€™s GHG Inventory... · Final Report on Nepal’s GHG Inventory Report for Third National Communication 2 Authors and Contributors WORKING TEAM Team Leader Dr. Madan Lall Shrestha

Nepal’s GHG Inventory For Third National Communication to the UNFCCC

Final Report

A Report Submitted to Third National Communication Project, Ministry of Population and Environment, Government of Nepal, Singh Durbar, Kathmandu.

July 2017

Tribhuvan University Central Department of Environmental Science

Kirtipur, Nepal

Final Report on Nepal’s GHG Inventory Report for Third National Communication

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AuthorsandContributors

WORKING TEAM

Team Leader

Dr. Madan Lall Shrestha

Thematic Leaders

Prof. Dr. Madan Koirala AFOLU Prof. Dr. Ramesh K. Maskey Energy Prof. Dr. Rejina Maskey Byanju Waste Dr. Kundan Lal Shrestha IPPU Thematic Experts Dr. Sudeep Thakuri Land Use Change Dr. Pashupati Chaudhary Agriculture Dr. Narayan P. Ghimire Forest and Biomass Dr. Bivek Baral Energy Dr. Alka Sapkota Waste Dr. Dibas Shrestha IPPU

Institutional Head: Prof. Kedar Rijal

Coordinator: Dr. Sudeep Thakuri

Technical Support and Data Management: Mr. Subesh Joshi

*Coverphoto:AviewofeasternKathmanduValley(SudeepThakuri,2016)


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Acknowledgements

Tribhuvan University Central Department of Environmental Science (TU-CDES) takes the pleasure of assisting the Government of Nepal in preparing this Third National Communication Report (TNC) on GHG Inventory of Nepal. We are thankfully obliged to the Government of Nepal, in particular to the Ministry of Population and Environment (GoN-MoPE) for entrusting us with this important task.

The preparation of TNC Report had been a formidable task but successfully completed with the generous support of many organizations. We express our gratitude to the Ministries, in specific Agriculture Development, Energy, and Federal Affairs & Local Development, and the Departments, mainly Forest Research and Survey, and Soil Conservation & Watershed Management. We are thankful to the National Planning Commission, Water & Energy Commission Secretariat, Solid Waste Management & Technical Support Centre, Alternative Energy Promotion Centre and Central Bureau of Statistics for providing essential data and information.

We extend our thankfulness to various research institutions and academia, viz. Institute of Science & Technology (TU), Kathmandu University, Nepal Academy of Science & Technology, and Nepal Agriculture Research Council, for their cooperation and support.

During the preparation of the TNC, we received valuable suggestions and inputs from many experts, government officials and researchers. We are particularly thankful to Secretary of MoPE Dr. Bishwa Nath Oli, and MoPE officials of concerned division Dr. Ram Prasad Lamsal, Mr. Ritu Pantha, and Mr. Binaya Joshi, who generously provided their support throughout the project period.

We thank all the faculty members and graduate students of TU-CDES who helped collect data from different sources and analyze them carefully.


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AcronymsandAbbreviation

ADB Asian Development Bank

BAU Business as Usual

AFOLU Agriculture, Forestry, and Other Land Use

BOD Biological Oxygen Demand CBS Central Bureau of Statistics

CDIAC Carbon dioxide Information Analysis Center

CKD Cement Kiln Dust

COD Chemical Oxygen Demand

DFRS Department of Forest Research and Survey

DHM Department of Hydrology and Meteorology

DOC Degradable Organic Carbon

DoC-India Department of Commerce, India

DoC-Nepal Department of Commerce, Nepal

DoI Department of Industries

DoTM Department of Transport Management

EDGAR Emission Database for Global Atmospheric Research EF Emission Factor

EFDB Emission Factor Data Base

ESN Environment Statistics of Nepal

FAO Food and Agriculture Organization

FO Fuel Oil

FOD First Order Decay

FYM Farm Yard Manure

GDP Gross Domestic Product

GHG Greenhouse Gas

GIZ Deutsche Gesellschaft für Internationale Zusammenarbeit

GWP Global Warming Potential

INC Initial National Communication ISW Industrial Solid Waste

IPCC Intergovernmental Panel on Climate Change

IPPU Industrial Processes and Product Use

JICA Japan International Cooperation Agency

LPG Liquefied Petroleum Gas

LRMP Land and Resource Management Plan

MoF Ministry of Finance

MoPE Ministry of Population and Environment

MoSTE Ministry of Science, Technology, and Environment

MSW Municipal Solid Waste

NCMA Nepal Cement Manufacturers’ Association

NEEP Nepal Energy Efficiency Programme NOC Nepal Oil Corporation

ODX Ozone Depleting Substances

QA/QC Quality Assurance and Quality Control

SNC Second National Communication

SUV Sports Utility Vehicle


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SWDS Solid Waste Disposal Sites

SWMTSC Solid Waste Management Technical Support Centre TEPC Trade Export Promotion Center

TNC Third National Communication

UCIL Udayapur Cement Industry Limited

UNEP United Nations Environment Programme

UNFCCC United Nations Framework Convention on Climate Change

USGS United States Geological Survey

WB World Bank

WECS Water and Energy Commission Secretariat

Chemical Compounds

CaO Calcium oxide

CH4 Methane

CO Carbon monoxide

CO2 Carbon dioxide

CO2-eq Carbon dioxide equivalent

HFC Hydrofluorocarbons

NMVOCs Non-Methane Volatile Organic Compounds N2O Nitrous oxide

NOx Oxides of Nitrogen

PFC Perflourocarbons

SF6 Surfur hexafluoride

SO2 Sulfur dioxide

Units

Gg Gigagram

hL hectoliters

kg kilogram

yr year

MW Mega Watt

t tonnes


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CONTENTS

Authors and Contributors .................................................................................................... 2

Acknowledgements ............................................................................................................ 3

Acronyms and Abbreviation ............................................................................................... 4

EXECUTIVE SUMMARY ..................................................................................................... 8

1. Background Information ........................................................................................... 101.1 Overview of Nepal’s GHG Inventory ....................................................................... 10

1.1.1 Inventory of GHG for the base year 1990 ......................................................... 111.1.2 Inventory of GHG for the Base Year 1994 ......................................................... 111.1.3 Inventory of GHG for the Base Year 2000 ......................................................... 12

1.2 Inventory of the National GHG for the Base Year 2011 ........................................... 121.2.1 Objective .......................................................................................................... 121.2.2 Scope ................................................................................................................ 12

1.3 Framework of Inventory planning, preparation and documentation ......................... 13

2. Energy ....................................................................................................................... 182.1 Brief summary ......................................................................................................... 182.2 Overview of the Sector ............................................................................................ 182.3 Data and Methods ................................................................................................... 19

2.3.1 Data Sources ..................................................................................................... 192.3.2 Methodology ..................................................................................................... 20

2.4 Energy Resources and Fuel Consumption Pattern ..................................................... 212.5 Issues Pertaining to the Estimation of GHG Emissions .............................................. 242.6 GHG Emission for the Base Year 2011 ..................................................................... 242.7 Trends in Greenhouse Gas Emissions ....................................................................... 302.8 GHG Emission Projection ........................................................................................ 312.9 Perspectives for Improvement .................................................................................. 33

3. Industrial Processes and Product Use ........................................................................ 343.1 Brief summary ......................................................................................................... 343.2 Overview of the Sector ............................................................................................ 343.3 Data and Methods ................................................................................................... 36

3.3.1 Data Sources ..................................................................................................... 363.3.2 Methodology ..................................................................................................... 37

3.4 GHG Emissions for the base year 2011 .................................................................... 423.5 Trend in Greenhouse Gas Emission ......................................................................... 443.6 GHG Emission Projection ........................................................................................ 503.7 Perspectives for improvement .................................................................................. 51

4. Agriculture, Forestry, and Other Land Use ............................................................... 534.1 Brief Summary ......................................................................................................... 534.2 Overview of the Sector ............................................................................................ 534.3 Data and Methods ................................................................................................... 54

4.3.1 Data Sources ..................................................................................................... 54


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4.3.2 Methodology ..................................................................................................... 54a) Livestock (3A) ........................................................................................................ 55b) Land (3B) .............................................................................................................. 55c) Aggregate Source and Non-CO2 Emission Sources on Land (3C) ............................ 57

4.4 GHG Emissions and Removals for the base year 2011 ............................................. 694.5 Trend in Greenhouse Gas Emission ......................................................................... 704.6 Perspectives for Improvement .................................................................................. 72

5. Waste ........................................................................................................................ 735.1 Brief Summary ......................................................................................................... 735.2 Overview of the Sector ............................................................................................ 735.3 Data and Methods ................................................................................................... 75

5.3.1 Solid Waste Disposal (4A) ................................................................................. 755.3.2 Biological Treatment of Solid Waste (4B) .......................................................... 765.3.3 Open Burning of Waste: CO2 Emissions ............................................................ 775.3.4 Wastewater Treatment and Discharge ............................................................... 78

5.4 Greenhouse Gas Emission for the Base Year 2011 ................................................... 825.4.1 Solid Waste Disposal ......................................................................................... 825.4.2 Biological Treatment of Solid Waste .................................................................. 835.4.3 Open Burning ................................................................................................... 835.4.4 Wastewater Treatment and Discharge ............................................................... 84

5.5 Trends in Greenhouse Gas Emission ........................................................................ 865.6 GHG Emission Projection ........................................................................................ 875.7 Perspectives for improvement .................................................................................. 91

6. Way Forwards ........................................................................................................... 93

References ....................................................................................................................... 94


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EXECUTIVESUMMARY

This report presents a detailed description of Nepal’s Greenhouse Gas (GHG) inventory prepared for the third national communication (TNC) to the UNFCCC. The inventory accounts the emission by sources and their removal by sinks for the base year 2011 considering the direct GHGs: Carbon dioxide (CO2), Methane (CH4), Nitrous oxide (N2O), Hydrofluorocarbons (HFCs), Perfluorocarbons (PFCs), Sulphur hexafluoride (SF6). Further, it accounts for the indirect GHGs such as, Carbon monoxide (CO), Nitrous oxides (NOx), Non-Methane Volatile Organic Compound (NMVOC), Sulphur dioxide (SO2). The sectors covered include energy; industrial processes and product use (IPPU); agriculture, forestry, and other land use (AFOLU); and waste. The reporting is in accordance with the 2006 IPCC guidelines for reporting National Communications from Non-Annex 1 Parties to the United Nations Framework Convention on Climate Change (UNFCCC).

The Ministry of Population and Environment (MoPE), the focal ministry for climate change in Nepal, prepared the GHG emissions for the second national communication (SNC) of Nepal considering the base year 2000 and submitted in 2014. A brief description of the same is also included in this report. The GHG emissions of 1994 reported in the Initial National Communication (INC) have also been compared with the GHG estimates of 2000 and current 2011 inventory. While reporting the GHG inventory, this report also gives a detailed account of the methodology used, the quality assurance/quality control (QA/QC) measures applied, the results of the key source analysis, the quantification of the uncertainties associated with the estimates, and the data gaps.

The net GHG emissions of 31,998.91 Gg CO2-Eq was estimated for Nepal in the base year 2011. This quantity represents about 0.060% of Nepal’s contribution to the global emission of total 53,197,386.48 Gg CO2-eq (Olivier and Janssens-Maenhout, 2014).

Summary Table of Nepal’s GHG emission and removal 2011

(a) Direct Gases

Sector, Sub-sectors Emission/Sink of Direct Gas (Gg)

CO2 CH4 N2O HFC* CO2-eq

TOTAL

-7335.82 1259.61 26.25 0.01 31998.91 1 Energy

4678.20 354. 90 3.90

14713.36

- Energy Industries 2.38 0.00 0.00

2.38

- Manufacturing Industries and Construction 2237.34 0.04 0.06

2256.10

- Transport 1708.92 0.27 0.08

1740.97

- Others (Commercial/Institutional, Residential, Agricultural) 729.58 354.59 3.89

10753.00

2 Industrial Processes and Product Use 355.40

0.00 0.01 379.80 3 AFOLU

-12371.79 882.36 21.12

15982.16


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- Livestock

705.49 0.09

17665.29

- Land (Forest and Cropland) -16436.14

-16436.14

- Land (Grassland, Settlement, and Other Land) 3253.36

3253.36

- Aggregate Sources and Non-CO2 Emissions Sources on Land (3C) 810.99 176.87 21.03

11499.68

4 Waste

2.36 22.35 1.22

923.59 Memo Items

International Bunker 172.51

Biomass Combustion for Energy Production 34990.76

(b) Indirect Gases

Sector, Sub-sectors Emission of indirect Gases (Gg)

NOx NMVOC CO SO2

TOTAL

2.87 6.00 186.44 0.20 1 Industrial Processes and Product Use 0.00 6.00 0.00 0.20

2 AFOLU

2.87

186.44

Aggregate Sources and Non-CO2 Emissions Sources on Land (3C) 2.87

186.44

Summary of emission and removal computation

Computed CO2-eq (Gg) 1990/91 1994/95 2000/01 2010/11

Emission 22468 54043 26222 48435 Removal NA 14778 12775 16436

Net 22468 39265 13447 31999


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1. BackgroundInformation

The UNFCCC Decision 17/CP.8 on guidelines for the preparation of national communication requires each Non-Annex I Party to provide, in its national inventory, information on GHGs, namely, CO2, CH4, and N2O, emitted from the anthropogenic sources. Also, the Non-Annex I Parties are encouraged, as appropriate, to provide information on the anthropogenic emissions of HFCs, PFCs, and SF6 by sources. Further, the Non-Annex 1 parties need to provide, to the extent possible, information on emissions from international aviation and marine bunker fuels separately in their inventories. Emission estimates from these sources should not be included in the national totals. This chapter provides information on the above-mentioned six gases in terms of their emission by sources and their removal by sinks. It also takes into account the emissions from international bunkers and biomass burning.

Nepal adopted and became Party to the United Nation Framework Convention on Climate Change (UNFCCC) at Rio Earth Summit, held in June 1992. As a Party, Nepal has commitment to communicate the updates of the national actions on climate change periodically to the Convention. To fulfill the commitment, Nepal has prepared and submitted Initial National Communication (INC) in July 2004 and Second National Communication (SNC) in December 2014. Such initiative gives an opportunity to share climate relevant information of Nepal to other countries and help to mainstream climate change into national policies, plans and development process.

1.1 Overview of Nepal’s GHG Inventory

One of the components of the National Communication document is an incorporation of greenhouse gas (GHG) inventories. The contribution of Nepal in the global GHGs emission was 0.025% and 0.027% as per the INC and SNC, respectively (MoPE, 2004; MoSTE, 2014). The main features of the GHGs Inventories of Initial and Second National Communication are summarized below in Table 1.1–1.4.

Table 1.1 Summary of Initial and Second National GHG inventory.

Initial National

Communication Second National Communication

Submission Jul 2004 Dec 2014 Base year 1994/95 2000/01 Sectors • Energy

• Industrial processes • Forestry and land-use • Agriculture • Waste

• Energy • Industrial processes • Agriculture • Land use, Land use change and

forestry


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• Waste • Memo items: International

bunkers Biomass

Reference Guidelines

Revised IPCC Guidelines for National GHG Inventories 1996

IPCC Guidelines for National GHG Inventories 1996

GHGs Used CH4, CO2, NO2 Direct gases: CH4, CO2, NO2

Indirect gases: NOx, CO, NMVOC, and SO2

Future projection 2000, 2010, 2020 2015, 2025, 2030

1.1.1 InventoryofGHGforthebaseyear1990

Table 1.2 Greenhouse Gas Emission by Different End-use Sectors during 1990/91 (DHM, 1997).

Greenhouse Gas Source and Sink Categories

CO2 (Gg) CH4 (Gg) N2O (Gg)

Emission Removal

Fuel Combustion 912.96 Agriculture 920.82 0.803 Biomass burning 85.00 0.590 Net Emission 912.96 1005.82 1.393

1.1.2 InventoryofGHGfortheBaseYear1994

Table 1.3 Nepal’s GHG emission Base Year 1994 (MOPE, 2004).

Greenhouse Gas Source and Sink Categories

CO2 (Gg) CH4 (Gg)

N2O (Gg) Emission Removal

1. Energy 1465 2. Industrial Processes 165 3. Agriculture 867 29 4. Land-Use Change & Forestry 22895 -14778 5. Waste 10 1 Total emission and Removals 24525 -14778 877 30 Net emission 9747 877 30


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1.1.3 InventoryofGHGfortheBaseYear2000

Table 1.4 Nepal’s direct and indirect GHG emissions in the base year 2000 (MOPE, 2014).

GHG Source and Sink Categories

Direct Indirect

CO2 CO2 CH4 N2O NOx CO NMVOC SO2

Emissions (Gg)

Removals (Gg)

Emission (Gg)

Total National Emissions and Removals

2,894 -12,776 662 26 67 2,889 333 76

1 Energy 2,763 0 164 2 67 2,755 332 76

2 Industrial Processes

131 0 0 0 1

3 Agriculture 466 23

4 Land-Use Change & Forestry

-12,776 15 0 134

5 Waste 17 1 6 Memo items

International Bunkers (Aviation)

162 1

CO2 emission from Biomass

30,294

1.2 Inventory of the National GHG for the Base Year 2011

This GHG inventory update is based on the past experiences and helps to imparove the GHG database. This GHG inventory provides critical emission data, under the foundation of previous two national communications.

1.2.1 Objective

The main objective of this assignment is to prepare a detailed and representative report on the national GHGs inventory for Third National Communication of Nepal.

1.2.2 Scope

The scope of this study includes the following:

1. Collect baseline information and other necessary data required for GHG inventory; 2. Identify inventory data gaps and suggest the ways to overcome short comings;


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3. Revise the input data taking into consideration data gaps and areas needing improvement identified in the stocktaking exercise;

4. Describe procedures and arrangements undertaken to collect and archive data for the preparation of national GHG inventories, as well as efforts to make this a continuous process including information on the role of the institutions involved;

5. Select a methodology of the IPCC Guidelines that is relevant for Nepal in each sectors (Energy, Industrial Process, Agriculture, Land use, land use change and forest and Waste);

6. Conduct assessment for the GHG inventory using local or regional emission factors and activity data as available for the base year 2011 in each sectors (Energy; Industrial Processes and Product Use; Agriculture, Forestry, and Other Land Use; and Waste);

7. Include information on the other non-direct GHGs according to the data availability;

8. Identify and develop methods for overcoming inventory data gaps, if there are no available data;

9. Identify barriers to obtaining existing data for key sources and propose solutions; 10. Organize consultation and validation workshops; 11. Participate in the training/consultation workshop organized by PMO regarding

tools, methodologies and guidelines for GHG Inventory;

In addition to the above scope of work, this study (i) compiled GHG emissions from 2011-2014 for the estimation of CO2, N2O, CH4, NOx, CO, NMVOC, SO2 as well as for HFCs, PFCs and SF6 using 2011 as the base year; (ii) conducted quality control and quality assurance of inventory data based on IPCC Good Practice Guidance and Uncertainty Management in National GHG Inventory, including key category analysis; (iii) analyzed data using sectoral and reference approaches based on 2006 IPCC Guidelines on national inventories; (iv) established and maintained a database for CO2, N2O, CH4 and other greenhouse gases as appropriate; and (v) projected GHG emission trends up to 2030.

1.3 Framework of Inventory planning, preparation and documentation

The IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2006) is the key procedural document used for the estimation of emissions and removal of the GHGs from four sectors (Energy; Industrial Processes and Product Use; Agriculture, Forestry and Other Land Use; Waste). This guideline provides a framework of robust methodologies and approaches for developing the inventory. Furthermore, following two IPCC guidelines are considered for quality assurance.

1) IPCC Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories (IPCC, 2000);

2) IPCC Good Practice Guidance for Land Use, Land-Use Change, and Forestry (IPCC, 2003);


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Table 1.5 The 100-Year Global Warming Potential values according to IPCC Fourth Assessment Report (IPCC, 2007) used in this study.

GHG Global Warming Potential

Carbon dioxide (CO2 ) 1

Methane (CH4 ) 25

Nitrous oxide (N2O) 298

Hydrofluorocarbon (HFC-134a) 1300

Hydrofluorocarbon (HFC-23) 11,700

Tetrafluoromethane (CF4 ) 6500

Hexafluroethane (C2F6 ) 9200

Sulphur hexafluoride (SF6 ) 23,900

Figure 1.1 Preparation of GHG Inventory.

