diff --git a/premise/activity_maps.py b/premise/activity_maps.py
index 3c894491..8f05c8a3 100644
--- a/premise/activity_maps.py
+++ b/premise/activity_maps.py
@@ -14,7 +14,7 @@
 
 POWERPLANT_TECHS = VARIABLES_DIR / "electricity_variables.yaml"
 FUELS_TECHS = VARIABLES_DIR / "fuels_variables.yaml"
-MATERIALS_TECHS = DATA_DIR / "utils" / "materials_vars.yml"
+MATERIALS_TECHS = DATA_DIR / "metals" / "activities_mapping.yml"
 DAC_TECHS = VARIABLES_DIR / "direct_air_capture_variables.yaml"
 CARBON_STORAGE_TECHS = VARIABLES_DIR / "carbon_storage_variables.yaml"
 CEMENT_TECHS = VARIABLES_DIR / "cement_variables.yaml"
@@ -22,7 +22,7 @@
     DATA_DIR / "GAINS_emission_factors" / "gains_ecoinvent_sectoral_mapping.yaml"
 )
 ACTIVITIES_METALS_MAPPING = DATA_DIR / "metals" / "activities_mapping.yml"
-METALS_MAPPING = DATA_DIR / "metals" / "metals_mapping.yml"
+# METALS_MAPPING = DATA_DIR / "metals" / "metals_mapping.yml"
 
 
 def get_mapping(filepath: Path, var: str, model: str = None) -> dict:
@@ -159,9 +159,9 @@ def __init__(
         self.activity_metals_filters = get_mapping(
             filepath=ACTIVITIES_METALS_MAPPING, var="ecoinvent_aliases"
         )
-        self.metals_filters = get_mapping(
-            filepath=METALS_MAPPING, var="ecoinvent_aliases"
-        )
+        # self.metals_filters = get_mapping(
+        #     filepath=METALS_MAPPING, var="ecoinvent_aliases"
+        # )
 
