Palander Teijo, PhD. Prof.

Potential Mechanisms for Co-operation between Transportation Entrepreneurs and Customers: A Case Study of Regional Entrepreneurship in Finland

volume: 33, issue: 1

Prospects and Challenges of Timber Trucking in a Changing Operational Environment in Finland

volume: 35, issue: 1

Attitudes of Small and Medium-Sized Enterprises towards Energy Efficiency in Wood Procurement: A Case Study of Stora Enso in Finland

volume: 40, issue: 1

Stora Enso Wood Supply Finland (WSF) was certified to the ISO 50001 Energy Efficiency
Management System standard in 2015. At Stora Enso WSF, the goal is to improve energy
efficiency by 4% by 2020 from 2015. Improving the energy efficiency of wood procurement
(i.e. logging and timber trucking) enterprises is currently one of the main focus areas for energy
efficiency development at Stora Enso WSF. In order to clarify its state-of-the-art in the
business of wood procurement enterprises at Stora Enso WSF, logging and timber-trucking
entrepreneurs were interviewed in November and December 2017. The survey data consisted
of 25 logging and 25 timber-trucking entrepreneurs. The coverage rate of both entrepreneur
groups was 73.5% in the survey. The results indicated that timber-trucking enterprises highlight
more energy efficiency and fuel efficiency than logging enterprises. For instance, the
timber-trucking entrepreneurs underscored more energy efficiency in their acquisition decisions
of new vehicles and the greater role of fuel efficiency in the energy-efficient business than
logging entrepreneurs during 2016 and 2017. Furthermore, the survey results revealed that
logging and trucking enterprises can improve energy efficiency in their business by organizing
more energy efficiency education (i.e. economical and anticipated driving training) for
their machine operators and truck drivers. There is a positive attitude towards energy efficiency
among both logging and timber-trucking entrepreneurs. This creates a solid background
to deepen and continue energy-effective work in the wood supply chain between the enterprises
and Stora Enso WSF in the future.

Fuel Consumption, Greenhouse Gas Emissions, and Energy Efficiency of Wood-Harvesting Operations: A Case Study of Stora Enso in Finland

volume: 43, issue:

The EU’s climate and energy framework and Energy Efficiency Directive drive European companies to improve their energy efficiency. In Finland, the aim is to achieve carbon neutrality by 2035. Stora Enso Wood Supply Finland (WSF) had a target, by 2020, to improve its energy efficiency by 4% from the 2015 level. This case study researches the use of the forest machine fleet contracted to Stora Enso WSF. The aims were to 1) clarify the forest machine fleet energy-efficiency as related to the engine power; 2) determine the fuel consumption and greenhouse gas (GHG) emissions from wood-harvesting operations, including relocations of forest machines by trucks; and 3) investigate the energy efficiency of wood-harvesting operations. The study data consisted of Stora Enso WSF’s industrial roundwood harvest of 8.9 million m3 (solid over bark) in 2016. The results illustrated that forest machinery was not allocated to the different cutting methods (thinning or final felling) based on the engine power. The calculated fuel consumption totalled 14.2 million litres (ML) for harvesting 8.9 million m3, and the calculated fuel consumption of relocations totalled 1.2 ML, for a total of 15.4 ML. The share of fuel consumption was 52.5% for harvesters (cutting), 39.5% for forwarders (forest haulage), and 8.0% for forest machine relocations. The average calculated cubic-based fuel consumption of wood harvesting was 1.6 L/m3, ranging from the lowest of 1.2 L/m3 for final fellings to the highest of 2.8 L/m3 in first thinnings. The calculated fuel consumption from machine relocations was, on average, 0.13 L/m3. The calculated carbon dioxide equivalent (CO2 eq.) emissions totalled 40,872 tonnes (t), of which 21,676 t were from cutting, 16,295 t were from forwarding, and 2,901 t from relocation trucks. By cutting method, the highest calculated CO2 eq. emissions were recorded in first thinnings (7340 g CO2 eq./m3) and the lowest in final fellings (3140 g CO2 eq./m3). The calculated CO2 eq. emissions in the forest machine relocations averaged 325 g CO2 eq./m3. The results underlined that there is a remarkable gap between the actual and optimal allocation of forest machine fleets. Minimizing the gap could result in higher work productivity, lower fuel consumption and GHG emissions, and higher energy efficiency in wood-harvesting operations in the future.


Web of Science Impact factor (2022): 3.200
Five-years impact factor: 3.000

Quartile: Q1 - Forestry

Subject area

Agricultural and Biological Sciences