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An analytical model to compare energy-efficiency indices and CO2 emissions in developed and developing countries
An analytical model to compare energy-efficiency indices and C O emissions in developed and developing countries
2
Luiz Pinguelli Rosa and Mauricio Tiomno Tolmasquim
This paper shows how conventional definitions of efficiency and energy intensity, based on the technological and economic framework of developed countries, can mask the real situation in developing countries. New definitions are proposed, such as a generalization of Laspeyre's index. A broad comparison is presented of COe emissions from the energy system of Brazil with those of USA and other OECD countries using a simple factorization model. The final comments point out the disturbing consequence of deregulation and free market international forces, which are pushing Brazil towards an increasing use of fossil fuels, which are COe emitters, in place of endogenous renewable energy, such as hydro and biomass, which are not. Keywords: CO2 emissions; Model; Developing countries
The use of fossil fuels and the burning of wood and subsequent deforestation are presently considered to be the major anthropogenic sources of greenhouse gas emissions into the atmosphere. The developed countries (DCs) consume most fossil fuel energy, while forest destruction occurs mostly in less developed countries (LDCs). Among other anthropogenic global warming gases (GWGs), COe is the most relevant for climate change. 1 There are still uncertainties about the degree of these changes but, in principle, they could cause severe damage to the environment and to human life. The risk of environmental catastrophe is Luiz Pinguelli Rosa is with COPPE/Universidade Federal do Rio de Janeiro, Centro de Tecnologia - Bloco C, 21949-900 - Rio de Janeiro, Brazil; Mauricio Tiomno Tolmasquim is with FINEP and Universidade Federal Fluminense, Praia do Flamengo, 200, 22210-030 - Rio de Janeiro, Brazil.
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therefore considered great enough to justify political decisions to limit GWG emissions, in particular that of CO2. The canonical solutions that have been proposed are: • to control CO2 emission through either energyefficiency improvement or fossil fuel substitution; • and to avoid deforestation or to create CO2 sinks through reforestation. 2 But these solutions can themselves generate problems such as the need for large investment and a possible reduction in economic growth. The situation is worse in LDCs than in DCs, because they do not have the capital for the necessary investment. External debt makes the economic situation of LDCs even more grave. Furthermore, the LDCs have low per capita energy consumption compared with DCs. There are also other differences: DCs have a better quality of life and higher levels of education and of scientific knowledge, as well as stronger technological capabilities. If ethical as well as economic considerations are taken into account it is apparent that responsibility for controlling CO2 emissions should not be shared equally between the international community. However, some proposals must consider the maintenance of LDC living standards, since the population growth is controlled, while DCs could improve their patterns of consumption and reduce energy intensity. In the next section, this point will be discussed in detail to show how conventional definitions, based on DCs' technological and economic framework, can mask the real situation in LDCs. Other authors have studied trends in energy indices) Here, they are analysed to correct old definitions and to propose new ones, such as a generalization of Laspeyre's index, for CO2 emissions. The third section consists of a broad comparison of COz emissions 0301-4215/93/030276-08 © 1993 Butterworth-Heinemann Ltd
An analytical model to compare energy-efficiency indices and
CO 2
emissions in developed and developing countries
14
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12
10
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--ql II
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i i
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Ii,! --
l
i
I
I
0
1973
I
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
Figure 1. Average fuel consumption of cars in Japan (l/kin) Source: K. Matsui, 'Energy in Japan', International Conference on Energy Consumption, Friedrich Ebert Foundation, New Delhi, 1989.
from the energy system of Brazil with those of USA and other OECD countries. A simple factorization model is presented and applied, showing that endogenous renewable energy uses can make LDCs more efficient than DCs in CO2 emission per unit of energy. The final comments in the last section point out the contradictory tendency of deregulation and free market international forces, which push LDCs such as Brazil towards replacing indigenous renewable energy, such as hydro and biomass, with increased fossil fuel consumption and consequent higher CO2 emissions.
L i m i t s o f e n e r g y intensity a n d efficiency indices
Analysis of energy-efficiency increase in DCs Recent data indicate a significant improvement in energy efficiency in DCs. The same is not true in LDCs. However, the improved efficiency of cars and household appliances in DCs has gone hand in hand with higher living standards and increased consumption. Car engines, for instance, are more efficient; but average car size is larger, cars are used more often and they are driven faster, This is particularly true in Western Europe and Japan. 4 The following arithmetic formulae make the point. E N E R G Y POLICY March 1993
Energy efficiency, f, can be defined as the relation between useful energy consumption, U, and final energy consumption, E, in such a way that E-
U f
(1)
It is true that f is growing in DCs; but if U also increases, the net result can be the increase of E for some types of equipment, according to Equation (1). For instance, Figure 1 shows that car fuel consumption per kilometre has increased in Japan in each year from 1982 to 1987.5 In West Germany, the same has occurred with electric energy in households, as shown in Table 1.6
Analysis of energy intensity increase in Brazil As far as productive activities are concerned, there Table 1. Electric energy consumption per capita in private households in West Germany (TWh/household/year). Appliance Lighting, TVs, small appliances Refrigerators, freezers Private household total
1970 9.0 7.(1 43.0
1983 13.8 15.2 90.0
1983/1970 53% 117% 109%
Source: U. Hansen, 'Decoupling of energy consumption and economic growth: the German experience', International Conference on Energy Consumption, Friedrich Ebert Foundation, New Delhi, 1989.
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An analytical model to compare energy-efficiency indices and C02 emissions in developed and developing countries Table 2. Electric energy content of some Brazilian export products.
Products Aluminium Production (103 t)
Export (103 t) Exported electric energy (GWh) Iron alloy Production (103 t) Export (103 t) Exported electric energy (GWh)
1975
1980
1985
1987
1987/1975
121.3 1.8 30.4
200.6 11.5 198.9
549.4 215.4 3463.1
843.5 456.9 7219.0
695% 25 383% 23 746%
255.8 58.6 304.7
548.1 175.6 930.7
757.3 348.4 2055.6
823.8 387.2 2400.6
322% 660% 788%
Source: M. Tolmasquim, La Strat~gie Br&ilienne d'Adaptation aux Chocs P~troliers, PhD thesis, l~coles des Hautes l~tudes, Paris, 1990.
