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Marine Oil Spills 2020
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Marine Oil Spills 2020

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Ocean Engineering".

Deadline for manuscript submissions: closed (15 March 2021) | Viewed by 20526

Special Issue Editor

Dr. Merv Fingas

E-Mail Website
Guest Editor
Spill Science, Edmonton, AB T6W 1J6, Canada
Interests: oil spills; remote sensing; oil spill behaviour and dynamics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Oil spill remote sensing has progressed significantly in the past few years. Remote sensing plays an increasingly important role in oil spill response efforts. Through the use of modern remote sensing instrumentation, oil can be monitored on the open ocean on a 24-hour basis. With knowledge of slick locations, response personnel can more effectively conduct countermeasures.

There is growing progress in the performance of both strategic sensors such as satellite-borne radars as well as low-cost sensors such as visible and infrared cameras. The most progress has been made in the development of the use and application software for all sensors. We are now able to eliminate noise; correct images; and focus on oil spills.

This Special Issue aims to highlight advances in the development, testing, and use of oil spill remote sensing systems. Topics include but are not limited to the following:

New developments in remote sensing;

Software to remove noise and enhance oil spill signals;

New sensors and testing of sensors;

Use of remote sensing on spills, e.g., DeepWater Horizon and others;

Use of remote sensing for illegal discharge detection;

Specialized sensors such as fluorosensors and thickness sensors;

Ship or coastal-mounted sensors;

Airborne sensors and campaigns;

Drone-mounted sensors.

Dr. Merv Fingas
Guest Editor

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. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly 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 2600 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

  • Oil spill remote sensing
  • Oil spill remote sensing software
  • New oil spill sensors
  • Use of remote sensing on spills
  • Use of remote sensing for illegal discharge detection
  • Fluorosensors or thickness sensors
  • Ship or coastal-mounted oil spill sensors
  • Drone-mounted oil spill sensors.

Published Papers (5 papers)

