Low-Cost Sensor-Based Spatial Screening of Urban Air Quality in a Medium-Sized City: A Case Study in Alba-Iulia, Romania

Abstract

Urban air pollution remains a major public health concern, with road traffic representing one of the dominant sources of particulate matter and volatile organic compounds in growing cities. This study evaluates the level of chemical air pollution in Alba-Iulia municipality (Romania) through two measurement campaigns (May 2025 and October 2025), carried out at 26 and 19 points, respectively, selected based on traffic intensity and population vulnerability criteria (schools, kindergartens, hospitals, and the food market). Measurements targeted PM2.5, PM10, total volatile organic compounds (TVOC) and formaldehyde (HCHO), as well as carbon dioxide (CO2), correlated with road traffic intensity. Statistical analysis revealed significant differences between the two seasons for PM2.5, PM10, and CO2 (p < 0.01), as well as a strong correlation between particulate matter concentrations and vehicle counts (r = 0.60–0.95), consistent with road traffic being an important local contributor to particulate matter, though correlation alone cannot establish source dominance in a strict causal sense. A multiple regression controlling for both traffic and season explained over 73% of the variance in PM2.5 and PM10 and showed that traffic and season each contribute independently to particulate levels. Both mean PM2.5 and PM10 exceeded WHO and EU limit values in both campaigns, and the low-cost sensor over-read absolute concentrations by roughly 2–4× relative to the official monitoring network, so absolute values should be treated as orientative. Despite this bias, the consistent spatial and seasonal patterns show that portable low-cost sensors can reliably rank exposure hotspots and support the targeting of traffic-mitigation measures, such as selective catalytic reduction (SCR) systems, in medium-sized cities that lack dense reference monitoring networks.