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==Downscaled High Resolution Datasets for Climate Change Projections==
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==PFAS Destruction by Ultraviolet/Sulfite Treatment==  
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Global climate models (GCMs) have generated projections of temperature, precipitation and other important climate change parameters with spatial resolutions of 100 to 300 km. However, higher spatial resolution information is required to assess threats to individual installations or regions.  A variety of “downscaling” approaches have been used to produce high spatial resolution output (datasets) from the global climate models at scales that are useful for evaluating potential threats to critical infrastructure at regional and local scales.  These datasets enable development of information about projections produced from various climate models, about downscaling to achieve desired locational specificity, and about selecting the appropriate dataset(s) to use for performing specific assessments. This article describes how these datasets can be accessed and used to evaluate potential climate change impacts.
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The ultraviolet (UV)/sulfite based reductive defluorination process has emerged as an effective and practical option for generating hydrated electrons (''e<sub><small>aq</small></sub><sup><big>'''-'''</big></sup>'' ) which can destroy [[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) | PFAS]] in water. It offers significant advantages for PFAS destruction, including significant defluorination, high treatment efficiency for long-, short-, and ultra-short chain PFAS without mass transfer limitations, selective reactivity by hydrated electrons, low energy consumption, low capital and operation costs, and no production of harmful byproducts. A UV/sulfite treatment system designed and developed by Haley and Aldrich (EradiFluor<sup><small>TM</small></sup><ref name="EradiFluor">Haley and Aldrich, Inc. (commercial business), 2024. EradiFluor. [https://www.haleyaldrich.com/about-us/applied-research-program/eradifluor/ Comercial Website]</ref>) has been demonstrated in two field demonstrations in which it achieved near-complete defluorination and greater than 99% destruction of 40 PFAS analytes measured by EPA method 1633.
 
<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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* [[Climate Change Primer]]
 
  
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'''Contributor(s):''' [[Dr. Rao Kotamarthi]]
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*[[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS)]]
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*[[PFAS Ex Situ Water Treatment]]
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*[[PFAS Sources]]
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*[[PFAS Treatment by Electrical Discharge Plasma]]
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*[[Supercritical Water Oxidation (SCWO)]]
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*[[Photoactivated Reductive Defluorination - PFAS Destruction]]
  
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'''Key Resource(s):'''
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'''Contributors:''' John Xiong, Yida Fang, Raul Tenorio, Isobel Li, and Jinyong Liu
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* Use of Climate Information for Decision-Making and Impacts Research: State of our Understanding<ref name="Kotamarthi2016">Kotamarthi, R., Mearns, L., Hayhoe, K., Castro, C.L., and Wuebble, D., 2016. Use of Climate Information for Decision-Making and Impacts Research: State of Our Understanding. Department of Defense, Strategic Environmental Research and Development Program (SERDP), 55pp. Free download from: [https://www.serdp-estcp.org/content/download/38568/364489/file/Use_of_Climate_Information_for_Decision-Making_Technical_Report.pdf SERDP-ESTCP]</ref>
 
  
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* Applying Climate Change Information to Hydrologic and Coastal Design of Transportation Infrastructure, Design Practices<ref name="Kilgore2019">Kilgore, R., Thomas, W.O. Jr., Douglass, S., Webb, B., Hayhoe, K., Stoner, A., Jacobs, J.M., Thompson, D.B., Herrmann, G.R., Douglas, E., and Anderson, C., 2019. Applying Climate Change Information to Hydrologic and Coastal Design of Transportation Infrastructure, Design Practices. The National Cooperative Highway Research Program, Transportation Research Board, Project 15-61, 154 pages. Free download from: [http://onlinepubs.trb.org/Onlinepubs/nchrp/docs/NCHRP1561_DesignProcedures.pdf The Transportation Research Board]</ref>
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'''Key Resources:'''
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*Defluorination of Per- and Polyfluoroalkyl Substances (PFAS) with Hydrated Electrons: Structural Dependence and Implications to PFAS Remediation and Management<ref name="BentelEtAl2019">Bentel, M.J., Yu, Y., Xu, L., Li, Z., Wong, B.M., Men, Y., Liu, J., 2019. Defluorination of Per- and Polyfluoroalkyl Substances (PFASs) with Hydrated Electrons: Structural Dependence and Implications to PFAS Remediation and Management. Environmental Science and Technology, 53(7), pp. 3718-28. [https://doi.org/10.1021/acs.est.8b06648 doi: 10.1021/acs.est.8b06648]&nbsp; [[Media: BentelEtAl2019.pdf | Open Access Article]]</ref>
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*Accelerated Degradation of Perfluorosulfonates and Perfluorocarboxylates by UV/Sulfite + Iodide: Reaction Mechanisms and System Efficiencies<ref>Liu, Z., Chen, Z., Gao, J., Yu, Y., Men, Y., Gu, C., Liu, J., 2022. Accelerated Degradation of Perfluorosulfonates and Perfluorocarboxylates by UV/Sulfite + Iodide: Reaction Mechanisms and System Efficiencies. Environmental Science and Technology, 56(6), pp. 3699-3709. [https://doi.org/10.1021/acs.est.1c07608 doi: 10.1021/acs.est.1c07608]&nbsp; [[Media: LiuZEtAl2022.pdf | Open Access Article]]</ref>
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*Destruction of Per- and Polyfluoroalkyl Substances (PFAS) in Aqueous Film-Forming Foam (AFFF) with UV-Sulfite Photoreductive Treatment<ref>Tenorio, R., Liu, J., Xiao, X., Maizel, A., Higgins, C.P., Schaefer, C.E., Strathmann, T.J., 2020. Destruction of Per- and Polyfluoroalkyl Substances (PFASs) in Aqueous Film-Forming Foam (AFFF) with UV-Sulfite Photoreductive Treatment. Environmental Science and Technology, 54(11), pp. 6957-67. [https://doi.org/10.1021/acs.est.0c00961 doi: 10.1021/acs.est.0c00961]</ref>
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*EradiFluor<sup>TM</sup><ref name="EradiFluor"/>
  
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* Statistical Downscaling and Bias Correction for Climate Research<ref name="Maraun2018">Maraun, D., and Wildmann, M., 2018. Statistical Downscaling and Bias Correction for Climate Research. Cambridge University Press, Cambridge, UK. 347 pages. [https://doi.org/10.1017/9781107588783 DOI: 10.1017/9781107588783]&nbsp;&nbsp; ISBN: 978-1-107-06605-2</ref>
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==Introduction==
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The hydrated electron (''e<sub><small>aq</small></sub><sup><big>'''-'''</big></sup>'' ) can be described as an electron in solution surrounded by a small number of water molecules<ref name="BuxtonEtAl1988">Buxton, G.V., Greenstock, C.L., Phillips Helman, W., Ross, A.B., 1988. Critical Review of Rate Constants for Reactions of Hydrated Electrons, Hydrogen Atoms and Hydroxyl Radicals (⋅OH/⋅O-) in Aqueous Solution. Journal of Physical and Chemical Reference Data, 17(2), pp. 513-886. [https://doi.org/10.1063/1.555805 doi: 10.1063/1.555805]</ref>. Hydrated electrons can be produced by photoirradiation of solutes, including sulfite, iodide, dithionite, and ferrocyanide, and have been reported in literature to effectively decompose per- and polyfluoroalkyl substances (PFAS) in water. The hydrated electron is one of the most reactive reducing species, with a standard reduction potential of about −2.9 volts. Though short-lived, hydrated electrons react rapidly with many species having more positive reduction potentials<ref name="BuxtonEtAl1988"/>.
  
