Lesson 1, Topic 1

In Progress

Intervention Boundaries, Baseline, Quantification Approach, Uncertainty 

Emissions and / or Removals

4.1. Intervention Boundary (SSRs)

Intervention boundary: used to identify the sources, sinks, and reservoirs that contribute to an intervention’s overall impact defined on a cradle-to-gate basis. Not a physical boundary. 
The concept of de minimis is used to identify information that, if omitted or misstated, would significantly misrepresent a compilation of quantitative environmental information to its intended application, thereby creating confusion or misunderstanding. 
- De minimis threshold: quantitative threshold under which GHG sources, sinks, and reservoirs (SSRs) in the Intervention boundary may be excluded from monitoring and quantification.
- SC VC Requirements: De minimis Level 1 = 5%; Level 2 = 2%

Exclusion of GHG SSRs from Quantification: can be justified when not surpassing the de minimis threshold
- Tip: Top-down methodologies generally provide a good indication as to what SSRs should be included

Example: Adoption of cover cropping – practice increases the consumption of diesel fuel because the farmer now has to make additional passes on her farm, however, the emissions associated with diesel make up less than 2% of the intervention boundary’s total emissions
- Therefore, you can exclude these emissions from the SSR table and provide justification for the exclusion
- Justify that exclusion by linking to a materiality analysis, literature review, scientific article, etc.

Example:

Fundamental principles: Completeness, Relevance & Transparency

Three components of this section must be addressed:

Describe the procedure you used to identify the SSRs (rational approach or methodology – did you conduct a materiality assessment?; did you refer to the relevant methodology?)

Identify all SSRs in the table provided in the IDD, and provide justification

Identify any sources of leakage (the unanticipated decrease or increase of GHG benefits outside of an intervention’s accounting boundary resulting from the intervention’s activities)

Key Questions – Intervention Boundary (SSRs)

Can you provide justification as to how the sources, sinks, and reservoirs relevant to your activities included in each intervention were identified? 
Have you conducted or are prepared to conduct a materiality analysis (Level 2) in order to determine relevant GHG SSRs? 
Have you justified any exclusions of GHG SSRs from your quantification, and provided documentation or a website link to back up that justification?

4.2. Description of the Baseline

Suggested to refer to Baseline Guidance in relevant Methodologies, e.g.: VM0022: Section 6, Procedure for Determining the Baseline Scenario

Baseline (noun): an initial set of critical observations or data used for comparison or a control

Intervention Baseline: The baseline must be the business-as-usual scenario most likely to take place in the absence of the Intervention. The baseline should account for the condition as close to reality and as consistent with the accounting for the Intervention state as is feasible. The baseline should be representative of the relevant operating conditions immediately prior, or within a reasonable timeframe (i.e., where data is available and where the situation can be accurately verified) to the implementation of the Intervention.

(SC Verification Requirements for VC Interventions v0.91)

Accurate: The baseline should account for the condition as close to reality and as consistent with the quantification approach used in the post-intervention state as is feasible.
Consistent: the approach enables meaningful comparisons in GHG-related information, like uniform procedures over time (and for both baseline and intervention)
Representative: the baseline time period shall be long enough to ensure that the variability is accounted for (multiple years may be necessary)

SC Requirements – “A baseline scenario shall be established for each different geographic area included in the Program. In a given geographic area, where several baseline scenarios are coexisting, the area shall be stratified such that a single baseline scenario can be described for each stratum.”

