Search Results (5,826)

The Earth system model ICON (ICOsahedral Nonhydrostatic general circulation) is a flexible framework that can be configured and tuned for various applications such as weather forecasting, simulations of aerosols and trace gases, and climate modelling. The numerical weather prediction component ICON is used in limited area mode (ICON-LAM) in Romania to obtain realistic weather simulations that support operational forecasting activities. The sensitivity of ICON-LAM is preliminarily evaluated for the geographical area of Romania. Numerical simulations using two parameterization schemes for radiation processes, two convection settings and different values for the laminar resistance of heat transfer from the surface to the air are evaluated against a control run employed for operational forecasts at the National Meteorological Administration. The validation is performed focusing on the precipitation field and surface continuous parameters. All configurations were integrated for a short period in summer when forecasted precipitation was strongly overestimated. Further on, selected configurations were evaluated for winter cases. The experiment with the shallow convection only, the ecRad radiation parameterization, and the laminar heat value 10 emerged as the best fit for Romania. This configuration (considered optimal) was evaluated alongside the operational control run for August 2022. Overall results indicate the selected optimal configuration generally outperforms the control run both with regard to precipitation and in forecasting surface parameters. This experiment has been adapted and implemented in operational workflow. Full article

Extracellular vesicles (EVs) are lipid-enclosed particles secreted from a wide variety of cells, with the ability to transfer biologically active content from parent to recipient cells. Lung epithelial-derived EVs (LE-EVs) play an important role in the progression of pulmonary disease, but there is limited evidence regarding the impact of cigarette smoke (CS) and electronic cigarette aerosol (ECA) on epithelial-derived EVs. The aim of this systematic review was to evaluate the current published literature on the impact of cigarette smoke and electronic cigarette aerosol on LE-EVs. Original research studies and clinical data were included, but research involving microparticles or non-epithelial-derived EVs was excluded. A total of 29 articles were identified from three databases (EMBASE, Web of Science and PubMed), of which nine demonstrated that CS exposure leads to molecular changes in epithelial-derived EVs, whereas 21 reported that CS-induced LE-EVs can deliver their cargo to neighbouring cells. The results highlighted that LE-EVs secreted in response to cigarette or e-cigarette exposure presented altered EV cargo, associated with increased cellular damage, inflammation and disease development. The current literature suggests that conventional and electronic cigarettes can influence the secretion of EVs from lung epithelial cells, with these EVs potentially playing a role in the development of lung inflammation. Nonetheless, there is limited research studying the impact of ECA on LE-EVS. Further research examining the impact of electronic cigarettes on lung epithelial-derived EVs, using robust human in vitro models coupled with clinical studies, is required. Full article

Accurate and interpretable air quality prediction remains a critical challenge for environmental health management due to complex, nonlinear interactions among emissions, meteorology, and atmospheric chemistry. This study presents a hybrid physics informed and multimodal deep learning framework for city-scale air quality and health risk prediction. The framework combines a Gaussian plume dispersion model with a residual CNN-LSTM network that learns data driven corrections while preserving physical consistency. Multimodal open datasets, including ground based pollutant sensors, meteorological records, and satellite derived aerosol and temperature features, are jointly fused to improve spatiotemporal fidelity. An Exposure Health Index module further links predicted pollutant fields with respiratory morbidity indicators, providing a quantitative bridge between atmospheric variability and health outcomes. Using open source datasets from Riyadh, Jeddah, and Dammam, the proposed approach achieves up to 25% lower mean absolute error and $R^2$ values above 0.85 compared with physics only and purely data driven baselines. Explainability analyses using SHAP and spatial attention highlight physically plausible drivers and confirm feature relevance. The results demonstrate that physics guided residual learning can unify deterministic dispersion modeling and multimodal inference, providing a transparent, scalable, and reproducible foundation for air quality forecasting and health risk assessment. Full article

This study employed Moderate-Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth data meteorological data, Digital Elevation Model (DEM), Normalized Difference Vegetation Index (NDVI), and ground monitoring data for particulate matter (PM2.5) to construct a model for estimating the PM2.5 concentration in Yangquan City, Shanxi Province, from 2015 to 2024. The spatial and temporal changes in the PM2.5 concentration were analyzed. The results revealed the following: (1) The random forest model was more accurate than the multiple linear regression model. The spring model R² increased by 38.7%, and the Root Mean Square Error (RMSE) decreased by 92.6%. The summer model R² increased by 65.1%, and the RMSE decreased by 92.5%. The autumn model R² increased by 2.7%, and the RMSE decreased by 83.4%. The winter model R² increased by 25.4%, and the RMSE decreased by 95.5%. (2) The PM2.5 concentration in Yangquan City showed an upward trend from 2015 to 2017, and then a downward trend from 2018 to 2024, with an average decrease of 18.3 μg/m³. The highest concentration of PM2.5 was 55–85 μg/m³ in winter, and the lowest concentration of PM2.5 was 25–40 μg/m³ in summer. In terms of spatial distribution, the PM2.5 concentration in Yangquan City exhibits a pattern of being lower in the northwest and higher in the southeast. The high values are primarily concentrated in the central urban areas and major industrial zones in the southeast. Full article

