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The large-scale convection during the Asian summer monsoon plays an important role in the rapid transport of boundary layer aerosols into the Asian summer monsoon anticyclone. Here, using the state-of-the-art ECHAM6–HAMMOZ aerosol-chemistry-climate model, we show that these aerosols are further transported to the Arctic along isentropic surfaces by the Brewer-Dobson-Circulation (BDC) during the monsoon season. Our model simulations show that East and South Asian anthropogenic emissions contribute significantly to the aerosol transported to the Arctic, which causes a higher negative net aerosol radiative forcing at the surface (dimming) of −0.09 ± 0.02 Wm−2 and −0.07 ± 0.02 Wm−2, respectively. Over the Arctic, the East Asian anthropogenic aerosols that include large amounts of sulfate cause a seasonal mean net radiative forcing at the top of the atmosphere (TOA) of −0.003 ± 0.001Wm−2 and a surface cooling of −0.56 K while the black carbon dominated aerosol from South Asia shows a positive TOA forcing of +0.004 ± 0.001Wm−2 with an only minor surface cooling of −0.043 K. Overall, the long-range transport of South Asian aerosols results in a notably warming throughout the atmospheric column but minimal temperature response at the Arctic surface. Conversely, East Asian aerosols cool the troposphere and heat the lower stratosphere in the Arctic. The Asian aerosol thus plays an ambivalent role, with the East Asian sources in particular having the potential to counteract the rapid rise in Arctic temperatures and the associated melting of snow and ice. [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]

Models assume that mixed‐phase clouds consist of uniformly mixed ice crystals and liquid cloud droplets when observations have shown that they consist of clusters, or "pockets," of ice crystals and liquid cloud droplets. We characterize the spatial distribution of cloud phase over the Arctic and the Southern Ocean using active satellite observations and determine the relative importance of collocated meteorological parameters and aerosols from reanalysis to predict how uniformly mixed mixed‐phase clouds are for the first time. We performed a multi‐linear regression fit to the data set to predict the spatial distribution of the ice and liquid pockets. Contrary to what models suggest, mixed‐phase clouds are rarely perfectly homogeneous. Our results suggest that high temperatures are associated with homogeneously mixed ice and liquid pockets. We also find that a high mixing ratio of black carbon is associated with heterogeneously mixed ice and liquid pockets. Plain Language Summary: The representation of clouds in numerical models remains one of the largest uncertainties in predicting our future climate. Clouds can consist solely of liquid droplets, ice crystals, or the coexistence of both hydrometeor types. The latter cloud type is referred to as mixed phase. Climate models assume that liquid droplets and ice crystals are uniformly mixed in space in mixed‐phase clouds, but observations show that mixed‐phase clouds are organized in separate pockets of clustered liquid droplets and ice crystals. This difference in representation has a large impact on the lifetime of clouds and on their role in climate change. Using satellite observations over the Arctic and the Southern Ocean, we quantify the spatial distribution of ice and liquid in clouds. We used a statistical method to determine the relationship between meteorology and aerosols and the spatial distribution of ice and liquid. Our results suggest that high temperatures are associated with homogeneously mixed mixed‐phase clouds and high concentrations of soot are associated with heterogeneously mixed mixed‐phase clouds. Furthermore, pockets of liquid within ice clouds are larger than pockets of ice within liquid clouds. These results will improve the representation of mixed‐phase clouds in large‐scale models. Key Points: Space‐based observations and reanalysis are considered to determine the factors that control how mixed mixed‐phase clouds areLiquid dominated clouds contain small and isolated ice pockets whereas ice dominated clouds contain large and isolated liquid pocketsTemperature and black carbon play an important role in controlling the cloud phase spatial distribution and increasing phase heterogeneity [ABSTRACT FROM AUTHOR]

