EE9800001

INIS-EE--001

OKOLOOGIA INSTITUUT ISTITUTE OF ECOLOGY

Jaan-Mati Punning (editor)

ESTONIA IN THE SYSTEM OF GLOBAL CLIMATE CHANGE

Publication 4/1996 Tallinn EE9800002

10 2. GREENHOUSE GASES AND THEIR IMPACT ON THE RADIATION BALANCE 2. GREENHOUSE GASES AND THEIR IMPACT ON THE RADIATION BALANCE

Kalju Eerme Tartu Observatory, Toomemdgi, EE2400 Tartu

Introduction For natural reasons, the global climate changes continually in different time scales as related to the processes dominant. The slowest changes, in millions and tens of millions of years, are caused by continental drift and global tectonics. The processes initiated by periodic changes in the Earth's orbital parameters occur in the time scale of tens and hundreds of thousands of years. The fastest changes are related to the changes in atmospheric composition as well as in atmospheric circulation and oceanic currents. A specific feature of present-day changes is a significant anthropogenic impact on atmospheric trace gases. Such an impact can be regarded as a test on natural climate feedbacks. It is believed that never before has the composition of the atmospheric trace gases changed so rapidly as at present.

Basically, global climate is determined by the global energy budget and redistribution of accumulated energy. This redistribution is realized by oceanic currents and atmospheric winds. Both energy supply and redistribution efficiency depend on the wide variety of processes taking place in the atmosphere, hydrosphere, biosphere, cryosphere, and soils. In short time scales, in tens of years, the changes in the atmospheric concentration of certain trace gases lead to the most significant climate forcing. The dynamic processes in the atmosphere and in the ocean are sensitive to small temperature deviations. Systematic increases or decreases in temperature are always accompanied by shifts in weather patterns and currents. As greenhouse gases (GHG) have controlled the climates in the past, so they are controlling the present climate. In a more detailed analysis, the GHG can be divided into radiatively active and chemically active gases. Some of them, for example, ozone are simultaneously both radiatively and chemically active. Radiatively active gases are immediatly interactive with the radiation penetrating the atmosphere, while chemically active gases control the atmospheric content of radiatively active gases. Typically, the atmospheric GHG have sources and sinks outside the atmosphere. If the corresponding fluxes are imbalanced for some reason, then the atmospheric pool can increase or decrease. At present, the atmospheric pools of several major GHG are increasing. This increase contains significant irregularities, which are still poorly understood (Khalil & Rasmussen, 1994; Siegenthaler & Sarmiento, 1993; IPCC, 1994).

The problem of GHG and climate change is closely linked to the problem of atmospheric ozone. A certain part of GHG acts in the chemistry of the ground level ozone and in the stratospheric ozone depletion. A troubling feature is that part of the gases causing the global climate change and stratospheric ozone depletion are man-made. For this reason, the current atmospheric chlorine and bromine burden is much higher than it could ever be in natural conditions.In the case of such perturbed chemical composition, the atmospheric cleansing processes are inhibited. Obviously, it 2. GREENHOUSE GASES AND THEIR IMPACT ON THE RADIATION BALANCE 11 restricts the application of the past climate analogy for estimating the present-day and future climate changes.

The GHG budgets For modeling present and future climate changes, complete data about the GHG is crucial. It must contain the intensities of sources and sinks, the rates of atmospheric increase, the participation in chemical reactions and the transport tracks inside the atmosphere.

The key species among the approximately 40 different GHG are CO2, CH4, NO2 and the tropospheric O3. On a global scale, water vapor is responsible for about 70% of the total greenhouse warming (IPCC, 1990). Usually, water vapor is not included in the listing of GHG gases. It is believed not to have global anthropogenic impact as a short-lived gas in the troposphere. Its mean tropospheric lifetime is about 10 days, similar to the mean lifetime of atmospheric boundary layer aerosol. Both tropospheric water and aerosol are removed by precipitation. In this case, being globally integrated, atmospheric water vapor does not cause any increase of global warming at present, but its local effects can be remarkable. The atmospheric distribution of water vapor is essentially nonuniform. There are certain preferable pathways of water vapor movement sometimes called the "tropospheric rivers" (Newell et al., 1992). Climate change certainly changes the "river beds" and can amplify the regional greenhouse warming. There are significant diurnal and seasonal fluctuations in the total column water vapour content. At least over the continental Eurasian area, a linear trend of increase in the column water vapor content has been observed during the last decade (Arefev et al., 1995). Obviously, there is a necessity for more detailed studies of the column water vapor content in different geographical regions. If such an increase is common, then additional warming due to water vapor cannot be neglected. At the present time, it is possible to use the Global Positional System for the column water vapor content observations. A detailed treatment of water vapor content change is essential in the regions of changing air mass movement.

The problem of how to calculate the global budgets of major GHG has been discussed from different viewpoints. The most logical way seems to be calculating the budgets separately for each country, as proposed for the Country Study Program. If local budgets are calculated with a sufficiently high accuracy, then the global budgets will undoubtedly be better specified. On the other hand, these more exact local balances have no significant benefit for the prediction of local climate.

GHG, with the exception of water vapor and quickly oxidizing species, such as CO and some hydrocarbons, have long atmospheric lifetimes. For this reason, they will be well mixed in the atmosphere, and the global pattern of their sources and sinks is of less importance than the total intensities. Among the sources, the best known are industrial emissions, which are estimated with an

accuracy of about ± 10% (King et al., 1995; Marland et al.,1989) for the carbon-containing CO2 and CH4 gases. The estimates of natural emissions and consumptions have a much lower accuracy. On a global scale, both the land use changes and gas exchange rates still have significant uncertainty. For these reasons, the global net exchange rates have an uncertainty of the order ± 60% (IPCC, 1992). It is noteworthy that the elemental constituents of GHG are mostly the macroelements of biological tissues. The natural exchange between biosphere and atmosphere is thus regulated by the intensity of biological processes. There is an urgent need to understand better the extent of coupling between the plant growth, global temperature and enhanced GHG concentration. The gas exchange, in particular, is realized by the microbial decay processes which are regulated by similar feedbacks. In the case of sulphur-containing gases, the climatic feedback is realized by the aerosol production in the 12 2. GREENHOUSE GASES AND THEIR IMPACT ON THE RADIATION BALANCE atmosphere. It is believed that the main climate feedback of marine algae is realized by their emission of dimetyl sulphide after transformation into the sulphate aerosol. The problem of dimetylsulphide emissions is quite complicated. A good survey can be found in Lawrence (1993). The release of dimetylsulphide into the surrounding water occurs only in the case of certain species of marine phytoplankton. The release depends not as much on the phytoplankton concentration as on the zooplankton grazing. In regions where the zooplankton population is high relative to the phytoplankton population, the highest dimetylsulphide releases can occur. The dimetylsulphide is released into the water primarily via lysis of phytoplankton cell walls. Thus, the production rates depend on the death rates of phytoplankton of the certain dimetylsulphide producing classes. The next steps leading from the dissolved dimetylsulphide in the water to the particular sulphate in the air are dependent on the gas exchange between the water and the air, and on the oxidation and particle formation rates. The main climatic influence of land plants is realized by the fixation of atmospheric carbon dioxide (Lovelock & Kump, 1994). For example, the carbon dioxide uptake is regulated by the El Nino Southern Oscillation. During the El Nino Warming events, the uptake by the terrestrial vegetation is reduced, resulting from the collapse of the Southeast Asian monsoon (Sarmiento, 1993). The long-lived GHG can be well mixed in the atmosphere, and their forcing is only latitude dependent due to different illumination conditions. The climate forcing of aerosols has a strong regional character. The anthropogenic emissions of sulphur dioxide from industry and power plants produce a local increase in sulphate aerosol abundances. The direct effect of local aerosol negative forcing is accompanied by the production of cloud condensation nuclei, supplementing the indirect forcing caused by the higher reflectance of clouds (Taylor & Penner, 1994). In some cases, specialized studies of the regional climate forcing by the increased aerosol production may be necessary. Most of Europe belongs to the region of high aerosol production.

In developed countries, the estimations of GHG budgets are supported by studies on the net flux measurements and the absorption-emission process levels. The process intensities and correspondingly, the net fluxes are sensitive to the background environmental changes, which are not strongly predictable. It is a key question how living organisms participate in climate regulation and how a coupled system including the biota, the atmosphere, the ocean, and the rocks operates. What effects do the organisms have on the environmental conditions and what effects do changed environmental conditions have on the organisms' growth and response? Currently, the flux measurements are made by the closed chamber or the enclosure method, and the eddy correlation method. The chamber method is significantly simpler and cheaper. Chambers of different complexity of construction and of different cost are in use (Roulet et al., 1992; Klinger et al., 1994; Valente & Thornton, 1993). The gas chromatograhy of the samples is the main method used in these studies.lt is difficult to obtain data, which is representative of an extended area using the chamber method by itself. Because of its high spatial resolution, this method is useful in exchange process studies in soils and plant canopies. The eddy correlation method has been elaborated for ecosystem- atmosphere exchange studies. This method combines the precise micrometeorological wind speed components and the gas flux measurements. Such a method has been widely used for the evaluation of vertical fluxes of heat, momentum and water vapor in natural environments for a long time. It is assumed that the vertical fluxes are constant in the atmospheric boundary layer. For climate change- oriented studies, the eddy correlation method is more representative than the enclosure method. Unfortunately, in Estonia's present conditions, this instrumentation seems to be too expensive. The technique of tunable diode laser spectroscopy is applied for the detection of atmospheric trace gas fluxes. Sonic anemometry is applied to detect fluctuations in the wind velocity components. The covariance of the vertical wind velocity and gas concentration, calculated over a time period, will 2. GREENHOUSE GASES AND THEIR IMPACT ON THE RADIATION BALANCE 13_ represent the flux of the gas. Abandonment of the eddy correlation method means that the GHG budgets cannot be detected with sufficient accuracy, at least as they relate to the exchange between the soil and plant canopies and the atmosphere.

The problem of reducing the GHG emissions in Estonia's present conditions is fortunately not typical of the world, but much easier. Since 1990, industrial emissions of GHG and atmospheric pollutants have been reduced more than a third due to reduced industrial production. Changes in land use are directed towards an increase of forested area. Taking into account quite a wide variety of natural conditions, there is a very good possibility of specialized studies. The most interesting research area seems to be how the GHG absorption-emission in soils and plant canopies depends on seasonal warming and other climate-related changes. Which are the governing processes, and how are they related to the gas exchange? Similar studies have been widely spread in developed countries during recent years (for example TIGER Eye No. 13, 14 , 1995).

The GHG and the ozone Frequently, the greenhouse warming and the stratospheric ozone depletion are treated separately. But a significant number of gases responsible for greenhouse warming coincide with those responsible for ozone depletion. Those gases are characterized by a global warming potential (GWP) on the one hand and by an ozone depleting potential (ODP) on the other. Even gases having no direct influence on ozone, such as CO2, enhance ozone depletion through stratospheric cooling. It is necessary to underline that cooling in the stratosphere and mesosphere due to the increased GHG content is much more evident than tropospheric warming. The total number of compensating feedbacks in these atmospheric layers is lower than those for the troposphere. The melting and freezing of water connected with significant heat release and absorption and direct biospheric effects are unique to the troposphere. The GWP are dependent on the integrated infrared absorption cross sections in the spectral region of the atmospheric infrared window and on the atmospheric lifetimes of gases. The reference gas is carbon dioxide. For other gases, the GWP is determined on a per molecule basis. The GHG have different atmospheric lifetimes, and correspondingly, the values of GWP depend on the time period of integration. For example, in the case of integration over a 100 year period, the GWP of the methane is 24.5 times higher and the GWP of CF2C12 or CFC-12 8500 times higher than GWP of CO2 (IPCC, 1994). The recently revised values are significantly higher than those published a few years ago. In 1991 (WMO, 1991), the corresponding GWP values were 11 and 7 100.

The climatic influence of halocarbons is realized in two different ways. Their current direct radiative warming is well quantified. But their net forcing contains an additional cooling due to stratospheric ozone destruction. The magnitude of this cooling depends strongly on the altitude of the ozone loss. At present, the halocarbon-induced direct heating is nearly compensated by indirect cooling (Daniel et al., 1995). This balance seems to be destroyed in the future. If the compounds destroying ozone are replaced by the "ozone-friendly" ones, then their greenhouse heating will not be compensated by indirect cooling.

The ODP represents the amount of ozone destroyed by emission of a gas over its entire atmospheric lifetime relative to that due to emission of the same mass of CFC-11 (or CFCI3). The ODP is a 14 2. GREENHOUSE GASES AND THEIR IMPACT ON THE RADIATION BALANCE relative measure of ozone depletion in the same way that the GWP is a relative measure of greenhouse warming. The chlorine and bromine compounds having significant ODP are often characterized with regard to the chlorine loading potential (CLP) or the bromine loading potential (BLP). The chemical depletion of stratospheric ozone depends most significantly on total chlorine and bromine burden.

The influence of depleted stratospheric ozone on GHG balance is realized through short wavelength irradiance. The increase of UV-B irradiance affects the terrestrial and oceanic ecosystems and the gas exchange between them and the atmosphere. At present, these processes are poorly understood. Another ozone problem is the ground level ozone and the atmospheric oxidizing capacity problem.The atmospheric balances of some greenhouse gases can be disturbed by the changes in atmospheric oxidizing capacity. A potential danger to methane oxidizing capacity of the lower atmosphere is an increasing use of the "ozone friendly" substances instead of chlorofluorocarbons. A certain part of the atmospheric OH radicals can be used for oxidizing these hydrochlorofluorocarbons, and changes in oxidizing capacity of CO, methane and some other greenhouse gases can occur (Fuglestvedt et al., 1994). Now it is believed that the most significant disturbances by tropospheric ozone and UV-B radiation lead to changes of microbial processes in soils and plants.

Carbon dioxide stands in a key position, not only as a major GHG, but as a carbon source for plant growth. Some recent studies (Rotmans & den Elzen, 1993; Friend et al., 1993 ) have shown that the elevated atmospheric concentration of COi induces significant changes in plant physiology. The acclimation to elevated CO2 levels has become a central problem. Some plant species react to higher CO2 concentrations by reducing their stomatal aperture (Pearson, 1995). At the same time, their water loss becomes reduced, and its redistribution between different species in the canopy occurs. This combination of modified gas exchange and water use changes the photosynthetic rates of the species and CO2 balance of the whole canopy. Most of the currently-used climate models are linear and do not take into account the response changes. Due to this, extrapolations may present significantly unrealistic results. Still, the response changes are poorly studied, and it is virtually impossible to take them into account. Estonian landscapes containing a wide variety of different soils and growth conditions can be considered a perspective area for response studies.

Change in Estonian climate The climate in a certain geographical location is dominantly influenced by atmospheric air masses and their movement. Estonia is geographically located on the crossing of different "imported" air masses. The impact of the local balance of GHG and the local land surface properties on the climatic air mass is small. The prediction of future Estonian climates will require the prediction of trajectories of the climate-forming air masses. Obviously, the origin of the dominating air masses is seasonally different, as are the speed and direction of their movement. To model and predict climate change is a very complicated endeavor, largely because future predictions cannot be checked immediately. The comparison of different models and climatic scenarios has been made on the basis of known past climates. Often, future climates have been predicted on the basis of analogous past climates or on that of very superficial general circulation models. Contemporary atmospheric chemistry and relative composition of trace gases are not directly comparable with past ones. The spatial smoothing of 2. GREENHOUSE GASES AND THEIR IMPACT ON THE RADIATION BALANCE 15_ general circulation models facilitates work at the level of climate zones, but not at the level of such small spatial details as Estonia represents.

For the most part, local climate changes are generated by changes in general circulation. Global warming does not have a direct impact on global climate, but acts through the cyclogenetic and other dynamical processes. In Estonian conditions, winter is believed to be the most sensitive season to climate change. The generation and movement of the determining climate air masses depend on the location of the polar front and on cyclogenetic activity over the Northern Atlantic. Specific effects include regional forcing by the water vapor, clouds and aerosol. In summer and fall, the climate- forming air can have a different origin and can be more stable. Still, it is poorly understood how the local effects of atmospheric circulation depend on the global energy distribution pattern and its changes.

References Arefev, V.N., Kamenogradsky, N.Ye., Kashin, F.V. & Ustinov.V.P. (1995). Investigation of total column water vapor content in the atmosphere. Izv. AN. Fizika atmosfery i okeana, 31, pp. 660-666 (in Russian).

Daniel J.S., Solomon, S. & Albritton, D.L. (1995). On the evaluation of halocarbon radiative forcing and Global Warming Potentials. J. Geophys. Res., 100, Dl, pp. 1271-1285.

Friend, A.D., Shugart, H.H. & Running, S.W. (1993). A physiology-based Gap Model of forest dynamics. Ecology, 74, pp. 792-797'.

Fuglestvedt, J.S., Jonson, J.E. & IsaksenJ.S.A. (1994). Effects of reductions of stratospheric ozone on tropospheric chemistry through changes in photolysis rates. Tellus,. 46B, pp. 172-192.

IPCC (1990). Houghton, J.T., Jenkins, G.J. & Ephraums, J.J. (eds.). Climate Change:The IPCC Scientific Assessment. Intergovernmental Panel on Climate Change. Cambridge University Press.

IPCC (1992). Houghton, J.T., Callander,B.A. & Varney,S.K. (eds.). Climate Change: the Supplementary Report to the IPCC Scientific Assessment. Intergovernmental Panel on Climate Change. Cambridge University Press.

IPCC (1994). Radiative Forcing of Climate Change:The 1994 Report of the Scientific Assessment Working Group of IPCC. Summary for Policymakers. WMO. UNEP.

Khalil, M.A.K. & Rasmussen, R.A. (1994). Global decrease in atmospheric carbon monoxide concentration. Nature, 370, pp.639-641.

King, A.W., Emanuel, W.R. Wullschleger, S.D. & Post, W.M. (1995). In search of the missing carbon sink: a model of terrestrial biospheric response to land-use change and atmospheric CO2.. Tellus, 47B, pp. 501-519. 16 2, GREENHOUSE GASES AND THEIR IMPACT ON THE RADIATION BALANCE

Klinger, L.F., Zimmermann, P.R., Greenberg, J.P., Heidt, L.E. & Guenther, A.B. (1994). Carbon trace gas fluxes along a successional gradient in the Hudson Bay Lowland. J. Geophys. Res., 99, Dl, pp. 1469-1494.

