After harvesting, the biomass is commonly stored and air-dried before it is trans­ported and further processed. The rate of drying depends strongly on environmental factors, such as temperature and humidity, the particle size and the stacking method. Whole logs lose their moisture slowly and reach a MC of about 30 % after drying anything between 4 weeks and 6 months. This time can be decreased, if the logs are sheltered and cut into smaller pieces. Chips of a few cm size can reach a MC of about 12 % after a few weeks in sunny, arid conditions (Sturos et al. 1983).

Good ventilation is vital to good drying results. This becomes especially a problem, when the biomass is first comminuted and then dried. If the chips are piled on top of each other, ventilation is inhibited and fungi and bacteria can attack the particles. Biological and chemical degradation caused by bacteria and other organisms lead to an increase of temperature, which can in some cases lead to self­ignition of the entire pile.

Air drying should ideally happen on a flat area without contact to moisture (e. g. on a concrete slab under shelter) and the pile should be turned over on a regular basis.

All these problems can be avoided by oven or kiln drying the biomass, which on the other hand increases the processing costs drastically and sets free carbon dioxide, which affects the energy balance negatively (see Chap. 10).

Institutional support for small scale producers of biofuel could include financing and loans, factors of production such as fertiliser, transport, legal and contract assistance, technology research and development, bargaining support, training and capacity building and marketing and market information. Various actors in the biofuel value chain could provide such support from cooperative small scale producer entities to government and large bioenergy companies (Practical Action Consulting 2009).

Switch grass producers in the United States advocated the formation of coopera­tive organisations as a way of countering corporate dominance in bioenergy projects. It was seen as a way of addressing some of the risks of becoming involved in a new sector. Some producers also saw government involvement as a way of avoiding corporate dominance in bioenergy but expressed reservations about the feasibility of such an approach (Rossi and Hinrichs 2011).

Through co-operatives, small scale producers can collectively provide the “crit­ical mass” that allows them to facilitate the harvesting, transport and marketing of their products. Cash flow regulation to individual members of the cooperative is a further opportunity to be realised by following a collaborative approach (Keyworth 2000).

Co-operatives are an ideal vehicle for emerging business people to establish themselves in a competitive market. Due to the democratic nature of representation, in simple terms one member one vote, it is difficult for a co-operative to be dominated by a minority of members. This can also be a drawback in that it can slow down decision-making, which can be a major disadvantage in competitive markets (Keyworth 2000).

Another type of institutional arrangement is that of outgrower schemes. South African timber companies have achieved success with such outgrower arrangements where they increase the supply of timber to mills by entering into partnership arrangements with small scale growers who have access to land where timber can be grown. The timber companies provide technical inputs (extension advice, seedlings, etc.), capital in the form of soft loans against the proceeds from the sale of the harvested timber and a market for the timber. In return, the grower provides land and labour as the means of growing the trees and undertakes to sell the timber to the processing companies at a market related price (Howard et al. 2005).

It is estimated that there are 24,000 small growers in formal schemes, and between 5,000 and 10,000 independent small growers in South Africa (Chamberlain et al. 2005). One of the more significant economic impacts of outgrower schemes in South Africa is that revenue is circulated within the community when growers employ the labour of both family and community members to work in their planta­tions. Small-scale growing has also created entrepreneurial opportunities for others, which has contributed to growth and diversification of economic opportunities of the broader community. In many cases growers do not have their own means of transporting timber from their land to the mill, creating an opportunity for the development of local transport contracting businesses where community members who have vehicles sell their services these growers (Howard et al. 2005).

Outgrower schemes not only contribute directly to the economies of rural communities but also empower some of the poorest of the poor. The effect of poverty on women and female-headed households is compounded by many cultural norms, for example lack of rights and independence (Lewis et al. 2003). Timber outgrower schemes have, however, provided women with an economic alternative. It is reported that within the Sappi Project Grow outgrower scheme, 80 % of the growers are women (van Loggerenberg 2004).

