Thomas J. R. Pettersson

Performance of an in situ passive sampling system for metals in stormwater

A passive sampler has been developed and is demonstrated in situ for urban runoff. The passive sampler is compared to conventional composite (time-dependent and flow-weighted) bottle sampling during and between storm events. The sampling was carried out at established stormwater stations; before and after a stormwater detention pond. In situ deployment of the passive sampler provides the metal concentrations, corresponding to the electrochemically available fraction of total metal, for time-dependent samples collected in parallel. The sampler provides improved accuracy compared to bottle sampling because contamination during sample transport and handling is minimised. Laboratory handling is reduced by direct analysis of the accumulated metals on the receiving membrane by laser ablation inductively coupled plasma mass spectrometry. Passive sampling also solves the problem of metal speciation change during transport to the laboratory, which is a potential problem for bottle samples. The low cost and convenience of the passive sampler and subsequent analysis should allow significantly more extensive spatial and temporal monitoring of metals in the aquatic environment than has previously been possible.

Decay of Bacteroidales Genetic Markers in Relation to Traditional Fecal Indicators for Water Quality Modeling of Drinking Water Sources

The implementation of microbial fecal source tracking (MST) methods in drinking water management is limited by the lack of knowledge on the transport and decay of host-specific genetic markers in water sources. To address these limitations, the decay and transport of human (BacH) and ruminant (BacR) fecal Bacteroidales 16S rRNA genetic markers in a drinking water source (Lake Rådasjön in Sweden) were simulated using a microbiological model coupled to a three-dimensional hydrodynamic model. The microbiological model was calibrated using data from outdoor microcosm trials performed in March, August, and November 2010 to determine the decay of BacH and BacR markers in relation to traditional fecal indicators. The microcosm trials indicated that the persistence of BacH and BacR in the microcosms was not significantly different from the persistence of traditional fecal indicators. The modeling of BacH and BacR transport within the lake illustrated that the highest levels of genetic markers at the raw water intakes were associated with human fecal sources (on-site sewers and emergency sewer overflow). This novel modeling approach improves the interpretation of MST data, especially when fecal pollution from the same host group is released into the water source from different sites in the catchment.

Variability analysis of pathogen and indicator loads from urban sewer systems along a river.

The pathogen loads within surface waters originating from urban wastewater sources needs to be assessed to support drinking water risk estimations and optimal selection of risk reduction measures. Locally reported discharges from sewer systems (>100,000 persons connected) were used to simulate the potential microbial loads into the Göta älv river, Sweden. Using Monte Carlo simulations, the median and 95% percentile (i.e. worst case) of total microbial load from wastewater treatment plants, sewer network overflows and emergency discharges were assessed and presented for dry and wet weather conditions. Wastewater treatment plants with secondary treatment represented a major source of E. coli, norovirus, Giardia and Cryptosporidium. During wet weather, comparably high microbial loads were found for sewer overflows due to heavy rains. Substantial loads were also associated with an incident of the emergency discharge of untreated wastewater. Simulated river water concentrations of faecal indicators (E. coli, sulfite reducing clostridia, somatic coliphages) and pathogens (norovirus, Giardia, Cryptosporidium) were confirmed by river sampling data, suggesting that urban wastewater is the major microbial source for this river.

Cost-effectiveness analysis of risk-reduction measures to reach water safety targets

Identifying the most suitable risk-reduction measures in drinking water systems requires a thorough analysis of possible alternatives. In addition to the effects on the risk level, also the economic aspects of the risk-reduction alternatives are commonly considered important. Drinking water supplies are complex systems and to avoid sub-optimisation of risk-reduction measures, the entire system from source to tap needs to be considered. There is a lack of methods for quantification of water supply risk reduction in an economic context for entire drinking water systems. The aim of this paper is to present a novel approach for risk assessment in combination with economic analysis to evaluate risk-reduction measures based on a source-to-tap approach. The approach combines a probabilistic and dynamic fault tree method with cost-effectiveness analysis (CEA). The developed approach comprises the following main parts: (1) quantification of risk reduction of alternatives using a probabilistic fault tree model of the entire system; (2) combination of the modelling results with CEA; and (3) evaluation of the alternatives with respect to the risk reduction, the probability of not reaching water safety targets and the cost-effectiveness. The fault tree method and CEA enable comparison of risk-reduction measures in the same quantitative unit and consider costs and uncertainties. The approach provides a structured and thorough analysis of risk-reduction measures that facilitates transparency and long-term planning of drinking water systems in order to avoid sub-optimisation of available resources for risk reduction.

