Assessing Spatiotemporal Characteristics of Urban PM2.5 Using Fractal Dimensions and Wavelet Analysis

• Published in: Mathematical problems in engineering Vol. 2020; no. 2020; pp. 1 - 15
• Main Authors: Li, Shan, Mao, Liang, Zhang, Haizhong, Wang, Ligang, Wu, Hao
• Format: Journal Article
• Language: English
• Published: Cairo, Egypt Hindawi Publishing Corporation 2020; Hindawi; John Wiley & Sons, Inc
• Subjects: Accuracy; Air pollution; Air quality; Airborne sensing; Algorithms; Engineering; Fractal analysis; Fractal geometry; Fractals; Humidity; Methods; Neural networks; Periodic variations; Pollutants; Pollution control; Remote monitoring; Remote sensing; Remote sensors; Spatial distribution; Spectroradiometers; Studies; Urbanization; Wavelet analysis; Wavelet transforms

Due to rapid urbanization and industrialization, atmospheric fine particulate matter (PM2.5) has become a primary urban pollutant, seriously affecting air quality and resident health. Existing airborne remote sensing and ground sensor monitoring can efficiently collect PM2.5 data. It is urgent yet c...