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Cities in South and Southeast Asia are developing rapidly, but lack routine, up-to-date, publicly available inventories of air pollutant precursor emissions such as nitrogen oxides (NO x). This data deficiency can be addressed by deriving city NO x emissions from satellite observations of nitrogen dioxide (NO 2) tropospheric column densities. In this approach, the city plume is aligned along a consistent direction using wind rotation and a best-fit Gaussian applied to estimate NO x emissions. Issues that impact success of this approach is subjective selection of the sampling area around the city centre and the Gaussian fit often fails or yields physically implausible parameters. Here, we automate this top-down approach by defining many (54) sampling areas that we test with TROPOspheric Monitoring Instrument (TROPOMI) NO 2 observations over 19 cities in South and Southeast Asia. Our approach is efficient, adaptable …