CGER-REPORTISSN 1341-4356
CGER-I152-2020

Report of the Mutual Learning on
Greenhouse Gas Inventories in 2020
21st, 22nd, and 28th July 2020

Greenhouse Gas Inventory Office of Japan (GIO), CGER, NIES

Center for Global Environmental Research

National Institute for Environmental Studies, Japan

CGER-REPORTISSN 1341-4356
CGER-I152-2020

Report of the Mutual Learning on
Greenhouse Gas Inventories in 2020
21st, 22nd, and 28th July 2020

Greenhouse Gas Inventory Office of Japan (GIO), CGER, NIES

Center for Global Environmental Research

National Institute for Environmental Studies, Japan

Report of the Mutual Learning on Greenhouse Gas Inventories in 2020
Prepared by:Greenhouse Gas Inventory Office of Japan (GIO)
Center for Global Environmental Research (CGER)
National Institute for Environmental Studies (NIES)
16-2 Onogawa, Tsukuba, Ibaraki 305-8506 Japan
Fax: +81-29-850-2219
E-mail: www-gio@nies.go.jp
http://www.nies.go.jp/gio/
Copies available from:Center for Global Environmental Research (CGER)
National Institute for Environmental Studies (NIES)
16-2 Onogawa, Tsukuba, Ibaraki 305-8506 Japan
Fax: +81-29-858-2645
E-mail: www-cger@nies.go.jp
http://www.cger.nies.go.jp
Copyright 2020:
NIES: National Institute for Environmental Studies
All rights reserved. No part of this publication may be reproduced or transmitted in any
form or by any means, electronic or mechanical, including photocopy, recording, or any
information retrieval system, without permission in writing from NIES.
All copies in PDF format are available from: http://www.cger.nies.go.jp
This publication is printed on paper manufactured entirely from recycled material (Rank A), in
accordance with the Law Concerning the Promotion of Procurement of Eco-Friendly Goods
and Services by the State and Other Entities.

CGER-I152-2020, CGER/NIES

Contents
Foreword .............................................................................................................................................. i
Preface ................................................................................................................................................. ii
List of Acronyms and Abbreviations .............................................................................................. iii
1
Executive Summary of the Mutual Learning on Greenhouse Gas Inventories in 2020 .... 1
2
Report on the Mutual Learning Sessions ............................................................................... 3
2.1

Overview of the Mutual Learning .................................................................................................3

2.2

Cross-Cutting Issues .......................................................................................................................6

2.3

Energy Sector ..................................................................................................................................9

2.4

Agriculture Sector ........................................................................................................................12

2.5Land Use, Land-Use Change and Forestry (LULUCF) Sector ................................................15

Annex I: Agenda .............................................................................................................................. 19
Annex II: List of Participants ......................................................................................................... 21

CGER-I152-2020, CGER/NIES

Foreword
The international community now recognizes increases in anthropogenic emissions of greenhousegases (GHGs) as the primary cause of climate change and its impacts. The 5th Assessment Report,
published by the Intergovernmental Panel on Climate Change (IPCC) in 2013, stated that “theatmospheric concentrations of the greenhouse gases carbon dioxide (CO2), methane (CH4), and nitrous
oxide (N2O) have all increased since 1750 due to human activity.” Moreover, many GHG observatories,
including Mauna Loa Observatory in Hawaii, have detected that the yearly mean concentration of CO2
surpassed 400 ppm since 2015. To address mitigation and adaptation to climate change, all of us on
the globe must be making more efforts than ever in each of our respective fields. To this end, theConference of the Parties (COP) to the United Nations Framework Convention on Climate Change(UNFCCC) agreed to hold the increase in the global average temperature to well below 2°C above
pre-industrial levels under the Paris Agreement at COP21 in 2015.
“Measurement, Reporting, and Verification”, abbreviated as MRV, and transparency of mitigation
actions are becoming increasingly important. In this respect, national GHG inventories, which provide
information on GHG emissions and their trends over time, play a critical role as a basis for decisionmakers to design and implement strategies of their countries’ mitigation actions for reducing GHG
emissions. Against this background, all parties will soon be required to submit Biennial Transparency
Reports under the Paris Agreement Enhanced Transparency Framework.
In order to support the enhancement of capacities for national GHG inventories in Asian countries,
the National Institute for Environmental Studies (NIES) has been organizing the “the Workshop on
GHG Inventories in Asia (WGIA)” annually since November 2003 with the support of the Ministry of
the Environment of Japan (MOEJ). This workshop supports government officials, compilers, andresearchers in the Asian countries to develop and improve their GHG inventories through enhancing
regional information exchange. The Greenhouse Gas Inventory Office of Japan (GIO), affiliated with
the Center for Global Environmental Research (CGER), NIES, has functioned as the Secretariat forthis workshop since its first session.
Unfortunately, this year, in light of the global pandemic, the Workshop had to be cancelled toprevent any risk of the spreading of COVID-19, and only Mutual Learning sessions (sector-by-sector
discussions between pairs of countries) were conducted online on July 21st, 22nd, and 28th. Mutual
Learning has been held during WGIA since WGIA9 in 2011 when it first became a regular session.
This report serves as the report of the Mutual Learning Sessions on Greenhouse Gas Inventories in2020 (ML2020). We hope that it will be useful for all those who work in the field of GHG inventories
as well as climate change, and will contribute to the further progress of inventory development in Asia.

