中国典型城市PM_(2.5)浓度时空演绎规律及影响因素分析
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摘要
为探讨空气中ρ(PM_(2. 5))的空间集聚特征和气候、大气成分变量对空气中ρ(PM_(2. 5))的影响,利用首批纳入PM_(2. 5)监测的74个城市的ρ(PM_(2. 5))数据计算Moran's I指数,并选取其中38个典型城市进行计量分析.在基于引力模型的空间权重矩阵基础上,构建面板数据SDM(空间面板杜宾模型).结果表明:ρ(PM_(10))、ρ(SO_2)、ρ(CO)、ρ(O_3)、RH(relative humidity,相对湿度)与城市ρ(PM_(2. 5))呈正相关,而T(temperature,温度)和WS(wind speed,风速)与城市ρ(PM_(2. 5))呈负相关;ρ(PM_(10))、ρ(CO)、RH是位于前3位影响城市ρ(PM_(2. 5))的关键性因素,其总效应分别为0. 720 1、0. 241 7、0. 133 9.地理上邻近城市ρ(PM_(2. 5))具有明显的外部空间溢出效应,即邻近城市ρ(PM_(2. 5))每增加10百分点,将导致该地区ρ(PM_(2. 5))增长6. 12百分点. 300 km左右是保证PM_(2. 5)区域"联防联控"最佳效果的最大门槛距离,超过该门槛距离,区域"联防联控"的力度和效果会随着距离的增加而逐渐减弱;当门槛距离大于500 km时,ρ(PM_(2. 5))的空间自相关性不显著.气候变量中,RH和ρ(PM_(2. 5))呈同方向变化,而T、WS与ρ(PM_(2. 5))呈反方向变化.研究显示,关注单一地区或单一因素(气候或大气成分)均不能有效控制PM_(2. 5)污染,在保持经济稳定增长的前提下,各地治理PM_(2. 5)应从调整产业结构、优化能源结构、完善防控机制等多个维度共同推进,促使经济增长方式早日从"粗放型"向"集约型"转变.
In order to describe the influence of spatial characteristics,climate and atmospheric composition variables on ρ(PM_(2. 5)) in the air,this paper uses the ρ(PM_(2. 5)) in 74 Chinese cities to calculate the Moran' I index. An econometric analysis of the climate and atmospheric composition data of the 38 typical cities has been made. Based on the spatial weight matrix of gravity model,a SDM model of panel data has been constructed. The results indicate that ρ(PM_(10)),ρ(SO_2),ρ(CO),ρ(O_3) and relative humidity have positive correlations with the ρ(PM_(2. 5)) in the typical cities. However,wind speed and temperature have negative correlations with the ρ(PM_(2. 5)) in typical cities. ρ(PM_(10)),ρ(CO) and relative humidity are the key factors affecting the ρ(PM_(2. 5)),and the total effect of the three factors are 0. 7201,0. 2417,0. 1339,respectively; The ρ(PM_(2. 5)) in the geographically neighboring cities has a significant external space spillover effect,which means that an increase of 10% in the ρ(PM_(2. 5)) in neighboring cities will result in an increase of 6. 12% in theρ(PM_(2. 5)) in this area. The maximum threshold distance for PM_(2. 5) is about 300 km ‘joint prevention and control'. The strength and the‘joint prevention and control'effect will gradually become weaker and weaker as the growth in distance. When the threshold distance is longer than 500 km,the spatial autocorrelation of the ρ(PM_(2. 5)) is not significant. The research shows that focusing on single area or single factor (climate or atmospheric composition) cannot effectively control PM_(2. 5) pollution. With the sustainable development of economics,each city should focus on different perspectives to explore haze treatment plans,such as adjusting industrial structures,optimizing the energy structures and so on. These efforts will transform the mode of economic growth from‘extensive form'to ‘intensive mode'in the future.
