Welcome to the Concawe LNAPL Toolbox
The toolbox can be accessed via:
More information about the Toolbox is found under the Toolbox Overview in the menu above.
Concawe was established as CONCAWE (CONservation of Clean Air and Water in Europe) in 1963 by a small group of leading oil companies to carry out research on environmental issues relevant to the petroleum refining industry. Its membership has broadened and currently includes most oil companies operating in EU-28, Norway and Switzerland, representing approximately 95% of petroleum refining capacity in those countries. In 2014, it became the Scientific Division of the European Fuel Manufacturers Association.
Read more on the Concawe website
Concawe organisation contact information
Gustavo Guerrero-Limón (Science Associate Water, Soil & Waste)
Eleni Vaiopoulou (Science Executive Water, Soil & Waste)
Source: ITRC LNAPL Training
User Manual for Concawe
LNAPL Toolbox
Concawe Soil Groundwater Taskforce (STF-33) |
GSI Environmental Team |
---|---|
Markus Hjort, MSc | Brian Strasert, P.E. |
Eleni Vaiopoulou, PhD | Charles Newell, Ph.D., P.E. |
Patrick Eyraud | Phil de Blanc, Ph.D., P.E. |
Tim Greaves | Poonam Kulkarni, P.E. |
Wayne Jones | Kenia Whitehead, Ph.D. |
Thomas Grosjean | Brandon Sackmann, Ph.D. |
Andrew Kirkman | Hannah Podzorski |
Jonathan Smith, Prof. | |
Richard Gill, PhD. | |
Jose Miguél Martinez Carmona | |
Peter Discart |
CL:AIRE. 2017. “Petroleum Hydrocarbons in Groundwater: Guidance on Assessing Petroleum Hydrocarbons Using Existing Hydrogeological Risk Assessment Methodologies.” London.: CL:AIRE. http://www.claire.co.uk/phg.
Concawe, 2003. European oil industry guideline for risk-based assessment of contaminated sites. CONCAWE Water Quality Management Group by its Special Task Force (WQ/STF-27), Crawford, R.L., Alcock, J., J. Couvreur, M. Dunk, C. Fombarlet,O. Frieyro, G. Lethbridge, T. Mitchell, M. Molinari, H. Ruiz, and T. Walden http://files.gamta.lt/aaa/Tipk/tipk/4_kiti%20GPGB/45.pdf
Concawe, 2020. “Detailed Evaluation of Natural Source Zone Depletion at a Paved Former Petrol Station” Concawe Report no. 13/20. https://www.concawe.eu/publication/detailed-evaluation-of-natural-source-zone-depletion-at-a-paved-former-petrol-station/
CRC Care, 2018. Technical measurement guidance for LNAPL natural source zone depletion. CRC Care Technical Report 18. https://www.crccare.com/files/dmfile/CRCCARETechnicalreport44_TechnicalmeasurementguidanceforLNAPLnaturalsourcezonedepletion.pdf
Farhat, S K, T M McHugh, and P C De Blanc. 2019. “LNAPL Remediation Technologies.” Enviro Wki. https://www.enviro.wiki/index.php?title=Main_Page: SERD/ESTCP. 2019. https://www.enviro.wiki/index.php?title=Main_Page.
Garg, Sanjay, Charles J. Newell, Poonam R. Kulkarni, David C. King, David T. Adamson, Maria Irianni Renno, and Tom Sale. 2017. “Overview of Natural Source Zone Depletion: Processes, Controlling Factors, and Composition Change.” Groundwater Monitoring and Remediation 37 (3): 62–81. Open Access.https://ngwa.onlinelibrary.wiley.com/doi/full/10.1111/gwmr.12219
Interstate Technology & Regulatory Council (IRTC). 2018. “LNAPL Site Management: LCSM Evolution, Decision Process, and Remedial Technologies (LNAPL-3).” Interstate Technology and Regulatory Council. https://lnapl-3.itrcweb.org
ITRC, 2014. “LNAPL Training Part 1: An Improved Understanding of LNAPL Behavior in the Subsurface".
Lari, S. Kaveh, Greg B Davis, John L Rayner, Trevor P Bastow, and Geoffrey J Puzon. 2019. “Natural Source Zone Depletion of LNAPL: A Critical Review Supporting Modelling Approaches.” Water Research 157: 630–46. Open Access. https://www.sciencedirect.com/science/article/pii/S0043135419302994
LNAPL Workgroup, LA. 2015. “LA Basin LNAPL Recoverability Study.” Los Angeles LNAPL Workgroup. www.gsi-net.com.
