Search Results (323)

Following the implementation of the Shanghai Clean Air Act, this study investigates the evolution of air pollution in central Shanghai (Putuo District) by analyzing continuous monitoring data (2016–2020) and chemical speciation of particulate matter (2017–2018). The results confirm a transition toward a “low exceedance rate and low background concentration” regime. However, short-term exceedance episodes persist, generally occurring in winter and spring, with significantly amplified diurnal variations on exceedance days. Distinct patterns emerged between PM fractions: PM₁₀ exceedances were characterized by a single morning peak linked to traffic-induced coarse particles, while PM₂.₅ exceedances showed synchronized diurnal peaks with NO₂, suggesting a stronger contribution from vehicle exhaust. Source apportionment revealed that mineral components (21.61%) and organic matter (OM, 21.02%) dominated in PM₁₀, implicating construction and road dust. In contrast, PM_2.5 was primarily composed of OM (26.73%) and secondary inorganic ions (dominated by nitrate), highlighting the greater importance of secondary formation. The findings underscore that sustained PM_2.5 mitigation requires targeted control of gasoline vehicle emissions and gaseous precursors. Full article

Civilisational progress contributes to an increase in the number of vehicles on the road, thereby intensifying air pollutant emissions and accelerating the degradation of the natural environment. Effective protection of urban areas against air pollution enhances safeguarding against numerous allergies and diseases resulting from unplanned and unintended absorption of harmful pollutants into the human body. Sustainable urban planning requires the collaboration of multiple scientific disciplines. In this context, measurement becomes crucial, as it reveals the spatial scale of the problem and identifies existing disparities. This study uses an integrated approach of standard measurement methods and statistical and geostatistical data analysis, identifying PM₁ fractions that are not included in EU air quality monitoring. The hypothesis explores how surface-based results correspond to point-based results from national air quality monitoring. The presented implications demonstrate similarities and differences between the studied measurement methods and the spatial distributions of PM₁₀, PM_2.5, and PM₁ dust. Full article

Road dust resuspension is widely recognized as a major contributor to traffic-related particulate matter (PM) in urban environments. Nevertheless, reported emission factors exhibit substantial variability. These discrepancies stem not only from the intrinsic complexity of the resuspension process but also from limitations in measurement techniques, which often fail to adequately control or characterize the influencing parameters. As a result, the contribution of each parameter remains difficult to isolate, leading to inconsistencies across studies. This study presents an experimental protocol developed to quantify PM10 and PM2.5 emission factors associated with vehicle-induced road dust resuspension. Experiments were conducted on a dedicated test track seeded with alumina particles of controlled mass and size distribution to simulate road dust. A network of microsensors was strategically deployed at multiple upwind and downwind locations to continuously monitor particle concentration variations during vehicle passages. Emission factors were derived through time integration of the mass flow rate of resuspended dust measured by the sensor network. The estimated PM10 emission factor showed excellent agreement, within 2.5%, with predictions from a literature-based formulation, thereby validating the accuracy and external relevance of the proposed protocol. In contrast, comparisons with U.S. EPA formulas and other empirical equations revealed substantially larger discrepancies, particularly for PM2.5, highlighting the persistent limitations of current modeling approaches. Full article

This article delineates the outcomes of a comprehensive analysis of occupational conditions in coal mining, focusing on dust exposure. A multifaceted model is proposed for the holistic evaluation of occupational environments, integrating risk assessment methodologies and decision-making frameworks within a risk-based paradigm. Risk assessment involved pairwise comparison, T. Saaty’s Analytic Hierarchy Process, a pessimistic decision-making approach, and fuzzy set membership functions. Correlations were established between respiratory disease risk among open pit coal mine workers and dust generation sources at the project design phase. The risk values were then validated using source attributes and particle physicochemical parameter analysis, including disperse composition and morphology. The risk assessment identified haul roads as a predominant factor in occupational disease pathogenesis, demonstrating a calculated risk level of R = 0.512. The dispersed analysis indicated the prevalence of PM1.0 and submicron particles (≤1 µm) with about 77% of the particle count, the mass distribution showed the respirable fraction (1–5 µm) comprising up to 50% of the total dust mass. Considering in situ monitoring data and particulate morphology analysis haul roads (R = 0.281) and the overburden face (R = 0.213) were delineated as primary targets for the implementation of enhanced health and safety interventions. While most critical at the design stage amidst data scarcity and exposure uncertainty, the approach permits subsequent refinement of occupational risks during operations through the incorporation of empirical monitoring data. Full article

