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- ItemAbsorption 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, AnttiAerosol 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.
- ItemThe importance of the representation of air pollution emissions for the modeled distribution and radiative effects of black carbon in the Arctic(Katlenburg-Lindau : EGU, 2019) Schacht, Jacob; Heinold, Bernd; Quaas, Johannes; Backman, John; Cherian, Ribu; Ehrlich, Andre; Herber, Andreas; Huang, Wan Ting Katty; Kondo, Yutaka; Massling, Andreas; Sinha, P.R.; Weinzierl, Bernadett; Zanatta, Marco; Tegen, InaAerosol particles can contribute to the Arctic amplification (AA) by direct and indirect radiative effects. Specifically, black carbon (BC) in the atmosphere, and when deposited on snow and sea ice, has a positive warming effect on the top-of-atmosphere (TOA) radiation balance during the polar day. Current climate models, however, are still struggling to reproduce Arctic aerosol conditions.We present an evaluation study with the global aerosol-climate model ECHAM6.3-HAM2.3 to examine emission-related uncertainties in the BC distribution and the direct radiative effect of BC. The model results are comprehensively compared against the latest ground and airborne aerosol observations for the period 2005-2017, with a focus on BC. Four different setups of air pollution emissions are tested. The simulations in general match well with the observed amount and temporal variability in near-surface BC in the Arctic. Using actual daily instead of fixed biomass burning emissions is crucial for reproducing individual pollution events but has only a small influence on the seasonal cycle of BC. Compared with commonly used fixed anthropogenic emissions for the year 2000, an up-to-date inventory with transient air pollution emissions results in up to a 30% higher annual BC burden locally. This causes a higher annual mean all-sky net direct radiative effect of BC of over 0.1Wm-2 at the top of the atmosphere over the Arctic region (60-90° N), being locally more than 0.2Wm-2 over the eastern Arctic Ocean. We estimate BC in the Arctic as leading to an annual net gain of 0.5Wm-2 averaged over the Arctic region but to a local gain of up to 0.8Wm-2 by the direct radiative effect of atmospheric BC plus the effect by the BC-in-snow albedo reduction. Long-range transport is identified as one of the main sources of uncertainties for ECHAM6.3-HAM2.3, leading to an overestimation of BC in atmospheric layers above 500 hPa, especially in summer. This is related to a misrepresentation in wet removal in one identified case at least, which was observed during the ARCTAS (Arctic Research of the Composition of the Troposphere from Aircraft and Satellites) summer aircraft campaign. Overall, the current model version has significantly improved since previous intercomparison studies and now performs better than the multi-model average in the Aerosol Comparisons between Observation and Models (AEROCOM) initiative in terms of the spatial and temporal distribution of Arctic BC. © Author(s) 2019.