has recently been a clear reduction of energy intensity in DCs. Energy intensity is defined as the relation, e, between final energy consumption, E, and the gross national product (GNP), R: e -
E R
g -
v
where V--
(3)
which is expressed in tonnes of oil equivalent per tonne of product (toe/t). It is related to the previous 278
(4)
e--
(2)
The index e is expressed in toe (tonnes of oil equivalent) per US dollar. It can also be applied to each particular sector, i, of the economy. However, a hypothesis to be checked is that part of the reduction of Equation (2) in DCs could be due to the transference of energy intensive industries from DCs to LDCs. Statistics show that there is a tendency for DCs to concentrate their economic development in technology services, high technology industries, computer systems and software, while they import steel, aluminium and other intensive energy materials. This tendency could mean that DCs' indirect energy consumption is hidden by the importing of these products. Table 2 shows the increase of electric energy content of some Brazilian export products. 7 On the other hand, energy intensity in LDCs has grown in several specific cases and has slowly decreased in others. However, this handicap seems to be worse than it really is, because the definition in Equation (2) is based on added value R instead of on physical quantity. That is the simplest operational way to define a global energy index for the economy, because it is always possible to sum monetary values in the denominator of the index. This is not valid for physical values expressed in units of mass, M, of different products. But, for a particular sector of industry, or of agriculture, it is useful to define an energy physical intensity: E M
measure of intensity by: g
R
(5)
M is the mean value of the product in US$/t. All these variables can be used for particular sectors. Hence, the increase in e (the energy intensity) could be partially due to the decrease in v (the mean value of the product) in such a way that energy physical intensity g could decrease while e increased. Table 3 shows the energy consumption (Ei) and the added values (Ri) in GNP for a selected set of industrial products in Brazil, with their respective energy intensities (ei). The physical quantities (M/) of the products corresponding to Table 3 are shown in Table 4, with the energy physical intensities (gi). It can be seen that in Brazil from 1974-88, for cement, iron and steel, other metals and paper, gi (energy physical intensities) declined, while ei (energy intensity) increased with the exception of cement for which, even so, the decrease in ei is smaller than that of gi. 8
Global intensity indices and generalization of Laspeyre's index for energy The above set of products accounted for 67% of Brazil's industry energy consumption in 1988. Overall, the total energy intensity index is ~,iEi
ET
Yigi
RT
er = - -
(6)
The same method is not applied to total energy physical intensity because the sum of masses of different goods is not a useful quantity; but it is meaningful to add the indices gi, ie the total energy needed to produce 1 unit of mass of each product i belonging to the set. Tables 3 and 4 give the indices ENERGY POLICY March 1993
An analytical model to compare energy-efficiency indices and C02 emissions in developed and developing countries Table 3. Energy intensity for a set of Brazilian products, a 1974
Cement-ceramics Metallurgy Chemicals Textiles Paper Total
1988
Added value R, (106 US$)
Energy consumption E, (103 toe)
Energy intensity e, (toe/lO 3 US$)
Added value R; (106 US$)
Energy consumption E, (103 toe)
Energy intensity c, (toe/lO 3 US$)
1988 Energy intensity variations e, (1974 = 100)
2799 5486 5391 6516 1598 21790
4884 8359 2717 1533 1930 18923
1.566 1.524 0.504 0.235 1.208 0.868
4122 9090 9297 8101 3009 33619
5887 26965 6877 2398 4947 47101
1.428 2.966 0.740 0.296 1.653 1.401
91 194 147 126 137 161
Source: Brazilian G o v e r n m e n t BEN, Balanfo EnergOtico Nacional, Brasilia, 1990. Note: aConstant 1980 dollars.
er and gr. From 1974 to 1988, the former (energy intensity) has increased 61%, while the latter (energy physical intensity) has decreased 7%:
gT =
Z" Ei = Zig i
(7)
' Mi
h (to,t) -
To improve this new indicator, it is possible to define the weighted index: g T = Zimigi
(8)
where the weights can be either m i --
Ei
(9)
Er
or
mi =
Alternatively, the so called Laspeyre's or base weighted price index of economic theory can be generalized for energy physical intensity through the formula: 9
R,
(10)
RT
It seems to be more realistic to use Equation (9) for a physical index definition, avoiding the effects of monetary varations in (10).
Zi Mi(to) gi(t)
(11)
Y~i Mi(to) gi(to)
The denominator is the energy needed for a basket of products defined by the physical set {Mi(to)} which means the quantities Ml(to) of product 1, M2(to) of 2 and so on, in the reference year t0. If the fixed basket is assumed as the real quantities produced in the year to, the denominator is total energy Ev(to). The numerator always gives the energy requirement for the fixed basket but with the energy physical intensities of the considered year t, gi(t). So Equation (11) is the ratio between energy consumption in the year t and the energy consumption in the year to for the assumed basket. In the case of choosing this basket as the unit set {Mi(to) } = {1,1 . . . 1 } , the generalized Laspeyre's index (11) is reduced to the relation:
Table 4. Energy physical intensity for a set of Brazilian products. 1974 Mass added value
Energy physical intensity gl (toe/t)
Mass added value
(103 t)
Energy consumption Ei (103 toe)
14920 7507 288 218 9036 1590 2984 ND
2271 5985 1964 410 2717 1533 1930 16810
0.152 0.797 6.819 1.881 0.3t) 1 0.964 0.647 11.561
Mi b
Cement Iron and s t e e p O t h e r metals ~ Iron alloys a Chemicals Textiles Paper Total
1988
(103 t)
Energy consumption Ei (103 toe)
Energy physical intensity gl (toe/t)
24819 24657 1509 894 16278 1948 8370 ND
2846 16796 7879 2302 7002 2384 4994 44203
0.115 0.681 5.221 2.575 0.430 1.224 0.597 10.843
Mi b
1988 Energy physical intensity variations gt
(1974 = 100) 75 85 76 137 143 127 92 93
Notes: aSum of iron and steel, other metals and iron alloys = metallurgy in Table 3. bMi = not defined (ND). Source: Calculated with E q u a t i o n (3) and Brazilian G o v e r n m e n t B E N , Balanqo Energ~tico Nacional, Brasflia, 1990.
ENERGY POLICY March 1993
279
An analytical model to compare energy-efficiency indices and C02 emissions in developed and developing countries Table 5. Weighted energy physical intensity and generalized Laspeyre's index for the products set of Table 4. Index
Weighted: gt h
1974 (toe/t)
1988 (toe/t)
1988 (1974= 100)
1.357 -
1.532 -
113 98
Source: Calculated with Equations (8), (9) and (11).
certainly the case for Brazil, which assumes a conventional thermal efficiency of 27% for overall electric energy generation in the country. But almost 90% of the electricity generation in Brazil is yielded by hydro, with an efficiency higher than 90% in energy conversion. The correction factor for energy E, which is registered in statistical data, 12 is easily obtained by: - 1 -aH
h(to,t)- gr(t)
gr(t0)
(12)
with gr given by the formula (7). The value of (12) can be seen in the last row and last column intersection in Table 4. Table 5 shows the values of h and gr for the same set of products considered in Table 4. The value of gT- in 1988 was higher than that in 1974, due to the increasing participation of energy intensive products in the Brazilian industry, especially in exports, as has been shown in Table 2. On the other side, the Laspeyre's index h shows that the energy consumption for the fixed basket of products, in 1988, was lower than in 1974, according to the last row of Table 4. This indicates an efficiency improvement. The comparison between Tables 3 and 5 shows that, while the energy intensity of a representative set of products of the Brazilian industry increased 61% between 1974 and 1988, the generalized Laspeyre's index decreased 2%. This means that there was an important decrease of the mean added value of the set of products analysed.
