The transesterification process for biodiesel production relies on efficient catalysts to accelerate the chemical reactions involved. Choosing the appropriate catalyst is crucial and depends primarily on the free fatty acid content of the oil feedstock. Conventional biodiesel production processes typically employ homogeneous catalysts, which present several disadvantage, including toxicity, high flammability, corrosiveness, and significant effluent generation. Consequently, there is growing interest in biomass-derived heterogeneous catalysts and bio-waste, as these offer sustainable, recyclable, and environmentally friendly alternatives. These catalysts exhibit excellent stability and catalytic efficiency in both acidic and basic environments, as well as superior water resistance. This review provides an in-depth analysis of biomass-based heterogeneous catalysts, emphasizing their potential for sustainable biodiesel production. The primary focus is on the usage of biomass and bio-waste-derived catalysts for producing cost-effective biodiesel. This review offers an overview of present methods for synthesizing various types of catalysts, such as basic, acidic, bifunctional, and nanocatalysts, using a range of feedstocks. Furthermore, it explores the impact of different catalyst preparation techniques on biodiesel yield and evaluates the sustainability of these catalysts. This study also identifies gaps in the present literature on biomass-derived heterogeneous catalysts and other biocatalysts, offering suggestions for future research avenues.

Biogas plants play a major role in Nepal’s renewable energy efforts. However, managing the by-product remains challenging due to its high water content. The high water content increases the difficulty in transporting, storing, or reusing the material, especially in rural and farming areas. Dewatering provides a practical solution by removing moisture, thereby transforming the slurry into a drier, more manageable material. This review compares several dewatering technologies used in agriculture, industry, and wastewater treatment, with a focus on how they can help manage biogas slurry in developing countries such as Nepal. Various machines, such as screw presses, belt presses, and centrifuges, as well as novel method including thermally assisted mechanical dewatering (TAMD), are included in this review. These technologies were compared based on key factors, including moisture removal rate, energy consumption, nutrient saving, and operational parameters. Results show that TAMD gives the best moisture removal, whereas screw presses use less energy and keep useful nutrients in the digestate. Low-cost and fuel-free machines also show potential for small-scale use in rural areas. Despite these options, the data, infrastructure, and support to apply these technologies widely are still insufficient in Nepal. This paper highlights the need for improved local research, enhanced policies, and increased investment to enlarge the scale of these systems. Doing so could help Nepal maximize the value of its biogas plants, providing cleaner energy and enhancing agricultural productivity.

Accurate and dynamic prediction of water quality indicators is increasingly critical due to rising pollution and water resource insecurity, particularly when dealing with high-dimensional, nonlinear time series data. Dissolved oxygen (DO), a key indicator of aquatic ecosystem health and pollution, requires high prediction accuracy for effective environmental management. This study aims to enhance the accuracy and adaptability of DO prediction by addressing the limitations of traditional deep learning methods, such as slow convergence and local optima. We propose a novel hybrid optimization framework that combines Nesterov-accelerated Adaptive Moment Estimation (Nadam) with the differential evolution algorithm. A dual-population cooperation strategy and an information exchange mechanism were incorporated during the training of a long short-term memory (LSTM) network to achieve a dynamic balance between global exploration and local exploitation. This improves the model’s optimization efficiency and generalization. The research utilized a multivariate water quality time series dataset from Kaggle based on official data monitoring. Correlation analysis was conducted to ensure the scientific validity and effectiveness of the selected input variables. Experimental results demonstrated that the proposed method significantly outperforms traditional optimization strategies for DO prediction. Compared to the original Nadam optimizer, it reduced the mean squared prediction error by 47.8%, exhibiting enhanced adaptability and robustness in complex pollution scenarios. This study presents an effective optimization strategy to improve LSTM performance in water quality forecasting, along with a scalable and interpretable intelligent analysis framework. It provides both theoretical and practical support for water quality forecasting, early warning systems, and intelligent environmental monitoring.

