jhalak ram final paper(final)

7/29/2019 Jhalak Ram Final Paper(Final)

1/31

1

Household Energy Planning for Low Carbon

Emission in Nepal (Vision 2030)Lohani S.P. *, Adhikari J.R., Lama R.Department of mechanical Engineering, Kathmandu University , Dhulikhel , Nepal

*Email: splohani @ ku.edu.np

Abstract-Although Nepal has very low per capita emissions as well as total emissions and still

needs to meet basic development needs like education, healthcare, and the like, it has moral

obligation to opt for low carbon development pathway. In this analysis the base case scenario

and the low carbon emission scenario has been compared for the emission and cost factors.This paper deals with energy planning for low carbon emission scenario at household energy

consumption sector till 2030. The base case scenario of energy mix and technological option are

changed with low carbon content energy mix such as renewable energy, and increase use of

modern and efficient technology. The low carbon emission energy planning is done using an

energy planning software Long-Range Energy Alternatives Planning System (LEAP). This

software provides long range emission projection for different emission scenario, which can be

used as a reference for future energy planning of the country.

The result of this analysis shows that the carbon dioxide (CO2) emission in base case scenario

is higher than that of low carbon development pathway. A comparative result indicates that

for base case scenario in 2030, CO2 emission is 44690 tons whereas for low carbon

development pathway, the CO2 emission is about 23100 tons. However, energy cost per capita

surge up with low emission scenario and is about 8951 USD / capita / year in contrast with

3282 USD / capita /year in base case scenario. Thus LCS will be very beneficial for sustainable

development and CO2 stabilization. Nevertheless, the increased energy cost in low emission

development pathway can be compensated through international financial assistance: direct

financial assistance, technological transfer or carbon trading mechanism like CDM.

Keywords- Base case scenario, Carbon dioxide, Energy cost, LEAP, Low carbon scenario,

Projection, Renewable energy


2/31

2

List of Acronyms

AEPC: Alternative Energy Promotion Center

BCS: Base case scenario

CDM: clean development mechanism

CO2: Carbon dioxide

GHG: green house gas

GJ: Gigajoule

HH: House hold

i.e.: that is

IPCC: Intergovernmental Panel ON Climate Change

LEAP: Long-range Energy Alternative Planning

LCS: low carbon scenario

LPG: Liquefied petroleum gas

$: U.S. dollar

sq.km: square kilometer


3/31

3

1. Introduction

The modern era of human civilization is confronted by global warming phenomenon, which is

resulting into climate change, one of the biggest challenges to humans. The Global Warming is

caused by increase in the GHG emissions which, in turn, is increasing the greenhouse effect of

the earth. According to IPCC, the temperature increase in 20 thcentury likely to have been the

largest of any century in past 100 years [1]. The overwhelming consensus among climate

scientists is that most of the increase is due to human economic activity, especially the burning

of fossil fuels and deforestation. These activities contribute as build-up in CO2 and other gases

in Earths atmosphere. There will be catastrophic effects in the ecosystems of the planet. About

15 to 40% of species will face potential extinction even after only 2C of warming [1]. Most of

the developing countries including Nepal which are in the already warm regions of the earth

are experiencing further increase in temperature. Over the last twentyfive years, the

temperature in Nepal has been increasing at the rate of 0.06 OC per year. In high altitudes, it

increased by 0.6OC over the last thirty years [2]. It is almost certain that Nepal, along with the

other developing countries will encounter greater impact of global warming in terms of

decreased agricultural produce (which these countries economy depend upon), shortage of

water, mass migration, increase in diseases causing overburden to the already poor health

sector. These impacts will further adversely affect the socio-economic development of this part

of the world. Since the extent of global warming and thus climate change is related to the

concentration of greenhouse gases. Stabilizing emissions of CO2 at current levels would not lead

to stabilization in the atmospheric concentration of CO2 [1]. The reason for this is human

activities adding CO2 to the atmosphere faster than its removal from natural processes.

On the other hand Climate change adaptation is especially important in developing countries

since those countries are predicted to bear the brunt of the effects of climate change as shown

by the Vulnerability Index. South Asian countries such as Nepal are the most vulnerable to the

climate change due to extreme levels of poverty and a high dependency on agriculture, coming

in first and second position [3]. In the developing country like Nepal that is already under the

considerable environmental stress, climate change will exert additional stress to the ecological

and the social systems. In addition, the Kyoto Protocol established three market-based


4/31

4

mechanisms to help bring down the costs of lowering emissions. These mechanisms are known

as joint implementation, the CDM, and emissions trading [4]. Under joint implementation and

the CDM, a country can invest in a project to curb emissions in another country, where it is

cheaper to do so and thereby acquire the resulting credit to offset against its own target. Under

emissions trading, a country that exceeds its own target of lowering emissions can transfer the

surplus credits to another country which is finding it more difficult to reduce its emissions.

Developing countries can participate, but only through the CDM. Nepal can take huge advantage

of CDM and carbon trading by increasing share of renewable energy in household.

