diff --git a/.gitattributes b/.gitattributes index 20be8994f..2c8ef3bc4 100644 --- a/.gitattributes +++ b/.gitattributes @@ -33,3 +33,4 @@ solution/telepresence/testdata/*.zip filter=lfs diff=lfs merge=lfs -text solution/trains/testdata/*.zip filter=lfs diff=lfs merge=lfs -text solution/trucks/testdata/*.zip filter=lfs diff=lfs merge=lfs -text solution/walkablecities/testdata/*.zip filter=lfs diff=lfs merge=lfs -text +solution/altcement/testdata/*.zip filter=lfs diff=lfs merge=lfs -text diff --git a/solution/altcement/__init__.py b/solution/altcement/__init__.py index dc03838d7..a8684dc70 100644 --- a/solution/altcement/__init__.py +++ b/solution/altcement/__init__.py @@ -1,11 +1,12 @@ -"""Alternative (High Vol. Fly Ash) Cement solution model. - Excel filename: Drawdown-Alternative (High Vol. Fly Ash) Cement_RRS_v1.1_16Nov2018_PUBLIC.xlsm +"""Alternative Cements solution model. + Excel filename: AlternativeCements_v1.1c_IntegrationJune2020.xlsm """ import pathlib import numpy as np import pandas as pd +import xlrd from model import adoptiondata from model import advanced_controls as ac @@ -26,245 +27,526 @@ DATADIR = pathlib.Path(__file__).parents[2].joinpath('data') THISDIR = pathlib.Path(__file__).parents[0] VMAs = { - 'Current Adoption': vma.VMA( - filename=THISDIR.joinpath("vma_data", "Current_Adoption.csv"), - use_weight=False), - 'CONVENTIONAL First Cost per Implementation Unit': vma.VMA( - filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_First_Cost_per_Implementation_Unit.csv"), - use_weight=False), - 'SOLUTION First Cost per Implementation Unit': vma.VMA( - filename=THISDIR.joinpath("vma_data", "SOLUTION_First_Cost_per_Implementation_Unit.csv"), - use_weight=False), - 'CONVENTIONAL Lifetime Capacity': vma.VMA( - filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_Lifetime_Capacity.csv"), - use_weight=False), - 'SOLUTION Lifetime Capacity': vma.VMA( - filename=THISDIR.joinpath("vma_data", "SOLUTION_Lifetime_Capacity.csv"), - use_weight=False), - 'CONVENTIONAL Average Annual Use': vma.VMA( - filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_Average_Annual_Use.csv"), - use_weight=False), - 'SOLUTION Average Annual Use': vma.VMA( - filename=THISDIR.joinpath("vma_data", "SOLUTION_Average_Annual_Use.csv"), - use_weight=False), - 'CONVENTIONAL Variable Operating Cost (VOM) per Functional Unit': vma.VMA( - filename=None, use_weight=False), - 'SOLUTION Variable Operating Cost (VOM) per Functional Unit': vma.VMA( - filename=None, use_weight=False), - 'CONVENTIONAL Fixed Operating Cost (FOM)': vma.VMA( - filename=None, use_weight=False), - 'SOLUTION Fixed Operating Cost (FOM)': vma.VMA( - filename=None, use_weight=False), - 'CONVENTIONAL Total Energy Used per Functional Unit': vma.VMA( - filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_Total_Energy_Used_per_Functional_Unit.csv"), - use_weight=False), - 'SOLUTION Energy Efficiency Factor': vma.VMA( - filename=None, use_weight=False), - 'SOLUTION Total Energy Used per Functional Unit': vma.VMA( - filename=None, use_weight=False), - 'CONVENTIONAL Fuel Consumed per Functional Unit': vma.VMA( - filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_Fuel_Consumed_per_Functional_Unit.csv"), - use_weight=False), - 'SOLUTION Fuel Efficiency Factor': vma.VMA( - filename=None, use_weight=False), - 'CONVENTIONAL Direct Emissions per Functional Unit': vma.VMA( - filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_Direct_Emissions_per_Functional_Unit.csv"), - use_weight=False), - 'SOLUTION Direct Emissions per Functional Unit': vma.VMA( - filename=THISDIR.joinpath("vma_data", "SOLUTION_Direct_Emissions_per_Functional_Unit.csv"), - use_weight=False), - 'CONVENTIONAL Indirect CO2 Emissions per Unit': vma.VMA( - filename=None, use_weight=False), - 'SOLUTION Indirect CO2 Emissions per Unit': vma.VMA( - filename=THISDIR.joinpath("vma_data", "SOLUTION_Indirect_CO2_Emissions_per_Unit.csv"), - use_weight=False), - 'CH4-CO2eq Tons Reduced': vma.VMA( - filename=None, use_weight=False), - 'N2O-CO2eq Tons Reduced': vma.VMA( - filename=None, use_weight=False), - 'CONVENTIONAL Revenue per Functional Unit': vma.VMA( - filename=None, use_weight=False), - 'SOLUTION Revenue per Functional Unit': vma.VMA( - filename=None, use_weight=False), - 'Discount Rate - Commercial': vma.VMA( - filename=THISDIR.joinpath("vma_data", "Discount_Rate_Commercial.csv"), - use_weight=False), - 'FlyAsh:OPC Replacement Ratio': vma.VMA( - filename=THISDIR.joinpath("vma_data", "FlyAsh_OPC_Replacement_Ratio.csv"), - use_weight=False), + 'Current Adoption': vma.VMA( + filename=THISDIR.joinpath("vma_data", "Current_Adoption.csv"), + use_weight=False), + 'CONVENTIONAL First Cost per Implementation Unit': vma.VMA( + filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_First_Cost_per_Implementation_Unit.csv"), + use_weight=False), + 'SOLUTION First Cost per Implementation Unit': vma.VMA( + filename=THISDIR.joinpath("vma_data", "SOLUTION_First_Cost_per_Implementation_Unit.csv"), + use_weight=False), + 'CONVENTIONAL Lifetime Capacity': vma.VMA( + filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_Lifetime_Capacity.csv"), + use_weight=False), + 'SOLUTION Lifetime Capacity': vma.VMA( + filename=THISDIR.joinpath("vma_data", "SOLUTION_Lifetime_Capacity.csv"), + use_weight=False), + 'CONVENTIONAL Average Annual Use': vma.VMA( + filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_Average_Annual_Use.csv"), + use_weight=False), + 'SOLUTION Average Annual Use': vma.VMA( + filename=THISDIR.joinpath("vma_data", "SOLUTION_Average_Annual_Use.csv"), + use_weight=False), + 'CONVENTIONAL Variable Operating Cost (VOM) per Functional Unit': vma.VMA( + filename=None, use_weight=False), + 'SOLUTION Variable Operating Cost (VOM) per Functional Unit': vma.VMA( + filename=None, use_weight=False), + 'CONVENTIONAL Fixed Operating Cost (FOM)': vma.VMA( + filename=None, use_weight=False), + 'SOLUTION Fixed Operating Cost (FOM)': vma.VMA( + filename=None, use_weight=False), + 'CONVENTIONAL Total Energy Used per Functional Unit': vma.VMA( + filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_Total_Energy_Used_per_Functional_Unit.csv"), + use_weight=False), + 'SOLUTION Energy Efficiency Factor': vma.VMA( + filename=None, use_weight=False), + 'SOLUTION Total Energy Used per Functional Unit': vma.VMA( + filename=THISDIR.joinpath("vma_data", "SOLUTION_Total_Energy_Used_per_Functional_Unit.csv"), + use_weight=False), + 'CONVENTIONAL Fuel Consumed per Functional Unit': vma.VMA( + filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_Fuel_Consumed_per_Functional_Unit.csv"), + use_weight=False), + 'SOLUTION Fuel Efficiency Factor': vma.VMA( + filename=THISDIR.joinpath("vma_data", "SOLUTION_Fuel_Efficiency_Factor.csv"), + use_weight=False), + 'CONVENTIONAL Direct Emissions per Functional Unit': vma.VMA( + filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_Direct_Emissions_per_Functional_Unit.csv"), + use_weight=False), + 'SOLUTION Direct Emissions per Functional Unit': vma.VMA( + filename=THISDIR.joinpath("vma_data", "SOLUTION_Direct_Emissions_per_Functional_Unit.csv"), + use_weight=False), + 'CONVENTIONAL Indirect CO2 Emissions per Unit': vma.VMA( + filename=THISDIR.joinpath("vma_data", "CONVENTIONAL_Indirect_CO2_Emissions_per_Unit.csv"), + use_weight=False), + 'SOLUTION Indirect CO2 Emissions per Unit': vma.VMA( + filename=THISDIR.joinpath("vma_data", "SOLUTION_Indirect_CO2_Emissions_per_Unit.csv"), + use_weight=False), + 'CH4-CO2eq Tons Reduced': vma.VMA( + filename=None, use_weight=False), + 'N2O-CO2eq Tons Reduced': vma.VMA( + filename=None, use_weight=False), + 'CONVENTIONAL Revenue per Functional Unit': vma.VMA( + filename=None, use_weight=False), + 'SOLUTION Revenue per Functional Unit': vma.VMA( + filename=None, use_weight=False), + 'Discount Rate - Commercial': vma.VMA( + filename=THISDIR.joinpath("vma_data", "Discount_Rate_Commercial.csv"), + use_weight=False), + 'Clinker to Cement Ratio in Year 2': vma.VMA( + filename=THISDIR.joinpath("vma_data", "Clinker_to_Cement_Ratio_in_Year_2.csv"), + use_weight=True), + 'Clinker to Cement Ratio of Conventional Technology': vma.VMA( + filename=THISDIR.joinpath("vma_data", "Clinker_to_Cement_Ratio_of_Conventional_Technology.csv"), + use_weight=False), + 'Clinker Ratio Range Selection': vma.VMA( + filename=THISDIR.joinpath("vma_data", "Clinker_Ratio_Range_Selection.csv"), + use_weight=False), + 'Variable 29': vma.VMA( + filename=None, use_weight=False), + 'Percent Adoption of Blended Cements in Year 2 (2050)': vma.VMA( + filename=THISDIR.joinpath("vma_data", "Percent_Adoption_of_Blended_Cements_in_Year_2_2050.csv"), + use_weight=False), } vma.populate_fixed_summaries(vma_dict=VMAs, filename=THISDIR.joinpath('vma_data', 'VMA_info.csv')) units = { - "implementation unit": "MMt", - "functional unit": "MMt Cement", - "first cost": "US$B", - "operating cost": "US$B", + "implementation unit": "MMt", + "functional unit": "MMt Cement", + "first cost": "US$B", + "operating cost": "US$B", } -name = 'Alternative (High Vol. Fly Ash) Cement' +name = 'Alternative Cements' solution_category = ac.SOLUTION_CATEGORY.REDUCTION scenarios = ac.load_scenarios_from_json(directory=THISDIR.joinpath('ac'), vmas=VMAs) class Scenario: - name = name - units = units - vmas = VMAs - solution_category = solution_category - - def __init__(self, scenario=None): - if scenario is None: - scenario = list(scenarios.keys())[0] - self.scenario = scenario - self.ac = scenarios[scenario] - - # TAM - tamconfig_list = [ - ['param', 'World', 'PDS World', 'OECD90', 'Eastern Europe', 'Asia (Sans Japan)', - 'Middle East and Africa', 'Latin America', 'China', 'India', 'EU', 'USA'], - ['source_until_2014', self.ac.source_until_2014, self.ac.source_until_2014, - 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', - 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES'], - ['source_after_2014', self.ac.ref_source_post_2014, self.ac.pds_source_post_2014, - 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', - 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES'], - ['trend', '3rd Poly', '3rd Poly', - '3rd Poly', '3rd Poly', '3rd Poly', '3rd Poly', '3rd Poly', '3rd Poly', - '3rd Poly', '3rd Poly', '3rd Poly'], - ['growth', 'Medium', 'Medium', 'Medium', 'Medium', - 'Medium', 'Medium', 'Medium', 'Medium', 'Medium', 'Medium', 'Medium'], - ['low_sd_mult', 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], - ['high_sd_mult', 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]] - tamconfig = pd.DataFrame(tamconfig_list[1:], columns=tamconfig_list[0], dtype=np.object).set_index('param') - tam_ref_data_sources = { - 'Baseline Cases': { - 'Project Drawdown - Based on Data from Several Sources. (See HVFAC Links Sheet and HVFAC Material Availability Models)': THISDIR.joinpath('tam', 'tam_Project_Drawdown_based_on_Data_from_Several_Sources__See_HVFAC_Links_Sheet_and_HVFAC_Mat_2961774c.csv'), - }, - } - self.tm = tam.TAM(tamconfig=tamconfig, tam_ref_data_sources=tam_ref_data_sources, - tam_pds_data_sources=tam_ref_data_sources) - ref_tam_per_region=self.tm.ref_tam_per_region() - pds_tam_per_region=self.tm.pds_tam_per_region() - - # Custom PDS Data - ca_pds_data_sources = [ - {'name': 'Adoption Based on Fly Ash Availability Analysis/ PDS 1', 'include': True, - 'filename': THISDIR.joinpath('ca_pds_data', 'custom_pds_ad_Adoption_based_on_Fly_Ash_Availability_Analysis_PDS_1.csv')}, - {'name': 'Adoption Based on Fly Ash Availability Analysis/ PDS 2', 'include': True, - 'filename': THISDIR.joinpath('ca_pds_data', 'custom_pds_ad_Adoption_based_on_Fly_Ash_Availability_Analysis_PDS_2.csv')}, - {'name': 'Adoption Based on Fly Ash Availability Analysis/ PDS 3', 'include': True, - 'filename': THISDIR.joinpath('ca_pds_data', 'custom_pds_ad_Adoption_based_on_Fly_Ash_Availability_Analysis_PDS_3.csv')}, - {'name': 'Drawdown Book Edition 1 PDS 1, 2 and 3', 'include': True, - 'filename': THISDIR.joinpath('ca_pds_data', 'custom_pds_ad_Drawdown_Book_Edition_1_PDS_1_2_and_3.csv')}, - ] - self.pds_ca = customadoption.CustomAdoption(data_sources=ca_pds_data_sources, - soln_adoption_custom_name=self.ac.soln_pds_adoption_custom_name, - high_sd_mult=1.0, low_sd_mult=1.0, - total_adoption_limit=pds_tam_per_region) - - # Custom REF Data - ca_ref_data_sources = [ - {'name': 'REF Custom Adoption Based on Fly Ash Availability Analysis', 'include': False, - 'filename': THISDIR.joinpath('ca_ref_data', 'custom_ref_ad_REF_Custom_Adoption_based_on_Fly_Ash_Availability_Analysis.csv')}, - {'name': 'Drawdown Book Edition 1 Scenario REF Adoption', 'include': False, - 'filename': THISDIR.joinpath('ca_ref_data', 'custom_ref_ad_Drawdown_Book_Edition_1_Scenario_REF_Adoption.csv')}, - ] - self.ref_ca = customadoption.CustomAdoption(data_sources=ca_ref_data_sources, - soln_adoption_custom_name=self.ac.soln_ref_adoption_custom_name, - high_sd_mult=1.0, low_sd_mult=1.0, - total_adoption_limit=ref_tam_per_region) - - ref_adoption_data_per_region = self.ref_ca.adoption_data_per_region() - - if False: - # One may wonder why this is here. This file was code generated. - # This 'if False' allows subsequent conditions to all be elif. - pass - elif self.ac.soln_pds_adoption_basis == 'Fully Customized PDS': - pds_adoption_data_per_region = self.pds_ca.adoption_data_per_region() - pds_adoption_trend_per_region = self.pds_ca.adoption_trend_per_region() - pds_adoption_is_single_source = None - - ht_ref_adoption_initial = pd.Series( - [222.22222222222223, 0.0, 0.0, 0.0, 0.0, - 0.0, 0.0, 0.0, 0.0, 0.0], - index=dd.REGIONS) - ht_ref_adoption_final = ref_tam_per_region.loc[2050] * (ht_ref_adoption_initial / ref_tam_per_region.loc[2014]) - ht_ref_datapoints = pd.DataFrame(columns=dd.REGIONS) - ht_ref_datapoints.loc[2014] = ht_ref_adoption_initial - ht_ref_datapoints.loc[2050] = ht_ref_adoption_final.fillna(0.0) - ht_pds_adoption_initial = ht_ref_adoption_initial - ht_regions, ht_percentages = zip(*self.ac.pds_adoption_final_percentage) - ht_pds_adoption_final_percentage = pd.Series(list(ht_percentages), index=list(ht_regions)) - ht_pds_adoption_final = ht_pds_adoption_final_percentage * pds_tam_per_region.loc[2050] - ht_pds_datapoints = pd.DataFrame(columns=dd.REGIONS) - ht_pds_datapoints.loc[2014] = ht_pds_adoption_initial - ht_pds_datapoints.loc[2050] = ht_pds_adoption_final.fillna(0.0) - self.ht = helpertables.HelperTables(ac=self.ac, - ref_datapoints=ht_ref_datapoints, pds_datapoints=ht_pds_datapoints, - pds_adoption_data_per_region=pds_adoption_data_per_region, - ref_adoption_limits=ref_tam_per_region, pds_adoption_limits=pds_tam_per_region, - ref_adoption_data_per_region=ref_adoption_data_per_region, - pds_adoption_trend_per_region=pds_adoption_trend_per_region, - pds_adoption_is_single_source=pds_adoption_is_single_source) - - self.ef = emissionsfactors.ElectricityGenOnGrid(ac=self.ac) - - self.ua = unitadoption.UnitAdoption(ac=self.ac, - ref_total_adoption_units=ref_tam_per_region, pds_total_adoption_units=pds_tam_per_region, - soln_ref_funits_adopted=self.ht.soln_ref_funits_adopted(), - soln_pds_funits_adopted=self.ht.soln_pds_funits_adopted(), - repeated_cost_for_iunits=True, - bug_cfunits_double_count=False) - soln_pds_tot_iunits_reqd = self.ua.soln_pds_tot_iunits_reqd() - soln_ref_tot_iunits_reqd = self.ua.soln_ref_tot_iunits_reqd() - conv_ref_tot_iunits = self.ua.conv_ref_tot_iunits() - soln_net_annual_funits_adopted=self.ua.soln_net_annual_funits_adopted() - - self.fc = firstcost.FirstCost(ac=self.ac, pds_learning_increase_mult=2, - ref_learning_increase_mult=2, conv_learning_increase_mult=2, - soln_pds_tot_iunits_reqd=soln_pds_tot_iunits_reqd, - soln_ref_tot_iunits_reqd=soln_ref_tot_iunits_reqd, - conv_ref_tot_iunits=conv_ref_tot_iunits, - soln_pds_new_iunits_reqd=self.ua.soln_pds_new_iunits_reqd(), - soln_ref_new_iunits_reqd=self.ua.soln_ref_new_iunits_reqd(), - conv_ref_new_iunits=self.ua.conv_ref_new_iunits(), - fc_convert_iunit_factor=1.0) - - self.oc = operatingcost.OperatingCost(ac=self.ac, - soln_net_annual_funits_adopted=soln_net_annual_funits_adopted, - soln_pds_tot_iunits_reqd=soln_pds_tot_iunits_reqd, - soln_ref_tot_iunits_reqd=soln_ref_tot_iunits_reqd, - conv_ref_annual_tot_iunits=self.ua.conv_ref_annual_tot_iunits(), - soln_pds_annual_world_first_cost=self.fc.soln_pds_annual_world_first_cost(), - soln_ref_annual_world_first_cost=self.fc.soln_ref_annual_world_first_cost(), - conv_ref_annual_world_first_cost=self.fc.conv_ref_annual_world_first_cost(), - single_iunit_purchase_year=2017, - soln_pds_install_cost_per_iunit=self.fc.soln_pds_install_cost_per_iunit(), - conv_ref_install_cost_per_iunit=self.fc.conv_ref_install_cost_per_iunit(), - conversion_factor=1.0) - - self.c4 = ch4calcs.CH4Calcs(ac=self.ac, - soln_net_annual_funits_adopted=soln_net_annual_funits_adopted) - - self.c2 = co2calcs.CO2Calcs(ac=self.ac, - ch4_ppb_calculator=self.c4.ch4_ppb_calculator(), - soln_pds_net_grid_electricity_units_saved=self.ua.soln_pds_net_grid_electricity_units_saved(), - soln_pds_net_grid_electricity_units_used=self.ua.soln_pds_net_grid_electricity_units_used(), - soln_pds_direct_co2_emissions_saved=self.ua.soln_pds_direct_co2_emissions_saved(), - soln_pds_direct_ch4_co2_emissions_saved=self.ua.soln_pds_direct_ch4_co2_emissions_saved(), - soln_pds_direct_n2o_co2_emissions_saved=self.ua.soln_pds_direct_n2o_co2_emissions_saved(), - soln_pds_new_iunits_reqd=self.ua.soln_pds_new_iunits_reqd(), - soln_ref_new_iunits_reqd=self.ua.soln_ref_new_iunits_reqd(), - conv_ref_new_iunits=self.ua.conv_ref_new_iunits(), - conv_ref_grid_CO2_per_KWh=self.ef.conv_ref_grid_CO2_per_KWh(), - conv_ref_grid_CO2eq_per_KWh=self.ef.conv_ref_grid_CO2eq_per_KWh(), - soln_net_annual_funits_adopted=soln_net_annual_funits_adopted, - fuel_in_liters=False) - - self.r2s = rrs.RRS(total_energy_demand=ref_tam_per_region.loc[2014, 'World'], - soln_avg_annual_use=self.ac.soln_avg_annual_use, - conv_avg_annual_use=self.ac.conv_avg_annual_use) + name = name + units = units + vmas = VMAs + solution_category = solution_category + + def __init__(self, scenario=None): + if scenario is None: + scenario = list(scenarios.keys())[0] + self.scenario = scenario + self.ac = scenarios[scenario] + + # TAM + tamconfig_list = [ + ['param', 'World', 'PDS World', 'OECD90', 'Eastern Europe', 'Asia (Sans Japan)', + 'Middle East and Africa', 'Latin America', 'China', 'India', 'EU', 'USA'], + ['source_until_2014', self.ac.source_until_2014, self.ac.source_until_2014, + 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', + 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES'], + ['source_after_2014', self.ac.ref_source_post_2014, self.ac.pds_source_post_2014, + 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES', + 'ALL SOURCES', 'ALL SOURCES', 'ALL SOURCES'], + ['trend', '3rd Poly', '3rd Poly', + '3rd Poly', '3rd Poly', '3rd Poly', '3rd Poly', '3rd Poly', '3rd Poly', + '3rd Poly', '3rd Poly', '3rd Poly'], + ['growth', 'Medium', 'Medium', 'Medium', 'Medium', + 'Medium', 'Medium', 'Medium', 'Medium', 'Medium', 'Medium', 'Medium'], + ['low_sd_mult', 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], + ['high_sd_mult', 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]] + tamconfig = pd.DataFrame(tamconfig_list[1:], columns=tamconfig_list[0], + dtype=np.object).set_index('param') + tam_ref_data_sources = { + 'Baseline Cases': { + 'Project Drawdown - Based on Data from Several Sources. (See HVFAC Links Sheet and HVFAC Material Availability Models)': THISDIR.joinpath('tam', 'tam_Project_Drawdown_based_on_Data_from_Several_Sources__See_HVFAC_Links_Sheet_and_HVFAC_Mat_2961774c.csv'), + }, + 'Conservative Cases': { + 'IEA 2018 Low-Variability': THISDIR.joinpath('tam', 'tam_IEA_2018_LowVariability.csv'), + 'Farfan et al. 2019': THISDIR.joinpath('tam', 'tam_Farfan_et_al__2019.csv'), + 'van Ruijven et al. 2016': THISDIR.joinpath('tam', 'tam_van_Ruijven_et_al__2016.csv'), + }, + 'Ambitious Cases': { + 'IEA 2018 High-Variability': THISDIR.joinpath('tam', 'tam_IEA_2018_HighVariability.csv'), + }, + 'Maximum Cases': { + 'WBCSD Cement 2002': THISDIR.joinpath('tam', 'tam_WBCSD_Cement_2002.csv'), + }, + } + self.tm = tam.TAM(tamconfig=tamconfig, tam_ref_data_sources=tam_ref_data_sources, + tam_pds_data_sources=tam_ref_data_sources) + ref_tam_per_region=self.tm.ref_tam_per_region() + pds_tam_per_region=self.tm.pds_tam_per_region() + + adconfig_list = [ + ['param', 'World', 'OECD90', 'Eastern Europe', 'Asia (Sans Japan)', + 'Middle East and Africa', 'Latin America', 'China', 'India', 'EU', 'USA'], + ['trend', self.ac.soln_pds_adoption_prognostication_trend, '3rd Poly', + '3rd Poly', '3rd Poly', '3rd Poly', '3rd Poly', '3rd Poly', + '3rd Poly', '3rd Poly', '3rd Poly'], + ['growth', self.ac.soln_pds_adoption_prognostication_growth, 'Medium', + 'Medium', 'Medium', 'Medium', 'Medium', 'Medium', + 'Medium', 'Medium', 'Medium'], + ['low_sd_mult', 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], + ['high_sd_mult', 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]] + adconfig = pd.DataFrame(adconfig_list[1:], columns=adconfig_list[0], + dtype=np.object).set_index('param') + ad_data_sources = { + } + self.ad = adoptiondata.AdoptionData(ac=self.ac, data_sources=ad_data_sources, + adconfig=adconfig) + + # Custom PDS Data + wb = xlrd.open_workbook(filename=THISDIR.joinpath('data.xlsx'), on_demand=True) + def isint(x): + try: + int(x) + return True + except ValueError: + return False + def demangle(name): + # Pandas tries to be helpful by mangling duplicate column names, so the first + # read_excel returns 'Latin America' and the second 'Latin America.1' + if not '.' in name: + return name + new, suffix = name.rsplit('.', 1) + return new if isint(suffix) else name + clinker_pct = self.ac.lookup_vma(vma_title='Clinker to Cement Ratio in Year 2') + + # Data Source 1 + hvfac_mmt_pds1 = pd.read_excel(io=wb, sheet_name='HVFAC Links', header=0, index_col=0, + usecols='B:L', dtype='float', engine='xlrd', skiprows=62, nrows=46 + ).rename(mapper=demangle, axis='columns').rename(columns={ + 'Asia (sans Japan)': 'Asia (Sans Japan)', + 'Middle East & Africa': 'Middle East and Africa', + }) + hvfac_mmt_pds1.index.name = 'Year' + hvfac_mmt_pds1.loc[2014] = 0.0 + ds1_df = hvfac_mmt_pds1.sort_index() / clinker_pct + + # Data Source 2 + hvfac_mmt_pds2 = pd.read_excel(io=wb, sheet_name='HVFAC Links', header=0, index_col=0, + usecols='O:Y', dtype='float', engine='xlrd', skiprows=62, nrows=46 + ).rename(mapper=demangle, axis='columns').rename(columns={ + 'Asia (sans Japan)': 'Asia (Sans Japan)', + 'Middle East & Africa': 'Middle East and Africa', + }) + hvfac_mmt_pds2.index.name = 'Year' + hvfac_mmt_pds2.loc[2014] = 0.0 + ds2_df = hvfac_mmt_pds2.sort_index() / clinker_pct + + # Data Source 3 + hvfac_mmt_pds3 = pd.read_excel(io=wb, sheet_name='HVFAC Links', header=0, index_col=0, + usecols='AB:AL', dtype='float', engine='xlrd', skiprows=62, nrows=46 + ).rename(mapper=demangle, axis='columns').rename(columns={ + 'Asia (sans Japan)': 'Asia (Sans Japan)', + 'Middle East & Africa': 'Middle East and Africa', + }) + hvfac_mmt_pds3.index.name = 'Year' + hvfac_mmt_pds3.loc[2014] = 0.0 + ds3_df = hvfac_mmt_pds3.sort_index() / clinker_pct + + # Data Source 4 + filename_ds4 = THISDIR.joinpath('ca_pds_data', 'pds_adoption_scenario_4.csv') + book_mmt = pd.read_csv(filename_ds4, header=0, index_col=0, skipinitialspace=True, + skip_blank_lines=True, comment='#', dtype=np.float64) + book_mmt.index = book_mmt.index.astype(int) + ds4_df = book_mmt / clinker_pct + + ca_pds_data_sources = [ + {'name': 'Adoption Based on Fly Ash Availability Analysis/ PDS 1', 'include': True, + 'description': ( + 'Fly Ash (FA) is a waste product of coal fired power stations. FA that is ' + 'not reused, is disposed in dry landfills or wet ponds. FA is valuable ' + 'because it can be used to replace Ordinary Portland Cement (OPC) in the ' + 'cement mix (up to a certain percentage) and hence it can be used to reduce ' + 'the CO2 footprint of concrete. The separate HVFAC model evaluates the total ' + 'amount of FA available in a market based on projected coal demand and ' + "coal's fly ash concentration. The model divides the total FA supply into " + "three streams (i) landfill; (ii) 'other uses' (i.e. reuse but not cement); " + 'and (iii) cement mixes. The total addressable market for cement ' + 'production/demand is initially defined as the total cement demand (assumed ' + 'OPC) plus that portion of FA that is reused for cement. A higher ratio of ' + 'FA:OPC (e.g. 45%:55%) for the cement mix is the adopted solution for CO2 ' + 'mitigation. The target FA:OPC ratio is input into the model to define the ' + 'PDS scenario. The model calculates the annual mass of OPC that can be ' + 'avoided, the energy saved, and the CO2 emissions avoided. There are two ' + 'factors (cement demand and FA supply) that have the potential to limit OPC ' + 'replacement with FA. Model input includes the PDS transition period (e.g. 5 ' + 'years) to implement the new policy for cement production, concrete ' + 'standards, and FA reuse infrastructure. The model allows an addtional ' + 'policy option: to utilise FA in landfill when the 100% of FA waste stream ' + 'is utilised in cement production and other uses. For this scenario, ' + 'reduction of coal demand for electricity generation in the PDS1 affects the ' + 'total amount of fly ash available. ' + ), + 'dataframe': ds1_df}, + {'name': 'Adoption Based on Fly Ash Availability Analysis/ PDS 2', 'include': True, + 'description': ( + 'Fly Ash (FA) is a waste product of coal fired power stations. FA that is ' + 'not reused, is disposed in dry landfills or wet ponds. FA is valuable ' + 'because it can be used to replace Ordinary Portland Cement (OPC) in the ' + 'cement mix (up to a certain percentage) and hence it can be used to reduce ' + 'the CO2 footprint of concrete. The separate HVFAC model evaluates the total ' + 'amount of FA available in a market based on projected coal demand and ' + "coal's fly ash concentration. The model divides the total FA supply into " + "three streams (i) landfill; (ii) 'other uses' (i.e. reuse but not cement); " + 'and (iii) cement mixes. The total addressable market for cement ' + 'production/demand is initially defined as the total cement demand (assumed ' + 'OPC) plus that portion of FA that is reused for cement. A higher ratio of ' + 'FA:OPC (e.g. 45%:55%) for the cement mix is the adopted solution for CO2 ' + 'mitigation. The target FA:OPC ratio is input into the model to define the ' + 'PDS scenario. The model calculates the annual mass of OPC that can be ' + 'avoided, the energy saved, and the CO2 emissions avoided. There are two ' + 'factors (cement demand and FA supply) that have the potential to limit OPC ' + 'replacement with FA. Model input includes the PDS transition period (e.g. 5 ' + 'years) to implement the new policy for cement production, concrete ' + 'standards, and FA reuse infrastructure. The model allows an addtional ' + 'policy option: to utilise FA in landfill when the 100% of FA waste stream ' + 'is utilised in cement production and other uses. For this scenario, ' + 'reduction of coal demand for electricity generation in the PDS2 affects the ' + 'total amount of fly ash available. ' + ), + 'dataframe': ds2_df}, + {'name': 'Adoption Based on Fly Ash Availability Analysis/ PDS 3', 'include': True, + 'description': ( + 'Fly Ash (FA) is a waste product of coal fired power stations. FA that is ' + 'not reused, is disposed in dry landfills or wet ponds. FA is valuable ' + 'because it can be used to replace Ordinary Portland Cement (OPC) in the ' + 'cement mix (up to a certain percentage) and hence it can be used to reduce ' + 'the CO2 footprint of concrete. The separate HVFAC model evaluates the total ' + 'amount of FA available in a market based on projected coal demand and ' + "coal's fly ash concentration. The model divides the total FA supply into " + "three streams (i) landfill; (ii) 'other uses' (i.e. reuse but not cement); " + 'and (iii) cement mixes. The total addressable market for cement ' + 'production/demand is initially defined as the total cement demand (assumed ' + 'OPC) plus that portion of FA that is reused for cement. A higher ratio of ' + 'FA:OPC (e.g. 45%:55%) for the cement mix is the adopted solution for CO2 ' + 'mitigation. The target FA:OPC ratio is input into the model to define the ' + 'PDS scenario. The model calculates the annual mass of OPC that can be ' + 'avoided, the energy saved, and the CO2 emissions avoided. There are two ' + 'factors (cement demand and FA supply) that have the potential to limit OPC ' + 'replacement with FA. Model input includes the PDS transition period (e.g. 5 ' + 'years) to implement the new policy for cement production, concrete ' + 'standards, and FA reuse infrastructure. The model allows an addtional ' + 'policy option: to utilise FA in landfill when the 100% of FA waste stream ' + 'is utilised in cement production and other uses. For this scenario, ' + 'reduction of coal demand for electricity generation in the PDS3 affects the ' + 'total amount of fly ash available. ' + ), + 'dataframe': ds3_df}, + {'name': 'Drawdown Book Edition 1 PDS 1, 2 and 3', 'include': True, + 'description': ( + 'Fly Ash (FA) is a waste product of coal fired power stations. FA that is ' + 'not reused, is disposed in dry landfills or wet ponds. FA is valuable ' + 'because it can be used to replace Ordinary Portland Cement (OPC) in the ' + 'cement mix (up to a certain percentage) and hence it can be used to reduce ' + 'the CO2 footprint of concrete. The separate HVFAC model evaluates the total ' + 'amount of FA available in a market based on projected coal demand and ' + "coal's fly ash concentration. The model divides the total FA supply into " + "three streams (i) landfill; (ii) 'other uses' (i.e. reuse but not cement); " + 'and (iii) cement mixes. The total addressable market for cement ' + 'production/demand is initially defined as the total cement demand (assumed ' + 'OPC) plus that portion of FA that is reused for cement. A higher ratio of ' + 'FA:OPC (e.g. 45%:55%) for the cement mix is the adopted solution for CO2 ' + 'mitigation. The target FA:OPC ratio is input into the model to define the ' + 'PDS scenario. The model calculates the annual mass of OPC that can be ' + 'avoided, the energy saved, and the CO2 emissions avoided. There are two ' + 'factors (cement demand and FA supply) that have the potential to limit OPC ' + 'replacement with FA. Model input includes the PDS transition period (e.g. 5 ' + 'years) to implement the new policy for cement production, concrete ' + 'standards, and FA reuse infrastructure. The model allows an addtional ' + 'policy option: to utilise FA in landfill when the 100% of FA waste stream ' + 'is utilised in cement production and other uses. This scenario uses inputs ' + 'calculated for the Drawdown book edition 1, some of which have been updated ' + 'with newer data. ' + ), + 'dataframe': ds4_df}, + ] + self.pds_ca = customadoption.CustomAdoption(data_sources=ca_pds_data_sources, + soln_adoption_custom_name=self.ac.soln_pds_adoption_custom_name, + high_sd_mult=self.ac.soln_pds_adoption_custom_high_sd_mult, + low_sd_mult=self.ac.soln_pds_adoption_custom_low_sd_mult, + total_adoption_limit=pds_tam_per_region) + + # Custom REF Data + # Data Source 1 + hvfac_mmt_ref = pd.read_excel(io=wb, sheet_name='HVFAC Links', header=0, index_col=0, + usecols='B:L', dtype='float', engine='xlrd', skiprows=113, nrows=46 + ).rename(mapper=demangle, axis='columns').rename(columns={ + 'Asia (sans Japan)': 'Asia (Sans Japan)', + 'Middle East & Africa': 'Middle East and Africa', + }) + hvfac_mmt_ref.index.name = 'Year' + hvfac_mmt_ref.loc[2014] = 0.0 + ref1_df = hvfac_mmt_ref.sort_index() / clinker_pct + + # Data Source 2 + filename_ref2 = THISDIR.joinpath('ca_ref_data', 'ref_adoption_scenario_2.csv') + book_ref_mmt = pd.read_csv(filename_ref2, header=0, index_col=0, skipinitialspace=True, + skip_blank_lines=True, comment='#', dtype=np.float64) + book_ref_mmt.index = book_ref_mmt.index.astype(int) + ref2_df = book_ref_mmt / clinker_pct + + ca_ref_data_sources = [ + {'name': 'REF Custom Adoption Based on Fly Ash Availability Analysis', 'include': True, + 'description': ( + 'Fly Ash (FA) is a waste product of coal fired power stations. FA that is ' + 'not reused, is disposed in dry landfills or wet ponds. FA is valuable ' + 'because it can be used to replace Ordinary Portland Cement (OPC) in the ' + 'cement mix (up to a certain percentage) and hence it can be used to reduce ' + 'the CO2 footprint of concrete. The separate HVFAC model evaluates the total ' + 'amount of FA available in a market based on projected coal demand and ' + "coal's fly ash concentration. The model divides the total FA supply into " + "three streams (i) landfill; (ii) 'other uses' (i.e. reuse but not cement); " + 'and (iii) cement mixes. The total addressable market for cement ' + 'production/demand is initially defined as the total cement demand (assumed ' + 'OPC) plus that portion of FA that is reused for cement. A higher ratio of ' + 'FA:OPC (e.g. 45%:55%) for the cement mix is the adopted solution for CO2 ' + 'mitigation. The target FA:OPC ratio is input into the model to define the ' + 'PDS scenario. The model calculates the annual mass of OPC that can be ' + 'avoided, the energy saved, and the CO2 emissions avoided. There are two ' + 'factors (cement demand and FA supply) that have the potential to limit OPC ' + 'replacement with FA. Model input includes the PDS transition period (e.g. 5 ' + 'years) to implement the new policy for cement production, concrete ' + 'standards, and FA reuse infrastructure. The model allows an addtional ' + 'policy option: to utilise FA in landfill when the 100% of FA waste stream ' + 'is utilised in cement production and other uses. ' + ), + 'dataframe': ref1_df}, + {'name': 'Drawdown Book Edition 1 Scenario REF Adoption', 'include': True, + 'description': ( + 'Fly Ash (FA) is a waste product of coal fired power stations. FA that is ' + 'not reused, is disposed in dry landfills or wet ponds. FA is valuable ' + 'because it can be used to replace Ordinary Portland Cement (OPC) in the ' + 'cement mix (up to a certain percentage) and hence it can be used to reduce ' + 'the CO2 footprint of concrete. The separate HVFAC model evaluates the total ' + 'amount of FA available in a market based on projected coal demand and ' + "coal's fly ash concentration. The model divides the total FA supply into " + "three streams (i) landfill; (ii) 'other uses' (i.e. reuse but not cement); " + 'and (iii) cement mixes. The total addressable market for cement ' + 'production/demand is initially defined as the total cement demand (assumed ' + 'OPC) plus that portion of FA that is reused for cement. A higher ratio of ' + 'FA:OPC (e.g. 45%:55%) for the cement mix is the adopted solution for CO2 ' + 'mitigation. The target FA:OPC ratio is input into the model to define the ' + 'PDS scenario. The model calculates the annual mass of OPC that can be ' + 'avoided, the energy saved, and the CO2 emissions avoided. There are two ' + 'factors (cement demand and FA supply) that have the potential to limit OPC ' + 'replacement with FA. Model input includes the PDS transition period (e.g. 5 ' + 'years) to implement the new policy for cement production, concrete ' + 'standards, and FA reuse infrastructure. The model allows an addtional ' + 'policy option: to utilise FA in landfill when the 100% of FA waste stream ' + 'is utilised in cement production and other uses. This scenario uses inputs ' + 'calculated for the Drawdown book edition 1, some of which have been updated ' + 'with newer data. ' + ), + 'dataframe': ref2_df}, + ] + self.ref_ca = customadoption.CustomAdoption(data_sources=ca_ref_data_sources, + soln_adoption_custom_name=self.ac.soln_ref_adoption_custom_name, + high_sd_mult=1.0, low_sd_mult=1.0, + total_adoption_limit=ref_tam_per_region) + + if self.ac.soln_ref_adoption_basis == 'Custom': + ref_adoption_data_per_region = self.ref_ca.adoption_data_per_region() + else: + ref_adoption_data_per_region = None + + if False: + # One may wonder why this is here. This file was code generated. + # This 'if False' allows subsequent conditions to all be elif. + pass + elif self.ac.soln_pds_adoption_basis == 'Fully Customized PDS': + pds_adoption_data_per_region = self.pds_ca.adoption_data_per_region() + pds_adoption_trend_per_region = self.pds_ca.adoption_trend_per_region() + pds_adoption_is_single_source = None + elif self.ac.soln_pds_adoption_basis == 'Existing Adoption Prognostications': + pds_adoption_data_per_region = self.ad.adoption_data_per_region() + pds_adoption_trend_per_region = self.ad.adoption_trend_per_region() + pds_adoption_is_single_source = self.ad.adoption_is_single_source() + elif self.ac.soln_pds_adoption_basis == 'Linear': + pds_adoption_data_per_region = None + pds_adoption_trend_per_region = None + pds_adoption_is_single_source = None + + ht_ref_adoption_initial = pd.Series( + list(self.ac.ref_base_adoption.values()), index=dd.REGIONS) + ht_ref_adoption_final = ref_tam_per_region.loc[2050] * (ht_ref_adoption_initial / + ref_tam_per_region.loc[2018]) + ht_ref_datapoints = pd.DataFrame(columns=dd.REGIONS) + ht_ref_datapoints.loc[2018] = ht_ref_adoption_initial + ht_ref_datapoints.loc[2050] = ht_ref_adoption_final.fillna(0.0) + ht_pds_adoption_initial = ht_ref_adoption_initial + ht_pds_adoption_final_percentage = pd.Series( + list(self.ac.pds_adoption_final_percentage.values()), + index=list(self.ac.pds_adoption_final_percentage.keys())) + ht_pds_adoption_final = ht_pds_adoption_final_percentage * pds_tam_per_region.loc[2050] + ht_pds_datapoints = pd.DataFrame(columns=dd.REGIONS) + ht_pds_datapoints.loc[2018] = ht_pds_adoption_initial + ht_pds_datapoints.loc[2050] = ht_pds_adoption_final.fillna(0.0) + self.ht = helpertables.HelperTables(ac=self.ac, + ref_datapoints=ht_ref_datapoints, pds_datapoints=ht_pds_datapoints, + pds_adoption_data_per_region=pds_adoption_data_per_region, + ref_adoption_limits=ref_tam_per_region, pds_adoption_limits=pds_tam_per_region, + ref_adoption_data_per_region=ref_adoption_data_per_region, + use_first_pds_datapoint_main=False, + copy_pds_to_ref=False, copy_ref_datapoint=False, copy_pds_datapoint=False, + pds_adoption_trend_per_region=pds_adoption_trend_per_region, + pds_adoption_is_single_source=pds_adoption_is_single_source) + + self.ef = emissionsfactors.ElectricityGenOnGrid(ac=self.ac, grid_emissions_version=4) + + self.ua = unitadoption.UnitAdoption(ac=self.ac, + ref_total_adoption_units=ref_tam_per_region, + pds_total_adoption_units=pds_tam_per_region, + soln_ref_funits_adopted=self.ht.soln_ref_funits_adopted(), + soln_pds_funits_adopted=self.ht.soln_pds_funits_adopted(), + repeated_cost_for_iunits=True, + bug_cfunits_double_count=False) + soln_pds_tot_iunits_reqd = self.ua.soln_pds_tot_iunits_reqd() + soln_ref_tot_iunits_reqd = self.ua.soln_ref_tot_iunits_reqd() + conv_ref_tot_iunits = self.ua.conv_ref_tot_iunits() + soln_net_annual_funits_adopted=self.ua.soln_net_annual_funits_adopted() + + self.fc = firstcost.FirstCost(ac=self.ac, pds_learning_increase_mult=2, + ref_learning_increase_mult=2, conv_learning_increase_mult=2, + soln_pds_tot_iunits_reqd=soln_pds_tot_iunits_reqd, + soln_ref_tot_iunits_reqd=soln_ref_tot_iunits_reqd, + conv_ref_tot_iunits=conv_ref_tot_iunits, + soln_pds_new_iunits_reqd=self.ua.soln_pds_new_iunits_reqd(), + soln_ref_new_iunits_reqd=self.ua.soln_ref_new_iunits_reqd(), + conv_ref_new_iunits=self.ua.conv_ref_new_iunits(), + fc_convert_iunit_factor=1.0) + + self.oc = operatingcost.OperatingCost(ac=self.ac, + soln_net_annual_funits_adopted=soln_net_annual_funits_adopted, + soln_pds_tot_iunits_reqd=soln_pds_tot_iunits_reqd, + soln_ref_tot_iunits_reqd=soln_ref_tot_iunits_reqd, + conv_ref_annual_tot_iunits=self.ua.conv_ref_annual_tot_iunits(), + soln_pds_annual_world_first_cost=self.fc.soln_pds_annual_world_first_cost(), + soln_ref_annual_world_first_cost=self.fc.soln_ref_annual_world_first_cost(), + conv_ref_annual_world_first_cost=self.fc.conv_ref_annual_world_first_cost(), + single_iunit_purchase_year=2017, + soln_pds_install_cost_per_iunit=self.fc.soln_pds_install_cost_per_iunit(), + conv_ref_install_cost_per_iunit=self.fc.conv_ref_install_cost_per_iunit(), + conversion_factor=1.0) + + self.c4 = ch4calcs.CH4Calcs(ac=self.ac, + soln_net_annual_funits_adopted=soln_net_annual_funits_adopted) + + self.c2 = co2calcs.CO2Calcs(ac=self.ac, + ch4_ppb_calculator=self.c4.ch4_ppb_calculator(), + soln_pds_net_grid_electricity_units_saved=self.ua.soln_pds_net_grid_electricity_units_saved(), + soln_pds_net_grid_electricity_units_used=self.ua.soln_pds_net_grid_electricity_units_used(), + soln_pds_direct_co2_emissions_saved=self.ua.soln_pds_direct_co2_emissions_saved(), + soln_pds_direct_ch4_co2_emissions_saved=self.ua.soln_pds_direct_ch4_co2_emissions_saved(), + soln_pds_direct_n2o_co2_emissions_saved=self.ua.soln_pds_direct_n2o_co2_emissions_saved(), + soln_pds_new_iunits_reqd=self.ua.soln_pds_new_iunits_reqd(), + soln_ref_new_iunits_reqd=self.ua.soln_ref_new_iunits_reqd(), + conv_ref_new_iunits=self.ua.conv_ref_new_iunits(), + conv_ref_grid_CO2_per_KWh=self.ef.conv_ref_grid_CO2_per_KWh(), + conv_ref_grid_CO2eq_per_KWh=self.ef.conv_ref_grid_CO2eq_per_KWh(), + soln_net_annual_funits_adopted=soln_net_annual_funits_adopted, + fuel_in_liters=False) + + self.r2s = rrs.RRS(total_energy_demand=ref_tam_per_region.loc[2014, 'World'], + soln_avg_annual_use=self.ac.soln_avg_annual_use, + conv_avg_annual_use=self.ac.conv_avg_annual_use) diff --git a/solution/altcement/ac/PDS-100p2050-027clinkercement-postintjune2020.json b/solution/altcement/ac/PDS-100p2050-027clinkercement-postintjune2020.json new file mode 100644 index 000000000..7f3ec7888 --- /dev/null +++ b/solution/altcement/ac/PDS-100p2050-027clinkercement-postintjune2020.json @@ -0,0 +1,157 @@ +{ + "name": "PDS-100p2050-0.27clinker/cement-postintjune2020", + "solution_category": "reduction", + "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.268957570755006 + }, + "description": "Updated emissions factors", + "report_start_year": 2020, + "report_end_year": 2050, + "conv_2014_cost": { + "value": 74790999.4544158, + "statistic": "" + }, + "conv_first_cost_efficiency_rate": 0.0, + "conv_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "conv_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "conv_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "conv_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_cost_per_funit": 0.0, + "pds_2014_cost": { + "value": 73863591.0611811, + "statistic": "" + }, + "ref_2014_cost": { + "value": 73863591.0611811, + "statistic": "" + }, + "soln_first_cost_efficiency_rate": 0.0, + "soln_first_cost_below_conv": true, + "soln_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "soln_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "soln_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "soln_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "soln_fuel_cost_per_funit": 0.0, + "npv_discount_rate": 0.0922, + "conv_annual_energy_used": { + "value": 0.097, + "statistic": "" + }, + "soln_energy_efficiency_factor": { + "value": 0.0, + "statistic": "" + }, + "soln_annual_energy_used": { + "value": 0.088, + "statistic": "" + }, + "conv_fuel_consumed_per_funit": { + "value": 3519.0, + "statistic": "" + }, + "soln_fuel_efficiency_factor": { + "value": 0.650705891634302, + "statistic": "" + }, + "conv_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "soln_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "conv_emissions_per_funit": { + "value": 350844.0, + "statistic": "" + }, + "soln_emissions_per_funit": { + "value": 136361.488372788, + "statistic": "" + }, + "conv_indirect_co2_per_unit": { + "value": 30025.072, + "statistic": "" + }, + "soln_indirect_co2_per_iunit": { + "value": 71264.940172519, + "statistic": "" + }, + "conv_indirect_co2_is_iunits": false, + "ch4_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "ch4_is_co2eq": false, + "n2o_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "n2o_is_co2eq": false, + "co2eq_conversion_source": "AR5 with feedback", + "emissions_use_co2eq": true, + "emissions_grid_source": "Meta-Analysis", + "emissions_grid_range": "Mean", + "source_until_2014": "ALL SOURCES", + "ref_source_post_2014": "Conservative Cases", + "pds_source_post_2014": "Conservative Cases", + "ref_base_adoption": { + "World": 0.001, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_basis": "DEFAULT Linear", + "soln_pds_adoption_regional_data": false, + "pds_adoption_final_percentage": { + "World": 1.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_ref_adoption_basis": "Default", + "soln_ref_adoption_regional_data": false, + "pds_adoption_use_ref_years": [ + 2014, + 2015, + 2016, + 2017 + ] +} diff --git a/solution/altcement/ac/PDS1,2,3-19p2050-Availability_Analysis_Book_Ed1.json b/solution/altcement/ac/PDS1,2,3-19p2050-Availability_Analysis_Book_Ed1.json index 4cc8442e5..b662d4604 100644 --- a/solution/altcement/ac/PDS1,2,3-19p2050-Availability_Analysis_Book_Ed1.json +++ b/solution/altcement/ac/PDS1,2,3-19p2050-Availability_Analysis_Book_Ed1.json @@ -2,6 +2,9 @@ "name": "PDS1,2,3-19p2050-Availability Analysis (Book Ed.1)", "solution_category": "reduction", "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.45 + }, "description": "This scenario is based on a Fly Ash availability analysis since Fly Ash incorporation in cement is the definition of this solution and that is based on coal burning which has an uncertain future. Fly Ash cement is therefore a transition solution. The availability assumptions are shown in the Custom Adoption sheets. All PDS scenarios are the same. This scenario uses inputs calculated for the Drawdown book edition 1, some of which have been updated since publication.", "report_start_year": 2020, "report_end_year": 2050, @@ -117,94 +120,34 @@ "source_until_2014": "ALL SOURCES", "ref_source_post_2014": "ALL SOURCES", "pds_source_post_2014": "ALL SOURCES", - "pds_base_adoption": [ - [ - "World", - 222.222222222222 - ], - [ - "OECD90", - 0.0 - ], - [ - "Eastern Europe", - 0.0 - ], - [ - "Asia (Sans Japan)", - 0.0 - ], - [ - "Middle East and Africa", - 0.0 - ], - [ - "Latin America", - 0.0 - ], - [ - "China", - 0.0 - ], - [ - "India", - 0.0 - ], - [ - "EU", - 0.0 - ], - [ - "USA", - 0.0 - ] - ], + "ref_base_adoption": { + "World": 222.222222222222, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, "soln_pds_adoption_basis": "Fully Customized PDS", "soln_pds_adoption_regional_data": false, - "pds_adoption_final_percentage": [ - [ - "World", - 0.0 - ], - [ - "OECD90", - 0.0 - ], - [ - "Eastern Europe", - 0.0 - ], - [ - "Asia (Sans Japan)", - 0.0 - ], - [ - "Middle East and Africa", - 0.0 - ], - [ - "Latin America", - 0.0 - ], - [ - "China", - 0.0 - ], - [ - "India", - 0.0 - ], - [ - "EU", - 0.0 - ], - [ - "USA", - 0.0 - ] - ], + "pds_adoption_final_percentage": { + "World": 0.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, "soln_pds_adoption_custom_name": "Drawdown Book Edition 1 PDS 1, 2 and 3", "soln_ref_adoption_basis": "Custom", "soln_ref_adoption_custom_name": "Drawdown Book Edition 1 Scenario REF Adoption", "soln_ref_adoption_regional_data": false -} \ No newline at end of file +} diff --git a/solution/altcement/ac/PDS1-100p2050-06ClinkerCement-postintJune2020.json b/solution/altcement/ac/PDS1-100p2050-06ClinkerCement-postintJune2020.json new file mode 100644 index 000000000..613f1ddf3 --- /dev/null +++ b/solution/altcement/ac/PDS1-100p2050-06ClinkerCement-postintJune2020.json @@ -0,0 +1,157 @@ +{ + "name": "PDS1-100p2050-0.6Clinker/Cement-postintJune2020", + "solution_category": "reduction", + "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.6 + }, + "description": "Updated emissions factors", + "report_start_year": 2020, + "report_end_year": 2050, + "conv_2014_cost": { + "value": 74790999.4544158, + "statistic": "" + }, + "conv_first_cost_efficiency_rate": 0.0, + "conv_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "conv_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "conv_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "conv_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_cost_per_funit": 0.0, + "pds_2014_cost": { + "value": 73863591.0611811, + "statistic": "" + }, + "ref_2014_cost": { + "value": 73863591.0611811, + "statistic": "" + }, + "soln_first_cost_efficiency_rate": 0.0, + "soln_first_cost_below_conv": true, + "soln_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "soln_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "soln_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "soln_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "soln_fuel_cost_per_funit": 0.0, + "npv_discount_rate": 0.0922, + "conv_annual_energy_used": { + "value": 0.097, + "statistic": "" + }, + "soln_energy_efficiency_factor": { + "value": 0.0, + "statistic": "" + }, + "soln_annual_energy_used": { + "value": 0.088, + "statistic": "" + }, + "conv_fuel_consumed_per_funit": { + "value": 3519.0, + "statistic": "" + }, + "soln_fuel_efficiency_factor": { + "value": 0.220782428874914, + "statistic": "" + }, + "conv_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "soln_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "conv_emissions_per_funit": { + "value": 350844.0, + "statistic": "" + }, + "soln_emissions_per_funit": { + "value": 304200.0, + "statistic": "" + }, + "conv_indirect_co2_per_unit": { + "value": 30025.072, + "statistic": "" + }, + "soln_indirect_co2_per_iunit": { + "value": 38993.6, + "statistic": "" + }, + "conv_indirect_co2_is_iunits": false, + "ch4_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "ch4_is_co2eq": false, + "n2o_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "n2o_is_co2eq": false, + "co2eq_conversion_source": "AR5 with feedback", + "emissions_use_co2eq": true, + "emissions_grid_source": "Meta-Analysis", + "emissions_grid_range": "Mean", + "source_until_2014": "ALL SOURCES", + "ref_source_post_2014": "Conservative Cases", + "pds_source_post_2014": "Conservative Cases", + "ref_base_adoption": { + "World": 0.001, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_basis": "DEFAULT Linear", + "soln_pds_adoption_regional_data": false, + "pds_adoption_final_percentage": { + "World": 1.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_ref_adoption_basis": "Default", + "soln_ref_adoption_regional_data": false, + "pds_adoption_use_ref_years": [ + 2014, + 2015, + 2016, + 2017 + ] +} diff --git a/solution/altcement/ac/PDS1-100p2050-60%_clinkercement_Ratio.json b/solution/altcement/ac/PDS1-100p2050-60%_clinkercement_Ratio.json new file mode 100644 index 000000000..7a959af8b --- /dev/null +++ b/solution/altcement/ac/PDS1-100p2050-60%_clinkercement_Ratio.json @@ -0,0 +1,157 @@ +{ + "name": "PDS1-100p2050-60% clinker/cement Ratio", + "solution_category": "reduction", + "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.268957570755006 + }, + "description": "PDS 1 - Plausible Scenario. Adoption of blended cements (CEM II and CEM V) in year 2 of 90% of total market share, resulting in a total clinker to cement ratio of 0.6. Full adoption of efficient kilns are also included (both from a thermal and electricity perspectives).", + "report_start_year": 2020, + "report_end_year": 2050, + "conv_2014_cost": { + "value": 74790999.4544158, + "statistic": "mean" + }, + "conv_first_cost_efficiency_rate": 0.0, + "conv_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "conv_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "conv_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "conv_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_cost_per_funit": 0.0, + "pds_2014_cost": { + "value": 73863591.0611811, + "statistic": "mean" + }, + "ref_2014_cost": { + "value": 73863591.0611811, + "statistic": "mean" + }, + "soln_first_cost_efficiency_rate": 0.0, + "soln_first_cost_below_conv": true, + "soln_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "soln_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "soln_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "soln_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "soln_fuel_cost_per_funit": 0.0, + "npv_discount_rate": 0.0922, + "conv_annual_energy_used": { + "value": 0.097, + "statistic": "mean" + }, + "soln_energy_efficiency_factor": { + "value": 0.0, + "statistic": "" + }, + "soln_annual_energy_used": { + "value": 0.088, + "statistic": "mean" + }, + "conv_fuel_consumed_per_funit": { + "value": 3519.0, + "statistic": "mean" + }, + "soln_fuel_efficiency_factor": { + "value": 0.220782428874914, + "statistic": "mean" + }, + "conv_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "soln_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "conv_emissions_per_funit": { + "value": 350844.0, + "statistic": "mean" + }, + "soln_emissions_per_funit": { + "value": 304200.0, + "statistic": "mean" + }, + "conv_indirect_co2_per_unit": { + "value": 30025.072, + "statistic": "mean" + }, + "soln_indirect_co2_per_iunit": { + "value": 38993.6, + "statistic": "mean" + }, + "conv_indirect_co2_is_iunits": false, + "ch4_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "ch4_is_co2eq": false, + "n2o_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "n2o_is_co2eq": false, + "co2eq_conversion_source": "AR5 with feedback", + "emissions_use_co2eq": true, + "emissions_grid_source": "Meta-Analysis", + "emissions_grid_range": "Mean", + "source_until_2014": "ALL SOURCES", + "ref_source_post_2014": "Conservative Cases", + "pds_source_post_2014": "Conservative Cases", + "ref_base_adoption": { + "World": 0.001, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_basis": "DEFAULT Linear", + "soln_pds_adoption_regional_data": false, + "pds_adoption_final_percentage": { + "World": 1.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_ref_adoption_basis": "Default", + "soln_ref_adoption_regional_data": false, + "pds_adoption_use_ref_years": [ + 2014, + 2015, + 2016, + 2017 + ] +} diff --git a/solution/altcement/ac/PDS1-21p2050-Availability_Analysis.json b/solution/altcement/ac/PDS1-21p2050-Availability_Analysis.json new file mode 100644 index 000000000..67d0bf6c4 --- /dev/null +++ b/solution/altcement/ac/PDS1-21p2050-Availability_Analysis.json @@ -0,0 +1,153 @@ +{ + "name": "PDS1-21p2050-Availability Analysis", + "solution_category": "reduction", + "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.45 + }, + "description": "This scenario is based on a Fly Ash availability analysis since Fly Ash incorporation in cement is the definition of this solution and that is based on coal burning which has an uncertain future. Fly Ash cement is therefore a transition solution. The availability assumptions are shown in the Custom Adoption sheets. The availability of fly ash depends on coal use for electricity generation which is reduced in each PDS scenario, but all end at zero coal use by 2050, albeit at different rates.", + "report_start_year": 2020, + "report_end_year": 2050, + "conv_2014_cost": { + "value": 76750000.0, + "statistic": "" + }, + "conv_first_cost_efficiency_rate": 0.0, + "conv_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "conv_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "conv_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "conv_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_cost_per_funit": 0.0, + "pds_2014_cost": { + "value": 47986781.25, + "statistic": "" + }, + "ref_2014_cost": { + "value": 47986781.25, + "statistic": "" + }, + "soln_first_cost_efficiency_rate": 0.0, + "soln_first_cost_below_conv": true, + "soln_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "soln_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "soln_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "soln_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "soln_fuel_cost_per_funit": 0.0, + "npv_discount_rate": 0.0922, + "conv_annual_energy_used": { + "value": 0.15726303528681215, + "statistic": "" + }, + "soln_energy_efficiency_factor": { + "value": 0.45, + "xls cell formula": "E192" + }, + "soln_annual_energy_used": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_consumed_per_funit": { + "value": 4558.606257936431, + "statistic": "" + }, + "soln_fuel_efficiency_factor": { + "value": 0.45, + "statistic": "" + }, + "conv_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "soln_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "conv_emissions_per_funit": { + "value": 505606.67, + "statistic": "" + }, + "soln_emissions_per_funit": { + "value": 278083.6685, + "statistic": "" + }, + "conv_indirect_co2_per_unit": { + "value": 0.0, + "statistic": "" + }, + "soln_indirect_co2_per_iunit": { + "value": 36189.00000000001, + "statistic": "" + }, + "conv_indirect_co2_is_iunits": false, + "ch4_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "ch4_is_co2eq": false, + "n2o_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "n2o_is_co2eq": false, + "co2eq_conversion_source": "AR5 with feedback", + "emissions_use_co2eq": true, + "emissions_grid_source": "Meta-Analysis", + "emissions_grid_range": "Mean", + "source_until_2014": "ALL SOURCES", + "ref_source_post_2014": "ALL SOURCES", + "pds_source_post_2014": "ALL SOURCES", + "ref_base_adoption": { + "World": 222.222222222222, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_basis": "Fully Customized PDS", + "soln_pds_adoption_regional_data": false, + "pds_adoption_final_percentage": { + "World": 0.