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On-line Water Quality Monitoring system in Borensberg, Motala, Sweden

Li, Jing LU (2011) In TVVR-11/5006 VVR820 20111
Division of Water Resources Engineering
Abstract
In one year water research project in Borensberg Waterworks, Motala, Sweden, water quality with respect to microscopic particle accounts both in raw water and drinking water were monitored by Predect’s Online Water Quality Monitoring System. Microscopic particle counts were documented with normalized value in real-time by P-100 for raw water and P-300 for pure water. This report aimed to evaluate the system for microbial contaminants condition in water.
Statistical tools were used for data sorting and arrangement. Pearson correlation matrix and regression analyses were applied for correlation analysis on variables of total particle counts in raw water and drinking water as well as within all particle size fractions. Furthermore, the... (More)
In one year water research project in Borensberg Waterworks, Motala, Sweden, water quality with respect to microscopic particle accounts both in raw water and drinking water were monitored by Predect’s Online Water Quality Monitoring System. Microscopic particle counts were documented with normalized value in real-time by P-100 for raw water and P-300 for pure water. This report aimed to evaluate the system for microbial contaminants condition in water.
Statistical tools were used for data sorting and arrangement. Pearson correlation matrix and regression analyses were applied for correlation analysis on variables of total particle counts in raw water and drinking water as well as within all particle size fractions. Furthermore, the similarities and difference of microbial particle counts between the two water bodies and seasonal variations were also discussed and analyzed. Log Reduction was used to measure particle removal for comparison of different treatment processes. Numerical analysis of GEV followed by recurrence curve analysis was suggested for threshold value definition.
Results show that Predect's design could be used as an early warning system against contaminants in terms of microscopic particle counts and inform the operator through GMS system and at the same time immediate auto-sample is processed. Correlation analysis show that there is no linear relation exists between total particle counts in raw water and drinking water. While in specific time periods, there exists variable correlation between all particle size fractions both within and between raw water and drinking water. Apparently, there are good correlation between almost all size fractions in Dec.2009, Mar.2010 and Jun.2010. It also demonstrates that there is a weak positive relation between microscopic particles in drinking water and microbiological counts in raw water.
Results from Log Reduction analysis show that the average values of Log Reduction is 2.82 in summer time and 1.05 for annual average situation. Comparison analysis between Borensberg Waterworks and Arboga Waterworks show that this system can be used to demonstrate different treatment processes. Results from threshold value definition show that the starting value should be determined by combination of theoretical analysis and practical situation.
Key Words: (Less)
Please use this url to cite or link to this publication:
author
Li, Jing LU
supervisor
organization
course
VVR820 20111
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Online Water Quality Monitoring System, microbiological water quality, microbiological contaminants, Borensberg Waterworks, Log Reduction, GEV (Generalized Extreme Value), threshold definition.
publication/series
TVVR-11/5006
report number
11/5006
ISSN
1101-9824
language
English
id
1983703
date added to LUP
2011-06-30 09:01:32
date last changed
2011-08-30 13:03:08
@misc{1983703,
  abstract     = {In one year water research project in Borensberg Waterworks, Motala, Sweden, water quality with respect to microscopic particle accounts both in raw water and drinking water were monitored by Predect’s Online Water Quality Monitoring System. Microscopic particle counts were documented with normalized value in real-time by P-100 for raw water and P-300 for pure water. This report aimed to evaluate the system for microbial contaminants condition in water.  
Statistical tools were used for data sorting and arrangement. Pearson correlation matrix and regression analyses were applied for correlation analysis on variables of total particle counts in raw water and drinking water as well as within all particle size fractions. Furthermore, the similarities and difference of microbial particle counts between the two water bodies and seasonal variations were also discussed and analyzed. Log Reduction was used to measure particle removal for comparison of different treatment processes. Numerical analysis of GEV followed by recurrence curve analysis was suggested for threshold value definition. 
Results show that Predect's design could be used as an early warning system against contaminants in terms of microscopic particle counts and inform the operator through GMS system and at the same time immediate auto-sample is processed. Correlation analysis show that there is no linear relation exists between total particle counts in raw water and drinking water. While in specific time periods, there exists variable correlation between all particle size fractions both within and between raw water and drinking water. Apparently, there are good correlation between almost all size fractions in Dec.2009, Mar.2010 and Jun.2010. It also demonstrates that there is a weak positive relation between microscopic particles in drinking water and microbiological counts in raw water.
Results from Log Reduction analysis show that the average values of Log Reduction is 2.82 in summer time and 1.05 for annual average situation. Comparison analysis between Borensberg Waterworks and Arboga Waterworks show that this system can be used to demonstrate different treatment processes. Results from threshold value definition show that the starting value should be determined by combination of theoretical analysis and practical situation.      
Key Words:},
  author       = {Li, Jing},
  issn         = {1101-9824},
  keyword      = {Online Water Quality Monitoring System,microbiological water quality,microbiological contaminants,Borensberg Waterworks,Log Reduction,GEV (Generalized Extreme Value),threshold definition.},
  language     = {eng},
  note         = {Student Paper},
  series       = {TVVR-11/5006},
  title        = {On-line Water Quality Monitoring system in Borensberg, Motala, Sweden},
  year         = {2011},
}