Contaminant Transport Processes Research Articles

Experimental and modeling insights into mixing-limited reactive transport in heterogeneous porous media: Role of stagnant zones

The understanding of mixing-controlled reactive dynamics in heterogeneous porous media remains limited, presenting significant challenges for modeling subsurface contaminant transport processes and for designing cost-effective environmental remedial efforts. The complexity of accurately observing, measuring, and modeling mixing-limited reactive transport has led to inadequate exploration of these critical processes. This study investigates the mixing and reaction kinetics affected by stagnant zones, which are commonly found in alluvial aquifers-aquitards and fracture-matrix systems. By conducting experiments involving conservative and bimolecular reactive transport through porous media within translucent chambers filled with two sizes of glass beads and under varying flow rates, we explored the effects of grain size and hydrodynamic conditions. Using a high-resolution camera, we monitored the concentration changes of conservative and reactive tracers, with subsequent interpretation through three-dimensional numerical simulations. The outcomes revealed the emergence of distinct mixing interfaces within both mobile and stagnant zones, culminating in a bi-peaked plume formation. Notably, the mixing and reaction times in media containing stagnant zones were found to be approximately 10 times longer than in homogeneous media. These findings, through experimental and modeling efforts, advance our understanding of mixing-limited reactive transport phenomena within heterogeneous media, underscoring the significant role of stagnant zones—a topic previously underexplored.

Multiscale pore‐network reconstruction of a fine‐textured heterogeneous soil

AbstractDigital samples offer many opportunities to study subsurface fluid flow and contaminant transport processes. The pore size distribution of especially fine‐textured porous media often covers many orders of magnitude in the length scale, which makes accurate microCT scanning and modeling of the underlying processes difficult. When a single‐resolution image is not capable of capturing all relevant details of a sample, one should scan the sample, or selected parts of it, at different resolutions. Combining multiple resolutions into one single sample for subsequent pore‐scale modeling is generally not possible due to limitations in computer memory and speed, thus making it necessary to create a simpler sample containing relevant information from the parent networks. We imaged four samples using different resolutions to capture the multiscale heterogeneity of a fine‐textured soil and combined them into one overall digital sample based on the original pore networks. The parent networks were characterized using their geometrical properties, correlations between these properties, and connectivity functions describing the network topologies. Our approach creates stochastic networks of arbitrary size with the same flow properties as the parent network. The method, implemented using the PoreStudio pore network model, repeatedly integrates information at two subsequent scales, with the resulting digital sample having the same hydraulic properties as the original samples. The procedure leads to more useful three‐dimensional digital models, facilitating basic analyses of underlying pore size distributions. Porosity calculations were compared with direct measurements, while those for the hydraulic conductivity were compared with estimates based on the particle size distribution and nearby field data.

Contaminant Transport Modeling and Source Attribution With Attention‐Based Graph Neural Network

AbstractGroundwater contamination induced by anthropogenic activities has long been a global issue. Characterizing and modeling contaminant transport processes is crucial to groundwater protection and management. However, challenges still exist in process complexity, data constraint, and computational cost. In the era of big data, the growth of machine learning has led to new opportunities in studying contaminant transport in groundwater systems. In this work, we introduce a new attention‐based graph neural network (aGNN) for modeling contaminant transport with limited monitoring data and quantifying causal connections between contaminant sources (drivers) and their spreading (outcomes). In five synthetic case studies that involve varying monitoring networks in heterogeneous aquifers, aGNN is shown to outperform LSTM‐based (long‐short term memory) and CNN‐ based (convolutional neural network) methods in multistep predictions (i.e., transductive learning). It also demonstrates a high level of applicability in inferring observations for unmonitored sites (i.e., inductive learning). Furthermore, an explanatory analysis based on aGNN quantifies the influence of each contaminant source, which has been validated by a physics‐based model with consistent outcomes with an R2 value exceeding 92%. The major advantage of aGNN is that it not only has a high level of predictive power in multiple scenario evaluations but also substantially reduces computational cost. Overall, this study shows that aGNN is efficient and robust for highly nonlinear spatiotemporal learning in subsurface contaminant transport, and provides a promising tool for groundwater management involving contaminant source attribution.

