Search Results (14,941)

Although prior research focused on Baghdad has identified variability in fine particulate matter concentrations (PM_2.5) and their origins, there remains uncertainty in the identification of the relative importance of local and long-range PM_2.5 sources. This study analysed hourly air pollutant concentrations and meteorological data from three monitoring sites over the year 2019 in Baghdad, namely Al-Wazeriya (WZ), Al-Andalus Square (AS), and Al-Saiydiya (SA) sites, to determine the nature of PM_2.5 sources. Multi-stage statistical models were utilised to address inherent data limitations and varying sampling dates caused by limitations on power supplies to monitoring equipment, thus improving the identification of urban particulate sources. Bivariate polar plots, concentration ratios, and conditional bivariate probability function (CBPF) plots were used to identify local sources of PM_2.5. Potential Source Contribution Function (PSCF) and concentration weighted trajectory (CWT) methods were employed for distant and regional source apportionment. Domestic diesel generators are suggested to be the primary local source of PM_2.5 pollutants in Baghdad’s WZ area (categorised as residential with significant traffic volumes). Gasoline- and diesel-fueled motor vehicles significantly contribute to PM_2.5 concentrations in the AS and SA areas, which are commercial areas with the latter having close proximity to motorway sources. Additional impacts result from gas flaring and thermal power plants in these regions. Long-range PM_2.5 transport may be attributed to the combustion of low-quality heavy fuel oils from several potential sources, including Nahrawan brick factories, oil fields, and Al-Musayyab thermal power plants, primarily towards the northeast, east, and southeast of Baghdad. Transboundary contributions to PM_2.5 concentrations in Baghdad were also identified, from industrial sources in western Iran and eastern Syria, as well as dust particulates, and oil and gas production from southwestern Iran’s Khuzestan Province, Kuwait, and the Arabian Gulf. Low to medium wind speeds (1–4 ms⁻¹) were linked with the highest source contributions, suggesting local emission sources to be the most significant contributors to high PM_2.5 at the studied sample locations. Full article

Emissions from transportation are rapidly increasing, representing the second-largest source within the energy sector. Switching to biofuels is a promising strategy to mitigate these environmental impacts. The main aim of this study is to evaluate and compare the environmental performance of fossil gasoline and bioethanol blends in a high-performance Formula SAE race car using a comprehensive well-to-wheel (WTW) life cycle assessment (LCA) approach. The vehicle was tested under three fuel scenarios: (i) 100% fossil gasoline, (ii) a blend of 85% first-generation bioethanol (1G-pure bioethanol) derived from corn and 15% fossil gasoline (E85-1G), and (iii) a blend of 85% second-generation bioethanol (2G-pure bioethanol) derived from grape pomace, a winemaking waste product, and 15% fossil gasoline (E85-2G). The novelty of this work lies in the combined experimental and LCA-based comparison of crop-based and waste-derived bioethanol under identical high-performance operating conditions, enabling a direct assessment of feedstock influence on environmental impacts. The well-to-tank (WTT) results show that 2G bioethanol achieves the lowest environmental burdens across all impact categories, while 1G-pure bioethanol is significantly affected by emissions from corn cultivation. Fossil gasoline exhibits the highest impacts in terms of global warming potential (GWP) and Abiotic Resource Depletion (ARD). The tank-to-wheel (TTW) analysis confirms the superior environmental performance of the E85-2G blend. Despite requiring 6–16% more fuel to complete the race, E85-2G maintains its environmental advantage, and both biofuel blends produce lower air emissions than conventional gasoline. Full article

