A21D-3065:
Identification of absorbing organic (brown carbon) aerosols through Sun Photometry: results from AEROCAN / AERONET stations in high Arctic and urban Locations

Tuesday, 16 December 2014
Gaige Hunter Kerr1, Jai Prakash Chaubey2, N. T. O'Neill2, P. Hayes3 and D. E. Atkinson4, (1)Cornell University, Department of Earth and Atmospheric Sciences, Ithaca, NY, United States, (2)CARTEL, Universite de Sherbrooke, Sherbrooke, QC, Canada, (3)Universite de Montreal, Department of Chemistry, Montreal, QC, Canada, (4)University of Alaska Fairbanks, Department of Atmospheric Sciences, Fairbanks, AK, United States
Abstract:
Light absorbing organic aerosols or brown carbon (BrC) aerosols are prominent species influencing the absorbing aerosol optical depth (AAOD) of the total aerosol optical depth (AOD) in the UV wavelength region. They, along with dust, play an important role in modifying the spectral AAOD and the spectral AOD in the UV region: this property can be used to discriminate BrC aerosols from both weakly absorbing aerosols such as sulfates as well as strongly absorbing aerosols such as black carbon (BC). In this study we use available AERONET inversions (level 1.5) retrieved for the measuring period from 2009 to 2013, for the Arctic region (Eureka, Barrow and Hornsund), Urban/ Industrial regions (Kanpur, Beijing), and the forest regions (Alta Foresta and Mongu), to identify BrC aerosols. Using Dubovik’s inversion algorithm results, we analyzed parameters that were sensitive to BrC presence, notably AAOD, AAODBrC estimated using the approach of Arola et al. [2011], the fine-mode-aerosol absorption derivative (αf, abs) and the fine-mode-aerosol absorption 2nd derivative (αf, abs'), all computed at a near UV wavelength (440 nm). Temporal trends of these parameters were investigated for all test stations and compared to available volume sampling surface data as a means of validating / evaluating the sensitivity of ostensible sunphotometer indicators of BrC aerosols to the presence of BrC as measured using independent indicators.

Reference:

Arola, A., Schuster, G., Myhre, G., Kazadzis, S., Dey, S., and Tripathi, S. N.: Inferring absorbing organic carbon content from AERONET data, Atmos. Chem. Phys., 11, 215–225, doi:10.5194/acp-11-215-2011, 2011