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Spatiotemporal Evolution of Territorial Spaces and Its Effect on Carbon Emissions in Qingdao City, China

Author

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  • Jiali He

    (College of Resources and Environment, Shandong Agricultural University, Tai’an 271018, China
    These authors contributed equally to this work.)

  • Xiangfei Liu

    (College of Resources and Environment, Shandong Agricultural University, Tai’an 271018, China
    These authors contributed equally to this work.)

  • Xuetong Wang

    (College of Resources and Environment, Shandong Agricultural University, Tai’an 271018, China)

  • Xueyang Li

    (College of Resources and Environment, Shandong Agricultural University, Tai’an 271018, China)

  • Linger Yu

    (College of Resources and Environment, Shandong Agricultural University, Tai’an 271018, China)

  • Beibei Niu

    (College of Resources and Environment, Shandong Agricultural University, Tai’an 271018, China)

Abstract

Land use change has always been a significant factor affecting global carbon emissions. Dissecting the characteristics of territorial space evolution and its impact on carbon emissions is crucial for developing low-carbon-oriented territorial space optimization and governance strategies. This paper calculates the carbon emissions associated with territorial spaces in Qingdao from 2000 to 2020, utilizing land use data alongside various statistical data. Based on the accounting results, the evolution characteristics of territorial spaces and their corresponding carbon emissions, as well as the carbon transition dynamics resulting from space transfer, are analyzed. A carbon transition decomposition formula is then proposed to quantify the differential and spatially heterogeneous impacts of changes in space types and socio-economic development on emissions. The results indicate that: (1) the evolution of territorial spaces in Qingdao during 2000–2020 is characterized by an expansion of living space and a contraction of production and ecological spaces; (2) net carbon emissions rose from 313.98 × 10 4 tons to 1068.58 × 10 4 tons, with urban production space contributing the most (69.96% in 2020) due to its significantly high emission density. The spatial distribution of carbon emissions exhibited a stable “northwest–southeast” pattern, with increased dispersion and weakened directionality; (3) the transformation of territorial spaces promoted carbon emissions in Qingdao, with the conversion of urban production space to other uses yielding the most favorable carbon transitions, while the expropriation of agricultural production spaces for urban production and residents’ living has resulted in the most detrimental carbon transitions; (4) socio-economic development shapes the overarching pattern of regional emission density changes, whereas space transfers account for local variations. This paper also identifies priorities for spatial optimization and key sectors for emission reduction. The findings contribute to a deeper understanding of the carbon emission consequences of territorial space transformation in Qingdao, thereby providing valuable insights for regional spatial planning and optimization aimed at promoting low-carbon development.

Suggested Citation

  • Jiali He & Xiangfei Liu & Xuetong Wang & Xueyang Li & Linger Yu & Beibei Niu, 2024. "Spatiotemporal Evolution of Territorial Spaces and Its Effect on Carbon Emissions in Qingdao City, China," Land, MDPI, vol. 13(10), pages 1-22, October.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:10:p:1717-:d:1502604
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    References listed on IDEAS

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    Cited by:

    1. Mengqi Liu & Yang Yu & Maomao Zhang & Pengtao Wang & Nuo Shi & Yichen Ren & Di Zhang, 2025. "Carbon Balance Matching Relationships and Spatiotemporal Evolution Patterns in China’s National-Level Metropolitan Areas," Land, MDPI, vol. 14(4), pages 1-26, April.
    2. Liangzhao Chen & Peng Tang & Jinhua Li & Junming Li, 2025. "Assessment of Low-Carbon Utilization in Territorial Space and Identification of Its Driving Factors: A Case Study of the Yangtze River Economic Belt in China," Land, MDPI, vol. 14(4), pages 1-31, March.

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