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This paper examines the effects of extreme temperatures on mortality rates, using random year-to-year variation in temperature based on county-level panel data from China. The analysis finds a robust, U-shaped relationship between temperature and mortality rates, indicating that extremely cold or hot temperatures lead to excess deaths. The heat-related (cold-related) effect is 3.5 times (3.2 times) as large as previous findings that used U.S. data, and it is especially large for the elderly population, mainly due to excess deaths caused by cardiovascular diseases. Applying these results to climate change predictions from Hadley Centre Global Environmental Model shows that by 2061–2080 the annual mortality rate is likely to increase by 14.2% if global greenhouse gas emissions continue to rise throughout the 21st century, the estimated health cost of which is around 0.98 trillion Chinese Yuan per year. The paper also explores households' adaptation behaviors to extreme temperatures. It finds that although urban households adaptively increase energy consumption when they are exposed to cold temperatures and purchase more air conditioners on hot and cold days, rural households are unresponsive to temperature fluctuations. This finding implies that rural people may be more resource constrained and suffer more when extreme temperatures occur. [ABSTRACT FROM AUTHOR]

This paper summarises the methodology and results of work involved in the investigation of energy demand in six Chinese villages included in the SUCCESS Project. The procedures used to collect data associated with local energy demand are explained and the approach to data analysis is explained. Results are provided in terms for delivered energy consumption, as an indicator of energy demand; primary energy consumption, as an indicator of energy resource depletion; and carbon dioxide emissions, as an indicator of global climate change. Similarities and differences between results for this sample of villages are considered. The important causes of differences in results are investigated. [Copyright &y& Elsevier]

To tackle climate change, Chinese government has applied an array of mitigating measures to reduce CO2 emissions. During the 11th Five-year Plan, Chinese government set the emission reduction target policy to reduce energy consumption per unit of gross domestic product (GDP) by 20%. This paper attempts to estimate the effect of this emission reduction target policy on industrial performance from complexity perspective. The result shows more complex industrial structure is related to less coal consumption. In general, emission reduction target policy has a negative effect on the probability of branching into new industries and lower the productivity and profitability of a given industry. However, this negative effect is weaker for more complex industries. Only for industries with very high complexity, emission reduction target policy can improve the performance of an industry rather than exerting a negative effect. Our finding not only helps to design a more effective policy to achieve industrial development strategy, but also provides a potential way to achieve economic growth while reduce the emission of greenhouse gases at the same time. • We investigate the impact of Emission reduction target policy(ERT) on industrial performance from complexity perspective. • We apply the method of reflection to calculate the Economic Complexity of provinces and Industry Complexity of industries. • More complex industrial structure contributes to the coal consumption reduction. • ERT has negative effects on the probability of branching into new industries, lowers the productivity and profitability of a given industry. • ERT has weaker negative effects for more complex industries. [ABSTRACT FROM AUTHOR]