  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
$\mu g/m^3$ 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.
