Spent coffee grounds (SCGs) are waste products obtained after brewing roasted coffee beans. The detoxification-based process used in the preparation of defatted spent coffee grounds (SCGO) involves: (i) direct acid pretreatment followed by enzymatic-hydrolysis (AE), (ii) solvent extraction followed by acid pretreatment and enzyme-hydrolysis (SAE), and (iii) solvent extraction followed by acid pretreatment and enzymatic-hydrolysis coupled with activated carbon detoxification (SAEAc) for polyhydroxyalkanoates (PHA) production. SCGO was subjected to optimized acid pretreatment (100 °C, 2.0% H2SO4, 6 h), followed by enzyme saccharification (20 FPU/g of SCGO). The effect of detoxification on the obtained hydrolysates was comparatively evaluated based on their inhibitor concentrations and suitability as substrates for fermentation by Lysinibacillus sp. RG.S. and PHA biosynthesis. The maximum biomass productivity (5.6 ± 0.44 g/dm3), PHA accumulation (53.0 ± 1.22%), and PHA yield (2.97 ± 0.32 g/dm3) were produced by the hydrolysates that were generated by the SAEAc-detoxification process with 1% corn steep liquor (CSL) and 1% acetic acid. The physicochemical and thermo-stable properties of the produced PHA were found to be comparable to those of standard PHB, making it appealing for a variety of applications. Extracted bioactive compounds from SCGO were employed as reducing and stabilizing agents for the synthesis of silver nanoparticles (AgNPs). Analytical results suggest that the SCGO-AgNPs were well phyto-fabricated and evenly dispersed, with particle diameters of about 10-40 nm. Furthermore, SCGO-AgNPs demonstrated potential antioxidant and antidiabetic activities, indicating their prospective for biomedical and nutraceutical applications. The foregoing results illustrate that detoxification strategy enhances the fermentability of SCGO hydrolysate and extracted bioactive compounds are used for biofunctional synthesis of AgNPs. In summary, the integrated cascading biorefinery concept supports sustainable and economically viable valorization of SCGO.

The Republic of Korea applies a residential soil fluoride standard of 800 mg/kg, while geogenically elevated fluoride occurs in some regions, creating uncertainty about how soil fluoride concentrations translate into potential health risk under multimedia exposure. Because fluoride exposure can also occur through groundwater and food crops, soil concentration alone may not fully characterize total exposure. This study compared health risk assessment guidance and quantify the parameterizations using explainable analyses to support media-integrated management guidance. Fluoride exposure scenarios, including crop intake, drinking water consumption, and soil/dust ingestion, were compared and evaluated using the U.S. EPA risk assessment guidance for superfund (RAGS) and the Korean soil-contamination risk assessment guidelines (KRAG). Simulated fluoride levels ranged from 200 to 4000 mg/kg in soil, 0.5 to 2.5 mg/L in water, and 5 to 40 mg/kg in crops. Additionally, explainable machine learning was applied to identify parameterization inconsistencies and to support guideline-relevant refinement. Children exhibited higher hazard index (HI) to fluoride under RAGS, reaching 9.116, whereas KRAG yielded lower HI estimates under the specified parameterization and, in some scenarios, produced lower HI values for children than for adults. A modified approach, RAGS-K, applies KRAG parameters within the RAGS calculation structure and yielded higher HI estimates than KRAG under the examined scenarios. The results show that intake from water and crops dominates child risk and drives the discrepancy between adult and child risk, supporting further evaluation of media-integrated risk assessment approaches.

