A Novel Method to Analyze NO2 Spatiotemporal Variability Over Eastern China

Abstract:

Weather-determined regional day-to-day variability is a major pattern for nitrogen dioxide (NO2) and other air pollutants over eastern China. This variability is largely non-periodic, compared to its diurnal cycle, posing a difficulty for traditional periodicity-based spatiotemporal analysis. Here, we combine the Empirical Orthogonal Functions (EOF) and the Ensemble Empirical Mode Decomposition (EEMD) analyses to study spatiotemporal variations of ground-level NO₂ (measured from more than 160 urban or suburban sites) and its association with meteorological processes over Eastern China. We find that diurnal variation dominates in summer, being associated with diurnally varying photochemistry and PBL mixing strength. In winter, day-to-day variability clearly exhibits, as governed by the weather system, mostly by the passage of clean and cold air from the north.

We further diagnose the scale-dependent processes and evaluate how well current chemical transport models can capture these processes and resulting NO₂ variations. We perform the EOF-EEMD analysis on GEOS-Chem and CMAQ simulations in winter. Both models cannot reproduce the observed day-to-day variation very well. CMAQ exhibits stronger NO₂ diurnal cycle than observed due to too strong variability in PBL mixing. Specifically, its PBL mixing is too strong in the daytime and too weak at night, leading to an underestimate of NO₂ by about 10 ppb in the day but an overestimate by ~10 ppb at night. Other Analyses are still ongoing.