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Organic micropollutants in the riverine sedimentsalong the lower stretch of the River Ganga: Occurrences, sources and risk assessment

Chakraborty, Paromita; Mukhopadhyay, Moitraiyee; Sampath, Srimurali; Ramaswamy, BabuRajendran; Katsoyiannis, Athanasios A.; Cincinelli, Alessandra; Snow, Daniel

2018

Levels and trends of poly- and perfluoroalkyl substances in the Arctic environment – An update

Muir, Derek; Bossi, Rossana; Carlsson, Pernilla; Evans, Marlene; Silva, Amila De; Halsall, Crispin; Rauert, Cassandra; Herzke, Dorte; Hung, Hayley; Letcher, Robert; Rigét, Frank; Roos, Anna

Poly- and perfluoroalkyl substances (PFASs) are important environmental contaminants globally and in the early 2000s they were shown to be ubiquitous contaminants in Arctic wildlife. Previous reviews by Butt et al. and Letcher et al. have covered studies on levels and trends of PFASs in the Arctic that were available to 2009. The purpose of this review is to focus on more recent work, generally published between 2009 and 2018, with emphasis on PFASs of emerging concern such as perfluoroalkyl carboxylates (PFCAs) and short-chain perfluoroalkyl sulfonates (PFSAs) and their precursors. Atmospheric measurements over the period 2006–2014 have shown that fluorotelomer alcohols (FTOHs) as well as perfluorobutanoic acid (PFBA) and perfluoroctanoic acid (PFOA) are the most prominent PFASs in the arctic atmosphere, all with increasing concentrations at Alert although PFOA concentrations declined at the Zeppelin Station (Svalbard). Results from ice cores show generally increasing deposition of PFCAs on the Devon Ice cap in the Canadian arctic while declining fluxes were found in a glacier on Svalbard. An extensive dataset exists for long-term trends of long-chain PFCAs that have been reported in Arctic biota with some datasets including archived samples from the 1970s and 1980s. Trends in PFCAs over time vary among the same species across the North American Arctic, East and West Greenland, and Svalbard. Most long term time series show a decline from higher concentrations in the early 2000s. However there have been recent (post 2010) increasing trends of PFCAs in ringed seals in the Canadian Arctic, East Greenland polar bears and in arctic foxes in Svalbard. Annual biological sampling is helping to determine these relatively short term changes. Rising levels of some PFCAs have been explained by continued emissions of long-chain PFCAs and/or their precursors and inflows to the Arctic Ocean, especially from the North Atlantic. While the effectiveness of biological sampling for temporal trends in long-chain PFCAs and PFSAs has been demonstrated, this does not apply to the C4–C8–PFCAs, perfluorobutane sulfonamide (FBSA), or perfluorobutane sulfonate (PFBS) which are generally present at low concentrations in biota. In addition to air sampling, sampling abiotic media such as glacial cores, and annual sampling of lake waters and seawater would appear to be the best approaches for investigating trends in the less bioaccumulative PFASs.

2019

Pervasive Arctic lead pollution suggests substantial growth in medieval silver production modulated by plague, climate, and conflict

McConnell, Joseph R.; Chellman, Nathan J.; Wilson, Andrew I.; Stohl, Andreas; Arienzo, Monica M.; Eckhardt, Sabine; Fritzsche, Diedrich; Kipfstuhl, Sepp; Opel, Thomas; Place, Philip F.; Steffensen, Jørgen Peder

2019

What caused a record high PM10 episode in northern Europe in October 2020?

Zwaaftink, Christine Groot; Aas, Wenche; Eckhardt, Sabine; Evangeliou, Nikolaos; Hamer, Paul David; Johnsrud, Mona; Kylling, Arve; Platt, Stephen Matthew; Stebel, Kerstin; Uggerud, Hilde Thelle; Yttri, Karl Espen

In early October 2020, northern Europe experienced an episode with poor air quality due to high concentrations of particulate matter (PM). At several sites in Norway, recorded weekly values exceeded historical maximum PM10 concentrations from the past 4 to 10 years. Daily mean PM10 values at Norwegian sites were up to 97 µg m−3 and had a median value of 59 µg m−3. We analysed this severe pollution episode caused by long-range atmospheric transport based on surface and remote sensing observations and transport model simulations to understand its causes. Samples from three sites in mainland Norway and the Arctic remote station Zeppelin (Svalbard) showed strong contributions from mineral dust to PM10 (23 %–36 % as a minimum and 31 %–45 % as a maximum) and biomass burning (8 %–16 % to 19 %–21 %). Atmospheric transport simulations indicate that Central Asia was the main source region for mineral dust observed in this episode. The biomass burning fraction can be attributed to forest fires in Ukraine and southern Russia, but we cannot exclude other sources contributing, like fires elsewhere, because the model underestimates observed concentrations. The combined use of remote sensing, surface measurements, and transport modelling proved effective in describing the episode and distinguishing its causes.

