Found 10461 publications. Showing page 387 of 419:
2024
The Opinion of the Scientific Committee on Health, Environmental and Emerging Risks advises the European Commission on whether the uses of titanium dioxide in toys and toy materials can be considered to be safe in light of the identified exposure, and the classification of titanium dioxide as carcinogenic category 2 after inhalation. Four toy products including casting kits, chalk, powder paints and white colour pencils containing various amounts of TiO2 as colouring agent were evaluated for inhalation risks. For the oral route, childrens’ lip gloss/lipstick, finger paint and white colour pencils were evaluated.
When it can be demonstrated with high certainty that no ultrafine fraction is present in pigmentary TiO2 preparations used in toys and toy materials, safe use with no or negligible risk for all products considered is indicated based on the exposure estimations of this Opinion. However, if an ultrafine fraction is assumed to be present, safe use is not indicated, except for white colour pencils.
2024
Holocene black carbon in New Zealand lake sediment records
Black carbon emitted from incomplete combustion of biomass and fossil fuel burning is an important aerosol; however, available long-term black carbon data are limited to remote polar and high-alpine ice cores from few geographic regions. Black carbon records from lake sediments fill geographic gaps but such records are still scarce, particularly in the Southern Hemisphere. We applied a new incandescence-based methodology to develop Holocene refractory black carbon (rBC) records from four lake-sediment archives in New Zealand and compare these with macroscopic charcoal records. Our rBC records suggest periods with substantial rBC deposition during the Holocene before human arrival in the 13th century reflecting long-range transport and possibly local wetland fires. With Polynesian settlement, rBC deposition increased on the South Island in agreement with macroscopic charcoal records, and it is this period of burning that is proposed as the source of rBC increases evident in Antarctic ice cores. However, sites on the North Island show no contemporaneous rBC increase suggesting regional differences in biomass burning patterns between the North and South islands. None of the New Zealand records show an increase in rBC from fossil fuel sources during the Industrial Era post-1850 CE.
2024
Evaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1
Isoprene, a key biogenic volatile organic compound, plays a pivotal role in atmospheric chemistry. Due to its high reactivity, this compound contributes significantly to the production of tropospheric ozone in polluted areas and to the formation of secondary organic aerosols.
The assessment of biogenic emissions is of great importance for regional and global air quality evaluation. In this study, we implemented the biogenic emission model MEGANv2.1 (Model of Emissions of Gases and Aerosols from Nature, version 2.1) in the surface model SURFEXv8.1 (SURface EXternalisée in French, version 8.1). This coupling aims to improve the estimation of biogenic emissions using the detailed vegetation-type-dependent treatment included in the SURFEX vegetation ISBA (Interaction between Soil Biosphere and Atmosphere) scheme. This scheme provides vegetation-dependent parameters such as leaf area index and soil moisture to MEGAN. This approach enables a more accurate estimation of biogenic fluxes compared to the stand-alone MEGAN model, which relies on average input values for all vegetation types.
The present study focuses on the assessment of the SURFEX–MEGAN model isoprene emissions. An evaluation of the coupled SURFEX–MEGAN model results was carried out by conducting a global isoprene emission simulation in 2019 and by comparing the simulation results with other MEGAN-based isoprene inventories. The coupled model estimates a total global isoprene emission of 443 Tg in 2019. The estimated isoprene is within the range of results obtained with other MEGAN-based isoprene inventories, ranging from 311 to 637 Tg. The spatial distribution of SURFEX–MEGAN isoprene is consistent with other studies, with some differences located in low-isoprene-emission regions.
Several sensitivity tests were conducted to quantify the impact of different model inputs and configurations on isoprene emissions. Using different meteorological forcings resulted in a ±5 % change in isoprene emissions using MERRA (Modern-Era Retrospective analysis for Research and Applications) and IFS (Integrated Forecasting System) compared with ERA5. The impact of using different emission factor data was also investigated. The use of PFT (plant functional type) spatial coverage and PFT-dependent emission potential data resulted in a 12 % reduction compared to using the isoprene emission potential gridded map. A significant reduction of around 38 % in global isoprene emissions was observed in the third sensitivity analysis, which applied a parameterization of soil moisture deficit, particularly in certain regions of Australia, Africa, and South America.
The significance of coupling the SURFEX and MEGAN models lies particularly in the ability of the coupled model to be forced with meteorological data from any period. This means, for instance, that this system can be used to predict biogenic emissions in the future. This aspect of our work is significant given the changes that biogenic organic compounds are expected to undergo as a result of changes in their climatic factors.
