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brightway_intro.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### *Author: Thomas Sonderegger (sonderegger@ifu.baug.ethz.ch)*\n",
"\n",
"# Getting started with Brightway2 and Ecoinvent\n",
"\n",
"This noteboook shows you how to manage Brightway2 projects and how to import Ecoinvent data (here version 3.4) in order to do LCA. It is based on the notebooks from the <a href=\"https://docs.brightwaylca.org/notebooks.html\">Brightway2 documentation</a>.\n",
"\n",
"\n",
"**Index**\n",
"* [Setting up a project](#Setting-up-a-project)\n",
"* [Setting up databases and LCIA methods](#Setting-up-databases-and-LCIA-methods)\n",
"* [Looking at and searching databases and LCIA methods](#Looking-at-and-searching-databases-and-LCIA-methods)\n",
"* [Selecting from databases and LCIA methods](#Selecting-from-databases-and-LCIA-methods)\n",
"* [Basic LCA calculations](#Basic-LCA-calculations)\n",
"* [Other cool stuff you can do](#Other-cool-stuff-you-can-do)\n",
"___________________________________________________________________________________________________________________\n",
"\n",
"First, we need to import Brightway2:"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import brightway2 as bw"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Setting up a project\n",
"\n",
"From the <a href=\"https://docs.brightwaylca.org/intro.html\">Brightway2 documentation</a>: Data in Brightway2 is structured in a hierarchy. At the top level, we have projects. A project is self-contained, with its own copy of data, LCIA methods, calculations, assumptions, and any other data you need. Each project is completely independent of other projects. Projects are saved as subdirectories in the file system."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Creating/setting, copying, and deleting projects:"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"Brightway2 projects manager with 3 objects:\n",
"\tbw2-vs-simapro\n",
"\tdefault\n",
"\tei22-import\n",
"Use `projects.report()` to get a report on all projects."
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bw.projects"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"bw.projects.set_current(\"brightway-intro\") # creates and sets a project"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Brightway2 projects manager with 4 objects:\n",
"\tbrightway-intro\n",
"\tbw2-vs-simapro\n",
"\tdefault\n",
"\tei22-import\n",
"Use `projects.report()` to get a report on all projects."
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bw.projects # lists projects"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Brightway2 projects manager with 5 objects:\n",
"\tbrightway-intro\n",
"\tbrightway-intro-copy\n",
"\tbw2-vs-simapro\n",
"\tdefault\n",
"\tei22-import\n",
"Use `projects.report()` to get a report on all projects."
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bw.projects.copy_project(\"brightway-intro-copy\") # copies current project (brightway-intro)\n",
"bw.projects"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'brightway-intro-copy'"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bw.projects.current"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"bw.projects.set_current(\"brightway-intro\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The following command deletes a project from the project list and the project folder from the directory (make sure another project than the one you want to delete is active!). If you only want to delete the project from the project list, don't use the `delete_dir=True`-command."
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Brightway2 projects manager with 4 objects:\n",
"\tbrightway-intro\n",
"\tbw2-vs-simapro\n",
"\tdefault\n",
"\tei22-import\n",
"Use `projects.report()` to get a report on all projects."
]
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bw.projects.delete_project(\"brightway-intro-copy\", delete_dir=True)\n",
"bw.projects"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'brightway-intro'"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bw.projects.current"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is the directory where the projects are stored:"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'C:\\\\Users\\\\Sonderegger\\\\AppData\\\\Local\\\\pylca\\\\Brightway3\\\\brightway-intro.ea95076bb23037791dc831280040d63d'"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bw.projects.dir"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"# Setting up databases and LCIA methods\n",
"\n",
"Once you have run this section, your project has all the databases it needs and you don't need to rerun this part of the code!"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"## Databases\n",
"From the <a href=\"https://docs.brightwaylca.org/intro.html\">Brightway2 documentation</a>: In Brightway2, a database is the object used to organize a set of nodes and edges in a life cycle inventory graph of the industrial supply chain and natural world. For example, a specific version of ecoinvent could be a database, but so would a set of biosphere flows, as biosphere flows are also nodes in our inventory graph. Databases can be big, like ecoinvent, or as small as a single dataset. You can have as many databases as you like, and databases can have links into other databases. You can also have databases that each depend on each other.\n",
"\n",
"So far, there is no database in our project:"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Databases dictionary with 0 objects"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bw.databases"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## The Biosphere Database\n",
"\n",
"The `bw2setup()` command creates a default biosphere3 database (has all the resource and emission flows from the ecoinvent database, elementary flow names are normalized to the ecoinvent 3 standard) and installs default LCIA methods:"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Creating default biosphere\n",
"\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Writing activities to SQLite3 database:\n",
"0% 100%\n",
"[#### ] | ETA: 00:00:00"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Applying strategy: normalize_units\n",
"Applying strategy: drop_unspecified_subcategories\n",
"Applied 2 strategies in 0.00 seconds\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"[##############################] | ETA: 00:00:00\n",
"Total time elapsed: 00:00:00\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Title: Writing activities to SQLite3 database:\n",
" Started: 05/28/2018 11:07:15\n",
" Finished: 05/28/2018 11:07:16\n",
" Total time elapsed: 00:00:00\n",
" CPU %: 91.30\n",
" Memory %: 1.55\n",
"Created database: biosphere3\n",
"Creating default LCIA methods\n",
"\n",
"Applying strategy: normalize_units\n",
"Applying strategy: set_biosphere_type\n",
"Applying strategy: drop_unspecified_subcategories\n",
"Applying strategy: link_iterable_by_fields\n",
"Applied 4 strategies in 1.30 seconds\n",
"Wrote 718 LCIA methods with 178008 characterization factors\n",
"Creating core data migrations\n",
"\n"
]
}
],
"source": [
"bw.bw2setup()"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"Now we have the biosphere3 database in our project:"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Databases dictionary with 1 object(s):\n",
"\tbiosphere3"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bw.databases"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Importing Ecoinvent\n",
"\n",
"There are two ways on how to get Ecoinvent data (here version 3.4) into your project, one with direct download within this notebook and one where you download the Ecoinvent data to your harddisk first. We are going to use the cutoff system model here (version 3.4), which is similar to the Ecoinvent 1.x and 2.x system model.\n",
"\n",
"For the first approach, you need to have the eidl-package installed (`conda install eidl`).\n",
"\n",
"For the second approach you need to downlaod the Ecoinvent database from <a href=\"https://www.ecoinvent.org\">ecoinvent.org</a> (from the `Files` tab), take the following:\n",
"* ecoinvent 3.4_cutoff_ecoSpold02.7z"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Code for approach 1\n",
"\n",
"(You only need to run code for approach 1 OR approach 2!)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"import eidl"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ecoinvent username: studentethz\n",
"ecoinvent password: ········\n",
"logging in to ecoinvent homepage...\n",
"login successful!\n",
"\n",
" available versions:\n",
"a 3.4\n",
"b 3.3\n",
"c 3.2\n",
"d 3.1\n",
"e 3.01\n",
"version: 3.4\n",
"\n",
" system models:\n",
"a apos\n",
"b consequential\n",
"c cutoff\n",
"system model: c\n",
"downloading cutoff 3.4 ...\n",
"download finished!: C:\\Users\\SONDER~1\\AppData\\Local\\Temp\\tmpqv593q7v\\cutoff34.7z\n",
"\n",
"patool: Extracting C:\\Users\\SONDER~1\\AppData\\Local\\Temp\\tmpqv593q7v\\cutoff34.7z ...\n",
"patool: running \"C:\\Program Files\\7-Zip\\7z.EXE\" x -oC:\\Users\\SONDER~1\\AppData\\Local\\Temp\\tmpqv593q7v -- C:\\Users\\SONDER~1\\AppData\\Local\\Temp\\tmpqv593q7v\\cutoff34.7z\n",
"patool: ... C:\\Users\\SONDER~1\\AppData\\Local\\Temp\\tmpqv593q7v\\cutoff34.7z extracted to `C:\\Users\\SONDER~1\\AppData\\Local\\Temp\\tmpqv593q7v'.\n",
"Extracting XML data from 14889 datasets\n",
"Extracted 14889 datasets in 51.07 seconds\n",
"Applying strategy: normalize_units\n",
"Applying strategy: remove_zero_amount_coproducts\n",
"Applying strategy: remove_zero_amount_inputs_with_no_activity\n",
"Applying strategy: remove_unnamed_parameters\n",
"Applying strategy: es2_assign_only_product_with_amount_as_reference_product\n",
"Applying strategy: assign_single_product_as_activity\n",
"Applying strategy: create_composite_code\n",
"Applying strategy: drop_unspecified_subcategories\n",
"Applying strategy: link_biosphere_by_flow_uuid\n",
"Applying strategy: link_internal_technosphere_by_composite_code\n",
"Applying strategy: delete_exchanges_missing_activity\n",
"Applying strategy: delete_ghost_exchanges\n",
"Applying strategy: remove_uncertainty_from_negative_loss_exchanges\n",
"Applying strategy: fix_unreasonably_high_lognormal_uncertainties\n",
"Applying strategy: set_lognormal_loc_value\n",
"Applied 15 strategies in 4.08 seconds\n",
"14889 datasets\n",
"520205 exchanges\n",
"0 unlinked exchanges\n",
" \n",
"\n",
"Write database cutoff34 in project brightway-intro?\n",
"[y]/n y\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"Writing activities to SQLite3 database:\n",
"0% 100%\n",
"[##############################] | ETA: 00:00:00\n",
"Total time elapsed: 00:01:33\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Title: Writing activities to SQLite3 database:\n",
" Started: 05/28/2018 11:11:41\n",
" Finished: 05/28/2018 11:13:14\n",
" Total time elapsed: 00:01:33\n",
" CPU %: 72.20\n",
" Memory %: 14.21\n",
"Created database: cutoff34\n"
]
}
],
"source": [
"eidl.get_ecoinvent() # choose '3.4' and 'cutoff'"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Code for approach 2\n",
"\n",
"(You only need to run code for approach 1 OR approach 2!)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"cutoff34 = bw.SingleOutputEcospold2Importer(\n",
" \"C:/Users/Sonderegger/Documents/ecoinvent_3/ecoinvent 3.4_cutoff_ecoSpold02/datasets\",\n",
" \"cutoff34\")\n",
"ei34cutoff.apply_strategies()\n",
"ei34cutoff.statistics()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The data is now stored in the so called 'importer' (`cutoff34`). We can now write the database and the reduce memory use by setting the importer to `None`:"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"cutoff34"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"cutoff34.write_database()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"cutoff34 = None"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Looking at and searching databases and LCIA methods\n",
"Now that we have everything set up, let's have a look at the databases and methods."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We have two databases installed, the biosphere database and the ecoinvent database:"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Databases dictionary with 2 object(s):\n",
"\tbiosphere3\n",
"\tcutoff34"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bw.databases"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Activities and Exchanges\n",
"In the database, nodes are called activities, and include transforming and market activities, but also products and biosphere flows. Edges are called exchanges, and describe a link between two nodes. An exchange could describe the\n",
"input of a product to a transforming activity, or an emission of a biosphere flow by an activity, or the name and amount of a product produced by an activity.\n",
"\n",
"Let's see how many flows/activities there are in our databases, and then look at one random flow/activity:"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of flows in `biosphere3`: 4079\n",
"'Dimethenamid' (kilogram, None, ('soil', 'agricultural'))\n"
]
}
],
"source": [
"bio = bw.Database(\"biosphere3\")\n",
"print(\"Number of flows in `biosphere3`:\", len(bio))\n",
"random_flow = bio.random()\n",
"print(random_flow)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The data output is structured as follows: `'Name' (unit, locoation, ('categories'))`.\n",
"We can select those one by one (for location it won't work becaus no location is given):"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Dimethenamid\n",
