Taihu Lake is the third largest freshwater lake in China and serves as a drinking water source for~30 million residents. Tiaoxi River is one of the main rivers connected to this lake and contributes >60% of the source water. Taihu Lake has been facing various environmental issues; therefore, it is important to study the water quality of its inflow rivers. This study aimed to evaluate the physico-chemical and microbiological characteristics of Tiaoxi River and to determine the spatial and seasonal variations in the water quality. Water samples were collected from 25 locations across the Tiaoxi River in three seasons in 2014-2015. Fourteen water quality parameters including multiple nutrients and indicator bacteria were assessed, and the data analyzed by multivariate statistical analyses. The physico-chemical analysis showed high levels (>1 mg/L) of total nitrogen (TN) in all locations for all seasons. Total phosphorus (TP), nitrite-N (NO 2 -N), and ammonium-N (NH 4 -N) exceeded the acceptable limits in some locations and fecal coliform counts were high (>250 CFU/100 mL) in 15 locations. Hierarchical cluster analysis showed that the sampling sites could be grouped into three clusters based on water quality, which were categorized as low, moderate, and high pollution areas. Principal component analysis (PCA) applied to the entire dataset identified four principal components which explained 83% of the variation; pH, conductivity, TP, and NO 3 -N were found to be the key parameters responsible for variations in water quality. The overall results indicated that some of the sampling locations in the Tiaoxi River are heavily contaminated with pollutants from various sources which can be correlated with land use patterns and anthropogenic activities.
Urbanization is increasing worldwide and is happening at a rapid rate in China in line with economic development. Urbanization can lead to major changes in freshwater environments through multiple chemical and microbial contaminants. We assessed the impact of urbanization on physicochemical characteristics and microbial loading in canals in Suzhou, a city that has experienced rapid urbanization in recent decades. Nine sampling locations covering three urban intensity classes (high, medium and low) in Suzhou were selected for field studies and three locations in Huangshan (natural reserve) were included as pristine control locations. Water samples were collected for physicochemical, microbiological and molecular analyses. Compared to medium and low urbanization sites, there were statistically significant higher levels of nutrients and total and thermotolerant coliforms (or fecal coliforms) in highly urbanized locations. The effect of urbanization was also apparent in the abundances of human-associated fecal markers and bacterial pathogens in water samples from highly urbanized locations. These results correlated well with land use types and anthropogenic activities at the sampling sites. The overall results indicate that urbanization negatively impacts water quality, providing high levels of nutrients and a microbial load that includes fecal markers and pathogens.
Taihu Lake is one of the largest freshwater lakes in China, serving as an important source of drinking water; >60% of source water to this lake is provided by the Tiaoxi River. This river faces serious fecal contamination issues, and therefore, a comprehensive investigation to identify the sources of fecal contamination was carried out and is presented here. The performance of existing universal (BacUni and GenBac), human (HF183-Taqman, HF183-SYBR, BacHum, and Hum2), swine (Pig-2-Bac), ruminant (BacCow), and avian (AV4143 and GFD) associated microbial source tracking (MST) markers was evaluated prior to their application in this region. The specificity and sensitivity results indicated that BacUni, HF183-TaqMan, Pig-2-Bac, and GFD assays are the most suitable in identifying human and animal fecal contamination. Therefore, these markers along with marker genes specific to selected bacterial pathogens were quantified in water and sediment samples of the Tiaoxi River, collected from 15 locations over three seasons during 2014 and 2015. Total/universal Bacteroidales markers were detected in all water and sediment samples (mean concentration 6.22 log 10 gene copies/100 ml and 6.11 log 10 gene copies/gram, respectively), however, the detection of host-associated MST markers varied. Human and avian markers were the most frequently detected in water samples (97 and 89%, respectively), whereas in sediment samples, only human-associated markers were detected more often (86%) than swine (64%) and avian (8.8%) markers. The results indicate that several locations in the Tiaoxi River are heavily polluted by fecal contamination and this correlated well with land use patterns. Among the five bacterial pathogens tested, Shigella spp. and Campylobacter jejuni were the most frequently detected pathogens in water (60% and 62%, respectively) and sediment samples (91% and 53%, respectively). Shiga toxin-producing Escherichia coli (STEC) and pathogenic Leptospira spp. were less frequently detected in water samples (55% and 33%, respectively) and sediment samples (51% and 13%, respectively), whereas E. coli O157:H7 was only detected in sediment samples (11%). Overall, the higher prevalence and concentrations of Campylobacter jejuni, Shigella spp., and STEC, along with the MST marker detection at a number of locations in the Tiaoxi River, indicates poor water quality and a significant human health risk associated with this watercourse. GRAPHICAL ABSTRACT Tracking fecal contamination and pathogens in watersheds using molecular methods.
The purpose of this study was to conduct a correlative assessment of SARS-CoV-2 RNA concentrations in wastewater with COVID-19 cases and a systematic evaluation of the effect of using different virus concentration methods and recovery and normalization approaches. We measured SARS-CoV-2 RNA concentrations at two different wastewater treatment plants (WWTPs) in the Bexar County of Texas from October 2020 to May 2021 (32 weeks) using reverse transcription droplet digital PCR (RT-ddPCR). We evaluated three different adsorption–extraction (AE) based virus concentration methods (acidification, addition of MgCl 2 , or without any pretreatment) using bovine coronavirus (BCoV) as surrogate virus and observed that the direct AE method showed the highest mean recovery. COVID-19 cases were correlated significantly with SARS-CoV-2 N1 concentrations in Salitrillo (ρ = 0.75, p < 0.001) and Martinez II (ρ = 0.68, p < 0.001) WWTPs, but normalizing to a spiked recovery control (BCoV) or a fecal marker (HF183) reduced correlations for both treatment plants. The results generated in this 32-week monitoring study will enable researchers to prioritize the virus recovery method and subsequent correlation studies for wastewater surveillance.
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