中国PM2.5排放数据的空间模拟方法研究
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摘要
采用多元线性回归分析方法,以近期某年中国31个省级PM2.5排放数据为因变量,选取省级的高速公路长度、干线公路长度、支线公路长度、人口、GDP和工业总产值6个因子为自变量构建模型,对PM2.5排放数据进行空间分布模拟,得到近期中国PM2.5排放数据公里格网分布图,然后在此基础上分析了PM2.5排放数据强度的空间分布规律。结果表明:(1)大部分省的相对误差小于30%,模拟结果精度较高,表明多元线性回归模型可以准确的模拟PM2.5排放数据的空间分布;(2)中国PM2.5排放强度区域分布差异明显,整体表现为从东部向中西部逐渐降低,同时还存在几个明显的高值和低值区域。
Based on the idea of attribute data spatialization,we first built a multiple regression model with the length of expressway,the length of trunk highway,the length of branch highway,population,GDP and gross industrial output value as independent variables,PM2. 5 emission data as dependent variables. Then the PM2. 5 emission data was spatialized from provincial level to the kilometer grid level with the method of combining model computation with error correction. Finally we analyzed the spatial distribution patterns of PM2. 5 emission data. The results showed:( 1) The mean relative errors of most provinces are less than 30%,which indicates the model is characterized by higher precision;( 2) There were distinct regional differences distribution characteristics,which mainly showed that the intensity of PM2. 5 emission data gradually reduced from the eastern areas to the middle-western areas,and there were several obvious high-value regions and low-value regions in China.
Based on the idea of attribute data spatialization,we first built a multiple regression model with the length of expressway,the length of trunk highway,the length of branch highway,population,GDP and gross industrial output value as independent variables,PM2. 5 emission data as dependent variables. Then the PM2. 5 emission data was spatialized from provincial level to the kilometer grid level with the method of combining model computation with error correction. Finally we analyzed the spatial distribution patterns of PM2. 5 emission data. The results showed:( 1) The mean relative errors of most provinces are less than 30%,which indicates the model is characterized by higher precision;( 2) There were distinct regional differences distribution characteristics,which mainly showed that the intensity of PM2. 5 emission data gradually reduced from the eastern areas to the middle-western areas,and there were several obvious high-value regions and low-value regions in China.
引文
[1]国家统计局.中华人民共和国2017年国民经济和社会发展统计公报.
[2]吴乐英,钟章奇,刘昌新,等.中国省区间贸易隐含PM2.5的测算及其空间转移特征[J].地理学报,2017,72(2):292-302.
[3]中华人民共和国环境保护部.GB3095-2010环境空气质量标准[S].北京:中国环境科学出版社.
[4]Rd P C,Dockery D W.Health effects of fine particulate air pollution:lines that connect.[J].Journal of the Air&Waste Management Association,2010,56(10):709-742.
[5]王占山,李云婷,陈添,等.2013年北京市PM2.5的时空分布[J].地理学报,2015,70(1):110-120.
[6]常炉予,许建明,周广强,等.上海典型持续性PM2.5重度污染的数值模拟[J].环境科学,2016,37(3):825-833.
[7]汉瑞英,陈健,王彬.利用LUR模型模拟杭州市PM2.5质量浓度空间分布[J].环境科学学报,2016,36(9):3379-3385.
[8]杨冕,王银.长江经济带PM2.5时空特征及影响因素研究[J].中国人口·资源与环境,2017,27(1):91-100.
[9]陶俊,柴发合,高健,等.16届亚运会期间广州城区PM2.5化学组分特征及其对霾天气的影响[J].环境科学,2013,34(2):409-415.
[10]张洛红,范芳,蒋炜炜,等.珠三角地区大气PM2.5中重金属污染水平及健康风险评价[J].环境科学学报,2017,37(1):370-380.
[11]焦利民,许刚,赵素丽,等.基于LUR的武汉市PM2.5浓度空间分布模拟[J].武汉大学学报:信息科学版,2015,40(8):1088-1094.
