Ghg assessment from forest fires - indonesia case study

Greenhouse Gasses
Assessment From Forest Fires:
Indonesia Case Study
Preliminary Assessment Report

Jakarta, November 2013

GREENHOUSE GASSES
ASSESSMENT FROM
FOREST FIRES:
INDONESIA CASE STUDY
Preliminary Assessment Report

Jakarta, November 2013

EXECUTIVE SUMMARY
In Indonesia, forest and land fires are direct threats that could lead to forest
destruction and resulting in negative impacts to the environment and human,
causing health and haze problem and directly emitting green house gasses
(GHG) that contribute to global warming. Most fires are generally caused by
human activities such as land conversion and clearing by burning, construction
of peat drainage that cause peat drying and easily burn, and other use of
fire by community related to land preparation and tenure. Data showed
that most forest and land fires occurred on outside concessions/forest areas
(64%), however there were also some fires recorded from the process of
management of concessions either, pulp plantation, timber concession, and
oil palm estates.
The recent 2013 fires, have made Indonesia experienced extensive media
coverage and world attention due to the occurrences of forest and land fires
mostly in Sumatera. The fires have caused serious impacts including smoky
haze that spread to Malaysia and Singapore where the pollution index was the
worst in 16 years.
Regulations have been issued and institutions have been assigned to prevent
and control forest and land fires. However forest and land fires still occur
almost every year. This is due to natural conditions in Indonesia and supported
by human activities as the causes of almost all fires. All ingridients of fires (fire
triangle) are available, heat, oxygen and potential fuel. Land preparation using
fire is still considered as the most effective way by local farmers and even
companies, although there is penalty for this.
In term of climate change, forest and land fires are the direct causes of
emission, especially peatland that contains high amount of carbon. However
up to present, uncertainty related to calculation of GHG emissions from peat
fires remains very high. This is due to lack of data, knowledge and information
on fire behavior that result in area burned and combustion factor. The use
of default values to calculate emission will have high uncertainties (Tier 1),
moreover measurement from a given peat fire, year, or location cannot be
extrapolated with confidence to other areas or years. To support the MRV in
GHG inventory in land use and forestry sector, including to calculate emission
from peatfires at particular period of time, some information is required such
as total area burned (including actual burned area from identified hotspots),
carbon stock of area burned, and fraction of biomass burning.

2

Greenhouse Gasses Assessment from Forest Fires: Indonesia Case Study - Preliminary Assessment Report

According to IPCC Guideline (2006), estimation of emission from any land and
forest fires including peatland fires, require information or data based on
general formula of :
Lfire = A MB Cf Gef 10 -3,
Where:
Lfire
A
MB
Cf
Gef

:
:
:
:
:

Amount of greenhouse gas emissions from fire, tonnes of each GHG
Area burnt, ha
Mass of fuel available for combustion, tonnes ha-1.
Combustion factor, dimensionless
Emission factor, g kg-1 dry matter burnt

Some activities required to calculate peatfire emission more accuratelly
include: Detecting fires and mapping burned areas, improving hotspots data,
to identify total burned areas, mapping of all land covers including peatlands
and their distribution based on peat depth and peat types to identify carbon
stock or availability of fuels, field observation to identify combustion factors
and necessary measurement to identify emission factors or the volume and
consumed biomass (fire intensity) of most fires, and eveloping the system of
general GHG inventory including estimation of emission from peatfires.
Exercise from this assessment shows that peatfires in 2007 resulted in total
emission of 147,9 Mt CO2-e in Sumatera and 94,2 Mt CO2-e in Kalimantan,
meanwhile in 2013, peatfires have emitted some 183,0 Mt CO2-e in Sumatera
and 54,9 Mt CO2-e in Kalimantan. This figures will vary greatly depending
on interval or period of estimation that reflect in total area burned, and
parameter used related to fuel mass, combustion factor and emission factor.
Improvement if estimation of emission from land and forest fires is required to
support the MRV in emission reduction or mitigation program. Some activities
are required to calculate peatfire emission more accuratelly , including:
• Detecting fires and mapping burned areas such as by improving hotspots
data.
• Mapping of all land covers including peatlands and their distribution based
on peat depth and peat types to identify carbon stock or availability of
fuels.
• Mapping of all land use to identify causes of fires, fire risk and fire effects
to establish prevention and control measures.
• Quantifying relevant emission factors and estimating the volume and
consumed biomass (fire intensity) based on field observation.
• Developing the system of general GHG inventory including estimation of
emission from peatfires


3

Moreover, mapping of all land use and land cover dynamics are required
to identify underlying causes of fires, fire risk and fire effects to establish
prevention and control measures. It is recommended that prevention actions
should be prioritized to control forest and land fires. Any areas should be
under management and kept safe from fires through several management
practices, and provided with sufficient resources. For community,
improvement of awareness, incentive system, prosperity approach and law
enforcement are required for fire preventions and control.

Keywords; Forest and land fires, peat land fires, GHG emission, haze, policy.

4


ACKNOWLEDGEMENTS
This report is a preliminary asessment on the assessment of haze impacts
including greenhouse gas emissions and policy recommendations for
preventing the forest and land fires, initiated by the National Council on Climate
Change (DNPI) and Japan International Cooperation Agency (JICA). This is to
response the recent 2013 fires, that have made Indonesia experienced world
attention due to the occurrences of forest and land fires mostly in Sumatera.
The fires have caused serious impacts including smoky haze that spread to
Malaysia and Singapore.
This assessment has identified the issues, causes of forest and land fires, as
well as methodology to estimate GHG emissions from land and forest fires.
From this assessment, further activities and program are required to improve
our efforts in prevention and control of future forest and land fires, as well
as to improve methodology to estimate emissions from forest and land fires.
Authors would like to thank to Agus Purnomo, Farhan Helmy, and Dody
Sukadri, DNPI, Bramantyo Dewantoputra, Project Officer of DNPI – JICA
Project, Yuniarto Nugroho for providing hotspots data, and Agus Djoko
Ismanto of CIFOR who provided valuable references.
Hopefully that this preliminary assessment would be continued with further
activities programs to improve Indonesia’s capacity to prevent and control
forest and land fires especially related to peatfires.

Leads Author: Ari Wibowo
Contributors: Farhan Helmy, Doddy Sukadri, Muhammad Farid, DNPI;
Agus Djoko Ismanto, CIFOR; Bramantyo Dewantoputra, JICA; Yuniarta
Nugraha, Luwin Eska, Waindo Spec Terra.
Reviewer: Agus Purnomo, Farhan Helmy, Doddy Sukadri, DNPI.


5

LIST OF CONTENTS
Executive Summary • 2
Acknowledgements • 5
List Of Content • 6
List Of Tables • 7
List Of Figures • 8
List Of Appendix • 9
I. INTRODUCTION • 10
1.1. Background • 10
1.2. Objectives • 11
II. ISSUE OF LAND AND FOREST FIRES • 12
2.1. Fire Occurrences • 12
2.2. The Recent Fires And Haze In Sumatera • 14
2.3. Drivers Of Forest And Land Fires • 18
2.4. Indonesia’s Response To The Fires And Smoke Haze • 19
2.5. Policy Redommendations For Preventing The Forest And Land Fires • 21
III. PEATLAND AND EMISSION • 24
3.1. About Peatland • 24
3.2. Sources Of Emissions And Sequestrations In The Peatland • 26
3.3. Carbon Sequestration In Peatland • 27
3.4. Emission From Drainaged Peatland • 28
IV. ESTIMATION OF EMISSION FROM PEAT FIRES • 29
4.1. Methodology To Calculate Emissions • 30
4.2. Example Of Estimation Of Emission From Peat Fires • 38
4.3. Improvement Of Methodology • 39
V. CONCLUSION AND RECOMMENDATION • 41
5.1. Conclusion • 41
5.2. Recommendations • 42
REFERENCES • 43
Appendix 1. • 46
Appendix 2. Some Photos • 58

6


LIST OF TABLES
Table 1. The area of forest and land fires in Indonesia during the period of
1997-2012 (Ministry of Forestry, 1998-2013) • 12
Table 2. Land use allocation (conservation, protection or production) and
land cover in Indonesia’s peat land by main islands with peat in 2006.
Source: Department of Forestry, Indonesia in Bappenas, 2009) • 24
Table 3. Emission factors for peatland drainaged for many purposses (Agus,
et al, 2012) • 28
Table 4. Total area of burned peatland (ha) • 29
Table 5. Emission from peatfires according to some studies (in million of ton
of CO2-e) • 30
Table 6. Target of hotspot reduction in National Action Plan of GHG • 32
Table 7. Carbon stock used as emission factor applied in preparation of
regional action plan of province (RAD) as reference for calculation
of GHG emission according to IPCC GL 2006 (Source: Santoso, 2012)
• 33
Tabel 8. Above ground stock of carbon on some natural forest cover.
(Sources: Team FORDA, 2010) • 34
Table 9. Peat specific density and carbon organic content • 35
Table 10. Default values of biomass consumption for fires in a range of
vegetation types (ton biomass/ha) to estimate Mb and Cf (IPCC,
2006) • 35
Table 11. Default of combustion factor values for fires in a range of vegetation
types (to be used as Cf) (IPCC, 2006) • 36
Table 12. Default emission factors for various types of burning (to be used as
Gef (g/kg) (IPCC, 2006) • 37
Table 13. Emission ratios for biomass fires, expressed relative to the carbon
emitted as CO2 • 37
Table 14. Excercise of estimation of emission from peatfires in Sumatera and
Kalimantan • 38


