Journal of Hazardous, Toxic, and Radioactive Waste

Experiments were conducted to remove palladium (Pd) from molten borosilicate glass (BSG) containing simulated nuclear waste using lead (Pb) or aluminum (Al) as solvent metal. The removal of Pd from molten BSG could be carried out successfully when lead was used as the solvent metal, and the percentage extraction fraction was nearly 100%. Significant quantities of Ni, Mo, and Fe also settled into the solvent metal phase along with Pd. The metal phase found to contain intermetallic compounds of ${\mathrm{Pb}}_2\mathrm{Pd}$ and ${\mathrm{Pb}}_9{\mathrm{Pd}}_{13}$. However, when Al was used as the collecting metal separation of metal and glass phase did not occur. The results of the experiments are interpreted based on the thermodynamic stabilities of the oxides of the collecting metals and the constituent elements in the molten BSG. Even though the experiments were conducted in argon atmosphere, the traces of oxygen present in the Ar are sufficient to oxidize Al metal powder to its oxide, leading to the formation of alumino-silicates (mullites) in molten BSG.

Simulation of a virus transport process in a groundwater aquifer is necessary for predicting the movement of viruses in an aquifer. It is also necessary in implementing remedial measures to inactivate viruses present in groundwater. For simulating the virus transport process in a groundwater aquifer, the parameters responsible for movement of viruses in an aquifer have to be estimated. In the case of saturated porous media, the transport parameters are linear distribution coefficient, hydrodynamic dispersion coefficient, and inactivation coefficient for aqueous and sorbed viruses. These parameters can be estimated using an inverse optimization procedure that minimizes an error function represented by the difference between the experimentally observed and simulated virus concentration. Gradient-based classical optimization methods can be applied to minimize the error function for estimating the parameters of the transport process. It is reported that the error function is nonlinear and nonconvex in nature when all four parameters are considered in the model. As such, classical optimization methods are not effective when all four parameters are considered. Global optimization methods, such as genetic algorithms, may be efficient to solve the inverse problem. However, in many cases, these algorithms yield a near global optimal solution. As such, a hybrid optimization model using genetic algorithms and the simplex method is proposed for estimating the parameters. Example problems have been solved to evaluate the efficiency of the proposed method. The evaluation shows that the proposed procedure is efficient and can be applied in the field for estimating parameters of the virus transport process in a groundwater aquifer.

The removal of heavy metal in drinking water was carried out using a new type of cation-exchange resin mixed polyethersulfone (PES) membrane adsorbent. Cation-exchange resins (Type 110-H) were incorporated into the PES porous matrix by the immersion phase separation method. The membrane adsorbents were characterized by the morphology and adsorption capacity. High values of heavy metal ion adsorption capacities of $361.79{\mathrm{mg}\mathrm{Hg}}^{2+}/\mathrm{g}$, $264.33{\mathrm{mg}\mathrm{Pb}}^{2+}/\mathrm{g}$, and $94.75{\mathrm{mg}\mathrm{Cu}}^{2+}/\mathrm{g}$ were obtained by the static adsorption test. The dynamic capacity experiment was performed by flowing the ${\mathrm{Cu}}^{2+}$ solution through a stack of three pieces of flat-sheet membranes. The ${\mathrm{Cu}}^{2+}$ mass adsorbed per unit of membrane bed was calculated at a breakthrough concentration (20% of the feed concentration). The dynamic ${\mathrm{Cu}}^{2+}$ binding capacity was $6.25\mathrm{mg}/\mathrm{g}$ membrane, and the desorption rate of the membrane adsorbent was up to 97.6%. The adsorption isotherm was fitted with the Langmuir model with a maximum adsorption capacity of $161.29{\mathrm{mg}\mathrm{Cu}}^{2+}/\mathrm{g}$ of the membrane.

Industrial and urban development is a common cause of increased pollution. Pollutants are in many instances discharged untreated to rivers due to lack of adequate treatment facilities and high treatment cost. In many cases, the detriment of pollution discharge to a river exceeds its self-purification capacity, and it may cause irreparable damages to the riverine environment. In this regard, water flow in a river is an effective characteristic behind its assimilative capacity that can be used to decrease pollution damages. Determining a river’s assimilation capacity and the flow necessary for dilution of pollutants are important tasks. In this paper, pollution damage to a riverine environment is a function of the pollutant’s concentration and the contact duration with river water. Pollutant transport in a river is simulated based on mathematical equations of pollutant advection-dispersion. The optimum values of a river’s assimilation capacity and the dilution flow required in a river to mitigate pollution are determined using a nonlinear programming (NLP) method and the nondominated sorting genetic algorithms II (NSGA-II). The optimum assimilation capacity of a river was calculated in an application example for different reservoir releases. The results show that the magnitude of river flow can improve the total riverine assimilation capacity by up to 80%. Optimal Pareto boundaries were obtained for pollutant concentration and the duration of pollutant contact by means of river flow adjustment.

Hydrous bismuth oxides (HBOs) have the sorptive property to remove nitrate from water. HBOs are also efficient in removing other competitive anions like bicarbonates and sulfates from water. To use HBOs as sorptive filtration media, their characteristics in terms of crystallinity and particle size are important. The objective of this study was to explore the kinetic and equilibria study of HBOs for the removal of nitrate from water. For the present study, three hydrous bismuth oxides, ${\mathrm{HBO}}_1$, ${\mathrm{HBO}}_2$, and ${\mathrm{HBO}}_3$, were prepared under increasing volumetric presence of hydroxide. Both ${\mathrm{HBO}}_2$ and ${\mathrm{HBO}}_3$ were found to be almost equally efficient for nitrate removal from aqueous solutions. Because ${\mathrm{HBO}}_2$ is a superior bismuth oxide, kinetic and equilibrium studies were performed with ${\mathrm{HBO}}_2$. X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and scanning electron microscopy (SEM) techniques were used to characterize the adsorbents. The pH of point of zero charge (${\mathrm{pH}}_{\text{PZC}}$) of the HBOs also supported the results of the removal of nitrate.

