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Keywords = mobile air quality study

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19 pages, 15535 KiB  
Article
Impact of Landfill Sites on Coastal Contamination Using GIS and Multivariate Analysis: A Case from Al-Qunfudhah in Western Saudi Arabia
by Talal Alharbi, Abdelbaset S. El-Sorogy, Naji Rikan and Hamdi M. Algarni
Minerals 2025, 15(8), 802; https://doi.org/10.3390/min15080802 - 30 Jul 2025
Viewed by 170
Abstract
The contamination due to coastal landfill is a growing environmental concern, particularly in fragile marine ecosystems, where leachate can mobilize toxic elements into soil, water, air, and sediment. This study aims to assess the impact of a coastal landfill in Al-Qunfudhah, western Saudi [...] Read more.
The contamination due to coastal landfill is a growing environmental concern, particularly in fragile marine ecosystems, where leachate can mobilize toxic elements into soil, water, air, and sediment. This study aims to assess the impact of a coastal landfill in Al-Qunfudhah, western Saudi Arabia, on nearby coastal sediments by identifying the concentration, distribution, and ecological risk of potentially toxic elements (PTEs) using geospatial and multivariate analysis tools. The results indicate significant accumulation of Pb, Zn, Cu, and Fe, with Pb reaching alarming levels of up to 1160 mg/kg in the landfill area, compared to 120 mg/kg in the coastal sediments. Zn contamination also exhibited substantial elevation, with values reaching 278 mg/kg in landfill soil and 157 mg/kg in coastal sediment. The enrichment factor values indicate moderate to severe enrichment for Pb (up to 73.20) and Zn (up to 6.91), confirming anthropogenic influence. The contamination factor analysis categorized Pb contamination as very high (CF > 6), suggesting significant ecological risk. Comparison with sediment quality guidelines suggest that Pb, Zn, and Cu concentrations exceeded threshold effect levels (TEL) in some samples, posing potential risks to marine organisms. The spatial distribution maps revealed pollutant migration from the landfill toward the coastal zone, emphasizing the necessity of monitoring and mitigation strategies. As the first comprehensive study on landfill-induced PTEs contamination in Al-Qunfudhah, these findings provide essential insights for environmental management and pollution control policies along the Red Sea coast. Full article
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33 pages, 16026 KiB  
Article
Spatiotemporal Analysis of BTEX and PM Using Me-DOAS and GIS in Busan’s Industrial Complexes
by Min-Kyeong Kim, Jaeseok Heo, Joonsig Jung, Dong Keun Lee, Jonghee Jang and Duckshin Park
Toxics 2025, 13(8), 638; https://doi.org/10.3390/toxics13080638 - 29 Jul 2025
Viewed by 232
Abstract
Rapid industrialization and urbanization have progressed in Korea, yet public attention to hazardous pollutants emitted from industrial complexes remains limited. With the increasing coexistence of industrial and residential areas, there is a growing need for real-time monitoring and management plans that account for [...] Read more.
