Volume 15, Issue 2 (8-2022)
ijhe 2022, 15(2): 275-288 |
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Karimi S R, Mansouri N, Taghavi L, Moeinaddini M. The receptor of heavy metals in total particulate matter with UNMIX determine the contribution model in 21st district of Tehran. ijhe 2022; 15 (2) :275-288
URL: http://ijhe.tums.ac.ir/article-1-6646-en.html
URL: http://ijhe.tums.ac.ir/article-1-6646-en.html
1- Department of Environmental Science and Engineering, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran
2- Department of Environmental Engineering, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran ,nmansouri@srbiau.ac.ir
3- Department of Environmental Sciences, Faculty of Natural Resources, University of Tehran, Karaj, Iran
2- Department of Environmental Engineering, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran ,
3- Department of Environmental Sciences, Faculty of Natural Resources, University of Tehran, Karaj, Iran
Abstract: (960 Views)
Background and Objective: The city of Tehran is always exposed to adverse consequences due to the establishment of various sources of heavy metals. Therefore, the purpose of this study is to identify the types of heavy metals in airborne particles and the origin of heavy metals in the 21st district of Tehran.
Materials and Methods: According to the EPA standard, 5 stations from District 21 of Tehran were selected for sampling. Using the ASTM D4096 method and using a high volume sampling pump, 50 samples of total airborne particles were collected. The samples were transferred to the laboratory and the concentration of heavy metals was measured by ICP-OES. The UNMIX source model was used to identify heavy metal sources.
Results: The average concentration of heavy metals in 1400 is a decreasing trend including Li
Conclusion: The source of light vehicles exhibited the highest share of emissions and the element aluminum showed the highest concentration among heavy metals in Region 21. Therefore, the UNMIX source model can correctly identify index elements and priority sources for contaminant control.
Materials and Methods: According to the EPA standard, 5 stations from District 21 of Tehran were selected for sampling. Using the ASTM D4096 method and using a high volume sampling pump, 50 samples of total airborne particles were collected. The samples were transferred to the laboratory and the concentration of heavy metals was measured by ICP-OES. The UNMIX source model was used to identify heavy metal sources.
Results: The average concentration of heavy metals in 1400 is a decreasing trend including Li
Conclusion: The source of light vehicles exhibited the highest share of emissions and the element aluminum showed the highest concentration among heavy metals in Region 21. Therefore, the UNMIX source model can correctly identify index elements and priority sources for contaminant control.
Type of Study: Research |
Subject:
Air
Received: 2022/03/28 | Accepted: 2022/07/6 | Published: 2022/09/28
Received: 2022/03/28 | Accepted: 2022/07/6 | Published: 2022/09/28
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