Exploring regional spatiotemporal dynamic evolution of urban road PM2.5 by integrating road network modeling and mobile monitoring data
文献类型：期刊论文
| 作者 | Xin, Rui2; Hou, Songji2; Pan, Jiale2; Wang, Jiaoe3,4; Hou, Chuanying1 |
| 刊名 | CITIES
 |
| 出版日期 | 2026-03-01 |
| 卷号 | 170页码:106648 |
| 关键词 | Mobile monitoring Urban road pollution Community detection Community evolution PM2.5 |
| ISSN号 | 0264-2751 |
| DOI | 10.1016/j.cities.2025.106648 |
| 产权排序 | 2 |
| 文献子类 | Article |
| 英文摘要 | With the rapid development of urbanization and motorization, urban road space has become a significant accumulation area of air pollution, posing higher demands for fine monitoring and regional partitioning of PM2.5 pollution under urban environmental governance. To overcome the low spatial resolution of fixed monitoring and the limitations of static partitioning in capturing pollution dynamics, this paper proposes a novel method for detecting the dynamic evolution of urban road PM2.5 pollution communities based on taxi mobile monitoring data. Urban roads are modelled as a weighted dual graph, and the Infomap algorithm combined with the consensus clustering algorithm is employed to identify pollution communities across different time periods. Evolution rules are designed to define and detect various dynamic evolution patterns of communities, and based on this, the mechanisms behind these evolutions are explored. The method was validated using real data from Jinan, China. The results indicate that pollution distribution patterns undergo significant changes driven by the daily rhythms of human mobility. Split communities during the morning peak exhibit linear diffusion along major commuting corridors, whereas those in the evening peak are more spatially fragmented and strongly associated with commercial activities. In addition, three primary evolution types are identified-growth-shrinkage (industrial zones), split-merge (commercial areas or traffic corridors), and continuation (urban periphery). This study achieves an innovative shift from static partitioning to dynamic evolution, providing support for the formulation of refined urban air pollution control policies. |
| URL标识 | 查看原文 |
| WOS研究方向 | Urban Studies |
| 语种 | 英语 |
| WOS记录号 | WOS:001613078200001 |
| 出版者 | ELSEVIER SCI LTD |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/217740]  |
| 专题 | 区域可持续发展分析与模拟院重点实验室_外文论文 |
| 通讯作者 | Wang, Jiaoe |
| 作者单位 | 1.Engineer Jinan Municipal Digital Applicat Ctr Ecol, Jinan 250102, Peoples R China 2.Shandong Univ Sci & Technol, Coll Geodesy & Geomat, Qingdao 266590, Peoples R China; 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China; 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Xin, Rui,Hou, Songji,Pan, Jiale,et al. Exploring regional spatiotemporal dynamic evolution of urban road PM2.5 by integrating road network modeling and mobile monitoring data[J]. CITIES,2026,170:106648. |
| APA | Xin, Rui,Hou, Songji,Pan, Jiale,Wang, Jiaoe,&Hou, Chuanying.(2026).Exploring regional spatiotemporal dynamic evolution of urban road PM2.5 by integrating road network modeling and mobile monitoring data.CITIES,170,106648. |
| MLA | Xin, Rui,et al."Exploring regional spatiotemporal dynamic evolution of urban road PM2.5 by integrating road network modeling and mobile monitoring data".CITIES 170(2026):106648. |
入库方式： OAI收割
来源：地理科学与资源研究所
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