Hybrid-Path Methodology

The ability to identify and target investment for scope 3 emissions reductions has not been easy. In fact, most companies have made little progress to date, due to the high costs of monitoring and verifying largely untraceable, and theoretically infinite, scope 3 emissions. TASA’s Hybrid-Path provides unprecedented visibility into the emissions structure of unique supply chains, helping companies transition away from highly aggregated and averaged emissions approaches, which are largely incomparable and unacceptable for decision-making, to multi-tier and multi-regional estimates incorporating company-provided and unit-process data. 

Scope 3 GHG accounting is fraught with methodological challenges, leading to wildly varying results across similar value chains and making it nearly impossible to compare the reported values of one company to the next. This poses significant difficulties for investors, sourcing managers, and other stakeholders seeking to mitigate climate risks within their spheres of influence. The use of EEIO inventories in spend-based approaches to scope 3 accounting is often criticized for being incomparable across suppliers or mitigation technologies, leading to the common refrain that “the only way to reduce emissions is to spend less”. But the problem isn’t with spend, it is the highly aggregated and blunt application of a single, average, emissions factor. Comparing ”average” to “average” of anything is still “average”. 

TASA Hybrid-Path analytics start with the disaggregated supply chain emissions structures created by TASA-EFX rLCA models and targets, for replacement, any of the over 130,000 nodes within that structure where emissions are generated (as well as the input paths behind them). Exchanging these average nodes and paths with data specific to your unique supply chains allows you to quickly quantify the impact of not just spending less, but also spending better.he ability to identify and target investment for scope 3 emissions reductions has not been easy. In fact, most companies have made little progress to date, due to the high costs of monitoring and verifying largely untraceable, and theoretically infinite, scope 3 emissions. TASA’s Hybrid-Path provides unprecedented visibility into the emissions structure of unique supply chains, helping companies transition away from highly aggregated and averaged emissions approaches, which are largely incomparable and unacceptable for decision-making, to multi-tier and multi-regional estimates incorporating company-provided and unit-process data. 

Based on the unique structure of monetary Leontief input-output systems, and the assumption that input-output, process-based, and activity-based node-path structures are theoretically equivalent, it is possible to establish concordance between inventory approaches. And, as a result, it is also possible to substitute, or exchange, average and aggregated top-down input-output inventories with more precise, bottom-up process data and company-reported data. 

TASA’s Hybrid-Path analytics allows for an assessment of specific products, differentiated by the technologies and processes adopted by unique supply chains while maintaining the system boundary completeness of the EEIO sector class. This approach also avoids double-counting, reduces widespread system disturbance, and increases its application by limiting the requirement for external information.

TASA scientists and leading scientists around the world have published extensively on the methodological development and application of hybrid and streamlined LCAs. But, until recently, these approaches have largely remained in theory and on the pages of academic papers. TASA’s Hybrid-Path analytics puts these tools into practice.

Hybrid-Path produces actionable insights into the differences between comparable product and activity systems in terms of both overall emissions and the emissions structure behind the footprint. Typical“spend-based” approaches to scope 3 footprinting often rely on a single EEIO model (e.g., US EPA’s USEEIO, EXIOBASE, Defra, etc.) to establish emissions factors for purchased goods, services, or capital inputs. As such, goods or services produced under different technological and organizational supply chain conditions are often characterized by the average industry sector to which the products are reported. Thus, the footprint calculated is the same for both products, where spending less is the only way toward reductions.

By contrast, Hybrid-Path provides increasingly comparable estimates of both emissions intensity and emissions structure. Through the customization of nodes and paths, unique foreground data for the processes, products, facilities, and organizational characteristics of each supply chain are reflected. These digital twins of specific supply chain networks replicate the emissions embodied in current products or services, or and can quantify changes to the system associated with the future adoption of new technologies or process improvements.