"kilogram\n",
"('soil', 'agricultural')\n"
]
}
],
"source": [
"print(random_flow['name'])\n",
"print(random_flow['unit'])\n",
"print(random_flow['categories'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Furthermore, we can check the type (for the biosphere database 'emission' or 'natural resource')"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"emission\n"
]
}
],
"source": [
"print(random_flow['type'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's repeat the procedure for the Ecoinvent database:"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of flows in `ecoinvent 3.4 cutoff`: 14889\n",
"'treatment of coal gas, in power plant' (kilowatt hour, SK, None)\n"
]
}
],
"source": [
"eco = bw.Database('cutoff34')\n",
"print(\"Number of flows in `ecoinvent 3.4 cutoff`:\", len(eco))\n",
"random_activity = eco.random()\n",
"print(random_activity)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"treatment of coal gas, in power plant\n",
"kilowatt hour\n",
"SK\n"
]
}
],
"source": [
"print(random_activity['name'])\n",
"print(random_activity['unit'])\n",
"print(random_activity['location'])"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"process\n"
]
}
],
"source": [
"print(random_activity['type'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Keys and codes\n",
"\n",
"Brightway2 uses keys to identify datasets. The key tuple contains the database and a unique code, called the unique identifier. The code can be anything - a number, a UUID, or just a name. All of the following would be valid keys:\n",
"\n",
" (\"biosphere\", \"f66d00944691d54d6b072310b6f9de37\")\n",
" (\"my new database\", \"building my dream house\")\n",
" (\"skynet\", 14832)\n",
"\n",
"From the <a href=\"https://docs.brightwaylca.org/intro.html\">Brightway2 documentation</a>: Linking activity datasets within and between databases requires a way to uniquely identify each dataset. When you create datasets manually, you will need to assign each dataset a code. When you import a database, the codes will be automatically generated for you.\n",
"\n",
"When you import an ecospold or SimaPro dataset, the data format does not provide a way to uniquely identify each dataset. Brightway2 will generate codes that look like a bunch of nonsense, e.g.: `6d336c64e3a0ff08dee166a1dfdf0946`. In this case, Brightway2 identifies an activity or flow with the MD5\n",
"hash of a few attributes: For ecoinvent 2, the name, location, unit, and categories. For ecoinvent 3, the activity and reference product names.\n",
"\n",
"The following command gives you the keys for the random flow/activity:"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('biosphere3', '71525276-3417-4d4b-9af8-0baa265de4a2')\n",
"('cutoff34', 'e58cd81275e6740f46e42b67871b2563')\n"
]
}
],
"source": [
"print(random_flow.key)\n",
"print(random_activity.key)"
]
},
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"### Searching datasets\n",
"\n",
"Every database is added to a search engine powered by <a href=\"https://bitbucket.org/mchaput/whoosh/wiki/Home\">Whoosh</a>. Searching covers the following data fields:\n",
"\n",
"* name\n",
"* comment\n",
"* product\n",
"* categories\n",
"* location\n",
"\n",
"Searching is done by using the `Database.search` method.\n"
]
},
{
"cell_type": "code",
"execution_count": 24,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"['Carbon dioxide, fossil' (kilogram, None, ('air',)),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'low population density, long-term')),\n",
" 'Carbon dioxide, in air' (kilogram, None, ('natural resource', 'in air')),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'non-urban air or from high stacks')),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'urban air close to ground')),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'lower stratosphere + upper troposphere')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'non-urban air or from high stacks')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air',)),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'urban air close to ground')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'low population density, long-term')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'lower stratosphere + upper troposphere')),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil',)),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'lower stratosphere + upper troposphere')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'indoor')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'non-urban air or from high stacks')),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil', 'agricultural')),\n",
" 'Carbon dioxide, non-fossil, from calcination' (kilogram, None, ['air']),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air',)),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil', 'forestry')),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil', 'industrial')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'low population density, long-term')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'urban air close to ground'))]"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bio.search(\"carbon dioxide\") # by default maximally 25 search results are returned"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Searches can also be filtered (where only the results that meet the specified criteria are included) or masked (where results that meet the specified criteria are excluded):"
]
},
{
"cell_type": "code",
"execution_count": 25,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Excluding 18 filtered results\n"
]
},
{
"data": {
"text/plain": [
"['Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil',)),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil', 'agricultural')),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil', 'forestry')),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil', 'industrial'))]"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bio.search(\"carbon dioxide\", filter={\"categories\": 'soil'})"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Excluding 4 filtered results\n"
]
},
{
"data": {
"text/plain": [
"['Carbon dioxide, fossil' (kilogram, None, ('air',)),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'low population density, long-term')),\n",
" 'Carbon dioxide, in air' (kilogram, None, ('natural resource', 'in air')),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'non-urban air or from high stacks')),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'urban air close to ground')),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'lower stratosphere + upper troposphere')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'non-urban air or from high stacks')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air',)),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'urban air close to ground')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'low population density, long-term')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'lower stratosphere + upper troposphere')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'lower stratosphere + upper troposphere')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'indoor')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'non-urban air or from high stacks')),\n",
" 'Carbon dioxide, non-fossil, from calcination' (kilogram, None, ['air']),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air',)),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'low population density, long-term')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'urban air close to ground'))]"
]
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bio.search(\"carbon dioxide\", mask={\"categories\": 'soil'})"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Because accessing activities in the database is quite fast, you can also filter the activities you want by just iterating over the entire database:"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"['Carbon dioxide, fossil' (kilogram, None, ('air',)),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'low population density, long-term')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'non-urban air or from high stacks')),\n",
" 'Carbon dioxide, in air' (kilogram, None, ('natural resource', 'in air')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'low population density, long-term')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'non-urban air or from high stacks')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air',)),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'low population density, long-term')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'indoor')),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'urban air close to ground')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'lower stratosphere + upper troposphere')),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil', 'agricultural')),\n",
" 'Carbon dioxide, non-fossil, from calcination' (kilogram, None, ['air']),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'lower stratosphere + upper troposphere')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'urban air close to ground')),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil', 'industrial')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'urban air close to ground')),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'non-urban air or from high stacks')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'lower stratosphere + upper troposphere')),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil',)),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air',)),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil', 'forestry'))]"
]
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"my_activities = [x for x in bio if 'Carbon dioxide' in x['name']]\n",
"my_activities"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This is nice because we can order the database first:"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"['Carbon dioxide, fossil' (kilogram, None, ('air', 'lower stratosphere + upper troposphere')),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air',)),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'non-urban air or from high stacks')),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'low population density, long-term')),\n",
" 'Carbon dioxide, fossil' (kilogram, None, ('air', 'urban air close to ground')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'indoor')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'lower stratosphere + upper troposphere')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'non-urban air or from high stacks')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'low population density, long-term')),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air',)),\n",
" 'Carbon dioxide, from soil or biomass stock' (kilogram, None, ('air', 'urban air close to ground')),\n",
" 'Carbon dioxide, in air' (kilogram, None, ('natural resource', 'in air')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'low population density, long-term')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'lower stratosphere + upper troposphere')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'urban air close to ground')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air', 'non-urban air or from high stacks')),\n",
" 'Carbon dioxide, non-fossil' (kilogram, None, ('air',)),\n",
" 'Carbon dioxide, non-fossil, from calcination' (kilogram, None, ['air']),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil', 'agricultural')),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil',)),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil', 'industrial')),\n",
" 'Carbon dioxide, to soil or biomass stock' (kilogram, None, ('soil', 'forestry'))]"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bio.order_by = \"name\"\n",
"my_activities = [x for x in bio if 'Carbon dioxide' in x['name']]\n",
"my_activities"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"bio.order_by = None # removes any ordering"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## LCIA methods\n",
"Number of installed methods:"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {
"scrolled": false
},
"outputs": [
{
"data": {
"text/plain": [
"718"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(bw.methods)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Because LCIA methods have many different impact categories, they are identified not by a single label, but by a list of labels. Let's look at an example:"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"('EDIP2003', 'land filling', 'radioactive waste')"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"method_key = bw.methods.random()\n",
"method_key"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We can now load the method data.\n",
"Method data has the format: `('biosphere flow'), numeric value, location`\n",
"\n",
"where\n",
"* `biosphere flow` is a dataset from any database which is used as a biosphere flow.\n",
"* `numeric value` can be either a fixed number or an uncertainty distribution.\n",
"* `location` is optional (default location does not show)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of CFs: 2\n"
]
},
{
"data": {
"text/plain": [
"[(('biosphere3', 'f6df5030-8e06-4276-bfeb-219db8dab104'), 2500.0),\n",
" (('biosphere3', 'adb4b590-7fb2-47b6-84e7-d4746a94c7b5'), 5400.0)]"
]
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"method = bw.Method(method_key)\n",
