Nature Environment and Pollution Technology

Energy-Efficient and Intelligent Autonomous Spraying Robot for Precision Agriculture Using Solar Power and Fuzzy Logic

This article presents the development of a solar-powered intelligent pesticide-spraying robot designed to enhance environmental sustainability in precision agriculture. By integrating renewable energy with intelligent decision-making, the system significantly reduces reliance on fossil fuels and minimizes pesticide overuse. The robot is powered by a solar panel with an adjustable tilt for optimal energy harvesting and incorporates a lead-acid battery for energy storage to maintain continuous operation. A water pump and DC motors facilitate mobility and spraying functions. The integration of fuzzy logic enables adaptive, real-time decision-making based on environmental parameters, ensuring precise and efficient pesticide application. Experiments across different weather conditions demonstrated superior performance in unshaded environments, with battery limitations observed during extended cloudy periods. Results showed a 24% reduction in pesticide use and 93% average coverage accuracy. This study underscores the environmental benefits of clean energy and intelligent control, and recommends the future integration of Internet of Things (IoT) technologies and battery upgrades to further enhance operational sustainability and field autonomy.

M. H. F. Md Fauadi, T. Tibyani, N. N. Majdi, S. J. Tay and D. A. Kurniawati

Machine Learning-Based Snow Cover Mapping in Uttarkashi, Chamoli and Pithoragarh Using Cloud-Based Remote Sensing Tool

Snow cover monitoring is essential for hydrological modelling, climate change analysis, and water resource management, especially in the Himalayan cryosphere. The most cutting edge global open-source platform for sophisticated geospatial big data analysis is Google Earth Engine (GEE). This study leverages Google Earth Engine (GEE) and data sets available, that is, Harmonized Sentinel-2 imagery, VIIRS, and Digital Elevation to delineate annual snow cover in Uttarkashi, Chamoli, and Pithoragarh districts of Uttarakhand. This paper aims to (i) Land Use Land Cover (LULC) Mapping. (ii) Detection of Snow cover in the Himalayan region districts of Uttarkashi, Chamoli, and Pithoragarh, Uttarakhand, India, using the annual composite median of Sentinel-2 imagery. (iii) To compare the performance of various machine learning models, that is, Random Forest (RF), Support Vector Machine (SVM), and Classification and Regression Tree (CART) for 5 classes. (iv) To calculate the area of 5 classes for the years 2019 and 2024. (v) To build classified maps using the algorithm that results in the best overall accuracy. Here, three machine Learning approaches, Random Forest (RF), Support Vector Machine (SVM), and Classification and Regression Tree (CART), are trained using input parameters such as bands, spectral indices (NDVI, NDBI, NDSI, BSI), and topographic parameters (elevation, slope) derived from ALOS DEM. Cloud masking techniques refine the dataset, ensuring high-quality spectral inputs. The result demonstrated the successful mapping of LULC’s five land cover classes: bare soil, snow, vegetation, built-up areas, and water bodies. The study demonstrated high classification accuracy in 2019 for RF, SVM, and CART across all districts, achieving 95.7%, 93.2%, and 90.7% in Chamoli, 96.5%, 97.3%, and 95.6% in Pithoragarh, and 88.6%, 90.0%, and 87.3% in Uttarkashi. In 2024, the accuracy rates improved to 96.2%, 93.9%, and 94.6% for Chamoli, 95.8%, 92.5%, and 91.6% for Pithoragarh, and showed significant gains reaching 95.4%, 95.4%, and 96.1% for Uttarkashi. Results indicated that estimated In Chamoli, RF consistently performed better, demonstrating an 8.3% increase in snow from 2,206 km² to 2,388 km², while Pithoragarh experienced a 25% loss from SVM to RF (from 2,099 km² to 1,573 km²). Snowfall in Uttarkashi increased by 10.8% from SVM to CART: from 1,804 km² to 1,998 km2, with CART doing exceptionally well in 2024.RF proved most reliable overall, but regional variability suggests a need for adaptive model selection.

Shikha Goswami and Alaknanda Ashok

Mathematical Modeling of Oxygenation Capacity in Wastewater Based on Air Diffuser Type

The oxygenation capacity in wastewater directly affects the performance of biological treatment systems. In this context, this study develops a mathematical model that describes this capacity as a function of the aeration system used. Three configurations were evaluated: fine bubble, coarse bubble, and extra coarse bubble, using experimental tests that measured dissolved oxygen concentration, saturation time, and the overall mass transfer coefficient (kLa). The resulting models achieved high fit (R² between 0.9988 and 1), supporting their validity in representing the observed behavior. The fine bubble system showed the highest initial oxygenation capacity, reaching 1.28 mg.L?¹.s?¹, though it decreased significantly over time by 96.09%. Overall, the results quantitatively characterize the dynamics of each diffuser type, providing relevant technical criteria for the design and selection of wastewater treatment systems.

