Release v1.1.4

.github/workflows/python-package.yml

@@ -31,7 +31,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [ubuntu-latest, windows-latest, macos-latest]
-        py-version: ['3.9', '3.10', '3.11']
+        py-version: ['3.9', '3.10', '3.11', '3.12', '3.13']
 
     steps:
     - uses: actions/checkout@v4

.github/workflows/test_methods.yml

@@ -17,7 +17,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v5
       with:
-        python-version: "3.10"
+        python-version: "3.12"
 
     - name: Update pip & install testing pkgs
       run: |

.zenodo.json

@@ -0,0 +1,38 @@
+{
+    "description": "Standardizes the format and flows of life cycle impact assessment (LCIA) data.", 
+    "license": "MIT",
+    "title": "LCIA Formatter",
+    "upload_type": "software", 
+    "creators": [
+        {
+            "affiliation": "Eastern Research Group, Inc.", 
+            "name": "Ben Young",
+            "orcid": "https://orcid.org/0000-0001-6276-8670"
+        }, 
+        {
+            "affiliation": "GreenDelta", 
+            "name": "Michael Srocka"
+        },
+        {
+            "affiliation": "US Environmental Protection Agency", 
+            "name": "Wesley Ingwersen",
+            "orcid": "https://orcid.org/0000-0002-9614-701X"
+        }, 
+        {
+            "affiliation": "Eastern Research Group, Inc.", 
+            "name": "Ben Morelli",
+            "orcid": "https://orcid.org/0000-0002-7660-6485"
+        },
+        {
+            "affiliation": "Eastern Research Group, Inc.", 
+            "name": "Sarah Cashman",
+            "orcid": "https://orcid.org/0000-0001-9859-9557"
+        },
+        {
+            "affiliation": "Eastern Research Group, Inc.", 
+            "name": "Andrew Henderson",
+            "orcid": "https://orcid.org/0000-0003-2436-7512"
+        }
+    ],
+    "access_right": "open"
+}

README.md

@@ -1,5 +1,6 @@
 # LCIA formatter
-[![DOI](https://joss.theoj.org/papers/10.21105/joss.03392/status.svg)](https://doi.org/10.21105/joss.03392)
+[![JOSS](https://joss.theoj.org/papers/10.21105/joss.03392/status.svg)](https://doi.org/10.21105/joss.03392)
+[![DOI](https://zenodo.org/badge/188049640.svg)](https://zenodo.org/doi/10.5281/zenodo.7400857)
 [![build](https://github.com/USEPA/LCIAformatter/actions/workflows/python-package.yml/badge.svg)](https://github.com/USEPA/LCIAformatter/actions/workflows/python-package.yml)
 
 The LCIA formatter, or `lciafmt`, is a Python tool for standardizing the format and flows of life cycle impact assessment (LCIA) data. The tool acquires LCIA data transparently from its original 
@@ -18,6 +19,7 @@ The LCIA Formatter v1 was peer-reviewed internally at USEPA and externally throu
 |ImpactWorld+ Endpoint*|International Reference Center for Life Cycle of Products, Services and Systems (CIRAIG)|[ImpactWorld+](http://www.impactworldplus.org/en/team.php)|
 |IPCC GWP|Intergovernmental Panel on Climate Change (IPCC)| |
 |FEDEFL Inventory Methods|US Environmental Protection Agency|[FEDEFL Inventory Methods](https://github.com/USEPA/LCIAformatter/wiki/Inventory-Methods)|
+|Cumulative Energy Demand|Federal LCA Commons|[FEDEFL Inventory Methods](https://github.com/USEPA/LCIAformatter/wiki/Inventory-Methods)|
 
 \* only works on Windows installations
 

lciafmt/__init__.py

@@ -13,6 +13,7 @@
 import pandas as pd
 
 import lciafmt.cache as cache
+import lciafmt.ced as ced
 import lciafmt.fmap as fmap
 import lciafmt.jsonld as jsonld
 import lciafmt.traci as traci
@@ -34,6 +35,7 @@ class Method(Enum):
     TRACI = "TRACI 2.1"
     RECIPE_2016 = "ReCiPe 2016"
     FEDEFL_INV = "FEDEFL Inventory"
+    CED = "Cumulative Energy Demand"
     ImpactWorld = "ImpactWorld"
     IPCC = "IPCC"
 