Expe

rt G

roup

Energy

Industrial Processes and Product Use

Agriculture, Forestry, and Other Land Use

Waste

TNC Project/MOPE

Working Groups

Activity Data and EF Provider

Stakeholders


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Overall procedure for preparing the national GHG inventory is presented in Figure 1.2.

Figure 1.2 Implementation Framework.


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Table 1.6 Tiers of estimation. Tier-I approach employs activity data that is relatively coarse, such as nationally or globally available estimates of deforestation rates, agricultural production statistics, and global land cover maps.

Tier-II uses the same methodological approach as Tier 1 but applies emission factors and activity data that are defined by the country.

Tier-III approach uses higher order methods, including models and inventory measurement systems tailored to address national circumstances, repeated over time and driven by disaggregated levels.

The GHG emissions are directly linked to economic prosperity of the nation and long term development goal of the country. Based on this development goal and economic prosperity of the nations, accurate GHG projections have to be done, which requires consideration of national plan on energy security, land use policy, and reforestation programs. The emission of GHGs are estimated by using methodologies consistent with those recommended in the Guidelines for National Greenhouse Gas Inventories (IPCC, 2006). The Good Practice Guidance (GPG) methodologies support the development of inventories that are transparent, documented, consistent overtime, complete, comparable, assessed for uncertainties, subject to quality control and quality assurance, and efficient in the use of resources. In addition, the IPCC guidelines and other documents are being updated regularly, which are closely followed and implemented in this assignment.

The general method for estimating GHG (IPCC, 2006) can be described as:

𝐸𝑚𝑖𝑠𝑠𝑖𝑜𝑛 = (𝐸𝐹 ∗ 𝐴𝑐)!

!

!!!

(1)

where, EF = emission factor, Ac = activity, i = various type of activities (1, 2, 3…n). EF is the quantity of GHG emitted per unit activity; for example, in the energy sector the amount of carbon dioxide emitted per unit of fuel consumed is an emission factor. Ac is the activity level measured in the units appropriate for the emission factor and Activity data refers to the magnitude of human activity resulting in emissions or removals happening during given period of time. Data on energy use, fuel consumption, land areas, lime and fertilizer use and waste generation are some of the example of activity data.

The rigor of any emission inventory relies on the quality of its activity data, the emission coefficients and inventory methodologies used (MoSTE, 2014). In this


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inventory, the authenticity of data is ensured by sourcing the primary activity data for various sectors from reports of the concerned government ministries and relevant organizations and institutions.

Choice of Emission Factor and Tier Selection

Decision trees based on 2006 IPCC standard guidelines are used for methodological choice in tier selection and key category analysis to identify key source/sink category. It is always good to look for using, the higher tier level, but due to lack of required data for calculation, tone has to solely depend on Tire I and Tier II. In the first and Second National communication, most of the calculations were based on the IPCC default values of emission factor. In this inventory, it has been tried to incorporate more information related national emission factor, else used IPCC default parameters.


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SECTOR-WISE GHG EMISSIONS AND SINKS

2. Energy

2.1 Brief summary The inventory of energy sector GHG emissions comprises estimates of emissions due to combustion of fuels in stationary and mobile sources. The stationary sources include fuel combustion in electricity generation, manufacturing industries as well as residential, commercial and agricultural activities. Mobile sources include road transport, civil aviation and railways. This section reports the emissions of GHGs including CO2, CH4, and N2O from the energy sector. The activity data and emission factors for the greenhouse gas inventory of Nepal were collected from various data sources and the data were categorized according to 2006 IPCC Guidelines. The data limitation was overcomed by appropriate interpolation. Generally, Tier 1 method with default emission factors was considered, however in some cases, like biomass stove combustion in residential sub sector, Tier 3 was used because of the availability of the emission factor for Nepal. The greenhouse gas inventory, thus prepared by using emission factors and activity data for the base year 2011 and the uncertainty in the data and methods were evaluated. The trend of greenhouse gas emissions was analyzed using the currently used emission factor for consistency. In addition, following the Government of Nepal’s vision on energy sector for the future reported in Nepal Energy Sector Vision, 2050, the GHG emissions for up to the year 2030 was projected for various scenario of economic growth and policy intervention.

2.2 Overview of the Sector Energy use and consumption emits more GHGs worldwide than any other anthropogenic activities. Burning fossil fuels such as coal, oil and natural gas converts carbon in the fuel to CO2, the predominant gas contributing to the greenhouse effect. The energy sector includes all fuel combustion-related emissions from energy industries, manufacturing and construction, transport and other source categories. According to the IPCC Guidelines (2006), emissions originating from energy activities (fossil fuel combustion and fugitive emissions) should be calculated for the sectors and subsectors shown in Table 2.1.

Table 2.1 GHG emissions source categories as suggested by IPCC (2006).

1 ENERGY 1 A FUEL COMBUSTION ACTIVITIES 1A1 Energy Industries 1A2 Manufacturing Industries and

Construction 1A3 Transportation


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1A3 A Civil Aviation 1A3 B Road Transportation 1A3 C Rail 1A4 Other Sectors 1A4 A Commercial/Institutional 1A4 B Residential 1A4 C Agricultural/Fishing 1A5 Non Specified

Memo Items International Bunkers International Aviation Information Items CO2 from Biomass Combustion for Energy Production

The Category 1B, i.e., Fugitive Emission from solid fuels, oils and natural gas has not been included because coal mining is negligible in Nepal and other gas and petroleum mining is absent. Similarly, Category 1C, i.e., CO2 Storage and Transport is also not included because of its irrelevance in Nepalese context.

2.3 Data and Methods

2.3.1 DataSources

Data collected at national level from numerous sources, including National Bureau of Statistics (CBS), Department of Transport Management (DOTM), Water and Energy Commission Secretariat (WECS), and Nepal Oil Corporation (NOC) and also from private institutions, organizations and companies that are approved and archived by the GoN was the basis and starting point for the compilation of the inventory. Additional and/or missing data, required to meet the level of disaggregation for higher than the Tier I level, was sourced from both public and private institutions.

The petroleum products sold in Nepal, as given by the data of NOC, was utilized to estimate the total CO2 emissions from petroleum (fossil fuel) products. However, sectoral scenario cannot be represented solely by this data because there is substantial use of diesel and petrol in other sectors, particularly in backup power generation, in recent years. Therefore, the information of channelization of the petroleum products to different sectors should be known. There have been recent studies on the use of petroleum product in power generation and industries. Those publications were also referred to. The data source is summarized in the Table 2.2.


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Table 2.2 A list of activity data and data Source.

Category Sub-Category Data Need Data Source

1A Fuel Combustion Activities

1A1 Energy Industries

Amount of energy produced by power plants

Nepal Electricity Authority (NEA)

1A2 Manufacturing Industries and Construction

Amount of Energy consumed by the industries, fuel supplied to the industries and specific fuel consumption per unit of product

CBS, NOC, WECS, Ministry of Energy, and GIZ (Deutsche Gesellschaft für Internationale Zusammenarbeit)

1A3 Transportation

Civil Aviation NOC

Road Transport DOTM, WECS

Rail WECS

Other Sectors

Commercial/Institutional Ministry of Energy, GIZ and WECS

Residential WECS

Agriculture and Fishing WECS

2.3.2 MethodologyThe guiding documents in the inventory’s preparation are the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2006), the Revised Supplementary Methods and Good Practice Guidance Arising from the Kyoto Protocol (IPCC, 2014). The 2006 IPCC Guidelines provide a number of possible methodologies for calculating emissions or removals from a given category. The methodologies are given in the forms of ‘tier’ which includes various levels of detail at which estimates can be made. The choice of method depends on factors such as the importance of the source category and availability of data. The methods for estimating emissions and/or removals are distinguished between the tiers as follows:

• Tier 1 methods apply IPCC default emission factors and use IPCC default models • Tier 2 methods apply country-specific emission factors and use IPCC default

models

• Tier 3 methods apply country-specific emission factors and use country-specific models.

This inventory was based on approaches as determined by Top Down Approach (Reference Approach) and Bottom Up Approach (Sectorial Approach) using the IPCC Tier 1 framework and default values for conversion and emission factors.


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Top Down Approach This approach uses the data of country’s energy supply to estimate the emissions of CO2 from combustion of fossil fuels. For this, data from Nepal Oil Corporation (NOC), which is the sole entity responsible for the import and distribution of all petroleum products in the country, except for fuel oil (FO), is used. The main fossil fuels imported in Nepal are petrol (gasoline), diesel, kerosene, air turbine fuel (ATF), FO, low speed diesel (in a very small amount), and liquefied petroleum gas (LPG). Various industries and business entities also import coal to be used mainly in brick kilns and cement industries. The Central Bureau of Statistics (CBS) provided the data of coal imports. In this case, since the amount of coal combustion is not known, the value of coal import is used to calculate the emissions using the reference approach. Bottom Up Approach In the bottom up approach, all of the selected data sources identified were the major energy-consuming sectors, including industries and commercial institutions. There is no comprehensive database available in Nepal that could provide the fuel consumption by all the sources in various sectors. Fuel consumption by each sectors were identified along with the fuel types. Relevant sectors were identified according to the IPCC 2006 Guidelines, however the sectors were not strictly adhered to as the sectors mentioned in the guidelines might not be relevant in the context of Nepal. On the other hand Nepal has some industries including brick and cement, which have significantly large contribution to GHGs emissions. These are specifically included in the list. The consumption of fuel was estimated either from the energy statistics provided by Central Bureau of Statistics (CBS) or from the report on energy consumption pattern of the selected sectors and subsectors or from NOC sales data, whichever appropriate. While preparing the GHG Inventory, only direct GHGs, namely CO2, CH4, and N2O from key sources were prioritized. Other indirect GHGs including CO, NOx, NMVOC, and SOx were excluded because of unavailability of data and detailed information, for instance, vehicular fleet plying on the street, vehicle age, engine size, emission control technology, fuel used, vehicle kilometer travelled. In the case of Nepal this is further complicated because of tempering or malfunctioning of emission control systems, fuel adulteration or poor fuel quality, overloading and poor maintenance of vehicles. Nepal has yet to develop the national circumstance that may be quite different even in the regional context.

2.4 Energy Resources and Fuel Consumption Pattern Nepal’s energy consumption per capita is low, one-third of the Asian average and less than one-fifth of the world average. In 2008-2009 total energy consumption of the country was 401,000 TJ, however compared with other countries, Nepal has high-energy consumption with respect to its gross domestic product (GDP). The annual average growth of energy consumption is 2.4% (WECS, 2010). A comparison of energy


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share by various sources is given in Table 2.3. The fuel wood has the largest share in energy distribution. During 2008-2009 fuel wood contributed to about 78% of primary energy consumption whereas other biomass resources like agriculture residue and animal dung contribute about 4% and 6%, respectively. During this period, the share of petroleum fuels was about 8% and the share of electricity in the total energy supply of the country was only about 2%.

Table 2.3 Primary energy shares in Nepal (WECS, 2010; WECS, 2014).

Energy, ‘000 GJ (% share)

Fuel Type Year 2008-09 Year 2011-12

Fuel wood 311,577 (77.7) 267,400 (71.1)

Agriculture residue 14,837 (3.7) 13,200 (3.5)

Animal dung 22,857 (5.7) 19,100(5.1)

Petroleum 32,882 (8.2) 46,200 (12.3)

Coal 7,619 (1.9) 14,800 (3.9)

Renewable and others 2,406 (0.6) 50,00 (1.3)

Electricity 8,020 (2) 10,600 (2.8)

This has somewhat changed in the recent years. The data of 2011-2012 indicates slight increase in the dependency on fossil fuel while decrease in the biomass consumption for primary energy resource. The share of fuel wood in primary energy has dropped from 77.7% to 71% (of total primary energy demand) during the period 2008/09 to 2011/12. During the same period, the consumption of petroleum products has increased by half while that of coal doubled. The increasing dependency on fossil fuel is indicated by the data of Nepal Oil Corporation, which shows a sharp rise in sales of petroleum product in recent years. This can probably be attributed to increase in economic activities after the beginning of peace process in 2007, at the same time, severe power shortages that the country has been facing which have led to extensive use of diesel generator for electric power generation. Figure 2.1 and Table 2.4 shows the sales of petroleum products in Nepal from year 2000/01 to 2014/15. It is seen that the consumption of diesel increased drastically from year 2008/09. Except for kerosene whose consumption has continuously declining, the consumption of all the other fuels has increased significantly. The decrease of kerosene consumption has been compensated by the increase in LPG consumption for cooking and electricity for lighting.


23

Figure 2.1. Sales of petroleum products in Nepal (Source: NOC, 2016).

Table 2.4 Petroleum product sales in Nepal (Source: NOC, 2016).

Figure 2.2 Share of energy from fossil fuel in Nepal in 2010/11.

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FiscalYear Petrol Diesel Kerosene ATF LPG2000/01 59,245 326,060 313,681 63,131 40,1022001/02 63,271 286,233 386,592 47,453 48,7572002/03 67,457 299,973 348,620 52,839 56,0792003/04 67,586 299,730 310,826 64,041 66,1422004/05 75,989 315,368 239,328 66,825 77,5942005/06 80,989 294,329 226,637 64,335 81,0052006/07 101,912 306,687 197,850 63,778 93,5622007/08 100,842 302,706 155,216 68,938 96,8372008/09 124,169 446,468 70,089 68,935 115,8132009/10 162,275 612,505 55,788 82,631 141,1712010/11 187,641 655,128 49,495 101,314 159,2862011/12 199,749 648,513 41,808 109,808 181,4112012/13 221,676 716,747 24,721 115,786 207,0382013/14 251,451 811,100 19,064 123,527 232,6602014/15 283,567 901,393 18,628 139,404 258,299

Petrol11%

Diesel41%

Kerosene3%

ATF6%

FurnaceOil2%

LPG13%

Coal24%


24

Figure 2.2 depicts the share of energy from fossil fuel in the year 2010/11. It has been observed that diesel fuel has the largest energy share followed by coal, and petrol. Diesel has the highest contribution because of its use in transportation, power production and thermal energy generation in industries. Coal is mostly used by cement and brick industries, which represent sectors of industries that consume high amount of thermal energy.

2.5 Issues Pertaining to the Estimation of GHG Emissions

Information on Sector-wise Fuel Consumption In order to compute the GHGs from several sectors and sub-sectors under fuel combustion activities, information on the fuel consumption in those sectors and sub-sectors should be known. Since NOC data provides data of total sales of the fuels, the fuel consumption in all the sectors is not known. This becomes more difficult in the case of diesel fuel, which is used in various sectors including industries, agriculture, and power production. Similarly, in the case of LPG, some of it is used in transportation as well as in commercial sector. In case of petrol (gasoline), majority of the fuel is consumed in transportation sector and only a small portion is used in commercial sector, agriculture and industries. So, every kind of information related to energy consumption in industries, transportation and commercial sectors was referred to. Appropriate interpolation technique was used for missing. All the petroleum fuel, except for fuel oil (FO), imported and sold in Nepal is the sole responsibility of NOC. Other private companies also import and supply of FO to the limited type of industries using the fuel. It is difficult to know exact amount of FO consumed. In this case, the data of thermal energy consumption by various industries was considered. On the basis of fuel shares by the industries, the amount of FO was estimated. Use of Biomass in Industries and Other Sectors Major thermal energy requirement of residential, industrial, commercial sector in Nepal is met by biomass. In this inventory the emission from biomass consumed in all the relevant sectors has been computed but neither added nor compared with the emissions from other fuels assuming that CO2 emission due to biomass combustion is assumed to be neutralized through regeneration. The CO2 emission has been reported as Information Item in the inventory. However, the non-CO2 emissions from biomass combustion (CH4 and N2O) have been incorporated and added in the national GHG emissions.

2.6 GHG Emission for the Base Year 2011 Energy Sector accounts for about 14,703 Gg of GHG emission (CO2-eq) in Nepal. The various contributors to the GHG emissions within this sector are summarized in Table 2.5. It can be seen from the table and Figure 2.3 (a) that manufacturing industries are the largest contributor to the CO2 emission followed by Transport and Other Sectors. The contribution of Energy Industries is the lowest, however when the total GHG


25

emission is compared (Figure 2.3 (b)), the Other Sector has the largest contribution. The Other sector includes commercial, institutional, and residential sub sectors, which burns large amount of biomass (in domestic stoves, heating furnaces and open fires) due to which, significant amount of CH4 and N2O are released along with CO2. This contributes to considerable portion of GHG released by energy sector. The amount of CO2 emitted by biomass combustion for energy related activities is substantially higher than fossil fuel combustion (34,990.76 Gg vs. 4678.20 Gg). However, the former is not added to the national emission total. High amount of CH4 and N2O emissions form biomass result into high national GHG emissions (14,702.85 Gg).

Table 2.5 Summary of GHG emissions from Energy Sector for 2011.

(a) (b) Figure 2.3 (a) Share of CO2 (in Gg) by various energy sectors, and, (b) CHG emissions (CO2

eq in Gg) by various energy sectors.

EMISSIONSUMMARYCategories CO2 CH4 N2O CO2eq1ENERGY Tonnes Gg1A FuelCombustionActivities1A1 EnergyIndustries 2,376.07 0.09 0.02 2.381A2 ManufacturingIndustriesandConstruction 2,237,336.52 321.60 55.54 2,261.931A3 Transport 1,708,915.97 274.28 79.72 1,739.531A4 Others 729,575.70 353,996.88 3,756.76 10,699.01GRANDTOTAL(inTonnes) 4,678,204.27 354,592.86 3,892.04 14,702.85GRANDTOTAL(inGigagram) 4,678.20 354.59 3.89 14,702.85

Categories CO2 CH4 N2O CO2eqMEMOITEMS Tonnes Gg

InternationalBunker 172,507.58 1.21 4.83 173.98

Categories CO2 CH4 N2O CO2eqINFORMATIONITEMS Gg

CO2fromBiomassCombustionforEnergyProduction(Gg) 34,990.76

EnergyIndustries

0%

ManufacturingIndustriesandConstruction

17%

Transport13%

Others70%

EnergyIndustries

0%

ManufacturingIndustriesandConstruction

48%Transport

36%

Others16%


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Table 2.6 Energy Sector GHG emissions inventory for 2011.

The GHG emission by various sub-sectors within the Energy Sector is elaborated in Table 2.6. Each subsector is discussed in subsequent sections.

Energy Production Emissions from the energy industries include emissions from fossil fuel combustion for electricity generation and solid fuel manufacturing. The later source is not significant in case of Nepal. There are two major fossil fuel-based energy production plants owned by Nepal Electricity Authority: Bansbari Multifuel Power Plant (39 MW) and Hetauda Diesel Power Plant (14.5 MW). These power plants are used during peak load hours. In 2010/2011 the Bansbari and Hetauda plants generated 2348 and 1333 MWh of electric power, respectively, which contributed to 2.38 Gg of GHGs. This amount is less than one percent of GHG from Energy Sector.

Apart from those power plants, large diesel generators were used by Manufacturing Industries and Other Sectors for back-up electricity as the country was facing a significant power deficit (6-12 hours of load shedding per day). The contribution of GHGs from power generation is reported in the Manufacturing Industries sub sectors.

