A cooperative governance model for SO2 emission rights futures that accounts for GDP and pollutant removal cost

Abstract

Due to the cross-regional mobility of air pollution, the traditional governance mode has been difficult to implement effectively. To solve the problem of excessive pollution governance costs, we determined the spot price of emission futures with a pricing model based on an arbitrage-free interval, and constructed a dual-objective optimization model that accounts for both GDP and the pollutant removal cost. By comparing the optimal removal volumes for each cooperator with the national allocation of removal quotas, we divided actors into sellers and buyers of cooperative emission rights based on futures trading. Finally, we used an asymmetric Nash negotiation model to distribute the benefits of cooperation. To demonstrate the approach, we used China’s Beijing-Tianjin-Hebei region as a case study, and found that the cooperative governance strategy can help to solve the air pollution problem. Compared with the independent autonomy model of the futures market, the Cooperative Governance Model (CGM) increased the GDP of the Beijing-Tianjin-Hebei region by 22.143 × 109 Yuan, an increase of 0.3 %, and decreased the removal cost by 124.030 × 106 Yuan, a decrease of 0.4 %. Our results provide a reference for policy decisions on collaborative air pollution control, and can be used to promote collaborative air pollution control in other regions.