@@ -122,6 +124,8 @@ def get_method(method_id, add_factors_for_missing_contexts=True,
         return ipcc.get()
     if method_id == Method.FEDEFL_INV:
         return fedefl_inventory.get(subset)
+    if method_id == Method.CED:
+        return ced.get()
 
 
 def clear_cache():

lciafmt/ced.py

@@ -0,0 +1,60 @@
+# ced.py (lciafmt)
+# !/usr/bin/env python3
+# coding=utf-8
+"""
+Generate method for Cumulative Energy Demand (CED)
+"""
+
+import numpy as np
+import pandas as pd
+
+import lciafmt
+from lciafmt.util import store_method
+
+
+def get() -> pd.DataFrame():
+
+    inv_orig = lciafmt.get_method(method_id = 'FEDEFL_INV', subset = ['ced'])
+    inv = inv_orig.copy()
+    inv['Indicator'] = ''
+    inv['Method'] = 'Cumulative Energy Demand'
+
+    conditions = [
+        inv['Flowable'].isin(['Wood, primary forest']),
+        inv['Flowable'].isin(['Biomass', 'Softwood', 'Hardwood', 'Wood']),
+        inv['Flowable'].isin(['Energy, hydro']),
+        inv['Flowable'].str.contains('|'.join(['wind', 'solar', 'geothermal'])),
+        inv['Flowable'].str.contains('Uranium'),
+        inv['Flowable'].str.contains('|'.join(['Coal', 'Oil', 'Crude',
+                                               'gas', 'Methane'])),
+        ]
+
+    indicators = ['Non-renewable, biomass',
+                  'Renewable, biomass',
+                  'Renewable, water',
+                  'Renewable, wind, solar, geothermal',
+                  'Non-renewable, nuclear',
+                  'Non-renewable, fossil',
+                  ]
+    inv['Indicator'] = np.select(conditions, indicators, default='')
+
+    ## Original CED Method included the
+    # "Energy, fossil, unspecified" technosphere flow;
+    # this has been dropped
+    # https://www.lcacommons.gov/lca-collaboration/National_Renewable_Energy_Laboratory/USLCI_Database_Public/dataset/FLOW/46dc4693-2f24-39d2-b69f-dd059737fd5e
+
+    ## Original CED Method used HHV for biomass/wood flows
+    # Some wood flows were removed after the original method in FEDEFLv1.0.8
+
+    # Dropped flows from FEDEFL inv method: "Hydrogen", "Energy, heat"
+    inv = inv.query('Indicator != ""').reset_index(drop=True)
+
+    return inv
+
+
+if __name__ == "__main__":
+    method = lciafmt.Method.CED
+    df = get()
+    store_method(df, method)
+    lciafmt.util.save_json(method, df)
+    # lciafmt.util.save_json(method, df, write_flows=True)

lciafmt/data/ReCiPe2016_endpoint_to_midpoint.csv

@@ -8,15 +8,15 @@
 ,Toxicity - Human health (non-cancer),Human noncarcinogenic toxicity,Human health
 ,Water consumption - human health,Water consumption,Human health
 ,Global Warming - Terrestrial ecosystems,Global Warming,Terrestrial ecosystems
-,Photochemical ozone formation - Terrestrial ecosystems,Ecosyste damage ozone formation,Terrestrial ecosystems
+,Photochemical ozone formation - Terrestrial ecosystems,Ecosystem damage ozone formation,Terrestrial ecosystems
 ,Acidification - Terrestrial ecosystems,Terrestrial acidification,Terrestrial ecosystems
 ,Toxicity - Terrestrial ecosystems,Terrestrial ecotoxicity,Terrestrial ecosystems
 ,Water consumption - terrestrial ecosystems,Water consumption,Terrestrial ecosystems
 ,Land use - occupation and transformation,Land occupation,Terrestrial ecosystems
 ,Global Warming - Freshwater ecosystems,Global Warming,Freshwater ecosystems
 ,Eutrophication - Freshwater ecosystems,Freshwater eutrophication,Freshwater ecosystems
 ,Toxicity - Freshwater ecosystems,Freshwater ecotoxicity,Freshwater ecosystems
-,Water consumption -aquatic ecosystems,Water consumption,Freshwater ecosystems
+,Water consumption - aquatic ecosystems,Water consumption,Freshwater ecosystems
 ,Toxicity - Marine ecosystems,Marine ecotoxicity,Marine ecosystems
 ,Eutrophication - Marine ecosystems,Marine eutrophication,Marine ecosystems
 ,Mineral resource scarcity,Mineral resource scarcity,Resources