Rapid industrialization and urbanization have progressed in Korea, yet public attention to hazardous pollutants emitted from industrial complexes remains limited. With the increasing coexistence of industrial and residential areas, there is a growing need for real-time monitoring and management plans that account for the rapid dispersion of hazardous air pollutants (HAPs). In this study, we conducted spatiotemporal data collection and analysis for the first time in Korea using real-time measurements obtained through mobile extractive differential optical absorption spectroscopy (Me-DOAS) mounted on a solar occultation flux (SOF) vehicle. The measurements were conducted in the Saha Sinpyeong–Janglim Industrial Complex in Busan, which comprises the Sasang Industrial Complex and the Sinpyeong–Janglim Industrial Complex. BTEX compounds were selected as target volatile organic compounds (VOCs), and real-time measurements of both BTEX and fine particulate matter (PM) were conducted simultaneously. Correlation analysis revealed a strong relationship between PM10 and PM2.5 (r = 0.848–0.894), indicating shared sources. In Sasang, BTEX levels were associated with traffic and localized facilities, while in Saha Sinpyeong–Janglim, the concentrations were more influenced by industrial zoning and wind patterns. Notably, inter-compound correlations such as benzene–m-xylene and p-xylene–toluene suggested possible co-emission sources. This study proposes a GIS-based, three-dimensional air quality management approach that integrates variables such as traffic volume, wind direction, and speed through real-time measurements. The findings are expected to inform effective pollution control strategies and future environmental management plans for industrial complexes. Full article
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31 pages, 4435 KiB  
Article
A Low-Cost IoT Sensor and Preliminary Machine-Learning Feasibility Study for Monitoring In-Cabin Air Quality: A Pilot Case from Almaty
by Nurdaulet Tasmurzayev, Bibars Amangeldy, Gaukhar Smagulova, Zhanel Baigarayeva and Aigerim Imash
Sensors 2025, 25(14), 4521; https://doi.org/10.3390/s25144521 - 21 Jul 2025
Viewed by 488
Abstract
The air quality within urban public transport is a critical determinant of passenger health. In the crowded and poorly ventilated cabins of Almaty’s metro, buses, and trolleybuses, concentrations of CO2 and PM2.5 often accumulate, elevating the risk of respiratory and cardiovascular [...] Read more.
The air quality within urban public transport is a critical determinant of passenger health. In the crowded and poorly ventilated cabins of Almaty’s metro, buses, and trolleybuses, concentrations of CO2 and PM2.5 often accumulate, elevating the risk of respiratory and cardiovascular diseases. This study investigates the air quality along three of the city’s busiest transport corridors, analyzing how the concentrations of CO2, PM2.5, and PM10, as well as the temperature and relative humidity, fluctuate with the passenger density and time of day. Continuous measurements were collected using the Tynys mobile IoT device, which was bench-calibrated against a commercial reference sensor. Several machine learning models (logistic regression, decision tree, XGBoost, and random forest) were trained on synchronized environmental and occupancy data, with the XGBoost model achieving the highest predictive accuracy at 91.25%. Our analysis confirms that passenger occupancy is the primary driver of in-cabin pollution and that these machine learning models effectively capture the nonlinear relationships among environmental variables. Since the surveyed routes serve Almaty’s most densely populated districts, improving the ventilation on these lines is of immediate importance to public health. Furthermore, the high-temporal-resolution data revealed short-term pollution spikes that correspond with peak ridership, advancing the current understanding of exposure risks in transit. These findings highlight the urgent need to combine real-time monitoring with ventilation upgrades. They also demonstrate the practical value of using low-cost IoT technologies and data-driven analytics to safeguard public health in urban mobility systems. Full article
(This article belongs to the Special Issue IoT-Based Sensing Systems for Urban Air Quality Forecasting)
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26 pages, 5914 KiB  
Article
BiDGCNLLM: A Graph–Language Model for Drone State Forecasting and Separation in Urban Air Mobility Using Digital Twin-Augmented Remote ID Data
by Zhang Wen, Junjie Zhao, An Zhang, Wenhao Bi, Boyu Kuang, Yu Su and Ruixin Wang
Drones 2025, 9(7), 508; https://doi.org/10.3390/drones9070508 - 19 Jul 2025
Viewed by 398
Abstract
Accurate prediction of drone motion within structured urban air corridors is essential for ensuring safe and efficient operations in Urban Air Mobility (UAM) systems. Although real-world Remote Identification (Remote ID) regulations require drones to broadcast critical flight information such as velocity, access to [...] Read more.
