Enhancing ambition levels in nationally determined contributions—Learning from Technology Needs Assessments,Wiley Interdisciplinary Reviews: Energy and Environment

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Enhancing ambition levels in nationally determined contributions—Learning from Technology Needs Assessments
Wiley Interdisciplinary Reviews: Energy and Environment ( IF 5.4 ) Pub Date : 2018-06-27 , DOI: 10.1002/wene.311
Erwin Hofman ₁ , Wytze van der Gaast ₁

Affiliation

Under the Paris Agreement, countries are to develop nationally determined contributions (NDCs) every 5 years, outlining their climate targets and plans. In order to ease this task, countries may use the experiences with the Technology Needs Assessment (TNA) program. In this paper, lessons with TNAs since 2001 are described, and it is analyzed how countries, with a focus on developing countries, may use these lessons in strengthening and implementing their successive NDCs. While some developing countries have already used the results of their TNA process in their NDC development, countries could benefit from following the TNA process, its stakeholder involvement, and the multi‐criteria decision analysis (MCDA) methodology, to strengthen their NDCs. Countries face challenges in their NDC with regard to the embedding of the contribution into the national development strategy, getting from plans to implementation, and the mobilization of finance. Through the positive and negative experiences with TNAs, countries can overcome these challenges. It is argued that all countries can use the TNA or parts thereof in their NDC process. For developing countries (mainly Least Developed Countries and Small Island Developing States) the TNA is useful for capacity building, strategy development, and the preparation of projects for investment with international support. Emerging markets and newly‐industrialized countries can use the TNA as a participatory approach for strategy development. Developed countries generally do not need the entire TNA process, but the participatory approaches and MCDA can be used to fine‐tune modeled strategies.

更新日期：2018-06-27

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