Disinfection of secondary effluents by O3, O3/H2O2 and UV/H2O2: Influence of carbonate, nitrate, industrial contaminants and regrowth

2018 ◽  
Vol 6 (1) ◽  
pp. 560-567 ◽  
Author(s):  
Jacqueline A. Malvestiti ◽  
Renato F. Dantas
Keyword(s):  
Industrial Contaminants ◽  
Secondary Effluents

Removal of tetracycline and the degradation products byLemna gibbaL. exposed to secondary effluents

2015 ◽  
Vol 34 (5) ◽  
pp. 1311-1321 ◽  
Author(s):  
Murat Topal ◽  
Gülşad Uslu Şenel ◽  
Erdal Öbek ◽  
E. Işıl Arslan Topal
Keyword(s):  
Degradation Products ◽  
Secondary Effluents

Coagulation of textile secondary effluents with Fenton's reagent

1997 ◽  
Vol 36 (12) ◽  
pp. 215-222 ◽  
Author(s):  
Shyh-Fang Kang ◽  
Huey-Min Chang
Keyword(s):  
Hydrogen Peroxide ◽  
Cod Removal ◽  
Color Removal ◽  
Fenton’S Reagent ◽  
Fenton's Reagent ◽  
Effluent Standards ◽  
Secondary Effluents ◽  
Removal Efficiencies

This study was designed to use both artificial and real textile secondary effluents to evaluate (1) the COD and color removal efficiencies for ferrous coagulation and Fenton's coagulation, and (2) the feasibility of using hydrogen peroxide to improve ferrous coagulation to meet more stringent effluent standards. The results indicate that the optimum pHs for both ferrous coagulation and Fenton's preoxidation processes range between 8.0–10 and 3.0–5.0, respectively. The rate for color removal is faster than that for COD removal in the Fenton's preoxidation process. The removals of COD and color are mainly accomplished during Fenton's preoxidation step. The ratio of COD removal for Fenton's coagulation versus ferrous coagulation, given the same ferrous dosage, ranges from 1.4 to 2.3, and it ranges from 1.1 to 1.9 for color removal, using two effluent samples. Therefore, using hydrogen peroxide can enhance the ferrous coagulation, and this ensures more stringent effluent standards of COD and color are met.

Simultaneous bacterial inactivation and microcontaminant removal by solar photo-Fenton mediated by Fe3+-NTA in WWTP secondary effluents

2021 ◽  
pp. 117686
Author(s):  
S. Miralles-Cuevas ◽  
P. Soriano-Molina ◽  
I. de la Obra ◽  
E. Gualda-Alonso ◽  
J.A. Sánchez Pérez
Keyword(s):  
Bacterial Inactivation ◽  
Secondary Effluents

Industrial contaminants

2022 ◽  
pp. 51-82
Author(s):  
Thomas H. Wines ◽  
Saeid Mokhatab
Keyword(s):  
Industrial Contaminants

Efficient synergistic disinfection by ozone, ultraviolet irradiation and chlorine in secondary effluents

2021 ◽  
Vol 758 ◽  
pp. 143641
Author(s):  
Qi Shi ◽  
Zhuo Chen ◽  
Hai Liu ◽  
Yun Lu ◽  
Kuixiao Li ◽  
...  
Keyword(s):  
Ultraviolet Irradiation ◽  
Secondary Effluents

Degradation of emerging pharmaceutical micropollutants in municipal secondary effluents by low-pressure UVC-activated HSO5− and S2O82− AOPs

2020 ◽  
Vol 393 ◽  
pp. 124712 ◽  
Author(s):  
Kang Zhou ◽  
Zhenkai Wang ◽  
Xiaoning Wang ◽  
Ganlai Jiao ◽  
Yifan Li ◽  
...  
Keyword(s):  
Low Pressure ◽  
Secondary Effluents

scholarly journals A modified fouling index (MFI40) and fouling predicting approach for ultrafiltration of secondary effluents

2018 ◽  
Vol 9 (1) ◽  
pp. 67-82 ◽  
Author(s):  
B. J. Cai ◽  
I. Baudin ◽  
H. Y. Ng
Keyword(s):  
Standard Deviation ◽  
Treatment Process ◽  
Pilot Scale ◽  
Operating Pressure ◽  
Combined Effects ◽  
Positive Role ◽  
Secondary Effluents ◽  
Pre Treatment ◽  
Modified Fouling Index ◽  
Turbidity Increase

Abstract Fouling indices for evaluating fouling propensity of secondary effluents (SEF) as feed of ultrafiltration (UF) systems are important parameters for the design and operation of the UF process. However, limited fouling indices have been developed and applied for UF feedwater. This study (i) established a modified UF fouling index (MFI40) by raising operating pressure from 30 psi in a traditional MFI test to 40 psi. Standard deviation of MFI40 tests was lower than that of traditional MFI by 68.6%, indicating better stability and repeatability of MFI40. It (ii) investigated the combined effects of UF feedwater characteristics on MFI40. Biopolymers and turbidity played a dominant and secondary positive role in the MFI40, respectively. The effect of conductivity on MFI40 changed from positive to negative with a turbidity increase. It also (iii) validated the MFI40 in both laboratory- and pilot-scale UF membrane units, and UF fouling rates were linearly correlated to the MFI40 of their feeds, and (iv) explored the practical use of the MFI40. It was applied to determine the maximum allowable UF feedwater quality (MFI40max), which could be used to select an appropriate pre-treatment process. A fouling predicting model was established based on the feedwater MFI40 and the operating flux, with an average predicting error of 26.8%.

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