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Do Individuals’ Activity Structures Influence Their PM 2 . 5 Exposure Levels? Evidence from Human Trajectory Data in Wuhan City

Author

Listed:
  • Siyu Ma

    (School of Geography and Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China)

  • Lin Yang

    (School of Geography and Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China
    National Engineering Research Center of Geographic Information System, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China)

  • Mei-Po Kwan

    (Department of Geography and Resource Management, Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, Hong Kong, China
    Department of Human Geography and Spatial Planning, Utrecht University, 3584 CB Utrecht, The Netherlands)

  • Zejun Zuo

    (School of Geography and Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China
    National Engineering Research Center of Geographic Information System, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China)

  • Haoyue Qian

    (School of Geography and Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China)

  • Minghao Li

    (School of Geography and Information Engineering, China University of Geosciences, 388 Lumo Road, Wuhan 430074, China)

Abstract

Severe air pollution has become a major risk to human health from a global environmental perspective. It has been recognized that human mobility is an essential component in individual exposure assessment. Activity structure reflects the characteristics of human mobility. Thus, a better understanding of the relationship between human activity structure and individual exposure level is of crucial relevance. This study examines this relationship using a large cell-phone GPS dataset in Wuhan, China. The results indicate that there is a strong linear relationship between people’s activity structures and exposures to PM 2 . 5 . Inter-group comparisons based on the four activity structure groups obtained with K-means clustering found that groups with different activity structures do experience different levels of PM 2 . 5 exposure. Furthermore, differences in detailed characteristics of activity structure were also found at different exposure levels at the intra-group level. These results show that people’s activity structures do influence their exposure levels. The paper provides a new perspective for understanding individual exposure through human activity structure, which helps move the perspective of research on individual exposure from the semantic of physical location to the semantic of human activity pattern.

Suggested Citation

  • Siyu Ma & Lin Yang & Mei-Po Kwan & Zejun Zuo & Haoyue Qian & Minghao Li, 2021. "Do Individuals’ Activity Structures Influence Their PM 2 . 5 Exposure Levels? Evidence from Human Trajectory Data in Wuhan City," IJERPH, MDPI, vol. 18(9), pages 1-27, April.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:9:p:4583-:d:543709
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    References listed on IDEAS

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    7. Xinlin Ma & Xijing Li & Mei-Po Kwan & Yanwei Chai, 2020. "Who Could Not Avoid Exposure to High Levels of Residence-Based Pollution by Daily Mobility? Evidence of Air Pollution Exposure from the Perspective of the Neighborhood Effect Averaging Problem (NEAP)," IJERPH, MDPI, vol. 17(4), pages 1-19, February.
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    2. Marcelle Virginia Canto & Mònica Guxens & Rebeca Ramis, 2022. "Exposure to Traffic Density during Pregnancy and Birth Weight in a National Cohort, 2000–2017," IJERPH, MDPI, vol. 19(14), pages 1-14, July.

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