Toward LCS-Indonesia Focusing on Peat Fire Management Rizaldi Boer - - PowerPoint PPT Presentation

Toward LCS-Indonesia Focusing on Peat Fire Management

Rizaldi Boer Centre for Climate Risk and Opportunity Management (CCROM) Bogor Agriculture Uinversity

LCS Scenarios-Indonesia

• Under Technology Needs Assessment

Study, Indonesia is now assessing the strategies toward LCS which will be completed by the end oif February.

• Projection of emission from all sector

under BAU and policy scenarios have been developed

• This presentation will focus on strategy for

reducing emission from peat fire

Abatement Potential 2030

Abatement Potential: Forestry and Agriculture 12.4 Gt CO2/y Energy Efficiency 14 Gt CO2/y Low Carbon Energy Supply 12 Gt CO2/y Emission: Forestry and Agriculture 15.1 Gt CO2/y

* Mitigation Opportunity Avoided Deforestation

Reduced Deforestation from Slash & Burn Agriculture Reduced Forest Conversion to Pasture and Intensive Agriculture Reduced Timber Harvesting

Forest Sequestration

Pastureland Afforestation Cropland Afforestation Degraded Forest Reforestation Forest Management

Agriculture

Tillage and residues management Grassland management Organic soils restoration Degraded lands restoration

• 2030 - Forest carbon; agricultural sequestration; and avoidance of N2O and CH4 emissions, mainly from livestock (< 0.1 Gt).

Source: Smith et al., 2007 (Figure 8.5: Total technical mitigation potentials (all practices, all GHGs: MtCO2-eq/yr) for each region by 2030, showing mean estimates); Nabuurs et al, 2007 (Table 9.3: Potential of mitigation measures of global forestry activities. Global model results indicate annual amount sequestered or emissions avoided, above business as usual, in 2030 for carbon prices 100 US$/tCO2 and less); both from Climate Change 2007: Mitigation. Contribution of working group III to the 4th assessment report of the IPCCC

GtCO2e pa

0.7 0.7 1.7 1.7 1.4 1.4 3.8 3.8

What is GHG Mitigation Potential from Land Use (South & South East Asian) *

agriculture

Annual Emissions from Fossil Fuel Use (MtCO2e 336) Coal 26% Oil 53% Gas 21%

Annual Emissions: Deforestation & Peat Loss (MtCO2e 2,398, Averaged Over Time)

Deforestation 22% Pulp & Palm

• n Peat

5% Peat Drainage 20% Peatland Fires 53%

Energy Forests / Land

Indonesia’s GHG Emissions: What’s Big, What’s Growing

Forests / Land Use May Be Stable Or Declining Fossil Fuels Growing at 6%/yr Data Source: IEA 2004

• Forests dominate emissions now, but no reason to expect major increase over

time; As forests depleted, or controls installed, emissions will decline.

• GHG Emissions from fossil fuel use are low relative to forests, but growing faster

than GDP

• By 2030, situation could change substantially depending on BAU, changes, land

use allocations, biofuels

All figures in MtCO2e. Forest data are compiled from various years

Source: From World Bank Office Indonesia, 2008. From Low Carbon Project-Phase 1

HIGH UNCERTAINTY 11 year average ranges from 360 to 3778 Mt)

Emission from Peat Fire

469+187 1029 3778 1191 360 1614 Mean 334 1225 385 117 524 2007 1111+433 2270 8334 2625 796 3560 2006 451+264 1078 3960 1250 378 1694 2005 440+180 1217 4462 1408 425 1907 2004 246+121 759 2783 876 264 1188 2003 678+246 1404 5155 1624 491 2204 2002 194+181 411 1511 477 143 645 2001 172+106 194 711 224 66 304 2000

• 396

1459 458 139 623 1999

• 689

2534 799 242 1082 1998

• 2567

9423 2970 898 4026 1997 Highest Lowest van der Werf et al. (2008) Duncan 2003 Page et al., 2002 Levine 1999 Heil et al. 2007 Year

Monthly ENSO Index and Average of Emission from Peat Fire from the Five Studies

• 15

15 30 45 60 1 6 1 6 1 6 1 6 1 6 1 6 1 6 1 6 1 6 1 6 1 6 1 99 7 19 9 8 1 9 99 2 00 2 00 1 2 00 2 20 3 2 04 2 05 2 00 6 2 00 7 Mean Emission (Mt C O2)

• 1

.5

• 1

.0

.5 .0 .5 1 .0 1 .5 2 .0 2 .5 3 .0 3 .5 EN SO Index (oC ) C O 2 Em issio n M

• n

tly EN SO In d ex

Emission from peat fire increased significantly in El Nino years

Relationship between ENSO Index Anomaly (Jun-Dec) and Emission Anomaly

• 1.00
• 0.50

0.00 0.50 1.00 1.50 2.00 2.50 3.00 19 97 19 98 19 99 20 00 20 01 20 02 20 03 20 04 20 05 20 06 20 07 In de x A n