Black carbon (BC) is a short-lived climate forcer affecting the Arctic climate through multiple mechanisms, which vary substantially from winter to summer. Several models still fail in reproducing BC seasonal variability, limiting the ability to fully describe BC climate implications. This study aims at gaining insights into the mechanisms controlling BC transport from lower latitudes to the Arctic lower troposphere. Here we investigate the drivers controlling black carbon daily and seasonal variability in the Arctic using generalized additive models (GAMs). We analysed equivalent black carbon (eBC) concentrations measured at the Gruvebadet Atmospheric Laboratory (GAL – Svalbard archipelago) from March 2018 to December 2021. The eBC showed a marked seasonality with higher values in winter and early spring. The eBC concentration averaged 22 ± 20 ngm-3 in the cold season (November–April) and 11 ± 11 ngm-3 in the warm season (May–October). The seasonal and interannual variability was mainly modulated by the efficiency of wet scavenging removal during transport towards higher latitudes. Conversely, the short-term variability was controlled by boundary layer dynamics as well as local-scale and synoptic-scale circulation patterns. During both the cold and warm seasons, the transport of air masses from Europe and northern Russia was an effective pathway for the transport of pollution to the European Arctic. Finally, in the warm season we observed a link between the intrusion of warm air from lower latitudes and the increase in eBC concentration. Changes in the synoptic-scale circulation system and precipitation rate in the Northern Hemisphere, linked to climate change, are expected to modify the BC burden in the Arctic. [ABSTRACT FROM AUTHOR]

Black carbon (BC) from anthropogenic and natural sources has a pronounced climatic effect on the polar environment. The interaction of BC with low-level Arctic clouds, important for understanding BC deposition from the atmosphere, is studied using the first long-term observational data set of equivalent black carbon (eBC) inside and outside of clouds observed at Zeppelin Observatory, Svalbard. We show that the measured cloud residual eBC concentrations have a clear seasonal cycle with a maximum in early spring, due to the Arctic haze phenomenon, followed by cleaner summer months with very low concentrations. The scavenged fraction of eBC was positively correlated with the cloud water content and showed lower scavenged fractions at low temperatures, which may be due to mixed-phase cloud processes. A trajectory analysis revealed potential sources of eBC and the need to ensure that aerosol-cloud measurements are collocated, given the differences in air mass origin of cloudy and non-cloudy periods. Black carbon in the Arctic has pronounced climatic effects, whilst residing in the atmosphere or after being deposited. Here long-term observations of black carbon inside Arctic clouds are used to study their seasonality, sources and links to other meteorological parameters. [ABSTRACT FROM AUTHOR]

A warming Arctic is expected to exacerbate wildfires in Siberia, potentially creating a critical feedback to the Arctic climate change. However, our understanding of these fire-climate interactions remains limited. This study investigated changes in East Siberian wildfires and their influence on fire emissions, aerosol optical depth (AOD), and the surface clear-sky insolation across the Siberian Arctic from 2000 to 2020 using satellite observations. Our analysis reveals a substantial increase in wildfires, with fire counts doubling (a 114% increase) and fire radiative power surging by 8.4 × 106 MW compared to the early 21st century. Over 93% of this increase occurred during the boreal summer months. These intensified wildfires led to a significant rise in aerosol emission (organic carbon, PM2.5, and black carbon) exceeding 75% in East Siberia. Consequently, fire-season AOD in the Siberian Arctic increased by 33% (6.0 × 10−2), with 85% (5.1 × 10−2) attributable to wildfire changes. The wildfire-associated increase in AOD resulted in enhanced clear-sky dimming of 4.1 ± 3.2 W m−2 across the Siberian Arctic from 2000 to 2020. These findings suggest a critical feedback mechanism: a warming Arctic drives increased wildfires in Siberia, which in turn significantly impact the Arctic surface radiative budget through enhanced clear-sky dimming. Future simulations and projections for the Arctic should prioritize incorporating the feedback effects of intensifying wildfires. • Active fire points in East Siberia increased by 114% from 2000 to 2020, nearly doubled. • Fire-season AOD in the Siberian Arctic increased by 33% during the study period. • Wildfires increase could explain 85% of the elevated AOD in the Siberian Arctic. • Wildfire-induced AOD increase led to a 4.1 W m−2 clear-sky dimming in the Siberian Arctic. [ABSTRACT FROM AUTHOR]

