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Spatial machine learning for air quality mapping in Poland
Poor air quality is one of Poland’s most serious environmental and health problems. In winter the dominant source is low-stack emission - domestic heating with solid fuels - and long-term exposure to particulate matter is associated with thousands of premature deaths per year. State monitoring (GIOŚ) relies on a sparse network of stations, only a few per voivodeship. The question is how to reconstruct a credible, continuous concentration field over the whole country from a small number of point measurements.
The aim of this project is to apply spatial machine learning methods to reconstruct the 2024 annual concentration surface for Poland from station measurements and to assess its health consequences through a population exposure analysis.
HD NHAP LIEU 24NH
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HUONG DAN NHAP LIEU
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HD NHAP LIEU - BUI HA UYEN NHI - 14.09.2026
HD NHAP LIEU - BUI HA UYEN NHI - 14.09.2026
HD NHAP LIEU - 24NH - 14.09.2026
HD NHAP LIEU - 24NH - 14.09.2026
Module 4 Chi-Squared - Goodness of Fit
Saint Louis University AA5221 Applied Analytics & Methods Chi Squared - Goodness of Fit