Process Intensification for Enhanced Fluoride Removal and Recovery as Calcium Fluoride Using a Fluidized Bed Reactor.

This study explored the feasibility of fluoride removal from simulated semiconductor industry wastewater and its recovery as calcium fluoride using fluidized bed crystallization. The continuous reactor showed the best performance (>90% fluoride removal and >95% crystallization efficiency) at a calcium-to-fluoride ratio of 0.6 within the first 40 days of continuous operation. The resulting particle size increased by more than double during this time, along with a 36% increase in the seed bed height, indicating the deposition of CaF2 onto the silica seed. The SEM-EDX analysis showed the size and shape of the crystals formed, along with the presence of a high amount of Ca-F ions. The purity of the CaF2 crystals was determined to be 91.1% though ICP-OES analysis. Following the continuous experiment, different process improvement strategies were explored. The addition of an excess amount of calcium resulted in the removal of an additional 6% of the fluoride; however, compared to this single-stage process, a two-stage approach was found to be a better strategy to achieve a low effluent concentration of fluoride. The fluoride removal reached 94% with this two-stage approach under the optimum conditions of 4 + 1 h HRT combinations and a [Ca2+]/[F-] ratio of 0.55 and 0.7 for the two reactors, respectively. CFD simulation showed the impact of the inlet diameter, bottom-angle shape, and width-to-height ratio of the reactor on the mixing inside the reactor and the possibility of further improvement in the reactor performance by optimizing the FBR configuration.

Optimization of Calcium Fluoride Crystallization Process for Treatment of High-Concentration Fluoride-Containing Semiconductor Industry Wastewater.

This study utilized a fluidized bed reactor (FBR) for fluoride removal from high-concentration fluoride-ion-containing simulated semiconductor industry wastewater and recovered high-purity CaF2 crystals. The effects of hydraulic retention time (HRT), pH, Ca2+ to F- ratio, upflow velocity, seed size and seed bed height were investigated by performing lab-scale batch experiments. Considering fluoride removal and CaF2 crystallization efficiency, 5 h HRT, pH 6, seed height of 50 cm and [Ca2+]/[F-] ratio of 0.55 (mol/mol) were found to be optimum. The effect of the interaction between the important process parameters on fluoride removal was further analyzed using response surface methodology (RSM) experimental design. The results showed that all the individual parameters have a significant impact (p = 0.0001) on fluoride removal. SEM-EDX and FTIR analysis showed the composition of the crystals formed inside FBR. HR-XRD analysis confirmed that the crystalline structure of samples was mainly CaF2. The results clearly demonstrated the feasibility of silica seed material containing FBR for efficient removal and recovery of fluoride as high-purity calcium fluoride crystals.

Predictive modelling and optimization of an airlift bioreactor for selenite removal from wastewater using artificial neural networks and particle swarm optimization.

Selenite (Se4+) is the most toxic of all the oxyanion forms of selenium. In this study, a feed forward back propagation (BP) based artificial neural network (ANN) model was developed for a fungal pelleted airlift bioreactor (ALR) system treating selenite-laden wastewater. The performance of the bioreactor, i.e., selenite removal efficiency (REselenite) (%) was predicted through two input parameters, namely, the influent selenite concentration (ICselenite) (10 mg/L - 60 mg/L) and hydraulic retention time (HRT) (24 h - 72 h). After training and testing with 96 sets of data points using the Levenberg-Marquardt algorithm, a multi-layer perceptron model (2-10-1) was established. High values of the correlation coefficient (0.96 ≤ R ≤ 0.98), along with low root mean square error (1.72 ≤ RMSE ≤ 2.81) and mean absolute percentage error (1.67 ≤ MAPE ≤ 2.67), clearly demonstrate the accuracy of the ANN model (> 96%) when compared to the experimental data. To ensure an efficient and economically feasible operation of the ALR, the process parameters were optimized using the particle swarm optimization (PSO) algorithm coupled with the neural model. The REselenite was maximized while minimizing the HRT for a preferably higher range of ICselenite. Thus, the most favourable optimum conditions were suggested as: ICselenite - 50.45 mg/L and HRT - 24 h, resulting in REselenite of 69.4%. Overall, it can be inferred that ANN models can successfully substitute knowledge-based models to predict the REselenite in an ALR, and the process parameters can be effectively optimized using PSO.

Biological selenate and selenite reduction by waste activated sludge using hydrogen as electron donor.

