大气污染防治综合决策支持技术平台典型城市应用研究

以典型城市济南市为研究对象，利用大气污染防治综合决策支持技术平台(简称“技术平台”)综合评估了济南市《2018年大气污染治理“十大措施”实施方案》(简称“‘十大措施’”)的实施效果，并进一步基于特定空气质量目标〔济南市2018年ρ(PM_2.5)、ρ(O₃)同比2017年分别下降20%、8%〕开展大气污染防治策略寻优及费效评估.结果表明:①“十大措施”实施后，SO₂、NO_x、VOCs、一次PM_2.5减排率分别为39%、24%、42%、41%，该情景在2017基准年气象条件下可使济南市2018年ρ(PM_2.5)同比下降19%，新增治污成本约4.70×108元，效益-成本比约1.40；单位减排成本最低的本地扬尘源减排对ρ(PM_2.5)下降的贡献率最大，建议济南市下一阶段应进一步强化扬尘源减排.②经过策略寻优，反算得到了SO₂、NO_x、VOCs、一次PM_2.5的减排率分别为46%、20%、42%、60%的优化策略，该策略下的新增治污成本约4.69×108元；对比“十大措施”，优化策略提高了SO₂和一次PM_2.5的减排率，降低对O₃具有负贡献的NO_x减排率，满足空气质量目标的同时又尽可能地降低了治污成本，将效益-成本比提升至1.88.技术平台在济南市的初步成功应用，为济南市下一阶段的大气污染防治提供基于实证的科学依据；同时对其在我国城市逐步推广具有重要示范意义，可有效支撑大气污染防治综合科学决策制定. 

Application and Research of Decision Support Technology Platform for Air Pollution Prevention and Control in Typical Polluted City

The decision support technology platform for air pollution prevention and control was applied to quantify the effects of the implementation plan of the 'Ten Measures' for air pollution control in Jinan. Furthermore, the optimization and cost-benefit assessment of air pollution prevention and control strategy were carried to reduce the ambient ρ(PM_2.5) and ρ(O₃) by 20% and 8%, respectively, in 2018 compared with 2017. The results show that: (1) After the implementation of the 'Ten Measures', the reduction rates of SO₂, NO_x, VOCs, and primary PM_2.5 were 39%, 24%, 42%, 41%, respectively, and this scenario could reduce the ρ(PM_2.5) in Jinan in 2018 by 19% compared with 2017. The additional cost of pollution control was about 4.70×108 RMB, and the benefit/cost ratio was 1.40. The reduction of local dust emissions with the lowest reduction cost per emission contributed the most to the reduction of ρ(PM_2.5). Therefore, it is recommended to further strengthen the emission reduction of dust sources in the next stage in Jinan City. (2) The reduction rates of SO₂, NO_x, VOCs, primary PM_2.5 obtained through inverse computation of strategy optimization were 46%, 20%, 42%, 60%, respectively, and the additional cost of pollution control was about 4.69×108 RMB under this strategy. Compared with the 'Ten Measures', the optimization strategy increased the emission reduction rates of SO₂ and primary PM_2.5, and decreased the reduction rate of NO_x that has a negative effect on O₃, which meets the air quality target while reducing the cost of pollution control as much as possible, and the benefit/cost ratio was improved to 1.88. The successful application of the technology platform in Jinan provides an empirical scientific basis for air pollution prevention and control in the next stage in Jinan City, which has demonstration significance for the gradual promotion and use of the technology platform in other cities in China. It can efficiently support comprehensive and scientific decision-making on air pollution prevention and control.