ARIMA Analysis of PM Concentrations during the COVID-19 Isolation in a High-Altitude Latin American Megacity

Abstract

The COVID-19 pandemic precipitated a unique period of social isolation, presenting an unprecedented opportunity to scrutinize the influence of human activities on urban air quality. This study employs ARIMA models to explore the impact of COVID-19 isolation measures on the PM10 and PM2.5 concentrations in a high-altitude Latin American megacity (Bogota, Colombia). Three isolation scenarios were examined: strict (5 months), sectorized (1 months), and flexible (2 months). Our findings indicate that strict isolation measures exert a more pronounced effect on the short-term simulated concentrations of PM10 and PM2.5 (PM10: −47.3%; PM2.5: −54%) compared to the long-term effects (PM10: −29.4%; PM2.5: −28.3%). The ARIMA models suggest that strict isolation measures tend to diminish the persistence of the PM10 and PM2.5 concentrations over time, both in the short and long term. In the short term, strict isolation measures appear to augment the variation in the PM10 and PM2.5 concentrations, with a more substantial increase observed for PM2.5. Conversely, in the long term, these measures seem to reduce the variations in the PM concentrations, indicating a more stable behavior that is less susceptible to abrupt peaks. The differences in the reduction in the PM10 and PM2.5 concentrations between the strict and flexible isolation scenarios were 23.8% and 12.8%, respectively. This research provides valuable insights into the potential for strategic isolation measures to improve the air quality in urban environments.