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U.S. Department of State 
March 1995 Interim Report on Climate Change Country Studies 
Oceans and International Environmental & Scientific Affairs 
Editor's Note:  Numbers and letters contained withtin "<" and ">" marks 
    represent subtext in scientific formulas.  Numbers between 
    "/" and "/" represent footnotes.  Footnotes by the names of authors 
    are located just beneath the names.  Footnotes contained within the 
    text can be found at the end of each chapter. 
             Egypt: Inventory and Mitigation Options, 
            and Vulnerability and Adaptation Assessment 
           Dr. Mohamed El-Raey,/1/ Dr. Dia H.El-Quosy,/2/ 
    Dr. Mahmoud El-Shaer,/3/ Dr. Osama A.El Kholy,4 Eng. Ayat Soliman5  
/1/Dean, Institute of Graduate Studies & Research, Alexandria University 
/2/Director, Water Management Research Institute, National 
   Water Research Center 
/3/Professor & Head of Agron. Dept., Cairo University 
/4/Senior Advisor, Egyptian Environmental Affairs Agency 
   (Project Manager) 
/5/Assistant to Project Manager, Egyptian Environmental 
   Affairs Agency  
     SUMMARY: Egypt has been actively involved within United 
     Nations forums in the deliberations leading to the Framework 
     Convention on Climate Change, which it signed in Rio in 1992. 
     Egypt was one of ten countries that took the lead in 
     implementing item 1.a in Article 4 concerning the development of 
     a national inventory of anthropogenic emissions, as well as a 
     preliminary assessment of mitigating measures as called for by 
     item 1.b. This was undertaken within UNEP's project on the cost 
     of abatement of GHG with financial and technical support from 
     the Technical Research Centre of Finland (VTT). The study has 
     shown that a reduction of more than 40 percent of the CO<2> 
     emissions in the year 2020 could be achieved at negative 
     incremental costs. Egypt is now conducting a country study with 
     U.S. support that will prepare a "Framework for a national 
     action plan." 
In 1993 Egypt concluded a cooperative agreement with the 
USA within the framework of the U.S. Country Studies Program 
to investigate further the implications of the climate change 
issue for Egypt. The first phase of the study aims at preparing 
a "framework for a national action plan" to address the issues 
of climate change appropriate to Egypt. 
     There are several important reasons for Egypt to be involved 
in such studies. Climate change could have an extremely 
dramatic effect on the flow of the Nile, causing the 
displacement of millions of people in the Nile delta due to 
changes in food production and sea level rise. A significant 
rise in the average annual temperature could also have adverse 
consequences on the living conditions and health of millions of 
people in the country. 
Within the framework of UNEP's project on the Methodologies 
of Determining the Costs of Abatement of GHG emissions, a case 
study on Egypt was undertaken by the Egyptian Environmental 
Affairs Agency (EEAA) in cooperation with the Technical Research 
Centre of Finland (VTT) and the involvement of an expert team 
from different Egyptian organizations. 
     First, a comprehensive inventory for the year 1990 was 
prepared of all the GHG emissions mainly, but not exclusively, 
from energy activities. The results are summarized in Table 1. 
As the table shows, electricity generation, industry and 
transport sectors are the major producers of CO<2>, emitting a 
total of over 66 Mt annually. Rice paddies are, on the other 
hand, the main source of CH<4>. They are responsible for over 80 
percent of methane production in Egypt. Finally, Nitrogen-based 
fertilizers and road transport are the main sources of nitrous 
oxide. The different GHGs have different global warming 
potentials (GWPs). The corresponding distribution of GWPs of 
emissions for each sector is given in Figure 1. 
     The next and most important step was to establish, to the best 
of our present knowledge, a realistic scenario for the energy 
demand associated with the different economic sectors and that 
of the whole country. For supply options to satisfy these 
demands using available sources up to the year 2020. The energy 
consumption of the different sectors in the base scenario is 
shown in Figure 2. It should be noted that power production is 
treated here as a separate sector. When power generation, the 
largest energy consumer sector, is distributed among the other 
economic sectors, industry gets the predominant share, followed 
by the residential and commercial sectors. The primary energy 
supply by source is shown in Figure 3.  
     The corresponding GWPs of the GHG emissions are shown in 
Figure 4. The figure shows that the largest source of CO<2> is 
heavy industry, although its share of energy consumption is much 
less than that of the electricity production sector.  
Abatement Scenarios 
Two abatement scenarios were considered: the first (A1) was 
to decrease the GHG emissions in the year 2020 to 25 percent, 
and the second (A2) to 50 percent of their values in the year 
1990. In each of the economic sectors, a number of measures 
and/or technologies were considered for decreasing the GHG 
emissions. These technologies were based on one or more of the 
following techniques: 
--  Energy conservation 
--  Fuel substitution   
--  Use of renewables 
--  Material replacement 
--  Increasing GHG sinks 
A great deal of concentration was focused on energy 
conservation, particularly in the industry, power production, 
and transport sectors, as its potential and cost-effectiveness 
in these sectors were rather high. Fuel substitution was 
primarily limited to replacing coal and petroleum products by 
natural gas as far as natural gas reserves permit. Other 
measures included the use of renewable energy, which was applied 
mainly in the power production, household, and agriculture 
sectors. Material replacement was considered to decrease the 
dependency on present energy-intensive construction materials. 
The replacement of Nitrogen-based fertilizers by fertilizers 
from sludge/compost, and options to increase GHG sinks through 
tree and crop plantation were applied in the agricultural 
sector. A list of all the measures considered in both abatement 
scenarios is given in Table 2. 
     After adjusting a base scenario for economic and energy growth 
of Egypt for the business-as-usual alternative using results 
of several optimization processes undertaken earlier in Egypt, 
both the bottom-up or engineering models and the top-down 
or macroeconomic models were used. In the bottom-up approach 
several measures/technologies were considered in each of the 
economic sectors to decrease CO<2> emissions with respect to the 
base scenario. The cost curves of the different measures 
and technologies for the abatement of CO<2> are shown in Figure 5 
and Table 2, in which measures are arranged according to their 
costs. A considerable number of measures are cost-effective and 
have what are called "negative incremental costs." There might 
be hidden costs that are difficult to estimate at this stage, 
but the cost effectiveness of these actions is positive. 
     In the top-down approach the effects of energy 
conservation measures on the economy of the country (GDP, 
welfare, and investment) were studied using a macroeconomic 
model, with a horizon up to the year 2020. These measures were 
found to have a positive impact on the economy. 
Assuming that the base scenario selected was a fairly 
good forecast of the business-as-usual scenario for Egypt, it 
was found that Egypt has considerable potential for 
energy conservation measures that should start at once, in view 
of their cost-effectiveness, as verified in the bottom-up 
approach, and their positive impact on the economy of the 
country, confirmed in the top-down approach. 
Within the Egyptian Climate Change Country Study, three 
economic sectors of particular importance to Egypt were 
identified for the assessment of their vulnerability to climate 
change and the options available to adapt to the possible 
consequences of climate change. These sectors were: 
--  Water resources 
--  Agricultural resources 
--  Coastal zones and resources 
In the first phase of the study, a comprehensive 
literature review was undertaken to assess the gaps in 
information and uncertainties relating to the various sectors. 
In the following section, the findings for the three chosen 
sectors are presented. 
