Fant 787 publikasjoner. Viser side 12 av 33:
Frontiers Media S.A.
2022
For the next-generation risk assessment (NGRA) of chemicals and nanomaterials, new approach methodologies (NAMs) are needed for hazard assessment in compliance with the 3R’s to reduce, replace and refine animal experiments. This study aimed to establish and characterize an advanced respiratory model consisting of human epithelial bronchial BEAS-2B cells cultivated at the air–liquid interface (ALI), both as monocultures and in cocultures with human endothelial EA.hy926 cells. The performance of the bronchial models was compared to a commonly used alveolar model consisting of A549 in monoculture and in coculture with EA.hy926 cells. The cells were exposed at the ALI to nanosilver (NM-300K) in the VITROCELL® Cloud. After 24 h, cellular viability (alamarBlue assay), inflammatory response (enzyme-linked immunosorbent assay), DNA damage (enzyme-modified comet assay), and chromosomal damage (cytokinesis-block micronucleus assay) were measured. Cytotoxicity and genotoxicity induced by NM-300K were dependent on both the cell types and model, where BEAS-2B in monocultures had the highest sensitivity in terms of cell viability and DNA strand breaks. This study indicates that the four ALI lung models have different sensitivities to NM-300K exposure and brings important knowledge for the further development of advanced 3D respiratory in vitro models for the most reliable human hazard assessment based on NAMs.
MDPI
2023
2023
Arctic tropospheric ozone: assessment of current knowledge and model performance
As the third most important greenhouse gas (GHG) after carbon dioxide (CO2) and methane (CH4), tropospheric ozone (O3) is also an air pollutant causing damage to human health and ecosystems. This study brings together recent research on observations and modeling of tropospheric O3 in the Arctic, a rapidly warming and sensitive environment. At different locations in the Arctic, the observed surface O3 seasonal cycles are quite different. Coastal Arctic locations, for example, have a minimum in the springtime due to O3 depletion events resulting from surface bromine chemistry. In contrast, other Arctic locations have a maximum in the spring. The 12 state-of-the-art models used in this study lack the surface halogen chemistry needed to simulate coastal Arctic surface O3 depletion in the springtime; however, the multi-model median (MMM) has accurate seasonal cycles at non-coastal Arctic locations. There is a large amount of variability among models, which has been previously reported, and we show that there continues to be no convergence among models or improved accuracy in simulating tropospheric O3 and its precursor species. The MMM underestimates Arctic surface O3 by 5 % to 15 % depending on the location. The vertical distribution of tropospheric O3 is studied from recent ozonesonde measurements and the models. The models are highly variable, simulating free-tropospheric O3 within a range of ±50 % depending on the model and the altitude. The MMM performs best, within ±8 % for most locations and seasons. However, nearly all models overestimate O3 near the tropopause (∼300 hPa or ∼8 km), likely due to ongoing issues with underestimating the altitude of the tropopause and excessive downward transport of stratospheric O3 at high latitudes. For example, the MMM is biased high by about 20 % at Eureka. Observed and simulated O3 precursors (CO, NOx, and reservoir PAN) are evaluated throughout the troposphere. Models underestimate wintertime CO everywhere, likely due to a combination of underestimating CO emissions and possibly overestimating OH. Throughout the vertical profile (compared to aircraft measurements), the MMM underestimates both CO and NOx but overestimates PAN. Perhaps as a result of competing deficiencies, the MMM O3 matches the observed O3 reasonably well. Our findings suggest that despite model updates over the last decade, model results are as highly variable as ever and have not increased in accuracy for representing Arctic tropospheric O3.
