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One of the worst natural, economic, and social catastrophes caused by human activity is the Aral Sea crisis in Central Asia. The Aral Sea's desiccation, which has an impact on the region's overall sustainable development, human welfare, security, and survival, is what led to the problem. This study assesses the effects of economic expansion, population ageing, life expectancy, internet usage, and greenhouse gas emissions on the fertility rate in the countries that made up the Aral Sea basin between 1990 and 2021. Several econometric techniques were used in this study, including Pooled OLS (Ordinary Least Squares) with the Driscoll–Kraay estimating method, FMOLS (Fully Modified Ordinary Least Square), and DOLS (Dynamic Ordinary Least Square). Additionally, we used the Hurlin and Dumitrescu non-cause tests to verify the causal links between the variables. The empirical findings verify that a decrease in the fertility rate among women in the nations surrounding the Aral Sea occurs when the population of a certain age (women aged 15–64 as a percentage of the total population) grows and life expectancy rises. Greenhouse gas emissions (GHGs) also have an adverse effect on reproductive rates. Conversely, the region's fertility rate may rise as a result of increased internet usage and economic growth. Furthermore, this study indicates that certain variables—aside from greenhouse gas emissions (GHGs)—have a causal relationship with the fertility rate. [ABSTRACT FROM AUTHOR]

Central Asia (CA) is a young integrated region formed after the collapse of the Soviet Union, with most of its infrastructure based on fossil fuels. The traditional energy and water infrastructure is facing huge inefficiency and technical losses. This study investigates the transition of the green, blue, and energy economies in Central Asia using a small-dimensional panel dataset on five countries, Uzbekistan, Kazakhstan, Kyrgyzstan, Tajikistan, and Turkmenistan, over the period 1995–2018. The authors analyze the impact of ecological footprint, water withdrawal, and energy consumption on gross domestic product. In applying the Panel Vector Error Correction Model, evidence was found supporting the long-running association between variables. Furthermore, the adjustment coefficients suggest that only GDP growth will adjust toward equilibrium. Overall, the findings suggest a more effective role of green transition compared to blue and energy transitions. [ABSTRACT FROM AUTHOR]

This study investigates how life expectancy is influenced by CO2 emissions, health spending, GDP, water usage, agricultural output, and renewable and non-renewable energy consumption within the Aral Sea basin, which is an environmentally catastrophic zone in the world. This research utilized data from the years 2002 to 2020 and employed various econometric approaches, including FMOLS, DOLS, and Driscoll–Kraay. The outcomes of the study reveal that health spending, GDP, water productivity, agriculture output, energy consumption, and human capital have a positive impact on life expectancy, but CO2 emissions have a negative impact on life expectancy. The most important policy takeaway from this study is the need to develop and implement comprehensive policies that take into account health spending, GDP, water, agricultural output, energy consumption, and education level in order to ensure life longevity. [ABSTRACT FROM AUTHOR]

Remittances are a crucial part of economic expansion, especially in Central Asia. Nevertheless, it is not possible to ignore its environmental damage. This paper is a pioneer in investigating the association among CO2 emissions, remittances, energy consumption and economic development in Central Asian countries (Uzbekistan, Kazakhstan, Kyrgyzstan and Tajikistan) spanning the period of 1995–2022. As a methodology, the FMOLS estimator is applied to check linear impact and long-run association as well. Panel threshold regression model and 2SLS method are applied to examine potential non-linear relations among the studied variables. Hausman–Taylor and Amacurdy estimators are employed to control the endogeneity issue among the variables of interest. The results suggest the existence of a long-run relationship among the studied variables. Precisely, applying the FMOLS method, remittances negatively impact CO2 emissions in the long run. The relationship between CO2 emissions and remittances is distorted when the endogeneity issue is considered with the Panel threshold regression model, 2SLS method, and Hausman–Taylor and Amacurdy estimators. This distortion validates the linear impact of remittances on CO2 emissions in CA. The Dumitrescu–Hurlin causality test shows that all independent variables have a causal effect on the dependent variable, validating the effect of the studied variables. Consequently, decision-makers should facilitate remittances towards more environmentally friendly and sustainable solutions to prevent the detrimental effects of remittance inflows on carbon emissions in Central Asia. [ABSTRACT FROM AUTHOR]

This study investigates the impacts of alternative energy use, urbanization, GDP, agriculture, ICT development, and FDI on carbon dioxide (CO2) emissions in the 14 leading CO2-emitting countries in Asia. This research comprises various econometric techniques, including MMQR, FMOLS, DOLS, and Driscoll–Kraay, to extend the data analysis from 1996 to 2020. The findings provide significant support for an inverted U-shaped link between economic expansion and environmental deterioration, known as the environmental Kuznets curve. Moreover, this paper verifies that the GDP square, renewable energy use, and agriculture are shown to help to decrease pollution, as indicated by the research findings. On the contrary, urbanization and the GDP are demonstrated to be variables that contribute to carbon emissions. Furthermore, the panel quantile regression models validate that the impacts of each explanatory variable on CO2 emissions vary across various quantiles. Finally, this analysis provides valuable suggestions to scholars, environmentalists, politicians, and authorities for identifying and mitigating the main cause of emissions. [ABSTRACT FROM AUTHOR]

Environmental sustainability concerns are growing worldwide. Reducing carbon dioxide (CO2) emissions is crucial to combating global warming and reaching sustainable global economic development. Many recent studies have focused on key indicators of CO2 emissions, but less consideration has been given to associated factors such as renewable energy and human capital. This article applies the two-step system FOD-GMM (Forward-Orthogonal Deviations-Generalized Method of Moments) to estimate the role of renewable energy and human capital in reducing environmental degradation in Europe and Central Asia. The results reveal that renewable energy consumption and human capital have a significant negative impact on CO2 emissions in the EU and Central Asian countries, government efficiency has a positive effect on CO2 emissions, and economic development has a neutral effect, confirming the strong role of renewable energy and human capital in reducing CO2 emissions in EU and Central Asian countries. The role of human capital and renewable energy in promoting CO2 reduction should be fully utilized. Policymakers should develop infrastructure for renewable energy and education to support the decrease in CO2 emissions in Europe and Central Asia. [ABSTRACT FROM AUTHOR]

Modern life is convincing us that renewable energy technologies, policies, strategies should be disseminated all over the world to provide sustainable development. As an instrument, feed-in tariffs of renewable energy should be designed considering public finance opportunities, buying power of consumers in order to tackle administrative barriers as an optimization strategy. The authors used the comparison, data analysis and logical access methods. The paper provides evidence from leading countries in the industry, explores ongoing challenges in the application of feed-in tariff policies, analyses the optimal methodologies to give recommendations to stakeholders.