Search Results (84)

In addition to the use of reference instruments, low-cost sensors (LCSs) are becoming increasingly popular for air quality monitoring both indoors and outdoors. These sensors provide real-time measurements of pollutants and facilitate better spatial and temporal coverage. However, these simpler devices are typically characterised by lower accuracy and precision and can be more sensitive to the environmental conditions than the reference instruments. It is therefore crucial to characterise the applicability and limitations of these instruments, for which a possible solution is their comparison with reference measurements in real-world conditions. To this end, a measurement campaign has been carried out to evaluate the PM_2.5 readings of several low- and medium-cost air quality instruments of different types and categories (IQAir AirVisual Pro, TSI DustTrak™ II Aerosol Monitor 8532, Xiaomi Mijia Air Detector, and Xiaomi Smartmi PM_2.5 Air Detector). A GRIMM EDM180 instrument was used as the reference. This campaign took place in Budapest, Hungary, from 12 November to 15 December 2020, during typically humid and foggy weather conditions, when the air pollution level was high due to the increased anthropogenic emissions, including wood burning for heating purposes. The results indicate that the individual sensors tracked the dynamics of PM_2.5 concentration changes well (in a linear fashion), but the readings deviated from the reference measurements to varying degrees. Even though the AirVisual sensors performed generally well (0.85 < R² < 0.93), the accuracy of the units showed inconsistency (13–93%) with typical overestimation, and their readings were significantly affected by elevated relative humidity levels and by temperature. Despite the overall overestimation of PM_2.5 by the Xiaomi sensors, they also exhibited strong correlation coefficients with the reference, with R² values of 0.88 and 0.94. TSI sensors exhibited slight underestimations with high explained variance (R² = 0.93–0.94) and good accuracy. The results indicated that despite the inherent bias, the low-cost sensors are capable of capturing the temporal variability of PM_2.5, thus providing relevant information. After simple and multiple linear regression-based correction, the low-cost sensors provided acceptable results. The results indicate that sensor data correction is a necessary prerequisite for the usability of the instruments. The ensemble method is a reasonable alternative for more accurate estimations of PM_2.5. Full article

Liquid atomization has wide applications in jet-type and reciprocating engines, powder generation, cooling towers, and atmosphere dust removal. Droplet size and distribution are the decisive factors in the performance of the above applications. The rapid development and usage of computer science brings huge differences in the research manner of liquid atomization and has shed great light on the micro-phenomena of the formation, deformation, and rupture of liquid ligaments. However, the numerical methods of liquid atomization still lack efficiency due to their huge cost of computer resources and their accuracy due to their dependence on empirical correlations. Before achieving reliable implementation in atomization device design, such computational models must undergo rigorous validation against experimentally measured data acquired through advanced diagnostic techniques. The present paper reviews the mainstream numerical methods of liquid atomization including interface capturing, particle tracking, smoothed particle hydrodynamics, etc. Their respective numerical kernels and some representative simulation cases are summarized. The aim of the present review is to provide a general idea and future research orientation on the capabilities of modern computer and numerical models in calculating atomization and designing relative devices and hopefully guide future research to strive efficiently and productively. Full article

Traditional solar trackers are designed to follow the sun’s exact position, assuming that perfect sun alignment always results in optimal energy generation. However, despite perfect alignment, external factors such as shading, dust, and wind can reduce power output in real-world conditions. To address these challenges, our novel system draws inspiration from the flocking behavior of birds, where individual entities adjust their behavior based on their energy output and the energy outputs of neighboring panels. The system uses Particle Swarm Optimization (PSO) to mimic this behavior, dynamically adjusting the solar tracker’s position to respond to varying environmental conditions. One key innovation is introducing a power threshold strategy, set between 1.5 W and 2 W, to avoid continuous tracker movement and conserve energy by minimizing unnecessary adjustments when the power difference is insignificant. The proposed system demonstrated an impressive 8% increase in energy gain and a reduction of up to 11% in energy consumption compared to the traditional continuous tracker. The tracking accuracy improved by 84%, with the mean tracking error reduced in the range of 0.78° to 1.09°. The system also captured 17.4% more solar irradiance, showcasing its superior efficiency. Despite environmental challenges such as dust and shading, the proposed system consistently outperformed the traditional tracker regarding energy savings and overall performance, offering a more resilient and energy-efficient solution for solar energy generation. Full article

