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Modeling Spatial Distribution and Determinant of PM 2.5 at Micro-Level Using Geographically Weighted Regression (GWR) to Inform Sustainable Mobility Policies in Campus Based on Evidence from King Abdulaziz University, Jeddah, Saudi Arabia

Author

Listed:
  • Alok Tiwari

    (Department of Urban and Regional Planning, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Mohammed Aljoufie

    (Department of Urban and Regional Planning, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

Air pollution is fatal. Fine particles, such as PM 2.5 , in ambient air might be the cause of many physical and psychological disorders, including cognitive decline. This is why educational policymakers are adopting sustainable mobility, and other policy measures, to make their campuses carbon-neutral; however, car-dependent cities and their university campuses are still lagging behind in this area. This study attempts to model the spatial heterogeneity and determinants of PM 2.5 at the King Abdulaziz University campus in Jeddah, which is ranked first among the Saudi Arabian universities, as well as in the MENA region. We developed four OLS and GWR models of different peak and off-peak periods during weekdays in order to estimate the determinants of the PM 2.5 concentration. The number of cars, humidity, temperature, windspeed, distance from trees, and construction sites were the estimators in our analysis. Because of a lack of secondary data at a finer scale, we collected the samples of all dependent and independent variables at 51 locations on the KAU campus. Model selection was based on RSS, log-likelihood, adjusted R2, and AICc, and a modal comparison shows that the GWR variant of Model-2 outperformed the other models. The results of the GWR model demonstrate the geographical variability of the PM 2.5 concentration on the KAU campus, to which the volume of car traffic is the key contributor. Hence, we recommend using the results of this study to support the development of a car-free and zero-carbon campus at KAU; furthermore, this study could be exploited by other campuses in Saudi Arabia and the Gulf region.

Suggested Citation

  • Alok Tiwari & Mohammed Aljoufie, 2021. "Modeling Spatial Distribution and Determinant of PM 2.5 at Micro-Level Using Geographically Weighted Regression (GWR) to Inform Sustainable Mobility Policies in Campus Based on Evidence from King Abdu," Sustainability, MDPI, vol. 13(21), pages 1-14, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:12043-:d:669516
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    References listed on IDEAS

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    1. Amanda Leigh Mascarelli, 2009. "How green is your campus?," Nature, Nature, vol. 461(7261), pages 154-155, September.
    2. Makio Ishiguro & Yosiyuki Sakamoto & Genshiro Kitagawa, 1997. "Bootstrapping Log Likelihood and EIC, an Extension of AIC," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 49(3), pages 411-434, September.
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    4. Sarah L. Stafford, 2011. "How Green Is Your Campus? An Analysis Of The Factors That Drive Universities To Embrace Sustainability," Contemporary Economic Policy, Western Economic Association International, vol. 29(3), pages 337-356, July.
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