Difference between revisions of "User:Jhurley/sandbox"

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Optically-based characterization of surface water contaminants is a cost-effective alternative to traditional discrete water sampling methods. Unlike discrete water sampling, which typically results in sparse data at low resolution, and therefore, is of limited use in determining mass loading, OPTICS (OPTically-based In-situ Characterization System) provides continuous data and allows for a complete understanding of water quality and contaminant transport in response to natural processes and human impacts<ref name="ChangEtAl2019"/><ref name="ChangEtAl2018"/><ref name="ChangEtAl2024"/><ref>Bergamaschi, B.A., Fleck, J.A., Downing, B.D., Boss, E., Pellerin, B., Ganju, N.K., Schoellhamer, D.H., Byington, A.A., Heim, W.A., Stephenson, M., Fujii, R., 2011. Methyl mercury dynamics in a tidal wetland quantified using in situ optical measurements. Limnology and Oceanography, 56(4), pp. 1355-1371. [https://doi.org/10.4319/lo.2011.56.4.1355 doi: 10.4319/lo.2011.56.4.1355]&nbsp;&nbsp; [[Media: BergamaschiEtAl2011.pdf | Open Access Article]]</ref><ref>Bergamaschi, B.A., Fleck, J.A., Downing, B.D., Boss, E., Pellerin, B.A., Ganju, N.K., Schoellhamer, D.H., Byington, A.A., Heim, W.A., Stephenson, M., Fujii, R., 2012. Mercury Dynamics in a San Francisco Estuary Tidal Wetland: Assessing Dynamics Using In Situ Measurements. Estuaries and Coasts, 35, pp. 1036-1048. [https://doi.org/10.1007/s12237-012-9501-3 doi: 10.1007/s12237-012-9501-3]&nbsp;&nbsp; [[Media: BergamaschiEtAl2012a.pdf | Open Access Article]]</ref><ref>Bergamaschi, B.A., Krabbenhoft, D.P., Aiken, G.R., Patino, E., Rumbold, D.G., Orem, W.H., 2012. Tidally driven export of dissolved organic carbon, total mercury, and methylmercury from a mangrove-dominated estuary. Environmental Science and Technology, 46(3), pp. 1371-1378. [https://doi.org/10.1021/es2029137 doi: 10.1021/es2029137]&nbsp;&nbsp; [[Media: BergamaschiEtAl2012b.pdf | Open Access Article]]</ref>. The OPTICS tool integrates commercial off-the-shelf in-situ aquatic sensors, periodic discrete surface water sample collection, and a multi-parameter statistical prediction model<ref name="deJong1993">de Jong, S., 1993. SIMPLS: an alternative approach to partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 18(3), pp. 251-263. [https://doi.org/10.1016/0169-7439(93)85002-X doi: 10.1016/0169-7439(93)85002-X]</ref><ref name="RosipalKramer2006">Rosipal, R. and Krämer, N., 2006. Overview and Recent Advances in Partial Least Squares, In: Subspace, Latent Structure, and Feature Selection: Statistical and Optimization Perspectives Workshop, Revised Selected Papers (Lecture Notes in Computer Science, Volume 3940), Springer-Verlag, Berlin, Germany. pp. 34-51. [https://doi.org/10.1007/11752790_2 doi: 10.1007/11752790_2]</ref> to provide high temporal and/or spatial resolution characterization of surface water chemicals of potential concern (COPCs).  
 
