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.