A novel future year air quality attainment prediction method, which is based on the design value of air pollutant concentration and relative response factor (RRF), has been developed to predict pollutant concentration levels under different emission control scenarios. The method first conducts numerical simulations to evaluate the effect of annual meteorological differences among the recent five years on the concentrations of air pollutants. The “typical” year, of which the meteorological condition is the closest to the five-year average, is selected as the base year. The air quality is simulated with the meteorological field and emission scenarios of the base year as the input of model so as to reduce the influence of inter-annual differences in meteorological conditions on the prediction of future pollutant concentration levels. Then it applies the regional air quality model for multiple times to simulate the pollutant concentration levels with different emission inputs that represent base and control emission scenarios. Lastly, it multiplies the design value of pollutant concentrations with the RRF derived from the ratios between the simulated concentrations of the control and base scenarios, to predict the future pollutant levels and to conduct air quality attainment tests. The method is applied to conduct scenario predictions and air quality attainment tests for the cities in Sichuan Province by designing multiple virtual air pollutant emission control scenarios based on the relevant emission reduction policies. The air quality attainment prediction results under different control scenarios, which aim to accomplish the goals of the 14th Five-Year Plan on air quality, can be useful for refining the local implementation strategies for control of air pollution.

提出一种基于污染物浓度设计值和相对响应因子的空气质量达标规划预测方法。首先通过数值模拟, 评估最近5年年际气象条件差异对空气污染物浓度的影响, 筛选出最接近5年平均气象条件的一年作为基准年, 将该基准年气象场和各排放情景作为输入进行空气质量模拟, 降低气象条件年际差异对未来污染物浓度水平预测的影响。然后, 基于基准情景和控制情景在不同排放水平的空气质量模式模拟结果, 将控制情景相对于基准情景的污染物模拟浓度的变化比例(相对响应因子)与污染物浓度设计值相结合, 进行控制情景的空气质量水平预测和达标分析。以四川省为例, 围绕相关减排政策, 设计多个虚拟控制情景, 对全省城市未来空气质量进行情景预测和达标分析, 为“十四五”空气质量规划落地策略的制定提供科学支撑。