The convention for the energy equivalent of hydroelectricity Last, but not the least, regarding energy index trends, there is the effect of conversion factor conventions which are adopted in the basic energy statistics of each country. For instance, the methodology of the International Energy Agency for OECD countries states that the primary energy equivalent of nuclear and hydro energies to electricity generation is calculated with a conventional efficiency of 38.5.1° In fact this does not mean technical efficiency, but represents the equivalent amount of thermal fuel which would be required to produce the same electric energy. Other countries assume different efficiencies, such as 57.3% in Norway and 35.1% in Japan. 11 In countries with large thermo electricity participation, as in most DCs, this kind of convention is not so far from reality. But, when hydroelectricity is dominant, this convention substantially magnifies real energy inputs. That is 280
(IT t 1 -~
(13)
where E' = corrected value corresponding to the registered energy E a H = participation of hydroelectricity fT = conventional thermal efficiency FH = actual hydro efficiency Formula (13) makes clear that when aH (the participation of electricity) increases the corrected value E' decreases; in other words, the energy intensity of the economy decreases. For the present calculation fT/fH = 0.3, a H = 14.4% in 1970, and a H = 33.1% in 1989.13 If the Brazilian energy balance is corrected by actual hydroelectricity efficiency, instead of the conventional measure, energy intensity decreases, as is shown in Table 6. The results of this section must not be considered as evidence that energy efficiency in LDCs, such as Brazil, is quite good. But these results point out that there are peculiarities that could be neglected by the usual indices for energy diagnosis, which should be constructed more carefully to take account of the specific situation of each country. Obviously, the Brazilian results cannot be applied to all LDCs. However, some features could also be present in other countries, such as the fall in monetary value of energy intensive goods. A hypothesis to be checked in future studies is the CO2 emission export from DCs to LDCs, due to the importing of energy intensive products by DCs. LDCs, on the other hand, have some comparative advantages in endogenous renewable energy sources, such as hydro and biomass, which avoid CO2 emissions.
Table 6. Corrected energy intensity due to electric energy equivalent (toe/103 US$).
Conventional Corrected
1970 0.675 0.602
1989 0.641 0.498
1989/1970 95% 83%
ENERGY POLICY March 1993
An analytical model to compare energy-efficiency indices and Comparative and biomass
Y~i Ci Ei
(14)
Ei Ei
where Ei = energy use of the form i (toe) ci = CO2 emission per unit energy used (t C/toe)
The coefficient ci depends on efficiency 1] (toe/t fuel) of energy conversion and on CO2 emission, di (t C/t fuel), of the fuel: Ci-
di
(15)
f, Energy substitution can decrease d~ and efficiency improvement increases f,-, giving a decrease in ci in (14) and (15). Among fossil fuels, coal has the largest d~, while the natural gas has the smallest. Oil has an intermediate position. Combined cycle plants with gas turbines give f/values higher than conventional thermoelectric plants. But hydro and sugarcane products, as well as nuclear energy, have di = O. Assuming an average value, Cx, for the CO2 emission by all energy forms with net CO2 emission, and calling their sum Ex, a rough approximation for (14) is given by: = c,. a~
(16)
where
Er
ax = .... ET
(17)
For electricity generation in Brazil, the following energy sources are used: 14 H N P C B BR M
= = = = = = =
hydro (89.9%) nuclear (4.9%) oil products (2.2%) coal (1.8%) biomass (1.1%) renewable biomass (bagasse) (0.3%) natural gas (0.1%)
Hence: ENERGY POLICY March 1993
emissions in developed and developing countries
ax = C + P + B - BR + M
advantage of LDCs in hydro energy without CO2 emissions
The Brazilian case is interesting for electricity generation and transport, because hydro and sugar-cane alcohol are used. Neither of these energy products contributes to CO2 emissions (or their contribution is so insignificant that it can be neglected for practical purposes). The average emission per energy consumption in a given sector is expressd by c -
CO 2
(18)
The fractions ax (18), in Brazil, corresponds to nearly 5%, while in the USA, it amounts to almost 75%. Using the approximation in Equation (16), Brazil is therefore more efficient than the USA in respect of CO2 emissions per unit of electric energy generated (t C/MWh) by the factor: ~(USA) ~(BR)
0.75
- - -
0.05
- 15
(19)
In car transport, Brazilian fuel consumption is approximately half and half alcohol and gasoline, while in the USA, it is almost 100% gasoline. So the relation between CO2 per gigajoule in the USA and Brazil is: ?(USA) ?(BR)
1.0 - -
0.5
- 2
(20)
The above rough calculations (19) and (20) provide an order of magnitude to estimate how much more efficient Brazil is than the USA in these cases. The time evolution of CO2 emission from an energy system can be analysed by a simple factorization model: CO2 POP
-
CO2 ENERG Y
x
ENERGY GNP
x
GNP P O P U L A TION
(21)
The first factor in Equation (21) can be interpreted as energy substitution, the second as variation of energy intensity, and the last as variation of income per capita. The results from (21) are shown in Table 7 for Brazil and some O E C D countries, in 1989, taking the year 1970 as reference (index = 100). Brazil has the worst position in the increase of CO2 emissions (first row of Table 7). But population has increased more in Brazil than in any of the other countries considered in Table 7. Even so, it continues to have the worst behaviour in the variation of CO2 per inhabitant (apart from Italy) from 1970 to 1989. However, in the coefficient of CO2 per unit of energy consumption (fourth row), Brazil turns out to have the second best position after France. This improvement can be explained by the large use of renewable energy sources such as hydroelectricity and alcohol in Brazil, and by nuclear instead of fossil fuel energy use in France to generate thermoelectricity. The absolute values of CO2 emission per inhabitant and per energy consumption, which are given in Table 8, show that Brazil presents the lowest figures in both coefficients. The first is an indicator of poverty, because it is a consequence of low energy use per capita, which is directly related to the low 281
An analytical model to compare energy-efficiency indices and C02 emissions in developed and developing countries Table 7. Time evolution of CO2 emission from the energy system in Brazil and selected OECD countries in 1989 (1970 = 100).
COz emissions Population COffpopulation CO2/energy Energy/GNP GNP/population
Brazil 195 159 122 75 95 174
Germany 94 101 93 82 74 154
France 93 111 84 64 84 157
Italy 135 107 126 103 74 165
UK 86 103 84 87 61 157
Japan 131 118 111 92 63 193
USA 125 122 103 101 72 141
Source: Calculated with Equation (21) and M. Tolmasquim, La Strat~gie Brdsilienne d'Adaptaion aux Chocs P(troliers, PhD thesis, t~coles des Hautes t~tudes, Paris, 1990.
income (GNP) per capita. This index reaches values about 10 times higher than those of Brazil, in the USA, Japan and Germany. If we compare the higher energy intensity of the Brazilian economy with the DC economies, we can see that the country undoubtedly needs to improve its energy efficiency. 15 But we should not forget either that: The great difference between the Brazilian and the DC energy/GNP coefficient is also the result of a conventional electric energy equivalent (see Table 6). • The high energy intensity indicator of the Brazilian industry reflects, in part, the decrease in the mean value of its products (see Tables 3, 4, 5). • One of the characteristics of the international division of labour is that the DCs produce high value products, while the LDCs produce energy intensive products and export them to the DCs (see Table 2); the main result of this is an increase in the energy intensity of the LDC economies. •
On the other hand, in Brazil, the lowest emission per unit energy use is a proof of efficiency and equilibrium in the use of endogenous renewable sources. This equilibrium, however, is being endangered by the changes in energy policy being forced upon Brazil by trends in the world economy.
