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基于多尺度交叉趋势样本熵的城市空气质量指数分析

赵文成,  王访

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文章导航 > 环境工程  > 2020 >  38(2): 91-98
徐珊, 杨光, 张承舟, 孙德华, 孙小婷. 基于PSR模型的城市土地生态安全评价:以青岛市为例[J]. 环境工程, 2019, 37(9): 199-204. doi: 10.13205/j.hjgc.201909036
引用本文: 赵文成, 王访. 基于多尺度交叉趋势样本熵的城市空气质量指数分析[J]. 环境工程, 2020, 38(2): 91-98. doi: 10.13205/j.hjgc.202002013
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ZHAO Wen-cheng, WANG Fang. ANALYSIS OF URBAN AIR QUALITY INDEX BASED ON MULTISCALE CROSS TREND SAMPLE ENTROPY[J]. ENVIRONMENTAL ENGINEERING , 2020, 38(2): 91-98. doi: 10.13205/j.hjgc.202002013
Citation: ZHAO Wen-cheng, WANG Fang. ANALYSIS OF URBAN AIR QUALITY INDEX BASED ON MULTISCALE CROSS TREND SAMPLE ENTROPY[J]. ENVIRONMENTAL ENGINEERING , 2020, 38(2): 91-98. doi: 10.13205/j.hjgc.202002013
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基于多尺度交叉趋势样本熵的城市空气质量指数分析

doi: 10.13205/j.hjgc.202002013

  • 湖南农业大学 信息与智能科学技术学院, 长沙 410128

基金项目: 

国家自然科学基金（61973111）；湖南省社科基金（18YBA226）；湖南省研究生创新项目（CX20190527）；湖南省教育厅科研项目（17C0755）。

详细信息
    作者简介:

    赵文成(1987-),女,硕士,主要研究方向为大气污染统计分析及防治。353771953@qq.com

    通讯作者:

    王访(1981-),男,博士,教授,主要研究方向为复杂系统统计分析。topwang619@163.com

ANALYSIS OF URBAN AIR QUALITY INDEX BASED ON MULTISCALE CROSS TREND SAMPLE ENTROPY

  • College of Information and Intelligence, Hunan Agricultural University, Changsha 410128, China

摘要

    摘要
  • 摘要: 为了研究城市的空气质量指数（air quality index，AQI）与各污染物浓度序列之间的一致性，以及相邻城市间污染物的相似程度，提出一种新的多尺度交叉趋势样本熵（multiscale cross trend sample entropy，MCTSE），用于刻画2个具有趋势的序列在不同尺度上的一致性。利用该方法对长沙、株洲和湘潭3个城市春、夏、秋、冬的AQI与PM2.5、PM10、SO2、NO2、CO和O3 6种污染物浓度序列展开研究，为寻找影响这些城市空气质量的污染源以及共同治理提供参考。最后为这些城市制定空气污染防治目标提出了可行的治理对策。
    Abstract: In order to study the consistency between air quality index (AQI) and various concentration series of pollutants in a city, as well as the similarities of each pollutant between its neighbor cities, a multi-scale cross-trend sample entropy (MCTSE) was proposed in this paper. The new method could be used to characterize the consistency of two series, and each of which had trend on different scales. It was applied to investigate the consistency between AQI and concentration series of PM2.5, PM10, SO2, NO2, CO and O3 in four seasons in Changsha, Zhuzhou and Xiangtan. The same method was also used to study the similarities of each pollutant between every two of these three cities. It provided a theoretical basis for finding pollution sources that affected the air quality of these cities and jointly preventing and controlling air pollution. Finally, the aim of air pollution prevention and control was formulated, and the feasible countermeasures were put forward.
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    • 参考文献(39)
  • 佘倩楠, 徐茜, 周陶冶,等. 长三角地区2015年大气重污染特征及其影响因素[J]. 环境科学学报, 2018, 38(8):3185-3196.
    李琛, 刘瑾, 王彦民. 气压对西安市城区空气质量的影响[J]. 环境工程, 2017, 35(3):101-105