Optically-based characterization of surface water contaminants is a cost-effective alternative to traditional discrete water sampling methods. Unlike discrete water sampling, which typically results in sparse data at low resolution, and therefore, is of limited use in determining mass loading, OPTICS (OPTically-based In-situ Characterization System) provides continuous data and allows for a complete understanding of water quality and contaminant transport in response to natural processes and human impacts<ref name="ChangEtAl2019"/><ref name="ChangEtAl2018"/><ref name="ChangEtAl2024"/><ref>Bergamaschi, B.A., Fleck, J.A., Downing, B.D., Boss, E., Pellerin, B., Ganju, N.K., Schoellhamer, D.H., Byington, A.A., Heim, W.A., Stephenson, M., Fujii, R., 2011. Methyl mercury dynamics in a tidal wetland quantified using in situ optical measurements. Limnology and Oceanography, 56(4), pp. 1355-1371. [https://doi.org/10.4319/lo.2011.56.4.1355 doi: 10.4319/lo.2011.56.4.1355]&nbsp;&nbsp; [[Media: BergamaschiEtAl2011.pdf | Open Access Article]]</ref><ref>Bergamaschi, B.A., Fleck, J.A., Downing, B.D., Boss, E., Pellerin, B.A., Ganju, N.K., Schoellhamer, D.H., Byington, A.A., Heim, W.A., Stephenson, M., Fujii, R., 2012. Mercury Dynamics in a San Francisco Estuary Tidal Wetland: Assessing Dynamics Using In Situ Measurements. Estuaries and Coasts, 35, pp. 1036-1048. [https://doi.org/10.1007/s12237-012-9501-3 doi: 10.1007/s12237-012-9501-3]&nbsp;&nbsp; [[Media: BergamaschiEtAl2012a.pdf | Open Access Article]]</ref><ref>Bergamaschi, B.A., Krabbenhoft, D.P., Aiken, G.R., Patino, E., Rumbold, D.G., Orem, W.H., 2012. Tidally driven export of dissolved organic carbon, total mercury, and methylmercury from a mangrove-dominated estuary. Environmental Science and Technology, 46(3), pp. 1371-1378. [https://doi.org/10.1021/es2029137 doi: 10.1021/es2029137]&nbsp;&nbsp; [[Media: BergamaschiEtAl2012b.pdf | Open Access Article]]</ref>. The OPTICS tool integrates commercial off-the-shelf in-situ aquatic sensors, periodic discrete surface water sample collection, and a multi-parameter statistical prediction model<ref name="deJong1993">de Jong, S., 1993. SIMPLS: an alternative approach to partial least squares regression. Chemometrics and Intelligent Laboratory Systems, 18(3), pp. 251-263. [https://doi.org/10.1016/0169-7439(93)85002-X doi: 10.1016/0169-7439(93)85002-X]</ref><ref name="RosipalKramer2006">Rosipal, R. and Krämer, N., 2006. Overview and Recent Advances in Partial Least Squares, In: Subspace, Latent Structure, and Feature Selection: Statistical and Optimization Perspectives Workshop, Revised Selected Papers (Lecture Notes in Computer Science, Volume 3940), Springer-Verlag, Berlin, Germany. pp. 34-51. [https://doi.org/10.1007/11752790_2 doi: 10.1007/11752790_2]</ref> to provide high temporal and/or spatial resolution characterization of surface water chemicals of potential concern (COPCs).  
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[[File:StrathmannFig1.png | thumb |300px|Figure 1. Illustration of PFAS adsorption by anion exchange resins (AERs). Incorporation of longer alkyl group side chains on the cationic quaternary amine functional groups leads to PFAS-resin hydrophobic interactions that increase resin selectivity for PFAS over inorganic anions like Cl<sup>-</sup>.]]
 
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[[File:StrathmannFig2.png | thumb | 300px| Figure 2. Effect of perfluoroalkyl carbon chain length on the estimated bed volumes (BVs) to 50% breakthrough of PFCAs and PFSAs observed in a pilot study<ref name="StrathmannEtAl2020">Strathmann, T.J., Higgins, C., Deeb, R., 2020. Hydrothermal Technologies for On-Site Destruction of Site Investigation Wastes Impacted by PFAS, Final Report - Phase I. SERDP Project ER18-1501. [https://serdp-estcp.mil/projects/details/b34d6396-6b6d-44d0-a89e-6b22522e6e9c Project Website]&nbsp;&nbsp; [[Media: ER18-1501.pdf| Report.pdf]]</ref> treating PFAS-contaminated groundwater with the PFAS-selective AER (Purolite PFA694E) ]]
 
