京津冀城市群PM_(2.5)的空间分布及相关性分析
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摘要
以京津冀城市群2014—2016年1 090 d PM_(2.5)浓度日值数据为基础,基于Arc GIS 10.2软件,选择典型月份分析PM_(2.5)月优良天数比例、月重度及严重污染天数比例的时空分布特征及其空间相关性。结果表明,研究区城市之间各年PM_(2.5)浓度月优良天数比例与月重度、严重污染天数比例整体波动趋势基本一致,其中PM_(2.5)月优良天数比例高值集中在5—9月,PM_(2.5)月重度与严重污染天数比例高值集中在11—次年2月;从区域分布看,PM_(2.5)月重度与严重污染天数比例从石家庄、保定市向周边城市由高到低递减。选取典型月份对研究区PM_(2.5)进行空间相关分析,结果表明PM_(2.5)存在正空间相关性,即PM_(2.5)浓度的空间分布表现出空间聚集性。
Based on daily averaged values of PM_(2.5)mass concentration in Beijing-Tianjin-Hebei Urban Agglomeration from2014 to 2016,this study employed Arc GIS 10.2 to analyze the temporal-spatial characteristics of pollution distribution.The spatial correlation of indices such as the percentage of superior,heavily and severely polluted days during typical PM_(2.5)months was also performed.The results show that the profile of the monthly rate of non-polluted days was consistent with the trend of the overall air quality fluctuation during the observation period.The higher proportion of PM_(2.5)-superior period was concentrated from May to September.The heavily and severely polluted days spanned between November and February.From the regional distribution,the proportional spatial pattern of PM_(2.5)heavy and severe pollution decreased from central cities as Shijiazhuang and Baoding to surrounding places.The typical months were selected to carry out spatial correlation of PM_(2.5).Corresponding results indicate that PM_(2.5)had a positive spatial correlation.The spatial distribution of PM_(2.5)mass concentration showed spatial clustering profile.
Based on daily averaged values of PM_(2.5)mass concentration in Beijing-Tianjin-Hebei Urban Agglomeration from2014 to 2016,this study employed Arc GIS 10.2 to analyze the temporal-spatial characteristics of pollution distribution.The spatial correlation of indices such as the percentage of superior,heavily and severely polluted days during typical PM_(2.5)months was also performed.The results show that the profile of the monthly rate of non-polluted days was consistent with the trend of the overall air quality fluctuation during the observation period.The higher proportion of PM_(2.5)-superior period was concentrated from May to September.The heavily and severely polluted days spanned between November and February.From the regional distribution,the proportional spatial pattern of PM_(2.5)heavy and severe pollution decreased from central cities as Shijiazhuang and Baoding to surrounding places.The typical months were selected to carry out spatial correlation of PM_(2.5).Corresponding results indicate that PM_(2.5)had a positive spatial correlation.The spatial distribution of PM_(2.5)mass concentration showed spatial clustering profile.
引文
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[17]陈斐,杜道生.空间统计分析与GIS在区域经济分析中的应用[J].武汉大学学报(信息科学版),2002,27(4):391-396.[CHEN Fei,DU Dao-sheng.Application of the Integration of Spatial Statistical Analysis With GIS to the Analysis of Regional E-conomy[J].Geomatics and Information Science of Wuhan University,2002,27(4):391-396.]
[18]万鲁河,王绍巍,陈晓红.基于Geo DA的哈大齐工业走廊GDP空间关联性[J].地理研究,2011,30(6):977-984.[WAN Luhe,WANG Shao-wei,CHEN Xiao-hong.GeoDA-Based Spatial Correlation Analysis of GDP in Hadaqi Industrial Corridor[J].Geographical Research,2011,30(6):977-984.]
[19]CLIFF A D,ORD K.Spatial Autocorrelation[M].London:Pion,1973:7-17.
[20]SAWADA M.Rookcase:An Excel 97/2000 Visual Basic(VB)Add-in for Exploring Global and Local Spatial Autocorrelation[J].Bulletin of the Ecological Society of America,1999,80(4):231-234.
[21]ANSELIN L.Local Indicators of Spatial Association-LISA[J].Geographical Analysis,1995,27(2):93-115.
