GHG quantification

GHG quantification [BiCRS]

General GHG quantification rules can be found in the Rainbow Standard Rules.

Calculations of GHG emissions for the baseline and project scenarios shall follow a robust, recognized method and good practice guidance. The overall methodological approach is a comparative life cycle assessment (LCA) at the project-scale, based on ISO 14064-2:2019.

BiCRS projects may be eligible for removal and avoidance Rainbow Carbon Credits. Removal and avoidance RCCs are calculated and issued according to two completely separate accounting mechanisms, described below. This conservative approach results in double counting the project's induced emissions, and avoids the need for allocation of emissions/removals.

GHG quantifications shall be completed either for each batch (batches are defined in the relevant carbon storage modules), or for each calendar year. Carbon storage module documents may provide specific requirements.

Functional unit [BiCRS]

The functional unit shall be 1 tonne of carbon storage solution (e.g. 1 tonne of biochar spread on soils, 1 tonne of biomass buried...).

The GHG quantification instructions from all other BiCRS modules used by the project must be used in conjunction with the present module in order to obtain full life-cycle GHG quantifications.

The system boundary of this quantification section starts at the arrival of biochar at the site of permanent incorporation/application (i.e. field for spreading, mixing into potting soil...) and ends at the biochar end of life, after accounting for decay and re-emission in its end use application.

The system boundary of this quantification section starts at the arrival of biochar at the site of permanent incorporation/application (i.e. field for spreading, mixing into potting soil...) and ends at the biochar end of life, after accounting for decay and re-emission in its end use application.

Quantification shall be done at a minimum for each biochar production batch, and may be done more frequently for continuous issuance.

GHG emissions covered in this module include:

• Permanent carbon storage modeling

• Production of avoided baseline scenario materials

Data sources [biomass]

The required data from all projects using biomass feedstocks are presented in Table 2.

Table 2 Summary of primary data needed from projects and their source for initial project certification and validation. Asterisks (*) indicate which data are required to be updated annually during verification (see Monitoring Plan section).

Parameter	Unit	Source
Amount of biomass used*	Tonnes of fresh matter	Primary: Internal tracking documents, invoices, contracts
Carbon content of biomass	% w/w, fraction, kg/tonne	Primary or secondary: Laboratory chemical analyses, scientific publications or local/national agriculture government agencies

Data sources [biochar]

The required primary data for GHG reduction calculations from projects are presented in Table 2. These data shall be provided for each production batch and made publicly available.

Table 2 Summary of primary data needed from projects and their source for initial project certification and validation. All primary data sources listed here are required to be monitored and updated during verification (see Monitoring Plan section).

Option 1: 100-year removals with H/C

Parameter	Unit	Source
Amount of biochar produced*	Tonnes of fresh matter	Internal tracking documents, invoices, contracts
Biochar $H/C_{\text{org}}$*	Ratio	Laboratory chemical analyses
Organic carbon content	Percent	Laboratory chemical analyses
Biochar moisture content () *	Percent	Laboratory chemical analyses
GPS coordinates of biochar spreading sites*	coordinates	Internal tracking documents, invoices, mapping software (e.g. Google Maps)
Amount and type of avoided horticultural product (optional)	kg, tonnes, m3	Operations tracking and invoices from the product user

Option 2: 1000-year removals random reflectance

The ecoinvent database version 3.12 (hereafter referred to as ecoinvent) shall be the main source of emission factors unless otherwise specified. Ecoinvent is preferred because it is traceable, reliable, and well-recognized. The ecoinvent processes selected are detailed in Appendix 1.

No other secondary data sources are used in this module.

Co-product allocation

The rules outlined at the methodology-level in the BiCRS methodology document shall be applied for allocating GHG emissions between co-products.

Assumptions [biomass]

Major assumptions in this module include:

• The permanent carbon sequestration rate in the baseline scenario is 0.5%.