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* Downscaling Techniques for High-Resolution Climate Projections: From Global Change to Local Impacts<ref name="Kotamarthi2021">Kotamarthi, R., Hayhoe, K., Wuebbles, D., Mearns, L.O., Jacobs, J. and Jurado, J., 2021. Downscaling Techniques for High-Resolution Climate Projections: From Global Change to Local Impacts. Cambridge University Press, Cambridge, UK. 202 pages.  [https://doi.org/10.1017/9781108601269 DOI: 10.1017/9781108601269]&nbsp;&nbsp; ISBN: 978-1-108-47375-0</ref>
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Among the electron source chemicals, sulfite (SO<sub>3</sub><sup>2−</sup>) has emerged as one of the most effective and practical options for generating hydrated electrons to destroy PFAS in water. The mechanism of hydrated electron production in a sulfite solution under ultraviolet is shown in Equation 1 (UV is denoted as ''hv, SO<sub>3</sub><sup><big>'''•-'''</big></sup>'' is the sulfur trioxide radical anion):
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</br>
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::<big>'''Equation 1:'''</big>&nbsp;&nbsp; [[File: XiongEq1.png | 200 px]]
  
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==Downscaling of Global Climate Models==
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The hydrated electron has demonstrated excellent performance in destroying PFAS such as [[Wikipedia:Perfluorooctanesulfonic acid | perfluorooctanesulfonic acid (PFOS)]], [[Wikipedia:Perfluorooctanoic acid|perfluorooctanoic acid (PFOA)]]<ref>Gu, Y., Liu, T., Wang, H., Han, H., Dong, W., 2017. Hydrated Electron Based Decomposition of Perfluorooctane Sulfonate (PFOS) in the VUV/Sulfite System. Science of The Total Environment, 607-608, pp. 541-48. [https://doi.org/10.1016/j.scitotenv.2017.06.197 doi: 10.1016/j.scitotenv.2017.06.197]</ref> and [[Wikipedia: GenX|GenX]]<ref>Bao, Y., Deng, S., Jiang, X., Qu, Y., He, Y., Liu, L., Chai, Q., Mumtaz, M., Huang, J., Cagnetta, G., Yu, G., 2018. Degradation of PFOA Substitute: GenX (HFPO–DA Ammonium Salt): Oxidation with UV/Persulfate or Reduction with UV/Sulfite? Environmental Science and Technology, 52(20), pp. 11728-34. [https://doi.org/10.1021/acs.est.8b02172 doi: 10.1021/acs.est.8b02172]</ref>. Mechanisms include cleaving carbon-to-fluorine (C-F) bonds (i.e., hydrogen/fluorine atom exchange) and chain shortening (i.e., [[Wikipedia: Decarboxylation | decarboxylation]], [[Wikipedia: Hydroxylation | hydroxylation]], [[Wikipedia: Elimination reaction | elimination]], and [[Wikipedia: Hydrolysis | hydrolysis]])<ref name="BentelEtAl2019"/>.
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Some communities and businesses have begun to improve their resilience to climate change by building adaptation plans based on national scale climate datatsets ([https://unfccc.int/topics/adaptation-and-resilience/workstreams/national-adaptation-plans National Adaptation Plans]), regional datasets ([https://www.dec.ny.gov/docs/administration_pdf/crrafloodriskmgmtgdnc.pdf New York State Flood Risk Management Guidance]<ref name="NYDEC2020">New York State Department of Environmental Conservation, 2020. New York State Flood Risk Management Guidance for Implementation of the Community Risk and Resiliency Act. Free download from: [https://www.dec.ny.gov/docs/administration_pdf/crrafloodriskmgmtgdnc.pdf New York State]&nbsp;&nbsp; [[Media: NewYorkState2020.pdf | Report.pdf]]</ref>), and datasets generated at local spatial resolutions. Resilience to the changing climate has also been identified by the US Department of Defense (DoD) as a necessary part of the installation planning and basing process ([https://media.defense.gov/2019/Jan/29/2002084200/-1/-1/1/CLIMATE-CHANGE-REPORT-2019.PDF DoD Report on Effects of a Changing Climate]<ref name="DoD2019">US Department of Defense, 2019. Report on Effects of a Changing Climate to the Department of Defense. Free download from: [https://media.defense.gov/2019/Jan/29/2002084200/-1/-1/1/CLIMATE-CHANGE-REPORT-2019.PDF DoD]&nbsp;&nbsp; [[Media: DoD2019.PDF | Report.pdf]]</ref>). More than 79 installations were identified as facing potential threats from climate change. The threats faced due to changing climate include recurrent flooding, droughts, desertification, wildfires and thawing permafrost.  
 
  
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Assessing the threats climate change poses at regional and local scales requires data with higher spatial resolution than is currently available from global climate models. Global-scale climate models typically have spatial resolutions of 100 to 300 km, and output from these models needs to be spatially and/or temporally disaggregated in order to be useful in performing assessments at smaller scales. The process of producing higher spatial-temporal resolution climate model output from coarser global climate model outputs is referred to as “downscaling” and results in climate change projections (datasets) at scales that are useful for evaluating potential threats to regional and local communities and businesses. These datasets provide information on temperature, precipitation and a variety of other climate variables for current and future climate conditions under various greenhouse gas (GHG) emission scenarios. There are a variety of web-based tools available for accessing these datasets to evaluate potential climate change impacts at regional and local scales.
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==Process Description==
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A commercial UV/sulfite treatment system designed and developed by Haley and Aldrich (EradiFluor<sup><small>TM</small></sup><ref name="EradiFluor"/>) includes an optional pre-oxidation step to transform PFAS precursors (when present) and a main treatment step to break C-F bonds by UV/sulfite reduction. The effluent from the treatment process can be sent back to the influent of a pre-treatment separation system (such as a [[Wikipedia: Foam fractionation | foam fractionation]], [[PFAS Treatment by Anion Exchange | regenerable ion exchange]], or a [[Reverse Osmosis and Nanofiltration Membrane Filtration Systems for PFAS Removal | membrane filtration system]]) for further concentration or sent for off-site disposal in accordance with relevant disposal regulations. A conceptual treatment process diagram is shown in Figure 1. [[File: XiongFig1.png | thumb | left | 600 px | Figure 1: Conceptual Treatment Process for a Concentrated PFAS Stream]]<br clear="left"/>
  
