Modeling and forecasting daily movement of ambient air mean PM₂.₅ concentration based on the elliptic orbit model with weekly quasi-periodic extension: a case study.

Nowadays, the issue of air pollution has continuously been a global public health concern. Modeling and forecasting daily movement of ambient air mean PM2.5 concentration is an increasingly important task as it is intimately associated with human health that the air pollution has unignorable negative effects in reducing air quality, damaging environment, even causing serious harm to health. It is demonstrated that daily movement of mean PM₂.₅ concentration approximately exhibits weekly cyclical variations as daily particle pollution in the air is largely influenced by human daily activities. Then, based on weekly quasi-periodic extension for daily movement of mean PM₂.₅ concentration, the called elliptic orbit model is proposed to describe its movement. By mapping daily movement of mean PM₂.₅ concentration as one time series into the polar coordinates, each 7-day movement is depicted as one elliptic orbit. Experimental result and analysis indicate workability and effectiveness of the proposed method. Here we show that with the weekly quasi-periodic extension, daily movements of mean PM₂.₅ concentration at the given monitoring stations in Xiangtan of China are well described by the elliptic orbit model, which provides a vivid description for modeling and prediction daily movement of mean PM₂.₅ concentration in a concise and intuitive way.