Validation mif

.buildlibrary

@@ -1,10 +1,12 @@
-ValidationKey: '22955016'
+ValidationKey: '23132480'
 AutocreateReadme: yes
 AutocreateCITATION: yes
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'
 - 'Warning: namespace ''.*'' is not available and has been replaced'
-AcceptedNotes: madrat:::getSourceFolder
+AcceptedNotes:
+- madrat:::getSourceFolder
+- .* includes the non-default packages.*
 allowLinterWarnings: yes
 enforceVersionUpdate: yes
 skipCoverage: yes

CITATION.cff

@@ -2,8 +2,8 @@ cff-version: 1.2.0
 message: If you use this software, please cite it using the metadata from this file.
 type: software
 title: 'mrmfa: Input data generation for the REMIND MFA'
-version: 1.11.2
-date-released: '2026-07-09'
+version: 1.12.0
+date-released: '2026-07-20'
 abstract: The mrmfa packages contains data preprocessing for the REMIND MFA.
 authors:
 - family-names: Dürrwächter

DESCRIPTION

@@ -1,8 +1,8 @@
 Type: Package
 Package: mrmfa
 Title: Input data generation for the REMIND MFA
-Version: 1.11.2
-Date: 2026-07-09
+Version: 1.12.0
+Date: 2026-07-20
 Authors@R: c(
     person("Jakob", "Dürrwächter", , "jakobdu@pik-potsdam.de", role = c("aut", "cre")),
     person("Bennet", "Weiss", , "bennet.weiss@pik-potsdam.de", role = "aut"),
@@ -20,6 +20,7 @@ Depends:
     magclass (>= 6.16.1),
     mrdrivers (>= 4.0.0),
     mrcommonsenergy (>= 0.3.4),
+    mrindustry (>= 1.2.1),
     GDPuc (>= 1.3.0),
 Imports:
     glue,
@@ -30,6 +31,7 @@ Imports:
     magrittr,
     purrr,
     quitte,
+    R.matlab,
     readr,
     readxl,
     rlang,

NAMESPACE

@@ -7,6 +7,7 @@ import(madrat)
 import(magclass)
 import(mrcommonsenergy)
 import(mrdrivers)
+import(mrindustry)
 importFrom(data.table,first)
 importFrom(dplyr,across)
 importFrom(dplyr,all_of)
@@ -24,7 +25,18 @@ importFrom(dplyr,summarise)
 importFrom(dplyr,summarize)
 importFrom(dplyr,ungroup)
 importFrom(magclass,"getComment<-")
+importFrom(magclass,"getItems<-")
+importFrom(magclass,"getNames<-")
+importFrom(magclass,add_dimension)
 importFrom(magclass,as.magpie)
+importFrom(magclass,collapseNames)
+importFrom(magclass,dimSums)
+importFrom(magclass,getItems)
+importFrom(magclass,getNames)
+importFrom(magclass,getYears)
+importFrom(magclass,mbind)
+importFrom(magclass,mselect)
+importFrom(magclass,setNames)
 importFrom(magclass,where)
 importFrom(magpiesets,findset)
 importFrom(magrittr,"%>%")

R/calcPlGaoCabrera.R

@@ -0,0 +1,34 @@
+#' Gao & Cabrera-Serrenho 2025 polymer consumption in IAMC variables
+#'
+#' @description
+#' Return total apparent polymer consumption from Gao & Cabrera-Serrenho (2025),
+#' "Global Plastic MFA", at ISO3 country level. The 14 polymer groups (plastics,
+#' fibres and rubber) are summed into a single total and mapped to the IAMC
+#' variable \code{Material Demand|Chemicals|Plastics} in Mt/yr. Note that the
+#' years 2020-2021 rely on incomplete trade data.
+#'
+#' @author Leonie Schweiger
+#' @return Total polymer consumption (Mt/yr)
+#' @seealso \code{\link{readGaoCabrera2025}}, \code{\link{calcPlPottinger}}
+#' @importFrom magclass dimSums getNames<-
+calcPlGaoCabrera <- function() {
+  x <- readSource("GaoCabrera2025")
+
+  # sum all 14 polymers into a single total and convert kt -> Mt
+  x <- dimSums(x, dim = 3) / 1000
+
+  getNames(x) <- "Material Demand|Chemicals|Plastics"
+
+  return(list(
+    x = x,
+    weight = NULL,
+    unit = "Mt/yr",
+    description = paste(
+      "Apparent polymer consumption 1978-2021 from Gao & Cabrera-Serrenho (2025),",
+      "total over all 14 polymer groups (incl. fibres and rubber), in the IAMC",
+      "variable Material Demand|Chemicals|Plastics. Years 2020-2021 rely on",
+      "incomplete trade data."
+    ),
+    note = "Disaggregated from 8 Gao regions to ISO3 via population weighting"
+  ))
+}

