[ Log In | Register]
! Skip Navigation Links
Skip Navigation Links
Image of Journal of Applied Nonlinear Dynamics
ISSN:2325-6192 (print)
ISSN:2325-6206 (online)
Journal of Environmental Accounting and Management
António Mendes Lopes (editor), Jiazhong Zhang(editor)
António Mendes Lopes (editor)

University of Porto, Portugal

Email: aml@fe.up.pt

Jiazhong Zhang (editor)

School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China

Fax: +86 29 82668723 Email: jzzhang@mail.xjtu.edu.cn

Identification of the Characteristics of the Industrial System of the Multilevel Urban Agglomeration in the Pearl River Delta

Journal of Environmental Accounting and Management 8(1) (2020) 1--17 | DOI:10.5890/JEAM.2020.03.001

Yao Song, Yanxu Yu, Jiansu Mao

State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China

Download Full Text PDF

 

Abstract

Hierarchical study of the industrial systems (ISs) of urban agglomerations, as compound systems under the interaction of multiple cities, is of great significance to the planning and management of a specific region. In the Pearl River Delta, one of the most vigorous economic zones in China, the developments of its nine component cities are unbalanced. Taking this area as a research object can not only promote its coordinated and sustainable development but can also predict and guide the industrial development of other regions. This study divides the Pearl River Delta into three levels from inside to outside as follows: Shenzhen, the urban belt composed of Guangzhou, Shenzhen and Dongguan, and the urban agglomeration composed of nine cities. According to the material flow process from resources to products, a framework of the relations between each component of an IS and the external environment as well as an evaluation index system are established. On this basis, taking China as a basic standard, the industrial characteristics of the three levels are quantitatively analyzed and compared. The results show that the concentration in the product processing and manufacture phase (PM), especially in the the manufacturing sector of computers, communication and other electronic equipment (CEM), is more significant in the Pearl River Delta compared with China and that the dominance of CEM becomes increasingly obvious with the convergence to the core city. This area also has characteristics of higher profits, lower energy consumption and lower pollutant discharges, which are 2.17%, 74.55% and 74.52% better than those of China, respectively. Shenzhen, whose discharges of smoke and dust and waste solids are as low as 0.43 ton/billion CNY and 0.51 ton/billion CNY, respectively, plays a leading role in energy saving and discharge reduction in the urban agglomeration. Huizhou, Zhaoqing and Jiangmen are key cities to increase the energy efficiency of the IS in the Pearl River Delta, whereas Dongguan is the key city to enhance the positive driving effect of the central city belt to marginal cities.

Acknowledgments

This work has been supported by the National Key Research and Development Program of China (No. 2016YFC-0502802).

