Found 9989 publications. Showing page 57 of 400:
A pooled analysis of molecular epidemiological studies on modulation of DNA repair by host factors
Levels of DNA damage represent the dynamics between damage formation and removal. Therefore, to better interpret human biomonitoring studies with DNA damage endpoints, an individual’s ability to recognize and properly remove DNA damage should be characterized. Relatively few studies have included DNA repair as a biomarker and therefore, assembling and analyzing a pooled database of studies with data on base excision repair (BER) was one of the goals of hCOMET (EU-COST CA15132). A group of approximately 1911 individuals, was gathered from 8 laboratories which run population studies with the comet-based in vitro DNA repair assay. BER incision activity data were normalized and subsequently correlated with various host factors. BER was found to be significantly higher in women. Although it is generally accepted that age is inversely related to DNA repair, no overall effect of age was found, but sex differences were most pronounced in the oldest quartile (>61 years). No effect of smoking or occupational exposures was found. A body mass index (BMI) above 25 kg/m2 was related to higher levels of BER. However, when BMI exceeded 35 kg/m2, repair incision activity was significantly lower. Finally, higher BER incision activity was related to lower levels of DNA damage detected by the comet assay in combination with formamidopyrimidine DNA glycosylase (Fpg), which is in line with the fact that oxidatively damaged DNA is repaired by BER. These data indicate that BER plays a role in modulating the steady-state level of DNA damage that is detected in molecular epidemiological studies and should therefore be considered as a parallel endpoint in future studies.
2022
Important clarifications regarding the long-range environmental transport of chemical additives contained in floating plastic debris are presented.
2022
Monitoring of environmental contaminants in air and precipitation. Annual report 2021.
This report presents data from 2021 and time-trends for the Norwegian monitoring programme "Atmospheric contaminants". The results cover 200 organic compounds (regulated and non-regulated), 11 heavy metals, and a selection of organic chemicals of concern.
NILU
2022
Operational retrievals of tropospheric trace gases from space-borne spectrometers are based on one-dimensional radiative transfer models. To minimize cloud effects, trace gas retrievals generally implement a simple cloud model based on radiometric cloud fraction estimates and photon path length corrections. The latter relies on measurements of the oxygen collision pair (O2–O2) absorption at 477 nm or on the oxygen A-band around 760 nm to determine an effective cloud height. In reality however, the impact of clouds is much more complex, involving unresolved sub-pixel clouds, scattering of clouds in neighbouring pixels, and cloud shadow effects, such that unresolved three-dimensional effects due to clouds may introduce significant biases in trace gas retrievals. Although clouds have significant effects on trace gas retrievals, the current cloud correction schemes are based on a simple cloud model, and the retrieved cloud parameters must be interpreted as effective values. Consequently, it is difficult to assess the accuracy of the cloud correction only based on analysis of the accuracy of the cloud retrievals, and this study focuses solely on the impact of the 3D cloud structures on the trace gas retrievals. In order to quantify this impact, we study NO2 as a trace gas example and apply standard retrieval methods including approximate cloud corrections to synthetic data generated by the state-of-the-art three-dimensional Monte Carlo radiative transfer model MYSTIC. A sensitivity study is performed for simulations including a box cloud, and the dependency on various parameters is investigated. The most significant bias is found for cloud shadow effects under polluted conditions. Biases depend strongly on cloud shadow fraction, NO2 profile, cloud optical thickness, solar zenith angle, and surface albedo. Several approaches to correct NO2 retrievals under cloud shadow conditions are explored. We find that air mass factors calculated using fitted surface albedo or corrected using the O2–O2 slant column density can partly mitigate cloud shadow effects. However, these approaches are limited to cloud-free pixels affected by surrounding clouds. A parameterization approach is presented based on relationships derived from the sensitivity study. This allows measurements to be identified for which the standard NO2 retrieval produces a significant bias and therefore provides a way to improve the current data flagging approach.
2022
2022
2022
While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios.
In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH4, O3, BC, and SO), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs.
Of the SLCFs in our study, model biases were smallest for CH4 and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.
2022
Assessment of heavy metal and POP pollution on global, regional and national scales
Meteorological Synthesizing Centre - East (MSC-E)
2022
Carbon felts are flexible and scalable, have high specific areas, and are highly conductive materials that fit the requirements for both anodes and cathodes in advanced electrocatalytic processes. Advanced oxidative modification processes (thermal, chemical, and plasma-chemical) were applied to carbon felt anodes to enhance their efficiency towards electro-oxidation. The modification of the porous anodes results in increased kinetics of acetaminophen degradation in aqueous environments. The utilised oxidation techniques deliver single-step, straightforward, eco-friendly, and stable physiochemical reformation of carbon felt surfaces. The modifications caused minor changes in both the specific surface area and total pore volume corresponding with the surface morphology.
