用AI聊天机器人一键分析食物碳足迹，让环保决策更简单。
The Carbon Footprint Wizard: A Knowledge-Augmented AI Interface for Streamlining Food Carbon Footprint Analysis
- 结合LCA与公开数据库，用AI增强检索生成技术估算食物碳排放。
- 可交互查询复合餐食碳足迹，并与日常活动对比直观感受。
- 适合关注可持续饮食的消费者、餐饮企业及政策制定者参考。
气候变化下的环境可持续性已成为消费者、生产者和政策制定者的共同关切。碳足迹作为衡量活动对气候影响的标准指标，通常通过生命周期评估（LCA）计算。然而，复杂的全球供应链和数据碎片化使得LCA实施困难。本文提出一种融合LCA进展与公开数据库的方法，利用知识增强型AI技术（如检索增强生成）估算食品从原料到工厂门的碳足迹。我们开发了一个聊天机器人界面，支持用户交互式探索复合餐食的碳影响，并将结果与常见活动进行类比。一个实时网页演示展示了该概念验证系统的运行效果，涵盖任意食品项及后续问题，凸显了在可访问格式中提供LCA洞察的潜力与局限，如数据库不确定性及AI误读风险。
原文摘要 · Abstract (English)
Environmental sustainability, particularly in relation to climate change, is a key concern for consumers, producers, and policymakers. The carbon footprint, based on greenhouse gas emissions, is a standard metric for quantifying the contribution to climate change of activities and is often assessed using life cycle assessment (LCA). However, conducting LCA is complex due to opaque and global supply chains, as well as fragmented data. This paper presents a methodology that combines advances in LCA and publicly available databases with knowledge-augmented AI techniques, including retrieval-augmented generation, to estimate cradle-to-gate carbon footprints of food products. We introduce a chatbot interface that allows users to interactively explore the carbon impact of composite meals and relate the results to familiar activities. A live web demonstration showcases our proof-of-concept system with arbitrary food items and follow-up questions, highlighting both the potential and limitations - such as database uncertainties and AI misinterpretations - of delivering LCA insights in an accessible format.
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