diff --git a/config.yaml b/config.yaml
index 31020ef5..6fbeb07e 100644
--- a/config.yaml
+++ b/config.yaml
@@ -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:
diff --git a/scripts/build_industry_sector_ratios.py b/scripts/build_industry_sector_ratios.py
index baad720b..5d3acb9c 100644
--- a/scripts/build_industry_sector_ratios.py
+++ b/scripts/build_industry_sector_ratios.py
@@ -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]
 
diff --git a/scripts/prepare_sector_network.py b/scripts/prepare_sector_network.py
index 3e89146d..508e51ee 100644
--- a/scripts/prepare_sector_network.py
+++ b/scripts/prepare_sector_network.py
@@ -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"],