Final comments: possible consequences of deregulation on CO2 emissions Energy policy in Brazil is changing to satisfy the present orientation of multilateral and international organizations, with the goal of reducing the state's role in the economy. The outcome is proposals for deregulating the electric energy generation and fuel supply. 16 A recent World Bank Report has recommended that Brazil must change from hydro to thermoelectric energy, using coal, oil products and natural gas in the new plants. 17 There are two different reasons for this recommendation. Hydro power has the inconvenience of causing environmental impacts when large dams are constructed in the Amazon, 18 where the major part of the still unused Brazilian hydro potential is concentrated. Brazil presently uses only about 20% of this hydro potential, which amounts to 213 GW. ~9 On the other hand thermoelectricity is much more attractive to private investment in electricity generation. Although the investment cost is low, the energy price is high, depending on the cost of the fuel. It depends on the international oil price, which also exhibits strong uncertainty. A recent revision of the Brazilian electric energy plan, brought about by the economic and political crisis of the Brazilian state electricity companies, has decided to delay the construction of 49 hydroelectric
Table 8. Absolute values of CO2 emission factors in Brazil and selected OECD countries in 1989.
CO2/population t C/103 per person CO2 energy (t C/toe) (Energy/GNP GNP/population (103 US$ per person
Brazil 530
Germany 3288
France 2043
Italy 2056
UK 2904
Japan 2400
USA 6369
399
746
523
770
808
730
819
0.641
0.204
0.207
0.164
0.259
0.149
0.374
2.068
21.599
18.781
16.256
14.214
22.135
20.801
Source: J. Leggett, Global Warming, The Greenpeacc Report, Oxford University Press, 1990 and own elaborations.
282
ENERGY POLICY March 1993
An analytical model to compare energy-efficiency indices and
projects for a long time span. Meanwhile, three thermoelectric plants using oil have been substituted, and four coal plants were retained in the revision .2o In the same way, the use of alcohol in transport is also endangered, because it costs more than gasoline. With no government protection, the free market must induce a progressive elimination of alcohol, substituting it with gasoline. As a concrete result of the policy of weak state intervention in the fuel market, the participation of alcohol fuelled vehicles in total car sales has been decreasing. It was 96% in 1985, 88% in 1988, 55% in 1989 and about 20% in 1990. 21 In 1989-90, there was a shortage in alcohol supply, due to the government no long stimulating sugar-cane production. 22 So deregulation and privatization of energy in LDCs could have a negative consequence for global warming since pure market forces will push out biomass and hydro. There will therefore be an increase of CO2 emission per unit of energy used if the present tendency continues. Finally, current proposals for sharing responsibility for the cutbacks of CO2 emissions among DCs and LDCs must take into consideration the differences between these countries. 23 The conventional efficiency indices for energy diagnosis hide important specific features of LDCs' energy systems, such as the advantages of using endogenous renewable energy.
The authors are grateful for the contributions of Luis Fernando Legey, Mauricio Arouca and Emilio de la Rovere and other colleagues from COPPE/UFRJ, through seminars to discuss specific points of the present work. They also acknowledge the cooperation of CIRED (Centre International de Recherche sur l'Environnement et le D6veloppement) in Paris, in particular Jean Charles Hourcade. The authors have received support from the IBAMA (Brazilian Institute for the Environment) and the Secretary for Science and Technology. The opinions expressed in this paper are those of the authors and do not necessarily represent the view of any institution or government.
ENERGY POLICY March 1993
CO 2
emissions in developed and developing countries
IIPCC, lntergovernmental Panel on Climate Change Report, Working Group 1, 1990. 2j. Leggett, Global Warming, The Greenpeace Report, Oxford University Press, 1990. 3p. Criqui, Le role des importations d'dnergie dans le jeu des eonstraintes internationales, ModOle Internationales, Modele Sibilin, IEJE, Grenoble, 1985; M. Arouca, The Utilization of Energy Intensity, COPPE/UFRJ, 1986; H. Geller and D. Zylbersztajn, 'Energy intensity trends in Brazil', Annual Review of Energy Environment, Vol 16, 1991, p 179. 4K. Matsui, 'Energy in Japan', International Conference on Energy Consumption, Friedrich Ebert Foundation, New Delhi, 1989. •Ibid. 6U. Hansen, 'Decoupling of energy consumption and economic growth: the German experience', International Conference on Energy Consumption, Friedrich Ebert Foundation, New Delhi, 1989. 7M.T. Tolmasquim, La Strat~gie Br(silienne d'Adaptaion aux Chocs P(troliers, PhD thesis, l~coles de Hautes l~tudes, Paris, 1990. 8There is little difference between the total energy of Tables 3 and 4, because in the latter the item cement appears, while in the former the corresponding item comprises cement and ceramics. 9R. Dornbush and S. Fischer, Macroeconomics, McGraw Hill, New York, 1987. I°IEA, International Energy Agency, Energy Balances of OECD Countries, 1984. lllbid. ~2Brazilian Government BEN, Balanqo Energ~tico Nacional, Brasilia, 1990. 131bid. 141bid. 15M.T. Tolmasquim, 'Energy demand adaptation to the oil shocks: Brazil 1973-1985', in Annals of lOth International IAEE Conference, Luxemburg, 9 July 1988. 16L. Rosa, Contribution to the Search of Equilibrium between the State and Private Participation on Electric Energy, COPPE/UFRJ, 1992. 17World Bank, Brazil Energy Strategy and Issues Study, Report 8502 BR, 1990. 18L. Rosa, O. Mielnik and L. Sigaud, Impacts of Hydroelectric and Nuclear Plants in Brazil, International Development Research Centre, Report 196, 1988. 190p cit, Ref 12. 2°ELETROBRAS, Piano Decenal, Revis/Eo do Plano 2010, 1990; L. Rosa, M.A. Santos and S. Ribeiro, Carbon Dioxide Emission by the Energy System in Brazil, COPPE/URFJ, 1992 (to be plublished). L. Rosa and Suzana Ribeiro, 'Implication of the greenhouse effect on energy planning: environmentally sound energy technologies', International Conference, ENI and ENEL, Milan, 1991. 221bid. 23j.C. Hourcade, 'CO2 emission control', RIO CIt~NCIA-92: Forum de Ci~ncia e Cultura/UFRJ, 1992.
