Investigating iron release in distribution systems with blend variations of source waters and phosphate inhibitors

2009 ◽  
Vol 8 (1-3) ◽  
pp. 211-220 ◽  
Author(s):  
Abdulrahman A. Alshehri ◽  
Steven J. Duranceau ◽  
James S. Taylor ◽  
Erica D. Stone
Keyword(s):  
Distribution Systems ◽  
Iron Release ◽  
Phosphate Inhibitors ◽  
Source Waters

Characterization of chemical composition and bacterial community of corrosion scales in different drinking water distribution systems

2017 ◽  
Vol 3 (1) ◽  
pp. 147-155 ◽  
Author(s):  
Haibo Wang ◽  
Chun Hu ◽  
Lang Yin ◽  
Sujia Zhang ◽  
Lizhong Liu
Keyword(s):  
Drinking Water ◽  
Chemical Composition ◽  
Distribution Systems ◽  
Water Distribution ◽  
Iron Release ◽  
Drinking Water Distribution Systems ◽  
Biochemical Function ◽  
Drinking Water Distribution ◽  
Corrosion Scales

There is a relationship between biochemical function and chemical composition of corrosion scales, and Fe3O4formation reduced iron release.

Why Red Water? Understanding Iron Release in Distribution Systems

Opflow ◽  
2006 ◽  
Vol 32 (12) ◽  
pp. 12-16 ◽  
Author(s):  
Gary A. Burlingame ◽  
Darren A. Lytle ◽  
Vernon L. Snoeyink
Keyword(s):  
Distribution Systems ◽  
Iron Release

Effect of Seasonal Variation on Iron Release in Drinking Water Distribution Systems

2014 ◽  
Vol 955-959 ◽  
pp. 3381-3384
Author(s):  
Hao Qiang Tan ◽  
Wen Jie He ◽  
Hong Da Han
Keyword(s):  
Drinking Water ◽  
Seasonal Variation ◽  
Distribution Systems ◽  
Water Distribution ◽  
Statistical Significance ◽  
Water Distribution Systems ◽  
Total Iron ◽  
Iron Release ◽  
Drinking Water Distribution Systems ◽  
Drinking Water Distribution

Analyzing the seasonal variation of water quality, the indices which include total iron, pH, temperature, DO, alkalinity and hardness were of high statistical significance, and total iron had a high correlation with temperature, which influences many parameters influencing iron release, such as DO, solution viscosity, thermodynamic properties and microbial activity. Therefore, it can be concluded that temperature is a main factor that affects iron release in seasonal change for drinking water distribution systems. Variation in season and temperature should be paid attention to in practice of water supply.

Research Progress on Velocity Model of Iron Release in Water Supply Pipe

2012 ◽  
Vol 446-449 ◽  
pp. 2833-2839
Author(s):  
Shan Wu ◽  
Long Yang ◽  
Dan Zuo
Keyword(s):  
Water Supply ◽  
Distribution Systems ◽  
Water Distribution ◽  
Dynamic Models ◽  
Velocity Model ◽  
Research Progress ◽  
Iron Release ◽  
Velocity Models ◽  
Supply Pipe ◽  
Release Model

The paper gives an overview on velocity models of iron release in water supply pipe at home and abroad, which incorporate empirical statistical models and dynamic models. Meanwhile, the characters of each iron release model are summarized. At last, the author analyzes the frequency of all parameters used in models mentioned in paper and puts forward the developing orientation on velocity models of iron release. The author also concludes that the establishment of velocity models of iron release is conducive to getting command of iron release in water distribution systems and guaranteeing the safety of potable water in drinking water pipe.

scholarly journals Development of a novel iron release flux model for distribution systems

2007 ◽  
Vol 99 (1) ◽  
pp. 102-111 ◽  
Author(s):  
Ginasiyo Mutoti ◽  
John D. Dietz ◽  
Syed Imran ◽  
James Taylor ◽  
C.D. Cooper
Keyword(s):  
Distribution Systems ◽  
Iron Release ◽  
Release Flux ◽  
Flux Model

scholarly journals Reproducible microbial community dynamics of two drinking water systems treating similar source waters

