ORIGINAL RESEARCH article
Front. Public Health
Sec. Environmental Health and Exposome
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1645402
Built Environment and Residential Blocks Carbon Emissions: A Study Using Advanced Metering Infrastructure Data
Provisionally accepted
- 1College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China, Shanghai, China
- 2School of Architecture and Urban Planning, Shandong Jianzhu University, Jinan 250101, China, Jinan, China
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Focusing on the carbon emissions mechanism of micro-scale residential blocks (RBs), this study takes 99 RBs in Hongqiao District, Tianjin as samples, integrates spatial statistical analysis and high precision machine learning models, and systematically reveals the spatial-temporal evolution law, spatial differentiation characteristics and the driving mechanism of the built environmental elements (BEF) on residential blocks carbon emissions (RBCE). Key findings include: (1) From 2021 to 2023, both the RBCE and residential blocks carbon emissions intensity (RBCEI) showed a "first rise then fall" fluctuation, with an overall 5.7% increase, signaling sustained emissions reduction pressure. (2) High emissions areas are spatially concentrated and contagious, while low carbon units are mostly peripheral. Spatial autocorrelation analysis indicates a significant positive correlation and a west-south clustering pattern. (3) Land area (LA) is the primary emissions affecting factor, followed by the green space ratio (GSR), whose inhibitory effect surpasses traditional high intensity development indicators. Land use mixing degree (LMD) is also valuable for emissions reduction. (4) Targeted planning strategies are proposed, such as strictly controlling land use expansion, boosting GSR, and promoting functional mix. These strategies offer micro scale solutions to the implementation challenges of macro emission reduction policies. Overall, the study deepens the theoretical understanding of the relationship between BEF and RBCE, providing a scientific foundation for low carbon community planning and renewal. These strategies not only provide a basis for the implementation of macro emission reduction policies, but also offer solutions for micro action plans centered on residents' mental health and cardiopulmonary system protection. Overall, this study has deepened the theoretical understanding of the relationship between BEF and RBCE, providing a scientific basis for the planning and renewal of low-carbon RBs that balance carbon reduction and health benefits.
Keywords: Built environment factors (BEF)1, residential blocks carbon emissions (RBCE) 2, Random forest model3, influence mechanism4, Tianjin5
Received: 11 Jun 2025; Accepted: 05 Aug 2025.
Copyright: © 2025 Zhang, Cui, Feng, Wen, Xiao and Ni. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Xiaoping Zhang, College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China, Shanghai, China
Jianbo Ni, School of Architecture and Urban Planning, Shandong Jianzhu University, Jinan 250101, China, Jinan, China
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