Fluxes of carbon dioxide (CO 2 ) to and from vegetation can be significant on regional scales. It is therefore important to understand biogenic CO 2 fluxes to quantify local carbon budgets. One method for estimating biogenic fluxes on regional scales is to use vegetation models which calculate biogenic CO 2 fluxes using remote sensing observations along with meteorology. In this work we have modified the Solar Induced Fluorescence (SIF) for Modelling Urban biogenic Fluxes (SMUrF) model so that it can use SIF, a signal emitted by vegetation during photosynthesis, measured from the TROPOspheric Monitoring Instrument (TROPOMI). This, along with other adjustments, improved the spatial resolution from 0.05° to 500m and resulted in similar agreement with ground-based vegetation flux measurements. We use this modified SMUrF model to estimate biogenic fluxes in the Greenbelt of Ontario, a protected region of natural vegetation and croplands surrounding the Greater Toronto and Hamilton Area. In light of the proposals to remove protection from portions of this land, we estimate the difference in biogenic CO 2 fluxes associated with replacing the vegetation in these areas with different housing scenarios. In addition, we have also investigated biogenic CO 2 fluxes in the city of Toronto itself to determine how vegetation affects the city’s carbon cycle. To put these results into context, we compare the estimated biogenic fluxes of both the Greenbelt and the city of Toronto to anthropogenic emission inventories. We find that the Greenbelt in its entirety plays a significant role in the local carbon budget by sequestering roughly a fifth of the Greater Toronto and Hamilton Area’s anthropogenic emissions. While vegetation in the city of Toronto provides a significantly smaller, but non-negligible sink of CO 2 .