Bacilus cereus and Pseudomonas fluorescens are major foodborne psychrotrophic bacteria posing global health and economic risks. B. cereus has a 23.8% food prevalence worldwide. P. fluorescens is a leading cause of spoilage in refrigerated products. Their rapid detection is crucial for food safety. However, existing detection methods often rely on open-tube operations, risking aerosol contamination. In this study, we developed two independent one-tube RPA-CRISPR/Cas12a visual detection assays for B. cereus and P. fluorescens. Using a physical separation design, the recombinase polymerase amplification (RPA) and CRISPR/Cas12a detection were pre-assembled in a single reaction tube. After incubation, a brief centrifugation combined the components for enclosed detection. This step is compatible with portable mini-centrifuges. The assays can be completed within 40 min at 37 °C, with results visualized directly under blue light. Both assays demonstrated good specificity against six common non-target pathogens. The visual detection limits were 5.1 × 10¹ copies/μL for B. cereus and 2.1 × 10¹ copies/μL for P. fluorescens. Each assay was applied to 14 types of real-world food samples (naturally contaminated and uncontaminated, confirmed by PCR), achieving 100% concordance with conventional PCR. The one-tube assays are tailored for psychrotrophic bacteria in refrigerated foods. They minimize aerosol contamination risk and provide a reliable solution for on-site cold-chain food safety monitoring. Full article

Background: The increasing use of electronic cigarettes (ECIGs), especially among youth, has raised concerns about the impact of vaping on oral health. While ECIGs are often marketed as a safer alternative, the existing literature suggests that their use may have detrimental effects on the pulmonary and cardiovascular systems. The oral cavity is the first point of contact for ECIG aerosol, and new reports link vaping to the onset of periodontal disease. It is critical to understand the potential effects of vaping on the oral microbiome, which affects systemic health. This study investigates how flavored E-liquids and commensal bacteria influence the growth of Porphyromonas gingivalis, a periodontal pathobiont, under planktonic and biofilm conditions. Methods: P. gingivalis was grown planktonically in the presence of the supernatants of four streptococcal species (Streptococcus gordonii, Streptococcus intermedius, Streptococcus mitis, and Streptococcus oralis) and flavored E-liquids (tobacco, menthol, cinnamon, strawberry, and blueberry) under anaerobic conditions. Multispecies biofilms, including all the species mentioned above and Fusobacterium nucleatum, were also grown anaerobically and quantified by crystal violet assays, qPCR, and CFU counts. Results: Although E-liquids inhibit P. gingivalis growth under planktonic conditions, the presence of commensal supernatants partially mitigates this effect. However, P. gingivalis growth in multispecies biofilms is increased by E-liquid treatments. Conclusions: This study highlights the enhanced growth of P. gingivalis as part of an oral microbial community in the presence of E-liquids. These results suggest that E-liquid-induced alterations in multispecies biofilms may contribute to the observed dysbiosis in vapers and the associated risk of oral diseases. Full article

The growing popularity of electronic cigarettes (e-cigarettes) necessitates a better understanding of their biological effects. In this study, we aimed to evaluate the effects of e-cigarette aerosol condensates generated from either e-cigarette carrier liquid alone or with e-cigarette liquid with nicotine and flavor on bronchial epithelial cells. BEAS-2B cells were exposed to e-cigarettes for 24 h, and transcriptional and proteomic profiling, including assessment of protein modifications, was performed. Additionally, cell-based assays were used to evaluate mitochondrial function, rate of protein synthesis, lysosomal signal, lipid droplet quantity and actin formation. Our findings reveal that short-term exposure to both types of aerosol condensates altered transcriptome and proteome profiles, disrupting cellular homeostasis in BEAS-2B cells through impaired proteostasis and mitochondrial function in response to both types of condensates. Changes in lipid and lysosome content, as well as a reduction in polymerized actin, were observed with nicotine- and flavor-containing condensate. E-cigarette exposure also induced irreversible protein modifications, including different chemical derivatives (25 out of 49 in nicotine/flavor condensate; 20 out of 48 in nicotine/flavor-free condensate; 4 out of 35 in control), suggesting their particularly harmful effect. Together, these findings point to early-onset cellular stress and impaired lung epithelial fitness caused by acute e-cigarette exposure. Full article

