Regional Scale Dynamic Prediction of Energy Ecological Footprint and Its Influencing Factors
International Journal of Environmental Protection and Policy
Volume 7, Issue 1, January 2019, Pages: 17-23
Received: Dec. 6, 2018; Published: Mar. 8, 2019
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Authors
Luyun Liu, School of Landscape Architecture, Central South University of Forestry and Technology, Changsha, China
Jian Zheng, School of Architecture, South China University of Technology, Guangzhou, China
Guo Li, School of Landscape Architecture, Central South University of Forestry and Technology, Changsha, China
Yan Wang, School of Landscape Architecture, Central South University of Forestry and Technology, Changsha, China
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Abstract
The regional energy ecological footprint is an important evaluation index which can reveal the energy consumption on regional environmental pressure and sustainable development. First, the study relied on EEF (energy ecological footprint) method to calculate the ecological footprint, the energy ecological footprint and the ecological capacity. While STIRPAT model was applied to examine the relationship between the regional populations scale, the economic level, the industrial structure, the energy utilization technology and the energy ecological footprint. Grey prediction model was used to predict the development tendency of the energy ecological footprint in the next 10 years. The data were elicited from statistical data of regional energy consumption. The energy ecological footprint was increased to 0.3437ghm2/person from 0.1234ghm2/person during 2006-2015 in Xiangtan region. Though the energy capacity per capita increased slightly, the energy ecological footprint was kept in deficit. The level was increased to 0.2504ghm2/person from 0.073ghm2/person. The ecological pressure of the energy ecological footprint was very large. Among the influencing factors, the industrial structure contributes the most to explain the energy ecological footprint, followed by the population scale and the GDP per capita. The influence of the energy strength was minimal. The indices of energy ecological footprint, energy capacity and ecological pressure increased to 1.1205, 0.1246 and 8.9013ghm2/person, respectively. The dynamic scale of energy ecological footprint and the analysis of the influencing factors can provide a theory for sustainable development of society-economy-resources and environment.
Keywords
Energy Ecological Footprint, Ecological Capacity, Dynamic Evaluation, Grey Prediction Model, Xiangtan
To cite this article
Luyun Liu, Jian Zheng, Guo Li, Yan Wang, Regional Scale Dynamic Prediction of Energy Ecological Footprint and Its Influencing Factors, International Journal of Environmental Protection and Policy. Vol. 7, No. 1, 2019, pp. 17-23. doi: 10.11648/j.ijepp.20190701.13
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