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Objective The development of urban underground space in China is showing a trend towards diversification, depth, and complexity, making it challenging to diagnose and decision-making on causative factors through multi-dimensional data integration. Therefore, there is a need to carry out research on the next generation comprehensive operation monitoring system. Method The current status of existing underground infrastructure operation monitoring systems is introduced. Based on disaster events in urban metro and underground complex, the integration of smart cities with IoT (internet of things) technology is proposed. Through data fusion with existing monitoring technologies, research is conducted on the integration of real-time perception data, control systems, and decision-making mechanisms related to urban underground infrastructure operation comprehensive monitoring platforms and existing monitoring systems. Result & Conclusion Multi-dimensional perception data fusion and unified management are achieved through unified interface bus and multi-protocol conversion technology. By integrating with existing monitoring system platforms, the intelligent identification of underground infrastructure operating status, intelligent classification and identification of various hazard sources are realized to provide intelligent diagnosis and analysis decision support. Unified security authentication technology enables the control of operator levels and dynamic configuration management of permissions.

In April 2023, a major dust storm event in Lanzhou attracted widespread attention. This study provides a comprehensive analysis of the causes, progression, and dust sources of this event using multiple data sources and methods. Backward trajectory analysis using the HYSPLIT model was employed to trace the origins of the dust, while FY-2H satellite data provided high-resolution dust distribution patterns. Additionally, the MAIAC AOD product was used to analyze Aerosol Optical Depth, and concentration-weighted trajectory (CWT) analysis was used to identify key dust source regions. The study found that PM10 played a dominant role in the storm, and the AOD values during the storm in Lanzhou were significantly higher than the annual average, highlighting the severe impact on regional air quality. Key meteorological conditions influencing the storm's occurrence were analyzed, including the formation and eastward movement of a high-potential ridge, convection driven by diurnal temperature variations, and surface temperature increases coupled with decreased relative humidity, which together promoted the generation and development of dust. Backward trajectory and dust distribution analyses revealed that the dust primarily originated from Central Asia, western Mongolia, Xinjiang, and Gansu. From the 19th to the 21st, the dust distribution showed similarities between day and night, with a noticeable increase in dust concentration from night to day due to strong vertical atmospheric mixing. To mitigate the impacts of future dust storms, this study highlights both short-term and long-term strategies, including enhanced monitoring systems, public health advisories, and vegetation restoration in key source regions. Strengthening regional and international cooperation for transboundary dust management is also emphasized as critical for sustainable mitigation efforts. These findings are significant for understanding and predicting the causes, characteristics, and environmental impacts of dust storms in Lanzhou and the Northwestern region. [ABSTRACT FROM AUTHOR]

As natural isotope tracers, δ18O and δ2H have been widely applied to examine the water uptake of plant root, but the various stable isotope mixing models may lead to different explanations. To understand the influence of models, here we selected a typical plant Caragana korshinskii Kom. in northeastern Tibetan Plateau, and analyzed the stable water isotope compositions in plant xylem and potential sources including precipitation and soil water. Three stable isotope mixing models, i.e., IsoSource, MixSIR and MixSIAR were used, and then the differences in the proportional contributions of various water sources for plant root were examined. The results showed that the IsoSource and MixSIR were generally similar, while the MixSIAR were significantly different. Although the proportional contributions of each water source were different due to different algorithms, the water source which contributed maximum proportion was the same for all models. This study provides a scientific reference for the selection of models for the study of plant water use strategies in similar study areas, i.e., the most dominant water source can be identified regardless of the choice of model. [ABSTRACT FROM AUTHOR]