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==Technology Overview==
 
==Technology Overview==
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[[File:StrathmannFig3.png | thumb | 300px| Figure 3. Fixed bed reactor vessels containing anion exchange resins treating PFAS-contaminated water in the City of Orange, NJ. Water flow goes through both vessels in a lead-lag configuration. Picture credit: AqueoUS Vets.]]
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[[File:ChangFig1.png | thumb | 300px| Figure 1. Schematic diagram illustrating the OPTICS methodology. High resolution in-situ data are integrated with traditional discrete sample analytical data using partial least-square regression to derive high resolution chemical contaminant concentration data series.]]
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[[File:ChangFig2.png | thumb | 300px| Figure 2. Example of instrumentation used for OPTICS monitoring.]]
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The principle behind OPTICS is based on the relationship between optical properties of natural waters and the particles and dissolved material contained within them<ref>Boss, E. and Pegau, W.S., 2001. Relationship of light scattering at an angle in the backward direction to the backscattering coefficient. Applied Optics, 40(30), pp. 5503-5507. [https://doi.org/10.1364/AO.40.005503 doi: 10.1364/AO.40.005503]</ref><ref>Boss, E., Twardowski, M.S., Herring, S., 2001. Shape of the particulate beam spectrum and its inversion to obtain the shape of the particle size distribution. Applied Optics, 40(27), pp. 4884-4893. [https://doi.org/10.1364/AO.40.004885 doi:10/1364/AO.40.004885]</ref><ref>Babin, M., Morel, A., Fournier-Sicre, V., Fell, F., Stramski, D., 2003. Light scattering properties of marine particles in coastal and open ocean waters as related to the particle mass concentration. Limnology and Oceanography, 48(2), pp. 843-859. [https://doi.org/10.4319/lo.2003.48.2.0843 doi: 10.4319/lo.2003.48.2.0843]&nbsp;&nbsp; [[Media: BabinEtAl2003.pdf | Open Access Article]]</ref><ref>Coble, P., Hu, C., Gould, R., Chang, G., Wood, M., 2004. Colored dissolved organic matter in the coastal ocean: An optical tool for coastal zone environmental assessment and management. Oceanography, 17(2), pp. 50-59. [https://doi.org/10.5670/oceanog.2004.47 doi: 10.5670/oceanog.2004.47]&nbsp;&nbsp; [[Media: CobleEtAl2004.pdf | Open Access Article]]</ref><ref>Sullivan, J.M., Twardowski, M.S., Donaghay, P.L., Freeman, S.A., 2005. Use of optical scattering to discriminate particle types in coastal waters. Applied Optics, 44(9), pp. 1667–1680. [https://doi.org/10.1364/AO.44.001667 doi: 10.1364/AO.44.001667]</ref><ref>Twardowski, M.S., Boss, E., Macdonald, J.B., Pegau, W.S., Barnard, A.H., Zaneveld, J.R.V., 2001. A model for estimating bulk refractive index from the optical backscattering ratio and the implications for understanding particle composition in case I and case II waters. Journal of Geophysical Research: Oceans, 106(C7), pp. 14,129-14,142. [https://doi.org/10.1029/2000JC000404 doi: 10/1029/2000JC000404]&nbsp;&nbsp; [[Media: TwardowskiEtAl2001.pdf | Open Access Article]]</ref><ref>Chang, G.C., Barnard, A.H., McLean, S., Egli, P.J., Moore, C., Zaneveld, J.R.V., Dickey, T.D., Hanson, A., 2006. In situ optical variability and relationships in the Santa Barbara Channel: implications for remote sensing. Applied Optics, 45(15), pp. 3593–3604. [https://doi.org/10.1364/AO.45.003593 doi: 10.1364/AO.45.003593]</ref><ref>Slade, W.H. and Boss, E., 2015. Spectral attenuation and backscattering as indicators of average particle size. Applied Optics, 54(24), pp. 7264-7277. [https://doi.org/10.1364/AO.54.007264 doi: 10/1364/AO.54.007264]&nbsp;&nbsp; [[Media: SladeBoss2015.pdf | Open Access Article]]</ref>. Surface water COPCs such as heavy metals and polychlorinated biphenyls (PCBs) are hydrophobic in nature and tend to sorb to materials in the water column, which have unique optical signatures that can be measured at high-resolution using in-situ, commercially available aquatic sensors<ref>Agrawal, Y.C. and Pottsmith, H.C., 2000. Instruments for particle size and settling velocity observations in sediment transport. Marine Geology, 168(1-4), pp. 89-114. [https://doi.org/10.1016/S0025-3227(00)00044-X doi: 10.1016/S0025-3227(00)00044-X]</ref><ref>Boss, E., Pegau, W.S., Gardner, W.D., Zaneveld, J.R.V., Barnard, A.H., Twardowski, M.S., Chang, G.C., Dickey, T.D., 2001. Spectral particulate attenuation and particle size distribution in the bottom boundary layer of a continental shelf. Journal of Geophysical Research: Oceans, 106(C5), pp. 9509-9516. [https://doi.org/10.1029/2000JC900077 doi: 10.1029/2000JC900077]&nbsp;&nbsp; [[Media: BossEtAl2001.pdf | Open Access Article]]</ref><ref>Boss, E., Pegau, W.S., Lee, M., Twardowski, M., Shybanov, E., Korotaev, G. Baratange, F., 2004. Particulate backscattering ratio at LEO 15 and its use to study particle composition and distribution. Journal of Geophysical Research: Oceans, 109(C1), Article C01014. [https://doi.org/10.1029/2002JC001514 doi: 10.1029/2002JC001514]&nbsp;&nbsp; [[Media: BossEtAl2004.pdf | Open Access Article]]</ref><ref>Briggs, N.T., Slade, W.H., Boss, E., Perry, M.J., 2013. Method for estimating mean particle size from high-frequency fluctuations in beam attenuation or scattering measurement. Applied Optics, 52(27), pp. 6710-6725. [https://doi.org/10.1364/AO.52.006710 doi: 10.1364/AO.52.006710]&nbsp;&nbsp; [[Media: BriggsEtAl2013.pdf | Open Access Article]]</ref>. Therefore, high-resolution concentrations of COPCs can be accurately and robustly derived from in-situ measurements using statistical methods.
  
