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Improving deep decarbonization modelling capacity for developed and developing country contexts

  • Autores: Steve Pye, Chris Bataille
  • Localización: Climate Policy, ISSN-e 1752-7457, ISSN 1752-7457, Vol. 16, Nº. 0 (Supplement 1), 2016
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • Energy models are essential for the development of national or regional deep decarbonization pathways (DDPs), providing the necessary analytical framework to systematically explore the system transitions that are required. However, this is challenging due to the long time horizon, the numerous data requirements and the need for transparent, credible approaches that can provide insights into complex transitions.

      This article explores how this challenge has been met to date, based on a review of the literature and the experiences of practitioners, drawing in particular on the Deep Decarbonization Pathways Project (DDPP), a collaborative effort by 16 national modelling teams. The article finds that there are a range of modelling approaches that have been used across different country contexts, chosen for different reasons, with recognized strengths and weaknesses. The key motivations for use of a given approach include being fit-for-purpose, having in-country capacity and the intertwined goals of transparency, communicability and policy credibility.

      From the review, a conceptual decision framework for DDP analysis is proposed. This three step process incorporates policy priorities, national characteristics and the model-agnostic principles that drive model choices, considering the needs and capabilities of developed and developing countries, and subject to data and analytical practicalities. Finally an agenda for the further development of modelling approaches is proposed, which is vital for strengthening capacity. These include a focus on model linking, incorporating behaviour and policy impacts, the flexibility to handle distinctive energy systems, incorporating wider environmental constraints and the development of entry-level tools. The latter three are critical for application in developing countries.


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