2022

Bird feathers as a biomonitor for environmental pollutants: Prospects and pitfalls

Jaspers, Veerle; Covaci, Adrian; Herzke, Dorte; Eulaers, Igor; Eens, Marcel

Due to increasing amounts of hazardous chemicals released into the environment, there is a high demand for developing easy and non-destructive biomonitoring tools. In a recent paper published in Trends in Analytical Chemistry, Rutkowska et al. (2018) concluded that feathers are a good matrix for biomonitoring of environmental pollutants in birds. In this commentary, we discuss the general conclusion of this paper. We provide several examples for which this statement is not correct, and we emphasize that only for legacy persistent organic pollutants (POPs) and mercury there is currently enough scientific evidence to use feathers as a reliable biomonitor, given that appropriate sampling designs and QA/QC protocols are taken into account. Furthermore, we discuss different pretreatment (e.g. feather washing) and analytical protocols along with specific QA/QC to be considered. In summary, this commentary provides an overview of the prospects and pitfalls when using feathers as a biomonitor for environmental pollutants.

2019

Toward Standardization of a Lung New Approach Model for Toxicity Testing of Nanomaterials

Elje, Elisabeth; Camassa, Laura Maria Azzurra; Shaposhnikov, Sergey; Anmarkrud, Kristine Haugen; Skare, Øivind; Nilsen, Asbjørn Magne; Zienolddiny, Shanbeh; Rundén-Pran, Elise

This study represents an attempt toward the standardization of pulmonary NAMs and the development of a novel approach for toxicity testing of nanomaterials. Laboratory comparisons are challenging yet essential for identifying existing limitations and proposing potential solutions. Lung cells cultivated and exposed at the air-liquid interface (ALI) more accurately represent the physiology of human lungs and pulmonary exposure scenarios than submerged cell and exposure models. A triculture cell model system was used, consisting of human A549 lung epithelial cells and differentiated THP-1 macrophages on the apical side, with EA.hy926 endothelial cells on the basolateral side. The cells were exposed to silver nanoparticles NM-300K for 24 h. The model used here showed to be applicable for assessing the hazards of nanomaterials and chemicals, albeit with some limitations. Cellular viability was measured using the alamarBlue assay, DNA damage was assessed with the enzyme-modified comet assay, and the expression of 40 genes related to cell viability, inflammation, and DNA damage response was evaluated through RT2 gene expression profiling. Despite harmonized protocols used in the two independent laboratories, however, some methodological challenges could affect the results, including sensitivity and reproducibility of the model.

2024

Atmospheric transport is a major pathway of microplastics to remote regions

Evangeliou, Nikolaos; Grythe, H.; Klimont, Zbigniew; Heyes, Chris; Eckhardt, Sabine; Lopez-Aparicio, S.; Stohl, Andreas

In recent years, marine, freshwater and terrestrial pollution with microplastics has been discussed extensively, whereas atmospheric microplastic transport has been largely overlooked. Here, we present global simulations of atmospheric transport of microplastic particles produced by road traffic (TWPs – tire wear particles and BWPs – brake wear particles), a major source that can be quantified relatively well. We find a high transport efficiencies of these particles to remote regions. About 34% of the emitted coarse TWPs and 30% of the emitted coarse BWPs (100 kt yr−1 and 40 kt yr−1 respectively) were deposited in the World Ocean. These amounts are of similar magnitude as the total estimated direct and riverine transport of TWPs and fibres to the ocean (64 kt yr−1). We suggest that the Arctic may be a particularly sensitive receptor region, where the light-absorbing properties of TWPs and BWPs may also cause accelerated warming and melting of the cryosphere.

