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Found 2670 publications. Showing page 26 of 267:

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Occurrence and backtracking of microplastic mass loads including tire wear particles in northern Atlantic air

Gossmann, Isabel; Herzke, Dorte; Held, Andreas; Schulz, Janina; Nikiforov, Vladimir; Georgi, Christoph; Evangeliou, Nikolaos; Eckhardt, Sabine; Gerdts, Gunnar; Wurl, Oliver; Scholz-Böttcher, Barbara

Few studies report the occurrence of microplastics (MP), including tire wear particles (TWP) in the marine atmosphere, and little data is available regarding their size or sources. Here we present active air sampling devices (low- and high-volume samplers) for the evaluation of composition and MP mass loads in the marine atmosphere. Air was sampled during a research cruise along the Norwegian coast up to Bear Island. Samples were analyzed with pyrolysis-gas chromatography-mass spectrometry, generating a mass-based data set for MP in the marine atmosphere. Here we show the ubiquity of MP, even in remote Arctic areas with concentrations up to 37.5 ng m−3. Cluster of polyethylene terephthalate (max. 1.5 ng m−3) were universally present. TWP (max. 35 ng m−3) and cluster of polystyrene, polypropylene, and polyurethane (max. 1.1 ng m−3) were also detected. Atmospheric transport and dispersion models, suggested the introduction of MP into the marine atmosphere equally from sea- and land-based emissions, transforming the ocean from a sink into a source for MP.

2023

Linking Nanomaterial-Induced Mitochondrial Dysfunction to Existing Adverse Outcome Pathways for Chemicals

Murugadoss, Sivakumar; Vrček, Ivana Vinković; Schaffert, Alexandra; Paparella, Martin; Pem, Barbara; Sosnowska, Anita; Stępnik, Maciej; Martens, Marvin; Willighagen, Egon L.; Puzyn, Tomasz; Cimpan, Mihaela-Roxana; Lemaire, Frauke; Mertens, Birgit; Dusinska, Maria; Fessard, Valérie; Hoet, Peter H.

The Adverse Outcome Pathway (AOP) framework plays a crucial role in the paradigm shift of toxicity testing towards the development and use of new approach methodologies. AOPs developed for chemicals are in theory applicable to nanomaterials (NMs). However, only subtle efforts have been made to integrate information on NM-induced toxicity into existing AOPs. In a previous study, we identified AOPs in the AOP-Wiki associated with the molecular initiating events (MIEs) and key events (KEs) reported for NMs in scientific literature. In a next step, we analyzed these AOPs and found that mitochondrial toxicity plays a significant role in several of them at the molecular and cellular levels. In this study, we aimed to generate hypothesis-based AOPs related to NM-induced mitochondrial toxicity. This was achieved by integrating science-based information collected on NM-induced mitochondrial toxicity into all existing AOPs in the AOP-Wiki, which already includes mitochondrial toxicity as a MIE/KE. The results showed that several AOPs in the AOP-Wiki related to the lung, liver, cardiovascular and nervous system, with extensively defined KEs and key event relationships (KERs), could be utilized to develop AOPs that are relevant for NMs. Our results also indicate that the majority of the studies included in our literature review were of poor quality, particularly in reporting NM physico-chemical characteristics, and NM-relevant mitochondrial MIEs were scarcely reported. This study highlights the potential role of NM-induced mitochondrial toxicity in human-relevant adverse outcomes and identifies useful AOPs in the AOP-Wiki for the development AOPs that are relevant for NMs.