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Anion exchange treatment of water is accomplished by pumping contaminated water through fixed bed reactors filled with AERs (Figure 3). A common configuration involves flowing water through two reactors arranged in a lead-lag configuration<ref name="WoodardEtAl2017">Woodard, S., Berry, J., Newman, B., 2017. Ion Exchange Resin for PFAS Removal and Pilot Test Comparison to GAC. Remediation, 27(3), pp. 19–27. [https://doi.org/10.1002/rem.21515 doi: 10.1002/rem.21515]</ref>. Water flows through the pore spaces in close contact with resin beads. Sufficient contact time needs to be provided, referred to as empty bed contact time (EBCT), to allow PFAS to diffuse from the water into the resin structure and adsorb to exchange sites. Typical EBCTs for AER treatment of PFAS are 2-5 min, shorter than contact times recommended for granular activated carbon (GAC) adsorbents (≥10 min)<ref name="LiuEtAl2022">Liu, C. J., Murray, C.C., Marshall, R.E., Strathmann, T.J., Bellona, C., 2022. Removal of Per- and Polyfluoroalkyl Substances from Contaminated Groundwater by Granular Activated Carbon and Anion Exchange Resins: A Pilot-Scale Comparative Assessment. Environmental Science: Water Research and Technology, 8(10), pp. 2245–2253. [https://doi.org/10.1039/D2EW00080F doi: 10.1039/D2EW00080F]</ref><ref>Liu, C.J., Werner, D., Bellona, C., 2019. Removal of Per- and Polyfluoroalkyl Substances (PFASs) from Contaminated Groundwater Using Granular Activated Carbon: A Pilot-Scale Study with Breakthrough Modeling. Environmental Science: Water Research and Technology, 5(11), pp. 1844–1853. [https://doi.org/10.1039/C9EW00349E doi: 10.1039/C9EW00349E]</ref>. The higher adsorption capacities and shorter EBCTs of AERs enable use of much less media and smaller vessels than GAC, reducing expected capital costs for AER treatment systems<ref name="EllisEtAl2023">Ellis, A.C., Boyer, T.H., Fang, Y., Liu, C.J., Strathmann, T.J., 2023. Life Cycle Assessment and Life Cycle Cost Analysis of Anion Exchange and Granular Activated Carbon Systems for Remediation of Groundwater Contaminated by Per- and Polyfluoroalkyl Substances (PFASs). Water Research, 243, Article 120324. [https://doi.org/10.1016/j.watres.2023.120324 doi: 10.1016/j.watres.2023.120324]</ref>.  
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The OPTICS method is analogous to the commonly used empirical derivation of total suspended solids concentration (TSS) from optical turbidity using linear regression<ref>Rasmussen, P.P., Gray, J.R., Glysson, G.D., Ziegler, A.C., 2009. Guidelines and procedures for computing time-series suspended-sediment concentrations and loads from in-stream turbidity-sensor and streamflow data. In: Techniques and Methods, Book 3: Applications of Hydraulics, Section C: Sediment and Erosion Techniques, Ch. 4. 52 pages. U.S. Geological Survey.&nbsp;&nbsp; [[Media: RasmussenEtAl2009.pdf | Open Access Article]]</ref>. However, rather than deriving one response variable (TSS) from one predictor variable (turbidity), OPTICS involves derivation of one response variable (e.g., PCB concentration) from a suite of predictor variables (e.g., turbidity, temperature, salinity, and fluorescence of chlorophyll-a) using multi-parameter statistical regression. OPTICS is based on statistical correlation – similar to the turbidity-to-TSS regression technique; the method does not rely on interpolation or extrapolation.  
  
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Like other adsorption media, PFAS will initially adsorb to media encountered near the inlet side of the reactor, but as ion exchange sites become saturated with PFAS, the active zone of adsorption will begin to migrate through the packed bed with increasing volume of water treated. Moreover, some PFAS with lower affinity for exchange sites (e.g., shorter-chain PFAS that are less hydrophobic) will be displaced by competition from other PFAS (e.g., longer-chain PFAS that are more hydrophobic) and move further along the bed to occupy open sites<ref name="EllisEtAl2022">Ellis, A.C., Liu, C.J., Fang, Y., Boyer, T.H., Schaefer, C.E., Higgins, C.P., Strathmann, T.J., 2022. Pilot Study Comparison of Regenerable and Emerging Single-Use Anion Exchange Resins for Treatment of Groundwater Contaminated by per- and Polyfluoroalkyl Substances (PFASs). Water Research, 223, Article 119019. [https://doi.org/10.1016/j.watres.2022.119019 doi: 10.1016/j.watres.2022.119019]&nbsp;&nbsp; [[Special:FilePath/EllisEtAl2022.pdf| Open Access Manuscript]]</ref>. Eventually, PFAS will start to breakthrough into the effluent from the reactor, typically beginning with the shorter-chain compounds. The initial breakthrough of shorter-chain PFAS is similar to the behavior observed for AER treatment of inorganic contaminants.  
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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.
  
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Upon breakthrough, treatment is halted, and the exhausted resins are either replaced with fresh media or regenerated before continuing treatment. Most vendors are currently operating AER treatment systems for PFAS in single-use mode where virgin media is delivered to replace exhausted resins, which are transported off-site for disposal or incineration<ref name="BoyerEtAl2021a" />. As an alternative, some providers are developing regenerable AER treatment systems, where exhausted resins are regenerated on-site by desorbing PFAS from the resins using a combination of salt brine (typically ≥1 wt% NaCl) and cosolvent (typically ≥70 vol% methanol)<ref name="BoyerEtAl2021a" /><ref name="BoyerEtAl2021b">Boyer, T.H., Ellis, A., Fang, Y., Schaefer, C.E., Higgins, C.P., Strathmann, T.J., 2021. Life Cycle Environmental Impacts of Regeneration Options for Anion Exchange Resin Remediation of PFAS Impacted Water. Water Research, 207, Article 117798. [https://doi.org/10.1016/j.watres.2021.117798 doi: 10.1016/j.watres.2021.117798]&nbsp;&nbsp; [[Special:FilePath/BoyerEtAl2021b.pdf| Open Access Manuscript]]</ref><ref>Houtz, E., (projected completion 2025). Treatment of PFAS in Groundwater with Regenerable Anion Exchange Resin as a Bridge to PFAS Destruction, Project ER23-8391. [https://serdp-estcp.mil/projects/details/a12b603d-0d4a-4473-bf5b-069313a348ba/treatment-of-pfas-in-groundwater-with-regenerable-anion-exchange-resin-as-a-bridge-to-pfas-destruction Project Website].</ref>. This mode of operation allows for longer term use of resins before replacement, but requires more complex and extensive site infrastructure. Cosolvent in the resulting waste regenerant can be recycled by distillation, which reduces chemical inputs and lowers the volume of PFAS-contaminated still bottoms requiring further treatment or disposal<ref name="BoyerEtAl2021b" />. Currently, there is active research on various technologies for destruction of PFAS concentrates in AER still bottoms residuals<ref name="StrathmannEtAl2020"/><ref name="HuangEtAl2021">Huang, Q., Woodard, S., Nickleson, M., Chiang, D., Liang, S., Mora, R., 2021. Electrochemical Oxidation of Perfluoroalkyl Acids in Still Bottoms from Regeneration of Ion Exchange Resins Phase I - Final Report. SERDP Project ER18-1320. [https://serdp-estcp.mil/projects/details/ccaa70c4-b40a-4520-ba17-14db2cd98e8f Project Website]&nbsp;&nbsp; [[Special:FilePath/ER18-1320.pdf| Report.pdf]]</ref>.
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OPTICS in situ measurement parameters include, but are not limited to current velocity, conductivity, temperature, depth, turbidity, dissolved oxygen, and fluorescence of chlorophyll-a and dissolved organic matter. Instrumentation for these measurements is commercially available, robust, deployable in a wide variety of configurations (e.g., moored, vessel-mounted, etc.), powered by batteries, and records data internally and/or transmits data in real-time. The physical, optical, and water quality instrumentation is compact and self-contained. The modularity and automated nature of the OPTICS measurement system enable robust, long-term, autonomous data collection for near-continuous monitoring.  
  
