Forecasting Ambient Air Pollutants in Tehran, Iran

Abstract

Breathing healthy air is one of the most basic rights of human societies. Air pollution is currently one of the main global environmental health and justice concerns, because it is imposing its burden more severely on low socioeconomic regions and countries. Understanding the time pattern of these pollutants can help in better management and control. The aim of this study was to forecast ambient air pollutants by time series models in Tehran, Iran. This study was an ecological study about six ambient air pollutants (ozone O, carbon monoxide CO, nitrogen dioxide NO2, sulfur dioxide SO2, particulate matter PM10 and PM2.5) measured in Tehran during 2005-2018. Monthly mean values were calculated for each pollutant, and Holt-Winters models were used to predict values for the next 3 years (2019-2021). O3, CO, NO2, and SO2 had a decreasing trend from 2005 until 2018, but PM10 had an increasing trend. All pollutants showed a seasonal pattern. Higher concentrations of O3 and PM10 occurred in the warm months; and for CO and SO2 higher concentrations occurred in the cool months. The forecasting models showed that PM10 will increase, whereas other pollutants will decrease in the future. It can be concluded that in the next years (2019-2021), PM10 could be a huge environmental problem for Tehran. Other pollutants have had a decreasing trend, but they still need surveillance. © Copyright 2020, Mary Ann Liebert, Inc., publishers 2020