If you are an atmospheric modeller like me doing air pollution or climate related research, have you tested the uncertainty of your results simply due to fire emissions? If not, you should, at least scroll down to get a sense, as it can be larger than we would expect.
A new study (link) by Carter and Heald from MIT shows that the difference of aerosol emissions from fires in North America can be a factor of 4-7 across commonly used inventories (such as GFED4, FINN1.5, GFAS1.2 and QFED2.4). The authors further find that the driving force of the variation is the amount of dry matter burned in fires in different inventories, not emission factors. This clearly points out the direction where the uncertainty can be reduced.
By now, you might have two questions coming to mind: 1) given the large uncertainty, which inventory is good to use? 2) what can we do to reduce the uncertainty?
For the first question, the authors recommend GFED4 and GFAS1.2. These emissions are at least in the best agreement with observations on the ground and aloft. If you're not sure which one to use, these two will put you're on the safe side.
For the second question, I'd like to leave it in suspense for now as there's an interesting paper recently that shed some light on this topic. I will write about it in my next blog. Stay tuned!
If you're interested in Carter and Heald's study, please check out:
Carter, T. S.et al: How emissions uncertainty influences the distribution and radiative impacts of smoke from fires in North America, Atmos. Chem. Phys. Discuss., 2019. [Link]
Comentários