Natural Hazards

, Volume 89, Issue 2, pp 741–756 | Cite as

An extended STIRPAT model-based methodology for evaluating the driving forces affecting carbon emissions in existing public building sector: evidence from China in 2000–2015

Original Paper
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Abstract

Productive building energy efficiency work is a non-ignored booster to achieve the sustainable development in China, and evaluating the driving forces of carbon emissions in Chinese public buildings (CECPB) plays a crucial role in China building energy efficiency work. Nevertheless, China building energy efficiency work is currently challenged by the lack of effective approaches to evaluating the driving forces affecting CECPB at a quantitative level. To improve the carbon emission control strategy of Chinese public buildings, this study utilized the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and ridge regression analysis to evaluate the driving forces affecting CECPB from 2000 to 2015. This study has three main results: (1) All of the five driving forces (i.e., population, urbanization level, floor area per capita of existing Chinese public buildings, GDP index in the Chinese tertiary industry sector, and carbon emission intensity in Chinese public buildings) have positive contributions to CECPB during the period of 2000–2015. (2) The different contributions of the aforementioned driving forces can be expressed by their different β values in decreasing order, as follows: floor area per capita of existing Chinese public buildings (21.12%), population (20.98%), urbanization level (20.81%), carbon emission intensity in Chinese public buildings (20.20%), and GDP index in the Chinese tertiary industry sector (19.44%). (3) The goodness of fit for the final ridge regression analysis proves that the proposed evaluation method is also applicable for evaluating these driving forces at a subitem level. Furthermore, this study demonstrates the feasibility of evaluating the driving forces affecting CECPB using the STIRPAT model and ridge regression analysis and fills the research gap. The discoveries of this study can impel the development of the carbon emission control strategy of Chinese public buildings for the upcoming phase.

Keywords

Carbon emissions in Chinese public buildings Driving forces STIRPAT model Ridge regression analysis 
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Notes

Acknowledgements

We thank all the anonymous reviewers for their invaluable and constructive comments on an earlier draft of this manuscript and hence their contribution to the substantial revisions made since that time. The study was supported by the Social Science and Humanity on Young Fund of the Ministry of Education PR China (15YJC630003), Graduate Scientific Research and Innovation Foundation of Chongqing of PR China (CYB17027), and the Fundamental Research Fund for the Central Universities of PR China (2017CDJSK03XK01 and 2017CDJSK03YJ05).

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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.School of Construction Management and Real EstateChongqing UniversityChongqingChina
  2. 2.China Energy GroupLawrence Berkeley National LaboratoryBerkeleyUSA

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