     def generate_activities_using_metals_map(self) -> dict:
         """
diff --git a/premise/data/metals/activities_mapping.yml b/premise/data/metals/activities_mapping.yml
index b01c7980..0c444ce9 100644
--- a/premise/data/metals/activities_mapping.yml
+++ b/premise/data/metals/activities_mapping.yml
@@ -213,10 +213,10 @@ CdTe:
       - photovoltaic laminate, CdTe
     mask:
       - market
-pv_perovskite:
-  ecoinvent_aliases:
-    fltr:
-      - photovoltaic panel, perovskite-Si-tandem, at plant
+#pv_perovskite:
+#  ecoinvent_aliases:
+#    fltr:
+#      - photovoltaic panel, perovskite-Si-tandem, at plant
 Parabolic Trough - SF:
   ecoinvent_aliases:
     fltr:
diff --git a/premise/data/metals/metals_db.csv b/premise/data/metals/metals_db.csv
index cf80c51e..fb8e521b 100644
--- a/premise/data/metals/metals_db.csv
+++ b/premise/data/metals/metals_db.csv
@@ -323,7 +323,7 @@ Manganese,kg/kWh,2020.0,,,0,0,LTO
 Nickel,kg/kWh,2020.0,0.07633587786259542,0.07633587786259542,0.07633587786259542,0.07633587786259542,LTO
 Phosphorus,kg/kWh,2020.0,0.7467302798982189,0.7467302798982188,0.17666666666666667,1.3167938931297711,LTO
 Titanium,kg/kWh,2020.0,3.466066666666667,3.466066666666667,1.6033333333333335,5.3288,LTO
-Pb,kg/kWh,2020.0,14,14,14,14,Lead-Acid
+Pb,kg/kWh,2020.0,14,14,14,14,Lead_Acid
 Vanadium,kg/kWh,2020.0,0.3,0.3,0.3,0.3,NiMH
 Cobalt,kg/kWh,2020.0,0.19433333333333336,0.17,0.088,0.325,NiMH
 Nickel,kg/kWh,2020.0,4.083333333333334,4.15,3.7,4.4,NiMH
diff --git a/premise/data/metals/metals_mapping.yml b/premise/data/metals/metals_mapping.yml
deleted file mode 100644
index 5f44e90c..00000000
--- a/premise/data/metals/metals_mapping.yml
+++ /dev/null
@@ -1,509 +0,0 @@
-# translation between metals_db names for metals and ecoinvent names ---
----
-
-Dysprosium:
-  ecoinvent_aliases:
-    fltr:
-      name: Dysprosium
-      categories: natural resource
-
-Neodymium:
-  ecoinvent_aliases:
-    fltr:
-      name: Neodymium, 4% in bastnasite, 0.4% in crude ore
-      categories: natural resource
-
-Nickel:
-  ecoinvent_aliases:
-    fltr:
-      name: Nickel
-      categories: natural resource
-
-Manganese:
-  ecoinvent_aliases:
-    fltr:
-      name: Manganese
-      categories: natural resource
-
-Yttrium:
-  ecoinvent_aliases:
-    fltr:
-      name: Yttrium
-      categories: natural resource
-
-Vanadium:
-  ecoinvent_aliases:
-    fltr:
-      name: Vanadium
-      categories: natural resource
-
-Cobalt:
-  ecoinvent_aliases:
-    fltr:
-      name: Cobalt
-      categories: natural resource
-
-Lithium:
-  ecoinvent_aliases:
-    fltr:
-      name: Lithium
-      categories: natural resource
-
-Sulfur:
-  ecoinvent_aliases:
-    fltr:
-      name: Sulfur
-      categories: natural resource
-
-Platinum:
-  ecoinvent_aliases:
-    fltr:
-      name: Platinum
-      categories: natural resource
-
-Cerium:
-  ecoinvent_aliases:
-    fltr:
-      name: Cerium
-      categories: natural resource
-
-Lanthanum:
-  ecoinvent_aliases:
-    fltr:
-      name: Lanthanum
-      categories: natural resource
-
-Zirconium:
-  ecoinvent_aliases:
-    fltr:
-      name: Zirconium
-      categories: natural resource
-
-Gadolinium:
-  ecoinvent_aliases:
-    fltr:
-      name: Gadolinium
-      categories: natural resource
-
-Scandium:
-  ecoinvent_aliases:
-    fltr:
-      name: Scandium
-      categories: natural resource
-
-Strontium:
-  ecoinvent_aliases:
-    fltr:
-      name: Strontium
-      categories: natural resource
-
-Potassium:
-  ecoinvent_aliases:
-    fltr:
-      name: Potassium
-      categories: natural resource
-
-Iridium:
-  ecoinvent_aliases:
-    fltr:
-      name: Iridium
-      categories: natural resource
-
-Silver:
-  ecoinvent_aliases:
-    fltr:
-      name: Silver
-      categories: natural resource
-
-Germanium:
-  ecoinvent_aliases:
-    fltr:
-      name: Germanium
-      categories: natural resource
-
-Indium:
-  ecoinvent_aliases:
-    fltr:
-      name: Indium
-      categories: natural resource
-
-Gallium:
-  ecoinvent_aliases:
-    fltr:
-      name: Gallium
-      categories: natural resource
-
-Selenium:
-  ecoinvent_aliases:
-    fltr:
-      name: Selenium
-      categories: natural resource
-
-Cadmium:
-  ecoinvent_aliases:
-    fltr:
-      name: Cadmium
-      categories: natural resource
-
-Tellurium:
-  ecoinvent_aliases:
-    fltr:
-      name: Tellurium
-      categories: natural resource
-
-#### NEW - I need to point to the metal compound that goes in the different technologies? not to the mining activities...
-
-#Aluminium:
-#  ecoinvent_aliases:
-#    fltr: market for aluminium, cast alloy
-#    mask:
-#      name:
-#
-#Antimony:
-#  ecoinvent_aliases:
-#    fltr: market for antimony
-#    mask:
-#      name:
-#
-#Beryllium:
-#  ecoinvent_aliases:
-#    fltr: market for beryllium
-#    mask:
-#      name:
-
-#I NEED TO REFINE THE DEMAND FOR BORATES
-## Reference: https://www.borax.com/BoraxCorp/media/Borax-Main/Resources/Data-Sheets/boric-oxide.pdf?ext=.pdf
-##            https://borates.today/boron-solar-energy-storage/ + permanent magnet (ecoinvent) already demands boric oxide
