Analyzing the Relationship Between Air Pollutant Emissions and Air Quality in Gyeongsangbuk-do (2017-2021)

A variety of policies have been suggested and implemented for air quality control in Korea. However, high ambient concentrations of PM10 and PM2.5 exceeding regulation levels have been frequently reported. In this study, the air quality in Gyeongsangbuk-do including 10 cities (si) and 12 counties (gun) was analyzed using data from the national air pollution monitoring network and from the clean air policy support system (CAPSS) from 2017 to 2021. The national air pollution monitoring network data showed that the concentrations of CO, NO2, SO2, PM10, and PM2.5 decreased gradually and the concentration of O3 maintained constantly during 5 years. The data from the CAPSS indicated that the main sources of CO, NOx, SOx, VOCs, and NH3, were the biomass combustion, road/non-road mobile sources, industrial activities, organic solvents usage, and agriculture, respectively. In addition, the main sources of total suspended particulate (TSP), PM10, and PM2.5 were fugitive dust and biomass combustion. It was found that no significant linear relationship between the air quality concentrations data and CAPSS data due to the different characteristics of the two data groups. Moreover, machine learning models were established using the national air pollution monitoring network data, CAPSS data, meteorological data, and socio-economic indices to predict the concentrations of PM10 and PM2.5. It was revealed that the concentrations of PM10 and PM2.5 were significantly affected by the emissions of CO and PM2.5 (CAPSS) and electricity, gas, steam, and air conditioning supply, respectively.