Carbon dioxide is the major GHG that is emitted in large volume by human activities. Carbon

dioxide is emitted during the production, transportation and consumption of the fossil fuels

(such as coal, oil, gas etc.) as energy sources in numerous activities to produce goods andservices. The global environmental consequences of anthropogenic GHG emissions are an

urgent concern in the scientific community. The UNFCCC, which was adopted in May 1992, sets

an ultimate objective of stabilizing GHG concentrations in the atmosphere at a level that will

prevent dangerous human-induced interference with the climate system.

Energy resources in Nepal are traditional and commercial sources. Traditional sources include

fuel wood, agricultural residues, and animal wastes (dung) whereas commercial sources

include hydropower and imported petroleum fuels. In addition, Nepal carries a diverse range

of renewable energy sources like biogas, solar, wind, hydro and modern biomass energies

which contribute to the countrys overall energy in a moderate proportion only.

Total energy consumption in Nepal in the year 2008/09 was about 9.4 million tons of oil

equivalent (401 million GJ) of which some 87% was derived from traditional resources such as

woody biomass and animal waste, 1% from small renewable energy sources, and only about

12% from commercial energy sources such as petroleum and fuel products and electricity from

small to large hydropower plants. In the residential sector, biomass contributes about 96% ofthe total energy consumed [5-6]. About two thirds of HH use firewood as their main source of

fuel for cooking, followed by LPG (12%), cow dung (11%), biogas (2.4%), and kerosene (1.4%).

However, LPG is the main source of fuel for cooking in urban areas (52%), and the proportion is

even higher in the urban areas of Kathmandu valley (83%). In rural areas, 75% of HH use

firewood for cooking and it is 36% in urban areas. Ecologically, firewood is the major source of


5/31

5

cooking fuel in the Mountain (88%), Hill (76%) and Terai (58%) regions. The second common

source of cooking fuel in the Hill and Mountain regions is LPG, which serves 18% and 6% of HH

respectively, whereas in Terai region cow dung serves as cooking fuel to 21% of HH. Firewood

remains the main source of fuel for cooking in all regions, and ranges from 53% in the central to

as high as 91% in the Mid-Western regions [5-6].

Though, Nepal is using huge amount traditional sources such as biomass, growing concern in

use of commercial sources such as fossil fuel is still prevailing. The use of such energy sources

in residential sector emits huge amount of CO2 and because of sustainability and environmental

issues, an alternative source of energy must be found to meet energy requirement and

mitigation of CO2 release from high energy consumption sector. The residential sector is one of

the prominent sectors, which can mitigate huge amount of CO2 release and save large amount offossil fuels such as LPG, kerosene etc if renewable energy such as hydropower, solar, wind,

biogas etc. substitute them. Nepal has high potential of renewable energies. It has the capacity

to generate 83,000MW hydroelectricity in which 42,000MW is technically feasible. According to

AEPC 659 projects, total around 17MW, especially in rural areas have been identified as

technically possible and financially viable micro hydro power. The average solar radiation

varying from 3.6 to 6.2 kWh/m2/day and sunshine around 300 days a year offers great

opportunities of solar technologies. According to AEPC, the commercial for solar power grid

connection is 2,100MW if only 2% of the land area of Nepal is considered as suitable land. It is

estimated that the technical potential of biogas plants is 1.9 million. The annual average wind

energy potential is about 3.387 MWh/m2 and potential area of wind power is about 6074 sq.km

with power density greater than 3000W/m2 [7]. If we increase the share of renewable energy, it

may increase total energy cost per capita. However renewable energy technologies are

advantageous from environment and sustainability point of view. Renewable energy sources

are considered to be carbon neutral. Widespread use of renewable energy sources will decrease

GHG emission. The application of such energy sources by new interventions will increase the

income of the people inhabited in the area.

This paper presents an initial technical exploration of how Nepals residential energy systems

might be altered over the coming 2 decades to meet ambitious goals for sustainable

development and keeping CO2 emissions to an optimal level for global response. To explore this


6/31

6

question two scenarios have been developed. The Base case scenario examines current and

historical trends in Nepals CO2 emissions in residential and projects CO2 emissions to 2030

assuming that Nepal continues to develop as usual. It assumes a general continuation of current

policies which include some significant efforts to address sustainability and the climate

challenge, but it does not foresee any fundamental shifts in energy policy. Additional analysis

has been done to extrapolate energy and CO2 emissions patterns out to 2030. The second, Low

Carbon Scenarios examine the feasibility of massively reducing Nepals CO2 emissions from

residential sector in 2030. To achieve this target, increase sharing of renewable energy other

than traditional ones is done. Due to the lack of crucial technologies, new policies and

improvement, Nepals emissions will continue to climb in the next decade even under the most

ambitious mitigation scenarios. LCS is intended to minimize the total cost as well as reduce the

total carbon emission.