Accurate prediction of drone motion within structured urban air corridors is essential for ensuring safe and efficient operations in Urban Air Mobility (UAM) systems. Although real-world Remote Identification (Remote ID) regulations require drones to broadcast critical flight information such as velocity, access to large-scale, high-quality broadcast data remains limited. To address this, this study leverages a Digital Twin (DT) framework to augment Remote ID spatio-temporal broadcasts, emulating the sensing environment of dense urban airspace. Using Remote ID data, we propose BiDGCNLLM, a hybrid prediction framework that integrates a Bidirectional Graph Convolutional Network (BiGCN) with Dynamic Edge Weighting and a reprogrammed Large Language Model (LLM, Qwen2.5–0.5B) to capture spatial dependencies and temporal patterns in drone speed trajectories. The model forecasts near-future speed variations in surrounding drones, supporting proactive conflict avoidance in constrained air corridors. Results from the AirSUMO co-simulation platform and a DT replica of the Cranfield University campus show that BiDGCNLLM outperforms state-of-the-art time series models in short-term velocity prediction. Compared to Transformer-LSTM, BiDGCNLLM marginally improves the R2 by 11.59%. This study introduces the integration of LLMs into dynamic graph-based drone prediction. It shows the potential of Remote ID broadcasts to enable scalable, real-time airspace safety solutions in UAM. Full article
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24 pages, 2488 KiB  
Article
UAM Vertiport Network Design Considering Connectivity
by Wentao Zhang and Taesung Hwang
Systems 2025, 13(7), 607; https://doi.org/10.3390/systems13070607 - 18 Jul 2025
Viewed by 206
Abstract
Urban Air Mobility (UAM) is envisioned to revolutionize urban transportation by improving traffic efficiency and mitigating surface-level congestion. One of the fundamental challenges in implementing UAM systems lies in the optimal siting of vertiports, which requires a delicate balance among infrastructure construction costs, [...] Read more.
Urban Air Mobility (UAM) is envisioned to revolutionize urban transportation by improving traffic efficiency and mitigating surface-level congestion. One of the fundamental challenges in implementing UAM systems lies in the optimal siting of vertiports, which requires a delicate balance among infrastructure construction costs, passenger access costs to their assigned vertiports, and the operational connectivity of the resulting vertiport network. This study develops an integrated mathematical model for vertiport location decision, aiming to minimize total system cost while ensuring UAM network connectivity among the selected vertiport locations. To efficiently solve the problem and improve solution quality, a hybrid genetic algorithm is developed by incorporating a Minimum Spanning Tree (MST)-based connectivity enforcement mechanism, a fundamental concept in graph theory that connects all nodes in a given network with minimal total link cost, enhanced by a greedy initialization strategy. The effectiveness of the proposed algorithm is demonstrated through numerical experiments conducted on both synthetic datasets and the real-world transportation network of New York City. The results show that the proposed hybrid methodology not only yields high-quality solutions but also significantly reduces computational time, enabling faster convergence. Overall, this study provides practical insights for UAM infrastructure planning by emphasizing demand-oriented vertiport siting and inter-vertiport connectivity, thereby contributing to both theoretical development and large-scale implementation in complex urban environments. Full article
(This article belongs to the Special Issue Modelling and Simulation of Transportation Systems)
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17 pages, 5004 KiB  
Article
Local Emissions Drive Summer PM2.5 Pollution Under Adverse Meteorological Conditions: A Quantitative Case Study in Suzhou, Yangtze River Delta
by Minyan Wu, Ningning Cai, Jiong Fang, Ling Huang, Xurong Shi, Yezheng Wu, Li Li and Hongbing Qin
Atmosphere 2025, 16(7), 867; https://doi.org/10.3390/atmos16070867 - 16 Jul 2025
Viewed by 313
Abstract
Accurately identifying the sources of fine particulate matter (PM2.5) pollution is crucial for pollution control and public health protection. Taking the PM2.5 pollution event that occurred in Suzhou in June 2023 as a typical case, this study analyzed the characteristics [...] Read more.
