Ground-Level Particulate Matter (PM 2.5 ) Concentration Mapping in the Central and South Zones of Peninsular Malaysia Using a Geostatistical Approach

Siti Hasliza Ahmad Rusmili, Firdaus Mohamad Hamzah (), Lam Kuok Choy, R. Azizah, Lilis Sulistyorini, Ririh Yudhastuti, Khuliyah Chandraning Diyanah, Retno Adriyani and Mohd Talib Latif
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Siti Hasliza Ahmad Rusmili: Faculty of Engineering and Build Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia
Firdaus Mohamad Hamzah: Centre for Defence Foundation Studies, Universiti Pertahanan Nasional Malaysia, Kem Perdana Sg. Besi, Kuala Lumpur 57000, Selangor, Malaysia
Lam Kuok Choy: Faculty of Social Sciences and Humanities, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia
R. Azizah: Department of Environmental Health, Faculty of Public Health, Universitas Airlangga, Surabaya 60115, Jawa Timur, Indonesia
Lilis Sulistyorini: Department of Environmental Health, Faculty of Public Health, Universitas Airlangga, Surabaya 60115, Jawa Timur, Indonesia
Ririh Yudhastuti: Department of Environmental Health, Faculty of Public Health, Universitas Airlangga, Surabaya 60115, Jawa Timur, Indonesia
Khuliyah Chandraning Diyanah: Department of Environmental Health, Faculty of Public Health, Universitas Airlangga, Surabaya 60115, Jawa Timur, Indonesia
Retno Adriyani: Department of Environmental Health, Faculty of Public Health, Universitas Airlangga, Surabaya 60115, Jawa Timur, Indonesia
Mohd Talib Latif: Department of Environmental Health, Faculty of Public Health, Universitas Airlangga, Surabaya 60115, Jawa Timur, Indonesia

Sustainability, 2023, vol. 15, issue 23, 1-17

Abstract: Fine particulate matter is one of the atmospheric contaminants that exist in the atmosphere. The purpose of this study is to evaluate spatial–temporal changes in PM 2.5 concentrations in the central and south zones of Peninsular Malaysia from 2019 to 2020. The study area involves twenty-one monitoring stations in the central and south zones of Peninsular Malaysia, using monthly and annual means of PM 2.5 concentrations. The spatial autocorrelation of PM 2.5 is calculated using Moran’s I, while three semi-variogram models are used to measure the spatial variability of PM 2.5 . Three kriging methods, ordinary kriging (OK), simple kriging (SK), and universal kriging (UK), were used for interpolation and comparison. The results showed that the Gaussian model was more appropriate for the central zone (MSE = 14.76) in 2019, while the stable model was more suitable in 2020 (MSE = 19.83). In addition, the stable model is more appropriate for both 2019 (MSE = 12.68) and 2020 (8.87) for the south zone. Based on the performance indicator, universal kriging was chosen as the best interpolation method in 2019 and 2020 for both the central and south zone. In conclusion, the findings provide a complete map of the variations in PM 2.5 for two different zones, and show that interpolation methods such as universal kriging are beneficial and could be extended to the investigation of air pollution distributions in other areas of Peninsular Malaysia.

Keywords: PM 2.5; air pollution; interpolation; kriging (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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