Assessing the sustainability of the shale gas industry by combining DPSIRM model and RAGA-PP techniques: An empirical analysis of Sichuan and Chongqing, China

Qiang Wang and Lina Zhan

Energy, 2019, vol. 176, issue C, 353-364

Abstract: Shale gas is a kind of unconventional natural gas stored in shale formation. Compared with traditional fossil fuels, it is more efficient and environmentally friendly. It can help to reduces a country's overdependence on high-energy and high-pollution resources. The sustainable development of the shale gas industry is a prerequisite for achieving an efficient, green, and long-term use of shale gas resources. In order to evaluate the sustainability of the shale gas industry correctly and scientifically, the driving force-pressure-state-impact-response-management (DPSIRM) model, the real-coded accelerated genetic algorithm (RAGA), and projection pursuit (PP) were combined to develop an assessment model for the sustainability of the shale gas industry (the DPSIRM-RAGA-PP model). The proposed model was then applied for an empirical analysis of the sustainable development of the shale gas industry of Chongqing and Sichuan, which currently produce over 90% of the Chinese shale gas. The obtained results show that (1) water shortage, water pollution and pipe network density are the major influencing factors for the sustainable development of the shale gas industry in the 15 indicators selected by DPSIRM model. (2) Compared to other factors, geological conditions, market risks and core technology exert less impact on the sustainable development of the shale gas industry in Chongqing and Sichuan. This may be related to the current stage of the shale gas development in Chongqing and Sichuan and the available statistical data. (3) The projection eigenvalues of the Chongqing and Sichuan samples are 3.1184 and 1.6826, respectively. It indicates that the sustainability of shale gas industry in Chongqing is better than that in Sichuan. Moreover, the proposed DPSIRM-RAGA-PP model can effectively utilize the high-dimensional, non-normal, and nonlinear complex data, and provides a practical method for the quantitative analysis and evaluation of the sustainable development of the fuel industry in general.

Keywords: Shale gas; Sustainability assessment; DPSIRM framework; Projection pursuit; Accelerated genetic algorithm (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:176:y:2019:i:c:p:353-364

DOI: 10.1016/j.energy.2019.03.158

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