Found 10034 publications. Showing page 388 of 402:
1999
Use of three-dimensional (3D) tissue equivalents in toxicology has been increasing over the last decade as novel preclinical test systems and as alternatives to animal testing. In the area of genetic toxicology, progress has been made with establishing robust protocols for skin, airway (lung) and liver tissue equivalents. In light of these advancements, a “Use of 3D Tissues in Genotoxicity Testing” working group (WG) met at the 7th IWGT meeting in Tokyo in November 2017 to discuss progress with these models and how they may fit into a genotoxicity testing strategy. The workshop demonstrated that skin models have reached an advanced state of validation following over 10 years of development, while liver and airway model-based genotoxicity assays show promise but are at an early stage of development. Further effort in liver and airway model-based assays is needed to address the lack of coverage of the three main endpoints of genotoxicity (mutagenicity, clastogenicity and aneugenicity), and information on metabolic competence. The IWGT WG believes that the 3D skin comet and micronucleus assays are now sufficiently validated to undergo an independent peer review of the validation study, followed by development of individual OECD Test Guidelines.
2020
2016
Use of satellite data for atmospheric pollution and greenhouse gas monitoring. A contribution to ACCENT-TROPOSAT-2, task group 3. ACCENT reports, 1.2007
2007
2009
<i>Background</i> - Concerns have been raised that extensive use of personal care products that contain endocrine disrupting compounds increase the risk of hormone sensitive cancers.<p> <p><i>Objective</i> - To assess the effect of skincare product use on the risk of pre- and postmenopausal breast cancer, estrogen receptor positive (ER+) and negative (ER-) breast cancer and cancer of the endometrium.<p> <p><i>Methods</i> - We used data from 106,978 participants in the population-based Norwegian Women and Cancer cohort. Participants were categorized into non-, light, moderate, frequent and heavy users of skincare products based on self-reported use of hand and facial cream and body lotion. Cancer incidence information from the Cancer Registry of Norway was linked to individual data through the unique identity number of Norwegian citizens. Multivariable Cox proportional hazard regression was used to assess the effect of skincare product use on the risk of cancer of the breast and endometrium. We used multiple imputation by chained equations to evaluate the effect of missing data on observed associations.<p> <p><i>Results</i> - We found no associations between use of skincare products and incidence of premenopausal breast cancer (frequent/heavy versus non−/light use: hazard ratio [HR] =1.10, 95% confidence interval [CI]: 0.92–1.32), postmenopausal breast cancer (heavy versus light use: HR = 0.87, 95% CI: 0.65–1.18, frequent versus light use: HR = 0.97, 95% CI: 0.88, 1.07) or endometrial cancer (frequent/heavy versus non−/light use: HR = 0.97, 95% CI: 0.79–1.20). Use of skincare products did not increase the risk of ER+ or ER- breast cancer and there was no difference in effect across ER status (0.58 ≤ <sub>pheterogeneity</sub> ≤ 0.99). The magnitude and direction of the effect estimates based on complete case analyses and multiple imputation were similar.<p> <p><i>Conclusion</i> Heavy use of skincare products, i.e. creaming the body up to two times per day during mid-life, did not increase the risk of cancer of the breast or endometrium.
2019
2008
2023
User's guide for the Gaussian type dispersion models CONCX and CONDEP. NILU TR
This report consists of a user's guide for the gaussian programs CONCX and CONDEP, which calculates short term and long term ground level concentrations, respectively, due to emission from one or more sources. The report contains a theoretical description of the theory included in the models, in addition to description of how to run the models.
1987
Using a citizen science approach to assess nanoplastics pollution in remote high-altitude glaciers
Nanoplastics are suspected to pollute every environment on Earth, including very remote areas reached via atmospheric transport. We approached the challenge of measuring environmental nanoplastics by combining high-sensitivity TD-PTR-MS (thermal desorption-proton transfer reaction-mass spectrometry) with trained mountaineers sampling high-altitude glaciers (“citizen science”). Particles < 1 μm were analysed for common polymers (polyethylene, polyethylene terephthalate, polypropylene, polyvinyl chloride, polystyrene and tire wear particles), revealing nanoplastic concentrations ranging 2–80 ng mL− 1 at five of 14 sites. The dominant polymer types found in this study were tire wear, polystyrene and polyethylene particles (41%, 28% and 12%, respectively). Lagrangian dispersion modelling was used to reconstruct possible sources of micro- and nanoplastic emissions for those observations, which appear to lie largely to the west of the Alps. France, Spain and Switzerland have the highest contributions to the modelled emissions. The citizen science approach was found to be feasible providing strict quality control measures are in place, and is an effective way to be able to collect data from remote and inaccessible regions across the world.
2025
Acoustic waves below the frequency limit of human hearing - infrasound - can travel for thousands of kilometres in the atmosphere. The global propagation signature of infrasound is highly sensitive to the wind structure of the stratosphere.
