Simulation of Air Pollution in Kyiv Caused by Wildfires in the Fall of 2024

Abstract

Introduction. Air pollution in Kyiv is frequently influenced by wildfires occurring outside the city, although their contributions are not always readily identifiable.
Problem Statement. Quantitative analysis and prediction of wildfire-induced air pollution require accurate assessment of emission rates, which can be derived from satellite data such as MODIS fire products.
Purpose. This study aims to implement a methodology for assessing air pollution following wildfires by combining existing parameterizations of pollutant emissions with state-of-the-art atmospheric transport models, and to validate this methodology using measurements collected during a real air pollution episode in Kyiv in September 2024.
Materials and Methods. MODIS fire products and established methods for their processing have
been employed. Atmospheric transport has been simulated with the dispersion module of the RODOS system. Meteorological input is taken from the WRF-Ukraine numerical weather prediction system. Observational data on PM2.5 concentrations in Kyiv have been used for validation. Lagrangian atmospheric transport modeling methods have been employed.
Results. A methodology for estimating wildfire emission rates has been developed by integrating parameterizations of particulate matter emissions from individual MODIS fire detections with methods for evaluating time-integrated fire radiative energy. The resulting emission estimates have been used to simulate PM2.55 pollution in Kyiv during the real pollution episode on 20 September 2024. The model has skillfully reproduced both the plume arrival time and the temporal evolution of PM2.55 concentrations in comparison with measurements. The 24-hour average wildfire-induced PM2.5 concentrations have ranged from 11.6 to 34.7 μg/m³ across different parts of Kyiv, exceeding the regulatory maximum permissible value of 25 μg/m³.
Conclusions. The developed methodology has demonstrated its suitability for operational forecasting of wildfirerelated air contamination and for retrospective analyses of historical pollution episodes, enab ling quantification of wildfire contributions to observed air quality degradation.