lciafmt/data/description.yaml

@@ -1,12 +1,14 @@
 base: >+
     [Method][version] is built from LCIA Formatter v[LCIAfmt_version] and
-    flows from the Federal Elementary Flow List (FEDEFL) v[FEDEFL_version]
+    flows from v[FEDEFL_version] of the Federal Elementary Flow List (FEDEFL),
+    using fedelemflowlist v[fedelemflowlist_version].
 
 description: >+
     [Method] source file: [url]
 
     Source citation: [citation]
 
+mapping: >+
     [Method] flowable and context input files are maintained in the FEDEFL
     GitHub Repository: https://github.com/USEPA/fedelemflowlist
 

lciafmt/data/lcia.bib

@@ -45,3 +45,12 @@ @incollection{smith_earths_2021
 	author = {Smith, Chris and Nicholls, Zebedee R. J. and Armour, Kyle and Collins, William and Forster, Piers and Meinshausen, Malte and Palmer, Matthew D. and Watanabe, Masahiro},
 	year = {2021},
 }
+
+@report{frischknecht_implementation_2007,
+	title = {Implementation of life cycle impact assessment methods},
+	url = {https://esu-services.ch/fileadmin/download/publicLCI/03_LCIA-Implementation.pdf},
+	number = {ecoinvent report No. 3},
+	author = {Frischknecht, Rolf and Jungbluth, Niels and Althaus, H. J. and Bauer, C. and Doka, G. and Dones, R. and Hischier, R. and Hellweg, S. and Humbert, S. and Köllner, T.},
+	urldate = {2024-11-13},
+	year = {2007},
+}

lciafmt/data/methods.json

@@ -25,17 +25,17 @@
                 "ReCiPe 2016 - Midpoint/E":"ReCiPe 2016 v1.1 midpoint method, Egalitarian version. The typical ReCiPe midpoint method used is the Hierarchist version."},
     "path": "recipe",
     "case_insensitivity": "True",
-    "url": "http://www.rivm.nl/sites/default/files/2018-11/ReCiPe2016_CFs_v1.1_20180117.xlsx",
+    "url": "https://www.rivm.nl/sites/default/files/2024-10/ReCiPe2016_CFs_v1.1_20180117.xlsx",
     "bib_id": "huijbregts_recipe_2017",
     "citation": "Huijbregts 2017",
     "source_type": "Excel file"
   },
   {
     "id": "FEDEFL_INV",
     "name": "FEDEFL Inventory",
-    "version": "1.0.0",
+    "version": "1.1.0",
     "path": "fedefl",
-    "url": "http://www.github.com/usepa//Federal-LCA-Commons-Elementary-Flow-List",
+    "url": "https://github.com/USEPA/fedelemflowlist/blob/master/fedelemflowlist/subset_list.py",
     "citation": "",
     "source_type": "FEDEFL Python function"
   },
@@ -49,7 +49,7 @@
                 "ImpactWorld+ - Endpoint":"This method includes all global endpoint flows and their attributes."},
     "path": "impactworld",
     "case_insensitivity": "False",
-    "url": "http://www.impactworldplus.org/en/writeToFile.php",
+    "url": "https://www.dropbox.com/sh/2sdgbqf08yn91bc/AABIGLlb_OwfNy6oMMDZNrm0a/IWplus_public_v1.3.accdb?dl=1",
     "citation": "Bulle, Cecile, Manuele Margni, Laure Patouillard, Anne-Marie Boulay, Guillaume Bourgault, Vincent De Bruille, Viet Cao, et al. IMPACT World+: A Globally Regionalized Life Cycle Impact Assessment Method. The International Journal of Life Cycle Assessment 24, no. 9 (September 2019), 1653–74. https://doi.org/10.1007/s11367-019-01583-0",
     "source_type": "Access file"
   },
@@ -67,6 +67,17 @@
                 },
     "citation": "Forster and Ramaswamy 2007 (AR4), Myhre and Shindell 2013 (AR5), Forster and Storelvmo 2021 (AR6)",
     "source_type": "csv"
+  },
+  {
+    "id": "CED",
+    "name": "Cumulative Energy Demand",
+    "version": "1.0",
+    "detail_note": "All heating values are per the FEDEFL, and the list of external references is found on the EPA FEDEFL GitHub at: https://github.com/USEPA/fedelemflowlist. This CED method is based on the categorization scheme used in Frischknecht et al. (2007) found in the ecoinvent report 'Implementation of Life Cycle Impact Assessment Methods.'",
+    "path": "fedefl",
+    "bib_id": "frischknecht_implementation_2007",
+    "url": "https://github.com/USEPA/fedelemflowlist/blob/master/fedelemflowlist/subset_list.py",
+    "citation": "Frischknecht et al. 2007",
+    "source_type": ""
   }
 
