The low density, strength, and stiffness of aspen make it unsuitable for many structural applications (Mackes & Lynch, 2001). However, aspen has an alternative use as bedding material or feedstock for biofuel or bio-oil. The amount of biomass produced per unit area by canola depends on irrigation and varies from 5 to 10 tons/ha (Enayati et al., 2009). According to the US Canola Association, canola was cultivated on 3.2 million ha during 2009, resulting in 16-32 million tons of canola straw. Early in the US history corn cobs were an important feedstock for heating houses, farm buildings, and small businesses. Now, corn cobs are reemerging as a potential feedstock for direct combustion, gasification, and cellulosic ethanol due to numerous advantages (dense and relatively uniform size, high heat value, and low N and S contents) over many competing feedstocks. The average cob yield is about 14 % of the grain yield and represents about 16 % of the corn stover biomass in a field on a dry matter basis (Roth & Gustafson, 2010). According to Blaschek and Ezeji (2010), 15% of corn stover is corn cob. Various sources have independently estimated that anywhere from 200 to 250 million dry tons of corn stover are produced per year (Sokhansanj et al., 2002; Kadam & McMillan, 2003). Based on the 15-16% of stover as cobs, the US annual production of corn cob is estimated at 30-40 million metric tons.

1.1 Introduction

In the past, it was assumed that the catalytic hydrotreatment of pyrolysis oils shows strong resemblances with conventional hydrotreatment processes of fossil feeds (hydrodesulphurisation, hydrodenitrogenation) and typical catalysts, process conditions and reactor configuration were taken from these conventional processes (Elliott, 2007). For all, the objective is a reduction of certain elements (oxygen, sulphur, nitrogen) in the feed by the action of hydrogen and a catalyst. However, common reaction conditions for the hydroprocessing of crude oil derivatives cannot be adopted directly for pyrolysis oils. For instance, pyrolysis oil cannot be treated as such at temperatures exceeding 300 oC because of its high charring tendency.

Numerous papers on hydrotreating pyrolysis oil in packed beds and autoclaves were published in the eighties and nineties, and now very recently as well (Elliott, 2007). Specifically the older literature seems rather phenomenological in nature, and merely focuses on ‘fact-finding’. Large differences in operating conditions like in pressure, temperature, residence times and hydrogen consumption are reported. In any case, without active catalyst or (high pressure) hydrogen, significant charring of pyrolysis oil occurs. Reduction of charring is possible by applying a (relatively) low temperature catalytic hydrotreatment at 175 to 250 oC, in which reactive components in the oil are ‘stabilized’. Subsequently, the stable product is further processed at higher temperatures (> 300 oC) and pressures (> 150 bar). High pressures are believed to be essential to keep the water in the pyrolysis oil feed in a liquid state (and as such probably reduce the charring reactions), to promote the solubility of hydrogen in the initially polar bio-oil, and to increase the rate of the actual hydrogenation reactions.

During the compression and extrusion processes of individual biomass compacts, the force — displacement data is recorded and can be used to calculate the specific compression and extrusion energies following the methodology reported by Adapa et al. (2006) and Mani et al. (2006). The area under the force-displacement curve can be integrated using the trapezoid rule (Cheney and Kincaid, 1980); when combined with the pellet mass, the specific energy values in MJ/t can be calculated.

During single-pellet compression and extrusion, the pellets are prepared by densifying material against a base plate (representing the specific energy required to overcome friction within the straw grinds) as opposed to commercial operation where compacts are formed due to back-pressure effect in the die. Therefore, the specific energy required to extrude the compact should be included, which will closely emulate the specific energy required to overcome the friction between the ground compressed biomass and the die. Mani et al. (2006) have indicated that the extrusion (frictional) energy required to overcome the skin friction was roughly half of the total energy (12-30 MJ/t) for corn stover. Mewes (1959) showed that roughly 40% of the total applied energy was used to compress the materials (straw and hay) and the remaining 60% was used to overcome friction. Faborode and O’Callaghan (1987) studied the energy requirement for compression of fibrous agricultural materials. They reported that chopped barley straw at 8.3% (wb) moisture content consumed 28-31 MJ/t of energy, while un-chopped material consumed 18-27 MJ/t. Shaw (2008) reported that between 95 and 99% of the total specific energy was required to compress the grinds, whereas between 1 and 5% of the total specific energy was required to extrude the compact in single pellet tests.

