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ammonia-prospective-scenarios GitHub release (latest by date) DOI

Description

This is a repository containing scenarios that implement the projections developed for the following publication:

A Prospective Life Cycle Assessment of Global Ammonia Decarbonisation Scenarios
Johanna Boyce, Romain Sacchi, Earl Goetheer, Bernhard Steubing
In review.

It is meant to be used in premise in addition to a global IAM scenario, to provide refined projections for the future supply of ammonia for each IAM region.

Note that projections regarding regional ammonia markets stop at 2050. Any premise database with a reference year beyond 2050 will use projections for 2050.

This data package contains all the files necessary for premise to implement this scenario and create market- and region specific technology supply shares for ammonia.

Note

Cannot be used together with update("fuels").

Sourced from publication

If you use this data package in your research, please cite the following publication: A Prospective Life Cycle Assessment of Global Ammonia Decarbonisation Scenarios
Johanna Boyce, Romain Sacchi, Earl Goetheer, Bernhard Steubing
In review.

Results

Unitary and absolute results per technology and region are available in the results folder.

Data validation

goodtables.io

Test

example workflow

Ecoinvent database compatibility

ecoinvent 3.9 cut-off

IAM scenario compatibility

The following coupling is done between IAM scenarios and the ammonia market scenarios (APS):

IAM scenario APS scenario
IMAGE SSP2-Base Business As Usual
IMAGE SSP2-RCP26 Sustainable development
IMAGE SSP2-RCP19 Sustainable development
REMIND SSP2-Base Business As Usual
REMIND SSP2-PkBudg1150 Sustainable development
REMIND SSP2-PkBudg500 Sustainable development

What does this do?

This external scenario update the ecoinvent market for ammonia, according to the projections described in the Master thesis study of J. Boyce, 2022.

Ammonia


The following markets are introduced:

  • market for ammonia, via steam reforming w/ CCS (APS)
  • market for hydrogen, electrolysis (APS)
  • market for ammonia (APS)

market for ammonia (APS) is supplied by seven ammonia production pathways:

  • MP (Methane Pyrolysis), called ammonia production, hydrogen from methane pyrolysis,
  • SMR (Steam Methane Reforming), called ammonia production, steam reforming,
  • SMRC (SMR with CCS), called market for ammonia, via steam reforming w/ CCS,
  • ELE (electrolysis), called ammonia production, hydrogen from electrolysis,
  • OIL (Partial oxidation of oil), called ammonia production, hydrogen from partial oxidation of oil,
  • CG (coal gasification), called ammonia production, hydrogen from coal gasification,
  • CGC (CG with CCS), called ammonia production, hydrogen from coal gasification w/ CCS.

This market re-links to activities that consume ammonia throughout the database.

Hydrogen


The following market is introduced:

  • market for hydrogen, electrolysis (APS)

It is supplied by two hydrogen production pathways:

  • AE (alkaline electrolysis), and
  • PEM electrolysis

This market re-links to ammonia-producing activities that consume hydrogen throughout the database.

Flow diagram

diagram ammonia markets

How to use it?

    import brightway2 as bw
    from premise import NewDatabase
    from datapackage import Package
    
    
    fp = r"https://raw.githubusercontent.com/premise-community-scenarios/ammonia-prospective-scenarios/main/datapackage.json"
    ammonia = Package(fp)
    
    bw.projects.set_current("your_bw_project")
    
    ndb = NewDatabase(
        scenarios = [
            {"model":"image", "pathway":"SSP2-Base", "year":2050, "external scenarios": [{"scenario": "Business As Usual - image", "data": ammonia}]},
            {"model":"image", "pathway":"SSP2-RCP26", "year":2030, "external scenarios": [{"scenario": "Sustainable development - image", "data": ammonia}]},
        ],        
        source_db="ecoinvent 3.10 cutoff",
        source_version="3.10",
        key='xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',
    )
        
   ndb.update("external") # or ndb.update() if you want to update the database with the IAM data plus the external scenario