基于小波变换的北京、上海等城市PM2.5浓度时空演化特征分析

摘要

The PM2.5 concentration series of five cities in Beijing, Shenyang, Shanghai, Guangzhou and Chengdu are selected and the spatial and temporal characteristics of PM2.5 concentration are analyzed by the method of wavelet transform.Based on the PM2.5 observation sequence of five cities, the missing value processing is carried out.Wavelet transform is used to decompose and reconstruct the PM2.5 concentration sequence, and the reconstructed PM2.5 concentration sequence is compared and analyzed.PM2.5 concentration showed a significant annual change characteristics, the PM2.5 concentration within the year, the highest concentration of PM2.5 in winter, summer PM2.5 concentration of the lowest;PM2.5 diurnal changes in the concentration of bimodal change;the South of the PM2.5 mass concentration is lower than the PM2.5 concentration in the north.%选取北京、沈阳、上海、广州和成都5个城市近年来的PM2.5浓度观测序列,利用小波变换方法开展PM2.5浓度时空演化特征分析.在对5个城市的PM2.5浓度观测序列进行缺失值处理的基础上,采用小波变换方法对PM2.5浓度序列进行小波分解与重构,并对重构后的PM2.5浓度序列进行比较分析.PM2.5浓度变化呈现明显的年变化特征,在年以内的PM2.5浓度变化中,冬季PM2.5浓度最高,夏季PM2.5浓度最低;PM2.5浓度日变化为双峰型变化;南方的PM2.5浓度整体低于北方的PM2.5浓度.