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The threat of global warming has increased due to industrialization, urbanization, population expansion, and changes in lifestyle among the Group of Seven(G7) Carbon dioxide emissions (CO2) directly affect how much electricity can be generated from various sources. This research aims to identify environmental hazards associated with various energy sources. Analyzing the impact of various energy sources on CO2 emissions from electricity and heat production using data from the G7. The data is analyzed using quantile regression (QR), generalized method of moments (GMM), random effects (RE), and fixed effects (FE). Our results indicate a substantial positive impact on CO2 emissions regardless of the technology used to generate coal and gas power. Coal-fired power plants have a larger impact on the environment than other sources of emissions. Also, all coal and gas coefficients are significant in FE, RE, GMM, and QR. Oil coefficients have a negative impact on environmental degradation and are significant for FE, RE, and D-GMM regressions. Hydroelectric and renewable energy production can reduce CO2 emissions in all regression models. Nuclear energy has a beneficial impact on the environment, but the coefficients are only significant for S-GMM and the last quantile. However, the most significant result of this study is the identification of a cause-and-effect relationship between CO2 emissions and energy production. Carbon dioxide (CO2) emissions can be lowered by shifting away from fossil fuels and toward renewable and hydroelectric sources. The research also suggests several renewable and alternative electricity production policies for sustainable energy.

The main purpose of this study was to examine how tourism, GDP, renewable energy, and fossil fuels cause environmental damage. This study examined ten African countries between 1997 and 2021 to test the environmental Kuznets curve (EKC) theory. Egypt, South Africa, Kenya, Morocco, Tanzania, Tunisia, Mauritius, Ghana, Uganda, and Nigeria are the ten African countries with the most tourists. In this paper, the augmented mean group (AMG), mean group (MG), and common correlated effects mean group (CCEMG) models were used to deal with slope heterogeneity (SH), cross-sectional dependence (CSD), and a mix of first-differenced and level stationary variables. Though the inverted U-shaped exists, the findings are significant only for MG. The impact of renewable energy is favorable for the environment and significant for the AMG estimator. Inversely, impact of tourist arrivals and fossil fuels are detrimental for environment and significant. Based on the findings for each country, the tourism-based EKC theory only works for Kenya, Egypt, and Tanzania. The research found that using more renewable energy minimizes CO2 emissions more effectively in almost all countries except Morocco and Ghana. Ghana, Kenya, and Uganda’s CO2 emissions increase when more tourists come from other countries. For the sake of both tourism and the environment, the government must reconsider its tourism policies and implement ones that include renewable energy. The findings of this study assist in the transition to clean energy, aiding in sustainable tourism growth. As a result, selected countries should develop a new tourism plan that focuses on renewable energy sources and protects the environment.

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