Arlitt Amy Lozano Povis, Oscar Sedano Vargas, Joel Colonio Llacua and Elvis Carmen Delgadillo

Eco-Smart Geomaterials and Nano-Engineered Soils: Innovations in Geotechnical Engineering for Pollution Mitigation and Environmental Sustainability

Nanotechnology and smart materials have emerged as? crucial fields for building, analyzing, and studying soil-related infrastructure systems with enhanced performance and sustainability. This review covers the recent progress in nano-engineered soils and smart materials, including their types and mechanisms of interaction with soil matrices, and further?explains their prospective applications in stabilization, reinforcement, sensing, and ground improvement technologies. Widely used nanomaterials, such as nano-silica, nano clay, carbon nanotubes, graphene, and nano-calcium carbonate, have? great potential to enhance geotechnical properties, including shear strength, compressibility, and permeability. A novel approach using smart materials, including piezoelectric materials, shape memory alloys (SMAs), electroactive polymers, and self-healing composites, bestows adaptive functions and integrated sensing capabilities upon soil systems, enabling real-time monitoring and adaptive behavior. This review also discusses the environmental consequences and sustainability considerations? of implementing these advanced materials. In this regard, aspects of life cycle?assessment (LCA), potential toxicity, and bioaccumulation risks are also highlighted, and the potential of eco-friendly and bio-inspired alternatives is highlighted as part of promoting green geotechnical practices and models of the circular economy. With advances on the horizon, the public implementation of these materials is impeded by challenges, including challenges with their?dispersion, their long-term performance, their high costs, the lack of verifiable guidelines, and regulatory frameworks. Finally, the?paper concludes with directions for future research, such as the necessity for field-scale validations, integration with Artificial Intelligence and Internet of Things technologies for smart soil systems, and formulation of eco-friendly, bio-compatible nanomaterials. This review emphasizes that?nano-engineered soils and smart materials can reshape geotechnical engineering and offers forward-looking perspectives on how asset (infrastructure) owners and the construction industry may benefit from resilient, intelligent, and sustainable solutions.

Krishna Prakash Arunachalam, Syed Aamir Hussain, Sameer Algburi, Syed Sabihuddin, Salah J. Mohammed, Hasan Sh. Majdi and Adel Hadi Al-Baghdadi

Comet Assay Evaluation of Cadmium Chloride-Induced DNA Damage in Cyprinus carpio (Common Carp) and the Genoprotective Role of Selenium

Heavy metal contamination in aquatic environments represents a significant threat to biodiversity and the sustainability of aquatic resources, with cadmium being among the most toxic pollutants owing to its high bioaccumulation potential and genotoxic effects. This study investigated the genotoxicity induced by cadmium chloride (0.78 ppm and 1.56 ppm) in Cyprinus carpio (common carp). The ameliorative efficacy of selenomethionine (0.25 and 0.50 ppm) as a genoprotective agent was evaluated. The comet assay, a widely used technique in genetic toxicology, was employed to quantify DNA damage in fish tissues, providing sensitive and reliable measures of genotoxic effects. The results revealed a dose dependent increase in DNA strand breaks following cadmium chloride exposure, indicating significant genotoxicity. Conversely, co-treatment with selenomethionine notably reduced DNA damage, highlighting its potential to mitigate Cd-induced genotoxicity. These findings enhance our understanding of heavy metal toxicity and instill hope for the potential use of selenomethionine as a sustainable intervention to protect aquatic life. From a societal perspective, protecting fish health is crucial for global food security and the well-being of millions who rely on fisheries for their livelihood. The protective capacity of selenium underscores the promise of sustainable, environmentally safe interventions to combat pollution, foster ecological resilience, and preserve natural resources for future generations. This study identifies knowledge gaps and provides a comprehensive understanding of DNA damage assessment through the prism of the comet assay, highlighting the protective role of selenium in alleviating Cd-induced genotoxicity.

P. Nivethitha and L. Arul Pragasan

Variation in the Concentrations of Polycyclic Aromatic Hydrocarbons in the Northern Part of Shatt Al-Arab River, Basrah, Iraq

Polycyclic aromatic hydrocarbons (PAHs) are long-lasting organic pollutants with serious environmental implications in aquatic ecosystems, notably the Shatt al-Arab River system that sustains millions of residents in southern Iraq. The north branch of this important waterway is under extreme environmental stresses of industry and oil activities, but the fluctuation patterns of PAHs by seasons remain unknown. The samples of water were collected at five strategic stations (Al-Qurna, Al-Shafi, Al-Dair, Karma Ali, and Al-Zuraiji) along the northern Shatt al-Arab River during summer (June-August 2024) and winter (December 2024-February 2025) seasons. Two replicate samples were collected at each station for each season, totaling 20 samples. PAH was determined by gas chromatography-mass spectrometry (GC-MS) following UNEP methodology. In situ environmental parameters like water temperature and pH were measured. Statistical analysis included ANOVA, cluster analysis, and correlation analysis to examine spatial and temporal variation. The PAHs ranged from 2.24 to 11.28 ng/L, far higher in summer (mean 9.46 ng/L) than winter (mean 7.20 ng/L). The most dramatic finding was the extreme seasonal variability in PAH composition, with higher molecular weight PAHs (4+ rings) dominating summer samples (78.4% total PAHs) and lower molecular weight PAHs (2-3 rings) dominating winter samples (82.7%). This provided a 17-fold seasonal difference in the low molecular weight/high molecular weight (LMW/HMW) ratio (summer: 0.28, winter: 4.81). Statistical correlation revealed a strong negative correlation between water temperature and the ratio of LMW/ HMW (r = -0.88, p < 0.001), indicating temperature as a dominant factor governing seasonal patterns of PAH composition. Spatial distribution of PAH concentration revealed hotspots at Karma Ali and Al-Shafi stations, close to industrial activities and oil installations. Diagnostic ratios revealed predominantly petrogenic sources in winter and mixed petrogenic-pyrogenic sources in summer. This study provides key baseline data on the seasonality of PAH composition variation for the Shatt al-Arab River system. The extreme seasonality of PAH composition, together with elevated summer levels of carcinogenic PAHs, suggests potential hazards to aquatic life and human health. The findings highlight the imperative need for seasonally specific monitoring protocols and focused pollution abatement measures for this ecologically and economically important water body.

