This study examines the relationships linking methanesulfonic acid (MSA, arising from the atmospheric oxidation of the biogenic dimethylsulfide, DMS) in atmospheric aerosol, satellite-derived chlorophyll a (Chl-a), and oceanic primary production (PP), also as a function of sea ice melting (SIM) and extension of the ice free area in the marginal ice zone (IF-MIZ) in the Arctic. MSA was determined in PM10 samples collected over the period 2010–2012 at two Arctic sites, Ny Ålesund (78.9°N, 11.9°E), Svalbard islands, and Thule Air Base (76.5°N, 68.8°W), Greenland. PP is calculated by means of a bio-optical, physiologically based, semi-analytical model in the potential source areas located in the surrounding oceanic regions (Barents and Greenland Seas for Ny Ålesund, and Baffin Bay for Thule). Chl-a peaks in May in the Barents sea and in the Baffin Bay, and has maxima in June in the Greenland sea; PP follows the same seasonal pattern of Chl-a, although the differences in absolute values of PP in the three seas during the blooms are less marked than for Chl-a. MSA shows a better correlation with PP than with Chl-a, besides, the source intensity (expressed by PP) is able to explain more than 30% of the MSA variability at the two sites; the other factors explaining the MSA variability are taxonomic differences in the phytoplanktonic assemblages, and transport processes from the DMS source areas to the sampling sites. The taxonomic differences are also evident from the slopes of the correlation plots between MSA and PP: similar slopes (in the range 34.2–36.2 ng m−3of MSA/(gC m−2 d−1)) are found for the correlation between MSA at Ny Ålesund and PP in Barents Sea, and between MSA at Thule and PP in the Baffin Bay; conversely, the slope of the correlation between MSA at Ny Ålesund and PP in the Greenland Sea in summer is smaller (16.7 ng m−3of MSA/(gC m−2 d−1)). This is due to the fact that DMS emission from the Barents Sea and Baffin Bay is mainly related to the MIZ diatoms, which are prolific DMS producers, whereas in the Greenland Sea the DMS peak is related to an offshore pelagic bloom where low-DMS producer species are present. The sea ice dynamic plays a key role in determining MSA concentration in the Arctic, and a good correlation between MSA and SIM (slope = 39 ng m−3 of MSA/106 km2 SIM) and between MSA and IF-MIZ (slope = 56 ng m−3 of MSA/106 km2 IF-MIZ) is found for the cases attributable to bloomings of diatoms in the MIZ. Such relationships are calculated by combining the data sets from the two sites and suggest that PP is related to sea ice melting and to the extension of marginal sea ice areas, and that these factors are the main drivers for MSA concentrations at the considered Arctic sites

We present results from a systematic study of vertical profiles of aerosol number size distribution and black carbon (BC) concentrations conducted in the Arctic, over Ny-Ålesund (Svalbard). The campaign lasted 2 years (2011–2012) and resulted in 200 vertical profiles measured by means of a tethered balloon (up to 1200 m a.g.l.) during the spring and summer seasons. In addition, chemical analysis of filter samples, aerosol size distribution and a full set of meteorological parameters were determined at ground. The collected experimental data allowed a classification of the vertical profiles into different typologies, which allowed us to describe the seasonal phenomenology of vertical aerosol properties in the Arctic. During spring, four main types of profiles were found and their behavior was related to the main aerosol and atmospheric dynamics occurring at the measuring site. Background conditions generated homogenous profiles. Transport events caused an increase of aerosol concentration with altitude. High Arctic haze pollution trapped below thermal inversions promoted a decrease of aerosol concentration with altitude. Finally, ground-based plumes of locally formed secondary aerosol determined profiles with decreasing aerosol concentration located at different altitude as a function of size. During the summer season, the impact from shipping caused aerosol and BC pollution plumes to be constrained close to the ground, indicating that increasing shipping emissions in the Arctic could bring anthropogenic aerosol and BC in the Arctic summer, affecting the climate.

While carbon dioxide is the main cause for global warming, modeling short-lived climate forcers (SLCFs) such as methane, ozone, and particles in the Arctic allows us to simulate near-term climate and health impacts for a sensitive, pristine region that is warming at 3 times the global rate. Atmospheric modeling is critical for understanding the long-range transport of pollutants to the Arctic, as well as the abundance and distribution of SLCFs throughout the Arctic atmosphere. Modeling is also used as a tool to determine SLCF impacts on climate and health in the present and in future emissions scenarios. In this study, we evaluate 18 state-of-the-art atmospheric and Earth system models by assessing their representation of Arctic and Northern Hemisphere atmospheric SLCF distributions, considering a wide range of different chemical species (methane, tropospheric ozone and its precursors, black carbon, sulfate, organic aerosol, and particulate matter) and multiple observational datasets. Model simulations over 4 years (2008–2009 and 2014–2015) conducted for the 2022 Arctic Monitoring and Assessment Programme (AMAP) SLCF assessment report are thoroughly evaluated against satellite, ground, ship, and aircraft-based observations. The annual means, seasonal cycles, and 3-D distributions of SLCFs were evaluated using several metrics, such as absolute and percent model biases and correlation coefficients. The results show a large range in model performance, with no one particular model or model type performing well for all regions and all SLCF species. The multi-model mean (mmm) was able to represent the general features of SLCFs in the Arctic and had the best overall performance. For the SLCFs with the greatest radiative impact (CH₄, O₃, BC, and SO${}_{\mathrm{4}}^{\mathrm{2}-}$ ), the mmm was within ±25 % of the measurements across the Northern Hemisphere. Therefore, we recommend a multi-model ensemble be used for simulating climate and health impacts of SLCFs. Of the SLCFs in our study, model biases were smallest for CH₄ and greatest for OA. For most SLCFs, model biases skewed from positive to negative with increasing latitude. Our analysis suggests that vertical mixing, long-range transport, deposition, and wildfires remain highly uncertain processes. These processes need better representation within atmospheric models to improve their simulation of SLCFs in the Arctic environment. As model development proceeds in these areas, we highly recommend that the vertical and 3-D distribution of SLCFs be evaluated, as that information is critical to improving the uncertain processes in models.

In situ atmospheric aerosol measurements have been performed from a Manta unmanned aircraft system (UAS) using recently developed miniaturized aerosol instruments. Flights were conducted up to an altitude of 3000 m (AMSL) during spring 2015 in Ny-Ålesund, Svalbard, Norway. We use these flights to demonstrate a practical set of miniaturized instruments that can be deployed onboard small UASs and can provide valuable information on ambient aerosol. Measured properties include size-resolved particle number concentrations, aerosol absorption coefficient, relative humidity, and direct sun intensity. From these parameters, it is possible to derive a comprehensive set of aerosol optical properties: aerosol optical depth, single scattering albedo, and asymmetry parameter. The combination of instruments also allows us to determine the aerosol hygroscopicity. Copyright © 2017 American Association for Aerosol Research