The life-cycle inventory (LCI) is used to estimate the direct and indirect inputs and releases at each step of a biofuel pathway. The results are the use of resources (e. g., energy consump­tion) and the environmental emissions (e. g., carbon dioxide, sulfur oxides, nitrogen oxides). Through characterization factors, the outcomes of LCI are utilized to assess impact categories such as climate change, stratospheric ozone depletion, photo-oxidant formation, acidification, eutrophication, ecotoxicity, human toxicity, depletion of biotic resources, and depletion of abiotic resources. The impact categories describe environmental mechanisms which convert the outcomes of the LCI into environmental damages. Indicators can be derived from these mechanisms at intermediate levels (midpoints) or damages levels, (endpoints) after normali­zation and sometimes weighting approaches. The use of endpoint methods to derive a global indicator of impact is controversial. The proponents claim for simplicity in communication of the results of the LCA to nonscientific public. The opponents emphasize the subjective nature of the weighting process and on the reductionism related to that approach.

In an entrained flow gasifier, the feed and air move cocurrently and the reactions occur in a dense cloud of very fine particles at high pressures, varying between 19.7 and 69.1 atm and very high temperatures >1000 °C. This type of gasifier has an elevated throughput of syngas (Zhang et al., 2010).

2.1.2 Low/High-Temperature Gasification

High-temperature gasification (typically above 1200 °C) results in a gas, which merely contains H2 and CO as combustible components. At low-temperature however (typically below 1000 °C), also hydrocarbons are present in the gas. A CFB gasifier operated on biomass operated at 900 ° C typically produces a gas containing 50% hydrocarbons (mainly methane, ethylene, and benzene) on energy basis (http://www. biosng. com/experimental-line-up/ gasification-technology/).

2.1.3 Heating Source for Gasification

2.1.3.1 INDIRECT (OR ALLOTHERMAL) GASIFICATION

It is characterized by the separation of the processes of heat production and heat consump­tion. It therefore generally consists of two reactors connected by an energy flow. The biomass is gasified in the first reactor and the remaining solid residue (char) is combusted in the second reactor to produce the heat for the first process. Hot sand is circulated to transport the heat from the combustor to the gasifier. These indirect gasifiers theoretically are operated at an equilibrium based on the temperature dependence of the char yield in the gasifier. This means that at a low temperature, much char is remaining from the gasifier. Since this char is combusted to produce the heat, the temperature will rise until char yield matches the energy demand of the gasification (http://www. biosng. com/experimental-line-up/ gasification-technology/).

The results again show a significant influence of the fuel blend and vehicle/fuel per­formance, with net GHG emissions ranging from 0.055 kg CO2 eq./km (E10-1, i. e., ethanol used as E10 based on actual test data) to 0.120 kg CO2 eq./km (E-3, i. e., energy basis), that is., from —77% to —49% with respect to gasoline, respectively. When taking into account actual fuel performance (from vehicle tests), E10 indeed appears to be the most favorable way of using fuel bioethanol as far as GHG emissions are concerned. This means that when considering a given volume of bioethanol to be introduced in a country, region or com­pany, the most significant reduction of GHG emissions will be achieved by using the ethanol as E10. When comparing the net GHG emissions of fuel blends (and not only of the bioethanol component in the fuel blends), E85 leads to the most significant reduction of GHG emissions, before E10 and E5 in this order (in relation to the ethanol content in the fuel blend and the amount of gasoline displaced).

In case of lack of actual vehicle test data, option E-2 (equivalent to fossil reference on a vol­ume basis) is undoubtedly the best choice for lower rates of ethanol incorporation (i. e., E5 to E20), while option E-3 (equivalent to fossil reference on an energy basis) is more appropriate for higher rates of incorporation (i. e., E85 to E100). In both situations however, options E-2 and E-3 lead to an underestimation of bioethanol merit (including the reduction of GHG emissions but also the reduction of nonrenewable energy consumption). In a very large majority of cases, E-3 (i. e., energy basis) is the choice adopted to take into account the utiliza­tion phase in a WtW approach.

When considering E5 (resp. E10) as the fuel blend, the error induced by choosing option 2 instead of option 1 is of the order of 20% (resp. 45%) to the disadvantage of ethanol. When considering E85 as the fuel blend, the error induced by choosing option 3 instead of option 1 is in the order of 3%, still to the disadvantage of ethanol. E-3 also leads to a small error when assessing the GHG balance of biodiesel, regardless of the incorporation rate.

There are several different types of grate firing, with both fixed and moving grates commonplace. They have the distinct advantage over underfeed stokers in that they can accommodate fuels with high moisture and ash content as well as with varying fuel sizes. It is very important that fuel is spread evenly over the grate surface in order to ensure that air is distributed uniformly throughout the fuel and thus combustion is kept homogeneous and stable. There are a number of different types of grate firing including fixed grates, moving grates, rotating grates, horizontal/inclined grate, water cooling grate, dumping grate, and travelling grates.