Transportation Sector

Categories CO2 CH4 N2O CO2eq1ENERGY Tonnes Gg1A FuelCombustionActivities1A1 EnergyIndustries 2,376.07 0.09 0.02 2.381A1a ElectricityProduction 2,376.07 0.09 0.02 2.381A2 ManufacturingIndustriesandConstruction 2,237,336.52 321.60 55.54 2,261.931A2a IronandSteel 78,596.67 2.34 0.83 78.901A2b SoapandChemicals 6,017.50 0.24 0.05 6.041A2c Cement 390,937.99 4.97 5.98 392.841A2d Brick 1,485,912.94 16.52 23.35 1,493.281A2e PulpandPaper 3,159.22 0.13 0.03 3.171A2f FoodandBeverages 272,712.20 11.00 2.20 273.64

NonCO2emissionsfrombiomasscombustioninindustries 286.40 23.11 14.051A3 Transport 1,708,915.97 274.28 84.55 1,740.971A3a CivilAviation1A3ai InternationalAviation 172,507.58 1.21 4.83 173.981A3aii DomesticAviation 83,059.02 0.58 2.32 83.771A3b RoadTransport1A3bi Bus 319,838.79 16.83 16.83 325.281A3bii Minibus/Microbus 148,826.13 7.83 7.83 151.361A3biii Truck/Tanker/Lorry 499,365.55 26.28 26.28 507.851A3biv Car/Jeep/Van/Pickup 449,596.29 141.00 21.87 459.641A3bv ThreeWheelers 30,488.55 14.89 0.92 31.141A3bvi Tractors/other 34,658.25 1.82 1.82 35.251A3bvii Twowheelers 135,767.73 64.65 6.27 139.251A3bviii Train 7,315.66 0.39 0.39 7.441A4 Others 729,575.70 353,996.88 3,756.76 10,699.011A4a Commercial/Institutional 129,295.52 4.92 0.99 129.711A4b Residential 300,742.38 5.60 0.69 301.091A4c Agriculture 299,537.81 12.14 2.43 300.56

NonCO2emissionsfrombiomasscombustioninothersector 353,974.23 3,752.66 9,967.65

MEMOITEMSInternationalBunker 172,507.58 1.21 4.83 173.98BiomassCombustion 34,990,760.00


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Transportation sector in Nepal has shown significant growth in recent times. Accounting for 90% of the movement of passengers and goods, road transportation is predominant mode of transport. Figure 2.4 shows the trend of yearly vehicle registration since 2000/01. The numbers of all the vehicle categories are increasing significantly. From the year 2000/01 to 2015/16 the registration per year of passenger cars and SUV increased by about 6 times (see Table 2.7). During the same period the motorcycle registration increased to about 10 folds.

Figure 2.4 Vehicle registration trend in Nepal from 2000/01 (Source: www.dotm.gov.np).

Table 2.7 Number of vehicles registered in Nepal (Source: www.dotm.gov.np).

Diesel is the main fuel consumed by the transportation sector in Nepal followed by petrol and LPG. This sector consumes about 68% of total diesel consumption in Nepal. This sector alone emits 1,741 Gg of CO2-eq of GHG, which is 37% of the total GHG emission. The contribution of various sub-sectors in transportation in CO2 emission is

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2000/01 1203 250 1271 5152 0 0 232 29291 35192001/02 868 475 1798 4379 0 0 248 36117 31892002/03 432 298 1212 2906 581 232 17 29404 24852003/04 732 237 1477 7079 478 884 16 26547 21912004/05 753 285 1592 4781 0 584 48 31273 13742005/06 1528 663 2263 5114 36 66 60 44610 6352006/07 1564 806 3278 5156 736 138 12 72568 29422007/08 1419 1179 3594 4741 1588 31 18 68667 32972008/09 1843 593 3643 6857 1287 128 20 83334 46632009/10 1888 780 4524 12268 1975 145 9 168707 114602010/11 1610 1370 1969 8510 3087 115 2 138907 79372011/12 2085 1170 1333 8711 2981 155 10 145135 84132012/13 3263 1328 3332 9595 5422 158 57 175381 97952013/14 2776 1412 2789 11372 5668 178 17 163945 100702014/15 3737 2270 4236 13560 6057 932 1541 196383 105242015/16 4353 4625 8328 28361 5060 1137 2613 267439 9786


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shown in Figure 2.5. From the figure it is seen that the heavy commercial vehicle category (truck, fuel tanker and lorry) emits about 500 Gg of CO2 followed by car, SUV and pickup category which contributes about 450 Gg of CO2. Bus and minibus/microbus category is the next largest emitters. The lowest contributor is the rail transportation with about 7.5 Gg of CO2.

Figure 2.5 CO2 Emissions from various land transport modes.

Figure 2.6 CO2 emissions share by subsectors under Transportation Sector.

Figure 2.6 shows the percentage share of CO2 emissions by different subsectors under Transportation Sector. It is to be noted that the international aviation has been excluded here. Manufacturing Industries and Construction Industrial sector in Nepal is not very developed because of lack of internal and external investments. The major industries are related to brick, cement and metal manufacturing industries along with food and beverage industries. This sector uses both thermal and electrical energy. For thermal energy, the industries use biomass, coal, and fuel oil. According to Water and Energy Commission Secretariat, coal, fuel wood and diesel contribute to 46.24%, 24%, and 15% of total energy required by the Industrial sector, respectively, all of which are higher than that supplied by electricity (13.6%) (WECS, 2014). A small amount of kerosene and LPG is also used. Diesel is basically used for

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DomesticAviation5%


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captive electricity generation because of severe power shortage. Among the total energy required in this sector, 10% is for backup electrical power generation and rest is for thermal energy. In this inventory, the emission from fuel wood used by various categories of industries in not compared due to unavailability of reliable data on fuel wood use in the industries. However, the total energy from fuel wood to the industrial sector is available and has been mentioned as Information Item. Non-CO2 emissions have been included in the inventory. Figure 2.7 compares the share of fuel type (fossil fuel-based) in this sector in the year 2011.

Figure 2.7 Share of fuel type (fossil fuel) in Manufacturing Industries and Construction.

Figure 2.8 CO2 emissions (tonnes) share by subsectors under Manufacturing Industries

and Construction.

Manufacturing Industries emit 2,248 Gg of CO2e. It is the largest contributor of CO2

(48%) under Energy Sector, however when total GHG is compared, it is the second largest contributor (17%). In this case construction sector is not included because of unavailability of proper data on the status of heavy equipment and construction machineries operation. A separate survey has to be carried out in this regard. As presented in Figure 2.8, brick industries are the largest contributor to CO2 emission in this sector with 1493 Gg of CO2 (66%) followed by cement industries (18%), food and beverages (12%) and metal (4%). Soap and Chemical and Pulp & Paper industries have the lowest contribution, both of which are less than 1%.

Coal79%

Diesel13%

FO4%

LPG0% Kerosene

4%

CEMENT, 390,938 PULP&PAPER,3,159

FOOD&BEVERAGES, 272,712

METAL,78,597

SOAP&CHEMICAL,6,017

BRICK,1,485,913


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Other Sectors Other Sectors includes Residential, Commercial and Agricultural subsectors. Total GHG emission from this sector is 729 Gg of CO2, which is 16% of the total CO2 emissions due to Fuel Combustion Activities. In terms of total GHG emissions, this sector has the largest contribution with 9,328 Gg CO2-eq (70% of the total GHG emissions) as this sector emits large amount of CH4 and N2O as a result of biomass combustion.

Figure 2.9 CO2 emissions (in tones) share by subsectors under Other Sectors.

Residential Subsector: Nepalese Residential Subsector depends primarily on biomass for its primary energy need, basically for cooking and heating, however due to rapid urbanization, there has been shift from traditional energy dependence towards fossil fuel, i.e., LPG (and kerosene). It is also seen in recent years that the rate of biomass consumption is slowing down and being compensated by LPG. This subsector emits 301 Gg of CO2. The emission from biomass (fuel wood) is not included here and it is reported as Information Items. Hotel Subsector: Hotels use fuels including coal, diesel and LPG for heating, and diesel and kerosene for backup electric power. In total, this subsector emits129.7 Gg of CO2. Agriculture Subsector: Most of the agriculture activities in Nepal are carried out in traditional way, however in recent years, the mechanization is increasing especially for tillage and threshing activities. Diesel is the major fuel used in this subsector (95% of the total energy input). This subsector emits 300 Gg CO2.

2.7 Trends in Greenhouse Gas Emissions A comparison has been made with regard to GHG emissions since the First National Communication. In order to have consistent data for comparison, the reported energy consumption scenario in the First National Communication and Second National Communication has been combined with the emission factors that have been used in this report. Figure 2.10 shows comparison of CO2, CH4 and total GHG (CO2-eq).

HotelSector,127,796.23

ResidentialSector,300,742.38

AgricultureSector,299,537.81

ColdStorage,1,499.29


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Figure 2.10 CO2, CH4, and Total GHG emissions trends in different inventory reporting reference years.

It is clear from the figure that CO2 emission has been increasing sharply over the years. It is to be noted that the CO2 emission mentioned here is only the result of fossil fuel combustion. The consumption of fossil fuel is increasing considerably in recent years, so the CO2 emission is increasing. The non-CO2 emissions (e.g., CH4), however, does not match with the trend of CO2 emission. Since the majority of CH4 and N2O emissions is due to the biomass combustion, the rate of consumption of which has not increased as drastically compared with fossil fuels. In fact, in recent years, the rate of increment in biomass consumption is gradually slowing down.

2.8 GHG Emission Projection The total energy consumption in the year 2010/11 has been estimated to be 376.3 million GJ, dominated largely by the use of traditional non–commercial forms of energy such as fuel wood, agricultural residue and animal wastes. For the GHG emission

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projection purpose, the following scenarios have been considered according to the Government of Nepal’s vision on energy sector for the future reported in Nepal Energy Sector Vision, 2050:

• Business- as-Usual (BAU): GDP growth rate according to low growth case, i.e. with an average GDP growth rate of 4.4%. The shares of each demand technology in the energy supply in future years are considered to be invariant, i.e., energy mix of total demand will be as similar to that of the base year.

• Medium Growth Scenarios: GDP growth rate according to Base case, i.e. with an average GDP growth rate of 5.6%. The shares of each demand technology in the energy supply in future years are considered to be invariant, i.e., energy mix of total demand will be as similar to that of the base year.

• High Growth Scenarios: GDP growth rate according to high growth case, i.e. with an average GDP growth rate of 6.5%. The shares of each demand technology in the energy supply in future years are considered to be invariant, i.e., energy mix of total demand will be as similar to that of the base year.

• Combined Policy Intervention Scenario: GDP growth rate according to medium growth rate i.e. 5.6%. Few intervention that have been considered are:

• Replacement of traditional and fossil fuels by clean energy alternatives – electricity, LPG, and ICS.

• Promotion of electrification in all 5 sectors for lighting, heating and other purposes.

• Intervention through more efficient process technologies in industries

• Intervention through mass transportation systems

• Introduction of new electric and bio-fuel transportation technologies

The LEAP Software was used to estimate, the projected energy demand and corresponding emissions under different scenarios. The Projection of emissions is shown in Figure 2.11.

It is observed that GHG emissions can be significantly reduced with combined policy interventions.


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Figure 2.11 Total GHG emissions projection under various scenarios.

2.9 Perspectives for Improvement For more accurate estimation of the GHG emissions, data on the energy consumption by various sectors should be updated and managed. The information on vehicular fleet, kilometer travelled and emission factor should be established through a comprehensive research. Similarly, the data on domestic sector energy consumption, particularly fuelwood, agriculture waste should be reassessed through countrywide study.

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3. IndustrialProcessesandProductUse

3.1 Brief summary

In this inventory, the emission CO2, N2O, HFC, NOx, NMVOC, CO, and SO2 were computed from the Industrial Processes and Product Use (IPPU). The activity data and emission factors for the greenhouse gas inventory of Nepal were collected from various data sources and the data were categorized according to 2006 IPCC guideline. The data requirements were analyzed and listed for the entire inventory process. The data and their quality were extensively checked and properly documented for integration with other sectors. Appropriate tier-based methods were employed to estimate the greenhouse gas emissions as per the limitation of the data collected from the recommended sources. The greenhouse gas inventory, thus prepared by using emission factors and activity data for the base year 2011 was assessed and the uncertainty in the data and methods were evaluated. Additionally, the trend of greenhouse gas emissions was assessed. The estimates and the projected data of the emissions were properly checked, reviewed and reported according to the IPCC (2006) guideline. The emission data regarding non-direct GHGs were also reported using the same method.

3.2 Overview of the Sector The greenhouse gas emissions from industrial processes and product use in Nepal are considered to contribute the least to the national greenhouse gas emission of Nepal when compared to other sectors (MoPE, 2004; MoSTE, 2014). Moreover, compared to other Asian countries, Nepal has very low manufacturing value added share to GDP, however CBS (2014a) has reported a gradual recovery in the manufacturing sector, and it may contribute significantly to the national greenhouse gas emission because economic development of the country may lead to industrial emissions more than on other types of emissions (Sanchez and Stern, 2016). The mineral production sub-sector shows the highest contribution and it is mainly contributed by process-related carbon dioxide emission in cement production. Even though the methods used may be different for different years, the past trend of greenhouse gas emissions has shown an increasing trend in GHG (greenhouse gas) emissions in IPPU (Industrial Processes and Product Use) sector. IPCC (2006) guidelines for national greenhouse gas inventories, volume 3 states the following categories for industrial processes and product use sector:

• Mineral Industry • Chemical Industry

• Metal Industry

• Non-Energy Products from Fuels and Solvent Use (lubricant use, paraffin waxes, solvent, etc.)

• Electronics Industry


35

• Emissions of Fluorinated Substitutes for Ozone Depleting Substances • Other Product Manufacture and Use (electrical equipment, N2O from product

uses in medical applications, etc.)

• Others (Pulp and paper, food and beverages, etc.)

Non-energy Use category means the use of fossil fuels as feedstock, reductant or non-energy products. The cement production is the major sector contributing to the GHG emission. There were 35 cement industries in 2069 BS throughout Nepal as per the data of NEEP (2012), and the trend of cement production may be growing since then. The greenhouse gas emission is mainly observed in clinker production from the following reaction: Limestone CaCO3 + heat → CaO + CO2. Other emissions are SO2 from cement production, NMVOC from food and drink industries, NOx, NMVOC, CO and SO2 from paper industries, and Hydrofluorocarbons (HFCs), perfluorocarbons (PFCs) and sulphur hexafluoride (SF6) gases that are used as alternatives to ozone depleting substances. Since the contribution of the cement production is the most significant in Nepal, it has been considered as the major category in the IPPU sector. HFCs and PFCs are not produced from Nepal, but they are consumed in Nepal in refrigeration and other sectors. Hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs) are serving as alternatives to ozone depleting substances (ODS). The Montreal Protocol does not control HFCs and PFCs as they do not contribute to depletion of the stratospheric ozone layer, however they have high global warming potentials (GWPs) and long atmospheric residence times. The category of non-energy products from fuels and solvent use reports emissions from the first use of fossil fuels as a product for primary purposes other than combustion for energy purposes and use as feedstock or reducing agent. The products covered here are lubricants, paraffin waxes, bitumen/asphalt, and solvents. The products that have been covered in this assessment include lubricants and paraffin wax. Lubricants are mostly used in industrial and transportation. They can be subdivided into (a) motor oils and industrial oils, and (b) greases, which differ in terms of physical characteristics (e.g., viscosity), commercial applications, and environmental fate. For calculating CO2 emissions the total amount of lubricants lost during their use is assumed to be fully combusted and these emissions are directly reported as CO2 emissions. Since there are no lubricant-producing companies in Nepal, import data obtained from the Department of Customs (DoC, 2012) and other annual reports, was used. Paraffin wax category includes such products as petroleum jelly, paraffin waxes and other waxes. Paraffin waxes are separated from crude oil during the production of light (distillate) lubricating oils. Paraffin waxes are categorized by oil content and the amount of refinement.


36


3.3.1 DataSources

Table 3.1 provides the categories of data and the corresponding sources for estimating the greenhouse gas emissions from industrial processes and products used in Nepal. Several governmental (national level) and global data sources are used to assure the quality of the GHG estimates.

Table 3.1 Overview of IPPU categories, activities, and data sources.

Category Subcategory GHG Required data

Analysis technique (T1, T2, T3)

Data Sources

2A. Mineral Industry

2A1 Cement Production

CO2, SO2

Clinker production data, cement production data, national import and export data of clinker and cement

T1 and T2

CBS (2014b), DoC (2012) and other annual reports, DoI-Nepal (2011) and other annual reports, MoF (2011) and other annual reports, MoSTE (2014), NEEP (2012), TEPC (2017), UCIL (2016), USGS (2016)

2A2 Lime Production CO2 Lime production data T1 No data for base year

2C. Metal Industry

2C1 Iron and Steel Production

NMVOC, NOx, SO2, CO

National iron and steel production data

T1 MoF (2011) and other annual reports

2D. Non-Energy Products from Fuels and solvent Use

2D1 Lubricant Use CO2

National data for non-energy uses of lubricants, motor oils and greases in transportation and industries

T1 DoC (2012) and other annual reports, TEPC (2017)

2D2 Paraffin Wax Use

CO2 National data for non-energy uses of paraffin waxes

T1 DoC (2012) and other annual reports, TEPC (2017)

2F. Product Uses as Substitutes for Ozone Depleting Substances

2F1 Refrigeration and Air conditioning

HFCs National import data of refrigerants

T1 MOPE (2017)

2G. Other Product Manufacture and Use

2G3 N2O from product uses

N2O National import data of nitrous oxide cylinders

T1 DoC-India (2017)

2H. Other 2H1 Pulp and Paper Industry

NMVOC National paper production data

T1 MoF (2011) and other annual reports, NEEP (2012)

2H2 Food and Beverages Industry

NMVOC National food and beverage production data

T1 MoF (2011) and other annual reports, NEEP (2012)

Notes: a) The categories are classified according to IPCC (2006) guideline. b) T1, T2 and T3 are tier 1, tier 2 and tier 3 methods of IPCC (2006) guideline. c) Past lime production data is available from USGS. But the lime production is available only till 2003.


37

3.3.2 Methodology

The IPCC (2006) guideline has been used to estimate the GHG emissions for each of the categories in the IPPU sector. Table 3.1 gives the analytical techniques for each of the categories of IPPU sector. Since cement production has been selected as the major category in the IPPU sector, Tier 2 method prescribed by the IPCC (2006) guideline is the preferred method for calculating the greenhouse gas emissions from this category. Tier 1 method has been employed and Tier 2 method has been used where the clinker production data are available. For other categories, the Tier 1 method has been used with the combination of mass balance approach and emission-factor approach. i) Choice of Emission Factors Most of the emission factors have been obtained from the IPCC emission database and European Monitoring and Evaluation Program/European Environment Agency emission (EMEP-EEA) database (Table 3.2). These sources of emission factors are used throughout the estimation since national emission factors are generally not available for Nepal. Emission Factors for Cement Production

Tier 1 Method Good practice guideline given by IPCC (2006): use a default CaO content for clinker of 65 percent EFclc = 0.51 • 1.02 (CKD correction)=0.52 tonnes CO2/tonne clinker

EFclc: emission factor for clinker in the particular cement, tonnes CO2 /tonne clinker

CKD: Cement kiln dust Tier 2 Method Good practice guideline given by IPCC (2006): estimate emissions from lost CKD based on a default value of 1.02. If a significant fraction of CaO in a cement plant is coming from a non-carbonate source (e.g., fly ash), then this component of CaO is first subtracted as per the IPCC (2006) guideline.


38

Table 3.2 IPPU's subcategories and emission computation.

Category Emission factor Data source

Iron and steel g NOx / tonne of produced steel

g NMVOC/tonne of produced steel

g CO/tonne of

produced steel

g SO2/tonne of

produced steel

Iron and steel (rolling mills)

40 30 1 45 IPCC-EFDB (2007)

Food kg NMVOCs/tonne food production

Margarine and solid cooking fats

10

EMEP-EEA (2016)

Cakes, biscuits and breakfast cereals

1

EMEP-EEA (2016)

Sugar 10

EMEP-EEA (2016)

Animal feed 1

EMEP-EEA (2016)

Beverage kg NMVOCs/hL beverage production

Beer 0.035

EMEP-EEA (2016)

Spirit, vodka 15

EMEP-EEA (2016)

kg NMVOCs/tonne dried pulp

Paper and pulp

3.7

EMEP-EEA (2016)

ii) Key Categories All the data sources including the first national communication and second national communication reports have shown that cement production is the major process that contributes to the GHG emissions in IPPU sector. Hence cement production is the obvious choice for the key category. iii) Activity datasets The activity datasets are obtained from the data sources given in Table 3.1. Table 3.3 shows the cement production data. The clinker and cement production data are obtained from different sources. Since the Tier 1 method of estimation requires the production as well as data of clinker and cement import, NEEP (2012) dataset was found the most reliable source of activity data because it contains the cement production data for the base year of 2011 from all the limestone-based industries. NEEP (2012) surveyed all the 8 limestone-based industries and 18 clinker-based cement industries. If limestone-based industry data are used, it is not necessary to remove the


39

imported clinker from the production. In the clinker-based industries, the clinker is imported and hence, the GHG emission during such clinker formation outside of Nepal has to be deducted from the cement production in Nepal. CBS (2014b) data is available for fiscal year 2011-2012 and it has been used to validate the cement production data from other sources. Import and export data was taken from Customs Datasheet and TEPC (2017). The longest record of national cement production is provided by the Economic Survey (MoF, 2011 and other annual Economic Survey Reports). But the comparison with other datasets show significant underestimation of cement production. Hence, the method used in Second National Communication (MoSTE, 2014) has been used to estimate GHG emissions from the cement industries by using only the cement production data. Since the imported clinker is not considered in this method, the real GHG emission may be still lower than the calculated values. The USGS (2016) data is also used to compare the production of cement with global datasets. Several USGS annual reports have different revised cement production data for Nepal and the continuous increase in cement production is clearly visible from 2009 onwards in the dataset.