Sonocatalysis is a rapidly emerging advanced method that uses acoustic cavitation to produce localized extreme conditions and reactive radical species that accelerate chemical reactions. Sonocatalysis offers numerous benefits over conventional catalysis and advanced oxidation processes, which include enhanced mass transfer, flexible reactor design, and operation in dark or murky environments. This review delineates a systematic framework correlating to cavitation mechanisms, charge transfer pathways, ultrasonic operational parameters, and structure–property relationships in catalysts. The sonocatalysts are classified as carbon-derived supports, graphitic carbon nitride, biomaterials, and carbon-free materials, including semiconductor-based materials, metal and metal-oxide systems, and heterostructured multifunctional composites. A comparative analysis highlights the distinct contributions of each category to radical generation, defect modulation, energy harvesting, recyclability, and scalability. Recent advances in piezoelectric polarization, plasmon-coupled activation, heterojunction engineering, and sonophotocatalytic hybrid architectures substantially expanded sonocatalysis toward pollutant degradation, H2 production, CO2 conversion, biomass valorization, disinfection, and biomedical applications. However, significant scientific challenges remain in the sonocatalysis system, related to the mechanistic understanding, energy efficiency, catalyst durability, reactor scalability, and industrial applicability. Operando spectroscopy, computational modeling (including density functional theory and machine learning-based approaches), microfluidic sonoreactor engineering, and techno-economic assessment are essential for advancing sonocatalysis from laboratory-scale studies to practical implementations. This review provides a comprehensive overview of the rapidly evolving materials, mechanistic pathways, applications, and scale-up challenges of sonocatalysis.

A sustainable approach for dye pollution mitigation through industrial residue and natural polymer-based wastewater treatment was developed in this work. In the present study, environmentally friendly bio-polymer-immobilised Zn-modified bauxite residue beads (BR-Zn-SA) were prepared to effectively remove toxic cationic dye malachite green, which has widespread applications in textile and paper industries. Zinc chloride was applied to activate the bauxite residue by enhancing its surface porosity, acidity, and Lewis active sites, which increased the amount of electrostatic and coordination binding centres for MG adsorption. Biodegradable polysaccharide sodium alginate acted as an encapsulating matrix providing mechanical stability with a hydrophilic nature and extra -COOH/-OH functional groups, preventing particle leaching and improving reusability in continuous systems. XRD, FTIR, BET, and PZC analyses identified a mesoporous structure with positive surface potential, hence favourable for cationic dye uptake. Batch adsorption study under optimised conditions resulted in the removal of 96-97% at pH 7, 60 g L-1 dosage, 300 rpm, and 10 mg L-1 MG. Fixed-bed column experiments demonstrated better breakthrough performance for the highest bed height of 14 cm and lowest flow rate of 10 mL min-1. Models fitted the column data, and CFD simulation confirmed the optimality of flow uniformity and mass transfer. In this work, a unique combination of waste valorisation through zinc activation, alginate-based biopolymer immobilisation, and CFD-assisted modelling was employed to develop a cost-effective, easily scalable, and ecofriendly adsorbent system for industrial dye remediation.

Scorpions are ancient arachnids of medical and ecological importance; they prey on insects and other arthropods while serving as prey to birds and reptiles. In this study, we reported for the first time on the characterization of the gut intestinal microbiome of Hottentotta tamulus native to northeastern Pakistan. The scorpions were identified on a morphological basis and the Cytochrome c oxidase subunit 1 gene sequence, while the gut microbiome was characterized through full-length 16S rRNA (V1-V9) Nanopore sequencing. The gut microbiota exhibited low to moderate alpha diversity with Chao1 and Shannon indices of 126 ± 90.54 and 0.85 ± 0.21, respectively. The intestinal microbial community was dominated by the phyla Firmicutes (79.48%-90.43%), followed by Proteobacteria (9.46%-20.48%), whereas Actinobacteriota (0.03%-0.11%) and Bacteroidota (0.00%-0.01%) were present at very low relative abundance. The functional profiling identified 23 notable pathways involved in energy metabolism, biomolecule synthesis, the biodegradation of various xenobiotics, and nucleotide metabolism, highlighting the role of the gut microbiome in metabolic homeostasis. The dominance of Bacillus and Mycoplasma in gut microbial communities may enhance host adaptation to low-resource environments.