-##
-#### Conversion: from boric oxide to boron
-#Boron oxide:
-#  ecoinvent_aliases:
-#    fltr: market for boric oxide
-#    mask:
-#      name:
-#
-## Reference: https://www.borax.com/products/applications/nuclear-energy
-#### ### Conversion: from boron carbide to boron
-#Boron carbide:
-#  ecoinvent_aliases:
-#    fltr: market for boron carbide
-#    mask:
-#      name:
-#
-#Brass:
-#  ecoinvent_aliases:
-#    fltr: market for brass
-#    mask:
-#      name:
-#
-#Cadmium:
-#  ecoinvent_aliases:
-#    fltr: market for cadmium
-#    mask:
-#      name:
-#
-##Cerium:
-##  ecoinvent_aliases:
-##    fltr:
-##    mask:
-##      name:
-##
-##Chromium:
-##  ecoinvent_aliases:
-##    fltr: market for chromite ore concentrate
-##    mask:
-##      name:
-##
-#Cobalt:
-#  ecoinvent_aliases:
-#    fltr: market for cobalt sulfate
-#    mask:
-#      name:
-##
-#Copper:
-#  ecoinvent_aliases:
-#    fltr: market for copper, cathode
-#    mask:
-#      name:
-#
-#Dysprosium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Erbium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Europium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Gadolinium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Gallium:
-#  ecoinvent_aliases:
-#    fltr: market for gallium, semiconductor-grade
-#    mask:
-#      name:
-#
-#Germanium:
-#  ecoinvent_aliases:
-#    fltr: market for germanium, concentrate
-#    mask:
-#      name:
-#
-#Gold:
-#  ecoinvent_aliases:
-#    fltr: market for gold
-#    mask:
-#      name:
-#
-#Graphite:
-#  ecoinvent_aliases:
-#    fltr: market for natural graphite, coated
-#    mask:
-#      name:
-#
-#Hafnium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Indium:
-#  ecoinvent_aliases:
-#    fltr: market for indium
-#    mask:
-#      name:
-#
-#Iridium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Lanthanum:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Lead:
-#  ecoinvent_aliases:
-#    fltr: market for lead
-#    mask:
-#      name:
-#
-#Lithium:
-#  ecoinvent_aliases:
-#    fltr: market for lithium carbonate, battery grade
-#    mask:
-#      name:
-#
-#Magnesium:
-#  ecoinvent_aliases:
-#    fltr: market for magnesium
-#    mask:
-#      name:
-#
-#Manganese:
-#  ecoinvent_aliases:
-#    fltr: market for manganese
-#    mask:
-#      name:
-#
-#Molybdenum:
-#  ecoinvent_aliases:
-#    fltr: market for molybdenum
-#    mask:
-#      name:
-#
-#Neodymium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Nickel:
-#  ecoinvent_aliases:
-#    fltr: market for nickel, class 1
-#    mask:
-#      name:
-#
-#Niobium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Palladium:
-#  ecoinvent_aliases:
-#    fltr: market for palladium
-#    mask:
-#      name:
-#
-#Phosphorous:
-#  ecoinvent_aliases:
-#    fltr: market for phosphate rock, beneficiated
-#    mask:
-#      name:
-#
-#Platinum:
-#  ecoinvent_aliases:
-#    fltr: market for platinum
-#    mask:
-#      name:
-#
-#Potassium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Praseodymium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Rhenium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Rhodium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Ruthenium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Rubidium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Samarium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Scandium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Selenium:
-#  ecoinvent_aliases:
-#    fltr: market for selenium
-#    mask:
-#      name:
-#
-#Silicon:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Silver:
-#  ecoinvent_aliases:
-#    fltr: market for silver
-#    mask:
-#      name:
-#
-#Sulfur:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Strontium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Tantalum:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Tellurium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Terbium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Tin:
-#  ecoinvent_aliases:
-#    fltr: market for tin
-#    mask:
-#      name:
-#
-#Titanium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Tungsten:
-#  ecoinvent_aliases:
-#    fltr: market for tungsten carbide powder
-#    mask:
-#      name:
-#
-#Vanadium:
-#  ecoinvent_aliases:
-#    fltr: market for vanadium pentoxide
-#    mask:
-#      name:
-#
-#Ytterbium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Yttrium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
-#
-#Zinc:
-#  ecoinvent_aliases:
-#    fltr: market for zinc
-#    mask:
-#      name:
-#
-#Zirconium:
-#  ecoinvent_aliases:
-#    fltr:
-#    mask:
-#      name:
\ No newline at end of file
diff --git a/premise/ecoinvent_modification.py b/premise/ecoinvent_modification.py
index eb57e61a..b8b8a226 100644
--- a/premise/ecoinvent_modification.py
+++ b/premise/ecoinvent_modification.py
@@ -1098,7 +1098,8 @@ def update_metals(self) -> None:
                         modified_datasets=self.modified_datasets,
                     )
 