Biological reduction of selenium oxyanions is widely used for selenium removal from wastewater. The process is, however, limited by the availability of a suitable, efficient and low cost electron donor. In this study, selenite and selenate reduction by waste activated sludge using hydrogen as the electron donor was investigated. Both selenite and selenate (80 mg/L) were completely removed using H2 within 8 days of incubation. In the presence of sulfate in the medium, the Se removal efficiency decreased to 77.8-95.4% (for selenite) and 88.2-99.4% (for selenate) at different temperatures and initial sulfate concentrations. Thermophilic conditions (50 °C) were better suited for both selenite and selenate reduction using H2 as electron donor with a 0.8-13.5% increase in overall Se removal. Similarly, sulfate reduction also increased from 69.1- 88% at 30 °C to 72-94.6% at 50 °C. Most of the H2 utilized was diverted towards Se and sulfate reduction with minimal production of byproducts such as methane (<0.32 mM) or volatile fatty acids (<0.92 mg/L). The elemental Se produced from selenite and selenate reduction ranged between 33.9 and 52.1 mg/L. The elemental selenium nanoparticles produced as a result of selenite and selenate reduction were characterized using transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX) and dynamic light scattering (DLS) spectroscopy. Furthermore, characterization of the biomass using Fourier-transform infrared spectroscopy (FTIR) and excitation emission matrix (EEM) spectra of the extracellular polymeric substances (EPS) produced by the waste activated sludge were performed to elucidate the mechanism of selenium oxyanion reduction to elemental selenium nanoparticles.

Selenite and tellurite reduction by Aspergillus niger fungal pellets using lignocellulosic hydrolysate.

The performance of Aspergillus niger pellets to remove selenite and tellurite from wastewater using batch and continuous fungal pelleted bioreactors was investigated. The acid hydrolysate of brewer's spent grain (BSG) was utilized by A. niger as the electron donor for selenite and tellurite reduction. The dilution of BSG hydrolysate using mineral medium had a positive effect on the selenite and tellurite removal efficiency with a 1:3 ratio giving the best efficiency. However, selenite and tellurite inhibited fungal growth with a 40.9% and 27.3% decrease in the A. niger biomass yield in the presence of 50 mg/L selenite and tellurite, respectively. The maximum selenite and tellurite removal efficiency using 25% BSG hydrolysate in batch incubations amounted to 72.8% and 99.5% Two fungal pelleted bioreactors were operated in continuous mode using BSG hydrolysate as the substrate. Both the selenite and tellurite removal efficiencies during steady state operation were > 80% with tellurite showing a maximum removal efficiency of 98.5% at 10 mg/L influent concentration. Elemental Se nanospheres for selenite and both Te nanospheres and nanorods for tellurite were formed within the fungal pellets. This study demonstrates the suitability BSG hydrolysate as a low cost carbon source for removal of selenite and tellurite using fungal pellet bioreactors.

Selective removal and recovery of gallium and germanium from synthetic zinc refinery residues using biosorption and bioprecipitation.

The depletion of primary ores, the environmental concerns related to mining activities, and the need to promote circular economy has drawn attention to the recycling of metallic compounds. Bio-based technologies are suitable for metal recovery, as they operate under mild conditions (ambient temperature and pressure) and are ideal for treating low-concentration waters. This study compared the effectiveness of adsorption and precipitation for the removal and recovery of gallium, germanium and zinc. Adsorption of the metallic ions on elemental forms of sulfur (S0), selenium (Se0) and tellurium (Te0), both of chemical and biological sources, was tested. Biosorption onto elemental forms of S0bio, Se0bio and Te0bio effectively removed Ga and Zn. The highest removal efficiency (Õ²) was obtained for Ga onto the adsorbent Te0bio (69 ± 0.4%), with an adsorption capacity (q) of 74 mg Ga (g Te0bio)-1, followed by Zn (Õ² = 40 ± 0.7%) with 43 mg Zn (g Te0bio)-1. Precipitation with chemical and biogenic sulfide at different metal to sulfide (Me/S) ratios was also assessed. Biologically produced sulfide was more efficient for Ga and Zn compared to chemical sulfide. Precipitation with biogenic sulfide was efficient for the removal of Ga (Õ² = 59.9 ± 2.6%) and Zn (Õ² = 44.2 ± 3.0%). The lowest ratio between metal to sulfide (Me/S = 0.2) achieved higher zinc removal efficiencies, whereas gallium removal was more efficient at Me/S = 1.5. None of the tested methods allowed for recovery of Ge. Biosorption and bioprecipitation gave nevertheless high removal and recovery of Ga and Zn.

