Assessing the Ecological Risks Based on the Three-Dimensional Ecological Footprint Model in Gansu Province

It has become a hot topic in sustainable development to determine how to use data series to predict the trajectory of ecological footprints (EFs), precisely map biocapacity (BC), and effectively analyze regional sustainability. The sustainability of the ecological system in Gansu province must be in...

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Veröffentlicht in:Sustainability 2022-12, Vol.14 (24), p.16995
Hauptverfasser: Liu, Hua, Li, Dan-Yang, Ma, Rong, Ma, Ming
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Sprache:eng
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Zusammenfassung:It has become a hot topic in sustainable development to determine how to use data series to predict the trajectory of ecological footprints (EFs), precisely map biocapacity (BC), and effectively analyze regional sustainability. The sustainability of the ecological system in Gansu province must be investigated because the province is situated in western China and serves as a significant economic and transportation hub. We used the EF model to compute the per capita EF and BC of Gansu province from 2010 to 2020. We created a three-dimensional ecological footprint (EF3D) model by incorporating the ecological footprint size (EFsize) and ecological footprint depth (EFdepth) into the EF model and the EF3D of Gansu province from 2010 to 2020 was measured. The EF3D value was estimated using the gray GM (1, 1) prediction model in order to determine the sustainability condition of Gansu province during the next ten years. Finally, the risk of ecosystem loss in the province of Gansu was ultimately assessed using an ecological risk model (EVR). The results show that Gansu province’s per capita EF and BC displayed generally rising trends and the province is experiencing unsustainable development. The region’s projected future consumption of natural capital was estimated by the results, and the EF3D of Gansu province is expected to increase significantly in the future. These findings have a certain reference value for adjusting the industrial structure and utilizing resources in Gansu province. Furthermore, these findings will assist Gansu province in achieving sustainable development policy recommendations.
ISSN:2071-1050
2071-1050
DOI:10.3390/su142416995