283
2
Luiz Pinguelli Rosa and Mauricio Tiomno Tolmasquim
This paper shows how conventional definitions of efficiency and energy intensity, based on the technological and economic framework of developed countries, can mask the real situation in developing countries. New definitions are proposed, such as a generalization of Laspeyre's index. A broad comparison is presented of COe emissions from the energy system of Brazil with those of USA and other OECD countries using a simple factorization model. The final comments point out the disturbing consequence of deregulation and free market international forces, which are pushing Brazil towards an increasing use of fossil fuels, which are COe emitters, in place of endogenous renewable energy, such as hydro and biomass, which are not. Keywords: CO2 emissions; Model; Developing countries
The use of fossil fuels and the burning of wood and subsequent deforestation are presently considered to be the major anthropogenic sources of greenhouse gas emissions into the atmosphere. The developed countries (DCs) consume most fossil fuel energy, while forest destruction occurs mostly in less developed countries (LDCs). Among other anthropogenic global warming gases (GWGs), COe is the most relevant for climate change. 1 There are still uncertainties about the degree of these changes but, in principle, they could cause severe damage to the environment and to human life. The risk of environmental catastrophe is Luiz Pinguelli Rosa is with COPPE/Universidade Federal do Rio de Janeiro, Centro de Tecnologia - Bloco C, 21949-900 - Rio de Janeiro, Brazil; Mauricio Tiomno Tolmasquim is with FINEP and Universidade Federal Fluminense, Praia do Flamengo, 200, 22210-030 - Rio de Janeiro, Brazil.
276
therefore considered great enough to justify political decisions to limit GWG emissions, in particular that of CO2. The canonical solutions that have been proposed are: • to control CO2 emission through either energyefficiency improvement or fossil fuel substitution; • and to avoid deforestation or to create CO2 sinks through reforestation. 2 But these solutions can themselves generate problems such as the need for large investment and a possible reduction in economic growth. The situation is worse in LDCs than in DCs, because they do not have the capital for the necessary investment. External debt makes the economic situation of LDCs even more grave. Furthermore, the LDCs have low per capita energy consumption compared with DCs. There are also other differences: DCs have a better quality of life and higher levels of education and of scientific knowledge, as well as stronger technological capabilities. If ethical as well as economic considerations are taken into account it is apparent that responsibility for controlling CO2 emissions should not be shared equally between the international community. However, some proposals must consider the maintenance of LDC living standards, since the population growth is controlled, while DCs could improve their patterns of consumption and reduce energy intensity. In the next section, this point will be discussed in detail to show how conventional definitions, based on DCs' technological and economic framework, can mask the real situation in LDCs. Other authors have studied trends in energy indices) Here, they are analysed to correct old definitions and to propose new ones, such as a generalization of Laspeyre's index, for CO2 emissions. The third section consists of a broad comparison of COz emissions 0301-4215/93/030276-08 © 1993 Butterworth-Heinemann Ltd
An analytical model to compare energy-efficiency indices and
CO 2
emissions in developed and developing countries
14
!
12
10
l
I
I
I
i
i
--ql II
-
i i
E
i
I
...J
-
!
-
I
I I
I
!
I
Ii,! --
l
i
I
I
0
1973
I
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
Figure 1. Average fuel consumption of cars in Japan (l/kin) Source: K. Matsui, 'Energy in Japan', International Conference on Energy Consumption, Friedrich Ebert Foundation, New Delhi, 1989.
from the energy system of Brazil with those of USA and other OECD countries. A simple factorization model is presented and applied, showing that endogenous renewable energy uses can make LDCs more efficient than DCs in CO2 emission per unit of energy. The final comments in the last section point out the contradictory tendency of deregulation and free market international forces, which push LDCs such as Brazil towards replacing indigenous renewable energy, such as hydro and biomass, with increased fossil fuel consumption and consequent higher CO2 emissions.
L i m i t s o f e n e r g y intensity a n d efficiency indices
Analysis of energy-efficiency increase in DCs Recent data indicate a significant improvement in energy efficiency in DCs. The same is not true in LDCs. However, the improved efficiency of cars and household appliances in DCs has gone hand in hand with higher living standards and increased consumption. Car engines, for instance, are more efficient; but average car size is larger, cars are used more often and they are driven faster, This is particularly true in Western Europe and Japan. 4 The following arithmetic formulae make the point. E N E R G Y POLICY March 1993
Energy efficiency, f, can be defined as the relation between useful energy consumption, U, and final energy consumption, E, in such a way that E-
U f
(1)
It is true that f is growing in DCs; but if U also increases, the net result can be the increase of E for some types of equipment, according to Equation (1). For instance, Figure 1 shows that car fuel consumption per kilometre has increased in Japan in each year from 1982 to 1987.5 In West Germany, the same has occurred with electric energy in households, as shown in Table 1.6
Analysis of energy intensity increase in Brazil As far as productive activities are concerned, there Table 1. Electric energy consumption per capita in private households in West Germany (TWh/household/year). Appliance Lighting, TVs, small appliances Refrigerators, freezers Private household total
1970 9.0 7.(1 43.0
1983 13.8 15.2 90.0
1983/1970 53% 117% 109%
Source: U. Hansen, 'Decoupling of energy consumption and economic growth: the German experience', International Conference on Energy Consumption, Friedrich Ebert Foundation, New Delhi, 1989.
277
An analytical model to compare energy-efficiency indices and C02 emissions in developed and developing countries Table 2. Electric energy content of some Brazilian export products.
Products Aluminium Production (103 t)
Export (103 t) Exported electric energy (GWh) Iron alloy Production (103 t) Export (103 t) Exported electric energy (GWh)
1975
1980
1985
1987
1987/1975
121.3 1.8 30.4
200.6 11.5 198.9
549.4 215.4 3463.1
843.5 456.9 7219.0
695% 25 383% 23 746%
255.8 58.6 304.7
548.1 175.6 930.7
757.3 348.4 2055.6
823.8 387.2 2400.6
322% 660% 788%
Source: M. Tolmasquim, La Strat~gie Br&ilienne d'Adaptation aux Chocs P~troliers, PhD thesis, l~coles des Hautes l~tudes, Paris, 1990.
