Although the emission reduction and innovation effects of carbon emissions trading have attracted considerable interest among academics and policy makers, there is a lack of empirical research on how carbon trading pilots in China promote regional green innovation. Therefore, we measured the green innovation efficiency of 30 provinces and cities in mainland China from 2005 to 2018, using selected panel data within a super-efficient SBM model that incorporated undesirable outputs. We used a double differential model to evaluate the impacts of carbon trading policies on the green innovation efficiency of seven carbon trading pilot regions. These impacts were confirmed using the double differential propensity score matching method. Our findings were as follows. (1) The implementation of carbon trading policies has a significant and continuous effect of promoting and improving green innovation efficiency in the pilot areas. (2) Carbon trading induces technological innovation effects, enabling green innovation potential to be realized. Regional green innovation efficiency is further improved through energy substitution and structural upgrading effects and subsequently through all three of the above effects. (3) The synergy between the three major effects of carbon trading policies amplifies regional green innovation efficiency. Therefore, the Chinese government should accelerate its efforts to develop and improve carbon markets, promote carbon trading policies, and actively foster synergy among the three effects to achieve green and sustainable regional development.

CO₂ emission resulted from fossil energy use is threatening human sustainability globally. This study focuses on the low-carbon transition of Hebei’s coal-dominated energy system by estimating its total end-use energy consumption, primary energy supply and resultant CO₂ emission up to 2030, by employing an energy demand analysis model based on setting of the economic growth rate, industrial structure, industry/sector energy consumption intensity, energy supply structure, and CO₂ emission factor. It is found that the total primary energy consumption in Hebei will be 471 and 431 million tons of coal equivalent (tce) in 2030 in our two defined scenarios (conventional development scenario and coordinated development scenario), which are 1.40 and 1.28 times of the level in 2015, respectively. The resultant full-chain CO₂ emission will be 1027 and 916 million tons in 2030 in the two scenarios, which are 1.24 and 1.10 times of the level in 2015, respectively. The full-chain CO₂ emission will peak in about 2025. It is found that the coal-dominated situation of energy structure and CO₂ emission increasing trend in Hebei can be changed in the future in the coordinated development scenario, in which Beijing-Tianjin-Hebei area coordinated development strategy will be strengthened. The energy structure of Hebei can be optimised since the proportion of coal in total primary energy consumption can fall from around 80% in 2015 to below 30% in 2030 and the proportions of transferred electricity, natural gas, nuclear energy and renewable energy can increase rapidly. Some specific additional policy instruments are also suggested to support the low-carbon transition of energy system in Hebei under the framework of the coordinated development of Beijing-Tianjin-Hebei area, and with the support from the central government of China.

Taking the system dynamics model as the modeling technology and Tianjin as the research area, the DPSIR analysis framework is used to construct the Tianjin green development system innovation and policy simulation model. The model consists of three subsystems, including the economic population subsystem, the resource energy subsystem, and the environmental assessment subsystem. This study designed three policy scenarios, namely, the extensive-adjustment policy scenario, the economic transition priority policy scenario, and the pollution governance priority policy scenario. Taking the data of Tianjin City in 2018 as a reference sample, the simulation results of the city from 2020 to 2035 were obtained. The simulation results show that in the aspect of economic aggregate growth and urbanization, the economic transformation priority policy scenario is optimal; in terms of energy supply, all three scenarios show a negative effect; in the aspect of air pollution control, the pollution control priority policy scenario is optimal. In terms of carbon emissions and water pollution control, the economic transformation priority policy scenario is the best. According to the simulation results, this paper puts forward corresponding policy recommendations for the reference of Tianjin green development system innovation.

New infrastructure construction is emerging as a key driver for achieving carbon peaking and carbon neutrality in the digital economy era, fostering green, low-carbon, and high-quality economic and social development. Using panel data from 30 provinces (autonomous regions and municipalities) in China from 2007 to 2022, this study measures indicators of new infrastructure development and empirically examines its synergistic effects on pollution reduction and carbon mitigation from the perspective of innovation factor misallocation. The findings indicate that: (1) New infrastructure significantly enhances coordinated governance in pollution reduction and carbon mitigation. This conclusion remains robust after a series of endogeneity and stability tests. However, the synergy between pollution reduction and carbon mitigation is not immediately observable. Only after the new infrastructure development surpasses certain "thresholds" does its effect on pollution and carbon reduction become evident. (2) Mechanism analysis reveals that new infrastructure alleviates the misallocation of R&D personnel, thereby promoting pollution reduction and carbon mitigation. However, the mechanism based on the misallocation of R&D capital has yet to fully manifest its effects. Factors such as R&D personnel mobility, human capital levels, and skill matching are effective in addressing R&D personnel misallocation and unlocking the benefits of technological innovation through new infrastructure, whereas government funding does not show a significant improvement in these outcomes. (3) Further analysis shows that new infrastructure can effectively reduce the "rebound" in carbon emissions currently. Nevertheless, in terms of spatial correlation, the overall impact of new infrastructure on coordinated pollution reduction and carbon mitigation exhibits negative externalities. The conclusions of this study provide a viable pathway for achieving the synergistic effects of pollution reduction and carbon mitigation, contributing to the "dual carbon" goals. These findings also offer empirical support for local governments in actively planning and advancing strategic layouts for new infrastructure.

This study explains and demonstrates whether China has the capability to avoid the Middle Income Trap. The 19th National Congress of CPC report points out: by 2035, China will become an international leader in innovation. At present, China is in the juncture of changing the mode of development, optimizing the economic structure and transforming the growth momentum. The juncture means that it is possible to be stagnation or retrogression of national economy as the national ability of innovation is insufficient, then sticking in the middle-income trap (MIC) for a long time. In this paper, we used the TFP to prove that the input-output ratio of different regions of China, with the per capita GDP and carbon emissions are fitting again, dividing China into optimized zones and non-optimized zones. It can be seen from the results that the optimized zones have achieved the peak of carbon emission and had relative advantages in green innovation. However, if China wants to achieve her overall carbon emissions and get out of the middle income trap, she must optimize the development zones to spillover technologies and talents.