Search Results (2,085)

As a promising alternative for cleaner vehicles, the growth of Battery Electric Vehicle (BEV) adoption should be supported by a reliable charging infrastructure. Therefore, projecting the charging load is required to ensure that the electricity supply is adequate as BEV adoption increases. This study proposes a multistage approach for projecting BEV charging load demand, linking a One-dimensional Convolutional Neural Network (1D-CNN) forecasting model with BEV users’ travel behavior analysis to perform spatiotemporal agent-based trip and charging simulations, which model various types of BEVs traveling across multiple regions. The 1D-CNN model achieves high performance with an RMSE of 0.073 and an R² of 0.881, providing a 10-year BEV adoption outlook. The empirical study in nine regions of Greater Jakarta, Indonesia, shows the one-week temporal charging load demand for three milestone periods—2025, 2030, and 2035—exploring weekday and weekend demand, as well as home and public charging demand at points of interest (POIs). This study identifies a difference between aggregate charging load demand and per-vehicle load intensity: the aggregate demand concentration occurs in South Jakarta (21% for public charging and 22% for home charging), while the highest per-vehicle spatial concentration ratio occurs in Depok (36% for public charging and 16% for home charging) due to long-distance travel patterns. The distribution of charging demand at the subdistrict level provides a basis for charging infrastructure placement, transformer sizing, and charging tariff design. Full article

Bisphenol compounds (BPs), widely utilized in industrial production, have raised significant concerns within the scientific community due to their high environmental risks, which pose serious threats to human health and ecological security. Consequently, numerous researchers have dedicated efforts to developing advanced technologies to address BPs pollution. In this study, bibliometric analysis was employed to visually analyze 13,639 publications related to BPs removal from 1994 to 2023, aiming to elucidate the development status, research hotspots, and frontier trends in BPs removal technologies. The consistent upward trend in annual publication numbers underscores the ongoing expansion and deepening of research in this field, with the Chinese Academy of Sciences emerging as the most prominent contributing institution. Keywords burst analysis revealed that advanced oxidative degradation has become a predominant research focus among BPs removal technologies (removal efficiency ranging between 80 and 100). It is anticipated that future research on BPs removal will likely concentrate on developing more efficient and cleaner technologies, emphasizing sustainability and environmental friendliness. Overall, this study offers an objective and comprehensive overview of the research landscape in BPs removal technologies, providing a valuable reference and insightful suggestions for future researchers in the field. Full article

Accurate prediction of the indoor temperature in pig housing facilities is vital for the optimization of environmental control and to ensure animal welfare. However, existing models struggle to capture the complex temporal data patterns in pig farm buildings. To overcome this challenge, a novel type of hybrid model is proposed, which combines the strengths of the Prophet, Transformer, and XGBoost models. The proposed framework integrates an adaptive time-delay attention block into the Transformer encoder that automatically extracts and assigns the optimal weight to the lag features. The Prophet component makes use of multiplicative seasonal decomposition in order to capture trend, seasonal, and cyclical patterns. The XGBoost component is the final predictor which makes use of its gradient boosting capabilities to train the nonlinear feature interactions. The performance of the proposed hybrid model is compared to another six machine learning models to assess its effectiveness. Experimental validation on a real-world dataset demonstrates its superior performance, achieving the R² value of 0.97, a mean absolute error of 0.584, and a root mean squared error of 0.797. It can effectively guide the process of maximizing energy efficiency of modern livestock farms and contributes to cleaner and sustainable pig production systems. Full article

