Occurrence and infection risk of waterborne pathogens in Wanzhou watershed of the Three Gorges Reservoir, China

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JOURNAL OF ENVIRONMENTAL SCIENCES ISSN 1001-0742 CN 11-2629/X

Journal of Environmental Sciences 2013, 25(9) 1913–1924

www.jesc.ac.cn

Occurrence and infection risk of waterborne pathogens in Wanzhou watershed of the Three Gorges Reservoir, China Guosheng Xiao1,2 , Zhaodan Wang2 , Ji’an Chen1 , Zhiqun Qiu1 , Yanjie Li2 , Junsheng Qi2 , Wenyi Liu1 , Weiqun Shu1, ∗ 1. Department of Environmental Hygiene, School of Military Preventive Medicine, Third Military Medical University, Chongqing 400038, China. E-mail: [email protected] 2. College of Life Science and Engineering, Chongqing Three Gorges University, Wanzhou Chongqing 404100, China Revised 12 November 2012; revised 09 January 2012; accepted 01 April 2013

Abstract The Three Gorges Reservoir (TGR), formed by China’s Yangtze Three Gorges Project, is the largest lake in the world, but there is too little information available about fecal contamination and waterborne pathogen impacts on this aquatic ecosystem. During two successive 1-year study periods (July 2009 to July 2011), the water quality in Wanzhou watershed of the TGR was tested with regard to the presence of fecal indicators and pathogens. According to Chinese and World Health Organization water quality standards, water quality in the mainstream was good but poor in backwater areas. Salmonella, Enterohemorrhagic Escherichia coli (EHEC), Giardia and Cryptosporidium were detected in the watershed. Prevalence and concentrations of the pathogens in the mainstream were lower than those in backwater areas. The estimated risk of infection with Salmonella, EHEC, Cryptosporidium, and Giardia per exposure event ranged from 2.9 × 10−7 to 1.68 × 10−5 , 7.04 × 10−10 to 2.36 × 10−7 , 5.39 × 10−6 to 1.25 × 10−4 and 0 to 1.2 × 10−3 , respectively, for occupational divers and recreational swimmers exposed to the waters. The estimated risk of infection at exposure to the 95% upper confidence limit concentrations of Salmonella, Cryptosporidium and Giardia may be up to 2.62 × 10−5 , 2.55 × 10−4 and 2.86 × 10−3 , respectively. This study provides useful information for the residents, health care workers and managers to improve the safety of surface water and reduce the risk of fecal contamination in the TGR. Key words: the Three Gorges Reservoir; microbial risk assessment; fecal contamination; waterborne pathogen; fecal indicator DOI:10.1016/S1001-0742(12)60241-1

Introduction Source water quality is highly variable in part due to frequent contamination of water resources by waterborne bacterial, viral and protozoan pathogens. Understanding this variability is important as it will influence the requirements for treatment, treatment efficiency and the resulting health risk associated with the finished water (Dechesne and Soyeux, 2007; Schets et al., 2008; WHO, 2009b; Xiao et al., 2012). Furthermore, exposure to microbiologically contaminated surface water may have adverse health effects and may result in waterborne diseases (WHO, 2003). Outbreaks of waterborne diseases have frequently occurred in developing countries (Ashbolt, 2004; WHO, 2009a). Since pathogens appear intermittently in natural waters at low concentrations, and detection and quantification of each pathogen is labor-intensive and not easy to perform in most cases, routine microbiological water analyses still * Corresponding author. E-mail: [email protected]

rely on fecal indicator organisms that share the same habitats (Savichtcheva and Okabe, 2006). However, many publications report that fecal indicator bacteria are poor surrogates for pathogen presence and concentrations, and outbreaks of waterborne disease have still occurred despite the absence of fecal indicators in source water (Barrell et al., 2000; Dechesne and Soyeux, 2007). Therefore, bacterial, viral and parasitic enteric pathogens are also monitored to achieve a representative quantification of numbers of pathogenic microorganisms in source water (Dechesne and Soyeux, 2007; WHO, 2011). The Three Gorges Reservoir (TGR) is formed by China’s Yangtze Three Gorges Project, the world’s largest hydropower project and a major source of drinking water in China, with a highly urbanized coast. The construction of the Three Gorges Dam started in 1993 and was mostly completed in 2009. The water level of the reservoir rose to 135 m above sea level in 2003, and was lifted to 156 m in late 2006 and 172 m in late 2008 (Fu et al., 2010),

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Journal of Environmental Sciences 2013, 25(9) 1913–1924 / Guosheng Xiao et al.

and it first reached the 175-m highest water level on 26 October 2010. The regulation of the water level of the TGR is divided into the flood recession period (June to September) and the impounding period (October to May), which are also known as the rainy season and the dry season. Water in the TGR has been seriously polluted by more than 1 billion tons of industrial polluted water and domestic sewage that are released into the reservoir every year, especially in cities’ sections (Fu et al., 2010; Gleick et al., 2009; MEP, 2010; Ye et al., 2008). Despite the awareness of sources possibly contributing to surface water contamination in the TGR, no data have been available on the water quality and the occurrence of pathogenic organisms in any watersheds of the TGR since the reservoir began to store water. Therefore, the objectives of this study were to: (1) assess the contribution of 800,000-population Wanzhou City, which is the largest city along the TGR, to microbial contamination; (2) test surface water in Wanzhou watershed of the TGR intended for occupational and recreational purpose for the presence of a range of waterborne pathogens and compliance with the standards for microbiological quality as required by Chinese environment quality standard for surface water and World Health Organization (WHO) guidelines for safe recreational water environments, and (3) provide the risk estimate of infection with pathogens from occupational and recreational exposure to waters in Wanzhou watershed.

1 Materials and methods 1.1 Site description and water sampling The TGR drains a 1084 km2 watershed that is home to approximately 16.8 million residents in 21 regions or counties of the Three Gorges Reservoir Area (left map, Fig. 1). Wanzhou watershed is located in the middle of the TGR and the Yangtze River runs across Wanzhou City, which at about 800,000 population is the largest city along the TGR. Sampling sites were located at the intake area of a water plant (1), upstream (2), downstream (4), and backwater areas of tributaries (3, 5), backwater areas of the city (6, 7), and wastewater treatment plants (WWTPs) (8, 9, 10) employing an A2 /O oxidation ditch process (right map, Fig. 1). Water samples were collected 1 or 2 times per month from July 2009 to July 2011. Water samples of each site were collected from surface strata at a depth of 0.5 m by using a TN-S water sampler (Jintan Taina Instrument Factory, Jiangshu, China). Mixed water samples of the left, middle, and right banks of the water body were collected at sampling sites 2, 3, 4, and 5. The samples were collected aseptically in 25-L sterilized high-density polypropylene, screw-capped water containers that were pre-washed by HCl and sterile distilled water. Samples were stored in the dark at 4°C and immediately transferred to the laboratory for analysis. At each sampling site, water temperature and total dis-

