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Norovirus dynamics in wastewater discharges and in the recipient drinking water source: Long-term monitoring and hydrodynamic modelling Olaf Dienus, Ekaterina Sokolova, Fredrik Nyström, Andreas Matussek, Sture Löfgren, Lena Blom, Thomas J.R. Pettersson, and Per-Eric Lindgren Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b02110 • Publication Date (Web): 20 Sep 2016 Downloaded from http://pubs.acs.org on September 20, 2016
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Norovirus dynamics in wastewater discharges and in the recipient drinking water source: Long-
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term monitoring and hydrodynamic modelling
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Olaf Dienus 1, 2, Ekaterina Sokolova 3, *, Fredrik Nyström 1, 2, a, Andreas Matussek 1, Sture Löfgren 1,
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Lena Blom 3, 4, Thomas J.R. Pettersson 3, Per-Eric Lindgren 1, 2
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1
Ryhov County Hospital, Medical Services, Clinical Microbiology, SE-551 85 Jönköping, Sweden
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2
Linköping University, Department of Clinical and Experimental Medicine, Medical Microbiology, SE-
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581 85 Linköping, Sweden
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3
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Environment Technology, SE-412 96 Gothenburg, Sweden
Chalmers University of Technology, Department of Civil and Environmental Engineering, Water
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4
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Sweden
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a
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Resources Engineering, Architecture and Water, SE-971 87 Luleå, Sweden
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* Corresponding author, e-mail:
[email protected]; phone: +46 31 7721929
City of Gothenburg, Department of Sustainable Waste and Water, Box 123, SE-424 23 Angered,
Currently: Luleå University of Technology, Department of Civil, Environmental and Natural
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Supporting Information. Details regarding the sampling programme, norovirus analyses,
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hydrodynamic modelling, measured microbial concentrations in wastewater, simulated microbial
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concentrations in source water.
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Abstract
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Norovirus (NoV) that enters drinking water sources with wastewater discharges is a common cause
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of waterborne outbreaks. The impact of wastewater treatment plants (WWTPs) on the river Göta älv
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(Sweden) was studied using monitoring and hydrodynamic modelling. The concentrations of NoV
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genogroups (GG) I and II in samples collected at WWTPs and drinking water intakes (source water)
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during one year were quantified using duplex real-time reverse-transcription PCR. The mean
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(standard deviation) NoV GGI and GGII genome concentrations were 6.2 (1.4) and 6.8 (1.8) in
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incoming wastewater, and 5.3 (1.4) and 5.9 (1.4) Log10 genome equivalents (g.e.) L-1 in treated
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wastewater, respectively. The reduction at the WWTPs varied between 0.4 and 1.1 Log10 units. In
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source water, the concentration ranged from below the detection limit to 3.8 Log10 g.e. L-1. NoV GGII
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was detected in both wastewater and source water more frequently during the cold than the warm
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period of the year. The spread of NoV in the river was simulated using a three-dimensional
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hydrodynamic model. The modelling results indicated that the NoV GGI and GGII genome
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concentrations in source water may occasionally be up to 2.8 and 1.9 Log10 units higher, respectively,
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than the concentrations measured during the monitoring project.
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Key words: Göta älv; E. coli; norovirus; somatic coliphages; sewage; real-time PCR; water quality.
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1 Introduction
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Human norovirus (NoV) is highly infectious.1-2 NoV spreads rapidly through person-to-person contact,
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airborne droplets, and water and food.1 Immunity after the disease is incomplete and short-lived,3
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thus repeated infections of the same agent are common. Stool from infected individuals contains 105
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to 1012 NoV per gram.4 Viruses are generally resistant to current methods of wastewater treatment
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and often remain infectious for a long time in the environment.5 Thus, wastewater discharges to
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drinking water sources pose risks of waterborne disease outbreaks.6-7
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NoV is one of the most common causes of nonbacterial waterborne outbreaks of gastroenteritis in all
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age groups.8 One of the largest waterborne NoV gastroenteritis outbreaks in Sweden in recent years
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occurred in the municipality of Lilla Edet in 2008, with approximately 2400 cases. It was suspected
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that the cause of the outbreak was the contamination of the drinking water source – the river Göta
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älv.9
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Traditionally, microbial water quality control is based on detection of faecal indicator
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microorganisms, e.g. E. coli, coliforms, and coliphages. However, there is a lack of correlation
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between the concentrations of faecal indicator bacteria and specific pathogens, such as NoV.10-12 Yet,
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there are contradictory reports regarding the correlation between the concentrations of somatic
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coliphages and NoV in source water.11, 13 Thus, traditional water quality monitoring may not fully
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predict the health risks.14
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Little is known about the concentrations of NoV in source water, but this information is crucial for
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the assessment of health risks for drinking water consumers.15 Molecular methods, like reverse
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transcription – quantitative polymerase chain reaction (RT-qPCR) with a high sensitivity for detection
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of NoV in water,16 have the potential to provide this information.