Replacement predictions for drinking water networks through historical data.

Lifetime distribution functions and current network age data can be combined to provide an assessment of the future replacement needs for drinking water distribution networks. Reliable lifetime predictions are limited by a lack of understanding of deterioration processes for different pipe materials under varied conditions. An alternative approach is the use of real historical data for replacement over an extended time series. In this paper, future replacement needs are predicted through historical data representing more than one hundred years of drinking water pipe replacement in Gothenburg, Sweden. The verified data fits well with commonly used lifetime distribution curves. Predictions for the future are discussed in the context of path dependence theory.

Microbial risk assessment of drinking water based on hydrodynamic modelling of pathogen concentrations in source water

Norovirus contamination of drinking water sources is an important cause of waterborne disease outbreaks. Knowledge on pathogen concentrations in source water is needed to assess the ability of a drinking water treatment plant (DWTP) to provide safe drinking water. However, pathogen enumeration in source water samples is often not sufficient to describe the source water quality. In this study, the norovirus concentrations were characterised at the contamination source, i.e. in sewage discharges. Then, the transport of norovirus within the water source (the river Göta älv in Sweden) under different loading conditions was simulated using a hydrodynamic model. Based on the estimated concentrations in source water, the required reduction of norovirus at the DWTP was calculated using quantitative microbial risk assessment (QMRA). The required reduction was compared with the estimated treatment performance at the DWTP. The average estimated concentration in source water varied between 4.8×10(2) and 7.5×10(3) genome equivalents L(-1); and the average required reduction by treatment was between 7.6 and 8.8 Log10. The treatment performance at the DWTP was estimated to be adequate to deal with all tested loading conditions, but was heavily dependent on chlorine disinfection, with the risk of poor reduction by conventional treatment and slow sand filtration. To our knowledge, this is the first article to employ discharge-based QMRA, combined with hydrodynamic modelling, in the context of drinking water.

Estimation of pathogen concentrations in a drinking water source using hydrodynamic modelling and microbial source tracking.

The faecal contamination of drinking water sources can lead to waterborne disease outbreaks. To estimate a potential risk for waterborne infections caused by faecal contamination of drinking water sources, knowledge of the pathogen concentrations in raw water is required. We suggest a novel approach to estimate pathogen concentrations in a drinking water source by using microbial source tracking data and fate and transport modelling. First, the pathogen (norovirus, Cryptosporidium, Escherichia coli O157/H7) concentrations in faecal contamination sources around the drinking water source Lake Rådasjön in Sweden were estimated for endemic and epidemic conditions using measured concentrations of faecal indicators (E. coli and Bacteroidales genetic markers). Afterwards, the fate and transport of pathogens within the lake were simulated using a three-dimensional coupled hydrodynamic and microbiological model. This approach provided information on the contribution from different contamination sources to the pathogen concentrations at the water intake of a drinking water treatment plant. This approach addresses the limitations of monitoring and provides data for quantitative microbial risk assessment (QMRA) and risk management in the context of faecal contamination of surface drinking water sources.

The association of drinking water treatment and distribution network disturbances with Health Call Centre contacts for gastrointestinal illness symptoms.

