Meteorological Factors Affecting on PM2.5 Concentrations in Bandaraya Melaka

Nur Alya Adriana Abdullah Sani; Nurkhairany Amyra Mokhtar

doi:10.24191/jcrinn.v10i2.514

Meteorological Factors Affecting on PM2.5 Concentrations in Bandaraya Melaka

Authors

Nur Alya Adriana Abdullah Sani Statistics Studies, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Negeri Sembilan Branch, Seremban Campus, 70300 Seremban, Negeri Sembilan, Malaysia.
Nurkhairany Amyra Mokhtar Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Johor Branch, Segamat Campus, 85000 Segamat, Johor, Malaysia.

DOI:

https://doi.org/10.24191/jcrinn.v10i2.514

Keywords:

Fine Particulate Matter, Meteorological Factors, Wind Speed, Ambient Temperature, Relative Humidity, Bandaraya Melaka

Abstract

The most hazardous pollutant, PM_2.5 has caused serious environmental and public health issues. Living in an area with PM_2.5 pollution can lead to respiratory problems as it can reach the human bloodstream through inhalation. Bandaraya Melaka was chosen to be the study area as it experienced urban tropical environments, where meteorological parameters, including ambient temperature, wind speed, and relative humidity, substantially impact the concentration of PM_2.5. Hence, this study investigates the relationship between the concentration of PM_2.5 and these meteorological factors using daily data collected from January to early July 2019. Statistical analyses were conducted after model adequacy checking on the linearity, normality, homoscedasticity, independence of the error term, no multicollinearity, and the absence of an outlier in multiple linear regression fulfilling through five iterations of outlier removal. The F-test revealed a relationship exists between meteorological factors and the concentration of PM_2.5. The results indicate a moderate positive relationship between meteorological factors and the concentration of PM_2.5, with only 38% of the total variation in the concentration of PM_2.5 explained by these factors. In the t-test, all meteorological variables were found to significantly influence the concentration of PM_2.5, and the final model, containing all factors, was identified as the best-fitting model supported with the lowest AIC and BIC values. This study contributed to better insight into forecasting the quality of the air in tropical urban environments, addressing a research gap in Bandaraya Melaka. These findings are essential for designing effective air quality management strategies, protecting public health, and supporting urban development.

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