Atmospheric mold spore counts in relation to meteorological parameters

Abstract

Fungal spore counts of Cladosporium, Alternaria, and Epicoccum were studied during 8 years in Denver, Colorado. Fungal spore counts were obtained daily during the pollinating season by a Rotorod sampler. Weather data were obtained from the National Climatic Data Center. Daily averages of temperature, relative humidity, daily precipitation, barometric pressure, and wind speed were studied. A time series analysis was performed on the data to mathematically model the spore counts in relation to weather parameters. Using SAS PROC ARIMA software, a regression analysis was performed, regressing the spore counts on the weather variables assuming an autoregressive moving average (ARMA) error structure. Cladosporium was found to be positively correlated (P < 0.02) with average daily temperature, relative humidity, and negatively correlated with precipitation. Alternaria and Epicoccum did not show increased predictability with weather variables. A mathematical model was derived for Cladosporium spore counts using the annual seasonal cycle and significant weather variables. The model for Alternaria and Epicoccum incorporated the annual seasonal cycle. Fungal spore counts can be modeled by time series analysis and related to meteorological parameters controlling for seasonallity; this modeling can provide estimates of exposure to fungal aeroallergens.

Primary biological aerosol particles in the atmosphere: a review

“…Dry-discharged spore concentrations tend to be enhanced during warm, dry weather conditions, whereas actively wet discharged spores tend to be enhanced during humid conditions such as those at night and in the early morning hours (Graham et al, 2003;Elbert et al, 2007). Emission and dispersal of fungal spores can thus be selectively correlated with various meteorological parameters and usually have specific behaviours, depending on the species involved (Fitt et al, 1989;Pasanen et al, 1991;Calderon et al, 1995;Katial et al, 1997;Sabariego et al, 2000;Troutt and Levetin, 2001;Burch and Leventin, 2002;Jones and Harrison, 2004;Grinn-Gofron and Mika, 2008;Oliviera et al, 2009).…”

“…As pollen is known to cause allergies in humans, these shifts may also lead to changes in human exposure and changes in the prevalence and severity of symptoms in individuals with allergic diseases (Reid and Gamble, 2009). Alterations in the timing of aeroallergen production in response to weather variables have been clearly demonstrated for certain tree species, but less for grass, weed and mould (Katial et al, 1997;Emberlin et al, 2002;Clot, 2003).…”

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

“…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.…”

Ocurrencia de Cladosporium en la atmósfera de la Plaza San Martín de Lima y su relación con algunos factores meteorológicos

“…Los mismos resultados fueron obtenidos por Aira et al (2012), en contraste, Katial et al (1997) halló una correlación positiva entre la humedad relativa y el número de conidios de Cladosporium. Además, se puede observar que existe una relación inversa entre la humedad relativa y la velocidad del viento (Figuras 1c y 1a) en la liberación de los conidios.…”