Microscale Chaotic Mixing as a Driver for Chemical Reactions in Porous Media.

Mixing-induced reactions play a key role in a large range of biogeochemical and contaminant transport processes in the subsurface. Fluid flow through porous media was recently shown to exhibit chaotic mixing dynamics at the pore scale, enhancing microscale concentration gradients and controlling mixing rates. While this phenomenon is likely ubiquitous in environmental systems, it is not known how it affects chemical reactions. Here, we use refractive index matching and laser-induced fluorescence imaging of a bimolecular redox reaction to investigate the consequence of pore scale chaotic mixing on the reaction rates. The overestimation of measured reaction rates by the classical macrodispersion model highlights the persistence of incomplete mixing on the pore scale. We show that the reaction product formation is controlled by microscale chaotic mixing, which induces an exponential increase of the mixing interface and of the reaction rates. We derive a reactive transport model that captures experimental results and predicts that chaotic mixing has a first order control on reaction rates across a large range of time scales and Péclet and Damköhler numbers. These findings provide a new framework for understanding, assessing, and predicting mixing-induced reactions and their role on the fate and mobility of environmental compounds in natural porous media.

The impact of slope and rainfall on the contaminant transport from mountainous groundwater to the lowland surface water

The surface water and groundwater in the mountainous area are vulnerable to contamination from the mining and transportation construction in Sichuan Province, China. Pollutants produced by anthropogenic activities transport within the groundwater from mountains to rivers on the plain, transferring contamination to the surface water. This study investigates the process of groundwater flow and contaminant transport from mountains to the lowlands based on synthetic numerical models. Two key factors are considered: precipitation and the slope of the mountain. Based on the real situation in Sichuan Province, four rainfall recharge rates are defined as 600, 800, 1,000, and 1,200 mm/yr, and five slope angles are considered: 20°, 25°, 30°, 35°, and 40°. The simulation results reveal that the groundwater level and solute transport are strongly influenced by the precipitation amounts and slope angles. The mountains with lower slopes maintain a relatively higher groundwater level under steady-state rainfall conditions; for example, groundwater levels decrease from 340 m to 300 m as slope angles increase at a 1,200 mm/yr precipitation level. Contaminant transport from the source in the mountain to the surface river is faster with increasing precipitations and decreasing slope angles. The model with 20° slope angle and 1,200 mm/yr precipitation exhibits the fastest solute migration, with the contaminant arrival time of 65 years. Furthermore, the models with 35° and 40° slope angles at a 600 mm/yr precipitation level show the slow transport speed with the contaminant arrival time of more than 75 years. In addition, higher precipitation may lead to more contaminant transport to the river. The analysis and findings of this study offer valuable insights into groundwater protection at the boundaries of mountains and plains.

Characteristics and environmental significance of sulfur isotope signatures in the water environment of typical pyrite mines

Contaminants in the water environment of different pyrite mines have varying characteristics due to different geological origins. Sulfur isotope (δ34S) is an effective tool to reveal the mechanism of water environment contamination, but no investigations have yet analyzed the characteristics and environmental significance of the δ34S in the water environment of different pyrite mines. This study involved a field investigation of four typical pyrite mines in China (representing volcanic, skarn, sedimentary-metamorphic, and coal-deposited types) and the analysis of the hydrochemistry of aqueous samples and the δ34S of both pyrite and dissolved sulfates. The S isotopes in minerals of different types of mines were associated with the deposit genesis, and S isotopes in the water environment were affected by sulfide minerals and indicative of the contaminant sources, types of contaminants, and contaminant transport processes. The environmental significance of δ34S in the water environment was further explored and a contamination model for pyrite mines established based on S isotope data. The study offers a theoretical foundation for further research on the prevention, control, and management of water pollution at various types of pyrite mines.

