长江经济带空气质量指数的时空特征及驱动因素分析——基于贝叶斯空间计量模型的实证
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摘要
基于2015年长江经济带126个城市空气质量监测数据,首先利用探索性空间数据分析方法揭示了空气质量指数(AQI)的时空演变特征,然后采用贝叶斯空间滞后模型探讨了长江经济带空气质量指数的社会经济驱动因素。研究结果表明:(1)长江经济带年AQI在空间上整体具有东高西低,长江以北高长江以南低的分布特点,具有明显的空间集聚特征。空气污染严重的热点地区主要集中长三角城市群的江苏省、浙北地区、皖北大部分地区以及上海市。空气质量较好的冷点地区则主要集中在云南省、四川的攀枝花以及贵州的大部分地区。(2)长江经济带AQI在季节上呈现冬春高、夏秋低的季节变化趋势。总体而言,四季的高值集聚主要分布在鄂皖苏,低值集聚主要分布在云贵地区。(3)贝叶斯空间滞后模型回归结果显示,长江经济带空气质量存在显著的空间溢出效应。此外,模型结果证实了"环境库兹涅兹曲线"假说;FDI回归系数为正,支持了"污染避难所"假说;人口密度、公路客运量均是导致空气污染加剧的重要因素,而第三产业比重和建成区绿化覆盖率增加有利于长江经济带空气质量的改善。
Based on a cross-sectional data at the city level in the Yangtze River Economic Belt, this paper firstly employs the exploratory spatial data analysis method to investigate the spatio-temporal variation characteristics of air quality index(AQI) of 126 cities in 2015, and then applies the Bayesian spatial econometric model to explore the socio-economic driving factors of air quality index of the Yangtze River Economic Belt. The findings are the following: 1) The distribution of the annual average AQI values in the Yangtze River Economic Belt exhibits a significant spatial cluster pattern, specifically high AQI values in the north and low AQI values in the south. Moreover, the hot spot analysis results show that the most polluted areas are mainly Jiangsu province,the northern Zhejiang province, Shanghai and the most areas of northern Anhui province while Yunnan province, Panzhihua city of Sichuan and the most areas of Guizhou province show better air quality. 2) Regarding the seasonal characteristics of AQI values in the Yangtze River Economic Belt, it also shows a typical seasonal characteristic, specifically, high AQI values in both winter and spring, and low AQI values in both summer and autumn. Overall, during the whole year high AQI values are mainly concentrated on Hubei province, Anhui province and Jiangsu province while low AQI values on Yunnan province. 3) The Bayesian spatial lag model indicates that the urban AQI values of the Yangtze River Economic Belt show significant spatial spillover effects. Moreover, the environmental Kuznets curve hypothesis has been verified, indicating that as GDP per capita increases, air quality worsens. However, when GDP per capita continues to increase, air quality becomes better. Besides, the coefficient of FDI variable is significant and positive, indicating the pollution haven hypothesis. Finally, the increase in population density and highway passenger transportation are important driving factors worsening air quality while the higher proportion of the tertiary industry and green coverage ratio improvements contribute to improving air quality of the Yangtze River Economic Belt.
Based on a cross-sectional data at the city level in the Yangtze River Economic Belt, this paper firstly employs the exploratory spatial data analysis method to investigate the spatio-temporal variation characteristics of air quality index(AQI) of 126 cities in 2015, and then applies the Bayesian spatial econometric model to explore the socio-economic driving factors of air quality index of the Yangtze River Economic Belt. The findings are the following: 1) The distribution of the annual average AQI values in the Yangtze River Economic Belt exhibits a significant spatial cluster pattern, specifically high AQI values in the north and low AQI values in the south. Moreover, the hot spot analysis results show that the most polluted areas are mainly Jiangsu province,the northern Zhejiang province, Shanghai and the most areas of northern Anhui province while Yunnan province, Panzhihua city of Sichuan and the most areas of Guizhou province show better air quality. 2) Regarding the seasonal characteristics of AQI values in the Yangtze River Economic Belt, it also shows a typical seasonal characteristic, specifically, high AQI values in both winter and spring, and low AQI values in both summer and autumn. Overall, during the whole year high AQI values are mainly concentrated on Hubei province, Anhui province and Jiangsu province while low AQI values on Yunnan province. 3) The Bayesian spatial lag model indicates that the urban AQI values of the Yangtze River Economic Belt show significant spatial spillover effects. Moreover, the environmental Kuznets curve hypothesis has been verified, indicating that as GDP per capita increases, air quality worsens. However, when GDP per capita continues to increase, air quality becomes better. Besides, the coefficient of FDI variable is significant and positive, indicating the pollution haven hypothesis. Finally, the increase in population density and highway passenger transportation are important driving factors worsening air quality while the higher proportion of the tertiary industry and green coverage ratio improvements contribute to improving air quality of the Yangtze River Economic Belt.
