Alternaria spores in the atmosphere of Sydney, Australia, and relationships with meteorological factors

Abstract

Alternaria spores are found in the atmosphere in many locations around the world. They are significant from a human health perspective because they have been known to trigger allergic respiratory disease such as asthma and hay-fever. The presence of Alternaria spores in the atmosphere has been related to meteorological factors in past studies, but this has not been done previously in Sydney, Australia. This paper reports the results of such a study in Sydney. Alternaria spore concentration data for the period 19 August 1992 to 31 December 1995 were examined with meteorological data for the same period. The daily Alternaria spore concentration was compared to the meteorological data for the same day and for up to 3 days previously. The analysis methods were Spearman's rank correlation and multiple regression. Alternaria spores appear in the atmosphere of Sydney year-round, although they peak over spring, summer, and autumn. A number of meteorological factors, including mean, minimum, and maximum, temperature, dew point temperature, and air pressure, are significantly correlated with the atmospheric concentration of Alternaria spores. Some of these meteorological variables (temperature and dew point temperature) show significant correlations with a 1, 2, and 3 day lag, as well as for the same day. Regression models indicate that up to 31.1% of the variation in Alternaria spore concentration can be explained by meteorological factors. There is potential for the results of this study to be used by public health authorities in the prediction of Alternaria spore concentrations in Sydney.

Airborne allergenic fungal spores and meteorological factors in Greece: Forecasting possibilities

“…Thus, it refers not only to the direct 'dose-response effect', but also to the construction of time-delayed relations (lags) among various variables (Chatfield, 1989). It is well known that environmental data collected over consecutive time periods are often serially correlated, with data closely associated having higher correlations between them than data farther apart (Katial et al 1997;Mitakakis et al 2001;Munuera Giner et al 2001;Stennett & Beggs, 2004). Similarly to dependent and independent variables, regression errors could additionally be correlated serially.…”

“…However, the majority of these efforts have more frequently aimed at the prediction of airborne pollen count; advanced forecasting models of airborne fungal spore circulation are comparatively few (Katial et al 1997), and most of them usually display low predictability (AnguloRomero et al 1999;Mitakakis et al 2001;Troutt & Levetin, 2001;Stennett & Beggs, 2004).…”

“…The dispersal and transport of airborne fungal spores -and therefore the predictive power of created statistical models -are influenced by several meteorological factors, such as wind, rainfall and air temperature components, atmospheric pressure, solar radiation, and relative humidity (Solomon, 1978;Hjelmroos, 1993;Katial et al 1997; Kurkela, 1997;Angulo-Romero et al 1999;Corden & Millington, 2001;Mitakakis et al 2001;Munuera Giner et al 2001;Troutt & Levetin, 2001;Stennett & Beggs, 2004). Nevertheless, the exact relationship of spore counts and meteorological factors is not thoroughly understood.…”

“…Nevertheless, the exact relationship of spore counts and meteorological factors is not thoroughly understood. Moreover, the indirect effect and time-delayed interrelationship has rarely been investigated and forecasts have been created either for rather short time-horizons or with limited accuracy Stennett & Beggs, 2004).…”

The ice nucleation ability of one of the most abundant types of fungal spores found in the atmosphere

“…The amount of fungal spores in the atmosphere is subject to the time of day and meteorological factors (Gilbert and Reynolds, 2005;Hirst, 1953;Kurkela, 1997;Stennett and Beggs, 2004;Stȩpalska and Wołek, 2009). The average number of fungal spores in the continental boundary layer air is on the order of 10 3 -10 4 m −3 (Elbert et al, 2007).…”