This work exploits processed continuous data from three high-latitude infrasound stations to characterize an aspect of the stratospheric polar vortex. Concretely, a mapping is developed which takes the infrasound data from these three stations as input and outputs an estimate of the polar cap zonal mean wind averaged over 60-90 degrees in latitude at the 1 hPa pressure level. This stratospheric diagnostic information is relevant to, for example, sudden stratospheric warming assessment and sub-seasonal prediction.
The considered acoustic data is within a low-frequency regime globally dominated by so-called microbarom infrasound, which is continuously radiated into the atmosphere due to nonlinear interaction between counter-propagating ocean surface waves.
We trained a stochastics-based machine learning model (delay-SDE-net) to map between a time series of five years (2014-2018) of processed infrasound data and the ERA5 (reanalysis-based) daily average polar cap wind at 1 hPa for the same period. The ERA5 data was hence treated as ground-truth. In the prediction, the delay-SDE-net utilizes time-lagged inputs and their dependencies, as well as the day of the year to account for seasonal differences. In the validation phase, the input was the 2019 and 2020 infrasound time series, and the model inference results in an estimate of the daily average polar cap wind time-series. This result was then compared to the ERA5 representation of the stratospheric diagnostic time-series for the same period.
The applied machine learning model is based on stochastics and allows for an interpretable approach to estimate the aleatoric and epistemic prediction uncertainties. It is found that the mapping, which is only informed of the trained model, the day of year, and the infrasound data from three stations, generates a 1 hPa polar cap average wind estimate with a prediction error standard deviation of around 10 m/s compared to ERA5.
Focus should be put on the winter months because this is when the coupling between the stratosphere and the troposphere can mostly influence the surface conditions and provide additional prediction skill, in particular during strong and weak stratospheric polar vortex regimes. The infrasound data is available in real-time, and we discuss how the developed approach can be extended to provide near real-time stratospheric polar vortex diagnostics.
2023
2018
2015
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2016
2025
In the framework of the Forum for Air Quality Modelling in Europe (FAIRMODE), a modelling intercomparison exercise for computing NO2 long-term average concentrations in urban districts with a very high spatial resolution was carried out. This exercise was undertaken for a district of Antwerp (Belgium). Air quality data includes data recorded in air quality monitoring stations and 73 passive samplers deployed during one-month period in 2016. The modelling domain was 800 × 800 m2. Nine modelling teams participated in this exercise providing results from fifteen different modelling applications based on different kinds of model approaches (CFD – Computational Fluid Dynamics-, Lagrangian, Gaussian, and Artificial Intelligence). Some approaches consisted of models running the complete one-month period on an hourly basis, but most others used a scenario approach, which relies on simulations of scenarios representative of wind conditions combined with post-processing to retrieve a one-month average of NO2 concentrations.
The objective of this study is to evaluate what type of modelling system is better suited to get a good estimate of long-term averages in complex urban districts. This is very important for air quality assessment under the European ambient air quality directives. The time evolution of NO2 hourly concentrations during a day of relative high pollution was rather well estimated by all models. Relative to high resolution spatial distribution of one-month NO2 averaged concentrations, Gaussian models were not able to give detailed information, unless they include building data and street-canyon parameterizations. The models that account for complex urban geometries (i.e. CFD, Lagrangian, and AI models) appear to provide better estimates of the spatial distribution of one-month NO2 averages concentrations in the urban canopy. Approaches based on steady CFD-RANS (Reynolds Averaged Navier Stokes) model simulations of meteorological scenarios seem to provide good results with similar quality to those obtained with an unsteady one-month period CFD-RANS simulations.
2024
Electronic waste (e-waste) is informally processed and recycled in Agbogbloshie in Accra (Ghana), which may be the largest such site in West Africa. This industry can lead to significant environmental contamination. In this study, surface dust samples were collected at a range of sites within Accra to establish the offsite consequences of such activities. Fifty-one samples were collected and analysed for 69 elements by ICP-mass spectrometry after nitric acid digestion. The data indicated a significant enrichment in metals associated with solder and copper wire at the site itself and a downwind dispersion of this source material to a distance of approximately 2.0 km. Chlorine and bromine were also elevated at this site as residues from polyvinyl chloride combustion and flame retardants respectively. The elemental composition indicated that only low technology electrical equipment was being treated this way. Multivariate statistical analyses by principal components analysis and polytopic vector analysis identified three sources contributing to the system; (i) burn site residue dispersing within 2 km from the source site, (ii) marine matter on the beaches alone and (iii) the baseline soil conditions of the city of Accra. Risk ratios and hazard quotients developed from the measured concentrations indicated that copper was providing the greatest risk to inhabitants in most cases although nickel, vanadium, chromium and zinc also contributed.
2019
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2009