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Impact of Land Use on PM 2.5 Pollution in a Representative City of Middle China

Author

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  • Haiou Yang

    (College of Forestry, Jiangxi Agricultural University, Nanchang 330045, China
    Key Laboratory of Landscape and Environment, Jiangxi Agricultural University, Nanchang 330045, China
    College of Tourism and Territorial Resources, Jiujiang University, Jiujiang 332005, China)

  • Wenbo Chen

    (Key Laboratory of Landscape and Environment, Jiangxi Agricultural University, Nanchang 330045, China)

  • Zhaofeng Liang

    (Key Laboratory of Landscape and Environment, Jiangxi Agricultural University, Nanchang 330045, China)

Abstract

Fine particulate matter (PM 2.5 ) pollution has become one of the greatest urban issues in China. Studies have shown that PM 2.5 pollution is strongly related to the land use pattern at the micro-scale and optimizing the land use pattern has been suggested as an approach to mitigate PM 2.5 pollution. However, there are only a few researches analyzing the effect of land use on PM 2.5 pollution. This paper employed land use regression (LUR) models and statistical analysis to explore the effect of land use on PM 2.5 pollution in urban areas. Nanchang city, China, was taken as the study area. The LUR models were used to simulate the spatial variations of PM 2.5 concentrations. Analysis of variance and multiple comparisons were employed to study the PM 2.5 concentration variances among five different types of urban functional zones. Multiple linear regression was applied to explore the PM 2.5 concentration variances among the same type of urban functional zone. The results indicate that the dominant factor affecting PM 2.5 pollution in the Nanchang urban area was the traffic conditions. Significant variances of PM 2.5 concentrations among different urban functional zones throughout the year suggest that land use types generated a significant impact on PM 2.5 concentrations and the impact did not change as the seasons changed. Land use intensity indexes including the building volume rate, building density, and green coverage rate presented an insignificant or counter-intuitive impact on PM 2.5 concentrations when studied at the spatial scale of urban functional zones. Our study demonstrates that land use can greatly affect the PM 2.5 levels. Additionally, the urban functional zone was an appropriate spatial scale to investigate the impact of land use type on PM 2.5 pollution in urban areas.

Suggested Citation

  • Haiou Yang & Wenbo Chen & Zhaofeng Liang, 2017. "Impact of Land Use on PM 2.5 Pollution in a Representative City of Middle China," IJERPH, MDPI, vol. 14(5), pages 1-14, April.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:5:p:462-:d:96854
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    References listed on IDEAS

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    1. Neal Fann & Amy D. Lamson & Susan C. Anenberg & Karen Wesson & David Risley & Bryan J. Hubbell, 2012. "Estimating the National Public Health Burden Associated with Exposure to Ambient PM2.5 and Ozone," Risk Analysis, John Wiley & Sons, vol. 32(1), pages 81-95, January.
    2. Tao Chen & Jun He & Xiaowei Lu & Jiangfeng She & Zhongqing Guan, 2016. "Spatial and Temporal Variations of PM 2.5 and Its Relation to Meteorological Factors in the Urban Area of Nanjing, China," IJERPH, MDPI, vol. 13(9), pages 1-16, September.
    3. Gang Lin & Jingying Fu & Dong Jiang & Wensheng Hu & Donglin Dong & Yaohuan Huang & Mingdong Zhao, 2013. "Spatio-Temporal Variation of PM 2.5 Concentrations and Their Relationship with Geographic and Socioeconomic Factors in China," IJERPH, MDPI, vol. 11(1), pages 1-14, December.
    4. Tianhao Zhang & Wei Gong & Wei Wang & Yuxi Ji & Zhongmin Zhu & Yusi Huang, 2016. "Ground Level PM 2.5 Estimates over China Using Satellite-Based Geographically Weighted Regression (GWR) Models Are Improved by Including NO 2 and Enhanced Vegetation Index (EVI)," IJERPH, MDPI, vol. 13(12), pages 1-12, December.
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    Cited by:

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    4. Chengming Li & Kuo Zhang & Zhaoxin Dai & Zhaoting Ma & Xiaoli Liu, 2020. "Investigation of the Impact of Land-Use Distribution on PM 2.5 in Weifang: Seasonal Variations," IJERPH, MDPI, vol. 17(14), pages 1-20, July.
    5. Wenbo Chen & Fuqing Zhang & Saiwei Luo & Taojie Lu & Jiao Zheng & Lei He, 2022. "Three-Dimensional Landscape Pattern Characteristics of Land Function Zones and Their Influence on PM 2.5 Based on LUR Model in the Central Urban Area of Nanchang City, China," IJERPH, MDPI, vol. 19(18), pages 1-18, September.
    6. Lili Guo & Yuting Song & Mengqian Tang & Jinyang Tang & Bright Senyo Dogbe & Mengying Su & Houjian Li, 2022. "Assessing the Relationship among Land Transfer, Fertilizer Usage, and PM 2.5 Pollution: Evidence from Rural China," IJERPH, MDPI, vol. 19(14), pages 1-18, July.
    7. Binghui Yang & Ye Chen, 2021. "PM2.5 Pollutant Concentrations in Greenspaces of Nanjing Are High but Can Be Lowered with Environmental Planning," IJERPH, MDPI, vol. 18(18), pages 1-20, September.
    8. Bumseok Chun & Kwangyul Choi & Qisheng Pan, 2022. "Key determinants of particulate matter 2.5 concentrations in urban environments with scenario analysis," Environment and Planning B, , vol. 49(7), pages 1980-1994, September.
    9. Sonja Dmitrašinović & Jelena Radonić & Marija Živković & Željko Ćirović & Milena Jovašević-Stojanović & Miloš Davidović, 2024. "Winter and Summer PM 2.5 Land Use Regression Models for the City of Novi Sad, Serbia," Sustainability, MDPI, vol. 16(13), pages 1-27, June.
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    11. Shibo Bi & Ming Chen & Zheng Tian & Peiyi Jiang & Fei Dai & Guowei Wang, 2024. "Optimizing Urban Green Spaces for Air Quality Improvement: A Multiscale Land Use/Land Cover Synergy Practical Framework in Wuhan, China," Land, MDPI, vol. 13(7), pages 1-24, July.

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