Black carbon (BC) particles in the Arctic contribute to rapid warming of the Arctic by heating the atmosphere and snow and ice surfaces. Understanding the source contributions to Arctic BC is therefore important, but they are not well understood, especially those for atmospheric and snow radiative effects. Here we estimate simultaneously the source contributions of Arctic BC to near-surface and vertically integrated atmospheric BC mass concentrations (MBC_SRF and MBC_COL), BC deposition flux (MBC_DEP), and BC radiative effects at the top of the atmosphere and snow surface (RE BC_TOA and RE BC_SNOW) and show that the source contributions to these five variables are highly different. In our estimates, Siberia makes the largest contribution to MBC_SRF , MBC_DEP , and RE BC_SNOW in the Arctic (defined as >70 ∘ N), accounting for 70 %, 53 %, and 41 %, respectively. In contrast, Asia's contributions to MBC_COL and RE BC_TOA are largest, accounting for 37 % and 43 %, respectively. In addition, the contributions of biomass burning sources are larger (29 %–35 %) to MBC_DEP , RE BC_TOA , and RE BC_SNOW , which are highest from late spring to summer, and smaller (5.9 %–17 %) to MBC_SRF and MBC_COL , whose concentrations are highest from winter to spring. These differences in source contributions to these five variables are due to seasonal variations in BC emission, transport, and removal processes and solar radiation, as well as to differences in radiative effect efficiency (radiative effect per unit BC mass) among sources. Radiative effect efficiency varies by a factor of up to 4 among sources (1471–5326 W g -1) depending on lifetimes, mixing states, and heights of BC and seasonal variations of emissions and solar radiation. As a result, source contributions to radiative effects and mass concentrations (i.e., RE BC_TOA and MBC_COL , respectively) are substantially different. The results of this study demonstrate the importance of considering differences in the source contributions of Arctic BC among mass concentrations, deposition, and atmospheric and snow radiative effects for accurate understanding of Arctic BC and its climate impacts. [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]

As explained in the latest Arctic Monitoring and Assessment Programme (AMAP) report released in early 2021, the Arctic has warmed 3 times more quickly than the planet as a whole, as well as faster than previously thought. The Siberian Arctic is of great interest mainly because observations are sparse or largely lacking. A research aerosol station has been developed on Bely Island (Kara Sea) in western Siberia. Measurements of equivalent black carbon (EBC) concentrations were carried out at the "Island Bely" station continuously from August 2019 to November 2020. The source origin of the measured EBC and the main contributing sources were assessed using atmospheric transport modeling coupled with the most updated emission inventories for anthropogenic and biomass burning sources of BC. The obtained climatology for BC during the period of measurements showed an apparent seasonal variation with the highest concentrations between December and April (60 ± 92 ng m -3) and the lowest between June and September (18 ± 72 ng m -3), typical of the Arctic haze seasonality reported elsewhere. When air masses arrived at the station through the biggest oil and gas extraction regions of Kazakhstan, Volga-Ural, Komi, Nenets and western Siberia, BC contribution from gas flaring dominated over domestic, industrial and traffic sectors, ranging from 47 % to 68 %, with a maximum contribution in January. When air was transported from Europe during the cold season, emissions from transportation were more important. Accordingly, shipping emissions increased due to the touristic cruise activities and the ice retreat in summertime. Biomass burning (BB) played the biggest role between April and October, contributing 81 % at maximum in July. Long-range transport of BB aerosols appeared to induce large variability to the absorption Ångström exponent (AAE) with values > 1.0 (excluding outliers). As regards the continental contribution to surface BC at the Island Bely station, Russian emissions dominated during the whole year, while European and Asian ones contributed up to 20 % in the cold period. Quantification of several pollution episodes showed an increasing trend in surface concentrations and frequency during the cold period as the station is directly in the Siberian gateway of the highest anthropogenic pollution sources to the Russian Arctic. [ABSTRACT FROM AUTHOR]

