The world must accelerate toward climate progress, which will require supply chain decarbonization. The message from the international community of policy makers and climate scientists is clear: More action is needed now and throughout this decade to limit global temperature rise to 1.5℃ this century.
That is the message from the International Energy Agency’s recent “Net Zero by 2050” report, as well as from the work of the Intergovernmental Panel on Climate Change (IPCC). In response to this, more companies are implementing science-based emission reduction plans.
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Pairing policy measures with market-based mechanisms provides the recipe to supercharge climate alignment. To enable this transformation, climate-related information must be compiled into actionable metrics to drive demand signals for greenhouse gas (GHG) emissions reduction at all stages of production and distribution along supply chains.
In this article, we propose a new, digitally native system for supply chain accountability. This solution would include an open-source attribution protocol and digital schema that anyone can use to trace emissions across supply chain operations, providing actionable intelligence to cut emissions at scale.
This system would draw on the principles of a distributed ledger application architecture by providing the means to attribute the source and progress of supply chain operations and associated emissions, to independent stakeholders, according to a common protocol. By doing so, this solution could enable a higher level of verifiability, transparency and fault-tolerance.
Marc Johnson, a senior associate of the Climate Intelligence Program at RMI, is working with RMI and its partner, the Energy Web Foundation, to develop a digitally-native GHG Protocol. Paolo Natali is a principal with RMI’s Climate Intelligence program. David Mann is a senior fellow at RMI.
It is reasonable to expect that corporate GHG inventories will become a requirement in U.S. Generally Accepted Accounting Principles (GAAP) and International Financial Reporting Standards (IFRS) within this decade. When that occurs, there must be a robust data standard to represent those disclosures. The U.S. Securities and Exchange Commission (SEC) is soliciting ideas on this topic, but the SEC does not plan to develop a data standard for climate-related disclosures. Rather, it will adopt one once it is proven in the market.
According to the GHG Protocol, supply chain emissions, referred to as “scope 3” emissions, are often the largest contributor to corporate carbon footprints, yet they are regularly left unmapped or roughly estimated. This is primarily because they are not defined in a way that establishes unequivocal accountability, nor are they trackable.
The current GHG Protocol scope 3 guidance would benefit from updated accounting principles that clarify responsibility, and from a system that adequately tracks GHG emissions. As it is, relationships between emissions and players within a supply chain fade in complex, multi-tiered supply chains involving the global movement of intermediary goods and services.
To address these issues we need a system that generates robust metrics and verifiable data that represent the materiality of climate risks. To fully represent the materiality of climate risks, these metrics and data must account for the embodied emissions in products moving through supply chains.
We envision a digitally native system for supply chain accountability. This solution’s open-source attribution protocol would enable anyone to define, track and trace emissions, and to report disclosures. It would also allow anyone to trade physical goods and digital attributes and their associated credit certificates (e.g., carbon offsets and insets).
It is RMI’s view that such a standard can be developed as an evolution of the existing GHG Protocol, including by enabling supply chain emissions to be defined and verified via digital attributes in addition to calculation, estimation and self-disclosure. This would be compatible with a distributed ledger or blockchain application architecture, enabling a higher level of verifiability, transparency, and fault-tolerance.
Our model calls for “digital twins” that represent the product, with emissions attached at the point of generation (when it is an actor’s direct emissions, or what their operations emit as part of making their product). As the product flows through the supply chain, we track the digital twins in parallel, before being expressed ultimately as scope 3 in the carbon accounts of the other actors in the supply chain.
The foundation of this vision is the creation of an open-source digital architecture that defines how an attribute is created, its basic format, and how it is represented in the accounts of each player along the supply chain. The unit of trade for the GHG attribute of any given product is a standard amount of avoided, embodied CO2 equivalent, where the source of the data (e.g., modeled or measured), and any verification, is included.
By incorporating digital attributes into a comprehensive standard, practitioners will be able to verify robust GHG and ESG data, while democratizing the process by lowering the reliance on centralized data service providers. Central registries may still exist for sensitive data and for products based on GHG attributes – certificates, offsets, compliance markets, and so on – but the GHG attributes themselves would enjoy distributed exchange and verification.
One way to accomplish this vision is to develop a system built on a peer-to-peer network that dynamically depicts the progress of supply chain operations, attributing and tracking the associated emissions according to a common protocol. To increase the veracity of data inputs, documentation or validation should be linked to every associated event, enabling a process tracking system that collects and stores information in a transparent manner.
For this proposed system to fulfill its function, it must accomplish two important goals. First, the system should complement the current GHG Protocol scope 3 guidance. Second, the system should be open-source and architecturally decentralized, thus enabling free use, interoperability, and future modification.