This chapter analyses past and present wood energy consumption patterns based on the AIT database. As mentioned in Chapter 2, the AIT database is more reliable than the other two databases in analysing wood energy situations in specific countries for it provides more information with respect to the different aspects of and the factors influencing wood energy use.

The AIT database compiles information mostly from country case studies on wood energy and data and statistics from national government and private agencies. Energy data and statistics from these studies and agencies are based on national standards of energy measurements and definitions that usually vary from one country to another. Some efforts have to be expended, therefore, to make energy units consistent and uniform for more precise comparisons.

The study converts all original energy units into petajoules (PJ), or its derivatives, which is the International System unit for energy. Most countries in Asia are using the tons of oil equivalent (TOE) and its derivatives. The study converts all derivatives of the TOE unit into PJ using the factor 41.9 GJ per TOE (UN, 1987). The Philippines is one exception as it uses the barrel of fuel oil equivalent (BFOE). The study converts BFOE and its derivatives into TOE using the country’s conversion factor of 0.1444 TOE/BFOE (Philippine Energy Plan, DOE, 1996). Another exception is India which uses the tons of coal replacement. The study converts from original physical units of the fuel to PJ using the conversion factors in UN (1987). For example, fuelwood consumption is converted to PJ by using the factor 12.60 GJ per metric tons. Animal dung consumption is converted to PJ assuming a net calorific value of 13.6 MJ per kg. Crop residues consumption are expressed in PJ using the net calorific value of 13.4 MJ per kg for rice husk

By global standards, the region as a whole has high population growth rates (despite serious efforts to control it). The numbers were in the range of 1.1% to 3.2% for the period 1989-1994. China’s average population growth has been maintained below 2% per year and declining since 1970 through the government’s "one-child policy." Average population growth in South Asia, except in Pakistan, Sri Lanka, and Maldives, as well as in some countries in Southeast Asia, is close to 2% per year. The rest have average annual population growth rate above 2.5%.

Table 3.1: Land Area and Population Data

Table 3.1 also shows the varied population densities among the countries covered by the study. The number ranges from 19 persons per sq. km. in Lao to 827 persons per sq. km. in Maldives. The national average, however, must be interpreted with caution. Population densities vary from one region to another within each country and between rural and urban areas. The major urban centers in the region have population density much higher than the national average.

Despite high concentration of population in major urban areas in the region, rural population continues to comprise the majority. The rural areas are still home to at least two-thirds of the total national population, with the exception of Malaysia and the Philippines. However, urban population tends to grow faster (in some cases much faster) than rural population. Table 3.2 shows the extent and growth of the urban population in the RWEDP member countries between 1970 and 1994. All of the countries’ urban population were growing faster than total population and in many the growth was twice as fast. In addition, it was only in the Philippines and Malaysia where total urban population exceeds rural population, though only slightly. In most of the countries, urban population accounted for less than one-third of total population.

The predominantly rural character of the countries in the region partly explains why agriculture continues to dominate or contribute significantly to their economies (or vice versa). Table 3.3 shows that in most countries agriculture still accounts for at least 30% of GDP. In recent years, though, contributions from the primary sectors have been declining. It is now only in the transition economies of Lao, Cambodia, and Myanmar and the South Asian countries of Bhutan and Nepal where agriculture contributes more than 40% of GDP.

The increasing relative output from the industry and services sectors contributed to the high GDP growth in 1985-1994. The result was a marked improvement in the per capita incomes during this period, though for majority of the countries, this performance is still way below that achieved even by the newly industrializing economies of Thailand and Malaysia (see Figure 3.1).

Table 3.2: Urban Population

The national per capita income, however, is an average and does not reflect how income is distributed or shared by the population. Measures of income distribution are better indicators of the poverty situation. Available data show that on top of the low income, many countries in the region suffer from inequitable income distribution in which more than 40% of national income are held by only the top 20% of households, while the bottom 20% of households get less than 10% of income (see Table 3.4). In fact, the situation is slightly worse in the better off countries of Indonesia, Malaysia, and Thailand.

The more important energy indicators are shown in Table 3.5. Together with the information presented in the last section, Table 3.5 shows that countries with better economic performance tend to have higher average energy consumption. This is particularly true for China, Malaysia, and Thailand. Indonesia and the Philippines, although they have relatively high GNP per capita, do not have comparable per capita energy consumption because many people in these countries do not yet enjoy nor can afford the benefits of modern energy. This is reflected in the relatively low electrification ratio in these two countries. Only 26% of households in Indonesia have access to electricity, while 37% of the households in the Philippines remain without access electricity.

However, access and affordability could mean different things in some situations. India and Maldives have high electrification coverage but the low income in India and the presumably poor income distribution in Maldives are partly responsible for the low average energy and electricity consumption in these two countries.

Table 3.3: Real GDP Growth and Sectoral Contributions

At any rate, the more obvious relationship has persisted in most of the countries: that is, low income countries tend to have low average energy or electricity consumption and have poor access to modern sources of energy like electricity.