"method_data = method.load()\n",
"print(\"Number of CFs:\", len(method_data))\n",
"method_data[:10]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Furthermore, we can look at the method's metadata, there we also find the unit:"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'abbreviation': 'edip2003lr.76dedbd6b1f45160f0bc883d6aa0d75b',\n",
" 'description': 'Danish method. The factors here represent only the first step within the three steps of the method - i.e. the environmental impact potentials / ressource consumption potentials. The following normalization and weighting steps are not included in these factors here.',\n",
" 'filename': 'LCIA_implementation_3.3.xlsx',\n",
" 'num_cfs': 2,\n",
" 'unit': 'kg waste'}"
]
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"method.metadata"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Selecting from databases and LCIA methods\n",
"First, we select an activity from the Ecoinvent database. In order to find a conventional passenger car, we search for \"car\" with the the `search`-command:"
]
},
{
"cell_type": "code",
"execution_count": 34,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"['transport, passenger car' (kilometer, RER, None),\n",
" 'transport, passenger car' (kilometer, RoW, None),\n",
" 'glider production, passenger car' (kilogram, GLO, None),\n",
" 'passenger car production, diesel' (kilogram, GLO, None),\n",
" 'maintenance, passenger car' (unit, RER, None),\n",
" 'maintenance, passenger car' (unit, RoW, None),\n",
" 'transport, passenger car, EURO 5' (kilometer, RoW, None),\n",
" 'transport, passenger car, EURO 5' (kilometer, RER, None),\n",
" 'transport, passenger car, EURO 4' (kilometer, RER, None),\n",
" 'transport, passenger car, EURO 3' (kilometer, RER, None),\n",
" 'transport, passenger car, EURO 4' (kilometer, RoW, None),\n",
" 'transport, passenger car, EURO 3' (kilometer, RoW, None),\n",
" 'transport, passenger car, electric' (kilometer, GLO, None),\n",
" 'charger production, for electric passenger car' (kilogram, GLO, None),\n",
" 'inverter production, for electric passenger car' (kilogram, GLO, None),\n",
" 'converter production, for electric passenger car' (kilogram, GLO, None),\n",
" 'powertrain production, for electric passenger car' (kilogram, GLO, None),\n",
" 'passenger car production, petrol/natural gas' (kilogram, GLO, None),\n",
" 'passenger car production, electric, without battery' (kilogram, GLO, None),\n",
" 'transport, passenger car with internal combustion engine' (kilometer, RER, None),\n",
" 'transport, passenger car with internal combustion engine' (kilometer, RoW, None),\n",
" 'internal combustion engine production, passenger car' (kilogram, GLO, None),\n",
" 'treatment of used glider, passenger car, shredding' (kilogram, GLO, None),\n",
" 'market for passenger car, diesel' (kilogram, GLO, None),\n",
" 'market for transport, passenger car' (kilometer, RoW, None)]"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"eco.search(\"car\")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's go with `'passenger car production, petrol/natural gas' (kilogram, GLO, None)`.\n",
"\n",
"Since `eco.search()` gives back a list, we need to choose the first item from the list to get the activity in the format we need (i.e. as <a href=\"https://docs.brightwaylca.org/lca.html\">*Activity proxy*</a>):"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'passenger car production, petrol/natural gas' (kilogram, GLO, None)"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"activity = eco.search(\"'passenger car production, petrol/natural gas'\")[0]\n",
"activity"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now check the type of `activity` and you will see that it is an *Activity proxy*:"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"bw2data.backends.peewee.proxies.Activity"
]
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"type(activity)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The *Activity proxy* knows how to pretend to be a key tuple. This means that `activity` contains the two elements, which define the key tuple:"
]
},
{
"cell_type": "code",
"execution_count": 37,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"cutoff34 1f49d6d756da5b89683a9b597803ae26\n",
"('cutoff34', '1f49d6d756da5b89683a9b597803ae26')\n"
]
}
],
"source": [
"print(activity[0], activity[1])\n",
"print(activity.key)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If we knew the unique code from the key, we could also select `'passenger car production, petrol/natural gas' (kilogram, GLO, None)` from the database by typing: "
]
},
{
"cell_type": "code",
"execution_count": 38,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'passenger car production, petrol/natural gas' (kilogram, GLO, None)"
]
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"activity = eco.get('1f49d6d756da5b89683a9b597803ae26')\n",
"activity"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now we need to select a method. The `search`-command does not work. Therefore, we make a list of the methods that we can search through:"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"[('CML 2001', 'acidification potential', 'average European'),\n",
" ('CML 2001', 'acidification potential', 'generic'),\n",
" ('CML 2001', 'climate change', 'GWP 100a'),\n",
" ('CML 2001', 'climate change', 'GWP 20a'),\n",
" ('CML 2001', 'climate change', 'GWP 500a'),\n",
" ('CML 2001', 'climate change', 'lower limit of net GWP'),\n",
" ('CML 2001', 'climate change', 'upper limit of net GWP'),\n",
" ('CML 2001', 'eutrophication potential', 'average European'),\n",
" ('CML 2001', 'eutrophication potential', 'generic'),\n",
" ('CML 2001', 'freshwater aquatic ecotoxicity', 'FAETP 100a'),\n",
" ('CML 2001', 'freshwater aquatic ecotoxicity', 'FAETP 20a'),\n",
" ('CML 2001', 'freshwater aquatic ecotoxicity', 'FAETP 500a'),\n",
" ('CML 2001', 'freshwater aquatic ecotoxicity', 'FAETP infinite'),\n",
" ('CML 2001', 'freshwater sediment ecotoxicity', 'FSETP 100a'),\n",
" ('CML 2001', 'freshwater sediment ecotoxicity', 'FSETP 20a'),\n",
" ('CML 2001', 'freshwater sediment ecotoxicity', 'FSETP 500a'),\n",
" ('CML 2001', 'freshwater sediment ecotoxicity', 'FSETP infinite'),\n",
" ('CML 2001', 'human toxicity', 'HTP 100a'),\n",
" ('CML 2001', 'human toxicity', 'HTP 20a'),\n",
" ('CML 2001', 'human toxicity', 'HTP 500a'),\n",
" ('CML 2001', 'human toxicity', 'HTP infinite'),\n",
" ('CML 2001', 'ionising radiation', 'ionising radiation'),\n",
" ('CML 2001', 'land use', 'competition'),\n",
" ('CML 2001', 'malodours air', 'malodours air'),\n",
" ('CML 2001', 'marine aquatic ecotoxicity', 'MAETP 100a'),\n",
" ('CML 2001', 'marine aquatic ecotoxicity', 'MAETP 20a'),\n",
" ('CML 2001', 'marine aquatic ecotoxicity', 'MAETP 500a'),\n",
" ('CML 2001', 'marine aquatic ecotoxicity', 'MAETP infinite'),\n",
" ('CML 2001', 'marine sediment ecotoxicity', 'MSETP 100a'),\n",
" ('CML 2001', 'marine sediment ecotoxicity', 'MSETP 20a'),\n",
" ('CML 2001', 'marine sediment ecotoxicity', 'MSETP 500a'),\n",
" ('CML 2001', 'marine sediment ecotoxicity', 'MSETP infinite'),\n",
" ('CML 2001', 'photochemical oxidation (summer smog)', 'EBIR'),\n",
" ('CML 2001', 'photochemical oxidation (summer smog)', 'MIR'),\n",
" ('CML 2001', 'photochemical oxidation (summer smog)', 'MOIR'),\n",
" ('CML 2001', 'photochemical oxidation (summer smog)', 'high NOx POCP'),\n",
" ('CML 2001', 'photochemical oxidation (summer smog)', 'low NOx POCP'),\n",
" ('CML 2001', 'resources', 'depletion of abiotic resources'),\n",
" ('CML 2001', 'stratospheric ozone depletion', 'ODP 10a'),\n",
" ('CML 2001', 'stratospheric ozone depletion', 'ODP 15a'),\n",
" ('CML 2001', 'stratospheric ozone depletion', 'ODP 20a'),\n",
" ('CML 2001', 'stratospheric ozone depletion', 'ODP 25a'),\n",
" ('CML 2001', 'stratospheric ozone depletion', 'ODP 30a'),\n",
" ('CML 2001', 'stratospheric ozone depletion', 'ODP 40a'),\n",
" ('CML 2001', 'stratospheric ozone depletion', 'ODP 5a'),\n",
" ('CML 2001', 'stratospheric ozone depletion', 'ODP steady state'),\n",
" ('CML 2001', 'terrestrial ecotoxicity', 'TAETP 100a'),\n",
" ('CML 2001', 'terrestrial ecotoxicity', 'TAETP 20a'),\n",
" ('CML 2001', 'terrestrial ecotoxicity', 'TAETP 500a'),\n",
" ('CML 2001', 'terrestrial ecotoxicity', 'TAETP infinite'),\n",
" ('CML 2001 w/o LT',\n",
" 'acidification potential w/o LT',\n",
" 'average European w/o LT'),\n",
" ('CML 2001 w/o LT', 'acidification potential w/o LT', 'generic w/o LT'),\n",
" ('CML 2001 w/o LT', 'climate change w/o LT', 'GWP 100a w/o LT'),\n",
" ('CML 2001 w/o LT', 'climate change w/o LT', 'GWP 20a w/o LT'),\n",
" ('CML 2001 w/o LT', 'climate change w/o LT', 'GWP 500a w/o LT'),\n",
" ('CML 2001 w/o LT', 'climate change w/o LT', 'lower limit of net GWP w/o LT'),\n",
" ('CML 2001 w/o LT', 'climate change w/o LT', 'upper limit of net GWP w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'eutrophication potential w/o LT',\n",
" 'average European w/o LT'),\n",
" ('CML 2001 w/o LT', 'eutrophication potential w/o LT', 'generic w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'freshwater aquatic ecotoxicity w/o LT',\n",
" 'FAETP 100a w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'freshwater aquatic ecotoxicity w/o LT',\n",
" 'FAETP 20a w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'freshwater aquatic ecotoxicity w/o LT',\n",
" 'FAETP 500a w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'freshwater aquatic ecotoxicity w/o LT',\n",
" 'FAETP infinite w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'freshwater sediment ecotoxicity w/o LT',\n",
" 'FSETP 100a w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'freshwater sediment ecotoxicity w/o LT',\n",
" 'FSETP 20a w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'freshwater sediment ecotoxicity w/o LT',\n",
" 'FSETP 500a w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'freshwater sediment ecotoxicity w/o LT',\n",
" 'FSETP infinite w/o LT'),\n",
" ('CML 2001 w/o LT', 'human toxicity w/o LT', 'HTP 100a w/o LT'),\n",
" ('CML 2001 w/o LT', 'human toxicity w/o LT', 'HTP 20a w/o LT'),\n",
" ('CML 2001 w/o LT', 'human toxicity w/o LT', 'HTP 500a w/o LT'),\n",
" ('CML 2001 w/o LT', 'human toxicity w/o LT', 'HTP infinite w/o LT'),\n",
" ('CML 2001 w/o LT', 'ionising radiation w/o LT', 'ionising radiation w/o LT'),\n",
" ('CML 2001 w/o LT', 'land use w/o LT', 'competition w/o LT'),\n",
" ('CML 2001 w/o LT', 'malodours air w/o LT', 'malodours air w/o LT'),\n",
" ('CML 2001 w/o LT', 'marine aquatic ecotoxicity w/o LT', 'MAETP 100a w/o LT'),\n",
" ('CML 2001 w/o LT', 'marine aquatic ecotoxicity w/o LT', 'MAETP 20a w/o LT'),\n",
" ('CML 2001 w/o LT', 'marine aquatic ecotoxicity w/o LT', 'MAETP 500a w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'marine aquatic ecotoxicity w/o LT',\n",
" 'MAETP infinite w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'marine sediment ecotoxicity w/o LT',\n",
" 'MSETP 100a w/o LT'),\n",
" ('CML 2001 w/o LT', 'marine sediment ecotoxicity w/o LT', 'MSETP 20a w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'marine sediment ecotoxicity w/o LT',\n",
" 'MSETP 500a w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'marine sediment ecotoxicity w/o LT',\n",
" 'MSETP infinite w/o LT'),\n",
" ('CML 2001 w/o LT', 'photochemical oxidation w/o LT', 'EBIR w/o LT'),\n",
" ('CML 2001 w/o LT', 'photochemical oxidation w/o LT', 'MIR w/o LT'),\n",
" ('CML 2001 w/o LT', 'photochemical oxidation w/o LT', 'MOIR w/o LT'),\n",
" ('CML 2001 w/o LT', 'photochemical oxidation w/o LT', 'high NOx POCP w/o LT'),\n",
" ('CML 2001 w/o LT', 'photochemical oxidation w/o LT', 'low NOx POCP w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'resources w/o LT',\n",
" 'depletion of abiotic resources w/o LT'),\n",
" ('CML 2001 w/o LT', 'stratospheric ozone depletion w/o LT', 'ODP 10a w/o LT'),\n",
" ('CML 2001 w/o LT', 'stratospheric ozone depletion w/o LT', 'ODP 15a w/o LT'),\n",
" ('CML 2001 w/o LT', 'stratospheric ozone depletion w/o LT', 'ODP 20a w/o LT'),\n",
" ('CML 2001 w/o LT', 'stratospheric ozone depletion w/o LT', 'ODP 25a w/o LT'),\n",
" ('CML 2001 w/o LT', 'stratospheric ozone depletion w/o LT', 'ODP 30a w/o LT'),\n",
" ('CML 2001 w/o LT', 'stratospheric ozone depletion w/o LT', 'ODP 40a w/o LT'),\n",
" ('CML 2001 w/o LT', 'stratospheric ozone depletion w/o LT', 'ODP 5a w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'stratospheric ozone depletion w/o LT',\n",
" 'ODP steady state w/o LT'),\n",
" ('CML 2001 w/o LT', 'terrestrial ecotoxicity w/o LT', 'TAETP 100a w/o LT'),\n",
" ('CML 2001 w/o LT', 'terrestrial ecotoxicity w/o LT', 'TAETP 20a w/o LT'),\n",
" ('CML 2001 w/o LT', 'terrestrial ecotoxicity w/o LT', 'TAETP 500a w/o LT'),\n",
" ('CML 2001 w/o LT',\n",
" 'terrestrial ecotoxicity w/o LT',\n",
" 'TAETP infinite w/o LT'),\n",
" ('EDIP', 'environmental impact', 'acidification'),\n",
" ('EDIP', 'environmental impact', 'ecotoxicity, acute, in water'),\n",
" ('EDIP', 'environmental impact', 'ecotoxicity, chronic, in soil'),\n",
" ('EDIP', 'environmental impact', 'ecotoxicity, chronic, in water'),\n",
" ('EDIP', 'environmental impact', 'ecotoxicity, in sewage treatment plants'),\n",
" ('EDIP', 'environmental impact', 'global warming, GWP 100a'),\n",
" ('EDIP', 'environmental impact', 'global warming, GWP 20a'),\n",
" ('EDIP', 'environmental impact', 'global warming, GWP 500a'),\n",
" ('EDIP', 'environmental impact', 'human toxicity, via air'),\n",
" ('EDIP', 'environmental impact', 'human toxicity, via soil'),\n",
" ('EDIP', 'environmental impact', 'human toxicity, via surface water'),\n",
