香港港口PM2.5和PM10的多重分形特征
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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.
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.
引文
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[17] Burgueno A, Lana X, Serra C, et al. Daily extreme temperature multifractals in Catalonia(NE Spain)[J]. Physics Letters A, 2014, 378(11-12):874-885.
[18] Yuan Ying, Zhuang Xintian. Application research of multifractal theory in sharp fluctuations of stock market[J].Journal of ystems and Management, 2008, 17(3):278-282(in Chinese).苑莹,庄新田.多重分形理论在股市大幅波动中的应用[J].系统管理学报,2008, 17(3):278-282.
[19] Li Wenyong, Shi Kai, Deng Guiping. Multifractal structure of tourism population fluctuations after the earthquake:A case study of Jiuzhaigou scenic area[J]. Tourism Tribune, 2013, 28(3):21-28(in Chinese).李文勇,史凯,邓贵平.震后景区旅游人数波动的多重分形结构研究-以九寨沟风景名胜区为例[J].旅游学刊,2013, 28(3):21-28.
[20] Huang Yi, Liu Chunqiong, Shi Kai, et al. Multifractal characterization of sharp fluctuations about PM10 before and after the haze[J]. Journal of Environmental Science and Technology, 2016, 39(1):140-146(in Chinese).黄毅,刘春琼,史凯,等.灰霾消散前后PM10浓度大幅波动的多重分形分析[J].环境科学与技术,2016, 39(1):140-146.
[21] Shi Kai, Liu Chunqiong, Ai Nanshan. Air quality analysis for Shanghai using multi-fractal approach[J].Environmental Pollution and Control, 2008, 30(9):60-64, 69(in Chinese).史凯,刘春琼,艾南山.上海市空气质量变化的多重分形分析[J].环境污染与防治,2008, 30(9):60-64, 69.
[22] Xu Yan, Liu Fucheng, Zhu Jiamei. Multifractal analysis of air pollutant concentration time series data in Lianyungang City[J]. Journal of Huaihai Institute of Technology:Natural Science Edition,2011,20(1):41-45(in Chinese).徐岩,刘付程,朱佳媚.连云港市大气污染物浓度变化的多重分形分析[J].淮海工学院学报:自然科学版,2011,20(1):41-45.
[23] Zhang Chen, Ni Zhiwei, Jiang Ting. Joint multifractal analysis of relationship of PM2.5 and meteorological conditions based on WPTMM[J]. Systems Engineering-Theory and Practice, 2015, 35(8):2166-2176(in Chinese).张琛,倪志伟,姜婷.基于WPTMM的PM2.5与气象条件关系的联合多重分形分析[J].系统工程理论与实践,2015, 35(8):2166-2176.
[24] Pavon-Dominguez P, Jiménez-Hornero F J, De Rave E G. Multifractal analysis of ground-level ozone concentrations at urban, suburban and rural background monitoring sites in Southwestern Iberian Peninsula[J]. Atmospheric Pollution Research, 2013, 4(2):229-237.
[25] Jiménez-Hornero F J, Jiménez-Hornero J E, De RavéE G, et al. Exploring the relationship between nitrogen dioxide and ground-level ozone by applying the joint multifractal analysis[J]. Environmental Monitoring and Assessment, 2010, 167(1-4):675-684.
[26] Kantelhardt J W, Zschiegner S A, K,oscielny-Bunde E, et al. Multifractal detrended fluctuation analysis of nonstationary time series[J]. Physica A:Statistical Mechanics and Its Applications, 2002, 316(1-4):87-114.
[27] Zhou W X. Multifractal detrended cross-correlation analysis for two nonstationary signals[J]. Physical Review E, 2008, 77(6):066211.
[2] Qiu H, Yu I T, Tian L, et al. Effects of coarse particulate matter on emergency hospital admissions for respiratory diseases:a time-series analysis in Hong Kong[J]. Environmental Health Perspectives, 2Q12, 120(4):572-576.
