Allocation of SO2 emission rights in city agglomerations considering cross-border transmission of pollutants: A new network DEA model

Schematic diagram of the research framework: A new network DEA method. [Display omitted] •A new network DEA allocation model considering cross-border transmission of SO2.•The WRF-CMAQ is combined with the DEA allocation model for the first time.•The principles of optimal efficiency, GDP protection and fairness is considered.•The per capita relative deprivation coefficient was used to evaluate the fairness.•The new network DEA model is a powerful tool for SO2 emission rights allocation. Currently SO2 emission rights are allocated without considering the cross-border transmission characteristics of pollutants, and the allocation scheme cannot reflect the fact that air pollutant overflows in space. In this paper, the WRF (Weather Research and Forecasting Model)-CMAQ (Community Multiscale Air Quality) is combined with the data envelopment analysis (DEA) allocation model for the first time, and a two-stage (Stage-1: SO2 formation, Stage-2: SO2 treatment) network DEA allocation model is proposed with the SO2 spatial transmission taken as the intermediate output or input index between decision-making units. Based on the principles of efficiency, economic protection and fairness, the model is applied to the study of SO2 emission rights allocation in the Yangtze River Delta city agglomeration with high homogeneity in China. The results show that: (1) When the weight coefficient (α1) in stage-1 is 0.7, 0.8 or 0.9, the per capita relative deprivation coefficient (PRDC) of each decision-making unit (DMU) is less than 0.5 in the allocation scheme, indicating that our scheme can be used as a reference to allocate emission rights in the Yangtze River Delta city agglomeration. (2) With great robustness and universality, our allocation model allows decision-makers to adjust the GDP constraint coefficient and the weight coefficients in the two stages according to their preferences, so as to obtain the optimal allocation results. The model proposed in this paper can help decision-makers to formulate effective policies to reduce pollutant emission, and promote energy conservation & emission reduction and coordinate environmental governance in regions of city agglomerations.