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ANNEX VI - Country Reports

NOTE:

This Annex includes only the papers produced for the workshop. Documents produced before, such as the wood energy country studies produced under TCDC arrangements, though relevant for the topic of the meeting, are not reproduced here.

Eritrea

Background Report :

Woodfuels production and consumption in Eritrea -
Review of the existing studies related to fuelwood and/or charcoal by
Estifanos Bein
and Elias Araya
Forestry and Wildlife Division.
Department of Land Resources and Crop Production,
Ministry of Agriculture, Asmara

This is a report of 27 pages, produced under TCDC arrangements, which describes in detail the wood energy sector in Eritrea and the state of the art concerning wood-fuel information.. The full report is not reproduced here but may be requested to the authors or to M.A. Trossero, FAO FOPW, Rome. A short description of this paper is given under "Synthesis of the workshop - workshop activities - presentation of country reports - Eritrea".

National Arrangements and Capacity to Collect
Wood Energy Information and Statistics

by

Elias Araya

Forestry Unit Head,
Forestry and Wildlife Division.
Department of Land Resources and Crop Production, Ministry of Agriculture, Asmara.

1. Relationship between forestry and energy institutions for the administration of the wood energy sector and their responsibilities

The Ministry of Agriculture is the responsible ministry for giving cutting permits of different wood products and controlling the movement of wood products at different checkpoints.

The amount and type of locally harvested wood products, which pass the checkpoint, is registered and reported to the zonal branch ministry office every week.

Usually reports concerning wood production are sent from the regional offices of the MOA to the head office at national level quarterly, every six months and annually. These data is analysed and compiled in the Division of Forestry and Wildlife.

Wood products, which are imported, are registered at the customs office. The division of Forestry and wildlife asks the custom's office at least once a year so as to analyse and compile it accordingly.

In regard to the imported wood products, the Ministry of Finance through its custom office is in charge of data collection and dissemination. The date on imported wood is obtained in terms of local value. The approximate price of the products is used to convert the values in quantitative units. Information on imported wood products could be also obtained from the National Bank of Eritrea, as importers need to open letter of credit (LC) in this bank in order to import goods, this could also be used as a means of validation.

Firewood at local level is usually collected and transported to the nearest depot by camels or donkeys. At each depot, there are licensed firewood concessionaires, which buy and transport the wood to the urban centres. These concessionaires have weighing balance at each depot and the amount they bought is registered. The branch of the Ministry of Agriculture at sub zonal level always monitor and report the amount of wood collected, since the royalty fees are paid based on the amount of wood collected.

The amount of wood, which is collected and utilized at the local level in the rural areas, is difficult to record. In such cases, therefore, the Ministry of Energy and Mines conducts household energy survey by taking samples in the rural households and any interested person or institution can make use of the output of the study.

2. Institutional roles and capabilities

2.1 Institutions responsible

Ministries, Institutions, and Organizations, which involve in one way and the other way, in the collection, analysis and dissemination of wood related products are

ˇ Ministry of Agriculture,
ˇ Ministry of Local Government,
ˇ Ministry of Energy and Mines,
ˇ Ministry of Finance (Customs Office),
ˇ National Bank of Eritrea,
ˇ Municipal Offices (City/Town Councils), and
ˇ Board of Eritrean Standards.

2.2 Roles and capabilities of responsible institutions

As mentioned above, data concerning wood products are collected from reports and compiled at the Division of Forestry and Wildlife of the Ministry of Agriculture.

ˇ This type of data is mainly for those forest products that are produced within the country.
ˇ This is validated by comparing with the royalty fees collected, permits granted to concessionaires, as well as from expert judgement through monitoring in the field.
ˇ Regarding the forest products, which are imported from abroad, data are collected from the customs office.
ˇ This is registered in terms of forest product type and corresponding value, Nakfa, the currency of Eritrea.

The weaknesses in this data collection are:

ˇ the customs office doesn't record the amount either by weight or by volume, and thus it is difficult to convert it accurately into m3 or ton.
ˇ However, the imported value of wood products is validated by comparing the letter of credit (LC), which the importer opened in the National Bank of Eritrea while importing the wood products.

The Division of Forestry and Wildlife compiles annual reports, after collecting all regional reports obtained from the customs office.

Table 9. Strength and weaknesses matrix

Setting

Strength

Weakness

Subregional level (MOA)

ˇ Forest guards at every check points are available
ˇ Permits are granted and Controlled
ˇ Data are collected daily
ˇ Reports are forwarded every week

ˇ No measurement at check point
ˇ Locally consumed wood products are not well recorded & controlled
ˇ No computer facilities for data processing

Regional Level  (MOA)

ˇ Reports are compiled and forwarded to head quarter
ˇ Cutting & collecting permits are granted and well controlled
ˇ Royalty fee collected and well recorded

ˇ No systematic record of data
ˇ Lack of skilled manpower & computer facilities

National Level  (MOA)

ˇ Computer facilities are relatively better
ˇ Compiled annual reports available

ˇ Shortage of manpower
ˇ Lack of systematic data collection and validation

Customs Office  (MOA)

ˇ Imported wood products are recorded at port of entry

ˇ Imported wood products are not recorded in terms of quantity (m3)

Department of  Energy

ˇ Biomass study survey is conducted systematically at national level

ˇ Biomass survey is not regularly conducted

2.3 Recommendations for improvement of national capacity to collect wood energy information and statistics

In order to have meaningful data and information concerning wood energy, the following points are recommended:

ˇ Promote coordination of data and information found in different organizations;
ˇ Measurements of forest products have to be standardized and accurate conversion factor is needed;
ˇ Production and consumption survey especially for fuel wood & charcoal should be done regularly;
ˇ The system of data collection on wood products is obtained from the concerned institutions (like the customs office) upon request. Therefore, easy access to available data should be organized;
ˇ The forestry sub-sector is constrained with limited capacity to handle and process wood product data and disseminate to the clients. Therefore, training of forestry staff in data base management is very important;
ˇ Regional and subregional offices of the MOA should be equipped with computer facilities so that data and information on forest products can be easily transferred through e-mails on time;
ˇ Reporting formats need to be easily understandable and thus, it has to be standardized
ˇ Production and consumption assessment on wood fuel and other wood products outside the forest, that is consumed locally, should be conducted, since there is lack of data on these products.

In conclusion, all wood products, imported or exported, have to be well-recorded, analysed, validated and disseminated to data users. These data also need to be updated regularly.

 

 

Gambia

Background Report :

Woodfuels Review and Assessment in the Gambia

by
Yorro M. A. Sallah

Former Senior Forestry Officer
Department of Forestry

This is a report of 20 pages, produced under TCDC arrangements, which describe in detail the wood energy sector in The Gambia and the state of the art concerning wood-fuel information. The report is not reproduced here but may be requested to the author or to M.A. Trossero, FAO FOPW, Rome.

A short description of this paper is given under "Synthesis of the workshop - workshop activities - presentation of country reports - Gambia".


Ghana

Report 1 -
Ghana's Wood Energy Sector

by

Eric Ofori-Nyarko
Energy Commission
PMB, MPO,
Accra, Ghana.
Email: enyarko@yahoo.com

1. Background

Ghana's forest resources are subject to many pressures and therefore the need to consider long-term resource management options. Similar to anywhere in sub-Saharan Africa, deforestation and degradation resulting from increased population pressure, agricultural encroachment, uncontrolled and wasteful fuel wood harvesting including inefficient charcoal production are common. According to FAO statistics Charcoal and Fuel wood consumption in 1988 was estimated at 15.9 million m3. In 1998 this figure increased to 20.6 million m3, which is about 30 percent increase within a period of 10 years. This implies that the per capita wood fuel consumption is now close to 1 m3/capita.year.

Wood fuel supply and demand patterns are seriously unbalanced at the rural areas. Denudation has occurred in large areas of the savannah surrounding towns and villages in the Brong Ahafo, Northern, Upper East, Upper West, Central, Greater Accra and Volta Regions of the country. Deforestation is also serious in the closed forest areas of the Ashanti, Western, Eastern and parts of Brong Ahafo Regions.

The Government has become increasingly concerned at the need for concerted action to preserve the country's wood fuel resources. Its stated objectives are to (a) manage the wood fuel resources by methods ensuring improved productivity, efficiency in transformation and distribution and (b) efficient use of these resources through the promotion of improved end-use devices and best practices.

However, data on wood fuels is very scarce and where the data is available it is not very reliable, thus making it very difficult to undertake relevant:

ˇ Planning activities; and
ˇ Environmental impact assessment activities on wood fuels use.

The Energy Commission, a public institution recently established by an Act of Parliament and given the statutory mandate to manage and regulate the utilisation of energy resources in Ghana, is considering measures to develop and recommend national policies for efficient and cost-effective utilisation of the wood fuel resource. For the development of sustainable wood fuel policies, the Commission would require updating and reorganising the existing wood fuel data.

2. Wood-fuel resources

Wood fuel production in Ghana is associated mainly with three major ecological zones: (i) the Rain Forest, (ii) the Moist Deciduous Forest and (iii) the Savannah Woodland. The total forest cover, according to FAO statistics (1995) is stated as follows:

Table 1. Forest cover 1995 (FAO)

Rain forest
1000 ha (%)

Deciduous forest
1000 ha (%)

S/woodland
1000 ha (%)

Total cover
1000 ha (%)

9 022 (40)

8 405 (37)

5 327 (23)

22 754 (100)

The majority of wood fuel production activities occur in the Savannah Woodland located in the Brong Ahafo, Ashanti, Eastern and Volta Regions. The main wood species preferred by producers are `Kane' (Anogeissus leiocarpus) and `Ongo (Terminalia avicenioides). Several other species are also used. Charcoal production sites, in most cases, are within 100 metres from where the wood is obtained. Most of the wood utilised for charcoal production originates from felling and crosscutting of trees on fallow lands as well as farmlands, using tools such as chainsaws and axes. Logging and sawmill residues in the form of wood off-cuts, are also used for charcoal production in Ashanti and Brong Ahafo Regions.

3. Wood-fuel supply and consumption

The main players in the wood fuel trade are producers, transporters, merchants (middlemen/dealers), retailers and consumers. Wood fuel supply by three ecological zones in Ghana is shown in percentages in the table 2 below:

Table 2. Wood-fuel supply by ecological zones (%)

Ecological zone
Savannah 
Regional Share (%) Eco-zone %
Brong Ahafo

50.7

Eastern (Afram)

14.6

79.0

Northern

6.9

Volta

4.0

Upper West

2.1

Upper East

0.3

Deciduous Forest Volta

5.0

Central

4.5

15.0

Ashanti - Sawmills

2.2

- Others

1.8

Eastern

1.0

Rain Forest Western

5.9

6.0

There is an indication that about 50 percent of the wood-fuel supply is from the Brong Ahafo Region whilst 79 percent of the total supply comes from the Savannah zone. The Deciduous Forest provides just about 15 percent of the wood fuel supply.

In terms of consumption, households are major consumers of wood fuel in Ghana. Not much wood fuel is consumed by the commercial and industrial sectors. Exports of charcoal fuel to the United Kingdom in 1988 accounted for 210 t. The export of charcoal to Europe is alleged to have been on the increase under the trade policy of non-traditional exports.

A comparison of the data from the FAO and the Ministry of Mines & Energy on wood fuel production and consumption from the period 1980-1994 indicates that there has been tremendous increase in the consumption of wood fuels.

The FAO source of wood fuel consumption from the graph above depicts two critical periods (1982-1984) and (1991-1992). The graph shows that sharp increases in wood fuel consumption have occurred. Though no serious analysis of the data has been carried out, it is assumed that some changes in socio-economic factors might have occurred within these periods.

4. Wood-fuel retailing

In regional capitals wood fuel, especially charcoal, is delivered to the markets and to major retail outlets in towns where there are no big markets. Direct sales from trucks to households are done, but to a very small extent. Wholesale of charcoal is carried out at these market centres where retailers and individual consumers obtain their supplies or consignments. Within residential areas small-scale retailers, mostly women, retail charcoal in small measuring units equivalent to a kilo-weight.

5. Critical issues

ˇ Due to the following factors all income groups use wood fuel:
  - The use of LPG, Kerosene and Electricity for cooking requires relatively higher capital outlay for the purchase of cooking devices, although the price of these fuels is cheaper than charcoal.
  - The supply and distribution of LPG, Kerosene and Electricity are quite unreliable.
  - Charcoal and fuel wood can be bought in small quantities at a time and are suitable for the preparation of indigenous Ghanaian dishes.

ˇ Ineffective promotion and use of wood fuel efficient end-use devices. For example the `Ahibenso' charcoal stove promotion could not be sustained due to the fact that there was no coordination between the implementing agency and the Customs Excise and Preventive Service (CEPS). Since the excise duty imposed on the stove rather increased the final price of the stove, making it unaffordable to the targeted users.

ˇ Weak wood fuel policies. Owing to the difficulty in obtaining reliable wood fuel data, policies have rather been developed on projections and estimates. As a result the current policies are not able to adequately address the existing problems.

6. Proposed measures for meeting the current wood fuel demand

ˇ Develop institutional capacities for both the Forestry Commission and the Energy Commission through the provision of adequate resources, manpower development and joint or collaborative programs.

ˇ Prepare wood fuels resource development plan, as part of a land use plan, based on (i) realistic assumptions about productive potentials and future demand, (ii) selective inventories of wood fuel resources within reasonable distance from the major consumption centres, (iii) evaluation of options to increase wood species that can be used for charcoal production, (iv) evaluation of options to increase the production of wood fuel resources and (v) wood fuel consumption surveys in major consumption centres for the purposes of preparing a wood fuel policy.

ˇ Develop policies focused on ensuring efficient utilisation of wood fuel resource. Revitalising promotional programs geared towards achieving fuel substitution for middle and high-income households and reduced cost of efficient end-use devices for all categories of households.

Ghana

Report 2 -
National Arrangements and Capacity
to Collect Wood Energy Information and Statistics

by

Eric Ofori-Nyarko
Energy Commission
PMB, MPO, Accra, Ghana.

1. Introduction

The energy sector of Ghana is currently undergoing reform. This is aimed at achieving a greater transparency in the decision making process. Wood fuel use however constitutes one of the key issues to be addressed in this reform process.

Despite the important role that wood fuels play in meeting household energy needs in Ghana, data on wood fuels is very scarce and where the data is available, it is not very reliable, thus making it very difficult to undertake relevant:

ˇ Planning activities,dd and
ˇ 
Environmental impact assessment activities on wood fuels use.

There are neither serious institutional arrangements nor any effective coordination among various institutions involved in wood fuel resource management in Ghana.

2. Institutional roles and capabilities

The Forestry Commission was established by law in 1984. It was assigned the responsibility, among other things, to:

ˇ Review practices relating to forest and forestry resources and formulate recommendations of national policy on forest resources,
ˇ Ensure that forests are maintained and protected as economic resources, and
ˇ Ensure that waste and destruction of the forest and associated natural resources are minimized.

Similarly the Energy Commission, established by an Act of Parliament in 1997,was given the statutory mandate to regulate, develop and manage the efficient utilization of energy resources including wood fuels in Ghana and coordinate policies relating to them.

The Energy Commission, in its present efforts to develop sustainable national energy policies for the production and utilization of indigenous energy resources, has identified wood fuel resource management as an area that needs immediate attention.

Both the Forestry Commission and the Energy Commission are presently building the manpower planning capacity and developing programmes for the creation of a comprehensive database on wood fuel resources, production and consumption.

2.1 Institutions responsible for the acquisition of data on wood-fuel consumption

The Ministry of Mines and Energy (MME), the Energy Commission and the Forestry Commission are the institutions responsible for the compilation and storage of data on wood fuel consumption. MME had complied wood fuel consumption data from 1974 to 1997, but this data is based primarily on projection. The Forestry Commission, although it had carried out some surveys on wood fuel consumption, it has no data. The Energy Commission now has the responsibility of data compilation and storage.

2.1.1 Resources deployed

The Energy Commission has in place a Division (Energy Resource Planning and Policy) with three Analysts whose duties, among others, include the compilation, storage, analysis and interpretation of wood fuel data.

There is also the Energy Fund, which is being managed by the Commission for activities that include data collection and database management on all forms of energy, including wood fuels.