2023
Spatial distribution of Dechlorane Plus and dechlorane related compounds in European background air
The highly chlorinated chemical Dechlorane Plus (DP) was introduced as a replacement flame retardant for Mirex, which is banned through the Stockholm Convention (SC) for its toxicity (T), environmental persistence (P), potential for bioaccumulation (B) and long-range environmental transport potential (LRETP). Currently, Dechlorane Plus is under consideration for listing under the Stockholm Convention and by the European Chemical Agency as it is suspected to also have potential for P, B, T and LRET. Knowledge of atmospheric concentrations of chemicals in background regions is vital to understand their persistence and long-range atmospheric transport but such knowledge is still limited for Dechlorane Plus. Also, knowledge on environmental occurrence of the less described Dechlorane Related Compounds (DRCs), with similar properties and uses as Dechlorane Plus, is limited. Hence, the main objective of this study was to carry out a spatial mapping of atmospheric concentrations of Dechlorane Plus and Dechlorane Related Compounds at background sites in Europe. Polyurethane foam passive air samplers were deployed at 99 sites across 33 European countries for 3 months in summer 2016 and analyzed for dechloranes. The study showed that syn- and anti-DP are present across the European continent...
Frontiers Media S.A.
2023
The 2021 East Asia sandstorm began from the Eastern Gobi desert steppe in Mongolia on March 14, and later spread to northern China and the Korean Peninsula. It was the biggest sandstorm to hit China in a decade, causing severe air pollution and a significant threat to human health. Capturing and predicting such extreme events is critical for society. The Lagrangian particle dispersion model FLEXPART and the associated dust emission model FLEXDUST have been recently developed and applied to simulate global dust cycles. However, how well the model captures Asian dust storm events remains to be explored. In this study, we applied FLEXPART to simulate the recent 2021 East Asia sandstorm, and evaluated its performance comparing with observation and observation-constrained reanalysis datasets, such as the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and CAMS global atmospheric composition forecasts (CAMS-F). We found that the default setting of FLEXDUST substantially underestimates the strength of dust emission and FLEXPART modelled dust concentration in this storm compared to that in MERRA-2 and CAMS-F. An improvement of the parametrization of bare soil fraction, topographical scaling, threshold friction velocity and vertical dust flux scheme based on Kok et al. (Atmospheric Chemistry and Physics, 2014, 14, 13023–13041) in FLEXDUST can reproduce the strength and spatio-temporal pattern of the dust storm comparable to MERRA-2 and CAMS-F. However, it still underestimates the observed spike of dust concentration during the dust storm event over northern China, and requires further improvement in the future. The improved FLEXDUST and FLEXPART perform better than MERRA-2 and CAMS-F in capturing the observed particle size distribution of dust aerosols, highlighting the importance of using more dust size bins and size-dependent parameterization for dust emission, and dry and wet deposition schemes for modelling the Asian dust cycle and its climatic feedbacks.
Frontiers Media S.A.
2023
Based upon the thermodynamic simulation of a biogas-SOFC integrated process and the costing of its elements, the present work examines the economic feasibility of biogas-SOFCs for combined heat and power (CHP) generation, by the comparison of their economic performance against the conventional biogas-CHP with internal combustion engines (ICEs), under the same assumptions. As well as the issues of process scale and an SOFC’s cost, examined in the literature, the study brings up the determinative effects of: (i) the employed SOFC size, with respect to its operational point, as well as (ii) the feasibility criterion, on the feasibility assessment. Two plant capacities were examined (250 m3·h−1 and 750 m3·h−1 biogas production), and their feasibilities were assessed by the Internal Rate of Return (IRR), the Net Present Value (NPV) and the Pay Back Time (PBT) criteria. For SOFC costs at 1100 and 2000 EUR·kWel−1, foreseen in 2035 and 2030, respectively, SOFCs were found to increase investment (by 2.5–4.5 times, depending upon a plant’s capacity and the SOFC’s size) and power generation (by 13–57%, depending upon the SOFC’s size), the latter increasing revenues. SOFC-CHP exhibits considerably lower IRRs (5.3–13.4% for the small and 16.8–25.3% for the larger plant), compared to ICE-CHP (34.4%). Nonetheless, according to NPV that does not evaluate profitability as a return on investment, small scale biogas-SOFCs (NPVmax: EUR 3.07 M) can compete with biogas-ICE (NPV: EUR 3.42 M), for SOFCs sized to operate at 70% of the maximum power density (MPD) and with a SOFC cost of 1100 EUR·kWel−1, whereas for larger plants, SOFC-CHP can lead to considerably higher NPVs (EUR 12.5–21.0 M) compared to biogas-ICE (EUR 9.3 M). Nonetheless, PBTs are higher for SOFC-CHP (7.7–11.1 yr and 4.2–5.7 yr for the small and the large plant, respectively, compared to 2.3 yr and 3.1 yr for biogas-ICE) because the criterion suppresses the effect of SOFC-CHP-increased revenues to a time period shorter than the plant’s lifetime. Finally, the economics of SOFC-CHP are optimized for SOFCs sized to operate at 70–82.5% of their MPD, depending upon the SOFC cost and the feasibility criterion. Overall, the choice of the feasibility criterion and the size of the employed SOFC can drastically affect the economic evaluation of SOFC-CHP, whereas the feasibility criterion also determines the economically optimum size of the employed SOFC.
