Finnfjord AS is a ferrosilicon manufacturing plant located in Finnsnes, Norway. It produces 100,000 tons of ferrosilicon and 15,000 tons of silica dust annually, using 950 GWh of electricity, 180,000 tons of quartzite, 30,000 tons of iron pellets, 34,000 tons of coke, and 79,000 tons of coal as resources. The plant employs 120 skilled workers. Finnfjord seeks to improve resource efficiency by recovering waste heat from furnaces to produce steam for industrial processes and district heating, as well as generating 340 GWh of electricity annually. This could reduce the plant's electricity consumption and associated CO2 emissions by up to

1. Resource efficency and energy intensive
industry
Dr. Toini Løvseth, Policy
Manager, Finnfjord AS

2. Finnfjord AS
 Manufacturing
– 100 000 tons of ferrosilicon
(alloying element in steel
production)
– 15 000 tons of silica dust
(cement,++)
 1960/1982
 9,5 MW/ton
 3.5 tons CO2/ton
 Privately held
 120 employees, skilled labor only
Of the 10 largest producers in the world
Provides 15% of European consumption

3. Resource use
• Electricity: 950 GWh
• Quartzite: 180 000 t
• Iron pellets: 30 000 t
• Coke: 34 000 t
• Coal: 79 000 t
Carbon is used for process purposes and
cannot be substituted

4. Flagship Roadmaps etc
 ”By reducing reliance on increasingly scarce fuels and
materials, boosting resource efficiency can also improve
the security of Europe's supply of raw materials and
make the EU's economy more resilient to future
increases in global energy and commodity prices”.
 ”The fact that resource efficiency requires action in such
a broad range of areas means that modelling is
particularly complex”.
– Add: And policies even more complex, and
overlapping…?

5. Pros
 Focus and awareness
 Policy incentives
 Possibilities for improved global
competitiveness

6. Cons
 Use of scrap metal/recycling not always possible
 Relationship between the choice of raw materials,
product quality and local emissions
– Scrap increases local emissions
– Limited availability of bio coal from hard wood
 Dedusting and cleansing means increased energy
consumption
 Value chains need to be sustainable on all accounts
 The solution is flexibility for choosing local solutions

7. The importance of energy
Labour
Finance
Quarts, coal, ir
on…
Other
operating cost
Electricit
y
Local pricing, EU carbon market

8. Energy consumption and “waste”
FeSi Furnaces Electricity Energy in
consumption waste heat
1 18,2 MW 14,6 MW
2 43,8 MW 36,5 MW
3 44,1 MW 38,1 MW
Most efficient use of waste heat energy:
- Process heat for industrial customers
- District heating

9. Finnsnes
- Close to:
- Large hydro power plants
- Quartzite resources
- Ice free harbor
- Far from:
- Everything else
- Population density: 5 inh/km2
- Everything on the picture, except
Finnfjord, is a vision

10. Waste heat recovery, principle
164 °
600 °

11. Electricity production
Total available effect for heat recovery 116 MW
Total recovery in steam producing canals and 94 MW
boilers
Electricity production, maximum capacity, 340 GWh
Reduction of consumption from grid

12. Impact on CO2-emissions
- Up to 40 % reduction of 2
electricity consumption, from the
1.8
grid: 340 GWh
- Mt CO2 saved globally by 1.6
Norwegian production and
export of….. 1.4
Electricity
1.2
- Impact on direct emissions 1
- None Ferrosilicon, wi
- Coming up next: Growing 0.8 th energy
micro algea for fish feed recovery
0.6
- Solving two local
problems in one 0.4
0.2
0

13. Policy message
 Know that
– Investments in upstream manufacturing is not
rewarded by consumers/customers
– State aid often necessary. Which means: Cannot be
mandatory, yet.
 Side effects of detailed regulation
– ETS: Almost impossible to reach allocation
benchmark if located in rural areas
– Good example: EED and the possibility to take into
account: “geographical feasibility, financial investment
potential of the installations and the existence of
alternatives”
 Double/triple and inconsistent regulation: ETS, EED and
Ecodesign on heat recovery: Which is the official view?
 Aim high, but allow for flexibility in the choice of
measures

14. Join the discussion!
 ER>ER: http://erer.ee-ip.org/erer_matrix/