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Challenges resulting from urban density and climate change for the EU energy transition


Dense urban morphologies further amplify extreme climate events due to the urban heat island phenomenon, rendering cities more vulnerable to extreme climate events. Here we develop a modelling framework using multi-scale climate and energy system models to assess the compound impact of future climate variations and urban densification on renewable energy integration for 18 European cities. We observe a marked change in wind speed and temperature due to the aforementioned compound impact, resulting in a notable increase in both peak and annual energy demand. Therefore, an additional cost of 20‒60% will be needed during the energy transition (without technology innovation in building) to guarantee climate resilience. Failure to consider extreme climate events will lower power supply reliability by up to 30%. Energy infrastructure in dense urban areas of southern Europe is more vulnerable to the compound impact, necessitating flexibility improvements at the design phase when improving renewable penetration levels.

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Fig. 1: A graphical overview of the model.
Fig. 2: Impact of future climate variations.
Fig. 3: The impact of climate change on heating and cooling demand.
Fig. 4: The Impact of urban climate.
Fig. 5: Impact of urban climate on peak and average energy demand.
Fig. 6: Impact of the UMM on energy demand in extreme scenarios.
Fig. 7: The energy system assessment.
Fig. 8: The compound impact of climate change and urbanization.

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Data availability

The data generated or analysed during this study are included in the published article and its Supplementary Information. The raw climate data are available through the Coordinated Regional Climate Downscaling Experiment ( For each of the building simulation models created, specific physical properties (U values for roof, walls, windows and ground surfaces, and solar heat gain coefficients) for the building envelopes were extracted from the TABULA database ( data relevant to the energy and climate models not found in Supplementary Notes13 are available from the corresponding author upon reasonable request. Data used for Fig. 2 are available at Source data are provided with this paper.

Code availability

The computational code is not publicly available due to intellectual property and patenting process but is available from the corresponding author for academic purposes upon reasonable request.


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The research presented in this paper is a contribution to the strategic research area Modelling the Regional and Global Earth system, MERGE. V.M.N. is supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement for the COLLECTiEF (Collective Intelligence for Energy Flexibility) project (101033683) (V.M.N.) and the joint programming initiative ‘ERA-Net Smart Energy Systems’ with support from the European Union’s Horizon 2020 research and innovation programme under grant agreement for the Flexi-Sync project (775970) (V.M.N.). Support from the Centre for Innovation Research at Lund University (CIRCLE), Sweden’s innovation agency (VINNOVA - MIRAI) and The Crafoord Foundation to V.M.N. are acknowledged.

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Authors and Affiliations



A.T.D.P.: conceptualization, methodology, formal analysis for climate and energy systems, and writing. K.J.: methodology, formal analysis for climate, energy demand, urban climate and microclimate, and writing. D.M.: conceptualization, formal analysis for urban climate and energy demand, and writing—original draft. V.M.N.: methodology, formal analysis for climate, and writing. P.F.: methodology, formal analysis for urban data and writing. T.H.: writing/reviewing. D.C.: conceptualization, methodology and writing/reviewing.

Corresponding author

Correspondence to A. T. D. Perera.

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Nature Energy thanks Mingxing Chen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Information

Figures, tables and discussion.

Source data

Source Data Fig. 3

Energy demand data.

Source Data Fig. 4

Temperature and wind speed data.

Source Data Fig. 5

Energy demand data.

Source Data Fig. 6

Energy demand data.

Source Data Fig. 7

Pareto points.

Source Data Fig. 8

Pareto points, population data and performance gaps.

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Perera, A.T.D., Javanroodi, K., Mauree, D. et al. Challenges resulting from urban density and climate change for the EU energy transition. Nat Energy 8, 397–412 (2023).

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