Removal of iron and manganese from groundwater sources using nano-biosorbents

Background The presence of iron (Fe) and manganese (Mn) ions in rocky beds leads to groundwater pollution. Moreover, their excessive concentration causes bad taste and color stains of water. Methods Tea leaves-derived char (TLC), rice straw-derived char (RSC), and nanosilica (NS) were used to adsorb Fe and Mn ions from water sources. The effects of parameters such as contact time, composition percentage, and particle size of biosorbents in a fixed-bed adsorption column were investigated. Results The study on the adsorption of Fe and Mn ions showed that the amount of adsorption increased significantly by decreasing the particle size. Furthermore, the combination of nano-biosorbents with nanosilica improved the adsorption. The Thomas and Adams–Bohart models adequately indicated the adsorption of Fe and Mn ions onto nano-biosorbents in the column mode. The TLC and RSC with NS are applicable for the removal of Fe and Mn ions from groundwater. Conclusions According to the BET analysis results, with more crushing of biosorbents by ball mill and placing them in the furnace, specific surface area of tea leaves and rice straw increased from 0.29 to 3.45 and from 3.70 to 10.99 m2/g, respectively. The absorption of iron and manganese from the aqueous solution increased with the percentage of nano-silica. According to breakthrough curves, under best conditions (the seventh mode), nano-biosorbents could remove 98.05% and 97.92% of iron and manganese ions, respectively. The maximum equilibrium capacity of the adsorption column (mg/g) was 256.56 for iron and 244.79 for manganese. Graphical abstract

Comparison of Nature and Synthetic Zeolite for Waste Battery Electrolyte Treatment in Fixed-Bed Adsorption Column

To support a sustainable energy development, CO2 reduction for carbon neutralization and water-splitting for hydrogen economy are two feasible technical routes, both of which require a significant input of renewable energies. To efficiently store renewable energies, secondary batteries will be applied in great quantity, so that a considerable amount of energy needs to be invested to eliminate the waste battery electrolyte pollution caused by heavy metals including Cu2+, Zn2+ and Pb2+. To reduce this energy consumption, the removal behaviors of these ions by using clinoptilolite and zeolite A under 5, 7 and 10 BV h−1 in a fixed-bed reactor were investigated. The used zeolites were then regenerated by a novel NH4Cl solution soaking, coupled with the ultrasonication method. Further characterizations were carried out using scanning electron microscopy, N2 adsorption and desorption test, and wide-angle X-ray diffraction. The adsorption breakthrough curves revealed that the leaching preference of clinoptilolite was Pb2+ > Cu2+ > Zn2+, while the removal sequence for zeolite A was Zn2+ > Cu2+ > Pb2+. The maximum removal percentage of Zn2+ ions for clinoptilolite under 5 BV h−1 was 21.55%, while it was 83.45% for zeolite A. The leaching ability difference was also discussed combining with the characterization results. The fact that unit cell stayed the same before and after the regeneration treatment approved the efficacy of the regeneration method, which detached most of the ions while doing little change to both morphology and crystallinity of the zeolites. By evaluating the pH and conductivity changes, the leaching mechanisms by adsorption and ion exchange were further studied.

Cadmium Removal from Giant Squid (Dosidicus gigas) Hydrolysate in Fixed-Bed Columns Packed with Iminodiacetic Resin: Tools for Scaling up the Process

Giant squid hydrolysate (GSH) elaborated from different batches from a fishing company was evaluated for cadmium removal. Fixed-bed column packed with iminodiacetic resin as adsorbent was used. GSH solution at different cadmium concentrations were fed in the fixed-bed column and breakthrough curves were evaluated. A high degree of metal removal from the solution was achieved and the saturation point (Ce/C0 ≤ 0.8) was achieved more quickly at higher concentrations of cadmium. The maximum capacity of adsorption (q0) was obtained using the Thomas model, where 1137.4, 860.4, 557.4, and 203.1 mg g−1 were achieved using GSH with concentrations of 48.37, 20.97, 12.13, and 3.26 mg L−1, respectively. Five cycles of desorption of the resin with HCl (1 M) backflow and regeneration with NaOH (0.5 M) were also evaluated, where no significant differences (p-value > 0.05) were observed between each cycle, with an average of 935.9 mg g−1 of qmax. The in-series columns evaluated reached a total efficiency of 90% on average after the third column in GSH with a cadmium concentration of 20.97 mg L−1. This kind of configuration should be considered the best alternative for cadmium removal from GSH. Additionally, the chemical composition of GSH, which was considered a quality parameter, was not affected by cadmium adsorption.

