Global warming and environmental degradation caused essentially by changes in climate have attracted enormous surveillance considering the menace of its reverberation on the health of humans during the past two decades. Utilization of energy and financial development (FD) are among the key drivers of climatic change. Thus, using second-generation panel cointegration (the Westerlund, 2007 error-correction model), pooled mean group autoregressive distributive lag model (PMG-ARDL), and the panel dynamic ordinary least square (PDOLS) estimation techniques, the paper scrutinized the nexus between financial development, clean energy usage, economic growth, and environmental quality (proxied by CO 2 emissions) of BRICS countries starting from 1980 to 2018. The findings from the study reveal that economic growth and labor force participation, in the long run, deteriorate the environmental quality by increasing the effusion of carbon. Contrarily, financial development, industrialization, trade openness, and renewable energy usage enhance the environmental quality of BRICS countries in the long run.In the short run, financial development was found to have a significant positive impact on the environmental quality of Brazil, China, and Russia, while it is negative for South Africa and India. The outcome of the PVECM Granger causality test reveals a two-way Granger causality that runs from renewable energy to carbon emissions in the short run. The policy implication of this study is that the government of BRICS countries needs to concentrate on improving their clean energy sources and also work on their industries. The BRICS nations' governments should formulate financial and trade policies that promote a sustainable environment and economic development.

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This paper examines the causation between economic growth, tourism import, industrialization, renewable energy, non-renewable energy use, trade openness, and environmental sustainability which is proxied by carbon emissions for 8 Asian countries (China, Japan, India, Indonesia, South Korea, Philippines, Thailand, and Vietnam) over 20 years. Causal relations were tested using Pooled Mean Group Autoregressive distributive lag model (PMG-ARDL) and Dumitrescu and Hurlin's (2012) panel granger causality test The PMG-ARDL model results reveal that in the long-run renewable energy usage, economic growth, and trade have a significant negative influence on the emission of carbon, while non-renewable energy usage, tourism import, and industrialization exhibit a significant positive impact on CO2 emissions of the sampled Asian countries. In the short run, renewable energy has a significant negative influence on CO2 emissions. While economic growth exhibit a significant positive influence on carbon emissions in the short-run. Furthermore, the Granger causality analysis reveals that there is a feedback mechanism between industrialization, tourism import, non-renewable energy, renewable energy, and CO2 emissions meaning that the future dynamics of carbon emissions in the sampled countries can be significantly explained by industrialization, tourism import, renewable energy, and non-renewable energy. Contrarily, trade and economic growth are good to explain the dynamics of carbon effusion of the sampled Asian countries in the future but without feedback. It is recommended that policymakers in Asian countries should formulate stringent environmental policies that will encourage industries in these countries to utilize clean energy sources so that economic growth will be achieved simultaneously with carbon neutrality.

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