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The coronavirus pandemic has infected more than 100 million people worldwide with COVID-19, with millions of deaths across the globe. In this research, we explored the effects of environmental and weather variables with daily COVID-19 cases and COVID-19 fatalities in Istanbul, Turkey. Turkey has the 8th highest number of COVID-19 cases globally, with the highest infections and deaths in Istanbul. This may be the first study to conduct a comprehensive investigation for environmental quality (air quality pollutants, e.g., PM2.5 and PM10, ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide, etc.), weather parameters (temperature, humidity) and COVID-19 in Turkey. The authors collected meteorological data from 11 March 2020 to 8 February 2021 and COVID-19 data from Istanbul and other regions. The results from empirical estimations, correlation analysis, and quantile on quantile techniques support that air quality and temperature significantly influence COVID-19 deaths in Istanbul. This research may help policymakers and health scientists to take specific measures to reduce the spread of coronavirus across different global cities. The effects of air quality on COVID-19 in Istanbul was investigated. The study applied correlation and quantile on quantile techniques over daily data. Temperature significantly induces the spread of COVID-19 in Istanbul at all quantiles. Air quality and Nitrogen are positively linked with COVID-19 new cases. [ABSTRACT FROM AUTHOR]

This study contributes to the environment-growth nexus literature by examining corruption's effect on environmental quality in 17 Middle East and North Africa (MENA) countries between 1984 and 2018. We use four different indicators of environmental degradation (ecological footprint, carbon dioxide emissions, greenhouse gas emissions, and carbon emission intensity) to gain a comprehensive view of the relationship. This study's methodological value added is the application of the method of moments quantile regression, which enables us to account for different relationships between the independent variables and environmental quality at different levels of environmental degradation. The results indicate that corruption worsens environmental quality based on three of the four indicators of environmental degradation, while the impact appears to become less severe at higher levels of environmental deterioration. The results also indicate that traditional mean-based panel data estimation methods provide an incomplete picture of the factors behind environmental problems: The explanatory variables' impacts tend to vary at different levels of environmental quality, and the impact's sign can even change when moving from the lowest to the highest environmental degradation quantiles. Overall, the results highlight the importance of curbing corruption to enable enforcement of more stringent environmental regulations. [Display omitted] • The effect of corruption on environmental degradation is investigated. • We used the Method of Moment Quantile Estimations. • Corruption worsens environmental quality in the MENA region. • Corruption increases ecological footprint, GHG emission and carbon emission intensity. [ABSTRACT FROM AUTHOR]

The G7 countries consist of some of the world's most economically developed nations. However, alongside such robust economic growth performances, the environmental qualities in these countries have simultaneously aggravated to raise deep concerns among the stakeholders. Hence, this study is designed to empirically examine the environmental effects of nuclear and renewable energy consumption, economic complexity, and economic growth in the context of the G7 countries for the period between 1995 and 2016. To ensure novelty, this study considers carbon footprints along with carbon dioxide emissions to measure environmental quality in the context of the G7 nations. The results reveal that although nuclear energy consumption is effective in mitigating carbon dioxide emissions and carbon footprints in the long run, renewable energy consumption degrades the environment in the G7 countries. Besides, the results also suggest that the G7 countries can transform their production processes in an environmentally friendly manner provided they can undergo a clean transition in energy use. Finally, economic growth is evidenced to be detrimental for the environment since higher economic growth levels are seen to boost both carbon dioxide emission and carbon footprint levels. Therefore, in line with the findings, this study recommends the G7 countries to significantly enhance their nuclear and renewable energy consumption levels, increase their economic complexity indices, and integrate environmental welfare policies within their economic growth strategies. • Determinants of CO 2 emissions and carbon footprints are evaluated in G7 countries. • Renewable energy use boosts CO 2 emissions and carbon footprints. • Nuclear energy use curbs CO 2 emissions and carbon footprints. • Economic complexity reduces CO 2 emissions and carbon footprints. • Economic growth stimulates CO 2 emissions and carbon footprints. [ABSTRACT FROM AUTHOR]

Achieving sustainable environmental development, while further avoiding environmental degradation is an unprecedented challenge for policymakers. This article aims to explore whether the Environmental Kuznets Curve (EKC) hypothesis holds if the relevant carbon emissions modelling approach includes both energy consumption and the Konjunkturforschungsstelle (KOF) globalization index. The analysis is performed through panel methods and for 67 developed and developing countries, spanning the period 1971–2018. The empirical results demonstrate that there is a significant and positive association between globalization and carbon emissions. At the same time, higher GDP increases carbon emissions, while higher coal energy also leads to higher emissions, with the coefficient of the squared GDP turning out to be negative, which lends amble support to the validity of the EKC hypothesis. The findings of this article might be helpful in policy making regarding overall energy structure, carbon emissions, and globalization trends in developing and developed countries. [ABSTRACT FROM AUTHOR]

This study investigates the dynamic interdependence between CO 2 emissions, real gross domestic product (GDP), renewable and non-renewable energy generation, urbanization, and export quality for both the top ten renewable energy and top ten economic complexity index (ECI) countries. The techniques of panel cointegration, long-run FMOLS, DOLS, and Granger causality are used spanning the period 1980–2014. Long-run estimates suggest that, for the top ten renewable energy countries, only renewable energy generation contributes to mitigating CO 2 emissions, while the other variables lead to increase emissions levels in the long-run. However, for the case of leading complex economies, the empirics highlighted the significant role of renewable energy in carbon mitigation. Exports quality leads to decrease emissions level and real GDP, non-renewable energy and urbanization contribute to the rise in emissions. Interestingly, for the top ten renewable energy countries, Granger causality analysis mentioned a two-ways short-run relationship between renewable energy generation and export quality and one-way causality from export quality to CO 2 emissions. The findings mention that adopting clean technologies using renewable energy might act as a key tool for export quality improvement and mitigation of CO 2 emissions. Results are related to Sustainable Development Goals (SDG-7: using more renewable, affordable energy; SDG-8: sustainable economic growth and decent employment for all, SDG-13: regulating emissions and promoting renewable energy) and discussed in this sense. • Dynamic interdependence between CO 2 emissions, energy generation, and exports quality is examined. • Panel data is used for renewable energy and economic complexity countries. • Export quality tend to have positive effects on CO 2 emissions. • Non-renewable energy induces pollution levels. • Renewable energy mitigates CO 2 emissions. [ABSTRACT FROM AUTHOR]