Using AI and Data Fusion to Determine Scope 3 Emissions

The Challenge: Uncovering obscured emissions in global supply chains

Companies are facing growing pressure from shareholders and customers to reduce their climate impact which, coupled with the rise of environmental disclosure regulations, means they need to take action soon or be left behind. Given that estimates show more than 70% of companies’ emissions are accounted for in the supply chain, it is critical to understand suppliers’ emissions in order to make tangible progress.

But in an increasingly globalized economy, supply chains are only becoming more opaque. With limited insights into their upstream suppliers, many companies struggle to understand the magnitude of their total supply chain emissions on their own. Muir AI is able to fill this gap; leveraging machine learning and satellite imagery to identify, track, and reduce emissions, Muir helps companies understand the full scope of their emissions. To demonstrate the capability of the Muir Intelligence Platform, we identified a company with a complex global supply chain, and estimated its emissions using our Carbon Origin service, without receiving any company-provided data.

The Approach: Fusing procurement data with advanced emissions and trade models

With Muir’s Carbon Origin, we identified an American sports equipment company’s (The Company) emissions for five of their product lines imported into the United States, between April 2022 - April 2023. Using only the shipping data of these products (see Figure 1), we analyzed more than 600 shipping logs, which included information on the product type, mass, and Tier 1 Supplier names. While Muir is able to ingest either public or customer-provided data, in this case, Muir exclusively leveraged publicly available shipping data to develop detailed emissions estimates.

As part of its AI Engine processing, Muir’s models factor in the specific country-level processing standards and upstream supply chain sourcing, to provide a more nuanced understanding of each product’s emissions. In addition to the estimated emissions, Carbon Origin also delivers a Carbon Impact Potential rating, a proprietary evaluation metric that identifies the relative potential to reduce carbon emissions for a specific supplier or product line, in comparison to the other products and services under evaluation.

The Results: Nuanced supply chain emissions data and insights

Muir’s Carbon Origin automatically ascertained the total emissions and the Carbon Impact Potential, by product category, supplier and shipment. After evaluating The Company’s product-level emissions, Muir found that during the time period under evaluation, footwear products accounted for the overwhelming majority of total emissions and had the highest Carbon Impact Potential. This means that there is significant potential to reduce The Company’s emissions by implementing changes in its footwear supply chain.

Muir also provided emissions for each supplier, providing a view of supplier-level upstream emissions and likely sourcing countries. This ultimately allowed Muir to determine the likely sourcing countries for each material component (see Figure 2 for an overview of the emissions for one of The Company’s specific suppliers).

The Path Forward: Utilize the Muir Intelligence Platform to understand the full scope of your emissions and take action

The use case for rapid carbon estimations is only growing. As corporations respond to heightened pressure from shareholders, consumers, and regulatory bodies, they will need a partner who can provide accurate and scalable emissions data and insights. Muir’s services can be leveraged across industries and customer types, whether you are a global corporation that does not have full visibility into your supply chain, or you are an investment firm interested in evaluating assets or companies before making an investment decision. The Muir Intelligence Platform can be leveraged across thousands of suppliers, and can support you by providing more clarity into your business operations across today’s complex global supply chains.

If you are interested in learning more and understanding the full scope of this case study, contact our Partnerships Team at info@muir.ai today.

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