Bayesian estimation of the transmissivity spatial structure from pumping test data

Estimating the statistical parameters (mean, variance, and integral scale) that define the spatial structure of the transmissivity or hydraulic conductivity fields is a fundamental step for the accurate prediction of subsurface flow and contaminant transport. In practice, the determination of the spatial structure is a challenge because of spatial heterogeneity and data scarcity. In this paper, we describe a novel approach that uses time drawdown data from multiple pumping tests to determine the transmissivity statistical spatial structure. The method builds on the pumping test interpretation procedure of Copty et al. (2011) (Continuous Derivation method, CD), which uses the time-drawdown data and its time derivative to estimate apparent transmissivity values as a function of radial distance from the pumping well. A Bayesian approach is then used to infer the statistical parameters of the transmissivity field by combining prior information about the parameters and the likelihood function expressed in terms of radially-dependent apparent transmissivities determined from pumping tests. A major advantage of the proposed Bayesian approach is that the likelihood function is readily determined from randomly generated multiple realizations of the transmissivity field, without the need to solve the groundwater flow equation. Applying the method to synthetically-generated pumping test data, we demonstrate that, through a relatively simple procedure, information on the spatial structure of the transmissivity may be inferred from pumping tests data. It is also shown that the prior parameter distribution has a significant influence on the estimation procedure, given the non-uniqueness of the estimation procedure. Results also indicate that the reliability of the estimated transmissivity statistical parameters increases with the number of available pumping tests.Peer ReviewedPostprint (author's final draft

Thermal based remediation technologies for soil and groundwater: a review

Thermal remediation technologies are fast and effective tools for the remediation of contaminated soils and sediments. Nevertheless, the high energy consumption and the effect of high temperature on the soil properties may hinder the wide applications of thermal remediation methods. This review highlights the recent studies focused on thermal remediation. Eight types of thermal remediation processes are discussed, including incineration, thermal desorption, stream enhanced extraction, electrical resistance heating, microwave heating, smoldering, vitrification, and pyrol-ysis. In addition, the combination of thermal remediation with other remediation technologies is presented. Finally, thermal remediation sustainability is evaluated in terms of energy efficiency and their impact on soil properties. The developments of the past decade show that thermal-based technologies are quite effective in terms of contaminant removal but that these technologies are associated with high energy use and costs and can has an adverse impact on soil properties. Nonetheless, it is anticipated that continued research on thermally based technologies can increase their sustainability and expand their applications. Low temperature thermal desorption is a prom-ising remediation technology in terms of land use and energy cost as it has no adverse effect on soil function after treatment and low temperature is required. Overall, selecting the sustainable remediation technology depends on the contaminant properties, soil properties and predicted risk level. © 2022 Desalination Publications. All rights reserved

Experimental investigation of cosolvent flushing of DNAPL in double-porosity soil using light transmission visualization

Abunada, Z ORCiD: 0000-0002-4143-1603This paper investigates the effect of cosolvent content and flushing velocity on the remediation of dense non-aqueous phase liquid (DNAPL) in double-porosity medium using light transmission visualization technique (LTV). Double-porosity was created using local silica sand and sintered spheres of kaolin, arranged in a periodic manner. The flushing solution consisted of ethanol-water mixtures with various ethanol concentrations ranging from 20% to 65% by volume. The effect of contact time was investigated by changing the flow rates of the flushing solution. The accuracy of the LTV technique was examined by comparing an actual injected volume of DNAPL with the calculated volumes generated from image analysis. The LTV results allowed for the visualization of the DNAPL enhanced dissolution as well as its mobilization. While the removal efficiency increased with the increase of the ethanol content, the removal efficiency was negatively affected by the velocity of flushing solution. Image analysis revealed that the highest DNAPL removal efficiency of 92% was obtained at 65% ethanol content and low flushing velocity. This efficiency decreased to 85%, in the case of high flushing velocity. Overall, this study demonstrated that the LTV technique is a viable laboratory tool that can accurately depict enhanced DNAPL dissolution and DNAPL mobilization due to cosolvent flushing

