Light-absorbing aerosols heat the atmosphere; an accurate quantification of their absorption coefficient is mandatory. However, standard reference instruments (CAPS, MAAP, PAX, PTAAM) are not always available at each measuring site around the world.

By integrating all previous published studies concerning the Aethalometers, the AE33 filter loading parameter, provided by the dual-spot algorithm, were used to determine the multiple scattering enhancement factor from the Aethalometer itself (hereinafter C_AE) on an yearly and a monthly basis. The method was developed in Milan, where Aethalometer measurements were compared with MAAP data; the comparison showed a good agreement in terms of equivalent black carbon (R² = 0.93; slope = 1.02 and a negligible intercept = 0.12 μg m⁻³) leading to a yearly experimental multiple scattering enhancement factor of 2.51 ± 0.04 (hereinafter C_MAAP). On a yearly time base the C_AE values obtained using the new approach was 2.52 ± 0.01, corresponding to the experimental one (C_MAAP). Considering the seasonal behavior, higher experimental C_MAAP and computed C_AE values were found in summer (2.83 ± 0.12) whereas, the lower ones in winter/early-spring (2.37 ± 0.03), in agreement with the single scattering albedo behavior in the Po Valley.

Overall, the agreement between the experimental C_MAAP and C_AE showed a root mean squared error (RMSE) of just 0.038 on the C_MAAP prediction, characterized by a slope close to 1 (1.001 ± 0.178), a negligible intercept (−0.002 ± 0.455) and a high degree of correlation (R² = 0.955). From an environmental point of view, the application of a dynamic (space/time) determination of C_AE increases the accuracy of the aerosol heating rate (compared to applying a fixed C value) up to 16 % solely in Milan, and to 114 % when applied in the Arctic at 80°N.

Semi-enclosed, fetch-limited waters create unique conditions for wind wave development and breaking. Parameters of breaking waves influence bubble entrainment depth and associated noise, which is why they differ in semi-enclosed sea compared to open waters. While the established noise-wind speed relationship holds in oceanic conditions, it differs in land-constrained basins like the Baltic Sea. To explore noise level, bubble entrainment depth and wind speed relationships, we conducted noise and sub-surface bubble measurements, coupled with wind observations, in the selected area of the Baltic Sea during two consecutive summers. A novel method was employed to estimate bubble entrainment depth under conditions of strong backscatter. Model data of wave field parameters were employed to assess their influence on noise level and bubble entrainment depth. Results suggest stronger connections between noise level and wind speed, as well as wave height, compared to wave age and wind sea steepness. The same patterns hold true for the correlation between bubble entrainment depth and both wind speed and wave field parameters. The parameterized noise level-wind speed relationship differs from that obtained for oceanic conditions and also varies across measurement periods. Observed differences were shaped by varying wind-wave conditions, notably differences in wind speed, direction, wave height, and the presence of swell. The noise level-bubble entrainment depth relation is reported for the first time for Baltic Sea conditions. For a thorough analysis of the influence of these factors on noise and bubbles, longer measurements under diverse wind-wave conditions are required to account for site-specific wave field characteristics.

Ship-based measurements of sea spray aerosol (SSA) gradient fluxes in the size range of 0.5–47 µm in diameter were conducted between 2009–2017 in both the Baltic Sea and the North Atlantic Ocean. Measured total SSA fluxes varied between 8.9 × 103 ± 6.8 × 105 m−2 s−1 for the Baltic Sea and 1.0 × 104 ± 105 m−2 s−1 for the Atlantic Ocean. The analysis uncovered a significant decrease (by a factor of 2.2 in the wind speed range of 10.5–14.5 m s−1) in SSA fluxes, with chlorophyll a (chl a) concentration higher than 3.5 mg m−3 in the Baltic Sea area. We found statistically significant correlations for both regions of interest between SSA fluxes and various environmental factors, including wind speed, wind acceleration, wave age, significant wave height, and wave Reynolds number. Our findings indicate that higher chl a concentrations are associated with reduced SSA fluxes at higher wind speeds in the Baltic Sea, while the influence of wave age showed higher aerosol emissions in the Baltic Sea for younger waves compared to the Atlantic Ocean. These insights underscore the complex interplay between biological activity and physical dynamics in regulating SSA emissions. Additionally, in both measurement regions, we observed weak correlations between SSA fluxes and air and water temperature and between SSA fluxes and atmospheric stability. Comparing the Baltic Sea and the North Atlantic, we noted distinct emission behaviors, with higher emissions in the Baltic Sea at low wave age values compared to the Atlantic Ocean. This study represents the first comparative analysis of SSA flux measurements using the same methodology in these contrasting marine environments.

