We additionally compare the InMAP predicted total PM2.5 concentrations using satellite derived PM2.5 concentrations among 91 cities in Figure (r 2 = 0.22), as well as using modeled total PM2.5 concentrations reported by in the first panel of Figure (r 2 = 0.27). (Note that total PM2.5 concentrations reported by are calibrated to measurement and remote sensing data, which explains their good agreement with measurement data.) We compare our estimates for fractions of total PM2.5 caused by six common emission sources with those reported by in Figure . Most fractions of these emission sources show good correlations (r 2 : 0.21-0.53) between the two studies except the fraction of PM2.5 from residential, commercial and other (r 2 = 0.01). We also compare InMAP fractions of total PM2.5 concentrations caused by within-city emissions with these fractions from 17 European cities as shown in Figure (r 2 = 0.17). Additionally, we compare the fractions of total PM2.5 caused by four common emission sources, as well as the fractions of total PM2.5 concentrations caused by these four emission sources generated by within-city emissions to that study in Figures and. There are no correlations between InMAP predictions and predictions by , except the fractions of total PM2.5 caused by agricultural and residential sources (the differences in emission source categories are listed in Table ). We also evaluate the InMAP within-city fractions for total PM2.5 against zero-out simulations with GEOS-Chem conducted in five cities and find good agreement (r 2 = 0.67) when InMAP is run at the coarser resolution used by GEOS-Chem. Model comparison is described in more detail in the supporting information.