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We use formaldehyde (HCHO) vertical column measurements from the Scanning Imaging Absorption spectrometer for Atmospheric Chartography (SCIAMACHY) and Ozone Monitoring Instrument (OMI), and a nested-grid version of the GEOS-Chem chemistry transport model, to infer an ensemble of top-down isoprene emission estimates from tropical South America during 2006, using different model configurations and assumptions in the HCHO air-mass factor (AMF) calculation. Scenes affected by biomass burning are removed on a daily basis using fire count observations, and we use the local model sensitivity to identify locations where the impact of spatial smearing is small, though this comprises spatial coverage over the region. We find that the use of the HCHO column data more tightly constrains the ensemble isoprene emission range from 27–61 Tg C to 31–38 Tg C for SCIAMACHY, and 45–104 Tg C to 28–38 Tg C for OMI. Median uncertainties of the top-down emissions are about 60–260% for SCIAMACHY, and 10–90% for OMI. We find that the inferred emissions are most sensitive to uncertainties in cloud fraction and cloud top pressure (differences of ˙10%), the a priori isoprene emissions (˙20%), and the HCHO vertical column retrieval (˙30%). Construction of continuous top-down emission maps generally improves GEOS-Chem’s simulation of HCHO columns over the region, with respect to both the SCIAMACHY and OMI data. However, if local time top-down emissions are scaled to monthly mean values, the annual emission inferred from SCIAMACHY are nearly twice those from OMI. This difference cannot be explained by the different sampling of the sensors or uncertainties in the AMF calculation.