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A Conceptual Site Model (CSM) is a collection of information about a contaminated site that integrates the available evidence regarding its hydrogeologic setting, contaminant sources, exposure pathways, potential receptors, and site history.  A CSM for a [[Wikipedia: Light non-aqueous phase liquid | Light Non-Aqueous Phase Liquid (LNAPL)]] site focuses on several key concepts:  the stage in the LNAPL site life cycle, LNAPL distribution in the subsurface and the resulting mobility of the LNAPL, LNAPL as a source of dissolved and vapor plumes, and the attenuation of LNAPL sources over time.
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==Assessing Vapor Intrusion (VI) Impacts in Neighborhoods with Groundwater Contaminated by Chlorinated Volatile Organic Chemicals (CVOCs)==
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The VI Diagnosis Toolkit<ref name="JohnsonEtAl2020">Johnson, P.C., Guo, Y., Dahlen, P., 2020.  The VI Diagnosis Toolkit for Assessing Vapor Intrusion Pathways and Mitigating Impacts in Neighborhoods Overlying Dissolved Chlorinated Solvent Plumes.  ESTCP Project ER-201501, Final Report. [https://serdp-estcp.mil/projects/details/a0d8bafd-c158-4742-b9fe-5f03d002af71 Project Website]&nbsp;&nbsp; [[Media: ER-201501.pdf | Final Report.pdf]]</ref> is a set of tools that can be used individually or in combination to assess vapor intrusion (VI) impacts at one or more buildings overlying regional-scale dissolved chlorinated solvent-impacted groundwater plumes. The strategic use of these tools can lead to confident and efficient neighborhood-scale VI pathway assessments.
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<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
 
<div style="float:right;margin:0 0 2em 2em;">__TOC__</div>
  
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'''Related Article(s)'''
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'''Related Article(s):'''
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* [[LNAPL Remediation Technologies]]
 
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* [[NAPL Mobility]]
 
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* [[Natural Source Zone Depletion (NSZD)]]
 
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* [[Natural Attenuation in Source Zone and Groundwater Plume - Bemidji Crude Oil Spill]]
 
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* [[Monitored Natural Attenuation (MNA)]]
 
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* [[Biodegradation - Hydrocarbons]]
 
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'''CONTRIBUTOR(S):''' [[Dr. Charles Newell, P.E. | Charles Newell]]
 
  
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'''Key Resource(s):'''
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*[[Vapor Intrusion (VI)]]
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* LNAPL Site Management: LCSM Evolution, Decision Process, and Remedial Technologies. LNAPL-3. ITRC.<ref name="LNAPL-3">Interstate Technology and Regulatory Council (ITRC), 2018. LNAPL Site Management: LCSM Evolution, Decision Process, and Remedial Technologies. LNAPL-3. ITRC, LNAPL Update Team, Washington, DC.  [https://lnapl-3.itrcweb.org LNAPL-3 Website]</ref>
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*[[Vapor Intrusion – Sewers and Utility Tunnels as Preferential Pathways]]
  
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* Managing Risk at LNAPL Sites - Frequently Asked Questions, 2nd Edition. API.<ref name="Sale2018"> Sale, T., Hopkins, H., and Kirkman, A., 2018.  Managing Risk at LNAPL Sites - Frequently Asked Questions, 2nd Edition. American Petroleum Institute (API), Washington, DC. 72 pages. [https://www.api.org/oil-and-natural-gas/environment/clean-water/ground-water/lnapl/lnapl-faqs Free download from API.] [https://www.enviro.wiki/index.php?title=File:Sale-2018_LNAPL_FAQs_2nd_ed.pdf Report.pdf]</ref>
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'''Contributor(s):'''
  
