Environmental impacts of various biomass supply chains for the provision of raw wood in Bavaria, Germany, with focus on climate change.

Wood biomass is considered a renewable raw product, but the supply chain of wood biomass involves non-renewable energy inputs, and thus possibly entailing environmental impacts. The objective of this study was to analyze different environmental impacts (GHG emissions, without biogenic CO2; primary energy consumption, non-renewable; particulate matter) caused by the provision of forest biomass for the four main tree species in Bavaria using Life Cycle Assessment (LCA) techniques. Based on forest growth simulations, a set of realistic forest biomass supply chains for Bavarian forestry conditions were modeled for the raw wood product system from site preparation to forest road and to plant/farm gate, respectively, analyzing the four different process groups: [A1] site preparation, [A2] site tending, [A3] biomass harvesting and [T] transport of biomass to plant/farm gate. Total GHG emissions of about 383,000tCO2-eq∗year(-1) (18.95kgCO2-eq∗m(-3)) are estimated for the Bavarian forestry sector (from site preparation to plant/farm gate) in the reference year 2013 indicating a share of 0.41% in the total GHG emissions of Bavaria. 0.035MJ of non-renewable energy has to be invested in order to provide 1MJ of woody biomass to plant/farm gate (267MJ∗m(-3)). One hundred and sixty six tons of particulate matter emissions per year are calculated for the Bavarian forestry sector in 2013 (0.008kgPM2.5-eq∗m(-3)). Our LCA results reveal that there is no single GHG emission value for raw wood but a broad range of possible GHG emissions for the Bavarian forestry. Most decisive parameters are forest road maintenance, biomass harvesting, forwarding and biomass transport, and GHG emissions are also notably influenced by tree species, age class, wood assortment and site quality. We recommend that environmental impact calculations should be implemented, for example in wood certification procedures as they are important key indicators for sustainable forest management.