• m

a ly (oC )

• 1

50

• 1

00

• 5

00 5 00 1 00 1 50 2 00 2 50 3 00 Em iss ion A no m aly (M t C O 2) E m ission A no m a ly E N S O In de x An

• m

aly

Relationship between Seasonal ENSO Index and CO2 emission from peat fire

y = 1229 .4x + 9 79.2 3 R

2 = 0.792

500 1000 1500 2000 2500 3000 3500 4000 4500

• 1.0

0.0 1.0 2.0 3 .0 J un e-Augu st EN SO Ind ex (oC ) Em ission (M t C O 2) y = 1107.7x + 1094 .9 R

2 = 0.8184

500 1000 1500 2000 2500 3000 3500 4000 4500

• 1.0

0.0 1.0 2.0 3 .0 J uly-Septe m be r EN SO Ind ex (oC ) Em ission (M t C O 2) y = 10 40.6x + 1208.7 R

2 = 0.8093

500 1000 1500 2000 2500 3000 3500 4000 4500

• 2.0
• 1.0

0.0 1 .0 2 .0 3 .0 August-O ctober EN SO Inde x (oC ) Em ission (M t C O 2) y = 1229 .4x + 9 79.2 3 R

2 = 0.792

500 1000 1500 2000 2500 3000 3500 4000 4500

• 1.0

0.0 1.0 2.0 3 .0 Septem ber-N

• v

e m ber EN SO Inde x (oC ) Em ission (M t C O 2) y = 946.7x + 1377 .2 R

2 = 0.7704

500 1000 1500 2000 2500 3000 3500 4000 4500

• 2.0
• 1.0

0.0 1 .0 2 .0 3 .0 O ctober-D ecem ber EN SO Index (oC ) Em ission (M t C O 2)

y = 1 134.1 x + 1 177.7 R

2 = 0

.8445 500 1000 1500 2000 2500 3000 3500 4000 4500

• 1.0

0.0 1.0 2.0 3.0 June-D ecem b er EN SO Index (oC ) Emission (Mt CO2)

Emission from Peat

Quick C emission Slow C emission Peat fire Drained Peat Emission from peat land

Fire control/delayed land clearing close to rainy season, particularly in El-Nino years Land clearing using zero burning Control peat conversion Improved water management Peat restoration (canal blocking and enrichment planting) Forest protection

Need Policy Reform, Law Enforcement, and Incentive system

Use of fire in land clearing/slash and burn practices), etc Establishment of timber and agriculture plantation etc

On-going initiatives

• Development of FEWS based on ENSO Index

(http://iridl.ldeo.columbia.edu/maproom/.Fire/)

• Development of fire prone map based on hot spot number

and fire driving factors (distance to main road/river/resettlement, soil types, soil cover etc).

• Establishing effective dissemination system for fire alert
• Enhancing community based peat fire management
• Facilitating local government to develop regulation on fire

management

• Creating incentive mechanism (insurance, carbon based

payment etc.) who successfully avoid or reduce fire area in extreme drought year as informed by ENSO index

• Creating fair payment distribution system

Fire Prone Map of Kalimantan

It was developed based on proximity from village centre, distance from road/river, land cover and soil types (Jaya and Boer, 2008)

Low-medium risk Medium-High risk High-Very high risk

Fire Risk Forecast 1 or 2 month lead time

• Hot Spot = exp(1.1*EI+6.8)
• ENSO Index (EI) = 1.5
• Hot Spot = exp(1.1*1.5+6.8)
• Hot Spot = 4678 > Median
• Cumulative rainfall is still

negative

• Risk of fire is high, need to

intensify fire control and call for implementing measures, particularly in high fire risk area)

Cumulative rainfall (real time and long term mean) Hot spot number ENSO Index

Decision process for fire management

Monitor SSTA or ENSO index Forecast hot spot number 1 or 2 month lead time Intensify fire control in fire prone areas and announce fire alert High hot spot number? Are fire control measures applied? Continue intensive monitoring until wet season start

Y N

Provide Incentive Warning/ Apply Penalty

Y N

Developed basis for reward (e.g. Carbon based payment-REL) Institutional system for payment distribution Certification Body Effective dissemination system

Supporting Policies & Government regulations

Funds for Payment (local/national/ global Monitoring system

Illustration of C-based Payment

1000 2000 3000 4000 5000 6000

• 1

1 2 3 E N S O In d ex E stim ate o f em issio n s

Baseline emission from peat fire ENSO index Jun- Dec: 2.0 Level of emission from peat after being monitored Achieved emission reduction