@article { author = {Goudarzi, Gh. and Geravandi, S. and Ahmadi Angali, K. and Neisi, A.K. and Yari, A.R. and Dobaradaran, S. and Ghalani, B. and Hashemzadeh, B. and Mohammadi, M.J.}, title = {Modeling of sulfur dioxide emissions in Ahvaz City, southwest of Iran during 2013}, journal = {Caspian Journal of Environmental Sciences}, volume = {14}, number = {3}, pages = {205-213}, year = {2016}, publisher = {University of Guilan}, issn = {1735-3033}, eissn = {1735-3866}, doi = {}, abstract = {Sulfur dioxide has two important sources in the atmosphere and this is why most of scientists believe in a geographic split in the globe. Power plants, major emitter of SO2, are located in north hemisphere such as in Russia, China, Canada and the USA. In south hemisphere, phytoplankton produces a massive amount of dimethyl sulfide (DMS) and dimethyl disulfide (DMDS). Then these types of reduced products dissociate in the atmosphere and convert into SO2. It is a colorless gas which is released from burning coal, high sulfur coal and diesel fuel. The sulfur dioxide emissions from transportation systems, steel, oil and other industries are major concerns of air pollution in Ahvaz city, Iran. The main objective of this study was to determine the behavior of data over the time in a specific statistical model framework and compare through intended one to implement the Box-Jenkins method to make time series models in Ahvaz (located in Southwestern Iran), during 2013. Data of sulfur dioxide from four monitoring stations were collected at the first step and processed by Excel software; finally, the model of sulfur dioxide dispersion were evaluated. Time series analysis showed that air pollutants were associated with one step delay of sulfur dioxide and two steps delay of moving average. The finding of this study showed that the average concentration of sulfur dioxide in winter was higher than in summer. According to the results of this study, distribution of sulfur dioxide data has a correlated structure over the time; therefore the time series model is an appropriate model to explain the behavior of sulfur dioxide over the time.}, keywords = {Sulfur dioxide,Emissions,Time series analysis,Iran}, url = {https://cjes.guilan.ac.ir/article_1855.html}, eprint = {https://cjes.guilan.ac.ir/article_1855_f9a5f84dbba9fc17067d0204da49f7bb.pdf} }