scholarly journals Coprostanol as a Population Biomarker for SARS-CoV-2 Wastewater Surveillance Studies

Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 225
Author(s):  
Liam J. Reynolds ◽  
Laura Sala-Comorera ◽  
Mohd Faheem Khan ◽  
Niamh A. Martin ◽  
Megan Whitty ◽  
...  

Wastewater surveillance is a cost-effective tool for monitoring SARS-CoV-2 transmission in a community. However, challenges remain with regard to interpretating such studies, not least in how to compare SARS-CoV-2 levels between different-sized wastewater treatment plants. Viral faecal indicators, including crAssphage and pepper mild mottle virus, have been proposed as population biomarkers to normalise SARS-CoV-2 levels in wastewater. However, as these indicators exhibit variability between individuals and may not be excreted by everyone, their utility as population biomarkers may be limited. Coprostanol, meanwhile, is a bacterial metabolite of cholesterol which is excreted by all individuals. In this study, composite influent samples were collected from a large- and medium-sized wastewater treatment plant in Dublin, Ireland and SARS-CoV-2 N1, crAssphage, pepper mild mottle virus, HF183 and coprostanol levels were determined. SARS-CoV-2 N1 RNA was detected and quantified in all samples from both treatment plants. Regardless of treatment plant size, coprostanol levels exhibited the lowest variation in composite influent samples, while crAssphage exhibited the greatest variation. Moreover, the strongest correlations were observed between SARS-CoV-2 levels and national and Dublin COVID-19 cases when levels were normalised to coprostanol. This work demonstrates the usefulness of coprostanol as a population biomarker for wastewater surveillance studies.

2014 ◽  
Vol 9 (3) ◽  
pp. 293-306 ◽  
Author(s):  
Adel A. S. Al-Gheethi ◽  
M. O. Abdul-Monem ◽  
A. H. S. AL-Zubeiry ◽  
A. N. Efaq ◽  
A. M. Shamar ◽  
...  

The aim of this study was to evaluate the efficiency of wastewater treatment plants (WWTPs) in Yemen for reduction of faecal indicators and pathogenic bacteria in the secondary effluents and sludge. Hundred sixty bacterial isolates were obtained from 27 secondary effluents and sludge samples generated from Ibb wastewater treatment plant (IWWTP), Taiz wastewater treatment plant (TWWTP), Aden wastewater treatment plant (AWWTP1 and 2) and Sana'a wastewater treatment plant (SWWTP) in Republic of Yemen. Isolation of the bacteria was carried out by the direct plate method on the several selective media. The concentrations of faecal coliforms (FCs) were more than that recommended by World Health Organisation guidelines in all secondary effluents samples expect for those collected from TWWTP. FCs in the sludge from IWWTP and SWWTP were more than the standards limits recommended by United State Environmental Protection Agency (U. S. EPA) Class B, while sludge from AWWTP and TWWTP meet U. S. EPA standards limits Class A and class B, respectively. Among 160 bacterial isolates, E. coli was the most common (detected in 88.88% of the samples), followed by Streptococcus faecalis (70.37%), Klebsiella pneumonia (66.67%), Enterobacter aerogenes (59.23%), Salmonella typhi (33.33%), S. typhimurium and Shigella sonni (25.93% for each) and Yersinia pestis (22.22%). The sludge samples collected from IWWTP and TWWTP and stored for 24 weeks at room temperature (25 ± 2 °C) met the standards limits recommended by U.S. EPA, Class A.


1997 ◽  
Vol 36 (1) ◽  
pp. 165-172 ◽  
Author(s):  
G. Koch ◽  
H. Siegrist

In co-ordination with the EU-guidelines the large wastewater treatment plants in Switzerland have to be extended with enhanced nitrogen removal. Denitrification in tertiary filtration is a cost-effective alternative to extended denitrification in the activated sludge system, which needs additional reactor volume. At the wastewater treatment plant Zürich-Werdhölzli full-scale experiments of denitrification with methanol in tertiary filtration were performed during a summer and a winter campaign of 4 months each. For this purpose one of the original 22 filter cells was equipped with a methanol dosage. At temperatures of 12-15°C rates of denitrification of about 1.0 kgN m−3 d−1 are attained. After main backwashing, denitrification is significantly reduced. Frequent backwashings (several times per day) led to methanol breakthroughs due to biofilm loss. The yield coefficient YCOD was 0.4 kg CODX kg−1 CODme. In spite of methanol dosage the quality of the filter effluent was very good during normal operation in the winter campaign. Accumulation of the nitrite intermediate product was observed in summer at temperatures of 20-22°C.