Lawrence, M.G. (1993). An empirical analysis of the strength of the phytoplankton-dimetylsulfide- cloud-climate feedback cycle. J. Geophys. Res., 98, Dl 1, pp. 20663-20673.

Lovelock, J.E. & Kump, L.R. (1994). Failure of climate regulation in a geophysiological model. Nature, 369, pp. 732-734.

Marland, G., Boden, T.A., Griffin, R.C., Huang, S.F. Kanciruk, P. & Nelson, T.R. (1989). Estimates of the CO2 emissions from fossil fuel burning and cement manufacturing using the United Nations energy statistics and the US Bureau of Mines cement manufacturing data. ORNL/CDIAC-25. NDP-030. Oak Ridge, TN: Oak Ridge National Laboratory.

Newell, R.E., Newell, N.E., Yong Zhu & Scott, C. (1992). Tropospheric rivers? - A Pilot Study. Geophys. Res. Lett., 12, pp. 2401-2404.

Pearson, M. (1995). CO2 and stomatal functioning. TIGER eye, Newsletter of TIGER: a NERC community research programme, No 14, p. 2.

Rotmans, J. & den Elzen, M.G.J. (1993). Modelling feedback mechanisms in the carbon cycle: balancing the carbon budget. Tellus, 45B, pp. 301-320.

Roulet, N.T., Ash, R. & Moore, T.R. (1992). Low boreal wetlands as a source of atmospheric methane. J. Geophys Res.,. 97 D4, pp. 3739-3749.

Siegenthaler, U. & Sarmiento, J.L. (1993). Atmospheric carbon dioxide and the ocean. Nature, 365, pp. 119-125.

WMO Report No. 25 (1991). Scientific assessment of the ozone depletion.

TIGER Eye (1995). Newsletter of TIGER: a NERC community research programme, No. 13, p.14. EE9800003

26 , 4. COMPOSITION OF ESTONIAN ATMOSPHERE

4. COMPOSITION OF ESTONIAN ATMOSPHERE

Jaan-Mati Punning and Agu Karindl Institute of Ecology, 2 Kevade Str., EE0001 Tallinn

Introduction Atmospheric study, particularly that of its chemical composition, has a long tradition in Estonia. Since middle of this century, in addition to meteorological observations, some chemical compounds in precipitations have been regularly measured in many meteorological stations. The main aim was to acquire information about the state and dynamics of the atmosphere. Therefore, main attention was paid to monitoring chemical compounds which have a direct impact on the human environment.

As energy production developed intensively and SO2 and NOX increased drastically in the atmosphere in acidic rock areas, like Scandinavia, the problem of acid rain became the most important environmental problem in Europe and North-America. As a consequence, monitoring the compounds of sulphur in precipitation was organized in Estonia. In the 1970s, as related to large operating oil shale-based power plants, Estonia became a country , where emissions of sulphur compounds per capita were extreamly high. In 1979, Estonia became a participant in the European Monitoring and Evaluation Programme - the network created to study transboundary air pollution. The aims of the precipitation chemistry study and the related problems of the formation and transformation of the atmospheric composition have varied over the years. But monitoring of pollutant (in particular, sulphur compound) loads has been a central issue. Over recent years, an attempt was made to estimate the spatial regularities of atmospheric impurities and their impact on the pH of mean monthly precipitations (Frey et al., 1991). Furthermore, calculations were provided to find out the origin of atmospheric impurities washed out in Estonia (Roots, et al., 1992;Punning,1993). Until the 1990s, CO2 and some other greenhouse gas (GHG) emissions were not studied in Estonia. The first inventory of GHG for Estonia was provided in 1995 using the Intergovernmental Panel on Climate Change (IPCC) methodology. The principles of this methodology are based on the following considerations: 1. The emission and removals were calculated for the sectors directly caused by human activities or as a result of natural processes affected by human activities. 2. Energy and industrial sector carbon dioxide emissions were calculated using Carbon Emission Factors (IPCC Guidelines, 1994), amounts of fuels and the carbon content of fuels. 4. COMPOSITION OF ESTONIAN ATMOSPHERE 27_

3. In forestry, the methodology was based on the assumption that the flux of CO2 to or from the atmosphere be equal to the changes in carbon stocks in the existing biomass, and soil. Changes in carbon stocks be estimated by the rates of change in the land use. 4. Since the main GHG source in agriculture is animal husbandry and the use of fertilizers, calculations of CH4 and NO2 emissions were made. 5. In the GHG budget calculations for wetlands, the mean values of carbon accumulation and the decay of natural and drained peatlands and for lakes were used. The resultant GHG budget contained very valuable information, but it is rather complicated to use the results to characterize Estonia's atmosphere. There are some other processes that have a significant influence on the composition of the atmosphere, such as: 1. The chemical processes with different GHG in the fuel burning process, their interaction with the atmosphere, their outwash from the atmosphere and the absorption by the surface of land or waterbodies. 2. Transboundary processes (import-export).

Therefore, to obtain an objective picture about the Estonian atmosphere, it is neccessary to conduct an additional study and compare the GHG inventory data with the results of direct measurements of atmospheric compounds.

Estonian Greenhouse Gas Inventory

The GHG Inventory for Estonia was compiled for the energy, industry, transport, agriculture, forestry, and land-use sectors. Thus, all directions of human activities related to GHG emissions were covered. In the Estonian GHG Inventory, six gases were found to have direct or indirect impact on the greenhouse effect: carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), nitrous oxide (N2O), nitrogen oxides (NOX), and non-methanous volatile compounds (NMVOC). In addition, there are other groups of compounds that contribute to the greenhouse effect, for instance, chlorofluorocarbons - CFCs, hydrofluorocarbons - HFCs, and sulphur hexafluoride - SF6, which are not included in this inventory because their share in Estonia's GHG emissions is insignificant. Energy-related activities are the most significant contributors to greenhouse gas emissions. Estonia's primary sources of energy are fossil fuels, in particular, oil shale, whose share in the total fuel consumption is approximately 68% (Punning, et al., 1995). Estonia's oil shale field is the largest commercially exploited deposit in the world. The deposit has been exploited since 1916, and its total output exceeds 800 million tons of shale. Oil shale has a low caloric value; the calorific value of dry material is approximately 7.5-18.8 MJ/kg (1800-4000 kcal/kg). The main components of oil shale are organic matter or kerogen (15-46%); carbonate matter (26-57%) and clastic material (18-42%). Oil shale contains a relatively small amount of sulphur, which mainly occurs in a sulphide form (Jiirgenfeld et al., 1994). 28 4. COMPOSITION OF ESTONIAN ATMOSPHERE

In the context of GHG emissions, the high content of carbonate rocks is particularly important, because they dissociate at high temperatures in boiler houses. The content of carbonate CO2 varies in different seams from 14 up to 23% (Ots, 1977), and therefore the total quantity of carbon dioxide increases up to 25% in the flue gases of oil shale. This type of fuel is not common in the world, and therefore in the IPCC methodology, the carbon emission factor for oil shale was absent and was calculated by A.Martins as 29.1 tC/TJ (Punning, et al., 1995). This value exceeds that of other common fuels and is comparable with the emission factors of some lignites and peat. Apart from GHG emissions, the oil shale-fired power production and industry are major contributors to atmospheric pollution. In 1990-1991, the quantity of air pollutants in north-eastern Estonia (where the main oil shale operating industry is located) might have been 440-470 thousand tons. During this period, only six thermal power plants have emitted annually about 180 thousand tons of fly-ash, 200 thousand tons of SO2 and 16 thousand tons of NOx (Liblik and Ratsep, 1994) ranking among the six largest pollution sources in Europe. The emissions by TPP were the largest in the late 1970s. Then the new purification systems (electrofilters) were established, and emissions decreased markedly. Since the 1990s, energy production has decreased considerably due to economic decline. The history of air pollution is recorded by peat and lake sediment sequences, where the distribution of heavy metals and spherical particle content closely follows the history of oil shale consumption (Varvas and Punning, 1993).

Table 1. Estonian GHG emissions from the energy and industry sector in 1990 and 1994, based on the IPCC methodology, Gg (Punning et al., 1995)

Compound 1990 1994

C02 39,597 23.7K CH4 322 187 N2O 2,3 1,3

N0X 93 50 CO 185 101 NMVOC 22.9 12.5

Apart from the energy production and industry (such as mining, gas transmission), waste decomposition contributes measurably to the methane emissions in the atmosphere. According to preliminary calculations, the total amount of methane emitted by landfills and wastewaters was approximately 42 Gg CH4 in 1990. In addition to direct GHG, solid matter (fly-ash) and sulphur dioxide emitted by oil shale- operated power plants and industry are substantial. According to the reports of the Environmental Data Centre (Estonian Environment, 1991), in 1990 278 thousand tons of fly ash and 233 thousand tons of SO2 were emitted to the atmosphere from stationary sources. Due to a decline in oil shale consumption and power production, the emissions were some 130 and 120 thousand tons in 1994. There are plenty of other pollutants (for instance, nitrogen oxides, polycyclic aromatic hydrocarbons and other organic compounds, heavy metals) emitted into the atmosphere, but, as a rule, their distribution is mainly restricted to the vicinity of the source. 4. COMPOSITION OF ESTONIAN ATMOSPHERE 29

The calculation and prediction of pollutant dispersion in the atmosphere is complicated because of various factors, such as the parameters of the sources (for instance, height above ground level), emissions (temperature, flow-out velocity, and intensity per time unit), meteorological characteristics (wind speed, direction, and atmospheric stratification), surface profile and temperature, chemical reactions in the atmosphere. Therefore, even today only such models have been elaborated that characterize a short-time pollution level, formed by wind parameters above certain points of the landscape (Liblik & Ratsep,1994). Isolines of the concentrations of fly-ash and sulphur dioxide around the pollution sources show that the concentration of pollutants decreases quickly in relation to the distance from the emission source. On the basis of these models alone, it is complicated to estimate the share of long-transported pollutants. In the non-energy sector (dispersed emission sources), the changes in emissions and sinks of GHG are related to changes in land-use. Calculations performed by M.Mandre (Punning, et al., 1995) showed that over the last fifty years, as the forest stands area has more than doubled, forest is essential in the sequestration of CO2. Consequently, CO2 uptake by forests in 1990 exceeded 3.3 times its emission, and the annual net removal of CO2 was approximately 7950 Gg. The main GHG sources in Estonia's agriculture are animal husbandry and the use of fertilizers. The calculations made by H.Roostalu showed that in 1990 the methane emissions from livestock were 60 Gg, and the nitrogen oxide from the mineral fertilizers used 0.91 Gg. Over the years since then, the decrease in these gas emissions has been significant (Punning, et al., 1995). Wetlands are a particular problem in providing the GHG inventory for Estonia. About one million ha or ca 22% of Estonia's territory is covered by wetlands (peatlands and lakes). Peat contains a huge amount of accumulated carbon. According to M.Hornets (Hornets et al., 1995), the mean peat organic matter accumulation on fens may be about one ton per hectare and 1.6 tons per hectare on ombrolrophic bogs (dominated by Sphagnum). During the Holocene (the last 10,000 years), this value has varied depending on the temporal-spatial development of peatlands. Up to the last century, the carbon balance was determined by natural processes. Due to amelioration activities, the carbon cycling of wetlands is greatly influenced by a human. There are two consequences resulting from the human impact on peatlands:

1. As a result of the drainage of peatlands, CO2 accumulation has ceased, and due to the intensive decay processes, the mineralization of organic matter and emission of CO2 has started.

2. In general, the drainage of peatlands has decreased CH4 emissions. The calculations performed by M. Hornets showed that in peatlands, strongly affected by amelioration work, carbon accumulation in 1990 was lower than in 1970 by approximately 300 Gg, and CH4 emissions had decreased approximately 5 Gg (Punning, et al., 1995). Summarized results of the GHG budget in Estonia for the years 1990 and 1994 are illustrated in Table 2. 30 4. COMPOSITION OF ESTONIAN ATMOSPHERE

Table 2. GHG budget in Estonia in 1990 and 1994

GHG Sources and Emissions, Gg

Sink Categories CO 2 CH4 N2O CO NOX NMVOC 1990 199+ 1990 199+ 1990 1994 1990 1994 1990 1994 1990 1994 Fuel Combustion 37184 2K13 3 2 1.4 0.8 184 100 93 50 22.9 12.5 Fugitive Fuel NO NO 217 109 NO NO NO NO NO NO NO NO Emissions Industrial Processes 613 215 NA NA NA NA NA NA NA NA NO NO Agriculture NO NO 60 46 0.9 0.5 NO NO NO NO NO NO Land Use Change & •7950 •7660 NO NO NO NO 1 1 NO NO NO NO Forestry Wetlands 9746 9746 NO NO NO NO NO NO NO NO NO NO Wastes NO NO 42 30 NO NO NO NO NO NO NO NO NA - not available NO - not occurring

Because of drastic changes in the Estonian economy and political life since 1990, strong trends towards the decrease of GHG emission have prevailed. As a result, within the recent 3-4 years, the total GHG emission in Estonia has diminished by about 40%. It is obvious that the decreasing trend of GHG emissions is partly related to the economic decline and cannot continue at such a rate indefinitely. After economic recovery, a period of stabilization and an increase in energy use will follow.

Accumulation of CO2 by alkaline matter Due to the high carbonate content in oil shale, the content of alkaline oxides, in particular, CaO, in combustion products is very high. According to the data reported by Ots (1977), the carbonate fraction contains 90.5% CaCO3; 9.2% CaMg(CO3)2; 0.3% FeCO3. Of oil shale combustion technologies, pulverized fuel combustion is the most common, Approximately 45% of the total amount of fired oil shale will be converted to ash. The bulk of the ash falls to the bottom of the furnace and is carried by hydrotransport to the ash fields, which cover some 10.6 km . The water (8-10 million m3) in the closed system of hydrotransport has a pH value of about 13 and a mineral content up to 11 g I"1. In this way, ca 7000 million tons of furnace bottom ash will be transported to the ash fields annually. This quantity contains approximately 3.1 million tons of free CaO. CaO will hydrolyse and react with atmospheric CO? according to the following formulas:

CaO + H2O = Ca(OH)2 + Ca(OH)2 = CaOH +OH~ CaOH+ = Ca2+ +OH~ 2+ 2 Ca + CO3 " = CaCO3. 4. COMPOSITION OF ESTONIAN ATMOSPHERE 31

To calculate the share of free CaO which will react with atmospheric CO2, such limitations have to be considered as the diffusion coefficient of CO2 in water and temperature, furthermore the fact that after a certain time, part of the CaO-rich ash will be buried by new layers of ash. if we presume that the share of reacted CaO is between 0.1 and 0.5, then the sink of CO2 in ash fields is 0.25-1.25 million tons per year (Table 3). This amount equals 1-5% of the total yearly emission of CO2 by thermal power plants in Estonia. Approximately 160 thousands tons of solid pollutants were emitted into the air in 1994. More than 95% of that was fly-ash emitted by plants operating on oil shale. The content of earth and alkali metals in fly-ash is even higher than in furnace bottom ash due to thermal destruction of clay minerals in the furnace with the volatilization of potassium (Opik, 1989). The concentrations of fly-ash in the atmosphere of Estonia vary greatly. Naturally, the highest concentrations has been found in north-eastern Estonia. Based on the results of numerical modelling (Liblik & Ratsep, 1994), it is possible to distinguish three zones. The first zone, comprising the area within a radius of 9-12 km from the Baltic TPP, is characterized by a dust level exceeding 300 jag m"-' of solid dust in the atmosphere. The second zone extends for 20-25 km to the west and south of the Estonian TPP with a maximum surface dust concentration of 100-300 fxg m~-\ The remaining territory of the Ida-Virumaa County belongs to the third zone, where the concentration of dust in the air is below 100 |Hg m"3 (Liblik & Ratsep, 1994). Therefore, the pH values of precipitation in north-eastern Estonia are high troughout the year, the mean values in the summer months being 5.9-7.5 (Punning, 1991). The pH value of the fly-ash precipitated on the electric filters is in the interval of 12.3-12.6 (Mandre, 1995). In general, free CaO content in the fine grain ash from cyclones and electrical precipitators is 40.0 % (Pets et al., 1985). Its proportion decreases with the reduction of the disintegration level. Therefore, we can presume that CaO content in fly-ash is ca 30%, and its content in the annual emissions into the atmosphere totals 50 thousand tons.

