Package 'mrremind'

Description

The mrremind packages contains data preprocessing for the REMIND model.

Author(s)

Maintainer: Lavinia Baumstark [email protected]

Authors:

• Renato Rodrigues

• Antoine Levesque

• Julian Oeser

• Christoph Bertram

• Ioanna Mouratiadou

• Aman Malik

• Felix Schreyer

• Bjoern Soergel

• Marianna Rottoli

• Abhijeet Mishra

• Alois Dirnaichner

• Michaja Pehl

• Anastasis Giannousakis

• David Klein

• Jessica Strefler

• Lukas Feldhaus

• Regina Brecha

• Sebastian Rauner

• Jan Philipp Dietrich

• Stephen Bi

• Falk Benke

• Pascal Weigmann

• Oliver Richters

• Robin Hasse

• Sophie Fuchs

• Rahel Mandaroux

• Johannes Koch

• Gabriel Abrahao

• Tabea Dorndorf

See Also

Useful links:

• https://github.com/pik-piam/mrremind

Description

Calculate REMIND final energy variables from historical AGEB values

Usage

calcAGEB(subtype = "balances")

Arguments

Author(s)

Falk Benke

Description

Calculate air pollutant emissions for a reference year at different sectoral aggregation levels based on CEDS2025 and GAINS2025 data.

Usage

calcAirPollBaseyearEmi(
  baseyear = 2020,
  CEDS.5yearmean = TRUE,
  data_source = "CEDS2025",
  outsectors = "GAINS"
)

Arguments

Value

magclass object

Author(s)

Gabriel Abrahao, Laurin Koehler-Schindler

Description

Provide price path data

Usage

calcBiocharBounds()

Author(s)

Tabea Dorndorf

Description

Provides back-of-envelope upper limits of biochar application on cropland.

Estimates upper limits as either cumulative stock capacity (t) over a compliance window, or as annual flow ceiling (t/yr) for cropland soils, using physical cropland area, adoption shares, and application-rate limits per area.

Usage

calcBiocharLimitCropland(
  dataBCLimit = "CRCF_draft_2025",
  adoptShare = 1,
  refYear = "y2020",
  annualLimit = TRUE
)

Arguments

Value

List of magpie objects with results on country level, weight on country level, unit and description.

Author(s)

Isabelle Weindl

See Also

mrlandcore::calcCroparea()

Examples

## Not run: 
calcOutput("BiocharLimitCropland",
           dataBCLimit = "CRCF_draft_2025",
           adoptShare = 1,
           refYear = "y2020",
           annualLimit = TRUE)

## End(Not run)

Description

read biomass supply curves from Magpie emulator

Usage

calcBiomassPrices()

Value

Magpie object with two parameters determining linear biomass supply curve

Description

Calculate REMIND variables from historical BP values

Usage

calcBP()

Author(s)

Falk Benke

Description

provides historical capacity values in TW

Usage

calcCapacity(subtype)

Arguments

Value

magpie object of capacity data

Author(s)

Renato Rodrigues, Stephen Bi, Fabrice Lécuyer

Examples

## Not run: 
calcOutput("Capacity", subtype = "capacityByTech")

## End(Not run)

Description

This function gathers project pipeline data for different technologies to generate REMIND input data for setting historical and near-term bounds. The output is technology capacity in three different categories: "operational": installed capacity that is operational in the respective year "construction": capacity that is currently under construction but expected to be completed in the respective year "planned": capacity that is planned to be completed by this year but not yet under construction. The exact definition of this category (e.g. whether only projects with FID are included)may vary by technology and is documented in calcProjectPipelines. Moreover, the function provides project pipeline data for the historical mif file.

Usage

calcCapacityBounds(subtype)

Arguments

Author(s)

Felix Schreyer

Description

provides capacity factor values

Usage

calcCapacityFactor()

Value

magpie object of the capacity factor data

Author(s)

Renato Rodrigues, Stephen Bi

Examples

## Not run: 
calcOutput("CapacityFactor")

## End(Not run)

Description

provides capacity factor values

Usage

calcCapacityFactorHist()

Value

magpie object of the capacity factor data

Author(s)

Renato Rodrigues, Stephen Bi, Fabrice Lécuyer

Examples

## Not run: 
calcOutput("CapacityFactor")

## End(Not run)

Description

use historical nuclear electricity generation capacity and calculate near-term estimates based on current nuclear power project status per country.

Usage

calcCapacityNuclear()

Author(s)

Robert Pietzcker, Christoph Bertram, Aman Malik, Pascal Weigmann

Description

Compute macroeconomic capital stock based on capital intensities from PWT and GDP scenarios from mrdrivers. The PWT capital intensities are used up until 2010. After that, the capital intensities converge towards that of Japan in 2010, at speeds that vary across scenarios. The final capital stocks are the product of the capital intensities and the gdp scenarios from mrdrivers.

Usage

calcCapital(scenario)

Arguments

Value

magpie object with the requested output data either on country or on regional level depending on the choice of argument "aggregate" or a list of information if supplementary is set to TRUE.

See Also

• See the vignette vignette("scenarios", "mrdrivers") for information on the GDP scenarios.

• readPWT() for information on the PWT version used.

Description

The capacity targets (GW) at regional level are produced from different databases

• UNFCCC_NDC database, an update of the Rogelj 2017 paper (see readme in inputdata)

• REN21 Global Renewables

• New Climate NPI policy database

Usage

calcCapTarget(sources)

Arguments

Author(s)

Aman Malik, Oliver Richters, Rahel Mandaroux, Léa Hayez, Falk Benke

Description

Calculate CCS capacity from IEA CCUS data

Usage

calcCCScapacity(subtype)

Arguments

Author(s)

Anne Merfort, Falk Benke

Description

This function merges the output of two other functions that calculate REMIND input data for the shares of cooling types per electricity technology and REMIND region, using as initial information the Davies (2013) data per electricity technology and GCAM region. The two other functions separately calculate data for the base year and for future time steps. The source data provide most required information but some assumptions on missing data are also made.

Usage

calcCoolingSharesAll()

Value

MAgPIE object on cooling type shares per elecricity technology and REMIND region

Author(s)

Ioanna Mouratiadou

See Also

readDaviesCooling, convertDaviesCooling, calcCoolingSharesBase,calcCoolingSharesFuture

Examples

## Not run: 
a <- calcOutput("CoolingSharesAll")

## End(Not run)

Description

This function calculates REMIND input data for the shares of cooling types per electricity technology and REMIND region in 2005, using as initial information the Davies (2013) data per electricity technology and GCAM region. The source data provide most required information but some assumptions on missing data are also made.

Usage

calcCoolingSharesBase()

Value

MAgPIE object on cooling type shares per elecricity technology and REMIND region

Author(s)

Lavinia Baumstark, Ioanna Mouratiadou

See Also

readDaviesCooling, convertDaviesCooling, calcCoolingSharesAll,calcCoolingSharesFuture

Examples

## Not run: 
a <- calcOutput("CoolingSharesBase")

## End(Not run)

Description

This function calculates REMIND input data for the shares of cooling types per electricity technology and REMIND region in post-2020, using as initial information the Davies (2013) data per electricity technology and GCAM region. The source data provide most required information but some assumptions on missing data are also made.

Usage

calcCoolingSharesFuture()

Value

MAgPIE object on cooling type shares per elecricity technology and REMIND region

Author(s)

Ioanna Mouratiadou calcCoolingSharesAll,calcCoolingSharesBase

Examples

## Not run: 
a <- calcOutput("CoolingSharesFuture")

## End(Not run)

Description

Provides REMIND data for PE tradecosts (energy losses on import).

Usage

calcCostsTrade()

Value

REMIND data forPE tradecosts (energy losses on import) and corresonding weights (1) as a list of two MAgPIE objects

Author(s)

Lavinia Baumstark

Examples

## Not run: 
calcOutput("CostsTrade")

## End(Not run)

Description

Provides REMIND data for PE trade cost (energy losses on import, export and use).

Usage

calcCostsTradePeFinancial()

Author(s)

Regina Brecha, Lavinia Baumstark

Examples

## Not run: 
calcOutput("CostsTradePeFinancial")

## End(Not run)

Description

Calculate costs of transport of enhanced weathering

Usage

calcCostsWeathering()

Value

transport costs of spreading rock on the fields

Examples

## Not run: 
calcOutput("CostsWeathering")

## End(Not run)

Description

Disaggregated investment cost data is aggregated and technologies renamed to REMIND names

Usage

calcDiffInvestCosts()

Details

REMIND does not have a classification of coal power plants e.g., sub-critical. Therefore, countries are given coal plant costs assuming what type of coal plants are expected to develop there. For other technologies, certain assumptions are taken to change to REMIND convention.