R/calcPlGeyer.R

@@ -0,0 +1,38 @@
+#' Geyer et al. 2017 global plastics production in IAMC variables
+#'
+#' @description
+#' Return the global annual plastics production time series (1950-2015) from
+#' Geyer et al. (2017), doi:10.1126/sciadv.1700782 (Table S1), reported at the
+#' global level under the IAMC variables \code{Production|Chemicals|Plastics}
+#' and \code{Material Demand|Chemicals|Plastics}, both in Mt/yr. The data are
+#' global only and are not disaggregated to countries or regions.
+#'
+#' @author Leonie Schweiger
+#' @return List with a global-only MagPIE object of plastics production (Mt/yr)
+#' in IAMC variables and metadata in calcOutput format.
+#' @seealso \code{\link{readGeyer}}, \code{\link{calcPlPottinger}},
+#' \code{\link{calcPlGaoCabrera}}
+#' @importFrom magclass setNames mbind
+calcPlGeyer <- function() {
+  x <- readSource("Geyer", subtype = "Prod_1950-2015", convert = FALSE)
+
+  # same global figure reported under both IAMC variables (setNames overwrites
+  # the single source data-column name with the IAMC variable name)
+  out <- mbind(
+    setNames(x, "Production|Chemicals|Plastics"),
+    setNames(x, "Material Demand|Chemicals|Plastics")
+  )
+
+  return(list(
+    x = out,
+    weight = NULL,
+    unit = "Mt/yr",
+    description = paste(
+      "Global annual plastics production 1950-2015 from Geyer et al. (2017),",
+      "Table S1, reported at the global level under the IAMC variables",
+      "Production|Chemicals|Plastics and Material Demand|Chemicals|Plastics."
+    ),
+    isocountries = FALSE,
+    note = "Global only; no regional disaggregation."
+  ))
+}

R/calcPlIEA.R

@@ -0,0 +1,87 @@
+#' IEA 2018 global plastics production in IAMC variables
+#'
+#' @description
+#' Return the global annual production of key thermoplastics (1980-2050) from the
+#' IEA report "The Future of Petrochemicals" (2018), Figure 4.2 (Reference
+#' Technology Scenario), read via \code{readSource("IEA_Petrochem",
+#' subtype = "plastics_All")}. The reported total (the source "SUM" series, in Mt)
+#' is returned at the global level under the IAMC variables
+#' \code{Production|Chemicals|Plastics} and \code{Material Demand|Chemicals|Plastics}.
+#' The data are global only and are not disaggregated to countries or regions.
+#'
+#' @param subtype Character. \code{"total"} (default) returns absolute production
+#' and demand in Mt/yr; \code{"perCapita"} returns demand per capita in kg/cap,
+#' using Stegmann's own Population variable.
+#'
+#' @author Leonie Schweiger
+#' @return List with a global-only MagPIE object of plastics production (Mt/yr) in
+#' IAMC variables.
+#' @importFrom magclass setNames mbind getItems getItems<-
+calcPlIEA <- function(subtype) {
+  if (!subtype %in% c("total", "perCapita")) {
+    stop("Unknown subtype '", subtype, "'. Use 'total' or 'perCapita'.")
+  }
+
+  x <- readSource("IEA_Petrochem", subtype = "plastics_All", convert = FALSE)
+
+  # readIEA_Petrochem runs make.names() on the header row, which prefixes the
+  # numeric year columns with "X" (e.g. 1980 -> X1980). For the plastics subtype
+  # these become the temporal dimension, so normalise to proper year format.
+  getYears(x) <- as.integer(sub("^[Xy]", "", getYears(x)))
+
+  # get the total production over all polymers
+  x <- dimSums(x, dim = 3, na.rm = TRUE)
+
+  # same global figure reported under both IAMC variables (setNames overwrites the
+  # single source data-column name with the IAMC variable name)
+  out <- mbind(
+    setNames(x, "Production|Chemicals|Plastics"),
+    setNames(x, "Material Demand|Chemicals|Plastics")
+  )
+
+  if (subtype == "total") {
+    return(list(
+      x = out,
+      weight = NULL,
+      unit = "Mt/yr",
+      description = paste(
+        "Global production of key thermoplastics 1980-2050 from IEA 'The Future of",
+        "Petrochemicals' (2018), Figure 4.2 (Reference Technology Scenario), reported",
+        "at the global level under the IAMC variables Production|Chemicals|Plastics",
+        "and Material Demand|Chemicals|Plastics."
+      ),
+      isocountries = FALSE,
+      note = paste(
+        "Global only; IEA 'key thermoplastics' is a subset of all plastics",
+        "(excludes thermosets and other polymers)."
+      )
+    ))
+  }
+
+  popEstimates <- readSource("UN_PopDiv", subtype = "pop", subset = "estimates")
+  popMedium <- readSource("UN_PopDiv", subtype = "pop", subset = "medium")
+  getNames(popEstimates) <- NULL
+  getNames(popMedium) <- NULL
+  pop <- dimSums(mbind(popEstimates, popMedium), dim = 1)
+  pop <- pop[, getYears(out), ]
+
+  out <- 1000 * out / pop # Mt / million people -> kg/cap
+  out[!is.finite(out)] <- NA
+  getItems(out, dim = 3) <- paste0(getItems(out, dim = 3), "|per capita")
+  getItems(out, dim = 1) <- "GLO"
+
+  return(list(
+    x = out,
+    weight = pop,
+    unit = "kg/cap",
+    description = paste(
+      "Per-capita Global production of key thermoplastics 1980-2050 from IEA 'The Future of",
+      "Petrochemicals' (2018), Figure 4.2 (Reference Technology Scenario), reported",
+      "at the global level under the IAMC variables Production|Chemicals|Plastics",
+      "and Material Demand|Chemicals|Plastics.; population from UN WPP (estimates + medium)."
+    ),
+    isocountries = FALSE,
+    note = "Population-weighted; intensive variable aggregated as weighted mean."
+  ))
+
+}