" ('EDIP', 'environmental impact', 'land filling, bulk waste'),\n",
" ('EDIP', 'environmental impact', 'land filling, hazardous waste'),\n",
" ('EDIP', 'environmental impact', 'land filling, radioactive waste'),\n",
" ('EDIP', 'environmental impact', 'land filling, slag and ashes'),\n",
" ('EDIP', 'environmental impact', 'nutrient enrichment, combined potential'),\n",
" ('EDIP', 'environmental impact', 'nutrient enrichment, separate N potential'),\n",
" ('EDIP', 'environmental impact', 'nutrient enrichment, separate P potential'),\n",
" ('EDIP',\n",
" 'environmental impact',\n",
" 'photochemical ozone formation, high NOx POCP'),\n",
" ('EDIP',\n",
" 'environmental impact',\n",
" 'photochemical ozone formation, low NOx POCP'),\n",
" ('EDIP', 'environmental impact', 'stratospheric ozone depletion, ODP 100a'),\n",
" ('EDIP', 'environmental impact', 'stratospheric ozone depletion, ODP 20a'),\n",
" ('EDIP', 'environmental impact', 'stratospheric ozone depletion, ODP 5a'),\n",
" ('EDIP',\n",
" 'environmental impact',\n",
" 'stratospheric ozone depletion, ODP steady state'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, aluminium'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, antimony'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, brown coal'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, cadmium'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, cerium'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, coal'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, cobalt'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, copper'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, gold'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, iron'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, lanthanum'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, lead'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, manganese'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, mercury'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, molybdenum'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, natural gas'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, nickel'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, oil'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, palladium'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, platinum'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, silver'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, tantalum'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, tin'),\n",
" ('EDIP', 'resource consumption', 'non-renewable resources, zinc'),\n",
" ('EDIP', 'resource consumption', 'renewable resources, wood'),\n",
" ('EDIP w/o LT', 'environmental impact w/o LT', 'acidification w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'ecotoxicity, acute, in water w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'ecotoxicity, chronic, in soil w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'ecotoxicity, chronic, in water w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'ecotoxicity, in sewage treatment plants w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'global warming, GWP 100a w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'global warming, GWP 20a w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'global warming, GWP 500a w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'human toxicity, via air w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'human toxicity, via soil w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'human toxicity, via surface water w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'land filling, bulk waste w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'land filling, hazardous waste w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'land filling, radioactive waste w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'land filling, slag and ashes w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'nutrient enrichment, combined potential w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'nutrient enrichment, separate N potential w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'nutrient enrichment, separate P potential w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'photochemical ozone formation, high NOx POCP w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'photochemical ozone formation, low NOx POCP w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'stratospheric ozone depletion, ODP 100a w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'stratospheric ozone depletion, ODP 20a w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'stratospheric ozone depletion, ODP 5a w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'environmental impact w/o LT',\n",
" 'stratospheric ozone depletion, ODP steady state w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, aluminium w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, antimony w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, brown coal w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, cadmium w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, cerium w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, coal w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, cobalt w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, copper w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, gold w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, iron w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, lanthanum w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, lead w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, manganese w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, mercury w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, molybdenum w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, natural gas w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, nickel w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, oil w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, palladium w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, platinum w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, silver w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, tantalum w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, tin w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'non-renewable resources, zinc w/o LT'),\n",
" ('EDIP w/o LT',\n",
" 'resource consumption w/o LT',\n",
" 'renewable resources, wood w/o LT'),\n",
" ('EDIP2003', 'acidification', 'acidification'),\n",
" ('EDIP2003', 'ecotoxicity', 'acute, in water'),\n",
" ('EDIP2003', 'ecotoxicity', 'chronic, in soil'),\n",
" ('EDIP2003', 'ecotoxicity', 'chronic, in water'),\n",
" ('EDIP2003', 'ecotoxicity', 'in sewage treatment plants'),\n",
" ('EDIP2003', 'eutrophication', 'combined potential'),\n",
" ('EDIP2003', 'eutrophication', 'separate N potential'),\n",
" ('EDIP2003', 'eutrophication', 'separate P potential'),\n",
" ('EDIP2003', 'eutrophication', 'terrestrial eutrophication'),\n",
" ('EDIP2003', 'global warming', 'GWP 100a'),\n",
" ('EDIP2003', 'global warming', 'GWP 20a'),\n",
" ('EDIP2003', 'global warming', 'GWP 500a'),\n",
" ('EDIP2003', 'human toxicity', 'via air'),\n",
" ('EDIP2003', 'human toxicity', 'via soil'),\n",
" ('EDIP2003', 'human toxicity', 'via surface water'),\n",
" ('EDIP2003', 'land filling', 'bulk waste'),\n",
" ('EDIP2003', 'land filling', 'hazardous waste'),\n",
" ('EDIP2003', 'land filling', 'radioactive waste'),\n",
" ('EDIP2003', 'land filling', 'slag and ashes'),\n",
" ('EDIP2003', 'non-renewable resources', 'aluminium'),\n",
" ('EDIP2003', 'non-renewable resources', 'antimony'),\n",
" ('EDIP2003', 'non-renewable resources', 'brown coal'),\n",
" ('EDIP2003', 'non-renewable resources', 'cadmium'),\n",
" ('EDIP2003', 'non-renewable resources', 'cerium'),\n",
" ('EDIP2003', 'non-renewable resources', 'coal'),\n",
" ('EDIP2003', 'non-renewable resources', 'cobalt'),\n",
" ('EDIP2003', 'non-renewable resources', 'copper'),\n",
" ('EDIP2003', 'non-renewable resources', 'gold'),\n",
" ('EDIP2003', 'non-renewable resources', 'iron'),\n",
" ('EDIP2003', 'non-renewable resources', 'lanthanum'),\n",
" ('EDIP2003', 'non-renewable resources', 'lead'),\n",
" ('EDIP2003', 'non-renewable resources', 'manganese'),\n",
" ('EDIP2003', 'non-renewable resources', 'mercury'),\n",
" ('EDIP2003', 'non-renewable resources', 'molybdenum'),\n",
" ('EDIP2003', 'non-renewable resources', 'natural gas'),\n",
" ('EDIP2003', 'non-renewable resources', 'nickel'),\n",
" ('EDIP2003', 'non-renewable resources', 'oil'),\n",
" ('EDIP2003', 'non-renewable resources', 'palladium'),\n",
" ('EDIP2003', 'non-renewable resources', 'platinum'),\n",
" ('EDIP2003', 'non-renewable resources', 'silver'),\n",
" ('EDIP2003', 'non-renewable resources', 'tantalum'),\n",
" ('EDIP2003', 'non-renewable resources', 'tin'),\n",
" ('EDIP2003', 'non-renewable resources', 'zinc'),\n",
" ('EDIP2003', 'photochemical ozone formation', 'impacts on human health'),\n",
" ('EDIP2003', 'photochemical ozone formation', 'impacts on vegetation'),\n",
" ('EDIP2003', 'renewable resources', 'wood'),\n",
" ('EDIP2003', 'stratospheric ozone depletion', 'ODP total'),\n",
" ('EDIP2003 w/o LT', 'acidification w/o LT', 'acidification w/o LT'),\n",
" ('EDIP2003 w/o LT', 'ecotoxicity w/o LT', 'acute, in water w/o LT'),\n",
" ('EDIP2003 w/o LT', 'ecotoxicity w/o LT', 'chronic, in soil w/o LT'),\n",
" ('EDIP2003 w/o LT', 'ecotoxicity w/o LT', 'chronic, in water w/o LT'),\n",
" ('EDIP2003 w/o LT',\n",
" 'ecotoxicity w/o LT',\n",
" 'in sewage treatment plants w/o LT'),\n",
" ('EDIP2003 w/o LT', 'eutrophication w/o LT', 'combined potential w/o LT'),\n",
" ('EDIP2003 w/o LT', 'eutrophication w/o LT', 'separate N potential w/o LT'),\n",
" ('EDIP2003 w/o LT', 'eutrophication w/o LT', 'separate P potential w/o LT'),\n",
" ('EDIP2003 w/o LT',\n",
" 'eutrophication w/o LT',\n",
" 'terrestrial eutrophication w/o LT'),\n",
" ('EDIP2003 w/o LT', 'global warming w/o LT', 'GWP 100a w/o LT'),\n",
" ('EDIP2003 w/o LT', 'global warming w/o LT', 'GWP 20a w/o LT'),\n",
" ('EDIP2003 w/o LT', 'global warming w/o LT', 'GWP 500a w/o LT'),\n",
" ('EDIP2003 w/o LT', 'human toxicity w/o LT', 'via air w/o LT'),\n",
" ('EDIP2003 w/o LT', 'human toxicity w/o LT', 'via soil w/o LT'),\n",
" ('EDIP2003 w/o LT', 'human toxicity w/o LT', 'via surface water w/o LT'),\n",
" ('EDIP2003 w/o LT', 'land filling w/o LT', 'bulk waste w/o LT'),\n",
" ('EDIP2003 w/o LT', 'land filling w/o LT', 'hazardous waste w/o LT'),\n",
" ('EDIP2003 w/o LT', 'land filling w/o LT', 'radioactive waste w/o LT'),\n",
" ('EDIP2003 w/o LT', 'land filling w/o LT', 'slag and ashes w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'aluminium w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'antimony w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'brown coal w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'cadmium w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'cerium w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'coal w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'cobalt w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'copper w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'gold w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'iron w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'lanthanum w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'lead w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'manganese w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'mercury w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'molybdenum w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'natural gas w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'nickel w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'oil w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'palladium w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'platinum w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'silver w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'tantalum w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'tin w/o LT'),\n",
" ('EDIP2003 w/o LT', 'non-renewable resources w/o LT', 'zinc w/o LT'),\n",
" ('EDIP2003 w/o LT',\n",
" 'photochemical ozone formation w/o LT',\n",
" 'impacts on human health w/o LT'),\n",
" ('EDIP2003 w/o LT',\n",
" 'photochemical ozone formation w/o LT',\n",
" 'impacts on vegetation w/o LT'),\n",
" ('EDIP2003 w/o LT', 'renewable resources w/o LT', 'wood w/o LT'),\n",
" ('EDIP2003 w/o LT',\n",
" 'stratospheric ozone depletion w/o LT',\n",
" 'ODP total w/o LT'),\n",
" ('EPS 2000', 'total', 'abiotic stock resources'),\n",
" ('EPS 2000', 'total', 'emissions into air'),\n",
" ('EPS 2000', 'total', 'emissions into soil'),\n",
" ('EPS 2000', 'total', 'emissions into water'),\n",
" ('EPS 2000', 'total', 'land occupation'),\n",
" ('EPS 2000', 'total', 'total'),\n",
" ('ILCD 1.0.8 2016 midpoint', 'climate change', 'GWP 100a'),\n",
" ('ILCD 1.0.8 2016 midpoint',\n",
" 'ecosystem quality',\n",
" 'freshwater and terrestrial acidification'),\n",
" ('ILCD 1.0.8 2016 midpoint', 'ecosystem quality', 'freshwater ecotoxicity'),\n",
" ('ILCD 1.0.8 2016 midpoint',\n",
" 'ecosystem quality',\n",
" 'freshwater eutrophication'),\n",
" ('ILCD 1.0.8 2016 midpoint', 'ecosystem quality', 'ionising radiation'),\n",
" ('ILCD 1.0.8 2016 midpoint', 'ecosystem quality', 'marine eutrophication'),\n",
" ('ILCD 1.0.8 2016 midpoint',\n",
" 'ecosystem quality',\n",
" 'terrestrial eutrophication'),\n",
" ('ILCD 1.0.8 2016 midpoint', 'human health', 'carcinogenic effects'),\n",