9.2 Conclusion

Energy from biomass is used by millions of poor people in developing countries as a primary source of energy. It is also becoming increasingly popular in devel­oped countries as a way of mitigating greenhouse gas emissions. Energy pricing programmes in developed countries have enabled consumers to choose renewable energy options while corporate consumers are starting to purchase renewable energy to improve their environmental image and as part of corporate social responsibility programmes (FAO 2005). This developed country focus on renewable energy has led to an increase in demand for bioenergy, often produced in developing countries.

Bioenergy companies that produce biofuels in developing countries often use the arguments of job creation and income generation as a way of justifying large scale biofuel operations. Questions can, however, be raised about the net gain to rural communities from these biofuel plantations. Often these plantations lead to displacement of the rural poor and environmental degradation. While it may seem that rural people are willing to engage in these biofuel production activities it cannot be assumed that these operations have positive social impacts (Van der Horst and Vermeylen 2011).

Several issues should be considered when bioenergy projects are planned in developing countries. These include:

• The potential to improve the sustainability of traditional biomass use (or even to substitute it with more sustainable forms of energy).

• The appropriate level and scale of bioenergy development.

• Definition of land tenure issues and economic opportunities for the rural poor.

• Feedstock choice in relation to land and environmental suitability.

• Sustainable land use planning to reduce conflicts and environmental degradation (Cushion et al. 2010).

Biofuel development driven by agreements between small scale producers and bioenergy companies could be seen as a potential way of ensuring social and environmental benefits, especially when it addresses local development. Carefully controlled development of biofuels that recognises the dangers of rapid unregulated expansion is more likely to result in a bioenergy industry that minimises its social and environmental impact and that ensures equitable benefits sharing (Phalan 2009). Sustainable long term business ventures could be established between small scale producers and bioenergy companies if care is take to define the relationship between the various actors, spread and share risks amongst the actors and define institutional structures. Timber outgrower schemes could serve as an example for such bioenergy business arrangements between small scale producers and bioenergy companies.

As mentioned in the goal and scope definition, the goal of this study was to support public decision-makers of the CWDM to identify the most favourable lignocellulosic bioenergy system. In the original study (Von Doderer 2012), the lignocellulosic bioenergy systems were assessed not only from an environmental perspective, but also from a financial — and socio-economic perspective. The gen­erated performance data was further applied in a multi-criteria decision-making analysis using the analytical hierarchy process, to determine the most sustainable alternative. The study concludes that lignocellulosic bioenergy system 26 is most favourable, showing a strong financial-economic viability, a high socio-economic potential and a relatively low environmental impact.

Generally, the main driver for each criterion, whether it be of an environmental, financial-economic or socio-economic nature, is the overall conversion efficiency (OCE) of the biomass upgrading and bioenergy conversion system. The greater the OCE, the less biomass is required, resulting in fewer upstream activities and less land required for biomass production. In terms of the environmental impact of the LBSs, a greater OCE is desired, resulting in lower total emissions and, therefore, in lower impacts for each life-cycle impact category. Similarly, for the financial — economic viability of the LBSs, a greater OCE results in lower costs, both in terms of capital and operating expenditure, as well as in higher internal rates of return on the capital invested.

Another important driver is the efficiency of the harvesting system, which has an effect similar to the OCE. The greater the degree of mechanisation and automation, the lower the environmental impact and the higher the cost-effectiveness and profitability.

11.4 Conclusions

As shown in this Chapter, the life-cycle assessment (LCA) approach, originally developed as an environmental assessment tool, is a very useful tool to provide environmental performance information in a structured and comprehensive way. It can be understood intuitively as a tool to capture the environmental impacts along the entire life-cycle of a product or a service (from its ‘cradle’ to its ‘grave’). The LCA method is structured in four phases, namely (1) goal and scope definition, (2) life-cycle inventory (LCI) analysis, (3) life-cycle impact assessment (LCIA), and (4) interpretation of the results.

