Breakthrough Curves Research Articles

Equilibrium adsorption, kinetic, thermodynamic, and breakthrough curves modelling of acetaminophen on Elaeagnus Angustifolia L. seeds-based granular activated carbon

ABSTRACT The widespread presence of pharmaceutical compounds as emerging environmental contaminants in aquatic environments has become a significant concern in recent years. In this study, synthesised granular activated carbon (GAC) derived from Elaeagnus Angustifolia L. seeds was utilised as an adsorbent to remove an emerging contaminant, acetaminophen (commercially known as paracetamol). The operating conditions for the chemical synthesis of the GAC, utilising ZnCl2 as an activating agent, included an impregnation ratio of 1:1, carbonisation at 500°C for 1 hour, and a heating rate of 5 °C/min. The efficacy of this adsorbent was assessed through both batch and fixed-bed column adsorption experiments under various operational parameters, including adsorbent mass (1–6 g/L), contact time, pH (2–10), temperature (20–60°C), inlet acetaminophen concentration (20–150 mg/L), and flow rate (0.5–1.5 mL/min). The results indicate that acetaminophen was better adsorbed in its neutral form rather than in its dissociated state. The findings also revealed that both the Langmuir (two-parameter) and Sips (three-parameter) models provided the best fit for the static adsorption equilibrium data. Furthermore, kinetic analysis indicated that the experimental data were best modelled by the Elovich model and governed by both external diffusion and intraparticle diffusion mechanisms. Therefore, the Yan-Viraraghavan model provided a good fit for the experimental breakthrough curves under various operating conditions. However, the adsorbed amounts of acetaminophen obtained from the column experiment indicated that the high-adsorbed amount of 204.11 mg/g was achieved with an inlet acetaminophen concentration of 150 mg/L, a bed depth of 6 cm, and a flow rate of 0.5 mL/min. These results highlight the potential of the synthesised GAC as a promising adsorbent for pharmaceutical wastewater treatment using fixed-bed column systems.

Enhancing slow sand filtration for safe drinking water production: interdisciplinary insights into Schmutzdecke characteristics and filtration performance in mini-scale filters

The demand for safe drinking water is constantly challenged by increasing biohazards. One widely used solution is implementing indoor-operated slow sand filtration (SSF) as one of the final barriers in water production. SSF has gained popularity due to its low energy consumption and efficient removal of biohazards, especially microorganisms, without using chemicals. SSF involves both physical-chemical and biological removal, particularly in the “Schmutzdecke”, which is a biofilm-like layer on the sand bed surface. To achieve the optimal performance of SSF, a systematic understanding of the influence of SSF operating parameters on the Schmutzdecke development and filter filtration performance is required. Our study focused on three operational parameters, i.e., sand material, sand size, and the addition of an inoculum (suspension of matured Schmutzdecke), on the mini-scale filters. The effects of these parameters on the Schmutzdecke development and SSF removal performance were studied by biochemical analyses and 16S amplicon sequencing, together with spiking experiments with Escherichia coli (E. coli) in the mini-scale filters. Our results indicate that the mini-scale filters successfully developed Schmutzdeckes and generated bacterial breakthrough curves efficiently. The sand size and material were found to have an impact on Schmutzdecke's development. The addition of inoculum to new filters did not induce significant changes in the microbial community composition of the Schmutzdecke, but we observed positive effects of faster Schmutzdecke development and better removal performance in some inoculated filters. Our study highlights the value of mini-scale filters for SSF studies, which provide insights into Schmutzdecke microbial ecology and bacterial removal with significantly reduced requirements of materials and effort as compared to larger-scale filters. We found that operational parameters have a greater impact on the Schmutzdecke biochemical characteristics and removal performances than on the microbial community composition. This suggests that Schmutzdecke characteristics may provide more reliable predictors of SSF removal performance, which could help to improve safe drinking water production.

