Search Results (285)

In April 2023, a major dust storm event in Lanzhou attracted widespread attention. This study provides a comprehensive analysis of the causes, progression, and dust sources of this event using multiple data sources and methods. Backward trajectory analysis using the HYSPLIT model was employed to trace the origins of the dust, while FY-2H satellite data provided high-resolution dust distribution patterns. Additionally, the MAIAC AOD product was used to analyze Aerosol Optical Depth, and concentration-weighted trajectory (CWT) analysis was used to identify key dust source regions. The study found that PM₁₀ played a dominant role in the storm, and the AOD values during the storm in Lanzhou were significantly higher than the annual average, highlighting the severe impact on regional air quality. Key meteorological conditions influencing the storm’s occurrence were analyzed, including the formation and eastward movement of a high-potential ridge, convection driven by diurnal temperature variations, and surface temperature increases coupled with decreased relative humidity, which together promoted the generation and development of dust. Backward trajectory and dust distribution analyses revealed that the dust primarily originated from Central Asia, western Mongolia, Xinjiang, and Gansu. From the 19th to the 21st, the dust distribution showed similarities between day and night, with a noticeable increase in dust concentration from night to day due to strong vertical atmospheric mixing. To mitigate the impacts of future dust storms, this study highlights both short-term and long-term strategies, including enhanced monitoring systems, public health advisories, and vegetation restoration in key source regions. Strengthening regional and international cooperation for transboundary dust management is also emphasized as critical for sustainable mitigation efforts. These findings are significant for understanding and predicting the causes, characteristics, and environmental impacts of dust storms in Lanzhou and the Northwestern region. Full article

Due to the high plant height, heavy ear, and easy forward tilt of millet during harvesting, the reel of a traditional combine harvester is often difficult to adapt to the special growth characteristics of millet, resulting in serious grain loss. Therefore, optimizing the design of the reel is important to improve the harvesting efficiency of millet and reduce the grain header loss. In order to determine the optimal reel speed ratio(λ), kinematics simulation experiments and analysis were carried out under different combinations of forward speed and reel revolution speed. The results showed that the supporting effect of the reel is insufficient when λ ≤ 1, and the trochoidal trajectory of the reel can provide a backward driving force when λ > 1, the optimum speed ratio of the reel should be controlled between 1.5 and 1.6. Field experiments results showed that the grain header loss rate was the lowest (0.9%) when λ = 1.6. This study provides key guidance for the adjustment of the combine harvester, effectively reducing the grain header loss rate in harvesting millet, and improving the harvesting efficiency. Full article

The “dust belt” region extending from the western Sahara to the Gobi Desert frequently generates severe dust storms that cause hazardous air quality and disrupt daily activities. Dust storm management systems with proactive mitigation strategies can minimize the detrimental impacts of dust storms. This study applies the HYSPLIT model to simulate dust storms in Saudi Arabia, specifically targeting the eastern region. The study’s main objective is to calibrate and validate the model’s dust storm prediction module for the eastern region of Saudi Arabia. The validated HYSPLIT model, with optimized parameters such as threshold friction velocity, particle release rate, and dry deposition velocity from model calibration studies, showed a strong linear correlation between measured and predicted values. It achieved an R² of 0.9965, indicating excellent model accuracy. The main findings of the source apportionment approach, employing air particle backward trajectories and frequency analyses, indicated that the northern regions, specifically Iraq and Syria, were the primary sources of the severe dust storms observed in the receptor area. The outcomes of this study will be a reference for future research aimed at improving dust storm management systems and selecting sites for tree-planting campaigns under the “Saudi & Middle East Green Initiatives”. Full article

In response to the current situation of backward automation levels, heavy labor intensities, and high accident rates in the underground coal mine auxiliary transportation system, the mining trackless auxiliary transportation robot (MTATBOT) is presented in this paper. The MTATBOT is specially designed for long-range, space-constrained, and explosion-proof underground coal mine environments. With an onboard perception and autopilot system, the MTATBOT can perform automated and unmanned subterranean material transportation. This paper proposes an integrated odometry-based method to improve position estimation and mitigate location ambiguities for simultaneous localization and mapping (SLAM) in large-scale, GNSS-denied, and perceptually degraded subterranean transport roadway scenarios. Additionally, this paper analyzes the robot dynamic model and presents a nonlinear control strategy for the robot to autonomously track a planned trajectory based on the path-following error dynamic model. Finally, the proposed algorithm and control strategy are tested and validated both in a virtual transport roadway environment and in an active underground coal mine. The test results indicate that the proposed algorithm can obtain more accurate and robust robot odometry and better large-scale underground roadway mapping results compared with other SLAM solutions. Full article

