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close this bookThe Global Greenhouse Regime. Who Pays? (UNU, 1993, 382 p.)
close this folderPart III National greenhouse gas reduction cost curves
close this folder12 Carbon abatement in Central and Eastern Europe and the Commonwealth of Independent States
View the document(introduction...)
View the documentEnergy-environment nexus
View the documentScenarios for the future
View the documentCountry results
View the documentPolicy implications
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View the documentReferences


energy-environment nexus
scenarios for the future
country results
policy implications

stanislav f kolar

the countries of central and eastern europe consume more than 6 per cent of the world's primary energy and release more than 7 per cent of global carbon dioxide emissions. the republics of the former soviet union (fsu) consume 16 per cent of the world's energy, and release 15 per cent of the carbon. on a per capita basis, their consumption of energy is similar to that of the industrialized economies in western europe. central planners in the former socialist bloc countries often measured success by the amount of energy produced and consumed by their economies. but they did not mention that their rations' per capita income was two to three times lower than in western europe. simple arithmetic indicates that the economies of the former socialist bloc use two to three times as much energy to produce one unit of national income (see figure 12.1).

the asymmetrical economic development in central and eastern europe, initiated in 1928 in the fsu by the first five-year plan and in the late 1940s in central europe and the balkans, is largely responsible for the region's high energy intensity. the economic theories of rapid industrialization that were implemented in these countries considered energy consumption as a means towards achieving strategic goals, such as producing a given amount of steel, cement, chemicals, and other products, many of them requiring vast inputs of energy. fulfilling the production of these products had always been the first priority, and resources were allocated to ensure that such production could take place. to make the production cycle function as smoothly as possible, both energy production and energy prices were heavily subsidized.

Figure 12.1 Carbon and energy intensities compared, 1988 (indexes of carbon and energy/$GDP)

Coupled with the lack of market incentives, this situation created obvious disincentives to use energy rationally.

Energy-environment nexus

The high energy intensity has had direct impact in the region on standards of living and environmental stability. It draws investment into the energy production sector in disproportionate amounts, and retards investments in other economic sectors. Only by increasing the energy efficiency in all activities can the peoples of Central and Eastern Europe hope to achieve living standards comparable to those enjoyed in Western Europe.

The immediate needs of the citizens of these countries, however, may seem to be far removed from global environmental concerns, such as greenhouse gas emissions. While the Western world contemplates setting national goals for the reduction of carbon dioxide emissions, the citizens of Central and Eastern Europe live in some of the most polluted areas of the world. Poland, Czechoslovakia, and Eastern Germany share a region with the highest sulphur dioxide depositions in the world. In the most affected communities in the former Czechoslovakia, bone growth in one-third of the children is retarded by 10 months or more. In Hungary, two-thirds of the drinking water is threatened by environmental hazards, and literally thousands of communities are exposed to unsafe drinking water.

Many of the environmental threats in Eastern Europe are directly related to energy use. It is in Eastern Europe's self-interest to adopt national energy policies that increase efficiency as well as reduce carbon dioxide, the major greenhouse gas produced during the burning of fossil fuels such as coal, oil, and natural gas. Energy efficiency will free capital from energy production and make it available for other productive uses. In Poland, for example, coal production now requires double the annual investment that it did in the early 1970s. Polish energy-related investments consume more than one-third of the total industrial investments. Almost a quarter of all steel produced in Poland is consumed by the energy sector, creating a vicious circle of industrial production for the sake of increased energy supply, which in turn feeds more of the inefficient industrial production that is required by the increased demand for energy.

Energy efficiency offers the single most effective means to reduce carbon dioxide emissions. It is a policy instrument that can achieve the twin goals of economic development and environmental protection. The capital and other resources that these countries invest in energy production could be reduced by substantial amounts if their energy-intensity was reduced to that of the economies of the European Community countries.

Scenarios for the future

Three scenarios were created for future energy supply and demand in Central and Eastern Europe by using the EPA energy end-use model. A base case scenario (BCS) considers the future in the absence of special incentives to save energy, although it incorporates structural changes that may occur (and indeed, are already occurring) in these countries. An energy efficiency scenario (EES) was simulated to show the effects of cost-effective energy efficiency measures on energy supply and demand. And finally, an inter-fuel substitution scenario (IFS) was used to estimate the effects on carbon dioxide emissions of reducing reliance on coal as the predominant fuel, and increasing the use of natural gas and non-fossil energy sources. Data were drawn from a series of detailed energy studies for the FSU and Eastern Europe.