2020

Design of multi-luminescent silica-based nanoparticles for the detection of liquid organic compounds

Delic, Asmira; Lindgren, Mikael; Psarrou, Maria; Economopoulos, Solon; Mariussen, Espen; Krivokapic, Alexander; Torsæter, Ole; Omran, Mohamed; Einarsrud, Mari-Ann

Tracer testing in reservoir formations is utilised to determine residual oil saturation as part of optimum hydrocarbon production. Here, we present a novel detection method of liquid organic compounds by monodisperse SiO2 nanoparticles (NPs) containing two luminophores, a EuIII:EDTA complex and a newly synthesised fluorophore based on the organic boron-dipyrromethene (BODIPY)-moiety. The particles exhibited stable EuIII PL emission intensity with a long lifetime in aqueous dispersion. The fluorescence of the BODIPY was also preserved in the aqueous environment. The ratiometric PL detection technique was demonstrated by using toluene and 1-octanol as model compounds of crude oil. The optimal synthesis conditions were found to give NPs with a diameter of ~100 nm, which is suitable for transport through porous oil reservoir structures. The cytotoxicity of the NPs was confirmed to be very low for human lung cell and fish cell lines. These findings demonstrate the potential of the NPs to replace the hazardous chemicals used to estimate the residual oil saturation. Moreover, the ratiometric PL detection technique is anticipated to be of benefit in other fields, such as biotechnology, medical diagnostics, and environmental monitoring, where a reliable and safe detection of a liquid organic phase is needed.

2024

The Lagrangian particle dispersion model FLEXPART version 10.4

Pisso, Ignacio; Sollum, Espen; Grythe, Henrik; Kristiansen, Nina Iren; Cassiani, Massimo; Eckhardt, Sabine; Arnold, Delia; Morton, Don; Thompson, Rona Louise; Zwaaftink, Christine Groot; Evangeliou, Nikolaos; Sodemann, Harald; Haimberger, Leopold; Henne, Stephan; Brunner, Dominik; Burkhart, John; Fouilloux, Anne Claire; Brioude, Jerome; Philipp, Anne; Seibert, Petra; Stohl, Andreas

The Lagrangian particle dispersion model FLEXPART in its original version in the mid-1990s was designed for calculating the long-range and mesoscale dispersion of hazardous substances from point sources, such as those released after an accident in a nuclear power plant. Over the past decades, the model has evolved into a comprehensive tool for multi-scale atmospheric transport modeling and analysis and has attracted a global user community. Its application fields have been extended to a large range of atmospheric gases and aerosols, e.g., greenhouse gases, short-lived climate forcers like black carbon and volcanic ash, and it has also been used to study the atmospheric branch of the water cycle. Given suitable meteorological input data, it can be used for scales from dozens of meters to global. In particular, inverse modeling based on source–receptor relationships from FLEXPART has become widely used. In this paper, we present FLEXPART version 10.4, which works with meteorological input data from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) and data from the United States National Centers of Environmental Prediction (NCEP) Global Forecast System (GFS). Since the last publication of a detailed FLEXPART description (version 6.2), the model has been improved in different aspects such as performance, physicochemical parameterizations, input/output formats, and available preprocessing and post-processing software. The model code has also been parallelized using the Message Passing Interface (MPI). We demonstrate that the model scales well up to using 256 processors, with a parallel efficiency greater than 75 % for up to 64 processes on multiple nodes in runs with very large numbers of particles. The deviation from 100 % efficiency is almost entirely due to the remaining nonparallelized parts of the code, suggesting large potential for further speedup. A new turbulence scheme for the convective boundary layer has been developed that considers the skewness in the vertical velocity distribution (updrafts and downdrafts) and vertical gradients in air density. FLEXPART is the only model available considering both effects, making it highly accurate for small-scale applications, e.g., to quantify dispersion in the vicinity of a point source. The wet deposition scheme for aerosols has been completely rewritten and a new, more detailed gravitational settling parameterization for aerosols has also been implemented. FLEXPART has had the option of running backward in time from atmospheric concentrations at receptor locations for many years, but this has now been extended to also work for deposition values and may become useful, for instance, for the interpretation of ice core measurements. To our knowledge, to date FLEXPART is the only model with that capability. Furthermore, the temporal variation and temperature dependence of chemical reactions with the OH radical have been included, allowing for more accurate simulations for species with intermediate lifetimes against the reaction with OH, such as ethane. Finally, user settings can now be specified in a more flexible namelist format, and output files can be produced in NetCDF format instead of FLEXPART's customary binary format. In this paper, we describe these new developments. Moreover, we present some tools for the preparation of the meteorological input data and for processing FLEXPART output data, and we briefly report on alternative FLEXPART versions.

2019

Long-term meteorology-adjusted and unadjusted trends of PM2.5 using the AirGAM model over Delhi, 2007–2022

Chetna, NN; Dhaka, Surendra K.; Walker, Sam-Erik; Rawat, Vikas; Singh, Narendra

This study investigates the impact of meteorological variations on the long-term patterns of PM2.5 in Delhi from 2007 to 2022 using the AirGAM 2022r1 model. Generalized Additive Modeling was employed to analyze meteorology-adjusted (removing the influence of inter-annual variations in meteorology) and unadjusted trends (trends without considering meteorology) while addressing auto-correlation. PM2.5 levels showed a modest decline of 14 μg m−3 unadjusted and 18 μg m−3 meteorology-adjusted over the study period. Meteorological conditions and time factors significantly influenced trends. Temperature, wind speed, wind direction, humidity, boundary layer height, medium-height cloud cover, precipitation, and time variables including day-of-week, day-of-year, and overall time, were used as GAM model inputs. The model accounted for 55% of PM2.5 variability (adjusted R-squared = 0.55). Day-of-week and medium-height cloud cover were non-significant, while other covariates were significant (p

2024

Cost-Efficient measurement platform and machine-learning-based sensor calibration for precise NO2 pollution monitoring

Pietrenko-Dabrowska, Anna; Koziel, Slawomir; Wojcikowski, Marek; Pankiewicz, Bogdan; Rydosz, Artur; Cao, Tuan-Vu; Wojtkiewicz, Krystian

2024

Data fusion for enhancing urban air quality modeling using large-scale citizen science data

O'Regan, Anna C.; Grythe, Henrik; Hellebust, Stig; Lopez-Aparicio, Susana; O’Dowd, Colin; Hamer, Paul David; Santos, Gabriela Sousa; Nyhan, Marguerite M.

Rapid urbanization has led to many environmental issues, including poor air quality. With urbanization set to continue, there is an urgent need to mitigate air pollution and minimize its adverse health impacts. This study aims to advance urban air quality management by integrating a dispersion model output with large-scale citizen science data, collected over a 4-week period by 642 participants in Cork City, Ireland. The dispersion model enabled the identification of major sources of NO2 air pollution while also addressing gaps in regulatory monitoring efforts. Integrating the diffusion tube data with the dispersion model output, we developed a data fusion model that captured localized fluctuations in air quality, with increases of up to 22μg/m3 observed at major road intersections. The data fusion model provided a more accurate representation of NO2 concentrations, with estimates within 1.3μg/m3 of the regulatory monitoring measurement at an urban traffic location, an improvement of 11.7μg/m3 from the priori dispersion model. This enhanced accuracy enabled a more precise assessment of the population exposure to air pollution. The data fusion model showed a higher population exposure to NO2 compared to the dispersion model, providing valuable insights that can inform environmental health policies aimed at safeguarding public health.

2024

Two-Stage Feature Engineering to Predict Air Pollutants in Urban Areas

Naz, Fareena; Fahim, Muhammad; Cheema, Adnan Ahmad; Nguyen, Trung Viet; Cao, Tuan-Vu; Hunter, Ruth; Duong, Trung Q.

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

The Integrated Carbon Observation System in Europe

Heiskanen, Jouni; Brümmer, Christian; Buchmann, Nina; Calfapietra, Carlo; Chen, Huilin; Gielen, Bert; Gkritzalis, Thanos; Hammer, Samuel; Hartman, Susan; Herbst, Mathias; Janssens, Ivan A.; Jordan, Armin; Juurola, Eija; Karstens, Ute; Kasurinen, Ville; Kruijt, Bart; Lankreijer, Harry; Levin, Ingeborg; Linderson, Maj-Lena; Loustau, Denis; Merbold, Lutz; Myhre, Cathrine Lund; Papale, Dario; Pavelka, Marian; Pilegaard, Kim; Ramonet, Michel; Rebmann, Corinna; Rinne, Janne; Rivier, Leonard; Saltikoff, Elena; Sanders, Richard; Steinbacher, Martin; Steinhoff, Tobias; Watson, Andrew; Vermeulen, Alex T.; Vesala, Timo; Vitkova, Gabriela; Kutsch, Werner

