B. Nag, J. Parikh r Energy Economics 22 2000 441]461 451
transport. Data for energy use in agriculture includes consumption of petroleum Ž
. products and natural gas by plantations like tea , but does not include petroleum
products used by the agriculture sector for transportation of agricultural commodi- Ž
. ties. Annual time series data for consumption and fuel quality in kcalrkg for each
of these six fuels, namely coal, high speed diesel oil, light diesel oil, furnace oil, LSHS and natural gas and electricity by each of the sectors has been used for the
period 1984]1994. Same data for aviation turbine fuel has been additionally used by the transport sector. Fuel consumption and fuel quality data are from energy
Ž .
statistics Ministry of Petroleum and Natural Gas, MoPNG and Central Electricity Ž
. Supply Authority, Government of India CEA . Data for sectoral value added have
Ž .
been acquired from National Accounts Statistics of India CSO . 3.3. Transformation and con
¨
ersion sector Study has been done for the period between 1974 and 1994 using annual time
series data for fuel quality of each of the six fuels, i.e. coal, high speed diesel oil, light diesel oil, furnace oil, LSHS and natural gas and their consumption by power
Ž .
sector. Source of this data is Central Electricity Supply Authority CEA .
4. Discussion of results
4.1. Per capita emissions Increase in per capita emission in itself is not so much of a concern to India as
the current level of emissions have reached a mere 0.23 Tc per capita. However, it is important to identify contribution of the various factors, namely mix of energy
sources, efficiency of energy use and rising income which boosts greater energy use, and also the change in trend of these factors for suitable policy analysis.
The results as shown in Fig. 1 indicate that until 1980, energy intensity was the major determining factor behind per capita emissions and from 1980 onwards
income effect became the major contributor to per capita emissions. In the first decade of study, growth rate of per capita emissions was lower than in the 1980s
Ž .
when per capita emissions grew by 51.7 from 1980 to 1990 Table 1 . In the period 1970]1980, it was 29.4. From 1980 to 1990, income effect showed a sharp
rise by 44 and approximately 89 of the growth in per capita emissions were contributed by this factor. From 1990 to 1995, per capita emission rose by
approximately 22 and all the three effects contributed to the rise, although fuel
Ž .
mix effect was almost nil the index being very close to 1 . Approximately 21 of the per capita emission rise was influenced by intensity component, that is, during
this period economic activity became more energy intensive. Fuel mix effect has been almost constant, slightly moving in favor of reduced emission.
The above analysis clearly shows that although rising energy intensity was the major factor behind per capita emission during the 1970s, from the 1980s onwards,
income became the most important factor. Such a trend could be indicative of
B. Nag, J. Parikh r Energy Economics 22 2000 441]461 452
Fig. 1. Divisia index decomposition of per capita emission.
higher energy efficiency in the 1980s and can be attributed to the reason that after the first oil crisis in 1973, India undertook the policy of energy independence,
which on the demand side implied energy efficiency. This along with the fact that India saw a high annual rate of growth in the 1980s led to a shift in the trend.
Annual growth rate increased to approximately 6 in the 1980s from a low of approximately 3 in the 1970s. So although energy intensity used to contribute
Table 1
a
Divisia index decomposition of per capita emission intensity 1970]1980
1980]1990 1990]1995
Per capita emission 1.294
1.517 1.216
Energy mix effect 0.987
0.986 1.002
Ž .
Ž .
Ž .
y 4.6
y 2.7
1.2 Energy intensity effect
1.210 1.068
1.043 Ž
. Ž
. Ž
. 75.0
13.8 20.61
Income effect 1.083
1.440 1.163
Ž .
Ž .
Ž .
29.6 88.9
78.1
a
Note. Figures in parentheses indicate percentage contribution of the various effects to change in
per capita emission.
B. Nag, J. Parikh r Energy Economics 22 2000 441]461 453
nearly 75 of the per capita emission in the 1970s, the contribution declined to only approximately 13.8 in the 1980s.
Ž .
If the existence of an environmental Kuznet’s curve EKC is assumed for India, the rapidly rising per capita emissions following the trend of rising per capita
income indicates that India is still in the rising slope of the inverted U-shaped EKC. CO being a global pollutant does not inflict local damage and its abatement
2
cost being very high, the peak of EKC for CO is usually expected to be very high,
2
Ž .
if at all it exists Cole et al., 1997 . The presence of Kuznets curve for CO
2
emission is debatable since CO being a global pollutant does not give rise to local
2
Ž .
disutility in the short run Arrow et al., 1995; Moomaw and Unruh, 1997 . However, in India, potential for improved efficiency in energy use, transmission
and distribution of electricity, completion of the shift towards commercial fuels from traditional fuels and full electrification of all villages indicate towards the
possibility of reaching a peak of the Kuznets curve. The downward movement might have to be a conscious effort towards removal of market distortions,
Ž .
structural change towards less polluting sectors growth of the service sector and international transfer of energy efficient and emission abating technologies.
4.2. TFE: cross-sectoral analysis Changes in emission intensity of the four sectors have been shown in Fig. 2 as
estimated from their energy use and composition including electricity. Comparing the different sectors, we find that transport sector had the strongest reduction in
intensity of 18, between 1984 and 1994 followed by the industrial sector where the reduction was approximately 8. Emission intensity in the agricultural sector,
however, has risen sharply by approximately 2.5 times. This could be explained by the fact that highly subsidized price of power in the agricultural sector, has led to
indiscriminate use of electricity in this sector. Emission pertaining to fossil fuel use in power generation is considered as emission from electricity. Electricity being a
transformed energy has a high emission coefficient due to generation and transmis- sion losses; thus, emission resulting from electricity consumption is very high for
the agricultural sector. Approximately 95 of emission in agriculture comes from electricity consumption.