Accurately identifying the sources of fine particulate matter (PM2.5) pollution is crucial for pollution control and public health protection. Taking the PM2.5 pollution event that occurred in Suzhou in June 2023 as a typical case, this study analyzed the characteristics and components of PM2.5, and quantified the contributions of meteorological conditions, regional transport, and local emissions to the summertime PM2.5 surge in a typical Yangtze River Delta (YRD) city. Chemical composition analysis highlighted a sharp increase in nitrate ions (NO3, contributing up to 49% during peak pollution), with calcium ion (Ca2+) and sulfate ion (SO42−) concentrations rising to 2 times and 7.5 times those of clean periods, respectively. Results from the random forest model demonstrated that emission sources (74%) dominated this pollution episode, significantly surpassing the meteorological contribution (26%). The Weather Research and Forecasting model combined with the Community Multiscale Air Quality model (WRF–CMAQ) further revealed that local emissions contributed the most to PM2.5 concentrations in Suzhou (46.3%), while external transport primarily originated from upwind cities such as Shanghai and Jiaxing. The findings indicate synergistic effects from dust sources, industrial emissions, and mobile sources. Validation using electricity consumption and key enterprise emission data confirmed that intensive local industrial activities exacerbated PM2.5 accumulation. Recommendations include strengthening regulations on local industrial and mobile source emissions, and enhancing regional joint prevention and control mechanisms to mitigate cross-boundary transport impacts. Full article
(This article belongs to the Section Air Quality)
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18 pages, 1268 KiB  
Article
An Optimistic Vision for Public Transport in Bucharest City After the Bus Fleet Upgrades
by Anca-Florentina Popescu, Ecaterina Matei, Alexandra Bădiceanu, Alexandru Ioan Balint, Maria Râpă, George Coman and Cristian Predescu
Environments 2025, 12(7), 242; https://doi.org/10.3390/environments12070242 - 15 Jul 2025
Viewed by 586
Abstract
Air pollution caused by CO2 emissions has become a global issue of vital importance, posing irreversible risks to health and life when concentration of CO2 becomes too high. This study aims to estimate the CO2 emissions and carbon footprint of [...] Read more.
Air pollution caused by CO2 emissions has become a global issue of vital importance, posing irreversible risks to health and life when concentration of CO2 becomes too high. This study aims to estimate the CO2 emissions and carbon footprint of the public transport bus fleet in Bucharest, with a comparative analysis of greenhouse gas (GHG) emissions generated by diesel and electric buses of the Bucharest Public Transport Company (STB S.A.) in the period 2021–2024, after the modernization of the fleet through the introduction of 130 hybrid buses and 58 electric buses. In 2024, the introduction of electric buses and the reduction in diesel bus mileage reduced GHG emissions by almost 13% compared to 2023, saving over 11 kilotons of CO2e. There was also a 2.68% reduction in the specific carbon footprint compared to the previous year, which is clear evidence of the potential of electric vehicles in achieving decarbonization targets. We have also developed two strategies, one for 2025 and one for the period 2025–2030, replacing the aging fleet with electric vehicles. This demonstrates the relevance of electric transport integrated into the sustainable development strategy for urban mobility systems and alignment with European standards, including improving air quality and living standards. Full article
(This article belongs to the Special Issue Air Pollution in Urban and Industrial Areas III)
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22 pages, 2150 KiB  
Article
Resource Utilization Enhancement and Life Cycle Assessment of Mangosteen Peel Powder Production
by Alisa Soontornwat, Zenisha Shrestha, Thunyanat Hutangkoon, Jarotwan Koiwanit, Samak Rakmae and Pimpen Pornchaloempong
Sustainability 2025, 17(14), 6423; https://doi.org/10.3390/su17146423 - 14 Jul 2025
Viewed by 439
Abstract
In alignment with the United Nations’ Sustainable Development Goals (SDGs) 12 (Responsible Consumption and Production) and 13 (Climate Action), this research explores the sustainable valorization of mangosteen peels into mangosteen peel powder (MPP), a value-added product with pharmaceutical properties. Mangosteen peels are an [...] Read more.