The Energy Sector is currently benefiting from a DANIDA funded project on Traditional and Renewable Energy that is supposed, as part of the project activities, to collect data on wood fuel supply and consumption in the northern parts of the country.

2.1.2 Methods of assessment

The Commission intends to carry out surveys in 2001 that will target the collection of data on household and commercial sectors wood-fuel consumption. In this process, enumerators will be used and will visit households and centres of commercial business to assess the quantities of wood fuel consumption

2.1.3 Frequency of assessment

The Commission intends to carry out wood fuel consumption surveys once every two years.

2.1.4 Items covered

The parameters will include the following:

ˇ Location (km)
ˇ Socio-demographic and economic (characteristics)
ˇ Cooking habits (frequency)
ˇ Fuel used (kilograms)
ˇ Fuel Cost (˘)
ˇ Types of end-use devices (efficiency % rating)
ˇ Conservation practices (characteristic cost saving)

2.2 Institutions responsible for the acquisition of data on wood fuel supply

The Forestry Commission and the Energy Commission are responsible for the acquisition of wood fuel supply data. The efforts of the Forestry Commission are not known. However the Forestry Commission is prepared to enter into any collaborative activities with the Energy Commission.

2.2.1 Resources deployed

The Forestry Commission, its staff and the personnel of other agencies like the Forestry Department and Forest Research Institute of Ghana are prepared to assist in the collection of data. However their sources of funding are basically from donor assistance.

The Energy Commission would deploy the same resources as indicated in 2.1.1.

2.2.2 Methods of assessment

The Energy Commission intends to identify all wood fuel market centres in the country and collect data on wood fuel supply. The members of the Wood Fuel Association will be invited to participate in providing information relating to sources of wood fuel supply and other relevant issues. The Commission, may probably, contract the services of data collection to personnel in each region, who will go round the markets to collect data and submit to the Commission.

2.2.3 Frequency of assessment

It is intended that the personnel engaged in the regions will be assigned the responsibility of wood fuel supply data collection and will submit data on monthly basis to the Commission.

2.2.4 Items covered

The parameters will include the following:

ˇ Location of market (km)
ˇ Storage facilities (Adequacy)
ˇ Source of Supply (km and frequency)
ˇ Price/Volume/Quantity of Sale (˘, bags & kg)
ˇ Taxes (˘)
ˇ Quality of product (grade)
ˇ Retailers (size)

2.3 Institutions responsible for the analysis of supply/demand balance and
the forecast of future scenarios

The Energy Commission's planning and policy division is responsible for the preparation of the energy balance and prediction of future scenarios of wood-fuel supply and demand of the country.

2.3.1 Resources deployed

The resources indicated in 2.1.1 are the same resources that would be used for the preparation of the energy balance. In addition, computers have been installed with a database to be created soon. Working groups from other stakeholder institutions like the Forestry Commission, EPA, and the Statistical Service would be formed to discuss and evaluate the scenarios.

2.3.3 Methods and frequency of analysis

Microsoft Access will be used for the compilation and storage of data. It is intended that most of the analysis will be done using Microsoft Excel. The planning software that will be used for the development of best options is not discussed yet.

2.3.4 Reporting units

The Energy Commission reports directly to the Office of the President and advises the Minister of Mines & Energy on energy matters. However, the preparation of the National Energy Plan will require that national forums are held to discuss newly developed energy policies with the public.



Kenya

National Arrangements and Capacity to
Collect Wood Energy Information and Statistics

The Kenyan Scenario

by
Kareko KK8 and Githiomi J9

Abstract

The wood energy sector in Kenya, as is undoubtedly the case elsewhere, is complex in nature and different issues pertaining to it are addressed by different agencies. Development activities in the sector are addressed by three main government agencies namely Forestry Department (FD) in the Ministry of Environment and Natural Resources (MENR), Renewable Energy Division of Ministry of Energy (MoE) and the Agroforestry Unit of Soil and Water Conservation Branch (SWCB) in the Ministry of Agriculture and Rural Development (MoA&RD). Policy issues are mainly addressed by MENR and MoE. The agencies collaborate among themselves in addressing wood energy production, utilization and conservation issues in the country. This is done through the extension services of the FD and MoA&RD

In assessment of consumption, supply and supply/demand balance and prediction of future scenarios, the 3 agencies play important roles. In particular, FD and MoE have each carried out production (supply), consumption and supply/demand analysis studies on several occasions and covering varying geographical extent. The surveys have produced varying consumption and production data and predicted future scenarios to varying extent. They used different survey methodologies and each methodology has its own weak and strong points. The different surveys have utilized different parameters and there has been no consistent or set frequency. All the surveys have not adopted repetitive monitoring hence future predictions have not been examined to find out the accuracy of the predictions. The Central Bureau of Statistics (CBS) produces annual statistical abstracts, which give charcoal supply and pricing data on quarterly basis. The surveys by CBS are not in-depth in terms of assessing where the charcoal is produced from or what the status of the production units are in terms of availability of raw materials, efficiency of production, etc. The data is therefore not very useful for planning purposes. Other surveys have been carried out by several development projects and individual observers. Most have dwelt on demand and supply, a few on production and fewer still on production, supply and demand/supply dynamics, including sources of material and prices.

All surveys carried out thus far lack vital aspects that would make them useful for planning in development of the wood energy sector. The paper recommends that a comprehensive national survey be carried out to determine the situation on the ground and develop cost-effective and efficient tools for prediction of future wood energy scenarios. Such a survey would require training of staff at FD, MoE, DRSRS and related institutions.

1. Description of institutional arrangements between forestry and energy institutions for the administration of the wood energy sector

Wood energy issues in Kenya are generally addressed by a number of agencies, both government and non-government, owing to the complex nature of the issues. Development activities in the sector are addressed by three main government agencies namely Forestry Department (FD) in the Ministry of Environment and Natural Resources (MENR), Renewable Energy Division of Ministry of Energy (MoE) and the Agroforestry unit of Soil and Water Conservation Branch (SWCB) in the Ministry of Agriculture and Rural Development (MoA&RD). In 1982, a Memorandum of Understanding (MoU) was signed between the 3 ministries. By this MoU, energy centres were created in the districts from which technologies would be disseminated to the rural populace. The MoE was to provide technical support for implementation of agroforestry in the country while FD and MoA&RD were to house the energy centres at forest stations and farmers training centres (FTCs).

Over the years, however, not much dissemination of agroforestry technologies has taken place through this arrangement even though at policy level, the aspirations of the MoU still exist. During the early years of the MoU, the mandate of developing agroforestry in the country was under MoE but at one point in time, this shifted to Forestry Extension Services Branch (FESB) of FD and SWCB of MoA&RD on the premise that MoE does not have capacity to disseminate agroforestry technologies. However, in terms of policy, MoE still has the mandate to promote development of wood fuel production at farm level. The forestry policy and that of agriculture also recognize the related agencies (FD and MoA&RD) as being mandated to carry out the same activity. Despite the conflicts in policy and mandate, the agencies collaborate among themselves and with development projects (donor or government aided) in addressing wood energy production, utilization and conservation issues in the country. This is done through the extension services of the FD and MoA&RD, as well as through outreach by projects.

In assessment of wood energy consumption, supply and supply/demand balance analysis and prediction of future scenarios, the agencies play important roles. In particular, MoE and FD have each carried out production (supply), consumption and supply/demand analysis studies and surveys on several occasions and covering varying geographical extent. The surveys have produced varying data and predicted future scenarios to varying extent. They used different survey methodologies each with its strong and weak points. The different surveys have utilized different parameters and there has been no consistent or set frequency of doing the surveys. All the surveys have not adopted repetitive monitoring hence future predictions have not been examined to find out the accuracy of the predictions.

In addition to the 3 major agencies, other government agencies have played important roles in providing data on wood energy. The Department of Resource Survey and Remote Sensing (DRSRS) of MENR has also carried out a wood fuel consumption survey under the auspices of the National Land Degradation Assessment and Mapping (NLDAM) Project. The Central Bureau of Statistics (CBS) produces annual statistical abstracts which give charcoal supply and pricing data on quarterly basis as well as quantities of fuelwood purchased from FD forest stations across the country. Other agencies and development projects and programmes within or outside the major government agencies mentioned above have done similar studies and surveys (annex 1). Similarly, individual observers have also done surveys or studies for varying purposes.

The Kenya Forestry Master Plan (KFMP), a blue-print to guide forestry development between 1995 and 2020 done by FD in 1994, predicted future scenarios for forest products, including wood energy resources. This document was set to be revised every five years. The first revision, supposed to have been done this year, has not been done and does not seem like it will be done.

2. Institutional roles and capabilities

The institutions whose mandate includes acquisition of data on wood fuel consumption, supply and demand/supply balance analysis are MoE and CBS. Other agencies, notably FD and DRSRS, have been involved in similar work also.

The MoE has the mandate to acquire data on all forms of energy, analyse it and recommend action and/or advise the government on development strategies in the energy sector. The ministry has the policy objective of ensuring adequate and sustainable supplies of energy efficiently and at least-cost methods in line with national development aspirations while, at the same time, aiming to achieve greater self-reliance in energy supply in the long term while conserving the environment. In doing this, the ministry has a mission, strategies and a 10-year programme (1996/97-2016/17) in place under which activities are organized. Effective management of the programme requires that reliable data be collected in all aspects of all types of energy. The ministry has personnel trained in dealing with energy issues but are handicapped by inadequate capacity (equipment and skills in survey methodologies and data analysis) and shortage of funds for implementation of surveys, which the ministry is expected to carry out every 3 or 5 years.

The CBS collects data on all development aspects of the country with the aim of advising the government in general on planning for development programmes. The bureau has in place an Integrated Rural Survey (IRS) network in which a national sampling framework has been established. Any agency doing any rural survey in Kenya can use this framework to draw a sampling frame. All information gathered and analysed is documented in Annual Statistical Abstracts. The data is collected monthly, quarterly or on ad hoc basis. In terms of wood energy, the CBS has been compiling information on charcoal prices and fuel sales, the latter being sourced from FD and based on fuelwood sold by the department's forest stations (receipted sales). The data at CBS, therefore, does not contain information on wood available for energy on farmlands, natural woodlands and bush lands (mainly in the drylands) and settlements, which forms the bulk of wood energy in Kenya. The charcoal pricing data is also never verified nor are any attempts ever made to determine sources of charcoal. The bureau has staff at district level who have been instrumental in collecting information. These staff, as in all other departments, are handicapped in terms of transport and operating funds and any data they collect cannot be said to be accurate for planning purposes.

The FD acquires data on wood energy as part of its monitoring and reporting requirements and which is a vital planning tool not only in its planting programme in gazetted forest lands but also for forestry extension programmes. During the master plan preparation, the department undertook studies on wood-fuel energy supply and demand and produced supply/demand balance data for the next 25 years, beginning 1995 through to 2020. The master plan has been an important reference in forestry development discussions (including wood fuel) despite failure to carry out scheduled revisions of the document.

The DRSRS also has the role of collecting data on natural resources and advice the MENR and other natural resource agencies on planning of development programmes.

2.1 Institution(s) responsible for acquisition of data on wood-fuel consumption

The MoE and CBS are responsible for acquisition of data on wood fuel consumption. MoE is supposed to carry out these surveys every 3 or 5 years in accordance with national planning. Areas where salient features of current concern need addressing are supposed to be picked out for the survey since a nation-wide survey may be outside the ministry's ability (capacity and financial constraints). These scheduled surveys are never implemented due to lack of funds in overall government functions.

Any data or information hitherto collected by these agencies for routine work or as special undertakings (annex 1) have suffered from inadequacies related to poor sampling techniques, failure to collect or use relevant related data or inappropriate analysis and documentation, among other reasons.

Of all the surveys carried out in Kenya on wood fuel supply, three can be said to be good to some extent. These are the Beijer Study of 1980-81 (Barnes et al., 1984 and Hosier, 1984), the CBS Rural and Urban Energy Surveys of 1978-1979 and the Ministry of Energy's rural energy surveys (1986-1987). A summary of these surveys and others are in annex 1. The surveys suffer from lack of repeat visits to households and from lack of any intensive monitoring of fuel use. The surveys thus give exaggerated consumption.

2.1.1 Resources deployed

The MoE and CBS, in the surveys they are supposed to carry out, are supposed to use the manpower and other resources (vehicles, computers, etc.) existing within the institution but may incorporate expertise from elsewhere when and if necessary.

In the 3 major surveys and others of similar or different calibre carried out in Kenya in the past, different resources were used but in all cases included logistics such as vehicles and funds for maintenance in the field and/or for hire of expertise. Data analysis was done by hand and/or computer in these surveys. In no case is the budget involved in the surveys indicated in the reports (annex 1).

2.1.2 Methods of assessment

MoE and CBS are supposed to use the sampling procedures based on the national frame established by the CBS for the national integrated sample survey programme to draw sampling frames. In all cases, the survey would be carried out by staff of the institutions. In the earlier surveys carried out by the 2 institutions, the methods of assessment varied from one survey to another (annex 1) but in all, a questionnaire was administered.

2.1.3 Frequency of assessment

Ideally, the MoE is supposed to carry out energy surveys every 3 or 5 years but never does so because of shortage of funds and inadequate staff capacity. The CBS is expected to produce statistics every month, every quarter or as may be requested. The data the Bureau currently produces is taken straight from raw data supplied from FD, which in turn, reflects sale of fuelwood at forest stations only. This leaves out other important wood energy sources. The charcoal pricing data collected on similar frequencies do not reflect much in the way of charcoal consumption.

The studies by CBS, MoE and Beijer Institute are probably the last best wood-fuel consumption assessments done in Kenya. However, the last assessment on wood fuel consumption done in Kenya is the one done by the National Land Degradation Assessment and Mapping (NLDAM) project (Agatsiva, 1997) done in 1995-96.

2.1.4 Items covered

The surveys cited above and others (annex 1) covered almost similar parameters to each other (i.e. amount of fuel used over a given period, distances to sources, etc.) with little variation and different reporting units depending on level of observation.

The MoE survey covered energy types (fuelwood, charcoal, agricultural residues, paraffin) and appliances used. Data were analysed on district-by-district basis.

The CBS survey covered quantity of fuel used in a given reference period and distances walked to obtain each fuel. Data analysis was done along provincial basis. Charcoal pricing data collected monthly, quarterly or on ad hoc basis can reflect consumption through further analysis.

Parameters covered by the Beijer Institute survey included quantity of each fuel used over a given period of time, cost of fuel, time and distance travelled to collect it, person in household responsible for collecting the fuel, number and type of appliances used to consume the fuel, number of persons eating with the household, major fuel consumed and major changes over the past 2 years and most commonly consumed meal. The reporting unit was the district.

2.2 Institution(s) responsible for the acquisition of data on wood-fuel supply

The same institutions responsible for acquisition of data on wood fuel supply are the ones involved in wood-fuel supply data acquisition. The above consumption surveys also had a component of wood fuel supply (annex 1). The NLDAM (Agatsiva, 1997) project and KFMP (1995) have also estimated wood fuel supplies based on MoE (1988) and Bess (1989) data respectively.

2.2.1 Resources deployed

Since these supply assessments were part of the wider energy surveys discussed under section 2.1, the same resources used for the consumption assessment were used for supplies assessment.

2.2.2 Methods of assessment

The supply assessment, being part of the wider energy survey, used the same methods of supplies assessment as used for consumption assessments by each survey.

2.2.3 Frequency of assessment

MoE, as with consumption assessments, is supposed to carry out assessment on supply every 3 or 5 years but has not been able to do so for reasons elicited above. The latest comprehensive assessment on supply can be said to be that done by NLDAM (based on MoE survey). The CBS collects fuelwood data sales (quantity and related prices) from forest stations as reported by FD every month, quarterly or on ad hoc basis. As earlier noted, this data only reflects fuelwood from gazetted government forest land and not from other land use categories.

2.2.4 Items covered

The MoE survey questionnaire covered energy supply by types of sources of energy and member of household collecting it. Data were analysed on district-by-district basis. The survey questionnaire included questions on charcoal production both as a level of activity as well as a source of income.

The CBS, in its monthly, quarterly or ad hoc basis data compilation for its statistical abstracts, gives data on fuelwood supplies and prices from forest stations under FD. It also gives data on retail prices of charcoal for major urban centres, which can form references for estimating charcoal supplies. The reporting unit here is national.