The warming-induced expansion of shrubs in the Arctic is transforming snowpacks into a mixture of snow, impurities and buried branches. Because snow is a translucent medium into which light penetrates up to tens of centimetres, buried branches may alter the snowpack radiation budget with important consequences for the snow thermal regime and microstructure. To characterize the influence of buried branches on radiative transfer in snow, irradiance profiles were measured in snowpacks with and without shrubs near Umiujaq in the Canadian Low Arctic (56.5 ∘ N, 76.5 ∘ W) in November and December 2015. Using the irradiance profiles measured in shrub-free snowpacks in combination with a Monte Carlo radiative transfer model revealed that the dominant impurity type was black carbon (BC) in variable concentrations up to 185 ng g -1. This allowed the separation of the radiative effects of impurities and buried branches. Irradiance profiles measured in snowpacks with shrubs showed that the impact of buried branches was local (i.e. a few centimetres around branches) and only observable in layers where branches were also visible in snowpit photographs. The local-effect hypothesis was further supported by observations of localized melting and depth hoar pockets that formed in the vicinity of branches. Buried branches therefore affect snowpack properties, with possible impacts on Arctic flora and fauna and on the thermal regime of permafrost. Lastly, the unexpectedly high BC concentrations in snow are likely caused by nearby open-air waste burning, suggesting that cleaner waste management plans are required for northern community and ecosystem protection. [ABSTRACT FROM AUTHOR]

Black Carbon (BC) aerosol is a major climate forcer in the Arctic. Here, we present 15 years (2001–2015) of surface observations of the aerosol absorption coefficient babs (corresponding to Equivalent BC), obtained at the Zeppelin Observatory, Ny Ålesund, Svalbard, coupled with backward transport modeling with Flexpart in order to calculate the Potential Source Contribution Function (PSCF) for BC. The observed long‐term variability superimposed on a strong annual cycle is studied as a function of large‐scale circulation patterns represented by monthly index values for the North Atlantic Oscillation (NAO) and the Scandinavian pattern (SCAN). We find a 35% increase of babs values at Zeppelin during the SCAN− phase in the winter half‐year compared to the SCAN+ phase but no significant difference in babs values between the NAO index phases. Both NAO and SCAN induce significant regional variability on the areas of origin of babs, mainly Siberia, Europe, and North America. Plain Language Summary: Here, we investigate the effect of the most important large circulation patterns for the European Arctic, namely the North Atlantic Oscillation (NAO) and Scandinavian (SCAN) patterns on the light absorbing carbon aerosol reaching the highly important area experiencing the effects of climate change as found before. We report important first time findings for an extended observation record of 15 years of aerosol light absorbing carbon, which was never been employed before as a continuous long record, and we performed the first rigorous assessment of the impact of large atmospheric circulation patterns like NAO and SCAN on the transport of black carbon aerosol expressed as the climate relevant aerosol absorption coefficient (babs) for the first time. We find a significant 35% increase in babs at Zeppelin during one of the phases of the SCAN. However, a significant regional variability induced by both NAO and SCAN phases is revealed. These findings allow a better quantified estimate of the fate of emissions over the years in the Northern Hemisphere and a better assessment of their influence in the observed BC metrics in the Artic. Key Points: An extended 15 years' observation record of Arctic aerosol light absorbing carbon is employedLarge‐scale circulation patterns appear to induce a long‐term modulation in aerosol absorption coefficient (babs) with regional featuresA 35% increase is found in babs at Zeppelin during the negative Scandinavian pattern (SCAN) phase in the 6‐month cold period compared to the positive SCAN phase [ABSTRACT FROM AUTHOR]

