IMPACT：面向城市的自下而上温室气体排放路径集成模型
IMPACT: Integrated Bottom-Up Greenhouse Gas Emission Pathways for Cities
AI总结：
本文提出自下而上的IMPACT模型，在住宅级粒度上集成技术采纳、分区、气候变化与电网脱碳情景，揭示城市蔓延的排放溢价及不利政策组合导致的排放反弹。
摘要：
日益加剧的城市化给城市带来压力，促使其优先考虑可持续增长并避免碳锁定。现有建模框架在指导地方层面此类关键决策方面严重不足。财政激励、行为干预和行政指令推动可持续技术采纳，而土地利用分区在建成环境的碳排放中发挥关键作用。研究人员通常自上而下地在国家尺度评估政策影响，或事后针对过去不同政策下的开发项目进行评估。此类分析无法预测特定城市的排放路径，因而不能作为地方决策者的输入。在此，我们提出IMPACT路径，该路径来自具有住宅级粒度的自下而上模型，将技术采纳政策与分区政策、气候变化和电网脱碳情景相集成。以城市为分析核心，我们识别出城市蔓延带来的排放溢价，并表明存在不利的政策组合，可能随时间表现出排放反弹。
英文摘要：
Increasing urbanization puts pressure on cities to prioritize sustainable growth and avoid carbon lock-in. Available modeling frameworks fall acutely of guiding such pivotal decision-making at the local level. Financial incentives, behavioral interventions, and mandates drive sustainable technology adoption, while land-use zoning plays a critical role in carbon emissions from the built environment. Researchers typically evaluate impacts of policies top down, on a national scale, or else post-hoc on developments vis-à-vis different polices in the past. Such analyses cannot forecast emission pathways for specific cities, and hence cannot serve as input to local policymakers. Here, we present IMPACT pathways, from a bottom-up model with residence level granularity, that integrate technology adoption policies with zoning policies, climate change, and grid decarbonization scenarios. With the city at the heart of our analysis, we identify an emission premium for sprawling and show that adverse policy combinations exist that can exhibit rebounding emissions over time.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
