Section 4. Carbon Stock Measurement
Methods
4.8. Monitoring non-CO2 GHGs
USAID LEAF
Regional Climate Change Curriculum Development
Module: Carbon Measurement and Monitoring (CMM)
Name
Affiliation
Name
Affiliation
Deborah Lawrence, Co-lead
University of Virginia
Megan McGroddy, Co-lead
University of Virginia
Bui The Doi, Co-lead
Vietnam Forestry University
Ahmad Ainuddin Nuruddin
Universiti Putra Malaysia
Prasit Wang, Co-lead
Chiang Mai University,
Thailand
Mohd Nizam Said
Universiti Kebangsaan Malaysia
Sapit Diloksumpun
Kasetsart University, Thailand
Pimonrat Tiansawat
Chiang Mai University, Thailand
Pasuta Sunthornhao
Kasetsart University, Thailand
Panitnard Tunjai
Chiang Mai University, Thailand
Wathinee Suanpaga
Kasetsart University, Thailand
Lawong Balun
University of Papua New Guinea
Jessada Phattralerphong
Kasetsart University, Thailand
Mex Memisang Peki
PNG University of Technology
Pham Minh Toai
Vietnam Forestry University
Kim Soben
Royal University of Agriculture, Cambodia
Nguyen The Dzung
Vietnam Forestry University
Pheng Sokline
Royal University of Phnom Penh,
Cambodia
Nguyen Hai Hoa
Vietnam Forestry University
Seak Sophat
Royal University of Phnom Penh,
Cambodia
Le Xuan Truong
Vietnam Forestry University
Choeun Kimseng
Royal University of Phnom Penh,
Cambodia
Phan Thi Quynh Nga
Vinh University, Vietnam
Rajendra Shrestha
Asian Institute of Technology, Thailand
Erin Swails
Winrock International
Ismail Parlan
FRIM Malaysia
Sarah Walker
Winrock International
Nur Hajar Zamah Shari
FRIM Malaysia
Sandra Brown
Winrock International
Samsudin Musa
FRIM Malaysia
Karen Vandecar
US Forest Service
Ly Thi Minh Hai
USAID LEAF Vietnam
Geoffrey Blate
US Forest Service
David Ganz
USAID LEAF Bangkok
Chi Pham
USAID LEAF Bangkok
I
II
III
OVERVIEW: CLIMATE CHANGE AND FOREST CARBON
1.1
Overview: Tropical Forests and Climate Change
1.2
Tropical forests, the global carbon cycle and climate change
1.3
Role of forest carbon and forests in global climate negotiations
1.4
Theoretical and practical challenges for forest-based climate mitigation
FOREST CARBON STOCKS AND CHANGE
2.1
Overview of forest carbon pools (stocks)
2.2
Land use, land use change, and forestry (LULUCF) and CO2 emissions and sequestration
2.3
Overview of Forest Carbon Measurement and Monitoring
2.4
IPCC approach for carbon measurement and monitoring
2.5
Reference levels – Monitoring against a baseline (forest area, forest emissions)
2.6
Establishing Lam Dong’s Reference Level for Provincial REDD+ Action Plan : A Case Study
CARBON MEASUREMENT AND MONITORING DESIGN
3.1
IV
V
Considerations in developing a monitoring system
CARBON STOCK MEASUREMENT METHODS
4.1
Forest Carbon Measurement and Monitoring
4.2
Design of field sampling framework for carbon stock inventory
4.3
Plot Design for Carbon Stock Inventory
4.4
Forest Carbon Field Measurement Methods
4.5
Carbon Stock Calculations and Available Tools
4.6
Creating Activity Data and Emission Factors
4.7
Carbon Emission from Selective Logging
4.8
Monitoring non-CO2 GHGs
NATIONAL SCALE MONITORING SYSTEMS

Introduction:
3 minutes

Lecture/content:

Exercise/Group discussion: 20 minutes
30 minutes
At the end of the session, learners will be able to:

Name the major non-CO2 GHGs, and describe whey
they are concerns

Recognize the major drivers of Non-CO2 GHGs
emissions

Explain how to measure/monitor Non-CO2 GHGs.

What are the most important GHGs in the Earth’s
atmosphere?

