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Effects of Land Urbanization on Smog Pollution in China: Estimation of Spatial Autoregressive Panel Data Models

Author

Listed:
  • Xuan Yu

    (Business School, Ningbo University, Ningbo 315211, China)

  • Manhong Shen

    (Business School, Ningbo University, Ningbo 315211, China
    College of Economics and Management, Zhejiang A&F University, Hangzhou 311300, China)

  • Weiteng Shen

    (Business School, Ningbo University, Ningbo 315211, China)

  • Xiao Zhang

    (Business School, Ningbo University, Ningbo 315211, China)

Abstract

Studying the impact of land urbanization on smog pollution has important guiding significance for the sustainable development of cities. This study adds the spatial effect between regions into the research framework of smog pollution control in China. On the basis of a panel dataset of 31 province-level administrative regions in China from 2000 to 2017, we investigate the impact of land urbanization on smog pollution. We construct a spatial weight matrix and use Moran’s I statistic and the spatial autoregressive panel data model. The research results show that land urbanization and smog pollution have an inverted U-shaped relationship. With the advancement of land urbanization, the area’s smog pollution first increases and then decreases. However, in general, China has not passed the inflection point and is still at a stage where increasing land urbanization rate aggravates smog pollution. Moreover, the country’s smog pollution has a significant spatial positive correlation that shows agglomeration. In that context, multiple environmental governance entities, including the government, enterprises, and the public, need to collaborate on measures to reduce smog pollution. Future urban construction in China will need to integrate solutions that address the current nexus between urbanization and smog pollution to achieve green and sustainable development.

Suggested Citation

  • Xuan Yu & Manhong Shen & Weiteng Shen & Xiao Zhang, 2020. "Effects of Land Urbanization on Smog Pollution in China: Estimation of Spatial Autoregressive Panel Data Models," Land, MDPI, vol. 9(9), pages 1-16, September.
    • Handle: RePEc:gam:jlands:v:9:y:2020:i:9:p:337-:d:417170
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    References listed on IDEAS

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    Cited by:

    1. Kai Yuan & Yabing Qin & Chenlu Wang & Zihao Li & Tingting Bai, 2023. "Balance between Smog Control and Economic Growth in China: Mechanism Analysis Based on the Effect of Green Technology Innovation," IJERPH, MDPI, vol. 20(2), pages 1-19, January.
    2. Ammar Javed & Farheen Aamir & Umar Farooq Gohar & Hamid Mukhtar & Muhammad Zia-UI-Haq & Modhi O. Alotaibi & May Nasser Bin-Jumah & Romina Alina Marc (Vlaic) & Oana Lelia Pop, 2021. "The Potential Impact of Smog Spell on Humans’ Health Amid COVID-19 Rages," IJERPH, MDPI, vol. 18(21), pages 1-19, October.
    3. Gao, Feng & Lin, Yijie & Zhang, Xuanming & Li, Shanhong & Lv, Yanqin, 2023. "Interconnectedness between land resource misallocation and environmental pollution: Exploring the sustainable development potential in China," Resources Policy, Elsevier, vol. 86(PB).
    4. Huang, Danyang & Hu, Wei & Jing, Bingyi & Zhang, Bo, 2023. "Grouped spatial autoregressive model," Computational Statistics & Data Analysis, Elsevier, vol. 178(C).
    5. Zhiyang Shen & Yunlong Zhang & Kaifa Wu & Muhammad Irfan & Yu Hao, 2024. "The Environmental Consequences of Local Government Competition: Evidence from 209 Chinese Cities," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2115-2137, June.
    6. Yao, Yourong & Shen, Yue & Liu, Kexin, 2023. "Investigation of resource utilization in urbanization development: An analysis based on the current situation of carbon emissions in China," Resources Policy, Elsevier, vol. 82(C).
    7. Yanjun Meng & Kun Wang & Yuanyuan Lin, 2021. "The Role of Land Use Transition on Industrial Pollution Reduction in the Context of Innovation-Driven: The Case of 30 Provinces in China," Land, MDPI, vol. 10(4), pages 1-20, April.

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