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Evaluation of Model Performance for Forecasting Fine Particle Concentrations in Korea
Young Sung Ghim1, Yongjoo Choi1, Soontae Kim2, Chang Han Bae2, Jinsoo Park3, Hye Jung Shin3
1 Department of Environmental Science, Hankuk University of Foreign Studies, Yongin, Gyeonggi 17035, Korea
2 Department of Environmental and Safety Engineering, Ajou University, Suwon, Gyeonggi 16499, Korea
3 Air Quality Research Division, National Institute of Environmental Research, Seo, Incheon 22689, Korea
- Degradation of the performance with increasing the concentration level.
- Performance for PM2.5 close to that for Europe rather than for North America.
- Underestimation of SO42– and overestimation of NO3– similar to those in the US.
- Model results typically peak early in the morning and at night.
The performance of a modeling system consisting of WRF model v3.4.1 and CMAQ model v4.7.1 for forecasting fine particle concentrations were evaluated using measurement data at the surface. Twenty-four hour averages of PM2.5 and its major components at Bulgwang (located in the northwest of Seoul) during the period February 2012 through January 2013 were compared with predicted concentrations as well as hourly averages of inorganic ions measured at Yongin (located to the southeast of Seoul) in spring 2012. The mean fractional bias (MFB) of –0.37 for PM2.5 at Bulgwang fell just outside the goal of –0.3, the level of accuracy that the best model can be achieved. Negative values of MFB, especially in winter, along with the correlation coefficient of 0.61 between measured and predicted concentrations showed that the model performance at Bulgwang was closer to that for Europe than that for North America. However, underestimation of SO42– and overestimation of NO3– were similarly observed at Bulgwang as in the United States. Although diurnal variations in the measured values showed distinctive features at Yongin according to the classified patterns, most variations in the predicted values typically showed a peak early in the morning followed by an increase at night.
CMAQ/WRF; Mean fractional bias; PM2.5; Major components; Temporal variations.