Parameters covered in the Beijer Institute survey that reflect supply are cost of fuel, time and distance travelled to collect it and person in household responsible for collecting the fuel. The reporting unit is the district.

2.3 Institutions responsible for analysis of supply/demand balance and for forecast of future scenarios

The same institutions responsible for compilation of data on wood fuel consumption and supply are also responsible for analysis of supply/demand balances and prediction of future scenarios. In addition, the FD (KFMP, 1995) did an intensive analysis on demand and supply balances and predicted the situation for the next 25 years (1995-2020).

2.3.1 Resources deployed

The same resources deployed in assessment of consumption and supply by MoE and the Beijer Institute are similarly used for supply/demand balance analysis and prediction of future scenarios. In the case of the CBS, not much is done by way of supply/demand balance but the data on retail price of charcoal provides important guidance on charcoal price trends.

The KFMP (1995) made its assessments starting with Bess's (1989) base figures for the per capita charcoal and fuelwood consumption for 1990. Much of the work done by Bess (1989) was, in turn, based on the work done by MoE in 1988-89. KFMP also relied a lot on other work done earlier (UNDP/World Bank study, 1987; 1989 Census Report and the National Water Master Plan of 1992, among others). Several consultants were hired to work alongside government officers assigned to look at the bio-energy resources in the country. These consultants did specific surveys on wood fuel utilization and biomass surveys in several parts of the country (KFMP, 1992 and KFMP, 1995).

2.3.2 Sources of demographic and economic data and projections

Sources of demographic data include the CBS and the Population Council of Kenya. The forestry master plan used adjusted population data from the National Water Master Plan (1992) while economic data was and is mainly sourced from annual economic surveys of the Ministry of Finance.

2.3.3 Methods and frequency of analysis

The MoE and Beijer Institute analysed supply and demand figures on basis of districts and differences between supply and demand gave the supply/demand balance. By incorporating per capita consumption figures, projected population growth figures and penetration of improved domestic energy utilization technologies (improved stoves and other techniques), the institutions were able to predict future scenarios but only in the short run. On the other hand, KFMP, using similar methods, and incorporating the role of improved charcoal production and improved cook-stoves, was able to project supply/demand balances for a period of 25 years and predicted scenarios to 2020. The KFMP was set to be revised every 5 years but the first revision has not been done. The MoE frequency of 3-5 years is also not adhered to either.

2.3.4 Reporting units

All the supply/demand balance analyses were based on districts. The MoE and Beijer Institute surveys were based on the premise of an energy crisis and therefore, predicted an energy crisis if tree planting was not enhanced to provide wood energy on a continuous basis. The KFMP was also based on similar assumptions but gave scenarios that could be adopted to avoid falling into a situation where there would be a wood gap. The demand/supply balances show that from the year 2000, a major wood deficit would occur, much of this being manifested as wood fuel deficit. This can however, be avoided if policy interventions are put in place (annex 1).

2.4 Conclusions and recommendations

It can be concluded that all the wood energy work carried out so far in Kenya has failed to contribute significantly to understanding of the rural household energy consumption in Kenya but their analysis can help point out common errors that should be avoided in future work for better results.

It is recommended that a comprehensive national wood-energy survey be carried out to determine the real situation on the ground and develop cost-effective and efficient tools for assessment of available resources and prediction of future scenarios. Such a survey should contribute to a national wood-fuel master plan and it would require financial support for capacity building at FD, MoE, DRSRS and related institutions.

Annex 1(Kenya paper): Summary of Wood fuel Surveys and Studies Done in Kenya

1. Beijer Institute Rural Energy Survey (1981)

This work was carried out with the express goal of verifying estimates of rural energy consumption for the development of a National Energy Policy and establishment of a solid information base from which to work in future. The survey was designed to obtain consumption data, supply data (source, quantity and value), relationship between demographic factors and energy consumption, variation of energy consumption with income and factors of decision-making in energy consumption at household level.

The sampling techniques used drew a sub sample from the frame designed by Central Bureau of Statistics (CBS) as part of the National Integrated Sample Phase I (CBS, 1975). A subset of the respondents from the energy survey of 1978 was re-interviewed. Fifteen districts were selected from the 3 ecological zones (high potential, savannah and arid) following Akinga (1980).

The parameters measured are:

ˇ Quantity of each fuel used over a given period of time.
ˇ Cost of fuel.
ˇ Time and distance travelled to get fuel.
ˇ Person responsible for obtaining fuel.
ˇ Number and type of appliances used to consume the fuel.
ˇ Number of persons eating with the household.
ˇ Major fuel consumed and changes over the past 2 years.
ˇ 
Most commonly eaten meal.

The questionnaire was administered by CBS enumerators who are permanently employed and live in the area.

Two weaknesses are identified in this survey (Hosier, 1981b):

ˇ The sample drawn from a cluster sampling frame was too small.
ˇ All households being surveyed had all been used for other studies and they could therefore have been potential sources of serious bias.

The survey estimated that the average household fuelwood consumption was 4 354.7 kg/a (equivalent to 6 m3/a) or a per capita figure of 725.8 kg/a while that of charcoal was 104.4 kg/a (average per capita of 17.4 kg/a) overall (national).

2. Wood-fuel availability as an indicator of land degradation

This is not strictly a wood fuel survey but the assessment came up with wood fuel consumption figures which can be a useful reference point for planning purposes. The assessment was done during the National Land Degradation Assessment and Mapping (NLDAM) Project, a collaborative activity of Government of Kenya, the Royal Netherlands Government and United Nations Environment Programme (UNEP) which covered a period of one year (1995-1996). Various components of the project were covered by different institutions and consultants. The part of the wood fuel indicators of land degradation was spearheaded by the Department of Resource Survey and Remote Sensing (DRSRS) and is documented by Agatsiva (1997).

The assessment by NLDAM was a study on fuelwood-based indicators of land degradation with the objectives of examining the availability and suitability of wood species as indicators of land degradation hazard within various vegetation communities of Kenya. Its scope was limited to:

ˇ Assessment of natural woodlands outside managed forests since the latter are not freely available for fuelwood.
ˇ Assessment of fuelwood species according to their suitability for charcoal and fuelwood.
ˇ Availability and suitability of fuelwood for communities living in major urban and rural centres.

The criteria used were:

ˇ Vegetation classes showing certain levels of concentration of woody biomass.
ˇ Quantity of wood in each category to determine available wood.
ˇ Various wood fuel species for their suitability for charcoal or fuelwood.
ˇ Population concentration and availability of suitable fuelwood in various communities.

Data Compilation

a) Use of satellite images

Remote sensing techniques were used to assess, map, and monitor vegetation resources, especially woody biomass. The information obtained was supplemented by that obtained from field surveys to provide quantitative information on categories of woody biomass observed. The survey used Landsat Thematic Mapper (Landsat TM) imagery. The high resolution of the imagery allowed further categorization of biomass classes into closed, dense, open or sparse vegetation, using the classes of Grunblatt and other (1989) with 33 possible classes of vegetation.

b) Field verification

Representative sample sites were visited. Two road transects, one running through the northern rangelands from west Pokot to Samburu and another through the southern rangelands from Narok to Kitui were adopted. The 2 transects provided a reasonable coverage of the entire spectrum of vegetation communities, and hence the variety of woody biomass types in Kenya.

Nineteen districts were visited: West Pokot, Turkana, Baringo, Elgeyo-Marakwet, Samburu, Nyandarua, Isiolo, Laikipia, Machakos, Makueni, Kitui, Kajiado, Narok, Taita Taveta, Kwale, Mombasa, Kilifi and Tana River. Sample sites were selected along the survey routes and in each stratum, woody biomass classes were checked and volume measurements made. A choice was made at each site for any of the following: 10 plots of 10 x 10 m, 5 plots of 20 x 20 m, 2 plots of 50 x 50 m and 1 plot of 100 x 100 m. In each plot, measurements of diameter at breast height (dbh), tree height and crown depth were made and used to calculate the commercial tree height. Major fuelwood species were identified. In total, 107 plots were sampled. A 2-cm base unit was adopted for trees that could be used for charcoal, following reasonable estimates in Uganda (Uganda Forest Department, 1992).

c) Estimation of biomass by plot

The total amount of wood contained in each biomass class was estimated using tree volume, plot volume and biomass class volume which was then converted into weight by multiplying the tree volume by a constant 0.95 that gives fresh weight and includes branches as part of the weight (Agatsiva, 1987) and also takes into account the conical shape of the tree. Fresh weight was converted to dry weight by a factor of 0.5 for most of the tree species (Uganda Forest Department, 1992). The averages for each biomass class sampled in the field were computed and values assigned to similar biomass classes which were not field checked.

d) Calculation of woody biomass by cover type

The remote sensing data were captured and processed in a geographical Information System (GIS). The attribute data analysed were wood cover classes and wood quantity. The resulting map was digitized and the area of each class calculated automatically using ARC/INFO software. The areas of all classes belonging to the same wood biomass level were added to obtain national aggregate data. The resulting wood-concentration map was merged with another map whose attributes were location boundaries and population concentration. Calculated production was multiplied by a factor of 0.2 to obtain the ultimate amount of wood fuel that can be taken out sustainably.

Calorific values of fuelwood species were obtained from literature. An assessment of the suitability of various species for charcoal was obtained from interviews with charcoal traders along the survey routes. This information, complemented by field measurements, gave a list of the suitable species [Annex 1-(i)]. Population data for 1989 census were extracted for each location and a map prepared to show population concentrations in various parts of the country. These data were used to calculate demand and supply dynamics. A per capita consumption figure was adopted and used for each district according to earlier surveys (Republic of Kenya, 1988). Finally, the population and associated wood fuel demand data were overlaid with those on wood fuel availability in order to identify areas of deficit, which are at risk of land degradation.

3. The Kenya Charcoal Survey by Bess (1989)

This is a study on charcoal production systems as part of the Ministry of Planning and National Development's long range planning programme. It examined the dynamics of charcoal production and its effects on rural land use and ecology. The necessary information was obtained through surveys, interviews and reviews of available data and information.

Phases of the survey

The survey proceeded through the following phases:

1) Literature review.
2) Design and review of models for rural production systems. This phase set out the key parameters affecting charcoal production and marketing.
3) Acquisition of charcoal consumption and demand data and incorporation of the same into the model. The data were acquired through surveys and extensive review of relevant data.

The result of this was an econometric model that could be applied on a district-by-district basis. The model allows one to determine where and under what conditions charcoal is produced and marketed hence can be used for forecasting and planning purposes.

A point to note is that the study does not commence with the assumption that there is a "fuelwood crisis" and that charcoal is a major contributor to that crisis unlike the past works of Fuelwood Cycle Surveys (early 1980s), the Beijer/Ministry of Energy National Assessment Programme (early 1980s) and the World Bank/Energy Sector Management Assistance Programme (ESMAP) Peri-Urban Charcoal and Fuelwood Programme and Forestry Sector Assessment (1985-1988). The Bess (1989) survey starts from the assumption that there is a major and growing demand for charcoal and that charcoal is produced to satisfy that demand.

Summary of dynamics and sustainability

Charcoal is produced from a variety of situations and systems. It is produced on a managed, sustainable basis in significant quantities on private small-holdings in high potential areas of Kenya. Usually, charcoal is produced as a by-product of land clearing wherever there is sufficient time and labour to produce it, and where a ready market for charcoal exists. It is produced, both on private as well as trust land, as a supplementary income activity, often when other sources of farm income are least available. In some cases, people produce charcoal, particularly on trust or communal lands in marginal areas, as their sole economic activity. Charcoal is produced in small quantities, generally in inefficient kilns, and is an occasional activity. It was also determined that between 6 and 8 tonnes of wood are required to produce 1 tonne of charcoal (13-17% efficiency).

After Beijer (1980-1981 and 1984-1988) subsequent studies have been carried out on urban and rural charcoal consumption. All these studies have indicated varying consumption levels and all have suffered from poor sampling techniques and/or from a lack of repetitive monitoring. Most previous estimates of charcoal consumption before Bess (1989) are based upon the Fuelwood Cycle Surveys and the Beijer work. Bess (1989) contends that the Beijer (1980-1981 and 1984-1988) and Kenya Energy and Environment Non-Governmental Organizations (KENGO)/Foundation for Wood-stove Dissemination (FWD) work estimates of household per capita (urban) consumption at 165 and 172 kg respectively are unrealistic within the large urban context since the percentage of income spent on charcoal would be unrealistically high (20-45%).

For his study, Bess (1989) stratified income groups and estimated maximum expenditures each group could be expected to pay for fuel. He assumed that the poorest stratum of the population could spend no more than 15 percent of their incomes on fuel while the highest stratum would probably spend no more than 5 percent of their income on fuel. By using average charcoal prices and quantities of purchase (bag or "tins"), he was able to calculate maximum consumption figures for different socio-economic groupings. For purposes of his study, he adjusted both urban and rural per capita consumption figures slightly upward to reflect non-household consumption. Bess (1989) contends that weights used by the Central Bureau of Statistics (CBS, 1988) are underestimated because they reflect patterns of more than 10 years (CBS Rural and Urban Energy Surveys of 1978-1979) before when real wood fuel prices were at least half as expensive as then (1989). Similarly, the Ministry of Energy's rural energy surveys (1986-1987) which sampled 25 districts, suffer from lack of repeat visits to households and from lack of any intensive monitoring of fuel use. The surveys thus give exaggerated consumption.

The Bess survey conducted interviews with charcoal dealers and transporters in Nairobi, and with producers, transporters and forestry officials in the rural areas of Kenya. Data from these surveys were compared primarily with previous Beijer Institute work carried out jointly by the World Bank and ESMAP between 1980 and 1985. For transport, marketing and pricing dynamics, the Bess study conducted three sets of surveys in and around Nairobi. Fifty-five retail and wholesale charcoal vendors were interviewed in 11 residential estates in Nairobi. During each of these sets of surveys, over 300 bags of charcoal were weighed (approximate average weight recorded was 34 kg which compares very well with the World Bank/ESMAP 1985 survey where the weight of a bag of charcoal was 35 kg using a smaller sample size while the First Kenya Fuelwood Cycle and Beijer Surveys showed bag weights of about 40 kg, but with considerable variation in measurements). Vendors in Nairobi were interviewed to obtain historical purchase and selling price information, stocks on hand, sources of supply and species of wood for charcoal. Further intensive interviews were carried out with large-scale vendors to verify observations on the dynamics of the market.

The study found out that there is seasonal variation in price. For example, road-side prices varied by as much as 50 percent between high and low demand.

The Bess Study measured the following parameters:

ˇ Weight of sack of charcoal.ˇ Current stock.
ˇ Number of bags sold per day; during highest/lowest price.
ˇ Purchase price from wholesaler.
ˇ Source (location of origin), including district.
ˇ
Tree species from which charcoal is made.ˇ Weight/price measurements (this was derived from charcoal purchased by survey enumerators in tins).

In addition, primary data from the ESMAP Retail Study was entered and tabulated. A revised questionnaire was developed for the next phase of the Bess Study and administered to 55 retailers in 11 stratified income divisions within Nairobi. This data were analysed and compared to charcoal marketing data obtained during the ESMAP Study, the Beijer work (1980-81), Central Bureau of Statistics (CBS) pricing data (annual statistical abstracts) and other sources of information. Additionally, information was obtained from the Ministry of Energy Rural Energy Surveys of 1986-87. Several key individuals involved in designing and carrying out the UNDP/World Bank ESMAP (1985) and related studies were interviewed for the Bess Study. Original primary data from these surveys were reviewed and analysed to gauge both the methodology employed and reliability of data updates on charcoal prices in Nairobi were undertaken.

4. UNDP/World Bank ESMAP Peri-Urban Study

The most extensive and comprehensive work on wood and charcoal production was carried out in Kenya under the Kenya Peri-Urban Charcoal and Fuelwood Survey of 1985 and its subsequent revisions (UNDP/World Bank ESMAP, 1985; World Bank, 1986 and World Bank, 1988). Numerous studies were carried out in 1985 to support a proposed large-scale forestry development programme to supply Kenya's future urban wood fuel demand. These included reviews of FD forestry management systems, wood and wood fuel prices, institutional structures and cost and price structures for all forestry products. The underlying premise of the original studies centred on the perception that Kenya was in the midst of a major wood fuel crisis and that immediate action was necessary if major economic and ecological disruptions were to be avoided.