7

LIST OF FIGURE
Figure 1. The number of hotspots in Indonesia during the period of 19992013 (Data of NOAA by BPPT, 2013) • 13
Figure 2. The number of hotspots in Sumatera and Kalimantan during the
period of 1999-2013 (BPPT, 2013) • 14
Figure 3. NASA’s daily fire alerts in Sumatra during the month of June - August
2013, showing a peak in fire activity between 17 and 25 June. • 14
Figure 4. A snapshot over Riau showing the areas burned by the June 2013
fires (red) mapped using LANDSAT 8 imagery acquired on 25 June
2013 (background) with NASA’s fire alerts (yellow dots) detected
between 1 and 30 June 2013. • 15
Figure 5. The 100,000 ha area were mapped as burned (red) within the worstaffected LANDSAT scene (black box). NASA’s fire alerts are marked
with yellow points. Not all burned areas were indicated due to cloud
and haze cover and missing imagery. Most fires located on peat
soils (brown areas). • 15
Figure 6. Areas that burned in June 2013 (red) and natural forest cover in 2007
(green). • 16
Figure 7. Fire locations in Sumatera • 17
Figure 8. Hotspots distribution in Indonesia that show mostly outside forest
areas (MoF, 2009) • 18
Figure 9. Peatland distribution in main islands of Indonesia, in Sumatera,
6.436.649 ha, in Kalimantan, 4.778.004 ha and in Papua, 3.690.921
ha, with total of 14.9 million ha (Agus et al, 2012). • 25
Figure 10.
Sources of emission from peatland, from fires, and drainage
that lead to peat oxidation, compaction and peat subsidence that
release CO2, (IFCA, 2008). • 26
Figure 11.
Estimated carbon emissions from Indonesia’s peat lands as
a result of loss of above-ground biomass, peat oxidation and fires
(controlled and uncontrolled) (left) and their source area (right).
Source: Bappenas, 2009) • 27
Figure 12.
Source of emission and removal of GHG for AFOLU sector
(Source: IPCC, 2006) • 30

8


LIST OF APPENDIX
Appendix 1 Data of hotspots distribution based on adminsitrative border
(Data of NOAA by BPPT, 2013) • 46
Appendix 2 Some photos • 58


9

I. INTRODUCTION
1.1. Background
In the mid of the year 2013, Indonesia experienced extensive media coverage
and world attention. This was due to the occurrences of forest and land fires
mostly in Sumatera and Kalimantan. The fires have caused more serious
impacts compared to the forest and land fires occurred in 1997/ 1998. The
smoky haze from fires burning in Indonesia spread to Malaysia and Singapore
where the pollution index was the worst in 16 years (NBC News, June 2013).
Fires occur in Indonesia (and Southeast Asia) annually during dry season
(April-September) due to human activities such as land clearing for cultivation.
During pronounced ENSO years, when conditions are unusually dry, fires and
smoke tend to have a much more serious and far-reaching effects. During
the past three decades, serious fires have occurred in 1982-83, 1987, 1991
and 1994. Indonesia experienced an exceptional year in 1997/1998 between
August and November when extensive fires ravaged large areas of Indonesia,
particularly the islands of Sumatra and Kalimantan. The burnt area has been
estimated between 2 and 5 million ha (forest and non- forest), the number of
people affected by smoke haze and fire were 75 million, and the total economic
cost to the region was as much as US$ 5 billion (Rowell and Moore, 1999).
These forest and land fires, and the accompanying smoke haze, caused serious
air pollution, damage to public health, loss of life, destruction of property,
and substantial economic losses in many parts of Southeast Asia. In term of
climate change, the forest and land fire also contribute to the increase of the
emissions from Green House Gasses (GHG) released to the atmosphere.
Fire is the most direct cause of GHG emission. Emission released from peatland
fire is even much higher than mineral land because of the high organic content
of peat soils. Peatland stores high quantity of carbon not above the ground
but below the ground as peatsoil. Some areas contain deep peatsoil up to
8 meter and peat soil can store up to 500-800 ton C/ha (Agus, et al. 2012),
compared with above ground biomass of natural forest on mineral soil that
‘only’ range between 100-250 ton C/ ha (Team Forda, 2010). Information on
quantification of emission released by fires especially peatfires is important
to identify its real contribution to global warming. This is also to support
Indonesia’s commitment to reduce its GHG emission by 26% or 41% with
international assistance in 2020.
Indonesian peatlands, particularly in Sumatra and Kalimantan regularly
burn during dry season. Fires have been used by farmers even by large
companies to prepare land for cultivation and the fires have also been used
extensively for land of conversion for establishment of estate crops such as

10


oilpalm, agriculture lands and other land uses. Report to the UNFCCC through
the Indonesian Second National Communication revealed the highest
contribution of emisssion from landuse-land use change and forestry by 48%
and 12% from peatland fires (MOE, 2009).
Although many studies/ assessment about forest and peat land fires have
been developed, but this issue remains unsolved. The fires still occur especially
during the dry season in fire prone areas such as in Sumatera and Kalimantan.
Serious actions should be taken, considering the negative impacts of fires to
the environment and community.
The growing concern to tackle the issue of global warming especially from
land based sector has caused high attention to deal with forest fires. As a
direct cause with significant contribution of emission especially involving the
peatfires, quantification of emission from peatfires is important to estimate.
So far in Indonesia, there has been little attention and knowledge to estimate
emission from peatfires. Therefore, quantification of emission from peatfires
is important to identify its actual contribution to total emission from land
based sector. This is required to monitor the overall target of emission
reduction through MRV system, and ultimatelly to support necessary stepts
in prevention and control of peatfires.

1.2. Objectives
The objective from this activity is to make assessment on calculation of
emission of Green House Gasses (GHG) released from forest and land fires,
and analyze the drivers of haze and provide policy recomendation on how to
prevent future forest and land fires.


11

II. ISSUE OF LAND AND FOREST FIRES
2.1. Fire Occurrences
Forest fire is a condition where the area is affected by fires resulting in damage
of forest and or forest products that cause economic and environmental
losses. In term of forest fires, Indonesia is potential to burn. All ingredients of
fire triangle are available, namely, oxygen, fuel and heat. All forest types except
mangrove are susceptible to burn. This condition is supported by dry season
that occur every year during April-September with sometimes worst during
the El-Nino years. Human activities such as preparation of land by burning
for cultivation by local communities or even big companies sometimes often
trigger the occurrences of wild fires.
In Indonesia, the fire is a direct threat that could lead to forest destruction
and resulting in emissions. Unlike forest fires that occur in temperate areas
that mostly caused by lightning, fires in Indonesia are generally triggered
by human activities. Adinugroho et al (2005) stated that 99.9% of fires in
Indonesia are caused by human either deliberately or negligence. Some
causes of fires include land conversion and clearing by burning, construction
of peat drainage that cause peat drying and easily burn, and other use of fire
by community related to land preparation and tenure.
Large forest fire events occurred in 1982/1983 which burned areas measuring
at 2.4 to 3.6 million hectares in East Kalimantan. Since then, forest fires occur
at intervals of 1987, 1991, 1994, 1997/1998 and in 2006/2007. The widespread
fires in the year 1997/1998 coincided with the arrival of nature phenomenon
known as El Nino, which affects the ocean currents in the Pacific Ocean, and
has an impact on the long drought in the Southeast Asian region. Drought
that occurred has caused forest fires in various regions of Indonesia.
Figure 1 shows the area of forest fires occurred in Indonesia during the period
1997-2012. These official data of Ministry of Forestry have shown relatively
small figures compared with actual fires. These data were based on official
reports from the regions to the Ministry of Forestry through The Directorate
General of Forest Protection and Natural Conservation (Dirjen PHKA).
Table 1.

The area of forest and land fires in Indonesia during the period of 19972012 (Ministry of Forestry, 1998-2013)

Year

Year

Area Burned (ha)

Year

Area Burned (ha)

1997

263,991

2003

5,672

2009

8,803

1998

515,026

2004

5,348

2010

5,760

1999

44,090

2005

14,329

2011

3,219

2000

3,016

2006

35,497

2012

6,642

2001

14,329

2007

5,672

2002

12

Area Burned (ha)

7,203

2008

5,348


The occurences of forest fires are often detected by the occurrences of
hotspots monitored by sattellite censores especially NOAA and MODIS.
The number of hotspots detected during the period of 1997-2012 is shown
in the figure 1. It shows that the number of hotspots is strongly related to
the fire season and the incidence of El-Nino phenomena. However, some
studies suggested that not all hotspots are actually forest or land fires. The
occurrences of hotspots cannot be directly linked with area burned. During
fire season, several hotspots can be monitored repetitively at the same
places, some hotspots might not be forest or land fires and not all land and
forest fires can be detected as hotspots. Therefore, ground check is required
to identify actual fires in the field.

Figure 1. The number of hotspots in Indonesia during the period of 1999-2013 (Data
of NOAA by BPPT, 2013)

Data of hotspots can also be used to identify fire prone areas as shown in the
following Figure. Kalimantan, especially West Kalimantan, Central Kalimantan
and Sumatera, Riau and South Sumatera are provinces with high frequency
of hotspots. These areas are also known as areas with extensive areas of
peatland.