[12]贺祥,林振山,刘会玉,等.基于灰色关联模型对江苏省PM2.5浓度影响因素的分析[J].地理学报,2016,71(7):1119-1129.
[13]乔宝文,刘子锐,胡波,等.北京冬季PM2.5中金属元素浓度特征和来源分析[J].环境科学,2017,38(3):876-883.
[14]林晓辉,赵阳,樊孝俊,等.南昌市秋季大气PM2.5中金属元素富集特征及来源分析[J].环境科学,2016,37(1):35-40.
[15]于扬,岑况,NORRA Stefan,等.北京市大气可吸入颗粒物的化学成分和来源[J].地质通报,2012,31(1):156-163.
[16]Pope CA 3rd;Thun MJ;Namboodiri MM et al.Particulate air pollution as a predictor of mortality in a prospective study of U.S.adults.[J].American Journal of Respiratory and Critical Care Medicine,1995,151(3 Pt 1):669-674.
[17]Hong Y C,Lee J T,Kim H,et al.Effects of air pollutants on acute stroke mortality[J].Environmental Health Perspectives,2002,110(2):187-191.
[18]Du X,Kong Q,Ge W,et al.Characterization of personal exposure concentration of fine particles for adults and children exposed to high ambient concentrations in Beijing,China[J].Journal of Environmental Sciences,2010,22(11):1757-1764.
[19]汉瑞英,陈健,王彬,等.利用LUR模型模拟浙江省PM2.5质量浓度空间分布[J].科技通报,2016,32(8):215-220.
[20]Gang L,Fu J,Dong J,et al.Spatio-Temporal Variation of PM2.5 Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China[J].International Journal of Environmental Research&Public Health,2013,11(1):173-186.
[21]王振波,方创琳,许光,等.2014年中国城市PM2.5浓度的时空变化规律[J].地理学报,2015,70(11):1720-1734.
[22]廖顺宝,张赛.属性数据空间化误差评价指标体系研究[J].地球信息科学学报,2009,11(2):176-182.
[23]Deichmann U,Gottsegen J,Maloy K.The global demography project[M].Santa Barbara:National Center for Geographic Information and Analysis,1995.
[24]Tobler W,Deichmann U,Gottsegen J,et al.World population in a grid of spherical quadrilaterals[J].International Journal of Population Geography,1997,3(3):203-225.
[25]Joly D,Nilsen L,Fury R,et al.Temperature interpolation at a large scale:test on a small area in Svalbard[J].International Journal of Climatology,2003,23(13):1637-1654.
[26]Vicente-Serrano S M,Saz-Sánchez M A,Cuadrat J M.Comparative analysis of interpolation methods in the middle Ebro Valley(Spain):application to annual precipitation and temperature[J].Climate Research,2003,24(2):161-180.
[27]廖顺宝,孙九林.基于GIS的青藏高原人口统计数据空间化[J].地理学报,2003,58(1):25-33.
[28]Yang,X H,Huang,Y H,Dong,P L,et al.An updating system for the gridded population database of China based on remote sensing,GIS and spatial database technologies[J].Sensors,2009,9(2):1128-1140.
[29]Elvidge C D,Baugh K E,Kihn E A,et al.Relation between satellite observed visible-near infrared emissions,population,economic activity and electric power consumption[J].International Journal of Remote Sensing,1997,18(6):1373-1379.
[30]Elvidge C D,Imhoff M L,Baugh K E,et al.Night-time lights of the world:1994-1995[J].Isprs Journal of Photogrammetry&Remote Sensing,2001,56(2):81-99.
[31]廖顺宝,秦耀辰.草地理论载畜量调查数据空间化方法及应用[J].地理研究,2014,33(1):179-190.
[32]Li M,Zhang Q,Kurokawa J,et al.MIX:a mosaic Asian anthropogenic emission inventory for the MICS-Asia and the HTAPprojects[J].Atmospheric Chemistry&Physics Discussions,2015,15(23):34813-34869.