MDPI
2022
Low trophic species are often mentioned as additional food sources to achieve broader and more sustainable utilisation of the ocean. The aim of this study was to map the food potential of Norwegian orange-footed sea cucumber (Cucumaria frondosa). C. frondosa contained 7% protein, 1% lipids with a high proportion of polyunsaturated fatty acids, and a variety of micronutrients. The nutrient density scores (NDS) of C. frondosa were above average compared towards daily recommended intakes (DRI) for men and women (age 31–60) but below when capped at 100% of DRI. The concentrations of persistent organic pollutants and trace elements were in general low, except for inorganic arsenic (iAs) (0.73 mg per kg) which exceeded the limits deemed safe by food authorities. However, the small number of samples analysed for iAs lowers the ability to draw a firm conclusion. The carbon footprint from a value chain with a dredge fishery, processing in Norway and retail in Asia was assessed to 8 kg carbon dioxide equivalent (CO2eq.) per kg C. frondosa, the fishery causing 90%. Although, C. frondosa has some nutritional benefits, the carbon footprint or possible content of iAs may restrict the consumption.
MDPI
2022
Inferring surface energy fluxes using drone data assimilation in large eddy simulations
Spatially representative estimates of surface energy exchange from field measurements are required for improving and validating Earth system models and satellite remote sensing algorithms. The scarcity of flux measurements can limit understanding of ecohydrological responses to climate warming, especially in remote regions with limited infrastructure. Direct field measurements often apply the eddy covariance method on stationary towers, but recently, drone-based measurements of temperature, humidity, and wind speed have been suggested as a viable alternative to quantify the turbulent fluxes of sensible (H) and latent heat (LE). A data assimilation framework to infer uncertainty-aware surface flux estimates from sparse and noisy drone-based observations is developed and tested using a turbulence-resolving large eddy simulation (LES) as a forward model to connect surface fluxes to drone observations. The proposed framework explicitly represents the sequential collection of drone data, accounts for sensor noise, includes uncertainty in boundary and initial conditions, and jointly estimates the posterior distribution of a multivariate parameter space. Assuming typical flight times and observational errors of light-weight, multi-rotor drone systems, we first evaluate the information gain and performance of different ensemble-based data assimilation schemes in experiments with synthetically generated observations. It is shown that an iterative ensemble smoother outperforms both the non-iterative ensemble smoother and the particle batch smoother in the given problem, yielding well-calibrated posterior uncertainty with continuous ranked probability scores of 12 W m−2 for both H and LE, with standard deviations of 37 W m−2 (H) and 46 W m−2 (LE) for a 12 min vertical step profile by a single drone. Increasing flight times, using observations from multiple drones, and further narrowing the prior distributions of the initial conditions are viable for reducing the posterior spread. Sampling strategies prioritizing space–time exploration without temporal averaging, instead of hovering at fixed locations while averaging, enhance the non-linearities in the forward model and can lead to biased flux results with ensemble-based assimilation schemes. In a set of 18 real-world field experiments at two wetland sites in Norway, drone data assimilation estimates agree with independent eddy covariance estimates, with root mean square error values of 37 W m−2 (H), 52 W m−2 (LE), and 58 W m−2 (H+LE) and correlation coefficients of 0.90 (H), 0.40 (LE), and 0.83 (H+LE). While this comparison uses the simplifying assumptions of flux homogeneity, stationarity, and flat terrain, it is emphasized that the drone data assimilation framework is not confined to these assumptions and can thus readily be extended to more complex cases and other scalar fluxes, such as for trace gases in future studies.
