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==Supercritical Water Oxidation (SCWO)==
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==Assessing Vapor Intrusion (VI) Impacts in Neighborhoods with Groundwater Contaminated by Chlorinated Volatile Organic Chemicals (CVOCs)==  
Supercritical water oxidation (SCWO) is a single step [[Wikipedia: Wet oxidation | wet oxidation]] process that transforms organic matter into water, carbon dioxide and, depending on the waste undergoing treatment, an inert mineral solid residue. The process is highly effective and can treat a variety of wet wastes without dewatering. The SCWO technology allows for the complete destruction of persistent and toxic organic contaminants such as [[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS) | perfluoroalkyl and polyfluoroalkyl substances (PFAS)]], [[1,4-Dioxane | 1,4-dioxane]], and many more.  
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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):'''
  
* [[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS)]]
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*[[Vapor Intrusion (VI)]]
* [[PFAS Transport and Fate]]
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*[[Vapor Intrusion – Sewers and Utility Tunnels as Preferential Pathways]]
* [[Chlorinated Solvents]]
 
  
'''Contributor(s):''' [[Kobe Nagar]] and [[Dr. Marc Deshusses]]
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'''Contributor(s):'''  
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*Paul C. Johnson, Ph.D.
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*Paul Dahlen, Ph.D.
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*Yuanming Guo, Ph.D.
  
 
'''Key Resource(s):'''
 
'''Key Resource(s):'''
  
*Treatment of municipal sewage sludge in supercritical water: A review<ref name="Qian2016">Qian, L., Wang, S., Xu, D., Guo, Y., Tang, X., and Wang, L., 2016. Treatment of municipal sewage sludge in supercritical water: A review. Water Research, 89, pp. 118-131.  [https://doi.org/10.1016/j.watres.2015.11.047 DOI: 10.1016/j.watres.2015.11.047]&nbsp;&nbsp; Free download from: [https://www.researchgate.net/profile/Shuzhong-Wang/publication/284563832_Treatment_of_Municipal_Sewage_Sludge_in_Supercritical_Water_a_Review/links/5d9b63b6299bf1c363fef63e/Treatment-of-Municipal-Sewage-Sludge-in-Supercritical-Water-a-Review.pdf ResearchGate]</ref>.
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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"/>
  
*Supercritical Water Oxidation – Current Status of Full-scale Commercial Activity for Waste Destruction<ref name="Marrone2013">Marrone, P.A., 2013. Supercritical Water Oxidation – Current Status of Full-scale Commercial Activity for Waste Destruction. Journal of Supercritical Fluids, 79, pp. 283-288. [https://doi.org/10.1016/j.supflu.2012.12.020 DOI: 10.1016/j.supflu.2012.12.020]&nbsp;&nbsp; Author’s manuscript available from: [https://semspub.epa.gov/work/06/9545963.pdf US EPA]</ref>.
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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>    
  
==Introduction==
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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>
[[File: Nagar1w2Fig1.png | thumb | 500px | Figure 1.  Water phase diagram showing the supercritical water region (not to scale).]]
 
Supercritical water oxidation (SCWO) is an [[Wikipedia: Advanced oxidation process | advanced oxidation process]] that holds enormous potential for the treatment of a wide range of organic wastes, in particular concentrated wet wastes in slurries such as biosolids, sludges, agricultural wastes, chemical wastes with recalcitrant chemicals such as [[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS)| perfluoroalkyl and polyfluoroalkyl substances (PFAS)]], and many more. SCWO relies on the unique reactivity and transport properties that occur when an aqueous waste stream is brought above the critical point of water (374&deg;C and 218 atm, or 704&deg;F and 3200 psi, see phase diagram in Figure 1). [[Wikipedia: Supercritical fluid |  Supercritical water]] is a dense single phase with transport properties similar to those of a gas, and solvent properties comparable to those of a non-polar solvent<ref name="Tassaing2002">Tassaing, T., Danten, Y., and Besnard, M., 2002. Infrared spectroscopic study of hydrogen bonding in water at high temperature and pressure. Journal of Molecular Liquids, 101(1-3), pp. 149-158.  [https://doi.org/10.1016/S0167-7322(02)00089-2 DOI: 10.1016/S0167-7322(02)00089-2]</ref>. Oxygen is fully soluble in supercritical water, resulting in extremely rapid and complete oxidation of all organics to carbon dioxide, clean water (that can be reused), and some non-leachable inorganic salts.
 
