Abstract
Although our knowledge of climate change impacts on energy systems has increased substantially over the past few decades, there remains a lack of comprehensive overview of impacts across spatial scales. Here, we analyse results of 220 studies projecting climate impacts on energy systems globally and at the regional scale. Globally, a potential increase in cooling demand and decrease in heating demand can be anticipated, in contrast to slight decreases in hydropower and thermal energy capacity. Impacts at the regional scale are more mixed and relatively uncertain across regions, but strongest impacts are reported for South Asia and Latin America. Our assessment shows that climate impacts on energy systems at regional and global scales are uncertain due partly to the wide range of methods and non-harmonized datasets used. For a comprehensive assessment of climate impacts on energy, we propose a consistent multi-model assessment framework to support regional-to-global-scale energy planning.
| Original language | English |
|---|---|
| Pages (from-to) | 794-802 |
| Journal | Nature Energy |
| Volume | 5 |
| DOIs | |
| Publication status | Published - 3 Aug 2020 |
Funding
We wish to thank the JPI Climate initiative and participating grant institutes for funding the ISIpedia project. We also thank J. Burrough for professional advice on the English of a near-final draft. E.d.C. has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 756194 (ENERGYA). J.G. is supported by a research grant from Science Foundation Ireland (SFI) and the National Natural Science Foundation of China (NSFC) under the SFI-NSFC Partnership Programme, grant no. 17/NSFC/5181. D.P.v.V., R.S. and D.E.H.J.G. are supported by the Horizon 2020 NAVIGATE project, and D.P.v.V., R.S. and D.E.H.J.G. also acknowledge support from the COMMIT and Horizon 2020 ENGAGE project. F.P. acknowledges support through the project ENGAGE funded in the framework of the Leibniz Competition (SAW-2016-PIK-1), as well as through the project CHIPS, part of AXIS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR/BMBF (DE, grant no. 01LS19XXY), AEI (ES) and ANR (FR) with cofunding by the European Union (grant no. 776608). R.S. acknowledges the financial support from the National Council for Scientific and Technological Development (CNPq), from the National Institute of Science and Technology for Climate Change Phase 2 under CNPq grant no. 465501/2014-1 and the National Coordination for High Level Education and Training (CAPES) grant no. 88887.136402/2017-00, all from Brazil. A.M. acknowledges support from the US Department of Energy, Office of Science’s Integrated Multisector Multiscale Modelling project and National Science Foundation’s Water Sustainability and Climate grant no. 1360445. This work was authored in part by the National Renewable Energy Laboratory (A.M.), operated by Alliance for Sustainable Energy, LLC, for the US Department of Energy (DOE) under Contract No. DE-AC36-08GO28308. S.F. is supported by the Environment Research and Technology Development Fund (2-1908 and 2-2002) provided by the Environmental Restoration and Conservation Agency, Japan. C.P. is supported by Korea Environment Industry & Technology Institute (KEITI) through Climate Change R&D Programme, funded by the Korea Ministry of Environment (MOE) (2018001310003).
Keywords
- Governance
- Projection and prediction