2023

Soil uptake of VOCs exceeds production when VOCs are readily available

Jiao, Yi; Kramshøj, Magnus; Davie-Martin, Cleo Lisa; Albers, Christian Nyrop; Rinnan, Riikka

Volatile organic compounds (VOCs) are reactive gaseous compounds with significant impacts on air quality and the Earth's radiative balance. While natural ecosystems are known to be major sources of VOCs, primarily due to vegetation, soils, an important component of these ecosystems, have received relatively less attention as potential sources and sinks of VOCs. In this study, soil samples were collected from two temperate ecosystems: a beech forest and a heather heath, and then sieved, homogenized, and incubated under various controlled conditions such as different temperatures, oxic vs. anoxic conditions, and different ambient VOC levels. A dynamic flow-through system coupled to a proton transfer reaction-time of flight-mass spectrometry (PTR-ToF-MS) was used to measure production and/or uptake rates of selected VOCs, aiming to explore the processes and their controlling mechanisms. Our results showed that these soils were natural sources of a variety of VOCs, and the strength and profile of these emissions were influenced by soil properties (e.g. moisture, soil organic matter), oxic/anoxic conditions, and temperature. The soils also acted as sinks for most VOCs when VOC substrates at parts per billions levels (ranging between 0.18 and 68.65 ppb) were supplied to the headspace of the enclosed soils, and the size of the sink corresponded to the amount of VOCs available in the ambient air. Temperature-controlled incubations and glass bead simulations indicated that the uptake of VOCs by soils was likely driven by microbial metabolism, with a minor contribution from physical adsorption to soil particles. In conclusion, our study suggests that soil uptake of VOCs can mitigate the impact of other significant VOC sources in the near-surface environment and potentially regulate the net exchange of these trace gases in ecosystems.

2023

Organizing the Indicator Zoo: Can a New Taxonomy Make It Easier for Citizen Science Data to Contribute to the United Nations Sustainable Development Goal Indicators?

Grossberndt, Sonja; Graff, Geir; Bartonova, Alena; Volchkova, Iuliia; Evensen, Thomas

In order to measure progress towards the aims outlined by the United Nations (UN) 2030 Agenda, data are needed for the different indicators that are linked to each UN Sustainable Development Goal (SDG). Where statistical or scientific data are not sufficient or available, alternative data sources, such as data from citizen science (CS) activities, could be used.

Statistics Norway, together with the Norwegian Association of Local and Regional Authorities, have developed a taxonomy for classifying indicators that are intended to measure the SDGs. The purpose of this taxonomy is to sort, evaluate, and compare different SDG indicators and to assess their usefulness by identifying their central properties and characteristics. This is done by organizing central characteristics under the three dimensions of Goal, Perspective, and Quality. The taxonomy is designed in a way that can help users to find the right indicators across sectors to measure progress towards the SDGs depending on their own context and strategic priorities. The Norwegian taxonomy also offers new opportunities for the re-use of data collected through CS activities. This paper presents the taxonomy and demonstrates how it can be applied for an indicator based on a CS data set, and we also suggest further use of CS data.