Wood fuel and charcoal production for major urban markets (Nairobi, Kisumu, Nakuru and Mombasa) were examined, and information was obtained on:

ˇ Source of supplies.
ˇ Principal actors in production and supplies.
ˇ Transport costs and structures of supplies.
ˇ Margins accruing at each and every stage of supply.
ˇ Future trends and potential impacts on sources of supply, prices and the resource base.
ˇ Areas for policy intervention along the production and supply chains.

It is worth noting that the first drafts of the ESMAP surveys have been revised and no longer perceive a major wood fuel crisis.

The charcoal transport component of the ESMAP survey interviewed transporters at police checks leading into Nairobi. The original ESMAP survey cites over 300 such interviews. This component of the surveys suffers from the following:

ˇ Interviews were done during a one week period at a time of relative surplus of charcoal (September 1985).
ˇ Interviewing at police checks had a strong effect on reliability of responses.
ˇ No attempt at randomness of selection was made, thereby skewing results in ways that cannot be properly interpreted.

Nonetheless, the transport survey provide useful data on source and cost of supply, level of active participation of transporters in the charcoal business and destination of transporters that were compared with information generated during the Bess study (1989).

5. Ministry of Energy Rural Energy surveys

The MoE contracted with the CBS to undertake rural energy surveys in 25 districts in Kenya, covering almost 5,000 households. The surveys were carried out with the objective of determining energy consumption profiles (patterns and end-use consumption) and focused on both traditional and non-traditional fuels. Data were analysed on district-by-district basis. The survey questionnaire included questions on charcoal production both as a level of activity as well as a source of income. The questionnaire contained a minor intertemporal element of production, which was useful in indicating changes in production patterns over the past several years.

In addition, the MoE survey generated data on household consumption of charcoal. Unfortunately, the survey did not include repeat visits or intertemporal monitoring. This leads to bias, which makes it difficult to extrapolate household consumption on an annual basis. The survey shows that charcoal consumption is higher than previously estimated which is thought to be unlikely by Bess (1989). The data supports the assumption that rural charcoal consumption increases as rural households move increasingly into monetary economy and as other sources of fuel, namely wood, become less accessible.

The survey by MoE used both human and non-human resources. In terms of human resources, an analyst, support officers and other staff were required. Data in the field was collected by CBS enumerators using a questionnaire while analysis was done with a computer, using Dbase.

6. The World Wildlife Fund (WWF) Nakuru Survey

The World Wildlife Fund (WWF), in conjunction with the Bellerive Foundation, conducted a series of short charcoal surveys in Nakuru district in 1989. The purpose of the surveys was to determine the impact of charcoal production, and other wood fuel production, on the catchment area for Lake Nakuru and the Nakuru National Park. Interviews were carried out with charcoal dealers in and around Nakuru town concerning prices per unit measured and perceived sources of supply. The survey methodology and questionnaire were reviewed and provided several key insights which support observed patterns elsewhere.

7. Swiss Development Cooperation (SDC)/Rural Afforestation and Extension Scheme (RAES) micro-surveys

The Swiss Development Cooperation (SDC) funded a series of micro-level (sub-location) studies in 6 districts (Nakuru, Machakos, Nyeri, Kisii, Kakamega and Kwale) to determine the scope for intensifying forestry extension (WOODEC, 1987) for Rural Afforestation and Extension scheme (RAES) of Ministry of Environment and Natural Resources (MENR). These extensive surveys contain complete inventories of on-farm, trust, reserves and other forestry resources within the sub-locations studied. They contain relevant information for charcoal production but their extreme micro-perspective, and their tangential references to charcoal, make them useful for verification purposes only.

8. GTZ/Special Energy Programme (SEP) Improved Charcoal Production

The German Technical Cooperation (GTZ) Special Energy Programme (SEP) have undertaken limited charcoal production and pricing data collection during the course of their work in Lamu and Machakos districts (IPC, 1986; GTZ/SEP, Undated). Additionally, they have examined the potential for charcoal production as a by-product of land-clearing in two areas of the country.

Their pricing and source of production data are spotty but they have obtained useful information on:

ˇ Transport costs (tonne/km).
ˇ Load factors for transporters (tonnes and tonne/km).
ˇ Actual wood and producers in specific areas (price per m3).
ˇ Retail prices in urban areas (prices per tonne).

This information was used to compare with the MoE Rural surveys, the ESMAP and The World Bank/Forestry Department charcoal data, CBS pricing data and the earlier Beijer work.

9. Central Bureau of Statistics (CBS)

The CBS, in conjunction with the National Council for Science and Technology (NCST), carried out a household energy consumption survey in 1978. It focused on consumption of all fuels for domestic purposes. It was intended to obtain an accurate picture of domestic energy consumption at national level. The NCST designed the survey to be implemented through the Integrated Rural Survey (IRS) network of the CBS. The survey was administered in 1978 and published two years later (CBS, 1980).

The questionnaire was designed to get information on quantity of fuel used for a given reference period. Fuelwood was identified on a daily basis, charcoal, paraffin and liquefied petroleum gas (LPG) on a weekly or monthly basis while electricity consumption was copied from the latest billing. The survey did not derive relevant demographic or economic information. It was hoped that the energy survey results could be linked to the results from other household surveys but no such computer linkage was devised.

The sampling procedure was based on the national frame established by the CBS for the national integrated sample survey programme (IRS). This method employs cluster sampling based on 1 percent sample of the rural population and a 2 percent sample of the urban population. Primary sampling units (PSUs) were selected for rural areas on the basis of agro-ecological crop zones within each province. North Eastern province and four other districts are not included in the sampling frame. The PSUs were each broken down into three or four clusters of approximately 200 households. Two clusters were selected at random from each PSU and finally the total sample included 31 000 households (23 000 rural and 8 000 urban). For the energy survey, 10 percent of the full national sample was used, which means 3 647 rural and 1 877 urban households (total of 5 647) were surveyed (0.25% of all households in Kenya).

The survey was administered by the same enumerators that had been used for the different rounds of the IRS. They were all familiar with the areas being surveyed, both through aerial photomosaics and previous survey experience. A training session and a pre-survey test were held for each province. The survey was conducted in October-November 1978 with 350 enumerators supervised by respective district statisticians. The results were analysed manually first and later with a computer.

Results showed that the total wood requirement was estimated at 11.4 million tonnes or 16.0 million m3.

The CBS survey was well carried out but the results are inconclusive (Hosier, 1985). This can be attributed to weaknesses in the questionnaire design and presentation and analysis. The questionnaire ignored relevant data (income, demographic and price). There was little or no attempt to explain the results. The write up presents patterns of energy use but no discussion for their consistency or accuracy is done. The presentation of data by provinces, rather than agro-ecological zones, does not tell much in terms of the relationship between use and availability.

Currently, CBS carry out periodic (usually quarterly) spot market surveys of the retail price of charcoal. Prices are obtained in Nairobi, Mombasa, Kisumu and Nakuru on a basis of interviews with retailers. No weight measurements are taken and no verification of actual purchase prices is done. However, the data provides important guidance on charcoal price trends.

10. KENGO household users survey

The Kenya Energy and Environment Non-Governmental Organizations (KENGO) have conducted at least 2 limited surveys on household charcoal consumption. One survey was funded by the Dutch-supported Fuelwood Development Programme (FWD) and covered charcoal consumption in several areas in Nairobi. Retail charcoal prices and actual household expenditures on charcoal were obtained. Also collected were data on rates of adoption of improved charcoal stoves and inter-fuel substitution. However, sample methodology was non-random and non-scientific. Thus, results are biased and data can only be used for indicative purposes.

The main importance of the KENGO material lies with level of user acceptance and market penetration of improved charcoal stoves. This information has been compared with work carried out by Bess (1989) between 1984 and 1989, USAID work carried out under the Kenya Renewable Energy Development Project and that carried out through various agencies (ATI, CARE-International, USAID Office of Energy and Bellerive Foundation) to examine:

ˇ Average efficiencies of improved stoves relative to traditional stoves.
ˇ Growth rate of stove production.
ˇ Expected market penetration (absolute terms and percentage of total charcoal stoves sold and utilized)
ˇ Expected utilization rates.

This information has been compared with urban (and monetized rural) population growth rates in an attempt to estimate and project the charcoal conservation potential of new stoves.

11. Kenya Energy Fuelwood Project (Beijer Institute and MoE)

The Beijer Institute (Swedish Royal Academy of Sciences) and the Ministry of Energy (MoE) undertook numerous surveys both as part of government's fuelwood cycle survey and the Kenya Wood fuel Development Project (KWDP) in the early 1980s (Hosier, 1985, 1984). Several studies were commissioned under the Beijer Project, including a biomass resource assessment (O'Keefe et al., 1984). The project estimated spatial patterns of supply based upon their household and market surveys. However, their estimates of sources of charcoal supply suffer from lack of intertemporal surveying. Additionally, the study does not contain any interviews with producers or transporters.

The survey questionnaire was administered to 572 households (out of the sampling frame of 600) in high potential, medium potential and savannah regions of Kenya. The survey contains useful baseline data on charcoal consumption and prices, but virtually none on charcoal production.

The team also drew upon select works carried out in the 1970s and commissioned for the Project to produce projections on urban and rural household energy consumption (Barnes et al., 1984). The Beijer work formed the basis for the USAID-funded Kenya Renewable Energy Development Project (KREDP), the Dutch-funded Kenya Wood fuel Development Project (KWDP) and much of the biomass work carried out by the Ministry of Energy.

The Beijer work represents the most comprehensive attempt to estimate wood fuel use and production in Kenya. While its major strength lies with its demand/end use estimates, its greatest weakness lies with its supply estimates. The work overestimates the rate of forestry offtake, underestimates the rate of wood fuel conservation and does not place enough emphasis on the potential for inter-fuel substitution (Bess, 1989).

Subsequent work carried out by the Beijer Institute under KWDP shows that the original work did not realize the potential response of farmers to wood (not necessarily wood fuel) shortages. Hence, KWDP and other observers found that, in fact, woody biomass cover increases in certain areas (particularly high potential areas) with population growth. These observations, when compared with the original Beijer work, the ESMAP/World Bank and SDC/RAES micro-surveys and the MoE Rural Energy Survey, provide good benchmarks to estimate changes in woody biomass in select agro-ecological and economic zones. This has provided good coefficients on how much charcoal (as compared to other forestry by-products) can be expected to be produced in specific zones.

The original Beijer data provide useful indications of order of magnitude. They also provide important indicators of estimates of household energy demand which have been compared with other contemporary data and estimates. The data has also been entered into the LEAP (LDC Energy Alternative Planning) Model which has been reviewed extensively by Spence (1986). The LEAP model has drawbacks that limit its use for developing a baseline database and for making projections. These are:

ˇ Lack of proper representation of dynamic processes that may tend to modify projected supply-demand imbalances.
ˇ Prices are not presented as variables, leading to a wood gap.

This inherent bias towards a wood fuel gap stems from basic assumptions utilized in designing the LEAP model. The dynamic processes, further defined by the same worker (Spence, 1988) regard key factors which Bess (1989) addressed carefully and include:

a) Changing relative prices of wood products (KSh/m3 and KSh/tonne).
b) Changing patterns of tree planting and production (m3/ha), particularly on-farm, agroforestry and other price-induced responses to price changes.
c) Growth in rural demand for charcoal and other more convenient fuels induced by economic factors (e.g. increased monetization of rural areas) and wood availability.
d) Urban inter-fuel substitution effects (e.g. wood to charcoal, charcoal to kerosene or electricity) induced by scarcity, price and other factors.
e) Urban and rural charcoal conservation pattern induced by price changes, availability of more efficient devices and changes in attitudes.

12. Kenya Wood-fuel Development Project (Beijer Institute and MENR)

The Kenya Wood fuel Development Project (KWDP) is a project that was funded by the Dutch government and implemented by Beijer Institute (1984-1988) as a follow up of Kenya Fuelwood Project. The major focus of the project was agroforestry development. Several district surveys covering Kisii, Kakamega and Murang'a were carried out during the project (Ngugi and Bradley, 1986; Chavangi, 1984 and Kuyper and Bradley, 1985). Forestry inventory, production and household energy consumption data were generated during the course of the project which are of use in determining charcoal production and consumption in those areas. The major points of comparison regard:

ˇ Changing patterns of rural charcoal utilization.
ˇ
Charcoal production as an on- and off-farm activity.
ˇ 333Changes in woody biomass cover in high potential areas.
ˇ Uses of wood (e.g. building poles vs. fuelwood vs. charcoal, etc.) from trees grown on-farm.
ˇ Real prices of wood produced in high potential area.
ˇ Projections for planting rates, tree cover and prices based on changes on the farm.
ˇ Observed and anticipated environmental effects in high potential areas induced by increased tree planting.

13. Brokensha and Riley: Mbeere Wood-fuel Studies

One of the earliest systematic wood fuel production and consumption surveys carried out in the 1970s and early 1980s.

The findings from the survey are:

ˇ An average household must make between one and four fuelwood collection trips weekly, each of which takes about 2.5 hours (2.5-10 hours every week).
ˇ Due to time taken and difficult of collecting fuelwood, men are increasingly becoming involved in this activity.
ˇ Whereas only certain tree species have traditionally been used for firewood, increasing scarcity has meant that all species were used for firewood.
ˇ Charcoal production has become an important source of off-farm income generation, even though those doing it know the dangers of deforestation.
ˇ Many households are purchasing fuelwood in an area where, until recently, it was only bought by school-teachers and businessmen.
ˇ Fuelwood shortage is becoming a serious social problem.

This work and other work by Castro (undated) in Kirinyaga district, Mung'ala (1979) and Mung'ala and Openshaw (1984) in Machakos district point to trends in inter-fuel substitution, particularly from fuelwood to charcoal, in rural areas. A common major observation by Brokensha and Riley (1978) and Castro (undated) is that land adjudication and privatization tends to be a necessary component for on-farm tree planting. Their observation that tree cover increases with increased population densities in high potential areas predate and support the latter KWDP observations in Murang'a (Ngugi and Bradley, 1986), Kisii (Kuyper and Bradley, 1985) and Kakamega (Chavangi, 1984). The studies also revealed reduced charcoal production, which implies that returns accruing to other tree products are higher than those of charcoal are.

14. Forestry Department wood-fuel survey

The survey was carried out in 1980 to determine wood fuel consumption, demand and supply. It was based on the assumption that an energy crisis was in existence and hence the need to review the national energy strategy. Data was collected from 15 districts which were sampled from 4 agro-ecological zones (high forest, savannah, arid and Nairobi). Four different questionnaires, based on categories of consumers (domestic, commercial, institutional and industrial) were used to collect data. Random sampling was used to draw interviewees from the four categories of consumers. The total number of trading premises, institutions and industries in each district where sampling took place was compiled and used to estimate the gross national consumption. The 1979 provisional population census data were used to estimate domestic consumption.

The sample data were tabulated and analysed, making adjustments where necessary. Individual district per capita consumption was calculated and the mean of all districts taken as the national per capita consumption. In calculating the quantity of wood fuel consumed by trading, institutional and commercial sectors, the sample mean of the districts in the agro-ecological zones was calculated and then multiplied by total number of the districts in the zone. The total of the 4 zones was taken as the national consumption. On the other hand, industrial consumption was calculated by assessing all wood fuel-consuming industries in the country. The grand total of the domestic, commercial, institutional and industrial consumption was taken as the country's wood fuel consumption.

Data collection was done by 17 foresters and was indicated to have been inefficient due to logistical problems, time conflicts and use of insufficiently trained enumerators (Akinga, 1980).

Parameters collected for domestic consumption were:

ˇ Quantities of fuelwood, charcoal and paraffin used.
ˇ Prices of each fuel type.
ˇ Time spent gathering fuelwood.
ˇ Number of construction poles.
ˇ Price of poles.

The other questionnaires placed more emphasis on quantities consumed and purchase prices, with no attention paid to collection time.

The survey's findings

ˇ The tobacco industry in Kenya (in 1980) had an average requirement of 0.15 million m3 of fuelwood per year most of which is availed from farmlands where the crop is grown.

