0022-3727/47/4/045203 DOI: 10.1088/0022-3727/47/4/045203]</ref><ref name="Yasuoka2011">Yasuoka, K., Sasaki, K., and Hayashi, R., 2011. An Energy-Efficient Process for Decomposing Perfluorooctanoic and Perfluorooctane Sulfonic Acids Using DC Plasmas Generated within Gas Bubbles. Plasma Sources Science and Technology, 20(3), p. 034009. [https://doi.org/10.1088/0963-0252/20/3/034009 DOI: 10.1088/0963-0252/20/3/034009]</ref><ref name="Yasuoka2010">Yasuoka, K., Sasaki, K., Hayashi, R., Kosugi, A., and Takeuchi, N., 2010. Degradation of Perfluoro Compounds and F<sup>-</sup> Recovery in Water Using Discharge Plasmas Generated within Gas Bubbles. International Journal of Plasma Environmental Science and Technology, 4(2), 113–117.  [http://ijpest.com/Contents/04/2/PDF/04-02-113.pdf Open access article].</ref><ref name="Lewis2020">Lewis, A.J., Joyce, T., Hadaya, M., Ebrahimi, F., Dragiev, I., Giardetti, N., Yang, J., Fridman, G., Rabinovich, A., Fridman, A.A., McKenzie, E.R., and Sales, C.M., 2020. Rapid Degradation of PFAS in Aqueous Solutions by Reverse Vortex Flow Gliding Arc Plasma. Environmental Science: Water Research and Technology, 6(4), pp.1044-1057. [https://doi.org/10.1039/c9ew01050e DOI: 10.1039/c9ew01050e]</ref><ref name="Saleem2020">Saleem, M., Biondo, O., Sretenović, G., Tomei, G., Magarotto, M., Pavarin, D., Marotta, E. and Paradisi, C., 2020. Comparative Performance Assessment of Plasma Reactors for the Treatment of PFOA; Reactor Design, Kinetics, Mineralization and Energy Yield. Chemical Engineering Journal, 382, p.123031. [https://doi.org/10.1016/j.cej.2019.123031 DOI: 10.1016/j.cej.2019.123031]</ref><ref name="Palma2021">Palma, D., Papagiannaki, D., Lai, M., Binetti, R., Sleiman, M., Minella, M. and Richard, C., 2021. PFAS Degradation in Ultrapure and Groundwater Using Non-Thermal Plasma. Molecules, 26(4), p. 924. [https://doi.org/10.3390/molecules26040924 DOI: 10.3390/molecules26040924]&nbsp;&nbsp; [https://www.mdpi.com/1420-3049/26/4/924/htm Open access article].</ref>.  Of those studies, the Enhanced Contact (EC) plasma reactor developed by researchers at Clarkson University is one of the most promising in terms of treatment time, cost, the range of PFAS treated and scale up/throughput. Their process has been shown to degrade PFOA, PFOS, and other PFAS in a variety of PFAS-impacted water sources.
 
  
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[[File: Plasma4PFASFig3.png | thumb |left|350px|Figure 3. Degradation profiles of combined PFOA and PFOS concentrations in investigation derived waste (IDW) obtained from nine different Air Force site investigations. In all the IDW samples, both PFOS and PFOA were removed to below EPA’s lifetime health advisory level concentrations (70 ng/L) in < 1 minute of treatment, demonstrating the lack of sensitivity of the plasma-based process to the effects of co-contaminants<ref name="Singh2019a"/>.]]
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==Background==
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[[File: Plasma4PFASFig4.png | thumb |550px|Figure 4. (a) Mobile plasma treatment trailer depicting the (b) plasma side of the trailer featuring two plasma reactors and the plasma-generating network; and (c) control and plumbing side of the plasma trailer featuring multiple rotameters, storage tanks and plumbing.]]
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[[File:ChangFig2.png | thumb | 400px| Figure 1. Example of instrumentation used for OPTICS monitoring.]]
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In the EC plasma reactor (Figure 2), argon gas is continuously pumped through the solution to form a layer of foam and thus concentrate PFAS at the gas-liquid interface where plasma is formed. The process is able to lower the concentrations of PFOA and PFOS in groundwater obtained from multiple DoD sites to below Environmental Protection Agency’s (EPA’s) lifetime health advisory level (HAL) of 70 parts per trillion (70 nanogram per liter, ng/L)<ref name="USEPA2016">US Environmental Protection Agency (EPA), 2016. Lifetime Health Advisories and Health Effects Support Documents for Perfluorooctanoic Acid and Perfluorooctane Sulfonate. Federal Register, Notices, 81(101), p. 33250-33251. [https://www.epa.gov/sites/production/files/2016-05/documents/2016-12361.pdf Free download].</ref> within 1 minute of treatment (Figure 3) with energy requirements much lower than those of alternative technologies (~2-6 kWh/m3 for plasma vs. 5000 kWh/m3 for persulfate, photochemical oxidation and sonolytic processes and 132 kWh/m3 for electrochemical oxidation)<ref name="Singh2019a"/><ref name="Nzeribe2019"/>. The EC plasma reactor owes its high efficacy to the plasma reactor design, in particular to the gas bubbling through submerged diffusers to transport PFAS to the plasma-liquid interface and thus minimize bulk liquid limitations.  
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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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[[File: Plasma4PFASFig5.png | thumb |left|350px|Figure 5. Plasma destruction of PFAS-impacted groundwater at the fire-training area at Wright-Patterson Air Force Base<ref name="Nau-Hix2021"/>. One cycle = 18 gallons.]]
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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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In 2019, a mobile plasma treatment system (Figure 4) was successfully demonstrated for the treatment of PFAS-contaminated groundwater at the fire-training area at Wright-Patterson Air Force Base<ref name="Nau-Hix2021">Nau-Hix, C., Multari, N., Singh, R.K., Richardson, S., Kulkarni, P., Anderson, R.H., Holsen, T.M. and Mededovic Thagard, S., 2021. Field Demonstration of a Pilot-Scale Plasma Reactor for the Rapid Removal of Poly-and Perfluoroalkyl Substances in Groundwater. ACS ES&T Water, 1(3), pp. 680-687. [https://doi.org/10.1021/acsestwater.0c00170 DOI: 10.1021/acsestwater.0c00170]</ref>.
 