Table 3.3 Annual cement productions in Nepal from different data sources.

Year

Cement production (tonnes)

From only the

limestone–based

industries

From all industries

NEEP

CBS MoF USGS 1987–1988

215010

1988–1989

217666

1989–1990

101179

1990–1991

135897

1991–1992

237327

1992–1993

247891

1993–1994

315514

1994–1995

326839

1995–1996

309466

1996–1997

226681

1997–1998

139080

1998–1999

190588

1999–2000

205835

2000–2001

215098

2001–2002

233000

2002–2003

310589

2003–2004

279412

2004–2005

610044

2005–2006

613643 300000

2006–2007

644325 295000 2007–2008

71132 295000

2008–2009

71000 295000


40

2009–2010 604480

72100 1360000 2010–2011 709003

84130 2200000

2011–2012

1627072 92543 2700000 2012–2013

86654 3000000

2013–2014

Data sources: NEEP: Nepal Energy Efficiency Programme (NEEP, 2012) CBS: Central Bureau of Statistics (CBS, 2014b) MoF: Ministry of Finance, Nepal (MoF, 2011) and other annual reports USGS: U.S. Geological Survey (USGS, 2016)

Table 3.4 shows the cement and clinker production data of Udayapur Cement Industry Limited, which can be used to calculate the GHG emissions by both Tier 1 and Tier 2 methods.

Table 3.4 Annual clinker and cement production of Udayapur Cement Industry

Limited.

Year Clinker production (tonnes)

Cement production (tonnes)

2005-2006 2006-2007 2007-2008 2008-2009 2009-2010 2010-2011 2011-2012 2012-2013 2013-2014 2014-2015 2015-2016

75781 110015 78426 57542 70020 73060 54530 74515 81015 76090 65135

79556.4 115509.2 82356.1 60429.6 73513.4 76701.2 57269.5 78253.6 85072.7 79889.0 68385.2

Data source: Udayapur Cement Industry Limited (UCIL, 2016)

Table 3.5 shows the iron and steel activity data of Nepal. Other activities for the categories in Table 3.1 are also available.

Table 3.5 Annual iron and steel production in Nepal.

Year Iron and steel production (tonnes)

1987-1988 1988-1989 1989-1990 1990-1991 1991-1992 1992-1993 1993-1994 1994-1995

25625 34834 36339 45631 59661 60316 71023 95118


41

1995-1996 1996-1997 1997-1998 1998-1999 1999-2000 2000-2001 2001-2002 2002-2003 2003-2004 2004-2005 2005-2006 2006-2007 2007-2008 2008-2009 2009-2010 2010-2011 2011-2012 2012-2013

91583 107346

91291 106646 131354 135951 140000 163940 169310 166451

35340 40641 35340

Data sources: Economic Survey, Ministry of Finance, Nepal (MoF, 2011) and other annual reports.

iv) Filling Data Gaps In the annual activity data of different industrial sectors, several data sources were investigated to fill the gaps in some of the production and import data. The existing gaps in the clinker production data is partially fulfilled by using the clinker production data of Udayapur Cement Industry Limited. The import of refrigerants used as substitutes of ozone depleting substances in Nepal is also partially obtained from the Ministry of Population and Environment (MoPE, 2017). It is also difficult to find the changes in demand for cement in Nepal. An approximate rate of the change of such cement demand was obtained from Nepal Cement Manufacturers' Association (2016). Though the former Tier 1 approach for estimating ‘potential’ emissions related to the consumption of HFCs, PFCs and SF6 is not recommended as a method for estimating HFCs, PFCs or SP6 emissions, this approach has been used due to the insufficiency of data for the application of other methods of calculating the actual emissions. Potential emission calculation could be helpful to monitor the use of the substitutes of ozone depleting substances. The use of nitrous oxide (N2O) in medical applications could not be quantified directly from the Department of Customs because the import of N2O was possibly lumped under the miscellaneous category. Consequently, the export data of N2O from India to Nepal was used to estimate the potential emission of N2O in Nepal. v) Data Quality Control and Quality Assurance The emission data in IPPU sector was checked and verified with the existing national inventory and activity data. The data was also checked with the trends of Nepal as well as other countries in the Asian region. The quality of the emission data was verified by comparing with other databases such as the regional and global datasets such as the Emission Database for Global Atmospheric Research (EDGAR, 2010) version 4.2. It is extensively used to obtain global anthropogenic emissions of greenhouse gases - CO2,


42

CH4, N2O, HFCs, PFCs and SF6 and precursor gases, and air pollutants CO, NOx, NMVOC, SO2. The EDGAR data is available at national level as well as in gridded format for several emission categories. The uncertainties in the emission factors and activity data was assessed using the IPCC (2006) guidelines. For the cement production category, the uncertainties inherent in the fraction of clinker in cement under Tier 1 method were assessed. The quality of the data sources was assessed by detailed comparison of available datasets. It is assumed that all imports such as N2O and lubricants are consumed in the same imported year. With this assumption it is likely that unused materials in the previous year is consumed in the following year.

3.4 GHG Emissions for the base year 2011 Table 3.6 shows the GHG emissions from industrial processes and product uses in Nepal for the base year of 2011. Though HFC data are not available for 2011, the HFC database of MoPE (2017) from 2013 onwards would be vital in future estimations of GHG emissions. Moreover, the HFC dataset is only the potential emission that may be actually emitted only after several years. The GHG emissions and precursor emissions are reasonably within the expected values. Since cement production is the major category, the NEEP (2012) dataset, with its detailed survey of all the limestone-based cement industries, was chosen to estimate the base year emissions. Similar to the previous National Communication reports of Nepal, the cement production is the most dominant category in IPPU sector for GHG emissions in Nepal with 92% contribution to the total GHG emissions of IPPU sector (Figure 3.1).


43

Table 3.6 Greenhouse gas emissions from the IPPU sector in base year 2011.

Category CO

2

(Gg) N

2O

(Gg)

HFC (kg) CO2-

equivalent (Gg)

NOx

(Gg) NMVOC

(Gg) CO (Gg)

SO2

(Gg) R134a R404a R407a R410a

Cement production

350.2

350.2

0.21

Iron and steel production

0.0014 0.0011 0.0000 0.0016

Product uses as substitutes for ozone depleting substances

7475.2 218 565 5085 23.4

N2O from

product uses

0.0035

1.0

Non-energy products from fuels and solvent use 5.2

5.2

Paper production

0.1457

Food and beverage production

5.8319

Total 355.4 0.0035 7475.2 218.0 565.0 5085.0 379.8 0.0 6.0 0.0 0.2

Notes:

a) HFC data is not the actual emission but only the potential emission. b) Since the HFC data is not available for 2011, the year 2013 has been taken as the base year for this category.

c) GWP values for 100-year time horizon are taken from IPCC Fourth Assessment Report. GWP values of N2O, R-134a (HFC-134a), R-404A, R-407A and R-410A are taken as 298, 1430, 3922, 2107, and 2088.


44

Figure 3.1 Contribution of different categories on total GHG emission of IPPU sector in Nepal for the base year 2011.

3.5 Trend in Greenhouse Gas Emission The trend of CO2 emission from cement production at Udayapur Cement Industry Limited shows a significant match between the Tier 1 and Tier 2 calculation methods (Table 3.7 and Figure 3.2). The comparison of the Tier 1 and Tier 2 emissions shows that the assumption of 95 percent clinker in cement of Nepal is justified. The CO2 and SO2 emissions from the cement production category are estimated for different data sources in Table 3.8 and Figure 3.3. Except for MoF dataset, all the datasets use IPCC (2006) method by deducting the clinker import from the total cement production in Nepal. The MoF dataset has underestimated the cement production from the beginning, this may highly underestimate the GHG emission when the imported clinker is deducted from the production of cement. If we compare other dataset of CO2 emissions, we see a clear indication of high rate of increase from around 2010 onwards. The global carbon database of Carbon dioxide Information Analysis Center (CDIAC, 2016) also exhibit this trend, but at a higher rate than others. This may be due to the use of the cement production data without incorporating the import of clinkers to Nepal. The NEEP (2012) dataset, only limestone-based industries were considered in the calculation. Hence, the import of clinker was not needed. Thus the rate of increase in CO2 emissions in NEEP is lower than that in the use of CDIAC dataset, hence the emissions from NEEP (2012) dataset can be used with high confidence. The trend of the emission of precursor gases like NOx, CO, SO2 and NMVOC (Table 3.9), potential HFC emissions (Table 3.10) and N2O emissions (Table 3.11 and Figure 3.4) are also reported. They do not show any definite changing trend as compared to the CO2 emissions. The precursor gases may lead to formation of secondary air pollutants such as ozone and sulfate particles. The contribution of non-energy uses of

92%

0%2%

6%

Cementproduction

N2Ofromproductuses

Non-energyproductsfromfuelsandsolventuse

Productusesassubstitutesforozonedepletingsubstances


45

paraffins and lubricants to emission of CO2 has also shown a relatively constant trend (Table 3.12).

Table 3.7 Annual CO2 emission from Udayapur Cement Industry Limited.

Year CO2 emission (Gg)

using Tier 1 method

CO2 emission (Gg) using Tier 2

method

2005-2006 2006-2007 2007-2008 2008-2009 2009-2010 2010-2011 2011-2012 2012-2013 2013-2014 2014-2015 2015-2016

39.3 57.1 40.7 29.9 36.3 37.9 28.3 38.7 42.0 39.5 33.8

39.4 57.2 40.8 29.9 36.4 38.0 28.4 38.8 42.1 39.6 33.9


46

Table 3.8 Annual emissions of air pollutants from the cement industries in Nepal.

Year

CO2 emission (Gg)

SO2 emission (Gg)

Using IPCC (2006) method



NEEP CBS USGS

MoF

NEEP 1987–1988

101.8

1988–1989

103.1

1989–1990

47.9

1990–1991

64.4

1991–1992

112.4

1992–1993

117.4

1993–1994

149.4

1994–1995

154.8

1995–1996

146.6

1996–1997

113.0

1997–1998

69.3

1998–1999

95.0

1999–2000

102.6

2000–2001

107.2

2001–2002

116.2

2002–2003

154.8

2003–2004

139.3

2004–2005

304.1

2005–2006

305.9

2006–2007

321.2

2007–2008

35.5

2008–2009

35.4

2009–2010 298.6

48.0

35.9

0.18

2010–2011 350.2

265.0

39.8

0.21 2011–2012 410.8 212.8 742.9

43.8

2012–2013 481.8

1021.1

41.0

2013–2014 565.2

Note: The bold emission values from NEEP data source for 2011-2012 to 2013-2014 are not actual emission, but the projected emissions. NEEP: Nepal Energy Efficiency Programme (NEEP, 2012) CBS: Central Bureau of Statistics (CBS, 2014b) MoF: Ministry of Finance, Nepal (MoF, 2011) and other annual reports USGS: U.S. Geological Survey (USGS, 2016)


47

Figure 3.3 Trend of annual CO2 emission in Nepal using different datasets.

Note: NEEP: Nepal Energy Efficiency Programme (NEEP, 2012) CBS: Central Bureau of Statistics (CBS, 2014b) MoF: Ministry of Finance, Nepal (MoF, 2011) and other annual reports SNC: Second National Communications (MoSTE, 2014) USGS: U.S. Geological Survey (USGS, 2016) CDIAC: Carbon dioxide Information Analysis Center (CDIAC, 2016) The NEEP (2012) data from 2011-2012 to 2013-2014 are the projected emissions.


48

Table 3.9 Annual emissions of air pollutants from various industries in Nepal.

Year

Emissions from iron and steel production (Gg)

Emissions from paper

production (Gg)

Emissions from food and beverage

production (Gg)

NOx NMVOC CO SO2

NMVOC NMVOC

1987–1988 0.0010 0.0008 0.0000 0.0012

0.0178 0.6921 1988–1989 0.0014 0.0010 0.0000 0.0016

0.0218 0.6208

1989–1990 0.0015 0.0011 0.0000 0.0016

0.0197 0.7869 1990–1991 0.0018 0.0014 0.0000 0.0021

0.0235 0.9873

1991–1992 0.0024 0.0018 0.0001 0.0027

0.0237 1.1631 1992–1993 0.0024 0.0018 0.0001 0.0027

0.0251 1.3126

1993–1994 0.0028 0.0021 0.0001 0.0032

0.0303 0.8900 1994–1995 0.0038 0.0029 0.0001 0.0043

0.0328 1.1115

1995–1996 0.0037 0.0027 0.0001 0.0041

0.0428 1.2970 1996–1997 0.0043 0.0032 0.0001 0.0048

0.0502 0.6701

1997–1998 0.0037 0.0027 0.0001 0.0041

0.0586 1.8501 1998–1999 0.0043 0.0032 0.0001 0.0048

0.0720 2.1040

1999–2000 0.0053 0.0039 0.0001 0.0059

0.1482 2.2813 2000–2001 0.0054 0.0041 0.0001 0.0061

0.1527 2.3654

2001–2002 0.0056 0.0042 0.0001 0.0063

0.1517 2.4139 2002–2003 0.0066 0.0049 0.0002 0.0074

0.1591 2.2570

2003–2004 0.0068 0.0051 0.0002 0.0076

0.1585 2.3981 2004–2005 0.0067 0.0050 0.0002 0.0075

0.1071 4.3285

2005–2006 0.0000 0.0000 0.0000 0.0000

0.1106 4.1652 2006–2007 0.0000 0.0000 0.0000 0.0000

0.1162 4.3749

2007–2008 0.0000 0.0000 0.0000 0.0000

0.1217 4.5804 2008–2009 0.0000 0.0000 0.0000 0.0000

0.0000 3.6332

2009–2010 0.0000 0.0000 0.0000 0.0000

0.1184 5.6321 2010–2011 0.0014 0.0011 0.0000 0.0016

0.1457 5.8319

2011–2012 0.0016 0.0012 0.0000 0.0018

0.0000 4.0066 2012–2013 0.0014 0.0011 0.0000 0.0016

0.0000 4.1123

Note: The production data required for calculation of NMVOC from paper industries was extracted from NEEP (2012) for 2009-2010 and 2010-2011 years.

Table 3.10 Annual potential HFC emission in Nepal.

Year HFC emission (kg)

R134a R404a R407a R410a

2013 2014

7475.2 4352

218 1308

565 2034

5085 3842

Data source: Ministry of Population and Environment, Nepal (MoPE, 2017) Note: HFC emissions reported here are only potential emissions.


49

Table 3.11 Annual N2O emission from various product uses in Nepal.

Year N2O emission from product uses (tonnes)

2003-2004 2004-2005 2005-2006 2006-2007 2007-2008 2008-2009 2009-2010 2010-2011 2011-2012 2012-2013 2013-2014 2014-2015 2015-2016

20.3 119.5

6.6 13.6 10.4 20.4 2.3 3.5

26.9 12.3 4.7

15.9 20.8

Data source: Department of Commerce, Ministry of Commerce and Industry, Government of India (DoC-India, 2017)

Figure 3.4 Trend of annual N2O emission in Nepal.


50

Table 3.12 Annual CO2 emission from lubricants and paraffin wax uses in Nepal.

Year CO2 emission (Gg)

Lubricant use Paraffin wax use 2007-2008 1.9 2.0 2008-2009 1.9 3.1 2009-2010 1.1 2.0 2010-2011 2.9 2.3 2011-2012 3.0 2.1 2012-2013 3.5 2.8 2013-2014 3.7 2.1 2014-2015 3.9 2.2 2015-2016 4.4 2.3

3.6 GHG Emission Projection Using the past trend of the industrial emissions from cement production, CO2 emission was projected up to 2030 for Nepal (Table 3.13; Figure 3.5). Since the trend of industrial sector is difficult to ascertain and cement is the most dominant category in IPPU, only the trend of cement production has been used. For the cement production, the growth rate of the population, number of households as well as the number of construction projects in Nepal could affect the future demand of cement. Similarly, the increase in the number of cement factories can play a major role in determining the future scenario of GHG emissions. Due to the lack of definite trend in these factors, the rate of 17.3 percent increase in the annual production of cement in Nepal is used for projecting the GHG emissions. This is obtained from the rate of increase in the study of NEEP (2012). This rate of increase in cement production is also consistent with the estimate of Nepal Cement Manufacturers' Association. Then the emission is projected according to the low-variant, medium-variant and high-variant population projection scenarios given by CBS (2014). The projection shows that cement production may possibly contribute approximately 4000 to 6000 Gg of CO2 per annum by 2030 in Nepal.


51

Table 3.13 Projected trend of annual CO2 emission from cement industries in Nepal.

Year Projected CO2 emission from cement production (Gg)

2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

410.8 481.8 565.2 662.9 777.5 912.0

1069.6 1254.6 1471.5 1726.0 2024.4 2374.5 2785.1 3266.6 3831.5 4494.0 5271.1 6182.5 7251.6

Figure 3.5 Projected trend of annual CO2 emission from cement industries in Nepal.

3.7 Perspectives for improvement The industrial output and export/import data should be properly managed at national level to maintain an accurate databank of the industrial processes and product uses. The industries may also be required to submit the production and sales data to the government on a continuous basis. When compared with the global datasets of CDIAC and EDGAR (Figure 3.6), the surveyed cement production data from NEEP (2012) seems a reasonable estimate of CO2 emissions from cement production. It may in fact

0

1000

2000

3000

4000

5000

6000

7000

2009–2010 2016–2017 2023–2024 2030-2031

CO

2 em

issi

on (G

g)

Year

Low-variant Population Medium-variant Population High-variant Population


52

improve the global datasets by incorporating the effect of the import of clinkers to Nepal. Hence, such intensive surveys of cement industries are very important for accurate assessment of GHG emissions in IPPU sector.

Figure 3.6 Comparison of annual CO2 emission from cement industries in Nepal (NEEP) with global emission datasets (CDIAC and EDGAR). The NEEP (2012) data from 2011-2012

to 2013-2014 are the projected missions.


53

4. Agriculture,Forestry,andOtherLandUse

4.1 Brief Summary

This section presents greenhouse gas (GHG) emissions by source and removal by sink in agriculture, forestry, and other land use (AFOLU) activities. The GHG emissions and sinks were computed for the base year 2011 from official national activity data applying standard methodologies developed by Intergovernmental Panel on Climate Change (IPCC) to ensure consistency with the GHG inventory processes established under the UNFCCC convention. Direct GHGs (CO2, CH4, N2O) and indirect GHGs (CO and NOx) were estimated in this sector. The computation shows that AFOLU sector resulted a net emission of GHG. In 2011, an estimated total of 15,982.16 Gg CO2-eq yr-1was emitted from this sector. The livestock (3A) sub-category contributed an emission of 17,665.29 Gg CO2-eq yr-1

, an increase of emission by 43.5% (from 12,308 Gg CO2-eq yr-1), from 2001 to 2011, Aggregated sources and non-CO2 emission sources on land (3C) contributed 11,499.65 Gg CO2-eq yr-1, while the Land (3B) subcategory acted as the net sink 13,182.78 Gg CO2-eq yr-1 due to sink of CO2 in forestland and cropland. If the trend continues under business as usual scenario, except sink from the forest cover increase, other activities will increase emissions of up to 25% by 2030. Uncertainties are really high in the emissions and sink figures from the AFOLU sector due to lack of national emission factors and consistent activities data. Improved and better information on AFOLU sector is indispensable for assessing the national capacity in removal of the GHG from the sector.

