5.1 Past efforts to improve wood energy data in the region
5.2 Approach to building a wood energy data base
5.3 Types of local wood energy surveys
5.4 Linking data base development with programme implementation
5.5 Integrating local studies for a national level wood energy analysis
5.6 Building institutional capabilities
5.7 The need for external assistance and support
Policy formulation and programme implementation for sustainable wood development require accurate, complete and up-to-date wood energy databases, however, data weaknesses and gaps still exist, as discussed in Section 2. Improving databases requires capacity building activities at national and local levels, and even at regional/international levels.
Many data improvements that are mentioned in Section 2 were the results of the RWEDP capacity building efforts in the countries that took place from 1994 to 2002.
Training courses – All the ten countries participated in regional training courses on wood energy data and planning conducted by RWEDP. These training activities covered methodologies for wood energy data collection and organization, techniques for wood energy assessment, and approaches to integrating wood in energy planning. Participants were planning staff of energy and forestry agencies as well as agriculture, economic planning and environment bodies.
Seven countries (Cambodia, Lao PDR, Nepal, Philippines, Sri Lanka, Thailand and Viet Nam) conducted follow-up national training courses. Some of these training courses were translated in to local languages, as few national participants understand English.
Case Studies – Recognizing the limitations of training courses, seven countries conducted pilot case studies to provide on-the-job training for national wood/biomass energy planning experts. The case study activities included limited local-level primary data collection, compilation and organization of secondary macro-level data, energy assessment and planning using the LEAP model43, and policy formulation exercises.
Much of the data and information submitted in this regional study were generated and obtained from these case studies. Six of the ten national consultants (Cambodia, Lao PDR, Nepal, Sri Lanka, Thailand and Viet Nam) that contributed to this regional study were participants of the case studies, and some of them were the case study leaders themselves.
The pilot studies, which were scheduled to last for a year, extended to as much as two years in some countries. But even with this extension, the countries were not able to complete the case studies. There were many problems and constraints encountered as discussed in the following section. Nevertheless, the case studies remain relevant in reviving efforts to strengthen wood energy databases in the countries, as called for in this regional study.
The following were the organizational and institutional problems that limited efforts to develop and strengthen wood energy databases in the countries:
Inadequate planning staff – Any effort to develop/improve wood energy databases became an additional burden to planning units of both energy and forestry agencies (in some countries, this included agriculture ministries). There were additional tasks (e.g. wood energy data collection and processing, data assessment, and modelling studies using yet-to-be-learned computerised planning tools such as LEAP) to be performed. Most energy and forestry planning units did not have adequate trained experts that could immediately handle these additional tasks. Even if training could have been provided, many units also did not have enough staff ready to participate in training activities.
High staff turnover – The problem of inadequate planning staff was further compounded by the high rate of staff turnover. Many staff who were trained in wood energy collection and planning were transferred to other units that were considered more important (e.g. solar/wind, rural electrification, forest management). Others left for graduate studies abroad or resigned from government service. Apparently, this was a constraint faced by almost all countries in almost all sectors and a problem that can be difficult to address.
Wood energy was not a priority to higher policy makers – Higher policy makers generally give priority to sub-sectors where there were potentially huge projects and funding involved, and/or big revenues were expected and/or were expected to have significant economic and political impacts. Thus, priority was given to visible and higher budgeted energy projects such hydropower plants, rural electrification, or solar/wind energy projects; or industrial tree plantations or commercial logging in the forestry sector. Local experts, particularly the best ones, were re-deployed to handle such activities, even at the expense of wood energy activities, as wood energy activities were apparently considered small and insignificant in terms of possible investments, potential revenues and/or economic and political impacts.
Language-barrier – Wood energy data collection, assessment, and planning concepts are complex. Reading technical English manuals was difficult for those who were not proficient in the language, as was the case of local experts in most of the countries. Concepts needed to be orally explained, or demonstrated, such as by computer exercises, using the “localized” version of the English language. As such, direct supervision was needed to conduct capacity building activities. The other option was to provide well-translated manuals and guidebooks that include case studies and exercises. Such technical support ccould only be provided by regional development agencies that were also faced with resource and time constraints.