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==Methods for Downscaling==
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==Advantages==
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{| class="wikitable" style="float:right; margin-left:10px;text-align:center;"
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A UV/sulfite treatment system offers significant advantages for PFAS destruction compared to other technologies, including high defluorination percentage, high treatment efficiency for short-chain PFAS without mass transfer limitation, selective reactivity by ''e<sub><small>aq</small></sub><sup><big>'''-'''</big></sup>'', low energy consumption, and the production of no harmful byproducts. A summary of these advantages is provided below:
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|+Table 1.  Two widely used methods for developing downscaled higher resolution climate model projections
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*'''High efficiency for short- and ultrashort-chain PFAS:''' While the degradation efficiency for short-chain PFAS is challenging for some treatment technologies<ref>Singh, R.K., Brown, E., Mededovic Thagard, S., Holson, T.M., 2021. Treatment of PFAS-containing landfill leachate using an enhanced contact plasma reactor. Journal of Hazardous Materials, 408, Article 124452. [https://doi.org/10.1016/j.jhazmat.2020.124452 doi: 10.1016/j.jhazmat.2020.124452]</ref><ref>Singh, R.K., Multari, N., Nau-Hix, C., Woodard, S., Nickelsen, M., Mededovic Thagard, S., Holson, 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. 13973-80. [https://doi.org/10.1021/acs.est.0c02158 doi: 10.1021/acs.est.0c02158]</ref><ref>Nau-Hix, C., Multari, N., Singh, R.K., Richardson, S., Kulkarni, P., Anderson, R.H., Holsen, T.M., Mededovic Thagard S., 2021. Field Demonstration of a Pilot-Scale Plasma Reactor for the Rapid Removal of Poly- and Perfluoroalkyl Substances in Groundwater. American Chemical Society’s Environmental Science and Technology (ES&T) Water, 1(3), pp. 680-87. [https://doi.org/10.1021/acsestwater.0c00170 doi: 10.1021/acsestwater.0c00170]</ref>, the UV/sulfite process demonstrates excellent defluorination efficiency for both short- and ultrashort-chain PFAS, including [[Wikipedia: Trifluoroacetic acid | trifluoroacetic acid (TFA)]] and [[Wikipedia: Perfluoropropionic acid | perfluoropropionic acid (PFPrA)]]. 
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|-
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*'''High defluorination ratio:''' As shown in Figure 3, the UV/sulfite treatment system has demonstrated near 100% defluorination for various PFAS under both laboratory and field conditions.
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!Dynamical Downscaling
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*'''No harmful byproducts:''' While some oxidative technologies, such as electrochemical oxidation, generate toxic byproducts, including perchlorate, bromate, and chlorate, the UV/sulfite system employs a reductive mechanism and does not generate these byproducts.
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!Statistical Downscaling
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*'''Ambient pressure and low temperature:''' The system operates under ambient pressure and low temperature (<60°C), as it utilizes UV light and common chemicals to degrade PFAS. 
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|-
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*'''Low energy consumption:''' The electrical energy per order values for the degradation of [[Wikipedia: Perfluoroalkyl carboxylic acids | perfluorocarboxylic acids (PFCAs)]] by UV/sulfite have been reduced to less than 1.5 kilowatt-hours (kWh) per cubic meter under laboratory conditions. The energy consumption is orders of magnitude lower than that for many other destructive PFAS treatment technologies (e.g., [[Supercritical Water Oxidation (SCWO) | supercritical water oxidation]])<ref>Nzeribe, B.N., Crimi, M., Mededovic Thagard, S., Holsen, T.M., 2019. Physico-Chemical Processes for the Treatment of Per- And Polyfluoroalkyl Substances (PFAS): A Review. Critical Reviews in Environmental Science and Technology, 49(10), pp. 866-915. [https://doi.org/10.1080/10643389.2018.1542916 doi: 10.1080/10643389.2018.1542916]</ref>.
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|Deterministic climate change simulations that output</br>many climate variables with sub-daily information ||Primarily limited to daily temperature and precipitation
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*'''Co-contaminant destruction:''' The UV/sulfite system has also been reported effective in destroying certain co-contaminants in wastewater. For example, UV/sulfite is reported to be effective in reductive dechlorination of chlorinated volatile organic compounds, such as trichloroethene, 1,2-dichloroethane, and vinyl chloride<ref>Jung, B., Farzaneh, H., Khodary, A., Abdel-Wahab, A., 2015. Photochemical degradation of trichloroethylene by sulfite-mediated UV irradiation. Journal of Environmental Chemical Engineering, 3(3), pp. 2194-2202. [https://doi.org/10.1016/j.jece.2015.07.026 doi: 10.1016/j.jece.2015.07.026]</ref><ref>Liu, X., Yoon, S., Batchelor, B., Abdel-Wahab, A., 2013. Photochemical degradation of vinyl chloride with an Advanced Reduction Process (ARP) – Effects of reagents and pH. Chemical Engineering Journal, 215-216, pp. 868-875. [https://doi.org/10.1016/j.cej.2012.11.086 doi: 10.1016/j.cej.2012.11.086]</ref><ref>Li, X., Ma, J., Liu, G., Fang, J., Yue, S., Guan, Y., Chen, L., Liu, X., 2012. Efficient Reductive Dechlorination of Monochloroacetic Acid by Sulfite/UV Process. Environmental Science and Technology, 46(13), pp. 7342-49. [https://doi.org/10.1021/es3008535 doi: 10.1021/es3008535]</ref><ref>Li, X., Fang, J., Liu, G., Zhang, S., Pan, B., Ma, J., 2014. Kinetics and efficiency of the hydrated electron-induced dehalogenation by the sulfite/UV process. Water Research, 62, pp. 220-228. [https://doi.org/10.1016/j.watres.2014.05.051 doi: 10.1016/j.watres.2014.05.051]</ref>.
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|Computationally expensive; hence, limited number of simulations – both</br>GHG emission scenarios and global climate models downscaled||Computationally efficient; hence, downscaled data typically</br>available for many different global climate models and GHG emission scenarios
 
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|-
 
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|May require additional bias correction||Method incorporates bias correction
 
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|-
 
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|Observational data at the downscaled location are not necessary</br>to obtain the downscaled output at the location||Best suited for locations with 30 years or more of observational data
 