[22]GETIS A,ORD K.The Analysis of Spatial Association by Use of Distance Statistics[J].Geographical Analysis,1992,24(3):189-206.
[23]GETIS A,ORD K.Local Spatial Statistics:An Overview[C]∥LONGLEY P,BATTY M E.Spatia Analysis:Modelling in a GISEnvirnnment.[s.l.]∶[s.n.],1996:261-277.
[24]麻永建,徐建刚.基于ESDA的河南省区域经济差异的时空演变研究[J].软科学,2006,20(5):51-54.[MA Yong-jian,XUJian-gang.A Study on the Spatial-Temporal Development of Regional Economic Disparities in Henan Province Based on ESDA[J].Soft Science,2006,20(5):51-54.]
[2]SHI Y,CHEN J M,HU D W,et al.Airborne Submicron Particulate(PM1)Pollution in Shanghai,China:Chemical Variability,Formation/Dissociation of Associated Semi-Volatile Components and the Impacts on Visibility[J].Science of the Total Environment,2014,473/474:199-206.
[3]CHOW J C,WATSON J G,KUHNS H,et al.Source Profiles for Industrial,Mobile and Area Sources in the Big Bend Regional Aerosol Visibility and Observational Study[J].Chemosphere,2004,54(2):185-208.
[4]李松,罗绪强,李恋,等.基于GIS的中国PM2.5浓度空间分布及影响因素分析[J].水土保持通报,2015,35(4):202-205,212.[LI Song,LUO Xu-qiang,LI Lian,et al.Spatial Distribution Model of Countrywide PM2.5Concentration and Influence Factors Using Geographical Information System[J].Bulletin of Soil and Water Conservation,2015,35(4):202-205,212.]
[5]LNDAHL J,PAGELS J,SWIETLICKI E,et al.A Set-Up for Field Studies of Respiratory Tract Deposition of Fine and Ultrafine Particles in Humans[J].Journal of Aerosol Science,2006,37(9):1152-1163.
[6]LONATI G,CRIPPA M,GIANELLE V,et al.Daily Patterns of the Multi-Modal Structure of the Particle Number Size Distribution in Milan,Italy[J].Atmospheric Environment,2011,45(14):2434-2442.
[7]陈媛,岑况,NORRA S,等.北京市区大气气溶胶PM2.5污染特征及颗粒物溯源与追踪分析[J].现代地质,2010,24(2):345-354.[CHEN Yuan,CEN Kuang,NORRA S,et al.Study on Pollution Characteristics of PM2.5in the Aerosol,Tracing and Tracking Atmospheric Particulates in Beijing City[J].Geoscience,2010,24(2):345-354.]
[8]赵普生,张小玲,孟伟,等.京津冀区域气溶胶中无机水溶性离子污染特征分析[J].环境科学,2011,32(6):1546-1549.[ZHAOPu-sheng,ZHANG Xiao-ling,MENG Wei,et al.Characteristics of Inorganoic Water-Soluble Ions From Aerosols in Beijing-Tianjin-Hebei Area[J].Environmental Science,2011,32(6):1546-1549.]
[9]黄德生,张世秋.京津冀地区控制PM2.5污染的健康效益评估[J].中国环境科学,2013,33(1):166-174.[HUANG De-sheng,ZHANG Shi-qiu.Health Benefit Evaluation for PM2.5Pollution Control in Beijing-Tianjin-Hebei Region of China[J].China Environmental Science,2013,33(1):166-174.]
[10]韩彩云,赵欣,单艳红,等.我国大气VOCs的监测技术和污染特征研究进展[J].生态与农村环境学报,2018,34(2):114-123.[HAN Cai-yun,ZHAO Xin,SHAN Yan-hong,et al.A Review of Researches on Atmospheric VOCs Monitoring Technique and Pollution Characteristics in China[J].Journal of Ecology and Rural Environment,2018,34(2):114-123.]