This study applies a dynamic strategic foresight to examine how Unmanned Aerial Systems (UAS)-based Advanced Air Mobility (AAM), supported by Advanced Communication Systems (ACS), can be integrated into a coherent System of Systems (SoS) for sustainable and effective Disaster Management (DM). These three domains (AAM, ACS, and DM) form a strongly coupled Internet of Things (IoT) triad within an integrated SoS. Using lessons learned from previous or running research projects of the contributing authors, i.e., SUDEM, REGUAS, 5G!Drones, and ETHER, the foresight identifies key enablers—including resilient 5G/6G communication architectures, interoperable data fusion frameworks, and UAS-supported situational awareness. It highlights structural challenges such as fragmented standards, limited cross-agency data integration, and gaps in ACS redundancy for emergency operations. The resulting roadmap outlines development priorities for ACS-enabled AAM, from unified communication protocols and hybrid TN-NTN architectures to education and capacity-building for digital-centric DM. Practically, the findings suggest that policymakers should prioritise harmonised regulatory frameworks for AAM-ACS interoperability and invest in global data exchange standards, while system designers should incorporate redundant communication layers and modular SoS architectures to ensure operational continuity under extreme conditions. Full article

Ground-source heat pump (GSHP) systems are widely used because of their energy-saving and environmentally friendly characteristics. However, the long-term operation of a standalone GSHP system leads to heat accumulation in the soil for cooling load-dominated buildings, which results in a decline in system performance. To address this issue, in this study, a high-speed railway station in Jinan was considered as the research object, and a hybrid system scheme in which a GSHP is coupled with an air-source heat pump (ASHP) was developed. The system uses the outdoor dry-bulb temperature as the control parameter and establishes a multi-unit operation control strategy. A dynamic simulation model of the hybrid system was constructed using TRNSYS software, and then the energy consumption, soil thermal balance, economics and environmental benefits of the system under various schemes and operating conditions were simulated and analyzed. Through a comparative analysis of the operating strategies, the optimal strategy that achieved the best performance was determined. Under the optimal strategy, the soil thermal imbalance rate after 10 years of operation was only 1%, the total energy consumption was significantly lower than that of a standalone ASHP system, and the initial investment was clearly lower than that of a standalone GSHP system. The results demonstrate that the hybrid system ensures soil thermal balance and high-efficiency operation while providing significant energy savings (a 28% primary energy savings rate compared to a standalone ASHP) and environmental benefits (reducing annual CO₂, SO₂, NOx, and dust emissions by 56.5 t, 384.2 kg, 361.6 kg, and 339 kg, respectively). Therefore, the emission of atmospheric pollutants such as CO₂, SO₂, NOx, and dust can be effectively reduced, thus providing an important reference for the development of building energy-saving technologies under the “dual carbon” goals. Full article

This study investigates the tariff-oriented operation of residential air-to-water heat pump systems integrated with thermal energy storage under long-term real climatic conditions. In contrast to studies based on short-term simulations or advanced predictive control, this work evaluates a simple rule-based control strategy with a focus on practical applicability. The analysis is based on hourly simulations using measured meteorological data over an eight-year period for multiple locations characterized by continental climatic conditions. Two system configurations were considered: a reference system without thermal energy storage and a storage-integrated system operating under a dual-tariff electricity pricing scheme. The results show that thermal energy storage enables effective load shifting toward lower tariff periods, resulting in consistent electricity cost reductions of 19–23% across all analyzed years and locations. These savings are achieved without significant changes in seasonal performance. However, the economic analysis indicates that the payback period remains relatively long (20 years), exceeding typical thresholds for residential investments under current conditions. Overall, the findings highlight the importance of operational flexibility and demonstrate that simple control strategies can improve the economic performance of residential heat pump systems. Full article

The rapid increase in memory power density has made memory thermal management a critical challenge in high-density servers, where extremely limited DIMM spacing significantly reduces the effectiveness of air cooling. Compared with CPUs and GPUs, memory-level liquid cooling has received less systematic study, particularly regarding the influence of cold plate structural design on thermal and hydraulic performance under realistic server conditions. In this paper, three engineering-feasible memory liquid cooling solutions (water-flowing cold plate, clamp-type cold plate and heat-pipe-based cold plate) are experimentally compared on a high-density server system. Experiments are conducted at coolant inlet temperatures of 37–50 °C with a fixed flow rate of 0.8–1.5 L/min. Memory, CPU, and voltage regulator temperatures, as well as system pressure drop, are measured. Results show that memory temperature increases with coolant inlet temperature for all configurations, while their relative performance remains unchanged. Memory temperatures range from 62.04 to 71.13 °C, 57.65 to 66.98 °C, and 66.22 to 76.07 °C, with corresponding pressure drops of 24.19–26.69 kPa, 32.73–35.98 kPa, and 27.00–29.96 kPa. These results provide insight into the role of coolant distribution and flow-path topology in memory thermal performance. Full article