In order to describe the influence of spatial characteristics,climate and atmospheric composition variables on ρ(PM_(2. 5)) in the air,this paper uses the ρ(PM_(2. 5)) in 74 Chinese cities to calculate the Moran' I index. An econometric analysis of the climate and atmospheric composition data of the 38 typical cities has been made. Based on the spatial weight matrix of gravity model,a SDM model of panel data has been constructed. The results indicate that ρ(PM_(10)),ρ(SO_2),ρ(CO),ρ(O_3) and relative humidity have positive correlations with the ρ(PM_(2. 5)) in the typical cities. However,wind speed and temperature have negative correlations with the ρ(PM_(2. 5)) in typical cities. ρ(PM_(10)),ρ(CO) and relative humidity are the key factors affecting the ρ(PM_(2. 5)),and the total effect of the three factors are 0. 7201,0. 2417,0. 1339,respectively; The ρ(PM_(2. 5)) in the geographically neighboring cities has a significant external space spillover effect,which means that an increase of 10% in the ρ(PM_(2. 5)) in neighboring cities will result in an increase of 6. 12% in theρ(PM_(2. 5)) in this area. The maximum threshold distance for PM_(2. 5) is about 300 km ‘joint prevention and control'. The strength and the‘joint prevention and control'effect will gradually become weaker and weaker as the growth in distance. When the threshold distance is longer than 500 km,the spatial autocorrelation of the ρ(PM_(2. 5)) is not significant. The research shows that focusing on single area or single factor (climate or atmospheric composition) cannot effectively control PM_(2. 5) pollution. With the sustainable development of economics,each city should focus on different perspectives to explore haze treatment plans,such as adjusting industrial structures,optimizing the energy structures and so on. These efforts will transform the mode of economic growth from‘extensive form'to ‘intensive mode'in the future.
引文
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[11]程兵芬,韩丽,程念亮,等.2014年10月太原市一次空气重污染过程分析[J].环境科学学报,2015,35(12):4071-4080.CHENG Bingfen,HAN Li,CHENG Nianliang,et al.Characteristics and formation mechanism of a serious pollution event in October2014 in Taiyuan[J].Acta Scientiae Circumstantiae,2015,35(12):4071-4080.
[12]ZHANG Yanyun,LANG Jianlei,CHENG Shuiyuan,et al.Chemical composition and sources of PM1,and PM2.5,in Beijing in autumn[J].Science of the Total Environment,2018,630:72-82.
[13]LANG Jianlei,ZHANG Yanyun,ZHOU Ying,et al.Trends of PM2.5and chemical composition in Beijing,2000-2015[J].Aerosol&Air Quality Research,2017,17(2):412-425.
[14]MUNIR S,HABEEBULLAH T M,MOHAMMED A M F,et al.Analysing PM2.5and its association with PM10and meteorology in the arid climate of Makkah,Saudi Arabia[J].Aerosol&Air Quality Research,2017,17(2):453-464.
[15]杨龙,贺克斌,张强,等.北京秋冬季近地层PM2.5质量浓度垂直分布特征[J].环境科学研究,2005,18(2):23-28.YANG Long,HE Kebin,ZHANG Qiang,et al.Vertical distributive characters of PM2.5at the ground layer in autumn and winter in Beijing[J].Research of Environmental Sciences,2005,18(2):23-28.
[16]DING Huifang,ZHANG Yunxia,SUN Hejiang,et al.Analysis of PM2.5distribution and transfer characteristics in a car cabin[J].Energy&Buildings,2016,127:252-258.
[17]FANIZZA C,BERARDIS B D,IETTO F,et al.Analysis of major pollutants and physico-chemical characteristics of PM2.5at an urban site in Rome[J].Science of the Total Environment,2018,616:1457-1468.
[18]HADLEY O L.Background PM2.5source apportionment in the remote northwestern United States[J].Atmospheric Environment,2017,167:298-308.
