The presence of volcanic clouds in the atmosphere affects air quality, the environment, climate, human health and aviation safety. The importance of the detection and retrieval of volcanic SO₂ lies with risk mitigation as well as with the possibility of providing insights into the mechanisms that cause eruptions. Due to their intrinsic characteristics, satellite measurements have become an essential tool for volcanic monitoring. In recent years, several sensors, with different spectral, spatial and temporal resolutions, have been launched into orbit, significantly increasing the effectiveness of the estimation of the various parameters related to the state of volcanic activity. In this work, the SO₂ total masses and fluxes were obtained from several satellite sounders—the geostationary (GEO) MSG-SEVIRI and the polar (LEO) Aqua/Terra-MODIS, NPP/NOAA20-VIIRS, Sentinel5p-TROPOMI, MetopA/MetopB-IASI and Aqua-AIRS—and compared to one another. As a test case, the Christmas 2018 Etna eruption was considered. The characteristics of the eruption (tropospheric with low ash content), the large amount of (simultaneously) available data and the different instrument types and SO₂ columnar abundance retrieval strategies make this cross-comparison particularly relevant. Results show the higher sensitivity of TROPOMI and IASI and a general good agreement between the SO₂ total masses and fluxes obtained from all the satellite instruments. The differences found are either related to inherent instrumental sensitivity or the assumed and/or calculated SO₂ cloud height considered as input for the satellite retrievals. Results indicate also that, despite their low revisit time, the LEO sensors are able to provide information on SO₂ flux over large time intervals. Finally, a complete error assessment on SO₂ flux retrievals using SEVIRI data was realized by considering uncertainties in wind speed and SO₂ abundance.

On the morning of 24 December 2018, an eruptive event occurred at Etna, which was followed the next day by a strong sequence of shallow earthquakes. The eruptive episode lasted until 30 December, ranging from moderate strombolian to lava fountain activity coupled with vigorous ash/gas emissions and a lava flow effusion toward the eastern volcano flank of Valle del Bove. In this work, the data collected from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instruments on board the Meteosat Second Generation (MSG) geostationary satellite are used to characterize the Etna activity by estimating the proximal and distal eruption parameters in near real time. The inversion of data indicates the onset of eruption on 24 December at 11:15 UTC, a maximum Time Average Discharge Rate (TADR) of 8.3 m³/s, a cumulative lava volume emitted of 0.5 Mm³, and a Volcanic Plume Top Height (VPTH) that reached a maximum altitude of 8 km above sea level (asl). The volcanic cloud ash and SO₂ result totally collocated, with an ash amount generally lower than SO₂ except on 24 December during the climax phase. A total amount of about 100 and 35 kt of SO₂ and ash respectively was emitted during the entire eruptive period, while the SO₂ fluxes reached peaks of more than 600 kg/s, with a mean value of about 185 kg/s. The SEVIRI VPTH, ash/SO₂ masses, and flux time series have been compared with the results obtained from the ground-based visible (VIS) cameras and FLux Automatic MEasurements (FLAME) networks, and the satellite images collected by the MODerate resolution Imaging Spectroradiometer (MODIS) instruments on board the Terra and Aqua- polar satellites. The analysis indicates good agreement between SEVIRI, VIS camera, and MODIS retrievals with VPTH, ash, and SO₂ estimations all within measurement errors. The SEVIRI and FLAME SO₂ flux retrievals show significant discrepancies due to the presence of volcanic ash and a gap of data on the FLAME network. The results obtained in this study show the ability of geostationary satellite systems to characterize eruptive events from the source to the atmosphere in near real time during the day and night, thus offering a powerful tool to mitigate volcanic risk on both local population and airspace and to give insight on volcanic processes.

Multi-sensor strategies are key to the real-time determination of eruptive source parameters (ESPs) of explosive eruptions necessary to forecast accurately both tephra dispersal and deposition. To explore the capacity of these strategies in various eruptive conditions, we analyze data acquired by two Doppler radars, ground- and satellite-based infrared sensors, one infrasound array, visible video-monitoring cameras as well as data from tephra-fallout deposits associated with a weak and a strong paroxysmal event at Mount Etna (Italy). We find that the different sensors provide complementary observations that should be critically analyzed and combined to provide comprehensive estimates of ESPs. First, all measurements of plume height agree during the strong paroxysmal activity considered, whereas some discrepancies are found for the weak paroxysm due to rapid plume and cloud dilution. Second, the event duration, key to convert the total erupted mass (TEM) in the mass eruption rate (MER) and vice versa, varies depending on the sensor used, providing information on different phases of the paroxysm (i.e., unsteady lava fountaining, lava fountain-fed tephra plume, waning phase associated with plume and cloud expansion in the atmosphere). As a result, TEM and MER derived from different sensors also correspond to the different phases of the paroxysms. Finally, satellite retrievals for grain-size can be combined with radar data to provide a first approximation of total grain-size distribution (TGSD) in near real-time. Such a TGSD shows a promising agreement with the TGSD derived from the combination of satellite data and whole deposit grain-size distribution (WDGSD).

