فهرست مطالب maryam zare shahne

The purpose of this research is to determine the toxicity of chemical components in PM2.5 particles and its production sources with the help of linear multivariate regression models between 2014 and 2015 at the Sharif University station. Based on the chemical analysis of the samples and the use of the oxidation capacity of suspended particles as an indicator of particle toxicity (ROS), it is possible to determine the toxicity of particles, their chemical compositions and provide resources. The amount of toxicity received in the cold seasons of the year was 1.5-3 times higher than in the hot seasons of the year, and due to the concentration of light vehicles in the cold seasons, the possibility between this source and the toxicity of particles is strengthened. The results of Pearson's correlation analysis showed that chemical components of human origin antimony, cadmium, nickel and arsenic had the highest correlation with toxicity index. This result is also consistent with Spearman's rank correlation analysis. Also, by examining the relationship between toxicity and resource contribution, the monthly contribution of MENA to gasoline vehicles and fuel oil is explained with both types of toxicity indices. By performing multivariate linear regression between toxicity and related chemical elements as well as two related sources, according to the obtained results, the contribution of gasoline vehicles in causing particle toxicity in the survey valley is equal to 83% on average.