Suspended particulate matter (SPM) plays a crucial role in biogeochemical cycles in the aquatic environment because of its ubiquitous presence, mobility, and physicochemical properties. This work gathered and summarized the published information about SPM in the Yangtze River system, including source, distribution, and environmental effects. Results indicated that the SPM concentration was high in the flood period and low in the dry period. Compared to midstream and downstream, the SPM concentration was the lowest in the upstream of the Yangtze River system. Furthermore, the level of SPM concentration was influenced by human activities, such as shipping, dredging, construction of water conservancy projects, and industrial/agricultural emissions, as well as natural conditions, such as wind, rainfall, and phytoplankton. Moreover, SPM would impact the element cycle in the water environment, including N, P, heavy metal, and persistent organic pollutants. In addition, SPM adsorbed these elemental ions or particles in water on its surface. Still, this adsorption was usually unstable, and when the properties of SPM itself or external environmental conditions changed, these elements would be released into the surrounding water body. With the flow of SPM in the water, these elements migrated upstream and downstream with the river. Thus, this work reveals the current status of SPM in the Yangtze River system, which provides an essential reference for further research on SPM in the water system.

In this work, a multidepot multiperiod vehicle routing problem with pickups and deliveries (MDPVRPPD) is solved by optimizing logistics networks with collaboration and resource sharing among logistics service providers. The optimal solution can satisfy customer demands with periodic time characteristics and incorporate pickup and delivery services with maximum resource utilization. A collaborative mechanism is developed to rearrange both the open and closed vehicle routes among multiple pickup and delivery centers with improved transportation efficiency and reduced operational costs. The effects of resource sharing strategies combining customer information sharing, facility service sharing, and vehicle sharing are investigated across multiple service periods to maximize resource utilization and refine the resource configuration. A multiobjective optimization model is developed to formulate the MDPVRPPD so that the minimum total operational costs, waiting time, and the number of vehicles are obtained. A hybrid heuristic algorithm incorporating a 3D clustering and an improved multiobjective particle swarm optimization (IMOPSO) algorithm is introduced to solve the MDPVRPPD and find Pareto optimal solutions. The proposed hybrid heuristic algorithm is based on a selective exchange mechanism that enhances local and global searching capabilities. Results demonstrate that the proposed IMOPSO outperforms other existing algorithms. We also study profit allocation issues to quantify the stability and sustainability of long-term collaboration among logistics participants, using the minimum costs remaining savings method. The proposed model and solution methods are validated by conducting an empirical study of a real system in Chongqing City, China. This study contributes to the development of efficient urban logistics distribution systems, and facilitates the expansion of intelligent and sustainable supply chains.