2022
Wetland emission and atmospheric sink changes explain methane growth in 2020
Atmospheric methane growth reached an exceptionally high rate of 15.1 ± 0.4 parts per billion per year in 2020 despite a probable decrease in anthropogenic methane emissions during COVID-19 lockdowns. Here we quantify changes in methane sources and in its atmospheric sink in 2020 compared with 2019. We find that, globally, total anthropogenic emissions decreased by 1.2 ± 0.1 teragrams of methane per year (Tg CH4 yr−1), fire emissions decreased by 6.5 ± 0.1 Tg CH4 yr−1 and wetland emissions increased by 6.0 ± 2.3 Tg CH4 yr−1. Tropospheric OH concentration decreased by 1.6 ± 0.2 per cent relative to 2019, mainly as a result of lower anthropogenic nitrogen oxide (NOx) emissions and associated lower free tropospheric ozone during pandemic lockdowns. From atmospheric inversions, we also infer that global net emissions increased by 6.9 ± 2.1 Tg CH4 yr−1 in 2020 relative to 2019, and global methane removal from reaction with OH decreased by 7.5 ± 0.8 Tg CH4 yr−1. Therefore, we attribute the methane growth rate anomaly in 2020 relative to 2019 to lower OH sink (53 ± 10 per cent) and higher natural emissions (47 ± 16 per cent), mostly from wetlands. In line with previous findings, our results imply that wetland methane emissions are sensitive to a warmer and wetter climate and could act as a positive feedback mechanism in the future. Our study also suggests that nitrogen oxide emission trends need to be taken into account when implementing the global anthropogenic methane emissions reduction pledge.
2022
Impacts of snow assimilation on seasonal snow and meteorological forecasts for the Tibetan Plateau
The Tibetan Plateau (TP) contains the largest amount of snow outside the polar regions and is the source of many major rivers in Asia. An accurate long-range (i.e. seasonal) meteorological forecast is of great importance for this region. The fifth-generation seasonal forecast system of the European Centre for Medium-Range Weather Forecasts (SEAS5) provides global long-range meteorological forecasts including over the TP. However, SEAS5 uses land initial conditions produced by assimilating Interactive Multisensor Snow and Ice Mapping System (IMS) snow data only below 1500 m altitude, which may affect the forecast skill of SEAS5 over mountainous regions like the TP. To investigate the impacts of snow assimilation on the forecasts of snow, temperature and precipitation, twin ensemble reforecasts are initialized with and without snow assimilation above 1500 m altitude over the TP for spring and summer 2018. Significant changes occur in the springtime. Without snow assimilation, the reforecasts overestimate snow cover and snow depth while underestimating daily temperature over the TP. Compared to satellite-based estimates, precipitation reforecasts perform better in the west TP (WTP) than in the east TP (ETP). With snow assimilation, the reforecasts of snow cover, snow depth and temperature are consistently improved in the TP in the spring. However, the positive bias between the precipitation reforecasts and satellite observations worsens in the ETP. Compared to the experiment with no snow assimilation, the snow assimilation experiment significantly increases temperature and precipitation for the ETP and around the longitude 95∘ E. The higher temperature after snow assimilation, in particular the cold bias reduction after initialization, can be attributed to the effects of a more realistic, decreased snowpack, providing favourable conditions for generating more precipitation. Overall, snow assimilation can improve seasonal forecasts through the interaction between land and atmosphere.
2022
Genotoxic effects of occupational exposure to glass fibres - A human biomonitoring study.
As part of a large human biomonitoring study, we conducted occupational monitoring in a glass fibre factory in Slovakia. Shopfloor workers (n = 80), with a matched group of administrators in the same factory (n = 36), were monitored for exposure to glass fibres and to polycyclic aromatic hydrocarbons (PAHs). The impact of occupational exposure on chromosomal aberrations, DNA damage and DNA repair, immunomodulatory markers, and the role of nutritional and lifestyle factors, as well as the effect of polymorphisms in metabolic and DNA repair genes on genetic stability, were investigated.
