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The study investigates impact of energy consumption on environmental degradation at aggregated and disaggregated levels. In this context, the study considers carbon dioxide (CO2) emissions as proxy of environmental degradation, and focuses on the United States of America (USA) as the biggest economy and highest second carbon-emitting country. Moreover, the study uses monthly data between 1989 January and 2021 September and performs nonlinear approaches as Wavelet Coherence (WC), Granger Causality-in-Quantiles (GCQ), and Quantile-on-Quantile Regression (QQR). Besides, Quantile Regression (QR) is used for robustness checks of the QQR. The results show that (i) energy consumption has an important impact on the CO2 emissions in the short, medium and long term, while the impact changes according to times and frequencies; (ii) causal effect exists in almost all quantiles excluding some lower (0.05, 0.25), middle (0.65, 0.70, 0.75, 0.80) and higher (0.95) quantiles, whereas indicator-based results change a bit; (iii) the QR results confirm that the QQR results are robust; (iv) overall, the effects of the energy consumption indicators change according to times, frequencies, quantiles, and aggregated/disaggregated levels. Hence, the empirical outcomes underline the significance of renewable energy consumption in improving environmental quality through limiting CO2 emissions at aggregated and disaggregated levels. The results imply that the USA policymakers should focus on the efforts the decreasing fossil sources and increasing renewable sources through conversion of energy systems to limit CO2 emissions while considering changing impacts of energy consumption at various times, frequencies, quantiles, and aggregated/disaggregated levels.
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