[33]黄莹,包安明,陈曦,等.基于绿洲土地利用的区域GDP公里格网化研究[J].冰川冻土,2009,31(1):162-169.
[34]廖顺宝,李泽辉.基于人口分布与土地利用关系的人口数据空间化研究---以西藏自治区为例[J].自然资源学报,2003,18(6):659-665.
[35]张智胜,陶俊,谢绍东,等.成都城区PM2.5季节污染特征及来源解析[J].环境科学学报,2013,33(11):2947-2952.
[36]胡鸣,张懿华,赵倩彪.上海市冬季PM2.5无机元素污染特征及来源分析[J].环境科学学报,2015,35(7):1993-1999.
[37]张振华.PM2.5浓度时空变化特性、影响因素及来源解析研究[D].杭州:浙江大学,2014.
[38]杨昆,杨玉莲,朱彦辉,等.中国PM2.5污染与社会经济的空间关系及成因[J].地理研究,2016,35(6):1051-1060.
[39]廖顺宝,姬广兴,侯鹏敏,等.面向粮食产量空间化的多元回归分析模型中的两个关键问题探讨[J].自然资源学报,2015,30(11):1922-1932.
[2]吴乐英,钟章奇,刘昌新,等.中国省区间贸易隐含PM2.5的测算及其空间转移特征[J].地理学报,2017,72(2):292-302.
[3]中华人民共和国环境保护部.GB3095-2010环境空气质量标准[S].北京:中国环境科学出版社.
[4]Rd P C,Dockery D W.Health effects of fine particulate air pollution:lines that connect.[J].Journal of the Air&Waste Management Association,2010,56(10):709-742.
[5]王占山,李云婷,陈添,等.2013年北京市PM2.5的时空分布[J].地理学报,2015,70(1):110-120.
[6]常炉予,许建明,周广强,等.上海典型持续性PM2.5重度污染的数值模拟[J].环境科学,2016,37(3):825-833.
[7]汉瑞英,陈健,王彬.利用LUR模型模拟杭州市PM2.5质量浓度空间分布[J].环境科学学报,2016,36(9):3379-3385.
[8]杨冕,王银.长江经济带PM2.5时空特征及影响因素研究[J].中国人口·资源与环境,2017,27(1):91-100.
[9]陶俊,柴发合,高健,等.16届亚运会期间广州城区PM2.5化学组分特征及其对霾天气的影响[J].环境科学,2013,34(2):409-415.
[10]张洛红,范芳,蒋炜炜,等.珠三角地区大气PM2.5中重金属污染水平及健康风险评价[J].环境科学学报,2017,37(1):370-380.
[11]焦利民,许刚,赵素丽,等.基于LUR的武汉市PM2.5浓度空间分布模拟[J].武汉大学学报:信息科学版,2015,40(8):1088-1094.
[12]贺祥,林振山,刘会玉,等.基于灰色关联模型对江苏省PM2.5浓度影响因素的分析[J].地理学报,2016,71(7):1119-1129.
[13]乔宝文,刘子锐,胡波,等.北京冬季PM2.5中金属元素浓度特征和来源分析[J].环境科学,2017,38(3):876-883.
[14]林晓辉,赵阳,樊孝俊,等.南昌市秋季大气PM2.5中金属元素富集特征及来源分析[J].环境科学,2016,37(1):35-40.
[15]于扬,岑况,NORRA Stefan,等.北京市大气可吸入颗粒物的化学成分和来源[J].地质通报,2012,31(1):156-163.
[16]Pope CA 3rd;Thun MJ;Namboodiri MM et al.Particulate air pollution as a predictor of mortality in a prospective study of U.S.adults.[J].American Journal of Respiratory and Critical Care Medicine,1995,151(3 Pt 1):669-674.
[17]Hong Y C,Lee J T,Kim H,et al.Effects of air pollutants on acute stroke mortality[J].Environmental Health Perspectives,2002,110(2):187-191.