Photocatalytic degradation of Congo Red by zinc sulfide quantum dots produced by anaerobic granular sludge.

ABSTRACTSulfate reducing bacteria present in anaerobic granular sludge mediate the metabolic conversion of sulfate to sulfide. In the presence of heavy metals, sulfides precipitate as metal sulfides. In this study, dissimilatory sulfate reduction was coupled to the precipitation of zinc as ZnS quantum dots (QDs) at ambient conditions. The biogenic ZnS QDs had average sizes of 5-7 nm and were formed within 2-4 days of incubation. X-ray diffraction analysis indicated that the biosynthesised ZnS QDs possessed a crystalline cubic lattice structure. The organics present during ZnS biosynthesis were characterized using 3D-fluorescence excitation-emission measurements (FEEM) and the presence of an organic coating on the biogenic ZnS QDs was affirmed using FTIR analysis. The UV-visible absorption spectra of the samples exhibited a prominent absorption peak below 325 nm, which is the characteristic of the surface plasmon resonance of ZnS QDs. The band gap energy of the biogenic ZnS QDs was estimated to be 3.84 eV, comparable to the values reported for chemically synthesised ZnS QDs. The direct band gap energy indicates a large redox potential and carrier mobility, which capacitate the application of these QDs as effective photocatalysts for the photo-assisted decolourization of dyes, as illustrated for the dye congo red.

Simultaneous removal of lead and selenium through biomineralization as lead selenide by anaerobic granular sludge.

This study demonstrated the simultaneous removal of lead (Pb) and selenium (Se) as lead selenide biomineralization using anaerobic granular sludge. The microbial community of the granular sludge was first enriched for 140 days in the presence of Pb(II) only, selenate and selenite only, Pb(II)+selenate, and Pb(II)+selenite. In the absence of Se, removal of Pb(II) mainly occurred via biosorption and deposited on the biomass as lead oxide and lead carbonate. The Pb removal efficiency (94% of initial 50 mg L-1) was reduced to 90% and 86% in the presence of selenate and selenite, respectively, due to biosorption. Addition of Pb(II) didn't exert any toxic effect on the Se-reducing microbial community, on the contrary: Pb(II) addition improved the Se removal efficiency for selenate from 85% to 90%, but did not affect selenite removal after 14 d of incubation. The bioreduction of the Se-oxyanions produced elemental Se (Se(0)) and selenide, which later interacted with Pb(II) to produce lead selenide (PbSe). Adsorption of Pb(II) onto the Se(0) nanoparticles and precipitation as the Se(0)-Pb complex might also have contributed to the simultaneous removal of Pb and Se. XPS and XRD analysis further confirmed the immobilization of Pb as PbSe, PbO and PbCO3 in the biomass.

Gas-phase trichloroethylene removal by Rhodococcus opacus using an airlift bioreactor and its modeling by artificial neural network.

This study evaluated the biological removal of trichloroethylene (TCE) by Rhodococcus opacus using airlift bioreactor under continuous operation mode. The effect of inlet TCE concentration in the range 0.12-2.34 g m-3 on TCE removal has studied for 55 days. During the continuous bioreactor operation, a maximum of 96% TCE removal was obtained for low inlet TCE concentration, whereas the highest elimination capacity was 151.2 g m-3 h-1 for the TCE loading rate of 175.0 g m-3 h-1. The carbon dioxide (CO2) concentration profile from the airlift bioreactor revealed that the degraded TCE has primarily converted to CO2 with a fraction of organic carbon utilized for bacterial growth. The artificial neural network (ANN) based model was able to successfully predict the performance of the bioreactor system using the Levenberg-Marquardt (LM) back propagation algorithm, and optimized biological topology is 3:12:1. The prediction accuracy of the model was high as the experimental data were in good agreement (R2 = 0.9923) with the ANN predicted data. Overall, from the bioreactor experiments and its ANN modeling, the potential strength of R. opacus in TCE biodegradation is proved.

Selenite removal from wastewater using fungal pelleted airlift bioreactor.

