Available online at www.sciencedirect.com
ScienceDirect Energy Procedia 104 (2016) 509 – 514
CUE2016-Applied Energy Symposium and Forum 2016: Low carbon cities & urban energy systems
An Evaluation of the Comprehensive Development Capacity —— Energy-based Cities in China Wenqiang Zhang a, Fang Zhao a, Yetang Wangb* a Business School, Unversity of Jinan, Jinan 250002,China College of Geography and Environment, Shandong Normal University, Jinan 250014,China
b
Abstract
To quantify the comprehensive development capacity of energy-based cities, the evaluation index system is established. Based on this index system, principal component analysis is used to evaluate the comprehensive development capacity. The past development of the energy-based cities seriously depends on energy exploitation and consumption, and the environmental protection is often ignored. As a result, these cities experienced serious environmental pollution and ecological destruction. With the superiority of the eastern and central region cities to the western, comprehensive development capacity varies from one region to another. High development capability and high vulnerability coexist among the energybased cities in China. The industrial structure is single, and the secondary industry remains dominant. © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license © 2016 The Authors. Published by Elsevier Ltd. (http://creativecommons.org/licenses/by-nc-nd/4.0/). responsibility of of CUE Selection and/or peer-reviewofunder Peer-review under responsibility the scientific committee the Applied Energy Symposium and Forum, CUE2016: Low carbon cities and urban energy systems. Keywords: Energy-based Cities; Comprehensive Development Capacity; Principal Component Analysis
Introdution Energy is closely related to the daily life. It has become the material basis of the effective social operation. To promote social development, many of the worldwide big cities have been built up. They were often dependent on energy in the early stages of establishment. However, they have to change their development pattern to fit the rapid economic development. The traditional development mode has caused
*Yetang Wang. Tel.: +86-156-1010-0956. E-mail address:
[email protected].
1876-6102 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, CUE2016: Low carbon cities and urban energy systems. doi:10.1016/j.egypro.2016.12.086
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a series of problems, such as environment pollution, community well-being etc. Thus more and more attention has paid to the cities’ sustainable development and transformation. Compared with China, researches on the development of energy-based cities were carried out earlier in countries such as the U.S, Australia, Germany and Canada. As early as 1990s, Grabher [1] made systematic studies on industrial structure adjustment and diversification of energy-based cities. After 2000, researchers concentrated on the impacts of resources endowment on the economic and industrial structure, such as Torvik [2], Mehlum [3] and Van der Ploeg [4]. As for the researches in China, three modes of sustainable development and industrial transformation were put forward by Lixin Hu and Jie Feng [5], Yazhen Nie [6]. Based on 44 energy exhausted cities, risks and capabilities of the industrial transformation were identified and analyzed by Bing Xue [7], Yayun Wu et al. [8]. Basically, the differences of the researches at home and abroad lie into two aspects. The first aspect is that more attention is paid to the long term tracing investigation of the energy-based cities in abroad, so the time span is long. The domestic researches pay more attention to the cross section investigation while the time series analysis is few. The second aspect is that foreign scholars use a variety of research methods. In view of the different research directions, they usually choose the mainstream research methods. Although domestic scholars have also used complex research methods, the mainstream method is not efficient. Nowadays, in order to clarify the comprehensive development capacity of China’s energy-based cities and provide the theoretical support for the industrial transformation and upgrading of the cities, a new method is presented in this paper. Considering the different development stages of the eastern, central and western regions in China, 10 eastern cities, 5 central cities and 8 western cities are chosen as typical energy-based cities. This paper mainly has two innovations. On the one hand, we focus on the evaluation of the comprehensive development capacity of China’s energy-based cities. So we build a comprehensive evaluation index system which is in line with the current situation of China’s development. On the other hand, there is a sophisticated analysis of the industrial structure and employment structure of energybased cities. As a result, we can grasp problems existing in the development course of China’s energybased cities. Construction of Evaluation System of Urban Comprehensive Development Capacity 1.1. Selection of evaluation index Not only the basic indicators of economic development, but also the indexes of environmental development are all contained within the comprehensive development capacity. Comprehensive development capability of a city is not only reflected in some basic indicators such as economic development capacity, but also in other indicators such as environment development capability. The evaluation must be objective and fair. In view of the availability and observability of data, we select 44 indicators as the research objects, which are closely related to the comprehensive development capacity of energy-based cities, as the research objection. Using principal component analysis, we evaluate and analyze the capacity. The evaluation index system includes five core indicators: 1) economic development, 2) inhabitants’ quality, 3) teaching & scientific research, 4) transportation & communication, 5) environment development. 1.2. Evaluation method of comprehensive development capacity According to the above evaluation index system of urban comprehensive development capacity, we use the method of principal component analysis to analyzed 44 sub-indicators with the help of SPSS 20.