7/31

7

2. Materials and Methods

2.1 Low Carbon Energy Planning Analysis

This paper focus on the emission and total energy cost increases due to substitution of

renewable energy in residential sector energy sources with two different scenario: one is base

case scenario and the other is low carbon scenario. The emission is based on the emission factor

given by the IPCC Tier 1 Default Emission Factors [8]. The analysis has been based on linear

forecasting and exponential forecasting technique on LEAP. The mitigation analysis uses the

LEAP model and examines the demand, energy cost, emissions and effects. LEAP is a scenario-

based energy environmental modeling tools on comprehensive accounting of how energy is

consumed, converted and produced in a given region or economy under a range of alternatives

assumptions[9]. Scenarios are self consistent story-lines of how future energy system might

involve over time in a particular socio-economic setting and under a particular set of policy

options. Scenario in LEAP can compare to assess their energy requirements, environmental

impacts and social costs and benefits. In engineering optimization model like LEAP, the model

itself provides a numerical assessment and comparison of different policies [10]. This model is a

linear programming energy model in which the most basic criterion is total cost of providing

economy- wide energy services under different scenarios. When this criterion is used the

structure of this type of model as used in mitigation analysis can be represented schematically to

minimize total cost of providing energy and satisfying end use demand subject to:

- Energy supplied >= energy demanded

- End use demands satisfied

- Available resource limits not exceeded

The validity of the results depends very much on the following assumptions:

- Future price of fuels

- Useful energy demands (projected)


8/31

8

- Technological characteristics

Technological characteristics mean the rate of emission of carbon- dioxide, costs, efficiency etc.

[10].

In developing the model the following basic assumptions have been made.

The socio-economic parameter other than assumed to change and a particular set ofpolicy options are as usual.

The inflation rate of energy cost will be increasing by 5% per year for coming 2 decades. The change of socioeconomic parameter in the BCS is similar to historical pattern for

coming 2 decades.

The increase or decrease of energy share in LCS to meet the target is linear. Emission factor is as given by the IPCC Tier 1 Default Emission Factors.

2.1.1 Carbon dioxide emission from different energy sources

The analysis uses a straightforward accounting methodology in which emissions of different

pollutants are calculated as the product of fuel combustion and an emission factor. Energy

consumption is in turn calculated as the product of an activity level measuring the level of

energy service provided (e.g. total population etc.) and energy intensity. Put simply, emissions

are calculated as follows:

P = A * E * F (1)

Where:

P is the total emission of CO2 (Thousands of kilograms)

A is a measure of economic activity

E is energy intensity of the activity [GJ/activity]

F is the CO2 emission factor [thousands of kilogram/GJ]

Levels of activity in residential sector is first projected forward based on overall assumptions

about levels of growth of the Nepal economy and how its structure might shift as income levels

grow. Also the energy from different sources is projected from historical energy consumption

(BCS) and target energy share (LCS) based on the assumptions.


9/31

9

Emission per capita per year can be calculated by dividing total emission of CO2 by total

population in respective year. The total population in respective year is projected from

historical population.

p=P/Po (2)

Where

p is CO2 Emission per capita per year (Thousand of kilogram)

P is the total emission of CO2 (Thousands of kilograms)

Po is total population of Nepal in respective year

2.1.2 Energy production cost of different energy sources

The total energy cost of different energy sources is calculated as the product of total GJ energy

consumption per year and energy cost to produce one GJ of different sources.i.e.

C= E*S (3)

Where

C is total energy cost per year ($)

E is total energy consumption per year (GJ)

S is energy cost per unit GJ ($/GJ)

The inflation in energy cost per unit GJ is assumed to be 5% per year. Energy per capita per year

can be calculated by dividing total energy cost per year by total population in respective year

which is projected from historical population.

i.e.

c=C/Po (4)

Where

c is energy cost per capita per year ($)

C is total energy cost per year ($)

Po is total population of Nepal in respective year


10/31

10

Table 1: Residential energy consumption in GJ from different energy sources (1996 to 2009)

[11].Traditional Commercial renewable

Year

Agriculture

residue

Animal

dung Fuel wood Coal Electrical

Kerosen

e LPG

Other

petroleum Biogas

Micro

hydropower solar

1996 10349 17568 231109 15 1183 6087 796 411 23

1997 10566 17936 235962 10 1278 7100 925 536 24

1998 10788 18313 240917 11 1363 8725 708 678 27

1999 11014 18698 245976 13 1478 9051 728 826 29

2000 11246 19090 251142 45 1681 10071 867 981 33

2001 11482 19491 256416 31 1866 9534 1102 1179 38 0.3

2002 11723 19901 266724 26 2008 11537 1301 1350 41 0.9

2003 11969 20319 272323 23 2221 10297 1450 1526 47 1.7

2004 12220 20748 278220 29 2434 9181 1711 1650 52 2.2

2005 12478 21181 284138 25 2729 7053 2007 1847 57 2.7

2006 12502 21626 289449 39 2900 6831 2183 2027 65 2.9

2007 13007 22080 295994 26 3215 6055 2688 2222 90 3.1

2008 13020 22544 302251 36 3352 4722 2713 49 2384 112 4.1

2009 13334 23017 308604 35 3534 2126 3201 163 2593 136 5.6

Table 2: Default Carbon dioxide emission factor [8]Fuel type Emission factor (Kg/GJ)

