While carbon accounting plays a fundamental role in our fight against climate change, it is not without its challenges. We begin the paper with a critique of the conventional carbon accounting practices, after which we proceed to introduce the E-liability carbon accounting methodology and Emissions Liability Management (ELM) originally proposed by Kaplan and Ramanna, highlighting their strengths. Recognizing the immense value of this novel approach for real-world carbon accounting improvement, we introduce a novel data-driven integrative framework that leverages AI and computation - the E-Liability Knowledge Graph framework - to achieve real-world implementation of the E-liability carbon accounting methodology. In addition to providing a path-to-implementation, our proposed framework brings clarity to the complex environmental interactions within supply chains, thus enabling better informed and more responsible decision-making. We analyze the implementation aspects of this framework and conclude with a discourse on the role of this AI-aided knowledge graph in ensuring the transparency and decarbonization of global supply chains.

翻译：碳核算在应对气候变化中发挥着基础性作用，但其本身也面临诸多挑战。本文首先对传统碳核算方法进行批判性评析，继而引入Kaplan与Ramanna首创的E-责任碳核算方法论及排放责任管理（ELM），重点阐释其优势。在充分认识这一创新方法对改善现实碳核算体系的重要价值后，我们提出一种新型数据驱动的集成框架——E-责任知识图谱框架——通过人工智能与计算技术实现E-责任碳核算方法论的落地应用。除提供实施路径外，该框架还能清晰呈现供应链中复杂的环境交互关系，从而支撑更明智且负责任的决策。我们分析了该框架的实施要点，并最终就这一AI辅助知识图谱在保障全球供应链透明度与去碳化进程中的作用展开讨论。