Heterogeneous effects of energy consumption structure on ecological footprint.

Attention to environmental sustainability has increased among nations, especially after the Paris Agreement and COP26 of 2021. Considering that fossil fuel consumption is one of the main factors causing environmental degradation, altering the energy consumption patterns of nations toward clean energy can be a suitable solution. For this purpose, this study investigates the impact of energy consumption structure (ECS) on the ecological footprint from 1990 to 2017. This research includes three steps: First, the energy consumption structure is calculated using the Shannon-Wiener index. Second, from 64 countries with middle- and high-income levels, the club convergence method is used to identify countries with similar patterns in an ecological footprint over time. Third, using the method of moments quantile regression (MM-QR), we examined the effects of ECS in different quantiles. The results of club convergence show that the two groups of countries with 23 and 29 members have similar behavior over time. The results of the MM-QR model show that for club 1, the energy consumption structure in quantiles of 10th, 25th, and 50th has positive effects on the ecological footprint, while in 75th and 90th are negative. The results of club 2 indicate that the energy consumption structure has positive effects on the ecological footprint in quantiles 10th and 25th, but negative effects on 75th. Also, the results show that GDP, energy consumption, and population in both clubs have positive effects, and trade openness has negative effects on ecological footprint. Considering that the results indicate that changing the structure of energy consumption from fossil fuels to clean energies improves the environmental quality, so governments should use incentive policies and support packages for the development of clean energy and reduce the costs of installing renewable energy.

Exploring necessary and sufficient conditions for carbon emission intensity: a comparative analysis.

This research investigates the factors influencing carbon emission intensity in 94 countries during 2018 using two qualitative methods: necessary condition analysis (NCA) and fuzzy-set qualitative comparative analysis (fsQCA). The study covers variables related to economics, human geography, energy, and institutions, showing significant variations among them. The NCA model identifies economic complexity and fossil energy consumption as necessary conditions for high-carbon emission intensity. On the other hand, the fsQCA model reveals sufficient conditions for both high- and low-carbon emission intensity, presenting different causal combinations of variables. For high-carbon emission intensity, nine causal solutions are identified, emphasizing the roles of economic growth, urbanization, fossil energy consumption, and institutional quality. Reducing carbon emission intensity requires addressing economic complexity and reducing reliance on fossil energy consumption. Policymakers should focus on sustainable economic development, environmentally friendly urbanization, and transitioning to renewable energy sources. This research's originality lies in its qualitative approach, going beyond traditional regression methods to explore necessary and sufficient conditions for carbon emission intensity. It offers valuable insights into the complex interplay of variables, providing multiple causal configurations for both high- and low-carbon emission intensity.

Heterogeneous impact of eco-innovation on premature deaths resulting from indoor and outdoor air pollution: empirical evidence from EU29 countries.

Environmental innovations play a vital role in reducing air pollution and the number of pollution-related mortality. Most of the previous studies have examined the role of eco-innovations in environmental quality. However, to our knowledge, no study has evaluated the effects of eco-innovation on air pollution as a cause of mortality. For this purpose, this research examines the effect of eco-innovations on premature deaths from indoor and outdoor air pollution in twenty-nine European countries from 1995 to 2019. The Method of Moments Quantile Regression (MM-QR) is used to assess the impacts. The results confirm the heterogeneous effects of the main variables in both models. Both models indicate that eco-innovations reduce premature deaths from outdoor and indoor air pollution, and these effects are more significant in high quantities (75th and 90th). Also, the effect of eco-innovations on reducing mortality due to indoor pollution is more significant than that related to outdoor pollution. Eco-innovation, economic growth, renewable energy consumption, and urbanization reduce premature mortality indoors and outdoors, but CO2 emissions increase this mortality. The results of the Dumitrescu-Hurlin causality test also support that all variables, including eco-innovation and CO2 emissions, have a bidirectional causal relationship with indoor (LIND) and outdoor (LOUT) mortality due to air pollution. Governments and politicians can help mitigate this problem by providing more environmental innovations by increasing support packages and reducing taxes.

Globalization, renewable energy consumption, and agricultural production impacts on ecological footprint in emerging countries: using quantile regression approach.

Nowadays, paying attention to globalization and the consumption of renewable energy on the ecological footprint is one of the most important issues in the world. In the age of globalization, all countries are trying to prevent the spread of ecological degradation by enacting laws and regulations at the national level and regulating international agreements. This study investigates the effect of explanatory variables of globalization, renewable energy consumption, and agricultural production on the ecological footprint in emerging countries using fixed-effect panel quantile regression of 10th, 25th, 50th, 75th, and 90th in the period 2002 to 2016. The results showed that the consumption of renewable energy at all levels except the 25th quantile has a positive and significant effect on the ecological footprint; this effect is more in higher quantiles. Globalization in all quantiles has a negative and significant impact on the ecological footprint and has had the most excellent effect among other explanatory variables. Agricultural production variable at the 25th and 50th quantile levels had the most significant and positive effect on the ecological footprint. Therefore, it can be concluded that the increase in agricultural production, income, renewable energy consumption, population, and trade openness can lead to increased environmental degradation. However, the effects of globalization have had the most negligible negative impact on the ecological footprint.