Different variables can influence how a baseline might be stratified, for example:

Unique activities that have a unique Quantification Approach, and unique set of SSRs
Geographic location (i.e., supply sheds where activities take place)
Agro-ecological zone (climate, soil type, etc.); activity-dependent

Table Example

Intervention	Activity	Geography (Supply Shed)	Annual Yield Impacted	Baseline Emissions
Energy Solutions	Renewable Energy, Solar	North East, United States Milk Shed (see section 3.2-3.3)	453 tonnes of milk	Baseline emissions from electricity consumption: Absolute: 9,394 tCO2e, Intensity: 0.11 tCO2e / MMBTU
Regenerative Agriculture	Cover Cropping with legumes	Winter Wheat Supply Shed, Central US (see section 3.2-3.3)	680 tonnes of winter wheat	Baseline removals from soil organic carbon stock: Absolute: 13,750 tCIntensity: 55 tC / ha

KEY QUESTIONS – BASELINE

Can you describe the baseline status of the proposed activities included in each Intervention?
Can you state the total amount of goods anticipated to be affected by the activities within each Intervention included in the Program?

4.3.1 – 4.2.12 Quantification Approach

4.3.1. Describe how criteria and procedures or methodologies for quantifying GHG emissions and/or removals for selected GHG SSRs for each one of the types of activities included in the stand-alone intervention/Program were selected and established. If the quantification approach is using a computer simulation model (e.g., process-based model), the Certificate Holder must fill out Annex B of the VC-IDD.

Note: Top-down QA is defined as approaches that have been approved, recognized, or published which may include approved methodologies and/or protocols from Standard Setting Organizations such as Gold Standard, CDM, CAR, Verra, etc.
Bottom-up approaches should be used only in cases where a Top-down approach is not available or appropriate. Bottom-up approaches will be reviewed by an internal SustainCERT committee and validated on a case-by-case basis.

4.3.2 Quantification Approach

Describe each quantification approach, including deviations.

4.3.2 Describe the proposed approach to quantifying emissions in both baseline(s) and intervention(s) scenarios – and clearly reference any existing methodologies/protocols approved under an established standard where used (e.g., Gold Standard, Verra, etc.).

Example table for listing each activity, its corresponding QA, if there are deviations, etc.

Intervention	Activity	Proposed Methodology / Quantification Approach / Model	Deviations (Yes, No)
Regenerative Agriculture	Reduced Tillage	VM0042, Methodology for Improved Agricultural Land Management (see link http://….)	Yes
Regenerative Agriculture	Reduced Tillage, SSR: CO2, CH4, N2O from increased pesticide usage	VM0042, Methodology for Improved Agricultural Land Management (see link http://….)	No

4.3.3 Quantification Approach:

How do you intend to monitor / How will you ensure functional and service equivalence? 

4.3.3. Demonstrate functional and service equivalence in the type and level of activity of goods or services provided between the intervention and the baseline scenario and explain, as appropriate, any significant differences between the intervention(s) and the baseline(s) scenario. Where service equivalence is not met, associated leakage shall be accounted for.

4.3.4-4.3.7- Quantification Approach:

Eligibility – How are these activities beyond BAU?

4.3.4. Describe how the activities result in GHG emissions reductions or removal enhancements beyond what would occur in comparison to the determined GHG baseline(s).

Fundamental Principles – Describe and justify how the QA is conservative and transparent in its limitations

4.3.5. Describe how the quantification approach is conservative
4.3.6. Justify the relevance, completeness, consistency, and accuracy of the quantification approach for the activities included in the Intervention/Program (baseline and activity).
4.3.7. Detail any references, limitations (including data quality), and assumptions applied

4.3.8–4.3.9  GHG emissions, Goods impacted

Quantify GHG emissions and/or removals separately for each relevant SSR, considering potential leakage inside and outside of the Scope 3 boundary

State the total amount of goods affected (for validation, the expected amount of goods)

Intervention	Activity	Geography (Supply Shed)	Annual Goods Affected
Energy Solutions	Renewable Energy, Solar	North East, United States Milk Shed (see section 3.2-3.3)	453 tonnes of milk
Regenerative Agriculture	Cover Cropping with legumes	Winter Wheat Supply Shed, Central US (see section 3.2-3.3)	680 tonnes of winter wheat

4.3.10-4.3.12  Uncertainty, Risks

Fundamental Principle: Transparency and conservativeness

Uncertainty Analysis

4.3.10. [Level 1] Perform a qualitative or quantitative uncertainty assessment (see guidance on Uncertainty assessment for SustainCERT’s Value Chain Interventions in Annex II).

