Search Results (1,985)

With the implementation of China’s low-sulfur fuel policy, the characteristics of volatile organic compounds (VOCs) emitted from ship exhausts have changed significantly, and the influence of these emissions on the local atmosphere of port cities needs to be evaluated. In this study, the characteristics of localized source profiles of ship-emitted VOCs with respect to different ship types, fuel types, and engine operating conditions were analyzed in Guangzhou Port. Oxygenated VOCs (OVOCs) dominated in ferry (91.1%), cargo ship (87.0%), and tugboat (54.4% ± 7.9%) emissions (diesel fuel), while alkanes (56.3% ± 1.6%) and alkenes (36.0% ± 0.9%) were major species in multi-purpose ship (LNG fuel) emissions. These results suggest the dominance of OVOCs in the exhaust emissions of diesel-type ships and the prominent difference in ship-emitted VOCs between diesel and LNG fuel ships, which also influenced the emission characteristics of VOCs from main and auxiliary engines. Based on the measured source profiles, ship emissions contributed 18.2% ± 0.8% (summer), 8.7% ± 1.9% (winter), 6.0% ± 1.1% (spring), and 5.6% ± 1.7% (autumn) to VOCs in the port area, and 7.8% ± 1.5% in July and 5.0% ± 0.5% in September in the urban area. An air mass trajectory analysis revealed that the south wind transported the ship exhaust emissions to the port area and inland urban area, which explained the higher contributions of ship emissions in summer and more ship emissions received in the port area than in the urban area. Therefore, estimating the influence of ship emissions on ambient air quality in port cities requires integrating local ship source profiles, locations, and meteorological conditions. This study provides insights into the ship-emitted VOC characteristics given China’s low-sulfur fuel policy and their differential contributions to urban atmospheric VOCs. Full article

The xeno-fungusphere, a novel microbial ecosystem formed by integrating exogenous fungi, indigenous soil microbiota, and electroactive microorganisms within microbial fuel cells (MFCs), offers a transformative approach for agricultural remediation and medicinal plant conservation. By leveraging fungal enzymatic versatility (e.g., laccases, cytochrome P450s) and conductive hyphae, this system achieves dual benefits. First, it enables efficient degradation of recalcitrant agrochemicals, such as haloxyfop-P, with a removal efficiency of 97.9% (vs. 72.4% by fungi alone) and a 27.6% reduction in activation energy. This is driven by a bioelectric field (0.2–0.5 V/cm), which enhances enzymatic activity and accelerates electron transfer. Second, it generates bioelectricity, up to 9.3 μW/cm², demonstrating real-world applicability. In medicinal plant soils, xeno-fungusphere MFCs restore soil health by stabilizing the pH, enriching dehydrogenase activity, and promoting nutrient cycling, thereby mitigating agrochemical-induced inhibition of secondary metabolite synthesis (e.g., ginsenosides, taxol). Field trials show 97.9% herbicide removal in 60 days, outperforming conventional methods. Innovations, such as adaptive electrodes, engineered strains, and phytoremediation-integrated systems, have been used to address soil and fungal limitations. This technology bridges sustainable agriculture and bioenergy recovery, offering the dual benefits of soil detoxification and enhanced crop quality. Future IoT-enabled monitoring and circular economy integration promise scalable, precision-based applications for global agroecological resilience. Full article

With the advent of the big data era in ocean remote sensing and fisheries, there is a growing demand for finer temporal scales to predict spatial distribution of the jumbo flying squid (Dosidicus gigas). This can help reduce fuel costs and provide higher quality and faster decision-making. Therefore, this study employed a deep neural network (DNN) model, using sea surface temperature, sea surface height, sea surface salinity, and photosynthetically active radiation as input factors, with catch per unit effort as the output factor. We construct five cases with temporal scales of 3, 6, 10, 15, and 30 days using data spanning 10 years (2012–2021). Additionally, the performance of DNN was compared with those of traditional methods such as generalized additive model (GAM), extreme gradient boosting (XGBoost), and artificial neural network (ANN). The results demonstrated that the DNN model had the best performance. As the temporal scale decreased, the mean squared error and the mean absolute error increased, whereas the area under the precision−recall curve decreased, indicating a decline in model performance. The interpretability analysis indicated that spatial and temporal factors significantly contributed to the model, with longitude exhibiting the highest contribution. To improve the accuracy of finer temporal scales, future research should focus on reducing noise in the data and address the presence-only nature of fishery data, particularly by cleaning the unsampled portions. Full article

