Global warming is one of the most significant challenges facing the world today, as it poses an alarming threat to the entire ecosystem, human health, the economy, and national security. With the ever-increasing emission of carbon dioxide and other greenhouse gases, there has been a progressive rise in mean temperatures recorded, causing global sea levels to increase as a result of the acceleration of warming oceans, shrinking ice sheets and glacial retreat. Global warming has heightened the ferocity and frequency of extreme calamities such as heat waves, drought, wildfires, hurricanes, floods and storm surges. Extreme mitigation measures must be taken to stop this trend, failing which global warming could cause a devastating impact on the entire planet and its communities. It is imperative that more research be carried out to evaluate the impact of various factors affecting carbon emissions, as it is one of the main greenhouse gases. This study is therefore in the right direction, as it examines the long-run relationships and short-run dynamic interactions between carbon emissions and its determinants comprising of income per capita, energy use, trade openness and financial development, over the period 1970 to 2016. The study applies the dynamic heterogenous panel estimation techniques of Mean Group (MG), Pooled Mean Group (PMG) and Dynamic Fixed Effects (DFE) to analyse a set of macro panel data of the ASEAN-5 countries, to establish the possible causal relations between these variables. An analysis of the results reveal the existence of a long-run causality between carbon emissions and its explanatory variables, indicated by the significant error correction terms for all the models tested in this study. There is evidence that energy use, trade openness and per capita income significantly contribute to carbon emissions, with energy use being the most dominant contributor. Interestingly, the study also reveals that financial development is not significant in determining carbon emissions in these selected countries. The study concludes with an examination of policy implications of the findings.

Education, environment, energies and economic, have several number high impacts of research in 5 years. Data from Dimensions.ai, the most comprehensive research grants database which links grants to millions of resulting publications, clinical trials and patents, have several results about education, environment, energies and economic research, in Studies in Human Society 146 papers, Economics 96 papers, Applied Economics 95 papers, Engineering 93 papers, Policy and Administration 63 papers. Using vosviewer.com analysis, files downloaded from the free version of Dimensions may contain data for at most 2500 documents. (Larger numbers of documents are supported when a subscription-based version of Dimensions is used), we can see that Education have high impact on energy, environment, sustainability and sustainable development. The study aims to investigate the environmental effects of mix energies on the three most polluted countries of ASEAN economies. The study uses the data of the Philippines, Vietnam, and Thailand over the period of 1995-2017 as gathered from the World Bank and Global Economy. The study uses Brush Pagon LM and Pearson CD to test the cross-section dependence among variables while Levin, Lin & Chu (2002) panel unit root test to check the stationary in the data. Westerlund (2007) cointegration and FMOLS tests are applied to analyze the long-run relationship. The result confirms the adverse environmental effects of fossil fuel electricity generation (FEG) and positive environmental effects of solar electricity generation (SEG), nuclear-power electricity generation (NEG), and geothermal electricity generation (GEG) on the ASEAN economies. Wind electricity generation (WEG) and hydroelectricity generation (HEG) do not significantly contribute to deteriorating the environment. The study suggests using GEG, WEG and SEG methods of producing electricity instead of FEG.

This study by using the random effects (RE) and robust least square estimates (RLS) examines the influence of two different types of FDI namely Greenfield (GF), Mergers & Acquisition (M&A) and energy consumption, on environmental performance of the eight selected economies in SAARC and ASEAN regions over the 2003-2014 period. Moreover, economic growth and population growth are used as controlled variables. The originality of this study is the use of Environmental Performance Index (EPI) to examine the effects of two different types of foreign capital inflows on the environment. According to the empirical outcomes of this study, GF and M&A investments have exacerbated the environmental performance in the selected eight SAARC and ASEAN countries, hence confirm the Pollution Haven Hypothesis (PHH) to be valid. In addition, energy consumption and population growth are also found to be serious havoc for the environmental performance in this case. Nonetheless, economic growth has improved the overall environmental performance in these countries. The study suggests the formulation and enforcement of strict environmental regulations to seek environment friendly and energy efficient GF and M&A investments. In addition, renewable energy use and population control policies are highly desirable in these countries for clean and healthy environment. Accordingly, these economies are recommended to develop policies to realize sustainable economic development for improved environmental performance.