I am curious if there are uncertainties for 4km and 12km emissions using NEI2017, and if their uncertainties are different.
I tried to convert 4km to 1km and 12km to 1km for a small domain, higher emissions concentrate in urban regions in the former 1km emission than in the latter 1km emission.
Did you use anything to “texturize” the 1km emissions or did you assume that the emissions were uniformly distributed throughout the 4km and 12km grid cells?
Assuming a uniform distribution is a pretty approximate method because you are not using real world information to distributed the emissions, so if there is a big highway through the grid cell, you’ll spread out all of the emissions on the highway throughout the grid cell instead of putting them in the 1km cells where the highway actually is.
Similarly for point sources – you’ll spread out all the emissions for the point throughout the grid cell.
The best way to prepare emissions on a 1km grid is to create spatial surrogates from the “bottom up” on that 1km grid, and to process the point sources so they end up in the appropriate grid cells.
Thank you for your quick and detailed clarification!
I just interpolated emissions from 4km to 1km. I used 4km and 12km surrogates to generate 4km and 12km emissions. Does it mean 4km emissions are more accurate than 12km emissions for a small domain, although higher emissions concentrate on source regions?
I see, thank you for the reply and suggestion. Is it easy to generate 1km surrogate files? I may try to do that last year, but not succeed to install sth at the beginning.
It is very I/O intensive if you try to do it for the whole country. But for smaller domains, it is possible.
Keep in mind that not all of the surrogate input data may have such a detailed resolution, so you may get a sense of “false precision” for some surrogates.