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|-
 
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|Does not assume stationarity or in other words the model</br>simulates the future regardless of what has happened in the past||Stationarity assumption - assumes that the statistical relationship between global</br>climate model and observations will remain constant in the future
 
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|}
 
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[[File: Kotamarthi2w2Fig1.jpg | thumb |left| 450px | Figure 1. Typical processes and spatial scales of Regional scale Climate Models. The models may calculate circulation in the atmosphere, cloud processes, precipitation, and land-atmospheric and ocean-atmospheric processes on a limited portion of the Earth, with boundary conditions provided by a Global Climate Model.<ref name="Kotamarthi2016"/>]]
 
  
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There are two main approaches to downscaling. One method, commonly referred to as “statistical downscaling”, uses the empirical-statistical relationships between large-scale weather phenomena and historical local weather data. In this method, these statistical relationships are applied to output generated by global climate models. A second method uses physics-based numerical models (regional-scale climate models or RCMs) of weather and climate that operate over a limited region of the earth (e.g., North America) and at spatial resolutions that are typically 3 to 10 times finer than the global-scale climate models. This method is known as “dynamical downscaling”.  These regional-scale climate models are similar to the global models with respect to their reliance on the principles of physics, but because they operate over only part of the earth, they require information about what is coming in from the rest of the earth as well as what is going out of the limited region of the model. This is generally obtained from a global model.  The primary differences between statistical and dynamical downscaling methods are summarized in Table 1.
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==Limitations==
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Several environmental factors and potential issues have been identified that may impact the performance of the UV/sulfite treatment system, as listed below. Solutions to address these issues are also proposed.
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*Environmental factors, such as the presence of elevated concentrations of natural organic matter (NOM), dissolved oxygen, or nitrate, can inhibit the efficacy of UV/sulfite treatment systems by scavenging available hydrated electrons. Those interferences are commonly managed through chemical additions, reaction optimization, and/or dilution, and are therefore not considered likely to hinder treatment success.
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*Coloration in waste streams may also impact the effectiveness of the UV/sulfite treatment system by blocking the transmission of UV light, thus reducing the UV lamp's effective path length. To address this, pre-treatment may be necessary to enable UV/sulfite destruction of PFAS in the waste stream. Pre-treatment may include the use of strong oxidants or coagulants to consume or remove UV-absorbing constituents.
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*The degradation efficiency is strongly influenced by PFAS molecular structure, with fluorotelomer sulfonates (FTS) and [[Wikipedia: Perfluorobutanesulfonic acid | perfluorobutanesulfonate (PFBS)]] exhibiting greater resistance to degradation by UV/sulfite treatment compared to other PFAS compounds.
  
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It is important to realize that there is no “best” downscaling method or dataset, and that the best method/dataset for a given problem depends on that problem’s specific needs. Several data products based on downscaling higher level spatial data are available ([https://cida.usgs.gov/gdp/ USGS], [http://maca.northwestknowledge.net/ MACA], [https://www.narccap.ucar.edu/ NARCCAP], [https://na-cordex.org/ CORDEX-NA]). The appropriate method and dataset to use depends on the intended application. The method selected should be able to credibly resolve spatial and temporal scales relevant for the application. For example, to develop a risk analysis of frequent flooding, the data product chosen should include precipitation at greater than a diurnal frequency and over multi-decadal timescales. This kind of product is most likely to be available using the dynamical downscaling method.  SERDP reviewed the various advantages and disadvantages of using each type of downscaling method and downscaling dataset, and developed a recommended process that is publicly available<ref name="Kotamarthi2016"/>. In general, the following recommendations should be considered in order to pick the right downscaled dataset for a given analysis:
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==State of the Practice==
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[[File: XiongFig2.png | thumb | 500 px | Figure 2. Field demonstration of EradiFluor<sup><small>TM</small></sup><ref name="EradiFluor"/> for PFAS destruction in a concentrated waste stream in a Mid-Atlantic Naval Air Station: a) Target PFAS at each step of the treatment shows that about 99% of PFAS were destroyed; meanwhile, the final degradation product, i.e., fluoride, increased to 15 mg/L in concentration, demonstrating effective PFAS destruction; b) AOF concentrations at each step of the treatment provided additional evidence to show near-complete mineralization of PFAS. Average results from multiple batches of treatment are shown here.]]
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* When a problem depends on using a large number of climate models and emission scenarios to perform preliminary assessments and to understand the uncertainty range of projections, then using a statistical downscaled dataset is recommended. 
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[[File: XiongFig3.png | thumb | 500 px | Figure 3. Field demonstration of a treatment train (SAFF + EradiFluor<sup><small>TM</small></sup><ref name="EradiFluor"/>) for groundwater PFAS separation and destruction at an Air Force base in California: a) Two main components of the treatment train, i.e. SAFF and EradiFluor<sup><small>TM</small></sup><ref name="EradiFluor"/>; b) Results showed the effective destruction of various PFAS in the foam fractionate. The target PFAS at each step of the treatment shows that about 99.9% of PFAS were destroyed. Meanwhile, the final degradation product, i.e., fluoride, increased to 30 mg/L in concentration, demonstrating effective destruction of PFAS in a foam fractionate concentrate. After a polishing treatment step (GAC) via the onsite groundwater extraction and treatment system, all PFAS were removed to concentrations below their MCLs.]]  
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* When the assessment needs a more extensive parameter list or is analyzing a region with few long-term observational data, dynamically downscaled climate change projections are recommended.
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The effectiveness of UV/sulfite technology for treating PFAS has been evaluated in two field demonstrations using the EradiFluor<sup><small>TM</small></sup><ref name="EradiFluor"/> system. Aqueous samples collected from the system were analyzed using EPA Method 1633, the [[Wikipedia: TOP Assay | total oxidizable precursor (TOP) assay]], adsorbable organic fluorine (AOF) method, and non-target analysis. A summary of each demonstration and their corresponding PFAS treatment efficiency is provided below.  
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*Under the [https://serdp-estcp.mil/ Environmental Security Technology Certification Program (ESTCP)] [https://serdp-estcp.mil/projects/details/4c073623-e73e-4f07-a36d-e35c7acc75b6/er21-5152-project-overview Project ER21-5152], a field demonstration of EradiFluor<sup><small>TM</small></sup><ref name="EradiFluor"/> was conducted at a Navy site on the east coast, and results showed that the technology was highly effective in destroying various PFAS in a liquid concentrate produced from an ''in situ'' foam fractionation groundwater treatment system. As shown in Figure 2a, total PFAS concentrations were reduced from 17,366 micrograms per liter (µg/L) to 195 µg/L at the end of the UV/sulfite reaction, representing 99% destruction. After the ion exchange resin polishing step, all residual PFAS had been removed to the non-detect level, except one compound (PFOS) reported as 1.5 nanograms per liter (ng/L), which is below the current Maximum Contaminant Level (MCL) of 4 ng/L. Meanwhile, the fluoride concentration increased up to 15 milligrams per liter (mg/L), confirming near complete defluorination. Figure 2b shows the adsorbable organic fluorine results from the same treatment test, which similarly demonstrates destruction of 99% of PFAS.
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==Uncertainty in Projections==
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*Another field demonstration was completed at an Air Force base in California, where a treatment train combining [https://serdp-estcp.mil/projects/details/263f9b50-8665-4ecc-81bd-d96b74445ca2 Surface Active Foam Fractionation (SAFF)] and EradiFluor<sup><small>TM</small></sup><ref name="EradiFluor"/> was used to treat PFAS in groundwater. As shown in Figure 3, PFAS analytical data and fluoride results demonstrated near-complete destruction of various PFAS. In addition, this demonstration showed: a) high PFAS destruction ratio was achieved in the foam fractionate, even in very high concentration (up to 1,700 mg/L of booster), and b) the effluent from EradiFluor<sup><small>TM</small></sup><ref name="EradiFluor"/> was sent back to the influent of the SAFF system for further concentration and treatment, resulting in a closed-loop treatment system and no waste discharge from EradiFluor<sup><small>TM</small></sup><ref name="EradiFluor"/>. This field demonstration was conducted with the approval of three regulatory agencies (United States Environmental Protection Agency, California Regional Water Quality Control Board, and California Department of Toxic Substances Control).
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{| class="wikitable" style="float:right; margin-left:10px;text-align:center;"
 
