Scenario-based quantitative microbial risk assessment to evaluate the robustness of a drinking water treatment plant

2016 ◽  
Vol 51 (2) ◽  
pp. 81-96 ◽  
Author(s):  
Mohamed A. Hamouda ◽  
William B. Anderson ◽  
Michele I. Van Dyke ◽  
Ian P. Douglas ◽  
Stéphanie D. McFadyen ◽  
...  

While traditional application of quantitative microbial risk assessment (QMRA) models usually stops at analyzing the microbial risk under typical operating conditions, this paper proposes the use of scenario-based risk assessment to predict the impact of potential challenges on the expected risk. This study used a QMRA model developed by Health Canada to compare 14 scenarios created to assess the increase in risk due to potential treatment failures and unexpected variations in water quality and operating parameters of a water treatment plant. Under regular operating conditions, the annual risk of illness was found to be substantially lower than the acceptable limit. Scenario-based QMRA was shown to be useful in demonstrating which hypothetical treatment failures would be the most critical, resulting in an increased risk of illness. The analysis demonstrated that scenarios incorporating considerable failure in treatment processes resulted in risk levels surpassing the acceptable limit. This reiterates the importance of robust treatment processes and the multi-barrier approach voiced in drinking water safety studies. Knowing the probability of failure, and the risk involved, allows designers and operators to make effective plans for response to treatment failures and/or recovery actions involving potential exposures. This ensures the appropriate allocation of financial and human resources.

2008 ◽  
Vol 7 (5) ◽  
pp. 525-530 ◽  
Author(s):  
Kristina D. Mena ◽  
Linda C. Mota ◽  
Mark C. Meckes ◽  
Christopher F. Green ◽  
William W. Hurd ◽  
...  

2009 ◽  
Vol 60 (3) ◽  
pp. 709-715 ◽  
Author(s):  
Kim van Schagen ◽  
Luuk Rietveld ◽  
Alex Veersma ◽  
Robert Babuška

Owing to the nature of the treatment processes, monitoring the processes based on individual online measurements is difficult or even impossible. However, the measurements (online and laboratory) can be combined with a priori process knowledge, using mathematical models, to objectively monitor the treatment processes and measurement devices. The pH measurement is a commonly used measurement at different stages in the drinking water treatment plant, although it is a unreliable instrument, requiring significant maintenance. It is shown that, using a grey-box model, it is possible to assess the measurement devices effectively, even if detailed information of the specific processes is unknown.


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