Chronic diabetic wounds pose a persistent clinical problem due to ongoing infections and impaired lifestyle. Traditional silver-based therapies are often constrained by cytotoxicity and variable healing outcomes, underscoring the need for safer, more efficacious wound care approaches. This study emphasizes the design and assessment of a multifunctional Ag-Collagen/Al2O3/Cellulose nanodressing, particularly for diabetic wound therapy. The Ag-Collagen nanocomposites were incorporated into an Al2O3-reinforced Cellulose scaffold to serve as an adsorbent, a biocompatible substrate, a mechanical stabilizer, and a prolonged antibacterial efficacy, achieving >90% biofilm inhibition against Acinetobacter baumannii. Transcriptomic analysis (log2 fold change ≥ 1, p ≤ 0.05) revealed significant dysregulation of genes involved in metabolic pathways, membrane integrity, stress response, and virulence, suggesting that nanodressing induces oxidative and metal stress while concurrently disrupting vital cellular functions. These molecular modifications indicate diminished bacterial adaptability and reduced resistance. The nanodressing exhibited significant cytocompatibility with RAW 264.7 and 3T3 cells, as well as superior hemocompatibility, indicated by red blood cell lysis remaining below 5%. In vivo wound-healing investigations in normal and diabetic murine models demonstrated excellent infection control and expedited wound closure, achieving 90%-95% closure within 21 days. The Ag-Collagen/Al2O3/Cellulose nanodressing is a biocompatible antibacterial platform for multidrug-resistant diabetic wounds.

High‐performance supercapacitors require electrode materials that can simultaneously deliver elevated energy storage capacity, rapid power output, and long‐term cycling stability. Compared to sulfur analogs, selenium (Se)‐based materials have shown great promise because of their favorable redox activity, enhanced polarizability, and superior electrical conductivity. Herein, recent developments in Co–Se, Ni–Se, sulfoselenides (S–O–Se), and other Se‐based electrode materials are critically reviewed, with emphasis on their synthesis techniques, structural advantages, and electrochemical performance in relation to charge storage mechanisms. Comparative analysis reveals that their capacitance and durability are significantly enhanced by morphological control, heterostructure engineering, and synergistic effects with conductive substrates. The incorporation of Se into materials and their charge storage mechanisms is discussed using density functional theory analysis and artificial intelligence/machine learning approaches. This review highlights the growing contribution of Se‐based electrodes to supercapacitor technology by critically examining their development from basic binary selenides to intricate hybrid systems. Furthermore, the influence of Se metal centers and carbon frameworks in enhancing mechanical stability, active site accessibility, and ion transport is meticulously investigated. To close the gap toward practical next‐generation energy storage devices, the advantages and limitations of Se and its composite systems are evaluated, and prospects for advancing Se‐based electrodes are carefully outlined.

The increasing demand for sustainable bioplastics is constrained by the high production costs associated with refined carbon sources, highlighting the need for low-cost, renewable feedstocks. This study evaluated the potential of spent coffee grounds (SCG), an abundant and sustainable feedstock for generating polyhydroxyalkanoates (PHA) using Cupriavidus necator. First, SCG was subjected to solvent extraction to remove coffee oil, followed by extraction of phenolic compounds, and the remaining biomass was referred to as SCGO. The originality of this work lies in the systematic comparison of acid, alkaline, and peracetic acid pretreatments and their subsequent evaluation for microbial PHA production. SCGO was subjected to various chemical pretreatments, including acid (H2SO4), alkaline (NaOH), and peracetic acid (PAA) pretreatment. The effects of the different pretreatments on SCGO delignification, hydrolysis yield, and enzymatic saccharification to release monomeric sugars were evaluated. Among the tested methods, alkaline pretreatment provided the highest delignification efficiency, enzymatic saccharification, and fermentable sugar recovery, resulting in superior bacterial growth and PHA production. Under optimized conditions, the alkaline-pretreated SCGO hydrolysate supplemented with corn steep liquor produced a maximum biomass concentration of 6.5 ± 0.26 g/L, 60.0 ± 1.45% PHA accumulation, and a PHA titer of 3.89 ± 0.14 g/L. Structural and thermal characterization confirmed that the produced polymer possessed properties comparable to those of conventional poly(3-hydroxybutyrate) (PHB). Overall, this study demonstrates that integrated valorization of spent coffee grounds can effectively generate fermentable substrates for microbial PHA production, providing a sustainable approach for converting agro-industrial residues into high-value bioplastics while supporting circular bioeconomy strategies.

