Spatial and Temporal Variation of Criteria Air Pollutants over Rwanda (2019-2023) and the Influence of Meteorological Factors — Oak Academic Publishing
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Spatial and Temporal Variation of Criteria Air Pollutants over Rwanda (2019-2023) and the Influence of Meteorological Factors
School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China
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School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China
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School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China
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School of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing, China
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School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China
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School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China
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School of Ecology and Applied Meteorology, Nanjing University of Information Science and Technology, Nanjing, China
Air pollution is among the most serious environmental and public health problems worldwide, especially in low and middle-income countries like Rwanda. This study explores the spatial and temporal variations of criteria air pollutants across Rwanda from 2019 to 2023, utilizing data from 18 national air quality monitoring stations and 16 weather stations. Results reveal that PM 2.5 and PM 10 concentrations exceeded WHO guidelines, with the mean reaching 90 µg/m 3 (PM 2.5 ) and 127 µg/m 3 (PM 10 ), predominantly in Kigali City, Northern, and Western provinces. CO concentration peaked in the Eastern province and Kigali. In contrast, NO 2 and O 3 were highest in the Central and Northern provinces. Over five years, NO 2 showed a slight increase trend, while CO, O 3 , and SO 2 displayed minor declines and remained in line with WHO guidelines. Diurnal variations highlighted morning (06:00-07:00 am) and evening (06:00-09:00 pm) pollutant peaks, driven by morning rush hour traffic, domestic stoves, and industrial activities. Border stations like Bugeshi-Rubavu recorded elevated pollutant levels due to cross-border emissions from the bordering countries. Seasonal analysis revealed higher pollutant levels during dry seasons, influenced by reduced rainfall and increased anthropogenic activities. CO concentration was positively correlated with temperature during MAM (r = 0.69) due to increased biomass burning and agricultural emissions. Wind speed is negatively correlated with PM 2.5 and PM 10 in JJA, aiding pollutant dispersion, while PM 2.5 is positively correlated with humidity in MAM (r = 0.7), linked to secondary aerosol formation. These findings underscore the urgent need to improve air quality, particularly in urban and border regions, and address Rwanda’s transboundary pollution concerns.
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