Vol. 25

N Wuxi Kaixian

Xingshan

Wushan Badong

Yunyang

Fengjie

Saiwangba Zhuxi River

Wanzhou

Yangtze River

Reservoir Dam

Zhongxian Shizhu Changshou Yubei

Fengdu

Yangtze River

Chongqing Fuling Wulong Banan

175-m water level area Wanzhou City Cities and towns Sampling sites Wastewater treatment plant Streets

Wuqiao River

Fig. 1 Regional (left) and local (right) maps of sampling sites located in Wanzhou watershed of the Three Gorges Reservoir. (1) intake area of water plant; (2) upstream, (3) backwater area of Wuqiao River, (4) downstream, (5) backwater area at Zhuxi River, (6, 7) backwater areas of the city, (8, 9, 10) wastewater treatment plants.

solved solids (TDS) were measured in situ using a portable SG3 conductivity meter (Mettler Toledo, Co., China), and turbidity was measured using a 1900C turbidimeter (Hach, Co., USA). Daily flow and water level data of the TGR on sampling days and the 3 days preceding sampling were obtained from the Yangtze River Waterway Bureau of China (http://www.moc.gov.cn/zizhan/). 1.2 Conventional procedures for fecal indicator bacteria The five-tube most probable numbers (MPN) procedure was used to enumerate total coliform, fecal coliform and Escherichia coli according to the Chinese standard examination method for drinking water, microbiological parameters (GB/T 5750.12-2006). An appropriate ten-fold serial dilution of each sample, in general, 100 , 10−1 ,10−2 for surface water, 10−3 , 10−4 , 10−5 for sewage, was carried out and 1 mL each of serial dilutions were transferred to five tubes of lactose peptone broth (10 mL) with inverted Durham tubes, which were then incubated at 37°C for (24 ± 2) hr. All positive presumptive tubes that demonstrated an acidic reaction or gas production were submitted to the confirmed phase with total coliform test using eosin methylene blue agar, fecal coliform test using EC medium, and E. coli test using ECMUG (4-methylumbelliferyl-β-D-glucuronide) (Biosynth AG, Staad, Switzerland) medium according to the above standards, respectively. Fecal streptococci were enumerated according to the Chinese standard for urban water supply–detection and enumeration of fecal streptococcus using Kenner Fecal (KF) streptococci agar (76.4 g KF streptococcus agar, 10 mL of 1% 2,3,5-triphenyltetrazolium chloride solution and 1 L distilled water, prepared according to the standard) as isolation medium (CJ/T 148-2001). Appropriate sample volumes were filtered through a 0.45-μm sterile membrane (Millipore, Corp., Bedford, USA) to give 20 to 100

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colonies on the membrane surface. 1.3 MPN-PCR for fecal indicators and pathogenic bacteria 1.3.1 Primers The MPN method combined with nested PCR, multiplex PCR, and PCR was used to detect and enumerate Salmonella spp., Enterchemorrhagic Escherichia coli (EHEC) and Enterococci in surface water and sewage. Primers of PCR were selected from the references (Table 1). 1.3.2 MPN-PCR amplification of Enterococci An appropriate ten-fold serial dilution of each sample, in general, 10, 1, 10−1 for surface water, l, 10−1 , 10−2 for sewage, was carried out and 10 mL or 1 mL each of three serial dilutions were transferred to three tubes of bile esculin azide broth (10 mL, using double-strength broth for 10-mL inocula) according to the Chinese standard for detection of Enterococci in food and water–Part 1: Method for plate count and MPN (SN/T 1933.1-2007). The tubes were incubated for (24 ± 2) hr at 37°C and then examined for brownish-black change. If negative, the culture was reincubated and examined again at (48 ± 2) hr. Positive presumptive tubes with a black change were confirmed by PCR amplification for the tuf gene of Enterococci (Ke et al., 1999). Each incubated culture of 1.5 mL from positive presumptive tubes was centrifuged at 6000 r/min for 4 min, and the sediment was washed 2 times with sterile distilled water and suspended with 0.5 mL sterile distilled water. The suspension was boiled for 10 min and then swiftly placed into a refrigerator at –20°C for 10 min. The suspension was centrifuged at 12,000 r/min for 10 min and the supernatant was used as the template of PCR. The 5 μL of DNA was subjected to PCR amplification and amplification conditions were as previously described (Ke et al., 1999). 1.3.3 MPN-PCR amplification of Salmonella and EHEC MPN-nested-PCR and MPN-multiplex-PCR were carried out to detect and enumerate Salmonella spp. and EHEC,

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respectively. Three replicates of three different volumes (1 L, 100 mL and 10 mL) for surface water, while for sewage samples, three volumes (100 mL, 10 mL and 1 mL) were used to determine the MPN (Lemarchand and Lebaron, 2003). Each water sample was filtered through one or more 50-mm-diameter, 0.45-μm-pore-sized nitrocellulose membrane filters (Millipore, Corp., Bedford, USA). Then, each set of filters (three per volume) was incubated and vortexed in one tube of buffered peptone water. After removing filters, bacteria were cultivated for pre-enrichment at 37°C for 20–24 hr. An aliquot of 0.2 mL was subsequently enriched in 20 mL of Rappaport Vassiliadis broth at 42°C for 48 hr and EC broth at 42°C for 24 hr. DNA extraction was performed as per the reference (Oliveira et al., 2003). The reaction mixture and PCR conditions were as previously described (Cebula et al., 1995; Deadre et al., 1998). 1.3.4 Quantification and confirmation After each PCR assay, 10 μL of the amplification product were analyzed on 1.5% agarose gel containing 0.4 μg/mL ethidium bromide. The number of tubes which showed positive results for the PCR was counted as containing target bacteria. The number of PCR-positive tubes in each dilution was recorded and the MPN of target bacteria present in the sample was back-calculated by reading from the MPN table. 10% of all positive PCR products were randomly sampled and purified, and then directly sequenced. The PCR products of the gene were sequenced directly with PCR primers on an ABI PrismTM ABI3130 genetic analyzer (Applied Biosystems, USA), using an ABI BigDye Terminator v. 3.1 cycle sequencing kit (Applied Biosystems, USA). Nucleotide sequences obtained in the study were aligned with reference sequences from the Genbank and analyzed to confirm target products using ClustalX 1.83. 1.4 Filtration/IMS/FA methods for Cryptosporidium and Giardia For enumeration of Cryptosporidium and Giardia, water samples (approximately 40 L in impounding period and 20 L in flood period) were concentrated using Envirochek HV

Table 1 List of MPN-PCR primers for detecting microbial indictors and pathogenic bacteria Target bacteria

Primer∗

Sequence (5 to 3 )

Target gene

Product size (bp)

Reference

Salmonella spp.