As global concerns about climate change and air quality intensify, nations are increasingly adopting sustainable transportation solutions, with electromobility emerging as a key alternative. This study investigates the factors influencing powertrain technology choice and the barriers to electric vehicle (EV) adoption in Poland, focusing on insights from technically educated youth, early-career researchers, and academic professionals. Drawing on a mixed-methods approach, the study investigates public perceptions, motivations, and challenges associated with EV uptake in a country historically reliant on fossil fuels. Key drivers such as environmental considerations, government policies, and infrastructure development are evaluated alongside persistent obstacles, including high initial purchase costs, inadequate charging networks, range anxiety, and scepticism about battery performance. While the sample is not representative of the broader Polish population, it provides insights from a technically literate cohort likely to shape future technological and policy advancements. Our findings reveal that the adoption of EVs among this group is influenced by factors such as technological innovation and government policies, while barriers include high initial costs, limited charging infrastructure, and scepticism about perceived sustainability, battery life, and performance. The research also highlights the critical role of education and awareness in shaping attitudes toward EVs. This study, though limited by sample size and demographic focus, offers valuable contributions to understanding the early-stage adoption of EVs in Poland and serves as a foundation for future research targeting a more diverse population. The applied research model is scalable, providing a framework for broader studies that could include different age groups, geographical regions, and professional sectors. Full article

The roughness of haul roads significantly impacts fuel consumption in open-pit coal mine trucks, yet there is currently a lack of quantitative road classification methods in this regard. This study proposes a fuel-efficient road classification methodology for open-pit coal mines. Using UAV-captured point cloud data of mine roads as the basis for roughness analysis and the International Roughness Index (IRI) as the evaluation metric, the research establishes linear relationships between IRI and fuel consumption for both loaded and unloaded trucks. The K-means clustering algorithm is employed to classify road quality into “good”, “moderate”, and “poor” categories, with the Haerwusu Open-pit Coal Mine serving as a case study. Results demonstrate that 150 m represents an appropriate IRI segmentation interval for Haerwusu, with IRI thresholds of 12 (15) and 20 (21) serving as critical segmentation points for loaded (unloaded) trucks. From analyzing two end-slope roads in the case study mine we found that upgrading “poor” roads to “moderate” quality could reduce fuel costs by 3% for loaded trucks and 2% for unloaded trucks. This study provides a quantitative road classification method for open-pit coal mines, offering a theoretical foundation for reducing transportation costs and promoting sustainable mining development. Full article

This review examines the current status of biomethane development in South America through a comprehensive comparative analysis of national legislation, scientific literature, and institutional data across all South American countries. The methodology consisted of a systematic review of technical and regulatory documents to assess the status of biomethane production, commercialization, and utilization throughout the region. The findings indicate that biomethane remains largely underdeveloped in most South American countries, primarily due to fragmented data, inadequate infrastructure, and a lack of targeted public policies. Brazil emerges as a regional leader, backed by robust legal frameworks such as the RenovaBio program, the Future Fuel Law, and specific regulations governing landfill waste treatment and biomethane quality standards. In contrast, other countries hold considerable biogas potential but lack the regulatory frameworks and financial incentives required to expand biomethane production. The principal contribution of this study is its comprehensive assessment of biomethane development in South America, providing a country-level analysis alongside direct comparisons with global leaders in both production and policy. By mapping legislation, infrastructure conditions, and energy strategies across the continent, this study offers a strategic reference to support future research, investment, and policy development. Full article

