| Title |
Modeling photocatalytic degradation of diazinon from aqueous solutions and effluent toxicity risk assessment using Escherichia coli LMG 15862
|
|---|---|
| Published in |
AMB Express, April 2018
|
| DOI | 10.1186/s13568-018-0589-0 |
| Pubmed ID | |
| Authors |
Ali Toolabi, Mohammad Malakootian, Mohammad Taghi Ghaneian, Ali Esrafili, Mohammad Hassan Ehrampoush, Mohsen AskarShahi, Maesome Tabatabaei |
| Abstract |
In this study, modeling and degradation of diazinon from contaminated water by advanced oxidation process together with a new test for effluent bioassay using E. coli were investigated. The experiments were designed based on response surface methodology. Nanoparticles (NPs) were synthesized using the sol-gel method. The shape characteristics and specifications of elements in the nanoparticles were characterized using scanning electron microscope and energy dispersive X-ray, respectively. Diazinon was measured using high performance liquid chromatography device and by-products due to its decomposition were identified by gas chromatography-mass (GC-MS). In the present study, effluent bioassay tests were conducted by defining the rate of dehydrogenase enzyme reducing alamar blue method. According to statistical analyses (R2 = 0.986), the optimized values for pH, dose of NPs, and contact time were found to be 6.75, 775 mg/L, and 65 min, respectively. At these conditions, 96.06% of the diazinon was removed. Four main by-products, diazoxon, 7-methyl-3-octyne, 2-isopropyl-6-methyl-4pyrimidinol and diethyl phosphonate were detected. According to the alamar blue reducing (ABR) test, 50% effective concentration, no observed effect concentration, and 100% effective concentration (EC100) for the mortality rate of E. coli were obtained as 2.275, 0.839, and 4.430 mg/L, respectively. Based on the results obtained, it was found that mentioned process was high efficiency in removing diazinon, and also a significant relationship between toxicity assessment tests were obtained (P < 0.05). |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 19% |
| Student > Postgraduate | 2 | 10% |
| Student > Bachelor | 2 | 10% |
| Lecturer | 1 | 5% |
| Professor | 1 | 5% |
| Other | 5 | 24% |
| Unknown | 6 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 4 | 19% |
| Engineering | 2 | 10% |
| Environmental Science | 1 | 5% |
| Nursing and Health Professions | 1 | 5% |
| Unspecified | 1 | 5% |
| Other | 4 | 19% |
| Unknown | 8 | 38% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 April 2018.
All research outputs
#20,481,952
of 23,043,346 outputs
Outputs from AMB Express
#974
of 1,242 outputs
Outputs of similar age
#288,379
of 327,287 outputs
Outputs of similar age from AMB Express
#39
of 62 outputs
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