SALa SALb SAIa SAIb ESLT-Ia ESLT-Ib ESLT-IIa ESLT-IIb ENTa ENTb

CTGAACGAAATCGACCGTGTA GGATGTACCGTTATCTGCAGT CGGGTGTCAACAATTGACCAA AATAGCTAATTGCTGCCGAGG CAGTTAATGTGGTGGCGAAGG CACCAGACAATGTAACCGCTG ATCCTATTCCCGGGAGTTTACG GCGTCATCGTATACACAGGAGC TACTGACAAACCATTCATGATG AACTTCGTCACCAACGCGAAC

Hl

699

Deadre et al., 1998

Hin

484

SLT-I

348

SLT-II

584

tuf

112

Enterohemorrhagic Escherichia coli (EHEC)

Enterococci * a: upper primer; b: lower primer.

Cebula et al., 1995

Ke et al., 1999

Journal of Environmental Sciences 2013, 25(9) 1913–1924 / Guosheng Xiao et al.

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filtration capsules (Pall Corporation, USA) as described in the Chinese standard examination method for drinking water, microbiological parameters (GB/T 5750.12-2006). Concentrated samples were purified by immunomagnetic separation (IMS) using the Dynal GC-Combo system (Dynal Biotech ASA, Oslo, Norway) according to the manufacturer’s instructions. Slides (Idexx Laboratories, Inc., Maine, USA) for microscopy were stained with 50 μL of 4 ,6-diamidino-2-phenylindole (DAPI) (Sigma, USA) solutions (10 μL of DAPI methanol solution (2 mg/mL) was added into 50 mL phosphate-buffered saline (0.01 mol/L, pH 7.4) for 2 min at room temperature; subsequently, 50 μL of EasyStain™ Cryptosporidium and Giardia fluorescein isothiocyanate (FITC)-antibody reagent (BTF Pty Ltd., Sydney, Australia) was added and incubated at 37°C for 30 min according to the manufacturer’s instructions. Slides were subsequently mounted with an EasyStain mounting kit (BTF Pty Ltd., Sydney, Australia), sealed with colorless nail polish, and examined at ×400 magnification using fluorescence microscopy (Olympus, Japan). When an apple green fluorescent event was observed, which was characteristic of a Cryptosporidium oocyst or Giardia cyst, the object was examined with the UV filter block for DAPI staining and subsequently with differential interface contrast microscopy. (Oo)cysts were examined in detail at ×1000 magnification to verify the presence of internal structures. 1.5 Quality control A reaction mixture containing ultrapure water was included as a negative and Enterococci fecal (ATCC 29212), E. coli O157 :H7 (NCTC 12900) and Salmonella typhimurium (CMCC 50115) were used as positive control strains. GC quality control EasySeed™ kits (BTF Pty Ltd., Sydney, Australia) containing 100 inactivated Cryptosporidium oocysts and 100 Giardia cysts in 1 mL of saline solution, were used for testing performance and to calculate (oo)cyst recovery rates. 1.6 Water quality assessment Observations obtained from the mainstream (n = 92), backwater areas of tributaries (n = 60) and backwater area of the city (n = 36) were tested for compliance with Chinese environmental quality standards for surface water (GB 3838-2002) and WHO guidelines for safe recreational Table 2

water environments volume 1: coastal and fresh water (WHO, 2003) for fecal indicators (Table 2). 1.7 Risk assessment 1.7.1 Exposure assessment Data on swimming water exposure in Wanzhou watershed in summer (June–August) of years 2009 and 2010 were collected through face-to-face administration of questionnaires to 718 swimmers who were provided by the Wanzhou Swimming Association according to the survey method previously reported (Schijven and de Roda Husman, 2006). Swimmers gave their consent for responding to questionnaires about various topics, in return for a small consideration. The questionnaire included questions about frequency and duration of swimming, the amount of water swallowed per swimming event, head submersion while swimming, the type of swimming mask, whether or not swimming took place at monitoring sites, and general health and health complaints that may possibly have been due to an infection from a waterborne pathogen after swimming. Questions about health complaints encompassed respiratory, eye, skin and ear complaints, diarrhea, vomiting, and nausea. Swimmers also provided information on basic demographic characteristics such as age, gender, address, and composition of family. An individual older than 15 years old was listed as an adult and individuals 15 years of age and younger were listed as non-adults. People of 15 years of age or older answered the questions for themselves and if they had children between zero and 14 years of age, they also answered the questions for their eldest child. Swimmers were asked to report actual numbers of swimming events in surface water. The time spent in the water could be reported in classes of minutes of water contact (0–30, 30–60, 60–120, 120–300 min). The participants were asked to report the volume of water they swallowed as an estimated number of mouthfuls in four classes: (1) no water or only a few drops, (2) one to two mouthfuls, (3) three to five mouthfuls, and, (4) six to eight mouthfuls. To provide a frame of reference it was indicated that the volume of one to two mouthfuls was comparable to the contents of a shot glass, that of three to five mouthfuls to the contents of a coffee cup and that of six to eight mouthfuls to the contents of a soda glass (Schijven and de Roda Husman, 2006).

Standards for fecal indicators according to Chinese environment quality standard for surface water and WHO guidelines for safe recreational water environments volume 1

Directive

Categorya

Parameter

WHO guideline GB 3838-2002

Moderate

Intestinal enterococci Fecal coliforms

Very good/I

a

Vol. 25

 40  20

Microbial water quality assessment categoryb (95th percentile fecal indicators/100 mL) Good/II Fair/III Poor/IV 41–200 21–200

201–500 201–1000

>500 1001–2000

V 2001–4000

Category refers to sanitary inspection category (susceptibility to fecal influence) according to the WHO guideline. A four-level classification for – very good, good, fair, and poor according to WHO guideline; a five-level classification for –I, II, III, IV and V according to GB 3838-2002. b

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Occurrence and infection risk of waterborne pathogens in Wanzhou watershed of the Three Gorges Reservoir, China

1.7.2 Risk of infection For both occupational and recreational contact with river water of the studied Wanzhou watershed, the risk of infection with Salmonella, EHEC,Cryptosporidium and Giardia per exposure event was estimated. The swallowed volume in the study and the four other estimated and ingested volumes per contact event obtained in a survey of diving behavior and water ingestion among occupational and sport divers (Schijven and de Roda Husman, 2006), and the outcome of a study on water ingestion by swimmers (men, women and children) in fresh water (Schets et al., 2011) were used in calculations. The following two models were chosen to determine the probability of infection (Pint ) from ingestion of various numbers of Salmonella and EHEC, and Cryptosporidium and Giardia, respectively. The Beta-Poisson dose-response model:

−α N Pinf = 1 − 1 + β

(1)

the exponential dose-response model:

Pinf = 1 − e−γN N =C×V

(2) (3)

where, α, β and γ are constants showing the probability that a single organism can reach the target organ to cause an infection, N is the pathogen number of exposures per event, C (number/L) is the measured concentration of pathogens in water samples and V (L) is individual consumption of water (McBride et al., 2002). Dose-response parameter values (αSalmonella = 0.33 and βSalmonella = 139.9, αpathogenicE.coli = 0.1778 and βpathogenic E.coli = 1.8×106 , γCryptosporidium = 0.0042 and γGiardia =0.0199) were used in this study (McBride et al., 2002). 1.8 Data analysis ProUCL 4.1 (version 4.1.01), a statistical software for environmental applications for data sets with and without non-detected observations (uncensored and censored data), was used in the study (US EPA, 2011). The 95% upper confidence limit (UCL) concentration was calculated with the Kaplan-Meier method of nonparametric statistics and the nonparametric Wilcoxon-Mann-Whitney test was used to evaluate significant differences of data sets. The nonparametric Spearman’s rho was calculated to evaluate relationships between bacterial indicators, hydrologic parameters and pathogen concentrations. The chi-squared test was used to evaluate possible significant differences in the prevalence of pathogen positive samples. Statistical significance was assessed at P < 0.05.

