Evaluating and simulating resource and environmental carrying capacity in arid and semiarid regions: A case study of Xinjiang, China. (1st March 2022)

• Record Type: Journal Article
• Authors: Han, Chuqiao; Zheng, Jianghua; Guan, Jingyun; Yu, Danlin; Lu, Binbin
• Is Part Of: Journal of cleaner production. Volume 338(2022)
• Publication Date: 2022-03-01
• Subjects: Resources and environmental carrying capacity (RECC) -- Arid and semiarid -- Spatiotemporal evolution -- Ordered Weighted Average (OWA) -- Sustainable development -- China; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2022.130646
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Resources and environment provide the fundamental conditions for human life. With the rapid growth of population and development of regional social economies, the environment and ecosystems have been disturbed to varying degrees. Contradictions among human beings, resources and environment have become a key issue restricting the sustainable development, particularly in arid and semiarid regions. This study takes the arid and semiarid region of Xinjiang, China, as an example. An evaluation model and index system of resource and environmental carrying capacity (RECC) are proposed based on the "pressure-vulnerability-adaptability" (PVA) concept. The RECCs in Xinjiang from 2000 to 2019 were quantitatively evaluated, and the reasons for the spatio-temporal changes of RECC were explored. In addition, the ordered weighted averaging (OWA) algorithm was introduced to realize multi-scenario simulations with concerning different decision-making preferences. Results indicated that: (1) the RECC in Xinjiang presents a spatial pattern of "high pressure around the three mountains and low pressure around the two basins" and the area of high carrying capacity decreased significantly from 2000 to 2019; (2) the pressure risk indicators are key factors in evaluating the RECC and the difference between the regional RECC and pressure risk is largely affected by vulnerability and adaptability; (3) the future regional RECC are predicted differently under different development orientations via the OWA algorithm, which is useful to provide decision-making references for promoting sustainable development. Highlights: The RECC evaluation model and index system for arid and semiarid regions were proposed. The reasons for the spatio-temporal changes of RECC were explored. The spatial difference between the RECC and the pressure was apparent. Multi-scenario simulations of the RECC through the OWA can provide guidance for sustainable development.