Nobuko Saigusa

Director
Center for Global Environmental Research
National Institute for Environmental StudiesiiPreface
An important lesson that we have learned from the history of the UNFCCC is the importance of
MRV and transparency. This includes measuring the effects of emissions reduction initiatives,
reporting the results of the measurements in the international arena, and verifying the status of
reductions. MRV and transparency ensures and enhances the accuracy of reports on each country’s
mitigation actions.
For the steady implementation of MRV and transparency, it is essential to develop national systems
for the preparation of national GHG inventories and to improve the accuracy of the inventories. In
the Paris Agreement, the importance of establishing an enhanced transparency framework to build
mutual trust and confidence and to promote effective implementation is stated. The purpose of theframework for transparency of actions is to provide a clear understanding of climate change actions,
including clarity and tracking of progress towards achieving the Parties’ individual nationallydetermined contributions (NDCs) to inform the global stocktake. Each Party shall provide national
inventory reports and information necessary to track progress made in implementing and achieving
its NDC under the Paris Agreement in Biennial Transparency Reports. Against this background, GHG
inventories are being accepted more and more as being valuable because they support thetransparency of national mitigation actions.
WGIA has contributed significantly to the construction and consolidation of a network of officials
involved in GHG inventory preparation in Asian countries, and to the identification and provision ofsolutions for common issues relevant to the inventories.
This year, however, the physical workshop of WGIA was cancelled due to COVID-19, and only
Mutual Learning (ML) Sessions on Greenhouse Gas Inventories were conducted online.
The outcomes of the ML2020 are summarized in this report. We hope that this report will be founduseful and will contribute to the further improvement of the GHG inventories of the WGIA-member
countries.
In conclusion, we would like to thank all the attendees for their participation and active contribution
to this year’s ML Sessions.

Yukihiro Nojiri

Toru Hayashi

ManagerGreenhouse Gas Inventory Office
Center for Global Environmental Research
National Institute for Environmental Studies

Chief Official
Decarbonized Society Promotion Office
Global Environment Bureau Ministry of the
Ministryof theJapan
Environment, Japan
Environment,ii
ii

CGER-I152-2020, CGER/NIES

List of Acronyms and Abbreviations
BUR
CO2-eq.
CGER
COP
CRF
CS
F-gases
GHG
GIO
GWP
HWP
IP
IPCC
KP
LULUCF
ML
MMS
MOEJ
MRV
NAI
NC
NDC
NIES
NIR
QA
QC
SOC
UNFCCC
WGIA
1996 IPCC GLs
2006 IPCC GLs

CO2
CH4
N2O
HFCs
PFCs
SF6
NF3

Biennial Update Report
Gas Emission in CO2 equivalent
Center for Global Environmental Research
Conference of the Parties
Common Reporting Format
Country SpecificFluorinated Gases (HFCs, PFCs, SF6, NF3)
Greenhouse Gas
Greenhouse Gas Inventory Office of Japan
Global Warming Potential
Harvested Wood Products
Industrial Processes
Intergovernmental Panel on Climate Change
Kyoto Protocol
Land Use, Land-Use Change and Forestry
Mutual Learning
Manure Management System
The Ministry of the Environment, Japan
Measurement, Reporting and Verification
Measurable, Reportable, and Verifiable
Non-Annex I
National Communication
Nationally Determined Contribution
National Institute for Environmental Studies, Japan
National Inventory Report
Quality Assurance
Quality Control
Soil Organic Carbon
United Nations Framework Convention on Climate ChangeWorkshop on Greenhouse Gas Inventories in Asia
Revised 1996 IPCC Guidelines for National Greenhouse Gas Inventories
2006 IPCC Guidelines for National Greenhouse Gas Inventories
Chemical terms

Carbon dioxide
MethaneNitrous oxide
Hydrofluorocarbons
Perfluorocarbons
Sulfur hexafluoride
Nitrogen trifluoride

iii
iii

Photos of the Online Meeting
Cross-Cutting Issues

Energy Sector

Agriculture Sector

LULUCF Sector

iv
iv

1. Executive Summary of the Mutual Learning on
Greenhouse Gas Inventories in 2020

CGER-I152-2020, CGER/NIES

1

Executive Summary of the Mutual Learning on Greenhouse Gas Inventories
in 2020

The Ministry of the Environment of Japan (MOEJ) and the National Institute for Environmental
Studies (NIES) have annually convened WGIA since 2003 in order to support non-Annex Ⅰ (NAI)
Parties in Asia to improve the accuracy of their GHG inventories and to facilitate the enhancement ofcooperative relationships in the Asian region.
This year, in light of the global pandemic, the Workshop was cancelled to prevent any risk of the
spreading of COVID-19, and only ML sessions (sector-by-sector discussions between pairs ofcountries) were conducted online in response to interests expressed. ML has contributed to theadvancement of the participants’ basic knowledge of GHG inventory estimation methodology,
reporting rules, data collection, institutional arrangements, including quality assurance and quality
control (QA/QC), and other related issues. Since it first started in 2011, ML has been held ten times,
with 29 pairs of countries participating, including four pairs this year.
This year’s session has succeeded in enhancing capacity-building in MRV/Transparency, andstrengthening the network of inventory experts and others in Asia.
A total of 36 participants attended the ML this year, including government and research
representatives from Cambodia, China, Indonesia, Japan, Mongolia, Myanmar, and Singapore.