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2 Results 2.1 Fecal indicator bacteria Total coliform, fecal coliform, E. coli, fecal streptococci and intestinal enterococci were detected in the majority of samples from all sites. Concentrations varied throughout sampling years and per sampling site. The arithmetic mean and standard deviation of fecal indicator bacteria, hydrologic and physical parameters are displayed in Table 3. Average concentrations of fecal indicators were significantly higher in backwater areas of tributaries and the city (3, 5, 6) than those in the mainstream of the Yangtze River (1, 2, 4) (P < 0.05), but in the flood period, concentrations of fecal indicators at all sites were not significantly different and were significantly influenced by daily inflow and heavy rainfall in the region and its upstream. In mainstream sites (1, 2, 4) of the Yangtze River and backwater area sites (3, 5, 6) of tributaries and the city, fecal indicator parameters displayed peak concentrations on 27 August 2009, 10 July 2010 and 7 July 2011, which coincided with heavy rainfall events on this sampling day and 3 days before sampling (daily inflow 27800 to 30700 m3 /sec, 18700 to 23000 m3 /sec, 15000 to 30000 m3 /sec in 4 days, respectively; average daily inflow 29175, 20550, 20200 m3 /sec, respectively) (Fig. 2), but the peak concentration of fecal indicator parameters did not coincide with the daily inflow peak of the TGR on this sampling day (on 24 July 2010) and 3 days before sampling (daily inflow 31,000 to 58,000 m3 /sec in 4 days; average daily inflow, 43,750 m3 /sec) (Fig. 2). Relationships between fecal indicators and daily inflow on the sampling day were significantly correlated with correlation coefficients from 0.56 to 0.93 (P < 0.01) in mainstream sites (1, 2, 4), except E. coli with correlation coefficient 0.2 in the downstream (4), but not in the backwater area of the city. Significant correlations were obtained between fecal indicator concentrations (r = 0.62 to 0.98, P < 0.01) and a weak but significant correlation was found between fecal indicators and Salmonella (r = 0.39 to 0.43, P < 0.01), fecal indicators and EHEC (r = 0.44 to 0.48, P < 0.01). However, a weak but significant negative correlation was also found between water level and fecal indicators (r = –0.35 to –0.43, P < 0.01) except E. coli with correlation coefficient –0.1. 2.2 Effects of reservoir impoundment on water quality During two impounding periods (Oct 2009 to May 2010 and Oct 2010 to May 2011), fecal indicator concentrations in 94.7% of water samples from the downstream (4) were much higher than those from the upstream (2), and average concentrations were significantly higher in the downstream and backwater areas than those in the upstream (P < 0.05, Table 3). Prevalence and average concentrations of Salmonella spp., Cryptosporidium and

Journal of Environmental Sciences 2013, 25(9) 1913–1924 / Guosheng Xiao et al.

1918

Vol. 25

6.0

60000

5.5 5.0 4.5

40000

4.0

35000

3.5

30000

3.0

25000

2.5

20000

2.0

15000

1.5

10000

1.0

5000

0.5

2 7 -J

u l-0 9

0

g -0 9 2 7 -A u g -0 9 1 2 -S e p -0 9 4 -Otc -0 9 1 7 -O ct-0 9 1 4 -N o v -0 9 5 - De c-0 9 1 -J a n -1 0 6 -Ma r-1 0 2 0 -M a r-1 0 1 5 -A p r -1 0 2 - Ma y -1 0 1 5 -M a y -1 0 2 9 -M a y -1 0 1 2 -J u n -1 0 2 6 -J u n -1 0 1 0 -J u l-1 0 2 4 -J u l-1 0 2 0 -A u g -1 0 1 8 -S e p -1 0 1 6 -O ct-1 0 1 3 -N o v -1 0 1 2 -D e c -1 0 8 -J a n -1 1 2 6 -F e b -1 1 1 9 -M a r-1 1 1 5 -A p r-1 1 1 4 -M a y -1 1 2 0 -J u n -1 1 7 -J u l11

45000

0

1 - Au

Daily flow (m3/sec)

50000

Fecal coliform Fecal streptococci Daily inflow Sampling day

Indicator bacteria (log number/100 mL)

Total coliform E. coli Intestinal enterococci Daily outflow

55000

Sampling time Fig. 2 Changes of fecal indicator bacteria and daily flow for the full sampling period in the downstream of Wanzhou watershed. Sampling time in the boxes of the X-axis is the impounding period of the Three Gorges Reservoir. Table 3

Fecal indicator bacteria, hydrologic and physical parameters in monitoring waters in Wanzhou watershed of the Three Gorges Reservoir

Site (sampling site No.)

Sampling period (no. of sample)

Concentrations of fecal indicator bacteria (log10 , mean±SD)a

Hydrologic and physical parameters (mean±SD)

TC

FC

EC

FS

IE

Turb.

Temp.

TDS

Level

Inflow

(MPN/100 mL)

(MPN/100 mL)

(MPN/100 mL)

(CFU/100 mL)

(MPN/100 mL)

(NTU)

(°C)

(mg/L)

(m)

(m3 /sec)

Flood period (12)

3.65±3.84

3.65±3.84

2.83±3.18

2.53±2.67

2.42±2.61

191.01±212.58

24.9±1.9

156.7±20.08

150.2±5.6

20608±5500

Impounding period (19)

1.89±1.90

1.86±1.91

1.57±1.53

1.23±1.29

0.83±0.88

4.99±2.68

17.1±3.9

57.6±77.63

164.1±8.0

6573±3094

Flood period (12)

3.29±3.33

3.27±3.34

2.50±2.63

2.47±2.38

2.31±2.25

262.39±316.58

24.5±1.5

157.28±21.09

150.2±5.6

20608±5500

Impounding period (19)

2.71±2.69

2.69±2.69

2.49±2.63

1.78±1.85

1.43±1.53

4.59±2.48

17.2±3.9

56.99±77.32

164.1±8.0

6573±3094

Flood period (11)

