Publications by authors named "Susan K Harry"
Article Synopsis
- The study investigates how climate change affects pollen levels and aims to enhance pollen forecasting using advanced models like CatBoost and deep learning across 23 cities worldwide.
- The results show that cities like Mexico City and Santiago have the most accurate pollen forecasts, while Brisbane and Seoul perform poorly, highlighting key environmental factors that influence pollen concentrations.
- Understanding which environmental variables are most significant for pollen predictions can improve the accuracy of forecasts, making this research valuable for public health and environmental planning.
Background: Ongoing climate change might, through rising temperatures, alter allergenic pollen biology across the northern hemisphere. We aimed to analyse trends in pollen seasonality and pollen load and to establish whether there are specific climate-related links to any observed changes.
Methods: For this retrospective data analysis, we did an extensive search for global datasets with 20 years or more of airborne pollen data that consistently recorded pollen season indices (eg, duration and intensity).