Assumptions [biochar]

1. By default, biochar application to soils does not replace any product.

2. The fraction of biochar with an $R_o$ below 2% does not contribute to any permanent carbon storage. This fraction, classified as semi-inertinite rather than inertinite, likely plays a role in long-term carbon storage. However, due to limited research on its quantification, it is conservatively excluded from this analysis.

3. All biochar from the same production batch has the same characteristics (e.g. , $H/C_{\text{org}}$, $R_o$).

Baseline Scenario [biomass]

This section is only required if the feedstock's alternative use was to be left on the soil or reapplied to soils for nutrient recycling. Specifically this includes but is not limited to:

• mulching

• composting

• spreading fast-decaying cellulose-based residues (e.g. decay within 5 years)

The Baseline Scenario shall include permanent carbon storage that would have occurred anyway in the absence of the project.

Although most biomass carbon would be released before the CDR project's permanence horizon, a small fraction is stabilized permanently as soil carbon. This portion is accounted for in the Baseline Scenario and deducted from the project's carbon removal capacity.

The uncertainty around biomass carbon being 1) naturally incorporated into the soil and 2) converted to a stable carbon form is high, influenced by factors such as climate, soil type, soil health, and land use, making it hard to estimate for individual projects. Thus, it is assumed that 0.5% of the carbon in the biomass feedstock left on the soil, or reapplied to soil, will be permanently stored in soils.

Calculations- Baseline scenario

$\textbf{(Eq.1)}\ {R}_{baseline}= A_{feedstock}* C * S*-1$

Where,

• ${R}_{baseline}$ represents the permanent carbon removal in the baseline scenario in the monitoring period, in t CO$_2$eq. This value shall be applied to Equation 1 from the general BiCRS methodology to calculate total project removals.

• $A_{feedstock}$ represents the amount of biomass feedstock used in the monitoring period, in tonnes of dry matter.

• $C$ represents the concentration of carbon in the biomass feedstock, in tonnes of carbon per tonne of dry matter.

• $S$ represents the permanent sequestration rate of carbon applied to soils, which is 0.5%, as described in the Assumptions section.

• It is multiplied by -1 to obtain a negative sign. Removals are reported as a negative value in the BiCRS methodology.

Baseline scenario [biochar]

The baseline scenario for the purpose of Removal vs Avoidance RCCs issuance is detailed below.

Removal RCCs

For removal RCCs, there is no baseline from this module because it is assumed that there is no significant share of the project activity already occurring in business-as-usual. Therefore, the baseline for removal credits is zero and is omitted from calculations.

According to the Rainbow Procedures Manual, this assumption shall be re-assessed at a minimum every 3 years during the mandatory methodology revision process, and any changes to this assumption would be applied to existing projects.

Note that baseline scenario carbon sequestration may be included for the project from the biomass feedstock module.

Avoidance RCCs

Project Scenario [biomass]

Because the only biomass types allowed are waste, they are assigned no environmental impacts from their production/cultivation stage. Impacts from following stages, such as harvest, transport, and processing, shall be accounted for in the Processing and energy use module.

Project scenario [BiCRS]

Modules include specific instructions on calculating GHG emissions and removals for the relevant processes.

Each project must use at least one module from the following categories: carbon capture, transformation and carbon storage.

Calculations: Removals

$\textbf{(Eq.1)}\ Net\ Removal = R_{baseline}-R_{project}-E_{project}$

where,

• $Net\ Removal$ represents the net removals from the project during the verification period, in tonnes of CO$_2$eq. Its sign is positive.

• $R_{baseline}$ represents any baseline GHG removals from the capture module(s), representing permanent storage that would have occurred in the absence of the project, in tonnes of CO$_2$eq. Its sign is negative.

• $R_{project}$ represents the project's gross GHG removals from the storage module(s) used by the project, in tonnes of CO$_2$eq. Its sign is negative.

• $E_{project}$ represents the project's total induced GHG emissions across the project life cycle, in tonnes of CO$_2$eq. Its sign is positive.

