2.1 Background
2.2 Wood energy consumption data
2.3 Woodfuels supply and production data
2.4 Comparison of country reports data with WEIS data
2.5 Other woodfuels data collected
In earlier studies, wood energy data were confined mainly to fuelwood consumption in the household sector and further confined to woodfuels consumption for cooking purposes only (the most significant use), even although woodfuels were also used for other types of heating applications (water and space heating, cooking of animal feed). Very few countries recognized and collected data on woodfuels consumption in other sectors, such as in industries, service establishments, agro-processing units and institutions (e.g. schools, army camps, crematoria). 13
Wood energy data were usually collected and presented in units of volume (e.g. cubic metres) or mass (metric ton). Most studies focused on the link between woodfuels use and deforestation, even if studies, particularly nationwide studies, of woodfuels supply production involving primary data collection and field measurements had not been conducted.
Many fuelwood consumption studies, particularly those initiated by forest agencies, were conducted in “isolation”, i.e. analyses of uses of other fuel types were not included. This limited appreciation of the significance of woodfuels in the total energy picture and constrained understanding of fuel shifting, an important consideration when projecting future demand for woodfuels. Projection studies did not account for the impact of using alternative fuels and the impact of fuel shifting, leading in many cases to overestimation of fuelwood demand.
Although asked for information on woodfuels production, countries only provided data on forest areas and/or change in forest areas. Some countries added volume and yield data (i.e. trunk volume of commercial/timber tree species). This ignored the fact that within forests, woodfuels are also harvested from non-commercial tree species, including other woody plants such as shrubs and bushes, and that fuelwood does not only come from trunks, but also (and mostly) from tree crowns (i.e. twigs and branches), roots, and barks. It also ignored the fact that woodfuels are produced from trees and other woody plants found outside forests too.
Data on “woodfuels flow”, i.e. the transformation, marketing, trading and distribution of woodfuels, were also almost non-existent. Woodfuels transformation refers to the conversion of “wood from tree” into fuelwood, and into other forms of wood energy. In general, the transformation processes include:
§ harvesting of wood (including pruning, thinning and collection of fallen twigs/ branches);
§ splitting and bundling of wood to produce convenient sizes of fuelwood;
§ thermal and/or chemical processes that convert fuelwood to others forms of wood energy (such as charcoal production, pyrolysis, and gasification); and
§ end use technologies (e.g. stoves, ovens, kilns, furnaces, and boilers) to generate the final useful forms of energy (heat or electricity).14
Except for data on stove efficiency and anecdotal information on the patterns of marketing and trading of woodfuels in a few cities (mainly from case studies initiated by RWEDP), no data had been collected on these aspects. Such data, however, are most helpful in formulating and analyzing wood energy policies, programmes and other interventions such as growing more trees to expand supply and increase production of fuelwood, substituting fuelwood, upgrading the technical efficiency of woodfuels conversion and end use, and improving the economic efficiency of woodfuels marketing and distribution. These are also relevant for assessing the economic and social impacts of interventions and the environmental and health effects of woodfuels production and use.
Time-series or historical data, based on primary data collection techniques (i.e. surveys involving field measurements), were also unavailable previously. These historical fuelwood consumption data presented by some countries (including those from FAO Statistics) were generated using extrapolation techniques. The most common approach was to relate fuelwood consumption linearly with population growth. Later analyses showed that this approach was erroneous, as population growth is not the only factor influencing woodfuels consumption.
However, as mentioned before, there have been improvements in wood energy databases as shown in the country reports submitted by the national consultants. However, data limitations and constraints persist. These are now discussed in the following sections.
A review of data submitted in the country reports and a comparison of these data with data on wood energy consumption presented in earlier reports show the following improvements:
Previously, fuelwood data were not included in detailed national-level energy statistics (i.e. where consumption data are provided for each type of end-using sector), as fuelwood data were considered to be unreliable compared to petroleum and electricity statistics. FAO, through the RWEDP, promoted the integration of wood energy data into detailed energy statistics. Some countries, namely Cambodia, Nepal, Philippines, Sri Lanka, Thailand and Viet Nam.15 have now integrated fuelwood consumption data into their overall energy statistics and “energy balance tables”.
It is true that aggregate consumption values for commercial fuels are relatively accurate as they are based on sales records of electricity and petroleum companies. However, electricity and petroleum companies do not have detailed records of their final users, except for large users (e.g. large corporations, industrial plants, etc.) that are directly connected or that buy energy from them directly. Detailed data on energy consumption for each end using sector (i.e. rural households, urban households, industries, commercial and service sectors) are drawn from energy consumption surveys that covered all types of fuels. As such, data reliability for wood and other biofuels would be just on a par with that of electricity and petroleum fuels.
Integrating woodfuels data into energy statistics is important as it puts woodfuels on the radar screen of planners, policy analysts and decision-makers. This is a key step in calling attention to the importance of woodfuels.
The majority of the country reports contain historical woodfuels consumption data not only for households, but also for other woodfuels-using sectors. Alhough the data are still the results of projection studies and not from periodic primary surveys, the techniques used in making the projections have improved.
