2001～2015年中国城镇化与PM_(2.5)浓度时空关联特征
|
摘要
综合运用时空统计、剪刀差、地理加权回归等手段分5个阶段从人口、土地、经济角度研究了2001～2015年中国大陆地区城镇化水平与PM_(2.5)浓度的时空分布以及相互关联特征.结果表明:2001～2015年,我国3a均人口、土地、经济城镇化水平平均值稳步提高,PM_(2.5)浓度波动上升(44.14～50.89μg/m~3),不同经济区之间时序变化趋势相似但强度存在差异.不同阶段PM_(2.5)浓度空间分布趋势基本一致,京津冀、河南与山东北部、新疆西部等地区始终为高值区,3类城镇化水平高值区域逐步扩大.城镇化水平的时序变化趋势与PM_(2.5)浓度随时间变化的趋势存在差异(切线夹角:15.33°～62.92°),难以解释PM_(2.5)浓度在时间上的突变.城镇化水平与PM_(2.5)浓度空间分布关联特征显著,土地城镇化水平与PM_(2.5)浓度在0.01水平上正相关,其相关系数依次为东北(0.609～0.723)>中部(0.572～0.631)>东部(0.218～0.323)>西部(0.079～0.255),除中、西部地区外,经济城镇化水平对PM_(2.5)浓度正效应明显,东北地区人口城镇化水平与PM_(2.5)浓度负相关,GWR模型调整R~2在2001～2003年阶段最高(0.6～0.77),2013～2015年阶段最低(0.08～0.64).
This study analyzed the spatial and temporal variations of PM_(2.5) concentration and the degrees of urbanization for the five periods of 2001～2003, 2004～2006, 2007～2009, 2010～2012, and 2013～2015 in Mainland China, on perspectives of population, land and economy. Scissors difference method, correlation analysis and geographically weighted regression(GWR) model were employed to explore their relationships. Results showed that the three-year average degrees of urbanization for population, land and economy increased steadilyand PM_(2.5) concentration fluctuated in an increase direction(44.14～50.89μg/m~3). However, rates of these variations were different between four economic regions. Spatial distributions of PM_(2.5) concentrations were similar for the five periods, they were high in Beijing-Tianjin-Hebei(BTH) area, north Henan and Shandong province, and west Xinjiang. The area with high urbanization degree increased gradually. Angles(15.33°～62.92°) between the two tangent lines of temporal variation curves of degree of urbanization and PM_(2.5) concentrations based on scissors difference method revealed the insignificant relationships between them temporally. In addition, significant association was found between the spatial distributions of PM_(2.5) concentrations and the degrees of urbanization. The degrees of urbanization for land were positively correlated with PM_(2.5) concentrations at the 0.01 level. The sequence of correlation coefficients from high to low was Northeast(0.609～0.723)>Midlands(0.572～0.631)>East(0.218～0.323) >West(0.079～0.255). Except for Midlands and West, the degrees of urbanization for economy had significantly positive effect on PM_(2.5) concentrations, while those for population were negatively associated with PM_(2.5) concentrations in Eastern area. The results for GWR models further demonstrated this varied spatial association with adjusted R2 were found to be the highest in 2001～2003 period(0.6～0.77) and the lowest in 2013～2015 period(0.08～0.64).
This study analyzed the spatial and temporal variations of PM_(2.5) concentration and the degrees of urbanization for the five periods of 2001～2003, 2004～2006, 2007～2009, 2010～2012, and 2013～2015 in Mainland China, on perspectives of population, land and economy. Scissors difference method, correlation analysis and geographically weighted regression(GWR) model were employed to explore their relationships. Results showed that the three-year average degrees of urbanization for population, land and economy increased steadilyand PM_(2.5) concentration fluctuated in an increase direction(44.14～50.89μg/m~3). However, rates of these variations were different between four economic regions. Spatial distributions of PM_(2.5) concentrations were similar for the five periods, they were high in Beijing-Tianjin-Hebei(BTH) area, north Henan and Shandong province, and west Xinjiang. The area with high urbanization degree increased gradually. Angles(15.33°～62.92°) between the two tangent lines of temporal variation curves of degree of urbanization and PM_(2.5) concentrations based on scissors difference method revealed the insignificant relationships between them temporally. In addition, significant association was found between the spatial distributions of PM_(2.5) concentrations and the degrees of urbanization. The degrees of urbanization for land were positively correlated with PM_(2.5) concentrations at the 0.01 level. The sequence of correlation coefficients from high to low was Northeast(0.609～0.723)>Midlands(0.572～0.631)>East(0.218～0.323) >West(0.079～0.255). Except for Midlands and West, the degrees of urbanization for economy had significantly positive effect on PM_(2.5) concentrations, while those for population were negatively associated with PM_(2.5) concentrations in Eastern area. The results for GWR models further demonstrated this varied spatial association with adjusted R2 were found to be the highest in 2001～2003 period(0.6～0.77) and the lowest in 2013～2015 period(0.08～0.64).