Estimating the impact of vadose zone heterogeneity on agricultural managed aquifer recharge: A combined experimental and modeling study

Agricultural managed aquifer recharge (Ag-MAR) is a promising approach to replenish groundwater resources using flood water and cropland as spreading grounds. However, site selection, particularly the layering of sediment deposits in the subsurface, can greatly influence Ag-MAR efficacy as it controls water flow and solute transport in the vadose zone. In this study, we use the HYDRUS-1D software to simulate water flow and solute transport from the land surface to the groundwater table in three vadose zone profiles (LS, MS, HS) characterized by differing fractions of sand (44 %, 47 %, and 64 %). For each profile, the single- and dual-porosity models (i.e., considering or not nonequilibrium water flow and solute transport) were calibrated using observed surface ponding, soil water content, and KBr breakthrough data. Water flow and bromide transport in the profile with the lowest sand fraction (LS) were best captured using the model that considered both preferential flow and nonequilibrium bromide transport. Water flow and bromide transport in the profile with the highest sand fraction (HS) was best simulated with the model that considered preferential flow and equilibrium bromide transport. Uniform water flow and nonequilibrium bromide transport provided the best fit for the third profile (MS). The degree of preferential flow was highest in the profile with the largest sand fraction (HS), which also showed the largest flow velocities compared to the profiles with lower sand amounts (LS and MS). Preferential flow did not significantly impact the overall water balance (within 3 %), but caused a significant decrease in vadose zone travel times (bromide) by up to 38 %, relative to a single-porosity model fit. Recharge efficiency varied between 88 % and 90 %, while the average travel times from the soil surface to groundwater varied up to 119 % (from 3.6 to 7.9 days) between the three sites. This study demonstrates that similar recharge efficiency can be achieved at sites with differing soil texture profiles, but subsurface heterogeneity can substantially affect contaminant transport processes and their travel times.

Comparison of transit time models for exploring seasonal variation of preferential flow in a Moso bamboo watershed

Understanding seasonal variations of the hydrological fluxes and preferential flow is crucial in exploring contaminant fate and transport processes in a watershed of interest. Here, performance of different StorAge Selection (SAS)-based rainfall-runoff models was compared for a Moso bamboo watershed under the East Asian monsoon climate. Most of these models are composed of a two-parallel-reservoir flow module and a companioned SAS module. The results show that the temporal variation in streamflow is well captured by a two-parallel-reservoir flow module. The tracer simulations from different models show that two-uniform-reservoir (SSU) model with no SAS function has the lowest NSE value (0.17), the model including an SAS in one of the two reservoir outflows (SSD(U) and SSD(L)) improves performance (NSE greater than 0.5). The performance in simulating streamflow δ18O is further improved when SAS functions are applied for outflows from both reservoirs (SSD (U, L), NSE = 0.76). Additional inclusion an SAS function for ET fluxes in the model (SSD (U, ET, L)) results in a minor improvement from SSD (U, L). The results of SSD (U, ET, L) have achieved the best transport performance (NSE = 0.77), with implication for preferential flow in the watershed. The preferential flow for deep drainage and lower reservoir outflow shows seasonal variation, with more young water in the East Asian summer monsoon period than that in the East Asian winter monsoon period. The upper reservoir storage and deep drainage rates are the main factors determining the temporal variation of preferential flow for deep drainage and lower reservoir outflow, respectively.

Analytical solution for contaminant transport through a GCL-enhanced composite cutoff wall system

The geosynthetic clay liners (GCLs) have been recently shown to be effective in cutoff wall applications. Yet, its influence on contaminant transport through cutoff wall system is rarely reported. This study presents an analytical solution for the transport of organic contaminant through a composite cutoff wall system comprising a soil-bentonite wall, a GCL, and an aquifer. The analytical solution was obtained by variable separation method and verified against an existing analytical solution and a numerical solution. Parametric analysis was conducted to elucidate the effects of GCL, soil-bentonite (SB) wall thickness (Lw), aquifer thickness (La), and contaminant half-life (t1/2) on contaminant transport. The results show that by adding a GCL layer, the contaminant concentration and the maximum flux can be significantly decreased. When the GCL retardation factor increases 1 to 300, the required time to reach the maximum flux is delayed from about 62 years to 1500 years. Larger aquifer thickness sufficiently weakens the contaminant transport process. Under the same breakthrough criteria, the required thickness of SB wall decreases by about 20% when the GCL retardation factor increases from 1 to 50. The proposed analytical solution provides a useful tool for the design of the SB-GCL cutoff wall system.