Particulate matter (PM) pollution is high in most Bulgarian regions, especially large urban areas. In a previous study covering one year of data collection and analysis by source apportionment techniques such as positive matrix factorization we show that the main source of high PM₁₀ (PM with a diameter of 10 μm or less) concentration in the city of Sofia is soil and road dust resuspension into the surface layer of the air. Resuspension has seasonal variations, with a relatively large impact (25%) associated with drying periods. In the present paper we combine classical indices (NDVI, BSI, NDMI) derived from Sentinel-2 imagery with meteorological and air quality data, as well as other related variables regarding yearly average traffic and inventory estimates, transportation infrastructure and demographic data, including motorized inhabitants and wood/coal stoves in use, by area. We apply statistical and machine learning methods to analyze the contribution of bare soil surfaces to the overall PM resuspension. Based on a series of stack ensemble meta-models with coefficient of determination $R^2\approx 0.9$ we conclude that the contribution of bare soil surfaces to the overall PM₁₀ resuspension is around $10\%$ (between $5\%$ and $15\%$), by our preliminary rough estimates. Full article

Accurate assessment of vehicular air pollution in arid urban environments remains a challenge because standard emission models often overlook localized influences such as climate-driven dust resuspension and urban canyon effects. This study develops an enhanced modeling framework that integrates critical regional parameters into established algorithms to improve estimates of traffic-related emissions, including PM₁₀, PM₂.₅, CO, and NO₂. The US EPA’s AP-42 algorithm was modified to incorporate a novel highway width-to-building height ratio (I/H) and a climate-driven dynamic silt loading model derived from satellite data, while the European EEA algorithm was refined by introducing an explicit fuel density correction (ρ). The framework was applied and validated on two representative highways in Jordan—an industrial corridor and an urban-commercial artery—using continuous sensor-based measurements. Results indicate substantial improvement in predictive performance, with reductions of 60–77% in normalized difference for particulate matter and 72% for CO. The model successfully distinguished between emission regimes, capturing a seasonal silt-loading peak of approximately 17.5 g/m² during autumn at the industrial site, compared to more stable, traffic-dominated emissions along the urban corridor. Although NO₂ performance showed modest gains (4–40%) due to complex photochemical processes, the overall framework proved to be a robust and reliable tool for air quality assessment in arid cities. This adaptable approach provides a foundation for targeted air pollution management, and future work will integrate real-time dispersion dynamics and photochemical modules to better capture secondary pollutant formation. Full article

Road dust contains a variety of heavy metals and is a widely used sustainability indicator for monitoring pollution and assessing environmental and health risks in sustainable development. Heavy metals in road dust mainly originate from worn-off particles from vehicles, such as tires, brake pads, road dust, and emissions from exhaust pipes. These heavy metal particles could remain on the road surface for a long period and cause environmental pollution. In this preliminary study, road dust was collected from 8 representative areas in Macao. The heavy metal content from road dust in Macao was extracted from each of the collected samples for an assessment of the heavy metal pollution and its potential threat to human health. The results show that heavy metals primarily originate from human activities, including transportation emissions (Mn: 67.37%, Zn: 57.01%, Sb: 54.1%) and industrial activities (Al: 84.70%, Fe: 76.71%, Pb: 65.32%). The metal-specific non-carcinogenic risk ranges from 1.17 × 10⁻⁷ to 2.65 × 10⁻⁵ and the total carcinogenic risk is 6.91 × 10⁻¹⁰, showing minimum health effects from heavy metals in road dust. Furthermore, there is a significant correlation between the total vehicle counts and the heavy metal contents such as Al, Si, As, V, and Fe (r = 0.50 to 0.82). This work represents the first characterization of heavy metal contents and risks of urban road dust in Macao. Full article