Black carbon (BC) aerosol particles in the Arctic heat the atmosphere and snow/ice surfaces and may strengthen the snow-albedo feedback that amplifies Arctic warming. Model simulations of BC concentrations in the Arctic depend strongly on the representation of microphysical processes such as aging, activation, and wet removal. Most BC modeling studies have classified BC particles into hydrophobic BC, which cannot form cloud droplets, and hydrophilic BC, which can form cloud droplets, by assuming a globally constant critical supersaturation threshold value (Sthre), without considering its consistency with cloud maximum supersaturation (Smax). Here we show that it is essential to consider the consistency of Sthre with Smax in global model simulations to reduce uncertainties in near-surface ambientBCconcentrations in the Arctic. Previous studies often obtained good agreement between simulated and observed near-surface Arctic BC mass concentrations when a low Sthre (;0.1%) was assumed in their models. However, this Sthre may be too low (activation and wet removal of BCmay be underestimated) for the Arctic, because some recent observations and our model simulations suggest that Smax may actually be higher (;0.3%) there. We also demonstrate that spatially varying Sthre values and their consistency with Smax, which previous studies did not consider, must be represented in models for more accurate estimation of BC budget in the Arctic. Because both Smax and BC-aging speed depend on climatic conditions, our findings are an important step toward better simulations of BC impacts on past, present, and future Arctic climates. [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]

Understanding the regional surface temperature responses to different anthropogenic climate forcing agents, such as greenhouse gases and aerosols, is crucial for understanding past and future regional climate changes. In modern climate models, the regional temperature responses vary greatly for all major forcing agents, but the causes of this variability are poorly understood. Here, we analyze how changes in atmospheric and oceanic energy fluxes due to perturbations in different anthropogenic climate forcing agents lead to changes in global and regional surface temperatures. We use climate model data on idealized perturbations in four major anthropogenic climate forcing agents (CO 2 , CH 4 , sulfate, and black carbon aerosols) from Precipitation Driver Response Model Intercomparison Project (PDRMIP) climate experiments for six climate models (CanESM2, HadGEM2-ES, NCAR-CESM1-CAM4, NorESM1, MIROC-SPRINTARS, GISS-E2). Particularly, we decompose the regional energy budget contributions to the surface temperature responses due to changes in longwave and shortwave fluxes under clear-sky and cloudy conditions, surface albedo changes, and oceanic and atmospheric energy transport. We also analyze the regional model-to-model temperature response spread due to each of these components. The global surface temperature response stems from changes in longwave emissivity for greenhouse gases (CO 2 and CH 4) and mainly from changes in shortwave clear-sky fluxes for aerosols (sulfate and black carbon). The global surface temperature response normalized by effective radiative forcing is nearly the same for all forcing agents (0.63, 0.54, 0.57, 0.61 K W -1 m 2). While the main physical processes driving global temperature responses vary between forcing agents, for all forcing agents the model-to-model spread in temperature responses is dominated by differences in modeled changes in longwave clear-sky emissivity. Furthermore, in polar regions for all forcing agents the differences in surface albedo change is a key contributor to temperature responses and its spread. For black carbon, the modeled differences in temperature response due to shortwave clear-sky radiation are also important in the Arctic. Regional model-to-model differences due to changes in shortwave and longwave cloud radiative effect strongly modulate each other. For aerosols, clouds play a major role in the model spread of regional surface temperature responses. In regions with strong aerosol forcing, the model-to-model differences arise from shortwave clear-sky responses and are strongly modulated by combined temperature responses to oceanic and atmospheric heat transport in the models. [ABSTRACT FROM AUTHOR]