There are relatively few studies on the association between disturbances in drinking water services and symptoms of gastrointestinal (GI) illness. Health Call Centres data concerning GI illness may be a useful source of information. This study investigates if there is an increased frequency of contacts with the Health Call Centre (HCC) concerning gastrointestinal symptoms at times when there is a risk of impaired water quality due to disturbances at water works or the distribution network. The study was conducted in Gothenburg, a Swedish city with 0.5 million inhabitants with a surface water source of drinking water and two water works. All HCC contacts due to GI symptoms (diarrhoea, vomiting or abdominal pain) were recorded for a three-year period, including also sex, age, and geocoded location of residence. The number of contacts with the HCC in the affected geographical areas were recorded during eight periods of disturbances in the water works (e.g. short stops of chlorine dosing), six periods of large disturbances in the distribution network (e.g. pumping station failure or pipe breaks with major consequences), and 818 pipe break and leak repairs over a three-year period. For each period of disturbance the observed number of calls was compared with the number of calls during a control period without disturbances in the same geographical area. In total about 55, 000 calls to the HCC due to GI symptoms were recorded over the three-year period, 35 per 1000 inhabitants and year, but much higher (>200) for children <3 yrs of age. There was no statistically significant increase in calls due to GI illness during or after disturbances at the water works or in the distribution network. Our results indicate that GI symptoms due to disturbances in water works or the distribution network are rare. The number of serious failures was, however limited, and further studies are needed to be able to assess the risk of GI illness in such cases. The technique of using geocoded HCC data together with geocoded records of disturbances in the drinking water network was feasible.

Uncertainty modelling in multi-criteria analysis of water safety measures

Water utilities must assess risks and make decisions on safety measures in order to obtain a safe and sustainable drinking water supply. The World Health Organization emphasises preparation of water safety plans, in which risk ranking by means of risk matrices with discretised probability and consequence scales is commonly used. Risk ranking enables prioritisation of risks, but there is currently no common and structured way of performing uncertainty analysis and using risk ranking for evaluating and comparing water safety measures. To enable a proper prioritisation of safety measures and an efficient use of available resources for risk reduction, two alternative models linking risk ranking and multi-criteria decision analysis (MCDA) are presented and evaluated. The two models specifically enable uncertainty modelling in MCDA, and they differ in terms of how uncertainties in risk levels are considered. The need of formal handling of risk and uncertainty in MCDA is emphasised in the literature, and the suggested models provide innovations that are not dependent on the application domain. In the case study application presented here, possible safety measures are evaluated based on the benefit of estimated risk reduction, the cost of implementation and the probability of not achieving an acceptable risk level. Additional criteria such as environmental impact and consumer trust may also be included when applying the models. The case study shows how safety measures can be ranked based on preference scores or cost-effectiveness and how measures not reducing the risk enough can be identified and disqualified. Furthermore, the probability of each safety measure being ranked highest can be calculated. The two models provide a stepwise procedure for prioritising safety measures and enable a formalised handling of uncertainties in input data and results.

Incorporating Expert Judgments in Utility Evaluation of Bacteroidales qPCR Assays for Microbial Source Tracking in a Drinking Water Source

Several assays for the detection of host-specific genetic markers of the order Bacteroidales have been developed and used for microbial source tracking (MST) in environmental waters. It is recognized that the source-sensitivity and source-specificity are unknown and variable when introducing these assays in new geographic regions, which reduces their reliability and use. A Bayesian approach was developed to incorporate expert judgments with regional assay sensitivity and specificity assessments in a utility evaluation of a human and a ruminant-specific qPCR assay for MST in a drinking water source. Water samples from Lake Rådasjön were analyzed for E. coli, intestinal enterococci and somatic coliphages through cultivation and for human (BacH) and ruminant-specific (BacR) markers through qPCR assays. Expert judgments were collected regarding the probability of human and ruminant fecal contamination based on fecal indicator organism data and subjective information. Using Bayes formula, the conditional probability of a true human or ruminant fecal contamination given the presence of BacH or BacR was determined stochastically from expert judgments and regional qPCR assay performance, using Beta distributions to represent uncertainties. A web-based computational tool was developed for the procedure, which provides a measure of confidence to findings of host-specific markers and demonstrates the information value from these assays.