A systematic review of industrial wastewater management: Evaluating challenges and enablers

Advances and future perspectives of water defluoridation by adsorption technology: A review

Fluoride contamination in water sources poses a significant challenge to human health and the environment. In recent years, adsorption technology has emerged as a promising approach for water defluoridation due to its efficiency and cost-effectiveness. This review article comprehensively explores the advances in water defluoridation through adsorption processes. Various adsorbents, including natural and synthetic materials, have been investigated for their efficacy in removing fluoride ions from water. The mechanisms underlying adsorption interactions are elucidated, shedding light on the factors influencing defluoridation efficiency. Moreover, the review outlines the current state of technology, highlighting successful case studies and field applications. Future perspectives in the field of water defluoridation by adsorption are discussed, emphasizing the need for sustainable and scalable solutions. The integration of novel materials, process optimization, and the development of hybrid technologies are proposed as pathways to address existing challenges and enhance the overall efficacy of water defluoridation. This comprehensive assessment of the advances and future directions in adsorption-based water defluoridation provides valuable insights for researchers, policymakers, and practitioners working towards ensuring safe and accessible drinking water for all.

A review on microbes mediated resource recovery and bioplastic (polyhydroxyalkanoates) production from wastewater

BACKGROUND

Plastic is widely utilized in packaging, frameworks, and as coverings material. Its overconsumption and slow degradation, pose threats to ecosystems due to its toxic effects. While polyhydroxyalkanoates (PHA) offer a sustainable alternative to petroleum-based plastics, their production costs present significant obstacles to global adoption. On the other side, a multitude of household and industrial activities generate substantial volumes of wastewater containing both organic and inorganic contaminants. This not only poses a threat to ecosystems but also presents opportunities to get benefits from the circular economy. Production of bioplastics may be improved by using the nutrients and minerals in wastewater as a feedstock for microbial fermentation. Strategies like feast-famine culture, mixed-consortia culture, and integrated processes have been developed for PHA production from highly polluted wastewater with high organic loads. Various process parameters like organic loading rate, organic content (volatile fatty acids), dissolved oxygen, operating pH, and temperature also have critical roles in PHA accumulation in microbial biomass. Research advances are also going on in downstream and recovery of PHA utilizing a combination of physical and chemical (halogenated solvents, surfactants, green solvents) methods. This review highlights recent developments in upcycling wastewater resources into PHA, encompassing various production strategies, downstream processing methodologies, and techno-economic analyses.

SHORT CONCLUSION

Organic carbon and nitrogen present in wastewater offer a promising, cost-effective source for producing bioplastic. Previous attempts have focused on enhancing productivity through optimizing culture systems and growth conditions. However, despite technological progress, significant challenges persist, such as low productivity, intricate downstream processing, scalability issues, and the properties of resulting PHA.

Exploring Trichoderma Species in Industrial Wastewater: Morphological and Molecular Insights from Isolates

The genus Trichoderma holds economic significance due to its widespread distribution and diverse applications, including biological control, enzyme production, and various biotechnological uses. The accurate identification of Trichoderma species is crucial given their close association with human activities. Despite previous efforts in classification, a comprehensive analysis combining morphological and molecular approaches is necessary. This study focuses on the isolation of four Trichoderma species from industrial wastewater in Pakistan, expanding on the known diversity in the region; isolation involved collecting samples from industrial wastewater effluents at specific sites in Punjab, Pakistan. Trichoderma strains were cultured and purified on solid media, with subsequent biomass production for bisorptional activity. Morphological characterization included colony features and microscopic examinations. DNA extraction, polymerase chain reaction (PCR), and sequencing of the internal transcribed spacer (ITS) region were conducted for molecular analysis. Phylogenetic analysis was performed using the Maximum Likelihood Algorithm. The study identified three Trichoderma species, viz. T. citrinoviride, T. erinaceum, and T. longibrachiatum. Each species was characterized morphologically and supported by molecular-phylogenetic analysis. Illustrations of microscopic features and a phylogenetic tree based on the ITS-nrDNA region were recorded. T. citrinoviride and T. longibrachiatum, isolated from steel mill and tanneries wastewater, respectively, were differentiated based on morphological characteristics such as phialides and conidia. The combination of morphological and molecular techniques enhances the accuracy of species identification. The study highlights the significance of Trichoderma in industrial wastewater environments and underscores the need for continued research in this area. Future research should focus on exploring the ecological roles and potential applications of the newly identified Trichoderma species. Additionally, further investigations into the biotechnological potential of these species, including enzyme production and bioremediation capabilities, would contribute to their practical applications.