Water Resources 
Water supply in Egypt comes from three main sources: 
--  Surface water: The Nile River and seasonal flash floods 
--  Precipitation 
--  Ground water: in locations in the western and eastern 
    desert, the Sinai peninsula and Nile valley and delta 
The future climate changes for the Mediterranean region 
in general have been investigated (Wigley 1993). The 
results predicted a warming of about 3.5oC spreading uniformly 
over the seasons, with most of the Mediterranean basin showing 
an increase in precipitation in winter. The projected change in 
precipitation between now and 2050 is +1 mm/day. As for the Nile 
basin, we cannot yet predict with confidence the nature of 
future climatic changes. However, there are indications that 
such changes will be significant and possibly severe. Recent and 
predicted future precipitation changes over the Nile basin 
(Hulme 1989), and monitoring of the upper White Nile catchment, 
upper Blue Nile catchment, and Middle Nile Basin from 1880-1989 
show declines in total precipitation. Global circulation models 
(GCM) for 1861-1988 show an overall warming of 0.5oC for this 
period. Various GCM models have been applied to study the 
potential climate change impacts on the Nile Basin, as can be 
seen in Table 3 (Saleh et al. 1994). 
     A large gap still exists in our knowledge and information on 
the vulnerability of this crucial sector for Egypt. 
Recommended actions include enhancement of knowledge on 
climatological models, monitoring and forecasting, and 
implementing water management schemes to ensure water saving and 
Agricultural Resources 
In the first phase of the study, some of the effects of 
climate change on cropping patterns and distribution in Egypt 
were identified. Plant production is characterized in Egypt by 
two main features: diversification and intensification. In this 
way the agricultural year (Nov-Oct) includes monoculture 
(orchards or sugarcane), double cropping (winter - summer season 
crops), and triple cropping (winter - early summer - autumn 
crops). The outcome of all these patterns forms an 
intensification index of more than 2.0. With the expected 
changes in global climate, drastic changes in the whole system 
of cropping are likely to occur. Consequently, the focus will be 
on more adaptive types of crops and/or modifications in the 
microclimates to cope with the expected changes. New dates for 
planting crops of different species or cultivars need to be 
investigated. Advanced dates for planting summer crops and 
delayed dates for planting winter crops should also be tested. 
     Crop plants differ in their response to changes in CO<2> 
and temperature. Increases in CO<2> concentration increase the 
rate of plant growth. C3 plants respond positively to increased 
CO<2>, while C4 plants, although more efficient in utilizing 
current CO<2> levels, are less responsive to increased CO<2> 
concentrations. The most important C3 plants are wheat, rice, 
and soybean, while C4 plants include maize, sorghum, sugarcane, 
and millet. Computerized crop models (e.g., DSSAT, IBSNAT and 
ICASA) have indicated that, at the national level, differences 
in areas devoted to the above crops are likely to occur due to 
climate change. Growing more small grains (wheat and barley) is 
advisable rather than more coarse grains (maize and sorghum). 
Rice areas could be increased, but the problem of water shortage 
will be a limiting factor. 
    So far, there is very little information on the impacts 
of climate change on pests and their control, on livestock or 
on marine resources. This is a serious gap that calls for 
an extensive national effort. 
Coastal Zones and Resources 
Climate change is expected to have serious impacts over 
coastal regions all over the world. In particular, many 
investigators have warned against impacts on low-lying deltaic 
coasts, especially those in Egypt and Bengal. 
     The shoreline of Egypt extends for about 3000 km and could 
be divided into four distinct sectors: 
a.  The coasts of the western desert (west of the city of Alexandria) 
b.  The Nile River delta and vicinity between the cities of 
    Alexandria and Port-Said, including the coasts of the cities of 
    Rosetta and Damietta 
c.  The coastal zone of the Sinai Peninsula 
d.  The coastal zone of the Red Sea 
These coastal zones constitute a particularly important 
region from the economic, industrial, social and cultural points 
of view. In addition to increased tourism activities, a 
tremendous move towards building new industrial complexes is in 
progress at this time. However, the coastal zone suffers from a 
number of serious problems, including population growth, land 
subsidence, erosion, water logging, salt water intrusion, soil 
salination, ecosystem pollution and degradation, and lack of 
appropriate institutional management coordination. Realizing the 
importance of this zone, the Egyptian government has already 
taken steps towards reducing the impact of these problems. 
     Problems of the impact of sea level rise (SLR), due to 
climate change, on the Egyptian delta and adjacent areas have 
been taken particularly seriously. Several studies have been 
carried out to assess the vulnerability of this region (e.g., 
Broadus et al. 1986, 1993; Sestini 1987, 1992; El-Raey et al. 
1990, 1992, 1994; CRI and Delft 1993; Stanley et al. 1988, 1990, 
1993). As a result, areas of high vulnerability in the Nile 
delta and possible socioeconomic impacts have been generally 
defined. These areas include Alexandria and Behaira governorate, 
Port Said and Damietta governorates, and Suez governorates. In 
addition, several other smaller areas, such as those near Matruh 
and north of Lake Bardaweel, have also been identified. 
     A pilot quantitative assessment was carried out over 
Alexandria governorate (El-Raey et al. 1994). The main objective 
was to explore possibilities of use of remote sensing and GIS 
techniques to obtain a quantitative assessment of the 
vulnerability of each environmental sector to the impacts of 
SLR. Satellite images of the governorate were used to obtain 
information on land use in the coastal area and were 
supplemented by available ground survey data. A geographic 
information system (IDRISI software) was built and checked with 
information based on available ground data. A scenario of SLR of 
0.5 m, 1.0 m, and 2.0 m was assumed. Analysis of the GIS data 
for the three scenarios indicates the capability of the 
technique to map vulnerable areas and to quantitatively assess 
vulnerable sectors in each area. 
     Table 4 presents gross percentage loss for each scenario of 
SLR. It illustrates that the agricultural sector is the most 
severely impacted sector (a loss of over 90 percent), followed 
by the industrial sector (loss of 65 percent) and the tourism 
sector (loss of 55 percent) due to a SLR of 0.5 m, if no 
protection action is taken. Estimation of the socioeconomic 
impact due to loss of land and jobs is possible using employment 
statistics relevant to each sector. Results of the impact on 
population and loss of employment are shown in Table 5. It is 
estimated that a SLR of 0.5m in the governorate of Alexandria 
alone would cause a displacement of almost 1.5 million people 
and a loss of about 200,000 jobs by the middle of the next 
century if no action were taken. 
     The most important limitation of these results is the lack 
of recent land-use data and recent reliable topographic 
and socioeconomic data. However, upgrading the topographic data 
using GPS (Geopositioning Satellites) and the land use data 
using high spatial resolution imaging satellites, and building 
geographic information systems on a more advanced ARC/INFO 
environment are now well-mastered techniques. 
     It is therefore recommended that a program be carried out, 
using the already available quantitative methodology, to update 
and upgrade the Alexandria vulnerability study. In addition, it 
is necessary to carry out a detailed vulnerability assessment 
for two other highly vulnerable areas (Port-Said-Damietta and 
Suez) as well as a number of other small vulnerable areas along 
the Egyptian coasts. 
Abu-Zeid, M. 1989. History and future role of water 
development and management in Egypt. In Land Drainage in Egypt, 
ed. by M. H. Amer and N. A. De Ridder, 23-40. Drainage Research 
Institute. Cairo. 
