Providing the best pattern Interpolation in the spatial distribution of partiulate matter smaller than 2.5 microns of mashhad

Air pollution is one of the most important environmental problems in the last century that threatens human health and particulate matter is one of the deadliest types of air pollution.This study was done to choose the best interpolation algorithm in the spatial distribution of PM2.5 suspended particles in Mashhad in 1395by different spatial models.

PM2.5 particulate concentrations was collected from 21 active air quality measuring stations in different parts of Mashhad and IDW, Ordinary Kriging (OK) and Universal Kriging (UK) interpolation models were evaluated to spatially investigate the air pollution situation in Mashhad. The root mean square error (RMSE) was used to compare the models and select the best model, and the Standardized RMSE was used to choose the most optimal conditions for running the OK and UK models.

The results showed that the highest seasonal average of PM2.5 pollutants in 1395 was related to autumn (40.84 µg/m3) and the lowest was related to spring (27.78 µg/m3). Also, the east to north area of Mashhad is in a more unfavorable situation in pollution concentration than the western areas of the city. Comparison of models using RMSE index also showed that OK model due to having the lowest amount of RMSE for seasonal average and annual concentration of suspended particles PM2.5 has a lower error in the predicted values than the measurement, so it has better conditions for intermediation.

This research eventually led to the production of maps of PM2.5 Pollutants situation in the whole city of Mashhad, which is very useful in order to identify high-risk areas in the city and use useful measures to reduce air pollution in those areas.