13

Figure 2. The number of hotspots in Sumatera and Kalimantan during the period of
1999-2013 (BPPT, 2013)

2.2. The Recent Fires and Haze in Sumatera
In mid 2013, forest and land fires occurred mainly in Sumatera, causing haze
pollution to the neighboring countries of Malaysia and Singapora. CIFOR has
made a preliminary analysis from new satellite imagery for the area in Riau
Province, Sumatra, which appears to have been worst affected by recent fires
(Gaveau and Salim , 2013). NASA’s daily fire alerts have been used to locate the
fires, additionally it was used higher-resolution imagery from the Landsat 8
satellite to map fire scars. The Landsat images were recorded on 25 June 2013.
Some findings were as follows:
There was a distinct peak in NASA’s daily fire alerts during a very short period
of time, between 17 and 25 June (Figure 3).

Figure 3. NASA’s daily fire alerts in Sumatra during the month of June - August 2013,
showing a peak in fire activity between 17 and 25 June.

14


There was found a strong spatial correspondence between fire alert locations
and observed burned areas in the Landsat 8 imagery of 25 June (Figure 4)

Figure 4. A snapshot over Riau showing the areas burned by the June 2013 fires (red)
mapped using LANDSAT 8 imagery acquired on 25 June 2013 (background)
with NASA’s fire alerts (yellow dots) detected between 1 and 30 June 2013.

A very high proportion of the fire scars were on peatland, as opposed to
mineral soil (Figure 5).

Figure 5. The 100,000 ha area were mapped as burned (red) within the worstaffected LANDSAT scene (black box). NASA’s fire alerts are marked with
yellow points. Not all burned areas were indicated due to cloud and haze
cover and missing imagery. Most fires located on peat soils (brown areas).


15

• Fire scars were predominantly observed in areas of established plantation
land use, both large and small scale. Most June 2013 fires in the studied
area have occurred outside natural forests. However, some of the fires
appear to have advanced from plantations into adjacent natural forest.
• Fire scars were observed both inside and outside boundaries of concession
areas, as determined from available official maps. Some fire scars outside
of these concession areas contain patterns that indicate plantation
establishment.
• Many of the June 2013 fire scars were in areas that were classified as
natural forest in 2007 (Figure 6).

Figure 6. Areas that burned in June 2013 (red) and natural forest cover in 2007 (green).

This observation has resulted hypothesis that many of the June 2013 fires
were part of the processes of plantation establishment and management.
The very short period over which fire incidents peaked, the high proportion
of fires occurring on peatlands, typical patterns of plantation management in
fire areas, and the lack of updated concession maps support this hypothesis.
Weather conditions (including wind patterns) exacerbated the haze problem
in June 2013 compared with previous fire incidents.
In August 2013, similar to the June fires, about 36 percent of fire alerts were
on land granted as concessions to oil palm, logging, and pulpwood companies
(according to maps from Indonesia’s Ministry of Forestry), however most fires
were recorded outside concession areas (64 %). Furthermore, the fire alerts
were more dispersed and in different locations compared with those of June
and July, showing that this problem remains widespread throughout the
region.

16


Figure 7. Fire locations in Sumatera

http://insights.wri.org/news/2013/08/indonesia-burning-forest-fires-flarealarming-levels#sthash.VRlt8hHY.dpuf


17

2.3. Drivers of Forest and Land Fires
Forest and land fires in Indonesia usually occur in dry season during AprilSeptember. Most of these fires are caused by human either deliberately or
negligence. Based on information on hotspots, most fires occurred outside
forest areas, as hown in the Figure 8.

Figure 8. Hotspots distribution in Indonesia that show mostly outside forest areas
(MoF, 2009)

Some causes of fires include:
• Most fires occurred outside forest areas, mostly were caused by local
people/communities in preparing land for cultivation or to regain their
right over land (Figure 8). However, some indigenous forest dwellers have
local wisdom or land-use and forest resource management skills, which
are highly adapted to the environment.
• Fire deliberately set for land preparation by company or community. As
land preparation by burning is considered the easiest and cheapest way to
prepare land for cultivation. CIFOR observation showed that many of the
June 2013 fires were part of the processes of plantation establishment and
management.
• Construction of peat drainage that cause peat drying and easily burn. Peat
in saturated condition is safe from fire. Most fires in Sumatera during fire
season in June 2013 occurred in peatland. Fires in peatland ususally occur
underground (ground fire) causing heavy smoke (haze) that spread to the
neighboring countries such as Malaysia and Singapore.
• Fires have strong relation with the occurrences of deforestation and
degradation. Fire risks increase dramatically by the conversion of natural
forests to other purposes such as estate crops and timber plantations,
and by the logging of natural forests, which opens the canopy and dries
out the ground cover. Logging and conversion have resulted in more

18


flammable condition, which increase the likelihood of fire. This condition
is also coupled with a severe El Nino climatic effect, which itself may be
intensified as a result of global climate change.
• Negligence such as fires escape from camp fires, illegal loggers, cigarrete
butts and others.
• Underlying causes include national land use policies and failure of
government intervention.

2.4. Indonesia’s Response to the Fires and Smoke
Haze
Regulations related to forest and land fires have been issued as follows:
• Acts/Law
• Law No 5/1967, renewed with No 41/1999 on Basic forestry
• Law No.5/1994 on ratification of UN Biodiversity
• Law No.6/1994 on ratification on UNFCCC
• Law No 23/1997 on enivironmental management
• Government Regulation
• PP No 28/1985 on Forest protection
• PP No 4/2001, on Control of damage and pollution of environment due
to forest and land fires
• Ministry of Forestry Regulation
• No. 195/Kpts-II/1986 on Guidance to prevent and control forest fire
• No. 523/Kpts-II/1993 on Guidance for protection in forest utilization
areas
• No 188/Kpts-II/1995 on Establishment of national forest fire control
center (PUS DALKARHUTNAS)
• No. 260/Kpts-II/1995 on Guidance to to prevent and control forest fire
• No. 365/Kpts-II/1997 on National mascot for forest fire control
• No. 97/Kpts-II/1998 on Procedures on forest fire handling
• State Ministry of Environment Regulation
• No. KEP-18/MENLH/3/1995 on Establishment of National Coordination
Agency for land fires
• No. KEP- 40/MENLH/09/97 on Establishment of National Coordination
Team for forest and land fires control


19

• DG of Forest Protection and Nature Conservation Regulation (PHKA)
• No.243/Kpts/DJ-VI/1994 on Technical guidance for prevention
control of forest fires in forest utilization areas and other areas.

and

• No. 244/Kpts/DJ-VI/1994 on Technical guidance of forest fire control
• No. 245/Kpts/DJ-VI/1994 on Fix procedure for the use of tools for forest
fire control
• No. 246/Kpts/DJ-VI/1994 on Guidance for preparation and placement
of fire signs
• No. 247/Kpts-DJ-VI/1994 on Guidance Standardization of infrastructure
for prevention and control of forest fire
• No. 248/Kpts/DJ-VI/1994 on Fix procedure for prevention and control
of forest fire
• No. 81/Kpts/DJ-VI/1995 on Guidance on implementation of forest and
land fires
• No. 46/Kpts/DJ- VI/1997 Technical guidance for self awareness and
working safety in forest fire suppression
• No. 47 /Kpts/DJ-VI/1997 Technical guidance for prescribed buring and
cancelled with No. 152/Kpts/DJ- VI/1997
• No. 48/Kpts/DJ- VI/1997 Technical guidance on command system of
forest fire control
• DG of Forest Utilization Regulation
• No.222/Kpts/IV- BPH/1997 on Technical guidance on Land preparation
for establishment of timber estates without burning
• DG of Estate Crop Regulation
• o No.38/KB.110/SK/Dj.Bun/05.95 on Technical guidance on land
preparation for estate crops without burning
• Local governments regulations related to fire control in several
provinces
In regional Asean and the Government of Indonesia has also assigned several
institutions charged with preventing, monitoring and controlling forest and
land fires. These institutions include:
• ASEAN Secretariat in Jakarta
• Ministry of Forestry and its office in provinces
• Ministry of Agriculture
• Ministry of Environment
• TKNPKHL: National Coordination Team for Land and Forest Fire Control

20


• Pusdalkarhutnas : Center of National Forest and Land Fires Control
• Bakornas PB: National Coordinating Board on Disaster Control
• Other related institutions such as Agency for Meteorology, Climate and
Geophysic (BMKG), LAPAN, BPPT, Transmigration, Agency for SAR, Police,
Army
by human activities as the causes of almost all fires. All ingridients of fires
(fire triangle) are available, heat, oxygen and potential fuel. Land preparation
using fire is still considered as the most effective way by local farmers and
even companies, although there is regulation and penalty for this.
Facts in the field show that management of forest fires in Indonesia is more
focussed on suppression aspect rather than prevention. This is shown by (a)
most institutions only act if there is already fire, and this requires big budget
compared with prevention efforts (b) short term programs are focussed on
suppression and (c) low commitment and willingness to alocate resources
including budget, human resources, technology and others as important
prevention and control mesures of forest and land fires (Suryadinata, et al,
2005)
Suppression alone is not effective if there is already big wildfire. Experiences
from developed countries such as America, Australia, Canada and others show
their difficulties to control foret fires. Therefore for Indonesia, attention and
resources should be given more to control fires. Prosperity approach to local
community, improve awareness and sense of belonging to forest resources
including to provide sufficient resources to control forest fires are the key
answers to prevent severe forest fires. Meanwhile, legal aspect or penalties
to those who make fires should be applied, especially for big companies that
are still using fires for their land preparation.