The presence of toxic hexavalent chromium poses a great challenge in the wastewater pretreatment of agricultural irrigation. The feasibility of using fine-grained sands as suitable filling materials in the permeable barrier filter was studied for the effective containment of hexavalent chromium. Based on the governing equations representing seepage-field coupled concentration-field, a physical model composed of the fine-grained sands ranging from 0.075–0.5 mm was tentatively designed to remove hexavalent chromium in the permeable barrier filters. The column physical model experiments of 0.5, 0.2, 0.1, and 0.075-mm sands were separately performed under low velocity of $14.92\mathrm{cm}{\mathrm{day}}^{-1}$, moderate velocity of $29.84\mathrm{cm}{\mathrm{day}}^{-1}$, and high velocity of $44.76\mathrm{cm}{\mathrm{day}}^{-1}$. The results were verified by numerical simulations under the corresponding experimental condition. According to the removal efficiency and hydraulic retention time of each sand model, 0.5, 0.2, and 0.1-mm sands were chosen as ideal materials to fill the permeable fine-grained sand barrier. By comparing single sand and combinatorial sands barrier filter, 0.5, 0.2, and 0.1-mm combinatorial sands extensively controlled flow velocity and slightly decreased hydraulic retention time in order to reach the same removal rate. To reach effluent hexavalent chromium concentration $0.01\mathrm{mg}{\mathrm{L}}^{-1}$, single sand barrier filer should control velocity of $14.92–22.38\mathrm{cm}{\mathrm{day}}^{-1}$ and take 60 h; however, combinatorial sands barrier filter should control velocity of $7.46–44.76\mathrm{cm}{\mathrm{day}}^{-1}$ and take 48 h. Therefore, combinatorial sands have more potential for usage as filling materials in the permeable barrier filters to meet agricultural irrigation water quality standard.

Soybean biodiesel with blends of B05 [5% biodiesel, 95% ultra-low-sulfur diesel (ULSD) or B00] and B20 (20% biodiesel and 80% ULSD) and ULSD were combusted in a closed chamber at 260 and 290°C (500 and 550°F) and 2.0 and 2.4 MPa (300 and 350 psi). B05 and B20 were selected because they are the most common biodiesel blends and very little has been reported on the emission compositions of these blends under various combustion conditions. CO, ${\mathrm{CO}}_2$, and ${\mathrm{CH}}_4$ emissions and elements of particulate matter (PM) were analyzed. ${\mathrm{CO}}_2$ emissions from B20 were more sensitive to temperature changes at low pressure. For both B00 and B20, decreases in the CO concentration were observed when combusted at high temperature and pressure. An increase in biodiesel blends appeared to reduce CO and increase ${\mathrm{CO}}_2$ emissions. For all the samples tested, the concentrations of Al, Ca, Cr, Na, S, and Si were higher than those of other elements in PM. The PM element concentrations founds in both B00 and B20 emissions were almost the same, except for Cu, Ga, and K, which were observed in high concentrations in B20 combustion.

Water pollution is one of the major problems in providing and preserving water resources, so identifying the pollution source plays a critical role in regulation actions. Thus, this paper addresses the process of pollution source identification, including location, concentration, and the time of injection in surface water by using a data-mining method [artificial neural network (ANN)] and optimization techniques [genetic algorithm (GA) and pattern search (PS)]. The CE-QUAL-W2 numerical model is used to produce input and output data in ANN and simulation models. To check the capability of the methodology, the identification of various hypothetical examples of pollution with several forms of injection of the pollutant in a nonprismatic water canal is performed. Results of data-driven and optimization methods are evaluated by employing statistical criteria. Final results show that the ANN method is capable of identifying a pollutant injection hydrograph and it is relatively sensitive to the accuracy of monitoring so that like the optimization method for errorless data, the determination coefficient ($R^2$) is nearly 100%, and the absolute average relative error (AARE) and total error ($E$) are nearly zero. If there is more than one active pollutant injection source and evaluation of the pollutant concentration is accompanied with errors, the optimization method gives better results than ANN so that in pollutant sources and for errors of 5 and 10%, the statistic AARE in the optimization method is less than 3.7 and 5.7% while in ANN it is less than 10.1 and 14.3%. If not all of the pollutant sources are active, the optimization method can well identify the inactive source even in several levels of error, while ANN can only identify the inactive source if there is no error.

Widespread production and use of industrial solvents and liquid petroleum products have created problems of subsurface contamination by nonaqueous phase liquids (NAPLs). The objective of this study is to relate NAPL dissolution dynamics to temporal variations of groundwater flux in the NAPL source zone. The approach is based on the idea that the source zone NAPL mass discharge into the aqueous phase is related to the temporal variations of the NAPL source zone groundwater flux. By incorporating this new idea, the NAPL source dynamics including source zone contaminant concentrations, reduction in the NAPL mass discharge to the aqueous phase, reduction in the NAPL mass in the source zone can be effectively related. In illustrating the new model development, an exponential form of the NAPL source zone groundwater flux is used to accommodate a range of potential temporal variations of groundwater flux. These models simply predict how NAPL source zone characteristics change with time, which can be easily used in modeling subsequent fate and transport. The models developed have automatically taken in account the requirement of NAPL mass conservation. Based on the developed models, this paper discusses how source zone contaminant concentrations, NAPL mass discharge, and remaining NAPL mass in the source zone are interrelated. Preliminary comparison with field data demonstrates that the models are capable of capturing the source zone NAPL discharge dynamics.