The first phase sets the foundation of an LCA, by defining goal and scope and by specifying functional unit and the different dimensions of the system boundaries. All relevant inputs and outputs of the considered system are brought together during the second phase, the life-cycle inventory. In the third phase, all potential environmental impacts associated with the inputs and outputs are evaluated, by translating the environmental loads into impacts, which makes the results more environmentally relevant, comprehensible and easier to communicate. Several LCIA methods exist, and there is not always an obvious choice between them. Common areas of protection covered by LCAs are human health, natural environment, natural resources, and to some extent, the man-made environment. However, other environmental concerns, such as impact on biodiversity, water balance or land-use change, which are more difficult to specify, are not included in the LCA method.

Due to its systematic and transparent approach, LCA is well suited to being extended to measure a product’s financial and social aspects along with its life­cycle. There is broad agreement in the scientific community that LCA is one of the most effective methods for evaluating the environmental burdens associated with biofuel and bioenergy production. This was confirmed in the second section of this chapter, which entails some of the results of a recent study aimed at determining the most sustainable lignocellulosic bioenergy system. Along the lines of the LCA framework, important aspects for assessing the environmental impacts of bioenergy systems are discussed. Furthermore, the from translating the environmental loads of 37 lignocellulosic bioenergy systems results in terms of their respective global warming potential were presented.

When comparing various bioenergy pathways, it can be further concluded that the overall conversion efficiency (OCE) of the biomass upgrading and bioenergy conversion system is one of the main drivers affecting the environmental perfor­mance of the assessed systems. The greater the OCE, the less biomass is required, resulting in fewer upstream activities and less land required for biomass production. In terms of the environmental impact of the LBSs, a greater OCE is desired, resulting in lower total emissions and, therefore, in lower impacts for each life-cycle impact category.

The efficiency of the harvesting system has an effect similar to the OCE. The results of this study show, that the greater the degree of mechanisation and automation, the lower the environmental impact.

[1]

[2]Code for additive estimation of biomass components for the freely available statistical language

R (R Core Team 2012) and a set of example data can be downloaded from http://www. springer. com/life+sciences/forestry/book/978- 94- 007-7447-6

As stated earlier sampling of foliage and branch biomass is usually done as a regression sampling process, because foliage and branches should be separated

for biomass, nutrient/ash content, and eco-physiological calculations. However, manually separating a tree’s foliage from the twigs is a task that can only be done for small trees with reasonable effort. Therefore a regression sampling is employed to estimate branch and foliage biomass from branch diameter. Consequently, all branches of the tree are measured in diameter for upscaling later on. A sub-sample is then cut and sampled in detail in the lab or field lab. In this context it is relevant whether the branch diameters are measured perpendicularly to the main stem axis or with the axis, since the measurement perpendicular to the stem axis usually yields smaller values. The difference in branch diameter for 14-year-old Pinus radiata was about 2.0 % (estimated from on 245 branches of 11 trees; Seifert, unpublished). It is therefore important that the measurements of the sample branches and the total branches are taken consistently in the same direction. Depth of branches in the crown, defined as the distance of the branch insertion from the tip, provides an additional variable that can improve the estimation of the proportions of branchwood and foliage. Thus, the position along the stem could be a second variable to be determined in the field. After separating the foliage from the branches and drying it, a regression model is established to estimate foliage and branch biomass from branch diameter or branch circumference. A possible method to limit branch sampling is to establish the branch biomass functions based on a data set where all sample branch data of one plot are pooled. An example is presented in Fig. 3.5. This way a more robust function can be established if several trees per plot are sampled. The clustered data structure with the inherent inter — and intra-tree variability can be taken into account with mixed models (Pearce et al. 2010).

Based on this methods a dry biomass for the stem, the branches and the foliage can be obtained.