Mutual Learning of each sector’s Greenhouse Gas Inventories

This year’s ML was held for the following four sectors: Cross-cutting issues (Indonesia-Japan),
Energy sector (Cambodia-Myanmar), Agriculture sector (China-Japan), and Land Use, Land-Use
Change and Forestry (LULUCF) sector (Singapore-Mongolia). Inventory personnel from participating
countries posed questions and provided answers on the development of each other’s inventory andnational system by e-mail in advance, and then engaged in online discussions to make improvements
through learning about each other’s inventory in detail and exchanging views.
The participating countries expressed interest in continuously improving their inventory throughdeveloping their own country-specific calculation methods and introducing methodologies based on
the 2006 IPCC Guidelines (GLs), which will be mandatory under the rules of the Paris Agreement.
Through learning in depth about the methodology and the national system for data collection andinventory development of the other country, each country used their newly-acquired knowledge as areference for future inventory improvements to regularly report under the Paris Agreement.
Although this online meeting was a first-time attempt, detailed discussions between the pairs ofcountries led to the strengthening of the network among inventory experts. In order to provide many
learning opportunities in the future, it was requested that mutual learning be held on an ongoing basis.

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1. Executive Summary of ML2020

22. Report on the Mutual Learning Sessions

CGER-I152-2020, CGER/NIES

2

Report on the Mutual Learning Sessions
2.1 Overview of the Mutual Learning

ML is an activity to improve the individual countries’ inventories through the following series ofprocesses: 1) exchanging inventories between two countries, 2) perusing a partner’s inventory, and 3)
exchanging comments on each other’s inventories. The primary purpose of the ML is to improve GHG
inventories by providing details of methods and data for GHG emission/removal estimation between
two countries and by exchanging comments on the methods and data. The ML is also expected to fosterand strengthen a cooperative relationship among GHG inventory experts. Since the aim of the ML is
not criticism or audit, participants can conduct a two-way communication and follow-ups throughdirect conversation.
The first ML was held on the Waste sector between GIO and Korea Environment Corporation(KECO) in the annual workshop in 2008. The Secretariat of WGIA introduced this activity in WGIA8
held in 2010. With the participants’ agreement, ML has been held as a regular session since WGIA9 in
2011. In this year 2020, however, in light of the global pandemic of COVID-19, the physical meetingof WGIA was cancelled to prevent any risk of spreading the COVID-19. Instead, the WGIA ML
Secretariat who concurrently serves as the ML Secretariat planned and conducted the remote ML
sessions via the Internet.
Table 2.1.1 History of ML

GeneralEnergy2008-2010
2010

WGIA8

2011

WGIA9

-

2012

WGIA10-2013

WGIA11-

2014

WGIA12-

2015

WGIA13

JapanVietnam

2016

WGIA14-2017

WGIA15-2018

WGIA16-2019

WGIA172020

ML2020IP*1
Agriculture
LULUCF
Trial implementation Japan - Korea

Introduction to ML (with hands-on training)

ChinaSingapore
IndonesiaJapan

IndonesiaMongolia--

CambodiaThailand
Lao PDRThailand
IndonesiaMyanmar

IndonesiaJapan--

BruneiKorea
MongoliaVietnam
IndiaVietnam
ThailandJapan
CambodiaMyanmar

MyanmarMalaysia

IndonesiaVietnam
ChinaMyanmar
ChinaMongolia
IndonesiaLao PDR

-

-

-

-

-

-

-

* Industrial Processes*2Reporting from Vietnam with comments from experts
1

Waste

CambodiaPhilippines
ChinaJapan

JapanLao PDR-

IndonesiaCambodiaKorea
ChinaKorea
MalaysiaVietnam

Vietnam*2-

CambodiaMongolia
IndonesiaLao PDR
Lao PDRMyanmar

KoreaMyanmar
MongoliaThailand
ChinaPhilippines
JapanLao PDR--

Mongolia
Singapore-

Participants
In December 2019, the WGIA Secretariat advertised the ML to the participants of WGIA andreceived applications from 22 groups from eight parties. Considering the participants’ potential
332. Report on Mutual Learning Sessioninterests and knowledge, an appropriate balance among sectors, and the feasibility of implementation,
the Secretariat set up four pairs (Indonesia and Japan on the General sector, Cambodia and Myanmar
on the Energy sector, China and Japan on the Agriculture sector, and Mongolia and Singapore on the
LULUCF sector).
Preparation
A few months before the remote session of the ML, the chosen participants submitted the materialsof their inventories to the Secretariat, including worksheets used for estimating emissions and reports
describing details of methodologies, and exchanged the materials with their partner countries throughthe Secretariat. Through studying the materials provided by the partner country, the participants foundgood points, such as advanced methodologies and well-institutionalized inventory management
systems, as well as unclear points and issues to be improved in the partner’s inventory. Thus,
participants wrote such findings as comments and questions to their partner countries onto “Question
and Answer Sheets”. After that, the “Question and Answer Sheets” were shared with the partnercountries through the Secretariat. The partner countries responded to these comments and questions
before the ML sessions took place.
Process
Material submission
Material exchange
Studying the materials
Comment exchange
Answers to comments
Sessions
Sector
GeneralEnergyAgriculture
LULUCF*1Biennial Update Report*2National Communication

Table 2.1.2 Preparation Process of the ML
Schedule
Middle of May to middle of June 2020
End of May to middle of June 2020
June, July 2020
Late June to middle of July 2020
July 2020
21st, 22nd, and 28th July 2020

Table 2.1.3 Submitted Materials for the ML
Country
Inventory
Indonesia
BUR2*1 in 2018, NC3*2 in 2017
Japan
NIR in 2020
Cambodia
NC2 in 2015
NC1 in 2012, National GHG Inventory of the Energy Sector
Myanmarin Myanmar
China
BUR2 in 2018
Japan
NIR in 2020
Mongolia
BUR1 in 2017, NC3 in 2018
Singapore
NC4 and BUR3 in 2018

Discussions
In the ML2020, four ML sessions were organized and implemented on July 21st (General,
Agriculture), 22nd (Energy), and 28th (LULUCF) to discuss sector-specific issues based on
preliminary comment exchanges. To encourage a frank discussion and to ensure confidence, thesesessions were held as closed-door discussions in a virtual meeting room on the Internet.
In these sessions, participants discussed their counterpart's inventory and national system, sharing
their own technical issues (e.g., data collection, adoption of emission factors, national system, etc.)
44

