摘要
以西安市PM10日平均浓度时间序列为例,根据小波分析的基本原理,应用小波分解和重构对PM10浓度时间序列的变化进行了分析,得到PM10的年变化趋势和突变特征。研究结果表明,用小波分析应用于大气污染物浓度时间序列的分析是可行的。
In illustration of the PM10 time series of daily average concentration in Xi'an City, the yearly change trend of PM10 time series and jump features of the variations are analyzed using the wavelet decomposition and reconstruction.The study shows that wavelet transform can clearly demonstrate the features of air pollutant time series of concentration.
出处
《环境工程》
CAS
CSCD
北大核心
2006年第1期61-63,共3页
Environmental Engineering
基金
西安市科技计划项目(SF200346)
关键词
小波分析
分解和重构
PM10
时间序列
wavelet analysis, decomposition and reconstruction, PM10 and time series