Journal
ENERGIES
Volume 14, Issue 18, Pages -Publisher
MDPI
DOI: 10.3390/en14185829
Keywords
economic growth; environmental Kuznets curve; renewable energy; spatio-temporal Durbin model; spatial spillovers
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The study presents a spatial approach to analyzing the relationship between air pollution, economic growth, and renewable energy consumption, showing the importance of renewable energy for environmental protection. The results demonstrate the impact of renewable energy consumption on CO2 emissions, with spatial and spatio-temporal effects identified.
The paper presents a spatial approach to the analysis of the relationship between air pollution, economic growth, and renewable energy consumption. The economic growth of every country is based on the energy consumption that leads to an increase in national productivity. Using renewable energy is very important for the environmental protection and security of the earth's resources. Promoting environmentally friendly operations increases awareness of sustainable development, which is currently a major concern of state governments. In this study, we explored the influence of economic growth and the share of renewable energy out of total energy consumption on CO2 emissions. The study was based on the classical environmental Kuznets curve (EKC) and enriched with the spatial dependencies. In particular, we determined the spatial spillovers in the form of the indirect effects of changes in renewable energy consumption of a specific country on the CO2 emissions of neighboring countries. A neighborhood in this study was defined by ecological development similarity. The neighborhood matrix was constructed based on the values of the ecological footprint measure. We used the spatio-temporal Durbin model, with which the indirect effects were determined in relation to the spatially lagged renewable energy consumption. The results of our study also show the strength of the effects caused by imitating actions from the states with high levels of environmental protection. The study was conducted using data for 75 selected countries from the period of 2013-2019. Cumulative spatial and spatio-temporal effects allowed us to determine (1) the countries with the greatest impact on others and (2) the countries that follow the leading ones.
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