Unraveling the separation mechanism of gas mixtures in MOFs by combining the breakthrough curve with machine learning and high-throughput calculation

In the field of metal–organic frameworks (MOFs) screening studies, the batch calculation of the mixed gas breakthrough time difference (ΔTi) in MOFs and its intricate correlation with various descriptors remain underexplored. This research undertook batch calculations of the breakthrough curves (BC) for different gases within a simulated natural gas environment, designating ΔTi as the performance metric for MOFs in gas separation. The separation performance of computation-ready experimental MOFs for CH4/C2H6 and CH4/CO2 mixtures was analyzed in depth utilizing machine learning (ML)-assisted high-throughput computational screening (HTCS) techniques. Then, five ML algorithms were used to quantify the relationship between MOF descriptors and performance, and the effect of the metal center site on the separation performance was further explored. Ultimately, the top ten MOFs were selected for each system. Combining HTCS, ML, and BC, this work provides fresh insights for understanding and designing MOFs with customized adsorption and separation properties.

Adsorption of steroid hormone micropollutant by polyethersulfone ultrafiltration membranes with varying morphology

The effective removal of micropollutants necessitates the use of dense membranes, such as thin-film composite (TFC) reverse osmosis (RO) and nanofiltration (NF) membranes. TFCs have a polyamide active layer interfacially polymerized on a support layer that is typically made of polysulfone (PSu) or polyethersulfone (PES). Retention by NF and RO is often incomplete because micropollutants are adsorbed to the polymer material and subsequently permeate via a combination of convection and diffusion, which evidences a breakthrough curve. When describing breakthrough phenomena, the role of the support membrane is commonly neglected, even though the adsorption in this layer can be significant. This work investigated the adsorption of steroid hormone micropollutants (17β-estradiol, E2) by fabricated and commercial PES ultrafiltration membranes with varying morphology.By increasing the coagulation bath temperature between 10 and 70 °C, the pure water permeability increased from 13 to 3800 L/m2·h−1·bar−1, and consequently, the average pore size rose from 12 to 191 nm. The fabricated membranes with smaller pore sizes showed higher E2 removal via adsorption which can be attributed to the higher internal surface area. The adsorbed mass of fabricated PES membranes (using dimethylformamide (coded as PDG) and N-methyl-2-pyrrolidone (coded as PNG) and PES (Istanbul Technical University (ITU), with non-woven supports) varies from 0.30 to 0.60, 0.27–0.60 and 1–1.2 ng·cm−2, respectively. These values are lower than the adsorbed masses with commercial Biomax (Millipore Inc.) membranes (0.5–2.0 ng·cm−2). Ultrafiltration membranes used as support for composite membranes, nanofiltration or as filters in sample preparation benefit from lower micropollutant adsorption.

Efficiently selective adsorption Rb(I) based on ion-imprinted membrane chromatography: Batch adsorption and dynamic filtration

The development of efficient separation and enrichment methods for rare and precious metal rubidium (Rb) has attracted more and more attention the hydrometallurgy. Here, based on the phenolic hydroxyl-rich copolymer poly(styrene-co-4-hydroxylstyrene) (P(S-co-VPh)), the Rb+ imprinting nanofiber membrane (P(S-co-VPh)-(IIP)) was prepared using electrostatic spinning. NMR, FTIR, XPS, FESEM and EDS were used to comprehensively characterize the composition and structure of the copolymer and nanofiber membranes. Batch adsorption results indicated that the optimal adsorption conditions were pH = 9 at room temperature, and the process of Rb+ adsorption was spontaneous exothermic reaction. Ion imprinting technology not only enhanced adsorption capacity and recycling performance of the P(S-co-VPh20)-(IIP) membrane, but more importantly, significantly improved its selectivity, so that the selectivity coefficient (β) of Rb+/Mn+ for the interfering ions Na+, Mg2+, Ca2+, and K+ were 1438.17, 864.38, 434.6, and 307.25, respectively. The adsorption kinetics fitted well to the pseudo-second-order rate expression, and the maximum theoretical adsorption capacity (qm) could reach 140.00 mg/g from the Langmuir model fitting. The dynamic filtration experiment of the stacked membranes chromatography indicated that the breakthrough times were significantly affected by the different operation conditions (Flow rate, initial Rb+ concentration and membrane dosage). Among the four typical models of Thomas, Yoon-Nelson, EXY and BJP, the breakthrough curves can be well described by the EXY model.

