Abstract

Climate change adaptation and mitigation remain critical to achieving sustainable development while reducing climate vulnerability, particularly among climate-exposed and sensitive regions. Yet, achieving a balance between climate-resilience pathways, high economic productivity, high human development, and energy efficiency appears complex, leading to potential trade-offs. Here, we examine the overarching effect of the diversified energy portfolio, socio-economic drivers, and governance adaptation readiness on Climate change vulnerability across 212 economies. Contrary to the poor conventional panel techniques reported in the existing literature, we employ novel machine learning and dynamic panel estimation techniques that control for chaos, nonlinearity, mutual coupling, and heterogeneity in dynamic systems. The convergent cross-mapping causality technique reveals mutual coupling effects between energy portfolio, governance readiness, socio-economic drivers, and climate change vulnerability. The rapidly increasing population and increasing demand for resources under the business-as-usual society and economic structure that normalizes unsustainable development pathways due to weak governance structures create ineffective climate-resilient policies that lead to unabated emissions with consequences on climate change. The effect of social and governance readiness leads the transformation process to attain sustainable development. Thus, high social and governance readiness spurs climate resilience through climate change adaptation and mitigation to achieve sustainable development. Alternative (renewables) and nuclear energy have displacement effects on fossil fuels, yet, the magnitude of displacement is not large enough to replace future fossil fuel consumption. Conversely, a low-carbon future is still attainable by replacing the fossil energy portfolio with more natural gas and carbon-abatement technologies. Our study demonstrates that energy innovations are useful climate-resilience pathways that lessen climate change vulnerability.

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