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小波方差分析北京市PM2.5质量浓度序列周期特征 |
Wavelet Variance Analysis on the Periodic Characteristic of PM2.5Mass Concentration in Beijing |
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DOI: |
中文关键词: 小波变换 方差分析 PM2.5 时间序列 周期性 北京 |
英文关键词: Wavelet transform Variance analysis PM2.5 Time series Periodicity Beijing |
基金项目:北京市属高等学校高层次人才引进与培养——“长城学者”培养计划项目“基于无线传感器网络的城市空气质量实时监测系统研究”基金资助项目(CIT&TCD20130320) |
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中文摘要: |
为分析北京市大气污染物PM2.5质量浓度的时间序列周期性,采用Morlet小波变换对PM2.5质量浓度进行分析,利用小波方差估计该市PM2.5日均质量浓度的主周期,并通过显著性检验。结果表明,北京市PM2.5日均质量浓度主周期为180 d左右,为后续大气污染物PM2.5时间序列研究提供参考。 |
英文摘要: |
In order to analyze the time series periodicity of atmospheric pollutant PM2.5 mass concentration in Beijing, Morlet wavelet transform was used to analyze the PM2.5 concentration, and the primary period of average daily concentration of PM2.5 in Beijing was estimated by the wavelet variance, and had passed the significance test. The results show that the average daily concentration of PM2.5 in Beijing is 180 d, which provides a reference for the follow up study of time series of atmospheric pollutants PM2.5. |
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