Selected Land Cover Factors as a Determinant of Differences in Particulate Matter Concentrations – A Case Study of Warsaw, Poland

An important aspect of modelling is the choice of descriptor variables. This study extended typical modelling of PM₁₀ concentrations based on meteorological parameters with additional variables related to the spatial characteristics of the environment. Meteorological parameters have smaller spatial gradients, while land cover is point-specific. Daily meteorological data from the Warsaw Chopin Airport (EPWA) and satellite land cover data from the Polish Space Agency were used to describe PM₁₀ concentrations at 5 air quality stations in Warsaw for 2021. The multilinear model developed in Gretl showed that significant factors increasing PM₁₀ concentrations included maximum daily temperature, duration of fog, haze, frost, and the proportion of artificial surfaces and coniferous tree cover within a 1 km radius of the stations. PM₁₀ concentrations were negatively correlated with increases in daily minimum temperature, duration of rainfall, snowfall, wind >=10m/s, and the proportion of deciduous tree cover and herbaceous vegetation. The use of land cover parameters improved the model’s coefficient of determination for daily PM₁₀ average concentrations.