R/calcPlOECDProjection.R

@@ -0,0 +1,64 @@
+#' OECD Global Plastics Outlook 2022 projections in IAMC variables
+#'
+#' @description
+#' Return the plastics-use projection 1980-2060) from the OECD Global Plastics Outlook 2022 
+#' at ISO3 country level, mapped to IAMC variables.
+#' \code{subtype = "total"} returns total plastics use as
+#' \code{Material Demand|Chemicals|Plastics} (Mt/yr); \code{subtype = "perCapita"}
+#' returns \code{Material Demand|Chemicals|Plastics|per capita} (kg/cap), using the
+#' OECD population projection where available (2019-2060) and \code{\link{calcCoPopulation}}
+#' (SSP2) for the earlier years (1980-2018).
+#'
+#' @param subtype Character, either "total" (plastics use, Mt/yr, summed on aggregation) or
+#' "perCapita" (plastics use per capita, kg/cap, population-weighted mean on aggregation).
+#'
+#' @author Leonie Schweiger
+#' @return List with a MagPIE object of the OECD plastics projection in IAMC variables and
+#' metadata.
+#' @seealso \code{\link{readOECD_Plastic}}, \code{\link{calcPlGaoCabrera}},
+#' \code{\link{calcCoPopulation}}
+#' @importFrom magclass setNames getYears getNames<-
+calcPlOECDProjection <- function(subtype = "total") {
+  # plastics use projection (Mt), ISO3, 1980-2060
+  use <- setNames(readSource("OECD_Plastic", "Use_1980-2060_projection"), NULL)
+
+  if (subtype == "total") {
+    getNames(use) <- "Material Demand|Chemicals|Plastics"
+    return(list(
+      x = use,
+      weight = NULL,
+      unit = "Mt/yr",
+      description = paste(
+        "Plastics use projection 1980-2060 from the OECD Global Plastics Outlook 2022."
+      ),
+      note = "Disaggregated from 15 OECD-Outlook regions to ISO3 via population weighting."
+    ))
+  } else if (subtype == "perCapita") {
+    # OECD population sheet (billion people), ISO3, 2019-2060
+    popOECD <- setNames(readSource("OECD_Plastic", "Pop_2019-2060_projection"), NULL)
+    # reference population (calcCoPopulation is in inhabitants -> convert to billion people)
+    popRef <- setNames(calcOutput("CoPopulation", scenarios = "SSP2", aggregate = FALSE), NULL) / 1e9
+
+    years <- getYears(use)                          # 1980-2060
+    pop <- popRef[, years, ]                         # CoPopulation for all years...
+    overlap <- intersect(years, getYears(popOECD))   # 2019-2060
+    pop[, overlap, ] <- popOECD[, overlap, ]         # ...prefer OECD source pop where available
+
+    perCap <- use / pop                              # Mt / billion people = kg/cap
+    perCap[is.na(perCap) | is.infinite(perCap)] <- 0
+    getNames(perCap) <- "Material Demand|Chemicals|Plastics|per capita"
+    return(list(
+      x = perCap,
+      weight = pop,
+      unit = "kg/cap",
+      description = paste(
+        "Per-capita plastics use projection 1980-2060 from the OECD Global Plastics",
+        "Outlook 2022. OECD population is used for 2019-2060 and ",
+        "calcCoPopulation (SSP2) for 1980-2018."
+      ),
+      note = "Population-weighted; intensive variable aggregated as weighted mean."
+    ))
+  }
+
+  stop("Invalid subtype: ", subtype, ". Use 'total' or 'perCapita'.")
+}