A pristine carbon felt electrode was capable of decomposing up to 70% of the acetaminophen in a 240 min electrolysis process, while the oxygen-plasma treated electrode achieved a removal yield of 99.9% estimated utilising HPLC-UV-Vis. Here, the electro-induced incineration kinetics of acetaminophen resulted in a rate constant of 1.54 h−1, with the second-best result of 0.59 h−1 after oxidation in 30% H2O2. The kinetics of acetaminophen removal was synergistically studied by spectroscopic and electrochemical techniques, revealing various reaction pathways attributed to the formation of intermediate compounds such as p-aminophenol and others.
The enhancement of the electrochemical oxidation rates towards acetaminophen was attributed to the appearance of surface carbonyl species. Our results indicate that the best-performing plasma-chemical treated CFE follows a heterogeneous mechanism with only approx. 40% removal due to direct electro-oxidation. The degradation mechanism of acetaminophen at the treated carbon felt anodes was proposed based on the detected intermediate products. Estimation of the cost-effectiveness of removal processes, in terms of energy consumption, was also elaborated. Although the study was focussed on acetaminophen, the achieved results could be adapted to also process emerging, hazardous pollutant groups such as anti-inflammatory pharmaceuticals.
2022
2022
The Eurodelta-Trends (EDT) multi-model experiment, aimed at assessing the efficiency of emission mitigation measures in improving air quality in Europe during 1990–2010, was designed to answer a series of questions regarding European pollution trends; i.e. were there significant trends detected by observations? Do the models manage to reproduce observed trends? How close is the agreement between the models and how large are the deviations from observations? In this paper, we address these issues with respect to particulate matter (PM) pollution. An in-depth trend analysis has been performed for PM10 and PM2.5 for the period of 2000–2010, based on results from six chemical transport models and observational data from the EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) monitoring network. Given harmonization of set-up and main input data, the differences in model results should mainly result from differences in the process formulations within the models themselves, and the spread in the model-simulated trends could be regarded as an indicator for modelling uncertainty.
The model ensemble simulations indicate overall decreasing trends in PM10 and PM2.5 from 2000 to 2010, with the total reductions of annual mean concentrations by between 2 and 5 (7 for PM10) µg m−3 (or between 10 % and 30 %) across most of Europe (by 0.5–2 µg m−3 in Fennoscandia, the north-west of Russia and eastern Europe) during the studied period. Compared to PM2.5, relative PM10 trends are weaker due to large inter-annual variability of natural coarse PM within the former. The changes in the concentrations of PM individual components are in general consistent with emission reductions. There is reasonable agreement in PM trends estimated by the individual models, with the inter-model variability below 30 %–40 % over most of Europe, increasing to 50 %–60 % in the northern and eastern parts of the EDT domain.
Averaged over measurement sites (26 for PM10 and 13 for PM2.5), the mean ensemble-simulated trends are −0.24 and −0.22 µg m−3 yr−1 for PM10 and PM2.5, which are somewhat weaker than the observed trends of −0.35 and −0.40 µg m−3 yr−1 respectively, partly due to model underestimation of PM concentrations. The correspondence is better in relative PM10 and PM2.5 trends, which are −1.7 % yr−1 and −2.0 % yr−1 from the model ensemble and −2.1 % yr−1 and −2.9 % yr−1 from the observations respectively. The observations identify significant trends (at the 95 % confidence level) for PM10 at 56 % of the sites and for PM2.5 at 36 % of the sites, which is somewhat less that the fractions of significant modelled trends. Further, we find somewhat smaller spatial variability of modelled PM trends with respect to the observed ones across Europe and also within individual countries.
The strongest decreasing PM trends and the largest number of sites with significant trends are found for the summer season, according to both the model ensemble and observations. The winter PM trends are very weak and mostly insignificant. Important reasons for that are the very modest reductions and even increases in the emissions of primary PM from residential heating in winter. It should be kept in mind that all findings regarding modelled versus observed PM trends are limited to the regions where the sites are located.
The analysis reveals considerable variability of the role of the individual aerosols in PM10 trends across European countries. The multi-model simulations, supported by available observations, point to decreases in concentrations playing an overall dominant role. Also, we see...
