Research on polarization detection technology of oil spill on sea surface

2021 ◽  
Author(s):  
Fuli Yang ◽  
Weimin Shen
Keyword(s):  
Oil Spill ◽  
Sea Surface ◽  
Detection Technology ◽  
Polarization Detection

scholarly journals Revisit of a Case Study of Spilled Oil Slicks Caused by the Sanchi Accident (2018) in the East China Sea

2021 ◽  
Vol 9 (3) ◽  
pp. 279
Author(s):  
Zhehao Yang ◽  
Weizeng Shao ◽  
Yuyi Hu ◽  
Qiyan Ji ◽  
Huan Li ◽  
...  
Keyword(s):  
East China Sea ◽  
Oil Spill ◽  
Oil Spills ◽  
Ocean Model ◽  
Sea Surface ◽  
East China ◽  
The East China Sea ◽  
Sar Images ◽  
China Sea ◽  
Spatial Coverage

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.

scholarly journals Sacrificial amphiphiles: Eco-friendly chemical herders as oil spill mitigation chemicals

2015 ◽  
Vol 1 (5) ◽  
pp. e1400265 ◽  
Author(s):  
Deeksha Gupta ◽  
Bivas Sarker ◽  
Keith Thadikaran ◽  
Vijay John ◽  
Charles Maldarelli ◽  
...  
Keyword(s):  
Crude Oil ◽  
Oil Spill ◽  
Oil Spills ◽  
Cold Water ◽  
Marine Ecosystem ◽  
Hot Water ◽  
Sea Surface ◽  
Marine Biota ◽  
Polar Group ◽  
Branched Chain

Crude oil spills are a major threat to marine biota and the environment. When light crude oil spills on water, it forms a thin layer that is difficult to clean by any methods of oil spill response. Under these circumstances, a special type of amphiphile termed as “chemical herder” is sprayed onto the water surrounding the spilled oil. The amphiphile forms a monomolecular layer on the water surface, reducing the air–sea surface tension and causing the oil slick to retract into a thick mass that can be burnt in situ. The current best-known chemical herders are chemically stable and nonbiodegradable, and hence remain in the marine ecosystem for years. We architect an eco-friendly, sacrificial, and effective green herder derived from the plant-based small-molecule phytol, which is abundant in the marine environment, as an alternative to the current chemical herders. Phytol consists of a regularly branched chain of isoprene units that form the hydrophobe of the amphiphile; the chain is esterified to cationic groups to form the polar group. The ester linkage is proximal to an allyl bond in phytol, which facilitates the hydrolysis of the amphiphile after adsorption to the sea surface into the phytol hydrophobic tail, which along with the unhydrolyzed herder, remains on the surface to maintain herding action, and the cationic group, which dissolves into the water column. Eventual degradation of the phytol tail and dilution of the cation make these sacrificial amphiphiles eco-friendly. The herding behavior of phytol-based amphiphiles is evaluated as a function of time, temperature, and water salinity to examine their versatility under different conditions, ranging from ice-cold water to hot water. The green chemical herder retracted oil slicks by up to ~500, 700, and 2500% at 5°, 20°, and 35°C, respectively, during the first 10 min of the experiment, which is on a par with the current best chemical herders in practice.

BRRDF Simulation Research on Detection Parameters of Oil-in-Water Emulsion of Oil Spill on Sea Surface

2020 ◽  
Vol 40 (17) ◽  
pp. 1701001
Author(s):  
张晓丹 Zhang Xiaodan ◽  
孔德明 Kong Deming ◽  
袁丽 Yuan Li ◽  
孔德翰 Kong Dehan ◽  
孔令富 Kong Lingfu ◽  
...  
Keyword(s):  
Oil Spill ◽  
Sea Surface ◽  
Simulation Research ◽  
Water Emulsion ◽  
Oil In Water ◽  
Oil In Water Emulsion

scholarly journals Marine Oil Spill Detection Based on the Comprehensive Use of Polarimetric SAR Data

2018 ◽  
Vol 10 (12) ◽  
pp. 4408 ◽  
Author(s):  
Yu Li ◽  
Yuanzhi Zhang ◽  
Zifeng Yuan ◽  
Huaqiu Guo ◽  
Hongyuan Pan ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Crude Oil ◽  
Oil Spill ◽  
Sea Surface ◽  
Synthetic Aperture ◽  
Polarimetric Sar ◽  
Classification Result ◽  
Marine Oil ◽  
Oil Spill Detection ◽  
Biogenic Slicks

As a major marine pollution source, oil spills largely threaten the sustainability of the coastal environment. Polarimetric synthetic aperture radar remote sensing has become a promising approach for marine oil spill detection since it could effectively separate crude oil and biogenic look-alikes. However, on the sea surface, the signal to noise ratio of Synthetic Aperture Radar (SAR) backscatter is usually low, especially for cross-polarized channels. In practice, it is necessary to combine the refined detail of slick-sea boundary derived from the co-polarized channel and the highly accurate crude slick/look-alike classification result obtained based on the polarimetric information. In this paper, the architecture for oil spill detection based on polarimetric SAR is proposed and analyzed. The performance of different polarimetric SAR filters for oil spill classification are compared. Polarimetric SAR features are extracted and taken as the input of Staked Auto Encoder (SAE) to achieve high accurate classification between crude oil, biogenic slicks, and clean sea surface. A post-processing method is proposed to combine the classification result derived from SAE and the refined boundary derived from VV channel power image based on special density thresholding (SDT). Experiments were conducted on spaceborne fully polarimetric SAR images where both crude oil and biogenic slicks were presented on the sea surface.

scholarly journals Enrichment of Fusobacteria in Sea Surface Oil Slicks from the Deepwater Horizon Oil Spill

2016 ◽  
Vol 4 (3) ◽  
pp. 24 ◽  
Author(s):  
Tony Gutierrez ◽  
David Berry ◽  
Andreas Teske ◽  
Michael Aitken
Keyword(s):  
Oil Spill ◽  
Deepwater Horizon ◽  
Sea Surface ◽  
Deepwater Horizon Oil Spill

scholarly journals Concentration Quantification of Oil Samples by Three-Dimensional Concentration-Emission Matrix (CEM) Spectroscopy

2019 ◽  
Vol 10 (1) ◽  
pp. 315
Author(s):  
Yunan Chen ◽  
Ruifang Yang ◽  
Nanjing Zhao ◽  
Wei Zhu ◽  
Yao Huang ◽  
...  
Keyword(s):  
Oil Spill ◽  
Three Dimensional ◽  
Emission Spectra ◽  
Quantitative Detection ◽  
Excitation Wavelength ◽  
Detection Technology ◽  
Shift Behavior ◽  
Relative Errors ◽  
Matrix Similarity

Developing fast and accurate fluorescence detection technology of oil spill is significant for quantitative analysis in unexpected oil spill events. As the oil sample concentration increases, the fluorescence spectrum produces red-shift behavior, which seriously affects the quantitative detection of concentration. In this work, a three-dimensional concentration-emission matrix (CEM) was constructed by using a series of emission spectra with different levels of concentration at the excitation wavelength of 266 nm. The database is the interpolated CEM of six samples using bicubic interpolation in the concentration dimension. With matrix similarity matching, the database was used to achieve quantification of the concentration of oil samples. The recovery rates of prediction for test samples and weathering samples of six oil samples were between 86.8% and 116.11%, with relative errors of predictions ranging from 2.09% to 15.2%. The results show that this method can provide accurate quantitative determination of the concentration of different oil samples.

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