IKONOS was launched in September of 1999 in a 680 km high sun-synchronous orbit with a descending node crossing at approximately 10h15 local solar time. The IKONOS satellite simultaneously collects imagery in four multispectral bands and a single panchromatic band with 11-bit radiometric resolution. Data used in this project were collected by the IKONOS sensor on September 23, 2006. Rational polynomial coefficients (RPCs) were included to aid in the geo-rectification of the imagery. Orthorectification was undertaken using ENVI 4.3. RPCs were used in conjunction with a digital elevation model provided by industry partners. The recti­fication of the data was undertaken using 20 ground control points collected using a Leica GS 20 DGPS; the resulting root mean square error was less than half a pixel (<2 m). IKONOS radiometric correction began with converting the 11 bit digital numbers to top-of-atmosphere (TOA) radiance (Pagnutti et al. 2003). Following this the data were radiometrically corrected and converted to unitless reflectance using the Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) correction model (Alder-Golden et al. 1999; Matthew et al. 2000). Conversion to reflectance generally results in temporally independent imagery, since the majority of atmospheric influences are corrected for. This theoretically enables extrapolation of results to other seasons and years, as opposed to the temporally restricted use of radiance imagery.

Much of the current knowledge of fire and its effects on Zambezian Phytoregion structure and functioning has come from anecdotal evidence supplemented by information derived from limited number of experiments. The interest of focus among the early researchers has been more on later stages in changing of vegetation communities with emphasis on ecological groups (see Lawton 1978). However, several studies attempted to determine the effects of fire frequency and burning period on the structure and function of the miombo woodlands (see Trapnell 1959; Kikula 1986; Chidumayo 1988a, b; Zolho 2005). In Zambia, Trapnell (1959) and Chidumayo (1988a, b) studied the response of miombo species to varying burning regimes. Similar studies were conducted in Tanzania (Kikula 1986) and Mozambique (Zolho 2005). All recent studies (Kikula 1986; Chidumayo 1988a, b; Zolho 2005) confirmed the findings of Trapnell (1959) about sprouting behavior of miombo species under fire influence. The effects of fire on forest composition have also been observed in other vegetation types such as the forest in Okavango in Namibia (Geldenhuys 1977) and Kruger National Park in South Africa (Higgins et al. 2007). These studies demonstrated that species dominance and coppice effectiveness can be influenced by fire frequency and intensity. This is because fire may affect the perennating organs and root food reserves. Fire attack on perennating organs and food reserves usually results in die-back of shoots as a result of depletion of root food reserve of parent plants due to systematic and continuous effect of fire (Kennard et al. 2002). From a management perspective, fire management in extensively managed woodland should take into account the age of the woodland, the phenology of the dominant and/or desirable species, the type of land use and the management objectives of the area. Burning may not be necessary where livestock grazing or litter harvesting removes most of the fuel biomass. If burning is carried out in woodland areas where wood is a desired product, it should be done at the end of the rainy season, when the moisture levels in both grass and tree layer are relatively high (Trapnell 1959; Chidumayo et al. 1996).

Bulk trailers take on a number of forms. Rigid trucks with a tipping bed can be used without a trailer, but transport a limited volume. These trucks are compelled to wait during the loading process, but are agile on poor forest roads and have a short unloading time. For longer chip transport, semi-trailers fitted with reciprocating slatted floors, such as the Walking Floor™ trailer, or side tilting designs, can be used successfully. Articulated trucks can have problems on winding or steep roads, but benefit greatly from their superior load capacity. Semi-trailers and drawbar trailers can be exchanged at the landing, or the truck can wait to be filled. This requires matching with a high production chipper. Side-tipping trailers have minimal offloading times, but require specialized receiving bunkers that run the entire length of the trailer. End-loading trailers can unload into more commonly available bunkers. Chipper-trucks (fitted with own chipper) have reduced transport capacity but have high mobility in that they are not dependent on other machines and work well in areas with a higher number of smaller landings.

Wood chunks or residues can be further comminuted with a hammermill (Fig. 8.1a) or a chipper (Fig. 8.1b). A hammermill breaks down particles with blunt metal hammers and the resulting particles have a fairly wide size distribution. The

maximum particle size can be determined by a sieve through which the particles have to pass before they can leave the mill. In a disk — or drum-chipper the particles are cut along the grain with a knife, which results in fairly even sized chips of a few centimetre side lengths.

Further mechanical comminution of chips can be attained by grinding or milling (0.2-2 mm) with various mills. Ball mills, vibratory mills, hammer mills, knife mills, two-roll mills, colloid mills, attrition mills or extruders can be employed for this purpose. The choice of equipment is largely determined by the moisture content of the biomass (Kratky and Jirout 2011). While colloid mills and extruders are only appropriate for materials with a moisture content of 15-20 %, ball or vibratory ball mills can be employed for dry and wet materials. The energy requirements and hence subsequent costs of the comminution step are dictated by the type of mill, the original and target particle size, and the lignocellulose characteristics.

