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Long-term measurements of the mass concentration of black carbon (BC) in the atmosphere (MBC) with well-constrained accuracy are indispensable to quantify its emission, transport, and deposition. The aerosol light absorption coefficient (babs), usually measured by a filter-based absorption photometer, including an Aethalometer (AE), is often used to estimate MBC. The measured babs is converted to MBC by assuming a value for the mass absorption cross section (MAC). Previously, we derived the MAC for AE (MAC (AE)) from measured babs and independently measured MBC values at two sites in the Arctic. MBC was measured with a filter-based absorption photometer with a heated inlet (COSMOS). The accuracy of the COSMOS-derived MBC (MBC (COSMOS)) was within about 15%. Here, we obtained additional MAC (AE) measurements to improve understanding of its variability and uncertainty. We measured babs (AE) and MBC (COSMOS) at Alert (2018–2020), Barrow (2012–2022), Ny-Ålesund (2012–2019), and Pallas (2019–2022). At Pallas, we also obtained four-wavelength photoacoustic aerosol absorption spectrometer (PAAS-4λ) measurements of babs. babs (AE) and MBC (COSMOS) were tightly correlated; the average MAC (AE) at the four sites was 11.4 ± 1.2 m2 g−1 (mean ± 1σ) at 590 nm and 7.76 ± 0.73 m2 g−1 at 880 nm. The spatial variability of MAC (AE) was about 11% (1σ), and its year-to-year variability was about 18%. We compared MAC (AE) in the Arctic with values at mid-latitudes, measured by previous studies, and with values obtained by using other types of filter-based absorption photometer, and PAAS-4λ. Copyright © 2024 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

Long-term measurements of atmospheric mass concentrations of black carbon (BC) are needed to investigate changes in its emission, transport, and deposition. However, depending on instrumentation, parameters related to BC such as aerosol absorption coefficient (babs) have been measured instead. Most ground-based measurements of babs in the Arctic have been made by filter-based absorption photometers, including particle soot absorption photometers (PSAPs), continuous light absorption photometers (CLAPs), Aethalometers, and multi-angle absorption photometers (MAAPs). The measured babs can be converted to mass concentrations of BC (MBC) by assuming the value of the mass absorption cross section (MAC; MBC= babs/ MAC). However, the accuracy of conversion of babs to MBC has not been adequately assessed. Here, we introduce a systematic method for deriving MAC values from babs measured by these instruments and independently measured MBC. In this method, MBC was measured with a filter-based absorption photometer with a heated inlet (COSMOS). COSMOS-derived MBC (MBC (COSMOS)) is traceable to a rigorously calibrated single particle soot photometer (SP2), and the absolute accuracy of MBC (COSMOS) has been demonstrated previously to be about 15 % in Asia and the Arctic. The necessary conditions for application of this method are a high correlation of the measured babs with independently measured MBC and long-term stability of the regression slope, which is denoted as MAC cor (MAC derived from the correlation). In general, babs – MBC (COSMOS) correlations were high (r2= 0.76–0.95 for hourly data) at Alert in Canada, Ny-Ålesund in Svalbard, Barrow (NOAA Barrow Observatory) in Alaska, Pallastunturi in Finland, and Fukue in Japan and stable for up to 10 years. We successfully estimated MAC cor values (10.8–15.1 m 2 g -1 at a wavelength of 550 nm for hourly data) for these instruments, and these MAC cor values can be used to obtain error-constrained estimates of MBC from babs measured at these sites even in the past, when COSMOS measurements were not made. Because the absolute values of MBC at these Arctic sites estimated by this method are consistent with each other, they are applicable to the study of spatial and temporal variation in MBC in the Arctic and to evaluation of the performance of numerical model calculations. [ABSTRACT FROM AUTHOR]

Following the emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) responsible for COVID-19 in December 2019 in Wuhan (China) and its spread to the rest of the world, the World Health Organization declared a global pandemic in March 2020. Without effective treatment in the initial pandemic phase, social distancing and mandatory quarantines were introduced as the only available preventative measure. In contrast to the detrimental societal impacts, air quality improved in all countries in which strict lockdowns were applied, due to lower pollutant emissions. Here we investigate the effects of the COVID-19 lockdowns in Europe on ambient black carbon (BC), which affects climate and damages health, using in situ observations from 17 European stations in a Bayesian inversion framework. BC emissions declined by 23 kt in Europe (20 % in Italy, 40 % in Germany, 34 % in Spain, 22 % in France) during lockdowns compared to the same period in the previous 5 years, which is partially attributed to COVID-19 measures. BC temporal variation in the countries enduring the most drastic restrictions showed the most distinct lockdown impacts. Increased particle light absorption in the beginning of the lockdown, confirmed by assimilated satellite and remote sensing data, suggests residential combustion was the dominant BC source. Accordingly, in central and Eastern Europe, which experienced lower than average temperatures, BC was elevated compared to the previous 5 years. Nevertheless, an average decrease of 11 % was seen for the whole of Europe compared to the start of the lockdown period, with the highest peaks in France (42 %), Germany (21 %), UK (13 %), Spain (11 %) and Italy (8 %). Such a decrease was not seen in the previous years, which also confirms the impact of COVID-19 on the European emissions of BC. [ABSTRACT FROM AUTHOR]

Aerosol 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 0.1 W m -2 at the top of the atmosphere over the Arctic region (60–90 ∘ N), being locally more than 0.2 W m -2 over the eastern Arctic Ocean. We estimate BC in the Arctic as leading to an annual net gain of 0.5 W m -2 averaged over the Arctic region but to a local gain of up to 0.8 W m -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. [ABSTRACT FROM AUTHOR]