Against the backdrop of energy conservation, emission reduction and green low-carbon development, traditional syngas production processes are plagued by high energy consumption and excessive greenhouse gas emissions. In contrast, the photocatalytic CO2reduction technology, driven by solar energy, enables the conversion of CO2into syngas. It combines the values of environmental protection and resource recycling, thus becoming a current research hotspot. In the design of high-efficiency single-atom catalysts (SACs) for photocatalytic CO2reduction, the microenvironment design of single-atom metal sites is of crucial importance. Based on this, in this work, a series of Co-coordinated COF catalysts named Triazine-COF-Co-Cl were synthesized to regulate the Co-coordination microenvironment for enhancing syngas production via photocatalytic CO2reduction. Among them, the Triazine-COF-Co-AA catalyst with the best performance achieved a syngas production rate of 381.7 mmol g−1h−1, and the H2/CO molar ratio could be continuously adjusted in the range of 1-3, which is sufficient to cover the commonly used syngas ratio range in industry. This paper improves the performance of COF-based photocatalysts for syngas production via CO2reduction through the regulation of Co-coordination environment, and provides ideas and certain data support for the research on solving energy and environmental problems and reducing CO2emissions.

In typical mountainous coal mines in Yunnan, Guizhou and Sichuan provinces, the complex "air-ground-ground" collaborative monitoring data has established a classification method that includes indicators such as static geological background, dynamic deformation and hydrogeochemical data. Subsequently, the research revealed the evolution mechanism of the combined disaster chain of surface deformation and sudden water outburst in old mines, and established a three-level early warning indicator system of background, status and impending disaster. The application in a certain mining area in Liupanshui, Guizhou Province demonstrated that this system can effectively identify high-risk areas, with the coincidence rate of identifying "unstable areas" exceeding 85%, and the physical mechanism of water chemical indicators was verified through hydrogen and oxygen isotope analysis. This integrated system provides a systematic technical solution for risk management and disaster prevention and mitigation in mining areas with similar complex geological conditions.

Magnesium silicate hydrate cement (MSHC) is considered a promising low-carbon alternative to ordinary Portland cement because of its lower calcination temperature and comparable mechanical performance. However, its application in reinforced concrete is limited by the corrosion risk of embedded steel, mainly associated with the relatively low alkalinity of the pore solution. This review summarizes the current understanding of the corrosion behavior and mechanisms of steel reinforcement in MSHC, with emphasis on passive film stability, chloride attack, and carbonation effects. Common evaluation methods, including electrochemical techniques and microstructural characterization, are also discussed. Existing studies indicate that although MSHC exhibits a relatively dense matrix and low chloride transport capacity, its weaker alkaline reserve reduces the stability of steel passivation compared with ordinary Portland cement. Current protection strategies mainly rely on modifying pore solution chemistry and improving interfacial conditions. Finally, key research needs are identified to support the durable application of reinforced MSHC in low-carbon construction.

The evaluation of the geological environment carrying capacity of mines is crucial for achieving sustainable development and risk management of mines. This study proposes a spatio-temporal evaluation model that integrates remote sensing ecological indices and geological safety indices to take into account the surface ecological status of the mining area and underground geological safety. This method is based on the theoretical framework of "state-pressure-response", integrates multi-source remote sensing, InSAR, geology and other multi-temporal data, constructs RSEI through principal component analysis, builds GSI through analytic hierarchy process, and determines the weights using entropy weight method for comprehensive evaluation, generating the spatial distribution of carrying capacity. Taking the Pingshuo mining area in Shanxi Province as an example, the application of the model (from 2015 to 2024) shows that the high carrying capacity vulnerable areas present a "point-line-plane" composite feature, which is highly correlated with mining activities and structural zones. The verification indicates that the overall accuracy of the model is 86.4%, and it can identify 35% of the emerging deformation and ecological degradation risk areas that were underestimated by traditional methods, providing an effective spatialization tool for dynamic monitoring and precise control of the mining area environment.