NAVFAC. 2017. “New Developments in LNAPL Site Management.” Environmental Restoration. https://frtr.gov/matrix/documents/Free-Product-Recovery/2017-Environmental-Restoration-New-Developments-in-LNAPL-Site-Management.pdf
Sale, Thomas C., H Hopkins, and A Kirkman. 2018. “Managing Risk at LNAPL Sites Frequently Asked Questions.” American Petroleum Institute Tech Bulletin. 2nd Edition. Vol. API Soil a. Washington, DC: American Petroleum Institute. https://www.api.org/oil-and-natural-gas/environment/clean-water/ground-water/lnapl/lnapl-faqs.
Smith, J. J., Benede, E., Beuthe, B., Marti, M., Lopez, A. S., Koons, B. W., Kirkman, A. J., Barreales, L. A., Grosjean, T., & Hjort, M. 2021. A Comparison of Three Methods to Assess Natural Source
USEPA, 2016: LNAPL Links to Additional Resources, U.S. Environmental Protection Agency. https://clu-in.org/conf/itrc/iuLNAPL/resource.cfm
Source: ITRC LNAPL Training
If a well has this much LNAPL: | |||
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0.1 metre | 0.3 metre | 1 metre | |
Soil Type | This much LNAPL is in the formation (m3/m2): | ||
Silty Clay | 0.000041 | 0.00039 | 0.0045 |
Silt | 0.00020 | 0.0028 | 0.040 |
Loam | 0.00034 | 0.0058 | 0.084 |
Sand | 0.0025 | 0.059 | 0.32 |
Table developed for Concawe Toolbox 2020 using LNAPL tool developed by
de Blanc, P. and S. K. Farhat, 2018. 25th IPEC: International Petroleum
Environmental Conference October 30 – November 1, 2018. Denver, Colorado.
Learn more about soil classification systems
This tool calculates several key LNAPL values, including specific volume, recoverable volume, and transmissivity, at multiple locations for multiple layers of differing soil types. These values are used to calculate a total subsurface LNAPL volume. Based on LNAPL gradients specified by the user, estimated LNAPL velocities are also calculated. The distribution of calculated values is depicted graphically.
The model is based on an extension of the methodology of the API’s LDRM (Charbeneau, 2007). The user enters data into three different input databases: 1) a soil parameter input database, 2) a well coordinate and fluid level gauging input database, and 3) a stratigraphy input database. The model determines the layers in which LNAPL is present, then calculates specific volume and other LNAPL parameters for the layered system. An area-weighted average of the specific volume is calculated to arrive at a total LNAPL volume.
To improve the site-wide LNAPL volume calculations, it is important to include nearby monitoring wells that do not have any apparent LNAPL thickness in the monitoring well database. This will help establish a “clean line” around the LNAPL body and prevent extrapolation errors.
If you are just calculating the LNAPL volume in only a portion of an LNAPL body, use the polygon tool in the map to the right.
Guidance on the selection of specific input parameters for this tool is provided in Section 4.2 of the User’s Manual which can be seen here:
More general guidance on parameters can be found in the API’s Parameter Selection Guide which can be downloaded here:
The model assumes that the LNAPL is in hydrostatic equilibrium with the surrounding media. Relative permeability is calculated by combining the Mualum model with the van Genuchten soil characteristic curve parameters (Charbeneau, 2007). The f-factor must be a positive value less than 1. Empirically-determined values range from 0.2 to 0.5, with a recommended median of 0.3 (Charbeneau and Beckett, 2007).
This LNAPL tool, sometimes referred to as the de Blanc LNAPL Model, was developed by Dr. Phil de Blanc and Dr. Shahla Farhat of GSI Environmental, Houston, Texas.
Charbeneau, 2007. LNAPL Distribution and Recovery Model (LDRM) Volume 1: Distribution and Recovery of Petroleum Hydrocarbon Liquids in Porous Media, Randall J. Charbeneau, American Petroleum Institute.
de Blanc, P.C. and S. K. Farhat, 2018. New Tool for Determining LNAPL Volume and Extent. GSI Environmental Inc. 25th International Petroleum Environmental Conference, October 30 – November 1, 2018, Denver, Colorado.
Note: If extreme values are entered, model may crash and the website will have to be reloaded.