Shaw (2008) also reported that the mean values of specific compression energy ranged from

7.2 (pretreated wheat straw using steam explosion) to 39.1 MJ/t (wheat straw). Kashaninejad and Tabil (2011) indicated that microwave-distilled water and microwave-NaOH pre­treatments significantly increased the specific energy required for compression of wheat straw grinds so that it increased from 16.60 MJ/t to as high as 29.04 and 27.84 MJ/t after pre­treatment by microwave-distilled water and microwave-NaOH, respectively. They also reported less specific energy was required to compress wheat straw pre-treated by combination of microwave and Ca(OH)2. More specific energy was required to eject the pre­treated wheat straw grinds than the untreated wheat straw grinds and it increased from 3.20 MJ/t to 23.08 after pre-treatment by microwave-NaOH. Data analysis showed that the total energy required for compression and ejection of wheat straw grinds pre-treated by microwave-distilled water or microwave-alkaline was higher than untreated samples.

Adapa et al. (2010b) reported that the type of agricultural biomass, steam explosion pretreatment, applied pressure and screen size all had significant effect on specific energy required to form a pellet. In addition, they have developed correlations for specific energy with applied pressure and hammer mill screen size having highest R2 values for barley, canola, oat and wheat straw (Table 4). In general, the total and compression specific energy for compaction of non-treated and steam exploded barley, canola, oat and wheat straw at any particular hammer mill screen size significantly increased with an increase in applied pressure and significantly decreased with a decrease in hammer mill screen size.

Adapa et al. (2010b) also reported that the specific energy values obtained from the single­pellet compression tests should be used to compare the densification variables. However, these values may not have practical applications since the energy consumed by commercial densification machines / pilot-scale pellet mills may be higher.

Zakir Khan1, Suzana Yusup1, Murni M. Ahmad1, Yoshimitsu Uemura1,

Vuoi S. Chok2, Umer Rashid1 and Abrar Inayat1

1Universiti Teknologi PETRONAS, Perak 2Platinum Energy Sdn. Bhd., Kuala Lumpur

Malaysia

1. Introduction

Malaysia is the largest producer of palm oil and contributes 43% of worldwide production (Shuit et al., 2009). Beside palm oil, palm oil industry generated 169.72 million metric tons solid wastes which contribute 85.5% of total biomass waste produced in the country (Khan et al., 2010). This huge amount of wastes can be converted into valuable chemical feed stocks and fuels due to environmental problems associated with conventional fossil fuels.

It is well known that lignocellulosic biomass mainly consists of hemicellulose, cellulose and lignin. The usual proportions (wt%) vary as 40-50% cellulose, 20-60% hemicellulose and 10­25% lignin (Yang et al., 2007). The thermal decomposition of these individuals is important since they influence the basics of thermochemical conversion processes such as pyrolysis, combustion and gasification. Decomposition of these components is intensively studied in the literature. Demirbas et al. (2001) observed the ease of lignocellulosic biomass components decomposition as hemicellulose > cellulose >>> lignin. Based on different reasoning, Yang et al. (2007) proposed different decomposition regions of 220-300 °C, 300­340 °C and >340 °C for hemicellulose, cellulose and lignin, respectively. Lignin is the last to decompose due to its heavy cross linked structure (Guo & Lua, 2001).

Several techniques are available to study the kinetics of biomass decomposition. Among these, thermogravimetric analysis (TGA) is the most popular and simplest technique (Luangkiattikhun et al., 2008), based on the observation of sample mass loss against time or temperature at a specific heating rate. TGA provides high precision (Varhegyi et al., 2009), fast rate data collection and high repeatability (Yang et al., 2004) under well defined kinetic control region.

Very few attempts have been carried out to study the kinetics of empty fruit bunch (EFB) and palm shell (PS) using TGA. Guo & Lua (2001) presented the effect of sample particle size and heating rate on pyrolysis process and kinetic parameters for PS. They concluded a first order reaction mechanism for the decomposition of PS at different heating rates. They also suggested higher heating rates for faster and easy thermal decomposition of PS. Yang et al. (2004) studied activation energy for decompositions of hemicellulose and cellulose in EFB and PS by considering different temperature region for first order kinetic reaction. They evaluated average activation energy and pre-exponential factor from single-step decompositions of hemicellulose and cellulose. Luangkiattikhun et al. (2008) considered the

effect of heating rate and sample particle size on the thermogram behaviour and kinetic parameters for palm oil shell, fibre and kernel. They observed that there is no significant effect of particle size on the thermogram behaviour at lower temperature i. e. <320 °C for palm oil shell. They further proposed nth order reaction mechanism to evaluate the kinetic parameters based on different models.