Assessment of the concentrations of dust pollution resulting from both measurements at reference stations and those determined using mathematical modelling requires accurate identification of the sources of emission. Although the concentration of dust results from several complex transport processes, as well as chemical and microphysical transformations of aerosols, sources of emissions may have a significant impact on the local level of pollution. This pilot study aimed to use measurements of the concentrations of dust (with the specification of the PM10 and PM2.5 fractions) made over a heap/excavation and its surroundings using an airship equipped with equipment for testing the optical and microphysical properties of atmospheric aerosols, and a ground station located at the facility. On the basis of the measurements, the function of the source of emissions of dust was estimated. According to our study, the yearly emission of dust varies between 42,470 and 886,289 kg for PM10, and between 42,470 and 803,893 for PM2.5 (minimum and maximum values). A model of local air quality was also used, which allowed us to verify the parameterization of emissions of dust pollutants for the PM10 and PM2.5 fractions from heaps and excavations based on the modelling results.

Primary biological aerosol particles (PBAPs) can influence the climate and affect human health. To investigate the aerosolization of PBAPs by sea spray aerosol (SSA), we conducted ship-based campaigns in the central Baltic Sea near Östergarnsholm in May and August 2021. Using a plunging-jet sea spray simulation chamber filled with local seawater, we performed controlled chamber experiments to collect filters and measure aerosols. We determined the abundance of microbial cells in the chamber air and seawater using staining and fluorescence microscopy, normalizing these values to sodium concentrations to calculate enrichment factors. Our results showed that microbes were enriched in the aerosol by 13 to 488 times compared to the underlying seawater, with no significant enrichment observed in the sea surface microlayer. Microbial abundances obtained through microscopy were compared with estimates of fluorescent PBAPs (fPBAPs) using a single-particle fluorescence spectrometer. We estimated microbial emission fluxes using two independent approaches: (1) applying the enrichment factors derived from this study with mass flux estimates from previous SSA parameterizations and (2) using a scaling approach from a companion study. Both methods produced microbial emission flux estimates that were in good agreement and of the same order of magnitude as previous studies, while fPBAP emission flux estimates were significantly lower. Furthermore, 16S rRNA sequencing identified the diversity of bacteria enriched in the nascent SSA compared to the underlying seawater.

To compare in situ and laboratory estimates of sea spray aerosol (SSA) production fluxes, we conducted two research campaigns in the vicinity of an eddy covariance (EC) flux tower on the island of Östergarnsholm in the Baltic Sea during May and August 2021. To accomplish this, we performed EC flux measurements for particles with diameters between 0.25 and 2.5 µm simultaneously with laboratory measurements using a plunging jet sea spray simulation chamber containing local seawater sampled close to the footprint of the flux tower. We observed a log-linear relationship between wind speed and EC-derived SSA emission fluxes, a power-law relationship between significant wave height and EC-derived SSA emission fluxes, and a linear relationship between wave Reynolds number and EC-derived SSA emission fluxes, all of which are consistent with earlier studies. Although we observed a weak negative relationship between particle production in the sea spray simulation chamber and seawater chlorophyll-α concentration and a weak positive relationship with the concentration of fluorescent dissolved organic matter in seawater, we did not observe any significant impact of dissolved oxygen on particle production in the chamber.