Since 1750, land use change and fossil fuel combustion has led to a 46 % increase in the atmospheric carbon dioxide (CO2) concentrations, causing global warming with substantial societal consequences. The Paris Agreement aims to limiting global temperature increases to well below 2°C above pre-industrial levels. Increasing levels of CO2 and other greenhouse gases (GHGs), such as methane (CH4) and nitrous oxide (N2O), in the atmosphere are the primary cause of climate change. Approximately half of the carbon emissions to the atmosphere is sequestered by ocean and land sinks, leading to ocean acidification but also slowing the rate of global warming. However, there are significant uncertainties in the future global warming scenarios due to uncertainties in the size, nature and stability of these sinks. Quantifying and monitoring the size and timing of natural sinks and the impact of climate change on ecosystems are important information to guide policy-makers’ decisions and strategies on reductions in emissions. Continuous, long-term observations are required to quantify GHG emissions, sinks, and their impacts on Earth systems. The Integrated Carbon Observation System (ICOS) was designed as the European in situ observation and information system to support science and society in their efforts to mitigate climate change. It provides standardized and open data currently from over 140 measurement stations across 12 European countries. The stations observe GHG concentrations in the atmosphere and carbon and GHG fluxes between the atmosphere, land surface and the oceans. This article describes how ICOS fulfills its mission to harmonize these observations, ensure the related long-term financial commitments, provide easy access to well-documented and reproducible high-quality data and related protocols and tools for scientific studies, and deliver information and GHG-related products to stakeholders in society and policy.

2021

Task Offloading Optimization for UAV-Aided NOMA Networks With Coexistence of Near-Field and Far-Field Communications

Bui, Tinh Thanh; Do, Thinh Quang; Huynh, Dang Van; Do-Duy, Tan; Nguyen, Long D.; Cao, Tuan-Vu; Sharma, Vishal; Duong, Trung Q.

2025

AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations

Gliss, Jonas; Mortier, Augustin; Schulz, Michael; Andrews, Elisabeth; Balkanski, Yves; Bauer, Susanne E.; Benedictow, Anna Maria Katarina; Bian, Huisheng; Checa-Garcia, Ramiro; Chin, Mian; Ginoux, Paul; Griesfeller, Jan; Heckel, Andreas; Kipling, Zak; Kirkevåg, Alf; Kokkola, Harri; Laj, Paolo G.; Sager, Philippe Le; Lund, Marianne Tronstad; Myhre, Cathrine Lund; Matsui, Hitoshi; Myhre, Gunnar; Neubauer, David; Noije, Twan van; North, Peter; Oliviè, Dirk Jan Leo; Remy, Samuel; Sogacheva, Larisa; Takemura, Toshihiko; Tsigaridis, Kostas; Tsyro, Svetlana

Within the framework of the AeroCom (Aerosol Comparisons between Observations and Models) initiative, the state-of-the-art modelling of aerosol optical properties is assessed from 14 global models participating in the phase III control experiment (AP3). The models are similar to CMIP6/AerChemMIP Earth System Models (ESMs) and provide a robust multi-model ensemble. Inter-model spread of aerosol species lifetimes and emissions appears to be similar to that of mass extinction coefficients (MECs), suggesting that aerosol optical depth (AOD) uncertainties are associated with a broad spectrum of parameterised aerosol processes.
Total AOD is approximately the same as in AeroCom phase I (AP1) simulations. However, we find a 50 % decrease in the optical depth (OD) of black carbon (BC), attributable to a combination of decreased emissions and lifetimes. Relative contributions from sea salt (SS) and dust (DU) have shifted from being approximately equal in AP1 to SS contributing about 2∕3 of the natural AOD in AP3. This shift is linked with a decrease in DU mass burden, a lower DU MEC, and a slight decrease in DU lifetime, suggesting coarser DU particle sizes in AP3 compared to AP1.
Relative to observations, the AP3 ensemble median and most of the participating models underestimate all aerosol optical properties investigated, that is, total AOD as well as fine and coarse AOD (AODf, AODc), Ångström exponent (AE), dry surface scattering (SCdry), and absorption (ACdry) coefficients. Compared to AERONET, the models underestimate total AOD by ca. 21 % ± 20 % (as inferred from the ensemble median and interquartile range). Against satellite data, the ensemble AOD biases range from −37 % (MODIS-Terra) to −16 % (MERGED-FMI, a multi-satellite AOD product), which we explain by differences between individual satellites and AERONET measurements themselves. Correlation coefficients (R) between model and observation AOD records are generally high (R>0.75), suggesting that the models are capable of capturing spatio-temporal variations in AOD. We find a much larger underestimate in coarse AODc (∼ −45 % ± 25 %) than in fine AODf (∼ −15 % ± 25 %) with slightly increased inter-model spread compared to total AOD. These results indicate problems in the modelling of DU and SS. The AODc bias is likely due to missing DU over continental land masses (particularly over the United States, SE Asia, and S. America), while marine AERONET sites and the AATSR SU satellite data suggest more moderate oceanic biases in AODc.
Column AEs are underestimated by about 10 % ± 16 %. For situations in which measurements show AE > 2, models underestimate AERONET AE by ca. 35 %. In contrast, all models (but one) exhibit large overestimates in AE when coarse aerosol dominates (bias ca. +140 % if observed AE < 0.5). Simulated AE does not span the observed AE variability. These results indicate that models overestimate particle size (or underestimate the fine-mode fraction) for fine-dominated aerosol and underestimate size (or overestimate the fine-mode fraction) for coarse-dominated aerosol. This must have implications for lifetime, water uptake, scattering enhancement, and the aerosol radiative effect, which we can not quantify at this moment.
Comparison against Global Atmosphere Watch (GAW) in situ data results in mean bias and inter-model variations of −35 % ± 25 % and −20 % ± 18 % for SCdry and ACdry, respectively. The larger underestimate of SCdry than ACdry suggests the models will simulate an aerosol single scattering albedo that is too low. The larger underestimate of SCdry than ambient air AOD is consistent with recent findings that models overestimate scattering enhancement due to hygroscopic growth. The broadly consistent negative bias in AOD and surface scattering suggests an underestimate of aerosol radiative effects in current global aerosol models.
Considerable ...

