MAPPING URBAN AIR-POLLUTION USING GIS - A REGRESSION-BASED APPROACH

As part of the EU-funded SAVIAH project, a regression-based methodolog y for mapping traffic-related air pollution was developed within a GIS environment. Mapping was carried out for NO2 in Amsterdam, Huddersfie ld and Prague. In each centre, surveys of NO2, as a marker for traffic -related pollution, were conducted using passive diffusion tubes, expo sed for four 2-week periods. A GIS was also established, containing da ta on monitored air pollution levels, road network, traffic volume, la nd cover, altitude and other, locally determined, features. Data from 80 of the monitoring sites were then used to construct a regression eq uation, on the basis of predictor environmental variables, and the res ulting equation used to map air pollution across the study area. The a ccuracy of the map was then assessed by comparing predicted pollution levels with monitored levels at a range of independent reference sites . Results showed that the map produced extremely good predictions of m onitored pollution levels, both for individual surveys and for the mea n annual concentration, with r(2) similar to 0.79-0.87 across 8-10 ref erence points, though the accuracy of predictions for individual surve y periods was more variable. In Huddersfield and Amsterdam, further mo nitoring also showed that the pollution map provided reliable estimate s of NO2 concentrations in the following year (r(2) similar to 0.59-0. 86 for n=20).