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Renewable energy development is a major response to address the issues of climate change and energy security. The utilization of renewable resources, however, highly depends on the climate conditions, which may be impacted in the future due to global climate change. Based on literature analysis, this paper presents a general framework for renewable energy vulnerability assessment and applies grey cluster analysis method to demonstrate the features of vulnerability, and then employs the Simple Additive Weighting Approach to address the multiple-attribute decision problems of vulnerability assessment in China. The categorized results imply that the proposed index system is suitable for decision-making analysis and comparative analysis of renewable energy vulnerability to climate change in China. In terms of exposure part, the cluster results are complex and varied due to the unique combination of natural factors, social factors and the energy structure. In the sensitivity section, the results are presented on the distribution of areas rich in hydropower, wind power and solar energy potential. Moreover, the main results of this study are the higher renewable energy vulnerability of the poorer regions of China to climate change and the relative higher importance of adaptive capacity building in vulnerability management. Finally, policy recommendations on regional renewable energy vulnerability management are also made. [ABSTRACT FROM AUTHOR]

Climate change and global warming have become severe environmental issues of global concern, and many countries have promulgated renewable energy development planning to achieve the targets of carbon emission reduction and sustainable development. Accelerating the development of renewable energy technology innovation is one of the major measures to stimulate the utilization of renewable resources. This paper analyzes the impact of renewable energy technology innovation on carbon intensity in 30 Chinese provinces from 2000 to 2015. Using the recent panel estimation methods that take cross-section dependence and slope heterogeneity into account, the results show that for every 1% increase in the innovation level of renewable energy technology, carbon intensity was significantly reduced by 0.051%. Specifically, renewable energy technology innovation does not affect carbon intensity in the short term. But in the long term, the influences are negative and significant. Moreover, the environmental benefits are most evident in eastern China, while there is no significant influence on the western regions. Finally, this paper provides some policy implications to further discuss the impetus of renewable energy technology innovation. • Renewable energy technology innovation can significantly reduce carbon intensity. • The influences of renewable energy technology innovation will change over time. • There exist differences in the innovation effects in different Chinese regions. [ABSTRACT FROM AUTHOR]