A graphical exploration of the Deepwater Horizon oil spill

Lendie Follett (), Ulrike Genschel () and Heike Hofmann ()

Computational Statistics, 2014, vol. 29, issue 1, 132 pages

Abstract: This paper investigates some of the immediate impacts of the Deepwater Horizon oil spill of 2010 on the environment using graphical means. The exploration focuses on the effects of the oil discharge on wildlife, the chemical pollution in the area following the spill, and salinity levels in the aftermath of the spill. Thousands of animals including birds, turtles, dolphins, and whales were found dead along the beaches and in the Gulf of Mexico in the months after the oil discharge. Levels of polycyclic aromatic hydrocarbons were found to be at dangerous levels along the coast line, making conditions for wildlife highly unfavorable. Salinity measurements, which can be used to determine currents and oil movement, are examined over time as well as geographically. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: ASA data exposition 2011; Oil spill; Exploratory data analysis (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1007/s00180-013-0432-7 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:compst:v:29:y:2014:i:1:p:121-132

Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/180/PS2

DOI: 10.1007/s00180-013-0432-7

Access Statistics for this article

Computational Statistics is currently edited by Wataru Sakamoto, Ricardo Cao and Jürgen Symanzik

More articles in Computational Statistics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().