2019 ◽  
Author(s):  
Sarah C Potgieter ◽  
Ameet J Pinto ◽  
Minette Havenga ◽  
Makhosazana Sigudu ◽  
Stefanus N Venter
Keyword(s):  
Drinking Water ◽  
Microbial Community ◽  
Microbial Communities ◽  
Surface Waters ◽  
Distribution Systems ◽  
Community Dynamics ◽  
Microbial Community Dynamics ◽  
Two Systems ◽  
The Impact ◽  
Source Waters

AbstractIn addition to containing higher concentrations of organics and bacterial cells, surface waters are often more vulnerable to pollution and microbial contamination with intensive industrial and agricultural activities frequently occurring in areas surrounding the water source. Therefore, surface waters typically require additional treatment, where the choice of treatment strategy is critical for water quality. Using 16S rRNA gene profiling, this study provides a unique opportunity to simultaneously investigate and compare two drinking water treatment plants and their corresponding distribution systems. The two treatment plants treat similar surface waters, from the same river system, with the same sequential treatment strategies. Here, the impact of treatment and distribution on the microbial community within and between each system was compared over an eight-month sampling campaign. Overall, reproducible spatial and temporal dynamics within both DWTPs and their corresponding DWDSs were observed. Although source waters showed some dissimilarity in microbial community structure and composition, pre-disinfection treatments (i.e. coagulation, flocculation, sedimentation and filtration) resulted in highly similar microbial communities between the filter effluent samples. This indicated that the same treatments resulted in the development of similar microbial communities. Conversely, post-disinfection (i.e. chlorination and chloramination) resulted in increased dissimilarity between disinfected samples from the two systems, showing alternative responses of the microbial community to disinfection. Lastly, it was observed that within the distribution system the same dominant taxa were selected where samples increased in similarity with increased residence time. Although, differences were found between the two systems, overall treatment and distribution had a similar impact on the microbial community in each system. This study therefore provides valuable information on the impact of treatment and distribution on the drinking water microbiome.HighlightsSource waters show some dissimilarity in microbial community.Treatment processes increases similarity and selects for the same dominant taxa.Differential response to chlorination causing increased dissimilarity and variation.Stabilisation of DWDS microbial community through selection of same dominant taxa.Microbial community dynamics are reproducible between the two systems.

Impact of RO-desalted water on distribution water qualities

2005 ◽  
Vol 51 (6-7) ◽  
pp. 285-291 ◽  
Author(s):  
J. Taylor ◽  
J. Dietz ◽  
A. Randall ◽  
S. Hong
Keyword(s):  
Large Scale ◽  
Iron Release ◽  
Distribution Study ◽  
Treatment Processes ◽  
Copper Release ◽  
Lead Release ◽  
High Alkalinity ◽  
Decreasing Ph ◽  
Distribution Water ◽  
Source Waters

A large-scale pilot distribution study was conducted to investigate the impacts of blending different source waters on distribution water qualities, with an emphasis on metal release (i.e. corrosion). The principal source waters investigated were conventionally treated ground water (G1), surface water processed by enhanced treatment (S1), and desalted seawater by reverse osmosis membranes (RO). Due to the nature of raw water quality and associated treatment processes, G1 water had high alkalinity, while S1 and RO sources were characterized as high sulfate and high chloride waters, respectively. The blending ratio of different treated waters determined the quality of finished waters. Iron release from aged cast iron pipes increased significantly when exposed to RO and SI waters: that is, the greater iron release was experienced with alkalinity reduced below the background of G1 water. Copper release to drinking water, however, increased with increasing alkalinity and decreasing pH. Lead release, on the other hand, increased with increasing chloride and decreasing sulfate. The effect of pH and alkalinity on lead release was not clearly observed from pilot blending study. The flat and compact corrosion scales observed for lead surface exposed to S1 water may be attributable to lead concentration less than that of RO water blends.

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