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4. Wood energy statistics

Fuelwood and charcoal production are rarely quantified and, because of their local and informal character, are only partially and inadequately accounted for in national forestry and energy statistics. This has several causes. In spite of their true importance in both forestry and energy, woodfuels are often considered “minor” forest products by foresters and “traditional” fuels (i.e. obsolete) by energy agencies, especially in developing countries. Forestry as well as energy management considers that the comparatively low commercial value of woodfuels does not guarantee adequate returns on investments in data collection.

Thus, most of the figures reported in national and international databases are the result of various estimation processes rather than field surveys.

In most cases the production of woodfuels is derived from consumption data, considering that fuelwood production is demand-driven and not independent, and that in a general national context woodfuel production is equal to woodfuel consumption (minus export plus import), since large accumulations and storage beyond the annual consumption are uncommon.

In other cases the production of woodfuels is derived from forest products statistics. These statistics should be checked extremely carefully since there are risks of systematic underestimation as a result of two main factors:

Detailed metadata on the original data sources, estimation methods, confidence intervals, etc. are never available. Reasonable information, useful for estimating data reliability, is sometimes provided by country studies. Regional and international databases provide only an approximate indication of data sources or very generic labels such as “official data” or “estimated value”.

In order to qualify i-WESTAT figures as well as possible, the secondary sources associated which each entry were ranked by “reference type” according to their original data sources and/or estimation approaches, as derived from available metadata or other documentation. A total of 15 reference types were defined, as described in Table 10.

The distribution of primary source data by reference types is summarized in Appendix 10.

In addition, the table in Appendix 10 provides a tentative reliability ranking, established with the assumption that field survey data are the most reliable and that the further from the “field survey” level, the lower the reliability. The results of this very tentative assessment of data reliability are summarized in Table 11.

TABLE 10
Common reference types

Type

Reference type

Remarks

1

National-level field surveys of fuelwood and charcoal consumption

Most consistent and reliable estimates of consumption and, indirectly, production.

Usually point data referring to single years, disaggregated by sector and by urban/rural areas. Weak definition of supply sources and sustainability (e.g. selected country reports)

2

Country studies based on national information from national and local surveys and other supporting material

The quality of these studies varies considerably. In general, they represent the best “blend” of scattered and fragmented data that are not available outside the countries. Usually providing short time series based on observed data rather than pure modeling. (e.g. country reports EC-FAO partnership program).

3

National forestry statistics on fuelwood and charcoal production/consumption (forestry perspective)

Forestry statistics based on concession data and timber control measures tend to underestimate woodfuel production because of informal unrecorded practices and the fraction of non-forest sources (e.g. Slovenia Statistical Office, forest products statistics) In other cases forestry agencies combine forestry and energy data and provide more comprehensive estimates.

4

National energy statistics on fuelwood and charcoal consumption (energy perspective)

These include energy data from national statistical offices as well as from regional databases directly linked to them (i.e. Eurostat, OLADE SIEE) (e.g. Slovenia Statistical Office, energy statistics).

5

Projection of woodfuel consumption based on per capita values and population statistics

Reliability depends on the quality and representation of reference consumption values. Valid approach for short projections since rarely account for saturation dynamics (e.g. WETT projections).

6

Modeling of fuelwood and charcoal consumption based on socio-economic variables

Estimation reliability depends on the quality and representation of reference consumption data. Suitable for longer projections since saturation dynamics are accounted for. Suitable for filling data gaps (e.g. GFPOS)

6.1

National model

Model valid for a specific country based on data exclusively from that country. National models can only be made in the presence of rich country data and are usually the most reliable (e.g. GFPOS national models).

6.2

Subregional/continental model

Model valid for all countries of a region, based on data from that region. Regional models are less reliable than national ones because the dataset used to develop them is rarely representative of all country conditions (e.g. GFPOS regional and continental models).

6.3

Global model

Model valid for all countries of the world, based on data from any country. Global models are less reliable than national and regional ones (e.g. GFPOS).

7.1

Questionnaires filled in by national forestry authorities (official statistics) or authoritative sources (unofficial statistics)

Reliability is extremely variable depending on the reference data used by government officials. Reliability of woodfuel data in forestry questionnaires is low when they refer exclusively to official forestry statistics. The reliability increases when forestry and energy statistics are integrated. Estimation processes are not documented (e.g. FAOSTAT, UN energy statistics).

7.2

Questionnaires filled in by national energy authorities

Reliability is extremely variable depending on the reference data used by government officials. Estimation processes are not documented (e.g. UNECE Questionnaire on Renewables; IEA/AFREPREN Questionnaire on Biomass Energy Statistics).

8

Modeling/processing of questionnaire data

Same as 7.1 and 7.2; reliability depends directly on the questionnaire data used as input data (e.g. GFPOS “FAOSTAT” models).

9

Derived from aggregation of official and estimated data (types 6 to 8)

Reliability of aggregated values depends on the quality and consistency of composing elements (e.g. aggregation of original FAOSTAT data on wood products to form WEIS parameters).

10

Quoting international databases, international and regional thematic studies and reviews

Based on miscellaneous sources (country reports, national and international statistics, etc.). Reliability is extremely variable. Considering the frequent revision of time series, these references are only valid for a few years.

11

Undefined

 

TABLE 11
Very tentative reliability ranking of fuelwood consumption statistics from primary sources based on reference types

Tentative reliability ranking (fuelwood consumption data)

High

Mid-high

Medium

Mid-low

Low

Undefined

WETT99 best estimate

8

14

 
 

42

36

Country report

89

10

1

 
 
 

ENDA/IEPE

 
 
 
 
 

100

ESMAP

 
 
 
 
 

100

Other national

21

32

4

 

29

13

IEA non-OECD 99

 
 
 
 
 

100

FAOSTAT (1998)

 
 
 
 
 

100

UN energy statistics 1995

 
 
 
 
 

100

RWEDP

3

 
 
 
 

97

FUNBAR

 
 
 
 
 

100

OLADE 80–97

 
 
 
 
 

100

FAOSTAT (2003)

 
 

100

 
 
 

GFPOS 1970–2030

 

6

24

70

 
 

OLADE 90–02

 

100

 
 
 
 

IEA (2002)

 

55

5

 

28

13

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