0572438 - ÚVGZ 2024 RIV NL eng J - Článek v odborném periodiku
Merkle, M. - Dellaccio, O. - Dunford, R. - Harmáčková, Veronika Zuzana - Harrison, P. A. - Mercure, J.F. - Pedde, S. - Seo, B. - Simsek, Y. - Stenning, J. - Rounsevell, M.
Creating quantitative scenario projections for the UK shared socioeconomic pathways.
Climate Risk Management. Roč. 40, APR (2023), č. článku 100506. ISSN 2212-0963. E-ISSN 2212-0963
Institucionální podpora: RVO:86652079
Klíčová slova: Extended SSPs * UK Socio-economics * Quantitative Scenarios * Stakeholderbased Modelling
Obor OECD: Environmental sciences (social aspects)
Impakt faktor: 4.4, rok: 2022
Způsob publikování: Open access
https://www.sciencedirect.com/science/article/pii/S2212096323000323?via%3Dihub

The Shared Socioeconomic Pathways (SSPs) were developed as a framework for exploring alternative futures with challenges for climate change mitigation and adaptation. Whilst origi-nally developed at the global scale, the SSPs have been increasingly interpreted at the national scale in order to inform national level climate change policy and impact assessments, including mitigation and adaptation actions. Here, we present a set of quantitative SSP scenario projections, based on narratives and semi-quantitative trends, for the UK (the UK-SSPs) for a wide range of sectors that are relevant to the UK climate research, policy and business communities. We show that a mixed-methods approach that combines computational modelling with an interpretation of stakeholder storylines and empirical data is an effective way of generating a comprehensive range of quantitative indicators across sectors and geographic areas in a specific national context. The global SSP assumptions of low challenges to climate adaptation lead to similar socioeconomic outcomes in UK-SSP1 and UK-SSP5, although based on very different dynamics and underlying drivers. Convergence was also identified in indicators related to more efficient natural resource use in the scenarios with low challenges to climate change mitigation (UK-SSP1 and UK-SSP4). Alternatively, societal inequality played a strong role in scenarios with high challenges to adaptation leading to convergence in indicator trends (UK-SSP3 and UK-SSP4).
Trvalý link: https://hdl.handle.net/11104/0343472