diff --git a/Snakefile b/Snakefile
index 9400d301..a16e60f0 100644
--- a/Snakefile
+++ b/Snakefile
@@ -160,6 +160,7 @@ rule build_energy_totals:
         co2="data/eea/UNFCCC_v23.csv",
         swiss="data/switzerland-sfoe/switzerland-new_format.csv",
         idees="data/jrc-idees-2015",
+        district_heat_share='data/district_heat_share.csv',
         eurostat=input_eurostat
     output:
         energy_name='resources/energy_totals.csv',
@@ -339,7 +340,6 @@ rule prepare_sector_network:
         energy_totals_name='resources/energy_totals.csv',
         co2_totals_name='resources/co2_totals.csv',
         transport_name='resources/transport_data.csv',
-        dh_share = "data/district_heat_share.csv",
         traffic_data_KFZ="data/emobility/KFZ__count",
         traffic_data_Pkw="data/emobility/Pkw__count",
         biomass_potentials='resources/biomass_potentials.csv',
diff --git a/scripts/build_energy_totals.py b/scripts/build_energy_totals.py
index aec1c61b..751f23bf 100644
--- a/scripts/build_energy_totals.py
+++ b/scripts/build_energy_totals.py
@@ -212,6 +212,12 @@ def idees_per_country(ct, year):
     assert df.index[47] == "Electricity"
     ct_totals["electricity residential"] = df[47]
 
+    assert df.index[46] == "Derived heat"
+    ct_totals["Derived heat residential"] = df[46]
+
+    assert df.index[50] == 'Thermal uses'
+    ct_totals["Thermal uses residential"] = df[50]
+
     # services
 
     df = pd.read_excel(fn_services, "SER_hh_fec", index_col=0)[year]
@@ -239,6 +245,12 @@ def idees_per_country(ct, year):
     assert df.index[50] == "Electricity"
     ct_totals["electricity services"] = df[50]
 
+    assert df.index[49] == "Derived heat"
+    ct_totals["Derived heat services"] = df[49]
+
+    assert df.index[53] == 'Thermal uses'
+    ct_totals["Thermal uses services"] = df[53]
+
     # transport
 
     df = pd.read_excel(fn_transport, "TrRoad_ene", index_col=0)[year]
@@ -342,6 +354,7 @@ def build_idees(countries, year):
     with mp.Pool(processes=nprocesses) as pool:
         totals_list = list(tqdm(pool.imap(func, countries), **tqdm_kwargs))
 
+
     totals = pd.concat(totals_list, axis=1)
 
     # convert ktoe to TWh
@@ -351,6 +364,13 @@ def build_idees(countries, year):
     # convert TWh/100km to kWh/km
     totals.loc["passenger car efficiency"] *= 10
 
+    # district heating share
+    district_heat = totals.loc[["Derived heat residential",
+                                "Derived heat services"]].sum()
+    total_heat = totals.loc[["Thermal uses residential",
+                             "Thermal uses services"]].sum()
+    totals.loc["district heat share"] = district_heat.div(total_heat)
+
     return totals.T
 
 
@@ -493,7 +513,7 @@ def build_energy_totals(countries, eurostat, swiss, idees):
 
     for purpose in ["passenger", "freight"]:
         attrs = [f"total domestic aviation {purpose}", f"total international aviation {purpose}"]
-        df.loc[missing, f"total aviation {purpose}"] = df.loc[missing, attrs].sum(axis=1)   
+        df.loc[missing, f"total aviation {purpose}"] = df.loc[missing, attrs].sum(axis=1)
 
     if "BA" in df.index:
         # fill missing data for BA (services and road energy data)
@@ -502,6 +522,14 @@ def build_energy_totals(countries, eurostat, swiss, idees):
         ratio = df.at["BA", "total residential"] / df.at["RS", "total residential"]
         df.loc['BA', missing] = ratio * df.loc["RS", missing]
 
+    # Missing district heating share
+    dh_share = pd.read_csv(snakemake.input.district_heat_share,
+                           index_col=0, usecols=[0, 1])
+    # make conservative assumption and take minimum from both data sets
+    df["district heat share"] = (pd.concat([df["district heat share"],
+                                            dh_share.reindex(index=df.index)/100],
+                                           axis=1).min(axis=1))
+
     return df