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Innovative Biosorbents from Agro-Waste: Advancing Sustainable Solutions for Heavy Metal, Dye, and Organic Pollutant Removal
Full text linkEnsuring clean water and safe food remains a global challenge due to the rising contamination of natural resources by heavy metals, dyes, and organic pollutants. This review highlights innovative, low-cost, and eco-friendly biosorbents derived from agricultural waste, presenting a comprehensive overview of their application in wastewater treatment. Unlike conventional reviews, this study categorizes a wide range of agro-waste materials including fruit peels, shells, husks, and plant residues according to their sorption properties and pollutant specificity. Notably, biosorbents such as activated carbon from rice husk, coconut shells, and banana peels demonstrated high adsorption capacities (up to 744.39 mg/g for dyes and 480.9 mg/g for heavy metals) under optimized conditions. The review further provides an in-depth analysis of chemical, thermal, and magnetic modifications that significantly enhance adsorption performance and selectivity. A key contribution of this work is the original economic analysis of these biosorbents, revealing their cost-effectiveness (as low as 0.49 €/kg) and practical scalability compared to commercial activated carbon. By integrating recent advancements, environmental implications, and regeneration potential, this review offers a valuable roadmap for researchers and practitioners aiming to implement sustainable, circular economy-based solutions in water purification systems
Mathematical Modelling and Numerical Simulation of Hydrodynamics with Flood Mitigation Strategies in the Mayo-Danay Department of Cameroon's Far North Region
Full text linkFlooding is the main structural problem faced by the Mayo-Danay department in the Far North Region of Cameroon, aggravated by climate change impacts, upstream deforestation, and the development and lack of maintenance of hydraulic infrastructure. This paper presents a new approach to develop a two-dimensional mathematical modelling combined with an advanced numerical simulation of hydrodynamics along the Logone River. The key originality aspect of this work lies in incorporating dynamic dyke breach scenarios together with seasonal real-time rainfall data allowing accurate flood propagation prediction at vital intervals. Flood risk mapping involves combining hydrodynamic behavior with topographic vulnerability parameters thus revealing areas under high risk. Detailed post-judgment analysis on Logone earthen dyke breach shows its highly destructive potential thereby emphasizing quite strongly the necessity for prevention strategies. Additionally, it evaluates sanitation infrastructure coupled with stormwater management through integrated urban drainage systems within this context. A preamble to what must be conceived as an exhaustive agenda for action is given by some recommendations: strengthening up Kousseri of the hydrometeorological network; satellite data and local observations complementing early warning systems; sustainable approaches that are reforested and integrated watershed managements done in parallelism with one another. The innovation lies in sophisticated digital and geospatial methodologies associated with territorial resilience strategies tailored to sub-Saharan contexts; this can be applied elsewhere where similar hydrological dynamics occur, thus providing a sound basis for scientific as well as political decision-making
Chlorophyll based Downy Mildew Analysis in Cucumber using Deep Learning
Full text linkCucumber is one of the major crops in Indian agrarian society, and it is affected by various diseases such as Downy Mildew. Monitoring the crop field's condition might help evade the disease, which is costly and time-consuming. Therefore, an economically intelligent farming system requires for disease monitoring. The grading of the disease can be recognized depending on the distribution of chlorophyll content in a leaf. However, previous grading techniques lead to an erroneous framework due to the inequitable statistics of real-time images' healthy and unhealthy pixel ordination. Hence, an optimized Deep Learning (DL) model is proposed according to the grading of the disease. The proposed DL model provides a training accuracy of 94.82% and a validation accuracy of 84.15%. The model also tested over 300 leaves with different grades of diseases captured randomly in an uncontrolled environment, and was found to be 90% accurate, compared to over 69% by visual identification of experts. A decision support system built on the proposed technology's instantaneous image capture and prediction capabilities is a huge help to farmers and agriculturists in understanding the state of the field and responding to such circumstances
Molecular Identification of Some African and Asian Tephritid Fruit Flies (Diptera) Using Mitochondrial Cytochrome Oxidase 1
Full text linkFruit flies of the family Tephritidae are among the most economically significant pests of horticultural crops worldwide, causing substantial losses in fruit production and trade. Accurate identification of species is crucial for effective pest management, quarantine, and biosecurity programs. In this study, mitochondrial cytochrome oxidase 1 (CO1) sequences were used to identify 15 fruit fly species from three genera (Bactrocera, Ceratitis, and Dacus). Complete DNA and amino acid sequences were determined, and phylogenetic relationships were assessed using sequences from both African and Asian populations. The CO1 marker proved effective for precise species identification and phylogenetic analysis, providing a valuable tool for both quarantine inspections and population genetics studies. This study provides the first molecular characterization of economically important fruit flies species from Sudan including some of Bactrocera species using mitochondrial COI gene sequencing. Previous work in the region focused mainly on morphological identification, which can be unreliable due to overlapping features among closely related species. The inclusion of molecular tools in this research enhances diagnostic precision, supports early detection of invasive fruit flies, and strengthens the foundation for integrated pest management (IPM) programs in tropical Africa. The generated COI sequence data will serve as a reference for future phylogenetic and biogeographical analyses of tephritid flies
Comparative Analysis and Optimization of Separation Technique of Carboxylic Acid-Water Mixture Using Aspen Plus
