Source Apportionment of Ambient PM2.5 Data using the EPA-PMF Model at Monitoring site near the steel mill

Various air pollution problems ultimately have a serious negative impact on human health and welfare, damage to property, and adversely affect animals and plants. For this reason, people's interest in air pollution problems has increased, and researchers' study to solve air pollution problems has become more diverse and increased. In order to efficiently manage PM_2.5 and prepare effective control measures, qualitative and quantitative analysis of pollutants emitting PM_2.5 must be conducted first, and PM_2.5 must be collected from the receptor and its characteristics analysed. Receptor methods that estimate and evaluate the contribution of pollutants are continuously implemented. The receptor model is a mathematical and statistical methodology that analyses the physical and chemical characteristics of air pollutants at the receptor, identifies sources that affect air quality, and quantitatively estimates the contribution of each source (source apportionment).

Since the release of PMF2 and ME, these programs have been successfully applied to assess ambient PM source contributions in many locations of virous countries. However, PMF and ME models are somewhat difficult to use because these models are DOS-base programs that require understanding of a special script language. Therefore, in order to provide a widely applicable PMF with a user-friendly and graphic user interface (GUI)-based program, the US Environmental Protection Agency (EPA) developed an EPA version of PMF. The US EPA continued to upgrade to the EPA-PMF model including the factor rotation functions. Therefore, the current version 5.0 model has been developed and widely used to source apportionment.

Pohang, the study area of this study, is where Korea's representative steel industry and steel-related industries are gathered, and a steel-related industrial complex is located there. In addition, it is one of the areas with severe air pollution that emits large amounts of particulate matter such as PM_2.5 and various gaseous pollutants due to the frequent operation of heavy trucks to transport produced steel products. Therefore, in this study, we performed EPA-PMF modeling using data from the PM_2.5 Pohang monitoring site, identified the PM_2.5 sources, and then estimated the contribution of each source.

The PM_2.5 samples were collected at Pohang air pollution monitoring site from January 2018 to August 2022 and 27 species (OC, EC, SO₄^2-, NO₃^-, Cl^-, Na⁺, NH₄⁺, K⁺, Mg²⁺, Ca²⁺, As, Br, Ca, Cd, Cr, Cu, Fe, K, Mn, Ni, Pb, S, Se, Si, Ti, V, and Zn) were analyzed by XRF (X-ray fluorescence spectroscopy; Xact-series 620, USA), IC (ion chromatography; URG-9000D, USA), and TOT (thermal optical transmittance; 4F-semi continuous field analyzer, USA) methods. The EPA-PMF model was used to identify sources and estimate source apportionment in Pohang site. The source apportionment data for this study area, which is characterized by the location of a large-scale steel plant and related industrial complexes, can be said to be of great importance, unlike the results of source contribution studies for the study area that have been widely conducted in general. More detailed results of source apportionment for PM_2.5 samples in Pohang site will be presented.