AAAR 35th Annual Conference October 17 - October 21, 2016 Oregon Convention Center Portland, Oregon, USA
Abstract View
Evaluation of the Absorption Ångström Exponents for Traffic and Wood Burning in the Aethalometer Based Source Apportionment Using Radiocarbon Measurements of Ambient Aerosol
ANDRE PRÉVÔT, Peter Zotter, Hanna Herich, Martin Gysel, Imad El Haddad, Yanlin Zhang, Grisa Mocnik, Christoph Hueglin, Urs Baltensperger, Soenke Szidat, Paul Scherrer Institute
Abstract Number: 321 Working Group: Carbonaceous Aerosols in the Atmosphere
Abstract Black carbon (BC) measured by a multi-wavelength Aethalometer can be apportioned to traffic and wood burning. The method is based on the differences in the wavelength dependence of the aerosol absorption for these two sources (Sandradewi et al. 2008). This dependence is typically parameterized by the Ångström absorption exponent (α). While the spectral dependence of the traffic-related BC light absorption is low, wood smoke particles are characterized by enhanced light absorption in the blue and near ultraviolet. Source apportionment results using this methodology are hence strongly dependent on the α–values assumed for the pure emissions from these two sources (traffic αTR, and wood burning αWB). Most studies use a single αTR and αWB pair in the Aethalometer model, derived from previous work. However, an accurate determination of the source specific α-values is currently lacking, and in some recent publications the applicability of the Aethalometer model was questioned.
The best combination of αTR and αWB (0.9 and 1.68, respectively) was obtained by fitting the Aethalometer model outputs against the fossil fraction of EC (ECF/EC) derived from 14C measurements. Aethalometer and 14C source apportionment results are well correlated (r = 0.81) and the fitting residuals exhibit only a minor positive bias of 1.6% and an average precision of 9.3%. This indicates that the Aethalometer model reproduces reasonably well the 14C results for all stations investigated in this study using our best estimate of a single αWB and αTR pair. We also show that αWB and αTR values previously used in literature (~2) significant residuals and biases. Therefore we recommend to use the best α combination as obtained here (αTR = 0.9 and αWB = 1.68) in future studies when no or only limited additional information are available.
Sandradewi et al. (2008) Environ. Sci. Technol. 42, 3316-3323.