earticle

영어

This study explores the impact of meteorological factors on fine dust concentrations (PM10 and PM2.5) in Jongno-gu, Seoul, using data from 2022. Four weather variables—temperature, precipitation, wind speed, and cloud cover—were analyzed through multiple linear regression to assess their influence on air pollution levels. The results indicate that precipitation and wind speed are statistically significant predictors, with precipitation showing a strong negative correlation due to its wash-out effect on airborne particles. In contrast, temperature and cloud cover did not exhibit significant relationships with fine dust concentrations. The proposed regression model, while limited in its overall explanatory power, provides foundational insights into the quantifiable relationship between weather changes and air quality. The model tends to underpredict dust concentrations, suggesting the need for improved variable selection or nonlinear modeling approaches. Despite its limitations, the study contributes to the development of practical, weather-based air quality forecasting systems and offers valuable implications for local policy planning. By highlighting the significance of precipitation and wind, the research supports the integration of meteorological data into real-time environmental monitoring frameworks aimed at protecting public health and guiding urban atmospheric management.