Modeling Spatial Distribution and Determinant of PM<sub>2.5</sub> 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

Air pollution is fatal. Fine particles, such as PM<sub>2.5</sub>, 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...

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Autores principales:	Alok Tiwari, Mohammed Aljoufie
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	King Abdulaziz University PM<sub>2.5</sub> GWR zero-carbon campus spatial heterogeneity Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/2d7ee6ce084f40c687ca4ebbd798f99d
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spelling	oai:doaj.org-article:2d7ee6ce084f40c687ca4ebbd798f99d2021-11-11T19:42:06ZModeling Spatial Distribution and Determinant of PM<sub>2.5</sub> at Micro-Level Using Geographically Weighted Regression (GWR) to Inform Sustainable Mobility Policies in Campus Based on Evidence from King Abdulaziz University, Jeddah, Saudi Arabia10.3390/su1321120432071-1050https://doaj.org/article/2d7ee6ce084f40c687ca4ebbd798f99d2021-10-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/21/12043https://doaj.org/toc/2071-1050Air pollution is fatal. Fine particles, such as PM<sub>2.5</sub>, 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<sub>2.5</sub> 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<sub>2.5</sub> 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<sub>2.5</sub> 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.Alok TiwariMohammed AljoufieMDPI AGarticleKing Abdulaziz UniversityPM<sub>2.5</sub>GWRzero-carbon campusspatial heterogeneityEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12043, p 12043 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	King Abdulaziz University PM<sub>2.5</sub> GWR zero-carbon campus spatial heterogeneity Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	King Abdulaziz University PM<sub>2.5</sub> GWR zero-carbon campus spatial heterogeneity Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Alok Tiwari Mohammed Aljoufie Modeling Spatial Distribution and Determinant of PM<sub>2.5</sub> 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
description	Air pollution is fatal. Fine particles, such as PM<sub>2.5</sub>, 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<sub>2.5</sub> 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<sub>2.5</sub> 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<sub>2.5</sub> 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.
format	article
author	Alok Tiwari Mohammed Aljoufie
author_facet	Alok Tiwari Mohammed Aljoufie
author_sort	Alok Tiwari
title	Modeling Spatial Distribution and Determinant of PM<sub>2.5</sub> 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
title_short	Modeling Spatial Distribution and Determinant of PM<sub>2.5</sub> 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
title_full	Modeling Spatial Distribution and Determinant of PM<sub>2.5</sub> 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
title_fullStr	Modeling Spatial Distribution and Determinant of PM<sub>2.5</sub> 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
title_full_unstemmed	Modeling Spatial Distribution and Determinant of PM<sub>2.5</sub> 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
title_sort	modeling spatial distribution and determinant of pm<sub>2.5</sub> 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
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/2d7ee6ce084f40c687ca4ebbd798f99d
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Modeling Spatial Distribution and Determinant of PM<sub>2.5</sub> 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

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