Inadequate external support – Capacity building required continued external assistance, which was woefully inadequate. External support needed was not only for local training and regular technical advice. Financial support was needed for conducting surveys and acquisition of computer software and hardware. These were tasks expected of regional/international development agencies, but, as mentioned earlier, these also faced resource and time constraints.
Lack of capability for local-based studies – As wood energy situations vary even in small and medium-size countries (e.g. Philippines, Cambodia, Nepal, Thailand, and Viet Nam), local-level data collection and assessment activities were needed. Planning and policy formulation needed to be systematically decentralized and conducted at local levels too and then integrated for macro-level analysis. This required institutional and organizational support at local levels, which most countries did not have. Developing local capacity requires innovative approaches to institutional building so that this will not lead to unnecessary expansion of the energy and forestry planning bureaucracy.
On the basis of the country reports and additional information from previous RWEDP studies, the situation of wood energy data in the developing countries of South Asia and Southeast Asia (including China) can be classified into four categories. The first category includes China and India, the two biggest countries in the region. These two countries currently implement national-scale government programmes addressing household energy. The targets of household energy programmes include improving woodfuels use for cooking and woodfuels plantation programmes. China and India have the most experience and expertise among the participating countries.
The vastness of the two countries presents opportunities for showcasing different types of wood energy situations and therefore different intervention approaches. Also, they have different social, cultural, political, institutional, and economic environments. Together, they can provide various models of interventions that other countries can emulate. They also have huge populations and therefore the potential impacts of interventions can be significant.
Both countries have capable national-level agencies and their capacities extend down to local levels (capacity refers to having adequate technical expertise and a sufficient number of personnel). This is particularly true for China, where the bureaucratic structure of the Ministry of Agriculture for its Integrated Rural Energy Development Program (that included improved cook stoves and woodfuels plantation programmes) extends down to village and commune levels. In China, activities are dominated by government agencies, primarily the Ministry of Agriculture through its Provincial Rural Energy Offices. India on the other hand has the Ministry of Non-Conventional Energy Sources, which has offices at state level. The government spearheads programmes, but significant activities are contributed also by NGOs and by the private sector.
In both countries, information to define situations, even local situations, can be obtained from existing records and past surveys, though they need updating and expansion to include some of the wood energy data gaps previously mentioned. Language can be a barrier in China; thus translation is necessary for externally initiated activities for strengthening capabilities, particularly at local levels. Since expertise and adequate institutional structures can be found in both countries, institutional strengthening activities may readily be formulated and initiated. Funding appears to be the key constraint to expanding capacities in these two countries.
The second category includes countries that have defined a national energy/forestry policy relating to wood or household energy, and/or have initiated related projects/activities that are not national in scope. (In many countries, wood energy activities are closely intertwined with household energy programmes). At least there is a government body responsible for household or wood energy identified. In such countries there might also be local projects/activities initiated independently by NGOs and academic institutions. Thus, several locally targeted interventions may be ongoing, but they are scattered and independent from each other.
Inadequate capabilities at both the national and local levels are major constraints, leading to inadequate information to assess situations and to formulate interventions. Also, national programmes may have been defined but are grossly under-budgeted and under-manned.
Resources are needed to develop more local expertise to conduct regular updating of data, formulate policies and oversee programme implementation. The resources could be substantial as they are for longer-term interventions that aim to strengthen and institutionalize such capabilities in the countries. Language is also a barrier in conducting interventions in many of these countries, since local expertise has to be developed from the mostly non-English speaking staff. Countries in this category include Nepal, Philippines, Thailand, and Viet Nam.
The third category includes countries that do not have any policy or national programmes, but officials recognize the importance of wood energy and are willing to support initiatives in this area. Capacity is definitely lacking (even within the organizations already involved in interventions) and so is data and information. One may find in these countries, a few local interventions undertaken by NGOs or academic institutions.
Resources are needed for initial capacity building activities such as awareness building, introductory training courses and assessment of current policies, programmes and institutions, in addition to resources needed for long-term interventions for institutional capacity-building activities. Countries in this category include Bangladesh, Bhutan, Cambodia, Indonesia, Lao PDR, Myanmar, Pakistan, and Sri Lanka.
