Found 10000 publications. Showing page 282 of 400:
2018
This paper presents the results of BC inversions at high northern latitudes (>50°N) for the 2013–2015 period. A sensitivity analysis was performed to select the best representative species for BC and the best a priori emission dataset. The same model ensemble was used to assess the uncertainty of the a posteriori emissions of BC due to scavenging and removal and due to the use of different a priori emission inventory. A posteriori concentrations of BC simulated over Arctic regions were compared with independent observations from flight and ship campaigns showing, in all cases, smaller bias, which in turn witnesses the success of the inversion. The annual a posteriori emissions of BC at latitudes above 50°N were estimated as 560±171ktyr−1, significantly smaller than in ECLIPSEv5 (745ktyr−1), which was used and the a priori information in the inversions of BC. The average relative uncertainty of the inversions was estimated to be 30%.
A posteriori emissions of BC in North America are driven by anthropogenic sources, while biomass burning appeared to be less significant as it is also confirmed by satellite products. In northern Europe, a posteriori emissions were estimated to be half compared to the a priori ones, with the highest releases to be in megacities and due to biomass burning in eastern Europe. The largest emissions of BC in Siberia were calculated along the transect between Yekaterinsburg and Chelyabinsk. The optimised emissions of BC were high close to the gas flaring regions in Russia and in western Canada (Alberta), where numerous power and oil and gas production industries operate. Flaring emissions in Nenets–Komi oblast (Russia) were estimated to be much lower than in the a priori emissions, while in Khanty-Mansiysk (Russia) they remained the same after the inversions of BC. Increased emissions at the borders between Russia and Mongolia are probably due to biomass burning in villages along the Trans-Siberian Railway. The maximum BC emissions in high northern latitudes (>50°N) were calculated for summer months due to biomass burning and they are controlled by seasonal variations in Europe and Asia, while North America showed a much smaller variability.
2018
Unleaded gasoline as a significant source of Pb emissions in the Subarctic
After the phasing out of leaded gasoline, Pb emissions to the atmosphere dramatically decreased, and other sources became more significant. The contribution of unleaded gasoline has not been sufficiently recognized; therefore, we evaluated the impact of Pb from unleaded gasoline in a relatively pristine area in Subarctic NE Norway. The influence of different endmembers (Ni slag and concentrate from the Nikel smelter in Russia, PM10 filters, and traffic) on the overall Pb emissions was determined using various environmental samples (snow, lichens, and topsoils) and Pb isotope tracing. We found a strong relationship between Pb in snow and the Ni smelter. However, lichen samples and most of the topsoils were contaminated by Pb originating from the current use of unleaded gasoline originating from Russia. Historical leaded and recent unleaded gasoline are fully distinguishable using Pb isotopes, as unleaded gasoline is characterized by a low radiogenic composition (206Pb/207Pb = 1.098 and 208Pb/206Pb = 2.060) and remains an unneglectable source of Pb in the region.
2018
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A Lagrangian particle dispersion model, the FLEXible PARTicle dispersion chemical transport model (FLEXPART CTM), is used to simulate global three-dimensional fields of trace gas abundance. These fields are constrained with surface observation data through nudging, a data assimilation method, which relaxes model fields to observed values. Such fields are of interest to a variety of applications, such as inverse modelling, satellite retrievals, radiative forcing models and estimating global growth rates of greenhouse gases. Here, we apply this method to methane using 6 million model particles filling the global model domain. For each particle, methane mass tendencies due to emissions (based on several inventories) and loss by reaction with OH, Cl and O(1D), as well as observation data nudging were calculated. Model particles were transported by mean, turbulent and convective transport driven by 1∘×1∘ ERA-Interim meteorology. Nudging is applied at 79 surface stations, which are mostly included in the World Data Centre for Greenhouse Gases (WDCGG) database or the Japan–Russia Siberian Tall Tower Inland Observation Network (JR-STATION) in Siberia. For simulations of 1 year (2013), we perform a sensitivity analysis to show how nudging settings affect modelled concentration fields. These are evaluated with a set of independent surface observations and with vertical profiles in North America from the National Oceanic and Atmospheric Administration (NOAA) Earth System Research Laboratory (ESRL), and in Siberia from the Airborne Extensive Regional Observations in SIBeria (YAK-AEROSIB) and the National Institute for Environmental Studies (NIES). FLEXPART CTM results are also compared to simulations from the global Eulerian chemistry Transport Model version 5 (TM5) based on optimized fluxes. Results show that nudging strongly improves modelled methane near the surface, not only at the nudging locations but also at independent stations. Mean bias at all surface locations could be reduced from over 20 to less than 5 ppb through nudging. Near the surface, FLEXPART CTM, including nudging, appears better able to capture methane molar mixing ratios than TM5 with optimized fluxes, based on a larger bias of over 13 ppb in TM5 simulations. The vertical profiles indicate that nudging affects model methane at high altitudes, yet leads to little improvement in the model results there. Averaged from 19 aircraft profile locations in North America and Siberia, root mean square error (RMSE) changes only from 16.3 to 15.7 ppb through nudging, while the mean absolute bias increases from 5.3 to 8.2 ppb. The performance for vertical profiles is thereby similar to TM5 simulations based on TM5 optimized fluxes where we found a bias of 5 ppb and RMSE of 15.9 ppb. With this rather simple model setup, we thus provide three-dimensional methane fields suitable for use as boundary conditions in regional inverse modelling as a priori information for satellite retrievals and for more accurate estimation of mean mixing ratios and growth rates. The method is also applicable to other long-lived trace gases.
