Search Results (1,214)

Understanding the dynamics of the urban atmospheric boundary layer is critical for accurate meteorological and air quality modeling. Utilizing one year of continuous Doppler wind lidar observations, this study investigates the seasonal and diurnal variability of wind fields, low-level jets (LLJs), and mixing-layer height (MLH) at an urban site in Beijing. Results show that horizontal winds are strongest in winter and spring and weaker in summer, with northwesterly flow dominating in winter and more diverse patterns in summer, while the corrected vertical-velocity distributions show seasonally varying structures and are interpreted cautiously as frequency-distribution characteristics. A distinct diurnal phase reversal in wind speed is identified near 0.3 km. LLJs occur predominantly at night, with core heights descending from 1.2–1.6 km in winter to 0.6–0.8 km in summer, and are associated with enhanced vertical shear. MLH reaches its deepest development in spring, with clear-sky peaks exceeding 1.5 km, while summer growth is comparatively limited and is associated with stronger latent heat partitioning. These findings indicate that wind fields, LLJs, and MLH exhibit coherent seasonal and diurnal covariations, while their direct causal relationships require further process-oriented analysis. This study provides a year-long observational basis for evaluating urban ABL parameterizations. Full article

Internal combustion engines are a well-established, efficient and dispatchable solution for distributed power generation and they are widely used in various sectors including grid balancing, data centers and combined heat and power systems. Current research efforts focus on further increasing efficiency, enabling decarbonization through renewable fuels and improving responsiveness to electricity demand in the presence of variable renewable energy sources. In this context, the free-piston linear generator (FPLG) stands out as a highly promising technology, as it directly converts piston motion into electricity, offering high efficiency, reduced mechanical complexity and seamless grid integration. Initially explored for its high-efficiency potential with homogeneous charge compression ignition combustion at extreme compression ratios, opposed-piston FPLGs are now commercially available for distributed power generation, delivering global efficiencies exceeding 45%, near-zero emissions and multi-fuel capability. Building on the detailed studies conducted by Svrcek and co-authors, this work investigates the power-generation potential of low-temperature homogeneous combustion using CFD simulations with detailed chemical kinetics. First, rapid compression machine (RCM) experiments with methane were reproduced in simulations to validate the proposed methodology and to consolidate experimental findings on the maximum achievable efficiency. Subsequently, an extensive RCM simulation campaign supported the identification of optimal operating conditions in terms of air–fuel ratio using methane as fuel. The RCM results enabled the definition of a preliminary methane-fueled opposed-piston FPLG configuration. Full-cycle simulations including gas exchange, mixing and combustion demonstrated an indicated efficiency of 58% at an equivalence ratio $\varphi =0.5$ and a compression ratio of 50. The key novelties of this study are the development of a novel RCM-2 configuration that more closely reproduces the dynamic behavior of an opposed-piston FPLG including air-spring effects and the introduction of a divided intake port strategy to simultaneously reduce fuel slip and mitigate knocking behaviour through charge stratification. The simulation results for the proposed configuration confirm the potential of opposed-piston FPLGs for high-efficiency power generation and highlight key parameters affecting performance and emissions formation. Full article

This study evaluates the potential of L-band passive microwave data for monitoring soil moisture (SM) in boreal and temperate forests using SMAP and SMOS AM and PM overpasses. SMAP and SMOS Level 3 SM products were first assessed for spring and summer seasons. SMOS showed lower accuracy (r² = 0.04–0.24, ubRMSE = 0.09–0.13 m³/m³), while SMAP performed better (r² = 0.18–0.62, ubRMSE = 0.05–0.07 m³/m³) across sites and overpasses. Given the larger number of SMAP TB observations at a fixed incidence angle and greater temporal coverage over the study area, SMAP was selected for SM estimation using ML models. Feature importance analysis identified brightness temperature (TB) as the most influential variable, followed by vegetation water content (VWC), air and soil temperatures, and the microwave polarization difference index (MPDI). Soil and air temperatures were interchangeable during AM overpasses, whereas PM overpasses showed distinct differences, likely due to thermal absorption by dense vegetation. Using optimal features, SM was estimated with CatBoost, Gradient Boosting (GB), Random Forest (RF), and Principal Component Regression (PCR), using stratified shuffle split (SSS) and leave-one-year-out cross-validation (LOYOCV). In SSS, CatBoost achieved slightly higher accuracy than the other ensemble models (AM: r² = 0.73; PM: R² = 0.74), while PCR yielded substantially lower accuracy across both overpasses. LOYOCV showed closer rankings among models, with CatBoost ranking highest overall (r² = 0.58 for AM and 0.54 for PM). Results highlight the feasibility of improved SM estimation in forests using L-band TB, VWC, temperature variables, and MPDI. Full article