Value

Magpie object with aggregated but differentiated investment costs for some technologies.

Author(s)

Aman Malik

Description

Calculates the share of distributed solar pv, wind-onshore/offshore, hydro-small/large from 2015 to 2050. For spv - Only includes grid-connected pv.

Usage

calcDspvShare(subtype)

Arguments

Details

Known limitations - source for distributed spv (IEA Renewables 2019) is different than source for total spv (IRENA 2019)

Value

magpie object with REMIND-aggregated regions

Author(s)

Aman Malik

Description

calcEDGAR7Fgases

Usage

calcEDGAR7Fgases()

Author(s)

Gabriel Abrahao

Description

Prepare EDGETransport inputs

Usage

calcEDGETransport(subtype)

Arguments

Value

REMIND/iterative EDGE-T input data for all scenario combinations

Author(s)

Johanna Hoppe

Description

Calculate historical GHG Emissions from European Environment Agency

Usage

calcEEAGHGEmissions()

Author(s)

Falk Benke, Renato Rodrigues

Description

Calculate EEA emission projections from the two projections sources provided by European Environment Agency

Usage

calcEEAGHGProjections()

Author(s)

Falk Benke, Renato Rodrigues

Description

Calculate distribution of total EEZ size

Usage

calcEEZdistribution()

Author(s)

Tabea Dorndorf

Description

prepare the yearly Ember electricity data set To use only a part of the Ember data, call calcOutput("Ember", subtype = "...") and convert to TW if you want to use capacities as input data to REMIND.

Usage

calcEmber(subtype = "all")

Arguments

Author(s)

Pascal Weigmann

Description

EmiCO2LandUse calculate co2 emissions from land use change

Usage

calcEmiCO2LandUse()

Value

magpie object

Author(s)

Julian Oeser

Examples

## Not run:  a <- calcOutput(type="EmiCO2LandUse")

Description

Fugitive methane emissions from fossil fuel extraction

Usage

calcEmiFossilFuelExtr(source)

Arguments

Details

REMIND uses historical data on fugitive methane emissions from fossil fuel extraction for coal, oil and gas to derive emission factors. The data is available from two sources: EDGAR (for base year 2005) and CEDS2025 (2020).

Value

Magpie object with CH4 emissions from fossil fuel extraction for coal, oil and gas in 2005, in Mt CH4

Author(s)

Gabriel Abrahao

Description

historical LULUCF CO2 emissions following country accounting

Usage

calcEmiLULUCFCountryAcc()

Value

Magpie object with historical LULUCF emissions

Author(s)

Felix Schreyer, Falk Benke

Description

Provides REMIND data for baseline emissions for maccs for 1990.

Usage

calcEmiMac1990()

Value

REMIND data for baseline emissions for maccs for 1990 and corresonding weights (NULL) as a list of two MAgPIE objects

Author(s)

Lavinia Baumstark

Examples

## Not run: 
calcOutput("EmiMac1990")

## End(Not run)

Description

provides European 2030 emission targets in relation to 1990 and 2005 emissions

Usage

calcEmiReference()

Value

2030 emission reductions tragets for 40%, 55% and 64% reductions in relation to 2005 values

Author(s)

Falk Benke and Renato Rodrigues

Examples

## Not run: 
calcOutput("EmiReference")

## End(Not run)

Description

calcEmissions

Usage

calcEmissions(datasource = "CEDS16")

Arguments

Value

magpie object with historical emissions

Author(s)

Steve Smith, Pascal Weigmann

Description

Calculates historical emissions needed for estimating emission factors in extra emissions reporting

Usage

calcEmissions4ReportExtra(sectors = "CEDS")

Arguments

Value

list of magclass with CEDS CH4 and N2O emissionsdata for CEDS sectors for 2020, in Mt N or Mt CH4 per year

Author(s)

Gabriel Abrahao

Description

This function calculates the emissions targets for the NDC scenarios applied in the REMIND module 45_carbonprice realization NDC. It contains the following steps: The parameters calculated in 3.) and 4.) are further used in the NDC realization to calculate the region-wide NDC emissions targets in terms of total GHG emissions excl. bunkers and excl. LULUCF sectors.

Usage

calcEmiTarget(sources, subtype, scenario)

Arguments

Author(s)

Aman Malik, Christoph Bertram, Oliver Richters, Rahel Mandaroux, Falk Benke

Description

Uses historical emissions from 1990-2022. CO2 (excl LU), CH4, N2O (so far no F-Gas historic time series) When available, UNFCCC data is used, otherwise CEDS data.

Usage

calcEmiTargetReference()

Author(s)

Rahel Mandaroux, Falk Benke

See Also

calcEmiTarget(), convertUNFCCC_NDC()

Description

Calculate REMIND variables from European Energy Datasheets

Usage

calcEuropeanEnergyDatasheets(subtype)

Arguments

Value

A magpie object.

Author(s)

Falk Benke

Description

Calculate REMIND emission variables from historical Eurostat (env_air_gge) values

Usage

calcEurostatEmissions()

Author(s)

Falk Benke

Description

prepare data for exogenuous FE and ES demand pathways that do not come from EDGE models but from other sources and/or scenario literature. REMIND can be fixed to those demand pathways if the switch cm_exogDem_scen is activated.

Usage

calcExogDemScen()

Value

A magpie object.

Author(s)

Felix Schreyer

Description

Calculate expert guesses

Usage

calcExpertGuess(subtype)

Arguments

Author(s)

Falk Benke

Description

Calculates FE historical from IEA energy balances

Usage

calcFE(ieaVersion = "default")

Arguments

Author(s)

Lavinia Baumstark, Aman Malik

Description

Returns the EDGE-Buildings data as REMIND variables

Usage

calcFeDemandBuildings(subtype, scenario)

Arguments

Author(s)

Robin Hasse

Description

Project the IEA flow ONONSPEC into the future. As we have no idea, where this energy demand comes from, we use a very generic methos to project it into the future: We assume an asymptotic model. It starts from the level $x_\text{EOD}$ at the end of data (EOD) with EOD slope $\dot{x}_\text{EOD}$ and approaches the fraction $\varepsilon$ of this slope within $\Delta t$. Both $x_\text{EOD}$ and $\dot{x}_\text{EOD}$ are determined through a linear regression of the last $n$ time steps with IEA data.

$x(t) = x_\text{EOD} + \dfrac{\dot{x}_\text{EOD}}{c} \cdot [1 - \exp (-c \cdot (t - t_\text{EOD}))]$

with the decay rate $c = -\dfrac{\ln \varepsilon}{\Delta t}$
$\Delta t$ is differentiated by scenarios thus approaching a low, med and high long-term level. To assure that scenarios don't differ at the end of history (EOH), time steps between EOD and EOH are projected with med value of $\Delta t$.

Usage

calcFeDemandONONSPEC(scenario, eoh)

Arguments

Details

Each scenario $s$ has a differentiated $\Delta t_s$. For $\dot{x}_\text{EOD} > 0$, the high (low) scenario assumes a longer (shorter) time span and for $\dot{x}_\text{EOD} < 0$ vice versa to reach a higher (lower) long-term value. We want to make sure that until the end of history (EOH), all scenarios are still identical. So we take the med parameterisation until EOH. Afterwards, we adjust the model such that we start with EOH level and slope and still reach the target slope $\varepsilon \cdot \dot{x}_\text{EOD}$ until $t_\text{EOD} + \Delta t_s$:

$x_s(t) = x_\text{EOH} + \dfrac{\dot{x}_\text{EOH}}{c_s} \cdot [1 - \exp (-c_s \cdot (t - t_\text{EOH}))]$

with the decay rate $c_s = -\dfrac{\ln \varepsilon } {\Delta t_s - (t_\text{EOH} - t_\text{EOD})} \cdot \left(1 - \dfrac{t_\text{EOH} - t_\text{EOD}} {\Delta t_\text{med}} \right)$

Value

list with MagPIE object

Author(s)

Robin Hasse

Description

FE Share parameters used in REMIND

Usage

calcFEShares(subtype, scenario)

Arguments

Author(s)

Antoine Levesque

Description

Reads in the data of the source IIASA_subs_taxes, by country. and calculate taxes at the final energy delivery level to the end-use sectors (industry, buildings and transport). Regional aggregation is done via the respective energy quantities as weights.