Ag+ anchored on hyper-crosslinked polymers as sorbent for C6, C7 and C8 olefin/paraffin separation

Liquid phase olefin/paraffin (O/P) separation has been less investigated thus far with respect to the gas phase counterparts, and the porous materials sorbents are limited to zeolites or metal organic frameworks (MOFs). Here, we designed Ag+ anchored on sulfonic group modified hyper-crosslinked polymers as sorbents for liquid olefin/paraffin (O/P) separation. Isotherms and breakthrough curves for adsorption measurement from 1-hexene/n-hexane mixture demonstrate that the adsorption capacity and separation factor increased with increasing adsorption site density. Comparisons to the homologue binary O/P series of C7 and C8 show that both adsorption capacity and separation factor decline with increasing carbon chain length.

Greedy Kernel Methods for Approximating Breakthrough Curves for Reactive Flow from 3D Porous Geometry Data

Greedy Kernel Methods for Approximating Breakthrough Curves for Reactive Flow from 3D Porous Geometry Data

Efficient PFAS removal from contaminated soils through combined washing and adsorption in soil effluents

This study investigates soil washing as a viable strategy to remove poly- and perfluoroalkyl substances (PFAS) from contaminated soils using various washing agents including water, methanol, ethanol, and cyclodextrin ((2-Hydroxypropyl)-β-cyclodextrin HPCD)). Water was less effective (removing only 30 % of PFAS), especially for long-chain hydrophobic PFAS. Methanol (50 % v/v) or HPCD (10 mg g–1 soil) achieved > 95 % PFAS removal regardless of PFAS type, soil size fraction (0–400 µm or 400–800 µm), or experimental setups (batch or column, at liquid/solid (L/S) = 1). Column optimization studies revealed improved efficiency at L/S = 10 with diluted washing solutions, where HPCD exhibited rapid PFAS mobilization even at lower concentrations (1 mg mL–1). We then applied a first-order decay model to effectively predict PFAS breakthrough curves and mobilization within soil columns. Subsequent treatment of wash effluents by activated carbon and biochar effectively reduced PFAS concentrations below detection limits. The performance of both soil washing and subsequent adsorption was found to depend strongly on the specific characteristics of PFAS compounds. These findings highlight the significant potential of methanol and HPCD in soil washing and the effectiveness of integrated soil washing and adsorption for optimizing PFAS removal.

Comparison of batch and continuous multi-column capture of monoclonal antibodies with convective diffusive membrane adsorbers

Protein A affinity membrane adsorbers are a promising alternative to resins to intensify the manufacturing of monoclonal antibodies. This study examined the process performance of convective diffusive membrane adsorbers operated in batch and continuous multi-column mode. Therefore, three different processes were compared regarding membrane utilization, productivity, and buffer consumption: the batch process, the rapid cycling parallel multi-column chromatography process, and the rapid cycling simulated moving bed process. The influence of the monoclonal antibody loading concentration (between 0.5 g L-1 and 5.2 g L-1) and the loading flow rate (between 1.25 MV min-1 and 10 MV min-1) on the monoclonal antibody binding behavior of the membrane adsorber were studied with breakthrough curve experiments. The determined breakthrough curves were used to calculate the monoclonal antibody dynamic binding capacity, the duration of the loading steps for each process, and the number of required membrane adsorbers for the continuous processes rapid cycling parallel multi-column chromatography and rapid cycling simulated moving bed. The highest productivity for the batch (176 g L-1 h-1) and rapid cycling parallel multi-column chromatography process (176 g L-1 h-1) was calculated for high monoclonal antibody loading concentrations and low loading flow rates. In contrast, the rapid cycling simulated moving bed process achieved the highest productivity (217 g L-1 h-1) for high monoclonal antibody loading concentrations and loading flow rates. Furthermore, due to the higher membrane utilization, the buffer consumption of the rapid cycling simulated moving bed process (1.1 L g-1) was up to 1.9 times lower than that of the batch or rapid cycling parallel multi-column chromatography operation (2.1 L g-1).