Which ones are primarily generated by human activities
(Time 5 to 10 minutes)
Name
Pre-industrial
concentrations
Current*
concentrations
Carbon dioxide
280 ppm
395 ppm
Methane
722 ppb
1893 ppb
Nitrous oxide
270 ppb
326 ppb
Ozone
237 ppb
337 ppb

A measure of how much heat a GHG traps in the
atmosphere relative to CO2

Calculated over a specific time interval (20, 100, or 500
years)
UNFCCC GWPs for CH4 and N2O
Global Warming Potential (Time Horizon)
Species
20 years
100 years
500 years
CO2
1
1
1
CH4
56
21
6.5
N2O
280
310
170

Ozone and Non-methane volatile organic compounds
(NMVOCs) are other effective greenhouse gases

Non-methane volatile organic compounds (NMVOCs)
include CCl2F2, CHClF2, CF4 and C2F6

Formation of GHGs from precursor gases is considered
indirect emission (NOx, NH3, and CO are common
precursor gases)
CH4
N2O
CO2
CH4
N2O
CH4 (rice)
N2O (fertilizer)
livestock
crop production
N2O primarily emitted
during the processes of
nitrification and
denitrification
Fertilizer additions
CH4 emitted through methanogenesis
CO2 + 8 H+
CH4 +2 H2O
The formation of methane by microbes
known as methanogens

In guts of humans and other animals,
especially ruminant animals (e.g.
cattle, sheep)

In anoxic environments, such as
wetlands and landfills/ manure
storage

Also produced in biomass burning


CH4 and N2O produced from
decomposition of manure

CH4 produced under anaerobic
conditions

N2O produced under aerobic
or mixed aerobic/anaerobic
conditions
Emissions of gas from manure
depends on storage system
GHG emissions from Agriculture in CO2-e 1990-2011
6000000
5000000
4000000
Annex I
3000000
2000000
1000000
0
non Annex I
World


When they constitute a significant proportion of
emissions from LULUCF, for example:

Slash and burn agriculture

Conversion of forest to pasture for livestock production

Application of synthetic fertilizers for crop production
Non-CO2 emissions are included in emission factors for
land use and land use change

The amount of N2O and CH4 emitted by fires is a function
of:

Area burned

Mass of fuel available for combustion in area

Proportion of fuel actually combusted – depends on size
and architecture of fuel load (twigs burn more efficiently
than large logs) moisture content and type of fires

Amount of GHGs emitted per unit fuel consumed
Emissions from Biomass = (1)*(2)*(3)*(4)*(5)
(1) Area burned *
(2) Biomass burned *
(3) combustion factor *
(4) Emission Factor for gas *
(5) GWP of gas

Using the emissions factors on the previous table and the
GWP values presented at the beginning of the lecture
calculate the size of the effect in the atmosphere from CO2,
CH4 and N2O emitted from burning 100 ha of tropical forest
after 10 years and after 100 years. Assume 85% of the
biomass is combusted

15 minutes

Nitrogen emissions are calculated as a function (fx) of the
amount of fertilizer applied

CH4 emissions from rice production are a function of:

Area cultivated

Cultivation period

Emission factor based on rice ecosystem type, flooding
pattern before and after cultivation, type and amount of
organic amendments, soil type, rice cultivar
General Equation:
CH4 emissions = CH4 EF * number of animals
CH4 emissions factors are calculated as a function of
livestock type, feed intake, and the conversion of feed
energy to methane
General Equation:
Emissions + EF * population of livestock
Tier 1 calculations use default values
Tier 2 includes more subclasses of livestock groups based on
management of both livestock and manure. For N2O feed type is
an addition consideration

Global Warming Potentials (GWP)



Global warming impact of non-CO2 GHGs
Key non-CO2 GHGs (N2O and CH4 )

Major sources of non-CO2 GHGs

Agriculture, Biomass Burning and Livestock

Other non-CO2 GHGs (Ozone, NMVOCs and precursor
gases)
Approaches for estimating non-CO2 GHGs emissions

EPA 430-R-12-006: Global Anthropogenic Non-CO2 Greenhouse Gas Emissions:
1990 – 2030:
http://www.epa.gov/climatechange/Downloads/EPAactivities/EPA_Global_NonCO
2_Projections_Dec2012.pdf

Samir Amous, Non-co2 emissions from stationary combustion. IPCC:
http://www.ipcc-nggip.iges.or.jp/public/gp/bgp/2_2_NonCO2_Stationary_Combustion.pdf

Rose , Steven K. and Huey-Lin Lee . 2008. Non-CO2 Greenhouse Gas Emissions
Data for Climate Change , GTAP Working Paper No. 43 2008:
https://www.gtap.agecon.purdue.edu/resources/download/3674.pdf

http://homework.uoregon.edu/pub/oldestPC/docs/pdf/ch_7_projecting_growth_
of_ghg_emissions.pdf