The (enzyme-modified) comet assay was employed to measure DNA strand breaks (SBs) and apurinic sites, oxidised and alkylated bases. Antioxidant status was estimated by resistance to H2O2-induced DNA damage. Base excision repair capacity was measured with an in vitro assay (based on the comet assay).
Exposure of workers to fibres was low, but still was associated with higher levels of SBs, and SBs plus oxidised bases, and higher sensitivity to H2O2. Multivariate analysis showed that exposure increased the risk of high levels of SBs by 20%. DNA damage was influenced by antioxidant enzymes catalase and glutathione S-transferase (measured in blood). DNA repair capacity was inversely correlated with DNA damage and positively with antioxidant status. An inverse correlation was found between DNA base oxidation and the percentage of eosinophils (involved in the inflammatory response) in peripheral blood of both exposed and reference groups. Genotypes of XRCC1 variants rs3213245 and rs25487 significantly decreased the risk of high levels of base oxidation, to 0.50 (p = 0.001) and 0.59 (p = 0.001), respectively.
Increases in DNA damage owing to glass fibre exposure were significant but modest, and no increases were seen in chromosome aberrations or micronuclei. However, it is of concern that even low levels of exposure to these fibres can cause significant genetic damage.
2023
Using the example of sulfur hexafluoride (SF6), we investigate the use of Lagrangian particle dispersion models (LPDMs) for inverse modeling of greenhouse gas (GHG) emissions and explore the limitations of this approach. We put the main focus on the impacts of baseline methods and the LPDM backward simulation period on the a posteriori emissions determined by the inversion. We consider baseline methods that are based on a statistical selection of observations at individual measurement sites and a global-distribution-based (GDB) approach, where global mixing ratio fields are coupled to the LPDM back-trajectories at their termination points. We show that purely statistical baseline methods can cause large systematic errors, which lead to inversion results that are sensitive to the LPDM backward simulation period and can generate unrealistic global total a posteriori emissions. The GDB method produces a posteriori emissions that are far less sensitive to the backward simulation period and that show a better agreement with recognized global total emissions. Our results show that longer backward simulation periods, beyond the often used 5 to 10 d, reduce the mean squared error and increase the correlation between a priori modeled and observed mixing ratios. Also, the inversion becomes less sensitive to biases in the a priori emissions and the global mixing ratio fields for longer backward simulation periods. Further, longer periods might help to better constrain emissions in regions poorly covered by the global SF6 monitoring network. We find that the inclusion of existing flask measurements in the inversion helps to further close these gaps and suggest that a few additional and well-placed flask sampling sites would have great value for improving global a posteriori emission fields.
2022
High-Resolution Emissions from Wood Burning in Norway—The Effect of Cabin Emissions
Emissions from wood burning for heating in secondary homes or cabins is an important part in the development of high-resolution emissions in specific areas. Norway is used as case study as 20% of the national wood consumption for heating occurs in cabins. Our study first shows a method to estimate emissions from cabins based on traffic data to derive cabin occupancy, which combined with heating need allows for the spatial and temporal distribution of emissions. The combination of residential (RWC) and cabin wood combustion (CWC) emissions shows large spatial and temporal differences, and a temporally “cabin population” can in areas be orders of magnitude larger than the registered population. While RWC emissions have been steadily reduced, CWC have kept relatively constant or even increased, which results in an increase in the cabin share to total heating emissions up to 25–35%. When comparing with regional emission inventories, our study shows that the gradient between rural and urban areas is not well-represented in regional inventories, which resembles a population-based distribution and does not allocate emissions in cabin municipalities. CWC emissions may become an increasing environmental concern as higher densification trends in mountain areas are observed.
