A GIS-based method for modelling air pollution exposures across Europe
D Vienneau1, K de Hoogh, D Briggs
1Imperial College London, Epidemiology and Public Health, MRC-HPA Centre for Environment and Health, St. Mary's Campus, Norfolk Place, London, W2 1PG, United Kingdom. danielle.vienneau@imperial.ac.uk
The Science of the Total Environment
|October 31, 2009
Summary
This study introduces a GIS-based moving window method for detailed air pollution mapping. The approach effectively models nitrogen dioxide (NO2) levels across large regions, outperforming traditional methods.
Area of Science:
- Environmental Science
- Geographic Information Systems (GIS)
- Atmospheric Chemistry
Background:
- High-resolution air pollution mapping is crucial for environmental monitoring and public health.
- Existing methods may lack the spatial detail required for comprehensive analysis over large areas.
Purpose of the Study:
- To develop and validate a novel GIS-based moving window approach for generating high-resolution air pollution maps.
- To model annual mean nitrogen dioxide (NO2) pollution across the EU-15 (excluding Sweden) at a 1 km resolution.
Main Methods:
- A GIS-based moving window technique was employed.
- Emission maps (NOx) were created by disaggregating national estimates to a 1 km grid using proxies.
- A calibration between measured NO2 concentrations and distance-weighted emissions was established using monitoring data and a focalsum function.
Main Results:
- The model achieved a validation performance of R²=0.61, RMSE=6.59, and FB=-0.01.
- The GIS-based approach demonstrated performance comparable to universal kriging.
- The method proved superior to ordinary kriging and land use regression techniques.
Conclusions:
- The developed GIS-based moving window approach is effective for creating high-resolution air pollution maps over extensive geographic areas.
- This method offers a valuable tool for environmental assessment and policy-making.
- The approach provides a robust and accurate alternative to existing air pollution modeling techniques.
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