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|+Table 2. Downscaling model characteristics and output<ref name="Kotamarthi2016"/>
 
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|-
 
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!Model or</br>Dataset Name
 
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!Model<br />Method
 
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!Output<br />Variables
 
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!Output<br />Format
 
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!Spatial</br>Resolution
 
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!Time</br>Resolution
 
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|-
 
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| colspan="6" style="text-align: left; background-color:white;" |'''Statistical Downscaled Datasets'''
 
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|-
 
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| [https://worldclim.org/data/index.html WorldClim]<ref name="Hijmans2005">Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G. and Jarvis, A., 2005. Very High Resolution Interpolated Climate Surfaces for Global Land Areas. International Journal of Climatology: A Journal of the Royal Meteorological Society, 25(15), pp 1965-1978. [https://doi.org/10.1002/joc.1276 DOI: 10.1002/joc.1276]</ref>
 
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|Delta||T(min, max,</br>avg), Pr||NetCDF||grid: 30 arc sec to</br>10 arc min||month
 
−
|-
 
−
| Bias Corrected / Spatial</br>Disaggregation (BCSD)<ref name="Wood2002">Wood, A.W., Maurer, E.P., Kumar, A. and Lettenmaier, D.P., 2002. Long‐range experimental hydrologic forecasting for the eastern United States. Journal of Geophysical Research: Atmospheres, 107(D20), 4429, pp. ACL6 1-15. [https://doi.org/10.1029/2001JD000659 DOI:10.1029/2001JD000659]&nbsp;&nbsp; Free access article available from: [https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2001JD000659 American Geophysical Union]&nbsp;&nbsp; [[Media: Wood2002.pdf | Report.pdf ]]</ref>
 
−
|Empirical Quantile</br>Mapping||Runoff,</br>Streamflow||NetCDF||grid: 7.5 arc min||day
 
−
|-
 
−
| [https://cida.usgs.gov/thredds/catalog.html?dataset=dcp Asynchronous Regional Regression</br>Model (ARRM v.1)]<ref name="Stoner2013">Stoner, A.M., Hayhoe, K., Yang, X., and Wuebbles, D.J., 2013. An Asynchronous Regional Regression Model for Statistical Downscaling of Daily Climate Variables. International Journal of Climatology, 33(11), pp. 2473-2494.  [https://doi.org/10.1002/joc.3603 DOI:10.1002/joc.3603]</ref>
 
−
|Parameterized</br>Quantile Mapping||T(min, max), Pr||NetCDF||stations plus</br>grid: 7.5 arc min||day
 
−
|-
 
−
| [https://sdsm.org.uk/ Statistical Downscaling Model (SDSM)]<ref name="Wilby2013">Wilby, R.L., and Dawson, C.W., 2013. The Statistical DownScaling Model: insights from one decade of application. International Journal of Climatology, 33(7), pp. 1707-1719. [https://doi.org/10.1002/joc.3544 DOI: 10.1002/joc.3544]</ref>
 
−
|Weather Generator||T(min, max), Pr||PC Code||stations||day
 
−
|-
 
−
| [https://climate.northwestknowledge.net/MACA/ Multivariate Adaptive</br>Constructed Analogs (MACA)]<ref name="Hidalgo2008">Hidalgo, H.G., Dettinger, M.D. and Cayan, D.R., 2008. Downscaling with Constructed Analogues: Daily Precipitation and Temperature Fields Over the United States. California Energy Commission PIER Final Project, Report CEC-500-2007-123. [[Media: Hidalgo2008.PDF | Report.pdf]]</ref>
 
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|Constructed Analogues||10 Variables||NetCDF||grid: 2.5 arc min||day
 
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|-
 
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| [http://loca.ucsd.edu/ Localized Constructed Analogs (LOCA)]<ref name="Pierce2013">Pierce, D.W., Cayan, D.R. and Thrasher, B.L., 2014. Statistical Downscaling Using Localized Constructed Analogs (LOCA). Journal of Hydrometeorology, 15(6), pp. 2558-2585. [https://doi.org/10.1175/JHM-D-14-0082.1 DOI: 10.1175/JHM-D-14-0082.1]&nbsp;&nbsp; Free access article available from: [https://journals.ametsoc.org/view/journals/hydr/15/6/jhm-d-14-0082_1.xml American Meteorological Society].&nbsp;&nbsp; [[Media: Pierce2014.pdf | Report.pdf]]</ref>
 
−
|Constructed Analogues||T(min, max), Pr||NetCDF||grid: 3.75 arc min||day
 
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|-
 
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| [https://www.nccs.nasa.gov/services/data-collections/land-based-products/nex-dcp30 NASA Earth Exchange Downscaled</br>Climate Projections (NEX-DCP30)]<ref name="Wood2002"/>
 
−
|Bias Correction /</br>Spatial Disaggregation||T(min, max), Pr||NetCDF||grid: 30 arc sec||month
 
−
|-
 
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| colspan="6" style="text-align: left; background-color:white;" |'''Dynamical Downscaled Datasets'''
 