To obtain an estimate of the size-resolved emission spectrum for particles with dry diameters between 0.015 and 10 µm, we combined the estimates of SSA particle production fluxes obtained using the EC measurements and the chamber measurements in three different ways: (1) using the traditional continuous whitecap method, (2) using air entrainment measurements, and (3) simply scaling the chamber data to the EC fluxes. In doing so, we observed that the magnitude of the EC-derived emission fluxes compared relatively well to the magnitude of the fluxes obtained using the chamber air entrainment method as well as the previous flux measurements of Nilsson et al. (2021) and the parameterizations of Mårtensson et al. (2003) and Salter et al. (2015). As a result of these measurements, we have derived a wind-speed-dependent and wave-state-dependent SSA parameterization for particles with dry diameters between 0.015 and 10 µm for low-salinity waters such as the Baltic Sea, thus providing a more accurate estimation of SSA production fluxes.

Light-absorbing aerosols (LAA) impact the atmosphere by heating it. Their effect in the Arctic was investigated during two summer Arctic oceanographic campaigns (2018 and 2019) around the Svalbard Archipelago in order to unravel the differences between the Arctic background and the local anthropic settlements. Therefore, the LAA heating rate (HR) was experimentally determined. Both the chemical composition and high-resolution measurements highlighted substantial differences between the Arctic Ocean background (average eBC concentration of 11.7 ± 0.1 ng/m³) and the human settlements, among which the most impacting appeared to be Tromsø and Isfjorden (mean eBC of 99.4 ± 3.1 ng/m³). Consequently, the HR in Isfjorden (8.2 × 10⁻³ ± 0.3 × 10⁻³ K/day) was one order of magnitude higher than in the pristine background conditions (0.8 × 10⁻³ ± 0.9 × 10⁻⁵ K/day). Therefore, we conclude that the direct climate impact of local LAA sources on the Arctic atmosphere is not negligible and may rise in the future due to ice retreat and enhanced marine traffic.

Microplastics (MPs) pollution is one of the most important problems of the Earth. They have been found in all the natural environments, including oceans and the atmosphere. In this study, the concentrations of both atmospheric and marine MPs were measured over the Baltic along a research cruise that started in the Gdansk harbour, till the Gotland island, and the way back. A deposition box (based on a combination of active/passive sampling) was used to collect airborne MPs while, marine MPs concentrations were investigated during the cruise using a dedicated net. Ancillary data were obtained using a combination of particle counters (OPC, LAS and CPC), Aethalometer (AE33 Magee Scientific), spectrofluorometer (sea surface samples, Varian Cary Eclipse), and meteorological sensors. Results showed airborne microplastics average concentrations higher in the Gdansk harbour (161 ± 75 m⁻³) compared to the open Baltic Sea and to the Gotland island (24 ± 9 and 45 ± 20 m⁻³). These latter values are closer to the ones measured in the sea (79 ± 18 m⁻³). The MPs composition was investigated using μ-Raman (for the airborne ones) and FTIR (for marine ones); similar results (e.g. polyethylene, polyethylene terephthalates, polyurethane) were found in the two environmental compartments. The concentrations and similar composition in air and sea suggested a linkage between the two compartments. For this purpose, the atmospheric MPs' equivalent aerodynamic diameter was calculated (28 ± 3 μm) first showing the capability of atmospheric MPs to remain suspended in the air. At the same time, the computed turnover times (0.3–90 h; depending on MPs size) limited the transport distance range. The estimated MPs sea emission fluxes (4–18 ∗ 10⁶ μm³ m⁻² s⁻¹ range) finally showed the contemporary presence of atmospheric transport together with a continuous emission from the sea surface enabling a grasshopper long-range transport of microplastics across the sea.

