1. Radon-based estimates of equivalent mixing layer heights: A long-term assessment
- Author
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Roberta Vecchi, Gianluigi Valli, F.A. Piziali, M. Favaron, and V. Bernardoni
- Subjects
Pollution ,Atmospheric Science ,010504 meteorology & atmospheric sciences ,media_common.quotation_subject ,Air pollution ,chemistry.chemical_element ,Radon ,010501 environmental sciences ,Atmospheric dispersion modeling ,Atmospheric sciences ,medicine.disease_cause ,01 natural sciences ,Term (time) ,chemistry ,Pollution monitoring ,Atmospheric instability ,medicine ,Environmental science ,Mixing (physics) ,0105 earth and related environmental sciences ,General Environmental Science ,media_common - Abstract
Air pollution events at urban locations are driven by both emissions and atmospheric dispersion conditions. Atmospheric dispersion is not routinely assessed at monitoring networks thus preventing the possibility of understanding if high pollution events are due to increasing emissions or to the occurrence of atmospheric stability conditions. In principle, this piece of information would be very useful to implement effective strategies for pollution abatement. In this work, an 18-year long dataset of radon (222Rn) progeny measurements was used to estimate equivalent mixing layer heights (hereafter referred to as MH) with hourly resolution by means of a box model. Mean MH obtained by more conventional modelling approaches based on turbulence variables on a 5-year long dataset agreed very well with results obtained by the box model. It is noteworthy that in the literature there are scarce MH data for such long periods and comparisons between estimates by radioactive tracers and other approaches are often limited to a few days/weeks. Results suggested that relatively simple methods like the one here proposed could be implemented at pollution monitoring stations in order to improve available information and better understand the evolution of pollution events on 1-h timescale. In addition, the long-term assessment here presented provides useful data to pursue MH climatological studies.
- Published
- 2019
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