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Climate change experiences raise environmental concerns and promote Green voting

Abstract

Public support is fundamental in scaling up actions to limit global warming. Here, we analyse how the experience of climate extremes influences people’s environmental attitudes and willingness to vote for Green parties in Europe. To this end, we combined high-resolution climatological data with regionally aggregated, harmonized Eurobarometer data (34 countries) and European Parliamentary electoral data (28 countries). Our findings show a significant and sizeable effect of temperature anomalies, heat episodes and dry spells on environmental concern and voting for Green parties. The magnitude of the climate effect differs substantially across European regions. It is stronger in regions with a cooler Continental or temperate Atlantic climate and weaker in regions with a warmer Mediterranean climate. The relationships are moderated by regional income level suggesting that climate change experiences increase public support for climate action but only under favourable economic conditions. The findings have important implications for the current efforts to promote climate action in line with the Paris Agreement.

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Fig. 1: Trends and patterns in environmental concerns and Green voting across Europe.
Fig. 2: Effects of climate extremes on environmental concern and Green voting by region.
Fig. 3: Estimated marginal effects of temperature anomalies conditional on regional climate and economic conditions.

Data availability

The regional data generated and analysed in the current study are available at the Harvard Dataverse repository at https://doi.org/10.7910/DVN/D2STBL.

Code availability

The data analysis was carried out in R. The scripts that generate and visualize the results reported in this study are available at the Harvard Dataverse repository at https://doi.org/10.7910/DVN/D2STBL (all packages used are acknowledged and cited in the source code file).

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Acknowledgements

We are grateful to D. Raimondo, M. Cuneo, L. Vicari., G. Vicidomini and M. Lo Faso for valuable assistance in the collection and preparation of the voting data. R.H. and R.M. gratefully acknowledge funding from IIASA and the National Member Organizations that support the institute. R.H. acknowledges funding from the EPICC (East Africa, Peru, India, Climate Capacities) project which is part of the International Climate Initiative (IKI). The German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) supports this initiative on the basis of a decision adopted by the German parliament. J.P. gratefully acknowledges funding from the Vienna Institute of Demography/Austrian Academy of Sciences.

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Authors and Affiliations

Authors

Contributions

R.M., R.H., P.S. and J.P. conceived the project, designed the research and collected and reviewed relevant literature. J.P., P.S. and R.H collected and processed the data. J.P. and R.H. analysed the data. R.M. and P.S. provided support with statistical techniques and procedures. R.H., J.P., R.M. and P.S. interpreted the results and wrote the manuscript. The authors are listed in alphabetical order.

Corresponding authors

Correspondence to Roman Hoffmann, Raya Muttarak, Jonas Peisker or Piero Stanig.

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The authors declare no competing interests.

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Nature Climate Change thanks Elke Weber and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Hypothetical relationship patterns reflecting different effects of positive and negative temperature extremes on concerns and voting.

a) The linear pattern implies a strictly positive effect of positive and a negative effect of negative anomalies, suggesting that cold episodes – unlike heat episodes – reduce concerns and Green vote. b) The v-shaped pattern suggests a positive effect of both positive and negative anomalies. c) This pattern implies a positive effect of positive anomalies but no effect of negative anomalies or cold episodes. Anomalies are illustrated here as deviations from the long-term mean (vertical dotted line). The illustration is based on Fig. 1 in Brooks et al., Rev. Policy Res. 31, 199–217 (2014) 20.

Extended Data Fig. 2 Classification of regions in Europe in different climate zones based on the Köppen-Geiger classification.

Panel a) shows the Köppen-Geiger climate classification plotted at 0.083 ° resolution based on Beck et al., Sci. Data 5, 1–12 (2018) 62. Panel b) shows the classifications of regions in three climate zones with a hot (Bwh, Bwk, Bsh, Bsk, Csa, Csb), temperate (Cfa, Cfb, Cfc) or cold (Dsa, Dsb, Dsc, Dfa, Dfb, Dfc, ET, EF) climate.

Extended Data Fig. 3 Effects of heat and cold-related climate extremes on environmental concern and Green voting by climate zones.

Coefficients are standardized using the observed variance of the variables in the given climate type after applying the fixed effects. Lines around the point estimates show the 95% confidence intervals. Estimates are based on interaction models displayed in Supplementary Table 26.

Supplementary information

Supplementary Information

Supplementary text A–D, Figs. 1–4 and Tables 1–30.

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Hoffmann, R., Muttarak, R., Peisker, J. et al. Climate change experiences raise environmental concerns and promote Green voting. Nat. Clim. Chang. 12, 148–155 (2022). https://doi.org/10.1038/s41558-021-01263-8

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