There are assumptions that the app makes for how stratigraphy profiles should be entered and the model may fail if the input does not meet these conditions. These assumptions are:
To refine the area of interpolation use the draw tools in the upper left-hand corner to draw the area you want to interpolate over. To remove the shape and reset the map click 'Calculate' again. At least 3 wells must be present for interpolation.
For more information, or to learn how to perform your own interpolation, go to this tutorial.
Information on this page can be downloaded using the button at the bottom of the page.
While the Concawe Toolbox includes the Tier 2 LNAPL Volume and Extent Model (de Blanc and Farhat, 2018) for evaluating how much LNAPL is present, another option is to apply the API LDRM Tool. These two tools can be found here:
“The API LNAPL Distribution and Recovery Model (LDRM) simulates the performance of proven hydraulic technologies for recovering free-product petroleum liquid releases to groundwater. Model scenarios included in the LDRM are hydrocarbon liquid recovery using: single- and dual-pump well systems, skimmer wells, vacuum-enhanced well systems, and trenches. The LDRM provides information about LNAPL distribution in porous media and allows the user to estimate LNAPL recovery rates, volumes and times.” “The Guide has been designed to meet the needs of very busy professionals. As such, the primers and tools can be utilized within 15 to 25 minutes so that information can be gained rapidly. A list of references is also provided to enable more detailed understanding.” (API web page).
In general, the LDRM is a very powerful tool to simulate multiphase flow behavior that controls LNAPL recovery. To run LDRM, it is helpful to have an understanding of capillary pressure relationships (e.g., van Genuchten relationship; van Genuchten, 1980), LNAPL residual saturation concepts such as the f-factor, and the design of LNAPL recovery systems.
A short video describing LDRM can be viewed here.
Images reproduced courtesy of the American Petroleum Institute from “LNAPL Distribution and Recovery Model (LDRM) Volume 2: User and Parameter Selection Guide”, API Publication 4760, January 2014
Images reproduced courtesy of the American Petroleum Institute from LNAPL Distribution and Recovery Model, version 2.0, January 2007
Examples of the LNAPL recovery and LNAPL transmissivity graphics are shown below.
ITRC LNAPL Training Part 2: LNAPL Characterization and Recoverability – Improved Analysis, 2016.
This tool calculates the additional distance that the leading edge of an existing LNAPL plume is expected to migrate until it eventually stabilizes in the presence of natural source zone depletion (NSZD). To run the model you need to know three things about your LNAPL body: 1) a representative LNAPL transmissivity from bail down tests or from transmissivities calculated using the “LNAPL Volume Tier 2 Tool; 2) the measured LNAPL body gradient (the slope of the LNAPL body surface); and 3) the current LNAPL body radius (the model makes a simplifying assumption that the LNAPL body is circular).
The model is based on multiple runs of the Hydrocarbon Spill Screening Model (HSSM; Weaver et al., 1994). For each run, an average LNAPL transmissivity (Tn) and gradient (i) were calculated across the oil lens at different times and for different soil types. These average properties were used as starting conditions to calculate the expected additional growth of an LNAPL body under one of five different NSZD rates using the steady-state relationship for a circular source derived by Mahler (Mahler et al., 2012)
The plot shows the calculated LNAPL body length increase for different average values of LNAPL transmissivity × gradient and piecewise linear fit to the data in the nomograph.
To use the model, enter the current LNAPL transmissivity (in m2/d) (see the bottom of the Tier 3 LNAPL Recovery tab), enter the LNAPL gradient (see Section 5.2.1.4 of the User Manual for a description), and select one of five different representative NSZD rates (see Tier 1 of the NSZD Estimation tab). The estimated additional LNAPL body growth from now will be automatically calculated. The model is a screening level model and will only give a general indication of the potential increase of the LNAPL body, but it will likely be more accurate than older models, such as HSSM, which do not account for NSZD processes.
The model assumes that there is an unlimited source of LNAPL and that the LNAPL flux is constant. This is an experimental model. Incorporation of HSSM (Weaver et al., 1994) and Mahler et al. (2012) represents a non-hysteric methodology where entrapment of LNAPL is ignored and loss rate inputs can account for partitioning and biodegradation losses.
Entrapment of LNAPL has been evaluated (Sookhak Lari et al., 2016; Pasha et al., 2014; Guarnaccia et al., 1997) and demonstrated to slow the rate of LNAPL migration. Current methods to incorporate entrapment require numerical models which are not within the scope of this tool. The lack of incorporating entrapment results in a conservative approach where the upper bound of LNAPL migration extent is estimated. The results of this tool are intended to be used for demonstrating LNAPL body stability by comparing the maximum potential for LNAPL migration to current extent.