IntroductionIn this study, the present work describes a work that analyzed the synthesis/performance of NiO@chitosan composite beads for the removal of Coomassie Brilliant Blue G (CBB-G) from aqueous systems successfully under both batch and fixed-bed conditions.MethodsNiO nanoparticles were prepared by co-precipitation and homogenized in a chitosan matrix to generate stable, spherical beads with improved adsorption performance. XRD, FTIR, FE-SEM/EDS, BET, zeta potential, and pHpzc characterization suggested NiO incorporation and adsorption sites existed. The batch analyses have shown that the adsorption efficiency was strongly dependent on stirring speed, dosage of the adsorbent, dye concentration, pH and temperature of the sample to attain an optimum condition at 150 r/min (revolutions per minute), 54 g/L, 30 mg/L, pH 7 °C and 30 °C. For linear kinetic analysis, a pseudo second order model (R2 = 0.9993) was used, while the equilibrium data supported Langmuir isotherm (R2 ≈ 0.99), confirming the dependence of monolayer adsorption on physical interactions.Results and DiscussionIn fixed-bed adsorptive investigations, breakthrough profiles were majorly dependent on bed height, inlet concentration, and feed flow velocity. The Thomas and Yoon–Nelson models with high R2 ≈ 0.99 corroborated significantly with experimental outcome where predictive accuracy was validated with Clark model. Thermodynamic results (ΔH° = 39.58 kJ/mol) suggested spontaneous, endothermic, and physisorption-powered adsorption. Molecular docking verified electrostatic, hydrogen bonding, and van der Waals interactions between dye and bead surface. The beads had good reusability with only minimal effect upon losses in efficiency. Life cycle analysis indicated bead synthesis exerts largest environmental burden (105 kg CO2-eq/kg), with 6.94 kg required per m3 treatment, leading to 852 kg CO2-eq/m3. Overall, the developed NiO@chitosan beads exhibited excellent adsorption performance and reusability; however, further optimization of the synthesis process is necessary before they can be considered a fully sustainable adsorbent for large-scale wastewater treatment.

Implementation of scalable photocatalytic inactivation systems still remain limited due to the absence of information regarding the impact of reactor design on bacterial inactivation. To elucidate the fundamental understanding of hydrodynamics, photocatalyst dispersion, and efficiency in batch and continuous flow reactors, this work combines computational fluid dynamics (CFD) and photocatalytic inactivation of Escherichia coli (E. coli), using Fe-doped ZnO nanoparticles (Fe/ZnO NPs) as visible-light-responsive photocatalysts in batch stirred tank reactor (BSTR) and continuous flow helical tube reactor (CFHTR). The key variables that influenced the process efficiency were identified by systematically running the reactions with varying catalyst and bacterial loading, flow rate, and pH. Total inactivation of E. coli was achieved within 60 min at a low catalyst loading (25 mg/L) in CFHTR, while the BSTR required 210 min at higher catalyst loading (1000 mg/L). The role of reactive oxygen species (ROS) in inactivation which induces membrane disruption was investigated by metabolic activity analysis and electron microscopy. To relate photocatalytic stress with the regulation of resistance genes in both of the reactor modes, parallel genomic profiling of E. coli genes was conducted. The CFD analysis suggested that the synergistic impact of velocity, turbulence kinetic energy and its gradient along with eddy viscosity varies with the change in the reactor design and hence, intensify the inactivation efficiency. Furthermore, a user-friendly, menu-driven simulation tool is developed to facilitate efficient optimization and performance evaluation of the proposed system. Findings of this study may help to design and upscale photocatalytic inactivation systems for water treatment.

