Air Quality Analysis by Using Fuzzy Inference System and Fuzzy C-mean Clustering in Tehran, Iran from 2009-2013
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Amir Abbas HAMEDIAN
,
Allahbakhsh JAVID
,
Saeed MOTESADDI ZARANDI
,
Yousef RASHIDI
,
Monireh MAJLESI
Abstract
Background: Since the industrial revolution, the rate of industrialization and urbanization has increased dramatically. Regarding this issue, specific regions mostly located in developing countries have been confronted with serious problems, particularly environmental problems among which air pollution is of high importance.
Methods: Eleven parameters, including CO, SO2, PM10, PM2.5, O3, NO2, benzene, toluene, ethyl-benzene, xylene, and 1,3-butadiene, have been accounted over a period of two years (2011-2012) from five monitoring stations located at Tehran, Iran, were assessed by using fuzzy inference system and fuzzy c-mean clustering.
Results: These tools showed that the quality of criteria pollutants between the year 2011 and 2012 did not as much effect the public health as the other pollutants did.
Conclusion: Using the air EPA AQI, the quality of air, and also the managerial plans required to improve the quality can be misled.
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| Files | ||
| Issue | Vol 45 No 7 (2016) | |
| Section | Original Article(s) | |
| Keywords | ||
| Fuzzy c-mean clustering Air quality Fuzzy inference system Iran | ||
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