Distribution of Cryptosporidium oocysts and Giardia cysts in water above and below the normal limit of detection
被引:0
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作者:
Jerry E. Ongerth
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机构:University of Wollongong,Civil, Mining and Environmental Engineering
Jerry E. Ongerth
Frhat M. A. Saaed
论文数: 0引用数: 0
h-index: 0
机构:University of Wollongong,Civil, Mining and Environmental Engineering
Frhat M. A. Saaed
机构:
[1] University of Wollongong,Civil, Mining and Environmental Engineering
[2] University of Wollongong,undefined
来源:
Parasitology Research
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2013年
/
112卷
关键词:
Faecal Coliform;
Recovery Efficiency;
Public Water Supply;
Cryptosporidium Oocyst;
Discrete Object;
D O I:
暂无
中图分类号:
学科分类号:
摘要:
Analysis of water samples for Cryptosporidium oocysts and Giardia cysts is a specialised and demanding pursuit. Understanding and evaluating data resulting from such analyses is equally specialised and complicated by the most common result—not finding any of the target organisms. Coming to an accurate conclusion regarding such monitoring results has been hampered by a lack of pertinent information presented in the context of current monitoring requirements. The work reported here presents laboratory data demonstrating an appropriate skewed distribution model statistical framework. It is shown that the Poisson model provides for understanding how Cryptosporidium oocysts and Giardia cysts are distributed in water at typical ambient concentrations that are near or most commonly below the limit of detection of the most widely used analytical procedure, USEPA Method 1623. From three to six replicate 50-L volumes of particle-free water were seeded with Cryptosporidium oocysts and Giardia cysts each at concentrations of ca. 0.2/L, 1–2/L, and 6–8/L. The seeded 50-L volumes were analysed in five 10-L aliquots to determine the number of oocysts and cysts in each. The data conformed to the Poisson distribution. This supports the interpretation that analysis of 10-L surface water samples resulting in not finding any target organisms is the result of their presence below the limit of detection. This interpretation strongly suggests that analysing fewer larger volume samples would provide more useful information.
机构:
National Key Laboratory of Pollution Control and Reuse, Tongji University, Shanghai 200092, ChinaNational Key Laboratory of Pollution Control and Reuse, Tongji University, Shanghai 200092, China
Li, Qing-Song
Gao, Nai-Yun
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机构:
National Key Laboratory of Pollution Control and Reuse, Tongji University, Shanghai 200092, ChinaNational Key Laboratory of Pollution Control and Reuse, Tongji University, Shanghai 200092, China
Gao, Nai-Yun
Chen, Guo-Guang
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机构:
Shanghai Municipal Water Supply Dispatching and Monitoring Center, Shanghai 200002, ChinaNational Key Laboratory of Pollution Control and Reuse, Tongji University, Shanghai 200092, China
Chen, Guo-Guang
Jiang, Zeng-Hui
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机构:
Shanghai Municipal Water Supply Dispatching and Monitoring Center, Shanghai 200002, ChinaNational Key Laboratory of Pollution Control and Reuse, Tongji University, Shanghai 200092, China
Jiang, Zeng-Hui
Le, Lin-Sheng
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机构:
Shanghai Water Works Shibei Co. Ltd., Shanghai 200086, ChinaNational Key Laboratory of Pollution Control and Reuse, Tongji University, Shanghai 200092, China
Le, Lin-Sheng
Wu, Jin-Ming
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机构:
Shanghai Water Authority, Shanghai 200003, ChinaNational Key Laboratory of Pollution Control and Reuse, Tongji University, Shanghai 200092, China
Wu, Jin-Ming
Harbin Gongye Daxue Xuebao/Journal of Harbin Institute of Technology,
2008,
40
(06):
: 985
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988