引文
[1]严翔,成长春,贾亦真.中国城镇化进程中产业、空间、人口对能源消费的影响分解[J].资源科学,2018,40(1):216-225.Yan X,Cheng C C,Jia Y Z.Effect decomposition of industry,space and population on energy consumption during Chineseurbanization[J].Resources Science,2018,40(1):216-225.
[2]童抗抗,马克明.居住-就业距离对交通碳排放的影响[J].生态学报,2012,32(10):2975-2984.Tong K K,Ma K M.Significant impact of job-housing distance on carbon emissions from transport:a scenario analysis[J].Acta Ecologica Sinica,2012,32(10):2975-2984.
[3]Song C,He J,Wu L,et al.Health burden attributable to ambient PM2.5in China[J].Environmental Pollution,2017,223:575-586.
[4]Pui D Y H,Chen S C,Zuo Z.PM2.5,in China:Measurements,sources,visibility and health effects,and mitigation[J].Particuology,2014,13(2):1-26.
[5]Zou B,Wilson J G,Zhan F B,et al.Air pollution exposure assessment methods utilized in epidemiological studies[J].Journal of Environmental Monitoring Jem,2009,11(3):475-490.
[6]Fang X,Zou B,Liu X,et al.Satellite-based ground PM2.5,estimation using timely structure adaptive modeling[J].Remote Sensing of Environment,2016,186:152-163.
[7]Eeftens M,Tsai M Y,Ampe C,et al.Variation of PM2.5,PM10,PM2.5absorbance and PM coarse concentrations between and within 20European study areas-results of the ESCAPE project[J].Atmospheric Environment,2012,62(12):303-317.
[8]李名升,任晓霞,于洋,等.中国大陆城市PM2.5污染时空分布规律[J].中国环境科学,2016,36(3):641-650.Li M S,Ren X X,Yu Y,et al.Spatiotemporal pattern of ground-level fine particulate matter(PM2.5)pollution in mainland China[J].China Environmental Sciences,2016,36(3):641-650.
[9]Vouitsis I,Ntziachristos L,Samaras C,et al.Particulate mass and number emission factors for road vehicles based on literature data and relevant gap filling methods[J].Atmospheric Environment,2017,168:75-89.
[10]周亮,周成虎,杨帆,等.2000~2011年中国PM2.5时空演化特征及驱动因素解析[J].地理学报,2017,72(11):2079-2092.Zhou L,Zhou C H,Yang F,et al.Spatio-temporal evolution and the influencing factorsof PM2.5 in China between 2000 and 2011[J].Acta Geographica Sinica,2017,72(11):2079-2092.
[11]邹滨,许珊,张静.土地利用视角空气污染空间分异的地理分析[J].武汉大学学报(信息科学版),2017,42(2):216-222.Zou B,Xu S,Zhang J.Spatial Variation Analysis of Urban Air Pollution Using GIS:A Land Use Perspective[J].Geomatics&Information Science of Wuhan University,2017,42(2):216-222.
[12]Guo J,Xia F,Zhang Y,et al.Impact of diurnal variability and meteorological factors on the PM2.5-AOD relationship:Implications for PM2.5 remote sensing[J].Environmental Pollution,2017,221:94-104.
[13]Feng H,Zou B,Tang Y.Scale-and region-dependence in landscapePM2.5 correlation:implications for urban planning[J].Remote Sensing,2017,9(918):1-20.
[14]贾梦唯,赵天良,张祥志,等.南京主要大气污染物季节变化及相关气象分析[J].中国环境科学,2016,36(9):2567-2577.Jia W M,Zhao T L,Zhang X Z,et al.Seasonal variations in major air pollutants in Nanjing and their meteorological correlation analyses.[J].China Environmental Sciences,2016,36(9):2567-2577.
[15]Baxter L K,Burke J,Lunden M,et al.Influence of human activity patterns,particle composition,and residential air exchange rates on modeled distributions of PM2.5 exposure compared with central-site monitoring data[J].Journal of Exposure Science&Environmental Epidemiology,2013,23:241-247.