Usage

calcFETaxes(subtype = "taxes")

Arguments

Value

MAgPIE object

Author(s)

Christoph Bertram and Renato Rodrigues

See Also

readIIASA_subs_taxes, convertIIASA_subs_taxes

Examples

## Not run: 
calcOutput("FETaxes")

## End(Not run)

Description

generate F-Gases based on IMAGE data

Usage

calcFGas(subtype = "IMAGE2025", interp = "interpolate2025", interpyear = 2030)

Arguments

Value

magpie object with F-gases information

Author(s)

Lavinia Baumstark, Gabriel Abrahao

Examples

## Not run: 
x <- calcOutput("FGas")

## End(Not run)

Description

Residential, commercial and total floor space from EDGE-B. Set

Usage

calcFloorspace(scenario, onlyTotal = FALSE)

Arguments

Value

MAgPIE object with buildings floor space

Author(s)

Antoine Levesque, Robin Hasse

Description

provides coefficients for fossil fuels (oil, gas and coal) and uranium extraction cost equations.

Usage

calcFossilExtraction(subtype = "FossilExtraction")

Arguments

Value

magpie object of the coefficients for fossil fuels and uranium extraction cost equations

Author(s)

Renato Rodrigues, Felix Schreyer

Examples

## Not run: 
calcOutput(type = "FossilExtraction", subtype = "FossilExtraction")

## End(Not run)

Description

This function is meant to be used to clean-up, fill gaps and smoothen the GAINS data to obtain consistent timeseries of emission factors from 2005 to 2100. The actual generation REMIND-specific files happens in calcGAINS2025forREMIND.

Usage

calcGAINS2025(
  weight_source = "CEDS2025",
  outsectors = "GAINS2025",
  outunit = "Tg/TWa"
)

Arguments

Value

Emission factor timeseries for all scenarios from 2005 to 2100: magclass object with dimensions region, year, and ssp.scenario.sectorGAINS.species

Author(s)

Gabriel Abrahao, Laurin Koehler-Schindler

Description

Extracts oil, gas and coal data from the GEA 2012 into a scenario- and time-dependent grade structure

Usage

calcGEA2012(subtype, datatype)

Arguments

Value

MAgPIE object containing regionally aggregated GEA 2012 data

Author(s)

Stephen Bi

Examples

## Not run: 
a <- calcOutput("GEA2012")

## End(Not run)

Description

Calculate near-term expectations of capacities for use in fullVALIDATION.R

Usage

calcGlobalEnergyMonitor()

Author(s)

Falk Benke

Description

Calculate historical landuse emissions

Usage

calcHistoricalLUEmissions()

Author(s)

David Klein, Falk Benke

Description

Calculate Final Energy for the buildings sector from Heat Roadmap Europe scenarios

Usage

calcHRE()

Value

A magpie object.

Author(s)

Pascal Weigmann

Description

Calculates PE|Coal, PE|Oil, PE|Gas, and FE as direct sums of relevant products for TES (PEs) or TFC (FE), minus (negative) bunkers. Used for benchmarking in the historical.mif and for the IIASA Scenario Compass Initiative vetting.

Usage

calcIEA_EB_directSum()

Description

Calculate REMIND emission variables from IEA ETP values

Usage

calcIEA_ETP()

Author(s)

Falk Benke

Description

Calculate REMIND variables from IEA Global EV Outlook data

Usage

calcIEA_EVOutlook()

Author(s)

Falk Benke

Description

Calculate REMIND variables from IEA World Energy Outlook data.

Usage

calcIeaWorldEnergyOutlook()

Author(s)

Falk Benke

Description

Calculate REMIND investment variables from IEA World Energy Investment Outlook (2024)

Usage

calcInvestmentHistorical()

Author(s)

Nicolas Bauer, Falk Benke

Description

Computes IEA-based model data for different "subtypes" by use of raw IEA "Energy Balances" data and a mapping that corresponds to the structure of "products" and "flows" of IEA.

Usage

calcIO(
  subtype = c("input", "output", "trade"),
  ieaVersion = "default",
  corrected = FALSE
)

Arguments

Details

Mapping structure example: IEA product ANTCOAL used for IEA flow TPATFUEL, contributes via REMIND technology coaltr for generating sesofos from pecoal (REMIND names)

Value

IEA data as MAgPIE object aggregated to country level

Author(s)

Anastasis Giannousakis

Examples

## Not run: 
a <- calcOutput("IO", subtype = "output")

## End(Not run)

Description

A wrapper around calcIO used to generate REMIND input data, created to apply corrective steps in a cache-conscious manner by avoiding additional subtypes in calcIO.

Usage

calcIoRemind(subtype)

Arguments

Author(s)

Falk Benke

Description

Calculate REMIND variables from historical IRENA capacities.

Usage

calcIRENA()

Author(s)

Falk Benke

Description

Calculate selected REMIND energy and emission variables from historical JRC IDEES values

Usage

calcJRC_IDEES(subtype)

Arguments

Value

A magpie object.

Author(s)

Falk Benke

Description

write KLW damage parameters (from Kotz et al. 2024) into input data they are country-specific and should not be aggregated to the regional level at all

Usage

calcKLWdamage(subtype)

Arguments

Value

MAgPIE object of damage parameters for KLW damage function on country level and for 1000 boostrapping samples

Author(s)

Franziska Piontek

Description

Calculate LDV Shares using EDGE-Transport

Usage

calcLDVShares()

Author(s)

Johanna Hoppe, Falk Benke

Description

Calculate baseline emissions trajectories for transport, adipic acid and nitric acid production

Usage

calcMACCbaseN2O(source = "PBL_2007")

Arguments

Value

list of magclass with REMIND input data for different sectors for timesteps 2000-2100, in Mt N per year

Author(s)

Lavinia Baumstark, Gabriel Abrhahao

Description

Rrange of possible abatement between maximum and minimum emission level in a year

Usage

calcMACCsCO2()

Value

MAgPIE object

Author(s)

David Klein

Examples

## Not run: 
calcOutput("MACCsCO2")

## End(Not run)

Description

Compute macroeconomic capital investments based on investments shares from the PWT and GDP scenarios from mrdrivers. The final investments are the product of the two.

Usage

calcMacroInvestments()

Value

magpie object with the requested output data either on country or on regional level depending on the choice of argument "aggregate" or a list of information if supplementary is set to TRUE.

See Also

• See the vignette vignette("scenarios", "mrdrivers") for information on the GDP scenarios.

• readPWT() for information on the PWT version used.

Description

This is used in remind2 reporting as input data to calculate additional capacity and secondary energy variables.

Usage

calcOtherFossilInElectricity()

Details

The projection focuses on a tight mitigation scenario and assumes that all fossil emissions from waste burning / other fossil processes can be reduced to 0 by 2050. Should be replaced in the future by actual modeling of waste / other fossil plants, or at least connected to RCP scenario assumptions.

Author(s)

Robert Pietzcker, Falk Benke

Description

Computes Primary Energy variables from IEA Energy Balances

Usage

calcPE(ieaVersion = "default")

Arguments

Description

Reads in the data of the source IIASA_subs_taxes, by country. and calculate taxes at primary energy level. Regional aggregation is done via the respective energy quantities as weights.

Usage

calcPETaxes(subtype = "subsidies")

Arguments

Value

MAgPIE object

Author(s)

Christoph Bertram and Renato Rodrigues

See Also

readIIASA_subs_taxes, convertIIASA_subs_taxes

Examples

## Not run: 
calcOutput("PETaxes")

## End(Not run)

Description

calculates projections for the end of life fate of plastic waste in particular, calculates the share that is incinerated

Usage

calcPlasticsEoL()

Author(s)

Falk Benke, Simón Moreno Leiva

Description

Provides geological storage potential

Usage

calcPotentialGeologicalStorage()

Value

geological storage potential data MAgPIE object

Author(s)

David Klein

Examples

## Not run: 
calcOutput("PotentialGeologicalStorage")

## End(Not run)

Description

Provides geothermal potential data

Usage

calcPotentialGeothermal()

Value

geothermal potential data MAgPIE object

Author(s)

Renato Rodrigues

Examples

## Not run: 
calcOutput("PotentialGeothermal")

## End(Not run)

Description

Provides hydro potential data

Usage

calcPotentialHydro()

Value

hydro potential data and corresponding weights as a list of two MAgPIE objects

Author(s)

Lavinia Baumstark

See Also

readWGBU, convertWGBU

Examples

## Not run: 
calcOutput("PotentialHydro")

## End(Not run)

Description

Provides weathering potential data

Usage

calcPotentialWeathering()

Value

weathering potential data and corresonding weights as a list of two MAgPIE objects

Author(s)

Lavinia Baumstark

Examples

## Not run: 
calcOutput("PotentialWeathering")

## End(Not run)

Description

Provides wind offshore potential data

Usage

calcPotentialWindOff()

Value

wind offshore potential data and corresonding weights as a list of two MAgPIE objects

Author(s)

Chen Chris Gong

See Also

readNREL, convertNREL

Examples

## Not run: 
calcOutput("PotentialWindOff")

## End(Not run)

Description

Provides wind onshore potential data

Usage

calcPotentialWindOn()

Value

wind onshore potential data and corresonding weights as a list of two MAgPIE objects

Author(s)

Lavinia Baumstark

See Also

readNREL, convertNREL

Examples

## Not run: 
calcOutput("PotentialWindOn")

## End(Not run)

Description

Shares of world manufacture for spv modules and wind turbines for 2018 and 2019

Usage

calcProdShares()

Value

magpie object with REMIND-aggregated region

Author(s)

Aman Malik

Description

Calculate the expected near-term deployment of technologies based on projects that are currently either being built or in a planning stage. For some technologies multiple sources are available. Output object currently needs to contain years 2020, 2025 and 2030.

