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The excessive growth of carbon emissions (CO2E) from industrial energy use not only exacerbates global warming and severely curbs the sustainable development of the economy and society. As a high energy-consuming sector second only to the fossil energy division, the power and heavy division, China's chemical industry should have received more attention for its CO2E. However, there are limited literatures on energy CO2E in China's chemical sector at present. Based on this fact, this current paper uses the energy utilization approach, the input–output analysis approach, and the extended structural decomposition method to evaluate the energy-related CO2E of China's chemical sector from 2007 to 2017. (1) China's chemical sector energy-related CO2E showed a trend of first growth and then a slow decline, demonstrating that the rapid growth of China's chemical sector energy-related CO2E has been effectively controlled; However, it should be noted that the chemical industry is still dominated by high-CO2E energy-related CO2E at the current stage. (2) Input structure and energy intensity effects have a reduced influence on the growth of energy-related CO2E in China's chemical sector. This is due to upgrading energy use technology and optimizing the generalized technology progress rate in the chemical sector. (3) Energy structure and final demand effects have encouraged the growth of the chemical sector's energy-related CO2E. It shows that the industrial system's demand for chemical products is constantly expanding, and the chemical products still have the characteristics of high carbonization. Also, the chemical sector's supply-side energy utilization structure has not been significantly enhanced. [ABSTRACT FROM AUTHOR]

The main objective of the current study is to analyze the nexus between public debt, renewable electricity, economic growth, and carbon dioxide (CO2) emissions in emerging economies between 1990 and 2020. The augmented mean group (AMG), fully modified ordinary least square (FMOLS), and dynamic ordinary least square (DOLS) models have been applied to analyze the long-run estimation. The empirical evidence demonstrates that public debt, renewable electricity reduces CO2 emissions. Furthermore, an N-shaped relationship has been identified between per capita CO2 emissions and per capita GDP in emerging nations. Also, the result reveals a bidirectional causal relationship between public debt and economic growth, CO2 emissions and economic growth, public debt and CO2 emissions, and renewable electricity and economic growth. The current study recommends promoting the renewable energy transition, elevating renewable electricity generation capacities, and ensuring greener economic growth by emitting carbon dioxide emissions across emerging countries. The government across each region could incorporate taxes and other incentives to encourage entrepreneurs and citizens to produce equipment that reduces carbon intensity and is ecologically friendly. [ABSTRACT FROM AUTHOR]

Climate change presents a substantial impediment for the global community and prompts policymakers worldwide to prioritize environmental goals when defining national development strategies. Prioritizing these goals is particularly challenging for governments of developing economies still relying on fossil fuels, foreign capital, and industry contribution to GDP. This study examines the relationships between carbon dioxide emissions, industry value added, financial development, and electricity generation in 15 Central and Eastern European countries from 1995 to 2021. To achieve this objective, we examined stationarity and cointegration and employed a vector error correction model to investigate causalities between the variables, along with a variance decomposition analysis. Our findings suggest that the short-run unidirectional causalities exist from industry value-added to carbon dioxide emissions and from carbon dioxide emissions to financial development and electricity generation. Long-term causality exists between carbon dioxide emissions and industry value added. The findings shed light on the challenges and opportunities these countries face in transitioning to climate neutrality and meeting the decarbonization targets. Within this context, the findings underscore the significance of crafting customized strategies for these economies to navigate the complex landscape of climate change while promoting sustainable industrial, electricity and financial sector development. [ABSTRACT FROM AUTHOR]

Understanding the complex interactions between the economy and the environment is crucial for promoting sustainable development and mitigating the negative impact of human activities on the Planet. The importance of this issue for Serbia is evident as the country strives to balance economic growth and environmental protection to ensure a sustainable and resilient future. Therefore, the main objective of this study is to investigate and model the relationship between CO2 emissions, economic growth, electricity consumption, and trade openness in Serbia. Initially, an Autoregressive Distributed Lag (ARDL) model is used to characterize the Environmental Kuznets Curve (EKC) using data from the period from 1995 to 2019, followed by the construction of a bootstrap logistic regression model to predict environmental quality in Serbia. Long-term estimates of the model confirm an inverted U-shaped relationship, where all three variables exert a statistically significant influence on CO2 emissions. In the short run, however, a causal relationship is only observed between electricity consumption and CO2 emissions. The logistic regression results show that all three factors significantly influence environmental quality. The study proposes policy recommendations for Serbia, such as promoting sustainable economic growth, implementing long-term programs to reduce CO2 emissions, reviewing trade policies to prioritize sustainable practices, and investing in renewable energy sources to reduce emissions. [ABSTRACT FROM AUTHOR]