R/calcPlPottinger.R

@@ -0,0 +1,91 @@
+#' Pottinger 2024 plastics material flows in IAMC variables
+#'
+#' @description
+#' Return the plastics material-flow data from Pottinger et al. (2024) for a
+#' specified scenario (Business-as-Usual or policy variants), at ISO3 country
+#' level, with the source flow columns renamed to a subset of IAMC variables.
+#' All flows are in Mt/yr.
+#'
+#' @param subtype Character, scenario to extract (e.g., "businessAsUsual" for BAU).
+#' Must match a scenario name encoded in the data dimension from readPottinger2024.
+#' @param perCapita Logical. If \code{FALSE} (default), return absolute flows in
+#' Mt/yr. If \code{TRUE}, return per-capita flows in kg/cap, using the same UN
+#' World Population Prospects population as \code{\link{convertPottinger2024}}.
+#'
+#' @author Leonie Schweiger
+#' @return List with a MagPIE object of plastics flows (Mt/yr, or kg/cap if
+#' \code{perCapita = TRUE}) in IAMC variables and metadata in calcOutput format.
+#' @seealso \code{\link{readPottinger2024}}
+#' @importFrom magclass getItems getItems<- mbind getYears getNames<-
+calcPlPottinger <- function(subtype = "businessAsUsual", perCapita = FALSE) {
+  x <- readSource("Pottinger2024")
+  scenarios <- getNames(x, dim=1)
+  variables <- getNames(x, dim=2)
+
+  if (subtype == "all") {
+    x <- x
+  } else if (!(subtype %in% scenarios)) {
+    stop("Scenario '", subtype, "' not found in Pottinger2024 data. ",
+      "Available scenarios: ", paste(scenarios, collapse = ", "))
+  } else {
+    x <- x[, , subtype]
+  }
+
+  # map raw source flow columns to IAMC variables
+  iamc <- c(
+    totalConsumptionMt     = "Material Demand|Chemicals|Plastics",
+    primaryProductionMt    = "Production|Chemicals|Plastics|Primary",
+    secondaryProductionMt  = "Production|Chemicals|Plastics|Secondary"
+  )
+
+  # identify which of the mapped variables are present in this scenario
+  keep_idx <- which(variables %in% names(iamc))
+  variables_kept <- variables[keep_idx]
+
+  if (length(keep_idx) == 0) {
+    stop("No mapped variables found for scenario '", subtype, "' in Pottinger2024. ",
+      "Expected one or more of: ", paste(names(iamc), collapse = ", "))
+  }
+
+  # subset to keep only mapped variables
+  x <- x[, , variables_kept]
+  new_names <- iamc[variables_kept]
+  getItems(x, dim = 3.2) <- as.vector(new_names)
+
+  if (!perCapita) {
+    return(list(
+      x = x,
+      weight = NULL,
+      unit = "Mt/yr",
+      description = paste(
+        "Plastics material-flow pathway 2011-2050 from Pottinger et al. (2024),",
+        "scenario:", subtype, "in IAMC variables"
+      ),
+      note = "Disaggregated from 4 Pottinger regions to ISO3 via population weighting"
+    ))
+  }
+
+  # per-capita: same UN World Population Prospects population as convertPottinger2024
+  # (estimates through 2021 + medium variant from 2022), in millions of people
+  popEstimates <- readSource("UN_PopDiv", subtype = "pop", subset = "estimates")
+  popMedium <- readSource("UN_PopDiv", subtype = "pop", subset = "medium")
+  getNames(popEstimates) <- NULL
+  getNames(popMedium) <- NULL
+  pop <- mbind(popEstimates, popMedium)
+  pop <- pop[getItems(x, dim = 1), getYears(x), ] # ISO3 countries & Pottinger years
+
+  x <- 1000 * x / pop # Mt / million people -> kg/cap
+  x[!is.finite(x)] <- NA
+  getItems(x, dim = 3.2) <- paste0(as.vector(new_names), "|per capita")
+
+  return(list(
+    x = x,
+    weight = pop,
+    unit = "kg/cap",
+    description = paste(
+      "Per-capita plastics material-flow pathway 2011-2050 from Pottinger et al. (2024),",
+      "scenario:", subtype, "in IAMC variables; population from UN WPP (estimates + medium)."
+    ),
+    note = "Population-weighted; intensive variable aggregated as weighted mean."
+  ))
+}