6
unit trains unload per week by Shell PSR ARUF
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In May 2015, discussions began with Washington State Department of Ecology, Skagit County, and Shell regarding 3rd party EIS.
In September and October 2015, RPS developed an approach.
In December 2015, the approach, scenarios, and deliverables were finalized with the Washington State Department of Ecology and Skagit County.
In January 2015, modelling work began.
In April 2016, the technical reports were completed.
In July 2016, the Probability, Oil Spill, and Fire and Explosion Technical Appendices to the EIS were completed.
In October 2016, the draft EIS was submitted to the Washington State Department of Ecology and Sakgit County.
In October 2016, the project put on hold by Proponent.
Shell Puget Sound Refinery (PSR) Anacortes Rail Unloading Facility (ARUF)
Shell
Understanding the potential trajectory of crude oil within the environment and its ultimate fate was necessary to identify the potential impacts. Results were also required for use in inform planning and response efforts. Oil spill release scenarios were defined by release location, release volume, and environmental conditions. Under the direction of the co-lead agencies, relatively low probability, high-impact accidents (i.e., large volume releases) were modeled to better understand the maximum potential consequences of a more extreme event. These results provide the upper range of estimates of consequence in the unlikely event that there is a large volume release of oil.
RPS provided computational oil spill modeling, technical assistance, and served as a co-author on the Environmental Impact Statement (EIS), which assessed the potential risks associated with shipments of crude-by-rail in Washington State.
Environment:
Water services:
Design and development:
Other services:
6
unit trains unload per week by Shell PSR ARUF
60,000
to 70,000 bbl of conditioned Bakken crude sarried by a single unit train
650
to 676 bbl per tank car
3
representative locations were assessed
2
release volumes studied
2
seasonal conditions per site were studied
2
biological sensitivities investigated
24
scenarios using 2 models OILMAPland and SIMAP
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