2.5. Policy Redommendations for Preventing the
Forest and Land Fires
Due to its natural condition, fires become potential threats for Indonesia in the
coming years. Availabilty of fuel, dry season and increasing human activities
will create repeated fire seasons. Efforts to control forest fires should be
focussed on prevention actions rather than suppression. The followings are
some important principles or measures that should be taken as prevention
actions:
• It is important that every piece of land should be someone’s responsibility.
For management purposes, each land should be under management


21

unit. This management unit wether under government or companies
(private sectors) should have management plan to protect its land from
disturbances such as fires. Resources should be allocated mainly for
prevention and to some extent for suppression efforts. Open access areas
are very vurnerable to disturbances like fire, because no one is responsible
to safeguard the areas. Therefore government program to establish forest
management unit (KPH) for production, conservation and protection
forests should be realized.
• Under clear management unit, enforcing existing legal requirements
is possible. For example, regulation of forbidding the cultivation of
peat more than three metres thick and zero burning policy can be
enforced. Furthermore, best practices such as soil management and
water management in peatland concession can be applied. Management
units can also the object of incentives as well as sanctions related to their
achievement in protection of land.
• Most fires occur on areas outside forest areas or belong to broad
community. Up to present, fires are still used for land preparation by
farmers. Uncontrolled fires often spread to become wild fires. Although
in some developed countries prescribed burnings are applied to reduce
fuel potency and intensity of fires, in Indonesia, this practice is almost
imposible. Safe prescribed buring cannot be guaranted with limited
knowledge and resources. Therefore, the approach should be through
awareness raising to community, socialization, improvement of their skill
to prepare land without fires and prosperity approach to reduce their
dependency to forest and improve their income through several programs.
• During dry season or fire season, under the supervision of local government
or related institutions , the use of fires for land preparation should be
prohibited. Legal action shoul also be applied.
• In some countries, and some areas of Indonesia, community voluntary fire
brigades can be established. Development of voluntary brigades for fire
control should be encouraged. These brigades should also given incentives
if they well performed in protecting their land from disturbances such as
fires. These brigades should also be improved through regular training
skill and provided with necessary tool/equipment.
• In broader level, government of Indonesia make cooperation with other
countries, including ratification of agreement on the transboundary haze
control. During fire seasons, supports from neigbouring coutries are
needed to control forest and land fires.
• Current maps that show land use and land cover including list of companies
that have been given licenses should be updated. This information and
data should be tranparent and accessible.
• To improve the quality of environment, activities of rehabilitation by
establishment of plantation on degraded land, enrichment planting can
also be done. In peatland, activities such as canal blocking or establishment

22


of small dam to prevent peatland drainage can be carried out by involving
local community. This is to improve prevention efforts and for climate
change, planting can be regarded as mitigation efort to sequester carbon.
Good practice has been applied through the program of KFCP (Kalimantan
Forest Carbon Partnership) in cooperation with Australia Government.
ITTO program on DA REDD+ in Meru Betiri National Park has also
conducted cooperation with community through facilitation of planting in
rehabilitation zone of Meru Betiri National Park
• For policy level in peatland, actions can be done through revising land
allocations in spatial plans and land swaps. This is the option to reduce
emissions through redirecting economic land use away from peat land to
mineral soils. The program includes:
1. Reclassification of forest in other land use (non-forestry area/APL) to
protection or conservation zone (revision of spatial plans)
2. Reclassification of remaining peat land that is not yet licensed for
production to protection or conservation (no new licenses on peat
and a revision of spatial plans). Governemnt has issued the President
Instruction No. 11/2011 on delay of new permit for opening of primary
forest and peatland, and renewed/extended with President Instruction
No. 6/2013 on delay of new permit and improvement of management
of primary forest and peatland.
3. Relocate licenses or parts of licenses where companies have not yet
initiated operations on the ground, from peat to mineral soils (land
swap). Revising land allocations in spatial plans and land swap will
require government action and support from the private sector. There
is regulation on termination of a plantation holder’s right if plantation
development has not commenced after three years of permit issue.
Action here will be required to implement this regulation, combined
with revision of spatial plans and possible land swaps.
4. eneral land swap from other land use areas (APL) with forest cover
G
to forest areas that have no forest cover. There has been idea for land
swap between other land use areas (APL) that still contain forest cover
with official forest areas but without forest cover. The discussion has
been initiated and academic paper has been prepared. This idea is
also a hope to protect forest cover, and to keep forest with high carbon
values.


23

III. PEATLAND AND EMISSION
3.1. About Peatland
Peatland is a unique ecosystem in terms of its roles in regulating water regime
and flooding, being the habitat of numerous species (some of them are
included in the CITES’ appendices), and an important part of local livelihoods.
In the context of climate change, peatlands have received considerable
attention in its role in global carbon budget.
Globally, peatlands cover an area of 400 Mha, which stores more than 500 Pg
of terrestrial carbon. Ten percent of the world’s peatland area, which contains
191 Pg is located in the tropics, of which 60 percent is in Southeast Asia with
an estimated area of 25 Mha (IFCA, 2008).
Between 1987 and 2000, at least 3 Mha have been converted or degraded.
In the past 10 years an increasing area of peatland is being drained and
developed for oil palm and pulpwood plantations. During 2000-2005 the
rates of deforestation on peatlands were 89,251 ha/y in Sumatra and 9,861
ha/y in Kalimantan. Peatland deforestation mostly occurred in deep (2-4 m)
and very deep (4-8 m) peat, resulted in significant amount of GHG emissions
(IFCA, 2008).
Indonesia harbors approximately 21 Mha and distributed in Sumatra (7.2 Mha),
Kalimantan (5.8 Mha), and Papua (8.0 Mha). Peat more than three metres thick
covering around 8 million hectares, is protected by law in order to preserve
the unity of the core peat dome. Almost one-quarter of Indonesia’s peat land
is protected or conserved (Table 2).
Table 2.

Land use allocation (conservation, protection or production) and land
cover in Indonesia’s peat land by main islands with peat in 2006. Source:
Department of Forestry, Indonesia in Bappenas, 2009)

Major Land Use
/ Land Cover

Peat
Thickness

Area (hectares)
Sumatera

Kalimantan

Papua

Total

1. Conservation
1.1 Forest

< 3m
> 3m

179,234
184,242

327,951
400,521

1,251,741
0

1,758,925
584,764

1.2 Non-forest

< 3m
> 3m

85,779
9,757

168,821
98,246

346,963
0

601,563
108,002

459,012

995,539

1,598,704

3,053,254

Total (Conservation)

2. Protection
1.1 Forest

< 3m
> 3m

81,328
41,657

143,990
132,850

617,470
0

842,788
174,507

1.2 Non-forest

< 3m
> 3m

131,281
12,847

106,762
242,828

203,591
0

441,634
255,674

267,113

626,430

821,061

1,714,604

Total (Protection)

24


Major Land Use
/ Land Cover

Peat
Thickness

Area (hectares)
Sumatera

Kalimantan

Papua

Total

3. Production
3.1 Forest
(land cover)

< 3m
> 3m

1,294,297
1,116,758

1,429,935
472,937

4,309,122
0

7,033,354
1,589,695

3.2 Timber
plantation

< 3m
> 3m

183,112
133,522

6,771
2,126

552
0

190,435
135,648

3.3 Plantation

< 3m
> 3m

1,110,082
136,051

150,253
20,394

2,150
0

1,262,485
156,444

3.4 Agriculture

< 3m
> 3m

855,153
22,387

346,596
20,333

34,838
0

1,236,587
42,720

3.5 Other

< 3m
> 3m

1,270,766
349,597

1,402,106
292,542

1,343,495
0

4,016,367
642,139

< 3m
> 3m

4,713,410
1,758,315

3,335,660
808,332

5,690,157
0

13,739,228
2,566,648

7,197,850

5,765,961

8,109,922

21,073,733

Total
(Production)
Total

Current study (Rinung, et al, in Agus, et al, 2012) estimated the area of peatland
in Indonesia of 14,9 million ha, as shown in the following Figure.

Figure 9. Peatland distribution in main islands of Indonesia, in Sumatera, 6.436.649
ha, in Kalimantan, 4.778.004 ha and in Papua, 3.690.921 ha, with total of
14.9 million ha (Agus et al, 2012).


25

3.2. Sources of Emissions and Sequestrations in the
peatland
Contribution of peatland to emissions is basically from fires and from the
process of oxidation and compaction that result in subsidence following
drainage, as shown in the Figure xx. Estimation of emission from peatland
fires is describerd in Chapter IV. In the peatland, there is also accumulation
of carbon through the natural process of peat formation and carbon
sequestration from the growth of vegetation. Overall, however, the amount
of carbon sequestered by peat land is much lower than the emissions from
oxidation, fire and the loss of above-ground biomass through deforestation.