Two national consultants generated historical consumption data as part of their studies (other national consultants collected and submitted secondary data, see discussion below). The India and Lao PDR consultants generated time-series data using a sector-by-sector linear extrapolation of woodfuels consumption data. This is an improvement over previous approaches (i.e. linear extrapolation of aggregate woodfuels consumption). The methods and assumptions used by the two consultants are discussed in their reports.16
The Philippines consultants generated estimates by analyzing two national household energy consumption surveys (1989 and 1992) and several energy studies. The consultants estimated a range of values for the consumption of woodfuels and other biofuels (i.e. agricultural residues and crop processing wastes), but refrained from generating historical data.
Other national consultants included data collected from official reports or from other studies. For example, the Nepal national consultants included “ten-year time series data” on woodfuels consumption for all sectors generated by the Water and Energy Commission Secretariat (WECS), the country’s energy planning agency, using a modelling study (in which the data were disaggregated further by types of end uses). However, the report does not include a discussion of the methods and assumptions used in the modelling study. Other national consultants, i.e. from Sri Lanka, Thailand and Viet Nam included (less detailed) historical data generated by their respective national energy planning agencies. But they also did not provide details of the projections techniques used (Table 1).
In recognition of the factors affecting fuel consumption and shifting, consumption data for the household sector are further disaggregated by administrative divisions, rural/urban areas, household income class levels, and even by agro-ecological regions in most country reports. A few national consultants disaggregated woodfuels consumption data by types of energy end uses such as cooking and other heating applications. Table 1 provides an overview of disaggregated woodfuels consumption data contained in the country reports.
The Nepal country report contains the most detailed data (again generated by WECS) on household fuelwood consumption with the data disaggregated by all the factors previously mentioned. WECS has generated similar detailed disaggregated data for the industry and commercial/service sectors. However, no discussions of the basis for data estimations are provided in the report. Like the Nepal country report, the Viet Nam and Thailand reports also contain disaggregated woodfuels consumption data that shows consumption by types of end uses.
As already mentioned, all country reports (except that of Malaysia) contains data on woodfuels consumption by non-household sectors. Most reports, i.e. those of Cambodia, India, Lao PDR, Nepal, Philippines, Sri Lanka, Thailand and Viet Nam provides estimates of total national consumption. The exception is the Pakistan country report, which provides data on specific consumption by various types of industries only.
The types of non-household sectors included in the consumption data in the reports vary among the countries. The India report includes industries, service establishments and institutions as separate categories. Other country reports include only industries and commercial establishments. No country report contains data on consumption by the informal sector as this sector is rarely studied (only a few local studies have been carried out).
As mentioned already, the India and Lao PDR national consultants generated their own estimates of historical consumption data. The Cambodia, Nepal, Thailand and Viet Nam national consultants submitted similar historical consumption data that were collected from national energy agencies, with the data from Nepal and Viet Nam being differentiated further by the types of non-households sectors.
The Philippines report contains data from a nationwide survey of industries and commercial establishments (1990), whereas the Sri Lanka report has data on the energy efficiency of fuelwood-using industries from recent case studies (1999). In fact, these were the only country reports that mention such detailed studies having been carried out. The Pakistan country report contains only data on specific energy consumption, i.e. woodfuels use/per production unit for different types of industry, but no estimates of national-level aggregate consumption.
Only a few country reports contain data on consumption of charcoal, sawdust (including wood shavings), and black liquor. Charcoal and sawdust used to be considered distinct from fuelwood and were usually left out in fuelwood consumption studies and statistics17. Some country reports still reflect this practice as can be seen from how the data were organized in the report, despite the guidelines provided for preparing the report.
Cambodia, Philippines, Thailand and Viet Nam generally include charcoal in household energy consumption surveys and their national reports contained data from those surveys. Lao PDR report contains extrapolated data on charcoal and sawdust consumption derived from local studies and government records, but it includes only charcoal in overall woodfuels consumption estimates. Several local studies on charcoal consumption have been conducted in India also, but these are not suitable for making confident estimates of total national-level consumption. In contrast, the Nepal country report contains detailed national-level historical data on charcoal consumption that were generated by WECS.
In most of these countries, charcoal consumption in informal sector activities, such as in unlisted food service establishments, appears to be significant. But, despite the efforts of the national consultants to estimate charcoal use by including data from formal surveys and government records, e.g. tax records, the generated values are most likely to be underestimates as consumption of the informal sector was not included in the calculations.18
Black liquor is liquid waste material produced during the pulping process (the bleaching of pulp with sulphuric acid). Thus, it can be considered another form of wood energy. It has sufficiently high organic content and heating value to be used in boilers to produce steam and even electricity. The amount of black liquor can readily be extrapolated from pulp and paper production data. As pulp and paper production is a substantial operation, the energy generated from black liquor can be substantial too. Only the India report identifies the energy contribution from using black liquor, although pulp and paper industries exist in other countries, including the Philippines, Thailand, and Malaysia, and black liquor is used in these countries.
As previously mentioned, data constraints and limitations still exist, particularly if data are needed for energy demand projections, policy analyses and programme formulation.
Few countries have conducted national energy consumption surveys because they are costly and time consuming. As discussed earlier, many countries generate historical or time-series national-level data using extrapolation/estimation techniques. The extrapolations are usually based on one detailed national and/or local sample studies. It was not clear from the country reports whether those surveys had used appropriate field measurement techniques or just conducted interviews in collecting data.19 (The importance of this is explained further in (b) and (c) below. In addition, it is apparent that the local “sample” studies used to extrapolate national aggregate values were not conducted using proper sampling techniques.
