Search Results

Now showing 1 - 2 of 2
  • Item
    Absorption instruments inter-comparison campaign at the Arctic Pallas station
    (Katlenburg-Lindau : European Geosciences Union, 2021) Asmi, Eija; Backman, John; Servomaa, Henri; Virkkula, Aki; Gini, Maria I.; Eleftheriadis, Konstantinos; Müller, Thomas; Ohata, Sho; Kondo, Yutaka; Hyvärinen, Antti
    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 0.01g¯Mm-1 levels when data were averaged to 1-2g¯h. The hourly averaged atmospheric absorption measured by the reference MAAP was 0.09g¯Mm-1 (at a wavelength of 637g¯nm). When data were averaged for >1g¯h, the filter-based methods agreed to around 40g¯%. 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 (slopeCombining double low line0.95, R2Combining double low line0.78), followed by AE31 (slopeCombining double low line0.93). 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 (R2Combining double low line0.65). 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 >0.1g¯Mm-1 at 1-2g¯h averaging times. The mass absorption cross section (MAC) value measured at a range 0-0.3g¯Mm-1 was calculated using the MAAP and a single particle soot photometer (SP2), resulting in a MAC value of 16.0±5.7g¯m2g-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. © Author(s) 2021.
  • Item
    The effect of rapid relative humidity changes on fast filter-based aerosol-particle light-absorption measurements: Uncertainties and correction schemes
    (Katlenburg-Lindau : Copernicus, 2019) Düsing, Sebastian; Wehner, Birgit; Müller, Thomas; Stöcker, Almond; Wiedensohler, Alfred
    Measuring vertical profiles of the particle light-absorption coefficient by using absorption photometers may face the challenge of fast changes in relative humidity (RH). These absorption photometers determine the particle light-absorption coefficient due to a change in light attenuation through a particle-loaded filter. The filter material, however, takes up or releases water with changing relative humidity (RH in %), thus influencing the light attenuation. A sophisticated set of laboratory experiments was therefore conducted to investigate the effect of fast RH changes (dRH/dt) on the particle light-absorption coefficient (σabs in Mm-1) derived with two absorption photometers. The RH dependence was examined based on different filter types and filter loadings with respect to loading material and areal loading density. The Single Channel Tricolor Absorption Photometer (STAP) relies on quartz-fiber filter, and the microAeth® MA200 is based on a polytetrafluoroethylene (PTFE) filter band. Furthermore, three cases were investigated: clean filters, filters loaded with black carbon (BC), and filters loaded with ammonium sulfate. The filter areal loading densities (ρ∗) ranged from 3.1 to 99.6 mg m-2 in the case of the STAP and ammonium sulfate and 1.2 to 37.6 mg m-2 in the case the MA200. Investigating BC-loaded cases, M8 scroll mrow miBCm 15pt was in the range of 2.9 to 43.0 and 1.1 to 16.3 mg m-2 for the STAP and MA200, respectively.

    Both instruments revealed opposing responses to relative humidity changes ("RH) with different magnitudes. The STAP shows a linear dependence on relative humidity changes. The MA200 is characterized by a distinct exponential recovery after its filter was exposed to relative humidity changes. At a wavelength of 624 nm and for the default 60 s running average output, the STAP reveals an absolute change in σabs per absolute change of RH ("σabsĝ•"RH) of 0.14 Mm-1 %-1 in the clean case, 0.29 Mm-1 %-1 in the case of BC-loaded filters, and 0.21 Mm-1 %-1 in the case filters loaded with ammonium sulfate. The 60 s running average of the particle light-absorption coefficient at 625 nm measured with the MA200 revealed a response of around -0.4 Mm-1 %-1 for all three cases. Whereas the response of the STAP varies over the different loading materials, in contrast, the MA200 was quite stable. The response was, for the STAP, in the range of 0.17 to 0.24 Mm-1 %-1 and, in the case of ammonium sulfate loading and in the BC-loaded case, 0.17 to 0.62 Mm-1 %-1. In the ammonium sulfate case, the minimum response shown by the MA200 was -0.42 with a maximum of -0.36 Mm-1 %-1 and a minimum of -0.42 and maximum -0.37 Mm-1 %-1 in the case of BC.

    A linear correction function for the STAP was developed here. It is provided by correlating 1 Hz resolved recalculated particle light-absorption coefficients and RH change rates. The linear response is estimated at 10.08 Mm-1 s-1 %-1. A correction approach for the MA200 is also provided; however, the behavior of the MA200 is more complex. Further research and multi-instrument measurements have to be conducted to fully understand the underlying processes, since the correction approach resulted in different correction parameters across various experiments. However, the exponential recovery after the filter of the MA200 experienced a RH change could be reproduced. However, the given correction approach has to be estimated with other RH sensors as well, since each sensor has a different response time. And, for the given correction approaches, the uncertainties could not be estimated, which was mainly due to the response time of the RH sensor. Therefore, we do not recommend using the given approaches. But they point in the right direction, and despite the imperfections, they are useful for at least estimating the measurement uncertainties due to relative humidity changes.

    Due to our findings, we recommend using an aerosol dryer upstream of absorption photometers to reduce the RH effect significantly. Furthermore, when absorption photometers are used in vertical measurements, the ascending or descending speed through layers of large relative humidity gradients has to be low to minimize the observed RH effect. But this is simply not possible in some scenarios, especially in unmixed layers or clouds. Additionally, recording the RH of the sample stream allows correcting for the bias during post-processing of the data. This data correction leads to reasonable results, according to the given example in this study. © Author(s) 2019.