2018
This paper presents the light-scattering properties of atmospheric aerosol particles measured over the past decade at 28 ACTRIS observatories, which are located mainly in Europe. The data include particle light scattering (σsp) and hemispheric backscattering (σbsp) coefficients, scattering Ångström exponent (SAE), backscatter fraction (BF) and asymmetry parameter (g). An increasing gradient of σsp is observed when moving from remote environments (arctic/mountain) to regional and to urban environments. At a regional level in Europe, σsp also increases when moving from Nordic and Baltic countries and from western Europe to central/eastern Europe, whereas no clear spatial gradient is observed for other station environments. The SAE does not show a clear gradient as a function of the placement of the station. However, a west-to-east-increasing gradient is observed for both regional and mountain placements, suggesting a lower fraction of fine-mode particle in western/south-western Europe compared to central and eastern Europe, where the fine-mode particles dominate the scattering. The g does not show any clear gradient by station placement or geographical location reflecting the complex relationship of this parameter with the physical properties of the aerosol particles. Both the station placement and the geographical location are important factors affecting the intra-annual variability. At mountain sites, higher σsp and SAE values are measured in the summer due to the enhanced boundary layer influence and/or new particle-formation episodes. Conversely, the lower horizontal and vertical dispersion during winter leads to higher σsp values at all low-altitude sites in central and eastern Europe compared to summer. These sites also show SAE maxima in the summer (with corresponding g minima). At all sites, both SAE and g show a strong variation with aerosol particle loading. The lowest values of g are always observed together with low σsp values, indicating a larger contribution from particles in the smaller accumulation mode. During periods of high σsp values, the variation of g is less pronounced, whereas the SAE increases or decreases, suggesting changes mostly in the coarse aerosol particle mode rather than in the fine mode. Statistically significant decreasing trends of σsp are observed at 5 out of the 13 stations included in the trend analyses. The total reductions of σsp are consistent with those reported for PM2.5 and PM10 mass concentrations over similar periods across Europe.
2018
We present the organization, instrumentation, datasets, data interpretation, modeling, and accomplishments of the multinational global atmospheric measurement program AGAGE (Advanced Global Atmospheric Gases Experiment). AGAGE is distinguished by its capability to measure globally, at high frequency, and at multiple sites all the important species in the Montreal Protocol and all the important non-carbon-dioxide (non-CO2) gases assessed by the Intergovernmental Panel on Climate Change (CO2 is also measured at several sites). The scientific objectives of AGAGE are important in furthering our understanding of global chemical and climatic phenomena. They are the following: (1) to accurately measure the temporal and spatial distributions of anthropogenic gases that contribute the majority of reactive halogen to the stratosphere and/or are strong infrared absorbers (chlorocarbons, chlorofluorocarbons – CFCs, bromocarbons, hydrochlorofluorocarbons – HCFCs, hydrofluorocarbons – HFCs and polyfluorinated compounds (perfluorocarbons – PFCs), nitrogen trifluoride – NF3, sulfuryl fluoride – SO2F2, and sulfur hexafluoride – SF6) and use these measurements to determine the global rates of their emission and/or destruction (i.e., lifetimes); (2) to accurately measure the global distributions and temporal behaviors and determine the sources and sinks of non-CO2 biogenic–anthropogenic gases important to climate change and/or ozone depletion (methane – CH4, nitrous oxide – N2O, carbon monoxide – CO, molecular hydrogen – H2, methyl chloride – CH3Cl, and methyl bromide – CH3Br); (3) to identify new long-lived greenhouse