" ('ILCD 1.0.8 2016 midpoint', 'human health', 'ionising radiation'),\n",
" ('ILCD 1.0.8 2016 midpoint', 'human health', 'non-carcinogenic effects'),\n",
" ('ILCD 1.0.8 2016 midpoint', 'human health', 'ozone layer depletion'),\n",
" ('ILCD 1.0.8 2016 midpoint', 'human health', 'photochemical ozone creation'),\n",
" ('ILCD 1.0.8 2016 midpoint',\n",
" 'human health',\n",
" 'respiratory effects, inorganics'),\n",
" ('ILCD 1.0.8 2016 midpoint', 'resources', 'land use'),\n",
" ('ILCD 1.0.8 2016 midpoint', 'resources', 'mineral, fossils and renewables'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT', 'climate change', 'GWP 100a'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT',\n",
" 'ecosystem quality',\n",
" 'freshwater and terrestrial acidification'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT',\n",
" 'ecosystem quality',\n",
" 'freshwater ecotoxicity'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT',\n",
" 'ecosystem quality',\n",
" 'freshwater eutrophication'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT', 'ecosystem quality', 'ionising radiation'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT',\n",
" 'ecosystem quality',\n",
" 'marine eutrophication'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT',\n",
" 'ecosystem quality',\n",
" 'terrestrial eutrophication'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT', 'human health', 'carcinogenic effects'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT', 'human health', 'ionising radiation'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT',\n",
" 'human health',\n",
" 'non-carcinogenic effects'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT', 'human health', 'ozone layer depletion'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT',\n",
" 'human health',\n",
" 'photochemical ozone creation'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT',\n",
" 'human health',\n",
" 'respiratory effects, inorganics'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT', 'resources', 'land use'),\n",
" ('ILCD 1.0.8 2016 midpoint no LT',\n",
" 'resources',\n",
" 'mineral, fossils and renewables'),\n",
" ('IMPACT 2002+ (Endpoint)', 'climate change', 'climate change'),\n",
" ('IMPACT 2002+ (Endpoint)', 'climate change', 'total'),\n",
" ('IMPACT 2002+ (Endpoint)', 'ecosystem quality', 'aquatic ecotoxicity'),\n",
" ('IMPACT 2002+ (Endpoint)', 'ecosystem quality', 'land occupation'),\n",
" ('IMPACT 2002+ (Endpoint)',\n",
" 'ecosystem quality',\n",
" 'terrestrial acidification & nutrification'),\n",
" ('IMPACT 2002+ (Endpoint)', 'ecosystem quality', 'terrestrial ecotoxicity'),\n",
" ('IMPACT 2002+ (Endpoint)', 'ecosystem quality', 'total'),\n",
" ('IMPACT 2002+ (Endpoint)', 'human health', 'human toxicity'),\n",
" ('IMPACT 2002+ (Endpoint)', 'human health', 'ionising radiation'),\n",
" ('IMPACT 2002+ (Endpoint)', 'human health', 'ozone layer depletion'),\n",
" ('IMPACT 2002+ (Endpoint)', 'human health', 'photochemical oxidation'),\n",
" ('IMPACT 2002+ (Endpoint)',\n",
" 'human health',\n",
" 'respiratory effects (inorganics)'),\n",
" ('IMPACT 2002+ (Endpoint)', 'human health', 'total'),\n",
" ('IMPACT 2002+ (Endpoint)', 'resources', 'mineral extraction'),\n",
" ('IMPACT 2002+ (Endpoint)', 'resources', 'non-renewable energy'),\n",
" ('IMPACT 2002+ (Endpoint)', 'resources', 'total'),\n",
" ('IMPACT 2002+ (Midpoint)', 'ecosystem quality', 'aquatic acidification'),\n",
" ('IMPACT 2002+ (Midpoint)', 'ecosystem quality', 'aquatic eutrophication'),\n",
" ('IPCC 2001', 'climate change', 'GWP 100a'),\n",
" ('IPCC 2001', 'climate change', 'GWP 20a'),\n",
" ('IPCC 2001', 'climate change', 'GWP 500a'),\n",
" ('IPCC 2007', 'climate change', 'GWP 100a'),\n",
" ('IPCC 2007', 'climate change', 'GWP 20a'),\n",
" ('IPCC 2007', 'climate change', 'GWP 500a'),\n",
" ('IPCC 2007 no LT', 'climate change', 'GWP 100a'),\n",
" ('IPCC 2007 no LT', 'climate change', 'GWP 20a'),\n",
" ('IPCC 2007 no LT', 'climate change', 'GWP 500a'),\n",
" ('IPCC 2013', 'climate change', 'GTP 100a'),\n",
" ('IPCC 2013', 'climate change', 'GTP 20a'),\n",
" ('IPCC 2013', 'climate change', 'GWP 100a'),\n",
" ('IPCC 2013', 'climate change', 'GWP 20a'),\n",
" ('IPCC 2013 no LT', 'climate change', 'GTP 100a'),\n",
" ('IPCC 2013 no LT', 'climate change', 'GTP 20a'),\n",
" ('IPCC 2013 no LT', 'climate change', 'GWP 100a'),\n",
" ('IPCC 2013 no LT', 'climate change', 'GWP 20a'),\n",
" ('ReCiPe Endpoint (E,A)',\n",
" 'ecosystem quality',\n",
" 'agricultural land occupation'),\n",
" ('ReCiPe Endpoint (E,A)', 'ecosystem quality', 'climate change, ecosystems'),\n",
" ('ReCiPe Endpoint (E,A)', 'ecosystem quality', 'freshwater ecotoxicity'),\n",
" ('ReCiPe Endpoint (E,A)', 'ecosystem quality', 'freshwater eutrophication'),\n",
" ('ReCiPe Endpoint (E,A)', 'ecosystem quality', 'marine ecotoxicity'),\n",
" ('ReCiPe Endpoint (E,A)', 'ecosystem quality', 'natural land transformation'),\n",
" ('ReCiPe Endpoint (E,A)', 'ecosystem quality', 'terrestrial acidification'),\n",
" ('ReCiPe Endpoint (E,A)', 'ecosystem quality', 'terrestrial ecotoxicity'),\n",
" ('ReCiPe Endpoint (E,A)', 'ecosystem quality', 'total'),\n",
" ('ReCiPe Endpoint (E,A)', 'ecosystem quality', 'urban land occupation'),\n",
" ('ReCiPe Endpoint (E,A)', 'human health', 'climate change, human health'),\n",
" ('ReCiPe Endpoint (E,A)', 'human health', 'human toxicity'),\n",
" ('ReCiPe Endpoint (E,A)', 'human health', 'ionising radiation'),\n",
" ('ReCiPe Endpoint (E,A)', 'human health', 'ozone depletion'),\n",
" ('ReCiPe Endpoint (E,A)', 'human health', 'particulate matter formation'),\n",
" ('ReCiPe Endpoint (E,A)', 'human health', 'photochemical oxidant formation'),\n",
" ('ReCiPe Endpoint (E,A)', 'human health', 'total'),\n",
" ('ReCiPe Endpoint (E,A)', 'resources', 'fossil depletion'),\n",
" ('ReCiPe Endpoint (E,A)', 'resources', 'metal depletion'),\n",
" ('ReCiPe Endpoint (E,A)', 'resources', 'total'),\n",
" ('ReCiPe Endpoint (E,A)', 'total', 'total'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'agricultural land occupation w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'climate change, ecosystems w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'freshwater ecotoxicity w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'freshwater eutrophication w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'marine ecotoxicity w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'natural land transformation w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'terrestrial acidification w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'terrestrial ecotoxicity w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT', 'ecosystem quality w/o LT', 'total w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'urban land occupation w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'climate change, human health w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'human toxicity w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'ionising radiation w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'ozone depletion w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'particulate matter formation w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'photochemical oxidant formation w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT', 'human health w/o LT', 'total w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'resources w/o LT',\n",
" 'fossil depletion w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT',\n",
" 'resources w/o LT',\n",
" 'metal depletion w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT', 'resources w/o LT', 'total w/o LT'),\n",
" ('ReCiPe Endpoint (E,A) w/o LT', 'total w/o LT', 'total w/o LT'),\n",
" ('ReCiPe Endpoint (H,A)',\n",
" 'ecosystem quality',\n",
" 'agricultural land occupation'),\n",
" ('ReCiPe Endpoint (H,A)', 'ecosystem quality', 'climate change, ecosystems'),\n",
" ('ReCiPe Endpoint (H,A)', 'ecosystem quality', 'freshwater ecotoxicity'),\n",
" ('ReCiPe Endpoint (H,A)', 'ecosystem quality', 'freshwater eutrophication'),\n",
" ('ReCiPe Endpoint (H,A)', 'ecosystem quality', 'marine ecotoxicity'),\n",
" ('ReCiPe Endpoint (H,A)', 'ecosystem quality', 'natural land transformation'),\n",
" ('ReCiPe Endpoint (H,A)', 'ecosystem quality', 'terrestrial acidification'),\n",
" ('ReCiPe Endpoint (H,A)', 'ecosystem quality', 'terrestrial ecotoxicity'),\n",
" ('ReCiPe Endpoint (H,A)', 'ecosystem quality', 'total'),\n",
" ('ReCiPe Endpoint (H,A)', 'ecosystem quality', 'urban land occupation'),\n",
" ('ReCiPe Endpoint (H,A)', 'human health', 'climate change, human health'),\n",
" ('ReCiPe Endpoint (H,A)', 'human health', 'human toxicity'),\n",
" ('ReCiPe Endpoint (H,A)', 'human health', 'ionising radiation'),\n",
" ('ReCiPe Endpoint (H,A)', 'human health', 'ozone depletion'),\n",
" ('ReCiPe Endpoint (H,A)', 'human health', 'particulate matter formation'),\n",
" ('ReCiPe Endpoint (H,A)', 'human health', 'photochemical oxidant formation'),\n",
" ('ReCiPe Endpoint (H,A)', 'human health', 'total'),\n",
" ('ReCiPe Endpoint (H,A)', 'resources', 'fossil depletion'),\n",
" ('ReCiPe Endpoint (H,A)', 'resources', 'metal depletion'),\n",
" ('ReCiPe Endpoint (H,A)', 'resources', 'total'),\n",
" ('ReCiPe Endpoint (H,A)', 'total', 'total'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'agricultural land occupation w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'climate change, ecosystems w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'freshwater ecotoxicity w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'freshwater eutrophication w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'marine ecotoxicity w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'natural land transformation w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'terrestrial acidification w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'terrestrial ecotoxicity w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT', 'ecosystem quality w/o LT', 'total w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'urban land occupation w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'climate change, human health w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'human toxicity w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'ionising radiation w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'ozone depletion w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'particulate matter formation w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'photochemical oxidant formation w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT', 'human health w/o LT', 'total w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'resources w/o LT',\n",
" 'fossil depletion w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT',\n",
" 'resources w/o LT',\n",
" 'metal depletion w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT', 'resources w/o LT', 'total w/o LT'),\n",
" ('ReCiPe Endpoint (H,A) w/o LT', 'total w/o LT', 'total w/o LT'),\n",
" ('ReCiPe Endpoint (I,A)',\n",
" 'ecosystem quality',\n",
" 'agricultural land occupation'),\n",
" ('ReCiPe Endpoint (I,A)', 'ecosystem quality', 'climate change, ecosystems'),\n",
" ('ReCiPe Endpoint (I,A)', 'ecosystem quality', 'freshwater ecotoxicity'),\n",
" ('ReCiPe Endpoint (I,A)', 'ecosystem quality', 'freshwater eutrophication'),\n",
" ('ReCiPe Endpoint (I,A)', 'ecosystem quality', 'marine ecotoxicity'),\n",
" ('ReCiPe Endpoint (I,A)', 'ecosystem quality', 'natural land transformation'),\n",
" ('ReCiPe Endpoint (I,A)', 'ecosystem quality', 'terrestrial acidification'),\n",
" ('ReCiPe Endpoint (I,A)', 'ecosystem quality', 'terrestrial ecotoxicity'),\n",
" ('ReCiPe Endpoint (I,A)', 'ecosystem quality', 'total'),\n",
" ('ReCiPe Endpoint (I,A)', 'ecosystem quality', 'urban land occupation'),\n",
" ('ReCiPe Endpoint (I,A)', 'human health', 'climate change, human health'),\n",
" ('ReCiPe Endpoint (I,A)', 'human health', 'human toxicity'),\n",
" ('ReCiPe Endpoint (I,A)', 'human health', 'ionising radiation'),\n",
" ('ReCiPe Endpoint (I,A)', 'human health', 'ozone depletion'),\n",
" ('ReCiPe Endpoint (I,A)', 'human health', 'particulate matter formation'),\n",
" ('ReCiPe Endpoint (I,A)', 'human health', 'photochemical oxidant formation'),\n",
" ('ReCiPe Endpoint (I,A)', 'human health', 'total'),\n",
" ('ReCiPe Endpoint (I,A)', 'resources', 'fossil depletion'),\n",
" ('ReCiPe Endpoint (I,A)', 'resources', 'metal depletion'),\n",
" ('ReCiPe Endpoint (I,A)', 'resources', 'total'),\n",
" ('ReCiPe Endpoint (I,A)', 'total', 'total'),\n",
" ('ReCiPe Midpoint (E)', 'agricultural land occupation', 'ALOP'),\n",
" ('ReCiPe Midpoint (E)', 'climate change', 'GWP500'),\n",
" ('ReCiPe Midpoint (E)', 'fossil depletion', 'FDP'),\n",
" ('ReCiPe Midpoint (E)', 'freshwater ecotoxicity', 'FETPinf'),\n",
" ('ReCiPe Midpoint (E)', 'freshwater eutrophication', 'FEP'),\n",
" ('ReCiPe Midpoint (E)', 'human toxicity', 'HTPinf'),\n",
" ('ReCiPe Midpoint (E)', 'ionising radiation', 'IRP_HE'),\n",
" ('ReCiPe Midpoint (E)', 'marine ecotoxicity', 'METPinf'),\n",
" ('ReCiPe Midpoint (E)', 'marine eutrophication', 'MEP'),\n",
" ('ReCiPe Midpoint (E)', 'metal depletion', 'MDP'),\n",
" ('ReCiPe Midpoint (E)', 'natural land transformation', 'NLTP'),\n",
" ('ReCiPe Midpoint (E)', 'ozone depletion', 'ODPinf'),\n",
" ('ReCiPe Midpoint (E)', 'particulate matter formation', 'PMFP'),\n",
" ('ReCiPe Midpoint (E)', 'photochemical oxidant formation', 'POFP'),\n",
" ('ReCiPe Midpoint (E)', 'terrestrial acidification', 'TAP500'),\n",
" ('ReCiPe Midpoint (E)', 'terrestrial ecotoxicity', 'TETPinf'),\n",
" ('ReCiPe Midpoint (E)', 'urban land occupation', 'ULOP'),\n",