The model is useful for estimating the upper bound of LNAPL migration. However, if the calculated LNAPL extent is used in cumulative LNAPL loss and time to depletion estimates then the resulting estimates would overestimate losses and underestimate time to depletion (Sookhak Lari et al., 2016). It is appropriate to use current delineated LNAPL body extent for cumulative loss calculations or time to depletion estimates.
Guidance on the selection of specific input parameters for this tool is provided in Section 5.2.1 of the User’s Manual which can be seen here:
This LNAPL tool, referred to as the Kirkman LNAPL Body Additional Migration Tool, was developed by Andrew Kirkman of BP.
Guarnaccia, J. , Pinder, G. , Fishman, M. , 1997. NAPL: Simulator Documentation, US EPA.
Kirkman, A., 2021. LNAPL Body Additional Migration Tool. Andrew Kirkman, BP. Programmed by GSI Environmental.
Mahler et al., 2012. A mass balance approach to resolving LNAPL stability, N. Mahler, T. Sale, and M. Lyverse, Ground Water 50(6): 861-571, November/December 2012.
Pasha, A.Y. , Hu, L. , Meegoda, J.N. , 2014. Numerical simulation of a light nonaqueous phase liquid (LNAPL) movement in variably saturated soils with capillary hysteresis, Can. Geotech. J. 51, 1046–1062.
Sookhak Lari, K. , Davis, G.B. , Johnston, C.D. , 2016 Incorporating hysteresis in a multi-phase multi-component NAPL modelling framework; a multi-component LNAPL gasoline example, Advances in Water Resources. 96, 190-201.
Weaver et al., 1994. The Hydrocarbon Spill Screening Model (HSSM); Volume 1: User’s Guide, J.W. Weaver, R.J. Charbeneau, B.K. Lien, and J.B. Provost, U.S. EPA, EPA/600/R-94/039a.
Methods developed by Mahler et al. (2012) illustrate that natural losses of LNAPL (e.g., NSZD) can play an important role in governing the overall extent of LNAPL bodies. This module calculates the overall length of a contiguous LNAPL body, given an inflow of LNAPL rate, NSZD rate, and time period.
The user is able to select a Long-Term LNAPL Release Rate, NSZD Rate, and a Time Period of Model. The output is an estimated ultimate LNAPL body length.
A limitation of the current methodology is the assumption of constant inflow of LNAPL throughout the entire lifetime of the LNAPL Body. Given either the reduction or termination of an LNAPL body, the times for stabilization and LNAPL body length could be much shorter. Additionally, LNAPL migration is not a function of the slope of the water table. Finally, the tool is limited to three different selections for the Long-term LNAPL Release Rate, three different selections for NSZD Rate, and three different selections for Time Period.
Guidance on the selection of specific input parameters for this tool is provided in Section 5.2.2 of the User’s Manual which can be seen here:
This LNAPL tool was derived from the work of Mahler et al., 2012 by Poonam Kulkarni, GSI Environmental.
Kulkarni, P., 2021. LNAPL Migration Calculator based on Mahler et al. Model. Concawe LNAPL Toolbox.
Mahler, N., Sale, T., Lyverse, M., 2012. A Mass Balance Approach to Resolving LNAPL Stability. Groundwater 50, 861–871.
Information on this page can be downloaded using the button at the bottom of the page.
The Concawe Toolbox includes a new Tool developed by Andrew Kirkman based on LNAPL mass limitations included in the HSSM conceptual model integrated with LNAPL transmissivity relationships and LNAPL removal via Natural Source Zone Depletion (NSZD) using the Mahler et al. (2012) model. This Tier 3 section provides additional information about HSSM and UTCHEM, two tools that can be used to answer the question “How far will the LNAPL migrate?” The 2012 paper by Mahler et al. (2012) presents important findings on how NSZD limits LNAPL migration. Finally, an emerging LNAPL modeling method being developed by GSI’s Dr. Sorab Panday is a promising new approach where LNAPL modeling can be performed using a commonly used groundwater model like MODFLOW.
LNAPL body stabilization figure from Mahler et al. (2012). Each contour line is either 40 years (for panels a, b, c), 20 years (panels d, e, f), or 10 years (panels g, h, and i). (Reprinted with Permission)
Appendix 3 of the HSSM User’s Guide (Weaver et al., 1994) lists key input data and provides support for parameter estimation. Key parameters with example values are reproduced below:
Users select one of three general release scenarios to the unsaturated zone and enter either an LNAPL flowrate over a certain time period, a volume of LNAPL released over a certain area, or a constant head of LNAPL in an impoundment.
