Biological 2,4,6-trinitrotoluene removal by extended aeration activated sludge: optimization using artificial neural network
Title: |
Biological 2,4,6-trinitrotoluene removal by extended aeration activated sludge: optimization using artificial neural network |
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Author(s): |
Karimi, H., Mohammadi, F., Rajabi, S., Mahvi, A.H., Ghanizadeh, G. |
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Published/Type: |
2023 (2023-12-1) / Original Article |
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Journal: |
Scientific Reports, 13(1),9053 |
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Abstract: FWCI: 1.6
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Serious health issues can result from exposure to the nitrogenous pollutant like 2,4,6-trinitrotoluene (TNT), which is emitted into the environment by the munitions and military industries, as well as from TNT-contaminated wastewater. The TNT removal by extended aeration activated sludge (EAAS) was optimized in the current study using artificial neural network modeling. In order to achieve the best removal efficiency, 500 mg/L of chemical oxygen demand (COD), 4 and 6 h of hydraulic retention time... |
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