Atmospheric aerosols modulate Earth’s radiation balance through direct effects and through their role as cloud condensation nuclei (CCN), contributing to variability in near-surface temperature (NST). Galactic cosmic rays (GCRs) further influence aerosol–cloud interactions by enhancing particle formation and growth, but combined aerosol optical depth (AOD)–GCR effects on NST remain poorly constrained across climates. Using satellite and reanalysis data, we examine joint influences on NST anomalies at three neutron-monitoring stations, Oulu, Newark, and Hermanus, during 2000–2022. The sites share similar geomagnetic cutoffs but contrasting climates, enabling separation of ionization from geomagnetic shielding. Multiple linear regression (MLR) captures AOD effects and their modulation by GCR flux. Adding an interaction term (AOD × GCR) improves fit, raising adjusted R² from 0.22→0.31 (Oulu), 0.37→0.52 (Newark), and 0.69→0.78 (Hermanus). ECMWF reanalysis shows hydrophilic organic matter aerosol (OMA) dominates (0.19, 0.29, 0.41 µg kg⁻¹ at Oulu, Newark and Hermanus), with sulphate elevated at Oulu/Newark and coarse sea salt at Hermanus. Elevated OMA and sulphate at Oulu/Newark imply GCR-enhanced fine CCN and cooling, whereas humid, sea-salt-rich Hermanus favors ion-mediated growth of larger hygroscopic particles that increase longwave trapping and warming. Findings provide site-specific evidence that GCR ionization modulates aerosol processes and contributes to regional NST variability, informing improved parameterizations in climate models. Full article

This paper describes a new methodology implemented in the ESTE decision support system for evaluating the source term resulting from a nuclear weapon detonation. The methodology is based on a model of a stabilized radioactive mushroom cloud, parameterized as the source term for a Lagrangian particle dispersion model. It includes radionuclide composition, spatial distribution of aerosol and gaseous particles, and particle size distribution. This method is designed for rapid assessment of radiological impacts primarily at medium- and long-range distances, for example, in neighboring countries. The parametrization has been calibrated and adjusted using data from historical nuclear tests, and its performance is evaluated in terms of impacted area, range, and spatial overlap of fallout regions. A comparison is presented between ESTE calculations and field measurements obtained after the British nuclear tests conducted in the 1950s at the Maralinga Range (Australia), using historical ERA5 meteorological reanalyses from ECMWF. Full article

Results of a methodological case study of low-level clouds in the atmosphere using a 1064 nm fiber lidar are presented. The lidar experiment was carried out in Daejeon, Republic of Korea, in January–March 2025. The study’s primary objective was to ascertain the vertical extinction coefficient profiles pertaining to tenuous, low-altitude cloud formations via implementation of a refined Sequential Lidar Signal Processing Algorithm (SLSPA). The SLSPA incorporates statistical estimation theory to assess signal and measurement error. Cloud extinction coefficient profiles are estimated within the SLSPA utilizing the modified Klett–Fernald inversion algorithm. The SLSPA adaptation is required (a) to evaluate the accuracy of Q-switch laser-based lidar sounding signal deconvolution, (b) to mitigate the impact of the lidar form factor on measurement results, (c) to account for aerosol extinction coefficient variability within the cloud in the modified inversion algorithm (MIA), and (d) to evaluate multiple scattering effect correction in the MIA. Theoretical and experimental aspects of the modified SLSPA are considered sequentially in the present work. The experimental results presented here are based on datasets sampled from the entire array of experimental data obtained during the measurement period. Full article

Urban air quality is influenced by the removal of particulate matter through dry deposition, yet this process is often simplified in models, potentially underestimating the role of vertical building surfaces. This study investigates the impact of aerosol deposition on building walls on PM_2.5 concentrations and the deposition budget within the urban canopy. We utilized a Large Eddy Simulation model coupled with a Lagrangian Particle Transport module to simulate aerosol dispersion in randomized urban configurations corresponding to Local Climate Zones (LCZs) 4, 5, and 6. The results indicate that under the considered conditions, vertical walls can act as a primary sink for PM_2.5, capturing over 70% of deposited particles downwind from sources in high-rise environments. We observed a non-linear sensitivity of airborne concentrations to wall deposition efficiency; a relatively low capture probability (10%) reduced near-surface concentrations by 25–30%. Furthermore, for fine and coarse particles (up to ~20 µm), the uncertainty in wall deposition parameterization appeared to outweigh the influence of particle physical properties on dispersion patterns. These findings suggest that neglecting wall deposition may lead to overestimation of urban pollution levels, highlighting the importance of refining particle–wall interaction parameterizations in air quality models. Full article

