Alireza Ehsanzadeh; Farhad Nejadkoorki; Sattar Khodadoostan
Abstract
Background & objectives: Air particulate matters which have natural and human made origins have significant effects on the climate, the environment and human health. Several epidemiological studies have shown a direct relationship among the concentrations of suspended particles with different ...
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Background & objectives: Air particulate matters which have natural and human made origins have significant effects on the climate, the environment and human health. Several epidemiological studies have shown a direct relationship among the concentrations of suspended particles with different adverse health effects. The general purpose of this research was to determine the most important parameters affecting on the concentration of PM10 in Tajrish station (Tehran) and develop an estimator model for PM10. Materials & methods: In this study, a model is constructed using principal component regression (PCR) for the relationship between the hourly concentration of particulate matter smaller than 10 microns with meteorological parameters (WD, WS, T, P, H) and air pollution parameters (CO, NO2, SO2, NOx, NMHC, THC) in Tajrish station (Tehran). The results of the performance evaluation of PCR model were measured in training and testing stages using RMSE, MAE, R and IA as statistical indicators. Results: The results of principal components import into multiple regression model showed that the most important variable affecting on the concentrations of PM10, are air temperature and the wind speed. Also, CO and SO2 emissions were known as synergic factors for PM10 concentration. The results showed that PCR model is able to estimate 41% of PM10 concentrations in the testing. Conclusion: The principal components regression analysis showed that meteorological parameters are one of most important factors affecting on the reduction of PM10 concentration in Tajrish station (Tehran).