This study examined the chemical composition and quantitative source contributions of coarse (PM_10–2.5) and fine (PM_2.5) particles in ship-based PM₁₀ and PM_2.5 filter samples from 2020 to 2024 across the Yellow Sea. The observations were primarily conducted during the spring season, when the influence of continental air masses from East Asia is pronounced, and detailed analyses of water-soluble ions and elemental species were performed. In coarse particles, sea salt components (e.g., Na⁺ and Cl⁻) and soil-derived species (e.g., nss-Ca²⁺ and CO₃²⁻) were predominant, whereas fine particles were dominated by secondary inorganic species such as nss-SO₄²⁻, NO₃₋, and NH₄⁺. Source contributions were estimated using Dispersion Normalized Positive Matrix Factorization (DN-PMF), and eight common factors were identified, including sea salt, soil, secondary nitrate, secondary sulfate, oil combustion, biomass burning, marine biogenic emissions, and plant growth. Additionally, an industry factor was uniquely resolved in coarse particles, whereas a mobile source factor was identified in fine particles. In coarse particles, sea salt (30.9%) and soil (15.1%) were the major contributing sources, whereas fine particles were dominated by secondary nitrate (48.6%) and secondary sulfate (15.6%). Potential Source Contribution Function (PSCF) analysis indicated that the sea salt and oil combustion factors in coarse particles were associated with coastal regions of the Yellow Sea and the East China Sea, while the soil factor corresponded spatially with inland regions of northern China. In contrast, the secondary nitrate, secondary sulfate, and biomass burning factors in fine particles showed strong associations with inland regions of eastern China. Using size-resolved DN-PMF and five years of repeated observations over the same marine region, this study provides the first quantitative source apportionment analysis of interannual atmospheric composition variability and long-range transport affecting air quality over the Yellow Sea. Full article

Xizang is characterized by high altitude, low air pressure, strong atmospheric transparency, and complex terrain, while sparse ground stations coexist with continuously available remotely sensed data, and systematic studies on SSR bias correction and meteorological influences under plateau conditions remain limited. This study focuses on a short-term spring case at one urban observation site in Lhasa, using observations collected from 4 to 30 April 2025 to investigate the bias correction of remotely sensed surface solar radiation (SSR) and the influence of meteorological factors. Ground observations and Himawari-8 remotely sensed data were first spatially and temporally matched and preprocessed. Spearman correlation analysis was then used to select key input variables. Support vector regression, random forest, XGBoost, and multiple linear regression models were subsequently developed, followed by a Stacking ensemble model for bias correction. Finally, local sensitivity analysis was conducted to examine the local response of the correction model to selected meteorological variables at a representative baseline point. The results showed that the correlation coefficient between remotely sensed SSR and ground-observed SSR was 0.88 ($p<0.001$). The Stacking ensemble model achieved the best performance, with a test set $R^2$ of 0.8796, an MAE of 118.54 W/m², and an RMSE of 152.41 W/m². Local sensitivity analysis showed that a +10 hPa perturbation in air pressure increased the model output by 173.45 W/m², while a +10 °C perturbation in air temperature increased the output by 23.76 W/m². This study provides a reference for improving the accuracy of remotely sensed SSR and for solar resource assessment in plateau regions. Full article

Background: High concentrations of coarse particulate matter PM₁₀ from road dust are a major air quality concern in Visby, Sweden. To mitigate these levels, local authorities replaced soft limestone with crushed granite as an anti-slip material starting in the winter of 2023/2024. This is a follow-up study evaluating the impact of this intervention on PM₁₀ concentrations and the associated short-term respiratory health effects. Methods: Daily counts of healthcare visits for respiratory diseases (ICD-10: J00–J99) and daily mean PM₁₀ concentrations were analyzed using a quasi-Poisson regression model. This study compared the limestone period (2015–2019) with the granite period (2023–2025), stratified by season (winter/spring and summer/autumn) and age group (children 0–17 years and adults >17 years). Results: The transition to crushed granite reduced peak PM₁₀ concentrations during the spring. For adults, the relative risks for respiratory visits during winter/spring decreased during the granite period when compared to the limestone period (Wald p < 0.05). However, when considering that there were a majority of non-statistically significant differences when comparing the granite and limestone periods, these results should be interpreted with caution. Among children, more pronounced associations were observed during summer, although no significant differences in risk were detected between the limestone and granite periods. Conclusions: Although the intervention effectively lowered particle mass concentrations, only minor changes were observed in the overall epidemiological pattern. This suggests that public health improvements may be limited by factors beyond total mass reduction, such as particle mineralogy or seasonal exposure dynamics. Full article