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==Life Cycle of LNAPL Sites==
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*Paul C. Johnson, Ph.D.
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[[File:Newell1w2Fig1.png |thumb|left|250px| Figure 1. Early, Middle, and Late Stage LNAPL releases<ref name= "Sale2018"/>. The key distinctions are the presence of continuous LNAPL that can be mobile and the amount of time that has elapsed for NSZD to remove LNAPL.]]
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*Paul Dahlen, Ph.D.
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A Conceptual Site Model (CSM) is a collection of information about a contaminated site that integrates the available evidence regarding its hydrogeologic setting, contaminant sources, exposure pathways, potential receptors, and site history (see ASTM E1689-95(2014)<ref name="ASTM2014a"> ASTM, 2014. Standard Guide for Developing Conceptual Site Models for Contaminated Sites. ASTM E1689-95(2014), ASTM International, West Conshohocken, PA. [https://doi.org/10.1520/E1689-95R14 DOI: 10.1520/E1689-95R14]  http://www.astm.org/cgi-bin/resolver.cgi?E1689</ref> and ASTM E2531-06(2014)<ref name="ASTM2014b"> ASTM, 2014. Standard Guide for Development of Conceptual Site Models and Remediation Strategies for Light Nonaqueous-Phase Liquids Released to the Subsurface. ASTM E2531-06(2014), ASTM International, West Conshohocken, PA. [https://doi.org/10.1520/E2531-06R14  DOI: 10.1520/E2531-06R14]  http://www.astm.org/cgi-bin/resolver.cgi?E2531</ref>).  When developing a CSM for an LNAPL site, it is important to understand that LNAPL releases evolve and change from what are referred to as Early Stage sites to Middle Stage and then to Late Stage sites<ref name="Sale2018"/> (Figure 1).
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*Yuanming Guo, Ph.D.
  
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An Early Stage site is characterized by the presence of a continuous LNAPL zone where a thick layer of LNAPL accumulation (also known as free product) is observed in monitoring wells. The continuous LNAPL zone (or LNAPL body) may be mobile at Early Stage sites, migrating into previously non-impacted areas. Removal of significant LNAPL mass by active pumping may be feasible at these sites. Early Stage sites are now relatively rare in the United States due to stringent environmental regulations enacted in the 1980s which emphasized preventing releases.
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'''Key Resource(s):'''
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[[File:Newell1w2Fig2a.png |thumb|500px| Figure 2a.  Time lapse conceptualization of the formation of an LNAPL body<ref name="ITRC2019"> Interstate Technology and Regulatory Council (ITRC), 2019. LNAPL Training: Connecting the Science to Managing Sites. Part 1: Understanding LNAPL Behavior in the Subsurface. ITRC, Washington, DC. [[Media: ITRC2019_LNAPLtrainingPart1.pdf | Slides.pdf]]</ref>.]]
 
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[[File:Newell1w2Fig2b.png |thumb|500px| Figure 2b.  Sand tank experiment of an LNAPL release<ref name="ITRC2019"/>.]]
 
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Many sites in the U.S. are now considered to be in the Middle Stage, where the LNAPL thickness in wells has been largely depleted by natural spreading of the LNAPL body, [[Natural Source Zone Depletion (NSZD)]], smearing of the water table, and/or active remediation, and where the LNAPL bodies are stable or shrinking<ref name="LNAPL-3"/><ref name="Sale2018"/> (Figure 1).  Active pumping characteristically only recovers LNAPL at relatively low rates of under 100 gallons per acre per year at Middle Stage sites, but NSZD rates may be much higher, on the order of 100s to 1,000s of gallons per acre per year.  Middle Stage dissolved phase plumes, typically comprised of monoaromatics such as benzene, toluene, ethyl benzene, and xylenes, are stable or shrinking over time.
 
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Late Stage sites only have a sparse distribution of residual (trapped) LNAPL due to long-term NSZD and any active remediation that has been performed at the site.  The potential risks to receptors are typically low at Late Stage sites due to relatively low concentrations of LNAPL constituents in the dissolved phase and/or vapor plumes.
 
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==LNAPL Body Formation==
 
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LNAPLs released from tanks, pits, pipelines, or other sources will percolate downwards under the influence of gravity through permeable pathways in the unsaturated zone (e.g., soil pore space, fractures, and macropores) depending on the volume and pressure head of the LNAPL release, until encountering an impermeable layer or the water table, causing the LNAPL body to spread laterally.  The Interstate Technology and Regulatory Council (ITRC)<ref name="LNAPL-3"/> describes this downward movement toward the water table this way:
 
