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ecwood / GCAM-CDR-modeling

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Implement a GCAM Scenario for H.R.7434 #16

Open ecwood opened 1 year ago

ecwood commented 1 year ago

The text of the bill is here: https://www.congress.gov/bill/117th-congress/house-bill/7434/text

In particular, it requires that these levels of CO2 are removed: Years CO2 Removed Per Year (Metric Tons CO2)
2024-2025 50,000
2026-2028 500,000
2029-2034 5,000,000
2035- 10,000,000
The economic conditions for this bill to take effect are that the removal cost per ton isn't more than Years Cost Per Metric Ton of CO2
2024-2025 $550
2026-2028 $400
2029-2031 $300
2032-2034 $200
2035- $150

I'm going to tag @khw21 in case they have any further info that should be included in the model for this scenario.

ecwood commented 1 year ago

Questions for @celinasb and/or @khw21: Should I use the global GCAM or the US only for implementing this scenario? If US: how should I distribute DAC among the states (OR should I try and edit this second... i.e. edit out the delete tags and implement what is discussed in #11)? If global: what should I do with the rest of the regions?

        <region name="USA">
            <supplysector delete="1" name="CO2 removal"/>
            <supplysector delete="1" name="process heat dac"/>
            <supplysector delete="1" name="airCO2"/>
            <energy-final-demand delete="1" name="CO2 removal"/>
        </region>

Thank you in advance!

ecwood commented 1 year ago

Here are the tables above laid out together and averaged for the 5 year increments:

Year CO2 Removed Per Year (MtCO2) Cost Per Metric Ton of CO2 Average CO2 Removed Per Year in 5 Year Increments (MtCO2) Average Cost Per Metric Ton of CO2 in 5 Year Increments
**2020*** 0.00 $550 0.01 $550
2021* 0.00 $550    
2022* 0.00 $550    
2023* 0.00 $550    
2024 0.05 $550    
2025 0.05 $550 1.31 $410
2026 0.50 $400    
2027 0.50 $400    
2028 0.50 $400    
2029 5.00 $300    
2030 5.00 $300 5 $240
2031 5.00 $300    
2032 5.00 $200    
2033 5.00 $200    
2034 5.00 $200    
2035 10.00 $150 10 $150
2036 10.00 $150    
2037 10.00 $150    
2038 10.00 $150    
2039 10.00 $150    
2040 10.00 $150 10 $150
2041 10.00 $150    
2042 10.00 $150    

Note: The lines with an asterisk denoted those not included in the policy. I am unsure if I should be making better assumptions with those. I would gladly take input on how to better handle those cases. I included them so that I have some way of including the 2024 case. Also, please correct me if I am implementing the GCAM 5-year increments wrong.

ecwood commented 1 year ago

This source mentions the delete flag as well as the nocreate flag mentioned in some error messages (to be posted shortly).

ecwood commented 1 year ago

These are the error messages I am currently getting:

This computer software was prepared by Battelle Memorial Institute,
hereinafter the Contractor, under Contract No. DE-AC05-76RL0 1830 with
the Department of Energy (DOE). NEITHER THE GOVERNMENT NOR THE
CONTRACTOR MAKES ANY WARRANTY, EXPRESS OR IMPLIED, OR ASSUMES ANY
LIABILITY FOR THE USE OF THIS SOFTWARE. This notice including this
sentence must appear on any copies of this computer software.

User agrees that the Software will not be shipped, transferred or
exported into any country or used in any manner prohibited by the United
States Export Administration Act or any other applicable export laws,
restrictions or regulations (collectively the 'Export Laws'). Export of
the Software may require some form of license or other authority from
the U.S. Government, and failure to obtain such export control license
may result in criminal liability under U.S. laws. In addition, if the
Software is identified as export controlled items under the Export Laws,
User represents and warrants that User is not a citizen, or otherwise
located within, an embargoed nation (including without limitation Iran,
Syria, Sudan, Cuba, and North Korea) and that User is not otherwise
prohibited under the Export Laws from receiving the Software.

Copyright 2011 Battelle Memorial Institute.  All Rights Reserved.
Distributed as open-source under the terms of the Educational Community
License version 2.0 (ECL 2.0). http://www.opensource.org/licenses/ecl2.php