In the transport sector, coal use in railways has been gradually substituted for electricity, so emission due to coal use shows a drop from 26 in 1984 to 1 in
1994. Although emission coefficient of electricity is higher than coal, emission from power consumption shows an increase of only 1 because end use efficiency of
electricity is very high. Diesel consumption and hence emission from it has increased, and it is the major contributor to emission from the transport sector. Its
share of emission increased to 75.5 in 1989 and 86 in 1994 from 62 in 1984. In the commercial sector, the major fuels consumed have been natural gas and
electricity and the share of natural gas in total emission has been increasing over time. It increased by 5 between 1984 and 1989 and by 1.5 between 1989 and
1994. Share of emission from electricity consumption has declined from 84 in 1984 to 76 in 1994. In the industrial sector emission due to coal consumption
B. Nag, J. Parikh r Energy Economics 22 2000 441]461 454
Fig. 2. Carbon emission intensities in different sectors.
increased from 38 in 1984 to 42 in 1994. Emission from power consumption has decreased by approximately 4 in this period.
11
Results of the Divisia decomposition on emission intensity due to consumption of major primary energy carriers and electricity are presented in Fig. 3, which
shows the evolution of carbon emission intensity, emission coefficient, fuel mix, energy intensity and structural effects. Fig. 4 presents the results of the analysis
without considering power consumption by the sectors. Hence it does not include the emission coefficient change effect which results solely from the changing
coefficient of power.
Fig. 3 shows that in the period between 1984 and 1987, all the three factors of energy intensity, emission coefficient and structural effect contributed to the rising
emission intensity. In the period between 1984 and 1987, emission intensity increased by 15, of which approximately 64.5 was contributed by the rise in
emission coefficient. The effect of this factor, however, declined gradually. From 1991 onwards energy intensity effect was the most dominating factor in the rise in
emission intensity. Results indicate that the contribution of the different factors have varied considerably over the years without showing any clear trend. So study
of sub-periods might be misleading depending on the choice of end-points.
When the above analysis is carried out without including power consumption by
11
We consider power bought from utilities. Some of the coal consumed by the industries is used for generating power within industries.
B. Nag, J. Parikh r Energy Economics 22 2000 441]461 455
Ž .
Fig. 3. Decomposition of emission intensity of final energy consumption including electricity .
Ž .
the different sectors, results show Fig. 4 that emission intensity from direct consumption of fossil fuels is falling and declining energy intensity is the major
causal factor behind this change emission intensity. Fuel mix effect and structural shift show similar movements as in the previous analysis including electricity, the
former contributing to reduction in emission intensity while the latter showing movement towards energy intensive sectors. In the period from 1984 to 1994,
emission intensity shows a fall of 28 caused primarily by energy intensity effect, which contributes 121 of the decline and by fuel mix effect, which contributes
14 of the decline. Structural shift has an effect of approximately 35 to an increase in emission intensity.
The two analyses, with and without power sector, captures implicitly the effect of fuel substitution. The sharply declining fuel energy intensity in the second analysis
and a rising energy intensity in the first analysis, shows that in Indian economic sectors, direct fossil fuel consumption has been substituted by power consumption.
This substitution has been distinct for the transport sector. However, the fact that
Ž .
the fuel mix effect is less than 1 0.973 , indicates that the reduction in fossil fuel use and improved efficiency of end use of electricity dominates over the rise in
electricity use.
B. Nag, J. Parikh r Energy Economics 22 2000 441]461 456
Ž .
Fig. 4. Decomposition of emission intensity of final energy consumption excluding electricity .
4.3. Transformation and con
¨
ersion sector Coal is the major fuel used in thermal power generation in India. However, the
quality of coal going to thermal power generation has been declining in India as shown in Fig. 5. Energy used in power generation, measured as gigajoules per
Ž .
gigawatt hour GWH of thermal power generation shows a sharp decline when the calorific value of coal used is taken into account. From 1974 to 1984, the ratio of
primary energy input in GJ to final electricity output in GWH declined by 12.4 and from 1984 to 1994, it further declined by 14.
Ž We have carried out our analysis using both constant calorific value 5000
. kcalrkg and varying calorific value of coal to study the impact of coal quality
Ž .
decline on measurement of emission intensity growth. Results show Figs. 6 and 7 that the impact of coal quality on emission is substantial and the analysis fails to
project the true picture if this aspect is ignored. Ž
. Emission intensity with constant calorific value of coal Fig. 6 follows the path
Ž of fuel intensity while fuel quality effect resulting from quality variations in other
. fuels used in power generation like various petroleum products and natural gas
and generation mix effects have remained almost constant. Emission intensity shows a decline by approximately 5.5 in the period of analysis. However, when
changing quality of fuels is included in the analysis, the decline in emission intensity turns out to be much higher, approximately 25. The decomposition for
sub-periods are shown in Table 2a,b and the major contributor to fall in emission
B. Nag, J. Parikh r Energy Economics 22 2000 441]461 457
Fig. 5. Calorific value of power grade coal in India.
intensity in all the sub-periods in Table 2a, is the fuel quality effect. In the overall period of analysis, fuel quality effect contributed almost 74 of the decline in
Ž .
emission and the rest of the decline was contributed by intensity 24 and
Fig. 6. Decomposition of emission intensity of power generation with constant calorific value of coal.
B. Nag, J. Parikh r Energy Economics 22 2000 441]461 458
Fig. 7. Decomposition of emission intensity of power generation with declining calorific value of coal.
Ž .
Ž .
generation mix effect 2 . In the analysis without coal quality Table 2b , intensity effect is the major determinant of emission intensity.
5. Policy implications and conclusion