-                    metals.create_metal_markets()
+
+                    _update_metals(scenario,self.version, self.system_model, self.modified_datasets)
                     scenario["database"] = metals.database
 
         print("Done!\n")
diff --git a/premise/metals.py b/premise/metals.py
index 182aae5e..89fd84fd 100644
--- a/premise/metals.py
+++ b/premise/metals.py
@@ -29,7 +29,6 @@
 
 logger = create_logger("metal")
 
-
 def _update_metals(scenario, version, system_model, modified_datasets):
     metals = Metals(
         database=scenario["database"],
@@ -43,6 +42,7 @@ def _update_metals(scenario, version, system_model, modified_datasets):
     )
 
     metals.create_metal_markets()
+    metals.update_metals_use_in_database()
 
     return scenario, modified_datasets
 
@@ -56,6 +56,40 @@ def load_mining_shares_mapping():
     df = pd.read_excel(filepath, sheet_name="Shares_mapping")
     return df
 
+def load_activities_mapping():
+    """
+    Load mapping for the ecoinvent exchanges to be updated by the new metal intensities
+    """
+
+    filepath = DATA_DIR / "metals" / "activities_mapping.xlsx"
+    df = pd.read_excel(filepath, sheet_name="activities_mapping")
+    return df
+
+
+# Define a function to replicate rows based on the generated activity sets
+def extend_dataframe(df, mapping):
+    """"
+     Extend a DataFrame by duplicating rows based on a mapping dictionary.
+
+    Parameters:
+    - df (pd.DataFrame): The original DataFrame to be extended.
+    - mapping (dict): A dictionary with keys corresponding to the 'technology'
+                      values in the DataFrame and values that are sets of processes.
+    """
+
+    new_rows = []
+
+    for key, processes in mapping.items():
+        # Find the rows in the DataFrame where the 'technology' matches the key
+        matching_rows = df[df['technology'] == key]
+        # For each process in the set associated with the key, duplicate the matching rows
+        for process in processes:
+            temp_rows = matching_rows.copy()
+            temp_rows['ecoinvent_technology'] = process
+            new_rows.extend(temp_rows.to_dict('records'))
+    new_df = pd.DataFrame(new_rows)
+
+    return new_df
 
 def get_ecoinvent_metal_factors():
     """
@@ -78,15 +112,17 @@ def get_ecoinvent_metal_factors():
     return ds
 