2022
Equal abundance of summertime natural and wintertime anthropogenic Arctic organic aerosols
Aerosols play an important yet uncertain role in modulating the radiation balance of the sensitive Arctic atmosphere. Organic aerosol is one of the most abundant, yet least understood, fractions of the Arctic aerosol mass. Here we use data from eight observatories that represent the entire Arctic to reveal the annual cycles in anthropogenic and biogenic sources of organic aerosol. We show that during winter, the organic aerosol in the Arctic is dominated by anthropogenic emissions, mainly from Eurasia, which consist of both direct combustion emissions and long-range transported, aged pollution. In summer, the decreasing anthropogenic pollution is replaced by natural emissions. These include marine secondary, biogenic secondary and primary biological emissions, which have the potential to be important to Arctic climate by modifying the cloud condensation nuclei properties and acting as ice-nucleating particles. Their source strength or atmospheric processing is sensitive to nutrient availability, solar radiation, temperature and snow cover. Our results provide a comprehensive understanding of the current pan-Arctic organic aerosol, which can be used to support modelling efforts that aim to quantify the climate impacts of emissions in this sensitive region.
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.
2022
Clean air policies are key for successfully mitigating Arctic warming
A tighter integration of modeling frameworks for climate and air quality is urgently needed to assess the impacts of clean air policies on future Arctic and global climate. We combined a new model emulator and comprehensive emissions scenarios for air pollutants and greenhouse gases to assess climate and human health co-benefits of emissions reductions. Fossil fuel use is projected to rapidly decline in an increasingly sustainable world, resulting in far-reaching air quality benefits. Despite human health benefits, reductions in sulfur emissions in a more sustainable world could enhance Arctic warming by 0.8 °C in 2050 relative to the 1995–2014, thereby offsetting climate benefits of greenhouse gas reductions. Targeted and technically feasible emissions reduction opportunities exist for achieving simultaneous climate and human health co-benefits. It would be particularly beneficial to unlock a newly identified mitigation potential for carbon particulate matter, yielding Arctic climate benefits equivalent to those from carbon dioxide reductions by 2050.
2022
BACKGROUND
All mouse strains are different, before choosing a strain for a large study, a small scale study should be done. In this study, we compared young males of two mouse strains, C57BL/6J and the hybrid B6129SF1/J, and gained knowledge on their performance in three different behavioral tests; open field (OF) test, Barnes maze (BM) test and a restraint stress test.
RESULTS
We found that the young males of the C57BL/6J strain spent more time moving in the OF. In the BM, the hybrid covered less ground before reaching the goal box during the first three sessions, than the C57BL/6J. The hybrid left more fecal pellets than C57BL/6J both in OF and BM. During the stress test, the C57BL/6J had a lower corticosterone response than the hybrid.
CONCLUSIONS
Our findings indicate that the C57BL/6J has a presumably higher locomotor activity and/or explorative behavior than the hybrid, while the hybrid appeared more sensitive to stress.
2022
Siberian Arctic black carbon: gas flaring and wildfire impact
As explained in the latest Arctic Monitoring and Assessment Programme (AMAP) report released in early 2021, the Arctic has warmed 3 times more quickly than the planet as a whole, as well as faster than previously thought. The Siberian Arctic is of great interest mainly because observations are sparse or largely lacking. A research aerosol station has been developed on Bely Island (Kara Sea) in western Siberia. Measurements of equivalent black carbon (EBC) concentrations were carried out at the “Island Bely” station continuously from August 2019 to November 2020. The source origin of the measured EBC and the main contributing sources were assessed using atmospheric transport modeling coupled with the most updated emission inventories for anthropogenic and biomass burning sources of BC.
The obtained climatology for BC during the period of measurements showed an apparent seasonal variation with the highest concentrations between December and April (60 ± 92 ng m−3) and the lowest between June and September (18 ± 72 ng m−3), typical of the Arctic haze seasonality reported elsewhere. When air masses arrived at the station through the biggest oil and gas extraction regions of Kazakhstan, Volga-Ural, Komi, Nenets and western Siberia, BC contribution from gas flaring dominated over domestic, industrial and traffic sectors, ranging from 47 % to 68 %, with a maximum contribution in January. When air was transported from Europe during the cold season, emissions from transportation were more important. Accordingly, shipping emissions increased due to the touristic cruise activities and the ice retreat in summertime. Biomass burning (BB) played the biggest role between April and October, contributing 81 % at maximum in July. Long-range transport of BB aerosols appeared to induce large variability to the absorption Ångström exponent (AAE) with values > 1.0 (excluding outliers). As regards the continental contribution to surface BC at the Island Bely station, Russian emissions dominated during the whole year, while European and Asian ones contributed up to 20 % in the cold period. Quantification of several pollution episodes showed an increasing trend in surface concentrations and frequency during the cold period as the station is directly in the Siberian gateway of the highest anthropogenic pollution sources to the Russian Arctic.
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