In 2020, a total of 2269 million m3 (Mm3) solid-over-bark of industrial roundwood were harvested globally (Food and Agriculture Organization [FAOSTAT] 2021). In Europe, industrial roundwood cuttings totalled 722 Mm3, with the biggest removals of industrial roundwood in Europe being harvested in the Russian Federation (231 Mm3), Sweden (80.7 Mm3), Germany (70.6 Mm3) and Finland (58.7 Mm3) (FAOSTAT 2021). Recently, AFRY Management Consulting (2021) estimated that the global market for forest industry products will have grown by €175 billion by 2035, from €540 billion in 2019 to a forecasted €715 billion in 2035. AFRY Management Consulting (2021) emphasised that market growth is being driven by the replacement of plastic packaging, digitalisation, more packaging for online retail purposes, population growth, urbanisation, the prosperity of a growing middle class, increased environmental awareness by consumers, a reduction in greenhouse gas (GHG) emissions, and targets for carbon neutrality.
Globally, in 2020, energy-related carbon dioxide (CO2) emissions were at a level of 31.5 Gt, with the European Union (EU27) producing approximately 2.6 Gt of CO2 emissions (Global Carbon Atlas 2022; International Energy Agency 2022). In Finland, the total GHG emissions corresponded to 48.1 Mt of CO2 equivalent (CO2eq) in 2020 (Statistics Finland 2021). The EU’s climate and energy framework has set three demanding targets for 2030––firstly, reduce GHG emissions by at least 40%; secondly, increase the share of renewable energy sources by at least 27%; and thirdly, improve energy efficiency by at least 27% from the level of 1990 (European Union 2014). Furthermore, there is an even more exacting aim for 2050––to decrease GHG emissions to 80% below the level of 1990 (European Union 2011). In Finland, there is an ambitious target to become a carbon-neutral country by 2035 (Finnish Government 2020).
The TYKO machinery model, developed and maintained by the VTT Technical Research Centre of Finland, is used to calculate the official annual GHG emissions from machinery (e.g. agricultural tractors, wheel loaders, excavators, harvesters, forklifts, generators and forwarders) and off-road vehicles powered by combustion engines throughout Finland. According to the TYKO model, the GHG emissions from machinery in Finland in 2020 amounted to 2.4 Mt CO2eq (VTT 2021).
The annual GHG emissions from forest machines (i.e. harvesters and forwarders) were approximately 13% of the total emissions from the work-machine fleet in 2020 (VTT, 2021). According to the TYKO model, 121.3 ML of fossil light fuel oil (LFO) is used in forest machines annually. In addition to the fuel consumption by harvesters and forwarders, there is the relocating of cut-to-length (CTL) logging machinery from one harvesting site to another (Berg and Karjalainen 2003; Haavikko et al. 2022), the car travel by harvester and forwarder operators from their homes to the harvesting sites and back, and the car travel by logging managers and service and maintenance staff to the harvesting sites, all of which consume diesel fuel. However, the TYKO model does not take this additional fuel consumption into account (Laurikko and Mäkelä 2019).
Emissions from machinery and how to reduce these have become areas of interest in Finland’s current climate and energy policy (Huttunen 2017; Markkanen and Lauhkonen 2021; Paloneva and Takamäki 2021; Ministry of the Environment 2022). Emissions reduction measures for machinery have been proposed, including a change in the obligation to distribute biofuel oil, the use of biogas in machinery, a review of fuel tax increases and investment subsidies, improvements to the energy efficiency of machinery, and the proliferation of electric and hydrogen-powered machinery (Vapaavuori et al. 2014; Huttunen 2017; Paloneva and Takamäki 2021; Ministry of the Environment 2022). However, electric versions of large machinery (i.e. harvesters and forwarders) that would be out of reach of any charging infrastructure is challenging in terms of both the energy capacity of the batteries and the power required by the machinery, and so these are not expected to gain a significant market share for the next 10 or more years (Lajunen et al. 2018). Consequently, the easiest action towards decreasing fuel consumption and GHG emissions in logging operations is to improve the energy efficiency of the CTL logging-machine fleet.