ˇ The tea industry's requirement then was estimated at 0.30 million m3 annually.
ˇ The national total wood-fuel consumption per year is 30.6 million m3 of which 22.7 m3 is fuelwood and 7.9 million m3 is charcoal (roundwood equivalent).
ˇ The domestic national wood-fuel consumption was estimated at 6.4 million m3 of charcoal while the commercial and institutional consumers take up 1.5 million m3. The remaining 0.01 million m3 is consumed by the industrial sector.
ˇ On per capita basis, fuelwood consumption is 0.928 m3 while the figure for charcoal is 111 kg, per year.

The figures given by this study are thought to be unrealistic due to the high conversion efficiency of wood to charcoal at 25 percent. This is too high given the nature of earth-kilns commonly used. Most estimates for earth-kiln efficiency place the figure close to 11 percent (Openshaw, 1978). Hosier (1985) has adjusted the figures based on 11 percent conversion efficiency (9 t of wood give 1 t of charcoal).

The study also came up with average wood fuel prices, availability indexes, average costs of production by ecological zones and sale price and profit margins (for FD production and sales).

It revealed that about 80 percent of all the wood fuel consumed comes from private farms, woodlands or trust lands while only 13 percent come from government-controlled forests. Forests under the county council supply 7 percent. It was further calculated that the 4 million m3 supplied by the forest estate was commonly consumed by the commercial, institutional and industrial sectors. About 8 million m3 of wood is converted to charcoal which is mainly used by urban households, hotels, butcheries, etc. The study concludes that use of charcoal in rural areas seems to be a luxury.

The survey's presentation circumvents the construction of any plausible explanation of observations (e.g. high per capita consumption of wood fuel for Nairobi and the arid zones, failure to explain figures for time spent gathering firewood in Nairobi, failure to explain magnitudes of arid zone figures for use of paraffin, etc.). The questionnaire did not elicit sufficient information relating to alternative fuel sources, response to shortage and income in order to paint a thorough assessment of the trends (Hosier, 1985). Also, there was no end-use information gathered and no information is given on the number of households actually making use of each fuel.

While the sample was nominally stratified by ecological zones, the stratification process and household selection processes are not clarified. The best standard way would have been that suggested by Warwick and Leininger (1975) which chooses the number of households in each stratum so that they are proportional to the total population of each stratum. In absence of this, it can only be assumed that the sample was either a haphazard sample or, worse still, an opportunity sample selected for the sake of convenience.

In terms of survey administration, the choice of foresters as enumerators could have been poor as they can be expected to induce a kind of "ingratiational bias" whereby respondents give the answer expected of them (Warwick and Leininger, 1975). A questionnaire about wood fuel consumption administered by foresters might be expected to yield unreliable data, particularly if the households were explained the relevance of the survey.

Analysis and presentation of the results is cursory and fails to make maximum use of all available data. Hosier (1985) intimates that the survey-derived estimates of per capita wood fuel consumption are high by international standards.

15. Kenya Forestry Master Plan (KFMP) wood-fuel assessment

Kenya Forestry Master Plan (KFMP, 1995) did significant work on wood fuel demand and supply estimates based on information presented by Bess (1989). Starting from Bess's base figures for the per capita charcoal and fuelwood consumption for 1990, the urban per capita consumption was projected to decrease so that from a range of 68-120 kg (average 90 kg) per capita in 1990, charcoal consumption in 2020 would range from 64 to 68 (average 67 kg) per capita. On the other hand, rural per capita charcoal consumption in 1990 was small (8-36 kg, or an average of 13 kg), and it was projected that it would remain constant through 1990 to 2020. Per capita firewood consumption was projected to decrease so that from a range of 324-402 kg or 0.45-0.56 m3 (excluding Nairobi which has a much lower consumption), or an average of 372 kg (0.52 m3) per capita in 1990, firewood consumption in 2020 would range from 287 (0.40 m3) to 350 kg (0.49 m3), or an average of 322 kg (0.45 m3), per capita [using a conversion factor of 1 m3 = 714 kg, air-dry weight (Openshaw, 1978)].

The total annual consumption of charcoal and firewood was projected by combining the population and the per capita annual consumption. The KFMP estimated that wood-charcoal conversion efficiency would improve gradually from 7.6:1 (13%) in 1990 to 5.95:1 (17%) in 2020.

KFMP (1995) projected that demand for wood fuel would rise steadily from 20.1 million m3 in 1995 to 40.1 million m3 as the country's population rises from 26.5 million people in 1995 to 57.9 million in 2020. During the same period, accessible wood fuel supplies were estimated to increase from about 18.3 million m3 in 1995 to 26.4 million m3 in 2020.

Based on the above projections, which are themselves based on the 1995 trends, the KFMP (1995) estimated that in the short term, the country would be able to meet its wood fuel requirements, although part of the supplies would be coming from non-sustainable sources (e.g. clearing of forests and woodlands) and wood fuel substitutes (e.g. agricultural residues, recycled wood from worn-out posts, construction props and forms, demolished houses, discarded furnishings, etc.). However, beyond year 2000, the increase in total wood supplies will not be able to meet increases in wood demand. Even when non-sustainable supplies and wood fuel substitutes are included, the total wood deficit is projected to increase to 6.8 million m3 in 2020, mainly manifested as wood fuel deficit.

This situation can, however, be avoided if a number of policy interventions, implemented by a set of programmes for the conservation, development and management of the forest and tree resources are put in place. This will translate into increased accessible wood supplies from indigenous forests, woodlands, bushlands, farmlands and settlement areas and forest plantations which will increase to almost double the 1995 levels. This will enable the country meet the growing demand for wood (mainly wood fuel).

16. Other studies and surveys

Many other surveys and studies have been conducted in Kenya that bear more on charcoal consumption and demand than on dynamics of production and distribution. These include work on energy-efficient stoves, renewable energy supply and utilization and institutional demand (Hyman and ATI, 1985; Jones, 1989 and Hankins, 1987). These works were used to develop a more comprehensive understanding of the factors of demand. A demand system model has been built upon this information.

The key variables of the model address:

ˇ Household and institutional charcoal energy conservation prospects including number of improved stoves, growth in demand and improved efficiencies, among others.
ˇ Potential for inter-fuel substitution and its effects on charcoal demand (real fuel prices, demand elasticity's, substitution of kerosene/paraffin and electricity for charcoal and product adoption rates).
ˇ
Other factors affecting demand (transport costs, licences, taxes and other enforcement costs).

Annex 1-(i): Suitable Woody Species for Wood fuel in Kenya (Agatsiva, 1997)

Acacia brevispica
Acacia bussei

Acacia drepanolobium
Acacia gerardii

Acacia hockii

Acacia lahai

Acacia mellifera

Acacia nilotica

Acacia nubica

Acacia reficiens

Acacia senegal

Acacia seyal

Acacia tortilis

Acacia xanthophloea

Afzelia quanzensis
Albizia amara

Albizia anthelmintica

Balanites aegyptiaca

Barleria spinisepala

Bauhinia taitensis

Boscia angustifolia

Combretum apiculata

Combretum brownii

Combretum constrictum

Combretum hereroensii

Combretum molle

Commiphora africana

Terminalia spinosa

Commiphora schimperi
Croton dichogamus

Dalbergia melanoxylon

Euclea divinorum

Grewia bicolor

Grewia plagiophylla

Grewia similis

Grewia vilosa

Maytenus
spp
Olea europaea
var. africana
Tarchonanthus camphoratus

Terminalia brownii

References

Agatsiva JL. 1997. Fuelwood as indicators in land degradation: Contribution to the National Land Degradation Assessment and Mapping in Kenya. Government of the Republic of Kenya, Royal Netherlands Government and United Nations Environment Programme (UNEP).

Agatsiva JL. 1987. Timber Volume Assessment for Management of a Tropical Forest: The Role of Remote Sensing. MSc Thesis, University of Manitoba, Winnipeg, Canada.

Akinga WW. 1980. Woodfuel Survey in Kenya. Forestry Department, Ministry of Natural Resources. Nairobi, Kenya (Unpublished).

Barnes C, Ensminger J and O'Keefe P. 1984. Wood, Energy and Households: Perspectives on Rural Kenya. Stockholm: The Beijer Institute and Scandinavian Institute of African Studies.

Bess M. 1989. Kenya Charcoal Survey. Final Report and Annexes. Prepared for the Long Range Planning Unit, Ministry of Planning and National Development and Carleton University by Bess Associates Ltd. (Development Assistance Consultants). Nairobi, Kenya.

Brokensha D and Riley B. 1978. Forestry, Foraging, Fences and Fuel in a Marginal Area of Kenya. USAID, Washington DC, 1978.

CBS. 1975. The National Integrated Sample Survey Programme, Phase I: October, 1974-August, 1979. Nairobi, Kenya: NISSP Series, Working Paper No. 1.

CBS. 1980. Results of Rural/Urban Survey 1978/79: Energy and Power Module. Ministry of Finance and Planning, Central Bureau of Statistics. Nairobi, Kenya.

Chavangi NA. 1984. Cultural Aspects of Fuelwood Procurement in Kakamega District. Working Paper No. 4, Kenya Woodfuel Development Programme, Nairobi, Kenya.

Grunblatt J, Ottichilo WK and Sinange RK. 1989. A hierarchical approach to vegetation classification in Kenya. African Journal of Ecology. 27: 45-51.

GTZ/SEP. Undated. Charcoal production and research activities within the Special Energy Programme, Kenya and woodfuel plantation in Kenya.

Hankins M. 1987. Renewable Energy in Kenya.

Hosier R. 1981b. Something to Buy Paraffin With: An Analysis of Domestic Energy Consumption Patterns in Rural Kenya. PhD Thesis, Clark University.

Hosier R. 1984. Domestic Energy Consumption in Rural Kenya. Results of a Nationwide Survey. In: Wood, Energy and Households: Perspectives on Rural Kenya. Barnes C, Ensminger J and O'Keefe P. (eds.). Stockholm: The Beijer Institute and Scandinavian Institute of African Studies.

Hosier R. 1985. Energy Use in Rural Kenya. Household Demand and Rural Transformation Stockholm. Stockholm: The Beijer Institute and the Scandinavian Institute of African Studies.

Hyman E and ATI. 1985. The Experience with Improved Charcoal and Wood Stoves for Households and Institutions in Kenya. Bellerive Foundation and Institutional Energy Efficient Stoves Programme, various project documents.

IPC. 1986. Interdisziplinarés Project Consult (IPC). Options for commercial charcoal production in the coastal region of Kenya, second draft. Frankfurt, A/M.

Jones HM. 1989. Energy Efficient Stoves in East Africa. USAID, Washington DC.

KFMP. 1995. Kenya Forestry Master Plan. Development Programmes. Ministry of Environment and Natural Resources, Forestry department. Nairobi, Kenya.

KFMP. 1992. Kenya Forestry Master Plan. Annex VI, Bio-energy. First Incomplete Draft (FID). June, 1992. MENR and FINNIDA.

Kuyper JBH and Bradley PN. 1985. Woodfuel and Agroforestry in Kisii District. Working Paper No. 7, Kenya Woodfuel Development Programme, Nairobi, Kenya.

Mung'ala PM and Openshaw K. 1984. Estimation of Present and Likely Future Demand for Fuelwood and Charcoal in Machakos District, Kenya In: Wood, Energy and Households: Perspectives on Rural Kenya. Barnes C, Ensminger J and O'Keefe P. (eds.). Stockholm: The Beijer Institute and Scandinavian Institute of African Studies.

Mung'ala PM. 1979. Estimation of Present and Likely Future Demand for Fuelwood and Charcoal in Machakos District, Kenya. Masters Thesis, University of Dar es Salaam, Tanzania.

Ngugi A and Bradley P. 1986. Agroforestry, Soil Conservation and Woodfuel in Murang'a District, Parts I and II, Kenya Woodfuel Development Programme, Nairobi, Kenya.

Openshaw K. 1978. Woodfuel .... A Time for Reassessment. Natural Resources Forum. 3:35-51.

O'Keefe P, Raskin P and Bernow S. 1984. Energy and Development in Kenya. Opportunities and Constraints. Stockholm: The Beijer Institute and the Scandinavian Institute of African Studies.

Republic of Kenya. 1988. National Energy Policy and Investment Plan. Nairobi. Ministry of Energy and Regional Development.

Spence RW. 1986. A National Model of Kenya's Wood and Charcoal Sectors: Structure, Projection and Alternative Simulations. Technical Paper No. 86-11, Ministry of Planning and National Development.

Spence RW. 1988. Kenya Woodfuels Model: Revised Base Case and Further Analysis of Major Policy Alternatives. Technical Paper No. 88-03, Ministry of Planning and National Development, Long Range Planning Unit.

Uganda Forest Department. 1992. Uganda National Biomass Study Phase I . Kampala, Uganda.

UNDP/World Bank ESMAP. 1985. Kenya: Peri-Urban Charcoal and Fuelwood Study Phase I Report. Working Papers I-V, and other various working documents.

Warwick DP and Leininger CA. 1975. The Sample Survey: Theory and Practice. New York: McGraw-Hill Book Company.

WOODEC. 1987. Baseline Surveys for Intensified Forestry Extension and Future Impact Evaluation. (Nakuru, Machakos, Nyeri, Kisii, Kakamega and Kwale districts). Prepared for the Rural Afforestation and Extension Schemes (RAES) of Forestry Department, Ministry of Environment and Natural Resources (MENR) and Swedish Development Cooperation (SDC).

World Bank. 1988. Kenya Forestry Sector Review. Main Report and Annexes I-VI.

World Bank. 1986. Kenya Urban Woodfuel development Programme, various working documents.

 

Lesotho

Background Report:
"An Update of the Lesotho Wood-fuel Database"
by
Mrs N. L. Masilo,

Forestry Division,
Ministry of Agriculture,
P. O. Box 774, Maseru 100. Lesotho
This is a report of 5 pages, produced under TCDC arrangements, which describes the wood energy sector in Lesotho and the state of the art concerning wood-fuel information. The full report is not reproduced here but may be requested to the author or to M.A. Trossero, FAO FOPW, Rome.

A short description of this paper is given under "Synthesis of the workshop - workshop activities - presentation of country reports - Lesotho".

 

National Arrangements and Capacity
to Collect Wood Energy Information and Statistics

by

Mrs N. L. Masilo,
Forestry Division,
Ministry of Agriculture,

Background

Lesotho is a small landlocked highland country of approximately 30 350Km2 situated in the Eastern part of the Republic of South Africa. Its population of 1,8 million at a growing rate of 2.6% p.a. Population density is on average 67 per Km but reaches up to 200 per Km2 in the lowlands (1 500m-1 800m above sea level).

The country's agricultural development is hampered by adverse climatic conditions 600 to 900mm of rainfall occurring erratically mainly in summer. About 70% of the land is used for agricultural purposes. Communal grazing land is overstocked and what is left as cropland is of low productivity. One of the most pressing problems of the country is soil erosion whereby it has been estimated that in only a decade the area of arable land has decreased from 13% to 9%. Furthermore agriculture contributes to only 10 - 15% GNP.

In land use, Forestry plays a small but significant role. The importance of afforestation was realized in the country and around 1855 initiatives started. It is from that period up to present that pure afforestation programs and projects with a tree-planting component are still on going. In the last three decades two approaches were/are pursued;

ˇ State Forestry approach (1973): to meet the energy demands, the Lesotho Government originally decided to produce fuel wood and timber (i.e. a joint venture with GOL owning 80% and communities 20% of the resource. This was under the Overseas Development Agency (ODA) and Anglo American De Beers Company and the project was called the Lesotho Woodlot Project. This project managed to successfully plant 12 000ha, approximately 300 woodlots country wide, of mainly Pinus and Eucalptus species.

ˇ
  Social Forestry approach (1993) - as a reaction to limited success of the state woodlot approach, an alternative approach was adopted within the Forestry Division namely the social Forestry approach. Implementation of the Division's objectives is achieved through the Social Forestry and Conservation Project (K_W/GTZ support). The data which will be presented in this paper refers mainly to collection of data on fuel wood supply however projections are still based on mainly the information provided by the Lesotho Energy Master Plan 1986.

1. Description of institutional arrangements between forestry and energy institutions
for the administration of the wood energy sector

Forestry plays an important role of ensuring the meeting of set targets based on surveys carried out by the Energy department, which is also, a Government entity. It is within this capacity that as stakeholders together with Non Governmental Organizations (NGOs) that they are members of the SADC Sub-committee on New and Renewable Energy Sources (NRSE) (list attached). The final development of the Lesotho Energy Masterplan has and is a product of close collaboration between all the stakeholders. Surveys and other data collection methods are carried out, new technologies tried and replicated. Strategy 13 of the Forestry Division directly addresses biomass energy conservation and an anticipated result is `wide use of biomass fuel efficient stoves in rural areas'. Appropriate Technology Section and other stakeholders address this issue from its different dimensions.

