Evaluation of the absorption Ångström exponents for traffic and wood burning in the Aethalometer-based source apportionment using radiocarbon measurements of ambient aerosol
- 1Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), 5232 Villigen PSI, Switzerland
- 2Laboratory for Air Pollution and Environmental Technology, Swiss Federal Laboratories for Materials Science and Technology (Empa), Überlandstrasse 129, 8600 Dübendorf, Switzerland
- 3Department of Chemistry and Biochemistry, University of Bern, Bern, Switzerland
- 4Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
- 5Laboratory of Radiochemistry and Environmental Chemistry, Paul Scherrer Institute (PSI), 5232 Villigen PSI, Switzerland
- 6Research and Development Department, Aerosol d.o.o., Ljubljana, Slovenia
- 7Condensed Matter Physics Department, Jožef Stefan Institute, Ljubljana, Slovenia
- anow at: Lucerne University of Applied Sciences and Arts, School of Engineering and Architecture, Bioenergy Research, Technikumstrasse 21, 6048 Horw, Switzerland
- bnow at: Kanton St.Gallen, Amt für Umwelt und Energie, 9001 St. Gallen, Switzerland
- cnow at: Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, 210044, Nanjing, China
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 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.
Here we present an indirect methodology for the determination of αWB and αTR 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 αTR and αWB (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 (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. 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 ECF ∕ EC as reference and constant a priori selected αTR values, αWB was also calculated for each individual data point. No clear station-to-station or season-to-season differences in αWB were observed, but αTR and αWB values are interdependent. For example, an increase in αTR by 0.1 results in a decrease in αWB by 0.1. The fitting residuals of different αTR and αWB combinations depend on ECF ∕ EC such that a good agreement cannot be obtained over the entire ECF ∕ EC range using other α pairs. Additional combinations of αTR = 0.8, and 1.0 and αWB = 1.8 and 1.6, respectively, are possible but only for ECF ∕ EC between ∼ 40 and 85 %. Applying α values previously used in the literature such as αWB of ∼ 2 or any αWB in combination with αTR = 1.1 to our data set results in large residuals. 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 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.