Table 3. Amounts of ash and CaO transported to ash fields and CO2 neutralized by CaO

Emission Amounts of ash Amounts of CaO Neutralized CO2, Gg year transported to in the ash, Share of reacted CaO ash fields, Gg Qg 0.1 0.25 0.5 1990 7.32 3.11 0.24 0.61 1.22 1991 7.45 3.20 0.25 0.63 1.26 1992 7.09 3.12 0.24 0.61 1.22 1990-1992 21.87 9.42 0.74 1.85 3.70

In the atmosphere, CaO is in a very dispersed form, and therefore an active reaction with CO2 will proceed intensely, depending mainly on the moisture content. Most probably in the case of the wet outwash, the reaction might be complete. If we again presume 0.5, 0.25 and 0.1 share of neutralization of CaO by CO2, the chemically bounded amount of CO2 (as CaCOi) is from twenty thousand tons up to four thousand tons annually or less than 0.1% of the total amount of CO2 emitted by oil shale combustion. 32 4. COMPOSITION OF ESTONIAN ATMOSPHERE

Fly-ash will deposit and reach the soil surface as dry and wet sediments. The study of the transect located in northern Estonia near the Kunda Cement Plant demonstrates explicitly that the accumulation of earth and alkaline oxydes causes alkalization and an increase in the pH values of soil. The hydrolytic acidity of the soil has decreased but the level of saturation with alkali has become very high, reaching 99% in the litter horizon and 75-85% in deeper horizons. In the vicinity of the cement plant, the pH of litter layer was above 7, being 4.5 units higher than the control. Moreover, the pH of subsoil water has increased, having values higher than 7 (Annuka & Mandre, 1995). In those conditions, CO2 will react with free CaO. Considering that about half of the free CaO is hydrolyzed and reacts with CO2 in the atmosphere, the remaining half would then react during some interval with CO2 in soil. It means that theoretically some 20 thousand tons of CO2 would be absorbed by this part of fly-ash. Summarizing all sinks related to combustion products of oil shale, we obtain a maximum value of CO2 of 1.25 million tons annually or approximately 6% from the total emitted CO2 from oil shale combustion. This facilitates the reduction of CO2 emissions if the amount of bonded CO2 can be increased.This can be accomplished by:

1. Reducing the amount of CO2 released in oil shale combustion from the mineral part of oil shale;

2. Increasing the share of CO2 neutralized by free CaO.

Long transported pollutants in Estonia's atmosphere As a result of the geographical position and open landscape of Estonia, its atmosphere is influenced both by local pollution sources and, to a great extent, by contaminants transferred from the neighbouring areas. The best indicators of that process are the distribution curves of heavy metals in snow cover and lichens, because there are no metallurgy industries in Estonia. The spatial distribution of industry in the territory of Estonia and the heavy metal isolines show that the majority of the elements studied (Zn, Cd, Cu, Pb) reach Estonia by long-distance transportation. The input is constant from the south-west and west and less explicit from the south-east (Punning et al., 1991). The influence of local pollution sources is more evident only in north-eastern Estonia near large industrial centers. The share of long-transported gaseous compounds is difficult to estimate. Within the European Monitoring and Evaluation Programme framework, it has been calculated that in 1980 71,000 tons of sulphur precipitated on the surface of Estonia, 26,000 tons of which originated from within Estonia (Roots et al., 1992). According to the data reported by Frey et al. (1988), 90,000 tons of sulphur precipitated in Estonia in 1987 half had a transboundary origin. Both estimates seem to be exaggregated, because the real precipitated amounts of sulphur were considerably lower (Punning, 1993). Model calculations provided by Tuovinen et al.(1990) showed that approximately 1/3 of the total amount of sulphur compounds deposited in Estonia originated from outside Estonia. These examples demonstrate that budget calculations for different atmospheric constituents are complex. In addition to the compounds transported over long distances, in the case of a rather 4. COMPOSITION OF ESTONIAN ATMOSPHERE 33_ small country such as Estonia, difficulties will also arise of how to calculate the contribution of gases emitted by long-distance vehicles like airplanes and ships, and overflying flights.

Conclusions To obtain a real picture of the composition of the atmosphere is an extremly complex task. Based on the IPCC methodology for the GHG Inventory, the first serious attempt was made to establish the fluxes of some gases (mainly GHG) to the atmosphere and from the atmosphere to the biosphere. The data show that in the Baltic Sea region in 1990 Estonia had the highest emissions of major GHG per capita. Due to the restructuring of Estonia's economy since 1990, the total emission of GHG has diminished approximately by 40%.

In addition to the CO2 fluxes to the biosphere, the flux to alkaline environments (such as soil, waterbodies), typical of those surrounding oil shale-fired factories, is still substantial. Preliminary calculations show that up to 5% of the total emitted CO2 might be bound by CaO into carbonate. Because of the open landscape, the transboundary exchange of pollutants is active. Rough estimates demonstrate that about half of the sulphur compounds precipitated in Estonia have a long-transported origin. Due to the dominating winds, southwestern and western Estonia are particularly influenced by long-transported airborne pollutants and to lesser extent, the south- eastern areas of the territory.

References Annuka, E. & Mandre, M. (1995). Soil responses to alkaline dust pollution. In: Mandre, M. (ed). Dust pollution and forest ecosystems. A study of conifers in an alkalized environment. Inst. of Ecology, Publ. 3, Tallinn, pp. 33-44. Estonian Environment (1991). Environmental Report 4. Environmental Data Centre, Helsinki, 64pp. Frey, J., Frey, T. & Rasta, E. (1991). Sademete saastusest Eestis 1986-1989.- Kaasaegse okoloogia probleemid, Tartu, pp. 25-29 (in Estonian). Hornets, M., Animagi, J. & Kallas, R. (1995). Estonian Peatlands. Ministry of Environment, Tallinn, 48pp. IPCC Guidelines for National Greenhouse Gas Inventories (1994). v.1-3. Liblik, V. & Ratsep, A. (1994). Pollution sources and distribution of pollutants. In: Punning, J.- M. (ed.). The influence of natural and anthropogenic factors on the development of landscpes. The results of a comprehensive study in NE Estonia. Inst. of Ecology, Publ. 2, Tallinn, 227 pp. Mandre, M. (ed)(1995). Dust pollution and forest ecosystems. A study of conifers in an alkalized environment. Inst. of Ecology, Publ. 3, Tallinn, 188 pp. Ots, A.,A. (1977). The processes in the boilerhouses by the combustion of oil shale and shale from Kansko-Atsinsk. Moscow, 312 pp. (in Russian). 34 4. COMPOSITION OF ESTONIAN ATMOSPHERE

Pets, L.I.,Vaganov, P.A., Knoth, I., Haldna, U., Schwenke, H., Schnier, C. & Juga, R.J. (1985). Microelements in oil shale ash of the Baltic thermoelectric power plant. Oil Shale, 2/4, pp.379-390 (in Russian). Punning, J.-M. (ed.)(1991). Ida-Viru District. Human impact on environment. Inst. of Ecol. and Marine Res. Tallinn, 19 pp. Punning, J.-M. (1993). Eesti atmosfaar nii ja teisiti. Eesti Loodus, pp. 118-120 (in Estonian). Punning, J.-M., Mandre, M., Hornets, M., Karindi, A., Martins, A. & Roostalu, H. (1995). EstoniarGreenhouse Gas Emissions.- In: Ramos-Mane, C. & Benioff, R. (eds.). Interim report on Climate Change Country Stuudies. Washington, pp. 33-39. Punning, J.-M., Zobel, M., Lillemets, S., Trass, H., Roosma, A., Minayeva, O., Saare, L., Viitak, A. & Hodrejarv, H. (1991). Heavy metals in snow and some indicator plants in Estonia. Proc. Estonian Acad. Sci., Ecol., 1, 2, pp. 65-71. Roots, O., Saar, J. & Saare, L. (1992). Air quality above the territory of Estonia. - In: Air pollution in Estonia 1985-1990.Environmental Data Centre, Helsinki, pp. 5-27. Tuovinen, J.-P., Kangas, L. & Nordlund, G. (1990). Model calculations of Sulphur and Nitrogen deposition in Finland. In: Kauppi, P., Antilla, P. & Kenttamies, K. (eds.).Acidification in Finland. Springer Verlag, pp. 167-199. Varvas, M. & Punning, J.-M. (1993). Use of the ^10pb method in studies of the development and human impact history of some Estonian lakes. The Holocene, 3, 1, pp.34-44. Opik, I. (1989). Ash utilization after combustion and thermal processing of Estonian (kukersite) oil shale. Oil Shale, 6, 3, pp.270-275. EE9800004

5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATION 35 AND CLIMATE SCENARIOS

5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATIONS AND CLIMATE SCENARIOS

Jaak Jaagus University of Tartu, Institute of Geography, 46 Vanemuise Str., EE2400 Tartu

Introduction Estonia is located on the eastern coast of the Baltic Sea between 57°30'N and 59°40'N. It represents a transition zone from the maritime climate type to the continental one. In spite of its comparatively small territory (45 215 km"), climatic differences in Estonia are significant, especially during the colder half of the year. For example, mean air temperature in January varies from -2.5°C on the western coast of the Island of Saaremaa up to -7.5°C in the coldest places in east Estonia. Mean duration of snow cover is between 75 and 130 days. Furthermore, temporal variability of meteorological values has been very high in Estonia. Weather conditions depend directly on cyclonic activity in the Northern Atlantic. Long-term fluctuations in its intensity reflect on meteorological anomalies. Based on high variability of weather conditions, Estonia can be expected to be a sensitive region for possible climate change. The aim of this study is to establish trends and long-term periodical fluctuations in meteorological time series in Estonia, and to develop climate change scenarios for the estimation of climate change tendencies caused by the increase in the concentration of greenhouse gases in the atmosphere.

Data The first regular meteorological observations in Estonia date back to the late 18th century. The longest continuous time series are available since the early 19th century. The majority of stations at that time were located on the seashore at lighthouses. In 1865, the Meteorological Observatory of the University of Tartu was founded. Since that year, high quality measurements, such as for precipitation, have been made. In this study, time series of five meteorological values - air pressure, sunshine duration, air temperature, precipitation and snow cover- are analyzed. Owing to the statistical peculiarities, each value needs an individual approach. A very high spatial variability is characteristic of precipitation and snow cover data. They are measured in a great number of stations. In this study, time series of spatial mean values of annual and seasonal precipitation and snow cover duration (e.g., number of days with snow cover during a winter) were analyzed. Territorial averaging of precipitation data was made by spatial interpolation into grid cells for the period 1866-1994 (Jaagus, 1992). 36 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATIONS AND CLIMATE SCENARIOS

Spatial mean values of snow cover duration in Estonia were found by means of a geographical information system. IDRISI raster images were created to represent snow cover fields. The mean value of all raster elements on the terrestrial part of Estonia was calculated for 124-year time series of winters (1891/1892-1994/1995) where snow cover was observed. Territorial variability of the other meteorological characteristics was much lower. Therefore, time series of single stations were studied. Four stations in different climatic regions in Estonia with the longest observation periods were chosen to describe trends and fluctuations of air temperature. Tallinn represents northern Estonia and has the longest observation period-1828- 1994. Tartu (1866-1994) is located in the continental part of Estonia in the south-east, Parnu (1842-1994) is situated on the coast of the Gulf of Riga in the south-west, and Vilsandi (1865- 1994) resides on a small island with the most maritime climate, near the western coast of the Island of Saaremaa. Sunshine duration and air pressure were studied only in Tartu during the periods 1901-1994 and 1881-1994, correspondingly. The absence of observations has replaced by values calculated on the basis of data measured at neighbouring stations. Time series both of annual and of seasonal values were analyzed. Fluctuations in intensity of cyclonic activity occur, first of all, in seasonal patterns. Seasonal values were calculated for a period of three months. For example, spring means the period from March to May and summer - from June to August. The problem of homogeneity in meteorological time series is of great importance. Typically,, they are not entirely homogenuous. Over a long time, locations of stations, surroundings of observation places, times of measurements, gauge types, and measuring techniques have changed. Possible inhomogeneities were studied and taken into account in the analysis of the results. The standard climatic period 1961-1990 was used as a baseline period for developing climate change scenarios. The baseline scenario was developed as a complex of mean values of monthly air temperature, precipitation and solar radiation measured at meteorological stations in Estonia and averaged over the baseline period. Mean temperature was calculated for 25 stations. Spatial mean totals of precipitation were found by averaging values interpolated into grid points by use of data recorded at more than a hundred precipitation stations. Solar radiation was measured only in Toravere.

Trends and periodicities By linear trend analysis trends were determined, and autocorrelation and spectral analyses were used to estimate periodical fluctuations in meteorological time series in Estonia. In some cases, significant trends and periodicities were found; in other cases they were not. It is important to emphasize that periodical fluctuations of meteorological times series are not exactly cyclic, but are more like quasi-periodical. It means that the alternation of maximum and minimum values is clearly distinguishable but the time interval between them varies.

Air pressure is a less variable meteorological 'alue, but it has a great significance. Air pressure expresses the character of the entire complex of meteorological conditions: the prevailing low or 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATION 37 AND CLIMATE SCENARIOS high pressure. Figure 1 represents the time series of annual mean air pressure in Tartu. A series of five-year moving means and a linear trend line were added to the figure. The weak increasing trend is not statistically significant. Noticeable fluctuations of air pressure were observed. In the 1960s, air pressure was the highest, while during the 1920s and 1980s it was the lowest. The long-term fluctuations were determined by the frequency of different types of atmospheric circulation. Lower pressure corresponded to the domination of zonal circulation and to intense cyclonic activity. Our analysis of the time series of seasonal mean air pressure gave interesting results. The increasing trend of air pressure in spring (March-May) and in summer (June-August) was clearly distinguishable and statistically truthful. At the same time, the decrease of air pressure was observed in autumn (September-November) and in winter (December-February). Such kinds of opposite trends allow one to conclude that the climate change in Estonia has progressed toward a more maritime climate type. High pressure during the warmer half of the year and low pressure during the colder half of the year is peculiar to a maritime climate, while the opposite fluctuations are characteristic of a continental one.

Fig. 1. Mean annual air pressure in Tartu.

The time series of annual sunshine duration in Tartu is somewhat similar to that of air pressure (Fig.2). A weak increasing tendency and significant deviations were observed. The most sunny years were the 1940s and the 1960s, and the most cloudy were the 1920s, the 1950s and the 1980s. Sunshine duration depends directly on cloudiness. Cloudiness was determined by atmospheric circulation and air pressure. 38 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATIONS AND CLIMATE SCENARIOS

1200 1901 1911 1921 1931 1941 1951 1961 1971 1981 1991

Fig. 2. Annual total of sunshine duration in Tartu.

Mean air temperature is the most important meteorological value for detecting climate change. There is a very high correlation (more than 0.95) between the times series of annual mean air temperature at the four stations. Therefore, data measured in Tallinn (Fig.3) can represent the whole country quite well. Annual mean air temperature has increased by 0.7-1.0°C at every station in Estonia since the middle of the last century.

o

1828 1848 1868 1888 1908 1928 1948 1968 1988

Fig. 3. Mean annual air temperature in Tallinn.

The temporal course of air temperature is coherent with large-scale temperature changes in the Northern Hemisphere. A significant increasing trend existed over the period from the middle of the last century up to the 1930s. Then followed a stable period. But the last decade was the warmest also in Estonia. The warming was observed in spring (by 1.9°C), autumn (by 0.3°C) and 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATION 39 AND CLIMATE SCENARIOS

winter (by 1.4°C) but not in summer. Remarkable periodicities in air temperature series were not determined. Air temperature in winter had the highest variations. It determined annual mean values. The time series of spatial mean annual precipitation has an increasing trend. It is mainly caused by the improvement of gauges and measuring techniques. The corrected time series (Fig.4) was characterized only by a small increase (by 27 mm). A reliable trend was detected only for autumn and winter precipitation. By spectral analysis, obvious periodical fluctuations of precipitation were detected with periods of 50-60, 25-30, and 5-7 years. The most important periods of high precipitation were observed in 1866-1873, 1923-1935, and 1978-1990. These maxima appeared in annual and in autumn totals of precipitation. There were weaker secondary maxima between them in 1897-1906 and 1952-1962. They corresponded to a periodicity of 25-30 years. During summer season, only the period of 5-7 years was determined. In case of spring rainfall, another periodicity (22-23, 45-47 years) was observed. Winter precipitation series was entirely inhomogenuous and was not analyzed.

850 k III I 1 1 ll I 750 Ail A E 650 i I 550 r \ 450 HrI j V!'

1866 1886 1906 1926 1946 966 1986

Fig. 4. Spatial mean annual precipitation in Estonia.

The analysis above has shown that the winter period has the highest variability of weather conditions. Snow cover duration is the best characteristic to describe winter weather. Figure 5 illustrates variations of spatial mean snow cover duration in Estonia. The time series has a decreasing trend. During the 104 years, mean number of days with snow cover has changed by 16 days - from 121 to 105. The first half of the period, until the 1930s, is characterized by a very significant trend, while, during the latter half, the trend is very weak. The decrease of snow cover duration over the recent ten years has been rapid again. Figure 5 demonstrates significant periodical fluctuations over 13-18 years. Periods of mild winters with a lower duration of snow cover were observed during the following periods: 1929/1930-1938/1939, 1948/1949- 1951/1952, 1958/1959-1960/1961, 1971/1972-1974/1975, and 1988/1989-1991/1992. 40 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATIONS AND CLIMATE SCENARIOS

1892 1902 1912 1922 1932 1942 1952 1962 1972 1982 1992

Fig. 5. Spatial mean duration of snow cover in Estonia.

Climate change scenarios Global climate warming due to the increase in greenhouse gas concentrations in the atmosphere has been the main research topic in climatology over the recent decades. Possible climate changes all around the world can be examined on the basis of general circulation model (GCM) outputs. They are the best sources for developing climate change scenarios (Robock et al., 1993). Results of five GCM runs were used in the current study (Table 1). These outputs were combined with the baseline climate data to produce climate change scenarios that could serve as inputs for vulnerability assessment (Carter et al., 1992; U.S. Country Studies Program, 1994).

Table 1. General circulation models used in this study

GCM developed by Abbrevation Date of model Model resolution (latitude x Vertical MeandT run longitude) levels for2xC0, Goddard Institute of Space Studies GISS 1982 7.83°x10.0° 9 4.2° Geophysical Fluid Dynamics Laboratory GFD3 1989 2.22°x3.75° 9 4.0° Canadian Climate Centre CCCM 1989 3.75°x3.75° 10 3.5° United Kingdom Meteorological Office UK89 1989 2.50x3.75° 11 3.5° Geophysical Fluid Dynamics Laboratory transient GF01 1991 4.44°x7.50° 9 4.0°

Two types of GCM output were used in this study. The first type, lxCO2, should correspond to the baseline climate, and the second one, 2xCC>2, to the climate in the case of a double carbon dioxide concentration. The outputs consisted of monthly mean air temperature, precipitation and solar radiation. The selection of GCMs for developing climate change scenarios was made by means of comparing 1 xCO2 model output data with the baseline climate scenario. 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATION 41 AND CLIMATE SCENARIOS

GCM outputs in lxCO2 scenarios for air temperature are quite similar within the continental part of Estonia and sligthly different in the West Estonian Archipelago. Figures 6 and 7 show the mean annual curve of monthly mean air temperature at two widely separated stations according to the baseline scenario and the GCM-based lxCO2 scenarios. Voru is located in the most continental part in south-east Estonia and Sorve - on the westernmost island.

• Baseline -GISS GFD3 CCCM _ _#_ _ GF01

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 6. lxCO2 air temperature scenarios for Voru.

• Baseline -GISS

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Fig. 7. lxCO2 air temperature scenarios for Sorve.