    ,122.
    别同, 韩立建, 何亮,等. 城市空气污染对周边区域空气质量的影响[J]. 生态学报, 2018, 38(12):4268-4275.
    XU L Z, BATTERMAN S, CHEN F, et al. Spatiotemporal characteristics of PM2.5, and PM10, at urban and corresponding background sites in 23 cities in China[J]. Science of the Total Environment, 2017, 599/600:2074-2084.
    XIAO K, WANG Y K, WU G, et al. Spatiotemporal characteristics of air pollutants (PM10, PM2.5, SO2, NO2, O3, and CO) in the inland basin city of Chengdu, Southwest China[J]. Atmosphere, 2018, 9(2):74.
    李礼, 许丽萍, 余家燕,等. 重庆主城区近年一次典型空气重污染过程分析[J]. 环境工程学报, 2017, 11(12):6379-6385.
    杨志文, 元洁, 吴琳,等. 夏季空气污染物指数与气象参数相关性分析[J]. 环境工程, 2018, 36(8):83-87.
    CHAN Z Y, XIE X M, CAI J, et al. Understanding meteorological influences on PM2.5 concentrations across China:a temporal and spatial perspective[J]. Atmospheric Chemistry and Physics Discussions, 2017:1-30.
    HAN L J, ZHOU W Q, LI W F. Increasing impact of urban fine particles (PM2.5) on areas surrounding Chinese cities[J]. Scientific Reports, 2015, 5:12467.
    戴孟莲, 王彤, 邓海银, 等. 基于偏相关与逐步回归方法的AQI影响因素分析及预测[J]. 环境保护前沿, 2017, 7(3):191-201.
    陈优良, 陶天慧, 刘新意. 环鄱阳湖城市群空气质量时空分布[J]. 环境污染与防治, 2018, 40(12):1418-1424.
    罗岳平, 刘孟佳, 甘杰,等. 长株潭城市环境空气中PM2.5和O3质量浓度的相关性研究[J]. 安全与环境学报, 2015, 15(4):313-317.
    刘艳萍, 王明仕, 桂晨露,等. 中国工业基地城市群PM2.5时空分布特征及相关性分析[J]. 科学技术与工程, 2018, 18(15):184-189.
    李婷婷,尉鹏,程水源,等. 2005-2014年中三角城市群大气污染特征及变化趋势[J]. 环境工程学报, 2017, 11(5):2977-2984.
    LIU J Z, LI W F, WU J S, et al. Visualizing the intercity correlation of PM2.5 time series in the Beijing-Tianjin-Hebei region using ground-based air quality monitoring data[J]. Plos One, 2018, 13(2):e0192614.
    GONG Z Z, ZHANG X P. Assessment of urban air pollution and spatial spillover effects in China:cases of 113 key environmental protection cities[J]. Journal of Resources and Ecology, 2017, 8(6):584-594.
    SHEN Y, ZHANG L P, FANG X, et al. Spatiotemporal patterns of recent PM2.5 concentrations over typical urban agglomerations in China[J]. Science of the Total Environment, 2019, 655(3):13-26.
    JIANG L, BAI L. Spatio-temporal characteristics of urban air pollutions and their causal relationships:evidence from Beijing and its neighboring cities[J]. Scientific Reports, 2018, 8(1):1279.
    王访, 范毅.基于AMF-HXA的长株潭空气质量指数互相关性分析[J]. 环境保护前沿, 2017, 7(6):443-452.
    WANG F, WANG L, CHEN Y M. Detecting PM2.5's correlations between neighboring cities using a time-lagged cross-correlation coefficient[J]. Scientific Reports, 2017,7:10109.
    WANG F, WANG L, CHEN Y. A DFA-based bivariate regression model for estimating the dependence of PM2.5 among neighbouring cities[J].Scientific Reports, 2018,8(1):7475.
    PINCUS S M. Approximate entropy as a measure of system complexity[J]. PNAS,1991,88(6):2297-2301.
    PINCUS S M. Approximate entropy (ApEn) as a complexity measure[J]. Chaos, 1995,5(1):110-117.
    PINCUS S M. Quantifying complexity and regularity of neurobiological systems[J]. Methods in Neurosciences, 1995, 28:336-363.
    RICHMAN J S, RANDALL M J. Physiological time-series analysis, using approximate entropy and sample entropy[J]. American Journal of Physiology-Heart and Circulatory Physiology, 2000, 278(6):2039-2049.
    刘慧, 和卫星, 陈晓平. 生物时间序列的近似熵和样本熵方法比较[J]. 仪器仪表学报, 2004, 25(增刊):806-807,812.
    LIU L Z, QIAN X Y, LU H Y. Cross-sample entropy of foreign exchange time series[J]. Physica A:Statistical Mechanics and Its Applications, 2010, 389(21):4785-4792.
    COSTA M, GOLDBERGER A L, PENG C K. Multiscale entropy analysis of complex physiologic time series[J]. Physical Review Letters, 2007, 89(6):705-708.
    WU Y, SHANG P J, LI Y L. Multiscale sample entropy and cross-sample entropy based on symbolic representation and similarity of stock markets[J]. Communications in Nonlinear Science and Numerical Simulation, 2018, 56:49-61.
    PENG C K, BULDYREV S V, HAVLIN S, et al. Mosaic organization of DNA nucleotides[J]. Journal of Physical Review. E, 1994, 49(2):1685-1689.
    PENG C K, HAVLIN S, STANLEY H E, et al. Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series[J]. Chaos, 1995, 5(1):82-87.
    KANTELHARDT J W, ZSCHIEGNER S A, KOSCIELNY-BUNDE E, et al. Multifractal detrended fluctuation analysis of nonstationary time series[J]. Physica A, 2002, 316(1/2/3/4):87-114.
    PODOBNIK B, STANLEY H E. Detrended cross-correlation analysis:a new method for analyzing two nonstationary time series[J]. Physical Review Letters, 2008, 100(8):084102.
    ZHOU W X. Multifractal detrended cross-correlation analysis for two nonstationary signals[J]. Physical Review E Statistical Nonlinear & Soft Matter Physics, 2008, 77(2):066211.
    XU W J, LIU C Q, SHI K, et al. Multifractal detrended cross-correlation analysis on NO, NO2 and O3 concentrations at traffic sites[J]. Physica A:Statistical Mechanics and Its Applications, 2018, 502:605-612.
    MANIMARAN P, NARAYANA A C. Multifractal detrended cross-correlation analysis on air pollutants of University of Hyderabad Campus, India[J]. Physica A:Statistical Mechanics and Its Applications, 2018, 502:228-235.
    XIONG H, SHANG P. Weighted multifractal cross-correlation analysis based on Shannon entropy[J]. Communications in Nonlinear Science and Numerical Simulation, 2016, 30(1/2/3):268-283.
    燕丽, 杜小申. 典型城市空气污染特征对比分析[J].中国环境管理, 2018, 10(6):92-98.
    汪伟全. 空气污染的跨域合作治理研究:以北京地区为例[J]. 公共管理学报, 2014, 11(1):55-64

    ,140.
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