On 16 February 2021, an eruptive paroxysm took place at Mt. Etna (Sicily, Italy), after continuous Strombolian activity recorded at summit craters, which intensified in December 2020. This was the first of 17 short, but violent, eruptive events occurring during February–April 2021, mostly at a time interval of about 2–3 days between each other. The paroxysms produced lava fountains (up to 1000 m high), huge tephra columns (up to 10–11 km above sea level), lava and pyroclastic flows, expanding 2–4 km towards East and South. The last event, which was characterised by about 3 days of almost continuous eruptive activity (30 March–1 April), generated the most lasting lava fountain (8–9 h). During some paroxysms, volcanic ash led to the temporary closure of the Vincenzo Bellini Catania International Airport. Heavy ash falls then affected the areas surrounding the volcano, in some cases reaching zones located hundreds of kilometres away from the eruptive vent. In this study, we investigate the Mt. Etna paroxysms mentioned above through a multi-platform satellite system. Results retrieved from Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), starting from outputs of the Robust Satellite Techniques for Volcanoes (RST_VOLC), indicate that the 17th paroxysm (31 March–1 April) was the most intense in terms of radiative power, with values estimated around 14 GW. Moreover, by the analysis of SEVIRI data, we found that the 5th and 17th paroxysms were the most energetic. The Multispectral Instrument (MSI) and the Operational Land Imager (OLI), providing shortwave infrared (SWIR) data at 20/30 m spatial resolution, enabled an accurate localisation of active vents and the mapping of the areas inundated by lava flows. In addition, according to the Normalized Hotspot Indices (NHI) tool, the 2nd (17–18 February) and 7th (28 February) paroxysm generated the largest thermal anomaly at Mt. Etna after April 2013, when Landsat-8 OLI data became available. Despite the impact of clouds/plumes, pixel saturation, and other factors (e.g., satellite viewing geometry) on thermal anomaly identification, the used multi-sensor approach allowed us to retrieve quantitative information about the 17 paroxysms occurring at Mt. Etna. This approach could support scientists in better interpreting changes in thermal activity, which could lead to future and more dangerous eruptions.

Natural gas flaring (GF) is a longstanding problem for the oil industry. Recent estimates indicate that this phenomenon has increased to levels recorded a full decade earlier. While in 2020 there was a decline in global GF due to COVID-19 pandemic, data suggest that GF continues to be a persistent issue, with solutions remaining difficult or uneconomical in certain countries. Nighttime satellite products are widely used to map and monitor GF affected areas, partially filling the general lack of information from oil companies and/or national reporting. In this work, we assess the potential of daytime infrared satellite observations at high spatial resolution from Operational Land Imager (OLI) and Multispectral Instrument (MSI) sensors, respectively onboard Landsat-8 (L8) and Sentinel-2 (S2) satellites, in monitoring GF activity. The Normalized Hotspot Indices (NHI) algorithm is used for this purpose, testing its performance over six different GF sites. Results show the NHI capability in providing accurate information about GF related thermal (e.g., 100% of detections offshore; up to 92% onshore), despite some limitations due to clouds and smoke. They open challenging scenarios regarding the possibility of quantifying the volume of emitted gas from daytime S2-MSI and L8-OLI data, integrating information from well-established nighttime operational systems.

In this paper, the robust satellite techniques (RST), a multi-temporal scheme of satellite data analysis, was implemented to analyze the flaring activity of the Val d'Agri Oil Center (COVA), the largest Italian gas and oil pre-treatment plant, owned by Ente Nazionale Idrocarburi (ENI). For this site, located in an anthropized area characterized by a large environmental complexity, flaring emissions are mainly related to emergency conditions (i.e., waste flaring), as industrial processes are regulated by strict regional laws. While regarding the peculiar characteristics of COVA flaring, the main aim of this work was to assess the performances of RST in terms of sensitivity and reliability in providing independent estimations of gas flaring volumes in such conditions. In detail, RST was implemented for 13 years of Moderate Resolution Imaging Spectroradiometer (MODIS) medium and thermal infrared data in order to identify the highly radiant records associated with the COVA flare emergency discharges. Then, using data provided by ENI about gas flaring volumes in the period 2003–2009, a MODIS-based regression model was developed and tested. The results achieved indicate that the such a model is able to estimate, with a good level of accuracy (R2 of 0.83), emitted gas flaring volumes at COVA.

The Daytime Approach for gas Flaring Investigation (DAFI), running in Google Earth Engine (GEE) environment, exploits a Normalized Hotspot Index (NHI), analyzing near-infrared and short-wave infrared radiances, to detect worldwide high-temperature gas flaring sites (GFs). Daytime Landsat 8—Operational Land Imager (OLI) observations, of 2013–2021, represents the employed dataset. A temporal persistence criterion is applied to a gas flaring customized NHI product to select the GFs. It assures the 99% detection accuracy of more intense and stable GFs, with a very low false positive rate. As a result, the first daytime database and map of GF sites, operating during the last 9 years at global scale, has been generated. For each site, geographical metadata, frequency of occurrence and time persistence levels, at both monthly and annual scale, may be examined, through the specific developed GEE App. The present database will complement/integrate existing gas flaring maps. The joint use of global scale daytime and nighttime GFs inventories, in fact, will allow for tracking gas flaring dynamics in a timely manner. Moreover, it enables a better evaluation of GF emissions into the atmosphere. Finally, the next DAFI implementation on Landsat 9 and Sentinel 2 data will further improve our capabilities in identifying, mapping, monitoring and characterizing the GFs.

An effective characterization of gas flaring is hampered by the lack of systematic, complete and reliable data on its magnitude and spatial distribution. In the last years, a few satellite methods have been developed to provide independent information on gas flaring activity at global, national and local scale. Among these, a MODIS-based method, aimed at the computation of gas flared volumes by an Italian plant, was proposed. In this work, a more general version of this approach, named RST-FLARE, has been developed to provide reliable information on flaring sites localization and gas emitted volumes over a long time period for the Niger Delta region, one of the top five gas flaring areas in the world. Achieved results showed a good level of accuracy, in terms of flaring sites localization (95% of spatial match) and volume estimates (mean bias between in 16% and 20%, at annual scale and 2–9% in the long period) when compared to independent data, provided both by other satellite techniques and national/international organizations. Outcomes of this work seem to indicate that RST-FLARE can be used to provide, at different geographic scales, quite accurate data on gas flaring, suitable for monitoring purposes for governments and local authorities.