Multigas Emission Quota Allocation Considering Policy Preferences and Synergistic Emission Reduction Potential: A Case Study of the Coal-Fired Power Sector

In the coordinated management of air pollutants and carbon emissions, governments impose differentiated regulatory requirements on gases, while mitigation technologies have heterogeneous abatement potential. However, existing studies on emission quota management, an important mitigation instrument, focus on single gases and neglect integrating multigas policy preferences and heterogeneous abatement potentials, weakening policy responsiveness and scheme feasibility. This study develops a two-stage allocation framework. First, policy preference weights are introduced to evaluate multigas synergistic emission reduction potential and determine maximum quota reduction constraints for each gas. Second, policy preference weights and a non-radial directional distance function (NDDF) are embedded in a zero-sum gains data envelopment analysis (ZSG-DEA) model to capture multigas heterogeneity in policy preferences and reduction constraints, improving applicability and feasibility. Applied to the coal-fired power sector, the results show that, relative to the equal weight scenario, CO2 incentive intensity rises by 22% under a carbon priority scenario and SO2 incentive intensity increases by 13% under a pollution priority scenario, while the maximum quota reduction ratios of CO2 and SO2 are constrained from 41.75% to 9.18% and from 78.57% to 37.28%, respectively, ensuring alignment with policy preferences and keeping abatement within feasible ranges to support carbon neutrality and pollution control targets, thereby contributing to sustainable development.