Separate basic chemicals into HVC, chlorine, methanol and ammonia

config.default.yaml

@@ -72,7 +72,7 @@ electricity:
 
 # regulate what components with which carriers are kept from PyPSA-Eur;
 # some technologies are removed because they are implemented differently
-# (e.g. battery or H2 storage) or have different year-dependent costs 
+# (e.g. battery or H2 storage) or have different year-dependent costs
 # in PyPSA-Eur-Sec
 pypsa_eur:
   Bus:
@@ -270,10 +270,23 @@ industry:
   MWh_elec_per_tNH3_electrolysis: 1.17 # from https://doi.org/10.1016/j.joule.2018.04.017 Table 13 (air separation and HB)
   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
-  HVC_primary_fraction: 1.0 #fraction of current non-ammonia basic chemicals produced via primary route
+  HVC_primary_fraction: 1. # fraction of today's HVC produced via primary route
+  HVC_mechanical_recycling_fraction: 0. # fraction of today's HVC produced via mechanical recycling
+  HVC_chemical_recycling_fraction: 0. # fraction of today's HVC produced via chemical recycling
+  HVC_production_today: 52. # MtHVC/a from DECHEMA (2017), Figure 16, page 107; includes ethylene, propylene and BTX
+  MWh_elec_per_tHVC_mechanical_recycling: 3. # estimate
+  MWh_elec_per_tHVC_chemical_recycling: 6.9 # Material Economics (2019), page 125; based on pyrolysis and steam cracking
+  chlorine_production_today: 9.58 # MtCl/a from DECHEMA (2017), Table 7, page 43
+  MWh_elec_per_tCl: 3.6 # DECHEMA (2017), Table 6, page 43
+  MWh_H2_per_tCl: -0.9372  # DECHEMA (2017), page 43; negative since hydrogen produced in chloralkali process
+  methanol_production_today: 1.5 # MtMeOH/a from DECHEMA (2017), page 62
+  MWh_elec_per_tMeOH: 0.167 # DECHEMA (2017), Table 14, page 65
+  MWh_CH4_per_tMeOH: 10.25 # DECHEMA (2017), Table 14, page 65
   hotmaps_locate_missing: false
   reference_year: 2015
-
+  # references:
+  # DECHEMA (2017): https://dechema.de/dechema_media/Downloads/Positionspapiere/Technology_study_Low_carbon_energy_and_feedstock_for_the_European_chemical_industry-p-20002750.pdf
+  # Material Economics (2019): https://materialeconomics.com/latest-updates/industrial-transformation-2050
 
 costs:
   lifetime: 25 #default lifetime
@@ -335,7 +348,7 @@ solving:
 
 plotting:
   map:
-    boundaries: [-11, 30, 34, 71] 
+    boundaries: [-11, 30, 34, 71]
     color_geomap:
       ocean: white
       land: whitesmoke

scripts/build_industrial_energy_demand_per_country_today.py

@@ -114,6 +114,11 @@ def add_non_eu28_industrial_energy_demand(demand):
     fn = snakemake.input.industrial_production_per_country
     production = pd.read_csv(fn, index_col=0) / 1e3
 
+    #recombine HVC, Chlorine and Methanol to Basic chemicals (without ammonia)
+    chemicals = ["HVC", "Chlorine", "Methanol"]
+    production["Basic chemicals (without ammonia)"] = production[chemicals].sum(axis=1)
+    production.drop(columns=chemicals, inplace=True)
+
     eu28_production = production.loc[eu28].sum()
     eu28_energy = demand.groupby(level=1).sum()
     eu28_averages = eu28_energy / eu28_production

scripts/build_industrial_production_per_country.py

@@ -179,8 +179,8 @@ def industry_production(countries):
     return demand
 
 
-def add_ammonia_demand_separately(demand):
-    """Include ammonia demand separately and remove ammonia from basic chemicals."""
+def separate_basic_chemicals(demand):
+    """Remove ammonia, chlorine and methanol from basic chemicals to get HVC."""
 
     ammonia = pd.read_csv(snakemake.input.ammonia_production, index_col=0)
 
@@ -198,9 +198,16 @@ def add_ammonia_demand_separately(demand):
     # EE, HR and LT got negative demand through subtraction - poor data
     demand['Basic chemicals'].clip(lower=0., inplace=True)
 
-    to_rename = {"Basic chemicals": "Basic chemicals (without ammonia)"}
-    demand.rename(columns=to_rename, inplace=True)
+    demand.insert(2, "HVC", 0.)
+    demand.insert(3, "Chlorine", 0.)
+    demand.insert(4, "Methanol", 0.)
 
