Modelling frameworks that aim to support policymakers in deriving effective measures to reduce environmental impacts should provide both: quantitative information on locally occurring consumption patterns and production systems as well as assessment of policy scenario outcomes. Regionalised models that can deliver on these aims are emerging, but are currently limited in resolution or have other restrictions. An advanced model can be achieved by exploiting the advantages and overcoming the limitations of top-down and bottom-up approaches. In this article, we describe a highly detailed, spatially-resolved modelling framework that quantifies local activities and simultaneously analyses system-wide environmental and economic effects of planned interventions. We combined an existing, highly detailed bottom-up model for Switzerland (focusing on individual households) with a macro-economic top-down approach by developing a new Swiss sub-national, multi-region input-output model. We conducted two case studies to demonstrate its abilities and to highlight its usefulness. First, production-based greenhouse gas emissions and consumption-based carbon footprints were computed for all Swiss cantons and regional differences, interdependencies as well as embodied carbon flows among regions were investigated. We find that rural cantons have higher production-based emissions per gross domestic product than more urban cantons because of different economic structures. In contrast, certain ‘city-cantons’ entail highest consumption carbon footprints per inhabitant due to high per-capita gross capital formation. Furthermore, this case study discusses the importance of providing regionalised information on effects of measures along the economic value chains. Second, a detailed scenario assuming a realistic lifestyle change for an actual household and a thorough physical retrofit of its home was set up. Regionalised environmental and economic consequences along the supply chains were evaluated. This case study exemplifies how the modelling framework can be used to inform policymakers about expected benefits and downsides of detailed scenarios and emphasises the importance of considering rebound effects.

旨在支持决策者制定有效措施以减少环境影响的建模框架应提供：关于当地消费模式和生产系统的定量信息以及政策情景结果的评估。可以实现这些目标的区域化模型正在出现，但目前分辨率有限或有其他限制。通过利用优势并克服自上而下和自下而上方法的局限性，可以实现高级模型。在本文中，我们描述了一个高度详细的、空间解析的建模框架，该框架量化了当地活动，同时分析了计划干预措施的全系统环境和经济影响。我们结合了现有的，通过开发新的瑞士次国家、多区域投入产出模型，采用自上而下的宏观经济方法为瑞士（侧重于个体家庭）构建高度详细的自下而上模型。我们进行了两个案例研究，以展示其能力并突出其实用性。首先，计算了所有瑞士州的基于生产的温室气体排放和基于消费的碳足迹，并调查了地区差异、相互依存关系以及地区之间的隐含碳流动。我们发现，由于经济结构不同，农村各州的单位国内生产总值排放量高于城市各州。相比之下，由于人均资本形成总额较高，某些“城市州”的人均消费碳足迹最高。此外，本案例研究讨论了提供有关经济价值链上措施效果的区域化信息的重要性。其次，建立了一个详细的场景，假设实际家庭的生活方式发生了现实的改变，并对其房屋进行了彻底的物理改造。评估了供应链沿线的区域化环境和经济后果。本案例研究举例说明了如何使用建模框架向决策者通报详细情景的预期收益和不利因素，并强调考虑反弹效应的重要性。评估了供应链沿线的区域化环境和经济后果。本案例研究举例说明了如何使用建模框架向决策者通报详细情景的预期收益和不利因素，并强调考虑反弹效应的重要性。评估了供应链沿线的区域化环境和经济后果。本案例研究举例说明了如何使用建模框架向决策者通报详细情景的预期收益和不利因素，并强调考虑反弹效应的重要性。