This document discusses developing policy scenarios to assess whether key forest countries will meet their Nationally Determined Contributions (NDCs). It outlines the project structure and work packages, including using scenario building to link science, policy, and politics. For Brazil case study, it presents preliminary results comparing business as usual, strong governance, and intermediate governance scenarios for deforestation and GHG emissions trajectories. Key challenges identified include obtaining appropriate spatial data and emission factors and aligning scenario results with country reporting under the Paris Agreement.

1. WP 4.2.Policy Scenario building
UFMG & CIT

2. Are key forest countries going to meet their NDCs?
Copenhagen’s NAMA
Paris’ NDC
Indicative NDC
https://themasites.pbl.nl/o/climate-ndc-policies-tool/#countries

3. Are key forest countries going to meet their NDCs?

4. Project structure
Work Package 1:
Achieving
transparency &
accountability
Work Package 2:
Tracking & assessing
actions
Work Package 3:
Bringing out the
politics
Global
Forests &
Climate
Arena
National
Policies &
Actions
Subnat’l
Policies &
Actions
Work Package 4:
Linking science,
policy & politics
• diagnostic
framework
• policy
scenarios
• science-policy
platforms

5. General process
• Refining LoA
• Phased approach
- Year 1: Brazil
- Year 2: Peru
- Year 3: DRC and Indonesia
• Submission of a publication describing model specificities for country
partners and country coordinators: Rochedo et al. (2018)

6. Current activities
• Compilation of list of demands for spatial data
- Focus on LULUCF
- AFOLU information important for assessing NDC attainment
• Presentation in the GCF meeting in Belém (October, 20th)
- Emission scenario platform within CIFOR project

7. GHG Emissions Scenarios
• Business as usual: current deforestation and emissions scenario
• NDC scenario: minimum deforestation reduction required to meet
NDC
• REDD+ scenario: ambitious deforestation reduction

8. Scenario components
• Overall narrative for each scenario
• Qualitative description of deforestation drivers
• Qualitative description of deforestation control policies
• Quantitative deforestation trajectory (total Km2 per year, with or without subdivision)
• Data set per country:
• Land use map (minimum 2-years, forest / non-forest use)
• Above ground/below ground carbon map
• BAU GHG for other non-LULUCF sectors (energy, agriculture)
• Spatially explicit drivers and policies (eg. built and planned roads, conservation areas)
• Fall back datasets: Hansen (land use), Saatchi (carbon), ClimateTracker (BAU GHG for
energy and agriculture), OpenStreet Map, WDPA, PBL.NL

9. Scenarios outputs
• Spatially explicit deforestation projections
• Improve deforestation policies by indicating priority areas
• Allow science-based regional target and benefit-sharing proposals (i.e.
avoid barrel/competition pushing between jurisdictions)
• GHG Emissions trajectory
• Assess if country is on track to meet its NDC
• Estimate potential for generating carbon credits / result-based payments
via LEAF ART-TREES, ITMOs (Art. 6.2) and REDD+ (Art. 5)

10. Brazil’s Case Study

11. Scenario components for Brazil
• Data set per country:
• Land use map: PRODES and National Inventory
• Above ground/below ground carbon map: Brazil’s National Inventory
• BAU GHG for other non-LULUCF sectors: Official projections from Min Science &
Technology
• Overall narrative for each scenario
• Deforestation drivers
• Deforestation control policies
• Deforestation trajectory (total Km2 per year, with or without subdivision)
• BAU: historical trajectory
• REDD+: original PNMC target (4 thousands km2, down from current 11 thousands km2)

12. Preliminary results for Brazil
REDD+ = SEG
BAU = IEG
NDC = to be developed

13. Preliminary results for Brazil

14. 0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
GtCO
2
Governança Forte
AFOLU Energia
Preliminary results for Brazil
Strong Governance

15. 0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2
0
1
8
2
0
2
0
2
0
2
2
2
0
2
4
2
0
2
6
2
0
2
8
2
0
3
0
2
0
3
2
2
0
3
4
2
0
3
6
2
0
3
8
2
0
4
0
2
0
4
2
2
0
4
4
2
0
4
6
2
0
4
8
2
0
5
0
GtCO
2
Governança Intermediária
AFOLU Energia
Preliminary results for Brazil
Intermediary Governance (BAU)

16. 0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
1.8
2.0
2018
2020
2022
2024
2026
2028
2030
2032
2034
2036
2038
2040
2042
2044
2046
2048
2050
GtCO
2
Governança Fraca
AFOLU Energia
Preliminary results for Brazil
Weak Governance (BAU)

17. Key challenges
• Identity appropriate spatially explicit data sources and Tier 2-3
emission factors
• Develop scenario narratives grounded on country’s expectations
• Align results with National GHG Inventories, FREL and ART-TREES
• Integration with other WPs: CIT&UFMG as final integrator
• Avoid missing the forest for the trees