The fourth category includes countries where wood energy is not seen as important, either as a problem or as an opportunity. Policy makers in these countries believe that their populations can take care of themselves as the family incomes are at levels high enough to allow market forces to influence substitution of woodfuels use (even if petroleum fuels are subsidized and therefore free market forces are not really at work here). They foresee that, eventually, the majority of their population will shift to petroleum fuels and even electricity to satisfy all energy needs. They do not seem to see the potential of commercial and industrial applications of modern woodfuels technologies. They also fail to see the environmental significance of encouraging continued use of woodfuels.
Significant use of woodfuels in developing countries will continue in the foreseeable future. Woodfuels producers and traders will continue with their business of selling and marketing woodfuels in spite of the continued presence of laws and legislation that make their activities illegal in many developing countries. Users, including households, institutions, enterprises and industries – in both rural and urban areas – will continue to buy or collect woodfuels as long as woodfuels are perceived to have relative advantages in terms of cost and availability. These facts should stimulate developing countries to improve understanding, re-think wood energy and give proper attention to policies and programmes for sustainable wood energy development.
Current wood energy data have gaps and limitations. Data are focused on consumption in the household sector and consist of outdated primary data or extrapolated values based on outdated data. Data to analyse consumption trends and fuel shifting (e.g. woodfuels consumption by income, location, urbanization, etc.) are scarce. Data on wood resources, woodfuels supply systems, trade, transportation and technologies are incomplete or totally lacking. This makes studies of the impacts of wood production on the economy and environment, particularly deforestation, unrealistic (unfortunately, even with data limitations, many countries still make generalized and erroneous conclusions, such as linking deforestation to woodfuels use).
Improving wood energy information means improving techniques for data collection, and using such techniques to improve data collection. But this should be an “action-oriented data collection activity”, i.e. it should result in sustainable wood energy development policies and programmes. Data improvement should be integrated with policy formulation, programme planning and implementation, with the aim being to strengthen overall capacity for wood energy development. The process is presented in summary form below and the details are discussed in the following pages.
An action-oriented approach to building a wood energy data base |
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1. Collect secondary data. 2. Define a framework for organizing a wood energy data base and design a system for managing (input-retrieval) wood energy data. 3. Develop a wood energy typology. 4. Define and identify representative areas for local-level studies (provincial- and /or town-village areas). 5. Implement studies for representative local-level areas 6. Analyse results of representative local-level studies (i.e. wood energy assessment and projection studies), formulate local policies, and plan local programmes. 7. Extrapolate wood energy assessment and projection studies for other local areas using results of representative local studies. 8. Integrate local studies for national-level wood energy assessment and projection studies. 9. Formulate national-level policies and planning of national-level programmes. 10. Identify follow-up local-level studies. |
An important aspect of understanding wood energy systems is the recognition that the situations, problems, solutions and opportunities for them vary, not only among countries, but also within countries. It is unwise to make generalisations, except in defining the set of factors that determines such situations, problems, solutions and opportunities. These factors include:
• biomass resource potential of the area;
• character of local economy;
• socio-economic condition of the area;
• factors that produce significant wood fuel exports; and
• major forms of structural reforms.
In analyzing the various types of wood energy situations found in a country, a set of criteria based on the above mentioned factors might be used to define and characterize each type of situation. Such criteria may include the following:
• agro-ecological setting;
• socio-economic conditions;
• demographics and local customs and traditions; and
• laws and legislation.
Based on the criteria, a wood energy typology system may be established. An example of a wood energy typology system developed on the basis of the above-mentioned criteria is given below:
Typology of Wood energy Situations44
- high woody biomass/low population density; - low woody biomass/low population density: mountain areas; - low woody biomass/low population density: semi-arid and arid areas; - urban areas; and - transition zones (e.g. refugee camps). |
Collecting data on all aspects of wood energy systems involves collecting data on consumption, resources, production, transportation, trade, technologies and related socio-economic factors. Since data collection is time consuming and expensive when carried out at national-level, locally based case studies in selected areas, representative of the various types of wood energy situation found in a country may be conducted instead.