UK89 output data were excluded from Fig.6 because the values were excessively low. In the continental part of Estonia, the model indicates below -20°C in winter. Summer maximum values are below +15°C. Such kinds of data are typical of the climate in Siberia at the same latitudes. The rest of the GCMs also tend to underestimate air temperature in winter. Only CCCM output indicates a 42 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATIONS AND CLIMATE SCENARIOS

higher temperature. In summer, overestimates (GF01, CCCM) as well as underestimates (UK89, GISS) occur. Among the single GCMs, the best results were obtained by CCCM, especially during spring and autumn when the other models markedly underestimated air temperature. CCCM overestimates winter temperatures, and in the continental Estonia also summer temperatures. GISS model results are satisfactory, too. They are the best in winter time. Air temperatures in spring and in autumn are obviously underestimated. GFD3 was the third suitable model for describing the annual curve of air temperature. Generally, it underestimates temperature except in the summer time. This model suits better for west Estonia, presenting quite well the influence of the Baltic Sea on air temperature. The GF01 transient model underestimates temperature in winter and overestimates it in summer. UK89 underestimates current climatic conditions during the whole year, particularly in the region of the continental type of climate. In terms of precipitation, the deviation of GCM results from the baseline data was substantially higher. Unfortunately, most of the GCMs highly overestimate precipitation during the colder half of the year, and underestimate it in summer, in July and August. Consequently, the models do not describe correctly annual curve of precipitation in Estonia. Precipitation measurements are representative only for the small area around a gauge. Therefore, it is not reasonable to use data from single stations. GCM results were compared with spatial mean data for the territory of Estonia (Fig. 8). The UK89 model gave the best results, expressing more or less correctly the annual curve of precipitation, although usually underestimating precipitation totals.

- Baseline -GISS

ID

E

Jul Sep Nov

Fig. 8. lxCO2 precipitation scenarios for Estonia.

Correlations between the baseline scenario and IXCO2 scenarios of the rest of the GCMs are uniformly insufficient. CCCM overestimates precipitation by the biggest amount. Only summer rainfall is within realistic limits. GISS, GFD3 and GF01 results are evenly high in winter and low in summer. It is ridiculous that, according to GFD3 model, the driest month in Estonia should be August, although, in fact, it is the richest in rainfall. 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATION 43 AND CLIMATE SCENARIOS

GCM results were compared with the solar radiation data measured in TSravere station (58.3°N, 26.5°E). They are in good agreement (Fig.9). The highest correlation was obtained using the GISS model. It overestimates solar radiation in summer and underestimates in winter. GF01 results are also good but the model tends to overestimate solar radiation in summer. CCCM permanently overestimates and UK89 strongly underestimates it.

A comparison of GCM lxCO2 results with the baseline scenarios indicated significant differences. No one GCM describes current climatic conditions in Estonia with sufficient adequacy. The UK89 model results seem to correspond to the much more severe climate of higher latitudes. At the same time, CCCM results are typical of the warmer climate of lower latitudes. Taking into consideration all the three parameters, the GISS model seems to have the lowest total deviation. GFD3 and GF01 results are rather similar and have a number of disadvantages. All the GCMs available, are more or less of the same kind, and each model describes one meteorological value as being better than another. Consequently, they can be used for developing climate change scenarios in Estonia. Only the UK89 model is not suitable, because of excessively low estimates of winter temperature. GCM-based climate change scenarios were developed according to the baseline scenarios, adding the difference between 2xCC>2 and lxCC>2 scenarios (in the case of air temperature) or multiplying by the ratio between the 2xCO2 and 1 xCO2 scenarios (in the case of precipitation and solar radiation). These adjustment statistics for Estonia are given in Tables 2-5. Annual curves of monthly mean air temperatures by use of different 2xCO2 scenarios for Voru and S5rve are shown in Figs. 10 and 11. All the scenarios show an increase in temperature by approximately 3-6°C. As a rule, warming is expected to be higher during the colder half of the year. The CCCM and GFD3 models indicate a stronger increase and the GISS model a smaller increase in summer.

-Baseline -GISS

CM

Jan Mar May Jul Nov

Fig. 9. lxCO2 solar radiation scenarios for T5ravere. 44 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATIONS AND CLIMATE SCENARIOS

Table 2. Adjustment statistics for the difference between 2XCO2 and current (1XCO2) in Estonia generated by the GISS model

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Year Tem- per. 6.5 5.6 4.8 4.2 3.8 1.5 1.2 1.0 3.4 3.6 5.2 5.5 3.9 Prec. ratio 1.18 1.37 1.35 1.48 1.45 1.07 1.88 1.43 1.27 1.32 1.28 1.13 1.35

Table 3. Adjustment statistics for the difference between 2XCO2 and current (1XCO2) in Estonia generated by the CCCM model

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Year Tem- per 6.5 6.4 5.8 4.9 3.1 3.0 3.1 3.3 2.9 3.3 2.9 3.9 4.1 Prec. ratio 1.12 1.33 1.39 1.42 1.09 1.00 0.79 1.20 0.97 1.14 1.29 1.39 1.18

Table 4. Adjustment statistics for the difference between 2XCO2 and current (IXCO2) in Estonia generated by the GFDL30 model

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Year Tem- per. 4.9 4.0 5.8 6.5 5.4 4.2 5.0 4.0 2.9 3.8 7.0 6.9 5.0 Prec. ratio 0.96 1.17 1.08 1.50 1.41 1.04 1.00 0.95 1.38 1.25 1.36 1.30 1.20

Table 5. Transient scenario, based on adjustment statistics from the GFDL transient general circulation model and daily weather data from 1961-1990

Fourth decade(2000) Seventh decade (2030) Tenth decade (2070) Temperatur Precip. ratio Temperatur Precip. ratio Temperatur Precip. ratio January 1.6 0.98 3.6 1.16 6.4 1.23 February 2.3 0.98 2.9 1.05 3.0 1.16 March 2.9 1.19 3.9 1.25 4.4 1.15 April 1.9 0.82 3.1 0.82 3.7 0.91 May 0.8 1.14 3.0 1.05 3.5 1.03 June -0.7 1.27 1.5 0.91 2.6 1.52 July •0.6 0.74 2.1 0.76 3.6 1.15 August 0.5 1.01 2.5 0.93 4.1 1.10 September 1.2 1.12 2.9 1.19 4.2 1.35 October 2.8 1.07 3.3 1.11 4.8 1.28 November 1.1 0.88 3.3 0.97 4.7 1.11 December 1.2 1.17 5.7 1.25 6.9 1.44 Annual 1.2 1.03 3.2 1.04 4.3 1.20 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATION 45 AND CLIMATE SCENARIOS

•Baseline -GISS GFD3 CCCM _ _*_ _ GF01

Jul Sep Nov

Fig. 10. 2xCO2 air temperature scenarios for Voru.

• Baseline -GISS

Jan Mar May Nov

Fig. 11. 2xCC>2 air temperature scenarios for S5rve.

Climate change scenarios for precipitation are highly variable (Fig. 12). In most cases, an increase in precipitation is expected. In some cases, it could be many times greater. The UK89 and GISS model results show the highest increase and CCCM and GFD3 the lowest one. Global circulation models indicate comparatively small changes in solar radiation in the case of a doubling concentration of greenhouse gases. Usually, 2xCO2 scenarios show solar radiation slightly smaller than in the baseline scenario (Fig. 13). As a conclusion, the data of climate change scenarios for doubled CO2 concentration are presented in Tables 6-9. 46 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATIONS AND CLIMATE SCENARIOS

• Baseline -GISS

Jan Mar May Jul Nov

Fig. 12. 2xCC>2 precipitation scenarios for Estonia.

•Baseline

-GISS

Jan Mar May Jul Nov

Fig. 13. 2xCC>2 solar radiation scenarios for Toravere. Table 6. Climate change scenarios for air temperature in Voru

Scenario Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Year

Baseline •7.1 •6.2 •2.0 4,6 11.5 15.6 16.9 15.7 10.9 6.0 0.5 •4.2 5.2

GISS •0.5 •0.2 2.7 8.9 15.4 16.8 18.0 16.8 14.5 9.5 6.0 1.2 9.1

GFD3 •2.5 •2.3 3.5 11.0 16.7 19.6 21.8 19.7 13.6 9.7 7.4 2.6 10.1 CCCM •0.6 0.8 4.7 9.9 14.2 18.3 19.9 19.0 13.7 9.2 3.5 -0.9 9.3

GF01 •0.6 •3.3 2.5 8.5 14.8 18.0 20.4 19.8 15.2 10.8 5.3 2.8 9.5

In addition to GCM-based climate change scenarios, incremental scenarios are also used in vulnerability assessment. They provide a wide range of potential regional climate changes in 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATION 47 AND CLIMATE SCENARIOS temperature and precipitation. In this study, a great number of incremental scenarios were used. Increases in air temperature by 2, 4 and 6°C have been combined with no change, and with ±10 and ±20 % changes in precipitation.

Table 7. Climate change scenarios for air temperature in Sorve

Scenario Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Year

Baseline -2.6 •3.4 •1.3 2.7 8.3 13.6 16.0 16.0 12.5 8.4 3.9 0.2 6.2 GISS 3.3 1.9 3.2 6.6 11.8 15.9 17.5 16.8 15.6 11.8 8.6 5.6 9.9 GFD3 2.1 0.8 4.1 8.9 13.8 18.2 20.9 19.7 15.6 12.2 10.2 6.7 11.1 CCCM 1.1 0.4 2.5 6.6 12.0 17.1 19.5 19.5 15.8 11.7 7.0 3.6 9.7 GF01 3.6 0.0 3.2 6.1 11.5 15.9 19.6 20.2 16.3 13.2 8.4 6.7 10.4 UK89 4.1 3.1 5.8 10.0 14.2 18.3 20.5 20.4 16.5 13.6 9.2 6.1 11.8

Table 8. Climate change scenarios for spatial mean precipitation in Estonia

Scenario Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Year Baseline 4-1 30 33 36 42 56 79 83 77 67 65 54 663 GISS 48 41 45 53 60 61 149 116 97 89 84 61 904 GFD3 39 35 36 54 58 59 78 78 104 82 86 70 779 CCCM 46 41 46 50 46 55 63 100 75 77 84 76 759 GF01 52 35 37 32 42 86 88 93 103 86 71 79 804 UK89 90 62 61 65 45 74 124 90 92 97 83 97 980

Table 9. Climate change scenarios for solar radiation in T5ravere

Scenario Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Year Baseline 18 47 105 151 205 239 219 169 105 48 18 11 111 GISS 15 40 98 146 203 232 204 157 99 47 16 10 106 GFD3 19 4-7 94 118 191 256 228 176 103 45 11 8 108 CCCM 16 41 98 139 199 237 214 163 104 47 16 10 107 GF01 16 43 99 136 189 220 204 168 97 41 16 9 103 UK69 14 39 79 140 217 239 204 186 106 39 15 9 107

Conclusions 1. Weather conditions in Estonia are quite variable. Long-term periodical fluctuations have been observed in meteorological values. At the same time, the climate change during the last 100-150 years is marked. As a general tendency, the climate has become more maritime. Air pressure is characterized by an increasing trend in spring and summer, and by a decreasing trend in autumn and winter. Mean air temperature has increased, particularly over the colder half of the year. Precipitation area totals have risen, most of all in autumn and winter. Snow cover duration has decreased significantly. 2. GCM-based climate change scenarios expect a general increase in air temperature in Estonia with warming in winter more significant than that in summer. Moreover, they indicate an increase 48 5. CLIMATIC TRENDS IN ESTONIA DURING THE PERIOD OF INSTRUMENTAL OBSERVATIONS AND CLIMATE SCENARIOS in precipitation, but the results of the individual models are quite variable. The transient scenario shows that the main increase in precipitation will not occur during next decades, but only at the end of the transient period, around 2070. It can be stated that observed tendencies of climate change in Estonia concur with expected changes caused by global warming. 3. According to the long-term fluctuations of meteorological values in Estonia, changes different from general trends can take place during the next decade. An increase in mean air pressure, sunshine duration and snow cover duration, as well as a decrease in mean air temperature and precipitation is expected in the following years.

References Carter, T. R., Parry, M. L., Nishioka, S. & Harasawa, H. (1992). Preliminary guidelines for assessing impacts of climate change. Environmental Change Unit, Oxford, United Kingdom, and Center for Global Environmental Research, Tsukuba, Japan, 28 pp. Jaagus, J. (1992). Periodicity of precipitation in Estonia. Estonia. Man and Nature. Tallinn, pp. 43- 53. Robock, A., Turco, R. P., Harwell, M. A., Ackermann, T. P., Andressen, R., Chang, H. S. & Sivakumar, M. (1993). Use of general circulation model output in the creation of climate change scenarios for impact analysis. Climatic Change, 23, pp. 293-335. U.S. Country Studies Program. (1994). Guidance for vulnerability and adaptation assessments. Version 1.0, Washington D.C., U.S.A. EE9800005

13. ENERGY EFFICIENCY AND GREENHOUSE GASES 163_

13. ENERGY EFFICIENCY AND GREENHOUSE GASES

A. Hamburg1, A. Martins2, A. Pesur2 and I. Roos2 1 Ministry of Economy -11 Harju Str., EE0001, Tallinn, Estonia 2 Institute of Energy Research - 1 Paldiski Rd., EE0001, Tallinn, Estonia

Introduction The Government of Estonia has identified the development of infrastructure, which includes the energy sector as a strategy component in the movement towards a market economy. Estonia's domestic production of natural gas, oil and coal is unsubstantial. Those fuels are therefore imported. However, Estonia has substantial domestic primary fuel resources of oil shale, peat and forests as well as secondary fuel resources of shale oil and peat briquette. Estonia produces almost all of its electricity at two large oil shale power plants. The environmental effects are significant because of gaseous and solid pollutant emissions(mainly CO2, SO2, and fly ash). Furthermore, the social affect is marked due to the employment and demographic situation in particular regions. It is evident that Estonia will continue to use oil shale in future. This will contribute to the security of supply and will maintain independence of imported energy resources. Taking into consideration the present political and economic situation and Estonia's energy resources, the main targets of reducing greenhouse gases (GHG) emission in the energy sector are: * to improve the efficiency of oil shale power plants, by use of new combustion technology, better control and automation equipment; * to improve the efficiency of heat production in district heating boiler houses; * to substitute imported fuels, in particular, fuel oils, with domestic wood fuels and peat; * to reduce the heat losses in heat transmission, distribution and consumption.

Energy Balance Half a century, Estonia was part of the former Soviet Union. Power-intensive and large material- consuming industries were developed in Estonia. At the same time, very low prices of fuels did not stimulate their economical use. Such a situation did not encourage anyone to economize energy. After restoration of Estonia's independence in 1991, the exports of electrical energy and industrial products decreased substantially, in particular, to the eastern market. In free market conditions, fuels prices rose sharply. This process caused a decrease in production and consumption of energy nearly twice. 164 13. ENERGY EFFICIENCY AND GREENHOUSE GASES

450

400

350

300-

250

200-

150 ~*~ Primary energy supply 100 -*- Final energy consumption 50 +

1988 1989 1990 1991 1992 1993 1994 YEAR Fig. 1. Primary energy supply and final energy consumption in 1988 - 1994.

In 1990-1993, primary energy supply decreased from 416.613 PJ to 224.169 PJ and final energy consumption, respectively, from 213.436 PJ to 114.048 PJ (Table 1, Fig. 1) (Energy Balance, 1995).

Table 1. Energy production and consumption, PJ Year Primary Energy Resources Primary Energy Supply Final Energy Consumption 1988 535.273 411.698 211.263 1989 530.791 420.315 212.585 1990 520.663 416.613 213.436 1991 462.511 390.614 208.878 1992 337.241 277.302 136.873 1993 277.043 224.169 114.048 1994 306.213 238.720 114.931

In 1993, the decrease in energy supply and consumption stopped, and in 1994, a slight increase followed (Table 1, Fig. 1). In 1994, the production of primary energy was approximately 11% higher than in 1933. The 1994 fuel imports increased by 13% as compared to 1993. It was mainly due to the imports of natural gas (30%). 13. ENERGY EFFICIENCY AND GREENHOUSE GASES 165

Fuels

Domestic Fuels Oil shale is obtained from the Estonian and partly from the Leningrad field of the Baltic oil shale basin. In 1986, oil shale reserves in the Estonian field formed 4,200 million t, while commercial supplies were estimated at 1,200 million t. The total thickness of the payable bed in Estonia's field is 2.5 - 3.2 m, of which oil shale layers account for 1.8 - 2.6 m, the other ones are limestone interlayers ( State Energy Department, 1992). The dry matter of Estonian oil shale consists of three main parts: organic, sandy-clay and carbonate. Estonian oil shale as fuel is characterized by a high ash content (45 - 50%), a moderate constant of moisture (11 - 13%) and that of sulphur (1.4 - 1.8%), a low net caloric value (8.5 - 9 MJ), and a high content of volatile matter in the combustible part (up to 90%). Oil shale is mined from three open pits (50%) and from six underground mines. In 1990, 22.5 million tons of oil shale were produced and in 1994 - 14.53 million tons (Energy Balance, 1995). Oil shale is produced in two qualities: with the grain size of 0-25 mm and 25-125 mm. The enriched lumpy oil shale (25 - 125 mm) with calorific value 11-13 MJ/kg is used in the oil shale industry to produce oil shale oil and as fuel in cement kilns. 80% of the minable oil shale (grain size 0-25 mm) with calorific value of 8.5-9 MJ/kg is suitable as boiler fuel in large power plants. Net calorific value of oil shale is changeable, showing a decreasing tendency, because best quality oil shale layers are mostly exhausted already. Oil shale mining and burning place severe strains on the environment, giving 80% of total harmful emissions in Estonia. The impact of oil shale mining on ground surface depends on the type of mining, either opencast or underground, and on the mining methods. Oil shale mining and handling is a source of methane emissions. As GHG emissions regard, it is important that during combustion of pulverized oil shale, CO2 forms not only as a burning product of organic carbon, but also as a decomposition product of fuel mineral part. But obviously Estonia has to produce oil shale-based power and heat as long as it is economically, technically and environmentally viable. It is because oil shale is an Estonian indigenous fuel and technologies from mining to power production and processing are available. Oil shale mining, power production and processing provides occupation to thousands of people. The crude oil shale oil is produced by the State Enterprise Kiviter (former Oil Shale Chemistry Enterprise at Kohtla-Jarve and the Kivi51i Oil Shale Chemical Integrated Plant) in internal combustion vertical retorts and by the Estonian Power Plant in solid heat carrier retorting units. In 1994, 301,000 t of oil shale oil was produced (Energy Balance, 1995). The crude oil shale oil has a low solidification point (-10°C) and a moderate sulphur content, S < 0.8%. The density of crude oil shale oil at 20°C is 1.00t/m3, and ash residue content is below 0.3%. The calorific value of shale oil is 40 MJ/kg. Crude oil shale oil is used as a fuel in medium and small boilers. In critical situations, with lack or shortage of heavy oil, oil shale oil has been and will be the best fuel to replace imported fuel oils or natural gas. Approximately 22% of Estonia's territory is covered by peatlands. The resources of peat for heating are estimated at 2,646 PJ (at moisture 40%) and production capacity is 58.49 PJ (IVL , 166 13. ENERGY EFFICIENCY AND GREENHOUSE GASES

1994; Biomass Tech., 1995). In 1994, the primary energy supply from peat was 4.29 PJ (Energy Balance, 1995). Peat is used as peat briquette, pressed peat, and sod peat. Peat briquette is mostly used in households. Pressed peat and the recent sod peat are burned in boilers of central heating systems. The calorific value of peat briquette is approximately 17.3 MJ/kg, that of pressed peat 12.6 MJ/kg (at 30% moisture), and that of sod peat 8.9 MJ/kg (at 45% moisture).