Ainer, N. G., H. M. Eid, A. A. Hosny and D. El Sergany. 
1993. Simulated seed cotton yield as a function of weather, soil 
and crop management curves. Journal of Agricultural Sciences 18 
(5): 1280-1287. 
Blitzer C. et al. 1992. Growth and welfare losses from 
carbon emissions restrictions: A general equilibrium analysis 
for Egypt. The Energy Journal. 
El Raey, M., O. Frihy, S. Nasr, S. Desouki and K. Dewidar. 
1992. Impact of sea level rise on the Governorate of Alexandria, 
Egypt. First Bahrain International Conference. 
El Raey, M. Vulnerability of the coastal zones. World 
Coast Conference, November 1993, Noordwjik, The Netherlands. 
Eid, H. M., N. G. Ainer, M. A. Rady, and W. M. Rizk. 1992. 
Impact of climate change on simulated wheat yield and water 
needs. Fifth Egyptian Botanical Conference, Saint Catherine, 
Sinai, Egypt. 
Eid, H. M., N. G. Ainer, K. M. R. Yousef, M. A. M. Ibrahim and 
G. M. Gad El-Rab. 1992. Climate change crop modeling study of 
wheat. Fifth Egyptian Botanical Conference, Saint Catherine, 
Sinai, Egypt. 
Eid, H. M., N. G. Ainer, K. M. R. Yousef, M. A. Sherif, W. 
I. Mesaha and D. Z. El-Sergany. 1992. Climate change crop 
modeling on maize. Fifth Egyptian Botanical Conference, Saint 
Catherine, Sinai, Egypt. 
Eid, H. M., M. I. Bashir, N. G. Ainer and M. A. Rady. 
1993. Climate change crop modeling study on sorghum. Annals of 
Ain Shams 1. 
Eid, H. M., and D. El Sergany. 1992. Impact of climate change 
on simulated soybean yield and water needs. Fifth Egyptian 
Botanical Conference, Saint Catherine, Sinai, Egypt. 
Eid, H. M., A. A. Hand El Serganyosny, N. G. Ainer and M. 
A. Sherif. 1993. Prediction of seed cotton yield under 
different sowing dates and plant population densities in the 
Middle East. Annals of Agriculture Sci 1: 205-218.  
Eid, H. M., D. El Sergany, and S. A. Attia. 1993. Effect 
of environmental conditions and crop management on simulated 
peanut yield in the new lands. Journal of Agricultural Science 
18 (5): 1280-1287.  
Hulme, M. 1989. Recent and future precipitation changes over 
the Nile Basin. In Proceedings of the International Seminar 
on Climatic Fluctuations and Water Management, 11-14 December 
1989, Cairo, Egypt. 
Mills E. et al. July/ August 1991. Getting started; 
No-regrets strategies for reducing greenhouse gas emissions. 
Energy Policy. 
Sestini, G. 1993. Implications of climatic changes for 
the Nile Delta. In Climatic Change in the Mediterranean, 
ed. G. Sestini, 535-601. 
Wigley, T. M. L. 1993. Future climate of the Mediterranean 
Basin with particular emphasis on changes in precipitation. In 
Climatic Change in the Mediterranean, ed. G. Sestini, 15-44. 
Wilson, D., and J. Swisher. March 1993. Exploring the 
gap. Top-down versus bottom-up analyses of the cost of 
mitigating global warming. Energy Policy. 
                     Estonia: Greenhouse Gas Emissions 
            J.M. Punning, M. Mandre, M. Ilomets, A. Karindi,/1/ 
                      A. Martins,/2/ H. Roostalu/3/ 
/1/Institute of Ecology, Estonian Academy of Sciences 
/2/Institute of Energy Research, Estonian Academy of Sciences 
/3/Institute of Soil Science and Agrochemistry, Estonian 
   Agricultural University 
     SUMMARY: To mitigate the influence of greenhouse gases (GHG) 
     and climate change on the unique boreal landscape in Estonia, 
     a better understanding is needed of Estonian GHG emissions. 
     Such data are especially valuable now, when privatization and 
     ongoing process of restructuring of socioeconomic system creates 
     a good possibility for decreasing GHG emissions. During the time 
     when Estonia belonged to the previous U.S.S.R., the emissions 
     and environment data had, as a rule, only restricted use. 
     Therefore the present study, supported by U.S. Country Studies 
     Program, is the first attempt to compile an inventory of GHG 
     emissions in Estonia. 
Estonia is situated in northwestern part of the flat 
East European plain, remaining entirely within the drainage area 
of the Baltic Sea. The coastline length is 3,794 km. The total 
area of Estonia is 45,215 sq. km, of which 4,132 sq. km (9.2 percent) 
is made up of more than 1,500 islands and islets. Estonia 
is characterized by a flat topography. The average elevation is 
50 m, with the highest point being 318 m above sea level. Of 
the total population of 1,575,000 persons (1990 census), 71.4 
percent live in urban areas. The population density is 35 
persons/sq. km. Fifty-one percent of the population live in the 
five largest cities (Tallinn 484,400, Tartu 115,400, Narva 
82,300, Kohtla-Ja„rve 76,800 and Parnu 54,200). 
     Estonia belongs to Atlantic continental region of the 
temperate zone, which is characterized by rather warm summers 
and comparatively mild winters. Since the annual amount 
of precipitation exceeds evaporation by a factor of two, the 
climate is excessively damp. The amount of solar radiation 
varies widely during the year.  
     Although not very large in area, Estonia is relatively rich 
in natural resources, both mineral and biological, which have 
been and will be the basis of the Estonian economy. The 
production and processing of mineral resources give a 
considerable share of the gross national product but cause 
serious environmental problems. One of the most important ones 
is connected with the excavation of oil shale and use for energy 
production, which is accompanied by emission of GHG and fly ash, 
decline of ground water table, degradation of the quality of the 
fields and forests, as well as direct reduction of useful land 
due to the subsidence of soil and the deposition of waste 
(Punning, 1994). 
     The most important branch of industry in Estonia is energy. 
The total power yield of the Estonia and Baltic Thermal Power 
Plant is about 3,000 MW. Approximately 75 percent of the 
pollutants (CO<2>, SO<2>, NO, fly-ash) are emitted by the Baltic 
and Estonian TPP, which ranks among the ten biggest sources of 
air pollution in Europe. 
     The biggest sources of GHG in Estonia are energy and industry. 
In 1990 the Estonian energy system consumed a total at 452,000 
TJ of fuel per year. Estonia satisfies most of its energy demand 
by using fossil fuels. In 1990 oil shale constituted 
approximately 52 percent of the energy balance; heavy and light 
oil, 31 percent; natural gas, 11 percent; coal, 2.7 percent; and 
peat, wood, and wood waste, 3.3 percent. During oil shale 
combustion, CO<2> is formed not only as a burning product of 
organic carbon, but also as a decomposition product of the 
carbonate fraction. In the years 1990-93, electricity production 
has decreased considerably due to economical depression in 
Estonia, Latvia, Lithuania, and Russia. This caused a decrease 
in oil shale consumption for electricity generation from 22.4 
million tons in 1990 to 15 million tons in 1993. At the same 
time emissions from transportation increased accordingly with 
the increasing number of vehicles.  
