Fire Characterization by Using an Original RST-Based Approach for Fire Radiative Power (FRP) Computation

Fire radiative power (FRP) is a basic parameter for fire characterization since it represents the heat emission rate of fires. Moreover, its temporal integration (fire radiative energy, FRE) is used as a proxy for estimating biomass burning and emissions. From satellite, FRP is generally computed by comparing the Medium InfraRed (MIR) signal of the fire pixel with the background value on the event image. Such an approach is possibly affected by some issues due to fire extent, clouds and smoke over the event area. The enlargement of the background window is the commonly used gimmick to face these issues. However, it may include unrepresentative signals of the fire pixel because of very different land use/cover. In this paper, the alternative Background Radiance Estimator by a Multi-temporal Approach (BREMA), based on the Robust Satellite Technique (RST), is proposed to characterize background and compute FRP. The approach is presented using data from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard the Meteosat Second Generation (MSG) platform. Moreover, BREMA is here combined with the RST-FIRES (RST for FIRES detection) technique for fire pixel identification and the -SEVIRI retrieval algorithm for transmittance evaluation. Results compared to the operational SEVIRI-based FRP-PIXEL product, although highly correlated in terms of background radiance (r2=0.95) and FRP values (r2=0.96), demonstrated a major capability of BREMA to estimate background radiances regardless of cloudiness or smoke presence during the event and independently on fire extent. The possible impact of the proposed approach on the estimates of CO2 emissions was also evaluated for comparison with the Global Fire Emissions Database (GFED4s)

Mt. Etna Paroxysms of February–April 2021 Monitored and Quantified through a Multi-Platform Satellite Observing System

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), and Spinning Enhanced Visible and Infrared Imager (SEVIRI), starting from outputs of the Robust Satellite Techniques for Volcanoes (RSTVOLC), indicate that the 17th paroxysm (31 March–1 April) was the most powerful, with values of radiative power 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 1st and 3rd paroxysm (18 and 28 February) generated the largest thermal anomaly at Mt. Etna after June 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

An EARLINET early warning system for atmospheric aerosol aviation hazards

A stand-alone lidar-based method for detecting airborne hazards for aviation in near real time (NRT) is presented. A polarization lidar allows for the identification of irregular-shaped particles such as volcanic dust and desert dust. The Single Calculus Chain (SCC) of the European Aerosol Research Lidar Network (EARLINET) delivers high-resolution preprocessed data: the calibrated total attenuated backscatter and the calibrated volume linear depolarization ratio time series. From these calibrated lidar signals, the particle backscatter coefficient and the particle depolarization ratio can be derived in temporally high resolution and thus provide the basis of the NRT early warning system (EWS). In particular, an iterative method for the retrieval of the particle backscatter is implemented. This improved capability was designed as a pilot that will produce alerts for imminent threats for aviation. The method is applied to data during two diverse aerosol scenarios: first, a record breaking desert dust intrusion in March 2018 over Finokalia, Greece, and, second, an intrusion of volcanic particles originating from Mount Etna, Italy, in June 2019 over Antikythera, Greece. Additionally, a devoted observational period including several EARLINET lidar systems demonstrates the network's preparedness to offer insight into natural hazards that affect the aviation sector. © 2020 Author(s)