+    # assume HVC, methanol, chlorine production proportional to non-ammonia basic chemicals
+    demand["HVC"] = config["HVC_production_today"]*1e3/demand["Basic chemicals"].sum()*demand["Basic chemicals"]
+    demand["Chlorine"] = config["chlorine_production_today"]*1e3/demand["Basic chemicals"].sum()*demand["Basic chemicals"]
+    demand["Methanol"] = config["methanol_production_today"]*1e3/demand["Basic chemicals"].sum()*demand["Basic chemicals"]
+
+    demand.drop(columns=["Basic chemicals"], inplace=True)
 
 if __name__ == '__main__':
     if 'snakemake' not in globals():
@@ -211,12 +218,14 @@ def add_ammonia_demand_separately(demand):
 
     year = snakemake.config['industry']['reference_year']
 
+    config = snakemake.config["industry"]
+
     jrc_dir = snakemake.input.jrc
     eurostat_dir = snakemake.input.eurostat
 
     demand = industry_production(countries)
 
-    add_ammonia_demand_separately(demand)
+    separate_basic_chemicals(demand)
 
     fn = snakemake.output.industrial_production_per_country
     demand.to_csv(fn, float_format='%.2f')

scripts/build_industrial_production_per_country_tomorrow.py

@@ -39,11 +39,14 @@
 
     al_primary_fraction = get(config["Al_primary_fraction"], investment_year)
     fraction_persistent_primary = al_primary_fraction * total_aluminium.sum() / production[key_pri].sum()
-    
+
     production[key_pri] = fraction_persistent_primary * production[key_pri]
     production[key_sec] = total_aluminium - production[key_pri]
 
-    production["Basic chemicals (without ammonia)"] *= config['HVC_primary_fraction']
+    production.insert(4, "HVC (mechanical recycling)", config["HVC_mechanical_recycling_fraction"]*production["HVC"])
+    production.insert(5, "HVC (chemical recycling)", config["HVC_chemical_recycling_fraction"]*production["HVC"])
+
+    production["HVC"] *= config['HVC_primary_fraction']
 
     fn = snakemake.output.industrial_production_per_country_tomorrow
     production.to_csv(fn, float_format='%.2f')

scripts/build_industrial_production_per_node.py

@@ -9,7 +9,11 @@
     'Integrated steelworks': 'Iron and steel',
     'DRI + Electric arc': 'Iron and steel',
     'Ammonia': 'Chemical industry',
-    'Basic chemicals (without ammonia)': 'Chemical industry',
+    'HVC': 'Chemical industry',
+    'HVC (mechanical recycling)': 'Chemical industry',
+    'HVC (chemical recycling)': 'Chemical industry',
+    'Methanol': 'Chemical industry',
+    'Chlorine': 'Chemical industry',
     'Other chemicals': 'Chemical industry',
     'Pharmaceutical products etc.': 'Chemical industry',
     'Cement': 'Cement',
@@ -40,12 +44,12 @@ def build_nodal_industrial_production():
 
     countries = keys.country.unique()
     sectors = industrial_production.columns
-    
+
     for country, sector in product(countries, sectors):
 
         buses = keys.index[keys.country == country]
         mapping = sector_mapping.get(sector, "population")
-        
+
         key = keys.loc[buses, mapping]
         nodal_production.loc[buses, sector] = industrial_production.at[country, sector] * key
 

scripts/build_industry_sector_ratios.py

@@ -279,7 +279,7 @@ def chemicals_industry():
 
     df = pd.DataFrame(index=index)
 
-    # Basid chemicals
+    # Basic chemicals
 
     sector = "Basic chemicals"
 
