Digital Monitoring, Reporting, and Verification (MRV), or DMRV, can enhance the traditional MRV process through digital technologies. What considerations need to be made by the conformity assessment community for the use of DMRV?

Climate change is an urgent issue that demands innovative measures. The voluntary carbon market seeks to channel performance-based financing toward climate mitigation opportunities. Typically, carbon credit methodologies support projects that avoid or remove emissions.  The transition from traditional MRV to DMRV represents a significant advancement in the carbon market infrastructure. However, the realisation of the full potential of DMRV necessitates international cooperation to create a unified approach. IAF is active in this work and continues to explore the integration of artificial intelligence (AI) into conformity assessment through the work of the ACT – Use of Conformity Assessment in AI Task Force. The objective of the task force is to develop recommendations and guidelines for the use of AI in accreditation and conformity assessment processes, which can be adopted by accreditation bodies and conformity assessment bodies worldwide.   

One important step being emphasized within the DMRV landscape is the initiation of the digitisation of emission reduction quantification and data collection. These are regarded as low-barrier interventions because they can be implemented using existing technologies and without altering the project cycle. It is imperative that emission reduction methodologies are translated into digital decision-tree structures that facilitate the automated selection of applicable formulas and options. These algorithms must explicitly delineate all input data parameters, inclusive of units and frequencies, whilst concurrently ensuring the capacity to track every modification in the data to guarantee traceability.

With regard to data collection, the primary requirement is to ensure data integrity during both transmission and storage. Distributed ledger technologies have been posited as a means of facilitating tamper-proof, verifiable data transfers.

In order to facilitate the comprehensive incorporation of DMRV into accredited validation and verification, it is imperative that consideration is given to potential barriers such as:

1. Complexity. DMRV systems can be complex and may require specialized skills and continuous updates.  The verification of algorithm logic and processed data is critical and may require the establishment of specialised conformity assessment bodies with expertise in both carbon methodologies and software auditing. It is imperative that these activities align with relevant international standards.
2. Bias. The use of algorithms can inherit biases from the training data, leading to incorrect or unfair outcomes.
3. Updates to existing standards, exploration of existing standards, and supporting quality infrastructure. ISO has developed standards that help mitigate risks and maximize the rewards of AI – ISO/IEC 42001 for example.
4. Approaches to quantitative versus qualitative data. The verification of non-GHG information, such as the outcomes of stakeholder consultations and sustainable development co-benefits, poses a challenge due to its qualitative and project-specific nature. This type of information is unlikely to be fully digitised in the short term. Consequently, it is recommended that a distinction be made in the scheduling of GHG and non-GHG data verifications. This approach would facilitate the ongoing issuance of verified emission reductions while preserving the integrity of broader sustainability assessments through conventional verification cycles.

Current accreditation frameworks, including ISO/IEC 17029 and ISO 14065, which require VVBs to ensure competence resources for the conduct of validations and verifications should be evaluated for suitability in the application of programs/schemes utilizing DMRV solutions.  Further work is also recommended from experts in the quality infrastructure and conformity assessment community regarding the best conformity assessment standards and tools to be applied to address digital validation and verification processes as well as software validation. The standardization and conformity assessment community may benefit from the large amount of work that is already ongoing globally.

In conclusion, the recommendation is to provide a clear roadmap for enabling scalable and high-integrity digital MRV systems. The implementation of immediate improvements in quantification and data handling, the updating of standard requirements, and the evolution of accreditation structures is recommended. This will allow stakeholders to accelerate the digital transition while maintaining the rigor and credibility required in voluntary carbon markets.