2020 ◽  
Vol 15 (2) ◽  
pp. 142-151
Author(s):  
Peter Lukac ◽  
Lubos Jurik

Abstract:Phosphorus is a major substance that is needed especially for agricultural production or for the industry. At the same time it is an important component of wastewater. At present, the waste management priority is recycling and this requirement is also transferred to wastewater treatment plants. Substances in wastewater can be recovered and utilized. In Europe (in Germany and Austria already legally binding), access to phosphorus-containing sewage treatment is changing. This paper dealt with the issue of phosphorus on the sewage treatment plant in Nitra. There are several industrial areas in Nitra where record major producers in phosphorus production in sewage. The new wastewater treatment plant is built as a mechanicalbiological wastewater treatment plant with simultaneous nitrification and denitrification, sludge regeneration, an anaerobic zone for biological phosphorus removal at the beginning of the process and chemical phosphorus precipitation. The sludge management is anaerobic sludge stabilization with heating and mechanical dewatering of stabilized sludge and gas management. The aim of the work was to document the phosphorus balance in all parts of the wastewater treatment plant - from the inflow of raw water to the outflow of purified water and the production of excess sludge. Balancing quantities in the wastewater treatment plant treatment processes provide information where efficient phosphorus recovery could be possible. The mean daily value of P tot is approximately 122.3 kg/day of these two sources. The mean daily value of P tot is approximately 122.3 kg/day of these two sources. There are also two outflows - drainage of cleaned water to the recipient - the river Nitra - 9.9 kg Ptot/day and Ptot content in sewage sludge - about 120.3 kg Ptot/day - total 130.2 kg Ptot/day.


2007 ◽  
Vol 56 (7) ◽  
pp. 21-31 ◽  
Author(s):  
D. Brdjanovic ◽  
M. Mithaiwala ◽  
M.S. Moussa ◽  
G. Amy ◽  
M.C.M. van Loosdrecht

This paper presents results of a novel application of coupling the Activated Sludge Model No. 3 (ASM3) and the Anaerobic Digestion Model No.1 (ADM1) to assess a tropical wastewater treatment plant in a developing country (Surat, India). In general, the coupled model was very capable of predicting current plant operation. The model proved to be a useful tool in investigating various scenarios for optimising treatment performance under present conditions and examination of upgrade options to meet stricter and upcoming effluent discharge criteria regarding N removal. It appears that use of plant-wide modelling of wastewater treatment plants is a promising approach towards addressing often complex interactions within the plant itself. It can also create an enabling environment for the implementations of the novel side processes for treatment of nutrient-rich, side-streams (reject water) from sludge treatment.


1999 ◽  
Vol 40 (7) ◽  
pp. 55-65 ◽  
Author(s):  
Mohamed F. Hamoda ◽  
Ibrahim A. Al-Ghusain ◽  
Ahmed H. Hassan

Proper operation of municipal wastewater treatment plants is important in producing an effluent which meets quality requirements of regulatory agencies and in minimizing detrimental effects on the environment. This paper examined plant dynamics and modeling techniques with emphasis placed on the digital computing technology of Artificial Neural Networks (ANN). A backpropagation model was developed to model the municipal wastewater treatment plant at Ardiya, Kuwait City, Kuwait. Results obtained prove that Neural Networks present a versatile tool in modeling full-scale operational wastewater treatment plants and provide an alternative methodology for predicting the performance of treatment plants. The overall suspended solids (TSS) and organic pollutants (BOD) removal efficiencies achieved at Ardiya plant over a period of 16 months were 94.6 and 97.3 percent, respectively. Plant performance was adequately predicted using the backpropagation ANN model. The correlation coefficients between the predicted and actual effluent data using the best model was 0.72 for TSS compared to 0.74 for BOD. The best ANN structure does not necessarily mean the most number of hidden layers.


Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 650 ◽  
Author(s):  
Ioanna Zerva ◽  
Ioanna Alexandropoulou ◽  
Maria Panopoulou ◽  
Paraschos Melidis ◽  
Spyridon Ntougias

Wastewater treatment plants (WWTPs) highly contribute to the transmission of antibiotic resistance genes (ARGs) in the environment. In this work, the diversity of ermF, ermB, sul1 and int1-enconding genes was examined in the influent, the mixed liquor and the effluent of a full-scale WWTP. Based on the clones analyzed, similar genotypes were recorded at all process stages. However, distinct genotypes of int1 were responsible for the expression of sul1 and ermF genes in Gammaproteobacteria and Bacteroidetes, respectively. Due to the detection of similar ARGs profiles throughout the biological process, it is concluded that additional treatment is needed for their retention.


2012 ◽  
Vol 428 ◽  
pp. 169-175
Author(s):  
Guo Kai Fu ◽  
Yi Yue Hu ◽  
Zhi Zhang

A reliable model for any wastewater treatment plant is essential in order to provide a tool for predicting its performance and to form a basis for controlling the operation of the process. This would minimize the operation costs and assess the stability of environmental balance. For the multi-variable, uncertainty, non-linear characteristics of the wastewater treatment system, a variable metric chaos optimization neural network (VMCNW) prediction model is established standing on the actual operation data in the wasterwater treatment system. The model overcomes several disadvantages of the conventional BP neural network. Namely:slow convergence, low accuracy and difficulty in finding the global optimum.The results of model calculation show that the predicted value can better match measured value,played a effect of simulating and predicting and be able to optimize the operation status. The establishment of the predicting model provide a simple and practical way for the operation and management in wastewater treatment plant,and have good research and engineering practical value.


2018 ◽  
Vol 4 (12) ◽  
pp. 1988-1996 ◽  
Author(s):  
Yan He ◽  
Yishuang Zhu ◽  
Jinghan Chen ◽  
Minsheng Huang ◽  
Guohua Wang ◽  
...  

The tense deficiency of available land resources is becoming one of the bottlenecks in dealing with wastewater treatment plant (WWTP) management issues.


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