Evaluation of Hydraulic Conductivity Estimates from Various Approaches with Groundwater Flow Models.

Significant efforts have been expended for improved characterization of hydraulic conductivity (K) and specific storage (Ss) to better understand groundwater flow and contaminant transport processes. Conventional methods including grain size analyses (GSA), permeameter, slug, and pumping tests have been utilized extensively, while Direct Push-based Hydraulic Profiling Tool (HPT) surveys have been developed to obtain high-resolution K estimates. Moreover, inverse modeling approaches based on geology-based zonations, and highly parameterized Hydraulic Tomography (HT) have also been advanced to map spatial variations of K and Ss between and beyond boreholes. While different methods are available, it is unclear which one yields K estimates that are most useful for high resolution predictions of groundwater flow. Therefore, the main objective of this study is to evaluate various K estimates at a highly heterogeneous field site obtained with three categories of characterization techniques including: (1) conventional methods (GSA, permeameter, and slug tests); (2) HPT surveys; and (3) inverse modeling based on geology-based zonations and highly parameterized approaches. The performance of each approach is first qualitatively analyzed by comparing K estimates to site geology. Then, steady-state and transient groundwater flow models are employed to quantitatively assess various K estimates by simulating pumping tests not used for parameter estimation. Results reveal that inverse modeling approaches yield the best drawdown predictions under both steady and transient conditions. In contrast, conventional methods and HPT surveys yield biased predictions. Based on our research, it appears that inverse modeling and data fusion are necessary steps in predicting accurate groundwater flow behavior.

Groundwater Vulnerability and Delineation of Protection Zones in the Discharge Area of a Karstic Aquifer—Application in Agyia’s Karst System (Crete, Greece)

This work represents a contribution to the protection techniques of karst aquifers against groundwater pollution. The paper sets out the methodology being introduced for the protection of the karstic system that gives rise to five (5) major groups of springs and supplies fourteen (14) pumping wells near Agyia Chania (Crete, Greece). Starting from a geological and hydrogeological survey of the area, the work presents a vulnerability assessment of the karstic aquifer based on the application of three index-based methods (EPIK, PRESK and DRISTPI). The protection zones for the discharge area of the aquifer were delineated through an integrated geomorphological approach and groundwater flow modeling. At first, the risk of polluting substances migration from ground surface to groundwater was considered based on the spatial distribution of vulnerability. Following this, the vulnerability was evaluated in the saturated zone, where the attenuation mechanisms of contaminants were reducing due to the raised flow velocity. The groundwater flow and contaminant transport processes was considered using the MODFLOW code. Next, the data from the vulnerability mapping and the groundwater flow simulation were merged into an integrated assessment to delimit the protection zones for the water abstraction points. The vulnerability assessment outlines zones of high vulnerability in the SE part of the area, far away from the discharge zone of the aquifer and the water abstraction points. These zones are associated with an intensive infiltration process via carbonate formations. Protection Zone I was delineated 20 m around the water abstraction points, and it should be excluded from any anthropogenic activity. Protection Zone II coves part of the very high and high vulnerability zones defined by the DRISTPI method (located upwards of the water abstraction points), as well as an area downwards of springs and wells, where the flow path lines which demonstrate the subsurface travelling time of 50 days are projected to the ground surface. Protection Zone III extends outside Zone Ι and Zone ΙΙ, up to the limits of the hydrogeological or hydrological basin, whichever is larger. It includes the entire capture zone (i.e., the surface and underground catchment area) that feeds the water abstraction points. In this manner the protection zones include the entire contributing area to water abstraction points, not just the ground surface recharge zone.