 
-def load_post_allocation_correction_factors():
-    """
-    Load yaml file with post-allocation correction factors
-    """
-
-    filepath = DATA_DIR / "metals" / "post-allocation correction" / "corrections.yaml"
-    with open(filepath, "r", encoding="utf-8") as stream:
-        factors = yaml.safe_load(stream)
-    return factors
+# def load_post_allocation_correction_factors():
+#     """
+#     Load yaml file with post-allocation correction factors
+#
+#     WE ARE NOT POST-ALLOCATING ANYMORE
+#     """
+#
+#     filepath = DATA_DIR / "metals" / "post-allocation correction" / "corrections.yaml"
+#     with open(filepath, "r", encoding="utf-8") as stream:
+#         factors = yaml.safe_load(stream)
+#     return factors
 
 
 def fetch_mapping(filepath: str) -> dict:
@@ -119,8 +155,8 @@ def load_conversion_factors():
 
 class Metals(BaseTransformation):
     """
-    Class that modifies emissions of hot pollutants
-    according to GAINS projections.
+    Class that modifies metal demand of different technologies
+    according to the Database built
     """
 
     def __init__(
@@ -146,21 +182,39 @@ def __init__(
         )
 
         self.version = version
-        self.metals = iam_data.metals
 
-        mapping = InventorySet(self.database, self.version)
+        self.metals = iam_data.metals # 1
+        # Precompute the median values for each metal and origin_var for the year 2020
+        self.precomputed_medians = self.metals.sel(variable="median").interp(year=self.year)
+
+        self.activities_mapping = load_activities_mapping() # 4
+
+        self.conversion_factors = load_conversion_factors() # 3
+        # Precompute conversion factors as a dictionary for faster lookups
+        self.conversion_factors_dict = self.conversion_factors.set_index('Activity')['Conversion_factor'].to_dict()
+
+        inv = InventorySet(self.database, self.version)
+
         self.activities_metals_map: Dict[
             str, Set
-        ] = mapping.generate_activities_using_metals_map()
+        ] = inv.generate_material_map()
+
         self.rev_activities_metals_map: Dict[str, str] = rev_metals_map(
             self.activities_metals_map
         )
+        self.extended_dataframe = extend_dataframe(self.activities_mapping,self.activities_metals_map)
+        self.extended_dataframe['final_technology'] = self.extended_dataframe.apply(
+            lambda row: row['demanding_process'] if pd.notna(row['demanding_process']) and row[
+                'demanding_process'] != '' else row['ecoinvent_technology'],
+            axis=1
+        )
+
         # self.metals_map: Dict[str, Set] = mapping.generate_metals_map()
-        # self.rev_metals_map: Dict[str, str] = rev_metals_map(self.metals_map)
-        self.conversion_factors = load_conversion_factors()
-        self.current_metal_use = get_ecoinvent_metal_factors()
+        # self.rev_metals_map: Dict[str, str] = rev_metals_map(self.metals_map) # 2
+
+        # self.current_metal_use = get_ecoinvent_metal_factors()
 
-        self.biosphere_flow_codes = biosphere_flows_dictionary(version=self.version)
+        # self.biosphere_flow_codes = biosphere_flows_dictionary(version=self.version)
 
     def update_metals_use_in_database(self):
         """
@@ -171,13 +225,15 @@ def update_metals_use_in_database(self):
         for ds in self.database:
             if ds["name"] in self.rev_activities_metals_map:
                 origin_var = self.rev_activities_metals_map[ds["name"]]
-                self.update_metal_use(ds, origin_var)
+                ds_name = ds["name"]
+                self.update_metal_use(ds, ds_name, origin_var)
 
             self.write_log(ds, "updated")
 
     def update_metal_use(
         self,
         dataset: dict,
+        ds_name: str,
         technology: str,
     ) -> dict:
         """
@@ -188,167 +244,132 @@ def update_metal_use(
         """
 
         # get the list of metal factors available for this technology
+        available_metals = self.precomputed_medians.sel(origin_var=technology).dropna(dim='metal', how='all')['metal'].values
+        mask = self.extended_dataframe['ecoinvent_technology'] == ds_name
+        matching_rows = self.extended_dataframe[mask]
 
-        if technology not in self.metals.origin_var.values:
-            print(f"Technology {technology} not found in metal intensity database.")
-            return dataset
+        if not matching_rows.empty:
 
-        data = self.metals.sel(origin_var=technology, variable="median").interp(
-            year=self.year
-        )
-        metals = [
-            m
-            for m in self.metals.metal.values
-            if not np.isnan(data.sel(metal=m).values)
-        ]
+            ecoinvent_technology = matching_rows['ecoinvent_technology'].iloc[0]
+            conversion_factor = self.conversion_factors_dict.get(ecoinvent_technology, None)
 