Facile synthesis of TiO2@ZnO nanoparticles for enhanced removal of methyl orange and indigo carmine dyes: Adsorption, kinetics

Water pollution represents one of the most important problems affecting the health of living organisms, so it was necessary to work on the formation of active materials to get rid of pollutants. In this study, Titanium dioxide (TiO2) doping Zinc oxide (ZnO) nanocomposites were produced via simple sonication method at 500 Hz in ethanol medium. At different weight concentrations (2.5, 5, 7.5, and 10 %). The morphology, structure configuration, chemical bonding, crystalline phase, and surface properties of obtained nanocomposites were characterized via FESEM, BET, XRD, XPS, RAMAN and FTIR instrumentation. The nanocomposites were employed as an adsorbent to eliminate the methyl orange (MO) and Indigo Carmine (IC) dyes from an aqueous solution. Batch removal experiments revealed that the elimination of MO and IC dyes by the TiZnO surface was pH and doping Ti concentration-dependent, with maximum removal occurring at pH = 7 for MO and pH = 3 for IC contaminants at 10 % doping Ti concentration (Ti (10 %)@ZnO). Langmuir model fit the absorptive removal of MO and IC dyes into the Ti (10 %)@ZnO surface well. The maximal removal capacity of Ti (10 %)@ZnO nanocomposite was found to be 994.24 mg. g-1 for MO and 305.39 mg. g-1 for IC. The Ti (10 %)@ZnO nanocomposite showed remarkable high stability towards the removal of both dyes through consecutive four cycles.

Exploring effects of carbon, nitrogen, and phosphorus on greywater treatment by polyculture microalgae using response surface methodology and machine learning

The microalgae-based wastewater treatment is a promising technique that contribute to achieving sustainable development goals (SDGs), such as SDG-6, "Clean Water and Sanitation". However, it is strongly influenced by the initial composition of wastewater. In this study, the impact of initial organics and nutrient concentration on the removal of total organic carbon (TOC), total carbon (TC), ammonium (NH4+), total nitrogen (TN), and phosphate (PO43-) from greywater using native polyculture microalgae was explored. Response surface methodology was employed along with two machine learning approaches, AdaBoost and XGBoost, to evaluate the interactions among three main factors: TOC, NH4+, and PO43-, and their effects on treatment efficiency. The C/N ratios for achieving maximum TOC and TC removal efficiency of 99.2% and 97.7% were determined to be 10.3, and 65.4-73.6, respectively. Notably, the N/P ratio did not significantly affect their removal. The highest NH4+ removal efficiency, reaching 96.2%, was attained at C/N ratios of 4.3, 24.0, 38.2, and 212.9, coupled with N/P ratios of 0.3, 2.6, and 23.4. Highest TN removal efficiency of 77.2% was achieved at C/N and N/P ratios of 12.2 and 2.0, respectively. Highest PO43- removal of 78.8% was obtained at N/P ratio 12.8. However, C/N ratio did not affect the removal efficiency. Maintaining these specified C/N and N/P ratios in the influent greywater would ensure that the treated greywater meets the required standards for various reuse applications, including flushing, groundwater recharge, and surface water discharge. The integration of RSM with AdaBoost and XGBoost provided accurate predictions of removal efficiencies. For all the models, XGBoost had the highest R2, and lowest MAE and MSE values. The cross validation of RSM models with AdaBoost and XGBoost further reinforced the reliability of these models in predicting treatment outcomes.