and ozone-depleting gases (e.g., SO2F2, NF3, heavy PFCs (C4F10, C5F12, C6F14, C7F16, and C8F18) and hydrofluoroolefins (HFOs; e.g., CH2 = CFCF3) have been identified in AGAGE), initiate the real-time monitoring of these new gases, and reconstruct their past histories from AGAGE, air archive, and firn air measurements; (4) to determine the average concentrations and trends of tropospheric hydroxyl radicals (OH) from the rates of destruction of atmospheric trichloroethane (CH3CCl3), HFCs, and HCFCs and estimates of their emissions; (5) to determine from atmospheric observations and estimates of their destruction rates the magnitudes and distributions by region of surface sources and sinks of all measured gases; (6) to provide accurate data on the global accumulation of many of these trace gases that are used to test the synoptic-, regional-, and global-scale circulations predicted by three-dimensional models; and (7) to provide global and regional measurements of methane, carbon monoxide, and molecular hydrogen and estimates of hydroxyl levels to test primary atmospheric oxidation pathways at midlatitudes and the tropics. Network Information and Data Repository: http://agage.mit.edu/data or http://cdiac.ess-dive.lbl.gov/ndps/alegage.html (https://doi.org/10.3334/CDIAC/atg.db1001).
2018
Background: This paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey.
Results: Correlations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5 km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75–100 km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of < 40% were found for As, Cr, Cu, Hg, Pb, and V. Land use-dependent predictions of spatial patterns split up Europe into investigation areas revealing potentially high (= above-average) or low (= below-average) correlation coefficients.
Conclusions: LDA is an eligible method identifying and ranking boundary conditions of correlations between atmospheric deposition and respective concentrations of heavy metals in moss and related mapping considering the influence of the land use around moss sampling sites.
2018
Interdecadal change in the relationship between the East Asian winter monsoon (EAWM) and the Arctic Oscillation (AO) has been documented by many studies. This study, utilizing the model outputs from phase 5 of the Coupled Model Intercomparison Project (CMIP5), evaluates the ability of the coupled models in CMIP5 to capture the intensified relationship between the EAWM and winter AO since the 1980s, and further projects the evolution of the EAWM–AO relationship during the 21st century. It is found that the observed evolution of the EAWM–AO relationship can be reproduced well by some coupled models (e.g., GFDL-ESM2M, GISS-E2-H, and MPI-ESM-MR). The coupled models’ simulations indicate that the impact of winter AO on the EAWM-related circulation and East Asian winter temperature has strengthened since the 1980s. Such interdecadal change in the EAWM–AO relationship is attributed to the intensified propagation of stationary planetary waves associated with winter AO. Projections under the RCP4.5 and RCP8.5 scenarios suggest that the EAWM–AO relationship is significant before the 2030s and after the early 2070s, and insignificant during the 2060s, but uncertain from the 2030s to the 2050s.
2018
Environmental contaminants are found throughout Arctic marine ecosystems, and their presence in seabirds has been
associated with toxicological responses. However, there are few studies of genotoxicity in Arctic avian wildlife. The purpose of
the present study was to quantify deoxyribonucleic acid (DNA) damage in lymphocytes of selected seabird species and to
examine whether accumulation of organohalogen contaminants (SOHCs) affects DNA damage. Blood was sampled from
common eider (Somateria mollissima), black guillemot (Cepphus grylle), black-legged kittiwake (Rissa tridactyla), glaucous gull
(Larus hyperboreus), arctic skua (Stercorarius parasiticus), and great skua (Stercorarius skua) in Kongsfjorden, Svalbard (Norway).
Contaminant concentrations found in the 6 species differed, presumably because of foraging ecology and biomagnification.