This study investigates the dry pneumatic separation of wheat flour using a newly designed rotating air classifier to obtain starch- and protein-enriched fractions. The process is based on differences in particle density and size, enabling separation without water or chemical reagents. The influence of key process parameters, including air flow velocity 6–12 m/s, classifier geometry, and particle size distribution, was investigated. Statistical analysis confirmed that the air flow velocity and orifice diameter significantly affect the separation efficiency. The optimal conditions of 9–10 m/s and 1.8 mm resulted in a starch fraction with a purity of about 89% and a protein-enriched fraction containing approximately 45% protein. Regression models (R² > 0.99) demonstrated a strong relationship between the process parameters and fraction yield. Compared with conventional wet fractionation, the proposed method reduces energy consumption by approximately 28% and eliminates water use. These results confirm the feasibility of dry pneumatic classification as a sustainable and efficient technology for producing functional wheat-based ingredients. All experiments were conducted in triplicate (n = 3), and the results are presented as mean ± standard deviation. The reported yields correspond to the fraction mass, while the composition values indicate component purity within each fraction. Full article

An exploding gas actuator uses H${}_2$ and O${}_2$ nanobubbles produced electrochemically. At some conditions, these nanobubbles merge and explode synchronously due to a combustion reaction. This actuator, with a volume of less than 10 nL, demonstrated excellent properties, but the actuation frequency was restricted to 1 Hz. In this paper, it is shown that the natural actuation frequency has to be as high as 100 Hz, and the reasons for the restricted frequency are analysed. It is found that there exists a threshold frequency, which increases with the chamber size. It reaches a value of 40 Hz for a chamber with a diameter of 1 mm. Above the threshold frequency, a residual gas is collected in the chamber. This gas is identified as air dissolved in the electrolyte. Explosions in the chamber provide conditions for the residual gas to form microbubbles, which are dissolved at a low operation frequency but collected above the threshold value. This study opens up opportunities to increase the actuation frequency of the exploding gas actuator. Full article

To address the current surge and speed fluctuation that occur when high-speed surface-mounted permanent magnet synchronous motors (HSPMSMs) switch from I-f open-loop control to sensorless closed-loop control, an adaptive switching method based on the cosine of the angle error is proposed. In this method, the angle error between the I-f open-loop reference angle and the angle estimated by the sensorless observer serves as the regulating variable, and its cosine is introduced to construct an adaptive attenuation factor, so that the rate of current reduction can vary continuously with the angle error. Specifically, a relatively large rate of current reduction is generated in the early stage of the switching process, when the angle error is large, to shorten the switching time. As the angle error decreases, the rate of current reduction is gradually lowered, allowing the current regulation process to better match the convergence process of the angle error and thereby improving switching stability. The proposed switching method is validated on a high-speed air compressor experimental platform. The experimental results show that the proposed method can shorten the switching time, reduce the current surge and speed fluctuation at switching, and exhibit good robustness under varying operating conditions. Full article

