Evaluation of the absorption Ångström exponents for traffic and wood burning in the Aethalometer-based source apportionment using radiocarbon measurements of ambient aerosol

Abstract. Equivalent black carbon (EBC) measured by a multi-wavelength Aethalometer can be apportioned to traffic and wood burning. The method is based on the differences in the dependence of aerosol absorption on the wavelength of light used to investigate the sample, parameterized by the source-specific absorption Ångström exponent (α). While the spectral dependence (defined as α values) of the traffic-related EBC light absorption is low, wood smoke particles feature 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 both types of emissions: traffic α_TR, and wood burning α_WB. Most studies use a single α_TR and α_WB 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.

Here we present an indirect methodology for the determination of α_WB and α_TR by comparing the source apportionment of EBC using the Aethalometer model with ¹⁴C measurements of the EC fraction on 16 to 40 h filter samples from several locations and campaigns across Switzerland during 2005–2012, mainly in winter. The data obtained at eight stations with different source characteristics also enabled the evaluation of the performance and the uncertainties of the Aethalometer model in different environments. The best combination of α_TR and α_WB (0.9 and 1.68, respectively) was obtained by fitting the Aethalometer model outputs (calculated with the absorption coefficients at 470 and 950 nm) against the fossil fraction of EC (EC_F ∕ 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 α_WB and α_TR pair. Combining the EC, ¹⁴C, and Aethalometer measurements further allowed assessing the dependence of the mass absorption cross section (MAC) of EBC on its source. Results indicate no significant difference in MAC at 880 nm between EBC originating from traffic or wood-burning emissions. Using EC_F ∕ EC as reference and constant a priori selected α_TR values, α_WB was also calculated for each individual data point. No clear station-to-station or season-to-season differences in α_WB were observed, but α_TR and α_WB values are interdependent. For example, an increase in α_TR by 0.1 results in a decrease in α_WB by 0.1. The fitting residuals of different α_TR and α_WB combinations depend on EC_F ∕ EC such that a good agreement cannot be obtained over the entire EC_F ∕ EC range using other α pairs. Additional combinations of α_TR  =  0.8, and 1.0 and α_WB  =  1.8 and 1.6, respectively, are possible but only for EC_F ∕ EC between  ∼  40 and 85 %. Applying α values previously used in the literature such as α_WB of  ∼  2 or any α_WB in combination with α_TR  =  1.1 to our data set results in large residuals. Therefore we recommend to use the best α combination as obtained here (α_TR  =  0.9 and α_WB  =  1.68) in future studies when no or only limited additional information like ¹⁴C measurements are available. However, these results were obtained for locations impacted by black carbon (BC) mainly from traffic consisting of a modern car fleet and residential wood combustion with well-constrained combustion efficiencies. For regions of the world with different combustion conditions, additional BC sources, or fuels used, further investigations are needed.