[16]陶双成,邓顺熙,高硕晗,等.北京采暖期典型区域环境空气污染特征分析[J].生态环境学报,2016,25(11):1741-1747.Tao S C,Deng S X,Gao S H,et al.Characteristics of air pollution in typicalregions of Beijing during heating season[J].Ecology and Environmental Sciences,2016,25(11):1741-1747.
[17]Zhou C,Chen J,Wang S.Examining the effects of socioeconomic development on fine particulate matter(PM2.5)in China's cities using spatial regression and the geographical detector technique[J].Science of the Total Environment,2018,619:436-445.
[18]Milojevic A,Niedzwiedz C L,Pearce J,et al.Socioeconomic and urban-rural differentials in exposure to air pollution and mortality burden in England[J].Environmental Health,2017,16(104):1-10.
[19]蔺雪芹,王岱.中国城市空气质量时空演化特征及社会经济驱动力[J].地理学报,2016,71(8):1357-1371.Ning X Q,Wang D.Spatio-temporal variations and socio-economic drivingforces of air quality in Chinese cities[J].Acta Geographica Sinica,2016,71(8):1357-1371.
[20]Van Donkelaar A,Martin R V,Brauer M,et al.Global estimates of fine particulate matter using a combined geophysical-statistical method with information from satellites[J].Environmental Science&Technology,2016,50(7):3762-3772.
[21]Huang B,Wu B,Barry M.Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices[J].International Journal of Geographical Information Science,2010,24(3):383-401.
[22]中国统计信息网[EB/OL].http://www.tjcn.org/,2018-05-31/2018-06-12.Statistics information of China[EB/OL].http://www.tjcn.org/,2018-05-31/2018-06-12.
[23]地理国情监测云平台[EB/OL].http://www.dsac.cn/,2016-06-21/2018-06-12.Geographical Information Monitoring Cloud Platform[EB/OL].http://www.dsac.cn/,2016-06-21/2018-06-12.
[24]盖美,连冬,耿雅冬.辽宁省经济与生态环境系统耦合发展分析[J].地域研究与开发,2013,32(5):88-94.Gai M,Lian D,Gen Y D.Coupling Analysis between Economicand Ecological Environment System in Liaoning Province[J].Areal Research and Development,2013,32(5):88-94.
[25]Rodgers J L,Nicewander W A.thirteen ways to look at the correlation coefficient[J].The American Statistician,1988,42(1):59-66.
[26]Zou B,Pu Q,Bilal M,et al.High-resolution satellite mapping of fine particulates based on geographically weighted regression[J].IEEEGeoscience&Remote Sensing Letters,2017,13(4):495-499.
[2]童抗抗,马克明.居住-就业距离对交通碳排放的影响[J].生态学报,2012,32(10):2975-2984.Tong K K,Ma K M.Significant impact of job-housing distance on carbon emissions from transport:a scenario analysis[J].Acta Ecologica Sinica,2012,32(10):2975-2984.
[3]Song C,He J,Wu L,et al.Health burden attributable to ambient PM2.5in China[J].Environmental Pollution,2017,223:575-586.
[4]Pui D Y H,Chen S C,Zuo Z.PM2.5,in China:Measurements,sources,visibility and health effects,and mitigation[J].Particuology,2014,13(2):1-26.
[5]Zou B,Wilson J G,Zhan F B,et al.Air pollution exposure assessment methods utilized in epidemiological studies[J].Journal of Environmental Monitoring Jem,2009,11(3):475-490.
[6]Fang X,Zou B,Liu X,et al.Satellite-based ground PM2.5,estimation using timely structure adaptive modeling[J].Remote Sensing of Environment,2016,186:152-163.
[7]Eeftens M,Tsai M Y,Ampe C,et al.Variation of PM2.5,PM10,PM2.5absorbance and PM coarse concentrations between and within 20European study areas-results of the ESCAPE project[J].Atmospheric Environment,2012,62(12):303-317.
[8]李名升,任晓霞,于洋,等.中国大陆城市PM2.5污染时空分布规律[J].中国环境科学,2016,36(3):641-650.Li M S,Ren X X,Yu Y,et al.Spatiotemporal pattern of ground-level fine particulate matter(PM2.5)pollution in mainland China[J].China Environmental Sciences,2016,36(3):641-650.
[9]Vouitsis I,Ntziachristos L,Samaras C,et al.Particulate mass and number emission factors for road vehicles based on literature data and relevant gap filling methods[J].Atmospheric Environment,2017,168:75-89.