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==Field Demonstrations==
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OPTICS measurements are provided at a significantly reduced cost relative to traditional monitoring techniques used within the environmental industry. Cost performance analysis shows that monitoring costs are reduced by more than 85% while significantly increasing the temporal and spatial resolution of sampling. The reduced cost of monitoring makes this technology suitable for a number of environmental applications including, but not limited to site baseline characterization, source control evaluation, dredge or stormflow plume characterization, and remedy performance monitoring. OPTICS has been successfully demonstrated for characterizing a wide variety of COPCs: mercury, methylmercury, copper, lead, PCBs, dichlorodiphenyltrichloroethane (DDT) and its related compounds (collectively, DDX), and 2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD or dioxin) in a number of different environmental systems ranging from inland lakes and rivers to the coastal ocean. To date, OPTICS has been limited to surface water applications; additional applications, e.g., groundwater, would require further research and development.  
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[[File:StrathmannFig4.png | thumb | 300px| Figure 4. Pilot treatment system comparing three AERs (2.5 min EBCT) with GAC (10 min EBCT) for treatment of a PFAS-contaminated groundwater. Picture courtesy of Charlie Liu.]]
 
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Field pilot studies are critical to demonstrating the effectiveness and expected costs of PFAS treatment technologies. A growing number of pilot studies testing the performance of commercially available AERs to treat PFAS-contaminated groundwater, including sites impacted by historical use of aqueous film-forming foam (AFFF), have been published recently (Figure 4)<ref name="WoodardEtAl2017"/><ref name="LiuEtAl2022"/><ref name="EllisEtAl2022"/><ref name="ChowEtAl2022">Chow, S.J., Croll, H.C., Ojeda, N., Klamerus, J., Capelle, R., Oppenheimer, J., Jacangelo, J.G., Schwab, K.J., Prasse, C., 2022. Comparative Investigation of PFAS Adsorption onto Activated Carbon and Anion Exchange Resins during Long-Term Operation of a Pilot Treatment Plant. Water Research, 226, Article 119198. [https://doi.org/10.1016/j.watres.2022.119198 doi: 10.1016/j.watres.2022.119198]</ref><ref>Zaggia, A., Conte, L., Falletti, L., Fant, M., Chiorboli, A., 2016. Use of Strong Anion Exchange Resins for the Removal of Perfluoroalkylated Substances from Contaminated Drinking Water in Batch and Continuous Pilot Plants. Water Research, 91, pp. 137–146. [https://doi.org/10.1016/j.watres.2015.12.039 doi: 10.1016/j.watres.2015.12.039]</ref>. A 9-month pilot study treating contaminated groundwater near an AFFF source zone, with total PFAS concentrations >20 &mu;g/L, showed that single-use PFAS-selective resins significantly outperform more traditional regenerable resins<ref name="EllisEtAl2022"/>. No detectable concentrations of ≥C7 PFCAs or PFSAs of any length were observed in the first 150,000 bed volumes (BVs) of water treated with PFAS-selective resins provided by three different manufacturers (one BV is a volume of water equivalent to the volume occupied by the pore spaces in the reactor). Earlier breakthrough of shorter-chain PFCAs was observed for all resins, with the shortest chain structures eluting chromatographically (PFAS breakthrough order follows increasing chain length). Moreover, the superiority of PFAS-selective resins was less dramatic for shorter-chain PFCAs, highlighting the importance of site-specific treatment criteria when selecting among resins. Analysis  of the used resin beds following completion of the study shows that breakthrough of PFAS with the lowest affinity for AERs (e.g., short-chain PFCAs) is accelerated by competitive displacement from adsorption sites by PFAS with greater affinity (e.g., PFSAs and long-chain PFCAs).
 