     The territory of arable land is 1,130,000 hectares, with 
the total cultivated area is 1,110,000 hectares. Main GHG 
sources in the agriculture sector in Estonia are animal 
husbandry and use of fertilizers.  
     The forest land area makes up 47.7 percent of the 
Estonian territory. During the past half-century the area of 
forest stands has more than doubled, and the growing stock on it 
has increased 2.4 times (Table 1). Estonian forests belong to 
the zone of mixed and coniferous forests with relatively 
favorable growth conditions. Predominant tree species are Norway 
spruce, Scotch pine, and birch.  
     The peatland area is approximately 10,000 sq. km, corresponding 
to 22 percent of the territory (partly coinciding with 
forest areas); total peat reserves are approximately 2.7 billion 
metric ton. At present 1.4 million ton of peat (mainly milled 
peat) is extracted annually (Estonia, 1994). During the last 
decades, Estonian peatlands have been significantly influenced 
by amelioration activities. 
An inventory of GHG emissions and removals by sinks has 
been performed accordingly to the Intergovernmental Panel on 
Climate Change (IPCC) preliminary methodology. In each sector 
having importance in the GHG inventory in Estonia (energy, 
industry, transport, forestry, agriculture, wetlands), 
step-by-step assembly, documentation, and transmittal of the 
national inventory of GHG was provided for the baseline year 
1990. The data were entered on the IPCC worksheets and then, if 
necessary, the data were checked and corrected. Due to the 
importance of wetlands in Estonia and lack of methodical 
approaches in IPCC Guidelines (1994), a special methodology was 
worked out for inventory of GHG in this sector. The reliability 
of the data in different sectors varies largely. While reliable 
data about the conversion of domestic fossil fuel resources like 
oil shale are available, data on other sources (imported fossil 
fuels, private fellings of fuelwood) are less reliable 
(Statistical Yearbook, 1991-94). 
Some problems arose in the use of the IPCC emission 
coefficients, since a factor does not exist for Estonian's 
specific fuels (e.g., oil shale). The amount of carbon in the 
fuel varies significantly by fuel type. The dry matter of 
Estonian oil shale is considered to consist of three parts: 
organic, sandy-clay, and carbonate. During oil shale combustion, 
CO<2> is formed not only as a combustion product of organic 
carbon, but also as a decomposition product of the carbonate 
part. And therefore the total quantity of carbon dioxide 
increases up to 25 percent in flue gases of oil shale. Carbon 
emission factors (CEF) used for calculation of CO<2> emissions 
from energy sources are given in Table 2. 
Data from 1990, 1991, and 1992 years were used for estimating 
of carbon fluxes from Estonian forestry. Current emissions of 
carbon from biomass left to decay were estimated with the data 
over the previous decade (1980-90). Current releases of carbon 
from soils due to conversions were estimated over the previous 
25 years (1965-90).  
     The methodology applied in the present inventory does not 
differ from that recommended in the IPCC Guidelines. The 
assumptions and default data (recommended by IPCC Guidelines, 
1994) have been used when national data or assumption were not 
     It should be stressed that statistical data on the 
Estonian forests is satisfactory for calculating GHG emissions 
with the simplified IPCC methods.  
     Finally the fundamental bases for the methodology rests upon two 
linked themes: 
1.  The flux of CO<2> to or from the atmosphere are assumed to be 
    equal to changes in carbon stocks in existing biomass and soils 
2.  Changes in carbon stocks can be estimated at first by 
    establishing rates of change in land use and then applying simple 
     assumptions about the biological response to a given land use 
The main GHG sources in agriculture for Estonia are 
animal husbandry and use of fertilizers. According to the 
IPCC methodology, more attention was paid to CH<4> and N<2>O 
emissions. Data concerning soil properties and location was 
collected. Emissions from burning straw and other plant residues 
were not calculated in the present inventory as the statistical 
data were not available. 
Our data indicate (Ilomets, 1994) that the peat accumulation 
in different peatland types is rather uniform and varies between 
1.5 and 1.9 t ha (to the -1 power) y (to the -1 power).Here the 
accounts are based on the mean value of 
1.7 t ha (to the -1 power) y (to the -1 power). In lakes the 
accumulation of organic sediments varies in large scale: 
from 1 to 100 mg cm (to the -2 power) y (to the -1 power). 
The mean value was taken as 
10 mg cm (to the -2 power) y ( to the -1 power) or 
1 t ha (to the -1 power) y (to the -1 power). 
If considered with a 54-percent carbon content in the dry 
matter both in peat and lake sediments then the mean 
accumulation of carbon in the virgin peatlands is about 
0.9 t ha (to the -1 power) y (to the -1 power) and in lakes 
ca 0.54 t ha (to the -1 power) y (to the -1 power). 
     As a result of the drainage of virgin peatlands the 
accumulation of organic matter ceases and mineralization of the 
organic matter begins. For several decades, the breakdown of 
peat deposit and peat losses on fenlands ameliorated for 
agricultural purposes is monitored in Estonia. It is shown that 
the mineralization of organic matter is about 15 to 20 tons per 
hectare per year during the first decade after the establishment 
of an amelioration system (Tomberg, 1992). Later it is 
stabilized and depending on the type of exploitation (crop 
field, grassland, pasture) the mineralization is between 5 and 
15 tons per hectare per year. The mean level is 8 tons per 
hectare per year. As shown in several studies, the rate of 
mineralization of the peat in bogs and swamps is probably on the 
same level as in fenlands (Tomberg, 1992). 
                          RESULTS AND DISCUSSION 
Energy, Industry, Transport 
Estonia satisfies most of its energy demand by using 
fossil fuels. The major part of primary energy in Estonia is 
converted to electricity and heat or refined to the peat 
briquettes and oil shale oil. In the energy sector the biggest 
part of CO<2> comes from oil shale. Total CO<2> emissions from 
fossil fuel consumption were 37,170 Gg in 1990. CO<2> emissions by 
sources are given in Table 3. 
     Biomass fuel is used in form of fuelwood and wood waste. For 
1990 CO<2> emissions from biomass consumption were 847 Gg. 
Fuelwood burned one year but regrown the next year only recycles 
carbon. As a result, carbon dioxide emissions from biomass have 
been estimated separately from fossil fuel-based emissions and 
are not included in national totals. 
     Approximately 68 percent of Estonian energy is produced 
through the combustion of oil shale. The remaining 32 percent 
comes from heavy fuel oil, natural gas or other energy sources 
such as coal, light fuel oil, or LPG. The energy conversion 
sector accounts 77 percent of Estonian emissions from fossil 
fuel consumption, making it the largest source of CO<2> emissions. 
Oil shale across all sectors of the economy was responsible for 
about 76 percent of total Estonian energy-related CO<2> emissions 
with heavy oil accounting for 14 percent; natural gas, 6 percent; 
and other sources, 4 percent. 
     The main production processes that emit CO<2> in Estonia 
include cement production, lime production, limestone 
consumption. Total CO<2> emissions from these sources were 
approximately 627 Gg in 1990, accounting for 1.7 percent of 
total emissions of carbon dioxide. Cement and lime production 
are main industrial processes of carbon dioxide emissions. 
     Emissions from mobile sources are estimated by major 
transportation activity (passenger cars, buses, lorries, 
special vehicles, motorcycles, tractors, small excavators, 
diesel locomotives, air transport), where several major fuel 
types, including gasoline, diesel fuel, jet kerosene, natural 
gas liquids, other kerosene and LPG are considered. 
