diff --git a/.buildlibrary b/.buildlibrary
index e8618ed..4b6da5e 100644
--- a/.buildlibrary
+++ b/.buildlibrary
@@ -1,4 +1,4 @@
-ValidationKey: '1236714'
+ValidationKey: '1397480'
 AutocreateReadme: yes
 AcceptedWarnings:
 - 'Warning: package ''.*'' was built under R version'
diff --git a/CITATION.cff b/CITATION.cff
index b797c51..c85ff1c 100644
--- a/CITATION.cff
+++ b/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: 'mredgebuildings: Prepare data to be used by the EDGE-Buildings model'
-version: 0.6.2
-date-released: '2024-08-12'
+version: 0.7.0
+date-released: '2024-08-29'
 abstract: Prepare data to be used by the EDGE-Buildings model.
 authors:
 - family-names: Hasse
diff --git a/DESCRIPTION b/DESCRIPTION
index 2ecefc5..f60b14b 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,8 +1,8 @@
 Type: Package
 Package: mredgebuildings
 Title: Prepare data to be used by the EDGE-Buildings model
-Version: 0.6.2
-Date: 2024-08-12
+Version: 0.7.0
+Date: 2024-08-29
 Authors@R: c(
     person("Robin", "Hasse", , "robin.hasse@pik-potsdam.de", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0003-1818-3186")),
diff --git a/NAMESPACE b/NAMESPACE
index 863ea68..f8d3c73 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -10,6 +10,7 @@ export(calcFEUE)
 export(calcFEUEefficiencies)
 export(calcFEbyEUEC)
 export(calcFEdemandBuildings)
+export(calcFloorspacePast)
 export(calcHeatingCapacity)
 export(calcHeatingSystem)
 export(calcHouseholdSize)
diff --git a/R/calcFloorspacePast.R b/R/calcFloorspacePast.R
index 307ac7d..5007080 100644
--- a/R/calcFloorspacePast.R
+++ b/R/calcFloorspacePast.R
@@ -14,12 +14,12 @@
 #' @author Robin Hasse, Antoine Levesque, Hagen Tockhorn
 #'
 #' @importFrom madrat readSource calcOutput toolCountryFill
-#' @importFrom quitte as.quitte calc_addVariable factor.data.frame
+#' @importFrom quitte as.quitte calc_addVariable factor.data.frame interpolate_missing_periods
 #' @importFrom dplyr filter mutate select anti_join group_by left_join %>%
-#' ungroup .data %>%
+#' ungroup .data %>% group_modify
 #' @importFrom rlang .data
 #' @importFrom magclass mbind as.magpie collapseDim mselect
-#' @importFrom tidyr spread
+#' @importFrom tidyr spread replace_na
 #'
 #' @export
 
@@ -37,25 +37,12 @@ calcFloorspacePast <- function() {
   }
 
 
-  #' Predict missing historic floorspace data
-  #'
-  #' A linear regression is performed to establish a general relationship between
-  #' floorspace per capita and gdp per capita and population density.
-  #' Predicted values are corrected w.r.t. to historical data where available,
-  #' otherwise the prediction is chosen.
-  #'
-  #' @param df data.frame containing floorspace per capita
-  #' @param gdppop data.frame containing gdp per capita
-  #' @param dens data.frame containing population density
-  #' @param endOfHistory upper temporal boundary of historic data
-  #' @param periodBegin lower temporal boundary of historic data
-  #'
-  #' @importFrom quitte factor.data.frame interpolate_missing_periods
-  #' @importFrom tidyr replace_na
-  #' @importFrom dplyr group_modify
-  #'
-  #' @returns floorspace per capita with filled missing entries
-
+  # Predict missing historic floorspace data
+  #
+  # A linear regression is performed to establish a general relationship between
+  # floorspace per capita and gdp per capita and population density.
+  # Predicted values are corrected w.r.t. to historical data where available,
+  # otherwise the prediction is chosen.
   makeFloorspaceProjection <- function(df, gdppop, dens, endOfHistory, periodBegin) {
 
