0000000000391091
AUTHOR
Mikhail Sofiev
A statistical model for predicting the inter-annual variability of birch pollen abundance in Northern and North-Eastern Europe
The paper suggests a methodology for predicting next-year seasonal pollen index (SPI, a sum of daily-mean pollen concentrations) over large regions and demonstrates its performance for birch in Northern and North-Eastern Europe. A statistical model is constructed using meteorological, geophysical and biological characteristics of the previous year). A cluster analysis of multi-annual data of European Aeroallergen Network (EAN) revealed several large regions in Europe, where the observed SPI exhibits similar patterns of the multi-annual variability. We built the model for the northern cluster of stations, which covers Finland, Sweden, Baltic States, part of Belarus, and, probably, Russia and…
ARIA‐EAACI care pathways for allergen immunotherapy in respiratory allergy
Funding Information: BSreports personal fees from Allergopharma, during the conduct of the study; grants from National Health Programm, grant, personal fees from Polpharma, ASTRA, personal fees from Mylan, Adamed, patient ombudsman, national Centre for Research and Development, Polish Allergology Society. Funding Information: NGP reports personal fees from Novartis, Nutricia, HAL, MENARINI/FAES FARMA, SANOFI, MYLAN/MEDA, BIOMAY, AstraZeneca, GSK, MSD, ASIT BIOTECH, Boehringer Ingelheim, grants from Gerolymatos International SA, Capricare. Funding Information: CA reports grants from Allergopharma, grants from Idorsia, Swiss National Science Foundation, Christine Kühne‐Center for Allergy Rese…
Statistical modelling of non-stationary processes of atmospheric pollution from natural sources: example of birch pollen
Abstract A statistical model for predicting daily mean pollen concentrations during the flowering season is constructed and its parameterization and application to birch pollen in Riga (Latvia) are discussed. The model involves several steps of transformations of both meteorological data and pollen observations, aiming at a normally distributed homogeneous stationary dataset with linearized dependencies between the transformed meteorological predictors and pollen concentrations. The data transformation includes normalization of daily mean birch pollen concentrations, a switch of the independent axis from time to heat sum, a projection of governing parameters to pollen concentrations, and a …
MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe
Abstract. This paper presents the first ensemble modelling experiment in relation to birch pollen in Europe. The seven-model European ensemble of MACC-ENS, tested in trial simulations over the flowering season of 2010, was run through the flowering season of 2013. The simulations have been compared with observations in 11 countries, all members of the European Aeroallergen Network, for both individual models and the ensemble mean and median. It is shown that the models successfully reproduced the timing of the very late season of 2013, generally within a couple of days from the observed start of the season. The end of the season was generally predicted later than observed, by 5 days or more…
ARIA digital anamorphosis: Digital transformation of health and care in airway diseases from research to practice: Review
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Multi-model ensemble simulations of olive pollen distribution in Europe in 2014
Abstract. A 6-models strong European ensemble of Copernicus Atmospheric Monitoring Service (CAMS) was run through the season of 2014 computing the olive pollen dispersion in Europe. The simulations have been compared with observations in 6 countries, members of the European Aeroallergen Network. Analysis was performed for individual models, the ensemble mean and median, and for a dynamically optimized combination of the ensemble members obtained via fusion of the model predictions with observations. The models, generally reproducing the olive season of 2014, showed noticeable deviations from both observations and each other. In particular, the season start was reported too early, by 8 days …