The simplest fixed-bed system is composed of one combustion room with a grate. Generally, as soon as the new biomass feed is added into the furnace, it is pyrolyzed into volatile gases and chars. Primary and secondary air supplies are provided under and above the grate for the combustion of chars and volatile gases, respectively. The heat generated through the combustion of chars is responsible for providing enough heat for the pyrolysis of newly added biomass. Because of the high content of volatile matter in biomass fuels, a greater secondary air supply is required than the primary air supply. This is one of the major differences from the process of coal combustion. Recent developments have been made to enhance the combustion efficiency. One example is the cyclonic combustion system, which may be viewed as a modified fixed-bed system, suitable for the combustion of agricultural residues and particulate wood wastes at a high efficiency (Quaak et al., 1999).

As mentioned earlier, LCA studies of biofuels (including project report, research papers, pol­icy documents, etc.) are numerous and have become even more popular with the recent imple­mentation of sustainability criteria in biofuels policy worldwide (especially in the European Union and the United States) and the increased research activities in advanced biofuel pathways (e. g., biofuels from microalgae). The results of biofuels LCA studies may vary significantly from one author to another for a variety of reasons: these include methodological choices as described in Table 1, but also the type of biofuel (including bioethanol, biodiesel, e. g., methyl esters of veg­etable oils, so-called renewable diesel, e. g., from Fischer-Tropsch synthesis, biobutanol, etc.), the type of technology (including first-, second-, and third-generation technologies, biochemical or biothermal, dedicated biofuel production, or multioutput biorefinery concept, etc.) and their corresponding level of maturity, the type of feedstock considered for a given biofuel, and the conditions under which a given feedstock is produced (dedicated production, agricultural, for­estry or industrial residues, wastes, etc.). In relation to the various aspects listed, the inventory data to characterize the production of biofuel may differ significantly depending on the level of detail (e. g., proven and long-lived technology, technology based on pilot/demonstration plant, laboratory-level experiments, physicochemical computer-based modeling, etc.). In addition, biofuels LCA studies will also vary with respect to the inventory database.

Many recent LCA studies have evaluated the environmental impact of biofuel production from microalgae (Batan et al., 2010; Campbell et al., 2011; Clarens et al., 2010; Collet et al., 2011; to cite only a few of the latest research papers). The large variety of research and develop­ment areas in this field (including biomass production, harvesting, separation, processing, transformation, and the possible products and applications) is detailed in Brennan and Owende (2010), Wijffels and Barbosa (2010), and Singh and Gu (2010). Wijffels and Barbosa (2010) con­clude by emphasizing the need for life-cycle assessment of algal biofuel production processes, while Singh and Gu (2010) report: "An adequate LCA study is still not available which may help to present a clear picture of the situation. The reason is nonavailability of commercial plant data." A similar situation can be found concerning the production of cellulosic bioethanol (Singh et al., 2010; Spatari et al., 2010) and more generally with the concept of biorefinery and the coproduction of biofuels, biochemicals and/or biomaterials (thereby stressing even more the significance of the allocation method).

All the aspects listed make it very complicated to compare the results of various biofuels LCA studies, even for a given feedstock-technology-biofuel system, according to the hypotheses and methodological choices. This is illustrated in a detailed case study in the following sections of this chapter.

Plasma gasification is a gasification process that decomposes biomass into basic components, such as H2, CO, and CO2 in an oxygen-starved environment at an extremely high temperature. Plasma is regarded as the 4th state of matter; it is an ionized gas produced by electric discharges. A plasma torch is a tubular device that has two electrodes to produce an arc. It is an independent heat source that is neither affected by the feed characteristics nor the air/oxygen/steam supply. When electricity is fed, an arc is created, and the electricity is converted into heat through the resistance of the plasma. A plasma torch can heat the biomass feedstock to a temperature of 3000 “C or higher (up to 15,000 °C). Under such extremely elevated temperature, the injected biomass stream can be gasified within a few milliseconds without any intermediate reactions. The plasma technique has high destruction and reduc­tion efficiencies. Any form of wastes, for example, liquid or solid, fine particles or bulk items, dry or wet, can be processed efficiently. In addition, it is a clean technique with little environmental impact. Plasma technique has great application potential for treating a wide range of hazardous wastes (Zhang et al., 2010).

The energy substitution efficiency (ESE) was calculated for a number of the options investigated in this study. The calculations show the effect of allocation methods as well as fuel blends and vehicle/fuel performance on the WtW net energy use and the energy sub­stitution efficiency. The results are given in Table 6 and illustrated in Figure 6.

FIGURE 6 WtW net non-renewable primary energy use of ethanol according to selected options.