Microplastic (MP) pollution in urban areas is a growing global concern due to its health risks and environmental effects. This study investigates the sources, spatial distribution, and health risks of MPs in road dust across industrial, capital city, and peri-urban areas of Bangladesh. Street dust samples were collected from 15 heavily congested traffic sites across Dhaka and its surrounding areas. The samples were analyzed using fluorescence microscopy and Fourier Transform Infrared (FTIR) spectroscopy to identify MP types and their morphological characteristics. We have identified six types of polymers, including Polyvinyl alcohol (PVA), Polyethylene (PE), Polypropylene (PP), Polystyrene (PS), Low-Density Polyethylene (LDPE) and High-Density Polyethylene (HDPE), with industrial areas exhibiting the highest levels of MPs followed by capital city and peri-urban zones. PP was the most prevalent MP polymer, with the highest level in industrial areas (14.1 ± 1.7 MPs/g), followed by capital city (9.6 ± 1.92 MPs/g) and peri-urban areas (7.2 ± 1.56 MPs/g). Principal Component Analysis (PCA) identified traffic emissions, industrial activities, and mismanaged plastic waste as the primary sources of MPs. Health risk evaluations indicated that children are more susceptible to MP exposure through ingestion and inhalation, with industrial areas posing the highest carcinogenic risk. The findings underscore the pressing demand for better waste management systems and stricter regulatory measures to mitigate MP pollution and safeguard public health in urban environments. Addressing these challenges is essential to reduce the growing threat of MPs and their long-term effects on ecosystems and human well-being. Full article

Urban industrial complexes have been expanding worldwide, reducing the spatial separation between agricultural, residential, and industrial zones, particularly in developing nations. Urban road dust contamination, a sensitive indicator of urban environmental quality, primarily originates in urbanization and industrialization. Its detrimental impacts on human health arise not only from particulate matter itself but also from toxic and harmful substances embedded within dust particles. Toxic metals in road dust can pose health risks through inhalation, ingestion and contact. To investigate the seasonal patterns, bioaccessibility levels and the potential human health risks linked to toxic metals (Cadmium (Cd), Nickel (Ni), Arsenic (As), Lead (Pb), Zinc (Zn), Copper (Cu), and Chromium (Cr)), 34 dust samples were collected from key roads in proximity to representative industrial facilities in Wuhan’s Qingshan District. The study found that the concentrations of Cd, Pb, and Cu in road dust were within the limits set by the national standard (GB 15618-2018), while Ni and As were not. Seasonally, Ni, As, Pb, Zn, and Cr exhibited higher concentrations during the summer than in other seasons, whereas Cd levels were lowest in spring and highest in autumn, the opposite of Cu. According to the Simplified Bioaccessibility Extraction Test (SBET), the average bioaccessibility rates of toxic metals were Cd > Zn > Cu > Ni > Cr > As > Pb. An improved health risk assessment model was developed, integrating metal enrichment, bioaccessibility, and parameter uncertainty. Results indicated that Cd, Ni, Zn, Cu, As, and Cr posed no significant non-carcinogenic risk. However, for children, the carcinogenic risks of Cd and As were relatively high, identifying them as priority control metals. Therefore, it is recommended to periodically monitor As and Cd and regulate their potential emission sources, especially in winter and spring. Full article

Road and pavement construction require huge volumes of borrowed soils in addition to the foundation soils. Unfortunately, not all soils are suitable for construction purposes. Soil stabilization is a fundamental technique used to enhance the engineering properties of weak ground/soil to meet the demands of large infrastructure projects, such as roads. It is in this regard that this study investigates the strength development, durability, and effectiveness of cement and quarry dust as stabilizers to enhance the geotechnical properties of a weak tropical clay soil. Cement was added in the range of 0% to 10% while quarry dust was used to partially replace soil in the range of 0% to 50%. The results show significant improvements in the Atterberg limits and strength properties of the tropical clay. The liquid limit reduced from 43.2% to 25.1% while the plasticity index reduced from 17.6% to 10.2% at 50% quarry dust and 10% cement content. Similarly, the maximum dry unit weight increased from 17.4 kN/m³ to 21.3 kN/m³ while the optimum moisture content decreased from 17.1% to 12.9%. The maximum soaked CBR value was 172%, representing a 1497% enhancement over untreated soil. Also, the maximum unconfined compressive strength (UCS) reached 2566 kN/m² at 28 days of curing, representing a 1793.73% increase when compared to the untreated soil. Cement content was found to be the predominant factor influencing strength development. The study shows that cement–quarry dust blends compacted at high energy can be adopted in sustainable road construction. Full article