4.2 Overview of the Sector

Agriculture and forestry plays a tremendous role in the economy by employing 65% of the population and contributing 36% towards the Gross Domestic Product (GDP) (CBS, 2016). Agricultural production faces a huge challenge and farmers struggle to produce enough food to feed their families (USAID/2015). Based on the land use statistics, 29% of the land is used for agriculture, while 12% is utilized as grass land and pasture areas for animals (MOAD, 2011). The forests and other wood lands cover 44.74% area of the country (DFRS, 2015). In contrast to other sectors, the AFOLU incorporates both emissions by sources and removal by sinks from managed land. For example, an emission is resulted from deforested area and a sink from other area converted into forests.

The 2006 IPCC Guidelines for National Greenhouse Gas Inventories integrates the previously separate components - Agriculture and Land Use, Land-Use Change and Forests - in the Revised 1996 IPCC Guidelines. This integration recognizes that the processes underlying greenhouse gas emissions and removals, as well as the different forms of terrestrial carbon stocks, can occur across all types of land. It recognizes that land-use changes can involve all types of land, i.e., forest, cropland, grassland,


54

wetland, settlement, and other lands. Generic methods for accounting of biomass, dead organic matter and soil C stock changes in all land-use categories. The detailed description of land representation and categorization are provided based on land area by land-use and management systems as well as stratification of land area by climate, soil, and other environmental strata. The AFOLU sector comprises emissions estimates from livestock, land conversion, and aggregate sources and non-CO2 emissions sources on land. This sector further accounts for carbon sink, for example, due to conversion of other land use category to forests. If forests are managed in a sustainable way then extraction and production of biomass in the forests remain balanced and does not have any impact on change, however the situation of Nepal is different and so far, practical sustainable forest management is not practiced widely, although forest improvement is reported through community forestry and afforestation or reforestation programme.


4.3.1 DataSources

The GHG emissions and removals in this inventory were calculated for most of the activities outlined in three sub-categories (3A Livestock, 3B Land, and 3C Aggregated Source and Non-CO2 Emission Sources from Land) of the IPCC guideline (Table 4.1).

The main sources of data used in this analysis were database, documents and information portals of the official governmental agencies. In case of non-availability of the government agency data, the data received from other sources were used. The different sources of data are reported in the Table 4.2.

4.3.2 Methodology

GHG emissions and sink by sources in the AFOLU sector were computed from the

official national activity data using the 2006 IPCC standard guideline. The type of

activity data used for GHG emissions or removals are summarized in Table 4.1.

Table 4.1 Overview of AFOLU categories, subcategories, and emission computation.

Activities CO2 CO Methane

(CH4) Nitrous oxide (N2O)

Livestock (3A) Enteric fermentation (3A1) √ Manure management (3A2) √ √ Land (3B) Forest Land (3B1) √ Crop Land (3B2) √ Grass Land (3B3) √ Settlement (3B5) √ Other lands (3B6) √ Aggregate sources and non-CO2 emissions sources on land (3C)


55

Biomass burning (3C1) √ √ √ √ Liming (3C2) √ Urea application (3C3) √ Direct N2O emissions from managed soils (3C4)

√

Indirect N2O emissions from managed soils (3C5)

√

Indirect N2O emissions from manure management (3C6)

√

Rice cultivations (3C7) √

i) Choice of Emission Factors

Due to the lack of national emission factor, default emission factors provided by the IPCC were used for each GHG of interest, using Tier I approach. For example, total CH4 emission from enteric fermentation was computed by multiplying the number of animal in heads (an activity data) with CH4 emission factor (EF). Tier 2 wasn’t used because it requires data on animal feed characteristics, which is not available.

ii) Key Categories Key categories applicable for national situation were used according to the IPCC methodology. Each of the outlined categories of the inventory methodology was revisited. a) Livestock (3A) Livestock plays an important role in the rural economy of Nepal. It contributes to a quarter of total agricultural Gross Domestic Product (GDP). The contribution of livestock to the national economy is increasingly becoming more important in the recent decades, as the number of livestock – almost all kinds – is increasing over time (Table 4.3). Livestock management contributes to GHG emission chiefly in two ways: Enteric fermentation and manure management.

Enteric fermentation takes place in rumen when CH4 is produced as a result of microbial fermentation of the feed consumed by the animals. Cattle, buffalo, goat, and sheep are the primary CH4 producers, whereas a number of other livestock also contributes to CH4 at different scales. Manure management produces CH4 when anaerobic respiration takes place in the heap of manure.

b) Land (3B) The land category (3B) is further divided into six sub-categories: Forest Land (3B1), Crop Land (3B2), Grassland (3B3), Wetland (3B4), Settlement (3B5) and Other Lands (3B6). The CO2 emissions from deforestation, forest degradation, reforestation, and forest management were estimated in this category. The “other land” sub-category includes areas with bare soil, rock, and ice, in addition to all land areas that do not fall


56

under other five land-use categories. In current inventory, this sub-category was not considered due to lack of national data.

• Forest Land (3B1) This sub-category covers estimate of emission and removal from Forest Land Remaining Forest Land and Land Converted to Forest Land. Land cover data from the recent forest resource assessment (DFRS, 2015), Official topographic map of 1992, and data from LRMP were used for emission and removal estimation in this category and other land categories.

• Crop Land (3B2) This sub-category is further divided into Cropland Remaining Cropland and Land Converted to Cropland. Cropland includes annual as well as temporary fallow land like arable and tillable land, rice field and agro-forestry system. Amount of carbon stored in and emitted or removed from cropland depends on the crop type, management practices and soil and climate variables. Land use conversion to cropland from other land usually result in a net loss of carbon from biomass and soils as well as N2O to the atmosphere.

• Grassland (3B3) This sub-category includes Grassland Remaining Grassland and Land Converted to Grassland.

• Wetland (3B4) This sub-category includes emission and removal estimation from wetlands, including peat extraction in natural peat lands and flooded lands. Even if the attempts for national wetland inventory, a nation-wide complete inventory is not available. Furthermore, data on the peat extraction is lacking. In the absence of required data for computation, the wetlands emission/sink from the wetlands are not considered in this inventory.

• Settlement (3B5) Estimates of emissions and removals from Settlements include two groups: Settlements Remaining Settlements and Land Converted to Settlements. Carbon stock change and greenhouse gas emission and removals associated with change in biomass dead organic carbon and soil carbon from settlement includes developed land i.e. residential, transportation, and commercial and production infrastructure. The land use category of settlement includes soil, herbaceous, vegetation as garden plant, tree in rural settlements, urban area, garden, aesthetic field, park, land along street, villages area etc.


57

Figure 4.1 Six Land use categories recommended by the IPCC guideline.

• Other Lands (3B6) This sub-category includes areas with bare soil, rock, and ice, in addition to all land areas that do not fall into the other five land-use categories. Carbon stock and non-CO2 emission with conversion from forestland to other land (above mentioned land) are estimated in this subcategory. Since GHG emissions and removals are not reported for unmanaged lands, methods and guidance in this chapter apply only to ‘Land Converted to Other Land’, for example, from extreme degradation of forest, cropland or grassland to barren land that is no longer managed for various useful purposes.

c) Aggregate Source and Non-CO2 Emission Sources on Land (3C) Agriculture is a principal economic sector and the mainstay of rural livelihoods in Nepal as it employs 65% of the population and contributes one-third of the national GDP. Agriculture land covers 4,243,160 ha (29.7% of total areas) area in Nepal, with per capita land availability of 0.082 ha, which is less than half of world’s average. Moreover, more than 53% of households operate in a farm size of less than 0.5 ha (CBS 2011). Nepal’s greenhouse gas emission in term of CO2 equivalent accounts for about 0.027 % of global total (2010), of which agriculture sector accounts for 56.3% and crop production and livestock production, respectively contribute about 25% and 75% to total share of agriculture (MoEST, 2014). Various agricultural activities contribute to emissions of GHG mainly Methane and Nitrous oxide, either directly or indirectly. The key activities include biomass burning, liming, urea application, direct N2O emissions from managed soils, and indirect N2O emissions from managed soils, indirect N2O emissions from manure management, rice cultivation and harvest of wood products. These activities are described below.


58

Agriculture Liming

Adding carbonates in the forms of limes (e.g., calcic limestone (CaCO3) or dolomite (CaMg(CO3)2) reduces soil acidity and improves plant growth in agricultural lands, which emits CO2. Nepal’s agriculture soils are observed more acidic and farmers sometimes use the agriculture lime to neutralize the soils. The south-eastern plain Terai lands are relatively more acidic compared to other parts of the country.

Urea Application

The improvement of soil fertility is essential for increasing productivity in order to meet Nepal’s growing demand of food. The fertilizer production is an energy-consuming industrial process. It consumes approximately 1.2% of the world’s energy and is an emitter of approximately 1.2% of global GHG emissions (Kongshaug 1998). Among various fertilizers, urea is the most common nitrogenous fertilizer used in Nepal.

Urea is one of important sources of ammonium (NH+) and CO2 emission. The CO2 released after urea application is a part of carbon tapped from the atmosphere during fertilizer manufacturing in the industrial process. Urea is used in most of the crops and vegetables for growth and development of plants, mainly in accessible areas such as the Terai plains and Kathmandu. The total amount of urea applied (tones per year) was multiplied by the EF.

Direct and Indirect N2O emissions from Managed Soils

Soils are the largest carbon reservoirs in terrestrial region, which accounts for 3.5% of the earth’s carbon reserves, and it is also a potential sink for atmospheric carbon (Jha et al., 2012; Lal, 1995). Both direct and indirect methods were employed to calculate the emission. Direct N2O emissions were calculated by multiplying the amount of annual synthetic Nitrogen (N) applications in the form of nitrogenous fertilizers (excluding urea as that was calculated separately) in kg N per year with the respective EF. Indirect N2O emission considered here was the result of the amount of annual synthetic N applications that volatilizes as NH3 and NOx and is lost through runoff and leaching in

kg N per year.

Indirect N2O Emissions from Manure Management

Nitrogen from animal wastes, biological N-fixation, and cultivation of mineral and organic soils through enhanced organic matter mineralization are also important sources of Nitrous Oxide (N2O) emissions from the soil (IPCC 1997). N2O emissions account for about 6% of the global anthropogenic GHG emission and its global warming potential is 300 times greater than carbon dioxide (IPCC 2007). It also causes destruction in stratospheric ozone.


59

The N2O is produced in soils through the microbial processes of nitrification and denitrification, which is influenced by soil water content, temperature, texture, carbon availability and application of N inputs to the system (Stehfest and Bouwman, 2006). Nitrogen inputs to agricultural soils also contribute to indirect N2O emissions (IPCC, 2006) through leaching, run off and volatilization.

The activity data represent the fraction of manure N applications that volatilizes as NH3

and NOx, and is lost through runoff and leaching in kg N per annum. Data was

obtained from total manure production calculated from the number of animals, and a standard technique was used to calculate how much of such nitrogenous gases are produced from a kg of manure. As the country level data was not available, a global figure was used to interpolate data for deriving national level figure. The farmyard manure (FYM) and compost data was calculated from the number of livestock for which a case study was done to analyze the amount of FYM and compost a single animal is able to produce.

Rice Cultivation

Methane emission from paddy field was calculated using harvest area of rice in different paddy field type and water regime as well as organic matter application, which was multiplied by the number of rice cultivation days in a year and emission factor and scale factors. Different paddy land types are found in Nepal: Lowland and upland. Uplands are often rainfed and lowlands include rainfed, irrigated, water logged and wetland.

Uplands, often terraced lands, never hold enough water for longer period to let methane produce, whereas lowlands produce methane depending on sub-type of land or level of water available and time of period of availability. The categories for which data is available for Nepal are rainfed and irrigated, and no data is available by upland and lowland. Moreover, for irrigated or lowland areas further sub-categories are described but data for each sub-category is not available. Since only about two-thirds of land is irrigated in the country (CBS, 2011; APBS, 2014), CH4 emission is expected to be low.

Biomass Burning

Biomass burnings in Nepal occurs in forests, grasslands, and agriculture fields. Burning of agricultural crops/commodities residues in the field is a common practice only in certain parts of Nepal. National emission factors from burning agricultural residues for both carbon and nitrogen are also not available. Both uncontrolled (wild fires) and managed (prescribed) fire can have a major impact on non-CO2 green house gas emission from several lands, like forests and grass lands. Non-CO2 emission (CH4, N2O) from the Crop land remaining crop land, Forest land remaining forest land, Grassland remaining grassland and Other land remaining other land are generally associated with burning of residues of that land.


60

The percent of the biomass burned on the land, which is the mass fuel available for burning, should be estimated for taking into account a fraction removed before burning due to animal consumption, decay in the field, and used in other sector (e.g., bio-fuel, building material, animal feeding). In this inventory, biomass burning in the forests, grasslands, and agriculture fields are considered.

Table 4.2 List of AFOLU activity data and the data sources.

Category Sub-Category Data Need Data Source

3A Livestock

3A1 Enteric Fermentation

Number of Animals (cattle, buffalo, goat, sheep, swine, mule and assess, horse)

Ministry of Agricultural Development (MoAD), CBS

3A2 Manure Management

Number of Animals (cattle, buffalo, goat, sheep, swine, mule and assess, horse, poultry, rabbit, duck)

MoAD, CBS

3B Land

3B1 Forest land

Land use maps, Land use change map, Land use change matrix

MoFSC, ICIMOD

Biomass estimate for 5 IPCC pools (Above ground biomass, below ground biomass, deadwood, herb, litter and soil)

MoFSC, DFRS, IPCC

Climate zones, soil classification and ecological zone maps

IPCC database, DHM, DFRS

Industrial round wood MoFSC, DFRS Wood fuel production MoFSC, DFRS Areas affected by fire FAOSTAT

3B2 Cropland


MoFSC, ICIMOD

Biomass estimate for 5 IPCC pools (Above ground biomass, below ground biomass, deadwood, herb, litter and soil)

MoFSC, DFRS, IPCC



3B3 Grassland


MoFSC, ICIMOD

Biomass estimate for 5 IPCC pools (Above ground biomass, below

MoFSC, DFRS, IPCC

Ground biomass, deadwood, herb, litter and soil)

MoFSC, DFRS, IPCC


61



3B5 Settlements


MoFSC, ICIMOD



3B6 Otherland


MoFSC, ICIMOD



3.C Aggregated Source and non CO2 emissions on land

3C1 Biomass burning

Areas affected by fire in cropland, forestland, and grassland

MoFSC, DoF, FAOSTAT

3C2 Liming Quantity of agriculture limes used

DoA-SMD, Agriculture Inputs Company Ltd

3C3 Urea application

Annual Urea consumption figures MoAD, CBS, FAOSTAT

3C4 Direct N2O emissions from manage soils

Annual generic NPK consumption

MoAD, CBS

3C5 Indirect N2O emissions from manage soils

Annual crop production in tonnes per annum

MoAD, CBS

3C6 Indirect N2O emissions from manure management

Number of Animals (cattle, buffalo, goat, sheep, swine, mule and assess, horse, poultry, rabbit, duck)

MoAD, CBS

3C7 Rice cultivation

Annual rice production areas MoAD, CBS Proportions of annual rice production area under rain fed, irrigated and upland systems

MoAD, CBS

iii) Activity datasets

- Animal population (3A1 and 3A2) Animal population data is required for computation of GHG from the enteric fermentation and manure management. Two sets of data were available for these activities: MoAD and CBS. The data from the MoAD (2011 to 2015) were


62

considered in this inventory for all available animal population. In case, if the data were not available from MoAD, the data from the CBS, produced based on the National sample census 2011/12 by the National Planning Commission, were used. In case of manure management, masses of animals were used from IPCC default database on masses for Asia/Indian sub-continent. The annual N-excretion rate per head was computed using the formula provided by the 2006 IPCC guideline.

Table 4.3 Animal population (head) for the period 1990-2011 in Nepal (Source: MoAD, 2015).

Year

Cattle

Milking

Cow

Buffa

loes

Milking

Buffa

loes

Sheep

Goat

Pigs

Fowl

Duck

Laying

Duck

Laying

Hen

1997/98

7048660

826320

3419150

882140

869142

6080060

765718

16664730

416943

218687

5181880

1998/99

7030698

828214

3470600

896415

855159

6204616

825132

17796826

421423

220400

5420900

1999/00

7023166

840673

3525952

910753

851913

6325144

877681

18619636

425160

222401

5667817

2000/01

6982660

852583

3624020

936811

850170

6478380

912530

19790060

411410

215376

5998367

2001/02

6978690

852790

3700864

958530

840141

6606858

934461

21370420

408584

214090

6453860

2002/03

6953584

870589

3840013

988035

828286

6791861

932192

22260700

408311

213751

6622558

2003/04

6966436

888190

3952654

1015727

824187

6979875

935076

23023979

405217

211838

6676954

2004/05

6994463

902286

4081463

1050977

816727

7153527

947711

22790224

391855

183208

6643350

2005/06

7002916

903376

4204886

1084764

812085

7421624

960827

23221439

392895

183690

6769050

2006/07

7044279

908712

4366813

1124454

813621

7847624

989429

23924630

394798

184608

6962076

2007/08

7090714

915411

4496507

1158300

809480

8135880

1013359

24665820

390748

182753

7153088

2008/09

7175198

932876

4680486

1211495

802993

8473082

1044498

24481286

383123

179187

7124054

2009/10

7199260

954680

4836984

1252770

801371

8844172

1064858

25760373

379753

175300

7290875

2010/11

7226050

974122

4993650

1291644

805070

9186440

1108465

4.00E+07

378050

175150

7478645

2011/12

7244944

998963

5133139

1331037

807267

9512958

1137489

45171185

376916

174978

7907468

2012/13

7274022

1E+06

5241873

1369796

809536

9786354

1160035

47959239

375975

174714

8233616

2013/14

7243916

1E+06

5178612

1345837

789216

1E+07

1190138

48079406

390209

179447

8350237

2014/15

7241743

1E+06

5167737

1345164

789292

1E+07

1203230

50195285

390287

179480

8412728


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- Land use change (3B) The refined land use dataset (2000 and 2010) by the REDD Implementation Center, Ministry of Forests and Soil Conservation under their project – Development of a REDD+ Forest Reference Level in Nepal – were used to calculate the annual carbon stock change in this inventory (MoFSC, 2015 & 2017). The land use data was originally prepared by the ICIMOD. The land use classes were designed according to the six land classes (Forest, crop, grassland, settlement, wetland, otherland) as defined by the IPCC guideline. Corresponding default emission factors and other data were used from the guideline evaluating the country specific climatic zone, physiographic range, forest types (ecological domain).

Table 4.4 Land classes change from 2000 to 2010 in Nepal (Source: MoFSC, 2015 & 2017).

Wall to Wall Change Matrix 2000 to 2010 (in hectre)

Forest land

Cropland Settlement Grassland Wetland Other land

2000 Total

Forest land 4491093 608837 1459 209685 938 26697 5338709 Cropland 906246 2872378 16782 170032 0 73070 4038508 Settlement 775 23072 23479 383 0 1032 48741 Grassland 348807 251554 1180 1842372 0 75083 2518996 Wetland 16 21 21 66 70938 124 71186 Otherland 39515 356 356 56052 4188 2526066 2626533 2010 Total 5786452 3756218 43277 2278590 76064 2702072 14642673

- Biomass burning (3C1) The reliable estimate of biomass burning areas and the amount of biomass burned do not exist in national records. Thus, the biomass burning data were obtained from the FAOSTAT (2016). According to FAOSTAT data, emissions were computed for three types of biomass burning activities: Forest land and other forest, grassland, and crop residue. Forest and grassland fires are more frequent in Nepal.


64

Figure 4.2 Biomass burning by the land use types (upper) and agriculture crops (lower) in Nepal in 2011 (Source: FAOSTAT, 2016).

- Liming (3C2) For Nepal, different forms of limes applied in agriculture are not recorded for long period of time and the available data are also questionable, however agriculture lime distribution data of the Agriculture Inputs Company Ltd and the Soil Management Directorate, Department of Agriculture suggests about 600-700 tonnes of agriculture lime being used in Nepal in 2016. An estimated total target purchase and the sale of lime for agriculture was 1,000 metric tons in 2016/17, however all the target amount was not achieved. Even though some factories are using Dolomite, the quantity of use is relatively in small percent (~5%). The � annual amount of 500 tonnes lime, according to use estimation in 2011-2012, are used to calculate the total amount of CO2 emission through liming process.

