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基于系统思维和数据驱动的城市脱碳框架,用于个人,社区和城市规模的气候行动
Lily Purcell1, Joanne Mac Mahon1, Donal Daly2
1Discipline of Civil, Structural and Environmental Engineering, School of Engineering & Architecture, University College Cork, Ireland; Environmental Research Institute, University College Cork, Lee Rd, Sunday's Well, Cork T23 XE10, Ireland.
The Science of the total environment
|December 31, 2024
概括
减少温室气体 (GHG) 排放需要了解个人和集体驱动因素. 本研究将数据驱动模型整合到城市脱碳框架中,以告知气候行动和政策.
科学领域:
- 环境科学 环境科学
- 气候变化缓解缓解 气候变化缓解
- 城市规划 城市规划
背景情况:
- 人类活动是温室气体 (GHG) 排放的主要驱动因素,需要迅速减少.
- 关于排放的主要个人和集体驱动因素以及将公民行动与政策协调的知识差距存在.
- 有效的气候行动需要将自下而上的公民努力与自上而下的缓解战略相结合.
研究的目的:
- 通过系统思维制定城市脱碳框架,以支持多层次的气候行动.
- 为了证明数据驱动的,基于活动的温室气体排放模型对个人的整合到框架中.
- 确定主要的排放驱动因素及其与城市脱碳框架的相互作用.
主要方法:
- 开发了一个基于系统思维的城市脱碳框架.
- 集成了一个数据驱动的,基于活动的温室气体排放模型,用于个人.
- 通过智能手机应用程序收集了172名参与者的个人活动和生活方式数据.
主要成果:
- 确定了个人和集体温室气体排放的主要驱动因素.
- 证明了单个排放驱动因素与城市脱碳框架之间的相互作用.
- 在规模上使用单个活动数据建模温室气体排放.
结论:
- 开发的框架和综合模型可以为个人,社区和城市规模的减排努力提供信息.
- 个人数据和规模化的温室气体排放建模可以指导公民层面的行动和高级别的政策.
- 这种方法加速了社会和城市的可持续性转型.
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