The wood energy typology system discussed above should provide a systematic framework for conducting representative case studies. A preliminary typology can be developed on the basis of the available secondary data. Secondary data are available from previous studies such as the country reports submitted for this study, or from the RWEDP wood energy database (see www.rwedp.org). Representative areas for case studies may be identified from this typology. The number of representative areas will depend on the variety of situations identified by the typology and the resources and the time available for the case studies. For example, in the typology of wood energy situations given above, at least six local-level case studies should be conducted if sufficient resources and time are available.
As these are local studies, only small areas are involved (e.g. provinces or town-village areas – see the following section). Budgets should be more affordable and implementation more manageable. The few experts that a country initially has, should have time to concentrate on these few representative local studies.
After a wood energy typology system has been established, the type and size of areas where case studies are to be conducted have to be defined. The most convenient way to do this is to follow the administrative division system of the country. Areas can be by administrative regions, by provinces (or states or districts), or even by towns/villages.
In most countries, administrative regions may be too geographically large and thus the wood energy situations within them will vary significantly. Provinces (or states) appear ideal for many small and medium-size countries like Cambodia, Lao PDR, Nepal, Philippines, Sri Lanka, Thailand, and Viet Nam, particularly if the wood energy situation in each province is uniform throughout. Representative provincial-level case studies will be undertaken for each type of situation identified under the wood energy typology. The results of the case studies will then be extrapolated for other similarly situated provinces. All the results will be integrated or aggregated for a national level analysis of the wood energy situation.
If the majority of the provinces appears to have a heterogeneous wood energy situation, then the case studies may have to be done at town-village area levels (i.e. an area comprising a town centre and its surrounding contiguous rural areas). Doing town-village area-level studies tends to be more attractive as studies may be more manageable and affordable (and so too the programmes and interventions that may be defined later).
However, extrapolating the results of case studies at town-village-levels for other similar areas and integrating all these results for a national level analysis may become unwieldy. An option is to conduct an aggregation or integration analysis at two levels.
Several representative provinces will be chosen first, then representative town-village areas in these provinces will be identified for case studies. The results of the town-village case studies will then be extrapolated for other town-village areas in the representative provinces. The results of the town-village area-level case studies and extrapolated analyses will be aggregated for a provincial-level wood energy analysis of the representative provinces.
The analyses of representative provinces will then be extrapolated for similarly situated provinces. All provincial level analyses will then be integrated for a national-level wood energy analysis. (For China and India, three levels of analysis may be needed: by provinces or states; by counties or districts; and by town-village areas).
The size and number of study areas will also be influenced by the following logistical factors:
§ the type of interventions the study is aiming at;
§ availability of data from previous studies;
§ ease of transport within the area (for conducting field surveys);
§ budget and time allotment for the survey; and
§ available expertise, including availability of local enumerators.
Wood energy data collected from the surveys need appropriate software and hardware for proper storage and management. This means proper hardware facilities for data storage and software systems for data input, retrieval and organization. As data collection starts with local surveys in a few representative areas, desktop computers located in energy and forestry planning units, at both national and local offices, would suffice at the beginning. Generalized data storage software (e.g. MS Excel or MS Access) may be used initially, but as more specialised data are gathered and the volume of data increases, expert advice may be needed to design more appropriate data storage and management software and hardware. An example of a specially designed database for wood energy is the RWEDP database (see www.rwedp.org). Countries may use WISDOM (Woodfuels Integrated Supply/Demand Overview Mapping), a “GIS methodological tool designed to cope with the spatial heterogeneity of woodfuels supply and demand patterns” developed with the assistance of FAO-FD.45 They may also adopt UWET (Unified Wood Energy Terminology) and WEIS (Wood Energy Information System), developed by FAO-FD for organizing the wood energy data they have collected.46
There are three types of surveys that have to be conducted for a comprehensive study of local wood energy situations. As these are local surveys involving smaller areas, they should be relatively manageable and affordable, even if the surveys seem comprehensive and complex.
.