The EPA energy end-use model is a parametric model which estimates future energy demand as a function of economic growth, energy prices, price-, income-, and price cross-elasticities of demand, technical improvements in energy efficiency, and structural change in the economy. The user specifies initial base year demand for oil, natural gas, coal, and electricity for six major industrial categories by two-digit standard industrial classification (SIC) for the residential and commercial sectors, and for transportation. The user also provides initial base year activity levels for each sector. Using these data, the model calculates initial sectoral energy intensity coefficients and carbon dioxide emission levels.

The model projects future energy demand to the year 2030 in five-year increments, giving results for the major fuel types and electricity as well as future aggregate industrial energy intensity. It estimates energy demand on the basis of economic growth, structural change, price response, and technical energy efficiency improvements not attributable to price response. Carbon dioxide emissions are calculated for each sector and for each of the six industrial subsectors according to carbon coefficients for each fuel and the composite coefficient for electricity.

Structural change is characterized as the ratio of the growth of the five industrial (two-digit SIC) sectors to growth in overall GNP, plus an additional sector for general manufacturing. Structural change assumptions affect the energy intensity of the overall economy because shifting levels of energyintensive activities (for example steel output as a share of GNP) change the energy required per unit of economic output. This rate should not be confused with energy-efficiency changes. Both GNP growth and sectoral growth rate ratios are exogenous assumption provided by the user.

The model projects future energy demand on the basis of three other important factors. First, it incorporates energy price response, which the user exogenously specifies by selecting rates of price change for oil, natural gas, coal, electricity, and the price elasticities of demand for each consuming sector. Second, the model modifies future energy demand estimates with a socalled technical factor, which is essentially a rate of change in energy intensity per unit of industrial activity - over and above the price response. This factor is justified empirically, and on the basis of case studies and is exogenous. Third, the model permits the user to specify a price cross-elasticity of demand for electricity which determines the rate of change in electricity demand as a function of the difference between fuel price and electricity price changes.

Marginal cost estimates for carbon dioxide emissions reduction were made using a simple spreadsheet model that calculates levelized cost for each category of energy efficiency measures. These selected energy efficiency measures are based on a Czechoslovak report prepared by a government agency in Prague, and applied to other countries of East Central Europe, except to Poland where separate estimates were developed by Polish experts.

Modelling energy demand scenarios

The base case and energy efficiency scenarios were generated with the assumption that these economies will grow at an annual rate of 2.5 per cent. Population growth also varies from country to country, with Hungary having negative population growth and Poland the fastest growing. These inputs were specified for each country, though a common set of basic assumptions was used for selected, less country-specific variables. These include energy prices, and price and income elasticities of demand, as follows:

• Energy prices: real oil and natural gas prices grow by an average 2.5 per cent per year and coal and electricity prices by 1 per cent per year.

• Price elasticities of energy demand: the model uses -0.25 as the basic price elasticity of energy demand in all economic sectors. Most analyses of future global energy demand use price elasticities that range from -0.25 to 0.75. The more conservative estimate was used because the EPA model does not generate cross-elasticities among different energy carriers, except from primary fuels to electricity.

• Income elasticities of demand: most income elasticities of demand are specified exogenously based on case studies developed by country experts. However, income elasticities of demand for transportation reflect the belief that transportation demand is driven by certain common factors. These include:

- truck travel - driven by average elasticities of service sector and heavy industry activities;
- growth in number of heavy trucks - a function of GNP growth and average growth in heavy industry, chemicals production, and service sector activity;
- bus travel - a function of population growth;
- air travel - a function of GNP growth;
- rail passenger travel - a function of population growth;
- rail freight travel - a function of GNP growth.

Country results

I estimated the energy efficiency potential by determining first the cost-effective energy efficiency measures in several selected activities. Nine broad categories were identified where energy efficiency potential and costs were estimated (see Table 12.1). If implemented, these selected energy efficiency measures alone can reduce carbon dioxide emissions in the countries of Central and Eastern Europe by more than 70 million tonnes of carbon from current levels. This amount represents over 20 per cent of current carbon dioxide emissions in the region, and is measured against current economic activity levels.