LPG 67.3

Kerosene 70.2

Biogas 81.5

Coal 92.644

Vented mud stove wood 83.43

Mud stove Vegetable waste 78.77

Mud stove animal waste 87.33

Petroleum 68.55


11/31

11

Table 3: Energy cost required to generate unit GJ of different energy sources [12-13]

Sources Cost ($/GJ)

Coal 6

Electricity 23

Kerosene 27

LPG 25

Petroleum Coke 40

Hydro 23Solar 80

Wind 74

Animal waste 5

Vegetable waste 3.12

wood 3.12

Table 4: Total population of Nepal [14-15]Year Population

1971 11555983

1981 15022839

1991 18491097

2001 23151423

2011 26620809


12/31

12

2.2 Scenario description

A need to make substantial future reductions in GHG emissions is actually a major challenge in

the energy system. The ability of nations to respond to this requirement depends entirely on

the technology as well as strong policy. To assist policy decisions, the potential of technology

and the cost of its applications must be estimated. Sustainable development requires

interrelationship among society, energy, economy, environment as well as technology. In this

context and to this extent, practicable and quantitative methods are needed to compare

possible national responses. In order to evaluate emission control measures the use of

simulation models have to be employed. These models require exploration of a wide range of

alternatives that would almost be impossible to test in reality.

Since this study is focused on comparing carbon emission and energy cost per capita in the

residential sector supplied with base case scenario which projected from historical data and

low carbon scenario which consist of more share of renewable energy, an exact and detailedsimulation of whole socioeconomic parameter is not imperative at the moment. This analysis is

focused on evaluating only few parameter such as population, energy cost , energy supply by

different sector etc. that can influences the carbon emission and energy cost per capita.


13/31

13

Table 1 shows energy consumption data from 1996 to 2009. In this analysis base year is 1996

and projection is done from 2010 to 2030. Historical data between 1996 and 2009 was used,

called current account (LEAP model terminology). Projections from the year 2010 to 2030 were

made for two groups of scenarios: the base case scenario and low carbon scenario. Use of

modules in LEAP models are key assumption and demand in residential sector, the key

assumption is population. The subcategories or branches in households were determined by

level of detail data that were available. The subcategories are traditional, commercial and

renewable sources of energy.

The 2001 and 2011 census provided detail household data for number of households

population which is shown in table 4. The energy intensity data for residential (household) was

used from Energy Sector Synopsis Report 2010 from 1996 to 2009 shown in Table 1. Theemission factors used are not available for Nepal and so IPCC Tier 2 Default emission factors

was used shown in Table 4. The energy cost for different residential energy sources was taken

from different report of energy which is shown in Table 3.

2.2.1 Scenario drive

This analysis considers two scenarios and show two alternative pathways for achieving the low

carbon emission. The time spans till 2030. The descriptions of scenarios are as under.

3.2.2 Base case scenario

The scenario assumes improvements in energy intensity similar to the dynamics-as-usual case

and the targeted share of commercial renewable energy. The base case scenario examine how

Nepals energy system in residential sector and its CO2 emissions might evolve to 2030 in the

absence of significant new policies especially designed to addresses climate mitigation. The

base case scenario covers energy consumption and production in residential areas and relative

CO2 emissions historically from 1996 to 2009 and its future projection till 2030. The analysis

uses straight forward methodology in which emission of different pollutant are calculated as

the product and fuel emission factor is taken from IPCC Tier 2 Default emission factors.

The levels of activities in households are first projected forward based on historical data. The

scenario is driven forward by two high levels: historical population and historical energy

consumption in residential sector. The energy consumption for future is estimated from overall


14/31

14

historical energy consumption in residential sector. Similarly energy consumption for different

branches such as traditional branch: animal waste, vegetable waste, fuel wood commercial

branch: coal, electricity, LPG, kerosene, petroleum coke and renewable branch: biogas, micro

hydro, solar, wind is projected from historical energy consumption by using linear forecast

method as shown in figure1. The total carbon dioxide emission given by equation (1) and total

cost by equation (3). The commercial energy consumption in residential sectors from 1996 to

2010 is shown in figure 2.

Figure 1: Energy share by different sources in residential sectors from 1996 to 2010

E

nergyShare%

Years


15/31

15

Figure 2: The commercial energy consumption in residential sectors from 1996 to 2010.

2.2.3 Low carbon scenario

In this scenario we reasonably increase the share of renewable energy and reduce share oftraditional energy. The scenario assumes greater improvements in the energy intensity and

higher target for the share of commercial renewable energy compared to the base case

scenario.

Nepal has very high potential of renewable energy sources. Let us consider the target energy

share within 2030 in residential sector by different energy sources i.e. electricity 25%, solar

10%,vegetable wastage 5%,animal wastage 5%,wind5%,LPG 10%, kerosene 5%, biogas 10%,

micro hydro 10%,wood 15% . The target energy consumption in residential sector in 2030 is

shown in table 5.