An EARLINET early warning system for atmospheric aerosol aviation hazards

A stand-alone lidar-based method for detecting airborne hazards for aviation in near real time (NRT) is presented. A polarization lidar allows for the identification of irregular-shaped particles such as volcanic dust and desert dust. The Single Calculus Chain (SCC) of the European Aerosol Research Lidar Network (EARLINET) delivers high-resolution preprocessed data: the calibrated total attenuated backscatter and the calibrated volume linear depolarization ratio time series. From these calibrated lidar signals, the particle backscatter coefficient and the particle depolarization ratio can be derived in temporally high resolution and thus provide the basis of the NRT early warning system (EWS). In particular, an iterative method for the retrieval of the particle backscatter is implemented. This improved capability was designed as a pilot that will produce alerts for imminent threats for aviation. The method is applied to data during two diverse aerosol scenarios: first, a record breaking desert dust intrusion in March 2018 over Finokalia, Greece, and, second, an intrusion of volcanic particles originating from Mount Etna, Italy, in June 2019 over Antikythera, Greece. Additionally, a devoted observational period including several EARLINET lidar systems demonstrates the network’s preparedness to offer insight into natural hazards that affect the aviation sector.ACTRIS-2 654109ACTRIS preparatory phase 739530EUNADICS-AV 723986E-shape (EuroGEOSS Showcases: Applications Powered by Europe) 820852Ministry of Research and Innovation, Ontario 19PFE/17.10.2018Romanian National Core Program 18N/2019European Commission European Commission Joint Research Centre 72569

First Implementation of a Normalized Hotspot Index on Himawari-8 and GOES-R Data for the Active Volcanoes Monitoring: Results and Future Developments

The Advanced Himawari Imager (AHI) and Advanced Baseline Imager (ABI), respectively aboard Himawari-8 and GOES-R geostationary satellites, are two important instruments for the near-real time monitoring of active volcanoes in the Eastern Asia/Western Pacific region and the Pacific Ring of Fire. In this work, we use for the first time AHI and ABI data, at 10 min temporal resolution, to assess the behavior of a Normalized Hotspot Index (NHI) in presence of active lava flows/lakes, at Krakatau (Indonesia), Ambrym (Vanuatu) and Kilauea (HI, USA) volcanoes. Results show that the index, which is used operationally to map hot targets through the Multispectral Instrument (MSI) and the Operational Land Imager (OLI), is sensitive to high-temperature features even when short-wave infrared (SWIR) data at 2 km spatial resolution are analyzed. On the other hand, thresholds should be tailored to those data to better discriminate thermal anomalies from the background in daylight conditions. In this context, the multi-temporal analysis of NHI may enable an efficient identification of high-temperature targets without using fixed thresholds. This approach could be exported to SWIR data from the Flexible Combined Imager (FCI) instrument aboard the next Meteosat Third Generation (MTG) satellites

First Implementation of a Normalized Hotspot Index on Himawari-8 and GOES-R Data for the Active Volcanoes Monitoring: Results and Future Developments

The Advanced Himawari Imager (AHI) and Advanced Baseline Imager (ABI), respectively aboard Himawari-8 and GOES-R geostationary satellites, are two important instruments for the near-real time monitoring of active volcanoes in the Eastern Asia/Western Pacific region and the Pacific Ring of Fire. In this work, we use for the first time AHI and ABI data, at 10 min temporal resolution, to assess the behavior of a Normalized Hotspot Index (NHI) in presence of active lava flows/lakes, at Krakatau (Indonesia), Ambrym (Vanuatu) and Kilauea (HI, USA) volcanoes. Results show that the index, which is used operationally to map hot targets through the Multispectral Instrument (MSI) and the Operational Land Imager (OLI), is sensitive to high-temperature features even when short-wave infrared (SWIR) data at 2 km spatial resolution are analyzed. On the other hand, thresholds should be tailored to those data to better discriminate thermal anomalies from the background in daylight conditions. In this context, the multi-temporal analysis of NHI may enable an efficient identification of high-temperature targets without using fixed thresholds. This approach could be exported to SWIR data from the Flexible Combined Imager (FCI) instrument aboard the next Meteosat Third Generation (MTG) satellites

Investigating Volcanic Plumes from Mt. Etna Eruptions of December 2015 by Means of AVHRR and SEVIRI Data

