Comparison of Filter-based Absorption Measurements of Biomass Burning Aerosol and Background Aerosol at the Mt. Bachelor Observatory

Laing, James R.; Jaffe, Daniel A.; Sedlacek, Arthur J.

doi:10.4209/aaqr.2019.06.0298

Cited by 32 publications

(40 citation statements)

References 79 publications

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“…Na (1), Nc (11) Situations with advection from the north NEa (2), NEc (12) Situations with advection from the northeast Ea (3), Ec (13) Situations with advection from the east SEa (4), SEc (14) Situations with advection from the southeast Sa (5), Sc (15) Situations with advection from the south SWa (6), SWc (16) Situations with advection from the southwest Wa (7), Wc (17) Situations with advection from the west NWa (8), NWc (18) Situations with advection from the northwest Situations without a specific direction of advection Ca (9) Central anticyclone situation (high center) Ka (10) Anticyclonic wedge or ridge of high pressure Cc (19) Central cyclonic, center of low Bc (20) Through of low pressure (different directions of air flow and frontal system in the axis of through) x (21) Unclassified situations or pressure col a-anticyclonic situation; c-cyclonic situation.…”

Section: Type Of Circulation Explanationmentioning

confidence: 99%

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Temporal Variability of Equivalent Black Carbon Components in Atmospheric Air in Southern Poland

2021

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This study assesses the air quality in Zabrze (southern Poland) based on the ambient concentrations of equivalent black carbon (eBC). eBC measurement campaigns were carried out from April 2019 to March 2020 using a modern AE33 Aethalometer, accompanied by parallel measurements of gaseous pollutants, PM10 and meteorological parameters. The use of the two-component AE33 model allows for the determination of the eBC from fossil fuel combustion (eBCff) and biomass burning (eBCbb). The obtained results showed a clear seasonal variability of eBC concentrations, with higher average levels in the heating season (4.70 µg·m−3) compared to the non-heating one (1.79 µg·m−3). In both seasons, the eBCff component had a dominant share in total eBC, which indicates significant emissions from the combustion of fossil fuels for heating purposes and from local traffic sources. The obtained results showed high correlation coefficients with gaseous and particulate pollutants, with the strongest relationship for eBC and carbon monoxide (CO). During the non-heating and heating period, both anticyclone and cyclone systems played an important role in shaping eBC, eBCff and eBCbb concentrations. High concentrations of all components occurred with a significant decrease in air temperature and solar radiation in winter.

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Section: Type Of Circulation Explanationmentioning

confidence: 99%

“…However, in the literature, both definitions are found in the part concerning the results obtained from the optical method [8,9]. Black carbon (BC) is the 2 of 23 most important light-absorbing aerosol that is co-emitted with another important fraction called brown carbon (BrC) [10,11].…”

Section: Introductionmentioning

confidence: 99%

Temporal Variability of Equivalent Black Carbon Components in Atmospheric Air in Southern Poland

2021

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“…absorption properties is still an open methodological issue especially for ambient aerosol measurements. Among filter-based instruments, the Multi-Angle Absorption Photometer (MAAP) is generally considered as a reference (Ammerlaan et al, 2017;Müller et al, 2011) and off-line measurements carried out with analogous principle will be used in this work to provide contribution to the debate on the treatment of multiple-scattering effects for Aethalometers (Backman et al, 2017;Collaud-Coen et al, 2010;Di Biagio et al, 2017;Kim et al, 2019;Laing et al, 2020;Müller et al, 2011;Saturno et al, 70 2017;Schmid et al, 2006;Segura et al, 2014;Weingartner et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

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

Bernardoni¹,

Ferrero²,

Bolzacchini³

et al. 2020

Preprint

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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 %).

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“…The aethalometer model AE31 (Magee Scientific Inc.) has been part of the permanent installation at the Pallas site since year 2005 (Lihavainen et al, 2015). It measures the aerosol absorption coefficient at seven wavelengths (370, 470, 520, 590, 660, 880, and 950 nm), with a typical nominal full width at half maximum (FWHM) of 20 nm and a measured FWHM Table 1.…”

Section: Ae31mentioning

confidence: 99%

Absorption instruments inter-comparison campaign at the Arctic Pallas station

et al. 2021

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Abstract. Aerosol light absorption was measured during a 1-month field campaign in June–July 2019 at the Pallas Global Atmospheric Watch (GAW) station in northern Finland. Very low aerosol concentrations prevailed during the campaign, which posed a challenge for the instruments' detection capabilities. The campaign provided a real-world test for different absorption measurement techniques supporting the goals of the European Metrology Programme for Innovation and Research (EMPIR) Black Carbon (BC) project in developing aerosol absorption standard and reference methods. In this study we compare the results from five filter-based absorption techniques – aethalometer models AE31 and AE33, a particle soot absorption photometer (PSAP), a multi-angle absorption photometer (MAAP), and a continuous soot monitoring system (COSMOS) – and from one indirect technique called extinction minus scattering (EMS). The ability of the filter-based techniques was shown to be adequate to measure aerosol light absorption coefficients down to around 0.01 Mm−1 levels when data were averaged to 1–2 h. The hourly averaged atmospheric absorption measured by the reference MAAP was 0.09 Mm−1 (at a wavelength of 637 nm). When data were averaged for >1 h, the filter-based methods agreed to around 40 %. COSMOS systematically measured the lowest absorption coefficient values, which was expected due to the sample pre-treatment in the COSMOS inlet. PSAP showed the best linear correlation with MAAP (slope=0.95, R2=0.78), followed by AE31 (slope=0.93). A scattering correction applied to PSAP data improved the data accuracy despite the added noise. However, at very high scattering values the correction led to an underestimation of the absorption. The AE31 data had the highest noise and the correlation with MAAP was the lowest (R2=0.65). Statistically the best linear correlations with MAAP were obtained for AE33 and COSMOS (R2 close to 1), but the biases at around the zero values led to slopes clearly below 1. The sample pre-treatment in the COSMOS instrument resulted in the lowest fitted slope. In contrast to the filter-based techniques, the indirect EMS method was not adequate to measure the low absorption values found at the Pallas site. The lowest absorption at which the EMS signal could be distinguished from the noise was >0.1 Mm−1 at 1–2 h averaging times. The mass absorption cross section (MAC) value measured at a range 0–0.3 Mm−1 was calculated using the MAAP and a single particle soot photometer (SP2), resulting in a MAC value of 16.0±5.7 m2 g−1. Overall, our results demonstrate the challenges encountered in the aerosol absorption measurements in pristine environments and provide some useful guidelines for instrument selection and measurement practices. We highlight the need for a calibrated transfer standard for better inter-comparability of the absorption results.

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Comparison of Filter-based Absorption Measurements of Biomass Burning Aerosol and Background Aerosol at the Mt. Bachelor Observatory

Cited by 32 publications

References 79 publications

Temporal Variability of Equivalent Black Carbon Components in Atmospheric Air in Southern Poland

Temporal Variability of Equivalent Black Carbon Components in Atmospheric Air in Southern Poland

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

Absorption instruments inter-comparison campaign at the Arctic Pallas station

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