Spatiotemporal Patterns and Lagged Effects in Urban Air Quality: A Comparative Analysis of Two Central American Cities (#2306)
Read ArticleDate of Conference
July 15-17, 2026
Published In
"Engineering without Borders: Artificial Intelligence, Knowledge, Innovation, and Alliances for a Future from the Americas"
Location of Conference
Santiago (Chile)
Authors
Deras, Nadia
Bulnes, Renata
Abstract
Air pollution remains a critical public health and sustainability challenge, particularly in rapidly urbanizing regions with limited regulatory monitoring infrastructure. While most urban air quality assessments rely on mean concentration comparisons and exceedance thresholds, less attention has been given to short-term temporal persistence dynamics that influence exposure duration. This study introduces the concept of urban atmospheric persistence to evaluate short-term retention of PM2.5 concentrations in two Central American urban systems using hourly open-access sensor data. A comparative time-series framework was applied to analyze lag-based autocorrelation (1–6 hours) over a multi-week period, including combustion-intensive celebration days. Results reveal strong immediate dependence in both cities (Lag 1 = 0.53), but distinct decay trajectories thereafter. The city of San Pedro Sula exhibits sustained multi-hour persistence, including secondary reinforcement at Lag 3 (0.53), whereas City of Tegucigalpa demonstrates faster monotonic decay, approaching near-zero correlation by Lag 6. These findings suggest that urban systems may differ not only in pollution magnitude but also in atmospheric retention structure. The study contributes empirical evidence from an underrepresented region and demonstrates the analytical value of combining open sensor networks with time-series methods. Limitations include the absence of meteorological covariate integration and API-based retrieval constraints inherent to open-access platforms, which restricted the analysis to approximately 1000 hourly observations per monitoring location. Despite these constraints, the results provide a replicable framework for evaluating temporal persistence as a complementary indicator for urban sustainability assessment.