Development of Equations to Predict the Concentration of Air Pollutants Indicators in Yazd City, Iran

Air pollution has become a major issue in all major cities throughout the world. Predicting air pollution can help to mitigate its detrimental consequences. The purpose of this study is to develop equations using multivariate regression to predict the concentration of particulate matter smaller than 10 µm (PM 10 ), sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), carbon monoxide (CO), and air quality index (AQI) in Yazd city, Iran. To this end, initially, the daily averages of air temperature, air pressure, wind speed, gust speed, precipitation, and humidity percentage of Yazd city between September 2020 and August 2021 were collected. Moreover, in the same period, the daily average concentrations of PM 10 , SO 2 , NO 2 , CO, and AQI of Yazd were collected. Then, by using multivariate regression, the relationships between meteorological parameters and air pollutants were investigated. Based on the results, seven different equations were developed to predict the concentrations of different air pollutants in different meteorological conditions. In addition, the results showed that the developed equations worked accurately in predicting the concentrations of O 3 , PM 10 , and NO 2 , but not very accurately in predicting the AQI, SO 2, and CO concentrations. More specifically, the most accurate equations belonged to PM 10 and NO 2 , which could predict the concentrations of these pollutants in the atmosphere of Yazd city with only 1% and 4% error, respectively. These equations provided a simple way to predict the concentration of important pollutants and AQI in Yazd city.