Personal exposure to air pollution in megacities of the world

Air pollution is one of the major concerns for human health. The effect of air pollution on health is often estimated using personal exposure to air pollution. This is the exposure to air pollution aggregated along the space-time path visited by an individual. An important question is how megacities in the world differ regarding personal exposure of their population. In this topic you will try to answer this question by calculating personal exposure of the entire population of a number of megacities in the world, using publicly available information. Air pollution will be mapped by downscaling (increasing the level of detail) remotely sensed air pollution products to a spatial resolution of approximately 10 m using existing land use regression models, using open streetmap data as input. Space-time paths visited by individuals are estimated using location of houses, possibly enriched with census data or other high resolution information on location of dwellings. Then, air pollution is aggregated for these locations, for each individual in the population. This results in distributions of personal exposure for the population of the city. The objective is to do this for a number of major cities in the world. This requires good skills in programming GIS operations, e.g. using Python and/or PCRaster, ArcGIS.

Location: n.a.

Number of students: 1-2

Prerequisite: Experience with programming (scripting, e.g. Python), background in GIS, spatio-temporal modelling, (geo-statistics).

Program/track: any track if you have the required prerequisite

Contact/info: Derek Karssenberg (d.karssenberg@uu.nl)