3.65±3.80

3.59±3.78

2.73±2.85

2.60±2.74

2.39±2.51

296.15±336.31

25.0±1.8

157.18±22.11

150.2±5.6

20608±5500

Impounding period (19)

2.72±3.08

2.69±3.08

2.57±3.09

1.60±1.65

1.58±1.99

5.06±2.99

17.1±4.2

55.02±73.03

164.1±8.0

6573±3094

Flood period (11)

4.14±3.70

4.15±3.61

3.76±3.78

3.52±3.55

3.26±3.49

259.06±524.72

25.3±1.6

163.25±23.75

150.2±5.6

–

Impounding period (19)

3.46±3.63

3.32±3.57

2.96±3.1

2.51±2.75

2.08±2.26

7.62±9.54

17.6±3.9

59.74±80.76

164.1±8.0

–

Flood period(11)

3.99±3.86

3.99±3.86

3.65±3.80

3.03±3.06

2.74±2.66

133.32±186.06

25.1±1.9

165.8±27.05

150.2±5.6

–

Impounding period (19)

3.72±3.66

3.59±3.57

3.12±2.97

2.62±2.83

2.38±2.53

5.38±2.76

17.6±4.1

64.4±90.44

164.1±8.0

–

Flood period (17)

3.72±3.82

3.74±3.81

2.40±2.77

2.38±2.35

2.16±2.14

292.45±433.34

25.2±1.9

161.18±21.31

150.2±5.6

20608±5500

Impounding period (19)

3.66±3.74

3.63±3.74

3.50±3.76

2.48±2.77

2.25±2.54

6.56±7.27

17.1±4.0

60.12±76.23

164.1±8.0

6573±3094

Mainstream of the Yangtze River Upstream (2)

Downstream (4)

Intake of water plant (1)

Backwater area of tributaries Wuqiao River (3)

Zhuxi River (5)

Backwater area of the city (6)

Wastewater treatment plant Intake water (8, 9, 10)

Full period (13)

6.93±6.87

6.91±6.88

6.20±6.28

6.78±6.11

6.30±6.46

–b

–

–

–

–

Outlet water (8, 9, 10)

Full period (13)

2.18±2.64

2.17±2.64

2.01±2.25

2.08±2.45

0.20±0.61

7.1±0.4

–

–

–

–

TC: total coliform; FC: fecal coliform; EC: E. coli; FS: fecal streptococci; IE: intestinal enterococci; MPN: most probable numbers; CFU: colonyforming units; Turb: turbidity; Temp: water temperature; Level: water level; Inflow: daily inflow; NTU: nephelometric turbidity units; TDS : total dissolved solids. a The absolute number of fecal indicator bacteria was converted into log for the mean ± standard deviation (SD). 10 b Not done or no data.

Giardia in the downstream were higher than those in the upstream (Table 4). The water quality of all monitoring sites of surface water in the impounding period was better than that in the flood period (Fig. 3). In the impounding period, the mainstream of the Yangtze River saw excellent water quality, with 92.9% of water samples from the mainstream having water quality ranging between grades I to III national standard (grades I–III are suitable for drinking), but water quality of only 22.2% to 28.9% of water samples from backwater areas met grades I to III according to Chinese environmental quality standards for surface water (Fig. 3a). Water quality of 71.1% to 98.2% of water samples from all sites

in Wanzhou watershed were, however, very good or good according to WHO guidelines for safe recreational water environments (Fig. 3c), but standards for good quality were not met in all monitored sites, especially in backwater areas, due to the presence of high numbers of Salmonella, EHEC, Cryptosporidium and Giardia in parts of water samples (Table 4). It is remarkable that concentrations of fecal streptococci and intestinal enterococci in the mainstream (2, 4) significantly increased in the second impounding period from Dec 2010 to May 2011 after reaching the 175-m water level, compared with the first impounding period from Dec 2009 to May 2010 after reaching the 171-m water level (P < 0.05) (Fig. 2).

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Occurrence and infection risk of waterborne pathogens in Wanzhou watershed of the Three Gorges Reservoir, China

100 90 80 70 60 50 40 30 20 10 0

Impounding period

70 Percentile (%)

25 20 15 10 5 0

Backwater area of the tributary 80

Backwater area of the city

Flood period

60 50 40 30 20 10

I

0

II III IV V Super-V Microbial water quality assessment category

I

II III IV V Super-V Microbial water quality assessment category

70 Impounding period

60 Percentile (%)

Percentile (%)

Percentile (%)

The mainstream of Yangtze River 50 45 40 35 30

1919

Flood period

50 40 30 20 10

0 Very good Good Fair Poor Very good Good Fair Poor Microbial water quality assessment category Microbial water quality assessment category Fig. 3 Microbial water quality assessment of surface water in Wanzhou watershed according to Chinese environmental quality standards for surface water (a, b) and WHO guidelines for safe recreational water environments (c, d).

2.3 Pathogens Salmonella and EHEC were detected in 16.13% to 45.83% of water samples from all sites of surface water in Wanzhou watershed (Table 4). Salmonella and EHEC were found in only 5 samples (n = 31) from the upstream (2) at the highest concentrations of 2.3 and 24 MPN/L, respectively. However, Salmonella and EHEC were detected in 38.71% to 45.83% of water samples from backwater areas (3, 5, 6, 7) with the highest concentrations of 24 and Table 4

Bacterial and parasite pathogens in monitoring waters in Wanzhou watersheda

Salmonella spp.

Site (sampling site No.)

(MPN/L) Prevalence (no.)b

Mean±SD

46 MPN/L, respectively (Table 4). Salmonella was not found in water samples of WWTP outlets, whereas EHEC was found in 3 samples (n = 12) from WWTP outlets at average concentrations of 2.47 MPN/L. Prevalence and average concentration of Salmonella (prevalence = 47.89%, mean = 2.26 ± 4.81 MPN/L, n = 71) and EHEC (prevalence = 46.48%, mean = 4.41 ± 8.9 MPN/L, n = 71) in the flood period were significantly higher than those in the impounding period (Salmonella for prevalence = 22.22%, mean = 1.55 ± 4.2 MPN/L, n = 108; EHEC for

95% UCLc

Prevalence (no.)b

EHEC

Cryptosporidium

Giardia

(MPN/L)

( no. of oocysts/10 L)

( no. of cysts/10 L)

Mean±SD

95% UCL

Prevalence

Mean±SD

95% UCL

(no.)b

Prevalence

Mean±SD

95% UCL

(no.)b

Mainstream of the Yangtze River Intake of water plant (1)

25.81% (31)

0.63±0.90

2.34

25.81% (31)

3.13±2.55

3.96

NDd

ND

ND

ND

ND

ND

Upstream (2)

16.13% (31)

0.47±0.50

0.64

19.35% (31)

