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The Environmental Impacts of Oil and Gas Industry: Potential and Limits of Remote Sensing Methods

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: closed (26 March 2023) | Viewed by 4255

Special Issue Editors


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Guest Editor
Italian National Research Council (CNR)—Institute of Methodologies for Environmental Analysis (IMAA), 85050 Tito Scalo, Italy
Interests: satellite data processing; satellite methods for environmental and anthropic risk investigation
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Engineering, University of Basilicata, Potenza, Italy
Interests: optical remote sensing for oil spill detection and monitoring; remote sensing of water quality; development of satellite data management and processing algorithms
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on the role of earth observation (EO) data and remote sensing (RS) techniques for the identification and assessment of environmental impacts of both onshore and offshore oil and gas (OG) activities on air, water, soil, and ecosystems.

The oil and gas industry is a significant source of threats to the environment. Despite this, the demand for these non-renewable resources remains high. The issue of environmental sustainability is a major concern for governments and players from the oil and gas industry worldwide, which are both engaged in promoting environmentally sound industrial development. To this aim, accurate knowledge of impacts, risks, and possible accidents that may arise from these activities is fundamental to reducing pollution from OG activities and their impacts on human and society. Substantial challenges remain in obtaining timely and accurate information about these phenomena.

Within this context, one promising method of addressing this issue is to use EO systems, recognized as effective tools for surveying the environment. The synergistic use of EO-derived data and the integration with ground-level observations are becoming a fundamental requirement for identifying pollution sources from oil and gas platforms, tracking their emissions over time, and measuring and monitoring local to global sustainable development policies and programs.

The purpose of this Special Issue is to collect research articles addressing this complex and multifaceted topic, with particular reference to:

  • Exploring the current earth observation capabilities in providing an overview of the environmental status and of trends over time seen in relation to OG activities;
  • Analyzing the capabilities and drawbacks of satellite data (both optical and synthetic aperture radar (SAR)) and methods for detecting, characterizing, and estimating all impacts (environmental, social, economic) of OG activities.

Dr. Mariapia Faruolo
Dr. Valeria Satriano
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • earth observation
  • remote sensing
  • oil and gas industry
  • environmental impacts
  • satellite methods
  • monitoring systems
  • impact assessment methods
  • environmental sustainability

Published Papers (2 papers)

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Research

20 pages, 8204 KiB  
Article
Assessment of RXD Algorithm Capability for Gas Flaring Detection through OLI-SWIR Channels
by Elmira Asadi-Fard, Samereh Falahatkar, Mahdi Tanha Ziyarati, Xiaodong Zhang and Mariapia Faruolo
Sustainability 2023, 15(6), 5333; https://0-doi-org.brum.beds.ac.uk/10.3390/su15065333 - 17 Mar 2023
Cited by 1 | Viewed by 1168
Abstract
The environment, the climate and human health are largely exposed to gas flaring (GF) effects, releasing significant dangerous gases into the atmosphere. In the last few decades, remote sensing technology has received great attention in gas flaring investigation. The Pars Special Economic Energy [...] Read more.
The environment, the climate and human health are largely exposed to gas flaring (GF) effects, releasing significant dangerous gases into the atmosphere. In the last few decades, remote sensing technology has received great attention in gas flaring investigation. The Pars Special Economic Energy Zone (PSEEZ), located in the south of Iran, hosts many natural oil/gas processing plants and petrochemical industries, making this area one of the most air-polluted zones of Iran. The object of this research is to detect GF-related thermal anomalies in the PSEEZ by applying, for the first time, the Reed-Xiaoli Detector (RXD), distinguished as the benchmark algorithm for spectral anomaly detection. The RXD performances in this research field have been tested and verified using the shortwave infrared (SWIR) bands of OLI-Landsat 8 (L8), acquired in 2018 and 2019 on the study area. Preliminary results of this automatic unsupervised learning algorithm demonstrated an exciting potential of RXD for GF anomaly detection on a monthly scale (75% success rate), with peaks in the months of January and February 2018 (86%) and December 2019 (84%). The lowest detection was recorded in October 2019 (48%). Regarding the spatial distribution of GF anomalies, a qualitatively analysis demonstrated the RXD capability in mapping the areas affected by gas flaring, with some limitations (i.e., false positives) due to possible solar radiation contribution. Further analyses will be dedicated to recalibrate the algorithm to increase its reliability, also coupling L8 and Landsat 9, as well as exploring Sentinel 2 SWIR imagery, to overcome some of the observed RXD drawbacks. Full article
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9 pages, 2210 KiB  
Article
Seawater Fluorescence Near Oil Occurrence
by Emilia Baszanowska and Zbigniew Otremba
Sustainability 2020, 12(10), 4049; https://0-doi-org.brum.beds.ac.uk/10.3390/su12104049 - 15 May 2020
Cited by 3 | Viewed by 2205
Abstract
Petroleum and its related products pose a serious pollution risk to the world’s seas and require a simple, rapid detection method. This is a difficult task if the pollution is under the water surface. One common approach to oil detection is excitation-emission spectroscopy [...] Read more.
Petroleum and its related products pose a serious pollution risk to the world’s seas and require a simple, rapid detection method. This is a difficult task if the pollution is under the water surface. One common approach to oil detection is excitation-emission spectroscopy (EEMs) of seawater exposed to oil for analyzing the fluorometric index (FIo/w) as a potential indicator of oil presence in the marine environment. In this paper, FIo/w was determined for both natural seawater and samples of the same water, but exposed to a relatively small portion of oil. The water samples were collected from the coastal and port waters of the Gdynia region (Southern Baltic Sea) from five stations, four times at two-week intervals. FIo/w indicates the changes between seawater sampled from the marine environment and the same seawater polluted with oil substances. Moreover, the obtained FIo/w values do not depend on the point and time of sampling. In all cases of seawater exposed to oil, significantly higher FIo/w values were observed than for unpolluted seawater. Moreover, the detection of oil by analyzing the value of FIo/w is efficient if the oil-to-water weight ratio is close to or above 5 × 10−6. Full article
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