Volume 3, Issue 1 (january 2019)                   AOH 2019, 3(1): 245-251 | Back to browse issues page


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Bajoghli M. Comparison of Application of AERMOD and ISCST3 Models for Simulating the Dispersion of Emitted Pollutant from the Stack of an Industrial Plant in Different Time Scales . AOH. 2019; 3 (1) :245-251
URL: http://aoh.ssu.ac.ir/article-1-124-en.html
MSc in Environmental Science, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran , Mehrshad.bajoghli@gmail.com
Abstract:   (165 Views)
Introduction: One of the main components of air quality management is modeling of atmospheric pollutants. The models by predicting and analyzing the emitted pollutant from various sources of pollution can contribute to effective implementation of policies to control and reduce the effects and costs resulting from these emissions. In this regards, simultaneous application of several models in a project and comparing the results obtained from these models could have considerable contribution on air quality managers for taking a more efficient decision. Methods: In this study, the stack of an industrial plant in the southwest of Isfahan was selected as the emission source and the total suspended particles emitted from this stack was simulated by applying AERMOD and ISCST3 models. Here the modelling process was conducted using MM5 meteorological data in a 50 50 km extent with 2000m network distance for each of the models. Results: Results indicated that the highest simulated concentration for both models occurred in a 2000 meters distance in the east of the stack. Moreover, the highest simulated concentration applying AERMOD was lower than that of applying ISCST3 in all term averages which is due to existing differences between applied algorithms in these two models. Conclusion: consequently, applying AERMOD due to the use of more advanced and up to date algorithms have priority over ISCST3 model. Applying ISCST3 can also be useful for small projects that require less input data compared to the AERMOD.  
Full-Text [PDF 1743 kb]   (69 Downloads)    
Type of Study: Research | Subject: Special
Received: 2018/11/24

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