Reducing the idle times of forest machines : A scenario analysis with machine big data in Finland

Abstract

The idling of forest machines reduces the energy and cost efficiencies of logging operations. This study aimed to estimate the idle times and fuel consumption during idling using automatically collected machine big data. Furthermore, a scenario approach was used to describe the influence of idle times on the volume and price of carbon dioxide (CO2) emissions. The dataset included monthly data from 2021 to 2024, covering 10 logging enterprises with a total of 28 harvesters and 23 forwarders. The results showed that the proportion of idle time of harvesters and forwarders regarding the total operating hours was 14.0% and 11.1%, respectively. Average fuel consumption during idling was 4.28 L h−1 for harvesters and 3.38 L h−1 for forwarders. Annual idle-related CO2 emissions for wood-harvesting machines in Finland were roughly estimated at around 11,000 metric tonnes (t) with costs equivalent to approximately €50 million. Reduction in idling by 25–50% could cut emissions by around 3000–5000 t CO2 and generate additional revenue roughly up to €55 million when the reduced idle engine hours were transferred into productive hours. This study concluded that understanding, as well as acknowledging, the influence of idling has a positive impact on energy and cost-efficiencies, while also ensuring more environmentally friendly logging operations. While more research is needed regarding the effects of idling in non-road machinery, this study provides a solid foundation for promoting low emissions non-road machinery operations.