SCIENTIA GEOGRAPHICA SINICA ›› 2018, Vol. 38 ›› Issue (7): 1042-1050.

### Green Development Level and the Obstacle Factors of Old Industrial Base in Northeast China

Jiamin Ren1,2(), Yanji Ma1()

1. 1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, Jilin, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
• Received:2018-02-12 Revised:2018-06-05 Online:2018-07-20 Published:2018-07-20
• Supported by:
National Natural Science Foundation of China (41371135)

Abstract:

Currently, both developed and developing countries emphasize the green development of their economy, which is also the focus against the context of the revitalization of Old Industrial Base(OIB). This article takes OIB in Northeast China as a case study to show its green development condition by evaluating its green development level and identifying its obstacle factors. Firstly, this article introduced the features of green development of OIB based on the existing literature both domestic and abroad. Secondly, we established a comprehensive index system which consists of five aspects: 1) The capacity of resource utilization; 2) The green industry; 3) The quality of economic development; 4) The environment protection and treatment; 5) The green residence environment. This index system includes 25 evaluation indices. Thirdly, the article analyzed the spatial distribution and regional differences of the green development level of 11 typical old industrial cities in Northeast China. The results are as following: First, we find that green development level of Shenyang and Changchun are much higher than other cities in 2014, the next are Dalian and Harbin, the rest cities are lower than these four cities. Second, these 11 cities can be divided into four categories by calculating the standard deviation of their green development level. We find that Shenyang, Changchun, Dalian are in the first group, Harbin is in the second group, Fushun is in the fourth group, and the other cities belong to the third group. Third, the capacity of green development has increased significantly from 2008 to 2014, but the polarization phenomena are even apparent. It gradually formed a green development level pattern in the space that took the four major cities as the center. The index of coefficient of variation shows that regional differences and spatial polarization of green development among old industrial cities tend to decrease. Fourth, based on the factor analysis of the obstacle degree, we find that the development of local economy and green industry is the major factor of rule hierarchy that affects green development in general. Their negative influence on green development becomes stronger over time. From the view of index hierarchy, we can see that the top five obstacle indicators didn’t change during the study period, shows a stable status. The ratio of technology expenditure to GDP are the major obstacle factors that affect green development level, and the major influences of each index on each city’s green development level show an obvious regional characteristic.

CLC Number:

• K902