In alignment with the United Nations’ Sustainable Development Goals (SDGs) 12 (Responsible Consumption and Production) and 13 (Climate Action), this research explores the sustainable valorization of mangosteen peels into mangosteen peel powder (MPP), a value-added product with pharmaceutical properties. Mangosteen peels are an abundant agricultural waste in Thailand. This study evaluates six MPP production schemes, each employing different drying methods. Life Cycle Assessment (LCA) is utilized to assess the global warming potential (GWP) of these schemes, and the quality of the MPP produced is also compared. The results show that a combination of frozen storage and freeze-drying (scheme 4) has the highest GWP (1091.897 kgCO2eq) due to substantial electricity usage, whereas a combination of frozen storage and sun-drying (scheme 5) has the lowest GWP (0.031 kgCO2eq) but is prone to microbial contamination. Frozen storage without coarse grinding, combined with hot-air drying (scheme 6), is identified as the optimal scheme in terms of GWP (11.236 kgCO2eq) and product quality. Due to the lack of an onsite hot-air-drying facility, two transportation strategies are integrated into scheme 6 for scenarios A and B. These transportation strategies include transporting mangosteen peels from orchards to a facility in another province or transporting a mobile hot-air-drying unit to the orchards. The analysis indicates that scenario B is more favorable both operationally and environmentally, due to its lower emissions. This research is the first to comparatively assess the GWP of different MPP production schemes using LCA. Furthermore, it aligns with the growing trend in international trade which places greater emphasis on environmentally friendly production processes. Full article
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18 pages, 6234 KiB  
Article
Autonomous System for Air Quality Monitoring on the Campus of the University of Ruse: Implementation and Statistical Analysis
by Maciej Kozłowski, Asen Asenov, Velizara Pencheva, Sylwia Agata Bęczkowska, Andrzej Czerepicki and Zuzanna Zysk
Sustainability 2025, 17(14), 6260; https://doi.org/10.3390/su17146260 - 8 Jul 2025
Viewed by 365
Abstract
Air pollution poses a growing threat to public health and the environment, highlighting the need for continuous and precise urban air quality monitoring. The aim of this study was to implement and evaluate an autonomous air quality monitoring platform developed by the University [...] Read more.
Air pollution poses a growing threat to public health and the environment, highlighting the need for continuous and precise urban air quality monitoring. The aim of this study was to implement and evaluate an autonomous air quality monitoring platform developed by the University of Ruse, “Angel Kanchev”, under Bulgaria’s National Recovery and Resilience Plan (project BG-RRP-2.013-0001), co-financed by the European Union through the NextGenerationEU initiative. The system, based on Libelium’s mobile sensor technology, was installed at a height of two meters on the university campus near Rodina Boulevard and operated continuously from 1 March 2024 to 30 March 2025. Every 15 min, it recorded concentrations of CO, CO2, NO2, SO2, PM1, PM2.5, and PM10, along with meteorological parameters (temperature, humidity, and pressure), transmitting the data via GSM to a cloud-based database. Analyses included a distributional assessment, Spearman rank correlations, Kruskal–Wallis tests with Dunn–Sidak post hoc comparisons, and k-means clustering to identify temporal and meteorological patterns in pollutant levels. The results indicate the high operational stability of the system and reveal characteristic pollution profiles associated with time of day, weather conditions, and seasonal variation. The findings confirm the value of combining calibrated IoT systems with advanced statistical methods to support data-driven air quality management and the development of predictive environmental models. Full article
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22 pages, 3045 KiB  
Article
Type-2 Fuzzy-Controlled Air-Cleaning Mobile Robot
by Chian-Song Chiu, Shu-Yen Yao and Carlo Santiago
Symmetry 2025, 17(7), 1088; https://doi.org/10.3390/sym17071088 - 8 Jul 2025
Viewed by 372
Abstract
This research presents the development of a type-2 fuzzy-controlled autonomous mobile robot specifically designed for monitoring and actively maintaining indoor air quality. The core of this system is the proposed type-2 fuzzy PID dual-mode controller used for stably patrolling rooms along the walls [...] Read more.