Evaluation of Heavy Metal Removal Capacity of Bioretention Systems

Bioretention is one of the most common low-impact development (LID) types but there is lack of knowledge in the capacity and local behavior of bioretentions. In this study, laboratory-scale experiments are conducted in order to investigate the heavy metal removal capacity of bioretentions. Batch sorption experiments were first performed to determine the sorption parameters and retardation factor of copper (Cu), lead (Pb), and zinc (Zn) on various bioretention media, namely mulch, turf, vegetative soil, sand, and gravel. Reaction kinetics of Cu, Pb, and Zn were determined in order to assess the sorption equilibrium time of these metals for the five different bioretention media. The results of the batch tests show that turf has the highest sorption capacity followed by mulch and vegetative soil. For the range of concentrations considered in this study, linear sorption isotherm was found to best represent the metal sorption for all bioretention media. Metal removal percentages were highest for Pb and lowest for Zn. The time required to reach equilibrium ranged from 1 to 6 h depending on the type of bioretention media and metal. In addition to batch sorption experiments, column sorption experiments were also conducted in order to investigate effects of soil textures and organic content on removal of heavy metal in bioretention columns. For this purpose, four bioretention columns with different vegetative soil, turf, and sand ratios were prepared. The column tests were conducted for a period of 127 days under continuous boundary source, i.e., constant flow rate is supplied to each column with a concentration of 5 mg/L for each metal. Results show that different local soil types in bioretention design affect removal of heavy metal concentration considerably. Breakthrough analysis indicates that the removal of Zn reaches almost zero in about 127 days, while Cu and Pb are almost fully retained in all columns until the end of the experiment

Biosorption of neodymium on Chlorella vulgaris in aqueous solution obtained from hard disk drive magnets

In recent years, biosorption is being considered as an environmental friendly technology for the recovery of rare earth metals (REE). This study investigates the optimal conditions for the biosorption of neodymium (Nd) from an aqueous solution derived from hard drive disk magnets using green microalgae (Chlorella vulgaris). The parameters considered include solution pH, temperature and biosorbent dosage. Best-fit equilibrium as well as kinetic biosorption models were also developed. At the optimal pH of 5, the maximum experimental Nd uptakes at 21, 35 and 50°C and an initial Nd concentration of 250 mg/L were 126.13, 157.40 and 77.10 mg/g, respectively. Analysis of the optimal equilibrium sorption data showed that the data fitted well (R2= 0.98) to the Langmuir isotherm model, with maximum monolayer coverage capacity (qmax) of 188.68 mg/g, and Langmuir isotherm constant (KL) of 0.029 L/mg. The corresponding separation factor (RL) is 0.12 indicating that the equilibrium sorption was favorable. The sorption kinetics of Nd ion follows well a pseudo-second order model (R2>0.99), even at low initial concentrations. These results show that Chlorella vulgaris has greater biosorption affinity for Nd than activated carbon and other algae types such as: A. Gracilis, Sargassum sp. and A. Densus.Bundesministerium für Bildung und Forschun

Biosorption of neodymium on Chlorella vulgaris in aqueous solution obtained from hard disk drive magnets.

In recent years, biosorption is being considered as an environmental friendly technology for the recovery of rare earth metals (REE). This study investigates the optimal conditions for the biosorption of neodymium (Nd) from an aqueous solution derived from hard drive disk magnets using green microalgae (Chlorella vulgaris). The parameters considered include solution pH, temperature and biosorbent dosage. Best-fit equilibrium as well as kinetic biosorption models were also developed. At the optimal pH of 5, the maximum experimental Nd uptakes at 21, 35 and 50°C and an initial Nd concentration of 250 mg/L were 126.13, 157.40 and 77.10 mg/g, respectively. Analysis of the optimal equilibrium sorption data showed that the data fitted well (R2 = 0.98) to the Langmuir isotherm model, with maximum monolayer coverage capacity (qmax) of 188.68 mg/g, and Langmuir isotherm constant (KL) of 0.029 L/mg. The corresponding separation factor (RL) is 0.12 indicating that the equilibrium sorption was favorable. The sorption kinetics of Nd ion follows well a pseudo-second order model (R2>0.99), even at low initial concentrations. These results show that Chlorella vulgaris has greater biosorption affinity for Nd than activated carbon and other algae types such as: A. Gracilis, Sargassum sp. and A. Densus

Modeling the impact of land use change on the hydrology of a rural watershed

Land use dynamics can have a significant impact on watershed hydrology. In this study, we develop a land use dynamics model coupled with a spatially distributed three-dimensional surface-subsurface hydrologic model. The coupled model is applied to the Bartin spring watershed, a rural watershed located in the northwestern Turkey. The land use dynamics model considers natural and anthropogenic transformations between land use categories classified as coniferous forests, deciduous forests, agriculture and settlement. The processes considered in the hydrodynamic model are evapotranspiration, overland flow, river channel flow, and saturated/unsaturated subsurface flow. The link between the land use model and the hydrodynamic model is through the vegetation parameters: leaf area index (LAI) and root depth (RD). The land use and hydrologic models were calibrated using satellite maps and daily flow and meteorological data, respectively. The correlation coefficient between the simulated and observed daily discharges for the considered watershed was about 0.72, indicating good agreement with observed data. The coupled model was used to simulate the water budget based on alternative land use and forest management scenarios. Results show that the water budget is most sensitive to variations in precipitation and conversion between forest and agricultural lands but is less sensitive to the type of forest stands. Overall, it is shown that the coupled model is a useful tool for assessing the impact of land use change on the watershed hydrological processes. (C) 2013 Elsevier B.V. All rights reserved