Micro–nanobubbles (MNBs) can generate ·OH in situ, which provides a new idea for the safe and efficient removal of pollutants in water supply systems. However, due to the difficulty in obtaining stable MNBs, the generation efficiency of ·OH is low, and the removal efficiency of pollutants cannot be guaranteed. This paper reviews the application research of MNB technology in water security from three aspects: the generation process of MNBs in water, the generation rule of ·OH during MNB collapse, and the control mechanisms of MNBs on pollutants and biofilms. We found that MNB generation methods are divided into chemical and mechanical (about 10 kinds) categories, and the instability of the bubble size restricts the application of MNB technology. The generation of ·OH by MNBs is affected by the pH, gas source, bubble size, temperature, and external stimulation. And the pH and external stimulus have more influence on ·OH generation in situ than the other factors. Adjusting the pH to alkaline or acidic conditions and selecting ozone or oxygen as the gas source can promote ·OH generation. MNB collapse also releases a large amount of energy, during which the temperature and pressure can reach 3000 K and 5 Gpa, respectively, making it efficient to remove ≈90% of pollutants (i.e., trichloroethylene, benzene, and chlorobenzene). The biofilm can also be removed by physical, chemical, and thermal effects. MNB technology also has great application potential in drinking water, which can be applied to improve water quality, optimize household water purifiers, and enhance the taste of bottled water. Under the premise of safety, after letting people of different ages taste water samples, we found that compared with ordinary drinking water, 85.7% of people think MNB water is softer, and 73.3% of people think MNB water is sweeter. This further proves that MNB water has a great prospect in drinking water applications. This review provides innovative theoretical support for solving the problem of drinking water safety.

Rainfall measurement at high quality and spatiotemporal resolution is essential for urban hydrological modeling and effective stormwater management. However, traditional rainfall measurement methods face limitations regarding spatial coverage, temporal resolution, and data accessibility, particularly in urban settings. Here, we show a novel rainfall estimation framework that leverages surveillance cameras to enhance estimation accuracy and spatiotemporal data coverage. Our hybrid approach consists of two complementary modules: the first employs an image-quality signature technique to detect rain streaks from video frames and selects optimal regions of interest (ROIs). The second module integrates depthwise separable convolution (DSC) layers with gated recurrent units (GRU) in a regression model to accurately estimate rainfall intensity using these ROIs. We evaluate the framework using video data from two locations with distinct rainfall patterns and environmental conditions. The DSC-GRU model achieves high predictive performance, with coefficient of determination (R²) values ranging from 0.89 to 0.93 when validated against rain gauge measurements. Remarkably, the model maintains strong performance during daytime and nighttime conditions, outperforming existing video-based rainfall estimation methods and demonstrating robust adaptability across variable environmental scenarios. The model's lightweight architecture facilitates efficient training and deployment, enabling practical real-time urban rainfall monitoring. This work represents a substantial advancement in rainfall estimation technology, significantly reducing estimation errors and expanding measurement coverage, and provides a practical, low-cost solution for urban hydrological monitoring.

To mitigate the incidence of waterlogging to livelihoods and property security, a combination of management measures has been necessary to achieve optimal benefits, reducing the risk caused by waterlogging to the development of the urban ecology. Thus, this study aims to analyze the sensitivity and sensitivity range of management measures under different rainfall conditions, focusing on establishing a foundation for their combined implementation. Based on different rainfall scenarios, the modified Morris method is employed to assess the sensitivity of key factors and subsequently determine their respective sensitivity ranges. The findings reveal that the sensitivity rankings for total overflow volume and maximum pipe flow are as follows: pipe volume per hectare (PV-H), proportion of impervious area (P-Imperv), and slope. Additionally, analyzing the variation pattern of sensitivity with factors highlight the high sensitivity ranges. As for total overflow volume, a very high sensitivity is observed when the P-Imperv ranges from 36.8% to 82.7% (Niujiaolong community) and from 82.7% to 94.5% (Zhuyuan community). Similarly, when PV-H is less than 148 (Niujiaolong community) and 89.6 (Zhuyuan community), the sensitivity of PV-H to total overflow volume is very high. Nevertheless, the slope had a lower influence on the sensitivity in the study areas. These findings provide a complete analysis of the management measures sensitivity, which can be valuable for creating optimal urban waterlogging management systems.

Micro nano bubbles (MNBs) can generate ·OH in situ, which provides a new idea for the safe and efficient removal of pollutants in water supply systems. However, the difficulty in obtaining stable MNBs causes the low efficiency of ·OH generation, which makes the inability to guarantee the removal efficiency of pollutants. This paper reviews the application research of MNBs technology in water security from three aspects: the generation process of MNBs in water, the generation rule of ·OH during MNBs collapse, and the control mechanism of MNBs on pollutants and biofilms. We found that MNBs generation methods are divided into chemical and mechanical (about 10 kinds) categories, and the instability of bubble size restricts the application of MNBs technology. The generation of ·OH by MNBs is affected by pH, gas source, bubble size, temperature, external stimulation. And pH and external stimulus have more influence on ·OH generation in situ than other factors. Adjusting pH to alkaline or acidic conditions and selecting ozone or oxygen as the gas source can promote the ·OH generation. MNBs’ collapse also releases a large amount of energy, which the temperature and pressure can reach 3000K and 5Gpa respectively, making it efficient to remove ≈90 % of pollutants (i.e., trichloroethylene, benzene, and chlorobenzene). The biofilm can also be removed by physical, chemical, and thermal effect. MNBs technology also has great application potential in drinking water, which can be applied to improve water quality, optimize household water purifiers, and enhance the taste of bottled water. Under the premise of safety, let people of different ages taste, finding that compared with ordinary drinking water, 85.7 % of people think MNBs water is softer, 73.3 % of people think MNBs water is sweeter. This further proves that MNBs water has a great prospect in the drinking water application. This review provides innovative theoretical support for solving the problem of drinking water safety.