" ('ReCiPe Midpoint (E)', 'water depletion', 'WDP'),\n",
" ('ReCiPe Midpoint (E) w/o LT',\n",
" 'agricultural land occupation w/o LT',\n",
" 'ALOP w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT', 'climate change w/o LT', 'GWP500 w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT', 'fossil depletion w/o LT', 'FDP w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT',\n",
" 'freshwater ecotoxicity w/o LT',\n",
" 'FETPinf w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT',\n",
" 'freshwater eutrophication w/o LT',\n",
" 'FEP w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT', 'human toxicity w/o LT', 'HTPinf w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT', 'ionising radiation w/o LT', 'IRP_HE w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT', 'marine ecotoxicity w/o LT', 'METPinf w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT', 'marine eutrophication w/o LT', 'MEP w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT', 'metal depletion w/o LT', 'MDP w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT',\n",
" 'natural land transformation w/o LT',\n",
" 'NLTP w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT', 'ozone depletion w/o LT', 'ODPinf w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT',\n",
" 'particulate matter formation w/o LT',\n",
" 'PMFP w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT',\n",
" 'photochemical oxidant formation w/o LT',\n",
" 'POFP w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT',\n",
" 'terrestrial acidification w/o LT',\n",
" 'TAP500 w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT',\n",
" 'terrestrial ecotoxicity w/o LT',\n",
" 'TETPinf w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT', 'urban land occupation w/o LT', 'ULOP w/o LT'),\n",
" ('ReCiPe Midpoint (E) w/o LT', 'water depletion w/o LT', 'WDP w/o LT'),\n",
" ('ReCiPe Midpoint (H)', 'agricultural land occupation', 'ALOP'),\n",
" ('ReCiPe Midpoint (H)', 'climate change', 'GWP100'),\n",
" ('ReCiPe Midpoint (H)', 'fossil depletion', 'FDP'),\n",
" ('ReCiPe Midpoint (H)', 'freshwater ecotoxicity', 'FETPinf'),\n",
" ('ReCiPe Midpoint (H)', 'freshwater eutrophication', 'FEP'),\n",
" ('ReCiPe Midpoint (H)', 'human toxicity', 'HTPinf'),\n",
" ('ReCiPe Midpoint (H)', 'ionising radiation', 'IRP_HE'),\n",
" ('ReCiPe Midpoint (H)', 'marine ecotoxicity', 'METPinf'),\n",
" ('ReCiPe Midpoint (H)', 'marine eutrophication', 'MEP'),\n",
" ('ReCiPe Midpoint (H)', 'metal depletion', 'MDP'),\n",
" ('ReCiPe Midpoint (H)', 'natural land transformation', 'NLTP'),\n",
" ('ReCiPe Midpoint (H)', 'ozone depletion', 'ODPinf'),\n",
" ('ReCiPe Midpoint (H)', 'particulate matter formation', 'PMFP'),\n",
" ('ReCiPe Midpoint (H)', 'photochemical oxidant formation', 'POFP'),\n",
" ('ReCiPe Midpoint (H)', 'terrestrial acidification', 'TAP100'),\n",
" ('ReCiPe Midpoint (H)', 'terrestrial ecotoxicity', 'TETPinf'),\n",
" ('ReCiPe Midpoint (H)', 'urban land occupation', 'ULOP'),\n",
" ('ReCiPe Midpoint (H)', 'water depletion', 'WDP'),\n",
" ('ReCiPe Midpoint (H) w/o LT',\n",
" 'agricultural land occupation w/o LT',\n",
" 'ALOP w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT', 'climate change w/o LT', 'GWP100 w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT', 'fossil depletion w/o LT', 'FDP w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT',\n",
" 'freshwater ecotoxicity w/o LT',\n",
" 'FETPinf w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT',\n",
" 'freshwater eutrophication w/o LT',\n",
" 'FEP w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT', 'human toxicity w/o LT', 'HTPinf w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT', 'ionising radiation w/o LT', 'IRP_HE w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT', 'marine ecotoxicity w/o LT', 'METPinf w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT', 'marine eutrophication w/o LT', 'MEP w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT', 'metal depletion w/o LT', 'MDP w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT',\n",
" 'natural land transformation w/o LT',\n",
" 'NLTP w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT', 'ozone depletion w/o LT', 'ODPinf w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT',\n",
" 'particulate matter formation w/o LT',\n",
" 'PMFP w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT',\n",
" 'photochemical oxidant formation w/o LT',\n",
" 'POFP w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT',\n",
" 'terrestrial acidification w/o LT',\n",
" 'TAP100 w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT',\n",
" 'terrestrial ecotoxicity w/o LT',\n",
" 'TETPinf w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT', 'urban land occupation w/o LT', 'ULOP w/o LT'),\n",
" ('ReCiPe Midpoint (H) w/o LT', 'water depletion w/o LT', 'WDP w/o LT'),\n",
" ('ReCiPe Midpoint (I)', 'agricultural land occupation', 'ALOP'),\n",
" ('ReCiPe Midpoint (I)', 'climate change', 'GWP20'),\n",
" ('ReCiPe Midpoint (I)', 'fossil depletion', 'FDP'),\n",
" ('ReCiPe Midpoint (I)', 'freshwater ecotoxicity', 'FETP100'),\n",
" ('ReCiPe Midpoint (I)', 'freshwater eutrophication', 'FEP'),\n",
" ('ReCiPe Midpoint (I)', 'human toxicity', 'HTP100'),\n",
" ('ReCiPe Midpoint (I)', 'ionising radiation', 'IRP_I'),\n",
" ('ReCiPe Midpoint (I)', 'marine ecotoxicity', 'METP100'),\n",
" ('ReCiPe Midpoint (I)', 'marine eutrophication', 'MEP'),\n",
" ('ReCiPe Midpoint (I)', 'metal depletion', 'MDP'),\n",
" ('ReCiPe Midpoint (I)', 'natural land transformation', 'NLTP'),\n",
" ('ReCiPe Midpoint (I)', 'ozone depletion', 'ODPinf'),\n",
" ('ReCiPe Midpoint (I)', 'particulate matter formation', 'PMFP'),\n",
" ('ReCiPe Midpoint (I)', 'photochemical oxidant formation', 'POFP'),\n",
" ('ReCiPe Midpoint (I)', 'terrestrial acidification', 'TAP20'),\n",
" ('ReCiPe Midpoint (I)', 'terrestrial ecotoxicity', 'TETP100'),\n",
" ('ReCiPe Midpoint (I)', 'urban land occupation', 'ULOP'),\n",
" ('ReCiPe Midpoint (I)', 'water depletion', 'WDP'),\n",
" ('TRACI', 'environmental impact', 'acidification'),\n",
" ('TRACI', 'environmental impact', 'ecotoxicity'),\n",
" ('TRACI', 'environmental impact', 'eutrophication'),\n",
" ('TRACI', 'environmental impact', 'global warming'),\n",
" ('TRACI', 'environmental impact', 'ozone depletion'),\n",
" ('TRACI', 'environmental impact', 'photochemical oxidation'),\n",
" ('TRACI', 'human health', 'carcinogenics'),\n",
" ('TRACI', 'human health', 'non-carcinogenics'),\n",
" ('TRACI', 'human health', 'respiratory effects, average'),\n",
" ('USEtox', 'ecotoxicity', 'total'),\n",
" ('USEtox', 'human toxicity', 'carcinogenic'),\n",
" ('USEtox', 'human toxicity', 'non-carcinogenic'),\n",
" ('USEtox', 'human toxicity', 'total'),\n",
" ('USEtox w/o LT', 'ecotoxicity w/o LT', 'total w/o LT'),\n",
" ('USEtox w/o LT', 'human toxicity w/o LT', 'carcinogenic w/o LT'),\n",
" ('USEtox w/o LT', 'human toxicity w/o LT', 'non-carcinogenic w/o LT'),\n",
" ('USEtox w/o LT', 'human toxicity w/o LT', 'total w/o LT'),\n",
" ('cumulative energy demand',\n",
" 'biomass',\n",
" 'renewable energy resources, biomass'),\n",
" ('cumulative energy demand',\n",
" 'fossil',\n",
" 'non-renewable energy resources, fossil'),\n",
" ('cumulative energy demand',\n",
" 'geothermal',\n",
" 'renewable energy resources, geothermal, converted'),\n",
" ('cumulative energy demand',\n",
" 'nuclear',\n",
" 'non-renewable energy resources, nuclear'),\n",
" ('cumulative energy demand',\n",
" 'primary forest',\n",
" 'non-renewable energy resources, primary forest'),\n",
" ('cumulative energy demand',\n",
" 'solar',\n",
" 'renewable energy resources, solar, converted'),\n",
" ('cumulative energy demand',\n",
" 'water',\n",
" 'renewable energy resources, potential (in barrage water), converted'),\n",
" ('cumulative energy demand',\n",
" 'wind',\n",
" 'renewable energy resources, kinetic (in wind), converted'),\n",
" ('cumulative exergy demand',\n",
" 'biomass',\n",
" 'renewable energy resources, biomass'),\n",
" ('cumulative exergy demand',\n",
" 'fossil',\n",
" 'non-renewable energy resources, fossil'),\n",
" ('cumulative exergy demand',\n",
" 'metals',\n",
" 'non-renewable material resources, metals'),\n",
" ('cumulative exergy demand',\n",
" 'minerals',\n",
" 'non-renewable material resources, minerals'),\n",
" ('cumulative exergy demand',\n",
" 'nuclear',\n",
" 'non-renewable energy resources, nuclear'),\n",
" ('cumulative exergy demand',\n",
" 'primary forest',\n",
" 'non-renewable energy resources, primary forest'),\n",
" ('cumulative exergy demand',\n",
" 'solar',\n",
" 'renewable energy resources, solar, converted'),\n",
" ('cumulative exergy demand',\n",
" 'water',\n",
" 'renewable energy resources, potential (in barrage water), converted'),\n",
" ('cumulative exergy demand',\n",
" 'water resources',\n",
" 'renewable material resources, water'),\n",
" ('cumulative exergy demand',\n",
" 'wind',\n",
" 'renewable energy resources, kinetic (in wind), converted'),\n",
" ('eco-indicator 99, (E,E)',\n",
" 'ecosystem quality',\n",
" 'acidification & eutrophication'),\n",
" ('eco-indicator 99, (E,E)', 'ecosystem quality', 'ecotoxicity'),\n",
" ('eco-indicator 99, (E,E)', 'ecosystem quality', 'land occupation'),\n",
" ('eco-indicator 99, (E,E)', 'ecosystem quality', 'total'),\n",
" ('eco-indicator 99, (E,E)', 'human health', 'carcinogenics'),\n",
" ('eco-indicator 99, (E,E)', 'human health', 'climate change'),\n",
" ('eco-indicator 99, (E,E)', 'human health', 'ionising radiation'),\n",
" ('eco-indicator 99, (E,E)', 'human health', 'ozone layer depletion'),\n",
" ('eco-indicator 99, (E,E)', 'human health', 'respiratory effects'),\n",
" ('eco-indicator 99, (E,E)', 'human health', 'total'),\n",
" ('eco-indicator 99, (E,E)', 'resources', 'fossil fuels'),\n",
" ('eco-indicator 99, (E,E)', 'resources', 'mineral extraction'),\n",
" ('eco-indicator 99, (E,E)', 'resources', 'total'),\n",
" ('eco-indicator 99, (E,E)', 'total', 'total'),\n",
" ('eco-indicator 99, (E,E) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'acidification & eutrophication w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'ecotoxicity w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'land occupation w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'total w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT',\n",
" 'human health w/o LT',\n",
" 'carcinogenics w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT',\n",
" 'human health w/o LT',\n",
" 'climate change w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT',\n",
" 'human health w/o LT',\n",
" 'ionising radiation w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT',\n",
" 'human health w/o LT',\n",
" 'ozone layer depletion w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT',\n",
" 'human health w/o LT',\n",
" 'respiratory effects w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT', 'human health w/o LT', 'total w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT', 'resources w/o LT', 'fossil fuels w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT',\n",
" 'resources w/o LT',\n",
" 'mineral extraction w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT', 'resources w/o LT', 'total w/o LT'),\n",
" ('eco-indicator 99, (E,E) w/o LT', 'total w/o LT', 'total w/o LT'),\n",
" ('eco-indicator 99, (H,A)',\n",
" 'ecosystem quality',\n",
" 'acidification & eutrophication'),\n",
" ('eco-indicator 99, (H,A)', 'ecosystem quality', 'ecotoxicity'),\n",
" ('eco-indicator 99, (H,A)', 'ecosystem quality', 'land occupation'),\n",
" ('eco-indicator 99, (H,A)', 'ecosystem quality', 'total'),\n",
" ('eco-indicator 99, (H,A)', 'human health', 'carcinogenics'),\n",
" ('eco-indicator 99, (H,A)', 'human health', 'climate change'),\n",
" ('eco-indicator 99, (H,A)', 'human health', 'ionising radiation'),\n",
" ('eco-indicator 99, (H,A)', 'human health', 'ozone layer depletion'),\n",
" ('eco-indicator 99, (H,A)', 'human health', 'respiratory effects'),\n",
" ('eco-indicator 99, (H,A)', 'human health', 'total'),\n",
" ('eco-indicator 99, (H,A)', 'resources', 'fossil fuels'),\n",
" ('eco-indicator 99, (H,A)', 'resources', 'mineral extraction'),\n",
" ('eco-indicator 99, (H,A)', 'resources', 'total'),\n",
" ('eco-indicator 99, (H,A)', 'total', 'total'),\n",
" ('eco-indicator 99, (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'acidification & eutrophication w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'ecotoxicity w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'land occupation w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT',\n",
" 'ecosystem quality w/o LT',\n",
" 'total w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'carcinogenics w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'climate change w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'ionising radiation w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'ozone layer depletion w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT',\n",
" 'human health w/o LT',\n",
" 'respiratory effects w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT', 'human health w/o LT', 'total w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT', 'resources w/o LT', 'fossil fuels w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT',\n",
" 'resources w/o LT',\n",
" 'mineral extraction w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT', 'resources w/o LT', 'total w/o LT'),\n",
" ('eco-indicator 99, (H,A) w/o LT', 'total w/o LT', 'total w/o LT'),\n",
" ('eco-indicator 99, (I,I)',\n",
" 'ecosystem quality',\n",
" 'acidification & eutrophication'),\n",
