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  1. Green finance: practices aligned with climate change mitigation and co-benefits (e.g. water and biodiversity conservation), where the certainty of directional change is likely, but the impact level is not measured. For example, companies or loans using "green lists" of eligible practices; "good enough" methods (lowest requirements)
  2. Results-based payments: payments based on defined climate mitigation supported by a MRV accounting systems that fosters confidence in results delivered, although medium/high quantification uncertainty applies (intermediary requirements)
  3. Carbon-credit markets: quantification of climate mitigation results following rules and procedures determined by protocols and standards under third-party verification (e.g. CDM, Verra and Gold Standard standards), which lowers uncertainties and increases credibility of results (highest requirements)

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  1. Scope - other carbon sinks (e.g. trees), GHGs emissions (e.g. emissions from livestock) and opportunities for avoided carbon loss
  2. Mitigation co-benefits (e.g. water and biodiversity conservation)
  3. Accuracy needs and tolerance for uncertainty
  4. Risk of impermanence (e.g. adoption of practices or events that may reduce soil C stocks)
  5. NonRisk of non-performance (e.g. unexpected practice effect) 
  6. Scalability
  7. Reporting requirements - given the timing to detect changes (e.g. usually > 5 years) and make payments.
  8. Verification needs (e.g. first, second and third-party)
  9. Costs (e.g. acceptable % of the total project budget spent on MRV)
  10. Ensure benefits to farmers 

C. Plan for improving

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accuracy and

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uncertainty over time toward carbon market-grade credits.

(lowest accuracy and highest uncertainty) Practice lists and criteria → Indicators and proxies → Modeling → Measurement (highest accuracy and lowest uncertainty)

D. Improving accuracy and uncertainty 

  1. Developing practice-based indicators "green lists" of eligible practices (e.g. scientific literature review and experts consultation)
  2. Using models - /remote sensing for understanding soil C sequestration magnitudes and trends: choosing a model, technical requirements, caveats, assumptions and uncertainties  
  3. Hybrid approach: direct measurements with modeling/remote sensing. sensing 
    1. Optimal measurement strategy based on project/region characteristics and resources available
      1. activity data collection (e.g.
      how to
      1. use of smartphone, interviews)
      2. focus on few high-quality measurements (e.g. what to measure and how - sampling design; soil C and soil bulk density; frequency)
      3. prioritization if needed (e.g. sampling design; soil C or bulk density; soil C determination using routine analysis or dry-combustionmethod; use of pedotransfer functionspedo-transfer functions,...)
    2. Dealing with data gaps (e.g. scientific literature, experts consultation, global databases) 
    3. Choosing a model, model calibration, technical requirements and acceptable uncertainties
    4. Remote sensing: application and requirements 
    5. Co-benefits assessment (e.g. generating water/biodiversity indicators from/in conjunction with soil C measurements)
  4. Aggregation aspects across larger scales to reduce project-level variation effects 
  5. Setting up baselines (e.g. Baseline v. base year)
  6. Verification type and frequency (credibility highest with third-party)

E. How to deal with risk of impermanence or non-performance: 

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  1. Soil carbon sequestration practice MRV goals
  2. Scope
    1. Other GHG sources and sinks  
    2. Data needs and dealing with data gaps
  3. Identify needs for accuracy and tolerance for uncertainty
  4. Address risk of impermanence or non performance
  5. Opportunities for avoided carbon loss
  6. Identify joint co-benefits 
  7. Ensuring benefits to farmers:  credit C/B and MRV as feedback to farmers on immediate benefits
  8. Scalability
  9. Baseline design and upfront costs
  10. Units, stratification and aggregation requirements.
  11. Timing of MRV to detect change, make payments and meet reporting requirements.
  12. Verification
  13. Costs and budget

C. Plan for improving over time in accuracy and uncertainty toward carbon market-grade credits.

  1. Practice lists and criteria (lowest accuracy and highest uncertainty)
  2. Indicators and proxies 
  3. Modeling
  4. Measurement (highest accuracy and lowest uncertainty)

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