基于网络的环境承载力与多重环境足迹的系统整合调控区域资源环境效应

IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Yizhong Chen , Lingzhi Yang , Lan Yao , Jing Li
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引用次数: 0

摘要

本文从多因素视角考察了京津冀城市群的资源环境效应(REE),在不确定条件下对基于水陆能粮关系和多重环境足迹的过去-未来环境承载力(ECC)进行了评价。利用三维魔方模型将区域划分为不同的单元进行稀土调控。结果表明,未来三季稀土元素和环境压力(EEP)将持续增加,分别增长9.92%和5.38%。ECC仍处于适度不和谐的状态,其轨迹预计将从过去的增长转向未来的下降。土地子系统和能源子系统是制约资源环境改善的主要因素,分别占总REE的51.39%和27.95%。城市群北部地区稀土元素含量高于南部地区。不确定性分析表明,降低指标阈值可提高整体ECC和REE,其变化幅度分别为+ 7%和- 5%。相比之下,增加阈值会导致显著的退化,变化分别为- 23%和+ 26%。值得注意的是,能源子系统对这些调整表现出相反的反应。秦皇岛、张家口、承德、廊坊、衡水等地应优先调控高REE、低ECC(高EEP)特征。北京和天津的稀土元素总量相对较低;然而,其水、土地和粮食子系统的承载能力对区域发展构成潜在风险。研究结果可为保障资源安全、促进人类活动与自然和谐发展提供科学依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Regulating regional resource environmental effect through systematic integration of nexus-based environmental carrying capacity and multiple environmental footprints
This study investigates the resource environmental effect (REE) in the Beijing–Tianjin–Hebei urban agglomeration from a multi-factor perspective, in which the past-to-future environmental carrying capacity (ECC) based on water–land–energy–food nexus and multiple environmental footprints are evaluated under uncertainty. The three-dimensional Rubik’s cube model is utilized to categorize the region into distinct units for REE regulation. Results reveal a sustained increase in REE and environmental pressure (EEP), growing by 9.92 % and 5.38 % in the future, respectively. The ECC remains in a moderately disharmonious state, with its trajectory expected to shift from past growth to future decline. Land and energy subsystems are the primary constraints on resource and environmental improvement, contributing 51.39 % and 27.95 % to the total REE, respectively. The urban agglomeration’s northern area exhibits a higher REE than the southern area. Uncertainty analysis reveals that lowering the indicator threshold improves the overall ECC and REE, which change by +7 % and –5 %, respectively. In contrast, increasing the threshold leads to a notable degradation, with changes of –23 % and +26 %, respectively. Notably, the energy subsystem demonstrates opposite responses to these adjustments. Qinhuangdao, Zhangjiakou, Chengde, Langfang, and Hengshui characterized by high REE and low ECC (high EEP) should be prioritized for regulation. The overall REE in Beijing and Tianjin is relatively low; however, the carrying capacity of their water, land, and food subsystems poses a potential risk to regional development. These findings can offer a scientific basis for safeguarding resource security and fostering harmony between human activities and nature.
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来源期刊
Sustainable Cities and Society
Sustainable Cities and Society Social Sciences-Geography, Planning and Development
CiteScore
22.00
自引率
13.70%
发文量
810
审稿时长
27 days
期刊介绍: Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including: 1. Smart cities and resilient environments; 2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management; 3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management); 4. Energy efficient, low/zero carbon, and green buildings/communities; 5. Climate change mitigation and adaptation in urban environments; 6. Green infrastructure and BMPs; 7. Environmental Footprint accounting and management; 8. Urban agriculture and forestry; 9. ICT, smart grid and intelligent infrastructure; 10. Urban design/planning, regulations, legislation, certification, economics, and policy; 11. Social aspects, impacts and resiliency of cities; 12. Behavior monitoring, analysis and change within urban communities; 13. Health monitoring and improvement; 14. Nexus issues related to sustainable cities and societies; 15. Smart city governance; 16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society; 17. Big data, machine learning, and artificial intelligence applications and case studies; 18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems. 19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management; 20. Waste reduction and recycling; 21. Wastewater collection, treatment and recycling; 22. Smart, clean and healthy transportation systems and infrastructure;
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