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Updated: Aug 5, 2026
Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples
Published on: June 30, 2023
Joint Monitoring and Early Warning of SARS-CoV-2 in Outdoor PM2.5 and Wastewater
Wenli Wang1,2, Haizhou Liu3,4, Dan Wang1,2
1School of Public Health, Fujian Medical University, Fuzhou 350122, China.
Background:
Fine particulate matter (PM2.5) and wastewater may carry severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and provide early signals for coronavirus disease 2019 (COVID-19) surveillance. This study investigated environmental factors affecting SARS-CoV-2 distribution in PM2.5 and wastewater in Fuzhou.
Methods:
PM2.5 and wastewater samples collected from January to December 2023 were tested for SARS-CoV-2 RNA using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Associations between air pollutants and meteorological factors were analyzed using generalized additive models (GAMs) and distributed lag nonlinear models (DLNMs).
Results:
SARS-CoV-2 was detected in 45.9% of PM2.5 samples. PM2.5 viral concentrations were positively associated with CO, PM2.5, and atmospheric pressure, and negatively associated with temperature and sunshine duration. Wastewater viral concentrations were positively associated with relative humidity and precipitation and negatively associated with NO2 and SO2. PM2.5 signals showed the strongest lag effect at approximately 2 days, while wastewater signals peaked at lag 0. The lag effect herein describes the time interval between environmental SARS-CoV-2 signals and predicted COVID-19 outpatient cases. Elderly populations showed higher environmental sensitivity, with sex-specific differences observed.
Conclusions:
SARS-CoV-2 signals in PM2.5 and wastewater reflected COVID-19 trends. Integrated multi-media monitoring may improve early warning and support targeted public health interventions.
