Synthetic diesel for trucks

Description

This is a repository containing scenarios that implement the projections developed the following publication:
Integrating emerging technologies deployed at scale within prospective life cycle assessment, Charalambous et al. (2024).

It is meant to be used in premise in addition to a global IAM scenario, to analyze synthetic diesel for heavy-duty trucks.

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

Sourced from publication

If you use this data package in your research, please cite the following publication:
Charalambous et al., 2024. Integrating emerging technologies deployed at scale within prospective life cycle assessment, Sustainable Production and Consumption.
DOI: https://doi.org/10.1016/j.spc.2024.08.016

Ecoinvent database compatibility

ecoinvent 3.8 cut-off

IAM scenario compatibility

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

IAM scenario	APS scenario	Climate policy
REMIND SSP2-Base	Business As Usual	None
REMIND SSP2-PkBudg1150	Sustainable development	Paris Agreement
REMIND SSP2-PkBudg500	Sustainable development	Paris Agreement
REMIND SSP2-NPi	Sustainable development	National Policies Implemented
REMIND SSP2-NDC	Sustainable development	National Determined Contributions
REMIND SSP1-Base	Business As Usual	None
REMIND SSP1-PkBudg1150	Sustainable development	Paris Agreement
REMIND SSP1-PkBudg500	Sustainable development	Paris Agreement
REMIND SSP1-NPi	Sustainable development	National Policies Implemented
REMIND SSP1-NDC	Sustainable development	National Determined Contributions
REMIND SSP5-Base	Business As Usual	None
REMIND SSP5-PkBudg1150	Sustainable development	Paris Agreement
REMIND SSP5-PkBudg500	Sustainable development	Paris Agreement
REMIND SSP5-NPi	Sustainable development	National Policies Implemented
REMIND SSP5-NDC	Sustainable development	National Determined Contributions

What does this do?

This external scenario introduces synthetic diesel fuel destined to replace the synthetic fraction of the diesel market which is fueling heavy-duty trucks.

We introduce efficiency improvements in hydrogen production and electrolysis.

We include 11 hydrogen production pathways and two technologies for capturing CO₂:

• For H₂: 10 PEM electrolysis and 1 bio-based
• For CO₂: one direct air capture (DAC) and one post-combustion capture

Resulting in 22 diesel production pathways by combining H₂ and CO₂.

Here we do not modify the technosphere using specific keywords of premise, but we perform the modifications later using inventory matrices. As shown in the Integrated-LCA repository and the IntLCA package that can be installed through pypi.

Despite the usage for trucks this package can be used in any othe application that requires synthetic diesel pathways.

Flow diagram

The locations that the synthetic diesel which is included in this data package will be added are shown with light blue in figure:

How to use it?

    import brightway2 as bw
    from premise import NewDatabase
    from datapackage import Package
    
    
    fp = r"https://raw.githubusercontent.com/MargotCha/HDdiesel-prospective-scenarios/main/datapackage.json?token=GHSAT0AAAAAACSIUT3TGN2FEDOVFGKKKJPAZSGACQQ"
    synfuel = Package(fp)
    
    bw.projects.set_current("your_bw_project")
    
    ndb = NewDatabase(
            scenarios = [
                {"model":"remind", "pathway":"SSP2-Base", "year":2050,},
                {"model":"remind", "pathway":"SSP2-PkBudg1150", "year":2030,},
            ],        
            source_db="ecoinvent 3.8 cutoff",
            source_version="3.8",
            key='xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',
            external_scenarios=[
                synfuel, # <-- list datapackages here
            ] 
        )