Adjustment Factors

EMISSIONS

  1. Initial Leakage Quantification

This section describes how a Project’s leakage is quantified at Certification. 

    1. For leakage quantification, ERS conservatively assumes that the carbon stock in Hosting Areas is reduced to 0.
    2. If a Project undertook pre-submission activities that resulted in leakage, ERS will quantify carbon stock in the Hosting Areas and deduct it from the Project’s net GHG removals. 

        1. Leakage resulting from Pre-submission activities is obtained for each Hosting Area using equation (12):

            • Where:
              • 𝗟i𝗉𝖺 = Monitored leakage on the Hosting Area i; tCO2e.
              • 𝗖i,t = Carbon stock in the Hosting Area where activity i is located at year t; tCO2e. 
    3. At Certification, the Developer can declare potential leakage through the following methods:
      1. If the Developer is able to provide the Hosting Area(s), ERS will estimate the potential impact represented by the leakage (𝗟𝗁𝖺) using the same calculation process as for the Restoration Site, derived from equations (1), (2), (3), (4), (5) and (6). 
      2. If the Developer cannot provide the Hosting Area(s), they must identify Displaced Activity Areas and their estimated displacement percentage. To estimate the potential impact of the displacement(s), ERS will generate random sampling plots within the Leakage Belt and determine the average carbon stock of these sampling plots, following the same calculation process as for the Reference Site, derived from equations (7), (8), (9). The average carbon stock of the sampling plots in the Leakage Belt is obtained using equation (13):

            • Where: 
              • 𝗟i𝗉 = leakage estimated for a Displaced Activity Area i within the Project Area; tCO2e.
              • 𝗔i = Land-surface of the Displaced Activity Area; ha.
              • 𝗖𝗌–𝗉𝗅𝗈𝗍 = Mean carbon stock of the sampling plots in the Leakage Belt; tCO2e·ha-1
              • 𝗣i = Declared % of displacement of the activity; dimensionless
      3. The estimated leakage is obtained using equation (14):

        1. Where: 

            • 𝗟i𝗉 = leakage estimated for a Displaced Activity Area i within the Project Area; tCO2e.
            • 𝗔i = Land-surface of the Displaced Activity Area; ha.
            • 𝗖𝗌–𝗉𝗅𝗈𝗍 = Mean carbon stock of the sampling plots in the Leakage Belt; tCO2e·ha-1
            • 𝗣i = Declared % of displacement of the activity; dimensionless
    4. Total leakage is obtained by aggregating leakage derived from the Hosting Area(s) (1.2.1) and equation (14), using equation (15): 

    • Where:
      • 𝗟𝖽 = Total declared Leakage; tCO2e.
      • 𝗟i𝗁𝖺 = Leakage of known Hosting Areas; tCO2e.
      • 𝗟i𝗉 =  Leakage of Displaced Activity Areas; tCO2e.

  1. Leakage Correction 

This section describes how initial leakage is corrected at year two (2) and/or year four (4) after Certification. 

To quantify leakage, ERS compares the total carbon stock in the Hosting Areas before and after the activity displacements. The delta is deducted from the Project’s total GHG removals. 

    • Where:
      • 𝗟𝖼 = Corrected Leakage; tCO2e.
      • 𝗟i,t𝗆 = Monitored GHG emissions from a Hosting Area i at Verification Cycle t; 𝗟i,t=0𝗆= 0 tCO2e.

To monitor the evolution of leakage emissions throughout the crediting period, ERS compares the total area of the Hosting Areas from one Verification to another. The impact of the new surface brought to production is then calculated following the procedure described in the equation (16). 


  1. Quantification of Loss Events 

    1. In case of a loss event, the GHG emissions of the Loss Area are quantified. 
    2. The carbon stock of the Loss Area is calculated before and after the loss event, following the Initial Carbon Stock calculation.
    3. The carbon stock loss is obtained using equation (17):

    • Where: 
      • 𝗖𝗅𝗈𝗌𝗌–𝖾𝗏𝖾𝗇𝗍 = Impact of the loss event; tCO2e. 
      • 𝗖𝗉𝗈𝗌𝗍–𝖾𝗏𝖾𝗇𝗍 = Carbon stock in the area after the loss event; tCO2e
      • 𝗖𝗉𝗋𝖾–𝖾𝗏𝖾𝗇𝗍 = Carbon stock in the area before the loss event; tCO2e

  1. Loss Event Characterisation

    1. Before Verification, ERS calculates the net GHG removals of the Verification Cycle, and categorises the loss event(s) of the period using equation (18):

    • Where: 
      • 𝗖t = Net GHG removals achieved during the Verification Cycle t; tCO2e.
      • 𝗖t = GHG removals achieved at the end of the Verification Cycle t; tCO2e.
      • 𝗖t–1 = GHG removals achieved at the end of Verification Cycle t–1; tCO2e.