     # Clean data
diff --git a/R/calcPFUDB.R b/R/calcPFUDB.R
index c695bd3..ba6d5b0 100644
--- a/R/calcPFUDB.R
+++ b/R/calcPFUDB.R
@@ -42,26 +42,6 @@ calcPFUDB <- function() {
     }
   }
 
-  # convert enduse "appliances" to "refrigerators" with respective scaling factor
-  addThermal <- function(df, mapping, fridgeShare) {
-    df <- df %>%
-      filter(.data[["enduse"]] != "lighting") %>%
-      left_join(mapping %>%
-                  select(-"RegionCodeEUR", -"RegionCodeEUR_ETP", -"X") %>%
-                  rename(region = "CountryCode") %>%
-                  left_join(fridgeShare, by = "RegionCode") %>%
-                  select(-"RegionCode"),
-                by = "region") %>%
-      mutate(value = ifelse(.data[["enduse"]] != "appliances",
-                            .data[["value"]],
-                            .data[["value"]] * .data[["share"]]),
-             enduse = ifelse(.data[["enduse"]] == "appliances",
-                             "refrigerators",
-                             as.character(.data[["enduse"]]))) %>%
-      select(-"share")
-    return(df)
-  }
-
 
 
   # PARAMETERS -----------------------------------------------------------------
@@ -175,7 +155,7 @@ calcPFUDB <- function() {
     mutate(value = ifelse(is.na(.data[["value.x"]]),
                           .data[["value.y"]],
                           .data[["value.x"]])) %>%
-    addThermal(regmappingEDGE, fridgeShare) %>%
+    toolAddThermal(regmappingEDGE, fridgeShare) %>%
     select("region", "period", "carrier", "enduse", "value")
 
 
diff --git a/R/calcShareETP.R b/R/calcShareETP.R
index 6b4604d..8261f4f 100644
--- a/R/calcShareETP.R
+++ b/R/calcShareETP.R
@@ -179,6 +179,8 @@ calcShareETP <- function(subtype = c("enduse", "carrier"), feOnly = FALSE) {
         group_by(across(all_of(c("region", "period")))) %>%
         mutate(value = proportions(.data[["value"]])) %>%
         ungroup()
+    } else {
+      etpFilter <- shareCorr
     }
   }
 
@@ -188,7 +190,7 @@ calcShareETP <- function(subtype = c("enduse", "carrier"), feOnly = FALSE) {
 
   # return only FE data
   if (isTRUE(feOnly)) {
-    feData <- shareCorr %>%
+    feData <- etpFilter %>%
       as.quitte() %>%
       mutate(value = .data[["value"]] * PJ2EJ,
              unit = "EJ") %>%
diff --git a/R/calcShareOdyssee.R b/R/calcShareOdyssee.R
index 15991f3..632bbf1 100644
--- a/R/calcShareOdyssee.R
+++ b/R/calcShareOdyssee.R
@@ -109,13 +109,17 @@ calcShareOdyssee <- function(subtype = c("enduse", "carrier", "enduse_carrier"),
     meanApplightShares <- odyssee %>%
       filter(.data[["enduse"]] %in% c("lighting", "appliances"),
              !is.na(.data[["value"]])) %>%
-      group_by(across(all_of(c("region", "period", "sector", "carrier")))) %>%
+      group_by(across(all_of(c("period", "sector", "carrier", "enduse")))) %>%
+      mutate(value = sum(.data[["value"]], na.rm = TRUE)) %>%
+      ungroup() %>%
+      group_by(across(all_of(c("period", "sector", "carrier")))) %>%
       mutate(value = proportions(.data[["value"]])) %>%
       ungroup() %>%
       group_by(across(all_of(c("period", "sector", "enduse")))) %>%
       mutate(share = mean(.data[["value"]])) %>%
       ungroup() %>%
-      select(all_of(c("period", "carrier", "sector", "enduse", "share")))
+      select(all_of(c("period", "carrier", "sector", "enduse", "share"))) %>%
+      unique()
 