This estimate of energy efficiency potential in selected industries and the residential and transportation sectors was used in the EPA energy end-use model to determine the emissions levels in Central and Eastern Europe in the year 2025. Allowing for an annual GNP growth rate of 2.5 per cent, and structural changes in these economies, a combined strategy of energy efficiency and decreasing share of fossil fuels in electricity generation can reduce total carbon dioxide emissions in Eastern Europe by 250 million tonnes from the projected level in 2025 (see Table 12.2 and Figure 12.2). An assumption was made that the share of coal in electricity production would decrease from the current 69 per cent to 50 per cent in 2005 and 30 per cent

Table 12.1 Cost of CO2 emission reduction in Eastern Europe, selected energy efficiency measures

  Energy savings potential (PJ) Capital cost ($mill.) Levelized cost ($mill) Cost of conserved energy ($/GJ) Total carbon emissions saved (mill. tons) Cost of carbon emissions saved ($/ton)
Building insulation 850 2,781 305 0.35 18.5 -44.6
Boiler replacement 170 857 92 0.43 3.7 -41.5
Heating improvement 135 685 75 0.56 2.9 -36.1
Cogeneration 150 1,768 151 1.01 2.9 -11.1
Transmission and distribution losses improvements 500 6,071 588 1.15 10.9 -10.9
Existing industrial equipment improvement 700 8,928 980 1.40 13.5 7.7
Ferrous metals 363 5,250 576 1.59 7.0 16.8
New electrical motors in industry 400 11,071 950 2.38 7.7 54.8
Construction industry improvementsa 150 4,286 368 2.45 2.9 58.5

a Mostly cement production
Source Henel, Cabicar, and author.

Table 12.2 Carbon dioxide emissions in Eastern Europe, energy efficiency scenario (MTC)

  Buildings Industry Transport Total
1985 108 210 38 356
2005 120 146 36 301
2025 159 117 47 310

Table 12.3 Energy efficiency scenario for Eastern Europe electricity generation, 1987-2025(%)

  1987 2005 2025
Coal 69 50 31
Natural gas 7 10 20
Oil 2 2 2
Non-fossil 22 38 48

Figure 12.2 Carbon dioxide emissions in Central and Eastern Europe, 1985-2025

Table 12.4 Selected Soviet energy efficiency measures, 7990-2005

  Annual energy savings in 2005 (EJ) Total capital cost 7990-2005 (Bill. R) Levelized cost (rubles) Cost of conserved energy (rubles/GJ) Total carbon emissions saved (mill. tons) Cost of carbon emissions saved ($/ton)
Shifting from harvesters to site threshing 0.3 0.2 0.19/0.22 7.32 5.83 -53.73
Switching small boilers to high-grace fuels 0.4 0.3 0.20/0.23 8.23 7.78 -52.94
Insulation of steam supply network 0.5 0.4 0.24/0.28 8.78 9.72 -52.47
Advanced technologies for industrial heating 0.2 0.2 0.22/0.27 10.98 3.89 -50.59
Insulation of cattle breeding buildings 0.2 0.4 0.42/0.42 21.96 3.89 -41.18
Automation of heating stations 0.2 0.4 0.52/0.59 21.96 3.89 -41.18
Efficient centralized boilers 0.6 1.2 0.47/0.55 21.06 11.67 -41.18
Change inefficient ovens to large boilers 0.3 0.7 0.53/0.54 25.62 5.83 -38.04
Regulated electric drive 1.4 3.7 0.7/10.82 29.02 27.22 -35.13
Control and measurement in energy use 0.5 1.7 1.11/1.41 37.33 9.72 -28.00
Low capacity multifuel boilers 0.7 3.3 1.09/1.27 51.76 13.61 -15.63
Reduction of electric transmission losses 0.2 1.3 1.85/2.29 71.37 3.89 1.17
Replacing wet cement clinker with dry method 0.2 1.4 1.93/1.86 76.86 3.89 5.88
Gas turbine and combined cycle plants 0.7 5.0 1.64/2.18 78.42 13.61 7.22
Efficient lighting 1.1 8.5 2.41/2.99 84.84 21.39 12.72
Improved brick production 0.1 0.9 1.80/1.80 98.82 1.94 24.70
Improved gas compressors in pipelines 0.3 4.7 3.38/3.95 172.01 5.83 87.44

Source Alexei A Makorov and Igor Bashmakov, Carbon Emissions Control Strategies Case Studies in International Cooperation, William U Chandler, Editor, World Wildlife Fund & The Conservation Foundation, Chapter 2 'The Soviet Union' (Washington DC 1990).