$\textbf{(Eq.2)}\ E_{project} = {E}_{project,\ biomass} + {E}_{project,\ Transformation}+ {E}_{project,\ Storage}$

where,

• $E_{project}$ was described in Eq. 1.

• $E_{project,\ biomass}$ represents the project's GHG emissions from the capture module(s) used by the project.

• $E_{project,\ Transformation}$ represents the project's GHG emissions from the transformation module(s) used by the project.

• ${E}_{project,\ Storage}$ represents the project's GHG emissions from the storage module(s) used by the project.

Calculations - Avoidance

$\textbf{(Eq.3)}\ E_{project} = \Sigma{E}_{P,\ Capture} + \Sigma{E}_{P,\ Transformation} + \Sigma{E}_{P,\ Storage}$

where,

• $E_{project}$ represents the induced GHG emissions from the project during the verification period, in tonnes of CO$_2$eq. It does not account for any carbon removals in the storage modules.

• $E_{P,\ Capture}$, $E_{P,\ Transformation}$ and ${E}_{P, Storage}$ were described in Equation 1.

$\textbf{(Eq.4)}\ E_{baseline} = \Sigma{E}_{B,\ Capture} + \Sigma{E}_{B,\ Transformation} + \Sigma{E}_{B,\ Storage}$

where,

• $E_{baseline}$ represents the GHG emissions from the baseline scenario during the verification period, in tonnes of CO$_2$eq.

• $E_{B,\ Capture}$, $E_{B,\ Transformation}$ and ${E}_{B, Storage}$ represent GHG emissions from any baseline scenario created in the respective modules.

$\textbf{(Eq.5)}\ E_{avoided} = E_{baseline} - E_{project}$

where,

• $E_{avoided}$ represents the avoided GHG emissions from the project scenario, in tonnes of CO$_2$eq.

• $E_{baseline}$ was calculated in Equation 5.

• $E_{project}$ was calculated in Equation 3.

Project scenario [biochar]

Project Developers must choose between one of two approaches to quantify the total carbon removals from their biochar product, as described in the Durability section. A single approach must be used consistently throughout each monitoring period, though a different approach may be chosen for subsequent monitoring periods.

1. Modeling 100-year removals using bulk measurements of $H/C_{\text{org}}$, or

2. Estimating 1000-year removals using random reflectance measurements as proxies for inertinite.

Approach 1: Modeling 100-year removals with $H/C_{\text{org}}$

This approach is based on research from Woolf et al., 2021, and the IPCC modeling method. It is rooted in soil ecology and soil biochemistry disciplines. The permanent fraction of biochar carbon remaining after 100 years ( $F_{\text{perm 100}}$) is modeled according to the local average annual soil temperature.

Soil temperature shall be obtained for the location of each biochar spreading/end use event, using the GPS coordinates provided in the Verification of end use report and the global soil temperature dataset from Lembrechts et al., 2021. The Rainbow Certification Team can provide soil temperature values for Project Developers based on the provided GPS coordinates.

For verification, Project Developers shall provide primary project data in the form of laboratory measurements for $H/C_{\text{org}}$ and following the Sampling requirements.

Table 3 Soil temperature ranges are categorized and their corresponding c and m regression coefficients are presented, which are used in Eq. 1 below to calculate $F_{perm}$. Values are taken from Woolf et al., 2021.

Soil temperature (°C)	c	m
<7.49	1.13	0.46
7.5-12.49	1.10	0.59
12.5-17.49	1.04	0.64
17.5-22.49	1.01	0.65
>22.5	0.98	0.66

Calculations: 100-year removal credits with $H/C_{org}$

$\textbf{(Eq.1)}\ F_{perm\ 100} = c - m*H/C_{org}$

where,

• $F_{perm\ 100}$ represents the fraction of biochar carbon remaining after 100 years

• $c$ and $m$ represent regression coefficients, taken from Woolf et al., 2021, and summarized in Table 3 for the corresponding project's soil temperature.

• $H/C_{org}$ represents the ratio of molar hydrogen to organic carbon in biochar, measured by laboratory analysis for each project.