 
   
 
   
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Another study treating a more dilute plume of AFFF-impacted groundwater (100 – 200 ng/L total PFAS) compared PFAS-selective AER with GAC<ref name="LiuEtAl2022"/>. The same compound-dependent breakthrough patterns were observed with all media, where earlier PFCA breakthrough will likely dictate media changeout requirements. Comparing AER with GAC shows that the former adsorbed 6-7 times more PFAS than the latter before breakthrough. All PFSAs appear to breakthrough AER simultaneously after >100,000 BVs due to fouling of resins by metals present in the sourcewater, highlighting the potential importance of sourcewater pretreatment. Although AERs outperform GAC, estimated operation and maintenance (O&M) costs for both media are similar due to the higher unit media costs for AER.
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==Applications==
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[[File:ChangFig3.png | thumb | 300px| Figure 3. OPTICS to characterize COPC variability in the context of site processes at BCSA. (A) Tidal oscillations (Elev.<sub>MSL</sub>) and precipitation (Precip.). (B) – (D) OPTICS-derived particulate mercury (PHg) and methylmercury (PMeHg) and total PCBs (TPCBs). Open circles represent discrete water sample data.]]
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[[File:ChangFig4.png | thumb | 300px| Figure 4. OPTICS reveals baseflow daily cycling and confirms storm-induced particle-bound COPC resuspension and mobilization through bank interaction. (A) Flow rate (Q) and precipitation (Precip). (B) – (C) OPTICS-derived particulate mercury (PHg) and methylmercury (PMeHg). Open circles represent discrete water sample data.]]
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[[File:ChangFig5.png | thumb | 300px| Figure 5. Three-dimensional volume plot of high spatial resolution OPTICS-derived PCBs in exceedance of baseline showing that PCBs were discharged from the outfall (yellow arrow), remained in suspension, and dispersed elsewhere before settling.]]
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An OPTICS study was conducted at Berry’s Creek Study Area (BCSA), New Jersey in 2014 and 2015 to understand COPC sources and transport mechanisms for development of an effective remediation plan. OPTICS successfully extended periodic discrete surface water samples to continuous, high-resolution measurements of PCBs, mercury, and methylmercury to elucidate COPC sources and transport throughout the BCSA tidal estuary system. OPTICS provided data at resolution sufficient to investigate COC variability in the context of physical processes. The results facilitated focused and effective site remediation and management decisions that could not be determined based on periodic discrete samples alone, despite over seven years of monitoring at different locations throughout the system over a range of different seasons, tidal phases, and environmental conditions. The BCSA OPTICS methodology and results have undergone official peer review overseen by the U.S. Environmental Protection Agency (USEPA) and results have been published in peer-reviewed literature<ref name="ChangEtAl2019"/>.  
  
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A third pilot study compared the long-term (>1 year) performance of PFAS-selective AERs with GAC treating contaminated groundwater dominated by short-chain PFCAs<ref name="ChowEtAl2022"/>. As noted in other studies, AER outperform GAC on a bed volume-normalized basis, especially for longer-chain PFCAs and PFSAs. With lower site groundwater concentrations, quantitative relationships between chain length and breakthrough was observed for both PFCAs and PFSAs, with log-linear relationships being observed between BV10 and BV50 (bed volumes at which 10% and 50% breakthrough occurs, respectively) and chain length. These investigators also noted that deviations from a linear PFAS structure (e.g., branching of the perfluoroalkyl chain) negatively affects AER adsorption to a lesser extent than GAC.
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OPTICS was applied at the South River, Virginia in 2016 to quantify sources of legacy mercury in the system that are contributing to recontamination and continued elevated mercury concentrations in fish tissue. OPTICS provided information necessary to identify mechanisms for COPC redistribution and to quantify the relative contribution of each mechanism to total mass transport of mercury and methylmercury in the system. Continuous, high-resolution COPC data afforded by OPTICS helped resolve baseflow daily cycling that had never before been observed at the South River and provided data at temporal resolution necessary to verify storm-induced particle-bound COC resuspension and mobilization through bank interaction. The results informed source control and remedy design and monitoring efforts. Methodology and results from the South River have been published in peer-reviewed literature<ref name="ChangEtAl2018"/>.  
  
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While most pilot studies have focused on evaluating single-use AERs, pilot studies have also been undertaken to test anion exchange treatment systems employing regenerable AER<ref name="WoodardEtAl2017"/>. Operating lead-lag packed beds, with 5-min EBCT each, the regenerable AER delayed breakthrough of PFCAs and PFSAs compared to GAC. Effluent PFOA breakthrough from the lag bed of AER occurred after ~10,000 BVs, necessitating resin regeneration, which was accomplished by backflushing with 10 BVs of a salt brine/organic cosolvent mixture (+1 BV salt brine pre-rinse and 10 BVs potable water post-rinse). PFAS removal results using the regenerated resin were then found to be comparable with virgin resin. Preliminary tests showed that cosolvent use can be minimized by recovering from the waste regenerant mixture by distillation. A number of studies are currently underway to test the effectiveness of different technologies for destruction of PFAS concentrates in the resulting still bottoms residual.
+
The U.S. Department of Defense’s Environmental Security Technology Certification Program (ESTCP) supported an OPTICS demonstration study at the Pearl Harbor Sediment Site, Hawaii, to determine whether stormwater from Oscar 1 Pier outfall is a contributing source of PCBs to Decision Unit (DU) N-2 (ESTCP Project ER21-5021). High spatial resolution results afforded by ship-based, mobile OPTICS monitoring suggested that PCBs were discharged from the outfall, remained in suspension, and dispersed elsewhere before settling. More details regarding this study were presented by Chang et al. in 2024<ref name="ChangEtAl2024"/>.  
  