The conjunctive use of groundwater and surface water near rivers can effectively balance both water quantity and quality, making the suitability of water source locations critically important. To address the issue of suitability for water intake from riverine terraces, this study develops a mathematical evaluation model based on the analytic hierarchy process (AHP) and establishes a comprehensive assessment system tailored to the optimal selection of riverside water intake sites. Based on a comprehensive analysis of the geomorphological and hydrogeological characteristics of the Weining-Yellow River alluvial plain, this study develops an evaluation model to assess the suitability of riverside water intake sites. The model incorporates eight key indicators: river low-flow discharge, riverbed siltation, aquifer permeability, aquifer thickness, presence of continuous impermeable interlayers, river water quality, groundwater quality, and groundwater depth. Indicator weights were determined using the AHP, and grading criteria were established for each parameter. Using the ArcGIS analytical platform, a suitability index was calculated, and the study area was categorized into different suitability zones based on the established classification standards. The results indicate that a substantial portion of the Weining Basin exhibits relatively favorable conditions for riverside water source extraction, with class I zones accounting for 8.63%, class II zones for 36.21%, class III zones for 17.54%, class IV zones for 23.18%, and class V zones for 14.44%. The comprehensive evaluation score for this water source site is 69 points, which can be classified as a class II (good suitability) zone. Both the theoretical framework and practical application demonstrate that the proposed evaluation method is well suited for assessing the intake suitability of riverside water intake sites.

China currently faces challenges related to the high volume of construction waste and its low utilization rate, which have varying impacts on resources and the environment. This study focuses on Shaanxi province in China and conducted online interviews with 12 respondents, comprising four representatives each from construction companies, recycling enterprises, and government departments. The research aims to explore the actual economic performance of recycling and utilization processes. Interview outlines were tailored to the professional attributes of the participants, revealing key issues: construction companies highlighted costs associated with the sorting process, recycling companies reported on the underdeveloped market for recycled products, and the government representatives identified challenges in the continuity and specificity of support policies. Based on these findings, this study proposes several recommendations to enhance the economic performance of recycling-related industries in the sample region and to improve recycling rates and resource utilization.

Land use and land cover (LULC) surrounding the Ngerengere River, Tanzania, which is a crucial water source, has led to a rapid decline in vegetated areas. Understanding these changes is vital for informed decision-making and sustainable river catchment management. This study assessed historical LULC trends from 2004 to 2024, projected the current trend of change to 2034, and analyzed the human activities driving the trends using Landsat TM imagery. The study utilized both spatial and non-spatial datasets from primary sources (Landsat imagery via Google Earth Engine and field surveys) and secondary sources (literature and government reports). Landsat 5 (2004) and Landsat 8 (2014, 2024) images were processed using Arc-GIS and QGIS to minimize cloud interference. Land cover classification combined unsupervised and supervised methods, validated with ground reference points collected through GPS. A rule-based classification system used spectral indices to identify land cover types. Classified maps were visualized and exported for further analysis. Furthermore, systematic field visits were conducted along the catchment to assess human land use activities, that is, agriculture, settlements, and deforestation. Results revealed a 17.6% decline in sparse vegetation between 2004 and 2014, and a further 27.01% decrease from 2014 to 2024. Bare land increased by 8.58% over the two decades. Built-up areas rose from 0.67% in 2004 to 5.44% in 2014, then dropped to 2.1% in 2024. In contrast, dense vegetation increased from 0.04% in 2004 to 7.13% in 2024. Overall, the land cover projection for 2034 indicates continued ecological transformation within the Ngerengere River catchment. These shifts, primarily driven by agricultural expansion and deforestation, underscore the urgent need for sustainable land management. The significant vegetation cover decline in the catchment is largely due to agricultural encroachment into forested areas.

