Title |
A-DROP: A predictive model for the formation of oil particle aggregates (OPAs)
|
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Published in |
Marine Pollution Bulletin, March 2016
|
DOI | 10.1016/j.marpolbul.2016.02.057 |
Pubmed ID | |
Authors |
Lin Zhao, Michel C. Boufadel, Xiaolong Geng, Kenneth Lee, Thomas King, Brian Robinson, Faith Fitzpatrick |
Abstract |
Oil-particle interactions play a major role in removal of free oil from the water column. We present a new conceptual-numerical model, A-DROP, to predict oil amount trapped in oil-particle aggregates. A new conceptual formulation of oil-particle coagulation efficiency is introduced to account for the effects of oil stabilization by particles, particle hydrophobicity, and oil-particle size ratio on OPA formation. A-DROP was able to closely reproduce the oil trapping efficiency reported in experimental studies. The model was then used to simulate the OPA formation in a typical nearshore environment. Modeling results indicate that the increase of particle concentration in the swash zone would speed up the oil-particle interaction process; but the oil amount trapped in OPAs did not correspond to the increase of particle concentration. The developed A-DROP model could become an important tool in understanding the natural removal of oil and developing oil spill countermeasures by means of oil-particle aggregation. |
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Geographical breakdown
Country | Count | As % |
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Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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India | 1 | 2% |
Unknown | 53 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Bachelor | 10 | 19% |
Student > Ph. D. Student | 9 | 17% |
Other | 4 | 7% |
Researcher | 4 | 7% |
Professor | 4 | 7% |
Other | 7 | 13% |
Unknown | 16 | 30% |
Readers by discipline | Count | As % |
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Engineering | 16 | 30% |
Environmental Science | 7 | 13% |
Chemical Engineering | 5 | 9% |
Earth and Planetary Sciences | 2 | 4% |
Unspecified | 1 | 2% |
Other | 5 | 9% |
Unknown | 18 | 33% |