It is estimated that some 48% of Estonia's territory is covered by forests. As wood has become one of the most important Estonia's export article today, it will be beneficial for forestry enterprises to use wood for energy production and for wood-chip sales. Wood chips are used in local boiler houses. The calorific value of wood is 11.5 MJ/kg (at 30% moisture). It is estimated that 22 - 35 PJ of wood fuel could be used annually in Estonia (Biomass Tech., 1995). In 1994, wood fuel use formed 12 PJ (Energy Balance, 1995).

Imported Fuels Among imported fuels, the share of heavy fuel oil (HFO) is the largest. HFO and light fuel oil (LFO) have been imported mostly by rail from Russia. From overloading places (Tallinn, Tartu, Parnu, Voru, Narva and Kohtla-Jarve), HFO and LFO are transported by trucks to boiler houses in towns and settlements. In 1994, 26.049 PJ of HFO and 2.069 PJ of LFO were used (Energy Balance, 1995). At present, natural gas is imported to Estonia only from Russia. The length of pipelines for gas transport is 2,139 km, that of transmission pipelines 930 km and that of distribution systems 1,209 km. The 1994 consumption of natural gas 1994 was 21.387 PJ (Energy Balance, 1995). Natural gas is best for boilers of district heating boiler houses and central heating power plants as well as for condensing power plants. Natural gas-based gas turbine or gas-combined cycle technologies can provide for small-town heating through high efficiency heat and power co- generation. To achieve wider availability and to loosen the dependence on Russian gas supplies, Estonia and other Baltic states (Latvia and Lithuania) have to collaborate in the studies of a possible interconnection to the Polish gas system. Further-more, the possible use of Latvian gas storage will increase the reliability of gas supplies. Norway-based pipeline projects appear in feasible within the considered period ( PHARE , 1995). In Estonia, coal is used in small boilers up to 1 MW, where fuel handling and ash removal is performed manually (Statistical Yearbook, 1992). Over the recent years, coal was imported to Estonia from Poland (Silesian coal) and from Russia. In 1994, 2.2 PJ of coal was used (Energy Balance, 1995). If oil shale price exceeds that of coal, large power plants could be refurbished to burn coal instead of oil shale. To burn coal with oil shale, using circulating fluidized bed (CFB) technology, would solve both burning and environmental problems for large oil shale-fired power plants. The motor fuels (gasoline, diesel oil, and jet kerosene) are imported chiefly from Russia. However, small quantities come from Lithuania, Finland, Byelorussia, Kazakhstan, Azerbaijan, Norway, and Sweden. Estonian road, railway, air and water transport is completely dependent on imported motor fuels. In 1994, motor fuels consumption was at 29.197 TJ, thus exceeding that of 1992 by 2.38 TJ. 13. ENERGY EFFICIENCY AND GREENHOUSE GASES 167

Other solid fuels 8%

Motor fuels 12%

Oil shale 59%

Fuel oils 13%

Fig. 2. Consumption by kinds of fuel in 1994, % of PJ.

Among the fuels described above, oil shale is the most important fuel for Estonia. In 1994, 151.7 PJ of oil shale was used, which forms 59% of the total fuel consumption (Fig. 2). The share of other fuels was: fuel oil - 13%, natural gas - 8% and other solid fuels - 8%. Oil shale is the main source of GHG emissions in Estonia. For oil shale burned in power plants, physical cleaning (enrichment) is not used. It means that limestone is not separated from oil shale. An important means of reducing CO2 emissions from limestone decomposition during oil shale combustion is separation of limestone particles from oil shale before burning. Another method of oil shale beneficiation is to use advanced mining technology, where oil shale layers and limestone interlayers are mined separately. Imported fuels are being substituted with domestic wood fuels and peat. This process can continue when efficient production and preparation technologies for domestic fuels have been established and implemented, and proper boiler types and combustion technologies have been selected. To reduce GHG emissions in combustion processes, it is crucial for the Ministry of Economy of the Republic of Estonia to elaborate the quality requirements for all fuels available and to implement the quality control and quality assurance systems in Estonia (Energy 2000, 1995). 168 13. ENERGY EFFICIENCY AND GREENHOUSE GASES Power Plants Two large power plants fired by oil shale: the Baltic Power Plant and the Estonian Power Plant are located near Narva (Table 2) (Energy Master Plan ..., 1992/93). These plants produce over 95% of total electricity consumption in Estonia. The efficiency of the Baltic Power Plant is 27% and that of the Estonian Power Plant forms 29%. The efficiencies of the Kohtla-Jarve and the Ahtme CHP Plants are 25 - 28%. The efficiency of conventional pulverized coal-fired power plants is about 33% and that of advanced pulverized coal-fired power plants is about 38% (Sathaye & Mayers, 1995). The aim is to achieve an approximate efficiency of 40%. The higher efficiency of a power plant corresponds to lower CO2 emissions per MWh electricity generated. A comparison of the efficiencies of oil shale-fired power plants with those of conventional and advanced coal-fired power plants shows that CO2 emissions per MWh electricity generated in oil shale-fired power plants are much higher than those in coal-fired power plants. Low efficiency of oil shale-fired power plants can be explained by the peculiarities of burned oil shale (such as high ash content, low net caloric value), but the main reason is that oil shale power plants are technically backward. The Estonian Power Plant is over twenty and the Baltic Power Plant thirty years old. The Kohtla-Jarve and the Ahtme CHP Plants were built in the 1940s and the 1950s.

Table 2. Largest power plants in Estonia

Name of Power Plant Real Capacity, UW, Heat Capacity, MW,h Efficiency, % Fuel Estonian Power Plant 1,610 84 29 Oil shale Baltic Power Plant 1,390 686 27 Oil shale Iru CHP Plant 190 749 49 HFO, natural gas Kohtla-Jarve CHP Plant 39 534 28 Oil shale, HFO Ahtme CHP Plant 20 338 25 Oil shale Ulemiste CHP Plant 11 278 68 Natural gas, HFO TOTAL: 3,260 2,669

Each year, millions of tons of alkaline ash containing several microelements are disposed of from the power plants to ash fields. Ash fields now cover surrounding areas of about 2,000 hectare, over 200 million t of ash having been disposed of there. To restructure the power plants in Narva, the State Enterprise (SE) Eesti Energia has planned several activities. Among the main aims established are: to increase the efficiency of power plants, to reduce the level of SO2 emissions to internationally acceptable values, to solve the ash removal problem. Theoretically, the molar Ca/S ratio of 8-10 in oil shale should be high enough for effective sulphur removal, but to the high temperature in pulverized combustion (PC) processes, the SO2 capture efficiency is low. In world practice, molar Ca/S ratio value 2-3 is enough in fuel for effective removal, in particular, using circulating fluidized bed (CFB) combustion technology. Therefore, SE Eesti Energia is planning to study the feasibility of using CFB combustion technology for oil shale instead of the PC technology. The largest energy companies (Lurgi, ABB, Ahlstrom) are engaged in this project (Refurbishment of Narva PP, 1995). 13. ENERGY EFFICIENCY AND GREENHOUSE GASES 169

The CFB combustion technology facilitates a substantial reduction of the decomposition rate of carbonates in the mineral part of oil shale, and that of CO2 content in flue gases of oil shale power plants.

Several other cheaper SO2 removal methods (wet gypsum process, semi-dry process, Ahlstrom scrubber) are being tested and studied for flue gas cleaning preserving pulverized combustion technology (Refurbishment .... , 1995). In this case, CO2 reduction in flue gases is insignificant.

Heat Production Heat is produced by power and co-generation plants in district heating boiler houses and industrial enterprises. Table 3 shows the number of boilers, capacity and generated heat for 1992-1994 (Energy Balance, 1995).

Table 3. Number of boilers, capacity and generated heat

Years 1992 1993 1991 Number of boilers at the end of the year 7,315 5,353 5,586 Total capacity, MW 11,777 11,449 11,810 Generated heat, PJ 46.79 33.53 33.14 The share of, % coal 6.3 4.9 4.2 oil shale 1.9 1.9 1.5 peat 1.2 1.5 2.4 wood 2.0 4.1 7.7 fuel oils 51.7 59.8 53.8 gaseous fuel 33.6 26.4 23.3 electric energy 1.2 1.0 1.3 other fuels 2.1 0.4 5.8

About 75% of district heating boilers are small with capacity up to 1 MW. Their total share in heat production was 20% in 1994. 80% of total heat was produced by hot water and steam boilers with capacities 2-116 MW. As the technical equipment is thirty years old, the boilers' efficiency is lower than stated on the manufacturer certificate, automation and control of burning process are non-existent or fail. As a result, boilers' efficiency and availability are low, heat losses are high, and repairs are frequent. Heat production efficiency of oil shale-based boilers is 62 - 70%, 70 - 85% for plants and boiler houses operating on heavy fuel oil and natural gas, and 50 - 70% for boiler houses operating on coal (Energy Master Plan ..., 1992/93). The efficiency of wood- and peat-fired boilers is 65 - 80%. In the highly developed countries, the efficiency of boilers with the same capacity is 85 - 90% and more (Lampinen, 1991). The higher efficiency of boilers corresponds to the lower CO2 emissions per PJ heat produced. Replacement of all old-fashioned boilers needs time and investment. However, the efficiency of old boilers could be increased by furnishing them with elementary control equipment to optimize combustion regimes and carry out 170 13. ENERGY EFFICIENCY AND GREENHOUSE GASES necessary repairs. Based on our experience, in many cases, the efficiency of old boilers could be increased by 5 - 10%.

Heat Transmission, Distribution and Consumption District heating, well developed in Estonia, supplies most towns and small towns with heat and steam. The system is also well developed in the rural areas. The total length of heat pipelines is about 2,200 km (Energy Master Plan ..., 1992/93). More than 90% of all pipelines are underground encased in concrete channels and isolated with mineral wool and covered with laminated or non-laminated bitumen board. The average age of heat pipelines exceeds ten years, and their condition is bad because of insufficient repairing facilities. Heat losses in the networks are estimated at 6 - 12%, but total heat losses through leakages from the heat source to the consumer are considerably higher, forming up to 30%. For instance, in highly developed countries, power transmission and distribution systems generally have losses in the range of 5 - 10% (Sathaye & Mayers, 1995). To achieve a good technical level, modern preinsulated pipes with control and adjustment equipment must be installed in district heating systems. Over 60% of state-owned buildings are post-war apartment buildings, mainly five- or nine- storeyed prefabricated concrete block constructions with very thin insulation layers. Heat losses in these buildings are very high, for instance, because of poor-quality window design, low heat resistant outer walls, natural ventilation. Major repair work to improve the insulation has started. But as these projects are very expensive, they can cover only a fraction of the real need.

GHG Emissions from Energy Use Energy-related activities are the most significant contributor to Estonia's GHG emissions. Emissions from fossil fuel combustion contribute massively to these energy-related emissions with releases of CO2 from fossil fuel combustion. Activities related to the production, transmission, storage and distribution of fossil fuels also emit GHG. The main gas emitted through these activities is methane, while smaller quantities of non-methanous volatile organic compounds (NMVOCs), CO2 and CO can also be emitted. The emissions of these gases are much lower than those of CO2 . The amount of carbon in fuel varies significantly by fuel type. To estimate the GHG from energy activities, the IPCC methodology (Greenhouse ... Workbook, 1994, 1995) was used. Carbon emission factors (CEF) used for calculating CO2 emissions from energy sources are given in Table 4. Greenhouse Gas Inventory Workbooks (1994, 1995) do not contain information about Estonian oil shale and its carbon emission factor. Therefore a formula compiled by A.Martins for calculating the carbon emission factor of Estonian oil shale, taking into account the decomposition of its mineral carbonate part, is as follows: 13. ENERGY EFFICIENCY AND GREENHOUSE GASES 171

r r CEFoilshaie = 10 x [ C\ + kx ( CO2) M x 12 /44 ] / Q i , tC /TJ,

where Q' - net caloric value oil shale as it burned, MJ/kg;

C't - carbon content of oil shale as it burned, %; r (C02) M - mineral carbon dioxide content of oil shale as it burned, %; k - decomposition rate of ash carbon part ( k = 0.95 -1.0 for pulverized combustion of oil shale) (Kull & et. al., 1974).

Table 4. Carbon emission factors ( CEF )

Fuel CEF, tC/TJ Fuel CEF, tC/TJ Primary Fuels Primary Fuels Liquid Fossil Solid Fossil Crude Oil 20.0 Anthracite 26.8 Natural Gas Liquids 17.2 Coking Coal 25.8 Sub-Bituminous Coal 26.2 Secondary Fuels Lignite 27.6 Gasoline 19.9 Peat 28.9 Jet Kerosene 19.5 Oil Shale 29.1 Other Kerosene 19.6 Gas/Diesel Oil 20.2 Secondary Fuels/Products Residual Fuel Oil 21.1 BKB & Patent Fuel 25.8 LPG 17.2 Coke 29.5 Ethane 16.8 Bitumen 22.0 Lubricant 20.0 Petroleum Coke 27.5 Refinery Feedstocks 20.0 OtherOil 20.0 Gaseous Fossil Biomass Natural Gas (Dry) 15.3 Solid Biomass 29.9

Table 5 shows reference approach of CO2 emissions from energy sources for 1990 - 1994. Fuel wood burned one year but regrown the next year only recycles carbon (short carbon cycle). As a result, carbon dioxide emissions from biomass have been estimated separately from fossil fuel- based emissions and are not included in national totals. Since 1990, energy production and consumption have continuously declined up to 1993 because of the economic depression in Estonia (Statistical Yearbook, 1994). The result was a decrease in CO2 emissions (Table 5, Fig. 3). For instance, in 1990 total CO2 emissions from fossil fuel combustion were 37,183.8 Gg, but in 1993 - 20,214.8 Gg. Thus, during these years CO2 emissions from energy sources have decreased by 45.6% in Estonia. 172 13. ENERGY EFFICIENCY AND GREENHOUSE GASES

Table 5. C02 from energy sources, Gg

Fuel Types 1990 1991 1992 1993 199+ Fossil Fuels Total 37,183.8 36,342.2 27,453.3 20,656.1 21,412.6 Liquid Fossil Fuels 9,731+ 8,566.6 5,023.+ +,393.6 3,868.0 Natural Gas Liquids 95.6 91.9 40.4 21.7 30.4 Gasoline 1,688.4 1,417.3 681.4 694.6 858.1 Kerosene 419.8 262.7 68.8 157.6 147.2 Jet Kerosene 112.1 109.9 37.3 57.4 47.4 Diesel Oil 1,886.9 1,826.2 1,198.9 1,280.1 1,174.7 Heavy Fuel Oil 5,500.2 4,700.0 2,921.2 2,182.2 1,608.9 Other Oil 31.4 158.6 75.4 1.3 Solid Fossil Fuels 24,595.+ 24,908.6 20,753.5 15,4-29.4- 16,350.8 Oil Shale 23,051.4 23,011.7 19,347.8 14,855.0 15,867.0 Coal and Coke 890.3 872.8 544.4 187.6 96.4 Peat 653.7 1,024.1 861.3 386.8 387.4 Gaseous Fossil 2,854.0 2,867.0 1,676.+ 833.1 1,193.8 Natural Gas 2,854.0 2,867.0 1,676.4 833.1 1,193.8 Biomass Total 1,073.9 796.5 8+3.7 793.5 1,289.3 Solid Biomass (Wood) 1,073.9 796.5 843.7 793.5 1,289.3

In 1990 - 1993, the largest decrease occurred in the consumption of imported fuels. Therefore, CO2 emissions decreased for natural gas - 71%, kerosene - 60%, gasoline - 57%, heavy fuel oil - 64%. From oil shale, a 35% decrease of CO2 was observed. Over this period, the prices of fuels have increased very sharply. The price of natural gas has risen more than 700 times, heavy fuel oil about 450 times, gasoline and diesel oil 150 times within a year and a half. Peat and wood are not used on a large scale, though their prices have not increased so steeply as those of imported fuels. There was several reasons. It is impossible to burn wood and peat directly in oil- or gas-fired boilers. Reconstruction of old boilers and purchase of new ones needs investment, but loans are often unfavourable. Out-of-date equipment hinders the further expansion of peat fuel production. If modern equipment is introduced, the price of peat energy will rise. In 1993, the decrease in energy production and consumption stopped and in 1994, a moderate increase followed. The increase in energy production led to an increase in CO2 emissions (Table 5 and Fig.3). In 1994, the increase in CO2 was 5.6% higher than in 1993 (excl. CO2 from wood burning).