Full text linkAcetic acid (ethanoic acid) is widely employed as a food preservative, a versatile solvent, and as an intermediate in the synthesis of various industrial chemicals. Recent studies have emphasized process intensification strategies for its separation. Conventional distillation, though straightforward, requires a large number of trays and significant energy input. In contrast, azeotropic and extractive distillation offer improved efficiency with fewer stages and lower energy demand. This study investigates the separation of acetic acid–water mixtures using azeotropic and extractive distillation. Among the azeotropic agents, isobutyl acetate demonstrated lower energy consumption and reduced total annual cost (TAC) compared to vinyl acetate, while achieving high product purity (98.6% acetic acid and 99% water). For extractive distillation, methyl tert-butyl ether (MTBE) exhibited superior performance, yielding 99% purity for both acetic acid and water with minimum energy requirement and solvent usage, outperforming ethyl acetate, which achieved 98.2% acetic acid and 99% water. In comparison, conventional distillation provided only 92.1% acetic acid and 86.4% water. Overall, extractive distillation with MTBE proved to be the most efficient and cost-effective option for acetic acid purification
Recent Progress in Using Peroxymonosulfate for the Treatment of Organic Wastewater – A Brief Review
Full text linkIn recent years, peroxymonosulfate advanced oxidation processes (PMS-AOPs) have become an attractive method for the treatment of refractory organic wastewater, relying on their ability to generate highly oxidizing active species (SO4·-, ·OH, and 1O2, etc.). In this review, the characteristics of PMS-AOPs are firstly introduced, followed by a systematic introduction of peroxymonosulfate (PMS) activation methods, including energy-assisted activation, metal-based material activation, carbon-based material activation, and composite system activation. Subsequently, the effects of critical parameters (wastewater pH, reaction temperature, PMS dosage, catalyst loading, inorganic ions and natural organic matter, and reaction time) on the performance of PMS-AOPs were discussed. Furthermore, the working mechanisms of PMS in PMS-AOPs were proposed, and finally, potential research directions in the near future were suggested. This review provides fundamental analysis and discussion of PMS-AOPs in the treatment of refractory organic wastewater
Corrigendum to: Human Footprint on Natural Systems: Missing Post-war Scenario in the Urban Context of Damascus
Full text linkAll regions in Syria have witnessed a decline in green spaces due to the spread of illegal logging operations and a decline in interest in agricultural wealth due to the
Systems. Missing post-war Scenario in the Urban Context of Damascus,” the author would like to revise the Acknowledgement and Credits sections to better reflect the contributions of collaborating institutions.
The revised sections are provided below:
Acknowledgement
[A]FA has been collaborating with the Faculty of Architecture of the University of Damascus and the Damascus-based Reparametrize Foundation as part of their ongoing project Recoding Post-War-Syria, Zamalka. Students have been selected from each institution to participate in the lab.
Credits
[APPLIED] FOREIGN AFFAIRS, IoA, University of Applied Arts Vienna / Reparametrize Studio
These revisions do not affect the scientific content, results, or conclusions of the article. The author and the editorial team regret the omission and have now rectified the record
GIS-Based Evaluation of Pollution Sources and Water Quality Status in the Turag River, Bangladesh
Full text linkThis study evaluates pollution sources and water quality status in the Turag River, Bangladesh, using Geographic Information System (GIS) techniques and Water Quality Index (WQI) assessment. The Turag River, classified as environmentally critical since 2009, faces severe degradation due to untreated industrial effluents from pharmaceutical facilities, textile mills, and manufacturing units located along its banks. Water samples were collected from nine strategic locations and analyzed for eight physicochemical parameters (pH, dissolved oxygen, biochemical oxygen demand, total suspended solids, turbidity, phosphate, nitrate, and temperature) using standard protocols. GIS-based spatial mapping revealed significant spatial heterogeneity in pollution levels, with BOD values (53-90 ppm, mean 73 ppm) and turbidity levels (40-80 NTU, mean 58.77 NTU) exceeding Department of Environment standards at all sampling sites. The calculated WQI values ranged from 35.14 to 38.83 (average 36.68), placing the river water quality consistently in the "Bad" category across all sampling locations. The northern section exhibited critical conditions for dissolved oxygen (3.4-3.5 ppm) and turbidity (75-80 NTU), while the southern segment showed elevated levels of BOD, phosphate, and nitrate. The consistently poor water quality classification indicates severe degradation, limiting usability to agricultural irrigation purposes only. These findings provide a foundation for developing targeted pollution control strategies and highlight the urgent need for comprehensive watershed management to restore this vital water resource
Editorial: Seaweed-based Carbon Sequestration: A Sustainable Green Approach Towards Climate Change Mitigation
Full text linkRising atmospheric CO₂ levels threaten global biodiversity and human well-being, driving interest in sustainable, carbon-negative solutions. Seaweeds have emerged as a key blue carbon resource due to their rapid growth and high capacity for organic carbon fixation. This paper examines various seaweed-based carbon sequestration mechanisms—photosynthesis, sedimentation, and carbon-neutral product development—and introduces models for estimating net CO₂ removal in aquaculture systems. Despite their potential, seaweed ecosystems face challenges such as ocean acidification and habitat degradation. To address these, the study advocates for large-scale seaweed mariculture, restoration, and ocean afforestation, supported by public-private initiatives and aligned with the UN Sustainable Development Goals. Seaweed cultivation is presented as a viable, nature-based solution for climate change mitigation and long-term carbon storage
Vector Lattice Data Analysis: Fitting and Model Uncertainty
Full text linkFunctional data analysis (FDA) is a popular research area of data analysis that is well-suited for modeling complex data structures such as time series data and images. In Linear Regression models, the random variables are often described using a finite--dimensional vector space, under the assumption that the random variables are represented by a finite set of parameters. FDA allows us to model random variables as functions. This can lead to a more flexible and expressive approach to the statistical model. Within FDA, the specific paper investigates the potential of vector lattices to enhance model flexibility and address model uncertainty. The limitations of finite-dimensional vector spaces in capturing the complexities of real-world random variables are discussed. An investigation is conducted into the concept of Vector Lattice Linear Regression Models (VLLM), highlighting their ability to effectively handle model uncertainty