Study on wastewater virus detection method and application based on ultrafiltration technology

MEN Jiang; YANG Shaolin; LI Hanwen; LI Huiqiang; WANG Xiaohui

doi:10.13205/j.hjgc.202602004

Volume 44 Issue 2

Feb. 2026

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Article Navigation > ENVIRONMENTAL ENGINEERING > 2026 > 44(2): 33-39

MEN Jiang, YANG Shaolin, LI Hanwen, LI Huiqiang, WANG Xiaohui. Study on wastewater virus detection method and application based on ultrafiltration technology[J]. ENVIRONMENTAL ENGINEERING , 2026, 44(2): 33-39. doi: 10.13205/j.hjgc.202602004

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MEN Jiang, YANG Shaolin, LI Hanwen, LI Huiqiang, WANG Xiaohui. Study on wastewater virus detection method and application based on ultrafiltration technology[J]. ENVIRONMENTAL ENGINEERING , 2026, 44(2): 33-39. doi: 10.13205/j.hjgc.202602004

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Study on wastewater virus detection method and application based on ultrafiltration technology

doi: 10.13205/j.hjgc.202602004

1. Engineering Technology Research Center of Water Treatment & Environmental Materials, College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029, China;
2. State Key Laboratory of Regional Environmental Security, School of Environment, Tsinghua University, Beijing 100084, China;
3. Beijing Drainage Management Center, Beijing 100195, China;
4. Haidian District Water Authority of Beijing, Beijing 100195, China

Received Date: 2025-03-05
Available Online: 2026-04-11
Publish Date: 2026-02-01

Abstract

Abstract

The COVID-19 pandemic highlighted critical shortcomings in traditional public health surveillance systems， particularly in terms of delayed response times and insufficient spatial coverage during the early stages of the outbreak. These limitations hindered the accurate tracking of viral spread and emphasized the urgent need for complementary surveillance approaches. In this context， Wastewater-based Epidemiology （WBE） has emerged as a promising strategy for cost-effective， large-scale monitoring of pathogen circulation， gaining global attention due to its potential for broad population coverage. However， the sensitivity and accuracy of WBE in detecting viral pathogens heavily depend on the efficiency of viral concentration and enrichment from wastewater samples， in which viruses typically exist at extremely low concentrations. Therefore， the development of effective viral concentration methods is essential to enhance the reliability， sensitivity， and overall accuracy of wastewater-based surveillance. In this study， a novel ultrafiltration-based viral enrichment method aimed at improving the efficiency of viral monitoring in wastewater was developed. The method was systematically evaluated for its applicability in detecting various viral pathogens in municipal wastewater. The results demonstrated that the ultrafiltration-based concentration method achieved high recovery rates （>40%） for the porcine epidemic diarrhea virus （PEDV）， transmissible gastroenteritis virus （TGEV）， and bacteriophage Phi6， with a lower detection limit of 10 copies/mL. These findings indicated the method’s capability to effectively concentrate and detect viral particles at trace levels， which is critical for early outbreak detection and ongoing monitoring. To further validate the feasibility and performance of the proposed method， a one-month field monitoring campaign was conducted in August 2023 at five sites in Haidian District， Beijing. Wastewater samples （n=50） were collected from the local sewage network， and SARS-CoV-2 concentrations were tracked over time using ultrafiltration combined with RT-qPCR quantification. Among the 50 collected samples， 49 （98.00%） tested positive for SARS-CoV-2， providing robust evidence of the virus’s persistent presence and circulation within the local wastewater system. Notably， the peak viral concentration observed in wastewater reached 1027.81 copies/mL. This study provides important technical support for improving the detection efficiency and sensitivity of wastewater viral monitoring， and has broad potential applications in various sectors， including environmental monitoring and water quality management.
- SARS-CoV-2,
- ultrafiltration,
- wastewater monitoring,
- RT-qPCR,
- public healthy

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References(28)

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