Example output is shown below (Weaver et al., 1994).
The UTCHEM Users Guide provides this list of processes. For each process there are required input data. The overall list of potential input data is determined by the nature of the UTCHEM simulation.
An example problem in the GMS Tutorials Document (Aquaveo, 2021) outlines this process:
Aquaveo, 2021. GMS Tutorials UTCHEM. Downloaded Feb. 2021.
EST, Aqui-Ver, 2006. API Interactive LNAPL Guide. American Petroleum Institute.
Panday, S., P. de Blanc, and R. Falta, in review. Simulation of LNAPL flow in the vadose zone using a single-phase flow equation. Submitted to Groundwater, in review (Feb. 2021).
University of Texas, 2000a. Volume I: User’s Guide for UTCHEM-9.0.
University of Texas, 2000b. Volume II: Technical Documentation for UTCHEM-9.0.
This simple LNAPL lifetime calculator shows two different models of how Natural Source Zone Depletion (NSZD) will remove LNAPL over time.
Kulkarni, P., 2021. LNAPL Body Lifetime Calculator, Concawe LNAPL Toolbox.
Newell, C.J., D.T. Adamson, 2005. Planning-Level Source Decay Models to Evaluate Impact of Source Depletion on Remediation Timeframe. Remediation 15.
Newell, C.J., Gonzales, J., McLeod, R. , 1996. BIOSCREEN Natural Attenuation Decision Support System. U.S. Environmental Protection Agency. (https://www.gsi-net.com/en/software/free-software/bioscreen.html)
Garg, S., C. Newell, P. Kulkarni, D. King, M. Irianni Renno, and T. Sale, 2017. Overview of Natural Source Zone Depletion: Processes, Controlling Factors, and Composition Change. Groundwater Monitoring and Remediation 37. (open access; https://ngwa.onlinelibrary.wiley.com/doi/full/10.1111/gwmr.12219).
Information on this page can be downloaded using the button at the bottom of the page.
A simple box model is provided in Tier 2 and provides a range of time required for the LNAPL to be removed by Natural Source Zone Depletion (NSZD). Users enter the estimated mass/volume of LNAPL present and the estimated NSZD rate.
Two more sophisticated computer tools that can be used to estimate how long the LNAPL might persist at a site are REMFuel (Falta et al., 2012) and LNAST (Huntley and Beckett, 2002). A short summary of each model is provided below:
Key input data are shown below. One key feature is that the plume produced by the source can be broken up into nine “space-time” domains with three separate time periods and three separate spatial zones. For example, the first third of the plume downgradient from a 40-year-old source can have its own first order decay coefficients for three separate time periods, such as a 20-year natural attenuation period, then a 5-year plume remediation period, then a 15-year post-remediation natural attenuation period.
While much of the input data below is commonly collected during site characterization activities (e.g., Darcy groundwater velocity, source width/height/length, porosity) the source zone gamma term may be unfamiliar to many users. Basically, gamma defines the relationship between mass flux leaving the source and the remaining mass in the source at any time. For example:
In this example, source remediation and plume remediation were performed, leading to the spikey concentration vs. distance curves in the 2021 panel (see the REMFuel video for a more detailed explanation). Note that the Y-axis is log-scale.
Images reproduced courtesy of the American Petroleum Institute from LNAPL Dissolution and Transport Screening Tool, version 2.0.4, February 2006
To use LNAST, the user first indicates the information desired from the tool:
The tool then takes the user through a series of eight input screens to define soil properties, groundwater conditions, source area parameters, LNAPL properties, and solute transport.
Images reproduced courtesy of the American Petroleum Institute from LNAPL Dissolution and Transport Screening Tool, version 2.0.4, February 2006
After performing the selected calculations, LNAST allows users to display results to the screen, create a report, or export the results.
An example of key output for LNAPL recovery in a trench is shown below:
This model calculates the theoretical concentration of dissolved hydrocarbons in groundwater downgradient of an LNAPL source over time due to dissolution processes. The model produces a graph of dissolved constituent (such as B,T,E, X and MTBE) in groundwater over time in units of mg/L as an LNAPL source is depleted of these soluble constituents.
A known volume of LNAPL is released to the subsurface. The LNAPL is comprised of several components whose volume fractions and densities are known. The unidentified fraction of the LNAPL is a mixed petroleum product with unknown components, but with a known average molecular weight and density.