2023

The AirGAM 2022r1 air quality trend and prediction model

Walker, Sam-Erik; Solberg, Sverre; Schneider, Philipp; Guerreiro, Cristina

This paper presents the AirGAM 2022r1 model – an air quality trend and prediction model developed at the Norwegian Institute for Air Research (NILU) in cooperation with the European Environment Agency (EEA) over 2017–2021. AirGAM is based on nonlinear regression GAMs – generalised additive models – capable of estimating trends in daily measured pollutant concentrations at air quality monitoring stations, discounting for the effects of trends and time variations in corresponding meteorological data. The model has been developed primarily for the compounds NO2, O3, PM10, and PM2.5. Meteorological input data consist of temperature, wind speed and direction, planetary boundary layer height, relative and absolute humidity, cloud cover, and precipitation over the period considered. The exact set of meteorological variables used in the model depends on the compound selected for analysis. In addition to meteorological variables introduced in the model as covariates, i.e. explanatory variables for the concentration levels, the model also incorporates time variables such as the day of the week, day of the year, and overall time, which is related to the model's trend term. The trend analysis is performed at each station separately. Thus, the model only considers the temporal features of concentrations and meteorology at a station, rather than any spatial correlations or dependencies between stations. AirGAM is implemented using the R language for statistical computing and, in particular, the GAM package mgcv. In the model, meteorological and time covariates are represented and estimated as smooth nonlinear functions of the corresponding variables. Thus, the trend term is defined and estimated as a smooth nonlinear function of time over the period selected for analysis. Once fitted to training data, the model may be used as a prediction tool capable of predicting air pollutant concentrations for new sets of meteorological and time data which are not in the training set – e.g. for cross-validation or forecasting purposes. The model does not explicitly use emissions or background concentrations – these are sought to be implicitly represented through the estimated nonlinear relations between meteorology, time, and concentrations. In addition to meteorology-adjusted trends, the program also produces unadjusted trends – i.e. trends based on the same regression set-up but only including the time covariates. Both types of trends can be output in the same run, making it possible to compare them. Ideally, the meteorology-adjusted trend will show the trend in concentration mainly due to changes in emissions or physicochemical processes not induced by changes in meteorology. AirGAM has been developed and tested primarily in trend studies based on measurement data hosted by the EEA, including the AirBase data (before 2013) and the Air Quality e-Reporting (AQER) data from 2013 and onwards. Still, the model is general and could be applied in other regions with other input data. The EEA data provide daily or hourly surface measurements at individual monitoring stations in Europe. For input meteorological data, we extract time series from the gridded meteorological re-analysis (ERA5) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) for each monitoring station. The paper presents results with the model for all AirBase/AQER stations in Europe from the latest EEA trend study for 2005–2019.

2023

An optimised organic carbon/elemental carbon (OC/EC) fraction separation method for radiocarbon source apportionment applied to low-loaded Arctic aerosol filters

Rauber, Martin; Salazar, Gary; Yttri, Karl Espen; Szidat, Sönke

Radiocarbon (14C) analysis of carbonaceous aerosols is used for source apportionment, separating the carbon content into fossil vs. non-fossil origin, and is particularly useful when applied to subfractions of total carbon (TC), i.e. elemental carbon (EC), organic carbon (OC), water-soluble OC (WSOC), and water-insoluble OC (WINSOC). However, this requires an unbiased physical separation of these fractions, which is difficult to achieve. Separation of EC from OC using thermal–optical analysis (TOA) can cause EC loss during the OC removal step and form artificial EC from pyrolysis of OC (i.e. so-called charring), both distorting the 14C analysis of EC. Previous work has shown that water extraction reduces charring. Here, we apply a new combination of a WSOC extraction and 14C analysis method with an optimised separation that is coupled with a novel approach of thermal-desorption modelling for compensation of EC losses. As water-soluble components promote the formation of pyrolytic carbon, water extraction was used to minimise the charring artefact of EC and the eluate subjected to chemical wet oxidation to CO2 before direct 14C analysis in a gas-accepting accelerator mass spectrometer (AMS). This approach was applied to 13 aerosol filter samples collected at the Arctic Zeppelin Observatory (Svalbard) in 2017 and 2018, covering all seasons, which bear challenges for a simplified 14C source apportionment due to their low loading and the large portion of pyrolysable species. Our approach provided a mean EC yield of 0.87±0.07 and reduced the charring to 6.5 % of the recovered EC amounts. The mean fraction modern (F14C) over all seasons was 0.85±0.17 for TC; 0.61±0.17 and 0.66±0.16 for EC before and after correction with the thermal-desorption model, respectively; and 0.81±0.20 for WSOC.

2023

On coarse patterns in the atmospheric concentration of ice nucleating particles

Conen, Franz; Yakutin, Mikhail V; Puchnin, Alexander; Yttri, Karl Espen

The atmospheric concentration of ice nucleating particles active at around −10 °C (INP−10) is very low. Nevertheless, these particles play a role in the development of cloud systems, so their spatial and temporal patterns merit attention. We collated available datasets on INP−10 to identify such patterns. Among the five low altitude observatories in northern Eurasia, median values throughout May to October were lowest in Scandinavia (4 and 6 m−3), somewhat higher in central Europe (11 m−3), substantially higher in the West Siberian Plain (69 m−3) and highest in the Central Yakutian Lowland (204 m−3), suggesting that the abundance of INP−10 in northern Eurasia may increase with continentality and from West to East. The range of values at the same observatories was narrower throughout November to April (2 to 27 m−3). On average, by an order of magnitude smaller values were reported for the four Arctic observatories. Consequently, increasing poleward transport of air masses from the midlatitudes likely raises the concentration of INP−10 in the Arctic, particularly when air masses had surface contact in eastern parts of northern Eurasia.

