GO, SiO2, and SnO2 nanomaterials as highly efficient adsorbents for Zn2+ from industrial wastewater—A second stage treatment to electrically enhanced membrane bioreactor

2019 ◽  
Vol 31 ◽  
pp. 100815 ◽  
Author(s):  
Menatalla Ahmed ◽  
Maria Elektorowicz ◽  
Shadi W. Hasan
Keyword(s):  
Industrial Wastewater ◽  
Membrane Bioreactor ◽  
Second Stage ◽  
Highly Efficient ◽  
Electrically Enhanced

Reclaiming Municipal and Industrial Wastewater Using Combined Membrane Bioreactor and Reverse Osmosis

2009 ◽  
Vol 3 (1) ◽  
pp. 1-15
Author(s):  
Glen T. Daigger ◽  
Andrew Hodgkinson ◽  
David Evans
Keyword(s):  
Reverse Osmosis ◽  
Industrial Wastewater ◽  
Membrane Bioreactor

Assessment of Microbial and Ecotoxicological Qualities of Industrial Wastewater Treated with Membrane Bioreactor (MBR) Process for Agricultural Irrigation

2021 ◽  
Vol 232 (11) ◽  
Author(s):  
Caner Vural ◽  
Tuğba Topbaş ◽  
S. Tuğçe Dağlıoğlu ◽  
Özlem Dağlı ◽  
Rahime Oral ◽  
...  
Keyword(s):  
Industrial Wastewater ◽  
Membrane Bioreactor ◽  
Agricultural Irrigation

High-strength nitrogen removal of opto-electronic industrial wastewater in membrane bioreactor - a pilot study

2003 ◽  
Vol 48 (1) ◽  
pp. 191-198 ◽  
Author(s):  
T.K. Chen ◽  
C.H. Ni ◽  
J.N. Chen ◽  
J. Lin
Keyword(s):  
Wastewater Treatment ◽  
Industrial Wastewater ◽  
Organic Nitrogen ◽  
Membrane Bioreactor ◽  
High Strength ◽  
Experimental Period ◽  
Ammonia Nitrogen ◽  
Nitrifying Bacteria ◽  
Biological Degradation ◽  
The Past

The membrane bioreactor (MBR) system has become more and more attractive in the field of wastewater treatment. It is particularly attractive in situations where long solids retention times are required, such as nitrifying bacteria, and physical retention critical to achieving more efficiency for biological degradation of pollutant. Although it is a new technology, the MBR process has been applied for industrial wastewater treatment for only the past decade. The opto-electronic industry, developed very fast over the past decade in the world, is high technology manufacturing. The treatment of the opto-electronic industrial wastewater containing a significant quantity of organic nitrogen compounds with a ratio over 95% in organic nitrogen (Org-N) to total nitrogen (T-N) is very difficult to meet the discharge limits. This research is mainly to discuss the treatment capacity of high-strength organic nitrogen wastewater, and to investigate the capabilities of the MBR process. A 5 m3/day capacity of MBR pilot plant consisted of anoxic, aerobic and membrane bioreactor was installed for evaluation. The operation was continued for 150 days. Over the whole experimental period, a satisfactory organic removal performance was achieved. The COD could be removed with an average of over 94.5%. For TOC and BOD5 items, the average removal efficiencies were 96.3 and 97.6%, respectively. The nitrification and denitrification was also successfully achieved. Furthermore, the effluent did not contain any suspended solids. Only a small concentration of ammonia nitrogen was found in the effluent. The stable effluent quality and satisfactory removal performance mentioned above were ensured by the efficient interception performance of the membrane device incorporated within the biological reactor. The MBR system shows promise as a means of treating very high organic nitrogen wastewater without dilution. The effluent of TKN, NOx-N and COD can fall below 20 mg/L, 30 mg/L and 50 mg/L.

Effect of 200 days' sludge retention time on performance of a pilot scale submerged membrane bioreactor for high strength industrial wastewater treatment

2006 ◽  
Vol 53 (11) ◽  
pp. 269-276 ◽  
Author(s):  
C.T. Hay ◽  
D.D. Sun ◽  
S.L. Khor ◽  
J.O. Leckie
Keyword(s):  
Retention Time ◽  
Industrial Wastewater ◽  
Membrane Bioreactor ◽  
Hydraulic Retention Time ◽  
High Strength ◽  
Pilot Scale ◽  
Submerged Membrane Bioreactor ◽  
Sludge Retention Time ◽  
Organic Removal ◽  
Sludge Concentration

A high strength industrial wastewater was treated using a pilot scale submerged membrane bioreactor (MBR) at a sludge retention time (SRT) of 200 d. The MBR was operated at a high sludge concentration of 20 g/L and a low F/M ratio of 0.11 during 300 d of operation. It was found that the MBR could achieve COD and TOC overall removal efficiencies at more than 99 and 98% TN removal. The turbidity of the permeate was consistently in the range of 0.123 to 0.136 NTU and colour254 absorbance readings varied from 0.0912 to 0.0962 a.u. cm−1. The sludge concentration was inversely proportional to the hydraulic retention time (HRT), yielded excellent organic removal and extremely low sludge production (0.0016 kgVSS/day).

The Two-Stage Recognition Method Based on Texture Signals of the Heterogeneous Unsteady Iris

2021 ◽  
Author(s):  
Shuai Liu ◽  
Yuanning Liu ◽  
Xiaodong Zhu ◽  
Jing Liu ◽  
Guang Huo ◽  
...  
Keyword(s):  
Iris Recognition ◽  
Recognition Accuracy ◽  
Texture Features ◽  
Unsteady State ◽  
Recognition Method ◽  
Two Stage ◽  
Second Stage ◽  
Highly Efficient ◽  
Training Samples ◽  
Gray Values

In this paper, a two-stage multi-category recognition structure based on texture features is proposed. This method can solve the problem of the decline in recognition accuracy in the scene of lightweight training samples. Besides, the problem of recognition effect different in the same recognition structure caused by the unsteady iris can also be solved. In this paper’s structure, digitized values of the edge shape in the iris texture of the image are set as the texture trend feature, while the differences between the gray values of the image obtained by convolution are set as the grayscale difference feature. Furthermore, the texture trend feature is used in the first-stage recognition. The template category that does not match the tested iris is the elimination category, and the remaining categories are uncertain categories. Whereas, in the second-stage recognition, uncertain categories are adopted to determine the iris recognition conclusion through the grayscale difference feature. Then, the experiment results using the JLU iris library show that the method in this paper can be highly efficient in multi-category heterogeneous iris recognition under lightweight training samples and unsteady state.

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