Ziyuan Kexue (Oct 2023)
Elastic range measurement of resource and environmental carrying capacity and future scenario analysis: A case study of the Lanzhou-Xining urban agglomeration
Abstract
[Objective] Developing an urban system scale that adapts to the resources and environmental carrying capacity (RECC) is an important foundation for achieving sustainable development of urban agglomerations. Previous studies often employed static and rigid constraints to represent RECC, which were characterized by single absolute values. Such approach does not align with the dynamic and uncertain nature of RECC. To address this issue, the purpose of this study was to measure the elastic ranges and project future scenarios of resources and environmental carrying capacity. [Methods] This study proposed a method for determining the elastic range and status of RECC. A quantitative analytical framework for RECC was constructed by integrating the system dynamic and CA-Markov models. Additionally, the shared socioeconomic pathways (SSPs) provide a series of future scenarios for analyzing RECC. The proposed framework was applied to an empirical study of the Lanzhou-Xining urban agglomeration (LXUA). [Results] (1) From 2000 to 2020, the elastic range of the RECC in the LXUA changed from [11.67, 13.67] million to [20.49, 20.69] million people, and the carrying capacity status type transitioned from critical overload to non-overload. (2) The elastic range of the RECC and the single-factor carrying capacity were basically on the rise in each prefecture-level administrative unit, and presented obvious spatial divergence. (3) From 2021 to 2035, under the SSP1 scenario most of the single-factor carrying capacities will be higher than under the other scenarios, while the population growth rate will be the lowest; As the baseline scenario of SSP2, the elastic range of comprehensive resources and environmental carrying capacity, each single-factor carrying capacity and the permanent population will be all at the middle level. SSP3 will be the scenario with the lowest elastic range of comprehensive resources and environmental carrying capacity and the largest permanent population; SSP5 will have the lowest energy carrying capacity and the highest environmental carrying capacity. (4) Under the SSP1 scenario, the LXUA will exhibit a balanced pattern of non-overload across the whole region. By contrast, the other scenarios will demonstrate a core-periphery spatial distribution pattern of “poor in the middle and excellent at the periphery”. [Conclusion] In the future, based on the SSP1 development path, resources and environmental carrying risks should be addressed from the two aspects of adaptive construction of urban development pattern and dynamic improvement of carrying potential, so as to promote the coordinated development of human-nature relationship.
Keywords
