Light Nonaqueous Phase Liquid Contamination Research Articles

Groundwater LNAPL Contamination Source Identification Based on Stacking Ensemble Surrogate Model

Groundwater LNAPL (Light Non-Aqueous Phase Liquid) contamination source identification (GLCSI) is essential for effective remediation and risk assessment. Addressing the GLCSI problem often involves numerous repetitive forward simulations, which are computationally expensive and time-consuming. Establishing a surrogate model for the simulation model is an effective way to overcome this challenge. However, how to obtain high-quality samples for training the surrogate model and which method should be used to develop the surrogate model with higher accuracy remain important questions to explore. To this end, this paper innovatively adopted the quasi-Monte Carlo (QMC) method to sample from the prior space of unknown variables. Then, this paper established a variety of individual machine learning surrogate models, respectively, and screened three with higher training accuracy among them as the base-learning models (BLMs). The Stacking ensemble framework was utilized to integrate the three BLMs to establish the ensemble surrogate model for the groundwater LNAPL multiphase flow numerical simulation model. Finally, a hypothetical case of groundwater LNAPL contamination was designed. After evaluating the accuracy of the Stacking ensemble surrogate model, the differential evolution Markov chain (DE-MC) algorithm was applied to jointly identify information on groundwater LNAPL contamination source and key hydrogeological parameters. The results of this study demonstrated the following: (1) Employing the QMC method to sample from the prior space resulted in more uniformly distributed and representative samples, which improved the quality of the training data. (2) The developed Stacking ensemble surrogate model had a higher accuracy than any individual surrogate model, with an average R2 of 0.995, and reduced the computational burden by 99.56% compared to the inversion process based on the simulation model. (3) The application of the DE-MC algorithm effectively solved the GLCSI problem, and the mean relative error of the identification results of unknown variables was less than 5%.

Migration and redistribution of LNAPL in inclined stratified soil media

Leakage of light non-aqueous phase liquid (LNAPL) into soil can cause serious environmental issues. In this study, a two-dimensional device with adjustable dip angles was designed to investigate the migration and redistribution of LNAPL in natural inclined stratified soil media by the light transmission visualization (LTV) technology. The captured experimental images were processed to obtain the diesel distribution based on gray value which could represent the LNAPL saturation distribution. LNAPL may not be able to penetrate through the fine-coarse interface due to the capillary barrier effects. In this case, the vertical and horizontal migration distances (V and H), contaminated area (S), as well as deviation angle (γ) of centroid increased with the dip angle. Increasing the leakage amount to more than 30 mL would result in LNAPL breakthrough at the 10°-inclined interface, leading to much larger V, H, S, and γ than those at 10 mL, while 20-mL LNAPL failed to break through. In the latter case, a lower leakage rate than 10 mL/min would cause larger H and γ but similar V or S in the long term. This study could enrich the understanding of LNAPL contamination in vadose zone, providing reference for the prediction and treatment in realistic inclined contaminated sites.

Identification of light nonaqueous phase liquid groundwater contamination source based on empirical mode decomposition and deep learning.

The simulation optimization method was used to the identification of light nonaqueous phase liquid (LNAPL) groundwater contamination source (GCS) with the help of a hypothetical case in this study. When applying the simulation optimization method to identify GCS, it was a common technical means to establish surrogate model for the simulation model to participate in the iterative calculation to reduce the calculation load and calculation time. However, it was difficult for a single modeling method to establish surrogate model with high accuracy for the LNAPL contamination multiphase flow simulation model (MFSM). To give full play to advantages of single surrogate model and improve the accuracy of the surrogate model to the MFSM, a combination of deep belief neural network (DBNN) and long short-term memory (LSTM) neural network was used to establish artificial intelligence ensemble surrogate model (AIESM) for the MFSM. At the same time, to reduce the influence of noise in observed concentrations on the accuracy of the identification results, empirical mode decomposition (EMD) and wavelet analysis methods were used to denoise the observed concentrations, and their noise reduction effects were compared. The observed concentrations with better noise reduction effect and the observed concentrations without denoising were used to construct the objective function, and constraints of the optimization model were determined meanwhile. Then, the objective function and the constraints were integrated to build the optimization model to identify GCS and simulation model parameters. Applying the AIESM instead of the MFSM to embed in the optimization model and participate in the iterative calculation. Finally, the genetic algorithm (GA) was used to solve the optimization model to obtain the identification results of GCS and simulation model parameters. The results showed that compared with the single DBNN and LSTM surrogate models, AIESM obtained the highest accuracy and could replace the MFSM to participate in the iterative calculation, thereby reducing the calculation load and calculation time by more than 99%. Comparing with the wavelet analysis, EMD could reduce the noise in the concentrations more effectively, improved the accuracy of the approximated concentrations to the actual values, and increased the accuracy of the GCSs identification results by 1.45%.