This study investigated the removal of selenite from wastewater using the fungus Asergillus niger KP isolated from a laboratory scale inverse fluidized bed bioreactor. The effect of different carbon sources and initial selenite concentration on fungal growth, pellet formation and selenite removal was first examined in a batch system. The fungal strain showed a maximum selenite removal efficiency of 86% in the batch system. Analysis of the fungal pellets by field-emission scanning electron microscopy, field-emission transmission electron microscopy and energy-dispersive X-ray spectroscopy revealed the formation of spherical-shaped elemental selenium nanoparticles of size 65-100 nm. An increase in the initial selenite concentration in the media resulted in compact pellets with smooth hyphae structure, whereas the fungal pellets contained hair like hyphae structure when grown in the absence of selenite. Besides, a high initial selenite concentration reduced biomass growth and selenite removal from solution. Using an airlift reactor with fungal pellets, operated under continuous mode, a maximum selenite removal of 94.3% was achieved at 10 mg L-1 of influent selenite concentration and 72 h HRT (hydraulic retention time). Overall, this study demonstrated very good potential of the fungal-pelleted airlift bioreactor system for removal of selenite from wastewater. Graphical abstract.

A novel carbon monoxide fed moving bed biofilm reactor for sulfate rich wastewater treatment.

In this study, a moving bed biofilm reactor was used for biodesulfuruization using CO as the sole carbon substrate. The effect of hydraulic retention time (HRT), sulfate loading rate and CO loading rate on sulfate and CO removal was examined. At 72, 48 and 24 h HRT, the sulfate removal was 93.5%, 91.9% and 80.1%, respectively. An increase in the sulfate loading reduced the sulfate reduction efficiency, which, however, was improved by increasing the CO flow rate into the MBBR. Best results in terms of sulfate reduction (>80%) were obtained for low inlet sulfate and high CO loading conditions. The CO utilization was very high at 85% throughout the study, except during the last phase of the continuous bioreactor operation it was around 70%. An artificial neural network based model was successfully developed and optimized to accurately predict the bioreactor performance in terms of both sulfate reduction and CO utilization. Overall, this study showed an excellent potential of the moving bed biofilm bioreactor for efficient sulfate reduction even under high loading conditions.

Process integration for biological sulfate reduction in a carbon monoxide fed packed bed reactor.

This study examined immobilized anaerobic biomass for sulfate reduction using carbon monoxide (CO) as the sole carbon source under batch and continuous fed conditions. The immobilized bacteria with beads made of 10% polyvinyl alcohol (PVA) showed best results in terms of sulfate reduction (84 ±â€¯3.52%) and CO utilization (98 ±â€¯1.67%). The effect of hydraulic retention time (HRT), sulfate loading rate and CO loading rate on sulfate and CO removal was investigated employing a 1L packed bed bioreactor containing the immobilized biomass. At 48, 24 and 12 h HRT, the sulfate removal was 94.42 ±â€¯0.15%, 89.75 ±â€¯0.47% and 61.08 ±â€¯0.34%, respectively, along with a CO utilization of more than 90%. The analysis of variance (ANOVA) of the results obtained showed that only the initial CO concentration significantly affected the sulfate reduction process. The reactor effluent sulfate concentrations were 27.41 ±â€¯0.44, 59.16 ±â€¯1.08, 315.83 ±â€¯7.33 mg/L for 250, 500 and 1000 mg/L of influent sulfate concentrations respectively, under the optimum operating conditions. The sulfate reduction rates matched well with low inlet sulfate loading rates, indicating stable performance of the bioreactor system. Overall, this study yielded very high sulfate reduction efficiency by the immobilized anaerobic biomass under high CO loading condition using the packed bed reactor system.

A novel biological sulfate reduction method using hydrogenogenic carboxydotrophic mesophilic bacteria.

Sulfate reduction by carbon monoxide (CO) utilizing anaerobic biomass from a large scale upflow anaerobic sludge blanket reactor was studied. Anaerobic mixed microbial consortia from five different sources were initially examined for their biological CO conversion potential. Among the different biomass, the biomass from an upflow anaerobic sludge blanket reactor treating domestic wastewater, located in Kavoor, Karnataka, India, showed a maximum CO conversion efficiency. The effect of three main culture parameters, i.e. inoculum volume, initial CO concentration and temperature on simultaneous CO conversion and sulfate reduction was assessed employing the Taguchi experimental design technique. A maximum CO conversion of 85.62% and a maximum sulfate reduction of 50.65% were achieved. Furthermore, the experimental data was fitted to substrate inhibition models reported in the literature. Among the different models, Monods and Haldane kinetic models were found most suitable to describe the kinetics of biomass growth and CO removal by the anaerobic biomass.