Chun-Ai Ma

In carbon capture and storage (CCS) systems, the wellbore serves as a critical connecting channel between CO₂ surface capture facilities and underground storage formations. Accurate prediction of the temperature, pressure, and physical properties of CO₂ fluid within the wellbore is essential for its safe sequestration. In this study, a coupled temperature–pressure-phase prediction model for CO₂ injection wells is established based on the conservation laws of mass, energy, and momentum, combined with the PR-TWU equation of state. The maximum errors in temperature and pressure for the CO₂ injection case well are only 4.57% and 2.05%, respectively, verifying the accuracy of the model. The distribution and variation in temperature, pressure, and physical property parameters in the CO₂ injection wellbore are systematically investigated. The results show that with increasing well depth, the temperature, pressure, and flow velocity of CO₂ fluid exhibit an increasing trend, while its density and viscosity gradually decrease. During CO₂ injection, the well depth at which the CO₂ phase transition occurs is closely related to the critical temperature of CO₂ (31.04 °C). Wellbore pressure is mainly controlled by injection pressure, whereas injection temperature and injection rate are the key parameters affecting wellbore temperature and CO₂ phase transition. The findings can provide a theoretical basis for the optimization of injection parameters and the integrity evaluation of CO₂ sequestration injection wells.

As a major resource region, Xinjiang is both China’s energy security base and an important hub connecting Asia and Europe. Following the country’s call for carbon emission reduction, the Xinjiang government proposes to accelerate the construction of eight major industrial clusters in 2023. The concept of sustainable development is also reflected in the industrial clusters in areas such as new energy. In this study, we combined panel data from 14 regions and cities in Xinjiang from 2006 to 2020 and analyzed the synergy between the development of industrial clusters, carbon emissions, and economic growth using a coupling coordination degree model. Subsequently, we used the super-efficiency slack-based measure (SE-SBM) and Dagum’s Gini coefficient to analyze the spatial disequilibrium of efficiency measures and efficiency cases. The results show the following: (1) Overall, the industrial clusters, carbon emissions, and economic growth in the 14 regions and cities of Xinjiang are not well coordinated. The best reported level has been medium coordination, but there exists a certain degree of correlation among the three. (2) Low-carbon economic efficiency under the influence of industrial clusters in the 14 regions and cities shows significant regional differences. The regions and cities with low-carbon economic efficiency greater than 0.8, which is significantly better than the other regions in terms of efficiency, are all located in northern Xinjiang. (3) During the study period, the overall regional difference in low-carbon economic efficiency under industrial clusters in Xinjiang decreased from 0.183 to 0.17. However, the regional differences were still large. The conclusions indicate that policies for industrial clusters in Xinjiang can promote industrial development, and there may be a correlation between them and the low-carbon economy. This will effectively contribute to local sustainable development. However, overall regional differences are significant, and the degree of coordination is low. Therefore, we suggest that the government can share the advantages of development by constructing cross-regional cooperation platforms. At the same time, the Xinjiang government should make full use of the rich local wind and solar energy resources and explore a low-carbon path toward transforming the traditional energy industry. It can also be seen that industrial clusters in Xinjiang can effectively promote local sustainable development.

Exploiting a comparative advantage through resource endowment is a way to promote the transformation and upgrading of enterprises and high-quality economic development. Based on resource-based theory, this paper takes the listed companies of China’s manufacturing industry as a sample and classifies them into leading, potential, catching-up, and exiting enterprises according to the abundance of financial and human resources. In terms of the research perspective, this paper adopts resource abundance as the starting point to explore its impact on enterprise transformation and upgrading and incorporates technological innovation into the framework to investigate its transmission mechanism. The results indicate that the resource abundance of enterprises directly promotes the transformation and upgrading of enterprises. Notably, the mechanism identification test suggests the following. (1) From the perspective of innovation investment, innovation investment intensity is an important channel for manufacturing companies to transform and upgrade. (2) From the perspective of innovation direction, higher levels of resources allow leading enterprises to accelerate transformation and upgrading through product and process innovation. In contrast, catching-up enterprises tend to foster product innovation rather than process innovation to transform and update, while potential enterprises are likely to foster process innovation to transform and update rather than product innovation. On the other hand, the path of transformation and upgrading through product or process innovation is obstructed for the exiting enterprises. (3) From the perspective of innovation output, all but the exiting enterprises can be transformed and upgraded by increasing their innovation output. Overall, considering the impact of corporate innovation behavior, this research offers new insights into the relationship between resource abundance and transformation and upgrading, and it provides inspiration for promoting transformation and upgrading in Chinese manufacturing enterprises.

Balancing sustainable economic growth and environmental protection in developing countries is an important way to mitigate climate change. Based on panel data from nine provinces along the Silk Road Economic Belt between 2004 and 2021, this paper takes Chongqing, a pilot city for carbon trading rights, as the experimental group and the remaining eight provinces as the control group; we mainly analyze the impact of the carbon emissions trading policy on Chongqing’s carbon emissions and economic development after its implementation in 2013 using the difference-in-differences method (DID) and propensity score matching difference-in-differences method (PSM-DID). Then we use the synthetic control method (SCM) to test its robustness. The results showed that while maintaining the economic development speed, carbon trading helps to reduce carbon emissions. In addition, we also found that the economic activity effect and the energy intensity effect are the mediating effects of the carbon emissions reduction. Finally, taking the policy effect of the carbon emissions trading in Chongqing as a reference, this article confirmed the importance of aligning the carbon trading pathway with targeted green policies from the government. The government should drive the establishment of a regional carbon market in the nine provinces along the Silk Road Economic Belt, which could help to achieve sustainable development.