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Spatiotemporally Heterogeneous Effects of Urban Landscape Pattern on PM 2.5 : Seasonal Mechanisms in Urumqi, China

Author

Listed:
  • Xingchi Zhou

    (School of Resources and Geosciences, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China)

  • Yantao Xi

    (School of Resources and Geosciences, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China)

  • Shuangqiao Wang

    (Xi’an Meihang Remote Sensing Information Co., Ltd., Xi’an 710199, China)

  • Yuanfan Zhang

    (School of Resources and Geosciences, China University of Mining and Technology, Daxue Road 1, Xuzhou 221116, China)

Abstract

PM 2.5 pollution presents a significant risk to urban habitability. The urban landscape pattern (ULP) serves as a crucial regulator that profoundly influences the spatiotemporal distribution features of PM 2.5 . Analysis of the driving mechanisms of the ULP is therefore essential for optimizing urban ecological spatial planning. However, the driving mechanism is dynamic and exhibits seasonal variations. This study selected four landscape metrics and four control variables, developed a geographically and temporally weighted regression (GTWR) model, and examined the spatiotemporal and seasonal effects of ULP on PM 2.5 concentrations in the central urban area of Urumqi (CUA) from 2003 to 2023. The results show the following: (1) Over the past two decades, the four ULP metrics have shown an increasing trend in the CUA. (2) The spatial distribution of PM 2.5 concentrations follows a latitudinal gradient, with higher concentrations observed in the northern regions and lower concentrations in the southern regions, initially increasing and then declining over time. (3) The driving mechanisms of ULP on PM 2.5 exhibited significant variations across different locations and time scales. (4) Seasonal variations arise from pronounced meteorological contrasts and intensified pollution from central heating, which is particularly evident in central CUA.

Suggested Citation

  • Xingchi Zhou & Yantao Xi & Shuangqiao Wang & Yuanfan Zhang, 2025. "Spatiotemporally Heterogeneous Effects of Urban Landscape Pattern on PM 2.5 : Seasonal Mechanisms in Urumqi, China," Land, MDPI, vol. 14(6), pages 1-22, May.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:6:p:1184-:d:1668554
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    References listed on IDEAS

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    1. Arturs Kalnins, 2018. "Multicollinearity: How common factors cause Type 1 errors in multivariate regression," Strategic Management Journal, Wiley Blackwell, vol. 39(8), pages 2362-2385, August.
    2. Yuanyuan Chen & Xinli Ke & Min Min & Yue Zhang & Yaqiang Dai & Lanping Tang, 2022. "Do We Need More Urban Green Space to Alleviate PM 2.5 Pollution? A Case Study in Wuhan, China," Land, MDPI, vol. 11(6), pages 1-16, May.
    3. Rui Wang & Qi Chen & Dexiang Wang, 2022. "Effects of Altitude, Plant Communities, and Canopies on the Thermal Comfort, Negative Air Ions, and Airborne Particles of Mountain Forests in Summer," Sustainability, MDPI, vol. 14(7), pages 1-22, March.
    4. Huicai Yang & Jingtao Ma & Xinying Jiao & Guofei Shang & Haiming Yan, 2023. "Characteristics and Driving Mechanism of Urban Construction Land Expansion along with Rapid Urbanization and Carbon Neutrality in Beijing, China," Land, MDPI, vol. 12(7), pages 1-17, July.
    5. Mingyue Jiang & Yizhen Wu & Zhijian Chang & Kaifang Shi, 2021. "The Effects of Urban Forms on the PM 2.5 Concentration in China: A Hierarchical Multiscale Analysis," IJERPH, MDPI, vol. 18(7), pages 1-16, April.
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