Cost estimates for energy efficiency measures through 2005 in the former Soviet Union have been developed by two leading Russian energy analysts, A. Makarov and 1. Bashmakov, (see Table 12.4). Almost 15 exajoules of energy, or approximately 25 per cent of current energy use, can be saved at net savings, that is below the cost of new energy supply. These energy savings translate into a reduction in carbon emissions of 250 million tonnes from current levels, that is 27 per cent of current carbon emissions in the former Soviet Union (see Figure 12.3). These measures span all sectors of economic activity, but, as in Eastern Europe, are concentrated in the industrial sector.

In spite of these reductions, however, the EPA energy end-use model projects that carbon emissions will increase absolutely in the FSU through 2025. Reducing reliance on coal, and increasing the use of natural gas and non-fossil energy sources, however, can further reduce carbon emissions by 400 million tonnes by 2025 (see Figure 12.3). Thus, fuel switching is necessary if the republics of the former Soviet Union are to reduce carbon emissions from current levels in 2025.

Economic restructuring

Economic restructuring is the most important aspect of devising policies for reducing energy use and carbon dioxide emissions in Central and Eastern Europe. The base case for each country assumes major changes in the economies of these countries. This restructuring implies that as income levels approach West European levels, demand for energy amenities also increases to that in Western Europe. Demand growth for energy services, therefore, was modelled in part as a function of income growth. For example, the number of cars per person and living area per capita in the region was assumed to increase approximately to the current West European average when East European per capita income reaches that of Western Europe (see Figures 12.4 and 12.5). The underlying assumption of economic restructuring is therefore the expectation that consumption as a share of gross national product will achieve current Western levels in Eastern Europe by the first quarter of the next century, and that structural change will significantly decrease the share of the industrial sector in total energy demand (see Table 2.5).

Figure 12.3 Carbon emissions in the former Soviet Union, 1990-2030

The East European economies have invested asymmetrically in heavy industry at the expense of services and consumer goods. This imbalance means, for example, that their economies are very steel intensive compared to Western nations. The former Federal Minister of Economy of Czechoslovakia, and now the Czech Republic's Minister of Industry and Trade, recently remarked that every citizen in his country can have a tonne of steel under his/her bed, but they cannot eat it or drive it. Indeed, Czechoslovakia produces one tonne of steel for every inhabitant each year, while the average in the OECD countries is less than half of that, and the European Community, a region with similar resource constraints as Czechoslovakia, produces only 40 per cent of the steel as Czechoslovakia on per capita basis.

Figure 12.4 Automobile ownership, country comparisons, 1985 and 2025

Figure 12.5 Living area per capita in Eastern Europe, 1985 and 2025

This concentration of heavy industry represents a structural imbalance in each of these economies deriving from the nature of central planning.

Just as demand for consumer goods was assumed to increase with growing incomes, demand for basic materials per unit of economic output was assumed to decline toward Western levels. The rates of decline assumed were also based on the expert judgements and recommendation of the case study participants, and vary from country to country. In the model, these changes were implemented through income elasticities of demand for each particular product or industry (see Table 12.6).

The industrial sector

On average, the industrial sector in Eastern Europe uses more than twice the energy to produce one dollar of output than do industries in the United States. Because of the large share of industrial production in the gross national product, high industrial energy intensity is a dominant factor in the overall high energy intensity of those economies.

Table 12.5 Energy demand in Eastern Europe, 1985 and 2025 (exajoules)

  Industry Buildings Transport Total
1985 Demand 10.78 5.20 2.30 18.28
2025 Base case 13.66 12.46 4.99 31.11
2025 Energy efficiency 7.69 7.62 3.43 18.74

Includes Bulgaria, Czechoslovakia, former East Germany, Hungary, Poland, and Romania.