References

  1. [1]  Chen, D., Chen, S., and Jin, H. (2018), Industrial agglomeration and CO2 emissions, evidence from 187 Chinese prefecturelevel cities over 2005-2013, Journal of Cleaner Production, 172, 993-1003.
  2. [2]  Combes, P.P., Duranton, G., Gobillon, L., Puga, D., and Roux, S. (2012), The productivity advantages of large cities, distinguishing agglomeration from firm selection, Econometrica, 80(6), 2543-2594.
  3. [3]  Ding, J. andWang, K. (2016), Spatial pattern and morphological characteristics of industrial production space and influential factors in the Pearl River Delta urban agglomeration, Progress in Geography, 35(5), 610-621.
  4. [4]  Feng, H., Xie, R., and Fang, J. (2018a), Urban agglomeration economies and industrial energy efficiency, Energy, 162, 45-59.
  5. [5]  Feng, H., Xie, R., Lu, Y., Fang, J., and Liu, Y. (2018b), The effects of urban agglomeration economies on carbon emissions: Evidence from Chinese cities, Journal of Cleaner Production, 172, 1096-1110.
  6. [6]  He, J., Li, C., Yu, Y., Liu, Y., and Huang, J. (2017), Measuring urban spatial interaction in Wuhan Urban Agglomeration, Central China: A spatially explicit approach, Sustainable Cities and Society, 32, 569-583.
  7. [7]  Huang, G., An, C., Fan, Y., Xu, L., Li, Y., Cai, Y., Li, Y., and Li, F. (2016), Development of ecological security protection techniques for the urban agglomeration area in the Great Pearl River Delta, Acta Ecologica Sinica, 36(22), 7119-7124.
  8. [8]  Huang, Y., Li, L., and Yu, Y. (2018), Does urban cluster promote the increase of urban eco-efficiency? Evidence from Chinese cities, Journal of Cleaner Production, 197, 967-971.
  9. [9]  Jiang, H. and Deng, J. (2015), The law of the industrial structure evolution in global cities & Shanghai’s gap, the perspective of education structure, Urban Development Research, 22, 64-70.
  10. [10]  Jin, X. and Zhao, X. (2016), The spillover effect of central city and urban economic growth, evidences from Panel Data 2000-2012 of the urban agglomeration in China, Journal of Zhejiang University (Humanities and Social Sciences), 46(5), 170-181.
  11. [11]  Li, H. and Li, S. (2011), Research on efficiency of urban agglomeration based on DEA model: An empirical study of the Pearl River Delta City Group, Soft Science, 25(5), 91-95.
  12. [12]  Li, L., Lei, Y., Wu, S., He, C., Chen, J., and Yan, D. (2018), Impacts of city size change and industrial structure change on CO2 emissions in Chinese cities, Journal of Cleaner Production, 195, 831-838.
  13. [13]  Li, Y. and He, C. (2013), Characteristics and mechanism of manufacturing industry shift in the Pearl River Delta during 1998-2009, Progress in Geography, 32(5), 777-787.
  14. [14]  Li, Y., Sun, L., Zhang, H., Liu, T., and Fang, K. (2018), Does industrial transfer within urban agglomerations promote dual control of total energy consumption and energy intensity? Journal of Cleaner Production, 204, 607-617.
  15. [15]  Lin, B. and Xu, B. (2018), Growth of industrial CO2 emissions in Shanghai city: Evidence from a dynamic vector autoregression analysis, Energy, 151, 167-177.
  16. [16]  Liu, B., Tian, C., Li, Y., Song, H., and Ma, Z. (2018), Research on the effects of urbanization on carbon emissions efficiency of urban agglomerations in China, Journal of Cleaner Production, 197, 1374-1381.
  17. [17]  Liu, J., Cheng, Z., and Zhang, H. (2017), Does industrial agglomeration promote the increase of energy efficiency in China? Journal of Cleaner Production, 164, 30-37.
  18. [18]  Liu, K., Bai, H., Yin, S., and Lin, B. (2018), Factor substitution and decomposition of carbon intensity in China’s heavy industry, Energy, 145, 582-591.
  19. [19]  Lu, D. (2015), Function orientation and coordinating development of subregions within the Jing-Jin-Ji Urban Agglomeration, Progress in Geography, 34(3), 265-270.
  20. [20]  Ma, Y. and Liu, J. (2015), Efficiency evaluation of regional industrial ecology of the Yangtze River Middle Reaches Urban Agglomerations, Economic Geography, 35(6), 124-129.
  21. [21]  Mao, J., Du, Y., Cai, H., and Jiang, P. (2010), Energy efficiencies of industrial sectors for China’s major cities, Procedia Environmental Sciences, 2, 781-791.
  22. [22]  Mao, J., Zeng, R., Du, Y., and Jiang, P. (2010), Eco-efficiency of industry sectors for China, Chinese Journal of Environmental Science, 31(11), 2788-2794.