This research presents the development of a type-2 fuzzy-controlled autonomous mobile robot specifically designed for monitoring and actively maintaining indoor air quality. The core of this system is the proposed type-2 fuzzy PID dual-mode controller used for stably patrolling rooms along the walls of the environment. The design method ingeniously merges the fast error correction capability of PID control with the robust adaptability of type-2 fuzzy logic control, which utilizes interval type-2 fuzzy sets. Furthermore, the type-2 fuzzy rule table of the right wall-following controller can be extended from the first designed fuzzy left wall-following controller in a symmetrical design manner. As a result, this study eliminates the drawbacks of excessive oscillations arising from PID control and sluggish response to large initial errors in typical traditional fuzzy control. The following of the stable wall and obstacle is facilitated with ensured accuracy and easy implementation so that effective air quality monitoring and active PM2.5 filtering are achieved in a movable manner. Furthermore, the augmented reality (AR) interface overlays real-time PM2.5 data directly onto a user’s visual field, enhancing situational awareness and enabling an immediate and intuitive assessment of air quality. As this type of control is different from that used in traditional fixed sensor networks, both broader area coverage and efficient air filtering are achieved. Finally, the experimental results demonstrate the controller’s superior performance and its potential to significantly improve indoor air quality. Full article
(This article belongs to the Special Issue Applications Based on Symmetry in Control Systems and Robotics)
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21 pages, 852 KiB  
Article
Technological Progress and Chinese Residents’ Willingness to Pay for Cleaner Air
by Xinhao Liu and Guangjie Ning
Sustainability 2025, 17(13), 6143; https://doi.org/10.3390/su17136143 - 4 Jul 2025
Viewed by 313
Abstract
This study examines whether China’s rapid spread of internet and mobile information technologies has translated into greater household support for government air-quality programs. Using nationally representative data from the Chinese General Social Survey (2018), this study estimates the causal impact of digital media [...] Read more.
This study examines whether China’s rapid spread of internet and mobile information technologies has translated into greater household support for government air-quality programs. Using nationally representative data from the Chinese General Social Survey (2018), this study estimates the causal impact of digital media use on residents’ willing to pay (WTP) each month for one additional “good-air” day. Ordinary least squares shows that individuals who rely primarily on the internet or mobile push services are willing to contribute CNY 1.9–2.7 more—about 43 percent above the sample mean of CNY 4.41. To address potential endogeneity, we instrumented digital media adoption using provincial computer penetration; two-stage least squares yielded roughly CNY 10.5, confirming a causal effect. Mechanism tests showed that digital access lowers complacency about local air quality, strengthens anthropogenic attribution of pollution, and heightens the moral norm that economic sacrifice is legitimate, jointly mediating the rise in WTP. Heterogeneity analyses revealed stronger effects among high-income households and renters, while extended tests showed that (i) the impact intensifies when the promised environmental gain rises from one to three or five clean-air days, (ii) attention to international news can crowd out local WTP, and (iii) digital media raise not only the likelihood of paying but also the amount paid among existing contributors. The findings suggest that targeted digital outreach—especially messages with concrete, locally salient goals—can substantially enlarge the fiscal base for air-quality initiatives, helping China advance its ecological-civilization and dual-carbon objectives. Full article
(This article belongs to the Special Issue Innovation and Low Carbon Sustainability in the Digital Age)
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12 pages, 234 KiB  
Article
Risk Perception and Self-Monitoring of Particulate Matter 2.5 (PM 2.5) Associated with Anxiety Among General Population in Urban Thailand
by Titaporn Luangwilai, Jadsada Kunno, Basmon Manomaipiboon, Witchakorn Ruamtawee and Parichat Ong-Artborirak
Urban Sci. 2025, 9(7), 256; https://doi.org/10.3390/urbansci9070256 - 3 Jul 2025
Viewed by 404
Abstract
Exposure to fine particulate matter (PM2.5) has become an increasing public health concern, particularly in urban areas facing severe air pollution. In response, individuals are increasingly turning to real-time tracking systems and self-monitoring tools. This study aimed to examine the association between PM2.5 [...] Read more.