  
For SCWO to be economical, the heat from the oxidation reaction is recovered and used in part to heat the influent stream, while the excess heat can be converted to electricity. Depending on the concentration of waste in the feedstock, SCWO reactors can be operated autothermally, i.e., no outside input of heat is required. Typical reaction times are in the order of 2-10 seconds, resulting in SCWO systems that are quite compact compared to other technologies (see Table 1). The process does not generate harmful by-products such as nitrogen oxides (NOx) or Sulfur oxides (SOx), carbon monoxide (CO), or odors<ref Name="Bermejo">Bermejo, M.D. and Cocero, M.J., 2006. Supercritical water oxidation: A technical review. AIChE Journal, 52(11) pp. 3933-3951. [https://doi.org/10.1002/aic.10993 DOI: 10.1002/aic.10993]</ref>. Typically, if present, ammonia and organic nitrogen in the waste undergoing treatment are converted to nitrogen gas, while phosphorous precipitates as phosphates and can be recovered. When [[Wikipedia: Halogen | halogen]] containing contaminants are treated (e.g., [[Perfluoroalkyl and Polyfluoroalkyl Substances (PFAS)| PFAS]]), halogen-carbon bonds are generally broken and [[Wikipedia: Halide | halide]] anions are released in solution (e.g., F- when treating PFAS or Cl- when treating [[Wikipedia: Trichloroethylene | trichloroethene (TCE)]] and [[Wikipedia: Tetrachloroethylene | tetrachloroethene (PCE)]]).
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==Background==
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[[File:ChangFig2.png | thumb | 400px| Figure 1. Example of instrumentation used for OPTICS monitoring.]]
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[[File:ChangFig1.png | thumb | 400px| Figure 2. Schematic diagram illustrating the OPTICS methodology. High resolution in-situ data are integrated with traditional discrete sample analytical data using partial least-square regression to derive high resolution chemical contaminant concentration data series.]]
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Nationwide, the liability due to contaminated sediments is estimated in the trillions of dollars. Stakeholders are assessing and developing remedial strategies for contaminated sediment sites in major harbors and waterways throughout the U.S. The mobility of contaminants in surface water is a primary transport and risk mechanism<ref>Thibodeaux, L.J., 1996. Environmental Chemodynamics: Movement of Chemicals in Air, Water, and Soil, 2nd Edition, Volume 110 of Environmental Science and Technology: A Wiley-Interscience Series of Texts and Monographs. John Wiley & Sons, Inc. 624 pages. ISBN: 0-471-61295-2</ref><ref>United States Environmental Protection Agency (USEPA), 2005. Contaminated Sediment Remediation Guidance for Hazardous Waste Sites. Office of Superfund Remediation and Technology Innovation Report, EPA-540-R-05-012. [[Media: 2005-USEPA-Contaminated_Sediment_Remediation_Guidance.pdf | Report.pdf]]</ref><ref>Lick, W., 2008. Sediment and Contaminant Transport in Surface Waters. CRC Press. 416 pages. [https://doi.org/10.1201/9781420059885 doi: 10.1201/9781420059885]</ref>; therefore, long-term monitoring of both particulate- and dissolved-phase contaminant concentration prior to, during, and following remedial action is necessary to document remedy effectiveness. Source control and total maximum daily load (TMDL) actions generally require costly manual monitoring of dissolved and particulate contaminant concentrations in surface water. The magnitude of cost for these actions is a strong motivation to implement efficient methods for long-term source control and remedial monitoring.  
  