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Research

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15 pages, 5402 KiB  
Article
Revisit of a Case Study of Spilled Oil Slicks Caused by the Sanchi Accident (2018) in the East China Sea
by Zhehao Yang, Weizeng Shao, Yuyi Hu, Qiyan Ji, Huan Li and Wei Zhou
J. Mar. Sci. Eng. 2021, 9(3), 279; https://doi.org/10.3390/jmse9030279 - 04 Mar 2021
Cited by 4 | Viewed by 2125
Abstract
Marine oil spills occur suddenly and pose a serious threat to ecosystems in coastal waters. Oil spills continuously affect the ocean environment for years. In this study, the oil spill caused by the accident of the Sanchi ship (2018) in the East China [...] Read more.
Marine oil spills occur suddenly and pose a serious threat to ecosystems in coastal waters. Oil spills continuously affect the ocean environment for years. In this study, the oil spill caused by the accident of the Sanchi ship (2018) in the East China Sea was hindcast simulated using the oil particle-tracing method. Sea-surface winds from the European Centre for Medium-Range Weather Forecasts (ECMWF), currents simulated from the Finite-Volume Community Ocean Model (FVCOM), and waves simulated from the Simulating WAves Nearshore (SWAN) were employed as background marine dynamics fields. In particular, the oil spill simulation was compared with the detection from Chinese Gaofen-3 (GF-3) synthetic aperture radar (SAR) images. The validation of the SWAN-simulated significant wave height (SWH) against measurements from the Jason-2 altimeter showed a 0.58 m root mean square error (RMSE) with a 0.93 correlation (COR). Further, the sea-surface current was compared with that from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2), yielding a 0.08 m/s RMSE and a 0.71 COR. Under these circumstances, we think the model-simulated sea-surface currents and waves are reliable for this work. A hindcast simulation of the tracks of oil slicks spilled from the Sanchi shipwreck was conducted during the period of 14–17 January 2018. It was found that the general track of the simulated oil slicks was consistent with the observations from the collected GF-3 SAR images. However, the details from the GF-3 SAR images were more obvious. The spatial coverage of oil slicks between the SAR-detected and simulated results was about 1 km2. In summary, we conclude that combining numerical simulation and SAR remote sensing is a promising technique for real-time oil spill monitoring and the prediction of oil spreading. Full article
(This article belongs to the Special Issue Marine Oil Spills 2020)
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20 pages, 12571 KiB  
Article
Oil Spill Detection Using LBP Feature and K-Means Clustering in Shipborne Radar Image
by Jin Xu, Xinxiang Pan, Baozhu Jia, Xuerui Wu, Peng Liu and Bo Li
J. Mar. Sci. Eng. 2021, 9(1), 65; https://doi.org/10.3390/jmse9010065 - 10 Jan 2021
Cited by 15 | Viewed by 2735
Abstract
Oil spill accidents have seriously harmed the marine environment. Effective oil spill monitoring can provide strong scientific and technological support for emergency response of law enforcement departments. Shipborne radar can be used to monitor oil spills immediately after the accident. In this paper, [...] Read more.
Oil spill accidents have seriously harmed the marine environment. Effective oil spill monitoring can provide strong scientific and technological support for emergency response of law enforcement departments. Shipborne radar can be used to monitor oil spills immediately after the accident. In this paper, the original shipborne radar image collected by the teaching-practice ship Yukun of Dalian Maritime University during the oil spill accident of Dalian on 16 July 2010 was taken as the research data, and an oil spill detection method was proposed by using LBP texture feature and K-means algorithm. First, Laplacian operator, Otsu algorithm, and mean filter were used to suppress the co-frequency interference noises and high brightness pixels. Then the gray intensity correction matrix was used to reduce image nonuniformity. Next, using LBP texture feature and K-means clustering algorithm, the effective oil spill regions were extracted. Finally, the adaptive threshold was applied to identify the oil films. This method can automatically detect oil spills in shipborne radar image. It can provide a guarantee for real-time monitoring of oil spill accidents. Full article
(This article belongs to the Special Issue Marine Oil Spills 2020)
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22 pages, 5497 KiB  
Article
Oil Droplet Dispersion under a Deep-Water Plunging Breaker: Experimental Measurement and Numerical Modeling
by Fangda Cui, Xiaolong Geng, Brian Robinson, Thomas King, Kenneth Lee and Michel C. Boufadel
J. Mar. Sci. Eng. 2020, 8(4), 230; https://doi.org/10.3390/jmse8040230 - 25 Mar 2020
Cited by 16 | Viewed by 3038
Abstract
Knowledge of the droplet size distribution (DSD) of spilled oil is essential for the accurate prediction of oil transport, dissolution, and biodegradation. Breaking waves play important roles in oil droplet formation in oceanic environments. To understand the effects of breaking waves on oil [...] Read more.
Knowledge of the droplet size distribution (DSD) of spilled oil is essential for the accurate prediction of oil transport, dissolution, and biodegradation. Breaking waves play important roles in oil droplet formation in oceanic environments. To understand the effects of breaking waves on oil DSD, oil spill experiments were designed and performed in a large-scale wave tank. A plunging breaker with a height of about 0.4 m was produced using the dispersive focusing method within the tank. Oil placed within the breaker resulted in a DSD that was measured using a shadowgraph camera and found to fit a Gaussian distribution N (µ = 1.2 mm, σ2 = 0.29 mm2). For droplets smaller than 1500 µm, the number-based DSD matched the DS1988 correlation, which gives N(d) ~ d−2.3, but this was N(d) ~ d−9.7 for droplets larger than 1500 µm. An order of magnitude investigation revealed that a Gaussian volume-based DSD results in a number-based DSD that may be approximated by d−b (with b ≈ 2) for small diameters (relative to the mean), which explains the occurrence of the DS1988 correlation. With the measured wave hydrodynamics, the VDROP model was adopted to simulate the DSD, which closely matched the observed DSD. The present results reduce the empiricism of the DS1988 correlation. Full article
(This article belongs to the Special Issue Marine Oil Spills 2020)
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14 pages, 4244 KiB  
Article
Thermal Infrared Spectral Characteristics of Bunker Fuel Oil to Determine Oil-Film Thickness and API
by Gang Guo, Bingxin Liu and Chengyu Liu
J. Mar. Sci. Eng. 2020, 8(2), 135; https://doi.org/10.3390/jmse8020135 - 19 Feb 2020
Cited by 23 | Viewed by 3690
Abstract
Remote sensing is an important method for monitoring marine oil-spill accidents. However, methods for measuring oil-film thickness remain insufficient. Due to the stable differences in the surface emissivity and temperature of oil and water, the oil film can be detected using thermal infrared. [...] Read more.
Remote sensing is an important method for monitoring marine oil-spill accidents. However, methods for measuring oil-film thickness remain insufficient. Due to the stable differences in the surface emissivity and temperature of oil and water, the oil film can be detected using thermal infrared. This study measured emissivity of seven different oil-film thicknesses and seven different American Petroleum Institute (API) densities, and analyzed the spectral characteristics. Results show an optimal wavelength position for oil-film thickness and fuel API density monitoring is 12.55 μm. Principal component analysis and continuum removal methods were used for data processing. Stepwise multiple linear regression was used to establish relationships between emissivity and oil slick thicknesses and API densities. Oil-film thickness and fuel API density data were analyzed by principal component analysis and continuum removal before regression analysis. The spectral emissivity data was convolved into Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Advanced Very High Resolution Radiometer (AVHRR) thermal bands to determine potential of the sensor in oil-film detection. The result shows that neither could be used to estimate thickness. The AVHRR-4 band and band 12 and 13 of the ASTER could be used to separate oils from water and have potential to distinguish different oil types. Full article
(This article belongs to the Special Issue Marine Oil Spills 2020)
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Review

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13 pages, 3023 KiB  
Review
Visual Appearance of Oil on the Sea
by Merv Fingas
J. Mar. Sci. Eng. 2021, 9(1), 97; https://doi.org/10.3390/jmse9010097 - 18 Jan 2021
Cited by 16 | Viewed by 7112
Abstract
The visual appearance of oil spills at sea is often used as an indicator of spilled oil properties, state and slick thickness. These appearances and the oil properties that are associated with them are reviewed in this paper. The appearance of oil spills [...] Read more.
The visual appearance of oil spills at sea is often used as an indicator of spilled oil properties, state and slick thickness. These appearances and the oil properties that are associated with them are reviewed in this paper. The appearance of oil spills is an estimator of thickness of thin oil slicks, thinner than a rainbow sheen (<3 µm). Rainbow sheens have a strong physical explanation. Thicker oil slicks (e.g., >3 µm) are not correlated with a given oil appearance. At one time, the appearance of surface discharges from ships was thought to be correlated with discharge rate and vessel speed; however, this approach is now known to be incorrect. Oil on the sea can sometimes form water-in-oil emulsions, dependent on the properties of the oil, and these are often reddish in color. These can be detected visually, providing useful information on the state of the oil. Oil-in-water emulsions can be seen as a coffee-colored cloud below the water surface. Other information gleaned from the oil appearance includes coverage and distribution on the surface. Full article
(This article belongs to the Special Issue Marine Oil Spills 2020)
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