Microplastics (MPs) are increasingly recognized as persistent and widespread pollutants that pose serious threats to environmental health. Due to their durability, resistance to natural degradation, and pervasive presence across ecosystems, microplastics accumulate across various environmental matrices. Therefore, this review synthesizes current knowledge on their sources, environmental distribution, and ecotoxicological impacts, aligned with the United Nations Sustainable Development Goals (SDGs). The ecotoxicological effects of MPs on biota at all trophic levels, through ingestion, entanglement, and trophic transfer, often result in physiological stress, reproductive toxicity, and mortality in aquatic and terrestrial organisms. Human exposure, particularly through food chains, drinking water, and atmospheric inhalation, raises concerns over long-term health effects, including inflammation, oxidative stress, and endocrine disruption. The growing threat of MPs also impedes progress toward several United Nations Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being), SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), and SDG 14 (Life Below Water). Effective management of MPs requires a multifaceted approach that involves source reduction, technological innovations in wastewater treatment, public awareness, policy interventions, and the promotion of circular economic principles. Hence, this review emphasizes the need for interdisciplinary research to understand the sources, behaviour, transport pathways, ecological fate, and long-term impacts of microplastics across various environmental matrices.

In this study, vermistabilization of dairy processing sludge (DPS) was performed by mixing with cattle dung (CD) in 1:1 ratio and subjecting it to varying pre-composting periods of 7 days to 35 days for the three earthworm species, Eisenia fetida (E.F), Eudrilus eugeniae (E.E), and Perionyx excavatus (P.E). Pre-composting times of 3 weeks (DPS21E.F), 2 weeks (DPS14E.E), and 3 weeks (DPS21P.E) gave optimal results for all three earthworms’ growth, reproduction, and composting efficiency in terms of total Kjeldahl nitrogen, total available phosphorus, and total potassium for the three species. E.F was found to have the most effective soil-builder capacity, which contributed to a higher seed germination index, 193

This work explores a waste valorization approach for producing rhamnolipids using two abundant residues: crude cellulose (40%) derived from sawdust and crude glycerol (45%) from waste cooking oil. Rigorous experimental studies showed that mono-substrate fermentations resulted in lower product yields, prompting the use of dual-substrate (3% w/v cellulose + 3% w/v glycerol) fermentations by Pseudomonas aeruginosa 2297. Dual-substrate fermentations produced the highest titer of 6021 +/- 235.25 mg/L of rhamnolipids, compared to the respective product concentrations of 3711.37 +/- 34.3 mg/L and 1634.90 +/- 131.49 mg/L obtained with crude glycerol (4% w/v) and crude cellulose (4% w/v) as sole carbon sources, respectively. Produced rhamnolipid showed about 40.73 +/- 2.09% oil recovery using a sand-packed column. Techno-economic evaluation established a minimum selling price of USD 1.57/g at a null net present value, indicating potential economic competitiveness. A cradle-to-gate life cycle assessment showed a carbon footprint of 1.73 kg CO2-eq/g of rhamnolipid, which is better than that reported in recent literature. Further optimization of utility consumption parameters can reduce the carbon footprint and other environmental impacts, thereby providing a basis for appropriate policy recommendations.

Assessment of groundwater quality is essential for its long-term and safe use in drinking supplies, agriculture, and industrial purposes. Therefore, this review paper focuses on a comprehensive assessment of the hydrochemistry and groundwater quality in Bihar, India. The study uses various techniques to interpret the comprehensive hydrochemical condition of groundwater, building on previous research. The study also examines various aspects of groundwater quality by evaluating its physical and chemical characteristics to estimate the status of groundwater quality. Key indicators, including the Water Quality Index (WQI), Sodium Absorption Ratio (SAR), Percentage Sodium (