A feed-forward neural network (FFNN) was used to estimate the monthly climatology of partial pressure of CO₂ (_pCO_2W) at a spatial resolution of 1° latitude by 1° longitude in the continental shelf of the European Arctic Sector (EAS) of the Arctic Ocean (the Greenland, Norwegian, and Barents seas). The predictors of the network were sea surface temperature (SST), sea surface salinity (SSS), the upper ocean mixed-layer depth (MLD), and chlorophyll-a concentration (Chl-a), and as a target, we used 2 853 _pCO_2W data points from the Surface Ocean CO₂ Atlas. We built an FFNN based on three major datasets that differed in the Chl-a concentration data used to choose the best model to reproduce the spatial distribution and temporal variability of _pCO_2W. Using all physical–biological components improved estimates of the _pCO_2W and decreased the biases, even though Chl-a values in many grid cells were interpolated values. General features of _pCO_2W distribution were reproduced with very good accuracy, but the network underestimated _pCO_2W in the winter and overestimated _pCO_2W values in the summer. The results show that the model that contains interpolating Chl-a concentration, SST, SSS, and MLD as a target to predict the spatiotemporal distribution of _pCO_2W in the sea surface gives the best results and best-fitting network to the observational data. The calculation of monthly drivers of the estimated _pCO_2W change within continental shelf areas of the EAS confirms the major impact of not only the biological effects to the _pCO_2W distribution and Air-Sea CO₂ flux in the EAS, but also the strong impact of the upper ocean mixing. A strong seasonal correlation between predictor and _pCO_2W seen earlier in the North Atlantic is clearly a yearly correlation in the EAS. The five-year monthly mean CO₂ flux distribution shows that all continental shelf areas of the Arctic Ocean were net CO₂ sinks. Strong monthly CO₂ influx to the Arctic Ocean through the Greenland and Barents Seas (>12 gC m⁻² day⁻¹) occurred in the fall and winter, when the _pCO_2W level at the sea surface was high (>360 µatm) and the strongest wind speed (>12 ms⁻¹) was present.

We present the first ever evaluation of sea spray aerosol eddy covariance (EC) fluxes at near coastal conditions and with limited fetch, and the first over water with brackish water (on average 7 ppt). The measurements were made on the island of Garpen in the Baltic Sea (56°23′ N, 16°06′ E) in September 2005. We found that wind speed is a major factor that is driving an exponential increase in sea spray sea salt emissions, comparable to previous studies over waters with higher salinity. We were able to show that the inclusion of a thermodenuder in the EC system allowed for the parallel measurements of the dry unheated aerosol flux (representing both organic and sea salt sea spray emissions) and the heated (300 °C) non-volatile sea salt emissions. This study’s experimental approach also included measurements of the artificial sea spray formed in a tank in locally sampled water at the same location as the EC fluxes. We attempted to use the EC aerosol flux measurements to scale the tank measurements to aerosol emissions in order to derive a complete size distribution for the sea spray emission fluxes below the size range (0.3–2 µm dry diameter) of the optical particle counters (OPCs) in the EC system, covering in total 0.01 µm to 2 µm diameter. In the wind directions with long fetches (corresponding to conditions similar to open sea), we were able to distinguish between the aerosol emission fluxes of dry aerosol and heated non-volatile (sea salt only) in the smallest size bins of the OPC, and could therefore indirectly estimate the organic sea spray fraction. In agreement with several previous ambient and tank experiments deriving the size resolved chemical mass concentration of sea salt and water-insoluble organic sea spray, our EC fluxes showed that sea sprays were dominated by sea salt at sizes ≥1 µm diameter, and by organics at the smallest OPC sizes. Since we used direct measures of the sea spray emission fluxes, we confirmed previous suggestions that this size distribution of sea salt and organics is a signature of sea spray aerosols. We were able to show that two sea salt source parameterizations (Mårtensson et al. (2003) and Salter et al. (2015)) agreed fairly well with our observed heated EC aerosol emission fluxes, as long as their predicted emissions were modified for the actual salinity by shifting the particle diameters proportionally to the cubic rote of the salinity. If, in addition, we added organics to the parameterized sea spray following the mono-layer model by Ellison et al. (1999), the combined sea spray parameterizations for sea salt and organics fell reasonably close to the observed fluxes for diameters > 0.15 µm, while one of them overpredicted the sea spray emissions below this size. The organic mono-layer model by Ellison et al. appeared to be able to explain most of the differences we observed between the aerosol emission fluxes with and without the thermodenuder.