Predicting Hourly Ozone Concentration in Dali Area of Taichung County Based on Multiple Linear Regression Method

In this study, multiple linear regression (MLR) method was used to establish the relationship between the O3 at time t + 1 and other indices including hourly air pollutant concentrations and meteorological conditions at time t. Then O3 was predicted using the obtained best-fitting MLR. The results indicated that the relationship between the O3 at time t + 1 and other indices including hourly air pollutant concentrations and meteorological conditions at time t agreed with MLR well, The values of mean absolute percentage error (MAPE), correlation coefficient (R), coefficient of determination (R2), mean square error (MSE), and root mean square error (RMSE) were 29.09 %, 0.95, 0.90, 45.33, and 6.73, respectively when determining the best-fitting equation. In addition, MLR could predict hourly ozone concentrations successfully. The values of MAPE, R, R2, MSE, and RMSE were 10.37 %, 0.93, 0.86, 0.33, and 0.57, respectively when predicting. It also indicated that the hourly air pollutant concentrations and meteorological conditions at time t could be applied on the prediction of ozone of time t +1.