Biochar alters hydraulic conductivity and impacts nutrient leaching in two agricultural soils

Biochar is purported to provide agricultural benefits when added to the soil, through changes in saturated hydraulic conductivity (Ksat) and increased nutrient retention through chemical or physical means. Despite increased interest and investigation, there remains uncertainty regarding the ability of biochar to deliver these agronomic benefits due to differences in biochar feedstock, production method, production temperature, and soil texture. In this project, a suite of experiments was carried out using biochars of diverse feedstocks and production temperatures, in order to determine the biochar parameters which may optimize agricultural benefits. Sorption experiments were performed with seven distinct biochars to determine sorption efficiencies for ammonium and nitrate. Only one biochar effectively retained nitrate, while all biochars bound ammonium. The three biochars with the highest binding capacities (produced from almond shell at 500 and 800 ∘C (AS500 and AS800) and softwood at 500 ∘C (SW500)) were chosen for column experiments. Biochars were amended to a sandy loam and a silt loam at 0 % and 2 % (w/w), and Ksat was measured. Biochars reduced Ksat in both soils by 64 %–80 %, with the exception of AS800, which increased Ksat by 98 % in the silt loam. Breakthrough curves for nitrate and ammonium, as well as leachate nutrient concentration, were also measured in the sandy loam columns. All biochars significantly decreased the quantity of ammonium in the leachate, by 22 % to 78 %, and slowed its movement through the soil profile. Ammonium retention was linked to high cation exchange capacity and a high oxygen-to-carbon ratio, indicating that the primary control of ammonium retention in biochar-amended soils is the chemical affinity between biochar surfaces and ammonium. Biochars had little to no effect on the timing of nitrate release, and only SW500 decreased total quantity, by 27 % to 36 %. The ability of biochar to retain nitrate may be linked to high micropore specific surface area, suggesting a physical entrapment rather than a chemical binding. Together, this work sheds new light on the combined chemical and physical means by which biochar may alter soils to impact nutrient leaching and hydraulic conductivity for agricultural production.

Machine Learning Models to Predict Early Breakthrough of Recalcitrant Organic Micropollutants in Granular Activated Carbon Treatment of Water

Granular activated carbon (GAC) adsorption is frequently considered to control recalcitrant organic micropollutants (MPs) in both drinking water and wastewater. To predict full-scale GAC adsorber performance, bench- and/or pilot- scale studies are widely used. These studies have generated a wealth of MP breakthrough curves. The overarching aim of this research was to develop machine learning (ML) models from these data to predict MP breakthrough from adsorbent, adsorbate, and background water matrix properties. These models provide a simple and fast tool to predict GAC performance. To develop information for model calibration, MP breakthrough curves were collected from the peer-reviewed literature, research reports, and engineering reports. These data sets, which included results from rapid small-scale column tests (RSSCTs) and pilot/full-scale adsorbers, were analyzed to determine the bed volumes of water that could be treated until MP breakthrough reached ten percent of the influent MP concentration (BV10). The data set encompassed 43 MPs (including neutral and ionizable organic compounds), 3 GAC types by base material (18 unique GAC products), and 38 water matrices, including groundwater, surface water, and treated wastewater. Approximately 400 data sets were split into training, validation, and test sets. Seventeen candidate features, such as MP properties (Abraham parameters), background water matrix characteristics, and GAC properties, were explored in ML models to predict log-10-transformed BV10 (logBV10). BV10 values obtained from the resulting predictive model were highly correlated with experimentally determined BV10 values (coefficient of determination ~0.89 for logBV10 prediction), and the most effective model predicted BV10 with an absolute mean error of ~ 0.11 log units. Key drivers influencing BV10 prediction included the MP’s partitioning coefficient between air and hexadecane (Abraham parameter L); dissolved organic matter concentration in background water matrix; and the adsorbent’s point of zero charge (pzc). The model can be used to estimate GAC bed life and select effective GACs for the removal of MPs such as per- and polyfluoroalkyl substances (PFASs), pesticides, pharmaceuticals, and volatile organic compounds (VOCs) in a wide range of water types.

