Particulate matter contains solid or liquid particles that are transported ans dispersed in the atmosphere. Study of particulate matter has attracted great interest of scientists due to effect on human health and its major role in climate change. Reduced lung function, development in respiratory diseases and premature death are effect of long term exposure of particle pollution. Wavelet transforms provide excellent analysis of non-stationary time series and extracts important information. Daubechies4 wavelet is orthogonal and compactly supportive and therefore, it is useful for multiresolution analysis of PM data. Skewness and Kurtosis parameter describe lack of the symmetry of data and correlation coefficient between PM10 and PM2.5 describes the linear relation between them.