Local wood energy studies may start with “woodfuels flow surveys”. These are studies directed at urban centers to characterize urban woodfuels markets and their rural linkages. The study covers the marketing, trading and distribution of woodfuels, including the conversion of woodfuels. The study should also identify the sources of commercial woodfuels and their users, who would then be the target of the subsequent surveys. 47
The data collection techniques that are used are similar to RRA (rapid rural assessment) techniques. Examples of such studies can be found in the RWEDP web site (www.rwedp.org). Woodfuels flow studies are basically local studies using an area-based approach requiring a small multi-disciplinary team of experts. Thus in spite of the abundance and complexity of data and information that have to be collected and analysed, the study should be manageable. This study should be led by forestry agencies, particularly those units dealing with wood products.48
The next study should consist of site-specific woodfuels supply surveys. These include surveys of areas identified by the flow studies as sources of commercial woodfuels and the areas identified in energy consumption surveys as sources of woodfuels gathered for own use.
Woodfuels supply surveys consist of wood resource assessments and wood production studies. Wood resource assessments involve characterising the types of tree/woody biomass production systems (i.e. natural forests, plantation forests, agroforestry, croplands, grasslands, woodlots, etc.) in the identified supply areas. They also involve conducting wood balance studies (see Section 3.2) that assess the woody biomass production potential of the areas, less the estimated future non-fuel demand for woody biomass. These studies should consider the impact of changes in land use as this is a key parameter in estimating resource potential. These studies should be led by forestry agencies, especially those involved in forest resource assessments activities.
Other sources of woodfuels such as wood waste from logging operations, wood processing and wood products industries may also appear to be significant. The mechanisms by which wood wastes are generated should be understood so that the potential supply from these sources is also accounted for in the resource assessment studies.
Wood production studies involve the collection of historical information on the actual production of woodfuels from the areas identified. This is more difficult as it involves collecting past information and records are rarely kept by those involved in this activity. This information will serve as a counter-check to the consumption studies and identify the gaps in woodfuels supply data.
Woodfuels supply studies may need to be expanded into biofuels supply studies, if other types of biofuels are available in the area, and particularly if the other biofuels (i.e. crop wastes and animal dung) are already being used as substitutes for woodfuels.
Complementing the two surveys are sectoral energy consumption surveys. The different sectors to be studied include households (rural and urban), industries (traditional and modern industries), and other enterprises including commercial and service establishments, which could either be in the formal (listed) or informal (unlisted) sector.
As these surveys are required to generate data for energy demand projection studies, they should include collection of information on factors that affect energy consumption, such as consumption of alternative fuels and socio-economic information about the areas under study. These surveys are not just woodfuels consumption surveys, but overall energy consumption surveys. It is better to integrate woodfuels consumption studies with overall energy consumption studies and as such, these studies should be led by energy agencies in cooperation with statistics offices.
Consumption energy surveys should also collect data on woodfuels sources, not only to validate the results of flow studies, but also, more importantly, to identify non-commercial sources of woodfuels, i.e. sources of woodfuels gathered for own use. This is most relevant in households and enterprises in rural areas. The results will be used in the woodfuels supply surveys.
There are several references available, which can be used in designing methodologies for formal structured surveys, particularly for the household sector. These include the following:
1. Guidelines for Wood Energy Surveys, (to be published in 2003 by FAO-FD).
2. Gerald Leach and Marcia Owen. 1987. Household Energy Handbook: An Interim Guide and Reference Manual. World Bank Technical Paper No. 67, Washington.
3. FAO. 1983. Wood Fuel Surveys. Forestry for Local Community Development Programme, Rome. See (http://www.fao.org/docrep/Q1085e/Q1085e00.htm)
4. FAO. 2000. Basics of Wood Energy Planning. RWEDP Report No. 64, Bangkok. See (http://www.rwedp.org/rm64.html).
Consumption surveys for the informal sector are more difficult to carry out as the respondents are unlisted (and some are probably operating illegally). There are very few references available for these studies, and techniques are just evolving (the Philippine country report includes a discussion of a general approach).
