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How Does Density Impact Carbon Emission Intensity: Insights from the Block Scale and an Optimal Parameters-Based Geographical Detector

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  • Liutong Li

    (School of Architecture, Tianjin University, Tianjin 300072, China)

  • Fengying Yan

    (School of Architecture, Tianjin University, Tianjin 300072, China)

Abstract

Density is a crucial indicator for urban sustainable development and is considered a critical factor influencing the carbon emission intensity of construction land (CICL). The impact of density on carbon emissions has been extensively explored, mainly focusing on grid-scale and single-factor effects. However, how density and its interactions affect carbon emissions at the block scale is unclear. Therefore, based on multiple data sources such as energy consumption, remote sensing, and the point of interest (POI) in the urban block of Changxing County, this study constructed a density system that reflects the block’s physical environment and socioeconomic characteristics. An optimal-parameters-based geographical detector was employed to investigate the effects and interactions of density factors on the carbon emission intensity of residential blocks (CIRB), carbon emission intensity of commercial blocks (CICB), and carbon emission intensity of public blocks (CIPB). The results indicate the following: (1) The impact of density factors on different types of CICL varied significantly. Physical environmental factors (PEFs) had greater explanatory power than socioeconomic factors (SEFs) across the CIRB, CICB, and CIPB, with the floor area ratio (FAR) being the most influential. The spatial morphology of blocks also influenced the relationship between density factors and the CICL. (2) The interactions between the FAR and building density (BD), the FAR and commercial outlet density (COD), and the FAR and population density (PD) had the strongest explanatory power for the CIRB, CICB, and CIPB, respectively, and all exhibited nonlinear enhancements. Some factors exhibited more significant effects only when interacting with others. (3) An association chain encompassing the interactions of multiple density factors was extracted for the CIRB, CICB, and CIPB, respectively, as the basis for conducting collaborative management and control in spatial planning. The research findings can provide decision support for urban planners to consider the comprehensive effects of density factors and promote the development of low-carbon urban spaces.

Suggested Citation

  • Liutong Li & Fengying Yan, 2024. "How Does Density Impact Carbon Emission Intensity: Insights from the Block Scale and an Optimal Parameters-Based Geographical Detector," Land, MDPI, vol. 13(7), pages 1-18, July.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:7:p:1036-:d:1432492
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    References listed on IDEAS

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    1. Ian W.H. Parry & Roberton C. Williams III & Lawrence H. Goulder, 2002. "When Can Carbon Abatement Policies Increase Welfare? The Fundamental Role of Distorted Factor Markets," Chapters, in: Lawrence H. Goulder (ed.), Environmental Policy Making in Economies with Prior Tax Distortions, chapter 25, pages 471-503, Edward Elgar Publishing.
    2. Liddle, Brantley, 2013. "Urban density and climate change: a STIRPAT analysis using city-level data," Journal of Transport Geography, Elsevier, vol. 28(C), pages 22-29.
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    Cited by:

    1. Guangshun Zhang & Yi Su & Ziming Wang & Ying Chen & Jiangjun Wan & Haichao Bai, 2024. "Spatial–Temporal Evolution and Driving Force Analysis of Blue–Green Space in the Chengdu–Chongqing Economic Circle, China," Land, MDPI, vol. 13(11), pages 1-22, October.

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