Huda A. Abdulraoof and Firas M. Al-Khatib

Health Risk Assessment of PM10-Bound Heavy Metals in the Ambient Air of Gurugram Urban Area

Gurugram is a rapidly developing corporate and industrial hub facing severe air pollution. In this study, ambient particulate matter (PM10)-bound heavy metals, their source apportionment, and potential human health risks were investigated in the urban area of Gurugram, Haryana. A total of 56 samples were collected using a respirable dust sampler (APM 460) with Whatman filter paper (EPM 2000) from October 2022 to April 2024, excluding the monsoon months. The annual average PM?? concentration was 169.5 ?g.m-³, which is about 11 times higher than the WHO (2021) guidelines and 3 times higher than the NAAQS by CPCB. Seasonal variations were observed, with the highest PM?? levels recorded during the post-monsoon season, followed by winter. Heavy metals (Cr, Mn, Ni, Pb, Cd, Cu, Fe) were analyzed using ICP-MS, with Fe (10.9 ?g.m³-) being the most abundant. Enrichment factor analysis revealed high Pb levels, indicating anthropogenic sources. Human health risk assessment revealed that the hazard index (HI) values exceeded the threshold limit (=1) for all three exposure pathways. This finding indicates that the population residing in the study area is prone to non-carcinogenic risks due to PM10-bound heavy metals. Excess cancer risk (ECR) values for the HI were found to be above the safe limit (10?? – 10??). Consequently, this suggests that exposure to PM10 in the study area may lead to an elevated risk of developing cancer over a lifetime, thereby underscoring the potential public health threat posed by these heavy metals. The conclusions demonstrate that tougher measures and stronger efforts must be taken to tackle heavy metal pollutants and the risks they pose to health.

Vandana Yadav and Vikram Mor

Assessment of Sediment-Associated Heavy Metals and Physicochemical Interactions in Telaje-Cabugan Creek, Philippines

Heavy metal contamination in freshwater ecosystems poses a persistent threat to environmental and public health, particularly in urban regions with limited waste management infrastructure. This study assessed the concentration and spatial distribution of cadmium, lead, manganese, and zinc in the water and sediments of Telaje-Cabugan Creek, a tributary of the Tandag River in Surigao del Sur, Philippines. Water and sediment samples were collected from three designated sites and analyzed using atomic absorption spectroscopy. Physicochemical parameters, including pH, salinity, temperature, turbidity, and depth, were also recorded. Statistical methods, including one-way ANOVA and Pearson correlation, were used to assess spatial variations and environmental influences on metal concentrations. Results showed that only manganese was detected in water, while zinc, lead, and cadmium were present in sediments, with cadmium below the detection limit in both matrices. Zinc concentrations exceeded international sediment quality thresholds, indicating moderate pollution, while other metals remained within acceptable levels. No significant spatial differences were observed in heavy metal concentrations across the sampling sites. Correlation analysis revealed that manganese in sediments was significantly influenced by salinity and pH, suggesting environmental conditions can affect its mobility. The findings provide baseline data for local water quality management and highlight the need for integrated interventions to address diffuse sources of contamination in urban freshwater systems.

Luzminda S. Bacquial, Khenn D. Temporosa, El Dixon G. Plazo and Niel O. Llano

Adaptation, Impact and Barriers to Climate-Smart Agriculture: Empirical Evidence from Arunachal Pradesh

This study analyzes how tribal farming communities in Arunachal Pradesh are adapting to climate-smart agriculture (CSA), its impact on their livelihoods, and the key challenges they face. The study is based on primary data collected from 250 farmers through a structured schedule. The analysis employs binary logistic regression to identify the factors that drive adaptation and applies propensity score matching (PSM) to measure its outcomes. A problem confrontation index (PCI) is used to rank the barriers. The results show that 43% of farmers have adopted CSA practices. Adaptation is more likely among individuals with higher levels of education, access to irrigation, younger household members, and involvement in institutions, such as farmer groups. Farmers who adopted CSA reported major gains: crop yields increased by 51%, farm income increased by 58%, and food security improved by 19%. However, CSA had limited effects on reducing greenhouse gas emissions and improving carbon sequestration. Despite its benefits, many farmers face serious obstacles. The biggest challenges include weak agricultural extension services, low awareness of CSA, high cost and poor availability of improved seeds, and limited access to institutional credit. The study suggests training on CSA, better agricultural extension support, and inclusive financial services for better CSA adaptation. CSA has the potential to enhance productivity and resilience in tribal farming systems with the right support. It can play a key role in promoting sustainable agriculture in the region.

Bondita Saikia, Krishna Raj and James Riffat

Performance Evaluation of Sustainable Pervious Concrete Incorporating Industrial and Agricultural Byproducts

The sustainable advancement of pervious concrete through the integration of industrial and agro-industrial waste materials presents a promising approach for addressing environmental challenges. This study investigated the effects of incorporating rice husk-derived activated carbon, iron slag, and 5% replacement of adhesive cement (by weight) into pervious concrete mixtures. The performance was evaluated in terms of compressive strength, porosity, permeability, and water purification capabilities, which are particularly relevant in pervious concrete applications, such as stormwater management, where both infiltration and pollutant filtration are crucial. The experimental findings showed that Mix 1 (iron slag + 5?hesive cement) achieved the highest 28-day compressive strength of 22.13 N.mm-², representing an increase of 4.2% over the control mix (CM) at 21.24 N.mm-². The 14-day and 7-day strengths of Mix 1 were 19.2 N/mm² and 14.52 N.mm-², respectively, which were higher than those of the control (17.24 N.mm-² and 11.9 N.mm-²), indicating improved early and long term strength. This mix also achieved the highest porosity (24.42%), a 13.5% improvement over the control (21.52%), leading to enhanced permeability and drainage capacity. Water quality testing demonstrated that Mix 2 reduced the pH from 8.65 to 7.34, bringing it within the WHO acceptable limits, and functioned effectively as a passive water treatment solution. While Mix 3 provided moderate pH neutralization (to 7.86), Mix 4 showed the greatest reduction (to 6.82), however, it may require buffering to prevent over-acidity. Regarding water hardness, Mix 4 achieved a 38.9% reduction (from 232.5 to 142 mg.L-1), likely due to enhanced ion exchange and precipitation mechanisms contributed by the activated carbon and iron slag. Mix 2 also showed a significant 26.2?crease, confirming its potential to improve water filtration. This study supports the incorporation of waste-derived materials into pervious concrete to enhance environmental sustainability, promote groundwater recharge, and improve urban infrastructure through eco-conscious construction methods.