MDPI
2022
Total oxidizable precursors assay for PFAS in human serum
Per- and polyfluoroalkyl substances (PFAS) are a class of chemicals including over 4700 substances. As a limited number of PFAS is routinely analyzed in human serum, complementary analytical methods are required to characterize the overlooked fraction. A promising tool is the total oxidizable precursors (TOP) assay to look for precursors by oxidation to perfluoroalkyl acids (PFAA). The TOP assay was originally developed for large volumes of water and had to be adapted for 250 μL of human serum. Optimization of the method was performed on serum samples spiked with model precursors. Oxidative conditions similar to previous TOP assay methods were not sufficient for complete oxidation of model precursors. Prolonged heating time (24 h) and higher oxidant amount (95 mg of Na2S2O8 per 225 μL of serum) were needed for complete conversion of the model precursors and accomplishing PFAA yields of 35–100 %. As some precursors are not fully converted to PFAA, the TOP assay can only provide semi-quantitative estimates of oxidizable precursors in human serum. However, the TOP assay can be used to give indications about the identity of unknown precursors by evaluating the oxidation products, including perfluoroalkyl sulfonic acids (PFSA) and perfluoroalkyl ether carboxylic acids (PFECA). The optimized TOP assay for human serum opens the possibility for high-throughput screening of human serum for undetected PFAA precursors.
Elsevier
2022
With the current possible presence of thousands of PFAS compounds in industrial emissions, there is an increasing need to assess the impacts of PFAS regulation of conventional PFAS on one hand and the exposure to emerging and yet unknown PFAS on the other. Today’s analytical methodologies using targeted approaches are not sufficient to determine the complete suite of PFAS present. To evaluate the presence of unknown PFAS, we investigated in this study the occurrence of an extended range of target PFAS in various species from the marine and terrestrial Norwegian environment, in relation to the extractable organic fluorine (EOF), which yields the total amount of organic fluorine. The results showed a varying presence of extractable fluorinated organics, with glaucous gull eggs, otter liver and polar bear plasma showing the highest EOF and a high abundance of PFAS as well. The targeted PFAS measurements explained 1% of the organic fluorine for moose liver as the lowest and 94% for otter liver as the highest. PFCAs like trifluoro acetic acid (TFA, reported semi-quantitatively), played a major role in explaining the organic fluorine present. Emerging PFAS as the perfluoroethylcyclohexane sulfonate (PFECHS), was found in polar bear plasma in quantifiable amounts for the first time, confirming earlier detection in arctic species far removed from emission sources. To enable a complete organic fluorine mass balance in wildlife, new approaches are needed, to uncover the presence of new emerging PFAS as cyclic- or ether PFAS together with chlorinated PFAS as well as fluorinated organic pesticides and pharmaceuticals.
Elsevier
2022
A freely available “in vitro dosimetry” web application is presented enabling users to predict the concentration of nanomaterials reaching the cell surface, and therefore available for attachment and internalization, from initial dispersion concentrations. The web application is based on the distorted grid (DG) model for the dispersion of engineered nanoparticles (NPs) in culture medium used for in vitro cellular experiments, in accordance with previously published protocols for cellular dosimetry determination. A series of in vitro experiments for six different NPs, with Ag and Au cores, are performed to demonstrate the convenience of the web application for calculation of exposure concentrations of NPs. Our results show that the exposure concentrations at the cell surface can be more than 30 times higher compared to the nominal or dispersed concentrations, depending on the NPs’ properties and their behavior in the cell culture medium. Therefore, the importance of calculating the exposure concentration at the bottom of the cell culture wells used for in vitro arrays, i.e., the particle concentration at the cell surface, is clearly presented, and the tool introduced here allows users easy access to such calculations. Widespread application of this web tool will increase the reliability of subsequent toxicity data, allowing improved correlation of the real exposure concentration with the observed toxicity, enabling the hazard potentials of different NPs to be compared on a more robust basis.
