This study aimed to investigate of the spatial analyses of the correlation coefficient between Particulate matter PM_2.5 and meteorological parameters in Iraq Using remote-sensing data and meteorological Parameters datasets for the period 2003–2020. PM_2.5 is one of the primary air pollutants across the world. Quantifying interactions between meteorological conditions and PM_2.5 concentrations is essential to understanding the variability of PM_2.5. The spatial variations of the relationships between the annual average PM_2.5, the annual average rainfall, temperature wind speed, and pressure were evaluated using the Pearson correlation coefficient model. The results indicated that there were positive correlations between PM_2.5 concentrations and both temperature and wind, while there was a negative correlation with pressure. As for rainfall, there were positive correlations in some areas and negative in others. The results also showed that the most associated factor with PM_2.5 is wind. it becomes clear to us that the correlations between fine particles and meteorological factors differ according to the regions, the terrain, the local climate, human and natural differences, and weather changes.