The LNAPL establishes a lens in the groundwater with a known width and average thickness. Groundwater flows through the LNAPL lens and dissolves the LNAPL constituents, reducing the remaining volume of LNAPL and changing its composition as the more soluble compounds dissolve out of the LNAPL. Equilibrium between the water and LNAPL within the lens is assumed, so that the concentration of constituents downgradient of the LNAPL are equal to the effective solubility of the LNAPL constituents. Effective solubility is the solubility of a pure phase component times its mole fraction in the LNAPL.
The key strengths of the model are:
Weakness of the model are:
Key assumptions of the model are as follows:
Many laboratory analysis of LNAPL show composition as mass concentrations (mg/L). To convert a mass concentration of a constituent like benzene to a volume fraction, you will need to divide the mg/L value by the density of the constituent (78,000 mg per gram-mole for benzene). So 1 mg/L benzene concentration in LNAPL becomes a volume fraction of 1.3x10-5 Liters benzene per Liter of LNAPL (unitless).
Guidance on the selection of specific input parameters for this tool is provided in Section 7.2 of the User’s Manual which can be seen here:
This LNAPL tool was developed by Dr. Phil de Blanc, GSI Environmental.
de Blanc, P., 2021. LNAPL Dissolution Calculator, Concawe LNAPL Toolbox.
Information on this page can be downloaded using the button at the bottom of the page.
The risk posed by the toxic components of an LNAPL plume is a function of the constituents’ concentration in groundwater in contact with the LNAPL. A multi-component LNAPL dissolution model based on the LNAPL constituent mole fraction and Raoult’s law (Mayer and Hassanizadeh, 2005) is provided in Tier 2 and shows how the dissolved constituent concentrations immediately downgradient of an LNAPL body change over time.
A more sophisticated computer tool, API’s LNAST model, also shows the change in dissolved phase LNAPL concentrations over time (Huntley and Beckett, 2002). It is summarized below. Finally, two other key LNAPL attenuation studies, a LNAPL mass balance developed by Ng et al. (2014) and a 2003 report about weathering of jet fuel LNAPL, are also reviewed below.
A short video to learn more about LNAST can be found here.
Images reproduced courtesy of the American Petroleum Institute from LNAPL Dissolution and Transport Screening Tool, version 2.0.4, February 2006
To use LNAST, the user first indicates the information desired from the tool:
The tool then takes the user through a series of eight input screens to define soil properties, groundwater conditions, source area parameters, LNAPL properties, and solute transport.
Images reproduced courtesy of the American Petroleum Institute from LNAPL Dissolution and Transport Screening Tool, version 2.0.4, February 2006
After performing the selected calculations, LNAST allows users to display results to the screen, create a report, or export the results.
An example of key output for LNAPL recovery in a trench is shown below:
This tool calculates the following variables that indicate LNAPL volume and mobility at a single location for a single soil type: LNAPL specific volume, transmissivity, and Darcy flux. LNAPL transmissivity is the product of the average LNAPL hydraulic conductivity times the thickness of the LNAPL lens. Large transmissivity values indicate that LNAPL has greater potential to move through the subsurface than small values and suggests that LNAPL may be more easily mobilized or recovered. Transmissivity is often used as an indication of when LNAPL recovery is no longer practical.
The model is based on the methodology of the API’s LDRM (Charbeneau, 2007). The user enters parameters for the soil type, fluid properties, and the thickness of LNAPL observed in a monitoring well. LNAPL saturations are computed over the LNAPL thickness to calculate specific volume. Transmissivity is then calculated by integrating the saturation-dependent relative permeability over the LNAPL thickness. The product of the average relative permeability and the saturated hydraulic conductivity for the LNAPL is the LNAPL transmissivity. The transmissivity divided by the LNAPL thickness, then multiplied by the LNAPL gradient (see Section 5.2.1.4 of the User Manual for a description) is the LNAPL Darcy flux (volume of LNAPL per unit area of formation). The model uses an “f-factor” approach in which the LNAPL residual saturation is a function of the LNAPL thickness across the lens (Charbeneau, 2007).
Based on guidance from ITRC (2018) the key threshold for LNAPL recovery is the LNAPL transmissivity has to be higher than this general range of numbers: 0.0093 to 0.074 m2/day . If the calculated or measured LNAPL transmissivity is below that the lowest value, then there is a high probability that LNAPL hydraulic recovery will not to be cost effective or efficient. If above the highest number, then hydraulic recovery has a much higher likelihood of being feasible. Wells exhibiting LNAPL transmissivity values within this range are likely dominated by residual LNAPL. These values account for multiple soil and LNAPL types (ITRC, 2018).
