基于复杂网络的区域空气污染PM_(2.5)分析
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摘要
把复杂网络方法应用于空气污染指数PM_(2.5)的研究。对中国区域的PM_(2.5)数据通过相关分析建立了相关性复杂网络。通过对网络的特质性质如节点度、社区结构、模体等性质的分析表明,能够有效分析出主要污染城市,空气污染城市具有群聚现象,需要一起进行治理,这与现实中的现象相符。由于污染空气的流动性性质,分析空气污染城市的群聚性对于空气污染的治理有一定的参考意义。
The complex network was used to investigate PM_(2.5) of the air pollution. The relevant data of PM_(2.5) were analyzed with correlation and the complex network in regions in china was established. Through the study of the degree, community structure and motif, the results showed that the main polluted cities in China could be effectively analyzed by this method, and the air polluted cities having cluster phenomena needed to be treated as a whole, which was consistent with real conditions. Because of the fluidity of the air, this research provides guidance for analyzing the agglomeration of polluted cities.
The complex network was used to investigate PM_(2.5) of the air pollution. The relevant data of PM_(2.5) were analyzed with correlation and the complex network in regions in china was established. Through the study of the degree, community structure and motif, the results showed that the main polluted cities in China could be effectively analyzed by this method, and the air polluted cities having cluster phenomena needed to be treated as a whole, which was consistent with real conditions. Because of the fluidity of the air, this research provides guidance for analyzing the agglomeration of polluted cities.
引文
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[28] WANG J, YANG H. Complex network-based analysis of air temperature data in china[J]. Mod Phys Lett B, 2009, 23(14): 1781-1789.
[29] XU X, ZHANG J, SMALL M. Superfamily phenomena and motifs of networks induced from time series[J]. Proceedings of the National Academy of Sciences, 2008, 105(50): 19601-19605.
[30] NEWMAN M E J. The structure and function of complex networks[J]. SIAM Rev, 2003, 45: 167256.
[31] FORTUNATO S. Community detection in graph[J]. Phys Rep, 2010, 486: 75-174.
[32] RAVASZ E, BARABáSI A L. Hierarchical organization in complex networks[J]. Phys Rev E Statistical Nonlinear & Soft Matter Physics, 2003, 67(2): 026112.
[33] SHENORR S, MILO R, MANGAN S, et al. Network motifs in the transcriptional regulatory network of Escherichia coli[J], Nature Genetics, 2002, (31): 64-68.
[34] AUSTIN R B, DAVID F G, JURE L. Supplementary materials for higher-order organization of complex network [J]. Science, 2016, 353(6295): 163-166.
[2] BOVE M C, BROTTO P, CASSOLA F, et al. An integrated PM2.5 source apportionment study: Positive matrix factorisation vs the chemical transport models CAMx[J]. Atmospheric Environment, 2014, 94: 274-286.
[3] WANG F, CHEN D S, CHENG S Y, et al. Identification of regional atmospheric PM10, transport pathways using HYSPLIT, MM5-CMAQ and synoptic pressure pattern analysis[J]. Environmental Modelling & Software, 2010. 25(8): 927-934.
[4] 杨新兴, 冯丽华, 尉鹏. 大气颗粒物 PM2.5 及其危害[J]. 前言科学, 2012, 6(21): 22-30.
[5] RODRIGUEZ S, QUEROL X, ALASTUEY A, et al. Comparative PM10-PM2.5 source contribution study at rural, urban and industrial sites during PM episodes in Eastern Spain[J].Science of the Total Environment, 2004, 328(1-3: 1-26.
[6] ELANGASINGHE M A, SINGHAL N, DIRKS K N, et al. Complex time series analysis of PM10 and PM2.5 for a coastal site using artificial neural network modelling and k-means clustering[J]. Atmospheric Environment, 2014(94): 106-116.
[7] 朱坦, 吴琳, 毕晓辉, 等.大气颗粒物源解析受体模型优化技术研究[J]. 中国环境科学2010, 30(7): 865-870.
[8] 杨洪斌, 邹旭东, 汪宏宇, 等. 大气环境中 PM2.5 的研究进展与展望[J]. 气象与环境学报, 2012, 28(3): 77-82.
