Atmospheric mold spore counts in relation to meteorological parameters

Area of Science:

• Environmental Science
• Aerobiology
• Biometeorology

Background:

• Fungal spores are significant aeroallergens.
• Understanding fungal spore dynamics is crucial for public health.
• Previous studies have explored fungal spore-weather relationships.

Purpose of the Study:

• To model daily fungal spore counts (Cladosporium, Alternaria, Epicoccum) in Denver, Colorado.
• To investigate the relationship between spore counts and meteorological parameters.
• To develop predictive models for fungal aeroallergen exposure.

Main Methods:

• Collected daily fungal spore counts for 8 years using a Rotorod sampler.
• Acquired daily weather data including temperature, humidity, precipitation, barometric pressure, and wind speed.
• Applied time series analysis, specifically autoregressive moving average (ARMA) models, to analyze spore count data and weather variables.

Main Results:

• Cladosporium spore counts showed a positive correlation with average daily temperature and relative humidity (P < 0.02).
• Cladosporium spore counts exhibited a negative correlation with precipitation.
• Alternaria and Epicoccum spore counts did not demonstrate significant predictability based on the studied weather variables.
• A mathematical model was developed for Cladosporium, incorporating seasonality and weather variables.

Conclusions:

• Time series analysis effectively models fungal spore counts and relates them to meteorological factors.
• Seasonal patterns and specific weather parameters significantly influence Cladosporium spore concentrations.
• The developed models can aid in estimating exposure to fungal aeroallergens.