引文
[1]汪克亮,孟祥瑞,杨宝臣,等.基于环境压力的长江经济带工业生态效率研究[J].资源科学, 2015, 37(7):1491-1501.[Wang Keliang, Meng Xiangrui, Yang Baochen et al. The industrial eco-efficiency of the Yangtze River Economic Zone based on environmental pressure. Resources Science, 2015, 37(7):1491-1501.]
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[6]柏玲,姜磊,刘耀彬.长江中游城市群环境压力的时空特征——以工业SO2排放为例[J].经济地理, 2017, 37(3):174-181.[Bai Ling, Jiang Lei, Liu Yaobin. Spatio-temporal characteristics of environmental pressures of the urban agglomeration in the middle reaches of the Yangtze River—A case study based on Industrial SO2Emissions. Economic Geography, 2017, 37(3):174-181.]
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[10] Lin G, Fu J Y, Jiang D et al. Spatio-temporal variation of PM2.5concentrations and their relationship with geographic and socioeconomic factors in China[J]. International Journal of Environmental Research and Public Health, 2013, 11(1):173-186.
[11]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.[He Xiang, Lin Zhenshan, Liu Huiyu et al. Analysis of the driving factors of PM2.5in Jiangsu province based on grey correlation model. Acta Geographica Sinica, 2016, 71(7):1119-1129.]
[12]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.[Lin Xueqin,Wang Dai. Spatio-temporal variations and socio-economic driving forces of air quality in Chinese cities. Acta Geographica Sinica, 2016, 71(8):1357-1371.]
[13]姜磊,周海峰,柏玲,等.中国城市空气质量指数(AQI)的动态变化特征[J].经济地理, 2018, 38(9):87-95.[Jiang Lei, Zhou Haifeng, Bai Ling et al. The spatio-temporal variation of air quality index of cities in China. Economic Geography, 2018, 38(9):87-95.]
[14]肖悦,田永中,许文轩,等.中国城市大气污染特征及社会经济影响分析[J].生态环境学报, 2018, 27(3):518-526.[Xiao Yue, Tian Yongzhong, Xu Wenxuan et al. Study on spatiotemporal characteristics and socioeconomic driving factors of air pollution in China. Ecology and Environmental Sciences, 2018, 27(3):518-526.]
[15]熊洁,陈楠,操文祥,等.武汉市一次重霾天气AQI演变及气象因子特征分析[J].环境科学与技术, 2015, 38(12):183-187.[Xiong Jie, Chen Nan, Cao Wenxiang et al. Study on heavy smog days in Wuhan in terms of AQI index and characteristics of meteorological factors. Environmental Science Technology,2015, 38(12):183-187.]
[16]王景云,张红日,赵相伟,等. 2012-2015年北京市空气质量指数变化及其与气象要素的关系[J].气象与环境科学, 2017,40(4):35-41.[Wang Jingyun, Zhang Hongri, Zhao Xiangwei et al. Variation of air quality index and its relationship with meteorological elements in Beijing from 2012 to 2015. Meteorological and Environmental Sciences, 2017, 40(4):35-41.]
[17]康恒元,刘玉莲,李涛.黑龙江省重点城市AQI指数特征及其与气象要素之关系[J].自然资源学报, 2017,32(4):692-703.[Kang Hengyuan, Liu Yulian, Li Tao. Characteristics of air quality index and its relationship with meteorological factors in key cities of Heilongjiang Province. Journal of Natural Resources,2017, 32(4):692-703.]