For further details, see: http://www.globalchange.umd.edu/models/gcam/

Running GCAM model code base version 6.0 revision gcam-v6.0

Configuration file:  configuration_usa.xml
Parsing input files...
OpenJDK 64-Bit Server VM warning: Archived non-system classes are disabled because the java.system.class.loader property is specified (value = "WildcardExpandingClassLoader"). To use archived non-system classes, this property must be not be set
Parsing ../input/gcamdata/xml/hector.xml scenario component.
Parsing ../input/gcamdata/xml/socioeconomics_gSSP2.xml scenario component.
Parsing ../input/gcamdata/xml/resources.xml scenario component.
Parsing ../input/gcamdata/xml/en_supply.xml scenario component.
Parsing ../input/gcamdata/xml/en_transformation.xml scenario component.
Parsing ../input/gcamdata/xml/electricity_water.xml scenario component.
Parsing ../input/gcamdata/xml/heat.xml scenario component.
Parsing ../input/gcamdata/xml/hydrogen.xml scenario component.
Parsing ../input/gcamdata/xml/en_distribution.xml scenario component.
Parsing ../input/gcamdata/xml/other_industry.xml scenario component.
Parsing ../input/gcamdata/xml/other_industry_incelas_gssp2.xml scenario component.
Parsing ../input/gcamdata/xml/iron_steel.xml scenario component.
Parsing ../input/gcamdata/xml/iron_steel_incelas_gssp2.xml scenario component.
Parsing ../input/gcamdata/xml/Off_road.xml scenario component.
Parsing ../input/gcamdata/xml/Off_road_incelas_gssp2.xml scenario component.
Parsing ../input/gcamdata/xml/chemical.xml scenario component.
Parsing ../input/gcamdata/xml/chemical_incelas_gssp2.xml scenario component.
Parsing ../input/gcamdata/xml/aluminum.xml scenario component.
Parsing ../input/gcamdata/xml/aluminum_incelas_gssp2.xml scenario component.
Parsing ../input/gcamdata/xml/cement.xml scenario component.
Parsing ../input/gcamdata/xml/cement_incelas_gssp2.xml scenario component.
Parsing ../input/gcamdata/xml/en_Fert.xml scenario component.
Parsing ../input/gcamdata/xml/HDDCDD_constdd_no_GCM.xml scenario component.
Parsing ../input/gcamdata/xml/building_det.xml scenario component.
Parsing ../input/gcamdata/xml/transportation_UCD_CORE.xml scenario component.
Parsing ../input/gcamdata/xml/Ccoef.xml scenario component.
Parsing ../input/gcamdata/xml/Cstorage.xml scenario component.
Parsing ../input/gcamdata/xml/ag_For_Past_bio_base_IRR_MGMT.xml scenario component.
Parsing ../input/gcamdata/xml/ag_cost_IRR_MGMT.xml scenario component.
Parsing ../input/gcamdata/xml/ag_prodchange_ref_IRR_MGMT.xml scenario component.
Parsing ../input/gcamdata/xml/resbio_input_IRR_MGMT.xml scenario component.
Parsing ../input/gcamdata/xml/an_input.xml scenario component.
Parsing ../input/gcamdata/xml/ag_Fert_IRR_MGMT.xml scenario component.
Parsing ../input/gcamdata/xml/land_input_1.xml scenario component.
Parsing ../input/gcamdata/xml/land_input_2.xml scenario component.
Parsing ../input/gcamdata/xml/land_input_3_IRR.xml scenario component.
Parsing ../input/gcamdata/xml/land_input_4_IRR_MGMT.xml scenario component.
Parsing ../input/gcamdata/xml/land_input_5_IRR_MGMT.xml scenario component.
Parsing ../input/gcamdata/xml/protected_land_input_2.xml scenario component.
Parsing ../input/gcamdata/xml/protected_land_input_3.xml scenario component.
Parsing ../input/gcamdata/xml/ag_an_demand_input.xml scenario component.
Parsing ../input/gcamdata/xml/bio_trade.xml scenario component.
Parsing ../input/gcamdata/xml/ag_trade.xml scenario component.
Parsing ../input/gcamdata/xml/unlimited_water_supply.xml scenario component.
Parsing ../input/gcamdata/xml/water_supply_constrained.xml scenario component.
Parsing ../input/gcamdata/xml/desalination.xml scenario component.
Parsing ../input/gcamdata/xml/water_td.xml scenario component.
Parsing ../input/gcamdata/xml/EFW_input_coefs.xml scenario component.
Parsing ../input/gcamdata/xml/EFW_irrigation.xml scenario component.
Parsing ../input/gcamdata/xml/EFW_manufacturing.xml scenario component.
Parsing ../input/gcamdata/xml/EFW_municipal.xml scenario component.
Parsing ../input/gcamdata/xml/ag_water_input_IRR_MGMT.xml scenario component.
Parsing ../input/gcamdata/xml/electricity_water_coefs.xml scenario component.
Parsing ../input/gcamdata/xml/water_demand_industry.xml scenario component.
Parsing ../input/gcamdata/xml/water_demand_livestock.xml scenario component.
Parsing ../input/gcamdata/xml/water_demand_municipal.xml scenario component.
Parsing ../input/gcamdata/xml/water_demand_primary.xml scenario component.
Parsing ../input/gcamdata/xml/ind_urb_processing_sectors.xml scenario component.
Parsing ../input/gcamdata/xml/all_energy_emissions.xml scenario component.
Parsing ../input/gcamdata/xml/all_fgas_emissions.xml scenario component.
Parsing ../input/gcamdata/xml/all_unmgd_emissions.xml scenario component.
Parsing ../input/gcamdata/xml/all_aglu_emissions_IRR_MGMT.xml scenario component.
