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Solar absorption by elemental and brown carbon determined from spectral observations
Open accessAbstract
Black carbon (BC) is functionally defined as the absorbing component of atmospheric total carbonaceous aerosols (TC) and is typically dominated by soot-like elemental carbon (EC). However, organic carbon (OC) has also been shown to absorb strongly at visible to UV wavelengths and the absorbing organics are referred to as brown carbon (BrC), which is typically not represented in climate models. We propose an observationally based analytical method for rigorously partitioning measured absorption aerosol optical depths (AAOD) and single scattering albedo (SSA) among EC and BrC, using multiwavelength measurements of total (EC, OC, and dust) absorption. EC is found to be strongly absorbing (SSA of 0.38) whereas the BrC SSA varies globally between 0.77 and 0.85. The method is applied to the California region. We find TC (EC + BrC) contributes 81% of the total absorption at 675 nm and 84% at 440 nm. The BrC absorption at 440 nm is about 40% of the EC, whereas at 675 nm it is less than 10% of EC. We find an enhanced absorption due to OC in the summer months and in southern California (related to forest fires and secondary OC). The fractions and trends are broadly consistent with aerosol chemical-transport models as well as with regional emission inventories, implying that we have obtained a representative estimate for BrC absorption. The results demonstrate that current climate models that treat OC as nonabsorbing are underestimating the total warming effect of carbonaceous aerosols by neglecting part of the atmospheric heating, particularly over biomass-burning regions that emit BrC.
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Cites
Warming and earlier spring increase western U.S. forest wildfire activity.
Westerling, A. L., Hidalgo, H. G., Cayan, D. R., & Swetnam, T. W. (2006) · Science · doi:10.1126/science.1128834 · Cited by 5,176
Light Absorption by Carbonaceous Particles: An Investigative Review
Bond, T. C., & Bergstrom, R. W. (2006) · Aerosol Science and Technology · doi:10.1080/02786820500421521 · Cited by 2,980
Black carbon or brown carbon? The nature of light-absorbing carbonaceous aerosols
Andreae, M. O., & Gelencsér, A. (2006) · Atmospheric Chemistry and Physics · doi:10.5194/acp-6-3131-2006 · Cited by 2,006
Hoelzemann, J. J., Longo, K. M., Fonseca, R. M., do Rosário, N. M. E., Elbern, H., Freitas, S. R., & Pires, C. (2009) · Journal of Geophysical Research: Atmospheres · doi:10.1029/2008jd010369 · Cited by 64
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Air Quality and Climate Connections
Fiore, A. M., Naik, V., & Leibensperger, E. M. (2015) · Journal of the Air & Waste Management Association · doi:10.1080/10962247.2015.1040526 · Cited by 537
Molecular Chemistry of Atmospheric Brown Carbon Inferred from a Nationwide Biomass Burning Event
Lin, P., Bluvshtein, N., Rudich, Y., Nizkorodov, S. A., Laskin, J., & Laskin, A. (2017) · Environmental Science & Technology · doi:10.1021/acs.est.7b02276 · Cited by 382
Photochemical processing of aqueous atmospheric brown carbon
Zhao, R., Lee, A. K. Y., Huang, L., Li, X., Yang, F., & Abbatt, J. P. D. (2015) · Atmospheric Chemistry and Physics · doi:10.5194/acp-15-6087-2015 · Cited by 373
Lee, H. J. (., Aiona, P. K., Laskin, A., Laskin, J., & Nizkorodov, S. A. (2014) · Environmental Science & Technology · doi:10.1021/es502515r · Cited by 359
Lin, P., Liu, J., Shilling, J. E., Kathmann, S. M., Laskin, J., & Laskin, A. (2015) · Physical Chemistry Chemical Physics · doi:10.1039/c5cp02563j · Cited by 306
Metadata
- Authors
- Bahadur, R., Praveen, P. S., Xu, Y., & Ramanathan, V.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2012-10-08
- Volume
- 109
- Issue
- 43
- Pages
- 17366-17371
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2060117860
- Cited by
- 412
- References
- 4
- FWCI
- 13.28
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Bahadur, R., Praveen, P. S., Xu, Y., & Ramanathan, V. (2012). Solar absorption by elemental and brown carbon determined from spectral observations. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1205910109
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