Figure 10. Sources of emission from peatland, from fires, and drainage that lead to
peat oxidation, compaction and peat subsidence that release CO2, (IFCA,
2008).

Undisturbed naturally forested peat lands either have a balanced carbon
budget or show a net accumulation of carbon through the natural process
of peat formation. Carbon sequestration rates from natural peat lands in
Indonesia have been estimated to be up to 0.8 t C ha-1yr-1 (Page et al. 2004 in
Bappenas, 2009)). Carbon is also sequestered by the growth of above-ground
biomass in secondary forests (7.0 t C ha-1yr-1), plantation crops (2.4 t C ha1yr-1) and other non-forest vegetation such as grassland and shrub land (0.6
t C ha-1yr-1).vi
An assessment of Indonesia’s peat land GHG emissions from fire, peat
oxidation and loss of AGB, completed according to IPCC Tier 2 standards,
showed average annual net emissions of 903 Mt CO2 yr-1 between 2000
and 2006 (Bappenas, 2009). This estimate was based on (a) estimates of
emissions from oxidation of 220 Mt CO2/yr using land use and land cover
data from 2000-2006 and previously published emissions factors, (b) loss of
AGB of 210 Mt CO2/yr based on past rates of deforestation and carbon stock

26


in peat swamp forests and (c) a fire emissions estimate of 470 Mt CO2/yr from
van der Werf et al. (2008).
The majority of the peat emissions during this period were estimated to be a
result of uncontrolled burning (contributing to 46% of total emissions), peat
oxidation (25%) and biomass removal (24%) with the main source regions
being Sumatra (44%) and Kalimantan (40%) (Figure 11). Emissions show a
strong inter-annual variation due to factors that influence dry season rainfall
such as El Nino and there has also been a reduction in loss of peat swamp
forest in the period 2003-2006. Sumatra and Kalimantan dominate the
national peat emissions profile with fire-related emissions being greater in
Kalimantan than Sumatra, while oxidation emissions are greater in Sumatra
than Kalimantan. This pattern probably reflects the fact that development
peat land in Sumatra preceded that in Kalimantan.

Figure 11. Estimated carbon emissions from Indonesia’s peat lands as a result of
loss of above-ground biomass, peat oxidation and fires (controlled and
uncontrolled) (left) and their source area (right). Source: Bappenas, 2009)

Uncertainties still remain over the exact figure and overall magnitude of
emissions from oxidation and to a lesser extent loss of AGB, with the
DNPI estimating oxidation emissions of 300 Mt CO2/yr and the SNC 222 Mt
CO2/yr (including soil carbon).

3.3. Carbon sequestration in peatland
Researches are still required to estimate carbon sequestration from peatland
due to variation of forest and peatsoil conditions. Study by Page et al (2004)
estimated carbon sequestration rates from natural peat lands in Indonesia
to be up to 0.8 t C ha-1yr-1 (Page et al. 2004), and 0,6-1.8 t C ha-1yr-1 (Agus et
al, 2012). Carbon is also sequestered by the growth of above-ground biomass
in secondary forests (7.0 t C ha-1yr-1), plantation crops (2.4 t C ha-1yr-1) and
other non-forest vegetation such as grassland and shrub land (0.6 t C ha-1yr-1).
vi To calculate sequestration in peatland, activity data and removal factors
required are as follows:

27

3.4. Emission from drainaged peatland
Peatlands that contain high organic material will follow the an-aerobic process
if exposed and interact with oxygen. Development of artificial drainage on
peatland with fragile structure will produce CO2 while digging irrigation
channels for plantation crops (Brown, 1997). Hooijer et al. (2006) stated that
in the last 10 years in Southeast Asia (especially Indonesia), drying of peatland
for oil palm estates and forest plantation for the paper industry and other
agricultural needs as well as unsustainable deforestation are estimated to
reach 6 million ha and produce additional emissions of GHG of 2 Gt C.
IPCC GL (2006) gives figures for each peatland default which is converted into
crops (oil palm plantations or forest plantation) that will produce emission
measuring at 9 ton C/ha/ year. While the study by Agus et al. (2012) give an
average figure of emission factor in drainaged peatland of 9.1 tons C / ha /
year for each drainage depth of 10 cm.
Table 3.

Emission factors for peatland drainaged for many purposses (Agus, et al,
2012)
Land use

Assumption of peat
drainaged depth (cm)

Emission CO2 (t CO2/ha/
year)

Primary forest peatland

0

0

Logged over forest peatland

30

19

Rubber

50

32

Oilpalm

60

38

Forest plantation

50

32

Agroforestry

50

32

Peat shrubs

30

19

Perrennial crops

30

19

Settlement

70

45

Ferns grass

30

19

Ricefield

10

6

100

64

Mining

The Table shows high emission factor from peatland if it is drainaged for
many purposes. Information required to calculate emission from drainaged
peatland include:
• Area of peatland being drainaged for particular purpose
• Emission factor based on the depth of peat drainage (Table 3).
For example, if in 2000-2001 an area of 100.000 ha peatland is managed
for oilpalm with drainage depth of 60 cm, average emission from this area:
100.000 ha x 38 ton CO2-e/ha/year = 3.800.000 t CO2-e or 3,8 Mt CO2-e.
Therefore, to reduce emission from drainaged peatland, conversion of natural
peatland should be avoided. Indonesia government has issued regulation on
moratorium of thick peatland conversion. Ministry of Agriculture has also
issued regulation for prohibition of the use of peat with more than 3 metres
depth for oilpalm establishment. Moreover, current draft of governmentsal
regulation also mentions protection of peatdome and thick peat as protected
area.

28


IV. ESTIMATION OF EMISSION FROM PEAT FIRES
Fire is rapid oxidation that releases energy (heat) and chemicals such as ash
(Ca, Mg, K), green house gasses (CO2, CH4) and particulates (PM2.5, PM10)
(Ryan and Cochrane, 2013). Emissions are complex and dynamic, every fire
has its own characteristic of emission. How much biomass burns, what kind
of biomass burns, how the biomass burns, together with terain condition, and
weather will influence the behaviour of fire, flaming or smoldering. In fire
science, the living and dead biomass that burns is called fuel. Fuel chemistry,
size and packing affect combustion and emissions. Total fuel is maximum
burnable biomass in worst case of fire. Meanwhile available fuel is biomass
that burns in a given fire situation that depend on specific site conditions. Light
grass fire will produce flame and clean fire, meanwhile peatfires (ground fires)
will burn slowly and produce dense smoke due to incomplete combustion.
For the issue of global warming, estimation of fire emissions is determined by
the amount of GHG released for every single fire with the biggest contribution
of CO2. Approach to calculate fire emission should cover the information of
carbon stock (total biomass) as determined from site classification or map
of vegetation, total fuel, available (consumed fuel) as determined from
combustion indicator and combustion efficiency (Ryan and Cochrane, 2013).
Therefore basic information that should be understood to calculate fire
emission is the knowledge of carbon stock (fuel).
So far, there has been high uncertainty in calculation of emission from peat
fires due to lack of data. For example, historical data on peatfire only mention
area of peatfire such as shown by Saharjo, (2010) as follows:
Table 4.

Total area of burned peatland (ha)

For estimation of emission from fires, Van der Werf et al. (2008) used several
approaches to estimate annual average fire emissions from peat and forest
fires. Their mean annual estimate from 2000-2006 of 466 Mt CO2/yr is widely
accepted, and this study has been used for both the Indonesian National
Climate Change Council (DNPI) assessment of the national GHG cost abatement
curve and the Government of Indonesia’s Second National Communication
(SNC) to the UNFCCC. Variation of estimate of emission from fires is shown
in the following Table, as a summary of several studies. This high contribution
of emission from peatfires will result in significant reduction of emission if
peatland fires can be prevented and reduced. Verchot (2010) predicted that
effort to prevent peatland fire would reduce Indonesia’s emission by 23-45%.


29

Table 5.

Emission from peatfires according to some studies (in million of ton of
CO2-e)

Year

Heil et al
(2007)

Levine
(1999)

Page et
al, 2002
Lowest

Page et
al, 2002
Highest

Duncan,
et al.
2003

Van der
Werf et
al. 2008

IFCA
2007

Average

1997

4026

898

2970

9423

2567

1202

16.6

3015

1998

1082

242

799

2534

689

271

3.7

803

1999

623

139

458

1459

396

190

2.6

467

2000

304

66

224

711

194

172

2.4

239

2001

645

143

477

1511

411

194

2.7

483

2002

2204

491

1624

5155

1404

678

9.4

1652

2003

1188

264

876

2783

759

246

3.4

874

2004

1907

425

1408

4462

1217

440

6.1

1409

2005

1694

378

1250

3960

1078

451

6.2

1260

2006

3560

796

2625

8334

2270

1111

15.3

2673

2007

524

117

385

1225

334

175

2.4

395

Average

1614

360

1191

3778

1029

466

6.4

1206

Note : Figures in italics are estimation using the pattern of emission according to Heil et al. (2007),
MoF (2008) only provided cummulative estimation in 2000-2005 ie 30 million ton CO2. Annual
emission was estimated using proportion of pattern of van der Warf et al (2008)

4.1. Methodology to Calculate Emissions
Methodology developed by IPCC has been broadly applied for calculation of
emission from Agriculture, Forestry and Landuse (AFOLU) sector. Sources
of emission and removal of GHG for AFOLU sector are shown in Figure xx.
IPCC has been developing the method for GHG inventory since 1996. The
IPCC revised guideline 1996 has been revised through the IPCC Good Practice
Guidance (GPG) 2003 and the IPCC Guideline 2006. Applications IPCC GL 2006
will result in a better inventory, reducing uncertainty, consistent distribution
of land category, estimating GHG emissions and removal for all categories of
carbon pools as well as relevant non-CO2 gases (based on analysis of the key
source / sink category).