[3] Wu Shenghu, Shi Kai, Liu Chunqiong, et al. Long-term persistence characteristics of PM2.5 evolution during a typical haze episode in Chengdu[J]. Environmental Science and Technology, 2014, 37(10):9-14, 20(in Chinese).吴生虎,史凯,刘春琼,等.成都市典型灰霾消散前后PM2.5演化的长期持续性特征[J].环境科学与技术,2014,37(10):9-14, 20.
[4] Xiao Zhenghui, Shao Longyi, Zhang Ning. Chemical composition and source analysis of PM10 in winter and spring in Chengguan district of Lanzhou[J]. Environmental Science and Technology, 2011, 34(12):164-168, 17(in Chinese).肖正辉,邵龙义,张宁.兰州城关区冬春季PM10的化学组分和来源分析[J].环境科学与技术,2011, 34(12):164-168, 17.
[5] Li Yang. Characteristics of spatio-temporal variations of PM 10 in key cities of China from 2000 to 2007[J].Journal of Arid Land Resources and Environment, 2009, 23(9):51-54(in Chinese).李杨. 2000~2007年中国重点城市PM10的时空变化特征[J].干旱区资源与环境,2009, 23(9):51-54.
[6] Li Juan, Zhang Guangxing, Li Xia, et al. Analysis of Seasonal variation of PM10 concentration and morphologyTaking Tianshan District, Urumqi in 2004 as example[J]. Urban Environment and Urban Ecology, 2005, 18(6):16-18(in Chinese).李娟,张广兴,李霞,等.PM10浓度及微观特征季节分布分析-以乌鲁木齐天山区2004年为例[J].城市环境与城市生态,2005, 18(6):16-18.
[7] Li Fei, Wu Dui, Tan Haobo, et al. The Characteristics and causes analysis of a Typical Haze Process during the dry season over Guangzhou area:A case study[J]. Journal of Tropical Meteorology, 2012, 28(1):113-122.李菲,吴兑,谭浩波,等.广州地区旱季一次典型灰霾过程的特征及成因分析[J].热带气象学报,2012, 28(1):113-122.
[8] Yu Ye, Xia Dunsheng, Chen Leihua, et al. Analysis of particulate pollution characteristics and its causes in Lanzhou, Northwest China[J]. Environmental Science, 2010, 31(1):22-28(in Chinese).余晔,夏敦胜,陈雷华,等.兰州市PM10污染变化特征及其成因分析[J].环境科学,2010, 31(1):22-28.
[9] Zhao Chenxi, Wang Yunqi, WangYujie, et al. Temporal and spatial distribution of PM2.5 and PM10 pollution status and the correlation of particulate matters and meteorological factors during winter and spring in Beijing[J]. Environmental Science, 2014, 35(2):418-427(in Chinese).赵晨曦,王云琦,王玉杰,等.北京地区冬春PM2.5和PM10污染水平时空分布及其与气象条件的关系[J].环境科学,2014, 35(2):418-427.
[10] Shi K, Liu C Q, Ai N S, et al. Using three methods to investigate time-scaling properties in air pollution indexes time series[J]. Nonlinear Analysis:Real World Applications, 2008, 9(2):693-707.
[11] Schlink U, Dorling S, Pelikan E, et al. A rigorous inter-comparison of ground-level ozone predictions[J]. Atmospheric Environment, 2003, 37(23):3237-3253.
[12] Cobourn W G. An enhanced PM2.5 air quality forecast model based on nonlinear regression and back-trajectory concentrations[J]. Atmospheric Environment, 2010, 44(25):3015-3023.
[13] Chelani A B. Nonlinear dynamical analysis of ground level ozone concentrations at different temporal scales[J].Atmospheric Environment, 2010, 44(34):4318-4324.
[14] Qiao J W, Wang Z. Self-organized criticality behavior in bulk metallic glasses[J]. Journal of Iron and Steel Research(International), 2016, 23(1):7-13.
[15] Zhuang X, Wei Y, Ma F. Multifractality, efficiency analysis of Chinese stock market and its cross-correlation with WTI crude oil price[J]. Physica A:Statistical Mechanics and Its Applications, 2015, 430:101-113.