Road transportation accounts for the majority of mobile source 
fuel consumption, and the majority of mobile source emissions. 
Table 4 summarizes emissions from mobile sources. Total 
emissions from mobile sources in 1990 were 279 Gg of CO, 53 Gg 
of NO , 3.4 Gg of CH<4>, and 37 Gg of NMVOC. The number of 
vehicles is increasing very quickly in Estonia. Among them more 
used old cars and lorries are imported from abroad. Therefore 
emissions from mobile sources show a continual tendency to 
     Methane will be emitted as a result of energy production, 
transmission, storage, and distribution activities, as well as from 
municipal landfills, covering large territories in Estonia (Table 5). 
Methane production typically begins one or two years after waste 
placement in landfill and may last a long time (more than 50 years). 
Methane may be recovered for use as an energy source. The availability  
of data on sources and sinks of GHG is best in the energy sector and not 
so good for wastes and solvents. 
As the accumulation of CO<2> by trees in the boreal zone 
exceeds emissions by respiration and decay, the GHG budget of 
natural forests is positive. Forests, which cover almost half of 
Estonian territory, are an important terrestrial sink for CO<2>. 
Beside trees, the soils and vegetative cover in forest also 
provide a potential sink for carbon emissions. Changes in land 
use and forest management activities can disturb the natural 
balance of CO<2> and other GHGs emissions. 
     During the last half-century the area of forest stands has 
more than doubled (in 1935--20.2 percent; in 1993--47.7 percent) 
and will be increasing for the nearest future in Estonia 
(Karoles et al., 1994). As a results of biological process 
(e.g., growth, mortality) and human activity (e.g., harvesting, 
thinning, etc.) the carbon balance in forest ecosystem has been 
changed, already if compared with the situation in the past and 
will be changed in the future due to alterations in Estonian 
     Despite the small territory of Estonia, the forests 
growing here are rather diverse. The great variability brought 
about by natural conditions (soil, relief, and climatic ) is 
increased by the fact that the majority of the forests of 
Estonia have been affected by man's activities in varying 
degrees and ways (cutting, drainage, fires, etc.). The carbon 
content in forest soils varies from 44 to 192 tons per hectare. 
     The total carbon flux in the Estonian forests presented 
in estimates for 1990 (+/- 2 years) is based on a total accounting 
of biomass carbon stored in aboveground biomass of trees, 
soil carbon, as well as carbon in product pools. The annual 
carbon flux from Estonian forest is estimated to have been a 
net sequestration of carbon from the atmosphere to the 
biosphere. The total removal of carbon from atmosphere to 
forests was estimated to be 3,094.6 Gg, including 2,476.6 Gg 
removed by trees and 617.9 Gg by soils (Table 6). 
     Commercial harvest and management of various kinds make up 
a large majority of total forests biomass losses. Depending on 
the level of management, the annual rate of removals and 
emissions may be changed. Carbon annual emission rates from 
Estonian forests are estimated to be 926.3 Gg. The harvested 
timber and fuelwood effectively result in immediate carbon 
emissions of 769.6 Gg. Additional carbon flux from forests have 
been estimated for the onsite burning of branches, barks, and 
other wood wastes at 9.5 Gg. By forest conversion some of the 
biomass remains on the ground (stumps) where it decays slowly 
and 9.2 Gg carbon is released to the atmosphere due to the 
decay. A rather high amount of carbon is released to the 
atmosphere from the forest soil. This indicates that less carbon 
is actually emitted to the atmosphere from the Estonian 
productive forests than accumulated during the inventory period. 
Due to the carbon removal processes the net annual accumulation 
estimate is 2,168.3 Gg/yr. 
     The estimation of CO<2> emissions from forestry and land-use 
change requires the consideration of events over a long period 
of time. When forests are cleared or agricultural lands 
abandoned, the biological responses result in "commitments" of 
fluxes of carbon to or from the atmosphere for many years after 
the land use change. 
     The basic calculations focus primarily on forest 
conversation processes and abandonment of managed lands. The 
calculations of CO<2> removals or emissions of forests have taken 
into account alterations of areas and aboveground biomass 
changes due to management of forests. Annual removal of CO<2> from 
atmosphere by Estonian forests is estimated during the inventory 
year to be 11,346.8 Gg. This figure includes 7,438.3 Gg CO<2> due 
to the accumulation by the total growth increment of managed 
forests and 3,908.5 Gg CO<2> due to the accumulation by 
abandonment of managed lands over previous 20 years (Table 6). 
     In the processes of forest management some amount of remains 
may be removed from the conversion site and used as fuelwood or 
for other purposes. By-products and wood waste from forest 
industries are partly used as raw material for fuel. This 
activity contributes 30 percent of the total burning releases of 
2,822.0 Gg of CO<2> annually. A portion may be burned on site or 
converted to slash and decayed to carbon dioxide step by step. 
The annual rate of soil CO<2> emission from forest conversions was 
estimated at 508.7 Gg CO<2>. Total CO<2> emissions from the forest 
ecosystem is 3,399.4 Gg CO<2>. Taking into account emissions and 
removals of CO<2> in forest ecosystems the net CO<2> uptake by 
forest ecosystems in Estonia is estimated at 7,947.3 Gg per 
     Forest management activities may also result in fluxes of 
other greenhouse and radiatively important gases present in 
the atmosphere. Open burning associated with forest clearing or 
other land-use change may cause emissions of non-CO<2> trace gases 
to the atmosphere. Our data show that methane (CH<4>), carbon 
monoxide (CO), nitrous oxide (N<2>O) and oxides of nitrogen (NO, 
i.e. NO and NO<2>) have been emitted in case of open burning 
associated with forest conversion in Estonia. However, the share 
of these gases from forestry is not considerable. 
During the last decades Estonian peatlands have been 
influenced by the agricultural and forestry activities. The role 
of the peat industry is considered to be somewhat lower. 
According to official data, drainage for agricultural purposes 
removes 120,000 ha and for forestry purposes 180,000 ha while 
industry needs 38,000 ha of peatlands per year. Most drastically 
affected are fens, swamps, and floodplains of which about 10 
percent are still in a virgin state. Calculations demonstrate 
that changes in the hydrological regime cause increases in the 
emissions of CO<2> and CH<4>, especially in connection with 
disturbances of natural regimes in fens (Table 7). 
Preliminary results for the GHG budget in Estonia in 1990 
are given in Table 8. In the industry sector the emissions of 
GHG decreased from 1990 to 1994 by about 1/3. In the energy 
sector the emissions will decrease when oil shale using Thermal 
Power Plants will be modernized and the efficiency of the 
boilers and flue gas cleaning equipment will be increased 
(Moetus, 1993; State Energy Dept., 1992; Statistical Office, 
1993; Taehtinen, 1992). The emissions from transport are 
stabilizing as a trend of increasing use of newer cars is 
occurring. The taxes on old cars are higher and the average 
salary is continuously increasing. 
     The CO<2> budget in boreal zone trees is positive since more 
carbon is accumulated than emitted during the respiration and decay. 
Forest management and industrial use of forest might lead to critical 
changes in the GHG budget. 