Figure 12. Source of emission and removal of GHG for AFOLU sector (Source: IPCC,
2006)

30


Basic formula for calculation of emission :
Emission or Removal Δ C
=Activity Data x Emission or Removal Factor
Data required to calculate emissions using the IPCC GL 2006 are activity data
and data of emission or removal factor. For land use change and forestry,
the land cover change analysis is carried out to produce land change matrix
as activity data. Land change data are obtained from remote sensing data
analysis. Land use change is analyzed for a period of time based on the period
of emission calculations and classification of land cover. Other activity data for
the calculation of emissions include data of fire, logging, other disturbances
and peatlands. Calculation of emission also considers five carbon pools
namely AGB, BGB, litter, necromass and soil.
IPCC Guidelines 2006 also include calculation of CO2 and non-CO2 emissions
from fires. The general method for estimating greenhouse gas emissions
from fires including peatlands (wetlands) is described in equation as follows
(IPCC, 2006, Mickler, 2013, Ayanz and Steinbrecher, 2013):
Lfire = A MB Cf Gef 10 -3
Where:
Lfire

: Amount of greenhouse gas emissions from fire, tonnes of each GHG

A

: Area burnt, ha

MB

: Mass of fuel available for combustion, tonnes ha-1.

Cf

: Combustion factor, dimensionless

Gef

: Emission factor, g kg-1 dry matter burnt

Based on data requirement for calculating emission from peatfires as in
above formula, to improve accuracy of emission calculation, the followings
are required:
1) Data of Area Burned
Basic need for calculation of peat fires emission is area burned as activity
data. Due to extensive area of peatlands, area burned is estimated using
remotely sensed data of adequate spatial and temporal resolutions analyzed
according to a robust sampling design.
Current approach to estimates area burned is using hotspot data. Hotspot
monitoring is considered as an effective early warning system to monitor
forest and land fires. From data of hotspot from NOAA sattellite, Adrian (2007)
reported that after calibration, on the average, hotspot was equal with about
2.98 km2 with a scale level of 2.25 km2 for peat land and easily burn forest.
2.85 km2 for plantation forest and 4.50 km2 for agriculture and savanna.


31

In the national action plan (NAP) for reduction of GHG, Indonesia has set the
target to reduce the number of hotspots by 20%. The target of number of
hotspots reduction is as follows:
Table 6.

Target of hotspot reduction in National Action Plan of GHG
Year

Number of hotspots

2010

25.556

2011

20.453

2012

16.362

2013

13.093

2014

10.472

2015

8.378

2016

6.702

2017

5.662

2018

4.289

2019

3.431

2020

2.745

Calculation of burned areas of forest and land fires by monitoring the
occurrences of hotspots has high uncertainty and requires groundcheck to
check the actual area burned and types of vegetation burned. Improvement
is still required to make good relation between the number and distribution of
hotspots detected and the total area of burned and its associated vegetation
or forest type. Hotspots data are available, however to improve the data in
relation with area burned and vegetation types, these hotspot data should be
overlaid with accurate map of vegetation cover, including land use and types
of management in these areas. Ground check is necessary to identify actual
burning areas in the field.
Ryan and Cohrane (2013) used MODIS to detect fires, they stated that
MODIS fire detections are only telling part of the story about flaming surface
vegetation fires. MODIS does not detect many of the fires, does not provide
area burned and cannot detect or quantify peat fires.
Information on land cover types is also important to be identified. For some
extent, annual landsat imageries provide the frequency (number of times)
of burned and land cover types. Improvement is certainly required related
to ability to detect and map fires and ability to monitor environmental
conditions that strongly related to fire occurrences. This is also possible by
using LIDAR technology that possible to simultaneously monitor, the height
of vegetation, the extent of peat loss due to subsidence and combustion.
Availability of resources (budget and skilled personnel) is required to support
LIDAR technology.

32


2) Mass of Available Fuel
Calculation of emission from peat fires requires information/data of carbon
stock (total biomass) of area burned. Based on land cover classification,
Ministry of Forestry has classified land cover in 23 classes with default stock
of carbon in each class as shown in the following Table.
Table 7.

Carbon stock used as emission factor applied in preparation of regional
action plan of province (RAD) as reference for calculation of GHG emission
according to IPCC GL 2006 (Source: Santoso, 2012)

Land cover code

Type of land cover

Carbon stock (ton C/ha)

2001

Primary dry land forest

195,4

2002

Secondary dry land forest

169,7

2004

Primary mangrove forest

170

2005

Primary swamp forest

196

2006

Plantation forest

64

2007

Shrubs

15

2010

Estate crops

63

2012

Settlement

1

2014

Bare land

0

3000

Grassland

4,5

5001

Water

0

20041

Secondary mangrove forest

120

20051

Secondary swamp forest

155

20071

Swamp shrubs

15

20091

Dry land agriculture

8

20092

Mix dry land agriculture

10

20093

Rice field

5

20094

Embankment

0

20121

Air port/port

5

20122

Transmigration

10

20141

Mining

0

50011

Swamp

0

Table 7 shows default figures of carbon stock for each land cover class based
on classification by Ministrty of Forestry. Team Forda (2010) provided some
information on carbon stocks of some forest types as follows:


33

Tabel 8.

No

Above ground stock of carbon on some natural forest cover. (Sources:
Team FORDA, 2010)
Class of landuses/
Location

1

Carbon Stock
(ton C/ha)

Source

Remark

Primary dryland forest
Natural forest of PT.
Sarpatim, Sampit, Central
Kalimantan

230,10 - 264,70

Malinau Research Forest,
East Kalimantan

Dharmawan and
Siregar (2009)
Samsoedin et al.
(2009)

Lowland tropical
forest DBH 7,0 –
70,0 cm.

Protection forest of
Sungai Wain, East
Kalimantan

211,86

Noor’an (2007)

DBH 5,0 – 40,0 cm

Primary forest of Gunung
Gede Pangrango, West
Java

103,16

Dharmawan
(2010)

Highland forest,
DBH 5,6 – 119,0 cm

Gede Pangrango National
park, West Java

275,56

Siregar (2007)

PT. Sari Bumi Kusuma,
Central Kalimantan

229,33

Junaedi (2007)

Lowland tropical
forest

102,11 - 21,84

Junaedi (2007)

Dipterocarp and
non commercial

104,78

Samsoedin, dkk
(2009)

Highland forest

601,28

Kurniadi and
Pujiono (2009)

Fatumnasi village

611,09

Junaedi (2007)

Noepesu village

Biospher reserve, Siberut
Island
Aek Nabara, Sibolga,
North Sumatera
Natural reserve Gunung
Mutis , Timor Island
2

Secondary dryland forest
17,5 – 55,3

Hiratsuka et al.
(2006)

Burned over forest

171,8 – 249,1

Dharmawan et
al. (2010)

LOA.

39,48

Rahayu et al.
(2006)

Burned over forest

Biosphere reserve,
Siberut Island

18,41-169,21

Bismark, et al.
(2008)

LOA

East Kalimantan

57,68-107,71

Adinugroho
(2006)

LOA

West Kalimantan

40,18

Onrizal (2004)

LOA

Bukit Soeharto, East
Kalimantan
Malinau, East Kalimantan
Nunukan, East
Kalimantan

3

Peat Swamp Forest
PT. SBK, Central
Kalimantan

62,81

Junaedi (2007)

Peat forest

Sibolga, North Sumatera

58,07

Samsoedin, et al
(2009)

Peat forest

179

Prasetyo (2000)

Peat forest

176,8

Perdhana (2009)

Peat forest

Jambi
PT. Diamond Raya
Timber, Riau
Central Kalimantan
4

34

268,2

MoFor (2008)

Peat forest

Papua

172,16

MoFor (2008)

Swamp forest

54,1 – 182,5

Muzahid (2008)

Mangroves

Mangrove Forest


Most information of carbon stock is for above ground biomass of mineral soil.
There is little information on carbon stock of peat soil. Information on carbon
stock of peat is required to calculate emission from peatfires. Mapping of peat
depth and field measurement are still required. Carbon stock of peatland is
determined by specific density of each peat maturity level and its carbon
orgabic content. Agus et al (2012) provided the figures of peat specific density
and carbon organic content based on peat maturity as follows:
Table 9. Peat specific density and carbon organic content
Properties

Maturity
Sapric

Hemic

Fibric

C-org

0.49

0.51

0.52

Specific Density

0.18

0.12

0.10

IPCC GL 2006 provides default data if data for MB and Cf are not available. A
default value for the amount of fuel actually burnt (the product of MB and Cf)
can be used under Tier 1 methodology.
Table 10. Default values of biomass consumption for fires in a range of vegetation
types (ton biomass/ha) to estimate Mb and Cf (IPCC, 2006)
Vegetation Type (Sub
Category)

