Petrochemical complexes are spatially expansive and host diverse emission sources, making accurate monitoring of volatile organic compounds (VOCs) challenging using conventional two-dimensional methods. This study introduces Mobile-extraction Differential Optical Absorption Spectroscopy (Me-DOAS), a real-time, three-dimensional remote sensing technique for assessing benzene emissions in the Ulsan petrochemical complex, South Korea. A vehicle-mounted Me-DOAS system conducted monthly measurements throughout 2024, capturing data during four daily intervals to evaluate diurnal variation. Routes included perimeter loops and grid-based transects within core industrial zones. The highest benzene concentrations were observed in February (mean: 64.28 ± 194.69 µg/m³; geometric mean: 5.13 µg/m³), with exceedances of the national annual standard (5 µg/m³) in several months. Notably, nighttime and early morning sessions showed elevated levels, suggesting contributions from nocturnal operations and meteorological conditions such as atmospheric inversion. A total of 179 exceedances (≥30 µg/m³) were identified, predominantly in zones with benzene-handling activities. Correlation analysis revealed a significant relationship between high concentrations and specific emission sources. These results demonstrate the utility of Me-DOAS in capturing spatiotemporal emission dynamics and support its application in exposure risk assessment and industrial emission control. The findings provide a robust framework for targeted management strategies and call for integration with source apportionment and dispersion modeling tools.

Rapid industrialization and urbanization have progressed in Korea, yet public attention to hazardous pollutants emitted from industrial complexes remains limited. With the increasing coexistence of industrial and residential areas, there is a growing need for real-time monitoring and management plans that account for the rapid dispersion of hazardous air pollutants (HAPs). In this study, we conducted spatiotemporal data collection and analysis for the first time in Korea using real-time measurements obtained through mobile extractive differential optical absorption spectroscopy (Me-DOAS) mounted on a solar occultation flux (SOF) vehicle. The measurements were conducted in the Saha Sinpyeong–Janglim Industrial Complex in Busan, which comprises the Sasang Industrial Complex and the Sinpyeong–Janglim Industrial Complex. BTEX compounds were selected as target volatile organic compounds (VOCs), and real-time measurements of both BTEX and fine particulate matter (PM) were conducted simultaneously. Correlation analysis revealed a strong relationship between PM10 and PM2.5 (r = 0.848–0.894), indicating shared sources. In Sasang, BTEX levels were associated with traffic and localized facilities, while in Saha Sinpyeong–Janglim, the concentrations were more influenced by industrial zoning and wind patterns. Notably, inter-compound correlations such as benzene–m-xylene and p-xylene–toluene suggested possible co-emission sources. This study proposes a GIS-based, three-dimensional air quality management approach that integrates variables such as traffic volume, wind direction, and speed through real-time measurements. The findings are expected to inform effective pollution control strategies and future environmental management plans for industrial complexes.

Understanding indoor air quality (IAQ) in childcare environments is critical for safeguarding young children, who are physiologically vulnerable to airborne pollutants due to higher inhalation rates and developing respiratory systems. This study characterized daypart-specific IAQ patterns and their multivariate structures by using high-resolution monitoring at seven childcare centers in Korea. Continuous 1-min measurements of PM₂.₅, PM₁₀, total volatile organic compounds (TVOC), CO₂, radon, temperature, and relative humidity were collected and aggregated into 5-min averages for analysis. PM₂.₅ (8.9–13.9 µg·m⁻³), PM₁₀ (18.4–25.8 µg·m⁻³), CO₂ (445–1,029 ppm), and radon (16–191 Bq·m⁻³) largely complied with domestic and WHO guidelines. In contrast, TVOC concentrations exceeded recommended reference ranges at all facilities and showed substantial inter-facility variability. Pollutant levels varied clearly by time of day: particles increased during active classroom periods and declined afterward; CO₂ temporarily exceeded 1,000 ppm during peak occupancy; TVOC showed activity-related peaks with evening persistence; and radon increased in one facility before morning ventilation. Exploratory principal component analysis (PCA) showed that the three components accounted for 83.5% of the total variance, reflecting increases in activity-related particulates, ventilation-dependent gaseous accumulation, and temperature-related variations in TVOC levels. K-means clustering grouped similar daypart profiles across centers, indicating recurring multivariate IAQ patterns beyond the daily average concentrations. The pollutant peaks did not occur simultaneously. Particulate matter aligned with occupancy, whereas gaseous pollutants accumulated under limited ventilation. These findings suggest that IAQ in childcare settings is better interpreted in relation to operational time segments rather than daily averages alone, and that ventilation strategies should consider both timing and pollutant-specific behavior when managing exposure in sensitive indoor environments.

Indoor radon is a leading source of natural radiation exposure, and its indoor concentrations vary substantially with building operation and ventilation conditions. Despite this, radon management in public facilities continues to rely on time-averaged measurements, which can obscure short-term accumulation episodes tied to occupancy and operational schedules. High-resolution continuous radon monitoring was conducted in 11 community service centers in Jeollanam-do, Korea, to characterize time-segmented concentration variability under real operational conditions. Hourly data were classified into four operational periods — working hours, extended working hours, non-working hours, and weekends — and analyzed using a linear mixed-effects model (LMM). Substantial inter-facility variability was observed across all concentration metrics. Radon concentrations were lowest during extended working hours and increased progressively during non-working hours and weekends. Variance decomposition attributed approximately 70% of total variability to facility-level differences (ICC ≈ 0.69), indicating that building-specific baseline characteristics exert a stronger influence on indoor radon exposure than operational time effects. Facility-specific temporal response patterns were further examined using continuous sensitivity indices alongside LMM-derived random intercepts, showing that temporal sensitivity and baseline radon level are not consistently related across facilities.