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Microbial water quality can also be studied by hydrodynamic models, which simulate the spread of
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faecal contamination in a water source. Hydrodynamic modelling can be used to describe the
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temporal and spatial variability of microbial concentrations,17 to study the influence of different
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processes on the microbial water quality,18 and to quantify the relative impact of different faecal
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sources.19 In addition, this approach can be used to quantify the concentrations that are below the
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detection limits of analytical methods, yet still high enough to be relevant to consumer health.20
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The aim of this study was to determine the seasonal dynamics of NoV in wastewater and in the
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recipient drinking water source – the river Göta älv in Sweden. For this purpose, the concentrations
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of NoV and faecal indicators E. coli and somatic coliphages were (i) measured during long-term
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monitoring, and (ii) simulated by means of hydrodynamic modelling. 3 ACS Paragon Plus Environment
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2 Methods
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2.1 Study area
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Göta älv is a river that drains Lake Vänern into the strait Kattegat at the city of Gothenburg on the
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west coast of Sweden (Figure S1). The total catchment area of the river Göta älv is 50 233 km2, which
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constitutes approximately 10 % of the area of Sweden. The part of the catchment area that is located
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downstream of Lake Vänern is approximately 3500 km2. The length of the river between the outflow
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from Lake Vänern and the mouth of the river is 93 km. The vertical drop of the river is approximately
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44 m. The water flow in the river Göta älv is regulated by several hydropower stations (Figure S1) and
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varies strongly; the mean and the maximum water flows are 550 and 1000 m3 s-1, respectively. The
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transport time between the outflow from Lake Vänern and the mouth of the river is between 1.5 and
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5 days.
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The river is used as a water source for the drinking water supply of 700 000 consumers in several
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municipalities, including Gothenburg with 500 000 consumers. Between Lake Vänern and the water
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intake for the city of Gothenburg (Figure S1) the river receives wastewater from approximately 100
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000 persons. Approximately 95 % of this wastewater is treated at municipal wastewater treatment
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plants (WWTPs), while 5 % is treated by on-site sewer systems.
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2.2 Sampling
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Source water samples (n=58) were collected from five drinking water treatment plants (DWTPs)
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along the river: Skräcklan in Vänersborg, Överby in Trollhättan, Lilla Edet, Dösebacka in Kungälv, and
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Lärjeholm in Gothenburg (Figure S1). Wastewater samples (n=160) were collected from four WWTPs:
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Holmängen in Vänersborg, Arvidstorp in Trollhättan, Ellbo in Lilla Edet, and Ryaverket in Gothenburg
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(Figure S1).
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Sampling was conducted during one year, from 8 June 2011 to 5 June 2012 (Table S1). Source water
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samples were collected as 10.5 L grab samples of the incoming water at the DWTPs. Wastewater 4 ACS Paragon Plus Environment
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samples were collected at the WWTPs continuously for 24 hours using automatic flow rate controlled
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samplers; 1.5 L was used for further analyses. The 24 hour sampling was done to compensate for
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fluctuations in concentration. All samples were collected in sterile glass containers and kept at 4 °C
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until analysis. From each sample, 0.5 L was used for faecal indicator analyses.
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2.3 Norovirus analyses
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In this study, NoV genogroups (GG) I and II were studied. NoV genome concentrations were analysed
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at the Microbiology Laboratory, Medical Services, County Hospital Ryhov, Jönköping. The details
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regarding enrichment from source water and wastewater, extraction of RNA and reverse
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transcription, detection and quantification by TaqMan real-time PCR, and controls of the
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methodology are described in supporting information.
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For source water, the limit of quantification (LOQ) was 3.8×101 g.e. L-1, and the limit of detection
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(LOD) was extrapolated to 1.1×101 g.e. L-1. For wastewater, the LOQ was 1.5×104 g.e. L-1, and the LOD
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was extrapolated to 4.5×103 g.e. L-1.
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To control virus enrichment and RNA extraction steps, the samples were spiked with murine
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norovirus 1 solution (MNV-1). The recovery rate was estimated for each sample using quantitative
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real-time PCR for MNV-1. Inhibition control of the reverse transcription step was done with Alien
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Reference RNA VIC QRT-PCR Detection Kit. To rule out PCR inhibition and to optimise PCR
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performance, tick-borne encephalitis virus (TBEV) was used.
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The process control MNV-1 showed that the virus recovery rate varied between 1.2 % and 23 % with
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a mean of 18 % for source water, and between 0.1 % and 31 % with a mean of 5 % for wastewater.
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All reported concentrations were corrected for the recovery rate. Inhibition control of the reverse
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transcription step showed no inhibition. The PCR inhibition control TBEV showed no inhibition.
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2.4 Faecal indicator analyses
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The concentrations of E. coli were analysed within four hours after sampling at ALcontrol AB,
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Linköping, Sweden, according to the Swedish standard SS 028167-2 (membrane filtration method).
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The concentrations of somatic coliphages were analysed on the sampling day at Lackarebäck
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laboratory, Gothenburg, Sweden, according to the standard ISO 10705-2 (plaque assay method).
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2.5 Statistical analyses
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The measured data were Log10 transformed and analysed using t-tests and correlation analyses. To
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analyse the seasonality of concentrations, the warm and cold periods were defined based on
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whether the air temperature was above or below +10 °C, respectively. The warm period included 13
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sampling occasions (8 Jun 2011 – 12 Oct 2011 and 9 May 2012 – 5 Jun 2012); and the cold period
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included 14 sampling occasions (26 Oct 2011 – 25 Apr 2012). To compare the number of samples
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above the LOD during the warm and cold periods, Fischer’s exact test was used. P-value
