Environmental data treatment to support exposure studies: The statistical behavior for NO2, O3, PM10 and PM2.5 air concentrations in Europe
2020
Bartzis, John G. | Kalimeri, Krystallia K. | Sakellaris, Ioannis A.
In determining and assessing external exposure, there is a need for extensive environmental data sets of sufficient time and space resolution. It is unlikely that a complete set of those data exist for a specific study. Therefore, there will be a need to fill the necessary data gaps. As a first step towards this direction, the statistical behavior of the parameters involved can be estimated so that such parameters can be statistically reconstructed in finer scales.In this study the methodology has been applied to the air concentrations of the priority pollutants NO₂, O₃, PM10 (particulate matter with an aerodynamic diameter of<10 μm) and PM2.5 (particulate matter with an aerodynamic diameter of<2.5 μm). More specifically, the hourly and the daily concentrations at a given site of those pollutants can be statistically reconstructed assuming known (a) the concentration annual average (m), (b) the pdf of the ratio of the standard deviation over the annual average (σ/m) for the hourly/daily concentrations and (c) the pdf for hourly/daily concentrations themselves. In the case that PM2.5 annual value is missing, it is estimated statistically from the PM10 annual value and the PM2.5/PM10 ratio statistics. As a first test, the proposed methodology is applied for the year 2012 arriving to concrete proposals concerning the statistical behavior of the above-mentioned parameters.
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