Do the effects of aggregate and disaggregate energy consumption on different environmental quality indicators change in the transition to sustainable development? Evidence from wavelet coherence analysis

Abstract

In the 2030 Agenda for Sustainable Development, adopted by the United Nations (UN) member states in 2015, half of the target period has been exceeded. However, China, whose energy consumption relies heavily on fossil resources, remains at the top of the list of global polluters. Therefore, investigating the environmental impacts of energy types is essential to China's path towards Sustainable Development Goals (SDG)-7 and SDG-13. Based on this motivation, the paper offers new insights into the energy-environment literature for China with wavelet coherence analysis (WCA). This approach can investigate the relationship between variables in a periodic manner based on the frequency behavior of the models. The paper separately analyzes the effects of primary energy consumption (PEC), fossil energy consumption (FEC), renewable energy consumption (REC), nuclear energy consumption (NEC), GDP, and population (POP) on three different environmental indicators in China. Using two environmental pollution indicators (carbon emission (CO₂) and ecological footprint (EF)) and one environmental quality indicator (load capacity factor (LCF)), the paper allows for comparison and robustness checks on the environmental impacts of energy indicators. Empirical findings reveal the following: (i) Except for REC and POP in the CO₂ model, the variables in all three models largely move together during the period under observation; (ii) variables other than POP have consistent coefficient signs; (iii) PEC, FEC, NEC, and GDP increase CO₂ and EF while decreasing LCF; (iv) the effect of NEC on LCF is more obvious until 2000; (v) unlike the others, REC affects CO₂ and EF negatively and LCF positively; (vi) there is bidirectional causality between PEC and environmental indicators but not for REC; (vii) the causality relations of other variables with environmental indicators differ in terms of model, time, and direction of causality. In light of the findings, the paper highlights that only the REC improves environmental quality in China. Other energy indicators contribute to environmental degradation. China, whose ecological deficit has increased dramatically in recent years, urgently needs to reduce its dependence on fossil energy sources by accelerating investments in REC. Governments should also review nuclear energy policies, which are expected to help achieve carbon neutrality.

Keywords: Energy consumption; Load capacity factor; Nuclear; Wavelet coherence.