Sources of ambient PM2.5 exposure in 96 global cities

21 February 2022, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


To improve air quality, knowledge of the sources and locations of air pollutant emissions is critical. However, for many global cities, no previous estimates exist of how much exposure to fine particulate matter (PM2.5), the largest environmental cause of mortality, is caused by emissions within the city vs. outside its boundaries. We use the Intervention Model for Air Pollution (InMAP) global-through-urban reduced complexity air quality model with a high-resolution, global inventory of pollutant emissions to quantify the contribution of emissions by source type and location for 96 global cities. Among these cities, we find that the fraction of PM2.5 exposure caused by within-city emissions varies widely (µ=51%; σ=23%) and is not well-explained by surrounding population density. The list of most-important sources also varies by city. Compared to a more mechanistically detailed model, InMAP predicts urban measured concentrations with less bias but more error. Predictive accuracy in urban areas is not particularly high with either model, suggesting an opportunity for improving global urban air emission inventories. We expect the results herein can be useful as a screening tool for policy options and in many cases may be robust enough to inform policy action to improve public health.


Environmental policy
fine particulate matter
air quality
air quality modeling
chemical transport modeling

Supplementary materials

Supporting information
Spatial surrogate evaluation; comparisons with other studies; city source apportionment data; labels and definitions; InMAP grid; exploration of the effect of using spatial surrogate data.
supporting data
data used to generate results


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