Indonesia is preparing to finalize its second Forest Reference Emission Level (FREL) with enhancements, transitioning to using country-specific values and focusing on peatlands and mangroves. Various challenges related to data availability and institutional capacity have been identified, alongside discussions on uncertainty analysis using Monte Carlo simulations to improve accuracy in emission reporting. Acknowledgments were made to various organizations, including Norway's NICFI and USAID, for their support in the development of the capacity-building materials.

2. Session 10
Open Discussions
Daniel Murdiyarso and Rupesh Bhomia
17 April 2020

3. Background
• Indonesia is poised to finalize 2nd FREL with significant
refinements over last version.
• Transition from default Tier 1 to Tier 2 using country
specific values for FREL determinations.
• Incorporation of UNFCCC Wetlands Supplement (2013)
with emphasis on Peatlands and Mangroves.
• Various challenges exists in terms of institutional
capacity, data availability, enhancing accuracy and
reducing uncertainty.

4. Sessions 1 and 2: Peatlands
• Included in AFLOU (NGHGI) – Loss and Gain approach
• Peatland Activity and Emission factors
• Drained Organic soils
• CO2, CH4, N2O
• Fires - CO2, CH4, N2O [and mass of peat]
• CH4 from Ditches
• Offsite - DOC
• Rewetted Organic soils - CO2 and CH4
• FREL 2016 to FREL 2020
• Fire
• Decomposition
• Gaps and data availability

5. Sessions 3 and 4: Mangroves
• Mangroves not included in AFOLU :- Part of appropriate
national land-use category according to national forest
definition
• Stock difference approach for Carbon; Loss and gain
approach for CH4 and N2O
• Activities relevant to
• CO2 EF – Forest management, Extraction, Drainage, Rewetting and
revegetation
• CH4 and N2O EF – Aquaculture and Rewetting (hydrology changes)
• Data on C stocks from protected and degraded mangroves
from across Indonesia available; Transition to Tier 2 values
possible

6. Sessions 5 and 6: Uncertainty Analysis
and Monte Carlo Simulation
• Lack of accuracy ->bias; lack of precision ->uncertainty
• Bias to be prevented; Uncertainty to be quantified/reported
• Declaring uncertainty in reported Emission Levels is
expected by UNFCCC, and required by many RBP
programs
• Two methods for uncertainty determination
• Addition /propagation
• Monte-Carlo Simulation (More robust, preferred, time
intensive)
• Running MC simulation for FREL 2020
• AD and EF per land use type per Island per period per carbon
pool (Complex but doable)

7. Sessions 7 and 8: TACCC Principles
and FREL Diagnostics
• Transparency, Accuracy, Comparability, Completeness and
Consistency
• Assumptions and methodologies for FREL are clearly explained
• Measure of the exactness of emissions or removal estimates;
Uncertainties are reduced as far as possible
• FREL emissions are comparable with the BUR/GHGI
• Covers all sources and sinks, as well as all gases; Full geographical
coverage
• Consistent in all its elements with the BUR/GHGI
• The countries should include the reasons for omitting a pool
and/or activity from the FREL.
• Good practice to - document the process, recognize lack of
data, use same methodology and units (for AD and EF),
estimate uncertainties, cover all potential sources of error.

8. Sessions 9: How best to support FREL
improvement?
Efforts to enhance our understanding and data
availability on
• The selected FREL emissions/sinks
• Preferences on how best to support GoI on the non-
selected emissions/sources
• Description of the MRV system to support FREL 2020
submission
• Description of the FREL uncertainty estimates

9. Acknowledgements
The capacity building materials were made possible through a grant
given by the Norway’s International Climate and Forest Initiative
(NICFI) to the Center for International Forestry Research (CIFOR)
under the Agreement No. INS 2070-19/0010. While CIFOR gratefully
acknowledges the support, the information provided in the
materials do not represent the views or positions of the Norwegian
Government. CIFOR would like to recognize the support by the
United States Agency for International Development (USAID) in
generating some of information used in the materials.

10. Thank you