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.

Environmental degradation mitigation has become a critical ecological and economic concern since the Kyoto Earth Summit in 1997 and the Paris Agreement in 2015. Yet, economic considerations continue to be a top focus. Globalization, urbanization, rapid economic growth, foreign direct investment (FDI), and tourist arrivals have put tremendous strain on natural resources, speeding climate change and exacerbating ecological disasters, especially in some nations, without considering environmental quality. This study examines the intertwined dynamics of FDI, urbanization, tourism, total patents, and globalization on the ecological footprint across nine selected Southeast Asian (ASEAN) countries from 1995 to 2020. Employing canonical cointegration regression (CCR), dynamic ordinary least squares (DOLS), and fully modified ordinary least squares (FMOLS) for baseline assessment, along with quantile regression for robustness, this research provides substantial insights. The results confirm the validity of the pollution haven hypothesis, revealing that FDI reduces environmental quality in ASEAN. Similarly, urbanization, tourism, and total patents have significant positive coefficients, signifying negative environmental impacts. Conversely, GDP and globalization have emerged as key factors in mitigating the ecological footprint. To achieve the sustainable development goals in ASEAN, policies on FDI, urbanization, and tourism must be designed to balance economic growth with environmental quality.

An important factor in trade is the currency's exchange rate and fluctuation of exchange rate is very concerning issue in current period over the world. Bangladesh, a developing economy, depends mostly on agriculture sector, recent period’s fluctuation of exchange rates of the country influences its export and import of the agricultural production. This research examines how the real exchange rate affects agricultural production's import and export between 1977 and 2015 in Bangladesh. Variables like Total Agricultural Production, Real Gross Domestic Product, Exchange rates, and Exports and Imports of Agricultural Product have been taken for this study. Ordinary Least Square Method (OLS) and other related econometrical techniques are applied to find the association among indicators. The research indicates that the exchange rate shows no discernible effect on the import and export of agricultural production in Bangladesh. However, Real Gross Domestic Product (GDP) of the country portraits no significant influence on agricultural exports while portraits positive significant influence on agricultural imports. This research contributes to appropriate policies and actions that must be implemented at an equitable level.

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.