The energy consumption surveys that were mentioned in the country reports all focused on the household sector, and they can be categorized into three types (Table 3).
The first type includes detailed energy consumption surveys that included “field or physical measurements” to collect data. These surveys covered fuelwood and all other fuels used for cooking. Such surveys can be more comprehensive, covering all types of household energy end uses and fuels used (e.g. lighting, refrigeration, transportation, etc.). Only three country reports contain references to this type of comprehensive nationwide exercise being carried out: those of India (1978)20, Philippines (1989 and 1995), and Pakistan (1992).21 The second type includes energy consumption surveys involving only interviews (i.e. no field measurements were undertaken), and although they appear to be less accurate, they are simpler, faster and cheaper to conduct.22
The third type of surveys includes the Income and Expenditure Surveys that are not really energy surveys, but socio-economic surveys regularly carried out to generate socio-economic indicators. In these surveys, data were collected on “household expenditures”, including that for fuel consumption. The results were in “monetary units”. Rarely were data collected on the amount of fuel used and for what purpose. The surveys provided data on types of energy used by households, expressed in terms of percentage of users. India, Lao PDR, and Sri Lanka country reports contain data based on this type of surveys.
Table 3. Latest national-level energy consumption surveys
No standard field data collection technique
The lack of a standard becomes apparent when deciding what technique to use for conducting physical measurements of woodfuels. Consultants chose either mass or volume values. But whether mass or volume values are selected, the techniques for measuring fuel amounts should be discussed. The reason for this is that the characteristics of woodfuels vary, depending on whether it is fuelwood, or charcoal, or some other form that is being measured. At least, four types or forms of woodfuels are mentioned in the country reports: fuelwood, charcoal, sawdust, and black liquor, and consumption data were provided for each of these. In all cases, no information is provided on the techniques used for measuring the amounts available.
Fuelwood – Amounts of fuelwood given in volume units can be measured in at least two different ways: piled wood or solid wood.23 Amounts of fuelwood can also be given in mass units, however measurement using mass units of fuelwood needs specifications of the moisture content. Some consultants used energy units (PJ or ktoe) in reporting fuelwood values. Since energy units cannot be measured directly, but have to be converted from either mass or volume units, there is a need to specify the moisture content, and to state whether it is piled or solid wood, if the measurement unit is in volume units.
Charcoal – Specifications have to be provided for charcoal also, although charcoal is commonly reported in mass units. The additional concern with charcoal is estimating the amount of fuelwood needed to produce the charcoal. In this case, more specifications are needed in addition to moisture content, e.g. heating values, efficiency of charcoal kilns, and type or species of wood used (e.g. tropical or non-tropical; coniferous or non-coniferous).
Conversion factors – Data in most of the country reports are given in different units, with some consultants obviously having used different conversion factors from the ones given in the TOR. The conversion factors given in the TOR were also incomplete. Since the country studies contain secondary data available in various units, it would not be surprising to learn that national consultants encountered problems when converting units to collate and compile their data.
None of the country reports contain the necessary specifications discussed above and none contain discussions of this issue in detail. But some consultants provided the conversion units they used (which can also be calculated back) when compiling national data. It was, therefore, difficult for the present author to make comparisons and to organize all the country data in a consistent format. To be able to do this when writing up in the regional report, it was assumed that all volume values were values for a solid volume of wood with moisture content of between 20 and 30 percent. This allowed the use of conversion factors provided by the ITTO/UNECE/FAO/EUROSTAT (2002) Joint Forest Sector Survey guidelines for heating values, weights and volumes for fuelwood. Conversion factors for heating value and weight for charcoal were also obtained from the same reference.
The conversion factor to derive the amount of fuelwood needed to produce charcoal was taken from another source, the Household Energy Handbook: An Interim Guide and Reference Manual - World Bank Technical Paper 67 by Leach and Owen. Here, the defined moisture content is 15 percent dry basis (this is not specified in the above mentioned ITTO/UNECE/FAO/EUROSTAT guidelines) and it assumes that the fuelwood used to produce charcoal is tropical hardwood. The type of kiln and its efficiency also affects the conversion, but this was not specified anywhere. Table 4 below, shows the conversion factors used in this report and the sources from which they were obtained.
Table 4. Conversion factors
| Density and heating values |
| Solid density of fuelwood (20-30% moisture content) = 0.73 metric ton/cubic metre |
| Heating value of fuelwood (by volume) = 9.4 gigajoule/cubic metre |
| Heating value of fuelwood (by mass) = 14 gigajoule/metric ton |
| Heating value of charcoal (by mass) = 29 gigajoule/metric ton |
Source: ITTO/UNECE/FAO/EUROSTAT (2002) Joint Forest Sector Survey Guidelines |
| Energy units conversion factors |
| 1 ton of oil equivalent = 42 gigajoule Source: FAO, 1997b. Energy and Environment Basics. |
| Fuelwood-charcoal conversion factor |
| Fuelwood to Charcoal Conversion Value (for tropical hardwood, moisture content of 13 percent – dry basis, kiln not specified) = 5.88 cubic metre fuelwood/ metric ton charcoal Source: Leach and Gowen (1987) |
Using standard or common methodologies for conducting surveys lessens or eliminates controversies and discords in survey results and makes them widely acceptable. This includes standards for sampling methods, survey and data collection techniques, and physical measurements. Yet even with the adoption of such standards, it is still possible for the results to contain inaccuracies.