Usage

calcProjectPipelines(subtype)

Arguments

Details

Discussions on sources and assumptions: https://github.com/pik-piam/mrremind/discussions

Author(s)

Pascal Weigmann

Description

calcRatioPPP2MER returns conversion factors from the World Bank's WDI to convert monetary values (in constant units with base year equal to the year argument) from PPP to MER. So for example from 'constant 2017 Int$PPP' to 'constant 2017 US$MER'.

Usage

calcRatioPPP2MER(
  year = as.numeric(mrdrivers::toolGetUnitDollar(returnOnlyBase = TRUE))
)

Arguments

Details

Missing conversion factors are set to 1 and regional aggregation is weighed by GDP from WDI-MI-James.

Value

magpie object with the requested output data either on country or on regional level depending on the choice of argument "aggregate" or a list of information if supplementary is set to TRUE.

See Also

madrat::calcOutput()

Examples

## Not run: 
calcOutput("RatioPPP2MER")

## End(Not run)

Description

This function calculates the renewable energy share targets by aggregating country-level targets to targets of REMIND regions. It calculates the following types of share targets: 1) share of renewables in electricity, 2) share of non-biomass renewables in electricty, 3) share of non-fossil generation in electricity, 4) share of renewables in total final energy. First, targets are aggregated to one of these 4 types. Second, countries without targets are assumed to maintain their renewable share from 2020. Third, targets are harmonized within a REMIND region and filtered based on how many countries within a REMIND region have a target. Finally, energy share targets are aggregated from country-level to REMIND region-level using projections of electricity or final energy demand on country-level. These country-level projections are derived from final energy trends by REMIND regions from the EDGE models as well as GDP trends by country from SSP scenarios (see toolCalcEnergyProj).

Usage

calcRenShareTargets(scenario)

Arguments

Author(s)

Felix Schreyer

Description

prepare secondary production data (e.g. electricity generation) to use in historical constraints in the model

Usage

calcSeProduction()

Value

A magpie object.

Author(s)

Renato Rodrigues

Description

provides region specific target

Usage

calcSharedTarget(subtype)

Arguments

Value

target data magpie object

Author(s)

Renato Rodrigues

Examples

## Not run: 
calcOutput("SharedTarget",subtype="FErenewablesShare")

## End(Not run)

Description

calcSolar calculate Area, Capacity and Energy for photovoltaics (PV) and contentrated solar power (CSP)

Usage

calcSolar()

Value

magpie object

Author(s)

Julian Oeser, modified by Renato Rodrigues

Examples

## Not run: 
a <- calcOutput(type = "Solar")

## End(Not run)

Description

provides capacity factor values

Usage

calcStorageFactor()

Value

magpie object of the capacity factor data

Author(s)

Lavinia Baumstark, Robert Pietzcker

Examples

## Not run: 
calcOutput("StorageFactor")

## End(Not run)

Description

write TC damage parameters into input data they are country-specific and should not be aggregated to the regional level at all

Usage

calcTCdamage(subtype)

Arguments

Value

MAgPIE object of damage parameters for country level tropical cyclone damage function

Author(s)

Franziska Piontek

Description

To calculate the regional Theil-T index (= correction to welfare function for a lognormal income distribution) we do the following: (1) convert country-level Gini coefficients to Theil (2) calculate contribution to Theil-T index that includes both between-countries and within-country inequality (see e.g. https://en.wikipedia.org/wiki/Theil_index). The latter can then be aggregated with calcOutput().

Usage

calcTheil(scenario)

Arguments

Details

The projections are SSP specific and use SSP GINI projections. For non-SSP scenarios, the projections are equal to the SSP2 projection.

The aggregation depends on the region mapping. It is implemented such that the regionmapping specified in getConfig()$regionmapping is used. The result of calcOutput('Theil', aggregate = FALSE), is NOT the country Theil-T, but the unweighted contribution from a given country to the regional value.

Value

magpie objects of unweighted contribution to Theil, weights (= country shares of regional GDP)

See Also

readGini

Description

Computes Trade variables based on latest IEA data available

Usage

calcTrade()

Value

a magclass object

Description

Calculate REMIND final energy variables from historical UBA values

Usage

calcUBA()

Author(s)

Falk Benke

Description

Calculate REMIND emission variables from historical UNFCCC values

Usage

calcUNFCCC()

Value

A magpie object.

Author(s)

Falk Benke, Pascal Weigmann

Description

The output of this function is used in remind2 for reporting purposes.

Usage

calcWasteEnergyUseShares()

Author(s)

Robert Pietzcker, Falk Benke

Description

This function calculates REMIND input data on water consumption coefficients per electricity technology, using as initial information the Macknick (2011) data per electricity technology. The source data provide most required information but some assumptions on missing data are also made.

Usage

calcWaterConsCoef()

Value

MAgPIE object on water consumption coefficients per electricity technology

Author(s)

Ioanna Mouratiadou

See Also

readMacknickIntensities, calcWaterWithCoef

Examples

## Not run: 
calcOutput("WaterConsCoef")

## End(Not run)

Description

This function calculates REMIND input data on water withdrawal coefficients per electricity technology, using as initial information the Macknick (2011) data per electricity technology. The source data provide most required information but some assumptions on missing data are also made.

Usage

calcWaterWithCoef()

Value

MAgPIE object on water withdrawal coefficients per elecricity technology

Author(s)

Ioanna Mouratiadou

See Also

readMacknickIntensities, calcWaterConsCoef

Examples

## Not run: 
calcOutput("WaterWithCoeff")

## End(Not run)

Description

Convert AGEB data

Usage

convertAGEB(x)

Arguments

Author(s)

Falk Benke

Description

convert Ariadne database data

Usage

convertAriadneDB(x)

Arguments

Value

A magpie object.

Author(s)

Felix Schreyer

Description

Converts BGR oil, gas, coal and uranium reserves data

Usage

convertBGR(x, subtype)

Arguments

Value

A MAgPIE object containing BGR (Federal Institute for Geosciences and Natural Resources) country reserves disaggregated data of oil, gas, coal and uranium.

Author(s)

Renato Rodrigues

Examples

## Not run: 
a <- convertBGR(x, subtype = "oil")

## End(Not run)

Description

Provide Biochar price path data

Usage

convertBiocharDeploymentData(x)

Arguments

Author(s)

Tabea Dorndorf

Description

Disaggregates and cleans BP data.

Usage

convertBP(x, subtype)

Arguments

Value

A magpie object.

Author(s)

Aman Malik, Falk Benke

Description

Convert ClimateTrace data

Usage

convertClimateTrace(x)

Arguments

Value

A magpie object.

Author(s)

Pascal Weigmann

Description

Convert Davies (2013) data on on shares of cooling types using mapping from GCAM regions to ISO country level.

Usage

convertDaviesCooling(x)

Arguments

Value

MAgPIE object of the Davies (2013) data disaggregated to country level

Author(s)

Lavinia Baumstark, Ioanna Mouratiadou

See Also

readDaviesCooling

Examples

## Not run:  a <- convertDaviesCooling(x)

Description

Converts Dylan's Australian gas cost to magpie

Usage

convertDylanAusGasCost(x)

Arguments

Value

magpie object of the CEMO data

Author(s)

Felix Schreyer

Description

convertEDGAR7Fgases

Usage

convertEDGAR7Fgases(x)

Arguments

Author(s)

Gabriel Abrahao

Description

Convert EDGE Buildings data to data on ISO country level.

Usage

convertEdgeBuildings(x, subtype, subset)

Arguments

Value

EDGE data as MAgPIE object aggregated to country level

Author(s)

Antoine Levesque, Robin Hasse

Description

Convert EDGEtransport

Usage

convertEDGETransport(x, subtype)

Arguments

Value

REMIND/iterative EDGE-T input data as MAgPIE object disaggregated to ISO level

Author(s)

Johanna Hoppe

Description

Convert Ember data

Usage

convertEmber(x)

Arguments

Value

A magpie object.

