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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]

Representing mixing state of black carbon (BC) is challenging for global climate models (GCMs). The Community Atmosphere Model version 6 (CAM6) with the four‐mode version of the Modal Aerosol Module (MAM4) represents aerosols as fully internal mixtures with uniform composition within each aerosol mode, resulting in high degree of internal mixing of BC with non‐BC species and large mass ratio of coating to BC (RBC, the mass ratio of non‐BC species to BC in BC‐containing particles). To improve BC mixing state representation, we coupled a machine learning (ML) model of BC mixing state index trained on particle‐resolved simulations to the CAM6 with MAM4 (MAM4‐ML). In MAM4‐ML, we use RBC to partition accumulation mode particles into two new modes, BC‐free particles and BC‐containing particles. We adjust RBC to make the modeled BC mixing state index (χmode) match the one predicted by the ML model (χML). On a global average, the mass fraction of BC‐containing particles in accumulation mode decreases from 100% (MAM4‐default) to 48% (MAM4‐ML). The globally averaged χmode decreases from 78% (MAM4‐default) to 63% (MAM4‐ML, 19% reduction) and agrees well with χML (66%). The RBC decreases by 52% for accumulation mode and better agrees with observations. The hygroscopicity drops by 9% for BC‐containing particles in accumulation mode, leading to a 20% reduction in the BC activation fraction. The surface BC concentration increases most (6.9%) in the Arctic, and the BC burden increases by 4%, globally. Our study highlights the application of the ML model for improving key aerosol processes in GCMs. Plain Language Summary: Black carbon (BC) mixing state is an important property for assessing impacts of BC on human health and climate. It describes how BC is distributed among the particle population and within individual particles. Due to computational costs, global climate models (GCMs) consider aerosols as either external mixtures (e.g., bulk models) or fully internal mixtures with uniform composition within a certain size range (e.g., an aerosol bin in sectional models or an aerosol mode in modal models). To improve BC mixing state representation, we coupled a machine learning (ML) model learned from particle‐resolved simulations to the online simulations of the Community Atmosphere Model version 6 (CAM6) with the four‐mode version of the Modal Aerosol Module (MAM4‐ML). We used the mass ratio of coating to BC (RBC) to determine the mass fraction of BC‐free particles and BC‐containing particles, and we adjusted RBC to make the modeled BC mixing state match ML model. The MAM4‐ML model reduces the degree of internal mixture of BC substantially. In addition, MAM4‐ML RBC is reduced by 52%, leading to a 20% reduction in BC activation fraction and a 4% increase in BC burden. This study proposes a method for the application of the ML to improve GCMs. Key Points: Machine learning model trained on particle‐resolved simulations has been coupled to CAM6 MAM4 to improve BC mixing state representationThe BC mixing state index is reduced by 19%, and the mass ratio of coating to BC is reduced by 52%, in better agreement with observationsDue to the drop in hygroscopicity of BC‐containing aerosol (9%), BC activation fraction decreased by 20%, and BC burden increased by 4% [ABSTRACT FROM AUTHOR]

Here we apply new analysis methods and approaches to existing long-term measurement series that provide additional insights into the atmospheric processes that control black carbon (BC) in the Arctic. Based on clustering size distribution data from Zeppelin Observatory for the years 2002–2010, observations classified as 'Polluted' were further investigated based on BC properties. The data were split into two subgroups, and while the microphysical and chemical fingerprints of the two subgroups are very similar, they show larger differences in BC concentration and correlation with the particle size distribution. Therefore, a source–receptor analysis was performed with HYSPLIT 10-days backward trajectories for both subsets. We demonstrate that within this 'Polluted' category, the airmasses that contributed to the largest BC signal at the Zeppelin station are not necessarily associated with traditional transport pathways from Eurasia. Instead, the strongest signal is from a region east of the Ural Mountains across the continent to the Kamchatka Peninsula. [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]

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 (PSAP), continuous light absorption photometer (CLAP), Aethalometers, and multi-angle absorption photometers (MAAP). 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 MACcor (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 in Alaska, Pallastunturi in Finland, and Fukue in Japan, and stable for up to 10 years. We successfully estimated MACcor values (10.6-15.2 m2 g-1 at a wavelength of 550 nm) for these instruments and these MACcor 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 in these Arctic sites estimated by this method are consistent with each other, they are applicable to the study of spatial and temporal variation of MBC in the Arctic and to evaluation of the performance of numerical model calculations. [ABSTRACT FROM AUTHOR]

