CO₂RE Evaluation Framework

CDR system boundaries

Appropriate causal, spatial, and temporal system boundaries are required for credible CDR evaluation. Boundaries must include all direct and indirect emissions and removals caused by the deployment of the CDR. Direct emissions and removals occur in the stages in which CO₂ emissions from the atmosphere are captured, the stages in which captured CO₂ is stored, and all processes connecting the capture and storage of CO₂.  

Indirect emissions and removals could be market-mediated material or energy displacements (e.g. displacement of renewable energy from heat decarbonisation to removals by DACCS potentially causing greater GHG emissions overall than removals by DACCS). Indirect impacts also include effects induced by co-production of other useful products alongside GHG removal (e.g. energy generation by BECCS projects).    

It is rare that one project or company controls the full supply chain of a CDR. However, regardless of ownership, the full supply chain of each CDR must be considered to enable consistent assessment of all CDRs on the same basis.    

A coherent CDR evaluation needs to consider all changes caused by the deployment of the CDR within a relevant timeframe to climate change. The temporal boundaries need to be set to a minimum of 100 years for land-based removals utilised to offset land-based GHG emissions, and to a minimum of 1,000 years for offsetting fossil GHG emissions.    

To evaluate the completeness of the boundary definition reported by each CDR project, we propose using a scale 1 to 5 (shown in the table above), with 1 representing incomplete or partial boundaries, and 5 representing complete representation of the CDR option, including its interactions with the wider system and specification of the assessment period. A higher score indicates a more credible removal estimate.  

Counterfactuals

Counterfactual captures what would occur in absence of a CDR project. The counterfactual scenario should be assessed on the same system boundaries and with the same accounting rules as the CDR deployment scenario. The counterfactual should also consider the same key emission and removal drivers over the assessment period as the CDR deployment scenario. This means that every emission sink and source category is included in the two scenarios, albeit under different circumstances, i.e. with and without deployment of the CDR option. The drivers should include both policy drivers, such as implemented or adopted policies, as well as non-policy drivers, such as economic conditions, energy prices, and technological development. If more than one set of drivers can be demonstrated as plausible, both should be considered, resulting in two or more counterfactuals.     

Note that if the CDR project delivers co-products, the delivery of these in the same amount should be also included in the counterfactual, although delivered by alternative processes. Continuing with the BECCS example in ‘Additionality’, if the BECCS project produces energy as well as it delivers removals, then the counterfactual should include the production of this energy by an alternative source.   

Evaluation of robustness of counterfactual(s) definition 

We propose assessing the accuracy of the counterfactual definition on a five-point scale, shown in the table above, with 1 representing no definition of the counterfactual and 5 representing a well-evidenced counterfactual, covering the complete system boundaries, accounting methods, and key drivers.  A high score in this case means that the counterfactual is robustly defined, hence the CDR case can be compared like-to-like against the counterfactual, to inform the real benefits and impacts from deploying the CDR option. For instance, the difference between the removals in the counterfactuals vs the CDR deployment scenarios will better characterise the uncertainty range around the size of removal delivered by a specific CDR option.    

Once a score is estimated, users should strive for improving it as much as possible by using the guidelines set by the GHG Protocol Policy and Action Standard.  

Natural resource use: Land use and water use

To appraise land-use impacts, we use a range of methods including local data collection and environmental modelling.  This requires location, state and time-specific data and methods. For example, soil erosion risk could be assessed based on agricultural practices for bioenergy crops or tree-planting, incorporating site-specific data on soil type and precipitation. Even more detail may be considered in biodiversity assessments, where different land-uses and management intensities affect ecological functioning relative to an intact ecosystem.   

Where possible, this site-specific detail on land-use and environmental impacts is also extended across the entire supply chain, in addition to the main on-site CDR assessment. This requires as much specificity in the life cycle inventory as possible.    

 Land use  

The amount of land and the type of land required for a CDR project should be reported. If the project is assumed to scale-up in the future, then the amount of additional land needed to enable the larger project should also be considered.    