2024
Marine litter and non-degradable plastic pollution is of global concern. Regular monitoring programs are being established to assess and understand the scale of this pollution. In Europe, the goal of the European Marine Strategy Framework Directive (MSFD) is to assess trends in Good Environmental Status and support large-scale actions at the regional level. Marine litter monitoring requires tailored sampling strategies, protocols and indicators, that align with specific objectives and are tailored for local or regional needs. In addition, the uneven spatial and temporal distributions of marine litter present a challenge when designing a statistically powerful monitoring program. In this paper, we critically review the existing marine litter monitoring programs in Europe. We discuss the main constraints, including environmental, logistical, scientific, and ethical factors. Additionally, we outline the critical gaps and shortcomings in monitoring MSFD beaches/shorelines, floating litter, seafloor litter, microplastics, and harm. Several priorities must be established to shape the future of monitoring within the MSFD. Recent developments in analytical approaches, including optimizing protocols and sampling strategies, gaining a better understanding of the spatiotemporal heterogeneity of litter and its implications for survey design and replication, and the inclusion of newly validated methodologies that have achieved sufficient technical readiness, must be considered. Although there are well-established methods for assessing beaches, floating and seafloor litter, it will be necessary to implement monitoring schemes for microplastics in sediments and invertebrates as robust analytical methods become available for targeting smaller particle size classes. Furthermore, the inclusion of indicators for entanglement and injury to marine organisms will have to be considered in the near future. Moreover, the following actions will enhance the effectiveness of monitoring efforts: (1) creating an inventory of accumulation areas and sources of specific types of litter (e.g., fishing gear), (2) monitoring riverine inputs of litter, (3) monitoring atmospheric inputs including microplastics, (4) accidental inputs during extreme weather events, and (5) studying how species at risk may be transported by litter. We provide recommendations to support long-term, effective, and well-coordinated marine litter monitoring within the MSFD to achieve a comprehensive and accurate understanding of marine litter in EU waters. This will allow the development of measures to mitigate the impacts of marine pollution and eventually to evaluate the success of the respective measures.
2024
High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage
In the modern “omics” era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography–HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.
2024
2024
2024
The 2023 Screening Programme aimed to investigate the presence of emerging environmental concerning substances 1) at so-called “hot spot” locations, and 2) in marine top predators. Part 1 covered emerging substances that were considered for EU regulation; persistent, mobile and toxic; identified as problematic (Sweden); and UV-stabilizers. Sampling sites were a wastewater treatment plant, indoor dust, agricultural soils, and consumer products. Part 2 covered substances found in the 2021 Screening Programme as well as selected through the LIfeAPEX project. Additionally, in part 2, several classical legacy contaminants were included. A unique sample set was assembled with different types of tissue from whales (killer whale, sperm whale, fin whale, humpback whale, white beaked dolphin, and harbor porpoise) and sharks (greenland shark, porbeagle shark, and spiny dogfish). Highlights from the results in part 1 covered a high detection frequency and concentrations of one phthalate (CAS 6422-86-2) and two UV-stabilizers (CAS 154702-15-5 and 103597-45-1). In part 2, only a small number of the emerging substances were identified, while many of the legacy substances were found at high levels.
Norsk institutt for vannforskning (NIVA)
2024
2024
Query-driven Qualitative Constraint Acquisition
Many planning, scheduling or multi-dimensional packing problems involve the design of subtle logical combinations of temporal or spatial constraints. Recently, we introduced GEQCA-I, which stands for Generic Qualitative Constraint Acquisition, as a new active constraint acquisition method for learning qualitative constraints using qualitative queries. In this paper, we revise and extend GEQCA-I to GEQCA-II with a new type of query, universal query, for qualitative constraint acquisition, with a deeper query-driven acquisition algorithm. Our extended experimental evaluation shows the efficiency and usefulness of the concept of universal query in learning randomly-generated qualitative networks, including both temporal networks based on Allen’s algebra and spatial networks based on region connection calculus. We also show the effectiveness of GEQCA-II in learning the qualitative part of real scheduling problems.
2024
Negative correlation between soil salinity and soil organic carbon variability
Soil organic carbon (SOC) is vital for terrestrial ecosystems, affecting biogeochemical processes, and soil health. It is known that soil salinity impacts SOC content, yet the specific direction and magnitude of SOC variability in relation to soil salinity remain poorly understood. Analyzing 43,459 mineral soil samples (SOC < 150 g kg−1) collected across different land covers since 1992, we approximate a soil salinity increase from 1 to 5 dS m−1 in croplands would be associated with a decline in mineral soils SOC from 0.14 g kg−1 above the mean predicted SOC (= 18.47 g kg−1) to 0.46 g kg−1 below (~−430%), while for noncroplands, such decline is sharper, from 0.96 above = 35.96 g kg−1 to 4.99 below (~−620%). Although salinity’s significance in explaining SOC variability is minor (<6%), we estimate a one SD increase in salinity of topsoil samples (0 to 7 cm) correlates with respective declines of ~4.4% and ~9.26%, relative to and. The decline in croplands is greatest in vegetation/cropland mosaics while lands covered with evergreen needle-leaved trees are estimated with the highest decline in noncroplands. We identify soil nitrogen, land cover, and precipitation Seasonality Index as the most significant parameters in explaining the SOC’s variability. The findings provide insights into SOC dynamics under increased soil salinity, improving understanding of SOC stock responses to land degradation and climate warming.
