Collaborative optimization of particulate matter pollution reduction between urban transport and pocket parks: A mobile monitoring and novel inverse network DEA approach

IF 13.3 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society Pub Date : 2026-03-01 Epub Date: 2026-01-22 DOI:10.1016/j.scs.2026.107171

Jiqiang Zhao , Le Zhan , Hongmei Zhao , Lijun Cheng , Hongdi He

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引用次数: 0

Abstract

Although pocket parks play an important role in mitigating traffic-related pollution and improving urban microenvironments, the resource allocation pathways for their collaborative emission reduction with transportation systems remain unclear. For the first time, this study integrates micro-scale mobile monitoring with an Inverse Network Data Envelopment Analysis (DEA) framework to systematically characterize the collaborative emission reduction mechanism between traffic emissions and pocket park purification, and to propose an efficiency-constrained optimal resource allocation pathway. Using 30 representative pocket parks in Yuhang District, Hangzhou, as case studies, a two-stage network DEA model linking traffic emissions and park purification was constructed and further extended into an inverse network DEA model to optimally estimate input–output adjustments under different emission reduction targets. The results reveal that: (1) particulate matter (PM) concentrations exhibit a distinct spatial attenuation pattern within parks, with the strongest reduction occurring within 10 meters of the road edge; (2) output-oriented efficiency is generally higher than input-oriented efficiency, indicating that enhancing collaborative emission reduction performance depends more on activating output potential and management efficiency rather than simply increasing inputs; and (3) under constant system efficiency, achieving a 5% increase in PM reduction requires an average 5.71% increase in input resources, among which greening ratio demonstrates the highest marginal benefit and serves as a key driver for improving synergistic performance. This study extends the application of inverse DEA models to the micro-scale environmental domain and provides a methodological framework and empirical evidence for refined resource allocation in transportation–green space collaborative emission reduction.

查看原文本刊更多论文

城市交通与袖珍公园的协同优化：移动监测与新型逆网络DEA方法

尽管袖珍公园在缓解交通污染和改善城市微环境方面发挥着重要作用，但其与交通系统协同减排的资源配置路径尚不明确。本研究首次将微尺度移动监测与反网络数据包络分析（DEA）框架相结合，系统表征交通排放与口袋公园净化协同减排机制，并提出效率约束下的资源最优配置路径。以杭州市余杭区30个具有代表性的口袋公园为例，构建交通排放与公园净化的两阶段网络DEA模型，并将其扩展为逆网络DEA模型，以最优估计不同减排目标下的投入产出调整。结果表明：①公园内颗粒物（PM）浓度呈现明显的空间衰减规律，在距离道路边缘10 m范围内下降幅度最大；(2)产出导向效率普遍高于投入导向效率，表明提高协同减排绩效更多地依赖于激活产出潜力和管理效率，而不是简单地增加投入；(3)在系统效率不变的情况下，每增加5%的PM减排，平均需要增加5.71%的投入资源，其中绿化率的边际效益最高，是提高协同绩效的关键驱动力。本研究将逆DEA模型的应用扩展到微观尺度环境领域，为交通—绿地协同减排的资源精细化配置提供了方法框架和经验证据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

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;