The objective of this study was to elucidate the transmission pathways and spatial distribution of potential source areas for PM_2.5 pollution in Chenzhou City across diverse seasons in southern Hunan. Utilizing Sampling Kriging interpolation analysis, we modeled the temporal and spatial oscillations of PM_2.5 concentrations in Chenzhou City, complemented by HYSPLIT air mass backward trajectories. Furthermore, the model conducted cluster analysis to identify discernible patterns. Our findings unveiled marked seasonal variations in PM_2.5 concentrations within Chenzhou City. The pinnacle is discerned during winter (75.13 μg·m⁻³), whereas the nadir is pronounced in summer (27.64 μg·m⁻³). Notably, the PM_2.5/PM₁₀ ratio surpasses 0.55 during both autumn and winter. Spatially, Chenzhou exhibits an annual average distribution of PM_2.5 pollution characterized by a gradient “from north to south in the western and central sectors, tapering towards the east”. Pollution source analysis suggests that PM_2.5 pollution in Chenzhou City is predominantly ascribed to local emissions. Transmission pathway analysis reveals that the primary transmission corridors, spanning northwest Guangdong, southwestern Henan, Hubei, southern Anhui, and specific zones of southwestern Jiangxi, consistently align with external PM_2.5 pollution sources affecting Chenzhou City throughout the year. Noteworthy seasonal disparities emerge in the spatial distribution and contribution of potential source regions. During spring, autumn, and winter, the predominant contributing regions are primarily located in adjacent provinces. In contrast, during summer, regions with relatively elevated values predominantly streak across the central and western sectors of Jiangxi and the southeastern Hunan region. A comprehensive examination of the seasonal distribution patterns, potential transmission routes, and likely contributing sources of PM_2.5 in Chenzhou City can offer invaluable insights for regional atmospheric environmental governance. Furthermore, it underscores the paramount importance of collaborative regional strategies directed towards the prevention and control of PM_2.5 pollution. Full article

This paper presents a scheme for the feedforward–feedback longitudinal trajectory tracking control of buses. The scheme is specifically designed to address the periodic and repetitive nature of bus operations. First, the vehicle’s longitudinal dynamics are linearized along the iterative axis via full-form dynamic linearization (FFDL), and parameters such as the pseudo-gradient are estimated with data and a projection algorithm to grasp the dynamic characteristics of the system. To better handle complex real-world traffic conditions, we then propose the forward and backward structure. At the same time, the iterative axis design performance index is verified, and the forward partial control law, namely, model-free adaptive iterative learning control (MFAILC), is derived. In order to further enhance the robustness to disturbance and other factors, the control law of the feedback part is designed with active disturbance rejection control (ADRC). A key advantage of this control approach is its sole reliance on the data generated during vehicle operation, without the need for specific information about the controlled vehicle. This feature enables the method to be adaptable to different vehicle types and resilient to various disturbances. Finally, MATLAB simulations are used to verify the practicality of the proposed method. Full article

This article presents a tuned control algorithm for the speed and course of a four-wheeled automobile-type robot as a single nonlinear object, developed by the analytical approach of compensation for the object’s dynamics and additive effects. The method is based on assessment of external effects and as a result new, advanced feedback features may appear in the control system. This approach ensures automatic movement of the object with accuracy up to a given reference filter, which is important for stable and accurate control under various conditions. In the process of the synthesis control algorithm, an inverse mathematical model of the robot was built, and reference filters were developed for a closed-loop control system through external effect channels, providing the possibility of physical implementation of the control algorithm and compensation of external effects through feedback. This combined approach allows us to take into account various effects on the robot and ensure its stable control. The developed algorithm provides control of the robot both when moving forward and backward, which expands the capabilities of maneuvering and planning motion trajectories and is especially important for robots working in confined spaces or requiring precise movement into various directions. The efficiency of the algorithm is demonstrated using a computer simulation of a closed-loop control system under various external effects. It is planned to further develop a digital algorithm for implementation on an onboard microcontroller, in order to use the new algorithm in the overall motion control system of a four-wheeled mobile robot. Full article