Table 12.6 Structural change in Eastern Europe, 1985 and 2025

  Eastern Europe European Community United States
GNP per capita ($1985)
1985 5,482 10,507 16,494
2025 16,189 - -
Industry share in GNP (%)
1985 39.6 - 26.2
2025 30.0 - -
Steel production (kg/$1000 GNP)
1985 66.0 34 18.6
2025 28.2 - -
Chemicols production (kg/$1000 GNP)
1985 14.5 4.4 3.9
2025 10.8 - -
Living area (sq. metres/cap)
1985 15 38 55
2025 37 - -
Persons per automobile
1985 7.0 2.8 1.7
2025 3.0 - -

a Production of nitrogen- and potassium-based fertilizers only

In the model, base-case industrial energy intensity (energy requirement per dollar of output) declines between 1990 and 2025 by 1 to 1.5 per cent in individual countries. This relatively high energy intensity reduction rate is due primarily to structural changes in each economy, and to a lesser extent to an assumed decrease (0.1 to 0.5 per cent per year) in the technical energy intensity of industrial production caused by capital turnover (see Table 12.7).

Industrial energy efficiency policy is assumed to increase the rate of energy intensity reduction beyond that of our Base Case - that is, beyond structural change - and will average 2.4 per cent per year for Eastern Europe as a whole (see Table 12.8).

The rate of energy intensity reduction will depend on the level of energy intensity in each country and on the relative costs of energy efficiency measures. The estimate is based on cost studies performed in Poland, Czechoslovakia, and Hungary. To provide an approximation for Eastern Europe as a whole, those results were extrapolated to Eastern Germany, Romania, and Bulgaria. Separate analysis was developed for the Common wealth of Independent States (formerly the Soviet Union) by experts in Moscow.

Table 12.7 Energy intensities, base case and efficiency case, 1985-2025 (% average annual change)

  Residential Commercial Steel Chemicals Manufacturing Transport
BCS 0.2 0.2 -0.3 -0.3 -0.5 -0.3
EES -1.2 -1.2 -1.1 -0.5 -3.0 -1.3
BCS 0.0 0.0 0.0 -0.1 -0.5 -0.5
EES -1.0 -1.0 -1.4 -1.9 -1.5 -1.5
BCS 0.6 0.6 0.0 0.0 0.0 0 0
EES -1.5 -1.5 -2.0 -2.5 -2.0 -1.0
BCS 1.0 1.0 -0.1 -0.4 -0.3 0.0
EES 0.0 0.0 -2.6 -3.1 -3.9 -1.3

BCS = base case scenario
EES - energy efficiency scenario

Industrial energy efficiency holds the most promise, simply because industry is the largest energy consuming sector in Eastern Europe. Despite major growth in the residential and commercial sectors - to match current West European energy use patterns - industrial energy use will continue to dominate the energy supply and demand picture in Eastern Europe and the former Soviet Union well into the twenty-first century. Compared to the base case, almost 6 exajoules of primary energy could be saved in the industrial sector in Eastern Europe by 2025 (see Table 12.5).

The reader is once again reminded that this potential is in addition to the energy savings embodied in the base case and therefore does not reflect the impact that economic reform will have on the energy intensity of national income. Economic reform in the region will result primarily in structural changes in each economy. Many experts in Czechoslovakia today, for example, call for reducing the production of steel from 15.5 to 7-8 million tonnes per year. Even more dramatic cuts have been recommended for nonferrous metallurgy and chemicals production. The structural change assumptions, embodied in both the base case and in the energy efficiency case, are based on the case studies completed in Poland, Hungary, and Czechoslovakia, and on consultations with experts in Romania and Bulgaria.

The major effect of structural changes in Eastern Europe will be a reduced role for industry in producing national incomes, and conversely, in the increased role of services. This outcome will have profound consequences on standards of living in Eastern Europe and will best be manifested in the increased living area per capita, currently less than one-half of the West European average (see Figure 12.5).


In the buildings sector, I assumed that as Eastern European incomes grow to match Western levels, so will living area per capita - and with it, energy demand in buildings. On the average, East European living area per capita will grow from 15 square metres today to over 37 square metres by 2025 (see Table 12.6).

