scholarly journals A satellite-based analysis of the Val d'Agri Oil Center (southern Italy) gas flaring emissions

2014 ◽  
Vol 14 (10) ◽  
pp. 2783-2793 ◽  
Author(s):  
M. Faruolo ◽  
I. Coviello ◽  
C. Filizzola ◽  
T. Lacava ◽  
N. Pergola ◽  
...  

Abstract. 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.

2014 ◽  
Vol 2 (6) ◽  
pp. 4101-4133 ◽  
Author(s):  
M. Faruolo ◽  
I. Coviello ◽  
C. Filizzola ◽  
T. Lacava ◽  
N. Pergola ◽  
...  

Abstract. 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 largest Italian gas and oil pre-treatment plant (i.e. the Ente Nazionale Idrocarburi – ENI – Val d'Agri Oil Center – COVA). 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), being the industrial process regulated by strict regional laws. With reference to 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 on thirteen years of Moderate Resolution Imaging Spectroradiometer (MODIS) medium and thermal infrared data in order to identify the highly radiant records associated to the COVA flare emergency discharges. Then, exploiting data provided by ENI about gas flaring volumes in the period 2003–2009, a MODIS-based regression model was developed and tested. Achieved results indicate that such a model is able to estimate, with a good level of accuracy (R2 of 0.83), emitted gas flaring volumes at COVA.


2020 ◽  
Vol 12 (5) ◽  
pp. 819 ◽  
Author(s):  
Mariapia Faruolo ◽  
Teodosio Lacava ◽  
Nicola Pergola ◽  
Valerio Tramutoli

The RST (Robust Satellite Techniques)-FLARE algorithm is a satellite-based method using a multitemporal statistical analysis of nighttime infrared signals strictly related to industrial hotspots, such as gas flares. The algorithm was designed for both identifying and characterizing gas flares in terms of radiant/emissive power. The Val d’Agri Oil Center (COVA) is a gas and oil pre-treatment plant operating for about two decades within an anthropized area of Basilicata region (southern Italy) where it represents a significant potential source of social and environmental impacts. RST-FLARE, developed to study and monitor the gas flaring activity of this site by means of MODIS (Moderate Resolution Imaging Spectroradiometer) data, has exported VIIRS (Visible Infrared Imaging Radiometer Suite) records by exploiting the improved spatial and spectral properties offered by this sensor. In this paper, the VIIRS-based configuration of RST-FLARE is presented and its application on the recent (2015-2019) gas flaring activity at COVA is analyzed and discussed. Its performance in gas flaring characterization is in good agreement with VIIRS Nightfire outputs to which RST-FLARE seems to provide some add-ons. The great consistency of radiant heat estimates computed with both RST-FLARE developed configurations allows proposing a multi-sensor RST-FLARE strategy for a more accurate multi-year analysis of gas flaring.


2006 ◽  
Vol 21 (4) ◽  
pp. 649-655 ◽  
Author(s):  
Thomas F. Lee ◽  
Steven D. Miller ◽  
Carl Schueler ◽  
Shawn Miller

Abstract The Visible/Infrared Imager Radiometer Suite (VIIRS), scheduled to fly on the satellites of the National Polar-orbiting Operational Environmental Satellite System, will combine the missions of the Advanced Very High Resolution Radiometer (AVHRR), which flies on current National Oceanic and Atmospheric Administration satellites, and the Operational Linescan System aboard the Defense Meteorological Satellite Program satellites. VIIRS will offer a number of improvements to weather forecasters. First, because of a sophisticated downlink and relay system, VIIRS latencies will be 30 min or less around the globe, improving the timeliness and therefore the operational usefulness of the images. Second, with 22 channels, VIIRS will offer many more products than its predecessors. As an example, a true-color simulation is shown using data from the Earth Observing System’s Moderate Resolution Imaging Spectroradiometer (MODIS), an application current geostationary imagers cannot produce because of a missing “green” wavelength channel. Third, VIIRS images will have improved quality. Through a unique pixel aggregation strategy, VIIRS pixels will not expand rapidly toward the edge of a scan like those of MODIS or AVHRR. Data will retain nearly the same resolution at the edge of the swath as at nadir. Graphs and image simulations depict the improvement in output image quality. Last, the NexSat Web site, which provides near-real-time simulations of VIIRS products, is introduced.


2020 ◽  
Author(s):  
Alfredo Falconieri ◽  
Francesco Marchese ◽  
Giuseppe Mazzeo ◽  
Nicola Pergola ◽  
Valerio Tramutoli

<p>RSTVOLC is a multi-temporal algorithm developed for detecting volcanic hotspots that was successfully used to monitor active volcanoes located in different geographic areas exploiting both polar and geostationary satellite data. The algorithm runs operationally at the Institute of Methodologies for Environmental Analysis (IMAA) to monitor Italian volcanoes in near-real time by means of Advanced Very-High-Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data. In this study, we assess the possible RSTVOLC implementation on data from the Sea and Land Surface Temperature Radiometer (SLSTR). The latter is a new generation sensor flying onboard the ESA (European Space Agency) Sentinel-3 mission, offering some spectral channels in the infrared bands particularly suited to identify high temperature surfaces such as lava flows. Here, we verify the RSTVOLC implementation on SLSTR data despite the absence of a multiannual time series of satellite records, by using synthetic spectral reference fields. Results achieved by investigating recent eruptions of Mt. Etna and Stromboli (Italy) volcanoes are presented and discussed.</p>


Sign in / Sign up

Export Citation Format

Share Document