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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
Sheath formation time for spherical Langmuir probes
The formation time of the surrounding sheath of Langmuir probes in an ionospheric plasma has been studied to better understand the constraints this puts on the sampling frequency of a probe. A fully kinetic three-dimensional particle-in-cell model is used to simulate the temporal effects in the electron saturation region as the sheath forms. The stability of the probe current and the stability of the ion and electron density in the vicinity of the probe have been used to evaluate when the sheath was formed. Simulated results were compared with theoretical models and are in good agreement with the theoretical results. This shows that theoretical models can be used as guidance to estimate the formation time and to determine the sampling rate for a swept bias Langmuir system. Our results also show that the formation time is less affected by the plasma temperature and bias voltage as we move into the thick sheath regime, and will instead be determined by the plasma density. The presented results also show that applying a step function to the probe could be used to characterise ions species composition, or to estimate the ion density.
Cambridge University Press
2023
An Unprecedented Arctic Ozone Depletion Event During Spring 2020 and Its Impacts Across Europe
The response of the ozone column across Europe to the extreme 2020 Arctic ozone depletion was examined by analyzing ground-based observations at 38 European stations. The ozone decrease at the northernmost site, Ny-Ålesund (79°N) was about 43% with respect to a climatology of more than 30 years. The magnitude of the decrease declined by about 0.7% deg−1 moving south to reach nearly 15% at 40°N. In addition, it was found that the variations of the ozone column at each of the selected stations in March-May were similar to those observed at Ny-Ålesund but with a delay increasing to about 20 days at mid-latitudes with a gradient of approximately 0.5 days deg−1. The distributions of reconstructed ozone column anomalies over a sector covering a large European area show decreasing ozone that started from the north at the beginning of April 2020 and spread south. Such behavior was shown to be similar to that observed after the Arctic ozone depletion in 2011. Stratospheric dynamical patterns in March–May 2011 and during 2020 suggested that the migration of ozone-poor air masses from polar areas to the south after the vortex breakup caused the observed ozone responses. A brief survey of the ozone mass mixing ratios at three stratospheric levels showed the exceptional strength of the 2020 episode. Despite the stronger and longer-lasting Arctic ozone loss in 2020, the analysis in this work indicates a similar ozone response at latitudes below 50°N to both 2011 and 2020 phenomena.
American Geophysical Union (AGU)
2023
Plastic pollution has long been identified as one of the biggest challenges of the 21st century. To tackle this problem, governments are setting stringent recycling targets to keep plastics in a closed loop. Yet, knowledge of the stocks and flows of plastic has not been well integrated into policies. This study presents a dynamic probabilistic economy-wide material flow analysis (MFA) of seven plastic polymers (HDPE, LDPE, PP, PS, PVC, EPS, and PET) in Norway from 2000 to 2050. A total of 40 individual product categories aggregated into nine industrial sectors were examined. An estimated 620 ± 23 kt or 114 kg/capita of these seven plastic polymers was put on the Norwegian market in 2020. Packaging products contributed to the largest share of plastic put on the market (∼40%). The accumulated in-use stock in 2020 was about 3400 ± 56 kt with ∼60% remaining in buildings and construction sector. In 2020, about 460 ± 22 kt of plastic waste was generated in Norway, with half originating from packaging. Although ∼50% of all plastic waste is collected separately from the waste stream, only around 25% is sorted for recycling. Overall, ∼50% of plastic waste is incinerated, ∼15% exported, and ∼10% landfilled. Under a business-as-usual scenario, the plastic put on the market, in-use stock, and waste generation will increase by 65%, 140%, and 90%, respectively by 2050. The outcomes of this work can be used as a guideline for other countries to establish the stocks and flows of plastic polymers from various industrial sectors which is needed for the implementation of necessary regulatory actions and circular strategies. The systematic classification of products suitable for recycling or be made of recyclate will facilitate the safe and sustainable recycling of plastic waste into new products, cap production, lower consumption, and prevent waste generation.
Elsevier
2023
Black carbon emitted by incomplete combustion of fossil fuels and biomass has a net warming effect in the atmosphere and reduces the albedo when deposited on ice and snow; accurate knowledge of past emissions is essential to quantify and model associated global climate forcing. Although bottom-up inventories provide historical Black Carbon emission estimates that are widely used in Earth System Models, they are poorly constrained by observations prior to the late 20th century. Here we use an objective inversion technique based on detailed atmospheric transport and deposition modeling to reconstruct 1850 to 2000 emissions from thirteen Northern Hemisphere ice-core records. We find substantial discrepancies between reconstructed Black Carbon emissions and existing bottom-up inventories which do not fully capture the complex spatial-temporal emission patterns. Our findings imply changes to existing historical Black Carbon radiative forcing estimates are necessary, with potential implications for observation-constrained climate sensitivity.
Springer Nature
2023
The AirGAM 2022r1 air quality trend and prediction model
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
State of the Climate in 2021: The Arctic
American Meteorological Society
2022
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