Articles by Kari Väätäinen

The EU’s influence on national forest policies is growing, and the implementation of forest-related policies proposed by the Commission will affect the practice of forestry in Europe. For instance, the Nature Restoration Law sets concrete areal goals for restoring forest ecosystems and for conservation, the Deforestation Regulation requires meticulous tracking of wood’s origin, and the renewed Renewable Energy Directive (RED III) sets new criteria to sustainable forest biomass procurement. So far there have been no studies that have looked into the impacts from the economic and operational point of view. In this study, structural systems analysis was first performed to discover the relevant variables (and their functioning) associated with the roundwood harvesting operations and the operating environment. A scenario approach was then applied to capture the potential levels of implementation of the EU’s forest-related policies. Finally, using different scenarios (low-, moderate- and high-impact) and a systems analysis framework, the impact of alternative levels of implementation was quantified in terms of harvesting costs, measured in € m^–3. The results indicate that with the low- and moderate-impact scenarios the harvesting costs would increase by less than 10% from the current levels in three different regions in Finland. Such an increase (less than 10%) could be tolerated over a period of a few years, but a sudden increase is likely to lead to challenges to the running of businesses. With the high-impact scenario the harvesting costs would increase by between 15% and 18%, depending on the region. This magnitude of increase (of approximately a sixth) corresponds to a severe change in the roundwood harvesting operations and operating environment.

• Ahtikoski, Natural Resources Institute Finland (Luke), Tekniikankatu 1, FI-33720 Tampere, Finland https://orcid.org/0000-0003-1658-3813 E-mail: anssi.ahtikoski@luke.fi
• Väätäinen, Natural Resources Institute Finland (Luke), Yliopistonkatu 6, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-6886-0432 E-mail: kari.vaatainen@luke.fi
• Anttila, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0002-6131-392X E-mail: perttu.anttila@luke.fi
• Laitila, Natural Resources Institute Finland (Luke), Yliopistonkatu 6, FI-80100 Joensuu, Finland E-mail: juha.laitila@luke.fi
• Mutanen, Natural Resources Institute Finland (Luke), Yliopistonkatu 6, FI-80100 Joensuu, Finland https://orcid.org/0000-0003-0533-9356 E-mail: antti.mutanen@luke.fi
• Lindblad, Natural Resources Institute Finland (Luke), Yliopistonkatu 6, FI-80100 Joensuu, Finland https://orcid.org/0009-0003-6766-6587 E-mail: jari.lindblad@luke.fi
• Sikanen, Natural Resources Institute Finland (Luke), Yliopistonkatu 6, FI-80100 Joensuu, Finland E-mail: lauri.sikanen@luke.fi
• Routa, Natural Resources Institute Finland (Luke), Yliopistonkatu 6, FI-80100 Joensuu, Finland https://orcid.org/0000-0001-7225-1798 E-mail: johanna.routa@luke.fi

Road transport produces 90% of greenhouse gas emissions in timber transport in Finland. It is therefore necessary to understand the factors that affect driving speed, fuel consumption, and ultimately, emissions. The objective of this study was to assess the effect of road characteristics on timber truck driving speed and fuel consumption. Data from the fleet management and transport management systems of two timber trucks were collected over a year. A sample of 104 trips was drawn, and the tracking points were overlaid on the road data in a geographical information system. Thereafter, work phases were determined for the points, and they were visually classified into road and pavement classes. Subsequently, the data of 80 trips were utilised in regression analysis to further study the effects of the visually interpreted variables on driving speed and fuel consumption. Fuel consumption was explained by the proportion of forest roads and distance travelled with a loader, and the number of crossings and season when driving without a load. When driving with a load, both asphalt and gravel pavements decreased consumption, in contrast to an unpaved road. Crossings increased fuel consumption, as did the winter and spring months, and the total laden mass of the truck. In conclusion, the study showed that the functional Finnish road and pavement classes can be used to predict driving speed and fuel consumption.

• Anttila, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0002-6131-392X E-mail: perttu.anttila@luke.fi
• Ojala, UPM Metsä, Sirkkalantie 13 b, FI-80100 Joensuu, Finland E-mail: johannes.ojala@upm.com
• Palander, School of Forest Sciences, University of Eastern Finland (UEF), Yliopistokatu 7, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-9284-5443 E-mail: teijo.s.palander@uef.fi
• Väätäinen, Natural Resources Institute Finland (Luke), Yliopistokatu 6, FI-80100 Joensuu, Finland https://orcid.org/0000-0002-6886-0432 E-mail: kari.vaatainen@luke.fi