Table 5: The target energy consumption (GJ) in 2030 in LCS

Traditional Commercial Renewable

EnergyShare

%

Years


16/31

16

Agriculture

residue

Animal

dung

Fuel

wood ElectricalKerosene

LPG Biogas

Micro

hydropower Solar Wind

28590 28590 85770 142950 28590 57180 57180 57180 57180 28590

2.3 Model analysis and simulation procedure

2.3.1 Base case scenario

Nepals population is estimated to be 39.4 million in 2030, projected from historical data of

population in 2001, 23151423[3] and in 2011, 26620809[15]. The total energy consumption

projected in 2030 is 5.710^5 GJ by using historical energy consumption in residential sector

[11]. The total energy consumption in residential sector is subdivided into different energy

sources: traditional, commercial and renewable energy and their projection up to 2030 are as

shown in figure 3. The figure shows that the energy share by traditional sources such as wood,

animal waste and vegetable waste is very high accounting to almost 90% of the total energy

consumption in 2030. The energy share by commercial energy sources is almost 8% in which

the share of kerosene continuously decrease to almost 0%, whereas share of electricity, coal

and LPG increases continuously to 2%, 3% and 3% in 2030. The energy share by renewable

energy sources such as hydro, wind, solar energy, and biogas is only 2% in 2030.


17/31

17

Similarly the total energy consumption in 2030 by different residential sector is shown in figure

4. The energy consumption is about 433000 GJ by wood, 31500GJ by animal waste and 18000

GJ by vegetable waste. Likewise energy consumption is about 7500GJ by electricity, 7300GJ by

LPG, 100 GJ by coal, and 500GJ by kerosene and 1300GJ by other petroleum products. The

renewable energy consumption by residential sector is forecasted by exponential method is

shown in figure 5. The energy consumption in 2030 is 3400GJ by biogas, 2000GJ by micro

hydropower, 1500 GJ by solar energy.

After forecasting these energy consumption data we can easily calculate the total carbon

emission and total energy cost by equation (1) and (3). The carbon emission by different

residential energy sources in this scenario are given in table 5.

Figure3: Historical and projection of energy share by different sources in residential sectors in

BCS.

EnergyShare%

Years


18/31

18

Figure 4: Historical and projected total energy consumption in different energy sources

residential sector in BCS

Years

ThousandsofGJ

ThousandsofGJ

Years


19/31

19

Figure 5: Renewable energy consumption in residential sector in BCS

2.3.2 Low carbon scenario

In this scenario, the targeted energy share is projected linearly from 2011 to 2030. The energy

share by traditional energy sources such as wood, animal wastage, agriculture residuedecreases linearly. However the share of commercial and renewable energy sources increases

linearly to attain the targeted energy share within 2030. The energy consumption in

residential sector by different energy sources is varying as shown in figure 6. Historical and

projected total energy consumption in residential sector in LCS is as shown in figure 7.

Renewable energy share in residential sector for LCS is as shown in figure 8.

After forecasting these energy consumption data we can easily calculate the total carbon

emission and total energy cost by equation (1) and (3). The carbon emission by differentresidential energy sources in this scenario are given in table 7. Figure 6 is a linear projection of

the energy share to meet the target that has been assumed for LCS.

Figure 6: Projected energy shares in different energy sources in LCS

2.4 Simulation procedure

Since the aim of this study is to compare the carbon emission and energy cost of a system

supplied with historical energy consumption pattern and targeted energy consumption for the

residential sector in two different scenarios, the self developed emission analysis model that

used dynamic values of energy consumption from LEAP is implemented on each scenario. The

Years

EnergyShare

%


20/31

20

simulation is performed dynamically with period startup for 2010 by using historical energy

consumption from 1996 to 2009, which is taken from Energy Sector Synopsis Report 2010. The

self developed emission model with emission equation 1 has used dynamic values of energy

from the simulation and calculates CO2 emission for each sub categories. The energy

consumption and energy cost of different scenario are calculated by using emission equation 1

and energy cost equation 3.

Figure 7: Historical and projected total energy consumption in residential sector in LCS

ThousandsofG

J

Years


21/31

21

Figure8: Renewable energy share in residential sector for LCS

3. Result and Discussion

The considered system has two parts: carbon emission part and energy demand part

considering energy supply in base case scenario and low carbon scenario. Table 1 and table 5

represent the energy consumption pattern for the base case scenario and low carbon scenario

for all categories studied here, while a glimpse of comparison followed by the carbon emission

in BCS and LCS are given in table 6 and table 7. These tables give the CO2 emission values for

each sub categories of different scenario analyzed. The result of implementing them in the

residential sector in the two paths is shown graphically in Figure 9-12. The graphs compare thecarbon dioxide emission from the BCS and the LCS.

