Index of "1995 1995 Interim Report on Climate Change Country Studies" ||
Index of "Environment and Science" ||
Electronic Research Collections Index ||
U.S. Department of State
March 1995 Interim Report on Climate Change Country Studies
Oceans and International Environmental & Scientific Affairs
[SECTION 2 OF 4]
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
/5/Assistant to Project Manager, Egyptian Environmental
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
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.
EMISSIONS INVENTORY and MITIGATION
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.
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
-- 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.
VULNERABILITY AND ADAPTATION
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 supply in Egypt comes from three main sources:
-- Surface water: The Nile River and seasonal flash floods
-- 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
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
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
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,
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,
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.
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
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
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
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.
Statistical Office of Estonia. 1993. Energy Balance of 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.
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
-- Waste emissions from landfills, municipal, and industrial
-- 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
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.
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.
EMISSIONS FROM THE ENERGY SECTOR
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
[**EQUATIONS NOT AVAILABLE IN ELECTRONIC TEXT**]
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
[**EQUATIONS NOT AVAILABLE IN ELECTRONIC TEXT**]
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
[**EQUATIONS NOT AVAILABLE IN ELECTRONIC TEXT**]
GHG EMISSIONS FROM THE AGRICULTURAL SECTOR
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
[**EQUATIONS NOT AVAILABLE IN ELECTRONIC TEXT**]
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
Manure 17,705.52 17,273.73 17,319.16 17,970.81 17,777.52 17,861.68
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.
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.
[**EQUATIONS NOT AVAILABLE IN ELECTRONIC TEXT**]
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:
[**EQUATIONS NOT AVAILABLE IN ELECTRONIC TEXT**]
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:
[**EQUATIONS NOT AVAILABLE IN ELECTRONIC VERSION**]
The total annual emission from livestock has been determined
[**EQUATIONS NOT AVAILABLE IN ELECTRONIC VERSION**]
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
EMISSIONS FROM FOREST COMBUSTION
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)
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:
[**EQUATIONS NOT AVAILABLE IN ELECTRONIC TEXT**]
CO<2> EMISSIONS FROM CEMENT FACTORIES
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>
CO<2> emissions = Physical unit of production (t)
x Emission Factor (tCO<2>/t product)
INVENTORY RESULTS AND DISCUSSION
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.
SYMBOLS DEFINITION OF SYMBOLS AND UNITS
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
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
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
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
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
[END OF SECTION 2]
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