Atmospheric aerosols in Southeast Asia, influenced by climate and seasonal circulation, are examined here. This study analyzes the impact of the 2015 El Niño and monsoonal variability on aerosol properties over Penang, Malaysia, from 2015–2019. Aerosol Optical Depth (AOD), Ångström Exponent (AE), Fine Mode Fraction (FMF), and Single Scattering Albedo (SSA) were analyzed using AERONET observations, complemented by satellite-derived fire data and NOAA HYSPLIT back-trajectory analysis. Pronounced seasonal variability was observed, with elevated AOD during the Southwest Monsoon (0.72 ± 0.15) associated with biomass burning and mixed urban aerosols, and lower AOD during the Northeast Monsoon (0.47 ± 0.12) due to cleaner maritime air masses. The inter-monsoon period exhibited the lowest AOD (0.28 ± 0.10), reflecting enhanced wet scavenging and mixed aerosol sources. Interannually, the 2015 El Niño recorded substantially higher aerosol loading, including extreme AOD events (>1.75), driven by intensified regional fire activity under dry conditions. A statistically significant but weak correlation (R² = 0.12, p = 0.047) indicates biomass burning contributed to AOD, though transport processes were the dominant driver. Trajectory analysis confirmed that aerosols originated from fire-affected Sumatra during the Southwest Monsoon and from the South China Sea during the Northeast Monsoon. These results show that climate and winds drive aerosol changes, so regional monitoring and cross-border air management in Southeast Asia are needed. Full article

The global effort to mitigate hazardous particulate matter (PM) emissions from diesel engines relies significantly on advances in separations technologies. The diesel particulate filter (DPF) is a critical component designed to trap soot and ash from diesel engine exhaust, ensuring cleaner emissions and compliance with environmental regulations. In the current paper, a gas-particle two-phase flow model in the microchannels of a DPF is developed. A novel statistical approach based on probability sampling is proposed aimed at generating a particle ensemble that adheres to the real-world soot particle size distribution (PSD). The Eulerian-Lagrangian approach is employed to model the soot-laden gas flow, where the gas phase flow field is solved in the Eulerian framework, while the particle phase motion is tracked in the Lagrangian framework. The results demonstrate that the through-wall velocity plays a predominant role in the overall deposition behavior of the mixed-sized particle group. Increasing upstream velocity shifts initial particle deposition positions further from the channel inlet and enhances mass accumulation at the channel’s terminal section. Reduced filtration wall permeability promotes the uniformity of soot deposition along the channel. A permeability of 5 × 10⁻¹³ m² is identified as the critical threshold, below which the soot deposition distribution approaches near-complete uniformity. Full article

Blade icing in cold climates poses significant risks to operational stability and results in substantial power generation deficits. This study establishes and validates an integrated multiscale framework, CFD-OpenFAST-Stacking, to characterize the complex aeroelastic behavior of iced wind turbines and facilitate high-fidelity power forecasting. The methodology utilizes high-fidelity CFD to quantify the aerodynamic degradation of simulated iced airfoils. These data are subsequently coupled with the OpenFAST aeroelastic platform for full-scale turbine simulations to evaluate the system’s dynamic response. A Stacking ensemble learning model is developed by synthesizing these simulation results with historical SCADA data through an innovative data-fusion approach. Numerical findings indicate that icing severely compromises aerodynamic efficiency, inducing a 17.65% reduction in the maximum lift coefficient and a 34.07% escalation in drag at the aerodynamically sensitive blade tip. Consequently, the rated power point is shifted from 10.5 m/s to 13 m/s, with performance degradation most prominent in the low-to-medium wind speed regime. Model validation demonstrates that the data-fusion technique significantly improves predictive robustness, increasing the R² from 0.75 to 0.84 while reducing the RMSE from 37.69 to 17.04. SHAP analysis further identifies generator speed and wind speed as the primary determinants of power variability. This research substantiates the efficacy of bridging physical simulations with data-driven methodologies, providing a robust theoretical framework for performance evaluation in extreme weather environments. Full article

Through this paper, an active disturbance rejection control scheme is designed based on an extended state observer capable of estimating the system’s internal variables and external disturbances without the need for expensive sensors and also attenuates sensor-induced noise, supporting cleaner measurements. The extended state observer is dynamically adjusted using fuzzy logic techniques. The proposed method is validated in Matlab/Simulink, with the results showing a significant reduction in both body displacement and acceleration compared to passive suspension systems, representing a direct improvement in vehicle stability and ride comfort; this demonstrates the robustness and adaptability of the proposed system. The evaluation covers three road excitations, sinusoidal, step, and trapezoidal, to broaden the analysis under both smooth and abrupt disturbances. Full article

