The method of Spatio-temporal Estimation of Parameters of Ambrosia Areas According to the Data of Only One Post of the European System of Aerobiological Monitoring

Abstract

The article is devoted to the development of the method of spatio-temporal estimation of the parameters of areas of ambrosia according to the data of only one post of the European Aerobic Monitoring System (EAM). It is noted that the low regularity of the EAM postal network on the territory of Ukraine does not allow the use of precise mathematical models (for example, SILAM) for modeling the processes of airborne embargo explosion in the air. This makes it more urgent to create less precise methods, but those that would allow simulation to be carried out under conditions of significant uncertainty of the task and the minimum amount of input data.

Adapted to Ukraine are known data of typical curves of the intensity of pollen production of ambrasia during the day after sunrise, depending on the relative humidity of the air by moving from the 1-hour to 2-hour interval, which corresponds to the step of observation in Ukraine. It is established that for the approximation of these curves, the complex functions lack data (there are only 3 to 6 points), and logistic, polynomial and other functions do not provide the necessary accuracy and monotony. Therefore, it was proposed to use the spline approximation of the first (line) and the second (parabola) order. This allows you to fit any typical curve, even at 2-3 points. However, such an attachment may lead to false coincidences; therefore, the validity criterion based on the weighting of the applied splines is proposed: the more splines are applied, the higher the accuracy of the approximation.

It is noted that due to a change in the direction of the wind within one day, the pollen can fly a greater distance to the EAM post, and therefore the measured data may be delayed. It is proposed to take into account this feature by the coefficient of deformity. The mathematical conditions for its inclusion are derived.

For the first time a method of spatio-chronological estimation of possible locations and intensity of pollen production in the areas of amygdala was developed on the basis of data of only one post of the EAM in conditions of uncertainty and the minimum amount of data using spline approximation of typical pollen production models.

The efficiency of the method is confirmed by real data — the known and discovered new possible habitats were confirmed.