CGER-I152-2020, CGER/NIES
with the partner country to overcome the obstacles, and clarifying matters in their own inventory whichshould be improved. Through the discussions, they recognized that the inventories of participant
countries have been continuously improved by adopting the methodologies of the 2006 IPCC GLs.
Closely studying the improvement of not only the methodology of the counterpart countries’
inventories but also their national systems for data collection and quality assurance/quality control,
participants found hints for improvements of their own inventories. To increase opportunities to learn
from other countries’ inventories, participants expressed their hope for the continuous implementationof the ML programme in the future.
The points of discussions and outcomes of each individual ML session are summarized in thefollowing sections (2.2 - 2.5).

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2. Report on Mutual Learning Session

2.2 Cross-Cutting Issues
Sector Overview
Indonesia and Japan participated in the ML session on cross-cutting issues. The general information
for the two countries is as shown in Table 2.2.1 below.
Table 2.2.1 Sector Overview for the ML on Cross-Cutting Issues
Indonesia
Japan
National total GHG
1,457,774
1,183,016
emissions (kt-CO2-eq., with (3 gases, in 2016, BUR2)(7 gases and indirect CO2, in
LULUCF)2018, CRF2020)
Responsible agency for the
Ministry of Environment
Ministry of the Environment
inventory
and Forestry (MoEF)(MOEJ)
Methodological basis

2006 IPCC GLs

2006 IPCC GLs

Materials Used
To prepare for the ML 2020, the partner countries exchanged their documents relevant to crosscutting issues through the Secretariat approximately six weeks before the remote session. The
documents exchanged were as follows:Indonesia- Indonesia Third National Communication (NC3), 2017
- Indonesia Second Biennial Update Report (BUR2), 2018
- Summary of “Guidance to the Implementation and Reporting of National Greenhouse Gases
Inventories”, Director General of Climate Change Regulation No. 73/2017- Summary of “Guidance of Quality Assurance and Quality Control (QA/QC) of Greenhouse Gas
Inventories”, Director General of Climate Change Regulation No. 10/2018
Japan- National Greenhouse Gas Inventory Report of JAPAN, 2020
Questions and Answers
After receiving the materials listed above, the countries studied them and submitted questions andcomments to the partner country three weeks before the remote session. The classification and thenumber of questions are as follows.
Table 2.2.2 Classification of Questions and Comments in the ML on Cross-Cutting Issues
Number of questions/comments
Classification of questions
from Japan to Indonesia from Indonesia to Japan
National system
3
4
Inventory compilation processes
2
3
Data collection procedure
1
2
Quality Assurance/Quality Control
1
1
Others2
1

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Outcomes of the Mutual Learning Session
Through the ML session, several issues and good practices in the participating countries’ preparationof GHG inventory were identified.
➢Issues and Solutions / Outstanding issues
The following were identified as issues, and the partner countries’ experience was shared to seek
options and solutions:1) There is a time lag for institutions in publishing data needed for inventory. The inventory
schedule, in certain cases, cannot match the publication periods of the data provider.
(Indonesia/Japan)
2) Utilizing the bottom-up approach (using data reported from local governments) in inventory
compilation is an ongoing process and the gap with the top-down approach (using nationaldata) still needs to be narrowed. (Indonesia)
3) There is a challenge for the general public to fully understand the process of recalculations (e.g.,recalculations due to changes in Global Warming Potential (GWP) or methodology).
(Indonesia).
4) From the viewpoint of speeding up data provision, data provided by ministries are preferred todata published by the Centralized Statistical Bureau. (Indonesia)➢Good Practices
The following were identified as good practices:Indonesia
1) A legal system for the institutional arrangement of the National GHG Inventory has beendeveloped by MoEF Regulation No. 73/2017.
2) Responsibilities are clearly defined in the institutional arrangement to prepare the inventory by
sector and led by Directorate General of Climate Change (DGCC), Ministry of Environment
and Forestry (MoEF).
3) An annual GHG estimation cycle is established, including estimating preliminary figures.
4) A national inventory system has been set up to promote the ministries’ ownership of mitigationin their relative sectors.
5) National Industry Information System (SINAS) has been set up to collect activity data,
mitigation actions, energy uses, and as a compliance monitoring system for industries.
6) QA activities have been steadily implemented under DGCC Regulation No. 10/2018.
Japan
1) The QA mechanism of Japan is feasible to implement.
2) There is a process in place to engage various stakeholders in the inventory process without
specific regulation/enforcement.
3) Japan’s emission reduction has been reflected in the GHG inventory through the use of Country
Specific (CS) Emission Factor for N2O from sewage sludge incineration, etc.
➢Suggestions for Future ML
The participants’ suggestions for future ML were as follows:
1) Learn more about the Japanese F-gas inventory system.
2) Learn more about the Japanese QA activities.
3) Engage in remote ML if circumstances similar to the current COVID-19 pandemic occur.

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2. Report on Mutual Learning Session
PartiesIndonesia

Japan

Table 2.2.3 Participants in the ML on Cross-Cutting Issues
Name
Organization
Ms. Masri Akma Yeni GHG Inventory Unit, Ministry of Environment andForestry of Indonesia (MoEF)
Ms. Oktavia Endah
Riana
Dr. Irawan Asaad
GHG Inventory Office of Japan (GIO)
Dr. Takefumi Oda(Facilitator)
Ms. Elsa Hatanaka
Ms. Eriko Hirata
Mr. Takashi Morimoto Mitsubishi UFJ Research and Consulting Co., Ltd.
(Resource person)
Ministry of the Environment, Japan (MOEJ)
Mr. Yoshihiro Okada(Workshop organizer)

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2.3 Energy Sector
Sector Overview
Cambodia and Myanmar participated in the ML session on the Energy sector. The general
information for the two countries is as shown in Table 2.3.1 below.
Table 2.3.1 Sector Overview for the ML on the Energy Sector
Cambodia
MyanmarNational total GHG-457-67,820emissions (kt-CO2-eq., with (in 2000, NC2)
(in 2000, NC1)
LULUCF)GHG emissions of the
2,767
7,863
Energy sector (kt-CO2-eq.)(in 2000, NC2)
(in 2000, NC1)
Responsible agency for theinventory

Ministry of Environment

Environmental Conservation
Department

Estimation methodology
Source of emission factors
Source of activity data

1996 IPCC GLs1), Tier 1
IPCC default values
National statistics

2006 IPCC GLs, Tier 1
IPCC default values
National statistics

Note:1) Cambodia plans to apply the 2006 IPCC GLs in the next NC submission.

Materials Used
To prepare for the ML 2020, the partner countries exchanged their documents relevant to the Energy
sector through the Secretariat approximately two months before the workshop. The documents
exchanged were as follows:
Cambodia- Spreadsheet
Myanmar- Sectoral reporting tables exported from the IPCC Inventory Software version 2- National GHG Inventory of Energy Sector in Myanmar (PDF document)
Questions and Answers
After receiving the materials listed above, the countries studied them and submitted questions andcomments to the partner country approximately a month before the remote session. The classificationand the number of questions are as follows.

992. Report on Mutual Learning Session
Table 2.3.2 Classification of Questions and Comments in the ML on the Energy Sector
Number of questions/comments
Classification of questions
from Cambodia to from Myanmar to
MyanmarCambodia1)
Acquisition of activity data11
Adoption of emission factors or parameters
1
1
Estimation methods
3
3
Institutional arrangement
00
Others02Note:1) Myanmar provided additional 25 questions after the exchange of the Q&A sheet.

Outcomes of the Mutual Learning Session
Through the ML session, several issues and good practices in the participating countries’ preparationof GHG inventory were identified.
➢Issues and Solutions / Outstanding issues
The following were identified as issues, and the partner countries’ experience was shared to seek
options and solutions:1) Smuggling of fuel across the border makes the emission estimates of the reference approach
uncertain. (Cambodia)
2) The archiving of calculation sheets is not fully sufficient. (Cambodia)
3) Disaggregated data are not available for the sectoral approach, especially for eachmanufacturing industry. (Myanmar)
4) Disaggregated data are not available for the sectoral approach. (Cambodia)5) It is difficult to make data providers understand the necessity of data. (Myanmar)➢Good Practices
The following were identified as good practices:
Cambodia
1) Fuel supply and demand data from ministries (e.g. Ministry of Mines and Energy) have been
compared with international data (International Energy Agency, and Economic ResearchInstitute for Asia).
2) All types of fuel have been included in the worksheets.
3) The UNFCCC software has been used.
4) Key Category Analysis has been conducted.
Myanmar1) The National Inventory Report has been prepared.
2) The IPCC Inventory Software has been used for emission estimation as well as Uncertainty
Assessment, Key Category Analysis, and archiving.
3) The national data have been compared with IEA data from 1990 to 2015.
4) The IPCC Emission Factor Database has been used for EFs that are not available in the IPCC
software (e.g. transport and residential).
➢Follow-up Activities
The following were identified as possible follow-up activities:
1) Participate in ML again to report the progress of the identified issues.
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10CGER-I152-2020, CGER/NIES
2) Provide written answers to additional questions. (Cambodia)
3) Check the methodology of fuelwood in the LULUCF sector to avoid omission of the fuelwood
emissions between energy and LULUCF sectors. (Myanmar)➢Suggestions for Future ML/WGIAs
The participants’ suggestions for future ML were as follows:
1) Continue to conduct WGIA in each country.
2) Discuss the difference between Revised 1996 IPCC GLs and 2006 GLs in the plenary sessionof WGIA.
3) Conduct ML again by the same pair of countries.
Table 2.3.3 Participants in the ML on the Energy Sector
Countries
Name
Organization
Cambodia Mr. Sophal Leang
Department of Climate Change
Ms. Reasey Phoeuk
Mr. Sokhim Pich
MyanmarMs. Thi Thi Soe Min
Environmental Conservation Department
Ms. Yu Yu Khing
Ms. Swe Lin Myint
Ministry of Electricity and Energy
Mr. Kyaw Moe Aung
Project Coordinator, Second National
Communication projectDr. San Win
Environmental Conservation Department
Facilitators Mr. Naofumi Kosaka
GHG Inventory Office of Japan (GIO)(Facilitator)
Mr. Hiroshi Ito (Secretariat)
Ms. Eriko Hirata (Secretariat)
Observer
Mr. Yu Gonda
Ministry of the Environment, Japan (MOEJ)(Workshop organizer)