1.41±4.25

2.83

80% (5)

2.25±2.00

4.46

0% (5)

0

0

Downstream (4)

32.26% (31)

0.70±0.78

1.07

32.26% (31)

1.25±2.73

2.13

100% (5)

2.39±1.42

3.75

60% (5)

1.10±0.67

1.88

Backwater area of tributaries Wuqiao River (3)

38.71% (31)

1.80±3.99

3.08

45.16% (31)

6.19±10.36

18.24

100% (5)

5.66±2.86

8.38

100% (5)

7.43±4.23

11.47

Zhuxi River (5)

38.71% (31)

4.18±7.38

6.53

41.94% (31)

6.47±11.61

10.15

100% (5)

8.05±8.78

16.42

80% (5)

1.83±1.43

3.41

41.67% (24)

3.43±6.30

5.76

45.83% (24)

3.46±6.24

5.74

100% (5)

6.15±2.42

8.82

80% (5)

16.24±11.43

38.83

0% (12)

BDLf

BDL

25% (12)

2.47±0.55

2.82

100% (5)

10.21±3.77

13.80

100% (5)

66.86±11.92

78.22

Backwater area of the citye (6, 7) Outlet water of WWTPs (8, 9, 10)

a Lower

detection limit of MPN-nested-PCR and MPN-multiplex-PCR for Salmonella and EHEC is 0.3 MPN/L read from the MPN table. no.: number of sample. c UCL: upper confidence limit concentration. d ND: not detected. e 12 water samples of 6 and 7 sites were collected from 20 August 2010 to 7 July 2011, respectively. f BDL: all below detection limit (0.3 MPN/L). b

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Journal of Environmental Sciences 2013, 25(9) 1913–1924 / Guosheng Xiao et al.

prevalence = 26.85%, mean = 2.64 ± 6.61 MPN/L, n = 108) (P < 0.05). Cryptosporidium was found in all monitoring sites, but concentrations in positive samples from sites of surface water were generally low, ranging from 2.25 to 8.05 oocysts/10 L, with outlier of 22.99 oocysts/10 L in one sample from a backwater area of the tributary (Table 4). Cryptosporidium and Giardia were the highest in outlet water samples of WWTPs, with mean concentrations of 10.21 oocysts/10 L and 66.86 cysts/10 L, but bacterial indicator concentrations were significantly low. In the mainstream, prevalence and concentrations of Giardia were significantly lower than those of Cryptosporidium (P < 0.05). In backwater area of the city and outlets of WWTPs, however, concentrations of Giardia in positive samples were significantly higher than those of Cryptosporidium (P < 0.05) (Table 4). Average concentrations of Giardia and Cryptosporidium in backwater areas were significantly higher than those in the mainstream (P < 0.05). Otherwise, prevalence and average concentrations of Cryptosporidium and Giardia in the flood period and impounding period were not significantly different (data not shown). 2.4 Health risk 2.4.1 Average volume ingested by swimmer In total, 442 swimmers responded to the inquiry (61.6%), of whom 78.28% were adult males, 15.84% adult females, 4.98% non-adult males and 0.9% non-adult females. Table 5 shows the distributions of the volumes of swallowed water per swimming event and the calculated volume of swallowed water per swimming event for different populations. Most frequently, the swimmers reported swallowing only a few drops or a shot glass. Because fewer adult females and non-adults swam in Wanzhou watershed, estimated volumes (28.5 mL) of water ingested by adult-male swimmers per swimming event were adopted in infection risk calculations. 78.3% of the swimmers reported having none of these health complaints at all. Most health complaints were for skin (8.1%), then for respiratory (4.1%), nausea (3.2%), vomiting (2.7%), eye (1.8%), diarrhea (1.6%) and ear (0.9%) symptoms in turn. 2.4.2 Microbial risk assessment Estimated average volumes of water ingested by occupational divers in fresh water (5.7 mL) (Schijven and de Roda Husman, 2006), by woman (18 mL), man (27 mL) and child (37 mL) swimmers in fresh water (Schets et al., 2011), and by adult-male swimmers (28.5 mL) in Wanzhou watershed were used to calculate the risk of infection with Salmonella, EHEC, Cryptosporidium and Giardia for an exposed individual. The infection risk per exposure event at ingestion of 5.7 to 37 mL ranged from 2.9 × 10−7 to 1.68 × 10−5 and 7.04 × 10−10 to 2.36 ×10−8 for average detected salmonella and

Vol. 25

EHEC concentrations at the studied surface water sites, respectively (Table 6). For Cryptosporidium and Giardia, the infection risk ranged from 5.39 × 10−6 to 1.25 ×10−4 and 0 to 1.2 × 10−3 , respectively (Table 6). For all sites of surface water and ingested volumes of 5.7 to 37 mL, 95% upper confidence limit (UCL) of Salmonella and EHEC concentrations resulted in an infection risk of 3.95×10−7 to 2.62×10−5 , 1.2×10−9 to 6.67×10−8 , respectively, whereas 95% UCL of Cryptosporidium and Giardia concentrations resulted in an infection risk of 8.98×10−6 to 2.55×10−4 , 2.13 × 10−5 to 2.86× 10−3 , respectively (Table 6).

3 Discussion The TGR is an important fresh water resource in China, but thus far, there is not much information about impacts of fecal indicators and waterborne pathogens on any watersheds of the TGR. This study provides new information on the contamination of the TGR by fecal indicators and waterborne pathogens Salmonella, EHEC, Cryptosporidium and Giardia, which is useful for improving the safety of surface water and reducing the risk of fecal contamination. Concentrations of fecal indicators and pathogens in backwater areas of tributaries and the city were in a higher range than those in the mainstream. With the rise of water level of the TGR in the impounding period, the flow slows down and the pollutants accumulate in the local watershed, which forms serious pollution strips and deteriorates the water environment. On the other hand, the ability of the reservoir to act as a barrier to transport of pathogens will reduce the concentration of pathogens and indicators by dilution, sedimentation and inactivation (Brookes et al., 2004; Hipsey et al., 2005). In particular, the reservoir offers a more effective barrier to the transport of bacteria due to their sedimentation as aggregates (Hipsey et al., 2005). It was reported that the elimination rates for pathogenic microorganisms ranged between 1.7 and 3.1 log10 units in a Dutch reservoir (Van Breemen et al., 1998). In this study, concentrations of some microbial indicators and pathogens in the downstream were lower than those in the upstream in the flood period (data not shown). Furthermore, concentrations of fecal indicators (such as E. coli and intestinal enterococci in the ranges of 2 to 150 MPN/100 mL and 3 to 28 MPN/100 mL, respectively) and pathogens (Table 4) were extremely low in the upstream (2) in the impounding period without the heavy rain, even though many cities are along the upstream watershed from Wanzhou to Chongqing (left map, Fig. 1), and large amounts of sewage are discharged into the reservoir (MEP, 2010; Ye et al., 2008). Hence, the TGR might have a great self-purification capacity and could effectively eliminate fecal microorganisms by serving as a barrier to transport of pathogens if fecal contamination does not exceed the selfpurification capacity. So far, however, the self-purification capacity of the TGR is unknown. If in circumstances

