Abstract

A river basin is a complex system of tributaries and a mainstream. It is vital to cooperatively manage the mainstream and the tributaries to alleviate water pollution and the ecological environment in the basin. On the other hand, existing research focuses primarily on upstream and downstream water pollution control mechanisms, ignoring coordinated control of the mainstream and tributaries, and does not consider the impacts of different environmental and economic conditions in each region on pollution control strategies. This study designed a differential game model for water pollution control in the Yellow River and two of its tributaries, taking regional differences into account and discussing the best pollution control strategies for each region under two scenarios: Nash noncooperative and cost-sharing mechanisms. Furthermore, the factors influencing regional differences in pollution control costs are analyzed, and their impacts on the cost-sharing mechanism of pollution control are discussed. The results show that: (1) The cost-sharing mechanism based on cooperative management can improve pollutant removal efficiency in the watershed and achieve Pareto improvement in environment and economy. (2) The greater the economic development pressure between the two tributaries, the fewer the effects of the cost-sharing mechanisms and the higher the proportion of pollution control costs paid by the mainstream government. (3) Industry water consumption, the proportion of the urban population to the total population at the end of the year, the value-added of secondary sectors as a percentage of regional GDP, the volume of industrial wastewater discharge, and granted patent applications all influence industrial wastewater pollution treatment investment. (4) The greater the coefficient of variation in pollution control costs between the two tributary areas, the less favorable the solution to water pollution management synergy. These findings can help governments in the basin regions negotiate cost-sharing arrangements.

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