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Account for chemical industry process emissions more carefully

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Remove emissions from hydrogen production for ammonia (since H2 now
comes from electrolysis).

Allow process emissions from petrochemical production to be captured
(the carbon is not necessarily fossil, but could come from CCU).
This commit is contained in:
Tom Brown 2019-12-18 09:45:14 +01:00
parent 105aeba215
commit 52581466b6
3 changed files with 23 additions and 22 deletions
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4
config.yaml
View File

@ -146,7 +146,9 @@ industry:
'DRI_ratio' : 0.5 #ratio of today's blast-furnace steel (60% primary route, 40% secondary) to future assumption (30% primary, 70% secondary), transformed into DRI + electric arc
'H2_DRI' : 1.7 #H2 consumption in Direct Reduced Iron (DRI), MWh_H2/ton_Steel from Vogl et al (2018) doi:10.1016/j.jclepro.2018.08.279
'Al_to_scrap' : 0.5 # ratio of primary-route Aluminum transformed into scrap (today 40% to future 20% primary route)
'H2_for_NH3' : 85000 # H2 for NH3 transformed from SMR to electrolyzed-H2, in GWh/year following Lechtenböhmer(2016)
'H2_for_NH3' : 85000 # H2 in GWh/a for 17 MtNH3/a transformed from SMR to electrolyzed-H2, following Lechtenböhmer(2016)
'NH3_process_emissions' : 24.5 # in MtCO2/a from SMR for H2 production for NH3 from UNFCCC for 2015 for EU28
'petrochemical_process_emissions' : 25.5 # in MtCO2/a for petrochemical and other from UNFCCC for 2015 for EU28
plotting:
map:

9
scripts/build_industry_sector_ratios.py
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@ -26,7 +26,7 @@ sub_sheet_name_dict = { 'Iron and steel':'ISI',
'Wood and wood products': 'WWP',
'Other Industrial Sectors': 'OIS'}
index = ['elec','biomass','methane','hydrogen','heat','naphtha','process emission']
index = ['elec','biomass','methane','hydrogen','heat','naphtha','process emission','process emission from feedstock']
df = pd.DataFrame(index=index)
@ -302,7 +302,11 @@ s_out = excel_out.iloc[8:9,year]
assert sector in str(s_out.index)
df.loc['process emission',sector] += s_emi['Process emissions']/s_out.values # unit tCO2/t material
df.loc['process emission',sector] += (s_emi['Process emissions'] - snakemake.config["industry"]['petrochemical_process_emissions']*1e3 - snakemake.config["industry"]['NH3_process_emissions']*1e3)/s_out.values # unit tCO2/t material
#these are emissions originating from feedstock, i.e. could be non-fossil origin
df.loc['process emission from feedstock',sector] += (snakemake.config["industry"]['petrochemical_process_emissions']*1e3)/s_out.values # unit tCO2/t material
# final energy consumption per t
sources=['elec','biomass', 'methane', 'hydrogen', 'heat','naphtha']
@ -315,7 +319,6 @@ df.loc[sources,sector] = df.loc[sources,sector]*conv_factor/s_out.values# unit M
sector = 'Other chemicals'
df[sector] = 0
# read the corresponding lines
s_fec = excel_fec.iloc[58:64,year]

32
scripts/prepare_sector_network.py
View File

@ -1219,10 +1219,6 @@ def add_industry(network):
"Fischer-Tropsch",
carrier="Fischer-Tropsch")
network.add("Bus",
"Fischer-Tropsch-demand",
carrier="Fischer-Tropsch-demand")
#use madd to get carrier inserted
network.madd("Store",
["Fischer-Tropsch Store"],
@ -1251,29 +1247,29 @@ def add_industry(network):
efficiency2=-costs.at["oil",'CO2 intensity']*costs.at["Fischer-Tropsch",'efficiency'],
p_nom_extendable=True)
#NB: CO2 gets released again to atmosphere when plastics decay or kerosene is burned
network.madd("Link",
["Fischer-Tropsch-demand"],
bus0="Fischer-Tropsch",
bus1="Fischer-Tropsch-demand",
bus2="co2 atmosphere",
carrier="Fischer-Tropsch-demand",
efficiency=1.,
efficiency2=costs.at["oil",'CO2 intensity'],
p_nom_extendable=True)
network.madd("Load",
["naphtha for industry"],
bus="Fischer-Tropsch-demand",
bus="Fischer-Tropsch",
carrier="naphtha for industry",
p_set = industrial_demand.loc[nodes,"naphtha"].sum()/8760.)
network.madd("Load",
["kerosene for aviation"],
bus="Fischer-Tropsch-demand",
bus="Fischer-Tropsch",
carrier="kerosene for aviation",
p_set = nodal_energy_totals.loc[nodes,["total international aviation","total domestic aviation"]].sum(axis=1).sum()*1e6/8760.)
#NB: CO2 gets released again to atmosphere when plastics decay or kerosene is burned
#except for the process emissions when naphtha is used for petrochemicals, which can be captured with other industry process emissions
#tco2 per hour
co2 = network.loads.loc[["naphtha for industry","kerosene for aviation"],"p_set"].sum()*costs.at["oil",'CO2 intensity'] - industrial_demand.loc[nodes,"process emission from feedstock"].sum()/8760.
network.madd("Load",
["Fischer-Tropsch emissions"],
bus="co2 atmosphere",
carrier="Fischer-Tropsch emissions",
p_set=-co2)
network.madd("Load",
nodes,
suffix=" low-temperature heat for industry",
@ -1298,7 +1294,7 @@ def add_industry(network):
["process emissions"],
bus="process emissions",
carrier="process emissions",
p_set = -industrial_demand.loc[nodes,"process emission"].sum()/8760.)
p_set = -industrial_demand.loc[nodes,["process emission","process emission from feedstock"]].sum(axis=1).sum()/8760.)
network.madd("Link",
["process emissions"],