Meso-scale Air Quality Forecasting Using Initial Conditions Generated by the Global Air Quality Forecasting Model CAMS

초록

An air quality forecasting system consisting of WRF3.6 and CMAQ5.2 was developed to forecast criteria air pollutants including PM10, PM2.5, NO2, SO2, CO and O3 in Korea. The model domain consists of three nested grids, the outer most domain encompasses the most part of China and inner most domain covers the Seoul Metropolitan Area. Both weather forecasting and air quality forecasting may benefit from real-time monitoring data to limit the propagating uncertainties of input parameters to forecasted parameters. In the present study, the global forecasted results with data assimilation using ground and satellite monitoring are used to generate initial conditions for weather and air quality forecasting. GFS (Global Forecasting System) is used for WRF3.6 and CAMS (Copernicus Atmospheric Monitoring System Model) is used for CMAS 5.1). The forecasted PM-10 and NO2 from the October of 2015 to the January of 2016 compares very well with observations for concentration levels and peak time. The IOA and R2 of Seoul were 0.90 and 0.85 for PM-10 and 0.87 and 0.87 for NO2. The NBIAS of Seoul is 0.05 for PM-10, exhibiting a slight over-prediction. On the contrary, the NBIAS of Seoul -0.14 for NO2, exhibiting moderate under-prediction. The signs of NBIAS for PM-10 differs from one city to another with a small magnitude. However, the signs of NBIAS for NO2 are always negative in all the major cities in Korea showing its negative bias. This is because the life time of NO2 is rather short and therefore initial condition correction may be not sufficient override underestimated NO2 emissions.