Scope 3 emissions and double counting: Fair allocation of supply chain emissions
Supply chain emissions are key to measuring climate risk
Given that climate change is one of the biggest risks facing the real economy as well as the financial industry, there is an urgent need to measure and manage this risk.[1] For example, this risk may come from new regulation of a company’s high emission products or from shifts in end-product market demand driven by climate concerns. One way to measure this risk is the carbon (or carbon dioxide) exposure of products and their corresponding supply chains, also known as carbon risk.[2]
Scoped emissions are the standard way to measure supply chain emissions
The carbon exposure of a business entity — e.g., a corporate or a financial institution — is typically measured in three different ways.[3] Scope 1 emissions are the entity’s emissions due to its own activities, e.g., coal power plant emissions for the corresponding power producer. Scope 2 emissions are the emissions from the electricity procured by the business entity, e.g., the coal power plant emissions for the corresponding buyer of electricity. Scope 3 emissions are the emissions of the remainder of the supply chain (i.e., minus Scope 2), of both upstream and downstream activities.
Scope 3 emission measurement and management lags Scope 1 and 2 emissions
While the process of calculating Scope 1 and Scope 2 emissions is well established, the same cannot be said of Scope 3 emissions, despite multiple ongoing efforts by coalitions and industry actors as well as commercial data providers.[4] For example, as of March 2020, only 18% of the constituents of MSCI ACWI IMI reported Scope 3 emissions,[5] with considerable variability across sectors. Furthermore, the Scope 3 emissions data from commercial data providers tends to be high inconsistent, with correlations as low as 1%, which calls for not only increased transparency but also standardization.[6]
This may be due to various barriers, such as lack of transparency of supply chains, complex accounting principles, lack of direct connections with various tiers of suppliers, and low leverage to influence action.[7] Furthermore, the industry standard (i.e., the Greenhouse Gas Protocol) provides so much scope for discretion and ambiguity that the ultimate reporting, if it is there at all, can be inconsistent and misleading.[8]
Calculating Scope 3 emissions can be straightforward in presence of reliable data
In theory, it can be quite straightforward to calculate Scope 3 emissions if (a) the supply chains as well as (b) constituent Scope 1 emissions are known with certainty. This is where artificial intelligence and machine learning (i.e., AI-ML) can play a key role.
The first step is to figure out the product-level supply chains themselves, which is a hard problem to begin with, given lack of visibility into supply chains. The good news is that AI-ML techniques, combined with variety of abundant data (e.g., company reports, media, satellite, etc.), are starting to piece together supply chains.[9]
The second step is to figure out constituent Scope 1 emissions, even better product-based marginal emission factors, to assign them appropriately to different members in the supply chain. This is also a hard problem, again given lack of quality reported data. Again, AI-ML techniques can help in estimating Scope 1 emissions![10]
Emissions need to be allocated appropriately to avoid double counting in supply chain emissions
In this context, assuming 100% reliable data based on accurate mapping of supply chains and accurate measurement of constituent Scope 1 emissions, the next biggest issue is the so-called double counting.[11] Supply chains are interconnected networks, and care needs to be taken to ensure that emissions are not counted multiple times in the Scope 3 emissions of a business entity, thereby inflating the perception of its carbon risk.
Double counting is of many types, some inherent in the standard, the Greenhouse Gas Protocol
Within supply chain double counting is when the Scope 1 emission of an upstream entity is part of the Scope 3 emissions of multiple downstream entities at different levels in the supply chain. Across supply chains double counting is when the Scope 1 emission of an upstream entity is being assigned entirely to multiple immediate downstream entities that split up the use of the product from the upstream entity.
Within supply chain double counting is inherent in calculating the Scope 3 emissions of different members within a product’s supply chain because it provides an accurate estimate of supply chain carbon exposure for any member. However, across supply chain double counting, which occurs due to entanglement of supply chains, is not inherent because it can inflate supply chain carbon exposures.
Across supply chain double counting can be avoided via appropriate allocation methods
Assuming that within supply chain double counting is inherent in calculating Scope 3 emissions and across supply chain double counting is not, across supply chain double counting can be avoided by appropriate recursive allocation of the upstream and downstream Scope 1 emissions to various downstream and upstream entities, respectively, as we discuss in a recent working paper at Stanford University.[12]
However, within supply chain double counting can be problematic for financial institutions
Scope 3 emissions, as calculated above, are useful for a product-based company (e.g., Apple), to figure out the total supply chain emissions of its products, to explore where the emissions are coming from (i.e., what are the location of hotspots), and to engage with supply chain partners in a meaningful manner in reducing supply chain emissions.[13]
However, these Scope 3 emissions would be problematic for financial institutions if they finance multiple members of a supply chain.[14] Simply adding the constituent Scope 3 emissions of these members, even in a proportional manner (based on financed capital) as suggested by the Partnership for Climate Aligned Finance,[15] could result in significantly inflating carbon risk exposures of financial portfolios.
