基于种植强度的福州市都市农业蔬菜产量及碳减排效益估算

IF 12 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Qunyue Liu , Zhiqian Lin , Taoyu Chen , Ni Zhang , Zubin Ye , Yourui Guo , Yaling Gao , Yuanping Shen , Weicong Fu , Yuanjing Wu
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引用次数: 0

摘要

城市农业可以增强粮食系统的抵御力,同时减少与长途粮食运输有关的碳排放。然而,评估其在不同种植情景下的生产潜力和缓解效益仍然具有挑战性。本研究开发了一个综合框架,将基于gis的土地适宜性分析、多准则决策(MCDM)和反硝化分解(DNDC)模型相结合。以中国福州为例,该框架确定了分散但适合UA的空间,并评估了集约化、半集约化和粗放化种植情景下特定作物的权衡。结果表明,城市核心区内适宜用地稀缺,高度适宜用地仅为41.32 hm2(0.24%),中度适宜用地为139.82 hm2(0.81%),轻度适宜用地为1509.74 hm2(8.7%)。情景模拟显示,减缓结果有很强的梯度。当地蔬菜种植每年可减少CO₂排放量,集约种植586.14 t,半集约种植2569.46 t,粗放种植23985 t。生菜提供了最大的运输相关减排,番茄结合了强大的封存潜力和更高的生产排放,马铃薯贡献不大,但支持饮食多样性。该研究强调了在多情景框架中整合作物生长、运输避免和生产排放的价值。研究结果为扩大UA规模提供了与政策相关的见解,包括促进半集约化战略、有针对性的作物分配以及屋顶利用规则、碳信用激励和电气化物流等支持性措施。更广泛地说,该框架为寻求将粮食安全与碳中和目标结合起来的城市提供了可转让的工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating the vegetable yield and carbon reduction benefits of urban agriculture in Fuzhou based on planting intensity
Urban agriculture (UA) can enhance food system resilience while reducing carbon emissions linked to long-distance food transport. Yet assessing its production potential and mitigation benefits across diverse planting scenarios remains challenging. This study develops an integrated framework that combines GIS-based land suitability analysis, multi-criteria decision making (MCDM), and the Denitrification-Decomposition (DNDC) model. Using Fuzhou, China as a case study, the framework identifies fragmented yet suitable spaces for UA and evaluates crop-specific trade-offs under intensive, semi-intensive, and extensive planting scenarios. The results reveal that suitable land within the urban core is scarce, with only 41.32 hm2 (0.24%) classified as highly suitable, 139.82 hm2 (0.81%) as moderately suitable, and 1509.74 hm2 (8.7%) as slightly suitable. Scenario simulations show strong gradients in mitigation outcomes. Local vegetable cultivation could reduce CO₂ emissions by 586.14 t under intensive planting, 2569.46 t under semi-intensive planting, and 23,985 t under extensive planting each year. Lettuce provides the largest transport-related reductions, tomato combines strong sequestration potential with higher production emissions, and potato contributes modestly but supports dietary diversity. The study highlights the value of integrating crop growth, transport avoidance, and production emissions in a multi-scenario framework. The findings provide policy-relevant insights for scaling UA, including the promotion of semi-intensive strategies, targeted crop allocation, and supportive measures such as rooftop utilization rules, carbon-credit incentives, and electrified logistics. More broadly, the framework offers transferable tools for cities seeking to align food security with carbon neutrality goals.
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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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