Efficient adsorption of lead and copper from water by modification of sand filter with a green plant-based adsorbent: Adsorption kinetics and regeneration

In this study, pomegranate seed waste (PSW) was added into sand filter (SF) to increase removal efficiency of Lead (Pb(II)) and Copper (Cu(II)) from polluted water. The performance of PSW was compared with activated carbon (AC) as a typical adsorbent. Based on the SEM, EDX, FTIR, XRD, BET and proximate analyses, PSW had porous structure with specific surface area of 2.76 m2/g and active compounds which suggested PSW as an appropriate adsorbent for heavy metals (HMs) adsorption. According to the batch experiments, SF without treatment could only remove 46% and 35% of Pb(II) and Cu(II), respectively. These numbers increased to 88% and 75% for Pb(II) and Cu(II) by adding 3 g/kg PSW to the SF, respectively under the optimal conditions of HMs initial concentrations = 100 mg/L, pH = 7 and contact time = 60 min. The adsorption kinetic and isotherm followed the pseudo-first-order and Langmuir models, respectively indicating that mainly physisorption was involved in the HMs adsorption process of PSW. Based on the column experiments (flow rate = 62.5 mL/min), the Pb(II) and Cu(II) removal increased from 14% to 60% and 10%–55%, respectively after 5 pore volumes (40 min) by adding 3 g/kg PSW to the SF. Breakthrough curves matched better with Thomas mode rather than Adam's Bohart proving Langmuir adsorption isotherm. Our finding suggested modification of SF with PSW is a promising approach for efficient removal of HMs from water.

An Imputation Method for Simulating 3D Well Screen Locations from Limited Regional Well Log Data.

In groundwater modeling studies, accurate spatial and intensity identification of water sources and sinks is of critical importance. Precise construction data about wells (water sinks) are particularly difficult to obtain. The collection of well log data is expensive and laborious, and government records of historic well log data are often imprecise and incomplete with respect to the precise location or pumping rate. In many groundwater modeling studies, such as groundwater quality assessments, a precise representation of the horizontal and vertical distribution of well screens is required to accurately estimate contaminant breakthrough curves. The number of wells under consideration may be very large, for example, in the assessment of nonpoint source pollution. In this paper, we propose an imputation framework that allows for proper reconstruction of missing well data. Our approach exploits available information and tolerates data gaps and imprecisions. We demonstrate the value of this method for a subregion of the Central Valley aquifer (California, USA). We show that our framework imputes missing values that preserve statistical properties of available data and that remain consistent with the known spatial distribution of well screens and pumping rates in the three-dimensional aquifer system.

Mathematical modeling of breakthrough curves in dynamic column adsorption: analytical solutions and validation

Mathematical modeling of breakthrough curves in dynamic column adsorption: analytical solutions and validation

Studying the kinetics and removal mechanism of the methylene blue dye in a continuous adsorption process using prepared mesoporous materials

ABSTRACT This study investigated the removal of a typical organic pollutant methylene blue (MB) dye from wastewater by a prepared mesoporous SBA-15 adsorbent in a continuous adsorption system (fixed-bed column). The structural and textural properties of the SBA-15 adsorbent were determined using different characterization techniques. The adsorption of continuous system experiments assessed the bed height effect, initial concentration, and flow rate on a breakthrough curve. The kinetic constants and breakthrough curves were obtained using the Thomas and Yan models. The breakthrough results revealed that SBA-15 has an excellent adsorption efficiency for use in the continuous adsorption system. The findings explain that MB removal achieved the maximum uptake (84 mg/g) at 6 cm of bed height, 0.5 mL/min of flow rate, and 30 mg/L initial concentration of MB. SBA-15 can be efficiently regenerated by calcination and re-employed 5 times in a fixed-bed system without a significant loss in its adsorption capacity of MB from MB solutions. As a result, SBA-15 was determined as the appropriate media to be adsorbent for MB. This study suggests that the prepared SBA-15 is feasible to use effectively for MB removal from the wastewater.