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|-
 
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| [http://www.narccap.ucar.edu/index.html North American Regional Climate</br>Change Assessment Program (NARCCAP)]<ref name="Mearns2009">Mearns, L.O., Gutowski, W., Jones, R., Leung, R., McGinnis, S., Nunes, A. and Qian, Y., 2009. A Regional Climate Change Assessment Program for North America. Eos, Transactions, American Geophysical Union, 90(36), p.311.  [https://doi.org/10.1029/2009EO360002 DOI: 10.1029/2009EO360002]&nbsp;&nbsp; Free access article from: [https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2009EO360002 American Geophysical Union]&nbsp;&nbsp; [[Media: Mearns2009.pdf  | Report.pdf]]</ref>
 
−
|Multiple Models||49 Variables||NetCDF||grid: 30 arc min||3 hours
 
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|-
 
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| [https://cordex.org/about/ Coordinated Regional Climate</br>Downscaling Experiment (CORDEX)]<ref name="Giorgi2009">Giorgi, F., Jones, C., and Asrar, G.R., 2009. Addressing climate information needs at the regional level: the CORDEX framework. World Meteorological Organization (WMO) Bulletin, 58(3), pp. 175-183. Free access article from: [https://public.wmo.int/en/bulletin/addressing-climate-information-needs-regional-level-cordex-framework World Meteorological Organization]&nbsp;&nbsp; [[Media: Giorgi2009.pdf | Report.pdf]]</ref>
 
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|Multiple Models||66 Variables||NetCDF||grid: 30 arc min||3 hours
 
−
|-
 
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| [https://esrl.noaa.gov/gsd/wrfportal/ Strategic Environmental Research and</br>Development Program (SERDP)]<ref name="Wang2015">Wang, J., and Kotamarthi, V.R., 2015. High‐resolution dynamically downscaled projections of precipitation in the mid and late 21st century over North America. Earth's Future, 3(7), pp. 268-288.  [https://doi.org/10.1002/2015EF000304 DOI: 10.1002/2015EF000304]&nbsp;&nbsp; Free access article from: [https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2015EF000304 American Geophysical Union]&nbsp;&nbsp; [[Media: Wang2015.pdf | Report.pdf]]</ref>
 
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|Weather Research and</br>Forecasting (WRF v3.3)||80+ Variables||NetCDF||grid: 6.5 arc min||3 hours
 
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|}
 
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A primary cause of uncertainty in climate change projections, especially beyond 30 years into the future, is the uncertainty in the greenhouse gas (GHG) emission scenarios used to make climate model projections. The best method of accounting for this type of uncertainty is to apply a climate change model to multiple GHG emission scenarios (see also: [[Wikipedia: Representative Concentration Pathway]]).
 
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The uncertainties in climate projections over shorter timescales, less than 30 years out, are dominated by something known as “internal variability” in the models. Different approaches are used to address the uncertainty from internal variability<ref name="Kotamarthi2021"/>. A third type of uncertainty in climate modeling, known as scientific uncertainty, comes from our inability to numerically solve every aspect of the complex earth system. We expect this scientific uncertainty to decrease as we understand more of the earth system and improve its representation in our numerical models.  As discussed in [[Climate Change Primer]], numerical experiments based on global climate models are designed to address these uncertainties in various ways. Downscaling methods evaluate this uncertainty by using several independent regional climate models to generate future projections, with the expectation that each of these models will capture some aspects of the physics better than the others, and that by using several different models, we can estimate the range of this uncertainty.  Thus, the commonly accepted methods for accounting for uncertainty in climate model projections are either using projections from one model for several emission scenarios, or applying multiple models to project a single scenario.
 
−
 
 
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A comparison of the currently available methods and their characteristics is provided in Table 2 (adapted from Kotamarthi et al., 2016<ref name="Kotamarthi2016"/>). The table lists the various methodologies and models used for producing downscaled data, and the climate variables that these methods produce.  These datasets are mostly available for download from the data servers and websites listed in the table and in a few cases by contacting the respective source organizations. 
 
−
 
 
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The most popular and widely used format for atmospheric and climate science is known as [[Wikipedia:NetCDF | NetCDF]], which stands for Network Common Data Form. NetCDF is a self-describing data format that saves data in a binary format. The format is self-describing in that a metadata listing is part of every file that describes all the data attributes, such as dimensions, units and data size and in principal should not need additional information to extract the required data for analysis with the right software.  However, specially built software for reading and extracting data from these binary files is necessary for making visualizations and further analysis. Software packages for reading and writing NetCDF datasets and for generating visualizations from these datasets are widely available and obtained free of cost ([https://www.unidata.ucar.edu/software/netcdf/docs/ NetCDF-tools]). Popular geospatial analysis tools such as ARC-GIS, statistical packages such as ‘R’ and programming languages such as Fortran, C++, and Python have built in libraries that can be used to directly read NetCDF files for visualization and analysis.
 
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==References==
 
==References==
 
<references />
 
<references />
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==See Also==
 
==See Also==
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[https://serdp-estcp.org/Program-Areas/Resource-Conservation-and-Resiliency/Infrastructure-Resiliency/Vulnerability-and-Impact-Assessment/RC-2242/(language)/eng-US Climate Change Impacts to Department of Defense Installations, SERDP Project RC-2242]
 

Latest revision as of 11:33, 29 January 2026

PFAS Destruction by Ultraviolet/Sulfite Treatment

The ultraviolet (UV)/sulfite based reductive defluorination process has emerged as an effective and practical option for generating hydrated electrons (eaq- ) which can destroy PFAS in water. It offers significant advantages for PFAS destruction, including significant defluorination, high treatment efficiency for long-, short-, and ultra-short chain PFAS without mass transfer limitations, selective reactivity by hydrated electrons, low energy consumption, low capital and operation costs, and no production of harmful byproducts. A UV/sulfite treatment system designed and developed by Haley and Aldrich (EradiFluorTM[1]) has been demonstrated in two field demonstrations in which it achieved near-complete defluorination and greater than 99% destruction of 40 PFAS analytes measured by EPA method 1633.

Related Article(s):

Contributors: John Xiong, Yida Fang, Raul Tenorio, Isobel Li, and Jinyong Liu

Key Resources:

  • Defluorination of Per- and Polyfluoroalkyl Substances (PFAS) with Hydrated Electrons: Structural Dependence and Implications to PFAS Remediation and Management[2]
  • Accelerated Degradation of Perfluorosulfonates and Perfluorocarboxylates by UV/Sulfite + Iodide: Reaction Mechanisms and System Efficiencies[3]
  • Destruction of Per- and Polyfluoroalkyl Substances (PFAS) in Aqueous Film-Forming Foam (AFFF) with UV-Sulfite Photoreductive Treatment[4]
  • EradiFluorTM[1]

Introduction

The hydrated electron (eaq- ) can be described as an electron in solution surrounded by a small number of water molecules[5]. Hydrated electrons can be produced by photoirradiation of solutes, including sulfite, iodide, dithionite, and ferrocyanide, and have been reported in literature to effectively decompose per- and polyfluoroalkyl substances (PFAS) in water. The hydrated electron is one of the most reactive reducing species, with a standard reduction potential of about −2.9 volts. Though short-lived, hydrated electrons react rapidly with many species having more positive reduction potentials[5].

