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

2014 ◽  
Vol 2 (6) ◽  
pp. 4101-4133 ◽  
Author(s):  
M. Faruolo ◽  
I. Coviello ◽  
C. Filizzola ◽  
T. Lacava ◽  
N. Pergola ◽  
...  
Keyword(s):  
Treatment Plant ◽  
Industrial Process ◽  
Environmental Complexity ◽  
Gas Flaring ◽  
Multi Temporal ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Pre Treatment ◽  
Infrared Data

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.

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 ◽  
...  
Keyword(s):  
Treatment Plant ◽  
Environmental Complexity ◽  
Gas Flaring ◽  
Multi Temporal ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Pre Treatment ◽  
Using Data ◽  
Infrared Data

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.

scholarly journals The VIIRS-Based RST-FLARE Configuration: The Val d’Agri Oil Center Gas Flaring Investigation in Between 2015–2019

2020 ◽  
Vol 12 (5) ◽  
pp. 819 ◽  
Author(s):  
Mariapia Faruolo ◽  
Teodosio Lacava ◽  
Nicola Pergola ◽  
Valerio Tramutoli
Keyword(s):  
Infrared Imaging ◽  
Treatment Plant ◽  
Radiant Heat ◽  
Emissive Power ◽  
Gas Flaring ◽  
Great Consistency ◽  
Gas Flares ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Pre Treatment

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.

Assessing the RST_VOLC algorithm implementation on infrared Sentinel 3 SLSTR data

2020 ◽  
Author(s):  
Alfredo Falconieri ◽  
Francesco Marchese ◽  
Giuseppe Mazzeo ◽  
Nicola Pergola ◽  
Valerio Tramutoli
Keyword(s):  
Land Surface ◽  
European Space Agency ◽  
Space Agency ◽  
Mt Etna ◽  
Multi Temporal ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
New Generation ◽  
Algorithm Implementation

<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>

scholarly journals Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China

2019 ◽  
Vol 16 (8) ◽  
pp. 1379 ◽  
Author(s):  
Zhenzhen Wang ◽  
Jianjun Zhao ◽  
Jiawen Xu ◽  
Mingrui Jia ◽  
Han Li ◽  
...  
Keyword(s):  
Northeast China ◽  
Arable Land ◽  
Pollution Index ◽  
Air Pollutant ◽  
Thermal Anomalies ◽  
Pollutant Concentrations ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Straw Burning ◽  
Moderate Resolution Imaging Spectroradiometer

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

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