2023

Impact of Aerosol Optical Properties, Precipitable Water, and Solar Geometry on Sky Radiances Using Radiative Transfer Modeling

Giannaklis, Christos-Panagiotis; Logothetis, Stavros-Andreas; Salamalikis, Vasileios; Tzoumanikas, Panagiotis; Kazantzidis, Andreas

Radiative transfer modeling is used to investigate the effect of aerosol optical properties and water vapor on cloud-free sky radiances at various atmospheric conditions. Simulations are generated by changing the most critical aerosol optical properties, namely aerosol optical depth, Ångström exponent, the single-scattering albedo, the precipitable water, and the solar zenith angle (SZA) in three different spectral ranges: ultraviolet A, visible, and near-infrared.

2023

Simulations of Sky Radiances in Red and Blue Channels at Various Aerosol Conditions Using Radiative Transfer Modeling

Giannaklis, Christos-Panagiotis; Logothetis, Stavros-Andreas; Salamalikis, Vasileios; Tzoumanikas, Panagiotis; Katsidimas, Konstantinos; Kazantzidis, Andreas

We conducted a theoretical analysis of the relationship between red-to-blue (RBR) color intensities and aerosol optical properties. RBR values are obtained by radiative transfer simulations of diffuse sky radiances. Changes in atmospheric aerosol concentration (parametrized by aerosol optical depth, AOD), particle’s size distribution (parametrized by Ångström exponent, AE) and aerosols’ scattering (parametrized by single scattering albedo—SSA) lead to variability in sky radiances and, thus, affect the RBR ratio. RBR is highly sensitive to AOD as high aerosol load in the atmosphere causes high RBR. AE seems to strongly affect the RBR, while SSA effect the RBR, but not to such a great extent.

2023

Rapid identification of in vitro cell toxicity using an electrochemical membrane screening platform

Kohl, Yvonne; William, Nicola; Elje, Elisabeth; Backes, Nadine; Rothbauer, Mario; Srancikova, Annamaria; Rundén-Pran, Elise; Yamani, Naouale El; Korenstein, Rafi; Madi, Lea; Barbul, Alexander; Kozics, Katarina; Sramkova, Monika; Steenson, Karen; Gabelova, Alena; Ertl, Peter; Dusinska, Maria; Nelson, Andrew

This study compares the performance and output of an electrochemical phospholipid membrane platform against respective in vitro cell-based toxicity testing methods using three toxicants of different biological action (chlorpromazine (CPZ), colchicine (COL) and methyl methanesulphonate (MMS)). Human cell lines from seven different tissues (lung, liver, kidney, placenta, intestine, immune system) were used to validate this physicochemical testing system. For the cell-based systems, the effective concentration at 50 % cell death (EC50) values are calculated. For the membrane sensor, a limit of detection (LoD) value was extracted as a quantitative parameter describing the minimum concentration of toxicant which significantly affects the structure of the phospholipid sensor membrane layer. LoD values were found to align well with the EC50 values when acute cell viability was used as an end-point and showed a similar toxicity ranking of the tested toxicants. Using the colony forming efficiency (CFE) or DNA damage as end-point, a different order of toxicity ranking was observed. The results of this study showed that the electrochemical membrane sensor generates a parameter relating to biomembrane damage, which is the predominant factor in decreasing cell viability when in vitro models are acutely exposed to toxicants. These results lead the way to using electrochemical membrane-based sensors for rapid relevant preliminary toxicity screens.

2023

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