This study examines the meteorological and gaseous pollutant drivers of PM_2.5 under mild, moderate, and severe pollution conditions in the Beijing–Tianjin–Hebei region, with the aim of supporting sustainable air quality management. Daily observations from approximately 65 monitoring stations from 1 November 2021 to 31 October 2024 were used, including PM_2.5, four gaseous pollutants (SO₂, NO₂, CO, and O₃), and five meteorological variables: temperature, pressure, relative humidity, precipitation, and wind speed. A CatBoost–SHAP framework was adopted, with CatBoost used for station-level spatial prediction of PM_2.5 and SHAP applied to interpret variable contributions. Based on predefined PM_2.5 thresholds, 425 pollution days were classified into those three pollution-level scenarios. These pollution days occurred mainly in winter and spring, with higher frequencies in Handan, Baoding, and Shijiazhuang, followed by Tianjin and Beijing. The model performed well across the three pollution-level scenarios. The severe-pollution scenario achieved the highest R², indicating a clearer spatial structure under high-PM_2.5 conditions. Although absolute RMSE and MAE increased with pollution severity, their normalized values changed little, suggesting that larger errors mainly reflected stronger spatial heterogeneity at higher PM_2.5 concentrations. SHAP results showed that CO, precipitation, wind speed, and temperature dominated the prediction structure. CO was the most stable and influential predictor, but its importance should be interpreted as an indicator of combustion-related pollution accumulation rather than direct causality. Precipitation represented event-dependent wet scavenging, wind speed reflected dispersion conditions, and temperature captured seasonal and thermal background effects. SHAP dependence analysis further indicated that CO had the clearest direct dependence, whereas wind speed and temperature were more background-dependent, and precipitation acted as an episodic nonlinear regulator. Full article

This paper aims to develop an on-board shock absorber detection method for general aviation aircraft. The effects of common gas and oleo leakage are analyzed in this paper. Based on the principle of landing gear dynamics, it is found that gas leakage and oleo leakage would mainly affect air spring force of shock absorbers in various ways. A rigid–flexible coupled landing gear multi-body system (MBS) model is developed by considering strut flexibility, aiming to offer more accurate simulated responses. A database is developed that considers common leakage faults and typical landing conditions using the developed landing gear model. A deep learning model is proposed in this paper. The proposed model is trained and tested using the database simulated from the rigid–flexible coupling landing gear model. The proposed method demonstrates robust detection performance, achieving over 95% precision for most fault types. This work provides a practical, sensor-efficient solution for real-time health monitoring of landing gear shock absorbers, contributing to improved maintenance strategies and operational safety for general aviation aircraft. As this is a preliminary feasibility study, full validation requires future drop tests or instrumented flight tests. Full article

The perinatal period is a critical window of susceptibility for fetal development and awareness for women’s health. Pregnant women are highly motivated to reduce environmental health risks, yet often lack personalized, actionable guidance on mitigating endocrine-disrupting chemicals and other household hazards. Grounded in Motivational Interviewing theory, a digital assessment was developed to empower parents to identify and reduce exposures. The tool screens for home-based and environmental risks across several domains: air quality, lead, tobacco, cleaning agents, pesticides, and plastics (BPA/phthalates). Based on user inputs, a defined algorithm generates a positive index score paired with prioritized, low-cost behavioral recommendations designed to shift users from risk awareness to active mitigation. Since its launch in Spring 2024, the tool has had over 1900 views. Preliminary analytics suggest promising engagement, and feedback more so suggests that the motivational-interview-based framing, which emphasizes empowerment over fear, facilitates immediate behavioral changes, such as switching to safer personal care products and improving indoor ventilation. Digital health interventions that translate complex environmental data into a single, manageable score can bridge the gap between clinical knowledge and household practice. This article details the score’s calculation methodology and underlying datasets, and reports usage analytics and user feedback, discussing how digital screening can scale environmental health literacy and improve maternal and child health outcomes. Full article