As many countries transition to electric vehicles (EVs) to reduce tailpipe emissions from internal combustion engine vehicles (ICEVs), both vehicle types continue to generate non-exhaust particulate matter (PM), including tire wear, brake wear, road surface wear, and particularly road dust resuspension. Among these, road dust resuspension is a major contributor to non-exhaust PM. While factors such as vehicle weight and drivetrain configuration have been extensively studied in fleet-level research, direct comparisons between ICEVs and EVs of the same model have not been explored. This study investigates the effects of drivetrain, vehicle weight, and payload on road dust resuspension emissions from ICEV and EV models. Two experimental approaches were employed: (1) acceleration from 0 to 60 km/h, and (2) a simulated real-world driving cycle (RDC). Each test was conducted under both light and heavy payload conditions. The results show that the EV consistently emitted more PM than the ICEV during both acceleration and RDC tests, based on factory-standard vehicle weights. Under identical vehicle weight conditions, the EV demonstrated higher PM resuspension levels, likely due to its higher torque and more immediate power delivery, which increases friction between the tires and the road, particularly during rapid acceleration. Both vehicle types exhibited significant increases in PM emissions under heavy payload conditions. These findings underscore the importance of addressing non-exhaust emissions from EVs, particularly road dust resuspension, and highlight the need for further research into mitigation strategies, such as vehicle lightweighting. Full article

Accurate boundary detection is critical for autonomous trackless rubber-wheeled vehicles in underground coal mines, as it prevents lateral collisions with tunnel walls. Unlike open-road environments, underground tunnels suffer from poor illumination, water mist, and dust, which degrade visual imaging. To address these challenges, this paper proposes a navigable area computation for underground autonomous vehicles via ground feature and boundary processing, consisting of three core steps. First, a real-time point cloud correction process via pre-correction and dynamic update aligns ground point clouds with the LiDAR coordinate system to ensure parallelism. Second, corrected point clouds are projected onto a 2D grid map using a grid-based method, effectively mitigating the impact of ground unevenness on boundary extraction; third, an adaptive boundary completion method is designed to resolve boundary discontinuities in junctions and shunting chambers. Additionally, the method emphasizes continuous extraction of boundaries over extended periods by integrating temporal context, ensuring the continuity of boundary detection during vehicle operation. Experiments on real underground vehicle data validate that the method achieves accurate detection and consistent tracking of dual-sided boundaries across straight tunnels, curves, intersections, and shunting chambers, meeting the requirements of underground autonomous driving. This work provides a rule-based, real-time solution feasible under limited computing power, offering critical safety redundancy when deep learning methods fail in harsh underground environments. Full article

Urban road dust (URD) is a major source of particulate matter (PM) and pollutants, including trace elements and organic compounds, affecting human health and the environment. This study investigates the chemical composition, toxicity, and environmental transport mechanisms of URD from road and rail systems in two Polish cities. It compares trace element concentrations (e.g., Cu, Zn, Pb), chemical composition, toxicity of road vs. rail dust, and the impact of rainfall on contaminant dispersion. The oral pathway was identified as the main exposure route in both adults and children, followed by that of dermal contact. Railways pose additional challenges due to frequent maintenance and increased PM emissions. Results show that smaller cities like Rawicz may present higher health risks from URD due to local industry (e.g., metal processing) than larger cities like Wrocław. Rainfall mobilizes trace elements in urban dust, increasing pollutant runoff and exposure risks, highlighting the need for better runoff management. The highest road-related pollution was found in Rawicz (S5), with the highest railway-related pollution also found at the Rawicz station. Microtox showed no toxicity in Wrocław URD (except for short-term effect) but higher toxicity in Rawicz. Daphtoxkit showed the highest Daphnia magna mortality near roads (40.0%) in Rawicz. Ostracodtoxkit revealed strong growth inhibition in Wrocław (up to 94.29%). ECR confirmed a higher cancer risk in Rawicz, especially in children (Cr, As). Full article

