scholarly journals Observed and Modeled Black Carbon Deposition and Sources in the Western Russian Arctic 1800–2014

Author(s):  
Meri M. Ruppel ◽  
Sabine Eckhardt ◽  
Antto Pesonen ◽  
Kenichiro Mizohata ◽  
Markku J. Oinonen ◽  
...  
2020 ◽  
Author(s):  
Marion Réveillet ◽  
Marie Dumont ◽  
Simon Gascoin ◽  
Pierre Nabat ◽  
Matthieu Lafaysse ◽  
...  

<p>Light absorbing particles such as black carbon(BC) or mineral dust are known to darken the snow surface when deposited on the snow cover and amplify several snow-albedo feedbacks, drastically modifying the snowpack evolution and the snow cover duration. Mineral dust deposition on snow is generally more variablein time than black carbon deposition and can exhibit both a high inter and intra annual variability. In France, the Alps and the Pyrenees mountain ranges are affected by large dust deposition events originating from the Sahara . The aim of this study is to quantify the impact of these impurities on the snow cover variability over the last 39 years (1979-2018).</p><p>For that purpose, the detailed snowpack model Crocus with an explicit representation of impurities is forced by SAFRAN meteorological reanalysis and a downscaling of the simulated deposition fluxes from a regional climate model (ALADIN-Climate). Different simulations are performed: (i) considering dust and/or BC (i.e. explicit representation), (ii) without impurities and (iii) considering an implicit representation (i.e. empirical parameterization based on a decreasing law of the albebo with snow age).</p><p>Simulations are compared at point scale to the snow depth measured at more than 200 Meteo-France’s stations in each massif, and spatially evaluated over the 2000-2018 period in comparing thesnow cover area, snow cover duration and the Jacard index to MODIS snow products. Scores are generally better when considering the explicit representation of the impurities than when using the snow age as a proxy for light absorbing particles content.</p><p>Results indicate that dust and BC have a significant impact on the snow cover duration with strong variations in the magnitude of the impact from one year to another and from one location to another.We also investigate the contribution of light absorbing particles depositionto snow cover inter-annual variability based on statistical approaches.</p>


Chemosphere ◽  
2017 ◽  
Vol 172 ◽  
pp. 242-248 ◽  
Author(s):  
Wenxue Xu ◽  
Fu Wang ◽  
Jiwei Li ◽  
Lizhu Tian ◽  
Xingyu Jiang ◽  
...  

2017 ◽  
Vol 29 (7) ◽  
pp. 2073-2081 ◽  
Author(s):  
Chuanyu Gao ◽  
Jiabao He ◽  
Jinxin Cong ◽  
Shaoqing Zhang ◽  
Guoping Wang

2015 ◽  
Vol 110 ◽  
pp. 15-22 ◽  
Author(s):  
Eva Lehndorff ◽  
Mareike Wolf ◽  
Thomas Litt ◽  
Achim Brauer ◽  
Wulf Amelung

2017 ◽  
Vol 114 (7) ◽  
pp. E1054-E1061 ◽  
Author(s):  
Patrik Winiger ◽  
August Andersson ◽  
Sabine Eckhardt ◽  
Andreas Stohl ◽  
Igor P. Semiletov ◽  
...  

Black carbon (BC) in haze and deposited on snow and ice can have strong effects on the radiative balance of the Arctic. There is a geographic bias in Arctic BC studies toward the Atlantic sector, with lack of observational constraints for the extensive Russian Siberian Arctic, spanning nearly half of the circum-Arctic. Here, 2 y of observations at Tiksi (East Siberian Arctic) establish a strong seasonality in both BC concentrations (8 ng⋅m−3 to 302 ng⋅m−3) and dual-isotope–constrained sources (19 to 73% contribution from biomass burning). Comparisons between observations and a dispersion model, coupled to an anthropogenic emissions inventory and a fire emissions inventory, give mixed results. In the European Arctic, this model has proven to simulate BC concentrations and source contributions well. However, the model is less successful in reproducing BC concentrations and sources for the Russian Arctic. Using a Bayesian approach, we show that, in contrast to earlier studies, contributions from gas flaring (6%), power plants (9%), and open fires (12%) are relatively small, with the major sources instead being domestic (35%) and transport (38%). The observation-based evaluation of reported emissions identifies errors in spatial allocation of BC sources in the inventory and highlights the importance of improving emission distribution and source attribution, to develop reliable mitigation strategies for efficient reduction of BC impact on the Russian Arctic, one of the fastest-warming regions on Earth.


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