Determination of PM10 and SO2 source contribution using emission inventory data in the multi-industrial city of Ulsan, South Korea

Abstract

Ulsan is the largest industrial city of South Korea. Among criteria air pollutants (CAPs), particulate matters (PM) and sulfur dioxide (SO2), directly emitted from industrial activities, are major environmental concerns in Ulsan. The effect of local sources is crucial for these pollutants, and also long-range atmospheric transport (LRAT) from China is also an important source of CAPs, especially the PM10. However, there have been no studies dealing with both the LRAT and local pollution of CAPs in Ulsan. In this study, we collected and interpreted hourly data on CAPs measured at 14 automatic monitoring stations. The conditional bivariate probability function (CBPF) and air dispersion model CALPUFF were used to identify the local pollution sources of PM10 and SO2. For the LRAT of PM10, potential source contribution function (PSCF) and cluster analysis of back-trajectories were performed. Totally, the monitoring data, modeling results, and back-trajectory data were derived at the hourly data set. These parameters were processed c-tree and randomforest analysis to assess the major sources between local and LRAT effects for each month. The hourly PM10 showed the highest level in April and May and the lowest in August and December. Moreover, the highest and the lowest concentrations of SO2 were observed in July and December, respectively. The CBPF results indicated that the petrochemical industry and road traffic were the main local sources for PM10, however, SO2 concentration was greatly influenced by the petrochemical industry. The CALPUFF results revealed that both PM10 and SO2 were dispersed from the industrial areas to the residential areas in summer. Additionally, the effect of PM emitted from neighboring cities was high. The PSCF and cluster analysis results showed the potential LRAT sources of PM10 was China in spring. Lastly, the importance of the local and LRAT impacts in each month was identified by randomforest analysis. The local impacts of PM10 and SO2 were largest in summer and decreased in winter. The LRAT of PM10 was observed in spring when high levels of PM coming from China. This study can contribute to the identification of the local and long-distance sources of CAPs in other cities.