Green pattern


Industrial symbiosis for a fossil-free society

OSMET logo

OSMET aims to use industrial symbiosis to upgrade and maximize the value chain of residues generated from various industrial sectors for metallurgical applications and beyond, thus contributing to climate change mitigation, minimizing residues to landfill and saving the natural resources.




Movie about OSMET (Click on the empty space)


We have been successfully running stage 2 and got promising results. We have confidence, and we are ready to run Stage 3.

The project will follow the whole value chain from residues to products towards the market! Stora Enso acts as the supplier of feedstock residues, these residues can be upgraded by HTC and agglomeration technologies. The newly developed products will be tested via pilot trials and industrial trials at Swerim, Höganäs and Outokumpu in WP2 and WP3. These trials are of sufficient length and size to build the necessary confidence for the future industrial implementations. In order to facilitate products for the market penetration, the business ecosystem development and analysis will be performed in WP4 and WP5.


11 partners from 2 countries (Spain and Sweden) in OSMET project, including 4 industrial partners, 2 SME and 5 academic partners.

  • Industrial partners: Stora Enso, Outokumpu, SMA Mineral, Höganäs, 
  • SME (Small and medium-sized enterprises): Ingelia (SME, Spain) and Gru Konsult (SME)
  • Academy partners: Swerim, RISE, KTH (Uni.) and LTU (Uni.)


OSMET is financed by Vinnova (Sweden’s innovation agency) Challenge-Driven Innovation, CDI program and industrial in-kind contributions.


Hurray, Tova Jarnerud Örell is now a Doctor! During her PhD, she was part of the OSMET project. ”I got excited every time we could see that our plan actually worked; that one industry’s waste could be processed into the others raw material!” That was one thing that kept her motivated.

Read Tova Jarnerud Örell’s Doctoral Thesis, ”Application of Wastes from Pulp and Paper Industries for Steelmaking Processes”, supervised by Andrey Karasev and Pär Jönsson.