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Indonesian GHG Inventory: LUCF Sector Rizaldi Boer Bogor Agricultural University INDONESIA Consultative Group of Expert:

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Presentation on theme: "Indonesian GHG Inventory: LUCF Sector Rizaldi Boer Bogor Agricultural University INDONESIA Consultative Group of Expert:"— Presentation transcript:

1 Indonesian GHG Inventory: LUCF Sector Rizaldi Boer Bogor Agricultural University INDONESIA E-mail: rboer@fmipa.ipb.ac.id Consultative Group of Expert: Hand on Training Workshop on GHG Inventory organized by UNFCCC Shanghai, 8-12 February 2004

2 Indonesia GHG Inventory: 1994

3 Total Emission by Sector: CO 2 -eq

4 Sector Emission by Gases

5 GHG Inventory: Forestry Sector

6 Main Factors cause the variations Selection of MAI for the succession forest. Estimated from [(WVVF- WVLOF)* BEF*BD]/30. In Indonesia MAI of LOF varied from 1.2-2.7 tB/ha) Area of production and conversion forest under succession Assumption of survival rates of A and R (NAtCOM used 100%)

7 Log Production & Area of Harvesting Area under succession was logged over forest (LOF). If LOF data for a given year is not available, it was estimated from log production data (the logged area is log production divided by 20 m 3 ) Log over forest map

8 Deforestation Rate (000 ha) Available data only for 1970S, 1980S and 1990s, average G&F conversion for 25 years = (Def70s+Def80s+Def90s)/3 ~ proportion similar to FAO 1990

9 Fraction of biomass burnt on and off site and decay

10 Abandoned Land Area being abandoned are three categories: –Area of abandoned land was shifting cultivation: 20*mean of SC (1990-1995) Grassland Forest fire

11 Data that need to be improved

12 CCFPI (Climate Change, Forest and Peatland in Indonesia) Develop software for estimating carbon stock change and GHG emission from peatland –Inventory of EF from Peatland –Development of Land Use change model –Development of software –Estimation of C-stock changes and GHG emission from peatland under current and projected land use (different project scenarios) Collaboration Project between Wetland International-Indonesian Program (WI-IP), Bogor Agricultural University and ARCATE Indonesia (Funded by CIDA): 2001-2005

13 CO2 and CH4 emission from Peatland of South Kalimantan, Indonesia Source: Hadi et al., 2002

14 A12: Sec. Forest (. 2m depth) A11: 2 years rice paddy (1-2 m depth) A10: 6 years rice-soybean rotation (0.2-0.4 m depth) M9:Sec. Forest (0.2-0.6 m depth) B8: Sec. Forest (0.05-0.15 m depth) B7:3 years cassava (0.7 m depth) B6:3 years paddy (0.4-0.5 m depth) J5: Sec. Forest (0.15-0.25 m depth) J4:1 year paddy (0.05-0.20 m depth) G3: Sec. Forest (1-2 m depth) G2: Rice paddy-fallow (0.1-0.4 m depth) G1: Upland-fallow (0.7-1 m depth) Source: Hadi et al. 2002) Seq. CH 4

15 Effect of flooding on CH4 emission from herbaceous arctic tundra Source: Mornsey et al, 1994

16 Study Site Merang Kepahyangan, South Sumatra Climate: bi-modal

17 Inventory of EF from past studies Socio-economic survey Current and projected LULUCF under the absence and the presence of C-projects Project scenario (WBS130, 140, 210, 230, 240, 250) and project boundary Equations that relate income and energy consumption Impact of projects on HH income Image analysis (Physical predictors) Data series of socio- economic Data of CS and MAI (WBS300) Database EF, Carbon stock & MAI Selection of EF, CS and MAI Water table of peat with and without blocking Water table observation data (WBS240), and fire risk Canal blocking (WBS120, 130) Calculation of CS change and emission within project boundary Leakage estimation Carbon Benefit Leakage quantity Software or estimating CS change and GHG emissions Map of peat depth and maturity Peat depth& maturity

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