ABSTRACT
Background: Forecasting of air pollutants has become a popular topic of environmental research today. For this purpose, the artificial neural network [AAN] technique is widely used as a reliable method for forecasting air pollutants in urban areas. On the other hand, the evolutionary polynomial regression [EPR] model has recently been used as a forecasting tool in some environmental issues. In this research, we compared the ability of these models to forecast carbon monoxide [CO] concentrations in the urban area of Tabriz city
Methods: The dataset of CO concentrations measured at the fixed stations operated by the East Azerbaijan Environmental Office along with meteorological data obtained from the East Azerbaijan Meteorological Bureau from March 2007 to March 2013, were used as input for the ANN and EPR models
Results: Based on the results, the performance of ANN is more reliable in comparison with EPR. Using the ANN model, the correlation coefficient values at all monitoring stations were calculated above 0.85. Conversely, the R2 values for these stations were obtained <0.41 using the EPR model
Conclusion: The EPR model could not overcome the nonlinearities of input data. However, the ANN model displayed more accurate results compared to the EPR. Hence, the ANN models are robust tools for predicting air pollutant concentrations
ABSTRACT
Natural disasters are always one of the human health threatening factors in the worldwide which Iran provinces including East Azerbaijan are involved. This study aimed to assess awareness of environmental health experts in East Azerbaijan province about health problems during natural disasters. In this descriptive study, 144 environmental health experts were randomly selected and studied in East Azerbaijan province [including 52.1% from all Townships and 47.9% from Tabriz city]. Questionnaires distributed among experts after validation by specialists; then the collected data was analyzed using SPSS. According to the results, significant differences were found between the awareness of participants [45/5% experts and 53/5% technician of environmental health] in Tabriz and other Townships of province. Significant differences were also found between the level of education and workplace [P /= 0/05]. The results indicate that the effect of education on experts' awareness of environmental health in natural disasters. So, some measures should be taken such as: to promote employees scientific level by training courses or retraining programs; to provide facilities in order to continue their education and recruiting new experts. Thus, these measures can reduce injuries or mortality rate due to lack of awareness of the health issues in natural disasters