Asset Details
Do you wish to reserve the book?
Monitoring Deep-Sea Mining's Effects
Hey, we have placed the reservation for you!
By the way, why not check out events that you can attend while you pick your title.
Oops! Something went wrong.
Looks like we were not able to place the reservation. Kindly try again later.
Are you sure you want to remove the book from the shelf?
Monitoring Deep-Sea Mining's Effects
Do you wish to request the book?
Monitoring Deep-Sea Mining's Effects
Please be aware that the book you have requested cannot be checked out. If you would like to checkout this book, you can reserve another copy
We have requested the book for you!
Your request is successful and it will be processed during the Library working hours. Please check the status of your request in My Requests.
Oops! Something went wrong.
Looks like we were not able to place your request. Kindly try again later.
Trade Publication Article
Monitoring Deep-Sea Mining's Effects
2020
Overview
With the significant development of exploratory deep-sea mining activities, the demand for routine environmental monitoring in the deep sea has become pressing. Today, no commercial instrumentation exists that can monitor the parameters of importance for regulators and operators. A collaboration led by Sequoia Scientific Inc., the Massachusetts Institute of Technology (MIT) and Scripps Institution of Oceanography (SIO) has been funded to develop a commercial instrument for deep-sea environmental monitoring of mining activity. The past decade has seen a substantial increase in activities surrounding the potential development of a global deep-sea mining industry, with numerous governments and private companies developing research and engineering programs. Besides the potential user base in the deep-sea mining industry, future users of the proposed new sensor could come from the ocean science, oil and gas, sediment transport, and coastal engineering sectors. An instrumentation package that can measure particle size, concentration and settling velocity in real time or near real time would be potentially attractive for scientists, managers and engineers in these sectors.
