Agnieszka Podstawczyńska

Radon-based technique for the analysis of atmospheric stability – a case study from Central Poland

Abstract An economical and easy-to-implement technique is outlined by which the mean nocturnal atmospheric mixing state (“stability”) can be assessed over a broad (city-scale) heterogeneous region solely based on near-surface (2 m above ground level [a.g.l.]) observations of the passive tracer radon-222. The results presented here are mainly based on summer data of hourly meteorological and radon observations near Łodź, Central Poland, from 4 years (2008–2011). Behaviour of the near-surface wind speed and vertical temperature gradient (the primary controls of the nocturnal atmospheric mixing state), as well as the urban heat island intensity, are investigated within each of the four radon-based nocturnal stability categories derived for this study (least stable, weakly stable, moderately stable, and stable). On average, the most (least) stable nights were characterized by vertical temperature gradient of 1.1 (0.5)°C·m−1, wind speed of ~0.4 (~1.0) m·s−1, and urban heat island intensity of 4.5 (0.5)°C. For sites more than 20 km inland from the coast, where soils are not completely saturated or frozen, radon-based nocturnal stability classification can significantly enhance and simplify a range of environmental research applications (e.g. urban climate studies, urban pollution studies, regulatory dispersion modelling, and evaluating the performance of regional climate and pollution models).

Soil heat flux and air temperature as factors of radon (Rn-222) concentration in the near-ground air layer

Abstract A unique, highly time-resolved, and synchronous three-year dataset of near-surface atmospheric radon-222 as well as soil heat flux and air temperature measurements at two sites (rural and urban) in Central Poland are investigated. The recognition of temporal variability of Rn-222 and selected meteorological variables in the urban and rural areas served to create two statistical models for estimation of this radionuclide concentration at 2 m a.g.l. The description of the relationships between the variables for individual months was established on the basis of an exponential function and an exponential function with time derivative of predictor to account for the hysteresis issue. The model with time derivative provided better results. The weakest fitting of modelled data to empirical ones is observed for the winter months. During subsequent seasons, air temperature as well as QG-driven (soil heat flux) models exhibited very high agreement with the empirical data (MBE, RMSE, MAE, and ‘index of agreement’ by Willmott were used to evaluate the models). A restriction in the use of QG for Rn-222 concentration was observed only in winter in the case of snow cover occurrence, which reduces the daily QG variability.