==Advantages and Disadvantages==
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Traditional surface water monitoring requires mobilization of field teams to manually collect discrete water samples, send samples to laboratories, and await laboratory analysis so that a site evaluation can be conducted. These traditional methods are well known to have inherent cost and safety concerns and are of limited use (due to safety concerns and standby requirements for resources) in capturing the effects of episodic events (e.g., storms) that are important to consider in site risk assessment and remedy selection. Automated water samplers are commercially available but still require significant field support and costly laboratory analysis. Further, automated samplers may not be suitable for analytes with short hold-times and temperature requirements.  
There are many advantages to SCWO treatment. SCWO is a destructive treatment in that the compounds treated are mineralized to simple elements or harmless molecules (e.g., water and carbon dioxide) rather than just being transferred to another medium. Another advantage is the absence of reaction by-products, incompletely oxidized contaminants or unreacted harmful oxidants (e.g., ozone). SCWO is an extremely rapid and effective reaction (typical reaction times are in the order of 5-10 seconds) making it possible to build systems that are very compact and have a high throughput. SCWO is also a very clean process. The highly oxidizing environment makes it possible to effectively treat all sorts of organic contaminants, often recalcitrant to other processes, with very high (>99%) destruction efficiencies. This includes treatment of trace contaminants, slurries of biosolids, waste oil, food wastes, plastics, or emerging contaminants such as PFAS or 1,4-dioxane. Also, the relatively moderate temperatures (380-600&deg;C) compared to other destructive technologies such as incineration, combined with the presence of supercritical water prevent the formation of NOx and SOx compounds. Lastly, SCWO treatment does not require drying of the waste, and both liquids and slurries can be treated using SCWO.  
 
  
There are several disadvantages to SCWO treatment. First, a significant amount of energy needs to be expended to bring the oxidant and the waste undergoing treatment to the critical point of water. Although a large fraction of this energy can be efficiently recovered in heat exchangers, compensating for heat losses constrains SCWO to the treatment of concentrated wastes with sufficient organic content for the exothermic oxidation reaction to provide the necessary heat. Typically, a minimum calorific content of around 2 MJ/kg (which generally corresponds to a chemical oxygen demand of about 120-150 g/L) is needed for autothermal operation. For more dilute streams, external heating or supplementation of fuel (diesel, alcohol, waste oil, etc.) can be implemented, but it can rapidly become cost prohibitive. Thus, SCWO is currently not economical for very large volumes (>50,000 gallon/day) of very dilute waste streams. A second limitation is related to the pumping of the waste. Because the process is conducted at high pressure (240 bars or 3500 psi), positive displacement pumps are required. This limits SCWO to liquids and slurries that can be pumped. Waste streams that contain excessive grit or abrasive materials, and soils cannot currently be processed using SCWO.  
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Optically-based characterization of surface water contaminants is a cost-effective alternative to traditional discrete water sampling methods. Unlike discrete water sampling, which typically results in sparse data at low resolution, and therefore, is of limited use in determining mass loading, OPTICS (OPTically-based In-situ Characterization System) provides continuous data and allows for a complete understanding of water quality and contaminant transport in response to natural processes and human impacts<ref name="ChangEtAl2019"/><ref name="ChangEtAl2018"/><ref name="ChangEtAl2024"/><ref>Bergamaschi, B.A., Fleck, J.A., Downing, B.D., Boss, E., Pellerin, B., Ganju, N.K., Schoellhamer, D.H., Byington, A.A., Heim, W.A., Stephenson, M., Fujii, R., 2011. Methyl mercury dynamics in a tidal wetland quantified using in situ optical measurements. Limnology and Oceanography, 56(4), pp. 1355-1371. [https://doi.org/10.4319/lo.2011.56.4.1355 doi: 10.4319/lo.2011.56.4.1355]&nbsp;&nbsp; [[Media: BergamaschiEtAl2011.pdf | Open Access Article]]</ref><ref>Bergamaschi, B.A., Fleck, J.A., Downing, B.D., Boss, E., Pellerin, B.A., Ganju, N.K., Schoellhamer, D.H., Byington, A.A., Heim, W.A., Stephenson, M., Fujii, R., 2012. Mercury Dynamics in a San Francisco Estuary Tidal Wetland: Assessing Dynamics Using In Situ Measurements. Estuaries and Coasts, 35, pp. 1036-1048. [https://doi.org/10.1007/s12237-012-9501-3 doi: 10.1007/s12237-012-9501-3]&nbsp;&nbsp; [[Media: BergamaschiEtAl2012a.pdf | Open Access Article]]</ref><ref>Bergamaschi, B.A., Krabbenhoft, D.P., Aiken, G.R., Patino, E., Rumbold, D.G., Orem, W.H., 2012. Tidally driven export of dissolved organic carbon, total mercury, and methylmercury from a mangrove-dominated estuary. Environmental Science and Technology, 46(3), pp. 1371-1378. [https://doi.org/10.1021/es2029137 doi: 10.1021/es2029137]&nbsp;&nbsp; [[Media: BergamaschiEtAl2012b.pdf | Open Access Article]]</ref>. The OPTICS tool integrates commercial off-the-shelf ''in situ'' aquatic sensors (Figure 1), periodic discrete surface water sample collection, and a multi-parameter statistical prediction model<ref name="deJong1993">de Jong, S., 1993. SIMPLS: an alternative approach to partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 18(3), pp. 251-263. [https://doi.org/10.1016/0169-7439(93)85002-X doi: 10.1016/0169-7439(93)85002-X]</ref><ref name="RosipalKramer2006">Rosipal, R. and Krämer, N., 2006. Overview and Recent Advances in Partial Least Squares, In: Subspace, Latent Structure, and Feature Selection: Statistical and Optimization Perspectives Workshop, Revised Selected Papers (Lecture Notes in Computer Science, Volume 3940), Springer-Verlag, Berlin, Germany. pp. 34-51. [https://doi.org/10.1007/11752790_2 doi: 10.1007/11752790_2]</ref> to provide high temporal and/or spatial resolution characterization of surface water chemicals of potential concern (COPCs) (Figure 2).
  
