| 基于MF-DCCA 的呼吸道疾病与大气污染物相关性分析 |
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| 引用本文： | 黄毅,郑凯莉,彭立平,刘春琼,杨艺池.基于MF-DCCA 的呼吸道疾病与大气污染物相关性分析[J].大气与环境光学学报,2021,16(1):35-43. |
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| 作者姓名： | 黄毅 郑凯莉 彭立平 刘春琼 杨艺池 |
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| 作者单位： | 1 江西财经大学统计学院, 江西 南昌 330013;2.吉首大学数学与统计学院, 湖南 吉首 416000;3.吉首大学旅游与管理工程学院, 湖南 张家界 427000;4.吉首大学生物资源与环境科学学院, 湖南 吉首 416000 |
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| 基金项目： | Scientific Research Project of Jishou University;Supported by National Natural Science Foundation;Project of the Natural Science Fund of Hunan Province;Open Fund for key Laboratories of Ecotourism in Hunan Province;Project of Hunan Education Department |
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| 摘 要： | 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。
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| 关 键 词： | PM2:5 SO2 多重分形 呼吸道系统疾病 大气污染物 |
| 收稿时间： | 2019-11-13 |
| 修稿时间： | 2020-05-13 |
Multifractal Detrended Cross-Correlation Analysis of Incidence Rate of Respiratory Diseases and Atmospheric Pollutants |
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| HUANG Yi,ZHENG Kaili,PENG Liping,LIU Chunqiong,YANG Yichi.Multifractal Detrended Cross-Correlation Analysis of Incidence Rate of Respiratory Diseases and Atmospheric Pollutants[J].Journal of Atmospheric and Environmental Optics,2021,16(1):35-43. |
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| Authors: | HUANG Yi ZHENG Kaili PENG Liping LIU Chunqiong YANG Yichi |
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| Affiliation: | 1.School of Statistics, Jiangxi University of Finance and Economics, Nanchang 330013 China;2.Department of Mathematic and Statistics, Jishou University, Jishou 416000, China;3.Department of Tourisim and Administrative Engineering, Jishou University, Zhangjiajie 427000, China;4.Department of Biology and Environmental Sciences, Jishou University, Jishou 416000, China |
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| Abstract: | 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. |
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| Keywords: | PM2:5 SO2 multifractal respiratory diseases atmospheric pollutant |
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