The authors of the Philippine country report discuss two nationwide household energy consumption surveys implemented six years apart (1989 and 1995) and show that even with well-funded, statistically well-designed surveys (in terms of sampling technique used), surveys may still be vulnerable to inaccuracies. The two surveys showed that fuelwood consumption for cooking in households decreased between the two surveys.
The authors of the country report, however, questioned such a result and suggest that the two statistically well designed surveys could have underestimated woodfuels consumption in the country. The authors’ analyses indicate that the two surveys not only showed a decrease in fuelwood consumption for cooking in households, but also showed a significant decrease in overall energy consumption for cooking in households. After assessing the impacts of the factors driving energy consumption, such as population growth, economic growth, urbanization and the expanding supply of petroleum fuels, the the authors concluded that fuelwood consumption had been underestimated by the two surveys.24
Further, the authors compared the results of the surveys with previous studies and surveys. The comparison shows that the estimations of overall energy consumption for cooking in households by the two surveys were lower than the estimates of the other studies.
The country report contains no explanations of why such underestimation could have occurred in the surveys. But the authors show that integrating woodfuels consumption surveys with more comprehensive energy consumption surveys allows a complete energy end use analysis, regardless of what fuel is used, that can be a method for data validation. Integrating woodfuels surveys in overall energy consumption surveys is one strategy for standardizing woodfuels survey methodologies that also allow data validation.
Estimating consumption by activities in the informal sector is a problem. Participants in the informal sector (e.g. roadside cafes, ambulant food vendors, small teahouses, makers of native sweets and delicacies, food processing, production of local alcoholic drinks, post-harvest processing) do not register their business activities. The reasons for such include avoidance of tax payments, small and irregular production schedules, itinerant operations or involvement in illegal activities. Data on woodfuels consumption by informal sector enterprises, which can be found in all the countries, have to be collected through specially designed surveys as formal structured surveys cannot capture such data. Just identifying and locating these informal sector enterprises is already a problem.
The Philippine country report contains a discussion of how woodfuels consumption may be underestimated if use by informal sector enterprises is not accounted for. The authors mentioned attempts in the country to study this sector, particularly in an urban setting. The Thailand country report also contains discussions of a study of this sector carried out in one of the country’s provinces.
Woodfuels consumption studies have improved their coverage over the past five years, as data now exist for both household and non-household users. Wood energy data now provide a better picture of trends and patterns of woodfuels consumption in most countries.
Data now show that woodfuels consumption remains significant and will remain significant in the foreseeable future, but uses vary across countries and within countries. Data show that woodfuels are not only used by poor rural households, but also by higher income households too, and woodfuels remain an important energy source for most low-income urban families. Data show that applications are not limited to cooking, and that woodfuels use could be an important reason why the operations of traditional industries and enterprises, which are important sources of local and rural employment and income, remain viable. Data also show that woodfuels, being an indigenous energy source, can create economic and social benefits.
Current wood energy data is far from complete though. Other non-household users are still not included, most notably the informal enterprise sector. Data collection activities in the household and service sectors still focus only on cooking applications, yet in most countries there are other heating applications that use woodfuels, e.g. cremation (India), water heating (Nepal), space heating (Nepal, Thailand and Viet Nam) and animal feed preparation (Nepal and Viet Nam).
As consumption of woodfuels is expected to remain at current levels in the foreseeable future (or may even grow slightly), both problems and opportunities can arise. A good database is needed to better understand energy consumption patterns to allow prognosis of possible problems and the formulation of solutions to these, and at the same time to recognize and develop potential opportunities.
An example of such an opportunity is the use of woodfuels in modern wood energy applications such as industrial heating and electricity generation. Only the consultants from India and Sri Lanka mention this in their reports. Modern wood energy technologies using woodfuels can create dramatic benefits but can also adversely affect traditional users. Given that dependence on woodfuels will continue in the foreseeable future for traditional uses, there should be a proper understanding of the impacts of modern wood energy systems that should start with the collection of relevant data.
The problem of indoor-air pollution resulting from woodfuels use is now better understood. Addressing the adverse health impacts of indoor-air pollution is another important rationale for wood energy interventions. Again, before any proper intervention can be formulated, better wood energy data and information are required, including data on health and socio-economic aspects. As the most affected are women and children, disaggregating data by gender and generation is most important in understanding how widespread the problem is and in formulating the solutions to it.
The factors driving consumption of woodfuels and other fuels have already been identified. However, understanding how such factors affect potential demand not only for woodfuels, but also for the various competing fuels – and trying to quantify the effects – is a more complex task that requires further improvements in wood energy data and information and in techniques for analyzing them. The required improvements will be specific for each country.
Countries still have inadequate data so are not able to make confident projections of consumption of woodfuels and other fuels used for cooking as determined by factors such as urbanization, household income, socio-economic conditions, agro-ecological situation, and availability/ affordability of fuels. Data are also inadequate for analyzing other types of energy applications (such as process heating, cooking in food establishments and others) using wood and other biofuels. It is desirable to have time-series data, but conducting regular national surveys, particularly household surveys, is expensive, time consuming and complex.