The many appealing benefits of supercritical water processing have stimulated engineers and entrepreneurs to invest significant efforts and resources in the development of the technology. Today, after roughly 30 years of development, commercial deployment is on the horizon<ref name="Marrone2013"/>. Technical challenges that have slowed down commercial deployment of SCWO are linked to the complex nature of a high-pressure, high-temperature process. Critical issues include reactor materials selection to resist corrosion (typically high nickel alloys are used), reactor designs and construction to withstand the corrosive nature of the reactive mass, dealing with highly exothermic reactions at high pressure and high temperature, plugging of the reactor by minerals deposits, and energy recovery for autothermal operation. Another challenge was the unrealistic goal of some companies entering the SCWO market to produce power from waste streams (often wastewater sludge) at a competitive cost (3-5 cents/kWh). This was not feasible with the available technology, which led to several business failures.  
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==Technology Overview==
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The principle behind OPTICS is based on the relationship between optical properties of natural waters and the particles and dissolved material contained within them<ref>Boss, E. and Pegau, W.S., 2001. Relationship of light scattering at an angle in the backward direction to the backscattering coefficient. Applied Optics, 40(30), pp. 5503-5507. [https://doi.org/10.1364/AO.40.005503 doi: 10.1364/AO.40.005503]</ref><ref>Boss, E., Twardowski, M.S., Herring, S., 2001. Shape of the particulate beam spectrum and its inversion to obtain the shape of the particle size distribution. Applied Optics, 40(27), pp. 4884-4893. [https://doi.org/10.1364/AO.40.004885 doi:10/1364/AO.40.004885]</ref><ref>Babin, M., Morel, A., Fournier-Sicre, V., Fell, F., Stramski, D., 2003. Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration. Limnology and Oceanography, 48(2), pp. 843-859. [https://doi.org/10.4319/lo.2003.48.2.0843 doi: 10.4319/lo.2003.48.2.0843]&nbsp;&nbsp; [[Media: BabinEtAl2003.pdf | Open Access Article]]</ref><ref>Coble, P., Hu, C., Gould, R., Chang, G., Wood, M., 2004. Colored dissolved organic matter in the coastal ocean: An optical tool for coastal zone environmental assessment and management. Oceanography, 17(2), pp. 50-59. [https://doi.org/10.5670/oceanog.2004.47 doi: 10.5670/oceanog.2004.47]&nbsp;&nbsp; [[Media: CobleEtAl2004.pdf | Open Access Article]]</ref><ref>Sullivan, J.M., Twardowski, M.S., Donaghay, P.L., Freeman, S.A., 2005. Use of optical scattering to discriminate particle types in coastal waters. Applied Optics, 44(9), pp. 1667–1680. [https://doi.org/10.1364/AO.44.001667 doi: 10.1364/AO.44.001667]</ref><ref>Twardowski, M.S., Boss, E., Macdonald, J.B., Pegau, W.S., Barnard, A.H., Zaneveld, J.R.V., 2001. A model for estimating bulk refractive index from the optical backscattering ratio and the implications for understanding particle composition in case I and case II waters. Journal of Geophysical Research: Oceans, 106(C7), pp. 14,129-14,142. [https://doi.org/10.1029/2000JC000404 doi: 10/1029/2000JC000404]&nbsp;&nbsp; [[Media: TwardowskiEtAl2001.pdf | Open Access Article]]</ref><ref>Chang, G.C., Barnard, A.H., McLean, S., Egli, P.J., Moore, C., Zaneveld, J.R.V., Dickey, T.D., Hanson, A., 2006. In situ optical variability and relationships in the Santa Barbara Channel: implications for remote sensing. Applied Optics, 45(15), pp. 3593–3604. [https://doi.org/10.1364/AO.45.003593 doi: 10.1364/AO.45.003593]</ref><ref>Slade, W.H. and Boss, E., 2015. Spectral attenuation and backscattering as indicators of average particle size. Applied Optics, 54(24), pp. 7264-7277. [https://doi.org/10.1364/AO.54.007264 doi: 10/1364/AO.54.007264]&nbsp;&nbsp; [[Media: SladeBoss2015.pdf | Open Access Article]]</ref>. Surface water COPCs such as heavy metals and polychlorinated biphenyls (PCBs) are hydrophobic in nature and tend to sorb to materials in the water column, which have unique optical signatures that can be measured at high-resolution using ''in situ'', commercially available aquatic sensors<ref>Agrawal, Y.C. and Pottsmith, H.C., 2000. Instruments for particle size and settling velocity observations in sediment transport. Marine Geology, 168(1-4), pp. 89-114. [https://doi.org/10.1016/S0025-3227(00)00044-X doi: 10.1016/S0025-3227(00)00044-X]</ref><ref>Boss, E., Pegau, W.S., Gardner, W.D., Zaneveld, J.R.V., Barnard, A.H., Twardowski, M.S., Chang, G.C., Dickey, T.D., 2001. Spectral particulate attenuation and particle size distribution in the bottom boundary layer of a continental shelf. Journal of Geophysical Research: Oceans, 106(C5), pp. 9509-9516. [https://doi.org/10.1029/2000JC900077  doi: 10.1029/2000JC900077]&nbsp;&nbsp; [[Media: BossEtAl2001.pdf | Open Access Article]]</ref><ref>Boss, E., Pegau, W.S., Lee, M., Twardowski, M., Shybanov, E., Korotaev, G. Baratange, F., 2004. Particulate backscattering ratio at LEO 15 and its use to study particle composition and distribution. Journal of Geophysical Research: Oceans, 109(C1), Article C01014. [https://doi.org/10.1029/2002JC001514 doi: 10.1029/2002JC001514]&nbsp;&nbsp; [[Media: BossEtAl2004.pdf | Open Access Article]]</ref><ref>Briggs, N.T., Slade, W.H., Boss, E., Perry, M.J., 2013. Method for estimating mean particle size from high-frequency fluctuations in beam attenuation or scattering measurement. Applied Optics, 52(27), pp. 6710-6725. [https://doi.org/10.1364/AO.52.006710 doi: 10.1364/AO.52.006710]&nbsp;&nbsp; [[Media: BriggsEtAl2013.pdf | Open Access Article]]</ref>. Therefore, high-resolution concentrations of COPCs can be accurately and robustly derived from ''in situ'' measurements using statistical methods.
  