Author(s)

Pascal Weigmann

Description

Convert European Energy Datasheets

Usage

convertEuropeanEnergyDatasheets(x, subtype)

Arguments

Value

converted European Energy Datasheets magpie object

Author(s)

Renato Rodrigues and Atreya Shankar

Source

European Energy Datasheets public database https://energy.ec.europa.eu/data-and-analysis/eu-energy-statistical-pocketbook-and-country-datasheets_en

Examples

## Not run: 
test <- readSource("EuropeanEnergyDatasheets", subtype = "EU27", convert = TRUE)

## End(Not run)

Description

Converts EU Effort Sharing targets and historical emissions

Usage

convertEurostat_EffortSharing(x, subtype)

Arguments

Value

A MAgPIE object containing the EU Effort Sharing targets (%) or Effort Sharing historical emissions (MtCO2)

Author(s)

Renato Rodrigues

Examples

## Not run:  a <- convertEurostat_EffortSharing(x,subtype="target")

Description

Converts Eurostat renewable energy share data

Usage

convertEurostat_REShare(x, subtype)

Arguments

Value

A MAgPIE object containing Eurostat renewable energy shares

Author(s)

Felix Schreyer

Description

Converts data from expert guess

Usage

convertExpertGuess(x, subtype)

Arguments

Author(s)

Falk Benke

Description

Converts oil, gas and coal data from the Global Energy Assessment 2012 to country-level aggregation

Usage

convertGEA2012(x, subtype)

Arguments

Value

MAgPIE object containing country-level disaggregation of GEA 2012 data

Author(s)

Stephen Bi

Examples

## Not run: 
a <- readSource("GEA2012")

## End(Not run)

Description

Convert GGDC 10-Sector Database - https://www.rug.nl/ggdc/structuralchange/previous-sector-database/10-sector-2014

Usage

convertGGDC10(x)

Arguments

Value

A MAgPIE object containing GGDC disaggregated data

Author(s)

Renato Rodrigues

Examples

## Not run: 
a <- convertGGDC10(x)

## End(Not run)

Description

Convert geological storage potential

Usage

convertGidden2025_geological_storage_potential(x)

Arguments

Value

A magpie object with geological storage potential

Author(s)

David Klein

Description

Convert Global CCS Institute Project Database

Usage

convertGlobalCCSinstitute(x, subtype = "08-09-2017")

Arguments

Value

A magpie object.

Description

Convert Global Energy Monitor data

Usage

convertGlobalEnergyMonitor(x)

Arguments

Author(s)

Rahel Mandaroux, Falk Benke

Description

Convert HRE data

Usage

convertHRE(x)

Arguments

Value

A magpie object.

Author(s)

Pascal Weigmann

Description

Data on currently operating and under-construction nuclear power plants, reactors planned and proposed, electricity generation from nuclear

Usage

convertIAEA(x)

Arguments

Author(s)

Christoph Bertram

Description

convert IAEA Power Reactor Information System

Usage

convertIAEA_PRIS(x)

Arguments

Author(s)

Pascal Weigmann

Description

Convert IEA CCUS data

Usage

convertIEA_CCUS(x)

Arguments

Value

A magclass object.

Author(s)

Anne Merfort, Falk Benke

Description

Convert IEA ETP projections

Usage

convertIEA_ETP(x, subtype)

Arguments

Author(s)

Falk Benke, Robin Hasse

Description

Convert IEA EV Outlook

Usage

convertIEA_EVOutlook(x)

Arguments

Author(s)

Falk Benke

Description

convert IEA Hydro Special Market Report

Usage

convertIEA_HSMR(x)

Arguments

Author(s)

Pascal Weigmann

Description

maps to iso countries

Usage

convertIEA_PVPS(x)

Arguments

Value

Magpie object with IEA PVPS investment cost per country

Author(s)

Felix Schreyer

Description

Reads the distributed solar pv capacity from IEA Renewables report (2019).

Usage

convertIEA_REN(x)

Arguments

Details

Capacity in GW. Distributed solar, defined in the IEA Renewables (2019), includes rooftop residential (0-10 kW, grid-connected), rooftop and ground-mounted commercial and industrial (10-1000kW, grid-connected), and off-grid (8W - 100 kW)

Value

magpie object with country-wise distributed solar pv capacity

Author(s)

Aman Malik

Description

Converts IEA World Energy Outlook data

Usage

convertIEA_WEO(x, subtype)

Arguments

Author(s)

Renato Rodrigues and Aman Malik

Description

Convert IEA World Energy Outlook Data from 2023

Usage

convertIEA_WorldEnergyOutlook(x)

Arguments

Author(s)

Falk Benke

Description

Convert IIASA subsidy and taxes data on ISO country level (removes countries not part of 249 oficial ISO countries and fills missing with zeros).

Usage

convertIIASA_subs_taxes(x, subtype)

Arguments

Value

IIASA_subs_taxes data as MAgPIE object aggregated to country level

Examples

## Not run: 
a <- convertIIASA_subs_taxes(x)

## End(Not run)

Description

convert IIASA Land Use Emissions

Usage

convertIIASALanduse(x, subtype)

Arguments

Author(s)

Falk Benke

Description

Disaggregates IMAGE 2025 F-gas emissions data, using EDGAR HFC emissions in 2005 as weights

Usage

convertIMAGE2025(x)

Arguments

Value

magpie object

Author(s)

Gabriel Abrahao

Description

Converts IRENA Regional data

Usage

convertIRENA(x, subtype)

Arguments

Value

A MAgPIE object containing IRENA country disaggregated data with historical electricity renewable capacities (MW) or generation levels (GWh)

Author(s)

Renato Rodrigues, Pascal Weigmann

Examples

## Not run: 
a <- convertIRENA(x, subtype = "Capacity")

## End(Not run)

Description

convert KLW damage fills in countries for which no damage parameters are provided, setting parameters to zero

Usage

convertKLWdamage(x)

Arguments

Value

MAgPIE object containing values for all 249 ISO countries

Author(s)

Franziska Piontek

Description

Convert Exclusive Economic Zone (EEZ) size data

Usage

convertMarineRegionsOrg(x)

Arguments

Author(s)

Tabea Dorndorf

Description

Converts conditional and unconditional capacity and production targets into total capacity (GW) in target year. For countries and years without targets, 2020 values from IRENA and BP are used to fill the gaps.

Usage

convertNewClimate(x, subtype, subset)

Arguments

Details

Emissions targets on absolute level for total GHG emissions without bunkers and land-use change emissions are calculated from country-specific target formulation and land-use change emissions data

Author(s)

Rahel Mandaroux, Léa Hayez, Falk Benke

See Also

readIRENA()

Description

Convert NREL data on ISO country level.

Usage

convertNREL(x)

Arguments

Value

NRELWirsenius data as MAgPIE object aggregated to country level

Author(s)

Lavinia Baumstark

Examples

## Not run: 
a <- convertNREL(x, subtype = "onshore")

## End(Not run)

Description

Converts Openmod capacities data

Usage

convertOpenmod(x)

Arguments

Value

A MAgPIE object containing openmod EU country disaggregated data with 2010 and 2015 electricity capacities (GW)

Author(s)

Renato Rodrigues

Examples

## Not run: 
a <- convertOpenmod(x)

## End(Not run)

Description

Disaggregates PBL emission factors from the 26 IMAGE regions to ISO3 country level. As these are emission factors, weights are constant, assuming all countries in a region emit the same amount of each gas per unit of activity.

Usage

convertPBL_EFsBaseline(x)

Arguments

Value

A magpie object.

Description

Reads shares of world manufacture for spv modules and wind turbines.

Usage

convertProdShares(x)

Arguments

Value

magpie object with shares

Author(s)

Aman Malik

Description

Converts REMIND 11 Regi data

Usage

convertREMIND_11Regi(x, subtype)

Arguments

Author(s)

unknown

Description

This code aggregates and homogenises different types of renewable energy targets into total installed capacity targets (in GW).

Usage

convertREN21(x, subtype)

Arguments

Details

Policy database accessible in "inputdata/sources/REN21/README"

Value

Magpie object with Total Installed Capacity targets. The target years differ depending upon the database.

Author(s)

Aman Malik

Description

Converts data on enhanced weathering

Usage

convertStrefler(x, subtype)

Arguments

Value

magpie object with a completed dataset

Description

Convert TCdamage fills in countries not affected by tropical cyclones (TC), setting parameters to zero

Usage

convertTCdamageKrichene(x)

Arguments

Value

MAgPIE object containing values for all 249 ISO countries

Author(s)

Franziska Piontek

Description

Convert UBA data

Usage

convertUBA(x)

Arguments

Author(s)

Falk Benke

Description

Convert UNFCCC data

Usage

convertUNFCCC(x)

Arguments

Value

A magpie object.

Author(s)

Falk Benke

Description

Converts conditional and unconditional capacity and production targets into total capacity (GW) in target year. For countries and years without targets, 2015 values from IRENA and BP are used to fill the gaps.

