This study investigated indoor air quality (IAQ) in 302 facilities (consisting of 638 monitoring points) across five types of multi-use facilities for the health of vulnerable populations in Seoul. The facility types consisted of the following: ICPs (indoor children’s playgrounds), PCCs (postnatal care centers), ECFs (elderly care facilities), HCFs (health care facilities), and CCCs (child care centers). The investigation was carried out over a 1-year period, from January to December 2024. The objective of this research was to provide a scientific basis for IAQ management by identifying characteristics specific to facility types and potential risk levels for vulnerable populations in Seoul. Five indoor air pollutants (PM10, PM2.5, CO2, HCHO, and TAB) were continuously measured, and their concentration distributions, temporal variability, and multi-pollutant patterns were analyzed using data visualization and statistical methods. Boxplots and ridgeline plots characterized distributions and seasonality by facility type, while star plots and K-means clustering were used to examine multi-pollutant combinations and inter-facility pattern differences. Most measurements were within national IAQ standards. However, HCFs and PCCs exhibited relatively higher mean levels and variability of HCHO and TAB, indicating a greater need to control chemical and microbiological sources. CO2 concentrations approached or temporarily exceeded the national standard, particularly in HCFs, reflecting differences in occupant density, occupancy time, and ventilation management. Kruskal-Wallis and pairwise Wilcoxon rank-sum tests revealed statistically significant differences among facility types, particularly for CO2 and HCHO, consistent with the visualized multi-pollutant profiles. K-means clustering identified three IAQ patterns-multi-pollutant-elevated, activity/ventilation-influenced, and low-pollutionindicating that management needs may vary across facilities despite uniform national standards. These findings provide a methodological basis for IAQ big data analysis, policy making, and supporting future research integrating multi-year, outdoor, building, activity, and health data.

Abstract
1. 서 론
2. 연구 방법
    2.1 연구대상 및 분석방법
    2.2 데이터 시각화
    2.3 통계분석
3. 결과 및 고찰
    3.1 건강민감군 다중이용시설 실내공기질 오염도현황 및 데이터 시각화
    3.2 건강민감군 다중이용시설 실내공기질 데이터시각화
    3.3 통계분석 결과
4. 결 론
References
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