Emerging paradigms into bioremediation approaches for nuclear contaminant removal: From challenge to solution

The release of radionuclides, including Cesium-137 (137Cs), Strontium-90 (90Sr), Uranium-238 (238U), Plutonium-239 (239Pu), Iodine-131 (131I), etc., from nuclear contamination presents profound threats to both the environment and human health. Traditional remediation methods, reliant on physical and chemical interventions, often prove economically burdensome and logistically unfeasible for large-scale restoration efforts. In response to these challenges, bioremediation has emerged as a remarkably efficient, environmentally sustainable, and cost-effective solution. This innovative approach harnesses the power of microorganisms, plants, and biological agents to transmute radioactive materials into less hazardous forms. For instance, consider the remarkable capability demonstrated by Fontinalis antipyretica, a water moss, which can accumulate uranium at levels as high as 4979 mg/kg, significantly exceeding concentrations found in the surrounding water. This review takes an extensive dive into the world of bioremediation for nuclear contaminant removal, exploring sources of radionuclides, the ingenious resistance mechanisms employed by plants against these harmful elements, and the fascinating dynamics of biological adsorption efficiency. It also addresses limitations and challenges, emphasizing the need for further research and implementation to expedite restoration and mitigate nuclear pollution's adverse effects.

A comprehensive review on artificial intelligence in water treatment for optimization. Clean water now and the future

Given the severe effects that toxic compounds present in wastewater streams have on humans, it is imperative that water and wastewater streams pollution be addressed globally. This review comprehensively examines various water and wastewater treatment methods and water quality management methods based on artificial intelligence (AI). Machine learning (ML) and AI have become a powerful tool for addressing problems in the real world and has gained a lot of interest since it can be used for a wide range of activities. The foundation of ML techniques involves training of a network with collected data, followed by application of learned network to the process simulation and prediction. The creation of ML models for process simulations requires measured data. In order to forecast and simulate chemical and physical processes such chemical reactions, heat transfer, mass transfer, energy, pharmaceutics and separation, a variety of machine-learning algorithms have recently been developed. These models have shown to be more adept at simulating and modeling processes than traditional models. Although AI offers many advantages, a number of disadvantages have kept these methods from being extensively applied in actual water treatment systems. Lack of evidence of application in actual water treatment scenarios, poor repeatability and data availability and selection are a few of the main problems that need to be resolved.

Microplastics in aquatic bodies: Assessing the role of governance mechanisms in industrial wastewater management

The purpose of this research is to examine the association between corporate governance mechanisms (board independence, board gender diversity, Chief Executive Officer (CEO) duality, and environmental, social and governance (ESG) linked compensation) and wastewater recycling as a strategy for managing the flow of microplastics into the aquatic environment. The study analysed an international sample of top companies on the Forbes 500 list over a 15-year period during the millennium development goals (MDGs) and sustainable development goals (SDGs) eras. Multiple regression analysis with fixed effect OLS, two-stage least squares regression, propensity score matching, and logistic regression were applied in the data analysis. The results show that, at the aggregate level, board gender diversity is positively associated with wastewater recycling, whilst CEO duality has a significant negative impact. When disaggregated into industries, board gender diversity is positively associated with wastewater recycling in high-polluting and low-polluting industries. In relation to the MDGs/SDGs eras, the impact of board gender diversity is more significant in the MDGs era than in the SDGs era. At the geographical region level, CEO duality has a significant negative impact on wastewater management in the America and Asia Pacific regions, whilst the effect of CEO duality is significantly positive in the Western Europe region. We also find that a minimum of two female directors is required to improve wastewater management practice. The study concludes that whilst board gender diversity is a notable driver of wastewater management, CEO duality diminishes the commitment of multinational entities (MNEs) to addressing wastewater management issues. Our result is robust to (i) alternative measures of wastewater management, (ii) alternate sample composition, (iii) alternate method of data analysis, and (iv) endogeneity checks. The study contributes to the limited literature on waste management and the circular economy, particularly governance mechanisms' role in wastewater management in an international context.