Multicomponent mass transfer modeling of antagonistic binary adsorption of metallic pollutants from water using helical fixed-bed columns

A multicomponent advection-dispersion model was proposed to simulate the breakthrough curves of antagonistic adsorption of zinc, nickel and cadmium cations from water using helical fixed-bed columns packed with bone char. It was formulated using a linear driving force model, empirical multicomponent Langmuir-based isotherm and retardation coefficient to correlate the experimental breakthrough curves obtained for different binary (metal 1 + metal 2) aqueous solutions, which showed a higher asymmetry degree because of the antagonistic adsorption and axial dispersion impact in this complex fixed-bed configuration. Several parameters of this model were handled as column feed concentration dependent to improve the results of data fitting. The experimental results indicated the presence of a strong antagonistic adsorption effect of zinc and cadmium cations, causing the nickel breakthrough curves to show a clear desorption process (i.e., a displacement effect of the ions already adsorbed on the bone char surface commonly known as roll up) during helical column operation. Experimental bed adsorption capacities ranged from 0.03 to 0.74 mmol/g. The proposed advection-dispersion model fitted the experimental breakthrough profiles satisfactorily for the tested binary adsorption systems, including the desorption zone where the mean modeling errors were lower than 10 % for tested mixtures. Several column operation and mass transfer parameters were calculated and discussed to analyze the separation performance of the tested helical fixed-bed bone char columns. These results suggest that the proposed advection-dispersion model can simulate the multicomponent antagonistic adsorption of relevant water pollutants using intensified adsorption equipment such as helical fixed-bed columns.

Continuous flow column adsorption and desorption for the study of interaction of fluoroquinolone antibiotic ofloxacin hydrochloride with ZnO and CuO nanometal oxides in aqueous solution: (Continuous column adsorption desorption)

Broad-spectrum antibiotic, major veterinary medicines, due to large consumption and inappropriate disposal contribute a major part in generation of pharmaceutical pollutants in aquatic environment. The study investigates the interaction of nanometal oxides for adsorption and desorption of Fluoroquinolone antibiotic, ofloxacin hydrochloride from aqueous solution using vertical and sequential bed adsorption columns: designing parameters of adsorption column determined using bed depth service time model. To optimize the continuous flow column adsorption, varying initial drug concentration and flow rates have been studied using ZnO and CuO nanoparticles at pH 4, already determined for optimized batch studies. To access the characteristic behaviour of breakthrough curves, Thomas model and Yoon-Nelson models have been studied, which were in good agreement with experimental data. Sequential bed column shows slightly better results than vertical bed column as the sequential bed is simple and economical, the solution flows in continuous manner under gravity without any mechanical devices and come into contact with fresh adsorbent bed having same amount as that in vertical bed. Therefore sequential bed column can consider in small scale industries for pharmaceutical wastewater treatment. Column desorption experiments have also been carried out by using HCl/NaOH as desorbing agent for the regeneration of drug loaded adsorbent column.

The bimolecular reactive transport in heterogeneous porous media: Sub-diffusion in interpretation of laboratory experiment

This present work consists of investigating the effects of particle size heterogeneity and flow rates on transport-reaction kinetics of CuSO4 and Na2EDTA2− in porous media, via the combination of a bimolecular reaction experiment and model simulations. In the early stages of transport, a peak is observed in the concentration breakthrough curve of the reactant CuSO4, related to the delayed mixing and reaction of the reactants. The numerical results show that an increase in flow rate promotes the mixing processes between the reactants, resulting in a larger peak concentration and a slighter tail of breakthrough curves, while an increase in medium heterogeneity leads to a more significant heavy tail. The apparent anomalous diffusion and heavy-tailing behavior can be effectively quantified by a novel truncated fractional derivative bimolecular reaction model. The truncated fractional-order model, taking into account the incomplete mixing, offers a satisfactory reproduction of the experimental data.