In subway tunnel construction, current hand–eye integrated drilling robots use a camera mounted on the drilling arm for image acquisition. However, dust interference and long-distance operation cause a decline in image quality, affecting the stability and accuracy of the visual recognition system. Additionally, the computational complexity of high-precision detection models limits deployment on resource-constrained edge devices, such as industrial controllers. To address these challenges, this paper proposes a dual-arm tunnel drilling robot system with hand–eye separation, utilizing the first-frame localization and follower tracking method. The vision arm (“eye”) provides real-time position data to the drilling arm (“hand”), ensuring accurate and efficient operation. The study employs an RFBNet model for initial frame localization, replacing the original VGG16 backbone with ShuffleNet V2. This reduces model parameters by 30% (135.5 MB vs. 146.3 MB) through channel splitting and depthwise separable convolutions to reduce computational complexity. Additionally, the GIoU loss function is introduced to replace the traditional IoU, further optimizing bounding box regression through the calculation of the minimum enclosing box. This resolves the gradient vanishing problem in traditional IoU and improves average precision (AP) by 3.3% (from 0.91 to 0.94). For continuous tracking, a SiamRPN-based algorithm combined with Kalman filtering and PID control ensures robustness against occlusions and nonlinear disturbances, increasing the success rate by 1.6% (0.639 vs. 0.629). Experimental results show that this approach significantly improves tracking accuracy and operational stability, achieving 31 FPS inference speed on edge devices and providing a deployable solution for tunnel construction’s safety and efficiency needs. Full article

Harsh winters, aging infrastructure, and the demand for modern amenities are major factors contributing to the deteriorating air quality in Bishkek. The city meets its winter heating energy needs through coal combustion at the central heating plant, heat-only boilers, and in situ heating equipment, while diesel and petrol fuel its transportation. Additional pollution sources include 30 km² of industrial area, 16 large open combustion brick kilns, a vehicle fleet with an average age of more than 10 years, 7.5 km² of quarries, and a landfill. The annual PM_2.5 emission load for the airshed is approximately 5500 tons, resulting in an annual average concentration of 48 μg/m³. Wintertime daily averages range from 200 to 300 μg/m³. The meteorological and pollution modeling was conducted using a WRF–CAMx system to evaluate PM_2.5 source contributions and to support scenario analysis. Proposed emissions management policies include shifting to clean fuels like gas and electricity for heating, restricting secondhand vehicle imports while promoting newer standard vehicles, enhancing public transport with newer buses, doubling waste collection efficiency, improving landfill management, encouraging greening, and maintaining road infrastructure to control dust emissions. Implementing these measures is expected to reduce PM_2.5 levels by 50–70% in the mid- to long-term. A comprehensive plan for Bishkek should expand the ambient monitoring network with reference-grade and low-cost sensors to track air quality management progress and enhance public awareness. Full article

Road transport plays a crucial role in sustaining all the personal and freight movement needs of residential, commercial, and industrial activities, and in Indian cities, big and small, vehicle exhaust emissions and dust from vehicle movement on the roads contribute to as much as 50% of particulate matter pollution in a year. Therefore, effective management of vehicle exhaust emissions is vital not only for improving current air quality but also for ensuring the long-term benefits from efforts to reduce air pollution. In the approved clean air action plans for 131 cities under the national clean air program (NCAP), more than 50% of the implementable actions are transport-centric. Having a reliable and replicable vehicle exhaust emissions inventory is essential for effective planning, which can help establish a baseline, support scenario analysis, and allow for tracking progress in the sector. This process begins with accessing accurate vehicle stock numbers, typically obtained from vehicle registration databases, traffic surveys, and other governmental records. Often, in low- and middle-income countries like India, these numbers require extensive data cleaning before they can be used for emissions and pollution analysis. This paper presents a cleaned, open-access vehicle stock database for India and outlines a methodology to build and maintain an in-use vehicle age-mix database for future years. The database covers the years 1993 to 2018 for the entire country and individual states, along with estimates of the age distribution of vehicles using survival functions. By offering a comprehensive and reliable data source, this paper aims to support sustainable national and urban air quality management efforts, helping policymakers and stakeholders make informed decisions to improve air quality and public health. Full article