Preliminary data on technologies for the conversion of wood to its various energy forms (e.g. charcoal, producer gas, alcohol, hydrogen, etc), and its utilization (improved stoves, kilns, boilers, furnaces) may be obtained through literature research. Developing countries today (except India and China) have very few research activities on wood energy technologies. The Internet is a very useful source of data and information. The same is true for data on health and environmental (particularly climate change) impacts of wood energy. Nevertheless, once technologies are to be used in the country, country-specific or even local-specific data will have to be obtained through pilot or demonstration projects.
To be more interesting and relevant, wood energy surveys or wood energy data collection should be linked with programme implementation. The objective of the surveys or data collection should not be limited to gathering information to inform planners about the wood energy situation. It should be to use such data to identify problems and opportunities, formulate policies, and most importantly, implement programmes to solve problems and exploit the opportunities.
Wood energy surveys are inputs to wood energy assessments and wood energy projection studies. Wood energy assessments involve analysis of the data collected to characterize the wood energy supply-demand situation of the area. The assessments should result in the identification of current problems and opportunities for wood energy development. Wood energy projection studies involve analysis of historical data using modelling tools to characterize the future situation of wood energy demand and supply. The studies should provide future scenario options for wood energy and inputs for wood energy policy analyses and planning and formulation programmes.
With local-level studies, budget and other resources for implementation of programmes that are going to be defined from the results of the wood energy surveys may be modest and affordable to national governments and international donors. Thus, any efforts in wood energy database development should be integrated with the implementation of programmes.
As stated earlier, investing not just in database development, but also in wood energy programme implementation may be an attractive approach for governments and donor agencies. This approach makes data collection a data base development effort that results in interventions that improve the local energy situation and the lives of people, rather than a mere academic exercise.
This presumes that enough preliminary and secondary data are available to draw up credible and interesting initial proposals for such an approach. Fortunately, this is the case for most of the countries covered by this regional study.
Through this approach, a wood energy development process may be established in countries consisting of: wood energy assessment studies; projection studies; policy analysis and formulation; programme planning; and programme implementation and monitoring. All these “process elements” provide inputs to data collection activities and provide a mechanism for regularly updating wood energy databases.
As previously discussed, this process can start with a handful of local case studies. The number of case studies depends on how varied is the wood energy situation in the country (i.e. types of local wood energy situation), available secondary data, and the resources needed for the studies (that can be raised from the local budget and external donor agencies). With the case studies resulting in better data, improved policies and programmes, and effective interventions, more local studies that integrate data base development with programme formulation and implementation can be identified and implemented.
This process may complement expensive and time-consuming wood energy surveys, and lead to reduced use of such surveys. In the end, these should result to the institutionalisation of a dynamic wood energy database that provides inputs to (and is given inputs in return by) an increasing number of local wood energy programmes that slowly build up to a national wood energy programme.
Integrating local wood energy studies for a national level study involves several steps. After representative local case studies are completed, similar local level studies are conducted in other areas using desk analysis. Data resulting from the case studies are used to extrapolate the needed data and to conduct energy analysis for other areas. The resulting analyses for the different local areas are then integrated or aggregated to make the national level analysis.
As discussed previously, for small and medium-size countries that are divided into provinces with generally heterogeneous wood energy situations, local-level case studies may be done at town-village areas. Then, using the results of the case studies, desk analyses are done for other town-village areas. A first level integration or aggregation can be done at the provincial level, where local case studies and the desk analyses of town-village areas are integrated to obtain a provincial level analysis.
As local-level studies for town-village areas are not done for all provinces, desk analyses are also used to conduct provincial level analyses for provinces where local-level case studies were not conducted. Again, data generated from the local level case studies will be used for the provincial level energy studies using desk analysis. The second level of integration or aggregation then is the integration or aggregation of different provincial level analyses into a national level analysis.
Tools are available for the different analyses discussed above. Extrapolation techniques can be used to apply the results of case studies in conducting parallel desk analyses. The LEAP model provides a tool for conducting such integration or aggregation analysis. WISDOM, a wood energy-planning tool developed by FAO-FD will be useful in organizing, presenting and conducting area-based analyses of the results of the local case studies and desk analyses.