The model assumes that the LNAPL is in hydrostatic equilibrium with the surrounding media. Relative permeability is calculated by combining the Mualum model with the van Genuchten soil characteristic curve parameters (Charbeneau, 2007).
The model uses default values for various soil and LNAPL properties. Soil properties can be found in Carsel and Parrish (1988), and LNAPL properties can be found in Mercer and Cohen (1990) and Charbeneau (2003).
Guidance on the selection of specific input parameters for this tool is provided in Section 8.2.3 of the User’s Manual which can be seen here:
This LNAPL tool was developed by Dr. Phil de Blanc, GSI Environmental.
Carsel, R.F., and R.S. Parrish. 1988. Developing joint probability distributions of soil water retention characteristics. Water Resour. Res. 24:755-769.
Charbeneau, R. 2003. Models for Design of Free-Product Recovery Systems for Petroleum Hydrocarbon Liquids. American Petroleum Institute.
Charbeneau, R., 2007. LNAPL Distribution and Recovery Model (LDRM) Volume 1: Distribution and Recovery of Petroleum Hydrocarbon Liquids in Porous Media. Volume 2: User and Parameter Selection Guide. American Petroleum Institute.
de Blanc, P., 2021. LNAPL Transmissivity Calculator, Concawe LNAPL Toolbox.
Mercer, J.W. and Cohen, R.M. 1990. A review of immiscible fluids in the subsurface: properties, models, characterization and remediation, Journal of Contaminant Hydrology, v6:107-163.
Information on this page can be downloaded using the button at the bottom of the page.
LNAPL Conceptual Site Model (LCSM): “The LCSM is the collection of information that incorporates key attributes of the LNAPL body with site setting and hydrogeology to support site assessment and corrective action decision-making. The LCSM integrates information and considerations specific to the LNAPL body relating to the risks of the contaminant source, exposure pathways, and receptors. The content of the LCSM will typically evolve over time as different phases of the corrective action process require different information. What remains consistent is the emphasis in the LCSM on characterizing and understanding the source component, the LNAPL.” (ITRC, 2018). At sites where LNAPL recovery is the key remediation question, the LSCM can be refined and improved by using computer models and/or LNAPL transmissivity to better understand the potential for LNAPL recovery.
Computer Models: Several computer models are available to help understand if LNAPL can be recovered effectively:
Videos: Short videos are available to learn more about each of these computer models:
LNAPL Transmissivity : More recently there has a been a move to use LNAPL transmissivity as a key metric to evaluate LNAPL recoverability (e.g., ITRC, 2018). The ITRC’s “Top Three Things To Know about LNAPL Transmissivity” is reproduced to the right.
The use of transmissivity has been catalyzed by a general consensus that hydraulic recovery of LNAPL (skimmer wells, trenches, groundwater pumping, etc.) has a Technology Threshold Metric consisting of LNAPL transmissivity greater than 0.1 to 0.8 ft2/day (0.0093 to 0.074 m2/day). This metric may be used as a decision point for remedial system operation or technology transitions (ITRC, 2018). For example, in the State of Michigan, LNAPL guidance states “if the NAPL has a transmissivity greater than 0.5 ft2/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.” (ITRC, 2018). ITRC also describes five sites in detail that were used as the basis of this range (Section 1.3).
LNAPL transmissivity can be determined in two general ways:
ASTM. 2013. Standard Guide for Estimation of LNAPL Transmissivity. ASTM International.
Lundegard, Paul D., and Paul C. Johnson, 2006. Source Zone Natural Attenuation at Petroleum Hydrocarbon Spill Sites - II: Application to a Former Oil Field. Ground Water Monitoring and Remediation 26 (4): 93–106. https://doi.org/10.1111/j.1745-6592.2006.00115.x.
NSZD rates are typically reported in units of volume of LNAPL biodegraded per area per time, such as “gallons per acre per year” in some of the NSZD projects performed in the United States. This model converts typical measures of NSZD rates between metric and imperial, as well as converting from carbon dioxide flux to mass or volume of LNAPL degraded per area per time (ex. Liters of LNAPL biodegraded per hectare per year).
The user is able to select an LNAPL type or representative compound, enter an NSZD value and select starting units, and select a final desired unit of mass or volume of LNAPL degradation.