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Assuming that the 44 sub-indicators are denoted as xij , in which, i represents the ith observation and j
represents the jth observation. During the analysis process, we selected 23 typical energy-based cities as observations, 44 sub-indicators as analysis variables, so the observations and indicators involved in the analysis can form a data table(23 u 44). The 23 typical energy-based cities include 10 eastern cities, 5 central cities and 8 western cities. The observations represent 5 categories of core indicators, which include 12 economic development indicators, 10 inhabitants’ quality indicators, 6 teaching & scientific research indicators, 7 transportation & communication indicators, 9 environment development indicators. Altogether, 44 variables are in the 5 core indexes. Each category of indicators, when analyzed, can be represented as a linear combination of various types of sub-indicators: The first core indicator: economic development level F1 f ( xi ,1 , xi ,2 , xi ,3, xi ,12 ) (1) The second core indicator: inhabitants’ quality F2 f ( xi ,13 , xi ,14 , xi ,15 xi ,22 )
(2)
The third core indicator: teaching & scientific research level F3 f ( xi ,23 , xi ,24 , xi ,25 xi ,28 )
(3)
The forth core indicator: transportation &communication level F4 f ( xi ,29 , xi ,30 , xi ,31 xi ,35 )
(4)
The fifth core indicator: environment development level F5 f ( xi ,36 , xi ,37 , xi ,38 xi ,44 )
(5)
Finally, we calculate the comprehensive development capacity indicator with the previous five core indicators. Then We can catch the economic development status of the cities more comprehensively. (6) Fz f (F1 , F2 , F3 , F4 , F5 ) According to the formulas (1) ~ (6), we get 6 core indicators. On the basis of this, we make a systematic analysis on the comprehensive development capacity of the 23 typical energy-based cities in China. Comments on the current situation of China’s energy-based cities Before we use the principal component analysis, firstly we should standardize 44 sub-indicators. Only in this way can we eliminate the influence of the dimension and unit of the data. Then we use principal component analysis to measure the sub-indexes from the 5 core indicators respectively. Now we take economic development level as an example to illustrate the process of principal components analysis. First of all, we make Bartlett test and KMO test to the core indicator of economic development level. From the point of inspection results, the statistics of the Bartlett test’s observed value is 343.73 and the corresponding p value is close to zero. The result shows that the correlation coefficient matrix and the unit matrix of the selected sub-indicators have significant difference. At the same time, KMO value is 0.887. The result indicates that the selected indicators are suitable for principal component analysis. Table 1. The principal component analysis result of economic development level Component
Initial eigenvalues Total
Extraction sums of squared loadings
% of
Cumulative
variance
%
Total
% of
Cumulative
variance
%
Rotating sums of squared loadings Total
% of
Cumulative
variance
%
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1
6.97
58.07
58.07
6.97
58.07
58.07
5.30
44.20
44.20
2
2.16
17.96
76.03
2.16
17.96
76.03
3.53
29.41
73.60
3
1.19
9.91
85.94
1.19
9.91
85.94
1.48
12.33
85.94
4
0.64
5.33
91.27
5
0.36
2.97
94.24