[10]周亮,周成虎,杨帆,等.2000~2011年中国PM2.5时空演化特征及驱动因素解析[J].地理学报,2017,72(11):2079-2092.Zhou L,Zhou C H,Yang F,et al.Spatio-temporal evolution and the influencing factorsof PM2.5 in China between 2000 and 2011[J].Acta Geographica Sinica,2017,72(11):2079-2092.
[11]邹滨,许珊,张静.土地利用视角空气污染空间分异的地理分析[J].武汉大学学报(信息科学版),2017,42(2):216-222.Zou B,Xu S,Zhang J.Spatial Variation Analysis of Urban Air Pollution Using GIS:A Land Use Perspective[J].Geomatics&Information Science of Wuhan University,2017,42(2):216-222.
[12]Guo J,Xia F,Zhang Y,et al.Impact of diurnal variability and meteorological factors on the PM2.5-AOD relationship:Implications for PM2.5 remote sensing[J].Environmental Pollution,2017,221:94-104.
[13]Feng H,Zou B,Tang Y.Scale-and region-dependence in landscapePM2.5 correlation:implications for urban planning[J].Remote Sensing,2017,9(918):1-20.
[14]贾梦唯,赵天良,张祥志,等.南京主要大气污染物季节变化及相关气象分析[J].中国环境科学,2016,36(9):2567-2577.Jia W M,Zhao T L,Zhang X Z,et al.Seasonal variations in major air pollutants in Nanjing and their meteorological correlation analyses.[J].China Environmental Sciences,2016,36(9):2567-2577.
[15]Baxter L K,Burke J,Lunden M,et al.Influence of human activity patterns,particle composition,and residential air exchange rates on modeled distributions of PM2.5 exposure compared with central-site monitoring data[J].Journal of Exposure Science&Environmental Epidemiology,2013,23:241-247.
[16]陶双成,邓顺熙,高硕晗,等.北京采暖期典型区域环境空气污染特征分析[J].生态环境学报,2016,25(11):1741-1747.Tao S C,Deng S X,Gao S H,et al.Characteristics of air pollution in typicalregions of Beijing during heating season[J].Ecology and Environmental Sciences,2016,25(11):1741-1747.
[17]Zhou C,Chen J,Wang S.Examining the effects of socioeconomic development on fine particulate matter(PM2.5)in China's cities using spatial regression and the geographical detector technique[J].Science of the Total Environment,2018,619:436-445.
[18]Milojevic A,Niedzwiedz C L,Pearce J,et al.Socioeconomic and urban-rural differentials in exposure to air pollution and mortality burden in England[J].Environmental Health,2017,16(104):1-10.
[19]蔺雪芹,王岱.中国城市空气质量时空演化特征及社会经济驱动力[J].地理学报,2016,71(8):1357-1371.Ning X Q,Wang D.Spatio-temporal variations and socio-economic drivingforces of air quality in Chinese cities[J].Acta Geographica Sinica,2016,71(8):1357-1371.
[20]Van Donkelaar A,Martin R V,Brauer M,et al.Global estimates of fine particulate matter using a combined geophysical-statistical method with information from satellites[J].Environmental Science&Technology,2016,50(7):3762-3772.
[21]Huang B,Wu B,Barry M.Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices[J].International Journal of Geographical Information Science,2010,24(3):383-401.
[22]中国统计信息网[EB/OL].http://www.tjcn.org/,2018-05-31/2018-06-12.Statistics information of China[EB/OL].http://www.tjcn.org/,2018-05-31/2018-06-12.
[23]地理国情监测云平台[EB/OL].http://www.dsac.cn/,2016-06-21/2018-06-12.Geographical Information Monitoring Cloud Platform[EB/OL].http://www.dsac.cn/,2016-06-21/2018-06-12.
[24]盖美,连冬,耿雅冬.辽宁省经济与生态环境系统耦合发展分析[J].地域研究与开发,2013,32(5):88-94.Gai M,Lian D,Gen Y D.Coupling Analysis between Economicand Ecological Environment System in Liaoning Province[J].Areal Research and Development,2013,32(5):88-94.
[25]Rodgers J L,Nicewander W A.thirteen ways to look at the correlation coefficient[J].The American Statistician,1988,42(1):59-66.
[26]Zou B,Pu Q,Bilal M,et al.High-resolution satellite mapping of fine particulates based on geographically weighted regression[J].IEEEGeoscience&Remote Sensing Letters,2017,13(4):495-499.