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Predicting Sudden Changes in Pollution Patterns

María J. Olascoaga, Sc.D.
University of Miami
NIEHS Grant P50ES012736

 

An NIEHS grantee and her colleague have developed a technique for forecasting major short-term changes in how oil spills will move in the ocean. The method, which is also applicable to harmful algal blooms and volcanic ash clouds, offers a tool for minimizing the impact of environmental disasters.

 

Over the last decade, the researchers have developed mathematical methods to describe hidden patterns in the way that air and water move, known as Lagrangian coherent structures (LCSs). The new technique uses these mathematical methods to detect LCS cores, which unite incoming flow from opposite directions and eject the resulting mass of water or air. LCS cores emerge before a sudden shape change in the contamination pattern and, thus, allow the forecast of dramatic changes that were previously considered unpredictable.

 

As a demonstration, the researchers showed that the method could have forecast the tigertail and coastal spread instabilities that occurred in the Deepwater Horizon oil spill. They developed high-precision forecasts of the location and time of these major instabilities, by detecting two strong LCS cores four to six days before the instabilities were observed.

 


Citation: Olascoaga MJ, Haller G. 2012. Forecasting sudden changes in environmental pollution patterns. Proc Natl Acad Sci U S A; doi: 10.1073/pnas.1118574109 [Online 12 March 2012].


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