Gunter Festel, Martin Bellof, Martin Wurmseher, Christian Rammer and Eckhard Boles

Abstract The current taxation benefits for biofuels are only temporary. Therefore, biofuel production costs need to be able to compete with those of conventional fuels in order to gain market share in the future. However, highly complex influ­encing factors make a comparison of biofuel production costs with those of fossil fuels challenging. This chapter has three major goals: (1) a projection of future feedstock prices for biofuels based on the development of the price for crude oil, (2) a simulation of the effects of likely economies of scale from scaling-up produc­tion size and technological learning on production costs and (3) a scenario analysis comparing different biofuels and fossil fuels. European biofuel production costs for 2015 as well as 2020 are projected based on a calculation model for biofuel production. Our scenarios assume prices for crude oil between Euro 50 and Euro 200 per barrel for both reference years. Our results indicate that mid — to long-term, second-generation biofuels are very likely to achieve competitive production costs, if technological learning and economies of scale are factored in. Bioethanol made

G. Festel (*)

Festel Capital, Mettlenstrasse 14, 6363 Fuerigen, Switzerland e-mail: gunter. festel@festel. com

G. Festel • M. Bellof

Autodisplay Biotech GmbH, Merowinger Platz 1a, 40225 Dusseldorf, Germany G. Festel • M. Wurmseher

Butalco GmbH, Mettlenstrasse 14, 6363 Fuerigen, Switzerland G. Festel • M. Wurmseher

Department of Management, Technology, and Economics, Swiss Federal Institute of Technology Zurich, Zurich, Switzerland

C. Rammer

Centre for European Economic Research (ZEW), Mannheim, Germany E. Boles

Institute of Molecular Biosciences, Goethe-University Frankfurt,

Frankfurt am Main, Germany

A. Domingos Padula et al. (eds.), Liquid Biofuels: Emergence, Development and Prospects, Lecture Notes in Energy 27, DOI: 10.1007/978-1-4471-6482-1_5, © Springer-Verlag London 2014

from lignocellulosic biomass and biodiesel from waste oil promise the highest cost-saving potential in all crude price scenarios and are capable of outperforming fossil fuels and first-generation biofuels in the future.

Keywords Biofuels ■ Production costs ■ Scale effects ■ Learning curve effects

1 Introduction

The economic dependence on fossil fuels and the potential replacement of crude oil by biomass have been investigated in research chapters. Biomass use for bio­fuels competes with residential applications, heat/power generation and the pro­duction of food, animal feed and other industrial products. This is the reason for negative influences of first-generation biofuel production on global food prices. Whenever crude oil prices rise, the positive correlation between the production scale of biofuels and food prices becomes clearly visible, due to arbitrage effects (Chen et al. 2010). For example, a rising oil price has significantly influenced production volumes, and prices of agricultural grain on a global basis, as the pro­duction of biodiesel and bioethanol from soybeans and corn, respectively, have grown accordingly. The fact that biomass can serve as raw material for chemicals and numerous other applications is not solely the fuel industry that drives prices (Swinnen and Tollens 1991; Hermann and Patel 2007). Due to substitution effects, the price for raw materials is not only dependent on the development of biomass markets but also on the cost of fossil raw materials, such as crude oil. Conversion costs are driven by scale effects as well as time-dependent learning effects.

In order to better understand complex energy production systems under various policy objectives, numerous different calculation models have been developed. Both technical bottom-up approaches as well as macroeconomic top-down approaches have been utilised to describe the entire energy system (de Wit et al. 2010). Other authors evaluate whole supply chains for bio-based products (Stephen et al. 2010; Kim et al. 2011), biorefinery concepts (Fernando et al. 2006; Clark 2007; Francesco 2010) as well as the potential of biofuels for individual countries (Martinsen et al. 2010). For example, a mixed integer linear programming model that allows the selection of fuel conversion technologies, capacities, biomass locations, as well as the logistics of transportation from the raw material locations to the conversion sites and then to the final markets has been established by Kim et al. (2011).

Numerous research chapters have evaluated biofuels, such as biodiesel (Zhang et al. 2003; van Kasteren and Nisworo 2007; Araujo et al. 2010), or simulated biofuel processes with specialised software, such as Aspen HYSYS (West et al. 2008). By contrast, comparisons of one biofuel production process with other production processes (biofuels or fossil fuels) that take scale and learning curve effects into account are rare, even though production costs are imperative to the demand of biofuels. Some studies focus on a single process step, such as enzymes (Tufvesson et al. 2011; Klein-Marcuschamer et al. 2012), while others compare biofuel types through production cost analysis (Bridgewater and Double 1994; Giampietro and Ulgiati 2005; de Wit et al. 2010; NREL 2011). de Wit et al. (2010), for example, show that biodiesel is the most cost competitive type of fuel, dominating the early market of first-generation biofuels. Lower oil crop feedstock prices compared to those of sugar — or starch-containing crops are one of the rea­sons for biodiesel’s better cost performance compared with first-generation bioeth­anol. In addition, capital and operating expenditures for the transesterification of oil to biodiesel are below those for hydrolysis and fermentation of starch to bioeth­anol (de Wit et al. 2010). This chapter intends to calculate the production costs for various types of biofuel in Europe. It will also compare them with production costs of fossil fuels. Raw material, conversion and capital costs are taken into account as well as different scenarios of price development for raw materials and crude oil.

Four steps are central to the developed calculation model in order to analyse and compare biofuel production costs: (1) the definition of biofuel production scenarios in 2015 and 2020, (2) an estimation of future raw material prices based on assump­tions for crude oil price development and the relation between crude oil price and prices for biofuel raw materials which has been observed in the past, (3) the model­ling of scale — and time-dependent costs for capital expenditures and the conversion of biomass and (4) a calculation of the total production costs as a total of raw material, capital and conversion costs. Our model is based on publicly available data for single production process steps and the whole production process. The input data have been collected in expert interviews and intensive literature research during the past 5 years (Festel 2007, 2008). As model output, we have chosen production costs in Euro-Cent per litre, as this is a measure which end users, such as car drivers, can refer to.

Within the next 5-10 years, estimates do not see biofuels gaining a market share larger than 15 % globally (Gnansounou et al. 2009; Bagheri 2011). European Union (EU) targets support this estimation. The EU has set a target market share of 10 % in terms of all petrol and diesel transport fuels by 2020 (EU Commission 2003). That is why future fuel markets prices will still be driven by fossil fuels. Today, it is government regulations and subsidies that enable biofuels to compete with fossil fuels. However, our hypothesis is that government incentives will have a decreasing influence on biofuel demand medium to long term and that demand will be more and more driven by cost competitiveness with fossil fuels through, e. g., new tech­nologies, reduced costs in the production process, improved logistics. In the case that production costs of biofuels will be lower than those of fossil fuels, we expect demand to be high enough to absorb all produced volumes of biofuel. In our model, we do not take the connection between biofuel demand and biofuel prices into account, as the market share of biofuels is determined by its production costs.

In our model, we neglect the option of biofuel import from outside Europe but rather assume that all demand for biofuels within Europe will be met by European biofuel producers. The more developed production infrastructure, economies of scope to other production activities and a close proximity to end users may be a benefit for European production sites. Our input data for production costs are solely focused on Europe. However, our model could easily be adapted to other regions if input is changed accordingly.