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2.4 Agriculture Sector
Sector Overview
China and Japan participated in an ML session on the Agriculture sector. The general informationof the two countries is shown in Table 2.4.1.
Table 2.4.1 Sector Overview for the ML on the Agriculture Sector
China
Japan
National total GHG
11,186,000 (in 2014, BUR2)
1,183,016 (in 2018,
emissions (kt-CO2-eq., with
NIR2020)
LULUCF)GHG emissions in the
830,000 (in 2014, BUR2)
33,252 (in 2018, NIR2020)
Agriculture sector (kt-CO2eq.)
Responsible agency for the
The National Leading Group Ministry of the Environment
inventory
on Climate Change, Energy(MOEJ)
Conservation, and Emissions
Reduction
Estimation methodology
1996 IPCC GLs, Tier 1/Tier2006 IPCC GLs
2, and CS model
Source of emission factors
Country-specific values andCountry-specific values and
IPCC default values
IPCC default values
Source of activity data
National statistics
National statistics
China Agriculture Yearbook
Materials Used
To prepare for the ML session, both countries exchanged their documents relevant to GHG emission
estimation of the sector with each other two months before the remote session. The exchanged
documents were as follows:
China:- The People’s Republic of China Second Biennial Update Report on Climate Change- Agro-GHG Platform for Planting or Breeding Enterprises- GHG Emissions from China Croplands in 2014
- Yao Huang et al., Modeling methane emission from rice paddies with various agricultural
practices, 2004
- Yao Huang et al., Estimates of methane emissions from Chinese rice paddies by linking amodel to GIS database, 2006
- Xunhua Zheng et al., Description and Application of a Model for Simulating Regional
Nitrogen Cycling and Calculating Nitrogen Flux, 2008
- Yao Huang et al., Agro-C: A biogeophysical model for simulating the carbon budget ofagroecosystems, 2009
Japan:- Japan. 2020 National Inventory Report (NIR)- Japan. 2020 Common Reporting Format (CRF) Table
Questions and Answers
After receiving the materials listed above, both countries studied them and provided questions and
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comments to their partner country approximately four weeks before the remote session. The
classification and the number of questions are shown in Table 2.4.2.
Table 2.4.2 Classification of Questions and Comments in the ML on the Agriculture Sector
Number of questions/comments
Classification of questions
from China to from Japan to
Japan
China
Acquisition of activity data25Adoption of emission factors or parameters
32
Estimation methods
5
4Institutional arrangement
02
Others41
Outcomes of the Mutual Learning Session
Through the ML, several issues and good practices in the participating countries’ preparation of
GHG inventory were identified.
➢Issues and solutions / Outstanding issues
The main issues discussed in the session were as follows:
1) The N2O estimation method for N mineralization in mineral soils is not in line with the
2006GLs, and therefore efforts have been made to improve the method. (Japan)
2) Some data are from the statistical yearbook, but other minor data are from sources that are notpublicly available. (China)3) It is difficult to acquire certain statistical data. (China)4) Some surveys to collect statistical data have been cancelled, and therefore solutions are being
explored. (Japan)
5) Estimation for grains cultivated in upland fields needs to be further disaggregated. (China)
6) Consistency of data across sectors is subject to improvement. (Japan/China)➢Good Practices
Good practices of the participant countries’ inventories were pointed out as follows.
China:
1) The organizations involved in the preparation of GHG inventory must report their work
progress to the Leading Group every three months during inventory compilation, and a coreteam of experts has been established and they work with persistent efforts.
2) The Tier 3 methods, which are based on comprehensive estimation models, were applied for
Cropland.
3) CS emission factors and estimation methodology for rice paddy field and agricultural soils
were developed.
Japan:
1) The emission factors of cattle are categorically provided according to factors such as animal
growth stages, feeds, body weights, and milk.
2) Emissions from livestock manure management systems (MMS) are very detailed and theinventory utilizes a lot of local MMS information in Japan.
3) Data used for soil carbon stock estimation is very comprehensive in the LULUCF sector.

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2. Report on Mutual Learning Session➢Follow-up activities
The following were proposed as possible follow-up activities:
1) Results from a new survey of Soil Organic Carbon (SOC) in land converted to grassland will
be reflected soon. (Japan)
2) More information on live stocks can be shared in future WGIAs/ML. (China)➢Suggestions for future ML
Suggestions for future ML from participants were as follows.
1) Exchange information to reflect emission reduction based on mitigation action in the
agriculture sector.
2) Continue communication with other countries and share data and best practices.
Parties
China
Japan

Table 2.4.3 Participants in the ML on the Agriculture Sector
Name
Organization
Dr. Han Shenghui
Institute of Atmospheric Physics, Chinese Academy of
Sciences
Prof. Zhang Wen
Dr. Yu Yongqiang
Mr. Hiromi Yoshinaga Greenhouse Gas Inventory Office of Japan (GIO)(Facilitator)
Mr. Hiroshi Ito
Dr. Wakana Taki
Ms. Atsuko Hayashi

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CGER-I152-2020, CGER/NIES

2.5 Land Use, Land-Use Change and Forestry (LULUCF) Sector
Sector Overview
Mongolia and Singapore participated in the ML session on the LULUCF sector. The general
information for the two countries is as shown in Table 2.5.1 below.
Table 2.5.1 Sector Overview for the ML on the LULUCF Sector
Mongolia
Singapore
National total GHG
10,030.80
50,908.13
emissions (kt-CO2-eq., with (in 2014, BUR1)(in 2014, BUR3)
LULUCF)GHG emissions/removals of -24,451.93
62.03
the LULUCF sector (kt(in 2014, BUR1)(in 2014, BUR3)
CO2-eq.)Responsible agency for theinventory

Ministry for Environment and National Parks
Tourism (MET)
Board (NParks)

Estimation methodology
Source of emission factors

2006 IPCC GLs, Tier 1/Tier 2
IPCC default values andcountry-specific values
Mainly National statistics andInternational data source
statistics

Source of activity data

2006 IPCC GLs, Tier 2/Tier 3
IPCC default values andcountry-specific values
National statistics

Materials Used
To prepare for the ML session, the partner countries exchanged their documents relevant to the
LULUCF sector through the Secretariat approximately two months before the ML meeting. The
documents exchanged were as follows:
Mongolia- Mongolia Third National Communication (NC3)- Mongolia’s Initial Biennial Update Report (BUR1)- Mongolia Sustainable Development Vision 2030
- Intended Nationally Determined Contribution of Mongolia- Calculation sheet-exported from IPCC Inventory Software for 2006 IPCC Guidelines
Singapore- Singapore’s Fourth National Communication (NC4) and Third Biennial Update Report (BUR3)- Chave, et al., Improved allometric models to estimate the above-ground biomass of tropical trees(2014) referenced for biomass estimation- Field survey sheet example for inventory data collection
Questions and Answers
After receiving the materials listed above, the countries studied them and submitted questions andcomments to the partner country approximately a month before the ML meeting. The classificationand the number of questions are as follows.