The consultants responsible for the Nepal country report made detailed projections of woodfuels consumption and showed that the country has surmounted these data constraints. It would be interesting to learn more about the methods and assumptions used by the consultants to generate comprehensive time-series data. It would also be interesting to assess their applicability to other countries. Other consultants (e.g. from Cambodia, India, Lao PDR, Thailand, Sri Lanka and Viet Nam) made similar attempts to provide detailed data, but their data were not as comprehensive as Nepal’s. Finally, it would be interesting to compare the methods by the consultants with those used by FAO-WEIS.
The majority of the country reports contain potential supply data but not production data. Some authors of the country reports, e.g. the author of the India country report, assume that exports and imports of woodfuels are non-existent or negligible, and equate consumption with production.
Estimating potential woodfuels supply is already difficult, even if estimation of supply is limited to sources coming from forests. Data on wood resource in forests is confined to trunk volume of commercial species (i.e. timber trees) only. Fuelwood that can be collected from crowns of commercial tree species have to be additionally estimated. Supplies coming from non-timber trees and other woody plants from forests have to be accounted for too.
Then, there are woodfuels coming from trees and other woody plants outside forests. These include other wooded lands, agroforestry systems, scattered trees in agricultural lands, homesteads or home gardens, and along roads, rivers and canals. Shrubs and bushes in degraded or wastelands can also be a major source, as in India.
There have been no previous studies that purposely assessed potential woodfuels supply from both forests and non-forest areas. This would involve taking account of the total above ground woody biomass and then subtracting the potential wood demand for non-energy uses. Above ground woody biomass includes the stem, branches, twigs and barks of both timber and non-timber trees and also other woody plants such as shrubs and bushes. The WB-ESMAP Group carried out a survey (1992) in Pakistan that used an approach close to this, but the Pakistan country report only briefly mentioned this study and did not submit data collected from it.25
Estimation of woodfuels production, which should include the identification of specific woodfuels sources, is more difficult. It requires, first, tracing and identifying the land areas that have produced the woodfuels, and then estimating the amount of resources that has already been produced or harvested from these sources. Tracing the sources of woodfuels that have already been consumed has rarely been done before. The same is true to an even greater extent for estimating woodfuels production from these sources. The authors of the India, Pakistan, the Philippines and Viet Nam country reports note that such questions were asked in the household energy consumption studies, but it just involved asking users for general information on the source of their woodfuels (e.g. forests, own land, neighbors’ land, common land).
In the late 1980s, there were studies on woodfuels flows in a handful of cities across the region. These studies were initiated by RWEDP and collected information on the specific sources of marketed woodfuels. But these studies were localized to the city being studied and confined only to woodfuels supplied to urban users. As such, aggregate national figures cannot be extrapolated from the data collected.
The complexity of estimating woodfuels production may explain why there are no production data in any of the country reports (except that of India, whose author, as mentioned before, equates consumption with production, and reasonably assumed there was no export or import of woodfuels in the country).26
As in the case of wood energy consumption data, there has also been improvements in wood energy supply data. However, such improvements are very limited, as can be seen from the wood energy data that were submitted in the country report.
Most consultants provided data that include estimates of woodfuels supplies from both forests and non-forests areas (India, Nepal, Philippines, Sri Lanka, and Viet Nam). Estimates are given in mass or volume units, or both. Those consultants who were not able to collect such data, acknowledge the need for collecting them (Cambodia, Lao PDR and Thailand)27.
The Nepal country report contains a very comprehensive set of time-series sustainable woodfuels supply data for fuelwood, disaggregated by administrative and agro-ecological regions. Data are disaggregated also by land use type for which values for specific woodfuels production per hectare were provided. The analysis of sustainable supply potential used the concept of accessibility. The report provides a good framework for a woodfuels supply database. However, no explanations are provided for the values used in the analyses and computations undertaken.
The Philippines and Viet Nam country reports contain data similar to that found in the Nepal country report, though not as detailed. These reports also contain estimates of sustainable woodfuels supply from both forests and non-forest areas, and provide explanations of how the consultants estimated the values and the assumptions used.
The India and Sri Lanka country reports contain aggregate values of woodfuels supply, but there are no discussions of how the figures were obtained. The remaining country reports contain only data on patterns of land uses, covering both forests and non-forest lands, but at least this is an indication that both are now recognized as important sources of woodfuels.
Several countrry reports contain information on other important factors affecting the potential supply of woodfuels, an indication that there is now a greater understanding of how woodfuels are produced. A survey in India (1993) made a distinction between fuelwood produced from logs (trunks) and those from twigs and branches. Tree management practices (e.g. natural forests, plantations, agroforestry, etc.) were also factors considered in assessing supply potential in other countries (India, Pakistan, Philippines, Sri Lanka, Thailand and Viet Nam), although some consultants provided only anecdotal or qualitative information.