Usage

convertUNFCCC_NDC(x, subtype, subset = NULL)

Arguments

Details

NDC Emissions targets on absolute level for total GHG emissions without bunkers and land-use change emissions are calculated from country-specific target formulation and land-use change emissions data

Author(s)

Aman Malik, Christoph Bertram, Oliver Richters, Sophie Fuchs, Rahel Mandaroux, Falk Benke

See Also

readIRENA()

Description

Convert WGBU data on ISO country level.

Usage

convertWGBU(x)

Arguments

Value

WGBU data as MAgPIE object aggregated to country level

Author(s)

Lavinia Baumstark

Examples

## Not run: 
a <- convertWGBU(x)

## End(Not run)

Description

Function that produces the complete regional data set required for the REMIND model.

Usage

fullREMIND()

Author(s)

Lavinia Baumstark

See Also

readSource, getCalculations, calcOutput

Examples

## Not run: 
fullREMIND()

## End(Not run)

Description

assemble near-term thresholds from project pipelines and potentially other data sources and export them to a file

Usage

fullTHRESHOLDS(type = "config")

Arguments

Author(s)

Pascal Weigmann

Description

Function that generates the historical regional dataset against which the REMIND model results can be compared.

Usage

fullVALIDATIONREMIND(rev = 0)

Arguments

Author(s)

David Klein, Falk Benke

See Also

readSource, getCalculations, calcOutput

Examples

## Not run: 
fullVALIDATIONREMIND()

## End(Not run)

Description

Read AGEB

Usage

readAGEB(subtype = "balances")

Arguments

Author(s)

Falk Benke

Description

Read GWP (or other metrics) from the AR6 WGIII Table SM7 per GHG species

Usage

readAR6GWP(subtype = "GWP100")

Arguments

Value

A data.frame with two columns, "Gas", with the common name of the GHG species, and "GWP", with the selected GWP

Author(s)

Gabriel Abrahao

Description

This reads in FORECAST industry production data for Germany used in the Ariadne scenarios

Usage

readAriadneDB()

Value

A magpie object.

Author(s)

Felix Schreyer

Description

Read-in BGR csv files as magclass object

Usage

readBGR(subtype)

Arguments

Value

magpie object of the BGR (Federal Institute for Geosciences and Natural Resources) data of reserves of oil, gas, coal and uranium per country.

Author(s)

Renato Rodrigues

Examples

## Not run: 
a <- readSource(type = "BGR", subtype = "oil")

## End(Not run)

Description

Source: Assumption for REMIND based on data collected in Dorndorf et al (submitted)

Usage

readBiocharDeploymentData()

Author(s)

Tabea Dorndorf

Description

BP Capacity and Generation Data

Usage

readBP(subtype)

Arguments

Value

A magpie object.

Author(s)

Aman Malik, Falk Benke

Description

Read Employment factors and cumulative jobs for RE techs (for India)

Usage

readCEEW(subtype)

Arguments

Details

Reports published by CEEW et al. See README.txt in the source folder for more information.

Author(s)

Aman Malik

Examples

## Not run: 
a <- readSource("CEEW",convert=F,subtype="Employment")

## End(Not run)

Description

Read in Climate Trace csv files as magclass object for CO2, CH4 and N2O emissions by subsector and country.

Usage

readClimateTrace()

Value

magpie object of the ClimateTrace data with historical emissions

Author(s)

Pascal Weigmann

Examples

## Not run: 
a <- readSource(type = "ClimateTrace")

## End(Not run)

Description

Read in Davies (2013) data on shares of cooling types per electricity technology and GCAM region

Usage

readDaviesCooling(subtype)

Arguments

Value

MAgPIE object of the Davies (2013) data

Author(s)

Lavinia Baumstark, Ioanna Mouratiadou

Examples

## Not run: 
a <- readSource(type = "DaviesCooling")

## End(Not run)

Description

read-in power Australian gas extraction cost curve based on Dylan's data Australian contact: Dylan McConnell, dylan.mcconnell(at)unimelb.edu.au

Usage

readDylanAusGasCost()

Value

magpie object of the cemo database data

Author(s)

Felix Schreyer

Description

Read EDGAR7 emissions data for F-gases per species, in kt of each gas

Usage

readEDGAR7Fgases()

Value

A magpie object with F-gases emissions per gas species and per country

Author(s)

Gabriel Abrahao

Description

Load an EDGE Buildings file as magclass object.

Usage

readEdgeBuildings(subtype = c("FE", "Floorspace"), subset)

Arguments

Value

magclass object

Author(s)

Antoine Levesque, Robin Hasse

Description

Run EDGE-Transport Standalone in all used scenario combinations to supply input data to REMIND and the iterative EDGE-T script

Usage

readEDGETransport(subtype)

Arguments

Value

magpie object of EDGEtransport iterative inputs

Author(s)

Johanna Hoppe, Alex K. Hagen

Examples

## Not run: 
a <- readSource(type = "EDGETransport")

## End(Not run)

Description

Read Ember Yearly Electricity Data

Usage

readEmber()

Value

A magpie object.

Author(s)

Pascal Weigmann

Source

https://ember-climate.org/data-catalogue/yearly-electricity-data/

Description

Read European Energy Datasheets .xlsx file as magpie object.

Usage

readEuropeanEnergyDatasheets(subtype)

Arguments

Value

magpie object of European Energy Datasheets

Author(s)

Renato Rodrigues, Atreya Shankar, Falk Benke

Source

European Energy Datasheets public database https://energy.ec.europa.eu/data-and-analysis/eu-energy-statistical-pocketbook-and-country-datasheets_en

Examples

## Not run: 
test <- readSource("EuropeanEnergyDatasheet", subtype = "EU27", convert = FALSE)

## End(Not run)

Description

Read-in EU Effort Sharing targets and historical emissions csv files as magclass object

Usage

readEurostat_EffortSharing(subtype)

Arguments

Value

magpie object of the EU Effort Sharing targets (%) or Effort Sharing historical historical emissions (MtCO2)

Author(s)

Renato Rodrigues

Examples

## Not run: 
a <- readSource(type = "Eurostat_EffortSharing", subtype = "target")

## End(Not run)

Description

Read Eurostat Historical Renewable FE Share Data as magclass object

Usage

readEurostat_REShare(subtype)

Value

magpie object of Eurostat Historical Renewable FE Share Data (share)

Author(s)

Felix Schreyer

Description

Read-in data that are based on expert guess

Usage

readExpertGuess(subtype)

Arguments

Value

magpie object of the data

Author(s)

Lavinia Baumstark, Falk Benke

Examples

## Not run: 
a <- readSource(type = "ExpertGuess", subtype = "ies")

## End(Not run)

Description

There's no associated convert function, as the disaggregation takes a combination of subtypes, and it is easier to carry out most calculations at the GAINS regional level first and then disaggregate the results

Usage

readGAINS2025final(subtype)

Arguments

Value

Activity levels, emissions or emission factors at the level of 25 GAINS regions, 35 GAINS sectors and 7 species: magclass object with dimensions region, year, and ssp.scenario.sectorGAINS.species

Author(s)

Gabriel Abrahao, Laurin Koehler-Schindler

Description

Historical data of operating, under-construction, planned and announced Coal Plants by country (in MW) from the Global Energy Monitor's Global Coal Plant Tracker, and extrapolations for 2025 capacity scenarios

Usage

readGCPT(subtype)

Arguments

Author(s)

Stephen Bi

Description

Read in datafiles comprising fossil fuel data from the Global Energy Assessment 2012

Usage

readGEA2012(subtype)

Arguments

Value

MAgPIE object of the GEA data

Author(s)

Stephen Bi

Examples

## Not run: 
a <- readSource("GEA2012", "coal")

## End(Not run)

Description

Read GGDC 10-Sector Database - https://www.rug.nl/ggdc/structuralchange/previous-sector-database/10-sector-2014

Usage

readGGDC10()

Author(s)

Renato Rodrigues

Examples

## Not run: 
a <- readSource("GGDC10",convert=F)

## End(Not run)

Description

Read geological storage potential

Usage

readGidden2025_geological_storage_potential()

Value

A magpie object with geological storage potential. Off = offshore; On = onshore; potTech = technical potential without any exclusion layers applied; potLim = applying all exclusion layers described in Table S1 (e.g. protected areas, population centers, max and min depth, etc.)

Author(s)

David Klein

Description

Read Gini coefficients for SSP scenarios from Rao et al., Futures, 2018. Data has been provided by the authors, but will be made publicly available as well. This contains data for 184 countries and from 2011 onwards.

Usage

readGini()

convertGini(x)

Arguments

Details

Copied from the documentation provided by the authors: This sheet contains the original Gini projections for 43 countries from the underlying empirical model (See reference to RSP 2016 in the main paper) and the extrapolations to all countries using the methodology described in the article. The country codes are the World Bank codes.