This study investigates the performance of a multi-media bio-scrubbing system that integrates activated sludge with loofah as a biofilm carrier for the purification of complex pollutants from simulated cooking fumes: oils, Non-Methane Hydrocarbons (NMHCs), PM_2.5/PM₁₀, and Volatile Organic Compounds (VOCs). Compared to conventional carriers like activated carbon, the biodegradable and low-cost loofah, with its hierarchical porous structure and balanced hydrophilic–lipophilic properties, showed enhanced support for microbial colonization (achieving a biomass density of 105 mg/g) and pollutant adsorption. The system achieved high removal efficiencies in lab-scale tests: 97.4% for total VOCs (including 96.5–100% removal of recalcitrant alkanes and olefins), 91.3% for oils, and >88% for PM_2.5/PM₁₀. Mechanistic analysis indicated that the biofilm was dominated by Proteobacteria and Actinomycetes, and the synergistic effect between physical adsorption (via loofah’s porosity) and biodegradation (by microbial consortia) enabled stable performance (maintaining >90% efficiency over a 25-day operation) without observed secondary pollution. The loofah-activated sludge configuration demonstrated improved operational stability and the potential for lower operating costs compared to single-medium systems in this experimental setting. This work explores a promising, eco-friendly approach for treating simulated cooking fumes, utilizing renewable biomass carriers and biological processes, which could contribute to cleaner production strategies. Full article

China’s export-oriented economic expansion has substantially influenced transport-sector CO₂ emissions, raising critical concerns about the environmental impacts of sustained industrial growth and global trade integration. Understanding the interplay between macroeconomic dynamics, trade composition, and industrial structure is essential for aligning economic development with climate mitigation objectives. This study examines transport-related CO₂ emissions in China over the period 1990–2023, employing a hybrid methodological framework that combines econometric modeling—including Autoregressive Distributed Lag (ARDL) bounds testing, Fully Modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS)—with machine-learning techniques using Extreme Gradient Boosting (XGBoost) interpreted through SHapley Additive exPlanations (SHAP). The analysis confirms a long-run cointegration relationship between transport emissions and the selected macroeconomic variables. Short-run dynamics indicate a strong sensitivity of emissions to GDP growth, while long-run estimates reveal that higher export-to-GDP ratios and industrial value added contribute to reducing transport emissions, reflecting the efficiency gains from industrial upgrading and cleaner trade practices. By contrast, the expansion of medium- and high-technology exports increases emissions due to the energy- and logistics-intensive nature of high-value goods. The XGBoost model achieves high predictive performance, with an out-of-sample R² of 0.9975 and a Root Mean Square Error (RMSE) of 87.16, confirming the dominant contribution of medium- and high-technology exports to transport-sector emissions. The results underscore the critical role of aligning trade structure, industrial productivity, and low-carbon logistics within China’s policy agenda. Implementing strategies that enhance industrial energy efficiency and develop sustainable transport infrastructure can substantially reduce the environmental impacts associated with export-driven economic expansion. Full article

The proliferation of single-use petroleum-based foams in protective packaging has become a major source of persistent plastic waste, posing significant challenges to environmental sustainability. To address this issue, we developed a fully biodegradable cushioning foam from bamboo, a rapidly renewable biomass, using an environmentally benign deep eutectic solvent (DES) process that avoids harsh chemical bleaching. The resulting lignin-containing cellulose nanofibril (LCNF)/sodium alginate (SA) foam exhibits low density (0.23 g/cm³), high compressive strength (0.24 MPa at 70% strain), and excellent elasticity (90% recovery at 50% strain), enabled by a dual-network structure of Ca²⁺-crosslinked SA and entangled LCNFs. Critically, the material is fully compostable and leaves no microplastic residues, offering a circular end-of-life pathway. In real-world banana drop tests, it matched the performance of commercial expanded polyethylene (EPE) while outperforming polyethylene bubble wrap. This work demonstrates a practical, scalable route to replace fossil-derived cushioning materials with a bio-based alternative that aligns with the principles of cleaner production and circular economy. Full article