The circum-Arctic region experienced serious fires in 2019 and 2020. Biomass burning is considered a primary source of black carbon (BC) aerosols. BC contributes to Arctic warming and impacts snow/ice melting. However, the impacts of biomass burning on BC in the Arctic during these recent serious fires have not been quantified in detail. In this study, based on numerical simulations using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), we calculated the contribution ratios of biomass burning to Arctic BC and revealed its transport pathways. Affected by biomass burning emissions, the near-surface BC concentrations over the terrestrial areas within the Arctic Circle were highest in summer, and declined in spring and autumn. Spatially, high-concentration levels of BC were distributed in the Russian central and eastern areas. Biomass burning accounted for 63.72% and 45.18% of the summer BC in the Arctic near-surface and middle troposphere, respectively. In the near-surface, the contributions from local Arctic sources were comparable to those from sources outside the Arctic Circle in summer. In the middle troposphere, contributions from sources outside the Arctic Circle were dominant. In summer, BC originating from biomass burning in Siberia was transported a short distance by southwesterly winds to the central Arctic near-surface, while the enhanced southwesterly winds in the middle troposphere transported BC from Siberia, Alaska and northern Canada to the central Arctic and Greenland. In spring and autumn, most BC originating from biomass burning in the near-surface of Eurasia was transported eastward by westerly winds and then transported northward over the North Pacific Ocean, and the long distance may have resulted in fewer effects on the Arctic. These results highlight the important role of biomass burning in the Arctic environment under a warming climate. [Display omitted] • Affected by biomass burning, the near-surface BC concentrations over the terrestrial areas within the Arctic Circle were highest in summer. • The biomass burning contributions from local sources to Arctic BC in the near-surface in summer were obvious. • BC from biomass burning in the near-surface of Siberia were transported by southwesterly winds to the central Arctic. • The enhanced southwesterly winds in the middle troposphere transported BC from Siberia, Alaska, and northern Canada to the central Arctic and Greenland. [ABSTRACT FROM AUTHOR]

The outbreak of SARS-CoV-2 and subsequent spread of the disease COVID-19 became classified as a pandemic in March of 2020, leading to global safety measures introduced to limit the impact of the virus. This combination of safety measures has become commonly referred to as "lockdown". The associated industry and lifestyle changes led to reductions in the anthropogenic emission of atmospheric pollutants such as black carbon (BC), which is transported from the mid-latitudes into the Arctic during the winter and spring. Measurements of BC and other anthropogenic pollutants are of increasing importance in the Arctic due to the rapid warming observed there in the past few decades. It is believed that BC has a significant role in this warming, and so understanding the Arctic's response to reduced BC emissions at lower latitudes will provide insight into how future changes might mitigate further warming. Reductions in BC have been reported worldwide, and so in this study, the impact of these reductions on BC concentrations at the High Arctic site Villum Research Station was investigated. The effect was examined from March 2020, around when global lockdowns began, to June 2020, when the Arctic haze period ended and BC levels were once again low. Firstly, the Danish Eulerian Hemispheric Model (DEHM) was used to assess this impact on BC concentrations by adjusting global anthropogenic pollution emission inventories to simulate those observed during the lockdown period and comparing the results to a similar model run with standard emission inventories. Secondly, equivalent BC data from an aethalometer at Villum Research Station were analysed, comparing the concentrations during the lockdown period to both aethalometer data from previous years and DEHM results from the lockdown period. It was found that when adjusted DEHM emission inventories were introduced from the 1st of March, the model predicted a reduction in BC concentrations beginning on the 10th of March and reached a 10% reduction by the 1st of April. This reduction fluctuated around 10% until the end of the Arctic haze period. Aethalometer data did not show any significant change from previous years, and no concentration reduction could be concluded from its comparison with DEHM results. This is likely because the predicted reduction of 10% is smaller than both the inter-annual and intra-annual variability of measured BC concentrations at Villum. • DEHM model and aethalometer used to assess effect of lockdown on Villum BC levels. • DEHM model simulated a 10% reduction in BC at Villum during April–May 2020. • Similar reductions are expected throughout the Arctic region (between 7% and 11%). • The aethalometer showed no response to the lockdown due to inherent BC variability. [ABSTRACT FROM AUTHOR]