6
0.26
2.14
96.38
When principal component analysis is used in the 12 sub-indicators of the core indicators of economic development, only three principal components(X1, X2, X3) can be extracted (see table 1). The three principal components can explain 85.94 percent of the variance of original 12 sub-indicators. Overall, the lost information of original sub-indicators is less. The principal components are ideal. So we can get a score of economic development: F1=0.4420X1+0.2941X2+0.1233X3. The same applies to the rest four core indicators and comprehensive development capacity. The specific results are shown in table 2. Table 2. Evaluation comparison table of economic development capacity of China’s energy-based cities
City
Economic development
Inhabitants’ quality
Teaching& scientific research
Transportation &communication
Environment development
Comprehensive development capacity
Hengyang
0.8041
-0.2074
1.0472
1.1380
0.6061
1.6175
Dongying
1.1423
0.5358
0.4544
0.4963
-0.0396
0.8486
Baotou
1.0558
0.8797
1.0674
0.5794
-0.4110
0.7829
Huaibei
-0.1759
0.2406
-0.2026
-0.3400
0.8061
0.4777
Zaozhuang
0.4324
0.3201
-0.2491
0.4794
0.1542
0.4363
Jingzhou
0.2789
0.0790
1.0405
0.6810
-0.4165
0.3745
Jiaozuo
0.4415
0.2579
0.6020
0.2433
-0.2859
0.2686
Chenzhou
0.5496
-0.1249
-0.0312
0.8399
-0.3473
0.1880
Panjin
0.0826
-0.0431
-0.3256
0.0377
0.1785
0.0811
Kelamayi
-0.3886
0.2693
0.8091
-0.2026
-0.0714
0.0343
Fushun
0.1750
0.2813
0.1721
0.2380
-0.3759
-0.0751
Zhangjiakou
0.1728
-0.0498
-0.1719
0.9840
-0.4866
-0.0808
Liaoyuan
-0.4962
-0.2786
-0.5645
-0.4292
0.5540
-0.1095
Lvliang
0.0332
-0.3520
-0.2937
0.0013
-0.0225
-0.1595
Pingxiang
-0.1489
0.1383
-0.1493
-0.5016
0.1283
-0.1600
Fuxin
-0.3171
0.0975
-0.3883
-0.2029
0.0602
-0.2767
Tongren
-0.4027
-0.9860
-0.3549
-0.4778
0.3568
-0.2815
Qitaihe
-0.7799
-0.3898
-0.1611
-0.5643
0.2191
-0.4386
Tongchuan
-0.6396
0.2530
-0.4589
-0.8011
0.2109
-0.4919
Guangan
-0.2377
-0.4174
-0.4870
-0.4154
-0.1760
-0.6320
Shizuishan
-0.5554
0.1096
-0.4302
-0.5642
-0.1938
-0.7396
Jiuquan
-0.4213
-0.2547
-0.4835
-0.5092
-0.2320
-0.7670
Laibin
-0.6046
-0.3584
-0.4411
-0.7102
-0.2156
-0.8976
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In view of the core indicators scores, we make a rank of the energy-based cities. We find that the high ranking cities in terms of the comprehensive development capacity usually have high level of economic development, inhabitants’ quality, teaching & scientific research, transportation & communication, but their environment development level is relatively low. In order to have a deeper understanding of the current comprehensive development capacity of energy-based cities, we will divide all energy-based cities into three districs: the eastern, central and western region. The result is shown in table 3. From table 3, we can find that the score of the eastern and central region is higher than the national average score. But the score of the west region is lower than the national average score. According to the geographical distribution of the comprehensive development capacity score(shown in Fig. 1), we also draw the same conclusions. Table 3. Statistical results of comprehensive development capacity of energy-based cities in China
Comprehensive development capacity Economic development Inhabitants’ quality Teaching &scientific research Transportation &communication Environment development
Indicators
Obs
Mean
Std.