Characterization and Performance of Peanut Shells in Caffeine and Triclosan Removal in Batch and Fixed-Bed Column Tests.

Peanut shells' adsorption performance in caffeine and triclosan removal was studied. Peanut shells were analyzed for their chemical composition, morphology, and surface functional groups. Batch adsorption and fixed-bed column experiments were carried out with solutions containing 30 mg/L of caffeine and triclosan. The parameters examined included peanut shell particle size (120-150, 300-600, and 800-2000 µm), adsorbent dose (0.02-60 g/L), contact time (up to 180 min), bed height (4-8 cm), and hydraulic loading rate (2.0 and 4.0 m3/m2-day). After determining the optimal adsorption conditions, kinetics, isotherm, and breakthrough curve models were applied to analyze the experimental data. Peanut shells showed an irregular surface and consisted mainly of polysaccharides (around 70% lignin, cellulose, and hemicellulose), with a specific surface area of 1.7 m2/g and a pore volume of 0.005 cm3/g. The highest removal efficiencies for caffeine (85.6 ± 1.4%) and triclosan (89.3 ± 1.5%) were achieved using the smallest particles and 10.0 and 0.1 g/L doses over 180 and 45 min, respectively. Triclosan showed easier removal compared to caffeine due to its higher lipophilic character. The pseudo-second-order kinetics model provided the best fit with the experimental data, suggesting a chemisorption process between caffeine/triclosan and the adsorbent. Equilibrium data were well-described by the Sips model, with maximum adsorption capacities of 3.3 mg/g and 289.3 mg/g for caffeine and triclosan, respectively. In fixed-bed column adsorption tests, particle size significantly influenced efficiency and hydraulic behavior, with 120-150 µm particles exhibiting the highest adsorption capacity for caffeine (0.72 mg/g) and triclosan (143.44 mg/g), albeit with clogging issues. The experimental data also showed good agreement with the Bohart-Adams, Thomas, and Yoon-Nelson models. Therefore, the findings of this study highlight not only the effective capability of peanut shells to remove caffeine and triclosan but also their versatility as a promising option for water treatment and sanitation applications in different contexts.

Simultaneous removal of Ni2+ and Congo red from wastewater by crystalline nanocellulose - Modified coal bionanocomposites: Continuous adsorption study with mathematical modeling

Due to ultra-fast technological improvement and rapid urbanization nowadays, industries have generated a huge amount of wastewater that is discharged directly into the environment. Resulting in harsh damage to ecology and public safety/security by contaminating the ground/surface water sources. Therefore, it is very crucial to purify this wastewater before discharging/reusing. This study will be devoted to the latest enhancements along with the new route of production of the multifunctional Crystalline Nanocellulose-Modified Bituminous Coal (CNC-MC) bionanocomposites. Besides these, the significant implementation of the fabricated CNC-MC bionanosorbents for the simultaneous removal of Ni2+ and Congo red (CR) from bulk-scale industrial wastewater has been stated. Conversely, influential parameters like inlet concentration (25–45 ppm), flow rate (3–5 mL/min), and adsorbent bed height (0.2–0.8 cm) were explored. The bionanosorbents were characterized by using some state-of-the-art equipment such as FTIR-ATR, XRD, BET, FESEM, and TGA analysis, while the water samples were analyzed by AAS and UV-NIR techniques. Results suggested that the fabricated CNC-MC bionanocomposites possessed a considerable amount of active binding sites/functional groups, showed high thermal stability up to 700°C, and had a high crystallinity index (around 92.41 ± 0.009%). They revealed a noteworthy honeycomb-like mesoporous microstructure with a significant specific surface area. Due to these outstanding features, this multifunctional bionanosorbents has exhibited sensational adsorption performance. Meanwhile, the maximum removal efficiency and percentage were observed at approximately 328.7 and 478.3 mg/g, as well as around 67.95 and 76.65% for Ni2+ and CR. The experimental data was evaluated by three well-known column models, namely the Thomas, Adam-Bohart, and Yoon-Nelson models, and respectable agreement was found. That is similarly appropriate for the justification of the experimental breakthrough curve by supporting the Langmuir isotherm and 2nd-order reversible reaction kinetics. Hence, this novel CNC-MC bionanosorbent could be beneficially used to purify industrial wastewater in an economical and eco-friendly way for sustainable environmental safety.

