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2022
The main goal of this feasibility study was to evaluate the potential of adding value to the Sentinel 5P TROPOMI methane product over Norway and the Arctic through the synergistic use of relevant observations from other Sentinel satellites and machine learning. We assessed the data availability of ESA operational and research-based WFMD XCH4 products over the Northern hemisphere, the Nordic countries and the Arctic/Northern latitudes. ESA’s XCH4 data have poor coverage over Norway. Seeing the two datasets as complementary, seems to be the most reasonable approach for utilization them. Furthermore, we investigated potential synergies between satellite products from different platforms. A random forest (RF) machine learning algorithm was implemented. It shows the importance of daytime land surface temperature (LST) as predictor variable for CH4. Our results indicate that the RF-model has a very good capability of filling small gaps in the data.
NILU
2022
2022
2022
The Eurodelta-Trends (EDT) multi-model experiment, aimed at assessing the efficiency of emission mitigation measures in improving air quality in Europe during 1990–2010, was designed to answer a series of questions regarding European pollution trends; i.e. were there significant trends detected by observations? Do the models manage to reproduce observed trends? How close is the agreement between the models and how large are the deviations from observations? In this paper, we address these issues with respect to particulate matter (PM) pollution. An in-depth trend analysis has been performed for PM10 and PM2.5 for the period of 2000–2010, based on results from six chemical transport models and observational data from the EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) monitoring network. Given harmonization of set-up and main input data, the differences in model results should mainly result from differences in the process formulations within the models themselves, and the spread in the model-simulated trends could be regarded as an indicator for modelling uncertainty.
The model ensemble simulations indicate overall decreasing trends in PM10 and PM2.5 from 2000 to 2010, with the total reductions of annual mean concentrations by between 2 and 5 (7 for PM10) µg m−3 (or between 10 % and 30 %) across most of Europe (by 0.5–2 µg m−3 in Fennoscandia, the north-west of Russia and eastern Europe) during the studied period. Compared to PM2.5, relative PM10 trends are weaker due to large inter-annual variability of natural coarse PM within the former. The changes in the concentrations of PM individual components are in general consistent with emission reductions. There is reasonable agreement in PM trends estimated by the individual models, with the inter-model variability below 30 %–40 % over most of Europe, increasing to 50 %–60 % in the northern and eastern parts of the EDT domain.
Averaged over measurement sites (26 for PM10 and 13 for PM2.5), the mean ensemble-simulated trends are −0.24 and −0.22 µg m−3 yr−1 for PM10 and PM2.5, which are somewhat weaker than the observed trends of −0.35 and −0.40 µg m−3 yr−1 respectively, partly due to model underestimation of PM concentrations. The correspondence is better in relative PM10 and PM2.5 trends, which are −1.7 % yr−1 and −2.0 % yr−1 from the model ensemble and −2.1 % yr−1 and −2.9 % yr−1 from the observations respectively. The observations identify significant trends (at the 95 % confidence level) for PM10 at 56 % of the sites and for PM2.5 at 36 % of the sites, which is somewhat less that the fractions of significant modelled trends. Further, we find somewhat smaller spatial variability of modelled PM trends with respect to the observed ones across Europe and also within individual countries.
The strongest decreasing PM trends and the largest number of sites with significant trends are found for the summer season, according to both the model ensemble and observations. The winter PM trends are very weak and mostly insignificant. Important reasons for that are the very modest reductions and even increases in the emissions of primary PM from residential heating in winter. It should be kept in mind that all findings regarding modelled versus observed PM trends are limited to the regions where the sites are located.
The analysis reveals considerable variability of the role of the individual aerosols in PM10 trends across European countries. The multi-model simulations, supported by available observations, point to decreases in concentrations playing an overall dominant role. Also, we see...
