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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 15, issue 22 | Copyright
Atmos. Chem. Phys., 15, 12805-12822, 2015
https://doi.org/10.5194/acp-15-12805-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 18 Nov 2015

Research article | 18 Nov 2015

Quantifying sources of black carbon in western North America using observationally based analysis and an emission tagging technique in the Community Atmosphere Model

R. Zhang2,5,6,1, H. Wang2, D. A. Hegg3, Y. Qian2, S. J. Doherty4, C. Dang3, P.-L. Ma2, P. J. Rasch2, and Q. Fu3,1 R. Zhang et al.
  • 1Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, Gansu, China
  • 2Atmospheric Sciences and Global Change Division, Pacific Northwest National Laboratory (PNNL), Richland, WA 99352, USA
  • 3Department of Atmospheric Sciences, Box 351640, University of Washington, Seattle, WA 98195, USA
  • 4Joint Institute for the Study of Atmosphere and Ocean, 3737 Brooklyn Ave NE, Seattle, WA 98195, USA
  • 5Institute for Climate and Global Change Research & School of Atmospheric Sciences, Nanjing University, Nanjing, 210023, China
  • 6Collaborative Innovation Center of Climate Change, Jiangsu Province, Nanjing, 210023, China

Abstract. The Community Atmosphere Model (CAM5), equipped with a technique to tag black carbon (BC) emissions by source regions and types, has been employed to establish source–receptor relationships for atmospheric BC and its deposition to snow over western North America. The CAM5 simulation was conducted with meteorological fields constrained by reanalysis for year 2013 when measurements of BC in both near-surface air and snow are available for model evaluation. We find that CAM5 has a significant low bias in predicted mixing ratios of BC in snow but only a small low bias in predicted atmospheric concentrations over northwestern USA and western Canada. Even with a strong low bias in snow mixing ratios, radiative transfer calculations show that the BC-in-snow darkening effect is substantially larger than the BC dimming effect at the surface by atmospheric BC. Local sources contribute more to near-surface atmospheric BC and to deposition than distant sources, while the latter are more important in the middle and upper troposphere where wet removal is relatively weak. Fossil fuel (FF) is the dominant source type for total column BC burden over the two regions. FF is also the dominant local source type for BC column burden, deposition, and near-surface BC, while for all distant source regions combined the contribution of biomass/biofuel (BB) is larger than FF. An observationally based positive matrix factorization (PMF) analysis of the snow-impurity chemistry is conducted to quantitatively evaluate the CAM5 BC source-type attribution. While CAM5 is qualitatively consistent with the PMF analysis with respect to partitioning of BC originating from BB and FF emissions, it significantly underestimates the relative contribution of BB. In addition to a possible low bias in BB emissions used in the simulation, the model is likely missing a significant source of snow darkening from local soil found in the observations.

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We use a global climate model with an explicit source tagging technique to quantify contributions of emissions from various geographical regions and sectors to BC in North America. Model results are evaluated against measurements of near-surface and in-snow BC. We found strong spatial variations of BC and its radiative forcing that can be quantitatively attributed to the various source origins, and also identified a significant source of BC in snow that is likely missing in most climate models.
We use a global climate model with an explicit source tagging technique to quantify...
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