Sanket Kalamkar, Sanjay Raut, Pawan Hinge, Akash Kaley and Rutuja Adhau

Comparative Assessment of Solar Distillation of Graywater with and without Boiling for the Production of Distilled Water

Water scarcity in dry urban areas has led to increased use of graywater for potential reuse. Among affordable water treatment methods, solar distillation stands out as an appealing option; however, there is limited documentation on its performance with actual effluents and a direct comparison between boiling and non-boiling configurations. In this study, we compared the solar distillation of domestic graywater using two setups: (i) a boiling system, comprising a CK-002 solar cooker connected to a black-painted copper still, copper coil, and condenser, and (ii) a non-boiling system, featuring a single-slope glass-covered solar still. Graywater was collected from five households in Tacna, Peru, with 5-liter batches treated over 11 h on sunny days. The study recorded distillate volume, physicochemical parameters (pH, conductivity, turbidity, nitrates, nitrites, sulfates, BOD?, and COD), metal concentrations, and microbiological indicators such as fecal coliforms, Escherichia coli, and heterotrophic bacteria. Results indicated that the boiling distillation produced 2,790 mL of distillate, while the non-boiling system yielded 1,725 mL, a statistically significant difference (? = 0.05). Physicochemical analysis showed significant differences only in turbidity, conductivity, and nitrates, with the non-boiling system demonstrating superior removal (>90%). Total metal removal was 98.63% (reducing from 445.03 mg L-1 to 6.06 mg L-1) in the boiling setup and 98.56% (to 6.37 mg L-1) in the non-boiling. Microbiological testing revealed both systems effectively reduced contaminants: fecal coliforms by 99.76%, heterotrophic bacteria by 99.99%, and E. coli by 98.04%. Overall, solar distillation-whether boiling or not-substantially decreases microbiological pathogens and metals. Nonetheless, due to the persistence of certain organic compounds, such as biodegradable organic matter that exceeds Peruvian environmental standards, solar distillation is best used as a barrier step within a treatment chain designed for limited reuse or combined with additional treatments to meet regulatory limits.

Mariel Alejandra Quispe-Collao, Javier Lozano-Marreros, Efren Eugenio Chaparro-Montoya, Augusto Cahuapaza-Morales, Yessenia Danidtza Gomez-Aguilar, Keila Abigail Muñante-Carrillo, Leo Ulises Michaell

Interlinking of Lakes with Emphasis on Groundwater Recharge Under the Climate Change Impact

Climate change has intensified water-related challenges, particularly in regions that rely on seasonal rainfall and groundwater for agriculture and daily needs. Among nature-based solutions, interlinking lakes has emerged as a promising approach to improve groundwater recharge, manage surface runoff, and enhance long-term water resilience. This review explores lake connectivity as a decentralized and adaptive strategy for sustainable water resource management under changing climatic conditions. It compiles and analyzes existing research on the hydrological, ecological, and climatic impacts of interlinked lake systems, with particular emphasis on their contribution to groundwater replenishment. The paper aims to synthesize the current state of research on lake interlinking, focusing on its potential to enhance groundwater recharge and contribute to climate change adaptation. It draws on academic literature, technological approaches, case studies, and institutional practices to offer a comprehensive perspective on this nature-based solution. The synthesis of findings indicates that interlinking lakes can serve as a nature-based solution to mitigate the adverse effects of climate change, enhance groundwater sustainability, and support integrated watershed development. The paper does not aim to test a specific hypothesis or introduce a new predictive model. Instead, it serves as a foundation by synthesizing existing knowledge, examining current research directions, and outlining areas that require further exploration.

Kumud S. Meshram, Tripti B. Gupta, Sameer Algburi, Salah J. Mohammed and Ali Majdi

Solar-Based Polygeneration Systems for a Carbon Neutral Future with Focus on Hydrogen Production: A Comprehensive Review

Solar-driven energy systems have made a significant contribution to accomplishing global sustainability goals and reducing greenhouse gas emissions and pollutant levels. The increase in the development of multigeneration systems is predominantly significant because these systems efficiently address the growing and diverse demands for energy. Simultaneously, hydrogen has emerged as a promising alternative fuel, garnering considerable attention for its potential to replace conventional energy sources. In addition to hydrogen, other distinctive outputs, such as power, heating, cooling, domestic hot water, and freshwater demands, can be met using this technology. As solar energy is used extensively for electricity and heat generation, photovoltaic–thermal (PVT) systems are emerging as highly reliable and capable approaches for sustainable energy solutions. This study emphasizes the inclusion of hydrogen production methods into polygeneration systems. Recent progress in concentrated photovoltaic-thermal and photovoltaic-thermal technologies, focusing on improvements in system performance. This study concludes that different system configurations and the incorporation of new technologies have significantly optimized PVT designs. Looking ahead, PVT systems offer a promising route for clean energy production. The integration of PVT and combined cooling, heat, and power (CCHP) technologies marks a transformative step toward achieving net-zero energy buildings and decarbonized energy systems, making them a crucial element in the global transition to clean and efficient energy production. Further progress in cost competitiveness could drive broader adoption. Additionally, it presents the growing demand to explore the potential of green hydrogen as an energy source and energy carrier. The study concludes that concentrated photovoltaic–thermal (CPVT) systems demonstrate outstanding performance in solar-based multigeneration applications, achieving energy efficiency as high as 78.93% and exergy efficiency of up to 65%. These high values underscore the capability of CPVT technology to effectively harness both electrical and thermal energy, making it highly suitable for integrated systems targeting hydrogen production, heating, and cooling.