Expertise in the cost-efficient utilization and treatment of brushwood on forest roadside sites is limited. In the present study, the productivity of brushwood clearing and harvesting on forest roadside sites was defined by creating time-consumption models or parameters for the aforementioned working methods. Compiled time consumption models and parameters for the brushwood clearing and harvesting can be used as a basis for evaluating alternative management practices and to determine when brushwood biomass should be harvested and when it should be left to decay. The harvesting of brushwood was based on the harwarder system and the clearing of brushwood was done with a spiral cutter, which is a novel accessory for cutting roadside vegetation. Based on the study results, the average volume of harvested brushwood and forwarding distance are the key elements that have an effect on harvesting productivity with harwarders. Correspondingly, stump diameter has a strong impact on the clearing productivity of brushwood. The plot-wise productivity of the spiral cutter in brushwood clearings varied in the range of 0.19–0.61 ha per PMh. An increase in stump diameter slowed down the clearing productivity of the spiral cutter and there was a clear step downward in clearing productivity as the average diameter increased from 30 mm to 40 mm. The machinery under study operated well and there were no interruptions due to machine breakdowns.

• Laitila, Natural Resources Institute Finland (Luke), Production systems, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: juha.laitila@luke.fi
• Väätäinen, Natural Resources Institute Finland (Luke), Production systems, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: kari.vaatainen@luke.fi

In wintertime, the payload capacity of a timber truck is reduced by snow that accumulates on the structures of the truck. The aim of this study was to quantify the potential payload loss due to snow and winter accessories and to predict the loss with weather variables. Tare weights of eight timber trucks were collected at mill receptions in Finland over a one-year period. Monthly and annual loss of potential payload was estimated using the tare measurements in summer months as a reference. Each load was also connected with weather data at the location and time of delivery and payload loss explained by the weather data with the aid of regression models. The maximum loss of payload varied between 1560 kg and 3100 kg. On a monthly basis, the highest losses occurred in January, when the median values varied between 760 kg and 2180 kg. Over the year, the payload loss ranged between the trucks from 0.5% to 1.5% (from 1.9% and 5.1% in January) of the total number of loads in the study. Payload loss was found to increase with decreasing temperature, increasing relative humidity and increasing precipitation. Although the average payload loss was not very high, the biggest losses occur just during the season of highest capacity utilization. Big differences were also found in the tare weights between the trucks. The results of the study give incentive to develop truck and trailer structures that reduce the adherence of snow.

• Anttila, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0002-6131-392X E-mail: perttu.anttila@luke.fi
• Nummelin, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland E-mail: tuomas.nummelin@luke.fi
• Väätäinen, Natural Resources Institute Finland (Luke), Yliopistokatu 6, FI-80100 Joensuu, Finland E-mail: kari.vaatainen@luke.fi
• Laitila, Natural Resources Institute Finland (Luke), Yliopistokatu 6, FI-80100 Joensuu, Finland https://orcid.org/0000-0003-4431-3319 E-mail: juha.laitila@luke.fi

• Karttunen, Lappeenranta University of Technology, LUT Savo Sustainable Technologies, Mikkeli, Finland E-mail: kalle.karttunen@lut.fi
• Väätäinen, The Finnish Forest Research Institute, Joensuu, Finland E-mail: kari.vaatainen@metla.fi
• Asikainen, The Finnish Forest Research Institute, Joensuu, Finland E-mail: antti.asikainen@metla.fi
• Ranta, Lappeenranta University of Technology, LUT Savo Sustainable Technologies, Mikkeli, Finland E-mail: tapio.ranta@lut.fi

• Nuutinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: yrjo.nuutinen@metla.fi
• Väätäinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: kv@nn.fi
• Asikainen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: aa@nn.fi
• Prinz, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: rp@nn.fi
• Heinonen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jh@nn.fi

• Nuutinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: yrjo.nuutinen@metla.fi
• Väätäinen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: kv@nn.fi
• Heinonen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: jh@nn.fi
• Asikainen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: aa@nn.fi
• Röser, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: dr@nn.fi

• Rantala, Finnish Forest Research Institute, Suonenjoki Research Station, FIN-77600 Suonenjoki, Finland E-mail: juho.rantala@metla.fi
• Väätäinen, Finnish Forest Research Institute, Joensuu Research Centre, FIN-80101 Joensuu, Finland E-mail: kv@nn.fi
• Kiljunen, Finnish Forest Research Institute, Suonenjoki Research Station, FIN-77600 Suonenjoki, Finland E-mail: nk@nn.fi
• Harstela, Finnish Forest Research Institute, Suonenjoki Research Station, FIN-77600 Suonenjoki, Finland E-mail: ph@nn.fi