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Covid-19 has brought about significant changes in people's daily lives, leading to a slowdown in economic activities and the implementation of restrictions and lockdowns. As a result, there have been noticeable effects on the environment. In this study, we examine the impact of Covid-19 total cases on the monthly average of carbon monoxide emissions in developed economies known for heavy pollution, covering the period from 2014 to 2023. We apply the Ambiental Kuznets curve approach to analyze the data. By employing different panel estimation techniques such as fixed effects and Driscoll-Kraay regressions, we observe a marked shift in environmental dynamics during the post-Covid era. This shift alters the statistical significance of the N-shaped Kuznets curve, rendering the relationship between economic activity and environmental impact non-significant. Interestingly, the Covid-related variables utilized in the various estimations are not statistically significant in explaining the long-term environmental effects. [ABSTRACT FROM AUTHOR]

The global relevance of food security has attracted a plethora of research, because it is a determinant of either the prosperity or poverty of any nation. Accordingly, food security is directly associated with the poverty in many developing countries of the world today. Rural people around the world continue to struggle with food insecurity, persistent poverty and inequality, and environmental degradation. This necessitated a research study on food security in the North West province of South Africa, with a view to evaluate the food security status and its determinants in the area, as well as to compare the impact of gender on the food security status of households. A cross-sectional survey was conducted, where 346 maize farmers in the Ngaka Modiri Molema District Municipality of the North West, South Africa, were interviewed. A logically structured questionnaire was used to collect data where household expenditure survey was used to evaluate the food security status of these farmers, after which a logistics regression model was used to determine the factors responsible for food security. The findings reveal that, with more farming experience, the probability of household food security decreased. Also, an increase in the household size, by one member, decreases the probability of a household achieving food security. Similarly, a unit increase in the age of the head of household decreases the probability or likelihood of being food secured in the study area. The result also revealed that more than half of the farming households were food secure, while the female-headed households were more food secure, proportionately, compared to male-headed households. [ABSTRACT FROM AUTHOR]