     In agriculture the emissions are decreasing since the use 
of fertilizers has considerably decreased when compared to 1990. 
     For peatlands the peatland loss has been reduced, but 
new problems arise in connection with land privatization. 
Some projects have been started to solve these problems and 
design laws and taxes to protect peatlands. 
Estonia: Sectoral Environmental Assessment on the Utilization 
of Domestic Peat and Wood as a Fuel Source for Heating Systems, 
1994. Prepared for Estonian State Energy Department, 
Ministry of Economy and Estonian Ministry of Environment. 
Prepared with funding from the Swedish Board for Investment and 
Technical Support (BITS). Stockholm and Tallinn. 
Ilomets, M., 1994. Why Preserve Our Mires? Estonian Nature Vol. 3, 1994. 
IPCC Draft Guidelines for National Greenhouse Gas Inventories, 
Final Draft. 1994. Vol. 1-3 
Karoles K., Leemet, A., Lugus, O. 1994. Forest and Forest Products 
Country Profile. Estonia. United Nations; New York and Geneva. 
Manabe, S. and R. T. Wetherald, 1980. On the Distribution 
of Climate Change Resulting from an Increase in CO<2>-content of 
the Atmosphere. Journal of the Atmospheric Sciences 37. pp. 99-118. 
Moetus, M. 1993. Energy Situation in Estonia after 
Currency Reform and New Energy Saving Program for the Near Future. 
Institute of Energy Research: Tallinn, Estonia. 
Punning, J.M. (ed.) 1994. The Influence of Natural 
and Anthropogenic Factors on the Development of Landscapes. 
The Results of a Comprehensive Study in NE-Estonia. 
Institute of Ecology, Publ. 2. Tallinn, 227 pp. 
Solomon, A., 1986. Transient Response of Forests to 
CO<2>-induced Climatic Change: Simulation Modeling Experiments 
in Eastern North America. Oecologia 68. pp. 567-579. 
State Energy Department. 1992. The Program for Energy 
Conservation in Estonia. 
Tallinn, Estonia. 
Statistical Office of Estonia. 1993. Energy Balance of Estonia. 
Tallinn, Estonia. 
Statistical Yearbook 1991. Statistical Office of Estonia 
Statistical Yearbook 1992. Statistical Office of Estonia 
Statistical Yearbook 1993. Statistical Office of Estonia 
Statistical Yearbook 1994. Statistical Office of Estonia 
Poeyry, J. (ed.) Supply, Production and Costs of Wood Fuels 
and Raw Material for Wood Fuels in Estonia, 1994. 
Energy Sector Emergency Investment Project, Utilization of Wood and 
Peat for Heat Supply. Draft Report. Ministry of Economy, 
State Energy Department, Estonia. Tallinn/Stockholm.  
Taehtinen, M. and H. Nurste. 1992. Energy Use and 
Emission Scenarios to the Year 2000 for Estonia. 
Espoo, Finland: Technical Research Center of Finland. 
Tomberg, U. 1992. Breakdown of Peat as a Result to Drainage. 
Estonia, Saku. 
               Ethiopia: Greenhouse Gas Emissions and Sources 
                          Asress Wolde Giorgis 
                        Ethiopian Energy Authority 
     SUMMARY: This paper deals with greenhouse gas emissions (GHG) 
     inventoried from different emission sources in Ethiopia. This 
     inventory of greenhouse gas emissions is phase I of the Ethiopian 
     Climate Change Country Study Project which is partially financed 
     by the United States Government. 
Although, it was planned to undertake a GHG emissions 
inventory for all sources recommended by IPCC, only emissions 
from the following sources are considered: 
--  Energy consumption, either traditional or modern 
--  Bagasse, stationary combustion 
--  Agricultural practices: livestock, burning of agricultural 
    residues, and savanna 
--  Natural forests (special attention given to emission from 
    onsite burning) 
--  Waste emissions from landfills, municipal, and industrial 
    liquid waste 
--  Industrial processes (for instance, emissions from cement 
The inventory was limited to these sources because statistics 
for the above sources were available. Further, these sources 
are believed to be the most significant based on Ethiopia's 
economic level of development. Five gases (CO<2>, CO, CH<4>, N<2>O, 
and NO) were inventoried for the abovementioned emission 
source categories. 
     The Ethiopian Energy Authority has a plan to undertake 
GHG emission inventories for anthropogenic activities 
(especially from the energy sector) through the year 1999. 
Therefore, it is hoped that in due course more information will 
be collected, in order to quantify the emission of gases which 
are not mentioned here (e.g., NMVOCs) and to quantify emissions 
from all sources recommended by the IPCC. 
                          INVENTORY METHODS 
The inventory of the greenhouse gases has been conducted 
in accordance with international guidelines, in order to 
facilitate comparison with similar works undertaken in other 
countries. IPCC default values provided in the greenhouse gas 
reference manual have been utilized whenever local statistics 
where unavailable. Methodologies utilized to quantify the GHG 
emission from each source category are briefly stated below. 
CO<2> Emissions from Fossil Fuels 
Except for liquid fossil fuels, solid fossil fuels like 
coking coal, steam coal, lignite, subbituminous coal, and peat ( 
primary solid fossil fuels) and coke (secondary solid fossil 
fuel) are not used for energy supply in Ethiopia. Therefore, 
only CO<2> emissions from liquid fossil fuels have been 
     Prior to the calculation of carbon emissions from 
each fossil fuel type, fuels used as raw materials for nonenergy 
use were identified. According to the observations of fuel 
characteristics and utilization methods in Ethiopia, bitumen and 
lubricants are the only important fuels used as raw materials 
for nonenergy use. Bitumen is used as asphalt for road 
construction and as lubricants for locomotive parts. Therefore, 
except for the abovementioned two fuels, all other fuel types 
are not considered to store carbon since they are used for 
energy production. The CO<2> emissions from each liquid fossil 
fuel is calculated based on the following relationship 
GHG Emissions from Traditional Fuels 
The main traditional biomass fuels burned for energy in 
Ethiopia are wood, agricultural residues, charcoal, and dung. 
The CH<4>, CO, N<2>O, NO emission calculation methodologies 
utilized for the above fuels (including charcoal production) are 
presented below: 
GHG Emissions From Bagasse 
Sugar cane residue is a byproduct of sugar production in 
large agro-industries. Therefore, it is logical to treat bagasse 
as an industrially made residue compared to other agri-residues. 
The emissions from bagasse have been calculated using the 
following formula: 
Methane Emissions from Enteric Fermentation and Animal 
Manure Methane Emissions from Enteric Fermentation Herbivorous 
animals produce CH<4> during the digestion process by which 
carbohydrates are broken down by microorganisms into 
simple molecules for absorption into the blood stream. The 
quantity of CH<4> produced during this process has been calculated 
as follows: 
Determination of Emission Factors and Methane 
Emissions from Manure Management 
The amount of manure produced from ruminant and 
non-ruminant animals and the portion of the manure that 
decomposes anaerobically is the primary determinant of the 
amount of CH<4> produced. 
     Manure management systems in Ethiopia may differ from 
other countries. Animal manure, especially cattle manure, is 
collected and is made into dung cakes. After drying it is used 
as a fuel. An attempt has been made to modify the emission 
factors for cattle because the management of manure from cattle 
in Ethiopia is unique. The following calculation has been 
carried out to determine the factors. 