The value proposition of treating recalcitrant wastes using SCWO is markedly different, especially in today’s context of increasing liability for trace levels of emerging contaminants such as PFAS. SCWO may prove to be the optimal treatment technology for many highly concentrated aqueous waste streams.  
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The OPTICS method is analogous to the commonly used empirical derivation of total suspended solids concentration (TSS) from optical turbidity using linear regression<ref>Rasmussen, P.P., Gray, J.R., Glysson, G.D., Ziegler, A.C., 2009. Guidelines and procedures for computing time-series suspended-sediment concentrations and loads from in-stream turbidity-sensor and streamflow data. In: Techniques and Methods, Book 3: Applications of Hydraulics, Section C: Sediment and Erosion Techniques, Ch. 4. 52 pages. U.S. Geological Survey.&nbsp;&nbsp; [[Media: RasmussenEtAl2009.pdf | Open Access Article]]</ref>. However, rather than deriving one response variable (TSS) from one predictor variable (turbidity), OPTICS involves derivation of one response variable (e.g., PCB concentration) from a suite of predictor variables (e.g., turbidity, temperature, salinity, and fluorescence of chlorophyll-a) using multi-parameter statistical regression. OPTICS is based on statistical correlation – similar to the turbidity-to-TSS regression technique. The method does not rely on interpolation or extrapolation.  
  
