Abstract

This study analyses potential associations between day-to-day variations in common ragweed pollen counts in the southern Hungarian district of Szeged and meteorological variables using adapted factor analysis. The database includes ten years (1997-2006) worth of data on daily common ragweed pollen ratios (value on the given day per value on the day before) and daily differences (value on the given day minus value on the day before) in eight meteorological variables (mean temperature, minimum temperature, maximum temperature, temperature range, irradiance, relative humidity, wind speed, and rainfall) over the ragweed pollen season. This method is new, as it has only been applied in the economics. In factor analysis it is advisable to combine all the weights of the factors and the resultant variable into one factor indicating the rank of importance of the given explanatory variables in influencing the resultant variable, while the remaining factors are uncorrelated with the resultant variable. The procedure shows that wind speed, rainfall, and temperature range are the most important, while minimum temperature and irradiance are the least important meteorological variables influencing daily pollen ratios. We found a tendency to stronger associations between the meteorological variables and the pollen variable when the pollen ratio was 1 or below. This is due to the fact that data corresponding to the pollen ratio over 1 come mainly from the prepeak pollen season, while data corresponding to less than 1 are characteristic of the post-peak pollen season (late summer to early autumn).

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