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January 20, 2026Indoor Air0 citationsOpen Access

Microbial and Chemical Drivers of Indoor Air Quality in Educational Environments

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MGMarin GladLZLucija ZekićSŽSandra Pavičić Žeželj

Key Points

  • The research investigates how microbial and chemical factors affect indoor air quality in university classrooms.
  • Sample collection from 33 locations across 11 educational rooms
  • Microbiological analysis of bacteria and moulds
  • Chemical monitoring of gases including CO₂, O₂, and CH₄
  • Use of MALDI-TOF MS for species identification
  • Correlation and regression analyses to examine relationships between variables.
  • Average CO₂ concentrations were 906 ppm, with over half of rooms exceeding the 1000 ppm guideline
  • Bacterial load averaged 572 CFU/m³ and mould load at 130 CFU/m³
  • Significant correlations determined between CO₂ levels and bacterial load, as well as humidity and bacterial abundance
  • Occupancy negatively impacted microbial species richness, promoting homogenization
  • CO₂ and relative humidity proved to be key predictors of bacterial load.

Abstract

Indoor air quality (IAQ) in educational facilities is shaped by a dynamic interplay of microbial, chemical and physical factors, all of which influence health and cognitive performance. This study explored IAQ in university classrooms by combining microbiological, chemical and physical measurements to better understand microbial–chemical interactions in such environments. Samples ( N = 33) were collected from 11 rooms of different sizes, including lecture halls, classrooms and computer labs. Bacteria and moulds were quantified using standard microbiological procedures, while CO₂, O₂, CH₄, temperature, relative humidity and pressure were monitored by portable analysers. MALDI‐TOF MS was applied to identify airborne bacterial and fungal species, providing insight into microbial diversity and sources. The average CO₂ concentration was 906 ppm (range 509–1462 ppm). Although the overall mean was below the recommended 1000 ppm limit, more than half of the monitored rooms recorded CO₂ levels above this threshold. Mean bacterial and mould loads were 572 CFU/m 3 (range 50–1376 CFU/m 3 ) and 130 CFU/m 3 (range 56–260 CFU/m 3 ), respectively. Oxygen remained stable at 20.6 vol.%, while methane concentrations were negligible (mean 2.5 ppm). Relative humidity varied between 25% and 55%. Identified microorganisms were dominated by human‐associated bacteria ( Staphylococcus, Micrococcus ) and environmental fungi ( Cladosporium, Penicillium ), with noticeable differences between occupied and unoccupied rooms. Correlation analysis showed significant positive associations between CO₂ and bacterial load ( ρ = 0.56, p < 0.05), as well as relative humidity and bacterial abundance ( ρ = 0.67, p < 0.05). Species richness was negatively correlated with occupancy ( ρ = –0.77, p < 0.01), indicating microbial homogenisation in crowded conditions. Multiple regression analysis identified CO₂ and relative humidity as significant independent predictors of bacterial load ( p < 0.05). These findings highlight the importance of integrating microbial and physico‐chemical monitoring in IAQ assessments. CO₂ and relative humidity emerged as key controllable indicators, offering practical targets for improving air quality and limiting microbial contamination in educational environments.

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Cite This Study

Glad et al. (2026) studied this question.

synapsesocial.com/papers/696f1b189e64f732b51ef1c2https://doi.org/10.1155/ina/2529495
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