Fair allocation of supply chain emissions may be more useful for assessing carbon risk in financial portfolios
In this context, it may be appropriate to focus on allocation of total supply chain emissions to various members in the supply chain, while avoiding double counting of any kind — i.e., both within and across supply chain. That is, total supply chain emissions would be allocated to members such as any unit of emission is allocated to only one member, while ensuring that this allocation is fair. This would then allow for appropriate measurement of carbon risk at the level of financial portfolios.
The basic idea behind fair allocation is to start with the total supply chain emissions — i.e., the sum of all Scope 1 emissions in the supply chain — and to allocate them across the members in the supply chain such that no member is allocated emissions that are larger than emissions that they are directly or indirectly responsible for. This would enable comparisons across members, allow tracking of how each member reduces emissions that it is responsible for, and enable further development of mechanisms for optimal reductions in emissions.
Game theory techniques provides elegant solutions to the problem of fair allocation in a product’s supply chain, via the so-called Shapley Value allocation, where the Scope 1 emissions of a member are equally divided among all members deemed responsible for these Scope 1 emissions.[16] In the simplest form, this responsibility could be allocated equally across buyers and sellers.[17] This allocation is not only fair but also allows for efficient management of emission reductions by so-called carbon leaders, such as Apple, Microsoft, and Google, who take responsibility for supply chain emissions.
This suggests that various industry protocols, such as the Greenhouse Gas Protocol and the Partnership for Climate Aligned Finance, should consider supporting fair allocation methods for assessment of supply chain carbon risk, at least for financial institutions, but also for carbon leaders.
[1] TCFD, 2017. Recommendations of the Task Force on Climate-related Financial Disclosures. Available at FINAL-2017-TCFD-Report-11052018.pdf (bbhub.io)
[2] Economist, 2020. Making Sense of Banks’ Climate Targets. December 10. Available at Making sense of banks’ climate targets | The Economist
[3] WRI, 2017. Methodology. Available at Methodology | World Resources Institute (wri.org)
[4] Busch T, Johnson M, Pioch T, Kopp M, 2018. Consistency of Corporate Carbon Emissions Data. University of Hamburg Working Paper.
[5] Baker B, 2020. Scope 3 Carbon Emissions: Seeing the Full Picture. Available at https://www.msci.com/www/blog-posts/scope-3-carbon-emissions-seeing/02092372761
[6] Busch et al, 2018. Ibid.
[7] BSR, 2020. Climate Action in the Value Chain: Reducing Scope 3 Emissions and Achieving Science-Based Targets. Available at https://www.bsr.org/en/our-insights/report-view/scope-3-emissions-science-based-targets-climate-action-value-chain
[8] Fickling D, He E, 2020. The Biggest Polluters Are Hiding in Plain Sight. Available at https://www.bloomberg.com/graphics/2020-opinion-climate-global-biggest-polluters-scope-3-emissions-disclosures/
[9] Wichmann et al, 2020. Extracting Supply Chain Maps from News Articles using Deep Neural Networks. International Journal of Production Research, 58: 1–17.
[10] SBTi, 2018. Best Practices in Scope 3 Greenhouse Gas Management. Available at https://sciencebasedtargets.org/wp-content/uploads/2018/12/SBT_Value_Chain_Report-1.pdf
[11] PCAF, 2020. Public Consultation of the draft Global Carbon Accounting Standard for the Financial Industry. Available at https://carbonaccountingfinancials.com/consultation-signup
[12] Shrimali, 2021. Scope 3 Emissions: Measurement and Management. Stanford University Working paper. Available at Working Paper | Scope 3 Emissions: Measurement and Management | Energy (stanford.edu)
[13] BSR, 2020. Ibid.
[14] See Liebreich: Climate and Finance — Lessons from a Time Machine | BloombergNEF (bnef.com)
[15] PCAF, 2020. Ibid.
[16] Gopalakrishnan S, Granot D, Granot F, Sosic G, Cui H, 2020. Incentives and Emission Responsibility Allocation in Supply Chains. Management Science.
[17] US, 2020. Dealing with Scope 3. Available at https://isa.org.usyd.edu.au/research/InformationSheets/ISATBLInfo17_new.pdf
