A Generalized Nash Equilibrium Game Model for Removing Regional Air Pollutant

As the main air pollution control pattern used in China, the independent emission reduction (IER) model mandated that each province reduce its air pollutant independently. Under this model, provinces paid huge pollutant removal costs because they could not select the optimal pollutant removal rate based on their emission reduction capacity and their marginal cost of pollutant reduction. To overcome the ineffectiveness and high cost of the IER model, a generalized Nash equilibrium game (GNEG) model was constructed to achieve the State-set regional emission reduction target while minimizing the pollutant removal cost for each sub-region. Next, the case of Yangtze River Delta region was investigated using the GNEG model. Further, an incentive mechanism was suggested to improve the willingness of all participants. Result shows that the optimal SO2 removal solution in the GNEG model saved US$4.8 × 107 compared with the IER model, amounting to 3.1% of the total pollutant removal cost. Finally, a sensitivity analysis was performed to simulate the effects of changes in the State-set SO2 reduction targets and the upper and lower bounds on the optimal pollutant removal rate and the removal cost of each province. The proposed model will help policy makers develop pollutant-reduction strategies that improve the effectiveness and economic benefits of pollution control.