Calculations and life-cycle assessments and analysis of GHG emissions call for a better understanding of, and up-to-date information on, fuel consumption from industrial roundwood CTL logging operations, including machine relocations and the car travel by operators, managers and service and maintenance staff to and from the harvesting sites (e.g. Handler et al. 2014; Han et al. 2015; de la Fuente et al. 2017; Abbas and Handler 2018; Palander et al. 2018; Haavikko et al. 2019). However, there are few recent long-term follow-up studies on the fuel consumption of CTL logging-machine chains that include both harvesters and forwarders. The latest comprehensive follow-up study on the fuel consumption of CTL logging machines in Finland was carried out in 2003––almost 20 years ago (Rieppo and Örn 2003). Rieppo and Örn (2003) reported an average hour-based fuel consumption of 12.2 L h− 1 for a harvester and 10.5 L h− 1 for a forwarder, with an average cubic-metre-based LFO consumption of 0.87 L m− 3 for cutting and 0.65 L m− 3 for forwarding.
Other comprehensive follow-up studies on the fuel consumption of CTL logging machinery in boreal forests are also quite old, such as Brunberg (2013), who studied the fuel consumption of 230 harvesters and 230 forwarders in Sweden over a two-week period. The study revealed that the total fuel consumption of forest machines had increased, on average, by 9% in 2012 compared to the level of 2006 (Brunberg 2007)––that is, from 1.50 to 1.63 L m− 3. In addition, Holzleitner et al. (2011) conducted a long-term follow-up fuel-consumption study on CTL logging machinery involving 12 harvesters and 18 forwarders in 2004–2008 in Austria, whereas Ackerman et al. (2017) assessed the fuel consumption of two harvesters and two forwarders in a follow-up study in 2014–2015 in South Africa. Magagnotti et al. (2017) and Spinelli and De Arruda Moura (2019) reported on a follow-up study of purpose-built and excavator-based harvesters using big data.
Recently, follow-up studies on fuel consumption have been made using data derived from the machines’ own data records. This new method simplifies the data collection compared to traditional studies in which fuel refills were measured. However, data from both methods are needed to ensure that the fuel consumption is of comparable magnitude, regardless of method used. In a long-term follow-up study using machine data, Jylhä et al. (2019) found that the fuel consumption of harvesters in industrial roundwood cutting operations averaged 0.90 L m− 3. This is close to the average cubic-metre-based fuel consumption of 0.87 L m− 3 for cutting reported by Rieppo and Örn (2003). In Sweden, Eliasson (2022) reported a total fuel consumption for cutting and forwarding of 1.48 L m− 3 based on machine data from 31 harvesters and 42 forwarders, which is also close to the amounts reported by Rieppo and Örn (2003) and Brunberg (2007).
Earlier fuel consumption studies have underlined that the harvesting conditions (e.g. removal stem size, cutting method, number of timber assortments), machine properties (e.g. engine power, type of machine, machine adjustments, use of tracks and wheel-chains) and machine operators (i.e. level of education, skills) have significant effects on the fuel consumption of harvesters (e.g. Rieppo and Örn 2003; Holzleitner et al. 2011; Brunberg 2013; Kenney et al. 2014; Ghaffariyan et al. 2015; Magagnotti et al. 2017; Prinz et al. 2018; Jylhä et al. 2019; Spinelli and De Arruda Moura 2019). The same is valid for forwarders, where the harvesting conditions (e.g. forwarding distance, hectare-based removals [m3 ha− 1], number of timber assortments harvested, removal stem size), machine properties (e.g. engine power, use of tracks and wheel-chains, payload) and machine operators (i.e. level of education, skills) have a large influence on fuel consumption (e.g. Nordfjell et al. 2003; Rieppo and Örn 2003; Holzleitner et al. 2011; Brunberg 2013; Kenney et al. 2014; Ghaffariyan et al. 2015; Oyier and Visser 2016; Pandur et al. 2019).
It is evident that up-to-date information on the fuel consumption of CTL harvesters and forwarders is needed, and that studies using both traditional methods and machine data are necessary for validating the latter method. Furthermore, it is essential to understand the effects of different factors on fuel consumption in cutting and forwarding. With a firm understanding of the fuel consumption of forest machines, the fuel and energy efficiency of logging machines can be improved and emissions reduction targets can be met.
Consequently, the target of this study was to measure and model the fuel consumption of CTL harvester and forwarder operations under Nordic harvesting conditions in Finland, and to clarify which factors have the most significant effect on the fuel consumption. In this study, the fuel consumption was examined in terms of the: 1) hour-based fuel consumption (L h− 1); and 2) fuel consumption per cubic metre (L m− 3) harvested. In addition, we calculated the total annual fuel consumption and CO2eq emissions caused by: 1) the harvesters and forwarders in the forests; 2) relocation of the CTL logging machinery; and 3) the car travel by harvester and forwarder operators, logging managers and service and maintenance staff to and from the harvesting sites.