Parsing ../input/gcamdata/xml/all_protected_unmgd_emissions.xml scenario component.
Parsing ../input/gcamdata/xml/emission_factor_controls.xml scenario component.
Parsing ../input/gcamdata/xml/all_energy_emissions_MAC.xml scenario component.
Parsing ../input/gcamdata/xml/all_fgas_emissions_MAC.xml scenario component.
Parsing ../input/gcamdata/xml/all_aglu_emissions_IRR_MGMT_MAC.xml scenario component.
Parsing ../input/gcamdata/xml/ind_urb_processing_sectors_MAC.xml scenario component.
Parsing ../input/gcamdata/xml/liquids_limits.xml scenario component.
Parsing ../input/gcamdata/xml/water_elec_liquids_limits.xml scenario component.
Parsing ../input/gcamdata/xml/negative_emissions_budget_gSSP2.xml scenario component.
Parsing ../input/gcamdata/xml/bio_externality.xml scenario component.
Parsing ../input/gcamdata/xml/onshore_wind.xml scenario component.
Parsing ../input/gcamdata/xml/socioeconomics_USA.xml scenario component.
Parsing ../input/gcamdata/xml/resources_USA.xml scenario component.
Parsing ../input/gcamdata/xml/Cstorage_USA.xml scenario component.
Parsing ../input/gcamdata/xml/en_prices_USA.xml scenario component.
Parsing ../input/gcamdata/xml/en_transformation_USA.xml scenario component.
Parsing ../input/gcamdata/xml/elec_segments_water_USA.xml scenario component.
Parsing ../input/gcamdata/xml/hydrogen_USA.xml scenario component.
Parsing ../input/gcamdata/xml/electd_USA.xml scenario component.
Could not delete node supplysector as it does not exist.
Parsing ../input/gcamdata/xml/transportation_USA_CORE.xml scenario component.
Parsing ../input/gcamdata/xml/building_USA.xml scenario component.
Parsing ../input/gcamdata/xml/HDDCDD_constdds_USA.xml scenario component.
Parsing ../input/gcamdata/xml/industry_USA.xml scenario component.
Parsing ../input/gcamdata/xml/industry_vintage_USA.xml scenario component.
Parsing ../input/gcamdata/xml/cement_USA.xml scenario component.
Parsing ../input/gcamdata/xml/Fert_USA.xml scenario component.
Parsing ../input/gcamdata/xml/solar_reeds_USA.xml scenario component.
Parsing ../input/gcamdata/xml/wind_reeds_USA.xml scenario component.
Parsing ../input/gcamdata/xml/elec_hydro_USA.xml scenario component.
Parsing ../input/gcamdata/xml/nuclear_USA.xml scenario component.
Parsing ../input/gcamdata/xml/nonewcoal_USA.xml scenario component.
Parsing ../input/gcamdata/xml/elecS_costs_USA_itc.xml scenario component.
Parsing ../input/gcamdata/xml/elecS_costs_USA_ptc.xml scenario component.
Parsing ../input/gcamdata/xml/geothermal_fixed_USA.xml scenario component.
Parsing ../input/gcamdata/xml/liquids_limits_USA.xml scenario component.
Parsing ../input/gcamdata/xml/negative_emissions_budget_USA_gSSP2.xml scenario component.
Parsing ../input/gcamdata/xml/regional_biomass_USA.xml scenario component.
Parsing ../input/gcamdata/xml/water_td_USA.xml scenario component.
Could not delete node subsector as it does not exist.
Could not delete node subsector as it does not exist.
Parsing ../input/gcamdata/xml/water_demand_municipal_USA.xml scenario component.
Parsing ../input/gcamdata/xml/water_demand_industry_USA.xml scenario component.
Parsing ../input/gcamdata/xml/ghg_emissions_USA.xml scenario component.
Parsing ../input/gcamdata/xml/elecS_ghg_emissions_water_USA.xml scenario component.
Parsing ../input/gcamdata/xml/trn_ghg_emissions_USA.xml scenario component.
Parsing ../input/gcamdata/xml/bld_emissions_USA.xml scenario component.
Parsing ../input/gcamdata/xml/othertrn_emissions_USA.xml scenario component.
Parsing ../input/gcamdata/xml/indenergy_emissions_USA.xml scenario component.
Parsing ../input/gcamdata/xml/elc_emissions_USA.xml scenario component.
Parsing ../input/gcamdata/xml/transport_emissions_USA.xml scenario component.
Parsing ../input/gcamdata/xml/ind_urb_processing_sectors_USA.xml scenario component.
Could not delete node supplysector as it does not exist.
Parsing ../input/gcamdata/xml/ind_urb_proc_emissions_USA.xml scenario component.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Parsing ../input/gcamdata/xml/refinery_emissions_USA.xml scenario component.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Did not create node supplysector as the nocreate input flag was set.
Parsing ../input/solution/cal_broyden_config.xml scenario component.
Parsing ../input/gcamdata/xml/dac_ssp2.xml scenario component.
Parsing ../input/gcamdata/xml/dac_USA_ssp2.xml scenario component.
XML parsing complete.
Starting new scenario: GCAM-USA_Reference
Thu Jul 14 22:57:50 2022:WARNING:printLogHeader: hector version 2.5.0
Thu Jul 14 22:57:50 2022:WARNING:setData: Disabling onelineocean
Thu Jul 14 22:57:50 2022:WARNING:printLogHeader: hector version 2.5.0
Thu Jul 14 22:57:50 2022:WARNING:setData: Disabling onelineocean
Thu Jul 14 22:57:50 2022:WARNING:prepareToRun: Disabling onelineocean
Starting a model run. Running all periods.
Model run beginning.
Period 0: 1975
Model solved with last period's prices.