The Southern African Development Community `Mission Statement'; Energy Protocol commits member state to co-operation and harmonising of national and regional energy policies, strategies and programs on the basis of common interest. To ensure that reliable, environmentally sustainable, least cost energy supplies are in place to assist in the attainment of economic efficiency and rural development.

2. Institutional roles and capabilities

2.1 Institutions and responsible for the acquisition of data on woodfuels consumption

Department of Statistics

2.1.1 Resources deployed

United Nations Population Fund (financial, technical and adminstrative support.
United Nations Children's Fund
Country Support Team

2.1.2 Methods of assessment (last assessment)

Censors procedures (collecting , compiling, evaluating, anlyising and publishing demographic, social and economic information, at a particular time for a particular population.

2.1.3 Frequency of assessment

10 year censors, last one 1996

2.1.4 Items covered (parameters and reporting units)

Percentage distribution of households by housing unit and heating fuel
Percentage distribution of households by households by Districts
Percentage distribution of households by type of housing unit, and principal lighting fuel

2.2 Institutions responsible for the acquisition of data on wood fuels supply

Forestry Division; NGOs; Community Based Organizations, Municipality;Projects;
Private enterprises

2.2.1 Resources deployed

Consultants, Technical Assistance
Donor Funding
GOL personnel

2.2.2 Methods of assessment

Surveys
Trees per hectare; calorific values;
Other socio-economic studies
Participatory Methods through the Extension service of the Government

2.2.3 Frequency of assessment (last assessment)

1999
Ongoing but not well coordinated

2.3 Institutions responsible for the analysis of supply/demand balance and for
forecast of future scenarios

Forestry Division
Energy Department

2.3.1 Resources deployed

GOL personnel

2.3.2 Source of demographic and economic data and projections

Department of Statistics

2.3.3 Reporting units (national, provincial, scenarios)

Department of Energy
Forestry Division

Malawi

Wood Energy Situation in Malawi

by:

R.F.E. Mumba
FSTCU, Department of Forestry
Lilongwe 3, Malawi

Introduction

The SADC Region comprises of the following member states: Angola, Botswana, Democratic Republic of Congo, Lesotho, Malawi, Mauritius, Mozambique, Seychelles, South Africa, Swaziland, Tanzania, Zambia and Zimbabwe.

Wood is the largest source of energy in the SADC Region; over 80 percent of the population depend on wood as energy source. Total wood requirements is estimated at more than 100 million cubic meters a year with an average per capita wood consumption of 1.5 cubic meters per year.

This high dependence on wood as source of energy is contributing to diminishing wood resources. It is reported that the effects of deforestation extend over 100 Km radius around major cities.

As a case study, this paper outlines the wood energy situation in Malawi.

1. Wood energy situation In Malawi

1.1 Population and energy usage

Malawi had a population of 9 million people in 1998, living in an area of 118,000 sq. Kilometres (National Statistical Report 1998). The rate of population growth is estimated at 3.2 percent per annum and 85 percent of the population leaves in rural areas. About 93 percent of the population depend on wood as energy source while the remaining 7 percent derive energy from other sources such as electricity, petroleum, coal and others (Table 1).

Table 1. Sources of energy

Type of Energy

Percentage of usage

Fuelwood

93

Petroleum

3.5

Electricity

 2.3

Coal

1.0

Other biomass

0.2

Source: National Energy Plan, 1988 - 1997

This high dependence on wood as a source of energy is contributing to deforestation, which is estimated at 1.6 percent per annum.

1.2 Sources of wood

The total forest area covers about 26 428 km2 of Malawi's land area. Indigenous trees/forests on customary cover 8 913 km2 while forest reserves cover 7 800 km2. More details on wood resources are presented in Annex l.

Most of the wood is obtained from customary land because of strict rules of access to the government forest reserves, and game reserves and national parks. In fact, wood collection in national parks the game reserves is prohibited.

Since most of the wood fuel is obtained from customary land, and that wood productivity is also low, land degradation is accelerating. Table 2 gives information on sources of firewood for 9 out of 27 districts. The survey was conducted in rural areas, where a large population (85%) of Malawi lives.

Table 2. Source of firewood (percentage)

   

SOURCE

 

District

Customary Land

Forest Reserve

Own Woodlot

Karonga

61

11

32

Mzimba

82

 3

18

Dedza

40

28

37

Kasungu

64

16

20

Nkhotakota

62

13

23

Mangochi

65

17

18

Blantyre

46

10

38

Zomba

30

28

45

Chikwawa

93

 5

 2

National

60

15

25

Source: Department of Forestry, 1993

As pressure on the available wood resources is increasing, it is becoming difficult to obtain wood, especially for women who do most of the collection. Both time and energy are lost on wood collection as wood resources are receding into distant places. Tables 3, 4 and 5 give information on how difficult it is to collect wood and frequency of firewood collection per week.

Table 3. Difficulty in firewood collection (percentage)

District

Easy

Difficulty

Don't collect

Charring

44

56

0

Mzimba

47

53

0

Dedza

43

52

5

Kasungu

33

67

0

Nkhotakota

32

68

0

Mangochi

38

60

2

Blantyre

51

44

5

Zomba

46

53

1

Chikwawa

30

70

0

National

40

58

2

Table 4. Distance covered to collect firewood (figures in percentage)

 

Distance

DISTRICT

1Km

1 - 3 Km

3 - 5Km

5 Km and above

Karonga

56

16

18

 6

Mzimba

38

40

18

 3

Dedza

42

35

15

 6

Kasungu

44

34

18

 4

Nkhotakota

27

16

32

23

Mangochi

37

35

22

 5

Blantyre

50

20

10

10

Zomba

54

23

 9

 5

Chikwawa

38

33

15

12

National

43

28

17

 8

Table 5. Frequency of firewood collection per week (figures in percentage)

 

Frequency

District

Once

Twice

3 Times

Over 3 Times

Karonga

40

24

15

16

Mzimba

42

33

10

10

Dedza

37

28

 5

19

Kasungu

48

25

13

10

Mkhotakota

68

23

 1

 6

Mangochi

57

20

 5

12

Blantyre

56

16

 7

8

Zomba

40

25

 5

21

Chikwawa

47

33

12

 7

National

48

25

 8

12

Source: Department of Forestry (1998):

1.3 Demand for wood fuel

In 1995, 12.98 million m3 of wood were consumed and in 1996, the demand was 14.28 million m3, indicating a growth of 10 percent. Households consume about 70 percent of the wood fuel while the rest is consumed by industries, mainly agro-based.

Based on the per capita consumption of 2 m3/a and that 93 percent (8.37 million) of the population depend on woodpile, then 18 million m3 is estimated to be the demand for wood fuel for the year 2000.

2. Strategies used in creating wood energy sources

2.1 Conservation of indigenous forest resources

Most of the wood for fuel is obtained from customary land. Game parks are conservation of wood resources on customary land through empowerment of local communities to manage the forest resources has a lot of constraints. Some of the constraints are limited resources to mobilize the local institutions and communities.

2.2 Afforestation

This is the most common strategy being pursued. It involves tree planting by individuals, education and training institutions the government and private companies.

2.3 Plantation establishment

The government has established about 23000 ha of fuelwood plantation under the World Band and NORAD funding. Most of the plantations have been established with fast exotic species, mostly of Eucalyptus (over 80%). The World Bank funded the Wood Energy Project, which established 18000 ha while NORAD funded the Blantyre City Fuelwood Project under SADC status. About 5000 ha were established between 1986 to 1992.

While most of the Wood Energy Project Plantations were established in the Government Forest Reserves, the Blantyre City Fuelwood Project establish the Plantations on Customary Land and the plantations are being handed over to the local communities for management under its phase lll implementation schedule.

Most of the plantations established under Wood Energy Project are far from the major cities. This results into high cost of transportation especially now that the price of petroleum products has gone up astronomically.

2.4 Tree planting by communities

Under the tree-planting programme, which started in 1976, about 14 million tree seedlings are planted every year by different categories of the population. It has been reported that about 70 percent of these survive (Malawi Government, 1989). But the focus is on exotic tree species like Eucalyptus, which are favoured by communities because of fast growth and straightness. The use of heavy branching species which produce high biomass should be encouraged.

High rate of population growth, impacting on available land for agriculture, precludes tree planting. The introduction of agroforestry by the Malawi Agroforesty Project is having a positive impact on both the improvements of agricultural production and fuelwood supply.

2.5 Recycling of waste

A number of technologies have been developed and introduced to utilize waste such as paper, residuals and sawdust but the adoption is limited. Briquette making by using wastes is one of the technologies.

2.6 Efficient use of fuelwood

One of the factors for high demand for wood energy is the use of inefficient methods. Over 80 percent of the population in rural areas use open fire methods of cooking which is wasteful. The Energy Studies Unit (19840 reported that the use of improved ceramic stove was 30 percent more efficient (saving wood fuel by 50 percent) than the open fire method which has a heats utilization efficiency of 10 percent. The use of the improved ceramic stove is restricted to the urban areas because most of the rural population cannot afford to buy it.

Most of the wood fuel used in urban centres is charcoal and most of this charcoal is produced by villagers, using the traditional method - earth mound. Studies done by the Malawi Charcoal Project (1988) indicated that the improved method of half-orange kiln was 50 - 65 percent more efficient than traditional earth mounds.

3. Existence of wood energy institutions - Achievements and constraints

3.1 Achievements

In 1983, the Malawi Government created the Energy Studies Unit within the Department of forestry under the World Bank Wood Energy project. The mandate of the unit was to carry out studies in the use of energy and provide information for the formulation of the energy policy.

The unit carried out extensive studies on the wood energy issues and this resulted into the following developments:

ˇ establishment of fuelwood plantations, such as the Blantyre City Fuelwood Project and Mulanje Government Fuelwood Plantations which are 5000ha and 2800 ha, respectively.
ˇ introduction of improved ceramic stoves for both firewood and charcoal.
ˇ introduction of improved kilns for charcoal production.
ˇ improvement of the efficiency on the curing of tobacco from 42 cubic metres of wood to 14 a kilogram of cured tobacco.

Other institutions involved in the fuelwood studies are the National Statistical Office, the University of Malawi, the Bureau of Standards and the Agricultural Estate Extension Service Trust.

3.2 Constraints

ˇ Funding
ˇ Limited manpower
ˇ Effective coordination with other relevant stake holders



Mozambique

Background Report :

Country Report on Woodfuels Review and Assessment
by
Pedro Duarte Mangue
and Mandrate Oreste Nakala
Forestry Research Center
Maputo, Mozambique

This is a report of 23 pages, produced under TCDC arrangements, which describe in detail the wood energy sector in Mozambique and the state of the art concerning wood-fuel information.. The full report is not reproduced here but may be requested to the authors or to M.A. Trossero, FAO FOPW, Rome.

A short description of this paper is given under "Synthesis o the workshop - workshop activities - presentation of country reports".

 

National Arrangements
and Capacity to Collect Wood Energy Information and Statistics

by

Mr Pedro Duarte Mangue,
Forestry Research Center
Maputo, Mozambique

1. Institutional arrangements between Forestry and Energy institutions

The Ministry of Agriculture and Rural Development through its National Directorate of Forestry and Wildlife (DNFFB) is the main institution that has the mandate of managing and controlling the utilization of the country wood energy resources. Whilst the Ministry of Energy and Natural Resources is responsible for defining the policy and strategy on domestic energy, chiefly around urban areas.

2. Institutional roles and capabilities

The role of DNFFB is to collect information on number of licenses (Forestry permits) issued at provincial level by the Provincial Services of Forestry and Wildlife (SPFFB) and create the Forest Resource Database. The information on licenses consists on size of the area and the cubic meters of round wood likely to be harvested or the number of charcoal bags to be made.

The SPFFB consist of the head of services, administration and accounting, and the body of forest and game scouts. The role of SPFFB is to issue felling licenses; collect the license royalty fees and revenues from penalties due to transgressions. The number and the capabilities of scouts vary from province to province. The forest and game scouts have the overall responsibility of controlling the transit permits, in order to check whether the commodities being transported are licensed or not, as well as the kinds and quantities transported.

3. Institutions responsible for the acquisition of data on wood fuels consumption

The institution responsible for the acquisition of data on wood fuels consumption is the National Institute of Statistics within the Ministry of Plan and Finance.

For the purpose of planning this activity should be done by the above institution in co-ordination with the Ministry of Energy and Natural Resources; Ministry of Agriculture and Rural Development; and Ministry of Environmental Co-ordination.

4. Institutions responsible for the acquisition of data on wood fuels supply

The institution responsible for the acquisition of data on wood fuels supply is the National Directorate of Forestry and Wildlife.

This activity should be carried out in co-ordination with the Ministry of Energy and Natural Resources; Ministry of Plan and Finance; and Ministry of Environmental Co-ordination.

4.1 Resource deployed

Funds from World Bank and some Agencies (like SIDA from Sweden, GTZ, and FAO); and consultants from foreign universities (University of Twente, The Netherlands; University of Cape, RSA) or local university (UEM, Department of Chemistry and/or Faculty of Agriculture and Forestry Engineering).

4.2 Methods of assessments

The studies were done on randomly selected households; markets; along the main entrance areas and some in production sites. Maputo was the favourite place for most of those studies, probably due to safety reasons and the high demand, particularly of charcoal and wood fuel.

4.3 Frequency of assessment

Most of the studies carried out up to now were project driven. Therefore, there is no defined calendar neither programme to carry on regular assessment on woody fuels. Besides, most of the information when available, is scattered and apparently without use, at least for planning purposes.

4.4 Items covered

The bulk of the studies are concerned with charcoal and fuelwood consumption, price, means of transport, production sites and users, aiming to gather as much information as possible for a biomass energy strategy. Some studies do some comparative analyses with alternative sources of energy like kerosene, LPG, coal and electricity.

5. Institutions responsible for the analysis of supply/demand balance and for prediction of future scenarios.

There was a unity within National Directorate of Forestry and Wildlife called Unity of Biomass Energy (BEU), but since was created outside national woody energy strategy ceased its functions. Most of the studies done during nineties were under this Unity.



Namibia

Background Report:

Wood-fuels Review and Assessment :
Namibia Country Report

by
H.O. Kojwang10

Ministry of Environment and Tourism, Directorate of Forestry,
Private Bag 13346, Windhoek, Namibia.


This is a report of 12 pages, produced under TCDC arrangements, which describe in detail the wood energy sector in Namibia and the state of the art concerning wood-fuel information.. The full report is not reproduced here but may be requested to the author or to M.A. Trossero, FAO FOPW, Rome.

A short description of this paper is given under "Synthesis o the workshop - workshop activities - presentation of country reports".

National Arrangements and Capacity
to Collect Wood Energy Information and Statistics in Namibia

by
Moses Chakanga,

Ministry of Environment and Tourism, Directorate of Forestry,
P/Bag 13346, Windhoek, Namibia.



1. Institutional Arrangements between Forestry and Energy institutions for the administration of wood energy sector

The Ministry of Environment and Tourism and the Ministry of Mines and Energy are the two main institutions for the administration of wood energy in Namibia.

Directorate of Forestry: The Directorate of Forestry, in the Ministry of Environment and Tourism, is mandated to administer the country's forest resources. The forest resources are an important source of:

ˇ Wood energy (firewood and charcoal). Firewood is used by rural and low-income urban households for cooking. According to the Ministry of Mines and Energy, about 90 percent of the population use firewood. On the other hand, charcoal is mainly used for braai and it is a major commodity for export to South Africa and Europe.
ˇ
Food, such as fruits, nuts, edible caterpillars and birds, in the rural areas.
ˇ
Materials for farm and household implements in the rural areas.
ˇ
Crafts and medicine for subsistence and commercial consumption
ˇ
Fodder for livestock
ˇ
Wildlife habitat for tourism industry

Energy for cooking derived from firewood is currently the most important domestic requirement satisfied by the exploitation of natural forest resources. The Directorate of Forestry controls the use of forest resources through the issue of permits to individuals or institutions who exploit the resources for commercial purposes.

