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- ItemOzone depletion in the Arctic and Antarctic stratosphere induced by wildfire smoke(Katlenburg-Lindau : EGU, 2022) Ansmann, Albert; Ohneiser, Kevin; Chudnovsky, Alexandra; Knopf, Daniel A.; Eloranta, Edwin W.; Villanueva, Diego; Seifert, Patric; Radenz, Martin; Barja, Boris; Zamorano, Félix; Jimenez, Cristofer; Engelmann, Ronny; Baars, Holger; Griesche, Hannes; Hofer, Julian; Althausen, Dietrich; Wandinger, UllaA record-breaking stratospheric ozone loss was observed over the Arctic and Antarctica in 2020. Strong ozone depletion occurred over Antarctica in 2021 as well. The ozone holes developed in smoke-polluted air. In this article, the impact of Siberian and Australian wildfire smoke (dominated by organic aerosol) on the extraordinarily strong ozone reduction is discussed. The study is based on aerosol lidar observations in the North Pole region (October 2019-May 2020) and over Punta Arenas in southern Chile at 53.2°S (January 2020-November 2021) as well as on respective NDACC (Network for the Detection of Atmospheric Composition Change) ozone profile observations in the Arctic (Ny-Ålesund) and Antarctica (Neumayer and South Pole stations) in 2020 and 2021. We present a conceptual approach on how the smoke may have influenced the formation of polar stratospheric clouds (PSCs), which are of key importance in the ozone-depleting processes. The main results are as follows: (a) the direct impact of wildfire smoke below the PSC height range (at 10-12 km) on ozone reduction seems to be similar to well-known volcanic sulfate aerosol effects. At heights of 10-12 km, smoke particle surface area (SA) concentrations of 5-7 μm2 cm-3 (Antarctica, spring 2021) and 6-10 μm2 cm-3 (Arctic, spring 2020) were correlated with an ozone reduction in terms of ozone partial pressure of 0.4-1.2 mPa (about 30 % further ozone reduction over Antarctica) and of 2-3.5 mPa (Arctic, 20 %-30 % reduction with respect to the long-term springtime mean). (b) Within the PSC height range, we found indications that smoke was able to slightly increase the PSC particle number and surface area concentration. In particular, a smoke-related additional ozone loss of 1-2 mPa (10 %-20 % contribution to the total ozone loss over Antarctica) was observed in the 14-23 km PSC height range in September-October 2020 and 2021. Smoke particle number concentrations ranged from 10 to 100 cm-3 and were about a factor of 10 (in 2020) and 5 (in 2021) above the stratospheric aerosol background level. Satellite observations indicated an additional mean column ozone loss (deviation from the long-term mean) of 26-30 Dobson units (9 %-10 %, September 2020, 2021) and 52-57 Dobson units (17 %-20 %, October 2020, 2021) in the smoke-polluted latitudinal Antarctic belt from 70-80°S. Copyright:
- 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.
- ItemComparison of particle number size distribution trends in ground measurements and climate models(Katlenburg-Lindau : EGU, 2022) Leinonen, Ville; Kokkola, Harri; Yli-Juuti, Taina; Mielonen, Tero; Kühn, Thomas; Nieminen, Tuomo; Heikkinen, Simo; Miinalainen, Tuuli; Bergman, Tommi; Carslaw, Ken; Decesari, Stefano; Fiebig, Markus; Hussein, Tareq; Kivekäs, Niku; Krejci, Radovan; Kulmala, Markku; Leskinen, Ari; Massling, Andreas; Mihalopoulos, Nikos; Mulcahy, Jane P.; Noe, Steffen M.; van Noije, Twan; O'Connor, Fiona M.; O'Dowd, Colin; Olivie, Dirk; Pernov, Jakob B.; Petäjä, Tuukka; Seland, Øyvind; Schulz, Michael; Scott, Catherine E.; Skov, Henrik; Swietlicki, Erik; Tuch, Thomas; Wiedensohler, Alfred; Virtanen, Annele; Mikkonen, SanttuDespite a large number of studies, out of all drivers of radiative forcing, the effect of aerosols has the largest uncertainty in global climate model radiative forcing estimates. There have been studies of aerosol optical properties in climate models, but the effects of particle number size distribution need a more thorough inspection. We investigated the trends and seasonality of particle number concentrations in nucleation, Aitken, and accumulation modes at 21 measurement sites in Europe and the Arctic. For 13 of those sites, with longer measurement time series, we compared the field observations with the results from five climate models, namely EC-Earth3, ECHAM-M7, ECHAM-SALSA, NorESM1.2, and UKESM1. This is the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five earth system models (ESMs). We found that the trends of particle number concentrations were mostly consistent and decreasing in both measurements and models. However, for many sites, climate models showed weaker decreasing trends than the measurements. Seasonal variability in measured number concentrations, quantified by the ratio between maximum and minimum monthly number concentration, was typically stronger at northern measurement sites compared to other locations. Models had large differences in their seasonal representation, and they can be roughly divided into two categories: for EC-Earth and NorESM, the seasonal cycle was relatively similar for all sites, and for other models the pattern of seasonality varied between northern and southern sites. In addition, the variability in concentrations across sites varied between models, some having relatively similar concentrations for all sites, whereas others showed clear differences in concentrations between remote and urban sites. To conclude, although all of the model simulations had identical input data to describe anthropogenic mass emissions, trends in differently sized particles vary among the models due to assumptions in emission sizes and differences in how models treat size-dependent aerosol processes. The inter-model variability was largest in the accumulation mode, i.e. sizes which have implications for aerosol-cloud interactions. Our analysis also indicates that between models there is a large variation in efficiency of long-range transportation of aerosols to remote locations. The differences in model results are most likely due to the more complex effect of different processes instead of one specific feature (e.g. the representation of aerosol or emission size distributions). Hence, a more detailed characterization of microphysical processes and deposition processes affecting the long-range transport is needed to understand the model variability.