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1.
Online chemical characterization and sources of submicron aerosol in the major mediterranean port city of Piraeus, Greece
Iasonas Stavroulas, Georgios Grivas, Eleni Liakakou, Panayiotis Kalkavouras, Aikaterini Bougiatioti, Dimitris G. Kaskaoutis, Maria Lianou, Kyriaki Papoutsidaki, M. Tsagkaraki, Evangelos Gerasopoulos, Pavlos Zarmpas, Nikolaos Mihalopoulos, 2021, original scientific article

Abstract: Port cities are affected by a wide array of emissions, including those from the shipping, road transport, and residential sectors; therefore, the characterization and apportionment of such sources in a high temporal resolution is crucial. This study presents measurements of fine aerosol chemical composition in Piraeus, one of the largest European ports, during two monthly periods (winter vs. summer) in 2018–2019, using online instrumentation (Aerosol Chemical Speciation Monitor—ACSM, 7-λ aethalometer). PMF source apportionment was performed on the ACSM mass spectra to quantify organic aerosol (OA) components, while equivalent black carbon (BC) was decomposed to its fossil fuel combustion and biomass burning (BB) fractions. The combined traffic, shipping and, especially, residential emissions led to considerably elevated submicron aerosol levels (22.8 μg m−3) in winter, which frequently became episodic late at night under stagnant conditions. Carbonaceous compounds comprised the major portion of this submicron aerosol in winter, with mean OA and BC contributions of 61% (13.9 μg m−3) and 16% (3.7 μg m−3), respectively. The contribution of BB to BC concentrations was considerable and spatially uniform. OA related to BB emissions (fresh and processed) and hydrocarbon-like OA (from vehicular traffic and port-related fossil fuel emissions including shipping) accounted for 37% and 30% of OA, respectively. In summer, the average PM1 concentration was significantly lower (14.8 μg m−3) and less variable, especially for the components associated with secondary aerosols (such as OA and sulfate). The effect of the port sector was evident in summer and maintained BC concentrations at high levels (2.8 μg m−3), despite the absence of BB and improved atmospheric dispersion. Oxygenated components yielded over 70% of OA in summer, with the more oxidized secondary component of regional origin being dominant (41%) despite the intensity of local sources, in the Piraeus environment. In general, with respect to local sources that can be the target of mitigation policies, this work highlights the importance of port-related activities but also reveals the extensive wintertime impact of residential wood burning. While a separation of the BB source is feasible, more research is needed on how to disentangle the short-term effects of different fossil-fuel combustion sources.
Keywords: Athens, harbor, shipping emissions, PM1, chemical speciation, organic aerosol, black carbon, ACSM, aethalometer, PMF
Published in RUNG: 10.05.2024; Views: 849; Downloads: 4
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2.
Determining the Aethalometer multiple scattering enhancement factor C from the filter loading parameter
Luca Ferrero, Niccolò Losi, Martin Rigler, Asta Gregorič, C. Colombi, L. D'Angelo, E. Cuccia, A. M. Cefalì, I. Gini, A. Doldi, 2024, original scientific article

Abstract: Light-absorbing aerosols heat the atmosphere; an accurate quantification of their absorption coefficient is mandatory. However, standard reference instruments (CAPS, MAAP, PAX, PTAAM) are not always available at each measuring site around the world. By integrating all previous published studies concerning the Aethalometers, the AE33 filter loading parameter, provided by the dual-spot algorithm, were used to determine the multiple scattering enhancement factor from the Aethalometer itself (hereinafter CAE) on an yearly and a monthly basis. The method was developed in Milan, where Aethalometer measurements were compared with MAAP data; the comparison showed a good agreement in terms of equivalent black carbon (R2 = 0.93; slope = 1.02 and a negligible intercept = 0.12 μg m−3) leading to a yearly experimental multiple scattering enhancement factor of 2.51 ± 0.04 (hereinafter CMAAP). On a yearly time base the CAE values obtained using the new approach was 2.52 ± 0.01, corresponding to the experimental one (CMAAP). Considering the seasonal behavior, higher experimental CMAAP and computed CAE values were found in summer (2.83 ± 0.12) whereas, the lower ones in winter/early-spring (2.37 ± 0.03), in agreement with the single scattering albedo behavior in the Po Valley. Overall, the agreement between the experimental CMAAP and CAE showed a root mean squared error (RMSE) of just 0.038 on the CMAAP prediction, characterized by a slope close to 1 (1.001 ± 0.178), a negligible intercept (−0.002 ± 0.455) and a high degree of correlation (R2 = 0.955). From an environmental point of view, the application of a dynamic (space/time) determination of CAE increases the accuracy of the aerosol heating rate (compared to applying a fixed C value) up to 16 % solely in Milan, and to 114 % when applied in the Arctic at 80°N.
Keywords: aethalometer, C factor, loading parameter, MAAP, heating rate
Published in RUNG: 02.02.2024; Views: 1674; Downloads: 7
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Black carbon emission factors of diesel vehicles : results from roadside measurement
Bálint Alföldy, Asta Gregorič, Matic Ivančič, Irena Ježek, Martin Rigler, 2021, published scientific conference contribution abstract

Keywords: black carbon, emission factor, aethalometer
Published in RUNG: 17.11.2021; Views: 2565; Downloads: 9
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Determination of Aethalometer multiple-scattering enhancement parameters and impact on source apportionment during the winter 2017/18 EMEP/ACTRIS/COLOSSAL campaign in Milan
Vera Bernardoni, Luca Ferrero, Ezio Bolzacchini, Alice Corina Forello, Asta Gregorič, Dario Massabo, Griša Močnik, Paolo Prati, Martin Rigler, Luca Santagostini, 2021, original scientific article

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 a 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 seven wavelengths (λ, where λ values are 370, 470, 520, 590, 660, 880, and 950 nm). The aerosol absorption coefficient at 637 nm (babs_MAAP) was determined by MAAP measurements. Furthermore, babs was also measured at four 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 enhancement parameters by linear regression of the Aethalometer bATN against the babs measured by PP_UniMI. We found significant dependence of the multiple-scattering enhancement parameter on filter material, hence on the instrument, with a difference of 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. In contrast, optimised multiple-scattering enhancement parameters led to a 5 % agreement among the approaches. Also, the component apportionment “MWAA model” (Multi-Wavelength Absorption Analyzer model) was applied to the dataset. It was 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 %).
Keywords: black carbon, filter photometer, Aethalometer, source apportionment
Published in RUNG: 16.04.2021; Views: 2935; Downloads: 0
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