This research aims to assess air quality (particulate matter (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), benzene, and toluene) in a transitional location of four polluted cities in the Indo-Gangetic Basin, India. According to the Air Quality World Report, these cities were among the top 30 most polluted, posing a higher risk to public health due to exposure to air pollutants. Therefore, we have analyzed annual and seasonal variabilities and their relationships with meteorology and the air quality index (AQI) from 2017 to 2022. The highest annual mean concentrations were observed at Patna for PM2.5 (113.14 ± 13.6 μg/m3), NO2 (58.32 ± 24.6 μg/m3), SO2 (18.17 ± 12.8 μg/m3), CO (1.58 ± 0.3 mg/m3), O3 (42.90 ± 16.0 μg/m3), and benzene (2.38 ± 2.4 μg/m3), except Toluene and Xylene during the study period. All the observed air pollutants exceeded the NAAQs and WHO permissible limits in the study locations. Pearson's correlation analysis of PM2.5 showed negative correlations with temperature (−0.9), RH (−0.1), WS (−0.5), SR (−0.7), and RF (−0.3), and a positive correlation with WD (0.3) at Aurangabad. The AQI values were in the good (0-50) and satisfactory (51-100) categories at Muzaffarpur and Patna, while in the winter months (Nov-Feb), the AQI lies in the poor (101-200) category, and in the good to satisfactory categories in the rest of the seasons. HYSPLIT Backward trajectory analysis identified northwest India and the Indo-Gangetic plain as major aerosol sources for Bihar, with contributions of sea salt, mineral dust, and mixed aerosols from the Bay of Bengal, the Arabian Sea, and the Thar Desert to the study areas.

Mass-scale therapeutic use of tetracycline (TC) is substantially increasing its prevalence in the aquatic environments, posing potential ecological and health concerns. In this study, humic acid-modified Jeanbandyite (HAJB) was synthesized via a simple co-precipitation method, and its efficacy as an adsorbent was tested for TC removal from wastewater. Characterization studies successfully confirmed the formation of crystalline HAJB with spherical morphology, thermal stability, and superparamagnetism. Batch adsorption studies revealed that TC removal efficiency was strongly influenced by contact time, adsorbent dose, initial TC concentration, solution pH, and temperature. HAJB exhibited rapid adsorption, reached equilibrium within 6 h, and followed a pseudo-second-order kinetic model. The adsorption data fitted well to the Langmuir isotherm model, indicating monolayer adsorption with a maximum monolayer adsorption capacity (qm) of 129.8 mg g-1. The adsorption was highly efficient under acidic conditions (pH 4), where electrostatic attraction dominated. Thermodynamic parameters confirmed that the process was spontaneous and exothermic. Recyclability tests demonstrated that HAJB maintained a significant TC removal efficiency after five adsorption-desorption cycles, and real water studies showed moderate performance in the presence of competing ions. Overall, HAJB combines high efficiency, magnetic recoverability, and reusability, offering a promising, cost-effective strategy for the removal of TC from contaminated water.

Biodiesel represents a sustainable alternative to fossil fuels and aligns with long-term decarbonization goals. Integrating economic efficiency with sustainability requires a reinvention of process technology and artificial intelligence (AI)-based advanced prediction tools to maximize performance and minimize costs and carbon footprint. Under conservative estimates of 1% efficiency enhancement in an AI-driven optimization process, a 100-million kg/year microalgal biodiesel plant could save 3.6–5.7 million MJ/year of energy, corresponding to 457–719 tonnes of CO2eq reductions. However, these transitions become challenging due to the significant energy consumption required for AI modeling of nonlinear, complex datasets in energy production systems. This review focuses on current progress in designing energy-efficient AI models using green computing systems to advance smart energy systems. Four essential integrated pillars have been identified and discussed for implementation in an AI model framework that minimizes environmental impacts in biofuel synthesis. These pillars are Real-Time Process Optimization and Control, Predictive Intelligence and Resilience, Sustainable and Scalable Architecture, and Trustworthy and Compliant AI. A four-stage roadmap has been proposed to develop a low-energy framework for process optimization and predictive control. This roadmap includes moving from basic data infrastructure and pilot trials to the integration of key performance indicator dashboards, a human-assisted, semi-automated co-pilot phase, and, finally, a fully autonomous, closed-loop control system. Ultimately, AI tools offer a pathway to lower their own carbon footprint by following a clear roadmap and turning traditional production systems into next-generation biodiesel manufacturing platforms through cutting-edge technologies and a focus on creating incremental value through continual validation.