1.  Daily Manure produced: 
   a) Dairy cattle         A = 2.01 (Kg/h/d dry) 
   b) Nondairy cattle      B = 2.27 (Kg/h/d dry) 
2.  Yearly manure produced (Kr) from: 
   Dairy cattle            X = A x DCy x 365 days 
   Nondairy cattle         Y = B x NDCy x 365 days 
   Total Manure produced: X + Y 
The Ethiopian Energy Authority has been collecting data on 
the amount of dung utilized for energy for a number of 
years. Therefore, the fraction of manure handled in a dung form 
to that of manure produced is as shown below. 
            87-88      88-89      89-90      90-91      91-92      92-93 
Dung     3,647.25   3,743.12   3,841.45   3,767.59   4,046.10   4,152.43 
(utilized Kt) 
Manure  17,705.52  17,273.73  17,319.16  17,970.81   17,777.52 17,861.68 
produced (Kr) 
MS percent  20.60      21.70      22.20      21.00       22.80     23.30 
Note: MS percent is manure management usage. The average ratio 
of dung to manure produced from cattle is 22 percent. This ratio 
has been used to derive/modify management emission factors. 
  Dairy                                              Nondairy 
    Climate    Slurry    Pasture    Fuel    Slurry    Pasture    Fuel 
     MS%         0%        83%       22%      0%        95%       22% 
In order to modify the manure management emission factor, 
the manure management system methane conversion factors, the 
maximum CH<4> producing capacity, the daily VS excreted (from IPCC 
manual) and the manure management usage (MS % to 22 
%) calculated above have been inserted in the manure 
management emission factor equation shown below. 
The result of the calculation shows the following 
emission factors for different climate regions: 
Dairy animals emission factor            Nondairy animal emission factor 
   (KgCH<4>/head/year)                          (KG CH<4>/head/year) 
 Cool      Temperate      Warm             Cool      Temperate      Warm 
 1.51        1.81         2.05             0.99         1.14        1.32 
Based on the above emission factors and percentage 
distribution of animals according to climate, the average manure 
management emission factor has been calculated as follows: 
Animal distribution and manure management emission factors 
calculated are presented in the following table: 
               Climate Region                  Average Manure Management 
                Cool          Temp.           Warm       Emission Factor 
                (%)           (%)              (%)        (Kg/head/year) 
Dairy cattle    46.00          42.50          11.50                 1.70 
Nondairy cattle 46.00          42.50          11.50                 1.09 
Sheep           34.88          43.97          21.15                 0.15 
Goats           48.40          28.94          12.66                 0.16 
Horses          31.52          46.08          22.40                 0.58 
Mules           42.83          44.15          13.02                 0.81 
Asses           42.07          38.50          19.43                 0.81 
Poultry         30.64          28.70          40.66                 0.02 
Therefore, the CH<4> emission from manure management has 
been determined by applying: 
The total annual emission from livestock has been determined 
by applying: 
Non-CO<2> Trace Gas Emissions From Field 
Burning of Agricultural Residues 
Crop residue burning is a significant net source of CH<4>, CO, 
NO and N<2>O. Burning of crop residues in fields is not 
considered to be a net source of CO<2>, because the carbon 
released to the atmosphere from the crop residues burning at the 
end of harvest is usually absorbed during the next growing 
season. Total agri-residues produced annually in Ethiopia can be 
mathematically represented as follows: 
TOTAL = AF + EU + CO + BF + DE 
The Ethiopian Energy Authority has been recording the amount 
of residues used in energy consumption for a number of 
years. Therefore, what is unknown here is the amount burned in 
fields and left to decay. The amount burned could be determined 
by calculating the difference between the total 
agri-residue produced, the amount used for various purposes, and 
the decayed part in the field as follows. 
BF = TOTAL - (EU + CO + DE) 
However, since the decayed amount is not known and the 
decay process may not be completed within one year, it is not 
easy to obtain the amount of residues burned in fields from the 
above relationship. Therefore, the following IPCC 
recommended relationship has been utilized to determine the 
emission of the non-CO<2> gases from the residues burned onsite. 
    Total Carbon Released = AP x R/C RATIO x ADMC x FABF x CE x CF 
    Therefore, CH<4> Emissions = Total carbon release x 
    Emission ratio of CH<4>x16/12 
    CO Emissions = Total carbon released x Emission ratio 
    of CO x 28/12 
    N<2>O Emissions = Total carbon released x N/C x N<2>O 
    Emission ratio x 44/28 
    NO Emissions = Total carbon released x N/C x NO 
    Emission Ratio x 30/14 
Fire is a natural component of all forest ecosystems, 
including those which occur in Ethiopia. The IPCC/OECD 
methodology was employed to estimate fire emissions from 
forests. The equations used in these estimates are referenced in 
the IPCC/OECD methods manual. 
     Given this background and based on available local data 
and assumptions, it is estimated that about 23 percent of the 
total natural forest biomass (Fr) is burned onsite annually. The 
carbon released from natural forests is initially determined as 
follows in order to calculate the GHG emission quantities. 
     ANFC x NCB x f x CE x CFAGB = Carbon released 
     Therefore, the gases emitted are determined from: 
     CO<2> Emissions = Carbon released x 44/12 
     CO Emissions = Carbon released x emission ratio x 28/12 
     CH<4> Emissions = Carbon released x emission ratio x 16/12 
     N<2>O Emissions = Carbon released x (N/C ratio) 
     x Emission ratio x 44/28 
    NO Emissions = Carbon released x (N/C ratio) 
    x Emission Ratio x 30/14  
                     METHANE EMISSIONS FROM WASTE 
Methane Emissions From Municipal Solid Waste (Landfills) 
Except in Addis Ababa there is not any record of solid waste collected 
from Ethiopian cities and towns. The solid waste of Addis Ababa 
is disposed of by the municipality office at Repi. The present 
solid waste collection efficiency of the city office is 60 
percent, in other words, the municipality of the city office has 
the capacity to collect about 60 percent of the solid waste 
produced in the city. The remaining 40 percent is collected and 
burned by individuals around their respective 
     Therefore, methane emissions from the waste 
collected by the municipality office is considered important, 
because it is well developed landfill. The quantity of net 
methane emission from Addis Adaba is therefore obtained by 
carrying out the following formula: 
     CH<4> emissions = MSW x FDOC x FAD x (GgC - CH<4>/Ggc - biogas) 
     x 16/12 - MR 
Since the other towns' solid waste production is not 
usually recorded. The quantity of solid waste is initially 
calculated based on the population, waste generation rate, and 
fraction landfilled. Therefore, the equation used to determine 
the methane emission from other Ethiopian landfills is: 
     CH<4> emissions = POP x WGR x FL x FDOC x FAD 
     x (GgC - CH<4>/GgC - biogas) x 16/12 - MR 
Methane Emissions from Municipal Liquid Waste 
In this submodule, only methane emissions from Addis Ababa 
have been calculated as there are statistics on the parameters 
useful to determine CH<4> emission from this source. About 70 
percent of the inhabitants of Addis Ababa population have 
toilets in their houses and the rest (30 percent) have no 
toilets. Therefore, they defecate anywhere. Fifty-eight percent, 
11 percent, and 1 percent of the population of Addis Ababa uses 
pit latrines, septic tanks, and sewerage lines, respectively. In 
general, the total fraction of the city waste water treated 
anaerobically is (0.11 + 0.01) 0.12 percent. Therefore, the 
annual CH<4> emissions is calculated applying the following 
CH<4> emissions = (POP x BOD<5>/capita-day x 365 days x EF x Fr) 
     - MR 
Methane Emissions from Industrial Waste Water 
Methane emissions from industrial waste water treatment 
are dependent on waste water outflow from industry. In 
Ethiopia, there are many small and large scale industries which 
produce waste water containing concentrations of organic 
material likely to produce significant quantities of CH<4> 
emission. The methane emission from all Ethiopian industries 
waste water has been computed applying the following formula: 
Cement production is the most notable example of an 
industrial transformation process that releases a significant 
amount of CO<2>. CO<2> released from cement factories is produced 
during the production of clinker, an intermediate product from 
which cement is produced. The basic formula used to compute CO<2> 
emission is: 
     CO<2> emissions = Physical unit of production (t) 
     x Emission Factor (tCO<2>/t product) 
Input statistical data used to calculate GHG emissions 
from consumption of fossil fuels, traditional fuels, bagasse 
and animal population, amount of agri-residues and Addis 
Ababa landfills were collected between the first of July 
(Ethiopian fiscal year) and the end of June for each year. 