[18]刘满凤,谢晗进.基于空气质量指数AQI的污染集聚空间异质性分析[J].经济地理,2016,36(8):166-175.[Liu Manfeng,Xie Hanjin. The spatial heterogeneity analysis of pollution agglomeration based on the AQI. Economic Geography, 2016, 36(8):166-175.]
[19] Liu H M, Fang C L, Zhang X L et al. The effect of natural and anthropogenic factors on haze pollution in Chinese cities:A spatial econometrics approach[J]. Journal of Cleaner Production,2017, 165:323-333.
[20] Jiang L, Zhou H F, Bai L et al. Does foreign direct investment drive environmental degradation in China? An empirical study based on air quality index from a spatial perspective[J]. Journal of Cleaner Production, 2018, 176:864-872.
[21] Zhan D S, Kwan M P, Zhang W Z et al. The driving factors of air quality index in China[J]. Journal of Cleaner Production,2018, 197:1342-1351.
[22] Huang W Y, Wang H W, Wei Y G. Endogenous or exogenous?examining trans-boundary air pollution by using the Air Quality Index(AQI):A case study of 30 provinces and autonomous regions in China[J]. Sustainability, 2018, 10(11):4200-4220.
[23]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. China Population, Resources and Environment, 2017, 27(1):91-100.]
[24]中国环境保护部.环境空气质量指数(AQI)技术规定(试行)[Z].2012.[China Environmental Protection Department. Technical regulation on ambient Air Quality Index(on trial).2012.]
[25] Moran P P. Notes on continuous stochastic phenomena[J].Biometrika, 1950, 37(1/2):17-23.
[26] Cliff A D, Ord J K. Spatial processes:Models&applications[M].London:Pion, 1981.
[27]熊欢欢,梁龙武,曾赠,等.中国城市PM2.5时空分布的动态比较分析[J].资源科学, 2017, 39(1):136-146.[Xiong Huanhuan,Liang Longwu, Zeng Zeng et al. Dynamic analysis of PM2.5spatial-temporal characteristics in China. Resources Science, 2017,39(1):136-146.]
[28]姜磊,周海峰,柏玲.外商直接投资对空气污染影响的空间异质性分析——以中国150个城市空气质量指数(AQI)为例[J].地理科学, 2018, 38(3):351-360.[Jiang Lei, Zhou Haifeng, Bai Ling. Spatial heterogeneity analysis of impacts of foreign direct investment on air pollution:Empirical evidence from 150 cities in China based on AQI. Scientia Geographica Sinica, 2018, 38(3):351-360.]
[29]姜磊,周海峰,柏玲,等.空气质量指数(AQI)的社会经济影响因素分析——基于指数衰减效应视角[J].环境科学学报,2018, 38(1):390-398.[Jiang Lei, Zhou Haifeng, Bai Ling et al.The analysis of socio-economic factors of air quality index(AQI)based on the perspective of the exponential decay effects. Acta Scientiae Circumstantiae, 2018, 38(1):390-398.]
[30]方丽婷.空间滞后模型的贝叶斯估计[J].统计研究, 2014, 31(5):102-106.[Fang Liting. Bayesian estimation of the spatial lag model. Statistical Research, 2014, 31(5):102-106.]
[31]中华人民共和国国家统计局.中国城市统计年鉴[M].北京:中国统计出版社, 2016.[National Bureau of Statistics of the People’s Republic of China. China city statistical yearbook.Beijing:China Statistics Press, 2016.]
[32]邵帅,李欣,曹建华,等.中国雾霾污染治理的经济政策选择——基于空间溢出效应的视角[J].经济研究, 2016(9):73-88.[Shao Shuai, Li Xin, Cao Jianhua et al. China’s economic policy choices for governing smog pollution based on spatial spillover effects. Economic Research Journal, 2016(9):73-88.]
[33] Grossman G, Krueger A. Economic environment and the economic growth[J].Quarterly journal of economics,1995, 110(2):353-377.
[2] Song M, Wang S, Yu H et al. To reduce energy consumption and to maintain rapid economic growth:Analysis of the condition in China based on expended IPAT model[J]. Renewable and Sustainable Energy Reviews, 2011, 15(9):5129-5134.
[3]郑晓霞,李令军,赵文吉,等.京津冀地区大气NO2污染特征研究[J].生态环境学报, 2014(12):1938-1945.[Zheng Xiaoxia,Li Lingjun, Zhao Wenji et al. Spatial and temporal characteristics of atmospheric NO2in the Beijing-Tianjin-Hebei region.Ecology and Environment Sciences, 2014(12):1938-1945.]