The relative parts of CO2 emissions from fuels burned in 1990, 1993 and 1994 are presented in Fig.4. The share of CO2 emission from oil shale burning is continuously increasing and that from liquid fossil fuels burning are decreasing. The share of CO2 emission from natural gas burning reached a minimum in 1993, but in 1994 it increased. Activities concerning the production, transmission, storage and distribution of fossil fuels also serve as sources of GHG. These are primary fugitive emissions from natural gas systems, oil shale mining and processing. The largest amount of non-CO2 emissions comes from the transport sector (Table 6). 13. ENERGY EFFICIENCY AND GREENHOUSE GASES 173

40000

15000 • Natural Gas Oil Shale; • Liquid Fossil Fuels 10000 • Coal, Peat, Coke 5000 • Oil Shale

0 1990 1991 1992 1993 1994 YEARS

Fig. 3. CO2 emissions from different energy sources

Table 6. CO2 and non-C02 emissions from energy use and transport, Gg

Sector CO, CH, N,0 NO, CO NMVOC Energy Conversion 28,4-61.0 0.047 0.002 35.780 7.329 NA Residential 1,588.7 0.4-61 0.4-25 3.043 0.969 NA Commercial 1,581.1 0.116 0.954 3.131 1.625 NA Industrial 2,897.5 0.051 NA 4.812 1.676 NA Transport 2,655.5 1.934 0.036 32.646 171.95 22.925 TOTAL 37,183.8 2.609 1.417 79.412 183.549 22.925 Note: The totals provided here do not reflect emissions from bunker fuels used in international transport activities NA - not available NMVOC - non-methanous volatile organic compounds 174 13. ENERGY EFFICIENCY AND GREENHOUSE GASES

80

70 --

1993 • 1994

Oil shale Liquid Fossil Fuel Natural Gas Coal, Peat, Coke FUELS

Fig. 4. The relative shares of CO2 emissions from fuels burned in 1990, 1993 and 1994

The prices of available fuels in Estonia do not reflect the environmental risks of these fuels. Figure 5 demonstrates the prices of fuels (Nov. 1995) and their carbon emission factors. The price of natural gas with CEF =15.3 tC/TJ was 185 EEK/MWh, and the price of oil shale with CEF = 29.1 tC/TJ was 34 EEK/MWh. CEF of oil shale is 1.9 times higher than that of natural gas, but the price of oil shale was 5.4 times lower than that of natural gas in 1995. This situation could be motivated by the origin of these fuels: natural gas is imported, but oil shale is a domestic fuel. Oil shale has high CEF resulting from decomposition of mineral carbon part of oil shale rock during the high temperature combustion. Without decomposition of mineral carbon part, oil shale could be qualified as a fuel with medium CEF (22 tC/TJ) (Fig. 5). As an extensive use of oil shale will continue, the reduction of oil shale CEF is very important. 13. ENERGY EFFICIENCY AND GREENHOUSE GASES 175

200 30

j| 180 Max. price S 3 Low price 25

2 160 (C E UJ UJ • CEF of oil shale without imposition of carbonat part

-; 140 -- offuels 20 FOR S ? 120 15 tC/T . CZO 100 LU 80 o 2 IISSIO N a. 10 LU a. 60

a 40 RBO N UJ -- 5 z O UJ 20

0 Natural Heavy fuel Coal Peat Wood Fire wood Peat Oil shale gas oil briquette waste FUELS

Figure 5. The prices of fuels (Nov. 1995) and their carbon emission factors.

Energy Development Plans in Estonia The main objectives for creating a new infrastructure in the energy sector are: * to establish laws regulating Estonian power engineering; * to favor local fuels use through tax and price policy; * to harness the program of oil shale mining and heat power production on the basis of oil shale; * to increase the possibilities of liquid fuels imports (terminals in the ports); * to identify and solve the strategic and technical issues of supply, distribution and use of gas in the Baltic states, particularly in Estonia; * to achieve the energy conservation by use of sophisticated commercialized technologies without imposing such curbs as of capital, labour force; * to apply administrative measure establishment of ownership forms and business of operating companies, and to guarantee the rights of the property owners; 176 13. ENERGY EFFICIENCY AND GREENHOUSE GASES

* to develop the standards, implement international agreements, and guarantee the implementation of the directives of EU. The main problems and goals of Estonian energy development are described in: 1. Energy Development Plan to 1995; 2. Energy Development Scenario to 2030; 3. Energy Master Plan for Estonia; 4. Energy Program "Energy 2000"; 5. Refurbishment of the Narva Power Plants and the Optimization of Oil Shale Mining in Estonia.

Conclusions Estonia's energy balance for 1990 - 1994 is characterized by the dramatic changes in the economy after regaining independence in 1991. In 1990 - 1993, primary energy supply decreased about 1.9 times. The reasons were a sharp decrease in exports of electric energy and industrial products, a steep increase in fuel prices and the transition from the planned to a market- oriented economy. Over the same period, the total amount of emitted GHG decreased about 45%. In 1993, the decrease in energy production and consumption stopped, and in 1994, a moderate increase occurred (about 6%), which is a proof stabilizing economy. Oil shale power engineering will remain the prevailing energy resource for the next 20 - 25 years. After stabilization, the use of oil shale will rise in Estonia's economy. Oil shale combustion in power plants will be the greatest source of GHG emissions in near future. The main problem is to decrease the share of CO2 emissions from the decomposition of carbonate part of oil shale. This can be done by separating limestone particles from oil shale before its burning by use of CFB combustion technology. Higher efficiency of oil shale power plants facilitates the reduction of CO2 emissions per generated MWh electricity considerably. In Estonia, heat is produced mainly on the basis of imported fuels (fuel oils and natural gas). But imported fuels are now being partly substituted by domestic wood fuels and peat. In district heating boiler houses, the boilers are over thirty years old and their efficiency is low. It is impossible to replace all old boilers for new ones because it needs time and investment. In a short term, the efficiency of old boilers could be increased by furnishing them with elementary control equipment for optimising combustion regimes and for facilitating necessary repairs. The reduction of heat losses in heat transmission, distribution and consumption spheres is crucial. The prognoses for the future development of power engineering depend essentially on the environmental requirements. Under the highly restricted development scenario, which includes strict limitations to emissions (CO2 , SO2 , thermal waste) and a severe penalty system, the competitiveness of nuclear power will increase. The conceptual steps taken by the Estonian energy management should be in compliance with those of neighboring countries, including the development programs of the other Baltic states. 13. ENERGY EFFICIENCY AND GREENHOUSE GASES 177 References Biomass Technology Group University of Twente (1995). Estonia: Utilisation of Wood and Peat for Heat Supply, pp. 517. Energy Balance 1994 (1995). Statistical Office of Estonia, Tallinn, pp. 48. Energy Master Plan for Estonia: Pre-Feasibility Study (1992/93). Ministry of Industry and Energetics, Vattenfall AB, Imatran Voima OY, State Enterprise Eesti Energia. Tallinn, pp. 119. Energy 2000 (1995) National Energy Research and Development Programme to Year 2000, Tallinn, pp. 25. Greenhouse Gas Inventory Workbook. Final Draft (1994). Vol. 2. IPCC, Washington D.C. Greenhouse Gas Inventory Workbook. Final Draft (1995). Vol. 2. IPCC, Washington D.C. IVL, Jaakko Poyry Consulting AB Sweden, Swedish Development Consulting Partners AB, Institute of Ecology, Institute of Energy Research (1994) Estonia: Sector Environmental Assessment on the Utilisation of Domestic Peat and Wood Chips as a Fuel for Heating Systems, Stockholm and Tallinn, pp. 318. IVO International LTD (1995), Operation, Repair, Maintenance and Conservation Plan for the Narva Power Plants, pp. 131. Kull, A., Mikk, I. & Ots, A. (1974). Heat Engineering, Tallinn, pp. 494 (in Estonian). Lampinen, K. (1991). Annual Report of LAKA 1992, Tampere, pp. 227 (in Finnish). PHARE Regional Programme (1995). Gas Interconnection Study, Executive Summary. Final Version, pp. 52. Refurbishment of the Narva Power Plants and Optimisation of Mining of Oil Shale in Estonia. Subproject: Investment Programme for Flue Gas Desulphurization (1995), SE Eesti Energia, Ministries of Estonia and Finland, Nordic Investment Bank, Tallinn, pp. 49. Sathaye, J. & Mayers, S. (1995). Greenhouse Gas Mitigation Assessment: A Guidebook, Dordrecht / Boston / London, pp. 203. State Energy Department (1994). Estonian Energy 1992, Tallinn, Estonia, pp. 46. Statistical Yearbook (1994). Statistical Office of Estonia, pp. 246. EE9800006

178 14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS

14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS

Inge Roos1 and Velio Selg2 'institute of Energy Research, I Paldiski Rd., EE001 Tallinn technical University, 116 Kopli Str., EE0017 Tallinn

Introduction In 1994, the amount of electricity produced in Estonia was 9.1 TWh (32.8 PJ). 28.22 TWh (101.6 PJ) of fuel energy was used og which 99% of the fuel was oil shale. In 1994, the share of oil shale was 60 % in the balance of primary energy, totalling 180 PJ (Statistical ..., 1995). Because oil shale is a domestic fuel, Estonia's national energy economy is based on it. However, oil shale resources are limited (according to expert estimates they can cover the main share of electricity demand approximately to the year 2025). The future vision of Estonia's energy economy is foreseen to be based on nuclear energy, and on a smaller scale, on the use of different renewable energy sources (Estonian ..., 1994). While the introduction of nuclear requires major investment, the long-term preliminary design, work and efforts for forming public opinion, promotion and development of different renewable energy potentials, as a rule, are affected by economic and ecological factors only. Among Estonia's most significant renewable energy sources are bioenergy, hydropower, solar and wind energy. Furthermore, peat is given a priority in the national fuel balance, but usually not considered a renewable energy source due to its prolonged rotation period.

Biomass energy Biomass can be divided mainly into three subgroups depending on origin: natural, man-made and animal biomass. Estonia's natural biomass resources include wood and residues of agricultural crops. The total area of forest land in Estonia is approximately 2.02 Mha, which accounts for about 48 % of the total area. The total volume of growing wood stock in Estonia's forests is about 350 Mm3, while in the recent years, the annual cut was about 3-3.5 Mm3. In addition to productive forest land, bushland on the former fields cover 200-300 thousand ha, where 1-1.5 Mm3 of firewood could be supplied. About one third of the harvested wood is used as firewood, the remaining two thirds is processed in the woodworking industry (Estonian Energy, 1992, 1994). Table 1 (Fig. 1) shows the use of wood and waste wood in 1980-1994 (Estonian Statistical Office (ESO)). 14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS 179

1600 U Fuel wood 14004V ^Wood chips o 1200

|5 1000 o T3 800-

C 03 3 o

1980 1985 1990 1993 1994

Fig. 1. Firewood consumption in Estonia 1980 - 1994, th m

Table 1. The used biomass resource

1980 1985 1990 1993 1994 Firewood, thrrTs 544.7 804.2 894.9 804.2 1413.7 (PJ) 4.2 6.2 6.9 6.2 10.9 Wood chips,th mas 171.6 249.6 K0.4 171.6 280.8 (PJ) 1.1 1.6 0.9 1.1 1.8

The total growing stock gives 66-75% of wood; branches, stumps and bark or the so-called logging residues form 25-33%. About 35-40% of timber becomes the residue of the wood industry (bark, saw dust, and shavings) (Kiipsaar, et. al., 1992). In 1994, the harvesting totalled 3.62 Mm3 (Statistical..., 1995), including 1.4 Mm3 of firewood, i.e., 39% of the total harvesting; and 0.28 Mm3 for processing into wood chips, i.e., about 10% of the wood waste (Table 1). 180 14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS

Animal biomass On January 1,1995 domestic animals in Estonia totalled (in the heads) cattle: 477.0, cows 280.7, sheep 139.9, horses 8.6, hogs 960.0, and poultry 6.536 t(Statistical Yearbook, 1995). Annually, 10- 12 t of manure is produced per animal unit. One animal unit means, respectively: 1 milk cow, 1.8 heads of young cattle, 5 calves, 6.7 hogs, 250 hens, 1 horse or 8.5 sheep. Considering the amount of biogas that can be produced from one ton of manure (it differs for different animal species) and the methane content in the produced biogas, the resource of animal biomass for Estonia was 4.07 PJ in 1995 (Table 2).

Table 2. Resource of animal biomass in Estonia in 1995

Domestic Numberof Production ofmanure, Biogas from the manure, Bioenergy resource, animals animals, th heads animal/yr m'/t PJ Cattle 215.8 5.6- 6.7 20.8 1.53 Cows 218.9 10- 12 20.8 1.56 Hogs 466.7 1.6-2.0 2.4 0.5 Poultry 3400.0 0.04- 0.048 57.7 0.48 Total 4.07

Table 2 shows the results calculated for the biomass with a methane content of 65% and a conversion factor 15 MJ/m3 (Pachel, 1993). The obtained total bioenergy resource is less than the real one, since horses, and sheep have not been included because there is no data on the amount of biogas that could be produced from one ton of horse or sheep manure. In Estonia manure-based biogas is processed in two enterprises:, the Parnu Seavabrik Ltd Parnu County and, Linnamae Peekon Ltd Laane County. Both firms use hog manure, and the obtained biogas is used in the local boiler house for heat production. The designed capacity of the biogas plant of the Parnu Seavabrik Ltd is 6,210 m3 with the meanly biogas content of 60%. At present, the capacity of the hog farm is 60%; the number of hogs is 17,000 and the daily output of biogas amounts to 3,500 m3. The thermal energy produced on the basis of this amount of biogas was about 6 TWh in 1994.

Waste Currently, most of the organic waste is stored in landfills, with the total quantity is estimated at 250- 300. Each year, 400 to 500 thousand tons of organic waste are delivered there. Municipal waste is not incinerated in Estonia, and only small amounts of oil product residues are burnt. A treatment system for hazardous waste is under construction, where oil and solvent residues will be incinerated. 14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS 181

Table 3. Origination, utilization and storage of organic waste, th t

Generation Utilization Deposition 1993 1994 1993 1994 1993 1994 Waste of animal and 574.6 628.9 551.8 609.9 41.9 36.2 vegetable origin Domestic waste" 308.9 694.1 122.2 113.4 344.6 579.9 Total: 883.5 1323.0 674.0 723.3 386.5 616.1 * Domestic waste is a mixed waste generated by households, enterprises and hospitals, as well as by water purification waste and sewage.

As Table 3 shows, in 1994, 1.32 Mt of organic waste was produced: 0.72 Mt was utilized, and 0.62 Mt was stored in landfills. If we could incinerate the combustible part of total domestic and industrial waste, then, according to Swedish experience, we could produce about 1.2 TWh of thermal energy per year. In Sweden, where waste incineration technology is used extensively, in 1994, about 3 TWh of heat energy were produced from 1.4 Mt of waste. (Statistical ...,1995). An alternative is to collect landfill gas and its combustion. By depositing waste in the natural environment-storage and burials-their organic decomposition will occur over time, resulting in the emergence of carbon dioxide and water, nitrous oxide and sulphur oxide and other gaseous compounds. With regard to environmental pollution, the anaerobic decomposition of waste by the limited access of oxygen, where one of the predominant released components is gaseous methane, is most unfavourable. In landfills, the self-ignition of methane may occur, resulting in fires and releasing toxic gases, such as dioxines and chlororganic compounds. On the other hand, methane has high greenhouse effect potential. At the end of 1994, at the Pa'askiila refuse dump in Tallinn, the largest dump in Estonia (2.5 Mm3), an environmentally sound project for collecting biogas and generating thermal energy from it was launched. This methane-based gas (with a methane content of about 50-60%), which earlier volatilized simply in the atmosphere, is now collected by special collector-pipes installed in the landfill at different levels. The compressors suck the gas out of the system and compress it. Further, the compressed hot gas is cooled and directed along pipelines to boiler plants for combustion. The designed productivity of this facility is 1,000 nnvVh, which corresponds to 5 MWh of energy. Biogas is an excellent fuel, and the flue gases from its burning are not as hazardous as the biogas itself. If it were possible to collect all the biogas from the decomposition of organic waste (0.6 Mt of organic waste was deposited in the landfill each year), we could produce about 40 GWh of energy per year on this basis.

Hydropower Estonia has 7,378 rivers and streams, but most of them are short and low-discharged. Only 420 rivers are longer than 10 km and 10 rivers are longer than 100 km (Pachel, 1993) (Table 4). Most of the rivers have a low-medium slope, and thus no large hydropower plants can be built on them. But several rivers can be harnessed for building mini- or micro-hydropower plants (MHPP). The total hydropower potential of Estonia's rivers is about 200 MW, accounting for only 1-2% of the total 182 14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS capacity of Estonian power plants. But, still, the implementation of this capacity would facilitate generation of 0.2-0.7 TWh of electrical energy (Raesaar, 1994).

Table 4. Major rivers in Estonia

River Length, km F, Profile, Hq, km' m m'/s m"/s l/s km1 1. The catchment area of Lake Peipsi Narva 77 56200 30 399 114 7.1 Piusa 109 796 208 5.8 1.85 7.3 Vohandu 162 1420 98 10.3 2.44 7.3 Suur-Emajogi 100 9740 4 70.1 17.9 7.2 Pedja 122 2710 67 25.4 3.04 9.3 Poltsamaa 135 1310 71 13.4 2.35 10.2 Ahja 95 1070 87 7.1 2.35 6.6 Amme 59 501 53 3.8 0.12 7.6 Vaike-Emajogi 83 1380 81 11.5 1.9 8.3 Ohne 94 573 63 4.5 0.6 7.9 2. The catchment area of the Gulf of Finland Purtse 51 810 77 6.6 0.48 8.1 Kunda 64 530 90 6 1 11.3 Loobu 62 308 93 2.9 0.39 9.4 Valgejogi 85 453 107 3.9 0.7 12.8 Jagala 97 1570 82 12.2 1.34 7.8 Soodla 46 236 62 2.3 0.32 9.7 Joelahtme 46 321 54 2.4 0.06 7.6 Pirita 105 799 75 7.8 0.51 9.8 Vain a 64 316 50 2.6 0.35 8.3 Keila 116 682 75 6.3 0.62 9.2 3. The catchment of the Vainameri and Livonian Gulf Kasari 112 3210 62 29.9 1.45 9.3 Vigala 95 1580 63 14.7 0.64 9.3 Velise 72 852 66 7.3 0.061 8.6 Parnu 144 6920 78 64.4 4.8 9.3 Navesti 100 3000 57 27.9 2.15 9.3 Halliste 86 1900 76 17.3 1.23 9.1 Sauga 77 570 60 5.1 0.045 9.0 Mustjogi 84 1820 30 14.4 2.82 7.9

In 1995, six mini-hydropower plants (with a capacity below 25 MW) with the installed total capacity of 925 kW and several private micro-hydropower plants with the capacity of some kW were operated in Estonia. Table 5 gives a survey of the working hydropower plants. 14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS 183

Table 5. Hydropower plants in Estonia in 1995

Plant Installed capacity, kW Yearof construction 1. Saesaare on the AhjaR. 2*0 1991 2. Leevaku on the Vohandu R. 195 1994 3. Kotka on the Valgejogi R. 180 1994- 4-. Poltsamaa on the Poltsamaa R. 60 194-5 -1950 5. Joaveski. on the Loobu R. 50 1945- 1950 6. Keila-Joa on the KeilaR. 200 1977 Total capacity: 925

The real capacity of the hydropower plants is somewhat lower, and, according to the Estonian Statistical Office, the total power generated by hydropower plants was 500 kW in 1994 (Energy Balance, 1995).The restoration of six more hydropower plants with a total expected capacity of 3.7 MW is planned.