Value

magpie object of the Gini data

Author(s)

Bjoern Soergel

Examples

## Not run: 
a <- readSource(type="Gini")

## End(Not run)

Description

Read Global CCS Institute Project Database

Usage

readGlobalCCSinstitute(subtype = "08-09-2017")

Arguments

Value

a magpie object

Description

read GEM data for all available technologies and relevant statuses

Usage

readGlobalEnergyMonitor()

Author(s)

Rahel Mandaroux, Falk Benke, Pascal Weigmann

Description

Read Heat Roadmap Europe data

Usage

readHRE()

Value

A magpie object.

Author(s)

Pascal Weigmann

Source

https://heatroadmap.eu/roadmaps/

Description

Data on currently operating and under-construction nuclear power plants, reactors planned and proposed, electricity generation from nuclear

Usage

readIAEA()

Author(s)

Christoph Bertram, Pascal Weigmann

Description

read Nuclear capacities and near-term outlook from data scraped from https://pris.iaea.org/PRIS/CountryStatistics/CountryStatisticsLandingPage.aspx

Usage

readIAEA_PRIS()

Author(s)

Pascal Weigmann

Description

Reads in capacities from projects in IEA CCUS database

Usage

readIEA_CCUS(subtype)

Arguments

Author(s)

Anne Merfort, Falk Benke

Description

Read IEA ETP projections

Usage

readIEA_ETP(subtype)

Arguments

Author(s)

Falk Benke

Description

Read IEA EV Outlook

Usage

readIEA_EVOutlook()

Author(s)

Falk Benke

Description

read Hydro capacities and near-term outlook from data scraped from https://www.iea.org/data-and-statistics/data-tools/hydropower-data-explorer

Usage

readIEA_HSMR()

Author(s)

Pascal Weigmann

Description

reads excel sheet with PV investment cost data

Usage

readIEA_PVPS()

Value

magpie object with PV investment cost data

Author(s)

Felix Schreyer

Description

Reads the distributed solar pv capacity from IEA Renewables report (2019).

Usage

readIEA_REN()

Details

Capacity in GW. Distributed solar, defined in the IEA Renewables (2019), includes rooftop residential (0-10 kW, grid-connected), tooftop and ground-mounted commercial and industrial (10-1000kW, grid-connected), and off-grid (8W - 100 kW)

Author(s)

Aman Malik

Description

Read 2015-2024 investments statistical data in energy sector (electricity, oil, gas) IEA World Energy Investment Outlook (2024) (https://www.iea.org/data-and-statistics/data-product/world-energy-investment-2024-datafile)

Usage

readIEA_WEIO()

Author(s)

Nicolas Bauer, Falk Benke

Description

Read-in IEA WEO 2016 data for investment costs of different technologies, and WEO 2017 data for historical electricity capacities (GW)

Usage

readIEA_WEO(subtype)

Arguments

Author(s)

Renato Rodrigues, Aman Malik, and Jerome Hilaire

Description

Read in IEA World Energy Outlook Data from 2023

Usage

readIEA_WorldEnergyOutlook()

Author(s)

Falk Benke

Description

Read-in country level data on final energy taxes and subsidies as provided from IIASA from .csv file as magclass object

Usage

readIIASA_subs_taxes(subtype)

Arguments

Value

magpie object of the IIASA_subs_taxes data

Author(s)

Christoph Bertram

Examples

## Not run: 
a <- readSource(type = "IIASA_subs_taxes", "tax_rate")

## End(Not run)

Description

read IIASA Land Use Emissions

Usage

readIIASALanduse(subtype)

Arguments

Author(s)

Falk Benke

Description

Read F-gases emissions data from several IMAGE scenarios, obtained in 2025

Usage

readIMAGE2025()

Value

magpie object with several F-gas emission variables for several IMAGE scenarios

Author(s)

Gabriel Abrahao

Description

Read-in an IRENA xlsx file as magclass object

Usage

readIRENA(subtype)

Arguments

Value

magpie object of the IRENA data with historical electricity renewable capacities (MW) or generation levels (GWh)

Author(s)

Renato Rodrigues, Pascal Weigmann

Examples

## Not run: 
a <- readSource(type = "IRENA", subtype = "Capacity")

## End(Not run)

Description

Reads country-specific damage coefficients for the damage function presented in Kotz et al. (2024). Data has been provided by the authors. This contains data for all countries and for 1000 boostrapping realizations per country, capturing uncertainty from climate and empirical modeling. Subtypes are the temperature and temperature^2 coefficients and the maximum temperature per country for which the function is defined.

Usage

readKLWdamage(subtype)

Arguments

Value

KLW damage coefficients

Author(s)

Franziska Piontek

Description

Read in Macknick (2011) data on water consumption and withdrawal coefficients per electricity technology

Usage

readMacknickIntensities(subtype)

Arguments

Value

MAgPIE object of the Macknick (2011) data

Author(s)

Ioanna Mouratiadou

Examples

## Not run: 
a <- readSource(type = "MacknickIntensities", convert = FALSE)

## End(Not run)

Description

Source: Flanders Marine Institute (2023). Maritime Boundaries Geodatabase: Maritime Boundaries and Exclusive Economic' Zones (200NM), version 12. Available online at https://www.marineregions.org/. https://doi.org/10.14284/632

Usage

readMarineRegionsOrg()

Author(s)

Tabea Dorndorf

Description

Reads excel sheet with NPi (National Policies Implemented) data on different policy targets (capacity, production, emissions) with different variations. NPI targets only include targets that are based on implemented policy instruments.

Usage

readNewClimate(subtype, subset)

Arguments

Author(s)

Rahel Mandaroux, Léa Hayez, Falk Benke

Description

Read-in NREL xlsx file as magclass object

Usage

readNREL(subtype)

Arguments

Value

magpie object of NREL

Author(s)

Lavinia Baumstark

Examples

## Not run: 
a <- readSource(type = "NREL", subtype = "onshore")

## End(Not run)

Description

Read-in risk premium

Usage

readOECD()

convertOECD(x)

Arguments

Value

The read-in data, usually a magpie object. If supplementary is TRUE a list including the data and metadata is returned instead. The temporal and data dimensionality should match the source data. The spatial dimension should either match the source data or, if the convert argument is set to TRUE, should be on ISO code country level.

See Also

madrat::readSource()

Examples

## Not run: 
readSource("OECD")

## End(Not run)

Description

Read-in an modified openmod capacities data file as magclass object

Usage

readOpenmod()

Value

magpie object of the LIMES team updated Openmod data on capacities (GW)

Examples

## Not run: 
a <- readSource(type = "Openmod")

## End(Not run)

Description

Read emission factors from a PBL IMAGE baseline (no mitigation) scenario for a specific sector and gas species (CH4 or N2O)

Usage

readPBL_EFsBaseline(subtype)

Arguments

Value

A magpie object.

Description

Reads shares of world manufacture for spv modules and wind turbines.

Usage

readProdShares()

Author(s)

Aman Malik

Description

Read-in PWT data (version 8.0) as magclass object

Usage

readPWT()

convertPWT(x)

Arguments

Value

The read-in data, usually a magpie object. If supplementary is TRUE a list including the data and metadata is returned instead. The temporal and data dimensionality should match the source data. The spatial dimension should either match the source data or, if the convert argument is set to TRUE, should be on ISO code country level.

See Also

madrat::readSource()

Examples

## Not run: 
readSource("PWT")

## End(Not run)

Description

Read REMIND 11 Regi data

Usage

readREMIND_11Regi(subtype)

Arguments

Author(s)

unknown

Description

Reads excel sheet with data on proposed policies, on Renewable energy capacity targets (which are broken down into Total Installed Capacity (TIC-Absolute), Additional Installed Capacity (AC-Absolute), and Production Absolute targets) or regional technology costs

Usage

readREN21(subtype)

Arguments

Details

Country name is ISO coded. Capacity/Additional Capacity targets are in GW. Generation/Production targets are in GWh.

Value

magpie object with Total Installed Capacity targets in GW for different target years

Author(s)

Aman Malik, Lavinia Baumstark

Description

Get data on enhanced weathering

Usage

readStrefler(subtype)

Arguments

Value

magpie object of region dependent data

Examples

## Not run: 
a <- readSource(type="Strefler", subtype="weathering_graderegi")

## End(Not run)

Description

Reads country-specific damage coefficients for tropical cyclones from Krichene et al. (in prep.). Data has been provided by the authors, but will be made publicly available as well. This contains data for 41 countries (those exposed to tropical cyclones), and two coefficients (constant and linear temperature)

Usage

readTCdamageKrichene(subtype)

Arguments

Value

TC damage coefficients

Author(s)

Franziska Piontek

Description

Read UBA

Usage

readUBA()

Author(s)

Falk Benke

Description

Read UNFCCC data

Usage

readUNFCCC()

Author(s)

Falk Benke

Description

Reads excel sheet with NDC (Nationally Determined Contributions) data on different policy targets (capacity, production, emissions) with different variations.

