Seasonal variability of air pollutants and their relationships to meteorological parameters in an urban environment

Air quality in urban areas is deteriorating over time with the increased pollutant distribution levels mainly caused due to anthropogenic activities. In addition, these pollutant distribution levels may relate to changing meteorological conditions. However, the relationships were not researched in-depth in the context of Sri Lanka, a country with a significant impact on climate change. The main objective of this study was to provide a broader perspective on the seasonal variation of tiny particles in air (PM2.5 and PM10), nitrogen dioxide (NO₂), carbon monoxide (CO), ozone (O₃), and sulfur dioxide (SO₂) in two urban cities (Colombo and Kandy) in Sri Lanka over 3 years period (2018-2021) and the possible relationships between air pollution and meteorological variables. Results show that all the aforementioned pollutants except O₃ consistently depict two peaks during the day, one in the morning (∼07:00-09:00 local time) and the other in the evening (∼18:00-20:00 local time). These peaks coincided with the traffic jams observed in both cities. The results further revealed that the concentration of all pollutants has significant seasonal variations. Compared to two monsoon seasons, the highest daily average PM2.5 (31.2 μg/m³), PM10 (49.5 μg/m³), NO₂ (18.9 ppb), CO (717.5 ppb), O₃ (18.5 ppb), and SO₂ (9.4 ppb) concentrations in Colombo are recorded during northeast monsoon (NEM) seasons while contrast pattern is observed in Kandy. In addition, it was found that wind speed with its direction is the most influencing factor for the pollutant concentration except for SO₂ and O₃ in two cities, and this is irrespective of the season. This study's findings contribute to understanding the seasonality of ambient air quality and the relationship between meteorological factors and air pollutants. These findings ultimately lead to designing and implementing season-specific control strategies to achieve air pollution reduction at a regional scale.