    1. If 𝗖t<0 , the loss event is considered as a reversal.

DYNAMIC BASELINE

  1. Concept 

    1. A dynamic baseline evaluation consists of a periodic re-evaluation of the initial baseline scenario to adjust unit issuance. 
    2. The dynamic baseline process is performed before each Verification. This process will lead to the adjustment of unit issuance, if necessary, following procedures detailed in the Units & Issuance section of the ERS Programme. 
    3. To generate a dynamic baseline, ERS selects control plots located outside the Project Area and the Leakage Belt but with similar ecological and biophysical characteristics, including degradation levels. Shapefiles of these control plots will be disclosed in the Project Design Document and on the ERS Registry. 

  1. Project Clustering

    1. Concept. Once the indicators are selected, the Restoration Site is stratified utilising the K-means clustering algorithm, a statistical technique that discerns natural patterns within the dataset and supports the identification of optimal clusters. Stratification involves the division of the Restoration Site into sub-zones based on the selected indicators listed in 2.2. Clusters refer to the grouping of naturally similar sub-zones, identified by the algorithm. For each sub-zone, median values for every indicator are calculated, minimising the impact of outliers and ensuring a robust analysis.
    2. Identification of Environmental Indicators. Various environmental indicators covering ecological, climatic, and land use aspects are identified to determine sub-zones within the Restoration Site. Indicators include: 
      • Landcover 
      • Elevation 
      • Slope (Derived from Elevation)
      • Forest Height 
      • Soil Physical and Chemical Parameters (bulk density, coarse fragment, clay content, pH, SOC) 
      • Biomes from IUCN classification
      • Distance to Roads

  1. Selection of Control Plots 

    1. Concept. Areas or sub-zones that share similar characteristics to the clusters, located outside of the Restoration site and the Leakage Belt and referred to as control plots, are identified using the K-Nearest Neighbors (KNN) algorithm. 

    2. Indicators. The selection of control plots relies on the set of indicators selected in 2.2 and important political factors such as political physical boundaries. This ensures that the selected control plots are located in the same country and governed under the same jurisdiction as the Project Area. 

      💡Land tenure and ownership are not included in this Methodology due to the lack of global and, in many cases, national land tenure registries that are available for public use

    3. Exclusion of Inappropriate Areas. Regions within the study area unsuitable to be considered control plots are systematically excluded. These include:
      • Protected areas: their conservation status does not ensure a real representation of a business-as-usual scenario.
      • Active carbon projects: they do not ensure a real representation of a business-as-usual scenario, as both the Project and control plots are subject to the same treatment.
      • Commercial plantations: these areas cannot act as control areas because a different treatment is applied. Commercial plantations differ significantly from restoration projects in incentive structures, in that there is typically a strong economic incentive for planting and harvesting the trees.
    4. This approach guarantees that only genuinely comparable plots are considered for the Project, enhancing the precision of the selection process.

  1. Dynamic Evaluation

Before each Verification, ERS performs a dynamic evaluation of the initial baseline.  

    1. Refinement of Control Plots. ERS verifies the relevance of control plots using the methodology detailed in the Selection of Control Plots.  If it is found that the current control plots are no longer representative or applicable, the process involves regenerating new control plots. 
    2. Assessment of Control Plots. For each cluster, the average change in carbon stock across all control plots is obtained using equation (19). 

        • Where: 
          • 𝗕t𝖼 = Corrected Baseline at the Verification Cycle t; tCO2e.
          • 𝗖t–1,i𝖼𝗉 = Mean carbon stock of the control plots that belong to the cluster i at Verification Cycle t–1; tCO2e·ha-1.
          • 𝗖t,i𝖼𝗉 = Mean carbon stock of the control plots that belong to the cluster i at Verification Cycle t; tCO2e·ha-1.
          • Ai = Project Area covered by cluster i; ha.
    3. Following the assessment of control plots, two distinct scenarios can emerge:
      1. ​​If the mean carbon stock in control plots has shown an upward trend from Y0 to the present, indicating positive forest growth, the Project will adjust for this increase when calculating GHG removals and issuing units. In such a scenario, the Project cannot claim full credit for the GHG removals on its Restoration Site. A corrective mechanism is used to adjust the overestimated baseline. Refer to the Units & Issuance section of the ERS Programme for more details.
      2. Conversely, if a decline in carbon stock is detected in the control plots, a corrective mechanism is applied to adjust the underestimated baseline. This mechanism involves adding GHG removals and their corresponding units to the Project. Refer to the Units & Issuance section of the ERS Programme for more details.
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