A Composite Indicator for Evaluating the Low-Carbon Performance of Cities in Jiangsu Province

Article Preview

Abstract:

This paper developed a composite indicator for evaluating the performance of low-carbon economy for the cities in Jiangsu province, China. The empirical results show that the performance of low carbon economy of cities in Jiangsu province may be divided into three levels. The first level include Yangzhou, Zhenjiang, and Nanjing, that the performance is below the province average level; the second level including Huaian, Suqian, Lianyungang, and Nantong which, that the performance is similar with the province average level; the rest of the cities in Jiangsu are set as third level. At same time, this paper analyze some cities’ performance of low carbon economy.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 1073-1076)

Pages:

2572-2577

Citation:

Online since:

December 2014

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] National Development and Reform Commission (NDRC). The notice of piloting low-carbon provinces and low-carbon cities. (2010) http: /www. gov. cn/zwgk/2010-08/10/content_1675733. htm.

Google Scholar

[2] Price, L., Zhou, N., Fridley, D., Ohshita, S., Lu, H., Zheng, N., &Fino-Chen, C. Development of a low-carbon indicator system for China. Habitat International, 37, 4-21. (2013).

DOI: 10.1016/j.habitatint.2011.12.009

Google Scholar

[3] Jiangsu Bureau of Statistical. Jiangsu statistical yearbook 2013. Nanjing.

Google Scholar

[4] Intergovernmental Panel on Climate Change (IPCC). (2006). 2006 IPCC Guidelines for National Greenhouse Gas Inventories. (2013) http: /www. ipcc-nggip. iges. or. jp/public/2006gl/index. html.

DOI: 10.1007/springerreference_28950

Google Scholar

[5] Nardo, M., Saisana, M., Saltelli, A., Tarantola, S., Hoffman, A., &Giovannini, E. Handbook on constructing composite indicators: methodology and user guide (No. 2005/3). OECD publishing. (2005).

Google Scholar

[6] Zhou, P., Ang, B. W., &Poh, K. L. A mathematical programming approach to constructing composite indicators. Ecological economics, 62(2), 291-297. (2007).

DOI: 10.1016/j.ecolecon.2006.12.020

Google Scholar

[7] Zhou, P., Ang, B. W., & Zhou, D. Q. Weighting and aggregation in composite indicator construction: a multiplicative optimization approach. Social Indicators Research, 96(1), 169-181. (2010).

DOI: 10.1007/s11205-009-9472-3

Google Scholar