Amount of fuel actually
burnt (ton biomass/ha)

Standard Error

Primary tropical forest

83.9

25.8

Primary open tropical forest

163.6

52.1

Primary tropical moist forest

160.4

11.8

Primary tropical dry forest

-

-

All primary tropical forest

119.6

50.7

Secondary tropical forest
Young secondary tropical
forest (3-5 yrs)

8.1

-

Intermediate secondary
tropical forest (6-10 yrs)

41.1

24.7

Advance secondary tropical
forest (14-17 yrs)

46.4

8.0

All secondary tropical forest

42.2

23.6

All tertiary tropical forest

54.1

-

Boreal forest
Wild fire (general)

52.8

48.4

Crown fire

25.1

7.9

Surface fire

21.6

25.1

Post logging slash burn

69.5

44.8

Land clearing fire

87.5

35.0

All boreal forest

41.0

36.5


35

3) Combustion Factor
Calculation of emission from peatfires requires data on combustion factor that
show intensity of fire or proportion of fuel that is actually burned. Syaufina
(2010) provided description on burning biomass fraction for grassland: 0,81.0, tropical forest 0.20-0.25, and organic soil, 0.1-0.9. For peatfires, severity
of fires is determined by the depth of burned peatsoil. Low fire severity with
burned peat depth up to 25 cm, moderate fire severity with burned peat depth
of 25-50 cm, and high fire severity with burned peat depth more than 50 cm,
IPCC GL provides default data for combustion factor as follows:
Table 11. Default of combustion factor values for fires in a range of vegetation types
(to be used as Cf) (IPCC, 2006)
Vegetation Type (Sub Category)

Combustion Factor

Standard Error


0.32

0.12

Primary open tropical forest

0.45

0.09

Primary tropical moist forest

0.50

0.03

Primary tropical dry forest

-

-

All primary tropical forest

0.36

0.13

Secondary tropical forest
Young secondary tropical forest (3-5 yrs)

0.46

-

Intermediate secondary tropical forest (6-10 yrs)

0.67

0.21

Advance secondary tropical forest (14-17 yrs)

0.50

0.10

All secondary tropical forest

0.55

0.06

All tertiary tropical forest

0.59

-

Wild fire (general)

0.40

0.06

Crown fire

0.43

0.21

Surface fire

0.15

0.08

Post logging slash burn

0.33

0.13

Boreal forest

Land clearing fire

0.59

-

All boreal forest

0.34

0.17

4) Emission Factor
For more accuracy of calculation, local activity data and emission factors are
required. Calculation of emission from peatland fires requires measurement
of the mass of actual burned peat, including weight / volume, and carbon
content of the burned peat. This is to support the data of emission factor
(Gef) in the eqution of emission.
IPCC GL 2006 provides default figures for emission factors of other gasses to
be used for calculation of emission of other gasses, as in the following Table.
The emission factors show emissions of gasses released for every kilogram of
dry matter burned.

36


Table 12. Default emission factors for various types of burning (to be used as Gef (g/
kg) (IPCC, 2006)
CO2

CO

CH4

N2O

NOx

Tropical forest

Category

1580+90

104+20

6.8+2.0

0.20

1.6+0.7

Agriculture residues

1515+177

92+84

2.7

0.07

2.5+1.0

Savanna and
grassland

1613+95

65+20

2.3+0.9

0.21+0.1

3.9+2.4

Biofuel burning

1550+95

78+31

6.1+2.2

0.06

1.3+0.6

Note that there is no default emission factor for peatfires

Forest fires also emit other gasses. Default emission factors of these gasses
are as follows (Ayernz and Schreibeder, 2013).
Table 13. Emission ratios for biomass fires, expressed relative to the carbon emitted
as CO2
Species

g X/kg C emitted as CO2 ‘best guess’

CO

230

CH4

15

NMVOC

21

NOX

8

NH3

1.8

N2O

0.4

SOX

1.6

There are several sources of uncertainty related to estimates of GHG
emissions from peatfires. These include the extent of area burnt, intensity of
the fire, and the rate of spread, especially in long-duration deep organic soil
combustion and in tropical ecosystems. Peat can also burn repeatedly and to
different depths. Furthermore, various compounds and gases can be emitted
depending on the type and density of the peat. Thus not only the area, but
also the depth of the fires and the type of emissions must be determined,
which is only feasible in higher Tier levels. Generally, the estimates are highly
uncertain due to the lack of reliable and accurate data.


37

4.2. Example of Estimation of Emission from Peat
Fires.
General formula to estimate emission : Lfire = A MB Cf Gef 10 -3, excercise
of estimation of emission from peatfires are shown in Table 14.
Table 14. Excercise of estimation of emission from peatfires in Sumatera and
Kalimantan
Parameter

2007 Peat Fires

2013 Peat Fires

Unit

Total area of Sumatera

47.132.000

47.132.000

Ha

Total area of Kalimantan

53.040.000

53.040.000

Ha

Total peat area in Sumatera

6.436.649

6.436.649

Ha

Total peat area in Borneo

4.778.004

4.778.004

Ha

Total hotspots detected in
Sumatera*

8.213

10.164

Number

Total hotspots detected in
Borneo*

7.928

4.624

Number

Approximate area of one
hotspot

298

298

Ha

Total peat area burned in
Sumatera

334.243

413.642

Ha

Total peat area burned in
Borneo

212.825

124.130

Ha

C-stock of peat soil

600

600

Ton C/ha

C-stock of AGB

100

100

Ton C/ha

Combustion Factor

0,4

0,4

Dimensionless

Emission Factor

1580

1580

g CO2-e/1000 g C

Emission in Sumatera from
surface fire

21,12

26,14

M Ton CO2-e

Emission in Borneo from
surface fire

13,45

7,85

M Ton CO2-e

Emission in Sumatera from
surface fire

126,74

156,85

M Ton CO2-e

Emission in Borneo from
surface fire

80,7

47,1

M Ton CO2-e

Total emission in Sumatera

147,9

183,0

M Ton CO2-e

Total emission in Borneo

94,2

54,9

M Ton CO2-e

Data and assumptions:
• Data of hotspots are based on observation by BPPT (2013) as shown in the
Appendix 1.
• One hotspot is assummed 2,86 km2 or 286 ha (Aldrian, 2007)
• Average C-stock of peat soil is 600 t C/ha
• Average C-stock of AGB is 100 t C/ha
• Combustion Factor = 0,4 (IPCC, 2006)
• Emission Factor 1580 g CO2-2/1000 g C. (IPCC, 2006)

38


4.3. Improvement of Methodology
Improvement of methodology to estimate emission from peatland fires
is required to get better results in mitigation efforts with higher Tier. Up to
present, uncertainty related to calculation of GHG emissions from peatfires
remains very high. This is due to lack of data, knowledge and information on
fire behavior that result in area burned and combustion factor. Fire behavior
including intensity of the fire, and rate of spread, especially in long-duration
deep organic soil combustion varies greatly among peatland types and
vegetative formations. The fraction of fuel that is actually combusted during
biomass burning (combustion and emission factors) varies greatly, not only
between ecosystems, but also between fires, between years, above and
below ground biomass. The use of default values will have high uncertainties
(Tier 1). Therefore, measurements from a given fire, year, or location cannot
be extrapolated with confidence to other areas or years.
Improvement of methodology is required to increase accuracy of estimation
of emission of peatfires, especially to support the MRV system in monitoring
of GHG. Data and information required to calculate emission from peatfires
at particular period of time include.
• Total area burned (including actual burned area from identified hotspots)
• Above ground biomass or carbon stock of area burned
• Fire intensity that is represented by fraction of biomass burning
• Carbon stock of peatsoil (including maturity, specific density and carbon
organic content of peat soil)
• Burning fraction in peatsoil
Activities required to calculate more accuratelly peatfire emission include:
• Detecting fires and mapping burned areas. If information of fires is
obtained from hotspots data, ground observation is required to identify
hotspots occurrences in term of area burned
fuels.
to establish ptevention and control measures.


39

To support these activities, it is required institutional system of GHG inventory
including to estimate emission from peatfires. Resources area needed
including budget, human resources and working plan, and some current
institutions have already available and have some data/information to
support. These institutions include Ministry of Agriculture (BBSDLP), Ministry
of Forestry (Directorate General of Forestry Planning and Forestry Resaerch
and Development (FORDA), DNPI, LAPAN, Ministry of Environment, private
sectors, local governments and other research institutions and organizations.