Climate change, predominantly driven by escalating global CO₂ emissions, is significantly altering global and regional weather patterns. The Lake Tana Basin, a critical ecological and agricultural zone, exhibits high vulnerability to this climatic variability. This study examined long-term trends in rainfall (1900 - 2023) and temperature (1901 - 2022) using the CenTrends and CRU datasets, along with the spatial variability of rainfall and temperature (1981 - 2022) based on the National Aeronautics and Space Administration data. It also investigated the relationship between climate variables and global CO₂ emissions (using the EDGAR dataset; 1970 - 2022) and assessed the efficacy of local climate policies. The findings revealed pronounced spatiotemporal variability. A significant decrease in crucial summer (Kiremt) rainfall was observed (Sen’s slope: −0.335 mm/year; p=0.011), whereas November rainfall displayed a significant increasing trend (Sen’s slope: 0.045 mm/month; p=0.04), contributing to rising autumn rainfall. Temperatures are rising unequivocally (p<0.05). Notable spatial variability was also observed across different agroecological zones - for instance, the Gondar station reported an annual rainfall with a coefficient of variation of 32.6% compared to 22.3% at Injibara. A significant decline in rainfall was observed in Woreta and Delgi, with Mann-Kendall trend values of −0.247 (p=0.022) and −0.265 (p=0.014), respectively. A robust, statistically significant positive correlation (r = 0.743; p<0.01) was established between global CO₂ emissions and local temperature changes over 53 years. An in-depth policy review identified substantial challenges that impede effective climate action. These results underscore the urgent need for strengthening policy implementation and promoting targeted, location- and season-specific adaptation and mitigation strategies. These include adopting climate-smart agricultural practices, improving carbon sequestration capacity, and aligning local climate actions with global mitigation efforts. Participation in global climate agreements and initiatives, integrated with local actions that contribute to global emission reduction targets, is essential for ensuring long-term sustainability and enhancing community resilience.

This study presents an in-depth analysis of China’s emission and carbon reduction support policies from 2016 to 2023 using text mining techniques. The main objective is to examine the evolution, thematic focus, and implementation outcomes of these policies across different stages, thereby providing insights into their development patterns and potential future direction. Based on the latent Dirichlet allocation model implemented in Python 3.7, the study identified and refined 14 initial topic terms spanning three policy phases, which were subsequently integrated and interpreted. Through topic clustering and visualization using the Sankey-bubble chart, the research simulated the evolution of policy themes over time. The results reveal a clear shift in policy focus - from market-driven mechanisms to green development and technology-led approaches. In the later stages, policies exhibit more comprehensive and systematic characteristics. In conclusion, the study contributes to a deeper understanding of the development trajectory, orientation, and implementation effectiveness of China’s carbon reduction policies, offering valuable insights for future policy development.

Camellia oleifera Abel, recognized as one of the world’s four major woody edible oil sources, is extensively cultivated in the acidic red soil regions in southern China. This study focused on C. oleifera seedlings to investigate the mechanisms through which phosphorus (P) mitigates aluminum (Al) toxicity. The seedlings were subjected to various P-Al solutions at different concentration ratios, and a metabolomic analysis of their leaves was then conducted. The analysis identified a total of 509 metabolites, predominantly flavonoids and tannins. Among these, 466 flavonoids showed significant increases across all comparison groups, whereas 35 differentially abundant metabolites were consistently detected. Kyoto Encyclopedia of Genes and Genomes functional annotation and enrichment analysis highlighted the isoflavone biosynthesis pathway as the most significantly enriched pathway among the differentially abundant metabolites. Key metabolites identified as significantly differentially abundant included glycitin, naringenin, and 3,9-dihydroxypterocarpan. This research elucidates the metabolic alterations in C. oleifera seedlings under P and Al stress, suggesting that changes in flavonoid metabolites and the activation of the isoflavone biosynthesis pathway may be crucial adaptive strategies for C. oleifera to withstand such stresses. The findings not only offer a theoretical foundation for enhancing plant stress resistance but also provide valuable insights into the cultivation and management practices of C. oleifera.

By systematically optimizing particle size distribution and solid mass concentration, this study develops high-performance coal gangue-fly ash backfill slurry with enhanced rheological properties and stability. X-ray diffraction and performance analyses confirmed that the synergistic combination of crystalline aluminosilicates in coal gangue and amorphous aluminosilicate glass in fly ash significantly contributes to the formation of a cohesive C-(A)-S-H gel network under alkaline conditions, thereby improving the mechanical integrity and stability of the backfill matrix. Slurries with solid mass concentrations between 68% and 76% displayed typical Bingham plastic behavior, with increasing concentration significantly improving both plastic viscosity and yield stress, thus enhancing resistance to bleeding and segregation. Particle size analysis indicated that a distribution modulus of i_k = 0.91 effectively minimized bleeding while maintaining high flowability, improving slurry homogeneity and pumpability. An optimal formulation was identified at a 72% solid mass concentration with optimized particle size distribution, providing a balance between workability and stability. These results confirm the potential of coal gangue-fly ash systems as sustainable and cost-effective backfill materials and offer practical guidance for mix design in large-scale underground mining applications. Furthermore, this approach promotes the green reuse of bulk industrial by-products, advancing the sustainable development of solid waste while supporting safe and environmentally responsible mine reclamation.