4.3.11. [Level 2] Perform a quantitative uncertainty analysis (see guidance on Uncertainty analysis for SustainCERT’s Value Chain Interventions in Annex II).

Risk assessment

Provide an assessment of risks potentially affecting expected emissions reductions or removals enhancements and discuss related mitigation measures introduced

Resources:

ANNEX II. Uncertainty Assessment Guidance of the SC VC Requirements v0.9

P.30 – The disclosure of the uncertainty assessment by the IR increases the level of information associated with emission reductions or removals. Therefore, it aligns with the transparency principle present in SustainCERT’s Value Chain requirements.

Model Uncertainty: uncertainty associated with the models used to characterize the relationships between various parameters and emission processes. (Also see modeling Annex in SC VC Requirements)
- Model uncertainty may arise either due to the use of an incorrect mathematical model or inappropriate parameters (i.e., inputs) in the model.
Parameter Uncertainty: uncertainty regarding whether a value applied accurately represents the activity
- Parameter uncertainty may arise, for example, from a measurement or sampling error.

The Intervention Representative (IR) must: 

Indicate quantified uncertainty [reported as standard deviation (minimum and maximum) or confidence intervals] for both model and parameter uncertainty for all inputs, including eventual modeling tool input parameters, used to estimate or monitor the emission reduction or removals associated with the intervention.
Disclose the number of parameters associated with the reported uncertainties and document that uncertainty is calculated for parameters that contribute to >80% of emissions sources.
Describe the limitations/sensitivity of this approach.

Parameter uncertainty unknown -> use a value that is conservative
Based on the outcomes of the assessment -> identify areas for improvement

The IR should convert the final result of uncertainty into high, medium, or low according to this kind of table.

KEY QUESTIONS – Quantification Approach

What existing methodologies / protocols / research / documentation serve as the basis of the intervention’s quantification approach? 
Does your proposed QA deviate from the top-down methodology chosen? If so, can you describe and justify the proposed deviations? 
Does your QA involve a model? If so, are you prepared to complete the Modelling Annex?
Can you demonstrate functional and service equivalence in the type and level of activity of goods or services provided between the project and the baseline scenario? 
Are you prepared to demonstrate that the activities result in GHG emissions reductions or removal enhancements beyond what would occur in comparison to the determined GHG baseline? 
Can you detail and justify the limitations or assumptions of the QA approach? 
Have you performed an uncertainty analysis? In cases where uncertainty values are unknown are you able to identify a value for the parameter that is indisputably conservative or conduct a pedigree matrix?

4.4. – Accounting for Sequestration and Permanence

This may or may not apply (refer to the IDD).

Permanence: Refers to a long-term guarantee that mitigation benefits are covered by a compensation or insurance mechanism against the risk of reversal.

Reversal: Refers to an event causing carbon that has been stored (in the soil or trees) to be released back into the atmosphere.

Five Major Risk Categories:

Natural disturbance risks
Political risks
Project Management risks
Financial risks
Market risks

Fundamental Principle: Transparency

A self-reported scoring system – indicators rated as ‘high’ should be associated with mitigation measures.

Interventions that present a high non-permanence risk are able to issue only 80% of the quantified carbon removals. This measure aims at mitigating the effect of eventual future reversals on the climate mitigation claims made on the basis of the Intervention’s verified carbon removals.
Note that in the case of an Intervention that generates carbon removals and emission reductions, only carbon removals are subject to qualifying the non-permanence risk and applying the 80% measure in case of high risk.

Intervention Boundaries, Baseline, Quantification Approach, Uncertainty ​​

Intervention Boundaries, Baseline, Quantification Approach, Uncertainty 