Analysis and Prediction of the Relationship between Meteorological Factors and Fine Dust Concentration

기상 요인과 미세먼지 농도 간의 관계 분석 및 예측

Urban air quality significantly impacts life and health, with fine dust (PM10) and ultrafine dust (PM2.5) posing serious health risks. This study investigates the seasonal variations in fine dust concentrations based on meteorological data from 2022 and 2023, including temperature, humidity, and precipitation. A random forest regression model was utilized to analyze the relationship between fine dust levels and meteorological factors. The results revealed that fine dust concentrations were highest during spring and winter, while summer exhibited the lowest levels. This seasonal pattern is attributed to increased precipitation and higher temperatures, which help reduce airborne particulate matter. The findings underscore the predictive potential of meteorological data in estimating fine dust concentrations. This research provides a foundation for improving urban air quality management and developing public health strategies to mitigate the adverse effects of air pollution.