[19]MA Xiaoyan,WANG Jianying,YU Fangqun,et al.Can MODISAOD be employed to derive PM2.5in Beijing-Tianjin-Hebei over China?[J].Atmospheric Research,2016,181:250-256.
[20]RAO M,D'ELIA I,PIERSANTI A.An uncertainty quantification of PM2.5emissions from residential wood combustion in Italy[J].Atmospheric Pollution Research,2018,9(3):526-533.
[21]WANG Zhaojun,YU Zhiyi.PM2.5and ventilation in a passive residential building[J].Procedia Engineering,2017,205:3646-3653.
[22]ZHANG Chen,NI Zhiwei,NI Liping,et al.Asymmetric multifractal detrending moving average analysis in time series of PM2.5concentration[J].Physica A Statistical Mechanics&Its Applications,2016,457:322-330.
[23]周颖璇.基于灰色关联度分析法的PM2.5影响因素分析[J].管理观察,2014(15):14-16.
[24]厉伟,汪国懋,姜玲.PM2.5影响因素构成及其计量检验:以江苏省为例[J].统计与决策,2014(24):97-100.
[25]BIANCOFIORE F,BUSILACCHIO M,VERDECCHIA M,et al.Recursive neural network model for analysis and forecast of PM10and PM2.5[J].Atmospheric Pollution Research,2017,8(4):652-659.
[26]晏振,田茂再.基于分位回归的北京市PM2.5的影响分析[J].统计与决策,2015(17):103-105.
[27]JIN Qiang,FANG Xinyue,WEN Bo,et al.Spatio-temporal variations of PM2.5emission in China from 2005 to 2014[J].Chemosphere,2017,183:429-436.
[28]YAN Dan,LEI Yalin,SHI Yukun,et al.Evolution of the spatiotemporal pattern of PM2.5concentrations in China:a case study from the Beijing-Tianjin-Hebei Region[J].Atmospheric Environment,2018,183:225-233.
[29]CHRISTAKOS G,YANG Yong,WU Jiaping,et al.Improved spacetime mapping of PM2.5distribution using a domain transformation method[J].Ecological Indicators,2018,85:1273-1279.
[30]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.YANG Mian,WANG Yin.Spatial-temporal characteristics of PM2.5and its influencing factors in the Yangtze River Economic Belt[J].China Population,Resources and Environment,2017,27(1):91-100.
[31]周天墨,付强,诸云强,等.空间自相关方法及其在环境污染领域的应用分析[J].测绘通报,2013(1):53-56.ZHOU Tianmo,FU Qiang,ZHU Yunqiang,et al.Research on the application of spatial autocorrelation method in environmental pollution[J].Bulletin of Surveying and Mapping,2013(1):53-56.
[32]韩贵锋,徐建华,王维升,等.重庆市大气污染物的空间统计分析[J].环境科学研究,2006,19(5):30-35.HAN Guifeng,XU Jianhua,WANG Weisheng,et al.The spatial statistic analysis of air pollutants in Chongqing City[J].Research of Environmental Sciences,2006,19(5):30-35.
[33]罗畏,邹峥嵘.空间统计分析的环境质量评价应用[J].测绘科学,2012,37(4):32-34.LUO Wei,ZOU Zhengrong.Application of spatial statistical analysis in environmental quality assessment[J].Science of Surveying and Mapping,2012,37(4):32-34.
[34]TINBERGEN J,HEKSCHER A.Shaping the world economy:suggestions for an international economic policy[M].New York:Twentieth Century Fund,1962:126-144.
[2]FANG Die,WANG Qingeng,LI Huiming,et al.Mortality effects assessment of ambient PM2.5,pollution in the 74 leading cities of China[J].Science of the Total Environment,2016,S569570:1545-1552.
[3]ZHOU Zhihua,LIU Yurong,YUAN Jianjuan,et al.Indoor PM2.5concentrations in residential buildings during a severely polluted winter:a case study in Tianjin,China[J].Renewable&Sustainable Energy Reviews,2016,64:372-381.