$\textbf{(Eq.2)}\ R_{project,\ 100}= F_{perm\ 100}*{C_{org}*A}_{biochar}*(1 - M_{\%})*C\ to\ {CO}_{2}*-1$

where,

• $R_{project,\ 100}$ represents the total carbon removals from biochar during the verification period, in tonnes of CO$_2$eq. This value shall be applied to Equation 1 from the General BiCRS methodology document to calculate total project removals.

• $F_{perm\ 100}$ is calculated in Equation 1

• $C_{org}$ represents the concentration of organic carbon in biochar, on a weight basis.

• $A_{biochar}$ represents the amount of biochar delivered during the verification period, in tonnes of fresh biochar.

• $M_{\%}$ represents the moisture content of biochar, on a weight basis (%w/w), so $1-M_{\%}$converts to dry mass of biochar

• $C\ to\ {CO}_{2}$ is 44/12 = 3.67, and represents the molar masses of CO$_2$ and C respectively, and is used to convert tonnes C to tonnes of CO$_2$eq.

• It is multiplied by -1 to obtain a negative sign. Removals are reported as a negative value in the BiCRS methodology.

Approach 2: Estimating 1000-year removals based on inertinite fraction

This approach is based on the research from Sanei et al., 2024, and is rooted in the organic petrology and geochemistry disciplines. This approach is built upon research showing that fractions of inertinite in biochar samples are:

• inert and permanent and will not re-release their carbon for at least 1000 years.

• represented by the fraction of residual (i.e. not reactive, not labile) organic carbon in the sample with a Random Reflectance ($R_o$) of 2% or higher.

For verification, Project Developers shall provide primary project data in the form of laboratory measurements for $R_o$ distribution, labile organic carbon content, and moisture content for each production batch, following the Sampling requirements.

To determine the inertinite fraction of the biochar's organic carbon, first the labile carbon fraction is measured and subtracted from total organic carbon content, and only the residual organic carbon content is considered.

Next, random reflectance measurements are used to determine the fraction of residual organic carbon that is classified as inertinite:

• The fraction of the distribution with an $R_o$ above 2% represents the fraction of the biochar carbon that is stored permanently for 1000 years.

• The fraction of the distribution with an $R_o$ below 2% represents the fraction of biochar carbon that is not permanently stored, and for which no removal RCCs are issued.

• $R_o$ distribution shall be based on at least 500 measurements, yielding a frequency distribution diagram similar to the examples in Figure 1a and 1b.

Figure 1a An example of a random reflectance frequency distribution diagram, with an analysis described below.

Example 1: This biochar sample has heterogenous quality and a wide distribution of $R_o$ measurements. The biochar sample has:

• labile organic carbon content of 5%,

• residual organic carbon content of 95%,

• mean $R_o$ of 2.12, and

• 72% of the $R_o$ measurements are above the 2% inertinite threshold.

Therefore, this biochar sample has an $F_{\text{perm\ 1000}}$ of $0.72 \times 0.95=0.684$ , so 68.4% of the organic carbon in the sample will be converted to CO$_2$eq and considered as 1000-year carbon removals. The remaining 31.6% of carbon is assumed to decompose within the 1000-year permanence horizon, and is not considered for any removal RCCs.

Figure 1b An example of a random reflectance frequency distribution diagram, with an analysis described below.

Example 2: This biochar sample has rather homogenous quality and a narrow distribution of $R_o$ measurements. The biochar sample has:

• labile organic carbon content of 1%

• residual organic carbon content of 99%

• mean $R_o$ of 2.32, and

• 95% of the $R_o$ measurements are above the 2% inertinite threshold.

Therefore, this biochar sample has an $F_{\text{perm\ 1000}}$ of $0.99*0.95=0.94$, so 94% of the organic carbon in the sample will be converted to CO$_2$eq and considered as 1000-year carbon removals. The remaining 6% of carbon is assumed to decompose within the 1000-year permanence horizon, and is not considered for any removal RCCs.

