ORIGINAL RESEARCH
Analysis of Influencing Factors of Ground-Source Heat Pump Applications in China Using Partial Least Squares Regression
Yong Jiang1-2, Yalin Lei1-2
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1School of Humanities and Economic Management, China University of Geosciences,
Beijing, 10083, China
2Key Laboratory of Carrying Capacity Assessment for Resources and the Environment,
Ministry of Land and Resources, Beijing, 100083, China
Submission date: 2017-03-03
Final revision date: 2017-04-11
Acceptance date: 2017-04-11
Online publication date: 2017-08-31
Publication date: 2017-11-07
Pol. J. Environ. Stud. 2017;26(6):2575-2583
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ABSTRACT
Energy crisis and environmental pollution have become major challenges in China’s economic development, which has triggered the demand for alternative energy sources and promoted the popularization of ground source heat pump technology. A ground source heat pump (GSHP) is a central heating and/or cooling system that transfers heat to or from the ground. It uses the earth as a heat source (in the winter) or a heat sink (in the summer). This design takes advantage of the moderate temperatures in the ground to boost efficiency and reduce the operational costs of heating and cooling systems. This paper adopted the STIRPAT model and the influencing factors were analyzed. The major influencing factors were population (P), urbanization level (U), GDP per capita (A), energy consumption per capita (E), industrial structure (IS), R&D (T), central heating area (HA), and policy investment (PI). However, these factors themselves had strong collinearity, which might produce some uncertain impacts on the final results. To avoid the impact of collinearity, the method of partial least squares (PLS) was used. The results showed that P, U, A, E, T, HA, and PI had positive effects on GSHP, while IS had a slight effect on GSHP. This paper found that A is the most dominant factor and the effect of the IS could almost be ignored. Some policy recommendations were given on how to promote the application of GSHP systems and mitigate the growth of CO2 emissions.