There is ample evidence that Black Carbon (BC) is harmful to the Arctic. BC can darken the otherwise highly reflective surfaces of snow and ice and increase atmospheric and ice surface temperatures. Because of the importance of BC to the Arctic, this work was designed to resolve the most significant source regions of Arctic BC as measured by monitoring stations in the Arctic. Using a bottom‐up approach, it is shown for the first time that there is one particular BC transport pathway from lower latitudes into the Arctic that registers at all but one of the Arctic surface monitoring stations included in this study. Through this pathway, pollutants are transported from the Indo‐Gangetic plane over Central Asia into the high Arctic in as little as 7 days. The measurement sites and BC pathways in this study are shown to be well representative of the Arctic as a whole. Plain Language Summary: Snow and sea ice are two of the most reflective surfaces occurring naturally on planet Earth. Light absorbing aerosols, such as wind blown black carbon, that stick to these pristine surfaces can make them less reflective, thus converting more sunlight into heat. The added heat leads to increased surface temperatures and is detrimental to the Arctic climate. There are few sources of light absorbing aerosols in the Arctic compared to the vast amounts of black carbon aerosols that are emitted closer to the equator. This research highlights an important pathway for light absorbing aerosols to enter the Arctic. Light absorbing aerosols that enter the Arctic through this pathway can then subsequently spread out throughout the Arctic. This pathway is shown to transport light absorbing airborne pollutants from South Asia, over Central Asia, and into the high Arctic in quantities that well exceed the background levels, thus highlighting the importance of this newly found pathway. Key Points: Black Carbon aerosols can travel from South Asia over Central Asia and to the Arctic in 7 daysBlack Carbon transported via this pathway measures well above the station average at almost all Arctic stationsThe identified pathway is significant for Black Carbon concentrations throughout the Arctic [ABSTRACT FROM AUTHOR]

The representation of aerosol activation into cloud droplets in climate models is important for accurate understanding of aerosol radiative impacts on the Arctic climate, but it remains highly uncertain. Here we show that the uncertainty range of subgrid vertical velocity (SVV) and maximum supersaturation (SSmax) in aerosol activation produces fourfold to fivefold differences in the direct radiative effect of black carbon (BC) in the Arctic (0.091–0.40 W m−2) because SVV and SSmax determine the activated fraction and wet removal efficiency of aerosols. Aerosols are particularly sensitive to SVV in remote regions but not near their sources because many aerosols near sources are not yet influenced by wet removal processes. Our results demonstrate that SVV treatment is a major source of uncertainty in Arctic aerosol simulations and may be key for reducing the large discrepancies among global models in estimates of BC and its radiative effects in the Arctic. Plain Language Summary: Black carbon aerosol, emitted mainly in midlatitude regions by combustion of fossil fuel and biomass, is transported to the Arctic and deposited on snow and ice surfaces, where it contributes to Arctic heating. However, estimates of its importance in Arctic warming have large uncertainties. Because global climate models usually use a coarse horizontal grid spacing, they rely on many assumptions to represent the small‐scale atmospheric processes within clouds. This study uses a global climate model to investigate the importance of one of these assumptions, the treatment of "subgrid vertical velocity," to aerosol simulations. We show that varying the subgrid vertical velocity within its uncertainty range changes the calculated heating effect of black carbon in the Arctic by as much as five times. Our results underscore the importance of treating subgrid vertical velocity treatment accurately in estimating how much black carbon from midlatitudes is warming the Arctic. Key Points: The importance of subgrid vertical velocity in activation to aerosol burden and radiative effects was investigated by using a global modelThe current uncertainty in subgrid vertical velocity produces fivefold differences in the radiative effect of black carbon in the ArcticThe subgrid treatment of updraft is important in estimating the long‐range transport of black carbon and its impacts on Arctic climate [ABSTRACT FROM AUTHOR]

Gas flaring is an important source of atmospheric soot/black carbon, especially in sensitive Arctic regions.However, emissions have traditionally been challenging to measure and remain poorly characterized, confounding international reporting requirements and adding uncertainty to climate models.The sky-LOSA optical measurement technique has emerged as a powerful means to quantify flare black carbon emissions in the field, but broader adoption has been hampered by the complexity of its deployment, where decisions during setup in the field can have profound, non-linear impacts on achievable measurement uncertainties.To address this challenge, this paper presents a prescriptive measurement protocol and associated open-source software tool that simplifies acquisition of sky-LOSA data in the field.Leveraging a comprehensive Monte Carlo-based General Uncertainty Analysis (GUA) to predict measurement uncertainties over the entire breadth of possible measurement conditions, general heuristics are identified to guide a sky-LOSA user toward optimal data collection.These are further extended in the open-source software utility, SetupSkyLOSA, which interprets the GUA results to provide detailed guidance for any specific combination of location, date/time, and flare, plume, and ambient conditions.Finally, a case study of a sky-LOSA measurement at an oil and gas facility in Mexico is used to demonstrate the utility of the software tool, where potentially small region(s) of optimal instrument setup are easily and quickly identified.It is hoped that this work will help increase the accessibility of the sky-LOSA technique and ultimately the availability of field measurement data for flare black carbon emissions. [ABSTRACT FROM AUTHOR]