Table 6: Carbon dioxide emission in thousands of Kilogram by different sources in BSCYear Vegetable

Waste

Animal

Waste

Wood Coal Kerosene LPG Other

petroleum

Biogas Total

1996 815.2 1534 21000 1.39 427 33.6 3.4 43.9 23879

ThousandsofGJ

Years


22/31

22

1997 832.3 1566 21500 0.936 498 62.3 3.4 49.9 24514

1998 849.8 1599 21900 1.038 612 47.6 3.4 56.7 25070

1999 867.6 1633 22400 1.177 635 49 3.4 64.5 25654

2000 885.8 1667.1 22800 4.169 707 58.3 3.4 73.3 26199

2001 904.4 1702 23300 3.521 669 74.2 3.4 83.3 26740

2002 922.6 1738 24300 2.872 810 87.6 3.4 94.7 279592003 942.8 1775 24800 2.131 722 87.6 3.4 107.7 28451

2004 962.6 1812 25800 2.677 644 115.2 3.4 122.4 29463

2005 982.9 1850 25800 2.316 495 135.1 3.4 139.1 29408

2006 984.8 1889 26300 3.613 479 146.9 3.4 158.1 29965

2007 1025 1928 26900 2.409 425 180.9 3.4 179.7 30644

2008 1026 1969 27500 3.335 331 182.6 3.4 204.3 31220

2009 1050 2010 28100 3.243 149 215.4 11.2 232.2 31772

2010 1050 2010 28100 3.243 149 215.4 11.2 264 31803

2011 1082 2067 29000 3.63 228 225 16.4 233.1 32855

2012 1099.1 2103.4 29600 3.78 207 239.1 20.3 246.7 33519

2013 1116 2139 30100 3.932 188 253 24 260 34086

2014 1135 2176 30700 4.081 170.8 267.3 28.1 274.1 34755

2015 1152 2212 31200 4.229 155.1 281.4 32 287.8 35325

2016 1169.8 2248 31800 4.3775 140.8 295.5 35.9 301.5 35996

2017 1188 2284 32300 4.526 127.9 309.7 39.8 315.2 36569

2018 1205.1 2320.3 32800 4.6744 116.1 323.8 43.7 328.9 37143

2019 1223 2356 33400 4.823 105.5 337.9 51.5 342.6 37818

2020 1440.4 2392.5 33900 4.9712 95.8 352 55.4 356.2 38393.4

2021 1258 2429 34500 5.12 87 366.1 59.3 369.9 39070

2022 1276 2465 35000 5.268 79 380.2 63.2 383.6 39648

2023 1293.4 2050 35600 5.4165 71.7 394.3 67.1 397.3 403262024 1311.1 2537.1 36100 5.565 65.1 408.4 71 411 40905

2025 1328.7 2573.2 36700 5.7134 59.1 422.5 74.9 424.7 41585

2026 1346.4 2609.4 37200 5.8618 53.7 436.7 78.8 438.4 42165.36

2027 1364.1 2645.5 37800 6.0103 48.8 450.8 82.7 452 42846

2028 1381.7 2681.6 38300 6.1587 44.3 464.9 86.7 465.7 43427

2029 13999.4 2717.8 38900 6.3072 40.2 479 90.6 479.4 44109

2030 1417 2754 39400 6.456 36.5 493.1 493.1 44691

Table 7: Carbon dioxide emission in thousands of Kilogram by different sources in LCSYear VegetableWaste

Animal

Waste

Wood Kerosene LPG Biogas Coal Total

1996 820 1500 21000 430 53 44 1.4 23848

1997 830 1600 21000 500 62 50 0.94 24042

1998 850 1600 22000 610 48 57 1 25165

1990 870 1600 22000 640 49 64 1.2 25223

2000 890 1700 23000 710 58 73 4.2 26431


23/31

23

2001 900 1700 23000 670 74 83 3.5 26427

2002 920 1700 24000 810 88 95 2.9 27613

2003 940 1800 25000 720 98 110 2.1 28668

2004 960 1800 25000 640 120 120 2.7 28640

2005 980 1800 26000 500 140 140 2.3 29560

2006 1000 1900 26000 480 150 160 3.6 296702007 1000 1900 27000 430 180 180 2.4 30690

2008 1000 2000 27000 330 180 200 3.3 30710

2009 1100 2000 28000 150 220 230 3.2 31700

2010 1100 2000 28000 150 220 260 3.2 31730

2011 1100 2000 28000 180 300 370 3.2 31950

2012 1100 2100 27000 220 400 490 3.2 32310

2013 1200 2100 27000 260 510 620 3.2 31690

2014 1200 2100 27000 310 620 760 3.1 31910

2015 1300 2200 26000 360 750 910 3.1 31520

2016 1300 2200 26000 430 890 1100 3 31920

2017 1400 2200 25000 500 1000 1300 2.9 31400

2018 1400 2200 24000 570 1200 1400 2.8 30770

2019 1500 2300 23000 660 1400 1600 2.6 30460

2020 1500 2300 22000 750 1500 1900 2.5 29950

2021 1600 2300 21000 840 1700 2100 2.3 29540

2022 1600 2300 20000 950 1900 2300 2.1 29050

2023 1700 2400 19000 1100 2100 2600 1.9 28900

2024 1800 2400 18000 1200 2300 2800 1.7 28500

2025 1900 2400 16000 1300 2600 3100 1.5 27300

2026 1900 2400 15000 1400 2800 3400 1.2 26900

2027 2000 2400 13000 1600 3000 3700 0.93 25700

2028 2100 2500 11000 1700 3300 4000 0.64 24600

2029 2200 2500 9700 1900 3600 4300 0.2 24200

2030 2300 2500 7800 2000 3800 4700 0 23100


24/31

24

Figure 9: CO2 emission from residential sector in BCS

Figure10: Thousands kilograms CO2 emission from residential sector in LCS.