The report from the Philippines contains an example of doing a thorough wood supply potential study. The consultants compared two nationwide studies conducted in the country; the “1989 WB-ESMAP Household Energy Strategy Study” and the “1990 Master Plan for Forest Development Study”. They also obtained data from several other local studies conducted in the country, and incorporated additional information from the international literature to come up with their own estimates of potential supply for the country. The report contains information on the methods and assumptions used, such as:
§ bases for identifying the different types of land uses in the country (despite conflicting data and information from previous studies and confusions in the definitions of forests and other land use terminology);
§ different types of tree management practices, particularly in non-forest lands; and
§ woody biomass productivity and accessibility factor for the different types of land uses and tree management practices.
The results obtained were for one year only. No attempts were made to project time-series data. Such an analysis would require time-series data on land-use changes, but data paucity is a serious problem.
The Philippine consultants did not consider the potential supply from wood wastes generated by the logging and wood processing industries, although examples of this were cited in the report. Neither did they consider wood demand for other end uses aside from energy applications, such as for building materials or raw materials for various wood processing industries. The assumption appears to be that all the potential wood supply will be used for fuel only.
The Viet Nam report also contains a comprehensive woodfuels supply analysis. The author presents official land use data, and values of “woody biomass productivity” and “availability factors” for various land use types. As in the Nepal report, there is no discussion on how these values were obtained, apart from saying that these are the “typical” values used in the country. The author also states that estimations used the “availability factor”, but this is not explained. It could mean the “accessibility factor”, or the supply available after other demands (e.g. building materials, poles, etc.) for wood are accounted for; it could also mean the combination of both factors. The Viet Nam report also contains an assessment of supply from other sources such waste from wood processing industries and recovered wood.
The Sri Lanka report contains a detailed discussion of biofuels supply. The discussions address assessment of supplies from home gardens, rubber tree plantations (resulting from re-planting activities) and various crop wastes, providing estimates of annual potential supply for each type of biofuels. The report contains brief discussions for each type data presented in the report.
The Viet Nam report is the only other report that includes an assessment of supply of other types of biofuels such as crop wastes and perennials.
All authors of the country reports appear to recognize that estimating potential supply or production of woodfuels is a more complex and difficult process than estimating timber resources from forests. Estimation studies require not only an understanding of forests classification systems, but also characterization of land uses that include both forests and non-forest areas. It requires not only an understanding of the management and harvesting practices of commercial (timber) tree production systems in forests, but also the production and management practices for other trees (non-timber) and other woody biomass (e.g. shrubs and bushes), which may be more important for woodfuels supply.
It further requires an understanding that allows identification and quantification of factors (e.g. terrain, land tenure, social factors, cultural practices) that reduce access to supply, including the competing demands for wood. Understanding the production systems for trees and woody biomass in non-forests areas is very difficult, as these production systems have not been studied before (as mentioned in the Philippine country report). Even if one or a few areas have been studied, it is difficult to generalize, as conditions of supply potential and production are site-specific.
Estimating potential supply also requires identifying and assessing other sources of woodfuels not coming from the harvesting of trees. The most important example is woodfuels from wastes (e.g. scrap wood, sawdust, wood shavings, barks, etc.) of wood-based industries.
Finally, woodfuels supply analysis is a “wood balance exercise” that involves assessing all potential supplies and then, deducting from the result all projected demand for non-energy uses of wood. Only the authors of the Philippines and Viet Nam country reports present such an exercise. Nevertheless, their efforts are incomplete as data to make justifiable and acceptable assumptions are lacking. No consultant collected all relevant data to estimate all parameters needed for a complete woodfuels supply analysis or wood balance exercise, as defined above.
There is a need to propagate further the concepts of “wood balance” and develop, on this basis, a clearer and more easily understood framework for woodfuels supply analysis. The exercises done by the Nepal, the Philippines and Viet Nam consultants can be starting points for these.
The data in the India country report are the most similar to the WEIS data. Figures for wood energy consumption are only slightly higher than the WEIS figures except for the figures for the years 1994 to 1998, which are slightly lower (Tables 5, 6 and 7).
The Nepal country report also contains figures similar to the WEIS figures if the FAO conversion standard is used (i.e. 1 MT = 14.3 GJ for wood at 20-30 pecent MC) for converting mass values to energy values.28
In most country reports, the figures are higher than the WEIS figures – by about 10 percent for Viet Nam, 20 percent for Cambodia, almost 100 percent for Philippines, and even higher for Lao PDR. The WEIS figures are higher than the figures from Pakistan (almost 100 percent) and Thailand (between 10 and 55 percent).
It is not surprising that the figures contained in the country reports differ markedly from the figures generated by WEIS. In some country reports, conflicting figures exist, even if the sources are all government agencies (e.g. India, Pakistan, Philippines, and Sri Lanka). Both the data in the country reports and from WEIS are based on estimations. Different estimation methods and assumptions were used and can account for the different results.
The India, Lao PDR, Pakistan, Philippines and Viet Nam reports contain some discussions on estimation methods and assumptions, and, as mentioned earlier, it would be an interesting, although difficult and time consuming, exercise to compare them with those used by WEIS.
Several country reports contain data on urban woodfuels flow. The TOR had explicitly asked for these types of data. As expected, consultants from countries that cooperated with RWEDP to conduct woodfuels flow studies submitted data within the “framework” provided for in the TOR (The TOR was based on the design of the RWEDP supported studies). Data were provided on woodfuels marketing network, actors in the marketing network (producers, charcoal makers, traders, transporters and retailers), the transportation system in use, and the social and economic impacts of woodfuels trading and marketing.
