Temporal assessment of air quality in major cities in Nigeria using satellite data

• Published in: Atmospheric Environment: X Vol. 20; p. 100227
• Main Authors: Mahmud, Khaled, Mitra, Bijoy, Uddin, Mohammed Sakib, Hridoy, Al-Ekram Elahee, Aina, Yusuf A., Abubakar, Ismaila Rimi, Rahman, Syed Masiur, Tan, Mou Leong, Rahman, Muhammad Muhitur
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2023; Elsevier
• Subjects: Air pollution; Multivariate statistics; Nighttime light data; Spatiotemporal analysis; Welch's ANOVA test; Air pollution; Multivariate statistics; Nighttime light data; Spatiotemporal analysis; Welch's ANOVA test
• ISSN: 2590-1621; 2590-1621
• DOI: 10.1016/j.aeaoa.2023.100227

This study evaluated the concentrations of tropospheric nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), and Aerosol Index (AI) as well as different meteorological parameters, including atmospheric temperature (AT), relative humidity (RH), and wind speed (WS) in nine Nigerian cities: Aba, Benin, Ibadan, Kaduna, Kano, Lagos, Onitsha, Port Harcourt, and Umuahia. The role of socioeconomic activities on air pollution was also investigated using nighttime light radiance as a surrogate measure. Welch's one-way ANOVA test was performed for the variance study to evaluate the concentration dynamics of the selected tropospheric air pollutants and their association with nighttime light radiance. The mean concentration of CO and AI was highest in Kano, while that of O3 was the lowest. A similar pattern was also observed in the spatiotemporal transition of the selected pollutants and the nighttime light during the study period. Further, the correlation analysis revealed that AT is positively correlated with NO2 except in Aba and Benin cities, while it is positively correlated with CO and AI for all cities. The principal component analysis (PCA) revealed that O3 and RH have strong negative factor loadings, whereas CO, AI, and AT have strong positive factor loadings. This study will guide future researchers by associating the level of pollution with socioeconomic activities, especially during the absence of permanent air quality stations. •Multifaceted analysis assesses air pollutants' dynamics and nighttime lights.•Multiple cities exceed WHO 24-h air pollutant standards.•Study guides linking pollution to socioeconomics, despite station absence.•Results aid policymakers in targeted air quality improvement efforts.