地理科学 ›› 2021, Vol. 41 ›› Issue (10): 1852-1861.doi: 10.13249/j.cnki.sgs.2021.10.017

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黄河流域空气污染的空间格局演化及影响因素

滕堂伟(), 谌丹华, 胡森林()   

  1. 华东师范大学中国现代城市研究中心/华东师范大学城市与区域科学学院,上海 200062
  • 收稿日期:2020-10-09 修回日期:2021-01-20 出版日期:2021-10-25 发布日期:2021-12-08
  • 通讯作者: 胡森林 E-mail:twteng@re.ecnu.edu.cn;hsllh520@163.com
  • 作者简介:滕堂伟(1973−),男,山东莒南人,博士,教授,主要从事区域创新与区域发展模式研究。E-mail: twteng@re.ecnu.edu.cn
  • 基金资助:
    国家社会科学基金(19ZDA087);华东师范大学优秀博士生学术创新能力提升计划(YBNLTS2020-021)

Spatial Evolution and Influencing Factors of Spatial Agglomeration Pattern of Air Pollution in the Yellow River Basin

Teng Tangwei(), Chen Danhua, Hu Senlin()   

  1. The Center for Modern Chinese City Studies/School of Urban and Regional Science, East China Normal University, Shanghai 200062, China
  • Received:2020-10-09 Revised:2021-01-20 Online:2021-10-25 Published:2021-12-08
  • Contact: Hu Senlin E-mail:twteng@re.ecnu.edu.cn;hsllh520@163.com
  • Supported by:
    National Social Science Foundation of China(19ZDA087);East China Normal University Academic Innovation Promotion Program for Excellent Doctoral Students(YBNLTS2020-021)

摘要:

基于2008—2017年黄河流域工业SO2和PM2.5两类典型空气污染物数据,首先刻画了两者的空间演化格局,并运用空间面板杜宾模型(SPDM)从直接效应和间接效应两方面对两者的影响因素进行对比分析。结果表明:① 工业SO2和PM2.5污染均存在显著的空间集聚特征,从东南至西北方向呈现梯度递减趋势;二者在城市尺度均存在显著的正向空间关联性,但PM2.5污染的空间关联性比工业SO2更强;② 2008—2017年,工业SO2和PM2.5污染有所缓解,其中工业SO2排放强度迅速下降;而PM2.5质量浓度下降相对缓慢,仍是黄河流域主要的空气污染源。③ 产业结构、技术创新、能源效率、人口规模、经济发展、工业规模等是影响黄河流域空气污染的主要因素,但PM2.5的影响因素更加复杂多样化。其中,技术创新能力和经济发展水平的提升虽然在研究期内加剧了本地工业SO2污染的排放强度,但却能缓解周边城市的工业SO2和PM2.5污染;工业规模的扩大会加剧本地和邻近城市的PM2.5污染。

关键词: 工业SO2, PM2.5, 空间杜宾模型, 黄河流域

Abstract:

The Yellow River Basin plays a very important strategic role in China’s economic and social development and ecological security. Based on the air pollution data of industrial SO2 and PM2.5 in the Yellow River Basin from 2008 to 2017, this article firstly describes the spatial evolution pattern of industrial SO2 and PM2.5 and then uses the spatial panel Durbin model (SPDM) to compare and analyze the influencing factors of the two types of atmospheric pollutants from the direct and indirect effects. The results are as follows: 1) Both industrial SO2 and PM2.5 pollution have significant spatial agglomeration which shows a gradient decline trend from southeast to northwest direction. There is a significant positive spatial correlation between industrial SO2 and PM2.5 from the prefecture-level city scale while the spatial correlation of PM2.5 is stronger the that of industrial SO2. 2) The pollution of industrial SO2 and PM2.5 had been alleviated from 2008 to 2017. The average emission intensity of industrial SO2 decreased rapidly while the average PM2.5 decreased relatively slowly. PM2.5 is still the main air pollution source in the Yellow River Basin. 3) The optimization of the industrial structure (OIS), energy efficiency (EE), technological innovation (Inno), population (POP), economic development (pcGDP), and industrial scale (Ind) are the main factors affecting air pollution in the Yellow River Basin. However, the influencing factors of PM2.5 are more complex and diverse. The improvement of technological innovation and economic development will increase the emission intensity of local SO2 pollution while it can alleviate the pollution of industrial SO2 and PM2.5 in neighboring cities. The expansion of industrial scale aggravates air pollution both locally and in neighboring cities during the study period (2008-2017). Therefore, this article proposes policy recommendations from 3 aspects: improving the city’s innovation capability, accelerating the upgrading of the industrial structure and strengthening joint prevention and control.

Key words: industrial SO2, PM2.5, spatial panel Durbin model, the Yellow River Basin

中图分类号: 

  • K902