Role of energy mix and eco-innovation in achieving environmental sustainability in the USA using the dynamic ARDL approach: Accounting the supply side of the ecosystem

Abstract

The United Nations Framework Convention on Climate Change (UNFCCC) partners agreed with a landmark decision on environmental concerns at the COP26 in Glasgow, outlining future attempts and measures to ensure a secure environment. In this regard, several prior studies have looked at environmental issues using carbon dioxide emissions, or ecological footprint. However, considering these variables may cause the supply side of environmental quality to be overlooked. To make up for this shortcoming, this study examines the effect of energy mix (fossil fuels, nuclear, and renewables), economic growth, and eco-innovation on the load capacity factor, which emphasizes both the demand and supply side of the ecosystem since it takes biocapacity and ecological footprint into account. Hence, this study differs from previous research in that it takes a broader view of environmental sustainability. In this milieu, the current research employs a recently developed dynamic autoregressive distributed lag (DARDL) simulation model for the United States of America (USA), harnessing data from 1990 to 2018. The findings unveil that nuclear and renewable energy consumption and eco-innovation all positively impress the load capacity factor, meaning that these variables help the USA maintain its environmental sustainability. On the other side, fossil fuel usage and economic expansion curbs environmental sustainability. Furthermore, since the short-run income elasticity is larger than the long-run elasticity, the environmental Kuznets curve hypothesis is legitimate for the USA. These findings also validated by the frequency domain causality test. Based on the findings, specific policy proposals are given to assist the USA in improving its environmental quality and achieving the UN Sustainable Development Goals (SDGs) 7 (clean energy) and 13 (climate change mitigation).