Exposure to fine particulate matter (PM2.5) has become an increasing public health concern, particularly in urban areas facing severe air pollution. In response, individuals are increasingly turning to real-time tracking systems and self-monitoring tools. This study aimed to examine the association between PM2.5 risk perception, self-monitoring behaviors, and anxiety levels in the general population of Thailand. A cross-sectional survey was conducted during the dry season using an online questionnaire, which included the 7-item Generalized Anxiety Disorder (GAD-7) scale. A total of 921 participants residing in Bangkok and Chiang Mai were included. Binary logistic regression analysis, adjusted for sex, age, marital status, monthly income, and years of residence, revealed a significant association between anxiety and perceived health risks of PM2.5 exposure (OR = 1.09; 95% CI: 1.06–1.13). Daily self-monitoring of air quality over the past two weeks was also significantly linked to higher anxiety levels compared to non-monitoring individuals: OR = 1.92 (95% CI: 1.11–3.33) for websites, OR = 1.65 (95% CI: 1.01–2.72) for mobile apps, OR = 1.72 (95% CI: 1.12–2.64) for air purifiers, and OR = 3.34 (95% CI: 1.77–6.31) for air quality detectors. Monitoring 4–6 days per week using apps and air detectors was similarly associated with increased anxiety (OR = 1.64 and 2.30, respectively). Heightened perception of PM2.5 health risks and frequent self-monitoring behaviors are associated with increased anxiety among urban residents in Thailand. Public health interventions should consider implementing targeted alert systems during high-pollution periods and prioritize strategies to reduce PM2.5 emissions to alleviate public anxiety. Full article
25 pages, 10333 KiB  
Article
Design of a Bionic Self-Insulating Mechanical Arm for Concealed Space Inspection in the Live Power Cable Tunnels
by Jingying Cao, Jie Chen, Xiao Tan and Jiahong He
Appl. Sci. 2025, 15(13), 7350; https://doi.org/10.3390/app15137350 - 30 Jun 2025
Viewed by 236
Abstract
Adopting mobile robots for high voltage (HV) live-line operations can mitigate personnel casualties and enhance operational efficiency. However, conventional mechanical arms cannot inspect concealed spaces in the power cable tunnel because their joint integrates metallic motors or hydraulic serial-drive mechanisms, which limit the [...] Read more.
Adopting mobile robots for high voltage (HV) live-line operations can mitigate personnel casualties and enhance operational efficiency. However, conventional mechanical arms cannot inspect concealed spaces in the power cable tunnel because their joint integrates metallic motors or hydraulic serial-drive mechanisms, which limit the arm’s length and insulation performance. Therefore, this study proposes a 7-degree-of-freedom (7-DOF) bionic mechanical arm with rigid-flexible coupling, mimicking human arm joints (shoulder, elbow, and wrist) designed for HV live-line operations in concealed cable tunnels. The arm employs a tendon-driven mechanism to remotely actuate joints, analogous to human musculoskeletal dynamics, thereby physically isolating conductive components (e.g., motors) from the mechanical arm. The arm’s structure utilizes dielectric materials and insulation-optimized geometries to reduce peak electric field intensity and increase creepage distance, achieving intrinsic self-insulation. Furthermore, the mechanical design addresses challenges posed by concealed spaces (e.g., shield tunnels and multi-circuit cable layouts) through the analysis of joint kinematics, drive mechanisms, and dielectric performance. The workspace of the proposed arm is an oblate ellipsoid with minor and major axes measuring 1.25 m and 1.65 m, respectively, covering the concealed space in the cable tunnel, while the arm’s quality is 4.7 kg. The maximum electric field intensity is 74.3 kV/m under 220 kV operating voltage. The field value is less than the air breakdown threshold. The proposed mechanical arm design significantly improves spatial adaptability, operational efficiency, and reliability in HV live-line inspection, offering theoretical and practical advancements for intelligent maintenance in cable tunnel environments. Full article
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20 pages, 4155 KiB  
Article
Green Wall System to Reduce Particulate Matter in Livestock Housing: Case Study of a Dairy Barn
by Alice Finocchiaro, Serena Vitaliano, Grazia Cinardi, Provvidenza Rita D’Urso, Stefano Cascone and Claudia Arcidiacono
Buildings 2025, 15(13), 2280; https://doi.org/10.3390/buildings15132280 - 28 Jun 2025
Viewed by 318
Abstract
Livestock farming has been identified as a significant contributor to atmospheric pollution, underscoring the necessity for the design and management of housing systems to adopt mitigation strategies. In the context of civil engineering, green wall systems are proving to be effective solutions for [...] Read more.