2021

Establishment of killer whale (Orcinus orca) primary fibroblast cell cultures and their transcriptomic responses to pollutant exposure

Bjørneset, J.; Blévin, P.; Bjørnstad, P.M.; Dalmo, R.A.; Goksøyr, A.; Harju, M.; Limonta, G.; Panti, C.; Rikardsen, A.H.; Sundaram, A.Y.M.; Yadetie, F.; Routti, H.

Populations of killer whale (Orcinus orca) contain some of the most polluted animals on Earth. Yet, the knowledge on effects of chemical pollutants is limited in this species. Cell cultures and in vitro exposure experiments are pertinent tools to study effects of pollutants in free-ranging marine mammals. To investigate transcriptional responses to pollutants in killer whale cells, we collected skin biopsies of killer whales from the Northern Norwegian fjords and successfully established primary fibroblast cell cultures from the dermis of 4 out of 5 of them. Cells from the individual with the highest cell yield were exposed to three different concentrations of a mixture of persistent organic pollutants (POPs) that reflects the composition of the 10 most abundant POPs found in Norwegian killer whales (p,p’-DDE, trans-nonachlor, PCB52, 99, 101, 118, 138, 153, 180, 187). Transcriptional responses of 13 selected target genes were studied using digital droplet PCR, and whole transcriptome responses were investigated utilizing RNA sequencing. Among the target genes analysed, CYP1A1 was significantly downregulated in the cells exposed to medium (11.6 µM) and high (116 µM) concentrations of the pollutant mixture, while seven genes involved in endocrine functions showed a non-significant tendency to be upregulated at the highest exposure concentration. Bioinformatic analyses of RNA-seq data indicated that 13 and 43 genes were differentially expressed in the cells exposed to low and high concentrations of the mixture, respectively, in comparison to solvent control. Subsequent pathway and functional analyses of the differentially expressed genes indicated that the enriched pathways were mainly related to lipid metabolism, myogenesis and glucocorticoid receptor regulation. The current study results support previous correlative studies and provide cause-effect relationships, which is highly relevant for chemical and environmental management.

2023

SuperDARN Radar Wind Observations of Eastward-Propagating Planetary Waves

Mirzaamin, Tina; Orsolini, Yvan; Espy, Patrick Joseph; Rhodes, Christian Todd

An array of SuperDARN meteor radars at northern high latitudes was used to investigate the sources and characteristics of eastward-propagating planetary waves (EPWs) at 95 km, with a focus on wintertime. The nine radars provided the daily mean meridional winds and their anomalies over 180 degrees of longitude, and these anomalies were separated into eastward and westward waves using a fast Fourier transform (FFT) method to extract the planetary wave components of zonal wavenumbers 1 and 2. Years when a sudden stratospheric warming event with an elevated stratopause (ES-SSW) occurred during the winter were contrasted with years without such events and composited through superposed epoch analysis. The results show that EPWs are a ubiquitous—and unexpected—feature of meridional wind variability near 95 km. Present even in non-ES-SSW years, they display a regular annual cycle peaking in January or February, depending on the zonal wavenumber. In years when an ES-SSW occurred, the EPWs were highly variable but enhanced before and after the onset.