==State of the Art==
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The OPTICS technique utilizes partial least-squares (PLS) regression to determine a combination of physical, optical, and water quality properties that best predicts chemical contaminant concentrations with high variance. PLS regression is a statistically based method combining multiple linear regression and principal component analysis (PCA), where multiple linear regression finds a combination of predictors that best fit a response and PCA finds combinations of predictors with large variance<ref name="deJong1993"/><ref name="RosipalKramer2006"/>. Therefore, PLS identifies combinations of multi-collinear predictors (''in situ'', high-resolution physical, optical, and water quality measurements) that have large covariance with the response values (discrete surface water chemical contaminant concentration data from samples that are collected periodically, coincident with ''in situ'' measurements). PLS combines information about the variances of both the predictors and the responses, while also considering the correlations among them. PLS therefore provides a model with reliable predictive power.
Relatively few large scale SCWO systems exist. Researchers at Duke University ([http://sanitation.pratt.duke.edu/community-treatment/about-community-treatment-project Deshusses lab]) have designed and built a prototype pilot-scale SCWO system housed in a standard 20-foot shipping container (Figure 2). This project was funded by the Reinvent the Toilet program of the [https://www.gatesfoundation.org/ Bill and Melinda Gates Foundation]. The pilot system is a continuous process designed to treat 1 ton of sludge per day at 10-20% dry solids content. The unit has been undergoing testing at Duke since early 2015. The design includes moderate preheating of the waste slurry, followed by mixing with supercritical water (~600&deg;C) and air, which serves as the oxidant. This internal mixing rapidly brings the waste undergoing treatment to supercritical conditions thereby minimizing corrosion and the risks of waste charring and associated reactor plugging. The organics in the sludge are rapidly oxidized to CO<sub>2</sub>, while the heat of oxidation is recovered to heat the influent waste. The reactor is a single tubular reactor. The high supercritical fluid velocity in the system helps with controlling mineral salts deposition in the reactor. The system is well instrumented, and operation is controlled using a supervisory control and data acquisition (SCADA) system with historian software for trends analysis and reporting of key performance indicators (e.g., temperatures and pressures, pollutant destruction). Experiments conducted with this pilot plant have shown effective treatment of a wide variety of otherwise problematic wastes such as primary, secondary and digested sludge slurries, landfill leachate (see Figure 3), animal waste, and co-contaminants including waste oil, food wastes, and plastics. The results are consistent with other SCWO studies and show very rapid treatment of all wastes with near complete conversion (often >99.9%) of organics to CO<sub>2</sub>. Total nitrogen and phosphorous removal are generally over 95% and 98%, respectively. Emerging contaminants such as pharmaceuticals, [[Perfluoroakyl and Polyfluoroalkyl Substances (PFAS) |PFAS]], [[1,4-Dioxane | 1,4-dioxane]] and [[Wikipedia: Microplastics | microplastics]] are also treated with destruction generally exceeding 99%.
 