No. 9

Occurrence and infection risk of waterborne pathogens in Wanzhou watershed of the Three Gorges Reservoir, China

1921

Table 5 Number of swimmers who swallowed the specified volume of river water per swimming event and arithmetic mean (maximum) volume of swallowed water per swimmera

Adult males Adult females Non-adult males Non-adult females Total a b c

Number (%) of swimmers swallowed water volume (mL) per swimming event None Few drops Shot glass Coffee cup Soda glass 0.5–5 (2.75) 20–30 (25) 80–120 (100) 170–210 (190) 0 (0)b

Total swimmers

Swallowed water per swimmer (mL)

44 (12.7) 6 (8.6) 0 (0) 2 (50) 52 (11.8)

346 70 22 4 442

28.5 (190)c 56.3 (190) 86.4 (190) 12.5 (25) 35.6 (190)

104 (30.1) 16 (22.9) 4 (18.2) 0 (0) 124 (28.1)

146 (42.2) 24 (34.3) 6 (27.3) 2 (50) 178 (40.3)

44 (12.7) 14 (20) 6 (27.3) 0 (0) 64 (14.5)

8 (2.3) 10 (14.3) 6 (27.3) 0 (0) 24(5.4)

All swimmers did not wear any masks. The specified volume (mL) of river water swallowed per swimming event is shown as range (average). Mean (maximum) volume of swallowed water per swimmer.

Table 6

Risk of infection with Salmonella, EHEC, Cryptosporidium and Giardia per exposure event for swimmers and divers in Wanzhou watershed

Site (sampling site No.)

Pathogen

Infection risk at ingested volume 5.7 mL (diver)a Mean

95%

18 mL (women)b Mean

UCLd

95%

27 mL (men)b Mean

UCL

95%

37 mL (children)b Mean

UCL

95%

28.5 mL (adult male)c Mean

UCL

95% UCL

Mainstream of the Yangtze River Upstream (2)

Downstream (4)

Intake of water plant (1)

Salmonella

2.9E-7

3.95E-7

9.17E-7

1.25E-6

1.38E-6

1.87E-6

1.88E-6

2.57E-6

1.45E-6

1.98E-6

EHEC

7.94E-10

1.59E-9

2.51E-9

5.03E-9

3.76E-9

7.55E-9

5.15E-9

1.03E-8

3.97E-9

7.97E-9

Cryptosporidium

5.39E-6

1.07E-5

1.70E-5

3.37E-5

2.55E-5

5.06E-5

3.50E-5

6.93E-5

2.70E-5

5.34E-5

Giardia

0

0

0

0

0

0

0

0

0

0

Salmonella

4.32E-7

6.61E-7

1.37E-6

2.09E-6

2.05E-6

3.13E-6

2.81E-6

4.29E-6

2.16E-6

3.31E-6

EHEC

7.04E-10

1.2E-9

2.22E-9

3.79E-9

3.33E-9

5.68E-9

4.57E-9

7.78E-9

3.52E-9

6.00E-9

Cryptosporidium

5.72E-6

8.98E-6

1.81E-5

2.83E-5

2.71E-5

4.25E-5

3.71E-5

5.83E-5

2.87E-5

4.49E-5

Giardia

1.25E-5

2.13E-5

3.94E-5

6.73E-5

5.91E-5

1.01E-4

8.10E-5

1.38E-4

6.24E-5

1.07E-4

Salmonella

3.89E-7

1.45E-6

1.23E-6

4.57E-6

1.84E-6

6.85E-6

2.53E-6

9.38E-6

1.95E-6

7.23E-6

EHEC

1.76E-9

2.23E-9

5.57E-9

7.04E-9

8.35E-9

1.06E-8

1.14E-8

1.45E-8

8.81E-9

1.11E-8

Salmonella

1.11E-6

1.9E-6

3.51E-6

6.01E-6

5.27E-6

9.01E-6

7.22E-6

1.24E-5

5.56E-6

9.51E-6

EHEC

3.49E-9

1.03E-8

1.10E-8

3.24E-8

1.65E-8

4.86E-8

2.26E-8

6.67E-8

1.74E-8

5.13E-8

Cryptosporidium

1.35E-5

2.01E-5

4.28E-5

6.34E-5

6.42E-5

9.50E-5

8.80E-5

1.30E-4

6.79E-5

1.00E-4

Giardia

8.43E-5

1.30E-4

2.66E-4

4.11E-4

3.99E-4

6.16E-4

5.47E-4

8.44E-4

4.21E-4

6.50E-4

Salmonella

2.58E-6

4.03E-6

8.16E-6

1.27E-5

1.22E-5

1.91E-5

1.68E-5

2.62E-5

1.29E-5

2.02E-5

EHEC

3.64E-9

5.71E-9

1.15E-8

1.80E-8

1.73E-8

2.71E-8

2.36E-8

3.71E-8

1.82E-8

2.86E-8

Cryptosporidium

1.93E-5

3.93E-5

6.09E-5

1.24E-4

9.13E-5

1.86E-4

1.25E-4

2.55E-4

9.66E-5

1.97E-4

Giardia

2.08E-5

3.87E-5

6.55E-5

1.22E-4

9.83E-5

1.83E-4

1.35E-4

2.51E-4

1.04E-4

1.93E-4

Salmonella

2.12E-6

3.56E-6

6.69E-6

1.12E-5

1.00E-5

1.69E-5

1.38E-5

2.31E-5

1.06E-5

1.78E-5

EHEC

1.95E-9

3.23E-9

6.15E-9

1.02E-8

9.23E-9

1.53E-8

1.26E-8

2.10E-8

9.74E-9

1.62E-8

Cryptosporidium

1.47E-5

2.11E-5

4.65E-5

6.67E-5

6.97E-5

1.00E-4

9.56E-5

1.37E-4

7.38E-5

1.06E-4

Giardia

1.84E-4

4.40E-4

5.82E-4

1.39E-3

8.72E-4

2.08E-3

1.20E-3

2.86E-3

9.21E-3

2.20E-3

Backwater area of tributaries Wuqiao river (3)

Zhuxi river (5)