−
==Costs and the Importance of Treatment Criteria==
+
==Summary==
−
Life cycle cost analyses show that anion exchange treatment is a viable alternative to GAC adsorption<ref name="LiuEtAl2022"/><ref name="EllisEtAl2023"/>. Like other adsorption treatment systems, single-use AER treatment systems have fairly simple design with lead-lag reactor vessels in series together with associated pumping, plumbing and any water pretreatment processes (e.g., sediment filters, process for metals removal). While similar in design to GAC treatment systems, single-use AER treatment systems can have significantly lower capital costs due to the smaller reaction vessels used (as a result of shorter required EBCTs for AER)<ref name="EllisEtAl2023"/>. The smaller reactor sizes may also reduce associated costs for any structure required to house the reactors. Capital costs for regenerable AER systems are more difficult to estimate because of their added system complexity, including added infrastructure for resin regeneration, cosolvent recovery by distillation, and still bottoms management. Over the full life cycle of AER treatment systems, typically >10 years, operating costs are expected to dominate overall PFAS treatment costs<ref name="EllisEtAl2023"/>. These costs are determined largely by media usage rate (MUR), which is the frequency for replacement and disposal or regeneration of exhausted resins. Despite the higher unit costs of anion exchange media relative to GAC (often ≥3-fold greater per m<sup>3</sup>), the superior adsorption capacity and PFAS affinity of AERs leads to lower MURs that more than offset this increased sorbent cost.
+
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.
  
−
A critical parameter that will dictate media usage or regeneration, and ultimately O&M costs, is the criteria used to determine when ‘PFAS breakthrough’ is reached. Sites are typically contaminated with a mix of different PFAS that will breakthrough resin beds into effluent at different bed volumes of water. For example, short-chain PFCAs breakthrough much more rapidly than long-chain PFCAs and PFSAs, so selection of treatment criteria that include short-chain PFCAs like perfluorobutanoic acid (PFBA) will necessitate more frequent media replacement or regeneration than criteria focused on long-chain PFAS. Likewise, adoption of the proposed drinking water limits for PFOS and PFOA (4 ng/L each)<ref>USEPA, 2023. PFAS National Primary Drinking Water Regulation Rulemaking. 88 Federal Register, pp. 18638-18754. [https://www.federalregister.gov/documents/2023/03/29/2023-05471/pfas-national-primary-drinking-water-regulation-rulemaking Federal Register Website]</ref> in effluent of the lead vessel of a lead-lag reactor system as the breakthrough criteria will require more frequent media replacement than using a less stringent criteria (e.g., 50% breakthrough of either compound in the lead vessel). Breakthrough criteria can also affect media selection because the performance advantages of the more expensive PFAS-selective AER over regenerable AER and GAC are most apparent when media replacement/regeneration is dictated by breakthrough of long-chain PFCAs and PFSAs, and when a greater extent of media adsorption capacity is used before replacement/regeneration; these advantages shrink when media replacement/regeneration is dictated by breakthrough of short-chain PFCAs<ref name="EllisEtAl2023"/><ref name="EllisEtAl2022"/><ref name="ChowEtAl2022"/>. While purchase of new media and disposal of exhausted media are minimal with regenerable AER, costs are still linked closely to regeneration frequency because of the needs for consumables (salt brine, cosolvent) and management and disposal of the resulting waste regenerant solutions, which often far exceeds media waste in terms of total waste mass and volume. These costs may be reduced by recovering cosolvent and destruction of PFAS in the resulting still bottoms<ref name="BoyerEtAl2021b"/>, areas of active research and development<ref name="StrathmannEtAl2020"/><ref name="HuangEtAl2021"/>
+
Because OPTICS monitoring involves deployment of autonomous sampling instrumentation, a substantially greater volume of data can be collected using this technique compared to traditional sampling, and at a far lower cost. A large volume of data supports evaluation of chemical contaminant concentrations over a range of spatial and temporal scales, and the system can be customized for a variety of environmental applications. OPTICS helps quantify contaminant mass flux and the relative contribution of local transport and source areas to net contaminant transport. OPTICS delivers a strong line of evidence for evaluating contaminant sources, fate, and transport, and for supporting the design of a remedy tailored to address site-specific, risk-driving conditions. The improved understanding of site processes aids in the development of mitigation measures that minimize site risks.
  
 
==References==
 
==References==

Revision as of 18:32, 9 July 2024

OPTically-based In-situ Characterization System (OPTICS)

OPTICS combines robust aquatic instrumentation and innovative data processing techniques to measure concentrations of a wide range of dissolved and particulate chemical contaminants in surface water at unprecedented scales. OPTICS is used for a variety of environmental applications including remedial investigation, conceptual site model validation, baseline characterization, source control evaluation, plume characterization, and remedial monitoring.