Regional Scale Assessment of Shallow Groundwater Vulnerability to Contamination from Unconventional Hydrocarbon Extraction.

Concerns over unconventional oil and gas (UOG) development persist, especially in rural communities that rely on shallow groundwater for drinking and other domestic purposes. Given the continued expansion of the industry, regional (vs local scale) models are needed to characterize groundwater contamination risks faced by the increasing proportion of the population residing in areas that accommodate UOG extraction. In this paper, we evaluate groundwater vulnerability to contamination from surface spills and shallow subsurface leakage of UOG wells within a 104,000 km2 region in the Appalachian Basin, northeastern USA. We test a computationally efficient ensemble approach for simulating groundwater flow and contaminant transport processes to quantify vulnerability with high resolution. We also examine metamodels, or machine learning models trained to emulate physically based models, and investigate their spatial transferability. We identify predictors describing proximity to UOG, hydrology, and topography that are important for metamodels to make accurate vulnerability predictions outside their training regions. Using our approach, we estimate that 21,000-30,000 individuals in our study area are dependent on domestic water wells that are vulnerable to contamination from UOG activities. Our novel modeling framework could be used to guide groundwater monitoring, provide information for public health studies, and assess environmental justice issues.

Decoding river pollution trends and their landscape determinants in an ecologically fragile karst basin using a machine learning model

Karst watersheds accommodate high landscape complexity and are influenced by both human-induced and natural activity, which affects the formation and process of runoff, sediment connectivity and contaminant transport and alters natural hydrological and nutrient cycling. However, physical monitoring stations are costly and labor-intensive, which has confined the assessment of water quality impairments on spatial scale. The geographical characteristics of catchments are potential influencing factors of water quality, often overlooked in previous studies of highly heterogeneous karst landscape. To solve this problem, we developed a machining learning method and applied Extreme Gradient Boosting (XGBoost) to predict the spatial distribution of water quality in the world's most ecologically fragile karst watershed. We used the Shapley Addition interpretation (SHAP) to explain the potential determinants. Before this process, we first used the water quality damage index (WQI-DET) to evaluate the water quality impairment status and determined that CODMn, TN and TP were causing river water quality impairments in the WRB. Second, we selected 46 watershed features based on the three key processes (sources-mobilization-transport) which affect the temporal and spatial variation of river pollutants to predict water quality in unmonitored reaches and decipher the potential determinants of river impairments. The predicting range of CODMn spanned from 1.39 mg/L to 17.40 mg/L. The predictions of TP and TN ranged from 0.02 to 1.31 mg/L and 0.25–5.72 mg/L, respectively. In general, the XGBoost model performs well in predicting the concentration of water quality in the WRB. SHAP explained that pollutant levels may be driven by three factors: anthropogenic sources (agricultural pollution inputs), fragile soils (low organic carbon content and high soil permeability to water flow), and pollutant transport mechanisms (TWI, carbonate rocks). Our study provides key data to support decision-making for water quality restoration projects in the WRB and information to help bridge the science:policy gap.

Single region substitute models for dual-porosity advection–dispersion migration process based on contaminant distribution

Dual-porosity (DP) model is recommended for describing the complex non-Fickian contaminant transport in soil, while advection–dispersion-equation (ADE) model is the most popular transport model due to its simplicity and convenience. In this study, single region substitute approaches for the DP model were established based on the contaminant distribution in the mobile and immobile phases. A time dependent parameter Ω was used to determine the participation degree of the immobile phase in contaminant transport. The single region substitute (SRS) model was modified by combining the mobile phase retardation factor with the adsorbed concentration of immobile phase. Furthermore, dispersion-modified SRS (DSRS) model was established for calculating the equivalent dispersion coefficient of the coupled mobile-immobile mass transfer and advection via Fourier transformation. Correlation analyses of the modified models shown that the SRS model fits DP well when advection velocity or the mobile-immobile mass transfer rate is relatively slow under both Cauchy and Dirichlet inlet boundary, whereas that the DSRS model is applicable when mobile-immobile mass transfer rate is relatively higher. Both SRS and DSRS models can provide better understanding to the contaminant transport process of DP model.