  
Early projections for treatment costs (Capital Expenditures + Operating Expenditures) for slurries are in the range of $12 to $90 per ton (or $0.04 to $0.37 per gallon) depending on system scale and contaminant concentration, with a majority of the cost coming from amortizing the equipment. These cost projections make SCWO treatment very competitive compared to other treatment technologies for high-strength wastes. When treating large volumes of water, combining SCWO with another technology (e.g., nanofiltration, reverse osmosis, or adsorption onto GAC) should be considered so that only the concentrated brines or spent sorbent are treated using SCWO, thereby increasing the cost effectiveness of the overall treatment.
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OPTICS ''in situ'' measurement parameters include, but are not limited to current velocity, conductivity, temperature, depth, turbidity, dissolved oxygen, and fluorescence of chlorophyll-a and dissolved organic matter. Instrumentation for these measurements is commercially available, robust, deployable in a wide variety of configurations (e.g., moored, vessel-mounted, etc.), powered by batteries, and records data internally and/or transmits data in real-time. The physical, optical, and water quality instrumentation is compact and self-contained. The modularity and automated nature of the OPTICS measurement system enables robust, long-term, autonomous data collection for near-continuous monitoring.  
  
==SCWO for the Treatment of PFAS and AFFF==
+
[[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.
Several reports have indicated that PFAS can be treated using SCWO<ref name="Kucharzyk2017">Kucharzyk, K.H., Darlington, R., Benotti, M., Deeb, R. and Hawley, E., 2017. Novel treatment technologies for PFAS compounds: A critical review. Journal of Environmental Management, 204(2), pp. 757-764. [https://doi.org/10.1016/j.jenvman.2017.08.016 DOI: 10.1016/j.jenvman.2017.08.016]&nbsp;&nbsp; Manuscript available from: [https://www.researchgate.net/profile/Katarzyna_kate_Kucharzyk/publication/319125507_Novel_treatment_technologies_for_PFAS_compounds_A_critical_review/links/5a06590b4585157013a3be77/Novel-treatment-technologies-for-PFAS-compounds-A-critical-review.pdf ResearchGate]</ref>. Several runs treating biosolids known to contain PFAS as well as dilutions of pure [[Wikipedia: Firefighting foam | aqueous film forming foam (AFFF)]] have also been conducted with the Duke SCWO system. Typical results are shown in Table 2. They indicate very effective treatment performance, with for example 110,000 ng/L PFOS in the feed reduced to 0.79 ng/L in the effluent, and many other PFAS reduced to below their detection limits. No HF was found in the effluent gas, and all the fluorine from the destroyed PFAS was accounted for as fluoride in the effluent water. These results show the ability of the SCWO process to destroy PFAS to levels well below the EPA health advisory levels of 70 ng/L for PFOS and PFOA. The [https://www.serdp-estcp.org/ Environmental Security Technology Certification Program (ESTCP)] project number [https://www.serdp-estcp.org/Program-Areas/Environmental-Restoration/ER20-5350/ER20-5350 ER20-5350]<ref name="Deshusses2020">Deshusses, M.A., 2020. Supercritical Water Oxidation (SCWO) for Complete PFAS Destruction. Environmental Security Technology Certification Program (ESTCP) Project number ER20-5350. [https://www.serdp-estcp.org/Program-Areas/Environmental-Restoration/ER20-5350/ER20-5350 Project website]</ref> launched in June 2020 will assess the technical feasibility of using supercritical water oxidation (SCWO) for the complete destruction of PFAS in a variety of relevant waste streams and will evaluate the cost effectiveness of the treatment.
 
  
 +
==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"/>.
  
[[File: revOsmosisPlant.png | thumb | 500px | Figure 1. A RO municipal drinking water plant in Arizona]]
+
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"/>.
  
{| class="wikitable" style="float:right; margin-left:10px;"
+
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"/>.
|+ Table 1. Comparison of SCWO with other thermal technologies
+
 
|-
+
==Summary==
! Technology
+
OPTICS provides:
! SCWO
+
*High resolution surface water chemical contaminant characterization
! SCWG
+
*Cost-effective monitoring and assessment
! HTL/HTC
+
*Versatile and modular monitoring with capability for real-time telemetry
! WAO
+
*Data necessary for development and validation of conceptual site models
|-
+
*A key line of evidence for designing and evaluating remedies.
| Temperature || >380&deg;C || >380&deg;C || 250-300&deg;C || 150-320&deg;C
+
 
|-
+
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.
| Pressure || >240 bar || >240 bar || 40-200 bar || 10-200 bar
 
|-
 
| Oxidant || Required || None || None || Required
 
|-
 
| Reaction time || 2-10 sec. || 40-90 sec. || 30 min. to 2 hr.s || 30 min. to 3 hr.s
 
