Found 2670 publications. Showing page 43 of 267:
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
Svalbard is a remote and scarcely populated Arctic archipelago and is considered to be mostly influenced by long-range-transported air pollution. However, there are also local emission sources such as coal and diesel power plants, snowmobiles and ships, but their influence on the background concentrations of trace gases has not been thoroughly assessed. This study is based on data of tropospheric ozone (O3) and nitrogen oxides (NOx) collected in three main Svalbard settlements in spring 2017. In addition to these ground-based observations and radiosonde and O3 sonde soundings, ERA5 reanalysis and BrO satellite data have been applied in order to distinguish the impact of local and synoptic-scale conditions on the NOx and O3 chemistry. The measurement campaign was divided into several sub-periods based on the prevailing large-scale weather regimes. The local wind direction at the stations depended on the large-scale conditions but was modified due to complex topography. The NOx concentration showed weak correlation for the different stations and depended strongly on the wind direction and atmospheric stability. Conversely, the O3 concentration was highly correlated among the different measurement sites and was controlled by the long-range atmospheric transport to Svalbard. Lagrangian backward trajectories have been used to examine the origin and path of the air masses during the campaign.
2022
Thymidine Kinase+/− Mammalian Cell Mutagenicity Assays for Assessment of Nanomaterials
The methods outlined here are part of a series of papers designed specifically for genotoxicity assessment of nanomaterials (NM). Common Considerations such as NM characterization, sample preparation and dose selection, relevant to all genotoxicity assays, are found in an accompanying paper. The present paper describes methods for evaluation of mutagenicity in the mammalian (mouse) thymidine kinase (Tk) gene occurring in L5178Y mouse lymphoma (ML) cells and in the designated TK gene in human lymphoblastoid TK6 cells. Mutations change the functional genotype from TK+/− to TK−/−, detectable as cells surviving on media selective for the lack of thymidine kinase (TK) function. Unlike cells with TK enzyme function, the TK−/− cells are unable to integrate the toxic selection agent, allowing these cells to survive as rare mutant colonies. The ML assay has been shown to detect a broad spectrum of genetic damage, including both small scale (point) mutations and chromosomal alterations. This assay is a widely used mammalian cell gene mutation assay for regulatory purposes and is included in the core battery of genotoxicity tests for regulatory decision-making. The TK6 assay is an assay using a human cell line derived similarly via mutagenic manipulations and optimal selection. Details are provided on the materials required, cell culture methods, selection of test chemical concentrations, cytotoxicity, treatment time, mutation expression, cloning, and data calculation and interpretation. The methods describe the microwell plate version of the assays without metabolic activation.
2022
The alamar blue assay in the context of safety testing of nanomaterials
The Alamar Blue (AB) assay is widely used to investigate cytotoxicity, cell proliferation and cellular metabolic activity within different fields of toxicology. The use of the assay with nanomaterials (NMs) entails specific aspects including the potential interference of NMs with the test. The procedure of the AB assay applied for testing NMs is described in detail and step-by-step, from NM preparation, cell exposure, inclusion of interference controls, to the analysis and interpretation of the results. Provided that the proper procedure is followed, and relevant controls are included, the AB assay is a reliable and high throughput test to evaluate the cytotoxicity/proliferation/metabolic response of cells exposed to NMs.
2022
In vivo Mammalian Alkaline Comet Assay: Method Adapted for Genotoxicity Assessment of Nanomaterials
The in vivo Comet assay measures the generation of DNA strand breaks under conditions in which the DNA will unwind and migrate to the anode in an electrophoresis assay, producing comet-like figures. Measurements are on single cells, which allows the sampling of a diversity of cells and tissues for DNA damaging effects. The Comet assay is the most common in vivo method for genotoxicity assessment of nanomaterials (NM). The Method outlined here includes a recommended step-by-step approach, consistent with OECD 489, taking into consideration the issues impacting assessment of NM, including choice of cells or systems, handling of NM test articles, dose determination, assay methods and data assessment. This method is designed to be used along with the accompanying “Common Considerations” paper, which discusses issues common to any genotoxicity assay using NM as a test article.
