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Atmosphere
Special Issues
Urban Carbon Emissions: Measurement and Modeling
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Urban Carbon Emissions: Measurement and Modeling

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality".

Deadline for manuscript submissions: 31 December 2025 | Viewed by 446

Special Issue Editors

Dr. Ji Zheng

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Guest Editor
1. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2. Department of Urban Planning and Design, The University of Hong Kong, Hong Kong SAR, China
Interests: methods for estimating urban transport carbon emissions; urban CO2 flux observations; evaluation of urban ETS
Special Issues, Collections and Topics in MDPI journals
Dr. Yingjie Hu

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Guest Editor
College of City Construction, Jiangxi Normal University, Nanchang 330022, China
Interests: carbon footprint; agricultural carbon emission; sustainable development
Special Issues, Collections and Topics in MDPI journals
Dr. Yifu Ou

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Guest Editor
School of Energy, Geoscience, Infrastructure, and Society, Heriot-Watt University, Edinburgh, UK
Interests: transport and land use planning; urban sustainability; environmental economics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Urban areas are significant contributors to global carbon emissions. As cities continue to expand, it is imperative to comprehend and address carbon emissions from urban areas towards global carbon neutrality. This Special Issue, “Urban Carbon Emissions: Measurement and Modeling”, seeks to explore cutting-edge methodologies and emerging technologies for the quantification of, analysis of, and reduction in urban carbon emissions. It aims to integrate interdisciplinary insights from environmental science, urban planning, transportation, and data science to foster a holistic understanding of urban carbon emissions.

Topics of interest of the Special Issue include, but are not limited to, the following:

  • Advanced technologies and methodologies for measuring urban carbon emissions;
  • Innovative modeling and simulation techniques for urban carbon emissions;
  • Quantification of carbon emissions from urban transportation systems;
  • Assessment of carbon emissions from changes in urban land use.

This Special Issue serves as a platform for researchers, policymakers, and practitioners to share insights and advancements in the measurement and modeling of urban carbon emissions. We welcome original research articles, reviews, and case studies that contribute to the advancement of urban carbon emissions research.

Dr. Ji Zheng
Dr. Yingjie Hu
Dr. Yifu Ou
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • urban carbon emissions
  • emission quantification techniques
  • measurement and modeling
  • urban transportation emissions
  • land use and carbon emissions
  • sustainable urban development

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Published Papers (1 paper)

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Research

23 pages, 15077 KB  
Article
Landscape Patterns and Carbon Emissions in the Yangtze River Basin: Insights from Ensemble Models and Nighttime Light Data
by Banglong Pan, Qi Wang, Zhuo Diao, Jiayi Li, Wuyiming Liu, Qianfeng Gao, Ying Shu and Juan Du
Atmosphere 2025, 16(10), 1173; https://doi.org/10.3390/atmos16101173 - 9 Oct 2025
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Abstract
Land use patterns are a critical driver of changes in carbon emissions, making it essential to elucidate the relationship between regional carbon emissions and land use types. As a nationally designated economic strategic zone, the Yangtze River Basin encompasses megacities, rapidly developing medium-sized [...] Read more.
Land use patterns are a critical driver of changes in carbon emissions, making it essential to elucidate the relationship between regional carbon emissions and land use types. As a nationally designated economic strategic zone, the Yangtze River Basin encompasses megacities, rapidly developing medium-sized cities, and relatively underdeveloped regions. However, the mechanism underlying the interaction between landscape patterns and carbon emissions across such gradients remains inadequately understood. This study utilizes nighttime light, land use and carbon emissions datasets, employing XGBoost, CatBoost, LightGBM and a stacking ensemble model to analyze the impacts and driving factors of land use changes on carbon emissions in the Yangtze River Basin from 2002 to 2022. The results showed: (1) The stacking ensemble learning model demonstrated the best predictive performance, with a coefficient of determination (R2) of 0.80, a residual prediction deviation (RPD) of 2.22, and a root mean square error (RMSE) of 4.46. Compared with the next-best models, these performance metrics represent improvements of 19.40% in R2 and 28.32% in RPD, and a 22.16% reduction in RMSE. (2) Based on SHAP feature importance and Pearson correlation analysis, the primary drivers influencing CO2 net emissions in the Yangtze River Basin are GDP per capita (GDPpc), population density (POD), Tertiary industry share (TI), land use degree comprehensive index (LUI), dynamic degree of water-body land use (Kwater), Largest patch index (LPI), and number of patches (NP). These findings indicate that changes in regional landscape patterns exert a significant effect on carbon emissions in strategic economic regions, and that stacked ensemble models can effectively simulate and interpret this relationship with high predictive accuracy, thereby providing decision support for regional low-carbon development planning. Full article
(This article belongs to the Special Issue Urban Carbon Emissions: Measurement and Modeling)
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