Income growth will significantly increase the use of household amenities in Eastern Europe, including air conditioning. In all countries, except Hungary, base case energy intensities in the residential sector rise by between 0.2 per cent in the former Czechoslovakia to 1.0 per cent in Romania (see Table 12.7).

In the energy efficiency scenario, technical energy intensities of the residential sector vary considerably again among countries, from 0 per cent change in Romania to -1.5 per cent per year improvement in Poland. Because of the currently very low energy consumption in Romanian residences, no decline in energy intensity per square foot is expected in Romania, even if substantial energy efficiency measures are implemented. In Poland, coal of inferior quality provides the vast majority of the heat in residential dwellings, and replacing it with better quality coal or natural gas will account for a significant part of the high rate of energy intensity improvement. Carbon dioxide emissions will be reduced by an even greater rate than energy intensity, due to the lower carbon content of natural gas.

Energy consumption in buildings in Eastern Europe, unlike in industry, will increase even in the energy efficiency scenario, and will do so by nearly 50 per cent (see Table 12.5). Compared to the base case, however, energy efficiency measures in the residential and commercial sector can save nearly 5 exajoules of primary energy in 2025. These measures include, roughly in order of importance, building insulation, space heating efficiency improvements, and coal quality improvements.


Energy service demand levels for transportation in Eastern Europe in 2025 are assumed to approach those in Western Europe today. Passenger and freight transport will increasingly employ private cars and large trucks, and on average, the rate of car ownership per capita is expected to more than double (see Figure 12.4). Air travel in Eastern Europe is assumed to increase at a rate ten times the increase in miles travelled by buses, but railroads will remain important for both passenger and freight travel.

Table 12.8 Eastern Europe final energy demand, 1985 and 2025 (exajoules)

    Base case Efficiency case
  1985 2025 2025
Coal 2.03 3.47 2.57
Oil 0.19 0.45 0.29
Gas 0.26 1.23 0.48
Electricity 0.40 1.23 0.65
Coal 0.37 1.00 0.64
Oil 0.10 0.23 0.15
Gas 0.15 0.36 0.22
Electricity 0.14 0.38 0.25
Iron & steel      
Coal 0.90 0.66 0.39
Oil 0.10 0.07 0.04
Gas 0.32 0.20 0.12
Electricity 0.19 0.15 0.10
Non-ferrous metals      
Coal 0.01 0.01 0.01
Oil 0.01 0.01 0.00
Gas 0.05 0.03 0.02
Electricity 0.07 0.06 0.04
Coal 0.19 0.24 0.18
Oil 0.11 0.10 0.05
Gas 0.42 0.44 0.22
Electricity 0.31 0.53 0.29
Coal 0.22 0.30 0.20
Oil 0.07 0.10 0.06
Gas 0.17 0.23 0.12
Electricity 0.06 0.08 0.05
Pulp & paper      
Coal 0.11 0.16 0.10
Oil 0.01 0.01 0.01
Gas 0.01 0.01 0.00
Electricity 0.04 0.05 0.03
Other industry      
Coal 1.79 2.25 1.48
Oil 0.95 1.18 0.71
Gas 1.24 2.01 0.93
Electricity 0.60 1.04 0.50

The base case assumes minimal improvement in automobile fuel economy. However, significant energy savings can be realized through policy measures such as standards for fuel economy. On the average, cars in Eastern Europe consume about 8.7 litres per 100 km. Increasing automobile fuel economy to 5 litres per 100 km - and implementing additional transportation energy savings measures, such as improving truck fuel economy, and converting the gasoline-powered trucks to diesel - can reduce transportation energy demand in 2025 by 1.5 exajoules compared to the base case (see Table 12.5). A net increase of 50 per cent over current levels would still be necessary even in the energy efficiency scenario, unless passenger transportation evolves completely differently to that in Western Europe. Policies to encourage or implement alternative transportation systems, however, have not been included in our energy efficiency scenario, despite the need of these countries to actively seek new transportation development patterns. Rather, I assumed that Central and Eastern Europe will develop a transportation system that is similar to the West European system.