- N-Fertilizer and urea application (3C3 and 3C4)

The data shows that the amount of urea application in agricultural land is rapidly increasing. The total amount of urea application was 63,020 tonnes in 2003, but it reached to 100,825 tonnes in 2011, although the cultivated land area has remained nearly constant. The increase in urea application is partly because of the adoption of modern/improved varieties by the farmers whose yield hinges on chemical fertilizer

34.2

2.0

2.4

0 10 20 30 40

HTF

OF

GL

Areaburned inThousandshectare

HTF-HumidTropicalForestOF-OtherForestGL-Grassland

906

823

41

307

Maize

Rice

Sugarcane

Wheat

0 200 400 600 800 1000

CropResidueBurning(Dryma4er)(inThousandstonnes)


65

use. It is also partly because in many villages, mainly in the Terai, farmers have stopped rearing traction animals as mechanization is becoming more common and easily accessible.

Urea includes 46% of N-content. The application of N-fertilizer was also calculated from the amount of nitrogenous fertilizers, other than urea, used in the country, which is presented in Table 4.5. The data shows that the application of N-fertilizer in the last three years has substantially increased as compared to previous years, and the trend is not linear prior to 2008. Between 2008 and 2011, the amount of N-fertilizer use has been increased nearly by 20 times, indicating that they are increasingly going to become an important contributor of GHG, which also demands for appropriate monitoring of sale and use of such fertilizers.

Table 4.5 Quantity of nitrogen-based fertilizer and Urea use for the period 2002-2011 in Nepal (tonnes) (Source: MoAD, 2015).

Fertilizer type 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Urea 0 63020 107995 22531 42262 7147 9600 50489 85191 100825 N-Fertilizer 21838 5465 8118 2856 8781 1939 2790 28331 43148 54769

- Crop production (3C4)

Crops and vegetables contribute to most of food requirement of the country and thus serve as staple foods, however crop productivity often remains poor despite a constant growth in the use of chemical fertilizer and pesticides and adoption of new tools, technologies and practices.

Crop production data includes, annual cereals crop production, improved and local (seed) crops, and vegetables. Data show that cereal crop production has increased in the period between 1991-2011 although there hasn’t been significant increase in cropped area. The increase in production corresponds with the amount of urea application and adoption of modern and hybrids varieties of crops and vegetables.

Table 4.6 Crop (cereal) production (‘000 ton/year) for the period 1991-2011 in Nepal (Source: MoAD, 2016).

Year 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001

Crop Production (tonnes)

5519 4901 5772 5374 6077 6378 6350 6389 6589 7115 7120

-

Year 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Crop Production (tonnes)

7220 7366 7754 7774 7663 7336 8077 8122 7770 8615


66

Table 4.7 Cereal crop production (ton/year) for the period 1984/85-2014/15 in Nepal (Source: MoAD, 2015).


67

Figure 4.3 Crop production (‘000 ton/year) for the period 1991-2011 in Nepal (FAOSTAT, 2016).

- Rice Cultivation (3C7)

Rice is a number one staple crop in Nepal. It is grown in 73 districts across the Terai and mid-hills regions, up to nearly 3,000 above the mean sea level in Jumla (Sapkota et al., 2010; Paudel, 2011). Nearly 50% of total cultivable land is suitable for rice cultivation (Paudel, 2011). Farmers grow rice in both lowland and upland areas, and use both modern and local varieties depending on land type and family preferences. Modern varieties are more common in the Terai region due to better access to markets and national research stations for the availability of seed, as well as suitable land and climate (Chaudhary, 2004). In the mid and high hills, rice-growing environments are limited due to cold and rainfed conditions and modern varieties are only recently becoming common (Sthapit and Witcombe, 1996). Local varieties are resistant to climate change on which modern and hybrid varieties cannot thrive. So far a total of 74 rice varieties (NARC, 2014) have been released and registered by the Nepal Agriculture Research Council.

Data shows that rice growing area is gradually increasing but not at rapid rate. If an in-depth analysis is done, the reality might be much grimmer because several rice-growing areas are being converted to residential areas in the villages and peri-urban areas owing to a rapid rate of land plotting and housing. The rice cultivation period differs for different physiographic regions, such as Terai 90 days, mountain 120 days, and Himalayan range 150 days (for irrigated category) and Terai 120 days, mountain 150 days, and Himalaya range 180 days for irrigated and Terai 120 days, mountain 150 days, and Himalaya range 180 days.

ha

hg/ha

tonnes

Cereals,totalproduction1961-2014

Nepal

Areaharvested

Cereals,Total

Nepal

Yield

Cereals,Total

Nepal

Production

Cereals,Total

1961

1967

1973

1979

1985

1991

1997

2003

2009

1964

1970

1976

1982

1988

1994

2000

2006

2012

1M

2M

3M

4M

10k

20k

30k

5M

10M

0

Source:FAOSTAT(Mar25,2017)


68

Figure 4.4 Rice yield (t/year) for the period 1991-2011 (Source: MoAD, 2015).

Table 4.8 Rice production areas by types (Source: MoAD, 2015 for FY 2014/2015).

Type Area (ha) Irrigated 919167 Non-irrigated 506179

iv) Filling Data Gaps

High quality and consistent data are lacking in the AFOLU sector. Database maintained by the government ministries and its departments are not regularly updated using standard and rigorous data collection and analytical techniques, it is rather done by using rapid surveys. For example, data for lime use in Nepal is not available on secondary sources including website. Similarly, the maintained database is difficult to transform into carbon emission, as they are aggregated and several of them are not available for a longer period. For instance, data for rice is only available for irrigated and rainfed lands, which is not disaggregated by upland and lowland. For some data, we have to rely on multiple sources and they are not easily available online, nor are several of them compatible.

The observed data gap includes the unavailability of annual change in the land use, inconsistency in the land category data maintained by the Government (FRA, DFR, MoFSC) and other national and international organization (ICIMOD and FAOSTAT).

v) Data Quality Control and Quality Assurance

The entire process of the inventory had carefully considered ensuring the data quality control and quality assurance (QA/QC). A QA/QC plan was developed which took into account the quality of the data. The inventory suffers both from non-availability of

1000

2000

3000

4000

1985 1990 1995 2000 2005 2010 2015

Ric

e yi

eld

(t/ye

ar)

Production year


69

activity data and their emission factors at the national level as required by the 2006 IPCC Guideline. Nepal has a traditional agriculture for which no suitable emission factor has been developed. Further, the activity data are not disaggregated as necessary for comparing with the emission factors reported by the IPCC Emission Factor Database. For example, paddy area data in Nepal are available in aggregate. No disaggregated data are available for upland paddy and lowland paddy. The upland paddy is not irrigated or flooded, but grown as rain-fed. Even among the low land paddy, some areas have no irrigation and crop is grown based on floodwater/rain water. In some other areas, irrigation is very limited and, most of the time, the field remains aerated. In some other cases, irrigation is available once a week or so in rotation from farmer to farmer or even plot to plot. There are still some paddy areas with continuous flooding with least chance of aeration. Such data limitation puts challenges on estimating the GHG emission in Nepal precisely.

4.4 GHG Emissions and Removals for the base year 2011 The overall GHG emissions and removal from the AFOLU sector is presented in Table 4.9. In the base year 2011, an estimated total of 15,982.16 Gg CO2-eq yr-1 emission was resulted from the AFOLU sector. The livestock (3A) sub-category contributed an emission of 17,665.29 Gg CO2-eq yr-1

., Aggregated sources and non-CO2 emission sources on land (3C) contributed 11,499.65 Gg CO2-eq yr-1, while the Land (3B) subcategory acted as the net sink 13,182.78 Gg CO2-eq yr-1 due to sink of CO2 in forestland and cropland.

The emissions occurred from manure management is smaller than enteric fermentation. The emission from manure management per capita is lower than the IPCC standard, because manure is not stored and used as liquid and often heaps are exposed to sun thus, reducing the chance of anaerobic action.

Table 4.9 Greenhouse gas emissions and removal (Gg) from the AFOLU sector in 2011.

Activities CO2 CH4 N2O CO2-Eq CO NOx

TOTAL AFOLU -12371.79 882.36 21.12 15982.16

Livestock (3A) 705.49 0.09 17665.29

Enteric fermentation (3A1)

648.74 16218.50

Manure management (3A2)

56.75 0.09 1446.63

Land(3B) -13182.78

-13182.78

Forest land (3B1) -13488.88

-13488.88

Cropland (3B2) -2947.26 -2947.26

Grassland (3B3) 1770.22

1770.22

Settlement (3B5) 870.79

870.79

Land Converted to otherland (3B6b) 612.35

612.35

Aggregate sources and non-CO2 emissions sources on land (3C)

810.99 176.87 21.03 11499.65 186.44 2.87


70

Biomass burning (3C1) 229.85 17.88 0.62 860.25

Forest 229.85 12.19 0.47 673.51 186.44 2.87 Crop residue

5.61 0.15 183.55

Grassland burning

0.08 0.00 3.20

Liming (3C2) 564.11

564.11

Urea application (3C3) 17.04

17.04

Direct N2O emissions from managed soils (3C4)

0.86 255.12

Indirect N2O emissions from managed soils (3C5)

0.23 67.93

Indirect N2O emissions from manure management (3C6)

19.33 5760.30

Rice cultivations (3C7)

159.00

3974.91

The emission of GHG emission and removal from the forest land class can be regarded as in line with the National Forest Reference Level Report of Nepal (2000-2010) (MoFSC, 2017). The report suggested a total emissions of 1,326.243 Gg CO2-eq/year and total removals of -150.110 Gg CO2-eq/year based on the estimation for forest deforestation, afforestation, and degradation. The annual emissions and removals due to deforestation and afforestation are 917.743 Gg CO2-eq/year and -150.110 Gg CO2-eq/year, respectively. It is estimated that the annual degradation due to unsustainable fuelwood extraction in Forest-remaining-Forest (FRF) resulted in emissions of 408.500 Gg CO2-eq/year. These estimations did not consider GHG removals in forest through natural biomass growth and long-term sustainable improvements in management as a results of community-based forest management and natural biomass growth. Furthermore, the estimation did not consider the forest degradation due to grazing and accounts only the forest patches with an area >2.25 hectare size. If considered all the activities (as reported in MoFSC, 2015), the emission and removal from the forest land class changes significantly.

4.5 Trend in Greenhouse Gas Emission Figure 4.5 indicates the GHG emissions and sink from the AFOLU sector. From 2001 to 2011, the GHG emission was increasing from the livestock and aggregate sources and non-CO2 emissions sources on land categories, while a continuous sink recorded from the land category. In fact, the GHGs sink was only recorded from the forest and cropland classes, whereas other classes: settlement, wetland, grassland, and other land contributed to the GHG emissions.

The trend analysis suggests that the emissions from livestock category increased from 12,308 Gg CO2-eq yr-1 in 2000 to 17,665 Gg CO2-eq yr-1 in 2011 (an increase of 43.5%). The contribution of agriculture to GHG emission has been gradually increasing in Nepal since the 1990s. The total contribution is linearly increased from 18,240 in 2000 to 26,621 Gg in 2011, an increase of 46.0%. A sharp increase has been noticed since 2009 the year when subsidy policy on fertilizer was resumed, which indicates that when fertilizer became less expensive, then farmers have started using more


71

fertilizer (also seen in urea and N-fertilizer use trend) and thus, more GHG emission was is recorded.

Figure 4.5 GHG Emission Trends. a) Livestock (3A), b) Land (3B), c) Aggregate and non-CO2 emission sources (3C), and d) overall AFOLU sector.

Figure 4.6 Projection of GHG Emission until 2030. a) Livestock (3A), b) Land (3B), c) Aggregate and non-CO2 emission sources (3C), and d) overall AFOLU sector.

10

12

14

16

18

2001 2003 2005 2007 2009 2011

LivestockEm

ission

(GgC

O2-eq)

Thousands

Year

-14

-13

-12

-11

-10 2001 2003 2005 2007 2009 2011

LandEmission/Re

moval

(GgCO

2-eq)

Thousands

Year

10

11

12

13

2001 2003 2005 2007 2009 2011

Aggregate/No

n-CO

2Em

ission(GgC

O2-eq)

Thousands

Year

10

12

14

16

18

2001 2003 2005 2007 2009 2011

Emiss

ion/Re

moval

(GgC

O2-eq)

Thousands

Year

10

15

20

25

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

LivestockEm

ission

(GgC

O2-eq)

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-15

-10 2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

LandEmiss

ion/Re

moval

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O2-eq)

Thousands

Year

10

11

12

13

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

Aggregate/No

n-CO

2Em

ission(GgC

O2-eq)

Thousands

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15

16

17

18

2012 2014 2016 2018 2020 2022 2024 2026 2028 2030

Emiss

ion/Re

moval

(GgC

O2-eq)

Thousands

Year


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4.6 Perspectives for Improvement In agriculture, it is important to practice more effective soil, water and crop management practices. Better soil management through agriculture practices such as conservation agriculture, organic agriculture along with improved cattle shed and manure management, and precision agriculture will help reduce or optimize the use of synthetic fertilizer such as urea and other N-fertilizer. This helps to reduce the emission of GHG. Various Climate Smart Agriculture Practices (CSAs) such as System of Rice Intensification (SRI), drip irrigation, sprinkler irrigation, wet and dry irrigation, zero or minimum tillage, mulching, and adoption of drought tolerant crops and varieties can reduce the use of irrigation and thus reduce fuel burning in the area where pump sets are used. If pump sets are substituted by solar irrigation pumps, that will also reduce emissions from burning of fuel. Agroforestry practices can also help to sequester carbon and thus, have less effect on global warming.


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5. Waste

5.1 Brief Summary This section presents greenhouse gas (GHG) emissions from waste sector, namely Solid Waste Management, Biological Treatment of Waste, Incineration and open burning of Solid Waste and Waste Water Treatment and Discharge. Typically, CH4 emissions from SWDS and wastewater discharge contribute most for the greenhouse gas emissions in the Waste Sector. The study adopted 2006 IPCC guidelines with regard to data collection, methodologies, and use of assumptions. It further provides guidance on how emission factors are chosen and used for different emission activities. This study adopted Tier 1 methodologies for inventory analysis. Higher Tier would not be used because of unavailability of national data for various activities. The activity data and emission factors for the greenhouse gas inventory of Nepal were collected from various data sources and the data were categorized according to IPCC (2006) guideline. In the absence of reliable data, appropriate statistical methods were used to extrapolate or interpolate available data. Expert judgment would be used, if no such data exists. Solid Waste generation in rural Nepal has been ignored assuming that waste generated from that region is managed locally (in backyards, open fields, etc) generating negligible amount of GHG emission. Solid Waste handling activities in urban area generates significant amount of GHG. Similarly, GHG emission from wastewater treatment and handling also generated large quantities of GHG. The greenhouse gas inventory, thus prepared by using emission factors and activity data for the base year 2011 was assessed along with trend of greenhouse gas emissions. The estimation and the projected data of the emissions were prepared according to the IPCC (2006) guideline.

5.2 Overview of the Sector

Disposal and treatment of solid waste and wastewater can produce emissions of several greenhouse gases (GHGs), which contributes to global climate change. The most significant GHG produced from waste is methane (CH4). It is released during the breakdown of organic matter in landfills. Other forms of waste disposal also produce GHGs but these are mainly in the form of biogenic carbon dioxide (CO2) and non-methane volatile organic compounds (NMVOCs) as well as smaller amounts of nitrous oxide (N2O), nitrogen oxides (NOx) and carbon monoxide (CO) (GRIDA/UNEP, 2016). Typically, CH4 emissions from solid waste disposal sites (SWDS) are the largest source of greenhouse gas emissions in the Waste Sector. CH4 emissions from wastewater treatment and discharge may also be important (IPCC, 2006).

The prevention of waste generation and waste recycling helps to address global climate change by decreasing the amount of greenhouse gas emissions and saving energy. Waste Recycling helps to reduce GHG by offsetting fossil fuel requirement that would be required to produce same material using new raw materials. Due to the


74

wide range of technologies that can mitigate GHG emissions, existing waste management practices (e.g., landfill gas recovery, improved landfill practices; and engineered wastewater management) can provide effective mitigation of GHG emissions from this sector. Reduced waste generation and the exploitation of energy from waste (landfill gas, incineration, and anaerobic digester biogas) contribute to an indirect reduction of GHG emissions through the conservation of raw materials, improved energy and resource efficiency, and fossil fuel avoidance (Bogner, 2008).

In majority of the rural parts of Nepal, systematic waste management system has not yet been practiced. Waste disposal is haphazard (thrown in field, roadside, etc) with no anaerobic processing. As anaerobic condition doesn’t develop, emission is mostly CO2. However, in urban areas, most of the waste is disposed in landfills, open dump, river banks and, in some towns, by land filling in low lying areas. This process of waste disposal causes emission of large quantities of methane gas.

Apart from solid waste, wastewater (both household and industrial) is also significant contributor to GHG emission. The method of handling of wastewater is an important factor to decide methane emission (IPCC, 2006). In Nepal, most of the domestic, commercial and industrial wastewater is usually discharged into the open pits/latrines, aerobic shallow ponds, and streams and rivers with few exception of discharging in septic tanks and deep lagoons. This process of wastewater handling can be important in terms of GHGs emission in Nepal.

Classification of Solid Waste

The following categories are covered in the waste sector: Solid Waste Disposal (4A), Biological Treatment of Solid Waste (4B), Incineration (4C) and Open Burning and Wastewater Treatment and Discharge (4D).

a. Solid Waste Disposal: Municipal Solid Waste disposal activity is the most significant source of GHG generation. Municipal Solid Waste consists of both household as well as business waste. The emissions can be estimated taking into account the population, per capita waste generation, and quantity generated and deposited in disposal sites. As separate disposal of solid waste and industrial waste is not practiced in Nepal, it is assumed that total solid waste disposal information is the combination of both.

b. Biological Treatment of Solid Waste: Composting and Biogas production from solid waste are two widely used biological treatment technologies used to manage organic component of solid waste. Composting is the natural biological breakdown of organic material into a more stable organic substance. During the process of aerobic composting (presence of oxygen), microorganisms consume organic matter (carbon) and release carbon dioxide (CO2). Biogas typically refers to a mixture of different gases produced by the breakdown of organic matter in the absence of oxygen. During composting large fraction of DOC (Degradable organic carbon) in waste is converted to CO2. CH4 and N2O can both be formed during composting. If biogas is produced using solid waste, methane is around 55-60% while rest is carbon dioxide and other


75

gases (Edelmann, 2011). N2O is also produced but is assumed to be negligible. Composting and anaerobic digestion of organic waste results in reduced volume in the waste material, stabilization of the waste and production of biogas for energy use.

c. Incineration and Open Burning: Incineration is a waste treatment process that involves the combustion of organic substances contained in waste materials. Incineration of waste materials converts the waste into ash, flue gas, and heat. Flue gas consists of GHG like N2O and CO2. Quantity of these gases depends on waste composition. Modern Incineration plants recover heat from the plant making it a net energy positive system. Open burning of waste is practiced to reduce waste volume in waste dumps including landfill sites. This practice is an inadvertent source of persistent organic pollutants. The open burning of waste cause pollution to surrounding and produces harmful GHG gases like CO2 and NOx (IPCC, 2006).

d. Wastewater Treatment and Discharge: Wastewater handling is the major sources of methane and nitrous oxide emission. For domestic wastewater, biological oxygen demand (BOD), type of treatment systems and the amount of protein intake per person per year would be used for estimation of the emission. Anaerobic decomposition of organic component present in wastewater generates methane gas. Similarly, Nitrous oxide (N2O), another GHG gas, is emitted from human sewage, as a result of nitrification and denitrification of the nitrogen present in the sewage (IPCC, 2006).