Wet processes, including aqueous-phase chemistry, wet scavenging, and wet surface uptake during dry deposition, are important for global modeling of aerosols and aerosol precursors. In this study, we improve the treatments of these wet processes in the Goddard Earth Observing System with chemistry (GEOS-Chem) v12.6.0, including pH calculations for cloud, rain, and wet surfaces, the fraction of cloud available for aqueous-phase chemistry, rainout efficiencies for various types of clouds, empirical washout by rain and snow, and wet surface uptake during dry deposition. We compare simulated surface mass concentrations of aerosols and aerosol precursors with surface monitoring networks over the United States, European, Asian, and Arctic regions, and show that model results with updated wet processes agree better with measurements for most species. With the implementation of these updates, normalized mean biases (NMBs) of surface nitric acid, nitrate, and ammonium are reduced from 78 %, 126 %, and 45 % to 0.9 %, 15 %, and 4.1 % over the US sites, from 107 %, 127 %, and 90 % to -0.7 %, 4.2 %, and 16 % over European sites, and from 121 %, 269 %, and 167 % to -21 %, 37 %, and 86 % over Asian remote region sites. Comparison with surface measured SO2 , sulfate, and black carbon at four Arctic sites indicated that those species simulated with the updated wet processes match well with observations except for a large underestimate of black carbon at one of the sites. We also compare our model simulation with aircraft measurement of nitric acid and aerosols during the Atmospheric Tomography Mission (ATom)-1 and ATom-2 periods and found a significant improvement of modeling skill of nitric acid, sulfate, and ammonium in the Northern Hemisphere during wintertime. The NMBs of these species are reduced from 163 %, 78 %, and 217 % to -13 %, -1 %, and 10 %, respectively. The investigation of impacts of updated wet process treatments on surface mass concentrations indicated that the updated wet processes have strong impacts on the global means of nitric acid, sulfate, nitrate, and ammonium and relative small impacts on the global means of sulfur dioxide, dust, sea salt, black carbon, and organic carbon. [ABSTRACT FROM AUTHOR]

Two months (Oct.–Nov. 2015) of online elemental carbon (EC) and organic carbon (OC) measurements were performed by two field OC/EC Sunset Laboratory analysers working in parallel with an 8-h time resolution at a subarctic remote station in Finland. During such a time resolution, thermal OC and EC concentrations were usually close to or below the recent limits of detection for the analyser. Thus, this work highlights the possible issues to consider during the online measurements of OC/EC analysers working at the threshold of their analytical possibilities. A detailed analysis of the data showed that even though the OC concentrations were always above the detection limit of the analyser, up to 70% of the given concentration was due to the dynamic blank (gaseous phase). The majority of the OC aerosol was present in the less volatile fractions that evolved during steps at 300–450 °C and 450–650 °C. The main bias at low EC concentrations originated from the automatically determined split point between OC and EC. The results from the RTCalc526 software often led to an early determination of the OC-EC split point, resulting in an overestimation of the EC concentrations. However, the comparison of the results was performed after processing the OC/EC raw data in the different RTCalc software versions 526 and 703. The results showed that the EC values from the newer version of the RTCalc703 software were more consistent with the equivalent black carbon (eBC) results from optical instruments (aethalometer and MAAP) measured in parallel in comparison with results from the older RTCalc526 software. Equivalent BC data from the laser attenuation measurement of the Sunset Lab. analyser also provided better agreement with the newer version of the RTCalc software (RTCalc703). Image 1 • A major part of the organic carbon (OC) was present in the less volatile fractions. • Up to 70% of the OC concentration was caused by a contribution of the dynamic blank (gaseous phase). • The elemental carbon (EC) results were overestimated in the earlier RTCalc526 evaluation software. • The updated RTCalc703 software provides reasonable results for very low EC concentrations. • The EC results are comparable to the parallel measurements of the equivalent black carbon. [ABSTRACT FROM AUTHOR]