|-
 
| Corrosion potential || Moderate to high || Moderate || Low || Low to moderate
 
|-
 
| Risk of reactor plugging || Moderate to high || High || High || Low
 
|-
 
| Reaction || Exothermic || Endothermic || Endothermic || Exothermic
 
|-
 
| Useable products || CO<sub>2</sub> + clean H<sub>2</sub>O + heat + minerals || Syngas (H<sub>2</sub> + CH<sub>4</sub> + CO) || Biocrude/Biochar || Possible H<sub>2</sub>O, volatile fatty acids
 
|-
 
| By-products || None || Tars, phenols, recalcitrant N,</br>contaminated water || Tars, phenols, recalcitrant N,</br>contaminated water ||Tars, phenols, recalcitrant N,</br>contaminated water
 
|-
 
| Fate of feedstock N,</br>if any || N<sub>2</sub> gas || NH<sub>4</sub><sup>+</sup> in liquid effluent || NH<sub>4</sub><sup>+</sup> in liquid effluent +</br>N in (by)-products || NH<sub>4</sub><sup>+</sup> in liquid effluent +</br>N in (by)-products
 
|-
 
| colspan="5" style="background:white;" | Notes: SCWG = supercritical water gasification, HTL/HTC = [[Wikipedia: Hydrothermal liquefaction | hydrothermal liquefaction]]/carbonization, WAO = wet air oxidation
 
|}
 
<br clear="left" />
 
  
 
==References==
 
==References==
 
 
<references />
 
<references />
  
 
==See Also==
 
==See Also==

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

  1. ^ 1.0 1.1 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. Project Website   Final Report.pdf
  2. ^ 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. Project Website   Technical_Report.pdf
  3. ^ Johnson, P.C., Guo, Y., and Dahlen, P., 2022. VI Diagnosis Toolkit User Guide, ESTCP ER-201501, User Guide. Project Website   User_Guide.pdf
  4. ^ 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
  5. ^ 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. Report.pdf
  6. ^ Lick, W., 2008. Sediment and Contaminant Transport in Surface Waters. CRC Press. 416 pages. doi: 10.1201/9781420059885
  7. ^ 7.0 7.1 Cite error: Invalid <ref> tag; no text was provided for refs named ChangEtAl2019
  8. ^ 8.0 8.1 Cite error: Invalid <ref> tag; no text was provided for refs named ChangEtAl2018
  9. ^ 9.0 9.1 Cite error: Invalid <ref> tag; no text was provided for refs named ChangEtAl2024
  10. ^ 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. doi: 10.4319/lo.2011.56.4.1355   Open Access Article
  11. ^ 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. doi: 10.1007/s12237-012-9501-3   Open Access Article
  12. ^ 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. doi: 10.1021/es2029137   Open Access Article
  13. ^ 13.0 13.1 de Jong, S., 1993. SIMPLS: an alternative approach to partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 18(3), pp. 251-263. doi: 10.1016/0169-7439(93)85002-X
  14. ^ 14.0 14.1 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. doi: 10.1007/11752790_2
  15. ^ 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. doi: 10.1364/AO.40.005503
  16. ^ 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. doi:10/1364/AO.40.004885
  17. ^ 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. doi: 10.4319/lo.2003.48.2.0843   Open Access Article
  18. ^ 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. doi: 10.5670/oceanog.2004.47   Open Access Article
  19. ^ 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. doi: 10.1364/AO.44.001667
  20. ^ 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. doi: 10/1029/2000JC000404   Open Access Article
  21. ^ 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. doi: 10.1364/AO.45.003593
  22. ^ Slade, W.H. and Boss, E., 2015. Spectral attenuation and backscattering as indicators of average particle size. Applied Optics, 54(24), pp. 7264-7277. doi: 10/1364/AO.54.007264   Open Access Article
  23. ^ 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. doi: 10.1016/S0025-3227(00)00044-X
  24. ^ 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. doi: 10.1029/2000JC900077   Open Access Article
  25. ^ 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. doi: 10.1029/2002JC001514   Open Access Article
  26. ^ 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. doi: 10.1364/AO.52.006710   Open Access Article
  27. ^ 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.   Open Access Article

See Also