The CO2 emission in low carbon scenario (LCS) first increases and gradually decreases ascompared to base case scenario (BCS) which is continuously increasing seen in figures 10 and 9

respectively. In 2030, residential sector CO2 emission at low carbon scenario is 23100 tons that is

lower than the base case scenario value of 2012, which is shown in figure 10.

0

5000

10000

15000

20000

25000

30000

35000

40000

45000

50000

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035

CO2inthousandofkg

0

5000

10000

15000

20000

25000

30000

35000

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035

Years

CO2in

thousandofk

Years


25/31

25

LCS results in residential sector show CO2 emissions (thousand kg per year) increases from a base

of 23848 in 1996, peaks to about 32310 in 2012 before falling to 23100 in 2030 as shown in

figure 10. Whereas in first path i.e. BCS results in residential sector CO2 emissions (thousand kg

per year) shows continuous growth from a base of 23848 in 1996 to about 33519 in 2012 and

further increase to 44690 in 2030 as shown in figure 9. This figure shows that the total CO 2

emission of BCS in 2030 increases by 40.52% to that of 2010. However, in LCS the total CO 2

emission in 2030 decreases by 27.69% of the emission value in 2010. This proves that energy

share in LCS is more environmental friendly than BCS in terms of emission point of view that

lead to reduction of CO2 following reduction in environmental impacts that upholds

sustainability.

Figure11: Energy cost per head increases in BCS

0

500

1000

1500

2000

2500

3000

3500

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035

C

ostperhead($)

Years


26/31

26

Figure12: Energy cost per head increases in LCS

The energy cost curves (figure11 and 12) give completely different pictures as compared to

emission curve; the energy cost curve increases continuously to a very high level in LCS than in

BCS to fulfill the same energy demand from 2010 to 2030. Total cost per head in residential

sector increases from 142 in 1996 to 594 in 2012 and increase up to 8951 in 2030 in LCS as

shown in figure12. Whereas in BCS, the total cost per head increases from 142 in 1996 to only

3282 in 2030 which is shown in figure 11. The graphs (figure 9, 10, 11 and 12) clearly indicate

that the LCS is far more sustainable approach than the BCS model. In both cases CO 2 emission

and energy cost analysis depict that the calculation to fulfill the energy demand has less CO2

emission in LCS as compared to BCS. Whereas energy cost is less in BCS than LCS.

This result is very useful for national policy instruments and their implementation,

initiatives of the private sector, local governments and non-governmental organizations,

and cooperative international agreements. It is very useful for policy makers to select and

evaluate policies. National policies and international agreements are discussed in terms of

two criteria by which it is evaluated that are environmental sustainability and cost-

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035

Costperhead($)

Years


27/31

27

effectiveness. The result continues to reflect that a wide variety of national policies and

measures are available to governments to limit or reduce GHG emissions. In general, climate

change policies, if integrated with other government policies, can contribute to sustainable

development.

The volume of emissions allowed determines the carbon price and the environmental

effectiveness of this instrument, while the distribution of allowances has implications for

competitiveness. Uncertainty in the price of emission reductions under a trading system makes

it difficult prior to estimate the total cost of meeting reduction targets.

Nepal signed the UNFCCC in Rio de Janeiro in June 1992 and ratified the Convention on 02 May

1994. Furthermore, Nepal ratified the Kyoto Protocol of the UNFCCC on 16 September 2005 and

Nepal is listed as the non-annex 1 party to the Protocol [2]. Nepal might have few opportunities

to attract foreign investment in the form of Clean Development Mechanism (CDM) projects.

Government support for research and development is a special type of incentive, which

can be an important instrument to ensure that low GHG-emitting technologies is available

in the long-term. Substantial additional investments and policies for R&D are needed to ensure

that technologies.

The Kyoto Protocols most notable achievements are the stimulation of an array of national

policies, the creation of an international carbon market and the establishment of new

institutional mechanisms. The CDM, in particular, has created a large project pipeline and

mobilized substantial financial resources, but it has faced methodological challenges regarding

the determination of baselines and additionality [4]. The protocol has also stimulated the

development of emissions trading systems, but a fully global system has not been implemented.

The Kyoto Protocol is currently constrained by the modest emission limits and will have a

limited effect on atmospheric concentrations. It would be more effective if the first

commitment period were to be followed up by measures to achieve deeper reductions and the

implementation ofNepals policy prospects to attract the foreign investment in CDM projects

are small at the moment. China and India are reported to be the major countries to host the


28/31

28

CDM projects due to their low marginal costs of GHG abatement. Primarily, HH energy sectors

are expected to be the major hosts of the CDM projects.