Based on ERA5 reanalysis data, best-track data of tropical cyclones, and satellite nighttime light data from 1995 to 2024, this study employs a statistical composite method to analyse spatiotemporal evolution characteristics and impact mechanisms of gale events in the South China Sea. The results indicate: ① The gale days exhibit a pattern of ‘high in the northeast and southwest, low in the middle’ with three high-value regions located in the Taiwan Strait, the Bashi Strait, and the offshore region southeast of Vietnam, where the average wind speed at the centres reaches 8 m/s. Maximum wind speeds show a ‘high in the north, low in the south’ pattern, with the dividing line near 10° N. The number of gale days peaks in winter, while maximum wind speeds are higher in summer and autumn than in winter and spring. ② The spatial distribution of gales is primarily influenced by the combined effects of land–sea topography and weather systems. Cold air masses in winter and spring are the dominant cause of gales in the South China Sea. Although typhoons in summer and autumn occur less frequently, they are more likely to trigger extreme gales. ③ Most regions of the South China Sea show an increasing trend in the gale days, while a few areas in the south and near Guangdong exhibit a decrease. The overall increase is primarily attributed to the intensification of the subtropical high, whereas the reduction near Guangdong is mainly due to increased surface roughness caused by urbanisation, which enhances friction and suppresses wind speeds. Full article

Urban forests (UFs) are increasingly promoted as a nature-based solution for mitigating particulate matter (PM) pollution, yet their removal performance can vary depending on surrounding emission sources and environmental conditions. Here, we quantified the particulate matter reduction efficiency (PMRE) of UFs located near roads, industrial complexes, and urban areas, together with background forests in South Korea, based on field observations during the late autumn–spring period across two consecutive years (November–May in 2021–2022 and 2022–2023). We applied vector autoregression (VAR) to examine the dynamic relationships between PMRE and meteorological and air pollutant variables across eight representative sites. The results revealed that PM mitigation dynamics were strongly particle-size-dependent and context-specific. Across all sites, ΔPM₁₀ RE was predominantly self-driven, explaining over 90% of its own variance, whereas fine-particle dynamics showed stronger interdependence. In particular, ΔPM_2.5 RE consistently acted as a key mediator, accounting for up to 70%–80% of the variation in ΔPM_1.0 RE depending on source context. Industrial-complex-adjacent UFs exhibited the strongest cross-variable interactions, while urban-core UFs were largely governed by intrinsic mitigation processes. Roadside UFs showed site-specific responses associated with CO and temperature variability. Notably, PMRE responses exhibited damped oscillation patterns across all source contexts, converging toward equilibrium over time, indicating stabilization of mitigation performance following disturbance events. These findings demonstrate that urban forest air-quality benefits are highly context dependent and governed by particle-size-specific dynamics. Our results provide evidence-based guidance for designing and managing urban forests, emphasizing the need for source-specific strategies and prioritization of PM_2.5-oriented mitigation, particularly in industrial and roadside environments where fine-particle interactions are strongest. Full article

This study develops an objective attribution framework, integrating a two-step K-means clustering procedure with a random forest algorithm, to classify the weather systems responsible for high winds over the mid- and lower reaches of the Yangtze River from 2020 to 2023. The analysis utilizes hourly automatic weather station observations, ERA5 reanalysis, and merged precipitation data. Four dominant HW types are identified: cold-air (CAHWs, 40.3%), tropical-cyclone (TCHWs, 27.9%), convective-system (CSHWs, 22.2%), and a residual “other” category (9.6%). Three main types exhibit distinct spatiotemporal distributions and environmental characteristics. CAHWs occur mainly in spring, autumn, and winter, concentrated in three sub-regions within the terrain channel or above the lake surface. CAHWs are characterized by non-precipitating northerlies associated with deformation frontogenesis and modulated by boundary layer processes, including terrain channeling and surface friction. TCHWs are confined to coastal areas in July and September, primarily controlled by tropical cyclone motion and land-sea distribution. CSHWs peak in afternoons from March to October and can be further divided into precipitating (PCSHWs, 40.3%) and non-precipitating (NPSCHWs, 59.7%) types. NPCSHWs typically occur in precipitation-free zones within 50 km of convective systems producing moderate to heavy rainfall, whereas PCSHWs form in smaller convective systems along the periphery of precipitation regions rather than within heavy-rainfall cores. PCSHWs are associated with higher instability, stronger low-level shear, and weaker inhibition than NPCSHWs, indicating a more organized convective environment. Full article