G. S. Girishkumar, M. R. Kamesh, N. Shreekala, D. Yogaraj, M. Mohammed Nadeem, B. R. Hemanth and K. S. Nagaprasad

Assessment of Groundwater Quality Affected Due to Leachate Contamination at Municipal Dumpsite, Mandya

Open disposal of municipal solid waste elevates the risk of groundwater contamination. This study evaluated the pollution potential of leachate from a solid waste disposal site and its impact on aquifers in the Mandya region of Karnataka, India. Unplanned disposal of municipal solid waste (MSW) led to leachate accumulation within the waste mass, subsequently flowing into nearby water bodies, such as open wells and ponds. Physico-chemical parameters and heavy metal tests were conducted on leachate and groundwater samples to assess their quality against drinking water standards (IS: 10500 – 2012). The Leachate Pollution Index (LPI) and Water Quality Index (WQI) were calculated based on the test results. The LPI value indicated that the leachate from the landfill site was moderately contaminated. The WQI revealed that groundwater quality in the area ranged from good to poor and unsuitable for drinking in certain cases. Hierarchical cluster analysis (HCA) categorized groundwater samples into high, moderate, and low groups based on their total dissolved solids (TDS) levels, helping to identify trends in water quality and potential pollution sources. The findings were visualized using geographic information system (GIS) software to enhance public understanding and support the implementation of preventive measures against potential environmental risks.

Madhusudhan, M. S., Chowdegowda, H. C. and Varshitha, M. S.

Evolution of Flood Forecasting: A Comprehensive Review of Traditional and Sophisticated Approaches

Flood forecasting is considered vital worldwide, as communities, infrastructure, and the environment face significant risks from floods. This study provides a comprehensive overview of both traditional and advanced flood forecasting methods, focusing on their strengths, limitations, and suitability for different situations. Traditional methods, such as empirical rainfall-runoff relationships and analysis of historical flood data, serve as fundamental approaches based on past patterns and local knowledge. However, these approaches often lack precision and responsiveness to real-time changes in climate and land use. Conversely, the accuracy and lead times of flood forecasts have been enhanced using advanced computational models, remote sensing, machine learning, and deep learning techniques. Technologies like hydrodynamic modeling, satellite-based monitoring, and hybrid models demonstrate higher predictive capabilities by incorporating real-time data and spatial analysis. Recent flood case studies are examined in this research, comparing the accuracy, efficiency, and flexibility of traditional versus modern methods. The results indicate that while traditional techniques are valued for their simplicity and low cost, modern forecasting methods offer greater precision and adaptability, both of which are crucial for proactive disaster management in a changing climate. This study recommends a hybrid approach that combines traditional knowledge with modern technology to improve the accuracy and reliability of flood forecasting systems.

Reena, S., Harikrishnan, D. and Salaji, S.

Enhancing Photovoltaic (PV) System Efficiency Through Integrated Inclination Control and I-V Curve-Based Diagnostics

Photovoltaic (PV) systems have become central to the global transition toward renewable energy; however, their efficiency is often compromised by environmental variability and inadequate monitoring integration. Therefore, advanced supervisory platforms that unify data acquisition, fault detection, and performance optimization have become increasingly important. Existing monitoring approaches do not adequately integrate grid-connected and isolated systems with real-time diagnostic capabilities. This study was undertaken to develop and validate a supervisory interface capable of simultaneously monitoring multiple PV configurations while incorporating image-based shading detection and tilt optimization. The methodology combined the hardware implementation of rooftop and ground-mounted PV modules, sensor-based data acquisition through LabVIEW, integration with MATLAB/ Simulink modeling for system validation, and camera-based analysis for shading and tilt detection. The results demonstrated that shading of a single cell could reduce the total power output by nearly 50%, whereas tilt optimization of approximately 34° increased the energy yield by 14%. The integrated operation of rooftop and ground-mounted systems improved the daily energy output by 11% compared to standalone systems. Statistical analysis confirmed the robustness of these findings, with performance ratio and efficiency indices showing consistent alignment across trials. The developed interface effectively linked the manufacturer specifications of modules and inverters with field performance, enabling accurate benchmarking and anomaly detection. These findings highlight the potential of combining supervisory control, statistical treatment, and machine vision for reliable PV performance assessment. The work suggests that future research should extend the supervisory platform toward predictive maintenance and integration with smart grid infrastructures to further enhance scalability and resilience.