Foliar nutrition is considered an effective approach to enhance crop productivity and quality. In a field experiment conducted at the College of Agriculture, University of Baghdad, during the 2023 - 2024 agricultural season, the effects of two foliar nutrient solutions (Al-Nibras and Kinglife) on eggplant yield, its traits, and soil nutrient availability were evaluated for two cultivars: Barcelona and Jawaher. The main plot was assigned to cultivar type, the subplot to foliar fertilizer type, and the sub-subplot to spray concentration (0, 3, 6, and 9 g/L). It was found that the Jawaher cultivar outperformed the Barcelona cultivar in terms of plant height, number of branches, number of fruits per plant, and the contents of the soil molybdenum, iron, and zinc. In addition, the foliar fertilizer Kinglife was consistently better than the Al-Nibras in all traits. All characteristics were markedly affected by spraying concentration; particularly, the highest averages of plant height (100.39 cm), the number of branches (7.68 branches/plant), the number of fruits (50.7 fruits/plant), and nutrients in the soil availability: Mo (0.113 mg/kg), Fe (5.04 mg/kg), and Zn (1.68 mg/kg) were achieved using 9 g/L Al-Nibras/Kinglife. The interaction between the Jawaher cultivar and Kinglife fertilizer had the most pronounced superiority in all studied features, recording the highest values of 96.57 cm (plant height), 7.78 branches/plant, 50.6 fruits/plant, 0.169 mg/kg for molybdenum, 6.45 mg/kg for iron, and 2.73 mg/kg for zinc. These findings indicate that the choices of cultivar, fertilizer, and spray concentration are important in increasing the yield of eggplant and enriching soil nutrients.

Biomedical waste (BMW) refers to any solid or liquid waste, including its packaging and by-products, generated during the diagnosis, treatment, or immunization of humans or animals. Poor and inappropriate management of healthcare waste poses significant health risks and can cause substantial environmental damage. Given the enduring importance of BMW management, this study aims to assess healthcare workers’ (HCWs) knowledge, attitudes, and practices regarding BMW management (BMWM) at various levels of hospitals and diagnostic services. This cross-sectional study included 163 participants and was carried out from April 2024 to June 2024 in the Nalgonda and Warangal districts of Telangana state, India. The findings revealed that a significant proportion of doctors (87.7%) and nurses (80%) demonstrated good to excellent knowledge of BMWM, whereas only 66.6% of other HCWs reached similar levels. A strong positive attitude toward BMWM was observed among 96.3% of participants. In terms of practices, 63.4% of doctors, 72% of nurses, and 76.3% of other HCWs exhibited excellent adherence to BMWM practices. The study also found knowledge regarding BMWM disparities based on workplace location. These findings provide critical insights for hospital executives, policymakers, and public health professionals to devise specialized training and awareness schemes to strengthen BMWM practices.

The separation of overburden strata in coal mining directly affects surface subsidence, the ecological environment, and mining safety. Backfilling technology is currently the primary solution to address these issues. This study examines the rheological performance of a coal gangue and fly ash mixed slurry as a filling material under different raw material proportions and injection pressures, and predicts its diffusion distance using a theoretical model. Orthogonal experiments were conducted to evaluate the influences of solid volume concentration, coal gangue particle size, and fly ash-to-coal gangue mass ratio on the density, viscosity, and water bleeding rate of the slurry. Results demonstrated that solid volume concentration had the most significant influence on density and viscosity, followed by coal gangue proportion and particle size. Increasing coal gangue content elevated density and viscosity due to higher interparticle friction, while finer particles reduced viscosity by 30-40%. The introduction of a polycarboxylate superplasticizer achieved a 45% viscosity reduction with an optimal dosage of 0.3 wt%, by dispersing particles and enhancing the availability of free water compared to sulfamic acid. Injection pressure accelerated water bleeding rates by 20-35%, while finer coal gangue particles prolonged bleeding time. A power-law fluid fracture grouting diffusion model predicted that higher injection pressures (0.1-0.4 MPa) and fracture widths (0.4-1.0 mm) linearly increased diffusion distance, whereas steeper fracture angles (5-20°) enhanced the spread range. This study provides a broad perspective for designing cost-effective, environmentally stable grouting systems using coal-based waste, balancing injectability and long-term performance in mining applications.