@@ -374,52 +374,84 @@ def chemicals_industry():
     # putting in ammonia demand for H2 and electricity separately
 
     s_emi = idees["emi"][3:57]
-    s_out = idees["out"][8:9]
     assert s_emi.index[0] == sector
-    assert sector in str(s_out.index)
-
-    ammonia = pd.read_csv(snakemake.input.ammonia_production, index_col=0)
-
-    # ktNH3/a
-    ammonia_total = ammonia.loc[ammonia.index.intersection(eu28), str(year)].sum()
 
-    s_out -= ammonia_total
+    # convert from MtHVC/a to ktHVC/a
+    s_out = config["HVC_production_today"]*1e3
 
     # tCO2/t material
     df.loc["process emission", sector] += (
         s_emi["Process emissions"]
         - config["petrochemical_process_emissions"] * 1e3
         - config["NH3_process_emissions"] * 1e3
-    ) / s_out.values
+    ) / s_out
 
     # emissions originating from feedstock, could be non-fossil origin
     # tCO2/t material
     df.loc["process emission from feedstock", sector] += (
         config["petrochemical_process_emissions"] * 1e3
-    ) / s_out.values
+    ) / s_out
 
     # convert from ktoe/a to GWh/a
     sources = ["elec", "biomass", "methane", "hydrogen", "heat", "naphtha"]
     df.loc[sources, sector] *= toe_to_MWh
 
+    # subtract ammonia energy demand
+    ammonia = pd.read_csv(snakemake.input.ammonia_production, index_col=0)
+    # ktNH3/a
+    ammonia_total = ammonia.loc[ammonia.index.intersection(eu28), str(year)].sum()
     df.loc["methane", sector] -= ammonia_total * config["MWh_CH4_per_tNH3_SMR"]
     df.loc["elec", sector] -= ammonia_total * config["MWh_elec_per_tNH3_SMR"]
 
+    # subtract chlorine demand
+    chlorine_total = config["chlorine_production_today"]
+    df.loc["hydrogen", sector] -= chlorine_total * config["MWh_H2_per_tCl"]
+    df.loc["elec", sector] -= chlorine_total * config["MWh_elec_per_tCl"]
+
+    # subtract methanol demand
+    methanol_total = config["methanol_production_today"]
+    df.loc["methane", sector] -= methanol_total * config["MWh_CH4_per_tMeOH"]
+    df.loc["elec", sector] -= methanol_total * config["MWh_elec_per_tMeOH"]
+
     # MWh/t material
-    df.loc[sources, sector] = df.loc[sources, sector] / s_out.values
+    df.loc[sources, sector] = df.loc[sources, sector] / s_out
 
-    to_rename = {sector: f"{sector} (without ammonia)"}
+    to_rename = {sector: "HVC"}
     df.rename(columns=to_rename, inplace=True)
 
-    # Ammonia
+    # HVC mechanical recycling
 
-    sector = "Ammonia"
+    sector = "HVC (mechanical recycling)"
+    df[sector] = 0.0
+    df.loc["elec", sector] = config["MWh_elec_per_tHVC_mechanical_recycling"]
 
+    # HVC chemical recycling
+
+    sector = "HVC (chemical recycling)"
     df[sector] = 0.0
+    df.loc["elec", sector] = config["MWh_elec_per_tHVC_chemical_recycling"]
 
+    # Ammonia
+
+    sector = "Ammonia"
+    df[sector] = 0.0
     df.loc["hydrogen", sector] = config["MWh_H2_per_tNH3_electrolysis"]
     df.loc["elec", sector] = config["MWh_elec_per_tNH3_electrolysis"]
 
+    # Chlorine
+
+    sector = "Chlorine"
+    df[sector] = 0.0
+    df.loc["hydrogen", sector] = config["MWh_H2_per_tCl"]
+    df.loc["elec", sector] = config["MWh_elec_per_tCl"]
+
+    # Methanol
+
+    sector = "Methanol"
+    df[sector] = 0.0
+    df.loc["methane", sector] = config["MWh_CH4_per_tMeOH"]
+    df.loc["elec", sector] = config["MWh_elec_per_tMeOH"]
+
     # Other chemicals
 
     sector = "Other chemicals"