[4]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.[Wang Zhenbo, Fang Chuanglin, Xu Guang et al. Spatial-temporal characteristics of the PM2.5in China in 2014. Acta Geographica Sinica, 2015, 70(11):1720-1734.]
[5]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 Mingsheng,Ren Xiaoxia, Yu Yang et al. Spatiotemporal pattern of groundlevel fine particulate matter(PM2.5)pollution in mainland China. China Environmental Science, 2016, 36(3):641-650.]
[6]柏玲,姜磊,刘耀彬.长江中游城市群环境压力的时空特征——以工业SO2排放为例[J].经济地理, 2017, 37(3):174-181.[Bai Ling, Jiang Lei, Liu Yaobin. Spatio-temporal characteristics of environmental pressures of the urban agglomeration in the middle reaches of the Yangtze River—A case study based on Industrial SO2Emissions. Economic Geography, 2017, 37(3):174-181.]
[7] Shaltout A A, Boman J, Al-Malawi D. Elemental composition of PM2.5particles sampled in industrial and residential areas of Taif, Saudi Arabia[J]. Aerosol and Air Quality Research, 2013,13(4):1356-1364.
[8]郑玫,张延君,闫才青,等.上海PM2.5工业源谱的建立[J].中国环境科学, 2013, 33(8):1354-1359.[Zheng Mei, Zhang Yanjun, Yan Caiqing et al. Establishing PM2.5industrial source profiles in Shanghai. China Environmental Science, 2013, 33(8):1354-1359.]
[9] Shen X J, Sun J Y, Zhang X Y et al. Characterization of submicron aerosols and effect on visibility during a severe haze-fog episode in Yangtze River Delta,China[J]. Atmospheric Environment, 2015, 120:307-316.
[10] Lin G, Fu J Y, Jiang D et al. Spatio-temporal variation of PM2.5concentrations and their relationship with geographic and socioeconomic factors in China[J]. International Journal of Environmental Research and Public Health, 2013, 11(1):173-186.
[11]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.[He Xiang, Lin Zhenshan, Liu Huiyu et al. Analysis of the driving factors of PM2.5in Jiangsu province based on grey correlation model. Acta Geographica Sinica, 2016, 71(7):1119-1129.]
[12]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.[Lin Xueqin,Wang Dai. Spatio-temporal variations and socio-economic driving forces of air quality in Chinese cities. Acta Geographica Sinica, 2016, 71(8):1357-1371.]
[13]姜磊,周海峰,柏玲,等.中国城市空气质量指数(AQI)的动态变化特征[J].经济地理, 2018, 38(9):87-95.[Jiang Lei, Zhou Haifeng, Bai Ling et al. The spatio-temporal variation of air quality index of cities in China. Economic Geography, 2018, 38(9):87-95.]
[14]肖悦,田永中,许文轩,等.中国城市大气污染特征及社会经济影响分析[J].生态环境学报, 2018, 27(3):518-526.[Xiao Yue, Tian Yongzhong, Xu Wenxuan et al. Study on spatiotemporal characteristics and socioeconomic driving factors of air pollution in China. Ecology and Environmental Sciences, 2018, 27(3):518-526.]
[15]熊洁,陈楠,操文祥,等.武汉市一次重霾天气AQI演变及气象因子特征分析[J].环境科学与技术, 2015, 38(12):183-187.[Xiong Jie, Chen Nan, Cao Wenxiang et al. Study on heavy smog days in Wuhan in terms of AQI index and characteristics of meteorological factors. Environmental Science Technology,2015, 38(12):183-187.]
[16]王景云,张红日,赵相伟,等. 2012-2015年北京市空气质量指数变化及其与气象要素的关系[J].气象与环境科学, 2017,40(4):35-41.[Wang Jingyun, Zhang Hongri, Zhao Xiangwei et al. Variation of air quality index and its relationship with meteorological elements in Beijing from 2012 to 2015. Meteorological and Environmental Sciences, 2017, 40(4):35-41.]
