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Abstract: The energy wood procurement possibilities for the eight regions making up Northwest Russia were assessed. Wood byproducts from logging and mechanical wood processing were considered for energy production based on actual cut, sawmill and plywood production figures for 2006. Of the total calculated potential of 31 million solid m3 (62 TWh), nearly 70% (21.8 million m3) is from logging. The remainder (9 million m3) is from sawmill and plywood production. The approximate available energy wood by region would be: 2.3 million m3 from the Republic of Karelia, 2.7 million m3 from the Republic of Komi, 5.4 million m3 from Arkhangelsk, 4.6 million m3 from Vologda, 3.8 million m3 from Leningrad, 2.0 million m3 from Novgorod, 0.8 million m3 from Pskov, and 41,000 m3 from the Murmansk region. There are large differences in the potentials between and within the regions. This is due to the differences in their forest resources; differences in their utilisation of these resources; the available infrastructures; and some limitations on logging. Nearly 65% of all the potential energy wood from logging is non-industrial roundwood, 19% is spruce stumps removed after final felling, 8% is unused branches and tops, and 8% is defective wood resulting from logging. About 58% of the total potential energy wood from logging is coniferous. However, there are large differences between the regions and within the regions in the species proportions. Currently about 40% of the allowable cut is used. This means that it would be possible to intensify the utilisation of the forest resources and thereby also to increase the use of wood for energy production. Full implementation of the allowable cut could provide 73.5 million m3 of energy wood (147 TWh). In addition, if the technical potential for thinnings is utilised, the total potential energy wood provided by logging, and mechanical wood processing could be 104 million m3 (208 TWh). [Copyright &y& Elsevier]

Forest biomass is one of the main contributors to the EU's renewable energy target of 20% gross final energy consumption in 2020 (Renewable Energy Directive). Following the RED, new sustainability principles are launched by the European energy sector, such as the Initiative Wood Pellet Buyers (IWPB or SBP). The aim of our study is the investigation of the quantitative impacts from IWPB's principles for forest biomass for energy only. We deploy a bottom up method that quantifies the supplies and the costs from log harvest until forest chip delivery at a domestic consumer. We have a reference situation with existing national (forest) legislation and voluntary certification schemes (scenario 1) and a future situation with additional criteria based on the IWPB principles (scenario 2). Two country studies were selected for our (2008) survey: one in Finland with nearly 100% certification and one in Leningrad province with a minor areal share of certification in scenario 1. The sustainable potential of forest resources for energy is about 54 Mm 3 (385 PJ) in Finland and about 13.5 Mm 3 (95 PJ) in Leningrad in scenario 1 without extra criteria. The potential volumes reduce considerably by maximum 43% respectively 39% after new criteria from the IWPB, like a minimum use of sawlogs, stumps and slash for energy, and by an increased area of protected forests (scenario 2A Maximum extra restrictions). In case sawlogs can be used, but instead ash recycling is applied after a maximum stump and slash recovery (scenario 2B Minimum extra restrictions), the potential supply is less reduced: 5% in Finland and 22% in Leningrad region. The estimated reference costs for forest chips are between €18 and €45 solid m −3 in Finland and between €7 and €33 solid m −3 in the Leningrad region. In scenario 2A, the costs will mainly increase by €7 m −3 for delimbing full trees (Finland), and maximum €0.3 m −3 for suggested improved forest management (Leningrad region). In scenario 2B, when ash recycling is applied, costs increase by about €0.3 to €1.6 m −3 , depending on the rate of soil contamination. This is an increase of 2%, on top of the costs in scenario 2A. [ABSTRACT FROM AUTHOR]