Found 2670 publications. Showing page 1 of 267:
Tire particles can enter the marine environment e.g. through direct discharge of road runoff, sewage systems or riverine inputs. Their fate in marine waters remains largely unknown, though the deep sea could be a final sink as for other marine litter. To simulate these conditions, we investigated in laboratory-controlled conditions the effects of high-hydrostatic pressure [20 MPa] vs atmospheric pressure [0.1 MPa] on the leaching of 17 organic compounds from cryo-milled tire tread particles (μm sized) and crumb rubber particles (mm sized) into natural seawater. We monitored the abundance of heterotrophic prokaryotes in the leachates over the 14 day exposure period under biotic conditions. Abiotic controls were employed to delineate the influence of prokaryotes on the fate of leached chemicals. Our results showed leaching of dissolved organic carbon and target chemicals under all experimental conditions, with higher concentrations of certain target chemicals under high-hydrostatic pressure conditions (e.g., 1,3-diphenylguanidine [DPG]: max. 703 (20 MPa) vs 119 μg/L (0.1 MPa) from cryo-milled tire tread particles under biotic conditions). Under abiotic conditions leaching was weaker for DPG and other chemicals, with contrasting trends for chemicals prone to biotransformation. In crumb rubber leachates chemical concentrations increased with time, but showed no significant differences between biotic/abiotic or high-hydrostatic/atmospheric pressure conditions. Prokaryotic abundance increased in all samples containing tire particles compared to seawater controls, indicating the use of the rubber and/or leached chemicals as an energy source.
2025
Divergent impacts of climate interventions on China’s north-south water divide
Abstract Solar radiation modification-based climate interventions may cause uneven regional hydrological changes while mitigating warming. Here, we investigate the effects of climate interventions on China’s North Drought-South Flood pattern using the Norwegian Earth System Model supplemented by volcanic data. Our results indicate that equatorial stratospheric aerosol injection could mitigate the north-south water divide by reducing inter-hemispheric and equator-to-North-pole temperature gradients, thereby modifying atmospheric circulation and the East Asian monsoon to increase precipitation and surface runoff in northern China while reducing them in the south, compared to the high emissions scenario. This mechanism is supported by observed precipitation changes following the Mount Pinatubo volcanic eruption. In contrast, marine cloud brightening may intensify southern flood risks, while cirrus cloud thinning and moderate emissions reduction might exacerbate northern droughts. Our findings reveal distinct regional hydroclimatic impacts of different climate interventions, highlighting potential synergies and trade-offs between their global intervention efficacy and regional water security.
2025
Analysis of source regions and transport pathways of sub-micron aerosol components in Europe
It is important to study aerosols and their origins, as they pose various negative health and environmental impacts. In this study, we combined year-long datasets from 15 different countries with Trajectory Statistical Methods (TSMs) for the first time at this comprehensive scale. We found possible source regions and seasonal variations of various particulate matter (PM) components in Europe, including total organic aerosol (OA), biomass burning OA (BBOA), oxygenated OA (OOA), ammonium (NH4), nitrate (NO3), and sulphate (SO4). We found that for all of the studied components, Eastern Europe was among the highest contributors. For NO3, other important source regions were Northern France and the Benelux, while for SO4 there were significant contributions from the Mediterranean region. We also compared our measurement-based model with simulated concentrations of an atmospheric chemistry transport model (CAMx). We observed a satisfactory agreement in regions where we had sufficient coverage with air pollution monitoring stations. The main deviations for OA were found around the Po Valley, where CAMx consistently estimated higher concentrations, while the TSM analysis did not highlight it as a hotspot because long-term monitoring datasets in this region are lacking. CAMx also underestimated the concentrations around Poland, mainly from residential burning. Our results provide opportunities to refine European emission inventories and deliver valuable information on long-range transported air pollutants. This work suggests that policies mitigating air pollution in Eastern Europe and the Benelux could help improve overall air quality in entire Europe more efficiently.
2025
Towards a remote-sensing-driven model of isoprene emissions from Alpine tundra
Abstract This study investigates isoprene emissions in a high-latitude Alpine tundra ecosystem, focusing on using near-field remote sensing of surface temperatures, the photochemical reflectance index (PRI) and normalized difference vegetation index (NDVI), and meteorological measurements to model these emissions. Isoprene is a key biogenic volatile organic compound (BVOC) emitted by select plants, which can impact atmospheric chemistry and climate. Increased temperatures, particularly in high latitudes, may enhance isoprene emissions due to extended growing seasons and heightened plant stress. The research was conducted in Finse, Norway, where isoprene and CO 2 fluxes were measured with eddy covariance alongside spectral and meteorological data, and surface temperature. A random forest (RF) model was developed to predict isoprene fluxes, considering the variable importance of different environmental factors. The results showed that surface temperature and CO 2 flux were consistently important predictors, across three differential temporal data aggregations (hourly, daily, weekly), while the PRI demonstrated low predictive power, possibly due to the heterogeneous vegetation and variable light conditions. The NDVI was more effective than anticipated, likely linked to phenological changes in vegetation. Model performance varied with temporal resolution, with weekly data achieving the highest predictive accuracy ( R 2 up to 0.76). The RF model accurately reflected seasonal emission patterns but underestimated short-term peaks, suggesting the potential to combine machine learning with process-based modelling. This research highlights the promise of proxy data from remote sensing for scaling BVOC emission models to regional levels, essential for understanding climate impacts in Arctic ecosystems.