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<blockquote>''During the downward movement of LNAPL through the soil, the presence of confining layers, subsurface heterogeneities, or other preferential pathways may result in irregular and complex lateral spreading and/or perching of LNAPL before the water table is encountered. Once at the water table, the LNAPL will spread laterally in a radial fashion as well as penetrate vertically downward into the saturated zone, displacing water to some depth proportional to the driving force of the vertical LNAPL column (or LNAPL head). The vertical penetration of LNAPL into the saturated zone will continue to occur as long as the downward force produced by the LNAPL head or pressure from the LNAPL release exceeds the counteracting forces produced by the resistance of the soil matrix and the buoyancy resulting from the density difference between LNAPL and groundwater.''<ref name="LNAPL-3"/></blockquote>
 
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While the release at the surface is still active, the LNAPL body can expand until the LNAPL addition rate is equal to the NSZD depletion rate.  However, once the release at the surface is stopped, the expansion will stop relatively quickly, and the LNAPL body will stabilize.  Figure 2a shows a conceptual depiction of this release scenario and Figure 2b shows a sand tank experiment of an LNAPL release.  Because of the buoyancy effects, LNAPL releases that reach the water table will form LNAPL bodies that “like icebergs, are partially above and below the water table”.<ref name="Sale2018"/>
 
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==Key Implications of the LNAPL Conceptual Site Model==
 
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The nature of multi-phase flow processes in porous media (e.g., the interaction of LNAPL, water, and air in the pore spaces of an unconsolidated aquifer) has several important implications for environmental professionals in areas including interpretation of LNAPL thickness in monitoring wells and assessment of the long-term risk associated with LNAPL source zones.  A few of the key implications are described below.
 
  
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===Three States of LNAPL===
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*The VI Diagnosis Toolkit for Assessing Vapor Intrusion Pathways and Impacts in Neighborhoods Overlying Dissolved Chlorinated Solvent Plumes, ESTCP Project ER-201501, Final Report<ref name="JohnsonEtAl2020"/>
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LNAPL can be found in the subsurface in three different states:
 
  
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# '''Residual LNAPL''' is trapped and immobile but can undergo composition and phase changes and generate dissolved hydrocarbon plumes in saturated zones and/or vapors in unsaturated zones. The fraction of the total pore space occupied by this discontinuous LNAPL is referred to as the residual saturation, with other phases such as water and air in the remainder of the pore space.
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*CPM Test Guidelines: Use of Controlled Pressure Method Testing for Vapor Intrusion Pathway Assessment, ESTCP Project ER-201501, Technical Report<ref name="JohnsonEtAl2021">Johnson, P.C., Guo, Y., Dahlen, P., 2021.  CPM Test Guidelines: Use of Controlled Pressure Method Testing for Vapor Intrusion Pathway Assessment. ESTCP ER-201501, Technical Report. [https://serdp-estcp.mil/projects/details/a0d8bafd-c158-4742-b9fe-5f03d002af71 Project Website]&nbsp;&nbsp; [[Media: ER-201501_Technical_Report.pdf | Technical_Report.pdf]]</ref>     
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# '''Mobile LNAPL''' is LNAPL at greater than the residual saturation. Mobile LNAPL can accumulate in a well and is potentially recoverable, but is not migrating (i.e., the LNAPL body is not expanding).
 
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# '''Migrating LNAPL''' is LNAPL at greater than the residual concentration which is observed to expand into previously non-impacted locations over time (e.g., LNAPL appears in a monitoring well that had previously been clean).
 
  
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These three LNAPL states can cause different concerns and in some cases require different remediation goals.  
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*VI Diagnosis Toolkit User Guide, ESTCP Project ER-201501<ref name="JohnsonEtAl2022">Johnson, P.C., Guo, Y., and Dahlen, P., 2022. VI Diagnosis Toolkit User Guide, ESTCP ER-201501, User Guide.  [https://serdp-estcp.mil/projects/details/a0d8bafd-c158-4742-b9fe-5f03d002af71 Project Website]&nbsp;&nbsp; [[Media: ER-201501_User_Guide.pdf | User_Guide.pdf]]</ref>
  
