IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i12p2336-d1008491.html
   My bibliography  Save this article

Spatial-Temporal Characteristics and Influencing Factors of Particulate Matter: Geodetector Approach

Author

Listed:
  • Hansol Mun

    (Urban Planning & Engineering, Pusan National University, Busan 46241, Republic of Korea)

  • Mengying Li

    (Urban Planning & Engineering, Pusan National University, Busan 46241, Republic of Korea)

  • Juchul Jung

    (Urban Planning & Engineering, Pusan National University, Busan 46241, Republic of Korea)

Abstract

In 2019, South Korea’s Framework Act on The Management of Disasters and Safety was revised to include respirable particulate matter as a social disaster. Urban air pollution, especially particulate matter pollution, has been a serious threat to socioeconomic development and public health. In order to address this problem, strong climate crisis response strategies and policies to improve urban air quality are necessary. Therefore, it is of great importance to assess the frequency of urban air pollution occurrence and its influencing factors. The objective of this study is to develop consistent methodologies for the construction of an index system and for assessing the influencing factors of urban particulate matter pollution based on population, social welfare, land use, environmental, transportation, and economic governance considerations. We applied the local indicators of spatial association and geographical detector methods, and 35 influencing factors were selected to assess their influence on urban air pollution occurrence in 229 cities and counties in South Korea. The results indicated the spatial pattern of the particulate matter concentration in these locations showed strong spatial correlation, and it was confirmed that there was a difference in distribution according to the season. As a result of the analysis of influencing factors, it was found that environment and land use characteristics were the main influencing factors for PM 10 and PM 2.5 . The explanatory power between the two influencing factors of particulate matter was greater than that of a single influencing factor. In addition, most influencing factors resulted in both positive and negative effects on urban fine particulate matter pollution. The interaction relationship of all factors showed a strong action effect in the case of both PM 10 and PM 2.5 , so it was confirmed that all influencing factors were interdependent. In particular, the findings proved that combining the two factors would have a more pronounced effect on particulate matter than when they were independent. We confirmed the significant results for the factors affecting particulate matter. This study offers suggestions on reducing urban air pollution occurrence that can be used to provide a basis and reference for the government to form policies on urban air pollution control in cities and counties.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:12:p:2336-:d:1008491
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/12/2336/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/12/2336/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chuanglin Fang & Haimeng Liu & Guangdong Li & Dongqi Sun & Zhuang Miao, 2015. "Estimating the Impact of Urbanization on Air Quality in China Using Spatial Regression Models," Sustainability, MDPI, vol. 7(11), pages 1-23, November.
    2. Jie Yang & Pengfei Liu & Hongquan Song & Changhong Miao & Feng Wang & Yu Xing & Wenjie Wang & Xinyu Liu & Mengxin Zhao, 2021. "Effects of Anthropogenic Emissions from Different Sectors on PM 2.5 Concentrations in Chinese Cities," IJERPH, MDPI, vol. 18(20), pages 1-13, October.
    3. 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.
    4. 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.
    5. Ji, Xi & Yao, Yixin & Long, Xianling, 2018. "What causes PM2.5 pollution? Cross-economy empirical analysis from socioeconomic perspective," Energy Policy, Elsevier, vol. 119(C), pages 458-472.
    6. Park, Soonae & Lee, Youngmi, 2011. "Regional model of EKC for air pollution: Evidence from the Republic of Korea," Energy Policy, Elsevier, vol. 39(10), pages 5840-5849, October.
    Full references (including those not matched with items on IDEAS)

