Impacts of Chemical Initial Conditions in the WRF-CMAQ Model on the Ozone Forecasts in Eastern China

Abstract

Ozone (O3) has become the major factor for exceeding air pollution standards in many Chinese cities, especially in the more economically developed and densely populated regions, such as eastern China. In this study, we applied the Weather Research and Forecasting/Community Multiscale Air Quality (WRF/CMAQ) model to predict the air quality, and evaluated the influences of different chemical initial conditions on the O3 forecasts with observations in Tai’an and other 13 cities in eastern China in June 2021. The influences of different chemical initial conditions on the O3 forecasts are presented by using two sets of meteorological data (NCEP Final Operational Global Analysis [FNL] and Global Forecast System [GFS]) as initial conditions (IC) and boundary conditions (BC) to drive the WRF/CMAQ model. It was found that the O3 concentrations forecasted by FNL-GFS, in which the chemical IC derived from the CMAQ simulation results by using the FNL data as IC and BC, were closer to observations in all cities than GFS-GFS, in which the chemical IC derived from the CMAQ simulation results by using the GFS data as IC and BC. The normalized mean bias (NMB) values of FNL-GFS for O3 met the benchmark (±15%), while the NMB values of GFS-GFS in Hangzhou and Shijiazhuang did not meet the benchmark. The model performances in Tai’an city were similar to those in 13 cities with better results for FNL-GFS than GFS-GFS. The comparisons of contributions of source regions to O3 in the receptor Tai’an city indicate that different episodes had different relative contributions of source regions and that the simulations of FNL-GFS were more similar to the retrospective simulations than GFS-GFS. The comparisons of contributions of different source sectors to O3 in Tai’an city show that industry emissions are the largest contributor, followed by transportation, power plants and residential emissions.