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

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, whilemore » 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.« less

Authors:
; ; ; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab. (EMSL)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1226386
Alternate Identifier(s):
OSTI ID: 1227599
Report Number(s):
PNNL-SA-108978
Journal ID: ISSN 1680-7324
Grant/Contract Number:  
AC05-76RLO1830; AC05-76RL01830
Resource Type:
Published Article
Journal Name:
Atmospheric Chemistry and Physics (Online)
Additional Journal Information:
Journal Name: Atmospheric Chemistry and Physics (Online); Journal Volume: 15; Journal Issue: 22; Journal ID: ISSN 1680-7324
Publisher:
European Geosciences Union
Country of Publication:
Germany
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; Environmental Molecular Sciences Laboratory

Citation Formats

Zhang, R., Wang, H., Hegg, D. A., Qian, Y., Doherty, S. J., Dang, C., Ma, P.-L., Rasch, P. J., and Fu, Q. Quantifying sources of black carbon in western North America using observationally based analysis and an emission tagging technique in the Community Atmosphere Model. Germany: N. p., 2015. Web. doi:10.5194/acp-15-12805-2015.
Zhang, R., Wang, H., Hegg, D. A., Qian, Y., Doherty, S. J., Dang, C., Ma, P.-L., Rasch, P. J., & Fu, Q. Quantifying sources of black carbon in western North America using observationally based analysis and an emission tagging technique in the Community Atmosphere Model. Germany. doi:10.5194/acp-15-12805-2015.
Zhang, R., Wang, H., Hegg, D. A., Qian, Y., Doherty, S. J., Dang, C., Ma, P.-L., Rasch, P. J., and Fu, Q. Wed . "Quantifying sources of black carbon in western North America using observationally based analysis and an emission tagging technique in the Community Atmosphere Model". Germany. doi:10.5194/acp-15-12805-2015.
@article{osti_1226386,
title = {Quantifying sources of black carbon in western North America using observationally based analysis and an emission tagging technique in the Community Atmosphere Model},
author = {Zhang, R. and Wang, H. and Hegg, D. A. and Qian, Y. and Doherty, S. J. and Dang, C. and Ma, P.-L. and Rasch, P. J. and Fu, Q.},
abstractNote = {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.},
doi = {10.5194/acp-15-12805-2015},
journal = {Atmospheric Chemistry and Physics (Online)},
number = 22,
volume = 15,
place = {Germany},
year = {2015},
month = {11}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.5194/acp-15-12805-2015

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Cited by: 4 works
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