In the European Union (EU), most countries are developed and economic activities are climbing. Because of that, CO 2 emissions in this area are rising. The EU must nd ways to reduce pollution before it is too late to ensure long-term sustainable growth. The study applies the STIRPAT model to check the impact of population, income, renewable energy, nuclear energy, and research and development on the environment.A newly developed Cross Section Autoregressive Distributed Lag (CS-ARDL) technique is used to investigate annual time series data from 1990 to 2021 for 30 European countries with slope heterogeneity and cross-sectional dependence. According to the study's ndings, fossil fuels and the population contribute to environmental pollution. On the other hand, increasing income and the use of renewable and nuclear energy can reduce long-term pollution. Similarly, research and development also help to reduce environmental degradation. The research shows that if the EU wants to stop the environment from getting worse, renewable energy is a must. It also shows that rising national wealth alone won't be enough to meet environmental needs.

Rapid population growth and economic expansion affect environmental sustainability by raising emissions from increased urbanization, industrialization, and energy consumption in South Asia. Therefore, the current research aims to scrutinize the dynamic impacts of urbanization, industrialization, and energy consumption on carbon dioxide (CO 2 ) emissions in five South Asian countries (Bangladesh, Pakistan, India, Nepal, and Sri Lanka) under the umbrella of the famous stochastic regression for impact for technology, population, and asset on environmental condition (STIRPAT) model. This research employed the second-generation unit root and cointegration tests by applying the data from 1972 to 2021 to investigate the existence of slope heterogeneity (SH) and cross-sectional dependence (CSD) problem. After checking CSD, SH, unit root, and cointegration tests, the research utilized cross-sectional autoregressive distributive lag (CS-ARDL) as a baseline model and augmented mean group (AMG), mean group (MG), and common correlated effects mean group (CCEMG) as a robustness check. The evidence shows that the economic boom, urbanization, and industrialization increase CO 2 emissions. CO 2 emissions in South Asian nations have been reduced due to population growth, natural resources rent, and electrification. All estimators point to urbanization's negative effects, being far more severe than any other environmental impact. Conversely, natural resource rent prevents environmental degradation more effectively than electricity. Therefore, it is recommended that South Asian economies adopt consistent, sustainable economic policies to reap the benefits of industrialization, urbanization, and increased electricity use. The findings are generally consistent with the policy implications.

<abstract> <p>This study looks at how Bangladesh's human capital investment has affected unemployment from 1995 to 2019. To identify the study's unit root, we employed the ADF and PP tests. The short- term and long-term impacts of human capital investment on unemployment are estimated using the Autoregressive Distributive Lag (ARDL) model. The presence or absence of cointegration is assessed using the ARDL bound cointegration test. The Pairwise Granger Causality test, in contrast, is used to ascertain whether there exist causal relationships between variables. The study's findings demonstrate that government health spending on human capital has a significant impact on Bangladesh's long-term unemployment rate. Government spending on education and the unemployment rate are causally related in a single direction, according to the Pairwise Granger test. In the short term, the analysis showed no discernible relationship between human capital investment and unemployment rates. To build a healthy nation and eventually lower Bangladesh's unemployment rate, it is urged that the government should increase health spending and strengthen the health sector. To connect education with employment, the government may give vocational and career-focused education equal weight with general education.</p> </abstract>

In the European Union (EU), most countries are developed and economic activities are climbing. Because of that, CO2 emissions in this area are rising. The EU must find ways to reduce pollution before it is too late to ensure long-term sustainable growth. The study applies the STIRPAT model to check the impact of population, income, renewable energy, nuclear energy, and research and development on the environment. A newly developed Cross Section Autoregressive Distributed Lag (CS-ARDL) technique is used to investigate annual time series data from 1990 to 2021 for 30 European countries with slope heterogeneity and cross-sectional dependence. According to the study's findings, fossil fuels and the population contribute to environmental pollution. On the other hand, increasing income and the use of renewable and nuclear energy can reduce long-term pollution. Similarly, research and development also help to reduce environmental degradation. The research shows that if the EU wants to stop the environment from getting worse, renewable energy is a must. It also shows that rising national wealth alone won't be enough to meet environmental needs.