Policy implications

The behavioural changes simulated in the base case scenario were designed assuming that the allocation of investment funds in the countries of Eastern Europe will change from the practices of forty years of central planning. The asymmetrical development of Eastern Europe has severely retarded the region's economic well-being, standards of living, and environmental stability. A direct consequence of the uneven economic infrastructure is high energy demand with a plethora of consequences. It is in the region's own interest to reduce its high energy intensity through a gradual change in investment allocation. This shift will occur naturally if those economies become open and market-oriented. The base case assumes that these economies will become fully integrated into the European market and that external economic developments - and basic dynamics of supply and demand in market economies - will influence how these countries produce their wealth.

Policy mechanisms for energy efficiency have been simulated in two separate ways, and were measured against the projected energy demand and carbon dioxide emission levels in the year 2025, that is against the base case. First, I assumed that investments - particularly in the buildings and transportation sectors - and energy efficiency standards were put in place to reduce the intensity of energy services to levels of efficiency deemed cost-effective. For example, automobile fuel usage should not exceed 5 litres per 100 km. Such analysis can readily be implemented in the EPA model for all economic sectors and subsectors.

Second, I assumed that economic reforms will cause energy prices to escalate from their current subsidized levels to equilibrium levels - that is, to world prices. Electricity and heat prices are still subsidized to most consumers. The EPA model calculates energy demand with an annual increase in real energy prices of between 1.0 and 2.5 per cent for different fuels and electricity. This method assumes that prices matter to enterprises, as well as to residential and commercial building consumers, and that energy users respond to prices as in the West.

In a sensitivity test, energy price elasticities were increased to -0.6. In this case, the necessary price increase required to simulate the entire energy conservation potential for Eastern Europe would have to be only half as steep. Interestingly, the results from the price reform case resembled those from the regulatory case through the next two decades. The price elasticity of demand was assumed to be only -0.3, exceedingly low for long-term elasticities by Western standards. The reader should note here that either the regulatory or the price reform cases may be simulated independently or conditionally in the EPA energy end-use model. Simulating one or the other case, or both, can serve to ascertain the necessary measures needed to achieve a level of energy efficiency in the national economy deemed cost-effective. In the real world, both energy prices and regulatory policies will have to be used as tools for reducing energy intensity.

Considering the results of the model runs for the price reform case and the regulatory case, it appears that the East European countries have a lot of flexibility in using price reform and regulatory policy to achieve their energy efficiency potential. The fact that energy prices in the region will eventually equal world market prices is virtually certain so long as these countries move toward the free market. What is yet to be ascertained is their resolve to make careful use of market regulation to balance their national interests and free market capitalism.


Central and Eastern Europe's self-interest requires that it spends less resources on energy production and consumption, and more on generating marketable products and services - at reduced costs, including reduced energy costs. Results from the case studies prepared by experts from these countries clearly indicate that it is often cheaper to save energy - and improve productivity at the same time - than to produce more energy. Doing so will also reduce the risk of climatic change by reducing the emission of greenhouse gases, particularly carbon dioxide.

The technological and economic changes that will be necessary in Central and Eastern Europe in order to achieve these goals will be enormous. To illustrate, the nation of Germany is subsidizing the region of the former East Germany - a region of only 16 million inhabitants - with about $90 billion per year. Still, many experts believe that it will take one generation before the former communist East Germany is culturally, economically, politically, and morally integrated into Germany as a whole. What resources will be required in the rest of Central and Eastern Europe, if that region wants to become a first class citizen of Europe? Clearly, no foreign government can play the leading role in such an undertaking. These countries must themselves take charge and lead the way. By the same token, Central and Eastern Europe, at once the most polluting and the most polluted part of the world, cannot expect that allowances be made always to accommodate their exceptional difficulties. These nations cannot disregard standards, environmental or otherwise, that are expected of those in Western Europe.

Reducing energy intensity and carbon dioxide emissions will require concerted effort on the part of these nations. They must implement economic and political reforms; assure non-inflationary growth, and create new forms of ownership of private property.

The end of the Cold War certainly presents a unique opportunity for Central and Eastern Europe and for the CIS to learn how best to create conditions for healthy market economies. Such conditions are necessary for their transition to economic and environmental well-being. Western aid agencies such as the European Bank for Reconstruction and Development, the World Bank, the International Monetary Fund, and bilateral aid organizations can only stimulate the process of reconstruction and restructuring. Their efforts, however important, cannot change the ways of a half billion people. Technology and know-how will be transferred in a lasting way only if Western commercial interests are rooted in the economies of these nations.