Min
Max
Nationwide Eastern Central Western Nationwide Eastern Central Western Nationwide Eastern Central Western Nationwide Eastern Central Western Nationwide Eastern Central Western Nationwide Eastern Central Western
23 10 5 8 23 10 5 8 23 10 5 8 23 10 5 8 23 10 5 8 23 10 5 8
-0.0000 0.0703 0.4578 -0.3741 0.0000 0.0087 0.4215 -0.2743 0.0000 0.0852 -0.0695 -0.0631 0.0000 -0.1586 0.4730 -0.0974 0.0000 0.0197 0.5807 -0.3876 0.0000 0.1198 -0.0932 -0.0915
0.5889 0.3964 0.6785 0.5550 0.5450 0.5340 0.2891 0.5533 0.3877 0.2821 0.2404 0.5645 0.5478 0.2869 0.6145 0.6442 0.5815 0.5174 0.4575 0.4308 0.3515 0.3825 0.4184 0.2529
-0.8976 -0.4386 -0.1595 -0.8976 -0.7799 -0.7799 0.0332 -0.6396 -0.9860 -0.3898 -0.3520 -0.9860 -0.5645 -0.5645 -0.2937 -0.4870 -0.8011 -0.5643 0.0013 -0.8011 -0.4866 -0.4866 -0.4165 -0.4110
1.6175 0.8486 1.6175 0.7829 1.1423 1.1423 0.8041 1.0558 0.8797 0.5358 0.2579 0.8797 1.0674 0.4544 1.0472 1.0674 1.1380 0.9840 1.1380 0.5794 0.8061 0.8061 0.6061 0. 3568
Fig. 1. Regional distribution map of comprehensive development capacity of energy-based cities in China
There are some significant differences in the comprehensive development capacity of energy-based cities. The gap among different regions is particularly conspicuous. One possible reason is that the structure of output value and employment is different. On the one hand, the industrial structure is
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relatively unitary. Most of the traditional dominant industries have gone into an aging state, while the new leading industry is lacked severely. On the other hand, economic development usually comes with the change of employment structure. The labour force transfers from primary products production to manufacturing and services industries. When the energy sources are exhausted, lots of workers who work in the primary industry will lose their jobs. Conclusion According to the evaluation system of the comprehensive development capacity of cities and the research on the typical energy-based cities in China, 4 conclusions are drawn in this paper. Firstly, the economic development of energy-based cities in China is at the expense of the environmental pollution. The environmental protection work was not fully carried out, which resulted in the poor environment development capacity. Secondly, the difference of development capacity among regions is huge. For example, the comprehensive development capacity in east regions are significantly superior to that of west regions. Thirdly, the character of coexistence of high development capability and high vulnerability crisis is obvious. The volatility of comprehensive development capacity in the central and west regions is higher than the east. Fourthly, due to the unchanged dominant position of secondary industry, the industrial structure of energy-based cities is unitary. Compared with the national average level, there is a large gap for the energy-based cities to catch up. Acknowledgements This paper benefits a lot from National Statistical Research Program (LX2012Y24), National Statistical Research Program (2015LX63) and Jinan Green Economic Research Association Research Project (12JSGE01). We appreciate the valuable comments of the anonymous referees, but we will bear the responsibility of the paper. Reference [1] Grabher G. The weakness of strong ties: the lock-in of regional development in the rural area, The Embedded Firm. London and New York: Rutledge, 1993. [2] Torvik R. Natural resources, rent seeking and welfare. Journal of Development Economics, 2002: 67:455-470. [3] Melham H, Moene K, Torvik R. Institutions and the resource curse. The Economic Journal, 2006: 116:1-20. [4] Van der Ploeg F, Poelhekkey S. Volatility and the natural resource curse. Oxford Economic Papers, 2009: 61:727-760. [5] Hu Lixin, Feng Jie. The choice of sustainable development model of energy-based cities in China. Development Research, 2000, 4: 20-22. [6] Nie Yazhen, Zhang Yun, Jiang Xueqin. The law of the rise and fall and transformation of resource-based cities. Beijing: China Books Publishing House, 2013. [7] Xue Bing. The risk of identification and prevention of the industrial transformation of resource based cities. Resources and Industry, 2014, 1: 8-12. [8] Wu Yayun, Gao Shikui. Evaluation on the industrial transformation ability of Inner Mongolia resource based cities. Resources and Industry, 2015,1: 1-5.
Biography Wenqiang Zhang (1990-), Male, business school of university of Jinan, the research direction is corporate finance and low-carbon economy, Tel:+86-182-6541-0797, E_mail:
[email protected].