Alternative Materials for the Enrichment of Biogas with Methane

Carbonaceous adsorbents have been pointed out as promising adsorbents for the recovery of methane from its mixture with carbon dioxide, including biogas. This is because of the fact that CO2 is more strongly adsorbed and also diffuses faster compared to methane in these materials. Therefore, the present study aimed to test alternative carbonaceous materials for the gas separation process with the purpose of enriching biogas in biomethane and to compare them with the commercial one. Among them was coconut shell activated carbon (AC) as the adsorbent derived from bio-waste, rubber tire pyrolysis char (RPC) as a by-product of waste utilization technology, and carbon molecular sieve (CMS) as the commercial material. The breakthrough experiments were conducted using two mixtures, a methane-rich mixture (consisting of 75% CH4 and 25% CO2) and a carbon dioxide-rich mixture (containing 25% CH4 and 75% CO2). This investigation showed that the AC sample would be a better candidate material for the CH4/CO2 separation using a fixed-bed adsorption column than the commercial CMS sample. It is worth mentioning that due to its poorly developed micropore structure, the RPC sample exhibited limited adsorption capacity for both compounds, particularly for CO2. However, it was observed that for the methane-rich mixture, it was possible to obtain an instantaneous concentration of around 93% CH4. This indicates that there is still much potential for the use of the RPC, but this raw material needs further treatment. The Yoon–Nelson model was used to predict breakthrough curves for the experimental data. The results show that the data for the AC were best fitted with this model.

Mathematical Tool Based on Breakthrough Curves to Evaluate the Economic Advantages of Chemical Regeneration of Activated Carbon in Power Plants: A Comparative Study

A mathematical tool has been developed to evaluate the economic advantages of in-situ chemical regeneration of fixed-bed industrial adsorbers of granular activated carbon for cooling water treatment systems in Cuban power plants. Two scenarios of activated carbon (AC) management in a power plant were compared by applying the proposed model. The economic profit by implementing the regeneration strategy as a function of the number of regeneration cycles was determined and optimized. Breakthrough curves were obtained to assess the adsorption performance of the AC after progressive saturation–chemical regeneration cycles using synthetic water and hydrochloric acid, respectively. For the first saturation cycle, the breakthrough time was 272 min and after 10 cycles, it was reduced to 58 min, indicating a decrease of the adsorption capacity of 21%. The AC adsorption performance in terms of saturation time as a function of the number of regeneration cycles was considered one of the tool parameters. The proposed tool allows to determine the optimal number of regeneration cycles for a maximum economic profit in the regeneration strategy. It was demonstrated, using the proposed tool, that after an optimum of seven regeneration cycles, the power plant expends only 26% of the total investment. The simplicity of the tool permits a rapid way to find the most profitable number of regeneration cycles by combining economic, technical and adsorption efficiency parameters in one function, thus improving the AC management strategy at an industrial scale with corresponding environmental and economic advantages, including sustainability.

Assessment of The Dioxins Leaching Potentials In Selected Soils Through Breakthrough Curves (BTCs) Model

The current study was to investigate the leaching and groundwater contamination potential of selected Dioxins, in local soil series. Solute transport was modelled through Breakthrough curve (BTC) plots, based on distribution coefficient (Kd), Retardation factor and Dispersivity, under normal velocity (20 cm day -1) and preferential or steady flow (50 cm day -1). In case of Dibenzo -p- Dioxin (DD), distribution coefficient values were found in order of Charsadda > Peshawar > Sultanpur series, while for 2 Chloro- p- Dioxin (2Cl-DD), the order was Charsadda > Sultanpur > Peshawar. However, the overall sorption was low. Under the normal velocity both of selected Dioxins (DD & 2Cl-DD), BTC plots relatively took longer time to reach the point of saturation as compared to high seepage velocity. However, the overall solute transport was found to be rapid. This behaviour showed that sorption of the Dioxins selected soil series is low and there is potential for leaching and groundwater contamination.

Deactivation Model Study of High Temperature H2S Wet-Desulfurization by Using ZnO

High-temperature desulfurization techniques are fundamental for the development of reliable and efficient conversion systems of low-cost fuels and biomass that answer to the nowadays environmental and energy security issues. This is particularly true for biomass gasification coupled to SOFC systems where the sulfur content has to be minimized before being fed to the SOFC. Thus, commercially available zinc oxide has been studied and characterized as a desulfurizing agent in a fixed-bed reactor at high temperatures from 400 °C to 600 °C. The sorbent material was characterized by XRD, BET, SEM, and EDS analyses before and after adsorption. The sorbent’s sorption capacity has been evaluated at different temperatures, as well as the breakthrough curves. Moreover, the kinetic parameters as the initial sorption rate constant k0, the deactivation rate constant kd, and the activation energy have been calculated using the linearized deactivation model. The best performances have been obtained at 550 °C, obtaining a sorption capacity of 5.4 g per 100 g of sorbent and a breakthrough time of 2.7 h. These results can be used to extend ZnO desulfurization techniques to a higher temperature than the ones used today (i.e., 550 °C with respect to 400 °C).