Quantitative Risk Assessment of Decentralized Wastewater Management Systems in a Drinking Water Catchment

2007 ◽  
Author(s):  
Ben A Asquith ◽  
Joe H Whitehead ◽  
Luke J Kidd
2018 ◽  
Vol 2018 (1) ◽  
Author(s):  
Jonathan Blohm ◽  
Adam Carl ◽  
Greg Sehongva ◽  
Lori Joshweseoma ◽  
Robin Harris ◽  
...  

2007 ◽  
Vol 5 (S1) ◽  
pp. 107-118 ◽  
Author(s):  
P. W. M. H. Smeets ◽  
J. C. van Dijk ◽  
G. Stanfield ◽  
L. C. Rietveld ◽  
G. J. Medema

Quantitative Microbiological Risk Assessment (QMRA) is increasingly being used to complement traditional verification of drinking water safety through the absence of indicator bacteria. However, the full benefit of QMRA is often not achieved because of a lack of appropriate data on the fate and behaviour of pathogens. In the UK, statutory monitoring for Cryptosporidium has provided a unique dataset of pathogens directly measured in large volumes of treated drinking water. Using this data a QMRA was performed to determine the benefits and limitations of such state-of-the-art monitoring for risk assessment. Estimates of the risk of infection at the 216 assessed treatment sites ranged from 10−6.5 to 10−2.5 person−1 d−1. In addition, Cryptosporidium monitoring data in source water was collected at eight treatment sites to determine how Cryptosporidium removal could be quantified for QMRA purposes. Cryptosporidium removal varied from 1.8 to 5.2 log units and appeared to be related to source water Cryptosporidium concentration. Application of general removal credits can either over- or underestimate Cryptosporidium removal by full-scale sedimentation and filtration. State-of-the-art pathogen monitoring can identify poorly performing systems, although it is ineffective to verify drinking water safety to the level of 10-4 infections person−1 yr−1.


2006 ◽  
Vol 40 (23) ◽  
pp. 7428-7433 ◽  
Author(s):  
Yoshifumi Masago ◽  
Hiroyuki Katayama ◽  
Toru Watanabe ◽  
Eiji Haramoto ◽  
Atsushi Hashimoto ◽  
...  

2021 ◽  
Vol 906 (1) ◽  
pp. 012043
Author(s):  
Gelu Madear ◽  
Camelia Madear

Abstract The consequences of contaminated groundwater can seriously affect sustainable development; present and future generations being seriously affected by inadequate drinking water quality, loss of water supply, degraded surface water systems, high remediation costs, more expenses for other water supplies, and likely health issues. Therefore, an effective way to protect groundwater resources is by assessing the risk of groundwater contamination. An assessment of groundwater pollution should be performed to determine the level of risk posed by soil and groundwater contamination and establish if remediation strategies are required to protect controlled waters from site-derived contamination. Furthermore, if remediation is deemed necessary, site-specific remedial targets should be derived. A case study is presented, where a Conceptual Site Model was derived based on a “Source-Pathway-Receptor” exposure mechanism using historical information. Primary sources of contamination at the site are residual contamination within the soil and groundwater, and samples were collected from the site and tested in the laboratory; the concentration of water samples was compared to Romanian Drinking Water Standards. The following potential migration pathways have been identified: Leaching from soil and Migration of contaminated groundwater. The Detailed Quantitative Risk Assessment (DQRA) has modelled the leaching of contaminants from the site via infiltration and vertical migration to the groundwater and subsequent lateral groundwater migration, with dilution and attenuation process active, to the compliance point, using Ogata-Banks equation. The results of this assessment indicate that the concentration of contaminants does not represent a significant risk to controlled waters.


2013 ◽  
Vol 19 (3) ◽  
pp. 521-527 ◽  
Author(s):  
Song YANG ◽  
Shuqin WU ◽  
Ningqiu LI ◽  
Cunbin SHI ◽  
Guocheng DENG ◽  
...  

1997 ◽  
Vol 35 (11-12) ◽  
pp. 29-34 ◽  
Author(s):  
P. Teunis ◽  
A. Havelaar ◽  
J. Vliegenthart ◽  
G. Roessink

Shellfish are frequently contaminated by Campylobacter spp, presumably originating from faeces from gulls feeding in the growing or relaying waters. The possible health effects of eating contaminated shellfish were estimated by quantitative risk assessment. A paucity of data was encountered necessitating many assumptions to complete the risk estimate. The level of Campylobacter spp in shellfish meat was calculated on the basis of a five-tube, single dilution MPN and was strongly season-dependent. The contamination level of mussels (<1/g) appeared to be higher than in oysters. The usual steaming process of mussels was found to completely inactivate Campylobacter spp so that risks are restricted to raw/undercooked shellfish. Consumption data were estimated on the basis of the usual size of a portion of raw shellfish and the weight of meat/individual animal. Using these data, season-dependent dose-distributions could be estimated. The dominant species in Dutch shellfish is C. lari but little is known on its infectivity for man. As a worst case assumption, it was assumed that the infectivity was similar to C. jejuni. A published dose-response model for Campylobacter-infection of volunteers is available but with considerable uncertainty in the low dose region. Using Monte Carlo simulation, risk estimates were constructed. The consumption of a single portion of raw shellfish resulted in a risk of infection of 5–20% for mussels (depending on season; 95% CI 0.01–60%). Repeated (e.g. monthly) exposures throughout a year resulted in an infection risk of 60% (95% CI 7–99%). Risks for oysters were slightly lower than for mussels. It can be concluded that, under the assumptions made, the risk of infection with Campylobacter spp by eating of raw shellfish is substantial. Quantitative risk estimates are highly demanding for the availability and quality of experimental data, and many research needs were identified.


2015 ◽  
Vol 2015 (2) ◽  
pp. 1-9 ◽  
Author(s):  
Carla Cherchi ◽  
Mohammad Badruzzaman ◽  
Joan Oppenheimer ◽  
Matthew Gordon ◽  
Simon Bunn ◽  
...  

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