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_custom_name": "Adoption Based on Fly Ash Availability Analysis/ PDS 1", + "soln_ref_adoption_basis": "Custom", + "soln_ref_adoption_custom_name": "REF Custom Adoption Based on Fly Ash Availability Analysis", + "soln_ref_adoption_regional_data": false +} diff --git a/solution/altcement/ac/PDS2-100p2050-046clinkercement-postintjune2020.json b/solution/altcement/ac/PDS2-100p2050-046clinkercement-postintjune2020.json new file mode 100644 index 000000000..b489e6d47 --- /dev/null +++ b/solution/altcement/ac/PDS2-100p2050-046clinkercement-postintjune2020.json @@ -0,0 +1,157 @@ +{ + "name": "PDS2-100p2050-0.46clinker/cement-postintjune2020", + "solution_category": "reduction", + "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.459236352425282 + }, + "description": "updated emissions factors", + "report_start_year": 2020, + "report_end_year": 2050, + "conv_2014_cost": { + "value": 74790999.4544158, + "statistic": "" + }, + "conv_first_cost_efficiency_rate": 0.0, + "conv_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "conv_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "conv_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "conv_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_cost_per_funit": 0.0, + "pds_2014_cost": { + "value": 73863591.0611811, + "statistic": "" + }, + "ref_2014_cost": { + "value": 73863591.0611811, + "statistic": "" + }, + "soln_first_cost_efficiency_rate": 0.0, + "soln_first_cost_below_conv": true, + "soln_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "soln_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "soln_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "soln_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "soln_fuel_cost_per_funit": 0.0, + "npv_discount_rate": 0.0922, + "conv_annual_energy_used": { + "value": 0.097, + "statistic": "" + }, + "soln_energy_efficiency_factor": { + "value": 0.0, + "statistic": "" + }, + "soln_annual_energy_used": { + "value": 0.088, + "statistic": "" + }, + "conv_fuel_consumed_per_funit": { + "value": 3519.0, + "statistic": "" + }, + "soln_fuel_efficiency_factor": { + "value": 0.40359160815138, + "statistic": "" + }, + "conv_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "soln_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "conv_emissions_per_funit": { + "value": 350844.0, + "statistic": "" + }, + "soln_emissions_per_funit": { + "value": 232832.830679618, + "statistic": "" + }, + "conv_indirect_co2_per_unit": { + "value": 30025.072, + "statistic": "" + }, + "soln_indirect_co2_per_iunit": { + "value": 52715.8034201738, + "statistic": "" + }, + "conv_indirect_co2_is_iunits": false, + "ch4_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "ch4_is_co2eq": false, + "n2o_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "n2o_is_co2eq": false, + "co2eq_conversion_source": "AR5 with feedback", + "emissions_use_co2eq": true, + "emissions_grid_source": "Meta-Analysis", + "emissions_grid_range": "Mean", + "source_until_2014": "ALL SOURCES", + "ref_source_post_2014": "Conservative Cases", + "pds_source_post_2014": "Conservative Cases", + "ref_base_adoption": { + "World": 0.001, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_basis": "DEFAULT Linear", + "soln_pds_adoption_regional_data": false, + "pds_adoption_final_percentage": { + "World": 1.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_ref_adoption_basis": "Default", + "soln_ref_adoption_regional_data": false, + "pds_adoption_use_ref_years": [ + 2014, + 2015, + 2016, + 2017 + ] +} diff --git a/solution/altcement/ac/PDS2-100p2050-46%_clinkercement_ratio.json b/solution/altcement/ac/PDS2-100p2050-46%_clinkercement_ratio.json new file mode 100644 index 000000000..e68a17221 --- /dev/null +++ b/solution/altcement/ac/PDS2-100p2050-46%_clinkercement_ratio.json @@ -0,0 +1,157 @@ +{ + "name": "PDS2-100p2050-46% clinker/cement ratio", + "solution_category": "reduction", + "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.459236352425282 + }, + "description": "PDS 2 - Drawdown Scenario. Adoption of blended cements (CEM II and CEM V) in Year 2 of 90% of total market share, resulting in a total clinker to cement ratio of 0.46. Full adoption of efficient kilns are also included (both from thermal and electricity consumption perspective)", + "report_start_year": 2020, + "report_end_year": 2050, + "conv_2014_cost": { + "value": 74790999.4544158, + "statistic": "mean" + }, + "conv_first_cost_efficiency_rate": 0.0, + "conv_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "conv_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "conv_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "conv_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_cost_per_funit": 0.0, + "pds_2014_cost": { + "value": 73863591.0611811, + "statistic": "mean" + }, + "ref_2014_cost": { + "value": 73863591.0611811, + "statistic": "mean" + }, + "soln_first_cost_efficiency_rate": 0.0, + "soln_first_cost_below_conv": true, + "soln_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "soln_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "soln_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "soln_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "soln_fuel_cost_per_funit": 0.0, + "npv_discount_rate": 0.0922, + "conv_annual_energy_used": { + "value": 0.097, + "statistic": "mean" + }, + "soln_energy_efficiency_factor": { + "value": 0.0, + "statistic": "" + }, + "soln_annual_energy_used": { + "value": 0.088, + "statistic": "mean" + }, + "conv_fuel_consumed_per_funit": { + "value": 3519.0, + "statistic": "mean" + }, + "soln_fuel_efficiency_factor": { + "value": 0.40359160815138, + "statistic": "mean" + }, + "conv_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "soln_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "conv_emissions_per_funit": { + "value": 350844.0, + "statistic": "mean" + }, + "soln_emissions_per_funit": { + "value": 232832.830679618, + "statistic": "mean" + }, + "conv_indirect_co2_per_unit": { + "value": 30025.072, + "statistic": "mean" + }, + "soln_indirect_co2_per_iunit": { + "value": 52715.8034201738, + "statistic": "mean" + }, + "conv_indirect_co2_is_iunits": false, + "ch4_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "ch4_is_co2eq": false, + "n2o_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "n2o_is_co2eq": false, + "co2eq_conversion_source": "AR5 with feedback", + "emissions_use_co2eq": true, + "emissions_grid_source": "Meta-Analysis", + "emissions_grid_range": "Mean", + "source_until_2014": "ALL SOURCES", + "ref_source_post_2014": "Conservative Cases", + "pds_source_post_2014": "Conservative Cases", + "ref_base_adoption": { + "World": 0.001, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_basis": "DEFAULT Linear", + "soln_pds_adoption_regional_data": false, + "pds_adoption_final_percentage": { + "World": 1.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_ref_adoption_basis": "Default", + "soln_ref_adoption_regional_data": false, + "pds_adoption_use_ref_years": [ + 2014, + 2015, + 2016, + 2017 + ] +} diff --git a/solution/altcement/ac/PDS2-20p2050-Availability_Analysis.json b/solution/altcement/ac/PDS2-20p2050-Availability_Analysis.json new file mode 100644 index 000000000..5d6b57b35 --- /dev/null +++ b/solution/altcement/ac/PDS2-20p2050-Availability_Analysis.json @@ -0,0 +1,153 @@ +{ + "name": "PDS2-20p2050-Availability Analysis", + "solution_category": "reduction", + "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.45 + }, + "description": "This scenario is based on a Fly Ash availability analysis since Fly Ash incorporation in cement is the definition of this solution and that is based on coal burning which has an uncertain future. Fly Ash cement is therefore a transition solution. The availability assumptions are shown in the Custom Adoption sheets. The availability of fly ash depends on coal use for electricity generation which is reduced in each PDS scenario, but all end at zero coal use by 2050, albeit at different rates.", + "report_start_year": 2020, + "report_end_year": 2050, + "conv_2014_cost": { + "value": 76750000.0, + "statistic": "" + }, + "conv_first_cost_efficiency_rate": 0.0, + "conv_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "conv_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "conv_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "conv_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_cost_per_funit": 0.0, + "pds_2014_cost": { + "value": 47986781.25, + "statistic": "" + }, + "ref_2014_cost": { + "value": 47986781.25, + "statistic": "" + }, + "soln_first_cost_efficiency_rate": 0.0, + "soln_first_cost_below_conv": true, + "soln_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "soln_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "soln_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "soln_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "soln_fuel_cost_per_funit": 0.0, + "npv_discount_rate": 0.0922, + "conv_annual_energy_used": { + "value": 0.15726303528681215, + "statistic": "" + }, + "soln_energy_efficiency_factor": { + "value": 0.45, + "xls cell formula": "E192" + }, + "soln_annual_energy_used": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_consumed_per_funit": { + "value": 4558.606257936431, + "statistic": "" + }, + "soln_fuel_efficiency_factor": { + "value": 0.45, + "statistic": "" + }, + "conv_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "soln_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "conv_emissions_per_funit": { + "value": 505606.67, + "statistic": "" + }, + "soln_emissions_per_funit": { + "value": 278083.6685, + "statistic": "" + }, + "conv_indirect_co2_per_unit": { + "value": 0.0, + "statistic": "" + }, + "soln_indirect_co2_per_iunit": { + "value": 36189.00000000001, + "statistic": "" + }, + "conv_indirect_co2_is_iunits": false, + "ch4_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "ch4_is_co2eq": false, + "n2o_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "n2o_is_co2eq": false, + "co2eq_conversion_source": "AR5 with feedback", + "emissions_use_co2eq": true, + "emissions_grid_source": "Meta-Analysis", + "emissions_grid_range": "Mean", + "source_until_2014": "ALL SOURCES", + "ref_source_post_2014": "ALL SOURCES", + "pds_source_post_2014": "ALL SOURCES", + "ref_base_adoption": { + "World": 222.222222222222, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_basis": "Fully Customized PDS", + "soln_pds_adoption_regional_data": false, + "pds_adoption_final_percentage": { + "World": 0.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_custom_name": "Adoption Based on Fly Ash Availability Analysis/ PDS 2", + "soln_ref_adoption_basis": "Custom", + "soln_ref_adoption_custom_name": "REF Custom Adoption Based on Fly Ash Availability Analysis", + "soln_ref_adoption_regional_data": false +} diff --git a/solution/altcement/ac/PDS3-100p2050-27%_clinkercement_ratio.json b/solution/altcement/ac/PDS3-100p2050-27%_clinkercement_ratio.json new file mode 100644 index 000000000..4922253f5 --- /dev/null +++ b/solution/altcement/ac/PDS3-100p2050-27%_clinkercement_ratio.json @@ -0,0 +1,157 @@ +{ + "name": "PDS3-100p2050-27% clinker/cement ratio", + "solution_category": "reduction", + "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.268957570755006 + }, + "description": "PDS 3 - Optimum Scenario. Adoption of blended cements (CEM II and CEM V) in year 2 of 90% of the total market share, resulting in a total clinker to cement ratio fo 0.27. Full adoption of efficient kilns from both a thermal and electricity perspective.", + "report_start_year": 2020, + "report_end_year": 2050, + "conv_2014_cost": { + "value": 74790999.4544158, + "statistic": "mean" + }, + "conv_first_cost_efficiency_rate": 0.0, + "conv_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "conv_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "conv_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "conv_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_cost_per_funit": 0.0, + "pds_2014_cost": { + "value": 73863591.0611811, + "statistic": "mean" + }, + "ref_2014_cost": { + "value": 73863591.0611811, + "statistic": "mean" + }, + "soln_first_cost_efficiency_rate": 0.0, + "soln_first_cost_below_conv": true, + "soln_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "soln_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "soln_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "soln_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "soln_fuel_cost_per_funit": 0.0, + "npv_discount_rate": 0.0922, + "conv_annual_energy_used": { + "value": 0.097, + "statistic": "mean" + }, + "soln_energy_efficiency_factor": { + "value": 0.0, + "statistic": "" + }, + "soln_annual_energy_used": { + "value": 0.088, + "statistic": "mean" + }, + "conv_fuel_consumed_per_funit": { + "value": 3519.0, + "statistic": "mean" + }, + "soln_fuel_efficiency_factor": { + "value": 0.650705891634302, + "statistic": "mean" + }, + "conv_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "soln_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "conv_emissions_per_funit": { + "value": 350844.0, + "statistic": "mean" + }, + "soln_emissions_per_funit": { + "value": 136361.488372788, + "statistic": "mean" + }, + "conv_indirect_co2_per_unit": { + "value": 30025.072, + "statistic": "mean" + }, + "soln_indirect_co2_per_iunit": { + "value": 71264.940172519, + "statistic": "mean" + }, + "conv_indirect_co2_is_iunits": false, + "ch4_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "ch4_is_co2eq": false, + "n2o_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "n2o_is_co2eq": false, + "co2eq_conversion_source": "AR5 with feedback", + "emissions_use_co2eq": true, + "emissions_grid_source": "Meta-Analysis", + "emissions_grid_range": "Mean", + "source_until_2014": "ALL SOURCES", + "ref_source_post_2014": "Conservative Cases", + "pds_source_post_2014": "Conservative Cases", + "ref_base_adoption": { + "World": 0.001, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_basis": "DEFAULT Linear", + "soln_pds_adoption_regional_data": false, + "pds_adoption_final_percentage": { + "World": 1.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_ref_adoption_basis": "Default", + "soln_ref_adoption_regional_data": false, + "pds_adoption_use_ref_years": [ + 2014, + 2015, + 2016, + 2017 + ] +} diff --git a/solution/altcement/ac/PDS3-20p2050-Availability_Analysis.json b/solution/altcement/ac/PDS3-20p2050-Availability_Analysis.json new file mode 100644 index 000000000..cf75e1741 --- /dev/null +++ b/solution/altcement/ac/PDS3-20p2050-Availability_Analysis.json @@ -0,0 +1,153 @@ +{ + "name": "PDS3-20p2050-Availability Analysis", + "solution_category": "reduction", + "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.45 + }, + "description": "This scenario is based on a Fly Ash availability analysis since Fly Ash incorporation in cement is the definition of this solution and that is based on coal burning which has an uncertain future. Fly Ash cement is therefore a transition solution. The availability assumptions are shown in the Custom Adoption sheets. The availability of fly ash depends on coal use for electricity generation which is reduced in each PDS scenario, but all end at zero coal use by 2050, albeit at different rates.", + "report_start_year": 2020, + "report_end_year": 2050, + "conv_2014_cost": { + "value": 76750000.0, + "statistic": "" + }, + "conv_first_cost_efficiency_rate": 0.0, + "conv_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "conv_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "conv_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "conv_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_cost_per_funit": 0.0, + "pds_2014_cost": { + "value": 47986781.25, + "statistic": "" + }, + "ref_2014_cost": { + "value": 47986781.25, + "statistic": "" + }, + "soln_first_cost_efficiency_rate": 0.0, + "soln_first_cost_below_conv": true, + "soln_lifetime_capacity": { + "value": 30.0, + "statistic": "" + }, + "soln_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "soln_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "soln_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "soln_fuel_cost_per_funit": 0.0, + "npv_discount_rate": 0.0922, + "conv_annual_energy_used": { + "value": 0.15726303528681215, + "statistic": "" + }, + "soln_energy_efficiency_factor": { + "value": 0.45, + "xls cell formula": "E192" + }, + "soln_annual_energy_used": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_consumed_per_funit": { + "value": 4558.606257936431, + "statistic": "" + }, + "soln_fuel_efficiency_factor": { + "value": 0.45, + "statistic": "" + }, + "conv_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "soln_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "conv_emissions_per_funit": { + "value": 505606.67, + "statistic": "" + }, + "soln_emissions_per_funit": { + "value": 278083.6685, + "statistic": "" + }, + "conv_indirect_co2_per_unit": { + "value": 0.0, + "statistic": "" + }, + "soln_indirect_co2_per_iunit": { + "value": 36189.00000000001, + "statistic": "" + }, + "conv_indirect_co2_is_iunits": false, + "ch4_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "ch4_is_co2eq": false, + "n2o_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "n2o_is_co2eq": false, + "co2eq_conversion_source": "AR5 with feedback", + "emissions_use_co2eq": true, + "emissions_grid_source": "Meta-Analysis", + "emissions_grid_range": "Mean", + "source_until_2014": "ALL SOURCES", + "ref_source_post_2014": "ALL SOURCES", + "pds_source_post_2014": "ALL SOURCES", + "ref_base_adoption": { + "World": 222.222222222222, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_basis": "Fully Customized PDS", + "soln_pds_adoption_regional_data": false, + "pds_adoption_final_percentage": { + "World": 0.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_custom_name": "Adoption Based on Fly Ash Availability Analysis/ PDS 3", + "soln_ref_adoption_basis": "Custom", + "soln_ref_adoption_custom_name": "REF Custom Adoption Based on Fly Ash Availability Analysis", + "soln_ref_adoption_regional_data": false +} diff --git a/solution/altcement/ac/PDS_1_-_061_clinker_to_cement_ratio_-_2050.json b/solution/altcement/ac/PDS_1_-_061_clinker_to_cement_ratio_-_2050.json new file mode 100644 index 000000000..59e094bd5 --- /dev/null +++ b/solution/altcement/ac/PDS_1_-_061_clinker_to_cement_ratio_-_2050.json @@ -0,0 +1,154 @@ +{ + "name": "PDS 1 - 0.61 clinker to cement ratio - 2050", + "solution_category": "reduction", + "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.6 + }, + "description": "PDS 1 - Plausible Scenario. Adoption of blended cements (CEM II and CEM V) in year 2 of 90% of total market share, resulting in a total clinker to cement ratio of 0.61. Full adoption of efficient kilns are also included (both from a thermal and electricity perspectives).", + "report_start_year": 2020, + "report_end_year": 2050, + "conv_2014_cost": { + "value": 74790999.4544158, + "statistic": "mean" + }, + "conv_first_cost_efficiency_rate": 0.0, + "conv_lifetime_capacity": { + "value": 60.0, + "statistic": "" + }, + "conv_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "conv_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "conv_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_cost_per_funit": 0.0, + "pds_2014_cost": { + "value": 73863591.0611811, + "statistic": "mean" + }, + "ref_2014_cost": { + "value": 73863591.0611811, + "statistic": "mean" + }, + "soln_first_cost_efficiency_rate": 0.0, + "soln_first_cost_below_conv": true, + "soln_lifetime_capacity": { + "value": 60.0, + "statistic": "" + }, + "soln_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "soln_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "soln_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "soln_fuel_cost_per_funit": 0.0, + "npv_discount_rate": 0.0922, + "conv_annual_energy_used": { + "value": 0.097, + "statistic": "mean" + }, + "soln_energy_efficiency_factor": { + "value": 0.0, + "statistic": "" + }, + "soln_annual_energy_used": { + "value": 0.088, + "statistic": "mean" + }, + "conv_fuel_consumed_per_funit": { + "value": 3519.0, + "statistic": "mean" + }, + "soln_fuel_efficiency_factor": { + "value": 0.101302401302401, + "statistic": "mean" + }, + "conv_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "soln_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "conv_emissions_per_funit": { + "value": 350844.0, + "statistic": "mean" + }, + "soln_emissions_per_funit": { + "value": 304200.0, + "statistic": "mean" + }, + "conv_indirect_co2_per_unit": { + "value": 30025.072, + "statistic": "mean" + }, + "soln_indirect_co2_per_iunit": { + "value": 38993.6, + "statistic": "mean" + }, + "conv_indirect_co2_is_iunits": false, + "ch4_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "ch4_is_co2eq": false, + "n2o_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "n2o_is_co2eq": false, + "co2eq_conversion_source": "AR5 with feedback", + "emissions_use_co2eq": true, + "emissions_grid_source": "Meta-Analysis", + "emissions_grid_range": "Mean", + "source_until_2014": "ALL SOURCES", + "ref_source_post_2014": "Conservative Cases", + "pds_source_post_2014": "Conservative Cases", + "ref_base_adoption": { + "World": 0.