The inventory adopted 2006 IPCC guidelines, which provide guidance on data collection, methodological choices and use of assumptions. The inventory adopted Tier 1 methodologies to estimate GHG emission using country specific emission and data. The higher tier method was not used because of lack of country specific data. As far as possible, country specific data were used. In case of unavailability of country specific data, data from reliable international sources were used. In case of gaps, appropriate statistical methods (e.g. trends extrapolation, interpolation, etc) were applied in practice with IPCC guideline. In events of complete absence of data for the activities, expert judgment was used and assumptions documented. Detailed descriptions of the respective methodologies are given in the specific sections of the various subcategories.

5.3.1 Solid Waste Disposal (4A)

The methane emissions from solid waste disposal for a single year can be estimated using Tier 1 methods based on IPCC, first order decay (FOD) method using mainly default activity data and default parameters. IPCC Model was used to calculate GHG Emission. As first tier model is time series, waste disposal in the past has effects on current emission; so waste disposal from 1991 is considered. Effect of Waste disposal before 1991 is considered to be negligible. Basic equation for FOD in the IPCC Waste Model (IPCC, 2006) using “bulk waste” option and time delay is

CH4 Emission T (Gg/yr) = 𝐶𝐻! 𝑔𝑒𝑛𝑒𝑟𝑎𝑡𝑒𝑑!,!! − 𝑅! *(1-OXT)


76

where, CH4 Emissions = CH4 emitted in year T, Gg T is the inventory year for which emissions are calculated x is waste category or type/material OXT = oxidation factor in year T, (fraction) RT = recovered CH4 in year T, Gg Solid Waste Management in Nepal, Current Status and Policy Recommendations by Asian Development Bank (ADB) is the most comprehensive study of urban waste management system in Nepal. Information about per capita waste generation, waste disposal and collection quantity and waste characteristics used for this study has been adopted from ADB, 2013. Per capita waste generation information obtained from other studies were not considered because per capita waste generation generally doesn’t decrease in developing countries like Nepal. Moreover, all studies prior to it were either focused only in few cities or had very small survey sample size. Biodegradable solid waste consisting of food waste, garden waste and nappies were taken into account to calculate methane emission. Degradable Organic Carbon (DOC) of Municipal Solid Waste was estimated by using equation given in 2006 IPCC Guidelines for National Greenhouse Gas Inventories. All other necessary parameters and default DOC were taken as default values from 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 5 (IPCC, 2006).

5.3.2 Biological Treatment of Solid Waste (4B)

Biological Treatment of solid waste may generate CH4, CO2 and N2O Emissions. Composting is the most widely used waste treatment method used since ancient time for the purpose of organic manure production. Lately, practice of anaerobic digestion of organic waste is increasing to generate biogas for energy use. Biological treatment helps to reduce volume of waste material and stabilize it. In composting process, a large fraction of DOC in waste is converted to CO2 because of aerobic decomposition of waste. CH4 and N2O can both be formed during composting. In anaerobic digestion Biogas is generated which consists of both CO2 and CH4. N2O production is negligible. Default method for estimation of CH4 emissions is

CH4 Emissions= 𝑀! .𝐸𝐹! . 10!!! − 𝑅 where, CH4 Emissions: total CH4 emissions in inventory year, Gg CH4 Mi : mass of organic waste treated by biological treatment type i, Gg EFi : emission factor for treatment i, g CH4/kg waste treated i : composting or anaerobic digestion R : total amount of CH4 recovered in inventory year, Gg CH4.

Default method for estimation of N2O emissions is

N2O Emissions = 𝑀! .𝐸𝐹! . 10!!!


77

where, N2O Emissions: total N2O emissions in inventory year, Gg N2O Mi : mass of organic waste treated by biological treatment type i, Gg EFi : emission factor for treatment i, g N2O/kg waste treated i : composting or anaerobic digestion

5.3.3 Open Burning of Waste: CO2 Emissions Based on the total amount of waste combusted

CO2 Emissions= 𝑆𝑊! .𝑑𝑚! . 𝐶𝐹! .𝐹𝐶𝐹! .𝑂𝐹! . 44/12! where, CO2 Emissions: CO2 emissions in inventory year, Gg/yr SWi: total amount of solid waste of type i (wet weight) incinerated or open-

burned, Gg/yr dmi: dry matter content in the waste (wet weight) incinerated or open-burned,

(Fraction) CFi: fraction of carbon in the dry matter (total carbon content), (fraction) FCFi: fraction of fossil carbon in the total carbon, (fraction) OFi: oxidation factor, (fraction) 44/12: conversion factor from C to CO2 i: type of waste incinerated/open-burned such as MSW, industrial solid waste

(ISW), sewage sludge, hazardous waste, clinical waste, etc. CH4 emissions result from incomplete combustion of waste and can be affected by temperature, residence time, and air to waste ratio.

CH4 Emissions= 𝐼𝑊! .𝐸𝐹!! . 10!! Gg where, CH4 Emissions: CH4 emissions in inventory year, Gg/yr IWi : amount of solid waste of type i incinerated or open-burned, Gg/yr EFi : aggregate CH4 emission factor, kg CH4/Gg of waste i : category or type of waste incinerated/open-burned (MSW, ISW, hazardous

waste, clinical waste, sewage sludge, etc.) Burning or incineration of solid waste also results in emission of N2O. The N2O emissions are mainly determined by technology, combustion temperature (emitted at relatively low combustion temperatures 500-950 oC) and waste composition.

N2O Emissions= 𝐼𝑊! .𝐸𝐹! . 10!!! Gg where, N2O Emissions: N2O emissions in inventory year, Gg/yr IWi : amount of incinerated/open-burned waste of type i, Gg/yr EFi

: N2O emission factor (kg N2O/Gg of waste) for waste of type i i : category or type of waste incinerated/open-burned (MSW, ISW, hazardous

waste, clinical waste, sewage sludge, etc.)


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5.3.4 Wastewater Treatment and Discharge

Wastewater (domestic, commercial and industrial) may be treated on site (uncollected), centralized plant (collected) or disposed untreated. Treatment and disposal of wastewater produce GHGs such as CO2, CH4 and N2O. CH4 production depends primarily on the amount of degradable organic material in the wastewater, the temperature and the type of treatment system. CH4 generated can be recovered and combusted in a flare or energy device. The N2O emissions are associated with the degradation of nitrogen components in the wastewater (e.g., urea, nitrate and protein). The N2O emissions can occur as direct emissions from treatment plants or from indirect emissions from wastewater after disposal of effluent into waterways, lakes or the sea. The emissions from industrial sources are believed to be insignificant compared to emissions from domestic wastewater. Due to lack of sizable functional wastewater treatment facility, it is assumed that all wastewater ends up in river. Because of inadequate published data on industrial wastewater generation and treatment process, some major industrial production were taken from industrial statistics and multiplied with wastewater generation per ton of production of that particular goods, which would be further multiplied with BOD/COD data. Estimation of an anaerobic handling of wastewater would be done based on collected information and appropriate assumption in line with INC—inadequate published data source. Biological Oxygen Demand (BOD) and Chemical Oxygen Demand (COD) values were found using 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Methane emissions from domestic and commercial as well as industrial wastewaters were estimated by using equation given by 2006 IPCC Guidelines for National Greenhouse Gas Inventories.

Total CH4 emissions from domestic wastewater:

CH4 Emission: 𝑈! .𝑇!,! .𝐸𝐹!!,! 𝑇𝑂𝑊 − 𝑆 − 𝑅

where,

CH4 Emissions: CH4 emissions in inventory year, kg CH4/yr TOW: total organics in wastewater in inventory year, kg BOD/yr S: organic component removed as sludge in inventory year, kg BOD/yr Ui: fraction of population in income group i in inventory year Ti,j : degree of utilization of treatment/discharge pathway or system, j, for each

income group fraction i in inventory year i: income group: rural, urban high income and urban low income j : each treatment/discharge pathway or system EFj : emission factor, kg CH4 / kg BOD R : amount of CH4 recovered in inventory year, kg CH4/yr

The CH4 emissions from industrial wastewater treatment:

CH4 Emissions= 𝑇𝑂𝑊! − 𝑆! .𝐸𝐹! − 𝑅!!


79

where, CH4 Emissions: CH4 emissions in inventory year, kg CH4/yr TOWi : total organically degradable material in wastewater from industry i in

inventory year, kg COD/yr i : industrial sector Si : organic component removed as sludge in inventory year, kg COD/yr EFi : emission factor for industry i, kg CH4/kg COD for treatment/discharge

pathway or systems. Ri : amount of CH4 recovered in inventory year, kg CH4/yr

Nitrous oxide is emitted from human sewage, which is the result of nitrification and denitrification of the nitrogen present in the sewage. Nitrous oxide emission from human sewage was estimated for whole population of the country for the base year 2011 (Population data source CBS). Emission factor and all other necessary parameters had been taken from 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Per Capita Protein Consumption had been taken from FAO data (FAO, 2016). Nitrous oxide emission from human sewage was estimated by using equation given by 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IPCC, 2006). Indirect N2O emissions from wastewater effluent discharged into aquatic environments

N2O Emissions =NEffluent .EFEffluent .44/28 where, N2O Emissions: N2O emissions in inventory year, kg N2O/yr N EFFLUENT: nitrogen in the effluent discharged to aquatic environments, kg N/yr EFEFFLUENT: emission factor for N2O emissions from discharged to wastewater, kg

N2O-N/kg N 44/28: conversion of kg N2O-N into kg N2O

Activity Datasets

There is dearth of comprehensive and reliable data on solid waste sector in Nepal. Few studies conducted by different agencies show that the results are not matching with each other. Similarly, demographic information from previous census cannot be directly compared with 2011 data because status of many villages has been changed into municipalities but they still retain some rural characteristics. Regression analysis had been performed to get demographic information for each year and interpolation and extrapolation has been performed to get corresponding solid waste information (when real study data is not available).

Various national and international sources were used to obtain data for this report. Similarly, census information, water use information and protein intake information were used to prepare GHG inventory due to domestic wastewater handling. Similarly, wastewater production was calculated by adding up wastewater produced as a result of industrial production.


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Urban Population

Emission from municipal solid waste disposal consists of domestic, commercial and institutional waste. Information about industrial solid waste is not separately available, hence assumed to be included in municipal waste. The emissions were calculated using urban population information, per capita waste generation, collection efficiency, and form of disposal activities. Information about population was obtained from national census (CBS, 2012) and solid waste from ADB study report (ADB, 2013). Urban population of Nepal reached 4.5 Million in 2011 that is more than 2.5 times of urban population in 1991 (CBS, 2001). Population growth has slowed down in Nepal but due to rapid urbanization, solid waste generation is increasing every year. Population growth trend and projection of urban Nepal is shown in Figure 5.1 (CBS, 2001; CBS, 2014).

Trend Projected

Figure 5.1 Urban Population Trend and Projection (CBS, 2001; CBS, 2014).

Generation and Composition of MSW

In 2011 more than 4.5 Million urban population generated over 523429 tons of solid waste out of which only 62% was collected (ADB, 2013). Rest of the waste ended up in roadsides, riversides and open field. Open burning and composting activities were also observed but these were not practices in a wider scale. Besides household composting, small-scale community and/or municipal composting are also found in some municipalities.

Various studies showed higher per capita waste generation in Nepal than study done by Asian Development Bank (ADB, 2013). But results from those studies were not considered for this inventory because they were not comprehensive enough and their study was limited to few urban centers. Without relying on past data it was also not possible to ascertain past per capita solid waste generation trend. So, per capita

0

2

4

6

8

10

12

1991

19

92

1993

19

94

1995

19

96

1997

19

98

1999

20

00

2001

20

02

2003

20

04

2005

20

06

2007

20

08

2009

20

10

2011

20

12

2013

20

14

2015

20

16

2017

20

18

2019

20

20

2021

20

22

2023

20

24

2025

20

26

2027

20

28

2029

20

30

Popu

lati

on

Mill

ions

Year


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information from (ADB, 2013) was used to ascertain solid waste generation for past years also for past years. With changing lifestyle, per capita waste generation is also expected to increase. Composition of municipal solid waste is shown in Figure 5.2.

Figure 5.2 Composition of Municipal Solid Waste.

Most of landfills in Nepal are not sanitary one. Those designed as sanitary has outgrown their use and is no more sanitary. Most of the collected municipal waste gets dumped on disposal sites without proper covering and methane recovery system. Many municipalities still practice riverside disposal, open field disposal without any covers. An analysis of the information provided by municipalities reveals that the present collection efficiency ranges between 70% and 90% in major towns, and is below 50% in several smaller towns, giving an average efficiency of 62%. Only 6 municipalities use sanitary landfill sites for final disposal, and 45 are practicing open dumping, including riverside and roadside. In total, 37% of MSW in Nepal is disposed of in sanitary landfills, although not necessarily in a sanitary manner (ADB, 2013).

Indirect method had been used to calculate values for wastewater generation because of inadequate published data on wastewater generation and handling in Nepal. Sanitation in Nepal is still poor and only 30% of population use water latrine with septic tank and rest use either open pit latrine or open sewerage latrine (CBS, 2012). Some major industrial production has been taken from industrial statistics (CBS, 2013) and multiplied with wastewater generation per ton of production of that particular goods, which has been further multiplied with BOD/COD data (IPCC, 2006). Nitrous oxide emission from human sewage was found for whole population of the country for the base year 2011 (CBS, 2011). Per Capita Protein Consumption was taken from “Food and Nutrition Security in Nepal: A Status Report, (FAO, 2016).

Overview of types of data and data source is given in Table 5.1.

Table 5.1 Overview of data used in the inventory.

56%

16% 16%

3%2%

2%1%

4%

7%

OrganicWaste Plastics Paper&PaperProducts

Glass Metals Textiles

Rubber&Leather Other


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Category Sub-Category GHG Data Required Data

Source 4A. Solid Waste Disposal

4A1. Solid Waste Disposal

CH4,

N2O Waste Generation Rate, Amount and Methods of Waste Disposal, Urban Population

ADB, SWMTSC, JICA, CBS

4B Biological Treatment of Solid Waste

4B1. Biological Treatment of Solid Waste

CH4, N2O

Fraction of Waste Composed IPCC Guideline 2006

4C. Incineration and Open Burning

4C2. Open Burning

CH4, N2O, CO2

Amount and type of waste burned

IPCC Guideline 2006

4D. Waste Water Treatment & Discharge

4D1. Domestic Wastewater

CH4,N2O

Population Data, Wastewater generated and treated per year, Protein consumption, Type of wastewater treatment system in use.

CBS, FAO, ADB

4D2. Industrial Wastewater

CH4, N2O

Industrial Production Data CBS, DoI, WB

5.4 Greenhouse Gas Emission for the Base Year 2011

5.4.1 Solid Waste Disposal

Nepal is predominantly a rural country; most of waste generated in rural communities decomposes aerobically. So this emission estimation has taken into account of only the urban solid waste generation and emission from it.

Based on studies, per capital generation of solid waste in Urban Nepal is 115.705 kg/yr. Since it represents collection efficiency of only 62%, rest of the solid waste ends up in Open Street dumps, riverbanks, etc. It has been reported that 30% of household practice some form of waste segregation and composting but their impact on total waste management is considered to be minimal. So, following regional practice, 10% of waste is assumed to be open burned and 5% is composted. Waste disposed using open incineration technologies is also considered to be negligible. Population and Waste characteristics is shown in Table 5.2. Various GHG emissions from Solid Waste Disposal are listed in Table 5.6.


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Table 5.2 Urban Population and Waste Characteristics 2011.

Urban Population

Waste Generation (ton)

Collection Efficiency

Deposited MSW (tons)

Organic Waste (tons)

Inert Waste (tons) Food &

Garden Paper

4,523,821 523,429 62% 324,511 181,726 51,921 84,373

5.4.2 Biological Treatment of Solid Waste

There are no sizeable anaerobic digestion biogas plants in Nepal that can treat solid waste and make any impact on GHG emission. There are many small-scale biogas plants in Nepal but their distribution is limited to rural Nepal and they are not used for treating solid waste, so any emission from anaerobic digestion of waste is assumed to be negligible. Composting, though practiced in small scale, generates GHG gases namely CH4, CO2, and N2O. It is assumed that 5% of waste generated in Nepali towns is used to make compost (Table 2A1, IPCC-Vol 5, 2006). Various GHG emissions from Biological Treatment of Waste are listed in Table 5.6.

Table 5.3. Biological Treatment of Waste in 2011. Type of Waste Annual Amount of

Waste treated (tons)

Emission Factor Recovered/Flared

CH4/year (g CH4/kg) (g N2O/kg)

Organic Waste 26,171 4 0.23 0

5.4.3 Open Burning

Open Burning is randomly but widely practiced waste management system in Nepal. It is practiced from household level to institutional level. As detail data to pinpoint exact quantity and nature of open burning is not available, 10% of total solid waste is assumed to be open burned. Different parameters considered to analyze emission from open burning are listed in Table 5.4. Various GHG emissions from Open Burning of Waste are listed in Table 5.6.

Table 5.4 Open Burning of Waste, 2011.

Waste Open

Burned (Gg)

Dry Matter

Content (Fraction)

CO2 Emission CH4 N2O

Carbon in Dry Matter

(Fraction)

Fraction of Fossil Carbon

in Total Carbon

Oxidation Factor

Emission Factor (kg/Gg)

Emission Factor (kg/Gg)

52.34 0.78 0.34 0.08 0.58 6500 150


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5.4.4 Wastewater Treatment and Discharge

There are few waste water treatment systems built to treat domestic and industrial wastewater in Nepal but most of them are wither not operating or operating irregularly below the capacity. So, to estimate GHG emission from domestic wastewater handling, indirect method was used. Organically degradable wastewater (kg/BOD/yr) was computed by multiplying population with IPCC default Degradable Organic Component (DOC) BOD (kg BOD/Cap/yr). As almost all wastewater ends in river without any treatment, maximum CH4 production capacity (kg/CH4/kg BOD) from organically degradable wastewater of 0.6 and Methane correction factor of 0.1 and Emission Factor (kg CH4/kg BOD) of 0.06 were used to compute Methane emission. Similarly, per capita protein consumption of 24.09 kg/yr was used to estimate Nitrogen in effluent (FAO, 2016). Similarly, GHG emission from Industrial Wastewater handling was estimated indirectly by calculating GHG emission to produce various industrial products. Details about industrial products produced are given in Table 5.5. Various GHG emissions estimated from domestic and domestic wastewater handling are listed in Table 5.6.

Table 5.5 Industrial Production (in tons) from 2000/1 to 2013/14 (FAO, 2013; CBS, 2013; DoI, 2004/2005: 2006/2007: 2011/2012; FAO, 2016).

Sectors /Year

Alcohol Refining

Beer &

Malt

Dairy Products

Leather &

Tanning

Meat & Poultry

Pulp &

Paper

Soft Drinks

Sugar Refining

Vegetable Oils

2001 7458 26584 1124000 18300 194000 22516 39567 102131 133504

2002 8587 28795 1158780 18200 199000 25956 43550 91992 135774

2003 8978 29977 1162095 18600 204000 25813 49325 100229 131050

2004 9531 29078 1231853 19000 208000 27992 44376 97758 108281

2005 9495 30439 1274228 19500 215000 28689 45645 101600 115871

2006 10025 31457 1312140 19700 219000 29638 47584 103829 117734

2007 11171 35487 1351394 20100 227000 30959 50336 115609 117398

2008 11495 37040 1388730 20400 234000 31410 53611 121112 100820

2009 12471 56163 1445419 20800 242000 29830 58736 127253 98885

2010 15282 56626 1495897 21200 249000 24280 64215 141774 95588

2011 16660 56756 1556510 21800 277000 28501 74658 160462 85123

2012 13993 65897 1622751 22200 288000 27097 79097 187652 90295

2013 16163 79471 2225945 23400 295000 45043 78354 183880 168895

2014 18083 83402 2572846 23800 N/A 48354 79822 157666 160391

Total CH4 emission in 2011 was 22.354 Gg, out of which wastewater handling was the biggest contributor, closely followed by Solid Waste Disposal. Open burning contributes very small part of GHG emission (Table 5.6). This result showcases the rural characteristics of Nepali economy. Methane emission from solid waste is predominantly from urban areas whereas emission from wastewater handling is from throughout the country. GHG emission different activities can be observed from Figure 5.3. Government’s plan to promote generation of biogas from solid waste and force


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Hospitals to manage their own waste may drastically alter GHG emission contribution in future due to establishment of Incineration plant and Anaerobic Waste Treatment plants. Wastewater Treatment and Discharge contributes 70% of total GHG Emission while solid waste disposal contributes 28% of total GHG Emission (equivalent CO2). The emission from Waste Water Treatment and Discharge is significantly high because of presence of N2O during wastewater handling.