Calculations: 1000-year removal credits with random reflectance

$\textbf{(Eq.3)}\ F_{perm\ 1000} = {Sample\ fraction}_{> 2\%\ Ro} \times C_{org,\ f\ residual}$

where,

• $F_{perm\ 1000}$ represents the fraction of biochar carbon remaining after 1000 years.

• ${Sample\ fraction}_{> 2\%\ Ro}$ represents the fraction of the distribution sample that has a random reflectance ($R_O$) of 2% or higher.

• $C_{org,\ f\ residual}$ represents the fraction of the biochar organic carbon that is residual carbon, as opposed to reactive/labile organic carbon. It may be measured and reported directly, or obtained by subtracting measured reactive carbon from 100.

$\textbf{(Eq.4)}\ R_{project,\ 1000}=F_{perm\ 1000}*{C_{org}*A}_{biochar}*{(1 - M}_{\%})*C\ to\ {CO}_{2}*-1$

where,

• $R_{project,\ 1000}$ represents the total carbon removals from biochar during the verification period, in tonnes of CO$_2$eq. This value shall be applied to Equation 1 from the General BiCRS methodology document to calculate overall project removals.

• $F_{perm\ 1000}$ is calculated in Equation 3

• $C_{org}$, $A_{biochar}$, $M_{\%}$, and $C\ to\ {CO}_{2}$ are described in Equation 1.

• It is multiplied by -1 to obtain a negative sign. Removals are reported as a negative value in the BiCRS methodology.

Rainbow is actively monitoring ongoing research and seeking expert advice on the potential development of a third approach that uses $H/C_{\text{org}}$ measurements as proxies for inertinite content. For example, if the $H/C_{\text{org}}$ value is less than 0.2, it could be interpreted as indicating that 95% of the biochar is inertinite. While this simplification has been suggested by experts and holds promise, it is currently considered insufficiently rigorous due to a lack of supporting evidence and clear guidance.

Future Approach 3: Using H/C as a proxy for inertinite

Rainbow is actively monitoring ongoing research and seeking expert advice on the potential development of a third approach that uses $H/C_{org}$ measurements as proxies for inertinite content. For example, if the $H/C_{org}$ value is less than 0.2, it could be interpreted as indicating that 95% of the biochar is inertinite. While this simplification has been suggested by experts and holds promise, it is currently considered insufficiently rigorous due to a lack of supporting evidence and clear guidance.

Uncertainty assessment [biochar]

An uncertainty assessment is presented below for all aspects of GHG quantification set at the methodology level. The findings from this assessment are then applied at the project level, where project-specific GHG quantification also undergoes an uncertainty assessment.

The overall project GHG quantification uncertainty is determined by qualitatively combining both the methodology-level and project-specific uncertainties for each identified source of uncertainty.

The three assumptions presented in the Assumptions section have moderate uncertainty, but the most conservative approach is taken in the quantifications.

The baseline scenario selection (if applicable) has low uncertainty, because the specific circumstances, amount and type of baseline horticultural material avoided must be proven by the Project Developer.

The equations and models have moderate uncertainty. The model for 100-year permanence from Woolf et al., 2021 has moderate uncertainty because it is a model fitted to experimental data, which always introduces variability. The equations for 1000-year permanence from Sanei et al., 2024 have low uncertainty because they are basic conversion equations.

The uncertainty at the methodology level is estimated to be low. This translates to an expected discount factor of at least 3% for projects under this methodology.

Uncertainty assessment [biomass]

See general instructions for uncertainty assessment in the Rainbow Standard Rules. The outcome of the assessment shall be used to determine the percent of RCCs to eliminate with the discount factor.

For projects that include baseline permanent carbon storage, the assumption that 0.5% of carbon is permanently sequestered is has high uncertainty, but the total net project removals is not sensitive to this assumption. Therefore, this translates to an expected discount factor of at least 3% for projects that include baseline permanent carbon storage.