The interactive effects of tree improvement, site-taxon matching, stocking, and cultural practices has been tested across five site types of different SI’s on the eastern seaboard of South Africa (Boreham and Pallett 2007; du Toit et al. 2010). As a departure point, a control treatment was selected that represented many short — rotation pulpwood production stands in warm climates: A species that was well adapted to each specific site (but not the very best match possible, i. e. the second best species on that particular site), which had not undergone genetic improvement, planted at a stocking of 1,111 stems/ha with no fertilization at planting and an intermediate level of weed control. The average productivity in this experimental series could be increased by 46 % above the control treatment at 5 years of age, by using genetically improved planting stock, the best site-taxon matching, a stocking of 1,667 stems/ha and intensive weed control plus fertilization at establishment. The most important finding of this study was that, although there were no significant interactions between major factors across all sites, the response to individual factors (genetics, site-species matching, stand density, fertilization and weed control) were additive. It follows each element of the intensive silviculture system contributes substantially to the overall gain in productivity, and that all elements should be implemented at the higher (or more intensive) level to realise the gain that had been achieved. Bio-energy production systems should be planned to integrate all the above elements of intensive silviculture into the production system.

The various thermochemical conversion technologies that may be applied to processing of lignocellulosic biomass are presented in Fig. 7.1.

7.3.1 Combustion

The production of thermal heat and electricity from lignocellulose, as well as the production of intermediate bioenergy products such as pellets, charcoal, gases and liquid fuels derived from lignocellulose, all proceed via combustion. Combustion processes combine three elements: a feedstock as fuel, air as oxidant of the feedstock and the application of a specifically required temperature from a heat source. The carbon and hydrogen components of a feedstock are totally or partially oxidized and converted into heat. Normally, combustion precedes pyrolysis. Burning of woody material proceeds in four steps: the temperature of the starting material is increased by application of heat, which leads to the evaporation of volatile species and char formation, followed by combustion of volatiles species (primary combustion) and finally the combustion of char (Gonzalez et al. 2005).

The production of steam in a boiler, facilitated by energy derived from com­bustion, is used either directly as thermal heat or to drive steam turbines for

I Liquefaction:

Catalytic or

1 non-catalytic Sub/near/ Supercritical fluids

Fig. 7.1 Overview of thermochemical processes for conversion of woody biomass into bioenergy products

electricity production, with high boiler pressures combined with multistage turbines providing the highest overall process efficiency. Similarly, the gases produced through gasification, anaerobic digestion and pyrolysis can be combusted directly in gas turbines or gas engines, with the biomass integrated gasifier/combined cycle (BIG/CC) systems delivering significantly higher conversion efficiencies than the boiler-steam turbine process (Laser et al. 2009). The recovery of waste heat from boilers, gas engines/turbines, steam turbines and other combustion applications can provide a useful form of low quality heat (e. g. warm water), which increases conversion efficiency.

The heat energy and steam delivered by gasification systems can be used for heating purposes and electrical power generation, respectively. Known and applied for many decades, many biomass combustion technologies can be found on the market and mainly categorized in two types, fixed-bed (Water-cooled vibrating grate (VG)) and fluidised-bed systems (Bubbling fluidised bed combustion (BFBC), Circulating fluidised bed combustion (CFBC)). Fluidised-bed boilers present a series of advantages such as limited emissions and relatively complete combustion which improves overall efficiency and makes it suitable for processing of a wide range of feedstocks (Wright et al. 2010; IEA ETSAP 2010; Demirbas 2005).

In addition to cellulose, hemicelluloses and lignin, wood cells also contain extra­neous substances. Many of these substances are extractable with neutral solvents and are generally referred to as extractives. Extractives (proteins, fats, fatty acids, terpenes, resins, phenols and alcohol, etc.) can represent between 4 and 10 % of lignocelluloses (Fengel and Wegener 2003). There is a considerable variation in the type, distribution and amount of extractives between tree species and even within species. Sugars and other sap-soluble constituents, such as starch are found in the cell lumens of parenchyma cells. Phenolic materials are deposited in the heartwood to protect the wood from insect, fungal or bacterial attack (Harju et al. 2003). Water repellent fats are found in the parenchyma cells, especially in the ray parenchyma, whereas resins are secreted by epithelial cells and tend to form resin ducts. Some extractives are utilized commercially such as vegetable tannins, turpentine and tall oil, fatty acids etc.

Resins have a high CV of >30 MJ/kg (Novaes et al. 2010), which explains why softwoods generally have a higher CV than hardwoods and also leads to a fairly high CV value of bark.

