Found 2678 publications. Showing page 70 of 268:
Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: A multi-cohort analysis
Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) has been proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life.
We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries.
The four biological aging biomarkers were associated with education and different sets of risk factors independently, and the magnitude of the effects differed depending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception of smoking, which had a significantly stronger effect.
Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity.
2019
The carbonaceous aerosol accounts for an important part of total aerosol mass, affects human health and climate through its effects on physical and chemical properties of the aerosol, yet the understanding of its atmospheric sources and sinks is still incomplete. This study shows the state-of-the-art in modelling carbonaceous aerosol over Europe by comparing simulations performed with seven chemical transport models (CTMs) currently in air quality assessments in Europe: CAMx, CHIMERE, CMAQ, EMEP/MSC-W, LOTOS-EUROS, MINNI and RCGC. The simulations were carried out in the framework of the EURODELTA III modelling exercise and were evaluated against field measurements from intensive campaigns of European Monitoring and Evaluation Programme (EMEP) and the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI). Model simulations were performed over the same domain, using as much as possible the same input data and covering four seasons: summer (1–30 June 2006), winter (8 January – 4 February 2007), autumn (17 September- 15 October 2008) and spring (25 February - 26 March 2009). The analyses of models’ performances in prediction of elemental carbon (EC) for the four seasons and organic aerosol components (OA) for the last two seasons show that all models generally underestimate the measured concentrations. The maximum underestimation of EC is about 60% and up to about 80% for total organic matter (TOM). The underestimation of TOM outside of highly polluted area is a consequence of an underestimation of secondary organic aerosol (SOA), in particular of its main contributor: biogenic secondary aerosol (BSOA). This result is independent on the SOA modelling approach used and season. The concentrations and daily cycles of total primary organic matter (TPOM) are generally better reproduced by the models since they used the same anthropogenic emissions. However, the combination of emissions and model formulation leads to overestimate TPOM concentrations in 2009 for most of the models. All models capture relatively well the SOA daily cycles at rural stations mainly due to the spatial resolution used in the simulations. For the investigated carbonaceous aerosol compounds, the differences between the concentrations simulated by different models are lower than the differences between the concentrations simulated with a model for different seasons.
2019
2019
Plastic litter in the European Arctic: What do we know?
Despite an exponential increase in available data on marine plastic debris globally, information on levels and trends of plastic pollution and especially microplastics in the Arctic remains scarce. The few available peer-reviewed scientific works, however, point to a ubiquitous distribution of plastic particles in all environmental compartments, including sea ice. Here, we review the current state of knowledge on the sources, distribution, transport pathways and fate of meso- and microplastics with a focus on the European Arctic and discuss observed and projected impacts on biota and ecosystems.
2019
2019
Eggs of snow buntings (Plectrophenax nivealis) were applied as a bio-indicator to examine differences in exposure to legacy persistent organic pollutants (POPs) and perflouroalkyl subtances (PFAS) from the terrestrial environment surrounding the settlements of Longyearbyen, Barentsburg and Pyramiden on Svalbard, Norway. Significantly higher concentrations of summed polychlorinated biphenyls (sumPCB7) in eggs collected from Barentsburg (2980 ng/g lipid weight (lw)) and Pyramiden (3860 ng/g lw) compared to Longyearbyen (96 ng/g lw) are attributed to local sources of PCBs within these settlements. Similar findings were observed for p,p′-dichlorodiphenyldichloroethylene (p,p′-DDE) where higher median concentrations observed in Pyramiden (173 ng/g lw) and Barentsburg (75 ng/g lw) compared to Longyearbyen (48 ng/g lw) may be influenced by guano inputs from breeding seabird populations, although other point sources cannot be ruled out. Concentrations of perfluorooctane sulphonate (PFOS) and several perfluorinated carboxylic acids (PFCAs) in snow bunting eggs were found to be statistically higher in the populated settlements of Longyearbyen and Barentsburg compared to the abandoned Pyramiden. Narrow foraging ranges of snow buntings during breeding season was useful in assessing point sources of exposure for PCBs and PFAS at particular sites with extreme differences observed between nest locations. SumPCB7 concentrations ranged from 2 μg/g ww to below detection limits between nest sites located less than a kilometer from each other in Pyramiden. Similar findings were observed in Longyearbyen, where several PFCAs ranged from 2 to 55 times higher between nest sites with similar spatial distances. These findings indicate that snow buntings can be a useful bio-indicator offering high spatial resolution for contaminant source apportionment in terrestrial environments on Svalbard.