Research on road construction has evolved and advanced. Environmental sustainability considerations are now an integral part of the specific focus of these infrastructure projects. This study investigated the feasibility of recycling on iron ore reject through cost-effective pavement techniques, demonstrating significant improvements in the performance of stabilized mixtures with the addition of anti-dust treatment. The mineralogical and chemical analysis of the reject, coupled with the conducted priming tests (LWT and WTAT), highlighted the effectiveness and promising application of these materials in construction. Under a load of 33 kg, the anti-dust-treated mixture showed a deformation of 5.3 mm, compared to 7.76 mm for the stabilized reject–emulsion mixture. Similar improvements were observed in reject–soil–emulsion mixtures, with a sinking of 4.16 mm for anti-dust-treated specimens compared to 6.99 mm for stabilized mixtures. The results of the WTAT test corroborated the effectiveness of the layer formed by the anti-dust treatment; in all cases, the mass loss was less than 2%. These findings have significant implications for sustainability in construction, contributing to environmental conservation and resource efficiency. Full article

Energy sources are crucial for the development and growth of economies and civilizations. Solar energy is an alternative energy to generate electrical power. The challenges of solar photovoltaic panels (PV) are the low output power and efficiency and the huge installation area beside PVs need a tracking system for better efficiency. The motivation of this paper is to design an innovative solar sphere system, which is a new concentrated photovoltaic technology that has better performance (efficiency and output power) than the normal conventional solar panel (PV) with a smaller installation area and without any tracking system. This design consists of an acrylic solar sphere entirely filled with cooking oil (sunflower or corn oil) that captures solar radiation and concentrates it on a focal point. The focal point is adjusted over a multi-junction cell that acts as a collector device (concentrator solar cell). This focused solar energy can generate a massive amount of power, which is used to produce more electricity than normal photovoltaic panels. The experiments were carried out in order to discover the best acrylic models or shape designs, which is the sphere, the best materials or media in the sphere, that is oil, the best sphere’s size and volume, and that is larger, the best sphere thickness, which at first is lower, the best fluid oil type, which is cooking oil, and finally the best fluid amount or volume inside the sphere, and this is the entire volume. Then, these factors mentioned above are compared with normal photovoltaics (PV) that have the same section area as these shapes. The results revealed that these factors have significant effects on the output power value and efficiency. It has been demonstrated that our innovative concentrated solar sphere system can produce nearly four times the output power or electricity greater than that of a conventional solar panel PV with the same cross-sectional area. This specific sort of compression is crucial because it shows that less space is required to establish this system than it would to install conventional solar panels. The performance of the system per unit of the square area it occupies was compared to the latest generation of flat panel PV available at the market performance; hence, the installation space will be decreased by 40% to 60%. Our system has about twice as much efficiency as solar PV and does not require a tracking system and maintenance. Our technology also has the benefit of not being impacted by extreme temperatures, clouds, dust, and humidity. Full article

During 14–16 March 2021, a large-scale dust storm event occurred in the northern region of China, and it was considered the most intense event in the past decade. This study employs observation data for PM2.5 and PM10 from the air quality monitoring station, the HYSPLIT model, ground-based polarized Lidar networks, AGRI payload data from Fengyun satellites and CALIPSO satellite Lidar data to jointly explore and scrutinize the three-dimensional spatial and temporal characteristics of aerosol transport. Firstly, by integrating meteorological data for PM2.5 and PM10, the air quality is assessed across six stations within the Lidar network during the dust storm. Secondly, employing a backward trajectory tracking model, the study elucidates sources of dust at the Lidar network sites. Thirdly, deploying a newly devised portable infrared 1064 nm Lidar and a pulsed 532 nm Lidar, a ground-based Lidar observation network is established for vertical probing of transboundary dust transport within the observed region. Finally, by incorporating cloud imagery from Fengyun satellites and CALIPSO satellite Lidar data, this study revealed the classification of dust and the height distribution of dust layers at pertinent sites within the Lidar observation network. The findings affirm that the eastward movement and southward compression of the intensifying Mongolian cyclone led to severe dust storm weather in western and southern Mongolia, as well as Inner Mongolia, further transporting dust into northern, northwestern, and northeastern parts of China. This dust event wielded a substantial impact on a broad expanse in northern China, manifesting in localized dust storms in Inner Mongolia, Beijing, Gansu, and surrounding areas. In essence, the dust emanated from the deserts in Mongolia and northwest China, encompassing both deserts and the Gobi region. The amalgamation of ground-based and spaceborne Lidar observations conclusively establishes that the distribution height of dust in the source region ranged from 3 to 5 km. Influenced by high-pressure systems, the protracted transport of dust over extensive distances prompted a gradual reduction in its distribution height owing to sedimentation. The comprehensive analysis of pertinent research data and information collectively affirms the precision and efficacy of the three-dimensional aerosol monitoring conducted by the ground-based Lidar network within the region. Full article