Despite large differences in contaminant concentrations, ranging from SOHCs 3.3 ng/g wet weight in the common eider to
SOHCs 895 ng/g wet weight in the great skua, there was no strong difference among the species in baseline DNA damage or
sensitivity to a genotoxic stressor (hydrogen peroxide). Baseline levels of DNA damage were low, with median values ranging
from 1.7% in the common eider to 8.6% in the great skua. There were no associations between DNA damage and contaminants
in the investigated species, suggesting that contaminant concentrations in Kongsfjorden are too low to evoke genotoxic effects,
or possibly that lymphocytes are resistant to strand breakage. Clearly, genotoxicity is a topic for future studies of Arctic seabirds
Arctic; Seabirds; Genotoxicity; Comet Assay; Persistent organic pollutants; Perfluoroalkyl substances
2018
2018
Sudden Stratospheric Warmings (SSW) affect the chemistry and dynamics of the middle atmosphere. Major warmings occur roughly every second winter in the Northern Hemisphere (NH), but has only been observed once in the Southern Hemisphere (SH), during the Antarctic winter of 2002. Observations by the Global Ozone Monitoring by Occultation of Stars (GOMOS, an instrument on board Envisat) during this rare event, show a 40% increase of ozone in the nighttime secondary ozone layer at subpolar latitudes compared to non-SSW years. This study investigates the cause of the mesospheric nighttime ozone increase, using the National Center for Atmospheric Research (NCAR) Whole Atmosphere Community Climate Model with specified dynamics (SD-WACCM). The 2002 SH winter was characterized by several reductions of the strength of the polar night jet in the upper stratosphere before the jet reversed completely, marking the onset of the major SSW. At the time of these wind reductions, corresponding episodic increases can be seen in the modelled nighttime secondary ozone layer. This ozone increase is attributed largely to enhanced upwelling and the associated cooling of the altitude region in conjunction with the wind reversal. This is in correspondence to similar studies of SSW induced ozone enhancements in NH. But unlike its NH counterpart, the SH secondary ozone layer appeared to be impacted less by episodic variations in atomic hydrogen. Seasonally decreasing atomic hydrogen plays however a larger role in SH compared to NH.
2018
Spatial inter-comparison of top-down emission inventories in European urban areas
This paper presents an inter-comparison of the main Top-down emission inventories currently used for air quality modelling studies at the European level. The comparison is developed for eleven European cities and compares the distribution of emissions of NOx, SO2, VOC and PPM2.5 from the road transport, residential combustion and industry sectors. The analysis shows that substantial differences in terms of total emissions, sectorial emission shares and spatial distribution exist between the datasets. The possible reasons in terms of downscaling approaches and choice of spatial proxies are analysed and recommendations are provided for each inventory in order to work towards the harmonisation of spatial downscaling and proxy calibration, in particular for policy purposes. The proposed methodology may be useful for the development of consistent and harmonised European-wide inventories with the aim of reducing the uncertainties in air quality modelling activities.
2018
2018
A multi-model comparison of meteorological drivers of surface ozone over Europe
The implementation of European emission abatement strategies has led to a significant reduction in the emissions of ozone precursors during the last decade. Ground-level ozone is also influenced by meteorological factors such as temperature, which exhibit interannual variability and are expected to change in the future. The impacts of climate change on air quality are usually investigated through air-quality models that simulate interactions between emissions, meteorology and chemistry. Within a multi-model assessment, this study aims to better understand how air-quality models represent the relationship between meteorological variables and surface ozone concentrations over Europe. A multiple linear regression (MLR) approach is applied to observed and modelled time series across 10 European regions in springtime and summertime for the period of 2000–2010 for both models and observations. Overall, the air-quality models are in better agreement with observations in summertime than in springtime and particularly in certain regions, such as France, central Europe or eastern Europe, where local meteorological variables show a strong influence on surface ozone concentrations. Larger discrepancies are found for the southern regions, such as the Balkans, the Iberian Peninsula and the Mediterranean basin, especially in springtime. We show that the air-quality models do not properly reproduce the sensitivity of surface ozone to some of the main meteorological drivers, such as maximum temperature, relative humidity and surface solar radiation. Specifically, all air-quality models show more limitations in capturing the strength of the ozone–relative-humidity relationship detected in the observed time series in most of the regions, for both seasons. Here, we speculate that dry-deposition schemes in the air-quality models might play an essential role in capturing this relationship. We further quantify the relationship between ozone and maximum temperature (mo3 − T, climate penalty) in observations and air-quality models. In summertime, most of the air-quality models are able to reproduce the observed climate penalty reasonably well in certain regions such as France, central Europe and northern Italy. However, larger discrepancies are found in springtime, where air-quality models tend to overestimate the magnitude of the observed climate penalty.