Previous works reported on EFB and PS kinetics were based on single heating rate in which activation energy is only a function of temperature. The present work evaluate the kinetic parameters based on a method, which requires at least three sets of experimental data generated at different heating rates. This method allows the dependence of activation energy on temperature and conversion at a desired heating rate (Vyazovkin & Wight, 1999) Secondly, lignin decomposition in EFB and PS is not intensively studied at relatively high heating rates. Present work considers lignin decomposition in EFB and PS to understand the effect of lignin content on kinetic parameters and decomposition rate. Furthermore, pure lignin decomposition is studied based on its thermogram analysis and kinetic parameters.

In this work, the kinetics of biomass decomposition which includes EFB, PS, pure cellulose and lignin were investigated using TGA under non-isothermal conditions. The detail thermogram analysis was presented to understand the decomposition of cellulose, hemicellulose and lignin as major components in lignocellulosic biomass. The decomposition kinetics of cellulose and lignin were studied under single-step first order kinetic model. Meanwhile, the decomposition of EFB and PS were reported based on single­step nth order kinetic model. Activation energy, pre-exponential factor and order of reaction were determined and discussed in comparison to the values reported in the literature.

So far, the biomass Life Cycle Assessment (LCA) analyses, in which the pre-processing process of chipping, transportation and drying of biomass materials are included, and in which the energy conversion process of a production energy of electricity and/or heat through an integrated gasification combined cycle (IGCC) power system or a co-generation system (CGS) is included, were analysed (Dowaki et al. 2002, Dowaki et al. 2003).

In this section, we describe on the BT-CGS and the production system of Bio-H2. At the beginning, in this section, we defined the system boundary of the biomass LCA. A target is to estimate a life cycle inventory (CO2 emissions and/or energy intensities) of the entire system with a biomass gasification system and/or a purification one. That is, we refer to the environmentally friendly system, such as the biomass energy system, considering CO2 emissions and/or energy intensities from the entire system based on LCA methodology.

In the case of BT-CGS or Bio-H2, due to the shortage of reaction heat in the furnace or the larger auxiliary power output of PSA, the specific CO2 emission might be affected. That is, the process design and the energy analysis on basis of the process simulation would be extremely significant.

The choice of the raw materials to use to produce ethanol depends largely on local climatic conditions. North America and Europe, for instance, have based their ethanol production on materials containing starch, because of their particular farming and ecological conditions, which make it unfeasible to sugar cane adequately, although this plant offers a higher ethanol yield. In these areas, the most often grown energy crops are cereals. Using these raw materials poses some energetic sustainability limits (Patzek et al., 2005; Pimentel, 2003). The yield per ton of raw material is higher for sugar beet molasses than for cereals, so although growing sugar beet is less productive in quantitative terms than growing cereals, the annual ethanol yield from beet is higher than from cereals. The importance of analyzing the geographical position of crops helps us to see that growing the same type of cereal in tropical regions would produce a distinctly lower yield than could be achieved from the same plant grown in more suitable areas (Espinal et al., 2005). The lignocellulose materials represent the future as concerns raw materials for ethanol, because of their excellent energy value, great availability, low cost and high bioethanol yield.

These materials cannot be used to produce food, but they provide important secondary products such as methanol, syngas, hydrogen and electricity. The choice of which lignocellulose material also depends on the nature of the waste products in a given country (Kim & Dale, 2004). Cereals that are discarded during the distribution process can be destined to ethanol production, together with farming waste and sugar cane bagasse. The drawback of these raw materials consists in the complexity of the phenomena involved in converting the biomass into ethanol. Various studies have been conducted on the process of bioethanol production starting from various raw materials, including lignocellulose materials, cereals (McAloon et al., 2000; Cardona et al., 2005), and sugar cane (Quintero et al., 2008).