Period 1: 1990
Model solved normally. Iterations period 1: 191. Total iterations: 192

Period 2: 2005
Model solved normally. Iterations period 2: 213. Total iterations: 404

Period 3: 2010
Model solved normally. Iterations period 3: 248. Total iterations: 652

Period 4: 2015
Model solved normally. Iterations period 4: 392. Total iterations: 1043

Period 5: 2020
SEVERE ERROR:In India, MiscCropTree_KrishnaR_IRR:  invalid or uninitialized base value parameter  -122241
SEVERE ERROR:This value will generate invalid sharing with absolute-cost-logit, please parse a reasonable value instead.

(The code died after that point)

ecwood commented 1 year ago

Here are some results that may help solve that error:

ubuntu@ip-172-31-60-46:~/gcam-core/input/gcamdata$ grep -R "122241" .
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,abw,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,atg,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,bhs,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,blz,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,bmu,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,brb,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,cri,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,cub,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,cuw,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,cym,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,dma,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,dom,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,glp,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,grd,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,gtm,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,hnd,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,hti,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,jam,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,kna,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,lca,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,msr,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,mtq,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,nic,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,pan,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,pri,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,slv,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,sxm,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,tca,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,tto,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,vct,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,vgb,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/emissions/CEDS/gains_iso_sector_emissions.csv:CH4,vir,2015,0.017573901,0.122241286,0.028642538
./inst/extdata/energy/comtrade_ff_trade.csv:2014,251,2,56,HS,2701,8,257670821,257670821,26122241,0
./inst/extdata/gcam-usa/emissions/state_tier1_caps.csv:31,NE,2,FUEL COMB. INDUSTRIAL,NH3,0.05119,0.08146,0.07815,0.07662,0.079174,0.081363,0.082504,0.133983241,0.161222416,0.188461591,0.215700766,0.178809052,0.141917339,0.105025625,0.114345356,0.123665086,0.132996833,0.158798277,0.184599722,0.210401166,0.262959321,0.315517476,0.36807563,0.36807563,0.36807563
./inst/extdata/aglu/Mekonnen_Hoekstra_Rep47_A2.csv:"Walnuts, with shell",Blue,5689.342703,,,,,,903.0689971,,,102.4649564,542.5194176,,,,,,9.939645979,,,,,,,,115.7700881,,76.81222415,,,,,,,,,,,3254.909034,163.0979956,,,,,,,,14.3766822,,13433.64534,101.1307059,,,,,,,2714.429599,,,,,,,,,592.5438909,,,,,810.1143225,375.6805502,8.7070284,,651.7166396,,,,,,,,,,113.5535529,,1571.347553,,4395.865339,13022.74043,,,354.7429949,,,,1989.693394,,,,64.70822974,,929.7427262,,,940.6195753,,,,,,511.6073634,,,,,,,,,,,3068.30938,61.06038448,,,1916.399059,,,,130.756823,,,,,,,,,,516.7561031,,,,883.8112863,,1.275064279,455.2528064,,,,3.137188049,6.00E-06,,,,,,,,,,27.31036868,,,,187.2088469,,,,,777.9566283,,,,,,2.480300057,,,,,,,,,,566.196884,,,,,,,1978.743023,,1924.096709,,,,,,,,
./inst/extdata/aglu/LDS/Land_type_area_ha.csv:civ,160,1002,1850,122241
./inst/extdata/aglu/LDS/Land_type_area_ha.csv:fra,62,512,1880,1222417
./inst/extdata/aglu/LDS/LDS_ag_HA_ha.csv:deu,31,Triticale,122241
./inst/extdata/aglu/FAO/FAO_an_Food_t_SUA.csv:Turkey,223,Cheese,2741,Food (tonnes),141,69293,76586,79190,80890,84741,84950,88060,89688,93514,94626,95104,95784,98814,105383,110321,114217,118569,125624,128523,132747,134285,135519,138727,133838,144665,135070,135247,135155,135865,136881,143103,145515,144389,139588,138478,142100,128384,128865,129676,129828,122241,111796,121093,133258,134407,136491,138509,132720,133611,,,,,,