-        # Update biosphere exchanges according to use factors ---
-        for exc in ws.biosphere(
-            dataset, ws.either(*[ws.equals("name", x) for x in self.rev_metals_map])
-        ):
-            print("Updating metal use for", dataset["name"], exc["name"])
-            metal = self.rev_metals_map[exc["name"]]
-            use_factor = data.sel(metal=metal).values
-
-            # check if there is a conversion factor
-            if dataset["name"] in self.conversion_factors["Activity"].tolist():
-                use_factor *= self.conversion_factors.loc[
-                    self.conversion_factors["Activity"] == dataset["name"],
-                    "Conversion_factor",
-                ].values[0]
+            for metal in available_metals:
 
-            else:
-                print(f"Conversion factor not found for {dataset['name']}.")
+                unit_converter = matching_rows.loc[matching_rows['Element'] == metal, 'unit_convertor']
 
-            # update the exchange amount
-            if metal in self.current_metal_use.metal.values:
-                ecoinvent_factor = self.current_metal_use.sel(
-                    metal=metal,
-                    activity=(
-                        dataset["name"],
-                        dataset["reference product"],
-                        dataset["location"],
-                    ),
-                ).values
-            else:
-                ecoinvent_factor = 0
-
-            exc["amount"] += use_factor - ecoinvent_factor
-
-            if "log parameters" not in dataset:
-                dataset["log parameters"] = {}
-
-            if metal not in dataset["log parameters"]:
-                dataset["log parameters"][f"{metal} old amount"] = ecoinvent_factor
-                dataset["log parameters"][f"{metal} new amount"] = exc["amount"]
-
-                # remove metal from metals list
-            metals.remove(metal)
-
-        # Add new biosphere exchanges for metals
-        # not present in the original dataset
-        for metal in metals:
-            use_factor = data.sel(metal=metal).values
-            # check if there is a conversion factor
-            if dataset["name"] in self.conversion_factors["Activity"].tolist():
-                use_factor *= self.conversion_factors.loc[
-                    self.conversion_factors["Activity"] == dataset["name"],
-                    "Conversion_factor",
-                ].values[0]
-            else:
-                print(f"Conversion factor not found for {dataset['name']}.")
-
-            if self.version != "3.9":
-                exc_id = (
-                    f"{metal}, in ground",
-                    "natural resource",
-                    "in ground",
-                    "kilogram",
-                )
-            else:
-                exc_id = (
-                    f"{metal}",
-                    "natural resource",
-                    "in ground",
-                    "kilogram",
-                )
+                if not unit_converter.empty:
 
-            if metal in self.current_metal_use.metal.values:
-                if (
-                    dataset["name"],
-                    dataset["reference product"],
-                    dataset["location"],
-                ) in self.current_metal_use.activity.values.tolist():
-                    ecoinvent_factor = self.current_metal_use.sel(
-                        metal=metal,
-                        activity=(
-                            dataset["name"],
-                            dataset["reference product"],
-                            dataset["location"],
-                        ),
-                    ).values
-                else:
-                    ecoinvent_factor = 0
-            else:
-                ecoinvent_factor = 0
-
-            exc = {
-                "name": f"{metal}, in ground",
-                "amount": use_factor - ecoinvent_factor,
-                "input": ("biosphere3", self.biosphere_flow_codes[exc_id]),
-                "type": "biosphere",
-                "unit": "kilogram",
-                "comment": (f"{ecoinvent_factor};{use_factor};{technology};{metal}"),
-            }
+                    unit_convertor_value = unit_converter.iloc[0]
+                    median_value = self.precomputed_medians.sel(metal=metal, origin_var=technology).item()
 
-            dataset["exchanges"].append(exc)
+                    if conversion_factor is not None:
 
-            if "log parameters" not in dataset:
-                dataset["log parameters"] = {}
+                        metal_activity = matching_rows.loc[matching_rows['Element'] == metal, 'Activity'].iloc[0]
+                        metal_reference_product = matching_rows.loc[matching_rows['Element'] == metal, 'Reference product'].iloc[0]
+                        result = median_value * unit_convertor_value * conversion_factor
+                        final_technology = matching_rows.loc[matching_rows['Element'] == metal, 'final_technology'].iloc[0]
 
-            dataset["log parameters"][f"{metal} old amount"] = ecoinvent_factor
-            dataset["log parameters"][f"{metal} new amount"] = exc["amount"]
 
-        return dataset
+                        ### GET METAL MARKET LOCATION
+                        locations = ['World', 'GLO', None]
+                        dataset_metal = None
 
-    def post_allocation_correction(self):
-        """
-        Correct for post-allocation in the database.
-        """
+                        for location in locations:
+                            try:
+                                if location:
+                                    dataset_metal = ws.get_one(
+                                        self.database,
+                                        ws.equals('name', metal_activity),
+                                        ws.equals('location', location)
+                                    )
+                                else:
+                                    dataset_metal = ws.get_one(
+                                        self.database,
+                                        ws.equals('name', metal_activity)
+                                    )
+                                if dataset_metal:  # If we found the dataset, break out of the loop
+                                    break
+                            except Exception as e:  # Replace Exception with the specific exception if possible
+                                print(f"Failed to get dataset for location '{location}': {e}")
+                            print(f"Dataset for metal activity '{metal_activity}' not found in any location.")
 