Among the electron source chemicals, sulfite (SO32−) has emerged as one of the most effective and practical options for generating hydrated electrons to destroy PFAS in water. The mechanism of hydrated electron production in a sulfite solution under ultraviolet is shown in Equation 1 (UV is denoted as hv, SO3•- is the sulfur trioxide radical anion):

Equation 1:   XiongEq1.png

The hydrated electron has demonstrated excellent performance in destroying PFAS such as perfluorooctanesulfonic acid (PFOS), perfluorooctanoic acid (PFOA)[6] and GenX[7]. Mechanisms include cleaving carbon-to-fluorine (C-F) bonds (i.e., hydrogen/fluorine atom exchange) and chain shortening (i.e., decarboxylation, hydroxylation, elimination, and hydrolysis)[2].

Process Description

A commercial UV/sulfite treatment system designed and developed by Haley and Aldrich (EradiFluorTM[1]) includes an optional pre-oxidation step to transform PFAS precursors (when present) and a main treatment step to break C-F bonds by UV/sulfite reduction. The effluent from the treatment process can be sent back to the influent of a pre-treatment separation system (such as a foam fractionation, regenerable ion exchange, or a membrane filtration system) for further concentration or sent for off-site disposal in accordance with relevant disposal regulations. A conceptual treatment process diagram is shown in Figure 1.

Figure 1: Conceptual Treatment Process for a Concentrated PFAS Stream


Advantages

A UV/sulfite treatment system offers significant advantages for PFAS destruction compared to other technologies, including high defluorination percentage, high treatment efficiency for short-chain PFAS without mass transfer limitation, selective reactivity by eaq-, low energy consumption, and the production of no harmful byproducts. A summary of these advantages is provided below:

  • High efficiency for short- and ultrashort-chain PFAS: While the degradation efficiency for short-chain PFAS is challenging for some treatment technologies[8][9][10], the UV/sulfite process demonstrates excellent defluorination efficiency for both short- and ultrashort-chain PFAS, including trifluoroacetic acid (TFA) and perfluoropropionic acid (PFPrA).
  • High defluorination ratio: As shown in Figure 3, the UV/sulfite treatment system has demonstrated near 100% defluorination for various PFAS under both laboratory and field conditions.
  • No harmful byproducts: While some oxidative technologies, such as electrochemical oxidation, generate toxic byproducts, including perchlorate, bromate, and chlorate, the UV/sulfite system employs a reductive mechanism and does not generate these byproducts.
  • Ambient pressure and low temperature: The system operates under ambient pressure and low temperature (<60°C), as it utilizes UV light and common chemicals to degrade PFAS.
  • Low energy consumption: The electrical energy per order values for the degradation of perfluorocarboxylic acids (PFCAs) by UV/sulfite have been reduced to less than 1.5 kilowatt-hours (kWh) per cubic meter under laboratory conditions. The energy consumption is orders of magnitude lower than that for many other destructive PFAS treatment technologies (e.g., supercritical water oxidation)[11].
  • Co-contaminant destruction: The UV/sulfite system has also been reported effective in destroying certain co-contaminants in wastewater. For example, UV/sulfite is reported to be effective in reductive dechlorination of chlorinated volatile organic compounds, such as trichloroethene, 1,2-dichloroethane, and vinyl chloride[12][13][14][15].

Limitations

Several environmental factors and potential issues have been identified that may impact the performance of the UV/sulfite treatment system, as listed below. Solutions to address these issues are also proposed.

  • Environmental factors, such as the presence of elevated concentrations of natural organic matter (NOM), dissolved oxygen, or nitrate, can inhibit the efficacy of UV/sulfite treatment systems by scavenging available hydrated electrons. Those interferences are commonly managed through chemical additions, reaction optimization, and/or dilution, and are therefore not considered likely to hinder treatment success.
  • Coloration in waste streams may also impact the effectiveness of the UV/sulfite treatment system by blocking the transmission of UV light, thus reducing the UV lamp's effective path length. To address this, pre-treatment may be necessary to enable UV/sulfite destruction of PFAS in the waste stream. Pre-treatment may include the use of strong oxidants or coagulants to consume or remove UV-absorbing constituents.
  • The degradation efficiency is strongly influenced by PFAS molecular structure, with fluorotelomer sulfonates (FTS) and perfluorobutanesulfonate (PFBS) exhibiting greater resistance to degradation by UV/sulfite treatment compared to other PFAS compounds.

State of the Practice

Figure 2. Field demonstration of EradiFluorTM[1] for PFAS destruction in a concentrated waste stream in a Mid-Atlantic Naval Air Station: a) Target PFAS at each step of the treatment shows that about 99% of PFAS were destroyed; meanwhile, the final degradation product, i.e., fluoride, increased to 15 mg/L in concentration, demonstrating effective PFAS destruction; b) AOF concentrations at each step of the treatment provided additional evidence to show near-complete mineralization of PFAS. Average results from multiple batches of treatment are shown here.
Figure 3. Field demonstration of a treatment train (SAFF + EradiFluorTM[1]) for groundwater PFAS separation and destruction at an Air Force base in California: a) Two main components of the treatment train, i.e. SAFF and EradiFluorTM[1]; b) Results showed the effective destruction of various PFAS in the foam fractionate. The target PFAS at each step of the treatment shows that about 99.9% of PFAS were destroyed. Meanwhile, the final degradation product, i.e., fluoride, increased to 30 mg/L in concentration, demonstrating effective destruction of PFAS in a foam fractionate concentrate. After a polishing treatment step (GAC) via the onsite groundwater extraction and treatment system, all PFAS were removed to concentrations below their MCLs.

The effectiveness of UV/sulfite technology for treating PFAS has been evaluated in two field demonstrations using the EradiFluorTM[1] system. Aqueous samples collected from the system were analyzed using EPA Method 1633, the total oxidizable precursor (TOP) assay, adsorbable organic fluorine (AOF) method, and non-target analysis. A summary of each demonstration and their corresponding PFAS treatment efficiency is provided below.