 ]

lciafmt/fedefl_inventory.py

@@ -27,7 +27,8 @@ def get(subset=None) -> pd.DataFrame:
         method['Characterization Factor'])
 
     if subset is None:
-        list_of_inventories = subsets.get_subsets()
+        list_of_inventories = [s for s in subsets.get_subsets() if s
+                               not in ('ced')]
     else:
         list_of_inventories = subset
 
@@ -39,7 +40,7 @@ def get(subset=None) -> pd.DataFrame:
                    axis=1, inplace=True)
         flows['Indicator'] = inventory
         flows['Indicator unit'] = subsets.get_inventory_unit(inventory)
-        flows['Characterization Factor'] = 1
+        flows['Characterization Factor'] = 1.0
 
         # Apply unit conversions where flow unit differs from indicator unit
         flows_w_conversion = pd.merge(flows, alt_units, how='left',
@@ -56,3 +57,6 @@ def get(subset=None) -> pd.DataFrame:
 
     method['Method'] = 'FEDEFL Inventory'
     return method
+
+if __name__ == "__main__":
+    df = get()

lciafmt/iw.py

@@ -6,6 +6,7 @@
 """
 
 import pandas as pd
+import lciafmt
 import lciafmt.cache as cache
 import lciafmt.df as dfutil
 from lciafmt.util import log, format_cas
@@ -38,13 +39,10 @@ def get(file=None, url=None, region=None) -> pd.DataFrame:
             "Please install drivers to remotely connect to Access Database. "
             "Drivers only available on windows platform. For instructions visit: "
             "https://github.com/mkleehammer/pyodbc/wiki/Connecting-to-Microsoft-Access")
-
+    method_meta = lciafmt.Method.ImpactWorld.get_metadata()
     f = file
     if f is None:
-        fname = "Impact_World.accdb"
-        if url is None:
-            url = "https://www.dropbox.com/sh/2sdgbqf08yn91bc/AABIGLlb_OwfNy6oMMDZNrm0a/IWplus_public_v1.3.accdb?dl=1"
-        f = cache.get_or_download(fname, url)
+        f = _get_file(method_meta, url)
     df = _read(f, region)
 
     # Identify midpoint and endpoint records and differentiate in data frame.
@@ -58,6 +56,12 @@ def get(file=None, url=None, region=None) -> pd.DataFrame:
 
     return df
 
+def _get_file(method_meta, url=None):
+    fname = "Impact_World.accdb"
+    if url is None:
+        url = method_meta['url']
+    f = cache.get_or_download(fname, url)
+    return f
 
 def _read(access_file: str, region) -> pd.DataFrame:
     """Read the Access database at passed access_file into DataFrame."""

lciafmt/jsonld.py

@@ -74,7 +74,7 @@ def write(self, df: pd.DataFrame, write_flows=False, preferred_only=False):
             indicator = self.__indicator(row)
             factor = o.ImpactFactor()
             unit = row['Unit']
-            factor.flow = self.__flow(row)
+            factor.flow = self.__flow(row).to_ref()
             factor.flow_property = units.property_ref(unit)
             factor.unit = units.unit_ref(unit)
             factor.value = row['Characterization Factor']

lciafmt/recipe.py

@@ -9,6 +9,7 @@
 import pandas as pd
 import openpyxl
 
+import lciafmt
 import lciafmt.cache as cache
 import lciafmt.df as dfutil
 import lciafmt.xls as xls
@@ -52,13 +53,10 @@ def get(add_factors_for_missing_contexts=True, endpoint=True,
     :return: DataFrame of method in standard format
     """
     log.info("getting method ReCiPe 2016")
+    method_meta = lciafmt.Method.RECIPE_2016.get_metadata()
     f = file
     if f is None:
-        fname = "recipe_2016.xlsx"
-        if url is None:
-            url = ("http://www.rivm.nl/sites/default/files/2018-11/" +
-                   "ReCiPe2016_CFs_v1.1_20180117.xlsx")
-        f = cache.get_or_download(fname, url)
+        f = _get_file(method_meta, url)
     df = _read(f)
     if add_factors_for_missing_contexts:
         log.info("adding average factors for primary contexts")
@@ -135,6 +133,14 @@ def get(add_factors_for_missing_contexts=True, endpoint=True,
     return df
 
 
+def _get_file(method_meta, url=None):
+    fname = "recipe_2016.xlsx"
+    if url is None:
+        url = method_meta['url']
+    f = cache.get_or_download(fname, url)
+    return f
+
+
 def _read(file: str) -> pd.DataFrame:
     log.info(f"read ReCiPe 2016 from file {file}")
     wb = openpyxl.load_workbook(file, read_only=True, data_only=True)
@@ -171,7 +177,7 @@ def _read_endpoints(file: str) -> pd.DataFrame:
                 continue
             endpoints['Method'] = "ReCiPe 2016 - Midpoint/" + perspectives[i]
             endpoints['EndpointMethod'] = "ReCiPe 2016 - Endpoint/" + perspectives[i]
-            endpoints['EndpointIndicator'] = indicator
+            endpoints['EndpointIndicator'] = indicator.replace(' -a', ' - a') # fix missing space
             endpoints['EndpointUnit'] = indicator_unit
             endpoints['EndpointConversion'] = val
             endpoint = pd.concat(
@@ -215,6 +221,7 @@ def _read_mid_points(sheet: openpyxl.worksheet.worksheet.Worksheet,
     cas_col = _find_cas_column(sheet)
     indicator_unit, flow_unit, unit_col = _determine_units(sheet)
     compartment, compartment_col = _determine_compartments(sheet)
+    sheet_title = sheet.title.replace('Ecosyste damage', 'Ecosystem damage')
 
     perspectives = ["I", "H", "E"]
     factor_count = 0
@@ -238,7 +245,7 @@ def _read_mid_points(sheet: openpyxl.worksheet.worksheet.Worksheet,
                     continue
                 dfutil.record(records,
                               method="ReCiPe 2016 - Midpoint/" + perspectives[i],
-                              indicator=sheet.title,
+                              indicator=sheet_title,
                               indicator_unit=indicator_unit,
                               flow=xls.cell_str(row[flow_col]),
                               flow_category=compartment,
@@ -253,7 +260,7 @@ def _read_mid_points(sheet: openpyxl.worksheet.worksheet.Worksheet,
             for p in perspectives:
                 dfutil.record(records,
                               method="ReCiPe 2016 - Midpoint/" + p,
-                              indicator=sheet.title,
+                              indicator=sheet_title,
                               indicator_unit=indicator_unit,
                               flow=xls.cell_str(row[flow_col]),
                               flow_category=compartment,