01 Sep 2020

01 Sep 2020

Review status: a revised version of this preprint was accepted for the journal AMT and is expected to appear here in due course.

Determination of Aethalometer multiple-scattering enhancement parameters and impact on source apportionment during the winter 2017–2018 EMEP/ACTRIS/COLOSSAL campaign in Milan

Vera Bernardoni1, Luca Ferrero2, Ezio Bolzacchini2, Alice Corina Forello1, Asta Gregorič3,4, Dario Massabò5, Griša Močnik4,6, Paolo Prati5, Martin Rigler3, Luca Santagostini2, Francesca Soldan1,a, Sara Valentini1, Gianluigi Valli1, and Roberta Vecchi1 Vera Bernardoni et al.
  • 1Dipartimento di Fisica “A. Pontremoli”, Università degli Studi di Milano & INFN-Milan, 20133 Milano, Italy
  • 2GEMMA and POLARIS Centre, Università degli Studi di Milano-Bicocca, 20126 Milano, Italy
  • 3Aerosol d.o.o., Kamniška 39A, SI-1000 Ljubljana, Slovenia
  • 4Center for Atmospheric Research, University of Nova Gorica, Vipavska 11c, SI-5270 Ajdovščina, Slovenia
  • 5Dip. di Fisica Università di Genova & INFN Sezione di Genova, Via Dodecaneso 33, 16146 Genova, Italy
  • 6Department of Condensed Matter Physics, Jozef Stefan Institute, Jamova 39, SI-1000 Ljubljana, Slovenia
  • anow at: Ricerca sul Sistema Energetico – RSE S.p.A., 20134 Milan, Italy

Abstract. In the frame of the EMEP/ACTRIS/COLOSSAL campaign in Milan during winter 2018, equivalent black carbon measurements using the Aethalometer 31 (AE31), the Aethalometer 33 (AE33), and the Multi-Angle Absorption Photometer (MAAP) were carried out together with levoglucosan analyses on 12-h resolved PM2.5 samples collected in parallel.

From AE31 and AE33 data, the loading-corrected aerosol attenuation coefficients (bATN) were calculated at 7 wavelengths (λs, where λ = 370, 470, 520, 590, 660, 880, 950 nm). Aerosol absorption coefficient at 637 nm (babs_MAAP) was determined by MAAP measurements. Furthermore, babs was also measured at 4 wavelengths (405, 532, 635, 780 nm) on the 12-h resolved PM2.5 samples by a polar photometer (PP_UniMI).

After comparing PP_UniMI and MAAP results, we exploited PP_UniMI data to evaluate the filter multiple-scattering enhancement parameter at different wavelengths for AE31 and AE33. We obtained instrument- and wavelength-dependent multiple-scattering parameters by linear regression of the Aethalometer bATN against the babs measured by PP_UniMI. We found significant filter material, and hence instrumental, dependence of the multiple-scattering enhancement parameter with the difference up to 30 % between the AE31 and the AE33 tapes. The wavelength dependence and day/night variations were small – the difference between the smallest and largest value was up to 6 %.

Data from the different instruments were used as input to the so-called “Aethalometer model” for optical source apportionment and instrument-dependence of the results was investigated. Inconsistencies among the source apportionment were found fixing the AE31 and AE33 multiple-scattering enhancement parameters to their usual values. Opposite, optimised multiple-scattering enhancement parameters led to 5 % agreement among the approaches.

Also, the component-apportionment “MWAA model” was applied to the dataset. It resulted less sensitive to the instrument and the number of wavelengths, whereas significant differences in the determination of the absorption Ångström exponent for brown carbon were found (up to 22 %).

Vera Bernardoni et al.

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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Vera Bernardoni et al.

Vera Bernardoni et al.


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Short summary
An instrument-dependent wavelength-independent parameter (C) is often used to face multiple-scattering issues affecting aerosol light-absorption measurements by Aethalometers. Opposite, we determined multi-wavelength C by comparison with absorption measurements of samples collected in parallel performed by an in-house developed instrument. Considering C wavelength-dependence, harmonized results were obtained applying source and component apportionment models to data from different Aethalometers.