Multivariate analysis of air pollution and associated potential respiratory health risks in urban areas of the Southeast Asian region and Africa

Samuel Nketia  Boateng; Felicia  Takyi; Gertrude  Oboh; Harriet Kyerewaah  Ampoful; Josephine  Kuttor; Albert Ebo  Duncan

doi:10.18502/japh.v11i1.21270

Samuel Nketia Boateng Department of Civil and Environmental Engineering, School of Sustainable Engineering, College of Agriculture and Natural Sciences, University of Cape Coast, Cape Coast, Ghan
Felicia Takyi Department of Environmental Sciences, School of Biological Sciences, College of Agriculture and Natural Sciences, University of Cape Coast, Cape Coast, Ghana
Gertrude Oboh Department of Civil and Environmental Engineering, School of Sustainable Engineering, College of Agriculture and Natural Sciences, University of Cape Coast, Cape Coast, Ghana
Harriet Kyerewaah Ampoful Department of Civil and Environmental Engineering, School of Sustainable Engineering, College of Agriculture and Natural Sciences, University of Cape Coast, Cape Coast, Ghana
Josephine Kuttor Department of Civil and Environmental Engineering, School of Sustainable Engineering, College of Agriculture and Natural Sciences, University of Cape Coast, Cape Coast, Ghana
Albert Ebo Duncan Department of Civil and Environmental Engineering, School of Sustainable Engineering, College of Agriculture and Natural Sciences, University of Cape Coast, Cape Coast, Ghana

DOI: https://doi.org/10.18502/japh.v11i1.21270

Keywords: Air pollution; Temporal coverage; Particulate matter; Southeast Asian region; African region

Abstract

Introduction: The nature of heavy pollution incidence that plagues the South East Asian (SEAR) Region and the African region demands the understanding of air pollution dynamics within these regions to inform policy formulation to improve environmental health. This study therefore aims to grasp the transformation of air pollutants in the last 10 years in the two regions and their potential to influence respiratory health.

Materials and methods: This study used the 6th edition of the ambient air quality data from the WHO website, which was revised and published on January 22, 2024. 1609 dataset was used for this research, spanning the 16 countries.

Results: The results of the analysis show that in the last 10 years, the mean PM10 (64.15 ± 40.38 g/m³), PM2.5 (22.98 ± 23.65 g/m3), and NO₂ (8.83 ± 7.99 g/m³) were 64.15 ± 40.38 g/m³, 22.98 ± 23.65 g/m³, and 8.83 ± 7.99 g/m³, respectively. Consequently, the air quality index for PM10 and PM2.5 stands at 57.73 and 96.59 for the African Region and 55.53 and 74.61 for SEAR, indicating a satisfactory air quality. The principal component analysis showed that NO₂ exposure and monitoring explained 39.91% of the variance in the data, while component 2 (PM10 and PM2.5) explained 19.43%. The regression model showed that PM10 temporal coverage can be used to predict NO₂ concentration. Indicating that better cover for PM10 can be used to estimate NO2 concentration.

Conclusion: This study has highlighted that temporal coverage can be a useful means for air pollutant estimation. Hence, governments should increase monitoring of air pollutants, in this peak era of industrialisation to capture the many unquantified contaminants