Industrial emissions, mainly from industrial complexes, are important sources of ambient Volatile Organic Compounds (VOCs). Identification of the significant VOC sources from industrial complexes has practical significance for emission reduction. VOC samples were collected from July 2019 to June 2020. A Positive Matrix Factorization (PMF) receptor model was used to evaluate the VOC sources in the area. Four sources were identified by PMF analysis, including coating-1, coating-2, printing, and vehicle exhaust. The coating-1 source was revealed to have the highest contribution (41.5%), followed by coating-2 (23.9%), printing (23.1%), and vehicle exhaust (11.6%). The source showing the highest contribution was coating emissions, originating from the northwest to southwest of the sample site. It also relates to facilities that produce auto parts. The major components of VOC emissions from the coating facilities were toluene, m,p-xylene, ethylbenzene, o-xylene, and butyl acetate. Industrial emissions should be the top priority to meet the relevant control criteria, followed by vehicular emissions. This study provides a strategy for VOC source apportionment from an industrial complex, which is helpful in the development of targeted control strategies.

X선을 이용한 chest radiography는 일반적으로 180 cm의 SID에서 실시되고 있다. digital chest radiography에서 AEC를 적용하고 120 kVp, 320 mA에서 SID를 180 cm부터 340 cm까지 20 cm 단위로 증가시켜 가며 영상의 질과 환자선량의 관계를 알아보았다. chest phantom 영상의 정성적인 영상평가를 위해 VGA를, 정량적인 평가를 위해 SNR을 분석하였다. 선량은 ESAK로 측정하고 effective dose는 PCXMC를 이용하였다. 연구결과 일반적으로 시행되는 SID 180 cm를 기준으로 했을 때, ESAK의 경우 240 cm, 280 cm, 320 cm에서 각각 8.7%, 11.47%, 13.56%의 유의한 감소가 있었다. effective dose의 경우 전신에 대해 2.89%, 4.67%, 6.41%의 감소, 폐에서 5.08%, 6.98%, 9.6%의 감소가 관찰되었다. SNR의 경우 각각 9.04%, 8.24%, 11.46%의 감소가 관찰되었으며 특히, SID 260 cm ~ 300 cm 구간에서 8.03%의 작은 감소가 나타났고 SID 340 cm까지도 5.24로 5이하로 감소되지 않았다. VGA에서는 통계적으로 유의한 차이가 없는 진단적 가치가 높은 영상으로 평가되었다. 따라서 eigital chest radiography에서 SID를 300 cm까지 증가시킴으로 화질의 저하 없이 환자선량을 감소시킬 수 있을 것으로 기대된다.

The objectives of this study were to measure ambient total gaseous mercury (TGM) concentrations in Seoul, to analyze the characteristics of TGM concentration, and to identify of possible source areas for TGM using back-trajectory based hybrid receptor models like PSCF (Potential Source Contribution Function) and RTWC (Residence Time Weighted Concentration). Ambient TGM concentrations were measured at the roof of Graduate School of Public Health building in Seoul for a period of January to October 2004. Average TGM concentration was 3.43±1.17 ng/㎥. TGM had no notable pattern according to season and meteorological phenomena such as rainfall, Asian dust, relative humidity and so on. Hybrid receptor models incorporating backward trajectories including potential source contribution function (PSCF) and residence time weighted concentration (RTWC) were performed to identify source areas of TGM. Before hybrid receptor models were applied for TGM, we analysed sensitivities of starting height for HYSPLIT model and critical value for PSCF. According to result of sensitivity analysis, trajectories were calculated an arrival height of 1000 m was used at the receptor location and PSCF was applied using average concentration as criterion value for TGM. Using PSCF and RTWC, central and eastern Chinese industrial areas and the west coast of Korea were determined as important source areas. Statistical analysis between TGM and GEIA grided emission bolsters the evidence that these models could be effective tools to identify possible source area and source contribution.

This study were to simulate major criteria air pollutants and estimate regional source-receptor relationship using air quality prediction model (TAPM ; The Air Pollution Model) in the Seoul Metropolitan area. Source-receptor relationship was estimated by contribution of each region to other regions and region itself through dividing the Seoul metropolitan area into five regions. According to administrative boundary, region Ⅰ and region Ⅱ were Seoul and Incheon in order. Gyeonggi was divided into three regions by directions like southern(region Ⅲ), northern(Ⅳ) and eastern(Ⅴ) area. Gridded emissions (1km×1km) by Clean Air Pollicy Support System (CAPSS) of National Institute of Environmental Research (NIER) was prepared for TAPM simulation. The operational weather prediction system, Regional Data Assimilation and Prediction System (RDAPS) operated by the Korean Meteorology Administration (KMA) was used for the regional weather forecasting with 30km grid resolution. Modeling period was 5 continuous days for each season with non-precipitation . The results showed that region Ⅰ was the most air-polluted area and it was 3～4 times more polluted region than other regions for NO2, SO2 and PM10. Contributions of SO2 NO2 and PM10 to region Ⅰ, Ⅱ and Ⅲ were more than 50 percent for their own sources. However region Ⅳ and Ⅴ were mostly affected by sources of region Ⅰ, Ⅱ and Ⅲ. When emissions of all regions were assumed to reduce 10 and 20 percent separately, air pollution of each region was reduced linearly and the contributions of reduction scenario were similar to those of base case. As input emissions were reduced according to different ratio - region Ⅰ 40 percent, region Ⅱ and Ⅲ 20 percent, region Ⅳ and Ⅴ 10 percent, air pollutions of region Ⅰ and Ⅲ were decreased remarkably. The contributions to regionⅠ, Ⅱ, Ⅲ were also reduced for their own sources. However, region Ⅰ, Ⅱ and Ⅲ affected more regions Ⅳ and Ⅴ. Shortly, graded reduction of emission could be more effective to control air pollution in emission imbalanced area.