The conservation of biodiversity and the use of scarce resources such as water are issues that belong at the landscape scale. The challenge is then to balance these impacts at the landscape scale and to ensure biological corridors/linkages in the indigenous vegetation that can facilitate the movement of individuals and genetic material. Evaluation of landscape scale impacts will also consider the effects of biomass production systems on water and air quality.

This book was developed to provide a guideline for biomass production, procurement and energy production for scientists, practitioners, and decision makers who are interested in a value-chain perspective of bioenergy production from wood in tropical and sub-tropical countries. It was written as a collaborative effort of several specialists on the topic, with a core group at the Department of Forest and Wood Science of Stellenbosch University in South Africa. In integrating all the authors’ expertise in a multi-disciplinary context, the goal was to address an identified gap of knowledge on dealing with sustainable wood-based bioenergy concepts in the tropical regions of the Southern Hemisphere.

The decision to cover the whole value-chain of bioenergy production from wood was made to provide a holistic view on bioenergy production and pinpoint issues that might be relevant for a truly sustainable implementation. In particular also socio-economic side effects of bioenergy production and effects on local and global environment were addressed. In the development of such a book it is always a balancing act to provide the right degree of detail and scientific depth. Due to size limitations of this book, such a rather wide scope inevitably led to sections that had to be formulated concise and more detail had to be acquired with help of the given references. However, we hope that the chosen approach will provide accessibility to a wider readership and at the same time open up the way for enough in-depth information.

Writing this multi-disciplinary book on bioenergy was a learning experience for all of us authors, and our hope is that this book provides valuable information on the many complex aspects of sustainability that are involved in bioenergy production from wood in the tropics in all its many aspects from the tree to the energy.

Professor for Forest Growth and Yield Science Thomas Seifert

Department of Forest and Wood Science The editor

University of Stellenbosch, Stellenbosch, South Africa

Acknowledgements

We would like to dedicate this book to our late colleagues Anthonie van Laar (t 2009) and Kobus Theron (f 2011), two extraordinary scientists, who pioneered biomass research in South Africa and contributed to this book in the early stages with their helpful comments. Sadly they did not have the opportunity to see this book finished, what would have surely pleased them since it took their work a step further.

The authors would further collectively like to acknowledge the contribution of several persons that provided helpful comments on chapters in this book or contributed illustrations:

Dr. Wale Aboyade

Environmental & Process Systems Engineering Research Group Chemical Engineering Department, University of Cape Town

Prof. Harro von Blottnitz

Associate Professor at the Department of Chemical Engineering University of Cape Town, South Africa

Dr. Michel Brienzo

National Institute of Metrology, Quality and Technology, Brazil

Dr. Willie Claassen

CEO EC Biomass, South Africa

Dr. Lutz Fehrmann

Abteilung Waldinventur und Fernerkundung Fakultat fur Forstwissenschaften und Waldokologie Georg-August-Universitat Gottingen, Germany

Dr. Johannes Gediga PE International Stuttgart, Germany

vn

Tarquinio Magalhaes Faculty of Agronomy and Forestry Eduardo Mondlane University Maputo, Mozambique

Dr. Matthias Schmidt Abteilung Waldwachstum Norwestdeutsche Forstliche Versuchsanstalt Gottingen, Germany

Prof. Almeida A. Sitoe

Associate Professor, Silviculture and Ecology of Tropical Forests Faculty of Agronomy and Forestry Eduardo Mondlane University Maputo, Mozambique

Jonathan Timberlake Editor — Flora Zambesiaca

Herbarium, Library, Art & Archives, Royal Botanic Gardens Kew, England

Dr. Wessel J. Vermeulen SANParks Science Services (Knysna)

South African National Parks (SANParks), South Africa

John de Wet

Facility Management (Sustainability)

University of Stellenbosch

Russell de la Porte, Esther van Vuuren and Hannes Wiese for their language editing work and Elisabete Machado from Springer Publishing for her professional work with us and her patience. We would also like to thank Prof. Klaus von Gadow for his encouragement to publish this book.

2.1.2 Challenges

The construction of statistical biomass models encompasses several challenges. Applicable models have to be accurate, which means precise and unbiased and should provide confidence limits to assess their applicability. Other typical issues are clustered data structures, heteroskedasticity of data and the desired additivity of biomass components. If sufficient data is available nonparametric fc-NN approaches have also shown to provide good results in estimating tree biomass (Fehrmann et al. 2008) but a constant challenge remains the scarcity of biomass data. This frequently leads to models based on a small number of trees from a few stands only. Chave et al. (2004) showed the exponential decline of the error in the estimation of total aboveground biomass for tropical tree species. Their data provides evidence that a minimum of about 50 trees would be required to achieve an error of 10 % in the determination of aboveground biomass; 5 % were achieved with a minimum of about 150 sampled trees. A logical conclusion seems to be to pool all available data on a tree species, to increase sites and tree numbers and achieve a more generic model (e. g. Wirth et al. 2003). This mostly valid option is unfortunately often impaired by the manifold of different ways used to measure biomass (cut­off diameters, drying prescriptions, definition of components etc.), all of which complicates the compilation of coherent data sets.

