STEMS-Air: A simple GIS-based air pollution dispersion model for city-wide exposure assessment

Current methods of air pollution modelling do not readily meet the needs of air pollution mapping for short-term (i.e. daily) exposure studies. The main limiting factor is that for those few models that couple with a GIS there are insufficient tools for directly mapping air pollution both at high spatial resolution and over large areas (e.g. city wide). A simple GIS-based air pollution model (STEMS-Air) has been developed for PM10 to meet these needs with the option to choose different exposure averaging periods (e.g. daily and annual). STEMS-Air uses the grid-based FOCALSUM function in ArcGIS in conjunction with a fine grid of emission sources and basic information on meteorology to implement a simple Gaussian plume model of air pollution dispersion. STEMS-Air was developed and validated in London, UK, using data on concentrations of PM10 from routinely available monitoring data. Results from the validation study show that STEMS-Air performs well in predicting both daily (at four sites) and annual (at 30 sites) concentrations of PM10. For daily modelling, STEMS-Air achieved r2 values in the range 0.19–0.43 (p < 0.001) based solely on traffic-related emissions and r2 values in the range 0.41–0.63 (p < 0.001) when adding information on ‘background’ levels of PM10. For annual modelling of PM10, the model returned r2 in the range 0.67–0.77 (P < 0.001) when compared with monitored concentrations. The model can thus be used for rapid production of daily or annual city-wide air pollution maps either as a screening process in urban air quality planning and management, or as the basis for health risk assessment and epidemiological studies.

Research highlights
► GIS grid (FOCALSUM) routines are used for city-wide mapping of PM10 concentrations.
► Models developed for short-term (daily) and long-term (annual) exposure assessment.
► STEMS-Air produced good predictions of monitored PM10 concentrations.
► Similar levels of performance were seen between STEMS-Air and ADMS-Urban.