S. M. Kamali, V. Malathy, Ratchagaraja Dhairiyasamy, Deekshant Varshney and Subhav Singh

Synergistic Effect of Hydraulic Upflow Velocity and TSS Concentration on Biogranule Formation in Fluidized Bed Reactors (FBR)

Rapid urbanization in Andean cities presents unique wastewater management challenges, particularly due to the high concentrations of suspended solids (SS) in stormwater runoff, which impair treatment efficiency. This study investigated the combined effects of upflow velocity (UV) and SS concentration on biogranule formation in an upflow anaerobic sludge blanket reactor (UASBR) under conditions simulating tropical highland environments. Synthetic wastewater containing kaolinite clay (83.17% SiO?, 13.52% Al?O?, particle size 0.32–0.87 µm) was used to simulate inorganic SS. The reactors were tested at UVs of 0.3, 0.6, and 0.9 m.h-1 and SS concentrations ranging from 212.5 to 280 mg.L-1. Granule morphology and size were monitored weekly using scanning electron microscopy (SEM). The results showed that UV critically affected granulation: low velocity (0.3 m.h-1) led to excessive compaction (10.8 µm), while high velocity (0.9 m.h-1) caused biomass washout (11.6 µm). The optimal conditions (0.6 m.h-1 and 212.5 mg.L-1) yielded stable, well-formed granules (13.05 µm) and high reactor efficiency. Higher SS loads disrupted microbial aggregation, reducing granule size to 7.6–12.91 µm. The findings highlight that maintaining a UV of 0.6 m.h-1 and SS ?212.5 mg.L-1 enhances granule development, offering a feasible strategy for the anaerobic treatment of SS-rich wastewater in high-altitude urban regions.

Orlando Vilca, Ever Ingaruca, Erick Huamán, Yanet Cusi Vargas and Ruth Campos

Potential of Agro-Industrial Wastes to Address Environmental Challenges - A Review

The cement industry is one of the largest contributors to global carbon emissions, accounting for a significant share of industrial greenhouse gases. In response to this challenge, researchers have increasingly explored the use of agro-industrial waste as a sustainable alternative to conventional cement-based materials. This study reviews and assesses the environmental potential of such waste-derived construction products, focusing on their ability to reduce emissions and conserve natural resources. Findings indicate that substituting traditional cement with eco-friendly, waste-based materials could achieve up to a 32% reduction in greenhouse gas emissions, thereby offering a tangible pathway toward decarbonization of the construction sector. Beyond emission reduction, these materials also address critical issues of resource scarcity by valorizing agricultural and industrial by-products that would otherwise contribute to waste streams. The integration of these innovative materials into mainstream construction practices represents a unique opportunity to simultaneously mitigate climate change, promote circular economy principles, and advance the development of environmentally responsible infrastructure.

Anshul Nikhade, Devendra Padole, Sameer Algburi, Monali Wagh, Harshal Nikhade, Ahmed M. Abdulhadi, Hasan Sh. Majdi, Adel Hadi Al-Baghdadi and Prajakta Waghe

High Energy Biocrude from Water Hyacinth via Hydrothermal Liquefaction

The world is transitioning to bioenergy from biomass to reduce carbon dependence and address environmental challenges. This study demonstrates the potential of hydrothermal liquefaction (HTL) to convert invasive water hyacinth biomass into renewable biofuel. Uniquely, this research comprehensively utilizes all plant components, roots, leaf stalks, and leaves, with particular emphasis on lipid-rich roots (18.25% lipid content), which have been largely overlooked in previous HTL studies. Water hyacinth underwent HTL at 300°C for 60 min using 10% solid loading, achieving 28.2% biocrude yield with a higher heating value of 33.02 MJ.kg-1, comparable to conventional petroleum. Elemental analysis confirmed biocrude’s renewable energy potential with 68.8?rbon and 9.1% hydrogen content. By-product biochar showed an HHV of 18.02 MJ/kg as well, suggesting that it can also be used for energy purposes. Large fractions of heavy fuel oils and a variety of functional groups (esters, alcohols, carboxylic acids) were detected by GC-MS and FTIR analysis, further confirming the feasibility of this technique. This study confirms that hydrothermal liquefaction of water hyacinth is an effective option for the reduction of this invasive species and a feedstock for renewable energy production.

Raihan Khan Opu, Md. Sabbir Hasan Monir, Md. Shafiul Bashar, Sreekanta Das and Md. Showkat Osman

A Comprehensive Review on Iron Oxide and Iron Oxide-based Nanomaterials for Wastewater Treatment

The growing need for water and the increase in wastewater generation globally demand efficient water treatment processes. Conventional water remediation efforts are insufficient to meet current water treatment requirements. Nanomaterial water remediation has shown promising results and needs to be explored on a larger scale to address these issues. The most recent focus has been on composite nanomaterials made of iron oxide magnetic and superparamagnetic NPs, which have attracted considerable interest owing to their desirable characteristics, including excellent after-use recovery, targeted quality, and affordability. Iron oxide-based nanomaterials can remove organic and inorganic contaminants in multiple ways. In addition, several nanocomposites have been employed to improve their performance and incorporate novel advantageous characteristics. Chemical, green, and biological processes are used to produce these materials. Synergistic properties for water cleanup have been demonstrated using various iron-based nanocomposites. Various mechanisms of pollution removal, such as adsorption, desorption, photocatalysis, and flocculation/coagulation, have been targeted during the design of NPs. The types of water pollutants, choice of remediation methods, and various methods required for QC and the efficiency of these nanomaterials were reviewed. This review discusses various methods for preparing magnetic nanoparticles, their composite materials, the mechanism of pollutant removal, and recent applications exploring synergistic behavior for pollution removal for efficient water remediation. Issues such as safety, toxicity, removal after use, and disposal of these materials are also discussed. This manuscript provides a quick overview of iron oxide nanomaterials as a reference for advancing further studies in this area. We plan to contribute to the production bibliography of various aspects of iron-based nanomaterials for water and wastewater treatment.

