An operational forecasting system for atmospheric environment over East China was introduced in this paper. The system was established based on the WRF-Chem Model, an online coupled regional chemical transport model. Anthropogenic emission inventory was composed of MEIC and INTEX-B data. The forecasting performance for fine particles (PM_2.5) was evaluated during two high-concentration time periods (November 1^st, 2013~January 31^st, 2014 and November 1^st, 2014~January 31^st, 2015). Evaluation results could be summarized with the following features. 1) The numerical forecasting system had generally good performance of regional PM_2.5 forecasts. The performance was comparable during the two periods and three forecast lengths of 24-hour, 48-hour, and 72-hour. The integrated correlation coefficients (Rs) were greater than 0.7, and CSI/TS score for PM_2.5 pollution days was 0.55. For the cities evaluated, Rs were mostly over 0.5, and about half of locations had mean biases below 25%. 2) Regional differences could be found in the performance of different cities. Better performance of Rs was found over northern and central part of the domain, whereas relatively larger errors occurred over the northern areas. 3) When evaluated for pollution category and major cities, the model showed degraded performance during heavy PM_2.5 pollution episodes. 4) PM_2.5 concentrations tended to be under-estimated in general. About 3/4 of the daily biases were negative and most mean biases were between -20% and -30%. 5) Lack of feedback from pollution to meteorology as well as errors in the emission inventory were likely the main reasons leading to lower forecast capability during heavy PM_2.5 pollution episodes. Therefore, further improvements were required to forecast accurately under these severe conditions.