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===LNAPL “Apparent Thickness” is a Poor Metric for Risk Management===
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==Background==
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[[File:Newell1w2Fig3.png |thumb|left|600px| Figure 3. Five LNAPL Thickness Scenarios for five different physical settings<ref name="Sale2018"/>.]]
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[[File:ChangFig2.png | thumb | 400px| Figure 1. Example of instrumentation used for OPTICS monitoring.]]
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[[File:Newell1w2Fig4.png |thumb|350px| Figure 4. Apparent LNAPL thickness versus LNAPL transmissivity, showing no correlation<ref name="Hawthorne2015">Hawthorne, J.M., 2015. Nationwide (USA) Statistical Analysis of LNAPL Transmissivity, in: R. Darlington and A.C. Barton (Chairs), Bioremediation and Sustainable Environmental Technologies—2015. Third International Symposium on Bioremediation and Sustainable Environmental Technologies (Miami, FL), page C-017, Battelle Memorial Institute, Columbus, OH.  www.battelle.org/biosymp  [[Media:Hawthorne2015.pdf | Abstract.pdf]]</ref>.]]
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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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LNAPL thickness in monitoring wells is often referred to as the “apparent LNAPL thickness” because at first glance this LNAPL thickness might be expected to be the thickness of LNAPL that is in the formation, but in reality it is not well correlated with the thickness of the LNAPL zone in the subsurface for several reasons.
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Nationwide, the liability due to contaminated sediments is estimated in the trillions of dollars. Stakeholders are assessing and developing remedial strategies for contaminated sediment sites in major harbors and waterways throughout the U.S. The mobility of contaminants in surface water is a primary transport and risk mechanism<ref>Thibodeaux, L.J., 1996. Environmental Chemodynamics: Movement of Chemicals in Air, Water, and Soil, 2nd Edition, Volume 110 of Environmental Science and Technology: A Wiley-Interscience Series of Texts and Monographs. John Wiley & Sons, Inc. 624 pages. ISBN: 0-471-61295-2</ref><ref>United States Environmental Protection Agency (USEPA), 2005. Contaminated Sediment Remediation Guidance for Hazardous Waste Sites. Office of Superfund Remediation and Technology Innovation Report, EPA-540-R-05-012. [[Media: 2005-USEPA-Contaminated_Sediment_Remediation_Guidance.pdf | Report.pdf]]</ref><ref>Lick, W., 2008. Sediment and Contaminant Transport in Surface Waters. CRC Press. 416 pages. [https://doi.org/10.1201/9781420059885 doi:  10.1201/9781420059885]</ref>; therefore, long-term monitoring of both particulate- and dissolved-phase contaminant concentration prior to, during, and following remedial action is necessary to document remedy effectiveness. Source control and total maximum daily load (TMDL) actions generally require costly manual monitoring of dissolved and particulate contaminant concentrations in surface water. The magnitude of cost for these actions is a strong motivation to implement efficient methods for long-term source control and remedial monitoring.  
  
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First, different physical settings can produce different LNAPL thicknesses in monitoring wells.  Sale et al. (2018) show five different scenarios that produce very different responses with regard to apparent LNAPL thickness (Figure 3).  Scenario A shows an LNAPL apparent thickness in the monitoring well that is at static equilibrium with LNAPL in an unconfined aquifer.  Scenario B, while also an unconfined aquifer, is comprised of very fine-grained soils that cause the LNAPL thickness in the well to be much higher than in Scenario A.  In Scenario C, the LNAPL has accumulated under a confined unit (likely due to an underground release of LNAPL below the confining unit), and the LNAPL has risen above the groundwater potentiometric surface, leading to a large (and misleading) LNAPL thickness in the monitoring well. Scenario D, LNAPL in a perched unit, also shows a very different response from the other scenarios. Scenario E, LNAPL in fractured system, shows that the LNAPL can penetrate below the water table, and that LNAPL thickness in a well is dependent on the pressure from accumulation of LNAPL in the fractures<ref name="Sale2018"/>.
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Traditional surface water monitoring requires mobilization of field teams to manually collect discrete water samples, send samples to laboratories, and await laboratory analysis so that a site evaluation can be conducted. These traditional methods are well known to have inherent cost and safety concerns and are of limited use (due to safety concerns and standby requirements for resources) in capturing the effects of episodic events (e.g., storms) that are important to consider in site risk assessment and remedy selection. Automated water samplers are commercially available but still require significant field support and costly laboratory analysis. Further, automated samplers may not be suitable for analytes with short hold-times and temperature requirements.  
  