    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. Jaeger, William K. & Kolpin, Van & Siegel, Ryan, 2023. "The environmental Kuznets curve reconsidered," Energy Economics, Elsevier, vol. 120(C).
    2. Yao, Wanxiang & Zheng, Zhimiao & Zhao, Jun & Wang, Xiao & Wang, Yan & Li, Xianli & Fu, Jidong, 2020. "The factor analysis of fog and haze under the coupling of multiple factors -- taking four Chinese cities as an example," Energy Policy, Elsevier, vol. 137(C).
    3. Moon-Jung Kim & Yu-Sang Chang & Su-Min Kim, 2021. "Impact of Income, Density, and Population Size on PM 2.5 Pollutions: A Scaling Analysis of 254 Large Cities in Six Developed Countries," IJERPH, MDPI, vol. 18(17), pages 1-30, August.
    4. Ye Yang & Haifeng Lan & Jing Li, 2019. "Spatial Econometric Analysis of the Impact of Socioeconomic Factors on PM 2.5 Concentration in China’s Inland Cities: A Case Study from Chengdu Plain Economic Zone," IJERPH, MDPI, vol. 17(1), pages 1-19, December.
    5. Qingyu Fan & Shan Yang & Shuaibin Liu, 2019. "Asymmetrically Spatial Effects of Urban Scale and Agglomeration on Haze Pollution in China," IJERPH, MDPI, vol. 16(24), pages 1-18, December.
    6. Zhipeng Zhu & Guangyu Wang & Jianwen Dong, 2019. "Correlation Analysis between Land Use/Cover Change and Air Pollutants—A Case Study in Wuyishan City," Energies, MDPI, vol. 12(13), pages 1-15, July.
    7. Yan Wang & Dong Yang, 2018. "Impacts of Freight Transport on PM 2.5 Concentrations in China: A Spatial Dynamic Panel Analysis," Sustainability, MDPI, vol. 10(8), pages 1-16, August.
    8. Zhipeng Zhu & Yuxuan Qiao & Qunyue Liu & Conghua Lin & Emily Dang & Weicong Fu & Guangyu Wang & Jianwen Dong, 2021. "The impact of meteorological conditions on Air Quality Index under different urbanization gradients: a case from Taipei," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(3), pages 3994-4010, March.
    9. Yue, Shen & Munir, Irfan Ullah & Hyder, Shabir & Nassani, Abdelmohsen A. & Qazi Abro, Muhammad Moinuddin & Zaman, Khalid, 2020. "Sustainable food production, forest biodiversity and mineral pricing: Interconnected global issues," Resources Policy, Elsevier, vol. 65(C).
    10. Li, Kunming & Fang, Liting & He, Lerong, 2019. "How population and energy price affect China's environmental pollution?," Energy Policy, Elsevier, vol. 129(C), pages 386-396.
    11. Tuo Shi & Yuanman Hu & Miao Liu & Chunlin Li & Chuyi Zhang & Chong Liu, 2020. "How Do Economic Growth, Urbanization, and Industrialization Affect Fine Particulate Matter Concentrations? An Assessment in Liaoning Province, China," IJERPH, MDPI, vol. 17(15), pages 1-14, July.
    12. Zhuang Miao & Tomas Baležentis & Zhihua Tian & Shuai Shao & Yong Geng & Rui Wu, 2019. "Environmental Performance and Regulation Effect of China’s Atmospheric Pollutant Emissions: Evidence from “Three Regions and Ten Urban Agglomerations”," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 74(1), pages 211-242, September.
    13. 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.
    14. Samargandi, Nahla, 2017. "Sector value addition, technology and CO2 emissions in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 868-877.
    15. Malayaranjan Sahoo & Narayan Sethi, 2022. "The dynamic impact of urbanization, structural transformation, and technological innovation on ecological footprint and PM2.5: evidence from newly industrialized countries," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(3), pages 4244-4277, March.
    16. Baiardi Donatella, 2014. "Technological Progress and the Environmental Kuznets Curve in the Twenty Regions of Italy," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 14(4), pages 1501-1542, October.
    17. Jun Bai & Shixiang Li & Nan Wang & Jianru Shi & Xianmin Li, 2020. "Spatial Spillover Effect of New Energy Development on Economic Growth in Developing Areas of China—An Empirical Test Based on the Spatial Dubin Model," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    18. Wang, Xiaomin & Tian, Guanghui & Yang, Dongyang & Zhang, Wenxin & Lu, Debin & Liu, Zhongmei, 2018. "Responses of PM2.5 pollution to urbanization in China," Energy Policy, Elsevier, vol. 123(C), pages 602-610.
    19. Weicong Fu & Qunyue Liu & Cecil Konijnendijk van den Bosch & Ziru Chen & Zhipeng Zhu & Jinda Qi & Mo Wang & Emily Dang & Jianwen Dong, 2018. "Long-Term Atmospheric Visibility Trends and Their Relations to Socioeconomic Factors in Xiamen City, China," IJERPH, MDPI, vol. 15(10), pages 1-16, October.
    20. Chun Chih Chen, 2021. "The path to a 2025 nuclear-free Taiwan: An analysis of dynamic competition among emissions, energy, and economy," Energy & Environment, , vol. 32(4), pages 668-689, June.

    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:jlands:v:11:y:2022:i:12:p:2336-:d:1008491. 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.