[18]Du X,Kong Q,Ge W,et al.Characterization of personal exposure concentration of fine particles for adults and children exposed to high ambient concentrations in Beijing,China[J].Journal of Environmental Sciences,2010,22(11):1757-1764.
[19]汉瑞英,陈健,王彬,等.利用LUR模型模拟浙江省PM2.5质量浓度空间分布[J].科技通报,2016,32(8):215-220.
[20]Gang L,Fu J,Dong J,et al.Spatio-Temporal Variation of PM2.5 Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China[J].International Journal of Environmental Research&Public Health,2013,11(1):173-186.
[21]王振波,方创琳,许光,等.2014年中国城市PM2.5浓度的时空变化规律[J].地理学报,2015,70(11):1720-1734.
[22]廖顺宝,张赛.属性数据空间化误差评价指标体系研究[J].地球信息科学学报,2009,11(2):176-182.
[23]Deichmann U,Gottsegen J,Maloy K.The global demography project[M].Santa Barbara:National Center for Geographic Information and Analysis,1995.
[24]Tobler W,Deichmann U,Gottsegen J,et al.World population in a grid of spherical quadrilaterals[J].International Journal of Population Geography,1997,3(3):203-225.
[25]Joly D,Nilsen L,Fury R,et al.Temperature interpolation at a large scale:test on a small area in Svalbard[J].International Journal of Climatology,2003,23(13):1637-1654.
[26]Vicente-Serrano S M,Saz-Sánchez M A,Cuadrat J M.Comparative analysis of interpolation methods in the middle Ebro Valley(Spain):application to annual precipitation and temperature[J].Climate Research,2003,24(2):161-180.
[27]廖顺宝,孙九林.基于GIS的青藏高原人口统计数据空间化[J].地理学报,2003,58(1):25-33.
[28]Yang,X H,Huang,Y H,Dong,P L,et al.An updating system for the gridded population database of China based on remote sensing,GIS and spatial database technologies[J].Sensors,2009,9(2):1128-1140.
[29]Elvidge C D,Baugh K E,Kihn E A,et al.Relation between satellite observed visible-near infrared emissions,population,economic activity and electric power consumption[J].International Journal of Remote Sensing,1997,18(6):1373-1379.
[30]Elvidge C D,Imhoff M L,Baugh K E,et al.Night-time lights of the world:1994-1995[J].Isprs Journal of Photogrammetry&Remote Sensing,2001,56(2):81-99.
[31]廖顺宝,秦耀辰.草地理论载畜量调查数据空间化方法及应用[J].地理研究,2014,33(1):179-190.
[32]Li M,Zhang Q,Kurokawa J,et al.MIX:a mosaic Asian anthropogenic emission inventory for the MICS-Asia and the HTAPprojects[J].Atmospheric Chemistry&Physics Discussions,2015,15(23):34813-34869.
[33]黄莹,包安明,陈曦,等.基于绿洲土地利用的区域GDP公里格网化研究[J].冰川冻土,2009,31(1):162-169.
[34]廖顺宝,李泽辉.基于人口分布与土地利用关系的人口数据空间化研究---以西藏自治区为例[J].自然资源学报,2003,18(6):659-665.
[35]张智胜,陶俊,谢绍东,等.成都城区PM2.5季节污染特征及来源解析[J].环境科学学报,2013,33(11):2947-2952.
[36]胡鸣,张懿华,赵倩彪.上海市冬季PM2.5无机元素污染特征及来源分析[J].环境科学学报,2015,35(7):1993-1999.
[37]张振华.PM2.5浓度时空变化特性、影响因素及来源解析研究[D].杭州:浙江大学,2014.
[38]杨昆,杨玉莲,朱彦辉,等.中国PM2.5污染与社会经济的空间关系及成因[J].地理研究,2016,35(6):1051-1060.
[39]廖顺宝,姬广兴,侯鹏敏,等.面向粮食产量空间化的多元回归分析模型中的两个关键问题探讨[J].自然资源学报,2015,30(11):1922-1932.