[16] Jiménez-Hornero F J, Gutiérrez D R E,A Ariza-Villarverde A B, et al. Description of the seasonal pattern in ozone concentration time series by using the strange attractor multifractal formalism[J]. Environmental Monitoring and Assessment, 2010, 160(1-4):229-236.
[17] Burgueno A, Lana X, Serra C, et al. Daily extreme temperature multifractals in Catalonia(NE Spain)[J]. Physics Letters A, 2014, 378(11-12):874-885.
[18] Yuan Ying, Zhuang Xintian. Application research of multifractal theory in sharp fluctuations of stock market[J].Journal of ystems and Management, 2008, 17(3):278-282(in Chinese).苑莹,庄新田.多重分形理论在股市大幅波动中的应用[J].系统管理学报,2008, 17(3):278-282.
[19] Li Wenyong, Shi Kai, Deng Guiping. Multifractal structure of tourism population fluctuations after the earthquake:A case study of Jiuzhaigou scenic area[J]. Tourism Tribune, 2013, 28(3):21-28(in Chinese).李文勇,史凯,邓贵平.震后景区旅游人数波动的多重分形结构研究-以九寨沟风景名胜区为例[J].旅游学刊,2013, 28(3):21-28.
[20] Huang Yi, Liu Chunqiong, Shi Kai, et al. Multifractal characterization of sharp fluctuations about PM10 before and after the haze[J]. Journal of Environmental Science and Technology, 2016, 39(1):140-146(in Chinese).黄毅,刘春琼,史凯,等.灰霾消散前后PM10浓度大幅波动的多重分形分析[J].环境科学与技术,2016, 39(1):140-146.
[21] Shi Kai, Liu Chunqiong, Ai Nanshan. Air quality analysis for Shanghai using multi-fractal approach[J].Environmental Pollution and Control, 2008, 30(9):60-64, 69(in Chinese).史凯,刘春琼,艾南山.上海市空气质量变化的多重分形分析[J].环境污染与防治,2008, 30(9):60-64, 69.
[22] Xu Yan, Liu Fucheng, Zhu Jiamei. Multifractal analysis of air pollutant concentration time series data in Lianyungang City[J]. Journal of Huaihai Institute of Technology:Natural Science Edition,2011,20(1):41-45(in Chinese).徐岩,刘付程,朱佳媚.连云港市大气污染物浓度变化的多重分形分析[J].淮海工学院学报:自然科学版,2011,20(1):41-45.
[23] Zhang Chen, Ni Zhiwei, Jiang Ting. Joint multifractal analysis of relationship of PM2.5 and meteorological conditions based on WPTMM[J]. Systems Engineering-Theory and Practice, 2015, 35(8):2166-2176(in Chinese).张琛,倪志伟,姜婷.基于WPTMM的PM2.5与气象条件关系的联合多重分形分析[J].系统工程理论与实践,2015, 35(8):2166-2176.
[24] Pavon-Dominguez P, Jiménez-Hornero F J, De Rave E G. Multifractal analysis of ground-level ozone concentrations at urban, suburban and rural background monitoring sites in Southwestern Iberian Peninsula[J]. Atmospheric Pollution Research, 2013, 4(2):229-237.
[25] Jiménez-Hornero F J, Jiménez-Hornero J E, De RavéE G, et al. Exploring the relationship between nitrogen dioxide and ground-level ozone by applying the joint multifractal analysis[J]. Environmental Monitoring and Assessment, 2010, 167(1-4):675-684.
[26] Kantelhardt J W, Zschiegner S A, K,oscielny-Bunde E, et al. Multifractal detrended fluctuation analysis of nonstationary time series[J]. Physica A:Statistical Mechanics and Its Applications, 2002, 316(1-4):87-114.
[27] Zhou W X. Multifractal detrended cross-correlation analysis for two nonstationary signals[J]. Physical Review E, 2008, 77(6):066211.