地理科学 ›› 2018, Vol. 38 ›› Issue (12): 2100-2108.doi: 10.13249/j.cnki.sgs.2018.12.019

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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

柏玲1,2(), 姜磊3(), 周海峰3, 陈忠升4   

  1. 1. 南昌大学中国中部经济社会发展研究中心,江西 南昌 330031
    2. 南昌大学经济管理学院, 江西 南昌 330031
    3. 浙江财经大学经济学院, 浙江 杭州 310018
    4. 西华师范大学国土资源学院, 四川 南充 637002
  • 收稿日期:2017-11-28 修回日期:2018-01-26 出版日期:2018-12-20 发布日期:2018-12-20
  • 作者简介:

    作者简介:柏玲(1987-), 女,河南新蔡人, 博士,讲师,研究方向为区域经济和生态经济。E-mail:lig@nwu.edu.cn

  • 基金资助:
    国家自然科学基金项目(41761021)、教育部人文社会科学青年基金项目(17YJC790061,18YJC790111)、江西省高校人文社会科学重点研究基地项目(JD17125)、浙江省自然科学基金项目(LY19G030013,LQ19D050001)资助

Spatio-temporal Characteristics of Air Quality Index and Its Driving Factors in the Yangtze River Economic Belt: An Empirical Study Based on Bayesian Spatial Econometric Model

Ling Bai1,2(), Lei Jiang3(), Haifeng Zhou3, Zhongsheng Chen4   

  1. 1. Research Center of the Central China Economic Development, Nanchang University, Nanchang 330031, Jiangxi, China
    2. School of Economics & Management, Nanchang University, Nanchang 330031, Jiangxi, China;
    3.School of Economics, Zhejiang University of Finance & Economics, Hangzhou 310018, Zhejiang, China;
    4.College of Land and Resources, China West Normal University, Nanchong 637002, Sichuan, China
  • Received:2017-11-28 Revised:2018-01-26 Online:2018-12-20 Published:2018-12-20
  • Supported by:
    National Natural Science Foundation of China (41761021), The Project of Humanities and Social Science Youth Fund of Ministry of Education (17YJC790061,18YJC790111), Key Research Base Project of Social Sciences and Humanities in Jiangxi Province (JD17125), Zhejiang Provincial Natural Science Foundation of China (LY19G030013, LQ19D050001).

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: 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。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。 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。

关键词: 长江经济带, 空气质量指数, 空间自相关, 热点分析, 贝叶斯空间计量模型

Abstract:

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.

Key words: Yangtze River Economic Belt, air quality index(AQI), spatial autocorrelation, hot spot analysis, Bayesian spatial econometric model

中图分类号: 

  • F205