2024

Decitabine potentiates efficacy of doxorubicin in a preclinical trastuzumab-resistant HER2-positive breast cancer models

Buociková, Verona; Longhin, Eleonora Marta; Pilalis, Eleftherios; Mastrokalou, Chara; Miklíková, Svetlana; Cihova, Marina; Poturnayova, Alexandra; Mackova, Katarina; Bábelová, Andrea; Trnkova, Lenka; Yamani, Naouale El; Zheng, Congying; Mondragon, Ivan Rios; Labudova, Martina; Csaderova, Lucia; Kuracinova, Kristina Mikus; Makovicky, Peter; Kučerová, Lucia; Matuskova, Miroslava; Cimpan, Mihaela-Roxana; Dusinska, Maria; Babal, Pavel; Chatziioannou, Aristotelis; Gábelová, Alena; Rundén-Pran, Elise; Smolkova, Bozena

Acquired drug resistance and metastasis in breast cancer (BC) are coupled with epigenetic deregulation of gene expression. Epigenetic drugs, aiming to reverse these aberrant transcriptional patterns and sensitize cancer cells to other therapies, provide a new treatment strategy for drug-resistant tumors. Here we investigated the ability of DNA methyltransferase (DNMT) inhibitor decitabine (DAC) to increase the sensitivity of BC cells to anthracycline antibiotic doxorubicin (DOX). Three cell lines representing different molecular BC subtypes, JIMT-1, MDA-MB-231 and T-47D, were used to evaluate the synergy of sequential DAC + DOX treatment in vitro. The cytotoxicity, genotoxicity, apoptosis, and migration capacity were tested in 2D and 3D cultures. Moreover, genome-wide DNA methylation and transcriptomic analyses were employed to understand the differences underlying DAC responsiveness. The ability of DAC to sensitize trastuzumab-resistant HER2-positive JIMT-1 cells to DOX was examined in vivo in an orthotopic xenograft mouse model. DAC and DOX synergistic effect was identified in all tested cell lines, with JIMT-1 cells being most sensitive to DAC. Based on the whole-genome data, we assume that the aggressive behavior of JIMT-1 cells can be related to the enrichment of epithelial-to-mesenchymal transition and stemness-associated pathways in this cell line. The four-week DAC + DOX sequential administration significantly reduced the tumor growth, DNMT1 expression, and global DNA methylation in xenograft tissues. The efficacy of combination therapy was comparable to effect of pegylated liposomal DOX, used exclusively for the treatment of metastatic BC. This work demonstrates the potential of epigenetic drugs to modulate cancer cells' sensitivity to other forms of anticancer therapy.

2022

Modified Target Diagram to check compliance of low-cost sensors with the Data Quality Objectives of the European air quality directive

Yatkin, Sinan; Gerboles, Michel; Borowiak, Annette; Davila, Silvije; Spinelle, Laurent; Bartonova, Alena; Dauge, Franck Rene; Schneider, Philipp; Poppel, Martine Van; Peters, Jan; Matheeussen, Christina; Signorini, Marco

The modified Target Diagram (MTD) was developed to evaluate the performance of low-cost sensors (LCS) for air quality monitoring in comparison with reference methods by reporting relative expanded uncertainty and its contributors. An MTD provides several pieces of information, including compliance with regulation, sources of error and how to diminish them, completeness and validity of LCS calibration etc. It allows the user to examine the effect of selecting different regression types and residual fitting on the LCS measurement uncertainty. The ordinary least squared regression with fitted residuals and dynamic between reference analyser uncertainty rather than constant ones yielded more realistic LCS measurement uncertainty compared to other options. The MTD is a fast visual tool to extract several pieces of information on evaluation of any candidate method against reference method.