-        factors_list = load_post_allocation_correction_factors()
 
-        for dataset in factors_list:
-            ds = ws.get_one(
-                self.database,
-                ws.equals("name", dataset["name"]),
-                ws.equals("reference product", dataset["reference product"]),
-                ws.equals("location", dataset["location"]),
-                ws.equals("unit", dataset["unit"]),
-            )
-            ds["exchanges"].append(
-                {
-                    "name": dataset["additional flow"]["name"],
-                    "amount": dataset["additional flow"]["amount"],
-                    "unit": dataset["additional flow"]["unit"],
-                    "type": "biosphere",
-                    "categories": tuple(
-                        dataset["additional flow"]["categories"].split("::")
-                    ),
-                    "input": (
-                        "biosphere3",
-                        self.biosphere_flow_codes[
-                            dataset["additional flow"]["name"],
-                            dataset["additional flow"]["categories"].split("::")[0],
-                            dataset["additional flow"]["categories"].split("::")[1],
-                            dataset["additional flow"]["unit"],
-                        ],
-                    ),
-                }
-            )
+                        dataset_demand = ws.get_many(
+                            self.database,
+                            ws.equals('name', final_technology),
+                        )
+
+                        for exc in dataset_demand:
+                            print(
+                                f"\nUpdating {metal_reference_product} for {exc['name']}, location:{exc['location']}. New value: {result}")
+                            exchange = {
+                                "uncertainty type": 0,
+                                "amount": result,
+                                "product": metal_reference_product,
+                                "name": metal_activity,
+                                "unit": "kilogram",
+                                "location": dataset_metal["location"],
+                                "type": "technosphere",
+                            }
+                            exc["exchanges"].append(exchange)
+                    else:
+                        print(
+                                f"\nCHECK!!!\n Origin: {technology}, Metal: {metal}, Calculation Result: Conversion factor missing, Ecoinvent Activity: {ecoinvent_technology}, Technology: {matching_rows.loc[matching_rows['Element'] == metal, 'final_technology'].iloc[0]}")
+                else:
+                    print(
+                            f"\nCHECK!!!\nOrigin: {technology}, Metal: {metal} - No unit converter found, Technology: {matching_rows['final_technology'].iloc[0]}")
+        else:
+            print(f"\nCHECK!!!\n No matching rows for {ds_name}.")
+
+
+            # if "log parameters" not in dataset:
+            #     dataset["log parameters"] = {}
+            #
+            # if metal not in dataset["log parameters"]:
+            #     # dataset["log parameters"][f"{metal} old amount"] = ecoinvent_factor
+            #     dataset["log parameters"][f"{metal} new amount"] = exc["amount"]
+
+        return dataset
+
+    # def post_allocation_correction(self):
+    #     """
+    #     Correct for post-allocation in the database.
+    #     """
+    #
+    #     factors_list = load_post_allocation_correction_factors()
+    #
+    #     for dataset in factors_list:
+    #         ds = ws.get_one(
+    #             self.database,
+    #             ws.equals("name", dataset["name"]),
+    #             ws.equals("reference product", dataset["reference product"]),
+    #             ws.equals("location", dataset["location"]),
+    #             ws.equals("unit", dataset["unit"]),
+    #         )
+    #         ds["exchanges"].append(
+    #             {
+    #                 "name": dataset["additional flow"]["name"],
+    #                 "amount": dataset["additional flow"]["amount"],
+    #                 "unit": dataset["additional flow"]["unit"],
+    #                 "type": "biosphere",
+    #                 "categories": tuple(
+    #                     dataset["additional flow"]["categories"].split("::")
+    #                 ),
+    #                 "input": (
+    #                     "biosphere3",
+    #                     self.biosphere_flow_codes[
+    #                         dataset["additional flow"]["name"],
+    #                         dataset["additional flow"]["categories"].split("::")[0],
+    #                         dataset["additional flow"]["categories"].split("::")[1],
+    #                         dataset["additional flow"]["unit"],
+    #                     ],
+    #                 ),
+    #             }
+    #         )
 
     def create_new_mining_activity(
-        self, name, reference_product, new_locations, geo_mapping
+        self, name, reference_product, new_locations
+        # self, name, reference_product, new_locations, geo_mapping
     ) -> dict:
         """
         Create a new mining activity in a new location.
@@ -431,11 +452,12 @@ def create_region_specific_markets(self, df: pd.DataFrame) -> List[dict]:
             # fetch shares for each location in df
             shares = self.get_shares(group, new_locations, name, ref_prod)
 
-            geography_mapping = self.get_geo_mapping(group, new_locations)
+            # geography_mapping = self.get_geo_mapping(group, new_locations)
 
             # if not, we create it
             datasets = self.create_new_mining_activity(
-                name, ref_prod, new_locations, geography_mapping
+                name, ref_prod, new_locations
+                # name, ref_prod, new_locations, geography_mapping
             )
 
             # add new datasets to database
@@ -518,7 +540,7 @@ def create_market(self, metal, df):
         return dataset
 
     def create_metal_markets(self):
-        self.post_allocation_correction()
+        # self.post_allocation_correction()
 
         print("Creating metal markets")
 
@@ -566,11 +588,12 @@ def create_metal_markets(self):
                     k: v for k, v in new_locations.items() if v is not None
                 }
 
-                geography_mapping = self.get_geo_mapping(group, new_locations)
+                # geography_mapping = self.get_geo_mapping(group, new_locations)
 
                 # if not, we create it
                 datasets = self.create_new_mining_activity(
-                    name, ref_prod, new_locations, geography_mapping
+                    name, ref_prod, new_locations
+                    # name, ref_prod, new_locations, geography_mapping
                 )
 
                 self.database.extend(datasets.values())
@@ -590,142 +613,144 @@ def create_metal_markets(self):
                     ]
                 )
 
-    def update_metal_use(
-        self,
-        dataset: dict,
-        technology: str,
-    ) -> dict:
-        """
-        Update metal use based on metal intensities data.
-        :param dataset: dataset to adjust metal use for
-        :param technology: metal intensity variable name to look up
-        :return: Does not return anything. Modified in place.
-        """
-
-        # get the list of metal factors available for this technology
-
-        if technology not in self.metals.origin_var.values:
-            print(f"Technology {technology} not found in metal intensity database.")
-            return dataset
-
-        data = self.metals.sel(origin_var=technology, variable="median").interp(
-            year=self.year
-        )
-        metals = [
-            m
-            for m in self.metals.metal.values
-            if not np.isnan(data.sel(metal=m).values)
-        ]
-
-        # Update biosphere exchanges according to DLR use factors
-
-        for exc in ws.biosphere(
-            dataset, ws.either(*[ws.equals("name", x) for x in self.rev_metals_map])
-        ):
-            print("Updating metal use for", dataset["name"], exc["name"])
-            metal = self.rev_metals_map[exc["name"]]
-            use_factor = data.sel(metal=metal).values
-
-            # check if there is a conversion factor
-            if dataset["name"] in self.conversion_factors["Activity"].tolist():
-                use_factor *= self.conversion_factors.loc[
-                    self.conversion_factors["Activity"] == dataset["name"],
-                    "Conversion_factor",
-                ].values[0]
-
-            else:
-                print(f"Conversion factor not found for {dataset['name']}.")
-
-            # update the exchange amount
-            if metal in self.current_metal_use.metal.values:
-                ecoinvent_factor = self.current_metal_use.sel(
-                    metal=metal,
-                    activity=(
-                        dataset["name"],
-                        dataset["reference product"],
-                        dataset["location"],
-                    ),
-                ).values
-            else:
-                ecoinvent_factor = 0
-
-            exc["amount"] += use_factor - ecoinvent_factor
-
-            if "log parameters" not in dataset:
-                dataset["log parameters"] = {}
-
-            if metal not in dataset["log parameters"]:
-                dataset["log parameters"][f"{metal} old amount"] = ecoinvent_factor
-                dataset["log parameters"][f"{metal} new amount"] = exc["amount"]
-
-                # remove metal from metals list
-            metals.remove(metal)
-
-        # Add new biosphere exchanges for metals
-        # not present in the original dataset
-        for metal in metals:
-            use_factor = data.sel(metal=metal).values
-            # check if there is a conversion factor
-            if dataset["name"] in self.conversion_factors["Activity"].tolist():
-                use_factor *= self.conversion_factors.loc[
-                    self.conversion_factors["Activity"] == dataset["name"],
-                    "Conversion_factor",
-                ].values[0]
-            else:
-                print(f"Conversion factor not found for {dataset['name']}.")
-
-            if self.version != "3.9":
-                exc_id = (
-                    f"{metal}, in ground",
-                    "natural resource",
-                    "in ground",
-                    "kilogram",
-                )
-            else:
-                exc_id = (
-                    f"{metal}",
-                    "natural resource",
-                    "in ground",
-                    "kilogram",
-                )
-
-            if metal in self.current_metal_use.metal.values:
-                if (
-                    dataset["name"],
-                    dataset["reference product"],
-                    dataset["location"],
-                ) in self.current_metal_use.activity.values.tolist():
-                    ecoinvent_factor = self.current_metal_use.sel(
-                        metal=metal,
-                        activity=(
-                            dataset["name"],
-                            dataset["reference product"],
-                            dataset["location"],
-                        ),
-                    ).values
-                else:
-                    ecoinvent_factor = 0
-            else:
-                ecoinvent_factor = 0
-
-            exc = {
-                "name": f"{metal}, in ground",
-                "amount": use_factor - ecoinvent_factor,
-                "input": ("biosphere3", self.biosphere_flow_codes[exc_id]),
-                "type": "biosphere",
-                "unit": "kilogram",
-                "comment": (f"{ecoinvent_factor};{use_factor};{technology};{metal}"),
-            }
-
-            dataset["exchanges"].append(exc)
-
-            if "log parameters" not in dataset:
-                dataset["log parameters"] = {}
-
-            dataset["log parameters"][f"{metal} old amount"] = ecoinvent_factor
-            dataset["log parameters"][f"{metal} new amount"] = exc["amount"]
-
-        return dataset
+    # def update_metal_use(
+    #     self,
+    #     dataset: dict,
+    #     technology: str,
+    # ) -> dict:
+    #     """
+    #       OLD FUNCTION WHERE WE WERE MODIFYING ENVIRONMENTAL FLOWS
+
+    #     Update metal use based on metal intensities data.
+    #     :param dataset: dataset to adjust metal use for
+    #     :param technology: metal intensity variable name to look up
+    #     :return: Does not return anything. Modified in place.
+    #     """
+    #
+    #     # get the list of metal factors available for this technology
+    #
+    #     if technology not in self.metals.origin_var.values:
+    #         print(f"Technology {technology} not found in metal intensity database.")
+    #         return dataset
+    #
+    #     data = self.metals.sel(origin_var=technology, variable="median").interp(
+    #         year=self.year
+    #     )
+    #     metals = [
+    #         m
+    #         for m in self.metals.metal.values
+    #         if not np.isnan(data.sel(metal=m).values)
+    #     ]
+    #
+    #     # Update biosphere exchanges according to DLR use factors
+    #
+    #     for exc in ws.biosphere(
+    #         dataset, ws.either(*[ws.equals("name", x) for x in self.rev_metals_map])
+    #     ):
+    #         print("Updating metal use for", dataset["name"], exc["name"])
+    #         metal = self.rev_metals_map[exc["name"]]
+    #         use_factor = data.sel(metal=metal).values
+    #
+    #         # check if there is a conversion factor
+    #         if dataset["name"] in self.conversion_factors["Activity"].tolist():
+    #             use_factor *= self.conversion_factors.loc[
+    #                 self.conversion_factors["Activity"] == dataset["name"],
+    #                 "Conversion_factor",
+    #             ].values[0]
+    #
+    #         else:
+    #             print(f"Conversion factor not found for {dataset['name']}.")
+    #
+    #         # update the exchange amount
+    #         if metal in self.current_metal_use.metal.values:
+    #             ecoinvent_factor = self.current_metal_use.sel(
+    #                 metal=metal,
+    #                 activity=(
+    #                     dataset["name"],
+    #                     dataset["reference product"],
+    #                     dataset["location"],
+    #                 ),
+    #             ).values
+    #         else:
+    #             ecoinvent_factor = 0
+    #
+    #         exc["amount"] += use_factor - ecoinvent_factor
+    #
+    #         if "log parameters" not in dataset:
+    #             dataset["log parameters"] = {}
+    #
+    #         if metal not in dataset["log parameters"]:
+    #             dataset["log parameters"][f"{metal} old amount"] = ecoinvent_factor
+    #             dataset["log parameters"][f"{metal} new amount"] = exc["amount"]
+    #
+    #             # remove metal from metals list
+    #         metals.remove(metal)
+    #
+    #     # Add new biosphere exchanges for metals
+    #     # not present in the original dataset
+    #     for metal in metals:
+    #         use_factor = data.sel(metal=metal).values
+    #         # check if there is a conversion factor
+    #         if dataset["name"] in self.conversion_factors["Activity"].tolist():
+    #             use_factor *= self.conversion_factors.loc[
+    #                 self.conversion_factors["Activity"] == dataset["name"],
+    #                 "Conversion_factor",
+    #             ].values[0]
+    #         else:
+    #             print(f"Conversion factor not found for {dataset['name']}.")
+    #
+    #         if self.version != "3.9":
+    #             exc_id = (
+    #                 f"{metal}, in ground",
+    #                 "natural resource",
+    #                 "in ground",
+    #                 "kilogram",
+    #             )
+    #         else:
+    #             exc_id = (
+    #                 f"{metal}",
+    #                 "natural resource",
+    #                 "in ground",
+    #                 "kilogram",
+    #             )
+    #
+    #         if metal in self.current_metal_use.metal.values:
+    #             if (
+    #                 dataset["name"],
+    #                 dataset["reference product"],
+    #                 dataset["location"],
+    #             ) in self.current_metal_use.activity.values.tolist():
+    #                 ecoinvent_factor = self.current_metal_use.sel(
+    #                     metal=metal,
+    #                     activity=(
+    #                         dataset["name"],
+    #                         dataset["reference product"],
+    #                         dataset["location"],
+    #                     ),
+    #                 ).values
+    #             else:
+    #                 ecoinvent_factor = 0
+    #         else:
+    #             ecoinvent_factor = 0
+    #
+    #         exc = {
+    #             "name": f"{metal}, in ground",
+    #             "amount": use_factor - ecoinvent_factor,
+    #             "input": ("biosphere3", self.biosphere_flow_codes[exc_id]),
+    #             "type": "biosphere",
+    #             "unit": "kilogram",
+    #             "comment": (f"{ecoinvent_factor};{use_factor};{technology};{metal}"),
+    #         }
+    #
+    #         dataset["exchanges"].append(exc)
+    #
+    #         if "log parameters" not in dataset:
+    #             dataset["log parameters"] = {}
+    #
+    #         dataset["log parameters"][f"{metal} old amount"] = ecoinvent_factor
+    #         dataset["log parameters"][f"{metal} new amount"] = exc["amount"]
+    #
+    #     return dataset
 
     def write_log(self, dataset, status="created"):
         """