Constructing Generalized Local Carbon Emission Zones (Lcezs): A 2d/3d Urban Morphology Clustering Framework for Low-Carbon Planning

46 Pages Posted: 25 Apr 2025

See all articles by Jiaheng Ju

Jiaheng Ju

University of Nottingham, Ningbo - University of Nottingham Ningbo China

Shudi Zuo

affiliation not provided to SSRN

Wu Deng

University of Nottingham - Department of Architecture and Built Environment

Runqi Liang

affiliation not provided to SSRN

Linjun Xie

University of Nottingham, Ningbo - University of Nottingham Ningbo China

Masoud Javadpoor

Shiraz University

Ayyoob Sharifi

Hiroshima University

Xiangyu Wang

affiliation not provided to SSRN

Yin Ren

affiliation not provided to SSRN

Abstract

The transition to low-carbon urbanisation is crucial for mitigating CO2 emissions. Previous research has characterised the low-carbon urban morphologies at the urban scale. However, there have been challenges in applying urban morphology control threshold values to achieve the goal of low CO2 emissions. This study introduces a novel approach by constructing Local carbon emissions zones (LCEZs) based on the general impact rules of urban form on residential and transport CO2 emissions (RTCE). After the downscaling process, geographically weighted regression was used to analyse the impact of 2D and 3D urban morphology factors on RTCE at a 123-meter resolution. Jenks Natural Breaks, K-means, and DBSCAN were applied to construct LCEZs. The Geodetecter model assessed the optimal cluster method and the representational performance of LCEZs, and their difference and consistency were tested and validated. The results showed that the degree of spatial congestion was the most significant influence of the seven urban morphology factors on RTCE. The impact of road length was the least. The Natural break method emerged as the most effective clustering technique for LCEZs construction. Building coverge ratio, Mean building height, and Road length were the most representative factors for RTCE in urban centres. Additionally, we analysed the variations and consistencies among LCEZs across 24 urban centres to validate the construct of LCEZs. Finally, suggestions for low-carbon urban construction were proposed based on the proportion of RTCE cold spots in different functional areas across various LCEZs.

Keywords: Cities, Urban morphology, Climate change mitigation, machine learning, GWR, GeoDetector

Suggested Citation

Ju, Jiaheng and Zuo, Shudi and Deng, Wu and Liang, Runqi and Xie, Linjun and Javadpoor, Masoud and Sharifi, Ayyoob and Wang, Xiangyu and Ren, Yin, Constructing Generalized Local Carbon Emission Zones (Lcezs): A 2d/3d Urban Morphology Clustering Framework for Low-Carbon Planning. Available at SSRN: https://ssrn.com/abstract=5230875 or http://dx.doi.org/10.2139/ssrn.5230875

Jiaheng Ju

University of Nottingham, Ningbo - University of Nottingham Ningbo China ( email )

199 Taikang East Road
Ningbo, 315100
China

Shudi Zuo (Contact Author)

affiliation not provided to SSRN ( email )

No Address Available

Wu Deng

University of Nottingham - Department of Architecture and Built Environment ( email )

Runqi Liang

affiliation not provided to SSRN ( email )

No Address Available

Linjun Xie

University of Nottingham, Ningbo - University of Nottingham Ningbo China ( email )

199 Taikang East Road
Ningbo, 315100
China

Masoud Javadpoor

Shiraz University ( email )

Eram Paradise
Shiraz 71454
Iran

Ayyoob Sharifi

Hiroshima University ( email )

Higashihiroshima, 739-0046
Japan

Xiangyu Wang

affiliation not provided to SSRN ( email )

No Address Available

Yin Ren

affiliation not provided to SSRN ( email )

No Address Available

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