The effects of reducing energy intensity in the region will have an immediate impact on the macroeconomic level. Production and consumption patterns of goods and services will change dramatically to reflect the prevailing patterns in Western Europe. This shift will be most immediately apparent in Hungary, the former Czechoslovakia, and Poland, countries with energy and resource constraints similar to those of Western Europe. The role of the industrial sector will gradually decrease in the overall GNP balance, which will require large adjustments in the workforce as services become more important than industry.

In Romania, Bulgaria, and the FSU, these changes will most likely take longer than in Central Europe. The lack of market-economy tradition and the slower pace of economic and political reforms have already put these countries behind Hungary, the former Czechoslovakia, and Poland in the race to become fully-fledged partners in the European economic and political union, and thus delay their transformation into modern industrial nations. If any meaningful acceleration of pace is to take place in the economic transformation of these nations, the European Community must extend market access and economic cooperation to these nations. All of these changes are preconditions for an effective energy efficiency strategy that can reduce carbon emissions in these transitional economies.


1 T Fleischer and J Vargha, eds, 'The Most Important Tasks of Environmental Protection in Hungary,' ISTER, East European Environment Research, Budapest, 1989

2 S Sitnicki, et al., Chapter 3: 'Poland,' in Carbon Emissions Control Strategies: Case Studies in International Cooperation, William U Chandler, ed.

3 This model is the 'EPA Energy End-Use Model' developed by Irving Mintzer, Projecting Future Energy Demand in Industrialised Countries: An End-Use Oriented Approach, World Resources Institute, October 1988, and modified by W U Chandler of Battelle, Pacific Northwest Laboratories for the US Environmental Protection Agency with the assistance of Stanislav Kolar, PNL, and the advice of Jean-Charles Hourcade and Richard Baron, CIRED, Paris, France

4 The studies on which this chapter is based are: William U Chandler, Stanislav Kolar, Adrian Gheorghe, and Stanislaw Sitnicki, 'Climate Change and Energy Policy in Eastern Europe: Two Scenarios for the Future,' Energy, Vol. 16, No. 111 12, pp 1423-1435, Pergamon Press, 1991; S Sitnicki, et al., Chapter 3: 'Poland,' in Carbon Emissions Control Strategies: Case Studies in International Cooperation, William U Chandler, ea., World Wildlife Fund and The Conservation Foundation, Washington, DC, 1990; Alexei A Makarov and Igor Bashmakov, Carbon Emissions Control Strategies: Case Studies in International Cooperation, Chapter 2: 'The Soviet Union,' in William U Chandler, ea., World Wildlife Fund and The Conservation Foundation, Washington, DC, 1990; TamJay, Chapter 4: 'Hungary,' in Carbon Emissions Control Strategies: Case Studies in International Cooperation, William U Chandler, ea., World Wildlife Fund and The Conservation Foundation, Washington, DC, 1990; Marie KostvJiri Suk and Stanislav Kolar, Reducing Greenhouse Gas Emissions in Czechoslovakia, Pacific Northwest Laboratory, Richland, Washington, December 1991

5 This model was developed by the author

6 M Henel and B Cabicar, Rentabilita statnich prostredku, vlozenych na podporu vyssiho zhodnocovani paliv a energie narodnim hospodarstvi - ekonomicke zduvodneni a oblasti pusobnosti, VUPEK (Research Institute of the Fuels and Energy Complex), Prague, September 1991

7 S Sitnicki, et al., Carbon Emissions, op. cit. (endnote 4)

8 For data, see, variously, Economic Commission on Europe, An Energy Efficient Future, New York: United Nations Economic Commission on Europe, 1983; D Shonak, et al., Transportation Energy Data Book, Oak Ridge: Oak Ridge National Laboratory, 1989

9 Opening remarks, US Electric Power Technologies Conference, Prague, Czechoslovakia, July 7, 1992

10 For data see, Central Intelligence Agency, Handbook of Economic Statistics, 1989, Directorate of Intelligence, Washington, DC, September 1989

11 See references in note 4 above

12 Communications with Jiri Suk, Forecasting Institute, Czechoslovak Academy of Sciences, Prague, Czechoslovakia, April 1990 13 See references in note 4 above