Capabilities for wood energy database development, policy formulation and programme planning will have to be strengthened at both the national and local levels. At the national level, the expertise needed is in data extrapolation to generate secondary data and to conduct desk analyses for various levels of studies (i.e. national, provincial, town-village areas), and the integration of local level analyses into a macro or national-level analysis. For policy formulation and programme planning, the expertise needed is in the integration of wood energy issues in the formulation of national and sectoral development priorities and in the allocation of public investment and resources.
At local levels, the expertise needed is in conducting the various types of wood energy surveys (woodfuels flow surveys, woodfuels supply surveys, and sectoral consumption surveys). Expertise is also needed in data extrapolation to generate secondary and desk analyses at local levels (i.e. provinces and town-village areas), and techniques for decentralised planning, and the formulation of site-specific strategies and programmes.
In general, forestry agencies should have expertise in developing and managing the wood energy database, and in formulating and implementating policies and programmes designed to improve woodfuels supply and flow, such as:
• improving tree production systems in forests and non-forest areas;
• legitimizing and improving the efficiency of woodfuels markets;
• promoting better conversion technologies improving traditional wood energy systems and introducing modern technologies;
• promoting alternative energy crops; and
• integrating wood energy production in land use policies.
Energy agencies should have expertise in developing and managing the wood energy database, and in formulating and implementating policies and programmes to manage woodfuels demand, such as:
• improving wood energy end uses – cooking in households, institutions and food enterprises; heating in agro-processing and small enterprises;
• promoting new end uses – large-scale industrial heating, co-generation, electricity generation, intermediate or secondary fuel production (gaseous or liquid fuels); and
• determining fuel substitution strategies – fuel pricing, subsidies.
Linking data base development, policy formulation and programme planning and implementation will be an effective and efficient approach to building overall national capacity for sustainable wood energy development. Data base development is not the goal itself. It is a means to implementing interventions that concretely demonstrate and lead to the attainment of sustainable wood energy development.
External support will continue to be an important input to building national capacities in developing countries. However, to provide assistance and support to countries, appropriate regional or international bodies should be able to conduct the following activities:
• fine-tune approaches, techniques and methods for data collection and generation, wood energy analysis, planning and implementation;
• provide technical support to countries in the form of policy advice, guidance in wood energy assessments and planning, technical support in implementation of strategies, including training;
• organize a wood energy data base accepted globally and collect and publish wood energy indicators;
• prepare and publish regular reports on the regional and global wood energy situation;
• conduct prognosis of future regional and global wood energy scenarios
and analyse impacts of such on relevant sectors;
• disseminate information on developments in wood energy and manage database.
Strengthening the capabilities of national wood energy agencies and bodies needs the support of international development organizations and agencies. The capabilities of international organizations and agencies, such as FAO, have to be developed or strengthened too so that they will have the proper level of resources to be able to provide the support needed by the developing countries.
The development of sustainable forest and wood energy systems is still a distant goal. Given that wood-based fuels constitute a main forest output in almost all countries, the development of sustainable wood energy systems is crucial for the implementation of overall sustainable forest management.
Many of the capacity building activities listed above will require additional resources. As such, the support of the international donor community will have to be mobilised, but first potential donors will have to be made aware of wood energy situations among countries, the problems and opportunities, and the constraints and potentials of the sector.
43 LEAP or Long-Range Energy Alternatives Planning is a computer based energy planning model that integrates land use analysis as part of the biomass energy analysis module of the model. The model was developed by the Stockholm Environment Institute-Boston (see http://www.seib.org/leap/)
44 Soussan and Mercer. 1991).
45 Masera.
(undated).
46 See “FAO-FD Forest Energy” web
page: (http://www.fao.org/forestry/FOP/FOPH/ENERGY/cont-e.stm)
47 See again Section 3.2.8 – Understanding woodfuels flow
48 Using local level studies and starting with woodfuels flow studies
also provides possibilities for directly working with woodfuels producers,
traders and “commercial” users for programme implementation. Thus, this can be
considered a market-approach for intervening in traditional woodfuels systems as
it allows for immediate “involvement of local entrepreneurs” and “mobilization
of local funds for counterpart financing” (i.e. the “investment” made by
traders, producers, and commercial users) for “profit-oriented
activities”.