Generating GRA2PES Content for the GHG Center

Native GRA2PES files are delivered as hourly data in 12-hourly files, two per day, for three days: satdy, sundy, weekdy. These are stored in /discover/nobackup/projects/gmao/geos_carb/embell/data/GRA2PES/<YYYY>/Month0<N>/<Sector>/<day> with filenames of the format GRA2PESv1.0_OFFROAD_202101_satdy_00to11Z.nc. These files contain TOTAL emissions, across all sectors, for five species: CO2, CO, NOx, SO2, and PM2.5.

EnA monthly emission rates

The EnA environment displays a monthly average of each species' emission rates, summed over all sectors.

To generate, follow these steps:

1. Run aggregate_monthly_gra2pes.py

   • inputs.sectors = ['total'] to sum up all sectors.
   • Description: Calculate average monthly emissions rate, regrid to EPSG 4326, convert moles to metric tons where applicable, output to NetCDF.
   • Outputs are stored in /discover/nobackup/projects/gmao/geos_carb/embell/data/GRA2PES/<YYYY>/Month0<N>
   • For easiest sync to GHGC S3 bucket, copy outputs to /data/GRA2PES/for_ghgc/monthly_subset_regrid directory or similar.

2. Double check using double_checks/monthly_aggregates_double_check.p0y

   • Prints Great sum well done! if the aggregate monthly output matches the validation aggregate to < 0.025% in the mean.

Urban Dashboard city totals

The Urban Dashboard requires a minimized number of sectors, for effective visualization.

Steps to produce aggregated sectors:

1. sectoral_aggregation.py
   • inputs.sum keywords are the aggregated sector names, and their corresponding lists are the individual sectors to be included in each.
   • Description: Simply add together native hourly data, duplicating the 12-hour, satdy/sundy/mondy output file format.
   • Creates a new sectoral directory in data/GRA2PES/<year> and populates the hourly 0to11Z and 12to23Z files with aggregated emissions rates.
2. Double check using sector_aggregates_double_check.py
   • inputs.sum should match the same field in sectoral_aggregation.py
   • Description: Calculates sums using a different method, compares to outputs from step 1. Will print 'Check your arithmetic!' if the sums do not match. Otherwise, 'Great sum well done!'
3. Run aggregate_monthly_gra2pes.py
   • Update inputs.sectors to include your new aggregated sectors (should be the same as inputs.sum from the previous two steps).
   • Description: Convert hourly emissions rate to average monthly emissions rate, regrid to EPSG 4326, convert moles to metric tons where applicable.
4. Double check using quick_total_sectors_check.py
   • Description: Outputs maps of reported Total emissions, native/aggregated sector emissions, and a map of % diff between reported Total and sum of sectors.
   • This is a visual spot check! Can be used on either native sectors or aggregated sectors.
5. Run city_totals.py
   • Description: Reads in the emissions per month, subsets them for the specified list of GHGC-focused cities, and calculates total emissions for the city for that month.
   • Output is one CSV per city, with chemical species as rows and sectors as columns. It reports sectoral breakdwon in both mass and as a percentage of the total.
   • CSVs get written directly to /data/GRA2PES/for_ghgc/city_totals.
6. Double check using city_annual_totals_vs_vulcan.py
   • Description: Compares monthly TOTAL, ANNUAL emissions from GRA2PES to those from Vulcan Scope 1/2 in a bar graph, as a sanity check.
   • Note that this only works for whichever time period the two datasets overlap, and that we only have annual totals for Vulcan.