In early December 2015, a rapid sequence of strong paroxysmal events took place at the Mt. Etna crater area (Sicily, Italy). Intense paroxysms from the Voragine crater (VOR) generated an eruptive column extending up to an altitude of about 15 km above sea level. In the following days, other minor ash emissions occurred from summit craters. In this study, we present results achieved by monitoring Mt. Etna plumes by means of RSTASH (Robust Satellite Techniques-Ash) algorithm, running operationally at the Institute of Methodologies for Environmental Analysis (IMAA) on Advanced Very High Resolution Radiometer (AVHRR) data. Results showed that RSTASH detected an ash plume dispersing from Mt. Etna towards Ionian Sea starting from 3 December at 08:40 UTC, whereas it did not identify ash pixels on satellite data of same day at 04:20 UTC and 04:40 UTC (acquired soon after the end of first paroxysm from VOR), due to a mixed cloud containing SO₂ and ice. During 8⁻10 December, the continuity of RSTASH detections allowed us to estimate the mass eruption rate (an average value of about 1.5 × 10³ kg/s was retrieved here), quantitatively characterizing the eruptive activity from North East Crater (NEC). The work, exploiting information provided also by Spinning Enhanced Visible and Infrared Imager (SEVIRI) data, confirms the important contribution offered by RSTASH in identifying and tracking ash plumes emitted from Mt. Etna, despite some operational limitations (e.g., cloud coverage). Moreover, it shows that an experimental RST product, tailored to SEVIRI data, for the first time used and preliminarily assessed here, may complement RSTASH detections providing information about areas mostly affected by volcanic SO₂

Implementation of the RST (Robust Satellite Techniques) approach on MSG-SEVIRI data: applications for volcanic activity monitoring

The Robust Satellite Techniques (RST) is a multitemporal approach of satellite data analysis proposed to study different natural/environmental hazards, including high risk volcanic phenomena. In particular, both thermal features and ash emissions may be investigated by RST, by using two specific configurations of such an approach. These algorithms have been tested on different volcanic areas exploiting data provided by polar satellite sensors, such as the Advanced Very High Resolution Radiometer (AVHRR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), showing a high trade-off between reliability and sensitivity of detection. In this work, the RST exportability on data provided by the Spinning Enhanced Visible Infrared Imager (SEVIRI), onboard Meteosat Second Generation (MSG) satellites, is assessed, by studying some recent eruptive events of Etna (Italy) and Grimsvotn (Iceland) volcanoes. Outcomes of this work confirm that the RST-based algorithms may give an important contribution for mitigating volcanic hazards during major eruptions, especially in the framework of integrated and automated early warning systems

Characterization of Essential Oils from Different Taxa Belonging to the Genus Teucrium in Sardinia Island, Italy

The genus Teucrium L. (Lamiaceae) is a genus growing in mild climate zones, particularly in the Mediterranean Basin and Central Asia. It is represented by 11 taxa in Sardinia (Italy), living commonly in sunny habitats. In this study, the following eight Sardinian Teucrium taxa were selected, and the essential oils (EOs), obtained by stem distillation, were analyzed by GC–FID and GC–MS: T. capitatum subsp. capitatum, T. chamaedrys subsp. chamaedrys, T. flavum subsp. glaucum, T. marum, T. massiliense, T. scordium subsp. scordioides, T. scorodonia, and T. subspinosum. The comprehensive analyses led to the identification of 87 constituents representing the majority of the volatile compounds. Significant differences, both qualitative and quantitative, were observed between the taxa. Overall, monoterpenes and sesquiterpenes characterized all Teucrium EOs: T. capitatum subsp. capitatum and T. flavum subsp. glaucum revealed the highest content of monoterpene hydrocarbons, while in the other Teucrium taxa sesquiterpene hydrocarbons prevailed. Worthy of note, diterpenes were found only in T. marum and T. subspinosum, whereas T. massiliense was rich in non-terpenic oxygenated compounds. To the best of our knowledge, this is the first comprehensive report on the chemical composition of EOs obtained from Sardinian Teucrium species