IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i6p985-d215157.html
   My bibliography  Save this article

Spatial-Temporal Evolution of PM 2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017

Author

Listed:
  • Yazhu Wang

    (Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China
    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China)

  • Xuejun Duan

    (Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China)

  • Lei Wang

    (Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
    Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China)

Abstract

PM 2.5 is a main source of China’s frequent air pollution. Using real-time monitoring of PM 2.5 data in 338 Chinese cities during 2014–2017, this study employed multi-temporal and multi-spatial scale statistical analysis to reveal the temporal and spatial characteristics of PM 2.5 patterns and a spatial econometric model to quantify the socio-economic driving factors of PM 2.5 concentration changes. The results are as follows: (1) The annual average value of PM 2.5 concentration decreased year by year and the monthly average showed a U-shaped curve from January to December. The daily mean value of PM 2.5 concentration had the characteristics of pulse-type fluctuation and the hourly variation presented a bimodal curve. (2) During 2014–2017, the overall PM 2.5 pollution reduced significantly, but that of more than two-thirds of cities still exceeded the standard value (35 μg/m 3 ) regulated by Chinese government. PM 2.5 pollution patterns showed high values in central and eastern Chinese cities and low values in peripheral areas, with the distinction evident along the same line that delineates China’s uneven population distribution. (3) Population agglomeration, industrial development, foreign investment, transportation, and pollution emissions contributed to the increase of PM 2.5 concentration. Urban population density contributed most significantly while economic development and technological progress reduced PM 2.5 concentration. The results also suggest that China in general remains a “pollution shelter” for foreign-funded enterprises.

