Tao Wang

This study employs panel data for 275 Chinese cities from 2011 to 2021. Water use efficiency is measured as an aggregate city-level indicator via stochastic frontier analysis, while the level of digital economy development is quantified using principal component analysis. We then employ the system generalized method of moments to investigate the causal relationship between the digital economy and urban water use efficiency, and further identify industrial structure upgrading as the mediating role through which the digital economy affects water efficiency. The main findings are as follows: (1) The digital economy has a significant positive impact on urban water use efficiency. (2) Regional heterogeneity analysis shows that the digital economy presents a stronger positive effect on water use efficiency in eastern regions than in central and western regions. (3) Exploratory mechanism analysis indicates that industrial structure upgrading serves as the mediating role through which the digital economy improves urban water use efficiency. Based on the empirical findings, this paper draws targeted policy implications.

With the continuous advancement of industrialization in China, industrial wastewater discharge has become a critical factor influencing water environmental quality, public health, and the long-term sustainability of regional development. This study systematically examines both the direct and spatial spillover effects of industrial wastewater on disease incidence. Based on panel data from 30 provincial-level regions in China over the period 2011–2020, a composite incidence index of four waterborne infectious diseases is constructed using the entropy weight method, and the Spatial Durbin Model (SDM) is employed to capture both local and cross-regional effects. The results show that industrial wastewater discharge significantly increases disease incidence and exhibits clear spatial spillover effects, suggesting that the associated health risks may extend beyond local boundaries. Moreover, the analysis suggests that the “Water Ten Plan” reduced both local effects and regional spillovers, highlighting the value of stricter discharge control and coordinated basin-level governance for sustainable regional development. Overall, this study uncovers the spatial health externalities of industrial pollution and provides empirical support for integrated policy approaches linking environmental governance with public health protection.

Fire safety in high-rise talent apartments, which is vital for safeguarding strategic human resources, was investigated to enhance evacuation resilience. A coupled fire-evacuation model was established using PyroSim and Pathfinder. This study analyzed multi-factor management strategies, including occupant vertical distribution, evacuation speed, evacuation priority settings, panic psychology, and guide intervention. Additionally, an Artificial Neural Network (ANN) model was developed using simulation data obtained under non-panic conditions to predict evacuation time and explore intelligent algorithms. Results show that the evacuation stairwells are the primary bottlenecks. Panic psychology significantly reduces evacuation efficiency, with severe panic increasing total evacuation time by up to 71.1%. The combined strategy CS4, integrating Pyramidal Vertical Distribution (VD7) and Organized Segmented Speed Control (ES6), reduced evacuation time by 17.42%. Guide intervention effectively mitigates the negative impact of panic. The ANN model achieved a coefficient of determination (R²) of 0.8695, confirming its predictive capability. Visibility was identified as the key parameter determining the Available Safe Egress Time (ASET). This study demonstrates that an integrated “hard–soft combination” strategy, complemented by intelligent modeling, offers an effective approach to building a resilient evacuation system for high-rise talent apartments.

Rapid urbanization in China has overwhelmed traditional drainage systems, resulting in frequent flooding and water pollution in densely populated urban areas. This study focuses on the East Lake core area of Wuhan, proposing a deep tunnel drainage system to improve sewage storage and conveyance capacity. A pilot-scale pipe model was employed to determine the critical non-silting velocity for full-pipe sewage flow. Based on projected dry-season inflows and intercepted combined sewer discharges, the design capacities for pumping stations and pretreatment facilities were defined. A three-dimensional gas–liquid two-phase numerical model was used to simulate inflow shaft hydraulics at Erlangmiao, Luobuzui, and Wudong pretreatment stations. Simulation results confirm that all shafts meet energy dissipation and ventilation requirements, with uniform flow and velocity distributions that could be obtained by a vortex-type shaft. The system not only mitigates regional environmental challenges but also shows significant social, environmental, and economic benefits. Overall project design, applied methodology, simulation study, and outcomes could provide a valuable reference to deep tunnel drainage design and research.