Usage

readUNFCCC_NDC(subtype, subset)

Arguments

Author(s)

Aman Malik, Christoph Bertram, Oliver Richters, Sophie Fuchs, Rahel Mandaroux, Falk Benke

Description

Read-in an WGBU xlsx file as magclass object

Usage

readWGBU()

Value

magpie object of WGBU

Author(s)

Lavinia Baumstark

Examples

## Not run: 
a <- readSource(type = "WGBU")

## End(Not run)

Description

Wrapper around magclass::add_dimension supporting more than one value for the new dimension. For each value, the input magclass object is copied, extended by the new dimension and appended to the output.

Usage

toolAddDimensions(x, dimVals, dimName, dimCode)

Arguments

Value

the extended magclass object

Description

Aggregate regional data, but if regional aggregations exist, discard the automatically aggregated values and replace them with source data.

Usage

toolAggregateCustomRegs(
  x,
  agg,
  rel,
  to = NULL,
  removeAllAgg = TRUE,
  regs = "GLO"
)

Arguments

Value

magclass object

Author(s)

Falk Benke, Pascal Weigmann

Description

Aggregate values to n-year averages to suppress volatility

Usage

toolAggregateTimeSteps(x, nYears = 5)

Arguments

Value

magclass object with averages

Author(s)

Robin Hasse

Description

toolBiomassSupplyAggregate The function aggregates biomass supply curves to regionmapping different from H12. It only works if all regions are subregions of H12 regions. The offset parameter (a) is taken from the H12 region. The slope parameter (b) is multiplied by a weight. The weight is the inverse of the share of agricultural area of the subregion in the H12 region.

Usage

toolBiomassSupplyAggregate(
  x,
  rel = NULL,
  weight = calcOutput("FAOLand", aggregate = FALSE)[, , "6610", pmatch = TRUE][, "y2010",
    ]
)

Arguments

Value

return: returns region aggregated biomass supply curve data

Author(s)

Felix Schreyer

Description

Calculate energy projections on country-level based on EDGE models outputs per country. These energy projections are used in the input data preparation for aggregating country-specific data to REMIND regions. They are a country-level proxy of the final energy demand trajectories on the level of REMIND regions provided by the EDGE models.

Usage

toolCalcEnergyProj(subtype, subset, scenario, years = seq(2020, 2050, 5))

Arguments

Author(s)

Felix Schreyer

See Also

convertNewClimate()

Description

Calculate absolute emission targets depending on country-specific emissions target formulations. So far, the function mainly used to calculate NDC emissions targets.

Usage

toolCalcGhgTarget(x, subtype, subset)

Arguments

Author(s)

Rahel Mandaroux, Felix Schreyer, Falk Benke

See Also

convertUNFCCC_NDC(), convertNewClimate()

Description

Estimates the function that represents the sum of cubic function inverses (sum in the x-axis)

Usage

toolCubicFunctionAggregate(
  x,
  rel = NULL,
  xLowerBound = 0,
  xUpperBound = 100,
  returnMagpie = TRUE,
  returnCoeff = TRUE,
  returnChart = FALSE,
  returnSample = FALSE,
  numberOfSamples = 1000,
  unirootLowerBound = -10,
  unirootUpperBound = 1e+100,
  colourPallete = FALSE,
  label = list(x = "x", y = "y", legend = "legend"),
  steepCurve = list()
)

Arguments

Details

Use case: aggregate country cubic cost functions to a single function that represents the entire region.

input: coefficients of the n-th country level cubic cost function.

Description of the problem: the aggregation of functions that represent unit costs, or prices in the y-axis, and quantities in the x-axis require operations with the inverse of the original functions. As complex functions present analytically challenging inverse function derivations, we adopt a sampling method to derive the function that corresponds to the sum of cubic function inverses.

Further extensions: the R function can be extended to support more complex curve estimations (beyonf third degree), whenever the mathematical function have a well defined inverse function in the selected boundaries.

Value

return: returns a list of magpie objects containing the coefficients for the aggregate function. If returnMagpie is FALSE, returns a list containing the coefficients for the aggregate function (returnCoeff=TRUE), charts (returnChart=FALSE) and/or samples used in the estimation (returnSample=FALSE).

Author(s)

Renato Rodrigues

See Also

toolCubicFunctionDisaggregate

Examples

# Example
# data
EUR <- setNames(data.frame(30, 50, 0.123432, 2), c("c1", "c2", "c3", "c4"))
NEU <- setNames(data.frame(30, 50, 1.650330, 2), c("c1", "c2", "c3", "c4"))
df <- rbind(EUR, NEU)
row.names(df) <- c("EUR", "NEU")
# maxExtraction (upper limit for function estimation)
maxExtraction <- 23
# output
output <- toolCubicFunctionAggregate(df,
  xUpperBound = maxExtraction,
  returnMagpie = FALSE, returnChart = TRUE, returnSample = TRUE,
  label = list(x = "Cumulated Extraction", y = "Cost", legend = "Region Fuel Functions")
)
output$coeff
output$chart

Description

Estimates cubic function inverses based on a weight factor that sum up to the original cubic function (sum in the x-axis)

Usage

toolCubicFunctionDisaggregate(
  x,
  weight,
  rel = NULL,
  xLowerBound = 0,
  xUpperBound = 100,
  returnMagpie = TRUE,
  returnCoeff = TRUE,
  returnChart = FALSE,
  returnSample = FALSE,
  numberOfSamples = 1000,
  unirootLowerBound = -10,
  unirootUpperBound = 1e+100,
  colourPallete = FALSE,
  label = list(x = "x", y = "y", legend = "legend")
)

Arguments

Details

Use case: disaggregate a single region cubic cost function to multiple country cubic functions weighted by a contribution factor. The sum of the countries function output is equal to the original regional function.

input: coefficients of the n-th country level cubic cost function.

Description of the problem: the disaggregation of functions that represent unit costs (or prices) in the y-axis and quantities in the x-axis require operations with the inverse of the original functions. As complex functions present analytically challenging inverse function derivations, we adopt a sampling method to derive the function that corresponds to the sum of cubic function inverses.

Further extensions: the R function can be extended to support more complex curve estimations (beyond third degree), whenever the mathematical function have a well defined inverse function in the selected boundaries.

Value

return: returns a list of magpie objects containing the coefficients for the aggregate function. If returnMagpie is FALSE, returns a list containing the coefficients for the aggregate function (returnCoeff=TRUE), charts (returnChart=FALSE) and/or samples used in the estimation (returnSample=FALSE).

Author(s)

Renato Rodrigues

See Also

toolCubicFunctionAggregate

Examples

# Example
# LAM coefficients
df <- setNames(data.frame(30, 50, 0.34369, 2), c("c1", "c2", "c3", "c4"))
row.names(df) <- "LAM"
# weight
weight <- setNames(c(21, 0, 579, 3, 228), c("ARG", "BOL", "BRA", "CHL", "COL"))
# maxExtraction (upper limit for function estimation)
maxExtraction <- 100
# output
output <- toolCubicFunctionDisaggregate(df, weight,
  xUpperBound = maxExtraction,
  returnMagpie = FALSE, returnChart = TRUE, returnSample = TRUE,
  label = list(x = "Cumulated Extraction", y = "Cost", legend = "Region Fuel Functions")
) #' output$chart
output$coeff
output$chart

Description

Sets values for 6 EU countries not belonging to EU 28 but EU 34 to zero if they are NA. Used to avoid EUR region yielding NA because of these countries.

Usage

toolFillEU34Countries(x)

Arguments

Author(s)

Falk Benke

Description

Does not do anything for slices where all timesteps are NA

Usage

toolFillYearsWithClosest(inx)

Arguments

Value

the magclass object with some of those NAs filled

Description

Returns the year associated with a given ieaVersion

Usage

toolGetIEAYear(ieaVersion)

Arguments

Author(s)

Falk Benke

Description

Helper to validate data read in from UNFCCC NDC and New Climate databases and apply some pre-processing

Usage

toolProcessClimateTargetDatabase(input, database, subtype)

Arguments

See Also

readUNFCCC_NDC(), readNewClimate()

Description

Aggregate Solar data into regions

Usage

toolSolarFunctionAggregate(
  x,
  rel = NULL,
  weight = calcOutput("FE", aggregate = FALSE)[, "y2015", "FE|Electricity (EJ/yr)"]
)

Arguments

Value

return: returns region aggregated solar data

Author(s)

Felix Schreyer, Renato Rodrigues, Julian Oeser