Suggested Citation

  • Yazhu Wang & Xuejun Duan & Lei Wang, 2019. "Spatial-Temporal Evolution of PM 2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017," IJERPH, MDPI, vol. 16(6), pages 1-18, March.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:6:p:985-:d:215157
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/6/985/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/16/6/985/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yonglin Shen & Ling Yao, 2017. "PM 2.5 , Population Exposure and Economic Effects in Urban Agglomerations of China Using Ground-Based Monitoring Data," IJERPH, MDPI, vol. 14(7), pages 1-15, July.
    2. Cai-Rong Lou & Hong-Yu Liu & Yu-Feng Li & Yu-Ling Li, 2016. "Socioeconomic Drivers of PM 2.5 in the Accumulation Phase of Air Pollution Episodes in the Yangtze River Delta of China," IJERPH, MDPI, vol. 13(10), pages 1-19, 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. Amit K. Gorai & Francis Tuluri & Paul B. Tchounwou, 2014. "A GIS Based Approach for Assessing the Association between Air Pollution and Asthma in New York State, USA," IJERPH, MDPI, vol. 11(5), pages 1-25, May.
    5. Lisa C. Vinikoor-Imler & J. Allen Davis & Thomas J. Luben, 2011. "An Ecologic Analysis of County-Level PM 2.5 Concentrations and Lung Cancer Incidence and Mortality," IJERPH, MDPI, vol. 8(6), pages 1-7, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chengming Li & Zhaoxin Dai & Lina Yang & Zhaoting Ma, 2019. "Spatiotemporal Characteristics of Air Quality across Weifang from 2014–2018," IJERPH, MDPI, vol. 16(17), pages 1-15, August.
    2. Wenhao Chen & Chang Zeng & Chuheng Ding & Yingfang Zhu & Yurong Sun, 2022. "Study on Spatio-Temporal Evolution Law and Driving Mechanism of PM 2.5 Concentration in Changsha–Zhuzhou–Xiangtan Urban Agglomeration," Sustainability, MDPI, vol. 14(22), pages 1-18, November.
    3. Huaxue Zhao & Yu Cheng & Ruijing Zheng, 2022. "Impact of the Digital Economy on PM 2.5 : Experience from the Middle and Lower Reaches of the Yellow River Basin," IJERPH, MDPI, vol. 19(24), pages 1-20, December.
    4. Lining Zhu & Yu Zhang & Zheng Wu & Chengcheng Zhang, 2021. "Spatio-Temporal Characteristics of SO 2 across Weifang from 2008 to 2020," IJERPH, MDPI, vol. 18(22), pages 1-17, November.
    5. Jingyuan Li & Jinhua Cheng & Yang Wen & Jingyu Cheng & Zhong Ma & Peiqi Hu & Shurui Jiang, 2022. "The Cause of China’s Haze Pollution: City Level Evidence Based on the Extended STIRPAT Model," IJERPH, MDPI, vol. 19(8), pages 1-18, April.
    6. Jun Li & Yu Chen & Fang Chen, 2024. "Analysis of the Factors Influencing the Spatial Distribution of PM2.5 Concentrations (SDG 11.6.2) at the Provincial Scale in China," Sustainability, MDPI, vol. 16(8), pages 1-18, April.
    7. Xiangxue Zhang & Changxiu Cheng, 2022. "Temporal and Spatial Heterogeneity of PM 2.5 Related to Meteorological and Socioeconomic Factors across China during 2000–2018," IJERPH, MDPI, vol. 19(2), pages 1-15, January.
    8. Xiangxue Zhang & Yue Lin & Changxiu Cheng & Junming Li, 2021. "Determinant Powers of Socioeconomic Factors and Their Interactive Impacts on Particulate Matter Pollution in North China," IJERPH, MDPI, vol. 18(12), pages 1-15, June.
    9. Lingyan Xu & Dandan Wang & Jianguo Du, 2022. "Spatial-Temporal Evolution and Influencing Factors of Urban Green and Smart Development Level in China: Evidence from 232 Prefecture-Level Cities," IJERPH, MDPI, vol. 19(7), pages 1-19, March.
    10. Chunshan Zhou & Rongrong Zhang & Xiaoju Ning & Zhicheng Zheng, 2020. "Spatial-Temporal Characteristics in Grain Production and Its Influencing Factors in the Huang-Huai-Hai Plain from 1995 to 2018," IJERPH, MDPI, vol. 17(24), pages 1-19, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yi Yang & Jie Li & Guobin Zhu & Qiangqiang Yuan, 2019. "Spatio–Temporal Relationship and Evolvement of Socioeconomic Factors and PM 2.5 in China During 1998–2016," IJERPH, MDPI, vol. 16(7), pages 1-24, March.
    2. Dan Xu & Wenpeng Lin & Jun Gao & Yue Jiang & Lubing Li & Fei Gao, 2022. "PM 2.5 Exposure and Health Risk Assessment Using Remote Sensing Data and GIS," IJERPH, MDPI, vol. 19(10), pages 1-24, May.
