I've looked into this briefly and noticed a few things that are worth pointing out. First, your EPA table looks like it was based on Table 8 of this EPA pdf:
There’s a note in the table that,
Air Travel factors from 2017 Guidelines to Defra / DECC's GHG
The unit is different.
The British data is in gram per passenger per kilometer travelled, while the US data is in gram per passenger per mile traveled.
1 mile = 1.609 km
So if you take the long haul flight, 102 g/km (UK) = 164 g/mi, which is almost similar to the US figure of 166 g/mi.
That will depend on the emission scenario you pick for the future, the more recent scenarios are the RCP's (Representative Concentration Pathway).
The scenarios involve future pathways in the emissions of a large range of different chemicals (Greenhouse gases and aerosols). Each RCP have a temperature tag, for example RCP6.0, is a scenario ...
The California Air Resources board posted this PDF that includes emission estimates up to 2017, which were 37.1 million metric tons. If anyone is interested in related info, the search phrase I used was, "CO2 estimates for california wildfires".
If you have access, I would recommend you to read this short chapter of the Encyclopedia of Volcanoes. In summary:
At ocean ridges, studies show a steady rate of oceanic crust production during the Cenozoic. There have been fluctuations before, maybe due to the breakup of Pangea or other major tectonic events. The present volcanic production rate is ~20 km$^...
You can try the R package eixport, with wrf_put
# Read the array emissions,
CO <- wrf_get(file = "Path_to_WRFCHEMI", name = "E_CO")
# Change the values, here you should use your data
CO = rnorm(length(CO))
# Inyect your emissions into the wrfchemi
wrf_put(file = "Path_to_WRFCHEMI", name = "E_CO", POL = CO)
How to deal with the speciation (...