Research Information System
Sustainable Futures, vol.11, 2026 (ESCI, Scopus)
Nuclear energy is considered a potential alternative for reducing energy dependence and environmental pollution. Furthermore, advances in artificial intelligence technologies stand out for their capacity to support the energy sector and have the potential to provide mutual benefits when integrated with nuclear energy. In this context, the study examines the effects of nuclear energy, artificial intelligence, the strictness of environmental policies, economic growth, and population density on the ecological footprint in countries with the highest nuclear energy consumption between 2007 and 2022. It also focuses on the role of artificial intelligence in nuclear energy interactions and on the effects of nuclear energy and of environmental policy stringency on environmental sustainability. The study employs second-generation panel methods that account for cross-sectional dependence and heterogeneity, quantile-on-quantile ARDL and quantile-on-quantile Granger causality approaches to reveal country-level relationships, and variance decomposition analysis to assess dynamic effects. Panel-level results show that economic growth, population, and artificial intelligence increase the ecological footprint, whereas nuclear energy and strict environmental policy reduce environmental pressures. Furthermore, the interaction terms between artificial intelligence and nuclear energy, and between artificial intelligence and environmental policy stringency, reduce the ecological footprint. However, quantile-based findings show that the effects of artificial intelligence, nuclear energy, and environmental policy stringency are heterogeneous and asymmetric across countries, with rebound effects and the green paradox emerging in some countries. Variance decomposition results show that nuclear energy and environmental policy strictness are more decisive in improving environmental quality in the long term, while AI-induced environmental pressure decreases over time.