Directorate of Energy: The Directorate of Energy in the Ministry of Mines and Energy is responsible for the development of all types of energy, including wood energy, in the country.

The Energy policy commits the government to supporting the development of renewable energy sources and technologies appropriate to poor rural communities.

The Ministry of Mines and Energy hosts the National Biomass Steering Committee. The members of the steering committee are Directorate of Energy (Chair), UNDP-UNESCO, Desert Research Foundation of Namibia (DRFN), Association for Local Authorities in Namibia (ALAN), Namibia NGO Forum, and Directorate of Agricultural Research and Training. Among the several terms of reference for the steering committee, one is to co-ordinate and liaise at national and regional level with organizations and partners involved in biomass energy conservation.

The Ministry of Mines and Energy also promotes the use of efficient wood stoves and is carrying out a Biomass Conservation Strategy Project. The Directorate of Forestry could collaborate with Mines and Energy by promoting the use of efficient stoves in its community forestry operational areas. The Ministry of Mines and Energy has several stove models that have been tested for their energy efficiency. The Directorate of Forestry in cooperation with other stakeholders, such as NGOs, could introduce the stoves to their focal communities and assess opportunities and constraints with regards to social acceptability. The Directorate of Forestry and other stakeholders could also identify women and men for setting up stove manufacturing enterprises.

2. Institutional roles and responsibilities

2.1 Institution(s) responsible for the acquisition of data on wood fuels consumption

The institutions mainly responsible for acquisition of data on wood fuels are the Directorate of Forestry, and the Directorate of Energy.

2.1.1 Resources deployed: Personnel, measuring instruments, and vehicles

n.a.

2.1.2 Methods of assessment

Stratified simple random sampling using structured questionnaires has been used in the assessments carried out by both the Directorate of Forestry and Directorate of Energy.

2.1.3 Frequency of assessment (last assessment)

At present there is no stipulated regular period for carrying out the assessment. The assessments are carried out at an ad hoc basis. The Directorate of Forestry carried out the first assessment in June 1996. The report was compiled in February 1997 (Kloebe and Omwami 1997). Since then no other assessments have been carried out.

The Directorate of Energy carried out a study on energy consumption patterns in Namibia in 1997 (Wamukonya 1997).

2.1.4 Items covered (parameters and reporting units)

The assessment carried out by the Directorate of Forestry covered the items in Table 1.

Table 1. Items covered in wood consumption survey

Item

Unit of measurement

Reporting units

Firewood

 kg

 kg/person/day; metric tons/year; metric tons/region

Charcoal and Briquettes

 kg

 kg, metric Tons

Mopane roots (decorative/ornamental roots)

 kg

 kg; metric tons

Timber

 cubic metres

 cubic metres

Construction and Fencing Poles

 number of poles

 Number of poles by diameter and height; 
 cubic metres/ homestead

 height, metres

 diameter in centimetres

Wood carvings

 kg

 kg; metric tons

[NOTE: The report from the Directorate of Energy (Wamukonya 1997) was not available at the time of writing this document.]

2.2 Institution(s) responsible for the acquisition of data on wood fuels supply

The Directorate of Forestry is the institution responsible for forest inventory in Namibia. It is capable of providing data on wood fuels supply in the country. Starting from January 1995 the Directorate of Forestry is carrying out forest inventory in the north/north eastern part of the country. So far nine areas have been inventories. The areas include specific community/state forests and administrative regions.

2.2.1 Resources deployed

The resources deployed are: Personnel, All Terrain Vehicles (ATVs), 4x4 vehicles, camping equipment, and computers. The Directorate of Forestry of Forestry has developed good capacity for forestry inventory. It has a well-equipped and manned Forest Inventory and Mapping Section. It also has a National Remote Sensing Centre (NRSC).

2.2.2 Methods of assessment

Stratified systematic cluster sampling is used.

2.2.3 Frequency of assessment (last assessment)

This is the first time a large-scale forest inventory has been carried out in Namibia. In its on-going Criteria and Indicators process, the Directorate is proposing a 5-10 year frequency of assessment to re-measure selected permanent measurement plots for purposes of monitoring the forest resources.

2.2.4 Items covered (parameters and reporting units)

Tables 2 to 4 show the items measured in the forest inventory. Table 5 shows sample results for West Tsumkwe area.

Table 2. Stand description (the area surrounding the clusters or sample plots)

Category

Item

Unit of measurement

Reporting Unit

The Environment

Land type

Classes



Area in ha, Percentages (%) of
categories in the inventory area.

The categories/items are also
used as `group by' units for
various calculated tree variables
(such as tree volume etc.).

Geology

Classes

Mean height of woody vegetation

Meters

Soil texture

Classes

Soil colour

Mussel soil colour chart

Land use

Permanent or shifting cultivation

Classes

Grazing

Classes

Cutting of fuelwood or timber

Classes

Ownership including occurrence
of fencing in communal land

Classes

Damages

Cause of damage on the trees and severity

Classes

Table 3. The following main characteristics are measured for the trees

Category

Item

Unit of measurement

Reporting unit

Tree size

Species

Genus and species name

 

DBH

mm

Volume in cubic metres

Height

meters

canopy diameter

meters

Area in square meters;
canopy cover in percent

Sawlog length (& DBH)

meters

Sawlog volume in cubic metres

Biomass

Weight of sample discs in grams

Biomass in kg and metric tons

Timber quality

Sawlog (Timber) quality

Quality class

Timber volume in m3 grouped
by quality class

Damage to trees

Length of deformed base

metres

metres

Reason for damage

Reason class (fire, insect etc)

Area in ha, percent (%)

Degree of damage

Severity class

Area in ha, percent (%)

Table 4. The following characteristics are measured for the shrubs

Item

Unit of measurement

Reporting unit

Species

Genus and species

Genus and species

Height

meters

Number of species by 8 height classes

Crown diameter

meters

Number of species by 8 crown diameter classes

2.3 Institution(s) responsible for the analysis of supply/demand balance and for the
forecast of future scenarios

At present no institution performs analysis of supply/demand balance and prediction of future scenarios. However, this task is the responsibility of the Central Bureau of Statistics at the National Planning Commission. The role of Directorates of Forestry and Energy would be to supply the data and information for the exercise.

2.3.1 Resources deployed

Personnel (Economists); Computers; forest resource data on standing stock; wood fuel (firewood, charcoal) consumption data.

2.3.2 Source of demographic and economic data and projections

Central Bureau of Statistics at the National Planning Commission

2.3.3 Methods and frequency of analysis

The method needs to be determined. The frequency could be, say, every 5-10 years.

2.3.4 Reporting units (national, provincial, ... scenarios)

The reporting units can be National and Regional, and scenarios.

Table 5. An example showing the results from West Tsumkwe area
(The inventoried area is 607 949 ha).

Species

No. of stems, in 1000s

% of No. of stems

Stems/ha

Total volume
including branches, 1000s m3

Mean volume
including branches, m3/Ha

Mean Biomass
including branches, Kg/Ha

Burkea africana

20,160

33.57

33.16

4,601

7.57

5,982.96

Terminalia sericea

7,662

12.76

12.60

307

0.51

368.33

Combretum collinum

7,581

12.63

12.47

544

0.89

758.02

Pterocarpus angolensis

6,740

11.22

11.09

2,672

4.40

2,395.50

Combretum psidioides (dinteri)

6,533

10.88

10.75

395

0.65

549.20

Lonchocarpus nelsii

2,168

3.61

3.57

234

0.38

362.78

Combretum zeyheri

1,353

2.25

2.23

120

0.20

165.02

Strychnos pungens

1,051

1.75

1.73

33

0.05

39.43

Ochna pulchra

1,014

1.69

1.67

101

0.17

99.42

Guibourtia coleosperma

932

1.55

1.53

1,035

1.70

900.84

Acacia erioloba

873

1.45

1.44

99

0.16

110.32

Baikiaea plurijuga

749

1.25

1.23

274

0.45

254.81

Boscia albitrunca

602

1.00

0.99

30

0.05

29.28

Acacia mellifera

444

0.74

0.73

8

0.01

9.53

Schinziophyton rautanenii

362

0.60

0.60

261

0.43

332.39

Acacia fleckii

291

0.48

0.48

4

0.01

5.16

Acacia tortilis (heterecantha)

256

0.43

0.42

18

0.03

20.01

Strychnos cocculoides

198

0.33

0.33

4

0.01

5.02

Unknown

198

0.33

0.33

20

0.03

19.38

Croton gratissimus

190

0.32

0.31

5

0.01

5.94

Combretum psidioides (psidioides)

141

0.24

0.23

3

0.00

4.32

Ozoroa schinzii

141

0.24

0.23

3

0.01

4.14

Securidaca longepedunculata

129

0.22

0.21

16

0.03

15.71

Dichrostachys cinerea

85

0.14

0.14

2

0.00

1.87

Peltophorum africanum

66

0.11

0.11

9

0.01

8.47

Commiphora angolensis

64

0.11

0.10

15

0.02

20.17

Dichapetalum cymosum

28

0.05

0.05

2

0.00

2.15

Ziziphus mucronata

22

0.04

0.04

17

0.03

14.77

Combretum imberbe

14

0.02

0.02

3

0.00

4.31

Total for the whole area

60,047

100.00

98.77

10,833

17.82

12,489.24




Sudan

Country Report

by
Mr Mohamed Ezeldeen Hussein

Coordinator of the National Forest Inventory Unit (FNC);

Preface

Before entering on the subject of this report, I must point out that, previous studies have indicated in quantitative and qualitative terms the almost complete dependence of Sudanese people on forest resources for the supply of wood for energy, building material and raw material for some industries.

In fact, the forestry sector lacks the most fundamental data, without which it cannot plan effectively nor function efficiently. The highest priority should be given to data collection and analysis in the immediate future.

This report reviews and summarizes, in a very general terms, existing information on forest products demand and supply, along with an up-dating of the FAO sponsored National Forest Inventory and the Forest Products Consumption Survey.

1. Introduction

1.1 Location and area

Sudan is the largest country in Africa, lies between latitudes 210 55- N - 30 53 N and longitudes 210 54 - 380 31 E with an area of 2 505 800 km2.

It is essentially an immense plain, bisected by the White Nile and Blue Nile, rivers which joined at Khartoum to form the Nile, mountain ranges and plateau occur along the Red Sea part of the border with the Ethiopia, in the south east and in the east.

The soil in about 60 percent of the country, particularly the northwest, north and northeast is predominately sand. Heavy cracking clay soils form triangular central easterly plain, which makes up some 30 percent of the country. Red soils of different types are characteristic of remaining southwest portion.

Rainfall varies from nothing in the northern desert to more than 1500 mm in the southern tropical mixed deciduous forests.

The vegetation can be divided into seven principal types, which in general follow the isohyetes and form constructive series from North to South:

ˇ desert;
ˇ acacia desert scrub;
ˇ acacia tall grass scrub;
ˇ broadleaved woodland in forests;
ˇ forest (gallery forest, bowl or depression forest and cloud forest);
ˇ swamps and grassland.

Effect of topography on vegetation is limited and confine to mountain massifs, hills, upland, country and Nile valley and its tributaries.

1.2 Population

Based on Sudan population census of 1993, the National Energy Administration (NEA) published following forecast figures for 2000.

Table 1. Sudan population in 2000

Region

Urban

Rural

Nomad

Total

Northern

306 859

1 077 521

67 504

1 451 884

Eastern

980 097

1 600 235

884 548

3 464 880

Central

1 215 162

4 443 215

368 701

6 027 078

Kordofan

558 975

2 825 692

1 147 246

4 531 913

Darfur

485 040

3 653 930

743 742

4 882 714

Khartoum

2 260  778

653 573

155 172

3 069 523

Equatoria

248 074

1 757 222

0

2 005 299

Bahr Elgazal

277 489

3 276 616

0

3 554 105

Upper Nile

75 989

2 288 110

0

2 364 099

Total

6 408 463

21 576 117

3 366 913

31 351 495

Source: NEA, based on 1993 census.
Population growth rate 2.7 % (1993- 2000 ).
Percentage of urban 24.6 % (1995).
Percentage of rural 75.4 % (1995).

Population density, population per km2 in Sudan:

1990

1995

2000

10

11

12

Source: population, incomes and forest resources in Africa baseline study 2000.

Above forecasted distribution pattern neglects basic changes that have occurred in the last seven years, mainly:

ˇ Khartoum population doubled, due to migration from West and South and displacement due to civil war.
ˇ
Drought years resulted in a massive migration from Darfur and Kordofan towards the Nile, i.e. Northern, Central and Khartoum regions lacking fuel wood resources.
ˇ
Population distribution in the southern region is unknown, due to massive migration (towards northern regions and neighbouring countries) as a result of the civil war.
ˇ
Recent influx of approximately 85 000 Eritrean refugees into eastern Sudan due to renewed hostilities between Ethiopia and Eritrea, resulting in massive destruction of forest resources in the area.

1.3 Economic activities

The main activity is agriculture (including livestock production, forestry and fishing), which altogether contribute to about 40 percent of the Gross National Product (GNP). The principal exports are primary agricultural products. Cotton is the main export commodity besides oil seeds and Gum Arabic (Sudan contributes 80% of world production)

Recent changes in land use, especially expansion of mechanized farming in Southern, Blue Nile and Southern Kordofan have been at the expense of forests and woodlands.

2. Sudan forest resources

According to the FAO, forest area decreased from 34 percent in 1958 to 17.7 percent in 1998 of the total country area. The forest and woodland area in Sudan currently amounts to 88.2 million hectares, this area representing 34.5 percent of the total land area of the country. 8.86 million ha constituted as forest reserves and under reservation, which make 3.6 percent of the total area (FNC 2000). Desert and semi-desert occupy 17.4 percent. Cultivated land, game reserves and urban area accounted for 6.7 percent, 4.74 percent and 1.46 percent respectively. While water made 0.58 percent, the rest of the land about 33.65 percent for other land use.

Table 2. Sudan land-use according to FAO (Global Forest Assessment 1995)

Forest reserves &under reservation

Natural forest &
woodland not reserved

Desert &
semi desert scrub

Cultivated land

Game reserves

Urban area

Water

Other land use

Total
(millionha)

8.86

79.31

43.25

16.66

11.78

3.63

1.43

83.67

258.59

  3.56%

   31.90%

 17.4%

   6.7%

    4.74%

   1.46%

 0.58%

   33.65%

100%

Early estimates made in the 1950s to the 1960s indicated forest area of 45.5 million ha. The lower figure was estimated to carry a growing stock of 1.28 billion m3 of (fuel) wood and building poles and 52 million m3 of timber, i.e. a total growing stock of 1.33 billion m3 .

The overall stocking based on this figure would be of the order of 22.2m3 to 28.6 m3 per ha. of productive forest , with actual values ranging from 150 m3 ha. in the montane forest of the Southern Sudan to less than 1 m3 per ha in the desert area.

A growing stock inventory at low intensity to provide ground truth was carried out in selected area including the Blue Nile, White Nile and Kassla States in 1982.

The result of this activities indicated an increase in total growing stock to 1.994 million m3, however, analysis of the ground truth data reveals severe reduction in growing stock volumes, particularly in the heavily forested areas of the Blue Nile, where the growing stock is estimated to only one-third of previous estimates i.e. less than 9 m3 per ha. Preliminary data from this survey indicates a total annual allowable cut of 15.1 million m3 for the southern.

World Bank estimates of total woody resources of Sudan in 1983 showed an area of 93.78 million ha, with growing stock of 2847.58 million m3.

These figures decreased to 72.85 million ha. and 2487.20 million respectively. This would make a total loss of about 21.01 million ha and 360.38 million m3 which is seem to be high estimates (see tables 3 & 4)

Table (3) shows estimates of the woody resources during the period 1983-2000 in Sudan according to the different sectors.

