Nonlinear regression models to forecast PM_2.5 concentration in Wuhan, China
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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 μ g/m^3 in goodness of fit analysis. The interval forecast model can efficiently forecast high-concentration and low-concentration days, which covers 60 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.
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