Found 9746 publications. Showing page 387 of 390:
2024
2024
Roadmap for action for advancing aggregate exposure to chemicals in the EU
The European Food Safety Authority (EFSA) has a goal to efficiently conduct aggregate exposure assessments (AEAs) for chemicals using both exposure models and human biomonitoring (HBM) data by 2030. To achieve EFSA's vision, a roadmap for action for advancing aggregate exposure (AE) in the EU was developed. This roadmap was created by performing a series of engagement and data collection activities to map the currently available methods, data, and tools for assessing AE of chemicals, against the needs and priorities of EFSA. This allowed for the creation of a AEA framework, identification of data and knowledge gaps in our current capabilities, and identification of the challenges and blockers that would hinder efforts to fill the gaps. The roadmap identifies interdependent working areas (WAs) where additional research and development are required to achieve EFSA's goal. It also proposes future collaboration opportunities and recommends several project proposals to meet EFSA's goals. Eight proposal projects supported by SWOT analysis are presented for EFSA's consideration. The project proposals inform high-level recommendations for multi-annual and multi-partner projects. Recommendations to improve stakeholder engagement and communication of EFSA's work on AEA were gathered by surveying stakeholders on specific actions to improve EFSA's communication on AE, including webinars, virtual training, social media channels, and newsletters.
2024
Surface warming in Svalbard may have led to increases in highly active ice-nucleating particles
The roles of Arctic aerosols as ice-nucleating particles remain poorly understood, even though their effects on cloud microphysics are crucial for assessing the climate sensitivity of Arctic mixed-phase clouds and predicting their response to Arctic warming. Here we present a full-year record of ice-nucleating particle concentrations over Svalbard, where surface warming has been anomalously faster than the Arctic average. While the variation of ice-nucleating particles active at around −30 °C was relatively small, those active at higher temperatures (i.e., highly active ice-nucleating particles) tended to increase exponentially with rising surface air temperatures when the surface air temperatures rose above 0 °C and snow/ice-free barren and vegetated areas appeared in Svalbard. The aerosol population relevant to their increase was largely characterized by dust and biological organic materials that likely originated from local/regional terrestrial sources. Our results suggest that highly active ice-nucleating particles could be actively released from Arctic natural sources in response to surface warming.
Springer Nature
2024
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Numerical methods and simulation codes are essential for the advancement of our understanding of complex atmospheric processes. As technology and computer hardware continue to evolve, the development of sophisticated code is vital for accurate and efficient simulations. In this paper, we present the recent advancements made in the FLEXible PARTicle dispersion model (FLEXPART), a Lagrangian particle dispersion model, which has been used in a wide range of atmospheric transport studies over the past 3 decades, extending from tracing radionuclides from the Fukushima nuclear disaster, to inverse modelling of greenhouse gases, and to the study of atmospheric moisture cycles.
This version of FLEXPART includes notable improvements in accuracy and computational efficiency. (1) By leveraging the native vertical coordinates of European Centre for Medium Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) instead of interpolating to terrain-following coordinates, we achieved an improvement in trajectory accuracy, leading to a ∼8 %–10 % reduction in conservation errors for quasi-conservative quantities like potential vorticity. (2) The shape of aerosol particles is now accounted for in the gravitational settling and dry-deposition calculation, increasing the simulation accuracy for non-spherical aerosol particles such as microplastic fibres. (3) Wet deposition has been improved by the introduction of a new below-cloud scheme, by a new cloud identification scheme, and by improving the interpolation of precipitation. (4) Functionality from a separate version of FLEXPART, the FLEXPART CTM (chemical transport model), is implemented, which includes linear chemical reactions. Additionally, the incorporation of Open Multi-Processing parallelisation makes the model better suited for handling large input data. Furthermore, we introduced novel methods for the input and output of particle properties and distributions. Users now have the option to run FLEXPART with more flexible particle input data, providing greater adaptability for specific research scenarios (e.g. effective backward simulations corresponding to satellite retrievals). Finally, a new user manual (https://flexpart.img.univie.ac.at/docs/, last access: 11 September 2024) and restructuring of the source code into modules will serve as a basis for further development.
