TY - JOUR
T1 - Ground-Level Particulate Matter (PM2.5) Concentration Mapping in the Central and South Zones of Peninsular Malaysia Using a Geostatistical Approach
AU - Rusmili, Siti Hasliza Ahmad
AU - Mohamad Hamzah, Firdaus
AU - Choy, Lam Kuok
AU - Azizah, R.
AU - Sulistyorini, Lilis
AU - Yudhastuti, Ririh
AU - Chandraning Diyanah, Khuliyah
AU - Adriyani, Retno
AU - Latif, Mohd Talib
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/12
Y1 - 2023/12
N2 - 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 PM2.5 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 PM2.5 concentrations. The spatial autocorrelation of PM2.5 is calculated using Moran’s I, while three semi-variogram models are used to measure the spatial variability of PM2.5. 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 PM2.5 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.
AB - 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 PM2.5 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 PM2.5 concentrations. The spatial autocorrelation of PM2.5 is calculated using Moran’s I, while three semi-variogram models are used to measure the spatial variability of PM2.5. 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 PM2.5 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.
KW - air pollution
KW - interpolation
KW - kriging
KW - PM
UR - http://www.scopus.com/inward/record.url?scp=85195060167&partnerID=8YFLogxK
U2 - 10.3390/su152316169
DO - 10.3390/su152316169
M3 - Article
AN - SCOPUS:85195060167
SN - 2071-1050
VL - 15
JO - Sustainability (Switzerland)
JF - Sustainability (Switzerland)
IS - 23
M1 - 16169
ER -