Biomass procurement per unit of land area can obviously be increase if whole tree harvesting is practised, rather than stem wood harvesting only. However, this relatively small increase in harvestable biomass per hectare comes with a relatively large export of nutrients. Several authors have constructed equations whereby bark, branch, and leaf mass and nutrient contents can be estimated from stem mass or volume, for example Dovey (2009). These tools are useful when calculating the additional nutrient export when the harvesting of additional biomass is considered. Increasingly intensive silviculture and frequent harvesting of ultra-short rotations may result in a net loss of nutrients in many plantations. Recent work in intensively managed short-rotation plantations has shown that fairly large nutrient losses of several elements may occur, which are seldom compensated for by increased inputs (through atmospheric deposition or fertilization). Nutrient losses and gains, as well as the long-term nutritional sustainability of short rotation forestry systems are discussed in detail with some case study data sets in Chap. 10.

Gasification involves the conversion of biomass into a combustible, non­condensable gas mixture by partial oxidation of biomass at high temperature (800-1,300 °C). The resulting gaseous mixtures consist mostly of carbon monoxide (CO), hydrogen (H2) and traces of methane (CH4). Unlike bio-oil, incondensable biogas cannot be stored easily, safely or economically. Therefore, this low heating value gas fuel must be used immediately. Different gasification technologies exist using a broad range of gasifiers, namely: fixed bed gasifiers; including updraft, downdraft and crossdraft gasifiers, fluidised bed gasifiers; including bubbling fluidised bed (BFB), circulating fluidised bed and entrained flow gasifiers, multi-bed gasifiers; including indirect heating, pyrolysis/char, cyclone and plasma gasifiers (Bridgwater 1995; Siedlecki et al. 2011; Gabra et al. 2001; Rutberg et al. 2011). Gasification conditions in various types of gasifiers have been thoroughly reviewed by Pfeifer etal. (2011).

The gasification products of lignocellulose can be applied to various channels of bioenergy production, such as thermal heat generation (steam, hot water), electrical power production by a steam or gas turbine/engine and as synthesis gas (or syngas), which can be used for the production of liquid fuels (biodiesel), hydrogen, methane, mixed alcohols and other chemicals. From raw syngas (the main product of gasification and a by-product of pyrolysis) a series of liquid hydrocarbons can be produced, such as bio-synthetic natural gas (SNG), bio­hydrogen, biomethanol, ethanol, dimethylether and Fischer-Tropsch fuels, which are synthesised via different catalytic processes (Swain et al. 2011; Zinoviev et al. 2010). Fischer-Tropsch (FT) fuels are mainly aliphatic straight chain and branched hydrocarbons and primary alcohols. The product distribution obtained from FT fuels include light hydrocarbon methane (CH4), ethylene (C2H4), ethane (C2H5), LPG (C3-C4), propane (C3), butane (C4), gasoline (C5-Ci2), diesel fuel (Ci3-C22) and wax (C23-C33) (Naik et al. 2010).

C, O and H can be broken down with the release of energy (heat) to form CO2, H2O and other by-products. The calorific value or energy content is a measure for the heat that can be produced and is measured in MJ/kg. The two major breakdown processes are:

C + O! CO2 + 32.8 MJ/kg (C)

2H2 + O2 ! 2H2O + 142.2 MJ/kg (H)

The amount of the released energy depends on the ratio of C, H and O in the biomass used and the MC, as part of the released energy will be consumed for the vaporization of present water. Commonly it is differentiated between gross and net calorific value or higher heating value (HHV) and lower heating value (LHV). The gross CV is the energy content of the sample without any moisture and therefore the maximum value, while the net value is measured in a moist sample, as it would be used for conversion.

Typical gross calorific values for different types of biomass that might be used for energy conversion are given in Table 8.5. It can be seen that the values do not differ much for woody biomass — they are generally between 19 and 20 MJ/kg. This suggests that other factors, such as ash content, are more important when deciding which biomass should be used for energy conversion.

The energy content is typically determined with a bomb calorimeter, which is a closed system in which small temperature increases after combustion in a pressurized oxygen atmosphere can be determined with high sensitivity. The calorific value is defined as the amount of thermal energy per weight unit produced by the total combustion of the sample in MJ/kg.

About 0.5 g of biomass are combusted in a pressurized oxygen atmosphere with a pressure of about 3,000 kPa. The measured temperature increase of the vessel is very small, requiring very sensitive temperature sensors in the calorimeter and good calibration before each measurement. Calibration is generally performed with benzoic acid.