[4]GUO Hong,CHENG Tianhai,GU Xingfa,et al.Assessment of PM2.5concentrations and exposure throughout China using ground observations[J].Science of the Total Environment,2017,601602:1024-1030.
[5]ZHOU Zhixiang,SHAO Tong,QIN Mengnan,et al.The effects of autophagy on vascular endothelial cells induced by airborne PM2.5[J].Journal of Environmental Sciences,2018,66:182-187.
[6]COX L A T.Effects of exposure estimation errors on estimated exposure-response relations for PM2.5[J].Environmental Research,2018,164:636-646.
[7]吴剑斌,王茜,伏晴艳.2013年12月上海市PM2.5重污染过程数值模拟研究[J].环境科学学报,2016,36(6):2152-2159.WU Jianbin,WANG Qian,FU Qingyan.Numerical simulation and process study of PM2.5pollution episode over Shanghai in December 2013[J].Acta Scientiae Circumstantiae,2016,36(6):2152-2159.
[8]魏薇,傅丽芳.基于改进高斯模型的哈尔滨市PM2.5扩散问题实证分析[J].数学的实践与认识,2014,44(22):205-211.WEI Wei,FU Lifang.An empirical study on the problem of diffusion based on the improved gauss model in Harbin City[J].Mathematics in Practice and Theory,2014,44(22):205-211.
[9]胡玉筱,段显明.基于高斯烟羽和多元线性回归模型的PM2.5扩散和预测研究[J].干旱区资源与环境,2015,29(6):86-92.HU Yuxiao,DUAN Xianming.PM2.5dispersion prediction based on gaussianplume model and multiple linear regression model[J].Journal of Arid Land Resources and Environment,2015,29(6):86-92.
[10]陈静锋,柴瑞瑞,闫浩,等.基于高斯烟羽模型的PM2.5污染源扩散规律模拟分析[J].系统工程,2015,23(9):153-158.CHEN Jingfeng,CHAI Ruirui,YAN Hao,et al.PM2.5pollution source diffusion law and simulation analysis based on the Gauss plume Model[J].Systems Engineering,2015,23(9):153-158.
[11]程兵芬,韩丽,程念亮,等.2014年10月太原市一次空气重污染过程分析[J].环境科学学报,2015,35(12):4071-4080.CHENG Bingfen,HAN Li,CHENG Nianliang,et al.Characteristics and formation mechanism of a serious pollution event in October2014 in Taiyuan[J].Acta Scientiae Circumstantiae,2015,35(12):4071-4080.
[12]ZHANG Yanyun,LANG Jianlei,CHENG Shuiyuan,et al.Chemical composition and sources of PM1,and PM2.5,in Beijing in autumn[J].Science of the Total Environment,2018,630:72-82.
[13]LANG Jianlei,ZHANG Yanyun,ZHOU Ying,et al.Trends of PM2.5and chemical composition in Beijing,2000-2015[J].Aerosol&Air Quality Research,2017,17(2):412-425.
[14]MUNIR S,HABEEBULLAH T M,MOHAMMED A M F,et al.Analysing PM2.5and its association with PM10and meteorology in the arid climate of Makkah,Saudi Arabia[J].Aerosol&Air Quality Research,2017,17(2):453-464.
[15]杨龙,贺克斌,张强,等.北京秋冬季近地层PM2.5质量浓度垂直分布特征[J].环境科学研究,2005,18(2):23-28.YANG Long,HE Kebin,ZHANG Qiang,et al.Vertical distributive characters of PM2.5at the ground layer in autumn and winter in Beijing[J].Research of Environmental Sciences,2005,18(2):23-28.
[16]DING Huifang,ZHANG Yunxia,SUN Hejiang,et al.Analysis of PM2.5distribution and transfer characteristics in a car cabin[J].Energy&Buildings,2016,127:252-258.
