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Reasonable allocation of carbon allowances and determination of coverage in the carbon market are essential to the realization of the emissions reduction goal. Using China as an example, we propose a multi-criteria allocation scheme based on the principle of equity, efficiency and feasibility, considering carbon abatement costs and carbon leakage risks. An improved zero-sum gains-data envelopment analysis model in accordance with China’s new carbon intensity target in climate ambition is used for allowance allocation. Subsequently, the sectoral coverage choice of the carbon market is proposed. We obtain an optimal reallocation scheme after five iterations. The results show that the allocation method in this study can better promote the carbon market to reduce emissions at a lower cost while preventing carbon leakage to a certain extent. Based on the contribution to the overall emission reduction, the emission reduction costs and carbon leakage risks, we further classify the sectors into three categories. With China as an example, these findings lay a scientific basis for China to achieve its climate ambition through the carbon market, and also have global implications in regard to developing a more scientific allocation scheme, especially for carbon markets in emerging and developing countries.

Carbon emissions trading is a major innovation in the practice of using market mechanism to control and reduce greenhouse gas (GHG) emissions and promote green and low-carbon development. It is an important way to achieve China’s carbon peaking and carbon neutrality goals (the “dual carbon” goals) at a relatively low cost. Starting late and having gone through three development stages, China’s national carbon market has entered a new stage. However, given the problems such as incomplete institutional, regulatory and carbon emissions verification systems, less balanced and vibrant market, limited transaction entities and trading products, and lack of voice due to insufficient participation in relevant international affairs, continuous efforts are still required to further improve this market by deepening reform, strengthening capacity building and increasing international cooperation.

On the scientific basis, the carbon sink estimation of wetland was summarized up, that is stock-difference method and gain–loss method as a fundamental approach. The major issues when those methods were applied in that estimation had been raised up for attention to be paid. Based upon the science achievements, the research approaches and policy foundation for market trading about the wetland carbon sink had been analyzed for that sink sustainability. It was concluded that the decomposition reduction of wetland plant material and rewetting and suitable restoration of wetland are essential for its sink conservation. Nowadays, China has already set the wetland conservation for its carbon sink sustainability as a part of the national goal in the carbon peaking road-map, further elaboration on the policymaking should be taken for the wetland sink conclusive into the voluntary market and as an offset of the partly compulsory reduction of emission.

Carbon market has attracted the attention from all over the world. This paper applies several statistical methods to analyze the price volatility properties of the Europe Union Emission Trade Scheme, and develops an integrated VEC-MVGARCH model to investigate the dynamic nonlinear relationships of EUA and CER markets under the EU-ETS. Empirical results indicate that both returns and volatilities are nonlinearly, asymmetrically and dynamically related. Returns of EUA and CER are cointegrated in the long run with deviations adjusted by their error correction mechanism. Significant effect of return spillover is detected and EUA plays the leading role in the short-run dynamics. Moreover, volatilities of EUA and CER are asymmetrically linked. Volatility spillover is detected and EUA reacts to new information first and transmits it to CER, leading the dynamics of market volatility. The findings of EUA and CER relations may help traders optimize carbon portfolio and manage climate risks.