Correct biofuels LCIs.

polca · Jun 25, 2023 · 3a6f816 · 3a6f816
1 parent ed9937f
commit 3a6f816
Show file tree

Hide file tree

Showing 8 changed files with 66 additions and 38 deletions.
diff --git a/premise/data/additional_inventories/lci-biofuels.xlsx b/premise/data/additional_inventories/lci-biofuels.xlsx
diff --git a/premise/data/iam_output_files/image_SSP1-Base.csv b/premise/data/iam_output_files/image_SSP1-Base.csv
diff --git a/premise/data/iam_output_files/image_SSP2-Base.csv b/premise/data/iam_output_files/image_SSP2-Base.csv
diff --git a/premise/data/iam_output_files/image_SSP2-RCP19.csv b/premise/data/iam_output_files/image_SSP2-RCP19.csv
diff --git a/premise/data/iam_output_files/image_SSP2-RCP26.csv b/premise/data/iam_output_files/image_SSP2-RCP26.csv
diff --git a/premise/data_collection.py b/premise/data_collection.py
@@ -544,10 +544,10 @@ def __init__(
         )
 
         self.land_use = self.__get_iam_production_volumes(
-            data=data, input_vars=land_use_vars
+            data=data, input_vars=land_use_vars, fill=True
         )
         self.land_use_change = self.__get_iam_production_volumes(
-            data=data, input_vars=land_use_change_vars
+            data=data, input_vars=land_use_change_vars, fill=True
         )
 
         self.trsp_cars = get_vehicle_fleet_composition(self.model, vehicle_type="car")
@@ -935,7 +935,7 @@ def __get_carbon_capture_rate(
 
         return rate
 
-    def __get_iam_production_volumes(self, input_vars, data) -> [xr.DataArray, None]:
+    def __get_iam_production_volumes(self, input_vars, data, fill: bool = False) -> [xr.DataArray, None]:
         """
         Returns n xarray with production volumes for different sectors:
         electricity, steel, cement, fuels.
@@ -976,6 +976,16 @@ def __get_iam_production_volumes(self, input_vars, data) -> [xr.DataArray, None]
             k for k, v in input_vars.items() if v in available_vars
         ]
 
+        if fill:
+            # if fill, we fill zero values
+            # with the nearest year's value
+            # first, convert zero values to NaNs
+            data_to_return = data_to_return.where(data_to_return != 0)
+            # then, backfill
+            data_to_return = data_to_return.bfill(dim="year")
+            # then, forward fill
+            data_to_return = data_to_return.ffill(dim="year")
+
         return data_to_return
 
     def get_external_data(self, datapackages):

diff --git a/premise/fuels.py b/premise/fuels.py
@@ -1481,11 +1481,16 @@ def adjust_land_use(self, dataset: dict, region: str, crop_type: str) -> dict:
         :return: adjusted dataset
 
         """
+        string = ""
+        land_use = 0
+
         for exc in dataset["exchanges"]:
             # we adjust the land use
             if exc["type"] == "biosphere" and exc["name"].startswith("Occupation"):
-                # lower heating value, dry basis
-                lhv_ar = dataset["LHV [MJ/kg dry]"]
+                if "LHV [MJ/kg as received]" in dataset:
+                    lower_heating_value = dataset["LHV [MJ/kg as received]"]
+                else:
+                    lower_heating_value = dataset.get("LHV [MJ/kg dry]", 0)
 
                 # Ha/GJ
                 land_use = (
@@ -1494,33 +1499,39 @@ def adjust_land_use(self, dataset: dict, region: str, crop_type: str) -> dict:
                     .values
                 )
 
+                # replace NA values with 0
+                if np.isnan(land_use):
+                    land_use = 0
+
                 if land_use > 0:
                     # HA to m2
                     land_use *= 10000
                     # m2/GJ to m2/MJ
                     land_use /= 1000
                     # m2/kg, as received
-                    land_use *= lhv_ar
+                    land_use *= lower_heating_value
                     # update exchange value
                     exc["amount"] = float(land_use)
 
-                string = (
-                    f"The land area occupied has been modified to {land_use}, "
-                    f"to be in line with the scenario {self.scenario} of {self.model.upper()} "
-                    f"in {self.year} in the region {region}. "
-                )
-                if "comment" in dataset:
-                    dataset["comment"] += string
-                else:
-                    dataset["comment"] = string
+                    string = (
+                        f"The land area occupied has been modified to {land_use}, "
+                        f"to be in line with the scenario {self.scenario} of {self.model.upper()} "
+                        f"in {self.year} in the region {region}. "
+                    )
 
-                if "log parameters" not in dataset:
-                    dataset["log parameters"] = {}
-                dataset["log parameters"].update(
-                    {
-                        "land footprint": land_use,
-                    }
-                )
+        if string and land_use:
+            if "comment" in dataset:
+                dataset["comment"] += string
+            else:
+                dataset["comment"] = string
+
+            if "log parameters" not in dataset:
+                dataset["log parameters"] = {}
+            dataset["log parameters"].update(
+                {
+                    "land footprint": land_use,
+                }
+            )
 
         return dataset
 
@@ -1551,13 +1562,20 @@ def adjust_land_use_change_emissions(
             .values
         )
 
+        # replace NA values with 0
+        if np.isnan(land_use_co2):
+            land_use_co2 = 0
+
         if land_use_co2 > 0:
             # lower heating value, as received
-            lower_heating_value_as_received = dataset["LHV [MJ/kg dry]"]
+            if "LHV [MJ/kg as received]" in dataset:
+                lower_heating_value = dataset["LHV [MJ/kg as received]"]
+            else:
+                lower_heating_value = dataset.get("LHV [MJ/kg dry]", 0)
 
             # kg CO2/MJ
             land_use_co2 /= 1000
-            land_use_co2 *= lower_heating_value_as_received
+            land_use_co2 *= lower_heating_value
 
             land_use_co2_exc = {
                 "uncertainty type": 0,

diff --git a/premise/iam_variables_mapping/crops_variables.yaml b/premise/iam_variables_mapping/crops_variables.yaml
@@ -11,9 +11,9 @@ sugar:
       temperate: sugarbeet
       tropical: sugarcane
   land_use:
-    image: Land Use|Average|Biomass|Sugar
+    image: Land Use|Marginal|Biomass|Sugar
   land_use_change:
-    image: Emission Factor|CO2|Energy|Supply|Biomass|Average|Sugar
+    image: Emission Factor|CO2|Energy|Supply|Biomass|Marginal|Sugar
 oil:
   crop_type:
     image:
@@ -23,9 +23,9 @@ oil:
       temperate: rapeseed
       tropical: palm oil
   land_use:
-    image: Land Use|Average|Biomass|OilCrop
+    image: Land Use|Marginal|Biomass|OilCrop
   land_use_change:
-    image: Emission Factor|CO2|Energy|Supply|Biomass|Average|Oilcrops
+    image: Emission Factor|CO2|Energy|Supply|Biomass|Marginal|Oilcrops
 wood:
   crop_type:
     image:
@@ -35,9 +35,9 @@ wood:
       temperate: poplar
       tropical: eucalyptus
   land_use:
-    image: Land Use|Average|Biomass|Woody
+    image: Land Use|Marginal|Biomass|Woody
   land_use_change:
-    image: Emission Factor|CO2|Energy|Supply|Biomass|Average|Woody
+    image: Emission Factor|CO2|Energy|Supply|Biomass|Marginal|Woody
 grass:
   crop_type:
     image:
@@ -47,9 +47,9 @@ grass:
       temperate: switchgrass
       tropical: miscanthus
   land_use:
-    image: Land Use|Average|Biomass|Grassy
+    image: Land Use|Marginal|Biomass|Grassy
   land_use_change:
-    image: Emission Factor|CO2|Energy|Supply|Biomass|Average|Grassy
+    image: Emission Factor|CO2|Energy|Supply|Biomass|Marginal|Grassy
 grain:
   crop_type:
     image:
@@ -59,6 +59,6 @@ grain:
       temperate: corn
       tropical: corn
   land_use:
-    image: Land Use|Average|Biomass|Maize
+    image: Land Use|Marginal|Biomass|Maize
   land_use_change:
-    image: Emission Factor|CO2|Energy|Supply|Biomass|Average|Maize
+    image: Emission Factor|CO2|Energy|Supply|Biomass|Marginal|Maize