Backwater area of the city (6, 7)

a

Average volume ingested by occupational divers in fresh water (Schijven and de Roda Husman, 2006). Average volume ingested by swimmers (women, men and children) in fresh water (Schets et al., 2011). c Average volume ingested by adult swimmers in Wanzhou watershed of the TGR in this study. d UCL: upper confidence limit concentration. b

where the microbial load is carried by strong inflows that create intrusions, then the reservoir is a poor barrier for attenuation (Hipsey et al., 2005). In the TGR, more than 1000 million tons of industrial effluent, urban sewage and ship pollutants are discharged into the reservoir, especially in cities’ sections (MEP, 2010; Ye et al., 2008). Therefore, high concentrations of fecal indicators and pathogens were detected in backwater areas. A weak but significant correlation was found between fecal indicators and Salmonella, EHEC, but results were not as clear for Cryptosporidium and Giardia because of high cost for testing. Several authors found that fecal

bacteria counts were associated with the concentration of Giardia, especially enterococci (Coupe et al., 2006; Mons et al., 2009). Graczyk et al. (2010) considered that enterococci count was a good indicator for the presence of Cryptosporidium and Giardia in recreational marine beach water. Significant associations were also observed between protozoa, Salmonella, total coliforms, and E. coli in natural surface waters (Carmena et al., 2007; Lemarchand and Lebaron, 2003; Touron et al., 2007). New approaches to the quantification of fecal indicators and pathogens in waters are emerging, such as quantitative PCR (Noble and Weisberg, 2005; WHO, 2009a), but

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Journal of Environmental Sciences 2013, 25(9) 1913–1924 / Guosheng Xiao et al.

there are drawbacks of weak correlation between colony count and genome copy cells, measuring the presence of specific genes without assessing cell viability, cost, and need for special molecular techniques (Haugland et al., 2005; Noble and Weisberg, 2005). The MPN-PCR, which utilizes PCR techniques for the detection of specific genes instead of isolation of target organisms, is a useful tool for estimation of the density of viable organisms in a sample. Detection methods based on MPN-PCR have been described previously for enumeration of Campylobacter (Savill et al., 2001), enterotoxigenic and enterohemorrhagic E. coli (Chern et al., 2004), Cryptosporidium (Carey et al., 2006), Salmonella (Jenkins et al., 2008) in water samples. In this study, MPN-PCR was used to detect and enumerate intestinal enterococci, Salmonella and EHEC, which does not require isolation and identification of those organisms. Thus, the technique yields significant labor and time savings, as opposed to the traditional confirmation method. We confine health effects modeling to infection, rather than illness. This means that we can use the dose-response data available in the literature for rates of infection. Fortunately, a great deal of work has been done to see how best to fit these data into dose-response models (McBride et al., 2002). Dose-response assessment examines the incidence of diarrhea infection as a health outcome in an exposed population. It represents the relationship between a dose (number of pathogens entering in the body to cause infection) and the response of the organism, which is the infection caused by pathogens (Ferrer et al., 2012). Two dose-response models are widely used from literature, the exponential and beta-Poisson models, as they fit well to several microorganisms (McBride et al., 2002). Protozoa and many viruses tend to follow the exponential model, whereas bacteria tend to conform to the beta-Poisson model (McBride et al., 2002). In our study, the data of quantitative risk assessment indicated that there is a health risk for occupational divers and recreational swimmers who are accidentally exposed to pathogens in the water of Wanzhou watershed, particularly in the water of backwater areas of the tributary and the city. For adult-male swimmers swallowing average volumes of approximately 28.5 mL water in Wanzhou watershed in our survey, the estimated average infection risk per swimming event is generally low in the mainstream (Table 6). However, the estimated average infection risk per swimming event in backwater areas is higher (approximately 2 to 7 times for Salmonella; 1 to 5 times for EHEC; 2 to 4 times for Cryptosporidium; 2 to 15 times for Giardia) than that in the mainstream. The estimated infection risk of non-adult swimmers could be much higher according to average volumes of 37 mL water ingested in fresh water (Schets et al., 2011), whereas the infection risk of occupational divers could be much lower according to average volumes of 5.7 mL water ingested in fresh water (Schijven and de Roda

Vol. 25

Husman, 2006). For microbiological risks, the annual individual probability of infection is the most commonly used (Xiao et al., 2012), and an annual individual risk of infection of 10–4 (which corresponds to a daily risk of 2.74 × 10–7 per person) suggested by the US EPA as an acceptable risk level for drinking water exposure to an infectious agent has been adopted to assess Cryptosporidium (An et al., 2011; Anderson et al., 1998; Diallo et al., 2008; Xiao et al., 2012), Giardia (An et al., 2012; Anderson et al., 1998; Diallo et al., 2008; Ferrer et al., 2012), diarrhegenic E. coli (Diallo et al., 2008), and Salmonella (Steyn et al., 2004) infection in many studies. The said criterion has been also used in many risk assessment studies for non-drinking water with accidental ingestion as the most adopted exposure scenario (Diallo et al., 2008; Ferrer et al., 2012; Steyn et al., 2004). Thus, compared with this US EPA level of acceptable risk, the average infection risks of Cryptosporidium for swimmers and divers were at least 20-fold greater than the acceptable risk in the mainstream, while at least 493-fold greater in backwater areas. Infection risk estimates for Giardia were 46-fold higher in the downstream and backwater areas of the city, but extremely low in the upstream. The health risk due to EHEC infection was 12-fold lower than the acceptable risk in all monitoring sites. For Salmonella, the estimated average infection risks were at least 4-fold greater than the acceptable risk in all backwater areas with a maximum (61 times) in backwater areas of the Zhuxi River, whereas the health risk due to Salmonella infection was acceptable in the mainstream. When Giardia cyst concentrations peak (95% UCL) in backwater areas, the infection risk per exposure event may be up to 10,000 times higher than the acceptable risk. However, these monitored pathogen concentrations and/or calculated risks were lower than the data obtained in other studies (An et al., 2011; Diallo et al., 2008; Schets et al., 2008; Steyn et al., 2004), whereas concentrations and risks of Cryptosporidium and Giardia in backwater areas were higher than the reported data in China (An et al., 2012; Xiao et al., 2012).

4 Conclusions This study demonstrated for the first time the presence of fecal indicators and waterborne pathogens Salmonella, EHEC, Cryptosporidium and Giardia in Wanzhou watershed of the TGR. Water quality in the mainstream is good but poor in backwater areas and it is influenced by the impoundment of the reservoir. The presence of pathogens in Wanzhou watershed may pose a possible health risk for professional or recreational contact exposure to the water despite fecal indicator parameters indicating safe swimming, especially in backwater areas of the tributary and the city. Although Wanzhou watershed is a fraction of the TGR, it is located in the middle of the TGR,

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Occurrence and infection risk of waterborne pathogens in Wanzhou watershed of the Three Gorges Reservoir, China

and therefore the data presented here may be of use for the residents, health care workers and managers in other watersheds. Acknowledgments This work was supported by the Key Project of Chinese Ministry of Education (No. 211150), the Natural Science Foundation Project of CQ CSTC (No. cstc 2013JCYJA20011), the China Postdoctoral Science Foundation (No. 20110491855), and the Science and Technology Projects of Chongqing Municipal Education Commission, China (No. KJ111115). We would like to thank all our partners who provided their sampling assistance. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Department or the Government.

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