摘要
颗粒物是港口地区的主要污染物之一,利用多重分形理论分析港口地区PM2.5和PM10浓度的多重分形特征。首先,运用多重分形消除趋势波动分析方法(Multifractal detrended fluctuation analysis, MF-DFA)分析PM2.5和PM10自身的多重分形特征,结果显示PM2.5和PM10浓度的演化过程表现出非线性、复杂性的多重分形特征,且PM10浓度的多重分形特征较PM2.5强.其次,利用多重分形消除趋势交叉波动分析方法(Multifractal detrended cross-correlation analysis, MF-DCCA)研究港口地区PM2.5和PM10的交叉相关性,结果表明两者之间不仅存在具有长期记忆性的多重分形特征,而且其互相关性多重分形特征具有明显的季节变化特征.港口地区PM2.5和PM10的多重分形特征在春季最强,夏季次之,秋季最弱。这些结论对港口地区PM2.5和PM10的联合控制具有一定的参考价值.
Particulate matter is one of the major pollutants in the port area. The multifractal theory was used to analyze the multifractal characteristics of the concentrations of PM2.5 and PM10 in the port area.Firstly, the multifractal characteristics of PM2.5 and PM10 were analyzed by Multifractal detrended fluctuation analysis(MF-DFA). The results showed that the evolution of PM2.5 and PM10 shows nonlinear and complex multifractal characteristics, and the multifractal characteristics of PM10 is more than that of PM2.5. Second,Multifractal detrended cross-correlation analysis(MF-DCCA) was used to study the cross-correlation of PM2.5 and PM10 in the port area. The results showed that there existed not only multifractal characteristics with long-term memory between them, but also obvious seasonal variation for its cross-correlation multifractal features. The multifractal characteristics of PM2.5 and PM10 in the port area are the strongest in spring, the second strongest in summer, and the weakest in autumn. These conclusions provide some reference value for the joint control of port area PM2.5 and PM10.
作者
谢焕丽
何红弟
XIE Huanli;HE Hongdi(Logistics Science and Engineering Research Institute, Shanghai Maritime University, Shanghai 201306, China)
出处
《大气与环境光学学报》
CAS
CSCD
2019年第3期179-190,共12页
Journal of Atmospheric and Environmental Optics
基金
国家自然科学基金,11672176
上海市科委资助项目,17DZ2280200~~
关键词
多重分形特征
多重分形理论
颗粒物
季节变化
香港港口
multifractal characteristics
multifractal theory
particulate matter
seasonal variation
Hongkong port