Skip to main content

K+S’s first crowdsourcing competition to help reduce the saline wastewater from the tailings piles

Published by
World Fertilizer,


K+S has established ambitious sustainability goals and the company is now taking a new path in driving the achievement of these targets. With the “Brine Challenge”, K+S is looking for new approaches, concepts, and ideas to significantly reduce the saline wastewater from the tailings piles.

As part of the international crowdsourcing competition “Brine Challenge”, K+S is calling on international scientists, companies, institutes, and non-professionals alike to submit innovative proposals for covering its tailings piles. The company intends to incorporate viable new approaches into its own plans and procedures.

“With Shaping 2030, we have declared our commitment to sustainability, innovation, and constructive dialogue with our stakeholders," said Mark Roberts, COO of K+S. "We can ideally combine all these goals in our Brine Challenge.”

The company has been working on long-term projects to cover the large tailings piles in the Werra potash district for some time now. The aim is to significantly reduce the amount of saline wastewater caused by rain. Experts at K+S have developed promising methods in recent years, some of which have already been tested and implemented. In order to further optimise these processes in the future, new, innovative ideas should now also be included.

K+S is cooperating with NineSigma, the open innovation provider which will stage the challenge on its internet platform and mobolise its international network. The ideas have to fulfil specific requirements and can be submitted until December 12, 2018. The proposals will then be evaluated by a jury. Up to three of the best ideas will then be awarded €20 000 each in April 2019.

Read the article online at: https://www.worldfertilizer.com/environment/24092018/kss-first-crowdsourcing-competition-to-help-reduce-the-saline-wastewater-from-the-tailings-piles/

 

Embed article link: (copy the HTML code below):