Loading...
Please wait, while we are loading the content...
Similar Documents
Evaluation of amoxicillin antibiotic removal by electrocoagulation process from aqueous solutions: optimization through response surface methodology
| Content Provider | Semantic Scholar |
|---|---|
| Author | Alidadi, Hosein Ghorbanian, Akram Ghorbanian, Mahdi Rahmanzadeh, Elham Nemanifar, Nasrin Mehrabpour, Marjan |
| Copyright Year | 2018 |
| Abstract | In this research, electrocoagulation (EC) was studied to investigate the efficiency of amoxicillin (AMX) antibiotic removal using iron electrodes from aqueous solution. For this purpose, a central composite design (CCD) was employed to optimize the operating parameters including pH (2-12), current density (5-15 mA.cm(-2)), AMX concentration (10-100 mg.L-1), and electrode spacing (1-3 cm). Experiments were performed in batch mode at the constant time of 35 min. The residual concentration of AMX in samples was analyzed by measuring the AMX concentration through high-performance liquid chromatography (HPLC). Further, pollutant removal, sludge generation, and energy consumption were measured and discussed through response surface methodology (RSM). The results showed that the removal efficiency was achieved as 80.9% under optimized levels of parameters (pH: 7.87, current density: 10.17 mA.cm(-2), AMX concentration: 50 mg.L-1, and electrode spacing: 1.5 cm), while sludge generation and energy consumption was 70.3 ml and 7.109 kWh.m(-3), respectively. The results revealed that at same conditions of all variables just one level reduction in current density has lead to the reduction to less than half of the energy consumption. |
| Starting Page | 350 |
| Ending Page | 358 |
| Page Count | 9 |
| File Format | PDF HTM / HTML |
| DOI | 10.5004/dwt.2018.23159 |
| Volume Number | 132 |
| Alternate Webpage(s) | http://www.deswater.com/DWT_abstracts/vol_132/132_2018_350.pdf |
| Alternate Webpage(s) | https://doi.org/10.5004/dwt.2018.23159 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |