This study examines aerosol optical depth (AOD), a crucial indicator of airborne particle (i.e. aerosol) concentration, in the semi-arid urban environment of Jaipur, India, spanning the years 2015 to 2025. We focused on understanding its seasonal rhythms, long-term direction, and any unusual deviations in relation to local weather patterns. To build this analysis, we combined satellite-derived and AERONET AOD data with ground-based air quality and meteorological observations. Our approach included climatological assessments, trend analysis using the Modified Mann - Kendall test, and both correlation and regression modelling. We also employed standardized anomaly detection to pinpoint exceptional events. The results highlight a clear seasonal cycle, with aerosol levels peaking during the pre-monsoon and monsoon periods. However, over the full decade, our trend analysis did not find statistically significant long-term increases or decreases in either AOD or the meteorological variables. A simple linear regression model explained only a small portion of the AOD variability (R2 approximate to 0.08), indicating the presence of more complex drivers. Nonlinear relationships between aerosol loading and meteorological variables were further examined using Generalized Additive Models (GAM), which revealed threshold-dependent responses in aerosol behaviour. Furthermore, the anomaly analysis identified specific, episodic events where AOD values spiked beyond the typical range (exceeding +/- 2 standard deviations). This indicates that extreme aerosol loads are often driven by individual events rather than a persistent, gradual change in the atmosphere. In essence, aerosol behaviour over Jaipur appears to be governed primarily by predictable seasonal forces and short-term atmospheric processes, rather than a pronounced long-term trend.