2025
Abstract Low-cost air quality sensors (LCS) are increasingly used to complement traditional air quality monitoring yet concerns about their accuracy and fitness-for-purpose persist. This scoping review investigates topics, methods, and technologies in the application of LCS networks in recent years that are gaining momentum, focusing on LCS networks (LCSN) operation, drone-based and mobile monitoring, data fusion/assimilation, and community engagement. We identify several key challenges remaining. A major limitation is the absence of unified performance metrics and cross-validation methods to compare different LCSN calibration and imputation techniques and meta-analyses. LCSN still face challenges in effectively sharing and interpreting data due to a lack of common protocols and standardized definitions, which can hinder collaboration and data integration across different systems. In mobile monitoring, LCS siting, orientation, and platform speed are challenges to data consistency of different LCS types and limit the transferability of static calibration models to mobile settings. For drone-based monitoring, rotor downwash, LCS placement, flight pattern, and environmental variability complicate accurate measurements. In integrating LCS data with air quality models or data assimilation, realistic uncertainty quantification, ideally at the individual measurement level, remains a major obstacle. Finally, citizen science initiatives often encounter motivational, technological, economic, societal, and regulatory barriers that hinder their scalability and long-term impact.
2025
The winter of 2023/24 exhibited remarkable stratospheric dynamics with multiple sudden stratospheric warmings (SSWs). Based on the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA5) polar-cap-averaged 10 hPa zonal wind, three major SSWs are identified. Two of the three SSWs were short-lived, lasting under 7 d. In this study, we give an overview of the three SSWs that occurred in the winter of 2023/24 and focus on the impact of tropospheric forcing on their duration. Blocking high-pressure systems are shown to modulate wave activity flux into the stratosphere through interactions with tropospheric planetary waves, depending on their location. The rapid termination of the first SSW (14–19 January 2024) is linked to a developing high-pressure system over the North Pacific. The second SSW (16–22 February 2024) terminated quickly due to more contributing factors, one of which was a high-pressure system that developed over the Far East. The third SSW (3–28 March 2024) was a long-duration canonical event extending to levels below 100 hPa. In contrast to the two short-lived SSWs in the winter of 2023/24, tropospheric forcing was sustained around the SSW onset in March 2024, allowing a long event to develop. We also note that conditions for these SSWs were particularly favorable due to external factors, including an easterly Quasi-Biennial Oscillation (QBO), the presence of El Niño conditions of the El Niño–Southern Oscillation (ENSO) cycle, and the proximity to the solar maximum.
2025
2025
Sex and Gender Dimensions in Hazard and Risk Assessment of Engineered Nanomaterials
The knowledge on hazards and risks connected to human exposure to engineered nanomaterials (ENMs) is still very limited, despite several decades of research and regulatory efforts at the international level. In particular, sex/gender‐related responses to such exposure have not been clearly articulated so far in any of the existing guidance documents or regulatory relevant opinions provided to the parties involved in the risk assessment and risk management of ENMs. We aimed to demonstrate the relevance of the sex/gender dimension for the characterization of the risks and hazards associated with ENMs by analyzing existing scientific data on sex‐related differences in response to ENMs exposure. This was achieved by performing an extensive review of in vivo mammalian toxicity studies published in PubMed and Web of Science databases. Further analysis was performed only for data reported in publications that satisfied scientific quality criteria assessed using the GUIDEnano approach. Finally, we demonstrated the importance of the sex/gender dimension for safety testing of ENMs in the future and provided recommendations on how to include the sex/gender dimension in toxicity testing of ENMs to ensure precise, transparent, and reliable conclusions in the process of hazard and risk assessments. This article is categorized under: Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials Toxicology and Regulatory Issues in Nanomedicine > Regulatory and Policy Issues in Nanomedicine
2025
2025
Abstract This study introduces a community-focused eCoach recommendation system aimed at enhancing physical activity by leveraging demographic data, wearable sensor inputs, and machine learning algorithms to generate both individual and community-based activity recommendations using advice-based collaborative filtering. Existing eCoaching systems largely focus on personalized feedback without incorporating social reinforcement or group-level motivation, creating a gap in leveraging community influence for sustained health behaviors. Our system combines real-time activity tracking through wearable sensors and advice-based collaborative filtering to deliver adaptive recommendations. We collected data from 31 participants (16 using MOX2-5 sensors and 15 from a public Fitbit-based dataset), targeting daily activity levels to generate actionable guidance. Through decision tree classification and SHAP-based interpretability, we achieved a model accuracy of 99.8%, with F1, precision, recall, and MCC metrics confirming robustness across both balanced and imbalanced datasets. Ethical considerations, including privacy, bias mitigation, and informed consent, were integral to our design and implementation. Limitations include potential biases due to sample size and data imbalances, suggesting the need for future validation on independent datasets. This system demonstrates the potential to integrate with real-world healthcare initiatives, offering trust, transparency, and user engagement opportunities to meet public health objectives.
2025