Air quality prediction is highly important in view of the health impacts caused by exposure to air pollutants in urban air. This work has presented a model based on support vector machine (SVM) technique to predict daily average carbon monoxide (CO) concentrations in the atmosphere of Tehran. Two types of SVM regression models, i.e. -SVM and -SVM techniques, were used to predict average daily CO concentration as a function of 12 input variables. Then, forward selection (FS) technique was applied to reduce the number of input variables. After converting 12 input variables to 7 using the FS, they were fed to SVM models (FS-(-SVM) and FS-(-SVM)). Finally, a comparison among SVM models operation and previously developed techniques, i.e. classical regression model and artificial intelligent methods such as ANN and adaptive neuro-fuzzy inference system (ANFIS) was carried out. Determination of coefficient (R2) and mean absolute error (MAE) for -SVM (-SVM) were 0.87 (0.40) and 0.87 (0.41), respectively, while they were 0.90 (0.39) and 0.91 (0.35) for ANN and ANFIS, respectively. Results of developed SVM models indicated that both FS-(-SVM) and FS-(-SVM) regression techniques were superior. Furthermore, it was founded that the performance of FS-(-SVM) and FS-(-SVM) models were generally a bit better than the best FS-ANFIS and FS-ANN solutions for short term forecasting of CO concentrations.

In recent times, the brick kiln contributes to air pollution is one of the most emerging issues worldwide. In this research work, the Peshawar city, ambient air quality was measured, using a fixed air monitoring station to evaluate the impact of gaseous emission from brick kilns on ground level. In this study, the portable gas analyzer (PG-250) was used to quantify brick-based emitting carbon monoxide (CO), sulfur dioxide (SO2) and nitrogen oxide (NOx) from 3 brick kilns in the city of Peshawar. It was noticed that the average concentration of SO2 and NOx exceeds the National Environmental Quality Standards (NEQS) of Pakistan specifically, in terms of air quality. The brick kilns in District Peshawar have shown negative effects on the environment. It is necessary to take various measures to monitor the brick kiln embosom regularly before it becomes a significant risk for individuals. In conclusion, the impact of air pollution on physical activity and sedentary behavior at a specific time may be different.