Climate control systems are critical to ensuring the continuous operation of data centers, as they maintain the environmental conditions required by sensitive electronic equipment. In this context, continuous supervision of refrigeration compressors is essential to prevent failures that may compromise thermal stability. This work presents the design, implementation, and experimental validation of a remote monitoring and condition-based maintenance framework built on Industrial Internet of Things (IIoT) technologies for air-conditioning compressors used in data centers. The proposed architecture integrates industrial-grade sensors for temperature, electric current, and vibration, a Siemens LOGO! programmable logic controller (PLC) for signal acquisition and scaling, a Node-RED middleware layer for data flow management, and the ThingSpeak cloud platform for remote storage and analysis. The novel contributions of this work are: (i) a fully integrated low-cost IIoT stack validated on a Copeland ZR144KCE-TF5 scroll compressor under real operating conditions over a continuous 49-day monitoring period; (ii) a hybrid anomaly detection model that combines Z-score statistical baselines with moving-average prediction error to reduce false positives from transient events; and (iii) a condition-based maintenance decision framework that maps the three monitored variables to ISO 10816-3 vibration severity zones and manufacturer-referenced thermal and electrical thresholds, producing recommended maintenance actions. The framework was applied to the acquired dataset, confirming predominantly stable operation (93.4% of samples in ISO 10816-3 Zones A–B) while detecting an emergent mechanical-wear trend (5.64% of samples in Zone C) concentrated in the final days of the monitoring period and demonstrating the feasibility of the proposed architecture as a scalable and replicable solution for condition monitoring and maintenance decision support in critical technological infrastructures. Full article

Optimizing isolator stiffness is essential for controlling vibration transmission in cylindrical shell structures operating in cross-environment conditions. This study investigates the influence of isolator stiffness on vibration transmission and fluid-coupled response through coordinated land-based experiments, water-immersed experiments, and ABAQUS simulations. Two damped spring isolators with stiffness values of 290 N/mm and 970 N/mm were tested under representative excitations of 25 Hz and 40 Hz. The results show that the lower-stiffness isolator provides consistently stronger vibration attenuation and produces higher vibration level differences than the higher-stiffness isolator. The measured vibration level differences between land-based and water-immersed conditions remain generally within 3 dB, indicating good cross-environment consistency. The numerical results agree well with the experimental trends, with deviations generally below 5 dB in the main low-frequency range. Mechanism analysis indicates that reducing isolator stiffness weakens the transmission of excitation energy from the raft frame to the base and shell, thereby reducing near-field fluid-coupled response around the excitation region. These findings support the use of lower-stiffness isolators and provide a practical framework for vibration assessment and parameter selection in cylindrical shell structures working under coupled air–water conditions. Full article

Accurate quantification of atmospheric column-averaged dry-air CO₂ mole fractions (XCO₂) is pivotal for quantifying carbon sources and supporting China’s dual carbon goals. However, existing satellite observations are limited by spatiotemporal gaps due to orbital constraints and atmospheric conditions. To bridge these gaps, we utilized a deep learning framework featuring a dual self-attention mechanism, Air-Transformer, to capture complex long-range spatiotemporal dependencies and non-linear interactions among variables. Utilizing OCO-2 retrievals and multi-source data, this approach generated a spatiotemporally consistent, daily 0.1° XCO₂ dataset over China during 2015–2020. Cross-validation demonstrates superior accuracy (R² = 0.98), with robust performance confirmed by spatial and temporal validation and ground-based TCCON benchmarks. The estimated full-coverage outputs reveal a national mean annual increase of 2.68 ppm, characterized by a distinct east-high/west-low pattern. Interpretable analysis based on Shapley Additive Explanations (SHAP) elucidates the non-linear interactions between XCO₂ and environmental drivers and exhibits significant regional heterogeneity. This spatiotemporally consistent and interpretable XCO₂ dataset offers vital data support for regional carbon monitoring and differentiated policy-making. Full article