" ('eco-indicator 99, (I,I)', 'ecosystem quality', 'ecotoxicity'),\n",
" ('eco-indicator 99, (I,I)', 'ecosystem quality', 'land occupation'),\n",
" ('eco-indicator 99, (I,I)', 'ecosystem quality', 'total'),\n",
" ('eco-indicator 99, (I,I)', 'human health', 'carcinogenics'),\n",
" ('eco-indicator 99, (I,I)', 'human health', 'climate change'),\n",
" ('eco-indicator 99, (I,I)', 'human health', 'ionising radiation'),\n",
" ('eco-indicator 99, (I,I)', 'human health', 'ozone layer depletion'),\n",
" ('eco-indicator 99, (I,I)', 'human health', 'respiratory effects'),\n",
" ('eco-indicator 99, (I,I)', 'human health', 'total'),\n",
" ('eco-indicator 99, (I,I)', 'resources', 'mineral extraction'),\n",
" ('eco-indicator 99, (I,I)', 'resources', 'total'),\n",
" ('eco-indicator 99, (I,I)', 'total', 'total'),\n",
" ('ecological footprint', 'total', 'CO2'),\n",
" ('ecological footprint', 'total', 'land occupation'),\n",
" ('ecological footprint', 'total', 'nuclear'),\n",
" ('ecological footprint', 'total', 'total'),\n",
" ('ecological scarcity 1997', 'total', 'deposited waste'),\n",
" ('ecological scarcity 1997', 'total', 'emission into air'),\n",
" ('ecological scarcity 1997', 'total', 'emission into top-soil/groundwater'),\n",
" ('ecological scarcity 1997', 'total', 'emission into water'),\n",
" ('ecological scarcity 1997', 'total', 'radioactive waste'),\n",
" ('ecological scarcity 1997', 'total', 'total'),\n",
" ('ecological scarcity 1997', 'total', 'use of energy resources'),\n",
" ('ecological scarcity 2006', 'total', 'deposited waste'),\n",
" ('ecological scarcity 2006', 'total', 'emission into air'),\n",
" ('ecological scarcity 2006', 'total', 'emission into groundwater'),\n",
" ('ecological scarcity 2006', 'total', 'emission into surface water'),\n",
" ('ecological scarcity 2006', 'total', 'emission into top soil'),\n",
" ('ecological scarcity 2006', 'total', 'energy resources'),\n",
" ('ecological scarcity 2006', 'total', 'natural resources'),\n",
" ('ecological scarcity 2006', 'total', 'total'),\n",
" ('ecological scarcity 2013', 'POP into water', 'total'),\n",
" ('ecological scarcity 2013', 'carcinogenic substances into air', 'total'),\n",
" ('ecological scarcity 2013', 'energy resources', 'total'),\n",
" ('ecological scarcity 2013', 'global warming', 'total'),\n",
" ('ecological scarcity 2013', 'heavy metals into air', 'total'),\n",
" ('ecological scarcity 2013', 'heavy metals into soil', 'total'),\n",
" ('ecological scarcity 2013', 'heavy metals into water', 'total'),\n",
" ('ecological scarcity 2013', 'land use', 'total'),\n",
" ('ecological scarcity 2013', 'main air pollutants and PM', 'total'),\n",
" ('ecological scarcity 2013', 'mineral resources', 'total'),\n",
" ('ecological scarcity 2013', 'non radioactive waste to deposit', 'total'),\n",
" ('ecological scarcity 2013', 'ozone layer depletion', 'total'),\n",
" ('ecological scarcity 2013', 'pesticides into soil', 'total'),\n",
" ('ecological scarcity 2013', 'radioactive substances into air', 'total'),\n",
" ('ecological scarcity 2013', 'radioactive substances into water', 'total'),\n",
" ('ecological scarcity 2013', 'radioactive waste to deposit', 'total'),\n",
" ('ecological scarcity 2013', 'total', 'total'),\n",
" ('ecological scarcity 2013', 'water pollutants', 'total'),\n",
" ('ecological scarcity 2013', 'water resources', 'total'),\n",
" ('ecological scarcity 2013 no LT', 'POP into water', 'total'),\n",
" ('ecological scarcity 2013 no LT',\n",
" 'carcinogenic substances into air',\n",
" 'total'),\n",
" ('ecological scarcity 2013 no LT', 'global warming', 'total'),\n",
" ('ecological scarcity 2013 no LT', 'heavy metals into air', 'total'),\n",
" ('ecological scarcity 2013 no LT', 'heavy metals into soil', 'total'),\n",
" ('ecological scarcity 2013 no LT', 'heavy metals into water', 'total'),\n",
" ('ecological scarcity 2013 no LT', 'main air pollutants and PM', 'total'),\n",
" ('ecological scarcity 2013 no LT',\n",
" 'non radioactive waste to deposit',\n",
" 'total'),\n",
" ('ecological scarcity 2013 no LT', 'ozone layer depletion', 'total'),\n",
" ('ecological scarcity 2013 no LT', 'pesticides into soil', 'total'),\n",
" ('ecological scarcity 2013 no LT',\n",
" 'radioactive substances into air',\n",
" 'total'),\n",
" ('ecological scarcity 2013 no LT',\n",
" 'radioactive substances into water',\n",
" 'total'),\n",
" ('ecological scarcity 2013 no LT', 'total', 'total'),\n",
" ('ecological scarcity 2013 no LT', 'water pollutants', 'total'),\n",
" ('ecological scarcity 2013 no LT', 'water resources', 'total'),\n",
" ('ecosystem damage potential', 'total', 'linear, land occupation'),\n",
" ('ecosystem damage potential', 'total', 'linear, land transformation'),\n",
" ('ecosystem damage potential', 'total', 'linear, land use, total')]"
]
},
"execution_count": 39,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"method_list = list(bw.methods)\n",
"method_list.sort()\n",
"method_list"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's go for the ReCiPe Midpoints including long-term emissions (i.e. excluding `w/o LT`):"
]
},
{
"cell_type": "code",
"execution_count": 40,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"[('ReCiPe Midpoint (H)', 'agricultural land occupation', 'ALOP'),\n",
" ('ReCiPe Midpoint (H)', 'climate change', 'GWP100'),\n",
" ('ReCiPe Midpoint (H)', 'fossil depletion', 'FDP'),\n",
" ('ReCiPe Midpoint (H)', 'freshwater ecotoxicity', 'FETPinf'),\n",
" ('ReCiPe Midpoint (H)', 'freshwater eutrophication', 'FEP'),\n",
" ('ReCiPe Midpoint (H)', 'human toxicity', 'HTPinf'),\n",
" ('ReCiPe Midpoint (H)', 'ionising radiation', 'IRP_HE'),\n",
" ('ReCiPe Midpoint (H)', 'marine ecotoxicity', 'METPinf'),\n",
" ('ReCiPe Midpoint (H)', 'marine eutrophication', 'MEP'),\n",
" ('ReCiPe Midpoint (H)', 'metal depletion', 'MDP'),\n",
" ('ReCiPe Midpoint (H)', 'natural land transformation', 'NLTP'),\n",
" ('ReCiPe Midpoint (H)', 'ozone depletion', 'ODPinf'),\n",
" ('ReCiPe Midpoint (H)', 'particulate matter formation', 'PMFP'),\n",
" ('ReCiPe Midpoint (H)', 'photochemical oxidant formation', 'POFP'),\n",
" ('ReCiPe Midpoint (H)', 'terrestrial acidification', 'TAP100'),\n",
" ('ReCiPe Midpoint (H)', 'terrestrial ecotoxicity', 'TETPinf'),\n",
" ('ReCiPe Midpoint (H)', 'urban land occupation', 'ULOP'),\n",
" ('ReCiPe Midpoint (H)', 'water depletion', 'WDP')]"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from operator import itemgetter\n",
"\n",
"method_search = [x for x in method_list if 'ReCiPe Midpoint (H)' in x[0]\n",
" and 'w/o' not in x[0]\n",
" ]\n",
"method_search = sorted(method_search, key=itemgetter(0, 1)) # sort for first then for second element\n",
"method_search"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's pick one impact key for further examples:"
]
},
{
"cell_type": "code",
"execution_count": 41,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"method_key_example = ('ReCiPe Midpoint (H)', 'particulate matter formation', 'PMFP')"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"With the activity in proxy format and the method key we now can now do basic LCA calculations."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Basic LCA calculations\n",
"\n",
"A brief review of LCA calculations:\n",
"\n",
"In matrix-based LCA, we construct a *technosphere* matrix, which describes the inputs needed to produce different products (e.g. cars need metal and electricity), and a *biosphere* matrix, which describes the emissions and resource consumption associated with the production of each product (e.g. car manufacturing releases air emissions). These two matrices come from the life cycle inventory database(s) (here *ecoinvent 3.3 cutoff* and *biosphere3*).\n",
"\n",
"We also have a *functional unit*, which is what we are trying to assess, e.g. one car. \n",
"\n",
"We then calculate the *life cycle inventory* (LCI) by first solving the linear system of the technosphere matrix and the functional unit, and then by multiplying it with the biosphere matrix.\n",
"\n",
"To do *life cycle impact assessment* (LCIA), we multiply the life cycle inventory by a matrix of *characterization factors*, which tell how bad different emissions and resource consumptions are.\n",
"_____________________________________________________________________________________________________________________\n",
"\n",
"First, we create the functional unit, i.e. 1 passenger car. The functional unit is a python dictionary of keys and amounts:"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{('cutoff34', '1f49d6d756da5b89683a9b597803ae26'): 1}"
]
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"functional_unit = {activity.key: 1}\n",
"functional_unit"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"So we could also write:"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"{('ei34_cutoff', 'ce22348142e9455aad472e54a4aa677e'): 1}"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"functional_unit = {('ei34_cutoff', 'ce22348142e9455aad472e54a4aa677e'): 1}\n",
"functional_unit"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Or we can also simply write:"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'passenger car production, petrol/natural gas' (kilogram, GLO, None): 1}"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"functional_unit = {activity: 1}\n",
"functional_unit"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"This output looks different but as we have learned above, the *Activity proxy* knows how to pretend to be a key tuple.\n",
"\n",
"We can now instantiate our [LCA object](https://docs.brightwaylca.org/technical/bw2calc.html#lca) with our selected method: "
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"lca_example = bw.LCA(demand = functional_unit, method = method_key_example)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Or simply:"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"lca_example = bw.LCA(functional_unit, method_key_example)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Then we do the LCI and LCIA calculations:"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"lca_example.lci()\n",
"lca_example.lcia()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Finally, we can print the LCA score:"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"0.019688163706404707"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lca_example.score"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Remember: to get the unit of the score, we need to create a method object and access the metadata:"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'abbreviation': 'recipe-midpoint-hpp.6de6d8746bebbbf823a89cc5fc8931de',\n",
" 'description': 'Implementation of the impact assessment method with the characterization factors (CF). Normalization factors: see XLS file of method - sheet \"Normalization\" - in files section of online database. Long-term emissions have same CF like normal emissions.',\n",
" 'filename': 'LCIA_implementation_3.3.xlsx',\n",
" 'num_cfs': 25,\n",
" 'unit': 'kg PM10-Eq'}"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"method_example = bw.Method(method_key_example)\n",
"method_example.metadata"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's have a look at what we analyzed:"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Functional unit: {'passenger car production, petrol/natural gas' (kilogram, GLO, None): 1}\n",
"Impact assessment method: ('ReCiPe Midpoint (H)', 'particulate matter formation', 'PMFP')\n",
"Score: 0.019688163706404707\n",
"Unit: kg PM10-Eq\n"
]
}
],
"source": [
"print(\"Functional unit: \", functional_unit)\n",
"print(\"Impact assessment method: \", method_key_example)\n",
"print(\"Score: \", lca_example.score)\n",
"print(\"Unit: \", method_example.metadata['unit'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now let's calculate all ReCiPe Midpoints:"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Functional unit: {'passenger car production, petrol/natural gas' (kilogram, GLO, None): 1}\n",
"agricultural land occupation :\t 0.252 square meter-year\n",
"climate change :\t 6.87 kg CO2-Eq\n",
"fossil depletion :\t 1.9 kg oil-Eq\n",
"freshwater ecotoxicity :\t 1.25 kg 1,4-DCB-Eq\n",
"freshwater eutrophication :\t 0.00523 kg P-Eq\n",
"human toxicity :\t 8.16 kg 1,4-DCB-Eq\n",
"ionising radiation :\t 0.461 kg U235-Eq\n",
"marine ecotoxicity :\t 1.07 kg 1,4-DCB-Eq\n",
"marine eutrophication :\t 0.00718 kg N-Eq\n",
"metal depletion :\t 2.97 kg Fe-Eq\n",
"natural land transformation :\t 0.000887 square meter\n",
"ozone depletion :\t 4.46e-07 kg CFC-11-Eq\n",
"particulate matter formation :\t 0.0197 kg PM10-Eq\n",
"photochemical oxidant formation :\t 0.0291 kg NMVOC\n",
"terrestrial acidification :\t 0.0341 kg SO2-Eq\n",
"terrestrial ecotoxicity :\t 0.00104 kg 1,4-DCB-Eq\n",
"urban land occupation :\t 0.0915 square meter-year\n",
"water depletion :\t 0.0277 cubic meter\n"
]
}
],
"source": [
"# function to cut results to n significant digits\n",
"import math\n",
"def round_figures(x, n):\n",
" return round(x, int(n - math.ceil(math.log10(abs(x)))))\n",
"\n",
"functional_unit = {activity: 1}\n",
"print(\"Functional unit: \", functional_unit)\n",
"for method_key in method_search:\n",
" method = bw.Method(method_key)\n",
" lca = bw.LCA(functional_unit, method_key)\n",
" lca.lci()\n",
" lca.lcia()\n",
" lca.score \n",
" print(method_key[1], \":\\t\", round_figures(lca.score, 3), method.metadata['unit'])"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Other cool stuff you can do\n",
"## Contribution analysis\n",
"\n",
"We can calculate the most important activities/processes and biosphere flows/emissions."