Enhancing predictive understanding and accuracy in geological carbon dioxide storage monitoring: Simulation and history matching of tracer transport dynamics

Co-injection of conservative tracers with carbon dioxide (CO2) is a viable tool for monitoring subsurface processes during geological CO2 storage (GCS). This research investigates the simulation and history-matching of a gas tracer (sulfur hexafluoride, SF6) during CO2 flooding, employing a core flooding result in Berea sandstone. Four extensively used saturation functions are assessed for their efficacy in history matching of CO2/SF6 injection at the core scale. The history-matching process incorporates particle swarm optimization (PSO) to fine-tune constitutive relationships parameters. Next, employing transport models at the aquifer scale, we interrogate the impact on tracer transport and mixing of saturation function uncertainties, arising from the non-uniqueness of constitutive relationships parameters and saturation function types. To assess the effects of geological heterogeneity on behavior of tracer breakthrough curves (BTCs), we employ two normalized parameters assessing the degree of mixing and SF6 breakthrough time. The aquifer-scale investigation encompasses both homogeneous and heterogeneous systems with and without capillary heterogeneity effects. Our findings underscore the critical importance of addressing saturation function uncertainties, emphasizing the significance of auxiliary experiments and innovative methodologies to enhance predictive accuracy. The findings highlight significant disparities in arrival times, BTC peaks, tails, and mixing levels, even under optimal conditions. Heterogeneity, with or without capillary heterogeneity, plays a crucial role in shaping BTC variations, resulting in accelerated SF6 breakthrough times and reduced BTC peaks. Evaluation of monitoring points distant from the injector reveals a dampening effect on the SF6 BTC peak, particularly in heterogeneous systems with capillary heterogeneity, where the peak is halved. These insights underscore the challenges associated with tracer monitoring and the necessity for enhanced methodologies to improve predictive accuracy in subsurface processes during GCS.

Theoretical investigations of the potential application of PVA-mixed-valent tunnel structured manganese oxide nano-composite in continuous simultaneous removal of multi-contaminants from aqueous waste stream

The potential use of PVA-mixed-valent tunnel structured manganese oxide nano-composite in the removal of multi-contaminants form aqueous solutions was assessed by studying the continuous simultaneous removal of lead, caesium, and cobalt. Within this context, the morphology and the nature of nanoparticle inclusion into the PVA matrix was assessed using SEM–EDX analysis. The nanoparticles are homogenously distributed in the polymeric matrix with some agglomerated inclusions of these particles. The thermal and chemical stability analyses prove the stability of the material up to 180 °C and in slightly acidic to slightly alkaline solutions. The analysis of the gravimetric thermal data shows that the thermal treatment is a feasible end of life management route for this material. The values of percentage uptake and bed capacity indicate the feasibility of the use of this material in the simultaneous removal of lead, caesium and cobalt. The breakthrough curves analyses provide insights into the breakthrough characteristics and underlying removal mechanisms. It was found that the removal reaction follows Langmuir kinetics of adsorption–desorption and that the rate driving forces follow second order reversible reaction kinetics, where the sorption occur at energetically equal sites.