Tree rings record environmental conditions and can serve as long-term biomonitors of urban pollution. This study evaluated the radial growth and chemical composition of Pinus greggii wood in three urban green areas of Mexico City: San Juan de Aragón Park (SJA), Sierra de Guadalupe State Park (GUAD), and Vivero Coyoacán National Park (COY). Tree ring chemical elements were analyzed at annual resolution for the period 2002 to 2022, and their relationships with atmospheric pollutant concentrations, including nitrogen oxides (NO_x), carbon monoxide (CO), ozone (O₃), and particulate matter (PM), of medium size or smaller than 10 µm, including the fractions PM_2.5 and PM₁₀, were assessed using a spatial scaling approach. Elemental concentrations were determined using X-ray fluorescence (XRF). Statistical analyses included analysis of variance (ANOVA), Theil–Sen trend estimation, and Pearson correlation with lag analysis (up to 3 years). The oldest trees were recorded in COY (52 years), while the youngest were recorded in GUAD (13 years). Distinct temporal patterns in elemental concentrations were detected among sites; for instance, peak concentrations of Fe (307 ppm), Cu (11 ppm), and Zn (51 ppm) occurred in GUAD in 2021, while Pb concentrations declined during 2019–2020 across all three sites. Significant correlations (p < 0.05) were identified between Cu, Fe, Zn, and Pb and the atmospheric pollutants (NO_x, PM_2.5, PM₁₀, O₃). Notably, O₃ showed significant positive correlations with Fe at SJA (up to r = 0.80) and GUAD (up to r = 0.46) with lags ranging from 0 to 3 years, suggesting delayed responses between atmospheric pollution and elemental deposition in tree rings. These findings highlight the sensitivity of P. greggii to urban atmospheric pollution and support its potential as a long-term biomonitoring tool, as well as its importance for informing policies aimed at improving air quality and promoting the sustainable management of urban green spaces. Full article

A coupled modeling framework is developed to predict coating thickness after air knife wiping in hot-dip galvanizing. A 3D large eddy simulation (LES) using the WALE sub-grid scale (SGS) model is performed to resolve the jet impingement on the moving strip. Time-averaged wall static pressure $p_{\omega }\left(y\right)$ and wall shear stress ${\tau }_{\omega }\left(y\right)$ along the strip direction are extracted and used as driving inputs for a thin film model. Starting from the continuity and momentum equations, a lubrication-type formulation is derived, leading to a local cubic equation for film thickness $h\left(y\right)$ that accounts for both pressure gradient and gravity. A coupling workflow is established to preprocess the LES wall signals and compute the final coating thickness $h_{final}$. Parametric sweeps of inlet total pressure $P_0$ and the knife-to-strip distance $H$ are employed to construct operating window maps. The predicted trends show that increasing $P_0$ or decreasing $H$ intensifies wall loading and reduces $h_{final}$, while the operating window boundary is governed by the balance between the gas-induced shears. Representative results, including peak wall loading and thickness ranges, are reported for industrially relevant operating conditions. Full article

Decarbonizing air travel poses a major technological challenge, driven by the substantial power requirements of the drivetrain and the demanding weight and volume constraints of airborne systems. One promising avenue involves leveraging the high specific energy of hydrogen by designing compact, high-power fuel cell stacks to supply power for electric drivetrains. However, a key drawback of such propulsion architectures is the substantial heat generated within the fuel cells, which necessitates bulky and heavy thermal management systems to ensure safe and continuous operation. This study investigates a proposed air-based thermal management system, which operates by introducing pulsating heat pipes into the bipolar plates of a High-Temperature Polymer Electrolyte Membrane Fuel Cell (HT-PEM FC) stack. If proven to be feasible, heat pipe assisted air cooling may provide the benefit of reducing overall system complexity by decreasing the number of components in the thermal management system. To evaluate the thermal performance of the proposed system, a one-dimensional thermal model was initially developed in a previous study to describe the temperature distribution along the length of a heat pipe. Building upon this foundation, the present work extends the model by incorporating a two-dimensional Computational Fluid Dynamic (CFD) analysis to account for geometry-specific effects within the hexagonal design. Results indicate that the heat transfer from the hexagonal heat pipe geometry to the coolant air flow was marginally overestimated in previous analytical calculations. Revised heat transfer rates led to a shift in the predicted temperature distributions, resulting in the need for either increased external airflow, extended condenser sections, or reduced inlet temperatures to maintain target operating conditions. Although these adjustments may result in a slight increase in system mass and parasitic power consumption, the overall impact is limited, and the heat pipe-assisted air cooling approach remains theoretically feasible. Based on the results, design modifications are proposed and their impact on thermal performance is evaluated to address the challenges of heat rejection and temperature uniformity. A modification based on variation and optimization of PHP meander lengths was evaluated using the updated model and it significantly improved temperature homogeneity across the evaporator. Full article