India has experienced notable advancements in trade liberalization, innovation tactics, urbanization, financial expansion, and sophisticated economic development. Researchers are focusing more on how much energy consumption of both renewable and non-renewable accounts for overall system energy consumption in light of these dynamics. In order to gain an understanding of this important and contentious issue, we aim to examine the impact of trade openness, inventions, urbanization, financial expansion, economic development, and carbon emissions affected the usage of renewable and non-renewable energy (REU and N-REU) in India between 1980 and 2020. We apply the econometric approach involving unit root tests, FE-OLS, D-OLS, and FM-OLS, and a new Quantile Regression approach (QR). The empirical results demonstrate that trade openness, urbanization and CO₂ emissions are statistically significant and negatively linked with renewable energy utilization. In contrast, technological innovations, financial development, and economic development in India have become a source of increase in renewable energy utilization. Technological innovations were considered negatively and statistically significant in connection with non-renewable energy utilization, whereas the trade, urbanization, financial growth, economic growth, and carbon emissions have been established that positively and statistically significant influence non-renewable energy utilization. The empirical results of this study offer some policy recommendations. For instance, as financial markets are the primary drivers of economic growth and the renewable energy sector in India, they should be supported in order to reduce CO₂ emissions.

We analyze Thailand’s projected 2023–2030 energy needs for power generation using a constructed linear programming model and scenario analysis in an attempt to find a formulation for sustainable electricity management. The objective function is modeled to minimize management costs; model constraints include the electricity production capacity of each energy source, imports of electricity and energy sources, storage choices, and customer demand. Future electricity demands are projected based on the trend most closely related to historical data. CO₂ emissions from electricity generation are also investigated. Results show that to keep up with future electricity demands and ensure the country’s energy security, energy from all sources, excluding the use of storage systems, will be necessary under all scenario constraints.

Urbanization plays a crucial role in facilitating the integration of population growth, industrial development, economic expansion, and energy consumption. In this paper, we aim to examine the relationships between CO2 emissions and various factors including economic growth, urbanization, financial development, and energy consumption within Pakistan’s building sector. The study utilizes annual data spanning from 1990 to 2020. To analyze the cointegration relationship between these variables, we employ the quantile autoregressive distributed lag error correction model (QARDL-ECM). The findings of this research provide evidence supporting the presence of an asymmetric and nonlinear long-term relationship between the variables under investigation. Based on these results, we suggest the implementation of tariffs on nonrenewable energy sources and the formulation of policies that promote sustainable energy practices. By doing so, policymakers and architects can effectively contribute to minimising environmental damage. Overall, this study offers valuable insights that can assist policymakers and architects in making informed decisions to mitigate environmental harm while fostering sustainable development.

Background: Bitcoin mining, an energy-intensive process, requires significant amounts of electricity, which results in a particularly high carbon footprint from mining operations. In the Republic of Kazakhstan, where a substantial portion of electricity is generated from coal-fired power plants, the carbon footprint of mining operations is particularly high. This article examines the scale of energy consumption by mining farms, assesses their share in the country’s total electricity consumption, and analyzes the carbon footprint associated with bitcoin mining. A comparative analysis with other sectors of the economy, including transportation and industry is provided, along with possible measures to reduce the environmental impact of mining operations. Materials and methods: To assess the impact of bitcoin mining on the carbon footprint in Kazakhstan, electricity consumption from 2016 to 2023, provided by the Bureau of National Statistics of the Republic of Kazakhstan, was used. Data on electricity production from various types of power plants was also analyzed. The Life Cycle Assessment (LCA) methodology was used to analyze the environmental performance of energy systems. CO₂ emissions were estimated based on emission factors for various energy sources. Results: The total electricity consumption in Kazakhstan increased from 74,502 GWh in 2016 to 115,067.6 GWh in 2023. The industrial sector’s electricity consumption remained relatively stable over this period. The consumption by mining farms amounted to 10,346 GWh in 2021. A comparative analysis of CO₂ emissions showed that bitcoin mining has a higher carbon footprint compared to electricity generation from renewable sources, as well as oil refining and car manufacturing. Conclusions: Bitcoin mining has a significant negative impact on the environment of the Republic of Kazakhstan due to high electricity consumption and resulting carbon dioxide emissions. Measures are needed to transition to sustainable energy sources and improve energy efficiency to reduce the environmental footprint of cryptocurrency mining activities.

The significant climate change the planet has faced in recent decades has prompted global leaders, policymakers, business leaders, environmentalists, academics, and scientists from around the world to unite their efforts since 1987 around sustainable development. This development not only promotes economic sustainability but also environmental, social, and corporate sustainability, where clean production, responsible consumption, and sustainable infrastructures prevail. In this context, the present article aims to propose a development framework for sustainability in food sector SMEs, which includes Life Cycle Assessment (LCA) and the integration of Environmental, Social, and Governance (ESG) strategies as key elements to reduce CO₂ emissions and improve operational efficiency. The methodology includes a comparative analysis of strategies implemented between 2019 and 2023, supported by quantitative data showing a 20% reduction in operating costs, a 10% increase in market share, and a 25% increase in productivity for companies that adopted clean technologies. This study offers a significant contribution to the field of corporate sustainability, providing a model that is adaptable and applicable across different regions, enhancing innovation and business resilience in a global context that requires collective efforts to achieve the sustainable development goals.

India’s economic growth is of significant interest due to its expanding Gross Domestic Product (GDP) and global market influence. This study investigates the interplay between production, trade, carbon dioxide (CO₂) emissions, and economic growth in India using Granger causality analysis. Also, the data from 1994 to 2023 were analyzed to explore the relationships among these variables. The results reveal strong positive correlations among production, trade, CO₂ emissions, and GDP, with production showing significant associations with export, import, and GDP. Co-integration tests confirm the presence of a long-term relationship among the variables, suggesting their interconnectedness in shaping India’s economic landscape. Regression analysis indicates that production, export, import, United States (US)-India trade, manufacturing cost of energy, and CO₂ emissions significantly impact GDP. Moreover, the Vector Error Correction Model (VECM) estimation reveals both short-term and long-term dynamics, highlighting the importance of understanding equilibrium and deviations in economic variables. Overall, this study contributes to a better understanding of the complex interactions driving India’s economic growth and sustainability.