As the sustainability of the environment is a very much concerning issue for developed countries, the drive of the paper is to reveal the effects of nuclear, environment-friendly, and non-friendly energy, population, and GDP on CO₂ emission for Italy, a developed country. Using the extended Stochastic Regression on Population, Affluence, and Technology (STIRPAT) framework, the yearly data from 1972 to 2021 are analyzed in this paper through an Autoregressive Distributed Lag (ARDL) framework. The reliability of the study is also examined by employing Fully Modified Ordinary Least Square (FMOLS), Dynamic Ordinary Least Square (DOLS), and Canonical Cointegration Regression (CCR) estimators and also the Granger causality method which is used to see the directional relationship among the indicators. The investigation confirms the findings of previous studies by showing that in the longer period, rising Italian GDP and non-green energy by 1% can lead to higher CO₂ emissions by 8.08% and 1.505%, respectively, while rising alternative and nuclear energy by 1% can lead to falling in CO₂ emission by 0.624%. Although population and green energy adversely influence the upsurge of CO₂, they seem insignificant. Robustness tests confirm these longer-period impacts. This analysis may be helpful in planning and developing strategies for future financial funding in the energy sector in Italy, which is essential if the country is to achieve its goals of sustainable development.

This study intends to shed light on the environmental impacts of energy decisions in South Korea by analyzing the correlation between energy consumption patterns and environmental indicators such as carbon dioxide emissions. In 2021, global CO₂ emissions increased by 6%—to the highest ever level of 36.3 billion tons—according to the International Energy Agency (IEA). This increase in CO₂ emissions is a big problem for all countries around the world. The aim of this article is an analyze the impact of fossil fuels, renewable energy, and nuclear energy on South Korea’s environment based on the STIRPAT (stochastic impact by regression on population, affluence, and technology) model. Exploring the intricate nexus between economic and energy indicators and environmental outcomes, this study employs the STIRPAT model to analyze the influence of GDP, population dynamics, fossil fuels, renewable energy, and nuclear energy on South Korea’s environment. The yearly data from 1972 to 2021 are analyzed in this paper using an autoregressive distributed lag (ARDL) model. The reliability of this study is also examined by employing FMOLS (fully modified ordinary least squares) and CCR (canonical cointegrating regression) estimators. This study confirms the findings of previous research by showing that the rising South Korea GDP and population can lead to higher CO₂ emissions and that a strategy switching to renewable energy can cut down on CO₂ emissions in Korea, as it exhibits a coefficient of −0.085 *. The robustness results of FMOLS and CCR’s findings support baseline ARDL findings.

This study aims to investigate the intricate relationship between multiple socioeconomic, human capital, and technological factors and their impacts on the ecological footprint within the ASEAN region. Focusing on eight ASEAN nations (Brunei, Cambodia, Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam) for the period between 1990 and 2020, this study employs Driscoll Kraay Standard Error (DKSE) and Quantile Regression methodologies to examine this phenomenon comprehensively. The findings reveal that the Human Capital Index (HCI) and technological patents exhibit negative coefficients, suggesting their beneficial impact on reducing ecological footprint by 0.162% and 0.027% sequentially in the DKSE approach. By contrast, population, GDP, tourism, globalization, and trade openness show positive coefficients, indicating their potential to exacerbate environmental degradation. Notably, population emerged as the most detrimental factor. Meanwhile, HCI demonstrated the most potent beneficial effect on environmental quality, suggesting that ASEAN nations should continue investing in their people to safeguard the environment. The implications of this study are critical for policymakers and stakeholders in the ASEAN region, highlighting the need for strategic interventions that balance economic and technological advancements with environmental preservation.

This study explores the relationships between electricity consumption, healthcare spending, carbon dioxide (CO₂) emissions, GDP growth, industrialization, urbanization, fertility rates, and child mortality rates in ten countries with the highest and lowest child mortality rates, using Driscoll-Kraay’s standard error approach (DKSE). The DKSE regression results show that in countries with high child mortality, the mortality declines significantly with electricity access, health expenditures, urbanization, and GDP growth, and increases with CO₂ emissions and fertility rates. In countries with low child mortality rates, the mortality declines significantly with health expenditures, GDP, and urbanization, and rises with industrialization. Electricity access, CO₂ emissions, and fertility rates do not impact child mortality in these countries. The study emphasizes the importance of electricity access, health expenditures, GDP, and tailored urbanization and industrialization strategies in child welfare and the need for comprehensive global policies.

This research study uses an autoregressive distributed lag (ARDL) paradigm to examine the effects of trade openness, urbanization (URBA), economic growth, and foreign direct investment (FDI) on energy demand in Ireland. This thorough theoretical framework anticipates a relationship between energy demand and trade, FDI, and URBA. This study demonstrates both short- and long-run cointegration among the variables employing an ARDL bounds-testing method for the data set period from 1972 to 2021. Additionally, fully modified ordinary least square (OLS), dynamic OLS, and canonical cointegrating regression were utilized in the study to verify the results’ robustness. Nonetheless, this analysis discovers that trade openness and rising gross domestic product per capita increase energy consumption (EC). The results show that for every 1% increase in GDP, EC increases by 0.967%. On the flip side, EC in Ireland is declining due to increased URBA and FDI. The results show that for every 1% increase in URBA, energy usage decreases by 1.738%. The investigation shows that Ireland’s energy usage is strongly impacted by trade liberalization, FDI, URBA, and economic expansion. Findings like these can help policymakers and stakeholders manage and optimize energy usage in the context of URBA, economic expansion, FDI, and global trade. The report recommends sustainable energy planning and policy initiatives to strike a healthy balance between meeting the increasing demand for energy and protecting the environment.