diff --git a/doc/release_notes.rst b/doc/release_notes.rst
index 918bb6dd..35e56660 100644
--- a/doc/release_notes.rst
+++ b/doc/release_notes.rst
@@ -14,6 +14,8 @@ Upcoming Release
 * PyPSA-EUR now supports the simultaneous execution of multiple scenarios. For this purpose, a scenarios.yaml file has been introduced which contains customizable scenario names with corresponding configuration overrides. To enable it, set the ``run: scenarios:`` key to ``True`` and define the scenario names to run under ``run: name:`` in the configuration file. The latter must be a subset of toplevel keys in the scenario file.
 
 
+* For industry distribution, use EPRTR as fallback if ETS data is not available.
+
 PyPSA-Eur 0.8.1 (27th July 2023)
 ================================
 
diff --git a/scripts/build_industrial_distribution_key.py b/scripts/build_industrial_distribution_key.py
index e93e43c2..979a1493 100644
--- a/scripts/build_industrial_distribution_key.py
+++ b/scripts/build_industrial_distribution_key.py
@@ -115,7 +115,9 @@ def build_nodal_distribution_key(hotmaps, regions, countries):
         facilities = hotmaps.query("country == @country and Subsector == @sector")
 
         if not facilities.empty:
-            emissions = facilities["Emissions_ETS_2014"]
+            emissions = facilities["Emissions_ETS_2014"].fillna(
+                hotmaps["Emissions_EPRTR_2014"]
+            )
             if emissions.sum() == 0:
                 key = pd.Series(1 / len(facilities), facilities.index)
             else:
diff --git a/scripts/build_sequestration_potentials.py b/scripts/build_sequestration_potentials.py
index e19a96da..f6ad3526 100644
--- a/scripts/build_sequestration_potentials.py
+++ b/scripts/build_sequestration_potentials.py
@@ -28,9 +28,7 @@ def allocate_sequestration_potential(
     overlay["share"] = area(overlay) / overlay["area_sqkm"]
     adjust_cols = overlay.columns.difference({"name", "area_sqkm", "geometry", "share"})
     overlay[adjust_cols] = overlay[adjust_cols].multiply(overlay["share"], axis=0)
-    gdf_regions = overlay.groupby("name").sum()
-    gdf_regions.drop(["area_sqkm", "share"], axis=1, inplace=True)
-    return gdf_regions.squeeze()
+    return overlay.dissolve("name", aggfunc="sum")[attr]
 
 
 if __name__ == "__main__":