Asphaltenes are the most polar and refractory fraction of crude oil, and are typically isolated using petroleum-derived precipitants (e.g., n-hexane, n-heptane) and then dissolved in aromatic solvents such as toluene, which raises safety and sustainability concerns. Here we evaluate D-limonene, a renewable terpene, as a green, room-temperature precipitant for asphaltene fractionation and benchmark it against n-alkanes and the ASTM D-6560 workflow. Multi-technique characterization (ATR-FTIR/NIR, TGA, CHN, EDS, LDI(+) FT-ICR MS, and ¹H/¹³C NMR) shows that D-limonene yields a lower mass of precipitate yet a fraction with reduced thermal refractoriness (lowest TGA residue, broader/attenuated DTG peak). Molecular readouts indicate lower aromatic condensation/cross-linking in the precipitated subpopulation—narrower DBE envelopes by FT-ICR MS and lower aromatic carbon indices (Car_tot, Car-b, Car-j) by ¹³C NMR—consistent with a mechanism in which π–π/dispersion interactions retain highly condensed multi-ring aggregates in solution under cold, static conditions. These results establish D-limonene as a selective green precipitant for asphaltenes, offering immediate analytical benefits (cleaner, safer fractionation for molecular studies) and a sustainable basis for pretreatments of heavy fractions. Full article

The global shift towards cleaner energy has accelerated the application of hydrogen as a clean fuel. Retrofitting and reusing existing natural gas (NG) pipeline infrastructure is a cost-effective way to enable bulk deployment of hydrogen. This study investigates the technical feasibility of retrofitting and rehabilitating NG pipelines for hydrogen transport. Material compatibility, especially hydrogen embrittlement, fatigue resistance, and permeability in steel pipes and weld joints, is examined in the analysis. Retrofitting approaches such as internal coatings, flow regulation, and pipeline pressure adjustments are reviewed in the context of current engineering standards. Structural integrity assessments, using established codes, are conducted to evaluate post-retrofit performance and safety. This is a literature-based technical assessment using existing codes and standards, such as CSA Z662 and ASME B31.12, combined with industry case studies and experimental insights to evaluate the readiness of legacy pipelines for hydrogen service. This paper provides a foundational framework for assessing the safe reuse of legacy pipeline systems for pure or blended hydrogen transport. It sets the stage for further techno-economic analysis in future research. Full article

CBAM is reshaping the external conditions under which open economies pursue decarbonization, raising new questions about how domestic carbon pricing can remain effective while supporting sustainability. We develop an environmental DSGE model for a small open economy with a cleaner green sector and an emissions-intensive brown sector, an endogenous green innovation margin, and a banking sector that prices sector-specific transition risk through credit spreads. Carbon pricing affects the economy through relative prices and resource reallocation, while CBAM acts as an export-revenue wedge that weakens cash flows in exposed activities and tightens financing conditions. In the baseline, a coordinated increase in the domestic effective carbon price cuts emissions quickly and shifts investment toward the green sector, with aggregate activity recovering as reallocation proceeds. Under CBAM, the near-term contraction is deeper, and the spread spikes more, but endogenous green innovation and a policy mix that combines targeted green credit support with macroprudential measures deliver a smoother adjustment and the largest welfare gains. The results suggest that coherent policy packages linking carbon pricing, innovation support, and financial stability are central to managing the transition in an open economy. Full article

Cleaning, the removal of parasites and dead tissue from clients, is common in the Sea. Reef-based cleaning stations are visited by many fish clients, some by both resident and visitor pelagic species, while others are visited solely by resident species. Nonetheless, no distinction has ever been made between the potentially different cleaning stations. Here we describe two distinct categories of cleaning stations: pelagic cleaning stations (PCS) and residential cleaning stations (RCS). We suggest that the two station types differ not only in their clientele but also in the characteristics of their cleaning services. We examined the behaviour of the cleaner wrasse, Labroides dimidiatus, at six cleaning stations on isolated knolls in Palawan, the Philippines—three stations that are routinely visited by pelagic manta rays (i.e., PCS), and three stations that service only resident clients (i.e., RCS). Our results indicate that PCS have more cleaners per station and that cleaners forage at greater distances from the station’s focal point. These distinct patterns suggest functional differences between pelagic and residential cleaning stations. Our findings may aid in the identification and conservation of shark and manta cleaning stations. Full article