THE USE OF ALTERNATE MICROBIOLOGICAL INDICATORS OF WATER TREATMENT PLANT PERFORMANCE

2001 ◽  
Vol 2001 (5) ◽  
pp. 394-402 ◽  
Author(s):  
Astrid Huertas ◽  
Benoit Barbeau ◽  
Christian Desjardins ◽  
Gary A. Toranzos
Keyword(s):  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Plant Performance ◽  
Microbiological Indicators

Use Dashboards to Improve Water Treatment Plant Performance

Opflow ◽  
2019 ◽  
Vol 45 (11) ◽  
pp. 24-27
Author(s):  
Nathan J. Boyle ◽  
Paul G. Biscardi ◽  
Dawn M. Guendert ◽  
Carl W. Spangenberg
Keyword(s):  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Plant Performance

Quantifying human exposure to contaminants for multiple-barrier water reuse systems

2010 ◽  
Vol 61 (1) ◽  
pp. 77-83 ◽  
Author(s):  
S. J. Khan ◽  
J. A. McDonald
Keyword(s):  
Water Treatment ◽  
Water Reuse ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Disinfection Byproducts ◽  
Plant Performance ◽  
Advanced Treatment ◽  
Safe Drinking Water ◽  
Treatment Processes ◽  
Wide Range

Reliance upon advanced water treatment processes to provide safe drinking water from relatively compromised sources is rapidly increasing in Australia and other parts of the world. Advanced treatment processes such as reverse osmosis have the ability to provide very effective treatment for a wide range of chemicals when operated under optimal conditions. However, techniques are required to comprehensively validate the performance of these treatment processes in the field. This paper provides a discussion and demonstration of some effective statistical techniques for the assessment and description of advanced water treatment plant performance. New data is provided, focusing on disinfection byproducts including trihalomethanes and N-nitrosamines from a recent comprehensive quantitative exposure assessment for an advanced water recycling scheme in Australia.

scholarly journals A NOVEL APPLICATION OF CHAOTIC PROPERTIES IN WATER TREATMENT PLANT

2016 ◽  
Vol 12 (12) ◽  
pp. 4749-4763
Author(s):  
Sridhar Natarajan ◽  
S. Senthil Kumaar
Keyword(s):  
Water Quality ◽  
Water Treatment ◽  
Tamil Nadu ◽  
Chaotic Behavior ◽  
Data Extraction ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Plant Performance ◽  
World Health ◽  
Treated Drinking Water

This paper aims at presenting a new optimization proposal to enhance the flocculation process in Water Treatment (WT) plant using a better flash mixing, located at KELAVERAPALLY, in Krishnagiri district, Tamil Nadu, India. Further, Sludge removal is done efficiently which decreases the water wastage as well as improvement in output water quality. Though WT plants are already equipped with systematic and sequential physicochemical processes, still they need to be optimized to obtain a better treated drinking water to maintain the quality standards as prescribed by World Health Organization. Chaotic behavior in chemical systems has been used to optimize the performance of WT plant. Measurement systems implemented in WT plant yield several chaotic based measurement parameters which are used to control the system operations to maintain the target water quality.  This intelligible data extraction through the proposed measurement  systems in a short span of time improves the plant performance without adding any costly systems except few changes in the existing plant setup.  Chaotic behavior is ensured through Lyapunov Exponents and Kolmogorov-Sinai Entropies. Both, water quality improvement and water wastage reduction is achieved simultaneously in the proposed work when a dosage prediction is done using Feed Forward Neural Networks. The treatment plant investigated has a maximum capacity of 14 MLD (Million litres per day) using two parallel streams with 7 MLD each

CFD Modeling Optimizes Water Treatment Plant Performance

2019 ◽  
Vol 111 (7) ◽  
pp. 40-45
Author(s):  
Edward Wicklein ◽  
Vincent Hart ◽  
Elizabeth Carter ◽  
Ralph Haight ◽  
Bobby Oligo ◽  
...  
Keyword(s):  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Plant Performance ◽  
Cfd Modeling

scholarly journals Spatial Assessment of Selangor, Malaysia Water Treatment Plant Performance Using Chemometric Technique

2018 ◽  
Vol 7 (3.14) ◽  
pp. 139
Author(s):  
H M. Zolkipli ◽  
H Juahir ◽  
G Adiana ◽  
N Zainuddin ◽  
A B. H. M. Maliki ◽  
...  
Keyword(s):  
Drinking Water ◽  
Water Treatment ◽  
Treatment Plant ◽  
Water Treatment Plant ◽  
Plant Performance ◽  
High Quality ◽  
Physico Chemical ◽  
Chemometric Technique ◽  
And Performance

This study aims to identify the most significant parameters in drinking water quality, spatial disparities of treated water (TW) and performance of water treatment plant (WTP) in Selangor. Physico- chemical (PCPs), Inorganic (IPs), Heavy metal and organic (HMOPs) and pesticide (PPs) were selected as parameters to discriminate the source of WTP pollutant. Chemometric technique such as principle component analysis (PCA), one-way analysis of variance (ANOVA) and discriminant analysis (DA) was applied to validate the performance of water treatment plant. PCA identified the most significant parameters which are highlighted six out of eight parameters for PCPs, six out of twelve parameters for IPs, nine out of sixteen parameters for HMOPs and all seventh parameters for PP. ANOVA for distinguish two categories region in WTP and showed both of PCPs and IPs had significant differences due to their concentration (p < 0.5) and HMOPs suggested fifth of significant differences within regions (p < 0.05). PP doesn’t give any significant differences (p > 0.05). DA was suggested PCPs, IPs and HMOPs in good performance (76.96%, 91.90% and 93.27%) except PP (50.43%). We can conclude that this chemometric technique can expose which area of WTP need to be properly maintains their performance to produce high quality of drinking water.  

scholarly journals Indigenous bacterial spores as indicators of Cryptosporidium inactivation using chlorine dioxide

2003 ◽  
Vol 1 (2) ◽  
pp. 91-100 ◽  
Author(s):  
Sophie Verhille ◽  
Ron Hofmann ◽  
Christian Chauret ◽  
Robert Andrews
Keyword(s):  
Drinking Water ◽  
Water Treatment ◽  
Chlorine Dioxide ◽  
Treatment Plant ◽  
Drinking Water Treatment ◽  
Water Treatment Plant ◽  
Common Species ◽  
Plant Performance ◽  
Inactivation Kinetics ◽  
Naturally Occurring

This objective of this study was to explore the practicality of monitoring naturally occurring organisms to predict drinking water treatment plant performance, in this case for the reduction of Cryptosporidium. Surface and ground water from seven drinking water treatment plants across North America that use chlorine dioxide were surveyed for aerobic and anaerobic bacterial spore concentrations. The concentrations of total spores were usually high enough in both raw and treated water to allow 4- to 5-log reductions to be observed across the treatment train by filtering up to 2 l of sample. These results suggested that naturally occurring treatment-resistant spores could be candidates as indicators of treatment performance. However, to be useful as indicators for Cryptosporidium reduction, the organisms would have to exhibit similar resistances to disinfection (chlorine dioxide in this case) in order to be useful. The inactivation kinetics of seven of the most common species were determined, and all were observed to be considerably more susceptible to chlorine dioxide inactivation than Cryptosporidium as reported in the literature. This study therefore did not identify an appropriate ambient microbial indicator for Cryptosporidium control.

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