基于MF-DCCA的呼吸道疾病与大气污染物相关性分析

Multifractal Detrended Cross-Correlation Analysis of Incidence Rate of Respiratory Diseases and Atmospheric Pollutants

针对呼吸道系统疾病与大气PM2.5、SO2浓度序列的相关性特征,应用多重分形消除趋势波动分析法(MF-DCCA),对张家界市永定区呼吸道系统疾病患病人数与大气PM2.5、SO2浓度序列进行了研究。结果发现该地区呼吸道系统疾病患病人数与大气PM2.5、SO2浓度的相关性具有长期持续特征和多重分形特征。随后对它们相关性多重分形特征的动力来源进行了分析,通过随机重排和相位随机处理,结果表明在不同时间尺度上的长期持续性影响是其主要动力来源。进一步研究发现该地区呼吸道系统疾病与大气PM2.5、SO2浓度序列的相关性在四个季节均具有长期持续性的多重分形特征,且夏季多重分形特征相对强于其他季节。

In order to get a better understanding of the correlation between respiratory diseases outpatients and atmospheric PM2.5,SO2 concentrations,multifractal detrended cross-correlation analysis(MF-DCCA)was used to study the sequence of respiratory diseases outpatients and PM2.5,SO2 concentrations in Yongding District.The results show that the correlation between respiratory diseases outpatients and atmospheric PM2.5,SO2 concentrations has the characteristics of long-term persistence and multifractal.Then the dynamic sources of their correlation multifractal features are analyzed.Through random rearrangement and phase randomization procedure,the results show that the long-term persistence effect is the main driving force at different time scales.Further study found that the correlation between respiratory system diseases and atmospheric PM2.5,SO2 concentrations sequence in the four seasons has long-term multifractal characteristics,and the multiple fractal features in summer are stronger than those in other seasons.