Application of statistical response surface methodology for optimization of fluoride removal efficiency by Padina sp. alga

Current progress on fluoride occurrence in the soil environment: Sources, transformation, regulations and remediation

Fluorine is a halogen element widely distributed in nature, but due to excessive emissions from industrial manufacturing and agricultural production, etc., the soil is over-enriched with fluoride and the normal growth of plants is under stress, and it also poses a great threat to human health. In this review, we summarized the sources of fluoride in soil, and then analyzed the potential mechanisms of fluoride uptake in soil-plant systems. In addition, the main influences of soil ecosystems on plant fluoride uptake were discussed, soil management options to mitigate fluoride accumulation in plants were also summarized. The bioremediation techniques were found to be a developmental direction to improve fluoride pollution. Finally, we proposed other research directions, including fluoride uptake mechanisms in soil-plant systems at the molecular expression levels, development of visualization techniques for fluoride transport in plants, interactions mechanisms between soil microhabitats and plant metabolism affecting fluoride uptake, as well as combining abiotic additives, nanotechnology and biotechnology to remediate fluoride contamination problems.

Using chemometric models to predict the biosorption of low levels of dysprosium by Euglena gracilis

The critical rare earth element dysprosium (Dy) is integral for sustainable technologies. What is concerning is that Dy is in imminent short supply and no current replacements yet exist, coupled with increasing environmental Dy levels influenced by anthropogenic activities. This study applies chemometric methods such as response surface methodology and artificial neural networks to predict low Dy removal levels using the biosorbent Euglena gracilis. A three-factor Box-Behnken experimental design was conducted with initial concentration (1 to 100 µg L^-1), contact time (30 to 180 min), and pH (3 to 8) as the three independent variables, and percentage removal and sorption capacity (q) as dependent variables. Using Dy percentage removal as response, for the worst and best conditions ranged from 0 to 92% respectively, with an average removal of 66 ± 4%. Using sorption capacity (q) as a different response variable, q varied from 0 to 93 µg/g with 27 ± 4 µg/g capacity as average. Maximum removal was 92% (q = 93 µg/g) was at pH 3, a contact time of 105 min and at a concentration of 100 µg/L. Using sorption capacity as the response variable for ANOVA, pH and metal concentrations were statistically significant factors, with lower pH and higher metal concentration having improved Dy removal, with a desirability near 1. Statistical tests such as analysis of variance, lack-of-fit, and coefficient of determination (R²) confirmed model validity. A 3-10-1 ANN network array was used to model experimental responses (q). RSM and ANN effectively modeled Dy biosorption. E. gracilis proved to be a cheap and effective biosorbent for Dy biosorption and has the potential to remediate acid mine drainage areas exhibiting low Dy concentrations.

Bioaccumulation of Fluoride in Plants and Its Microbially Assisted Remediation: A Review of Biological Processes and Technological Performance

Fluoride is widely found in soil–water systems due to anthropogenic and geogenic activities that affect millions worldwide. Fluoride ingestion results in chronic and acute toxicity, including skeletal and dental fluorosis, neurological damage, and bone softening in humans. Therefore, this review paper summarizes biological processes for fluoride remediation, i.e., bioaccumulation in plants and microbially assisted systems. Bioremediation approaches for fluoride removal have recently gained prominence in removing fluoride ions. Plants are vulnerable to fluoride accumulation in soil, and their growth and development can be negatively affected, even with low fluoride content in the soil. The microbial bioremediation processes involve bioaccumulation, biotransformation, and biosorption. Bacterial, fungal, and algal biomass are ecologically efficient bioremediators. Most bioremediation techniques are laboratory-scale based on contaminated solutions; however, treatment of fluoride-contaminated wastewater at an industrial scale is yet to be investigated. Therefore, this review recommends the practical applicability and sustainability of microbial bioremediation of fluoride in different environments.

Techno-economical optimization using Box-Behnken (BB) design for chemical oxygen demand and chloride reduction from hospital wastewater by electro-coagulation

The study examines the optimum condition of an electro-coagulation (EC) unit for treatment of hospital wastewater (HWW) using iron (Fe) electrodes. The impact of factors such as pH, current, and electrolysis time on COD, chloride, and anode dissolution was investigated. For this purpose, Box-Behnken (BB) design based on the response surface methodology (RSM) was used to design and analyze the results. The predicted value of chemical oxygen demand (COD) and chloride removal at optimum conditions (pH: 7.41, current: 2.64 A and electrolysis time: 41.31 min) were 92.81% and 71.23%, respectively. At same optimum conditions, the value of energy and electrode consumption per kg of COD was 0.06376 kWh/kg COD and 1.362 kg/kg COD, respectively. High value of R² (i.e., R²  > 99%) for all three responses (Y₁ , Y₂ , and Y₃ ) obtained from ANOVA confirms that the proposed model is valid, accurate, and acceptable. The kinetic study shows linear relationship and follows pseudo-first-order kinetics. Pareto graph shows that the percentage impact of current factor on COD and chloride removal was maximum, that is, 54.984% and 66.79%, respectively. Lastly, the total cost of EC treatment was calculated in terms of COD removal and was found to be 55.47 ₹/kg COD. PRACTITIONER POINTS: Using Fe electrode results in 92.81% COD and 71.23% Chloride removal, respectively. High value of R²  > 99% for all three responses from ANOVA confirms the proposed model is valid. Pareto analysis shows current factor has maximum percentage impact on pollutant removal. Kinetic study shows linear relationship and follows pseudo-first-order kinetics.