2022

A satellite-based estimate of combustion aerosol cloud microphysical effects over the Arctic Ocean

Zamora, Lauren M; Kahn, Ralph A.; Huebert, Klaus B; Stohl, Andreas; Eckhardt, Sabine

Climate predictions for the rapidly changing Arctic are highly uncertain, largely due to a poor understanding of the processes driving cloud properties. In particular, cloud fraction (CF) and cloud phase (CP) have major impacts on energy budgets, but are poorly represented in most models, often because of uncertainties in aerosol–cloud interactions. Here, we use over 10 million satellite observations coupled with aerosol transport model simulations to quantify large-scale microphysical effects of aerosols on CF and CP over the Arctic Ocean during polar night, when direct and semi-direct aerosol effects are minimal. Combustion aerosols over sea ice are associated with very large (∼ 10Wm−2) differences in longwave cloud radiative effects at the sea ice surface. However, co-varying meteorological changes on factors such as CF likely explain the majority of this signal. For example, combustion aerosols explain at most 40% of the CF differences between the full dataset and the clean-condition subset, compared to between 57% and 91% of the differences that can be predicted by co-varying meteorology. After normalizing for meteorological regime, aerosol microphysical effects have small but significant impacts on CF, CP, and precipitation frequency on an Arctic-wide scale. These effects indicate that dominant aerosol–cloud microphysical mechanisms are related to the relative fraction of liquid-containing clouds, with implications for a warming Arctic.

2018

Zurich statement on future actions on per-and polyfluoroalkyl substances (PFASs)

Ritscher, Amélie; Wang, Zhanyun; Scheringer, Martin; Boucher, Justin M.; Ahrens, Lutz; Berger, Urs; Bintein, Sylvain; Bopp, Stephanie K.; Borg, Daniel; Buser, Andreas M.; Cousins, Ian; DeWitt, Jamie; Fletcher, Tony; Green, Christopher; Herzke, Dorte; Higgins, Christopher; Huang, Jun; Hung, Hayley; Knepper, Thomas; Lau, Christopher S.; Leinala, Eeva; Lindstrom, Andrew B.; Liu, Jinxia; Miller, Mark; Ohno, Koichi; Perkola, Noora; Shi, Yali; Haug, Line Småstuen; Trier, Xenia; Valsecchi, Sara; Jagt, Katinka van der; Vierke, Lena

Per- and polyfluoroalkyl substances (PFASs) are man-made chemicals that contain at least one perfluoroalkyl moiety, –CnF2n–. To date, over 4,000 unique PFASs have been used in technical applications and consumer products, and some of them have been detected globally in human and wildlife biomonitoring studies. Because of their extraordinary persistence, human and environmental exposure to PFASs will be a long-term source of concern. Some PFASs such as perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) have been investigated extensively and thus regulated, but for many other PFASs, knowledge about their current uses and hazards is still very limited or missing entirely. To address this problem and prepare an action plan for the assessment and management of PFASs in the coming years, a group of more than 50 international scientists and regulators held a two-day workshop in November, 2017. The group identified both the respective needs of and common goals shared by the scientific and the policy communities, made recommendations for cooperative actions, and outlined how the science–policy interface regarding PFASs can be strengthened using new approaches for assessing and managing highly persistent chemicals such as PFASs.

2018

Plastic ingestion and associated additives in Faroe Islands chicks of the Northern Fulmar Fulmarus glacialis

Collard, France; Leconte, Simon; Danielsen, Jóhannis; Halsband, Claudia; Herzke, Dorte; Harju, Mikael; Tulatz, Felix; Gabrielsen, Geir Wing; Tarroux, Arnaud

Northern Fulmars (Fulmarus glacialis) are a pelagic seabird species distributed at northern and polar latitudes. They are often used as an indicator of plastic pollution in the North Sea region, but data are lacking from higher latitudes, especially when it comes to chicks. Here, we investigated amounts of ingested plastic and their characteristics in fulmar chicks from the Faroe Islands. Plastic particles (≥1 ​mm) in chicks of two age classes were searched using a digestion method with KOH. In addition, to evaluate if additive tissue burden reflects plastic ingestion, we measured liver tissue concentrations of two pollutant classes associated with plastic materials: polybrominated diphenyl ethers (PBDEs) and several dechloranes, using gas chromatography with high-resolution mass spectrometry. The most common shape was hard fragment (81%) and the most common polymer was polyethylene (73%). Plastic contamination did not differ between either age class, and we found no correlation between neither the amount and mass of plastic particles and the concentration of additives. After comparison with previous studies on adult fulmars, we do not recommend using chicks for biomonitoring adults because chicks seem to ingest more plastics than adults.

2022

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