European biomass resource potential and costs
Introduction
Transport related primary energy demand in Europe is projected to increase from 11.7 to 16.1 EJ y−1 between 2000 and 2030. Transport thereby contributes to the European primary energy demand by a third [2]. The European Union (EU) has set targets to curb transport related emissions while allowing for mobility to increase. It aims to establish this reduction by increased efficiency, i.e. by stimulating fuel efficiency for conventional drive trains, by encouraging penetration of (fuel and electricity) hybrid vehicles, by planning for the introduction of electric and hydrogen vehicles in the future and by the use of biofuels. The biofuel directive sets its first target to blend 5.75% of bio-based fuels with conventional gasoline and diesel for road transport by 2010 and 10% by 2020 [3].
Various studies have assessed the European biomass resource potential, with differences in scope, in approach and, consequently, in outcome [4], [5], [6], [7]. Production costs for biomass resources are assessed in the VIEWLS study [6]. Differences exist in the spatial coverage of the various studies. Ericsson and Nilsson [5] assess most countries, including the EU27 plus the large agricultural countries of Ukraine and Belarus. VIEWLS assesses seven Eastern European countries, selected for their assumed substantial supply potential. The EEA study [4] covers the EU25 (minus the three smallest EU states). Common to all the analyses is the use of statistical data and presentation of results on country level. This limits the opportunity of gaining insight into spatial differences between regions, especially within larger countries.
This study assesses the European cost and supply potential, covering the EU27 and Ukraine which has been explicitly included because of its vast potential and because of its neighboring location to the EU. Calculations for estimates on the supply potential of dedicated bioenergy crops are based on a land availability assessment and a detailed spatial one by one km grid-cell size yield modeling. Results have been aggregated over 280 European regions. For estimating crop production costs detailed bottom-up cost studies are used. When combined, this bottom-up approach and high level of spatial detail provides comprehensive insight into the important factors driving production costs. Scenarios are applied in order to explore how key variables impact on the supply potential and production costs of biomass resources. Agricultural productivity determines the land that is required to meet food demand. Consequently, gains with respect to this productivity determine, to a large extent, the amount of land that can be freed up for other land uses. The scenarios emphasize this crucial role of agricultural productivity and elaborate on drivers underlying the development of this productivity.
Three methodological steps can be distinguished. 1) An assessment is made of the land required for current and future land use for food and feed production. A key driver for changes in the food-related land claim is the rise in productivity that can be established in the future. For this variable, three scenarios are developed that project rates of change into the future for agricultural productivity and livestock production. Development speeds are differentiated between the Western European Countries (WEC) and the Central and Eastern European Countries (CEEC). The surplus land area potentially available for a dedicated bioenergy crop production is determined by this exercise. 2) A parametrisation of 13 bioenergy crops is coupled with an Agro-Ecological Zoning (AEZ) database, providing information on soil characteristics and climate data. Data for the analysed crops are obtained from this spatially-explicit productivity, see Fischer et al. [8]. 3) A bottom-up economic analysis is carried out to calculate the production costs of the assessed bioenergy crops. The cost calculation is based on data providing information on capital and miscellaneous costs, land costs, labour costs and fertilizer costs. These data are gathered from an extensive literature review. Following the scenarios, the development of labour and land costs is also hypothesized to increase with productivity increases.
The results, obtained from the three analysis steps enable the construction of cost–supply curves for the five analysed crop groups. Assuming different rates of development (according to the scenarios) for the key variables, especially the increase in productivity, we have obtained ranges around the base case values for both the supply and cost. In addition, the spatial detail of the results enables the construction of maps of Europe indicating the supply and costs for over 280 European regions. The outcomes of the study can provide insight into the spatial distribution of resources and can hence serve as an indication to identify promising (high-supply and low cost) regions.
Section snippets
Land availability
Fig. 1 provides an overview of the variables included for projecting how much land could become available for bioenergy crop production. The land available for biomass production is the residual land base after subtracting the land needed for food, feed and livestock, built areas, and set aside for nature conservation. The methodology applied is described in more detail elsewhere in this volume [8]. Key variables that steer projected changes in land area requirements include food demand
Dedicated bioenergy crop potential
Fig. 4 shows six cost–supply curve graphs: five for each crop group and one summary figure for 2030. The cost–supply potential for the dedicated bioenergy crops is based on the available land, the crop-specific agro-ecological attainable yield (under rain-fed conditions) and the crop-specific production cost. The cost–supply curves are constructed for three reference years 2010, 2020 and 2030. The curves (the lines within the grey areas) indicate the baseline scenario for both the supply and
Discussion
The production of bioenergy crops connects to sustainability considerations in several ways, e.g. via the intensification of agriculture and associated land use change, the potential to reduce emissions compared to the fossil reference, etc.
The main driver to steer the freeing-up of arable land is intensification of the production of food crops. Application of an intensified management can, however, increase pressures on the environment and alter the (sustainable) use of resources. Some adverse
Conclusions
The European biomass resource potential can vary largely, depending on a number of factors. Driven essentially by productivity increases in conventional food and feed production in CEEC and to a lesser extent in WEC; agricultural land can be freed up for the production of dedicated bioenergy crop production. For the scenario's considered, ‘surplus’ agricultural land can, between 2010 and 2030, amount 360 000–660 000 km2 arable land, grassland and pastures can add an additional 50 000–240 000 km2.
Acknowledgements
The authors acknowledge the feedback and comments from project partners, in particular Marc Londo (ECN), Günther Fischer, Sylvia Prieler and Harrij van Velthuizen (all IIASA). We thank the (anonymous) reviewers for their review and useful suggestions and feel that it has significantly increased the quality of this paper. This study is conducted as part of the REFUEL project funded by the European Commission under the Intelligent Energy Europe programme.
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