Wind power Among Estonia's resources of renewable energy, wind power is most significant. However, several questions must be answered when assessing the possible use of this power. Among others, the most important are: are the wind resources sufficient, and is it economically justified to use wind energy? Will there be compatible local consumers in the locations where the wind energy presumably will be used? How can energy be stored or used in hybrid power systems for the changing wind speed? Can domestic industry and researchers be involved in the production of the necessary equipment? How expensive will the introduction of this type of energy be, and what will the production cost of wind energy be after its introduction? In order to make a valid assessment, all direct and indirect costs must be included by comparing different types of energy. Very often the problems are interrelated and need to be studied. It is evident that to introduce any new type of energy, supplementary expenses are required, and therefore thorough preparation and study of the influence of active processes and exterior factors are crucial. This assumes a national energy program, whereas at the initial period with the planning and funding of the studies should be supported from the state budget or respective foundations. Efficient legal procedures of the acts and regulations promoting the introduction of a new type of energy is also essential. For example, the projects of wind power, one of the most promising renewable energy sources in Estonia, have been successful when the manufacturers of the equipment and the energy producers have been provided with subsidies and exempted from the sales tax by the state during early operation. This was the practice in the USA, Denmark, Germany and in other countries which developed wind power technology.

Taking into account the natural conditions and the economic expediency, in the first years it pays to develop the capturing of wind power or wind power technology in those regions where the average annual wind speed at 10 m above the surface is 5 m/s, although the foreign experience shows that wind energy can be used efficiently in the areas with an average wind speed of 3.5 m/s or even lower (Wind...,1995). In the latter case the site of wind turbines must be carefully selected, and the height of the tower must be at least 40 to 50 m. For several years, the average wind speed at the Estonian western and northern coast and in particular on the islands has been over 5 m/s. The processing of meteorological data (SU Climate ..., 1966) shows that the highest wind speeds are at the western 184 14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS coast of Saaremaa and Hiiumaa, on Muhumaa, Vormsi and Kihnu islands and on thesmaller islands not-connected to the interconnected electrical network - Osmussaar, Ruhnu, Naissaar, Prangli. (Figure 2).

GULF OF FINLAND

6,0 m/s

Fig. 2. Perspective areas for wind energy use.

1 - Tahkuna, 2 - Prangli, 3 - Vormsi, 4 - Ruhnu, 5 - Vatta, 6 - Sorve, 7 - Undva, 8 - Muhu, 9 - Naissaar, 10 - Kihnu

Wind speeds at the Estonian meteorological stations Considering the presumably high wind resources, in particular, on the islands and at the coast, detailed investigations should be carried out concerning the average wind speeds and the frequency of their occurrence. As a result, the best sites for installing wind turbines could be selected, and sufficient objective data on Estonia's potentials of wind power could be collected. In addition to the conventional wind speed measurements at 10 to 13 m above the surface taken at the meteorological stations, the wind speed, direction and frequency of occurrence according to wind classes at different heights should be measured in the special measuring towers at the sites of future wind plants. Such measurements are presently made on the island of Hiiumaa at Cape Kootsaare, on the islands of 14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS 185

Vormsi and Prangli, and on the Harilaid.The wind speed measurements taken earlier at the Estonian meteorological stations are not as reliable as those taken by modern equipment. In the past, low-precision equipment was common, the measurements were made infrequently, and self-recording facilities were not available. However, the results of the earlier long-term observations permit to state that on Estonia's islands, in particular, the wind conditions are good and suitable for the installment of wind power plants. Table 6 shows the wind speeds of energy-producing value recorded at the meteorological stations on the Estonian islands and the results of data processing.

Table 6. Annual average wind speeds at the meteorological stations

Meteorological Heightofthe vane H, Average wind speed Calculated wind speed Calculated wind speed station ,m V,, m/s VH.,,,m/s ¥„„.„> m/s Tahkuna 13 6.4 6.1 7.3 Votmsi 11 5.6 5.5 6.6 Pakri 13 5.6 5.4 6.4 Naissaar 13 5.8 5.6 6.6 Kihnu 13 6.2 5.9 7.1 Ruhnu 12 5.8 5.6 6.7 Soru (Hiiumaa) 13 5.8 5.6 6.6 Kuressaare 13 5.9 5,7 6,7 Sorve saar 12 6.2 6.0 7.2 Raugi(Muhu) 13 5.3 5.1 6.1 Osmussaar 13 6.8 6.5 7.8 Vilsandi 13 6.5 6.2 7.4-

Table 6 shows the average readings of the annual average wind speeds Vo for the vane height Ho (SU Climate ...,1966) and the corrected annual average wind speeds VH=io and VH=3o, at the respective height from the ground of 10 and 30 m from 1945 to 1963. The first height (10 m) is generally recognized as the standard height for comparing wind speeds, the other (30 m) is the height of a usual middle class 100 to 250 kW rotor center. The correction of wind speeds was necessary in order to equalize the conditions by comparing the sites. It was calculated according to the formula

,0.16 VH=io= Vo x (10/Hof'" or VH=3o=Vo x (30/H0)'

The exponent 0.16 (Kleemann,. 1988) corresponds to a landscape with low obstacles (single trees or bushes), flat islands and coastal areas, which are the traditional sites of wind power plants and meteorological stations.

Assessment of production and resources The annual average wind speed alone cannot give a complete survey of the energy available. Our estimation of the resources of wind power was based on the frequency of wind speed occurrence at 186 14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS different observation stations in Estonia and on the dependence of the capacity of the modern Danish wind plant Vestas V27 rated at 225 kW on the wind speed (Technical..., 1989). The blade diameter of the wind turbine controlled by changing the adjustment angle of the blade was 27 meters. This facilitates operation at the wind speeds of 3 to 25 m/s. For resource estimates, wind speeds of 3.5 to 24 m/s were considered. Table 7 shows the amount of electricity produced by a wind mill and the resource of wind power per square kilometre. The latter is obtained by adding the output of 16 turbines and reducing the sum by 10%, which shows the stand-by of the equipment for maintenance. The resources have been assessed conservatively, since the wind speed has not been corrected for heights - the measurements were made at the height of 10 to 30 m, but the axis of the rotor is at the height of 30 m in the area of higher winds. In addition, 25 windmills can be installed on a square kilometre for normal separation (7 diameters of a blade), or 200 m from each other. The data is given separately for winter (October -March), summer (April-December) and the whole year.

Fig. 3. The first wind turbine GENVIND CV - 150 kW in Estonia, Hiiumaa, Cape Tahkuna.

Table 7 includes no data on the site of the first Estonian pilot wind plant at Cape Tahkuna, Hiiumaa (Fig. 3). The reason is the lack of data on the frequency of the occurrence of respective wind speeds (no initial data for calculations) in the initial source (SU Climate ..., 1966). But it included data on the average wind speeds, and according to this data, Tahkuna is one of the windiest places in Estonia (see Table 6). The calculated outputs show that the wind resources on the Estonian islands (coastal regions) are sufficiently high to wind power production. 14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS 187

Table 7. Estimated wind resources

Output of Vestas V27, MWh Wind Resource, GWh/km! Meteorological Winter Summer Yearly Winter Summer Yearly Station Kuressaare 277.7 209.6 487.2 3.998 3.018 7.016 Vilsandi 364.1 255.9 620.0 5.243 3.685 8.928 Sorve 329.8 215.9 545.7 4.749 3.109 7.858 Rutinu 317.9 169.4 487.3 4.578 2.439 7.018 Ristna 254.3 140.1 394.4 3.662 2.018 5.680 Soru 267.4 189.8 457.2 3.850 2.733 6.583 Raugi 244.8 179.5 424.4 3.526 2.585 6.111 Osmussaar 422.8 249.8 672.6 6.089 3.597 9.686 Pakri 266.9 180.9 447.8 3.843 2.605 6.448 Naissaar 311.2 195.1 506.3 4.481 2.810 7.291

How and what type of wind turbines can be used in Estonia In terms of wind energy, small- and large-scale power engineering are distinguished. Large-scale power engineering covers wind power equipment rated at 100 kW and higher, used to produce electricity for the public electrical grid or independently (also in hybrid power systems), with a diesel generator to produce electricity and heat. Small power engineering covers low capacity equipment, mainly independent machines for the production of electricity or heat. However, in most cases, this differentiation is not significant. Four different approaches can be considered for the use of wind turbines: * wind plants with a unit power of 200 to 600 kW or more, consisting of several wind turbines could be operated as a single source of power for producing electricity to the public grid with the equipment owned by a shareholders' company, a municipal enterprise or a power network. The distribution network would pay an agreed price for the generated power, which should not be lower than 80-90% of the average sales tariff to provide normal conditions. * A private or a cooperative owner of a 75 to 250 kW wind turbine could supply electricity to the public grid throughout a year in the amount that satisfies the owner or exceeds his demand by using electrical heating in winter. The electricity distribution network would purchase the produced electricity at the price agreed (85-90% of the tariff of a small consumer is recommended) and would sell the demanded amount of electricity to the owner at a 100% tariff. * A 30-150 kW wind turbine could be used in a hybrid system with a diesel generator as a power plant for a local electrical network. The system would include a rectifier, a storage battery, an inverter for converting the direct current into the 50 kW alternating current and some additional components for the use of the generated alternating or direct current under high wind conditions. No special constraints limit the type of the wind turbine, since a direct current interface would be used. According to this circuit, the diesel power plants on the Estonian islands of Prangli and Ruhnu are planned for reconstruction. This system is suitable for the island of Naissaar too. 188 14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS

* An autonomous 3-30 kW small- or medium- size wind turbine could cover the heat load for electrical heating and, if necessary, for charging storage batteries or for any other purpose, such as sawing wood. Such use of wind energy would be typical of self-built windmills, but here the controllability and wind harnessing would not very efficient. The above options show the principal approaches to the implementation of wind energy in the near future. But the main interest of scientific investigations will be focused on the possible loading autonomous system, which facilitates the use of hydrogen as a fuel for diesel generators readjusted for this purpose. In principle, hydrogen could be added to the existing main of natural gas thus increasing the content of hydrogen in the gas. As a result of this application, the wind turbines installed at the north coast would operate in parallel with the electric network while producing hydrogen for the gas pipelines. Gas is fired in the power plants of major towns for starting gas turbines which combined cycles, primarily to cover the peak loads in Tallinn. To seek the possible implementations of such wind energy strategy, additional investigations are needed.

Solar energy In practice, solar energy is not used in Estonia. However, this does not imply that this resource could not be used in the future. The average actinometrical resource in Estonia is estimated at about 977 kWh/m2, which is sufficient as regards Estonia's geographical location. For example, in Denmark the corresponding figure is ca 1018 kWh/m2, but as compared to Denmark, the lowest average outdoor temperature essentially limits Estonia's use of solar energy. Considering the large-scale private house projects in Estonia, it seems reasonable to develop solar energy-based household hot water production. The so-called "passive" or architectural trends in the use of solar energy (for instance, closing balconies to make them weatherproof) could also be feasible under Estonia's conditions.

Conclusions Estonia's most promising resource of renewable energy is the natural biomass. In 1994 the use of wood and waste wood formed about 4.9% of the primary energy supply, the available resource will provide for a much higher share of biomass in the future primary energy supply, reaching 9 - 14%.Along with the biomass, wind energy can be considered the largest resource. On the western and northern coast of Estonia, in particular, on the islands, over several years, the average wind speed has been 5 m/s. Based on the assumption that the wind speed exceeds 6m/s in the area that forms ca 1.5% of the Estonian territory (the total area of Estonia is about 45,000 km2) and is 5 - 6 m/s on about 15% of the total area, using 0.5 MW/km2 for the installation density, very approximate estimates permit to state that the maximum hypothetical installed capacity could be 3750 MW. It might be useful to make use of the current maximum 50 MW, which could enable the generation of approximately 70 - 100 GWh of energy per year.Although the solar energy currently has no practical use in Estonia and the resource of hydropower is also insignificant (only ca 1% of the electricity consumption), these two resources of renewable energy hold future promise in view of the use of local resources and that of environmental protection. It is not reasonable to regard renewable energy sources as a substitute for the traditional oil shale-based power engineering in Estonia. But, to some extent, local energy demand can be covered by renewable energy sources. Thus, they can contribute to the reduction of the greenhouse gases emissions in Estonia. 14. POTENTIAL UTILIZATION OF RENEWABLE ENERGY SOURCES AND THE RELATED PROBLEMS 189 References Energy Balance 1994 (1995). Statistical Office of Estonia, Tallinn, 48 p. Estonian Energy 1992 (1994). Estonian State Energy Department, Tallinn, 46p. Kleemann, M., (1988). Regenerating Energy Waves. Springer-Verlag, 264 p. (In German). Kiipsaar, O., Koppel, A., Kiippas, A., Lugus, O., Paist, A., Poobus, A., Reiska, R. & Viik, J. (1992). Opportunities for Using of Biomass in Estonia. Tallinn Technical University, Tallinn, 67p. (In Estonian). Pachel, K. (1993). The State of Rivers.In: Environmental Report 7, Water Pollution and Quality in Estonia. Environmental Data Centre, National Board of Waters and the Environment, Helsinki, 79 p. (In Estonian). Raesaar, P. (1994). About the Problems of the Estonian Hydroenergy Development. Estonian State Energy Department, Information Bulletin No 8, 30 - 33. (in Estonian). Technical specifications: Vestas V27-225 kW. RIS0 (1989). The Test Station for Windmills. Measurement Summary No 6.1, 36 p. SU Climate Reference Book (1966). Part 3, Estonian SSR, Wind 4. Gidrometizdat, Leningrad, 79 p. (In Russian). Statistical Yearbook (1995). Statistical Office of Estonia, Tallinn, 282 p. The European Renewable Energy Study (1994). Country Report, Latvia 102 p. Wind Power Statistic, Wind Energy Magazine (1995). (Vol. 15), No 1, 16 p. (In German). EE9800007

190 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM

15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM

Olev Liik and Mart Landsberg Tallinn Technical University, Department of Electrical Power Engineering 82 Kopli Str., EE0004 Tallinn

Introduction After Estonia regained its independence, planning of energy policy became topical. Since 1989, several expert groups have worked on the urgent problems and developments of Estonia's power engineering (e.g., Eesti energeetika ..., 1990; Energy Master Plan, 1992/93). However, the researchers have not had powerful and sufficiently detailed mathematicals model capable of describing the energy sector as a whole and facilitating to study of different development strategies. Comprehensive energy system planning by mathematical modeling was accomplished in 1994. Then Tallinn Technical University acquired the MARKAL model (Fishbone & Abilock, 1981) from the Swedish National Board for Industrial and Technical Development (NUTEK). The authors of this paper took a training course at the Chalmers University of Technology, Goteborg, Sweden. First, this model facilitated data base building and conversion technology options study (mainly for electricity production) (Liik, 1995). The influence of air pollution constraints on energy system development was first investigated in 1995. At the end of 1995, under the U.S. Country Studies Program, a detailed analysis of future CO2 emissions and their reduction options began.

Model Description MARKAL (an acronym for market allocation) is a demand-driven multi-period linear programming model of a technical energy system concerned evenhandedly with supply- and demand-side options. It is a cost-minimizing energy-environment system planning model used to investigate mid- and long-term responses to different future technological options, emission limitations, and policy scenarios (Fishbone & Abilock, 1981; Fishbone et al., 1983; Kram, 1993). MARKAL was developed in the late 1970s jointly at Brookhaven National Laboratory (BNL), USA and Kernforschungsanlage-Jiilich (KFA), Germany, as part of a collaborative effort of seventeen nations under the auspices of the International Energy Agency (IEA). Today, the model is used worldwide and it is being further developed under the IEA Energy Technology Systems Analysis Programme (ETSAP). Figure 1 shows the model interfaces (Fishbone, et al., 1983). In Estonian applications, the total discounted net present cost of the energy system over the whole planning horizon has been an objective function. However, it can also be a weighted sum of this cost and the environmental emissions or security of energy supply (Kram, 1993). 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM 191

Energy Economy

Availabilities Capital of Resources requirements Technologies Economy and Limits on Useful Mining, Energy and Imports and World Demands Exports Society Trade Ecological effects Environment

Fig. 1. Interfaces of the MARKAL model.

Estonia has not yet run a hybrid MARKAL-MACRO model that combines "bottom-up" engineering model MARKAL and MACRO, a "top-down" single producer/consumer macroeconomic growth model (Manne & Wene, 1992).

