In this paper, we take a global view at air pollution looking at cities and countries worldwide. We pay special attention at the spatial distribution of population and its relationship with the evolution of emissions. To do so, we build i) a unique and large dataset for more than 1200 (big) cities around the world, combining data on emissions of CO2 and PM2.5 with satellite data on built-up areas, population and light intensity at night at the grid-cell level for the last two decades, and ii) a large dataset for more than 190 countries with data from 1960 to 2010. At the city level, we find that denser cities show lower emissions per capita. We also find evidence for the importance of the spatial structure of the city, with polycentricity being associated with lower emissions in the largest urban areas, while monocentricity being more beneficial for smaller cities. In sum, our results suggest that the size and structure of urban areas matters when studying the density-emissions relationship. This is reinforced by results using our country-level data where we find that higher density in urban areas is associated with lower emissions per capita. All our main findings are robust to several controls and different specifications and estimation techniques, as well as different identification strategies.