\[ C_{\text{baseline},i,t} = \begin{cases} CBI_b \times ((LAG_{\text{bsl},i,t} - LAG_{\text{bsl},i,t+1}) + (DW_{\text{bsl},i,t} - DW_{\text{bsl},i,t+1})) & \text{if fire occurs in } t, \\ 1 \times ((LAG_{\text{bsl},i,t} - LAG_{\text{bsl},i,t+1}) + (DW_{\text{bsl},i,t} - DW_{\text{bsl},i,t+1})) & \text{if no fire in } t. \end{cases} \]
Where:
\(C_{\text{baseline},i,t}\): Biomass loss in the baseline scenario for composite baseline \(i\) at time \(t\), accounting for both fire and non-fire conditions; measured in t CO₂-e per unit area.
\(CBI_b\): Composite Burn Index scaling factor for burn severity \(b\), applied only when fire occurs.
\(LAG_{\text{bsl},i,t}\): Live aboveground biomass stocks in the baseline scenario for composite baseline \(i\) at time \(t\); measured in t CO₂-e per unit area.
\(LAG_{\text{bsl},i,t+1}\): Live aboveground biomass stocks in the baseline scenario for composite baseline \(i\) at time \(t+1\); measured in t CO₂-e per unit area.
\(DW_{\text{bsl},i,t}\): Deadwood stocks in the baseline scenario for composite baseline \(i\) at time \(t\); measured in t CO₂-e per unit area.
\(DW_{\text{bsl},i,t+1}\): Deadwood stocks in the baseline scenario for composite baseline \(i\) at time \(t+1\); measured in t CO₂-e per unit area.
To calculate the net change in biomass in the baseline scenario for each timestep, where negative values represent biomass loss and positive values represent biomass gain, we define:
\[ \Delta C_{\text{baseline},i,t} = C_{\text{baseline},i,t} - C_{\text{baseline},i,t-1} \]
Where:
\(\Delta C_{\text{baseline},i,t}\): The net change in biomass in the baseline scenario for composite baseline \(i\) at each project reporting timestep \(t\); measured in t CO₂-e per unit area. Negative values represent a biomass loss, while positive values represent a biomass gain.
\(C_{\text{baseline},i,t}\): Biomass value at each project reporting timestep \(k\), calculated using the baseline biomass loss equation.
\(k\): Timestep in the project period, where \(t = 1, 2, 3, \dots, T\).
The cumulative net change (loss or gain) in biomass from the project start up to time \(t\) is calculated by summing the net changes over each timestep:
\[ \Delta C_{\text{net_baseline},i,t} = \sum_{t=1}^{T} \Delta C_{\text{baseline},i,t} \]
Where:
To calculate the project net biomass change, we define equations that account for fire, treatment, or neither event at each timestep. It is assumed that all biomass loss due to treatment activities is immediately released, meaning that any biomass reduction observed in \(TRT_{\text{proj},i,k}\) is considered to be an instantaneous emission.
\[ C_{\text{project},i,t} = \begin{cases} CBI_b \times ((LAG_{\text{proj},i,t} - LAG_{\text{proj},i,t-1}) + (DW_{\text{proj},i,k} - DW_{\text{proj},i,t-1})) & \text{if fire occurs in } t, \\ TRT_{\text{proj},i,t} & \text{if treatment occurs in } t, \\ (LAG_{\text{proj},i,t} - LAG_{\text{proj},i,t-1}) + (DW_{\text{proj},i,t} - DW_{\text{proj},i,t-1}) & \text{if neither fire nor treatment occurs in } t. \end{cases} \]
Where:
\(C_{\text{project},i,t}\): Biomass change in the project scenario for composite treatment \(i\) at time \(t\), accounting for fire, treatment, or no event conditions; measured in t CO₂-e per unit area.
\(LAG_{\text{proj},i,t}\) and \(LAG_{\text{proj},i,t-1}\): Live aboveground biomass stocks in the project scenario for composite treatment \(i\) at times \(k\) and \(k+1\); measured in t CO₂-e per unit area.
\(DW_{\text{proj},i,t}\) and \(DW_{\text{proj},i,t-1}\): Deadwood biomass stocks in the project scenario for composite treatment \(i\) at times \(k\) and \(t-1\); measured in t CO₂-e per unit area.
\(CBI_b\): Composite Burn Index scaling factor for burn severity \(b\), applied only if fire occurs.
\(TRT_{\text{proj},i,t}\): Observed biomass change due to treatment activities in the project scenario for composite treatment \(i\) at time \(k\); measured in t CO₂-e per unit area. Assumes that all biomass loss from treatment is immediately released.
\[ \Delta C_{\text{project},i,t} = C_{\text{project},i,t} - C_{\text{project},i,t-1} \]
Where:
\(\Delta C_{\text{project},i,t}\): The net biomass change in the project scenario for composite treatment \(i\) at each timestep \(t\) (where \(t \leq T\)); measured in t CO₂-e per unit area. Negative values represent a biomass loss, while positive values represent a biomass gain.