Testing an Analytical Model for Predicting Subsurface LNAPL Distributions from Current and Historic Fluid Levels in Monitoring Wells: A Preliminary Test Considering Hysteresis

Knowledge of subsurface light nonaqueous phase liquid (LNAPL) saturation is important for developing a conceptual model and a plan for addressing LNAPL contaminated sites. Investigators commonly predict LNAPL mobility and potential recoverability using information such as LNAPL physical properties, subsurface characteristics, and LNAPL saturations. Several models exist that estimate the LNAPL specific volume and transmissivity from fluid levels in monitoring wells. Commonly, investigators use main drainage capillary pressure–saturation relations because they are more frequently measured and available in the literature. However, main drainage capillary pressure–saturation relations may not reflect field conditions due to capillary pressure–saturation hysteresis. In this paper, we conduct a preliminary test of a recent analytical model that predicts subsurface LNAPL saturations, specific volume, and transmissivity against data measured at a LNAPL contaminated site. We call our test preliminary because we compare only measured and predicted vertical LNAPL saturations at a single site. Our results show there is better agreement between measured and predicted LNAPL saturations when imbibition capillary pressure–saturation relations are employed versus main drainage capillary pressure–saturation relations. Although further testing of the model for different conditions and sites is warranted, the preliminary test of the model was positive when consideration was given to capillary pressure–saturation hysteresis, which suggests the model can yield reasonable predictions that can help develop and update conceptual site models for addressing subsurface LNAPL contamination. Parameters describing capillary pressure–saturation relations need to reflect conditions existing at the time when the fluid levels in a well are measured.

Understanding complex LNAPL sites: Illustrated handbook of LNAPL transport and fate in the subsurface

The goal of the paper is to highlight the management of the complexities and risks for light non-aqueous phase liquid (LNAPL) sites, and how the Illustrated Handbook of LNAPL Transport and Fate in the Subsurface (CL:AIRE, London. ISBN 978-1-905046-24-9. http://www.claire.co.uk/LNAPL; “LNAPL illustrated handbook”) is useful guidance and a tool for professionals to understand these complexities and risks. The LNAPL illustrated handbook provides a clear and concise best-practice guidance document, which is a valuable decision support tool for use in discussions and negotiations regarding LNAPL impacted sites with respect to the risks of LNAPL. The LNAPL illustrated handbook is a user-friendly overview of the nature of LNAPL contamination in various geological settings including unconsolidated, consolidated, and fractured rock environments to best understand its fate and behavior leading to the appropriate management and/or remedial approach of the two major risks associated with a LNAPL source. As a source term, LNAPL has chemicals that form dissolved- and vapor-phase plumes, which are referred to as composition-based risks; and being a liquid there is the risk that the source may expand impacting a greater volume of the aquifer, which are referred to as saturation-based risks. There have been significant developments in recent years on the understanding of the complex behavior of LNAPL and associated groundwater and vapor plumes; however, the state of practice has often lagged these improvements in knowledge. The LNAPL illustrated handbook aids the site investigator, site owners, and regulators to understand these risks, and understand how these risks behave through better conceptual understanding of LNAPL transport and fate in the subsurface.

Scenario-based modelling of mass transfer mechanisms at a petroleum contaminated field site-numerical implications

Knowledge about distribution of dissolved plumes and their influencing factors is essential for risk assessment and remediation of light non-aqueous phase liquid contamination in groundwater. Present study deals with the applicability of numerical model for simulating various hydro-geological scenarios considering non-uniform source distribution at a petroleum contaminated site in Chennai, India. The complexity associated with the hydrogeology of the site has limited scope for on-site quantification of petroleum pipeline spillage. The change in fuel composition under mass-transfer limited conditions was predicted by simultaneously comparing deviations in aqueous concentrations and activity coefficients (between Raoult's law and analytical approaches). The effects of source migration and weathering on the dissolution of major soluble fractions of petroleum fuel were also studied in relation to the apparent change in their activity coefficients and molar fractions. The model results were compared with field observations and found that field conditions were favourable for biodegradation, especially for the aromatic fraction (benzene and toluene (nearly 95% removal), polycyclic aromatic hydrocarbons (up to 65% removal) and xylene (nearly 45% removal). The results help to differentiate the effect of compositional non-ideality from rate-limited dissolution towards tailing of less soluble compounds (alkanes and trimethylbenzene). Although the effect of non-ideality decreased with distance from the source, the assumption of spatially varying residual saturation could effectively illustrate post-spill scenario by estimating the consequent decrease in mass transfer rate.