The destructionof clouds by strong shocks and hot winds is the key process responsible for the transporting of metals and dust from the ISM to the ICM/IGM, and establishing the multiphase structure in and around galaxies. In this work, we perform a detailed analysis of this process using two different approaches for tracking the cloud material (gas and dust): the so-called ‘colored’ fluid, and the Lagrangian (trace) particles. We find that for the clouds in the hot phase ($T>{10}^5$ K), the two methods produce significantly different mass fractions and velocities of the cloud material. In contrast, the two methods produce similar results for the clouds that are in the warm/cold phases ($T<{10}^5$ K). We find that the Kelvin–Helmholtz instability is suppressed in the warm clouds of size ∼100 pc and metallicity Z> 0.1Z$duetoeffectivegascooling.ThiscausesadelayinthedestructionofsuchcloudsthatareinteractingwiththehotICMflow.Wedemonstratethatthedustparticlesthatareevacuatedfromtheir‘parent’cloudstothehotmediumshowdifferentdynamicswhencomparedtothatoftheLagrangian\left(trace\right)particles.Ourresultsindicatethatthedustgrainssweptouttothehotgasaredestroyed.$ Full article

Millimeter-wave (mmWave) radars attain high resolution without compromising privacy while being unaffected by environmental factors such as rain, dust, and fog. This study explores the challenges of using mmWave radars for the simultaneous detection of people and small animals, a critical concern in applications like indoor wireless energy transfer systems. This work proposes innovative methodologies for enhancing detection accuracy and overcoming the inherent difficulties posed by differences in target size and volume. In particular, we explore two distinct positioning scenarios that involve up to four mmWave radars in an indoor environment to detect and track both humans and small animals. We compare the outcomes achieved through the implementation of three distinct data-fusion methods. It was shown that using a single radar without the application of a tracking algorithm resulted in a sensitivity of 46.1%. However, this sensitivity significantly increased to 97.10% upon utilizing four radars using with the optimal fusion method and tracking. This improvement highlights the effectiveness of employing multiple radars together with data fusion techniques, significantly enhancing sensitivity and reliability in target detection. Full article

The utilization of photovoltaic (PV) cleaning robots has proven to be an effective method for maintaining the conversion efficiency of utility-scale PV power plants by mitigating the impact of dust accumulation. However, ensuring the safe operation of these robots, resembling tanks in appearance, particularly in wet working conditions, relies heavily on their adherence to PV panels. This study focuses on assessing the slip resistance of candidate materials coated on endless polyurethane timing belts, which are equipped on PV cleaning robots to enable the efficient cleaning of uneven and misaligned PV arrays. A novel apparatus is proposed to evaluate the coefficient of static friction (COSF) of slip specimens, considering factors such as outsole patterns, area density, and shore hardness. The results highlight the significant influence of shore hardness and area density on the slip resistance of the specimens. Based on the findings, it is recommended to design track grooves with hexagon or zigzag patterns and maintain a low area density (e.g., 0.44 g·mm⁻²) to ensure the safe operation of PV cleaning robots, irrespective of the working conditions they encounter. By addressing the slip resistance challenge, this research contributes to the overall efficiency and reliability of PV cleaning robots, enhancing their performance in maintaining clean and optimal PV panel surfaces. Full article

