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Added global carbon emissions have mainly come from China and India since 2012, which indicates importance of two countries in curbing global CO 2 emissions. Thus, their respective mitigation lessons have more realistic significance in developing more effective mitigation strategy. This study compared the dynamic evolution of their CO 2 emissions and driving factors behind changes, in order to find similarities and differences of two countries, and provide available policy implications to further reduce carbon emissions. Firstly, both China's and India's carbon emissions have been increasing during 2000-14: 3.4–9.9 Gt and 0.9–2.0 Gt, respectively. However, tendency of two countries varied differently: growth of China 's CO 2 have slowed down after the 2008 financial crisis, while India 's emissions were still accelerating at a high level on account of growing share of carbon-intensive energy in the whole energy structure. From the national and sectoral perspectives, both trends of carbon emissions from two countries have been analyzed. According to structural decomposition analysis, efficiency gains and slowdown of economic growth in China contributed to most decline of CO 2 but both production and consumption structures urged emissions up, while structure effects in India slightly reduced its CO 2 but low emission efficiency and expansion of trade scales caused growth of emissions. On this basis, firstly, China should optimize production structures by upgrading industries, while India should promote energy transformation and improve energy efficiencies. Secondly, strengthening cooperation and communications with developed countries with advanced technology and experience may make more progress in climate change for two countries. Experience and lessons of emission reduction deriving from the two would also provide references for other regions. Image 1 • Investigating CO 2 emissions of China and India for 2000–2014. • Explore main sources and sectors that dominated CO 2 emissions. • Improving efficiency and optimizing energy structure offset China's emission growth. • Optimizing its consumption structure offset India's emission growth. • Optimizing their consumption structure should be considered in China and India. [ABSTRACT FROM AUTHOR]

A boom in renewable energy consumption as a percentage of final energy consumption (REC) has a significant impact on cleaner production and environmental sustainability. However, studies on REC as for an individual country-case and panel case approach for top emitters are rare. Against this backdrop, this study investigates the long-run drivers of REC by using a time series data from 1990 to 2015. The FMOLS-grouped results indicate that economic growth and trade openness increase REC whereas population growth has a negative but significant impact on REC. To check for causal links, the innovating accounting approach using variance decomposition analysis is applied. The results show that there is a unidirectional causality running from economic growth, trade openness, and population growth to REC. Further, the predictive accuracy of the FMOLS based econometric output and the bi-directional long short-term memory (Bi-LSTM) is analyzed. The Bi-LSTM formulated algorithm outperformed the econometric output. The Bi-LSTM is utilized to forecast REC to the year 2030. The output from the Bi-LSTM shows that China, the US, India, the Russian Federation's, and Japan's REC will hit ∼11.3395, ∼11.1245, ∼34.6969, ∼2.9097, and ∼7.4859, respectively. The US and Japan's REC levels will increase while that of China, India, and Russia Federation will decrease. As a policy implication, new policy directives for China, India, and the Russian Federation are required to boost REC levels. [ABSTRACT FROM AUTHOR]