MDPI
2022
2022
Plastic burdens in northern fulmars from Svalbard: looking back 25 years
The northern fulmar Fulmarus glacialis ingests a larger number of (micro)plastics than many other seabirds due to its feeding habits and gut morphology. Since 2002, they are bioindicators of marine plastics in the North Sea region, and data are needed to extend the programme to other parts of their distribution areas, such as the Arctic. In this study, we provide data on ingested plastics by fulmars collected in 1997 in Kongsfjorden, Svalbard. An extraction protocol with KOH was used and for half of the birds, the gizzard and the proventricular contents were analysed separately. Ninety-one percent of the birds had ingested at least one piece of plastic with an average of 10.3 (±11.9 SD) pieces. The gizzards contained significantly more plastics than the proventriculus. Hard fragments and polyethylene were the most common characteristics. Twelve percent of the birds exceeded the EcoQO value of 0.1 g.
Elsevier
2022
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
Comparison of particle number size distribution trends in ground measurements and climate models
Despite a large number of studies, out of all drivers of radiative forcing, the effect of aerosols has the largest uncertainty in global climate model radiative forcing estimates. There have been studies of aerosol optical properties in climate models, but the effects of particle number size distribution need a more thorough inspection. We investigated the trends and seasonality of particle number concentrations in nucleation, Aitken, and accumulation modes at 21 measurement sites in Europe and the Arctic. For 13 of those sites, with longer measurement time series, we compared the field observations with the results from five climate models, namely EC-Earth3, ECHAM-M7, ECHAM-SALSA, NorESM1.2, and UKESM1. This is the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five earth system models (ESMs). We found that the trends of particle number concentrations were mostly consistent and decreasing in both measurements and models. However, for many sites, climate models showed weaker decreasing trends than the measurements. Seasonal variability in measured number concentrations, quantified by the ratio between maximum and minimum monthly number concentration, was typically stronger at northern measurement sites compared to other locations. Models had large differences in their seasonal representation, and they can be roughly divided into two categories: for EC-Earth and NorESM, the seasonal cycle was relatively similar for all sites, and for other models the pattern of seasonality varied between northern and southern sites. In addition, the variability in concentrations across sites varied between models, some having relatively similar concentrations for all sites, whereas others showed clear differences in concentrations between remote and urban sites. To conclude, although all of the model simulations had identical input data to describe anthropogenic mass emissions, trends in differently sized particles vary among the models due to assumptions in emission sizes and differences in how models treat size-dependent aerosol processes. The inter-model variability was largest in the accumulation mode, i.e. sizes which have implications for aerosol–cloud interactions. Our analysis also indicates that between models there is a large variation in efficiency of long-range transportation of aerosols to remote locations. The differences in model results are most likely due to the more complex effect of different processes instead of one specific feature (e.g. the representation of aerosol or emission size distributions). Hence, a more detailed characterization of microphysical processes and deposition processes affecting the long-range transport is needed to understand the model variability.
2022
An actionable annotation scoring framework for gas chromatography-high-resolution mass spectrometry
Omics-based technologies have enabled comprehensive characterization of our exposure to environmental chemicals (chemical exposome) as well as assessment of the corresponding biological responses at the molecular level (eg, metabolome, lipidome, proteome, and genome). By systematically measuring personal exposures and linking these stimuli to biological perturbations, researchers can determine specific chemical exposures of concern, identify mechanisms and biomarkers of toxicity, and design interventions to reduce exposures. However, further advancement of metabolomics and exposomics approaches is limited by a lack of standardization and approaches for assigning confidence to chemical annotations. While a wealth of chemical data is generated by gas chromatography high-resolution mass spectrometry (GC-HRMS), incorporating GC-HRMS data into an annotation framework and communicating confidence in these assignments is challenging. It is essential to be able to compare chemical data for exposomics studies across platforms to build upon prior knowledge and advance the technology. Here, we discuss the major pieces of evidence provided by common GC-HRMS workflows, including retention time and retention index, electron ionization, positive chemical ionization, electron capture negative ionization, and atmospheric pressure chemical ionization spectral matching, molecular ion, accurate mass, isotopic patterns, database occurrence, and occurrence in blanks. We then provide a qualitative framework for incorporating these various lines of evidence for communicating confidence in GC-HRMS data by adapting the Schymanski scoring schema developed for reporting confidence levels by liquid chromatography HRMS (LC-HRMS). Validation of our framework is presented using standards spiked in plasma, and confident annotations in outdoor and indoor air samples, showing a false-positive rate of 12% for suspect screening for chemical identifications assigned as Level 2 (when structurally similar isomers are not considered false positives). This framework is easily adaptable to various workflows and provides a concise means to communicate confidence in annotations. Further validation, refinements, and adoption of this framework will ideally lead to harmonization across the field, helping to improve the quality and interpretability of compound annotations obtained in GC-HRMS.
