STA 223 project 2
Beijing experienced serious air pollution, especially PM 2.5 problems during 2010-2014. The daily PM 2.5 levels could be affected by season, weather, and some other meteorological parameters. This project used functional data analysis and time series data on PM 2.5 in Beijing to unveil the seasonal change in PM 2.5 levels and its relationship with wind speed, which is believed to alleviate air pollution to some extent. The data smoothing and functional principal component analysis revealed differences in PM 2.5 patterns among different seasons and an opposite trend to that of wind speed. Further functional linear regression showed that wind speed was negatively associated with PM 2.5 level most of the time.