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from bw2analyzer import ContributionAnalysis"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Most important activities/processes (contributing to `'ReCiPe Midpoint (H)', 'particulate matter formation', 'PMFP'`):"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"[(0.0027458049020219317,\n",
" 1.9048908547402148,\n",
" 'iron mine operation, crude ore, 46% Fe' (kilogram, GLO, None)),\n",
" (0.00091372710948404783, 7.9571868692872032, 'coking' (megajoule, RoW, None)),\n",
" (0.00078252607470350442,\n",
" 0.017393178465559558,\n",
" 'electricity production, lignite' (kilowatt hour, ID, None)),\n",
" (0.00054266665844811181,\n",
" 0.014389570316905987,\n",
" 'ferrochromium production, high-carbon, 68% Cr' (kilogram, GLO, None)),\n",
" (0.00052200035006593989,\n",
" 2.2015533712189207e-07,\n",
" 'platinum group metal mine operation, ore with high palladium content' (kilogram, RU, None)),\n",
" (0.00050995409638576652,\n",
" 0.04784707238242121,\n",
" 'electricity production, lignite' (kilowatt hour, RFC, None)),\n",
" (0.00050679973658129612,\n",
" 8.2086124943342718,\n",
" 'transport, freight, sea, transoceanic ship' (ton kilometer, GLO, None)),\n",
" (0.00045000929793740914,\n",
" 0.042874361547999264,\n",
" 'electricity production, lignite' (kilowatt hour, SERC, None)),\n",
" (0.00042480167750389244,\n",
" 0.73934793379450658,\n",
" 'sinter production, iron' (kilogram, GLO, None)),\n",
" (0.00041193096580147121,\n",
" 0.68655159347095995,\n",
" 'hard coal mine operation and hard coal preparation' (kilogram, CN, None))]"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a = ContributionAnalysis().annotated_top_processes(lca_example)\n",
"a[0:10]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"whereby for each activity/process the impact, the amount, and the name are displayed: 0.00274 kg PM 10-eq are contributed from 1.9 kg of crude iron ore."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Most important biosphere flows/emissions:"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"[(0.0051961299039481792,\n",
" 0.0051961299039481766,\n",
" 'Particulates, < 2.5 um' (kilogram, None, ('air', 'non-urban air or from high stacks'))),\n",
" (0.0043097562262062721,\n",
" 0.0043097562262062713,\n",
" 'Particulates, > 2.5 um, and < 10um' (kilogram, None, ('air', 'non-urban air or from high stacks'))),\n",
" (0.0036239529816562413,\n",
" 0.018119764638275668,\n",
" 'Sulfur dioxide' (kilogram, None, ('air', 'non-urban air or from high stacks'))),\n",
" (0.0016825675785523662,\n",
" 0.0076480344894069713,\n",
" 'Nitrogen oxides' (kilogram, None, ('air', 'non-urban air or from high stacks'))),\n",
" (0.00090886298313435656,\n",
" 0.0041311954002687485,\n",
" 'Nitrogen oxides' (kilogram, None, ('air',))),\n",
" (0.00087901872449508834,\n",
" 0.004395093556983436,\n",
" 'Sulfur dioxide' (kilogram, None, ('air', 'urban air close to ground'))),\n",
" (0.00072230462843204913,\n",
" 0.00072230462843204956,\n",
" 'Particulates, < 2.5 um' (kilogram, None, ('air', 'urban air close to ground'))),\n",
" (0.00063248951475931424,\n",
" 0.0028749523553932982,\n",
" 'Nitrogen oxides' (kilogram, None, ('air', 'urban air close to ground'))),\n",
" (0.00054939549880589659,\n",
" 0.00054939549880589692,\n",
" 'Particulates, < 2.5 um' (kilogram, None, ('air',))),\n",
" (0.00042227381682591461,\n",
" 0.0021113690526677218,\n",
" 'Sulfur dioxide' (kilogram, None, ('air',))),\n",
" (0.00033945439732660428,\n",
" 0.00033945439732660407,\n",
" 'Particulates, > 2.5 um, and < 10um' (kilogram, None, ('air', 'urban air close to ground'))),\n",
" (0.00023971268851514358,\n",
" 0.00023971268851514366,\n",
" 'Particulates, > 2.5 um, and < 10um' (kilogram, None, ('air',))),\n",
" (0.00010006229866060554,\n",
" 0.00031269469030366321,\n",
" 'Ammonia' (kilogram, None, ('air',))),\n",
" (5.6926972512458601e-05,\n",
" 0.00017789679307773625,\n",
" 'Ammonia' (kilogram, None, ('air', 'non-urban air or from high stacks'))),\n",
" (1.2597314111728508e-05,\n",
" 3.9366607479063772e-05,\n",
" 'Ammonia' (kilogram, None, ('air', 'urban air close to ground'))),\n",
" (7.1564080049721147e-06,\n",
" 7.1564080049721156e-06,\n",
" 'Particulates, > 2.5 um, and < 10um' (kilogram, None, ('air', 'low population density, long-term'))),\n",
" (4.9164595624831306e-06,\n",
" 4.9164595624831314e-06,\n",
" 'Particulates, < 2.5 um' (kilogram, None, ('air', 'low population density, long-term'))),\n",
" (5.8363301410979105e-07,\n",
" 2.6528773512375789e-06,\n",
" 'Nitrogen oxides' (kilogram, None, ('air', 'lower stratosphere + upper troposphere'))),\n",
" (1.5199232165654058e-09,\n",
" 4.7497601579323064e-09,\n",
" 'Ammonia' (kilogram, None, ('air', 'low population density, long-term'))),\n",
" (1.5740699245280978e-10,\n",
" 7.1548633320789096e-10,\n",
" 'Nitrogen oxides' (kilogram, None, ('air', 'low population density, long-term'))),\n",
" (4.627804562677414e-13,\n",
" 2.3139022468588759e-12,\n",
" 'Sulfur dioxide' (kilogram, None, ('air', 'lower stratosphere + upper troposphere'))),\n",
" (8.7928429790630815e-14,\n",
" 8.7928429790630815e-14,\n",
" 'Particulates, < 2.5 um' (kilogram, None, ('air', 'lower stratosphere + upper troposphere'))),\n",
" (0.0,\n",
" 4.6390209617935031e-06,\n",
" 'Transformation, to dump site, sanitary landfill' (square meter, None, ('natural resource', 'land'))),\n",
" (0.0,\n",
" 8.6190548928048318e-13,\n",
" 'Triadimenol' (kilogram, None, ('soil', 'agricultural'))),\n",
" (0.0,\n",
" 7.3340129718937143e-05,\n",
" 'Transformation, to shrub land, sclerophyllous' (square meter, None, ('natural resource', 'land')))]"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ContributionAnalysis().annotated_top_emissions(lca_example)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Look at the LCA object\n",
"Let's have a look at the LCA object, e.g. the three matrices we used in the LCA calculation:"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<14889x14889 sparse matrix of type '<class 'numpy.float64'>'\n",
"\twith 155231 stored elements in Compressed Sparse Row format>"
]
},
"execution_count": 55,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lca_example.technosphere_matrix"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<2029x14889 sparse matrix of type '<class 'numpy.float64'>'\n",
"\twith 364348 stored elements in Compressed Sparse Row format>"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lca_example.biosphere_matrix"
]
},
{
"cell_type": "code",
"execution_count": 57,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<2029x2029 sparse matrix of type '<class 'numpy.float64'>'\n",
"\twith 22 stored elements in Compressed Sparse Row format>"
]
},
"execution_count": 57,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"lca_example.characterization_matrix"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"You can also visualize a matrix:"
]
},
{
"cell_type": "code",
"execution_count": 58,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline"
]
},
{
"cell_type": "code",
"execution_count": 59,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from bw2analyzer.matrix_grapher import SparseMatrixGrapher"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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ahjlm9CVItR4B/oEKNC3MUPD2OdT7ZQrqpvwDVBCs+r6ovg5XFUrZPVsYr2/yufJSqKVQ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EAAAg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R8Dtb7WDWZrYEukS+T9wz1IMZY+AJje2tf5zUEHV9+/ZSrmkWPSP84CqxHXYqpKDVfDgiLd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\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zyiwVBHQ5pE38hLT9oUh7HeTbNxOZlFrA3UiK8NWA55FYKsMQRfudiNLvKuR5HofE02hS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\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J+IE5neZihjNq/mbWvZ5Zt77+f0P8wGw3HHomEt2SQ54g147Z9k2XH5iv1/RXte8c4K+D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\nAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1f6efdf1e10>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"SparseMatrixGrapher(lca_example.technosphere_matrix).ordered_graph()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Monte Carlo\n",
"\n",
"We can do a Monte Carlo analysis (this will take a while if you increase the range):"
]
},
{
"cell_type": "code",
"execution_count": 64,
"metadata": {
"collapsed": true,
"scrolled": true
},
"outputs": [],
"source": [
"mc_list = []\n",
"mc = bw.MonteCarloLCA(functional_unit, method_key_example)\n",
"mc.load_data()\n",
"for x in range(100):\n",
" mc_list.append(next(mc))"
]
},
{
"cell_type": "code",
"execution_count": 65,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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vGKhv7Z7/LLC2YdnrgHuAHzHeCnpR9/jTgIPdm7gf+I2dytW9dgGfAQ53tyu65x4N/Cvw\nBcZHJTxqSXJ9kXH5nHz8H5Yh1zwG70Dv15nAu4EjwCHgkiXJtchx/2vAp7tcR4DXbljntsf9gNkW\nOfYn5prH2K8qz5yUpNa09uGkJD3oWdyS1BiLW5IaY3FLUmMsbklqjMUtSY2xuCWpMRa3JDXm/wF8\nuqEPM0e8zAAAAABJRU5ErkJggg==\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x1f6ec78f198>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import matplotlib.pyplot as plt\n",
"\n",
"plt.hist(mc_list, 100)\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.023865761121013126\n",
"0.02348982829770894\n",
"0.0033593909344253477\n",
"1.1285507450299211e-05\n"
]
}
],
"source": [
"import statistics\n",
"\n",
"print(statistics.mean(mc_list))\n",
"print(statistics.median(mc_list))\n",
"print(statistics.stdev(mc_list))\n",
"print(statistics.variance(mc_list))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"anaconda-cloud": {},
"kernelspec": {
"display_name": "Python [conda env:py36_bw]",
"language": "python",
"name": "conda-env-py36_bw-py"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.2"
}
},
"nbformat": 4,
"nbformat_minor": 1
}
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