Application of Low-Cost Sensors for Pollutant Source Attribution in Various Indoor Environments

To address the scarcity of high-time-resolution data on indoor pollutants, this study used low-cost air quality sensors for continuous monitoring in four typical indoor environments: an office, a residential heating room, a street kitchen, and a residential kitchen. Key pollutants (PM_2.5, PM₁₀, O₃, NOx, CO, CO₂, TVOC) and environmental factors (temperature, humidity, noise) were measured. Integrating wavelet analysis, peak/background decomposition, and the positive matrix factorization (PMF) model, three sources were identified: PM-related (particle intrusion/resuspension/oil aerosolization), noise-related (activity-ventilation coupling), and other-gases (combustion and material/surface processes). Wavelet analysis revealed obvious diurnal/semidiurnal cycles and multi-scale periodic characteristics dominated by human activities and ventilation. All environments exhibited distinct pollutant concentration variations linked to their specific functional uses and emission sources. The street kitchen had the highest PM and TVOC levels, while the residential heating room showed the highest CO and CO₂. Health risk assessment revealed distinct drivers: office risks from particles and NO₂, heating rooms from CO, street kitchens from cooking particles and near-road combustion, and residential kitchens from balanced particle and CO risks. The study confirms low-cost sensors effectively capture pollutant variations and source differences, providing scientific support for targeted indoor pollution control.