The above data indicate that the most important advantage of this technology is that it can utilize any form of biomass feedstock for H2 and CO generation. The mixture of gases can be utilized as direct burning both for heat and for electricity generation. High yields of methanol will be efficiently produced from the mixture of gases by using a Cu/Zn-based catalyst. The disadvantage of the system is with the size of the processing facility. The larger the plant, the higher the efficiency. The biomethanol yield from a 100 t/day gasifier would be more than twice that of the 2 t/day gasifier from the same raw materials. Although it is feasible to construct a biomethanol plant of this size, it may be very difficult to collect and provide the required 100 dry matter tons of biomass each day for the operation; with the possible exception of large sugarcane mills and palm oil industry in Southeast Asian countries. In addition, required permits and a license of boiler operation to operate such a large-scale gasifier in Japan, would add additional costs.

Prof. Sakai, of the Nagasaki Institute of Applied Science, one of the authors of this report, has developed another type of plant in the university, named "Norin Biomass No. 3" test plant (Fig. 9) by using another gasification technology, called as "high-calorie gasification reaction", that is introduced in the following sentence.

Storage stability refers to the ability of the fuel to resist chemical changes during long term storage. These changes usually consist of oxidation due to contact with oxygen from the air. The fatty acid composition of the biodiesel fuel is an important factor in determining stability towards air. Generally, the polyunsaturated fatty acids (C18:2, linoleic acid; C18:3 linolenic acid) are most susceptible to oxidation. The changes can be catalyzed by the presence of certain metals (including those making up the storage container) and light. If water is present, hydrolysis can also occur. The chemical changes in the fuel associated with oxidation usually produce hydroperoxides that can, in turn, produce short chain fatty acids, aldehydes, and ketones.

Under the right conditions, the hydroperoxides can also polymerize. Therefore, oxidation is usually denoted by an increase in the acid value and viscosity of the fuel. Often these changes are accompanied by a darkening of the biodiesel color from yellow to brown and the development of a "paint" smell. When water is present, the esters can hydrolyze to long chain free fatty acids which also cause the acid value to increase.

There is currently no generally accepted method for measuring the stability of biodiesel. The techniques generally used for petroleum-based fuels, such as ASTM D 2274, have been shown to be incompatible with biodiesel. Other procedures, such as the Oil Stability Index or the Rancimat apparatus, which are widely used in the fats and oils industry, seem to be more appropriate for use with biodiesel. However, the engine industry has no experience with these tests and acceptable values are not known. Also, the validity of accelerated testing methods has not been established or correlated to actual engine problems. If biodiesel’s acid number, viscosity, or sediment content increase to the point where they exceed biodiesel’s ASTM limits, the fuel should not be used as a transportation fuel. Additives such as BHT (butylated hydroxytoluene) and TBHQ (t-butylhydroquinone) are common in the food industry and have been found to enhance the storage stability of biodiesel. Biodiesel produced from soybean oil naturally contain some antioxidants (tocopherols, i. e., vitamin E), providing some protection against oxidation (some tocopherol is lost during refining of the oil prior to biodiesel production). Any fuel that will be stored for more than 6 months, whether it is diesel fuel or biodiesel, should be treated with an antioxidant additive.

Julian N. Rosenberg, Michael J. Betenbaugh and George A. Oyler

Johns Hopkins University United States

1. Introduction

It is anticipated that the global demand for energy will double within the next forty years (Hoffert et al., 1998). This leaves a relatively short period of time for a momentous shift in the fundamental sources of global energy. Nonetheless, satisfying our energy requirements with alternative sources can be achieved while allowing for continued technological progress, economic growth, and political stability over this period. The need for clean, sustainable energy sources is even more urgent when considered in light of the environmental consequences related to the liberation of carbon dioxide from fossil fuels.

For instance, increased production of electricity will undoubtedly necessitate a rapid expansion of nuclear, wind, solar, and hydro — power generation. Even if these sources of energy are aggressively developed, few alternatives appear to be available for the continued expansion of coal-based electricity extending to mid-century; thus, there is a pressing need for mechanisms of carbon dioxide (CO2) abatement. Energy derived from biomass presents a means of both capturing CO2 and reducing the need for a fossil fuel-based infrastructure. As such, bioenergy has the advantage of being carbon neutral and will prove to be an important asset in our repertoire of renewable energy solutions.