has recently been a clear reduction of energy intensity in DCs. Energy intensity is defined as the relation, e, between final energy consumption, E, and the gross national product (GNP), R: e -
E R
g -
v
where V--
(3)
which is expressed in tonnes of oil equivalent per tonne of product (toe/t). It is related to the previous 278
(4)
e--
(2)
The index e is expressed in toe (tonnes of oil equivalent) per US dollar. It can also be applied to each particular sector, i, of the economy. However, a hypothesis to be checked is that part of the reduction of Equation (2) in DCs could be due to the transference of energy intensive industries from DCs to LDCs. Statistics show that there is a tendency for DCs to concentrate their economic development in technology services, high technology industries, computer systems and software, while they import steel, aluminium and other intensive energy materials. This tendency could mean that DCs' indirect energy consumption is hidden by the importing of these products. Table 2 shows the increase of electric energy content of some Brazilian export products. 7 On the other hand, energy intensity in LDCs has grown in several specific cases and has slowly decreased in others. However, this handicap seems to be worse than it really is, because the definition in Equation (2) is based on added value R instead of on physical quantity. That is the simplest operational way to define a global energy index for the economy, because it is always possible to sum monetary values in the denominator of the index. This is not valid for physical values expressed in units of mass, M, of different products. But, for a particular sector of industry, or of agriculture, it is useful to define an energy physical intensity: E M
measure of intensity by: g
R
(5)
M is the mean value of the product in US$/t. All these variables can be used for particular sectors. Hence, the increase in e (the energy intensity) could be partially due to the decrease in v (the mean value of the product) in such a way that energy physical intensity g could decrease while e increased. Table 3 shows the energy consumption (Ei) and the added values (Ri) in GNP for a selected set of industrial products in Brazil, with their respective energy intensities (ei). The physical quantities (M/) of the products corresponding to Table 3 are shown in Table 4, with the energy physical intensities (gi). It can be seen that in Brazil from 1974-88, for cement, iron and steel, other metals and paper, gi (energy physical intensities) declined, while ei (energy intensity) increased with the exception of cement for which, even so, the decrease in ei is smaller than that of gi. 8
Global intensity indices and generalization of Laspeyre's index for energy The above set of products accounted for 67% of Brazil's industry energy consumption in 1988. Overall, the total energy intensity index is ~,iEi
ET
Yigi
RT
er = - -
(6)
The same method is not applied to total energy physical intensity because the sum of masses of different goods is not a useful quantity; but it is meaningful to add the indices gi, ie the total energy needed to produce 1 unit of mass of each product i belonging to the set. Tables 3 and 4 give the indices ENERGY POLICY March 1993
An analytical model to compare energy-efficiency indices and C02 emissions in developed and developing countries Table 3. Energy intensity for a set of Brazilian products, a 1974
Cement-ceramics Metallurgy Chemicals Textiles Paper Total
1988
Added value R, (106 US$)
Energy consumption E, (103 toe)
Energy intensity e, (toe/lO 3 US$)
Added value R; (106 US$)
Energy consumption E, (103 toe)
Energy intensity c, (toe/lO 3 US$)
1988 Energy intensity variations e, (1974 = 100)
2799 5486 5391 6516 1598 21790
4884 8359 2717 1533 1930 18923
1.566 1.524 0.504 0.235 1.208 0.868
4122 9090 9297 8101 3009 33619
5887 26965 6877 2398 4947 47101
1.428 2.966 0.740 0.296 1.653 1.401
91 194 147 126 137 161
Source: Brazilian G o v e r n m e n t BEN, Balanfo EnergOtico Nacional, Brasilia, 1990. Note: aConstant 1980 dollars.
er and gr. From 1974 to 1988, the former (energy intensity) has increased 61%, while the latter (energy physical intensity) has decreased 7%:
gT =
Z" Ei = Zig i
(7)
' Mi
h (to,t) -
To improve this new indicator, it is possible to define the weighted index: g T = Zimigi
(8)
where the weights can be either m i --
Ei
(9)
Er
or
mi =
Alternatively, the so called Laspeyre's or base weighted price index of economic theory can be generalized for energy physical intensity through the formula: 9
R,
(10)
RT
It seems to be more realistic to use Equation (9) for a physical index definition, avoiding the effects of monetary varations in (10).
Zi Mi(to) gi(t)
(11)
Y~i Mi(to) gi(to)
The denominator is the energy needed for a basket of products defined by the physical set {Mi(to)} which means the quantities Ml(to) of product 1, M2(to) of 2 and so on, in the reference year t0. If the fixed basket is assumed as the real quantities produced in the year to, the denominator is total energy Ev(to). The numerator always gives the energy requirement for the fixed basket but with the energy physical intensities of the considered year t, gi(t). So Equation (11) is the ratio between energy consumption in the year t and the energy consumption in the year to for the assumed basket. In the case of choosing this basket as the unit set {Mi(to) } = {1,1 . . . 1 } , the generalized Laspeyre's index (11) is reduced to the relation:
Table 4. Energy physical intensity for a set of Brazilian products. 1974 Mass added value
Energy physical intensity gl (toe/t)
Mass added value
(103 t)
Energy consumption Ei (103 toe)
14920 7507 288 218 9036 1590 2984 ND
2271 5985 1964 410 2717 1533 1930 16810
0.152 0.797 6.819 1.881 0.3t) 1 0.964 0.647 11.561
Mi b
Cement Iron and s t e e p O t h e r metals ~ Iron alloys a Chemicals Textiles Paper Total
1988
(103 t)
Energy consumption Ei (103 toe)
Energy physical intensity gl (toe/t)
24819 24657 1509 894 16278 1948 8370 ND
2846 16796 7879 2302 7002 2384 4994 44203
0.115 0.681 5.221 2.575 0.430 1.224 0.597 10.843
Mi b
1988 Energy physical intensity variations gt
(1974 = 100) 75 85 76 137 143 127 92 93
Notes: aSum of iron and steel, other metals and iron alloys = metallurgy in Table 3. bMi = not defined (ND). Source: Calculated with E q u a t i o n (3) and Brazilian G o v e r n m e n t B E N , Balanqo Energ~tico Nacional, Brasflia, 1990.
ENERGY POLICY March 1993
279
An analytical model to compare energy-efficiency indices and C02 emissions in developed and developing countries Table 5. Weighted energy physical intensity and generalized Laspeyre's index for the products set of Table 4. Index
Weighted: gt h
1974 (toe/t)
1988 (toe/t)
1988 (1974= 100)
1.357 -
1.532 -
113 98
Source: Calculated with Equations (8), (9) and (11).
certainly the case for Brazil, which assumes a conventional thermal efficiency of 27% for overall electric energy generation in the country. But almost 90% of the electricity generation in Brazil is yielded by hydro, with an efficiency higher than 90% in energy conversion. The correction factor for energy E, which is registered in statistical data, 12 is easily obtained by: - 1 -aH
h(to,t)- gr(t)
gr(t0)
(12)
with gr given by the formula (7). The value of (12) can be seen in the last row and last column intersection in Table 4. Table 5 shows the values of h and gr for the same set of products considered in Table 4. The value of gT- in 1988 was higher than that in 1974, due to the increasing participation of energy intensive products in the Brazilian industry, especially in exports, as has been shown in Table 2. On the other side, the Laspeyre's index h shows that the energy consumption for the fixed basket of products, in 1988, was lower than in 1974, according to the last row of Table 4. This indicates an efficiency improvement. The comparison between Tables 3 and 5 shows that, while the energy intensity of a representative set of products of the Brazilian industry increased 61% between 1974 and 1988, the generalized Laspeyre's index decreased 2%. This means that there was an important decrease of the mean added value of the set of products analysed.