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Second, apparent LNAPL thickness is affected by changes in the groundwater surface elevation (or water table). Generally, when groundwater elevations are higher than typical, the LNAPL thickness in monitoring wells will decrease or go to zero because the groundwater will redistribute any mobile LNAPL into what previously was the unsaturated zone. During lower groundwater elevation periods, much more of the LNAPL will occur as a continuous phase near the water table, leading to higher LNAPL thicknesses in wells.
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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).
  
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Overall, LNAPL thickness measurements are useful for delineating the extent of mobile LNAPL in the saturated zone and can provide useful data for understanding the vertical distribution of LNAPL in the formation<ref name="Hawthorne2011">Hawthorne, J.M., 2011. Diagnostic Gauge Plots—Simple Yet Powerful LCSM Tools. Applied NAPL Science Review (ANSR), 1(2). [http://naplansr.com/diagnostic-gauge-plots-volume-1-issue-2-february-2011/ Website] [[Media:Hawthorne2011.pdf | Report.pdf]]</ref><ref name="Kirkman2013">Kirkman, A.J., Adamski, M., and Hawthorne, M., 2013. Identification and Assessment of Confined and Perched LNAPL Conditions. Groundwater Monitoring and Remediation, 33 (1), pp. 75–86. [https://doi.org/10.1111/j.1745-6592.2012.01412.x  DOI:10.1111/j.1745-6592.2012.01412.x]</ref>. But LNAPL thickness by itself is a very poor indicator of the feasibility of LNAPL recovery<ref name="LNAPL-2">Interstate Technology and Regulatory Council (ITRC), 2009. Evaluating LNAPL Remedial Technologies for Achieving Project Goals. LNAPL-2. ITRC, LNAPLs Team, Washington, DC. www.itrcweb.org  [[Media:ITRC-LNAPL-2.pdf | Report.pdf]]</ref><ref name="Hawthorne2015"/> (see [[NAPL Mobility]]) (Figure 4). Because there is little correlation between apparent LNAPL thickness and LNAPL mobility, there is also little correlation between apparent thickness and the risk to receptors from the LNAPL.
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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.
  
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===Complete LNAPL Remediation Is Very Challenging===
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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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Sale et al. (2018) described the problems with attaining complete LNAPL remediation this way:
 
  
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<blockquote>''Experience of the last few decades has taught us: 1) our best efforts often leave some LNAPL in place, and 2) the remaining LNAPL often sustains exceedances of drinking water standards in release areas for extended periods. Entrapment of LNAPLs at residual saturations is a primary factor constraining our success. Other challenges include the low solubility of LNAPL, the complexity of the subsurface geologic environment, access limitations associated with surface structures, and concentration goals that are often three to five orders of magnitude less than typical initial concentrations within LNAPL zones.''<ref name="Sale2018"/></blockquote>
+
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.
  
−
In particular, the discontinuous residual LNAPL cannot be removed (or recovered) by pumping, and ''in situ'' remediation is expensive and not completely effective (see [[LNAPL Remediation Technologies]]).  However, many regulatory programs require “LNAPL recovery to the extent practicable.”  The lack of quantitative metrics and the lack of correlation between apparent LNAPL thicknesses and subsurface LNAPL makes this a problematic requirement in many cases and the ITRC (2018) cautions “Thickness or concentration data alone may not provide a sound basis for defining the point at which a cleanup objective is achieved.”<ref name="LNAPL-3"/>  However, Sale et al. (2018) describe metrics such as LNAPL transmissivity, limited/infrequent well thicknesses, decline curve analysis, asymptotic analysis, and comparison to NSZD rates that can be used to determine when LNAPL has been removed the extent practicable<ref name="Sale2018"/>.
+
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.  
  