2024
2024
2024
2024
2024
Aerosol hygroscopicity influenced by seasonal chemical composition variations in the Arctic region
In this study, we quantified aerosol hygroscopicity parameter using aerosol microphysical observation data (κphy), analyzing monthly and seasonal trends in κphy by correlating it with aerosol chemical composition over 6 years from April 2007 to March 2013 at the Zeppelin Observatory in Svalbard, Arctic region. The monthly mean κphy value exhibited distinct seasonal variations, remaining high from winter to spring, reaching its minimum in summer, followed by an increase in fall, and maintaining elevated levels in winter. To verify the reliability of κphy, we employed the hygroscopicity parameter calculated from chemical composition data (κchem). The chemical composition and PM2.5 mass concentration required to calculate κchem was obtained through Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis data and the calculation of κchem assumed that Arctic aerosols comprise only five species: black carbon (BC), organic matter (OM), ammonium sulfate (AS), sea salt aerosol less than a diameter of 2.5 μm (SSA2.5), and dust aerosol less than a diameter of 2.5 μm (Dust2.5). The κchem had no distinct correlation but had a similar seasonal trend compared to κphy. The κchem value followed a trend of SSA2.5 and was much higher by a factor of 1.6 ± 0.3 than κphy on average, due to a large proportion of SSA2.5 mass concentration in MERRA-2 reanalysis data. This may be due to the overestimation of sea salt aerosols in MERRA-2 reanalysis. The relationship between monthly mean κphy and the chemical composition used to calculate κchem was also analyzed. The elevated κphy from October to February resulted from the dominant influence of SSA2.5, while the maximum κphy in March was concurrently influenced by increasing AS and Dust2.5 associated with long-range transport from mid-latitude regions during Arctic haze periods and by SSA mass concentration obtained from in-situ sampling, which remained high from the preceding winter. The relatively low κphy from April to September can be attributed to low SSA2.5 and the dominance of organic compounds in the Arctic summer. Either natural sources such as those of marine and terrestrial biogenic origin or long-range-transported aerosols may contribute to the increase in organic aerosols in summer, potentially influencing the reduction in κphy of atmospheric aerosols. To our knowledge, this is the first study to analyze the monthly and seasonal variation of aerosol hygroscopicity calculated using long-term microphysical data, and this result provides evidence that changes in monthly and seasonal hygroscopicity variation occur depending on chemical composition.
Elsevier
2025
2025
We have used the NASA Goddard Institute for Space Studies (GISS) Earth system model GISS-E2.1 to study the future budgets and trends of global and regional CH4 under different emission scenarios, using both the prescribed GHG concentrations as well as the interactive CH4 sources and sinks setup of the model, to quantify the model performance and its sensitivity to CH4 sources and sinks. We have used the Current Legislation (CLE) and the maximum feasible reduction (MFR) emission scenarios from the ECLIPSE V6b emission database to simulate the future evolution of CH4 sources, sinks, and levels from 2015 to 2050. Results show that the prescribed GHG version underestimates the observed surface CH4 concentrations during the period between 1995 and 2023 by 1%, with the largest underestimations over the continental emission regions, while the interactive simulation underestimates the observations by 2%, with the biases largest over oceans and smaller over the continents. For the future, the MFR scenario simulates lower global surface CH4 concentrations and burdens compared to the CLE scenario, however in both cases, global surface CH4 and burden continue to increase through 2050 compared to present day. In addition, the interactive simulation calculates slightly larger O3 and OH mixing ratios, in particular over the northern hemisphere, leading to slightly decreased CH4 lifetime in the present day. The CH4 forcing is projected to increase in both scenarios, in particular in the CLE scenario, from 0.53 W m−2 in the present day to 0.73 W m−2 in 2050. In addition, the interactive simulations estimate slightly higher tropospheric O3 forcing compared to prescribed simulations, due to slightly higher O3 mixing ratios simulated by the interactive models. While in the CLE, tropospheric O3 forcing continues to increase, the MFR scenario leads to a decrease in tropospheric O3 forcing, leading to a climate benefit. Our results highlight that in the interactive models, the response of concentrations are not necessarily linear with the changes in emissions as the chemistry is non-linear, and dependent on the oxidative capacity of the atmosphere. Therefore, it is important to have the CH4 sources and chemical sinks to be represented comprehensively in climate models.
IOP Publishing
2025
Using a citizen science approach to assess nanoplastics pollution in remote high-altitude glaciers
Nature Portfolio
2025
Per- and polyfluoroalkyl substances (PFAS) have gained significant global attention due to their extensive industrial use and harmful effects on various organisms. Among these, perfluoroalkyl acids (PFAAs) are well-studied, but their diverse precursors remain challenging to monitor. The Total Oxidizable Precursor (TOP) assay offers a powerful approach to converting these precursors into detectable PFAAs. In this study, the TOP assay was applied to samples from the East Asian-Australian Flyway, a critical migratory route for millions of shorebirds. Samples included shellfish from China's coastal mudflats, key stopover sites for these birds, and blood and liver samples from shorebirds overwintering in Australia. The results showed a substantial increase in perfluorocarboxylic acids (PFCAs) across all sample types following the TOP assay, with the most significant increases in shorebird livers (Sum PFCAs increased by 18,156 %). Intriguingly, the assay also revealed unexpected increases in perfluorosulfonic acids (PFSAs), suggesting the presence of unidentified precursors. These findings highlight the need for further research into these unknown precursors, their sources, and their ecological impacts on shorebirds, other wildlife, and potential human exposure. This study also provides crucial insights into the TOP assay’s strengths and limitations in studying PFAS precursor dynamics in biological matrices.