The concept of an urban woodfuels flow study was new to many forestry, energy and agricultural agencies in the early 1990s. The RWEDP raised the awareness of the importance of such studies. The aim of RWEDP was to persuade government agencies and others that woodfuels was a “commodity”, and should be given due attention just like a forest product, or commercial fuel or an agricultural commodity. This is now reflected in most of the country reports29.
Data on wood energy conversion technologies are also presented in some of the reports. For example, the Sri Lanka country report includes not only efficiency figures for various types of biofuels stoves, but also discussions on various woodfuels dependent industries and the efficiency of woodfuels-using processes and the devices common to these industries. The India country report briefly mentions the contribution of biofuels to electricity generation, an emerging modern application of wood and other biofuels.
Table 5. Comparison of WEIS and country report data – PJ per year
|
|
|
Wood energy consumption data (PJ/year) | ||||||||
|
|
|
1990 |
1991 |
1992 |
1993 |
1994 |
1995 |
1996 |
1997 |
1998 |
|
Cambodia |
WEIS Data |
57 |
58 |
60 |
62 |
64 |
66 |
67 |
69 |
70 |
|
|
Country Data |
No data |
No data |
No data |
No data |
94 |
95 |
No data |
No data |
No data |
|
India |
WEIS Data |
2 452 |
2 498 |
2 544 |
2 589 |
2 634 |
2 678 |
2 723 |
2 768 |
2 831 |
|
|
Country Data |
2 514 |
2 556 |
2 575 |
2 592 |
2 610 |
2 630 |
2 647 |
2 664 |
2 683 |
|
Lao PDR |
WEIS Data |
7 |
7 |
7 |
7 |
8 |
8 |
8 |
8 |
44 |
|
|
Country Data |
No data |
No data |
No data |
No data |
No data |
48 |
50 |
51 |
53 |
|
Malaysia |
WEIS Data |
77 |
77 |
79 |
81 |
83 |
84 |
88 |
90 |
92 |
|
|
Country Data |
No data |
No data |
No data |
No data |
No data |
No data |
No data |
No data |
No data |
|
Nepal |
WEIS Data |
172 |
177 |
182 |
187 |
192 |
197 |
202 |
207 |
210 |
|
|
Country Data |
208 |
212 |
217 |
221 |
226 |
231 |
235 |
238 |
243 |
|
Pakistan |
WEIS Data |
235 |
241 |
248 |
256 |
263 |
270 |
277 |
285 |
311 |
|
|
Country Data |
No data |
No data |
No data |
No data |
No data |
278 [A] |
No data |
No data |
No data |
|
Philippines |
WEIS Data |
321 |
328 |
335 |
343 |
350 |
358 |
366 |
374 |
382 |
|
|
Country Data [B] |
No data |
No data |
688 |
No data |
No data |
No data |
No data |
871 |
871 |
|
Sri Lanka |
WEIS Data |
91 |
93 |
90 |
93 |
97 |
98 |
98 |
97 |
97 |
|
|
Country Data [C] |
160 |
159 |
159 |
160 |
163 |
166 |
166 |
165 |
166 |
|
Thailand |
WEIS Data |
327 |
331 |
335 |
338 |
342 |
347 |
355 |
359 |
366 |
|
|
Country Data |
285 |
297 |
287 |
268 |
255 |
233 |
221 |
234 |
232 |
|
Viet Nam |
WEIS Data |
273 |
279 |
285 |
291 |
297 |
303 |
309 |
315 |
319 |
|
|
Country Data |
238 |
357 |
360 |
366 |
369 |
238 |
357 |
360 |
366 |
[A] Excludes an 1989 independent estimate of consumption by industries of about 12.8 million mt or 183 PJ; estimate was for aggregate consumption of wood and other biofuels
[B] The two figures represent the lower and mid range vaues estimated for the country report on the basis of several surveys and studies conducted between 1992 and 2001.
[C] Includes all biofuels, that is, woodfuels and crop wastes.