Livestock farming has been identified as a significant contributor to atmospheric pollution, underscoring the necessity for the design and management of housing systems to adopt mitigation strategies. In the context of civil engineering, green wall systems are proving to be effective solutions for air filtration and purification. Nevertheless, research related to their application in livestock buildings is limited. This study focuses on the design, implementation, and performance evaluation of a modular, mobile green wall system that has been specifically developed to test PM2.5 concentrations’ reduction in naturally ventilated, free-stall dairy barns in the Mediterranean region. To this end, PM2.5 concentrations and climatic parameters have been measured before and after the application of the green wall system. Based on one-way analysis of variance, PM2.5 concentrations after the application were significantly lower (p < 0.001) than those before the mitigation strategy. The results of this study showed that the overall efficacy of the green wall reached 44%. The implementation of green wall systems offers a promising strategy to improve air quality in livestock facilities and to design aesthetically pleasing barns with a positive impact on the surrounding landscape. Full article
(This article belongs to the Section Building Energy, Physics, Environment, and Systems)
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29 pages, 1069 KiB  
Article
Assessing Walkability in Riyadh’s Commercial Streets: Public Perceptions and Prioritization
by Bander Fahad Alkrides, Tracy Washington, Mark Limb and Debra Cushing
Sustainability 2025, 17(13), 5748; https://doi.org/10.3390/su17135748 - 23 Jun 2025
Viewed by 692
Abstract
Urban sustainability is closely linked to walkability, as it impacts social interaction, public health, and economic development. In megacities like Riyadh, where automobiles dominate mobility, the development of pedestrian infrastructure remains inadequate. An online survey was conducted through public sampling to evaluate walking [...] Read more.
Urban sustainability is closely linked to walkability, as it impacts social interaction, public health, and economic development. In megacities like Riyadh, where automobiles dominate mobility, the development of pedestrian infrastructure remains inadequate. An online survey was conducted through public sampling to evaluate walking conditions in central Riyadh’s commercial districts. The 302 participants evaluated 49 critical walkability indicators to determine their significance and satisfaction with the current conditions. Gap analysis and a displeasure measurement framework identified pedestrian challenges. Participants acknowledged the importance of walkability aspects but expressed strong dissatisfaction with existing conditions. Key barriers to pedestrian comfort included inadequate facilities, environmental discomfort, weak safety measures, and cultural driving preferences. The study highlighted crucial walkability issues requiring improvement, such as public toilets, shaded pathways, air quality, and pedestrian-friendly infrastructure. The findings emphasize the need for targeted policy interventions in Riyadh’s commercial districts to enhance pedestrian accessibility and comfort, to promote urban sustainability through improved walkability. This study offers a methodological advancement by combining Relative Importance Index, gap analysis, and a novel disgruntlement measurement framework to assess walkability. The use of 49 Delphi-derived indicators contextualized within a GCC megacity adds a unique perspective to urban sustainability research. The findings inform both local policy and global urban studies by demonstrating how culturally and climatically adaptive walkability metrics can guide equitable, data-driven interventions. Full article
(This article belongs to the Section Sustainable Urban and Rural Development)
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