[17]康恒元,刘玉莲,李涛.黑龙江省重点城市AQI指数特征及其与气象要素之关系[J].自然资源学报, 2017,32(4):692-703.[Kang Hengyuan, Liu Yulian, Li Tao. Characteristics of air quality index and its relationship with meteorological factors in key cities of Heilongjiang Province. Journal of Natural Resources,2017, 32(4):692-703.]
[18]刘满凤,谢晗进.基于空气质量指数AQI的污染集聚空间异质性分析[J].经济地理,2016,36(8):166-175.[Liu Manfeng,Xie Hanjin. The spatial heterogeneity analysis of pollution agglomeration based on the AQI. Economic Geography, 2016, 36(8):166-175.]
[19] Liu H M, Fang C L, Zhang X L et al. The effect of natural and anthropogenic factors on haze pollution in Chinese cities:A spatial econometrics approach[J]. Journal of Cleaner Production,2017, 165:323-333.
[20] Jiang L, Zhou H F, Bai L et al. Does foreign direct investment drive environmental degradation in China? An empirical study based on air quality index from a spatial perspective[J]. Journal of Cleaner Production, 2018, 176:864-872.
[21] Zhan D S, Kwan M P, Zhang W Z et al. The driving factors of air quality index in China[J]. Journal of Cleaner Production,2018, 197:1342-1351.
[22] Huang W Y, Wang H W, Wei Y G. Endogenous or exogenous?examining trans-boundary air pollution by using the Air Quality Index(AQI):A case study of 30 provinces and autonomous regions in China[J]. Sustainability, 2018, 10(11):4200-4220.
[23]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. China Population, Resources and Environment, 2017, 27(1):91-100.]
[24]中国环境保护部.环境空气质量指数(AQI)技术规定(试行)[Z].2012.[China Environmental Protection Department. Technical regulation on ambient Air Quality Index(on trial).2012.]
[25] Moran P P. Notes on continuous stochastic phenomena[J].Biometrika, 1950, 37(1/2):17-23.
[26] Cliff A D, Ord J K. Spatial processes:Models&applications[M].London:Pion, 1981.
[27]熊欢欢,梁龙武,曾赠,等.中国城市PM2.5时空分布的动态比较分析[J].资源科学, 2017, 39(1):136-146.[Xiong Huanhuan,Liang Longwu, Zeng Zeng et al. Dynamic analysis of PM2.5spatial-temporal characteristics in China. Resources Science, 2017,39(1):136-146.]
[28]姜磊,周海峰,柏玲.外商直接投资对空气污染影响的空间异质性分析——以中国150个城市空气质量指数(AQI)为例[J].地理科学, 2018, 38(3):351-360.[Jiang Lei, Zhou Haifeng, Bai Ling. Spatial heterogeneity analysis of impacts of foreign direct investment on air pollution:Empirical evidence from 150 cities in China based on AQI. Scientia Geographica Sinica, 2018, 38(3):351-360.]
[29]姜磊,周海峰,柏玲,等.空气质量指数(AQI)的社会经济影响因素分析——基于指数衰减效应视角[J].环境科学学报,2018, 38(1):390-398.[Jiang Lei, Zhou Haifeng, Bai Ling et al.The analysis of socio-economic factors of air quality index(AQI)based on the perspective of the exponential decay effects. Acta Scientiae Circumstantiae, 2018, 38(1):390-398.]
[30]方丽婷.空间滞后模型的贝叶斯估计[J].统计研究, 2014, 31(5):102-106.[Fang Liting. Bayesian estimation of the spatial lag model. Statistical Research, 2014, 31(5):102-106.]
[31]中华人民共和国国家统计局.中国城市统计年鉴[M].北京:中国统计出版社, 2016.[National Bureau of Statistics of the People’s Republic of China. China city statistical yearbook.Beijing:China Statistics Press, 2016.]
[32]邵帅,李欣,曹建华,等.中国雾霾污染治理的经济政策选择——基于空间溢出效应的视角[J].经济研究, 2016(9):73-88.[Shao Shuai, Li Xin, Cao Jianhua et al. China’s economic policy choices for governing smog pollution based on spatial spillover effects. Economic Research Journal, 2016(9):73-88.]
[33] Grossman G, Krueger A. Economic environment and the economic growth[J].Quarterly journal of economics,1995, 110(2):353-377.