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On December 19, 2017, China's National Development and Reform Commission (NDRC) announced the official launch of the much-anticipated national emissions trading system (ETS), which is a critical period for the transition from the eight carbon emission trading pilot projects to the national market at this stage. Comprehensively evaluating the efficiency of China's eight carbon trading pilots is vital for strengthening the construction of its national ETS. This paper investigates the weak-form efficiency of eight carbon trading markets in China. We use a series of variance ratio tests to identify the efficiency from the market set up to the May 4, 2018, of all markets. The results indicate that the majority of the carbon trading markets are inefficient and only Beijing, Hubei, and Fujian markets are efficient. The China's carbon trading market is gradually maturing and implemented. In addition, we analyze the factors have impact on the market efficiency. It shows that the liquidity, volume, allocation allowance, and transparency in information are significant factors; meanwhile, the regional policy and cross cooperation also are important factors. Finally, this paper puts forward several policy recommendations on how to strengthen the effectiveness of China carbon trading markets based on the empirical results.

To clarify the current situation of haze emission and governance in China, the study analyzed the characteristics of spatial correlation structure and synergistic governance development of the haze emission of 31 provinces in China, based on social network analysis and distance synergistic model. The results indicated that the spatial correlation of inter-provincial haze emission in China presented a typical "central-marginal" network structure. The provinces in the network center were mostly located in the Beijing-Tianjin-Hebei region and the Yangtze River Delta region. The synergistic governance development of haze in China showed a lower level and fluctuating upward trend. In addition, the increase of network density, the decline of network grade, and the decrease of network efficiency would all improve the level of synergistic governance development. Therefore, focusing on the haze of the central provinces, improving the network structure, and improving regional synergy are important measures for effective governance. This paper improves the previous research model, considers the impact of economic and demographic factors on haze pollution, establishes a new model for analyzing spatial correlation structure of haze and calculating the synergistic governance level of haze, and designs feasible ways to raise the synergistic governance level of haze in China.

Large amounts of air pollutants emitted from massive coal combustion result in the air quality deterioration and threaten public health in China. To improve air quality, the Chinese government released the coal cap policy to reduce coal consumption. So it is important and necessary to understand the possible environmental impact and relevant health benefits from the coal cap policy. The purpose of this paper is to quantify the air quality improvement and to evaluate the health benefits from the implementation of the coal cap policy, with the Beijing-Tianjin-Hebei (BTH) region as the study area. The results showed that the emissions of SO 2 , NOx, CO, VOCs, PM 10 , and PM 2.5 could be reduced by 20-40% in the BTH region in 2020 and all pollutants from industrial boilers notably decreased. Under the coal cap policy, the PM 2.5 concentration in the whole region would fall by 11.27%, and the total economic benefit from health impacts could achieve 26.61 (13.29 to 39.14) billion RMB (3.9 billion USD) in the BTH region in 2020, accounting for 0.43% (0.21 to 0.63%) of regional GDP in 2013. This study demonstrated the quantification of environmental effect and health benefit from the coal cap policy, which could be used for the complete cost-benefit analysis and provide the sufficient support for policy makers to implement the coal cap policy in the BTH region and other areas of China.