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_basis": "DEFAULT Linear", + "soln_pds_adoption_regional_data": false, + "pds_adoption_final_percentage": { + "World": 1.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_ref_adoption_basis": "Default", + "soln_ref_adoption_regional_data": false, + "pds_adoption_use_ref_years": [ + 2014 + ] +} diff --git a/solution/altcement/ac/PDS_2_-_046_clinker_to_cement_ratio_-_2050.json b/solution/altcement/ac/PDS_2_-_046_clinker_to_cement_ratio_-_2050.json new file mode 100644 index 000000000..3f550d26d --- /dev/null +++ b/solution/altcement/ac/PDS_2_-_046_clinker_to_cement_ratio_-_2050.json @@ -0,0 +1,154 @@ +{ + "name": "PDS 2 - 0.46 clinker to cement ratio - 2050", + "solution_category": "reduction", + "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.459236352425282 + }, + "description": "PDS 2 - Drawdown Scenario. Adoption of blended cements (CEM II and CEM V) in Year 2 of 90% of total market share, resulting in a total clinker to cement ratio of 0.46. Full adoption of efficient kilns are also included (both from thermal and electricity consumption perspective)", + "report_start_year": 2020, + "report_end_year": 2050, + "conv_2014_cost": { + "value": 74790999.4544158, + "statistic": "mean" + }, + "conv_first_cost_efficiency_rate": 0.0, + "conv_lifetime_capacity": { + "value": 60.0, + "statistic": "" + }, + "conv_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "conv_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "conv_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_cost_per_funit": 0.0, + "pds_2014_cost": { + "value": 73863591.0611811, + "statistic": "mean" + }, + "ref_2014_cost": { + "value": 73863591.0611811, + "statistic": "mean" + }, + "soln_first_cost_efficiency_rate": 0.0, + "soln_first_cost_below_conv": true, + "soln_lifetime_capacity": { + "value": 60.0, + "statistic": "" + }, + "soln_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "soln_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "soln_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "soln_fuel_cost_per_funit": 0.0, + "npv_discount_rate": 0.0922, + "conv_annual_energy_used": { + "value": 0.097, + "statistic": "mean" + }, + "soln_energy_efficiency_factor": { + "value": 0.0, + "statistic": "" + }, + "soln_annual_energy_used": { + "value": 0.088, + "statistic": "mean" + }, + "conv_fuel_consumed_per_funit": { + "value": 3519.0, + "statistic": "mean" + }, + "soln_fuel_efficiency_factor": { + "value": 0.101302401302401, + "statistic": "mean" + }, + "conv_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "soln_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "conv_emissions_per_funit": { + "value": 350844.0, + "statistic": "mean" + }, + "soln_emissions_per_funit": { + "value": 232832.830679618, + "statistic": "mean" + }, + "conv_indirect_co2_per_unit": { + "value": 30025.072, + "statistic": "mean" + }, + "soln_indirect_co2_per_iunit": { + "value": 52715.8034201738, + "statistic": "mean" + }, + "conv_indirect_co2_is_iunits": false, + "ch4_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "ch4_is_co2eq": false, + "n2o_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "n2o_is_co2eq": false, + "co2eq_conversion_source": "AR5 with feedback", + "emissions_use_co2eq": true, + "emissions_grid_source": "Meta-Analysis", + "emissions_grid_range": "Mean", + "source_until_2014": "ALL SOURCES", + "ref_source_post_2014": "Conservative Cases", + "pds_source_post_2014": "Conservative Cases", + "ref_base_adoption": { + "World": 0.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_basis": "DEFAULT Linear", + "soln_pds_adoption_regional_data": false, + "pds_adoption_final_percentage": { + "World": 1.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_ref_adoption_basis": "Default", + "soln_ref_adoption_regional_data": false, + "pds_adoption_use_ref_years": [ + 2014 + ] +} diff --git a/solution/altcement/ac/PDS_3_-_027_clinker_to_cement_ratio_-_2050.json b/solution/altcement/ac/PDS_3_-_027_clinker_to_cement_ratio_-_2050.json new file mode 100644 index 000000000..5d34cd91f --- /dev/null +++ b/solution/altcement/ac/PDS_3_-_027_clinker_to_cement_ratio_-_2050.json @@ -0,0 +1,154 @@ +{ + "name": "PDS 3 - 0.27 clinker to cement ratio - 2050", + "solution_category": "reduction", + "vmas": "VMAs", + "vma_values": { + "Clinker to Cement Ratio in Year 2": 0.268957570755006 + }, + "description": "PDS 3 - Optimum Scenario. Adoption of blended cements (CEM II and CEM V) in year 2 of 90% of the total market share, resulting in a total clinker to cement ratio fo 0.27. Full adoption of efficient kilns from both a thermal and electricity perspective.", + "report_start_year": 2020, + "report_end_year": 2050, + "conv_2014_cost": { + "value": 74790999.4544158, + "statistic": "mean" + }, + "conv_first_cost_efficiency_rate": 0.0, + "conv_lifetime_capacity": { + "value": 60.0, + "statistic": "" + }, + "conv_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "conv_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "conv_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "conv_fuel_cost_per_funit": 0.0, + "pds_2014_cost": { + "value": 73863591.0611811, + "statistic": "mean" + }, + "ref_2014_cost": { + "value": 73863591.0611811, + "statistic": "mean" + }, + "soln_first_cost_efficiency_rate": 0.0, + "soln_first_cost_below_conv": true, + "soln_lifetime_capacity": { + "value": 60.0, + "statistic": "" + }, + "soln_avg_annual_use": { + "value": 1.0, + "statistic": "" + }, + "soln_var_oper_cost_per_funit": { + "value": 0.0, + "statistic": "" + }, + "soln_fixed_oper_cost_per_iunit": { + "value": 0.0, + "statistic": "" + }, + "soln_fuel_cost_per_funit": 0.0, + "npv_discount_rate": 0.0922, + "conv_annual_energy_used": { + "value": 0.097, + "statistic": "mean" + }, + "soln_energy_efficiency_factor": { + "value": 0.0, + "statistic": "" + }, + "soln_annual_energy_used": { + "value": 0.088, + "statistic": "mean" + }, + "conv_fuel_consumed_per_funit": { + "value": 3519.0, + "statistic": "mean" + }, + "soln_fuel_efficiency_factor": { + "value": 0.101302401302401, + "statistic": "mean" + }, + "conv_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "soln_fuel_emissions_factor": { + "value": 95.3, + "statistic": "" + }, + "conv_emissions_per_funit": { + "value": 350844.0, + "statistic": "mean" + }, + "soln_emissions_per_funit": { + "value": 136361.488372788, + "statistic": "mean" + }, + "conv_indirect_co2_per_unit": { + "value": 30025.072, + "statistic": "mean" + }, + "soln_indirect_co2_per_iunit": { + "value": 71264.940172519, + "statistic": "mean" + }, + "conv_indirect_co2_is_iunits": false, + "ch4_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "ch4_is_co2eq": false, + "n2o_co2_per_funit": { + "value": 0.0, + "statistic": "" + }, + "n2o_is_co2eq": false, + "co2eq_conversion_source": "AR5 with feedback", + "emissions_use_co2eq": true, + "emissions_grid_source": "Meta-Analysis", + "emissions_grid_range": "Mean", + "source_until_2014": "ALL SOURCES", + "ref_source_post_2014": "Conservative Cases", + "pds_source_post_2014": "Conservative Cases", + "ref_base_adoption": { + "World": 0.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_pds_adoption_basis": "DEFAULT Linear", + "soln_pds_adoption_regional_data": false, + "pds_adoption_final_percentage": { + "World": 1.0, + "OECD90": 0.0, + "Eastern Europe": 0.0, + "Asia (Sans Japan)": 0.0, + "Middle East and Africa": 0.0, + "Latin America": 0.0, + "China": 0.0, + "India": 0.0, + "EU": 0.0, + "USA": 0.0 + }, + "soln_ref_adoption_basis": "Default", + "soln_ref_adoption_regional_data": false, + "pds_adoption_use_ref_years": [ + 2014 + ] +} diff --git a/solution/altcement/ca_pds_data/custom_pds_ad_Adoption_based_on_Fly_Ash_Availability_Analysis_PDS_1.csv b/solution/altcement/ca_pds_data/custom_pds_ad_Adoption_based_on_Fly_Ash_Availability_Analysis_PDS_1.csv deleted file mode 100644 index 95bcd8d48..000000000 --- a/solution/altcement/ca_pds_data/custom_pds_ad_Adoption_based_on_Fly_Ash_Availability_Analysis_PDS_1.csv +++ /dev/null @@ -1,50 +0,0 @@ -Year,World,OECD90,Eastern Europe,Asia (Sans Japan),Middle East and Africa,Latin America,China,India,EU,USA -2012,,,,,,,,,, -2013,,,,,,,,,, -2014,,,,,,,,,, -2015,205.4758688265636,42.11699638746252,12.42443113217078,163.8007135327816,3.206396782645229,1.1546541478275518,170.81114031267995,41.66504068404839,13.602437768717738,16.646778919053553 -2016,619.5312400142516,117.97790118165148,27.112989964341736,412.84926591225434,33.77584366076684,17.4323362933865,325.6129676353397,65.17530175181759,13.669528537771514,31.277073110884857 -2017,1036.3132625592384,194.5997172330718,42.25448281392832,633.3890246480456,46.44003485133595,17.88240434488012,330.58958707218517,92.2017341671462,13.8783524763163,46.823305929093614 -2018,1368.892715892798,242.60922163972094,57.75309441177246,609.4242819057773,46.986308696339655,18.346698023161753,340.50458554785604,93.04745292954948,14.209509633945926,63.16460112595715 -2019,1391.9734646511936,237.41940615513593,73.53446415313071,595.5330689053006,47.69390154744844,18.82520268959779,354.23637710303905,91.60422220373601,14.64648199659084,63.11900253250553 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-2030,1496.6049478888885,214.20259342702747,99.81589397391835,574.1881021899602,54.47308541992705,22.529619235287836,417.0645730736512,109.00982662110097,17.484046939379276,74.60048478420181 -2031,1476.650745190342,210.3888565487188,97.54936152744847,563.8372086944113,54.754525487016835,22.681044325464303,402.3213763469107,109.58911777782228,17.311451239811884,74.0677163928066 -2032,1453.252762316256,207.04593694065417,95.55206224598454,554.7131673804623,55.077391870494424,22.830545485825933,388.1084028063453,110.35257790292323,17.159979626706694,73.65383480206849 -2033,1429.2802769500624,204.13158633392615,93.7911632581773,546.676188015722,55.44036795178949,22.978116031311753,374.36345241152213,111.28126489067685,17.02794687061667,73.34465584463861 -2034,1404.4314779164235,201.6099099011188,92.23954029249508,539.6099415511071,55.84228690332913,23.123749912228472,361.0349211580767,112.35926141591582,16.913909690171504,73.12843308367583 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-2055,846.7589119293795,191.65928323340157,80.92764795729043,492.5513487890498,69.33604269956383,25.896817168357813,257.901348657152,150.68706101102939,16.615377451327415,77.85033663938309 -2056,827.2719883479758,191.54678323340158,80.52764795729044,490.9763487890498,70.02354269956383,26.026817168357816,255.90134865715203,152.64206101102937,16.615377451327415,78.15033663938307 -2057,808.5214959001235,191.43428323340157,80.12764795729043,489.4013487890498,70.71104269956383,26.156817168357815,253.90134865715206,154.59706101102938,16.615377451327415,78.45033663938308 -2058,790.4612389254725,191.3217832334016,79.72764795729042,487.82634878904975,71.39854269956383,26.286817168357814,251.90134865715206,156.5520610110294,16.615377451327415,78.75033663938308 -2059,770.5202370811417,191.2092832334016,79.32764795729044,486.25134878904987,72.08604269956383,26.416817168357813,249.90134865715203,158.50706101102938,16.615377451327415,79.05033663938308 -2060,754.7258958594863,191.09678323340157,78.92764795729042,484.6763487890498,72.77354269956383,26.546817168357816,247.90134865715203,160.4620610110294,16.615377451327415,79.35033663938309 diff --git a/solution/altcement/ca_pds_data/custom_pds_ad_Adoption_based_on_Fly_Ash_Availability_Analysis_PDS_2.csv b/solution/altcement/ca_pds_data/custom_pds_ad_Adoption_based_on_Fly_Ash_Availability_Analysis_PDS_2.csv deleted file mode 100644 index c682bc729..000000000 --- a/solution/altcement/ca_pds_data/custom_pds_ad_Adoption_based_on_Fly_Ash_Availability_Analysis_PDS_2.csv +++ /dev/null @@ -1,50 +0,0 @@ -Year,World,OECD90,Eastern Europe,Asia (Sans Japan),Middle East and Africa,Latin America,China,India,EU,USA -2012,,,,,,,,,, -2013,,,,,,,,,, -2014,,,,,,,,,, -2015,205.4758688265636,,,,,,,,, -2016,615.886276036275,,,,,,,,, -2017,1032.2668156086304,,,,,,,,, -2018,1333.1746890696577,,,,,,,,, -2019,1364.1148859725174,,,,,,,,, -2020,1392.3664353473264,,,,,,,,, -2021,1418.143539514548,,,,,,,,, -2022,1442.745147499564,,,,,,,,, -2023,1466.1279973675653,,,,,,,,, -2024,1488.5567358888027,,,,,,,,, -2025,1510.3344510174015,,,,,,,,, -2026,1484.4632817037625,,,,,,,,, -2027,1458.066164685774,,,,,,,,, -2028,1431.1975890404499,,,,,,,,, -2029,1404.0311949516124,,,,,,,,, -2030,1375.8670021003702,,,,,,,,, -2031,1349.7596826306383,,,,,,,,, -2032,1322.8191826588693,,,,,,,,, -2033,1296.1066280594184,,,,,,,,, -2034,1269.7177457076302,,,,,,,,, -2035,1242.649346218113,,,,,,,,, -2036,1218.2476497751484,,,,,,,,, -2037,1193.1518288313528,,,,,,,,, -2038,1168.5454440920146,,,,,,,,, -2039,1144.426180471864,,,,,,,,, -2040,1122.4854852807614,,,,,,,,, -2041,1097.5062188818838,,,,,,,,, -2042,1074.6470950917528,,,,,,,,, -2043,1052.0141933998063,,,,,,,,, -2044,1029.499977610421,,,,,,,,, -2045,1007.886446772224,,,,,,,,, -2046,988.1301105172802,,,,,,,,, -2047,969.9570427302226,,,,,,,,, -2048,952.2914719047196,,,,,,,,, -2049,935.0024621651937,,,,,,,,, -2050,916.8437271062032,,,,,,,,, -2051,901.0583372114426,,,,,,,,, -2052,884.4089827203472,,,,,,,,, -2053,867.8332470733044,,,,,,,,, -2054,851.3437816947035,,,,,,,,, -2055,834.9520002385433,,,,,,,,, -2056,818.6671228836123,,,,,,,,, -2057,802.4961540867506,,,,,,,,, -2058,786.4454594230948,,,,,,,,, -2059,770.5202370811417,,,,,,,,, -2060,754.7258958594863,,,,,,,,, diff --git a/solution/altcement/ca_pds_data/custom_pds_ad_Adoption_based_on_Fly_Ash_Availability_Analysis_PDS_3.csv b/solution/altcement/ca_pds_data/custom_pds_ad_Adoption_based_on_Fly_Ash_Availability_Analysis_PDS_3.csv deleted file mode 100644 index a82e69fc2..000000000 --- a/solution/altcement/ca_pds_data/custom_pds_ad_Adoption_based_on_Fly_Ash_Availability_Analysis_PDS_3.csv +++ /dev/null @@ -1,50 +0,0 @@ -Year,World,OECD90,Eastern Europe,Asia (Sans Japan),Middle East and Africa,Latin America,China,India,EU,USA -2012,,,,,,,,,, -2013,,,,,,,,,, -2014,,,,,,,,,, -2015,205.4758688265636,,,,,,,,, -2016,615.6261443552502,,,,,,,,, -2017,1032.0283557957946,,,,,,,,, -2018,1330.8750785328943,,,,,,,,, -2019,1361.19934327044,,,,,,,,, -2020,1389.4046849918059,,,,,,,,, -2021,1414.7179868907117,,,,,,,,, -2022,1438.6567542539187,,,,,,,,, -2023,1460.9987519332306,,,,,,,,, -2024,1484.3781994637875,,,,,,,,, -2025,1506.5027165658619,,,,,,,,, -2026,1480.526443559713,,,,,,,,, -2027,1453.4735640103702,,,,,,,,, -2028,1425.4446582381247,,,,,,,,, -2029,1396.811611036988,,,,,,,,, -2030,1370.0158873834796,,,,,,,,, -2031,1345.8795236562241,,,,,,,,, -2032,1320.6252820977863,,,,,,,,, -2033,1295.3300151580133,,,,,,,,, -2034,1270.1079735321205,,,,,,,,, -2035,1243.976408629789,,,,,,,,, -2036,1220.2696367582187,,,,,,,,, -2037,1195.6798721945117,,,,,,,,, -2038,1171.4153192741287,,,,,,,,, -2039,1147.4911163167874,,,,,,,,, -2040,1125.6247443315717,,,,,,,,, -2041,1100.6017520871937,,,,,,,,, -2042,1077.6092635506457,,,,,,,,, -2043,1054.7643731954086,,,,,,,,, -2044,1031.976692133753,,,,,,,,, -2045,1010.0405014740146,,,,,,,,, -2046,989.940067629583,,,,,,,,, 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-2015,222.7031919828877,42.11699638746252,12.42443113217078,163.8007135327816,3.206396782645229,1.1546541478275518,170.81114031267995,41.66504068404839,13.602437768717738,16.646778919053553 -2016,609.1483370124009,117.97790118165148,27.112989964341736,412.84926591225434,33.77584366076684,17.4323362933865,325.6129676353397,65.17530175181759,13.669528537771514,31.277073110884857 -2017,934.5656638912618,194.5997172330718,42.25448281392832,633.3890246480456,46.44003485133595,17.88240434488012,330.58958707218517,92.2017341671462,13.8783524763163,46.823305929093614 -2018,975.1196046767722,242.60922163972094,57.75309441177246,609.4242819057773,46.986308696339655,18.346698023161753,340.50458554785604,93.04745292954948,14.209509633945926,63.16460112595715 -2019,973.0060434506134,237.41940615513593,73.53446415313071,595.5330689053006,47.69390154744844,18.82520268959779,354.23637710303905,91.60422220373601,14.64648199659084,63.11900253250553 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0dd1e84c6..000000000 --- a/solution/altcement/ca_ref_data/custom_ref_ad_Drawdown_Book_Edition_1_Scenario_REF_Adoption.csv +++ /dev/null @@ -1,50 +0,0 @@ -Year,World,OECD90,Eastern Europe,Asia (Sans Japan),Middle East and Africa,Latin America,China,India,EU,USA -2012,,,,,,,,,, -2013,,,,,,,,,, -2014,,,,,,,,,, -2015,222.7031919828877,42.11699638746252,12.42443113217078,163.8007135327816,3.206396782645229,1.1546541478275518,170.81114031267998,41.66504068404839,36.77673206471707,16.646778919053553 -2016,227.634005076797,44.26652309197819,12.504591721179082,166.16672383936623,3.394742904766538,1.3014235195069652,171.83094608373196,43.077331248272124,38.795366024713765,17.800955590774596 -2017,232.5425926395404,46.43886172519564,12.582166503153063,168.47459500380185,3.5864830132764998,1.460486394113372,172.8173829964349,44.481333155623226,40.842899231573654,18.987685963492904 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-2048,307.42521584258833,82.75170918361587,13.532377815664848,198.21753065398593,6.9623884794536215,5.961209709868015,185.07588072693073,65.4167917432004,75.96799187787909,41.44025908696208 -2049,307.42521584258833,82.75170918361587,13.532377815664848,198.21753065398593,6.9623884794536215,5.961209709868015,185.07588072693073,65.4167917432004,75.96799187787909,41.44025908696208 -2050,307.42521584258833,82.75170918361587,13.532377815664848,198.21753065398593,6.9623884794536215,5.961209709868015,185.07588072693073,65.4167917432004,75.96799187787909,41.44025908696208 -2051,,,,,,,,,, -2052,,,,,,,,,, -2053,,,,,,,,,, -2054,,,,,,,,,, -2055,,,,,,,,,, -2056,,,,,,,,,, -2057,,,,,,,,,, -2058,,,,,,,,,, -2059,,,,,,,,,, -2060,,,,,,,,,, diff --git a/solution/altcement/ca_ref_data/custom_ref_ad_REF_Custom_Adoption_based_on_Fly_Ash_Availability_Analysis.csv b/solution/altcement/ca_ref_data/custom_ref_ad_REF_Custom_Adoption_based_on_Fly_Ash_Availability_Analysis.csv deleted file mode 100644 index 27eab9033..000000000 --- a/solution/altcement/ca_ref_data/custom_ref_ad_REF_Custom_Adoption_based_on_Fly_Ash_Availability_Analysis.csv +++ /dev/null @@ -1,50 +0,0 @@ -Year,World,OECD90,Eastern Europe,Asia (Sans Japan),Middle East and Africa,Latin America,China,India,EU,USA -2012,,,,,,,,,, -2013,,,,,,,,,, -2014,,,,,,,,,, -2015,205.4758688265636,42.11699638746252,12.42443113217078,163.8007135327816,3.206396782645229,1.1546541478275518,170.81114031267998,41.66504068404839,36.77673206471707,16.646778919053553 -2016,208.8252853657039,44.26652309197819,12.504591721179082,166.16672383936623,3.394742904766538,1.3014235195069652,171.83094608373196,43.077331248272124,38.795366024713765,17.800955590774596 -2017,212.0983763607541,46.43886172519564,12.582166503153063,168.47459500380185,3.5864830132764998,1.460486394113372,172.8173829964349,44.481333155623226,40.842899231573654,18.987685963492904 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+2055,6332.403484073045,,,,,,,,, +2056,6614.2149128733545,,,,,,,,, +2057,6934.324865761184,,,,,,,,, +2058,7301.383833087428,,,,,,,,, +2059,7726.823020273867,,,,,,,,, +2060,8226.052600951778,,,,,,,,, diff --git a/solution/altcement/tam/tam_van_Ruijven_et_al__2016.csv b/solution/altcement/tam/tam_van_Ruijven_et_al__2016.csv new file mode 100644 index 000000000..0495afa81 --- /dev/null +++ b/solution/altcement/tam/tam_van_Ruijven_et_al__2016.csv @@ -0,0 +1,50 @@ +Year,World,OECD90,Eastern Europe,Asia (Sans Japan),Middle East and Africa,Latin America,China,India,EU,USA +2012,3309.630548894528,,,,,,,,, +2013,3397.739792997278,,,,,,,,, +2014,3478.8203645347403,,,,,,,,, +2015,3553.1651841581815,,,,,,,,, +2016,3621.067172518868,,,,,,,,, +2017,3682.819250268068,,,,,,,,, +2018,3738.714338057047,,,,,,,,, +2019,3789.0453565370726,,,,,,,,, +2020,3834.105226359412,,,,,,,,, +2021,3874.1868681753313,,,,,,,,, +2022,3909.5832026360977,,,,,,,,, +2023,3940.5871503929784,,,,,,,,, +2024,3967.4916320972397,,,,,,,,, +2025,3990.589568400149,,,,,,,,, +2026,4010.173879952973,,,,,,,,, +2027,4026.537487406979,,,,,,,,, +2028,4039.973311413433,,,,,,,,, +2029,4050.7742726236024,,,,,,,,, +2030,4059.2332916887544,,,,,,,,, +2031,4065.643289260155,,,,,,,,, +2032,4070.297185989072,,,,,,,,, +2033,4073.487902526772,,,,,,,,, +2034,4075.5083595245214,,,,,,,,, +2035,4076.6514776335885,,,,,,,,, +2036,4077.2101775052383,,,,,,,,, +2037,4077.477379790739,,,,,,,,, +2038,4077.7460051413573,,,,,,,,, +2039,4078.3089742083594,,,,,,,,, +2040,4079.4592076430126,,,,,,,,, +2041,4081.489626096584,,,,,,,,, +2042,4084.6931502203397,,,,,,,,, +2043,4089.362700665549,,,,,,,,, +2044,4095.791198083475,,,,,,,,, +2045,4104.271563125389,,,,,,,,, +2046,4115.096716442553,,,,,,,,, +2047,4128.559578686238,,,,,,,,, +2048,4144.953070507709,,,,,,,,, +2049,4164.570112558232,,,,,,,,, +2050,4187.703625489077,,,,,,,,, +2051,4214.646529951507,,,,,,,,, +2052,4245.691746596791,,,,,,,,, +2053,4281.132196076198,,,,,,,,, +2054,4321.26079904099,,,,,,,,, +2055,4366.370476142438,,,,,,,,, +2056,4416.754148031807,,,,,,,,, +2057,4472.704735360364,,,,,,,,, +2058,4534.515158779376,,,,,,,,, +2059,4602.478338940111,,,,,,,,, +2060,4676.8871964938335,,,,,,,,, diff --git a/solution/altcement/testdata/expected.zip b/solution/altcement/testdata/expected.zip index 4c1f97a86..7c41d4545 100644 Binary files a/solution/altcement/testdata/expected.zip and b/solution/altcement/testdata/expected.zip differ diff --git a/solution/altcement/vma_data/CONVENTIONAL_Average_Annual_Use.csv b/solution/altcement/vma_data/CONVENTIONAL_Average_Annual_Use.csv index 5222c3126..c5712d4ff 100644 --- a/solution/altcement/vma_data/CONVENTIONAL_Average_Annual_Use.csv +++ b/solution/altcement/vma_data/CONVENTIONAL_Average_Annual_Use.csv @@ -1,2 +1,2 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -Project Drawdown assumption.,,World,,,,,1.0,,,MMt Cement/MMt FlyAsh Cement (Sol) or MMt OPC (Conv)/year,,, +Project Drawdown assumption.,,World,,,,,1.0,,,MMt Cement/MMt Cement/year,,, diff --git a/solution/altcement/vma_data/CONVENTIONAL_Direct_Emissions_per_Functional_Unit.csv b/solution/altcement/vma_data/CONVENTIONAL_Direct_Emissions_per_Functional_Unit.csv index f89cafca1..414f0fcb5 100644 --- a/solution/altcement/vma_data/CONVENTIONAL_Direct_Emissions_per_Functional_Unit.csv +++ b/solution/altcement/vma_data/CONVENTIONAL_Direct_Emissions_per_Functional_Unit.csv @@ -1,3 +1,5 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -"Marceau, M., Nisbet, M. A., & Van Geem, M. G. (2006). Life cycle inventory of portland cement manufacture (No. PCA R&D Serial No. 2095b). IL: Portland Cement Association.",https://www.nrmca.org/taskforce/Item_2_TalkingPoints/Sustainability/Sustainability/SN2095b%20-%20Cement%20LCI%202006.pdf,OECD90,North America,4 - Independently Verified,2006,,,kg CO2/ tonne Cement,0.0,t CO2-eq/MMt Cement,,, -"Liu, Z., Guan, D., Wei, W., Davis, S. J., Ciais, P., Bai, J., ... & Andres, R. J. (2015). Reduced carbon emission estimates from fossil fuel combustion and cement production in China. Nature, 524(7565), 335.",https://www.nature.com/articles/nature14677,Asia (Sans Japan),China,1 - Peer Reviewed,2015,,,t C/ ton cement,0.0,t CO2-eq/MMt Cement,,Data for cement manufacturing in China indicated 58% typical Clinker-to-Cement ratio and assuming a zero Cement Kiln Dusts adjustment factor gives the ratio of 21.55% C emission to ton clinker based on molar mass balance of calcination equation., +"Marceau, M., Nisbet, M. A., & Van Geem, M. G. (2006). Life cycle inventory of Portland cement manufacture (No. PCA R&D Serial No. 2095b). IL: Portland Cement Association.",https://www.nrmca.org/taskforce/Item_2_TalkingPoints/Sustainability/Sustainability/SN2095b%20-%20Cement%20LCI%202006.pdf,OECD90,North America,4 - Independently Verified,2006,,553.0,kg CO2/ tonne Cement,553000.0,t CO2-eq/MMt Cement,,,True +"Liu, Z., Guan, D., Wei, W., Davis, S. J., Ciais, P., Bai, J., ... & Andres, R. J. (2015). Reduced carbon emission estimates from fossil fuel combustion and cement production in China. Nature, 524(7565), 335.",https://www.nature.com/articles/nature14677,Asia (Sans Japan),China,1 - Peer Reviewed,2015,,0.12498999999999999,t C/ ton cement,458213.33999999997,t CO2-eq/MMt Cement,,Data for cement manufacturing in China indicated 58% typical Clinker-to-Cement ratio and assuming a zero Cement Kiln Dusts adjustment factor gives the ratio of 21.55% C emission to ton clinker based on molar mass balance of calcination equation.,True +IEA 2018 [World]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,World,,2 - Public Sector/ Multilateral Agency,2014,,0.34,tonne CO2 / tonne cement,340000.0,t CO2-eq/MMt Cement,,,True +"Gibbs et al (2001) - Gibbs, M. J., Soyka, P., & Conneely, D. (2001). CO2 Emissions from Cement Production. Retrieved from Intergovernmental Panel on Climate Change website: http://www.ipcc-nggip.iges.or.jp/public/gp/bgp/3_1_Cement_Production.pdf",http://www.ipcc-nggip.iges.or.jp/public/gp/bgp/3_1_Cement_Production.pdf,World,,1 - Peer Reviewed,2001,,0.507,tonne CO2 / tonne clinker,350844.0,t CO2-eq/MMt Cement,,Emissions factor by clinker/cement ratio in Year 1, diff --git a/solution/altcement/vma_data/CONVENTIONAL_First_Cost_per_Implementation_Unit.csv b/solution/altcement/vma_data/CONVENTIONAL_First_Cost_per_Implementation_Unit.csv index a3fe8ce2f..5b3b87d65 100644 --- a/solution/altcement/vma_data/CONVENTIONAL_First_Cost_per_Implementation_Unit.csv +++ b/solution/altcement/vma_data/CONVENTIONAL_First_Cost_per_Implementation_Unit.csv @@ -1,3 +1,8 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -"U.S. Geological Survey, 2015, Mineral commodity summaries 2015: U.S. Geological Survey, 196 p., http://dx.doi.org/10.3133/70140094.",https://minerals.usgs.gov/minerals/pubs/mcs/2015/mcs2015.pdf,OECD90,USA,2 - Public Sector/ Multilateral Agency,2015,,,US$2014/metric ton cement,0.0,US2014$/MMt FlyAsh Cement (Sol) or MMt OPC (Conv),,, -Alibaba ,https://www.alibaba.com/showroom/cement-price.html,Asia (Sans Japan),China,3 - For Profit,2018,,,US$2014/metric ton cement,0.0,US2014$/MMt FlyAsh Cement (Sol) or MMt OPC (Conv),,, +"U.S. Geological Survey, 2015, Mineral commodity summaries 2015: U.S. Geological Survey, 196 p., http://dx.doi.org/10.3133/70140094.",https://minerals.usgs.gov/minerals/pubs/mcs/2015/mcs2015.pdf,OECD90,USA,2 - Public Sector/ Multilateral Agency,2015,,98.5,US$2014/metric ton cement,98500000.0,US2014$/MMt Cement,,, +Alibaba ,https://www.alibaba.com/showroom/cement-price.html,Asia (Sans Japan),China,3 - For Profit,2018,,55.0,US$2014/metric ton cement,55000000.0,US2014$/MMt Cement,,, +"CemWeek. (2018, February 18). World cement prices to stabilize in 1Q 2018. Retrieved December 10, 2019, from CemWeek website: https://www.cwgrp.com/cemweek-features/497297-cement-prices-to-stabilize-in-1q-2018",https://www.cwgrp.com/cemweek-features/497297-cement-prices-to-stabilize-in-1q-2018,Latin America,Mexico,4 - Independently Verified,2018,,70.3,US$2018/metric ton cement,66276690.01660646,US2014$/MMt Cement,,, +"CemWeek. (2018, February 18). World cement prices to stabilize in 1Q 2018. Retrieved December 10, 2019, from CemWeek website: https://www.cwgrp.com/cemweek-features/497297-cement-prices-to-stabilize-in-1q-2018",https://www.cwgrp.com/cemweek-features/497297-cement-prices-to-stabilize-in-1q-2018,World,,4 - Independently Verified,2018,,65.6,US$2018/metric ton cement,61845673.75660574,US2014$/MMt Cement,,, +"Alibaba. (2019). International Cement Prices, Wholesale & Suppliers—Alibaba. Retrieved December 10, 2019, from https://www.alibaba.com/showroom/international-cement-prices.html",https://www.alibaba.com/showroom/international-cement-prices.html,Asia (Sans Japan),China,3 - For Profit,2019,,49.0,US$2018/metric ton cement,46195701.43405002,US2014$/MMt Cement,,, +"Indiamart. (2019). Ambuja Cement—Ambuja Cement Latest Price, Dealers & Retailers in India. Retrieved December 10, 2019, from https://dir.indiamart.com/impcat/ambuja-cement.html",https://dir.indiamart.com/impcat/ambuja-cement.html,Asia (Sans Japan),India,3 - For Profit,2019,,69.2,US$2018/metric ton cement,65239643.65788289,US2014$/MMt Cement,,, +"Nigerian Price. (2019, December). Current Price of Cement in Nigeria Today (December 2019). Retrieved December 10, 2019, from https://nigerianprice.com/current-price-of-cement-in-nigeria-today/",https://nigerianprice.com/current-price-of-cement-in-nigeria-today/,Middle East and Africa,Nigeria,3 - For Profit,2019,,138.4,US$2018/metric ton cement,130479287.31576578,US2014$/MMt Cement,,, diff --git a/solution/altcement/vma_data/CONVENTIONAL_Fuel_Consumed_per_Functional_Unit.csv b/solution/altcement/vma_data/CONVENTIONAL_Fuel_Consumed_per_Functional_Unit.csv index b0e9c8b86..d1ebb9471 100644 --- a/solution/altcement/vma_data/CONVENTIONAL_Fuel_Consumed_per_Functional_Unit.csv +++ b/solution/altcement/vma_data/CONVENTIONAL_Fuel_Consumed_per_Functional_Unit.csv @@ -1,4 +1,5 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -"Worrel (2008) Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers, Lawrence Berkeley National Lab Series Paper",https://escholarship.org/uc/item/8wm6q3v3,OECD90,USA,,2008,,,Mbtu/ short ton,0.0,TJ/ MMt Cement,,"Wet Process Higher Heating Value (converted to LHV) (Assumed- HHV:27.06, LHV: 25.87 MJ/kg, according to: https://hub.globalccsinstitute.com/publications/co2-capture-cement-industry/appendix-coal-specification", -"Worrel (2008) Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers, Lawrence Berkeley National Lab Series Paper",https://escholarship.org/uc/item/8wm6q3v3,OECD90,USA,,2008,,,Mbtu/ short ton,0.0,TJ/ MMt Cement,,"Dry Process Higher Heating Value (converted to LHV) (Assumed- HHV:27.06, LHV: 25.87 MJ/kg, according to: https://hub.globalccsinstitute.com/publications/co2-capture-cement-industry/appendix-coal-specification", -"Worrel (2008) Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers, Lawrence Berkeley National Lab Series Paper",https://escholarship.org/uc/item/8wm6q3v3,OECD90,USA,,2008,,,Mbtu/ short ton,0.0,TJ/ MMt Cement,,"Overall Higher Heating Value (converted to LHV) (Assumed- HHV:27.06, LHV: 25.87 MJ/kg, according to: https://hub.globalccsinstitute.com/publications/co2-capture-cement-industry/appendix-coal-specification", +"Worrell et al (2008) [wet kiln] - Worrell, E., Galitsky, C., & Galitsky, C. (2008). Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers (No. LBNL-54036-Revision, 927882; p. LBNL-54036-Revision, 927882). https://doi.org/10.2172/927882",http://www.osti.gov/servlets/purl/927882-7iEuRo/,OECD90,USA,2 - Public Sector/ Multilateral Agency,1999,,4.8,Mbtu/short ton,5336.904887340211,TJ/ MMt Cement,,"Wet Process Higher Heating Value (converted to LHV) (Assumed- HHV:27.06, LHV: 25.87 MJ/kg, according to: https://hub.globalccsinstitute.com/publications/co2-capture-cement-industry/appendix-coal-specification",True +"Worrell et al (2008) [dry kiln] - Worrell, E., Galitsky, C., & Galitsky, C. (2008). Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers (No. LBNL-54036-Revision, 927882; p. LBNL-54036-Revision, 927882). https://doi.org/10.2172/927882",http://www.osti.gov/servlets/purl/927882-7iEuRo/,OECD90,USA,2 - Public Sector/ Multilateral Agency,1999,,3.6,Mbtu/short ton,4002.6786655051587,TJ/ MMt Cement,,"Dry Process Higher Heating Value (converted to LHV) (Assumed- HHV:27.06, LHV: 25.87 MJ/kg, according to: https://hub.globalccsinstitute.com/publications/co2-capture-cement-industry/appendix-coal-specification",True +"Worrell et al (2008) [weighted US average] - Worrell, E., Galitsky, C., & Galitsky, C. (2008). Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers (No. LBNL-54036-Revision, 927882; p. LBNL-54036-Revision, 927882). https://doi.org/10.2172/927882",http://www.osti.gov/servlets/purl/927882-7iEuRo/,OECD90,USA,2 - Public Sector/ Multilateral Agency,1999,,3.9,Mbtu/short ton,4336.235220963922,TJ/ MMt Cement,,"Overall Higher Heating Value (converted to LHV) (Assumed- HHV:27.06, LHV: 25.87 MJ/kg, according to: https://hub.globalccsinstitute.com/publications/co2-capture-cement-industry/appendix-coal-specification",True +"GNR (2016) [World, 25aAG] - WBCSD. (2016). Getting the Numbers Right Project Emissions Report. Retrieved from https://www.wbcsdcement.org/GNR-2016/",https://www.wbcsdcement.org/GNR-2016/,World,,2 - Public Sector/ Multilateral Agency,2016,,3519.0,MJ/tonne cement,3519.0,TJ/ MMt Cement,,Global weighted average of all kiln types., diff --git a/solution/altcement/vma_data/CONVENTIONAL_Indirect_CO2_Emissions_per_Unit.csv b/solution/altcement/vma_data/CONVENTIONAL_Indirect_CO2_Emissions_per_Unit.csv new file mode 100644 index 000000000..42f7d8715 --- /dev/null +++ b/solution/altcement/vma_data/CONVENTIONAL_Indirect_CO2_Emissions_per_Unit.csv @@ -0,0 +1,6 @@ +"SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? +Project Drawdown assumption [Fly Ash],,OECD90,USA,,,,0.08042,t CO2 / t FlyAsh shipped,24769.360000000004,t CO2-eq/ MMt Cement,,, +"Miller et al. 2018 [Fly Ash] - Miller, S. A., John, V. M., Pacca, S. A., & Horvath, A. (2018). Carbon dioxide reduction potential in the global cement industry by 2050. Cement and Concrete Research, 114, 115–124. https://doi.org/10.1016/j.cemconres.2017.08.026",https://linkinghub.elsevier.com/retrieve/pii/S0008884616310833,World,,1 - Peer Reviewed,2018.0,,0.04,kg CO2e / kg material,12320.000000000004,t CO2-eq/ MMt Cement,,, +"Miller et al. 2018 [Slag] - Miller, S. A., John, V. M., Pacca, S. A., & Horvath, A. (2018). Carbon dioxide reduction potential in the global cement industry by 2050. Cement and Concrete Research, 114, 115–124. https://doi.org/10.1016/j.cemconres.2017.08.026",https://linkinghub.elsevier.com/retrieve/pii/S0008884616310833,World,,1 - Peer Reviewed,2018.0,,0.09,kg CO2e / kg material,27720.000000000004,t CO2-eq/ MMt Cement,,, +"Miller et al. 2018 [Natural Pozzolans] - Miller, S. A., John, V. M., Pacca, S. A., & Horvath, A. (2018). Carbon dioxide reduction potential in the global cement industry by 2050. Cement and Concrete Research, 114, 115–124. https://doi.org/10.1016/j.cemconres.2017.08.026",https://linkinghub.elsevier.com/retrieve/pii/S0008884616310833,World,,1 - Peer Reviewed,2018.0,,0.007,kg CO2e / kg material,2156.0000000000005,t CO2-eq/ MMt Cement,,, +"Miller et al. 2018 [Calcined Clays] - Miller, S. A., John, V. M., Pacca, S. A., & Horvath, A. (2018). Carbon dioxide reduction potential in the global cement industry by 2050. Cement and Concrete Research, 114, 115–124. https://doi.org/10.1016/j.cemconres.2017.08.026",https://linkinghub.elsevier.com/retrieve/pii/S0008884616310833,World,,1 - Peer Reviewed,2018.0,,0.27,kg CO2e / kg material,83160.00000000003,t CO2-eq/ MMt Cement,,, diff --git a/solution/altcement/vma_data/CONVENTIONAL_Lifetime_Capacity.csv b/solution/altcement/vma_data/CONVENTIONAL_Lifetime_Capacity.csv index 2d0af6a06..c93ad0339 100644 --- a/solution/altcement/vma_data/CONVENTIONAL_Lifetime_Capacity.csv +++ b/solution/altcement/vma_data/CONVENTIONAL_Lifetime_Capacity.csv @@ -1,3 +1,3 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -"Black, A. P., Crane, S., Hadley, D., & Candela, N. (2011). The Economic Impacts of Prohibiting Coal Fly Ash Use in Transportation Infrastructure Construction.",https://www.artba.org/wp-content/uploads/2017/06/study2011flyash.pdf,OECD90,USA,,2011,,,years,0.0,MMt Cement/MMt FlyAsh Cement (Sol) or MMt OPC (Conv),,, -"Black, A. P., Crane, S., Hadley, D., & Candela, N. (2011). The Economic Impacts of Prohibiting Coal Fly Ash Use in Transportation Infrastructure Construction.",https://www.artba.org/wp-content/uploads/2017/06/study2011flyash.pdf,OECD90,USA,,2011,,,years,0.0,MMt Cement/MMt FlyAsh Cement (Sol) or MMt OPC (Conv),,, +"Black, A. P., Crane, S., Hadley, D., & Candela, N. (2011). The Economic Impacts of Prohibiting Coal Fly Ash Use in Transportation Infrastructure Construction.",https://www.artba.org/wp-content/uploads/2017/06/study2011flyash.pdf,OECD90,USA,,2011,,20.0,years,,MMt Cement/MMt Cement,,, +"Black, A. P., Crane, S., Hadley, D., & Candela, N. (2011). The Economic Impacts of Prohibiting Coal Fly Ash Use in Transportation Infrastructure Construction.",https://www.artba.org/wp-content/uploads/2017/06/study2011flyash.pdf,OECD90,USA,,2011,,25.0,years,,MMt Cement/MMt Cement,,, diff --git a/solution/altcement/vma_data/CONVENTIONAL_Total_Energy_Used_per_Functional_Unit.csv b/solution/altcement/vma_data/CONVENTIONAL_Total_Energy_Used_per_Functional_Unit.csv index 4bfd3b0ba..2ef41e8b7 100644 --- a/solution/altcement/vma_data/CONVENTIONAL_Total_Energy_Used_per_Functional_Unit.csv +++ b/solution/altcement/vma_data/CONVENTIONAL_Total_Energy_Used_per_Functional_Unit.csv @@ -1,4 +1,6 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -"Worrel (2008) Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers, Lawrence Berkeley National Lab Series Paper",https://escholarship.org/uc/item/8wm6q3v3,OECD90,USA,,1999,,,kWh/short ton,0.0,TWh/MMt Cement,,Wet Process, -"Worrel (2008) Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers, Lawrence Berkeley National Lab Series Paper",https://escholarship.org/uc/item/8wm6q3v3,OECD90,USA,,2008,,,kWh/short ton,0.0,TWh/MMt Cement,,Dry Process, -"Worrel (2008) Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers, Lawrence Berkeley National Lab Series Paper",https://escholarship.org/uc/item/8wm6q3v3,OECD90,USA,,2008,,,kWh/short ton,0.0,TWh/MMt Cement,,Overall, +"Worrell et al (2008) [wet kiln] - Worrell, E., Galitsky, C., & Galitsky, C. (2008). Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers (No. LBNL-54036-Revision, 927882; p. LBNL-54036-Revision, 927882). https://doi.org/10.2172/927882",http://www.osti.gov/servlets/purl/927882-7iEuRo/,OECD90,USA,2 - Public Sector/ Multilateral Agency,1999,,132.0,kWh/short ton cement,0.14550505134013458,TWh/MMt Cement,,Wet Process,True +"Worrell et al (2008) [dry kiln] - Worrell, E., Galitsky, C., & Galitsky, C. (2008). Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers (No. LBNL-54036-Revision, 927882; p. LBNL-54036-Revision, 927882). https://doi.org/10.2172/927882",http://www.osti.gov/servlets/purl/927882-7iEuRo/,OECD90,USA,2 - Public Sector/ Multilateral Agency,1999,,150.0,kWh/short ton cement,0.16534664925015294,TWh/MMt Cement,,Dry Process,True +"Worrell et al (2008) [weighted US average] - Worrell, E., Galitsky, C., & Galitsky, C. (2008). Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers (No. LBNL-54036-Revision, 927882; p. LBNL-54036-Revision, 927882). https://doi.org/10.2172/927882",http://www.osti.gov/servlets/purl/927882-7iEuRo/,OECD90,USA,2 - Public Sector/ Multilateral Agency,1999,,146.0,kWh/short ton cement,0.16093740527014888,TWh/MMt Cement,,Overall,True +"GNR (2016) [World, 33AGW] - WBCSD. (2016). Getting the Numbers Right Project Emissions Report. Retrieved from https://www.wbcsdcement.org/GNR-2016/",https://www.wbcsdcement.org/GNR-2016/,World,,2 - Public Sector/ Multilateral Agency,2016,,103.0,kWh/tonne cement,0.103,TWh/MMt Cement,,World average (all kiln types), +IEA 2018 [World]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,World,,2 - Public Sector/ Multilateral Agency,2014,,91.0,kWh/tonne cement,0.09100000000000001,TWh/MMt Cement,,World average (all kiln types), diff --git a/solution/altcement/vma_data/Clinker_Ratio_Range_Selection.csv b/solution/altcement/vma_data/Clinker_Ratio_Range_Selection.csv new file mode 100644 index 000000000..d9b523d8c --- /dev/null +++ b/solution/altcement/vma_data/Clinker_Ratio_Range_Selection.csv @@ -0,0 +1,4 @@ +"SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? +High,,,,,,,,,,,,, +Medium,,,,,,,,,,,,, +Low,,,,,,,,,,,,, diff --git a/solution/altcement/vma_data/Clinker_to_Cement_Ratio_in_Year_2.csv b/solution/altcement/vma_data/Clinker_to_Cement_Ratio_in_Year_2.csv new file mode 100644 index 000000000..2e77b4606 --- /dev/null +++ b/solution/altcement/vma_data/Clinker_to_Cement_Ratio_in_Year_2.csv @@ -0,0 +1,28 @@ +"SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? +"Jayraj Vinodsinh Solanki,Ronak Prakashkumar Patel,Jayeshkumar Pitroda A Study on Low Quality Fly Ash as an Opportunity for Sustainable and economical Concrete International Journal of Scientific Research, Vol.II, Issue.II February 2013 - Low Quality Fly Ash",https://www.worldwidejournals.com/international-journal-of-scientific-research-(IJSR)/articles.php?val=NDc1&b1=153&k=39,Asia (Sans Japan),India,1 - Peer Reviewed,2013,Low,0.6,Clinker/Cement,,,0.14783333333333334,CEM II, +CEMEX Readymix Concrete Standards,http://www.cemex.co.uk/Userfiles/datasheets/concrete-blended-cement-concrete.pdf,World,,3 - For Profit,nd,Medium,0.7,Clinker/Cement,,,,,1.0 +"Sear, L. K. (2001). Fly ash standards, market strategy and UK practice. In Progress Workshop on Novel Products from Combustion Residues.",http://www.flyash.info/2001/govprog/36sear.pdf,OECD90,EU,4 - Independently Verified,2001,High,0.8,Clinker/Cement,,,,,1.0 +"Sear, L. K. (2001). Fly ash standards, market strategy and UK practice. In Progress Workshop on Novel Products from Combustion Residues.",http://www.flyash.info/2001/govprog/36sear.pdf,OECD90,EU,4 - Independently Verified,2001,Medium,0.65,Clinker/Cement,,,,,1.0 +"Worrel (2008) Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers, Lawrence Berkeley National Lab Series Paper",https://escholarship.org/uc/item/8wm6q3v3,OECD90,USA,2 - Public Sector/ Multilateral Agency,2008,Medium,0.65,Clinker/Cement,,,,,1.0 +"Thomas, M. D. A. (2007). Optimizing the use of fly ash in concrete (Vol. 5420). Skokie, IL: Portland Cement Association.",http://www.cement.org/docs/default-source/fc_concrete_technology/is548-optimizing-the-use-of-fly-ash-concrete.pdf,World,,4 - Independently Verified,2007,Low,0.4,Clinker/Cement,,,0.110875,CEM V, +"Bentz, D. P., Ferraris, C. F., & Snyder, K. A. (2013). Best practices guide for high-volume fly ash concretes: Assuring properties and performance (No. Technical Note (NIST TN)-1812).",https://concrete.nist.gov/~bentz/NIST.TN.1812.pdf,OECD90,USA,2 - Public Sector/ Multilateral Agency,2013,Low,0.4,Clinker/Cement,,,0.110875,CEM V, +"Bentz, D. P., Ferraris, C. F., & Snyder, K. A. (2013). Best practices guide for high-volume fly ash concretes: Assuring properties and performance (No. Technical Note (NIST TN)-1812).",https://concrete.nist.gov/~bentz/NIST.TN.1812.pdf,OECD90,USA,2 - Public Sector/ Multilateral Agency,2013,Low,0.09999999999999998,Clinker/Cement,,,0.018666666666666668,CEM III, +CEM II/B [Portland Composite Cement] | High,https://www.cemex.co.uk/documents/45807659/45840198/mortar-cementitious.pdf/46571b2a-3efd-4743-20c8-d33feb1aed9d,World,Europe,2 - Public Sector/ Multilateral Agency,,High,0.79,Clinker/Cement,,,,,1.0 +CEM II/B [Portland Composite Cement] | Medium,https://www.cemex.co.uk/documents/45807659/45840198/mortar-cementitious.pdf/46571b2a-3efd-4743-20c8-d33feb1aed9d,World,Europe,2 - Public Sector/ Multilateral Agency,,Medium,0.72,Clinker/Cement,,,,,1.0 +CEM II/B [Portland Composite Cement] | Low,https://www.cemex.co.uk/documents/45807659/45840198/mortar-cementitious.pdf/46571b2a-3efd-4743-20c8-d33feb1aed9d,World,Europe,2 - Public Sector/ Multilateral Agency,,Low,0.65,Clinker/Cement,,,0.14783333333333334,CEM II, +"CEM III/A [Blastfurnace Cement, slag] | High",https://www.cemex.co.uk/documents/45807659/45840198/mortar-cementitious.pdf/46571b2a-3efd-4743-20c8-d33feb1aed9d,World,Europe,2 - Public Sector/ Multilateral Agency,,High,0.495,Clinker/Cement,,,,,1.0 +"CEM III/B [Blastfurnace Cement, slag] | Medium",https://www.cemex.co.uk/documents/45807659/45840198/mortar-cementitious.pdf/46571b2a-3efd-4743-20c8-d33feb1aed9d,World,Europe,2 - Public Sector/ Multilateral Agency,,Medium,0.27,Clinker/Cement,,,,,1.0 +"CEM III/C [Blastfurnace Cement, slag] | Low",https://www.cemex.co.uk/documents/45807659/45840198/mortar-cementitious.pdf/46571b2a-3efd-4743-20c8-d33feb1aed9d,World,Europe,2 - Public Sector/ Multilateral Agency,,Low,0.12,Clinker/Cement,,,0.018666666666666668,CEM III, +CEM IV [Pozzolanic Cement] | High,https://www.cemex.co.uk/documents/45807659/45840198/mortar-cementitious.pdf/46571b2a-3efd-4743-20c8-d33feb1aed9d,World,Europe,2 - Public Sector/ Multilateral Agency,,High,0.89,Clinker/Cement,,,,,1.0 +CEM IV [Pozzolanic Cement] | Medium,https://www.cemex.co.uk/documents/45807659/45840198/mortar-cementitious.pdf/46571b2a-3efd-4743-20c8-d33feb1aed9d,World,Europe,2 - Public Sector/ Multilateral Agency,,Medium,0.67,Clinker/Cement,,,,,1.0 +CEM IV [Pozzolanic Cement] | Low,https://www.cemex.co.uk/documents/45807659/45840198/mortar-cementitious.pdf/46571b2a-3efd-4743-20c8-d33feb1aed9d,World,Europe,2 - Public Sector/ Multilateral Agency,,Low,0.45,Clinker/Cement,,,0.0285,CEM IV, +CEM V [Composite Cement | High,https://www.cemex.co.uk/documents/45807659/45840198/mortar-cementitious.pdf/46571b2a-3efd-4743-20c8-d33feb1aed9d,World,Europe,2 - Public Sector/ Multilateral Agency,,High,0.64,Clinker/Cement,,,,,1.0 +CEM V [Composite Cement | Medium,https://www.cemex.co.uk/documents/45807659/45840198/mortar-cementitious.pdf/46571b2a-3efd-4743-20c8-d33feb1aed9d,World,Europe,2 - Public Sector/ Multilateral Agency,,Medium,0.42000000000000004,Clinker/Cement,,,,,1.0 +CEM V [Composite Cement | Low,https://www.cemex.co.uk/documents/45807659/45840198/mortar-cementitious.pdf/46571b2a-3efd-4743-20c8-d33feb1aed9d,World,Europe,2 - Public Sector/ Multilateral Agency,,Low,0.2,Clinker/Cement,,,0.110875,CEM V, +Type IS Portland-Slag Cement [Upper Limit],http://www.astm.org/cgi-bin/resolver.cgi?C595C595M-19,OECD90,USA,2 - Public Sector/ Multilateral Agency,2019,Low,0.3,Clinker/Cement,,,0.018666666666666668,CEM III, +Type IP Portland-Pozzolan Cement [Upper Limit],http://www.astm.org/cgi-bin/resolver.cgi?C595C595M-19,OECD90,USA,2 - Public Sector/ Multilateral Agency,2019,Low,0.4,Clinker/Cement,,,0.0285,CEM IV, +Type IL Portland-Limestone Cement [Upper Limit],http://www.astm.org/cgi-bin/resolver.cgi?C595C595M-19,OECD90,USA,2 - Public Sector/ Multilateral Agency,2019,Low,0.85,Clinker/Cement,,,0.14783333333333334,CEM II, +Type IT Ternary Blended Cement [Upper Limit],http://www.astm.org/cgi-bin/resolver.cgi?C595C595M-19,OECD90,USA,2 - Public Sector/ Multilateral Agency,2019,Low,0.3,Clinker/Cement,,,0.110875,CEM V, +"IEA 2018 [World, 2DS Low-variability]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry",https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,World,,2 - Public Sector/ Multilateral Agency,2018,,0.6,Clinker/Cement,,,,,1.0 +"CSI 2017 [Global 2050 High] - Cement Sustainability Initiative, & European Cement Research Academy. (2017). Development of State of the Art-Techniques in Cement Manufacturing: Trying to Look Ahead (p. 190). Retrieved from http://www.wbcsdcement.org/technology",http://www.wbcsdcement.org/technology,World,,2 - Public Sector/ Multilateral Agency,2017,,0.6,Clinker/Cement,,,,,1.0 +"CSI 2017 [Global 2050 Low] - Cement Sustainability Initiative, & European Cement Research Academy. (2017). Development of State of the Art-Techniques in Cement Manufacturing: Trying to Look Ahead (p. 190). Retrieved from http://www.wbcsdcement.org/technology",http://www.wbcsdcement.org/technology,World,,2 - Public Sector/ Multilateral Agency,2017,,0.65,Clinker/Cement,,,,,1.0 diff --git a/solution/altcement/vma_data/Clinker_to_Cement_Ratio_of_Conventional_Technology.csv b/solution/altcement/vma_data/Clinker_to_Cement_Ratio_of_Conventional_Technology.csv new file mode 100644 index 000000000..fe19f383d --- /dev/null +++ b/solution/altcement/vma_data/Clinker_to_Cement_Ratio_of_Conventional_Technology.csv @@ -0,0 +1,14 @@ +"SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? +IEA 2018 [World]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,World,,2 - Public Sector/ Multilateral Agency,2018,,0.65,Clinker/Cement,,,,, +IEA 2018 [China]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,Asia (Sans Japan),China,2 - Public Sector/ Multilateral Agency,2018,,0.57,Clinker/Cement,,,,,1.0 +IEA 2018 [India]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,Asia (Sans Japan),India,2 - Public Sector/ Multilateral Agency,2018,,0.72,Clinker/Cement,,,,,1.0 +IEA 2018 [Africa]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,Middle East and Africa,Africa,2 - Public Sector/ Multilateral Agency,2018,,0.74,Clinker/Cement,,,,,1.0 +IEA 2018 [Middle East]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,Middle East and Africa,Middle East,2 - Public Sector/ Multilateral Agency,2018,,0.8,Clinker/Cement,,,,,1.0 +IEA 2018 [America]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,Latin America,America,2 - Public Sector/ Multilateral Agency,2018,,0.71,Clinker/Cement,,,,,1.0 +IEA 2018 [Europe]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,OECD90,Europe,2 - Public Sector/ Multilateral Agency,2018,,0.76,Clinker/Cement,,,,,1.0 +IEA 2018 [Other Asia Pacific]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,Asia (Sans Japan),Other Asia Pacific,2 - Public Sector/ Multilateral Agency,2018,,0.79,Clinker/Cement,,,,,1.0 +IEA 2018 [Eurasia]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,Eastern Europe,Eurasia,2 - Public Sector/ Multilateral Agency,2018,,0.87,Clinker/Cement,,,,,1.0 +"CSI 2017 [China] - Cement Sustainability Initiative, & European Cement Research Academy. (2017). Development of State of the Art-Techniques in Cement Manufacturing: Trying to Look Ahead (p. 190). Retrieved from http://www.wbcsdcement.org/technology",http://www.wbcsdcement.org/technology,Asia (Sans Japan),China,2 - Public Sector/ Multilateral Agency,2017,,0.58,Clinker/Cement,,,,, +"CSI 2017 [Europe] - Cement Sustainability Initiative, & European Cement Research Academy. (2017). Development of State of the Art-Techniques in Cement Manufacturing: Trying to Look Ahead (p. 190). Retrieved from http://www.wbcsdcement.org/technology",http://www.wbcsdcement.org/technology,OECD90,Europe,2 - Public Sector/ Multilateral Agency,2017,,0.73,Clinker/Cement,,,,, +"CSI 2017 [Global] - Cement Sustainability Initiative, & European Cement Research Academy. (2017). Development of State of the Art-Techniques in Cement Manufacturing: Trying to Look Ahead (p. 190). Retrieved from http://www.wbcsdcement.org/technology",http://www.wbcsdcement.org/technology,World,,2 - Public Sector/ Multilateral Agency,2017,,0.75,Clinker/Cement,,,,, +WBCSD 2016 [92AGW] - WBCSD. (2016). Getting the Numbers Right Project Emissions Report. Retrieved from https://www.wbcsdcement.org/GNR-2016/,https://www.wbcsdcement.org/GNR-2016/,World,,2 - Public Sector/ Multilateral Agency,2016,,0.75,Clinker/Cement,,,,, diff --git a/solution/altcement/vma_data/Current_Adoption.csv b/solution/altcement/vma_data/Current_Adoption.csv index 51021e17a..393d9a11f 100644 --- a/solution/altcement/vma_data/Current_Adoption.csv +++ b/solution/altcement/vma_data/Current_Adoption.csv @@ -1,2 +1,2 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -Project Drawdown Estimations in Additional HVFAC Model,,World,,,2018,,,MMT Fly Ash in use in cement,0.0,MMt Cement,,, +Current adoption is modeled in the clinker/cement ratio,,World,,,2018,,0.0,,0.0,MMt Cement,,, diff --git a/solution/altcement/vma_data/Discount_Rate_Commercial.csv b/solution/altcement/vma_data/Discount_Rate_Commercial.csv index ce30a7546..8ebf97f8a 100644 --- a/solution/altcement/vma_data/Discount_Rate_Commercial.csv +++ b/solution/altcement/vma_data/Discount_Rate_Commercial.csv @@ -1,6 +1,6 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -Costs and potentials of greenhouse gas abatement in Germany (2007),,EU,Germany,,2007,,,,,,,, -"Development of an integrated heating and cooling strategy for Germany (2012, 2013)",,EU,Germany,,2012,,,,,,,, -Policy Scenarios for climate protection VI (2013),,EU,Germany,,2013,,,,,,,, -Steinbach (2013) Discount rates in energy system analysis,,,,,2013,,,,,,,, -Steinbach (2013) Discount rates in energy system analysis,,,,,2013,,,,,,,, +McKinsey & Company. (2007). Costs and Potentials of Greenhouse Gas Abatement in Germany.,https://www.mckinsey.com/~/media/McKinsey/dotcom/client_service/Sustainability/cost%20curve%20PDFs/costs_and_potentials_of_greenhouse_gas_full_report.ashx,OECD90,Germany,3 - For Profit,2007,,0.095,percent,,,,, +"H.-M. Henning, V. Bürger, L. Kranzl, W. Schulz, J. Steinbach, J. Kockat, 2013. Development of an Integrated Heat and Cooling Strategy (Phase 2) target system for the building sector in 2050, Fraunhofer ISE, Fraunhofer ISI, IREES, Öko-Institut, Bremer Energy Institute, Vienna University of Technology on behalf of the Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) (in German)",,OECD90,Germany,2 - Public Sector/ Multilateral Agency,2012,,0.076,percent,,,,, +"Felix Chr. Matthes; Julia Busche; Ulrike Döring; Lukas Emele; Sabine Gores; Ralph O. Harthan, Hauke Hermann; Wolfram Jörß; Charlotte Loreck; Margarethe Scheffler , 2013. Policy Scenarios for climate protection VI, Greenhouse gas emission scenarios up to the year 2030 (In German), for the German Federal Ministry of the Environment",https://www.umweltbundesamt.de/sites/default/files/medien/461/publikationen/4412.pdf,OECD90,Germany,2 - Public Sector/ Multilateral Agency,2013,,0.08,percent,,,,, +"Steinbach, J., & Staniaszek, D. (2015). Discount rates in energy system analysis Discussion Paper. BPIE: Berlin, Germany.",http://bpie.eu/wp-content/uploads/2015/10/Discount_rates_in_energy_system-discussion_paper_2015_ISI_BPIE.pdf,World,,4 - Independently Verified,2013,,0.06,percent,,,,, +"Steinbach, J., & Staniaszek, D. (2015). Discount rates in energy system analysis Discussion Paper. BPIE: Berlin, Germany.",http://bpie.eu/wp-content/uploads/2015/10/Discount_rates_in_energy_system-discussion_paper_2015_ISI_BPIE.pdf,World,,4 - Independently Verified,2013,,0.15,percent,,,,, diff --git a/solution/altcement/vma_data/FlyAsh_OPC_Replacement_Ratio.csv b/solution/altcement/vma_data/FlyAsh_OPC_Replacement_Ratio.csv deleted file mode 100644 index 5ad6eb390..000000000 --- a/solution/altcement/vma_data/FlyAsh_OPC_Replacement_Ratio.csv +++ /dev/null @@ -1,9 +0,0 @@ -"SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -"Jayraj Vinodsinh Solanki,Ronak Prakashkumar Patel,Jayeshkumar Pitroda A Study on Low Quality Fly Ash as an Opportunity for Sustainable and conomical Concrete International Journal of Scientific Research, Vol.II, Issue.II February 2013",https://www.worldwidejournals.com/international-journal-of-scientific-research-(IJSR)/articles.php?val=NDc1&b1=153&k=39,Asia (Sans Japan),India,1 - Peer Reviewed,2013,,,percent,,,,Study uses low quality fly ash, -CEMEX Readymix Concrete Standards,http://www.cemex.co.uk/Userfiles/datasheets/concrete-blended-cement-concrete.pdf,World,,3 - For Profit,nd,,,percent,,,,Cemex Standards for FlyAsh % content, -"Sear, L. K. (2001). Fly ash standards, market strategy and UK practice. In Progress Workshop on Novel Products from Combustion Residues.",http://www.flyash.info/2001/govprog/36sear.pdf,OECD90,EU,4 - Independently Verified,2001,,,percent,,,,Maximum for European standard CEM II/ A, -"Sear, L. K. (2001). Fly ash standards, market strategy and UK practice. In Progress Workshop on Novel Products from Combustion Residues.",http://www.flyash.info/2001/govprog/36sear.pdf,OECD90,EU,4 - Independently Verified,2001,,,percent,,,,Maximum for European standard CEM II/ B, -"Worrel (2008) Energy Efficiency Improvement and Cost Saving Opportunities for Cement Making. An ENERGY STAR Guide for Energy and Plant Managers, Lawrence Berkeley National Lab Series Paper",https://escholarship.org/uc/item/8wm6q3v3,OECD90,USA,2 - Public Sector/ Multilateral Agency,2008,,,percent,,,,Average assumed for US blended cement, -"Thomas, M. D. A. (2007). Optimizing the use of fly ash in concrete (Vol. 5420). Skokie, IL: Portland Cement Association.",http://www.cement.org/docs/default-source/fc_concrete_technology/is548-optimizing-the-use-of-fly-ash-concrete.pdf,World,,4 - Independently Verified,2007,,,percent,,,,Reference to Marceau (2002) on p1., -"Bentz, D. P., Ferraris, C. F., & Snyder, K. A. (2013). Best practices guide for high-volume fly ash concretes: Assuring properties and performance (No. Technical Note (NIST TN)-1812).",https://concrete.nist.gov/~bentz/NIST.TN.1812.pdf,OECD90,USA,2 - Public Sector/ Multilateral Agency,2013,,,percent,,,,"Building for LEED certification, p12", -"Bentz, D. P., Ferraris, C. F., & Snyder, K. A. (2013). Best practices guide for high-volume fly ash concretes: Assuring properties and performance (No. Technical Note (NIST TN)-1812).",https://concrete.nist.gov/~bentz/NIST.TN.1812.pdf,OECD90,USA,2 - Public Sector/ Multilateral Agency,2013,,,percent,,,,Flowable fill and low density applications, diff --git a/solution/altcement/vma_data/Percent_Adoption_of_Blended_Cements_in_Year_2_2050.csv b/solution/altcement/vma_data/Percent_Adoption_of_Blended_Cements_in_Year_2_2050.csv new file mode 100644 index 000000000..03892d0d1 --- /dev/null +++ b/solution/altcement/vma_data/Percent_Adoption_of_Blended_Cements_in_Year_2_2050.csv @@ -0,0 +1,2 @@ +"SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? +"Miller et al. 2018 - IEA 2DS - Miller, S. A., John, V. M., Pacca, S. A., & Horvath, A. (2018). Carbon dioxide reduction potential in the global cement industry by 2050. Cement and Concrete Research, 114, 115–124. https://doi.org/10.1016/j.cemconres.2017.08.026",https://linkinghub.elsevier.com/retrieve/pii/S0008884616310833,World,,1 - Peer Reviewed,2050,,0.48,percent,,,,48% is for CEM V only., diff --git a/solution/altcement/vma_data/SOLUTION_Average_Annual_Use.csv b/solution/altcement/vma_data/SOLUTION_Average_Annual_Use.csv index 5222c3126..c5712d4ff 100644 --- a/solution/altcement/vma_data/SOLUTION_Average_Annual_Use.csv +++ b/solution/altcement/vma_data/SOLUTION_Average_Annual_Use.csv @@ -1,2 +1,2 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -Project Drawdown assumption.,,World,,,,,1.0,,,MMt Cement/MMt FlyAsh Cement (Sol) or MMt OPC (Conv)/year,,, +Project Drawdown assumption.,,World,,,,,1.0,,,MMt Cement/MMt Cement/year,,, diff --git a/solution/altcement/vma_data/SOLUTION_Direct_Emissions_per_Functional_Unit.csv b/solution/altcement/vma_data/SOLUTION_Direct_Emissions_per_Functional_Unit.csv index 8a191e493..1cd207cc0 100644 --- a/solution/altcement/vma_data/SOLUTION_Direct_Emissions_per_Functional_Unit.csv +++ b/solution/altcement/vma_data/SOLUTION_Direct_Emissions_per_Functional_Unit.csv @@ -1,2 +1,3 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -Project Drawdown assumptions of Fly Ash ratio and Fly Ash Source (see below),,World,,,,,,t CO2-eq/MMt Cement,,t CO2-eq/MMt Cement,,, +"Gibbs et al (2001) - Gibbs, M. J., Soyka, P., & Conneely, D. (2001). CO2 Emissions from Cement Production. Retrieved from Intergovernmental Panel on Climate Change website: http://www.ipcc-nggip.iges.or.jp/public/gp/bgp/3_1_Cement_Production.pdf",http://www.ipcc-nggip.iges.or.jp/public/gp/bgp/3_1_Cement_Production.pdf,World,,1 - Peer Reviewed,2001,,0.507,tonne CO2 / tonne clinker,136361.48837278804,t CO2-eq/MMt Cement,,Emissions factor by clinker/cement ratio in Year 2, +"IEA 2018 [World, 2DS]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry",https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,World,,2 - Public Sector/ Multilateral Agency,2050,,0.24,tonne CO2 / tonne cement,240000.0,t CO2-eq/MMt Cement,,,1.0 diff --git a/solution/altcement/vma_data/SOLUTION_First_Cost_per_Implementation_Unit.csv b/solution/altcement/vma_data/SOLUTION_First_Cost_per_Implementation_Unit.csv index f0cb48830..b705078b1 100644 --- a/solution/altcement/vma_data/SOLUTION_First_Cost_per_Implementation_Unit.csv +++ b/solution/altcement/vma_data/SOLUTION_First_Cost_per_Implementation_Unit.csv @@ -1,6 +1,11 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -"Black, A. P., Crane, S., Hadley, D., & Candela, N. (2011). The Economic Impacts of Prohibiting Coal Fly Ash Use in Transportation Infrastructure Construction.",https://www.artba.org/wp-content/uploads/2017/06/study2011flyash.pdf,OECD90,USA,,2011,,,Price reduction of FA compared to Portland cement,45900000.0,US2014$/MMt FlyAsh Cement (Sol) or MMt OPC (Conv),,FA is 17-50% cheaper than Portland., -"Black, A. P., Crane, S., Hadley, D., & Candela, N. (2011). The Economic Impacts of Prohibiting Coal Fly Ash Use in Transportation Infrastructure Construction.",https://www.artba.org/wp-content/uploads/2017/06/study2011flyash.pdf,OECD90,USA,,2011,,,Price reduction of FA compared to Portland cement,45900000.0,US2014$/MMt FlyAsh Cement (Sol) or MMt OPC (Conv),,FA is 17-50% cheaper than Portland., -Intergovernmental Panel on Climate Change. (2015). Climate change 2014: mitigation of climate change (Vol. 3). Cambridge University Press. Fig TS.27,http://www.ipcc.ch/report/ar5/wg3/,World,,1 - Peer Reviewed,2010,,,US$2014 levelized cost per t CO2,0.0,US2014$/MMt FlyAsh Cement (Sol) or MMt OPC (Conv),,"The IPCC WGIII AR5 (2014) estimate the cost of CO2 emission intensity reductions for cement with an indicative levelized cost of <$0-$50 per tonne of CO2 conserved for the 450ppm CO2-eq scenario (i.e. for ""best practice clinker subsititution""). We assume that each tonne of FA conserves 0.79 t CO2, so the cost of FA is about (price)*0.79.", -Intergovernmental Panel on Climate Change. (2015). Climate change 2014: mitigation of climate change (Vol. 3). Cambridge University Press. Fig TS.27,http://www.ipcc.ch/report/ar5/wg3/,World,,1 - Peer Reviewed,2010,,,US$2014 levelized cost per t CO2,25245000.000000004,US2014$/MMt FlyAsh Cement (Sol) or MMt OPC (Conv),,"The IPCC WGIII AR5 (2014) estimate the cost of CO2 emission intensity reductions for cement with an indicative levelized cost of <$0-$50 per tonne of CO2 conserved for the 450ppm CO2-eq scenario (i.e. for ""best practice clinker subsititution""). We assume that each tonne of FA conserves 0.79 t CO2, so the cost of FA is about (CO2 price)*0.79.", -"Mehta, P. K., & Langley, W. S. (2000). Monolith foundation: built to last a 1000 years. Concrete International, 22(7), 27-32.",http://maquinamole.net/EcoSmartconcrete.com/docs/trmehtalangley00.pdf,OECD90,USA - Hawaii imported,,2000,,,US$2000/tonne,25245000.000000004,US2014$/MMt FlyAsh Cement (Sol) or MMt OPC (Conv),,This is likely an outlier on the global scale due to the isolation of Hawaii for importation.,1.0 +"Black, A. P., Crane, S., Hadley, D., & Candela, N. (2011). The Economic Impacts of Prohibiting Coal Fly Ash Use in Transportation Infrastructure Construction.",https://www.artba.org/wp-content/uploads/2017/06/study2011flyash.pdf,OECD90,USA,,2011,,0.17,Price reduction of FA compared to Portland cement,62076529.54716511,US2014$/MMt Cement,,FA is 17-50% cheaper than Portland.,True +"Black, A. P., Crane, S., Hadley, D., & Candela, N. (2011). The Economic Impacts of Prohibiting Coal Fly Ash Use in Transportation Infrastructure Construction.",https://www.artba.org/wp-content/uploads/2017/06/study2011flyash.pdf,OECD90,USA,,2011,,0.5,Price reduction of FA compared to Portland cement,37395499.7272079,US2014$/MMt Cement,,FA is 17-50% cheaper than Portland.,True +Intergovernmental Panel on Climate Change. (2015). Climate change 2014: mitigation of climate change (Vol. 3). Cambridge University Press. Fig TS.27,http://www.ipcc.ch/report/ar5/wg3/,World,,1 - Peer Reviewed,2010,,0.0,US$2014 levelized cost per t CO2,0.0,US2014$/MMt Cement,,"The IPCC WGIII AR5 (2014) estimate the cost of CO2 emission intensity reductions for cement with an indicative levelized cost of <$0-$50 per tonne of CO2 conserved for the 450ppm CO2-eq scenario (i.e. for ""best practice clinker substitution""). We assume that each tonne of FA conserves 0.79 t CO2, so the cost of FA is about (price)*0.79.",True +Intergovernmental Panel on Climate Change. (2015). Climate change 2014: mitigation of climate change (Vol. 3). Cambridge University Press. Fig TS.27,http://www.ipcc.ch/report/ar5/wg3/,World,,1 - Peer Reviewed,2010,,50.0,US$2014 levelized cost per t CO2,66255362.135673925,US2014$/MMt Cement,,"The IPCC WGIII AR5 (2014) estimate the cost of CO2 emission intensity reductions for cement with an indicative levelized cost of <$0-$50 per tonne of CO2 conserved for the 450ppm CO2-eq scenario (i.e. for ""best practice clinker substitution""). We assume that each tonne of FA conserves 0.79 t CO2, so the cost of FA is about (CO2 price)*0.79.",True +"Mehta, P. K., & Langley, W. S. (2000). Monolith foundation: built to last a 1000 years. Concrete International, 22(7), 27-32.",http://maquinamole.net/EcoSmartconcrete.com/docs/trmehtalangley00.pdf,OECD90,USA - Hawaii imported,,2000,,200.0,US$2000/tonne,128369768.31368878,US2014$/MMt Cement,,This is likely an outlier on the global scale due to the isolation of Hawaii for importation.,True +"Fly Ash - Cal Portland Cement. (2019, October 15). Price of SCMs in California [Email].",,OECD90,USA,3 - For Profit,2019,,0.03300000000000003,Price reduction,72322896.47242008,US2014$/MMt Cement,,, +"Blast Furnace Slag - Cal Portland Cement. (2019, October 15). Price of SCMs in California [Email].",N/A,OECD90,USA,3 - For Profit,2019,,0.06699999999999995,Price reduction,69780002.49096994,US2014$/MMt Cement,,, +"Blended cements - Levy, S. M. (2012). Section 5—Calculations Relating to Concrete and Masonry. In S. M. Levy (Ed.), Construction Calculations Manual (pp. 211–264). https://doi.org/10.1016/B978-0-12-382243-7.00005-X",http://www.sciencedirect.com/science/article/pii/B978012382243700005X,OECD90,USA,2 - Public Sector/ Multilateral Agency,2012,,1.1,Price of cement,82270099.39985739,US2014$/MMt Cement,,, +"Slag cement - Kim, T. (2016). Assessment of Construction Cost Saving by Concrete Mixing the Activator Material. Sustainability, 8(4), 403. https://doi.org/10.3390/su8040403",,Asia (Sans Japan),South Korea,1 - Peer Reviewed,2016,,0.975,Price of cement,72921224.4680554,US2014$/MMt Cement,,, +"Slag cement - Kim, T. (2016). Assessment of Construction Cost Saving by Concrete Mixing the Activator Material. Sustainability, 8(4), 403. https://doi.org/10.3390/su8040403",,Asia (Sans Japan),South Korea,1 - Peer Reviewed,2016,,0.963,Price of cement,72023732.47460242,US2014$/MMt Cement,,, diff --git a/solution/altcement/vma_data/SOLUTION_Fuel_Efficiency_Factor.csv b/solution/altcement/vma_data/SOLUTION_Fuel_Efficiency_Factor.csv new file mode 100644 index 000000000..b8e618762 --- /dev/null +++ b/solution/altcement/vma_data/SOLUTION_Fuel_Efficiency_Factor.csv @@ -0,0 +1,3 @@ +"SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? +IEA 2018 [World]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 18). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,World,,2 - Public Sector/ Multilateral Agency,2050,,3.1,GJ/ton clinker,0.6557520770683243,%,,Thermal efficiency estimated gain above 3.5 GJ/t reference, +"CSI 2017 [Global] - Cement Sustainability Initiative, & European Cement Research Academy. (2017). Development of State of the Art-Techniques in Cement Manufacturing: Trying to Look Ahead (p. 190). Retrieved from http://www.wbcsdcement.org/technology",http://www.wbcsdcement.org/technology,World,,2 - Public Sector/ Multilateral Agency,2050,,3200.0,MJ/ton clinker,0.6456597062002786,%,,Thermal efficiency estimated gain above 3510 MJ/t clinker, diff --git a/solution/altcement/vma_data/SOLUTION_Indirect_CO2_Emissions_per_Unit.csv b/solution/altcement/vma_data/SOLUTION_Indirect_CO2_Emissions_per_Unit.csv index ec587365d..3fbad4825 100644 --- a/solution/altcement/vma_data/SOLUTION_Indirect_CO2_Emissions_per_Unit.csv +++ b/solution/altcement/vma_data/SOLUTION_Indirect_CO2_Emissions_per_Unit.csv @@ -1,2 +1,6 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -Project Drawdown assumption,,OECD90,USA,,,,,t CO2 / t FlyAsh shipped,0.0,t CO2-eq/ MMt Cement,,It is assumed that the FlyAsh used in the production of cement is shipped by the average rail (1400km) and average truck (960km) distances in the US (50% each). Truck emissions: 134g CO2/ t-km. Rail Emissions: 23g CO2/ t-km., +Project Drawdown assumption,,OECD90,USA,,,,0.08042,t CO2 / t FlyAsh shipped,58790.43215988242,t CO2-eq/ MMt Cement,,It is assumed that the FlyAsh used in the production of cement is shipped by the average rail (1400km) and average truck (960km) distances in the US (50% each). Truck emissions: 134g CO2/ t-km. Rail Emissions: 23g CO2/ t-km., +"Miller et al. 2018 [Fly Ash] - Miller, S. A., John, V. M., Pacca, S. A., & Horvath, A. (2018). Carbon dioxide reduction potential in the global cement industry by 2050. Cement and Concrete Research, 114, 115–124. https://doi.org/10.1016/j.cemconres.2017.08.026",https://linkinghub.elsevier.com/retrieve/pii/S0008884616310833,World,,1 - Peer Reviewed,2018.0,,0.04,kg CO2e / kg material,29241.697169799758,t CO2-eq/ MMt Cement,,, +"Miller et al. 2018 [Slag] - Miller, S. A., John, V. M., Pacca, S. A., & Horvath, A. (2018). Carbon dioxide reduction potential in the global cement industry by 2050. Cement and Concrete Research, 114, 115–124. https://doi.org/10.1016/j.cemconres.2017.08.026",https://linkinghub.elsevier.com/retrieve/pii/S0008884616310833,World,,1 - Peer Reviewed,2018.0,,0.09,kg CO2e / kg material,65793.81863204946,t CO2-eq/ MMt Cement,,, +"Miller et al. 2018 [Natural Pozzolans] - Miller, S. A., John, V. M., Pacca, S. A., & Horvath, A. (2018). Carbon dioxide reduction potential in the global cement industry by 2050. Cement and Concrete Research, 114, 115–124. https://doi.org/10.1016/j.cemconres.2017.08.026",https://linkinghub.elsevier.com/retrieve/pii/S0008884616310833,World,,1 - Peer Reviewed,2018.0,,0.007,kg CO2e / kg material,5117.297004714958,t CO2-eq/ MMt Cement,,, +"Miller et al. 2018 [Calcined Clays] - Miller, S. A., John, V. M., Pacca, S. A., & Horvath, A. (2018). Carbon dioxide reduction potential in the global cement industry by 2050. Cement and Concrete Research, 114, 115–124. https://doi.org/10.1016/j.cemconres.2017.08.026",https://linkinghub.elsevier.com/retrieve/pii/S0008884616310833,World,,1 - Peer Reviewed,2018.0,,0.27,kg CO2e / kg material,197381.4558961484,t CO2-eq/ MMt Cement,,, diff --git a/solution/altcement/vma_data/SOLUTION_Lifetime_Capacity.csv b/solution/altcement/vma_data/SOLUTION_Lifetime_Capacity.csv index 2d0af6a06..8ecaab775 100644 --- a/solution/altcement/vma_data/SOLUTION_Lifetime_Capacity.csv +++ b/solution/altcement/vma_data/SOLUTION_Lifetime_Capacity.csv @@ -1,3 +1,3 @@ "SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? -"Black, A. P., Crane, S., Hadley, D., & Candela, N. (2011). The Economic Impacts of Prohibiting Coal Fly Ash Use in Transportation Infrastructure Construction.",https://www.artba.org/wp-content/uploads/2017/06/study2011flyash.pdf,OECD90,USA,,2011,,,years,0.0,MMt Cement/MMt FlyAsh Cement (Sol) or MMt OPC (Conv),,, -"Black, A. P., Crane, S., Hadley, D., & Candela, N. (2011). The Economic Impacts of Prohibiting Coal Fly Ash Use in Transportation Infrastructure Construction.",https://www.artba.org/wp-content/uploads/2017/06/study2011flyash.pdf,OECD90,USA,,2011,,,years,0.0,MMt Cement/MMt FlyAsh Cement (Sol) or MMt OPC (Conv),,, +"Black, A. P., Crane, S., Hadley, D., & Candela, N. (2011). The Economic Impacts of Prohibiting Coal Fly Ash Use in Transportation Infrastructure Construction.",https://www.artba.org/wp-content/uploads/2017/06/study2011flyash.pdf,OECD90,USA,,2011,,30.0,years,30.0,MMt Cement/MMt Cement,,, +"Black, A. P., Crane, S., Hadley, D., & Candela, N. (2011). The Economic Impacts of Prohibiting Coal Fly Ash Use in Transportation Infrastructure Construction.",https://www.artba.org/wp-content/uploads/2017/06/study2011flyash.pdf,OECD90,USA,,2011,,60.0,years,60.0,MMt Cement/MMt Cement,,, diff --git a/solution/altcement/vma_data/SOLUTION_Total_Energy_Used_per_Functional_Unit.csv b/solution/altcement/vma_data/SOLUTION_Total_Energy_Used_per_Functional_Unit.csv new file mode 100644 index 000000000..85708fcbc --- /dev/null +++ b/solution/altcement/vma_data/SOLUTION_Total_Energy_Used_per_Functional_Unit.csv @@ -0,0 +1,4 @@ +"SOURCE ID: Author/Org, Date, Info",Link,World / Drawdown Region,Specific Geographic Location,Source Validation Code,Year / Date,License Code,Raw Data Input,Original Units,Conversion calculation,Common Units,Weight,Assumptions,Exclude Data? +"IEA 2018 [World, 2DS]- IEA. (2018). Technology Roadmap—Low-Carbon Transition in the Cement Industry (p. 66). Retrieved from International Energy Agency website: https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry",https://webstore.iea.org/technology-roadmap-low-carbon-transition-in-the-cement-industry,World,,2 - Public Sector/ Multilateral Agency,2050,,79.0,kWh/tonne cement,0.079,TWh/MMt Cement,,, +"CSI 2017 [Global, Low] - Cement Sustainability Initiative, & European Cement Research Academy. (2017). Development of State of the Art-Techniques in Cement Manufacturing: Trying to Look Ahead (p. 190). Retrieved from http://www.wbcsdcement.org/technology",http://www.wbcsdcement.org/technology,World,,2 - Public Sector/ Multilateral Agency,2050,,90.0,kWh/tonne cement,0.09000000000000001,TWh/MMt Cement,,, +"CSI 2017 [Global, High] - Cement Sustainability Initiative, & European Cement Research Academy. (2017). Development of State of the Art-Techniques in Cement Manufacturing: Trying to Look Ahead (p. 190). Retrieved from http://www.wbcsdcement.org/technology",http://www.wbcsdcement.org/technology,World,,2 - Public Sector/ Multilateral Agency,2050,,95.0,kWh/tonne cement,0.095,TWh/MMt Cement,,, diff --git a/solution/altcement/vma_data/VMA_info.csv b/solution/altcement/vma_data/VMA_info.csv index c8762d541..283cd7a79 100644 --- a/solution/altcement/vma_data/VMA_info.csv +++ b/solution/altcement/vma_data/VMA_info.csv @@ -1,15 +1 @@ VMA number,Title on xls,Fixed Mean,Fixed High,Fixed Low -1,Current Adoption,0.0,0.0,0.0 -2,CONVENTIONAL First Cost per Implementation Unit,76750000.0,98500000.0,55000000.0 -3,SOLUTION First Cost per Implementation Unit,30645225.0,48649413.637178995,12641036.362821005 -4,CONVENTIONAL Lifetime Capacity,22.5,25.0,20.0 -5,SOLUTION Lifetime Capacity,45.0,60.0,30.0 -6,CONVENTIONAL Average Annual Use,1.0,1.0,1.0 -7,SOLUTION Average Annual Use,1.0,1.0,1.0 -12,CONVENTIONAL Total Energy Used per Functional Unit,0.15726303528681215,0.16576981681633496,0.14875625375728935 -15,CONVENTIONAL Fuel Consumed per Functional Unit,4558.606257936431,5125.543386326768,3991.669129546093 -17,CONVENTIONAL Direct Emissions per Functional Unit,505606.67,553000.0,458213.33999999997 -18,SOLUTION Direct Emissions per Functional Unit,278083.6685,278083.6685,278083.6685 -20,SOLUTION Indirect CO2 Emissions per Unit,36189.00000000001,36189.00000000001,36189.00000000001 -25,Discount Rate - Commercial,0.09219999999999999,0.1231735370921695,0.06122646290783049 -26,FlyAsh:OPC Replacement Ratio,0.4625,0.672782548015759,0.25221745198424106 diff --git a/tests/test_solutions.py b/tests/test_solutions.py index ec94f5bee..f19a77205 100644 --- a/tests/test_solutions.py +++ b/tests/test_solutions.py @@ -27,7 +27,7 @@ def test_solutions(name, constructor, scenarios): 'Grassland Protection', 'Peatland Protection', 'IP Forest Management', 'Tree Intercropping', 'Mangrove Protection', 'Conservation Agriculture', 'Forest Protection', 'Aircraft Fuel Efficiency', 'Bike Infrastructure', - 'Composting'] + 'Composting', 'Alternative Cements'] if obj.name not in skip: errstr = f"{obj.name}: {scenario} : {obj.ac.incorrect_cached_values}" assert len(obj.ac.incorrect_cached_values) == 0, errstr