−
===Attenuation Processes are Active and Important===
+
[[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.
−
Both LNAPL source zones and their dissolved phase hydrocarbon plumes are attenuated by biodegradation and other attenuation process. In the source zone, this attenuation is called [[Natural Source Zone Depletion (NSZD)]] (see also [[Natural Attenuation in Source Zone and Groundwater Plume - Bemidji Crude Oil Spill]]). In the dissolved plume it is called [[Monitored Natural Attenuation (MNA)]] (see also  [[Biodegradation - Hydrocarbons]]). These processes generally limit the length of dissolved phase hydrocarbon plumes to a few hundred feet<ref name="Newell1998">Newell, C.J., and Connor, J.A., 1998. Characteristics of Dissolved Hydrocarbon Plumes: Results from Four Studies, Version 1.1. American Petroleum Institute, Soil/Groundwater Technical Task Force, Washington, DC. [https://www.enviro.wiki/index.php?title=File:Newell-1998-chararacterization_of_dissolved_Pet._Hydro_Plumes.pdf  Report.pdf]</ref> via processes that have been well known and understood since the mid-1990s.
 
  
−
However, NSZD is “by far, the biggest new idea for LNAPLs in the last decade.”<ref name="Sale2018"/>  Originally, LNAPL bodies were thought to attenuate very slowly via dissolution and volatilization.  In 2006, it was discovered that NSZD rates are orders of magnitude higher than originally thought, largely due to direct biodegradation of LNAPL constituents to methane and carbon dioxide by methanogenic consortiums of naturally occurring bacteria<ref name="Lundegard2006">Lundegard, P.D., and Johnson, P.C., 2006. Source Zone Natural Attenuation at Petroleum Spill Sites—II: Application to a Former Oil Field. Groundwater Monitoring and Remediation. 26(4), pp. 93-106. [https://doi.org/10.1111/j.1745-6592.2006.00115.x  DOI: 10.1111/j.1745-6592.2006.00115.x]</ref><ref name="Garg2017">Garg, S., Newell, C., Kulkarni, P., King, D., Adamson, D.T., Irianni Renno, M., and Sale, T., 2017. Overview of Natural Source Zone Depletion: Processes, Controlling Factors, and Composition Change. Groundwater Monitoring and Remediation, 37(3), pp. 62-81.  [https://doi.org/10.1111/gwmr.12219 DOI:  10.1111/gwmr.12219] [[Media:Garg2017gwmr.12219.pdf | Report.pdf]]</ref>.  NSZD processes play an important role in risk mitigation and the long-term stability of LNAPL bodies<ref name="Mahler2012">
+
==Applications==
−
Mahler, N., Sale, T., and Lyverse, M., 2012. A Mass Balance Approach to Resolving LNAPL Stability. Groundwater, 50(6), pp 861-871.  [https://doi.org/10.1111/j.1745-6584.2012.00949.x DOI: 10.1111/j.1745-6584.2012.00949.x]</ref><ref name="LNAPL-3"/>.
+
[[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"/>.  
  
−
===Risk from LNAPL Source Zones Diminishes Over Time===
+
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"/>.  
−
At Early Stage LNAPL sites, the expansion of the LNAPL body is a risk that needs to be addressed. Fortunately, this type of site is relatively rare.  For Middle and Late Stage sites, the primary risks are associated with phase changes (dissolution of the LNAPL forming a dissolved plume and volatilization from the LNAPL or dissolved plume forming hydrocarbon vapors). As described above, MNA can often control the dissolved phase (see [[Monitored Natural Attenuation (MNA) of Fuels]]), while aerobic biodegradation in the unsaturated zone greatly reduces the vapor intrusion risk from hydrocarbon vapors (see [[Vapor Intrusion - Separation Distances from Petroleum Sources]]).
 
  
−
Understanding LNAPL body mobility and stability is important to understand the potential risks posed by LNAPL. The relative magnitude of LNAPL mobility can be determined by measuring the LNAPL transmissivity (see [[NAPL Mobility]]).  If the transmissivity is below a threshold level (in the range of 0.1 to 0.8 ft<sup>2</sup>/day) then the LNAPL likely cannot be recovered efficiently by pumping, but above this transmissivity level recovery is feasible<ref name="LNAPL-3"/>.  Michigan’s LNAPL guidance states “if the NAPL has a transmissivity greater than 0.5 ft<sup>2</sup>/day, it is likely that the NAPL can be recovered in a cost-effective and efficient manner unless a demonstration is made to show otherwise.”  Kansas LNAPL guidance requires “recovery of all LNAPL with a transmissivity greater than 0.8 ft<sup>2</sup>/day that can be recovered in an efficient, cost-effective manner.”<ref name="LNAPL-3"/>.  The stability of the entire LNAPL body can be evaluated using statistical tools to determine if migration of LNAPL is occurring<ref name="Hawthorne2013">Hawthorne, J.M., Stone, C.D., Helsel, D., 2013. LNAPL Body Stability Part 2: Daughter Plume Stability via Spatial Moments Analysis. Applied NAPL Science Review (ANSR), 3(5).  [http://naplansr.com/lnapl-body-stability-part-2-daughter-plume-stability-via-spatial-moments-analysis-volume-3-issue-5-september-2013/ Website] [[Media:Hawthorne2013.pdf | Report.pdf]]</ref>.
+
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"/>.
  