./inst/extdata/aglu/FAO/FAO_ag_Food_t_SUA.csv:Czechoslovakia,51,Tomatoes and products,2601,Food (tonnes),141,117768,136132,168960,162769,135839,144892,179728,183576,147475,136555,145821,141914,145599,143905,149333,139807,174161,144108,182437,136686,152267,156348,137884,101120,138696,122241,138232,151419,144837,141128,166662,121204,,,,,,,,,,,,,,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP3_v9_130115,GUY,Population|Female|Aged70-74|Primary Education,million,,,,,,,,,,,,,0.002580375,0.002362255,0.002094002,0.002492661,0.00256369,0.002693991,0.002558664,0.001355789,0.001238836,0.001269763,0.001222412,0.001652792,0.002115357,0.001943,0.001428304,0.001539335,0.001768418,0.00201467,0.002146472,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP5_v9_130115,DEU,Population|Female|Aged85-89|Primary Education,million,,,,,,,,,,,,,0.03877776,0.037126878,0.045994177,0.044587134,0.034414038,0.049399588,0.050210669,0.055244171,0.065698036,0.066054313,0.059325761,0.048114815,0.016145948,0.012224126,0.008301781,0.00645749,0.005053045,0.004260081,0.003612725,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP5_v9_130115,NOR,Population|Female|Aged35-39|Secondary Education,million,,,,,,,,,,,,,0.089354957,0.077042887,0.075515506,0.070613017,0.06600182,0.05743196,0.051956008,0.051606045,0.052631851,0.055680408,0.058362295,0.060035434,0.057863311,0.056746856,0.057122241,0.058225793,0.058529307,0.057865125,0.056405041,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP5_v9_130115,THA,Population|Female|Aged70-74|Primary Education,million,,,,,,,,,,,,,0.714064221,0.772453077,0.97200674,1.306373314,1.512978682,1.550958812,1.591222412,0.845938691,0.716206789,0.496975753,0.395945058,0.315831111,0.247926871,0.198469443,0.157235561,0.119906676,0.093299982,0.072829766,0.055472926,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP1_v9_130115,HTI,Population|Male|Aged55-59|Secondary Education,million,,,,,,,,,,,,,0.012986149,0.019412342,0.028303698,0.05423528,0.073098732,0.10122241,0.14720018,0.16665089,0.190959816,0.207341824,0.211040072,0.213146265,0.188858618,0.172479277,0.158056487,0.141894555,0.131703267,0.120167344,0.107696488,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP1_v9_130115,LAO,Population|Male|Aged55-59|Primary Education,million,,,,,,,,,,,,,0.044068852,0.049283138,0.050240239,0.052143164,0.061916347,0.075956685,0.074669018,0.081865962,0.085468125,0.075157434,0.062828486,0.053587524,0.044993186,0.038850504,0.032048161,0.02492789,0.019826902,0.015586853,0.012224112,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP1_v9_130115,PAN,Population|Male|Aged60-64|Tertiary Education,million,,,,,,,,,,,,,0.007278082,0.011222419,0.015194942,0.017802602,0.020971461,0.024428172,0.025814734,0.035621691,0.046840345,0.057186477,0.069819408,0.081833634,0.092026635,0.089754244,0.090365905,0.089933422,0.087286651,0.084674454,0.079244911,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP2_v9_130115,SOM,Population|Male|Aged50-54|Primary Education,million,,,,,,,,,,,,,0.013605772,0.021722047,0.027622545,0.035091698,0.066445744,0.061476054,0.069483718,0.080794252,0.099470335,0.118527021,0.135149681,0.144251482,0.148422033,0.154861951,0.160155578,0.15437037,0.139805869,0.122241814,0.105914588,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP2_v9_130115,SWZ,Population|Male|Aged80-84,million,,,,,,,,,,,,,0.0012,0.001409066,0.00172777,0.00187951,0.00216405,0.002332952,0.002288113,0.002221367,0.002310115,0.002444618,0.003066107,0.004547493,0.00662749,0.007987869,0.008423016,0.009260026,0.010632588,0.012224108,0.013651736,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP4d_v9_130115,MNG,Population|Male|Aged90-94,million,,,,,,,,,,,,,4.44E-04,5.21E-04,6.05E-04,7.15E-04,8.30E-04,9.41E-04,9.94E-04,0.001433536,0.002030371,0.003007071,0.003454854,0.004323741,0.005328155,0.006845106,0.0094757,0.009714216,0.010112542,0.011222418,0.017671204,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP4d_v9_130115,NER,Population|Female|Aged60-64|Tertiary Education,million,,,,,,,,,,,,,1.12E-04,1.70E-04,8.95E-04,8.66E-04,7.87E-04,0.001645631,0.00280731,0.002442014,0.00353039,0.003884251,0.004440428,0.005079235,0.005779453,0.006879049,0.008359818,0.010103057,0.01222418,0.014973572,0.018377102,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP4d_v9_130115,NZL,Population|Female|Aged50-54|Secondary Education,million,,,,,,,,,,,,,0.088501738,0.102953849,0.099028641,0.094771051,0.085327316,0.100385446,0.117831481,0.12296147,0.116866635,0.116351605,0.125033875,0.122241638,0.120008859,0.115437997,0.107983021,0.104364263,0.100845577,0.097163034,0.091933411,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP4d_v9_130115,STP,Population|Male|Aged60-64|Secondary Education,million,,,,,,,,,,,,,5.53E-05,1.55E-04,3.26E-04,3.83E-04,4.41E-04,5.16E-04,5.41E-04,8.95E-04,8.67E-04,0.001041692,0.001135759,0.001204815,0.001222414,0.001263526,0.001340732,0.001424143,0.001508579,0.001543434,0.001596586,,,,,,,,,,
./inst/extdata/socioeconomics/SSP_database_v9.csv:IIASA-WiC POP,SSP4d_v9_130115,ALB,Population|Male|Aged35-39|Primary Education,million,,,,,,,,,,,,,0.003746817,0.003280797,0.00494829,0.005121803,0.004513005,0.004380288,0.003985576,0.003512741,0.003116691,0.002983792,0.002747072,0.002432641,0.002175551,0.001946758,0.001762485,0.001607728,0.00147986,0.00134782,0.001222415,,,,,,,,,,
./xml/transport_emissions_USA.xml:                                <emiss-coef>7.12224149719967e-08</emiss-coef>
./xml/transport_emissions_USA.xml:                                <emiss-coef>7.12224149719967e-08</emiss-coef>
./xml/transport_emissions_USA.xml:                                <emiss-coef>7.12224149719967e-08</emiss-coef>
./xml/transport_emissions_USA.xml:                                <emiss-coef>7.12224149719967e-08</emiss-coef>
./xml/transport_emissions_USA.xml:                                <emiss-coef>7.12224149719967e-08</emiss-coef>
./xml/transport_emissions_USA.xml:                                <emiss-coef>7.12224149719967e-08</emiss-coef>
