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...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2025-05-01
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| Series: | Architecture, Civil Engineering, Environment |
| Online Access: | https://doi.org/10.2478/acee-2025-0012 |
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| Summary: | 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. |
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| ISSN: | 2720-6947 |