  23. [23]  Mao, J., Du, Y., Xu, L., and Zeng, Y. (2011), Quantification of energy related industrial eco-efficiency of China, Frontiers of environmental science & engineering in China, 5(4), 585-596.
  24. [24]  Mao, J. and Ma, L. (2013), Method for grading industrial sectors in energy consumption and its application, Chinese Journal of Environmental Science, 34(4), 1628-1635.
  25. [25]  Mao, J., Li, C., Pei, Y., and Xu, L. (2018), Circular Economy and Sustainable Development Enterprises, 1st ed, Singapore, Springer.
  26. [26]  Mei, Z., Xu, S., Ouyang, J., and Shi, C. (2012), The spatio-temporal evolvement of spatial interaction among cities of Zhujiang River Delta in recent 20 years, Scientia Geographica Sinica, 32(6), 694-701.
  27. [27]  National Bureau of Statistics of China (NBSC) (2016), China city statistical yearbook 2016. China Statistical Press, Beijing.
  28. [28]  Qi, Y. and Zhang, Y. (2015). Relation between industrial structure evolution and industrial SO2 emissions: taking Beijing- Tianjin-Hebei Region as an example, Urban Problems, 6, 54-62.
  29. [29]  Statistical Bureau of Dongguan (SBDG) (2016), Dongguan statistical yearbook 2016. China Statistics Press, Beijing.
  30. [30]  Statistical Bureau of Foshan (SBFS) (2016), Foshan statistical yearbook 2016. China Statistics Press, Beijing.
  31. [31]  Statistical Bureau of Guangdong (SBGD) (2016), Guangdong statistical yearbook 2016. China Statistics Press, Beijing.
  32. [32]  Statistical Bureau of Guangzhou (SBGZ) (2016), Guangzhou statistical yearbook 2016. China Statistics Press, Beijing.
  33. [33]  Statistical Bureau of Huizhou (SBHZ) (2016), Huizhou statistical yearbook 2016. China Statistics Press, Beijing.
  34. [34]  Statistical Bureau of Jiangmen (SBJM) (2016), Jiangmen statistical yearbook 2016. China Statistics Press, Beijing.
  35. [35]  Statistical Bureau of Shenzhen (SBSZ) (2016), Shenzhen statistical yearbook 2016. China Statistics Press, Beijing.
  36. [36]  Statistical Bureau of Zhuhai (SBZH) (2016), Zhuhai statistical yearbook 2016. China Statistics Press, Beijing.
  37. [37]  Statistical Bureau of Zhaoqing (SBZQ) (2016), Zhaoqing statistical yearbook 2016. China Statistics Press, Beijing.
  38. [38]  Statistical Bureau of Zhongshan (SBZS) (2016), Zhongshan statistical yearbook 2016. China Statistics Press, Beijing.
  39. [39]  Shang, H. and Mao, B. (2016), An empirical study on industrial agglomeration and the environmental pollution based on IPAT model, Ecological Economy (in Chinese), 32(6), 77-87.
  40. [40]  Shen, Y., Zhang, L., Fang, X., Ji, H., Li, X., and Zhao, Z. (2019), Spatiotemporal patterns of recent PM2.5 concentrations over typical urban agglomerations in China, Science of The Total Environment, 655, 13-26.
  41. [41]  Song, Y., Yu, Y., and Mao, J. (2018), Comparative analysis of three major cities’ industrial systems and their environmental impacts in the Pearl River Delta, Journal of Economics and International Business Management, 6(3), 51-61.
  42. [42]  Su, X. (2004), Agglomeration of factors, industrial cluster and megalopolis in the urbanization, Journal of Central University of Finance & Economics (in Chinese), 1, 49-52.
  43. [43]  Ye, C., Zhu, J., Li, S., Yang, S., and Chen, M. (2018), Assessment and analysis of regional economic collaborative development within an urban agglomeration: Yangtze River Delta as a case study, Habitat International, in press.
  44. [44]  Yu, B. (2015), Economic growth effect of industrial structure adjustment and productivity promotion, an analysis based on China’s urban dynamic spatial panel model, China’s Industrial Economy, 12, 83-98.
  45. [45]  Zhang, Y. (2014), Empirical studies on the relationship between industrial agglomeration and economic growth within the urban agglomeration: Based on panel data analysis, Economic Geography (in Chinese), 34(1), 108-113.
  46. [46]  Zhao, H. and Lin, B. (2019), Will agglomeration improve the energy efficiency in China’s textile industry: Evidence and policy implications, Applied Energy, 237(1), 326-337.
  47. [47]  Zhao, Z.,Wang, J., and Feng, J. (2017), Research on the spatial correlation of central cities in Beijing-Tianjin-Hebei Urban Agglomeration, Economic Geography, 37(6), 60-66.
  48. [48]  Zhu, Z., Zheng, B. and He, Q. (2011), Study on evolution of spatial structure of Pearl River Delta urban agglomeration and its effects, Economic Geography, 31(3), 404-408.

Copyright © 2011-2024 L & H Scientific Publishing. All rights reserved. Wildcard SSL Certificates