The convention for the energy equivalent of hydroelectricity Last, but not the least, regarding energy index trends, there is the effect of conversion factor conventions which are adopted in the basic energy statistics of each country. For instance, the methodology of the International Energy Agency for OECD countries states that the primary energy equivalent of nuclear and hydro energies to electricity generation is calculated with a conventional efficiency of 38.5.1° In fact this does not mean technical efficiency, but represents the equivalent amount of thermal fuel which would be required to produce the same electric energy. Other countries assume different efficiencies, such as 57.3% in Norway and 35.1% in Japan. 11 In countries with large thermo electricity participation, as in most DCs, this kind of convention is not so far from reality. But, when hydroelectricity is dominant, this convention substantially magnifies real energy inputs. That is 280
(IT t 1 -~
(13)
where E' = corrected value corresponding to the registered energy E a H = participation of hydroelectricity fT = conventional thermal efficiency FH = actual hydro efficiency Formula (13) makes clear that when aH (the participation of electricity) increases the corrected value E' decreases; in other words, the energy intensity of the economy decreases. For the present calculation fT/fH = 0.3, a H = 14.4% in 1970, and a H = 33.1% in 1989.13 If the Brazilian energy balance is corrected by actual hydroelectricity efficiency, instead of the conventional measure, energy intensity decreases, as is shown in Table 6. The results of this section must not be considered as evidence that energy efficiency in LDCs, such as Brazil, is quite good. But these results point out that there are peculiarities that could be neglected by the usual indices for energy diagnosis, which should be constructed more carefully to take account of the specific situation of each country. Obviously, the Brazilian results cannot be applied to all LDCs. However, some features could also be present in other countries, such as the fall in monetary value of energy intensive goods. A hypothesis to be checked in future studies is the CO2 emission export from DCs to LDCs, due to the importing of energy intensive products by DCs. LDCs, on the other hand, have some comparative advantages in endogenous renewable energy sources, such as hydro and biomass, which avoid CO2 emissions.
Table 6. Corrected energy intensity due to electric energy equivalent (toe/103 US$).
Conventional Corrected
1970 0.675 0.602
1989 0.641 0.498
1989/1970 95% 83%
ENERGY POLICY March 1993
An analytical model to compare energy-efficiency indices and Comparative and biomass
Y~i Ci Ei
(14)
Ei Ei
where Ei = energy use of the form i (toe) ci = CO2 emission per unit energy used (t C/toe)
The coefficient ci depends on efficiency 1] (toe/t fuel) of energy conversion and on CO2 emission, di (t C/t fuel), of the fuel: Ci-
di
(15)
f, Energy substitution can decrease d~ and efficiency improvement increases f,-, giving a decrease in ci in (14) and (15). Among fossil fuels, coal has the largest d~, while the natural gas has the smallest. Oil has an intermediate position. Combined cycle plants with gas turbines give f/values higher than conventional thermoelectric plants. But hydro and sugarcane products, as well as nuclear energy, have di = O. Assuming an average value, Cx, for the CO2 emission by all energy forms with net CO2 emission, and calling their sum Ex, a rough approximation for (14) is given by: = c,. a~
(16)
where
Er
ax = .... ET
(17)
For electricity generation in Brazil, the following energy sources are used: 14 H N P C B BR M
= = = = = = =
hydro (89.9%) nuclear (4.9%) oil products (2.2%) coal (1.8%) biomass (1.1%) renewable biomass (bagasse) (0.3%) natural gas (0.1%)
Hence: ENERGY POLICY March 1993
emissions in developed and developing countries
ax = C + P + B - BR + M
advantage of LDCs in hydro energy without CO2 emissions
The Brazilian case is interesting for electricity generation and transport, because hydro and sugar-cane alcohol are used. Neither of these energy products contributes to CO2 emissions (or their contribution is so insignificant that it can be neglected for practical purposes). The average emission per energy consumption in a given sector is expressd by c -
CO 2
(18)
The fractions ax (18), in Brazil, corresponds to nearly 5%, while in the USA, it amounts to almost 75%. Using the approximation in Equation (16), Brazil is therefore more efficient than the USA in respect of CO2 emissions per unit of electric energy generated (t C/MWh) by the factor: ~(USA) ~(BR)
0.75
- - -
0.05
- 15
(19)
In car transport, Brazilian fuel consumption is approximately half and half alcohol and gasoline, while in the USA, it is almost 100% gasoline. So the relation between CO2 per gigajoule in the USA and Brazil is: ?(USA) ?(BR)
1.0 - -
0.5
- 2
(20)
The above rough calculations (19) and (20) provide an order of magnitude to estimate how much more efficient Brazil is than the USA in these cases. The time evolution of CO2 emission from an energy system can be analysed by a simple factorization model: CO2 POP
-
CO2 ENERG Y
x
ENERGY GNP
x
GNP P O P U L A TION
(21)
The first factor in Equation (21) can be interpreted as energy substitution, the second as variation of energy intensity, and the last as variation of income per capita. The results from (21) are shown in Table 7 for Brazil and some O E C D countries, in 1989, taking the year 1970 as reference (index = 100). Brazil has the worst position in the increase of CO2 emissions (first row of Table 7). But population has increased more in Brazil than in any of the other countries considered in Table 7. Even so, it continues to have the worst behaviour in the variation of CO2 per inhabitant (apart from Italy) from 1970 to 1989. However, in the coefficient of CO2 per unit of energy consumption (fourth row), Brazil turns out to have the second best position after France. This improvement can be explained by the large use of renewable energy sources such as hydroelectricity and alcohol in Brazil, and by nuclear instead of fossil fuel energy use in France to generate thermoelectricity. The absolute values of CO2 emission per inhabitant and per energy consumption, which are given in Table 8, show that Brazil presents the lowest figures in both coefficients. The first is an indicator of poverty, because it is a consequence of low energy use per capita, which is directly related to the low 281
An analytical model to compare energy-efficiency indices and C02 emissions in developed and developing countries Table 7. Time evolution of CO2 emission from the energy system in Brazil and selected OECD countries in 1989 (1970 = 100).
COz emissions Population COffpopulation CO2/energy Energy/GNP GNP/population
Brazil 195 159 122 75 95 174
Germany 94 101 93 82 74 154
France 93 111 84 64 84 157
Italy 135 107 126 103 74 165
UK 86 103 84 87 61 157
Japan 131 118 111 92 63 193
USA 125 122 103 101 72 141
Source: Calculated with Equation (21) and M. Tolmasquim, La Strat~gie Brdsilienne d'Adaptaion aux Chocs P(troliers, PhD thesis, t~coles des Hautes t~tudes, Paris, 1990.
income (GNP) per capita. This index reaches values about 10 times higher than those of Brazil, in the USA, Japan and Germany. If we compare the higher energy intensity of the Brazilian economy with the DC economies, we can see that the country undoubtedly needs to improve its energy efficiency. 15 But we should not forget either that: The great difference between the Brazilian and the DC energy/GNP coefficient is also the result of a conventional electric energy equivalent (see Table 6). • The high energy intensity indicator of the Brazilian industry reflects, in part, the decrease in the mean value of its products (see Tables 3, 4, 5). • One of the characteristics of the international division of labour is that the DCs produce high value products, while the LDCs produce energy intensive products and export them to the DCs (see Table 2); the main result of this is an increase in the energy intensity of the LDC economies. •
On the other hand, in Brazil, the lowest emission per unit energy use is a proof of efficiency and equilibrium in the use of endogenous renewable sources. This equilibrium, however, is being endangered by the changes in energy policy being forced upon Brazil by trends in the world economy.