Application of Electromagnetic Exploration Techniques to Oil Contaminated Soil

The effectiveness of various electromagnetic geophysical exploration techniques for detecting near-surface soil contaminants is described in this paper. Field tests were carried out at an industrial site containing light nonaqueous phase liquid (LNAPL) in soil. Experiment results show that the combination of ground penetrating radar (GPR), electrical resistivity and electromagnetic (EM) exploration provide a means of mapping of subsurface contamination. The region where radar signal amplitude is decreased and high resistivity appears is illustrated over areas with LNAPL contamination under site specific circumstances. Electrical resistivity and EM exploration gave the similar resistivity distribution. A relationship between contaminant saturation and dielectric constant is established based on chemical analysis and modeling of mixed material. It is necessary to understand the geophysical properties of hydrocarbon contaminants for detecting them by geophysical techniques successfully.

2D Electrical Imaging of an LNAPL Contamination, Al Amiriyya Fuel Station, Jordan

The detection of organic contaminants such as light non-aqueous phase liquid (LNAPL) in the subsurface using geophysical methods, particularly electrical resistivity methods has been the subject of considerable interest in recent years. Their detection is based principally upon the electrical properties of the hydrocarbons. During 2002, direct current resistivity data were collected with the Iris Syscal R2 resistivity instrument at the location of Al Amiriyya fuel station site, Jordan. The objective of this study was to evaluate the resolution of resistivity techniques in detecting and locating anomalies of organic contamination. Resistivity measurements were carried out utilizing the Wenner and dipole-dipole array configurations in order to achieve good vertical and lateral resistivity distributions for the investigated site. The interpretations obtained from 2D-modelling of the field data show a highly conductive region in areas with LNAPL contamination. This explanation was supported by the presence of hydrocarbon sheens floated on the surface of water filling the subsidence feature and by excavation works. Correlation between field results obtained shows that the dipole-dipole array is the most reliable since it showed details over the fuel station site that were poorly indicated by the Wenner array.

4-D ground penetrating radar monitoring of a hydrocarbon leakage site in Fortaleza (Brazil) during its remediation process: a case history

A 4-D monitoring GPR survey was carried out in order to outline the light non-aqueous phase liquid (LNAPL) plume underground during a remediation process in the area of an impacted gas station in Fortaleza, NE Brazil. The complex GPR signature of the plume was well characterized. Low reflectivity zone corresponds to hydrocarbon vapor phase in the vadose zone. Enhanced reflections are associated with free and residual products directly above the water table. A theoretical model based on geochemical zonation of the LNAPL was calculated using a finite difference time domain (FDTD) forward modeling code, whose synthetic radargrams provide useful insight into the nature of the reflection events related to LNAPL contamination. Hydrogeologic and hydrochemical data from installed monitoring wells provided additional support for interpreting of the GPR response. Moreover, a network of radar sections collected during fifteen months at the polluted site show clearly temporal changes in the plume dimensions, induced by regular pumping of groundwater. This corrective action caused an important drop of the water table that was followed by a rapid shrinking of the impacted area in the vadose zone, generating pooling of vapor products. A steady restore of the reflectivity in the shadow zone suggests a decrease of LNAPL saturation along the GPR survey.

Hydrocarbon contamination of groundwater at Ploiesti, Romania

Abstract The area of Ploiesti in Romania was among the first oil producing regions in the world. The refineries and oil pipelines have leaked petroleum products over many years. An area of at least 500 ha is contaminated by free product light non-aqueous-phase liquid (LNAPL), affecting one third of Ploiesti’s water supplies. To date it has been possible to compensate by extending the well fields and using surface water, but the long-term sustainability of these measures has not been investigated. The Prahova and Teleajan rivers, tributaries of the River Danube, are also at risk. A conceptual map is presented to show the evolution of LNAPL contamination between 1980 and 2000, and the quantity of oil in each plume is estimated. Potential recovery of oil using a conventional pump-and-treat system is also calculated, with costs and possible revenue. An outline programme for investigation and remediation is presented, part of which is being implemented with a European Community grant. Although the severity of contamination was at least partly realised in the 1970s, only the recent move towards privatization could mobilize sufficient financial resources to address this problem and protect groundwater resources for future use.