Usually, the amount of land is reported as a generic total area footprint. 

We recommend a more detailed land reporting, including: 

1. 1. Location of the land-use as it determines other impacts resulting from land-use and land-use change;  
   2. The type of land used or converted as it has important consequences for the environmental impacts and for the type of farms and farmers that could be affected, e.g.  a CDR could be deployed on ‘marginal’ agricultural land vs prime agricultural land; 
   3. CDR land management, to highlight where practices can be integrated with other land-uses, e.g. agriculture or ecosystem protection/recovery and the co-benefits provided.    

Water use  

Water use by CDR considers water usage in the area in which the CDR methods are directly applied, and the water embedded or utilised in ‘upstream’ areas required to produce inputs to CDR, e.g. the water utilised in a nursery for tree saplings. To reflect the impact of water usage onto the local water availability, LCA best practice recommends applying a water scarcity weighting onto the amount of water consumed. The weighting factor accounts for variation in water availability across different locations.  

Biodiversity change 

To quantify biodiversity change, we need to anticipate (and, ideally, eventually measure) how species diversity and abundance changes in response to CDR deployment. Measuring biodiversity is not straightforward.  Biodiversity indicators could include a range of simpler metrics monitoring the diversity of life, from genetic diversity within individual species, to changes in population size and ecosystem species composition. There are also ongoing attempts to develop indicators that link biodiversity change and ecosystem health to ecosystem functioning, i.e. provision of ecosystem services such as pollination.   

LCA methods typically report impacts on biodiversity as the ‘Potentially Disappeared Fraction’, determined primarily by land conversion and usage, with more recent versions including type of land use and its intensity.  In some cases, climate change and ecotoxicological impacts from greenhouse gases and other emissions are included. Where there are more specific regional or national scale biodiversity concerns, or particular risks associated with a given CDR, more specific biodiversity indicators and modelling may be useful or even legislatively required.  

The most robust approach is to combine biodiversity indicators and/or modelling approaches with on-the-ground monitoring of biodiversity. Ideally, species diversity and abundance would be measured before the project started and monitored over time. With further development, this approach can be complemented with indicators of ecosystem functioning, i.e. translating biodiversity change to ecological stability and resilience which can affect the long-term store of carbon. 

Water, air and soil quality 

As an initial approach to generating water, air, and soil indicators, we recommend using LCA characterisation factors to determine the eventual impacts of fertilizer loss on air or water quality. These can be developed with more detailed and location-specific environmental modelling, considering as well how land is managed, e.g., erosion risk based on soil type and field operations.  Considering land management may also reveal co- benefits. For example, increasing soil carbon may also enhance soil stability and reduce nutrient losses.   

We identified a long list of potential indicators for the ‘social’ dimension, from various bodies of literature on different types of technologies and organisations. From the long list, we selected indicators applicable to CDRs and simplified the indicators into a questionnaire, comprising 12 ‘yes/no’ questions relating to social readiness factors, and 5 multiple choice questions relating to socio-cultural worldviews. The questions enable identification of areas in which a project might encounter social risks and enable better alignment of CDR approaches with preferred implementation contexts. For each of the 17 questions, we also include open-ended questions to ‘please explain the reasons for your choice’. These are intended to enable respondents to consider in more depth the ways in which a project or proposal might encounter social risks, to assist with their planning.  

It is important that the answers to these questions are supported by robust evidence, and ideally by empirical data on the specific project or proposal, conducted by social science experts. Therefore, for each of the 17 questions, proposals score an ‘X’ if no data is available. A large number of ‘X’ scores shows that social considerations are under-considered by this project, and action must be taken to support the evidence base and to identify societal risks.  

The questionnaire, linked below, is designed to enable identification of areas in which a project might encounter such risks, so that innovators can take action. 

Public perceptions questionnaire

Energy footprint 

We recommend using a unified unit of MJ energy/t CO₂ removed to enable cross-CDR comparison. 