    3. Jin-Wei Yan & Fei Tao & Shuai-Qian Zhang & Shuang Lin & Tong Zhou, 2021. "Spatiotemporal Distribution Characteristics and Driving Forces of PM2.5 in Three Urban Agglomerations of the Yangtze River Economic Belt," IJERPH, MDPI, vol. 18(5), pages 1-25, February.
    4. Huilin Yang & Rui Yao & Peng Sun & Chenhao Ge & Zice Ma & Yaojin Bian & Ruilin Liu, 2023. "Spatiotemporal Evolution and Driving Forces of PM 2.5 in Urban Agglomerations in China," IJERPH, MDPI, vol. 20(3), pages 1-15, January.
    5. Hongbin He & Yonglin Shen & Changmin Jiang & Tianqi Li & Mingqiang Guo & Ling Yao, 2020. "Spatiotemporal Big Data for PM 2.5 Exposure and Health Risk Assessment during COVID-19," IJERPH, MDPI, vol. 17(20), pages 1-19, October.
    6. Junming Li & Meijun Jin & Honglin Li, 2019. "Exploring Spatial Influence of Remotely Sensed PM 2.5 Concentration Using a Developed Deep Convolutional Neural Network Model," IJERPH, MDPI, vol. 16(3), pages 1-11, February.
    7. Ling Yao & Ning Lu, 2014. "Particulate Matter Pollution and Population Exposure Assessment over Mainland China in 2010 with Remote Sensing," IJERPH, MDPI, vol. 11(5), pages 1-10, May.
    8. Hansol Mun & Mengying Li & Juchul Jung, 2022. "Spatial-Temporal Characteristics and Influencing Factors of Particulate Matter: Geodetector Approach," Land, MDPI, vol. 11(12), pages 1-26, December.
    9. Jianhua Wang & Susumu Ogawa, 2015. "Effects of Meteorological Conditions on PM 2.5 Concentrations in Nagasaki, Japan," IJERPH, MDPI, vol. 12(8), pages 1-13, August.
    10. Yu Chen & Qianqian Miao & Qian Zhou, 2022. "Spatiotemporal Differentiation and Driving Force Analysis of the High-Quality Development of Urban Agglomerations along the Yellow River Basin," IJERPH, MDPI, vol. 19(4), pages 1-21, February.
    11. Yusuf A. Aina & Johannes H. Van der Merwe & Habib M. Alshuwaikhat, 2014. "Spatial and Temporal Variations of Satellite-Derived Multi-Year Particulate Data of Saudi Arabia: An Exploratory Analysis," IJERPH, MDPI, vol. 11(11), pages 1-15, October.
    12. Ling Yao & Changchun Huang & Wenlong Jing & Xiafang Yue & Yuyue Xu, 2018. "Quantitative Assessment of Relationship between Population Exposure to PM 2.5 and Socio-Economic Factors at Multiple Spatial Scales over Mainland China," IJERPH, MDPI, vol. 15(9), pages 1-13, September.
    13. Wenting Wang & Lijun Zhang & Jun Zhao & Mengge Qi & Fengrui Chen, 2020. "The Effect of Socioeconomic Factors on Spatiotemporal Patterns of PM 2.5 Concentration in Beijing–Tianjin–Hebei Region and Surrounding Areas," IJERPH, MDPI, vol. 17(9), pages 1-16, April.
    14. Lisha Luo & Junfeng Jiang & Ganshen Zhang & Lu Wang & Zhenkun Wang & Jin Yang & Chuanhua Yu, 2017. "Stroke Mortality Attributable to Ambient Particulate Matter Pollution from 1990 to 2015 in China: An Age-Period-Cohort and Spatial Autocorrelation Analysis," IJERPH, MDPI, vol. 14(7), pages 1-17, July.
    15. Wenfeng Fan & Linyu Xu & Hanzhong Zheng, 2022. "Using Multisource Data to Assess PM 2.5 Exposure and Spatial Analysis of Lung Cancer in Guangzhou, China," IJERPH, MDPI, vol. 19(5), pages 1-17, February.
    16. Weiguang Wang & Yangyang Wang, 2023. "Regional Differences, Dynamic Evolution and Driving Factors Analysis of PM 2.5 in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    17. Yafei Wu & Ke Hu & Yaofeng Han & Qilin Sheng & Ya Fang, 2020. "Spatial Characteristics of Life Expectancy and Geographical Detection of Its Influencing Factors in China," IJERPH, MDPI, vol. 17(3), pages 1-15, February.
    18. Tiansong Zhu & Kaiping Yu & Bo Wang, 2023. "Spatial Distribution Characteristics and Influencing Factors of Cultural and Tourism Resources in Xihu District of Hangzhou," Sustainability, MDPI, vol. 15(14), pages 1-20, July.
    19. Xiangxue Zhang & Yue Lin & Changxiu Cheng & Junming Li, 2021. "Determinant Powers of Socioeconomic Factors and Their Interactive Impacts on Particulate Matter Pollution in North China," IJERPH, MDPI, vol. 18(12), pages 1-15, June.
    20. Yuan Shi & Alexis Kai-Hon Lau & Edward Ng & Hung-Chak Ho & Muhammad Bilal, 2021. "A Multiscale Land Use Regression Approach for Estimating Intraurban Spatial Variability of PM 2.5 Concentration by Integrating Multisource Datasets," IJERPH, MDPI, vol. 19(1), pages 1-16, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:16:y:2019:i:6:p:985-:d:215157. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.