Investigating the vertical and spatial extent of radon-based classification of the atmospheric mixing state and impacts on seasonal urban air quality.

A recently-developed radon-based method for combined classification of both diurnal and synoptic timescale changes in the atmospheric mixing state is applied to 1-year of observations in Ljubljana (capital of Slovenia). Five diurnal-timescale mixing classes (#1 to #5) were defined for each season along with an additional mixing class (#6) in non-summer months, representative of synoptic-timescale changes of the atmospheric mixing state associated with "persistent temperature inversion" (PTI) events. Seasonal composite radiosonde profiles and mean sea level pressure charts within each mixing class are used to demonstrate the link between prevailing synoptic conditions and the local mixing state, which drives changes in urban air quality. Diurnal cycles of selected pollutants (BC, NO2, CO, PM10, SO2 and O3) exhibited substantial seasonality as a result of changing mixing conditions, source types and strengths. For the more well-mixed conditions (classes #2 to #3), surface wind speeds were 3 times higher than during class #6 (PTI) conditions, resulting in a 3-fold reduction of primary pollutant accumulation. Daily-mean PM10 concentrations only exceeded EU and WHO guideline values in winter and autumn for two of the radon-defined mixing classes: (i) class #5 (strongly stable near-surface conditions associated with passing synoptic anti-cyclone systems), and (ii) class #6 (PTI conditions driven by regional subsidence in the presence of the "Siberian High"). Both mixing states were associated with low mean wind speeds (∼0-0.7 m s-1) and strong thermal stratification, as indicated both by pseudo-vertical temperature gradients (∆T/∆z) and radiosonde profiles. Diurnal ∆T/∆z values indicated limited opportunity for convective mixing of pollutants from the basin atmosphere under these conditions. The demonstrated consistency in atmospheric mixing conditions (vertically and spatially) across the diurnal cycle within each of the defined mixing classes suggests the radon-based classification scheme used in conjunction with 3-D urban sensor networks could be well suited to evaluate mitigation schemes for urban pollution and urban climate.