Viscous fluid dampers are widely used for mechanical vibration reduction to ensure the stability and safety of structures and systems. However, when a small amount of air (less than 10%) is mixed into the fluid, the compressibility of the fluid increases, leading to a decrease in the physical series stiffness of the damper. Consequently, under dynamic excitation, the proportion of elastic force in the total output force rises, resulting in an increase in the equivalent parallel additional stiffness—a concept often conflated with the series stiffness in the literature. This paper aims to demonstrate these two aspects of stiffness change by investigating the dynamic characteristics of air-mixed viscous fluid dampers through nonlinear modeling, finite element simulation, and experimental validation. Starting from a nonlinear series model comprising nonlinear damping and a nonlinear fluid spring (series stiffness), the energy dissipation and physical series stiffness under different air mixtures are simulated using a finite element model. To further explore the influence of air, an equivalent linear parallel model is established based on the equal energy principle, yielding an equivalent parallel additional stiffness. The results reveal that the energy dissipation effectiveness and the dynamic stiffness of viscous fluid dampers decrease as the air mixture increases. Nevertheless, the additional stiffness is increased with the air content. When the amount of air mixing is the same, the energy dissipation characteristics of the viscous fluid damper under different excitation frequencies vary. Both the damper efficiency and the additional stiffness are increased with the increase of the excitation frequency. The proposed equivalent linear model effectively captures the coupled effects of air mixture and excitation conditions on damper performance. Full article

Sustainable air quality governance requires robust monitoring and updated air quality management plans (AQMPs) to translate legislation into meaningful environmental and health protection. The Highveld Priority Area (HPA), which was declared South Africa’s second National Air Pollution Priority Area in 2007, includes the Ekurhuleni Metropolitan Municipality (EMM), where AQMPs are outdated and long-term chemical characterization data remain limited. This study provides baseline evidence to support AQMP revision by characterizing PM_2.5 mass concentrations and chemical composition in a residential area of Kempton Park within the EMM and HPA. A total of 57 24 h PM_2.5 samples were collected every sixth day from May 2021 to April 2022. Concentrations ranged from 0.9 to 32 µg/m³ (annual mean 10 µg/m³), exceeding the WHO annual guideline (5 µg/m³) but remaining below the South African standard (20 µg/m³). The daily WHO guideline (15 µg/m³) was exceeded on 13 days. PM_2.5, black carbon and organic carbon peaked during winter and spring, consistent with enhanced atmospheric stability and combustion emissions, while elements Br, Fe, K, S, Si and Sr exhibited seasonal variability. Principal component analysis and enrichment factor assessment distinguished crustal sources (Si, Ca, Fe, Ti) from enriched anthropogenic elements (S, Zn, Br, U), indicating contributions from combustion, industrial activities and mining. Correlation patterns and 72 h back-trajectory analysis further demonstrated shared sources and significant regional transport influences. These findings highlight the combined role of local emissions, meteorology and long-range transport, providing locally relevant evidence to inform sustainable air quality management within the EMM and HPA. Full article

In urban environments, large buildings influence air quality in their surroundings by altering natural wind patterns, obstructing airflow or creating high-velocity wind tunnels, often resulting in stagnant zones that trap pollutants. Furthermore, the extensive shadows cast by these structures reduce ground-level temperatures. For urban planners, accounting for these aerodynamic, thermal and air quality effects is important to fostering healthier, more livable cities. In this work, measurements assessing how shadow and micrometeorological conditions—driven by the proximity of large buildings—influence PM_2.5 levels were conducted in an urban commune of Santiago, Chile, during the winter and spring seasons. This commune is characterized by a mixture of one-story houses and high-rise buildings. PM_2.5 and meteorological parameters were measured outside three pairs of houses in winter of 2021, one of which received shadow from a nearby building and the other was under the sun. In one pair of houses, PM_2.5 concentrations were elevated in the shaded site exclusively during the winter months. This was attributed to shadow-induced temperature reductions, which likely increased local atmospheric stability and inhibited pollutant dispersion. However, this effect was limited to periods of low wind speed; during the spring, the transition to a higher wind speed regime facilitated sufficient mechanical mixing to neutralize the thermal influence of the shadow, resulting in no detectable difference between the sites. In another pair of houses, the result was attributed to the difference in wind speed in one of the houses, because the building acts as a windbreak, no shading effect were observed. Regarding the third pair of houses, no significant impact on PM_2.5 concentrations was observed in the whole period. This lack of variation is likely attributable to the absence of substantial micrometeorological differences between the two sites. Full article