Present Situation and Key Assumptions Economic Development Political and economic independence brought about drastic changes in Estonia's economy. These changes mean a transition from a highly centralized planned economy to a demand-driven and market-oriented economy, a sharp shift in the foreign trade orientation and a dramatic rise of fuel and raw material prices. As a result, in 1991-1993, Estonia's economy declined markedly. Revisions of the GDP data have been multiple, revealing discrepancies in different sources. However, these sources show that the drastic decline in economy stopped in 1993-94. Figure 2 illustrates annual growth in the GDP according to the Statistical Office of Estonia (Estonian Statistics Monthly No 1 (37) and No 10 (46), 1995). The 1995 GDP makes up 63.4% of that of 1989. Because of different accounting and monetary systems, before 1993, the evaluation of the GDP was complicated. Estonia carried out the currency reform on June 20, 1992, introducing the freely convertible Estonian Kroon (EEK) with the exchange rate at fixed 1 DEM = 8 EEK. The official exchange rate of EEK was set approximately three times lower than its purchasing power (Schipper, et al., 1994). The same source, based mainly on the World Bank reports, estimates the GDP for 1990, 1991 and 1992 at 6.6 billion, 5.9 billion and 4.4 billion, respectively (1990 US dollars). 192 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM

1990 1991 1992 1993 1994 1995

5T 3 0 •

% -5- -2,8 -6,5 -10- -8,6 -15 -13,6 -14,2

Fig. 2. Annual growth of GDP, %.

However, the Statistical Office of Estonia calculates the GDP value in EEK (Table 1). The official figure for 1993 was 21.918 billion EEK (Statistical Yearbook, 1995). However, taking into account the official exchange rate of EEK and neglecting its real purchasing power, GDP values in foreign currencies are much lower than in (Schipper, et al., 1994). During 1992-95, the total population has decreased from 1.56 to 1.5 million.

Table 1. The structure of Estonian GDP, 1993-1994

Economy sector 1993,% 1991,% Agriculture, forestry, fishing 10.0 9.2 Manufacturing 17.1 16.8 Fuels, energy and water supply 4.9 4.7 Construction 5.9 5.5 Trade 15.4 16.9 Transport, communications 11.2 9.0 Services, real estate 12.6 11.8 Education 5.1 5.0 Health and social care 2.3 3.0 Banking, insurance 2.6 2.8 Public administration 3.1 4.0 Taxes 11.3 13.5

Subsidies •1.5 •2.2

As compared to the previous year, in 1990, 1991, 1992, 1993, and 1994, average inflation was 84%, 249%, 1152%, 36%, and 47.7%, respectively (Energy Master Plan, 1992/93; Rajasalu, 1994; Statistical Yearbook, 1995). The inflation rate for 1995 was estimated to be approximately 29%. Estonia's energy sector is totally dependent on fossil fuels, its substantial part being imported. The mining and power generation equipment as well as heat production and energy networks are old and depricated, and the abatement equipment is poor or is absent. 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM 193

Estonia's domestic fuels are oil shale, peat and wood. All other fuels are imported, mainly from Russia. The share of domestic fuels in energy balance is approximately 60%. Real hydro-potential makes up less than 1 % of the present power generation capacity, whereas nuclear reactors are absent. Although the wind potential is quite substantial, in particular on islands, both technical and economical conditions for its utilization are non-existent today. Estonia's main fuel is oil shale: 99% of electricity generation and ca 25% of heat production is based on its combustion. Furthermore, it is used for shale-oil (synthetic crude oil) production (25 PJ in 1993) and as a raw material for the chemicals and the cement industry. Oil shale has an average calorific value of 8.7 MJ/kg, containing 45-50% of ash, 11-13% of moisture, 1.4-1.8% of sulphur and 0.3% of nitrogen (Energy Master Plan, 1992/93). Its carbon emission factor is 29.1 tC/TJ (Punning, et al., 1995). Oil shale is extracted from both underground mines (50%) and openpit quarries (50%). Nowadays the mines and quarries occupy ca 8% of Estonia's territory. An annual extraction was 31.3 Mt in 1980, 22.5 Mt in 1990, and 14.9 Mt in 1993. Part of oil shale is imported from Russia (16 PJ in 1993). Tables 2, 3 and 4 show primary energy resources, supply and final energy consumption (Eesti energiabilanss 1994; Energy Balance 1995).

Table 2. Estonia's primary energy resources, supply and final energy consumption

Category/Year 1990 1991 1992 1993 199+ Total resources 520.6 PJ 462.5 PJ 337.2 PJ 277.0 PJ 306.2 PJ Oil shale 54% 53% 63% 61 % 60% Fuel oil 18% 16% 11 % 14% 12% Motor fuels 11 % 11 % 8 % 11 % 12% Gas 10% 11 % 9 % 6% 7% Coal 2% 3% 3% 2% 2% Wood and peat 4% 4% 0 /o 6% 7% Electricity (hydrotimport) 1 % 2% 0 0 0 Share of domestic fuels 53% 52% 63% 62% 61 % Total supply 416.6 PJ 390.6 PJ 277.3 PJ 224.2 PJ 238.7 PJ Final consumption 213.4PJ 208.9 PJ 136.9 PJ 114.0 PJ 1K.9PJ 194 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM

Table 3. Primary energy use in 1993, %

Category Share in total resources, % Electricity generation 36.2 District heat production 19.9 Oil shale processing 9.0 Peat processing 0.8 Direct use of fuels 15.1 Non-energy use 1.1 Fuel losses 0.3 Export 3.4 Stockpiles K.2

Table 4. Structure of final energy consumption in 1993, PJ

Sector Electricity Heat Fuels TOTAL Industry 7.0 25.5 7.1 39.6 Construction 0.2 0.3 1.3 1.8 Agriculture 2.7 0.9 4.8 8.4 Transport 0.5 0.9 20.2 21.6 Households 3.9 16.5 17.2 37.6 Other economy 3.1 1.9 0.2 5.2 TOTAL 17.4 +5.9 50.8 1H.0 Losses 5.3 3.4 0.7

Key Assumptions MARKAL calculations, based on the accounting year of 1993, were planned for 45 years, divided into nine five-year periods. Table 5 illustrates the development of fuel prices during recent years (Energy Master Plan, 1992/93; Foreign Trade, 1994) and future price projections used in the MARKAL runs. Future price estimates were based on the Energy Master Plan (1992/93) and on the Swedish MARKAL data used in the Chalmers University of Technology. The 1990 and 1991 prices were converted from Soviet Roubles (SUR) to EEK (official exchange rate on June 20, 1992, 1 EEK = 10 SUR). Table 5. Import and producer prices of fuels, EEK/GJ

Fuel/Year 1990 1991 1992 1993 1998 2018 2033 Oil shale 0.117 0.169 2.22 4.41 10 15 20 Coal 0.186 0.328 9.17 13.35 20 27 30 Heavy fuel oil 0.144 0.253 17.86 18.54 30 58 65 Natural gas 0.067 0.158 13.0 29.75 35 50 55 Peat 8.7 30 Wood 0.192 0.239 7.26 8.7 30 Gasoline 0.361 1.05 43.78 50.46 70 115 130 Diesel oil 0.261 0.675 32.64 32.86 55 90 105 Approximate exchange rate 1 USD= 12 EEK 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM 195_

Two final energy demand growth scenarios were considered: increasing two-fold in fourty years and in twenty years. It was assumed that economic growth leads to significant energy conservation. An electricity consumption growth rate higher than that of heat and fuels was considered. Because new prognosis have not been publicized, the future energy demands, phase-out speed of existing capacity, and availability of new technologies are the estimates made by the authors. The early 1990s forecasts (Eesti energeetika..., 1990; Energy Master Plan, 1992/93), appear improper because since then Estonia's economy has changed drastically. Only this year, under an EU PHARE Programme project, work on Estonia's energy strategy can begin. Other key assumptions for MARKAL runs were: • long-term annual discount rate - 0.06; • no limits on fuel import and investment; • upper capacity bounds established for coal- and gas-fuelled power plants only in the scenarios with forced oil shale use; • electricity import restricted; • social and political constraints non-existent or scarcely considered in the scenarios with forced use of oil shale in power production; • no sizeable electricity exports in the future; • limit for annual wind power production is 10 PJ; • gradual elimination of so-called "commercial losses" in the electric network during fifteen years (presently ca 10% of production); • environmental constraints accounted as upper bounds on total emissions, taxes not considered.

Technological and Environmental Constraints Currently, Estonia's installed capacity of electricity generation exceeds the domestic winter peak load approximately two-fold. However, the oil shale power plants have been in operation for 23- 47 years, and their equipment appears next to the operation time limit. In the following ten or twenty years, these plants must be either reconstructed or closed (Table 6). They were designed to supply electricity to the north-west of the USSR, nearly neglecting environmental impact. During Soviet regime, approximately 50% of electricity was exported (Fig. 3). Heat is produced by cogeneration plants, boiler houses of district heating and enterprises, and small boilers of private houses. All towns, most small towns and villages have district heating networks, about 80% of apartments being connected to it (Energy Master Plan, 1992/93). Today, heat production capacity exceeds its demand about three times. 196 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM

Table 6. Electricity and heat production capacity

Plant Erected El. cap. Th. cap. Effi- Fuel MW MW ciency Eesti PP 1969-73 1610 84 29% oil shale BaltiPP 1959-66 1390 690 27% oil shale Iru PP 1981 - 190 460 49% oil, gas Kohtfa-Jarve PP 194-9-59 39 301 28% oil shale Ahtme PP 1951-56 20 102 25% oil shale Other power plants 64 138 oil, peat, diesel Boiler houses 11450 oil, gas, solids TOTAL 3313 13 225

70

60

50 /Net production 40 \ PJ / 30 / Consu np t ion ^^_^- ' +10!ses^ 20 .^ 10 / Grid losses . 0 _ 1945 1955 1965 1975 1985 1995 Year

Fig. 3. Electricity net production, consumption (incl. losses), and grid losses in 1945-1995.

The future electricity generation technology options are listed in Table 7. Such figures as investment costs, fixed and variable operation and maintenance costs, efficiencies were taken as European average values from (Kram, 1994) or from the Swedish data base.

Table 7. New generating capacity options

Planttype First year of availability Reconstruction of existing oil-shale plant 1998 New oil-shale power plant 2008 Coal fluidized bed (FB) 2008 Natural gas combined cycle 2008 Peak-load gas turbine 2003 Light water nuclear reactor 2023 Wind generator (land) 1998 Peat-fired cogeneration heat and power (CHP) 2003 CoalCHP 2003 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM 197

Air pollution data are presented in Table 7 (Energy Master Plan, 1992/93; Punning, et al., 1995; Estonian Energy, 1994). Today, CO2 is not considered as a pollutant in Estonia. According to international agreements, Estonia must reduce its SO2 emissions by 50% by 1997 and by 80% by 2005 from the 1980 level. The NOX emissions cannot exceed the 1987 level.

Table 7. Air pollution 1990-1992, thousands of tonnes. Year Solids SO, CO NO, CO, 1990 300 240 WO 74 37797 1991 278 232 390 60 33590 1992 130 177 125 30

CO2 Reduction Options The CO2 reduction options for Estonia are: • Energy conservation, more efficient appliances on the consumer side. The economically feasible energy conservation potential is estimated to be up to 50% of heat and 30% of electricity (Energy Master Plan, 1992/93). In MARKAL runs, conservation was taken into consideration by assuming low demand growth. • Change of fuels, especially reducing share of oil shale in electricity production. • New clean and efficient conversion technologies.

Result Description of CO2 Emission Scenarios

Development of CO2 Emissions by Different Scenarios Development of CO2 emissions was calculated for nine scenarios: 1. Scenarios with low final energy demand growth (doubling in 40 years): l.a. BASE - no emissions control,

1 .b. REF - reference case considering SO2 and NOX restrictions,

I.e. REF-40%CO2 - reference case + CO2 emissions not allowed to exceed 60% of 1990 level. 2. Scenarios with high energy demand growth (doubling in 20 years): 2.a. BASEH - no emissions control,

2.b. REFH - reference case considering SO2 and NOX restrictions,

2.c. REFH-20%CO2 - reference case + CO2 emissions not allowed to exceed the 80% of 1990 level. 198 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM

3. Scenarios with high energy demand growth and forced use of oil shale in power production: 3.a. OSH_B - no emissions control,

3.b. OSH_R - reference case considering SO2 and NOX restrictions,

3.c. OSH_RC - reference case + CO2 emissions not allowed to exceed 82% of the 1990 level.

Forced use of oil shale means that reconstruction of existing power generating capacity has lower bound and the corresponding upper bound is almost three times higher than in other scenarios. At the same time, upper bounds were put on the capacity of possible new coal and natural gas power plants. The results of model runs are shown in the Figs. 4, 5 and 6.

27

25 -- •••••BASE — REF -^-REF-40%CO2 23

Mt 21 --

15 1 1 —i—i—i—i—i— 1993 1998 2003 2008 2013 2018 2023 2028 2033 Year

Fig. 4. CO2 emissions under low energy demand growth.

•••••BASEH 45 - ——REFH •in - -^•REFH-2 0%CO2

35 - Mt •\ 30 - /i*^- * *

- \ 25 -

20 -

,r 1 1 1 \ 1 1 1 1 1 1988 1993 1998 2003 2008 2013 2018 2023 2028 2033 Year

Fig. 5. CO2 emissions under high energy demand growth. 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM 199

••-• OSH_B 45 - —OSH_R 40 -^•OSH_RC

35 - Mt 30

\ ••/ 25

20 -

- \^-^ 15 - 1988 1993 1998 2003 2008 2013 2018 2023 2028 2033 Year

Fig. 6. CO2 emissions under high energy demand growth and forced use of oil shale.

CO2 Reduction Costs Figure 7 illustrates increments in the total discounted system cost of all scenarios as compared to the BASE scenario (measured in 1993 GDP). The extra costs to reduce CO2 are not high because the old and inefficient oil shale power plants must be closed. Moreover, measures to reduce SO2 and NOX will also reduce CO2. Presently, approximately 50% of the 1990 level, CO2 reduction is caused by a reduced domestic energy demand and a sharp decrease of electricity exports. Expenditures for the scenarios with forced oil shale use are less than they should be. Factors related to highly extensive mining will raise oil shale price (such as opening of new mines, deeper mines, worsened quality of oil shale, environmental problems). Because no evaluations of the dependence of oil shale price on its amount extracted were publicly available, the same price forecast was used for all scenarios.

Marginal cost curves of CO2 reduction for different scenarios for 2018 are illustrated in Fig. 8. 200 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM

D ° 3 - CO

E. 2 - I 1 - wit h

o " I—I , I—I , —I— —I— '—1— X I CM LU U_ m a: o LU X O 1 I DC a. LU ti X X <^ a: LU o CO CO X CO It o O O CO CM o

Fig. 7. Increment in the total discounted system cost as compared to the BASE scenario and measured in 1993 GDP.

140 - - • - BASEH [ [ co 120 Q -•-OSH_B 100 - -x-0SH_R Q 1 LU CC CM O 80 - o j i j 60 - co O X _ . .* X BASE o 40 o a: 20 n - .,,--'-•'''7"/ ,.^^^^ 0 10 20 30 40 50 60 70 CO2 REDUCTION IN 2018 [% FROM 1990 LEVEL]

Fig. 8. Marginal cost of CO2 reduction in 2018.

Impacts of CO2 Reduction on the Development of Energy System Primary energy demand and fuel composition for the nine scenarios are presented in Figs. 9 and 10. As shown in the use of oil shale, coal and natural gas major differences exist. Nuclear energy will be used under every scenario considered here. Its share is significant in the case of high demand growth and emissions control. Wind power will be used only under the high demand growth and constrained CO2 emissions. 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM 201

Figures 11 and 12 show electricity production by fuel for all the scenarios. During 1993-2000 slow growth or even reduction in the total generation under constrained emissions is caused by a decreas in electricity exports as compared to the unconstrained cases. In 1993 electricity exports were 5.74 PJ (Energy Balance 1994, 1995). The upper limit of export was assumed to grow from this figure to 10 PJ in 2033. No electricity imports were allowed. An analysis of the new generating capacity based on (Eesti energiabilanss, 1993, 1994) and corresponding to the slow growth in demand can be found in (Liik, 1995). Results show that the construction of a new oil-shale power plant is not attractive under any scenario.

350 •MOTOR FUELS 300 nW00D 250 0 200 NUCLEAR PJ •PEAT 150 a -.— ^S^^^^BBBM^ FUELOIL 100 nGAS 50 •COAL

—»—i—i—r-—f—i—i—~ "OIL SHALE 1993 2003 2013 2023 2033 Years a) BASE

2033 1993 2033

b)REF c) REF-40%CO2

Fig. 9. Primary energy consumption under low growth in demand (including export of electricity and secondary fuels such as shale oil, coke and peat briquettes). 202 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM

1993 2033

1993 2013 2033 Years

500 . c) REFH-

1993

• Oil shale HCoal DGas • Fuel oil BPeat • Nuclear BHydro+Wind DWood • Motor fuels

Fig. 10. Primary energy consumption under high demand growth (including export of electricity and secondary fuels). 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM 203

1993 2033

180

1993 2033

180

2033 1993 2033

• Oil shale Coal DGas DON BPeat Nuclear •Hydro+Wind

Fig. 11. Electricity production by fuel under high demand growth. 204 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM

• Hydro+Wind SUNuclear • Peat PJ HOil • Gas • Coal El Oil shale

1993 2003 2013 2023 2033 Years

a) BASE

70 T-- 60 - 50- 40- PJ 30 -U- 20- 10 -

0 ,• 2DB3 1993 2003 2033

b)REF c) REF-40%CO2

Fig. 12. Electricity production by fuel under low demand growth.

Conclusions During 1990-1993, energy demand lowered due to economic decline and sharp rise in the fuel and energy prices as well as a decrease in electricity exports, has resulting in 50% reduction of CO2 emissions. For the same reasons, Estonia has been able to meet the requirements set in the agreements on SO2 and NOX emissions with no special measures or costs. To meet the rigiding SO2 restrictions and growing energy consumption in the future, Estonia must invest in abatement and in new clean and efficient oil-shale combustion technology. Along with the old oil-shale plants closing and electricity consumption growing, other fuels will be used. The increase in 15. SOME SCENARIOS OF CO2 EMISSIONS FROM THE ENERGY SYSTEM 205 energy demand then should not be fast due to constantly rising prices and efficient energy use. Measures to reduce SO2 and NOX emissions will also reduce CO2. In MARKAL runs the 1990 level of CO2 emissions will be exceeded only along with high demand growth and absence of emissions control. Restricted availability of imported fuels and nuclear power or enabling electricity import can change the results significantly. The results discussed here can also change because the data base is being improved (such as detailed description of energy networks, description of demand-side technologies, accounting of energy conservation measures, addition of new technology options).

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