Therefore, GHG emissions released annually from the above 
sources are reported for those years where sufficient data were 
available for calculating emissions. 
     Inventory output from the abovementioned sources show that in 
all the years reported the major emissions were carbon monoxide 
from traditional fuels, carbon dioxide from fossil fuels, 
methane emissions from livestock enteric fermentation, carbon 
monoxide from agri-residues, and methane from traditional fuels. 
Although very low in quantity compared to the abovementioned 
emissions, significant quantities of emissions like oxides of 
nitrogen emitted from traditional fuels, methane emissions from 
manure, carbon dioxide from bagasse, methane emissions 
from agri-residues, nitrous oxide from agri-residues, and 
traditional fuels have been released from 1987-88 to 1992-93. 
     Information used to calculate emissions from onsite burning 
of natural forests, savanna burning, municipal solid and 
liquid waste, industrial waste water, and cement factory has 
been collected between January and December of the mentioned 
years. Inventory output from the above sources shows that carbon 
dioxide from onsite burning of natural forests, carbon monoxide 
from savanna burning, methane from municipal liquid waste of 
Addis Ababa, carbon monoxide from natural forests, and carbon 
dioxide from cement factories, respectively, were the gases with 
the highest emissions in the years mentioned. 
ACH4     Annual CH<4> emission from enteric fermentation [Gg] 
ADMC     Agri-residue dry matter content [percent] 
AEF      Average emission factor [KgCH<4>/head/yr] 
AF       Agri-residue used for animal feed [Kt] 
AGBD     Above-ground biomass density [Kt dm/ha] 
AMCH4    Annual CH<4> emission from animal manure [Gg] 
ANFC     Annual natural forest cleared [Kt dm] 
AP       Annual production [Kt] 
APC      Apparent consumption [Gj] 
AS       Area of savanna [Kha] 
ASB      Area of savanna burned annually [Kha] 
A%C      Animal population ratio living in cool climate region [percent] 
BB       Biomass burned [Kt dm] 
BF       Biomass quantity burned in fields [Kt dm] 
BO       CH<4> producing potential [M3 CH<4>/Kg of VS] 
BOD      Biochemical oxygen demand [GgBOD<5>/cap./day] 
Bs       Natural forest biomass burned onsite [Kt dm] 
B%T      Animal population ratio living in temperate 
         climate region [percent] 
CCDB     Carbon content of dead biomass [t C/ t dm] 
CCLB     Carbon content of living biomass [t C/ t dm] 
CE       Combustion efficiency [percent] 
CF       Carbon fraction [percent] 
CFAGB    Carbon fraction of above-ground biomass [percent] 
CH4-C    Methane carbon ration [percent] 
CFF      Carbon fraction of fuel [percent] 
CO-C     Carbon monoxide carbon trace gas emission ratio [percent] 
CRD      Carbon released from dead biomass [Kt C or Gg C] 
CRL      Carbon released from living biomass [Kt C or Gg C] 
CS       Carbon stored [percent] 
C%W      Animal population ratio living in warm climate region [percent] 
DC       Dairy cattle [103 head] 
DE       Decay [Kt dm] 
EF       Emission factor [Gg CH<4>/ GgBOD5] 
EFQ      Estimated fuel quantity consumed [MT] Used to determine 
         carbon stored 
En       Natural forest biomass used for energy [Kt dm] 
EU       Agri-residue utilized for energy supply [Kt dm] 
f        Fraction [percent] 
FAB      Fraction actually burned [percent] 
FABF     Fraction of agri-residue burned in fields [percent] 
FAD      Fraction actually degrades [percent] 
FB       Fraction burned annually [percent] 
FC       Fuel consumption [Kt dm] 
FFO      Fraction of oxidized [percent] 
%FCO     Fraction of carbon oxidized [percent] 
FD       Fraction that is dead [percent] 
FDOC     Fraction of degradable organic carbon [CgDOC/GgMSW] 
FL       Fraction that live [percent] 
Fr       Quantity of biomass cleared annually from natural forests 
         [Kt dm] 
Fr       (In methane emissions from municipal liquid waste) 
         Fraction of liquid waste treated anaerobically 
FWWTA    Fraction of waste water treated anaerobically 
         [GgBOD - percent] 
MCF      Methane conversion factor [percent] 
MMCH<4>  Methane emitted from animal manure [Gg]g 
MR       Methane recovery [Gg] 
MSW      Municipal solid waste [Gg or Kt] 
N-C      Nitrogen carbon ratio [percent] 
NCB      Net change of biomass [Kt dm] 
NCE      Net carbon emission [Gg] 
NDC      Nondairy cattle [10 head] 
N<2>O-N  Nitrous oxide nitrogen trace gas emission ration [percent] 
NO-N  Nitrogen oxides nitrogen trace gas emission ration [percent] 
POP      Population [10 head] 
R/C      Residue Crop ration [percent] 
VS       Average manure volatile solids [Kg] 
WGR      Waste generation rate [Gg MSW/10 head/yr] 
WWO      Waste water outflow [10 litre] 
a: Fuel type  
b: Sector activity 
c: Technology type, Charcoal consumption (depends on the area 
   of discussion) 
d: dung  
e: Charcoal production 
f: Fuel wood 
i: Animal species, Industry (depends on the area of discussion) 
j: Manure management system 
k: Climate region 
p: primary, Re: recorded 
s: secondary 
y: year 
Greenhouse Gas Inventory Reference Manual, IPCC 
National Energy Balance, Ethiopian Energy Authority, 1990-91 
National Energy Balance, EEA, 1991 
Greenhouse Gas Inventory Workbook, IPCC 
Estimation of Greenhouse Gas Emission and Sources, 
OECD/OCDE, Aug. 1991, pp. 2-34 
Ethiopian Statistical Abstract, 1988 and 1990 
Assistance to Landuse Planning Thiopia, FAO, ROME, 1984 
Natural Biomass Data for Leap Preliminary Report, EEA, 1992 
Ethiopian Forestry Action Program, May 1992 
African Compendium of Environment Statistics, 1993 
Energy Database Sources and Methods, June 1991 

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