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A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province

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  • Shen Zhao

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Guanpeng Dong

    (Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center for Yellow River Civilization, Henan University, Minglun Street 86, Kaifeng 475001, China)

  • Yong Xu

    (Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

Urbanization processes at both global and regional scales are taking place at an unprecedent pace, leading to more than half of the global population living in urbanized areas. This process could exert grand challenges on the human living environment. With the proliferation of remote sensing and satellite data being used in social and environmental studies, fine spatial- and temporal-resolution measures of urban expansion and environmental quality are increasingly available. This, in turn, offers great opportunities to uncover the potential environmental impacts of fast urban expansion. This paper investigated the relationship between urban expansion and pollutant emissions in the Fujian province of China by building a Bayesian spatio-temporal autoregressive model. It drew upon recently compiled pollutant emission data with fine spatio-temporal resolution, long temporal coverage, and multiple sources of remote sensing data. Our results suggest that there was a significant relationship between urban expansion and pollution emission intensity—urban expansion significantly elevated the PM 2.5 and NO x emissions intensity in Fujian province during 1995–2015. This finding was robust to different measures of urban expansion and retained after controlling for potential confounding effects. The temporal evolution of pollutant emissions, net of covariate effects, presented a fluctuation pattern rather than a consistent trend of increasing or decreasing. Spatial variability of the pollutant emissions intensity among counties was, however, decreasing steadily with time.

Suggested Citation

  • Shen Zhao & Guanpeng Dong & Yong Xu, 2020. "A Dynamic Spatio-Temporal Analysis of Urban Expansion and Pollutant Emissions in Fujian Province," IJERPH, MDPI, vol. 17(2), pages 1-15, January.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:2:p:629-:d:310386
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    References listed on IDEAS

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    1. Usama Al-Mulali & Ilhan Ozturk & Hooi Lean, 2015. "The influence of economic growth, urbanization, trade openness, financial development, and renewable energy on pollution in Europe," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 79(1), pages 621-644, October.
    2. Krugman, Paul, 1991. "Increasing Returns and Economic Geography," Journal of Political Economy, University of Chicago Press, vol. 99(3), pages 483-499, June.
    3. Klaus Desmet & Dávid Krisztián Nagy & Esteban Rossi-Hansberg, 2018. "The Geography of Development," Journal of Political Economy, University of Chicago Press, vol. 126(3), pages 903-983.
    4. Stef Proost & Jacques-François Thisse, 2019. "What Can Be Learned from Spatial Economics?," Journal of Economic Literature, American Economic Association, vol. 57(3), pages 575-643, September.
    5. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    6. Alastair Rushworth & Duncan Lee & Christophe Sarran, 2017. "An adaptive spatiotemporal smoothing model for estimating trends and step changes in disease risk," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(1), pages 141-157, January.
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    Cited by:

    1. Shen Zhao & Yong Xu, 2021. "Exploring the Dynamic Spatio-Temporal Correlations between PM 2.5 Emissions from Different Sources and Urban Expansion in Beijing-Tianjin-Hebei Region," IJERPH, MDPI, vol. 18(2), pages 1-18, January.

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