Storage and release of conservative solute between karst conduit and fissures using a laboratory analog

The contaminant transport processes in karst water systems have a direct impact on the quality and utilization of karst water resources. The storage and release of contaminants or conservative solutes during the solute transport process is a common phenomenon in karst aquifers. The impact of the storage and release is more prevalent after focused recharge events. In this study, laboratory experimental and numerical studies were conducted to quantify the storage and release processes of conservative solute. The results showed that, conduit water recharges into fissures under high water head conditions, and the fissure water drains back into the conduit while the hydraulic gradient reverse. The conservative solute storage-release process controlled by hydrodynamic conditions produces strong asymmetry, long tailing, or bi-peak in the breakthrough curves (BTCs). The BTCs change from single peak to bi-peak with enhanced hydrodynamics under focused recharge conditions. The dual heterogeneous domain model was calibrated to simulate the long-tailing of the BTCs and their noticeably bimodal characteristics. The flow velocity and dispersion coefficient are the major variables that regulate the bimodal structure of the BTCs, which also control the solute storage-release differences between the conduit and fissures. The bimodal structure of the BTCs becomes more pronounced for large discrepancies in flow velocities. The total BTCs are a superposition of solute transport in the conduit path and storage-release path. A method to evaluate the mass of conservative solute transport in storage-release paths was proposed by segmenting the transport curve in the conduit from the total BTCs, thus quantifying the effects of the groundwater storage-release mechanism on the solute transport process in the karst water system.

Writing Essay as Essential Assessment in Groundwater Contamination Course

An essay was used as an assessment to illustrate a certain way of thinking and attitude of a student. The essay demonstrates the student's utmost degree as an author with a cognitive and affective style. The study aimed to provide a simple description of the essay as an assessment and critical function in the Groundwater Contamination course of the Environmental Engineering Program offered by Curtin University Malaysia. Groundwater Contamination is designed for students of environmental engineering and covers a number of topics, including groundwater characterization, contaminant transport processes in groundwater flow systems, migration and chemical development of contamination plumes, and groundwater remediation. No correlation exists between essay length (word count) and report or presentation grades, while there was a strong relationship between the student mark and essay content (R2 = 0.88), but a moderate relationship to essay format (R2 = 0.55). Overall, the students at Curtin University Malaysia were able to meet the Course Outcome of Groundwater Contamination and the Program Outcome of Environmental Engineering because of the essay they wrote as a test.

Characterization of the non-Gaussian hydraulic conductivity field via deep learning-based inversion of hydraulic-head and self-potential data

Accurate characterization of the spatial heterogeneity of hydraulic properties such as hydraulic conductivity (K) is essential for understanding groundwater flow and contaminant transport processes. Deep learning-based ensemble smoother methods have proven to be effective in estimating non-Gaussian K fields by assimilating hydrodynamic measurements. However, traditional hydrogeological investigations (e.g., hydraulic tomography) often suffer from the limited number of invasive borehole data (e.g., hydraulic head), making the non-Gaussian K inversion problem strongly underdetermined. As a non-invasive and high-sampling-density geophysical approach, the self-potential (SP) method can measure fluctuations of the electrical field caused by subsurface fluid movement. Thus, the recorded SP signals are electro-kinetic responses of the groundwater flow and can provide complementary information for delineating non-Gaussian heterogeneity. In this paper, we performed a joint hydrogeophysical inversion of hydraulic-head and SP data to characterize the non-Gaussian K field within a deep learning-based inversion framework. We conducted three synthetic cases in a 3-D non-Gaussian aquifer with 16,000 unknown K, to assess the ability of the proposed joint inversion framework for K imaging by assimilating different types of data. The results show that using limited hydraulic-head data alone may capture the large-scale features of the non-Gaussian reference field but might lose fine features. By integrating the hydraulic-head and SP data, the non-Gaussian K field can be reconstructed with an improved accuracy and reduced estimation uncertainty. The low-cost SP method opens up new opportunities for non-Gaussian K characterization and fluid-dynamic monitoring.

