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Journal of Mountain Science

, Volume 8, Issue 4, pp 611–618 | Cite as

Analysis of major driving forces of ecological footprint based on the STRIPAT model and RR method: A case of Sichuan Province, Southwest China

  • Wei Tang
  • Xianghao ZhongEmail author
  • Shaoquan Liu
Article

Abstract

The Ecological Footprint (EF) equation provides useful accounting to analyze the relationship between human activities and the environment. Knowledge of the specific forces driving EF is not fully understood but the STIRPAT model provides a simple framework for decomposing the impact of human activities on environment. We applied the EF model in Sichuan Province, China to assess the impact of human activities. The per capita EF increased by 2 fold in the 14 years between 1995 and 2008, but ecological capacity decreased in the same period, suggesting that the biologically productive area of Sichuan Province is inadequate to sustain human activities. According to the refined STIRPAT model, the hypothesized driving forces of EF include population size (P), GDP per capita (A1), quadratic term of GDP per capita (A2), percentage of GDP from industry (T1) and urbanization rate (T2). However, the multi-collinearity among these drivers could be a substantial problem which may reveal negative effect in the final results. Application of the Ridge Regression (RR) method to fit the STIRPAT model had the advantage of being able to avoid the collinearity among independent variables. The results showed that population is the principal driving force of EF variation in Sichuan Province and that urbanization and industrialization also have a positive association with the EF. Analysis of affluence elasticity (EEA) showed that the relationship between EF and economic growth was not curvilinear, suggesting that variation of EF does not follow an Environmental Kuznets Curve relative to economic growth in Sichuan Province.

Keywords

Ecological footprint STIRTPAT model Ridge Regression Major driving forces Sichuan Province China 

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Copyright information

© Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  1. 1.Institute of Mountain Hazard and EnvironmentChinese Academy of ScienceChengduChina
  2. 2.Graduate school of Chinese Academy of SciencesBeijingChina

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