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2. Report on Mutual Learning Session
Table 2.5.2 Classification of Questions and Comments in the ML on the LULUCF Sector
Number of questions/comments
Classification of questions
from Singapore to from Mongolia to
Mongolia
Singapore
National system
00Inventory compilation processes
84
Data collection procedure
6
3
Quality Assurance/Quality Control
00Others20Outcomes of the Mutual Learning Session
Through the ML session, several issues and good practices in the participating countries’ preparationof GHG inventory were identified.
➢Issues and Solutions / Outstanding issues
The following were identified as issues, and the partner countries’ experience was shared to seek
options and solutions:
1)
2)
3)
4)

There is a lack of detailed information for uncertainty analysis (Mongolia).
Some categories are not estimated (Mongolia).
It is difficult to differentiate between anthropogenic and natural forest fires (Mongolia).
It is difficult to align data from satellite surveys / data from different agencies with data fromnational statistics (Mongolia).
5) It is difficult to collect data for year X-2 (Mongolia, Singapore).

➢Good Practices
The following were identified as good practices:
Mongolia
1) The 2006 IPCC GLs were applied.
2) In accordance with the 2006 IPCC GLs, Key category analysis was conducted for the data of
2014.
3) Uncertainty analysis was conducted qualitatively.
4) Memorandums of Understanding (MoU) on data exchange are made with major line ministries.
5) Harvested Wood Products (HWP) emissions/removals were estimated using the Kyoto Protocol(KP) Supplement.
6) Systematic surveys are conducted to detect land use and land-use change in forest areas.
7) Land use classification is aligned with that of the 2006 IPCC GLs.
8) Data collection for National Forest Inventory (NFI) has been improved to detect changes
occurring every 5 or 10 years.
Singapore
1) The 2006 IPCC GLs were applied.
2) The IPCC (2014) Wetlands Supplement was applied.
3) Key category and Uncertainty analysis were conducted qualitatively.
4) An institutionalized MRV system, including QA/QC process, is in place.
5) All land use and land-use change categories and all five carbon pools were included in theinventory.
6) High-resolution satellite images were acquired, covering 100% of the country and all land uses.
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CGER-I152-2020, CGER/NIES
7) Annual land-use change including small and dynamic land-use changes within Settlements wasanalyzed over the time series based on the satellite images acquired every 2 years.
8) Sampling methods in national studies are used for collecting data, including that for soil carbon
in Stocked Forest Areas and Tree-Covered Areas in Settlements.
➢Follow-up Activities
The following was identified as a possible follow-up activity:
1) Contact each other to continuously share more information.
➢Suggestions for Future ML
The participants’ suggestion for future ML was as follows:
1) Have ML again with a country with similar land circumstances.
Table 2.5.3 Participants in the ML on the LULUCF Sector
Name
Organization
Mr. Khongor Tsogt
Climate Change Project Implementing Unit
Environment and Climate Fund (CCPIU, ECF)
Ministry of Environment and Tourism
Singapore
Ms. Lorraine Tan
National Parks Board
Mr. Fairoz Mohamed
Mr. Hassan Ibrahim
Mr. Lek Kong Wan
National Environment Agency
Facilitators
Dr. Midori Yanagawa
GHG Inventory Office of Japan (GIO), National
and Resource (Facilitator)
Institute for Environmental Studies (NIES)
persons
Ms. Atsuko Hayashi(Sub-facilitator)
Ms. Elsa Hatanaka(Secretariat)
Mr. Atsushi Sato
Environment and Energy Dept., Mitsubishi UFJ(Resource person)
Research and Consulting Co., Ltd.
Mr. Akihiro Goto
Ministry of the Environment, Japan (MOEJ)(Workshop organizer)
PartiesMongolia

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Annex I: Agenda

CGER-I152-2020, CGER/NIES

Annex I: Agenda
Mutual Learning on GHG Inventories in 2020
Date: 21, 22, and 28 July 2020
Meeting Style: ONLINE

11:00 - 15:15 (JST) on 21st July

SectorCombination of Countries
Local Time(including 1h lunch break)Subjects

Agriculture

China
10:00-14:45 (CST)Japan
11:00-15:15 (JST)● Discussion on the Agriculture sector inventory (China)･Q&A, explanation, comments, future improvements, etc.
● Discussion on the Agriculture sector inventory (Japan)･Q&A, explanation, comments, future improvements, etc.
● Overall discussion･Issues and solutions, Outstanding issues, Good practices, Followup activities, Suggestions for future ML

12:00 - 16:15 (JST) on 21st July

SectorCombination of Countries
Local Time(including 1h lunch break)Subjects

GeneralIndonesia
10:00-14:45 (WIB)Japan
12:00-16:15 (JST)● Discussion on the General sector inventory1) National system
2) Inventory compilation processes
3) Data collection procedure
4) QA/QC
5) Other issues･Q&A, explanation, comments, future improvements, etc.
● Overall discussion･Issues and solutions, Outstanding issues, Good practices, Followup activities, Suggestions for future ML1919