[11]陈飞,张小华,于洪霞,等.石家庄市冬季PM2.5污染特征、成因及潜在源区分析[J].生态与农村环境学报,2017,33(11):975-982.[CHEN Fei,ZHANG Xiao-hua,YU Hong-xia,et al.Characteristics,Causes and Potential Source Regions of PM2.5Pollution in Winter in Shijiazhuang,China[J].Journal of Ecology and Rural Environment,2017,33(11):975-982.]
[12]王旭,胡引翠,田冰,等.京津冀地区AOD和PM2.5浓度的特征及相关性分析[J].环境工程学报,2016,10(9):5069-5074.[WANG Xu,HU Yin-cui,TIAN Bing,et al.Analysis of Characteristic and Correlation of Mass Concentration of Aerosoloptical Depth Retrievals and Ground-Level PM2.5in the Beijing-Tianjin-Hebei Region,China[J].Chinese Journal of Environmental Engineering,2016,10(9):5069-5074.]
[13]马丽梅,张晓.中国雾霾污染的空间效应及经济、能源结构影响[J].中国工业能源,2014(4):19-31.[MA Li-mei,ZHANGXiao.The Spatial Effect of China's Haze Pollution and the Impact From Economic Change and Energy Structure[J].China Industrial Economics,2014(4):19-31.]
[14]昌晶亮,余洪,罗伟伟.珠三角地区PM2.5浓度空间自相关分析[J].生态与农村环境学报,2015,31(6):853-858.[CHANG Jingliang,YU Hong,LUO Wei-wei.Spatial Autocorrelation Analysis of PM2.5Concentration in the Pearl River Delta[J].Journal of Ecology and Rural Environment,2015,31(6):853-858.]
[15]陈小勇,林鹏.我国红树植物分布的空间自相关分析[J].华东师范大学学报,2000(3):104-109.[CHEN Xiao-yong,LINPeng.Spatial Autocorrelation Analysis on the Distribution of Mangrove in China[J].Journal of East China normal University,2000(3):104-109.]
[16]戴维·W·S·黄,杰·李.ArcView GIS与Arc GIS地理信息统计分析[M].北京:中国财政经济出版社,2008:8.[DAVID W SW,JAY L.Statistical Analysis of Geographic Information With ArcView GIS and Arc GIS[M].Beijing:China Financial&Economic Publishing House,2008:8.]
[17]陈斐,杜道生.空间统计分析与GIS在区域经济分析中的应用[J].武汉大学学报(信息科学版),2002,27(4):391-396.[CHEN Fei,DU Dao-sheng.Application of the Integration of Spatial Statistical Analysis With GIS to the Analysis of Regional E-conomy[J].Geomatics and Information Science of Wuhan University,2002,27(4):391-396.]
[18]万鲁河,王绍巍,陈晓红.基于Geo DA的哈大齐工业走廊GDP空间关联性[J].地理研究,2011,30(6):977-984.[WAN Luhe,WANG Shao-wei,CHEN Xiao-hong.GeoDA-Based Spatial Correlation Analysis of GDP in Hadaqi Industrial Corridor[J].Geographical Research,2011,30(6):977-984.]
[19]CLIFF A D,ORD K.Spatial Autocorrelation[M].London:Pion,1973:7-17.
[20]SAWADA M.Rookcase:An Excel 97/2000 Visual Basic(VB)Add-in for Exploring Global and Local Spatial Autocorrelation[J].Bulletin of the Ecological Society of America,1999,80(4):231-234.
[21]ANSELIN L.Local Indicators of Spatial Association-LISA[J].Geographical Analysis,1995,27(2):93-115.
[22]GETIS A,ORD K.The Analysis of Spatial Association by Use of Distance Statistics[J].Geographical Analysis,1992,24(3):189-206.
[23]GETIS A,ORD K.Local Spatial Statistics:An Overview[C]∥LONGLEY P,BATTY M E.Spatia Analysis:Modelling in a GISEnvirnnment.[s.l.]∶[s.n.],1996:261-277.
[24]麻永建,徐建刚.基于ESDA的河南省区域经济差异的时空演变研究[J].软科学,2006,20(5):51-54.[MA Yong-jian,XUJian-gang.A Study on the Spatial-Temporal Development of Regional Economic Disparities in Henan Province Based on ESDA[J].Soft Science,2006,20(5):51-54.]