Elsevier
2025
Recommendation technologies are widespread in streaming services, e-commerce, social media, news, and content management. Besides recommendation generation, its presentation is also important. Most research and development focus on the technical aspects of recommendation generation; therefore, a gap exists between recommendation generation and its effective presentation and user interaction. This study focuses on how personalized recommendations can be presented and interacted with in a music recommendation system using interactive visual interfaces. Interactive interface modeling with User-Centered Design (UCD) in a recommendation system is essential for creating a user-friendly, engaging, and personalized experience. By involving users in the recommendation process and considering their feedback, the system can deliver more relevant content, foster user trust, and improve overall user satisfaction and engagement. In this study, the visual interface design and development of a personalized music recommendation prototype (MusicReco) are presented using an iterative UCD approach, involving twenty end-users, one researcher, three academic professionals, and four experts. As the study is more inclined toward the recommendation presentation and visual modeling, we used a standard content-based filtering algorithm on the publicly available Spotify dataset for music recommendation generation. End-users helped to mature the MusicReco prototype to a basic working version through continuous feedback and design inputs on their needs, context, preferences, personalization, and effective visualization. Moreover, MusicReco captures the idea of mood-based tailored recommendations to encourage end-users. Overall, this study demonstrates how UCD can enhance the presentation and interaction of mood-based music recommendations, effectively engaging users with advancements in recommendation algorithms as a future focus.
IEEE (Institute of Electrical and Electronics Engineers)
2025
Permafrost is a considerable carbon reservoir harboring up to 1700 petagrams of carbon accumulated over millennia, which can be mobilized as permafrost thaws under global warming. Recent studies have highlighted that a fraction of this carbon can be transformed to atmospheric volatile organic compounds, which can affect the atmospheric oxidizing capacity and contribute to the formation of secondary organic aerosols. In this study, active layer soils from the seasonally unfrozen layer above the permafrost were collected from two distinct locations of the Greenlandic permafrost and incubated to explore their roles in the soil-atmosphere exchange of volatile organic compounds. Results show that these soils can actively function as sinks of these compounds, despite their different physiochemical properties. Upper active layer possessed relatively higher uptake capacities; factors including soil moisture, organic matter, and microbial biomass carbon were identified as the main factors correlating with the uptake rates. Additionally, uptake coefficients for several compounds were calculated for their potential use in future model development. Correlation analysis and the varying coefficients indicate that the sink was likely biotic. The development of a deeper active layer under climate change may enhance the sink capacity and reduce the net emissions of volatile organic compounds from permafrost thaw.
Springer Nature
2025
Citizen-operated low-cost air quality sensors (LCSs) have expanded air quality monitoring through community engagement. However, still challenges related to lack of semantic standards, data quality, and interoperability hinder their integration into official air quality assessments, management, and research. Here, we introduce FILTER, a geospatially scalable framework designed to unify, correct, and enhance the reliability of crowd-sourced PM2.5 data across various LCS networks. FILTER assesses data quality through five steps: range check, constant value detection, outlier detection, spatial correlation, and spatial similarity. Using official data, we modeled PM2.5 spatial correlation and similarity (Euclidean distance) as functions of geographic distance as benchmarks for evaluating whether LCS measurements are sufficiently correlated/consistent with neighbors. Our study suggests a −10 to 10 Median Absolute Deviation threshold for outlier flagging (360 h). We find higher PM2.5 spatial correlation in DJF compared to JJA across Europe while lower PM2.5 similarity in DJF compared to JJA. We observe seasonal variability in the maximum possible distance between sensors and reference stations for in-situ (remote) PM2.5 data correction, with optimal thresholds of ∼11.5 km (DJF), ∼12.7 km (MAM), ∼20 km (JJA), and ∼17 km (SON). The values implicitly reflect the spatial representativeness of stations. ±15 km relaxation for each season remains feasible when data loss is a concern. We demonstrate and validate FILTER's effectiveness using European-scale data originating from the two community-based monitoring networks, sensor.community and PurpleAir with QC-ed/corrected output including 37,085 locations and 521,115,762 hourly timestamps. Results facilitate uptake and adoption of crowd-sourced LCS data in regulatory applications.
Elsevier
2025
American Chemical Society (ACS)
2025