Temporal evolution characteristics of PM2.5 concentration based on continuous wavelet transform

• Published in: The Science of the total environment 2020-01, Vol.699, p.134244-134244, Article 134244
• Main Authors: Chen, Xiaobing, Yin, Lirong, Fan, Yulin, Song, Lihong, Ji, Tingting, Liu, Yan, Tian, Jiawei, Zheng, Wenfeng
• Format: Article
• Language: English
• Subjects: Continuous wavelet transform; Morlet wavelet; PM2.5; Temporal evolution characteristic
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2019.134244

Fine particulate matter (PM2.5) is an important haze index, and the researches on the evolutionary characteristics of the PM2.5 concentration will provide a fundamental and guiding prerequisite for the haze prediction. However, the past researchers were usually based on the overall time-domain evolution information of PM2.5. Since the temporal evolution of PM2.5 concentration is nonstationary, previous studies might neglect some important localization features that the evolution has various predominant periods at different scales. Therefore, we applied the wavelet transform to study the localized intermittent oscillations of PM2.5. First, we analyze the daily average PM2.5 concentration collected from the automatic monitoring stations. The result reveals that the predominant oscillation period does vary with time. There exist multiple oscillation periods on the scale of 14–32 d, 62–104 d, 105–178 d and 216–389 d and the 298d is the first dominant period in the entire evolutionary process. Moreover, we want to figure out whether the temporal characteristics of PM2.5 in the days with heavy haze also have localized intermittent periodicities. We select the hourly average PM2.5 concentration in 120 h when the haze pollution is serious. We find that the principal period has experienced two abrupt shifts and the energy at the 63-hour scale is the most powerful. The results in these two independent analyses come into the same conclusion that the multiscale features shown in the temporal evolution of PM2.5 cannot be ignored and may play an important role in the further haze prediction. [Display omitted] •The evolutionary characteristics of PM2.5 vary with time.•Wavelet transform is powerful to capture the temporal features of PM2.5 concentration at different scales.•In the temporal characteristics of PM2.5 from 2014 to 2017, there exist multiple oscillation periods.•The time scale of 216-389 d is the predominant oscillation period of the PM2.5 daily evolution.•In the evolution of PM2.5 in 120 hours, the dominant period experiences two abrupt changes.