[17]FANIZZA C,BERARDIS B D,IETTO F,et al.Analysis of major pollutants and physico-chemical characteristics of PM2.5at an urban site in Rome[J].Science of the Total Environment,2018,616:1457-1468.
[18]HADLEY O L.Background PM2.5source apportionment in the remote northwestern United States[J].Atmospheric Environment,2017,167:298-308.
[19]MA Xiaoyan,WANG Jianying,YU Fangqun,et al.Can MODISAOD be employed to derive PM2.5in Beijing-Tianjin-Hebei over China?[J].Atmospheric Research,2016,181:250-256.
[20]RAO M,D'ELIA I,PIERSANTI A.An uncertainty quantification of PM2.5emissions from residential wood combustion in Italy[J].Atmospheric Pollution Research,2018,9(3):526-533.
[21]WANG Zhaojun,YU Zhiyi.PM2.5and ventilation in a passive residential building[J].Procedia Engineering,2017,205:3646-3653.
[22]ZHANG Chen,NI Zhiwei,NI Liping,et al.Asymmetric multifractal detrending moving average analysis in time series of PM2.5concentration[J].Physica A Statistical Mechanics&Its Applications,2016,457:322-330.
[23]周颖璇.基于灰色关联度分析法的PM2.5影响因素分析[J].管理观察,2014(15):14-16.
[24]厉伟,汪国懋,姜玲.PM2.5影响因素构成及其计量检验:以江苏省为例[J].统计与决策,2014(24):97-100.
[25]BIANCOFIORE F,BUSILACCHIO M,VERDECCHIA M,et al.Recursive neural network model for analysis and forecast of PM10and PM2.5[J].Atmospheric Pollution Research,2017,8(4):652-659.
[26]晏振,田茂再.基于分位回归的北京市PM2.5的影响分析[J].统计与决策,2015(17):103-105.
[27]JIN Qiang,FANG Xinyue,WEN Bo,et al.Spatio-temporal variations of PM2.5emission in China from 2005 to 2014[J].Chemosphere,2017,183:429-436.
[28]YAN Dan,LEI Yalin,SHI Yukun,et al.Evolution of the spatiotemporal pattern of PM2.5concentrations in China:a case study from the Beijing-Tianjin-Hebei Region[J].Atmospheric Environment,2018,183:225-233.
[29]CHRISTAKOS G,YANG Yong,WU Jiaping,et al.Improved spacetime mapping of PM2.5distribution using a domain transformation method[J].Ecological Indicators,2018,85:1273-1279.
[30]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.YANG Mian,WANG Yin.Spatial-temporal characteristics of PM2.5and its influencing factors in the Yangtze River Economic Belt[J].China Population,Resources and Environment,2017,27(1):91-100.
[31]周天墨,付强,诸云强,等.空间自相关方法及其在环境污染领域的应用分析[J].测绘通报,2013(1):53-56.ZHOU Tianmo,FU Qiang,ZHU Yunqiang,et al.Research on the application of spatial autocorrelation method in environmental pollution[J].Bulletin of Surveying and Mapping,2013(1):53-56.
[32]韩贵锋,徐建华,王维升,等.重庆市大气污染物的空间统计分析[J].环境科学研究,2006,19(5):30-35.HAN Guifeng,XU Jianhua,WANG Weisheng,et al.The spatial statistic analysis of air pollutants in Chongqing City[J].Research of Environmental Sciences,2006,19(5):30-35.
[33]罗畏,邹峥嵘.空间统计分析的环境质量评价应用[J].测绘科学,2012,37(4):32-34.LUO Wei,ZOU Zhengrong.Application of spatial statistical analysis in environmental quality assessment[J].Science of Surveying and Mapping,2012,37(4):32-34.
[34]TINBERGEN J,HEKSCHER A.Shaping the world economy:suggestions for an international economic policy[M].New York:Twentieth Century Fund,1962:126-144.