Data on particulate matter, gaseous pollutants, and AQI values from three cities (Haikou, Sanya, and Danzhou) between January 2018 and December 2022 were obtained in order to analyze the spatiotemporal distribution characteristics of air pollution, the correlation between pollutants with meteorological conditions, and the potential sources in Hainan Island. The spatiotemporal distribution’s characteristics demonstrated that the annual mean concentrations of SO₂, NO₂, CO, O₃, PM₁₀ and PM_2.5 were 4.34 ± 1.11 μg m⁻³, 9.87 ± 1.87 μg m⁻³, 0.51 ± 0.06 mg m⁻³, 73.04 ± 6.36 μg m⁻³, 27.31 ± 3.63 μg m⁻³, and 14.01 ± 2.02 μg m⁻³, respectively. The yearly mean concentrations were trending downward in the past few years and were below the National Ambient Air Quality Standard (NAAQS) Grade II. Summer was the season with the lowest concentrations of all pollutants (3.84 μg m⁻³, 7.34 μg m⁻³, 0.42 mg m⁻³, 52.80 μg m⁻³, 18.67 μg m⁻³ and 8.67 μg m⁻³ for SO₂, NO₂, CO, O₃, PM₁₀ and PM_2.5, respectively), and afternoons were the time with the lowest concentrations of pollutants (except for 78.04 μg m⁻³ for O₃). The influence of meteorological conditions on pollutants was examined: there was a prominent positive correlation between temperature and O₃ in summer, and relative humidity largely influenced the concentrations of PM. The pollution in Hainan was affected more by regional transport; according to the backward trajectory results, Hainan is susceptible to air masses from Guangdong and Fujian to the northeast, the Indochina Peninsula to the southwest, and the South China Sea to the southeast. The results of PSCF and CWT analyses indicated that Guangdong, Jiangxi, Hunan, and Fujian were the primary potential sources of PM_2.5 and O₃. Full article

Understanding the spatiotemporal distribution and transport of atmospheric water vapor in urban areas is crucial for improving mesoscale models and weather and climate predictions. This study employs Multi-Axis Differential Optical Absorption Spectroscopy to monitor the dynamic distribution and transport flux of water vapor in Beijing within the tropospheric layer (0–4 km) from June 2021 to May 2022. The seasonal peaks in precipitable water occur in August, reaching 39.13 mm, with noticeable declines in winter. Water vapor was primarily distributed below 2.0 km and generally decreases with increasing altitude. The largest water vapor transport flux occurs in the southeast–northwest direction, whereas the smallest occurs in the southwest–northeast direction. The maximum flux, observed at about 1.2 km in the southeast–northwest direction during summer, reaches 31.77 g/m²/s (transported towards the southeast). Before continuous rainfall events, water vapor transport, originating primarily from the southeast, concentrates below 1 km. Backward trajectory analysis indicates that during the rainy months, there was a higher proportion of southeasterly winds, especially at lower altitudes, with air masses from the southeast at 500 m accounting for 69.11%. This study shows the capabilities of MAX-DOAS for remote sensing water vapor and offers data support for enhancing weather forecasting and understanding urban climatic dynamics. Full article

Autonomous navigation systems often struggle in dynamic, complex environments due to challenges in safety, intent prediction, and strategic planning. Traditional methods are limited by rigid architectures and inadequate safety mechanisms, reducing adaptability to unpredictable scenarios. We propose SafeMod, a novel framework enhancing safety in autonomous driving by improving decision-making and scenario management. SafeMod features a bidirectional planning structure with two components: forward planning and backward planning. Forward planning predicts surrounding agents’ behavior using text-based environment descriptions and reasoning via large language models, generating action predictions. These are embedded into a transformer-based planner that integrates text and image data to produce feasible driving trajectories. Backward planning refines these trajectories using policy and value functions learned through Actor–Critic-based reinforcement learning, selecting optimal actions based on probability distributions. Experiments on CARLA and nuScenes benchmarks demonstrate that SafeMod outperforms recent planning systems in both real-world and simulation testing, significantly improving safety and decision-making. This underscores SafeMod’s potential to effectively integrate safety considerations and decision-making in autonomous driving. Full article

Carbonyl compounds are important oxygenated volatile organic compounds (VOCs) that play significant roles in the formation of ozone (O₃) and atmospheric chemistry. This study presents comprehensive field observations of carbonyl compounds during an unusual wintertime ozone pollution event at a suburban site in Guangzhou, South China, from 19 to 28 December 2020. The aim was to investigate the characteristics and sources of carbonyls, as well as their contributions to O₃ formation. Formaldehyde, acetone, and acetaldehyde were the most abundant carbonyls detected, with average concentrations of 7.11 ± 1.80, 5.21 ± 1.13, and 3.00 ± 0.94 ppbv, respectively, on pollution days, significantly higher than those of 2.57 ± 1.12, 2.73 ± 0.88, and 1.10 ± 0.48 ppbv, respectively, on nonpollution days. The Frame for 0-D Atmospheric Modeling (F0AM) box model simulations revealed that local production accounted for 62–88% of observed O₃ concentrations during the pollution days. The calculated ozone formation potentials (OFPs) for various precursors (carbonyls and VOCs) indicated that carbonyl compounds contributed 32.87% of the total OFPs on nonpollution days and 36.71% on pollution days, respectively. Formaldehyde, acetaldehyde, and methylglyoxal were identified as the most reactive carbonyls, and formaldehyde ranked top in OFPs, and it alone contributed 15.92% of total OFPs on nonpollution days and 18.10% of total OFPs on pollution days, respectively. The calculation of relative incremental reactivity (RIR) indicates that ozone sensitivity was a VOC-limited regime, and carbonyls showed greater RIRs than other groups of VOCs. The model simulation showed that secondary formation has a significant impact on formaldehyde production, which is primarily controlled by alkenes and biogenic VOCs. The characteristic ratios and backward trajectory analysis also indicated the indispensable impacts of local primary sources (like industrial emissions and vehicle emissions) and regional sources (like biomass burning) through transportation. This study highlights the important roles of carbonyls, particularly formaldehyde, in forming ozone pollution in megacities like the Pearl River Delta region. Full article

