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Fine-Scale Spatial Variability of Pedestrian-Level Particulate Matters in Compact Urban Commercial Districts in Hong Kong

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  • Yuan Shi

    (School of Architecture, The Chinese University of Hong Kong, Shatin, NT, Hong Kong, China)

  • Edward Ng

    (School of Architecture, The Chinese University of Hong Kong, Shatin, NT, Hong Kong, China
    Institute of Environment, Energy and Sustainability (IEES), The Chinese University of Hong Kong, Shatin, NT, Hong Kong, China
    Institute of Future Cities (IOFC), The Chinese University of Hong Kong, Shatin, NT, Hong Kong, China)

Abstract

Particulate matters (PM) at the pedestrian level significantly raises the health impacts in the compact urban environment of Hong Kong. A detailed investigation of the fine-scale spatial variation of pedestrian-level PM is necessary to assess the health risk to pedestrians in the outdoor environment. However, the collection of PM data is difficult in the compact urban environment of Hong Kong due to the limited amount of roadside monitoring stations and the complicated urban context. In this study, we measured the fine-scale spatial variability of the PM in three of the most representative commercial districts of Hong Kong using a backpack outdoor environmental measuring unit. Based on the measurement data, 13 types of geospatial interpolation methods were examined for the spatial mapping of PM 2.5 and PM 10 with a group of building geometrical covariates. Geostatistical modelling was adopted as the basis of spatial interpolation of the PM. The results show that the original cokriging with the exponential kernel function provides the best performance in the PM mapping. Using the fine-scale building geometrical features as covariates slightly improves the interpolation performance. The study results also imply that the fine-scale, localized pollution emission sources heavily influence pedestrian exposure to PM.

Suggested Citation

  • Yuan Shi & Edward Ng, 2017. "Fine-Scale Spatial Variability of Pedestrian-Level Particulate Matters in Compact Urban Commercial Districts in Hong Kong," IJERPH, MDPI, vol. 14(9), pages 1-16, September.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:9:p:1008-:d:110742
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    References listed on IDEAS

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    1. EunHye Yoo & C. Rudra & M. Glasgow & L. Mu, 2015. "Geospatial Estimation of Individual Exposure to Air Pollutants: Moving from Static Monitoring to Activity-Based Dynamic Exposure Assessment," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 105(5), pages 915-926, September.
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    Cited by:

    1. Thomas M. T. Lei & Martin F. C. Ma, 2023. "The Relationship between Roadside PM Concentration and Traffic Characterization: A Case Study in Macao," Sustainability, MDPI, vol. 15(14), pages 1-14, July.
    2. 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.

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