Annex I
16:00 – 19:30 (JST) on 22nd July

SectorCombination of Countries
Local Time(including 15min. break)Subjects

EnergyCambodia
14:00-17:30 (ICT)

Myanmar13:30-17:00 (MMT)● Discussion on the Energy sector inventory (Cambodia)･Q&A, explanation, comments, future improvements, etc.
● Discussion on the Energy sector inventory (Myanmar)･Q&A, explanation, comments, future improvements, etc.
● Overall discussion･Issues and solutions, Outstanding issues, Good practice, Followup activities, Suggestions for future ML

11:00 – 15:15 (JST) on 28th July

SectorCombination of Countries
Local Time(including 1h lunch break)Subjects

LULUCF

Singapore
10:00-14:15 (SGT)

Mongolia
10:00-14:15 (ULAT)● Discussion on the LULUCF sector inventory (Mongolia)･Q&A, explanation, comments, future improvements, etc.
● Discussion on the LULUCF sector inventory (Singapore)･Q&A, explanation, comments, future improvements, etc.
● Overall discussion･Issues and solutions, Outstanding issues, Good practices, Followup activities, Suggestions for future ML2020

Annex II: List of Participants

CGER-I152-2020, CGER/NIES

Annex II: List of Participants

JAPAN
Mr. Yu GONDA
Decarbonized Society Promotion Office,Global Environment Bureau,
Ministry of the Environment, JapanBY PARTICIPATING COUNTRIES(Alphabetical order by family name)

Mr. Akihiro GOTO
Decarbonized Society Promotion Office,Global Environment Bureau,
Ministry of the Environment, JapanCAMBODIA
Mr. Sophal LEANG
Department of Climate Change, General
Secretariat of National Council for Sustainable
Development, Ministry of Environment

Ms. Elsa HATANAKA
Greenhouse Gas Inventory Office of Japan,
Center for Global Environmental Research,
National Institute for Environmental Studies

Ms. Reasey PHOEUKDepartment of Climate Change, General
Secretariat of National Council for Sustainable
Development, Ministry of Environment

Ms. Atsuko HAYASHI
Greenhouse Gas Inventory Office of Japan,
Center for Global Environmental Research,
National Institute for Environmental Studies

Mr. Sokhim PICH
Department of Climate Change, General
Secretariat of National Council for Sustainable
Development, Ministry of Environment

Ms. Eriko HIRATA
Greenhouse Gas Inventory Office of Japan,
Center for Global Environmental Research,
National Institute for Environmental Studies

CHINA
Dr. HAN Shenghui
Institute of Atmospheric Physics,
Chinese Academy of Sciences

Ms. Naoko IKEDA
Greenhouse Gas Inventory Office of Japan,
Center for Global Environmental Research,
National Institute for Environmental Studies

Dr. YU Yongqiang
Institute of Atmospheric Physics,
Chinese Academy of Sciences

Mr. Hiroshi ITO
Greenhouse Gas Inventory Office of Japan,
Center for Global Environmental Research,
National Institute for Environmental Studies

Prof. ZHANG Wen
Institute of Atmospheric Physics,
Chinese Academy of Sciences

Mr. Naofumi KOSAKA
Greenhouse Gas Inventory Office of Japan,
Center for Global Environmental Research,
National Institute for Environmental Studies

INDONESIA
Dr. Irawan ASAAD
GHG Inventory Unit,
Ministry of Environment and Forestry

Mr. Takashi MORIMOTO
Environment and Energy Dept., Mitsubishi UFJ
Research and Consulting Co., Ltd.

Ms. OKTAVIA Endah Riana
GHG Inventory Unit,
Ministry of Environment and Forestry

Dr. Takefumi ODA
Greenhouse Gas Inventory Office of Japan,
Center for Global Environmental Research,
National Institute for Environmental Studies

Ms. MASRI Akma Yeni
GHG Inventory Unit,
Ministry of Environment and Forestry
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21Annex II
Mr. Yoshihiro OKADA
Decarbonized Society Promotion Office,Global Environment Bureau,
Ministry of the Environment, Japan

Ms. YU YU KHING
Environmental Conservation Department,
Ministry of Natural Resources andEnvironmental Conservation

Mr. Atsushi SATO
Environment and Energy Dept., Mitsubishi UFJ
Research and Consulting Co., Ltd.

SINGAPORE
Mr. Fairoz MOHAMED
National Parks Board

Dr. Wakana TAKI
Greenhouse Gas Inventory Office of Japan,
Center for Global Environmental Research,
National Institute for Environmental Studies

Mr. Hassan IBRAHIM
National Parks Board
Ms. Lorraine TAN
National Parks Board

Dr. Midori YANAGAWA
Greenhouse Gas Inventory Office of Japan,
Center for Global Environmental Research,
National Institute for Environmental Studies

Mr. Lek Kong WAN
Resource Conservation Department,
National Environment Agency

Mr. Hiromi YOSHINAGAGreenhouse Gas Inventory Office of Japan,
Center for Global Environmental Research,
National Institute for Environmental Studies

MONGOLIA
Mr. Khongor TSOGT
Environment and Climate Fund,
Ministry of Environment and Tourism

MYANMAR
Mr. KYAW MOE AUNG
Project Coordinator,
Second National Communication projectDr. SAN WIN
Environmental Conservation Department,
Ministry of Natural Resources andEnvironmental Conservation
Ms. SWE LIN MYINT
Ministry of Electricity and Energy
Ms. THI THI SOE MIN
Environmental Conservation Department,
Ministry of Natural Resources andEnvironmental Conservation
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