2022
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2022
Fourteen legacy organochlorine (OC) contaminants and 12 perfluoroalkyl substances (PFASs) were measured in eggs of tawny owls (Strix alueco) in central Norway (1986–2019). We expected OCs to have reached stable equilibrium levels due to bans, and that recent phase-out of some PFASs would have slowed the increase of these compounds. ∑OC comprised on average approximately 92% of the measured compounds, whereas ∑PFAS accounted for approximately 8%. However, whereas the ∑OC to ∑PFAS ratio was approximately 60 in the first 5 years of the study, it was only approximately 11 in the last 5 years. Both OC pesticides and polychlorinated biphenyls (PCBs) showed substantial declines over the study period (~85%–98%): hexachlorocyclohexanes and chlordanes seemed to be levelling off, whereas p,p′-dichlorodiphenyldichloroethylene (p,p′-DDE) and hexachlororbenzene (HCB), and most PCB congeners still seemed to decline at a more or less constant rate. While the concentration of perfluorooctane sulfonic acid (PFOS), the dominating PFAS, was reduced by approximately 43%, other perfluorinated sulfonates (PFSAs) showed only minor changes. Moreover, the median concentrations of seven perfluorinated carboxylic acids (PFCAs) increased approximately five-fold over the study period. Perfluorononanoic acid and perfluoroundecanoate acid, however, seemed to be levelling off in recent years. In contrast, perfluorododecanoic acid, perfluorodecanoate acid, perfluorotridecanoic acid, and perfluorotetradecanoic acid seemed to increase more or less linearily. Finally, perfluorooctanoic acid (PFOA) was increasingly likely to be detected over the study period. Hence, most legacy OCs and PFOS have not reached a lower threshold with stable background levels, and voluntary elimination of perfluoroalkyl carboxylates still has not resulted in declining levels in tawny owls in central Norway.
2022
Insight into processes determining the exposure of organohalogenated contaminants (OHCs) in wildlife might be gained from comparing predators in different ecosystems. This study compared two avian predator species with similar food chain lengths: the goldeneye duck (Bucephala clangula) and the tawny owl (Strix aluco) breeding in adjacent freshwater- and terrestrial ecosystems in central Norway. We measured lipophilic organochlorines (OCs) and protein-bound perfluorinated substances (PFASs) in eggs of the two species over 21 years (1999–2019). Across years, the proportional distribution of OCs (∼90% of the ΣOHC load) relative to PFASs (∼10%) was similar in the two species. Moreover, ΣOC concentrations were similar between the species, but PFAS compounds were 2–12 times higher in the goldeneyes than in tawny owls. OC-pesticides dominated in tawny owls (∼60% of ΣOC), whereas persistent polychlorinated biphenyl (PCBs) congeners were the main OC components in goldeneyes (∼70% of ΣOC). The lipid-normalized concentrations of most OC-pesticides and the less persistent PCB101 declined significantly in both species. Hexachlorobenzene (HCB), p,p’-dichlorodiphenyldichloroethylene (p,p’-DDE), and more persistent PCBs decreased in tawny owls, while they tended to increase in goldeneyes. The increase in HCB was particulary robust. Among the PFASs, contrasted temporal trends were found across the species for four out of 11 compounds: PFOS declined while most perfluorocarboxylic acids (PFCAs) increased in tawny owls. In contrast, most PFASs were stable in goldeneyes. Moreover, there was no annual covariance between the OHC exposure in the two species: i.e., high concentrations in one species in a given year did not translate into high concentrations in the other. Hence, the two avian predators in adjacent ecosystems seem to be subject to different processes determining the OHC exposure, probably related to variation in diet and climate, long-range transport of different contaminants, and emissions of pollution locally.
2022
Three-dimensional (3D) cloud structures may impact atmospheric trace gas products from ultraviolet–visible (UV–Vis) sounders. We used synthetic and observational data to identify and quantify possible cloud-related bias in NO2 tropospheric vertical column density (TVCD). The synthetic data were based on high-resolution large eddy simulations which were input to a 3D radiative transfer model. The simulated visible spectra for low-earth-orbiting and geostationary geometries were analysed with standard retrieval methods and cloud correction schemes that are employed in operational NO2 satellite products. For the observational data, the NO2 products from the TROPOspheric Monitoring Instrument (TROPOMI) were used, while the Visible Infrared Imaging Radiometer Suite (VIIRS) provided high-spatial-resolution cloud and radiance data. NO2 profile shape, cloud shadow fraction, cloud top height, cloud optical depth, and solar zenith and viewing angles were identified as the metrics being the most important in identifying 3D cloud impacts on NO2 TVCD retrievals. For a solar zenith angle less than about 40∘ the synthetic data show that the NO2 TVCD bias is typically below 10 %, while for larger solar zenith angles the NO2 TVCD is low-biased by tens of percent. The horizontal variability of NO2 and differences in TROPOMI and VIIRS overpass times make it challenging to identify a similar bias in the observational data. However, for optically thick clouds above 3000 m, a low bias appears to be present in the observational data.
2022