Table 3. Woody resources of Sudan during the period 1983-2000

Sectors

Area of the remaining woody resources (million ha)

1983

1985

1990

1995

2000

Northern

0.00

0.00

0.00

0.00

0.00

Eastern

2.75

0.00

0.00

0.00

0.00

Central

5.12

3.88

0.00

0.00

0.00

Kordofan

11.63

11.54

11.36

5.81

0.00

Darfur

17.69

17.63

17.52

17.41

17.31

Khartoum

0.00

0.00

0.00

0.00

0.00

Total of northern sector

37.19

33.05

28.88

23.22

17.31

Deficit from 1983

0.00

4.14

8.31

13.97

19.88

Equatoria

18.79

18.76

18.68

18.63

18.57

Bahr Elgazal

18.08

18.03

17.95

17.88

17.80

Upper Nile

19.80

19.70

19.48

19.31

19.17

Total of the Southern sectors

56.67

56.49

56.11

55.82

55.54

Deficit from 1983

0.00

0.18

0.56

0.85

1.13

Grand total of Sudan

93.86

89.54

84.99

79.04

72.85

Deficit from 1983

0.00

4.32

8.87

14.82

21.01

Source World Bank 1986

Table 4. Estimates of remaining growing stock during the period 1983-2000
according to the different sectors

Sectors

Remaining growing stock (million m3)

1983

1985

1990

1995

2000

Northern

0.00

0.00

0.00

0.00

0.00

Eastern

6.75

0.00

0.00

0.00

0.00

Central

38.01

20.27

0.00

0.00

0.00

Kordofan

186.58

185.70

165.07

96.41

0.00

Darfur

667.06

665.54

641.91

607.81

557.18

Khartoum

0.000

0.000

0.000

0.000

0.000

Total of northern sector

898.40

871.96

806.98

704.22

557.18

Deficit from 1983

0.000

26.44

91.42

194.18

241.22

Equatoria

999.95

998.89

996.24

994.94

993.64

Bahr Elgazal

793.24

792.14

788.94

786.79

784.64

Upper Nile

155.81

155.29

153.99

152.69

151.74

Total of the Southern sectors

1949.18

1946.32

1939.17

1934.42

1930.02

Deficit from 1983

0.00

2.86

10.01

14.76

19.16

Grand total of Sudan

2847.58

2818.28

2746.15

2638.64

2487.20

Deficit from 1983

0.00

29.30

101.43

208.94

360.38

Source World Bank 1986

2.1 Forest product consumption survey (1994)

This survey was initiated by FNC with the assistance of the Bureau of statistics, with technical and financial support from the FAO /Netherlands Project Forestry Development in Sudan.

Main objective was to obtain reliable estimates of consumption of forest products at the national and state levels and to develop consumption models to enable long term policy formulation and planning and national management of the forest resources.

The survey showed in very broad lines the following:

In 1994, total consumption was estimated as 15.77 million m3 for all wood products. The percentage distribution among different sector was 89.4 percent for household, 6.8 percent for industry, 2.5 percent for commercial and services sector and 1.3 percent for Quaranic schools.

By product analysis, wood fuel (firewood and charcoal) consumption accounted for 87.5 percent while construction, maintenance and furniture wood accounted for 7.2 percent, 3.8 percent and 1.5 percent respectively.

Consumption estimates for individual states for the major wood products. In aggregate Khartoum, Gezira and South Darfur have the highest consumption reaching 18.39 percent, 11.25 percent and 10.73 percent of total consumption respectively. The States Northern (1.83%), River Nile (2.68%) and Red Sea (2.74%)has the lowest consumption. This reflects the distribution of population on one hand and the per capita estimates as with high fuel wood consumption (Darfur and Kordofan) are characterized by low charcoal consumption. Similarly Gezira and Khartoum, which has the highest charcoal consumption., have the lowest firewood consumption Figure(2)

The per capita consumption for wood products for different States, consumption range between 0.47 m3 in the Rive Nile to 1.05 m3 in Blue Nile State. With a national average of 0.73 m3. In general, States with high wood consumption are characterized by high household firewood per capita (Darfur States, North and West Kordofan, high charcoal per capita ( Khartoum, Gezira, Sinnar) or both (Blue Nile). In general, eighty States have per capita estimate above the national average (1.05 m3 to 0.76m3) and the remaining have per capita estimate lower than the national average (0.70m3 to 0.47m3)

2.1.1 Wood energy

Sudan depends mainly on forestry sector as energy source, it contributes a total of 4.01 million T.O.E representing 70.8 percent of energy supply in the country (FNC,1995)

Demand for fuel wood increased in last years due to rapid population growth, urbanization and shortage of modern energy, However, wood fuel consumption in the Sudan is expected to decrease from current consumption as a result of investments and refining of petroleum by 2000 especially in household and traditional industries sectors - table (6 ) shows the total energy supply in the period 1993- 1994).

Table 6. Total energy supply (1993-1994)

Source

Supply (`000 T.O.E)

% of total

Hydro(electricity)

102

1

Petroleum

1 460

13

Wood fuel

9 016

81

Residues

560

5

Total

11 139

100

Source Ministry of Energy & Mining

Table 7 indicates that annual household wood fuel consumed in 1994 constituted the highest components of consumption (86.8%), as a result of population growth and urbanization.

Table 7. Energy balance 1994 (consumption)

Sector

Wood fuel

Agro-residues

Petroleum

Electricity

Total %

000 T.O.E

%

000 T.O.E

%

000 T.O.E

%

000. T.O.E

%

000. T.O.E

 

Household

3423

86.8

434

11

25

0.6

60

1.5

3 942

69.6

Industry

443

69.3

-

-

160

2.5

36

5.6

639

11.3

Commercial/services

57

67.1

-

-

20

23.5

8

9.4

85

1.5

Quaranic schools

88

100

-

-

-

-

-

-

88

106

Other

-

-

-

-

895

98.4

15

106

910

16.1

Total sectors

4 011

70.8

434

7.7

1100

19.4

119

2.1

5 664

100

Source: FNC 1995

Population growth, urbanization and limited supply put more pressure on forests resources, especially in subsistence sector where fuelwood is collected directly by family members from nearby forests.

Table 8. Wood consumption in industry in 1994 (m3 roundwood)

Industry

Fire wood

Charcoal

Construction

Maintenance

Furniture

Total

%

Bakery

384.7

0.3

0.3

0.0

0.1

385.4

36.2

Brick kiln

548.9

0.1

0.1

0.0

0.0

549.0

51.5

Lime product.

32.0

 

 

 

 

32.0

3.0

Veg. oil soap

82.8

 

 

 

 

82.8

7.8

Other

1.7

11.3

1.4

0.7

1.3

16.4

1.5

Total

1050.2

11.7

1.8

0.7

1.3

1065.7

 

%

98.5

1.1

.02

0.1

0.1

100

100

2.1.2 Forest products demand in 2000

Several scenarios were developed to arrive at a prediction of forest products demand at year 2000. The scenarios are based on Forest Product Survey (1993). The population size is estimated on the basis of an annual growth rate of 2.7 percent and possible influx of people from Southern Sudan.

2.1.3 Fuelwood consumption for the household sector

1. Three possible scenarios concerning total fuelwood consumption are shown in Table 9.

Table 9. Firewood consumption by the household sector

Year

Sc1

Sc2

Sc3

1994

5 902

5 902

5 902

1995

6 099

6 003

5 745

2000

6 992

6 698

5 230

Forecasting was based on the assumption that household consumption is related to the size of the families and to the level of urbanization. As effect of the urbanization the per capita household consumption decreased but the cumulative consumption increased as effect of the growing number of households (1993 census).

2.1.4 Pattern of charcoal consumption

Table 10. Charcoal consumption

Year

Sc1

Sc2

Sc3

Sc4

Sc5

Sc6

1994

6 070

6 070

6 070

6 070

6 070

6 070

1995

6 278

6 423

6 938

5 942

6 092

6 222

2000

7 196

7 612

10 532

5 271

6 060

6 303

If the pattern of the consumption remains, and the distribution of the population between urban and rural areas remains the same, in 2000 the consumption will be 7.196 million m3 (Sc1). Sc3 represents the maximum consumption pattern, assuming that urban population increased to 45 percent of the total population.

This will lead to a decrease in per capita consumption (5% yearly).

Sc4 assumes a considerable change from charcoal to other energy sources (This situation is undesired).
Sc5 and Sc6 are based on the most probable assumptions, such as the improvement of other energy resources (I.e. gas, kerosene diesel).

2.1.5 Consumption of wood energy in industry

The following assumptions are made for all scenarios:

1. Distribution of urban and rural remains as such.
2. Urban population increased gradually to 6408463 in 2000.
3. Sc1 assumes a 2.7% annual population growth rate, whereas
4. Sc2 assumes a 4.6% annual population growth rate.

Table 11. Fuelwood consumption by industry based on 1994

Year

Sc1 million m3

Sc2 million m3

1994

1 050

1 050

1995

1 078

1 098

2000

1 232

1 375

In 1994 the industrial consumption from other different end uses of forest products, i.e. building materials, furniture, etc., was about 15 517 m3, and this constitute about 1.5 percent out of total industrial consumption forecast. Table (12 ) illustrate this

Table 12.

Year

Sc1 million m3

Sc2 million m3

1994

0.0160

0.0160

1995

0.0160

0.0160

2000

0.0180

0.0200

2.1.6 Consumption of wood in the service sector

This sector includes a number of institutions e.g. schools, hospitals, restaurants, commercial and institutions besides unofficial activities and the making of Kisra, these constitute 2.5 percent of the total wood consumption in the Sudan. Needless to say that above activities are centralized in urban areas, therefore, two alternatives of urbanization coefficient were used as indicators for the consumption pattern of different products.

Table 13. Wood consumption scenarios in million m3

Year

Fuel wood

Other

Sc1

Sc2

Sc1

Sc2

1994

0.136

0.136

0.074

0.074

1995

0.325

0.331

0.076

0.077

2000

0.371

0.414

0.087

0.097

Fuelwood and charcoal constitute over 80 percent of the total wood consumption of the institutional sector in the urban areas, consequently a shift to energy resources other than biomass may take place.

The survey indicates that, consumption of charcoal exceed 6149340 m3 but at the same time the use of liquid petroleum gas LPG as well as Kerosene in urban areas is increased due to the government announcement in Jan. 2000 of adopting a policy towards petroleum products prices, e.g. reduction of LPG prices (dropped by 50%).

This resulted in decrease of the consumption rate.

The main reasons for the fuelwood problem in Sudan can be summarized as follows:-

ˇ The supply gap, defined as the difference between demand for forest biomass and sustainable supply, continue to widen tremendously.
ˇ The increase of the population and degree of urbanization as result of huge migrations to urban centres as consequence of droughts and desertification.
ˇ The impact of the expansion of the mechanized farming affects the supply gap negatively in the absence of a defined land use plan.
ˇ Insufficient investments for afforestation and reforestation.
ˇ The high cost of transporting fuelwood from long distances is the key factor inflating the price of fuelwood and charcoal.
ˇ Lack of alternative fuels
ˇ Civil war and political conflicts in neighbouring countries created large flows of refugees, who have a significant role in the consumption of fuelwood.
ˇ Natural hazards (drought, floods and rainstorms).
ˇThe uneven distribution of the forestry resources and population between the North and South.

3. The National Forest Inventory (NFI 1998)

Figures appearing in the various reports estimate the total forest area varying between 40.6 percent and 18.2 percent of the country's surface area. All these figures were estimates based on partial observations. No national forest inventory has ever been carried out. However, a number of localized inventories have been carried out but these covered small areas, compared to the size of the country, and parts of Sudan that were known to be forested were never inventoried. The need for a national forest inventory was especially felt after the completion of forest product consumption survey. The consumption survey constituted the demand side of the situation. To complete the picture estimates of the available forest resources and the related parameters had to be obtained by a full fledged national inventory. The inventory was started in March 1995 and completed in July 1997. This inventory as well as the consumption survey were carried out by the Forests National Corporation (FNC) in collaboration with the FAO, through the project (Forestry Development in the Sudan IGCP/SUD/047/NET), which was supported by the government of the Netherlands.

The main objective of NFI was to provide the government of Sudan with the basic information on the current state of the country's forestry resources, for the purpose of socio-economic development, maintenance of the environmental stability and enhancement of the quality of life for the people of Sudan.

NFI showed very important facts about Sudan forest resources situation

The inventory covered such parameters as land use, land condition, crown closure, volume of woody material, number of species, regeneration and a comparison of harvest level (annual allowable cut) and consumption

In figures terms the inventory covered the following area

a) Total area of Sudan 250 060 000 ha
b) Area targeted 95 000 000 ha
c) Total area inventoried 62 270 000 ha
d) Total area inventoried % of target 65.5%
e) Total area inventoried % of Sudan 24.9%

NFI have not covered inaccessible areas for various reasons e.g. Southern Sudan Civil war and areas bordering some neighbouring countries, these areas are estimated to be 75.1 percent of the Sudan total land.

Summary Table 14. Overall statistics of tree cover and wood volume in inventory area (000 ha),
wood volume m3

Sector

Area inventoried

Area with tree or shrub cover

Area of forest with crown>10%

Average total vol./ha of all veg.m3

Total vol. of all woody veg. m3

Total number of trees

Aver. trees /ha

RiverNile

1 690 000

640 000

50 000

1.05

672 000

12 160 000

19

Eastern

63

2 100 000

240 000

1.54

3 234 000

68 100 000

41

Central

16 730 000

4 680 000

11 600 000

6.31

29 531 000

18 720 000

40

Kordofan

19 650 000

1 038 000

1730 000

4.26

44 218 800

332 160 000

32

Darfur

18 320 000

13 180 000

4310 000

6.76

89 096 800

817 160 000

62

Total

62 700 000

30 820 000

7 490 000

2.49

166 752 600

1 266 300 000

20

Summary Table 15. Annual allowable cut and total wood consumption in inventory area

Sector

Total volume of all woody veg. m3 *1

Annual allowable cut
(increment) cubic *1

Wood consumption cubic(1995) *2 *3

Surplus
(deficit) m3

River Nile

672 000

47 040

451 851

(404 811)

Eastern

3 234 000

226 380

2 025 763

(1 799 383)

Central

29 531 000

2 067 170

7 475 000

(5 407 830)

Kordofan

44 218 800

3 095 316

2 551 097

544 219

Darfur

89 096 800

6 236 776

4 018 401

2 218 375

Total

166 752 600

11 672 682

16 522 112

(4 849 430)

Note:

*1. Source: Sudan National Inventory (1998)
*2. Wood consumption in households, establishment & industrial sectors
*3. Forests products consumption survey in the Sudan (1995)
*4. Khartoum, Gezira, Sennar and White Nile



Uganda

Biomass Energy - Methodologies for Data Collection, Analysis and Use11
(abstract)

by
Kenneth L.Opiro,12 John Tumuhimbise,13 Patience Turyareeba14
Paper presented by
John Tumuhimbise


Abstract

Biomass energy is the major source of energy used in Uganda accounting for over 96 percent of total energy consumption but receiving less than 0.001 percent of national development resources allocated to the energy sector. Biomass is used mainly in the household, commercial and institutional sectors and to a lesser extent in the industrial sector.

In the context of a society whose major source of energy is biomass, it is crucial to understand and address multi-sectoral concerns at national, district and sub-county level. To accomplish this, stakeholders require both qualitative and quantitative information on biomass energy demand and supply. This high quality information should be rich and reliable so that it can aid formulation of effective interventions and the evolution of well informed policy decisions in the forestry and energy sectors.

The paper reviews the biomass energy sector, provides an insight of different stakeholders and their interests, reviews methodologies used for data collection, analysis and use and finally recommends a way forward.

The methodologies used for data collection and analysis used in Uganda are considered to be suitable for data collection under the pilot study. Once objectives of the study have been formulated, target groups will be identified and secondary data will be reviewed before primary data collection. It is proposed that three districts are selected for the pilot study, a biomass deficit district, a biomass surplus district and a biomass balanced district. The pilot study would then collect and process data to meet the objectives outlined at district, sub-county and village levels.

There is need to institute a systematic method for regular data collection as part of routine activities. Officers deployed at sub-county level should be involved in regular data collection. In addition, standards for different biomass fuels and quantities should be determined.


    8 Forestry Department, Ministry of Environment and Natural Resources
    9
Kenya Forestry Research Institute (KEFRI)
    10
Dr Kojwang could not participate to the workshop. He was replaced by Mr Moses Chakanga, author of the second report.
   11
Paper Presented at the National Seminar on Strengthening Information Systems for Sustainable Forest Management in Uganda, Jinja, Uganda,11-12 April 2000. The full report may be requested to the authors or to M.A. Trossero, FAO FOPW, Rome. 
    12
Forest Department
    13 Department of Energy
    14 Forest Research Institute


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