Final comments: possible consequences of deregulation on CO2 emissions Energy policy in Brazil is changing to satisfy the present orientation of multilateral and international organizations, with the goal of reducing the state's role in the economy. The outcome is proposals for deregulating the electric energy generation and fuel supply. 16 A recent World Bank Report has recommended that Brazil must change from hydro to thermoelectric energy, using coal, oil products and natural gas in the new plants. 17 There are two different reasons for this recommendation. Hydro power has the inconvenience of causing environmental impacts when large dams are constructed in the Amazon, 18 where the major part of the still unused Brazilian hydro potential is concentrated. Brazil presently uses only about 20% of this hydro potential, which amounts to 213 GW. ~9 On the other hand thermoelectricity is much more attractive to private investment in electricity generation. Although the investment cost is low, the energy price is high, depending on the cost of the fuel. It depends on the international oil price, which also exhibits strong uncertainty. A recent revision of the Brazilian electric energy plan, brought about by the economic and political crisis of the Brazilian state electricity companies, has decided to delay the construction of 49 hydroelectric
Table 8. Absolute values of CO2 emission factors in Brazil and selected OECD countries in 1989.
CO2/population t C/103 per person CO2 energy (t C/toe) (Energy/GNP GNP/population (103 US$ per person
Brazil 530
Germany 3288
France 2043
Italy 2056
UK 2904
Japan 2400
USA 6369
399
746
523
770
808
730
819
0.641
0.204
0.207
0.164
0.259
0.149
0.374
2.068
21.599
18.781
16.256
14.214
22.135
20.801
Source: J. Leggett, Global Warming, The Greenpeacc Report, Oxford University Press, 1990 and own elaborations.
282
ENERGY POLICY March 1993
An analytical model to compare energy-efficiency indices and
projects for a long time span. Meanwhile, three thermoelectric plants using oil have been substituted, and four coal plants were retained in the revision .2o In the same way, the use of alcohol in transport is also endangered, because it costs more than gasoline. With no government protection, the free market must induce a progressive elimination of alcohol, substituting it with gasoline. As a concrete result of the policy of weak state intervention in the fuel market, the participation of alcohol fuelled vehicles in total car sales has been decreasing. It was 96% in 1985, 88% in 1988, 55% in 1989 and about 20% in 1990. 21 In 1989-90, there was a shortage in alcohol supply, due to the government no long stimulating sugar-cane production. 22 So deregulation and privatization of energy in LDCs could have a negative consequence for global warming since pure market forces will push out biomass and hydro. There will therefore be an increase of CO2 emission per unit of energy used if the present tendency continues. Finally, current proposals for sharing responsibility for the cutbacks of CO2 emissions among DCs and LDCs must take into consideration the differences between these countries. 23 The conventional efficiency indices for energy diagnosis hide important specific features of LDCs' energy systems, such as the advantages of using endogenous renewable energy.
The authors are grateful for the contributions of Luis Fernando Legey, Mauricio Arouca and Emilio de la Rovere and other colleagues from COPPE/UFRJ, through seminars to discuss specific points of the present work. They also acknowledge the cooperation of CIRED (Centre International de Recherche sur l'Environnement et le D6veloppement) in Paris, in particular Jean Charles Hourcade. The authors have received support from the IBAMA (Brazilian Institute for the Environment) and the Secretary for Science and Technology. The opinions expressed in this paper are those of the authors and do not necessarily represent the view of any institution or government.
ENERGY POLICY March 1993
CO 2
emissions in developed and developing countries
IIPCC, lntergovernmental Panel on Climate Change Report, Working Group 1, 1990. 2j. Leggett, Global Warming, The Greenpeace Report, Oxford University Press, 1990. 3p. Criqui, Le role des importations d'dnergie dans le jeu des eonstraintes internationales, ModOle Internationales, Modele Sibilin, IEJE, Grenoble, 1985; M. Arouca, The Utilization of Energy Intensity, COPPE/UFRJ, 1986; H. Geller and D. Zylbersztajn, 'Energy intensity trends in Brazil', Annual Review of Energy Environment, Vol 16, 1991, p 179. 4K. Matsui, 'Energy in Japan', International Conference on Energy Consumption, Friedrich Ebert Foundation, New Delhi, 1989. •Ibid. 6U. Hansen, 'Decoupling of energy consumption and economic growth: the German experience', International Conference on Energy Consumption, Friedrich Ebert Foundation, New Delhi, 1989. 7M.T. Tolmasquim, La Strat~gie Br(silienne d'Adaptaion aux Chocs P(troliers, PhD thesis, l~coles de Hautes l~tudes, Paris, 1990. 8There is little difference between the total energy of Tables 3 and 4, because in the latter the item cement appears, while in the former the corresponding item comprises cement and ceramics. 9R. Dornbush and S. Fischer, Macroeconomics, McGraw Hill, New York, 1987. I°IEA, International Energy Agency, Energy Balances of OECD Countries, 1984. lllbid. ~2Brazilian Government BEN, Balanqo Energ~tico Nacional, Brasilia, 1990. 131bid. 141bid. 15M.T. Tolmasquim, 'Energy demand adaptation to the oil shocks: Brazil 1973-1985', in Annals of lOth International IAEE Conference, Luxemburg, 9 July 1988. 16L. Rosa, Contribution to the Search of Equilibrium between the State and Private Participation on Electric Energy, COPPE/UFRJ, 1992. 17World Bank, Brazil Energy Strategy and Issues Study, Report 8502 BR, 1990. 18L. Rosa, O. Mielnik and L. Sigaud, Impacts of Hydroelectric and Nuclear Plants in Brazil, International Development Research Centre, Report 196, 1988. 190p cit, Ref 12. 2°ELETROBRAS, Piano Decenal, Revis/Eo do Plano 2010, 1990; L. Rosa, M.A. Santos and S. Ribeiro, Carbon Dioxide Emission by the Energy System in Brazil, COPPE/URFJ, 1992 (to be plublished). L. Rosa and Suzana Ribeiro, 'Implication of the greenhouse effect on energy planning: environmentally sound energy technologies', International Conference, ENI and ENEL, Milan, 1991. 221bid. 23j.C. Hourcade, 'CO2 emission control', RIO CIt~NCIA-92: Forum de Ci~ncia e Cultura/UFRJ, 1992.
283