Environmental Health Engineering and Management Journal
Environmental Health Engineering and Management Journal
Environ. Health Eng. Manag.
Medical Sciences
http://ehemj.com
1
admin
2423-3765
2423-4311
8
7
14
8888
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en
jalali
1394
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gregorian
2015
12
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online
1
fulltext
en
Sulfur dioxide AQI modeling by artificial neural network in Tehran between 2007 and 2013
عمومى
General
مقاله اصیل
Original Article
<p style="text-align: left">Background: Air pollution and concerns about health impacts have been raised in metropolitan cities like Tehran. Trend and prediction of air pollutants can show the effectiveness of strategies for the management and control of air pollution. Artificial neural network (ANN) technique is widely used as a reliable method for modeling of air pollutants in urban areas. Therefore, the aim of current study was to evaluate the trend of sulfur dioxide (SO2) air quality index (AQI) in Tehran using ANN.<br>
Methods: The dataset of SO2 concentration and AQI in Tehran between 2007 and 2013 for 2550 days were obtained from air quality monitoring fix stations belonging to the Department of Environment (DOE). These data were used as input for the ANN and nonlinear autoregressive (NAR) model using Matlab (R2014a) software.<br>
Results: Daily and annual mean concentration of SO2 except 2008 (0.037 ppm) was less than the EPA standard (0.14 and 0.03 ppm, respectively). Trend of SO2 AQI showed the variation of SO2 during different days, but the study declined overtime and the predicted trend is higher than the actual trend.<br>
Conclusion: The trend of SO2 AQI in this study, despite daily fluctuations in ambient air of Tehran over the period of the study have decreased and the difference between the predicted and actual trends can be related to various factors, such as change in management and control of SO2 emissions strategy and lack of effective parameters in SO2 emissions in predicting model.</p>
Sulfur dioxide, Neural networks, Air quality index, Tehran
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http://ehemj.com/browse.php?a_code=A-10-1-34&slc_lang=en&sid=1
Saeed
Motesaddi
10031947532846002030
10031947532846002030
No
Department of Environmental Health Engineering, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Parviz
Nowrouz
Nowrouzp@gmail.com
10031947532846002031
10031947532846002031
Yes
Environmental Health Engineering, Department of Environmental Health Engineering, School of Public Health, Sulfur dioxide AQI modeling by artificial neural network in Tehran between 2007 and 2013 Saeed Motesaddi 1 , Parviz Nowrouz 2* , Behrouz Alizadeh 3 , Fariba Khalili 4 , Reza Nemati 2 1 Associate Professor, Department of Environmental Health Engineering, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran 2 Shahid Beheshti University of Medical Sciences, Tehran, Iran
Behrouz
Alizadeh
10031947532846002032
10031947532846002032
No
Department of Medical Informatics, School of Allied Medical Sciences, Shahid Beheshti University Ph.D Student of Environmental Health Engineering, Department of Environmental Health Engineering, School of Public Health, Sulfur dioxide AQI modeling by artificial neural network in Tehran between 2007 and 2013 Saeed Motesaddi 1 , Parviz Nowrouz 2* , Behrouz Alizadeh 3 , Fariba Khalili 4 , Reza Nemati 2 1 Associate Professor, Department of Environmental Health Engineering, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran 2 Shahid Beheshti University of Medical Sciences, Tehran, Iran 3 of Medical Sciences, Tehran, Iran
Fariba
Khalili
10031947532846002033
10031947532846002033
No
Department of Environmental Health Engineering, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
Reza
Nemati
10031947532846002034
10031947532846002034
No
Department of Environmental Health Engineering, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran