add Perennialisation as Carbon Dioxide Removal Technology and Biogas producer

config/config.default.yaml

@@ -420,6 +420,10 @@ renewable:
     eia_correct_by_capacity: false
     eia_approximate_missing: false
 
+# docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#perennials
+perennials:
+  sequestration_co2: 2
+
 # docs in https://pypsa-eur.readthedocs.io/en/latest/configuration.html#conventional
 conventional:
   unit_commitment: false
@@ -837,6 +841,7 @@ sector:
   methanation: true
   coal_cc: false
   dac: true
+  perennials: false
   co2_vent: false
   heat_vent:
     urban central: true
@@ -1325,6 +1330,9 @@ data:
   instrat_co2_prices:
     source: primary
     version: latest
+  co2_removal_data:
+    source: primary
+    version: latest
   co2stop:
     source: archive
     version: latest

config/plotting.default.yaml

@@ -741,3 +741,4 @@ plotting:
     import NH3: '#e2ed74'
     import oil: '#93eda2'
     import methanol: '#87d0e6'
+    co2 perennials: '#008ffc'

config/schema.default.json

@@ -1044,6 +1044,26 @@
             }
           }
         },
+        "co2_removal_data": {
+          "description": "Configuration for a single data source.",
+          "properties": {
+            "source": {
+              "default": "archive",
+              "description": "Source of the data. 'archive' retrieves pre-built data, 'primary' retrieves from primary source.",
+              "enum": [
+                "archive",
+                "primary",
+                "build"
+              ],
+              "type": "string"
+            },
+            "version": {
+              "default": "latest",
+              "description": "Version of the data to use. Uses the specific 'version' for the selected 'source' or the dataset tagged 'latest' for this source.",
+              "type": "string"
+            }
+          }
+        },
         "co2stop": {
           "description": "Configuration for a single data source.",
           "properties": {
@@ -2925,6 +2945,16 @@
         }
       }
     },
+    "PerennialsConfig": {
+      "description": "Configuration for `perennials` settings.",
+      "properties": {
+        "sequestration_co2": {
+          "default": 2,
+          "description": "Tonnes of CO2 equivalent sequestered per hectare per year when 1st-generation biofuel cropland is converted to perennial grasses.",
+          "type": "number"
+        }
+      }
+    },
     "PypsaEurConfig": {
       "description": "Configuration for `pypsa_eur` settings.",
       "properties": {
@@ -4647,6 +4677,11 @@
           "description": "Add option for Direct Air Capture (DAC).",
           "type": "boolean"
         },
+        "perennials": {
+          "default": false,
+          "description": "Add option for perennialisation (converting 1st-generation biofuel cropland to perennial grasses) as a carbon dioxide removal (CDR) technology.",
+          "type": "boolean"
+        },
         "co2_vent": {
           "default": false,
           "description": "Add option for vent out CO2 from storages to the atmosphere.",
@@ -10091,6 +10126,16 @@
         }
       }
     },
+    "perennials": {
+      "description": "Configuration for `perennials` settings.",
+      "properties": {
+        "sequestration_co2": {
+          "default": 2,
+          "description": "Tonnes of CO2 equivalent sequestered per hectare per year when 1st-generation biofuel cropland is converted to perennial grasses.",
+          "type": "number"
+        }
+      }
+    },
     "conventional": {
       "additionalProperties": true,
       "description": "Configuration for `conventional` settings.",
@@ -11139,6 +11184,11 @@
           "description": "Add option for Direct Air Capture (DAC).",
           "type": "boolean"
         },
+        "perennials": {
+          "default": false,
+          "description": "Add option for perennialisation (converting 1st-generation biofuel cropland to perennial grasses) as a carbon dioxide removal (CDR) technology.",
+          "type": "boolean"
+        },
         "co2_vent": {
           "default": false,
           "description": "Add option for vent out CO2 from storages to the atmosphere.",
@@ -12901,6 +12951,26 @@
             }
           }
         },
+        "co2_removal_data": {
+          "description": "Configuration for a single data source.",
+          "properties": {
+            "source": {
+              "default": "archive",
+              "description": "Source of the data. 'archive' retrieves pre-built data, 'primary' retrieves from primary source.",
+              "enum": [
+                "archive",
+                "primary",
+                "build"
+              ],
+              "type": "string"
+            },
+            "version": {
+              "default": "latest",
+              "description": "Version of the data to use. Uses the specific 'version' for the selected 'source' or the dataset tagged 'latest' for this source.",
+              "type": "string"
+            }
+          }
+        },
         "co2stop": {
           "description": "Configuration for a single data source.",
           "properties": {

data/versions.csv

@@ -11,6 +11,7 @@ bidding_zones_electricitymaps,v1.238.0,primary,latest supported,2026-01-22,,http
 bidding_zones_electricitymaps,v1.238.0,archive,latest supported,2026-01-22,,https://data.pypsa.org/workflows/eur/bidding_zones_electricitymaps/v1.238.0/world.geojson
 bidding_zones_entsoepy,v0.6.18,primary,latest supported,2026-01-22,,https://raw.githubusercontent.com/EnergieID/entsoe-py/refs/tags/V0.6.18/entsoe/geo/geojson
 bidding_zones_entsoepy,v0.6.18,archive,latest supported,2026-01-22,,https://data.pypsa.org/workflows/eur/bidding_zones_entsoepy/v0.6.18
+co2_removal_data,v1.0.1,primary,latest supported,2026-06-22,"Afforestation and perennialisation input data for the CDR sector technologies, archived from https://github.com/BertoGBG/CO2-removal",https://zenodo.org/records/20799337/files/BertoGBG/CO2-removal-v1.0.1.zip
 co2stop,26-august-2020,primary,latest supported,2025-12-02,,https://setis.ec.europa.eu/document/download/786a884f-0b33-4789-b744-28004b16bd1a_en?filename=co2jrc_openformats.zip
 co2stop,26-august-2020,archive,latest supported,2026-01-13,,https://data.pypsa.org/workflows/eur/co2stop/26-august-2020/co2jrc_openformats.zip
 copernicus_land_cover,v3.0.1,primary,latest supported,2025-12-02,"The primary is already from Zenodo, documentation in https://zenodo.org/records/4723921",https://zenodo.org/records/3939050/files/PROBAV_LC100_global_v3.0.1_2019-nrt_Discrete-Classification-map_EPSG-4326.tif

doc/release_notes.md

@@ -5,6 +5,7 @@
 
 <!-- Upcoming Release -->
 <!-- ================= -->
+* feat: Add perennialisation as a carbon dioxide removal (CDR) technology, converting 1st-generation biofuel cropland to perennial grasses, with node-level potential derived from NUTS2-resolved Eurostat crop yields ([#2143](https://github.com/PyPSA/pypsa-eur/issues/2143)).
 
 ## PyPSA-Eur v2026.08.0 (19th August 2026)
 

doc/sector.md

@@ -35,6 +35,14 @@ Having downloaded the necessary data,
 
 ::: build_biomass_potentials
 
+## Rule `build_perennials_yields_eurostat_average`
+
+::: build_perennials_yields_eurostat_average
+
+## Rule `build_perennials_yields`
+
+::: build_perennials_yields
+
 ## Rule `build_egs_potentials`
 
 ::: build_egs_potentials

rules/build_sector.smk

@@ -953,6 +953,38 @@ rule build_biomass_potentials:
         scripts("build_biomass_potentials.py")
 
 
+rule build_perennials_yields_eurostat_average:
+    input:
+        nuts2021=rules.retrieve_eu_nuts_2021.output.shapes_level_2,
+        crops_nuts2=rules.retrieve_co2_removal_data.output.eurostat_crops_nuts2,
+        crops_nuts0=rules.retrieve_co2_removal_data.output.eurostat_crops_nuts0,
+        costs=resources(f"costs_{config['costs']['year']}_processed.csv"),
+    output:
+        yields_all=resources("perennials_yields_1G_biofuels.csv"),
+    log:
+        logs("build_perennials_yields_eurostat_average.log"),
+    script:
+        scripts("build_perennials_yields_eurostat_average.py")
+
+
+rule build_perennials_yields:
+    input:
+        nuts2=rules.retrieve_eu_nuts_2021.output.shapes_level_2,
+        country_shapes=resources("country_shapes.geojson"),
+        perennials_yields_1G_biofuels=resources("perennials_yields_1G_biofuels.csv"),
+        regions_onshore=resources("regions_onshore_base_s_{clusters}.geojson"),
+    output:
+        csv_file=resources("perennials_yields_1G_biofuels_s_{clusters}.csv"),
+    log:
+        logs("build_perennials_yields_s_{clusters}.log"),
+    resources:
+        mem_mb=8000,
+    params:
+        biomass=config_provider("biomass"),
+    script:
+        scripts("build_perennials_yields.py")
+
+
 rule build_biomass_transport_costs:
     input:
         sc1="data/biomass_transport_costs_supplychain1.csv",
@@ -1722,6 +1754,11 @@ rule prepare_sector_network:
             if config_provider("sector", "district_heating", "ates", "enable")(w)
             else []
         ),
+        perennials_yields_1G_biofuels=lambda w: (
+            resources("perennials_yields_1G_biofuels_s_{clusters}.csv")
+            if config_provider("sector", "perennials")(w)
+            else []
+        ),
     output:
         resources(
             "networks/base_s_{clusters}_{opts}_{sector_opts}_{planning_horizons}.nc"

rules/retrieve.smk

@@ -1629,3 +1629,61 @@ if (MOBILITY_PROFILES_DATASET := dataset_version("mobility_profiles"))["source"]
         run:
             copy2(input["kfz"], output["kfz"])
             copy2(input["pkw"], output["pkw"])
+
+
+if (CO2_REMOVAL_DATASET := dataset_version("co2_removal_data"))["source"] in [
+    "primary",
+    "archive",
+]:
+
+    rule retrieve_co2_removal_data:
+        input:
+            zip=storage(CO2_REMOVAL_DATASET["url"]),
+        output:
+            afforestation_nuts_biomass_densities=resources(
+                "afforestation_nuts_biomass_densities.xlsx"
+            ),
+            afforestation_nuts2_afforestation_rates=resources(
+                "afforestation_rates_nuts2_full.csv"
+            ),
+            afforestation_nuts2_monthly_weights=resources(
+                "afforestation_nuts2_monthly_weights.csv"
+            ),
+            eurostat_crops_nuts2=resources("eurostat_apro_cpshr_nuts2_raw.csv"),
+            eurostat_crops_nuts0=resources("eurostat_apro_cpshr_nuts0_raw.csv"),
+        retries: 2
+        message:
+            "Downloading carbon dioxide removal data (afforestation, perennialisation inputs)"
+        run:
+            with ZipFile(input.zip) as z:
+                # GitHub's release archive nests everything under a single
+                # top-level "<owner>-<repo>-<commit-sha>/" folder whose name
+                # changes with every release, so resolve it at runtime.
+                top_dir = z.namelist()[0].split("/")[0]
+                for src_path, dest in [
+                    (
+                        "outputs/afforestation/afforestation_nuts_biomass_densities.xlsx",
+                        output.afforestation_nuts_biomass_densities,
+                    ),
+                    (
+                        "outputs/afforestation/afforestation_rates_nuts2_full.csv",
+                        output.afforestation_nuts2_afforestation_rates,
+                    ),
+                    (
+                        "outputs/afforestation/afforestation_nuts2_monthly_weights.csv",
+                        output.afforestation_nuts2_monthly_weights,
+                    ),
+                    (
+                        "outputs/perennialisation/eurostat_apro_cpshr_nuts2_raw.csv",
+                        output.eurostat_crops_nuts2,
+                    ),
+                    (
+                        "outputs/perennialisation/eurostat_apro_cpshr_nuts0_raw.csv",
+                        output.eurostat_crops_nuts0,
+                    ),
+                ]:
+                    with (
+                        z.open(f"{top_dir}/{src_path}") as src,
+                        open(dest, "wb") as dst,
+                    ):
+                        dst.write(src.read())

scripts/_helpers.py

@@ -1093,6 +1093,51 @@ def load_costs(cost_file: str) -> pd.DataFrame:
     return pd.read_csv(cost_file, index_col=0)
 
 
+# 1G biofuel crop groups and their target biomass class names.
+# In the upstream default config these sit in "not included".
+# When sector: perennials=True, resolve_biomass_classes() moves them automatically.
+ONE_G_BIOFUEL_CLASSES = {
+    "Bioethanol barley, wheat, grain maize, oats, other cereals and rye": "biofuels_1G_bioethanol_cereals",
+    "Sugar from sugar beet": "biofuels_1G_bioethanol_sugar",
+    "Rape seed": "biofuels_1G_biodiesel",
+    "Sunflower, soya seed ": "biofuels_1G_biodiesel",
+}
+
+
+def resolve_biomass_classes(classes, perennials_enabled):
+    """
+    Auto-reallocate 1G biofuel crop groups from 'not included' into their
+    biofuels_1G_* target classes when perennials are enabled.
+
+    Cases:
+      perennials=False  → return classes unchanged.
+      perennials=True, all groups in 'not included' → move them (normal case).
+      perennials=True, no groups in 'not included' → raise AssertionError.
+      perennials=True, some groups elsewhere → move available ones, warn about rest.
+    """
+    if not perennials_enabled:
+        return classes
+    classes = copy.deepcopy(classes)
+    not_incl = classes.get("not included", [])
+    in_ni = [g for g in ONE_G_BIOFUEL_CLASSES if g in not_incl]
+    elsewhere = [g for g in ONE_G_BIOFUEL_CLASSES if g not in not_incl]
+    if not in_ni:
+        raise AssertionError(
+            "sector: perennials=true but no 1G-biofuel groups are in "
+            "biomass: classes: 'not included'. Restore upstream defaults "
+            "so the groups can be reallocated automatically."
+        )
+    if elsewhere:
+        logger.warning(
+            "perennials: 1G groups already allocated outside 'not included' "
+            f"— skipped (running perennials only for available groups): {elsewhere}"
+        )
+    for g in in_ni:
+        classes["not included"].remove(g)
+        classes.setdefault(ONE_G_BIOFUEL_CLASSES[g], []).append(g)
+    return classes
+
+
 def _simplify_polys(
     polys, minarea=100 * 1e6, maxdistance=None, tolerance=None, filterremote=True
 ):  # 100*1e6 = 100 km² if CRS is DISTANCE_CRS

scripts/build_biomass_potentials.py

@@ -12,7 +12,11 @@
 import numpy as np
 import pandas as pd
 
-from scripts._helpers import configure_logging, set_scenario_config
+from scripts._helpers import (
+    configure_logging,
+    resolve_biomass_classes,
+    set_scenario_config,
+)
 
 logger = logging.getLogger(__name__)
 AVAILABLE_BIOMASS_YEARS = [2010, 2020, 2030, 2040, 2050]
@@ -184,17 +188,15 @@ def disaggregate_nuts0(bio):
     return bio
 
 
-def build_nuts2_shapes():
+def build_nuts2_shapes(nuts2_fn, country_shapes_fn):
     """
     - load NUTS2 geometries
     - add RS, AL, BA country shapes (not covered in NUTS 2013)
     - consistently name ME, MK
     """
-    nuts2 = gpd.GeoDataFrame(
-        gpd.read_file(snakemake.input.nuts2).set_index("NUTS_ID").geometry
-    )
+    nuts2 = gpd.GeoDataFrame(gpd.read_file(nuts2_fn).set_index("NUTS_ID").geometry)
 
-    countries = gpd.read_file(snakemake.input.country_shapes).set_index("name")
+    countries = gpd.read_file(country_shapes_fn).set_index("name")
     missing_iso2 = countries.index.intersection(["AL", "RS", "XK", "BA"])
     missing = countries.loc[missing_iso2]
 
@@ -382,7 +384,7 @@ def add_unsustainable_potentials(df, input_eurostat):
 
     enspreso = disaggregate_nuts0(enspreso)
 
-    nuts2 = build_nuts2_shapes()
+    nuts2 = build_nuts2_shapes(snakemake.input.nuts2, snakemake.input.country_shapes)
 
     df_nuts2 = gpd.GeoDataFrame(nuts2.geometry).join(enspreso)
 
@@ -392,7 +394,10 @@ def add_unsustainable_potentials(df, input_eurostat):
 
     df.to_csv(snakemake.output.biomass_potentials_all)
 
-    grouper = {v: k for k, vv in params["classes"].items() for v in vv}
+    classes = resolve_biomass_classes(
+        params["classes"], snakemake.config["sector"].get("perennials", False)
+    )
+    grouper = {v: k for k, vv in classes.items() for v in vv}
     df = df.T.groupby(grouper).sum().T
 
     input_eurostat = snakemake.input.eurostat