The University of Colorado Airborne Solar Occultation Flux (CU AirSOF) instrument conducted the first suborbital carbon monoxide (CO) mass flux measurements on the scale of large wildfires, showing that the destructive fires in northern California in October 2017 emitted 2,040 +/- 316 tonnes CO hr(-1). Pyrogenic estimates from seven satellite-based emission inventories bracket the observed flux, but their range spans a factor of 83. The simulated air quality impacts in the form of ozone and fine particulate matter scale primarily with these uncertain emission amounts, and range from insignificant to very severe. This uncertainty in predicting emissions is reduced to a factor of similar to 2 by the CU AirSOF flux measurements, with potential for future improvements. The uncertainty is primarily the result of uncertain vegetation types and sources of radiative power measurements, and to a lesser extent uncertain emission factors and fire diurnal cycles. Plain Language Summary Wildfire smoke is a major source of air pollution that affects public health and natural areas, but the amounts of vegetation that go up in smoke and the emitted amounts of smoke are not well known, due to a lack of direct measurements. The accuracy of models used to predict smoke impacts on public health in affected communities is significantly impacted by their reliance on uncertain emissions estimates. In this study, a new instrument, the University of Colorado Airborne Solar Occultation Flux (CU AirSOF), measured the amount of carbon monoxide (CO) produced by the destructive fires in northern California during October 2017. These are the first airborne emission measurements on the scale of a large wildfire. The measured CO emissions from the fires fall within the large range among satellite-based emission estimates, reducing the uncertainty in fire emissions. Air quality impacts in the form of ozone (O-3) and fine particulate matter (PM2.5) range from insignificant to very severe, in direct relationship to the uncertain satellite-based emission estimates.