[9] SUN Y, WANG Y, ZHUANG G. The airborne particulate pollution in Beijing concentration, composition, distribution and sources[J]. Atmosphere Environment, 2004, 38(35): 5991-6004.
[10] 于兴娜, 李新姝, 登增然, 等. 北京雾霾天气期间气溶胶光学特征[J]. 环境科学, 2012, 33(4): 1057-1062.
[11] 宋宇, 唐孝炎, 方晨, 等. 北京市能见度下降与颗粒物污染的关系[J]. 环境科学学报, 2003, 23(4): 468-471.
[12] 苏福庆, 高庆先, 张志刚, 等. 北京边界层外来污染物输送通道[J]. 环境科学研究, 2004, 17(1): 26-29.
[13] FAN X H, WANG L, XU H H, et al. Characterizing air quality data from complex network perspective[J]. Environmental Science and Pollution Research International, 2016, 23(4): 3621-3631.
[14] GU C, COOMANS C P, HU K, et al. Lack of exercise leads to significant and reversible loss of scale invariance in both aged and young mice [J]. PNAS, 2015, 112(8), 2320-2324.
[15] YANG T G, GU C G, YANG H J, et al. Long-range correlations in sentence series from a story of the stone [J].Plos One, 2016, 11(9): e0162423.
[16] QIU L, YANG T G, YIN Y H, et al. Multifractals embedded in short time series: An unbiased estimation of probability moment[J]. Phy. Rev. E, 2016, 94(6): 062201.
[17] YANG Y, GU C, XIAO Q, et al. Evolution of scaling behaviors embedded in sentence series from a story of the stone [J]. Plos One, 2017, 12(2): e0171776.
[18] 肖琴.网络在股票市场相关分析中的应用[J].中国管理科学, 2016, 24(SI): 470-474.
[19] 肖琴.网络在股票市场相关分析中的应用[C]//第十八届中国管理科学学术年会论文集.[s.l.]: [s.n.], 2016, 476-480.
[20] 王燕娟、齐景超、严捷冰, 等. 中国大学关系的复杂网络[J]. 科学通报, 2012, 10: 875-884.
[21] 刘珊, 彭林, 温彦平, 等.太原市 PM2.5 中有机碳和元素碳的污染特征[J].环境科学, 2015, 36(2): 396-401.
[22] 王丽.基于复杂网络理论的空气质量数据分析[D].江苏大学硕士论文, 2017.
[23] 张仲勇, 王仲君. 城市 PM2.5 扩散网络模型的研究[J]. 中国环境监测, 2014(6): 129-132.
[24] 薛安, 耿恩泽. 基于复杂网络的中国 PM2.5 区域划分[J]. 应用基础与工程科学学报, 2015(SI): 68-78.
[25] 马宇博, 高广阔.基于节点重要性评价的京津冀雾霾污染网络研究[J].环境科学学报, 2018, 38(6): 2287-2296.
[26] KRUSKAL J B. On the shortest spanning sub-tree of a graph and traveling salesman problem[J]. Proc Am Math Soc, 1956, 7(1): 48-50.
[27] YANG Y, YANG H. Complex network-based time series analysis[J]. Physica A: Statistical Mechanics & Its Applications, 2008, 387(5): 1381-1386.
[28] WANG J, YANG H. Complex network-based analysis of air temperature data in china[J]. Mod Phys Lett B, 2009, 23(14): 1781-1789.
[29] XU X, ZHANG J, SMALL M. Superfamily phenomena and motifs of networks induced from time series[J]. Proceedings of the National Academy of Sciences, 2008, 105(50): 19601-19605.
[30] NEWMAN M E J. The structure and function of complex networks[J]. SIAM Rev, 2003, 45: 167256.
[31] FORTUNATO S. Community detection in graph[J]. Phys Rep, 2010, 486: 75-174.
[32] RAVASZ E, BARABáSI A L. Hierarchical organization in complex networks[J]. Phys Rev E Statistical Nonlinear & Soft Matter Physics, 2003, 67(2): 026112.
[33] SHENORR S, MILO R, MANGAN S, et al. Network motifs in the transcriptional regulatory network of Escherichia coli[J], Nature Genetics, 2002, (31): 64-68.
[34] AUSTIN R B, DAVID F G, JURE L. Supplementary materials for higher-order organization of complex network [J]. Science, 2016, 353(6295): 163-166.