Forecasting PM$_{2.5}$ concentration is important to solving air pollution problems in Wuhan. This paper proposes a PM$_{2.5}$ concentration forecast model based on nonlinear regression, including a single-value forecast model and an interval forecast model. The single-value forecast model can precisely forecast PM$_{2.5}$ concentration for the next day, with forecast bias about 6 $μg/m^3$ in goodness of fit analysis. The interval forecast model can efficiently forecast high-concentration and low-concentration days, which covers 60%-80% observed samples in model validation. Moreover, this paper combines the PM$_{2.5}$ concentration forecast model with NCEP Climate Forecast System Version 2 to realize its forecast application, then develops NCEP CFS2's PM$_{2.5}$ concentration forecast model to enhance forecast accuracy. The results indicate that the PM$_{2.5}$ concentration forecast model has good capacity for independent forecasting.

翻译：PM$_{2.5}$浓度预测对解决武汉市空气污染问题具有重要意义。本文提出一种基于非线性回归的PM$_{2.5}$浓度预测模型，包括单值预测模型和区间预测模型。单值预测模型可精确预测次日PM$_{2.5}$浓度，在拟合优度分析中预测偏差约为6 $μg/m^3$。区间预测模型能有效预测高浓度日和低浓度日，在模型验证中覆盖了60%-80%的观测样本。此外，本文将PM$_{2.5}$浓度预测模型与NCEP气候预测系统第二版（NCEP CFS2）相结合以实现其预测应用，进而开发了基于NCEP CFS2的PM$_{2.5}$浓度预测模型以提升预测精度。结果表明，该PM$_{2.5}$浓度预测模型具有良好的独立预测能力。