For converting from a carbon dioxide flux in units of µmol/m2/sec to an LNAPL volume or mass per area per time, the table below summarizes densities and molecular weights applied for each LNAPL type or representative compound. Note that default parameters apply the density of fresh gasoline (0.77 g/mL), and the molecular weight of octane (114.2 g/mol).
Guidance on the selection of specific input parameters for this tool is provided in Section 9.2.1 of the User’s Manual which can be seen here:'
This LNAPL tool was developed by Poonam Kulkarni of GSI Environmental.
Kulkarni, P., 2021. NSZD Rate Converter, Concawe LNAPL Toolbox.
Hydrocarbon degradation can be enhanced with increases in temperature (Sustained Thermally Enhanced LNAPL Attenuation [STELA]) (Zeman et al., 2014; Kulkarni et al., 2017). This model uses the Arrhenius Law to estimate the potential NSZD rate enhancement with any externally created temperature increase up to 45 °C.
Arrhenius Law estimates for most biological systems, the temperature coefficient is 2.0 (i.e., rates will double with a 10 °C increase in temperature) (Atlas and Bartha 1986; Riser-Roberts 1992).
Q10 = R2/R1[10/(T2-T1)]
Where
Q10 = temperature coefficient, typically 2.0
R1 = NSZD Rate at temperature T1
R2 = NSZD Rate at temperature T2
T1 = Initial temperature (°C)
T2 = Final temperature (°C)
For mesophilic anaerobic digestors, optimum temperature range between 30 and 38 °C (Metcalf and Eddy, 1991; Gerardi, 2003). Maximum temperature approximated to be 40 °C, after which bacterial populations decline.
Guidance on the selection of specific input parameters for this tool is provided in Section 9.2.2 of the User’s Manual which can be seen here:
This LNAPL tool was developed by Poonam Kulkarni of GSI Environmental.
Atlas, R.M. , and R. Bartha. 1986. Microbial Ecology: Fundamentals and Applications. Menlo Park, California : Benjamin- Cummings.
Kulkarni, P., 2021. NSZD Temperature Enhancement Calculator, Concawe LNAPL Toolbox.
Gerardi, M.H. 2003. The Microbiology of Anaerobic Digesters. Hoboken, New Jersey : John Wiley & Sons.
Metcalf and Eddy. 1991. Wastewater Engineering—Treatment, Disposal, and Reuse. 3rd ed. New York: McGraw-Hill Publishing Company.
Kulkarni, P.R., King, D.C., McHugh, T.E., Adamson, D.T., Newell, C.J., 2017. Impact of Temperature on Groundwater Source Attenuation Rates at Hydrocarbon Sites. Groundwater Monitoring & Remediation, 37(3): 82-93.
Riser-Roberts, E. 1992. Bioremediation of Petroleum Contaminated Sites. Boca Raton, Florida : CRC Press Inc.
Zeman, N.R. , M.I. Renno , M.R. Olson , L.P. Wilson , T.C. Sale , and S.K. De Long . 2014. Temperature impacts on anaerobic biotransformation of LNAPL and concurrent shifts in microbial community structure. Biodegradation 25: 569–585.
Information on this page can be downloaded using the button at the bottom of the page.
Natural Source Zone Depletion (NSZD) has emerged as an important new remediation alternative for LNAPL sites. Key references and a description of what they explain about NSZD are provided below:
Two videos were developed for the NSZD article in the ESTCP Environmental Wiki. They can be viewed here:
The following table from Garg et al. (2017) summarizes measured NSZD rates at various hydrocarbon sites in the U.S. The middle 50% of the NSZD rates range from 700 – 2,800 gallons per acre per year.
Hydrocarbon degradation can be enhanced with increase in temperature (Sustained Thermally Enhanced LNAPL Attenuation [STELA]) (Zeman et al., 2014; Kulkarni et al., 2017). Specifically, the Arrhenius Law can be used to estimate the potential NSZD rate enhancement with any externally created temperature increase up to 45°C. The Arrhenius Law estimates for most biological systems, the temperature coefficient is 2.0 (i.e., rates will double with a 10°C increase in temperature) (Atlas and Bartha 1986; Riser-Roberts 1992).
Atlas, R.M. , and R. Bartha. 1986. Microbial Ecology: Fundamentals and Applications . Menlo Park, California : Benjamin- Cummings.
Riser-Roberts, E. 1992. Bioremediation of Petroleum Contaminated Sites . Boca Raton, Florida : CRC Press Inc.