Zhichao Wang

Understanding the motion parameters of floating ice is very important for characterizing the ice water dynamics of rivers during freezing periods. Due to the low spatiotemporal resolution of satellite images, limited observation range of unmanned aerial vehicles, and deformation of shore-based camera images, it is difficult to simultaneously quantify the translational and rotational motion characteristics of floating ice and long-distance transportation. This study used the unmanned aerial vehicle GPS joint observation method to observe and obtain various motion parameters such as local translation, rotation, and long-distance transportation in the curved section of the upper reaches of the Yellow River and the straight section of the middle reaches of the Yellow River during the winter of 2024–2025 under conditions of ice density of 50–90%. The velocity field obtained by the drone shows an average ice velocity of 1.27 m/s at the bend and 1.18 m/s in the straight section, with lateral velocity gradients of −0.245 to 0.050 s⁻¹ and −0.141 to 0.222 s⁻¹, respectively. The angular velocity of a single floating ice block is 0.008–0.016 rad/s at bends and 0.010–0.036 rad/s in straight sections. The angular velocity is positively correlated with the local shear strength, and the rotation direction is consistent with the sign of the velocity gradient. GPS tracking provides long-distance transportation trajectories, and the average difference between the speeds obtained by GPS and drones is 0.10 m/s, confirming the reliability of speed estimation based on drones. These results indicate that integrated unmanned aerial vehicle GPS observation can quantitatively characterize local floating ice movement and long-distance floating ice transport behavior, providing on-site parameters for river ice water dynamics research and hazard assessment, and has the potential to be applied to rivers in other cold regions.

Quantitatively analyzing the factors influencing the horizontal migration of microplastics (MPs) in water bodies and understanding their movement patterns are crucial for explaining and predicting their transport principles and final destinations. This study used nearly spherical polyethylene (PE), polypropylene (PP), and polystyrene (PS) MPs as experimental subjects. By tracking their motion characteristics through video recording, we established relationships among the Reynolds number (Re), MP density, and floating velocity. The results showed that the Re and MP density jointly affect the horizontal drift of MPs. The horizontal floating velocity of MPs significantly increases with the increase in the Re and shows a power function growth trend. The difference in density of MPs mainly affects their dispersion during the floating process. Moreover, the coefficient of variation (CV) of PP’s horizontal floating velocity increased with the Re, suggesting PP’s motion is more random and discrete than that of PE and PS. Ultimately, we fitted the horizontal floating velocity of MPs to the equation to comprehensively evaluate the relationship between the floating velocity, Re, and density of MPs. This analysis underscores that the Re predominantly influences the MP velocity in water, while the MP density chiefly impacts the discrete nature of their motion.

Aquaculture wastewater is rich in nutrients such as nitrogen and phosphorus. If discharged directly without treatment, it can cause eutrophication of water bodies and the proliferation of algae. This study explores the treatment of aquaculture wastewater using cerium nitrate and hydrogen peroxide. To improve the treatment efficiency of ammonia and nitrite in aquaculture wastewater, a Box–Behnken design with three factors at three levels was used to optimize the process of treating aquaculture wastewater with cerium nitrate and hydrogen peroxide. The optimal process conditions for removing ammonia and nitrite were determined to be a Ce(NO₃)₃ dosage of 0.18 g/L, an H₂O₂ reaction concentration of 1.0%, and a reaction time of 30 min. Under the optimal reaction conditions, the degradation rate of ammonia and nitrite can reach 80% or more. Finally, high-throughput sequencing technology was used to explore the impact of cerium nitrate and hydrogen peroxide treatment on microbial community structure and metabolic pathways. The results showed that, at the phylum level, the dominant positions of Actinobacteriota, Proteobacteria, and Bacteroidota were maintained throughout the entire culture period. At the genus level, the relative abundance of the hgcI_clade genus under Actinobacteriota significantly increased, becoming the main dominant genus throughout the culture period. Under the condition of adding cerium nitrate and hydrogen peroxide, the metabolic functions of the microbial community were enhanced. The addition of cerium nitrate and hydrogen peroxide increased the abundance of key nitrogen metabolism genes such as amo, hao, and nap, thereby enhancing the potential nitrification/denitrification capabilities of microorganisms. The combination of cerium nitrate and hydrogen peroxide showed positive effects in the treatment of aquaculture wastewater, providing a new strategy for the green treatment of wastewater.

When treating municipal wastewater, nitrogen removal is often limited due to low C/N, which needs to be compensated for by additional carbon source injections. This study investigated the feasibility of using industrial-waste polyglycolic acid (PGA) as a carbon source for denitrification in an SBR to obtain an economical carbon source. The results revealed that an optimal denitrification performance in a methanol-fed activated sludge system was achieved with a PGA dosage of 1.2 mL/L, a pH of 7–8, and a dissolved-oxygen (DO) concentration of 3 ± 0.5 mg/L. Under these conditions, all quality parameters for effluent water met the required criteria [COD < 50 mg/L; TN < 15 mg/L; NH₄⁺-N < 5(8) mg/L]. PGA enhanced the variety and richness of microbial communities, thereby markedly increasing the relative abundance of major phyla such as Proteobacteria and Bacteroidota and major genera such as Paracoccus and Dechloromonas. Furthermore, PGA upregulated the expression of nitrogen-metabolism-related genera, including amo, hao, nar, and nor, which improved the denitrification performance of the system. This study provides a reference for applying PGA as a carbon source for low-C/N-wastewater treatment and solid-waste utilization.