2024
Background
Chlorinated paraffins (CPs) are industrial chemicals categorised as persistent organic pollutants because of their toxicity, persistency and tendency to long-range transport, bioaccumulation and biomagnification. Despite having been the subject of environmental attention for decades, analytical methods for CPs still struggle reaching a sufficient degree of accuracy. Among the issues negatively impacting the quantification of CPs, the unavailability of well-characterised standards, both as pure substances and as matrix (certified) reference materials (CRMs), has played a major role. The focus of this study was to provide a matrix CRM as quality control tool to improve the comparability of CPs measurement results.
Results
We present the process of certification of ERM®-CE100, the first fish reference material assigned with certified values for the mass fraction of short-chain and medium-chain chlorinated paraffins (SCCPs and MCCPs, respectively). The certification was performed in accordance with ISO 17034:2016 and ISO Guide 35:2017, with the value assignment step carried out via an intercomparison of laboratories of demonstrated competence in CPs analysis and applying procedures based on different analytical principles. After confirmation of the homogeneity and stability of the CRM, two certified values were assigned for SCCPs, depending on the calibrants used: 31 ± 9 μg kg−1 and 23 ± 7 μg kg−1. The MCCPs certified value was established as 44 ± 17 μg kg−1. All assigned values are relative to wet weight in the CRM that was produced as a fish paste to enhance similarity to routine biota samples.
Significance and novelty
The fish tissue ERM-CE100 is the first matrix CRM commercially available for the analysis of CPs, enabling analytical laboratories to improve the accuracy and the metrological traceability of their measurements. The certified CPs values are based on results obtained by both gas and liquid chromatography coupled with various mass spectrometric techniques, offering thus a broad validity to laboratories employing different analytical methods and equipment.
2024
The Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) officially became the 33rd European Research Infrastructure Consortium (ERIC) on April 25, 2023 with the support of 17 founding member and observer countries. As a pan-European legal organization, ACTRIS ERIC will coordinate the provision of data and data products on short-lived atmospheric constituents and clouds relevant to climate and air pollution over the next 15-20 years. ACTRIS was designed more than a decade ago, and its development was funded at national and European levels. It was included in the European Strategy Forum on Research Infrastructures (ESFRI) Roadmap in 2016 and subsequently, in the national infrastructure roadmaps of European countries. It became a landmark of the ESFRI roadmap in 2021. The purpose of this paper is to describe the mission of ACTRIS, its added value to the community of atmospheric scientists, providing services to academia as well as the public and private sectors, and to summarize its main achievements. The present publication serves as a reference document for ACTRIS, its users and the scientific community as a whole. It provides the reader with relevant information and an overview on ACTRIS governance and services, as well as a summary of the main scientific achievements of the last 20 years. The paper concludes with an outlook on the upcoming challenges for ACTRIS and the strategy for its future evolution.
2024
Two-Stage Feature Engineering to Predict Air Pollutants in Urban Areas
Air pollution is a global challenge to human health and the ecological environment. Identifying the relationship among pollutants, their fundamental sources and detrimental effects on health and mental well-being is critical in order to implement appropriate countermeasures. The way forward to address this issue and assess air quality is through accurate air pollution prediction. Such prediction can subsequently assist governing bodies in making prompt, evidence-based decisions and prevent further harm to our urban environment, public health, and climate, all of which co-benefit our economy. In this study, the main objective is to explore the strength of features and proposed a two stage feature engineering approach, which fuses the advantage of influential factors along with the decomposition approach and generates an optimum feature combination for five major pollutants including Nitrogen Dioxide (NO 2 ), Ozone (O 3 ), Sulphur Dioxide (SO 2 ), and Particulate Matter (PM2.5, and PM10). The experiments are conducted using a dataset from 2015 to 2020 which is publicly available and is collected from Belfast-based air quality monitoring stations in Northern Ireland, UK. In stage-1, using the dataset new features such as trigonometric and statistical features are created to capture their dependency on the target pollutant and generated correlation-inspired best feature combinations to improve forecasting model performance. This is further enhanced in stage-2 by an optimum feature combination which is an integration of stage-1 and Variational Mode Decomposition (VMD) based features. This study employed a simplified Long Short Term Memory (LSTM) neural network and proposed a single-step forecasting model to predict multivariate time series data. Three performance indicators are used to evaluate the effectiveness of forecasting model: (a) root mean square error (RMSE), (b) mean absolute error (MAE), and (c) R-squared (R 2 ). The results demonstrate the effectiveness of proposed approach with 13% improvement in performance (in terms of R 2 ) and the lowest error scores for both RMSE and MAE.
2024
2024