Cite: Arvesen et al. for the LCA coefficients and Pehl et al. or Luderer et al. for MAgPIE LULUC coefficients as well as methodology on joining LCA and IAM data.
All files required to use the module are available here
The data set of lifecycle impacts is differentiated by scenario (baseline or climate policy), region (nine IEA regions), power-sector technology, technology variant (different types of technologies employing the same energy conversion, see first worksheet of NTNU_LCA_coefficients.xlsx), lifecycle phase (construction, operation, end-of-life) and period (2010, 2030, 2050). Impacts include:
The R script provided with the module combines IAM results with these coefficients to produce impacts differentiated by technology and lifecycle phase for different models, scenarios, regions and periods.
As the module is written in the R language, it is necessary to have a working R installation to run it. See the R website for details.
To use the module, edit the configuration block in ADVANCE_Toolbox_EI.R and
Then run the script using Rscript ADVANCE_Toolbox_EI.R or any method provided by your R environment.
The module will generate three files in the ./output/ subdirectory. The base file contains all impacts for the mix of technology variants (see below) in a format like that of the IIASA data base (i.e. with columns for model, scenario, region, variable, unit and the different time steps). The two files with _energy and _environment appended to the file name contain the data for embodied energy use and environmental impacts in a similar format, but with more columns for different dimensions, and also include the full range of technology variants.
IAM Input Data
The module requires input data on capacity, capacity additions and electricity production of power sector technologies. See the file Variable_Definitions.csv for a detailed listing and descriptions.
Lifecycle Coefficient Scenarios
The two scenarios for lifecycle impact coefficients differ in assumptions for future improvements in performance parameters for selected industrial process (Arvesen et al., submitted). They are based on the Baseline and BLUE Map scenarios of IEA (2010). The use of the BLUE Map scenario is suggested for all IAM scenarios with climate mitigation policy, as the assumed technology and efficiency improvements are generally in line with concerted climate mitigation efforts. The Baseline coefficients may be used for uncertainty analysis in addition to the assessment of baseline scenarios. For the time being, scenarios based on nationally determined contributions (NDC) should be based on the Baseline scenario, as efficiency improvements are likely to be lower than under stringent climate change mitigation policies.
The LCA data set contains coefficients for different variations of the same technology (see first worksheet of NTNU_LCA_coefficients.xlsx). The "mix" variant holds the data for the share of technology variants assumed for a given period in Arvesen et al. (submitted), or for the "default" variant in the case of bioenergy (see below).
MAgPIE LULUC Coefficients
Coefficients for emissions from (induced) land use and land-use change were calculated using results from the MAgPIE land use model. They spanned eighteen scenarios along the three axes
To compute effects due to the use of bioenergy, emissions from the scenarios with no biomass production were subtracted from those with biomass production (resulting in nine scenarios for biomass production). Also, a scenario with no dedicated production of biomass, but use of biomass residues is included, which does not entail emissions from land use and land-use change.
Since the conversion of areas for agriculture use entail large none-recurring emissions of CO2, these have been calculated as the quotient of cumulated CO2 emissions and cumulated bioenergy production. N2O and CH4 emission coefficients were calculated as the quotient of emissions and bioenergy use. Furthermore, only global values were used for the LULUC coefficients, as changes in regional production and trade could lead to skewed regional values. Note also that the LULUC coefficients in MAgPIE_LULUC_GHG_coefficients.csv are in terms of primary energy and are therefore converted to Mt CO2eq/EJelectricity using the generic efficiencies of 41% and 31% for Bioenergy without and with CCS.
As LCA coefficients are only available for the years 2010, 2030 and 2050, they are linearly interpolated for the periods in between (i.e., C2035 = 3/4 C2030+1/4 C2050) and constant before and after at the level of the closest period available (i.e., C2070 = C2050). If values after 2050 are reported, they should be qualified by the information that possible future (after 2050) developments are not accounted for in the LCA coefficients.