The production of very-low-sulfur residual fuel oil is a great challenge for modern petroleum refining because of the instability issues caused by blending incompatible relatively high-sulfur residual oils and ultra-low-sulfur light distillates. Another obstacle in the production of very-low-sulfur residual fuel oil using hydroprocessing technology is the contradiction of hydrodesulfurization with hydrodemetallization, as well as the hydrodeasphaltization functions of the catalytic system used. Therefore, the production of very-low-sulfur residual fuel oil by employing hydroprocessing could be achieved by finding an appropriate residual oil to be hydroprocessed and optimal operating conditions and by controlling catalyst system condition management. In the current study, data on the characteristics of 120 samples of heavy fuel oils produced regularly over a period of 10 years from a high-complexity refinery utilizing H–oil vacuum residue hydrocrackers in its processing scheme, the crude oils refined during their production, the recipes of the heavy fuel oils, and the level of H–oil vacuum residue conversion have been analyzed by using intercriteria and regression analyses. Artificial neural network models were developed to predict the characteristics of hydrocracked vacuum residues, the main component for the production of heavy fuel oil. It was found that stable very-low-sulfur residual fuel oil can be manufactured from crude oils whose sulfur content is no higher than 0.9 wt.% by using ebullated bed hydrocracking technology. The diluents used to reduce residue viscosity were highly aromatic FCC gas oils, and the hydrodemetallization rate was higher than 93%. Full article

A crucial stage in the post-harvest processing of cocoa beans, drying, has a direct effect on the finished product’s quality and market value. This study investigates the efficiency, quality outcomes, and environmental implications of a mixed forced convection solar dryer designed for drying cocoa beans in Ntui, Cameroon, compared to traditional open-air drying methods. The solar dryer’s design, incorporating a solar collector, forced ventilation, and thermal storage, leverages local materials and renewable energy, offering an environmentally sustainable alternative by reducing fossil fuel reliance and post-harvest losses. Experimental trials were conducted to assess key drying parameters, including the temperature, relative humidity, water removal rate, pH, and free fatty acid (FFA) content, under the equatorial climate conditions of high solar irradiation and humidity. Results demonstrate that the solar dryer significantly reduces drying time from an average of 4.83 days in open-air drying to 2.5 days, a 50% improvement, while maintaining optimal conditions for bean quality preservation. The solar-dried beans exhibited a stable pH (5.7–5.9), a low FFA content (0.282% oleic acid equivalent, well below the EU standard of 1.75%), and superior uniformity in texture and color, meeting international quality standards. In contrast, open-air drying showed greater variability in quality due to weather dependencies and contamination risks. The study highlights the dryer’s adaptability to equatorial climates and its potential to enhance cocoa yields and quality for small-scale producers. These findings underscore the viability of solar drying as a high-performance, eco-friendly solution, paving the way for its optimization and broader adoption in cocoa-producing regions. This research contributes to the growing body of knowledge on sustainable drying technologies, addressing both economic and environmental challenges in tropical agriculture. Full article

In this research, we present the development and validation of a compact, resource-efficient (low-cost, low-energy), distributed, real-time traffic and air quality monitoring system. Deployed since November 2023 in a small town that relies on burning various fuels and waste for winter heating, the system comprises three IoT units that integrate image processing and environmental sensing for sustainable urban and environmental management. Each unit uses an embedded camera and sensors to process live data locally, which are then transmitted to a central database. The image processing algorithm counts vehicles by type with over 95% daylight accuracy, while air quality sensors measure pollutants including particulate matter (PM), equivalent carbon dioxide (eCO₂), and total volatile organic compounds (TVOCs). Data analysis revealed fluctuations in pollutant concentrations across monitored areas, correlating with traffic variations and enabling the identification of pollution sources and their relative impacts. Recorded PM10 daily average levels even reached eight times above the safe 24 h limits in winter, when traffic values were low, indicating a strong link to household heating. This work provides a scalable, cost-effective approach to traffic and air quality monitoring, offering actionable insights for urban planning and sustainable development. Full article

