Ghg assessment from forest fires - indonesia case study

Jakarta, November 2013

Greenhouse Gasses Assessment From Forest Fires:

Indonesia Case StudyPreliminary Assessment Report

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 Report2 Greenhouse Gasses Assessment from Forest Fires: Indonesia Case Study - Preliminary Assessment Report

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.

3Greenhouse Gasses Assessment from Forest Fires: Indonesia Case Study - Preliminary Assessment ReportGreenhouse 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 : 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

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


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.


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.


LIST OF CONTENTS

Executive Summary • 2Acknowledgements • 5List Of Content • 6List Of Tables • 7List Of Figures • 8List Of Appendix • 9

I. INTRODUCTION • 101.1. Background • 10

1.2. Objectives • 11

II. ISSUE OF LAND AND FOREST FIRES • 122.1. 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 • 243.1. 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 • 294.1. 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 • 415.1. Conclusion • 41

5.2. Recommendations • 42

REFERENCES • 43

Appendix 1. • 46

Appendix 2. Some Photos • 58


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


LIST OF FIGURE

Figure 1. The number of hotspots in Indonesia during the period of 1999-2013 (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 worst-affected 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


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


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


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.


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 1997-2012 (Ministry of Forestry, 1998-2013)

Year Area Burned (ha) 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 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.


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.


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 worst-affected 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).


• 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.


Figure 7. Fire locations in Sumatera

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


2.3. Drivers of Forest and Land Fires

Forest and land fires in Indonesia usually occur in dry season during April-September. 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


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


• DG of Forest Protection and Nature Conservation Regulation (PHKA)

• No.243/Kpts/DJ-VI/1994 on Technical guidance for prevention and control of forest fires in forest utilization areas and other areas.

• 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


• 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

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 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


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


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. General land swap from other land use areas (APL) with forest cover 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.


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

179,234184,242

327,951400,521

1,251,7410

1,758,925584,764

1.2 Non-forest < 3m> 3m

85,7799,757

168,82198,246

346,9630

601,563108,002

Total (Conservation) 459,012 995,539 1,598,704 3,053,254

2. Protection

1.1 Forest < 3m> 3m

81,32841,657

143,990132,850

617,4700

842,788174,507

1.2 Non-forest < 3m> 3m

131,28112,847

106,762242,828

203,5910

441,634255,674

Total (Protection) 267,113 626,430 821,061 1,714,604


Major Land Use / Land Cover

Peat Thickness

Area (hectares)

Sumatera Kalimantan Papua Total

3. Production

3.1 Forest(land cover)

< 3m> 3m

1,294,2971,116,758

1,429,935472,937

4,309,1220

7,033,3541,589,695

3.2 Timber plantation

< 3m> 3m

183,112133,522

6,7712,126

5520

190,435135,648

3.3 Plantation < 3m> 3m

1,110,082136,051

150,25320,394

2,1500

1,262,485156,444

3.4 Agriculture < 3m> 3m

855,15322,387

346,59620,333

34,8380

1,236,58742,720

3.5 Other < 3m> 3m

1,270,766349,597

1,402,106292,542

1,343,4950

4,016,367642,139

Total (Production)

< 3m> 3m

4,713,4101,758,315

3,335,660808,332

5,690,1570

13,739,2282,566,648

Total 7,197,850 5,765,961 8,109,922 21,073,733

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).


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 ha-1yr-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


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:


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 useAssumption 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

Mining 100 64

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.


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%.


Table 5. Emission from peatfires according to some studies (in million of ton of CO2-e)

YearHeil 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)


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.


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.


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:


Tabel 8. Above ground stock of carbon on some natural forest cover. (Sources: Team FORDA, 2010)

NoClass of landuses/

Location Carbon Stock

(ton C/ha)Source Remark

1 Primary dryland forest

Natural forest of PT. Sarpatim, Sampit, Central Kalimantan 230,10 - 264,70

Dharmawan and Siregar (2009) Lowland tropical

forest DBH 7,0 – 70,0 cm.Malinau Research Forest,

East Kalimantan Samsoedin et al.

(2009)

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

103,16Dharmawan

(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

Biospher reserve, Siberut Island

102,11 - 21,84 Junaedi (2007)Dipterocarp and non commercial

Aek Nabara, Sibolga, North Sumatera

104,78Samsoedin, dkk

(2009)Highland forest

Natural reserve Gunung Mutis , Timor Island

601,28Kurniadi and

Pujiono (2009)Fatumnasi village

611,09 Junaedi (2007) Noepesu village

2 Secondary dryland forest

Bukit Soeharto, East Kalimantan

17,5 – 55,3Hiratsuka et al.

(2006)Burned over forest

Malinau, East Kalimantan 171,8 – 249,1Dharmawan et

al. (2010)LOA.

Nunukan, East Kalimantan

39,48Rahayu et al.

(2006)Burned over forest

Biosphere reserve, Siberut Island

18,41-169,21Bismark, et al.

(2008)LOA

East Kalimantan 57,68-107,71Adinugroho

(2006) LOA

West Kalimantan 40,18 Onrizal (2004) LOA

3 Peat Swamp Forest

PT. SBK, Central Kalimantan

62,81 Junaedi (2007) Peat forest

Sibolga, North Sumatera 58,07Samsoedin, et al

(2009)Peat forest

Jambi 179 Prasetyo (2000) Peat forest

PT. Diamond Raya Timber, Riau

176,8 Perdhana (2009) Peat forest

Central Kalimantan 268,2 MoFor (2008) Peat forest

Papua 172,16 MoFor (2008) Swamp forest

4 Mangrove Forest 54,1 – 182,5 Muzahid (2008) Mangroves


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

PropertiesMaturity

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

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


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: 0,8-1.0, 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

Primary tropical forest

Primary tropical forest 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 -

Boreal forest

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

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.


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

Category CO2 CO CH4 N2O NOx

Tropical forest 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.


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)


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


• Mapping of all land use to identify causes of fires, fire risk and fire effects to establish ptevention and control measures.



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.


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.

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 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.


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.


• Mapping of all land use to identify causes of fires, fire risk and fire effects 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.


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

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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


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

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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

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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-forest-fires-flare-alarming - levels#sthash.VRlt8hHY.dpuf


Appendix 1.


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


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


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

Haze over Malaysia (Asean Specialized Meteorological Center, 2013)


Haze over Malaysia (Asean Specialized Meteorological Center, 2013)


Some information on haze and fires in June, 2013


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


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

Published byDewan Nasional Perubahan Iklim (DNPI)/

National Council on Climate Change - Indonesia

BUMN Building 18th floorJl. Medan Merdeka Selatan no.13

Jakarta 10110 - IndonesiaPh. +6221 3511 400, Fax + 6221 3511 403

www.dnpi.go.id

Ghg assessment from forest fires - indonesia case study

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