促进 CCUS 项目的可持续发展:多源数据驱动的选址决策优化框架

IF 10.5 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
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引用次数: 0

摘要

碳捕集、利用和封存(CCUS)技术对于实现全球碳减排目标至关重要。然而,技术和经济可行性的不确定性受到选址的影响。为促进 CCUS 技术的可持续发展,本研究提出了一个数据驱动的选址优化决策框架。首先,该框架考虑了多种因素,包括有关资源、风险、电力生产、交通和环境的地理空间数据。该框架还评估了经济、社会、环境和技术等方面的定性和定量数据。其次,采用以下两阶段模型:第一阶段利用地理信息系统(GIS)技术确定适合开展 CCUS 项目的地区,第二阶段利用 TODIM 方法确定这些地区的优先次序。经过验证,中国的准噶尔盆地、塔里木盆地、鄂尔多斯盆地、四川盆地和环渤海盆地适合开展 CCUS 项目。华能珞璜电厂是最适合开展 CCUS 项目试点示范的地点。最后的敏感性分析、情景分析和比较分析分别肯定了模型的稳定性、动态性和可靠性。这些分析还有助于阐明各种决策偏好和战略取向下的最终优选结果。本研究提出的 CCUS 项目布局决策框架和数据驱动优先模型可为决策者规划 CCUS 项目和制定支持政策提供技术支持和实践依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Promoting the sustainable development of CCUS projects: A multi-source data-driven location decision optimization framework

Carbon Capture, Utilization, and Storage (CCUS) technology is vital for achieving global carbon reduction targets. However, the uncertainties in technology and economic viability are influenced by location. To promote the sustainable development of CCUS technology, the study proposes a data-driven framework for optimizing location decisions. Firstly, the framework considers multiple factors, including geospatial data on resources, risks, power production, transportation, and environment. It also evaluates qualitative and quantitative data across economic, social, environmental, and technological dimensions. Secondly, the two-stage model is conducted as follows: Using Geographic Information System (GIS) technology, the first stage identifies suitable regions for CCUS projects, while the second stage prioritizes these regions using the TODIM method. Further, validated in China, the Junggar Basin, Tarim Basin, Ordos Basin, Sichuan Basin, and Bohai Rim Basin are identified as suitable for CCUS deployment. The Huaneng Luohuang Power Plant is the most conducive location for CCUS projects as pilot demonstrations. Final sensitivity analysis, scenario analysis, and comparative analysis have respectively affirmed the stability, dynamism, and reliability of the model. These analyses have also been instrumental in elucidating the final preferred outcomes under various decision-making preferences and strategic orientations. The framework for decision-making and data-driven priority model for CCUS projects layout proposed in the study can provide technical support and practical evidence for decision-makers in planning CCUS projects and formulating supportive policies.

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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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