     # split existing aggregated data into "appliances" and "lighting"
     applightData <- odysseeData %>%
diff --git a/R/calcShares.R b/R/calcShares.R
index c567327..c080d6e 100644
--- a/R/calcShares.R
+++ b/R/calcShares.R
@@ -24,7 +24,6 @@
 #' @param subtype specifies share
 #' @param carrierCorrection allows additional corrections
 #' @param feOnly specifies if shares or quantities are returned
-#' @param feWeights calculate additional FE weights for share aggregation
 #'
 #' @note The parameter "feOnly" is only applicable to IEA_ETP and TCEP data,
 #' since this is the necessary data to do a full disaggregation of EU and EC
@@ -38,9 +37,8 @@
 #'
 #' @author Hagen Tockhorn, Robin Hasse
 #'
-#' @importFrom rlang .data
 #' @importFrom dplyr mutate as_tibble filter select rename group_by across
-#'   all_of ungroup %>% .data left_join summarise group_modify cross_join
+#'   all_of ungroup %>% .data left_join reframe group_modify cross_join .data
 #' @importFrom tidyr replace_na unite complete
 #' @importFrom madrat toolGetMapping calcOutput readSource toolCountryFill
 #' @importFrom magclass time_interpolate as.magpie
@@ -53,8 +51,7 @@ calcShares <- function(subtype = c("carrier_nonthermal",
                                    "enduse_nonthermal",
                                    "enduse_thermal"),
                        carrierCorrection = FALSE,
-                       feOnly = FALSE,
-                       feWeights = TRUE) {
+                       feOnly = FALSE) {
 
 
 
@@ -66,43 +63,6 @@ calcShares <- function(subtype = c("carrier_nonthermal",
   thermVar <- strsplit(subtype, "_")[[1]][2]
 
 
-
-  #---Corrections for specific carrier shares
-  # nolint start
-  correction <- inline.data.frame(
-    "region;        enduse;                                carrier; value",
-    ".*;            water_heating;                         heat;    0",
-    "(OCD|EUR|USA); (water_heating|cooking);               biomod;  0",
-    "EUR;           (water_heating|cooking);               biotrad; 0",
-    "RUS;           space_heating;                         heat;    0.60",
-    "RUS;           (water_heating|cooking);               natgas;  0.70",
-    "RUS;           (water_heating|cooking);               elec;    0.07",
-    "RUS;           space_heating;                         elec;    0.03",
-    "RUS;           (space_heating|water_heating|cooking); coal;    0.04",
-    "RUS;           (space_heating|water_heating|cooking); petrol;  0.10",
-    "IND;           (space_heating|water_heating);         biotrad; 0.80",
-    "IND;           (space_heating|water_heating|cooking); coal;    0.10",
-    "IND;           (space_heating|water_heating);         petrol;  0.12",
-    "IND;           (space_heating|water_heating);         natgas;  0",
-    "IND;           (space_heating|water_heating);         elec;    0.02",
-    "IND;           cooking;                               natgas;  0.04",
-    "IND;           cooking;                      (biotrad|petrol); 0.50") %>%
-    unite("regex", all_of(c("region", "enduse", "carrier")), sep = "\\.")
-  # nolint end
-
-
-  # Enduse-Carrier combinations which will be systematically excluded
-  exclude <- toolGetMapping(name  = "excludeEnduseCarrier.csv",
-                            type  = "sectoral",
-                            where = "mredgebuildings")
-
-
-  # Percentage of Appliances for Refrigerators
-  fridgeShare <- rbind(data.frame(RegionCode = "USA", share  = 0.12),
-                       data.frame(RegionCode = c("EUR", "OCD", "RUS", "JPN"), share = 0.17),
-                       data.frame(RegionCode = c("CHN", "IND", "NCD", "AFR", "MIE", "OAS"), share = 0.3))
-
-
   # Regions taken into account from WEO
   regWEO <- c("Africa", "Middle East", "Japan")
 
@@ -114,11 +74,6 @@ calcShares <- function(subtype = c("carrier_nonthermal",
 
   # Shares
 
-  # IEA
-  ieaIO <- calcOutput("IOEdgeBuildings", subtype = "output_EDGE_buildings",
-                      aggregate = FALSE) %>%
-    as.quitte(na.rm = TRUE)
-
   # Odyssee
   sharesOdyssee <-
     calcOutput("ShareOdyssee", subtype = shareOf, aggregate = FALSE) %>%
@@ -171,6 +126,21 @@ calcShares <- function(subtype = c("carrier_nonthermal",
                                   type  = "regional",
                                   where = "mredgebuildings")
 