The results indicate that the choice of the allocation method has a significant impact on the WtW net energy use, with values ranging from -1.485 MJp/km (S-4, i. e., substitution with both straw and DDGS as fuel) to 1.810 MJp/km (S-1, i. e., substitution with both straw and DDGS as animal feed), that is, from -143% to -48% with respect to gasoline, with E5-1 as the option regarding fuels blend and vehicle/fuel performance. The effect of the fuel blend and vehi — cle/fuel performance is also significant, with net energy uses ranging from 0.471 MJp/km (E10-1, i. e., ethanol used as E10 based on actual test data) to 1.029 MJp/km (E-3, i. e., energy basis), that is, from -86% to -70% with respect to gasoline, respectively.

Both these methodological choices also significantly affect the energy substitution effi­ciency (ESE). For a given fuel blend and vehicle/fuel performance, the higher the nonrenew­able primary energy use, the lower the ESE. For a given allocation method and bioethanol production pathway, the ESE is best when bioethanol is used in the form of E10. This notion is particularly useful when considering a given volume of bioethanol (at the scale of a country or a region for example). The results show how much more efficient it is to use this volume of bioethanol as E10 than to use it as E85 or even E5, for a given service (i. e., a given overall dis­tance traveled). The situation is obviously different when considering a vehicle owner traveling a given distance every year. The best choice (in terms of both energy and GHG bal­ance) for a specific consumer is obviously to use E85 (with a maximum volume of gasoline displaced), as long as the net energy use or net GHG emissions of the biofuel are better than those of gasoline.

Fluidized-bed furnaces operate in quite a different manner from fixed-bed furnaces and have a number of advantages associated with them. Fluidized-bed combustion uses silica sand (lime stone, dolomite, or other noncombustible materials) for bed material, keeps fuel and sand in furnace in boiling state with high-pressure combustion air, and burns through thermal storage and heat transmission effect of sand. It is suitable for high-moisture fuel or low-grade fuel. The typical operating temperatures are lower than fixed-bed systems. Depending on the blowing air velocity, fluidizing-bed systems can be further divided into Bubbling Fluidized-Bed (BFB) and Circulating Fluidized-Bed (CFB).

The system studied in this chapter as for illustration is concerned with the production, dis­tribution and use (WtW approach) of anhydrous fuel-bioethanol (99.7% wt.) as a transport fuel in Switzerland. Bioethanol is supposed to be produced from wheat also grown in Switzerland. The functional unit is 1 km.

The LCI is established by means of a spreadsheet model developed by ENERS Energy Concept and the Bioenergy and Energy Planning Research Group (BPE) of the Swiss Federal Institute of Technology, Lausanne (EPFL). The model is based on Microsoft® Excel and integrates the ecoinvent v2 database (ecoinvent, 2007; Frischknecht, 2004; Frischknecht et al., 2004), a reference in the field of LCA, developed by the Swiss Centre for Life-Cycle Inventories. The model is based on industrial data from the EU provided by the Swiss Alcohol Board, and was actually used in the implementation of various bioenergy datasets in the ecoinvent v2.0 database (Jungbluth et al., 2007; Nemecek and Kagi, 2007). The model reports on the consumption of resources (energy, chemicals, land, water, infrastructures) and emissions all along the production chain. The model was implemented in order to offer an extensive set of options regarding methodological choices.

The LCA carried out in this chapter complies with the ISO standard on LCA (ISO, 2006a, b). GHG emissions were assessed using the IPCC Global Warming Potentials (GWPs) with a time frame of 100 years. This method is most commonly used in the literature when dealing with global warming. The main greenhouse gases taken into account are carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), with respective global warming potentials (GWP) of 1, 23, and 296. Because biogenic CO2 captured by photosynthesis during plant growth is eventually almost totally emitted as CO2 during bioethanol production (fermenta­tion) and utilization (combustion), only fossil CO2 emissions are taken into account. Direct field emissions of N2O are based on a model by Agroscope (Nemecek and Kagi, 2007), also included in the ecoinvent database.

The concept’s key feature is the use of high-temperature heat from a solar-concentrating tower to drive the chemical process of converting biomass to a biofuel, obtaining a near­complete utilization of carbon atoms in the biomass. The aim of the concept is to obtain an easy to handle fuel with near-zero CO2 emission and reduced land-use requirements com­pared to first — and second-generation biofuels. H2 from water electrolysis with solar power is used for reverse water gas shift to avoid producing CO2 during the process. The solar — driven third-generation biofuel requires only 33% of the biomass input and 38% of total land as the second-generation biofuel, while still exhibiting a CO2-neutral fuel cycle. With CO2 capture, second-generation biofuel would lead to the removal of 50% of the carbon in the biomass from the atmosphere. There is a trade-off between reduced biomass feed costs and the increased capital requirements for the solar-driven process; it is attractive at intermediate biomass and CO2 prices (Hertwich and Zhang, 2009).