This paper addresses the study of synoptic-scale meteorological conditions that favor long-range pollen transport in southern South America combining airborne pollen counts, modeled three-dimensional backward trajectories, and synoptic and surface meteorological data. Alnus pollen transport trajectories indicate origins predominantly in montane forests of the Yungas between 1500 and 2800 m altitude. The South American Low-Level Jet is the main meteorological feature that explains 64% of the detected pollen arrival at the target site. Podocarpus and Nothofagus pollen instead are linked primarily to the widespread Subantartic forests in southern Patagonia. Their transport patterns are consistent with previous studies, which show an association with synoptic patterns related to cold front passages carrying pollen in the free atmosphere (27% for Nothofagus and 25% for Podocarpus). These results show the significance of understanding long-distance pollen transport for disciplines such as climate change reconstruction and agriculture, emphasizing the need for further research to refine atmospheric circulation models and refine interpretations of past vegetation and climate dynamics. Full article

To observe the long-term variations in halocarbons in the Yangtze River Delta (YRD) region, this study analyzes halocarbon concentrations and composition characteristics in Shanxi from 2018 to 2020, exploring their origins and the health effects. The total concentration of halocarbons has shown an overall increasing trend, which is driven by both regulated substances (CFC-11 and CFC-113) and unregulated substances, such as dichloromethane, chloromethane and chloroform. The results of the study also reveal that dichloromethane (1.194 ± 1.003 to 1.424 ± 1.004 ppbv) and chloromethane (0.205 ± 0.185 to 0.666 ± 0.323 ppbv) are the predominant halocarbons in Shanxi, influenced by local and northwestern emissions. Next, this study identifies that neighboring cities in Zhejiang Province and other YRD areas are potentially affected by backward trajectory models. Notably, chloroform and 1,2-dichloroethane have consistently surpassed acceptable thresholds, indicating a significant carcinogenic risk associated with solvent usage. This research sheds light on the evolution of halocarbons in the YRD region, offering valuable data for the control and reduction in halocarbon emissions. Full article

A four-dimensional (4D) trajectory is a multi-dimensional time series that embodies rich spatiotemporal features. However, its high complexity and inherent uncertainty pose significant challenges for accurate prediction. In this paper, we present a novel 4D trajectory prediction model that integrates convolutional neural networks (CNNs), bidirectional long short-term memory networks (BiLSTMs), and multi-head attention mechanisms. This model effectively addresses the characteristics of aircraft flight trajectories and the difficulties associated with simultaneously extracting spatiotemporal features using existing prediction methods. Specifically, we leverage the local feature extraction capabilities of CNNs to extract key spatial and temporal features from the original trajectory data, such as geometric shape information and dynamic change patterns. The BiLSTM network is employed to consider both forward and backward temporal orders in the trajectory data, allowing for a more comprehensive capture of long-term dependencies. Furthermore, we introduce a multi-head attention mechanism that enhances the model’s ability to accurately identify key information in the trajectory data while minimizing the interference of redundant information. We validated our approach through experiments conducted on a real ADS-B trajectory dataset. The experimental results demonstrate that the proposed method significantly outperforms comparative approaches in terms of trajectory estimation accuracy. Full article

The locomotion mechanisms and structural characteristics of insects in nature offer new perspectives and solutions for designing miniature actuators. Inspired by the underwater movement of aquatic beetles, this paper presents a bidirectional self-propelled linear piezoelectric micro-actuator (SLPMA), whose maximum size in three dimensions is currently recognized as the smallest known of the self-propelled piezoelectric linear micro-actuators. Through the superposition of two bending vibration modes, the proposed actuator generates an elliptical motion trajectory at its driving feet. The size was determined as 15 mm × 12.8 mm × 5 mm after finite element analysis (FEA) through modal and transient simulations. A mathematical model was established to analyze and validate the feasibility of the proposed design. Finally, a prototype was fabricated, and an experimental platform was constructed to test the driving characteristics of the SLPMA. The experimental results showed that the maximum no-load velocity and maximum carrying load of the prototype in the forward motion were 17.3 mm/s and 14.8 mN, respectively, while those in the backward motion were 20.5 mm/s and 15.9 mN, respectively. Full article