2022
Mercury in air and soil on an urban-rural transect in East Africa
There are large knowledge gaps concerning concentrations, sources, emissions, and spatial trends of mercury (Hg) in the atmosphere in developing regions of the Southern Hemisphere, particularly in urban areas. Filling these gaps is a prerequisite for assessing the effectiveness of international regulation and for enabling a better understanding of the global transport of Hg in the environment. Here we use a passive sampling technique to study the spatial distribution of gaseous elemental Hg (Hg(0), GEM) and assess emission sources in and around Dar es Salaam, Tanzania's largest city. Included in the study were the city's main municipal waste dumpsite and an e-waste processing facility as potential sources of GEM. To complement the GEM data and for a better overview of the Hg contamination status of Dar es Salaam, soil samples were collected from the same locations where passive air samplers were deployed and analysed for total Hg. Overall, GEM concentrations ranged between <0.86 and 5.34 ng m−3, indicating significant local sources within the urban area. The municipal waste dumpsite and e-waste site had GEM concentrations elevated above the background, at 2.41 and 1.77 ng m−3, respectively. Hg concentrations in soil in the region (range 0.0067 to 0.098 mg kg−1) were low compared to those of other urban areas and were not correlated with atmospheric GEM concentrations. This study demonstrates that GEM is a significant environmental issue in the urban region of Dar es Salaam. Further studies from urban areas in the Global South are needed to better identify sources of GEM.
Royal Society of Chemistry (RSC)
2022
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2022
Do Carbon Nanotubes and Asbestos Fibers Exhibit Common Toxicity Mechanisms?
During the last two decades several nanoscale materials were engineered for industrial and medical applications. Among them carbon nanotubes (CNTs) are the most exploited nanomaterials with global production of around 1000 tons/year. Besides several commercial benefits of CNTs, the fiber-like structures and their bio-persistency in lung tissues raise serious concerns about the possible adverse human health effects resembling those of asbestos fibers. In this review, we present a comparative analysis between CNTs and asbestos fibers using the following four parameters: (1) fibrous needle-like shape, (2) bio-persistent nature, (3) high surface to volume ratio and (4) capacity to adsorb toxicants/pollutants on the surface. We also compare mechanisms underlying the toxicity caused by certain diameters and lengths of CNTs and asbestos fibers using downstream pathways associated with altered gene expression data from both asbestos and CNT exposure. Our results suggest that indeed certain types of CNTs are emulating asbestos fiber as far as associated toxicity is concerned.
MDPI
2022
Microplastics and nanoplastics in the marine-atmosphere environment
The discovery of atmospheric micro(nano)plastic transport and ocean–atmosphere exchange points to a highly complex marine plastic cycle, with negative implications for human and ecosystem health. Yet, observations are currently limited. In this Perspective, we quantify the processes and fluxes of the marine-atmospheric micro(nano)plastic cycle, with the aim of highlighting the remaining unknowns in atmospheric micro(nano)plastic transport. Between 0.013 and 25 million metric tons per year of micro(nano)plastics are potentially being transported within the marine atmosphere and deposited in the oceans. However, the high uncertainty in these marine-atmospheric fluxes is related to data limitations and a lack of study intercomparability. To address the uncertainties and remaining knowledge gaps in the marine-atmospheric micro(nano)plastic cycle, we propose a future global marine-atmospheric micro(nano)plastic observation strategy, incorporating novel sampling methods and the creation of a comparable, harmonized and global data set. Together with long-term observations and intensive investigations, this strategy will help to define the trends in marine-atmospheric pollution and any responses to future policy and management actions.
2022
We describe the outcome of a large international interlaboratory study of the measurement of particle number concentration of colloidal nanoparticles, project 10 of the technical working area 34, “Nanoparticle Populations” of the Versailles Project on Advanced Materials and Standards (VAMAS). A total of 50 laboratories delivered results for the number concentration of 30 nm gold colloidal nanoparticles measured using particle tracking analysis (PTA), single particle inductively coupled plasma mass spectrometry (spICP-MS), ultraviolet-visible (UV-Vis) light spectroscopy, centrifugal liquid sedimentation (CLS) and small angle X-ray scattering (SAXS). The study provides quantitative data to evaluate the repeatability of these methods and their reproducibility in the measurement of number concentration of model nanoparticle systems following a common measurement protocol. We find that the population-averaging methods of SAXS, CLS and UV-Vis have high measurement repeatability and reproducibility, with between-labs variability of 2.6%, 11% and 1.4% respectively. However, results may be significantly biased for reasons including inaccurate material properties whose values are used to compute the number concentration. Particle-counting method results are less reproducibile than population-averaging methods, with measured between-labs variability of 68% and 46% for PTA and spICP-MS respectively. This study provides the stakeholder community with important comparative data to underpin measurement reproducibility and method validation for number concentration of nanoparticles.
Royal Society of Chemistry (RSC)
2022