Saumya Mankad, Sakshi Chaudhari, Saloni Ghodmare, Rohan Mahajan, Siddhi Susladkar, Niraj Topare, Vishnu Choudhari, Satish Khedkar and Prashant Thorat

Evaluation of the Effect of Molasses on Compressive Strength and Water Absorption of Cement-Gold Mill Tailings-Sand Mixture

This study investigates the effect of molasses as a natural admixture on the compressive strength and water absorption of a cementitious mix incorporating gold mill tailings (GMT) and sand. A constant mix ratio of 30?ment, 40% GMT, and 30% sand by weight was used, with molasses incorporated at varying dosages (0%, 1.5%, 2.0%, and 2.5% by total solid mass). The resulting mortar samples were evaluated for compressive strength and water absorption at 7, 14, and 28 days of curing. The results showed that a 1.5% molasses dosage produced the highest 28-day compressive strength (15.83 MPa), representing a 101% increase over the control mix (7.87MPa). The 1.5% molasses dosage also achieved the lowest water absorption (7.2%), which was 19% lower than that of the control mix (8.9%). In contrast, higher molasses levels (2.5%) resulted in reduced performance, likely because excess sugar interfered with cement hydration. Analysis of variance revealed that molasses dosage and curing age had a statistically significant effect on compressive strength (p < 0.01), while no significant difference was found for water absorption. These findings highlight the potential of combining GMT and molasses to produce sustainable, low-cost cementitious materials for non-structural applications, such as masonry blocks. The use of molasses not only improves performance but also offers a viable alternative to synthetic admixtures, supporting circular economy and waste valorization goals. Further research is warranted to evaluate long-term durability and environmental safety for practical applications.

John Angel Andrada, Brent Cordova, Abigael Lozano-Balbin and Gerome Amper

Assessment of Biomethanation from Cattle Manure Through Continuous Stirred Tank Reactor (CSTR)

This study explores biogas production through anaerobic digestion of cattle manure (CM) in a Continuous Stirred Tank Reactor (CSTR), using Response Surface Methodology (RSM) to optimize conditions for enhanced methane yield. Cattle manure, a primary substrate in biogas generation, holds untapped methane potential due to its high fiber content, which is only partially degraded in typical single-phase CSTR systems. Experiments were conducted under controlled mesophilic conditions to compare biogas outputs with and without stirring. Key variables, including Volatile Solids (VS), volatile fatty acids (VFA), total alkalinity (TA), and pH, were monitored and optimized using a Box-Behnken design. Results showed that stirring significantly increased methane yield to 0.4713 m3 .kg-1 VS, attributed to uniform microbial activity and enhanced degradation of organic matter. The findings also show that intermittent stirring improves methane yield by 34.36%, achieving a peak value, and offer practical insights into energy-efficient alternatives to continuous mixing, with direct implications for scaling up industrial biogas systems. Statistical analysis via ANOVA confirmed the regression model’s reliability, identifying significant factors influencing biogas production. This study’s findings underscore the efficiency of serial CSTR configurations and optimized operating conditions for sustainable biogas production.

Harshal Warade, Dhiraj Agrawal, Sameer Algburi, Khalid Ansari, Sandip Khedkar, Salah J. Mohammed and Ali Majdi

Agrochemical Implications for Cereal Production, Processing, Public Health, and Food Security in Sub-Saharan Africa

The use of pesticides, herbicides, and fertilizers has dire effects on the environmental sustainability, public health, and food security of sub-Saharan Africa. Although these agrochemicals have improved yields and pest control during harvest seasons, their rampant use has led to soil erosion, biodiversity loss, food contamination through agrochemical remnants, and water pollution. The rural population and consumers, particularly children and expectant mothers, are most at risk from these socioeconomic threats, which, coupled with chronic exposure, cause numerous long-term health issues, such as respiratory problems, neurological damage, endocrine disruption, alterations, and different forms of cancer. Moreover, sustaining long-term food security is impossible because of the perpetual misuse of agrochemicals that deteriorate soil fertility, raise production costs, and induce pesticide resistance. The absence of appropriate legislation or farmer education further exacerbates the situation. Public health outcomes can improve significantly if agrochemical dependency is lessened through training farmers in integrated pest management, organic farming, or other sustainable alternatives. This study specifically identifies the knowledge gap in the current understanding of the long-term, cumulative impact of agrochemical use on both the environment and public health, especially in the context of sub-Saharan Africa. It also proposes actionable solutions to bridge this gap through policy recommendations and farmer education programs. There is an immediate need for policies in agronomic governance to restrict the widespread use of agrochemicals, paired with requisite policy frameworks to monitor compliance toward actionable sustainable agriculture designed to support nutritional security for the region, which this study articulates.

Gbeminiyi Olamiti

Environmental Impact of E-Waste on Biotic and Abiotic Parameters

The exponential increase in electronic waste (e-waste) caused by rapid technological change is now a global environmental issue, particularly in urban informal economies, as lamented in Seelampur, Delhi. This study evaluated the environmental impacts of e-waste on biotic and abiotic parameters, specifically by assessing heavy metal contamination in soil, groundwater, plants, microorganisms, and smaller fauna. Employing mixed-method methodologies, the research employed a stratified random sampling technique throughout six sites, followed by the collection and analysis of soil and groundwater samples utilizing inductively coupled plasma–mass spectrometry (ICP-MS), as well as assessments of microbial diversity, plant uptake, and accumulation in animals. In terms of quantitative findings, lead, cadmium, mercury, and chromium concentrations were very high in relation to the World Health Organization (WHO) and national allowed limits and generally exceeded the WHO and permissible limits, with statistically significant differences in spatial exposures. Biological assessments based on soil microbial diversity revealed a diminishment in the microbial range, quantifiable signs of vegetal stress, and quantifiable bioaccumulation in invertebrates. Occupational health records also indicated high levels of harmful exposures to e-waste workers. The study concluded that informal e-waste recycling practices are correlated with quantifiable negative effects on ecosystem functions and human health indicators, and that there is an urgent need to provide good environmental practices through environmental regulations, raise awareness of the issue, and sustain approaches to mitigate long-term environmental degradation and negative public health outcomes.

