Monitoring and assessing the impact of wastewater treatment on release of both antibiotic-resistant bacteria and their typical genes in a Chinese municipal wastewater treatment plant

There is increasing attention toward factors that potentially contribute to antibiotic resistance (AR), as well as an interest in exploring the emergence and occurrence of antibiotic resistance bacteria (ARB). We monitored six ARBs that cause hospital outbreaks in wastewater influent to highlight the presence of these ARBs in the general population. We analyzed wastewater samples from a municipal wastewater treatment plant (MWWTP) and hospital wastewater (HW) for six species of ARB: Carbapenem-resistant Enterobacteria (CARBA), extended-spectrum β-lactamase producing Enterobacteria (ESBL), multidrug-resistant Acinetobacter (MDRA), multidrug-resistant Pseudomonas aeruginosa (MDRP), methicillin-resistant Staphylococcus aureus (MRSA), and vancomycin-resistant Enterococci (VRE). We registered a high percentage of ARBs in MWWTP samples (>66%) for all ARBs except for MDRP, indicating a high prevalence in the population. Percentages in HW samples were low (<78%), and no VRE was detected throughout the study. CARBA and ESBL were detected in all wastewater samples, whereas MDRA and MRSA had a high abundance. This result demonstrated the functionality of using raw wastewater at MWWTP to monitor the presence and extent of ARB in healthy populations. This kind of surveillance will contribute to strengthening the efforts toward reducing ARBs through the detection of ARBs to which the general population is exposed.

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Impact of a wastewater treatment plant on Cryptosporidium oocysts and Giardia cysts occurring in a surface water

Water Science & Technology ◽

10.2166/wst.2000.0112 ◽

2000 ◽

Vol 41 (7) ◽

pp. 31-37 ◽

Cited By ~ 18

Author(s):

E. Carraro ◽

E. Fea ◽

S. Salva ◽

G. Gilli

Keyword(s):

Wastewater Treatment ◽

Wastewater Treatment Plant ◽

Municipal Wastewater ◽

Treatment Plant ◽

Municipal Wastewater Treatment ◽

Mean Values ◽

Cryptosporidium Oocysts ◽

The Impact ◽

Receiving Water ◽

Giardia Cysts

The aim of this study was to assess the impact of a municipal wastewater treatment plant (MWTP) on the occurrence of Cryptosporidium oocysts and Giardia cysts in the receiving water. All MWTP effluent samples were Giardia and Cryptosporidium contaminated, although low mean values were found for both parasites (0.21±0.06 oocysts/L; 1.39±0.51 cysts/L). Otherwise, in the raw sewage a greater concentration was detected (4.5±0.3 oocysts/L; 53.6±6.8 cysts/L). The major occurrence of Giardia over Cryptosporidium, both in the influent and in the effluent of the MWTP, is probably related to the human sewage contribution to the wastewater. Data on protozoa contamination of the receiving water body demonstrated similar concentrations in the samples collected before (0.21±0.07 oocysts/L; 1.31±0.38 cysts/L) and after (0.17±0.09 oocysts/L and 1.01±1.05 cysts/L) the plant effluent discharge. The results of this study suggest that the MWTP has no impact related to Giardia and Cryptosporidium river water contamination, and underline the need for investigation into the effectiveness of these protozoa removal by less technologically advanced MWTPs which are the most widespread and could probably show a lower ability to reduce protozoa.

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Integrated Wastewater Treatment Plant Performance Evaluation Using Artificial Neural Networks

Water Science & Technology ◽

10.2166/wst.1999.0327 ◽

1999 ◽

Vol 40 (7) ◽

pp. 55-65 ◽

Cited By ~ 12

Author(s):

Mohamed F. Hamoda ◽

Ibrahim A. Al-Ghusain ◽

Ahmed H. Hassan

Keyword(s):

Neural Networks ◽

Wastewater Treatment ◽

Artificial Neural Networks ◽

Wastewater Treatment Plant ◽

Municipal Wastewater ◽

Wastewater Treatment Plants ◽

Treatment Plant ◽

Plant Performance ◽

Municipal Wastewater Treatment ◽

Artificial Neural

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.

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Assessment of land occupation of municipal wastewater treatment plants in China

Environmental Science Water Research & Technology ◽

10.1039/c8ew00344k ◽

2018 ◽

Vol 4 (12) ◽

pp. 1988-1996 ◽

Cited By ~ 4

Author(s):

Yan He ◽

Yishuang Zhu ◽

Jinghan Chen ◽

Minsheng Huang ◽

Guohua Wang ◽

...

Keyword(s):

Wastewater Treatment ◽

Wastewater Treatment Plant ◽

Municipal Wastewater ◽

Wastewater Treatment Plants ◽

Treatment Plant ◽

Land Resources ◽

Municipal Wastewater Treatment ◽

Land Occupation ◽

Municipal Wastewater Treatment Plants ◽

Management Issues

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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