Numerical simulation of allergic pollen over a coastal city in Korea

Abstract

Background: The recent increase in prevalence of allergic diseases and climate change stimulate the interest in allergic pollen. Numerical modeling techniques can enhance our understanding about spatiotemporal pollen patterns and help to achieve a better management of pollen-related allergic diseases. Aims: This study aims to simulate oak pollen distributions in multiscale domain using a new model system developed by modifying the existing pollen emission and air quality models and to evaluate modeled concentrations for urban scale prediction with observations in Ulsan city, Korea. Methods: Gridded inventories of oak pollen sources were calculated by a pollen-emission model using the Weather Research and Forecasting (WRF) model-based meteorology fields and detailed land cover information. The emission model was incorporated into the modified Community Multiscale Air Quality (CMAQ) model which can address pollen dispersion and deposition in urban and regional scales. A 10 day-run for oak pollen simulation was conducted using the developed model during an episode of the 2011 spring pollen season. Results: Modeled pollen concentrations were evaluated against data collected at the Ulsan Environmental Health Center sampling site within the model domain. Overall, the simulated temporal patterns reasonably followed the measured profiles of oak pollen, but there were large differences between modeled and measured concentrations at certain times due to the discrepancy in winds. Some simulations indicated nighttime peak of oak concentration was closely associated with regional transport under strong wind condition and change in boundary layer structure. In addition, the inflow of marine air masses mainly contributed to decrease in surface oak concentrations in the city atmosphere. Conclusions: The present study describes the successful application of air quality modeling system to simulate oak concentration in urban scale. However, a better understanding of the pollen release and deposition processes will be needed to improve pollen prediction by numerical models.