In addition to producing energy from sustainable sources that maintain carbon neutrality, the obligation to use energy efficiently has never been more important — not only in our daily lives, but also in the mechanisms through which we will generate energy at large scales in the future. In biological systems, the utilization of energy is accomplished by a cascade of biochemical reactions mediated by tightly regulated metabolic networks, which are substantially more efficient than the internal combustion engine. One of the most important and impressive molecular mechanisms for harvesting energy is the photosynthetic process. While photovoltaic technology has improved considerably in recent decades, the plants and algae that have been refined over billions of years of evolution represent a fully developed living framework for solar energy collection.

Conventional azeotropic distillation processes, which have one distillation column for dehydration to separate ethanol and another to separate water from their mixture, are divided into three modules. The sum of the feed enthalpy is made equal to that of the effluent stream enthalpy in each module to analyze the heating and cooling loads of all process streams by following self-heat recuperation technology. According to this analysis, the recovery streams are selected and the internal heat of the process stream in each module can be recovered and recirculated using a compressor and heat exchanger through self-heat recuperation technology.

Figure 5 a) shows the structure of the self-heat recuperative azeotropic distillation module (Kansha et al. 2010c), consisting of three modules, namely, the first distillation module, the heat circulation module, and the second distillation module. In this self-heat recuperative distillation module, stream 1 represents a feed stream of the ethanol-water azeotropic mixture and stream 2 represents an entrainer (benzene and cyclohexane) feed stream. These streams are fed into the distillation column of the first distillation module. The vapor stream from the first distillation process is compressed adiabatically by a compressor (4^5). Subsequently, stream 5 is cooled in a heat exchanger (5^6), and the pressure and

Heat exchanger

Heat

Fig. 5. Self-heat recuperative azeotropic distillation process for dehydration a) process flow diagram, b) temperature-heat diagram

temperature of stream 6 are adjusted by a valve and a cooler (6^7^8). The liquid stream (8) is divided into two streams (9 and 10) in a decanter. Stream 9 consists mainly of the entrainer, which is recycled to the feed benzene (3). The bottom (11) of the distillation
column is divided into two streams (12 and 14). Stream 14 becomes a product stream (pure ethanol). Stream 12 is heated in the heat exchanger and fed into the distillation column. In the heat circulation module, the effluent stream (10) from the first distillation module is heated in a heat exchanger and fed to the distillation column in the second distillation module. At the same time, the recycled stream, which is the distillate stream from the second distillation module, is adiabatically compressed by a compressor (18^27) and cooled by exchanging heat in the heat exchanger (27^28). The pressure and temperature of stream 28 are adjusted by a valve and cooler (28^29^30) and stream 30 is fed into the distillation column of the first distillation module as the recycled stream. Next, in the second distillation module, the feed stream (15) is separated into the distillate (16) and the bottoms (17) by the distillation column. The vapor distillate (16) is divided into two streams (18 and 19) by a separator. Stream 18 is recycled to the heat circulation module, while stream 19 is adiabatically compressed (19^20) and exchanged with the heat in a heat exchanger (20^21). The temperature and pressure of stream 21 are adjusted by a valve and a cooler (21^22^23), and then the effluent stream is fed into the distillation column. Subsequently, the bottom stream (17) from the distillation column is divided into two streams (24 and 25). Stream 25 is the product water. The other stream (24) is vaporized in the heat exchanger and fed into the distillation column (26).

Figure 5 b) shows a temperature-heat diagram for the self-heat recuperative distillation module for azeotropic distillation. Note that numbers beside the composite curve correspond to the stream numbers in Figure 5 a). It can be seen that the latent heats of the effluent streams are exchanged with those of the feed streams, as well as the sensible heats in each module, leading to minimization of the exergy loss in the heat exchangers. From this figure, it can be understood that all of process heat is recirculated without any heat addition and the total heating duty was covered by internal heat recovery. All of the compression work in each module was discarded into coolers in each module, because the sum of enthalpy in the feed streams was equal to that of the effluent streams in each module when using internal heat recovery. As this relationship indicates, the compression work was used for inducing heat recovery and circulation in each module and exhausted as low exergy heat. As a consequence, the energy required of the self-heat recuperative distillation module for azeotropic distillation is 1/8 of that of the conventional azeotropic distillation process.