Asphalt plant reclaimed powder is a common solid waste in road engineering. Reusing reclaimed powder as filler holds significant importance for environmental protection and resource conservation. The key factors affecting the feasibility of reclaimed powder reuse are its acidity/alkalinity and cleanliness. Traditional evaluation methods, such as the methylene blue test and plasticity index, can assess reclaimed powder properties to guide its recycling. However, these methods suffer from inefficiency, strong empirical dependence, and high variability. To address these limitations, this study proposes a rapid and precise evaluation method for reclaimed powder properties based on Fourier transform infrared spectroscopy (FTIR). To do so, five field-collected reclaimed powder samples and four artificial samples were evaluated. Scanning electron microscopy (SEM), X-ray fluorescence spectroscopy (XRF), and X-ray diffraction (XRD) were employed to characterize their microphase morphology, chemical composition, and crystal structure, respectively. Subsequently, FTIR was used to establish correlations between key acidity/alkalinity, cleanliness, and multiple characteristic peak intensities. Representative infrared characteristic peaks were selected, and a quantitative functional group index (Is) was proposed to simultaneously evaluate acidity/alkalinity and cleanliness. The results indicate that reclaimed powder primarily consists of tiny, crushed stone particles and dust, with significant variations in crystal structure and chemical composition, including calcium carbonate, silicon oxide, iron oxide, and aluminum oxide. Some samples also contained clay, which critically influenced the reclaimed powder properties. Since both filler acidity/alkalinity and cleanliness are affected by clay (silicon/carbon ratio determining acidity/alkalinity and aluminosilicate content affecting cleanliness), this study calculated four functional group indices based on FTIR absorption peaks, namely the Si-O-Si stretching vibration (1000 cm⁻¹) and the CO₃²⁻ asymmetric stretching vibration (1400 cm⁻¹). These indices were correlated with conventional testing results (XRF for acidity/alkalinity, methylene blue value, and pull-off strength for cleanliness). The results show that the Is index exhibited strong correlations (R² = 0.89 with XRF, R² = 0.80 with methylene blue value, and R² = 0.96 with pull-off strength), demonstrating its effectiveness in predicting both acidity/alkalinity and cleanliness. The developed method enhances reclaimed powder detection efficiency and facilitates high-value recycling in road engineering applications. Full article

Dust emissions from unpaved haul roads in open-pit coal mining pose a significant risk to air quality, health, and operational efficiency of mining operations. This study integrated real-time field monitoring with numerical simulations using ANSYS Fluent 2023 R1 to investigate the generation, dispersion, and migration of particulate matter (PM) at the Ha’erwusu open-pit coal mine under varying meteorological conditions. Real-time measurements of PM2.5, PM10, and TSP, along with meteorological variables (wind speed, wind direction, humidity, temperature, and air pressure), were collected and analyzed using Pearson’s correlation and multivariate linear regression analyses. Wind speed and air pressure emerged as dominant factors in winter, whereas wind and temperature were more influential in summer (R² = 0.391 for temperature vs. PM2.5). External airflow simulations revealed that truck-induced turbulence and high wind speeds generated wake vortices with turbulent kinetic energy (TKE) peaking at 5.02 m²/s², thereby accelerating particle dispersion. The dust migration rates reached 3.33 m/s within 6 s after emission and gradually decreased with distance. The particle settling velocities ranged from 0.218 m/s for coarse dust to 0.035 m/s for PM2.5, with dispersion extending up to 37 m downwind. The highest simulated dust concentration reached 4.34 × 10⁻² g/m³ near a single truck and increased to 2.51 × 10⁻¹ g/m³ under multiple-truck operations. Based on spatial attenuation trends, a minimum safety buffer of 55 m downwind and 45 m crosswind is recommended to minimize occupational exposure. These findings contribute to data-driven, weather-responsive dust suppression planning in open-pit mining operations and establish a validated modeling framework for future mitigation strategies in this field. Full article