Human health may be affected by exposure to particular matter (PM) in the air which can be generated from human activities, industrial emissions, automobile exhuast, and meteorological factors. Therefore, it is necessary to evaluate the factors affecting on ambient PM2.5 levels and accordingly to assess the exposure on whole population and sub-populations. The purposes of this study were to evaluate the factors affecting on ambient PM2.5 concentration according to human activities and meteorological factors, and to assess the exposure levels on populations.
PM2.5 concentrations according to the changes in weather and population distribution were measured from January to March in 2020 in Guro-gu, Seoul, Korea. Guro-gu was divided into 2,204 scale standard grids of 100 m × 100 m. The hourly PM2.5 concentrations of each grid were estimated by the inverse distance weight method using 24 sensor-based air monitoring instruments. Hourly dynamic population distribution of each grid was evaluated according to gender and age using mobile phone network data. Human activities were determined by changes in the hourly number of population in each grid. Weather data were collected from the Korea Meteorological Administration on temperature, humidity, rainfall, wind speed, and air pressure. Using the multiple regression analysis and Structural Equation Modeling(SEM), changes in the concentration of ambient PM2.5 (dependent variable) according to meteorological factors and population (independent variable) were evaluated on weekdays and weekends.
The average of PM2.5 concentration in Guro-gu for 3 months was 27.45 ㎍/m3 and the standard deviation was 19.34 ㎍/m3. The average of population exposures to PM2.5 concentration in Guro-gu for 3 months was 22.06 ㎍/m3 and the standard deviation was 12.96 ㎍/m3. Multiple regression analysis on weekday, weather factors were significant excluding the population distribution. On the other hand, the remaining independent variables excluding wind and rainfall were significant on weekend. SEM on weekday, weather factors were significant excluding the population distribution. The remaining independent variables exluding the temperature and rainfall were significant on weekend. As a result of this study, human activity such as dynamic population might have an effect on PM2.5 concentration in the atmosphere with meteorological factors.