Mitali Yadav, Puja Gupta and Juhi Gupta

The Effect of Long-Term Permeation of Inorganic Salts on the Geotechnical Characteristics of Bentonite-Amended Clay Liners

Bentonite-amended clay liners in engineered landfills are designed to prevent groundwater contamination from landfill leachate. Although numerous studies have examined the shortterm effect of inorganic salts present in the landfill leachate on geotechnical properties of the bentonite-amended clay liners, studies on their long-term effects remain limited. Therefore, this study evaluated the long-term effects of CaCl? and NaCl, salts commonly found in landfill leachate, on the plasticity, swelling, compressibility, and hydraulic conductivity of clayey soil amended with 10% and 20?ntonite. These samples were immersed in 1M solutions of CaCl2 and NaCl for 180 days to investigate their long-term effects. In contrast to the results obtained when water was the pore fluid, the liquid limit, plastic limit, free swell index, and free swell of bentonite-amended soils decreased in the presence of CaCl2, MgCl2, and NaCl solutions. Samples immersed in salt solutions showed significantly lower liquid and plastic limits than fresh samples prepared with the same salt solutions. The hydraulic conductivity of all samples exposed to CaCl2 and NaCl decreased with effective stress and reached values less than 1 × 10?? m.s-1. The addition of more bentonite did not significantly improve hydraulic conductivity when exposed to different salt solutions in the long term. In conclusion, samples with higher bentonite content are more susceptible to attack by inorganic salts over the long term.

Luxmy Thayaparan, Kaushalya Dhanapala, Sakura Bogoda and Darshika Wanigarathna

Performance Evaluation of Polyether Sulfone Nanocomposite Membranes in the Separation of Evans Blue Dye

Water pollution caused by the textile industry poses significant health and environmental challenges because of the discharge of untreated dye-laden effluents into natural water bodies. Conventional dye removal methods are often cost-prohibitive and energy-intensive. Membrane filtration has advantages such as scalability; however, it exhibits fouling. This study focuses on preparing cost-effective and eco-friendly membranes and evaluating the performance of PES-incorporated inorganic (TiO2), carbon-based (AC), and green-synthesized, eco-friendly Moringa seed extract biosorbents. Previous research has conducted studies on these nanoparticles separately; however, in this study, they were compared altogether, and the nanocomposite membranes were compared with commercial nanofiltration membranes (CM NF 90). The physical properties of the membranes were evaluated based on water uptake, porosity, and mean pore radius. Membrane characterizations were determined using field emission scanning electron microscopy (FESEM) and energy dispersive X-ray spectroscopy (EDS), confirming the successful integration of nanomaterials and improvements in membrane morphology. A dead-end filtration system was used to evaluate the performance of the membranes in removing Evans blue dye. The color removal efficiency (CRE) of PES/ TiO2, PES/AC, and Moringa-based membranes was 97.9%, 92%, and 98.2%, respectively. The activated carbon (AC) and titanium dioxide (TiO2) PES membranes exhibited steady flux. The Moringa-based membrane exhibited a remarkable dye rejection rate and high flux; however, the flux decreased gradually because of fouling. These results confirm that nanocomposite membranes enhance dye removal efficiency and stability. Therefore, the nanocomposite PES membrane has the potential for better dye removal and has broad applications in dye removal from wastewater in the textile industry.

S. Joy Madhumitha, P. Jegathambal, S. Devika and C. Mayilswami

Paraffin-Olefin Content Analysis and Potential Solutions of Tar from Municipal Solid Waste Gasification Process in Indonesia

The main drawback of gasification technology is the production of tar (byproducts). If not properly managed, tar formation can affect syngas gasification and potentially pollute the environment. The focus of this study was to detect paraffin-olefin content and propose mitigation strategies for tar. Compositional analysis was conducted using GC–MS, FT-IR, and XRF on tar samples extracted using different solvents. The findings indicated that the characterization of tar revealed the presence of aliphatic hydrocarbon compounds belonging to the alkane and alkene groups. GC–MS analysis of solvent extracts showed paraffinolefin contents of 65.98% (n-heptane), 64.80 wt% (n-hexane), and 22.96% (ethyl acetate), calculated from GC–MS peak area percentages. FT-IR spectra confirmed the C–H stretching of –CH?/–CH?– groups (paraffin indicators) and C=C stretching (olefin indicators). Nonpolar solvents were more effective in extracting paraffinic and olefinic fractions. Compared with coal and biomass tar studies, this study uniquely targeted MSW-derived tar and its direct potential as a paraffin-olefin feedstock. Tar exhibits potential as a raw material for paraffin-olefins, which are widely used in the wax, lubricant, asphalt, and fuel industries. The method of converting tar into alternative materials depends on the desired application of tar derivatives and economic feasibility. This research contributes to SDG 7 (affordable clean energy) through the potential of tar and SDG 12 (responsible production) through the clean production of gasification waste.

Muhammad Ridwan, Prabang Setyono and Maria Theresia Sri Budiastuti

Acceptance Rate and Publication Time

Acceptance rate: 30-40 %
Preliminary Scrutiny: 10-15 days from submission
Initial Acceptance Letter: 7-8 weeks from submission
Prepublished Paper: 4-6 weeks from final acceptance
Final Publication: 7-10 months from final acceptance

Journal Metrics

Scopus CiteScore (2024): 1.5
Scopus SJR Index (2024) = 0.234
SJR H Index (2024) = 20
Index Copernicus International (2023) = 132.21
NAAS Rating (2024) = 5.33

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