Local government can establish local ambient air quality standard and also be under an obligation to have a long-term air quality improvement plan in Korea. At this process long-term air quality prediction model and optimal emission control strategies will be needed. Air dispersion model can't be applicable directly due to the lack of present and future emission data at each TM grid. And optimal air quality control is not tried before in Korea.
So at this study the proportional model(rollback, modified(considered emission area and effective stack height) rollback and multiple regression model) for the prediction of future air quality and environmental capacity is developed in Taejon city(population 1.2 million). The future air quality and environmental capacity are expected by using the developed model.
And the optimal fuel switching model for satisfaction the future air quality goal and environmental capacity is also developed. And through this model optimal fuel composition, resulting air quality and minimum fuel costs can be directly expected.
To predict the future air quality of surfer dioxides proportional models was tested in Taejon. The coefficient of determination(R^2) of all kinds of proportional model(rollback model, modified rollback model, multiple regression model and modified multiple regression model) is more than 0.85 in Taejon. So these all kinds of proportional model can be used for the prediction of future surfer dioxides air quality at Taejon City. And coefficient of determination of nitrogen dioxides is more than 0.89 at rollback and multiple regression model. These two model can be used for prediction future air quality of nitrogen dioxides. But in cases of the total suspended particulate and carbon mono oxide model in Taejon, coefficient of determination is high enough to use only at the rollback model.
Environmental capacity of each air pollutant was calculated with the developed proportional model. The optimal fuel switching model was set up to simultaneously satisfy environmental capacity of four kinds of air pollutant(TSP, $SO_2$, $NO_2$, CO) and minimum cost.
The result of this modeling in Taejon, gas fuel is most preferred fuel. Carbon mono oxides is most sensitive air pollutant, the optimized emission quantity will exceed the boundary condition before 2001. The nitrogen dioxides is also sensitive pollutant, and it will exceed before 2016. But TSP and surfer dioxides is always under the air quality goal.
The optimized fuel costs will increase 50%(2001), 43%(2005), 32%(2016) to the cost of fuel before fuel switching. The proportional prediction model and fuel switching model is also useful and effective tools for planning of local air quality management.