SMOKE outputs are county based

Hi,

I’m running the NEI2017 platform. By means of Spatial Allocator, I made Spatial Surrogates for Houston without any errors. Then, using those surrogate files, I ran the NEI2017 platform to prepare the nonpoint source’s emissions. However, once I check the outputs, the results are weird as for some species each county has the same value throughout that county. I attached the snapshot of the output visualization.

Screen Shot 2021-03-22 at 3.28.56 PM

Screen Shot 2021-03-22 at 3.28.42 PM

Regards,
Ali

How did you configure your surrogates in terms of the data and weight shapefiles and what attribute you used for the surrogates?

I suspect there is an error in your configuration.

Thank you for your prompt reply.
I used the default surrogate specification file within the Spatial Allocator package.
I attached the specification that I used.

surrogate_specification_pg.csv (21.3 KB)

Hmm, there is nothing that jumped out at me. Have you tried reproducing one of the provided 12km surrogates and comparing to check your configuration?

Also, we have posted 4km surrogates with the EPA 2016 and 2017 platforms – have you tried using those?

If the grid is aligned with our grid, it should work even if the surrogate files cover a larger area than your grid.

The grid size is 1km.
Thank you for your good suggestion. I will try making 12km surrogates and comparing them with the provided 12km surrogates.

Can you also share your 1km domain description for me to review? I would like to have the domain definition from your GRIDDESC and the first headline of surrogate you created over Houston region.

I attached the surrogate description.

srgdesc_hgb1k_336x264.txt (8.2 KB)

What about your modeling domain? Is it same as surrogate domain?

As @eyth.alison suggested, you need to review your weight and attributes to make sure that they overlay correctly. I don’t think the tool was able to compute the weighting factors correctly. I would suggest for you to check one of your surrogates like population 100 and then identify a couple of counties with the same surrogate factors and investigate the cause.