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A comprehensive study assessed indoor air quality parameters, focusing on relevant air pollutants such as particulate matter (PM 10 and PM 2.5 ), gaseous compounds (CO, CO 2 , formaldehyde, NO 2 ) and volatile/semi-volatile organic chemicals, as well as respiratory viruses (including SARS-CoV-2), fungi and bacteria in Spanish university classrooms. Non-target screening strategies evaluated the presence of organic pollutants inside and outside the classrooms. Saliva samples from teachers and students were collected to explore correlations between respiratory viruses in the air and biological samples. Indoor results revealed the punctual exceedance of recommended guidelines for CO 2 , formaldehyde (HCHO), volatile organic compounds (TVOCs) and PM in the least naturally ventilated classrooms. Significant differences occurred between the classes, with the least ventilated one showing higher average concentrations of CO 2 , HCHO, NO 2 , PM 10 and PM 2.5 . A respiratory virus (rhinovirus/enterovirus) was detected in the medium naturally ventilated classroom, although saliva samples tested negative. Suspect screening tentatively identified 65 substances indoors and over 200 outdoors, with approximately half reporting a high toxicological risk based on the Cramer rules. The study provides a comprehensive overview of indoor air quality, respiratory viruses and organic pollutants in university classrooms, highlighting the variations and potential health risks associated with ventilation differences.

A fast and automated strategy has been developed for identifying unknown substances in the atmosphere (concretely, in the particulate matter, PM 10 ) using LC-HRMS (MS 3 ). A total of 15 samples were collected in three different areas (rural, urban and industrial). A sampling flow rate of 30 m 3 h -1 was applied for 24 h, sampling a total volume of around 720 m 3 . A total of 49 compounds were tentatively identified using very restrictive criteria regarding exact mass, retention time, isotopic profile and both MS 2 and MS 3 spectra. Pesticides, pharmaceutical active compounds, drugs, plasticizers and metabolites were the most identified compounds. To verify whether the developed methodology was suitable, 11 substances were checked with their analytical standards and all of them were confirmed. Different profiles for industrial, rural and urban areas were examined. The Principal Component Analysis (PCA) model allowed us to separate the obtained data of the three assessed area. When the profiles obtained in the three evaluated areas were compared using a Volcano plot (the rural area was taken as reference), 11 compounds were confirmed as being discriminant: three of them (3-hydroxy-2-methylpyridine, 3-methyladenine and nicotine) were more likely to be found in industrial sites; ten compounds (3-hydroxy-2-methylpyridine, 3-methyladenine, azoxystrobin, cocaine, cotinine, ethoprophos, imidacloprid, metalaxyl-M, nicotine and pyrimethanil) were more probable in the case of urban sites; finally, triisopropanolamine was more likely to be detected in rural locations.