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Create environmentally extended input-output models

License: Other

Python 38.93% Jupyter Notebook 61.07%

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io-model-builder's Introduction

iomb - Input-Output Model Builder

iomb is an open source Python library for creating environmentally extended input-output models (EEIO models) from CSV files in a simple data format. It includes functions to calculate different result types (e.g. life cycle assessment results, direct and upstream contributions, etc.) from such models and convert them into JSON-LD data packages that can be imported into openLCA.

Installation

iomb is tested with Python 3.5 but should also work with older versions of Python 3. The easiest way to install the package is to do so using pip, which is generally packaged with a Python installation. Open up the command line and enter:

pip install IO-Model-Builder

This will also install the dependencies of the IO-Model-Builder (NumPy, pandas, and matplotlib) if required. After this you should be able to use the iomb package in your Python code. To uninstall the package, you can again use pip from the command line:

pip uninstall IO-Model-Builder

Usage

You can find a more detailed example here in form of a Jupyter notebook which is a convenient way to use iomb. The following script shows the basic usage of iomb. For detailed information about the data format see the data format specification

import iomb

# optionally show all logging information of iomb
iomb.log_all()

# create a direct requirements coefficients matrix from a supply and use table
# and save it to a CSV file
drc = iomb.coefficients_from_sut('supply_table.csv', 'use_table.csv')
drc.to_csv('drc.csv')

# create an EEIO model from a coefficients matrix, satellite tables, and a
# LCIA method
model = iomb.make_model('drc.csv',
                        ['satellite_table1.csv', 'satellite_table2.csv'],
                        "sector_meta_data.csv",
                        ['LCIA_factors1.csv', 'LCIA_factors1.csv'])

# validate the model
import iomb.validation as val
vr = validation.validate(model)
print(vr)

# calculate results for a given demand
result = iomb.calculate(model, {'1111a0/oilseed farming/us': 1})
print(result.total_result)

# export the model to a JSON-LD package
import iomb.olca as olca
olca.Export(model).to('model_as_json-ld.zip')

License

This project is in the worldwide public domain, released under the CC0 1.0 Universal Public Domain Dedication.

Public Domain Dedication

Citation

Please cite as: Srocka, M. and W. Ingwersen (2017). IO Model Builder, v1.1 (or current version). US Environmental Protection Agency. https://www.github.com/usepa/io-model-builder

A brief description of the iomb is also included in: Yang, Y., Ingwersen, W.W., Hawkins, T.R., Srocka, M., Meyer, D.E., 2017. USEEIO: A New and Transparent United States Environmentally-Extended Input-Output Model. Journal of Cleaner Production 158, 308-318. DOI: 10.1016/j.jclepro.2017.04.150

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metacodetools ianmadlenya tjlca shaobinli james-condliffe m4h1rdev

io-model-builder's Issues

regarding some missing files

model = iomb.make_model('drc.csv',
['satellite_table1.csv', 'satellite_table2.csv'],
"sector_meta_data.csv",
['LCIA_factors1.csv', 'LCIA_factors1.csv'])
I would like to know if the files "satellite_table1.csv, satellite_table2.csv, LCIA_factors_factors1.csv, etc." need to be provided or is automatically created by the program. This program is giving many errors mostly regarding missing files.

result = iomb.calculate(model, {'1111a0/oilseed farming/us': 1})
print(result.this_result)
Also, there is no attribute in the Result class called this_result.

Would appreciate if someone got back to me.

I am running the code in Acanonda Python Spyder.

Should we use metadata files for elementary flows?

Metadata files of elementary flows are currently not used as all information about a flow is currently also available in the satellite tables. However, it could be useful to extract fields like CAS number, flow UUID, chemical formula, description, etc. from the satellite tables and add them to a metadata file.

This could be also useful when we want to create links to other product flows via the satellite matrix.

as_matrix deprecated

the as_matrix function here has been deprecated since pandas 0.23

recommendation is to use .to_numpy() isntead.

Sat table .. Repeat rows ignore

When two rows are identical in every respect except the amount, one will be ignored. Here is an example satellite table where this occurs. Note the line with the Nitrogen in gets replaced by a later line in the table that is identical except with a different amount.
GAUSEEIO_Satellite_N&P_oldnotworking.txt

Capturing additional data quality information

Currently we have the ability to capture flow level data quality scores in the satellite tables.

We should be able to include the USEPA data quality schemes in the background. I will upload a json-ld file with the flow and process level schemes.

I would like also to be able to assign flow level data quality for the commodity inputs created from the direct requirements table. To keep this simple, this can be added manually for now. For the USEEIO, using the USEPA data quality scheme the scores would be {1;3;1;1;1}

Perhaps the sector metadata file format can be expanded to allow for process level scores to be entered for each process/sector.
USEPA_DataQualitySchemes_JSON-LDforopenLCA1.6.zip

In the end we would like to be able to export the flow-level data quality and process-level data quality data into JSON-LD

Elementary flows without subcategory not working with JSON-LD

Elementary flows without subcategories are not being correctly handled in the JSON-LD export and import into openLCA.

LCIA method will not import into < olca 1.5

Just an FYI and not a request, a JSON-LD export from the IOMB will not import the impact method into versions of openlca pre 1.5.

DQI calc for U can results in errant values

Results in values not 1,2,3,4 or 5
examples from trial of USEEIOv1.2

(-7,-17,1,-124,-106)
(9,14,1,93,87)
(14,2,1,4,5)

Validation - check for repeat UUIDs

Upon creation of the JSON-LD files from a model, I received warnings that a duplicate .json file for a flow was being created:

site-packages\iomb\olca_init_.py:267: UserWarning: Duplicate name: 'flows/eff3fef5-fcfc-4201-be4e-a2d342c2e0c7.json'
pack.writestr(path, s)

I believe this is because the UUIDs were repeated for the flow. This was not reported during the validation. It would be nice if the Validation tested for repeat UUIDs.

Potential special session at the IIOA 2023

Hi folks,

Just a short question:
I check if there is enough interest for a special session on Open Source software for IO development/analysis at the IIOA 2023 (https://iioa.org/conferences/29th/important_dates.html ). Would any of the authors of IO-Model-Builder to be interested in presenting there?

Cheers
Konstantin

matio needs to provide ID to indicators.csv

The matio export is not giving the indicators an ID in the indicators.csv file