A new metric space incorporating radon-222 for generation of back trajectory clusters in atmospheric pollution studies

A novel metric space for the clustering of back trajectories to be used in fine particle aerosol data analysis was proposed and evaluated. The metric is based on spatial and non-spatial variables incorporating great-circle distance, altitude and radon-222.Its performance was examined using the intra-cluster variation of measured and fingerprint apportioned aerosol mass as the quantitative criterion. The new metric was demonstrated to perform better than those based on great-circle distance, or a great-circle distance and altitude alone. The same criterion was applied to investigate the clustering performance as a function of the length of its back trajectories. The optimum back trajectory length was found to be dependent on the pollution source being considered.Performance tests, as well as the application of the new metric space to re-analysis of previously published results, were based on a three year long dataset comprising co-located aerosol fine particles (PM_2.5) collection and hourly measurements of radon-222 concentration.The new metric space can easily be redefined to include other trace species.     

Ground based radon-222 observations and their application to atmospheric studies

The aim of this paper is to review recent trends in the application of ground based radon observations to atmospheric research. In spite of over four decades of atmospheric radon monitoring, only in the past decade has the potential of this passive tracer been realised through a series of atmospheric model evaluation studies. Firstly, the key operational requirements for baseline radon detectors are briefly discussed, including lower limit of detection and response time. Then, current radon-related benchmarks for the evaluation of regional and global models are reviewed, with particular consideration given to the implications of data availability, resolution, site location and model spatial/temporal resolution. An 8-year subset of radon observations from the Cape Grim Baseline Air Pollution Station is used to suggest new benchmarks that exploit long-term data sets. Lastly an overview is presented of a technique that uses radon to estimate regional fluxes of climatically sensitive gases, with specific examples for CO2, CH4 and N2O.     

Seasonal variability of radon-derived fetch regions for Sado Island,Japan, based on 3 years of observations: 2002–2004

Three years of hourly atmospheric radon measurements at Sado Island (Japan) are discussed and compared with corresponding measurements at Gosan (South Korea), and Hok Tsui (China). In conjunction with back trajectory analysis, Sado radon data are used to characterise the seasonal variability in fetch regions of air masses subject to extremes of terrestrial influence. In winter, fetch regions of air masses that have experienced the greatest terrestrial influence covered southern Siberia; in summer, the terrestrial fetch was dominated by Japan; throughout the remaining months the terrestrial fetch encompassed the Korean Peninsula and far eastern China. Summer radon data are then used to estimate the radon flux from central Honshu (23.5 mBq m^?2 s^?1), which varied regionally between 10.6 and 47.9 mBq m^?2 s^?1. The Sado radon record reported here completes a 4-site, multi-year dataset of hourly radon concentrations across East Asia and the central Pacific (spanning 16° of latitude), which constitutes a unique evaluation tool for transport and mixing schemes of atmospheric and chemical transport models.