Variation in extractives within the stem is mostly between sap — and heartwood, except for resins. The resin content in softwoods is reported to be highest near the pith and at the butt of the tree, decreasing upward and towards the outside (Fengel and Wegener 2003). The resin content is significantly lower in the sapwood than in the heartwood and slightly lower in earlywood than latewood. Many heartwood extractives, on the other hand, increase from the pith to the outer heartwood boundary (Panshin and De Zeeuw 1980) (Table 8.4).

Management of the ecological impacts at the site level has the goal to ensure sustainable productivity over the long term. Site-level impacts such as nutrient depletion, soil loss or degradation, pest and disease outbreaks or uncontrolled fires are likely to impact negatively on the sustainable production capacity of the system. Careful monitoring of intensively managed systems is thus needed, along with strategies to mitigate against negative site impacts that may take place. It is in this regard that agro-forestry systems and mixed cropping systems with nitrogen fixing trees can contribute to mitigate against nutrient depletion. Silvicultural systems have to be so designed to offer a degree of buffer against biotic or abiotic risks. The discussion on mitigation strategies and ecological buffering is supported by information from case studies in plantation and agro-forestry systems.

Maps and the electronic successors of maps, namely Geographic Information Systems (GIS), have been used for ages to describe the lay of the land. Planimetry on maps and area calculation in GIS are used to estimate extent of an area of interest, for example a stand of trees. If no map is available, a chain and compass (Fig. 2.1) or Global Navigation Satellite System (GNSS) receiver can be used to determine the boundary of an area of interest. Most modern GNSS receivers include a function to estimate the area described by a set of points (coordinates).

Chain distances and compass directions can be entered in a GIS or drawn on scale, which allow for areas to be estimated. Dimensions can be drawn on a scaled diagram and the area of the resulting polygon determined by subdividing it in a series of regular figures, for example triangles (Fig. 2.1 A, B, C). Calculating area from coordinates can be done via many methods. One such formula is provided below:

Area = 2 {(Y1X2 C Y2X3 ••• C YnXi) — (Xi Y2 C X2Y3 •

where

Xj is the x coordinate of vertex 1 Yn is the y coordinate of the nth vertex.

Area is a by-product of the mapping procedure (GIS) or from image processing, e. g., classification, and is discussed again in the section on Remote Sensing methods.

Mopane woodlands, with Colophospermum mopane as the dominant tree species, are mostly confined to the lower lying areas on heavier textured soils in the wide, flat valley bottoms of lower Okavango, Cunene, Zambezi, Shire, Limpopo and Luanga in southern Angola, northern Namibia, northern Botswana, Zimbabwe, northern South Africa, southern Zambia, southern Malawi and south central Mozambique (Timberlake et al. 2010). It occurs at an elevation of 200-1,200 m although normally it ranges between 300 and 900 m. The rainfall in these areas ranges from 400 to 700 mm per year, although the species itself may be found in drier areas in north­western Namibia (Timberlake et al. 2010). Sometimes the woodland forms pure stands of Colophospermum mopane. Mopane woodland can be 10-20 m tall, with stands up to 25 m, but in some areas scrub mopane of 2-3 m tall covers extensive areas, in mosaic with taller stands (Geldenhuys and Golding 2008). It is capable of growing under a range of climatic and edaphic conditions but is restricted in distribution by fires and competition from other species (Geldenhuys and Golding 2008). Mopane has a shallow root system with a dense concentration of fine roots in the top soil (Fanshawe 1971). Some scattered Munga woodland elements occur in places represented chiefly by Acacia nigrescens, Adansonia digitata, Combretum imberbe, Kirkia acuminata and Lannea stuhlmannii. The canopy dominants are Colophospermum mopane, Acacia luedertzii, Acacia nigrescens, Adansonia dig — itata, Afzelia quanzensis, Albizia harveyi, Albizia amara, Brachystegia boehmii,

Combretum imberbe, Hyphaene ventricosa, Kirkia acuminata, Lannea stulhmannii, Philenoptera violacea, Pterocarpus angolensis, Sclerocarya birrea and Strychnos potatorum.