In Nepal , the mitigation options available for household are more limited because the

electricity generation will continue to be based on hydropower. The main option considered is

substution of LPG and kerosene with in cooking , cost of such substitution was found to be high.

On the whole the emission level of Nepal is negligible as compared to other developing

neighboring countries. It is quite clear that Nepal's developmental effort will be hampered if

energy consuming activities are checked since these are the cornerstones of its overall

development. The trend towards increased fossil fuel consumption seems almost unavoidable

such that any relevant long-term GHG mitigation policy initiatives may be expected to reduce

the rate of increase in carbon emissions, but not lower them. Some long and short term

measures such as hydro power development, afforestation programs, and use of energy

efficient technology have been recommended to reduce GHG emissions, but it would be very

expensive as well as detrimental to the country's developmental efforts if strict mitigation

measures were to be applied.


29/31

29

4. Conclusion

The analysis of the two scenarios with two different energy shares to fulfill the residential

energy demand revealed that historical energy consumption pattern is also very important for

the analysis. In this two different analysis variation in residential energy demand by changingenergy share of renewable energy, the CO2 emission in BCS is very large as compared to LCS in

2030. Higher emission in BCS is due to large utility of traditional energy sources in residential

sector. However, the energy cost in LCS is higher than BCS due to substitution of traditional

energy by renewable energy which is expensive.

From this analysis, we conclude that if we increase total cost per head from $3282 to $8951 in

residential sector in 2030 to increase consumption of renewable energy, we can actually reduce

thousands kg of CO2 per year (from 44690 to 23100) from residential sector in 2030. Thus LCS

will be very beneficial for environmental sustainability due to the reduction of carbon emission

in the atmosphere.

The comparison of the analysis proves that LCS is one of the realistic models for the sustainable

development considering environment point of view. Its effectiveness would be enhanced if we

substitute energy cost in this scenario by international financial assistance like carbon credit.


30/31

30

References

1. IPCC (2001), Third Assessment Report (2001), Intergovernmental Panel on ClimateChange.

2. KEEP (2011), Workshop Report-2011 (2011). Kathmandu Environmental EducationProject, Kathmandu , Nepal

3. 14. IPCC (1997). The regional Impacts of Climate Change: An Assessment ofVulnerability Intergovernmental Panel on Climate Change (IPCC) Summary for

Policymaker.

4. Barker T., I. Bashmakov, L. Bernstein, J. E. Bogner, P. R. Bosch, R. Dave, O. R. Davidson,B. S. Fisher, S. Gupta, K. Halsns, G.J. Heij, S. Kahn Ribeiro, S. Kobayashi, M. D. Levine,

D. L. Martino, O. Masera, B. Metz, L. A. Meyer, G.-J. Nabuurs, A. Najam, N. Nakicenovic,

H. -H. Rogner, J. Roy, J. Sathaye, R. Schock, P. Shukla, R. E. H. Sims, P. Smith, D. A. Tirpak,

D. Urge-Vorsatz, D. Zhou, 2007: Technical Summary. In: Climate Change 2007:

Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the

Intergovernmental Panel on Climate Change [B. Metz, O. R. Davidson, P. R. Bosch, R.

Dave, L. A. Meyer (eds)], Cambridge University Press, Cambridge, United Kingdom and

New York, NY, USA. IPCC (2004), Technical Summary Contribution of Working Group

III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change

5. SREP (2011). Scaling-up Renewable Energy Program Investment Plan For Nepal, draft of11 September 2011, Kathmandu, Nepal.

6. AEPC (2009), Alternative Energy Promotion Centre Renewable Energy Data Book 2009,AEPC and other sources, Kathmandu, Nepal.

7. AEPC (2010), Alternative Energy Promotion Centre report 2010, Potential of Solar homesystems, Biogas-plants and Micro-hydro in Nepal Opportunities for MFI Khumalter Height

Lalitpur, Kathmandu, Nepal8. IPCC (1996], Intergovernmental Panel on Climate Change IPCC Guidelines for National

Greenhouse Gas Inventories. Volume 3: Reference Manual 1996.

9. Heaps, C.G., 2012. Long-range Energy Alternatives Planning (LEAP) system, [Softwareversion 2012.0018] Stockholm Environment Institute. Somerville, MA, USA.


31/31

10. CSMT (1996), draft report on mitigation assessment of greenhouse gases emissionsfor energy sector in Nepal, country study management team Washington, USA

11. WECS (2010).Energy Sector Synopsis Report 2010. Water and Energy CommissionSecretariat, Kathmandu, Nepal

12. NEA (2011), Annual Report 2011. Nepal Electricity Authority, Durbar Marg,Kathmandu, Nepal.

13. NOC (2011), Selling price 2011. Nepal Oil Corporation Limited, Kathmandu, Nepal,14. CBS (2004), Nepal Living Standards Survey Report: 1995/96-2003/04, Central Bureau of

Statistics, National Planning Commission Secretariat, Nepal.

15. CBS (2011), Nepal Living Standards Survey Report: 1995/96-2010/11, Central Bureau ofStatistics, National Planning Commission Secretariat, Nepal.

jhalak ram final paper(final)

Documents