Related Article(s):

Contributor(s):

  • Grace Chang, Ph.D.
  • Todd Martin, P.E.

Key Resource(s):

  • Optically based quantification of fluxes of mercury, methyl mercury, and polychlorinated biphenyls (PCBs) at Berry’s Creek tidal estuary, New Jersey[1]
  • OPTically-based In-situ Characterization System (OPTICS) to quantify concentrations of mass fluxes of mercury and methylmercury in South River, Virginia, USA[2]
  • Evaluation of stormwater as a potential source of polychlorinated biphenyls (PCBs) to Pearl Harbor, Hawaii[3]

Background

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 ensure remedy effectiveness. Source control and total maximum daily load (TMDL) actions generally require costly manual monitoring of surface water dissolved and particulate contaminant concentrations. 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 in capturing episodic events (e.g., storms) important to site risk and remedy due to safety concerns and standby requirements for resources. Automated water samplers are commercially available but still require significant field support and costly laboratory analysis. Further, automated samplers may not be suitable for analytes with short hold-times and temperature requirements.

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[1][2][3][7][8][9]. The OPTICS tool integrates commercial off-the-shelf in-situ aquatic sensors, periodic discrete surface water sample collection, and a multi-parameter statistical prediction model[10][11] to provide high temporal and/or spatial resolution characterization of surface water chemicals of potential concern (COPCs).

Technology Overview

Figure 1. Schematic diagram illustrating the OPTICS methodology. High resolution in-situ data are integrated with traditional discrete sample analytical data using partial least-square regression to derive high resolution chemical contaminant concentration data series.
Figure 2. Example of instrumentation used for OPTICS monitoring.

The principle behind OPTICS is based on the relationship between optical properties of natural waters and the particles and dissolved material contained within them[12][13][14][15][16][17][18][19]. 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[20][21][22][23]. 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[24]. 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[10][11]. 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 enable robust, long-term, autonomous data collection for near-continuous monitoring.

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 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.
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 facilitated focused and effective site remediation and management decisions that could not be determined based on periodic discrete samples alone, despite over seven years of monitoring at different locations throughout the system over a range of different seasons, tidal phases, and environmental conditions. The BCSA OPTICS methodology and results have undergone official peer review overseen by the U.S. Environmental Protection Agency (USEPA) and results have been published in peer-reviewed literature[1].

OPTICS was applied at the South River, Virginia in 2016 to quantify sources of legacy mercury in the system that are contributing to recontamination and continued elevated mercury concentrations in fish tissue. OPTICS provided information necessary to identify mechanisms for COPC redistribution and to quantify the relative contribution of each mechanism to total mass transport of mercury and methylmercury in the system. Continuous, high-resolution COPC data afforded by OPTICS helped resolve baseflow daily cycling that had never before been observed at the South River and provided data at temporal resolution necessary to verify storm-induced particle-bound COC resuspension and mobilization through bank interaction. The results informed source control and remedy design and monitoring efforts. Methodology and results from the South River have been published in peer-reviewed literature[2].

The U.S. Department of Defense’s Environmental Security Technology Certification Program (ESTCP) supported an OPTICS demonstration study at the Pearl Harbor Sediment Site, Hawaii, to determine whether stormwater from Oscar 1 Pier outfall is a contributing source of PCBs to Decision Unit (DU) N-2 (ESTCP Project ER21-5021). High spatial resolution results afforded by ship-based, mobile OPTICS monitoring suggested that PCBs were discharged from the outfall, remained in suspension, and dispersed elsewhere before settling. More details regarding this study were presented by Chang et al. in 2024[3].

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 1.2 Chang, G., Martin, T., Whitehead, K., Jones, C., Spada, F., 2019. Optically based quantification of fluxes of mercury, methyl mercury, and polychlorinated biphenyls (PCBs) at Berry’s Creek tidal estuary, New Jersey. Limnology and Oceanography, 64(1), pp. 93-108. doi: 10.1002/lno.11021   Open Access Article
  2. ^ 2.0 2.1 2.2 Chang, G., Martin, T., Spada, F., Sackmann, B., Jones, C., Whitehead, K., 2018. OPTically-based In-situ Characterization System (OPTICS) to quantify concentrations and mass fluxes of mercury and methylmercury in South River, Virginia, USA. River Research and Applications, 34(9), pp. 1132-1141. doi: 10.1002/rra.3361
  3. ^ 3.0 3.1 3.2 Chang, G., Spada, F., Brodock, K., Hutchings, C., Markillie, K., 2024. Evaluation of stormwater as a potential source of polychlorinated biphenyls (PCBs) to Pearl Harbor, Hawaii. Case Studies in Chemical and Environmental Engineering, 9, Article 100659. doi: 10.1016/j.cscee.2024.100659   Open Access Article
  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. ^ 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
  8. ^ 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
  9. ^ 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
  10. ^ 10.0 10.1 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
  11. ^ 11.0 11.1 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
  12. ^ 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
  13. ^ 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
  14. ^ 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
  15. ^ 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
  16. ^ 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
  17. ^ 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
  18. ^ 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
  19. ^ 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
  20. ^ 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
  21. ^ 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
  22. ^ 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
  23. ^ 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
  24. ^ 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

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