  • Under the Environmental Security Technology Certification Program (ESTCP) Project ER21-5152, a field demonstration of EradiFluorTM[1] was conducted at a Navy site on the east coast, and results showed that the technology was highly effective in destroying various PFAS in a liquid concentrate produced from an in situ foam fractionation groundwater treatment system. As shown in Figure 2a, total PFAS concentrations were reduced from 17,366 micrograms per liter (µg/L) to 195 µg/L at the end of the UV/sulfite reaction, representing 99% destruction. After the ion exchange resin polishing step, all residual PFAS had been removed to the non-detect level, except one compound (PFOS) reported as 1.5 nanograms per liter (ng/L), which is below the current Maximum Contaminant Level (MCL) of 4 ng/L. Meanwhile, the fluoride concentration increased up to 15 milligrams per liter (mg/L), confirming near complete defluorination. Figure 2b shows the adsorbable organic fluorine results from the same treatment test, which similarly demonstrates destruction of 99% of PFAS.
  • Another field demonstration was completed at an Air Force base in California, where a treatment train combining Surface Active Foam Fractionation (SAFF) and EradiFluorTM[1] was used to treat PFAS in groundwater. As shown in Figure 3, PFAS analytical data and fluoride results demonstrated near-complete destruction of various PFAS. In addition, this demonstration showed: a) high PFAS destruction ratio was achieved in the foam fractionate, even in very high concentration (up to 1,700 mg/L of booster), and b) the effluent from EradiFluorTM[1] was sent back to the influent of the SAFF system for further concentration and treatment, resulting in a closed-loop treatment system and no waste discharge from EradiFluorTM[1]. This field demonstration was conducted with the approval of three regulatory agencies (United States Environmental Protection Agency, California Regional Water Quality Control Board, and California Department of Toxic Substances Control).

References

  1. ^ 1.00 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.10 Haley and Aldrich, Inc. (commercial business), 2024. EradiFluor. Comercial Website
  2. ^ 2.0 2.1 Bentel, M.J., Yu, Y., Xu, L., Li, Z., Wong, B.M., Men, Y., Liu, J., 2019. Defluorination of Per- and Polyfluoroalkyl Substances (PFASs) with Hydrated Electrons: Structural Dependence and Implications to PFAS Remediation and Management. Environmental Science and Technology, 53(7), pp. 3718-28. doi: 10.1021/acs.est.8b06648  Open Access Article
  3. ^ Liu, Z., Chen, Z., Gao, J., Yu, Y., Men, Y., Gu, C., Liu, J., 2022. Accelerated Degradation of Perfluorosulfonates and Perfluorocarboxylates by UV/Sulfite + Iodide: Reaction Mechanisms and System Efficiencies. Environmental Science and Technology, 56(6), pp. 3699-3709. doi: 10.1021/acs.est.1c07608  Open Access Article
  4. ^ Tenorio, R., Liu, J., Xiao, X., Maizel, A., Higgins, C.P., Schaefer, C.E., Strathmann, T.J., 2020. Destruction of Per- and Polyfluoroalkyl Substances (PFASs) in Aqueous Film-Forming Foam (AFFF) with UV-Sulfite Photoreductive Treatment. Environmental Science and Technology, 54(11), pp. 6957-67. doi: 10.1021/acs.est.0c00961
  5. ^ 5.0 5.1 Buxton, G.V., Greenstock, C.L., Phillips Helman, W., Ross, A.B., 1988. Critical Review of Rate Constants for Reactions of Hydrated Electrons, Hydrogen Atoms and Hydroxyl Radicals (⋅OH/⋅O-) in Aqueous Solution. Journal of Physical and Chemical Reference Data, 17(2), pp. 513-886. doi: 10.1063/1.555805
  6. ^ Gu, Y., Liu, T., Wang, H., Han, H., Dong, W., 2017. Hydrated Electron Based Decomposition of Perfluorooctane Sulfonate (PFOS) in the VUV/Sulfite System. Science of The Total Environment, 607-608, pp. 541-48. doi: 10.1016/j.scitotenv.2017.06.197
  7. ^ Bao, Y., Deng, S., Jiang, X., Qu, Y., He, Y., Liu, L., Chai, Q., Mumtaz, M., Huang, J., Cagnetta, G., Yu, G., 2018. Degradation of PFOA Substitute: GenX (HFPO–DA Ammonium Salt): Oxidation with UV/Persulfate or Reduction with UV/Sulfite? Environmental Science and Technology, 52(20), pp. 11728-34. doi: 10.1021/acs.est.8b02172
  8. ^ Singh, R.K., Brown, E., Mededovic Thagard, S., Holson, T.M., 2021. Treatment of PFAS-containing landfill leachate using an enhanced contact plasma reactor. Journal of Hazardous Materials, 408, Article 124452. doi: 10.1016/j.jhazmat.2020.124452
  9. ^ Singh, R.K., Multari, N., Nau-Hix, C., Woodard, S., Nickelsen, M., Mededovic Thagard, S., Holson, 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. 13973-80. doi: 10.1021/acs.est.0c02158
  10. ^ Nau-Hix, C., Multari, N., Singh, R.K., Richardson, S., Kulkarni, P., Anderson, R.H., Holsen, T.M., Mededovic Thagard S., 2021. Field Demonstration of a Pilot-Scale Plasma Reactor for the Rapid Removal of Poly- and Perfluoroalkyl Substances in Groundwater. American Chemical Society’s Environmental Science and Technology (ES&T) Water, 1(3), pp. 680-87. doi: 10.1021/acsestwater.0c00170
  11. ^ Nzeribe, B.N., Crimi, M., Mededovic Thagard, S., Holsen, T.M., 2019. Physico-Chemical Processes for the Treatment of Per- And Polyfluoroalkyl Substances (PFAS): A Review. Critical Reviews in Environmental Science and Technology, 49(10), pp. 866-915. doi: 10.1080/10643389.2018.1542916
  12. ^ Jung, B., Farzaneh, H., Khodary, A., Abdel-Wahab, A., 2015. Photochemical degradation of trichloroethylene by sulfite-mediated UV irradiation. Journal of Environmental Chemical Engineering, 3(3), pp. 2194-2202. doi: 10.1016/j.jece.2015.07.026
  13. ^ Liu, X., Yoon, S., Batchelor, B., Abdel-Wahab, A., 2013. Photochemical degradation of vinyl chloride with an Advanced Reduction Process (ARP) – Effects of reagents and pH. Chemical Engineering Journal, 215-216, pp. 868-875. doi: 10.1016/j.cej.2012.11.086
  14. ^ Li, X., Ma, J., Liu, G., Fang, J., Yue, S., Guan, Y., Chen, L., Liu, X., 2012. Efficient Reductive Dechlorination of Monochloroacetic Acid by Sulfite/UV Process. Environmental Science and Technology, 46(13), pp. 7342-49. doi: 10.1021/es3008535
  15. ^ Li, X., Fang, J., Liu, G., Zhang, S., Pan, B., Ma, J., 2014. Kinetics and efficiency of the hydrated electron-induced dehalogenation by the sulfite/UV process. Water Research, 62, pp. 220-228. doi: 10.1016/j.watres.2014.05.051

See Also

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