The energy footprint should include all relevant energy consumption and production processes, e.g. 

• • BECCS: energy consumption in farming and forestry activities, biomass feedstock preparation (e.g., pelleting and drying) and transport; CO2 capture, compression, and transport to storage + energy production;  

• • Enhanced Rock Weathering: energy consumption for rock crushing and transport, spreading on soil.  

• • DACCS: energy consumption for CO2 capture, compression, and transport to storage.  

• • Biochar: energy consumption in farming and forestry activities, biomass feedstock preparation (e.g., pelleting and drying) and transport to pyrolysis plant, application of biochar to soil + energy production in pyrolysis. 

Critical materials footprint 

We recommend using a unified unit of kg critical material/t CO₂ removed to enable cross-CDR comparison. 

Infrastructure requirements 

To enable faster CDR scale-up we recommend a statement on infrastructure requirements and expectations that indicates how contingent the CDR is on certain infrastructure assumptions. It is important to state whether new infrastructure needs include processes or materials considered hard-to-decarbonise, to avoid making climate mitigation harder. 

Economic costs 

The cost of CDR removal can be estimated by considering costs associated with the full life cycle of delivering that removal, as described in the Removal dimension. The economic costs of removal should be sustainable over time, e.g. the CDR supply chain should become self-sustaining in economic terms, lessening the costs on the wider system. The economic costs of the CDR include expenditures on e.g. energy, infrastructure, labour- costs. 

A good indicator of the removal cost is the annual capital and operating expenses. To allow for a consistent comparison across different CDR projects, these costs should be normalised on the net amount of CO₂ removed, estimated as described in the ‘Net GHG flux’ indicator in the GHG Removal dimension. 

To evaluate the application and the extent of regulatory control and support with respect to a given CDR project’s component activities, we recommend taking a ‘stepwise approach.’

The UNFCCC¹ lays out five principles of MRV specifically for carbon removal. We suggest applying the UNFCCC’s five principles for GHG emissions reporting across all of the evaluation indicators (environmental and social in addition to GHG emissions estimations). These principles are: 

• Transparency: Refers to maintaining transparent data, methods and reporting. 
• Accuracy: Refers to use of the best available methods and data and to estimate uncertainty, but noting the need to consider capabilities, capacity and pragmatism.  
• Consistency: Refers to using the same datasets and methodologies to estimate emissions and removals from sources and sinks.
• Completeness: Refers to including, as far as possible, all fluxes, pools and stores. For the CO2RE framework, completeness may extend to apply to the sustainability dimensions beyond GHG Removal.  
• Comparability: Refers to the time series of reporting. This can also capture a degree of standardisation to enable cross-national or cross-project comparison.  

The summary table describes the five-point scale on which MRV can be evaluated.

1 Measurement, reporting and verification (MRV) and accounting for carbon dioxide removal (CDR) in the context of both project-based approaches and national greenhouse gas inventories (NGHGI). IEAGHG, 2024.  

At the firm level, we propose three questions, which assess the clarity of the revenue model, the connection between the revenue model and co-benefits, and the identification of revenue risks related to the proposal. These questions are: 

1. How clear is the revenue model for the project?
2. Are any of the co-benefits identified under environmental indicators being translated into revenue streams now? If yes, please specify. 
3. To what extent have risks to revenue been considered?
   1. Not at all.
   2. Somewhat (e.g.for some revenue sources).
   3. In detail (e.g.for multiple revenue sources).

A key area for further development in the coming years is considering  the business model at the network level, as projects and technologies become more advanced. Additional indicators could include questions that capture the extent to which proposals are actively including collaborations or activities that will later support technologies to scale. 

Using the above questions and the summary table, it is possible to evaluate a CDR’s business model, with 1 meaning there is very low confidence in the business model and 5 meaning the business model is very strong. The table characterises how clear the value proposition of a proposal is, and whether the revenue model, non-revenue benefits and revenue risks are fully understood. 

Coming soon.