Oxford University Press
2022
The miniaturized enzyme-modified comet assay for genotoxicity testing of nanomaterials
The in vitro comet assay is a widely applied method for investigating genotoxicity of chemicals including engineered nanomaterials (NMs). A big challenge in hazard assessment of NMs is possible interference between the NMs and reagents or read-out of the test assay, leading to a risk of biased results. Here, we describe both the standard alkaline version of the in vitro comet assay with 12 mini-gels per slide for detection of DNA strand breaks and the enzyme-modified version that allows detection of oxidized DNA bases by applying lesion-specific endonucleases (e.g., formamidopyrimidine DNA glycosylase or endonuclease III). We highlight critical points that need to be taken into consideration when assessing the genotoxicity of NMs, as well as basic methodological considerations, such as the importance of carrying out physicochemical characterization of the NMs and investigating uptake and cytotoxicity. Also, experimental design—including treatment conditions, cell number, cell culture, format and volume of medium on the plate—is crucial and can have an impact on the results, especially when testing NMs. Toxicity of NMs depends upon physicochemical properties that change depending on the environment. To facilitate testing of numerous NMs with distinct modifications, the higher throughput miniaturized version of the comet assay is essential.
Frontiers Media S.A.
2022
Background
The NORMAN Association (https://www.norman-network.com/) initiated the NORMAN Suspect List Exchange (NORMAN-SLE; https://www.norman-network.com/nds/SLE/) in 2015, following the NORMAN collaborative trial on non-target screening of environmental water samples by mass spectrometry. Since then, this exchange of information on chemicals that are expected to occur in the environment, along with the accompanying expert knowledge and references, has become a valuable knowledge base for “suspect screening” lists. The NORMAN-SLE now serves as a FAIR (Findable, Accessible, Interoperable, Reusable) chemical information resource worldwide.
Results
The NORMAN-SLE contains 99 separate suspect list collections (as of May 2022) from over 70 contributors around the world, totalling over 100,000 unique substances. The substance classes include per- and polyfluoroalkyl substances (PFAS), pharmaceuticals, pesticides, natural toxins, high production volume substances covered under the European REACH regulation (EC: 1272/2008), priority contaminants of emerging concern (CECs) and regulatory lists from NORMAN partners. Several lists focus on transformation products (TPs) and complex features detected in the environment with various levels of provenance and structural information. Each list is available for separate download. The merged, curated collection is also available as the NORMAN Substance Database (NORMAN SusDat). Both the NORMAN-SLE and NORMAN SusDat are integrated within the NORMAN Database System (NDS). The individual NORMAN-SLE lists receive digital object identifiers (DOIs) and traceable versioning via a Zenodo community (https://zenodo.org/communities/norman-sle), with a total of > 40,000 unique views, > 50,000 unique downloads and 40 citations (May 2022). NORMAN-SLE content is progressively integrated into large open chemical databases such as PubChem (https://pubchem.ncbi.nlm.nih.gov/) and the US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard/), enabling further access to these lists, along with the additional functionality and calculated properties these resources offer. PubChem has also integrated significant annotation content from the NORMAN-SLE, including a classification browser (https://pubchem.ncbi.nlm.nih.gov/classification/#hid=101).
Conclusions
The NORMAN-SLE offers a specialized service for hosting suspect screening lists of relevance for the environmental community in an open, FAIR manner that allows integration with other major chemical resources. These efforts foster the exchange of information between scientists and regulators, supporting the paradigm shift to the “one substance, one assessment” approach. New submissions are welcome via the contacts provided on the NORMAN-SLE website (https://www.norman-network.com/nds/SLE/).
Springer
2022