Figure 5.3 GHG Emission (CO2-eq) from different activities.

Table 5.6 GHG Emission from different Waste Categories, 2011.

Categories

Emissions [Gg] Emissions [Gg; CO2-Eq]

CO2 CH4 N2O CO2 CH4 N2O Total CO2-Eq

Solid Waste Disposal

10.4633 261.5813 261.5813

Biological Treatment of Solid Waste

0.1047 0.0063 2.6171 1.8718 4.4889

Open Burning of Waste

2.3617 0.3402 0.0061 2.3617 8.5057 1.8250 12.6924

Wastewater Treatment and

Discharge 11.4461 1.2036 286.1522 358.6615

644.8137

Domestic Wastewater

6.9628 1.2036 174.0689 358.6615 532.7304

Industrial Wastewater

4.4833 112.0833 112.0833

Total 2.3617 22.3543 1.2160 2.3617 558.8563 362.3583 923.5860


86

5.5 Trends in Greenhouse Gas Emission In 2011, wastewater handling contributed over 53% of CH4 emission. It was the most significant contributor of GHG emission for whole decade due to poor urbanization of the country. GHG emission from domestic wastewater handling was more than emission from Industrial wastewater handling which shows low level of industrialization in Nepal. Organic Waste (Food and garden waste) is the major GHG emitter followed by Paper and Textile (Figure 5.4). Linear Growth Trend of CH4, N2O and CO2 emissions from solid waste disposal activities was obtained due to result of linear population growth, which was used to assess waste generation (Figure 5.5 and Figure 5.6).

Figure 5.4 Trend of CH4 Emission (CO2 Equivalent) from different types of waste disposal.

Figure 5.5 Trend of CO2, CH4 and N2O Emission (CO2 Equivalent) from different types of

waste disposal.


87

Figure 5.5 shows overall GHG emission trend in Nepal from 2001 to 2014. The plot clearly shows that trend of GH4 emission is increasing at faster pace than N2O emission and CO2 emission. It can be attributed to CH4 emission associated with solid waste disposal. CH4 emission has followed same trend as of population growth. However, slower growth rate of CO2 and N2O suggests slow adoption of waste to energy technologies and slower industrial growth.

5.6 GHG Emission Projection Past trend and projection of population and municipal solid waste generation is presented in Figure 5.6. In business as usual scenario, it is assumed that urban population will continue to generate solid waste in same per capita generation. However, there is strong likelihood that per capita waste generation will continue to rise with changing lifestyle of people. Figure 5.7 presents Waste Generation Projection with different increment in per capita waste generation. It shows that by increment of 5% on per capita waste generation, solid waste generation will double by 2030. It shows urgency to bring new plans and policy to change current approach on waste sector management. It means intervention at various level needs to be made to control and reduce GHG emission.

Figure 5.6 Past trends (1991-2011) and projections (2012-2030) of Urban Population and Solid Waste.


88

Figure 5.7 Waste Generation Projection with different increment in per capita waste generation.

Projections of GHG emission alone doesn’t give clear picture to policymakers about sectoral aspect of GHG emission. By knowing sectoral GHG emission, intervention can be made at different levels (e.g., policy making, infrastructure development, provide tax incentives, etc) to reduce GHG emission. Figure 5.8 shows that the biggest contributor of GHG emission would be Organic waste followed by Paper Waste. By encouraging source selection of waste and production of compost, CH4 emission as a result of organic waste can be reduced. It can also be reduced by building Biogas plant to extract CH4 (and use it as fuel or raw material for industrial process) or by recovering CH4 from landfill site. Simple intervention like flaring of CH4 emitted from landfill site can significantly reduce GHG emission. Similarly, it also shows that by encouraging recycling of paper waste, GHG emission would be significantly reduced.

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

Waste(G

g)

YearNoIncrement 2.50% 5% 7.50%

0

100

200

300

400

500

600

Emission(Gg,CO 2Equivalent)

YearOrganicWaste PaperWaste Textile


89

Figure 5.8 GHG Emission Projection from different waste Categories.

Similarly, Figure 5.9 shows the trend of increasing contribution of N2O on GHG emission from domestic wastewater handling activities. It can be attributed to growing per capita protein consumption owing to changing food habit. It also shows the need of building wastewater treatment facilities to limit N2O emission growth.

Figure 5.9 GHG Emission Projection from Domestic Waste Water

GHG Emission Projection with Policy Intervention

To understand emission projection, it is important to judge effect of possible policy interventions that can affect GHG emission. Enforcing policy change can change GHG emission by reducing waste going for disposal or by treating waste with technology that emits less emission or both. GHG emission has been estimated assuming first intervention can happen only from 2018 and it remains flat till 2030.

a. Composting Composting is the simple and cost effective intervention that can reduce GHG emission and reduce amount of waste that goes to landfill. During composting GHG gas emitted are CH4 and N2O. Four scenarios of composting have been considered.

i. 5% of waste composted ii. 10% of waste composted iii. 15% of waste composted iv. 20% of waste composted

b. Anaerobic Treatment of Waste (Biogas)

0

100

200

300

400

500

600

700

800

900

1000

GHGEm

ission(Gg,CO 2Equivalent)

Year

CH4 N2O


90

Anaerobic treatment of solid waste produces biogas that is predominantly methane. During anaerobic decomposition of waste only CH4 is generated. N20 generated is insignificant in quantity. Four scenarios of composting have been considered.

i. 5% of waste composted ii. 10% of waste composted iii. 15% of waste composted iv. 20% of waste composted

Comparing Composting with Biogas it can be observed that CH4 emission from Composting is many times more than that from Biogas (Table 5.7). Similarly, N2O generated from biogas is insignificant while it is important factor (in terms of CO2 Equivalent) for Biogas.

Table 5.7 Comparison of Cumulative GHG Emission (Gg) between Composting and Biogas for different waste amount utilization (from 2018-2030).

CH4 N2O Waste Utilization

5% 10% 15% 20% 5% 10% 15% 20%

Composting 59.09 118.17 177.26 236.34 42.26 84.52 126.77 169.03 Anaerobic Treatment

11.82 23.63 35.45 47.27 - - - -

c. Carbon Capture Landfill sites emit a large amount of CH4 every year. Introducing carbon-capturing technologies can significantly reduce CH4 gas emitted into the environment. Three scenarios have been analyzed; Business as Usual (BAU), 5% methane capture, 10% methane capture and 20% methane capture, starting from 2018. CH4 emission at different scenarios for different years can be observed in Figure 5.10. By 2030 total amount of CH4 emission emitted by using carbon capture would be 5.84 Gg, 11.68 Gg and 23.36 Gg for 5%, 10%, and 20% methane capture scenario, respectively.


91

Figure 5.10. Projection of CH4 Emission from Landfill Sites (with and without carbon

capture scenario).

5.7 Perspectives for improvement The waste prevention and improved waste management can play important role in reducing GHG emissions and the development of a low carbon economy. Changes in waste policies are likely to change the amount of wastes generated, waste recycled or energy recovery from waste. Apart from reduced landfill requirement, most significant benefit from effort to reduce GHG emissions are reduced landfill methane generation, avoided fertilizer production associated with composting and anaerobic digestion and avoided energy used for transportation of fuel associated with production of biogas and biofuels. Table 5.8 shows what type of interventions can be done on different GHG sources to reduce emissions.

Table 5.2 Expected Intervention to reduce GHG emissions.

GHG Sources GHG gases Intervention

Landfills CH4 diversion to composting, Methane Recovery, and Biogas Production

Incineration & Open Burning

CO2, CH4, N2O Legal Intervention, Improvement of waste collection and disposal system, Energy recovery

Domestic Wastewater

CH4, N2O Legal enforcement to require people to build septic tank, building waste water treatment

system Industrial

Wastewater CH4 Separate Wastewater treatment facility on

factories. Improving water use efficiency in factories, promoting industries and services that

emits less GHG

0

5

10

15

20

25

201620172018201920202021202220232024202520262027202820292030

Emission(Gg)

Year

NoCapture 5%Capture 10%Capture 15%Capture 20%Capture


92

Source segregation of solid waste is the key to reduce GHG emission from various activities. Without source segregation, it would be very difficult to promote composting and biogas generation. Source segregation would also make it easier for recycler to collect paper and other products helping to further reduce emission. Implementing source segregation requires public awareness, policy enforcement, waste collection and management system improvement. Interestingly, improvement in waste management system would also contribute in GHG emission reduction in other subsectors. For example, CH4 recovery by building biogas plant produces CH4 which can be burned as fuel (displacing fossil fuel), digest can be used as organic manure in field (displacing Nitrogen fertilizer produced from petroleum product) and reduce volume of waste that ends up in disposal sites. As sanitary landfill site itself is also emitter of GHG gas, all landfill sites should be equipped with methane capture system. Methane trapped in landfill sites can also be extracted and utilized. Similarly, strict enforcement of environmental safeguards standards is required for industries to reduce GHG emission from industrial wastewater. Industrial activities to reduce GHG emission should also improve their efficiency by reducing required raw material demand and energy use.


93

6. WayForwardsThis GHG inventory suggests a net GHG emissions of 31,998.91 Gg CO2-eq from Nepal in the base year 2011. This quantity represents about 0.060% of Nepal’s contribution to the global emission of total 53,197,386.48 Gg CO2-eq (Olivier and Janssens-Maenhout, 2014). The projection until 2030 indicates that a net increasing trend of GHG emission can be expected in the coming days, however an uncertainty exists due to existing data quality. Until completion of this much part of the national GHG inventory, we suggest necessities of some considerations for ensuring a better quality next inventory.

- Need to address in minimizing data gaps and inconsistencies; - Develop country specific emission factor for GHGs inventory; - Need to promote research in different sectors taking into consideration of the

academic as well as research institutions; - Need to institutionalize the mechanism to monitor, carry on field surveys, and

prepare the reports on the regular basis; It can be achieved by giving responsibility to one or more relevant institution (s) to undertake these tasks.

- Need to updated existing activities data in a systematic manner; - The industrial output and export/import data should be properly managed at

national level to maintain an accurate data bank of the industrial processes and product uses. The same applies in other sectors. The industries may also be required to submit the production and sales data to the government on a continuous basis;

- Need to mobilize various institutions to archive in a proper format in a regular way with the national perspective, which at present is carrying on as per the institutional need.

- Need regular training to build the capacity of the individuals as well as the relevant institutions.

- Adhoc kind of mechanism in the preparation of GHGs inventory exists. It lacks the continuity in the inventory preparation process and also the matter of accountability.

- Institutional memory has to be strengthened, which at present is very weakly exist;


94

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97

ANNEXES

Annex 1:

Tier 1 Method for Cement Production

In this method the clinker production is estimated from the use of cement production data. After the clinker production is estimated, we can use the emission-factor approach to calculate the CO2 emissions by employing the following equation: CO2 Emissions = [∑i(Mci • Ccli) − Im + Ex] • EFclc

Where, CO2 Emissions: emissions of CO2 from cement production, tonnes;

Mci : weight (mass) of cement produced of type i, tonnes;

Ccli : clinker fraction of cement of type i, fraction;

Im: imports for consumption of clinker, tonnes; Ex: exports of clinker, tonnes;

EFclc: emission factor for clinker in the particular cement, tonnes CO2 /tonne clinker

Annex 2: Tier 2 Method for Cement Production

In this method, the clinker production data from the plants are directly used in the following formula to calculate the CO2 emissions: CO2 Emissions = Mcl • EFcl • CFckd

Where, CO2 Emissions: emissions of CO2 from cement production, tonnes;

Mcl : weight (mass) of clinker produced, tonnes;

CFckd : emission correction factor for CKD (cement kiln dust), dimensionless;

EFcl : emission factor for clinker, tonnes CO2 /tonne clinker


98

Annex 3: Urban Population & Municipal Solid Waste

(Continued….)

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0.

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9035

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25

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71

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20

1504

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1880

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01

3760

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0.

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006

9401

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26

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5473

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1563

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2932

3 19

549

1954

9 97

74

3909

7 97

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0.

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48

872

9774

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27

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009

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40

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3 20

309

2030

9 10

154

4061

7 10

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8 1.

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50

771

1015

43

2028

91

1001

5 59

0282

16

8652

16

8652

31

622

2108

1 21

081

1054

1 42

163

1054

074

1.05

41

5270

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20

29

9449

402

6122

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35

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3280

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867

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9334

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9390

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18

1313

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996

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1133

204

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32

5666

0 11

3320


99

Yea

r Po

pula

tion

Mun

icip

al S

olid

Was

te G

ener

atio

n by

Cha

ract

eris

tics

(ton)

, Ann

ual

Gg/

year

Was

te

for

Com

post

Was

te

for

Ope

n bu

rnin

g O

rgan

ic

Plas

tics

Pape

r G

lass

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etal

s Te

xtile

s

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ber

&

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her

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ers

Tota

l(ton

) 19

91

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24

3924

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98

10

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0 19

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68

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84

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3283

9 20

00

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925

1961

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02

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0.

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3 20

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4 74

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3861

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958

3991

6 20

04

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374

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7 72

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8 91

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1823

7 45

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0.

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4559

2 20

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4073

549

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437

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2015

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586

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18

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08

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16

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16

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9 14

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20

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35

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19

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176

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16

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19

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19

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32

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0.

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36

662

7332

4 20

20

6615

881

4286

75

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78

1224

78

2296

5 15

310

1531

0 76

55

3062

0 76

5491

0.

7655

38

275

7654

9 20

21

6902

867

4472

70

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91

1277

91

2396

1 15

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87

3194

8 79

8696

0.

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39

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0 20

22

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49

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49

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28

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41

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23

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899

4859

54

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44

1388

44

2603

3 17

356

1735

6 86

78

3471

1 86

7776

0.

8678

43

389

8677

8 20

24

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177

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94

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70

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70

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7 18

071

1807

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36

3614

2 90

3561

0.

9036

45

178

9035

6 20

25

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202

5264

71

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20

1504

20

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803

1880

3 94

01

3760

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0.

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26

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549

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0.

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27

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009

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40

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68

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309

2030

9 10

154

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1542

8 1.

0154

50

771

1015

43

2028

91

1001

5 59

0282

16

8652

16

8652

31

622

2108

1 21

081

1054

1 42

163

1054

074

1.05

41

5270

4 10

5407

20

29

9449

402

6122

72

1749

35

1749

35

3280

0 21

867

2186

7 10

933

4373

4 10

9334

3 1.

0933

54

667

1093

34

2030

97

9390

8 63

4594

18

1313

18

1313

33

996

2266

4 22

664

1133

2 45

328

1133

204

1.13

32

5666

0 11

3320


100

Annex 4: Emission for Inventory Year 2011

Categories

Emissions [Gg] Emissions [Gg; CO2-Eq]

CO2 CH4 N2O CO2 CH4 N2O Solid Waste

Disposal 10.4633 261.5813

Biological Treatment of Solid Waste

0.1047 0.0063 2.6171 1.8718

Open Burning of Waste

2.3617 0.3402 0.0061 2.3617 8.5057 1.8249

Wastewater Treatment and

Discharge 11.4461 1.2036 286.1522 358.6615

Domestic Wastewater

6.9628 1.2036 174.0689 358.6615

Industrial Wastewater

4.4833 112.0833

Total 2.3617 22.3543 1.2160 2.3617 558.8563 362.3584


101

Annex 5: Waste Generation Projection till 2030 indifferent per capita waste growth scenario

Yea

r

Population (Million)

BA

U

2.5

0%

5

%

7.5

0%

1

0%

Per

C

apit

a W

aste

(g

m/d

ay)

Was

te

(to

n)

Per

Cap

ita

Was

te

(gm

/day

)

Was

te

(to

n)

Per

Cap

ita

Was

te

(gm

/day

)

Was

te

(to

n)

Per

Cap

ita

Was

te

(gm

/day

)

Was

te

(to

n)

Per

Cap

ita

Was

te

(gm

/day

)

Was

te

(to

n)

20

16

5.5

53

11

5.7

05

64

2

13

0.9

1

72

7

14

7.6

7

82

0

16

6.1

1

92

2

18

6.3

4

10

34

71

5

20

17

5.8

05

11

5.7

05

67

2

13

4.1

8

77

9

15

5.0

6

90

0

17

8.5

7

10

37

20

4.9

8

11

89

99

0

20

18

6.0

67

11

5.7

05

70

2

13

7.5

4

83

4

16

2.8

1

98

8

19

1.9

6

11

65

22

5.4

8

13

67

95

7

20

19

6.3

37

11

5.7

05

73

3

14

0.9

8

89

3

17

0.9

5

10

83

20

6.3

6

13

08

24

8.0

2

15

71

77

1

20

20

6.6

16

11

5.7

05

76

5

14

4.5

9

56

17

9.5

1

18

8

22

1.8

3

14

68

27

2.8

3

18

04

98

7

20

21

6.9

03

11

5.7

05

79

9

14

8.1

1

10

22

18

8.4

7

13

01

23

8.4

7

16

46

30

0.1

1

20

71

61

2

20

22

7.1

98

11

5.7

05

83

3

15

1.8

1

10

93

19

7.8

9

14

24

25

6.3

6

18

45

33

0.1

2

23

76

09

8

20

23

7.5

1

15

.70

5

86

8

15

5.6

1

11

67

20

7.7

9

15

58

27

5.5

8

20

67

36

3.1

3

27

23

45

2

20

24

7.8

09

11

5.7

05

90

4

15

9.5

1

24

6

21

8.1

8

17

04

29

6.2

5

23

13

39

9.4

5

31

19

33

7

20

25

8.1

25

11

5.7

05

94

0

16

3.4

9

13

28

22

9.0

9

18

61

31

8.4

7

25

88

43

9.3

9

35

70

12

9

20

26

8.4

48

11

5.7

05

97

7

16

7.5

8

14

16

24

0.5

4

20

32

34

2.3

6

28

92

48

3.3

3

40

82

97

7

20

27

8.7

76

11

5.7

05

10

15

17

1.7

6

15

07

25

2.5

7

22

17

36

8.0

3

32

30

53

1.6

6

46

65

86

5

20

28

9.1

1

11

5.7

05

10

54

17

6.0

6

16

04

26

5.2

2

41

6

39

5.6

4

36

04

58

4.8

3

53

27

78

7

20

29

9.4

49

11

5.7

05

10

93

18

0.4

6

17

05

27

8.4

6

26

31

42

5.3

1

40

19

64

3.3

1

60

78

89

7

20

30

9.7

94

11

5.7

05

11

33

18

4.9

7

18

12

29

2.3

8

28

64

45

7.2

1

44

78

70

7.6

4

69

30

57

3


102

Annex 6:

GHG Emission (Gg) without carbon capture and with different scenario of carbon capture

Year No Capture 5% 10% 15% 20%

2016 11.64365737 11.64366 11.64366 11.64366 11.64366

2017 12.15501081 11.54726 10.93951 10.33176 9.724009

2018 12.69433897 12.05962 11.42491 10.79019 10.15547

2019 13.26102255 12.59797 11.93492 11.27187 10.60882

2020 13.85452461 13.1618 12.46907 11.77635 11.08362

2021 14.4743465 13.75063 13.02691 12.30319 11.57948

2022 15.12001131 14.36401 13.60801 12.85201 12.09601

2023 15.79096875 15.00142 14.21187 13.42232 12.63278

2024 16.48660954 15.66228 14.83795 14.01362 13.18929

2025 17.20630797 16.34599 15.48568 14.62536 13.76505

2026 17.94942878 17.05196 16.15449 15.25701 14.35954

2027 18.75779503 17.81991 16.88202 15.94413 15.00624

2028 19.53945231 18.56248 17.58551 16.60853 15.63156

2029 20.34344469 19.32627 18.3091 17.29193 16.27476

2030 21.1689043 20.11046 19.05201 17.99357 16.93512

Documents

€™s GHG Inventory... · Final Report on Nepal’s GHG Inventory Report for Third National Communication 2 Authors and Contributors WORKING TEAM Team Leader Dr. Madan Lall Shrestha