Core Insights - The article discusses the introduction of Chat-LCA, an intelligent life cycle assessment (LCA) solution that integrates large language models (LLM) to enhance carbon accounting efficiency and accuracy in the context of China's "dual carbon" strategy [1][3]. Group 1: Technology and Innovation - Chat-LCA represents a significant advancement by integrating cutting-edge AI technologies such as retrieval-augmented generation (RAG), Text2SQL, chain of thought (CoT), and code chain (CoC) into the entire LCA process [3]. - The system automates the entire workflow from knowledge acquisition to report generation, effectively breaking down knowledge barriers and data silos [3][4]. Group 2: Performance Metrics - Chat-LCA has demonstrated high accuracy and efficiency, achieving a BERTScore of 0.85 in answering professional questions across ten industries, a Text2SQL execution accuracy of 0.9692 on real LCI databases, and a report generation accuracy of 0.9832 with a readability score of 8.42 out of 10 [4]. - The system can reduce traditional LCA analysis time from weeks to just a few hours, marking a qualitative leap in carbon accounting efficiency [4]. Group 3: Practical Applications - In practical applications, such as assessing the carbon footprint of lithium-sulfur batteries, Chat-LCA identified raw material acquisition (47.2%) and production stages (31.3%) as major carbon emission hotspots, providing targeted emission reduction suggestions like clean energy alternatives [4]. - The solution significantly lowers the technical barriers for carbon accounting and expands the applicability of LCA methods across various industrial and policy scenarios, supporting the realization of "dual carbon" goals with actionable technological and decision-making tools [4].