Tropical cyclones kill thousands and inflict vast destruction annually. While ocean temperatures and atmospheric conditions dominate their formation and behaviour, forests’ potential influence has received little systematic attention. This review examines whether and how forests may affect tropical cyclone frequency, intensity, and behaviour. Support varies by mechanism and stage. Post-landfall effects have the strongest support: forests slow storms, moderate wind speeds and curb flooding through enhanced soil infiltration. Forests also influence storm tracks, though magnitudes are uncertain. Pre-landfall effects are less certain. These include processes that modify offshore humidity, temperature, and aerosols. The Biotic Pump theory proposes that forest cover creates pressure gradients drawing moisture inland, reducing its availability for ocean storms. Forest influences are likely to be most evident near thresholds for storm formation or intensification, where small perturbations in conditions can alter outcomes. This context-dependency reconciles divergent findings and aids the integration of forests into climate risk assessments. Forest conservation provides clear post-landfall protection; pre-landfall effects, while uncertain, further strengthen the case for protection and highlight research priorities. Full article

Electronic cigarette (ECIG) liquids are marketed with labeled nicotine concentrations and propylene glycol (PG) to vegetable glycerin (VG) ratios, yet quality control inconsistencies may alter vaping emissions. We quantified discrepancies between labeled and measured chemical content and evaluated how these differences affect emissions of particulate matter with an aerodynamic diameter of 2.5 µm or smaller (PM_2.5). Flavor-free liquids (n = 20) spanning nicotine labels of 0, 9, 18, and 48 mg/mL and PG content from 0% to 80% were purchased. Nuclear magnetic resonance spectroscopy measured nicotine, PG, and VG. Aerosols were generated using a standardized device in a controlled exposure chamber. PM_2.5 was measured using a pDR-1500 and SMPS/APS, with gravimetric correction factors calculated. Labeling inaccuracies were widespread: “nicotine-free” liquids contained 0.1 to 0.4 mg/mL nicotine, and labeled nicotine deviated by up to ±30%. PG/VG ratios were frequently incorrect; 70% of samples contained higher VG than labeled, including “100% VG” products with about 10% PG. Higher VG consistently increased PM_2.5 mass, while nicotine had a minimal effect. The pDR overestimated mass, whereas SMPS/APS underestimated due to volatilization losses. Overall, inaccurate ECIG liquid labeling can alter measured PM_2.5 emissions under controlled conditions. Full article

Titanium dioxide nanoparticles (TiO₂ NPs) are incorporated into automotive coatings to enhance durability, corrosion, UV resistance, and, in some formulations, photocatalytic self-cleaning. While the toxicology of pristine TiO₂ is well studied, the behavior of TiO₂ NPs embedded in polymer matrices and subjected to real-world aging, maintenance, and removal remains poorly characterized. This narrative review synthesizes 24 publications spanning the lifecycle of TiO₂ nano-enabled automotive coatings, from synthesis and formulation through application, in-service weathering, repair, refinishing, and end-of-life environmental fate. Upstream properties, such as coating functionality and performance, have been examined as determinants of later-life release, exposure, and fate. Across studies, dispersion state, interfacial compatibility, and surface modification—together with transformations such as agglomeration, photocatalysis, weathering, and eco-corona formation—shape particle stability, release, exposure relevance, and toxicological risk. Evidence indicates that sanding and accelerated weathering predominantly generate matrix-associated, polymer-fragment-dominated aerosols rather than pristine TiO₂ NPs, while NP-specific exposure measurements during spray application remain limited. Hazard data suggest matrix embedding may attenuate, but does not eliminate, biological responses relative to pure particles. Wastewater treatment plants and biosolids have been shown to act as sinks with potential for soil accumulation following sludge application. Regulatory frameworks rarely account for aging, transformation, and release, stressing the need for synchronized testing of aged materials and nano-specific exposure metrics to support safer-by-design coatings and risk governance. Full article

Conventional deposition techniques hinder the integration of high-performance lead-free piezoelectric thick films on silicon substrates due to slow growth kinetics and complex processing. Herein, dense, crack–free Ba(Zr_xTi_1−x)O₃ (BZT, x = 0–0.10) thick films (~2 μm) were fabricated via aerosol deposition (AD) followed by annealing, forming a nanocrystalline microstructure with an average grain size of ~78 nm. Compositional tuning showed optimal electromechanical performance at x = 0.03, attributed to the coexistence of tetragonal and orthorhombic phases near room temperature that reduce the phase transformation energy barrier. The optimized BZT films exhibit excellent electrical properties: saturation polarization of 31.3 μC/cm², relative permittivity of 430, dielectric tunability figure of merit (FOM) of 155, and a large transverse piezoelectric coefficient |e_31, f| of 1.01 C/m²—comparable to textured magnetron–sputtered BaTiO₃ films but with higher deposition efficiency. This work provides a high-throughput route for fabricating piezoelectric thick films, highlighting the potential of compositionally engineered AD–processed BZT in lead-free MEMS applications. Full article