With the global emphasis on sustainable growth and development, the depletion of natural energy reserves due to reliance on fossil fuels and non-renewable sources remains a critical concern. Despite strides in transitioning to electrical mobility, rural and agricultural communities depend heavily on liquefied petroleum gas and firewood for cooking, lacking viable, sustainable alternatives. This study focuses on community-led efforts to advance biogas adoption, providing an eco-friendly and reliable energy alternative for rural and farming households. By designing and developing balloon-type anaerobic biodigesters, this initiative provides a robust, cost-effective, and scalable method to convert farm waste into biogas for household cooking. This approach reduces reliance on traditional fuels, mitigating deforestation and improving air quality, and generates organic biofertilizer as a byproduct, enhancing agricultural productivity through organic farming. The study focuses on optimizing critical parameters, including the input feed rate, gas production patterns, holding time, biodigester health, gas quality, and liquid manure yield. Statistical tools, such as descriptive analysis, regression analysis, and ANOVA, were employed to validate and predict biogas output data based on experimental and industrial-scale data. Artificial neural networks (ANNs) were also utilized to model and predict outputs, inspired by the information processing mechanisms of biological neural systems. A comprehensive database was developed from experimental and literary data to enhance model accuracy. The results demonstrate significant improvements in cooking practices, health outcomes, economic stability, and solid waste management among beneficiaries. The integration of statistical analysis and ANN modeling validated the biodigester system’s effectiveness and scalability. This research highlights the potential to harness renewable energy to address socio-economic challenges in rural areas, paving the way for a sustainable, equitable future by fostering environmentally conscious practices, clean energy access, and enhanced agricultural productivity. Full article

Air pollution poses a serious threat to human health and the environment. Emissions from motor vehicles, especially in large cities, contribute significantly to this problem. This study analyzes the results of emission inspections in the Slovak Republic to identify factors influencing emissions and their impact on air quality. The research analyzed data from emission inspections and their relationship to vehicle age, fuel type, and type of failure. The results show that older vehicles, especially those aged 10 to 20 years, have a higher probability of failing to meet emission standards. Specifically, up to 42.75% of diesel vehicles aged 15 to 20 years were rated as unfit, compared to 33.07% of gasoline vehicles in the same age category. An increased proportion of unfit vehicles was recorded for diesel engines, which indicates their negative impact on air quality. The most common failures were related to direct emission measurements. These findings have implications for environmental policy and the regulation of vehicle imports to improve air quality and reduce pollution. Data on emission inspections were drawn from the national system and show knowledge about the observation of emission inspections carried out during one calendar year. The study recommends the introduction of stricter control mechanisms for older vehicles, supporting the renewal of the vehicle fleet, and the implementation of modern technologies to reduce emissions. Rigorous emission inspections are essential for the protection of public health. Regular inspections and modern technologies reduce emissions of harmful substances, thus contributing to the improvement of air quality and public health. Full article

Enhancing the operational flexibility and environmental performance of coal-fired boilers under wide-load conditions presents a critical challenge in China’s low-carbon transition, particularly for low-quality coals (LQCs) with abundant reserves, poor combustibility, and high NO_x emissions. To overcome the intrinsically low reactivity of LQC, peak-shaving performance and combustion behavior were systematically investigated on an MW-grade pilot-scale test platform employing the fuel modification strategy in this study. Stable fuel modification was achieved without any auxiliary energy for LQCs and Shenmu bituminous coal (SBC) across a load range of 20~83% and 26~88%, respectively, demonstrating the excellent fuel reactivity and strengthened release control of volatile and nitrogenous species. The modified LQC exhibited ignition, combustion, and burnout characteristics comparable to Shouyang lean coal (SLC), enabling a “dimensionality-reduction utilization” strategy. The double-side fuel modification device (FMD) operation maintained axially symmetric temperatures (<1250 °C) in horizontal combustion chambers, while single-side operation caused thermal asymmetry, with peak temperatures skewed toward the FMD side (<1200 °C). Original NO_x emissions were effectively suppressed, remaining below 106.89 mg/m³ (@6%O₂) for LQC and 122.76 mg/m³ (@6%O₂) for SBC over broad load ranges, and even achieved ultra-low original NO_x emissions (<50 mg/m³). Distinct load-dependent advantages were observed for each coal type: SBC favored high-load thermal uniformity and low-load NO_x abatement, whereas LQC exhibited the inverse trend. These findings underscore the importance of a load-adaptive coal selection and FMD operation mode. This study provides both theoretical insights and engineering guidance for retrofitting coal-fired power units toward flexible, low-emission operation under deep peak-shaving scenarios. Full article