2018
2018
Seasonality of aerosol optical properties in the Arctic
Given the sensitivity of the Arctic climate to short-lived climate forcers, long-term in situ surface measurements of aerosol parameters are useful in gaining insight into the magnitude and variability of these climate forcings. Seasonality of aerosol optical properties – including the aerosol light-scattering coefficient, absorption coefficient, single-scattering albedo, scattering Ångström exponent, and asymmetry parameter – are presented for six monitoring sites throughout the Arctic: Alert, Canada; Barrow, USA; Pallas, Finland; Summit, Greenland; Tiksi, Russia; and Zeppelin Mountain, Ny-Ålesund, Svalbard, Norway. Results show annual variability in all parameters, though the seasonality of each aerosol optical property varies from site to site. There is a large diversity in magnitude and variability of scattering coefficient at all sites, reflecting differences in aerosol source, transport, and removal at different locations throughout the Arctic. Of the Arctic sites, the highest annual mean scattering coefficient is measured at Tiksi (12.47Mm−1), and the lowest annual mean scattering coefficient is measured at Summit (1.74Mm−1). At most sites, aerosol absorption peaks in the winter and spring, and has a minimum throughout the Arctic in the summer, indicative of the Arctic haze phenomenon; however, nuanced variations in seasonalities suggest that this phenomenon is not identically observed in all regions of the Arctic. The highest annual mean absorption coefficient is measured at Pallas (0.48Mm−1), and Summit has the lowest annual mean absorption coefficient (0.12Mm−1). At the Arctic monitoring stations analyzed here, mean annual single-scattering albedo ranges from 0.909 (at Pallas) to 0.960 (at Barrow), the mean annual scattering Ångström exponent ranges from 1.04 (at Barrow) to 1.80 (at Summit), and the mean asymmetry parameter ranges from 0.57 (at Alert) to 0.75 (at Summit). Systematic variability of aerosol optical properties in the Arctic supports the notion that the sites presented here measure a variety of aerosol populations, which also experience different removal mechanisms. A robust conclusion from the seasonal cycles presented is that the Arctic cannot be treated as one common and uniform environment but rather is a region with ample spatiotemporal variability in aerosols. This notion is important in considering the design or aerosol monitoring networks in the region and is important for informing climate models to better represent short-lived aerosol climate forcers in order to yield more accurate climate predictions for the Arctic.
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2018
In birds, incubation‐related behaviors and brood patch formation are influenced by hormonal regulation such as prolactin secretion. Brood patch provides efficient heat transfer between the incubating parent and the developing embryo in the egg. Importantly, several environmental contaminants are already known to have adverse effects on avian reproduction. However, relatively little is known about the effect of contaminants on incubation temperature (Tinc) in wild birds. By using temperature thermistors placed into artificial eggs, we investigated whether the most contaminated parent birds are less able to provide appropriate egg warming and thus less committed to incubating their clutch. Specifically, we investigated the relationships among 3 groups of contaminants (organochlorines, perfluoroalkyl substances [PFASs], and mercury [Hg]) with Tinc and also with prolactin concentrations and brood patch size in incubating Arctic black‐legged kittiwakes (Rissa tridactyla). Our results reveal that among the organochlorines considered, only blood levels of oxychlordane, the main metabolite of chlordane, a banned pesticide, were negatively related to the minimum incubation temperature in male kittiwakes. Levels of PFASs and Hg were unrelated to Tinc in kittiwakes. Moreover, our study suggests a possible underlying mechanism: since we reported a significant and negative association between blood oxychlordane concentrations and the size of the brood patch in males. Finally, this reduced Tinc in the most oxychlordane‐contaminated kittiwakes was associated with a lower egg hatching probability.
2018
Curating scientific information in knowledge infrastructures
Interpreting observational data is a fundamental task in the sciences, specifically in earth and environmental science where observational data are increasingly acquired, curated, and published systematically by environmental research infrastructures. Typically subject to substantial processing, observational data are used by research communities, their research groups and individual scientists, who interpret such primary data for their meaning in the context of research investigations. The result of interpretation is information—meaningful secondary or derived data—about the observed environment. Research infrastructures and research communities are thus essential to evolving uninterpreted observational data to information. In digital form, the classical bearer of information are the commonly known “(elaborated) data products,” for instance maps. In such form, meaning is generally implicit e.g., in map colour coding, and thus largely inaccessible to machines. The systematic acquisition, curation, possible publishing and further processing of information gained in observational data interpretation—as machine readable data and their machine readable meaning—is not common practice among environmental research infrastructures. For a use case in aerosol science, we elucidate these problems and present a Jupyter based prototype infrastructure that exploits a machine learning approach to interpretation and could support a research community in interpreting observational data and, more importantly, in curating and further using resulting information about a studied natural phenomenon.
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