./xml/transport_emissions_USA.xml:                                <emiss-coef>7.12224149719967e-08</emiss-coef>
./xml/transport_emissions_USA.xml:                                <emiss-coef>7.12224149719967e-08</emiss-coef>
./xml/transport_emissions_USA.xml:                                <emiss-coef>7.12224149719967e-08</emiss-coef>
./xml/transport_emissions_USA.xml:                                <emiss-coef>7.12224149719967e-08</emiss-coef>
./xml/all_aglu_emissions_IRR_MGMT.xml:                                <input-emissions>7.6943951222419e-07</input-emissions>
./xml/all_aglu_emissions_IRR_MGMT.xml:                                <input-emissions>9.00005106122241e-10</input-emissions>
./xml/all_aglu_emissions_IRR_MGMT.xml:                                <input-emissions>0.00022491712224142</input-emissions>
./xml/protected_land_input_2.xml:                            <landAllocation year="2015">0.0546473752122241</landAllocation>
./xml/bld_emissions_USA.xml:                                <emiss-coef>0.0129212224147042</emiss-coef>
./xml/bld_emissions_USA.xml:                                <emiss-coef>0.0129212224147042</emiss-coef>
./xml/bld_emissions_USA.xml:                                <emiss-coef>0.0129212224147042</emiss-coef>
./xml/bld_emissions_USA.xml:                                <emiss-coef>0.0129212224147042</emiss-coef>
./xml/bld_emissions_USA.xml:                                <emiss-coef>0.0129212224147042</emiss-coef>
./xml/bld_emissions_USA.xml:                                <emiss-coef>0.0129212224147042</emiss-coef>
./xml/bld_emissions_USA.xml:                                <emiss-coef>0.0129212224147042</emiss-coef>
./xml/bld_emissions_USA.xml:                                <emiss-coef>0.0129212224147042</emiss-coef>
./xml/ssp34_emissions_factors.xml:                                <emiss-coef>0.0122241027</emiss-coef>
./xml/ssp34_emissions_factors.xml:                                <emiss-coef>0.0122241027</emiss-coef>
./xml/ag_For_Past_bio_base_IRR_MGMT.xml:                                <calOutputValue>0.0122241</calOutputValue>
ubuntu@ip-172-31-60-46:~/gcam-core/input/gcamdata$ grep -R "MiscCropTree_KrishnaR_IRR" .
./xml/resbio_input_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo">
./xml/resbio_input_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi">
./xml/MACC_TC_SSP2.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo" nocreate="1">
./xml/MACC_TC_SSP2.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi" nocreate="1">
./xml/land_input_5_IRR_MGMT.xml:                                <LandNode name="MiscCropTree_KrishnaR_IRR">
./xml/land_input_5_IRR_MGMT.xml:                                    <LandLeaf name="MiscCropTree_KrishnaR_IRR_lo">
./xml/land_input_5_IRR_MGMT.xml:                                    <LandLeaf name="MiscCropTree_KrishnaR_IRR_hi">
./xml/ag_prodchange_ssp1_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi">
./xml/ag_prodchange_ssp1_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo">
./xml/MACC_TC_SSP5.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo" nocreate="1">
./xml/MACC_TC_SSP5.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi" nocreate="1">
./xml/ag_prodchange_ssp2_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi">
./xml/ag_prodchange_ssp2_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo">
./xml/ag_cost_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi">
./xml/ag_cost_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo">
./xml/all_aglu_emissions_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi" nocreate="1">
./xml/all_aglu_emissions_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo" nocreate="1">
./xml/ag_water_input_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi">
./xml/ag_water_input_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo">
./xml/all_aglu_emissions_IRR_MGMT_MAC.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo" nocreate="1">
./xml/all_aglu_emissions_IRR_MGMT_MAC.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi" nocreate="1">
./xml/ag_Fert_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi">
./xml/ag_Fert_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo">
./xml/ag_prodchange_ssp3_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi">
./xml/ag_prodchange_ssp3_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo">
./xml/ag_prodchange_ref_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi">
./xml/ag_prodchange_ref_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo">
./xml/ag_prodchange_ssp4_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi">
./xml/ag_prodchange_ssp4_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo">
./xml/MACC_TC_SSP1.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo" nocreate="1">
./xml/MACC_TC_SSP1.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi" nocreate="1">
./xml/ag_prodchange_ssp5_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi">
./xml/ag_prodchange_ssp5_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo">
./xml/ag_For_Past_bio_base_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_hi">
./xml/ag_For_Past_bio_base_IRR_MGMT.xml:                    <AgProductionTechnology name="MiscCropTree_KrishnaR_IRR_lo">
ecwood commented 1 year ago