Soil pollution at airports is a critical environmental issue that affects not only the local ecology but also the health of people living near these infrastructures. The main causes of pollution include the use of chemical products such as de-icing agents, fuels, and lubricants, as well as waste from aircraft and ground vehicles. These substances often seep into the soil, leading to the accumulation of toxic elements. However, due to security reasons, there is a great scarcity of real data on the impact of airport operations on ecosystems and the role trees could play in pollutant limitation. Thus, the aim of this study was to determine whether airport operations have toxic effects on soils within and around Macedonia Airport, Thessaloniki, Northern Greece, by determining the concentrations of potentially toxic elements (Cu, Ni, Pb, Mn, Fe, Co, Cr, Cd, and Zn) in soil samples taken within the airport and near the airport. Furthermore, this study aimed to investigate the effect of the canopies of forest species on the accumulation of toxic metals in the soil inside the airport and in the peripheral zone. The results show that, overall, no important pollution was detected in the soil of the Thessaloniki Airport, Northern Greece, both inside and outside the airport area. Some differences were observed in the content of toxic metals studied between the samples taken inside and outside the airport, and some effects of tree canopy were noted. However, all values were lower than the defined permissible limits according to international standards (except for iron). It is important, however, to perform regular re-checking of soil quality with new samples in order to prevent soil contamination and mitigate any contamination found. Full article

The evolving macroeconomic landscape, shaped by the global financial crisis and the COVID-19 pandemic, poses significant challenges for economies worldwide. However, Central, Eastern, and Southeastern European (CESEE) countries have demonstrated resilience and rapid recovery during crises, driven by a surge in consumption fueled by domestic credit and robust export growth supported by flexible exchange rates and adaptive monetary policies. Prior to EU accession, substantial foreign direct investment (FDI) during privatization and restructuring facilitated knowledge and technology transfers in CESEE economies. This study examines the interplay of exports, real exchange rates, GDP growth, FDI, inflation, domestic credit, and the human development index (HDI) in the CESEE region from 1995 to 2022, covering the transition period, EU accession, and major crises. Employing a panel ARDL model, we account for asymmetric effects of these variables on exports. The results reveal that GDP, FDI, inflation, domestic credit, and HDI significantly and positively influence exports, with HDI and GDP exerting the strongest effects, underscoring the pivotal roles of human capital and economic growth in enhancing export competitiveness. Conversely, real exchange rate depreciation negatively impacts exports, though non-price factors, such as product quality, mitigate this effect. These findings provide a robust basis for targeted policy measures to strengthen economic resilience and export performance in the CESEE region. Full article

This study aims to optimize the production of biodiesel from Blighia sapida (Ackee) seed oil, a non-edible and underutilized feedstock, as a sustainable alternative to conventional fossil-based diesel fuels. The transesterification of Blighia sapida seed oil was optimized using Response Surface Methodology (RSM) with a Box–Behnken experimental design. Three process variables, reaction time, temperature, and methanol-to-oil molar ratio, were selected for modeling biodiesel yield. The resulting biodiesel was characterized by physicochemical properties in accordance with ASTM D6751 standards. The optimal transesterification conditions were found to be 60 min, 60 °C, and a methanol-to-oil ratio of 3:1, yielding 98.36% biodiesel. This represents an improvement over the unoptimized yield of 94.3% at a 6:1 molar ratio. Experimental validation produced an average yield of 97.49%, confirming the model’s reliability. The produced biodiesel exhibited a kinematic viscosity of 4.02 mm²/s, cetane number of 54.6, flash point of 138 °C, and acid value of 0.421 mg KOH/g, which are all within the ASTM D6751 standard limits. This work is among the first to systematically optimize Blighia sapida biodiesel production using RSM. The results demonstrate its viability as a clean-burning, high-quality biodiesel fuel with promising fuel properties and environmental benefits. Its high cetane number and low methanol requirement enhance its combustion performance and production efficiency, positioning Blighia sapida as a competitive feedstock for sustainable biofuel development. Full article