Evaluation of aqueous Cd2+ and Pb2+ removal by natural loess using spectral induced polarization and microscopic characterization.

Mining and landfill activities can cause serious soil and groundwater contamination with lead (Pb) and cadmium (Cd). Loess soils are common and have been reported as effective for the removal of heavy metals. The spectral induced polarization (SIP) technique has been approved for its nondestructive ability to characterize the contaminant transport process and surface geochemical properties in porous media. In the present study, SIP was applied to monitor Pb2+ and Cd2+ removal processes using loess through column flow-through experiments. The outflow aqueous geochemical analyses indicated a better retention capability of loess for Pb2+, which was through precipitation induced by calcite dissolution and aqueous pH increment, as confirmed by SEM-EDS and XRD results. Cd retention took place mainly through ion exchange with Ca2+ and Mg2+ on the loess surface. The SIP signals showed a continuous decrement on the magnitude of imaginary conductivity during both Pb2+ and Cd2+ flow-through, which was attributed to the total surface area and decrement of polarizable surface charges. The SIP signals differentiated the interactions between loess and Pb2+/Cd2+ by displaying a peak shift to a higher frequency on the imaginary conductivity spectra during Pb2+ flow-through, which was attributed to calcite dissolution and proved by the high correlation (R2 = 0.9366) between the estimated dissolved calcite mass and the peak of imaginary conductivity. The above results suggest that loess has a great potential for field heavy metal remediation applications, and the SIP technique displays a promising capability of monitoring the remediation performance.

Design of Soil Remediation Techniques from Column Leaching Test Results

The soil remediation at a contaminated site requires knowledge of contaminant transport parameters and processes. This paper presents the determination of transport parameters from column leaching tests in context with two soil remediation techniques i.e., soil washing and immobilization. To evaluate the soil washing technique, the column leaching tests on the polluted soil were conducted with diluted acid solutions of hydrochloric acid, ethylene diamine tetraacetic acid and ferric chloride to evaluate the leaching efficiencies of the selected leaching solutions. It was observed that the efficiency of diluted ferric chloride solution was higher as it removed the higher percentage of metals from the soil. From these test results, the contaminant transport parameters i.e., retardation factor and dispersion coefficient were determined which are useful to calculate the volume of leaching solution that will be required for soil washing at a site. As part of immobilization study on this soil, the soil was mixed with the selected amendments (lime, sodium hydroxide and cement) to increase the pH of the soil to 10 and the retardation factors were estimated through batch leaching test results. The retardation factors of different metals obtained with lime addition were found higher than the other amendments.To analyze the long-term stability of the amended mixtures, the leaching tests were conducted on amended soil samples and the immobilization efficiencies were estimated. It was found that the immobilization efficiencies were higher with lime addition and also concluded that the immobilization effiencies are directly related to retardation factors.

Analysis of environmental dispersion in wetland flows with floating vegetation islands

The fate of the contaminant transport process within wetland flows considering contaminant depletion via a floating vegetation island (FVI) is the focus of this work. To identify the feature of contaminant cloud expansion under an FVI, multiscale theory is extended to obtain a two-dimensional spatial concentration distribution analytical solution. The characteristics of two-dimensional concentration distributions under upper FVI absorption and damping factor within wetland flows are illustrated. The performance of the contaminant depletion process via an FVI is also examined in this work, with discussions on removal efficiency, the absorption ratio, and the nonuniformity of contaminant mass. As FVI removal intensity changes along the stream direction, the analytical solution of removal efficiency is obtained to illustrate the longitudinal variation in the FVI removal intensity. Furthermore, the effects of removal intensity and damping factor on FVI removal efficiency are expressed separately. In addition, the removal intensity variance in the vertical direction is discussed using the defined absorption ratio. Moreover, as residual mass is a fatal issue in the contaminant removal process, temporal residual mass is discussed, and the residual mass proportion within different layers is depicted. Finally, the difference of the mass proportion between layers is employed to explain the transformation of the contaminant cloud.