This source in the documentation offers this quote. So, if we get the proportions, we can presumably apply them to the values above.

Share of cumulative carbon storage potential by state. State-level DAC potential is directly correlated with the carbon storage potential. Carbon storage assumptions can be found in GCAM data system in Dooley_CCS_USA.

ecwood commented 1 year ago

I believe these are the correct units for GCAM for the above table:

Year Average CO2 Removed Per Year in 5 Year Increments (MtC) Average Cost (1990$/tC) in 5 Year Increments Average Cost (1975$/tC) in 5 Year Increments
2020* 0.002729214479 $888 $366
2021*      
2022*      
2023*      
2024      
2025 0.3575270967 $662 $273
2026      
2027      
2028      
2029      
2030 1.364607239 $387 $160
2031      
2032      
2033      
2034      
2035 2.729214479 $242 $100
2036      
2037      
2038      
2039      
2040 2.729214479 $242 $100
2041      
2042      

Here are the conversions I used:

Mass Ratio of C to CO2 Inflation (1975->today, https://www.in2013dollars.com/us/inflation/1975?amount=1) Inflation (1990->today, https://www.in2013dollars.com/us/inflation/1990?amount=1)
0.2729214479 5.51 2.27
ecwood commented 1 year ago

Using commit a05a438, I generated this list, which contains the current assumptions regarding what proportion of DAC each state is assumed to have:

{
    "AK": 0.0,
    "AL": 0.033030400627577616,
    "AR": 0.01112524521137966,
    "AZ": 0.014039065266742241,
    "CA": 0.023335355443371755,
    "CO": 0.01631105030990996,
    "CT": 0.003974256575510875,
    "DC": 0.0,
    "DE": 0.002728366051838955,
    "FL": 0.046985135892717585,
    "GA": 0.03238933061539728,
    "HI": 0.0,
    "IA": 0.019552655371500454,
    "ID": 0.0005838320110928083,
    "IL": 0.04296699581637292,
    "IN": 0.056223401068244624,
    "KS": 0.015316245291008663,
    "KY": 0.03414273564871198,
    "LA": 0.04185848079531114,
    "MA": 0.0014378300273187705,
    "MD": 0.012909180245274425,
    "ME": 0.0,
    "MI": 0.032278670613294744,
    "MN": 0.01615078530686492,
    "MO": 0.02525475047984026,
    "MS": 0.011430520217179885,
    "MT": 0.0076546901454391135,
    "NC": 0.025915665492397648,
    "ND": 0.01223185523240525,
    "NE": 0.009825935186692768,
    "NH": 0.0005494890104402912,
    "NJ": 0.009152430173896175,
    "NM": 0.012508510237661695,
    "NV": 0.0033060930628157686,
    "NY": 0.018881055358740052,
    "OH": 0.05364960101934242,
    "OK": 0.02133468040535893,
    "OR": 0.0034201880649835734,
    "PA": 0.04953034094107649,
    "RI": 0.000311377155916166,
    "SC": 0.016810935319407774,
    "SD": 0.0008089700153704303,
    "TN": 0.02188989041590792,
    "TX": 0.13116000249204005,
    "UT": 0.015099505286890602,
    "VA": 0.015973345303493564,
    "VT": 0.00013546435257382272,
    "WA": 0.007150990135868813,
    "WI": 0.018125510344384695,
    "WV": 0.03187609560564582,
    "WY": 0.018673090354788716
}
ecwood commented 1 year ago

Here are the values I got from running these commands:

python3 get_DAC_state_potentials.py dac_USA_ssp2.xml dac_potentials.json
python3 calculate_hr7434_levels.py dac_potentials.json hr7434.csv hr7434_levels.csv
python3 modify_dac_ssp.py dac_USA_ssp2.xml hr7434_levels.csv dac_USA_ssp2_test.xml
Year Base Temperature Change (C) Commit 6969631 Temperature Change (C) Difference
1975 0 0 0
1980 0.345863 0.345863 0
1985 0.451742 0.451742 0
1990 0.563683 0.563683 0
1995 0.682267 0.682267 0
2000 0.798416 0.798416 0
2005 0.898257 0.898257 0
2010 1.01443 1.01443 0
2015 1.17425 1.17425 0
2020 1.32281 1.32278 0.00003
2025 1.46145 1.46141 0.00004
2030 1.60053 1.60049 0.00004
2035 1.73978 1.73973 0.00005
2040 1.87762 1.87755 0.00007
2045 2.0134 2.01331 0.00009
2050 2.148 2.1479 0.0001
2055 2.28172 2.2816 0.00012
2060 2.41537 2.41524 0.00013
2065 2.54918 2.54903 0.00015
2070 2.68369 2.68354 0.00015
2075 2.81959 2.81942 0.00017
2080 2.95771 2.95754 0.00017
2085 3.09591 3.09573 0.00018
2090 3.23343 3.23324 0.00019
2095 3.37031 3.3701 0.00021
2100 3.50662 3.5064 0.00022
ecwood commented 1 year ago

In commit 6969631, I used a fixedOutput and did not consider the cost of deployment. Therefore, in the next run to try and implement this scenario, we want to take these steps:

  1. Determine how to set a lower bound on the DAC deployment in each state (if they want to go over, they can, that is a minimum)
  2. Learn how to set a max price for deployment (for that CO2 removal to occur)
    • We don't want this to be a carbon price, because this is the price of deployment
    • This may or may not be (depending on how you read it) be a subsidy. Effectively, the government will be paying for CDR so long as it is under a certain price point. Above that, it won't be paying. But it's not exactly a subsidy since it won't be covering that much, then the remover (for lack of a better term) can cover the rest. It is more binary than that (from my reading).
  3. Learn to (potentially) have to convert price into a per GJ situation (though cost-unit appears to be in terms of 1975$/kg)
  4. Learn how to implement it so it doesn't have to be entirely DAC (if this is in scope)
  5. Learn how to ignore non-US regions (to hopefully make output file smaller)
ecwood commented 1 year ago

The code deployed in daf4ace did not create any meaningful results. It listed no DAC deployment. I think I need to also add in a carbon price. I am going to look through this document for more information.

ecwood commented 1 year ago

I am a little stuck of how to implement these constraints considering it's unclear how to apply them to these options:

https://github.com/JGCRI/gcam-core/blob/8d00382cde133119b0beca9716e8494506a8fc9c/cvs/objects/policy/source/policy_portfolio_standard.cpp#L146-L161

We might want to take the BioFuel approach from the link above (using RES).

ecwood commented 1 year ago

I feel like I need to narrow down my question a bit more, so I am going to work through some of my thoughts here: Overarching Question: What are the impacts if a policy like H.R. 7434 is deployed? More specific questions due to GCAM setup:

ecwood commented 1 year ago

In order to implement an emissions cap, we want to use the cumulative-emissions tag (previewed in the forcing_target files). The code governing this tag is here: cumulative_emissions_target.cpp cumulative_emissions_target.h