Companies need reliable emission data for their products and services to take effective climate action, yet obtaining it is challenging. In today's interconnected economy, product and service carbon footprints (PCF) cannot be determined in isolation but require emission data exchange throughout supply chains. Typical cradle-to-gate accounting models require companies to include suppliers' PCFs as scope 3 emissions, making the trustworthiness of this externally provided data critical. This calls for effective emission data verification to prevent greenwashing and ensure consistency, but current methods face fundamental limitations: they are either non-scalable (e.g., relying on individual auditors) or require access to suppliers' confidential business information. Trust-enhancing technologies like zero-knowledge proofs (zk-SNARKs), combined with verifiable decentralized data structures, can resolve this tension by enabling verification without exposing confidential trading information. This talk introduces verifiable carbon accounting (VCA) as a framework that synthesizes multiple such technologies to enable scalable, confidentiality-preserving emission data verification. We provide an overview of recent and ongoing research, present open challenges, and discuss practical adoption strategies. While still in its infancy, VCA has the potential to transform data-driven supply chain collaboration by offering a scalable alternative to existing approaches while delivering the trustworthy emission data urgently needed to combat climate change.
*Bio*: Jonathan Heiss is a postdoctoral researcher at TU Berlin, Germany, and a senior research engineer at SINE Foundation. He earned his Ph.D. in computer science from TU Berlin in 2023 and holds two master's degrees from TU Delft (computer science) and TU Berlin (ICT Innovation), both completed in 2017. He received his bachelor's degree in information systems from TU Dresden in 2015. Jonathan's research focuses on trustworthy distributed systems engineering, with particular emphasis on incorporating trust-enhancing technologies such as zero-knowledge proofs, secure hardware, and verifiable data structures into platform-based system architectures. Target platforms include cloud systems and blockchain networks, and their synergistic combination and interplay. He employs research methods drawn from software engineering and distributed systems, including systems modeling, prototyping, and experiment- and measurement-driven approaches. Recent work applies these technologies to contexts such as decentralized federated learning and carbon accounting.
