Toward Periodicity Correlation of Roadside PM$_{2.5}$ Concentration and Traffic Volume: A Wavelet Perspective

Periodicity correlations between roadside PM
_2.5
concentration and traffic volume are difficult to explore due to the complicated process of production and diffusion of PM
_2.5
: a reaction of vehicle emission with atmosphere, dependence with wind speed, pavement width, vehicle speed, vehicle type, etc. We propose a framework to explore the periodicity correlation between roadside PM
_2.5
concentration and traffic volume using wavelet transform. The framework utilizes wavelet spectrum to obtain the characteristic periods of PM
_2.5
concentration and traffic volume, and utilizes cross-wavelet spectrum to explore the hysteresis response of PM
_2.5
concentration with respect to traffic volume. Different from traditional research work which handle pollutants and traffic data of macro scales, our study examines the micro-scale relationship of PM
_2.5
concentration and traffic volume. We conduct experiments from four urban streets of Beijing, and reveal two micro-scale rules: (a) the characteristic period of PM
_2.5
concentration approximates the characteristic period of traffic volume, and both of them are significantly affected by the traffic signal cycle; (b) PM
_2.5
concentration exhibits a time delay within 0.3-0.9 minutes with respect to traffic volume. The research will benefit the further study on the evolution of PM
_2.5
concentration and traffic volume, and provide a reference for the mitigation of PM
_2.5
pollution by traffic control as well as practical traffic pollutant regulations in metropolises.