Fugitive dust (FD) is a nuisance and potential health issue, particularly in environmental justice communities that can experience high levels of contaminated FD. This community-initiated study examined FD from a scrap metal processor in Detroit, Michigan, to determine whether the FD was contaminated, how it migrated through the community, whether wipe or composite road dust samples were preferable, and whether literature profiles adequately characterized this source. The study was motivated by community concerns, as well as a massive subsidence/upheaval event resulting from excessive accumulation of mill scale, which is a type of scrap metal, at the facility. We collected 57 wipe samples from windows and other surfaces, and 20 composite road dust and surface soil samples, which were analyzed by X-ray fluorescence. Concentrations were expressed using the fraction of the reconstructed mass. We also compared results to air quality monitoring data and calculated pollution indices and enrichment factors. Samples collected near the processor had high levels of Cr, Cu, Fe, Ni, Sr, and Zn compared with background soils, and levels remained elevated in residential areas several blocks distant. Composite road dust/sediment samples appeared preferable to wipe samples for chemical characterization. The available chemical profiles did not match the FD composition, suggesting the need for local profiles. The high level of Fe, which is consistent with mill scale, was a novel finding and caused the road dust to exceed health protection screening levels. Numerous metal scrap facilities operate locally and nationally, and our results show the need to improve controls to limit or eliminate FD emissions from industrial sources using enforced policies that reduce dust generation and truck track-out. Full article

Numerous studies about solar panel cleaning robot (SPCR) have been conducted globally to enhance the performance of photovoltaic panels (PV panels). However, there is a reality: scant attention has been paid to the large pressure and vibration that SPCR movements induce, not only on the photovoltaic panel surface but also on the mounting structure. Most of the research is focused on evaluating the “cleanliness” of the PV surface by using a clearing robot or the effects of natural factors (wind, dust, etc.) on the PV panels. Nonetheless, the large pressure and vibration constitute one of the primary factors contributing to the degradation of photovoltaic panel longevity and efficiency, especially affecting poorly installed PV arrays. To address these issues, this study proposes the design of a multi-suspension unit for the SPCRs equipped with track-wheeled, which might reduce vibration on the PV panel surface generated by the SPCRs’ motion and brushing action during operation. The multi-suspension unit facilitates the expansion of the contact area between the track-wheeled and the PV panel surface; hence, the negative effect is reduced owing to the vibration-absorbing properties of the rubber track pads. In the case of a static SPCR state, with only the impact of rotating brushes on vibration, the effectiveness of the multi-suspension unit can reduce vibration by a maximum of 72.63. Moreover, a metric (Δz) is proposed to evaluate the change in deflection of PV panels over time. The results show that the number of significant changes in PV panel deflection gradually decreases or disappears, while the number of small changes increases. In the case of SPCR operating on portrait PV modules, the number of occurrences of Δz (greater than 0.5 mm) is reduced from 18 counts to 5 counts, while the number of occurrences of Δz (less than 0.5 mm) increased from 61 counts to 91 counts. Overall, the proposed multi-system suspension is effective in reducing or eliminating large deflections while keeping the vibration frequency constant. Full article

The terrestrial components of the hydrological cycle include rainwater, surface water, and groundwater. Carbon (C) isotopes allow hydrologists to pinpoint the age of groundwater, track its flow rate, and identify the sources and processes. This research summarizes previous investigations conducted on the isotopes of groundwater and precipitation. The Scopus database contains works from authors from fifty nations, who have conducted research integrating C isotopes in groundwater and precipitation. The review shows that there have been few C isotope investigations on carbon storage and sequestration, as well as on δ¹³C of precipitation in arid regions. An integrated e-DNA investigation on the process of C isotope fractionation in diverse environments, as well as research on ¹³C of precipitation in arid regions before and after dust storms, is required to elucidate the relative contributions of biogenic, geogenic, and anthropogenic sources. However, carbon isotope fingerprints that are unique to individual compounds, such as those of fugitive gases, need sophisticated analytical equipment in order to be investigated, limiting this type of study to nations with robust scientific infrastructures and well-trained manpower. The International Atomic Energy Agency (IAEA) has been instrumental in this effort by providing collaborative research and analytical support, resulting in the development of a network for isotope data generation. Full article