  
−
Over 300 gallons of PFAS-impacted groundwater were treated at a maximum flowrate of 1.1  gallons per minute (gpm) resulting in ≥90% reduction (mean percent removal of 99.7%) of long-chain PFAAs (fluorocarbon chain ≥ 6) and PFAS precursors in a single pass through the reactor (Figure 5) at a treatment cost of $7.30/1000 gallons<ref name="Nau-Hix2021"/>. As expected, the removal of short-chain PFAS was slower due to their lower potential for interfacial adsorption compared to long-chain PFAS. However, post-field laboratory studies revealed that the addition of a cationic surfactant such as CTAB (cetrimonium bromide) minimizes bulk liquid transport limitations for short-chain PFAS by electrostatically interacting with these compounds and transporting them to the plasma-liquid interface where they are degraded<ref name="Palma2021"/>. Both bench and pilot-scale EC plasma-based process have been extended for the treatment of PFAS in membrane concentrate, ion exchange brine, and landfill leachate<ref name="Singh2020">Singh, R.K., Multari, N., Nau-Hix, C., Woodard, S., Nickelsen, M., Mededovic Thagard, S. and Holsen, T.M., 2020. Removal of Poly- And Per-Fluorinated Compounds from Ion Exchange Regenerant Still Bottom Samples in a Plasma Reactor. Environmental Science and Technology, 54(21), pp.13973-13980. [https://doi.org/10.1021/acs.est.0c02158 DOI: 10.1021/acs.est.0c02158]</ref><ref name="Singh2021">Singh, R.K., Brown, E., Mededovic Thagard, S., and Holsen, T.M., 2021. Treatment of PFAS-Containing Landfill Leachate Using an Enhanced Contact Plasma Reactor. Journal of Hazardous Materials, 408, p.124452. [https://doi.org/10.1016/j.jhazmat.2020.124452 DOI: 10.1016/j.jhazmat.2020.124452]</ref>.  
+
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.  
  
−
As a part of a currently-funded ESTCP project (ESTCP ER20-5535)<ref name="Mededovic2020">Mededovic, S., 2020. An Innovative Plasma Technology for Treatment of AFFF Rinsate from Firefighting Delivery Systems. Environmental Security Technology Certification Program (ESTCP), Project ER20-5355. [https://www.serdp-estcp.org/Program-Areas/Environmental-Restoration/ER20-5355  Project Overview]</ref>, the Clarkson University team with the support of GSI Environmental Inc. is evaluating the effectiveness of their plasma process in treating diluted aqueous film-forming foams (AFFFs) as well as the benefits of pre-oxidation of PFAS precursors in high concentration AFFF solutions in terms of post-oxidation plasma treatment time, destruction efficiency and cost.
+
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).
  
−
==Advantages and Limitations of the Technology for PFAS Treatment==
+
==Technology Overview==
−
===Advantages:===
+
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.
−
* High removal rates of long-chain PFAS (C5-C8) due to the production of versatile reactive species
 
−
* Requires no chemical additions and produces no residual waste
 
−
* Total organic carbon (TOC) concentration and other non-surfactant co-contaminants do not influence the process efficiency
 
−
* The process is mobile and scalable
 
−
* Versatile: can be used in batch and continuous systems
 
  
−
===Limitations:===
+
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. 
−
* Limited removal of short-chain PFAS due to their inability to concentrate at plasma-liquid interfaces. Addition of surfactants such as CTAB improves their removal and degradation rates.
+
 
−
* Excessive foaming caused by bubbling argon gas through a solution containing high (>10 mg/L) concentrations of long-chain (surfactant) PFAS may interfere with the formation of plasma.
+
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.
 +
 
 +
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: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.
 +
 
 +
==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"/>.
 +
 
 +
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"/>.
 +
 
 +
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"/>.
  
 
==Summary==
 
==Summary==
−
PFAS are susceptible to plasma treatment because the hydrophobic PFAS accumulates at the gas-liquid interface, exposing more of the PFAS to the plasma. Plasma-based treatment of PFAS contaminated water successfully degrades PFOA and PFOS to below the EPA health advisory level of 70 ppt and accomplishes the near complete destruction of other PFAS within a short treatment time. PFAS concentration reductions of ≥90% and post-treatment concentrations below laboratory detection levels are common for long chain PFAS and precursors.
+
OPTICS provides:
−
The lack of sensitivity of plasma to co-contaminants, coupled with high PFAS removal and defluorination efficiencies, makes plasma-based water treatment a promising technology for the remediation of PFAS-contaminated water. The plasma treatment process is currently developed for ''ex situ'' application and can also be integrated into a treatment train<ref name="Richardson2021">Richardson, S., 2021. Nanofiltration Followed by Electrical Discharge Plasma for Destruction of PFAS and Co-occurring Chemicals in Groundwater: A Treatment Train Approach. Environmental Security Technology Certification Program (ESTCP), Project Number ER21-5136. [https://www.serdp-estcp.org/Program-Areas/Environmental-Restoration/ER21-5136  Project Overview]</ref>.
+
*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==
 
==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

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