40


V. CONCLUSION AND RECOMMENDATION
5.1. Conclusion
In Indonesia, forest and land fires are direct threats that could lead to forest
destruction and resulting in negative impacts to the environment and human,
causing health and haze problem and directly emitting green house gasses
(GHG) that contribute to global warming. Most fires are generally caused by
human activities such as land conversion and clearing by burning, construction
of peat drainage that cause peat drying and easily burn, and other use of
fire by community related to land preparation and tenure. Data showed that
most forest and land fires occurred on outside concessions/forest areas
(64%), however there were also some fires recorded from the process of
management of concessions either, pulp plantation, timber concession, and
oil palm estates.
The recent 2013 fires, have made Indonesia experienced extensive media
coverage and world attention due to the occurrences of forest and land fires
mostly in Sumatera. The fires have caused serious impacts including smoky
haze that spread to Malaysia and Singapore where the pollution index was the
worst in 16 years.
by human activities as the causes of almost all fires. All ingridients of fires (fire
triangle) are available, heat, oxygen and potential fuel. Land preparation using
fire is still considered as the most effective way by local farmers and even
companies, although there is penalty for this.
In term of climate change, forest and land fires are the direct cause of
emission. Especially peatland that contains high amount of carbon, fires in
peatland will produce high emission. However up to present, uncertainty
related to calculation of GHG emissions from peatfires remains very high. This
is due to lack of data, knowledge and information on fire behavior that result
in area burned and combustion factor. The use of default values to calculate
emission will have high uncertainties (Tier 1), moreover measurement from
a given peat fire, year, or location cannot be extrapolated with confidence to
other areas or years.
Exercise from this assessment shows that peatfires in 2007 resulted in total
emission of 147,9 Mt CO2-e in Sumatera and 94,2 Mt CO2-e in Kalimantan,
meanwhile in 2013, peatfires have emitted some 183,0 Mt CO2-e in Sumatera
and 54,9 Mt CO2-e in Kalimantan.


41

To support the MRV in GHG inventory, including to calculate emission from
peatfires at particular period of time, some information is required such as
total area burned (including actual burned area from identified hotspots),
carbon stock of area burned, and fraction of biomass burning.

5.2. Recommendations
Prevention actions should be prioritized to control forest fires. The areas
should be under management and kept safe from fires through several
management practices. For community, improvement of awareness, incentive
system, prosperity approach and sanctions are required for fire preventions
as well as control.
Some activities are required to calculate peatfire emission more accuratelly ,
including:
• Detecting fires and mapping burned areas. Improving hotspots data.
fuels.
to establish prevention and control measures.
• Developing the system of general GHG inventory including estimation of
emission from peatfires
The prevention of annual fires including peatlands requires not only technical
and policy issues but also behavior change of all stakeholders including
community, private companies and others, to safeguard the land from fires.
It also requires local government commitment for the prevention and control
of fires with investment in enhancing capacity and equipment.

42


REFERENCES
Adinugroho, W.C, Suryadiputra, INN, Saharjo, BH, and Siboro, L. 2005.
Guidance on Forest and Peatland Fire. Project of Climate Change, Forests
and Peatlands in Indonesia. Wetlands International-Indonesia Program
and Wildlife Habitat Canada. Bogor. Indonesia.
Agus, F, Maswar, and Dariah, A. 2012. GHG Emissions Calculation Method
in Peatlands and Agriculture. Center for Agricultural Land Resources
Ministry of Agriculture. Training materials BAU Baseline Calculation for
Local Government. Bandung 21-25 May 2012
Ayanz, J.S.M and Steinbrecher, R. 2013. Forest and other vegetation fires
Emission Inventory Guidebook 2013. EMEP/EEA
Bapenas, 2009. Reducing carbon emissions from Indonesia’s peat lands
Interim Report of a Multi-Disciplinary Study. December 2009. Jakarta.
BPPT. 2013. Data of hotspots distribution based on adminsitrative boundaries
by NOAA sattellite. BPPT. Jakarta.
Duncan, BN, Bey I, Chin M, Mickley LJ, Fairlie TD, Martin RV, Matsueda H (2003)
Indonesian wild- fires of 1997: Impact on tropospheric chemistry. Journal
of Geophysical Research 108(D15):4458
Team FORDA, 2010. Information of Carbon stock on some forest types and
plantation in Indonesia. Forestry Research and Development Agency.
Jakarta
Gaveau, D and Agus Salim, M. 2013. New data on Riau fires generate important
insights. CIFOR. Bogor.
Heil, A., Langmann B, Aldrian E. 2007. Indonesian peat and vegetation
fire emissions: Factors influencing large-scale smoke-haze dispersion,
Mitigation and Adaptation
IFCA. 2008. Reducing Emission from Deforestation and Degradation in
Indonesia. Consolidation Report
IPCC (Intergovernmental Panel on Climate Change), 2006. IPCC Guidelines for
National Greenhouse Gas Inventories, prepared by National Greenhouse
Gas Inventories Programme, Eggleton, H. S., Buendia, L., Miwa, K., Ngara,
T., and Tanabe, K. (editor), IGES, Jepang.
IPCC (Intergovernmental Panel on Climate Change),. 1996. Revised 1996 IPCC
Guidelines for National Greenhouse Gas Inventories. IGES, Japan. IPCC


43

IPCC. 2003. Good Practice Guidance for Land Use, Land-Use Change and
Forestry. Intergovernmental Panel on Climate Change. IPCC National
Greenhouse Gas Inventories Programme. IGES. Japan.
Levine J.S. 1999. The 1997 fires in Kalimantan and Sumatra, Indonesia: gaseous
and particulate emissions. Geophysical Research Letters 26:815–818.
Mickler, R.A. 2013. Carbon fluxes and greenhouse gas emissions from wetland
wildland fires in the 2013 Supplement to the 2006 IPCC Guidelines for
National Greenhouse Gas Inventories: Wetlands Alion Science and
Technology Corporation, Durham, NC
Ministry of Environment. 2009. Indonesia: Second National Communication
to the United Nation Framework Convention on Climate Change. MOE.
Jakarta
Page SE, Siegert F, Rieley JO, B¨ohm HDV, Jaya A, Limin S. 2002. The amount
of carbon released from peat and forest fires in Indonesia during 1997.
Nature 420:61–65.
Rowell, A dan P.F. Moore. 1999. Global Review of Forest Fore. WWF-IUCN.
Ryan, K and Cochrane, M. 2013. Estimating Emissions from Peat Fires.
Presentation Material. Indonesia Climate Change Center. Peatfire
workshop, Hotel Mandarin, Jakarta.
Saharjo, B.H. 2011. Indonesian peat fires and emission reduction through
prevention Activities. Forest Fire Laboratory, Faculty of Forestry, Bogor
Agricultural University (IPB), Bogor, Indonesia
Santosa, I. 2012. National Forest Monitoring System to support REDD + in
Indonesia. Inventory and Monitoring Directorate of Forest Resources
Ministry Directorate General of Forestry Planning Keforesta. Papers on
Carbon Accounting Workshop MRV system for REDD + in Padang and
Ambon. September 2012.
Van der Werf, G. R, Dempewolf, J, Trigg, S. N, Randerson, J. T, Kasibhatla, P.
S, Giglio, L, Murdiyarso, D, Peters, W, Morton, D. C, Collatz, G. J, Dolman,
A. J and DeFries, R. S. 2007. Climate regulation of fire emissions and
deforestation in equatorial Asia. www.pnas.org”cgi”doi” 10.1073” pnas.
0803375105
WRI. 2013. http://insights.wri.org/news/2013/08/indonesia-burning-forestfires-flare-alarming - levels#sthash.VRlt8hHY.dpuf

44



45

Appendix 1.

46



47

48



49

50



51

52



53

54



55

56



57

Appendix 2. Some Photos

A woman is seen wearing a safety-mask in the middle of Singapore (20/6). Indonesia’s forest fires has
caused thick haze to its neighboring countries. AP Photo/Joseph Nair

A helicopter sprays water to put out the fires in a forest in Siak, Riau (6/24). The fire causes a thick
haze that spreads to neighbouring countries such as Singapore and Malaysia. REUTERS/Fikih Auli

An aerial view of burning trees is seen during the haze in Indonesia’s Riau province. Indonesian
investigators are building criminal cases against eight Southeast Asian companies they suspect of
being responsible for raging fires. REUTERS/Beawiharta

58


A child in Pekanbaru, Riau covers his face with a mask as he walks to school (8/27). ANTARA/FB
Anggoro

Haze in Kuala Lumpur, Malaysia ANTARA


59

Land clearing for oilpalm in Riau, Sumatera (VOA, 2011)

Haze over Malaysia (Asean Specialized Meteorological Center, 2013)

60


Haze over Malaysia (Asean Specialized Meteorological Center, 2013)


61

Some information on haze and fires in June, 2013

62


Deliberately lit forest fires is destroying the health of Southeast Asians, and looks set to be a yearly
event. EPA/Amriyadi Bahar

http://earthobservatory.nasa.gov/IOTD/view.php?id=81431&src=iotdssi morning (Terra MODIS)
acquired June 19, 2013 morning


63

http://earthobservatory.nasa.gov/IOTD/view.php?id=81431&src=iotdssi morning (Terra MODIS)
acquired June 19, 2013: Afternoon (Terra MODIS)

Information on haze and polutant index in Singapore

64


Published by
Dewan Nasional Perubahan Iklim (DNPI)/
National Council on Climate Change - Indonesia
BUMN Building 18th floor
Jl. Medan Merdeka Selatan no.13
Jakarta 10110 - Indonesia
Ph. +6221 3511 400, Fax + 6221 3511 403
www.dnpi.go.id

Ghg assessment from forest fires - indonesia case study

Recommandé

Recommandé

Contenu connexe

Tendances

Tendances (20)

Similaire à Ghg assessment from forest fires - indonesia case study

Similaire à Ghg assessment from forest fires - indonesia case study (20)

Plus de Farhan Helmy

Plus de Farhan Helmy (20)

Dernier

Dernier (20)

Ghg assessment from forest fires - indonesia case study