Evaporation is a vital process in the hydrological cycle, accounting for approximately 70% of water loss from the Earth’s surface. In semi-arid and rapidly urbanizing regions, such as Mbeya, Tanzania, understanding the meteorological drivers of evaporation is critical for water resource management and agricultural planning. This study utilized principal component analysis (PCA) on a 10-year dataset comprising solar radiation, sunshine hours, minimum and maximum temperatures, and wind speed to identify key factors influencing evaporation. Descriptive statistics revealed significant non-normality in most variables, particularly radiation and wind speed. At the same time, correlation analysis showed a strong positive relationship between sunshine hours and radiation (r= 0.66) and a moderate negative correlation between radiation and minimum temperature (r= −0.30). PCA identified two principal components accounting for 66.61% of the total variance. Component 1 (38.06%) captured solar-driven variability, dominated by sunshine duration and radiation, whereas Component 2 (28.55%) reflected thermal influences, particularly maximum and minimum temperatures. Wind speed contributed minimally, suggesting a more localized or less consistent role in evaporation dynamics. These findings demonstrate the value of PCA in simplifying complex climatic datasets and improving the interpretation of evaporation processes. Solar radiation and sunshine hours emerged as the dominant drivers, with temperature as a secondary influence. The results emphasize the need to integrate surface-level variables, such as land use, vegetation cover, and soil moisture, in future studies to capture spatial heterogeneity and improve predictive accuracy, especially in data-scarce, climate-sensitive regions like Mbeya.

Water is essential to life, yet scarcity and contamination remain persistent global challenges. This study analyzed the water situation in Las Vigas, a rural community in the Costa Chica region of Guerrero, Mexico, from a socioenvironmental perspective, focusing on three water sources: natural streams, artificial irrigation canals, and potable water from the community system. A mixed-methods approach was used, comprising participant observation, surveys, and interviews. The participant observation revealed that water issues are tied to economic marginalization, the presence of urban solid waste and agrochemical containers in water bodies, and insufficient institutional infrastructure. A structured questionnaire with 41 closed-ended questions was applied to 35 residents. In the socioeconomic dimension, 66% of respondents were women, 77% had stable jobs, and 60% lived in owned homes, although 43% had only a primary education, limiting access to technical knowledge. In the environmental dimension, 86% perceived stream contamination, 94% canal contamination, 97% recurrent droughts, and 83% a lack of water conservation culture. In the sociopolitical dimension, 89% perceived a lack of environmental education, and 86% attributed water shortages to institutional failures, especially in the pumping system (69%). Only 20% believed that wastewater treatment plants existed, although none currently do. Interviews with 42 key informants reinforced that water scarcity, contamination, and unequal access are interconnected challenges rooted in structural weaknesses. The findings highlight the urgent need for integrated strategies that promote water governance, environmental education, community participation, and infrastructure enhancement to ensure sustainable and equitable access to water in the Las Vigas community.

This study investigates the spatiotemporal variability of unconfined and semi-confined aquifers in N’Djamena, Chad, based on dynamic monitoring conducted from 2020 to 2024. A total of 40 boreholes—18 in unconfined aquifers and 22 in semi-confined systems—were monitored using piezometers, probes, and GPS instruments during two key periods each year: May (end of the dry season) and November (post-rainy season). Groundwater depths exhibited marked seasonal fluctuations, ranging from 13.5 m to 4.1 m in unconfined aquifers and from 29.1 m to 6.3 m in semi-confined aquifers. Pearson correlation analysis revealed only a moderate relationship with temperature (r = 0.582) and a weak correlation with precipitation (r = 0.390), suggesting that groundwater level variations are not solely or linearly governed by climatic parameters. Instead, they likely result from a combination of thermal influences, delayed infiltration, and lateral recharge through semi-permeable layers. A comparative analysis with the Lake Chad Basin highlighted distinct recharge mechanisms shaped by geological and hydrological contrasts. These findings support differentiated aquifer management strategies—such as using unconfined aquifers for emergency supply and preserving semi-confined aquifers for long-term needs—as well as urban planning interventions, including improved drainage in flood-prone areas such as Sabangali and Gassi. This study contributes to the development of adaptive groundwater governance frameworks in water-stressed and rapidly urbanizing Sahelian environments.