Table 6. Comparison of WEIS and country report data – million mt per year30
Table 7. Comparison of WEIS and country report data – million cu m per year31
| COUNTRY |
|
Wood energy consumption data (Million cu m/Year) | ||||||||
|
|
1990 |
1991 |
1992 |
1993 |
1994 |
1995 |
1996 |
1997 |
1998 | |
|
Cambodia |
WEIS Data |
5.51 |
5.60 |
5.80 |
5.99 |
6.18 |
6.38 |
6.47 |
6.67 |
6.76 |
|
|
Country Data |
No data |
No data |
No data |
No data |
8.53 |
8.80 |
No data |
No data |
No data |
|
India |
WEIS Data |
236.63 |
241.07 |
245.50 |
249.85 |
254.20 |
258.43 |
262.78 |
267.13 |
273.20 |
|
|
Country Data |
242.60 |
246.66 |
248.50 |
250.14 |
251.88 |
253.81 |
255.44 |
257.08 |
258.92 |
|
Lao PDR |
WEIS Data |
0.68 |
0.68 |
0.68 |
0.68 |
0.77 |
0.77 |
0.77 |
0.77 |
4.25 |
|
|
Country Data |
No data |
No data |
No data |
No data |
No data |
4.64 |
4.83 |
4.93 |
5.12 |
|
Malaysia |
WEIS Data |
7.42 |
7.42 |
7.62 |
7.81 |
8.00 |
8.10 |
8.49 |
8.68 |
8.87 |
|
|
Country Data |
No data |
No data |
No data |
No data |
No data |
No data |
No data |
No data |
No data |
|
Nepal |
WEIS Data |
16.60 |
17.08 |
17.57 |
18.05 |
18.53 |
19.02 |
19.50 |
19.98 |
20.27 |
|
|
Country Data |
20.08 |
20.47 |
20.93 |
21.32 |
21.80 |
22.29 |
22.67 |
22.96 |
23.45 |
|
Pakistan |
WEIS Data |
22.67 |
23.25 |
23.93 |
24.70 |
25.38 |
26.05 |
26.73 |
27.50 |
30.02 |
|
|
Country Data |
No data |
No data |
No data |
No data |
No data |
26.83 |
No data |
No data |
No data |
|
Philippines |
WEIS Data |
30.98 |
31.66 |
32.33 |
33.11 |
33.78 |
34.54 |
35.31 |
36.09 |
36.86 |
|
|
Country Data |
No data |
No data |
66.39 |
No data |
No data |
No data |
No data |
84.06 |
84.06 |
|
Sri Lanka |
WEIS Data |
8.78 |
8.97 |
8.68 |
8.97 |
9.36 |
9.45 |
9.45 |
9.36 |
9.36 |
|
|
Country Data |
15.44 |
15.35 |
15.35 |
15.44 |
15.73 |
16.02 |
16.02 |
15.93 |
16.02 |
|
Thailand |
WEIS Data |
31.56 |
31.95 |
32.33 |
32.62 |
33.01 |
33.49 |
34.27 |
34.64 |
35.31 |
|
|
Country Data |
27.50 |
28.66 |
27.70 |
25.86 |
24.61 |
22.48 |
21.32 |
22.58 |
22.38 |
|
Viet Nam |
WEIS Data |
26.34 |
26.92 |
27.50 |
28.08 |
28.66 |
29.24 |
29.82 |
30.40 |
30.79 |
|
|
Country Data |
22.96 |
34.46 |
34.73 |
35.31 |
35.60 |
22.96 |
34.46 |
34.73 |
35.31 |
13 See FAO. 1997a.
14
End uses and energy end use devices should actually be part of
consumption data.
15 India and the Philippines have also
done this, but this is not reflected in their country reports. Sri Lanka’s
report includes “biomass”, which is a collective term for fuelwood, charcoal and
crop wastes.
16 Some country papers used studies
previously carried out by the national consultants themselves (e.g. Sri Lanka
and Viet Nam).
17 Charcoal is a secondary energy form
of fuelwood produced through a thermo-chemical process, i.e. carbonization or
pyrolysis. Sawdust may also be considered another secondary form of woodfuels
produced through a physical process.
18 Records from the Thailand’s Royal
Forestry Department shows zero consumption of charcoal in many provinces despite
the widespread used of this fuel in urban sidewalk restaurants throughout the
country. Two of the most popular daily Thai dishes – kai yang (barbecued
chicken) and moo yang (barbecued pork) – are prepared both outside and inside
homes using charcoal.
19 Although field measurement
techniques are not mentioned in the India, Pakistan and Philippines country
reports, the present author is familiar with the national household energy
consumption surveys in these countries and can verify that proper field
measurement techniques were used.
20 India conducted another nationwide
household energy consumption survey in 1993, but this was limited to rural
areas. India has also conducted several state-level “category 2” surveys.
21
In 1992, Viet Nam carried out a household energy consumption survey
(supported by WB-ESMAP), covering the Red River Delta Region and the results
were extrapolated nationwide. Sri Lanka did a similar exercise (covering five
districts) in 1999.
22 Thailand is known to carry out
household energy consumption surveys regularly, which can be considered as
category 2, but this was not mentioned in the country report.
23
In surveys involving only interviews, amounts are usually given in
volume units in terms of “piles” of wood, which in actual amount varies across
areas, as the manner of piling and sizes of split wood varies. This is one
reason why woodfuels surveys are complicated.
24 The results of the analyses put
into question the results of the surveys – how could total energy consumption
for cooking in households have decreased significantly when the population has
increased substantially between the two surveys? Were more people eating outside
and/or buying rather than cooking their meals? Was there a massive shift to more
efficient cooking devices? No additional data were provided to do the further
analyses that would allow these questions to be answered.
25
Part of this WB-ESMAP Group survey for Pakistan was a comprehensive
woodfuels supply assessment study involving field measurements. However, the
country report contains data on the areas of the various land use types
producing wood for fuel only, even although volume and mass values were
estimated in the WB-ESMAP study. The data contained in the country report were
not even in a tabulated format.
26 The author of the India country
report seems to negate this assumption himself as the report contained data from
government records on international trade of wood, including woodfuels. The
data, however, were incomplete.
27 The Thailand report includes data
on woodfuels supply from non-forest areas from a woodfuels flow study for Khon
Kaen province.
28 The present author assumes that
all country reports, except Nepal, used the FAO conversion standards.
29
However, this could just be the view of the national consultants
rather than a more widespread view. The issue is not discussed in the
reports.
30 See footnotes of Table 5.
31
See footnotes of Table 5.