\(C_{\text{project},i,t}\) and \(C_{\text{project},i,t-1}\): Biomass values for composite treatment \(i\) at times \(t\) and \(t-1\), calculated using the equation above.
\[ \Delta C_{\text{net_project},i,t} = \sum_{t=1}^{T} \Delta C_{\text{project},i,t} \]
Where:
\(\Delta C_{\text{net_project},i,t}\): The cumulative net change (loss or gain) in biomass in the project scenario for composite treatment \(i\) from the project start (t=0) up to time \(t\); measured in t CO₂-e per unit area. Negative values represent a net biomass loss, and positive values represent a net biomass gain.
\(\Delta C_{\text{project},i,t}\): Net biomass change for each timestep \(k\) in the project scenario.
\(t\): Timestep in the project period, where \(t = 1, 2, 3, \dots, T\).
To calculate the difference in biomass between the project and baseline scenarios at each timestep, where positive values indicate more carbon in the project scenario, we define:
\[ \Delta C_{\text{diff},i,t} = C_{\text{project},i,t} - C_{\text{baseline},i,t} \]
Where:
\(\Delta C_{\text{diff},i,t}\): The difference in biomass between the project and baseline scenarios for composite baseline \(i\) at time \(t\); measured in t CO₂-e per unit area. Positive values indicate more carbon in the project scenario relative to the baseline, while negative values indicate less.
\(C_{\text{project},i,t}\): Biomass in the project scenario for composite treatment \(i\) at time \(t\), calculated based on fire, treatment, or no event conditions as described in the project equation.
\(C_{\text{baseline},i,t}\): Biomass in the baseline scenario for composite baseline \(i\) at time \(t\), calculated based on fire or no fire conditions as described in the baseline equation.
This equation enables a direct comparison of carbon stocks between the project and baseline scenarios dynamically at each timestep, providing insight into the net carbon impact of the project.
This methodology addresses uncertainty by quantifying potential errors between in-situ (plot-based) and remotely sensed estimates of aboveground live biomass (AGLB). Following Verra standards, this uncertainty is accounted for in emissions reduction and removal calculations, ensuring conservative and statistically robust estimates.
Field Measurement: Live aboveground biomass (\(LAG_{\text{plot}}\)) and deadwood biomass (\(DW_{\text{plot}}\)) are measured in a representative sample of plots within the project boundary. Standard forest mensuration techniques are used, such as measuring tree diameter at breast height (DBH) and height, and applying allometric equations to estimate biomass stocks.
Carbon Fraction: A carbon fraction (e.g., 0.5) is applied to convert biomass stocks to carbon, measured in t CO₂-e per unit area.
Remote Sensing Data: High-resolution satellite or LiDAR data are used to estimate live aboveground biomass (\(LAG_{\text{remote}}\)) and deadwood biomass (\(DW_{\text{remote}}\)) across the reference region, calibrated using plot-based data to ensure comparability. The remote sensing metric must demonstrate a statistically significant correlation with in-situ measurements.
Spatial Aggregation: Biomass stocks (\(LAG_{\text{remote}}\) and \(DW_{\text{remote}}\)) are averaged across pixels in the reference region to produce a composite estimate, reflecting the mean baseline biomass stock at each timestep.
Uncertainty in Plot-Based Estimates (\(U_{\text{plot}}\)): Calculated as the standard error of the mean biomass stocks (\(LAG_{\text{plot}}\) and \(DW_{\text{plot}}\)) from plot measurements at a 90% confidence interval.
Uncertainty in Remote Sensing Estimates (\(U_{\text{remote}}\)): Derived from the calibration process and spatial variance, including error propagation from remote sensing models used to estimate \(LAG_{\text{remote}}\) and \(DW_{\text{remote}}\).
The combined uncertainty for biomass estimates in the baseline scenario is calculated as follows:
\[ U_{\text{combined}} = \sqrt{U_{\text{plot}}^2 + U_{\text{remote}}^2} \]
Where:
Uncertainty Threshold: If \(U_{\text{combined}}\) exceeds a defined threshold (e.g., 15%), a conservative adjustment factor is applied to baseline biomass stocks. This adjustment prevents overestimation in carbon credits.
Adjustment Calculation:
\[ \text{Adjusted Baseline Biomass Stock} = \text{Baseline Biomass Stock} \times (1 - U_{\text{combined}}) \]
This adjusted baseline value ensures conservative crediting by reducing biomass stocks based on the estimated uncertainty.
All sources of uncertainty are documented, including data collection, remote sensing calibration, and statistical validation processes.
Sensitivity analyses are conducted to evaluate the impact of key sources of uncertainty on baseline emissions and removal estimates.
By integrating plot-based and remote sensing data, and applying adjustments based on quantified uncertainty, this methodology ensures compliance with Verra’s standards for high-integrity emissions reductions accounting.