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Noroviruses (NoVs) are responsible for numerous cases of waterborne and foodborne gastroenteritis every year. They are released in the sewage and their detection in this environment can reflect the epidemiology of the viral strains circulating in the community. A three-year (2007–2010) survey was conducted in order to evaluate the presence of human NoVs using RT-PCR in 518 sewage samples collected at the entrance and exit of two biological sewage treatment plants located in Monastir region, Tunisia. In this study, we aimed to genetically characterize the most prevalent GI and GII NoV strains, in order to obtain a rough estimate of the efficacy of disinfection treatments and to compare the results with clinical data documented in the same area during the same period. This work confirms the wide circulation and the genetic diversity of NoVs in Tunisia and the widespread distribution of NoV variants in both raw and treated wastewater. Indeed, NoV was detected in 192 (37.1 %) sewage samples, among them mixed infections with group A rotavirus were detected in 125 (65.1 %) cases. The genotypes of the GI NoVs were GI.1, GI.2, GI.4, GI.5, and GI of unassigned genotype (GI.UA), and the genotypes of the GII NoVs were all GII.12. This study enhances the currently poor environmental virological data gathered in Tunisia, demonstrates the benefit of environmental surveillance as a tool to determine the epidemiology of NoVs circulating in a given community, and underlines the need for the design and support of similar long-term studies in our country, in order to compensate for the absence of a national surveillance system for gastroenteric viruses.  相似文献   
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Enteric viruses transmitted via the faecal-oral route occur in high concentrations in wastewater and may contaminate drinking water sources and cause disease. In order to quantify enteric adenovirus and norovirus genotypes I and II (GI and GII) impacting a drinking source in Norway, samples of surface water (52), wastewater inlet (64) and outlet (59) were collected between January 2011 and April 2012. Samples were concentrated in two steps, using an electropositive disc filter and polyethylene glycol precipitation, followed by nucleic acid extraction and analysis by quantitative polymerase chain reaction. Virus was detected in 47/52 (90.4 %) of surface water, 59/64 (92 %) of wastewater inlet and 55/59 (93 %) of wastewater outlet samples. Norovirus GI occurred in the highest concentrations in surface water (2.51e + 04) and adenovirus in wastewater (2.15e + 07). While adenovirus was the most frequently detected in all matrices, norovirus GI was more frequently detected in surface water and norovirus GII in wastewater. This study is the first in Norway to monitor both sewage and a drinking water source in parallel, and confirms the year-round presence of norovirus and adenovirus in a Norwegian drinking water source.  相似文献   
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Rainwater characteristics can reveal emissions from various anthropogenic and natural sources into the atmosphere. The physico-chemical characteristics of 44 monthly rainfall events (collected between January and December 2012) from 4 weather stations (Bamenda, Ndop plain, Ndawara and Kumbo) in the Bamenda Highlands (BH) were investigated. The purpose was to determine the sources of chemical species, their seasonal inputs and suitability of the rainwater for drinking. The mean pH of 5 indicated the slightly acidic nature of the rainwater. Average total dissolved solids (TDS) were low (6.7 mg/L), characteristic of unpolluted atmospheric moisture/air. Major ion concentrations (mg/L) were low and in the order K+ 〉 Ca2+ 〉 Mg2~ 〉 Na+ for cations and NO3 〉〉 HCO3 〉 SO] 〉 CI- 〉 PO3- 〉 F- for anions. The average rainwater in the area was mixed Ca-Mg-SO4-CI water type. The CI-/Na+ ratio (1.04) was comparable to that of seawater (1.16), an indication that N a+ and CI originated mainly from marine (Atlantic Ocean) aerosols. High enrichments of Ca2+, Mg2+ and SO2- to Na+ ratios relative to seawater ratios (constituting 44% of the total ions) demonstrated their terrigenous origin, mainly from Saharan and Sahelian arid dusts. The K+/Na+ ratio (2.24), which was similar to tropical vegetation ash (2.38), and NO3 was essentially from biomass burning. Light (〈 100 mm) pre-monsoon and post-monsoon convective rains were enriched in major ions than the heavy (〉 100 mm) monsoon rains, indicating a high contribution of major ions during the low convective showers. Despite the acidic nature, the TDS and major ion concentrations classified the rainwater as potable based on the WHO guidelines.  相似文献   
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Stormwater runoff has been identified as a source of pollution for the environment, especially for receiving waters. In order to quantify and manage the impacts of stormwater runoff on the environment, predictive models and mathematical models have been developed. Predictive tools such as regression models have been widely used to predict stormwater discharge characteristics. Storm event characteristics, such as antecedent dry days (ADD), have been related to response variables, such as pollutant loads and concentrations. However it has been a controversial issue among many studies to consider ADD as an important variable in predicting stormwater discharge characteristics. In this study, we examined the accuracy of general linear regression models in predicting discharge characteristics of roadway runoff. A total of 17 storm events were monitored in two highway segments, located in Gwangju, Korea. Data from the monitoring were used to calibrate United States Environmental Protection Agency's Storm Water Management Model (SWMM). The calibrated SWMM was simulated for 55 storm events, and the results of total suspended solid (TSS) discharge loads and event mean concentrations (EMC) were extracted. From these data, linear regression models were developed. R2 and p-values of the regression of ADD for both TSS loads and EMCs were investigated. Results showed that pollutant loads were better predicted than pollutant EMC in the multiple regression models. Regression may not provide the true effect of site-specific characteristics, due to uncertainty in the data.  相似文献   
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