From December 2020 to February 2022, 66 lava fountains (LF) occurred at Etna volcano (Italy). Despite their short duration (an average of about two hours), they produced a strong impact on human life, environment, and air traffic. In this work, the measurements collected from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) instrument, on board Meteosat Second Generation (MSG) geostationary satellite, are processed every 15 min to characterize the volcanic clouds produced during the activities. In particular, a quantitative estimation of volcanic cloud top height (VCTH) and ash/ice/SO₂ masses’ time series are obtained. VCTHs are computed by integrating three different retrieval approaches based on coldest pixel detection, plume tracking, and HYSPLIT models, while particles and gas retrievals are realized simultaneously by exploiting the Volcanic Plume Retrieval (VPR) real-time procedure. The discrimination between ashy and icy pixels is carried out by applying the Brightness Temperature Difference (BTD) method with thresholds obtained by making specific Radiative Transfer Model simulations. Results indicate a VCTH variation during the entire period between 4 and 13 km, while the SO₂, ash, and ice total masses reach maximum values of about 50, 100, and 300 Gg, respectively. The cumulative ash, ice, and SO₂ emitted from all the 2020–2022 LFs in the atmosphere are about 750, 2300, and 670 Gg, respectively. All the retrievals indicate that the overall activity can be grouped into 3 main periods in which it passes from high (December 2020 to March 2021), low (March to June 2021), and medium/high (June 2021 to February 2022). The different products have been validated by using TROPOspheric Monitoring Instrument (TROPOMI) polar satellite sensor, Volcano Observatory Notices for Aviation (VONA) bulletins, and by processing the SEVIRI data considering a different and more accurate retrieval approach. The products’ cross-comparison shows a generally good agreement, except for the SO₂ total mass in case of high ash/ice content in the volcanic cloud.

Accurate automatic volcanic cloud detection by means of satellite data is a challenging task and is of great concern for both the scientific community and aviation stakeholders due to well-known issues generated by strong eruption events in relation to aviation safety and health impacts. In this context, machine learning techniques applied to satellite data acquired from recent spaceborne sensors have shown promising results in the last few years. This work focuses on the application of a neural-network-based model to Sentinel-3 SLSTR (Sea and Land Surface Temperature Radiometer) daytime products in order to detect volcanic ash plumes generated by the 2019 Raikoke eruption. A classification of meteorological clouds and of other surfaces comprising the scene is also carried out. The neural network has been trained with MODIS (Moderate Resolution Imaging Spectroradiometer) daytime imagery collected during the 2010 Eyjafjallajökull eruption. The similar acquisition channels of SLSTR and MODIS sensors and the comparable latitudes of the eruptions permit an extension of the approach to SLSTR, thereby overcoming the lack in Sentinel-3 products collected in previous mid- to high-latitude eruptions. The results show that the neural network model is able to detect volcanic ash with good accuracy if compared to RGB visual inspection and BTD (brightness temperature difference) procedures. Moreover, the comparison between the ash cloud obtained by the neural network (NN) and a plume mask manually generated for the specific SLSTR images considered shows significant agreement, with an F-measure of around 0.7. Thus, the proposed approach allows for an automatic image classification during eruption events, and it is also considerably faster than time-consuming manual algorithms. Furthermore, the whole image classification indicates the overall reliability of the algorithm, particularly for recognition and discrimination between volcanic clouds and other objects.

Light-absorbing aerosols (LAAs) are short-lived climate forcers with a significant impact on Earth's radiative balance. LAAs include dust aerosols, black carbon (BC) and organic light-absorbing carbonaceous aerosol (collectively termed brown carbon, BrC), which have also been proven to be highly toxic. In this study, aerosol absorption at five wavelengths (ranging from ultraviolet to infrared) was monitored continuously using filter-based photometers during two winter seasons in 2020 and 2021 in the city of Modena (southern central Po Valley, northern Italy), at two regulatory air quality monitoring sites, along with other pollutants (coarse particulate matter, PM₁₀; fine particulate matter, PM_2.5; O₃; NO; NO₂; and C₆H₆) and the vehicular traffic rate. The aerosol optical depth (AOD) and other column aerosol optical properties were concurrently monitored at four wavelengths by an AErosol RObotic NETwork (AERONET) sun photometer under urban background conditions within Modena. In situ absorption levels were apportioned to both sources (fossil fuel and biomass burning) and species (BC and BrC), while columnar absorption was apportioned to BC, BrC and mineral dust. The combined analysis of the atmospheric aerosol and gas measurements and of the meteorological conditions (in situ and from the ERA5 reanalysis) identified the location of potential urban sources of BC and BrC, most likely related to traffic and biomass burning. In situ data show different diurnal/weekly patterns for BrC from biomass burning and BC from traffic, with minor differences between the background and the urban traffic conditions. AERONET version 3 absorption aerosol optical depth (AAOD) retrievals at four wavelengths allowed the estimation of the absorptive direct radiative effect due to LAAs over the same period under the reasonable assumption that the AOD signal is concentrated within the mixing layer. AERONET retrievals showed a modest correlation of columnar absorption with planetary boundary layer (PBL)-scaled in situ observations, although the correlation improved significantly during a desert dust transport event that affected both in situ aerosol and columnar absorption, particularly in the blue spectrum range. A low correlation occurred between the contribution of BrC to aerosol absorption for the in situ and the columnar observations, with the BrC contribution being generally larger for in situ observations. Finally, evidence of a highly layered atmosphere during the study period, featuring significant spatial mixing and modest vertical mixing, was shown by ERA5-based atmospheric temperature profiles and by the large correlation of concurrent AERONET AOD retrievals in Modena and in Ispra (on the northwestern side of the Po Valley, ca. 225 km from Modena).