2019
Supporting the improvement of air quality management practices: The “FAIRMODE pilot” activity
This paper presents the first outcomes of the “FAIRMODE pilot” activity, aiming at improving the way in which air quality models are used in the frame of the European “Air Quality Directive”. Member States may use modelling, combined with measurements, to “assess” current levels of air quality and estimate future air quality under different scenarios. In case of current and potential exceedances of the Directive limit values, it is also requested that they “plan” and implement emission reductions measures to avoid future exceedances. In both “assessment” and “planning”, air quality models can and should be used; but to do so, the used modelling chain has to be fit-for-purpose and properly checked and verified. FAIRMODE has developed in the recent years a suite of methodologies and tools to check if emission inventories, model performance, source apportionment techniques and planning activities are fit-for-purpose. Within the “FAIRMODE pilot”, these tools are used and tested by regional/local authorities, with the two-fold objective of improving management practices at regional/local scale, and providing valuable feedback to the FAIRMODE community. Results and lessons learnt from this activity are presented in this paper, as a showcase that can potentially benefit other authorities in charge of air quality assessment and planning.
2019
Although aerosols in the Arctic have multiple and complex impacts on the regional climate, their removal due to deposition is still not well quantified. We combined meteorological, aerosol, precipitation, and snowpack observations with simulations to derive information about the deposition of sea salt components and black carbon (BC) from November 2011 to April 2012 to the Arctic snowpack at two locations close to Ny-Ålesund, Svalbard. The dominating role of sea salt and the contribution of dust for the composition of atmospheric aerosols were reflected in the seasonal composition of the snowpack. The strong alignment of the concentrations of the major sea salt components in the aerosols, the precipitation, and the snowpack is linked to the importance of wet deposition for transfer from the atmosphere to the snowpack. This agreement was less strong for monthly snow budgets and deposition, indicating important relocation of the impurities inside the snowpack after deposition. Wet deposition was less important for the transfer of nitrate, non-sea-salt sulfate, and BC to the snow during the winter period. The average BC concentration in the snowpack remains small, with a limited impact on snow albedo and melting. Nevertheless, the observations also indicate an important redistribution of BC in the snowpack, leading to layers with enhanced concentrations. The complex behavior of bromide due to modifications during sea salt aerosol formation and remobilization in the atmosphere and in the snow were not resolved because of the lack of bromide measurements in aerosols and precipitation.
2019
2019
Monitoring Soil Moisture Drought over Northern High Latitudes from Space
Mapping drought from space using, e.g., surface soil moisture (SSM), has become viable in the last decade. However, state of the art SSM retrieval products suffer from very poor coverage over northern latitudes. In this study, we propose an innovative drought indicator with a wider spatial and temporal coverage than that obtained from satellite SSM retrievals. We evaluate passive microwave brightness temperature observations from the Soil Moisture and Ocean Salinity (SMOS) satellite as a surrogate drought metric, and introduce a Standardized Brightness Temperature Index (STBI). We compute the STBI by fitting a Gaussian distribution using monthly brightness temperature data from SMOS; the normal assumption is tested using the Shapior-Wilk test. Our results indicate that the assumption of normally distributed brightness temperature data is valid at the 0.05 significance level. The STBI is validated against drought indices from a land surface data assimilation system (LDAS-Monde), two satellite derived SSM indices, one from SMOS and one from the ESA CCI soil moisture project and a standardized precipitation index based on in situ data from the European Climate Assessment & Dataset (ECA&D) project. When comparing the temporal dynamics of the STBI to the LDAS-Monde drought index we find that it has equal correlation skill to that of the ESA CCI soil moisture product ( 0.71 ). However, in addition the STBI provides improved spatial coverage because no masking has been applied over regions with dense boreal forest. Finally, we evaluate the STBI in a case study of the 2018 Nordic drought. The STBI is found to provide improved spatial and temporal coverage when compared to the drought index created from satellite derived SSM over the Nordic region. Our results indicate that when compared to drought indices from precipitation data and a land data assimilation system, the STBI is qualitatively able to capture the 2018 drought onset, severity and spatial extent. We did see that the STBI was unable to detect the 2018 drought recovery for some areas in the Nordic countries. This false drought detection is likely linked to the recovery of vegetation after the drought, which causes an increase in the passive microwave brightness temperature, hence the STBI shows a dry anomaly instead of normal conditions, as seen for the other drought indices. We argue that the STBI could provide additional information for drought monitoring in regions where the SSM retrieval problem is not well defined. However, it then needs to be accompanied by a vegetation index to account for the recovery of the vegetation which could cause false drought detection.
2019