−
==Overview of Modern LNAPL Conceptual Site Model==
+
==Summary==
−
[[File:Newell1w2Fig5.png |thumb|500px| Figure 5.  A higher tier of LNAPL CSM is useful as LNAPL site complexity increases<ref name="LNAPL-3"/>.]]
+
OPTICS provides:
−
The ITRC (2018) describes the typical evolution of an LCSM over the course of the remediation process which can be broken into three separate stages:
+
*High resolution surface water chemical contaminant characterization
−
* An ''Initial LCSM'' focuses on identifying the LNAPL concerns, such as a risk to health or safety, any LNAPL migration, LNAPL-specific regulations, and physical or aesthetic impacts.
+
*Cost-effective monitoring and assessment
−
* A ''Remedy Selection LCSM'' supports remedial technology evaluation by characterizing aspects of the LNAPL and site subsurface that may impact remedial technology performance.
+
*Versatile and modular monitoring with capability for real-time telemetry
−
* A ''Design and Performance LCSM'' focuses on presenting the technical information needed to establish remediation objectives, design and implement remedies or control measures, and track progress toward defined remediation endpoints.
+
*Data necessary for development and validation of conceptual site models
 +
*A key line of evidence for designing and evaluating remedies.
  
−
One key question when developing an LCSM is “how much data is enough.”  In general, the answer is that the existing data is sufficient for the current stage of the remediation project when it allows the stakeholders to agree on a path forward<ref name="LNAPL-3"/>. Figure 5 shows that as the level of complexity of a site increases, a higher tier of LCSM is useful to provide enough information for making decisions<ref name="LNAPL-3"/><ref name="ASTM2014a"/>. The higher tier of information could be higher data density, additional tools for a given line of evidence, or other evaluations.
+
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.  
−
 
 
−
==LNAPL Concerns, Remediation Goals and Objectives==
 
−
Finally, the ITRC (2018) provides a methodology for identifying LNAPL concerns, verifying those concerns, selecting LNAPL remediation goals, and determining LNAPL remediation objectives.  Examples of each of these concepts are provided below:
 
−
 
 
−
* '''Potential Concerns:'''  Human or ecological risk concerns, fire or explosivity issues, LNAPL migration, LNAPL-specific regulatory concerns, other concerns such as odors or geotechnical issues.
 
−
* '''Verifying Concerns:'''  Measure LNAPL transmissivity to determine if it is recoverable; measure vertical and horizontal separation distances between buildings and LNAPL bodies to screen for vapor intrusion concerns.
 
−
* '''Remediation Goals:'''  Reduce mobile LNAPL saturation, abate unacceptable soil concentrations, terminate LNAPL body migration, abate unacceptable constituent concentrations in dissolved and vapor phases.
 
−
* '''Remediation Objectives:'''  Recover LNAPL to the extent practicable based on transmissivity, reduce soil concentrations to below regulatory limits, stop LNAPL migration with a barrier, contain migrating groundwater plume (if present), reduce groundwater and vapor concentration to acceptable levels.
 
−
* '''Remediation Technologies:'''  LNAPL Mass Recovery technologies, LNAPL phase change technologies, LNAPL Mass Control technologies, combinations of technologies.
 
−
 
 
−
Overall, a LNAPL Conceptual Site Model that integrates key site specific information and current technical knowledge about LNAPL sites in general is instrumental to successful site management, where LNAPL concerns drive remediation goals, goals drive remediation objectives, and the objectives form the basis for the selection of remediation technologies.  
 
  
 
==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

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