+  # Carrier share corrections
+  shareCorrections <- toolGetMapping(name  = "correction_carrierShares.csv",
+                                     type  = "sectoral",
+                                     where = "mredgebuildings")
+
+  # Percentage of Appliances for Refrigerators
+  fridgeShare <- toolGetMapping(name  = "fridgeShare.csv",
+                                type  = "sectoral",
+                                where = "mredgebuildings")
+
+  # Enduse-Carrier combinations which will be systematically excluded
+  exclude <- toolGetMapping(name  = "excludeEnduseCarrier.csv",
+                            type  = "sectoral",
+                            where = "mredgebuildings")
+
 
 
 
@@ -184,31 +154,6 @@ calcShares <- function(subtype = c("carrier_nonthermal",
   }
 
 
-  addThermal <- function(df, mapping, fridgeShare) {
-    df <- df %>%
-      filter(.data[["enduse"]] != "lighting") %>%
-      left_join(regmappingEDGE %>%
-                  select(-"RegionCodeEUR", -"RegionCodeEUR_ETP", -"X") %>%
-                  rename(region = "CountryCode") %>%
-                  left_join(fridgeShare, by = "RegionCode") %>%
-                  select(-"RegionCode"),
-                by = "region") %>%
-      mutate(value = ifelse(.data[["enduse"]] != "appliances",
-                            .data[["value"]],
-                            .data[["value"]] * .data[["share"]]),
-             enduse = ifelse(.data[["enduse"]] == "appliances",
-                             "refrigerators",
-                             as.character(.data[["enduse"]]))) %>%
-      select(-"share")
-
-    if (!feOnly) {
-      df <- normalize(df, shareOf)
-      return(df)
-    }
-
-    return(df)
-  }
-
 
   # PROCESS DATA ---------------------------------------------------------------
 
@@ -244,7 +189,7 @@ calcShares <- function(subtype = c("carrier_nonthermal",
 
 
 
-    if (!feOnly) {
+    if (isFALSE(feOnly)) {
       # Extrapolate ETP FE Data
       evolutionFactor <- sharesTCEP %>%
         left_join(regmappingETP %>%
@@ -307,62 +252,65 @@ calcShares <- function(subtype = c("carrier_nonthermal",
         select(-"value.x", -"value.y")
     }
 
-    if (feOnly || feWeights) {
-      # Extrapolate ETP FE Data
-      evolutionFactor <- dataTCEP %>%
-        left_join(regmappingETP %>%
-                    select("CountryCode", "EEAReg") %>%
-                    rename(region = "CountryCode",
-                           regionAgg = "EEAReg"),
-                  by = "region") %>%
-        group_by(across(all_of(c("regionAgg", "enduse", "period")))) %>%
-        summarise(value = sum(.data[["value"]], na.rm = TRUE)) %>%
-        ungroup() %>%
-        group_by(across(all_of(c("regionAgg", "enduse")))) %>%
-        summarise(factor = .data[["value"]] / dplyr::lead(.data[["value"]])) %>%
-        ungroup() %>%
-        filter(!is.na(.data[["factor"]])) %>%
-        left_join(regmappingETP %>%
-                    select("CountryCode", "EEAReg") %>%
-                    rename(region = "CountryCode",
-                           regionAgg = "EEAReg"),
-                  by = "regionAgg") %>%
-        select(-"regionAgg")
-
-
-      dataETPstart <- feETP %>%
-        left_join(evolutionFactor, by = c("region", "enduse")) %>%
-        mutate(value = .data[["value"]] * .data[["factor"]],
-               period = 2000) %>%
-        select(-"factor") %>%
-        filter(!is.na(.data[["value"]]))
-
 
-      dataETPfull <- rbind(dataETPstart,
-                           feETP %>%
-                             filter(!is.na(.data[["value"]])))
+    # Calculate FE Data
 
-
-      dataETPfull <- dataETPfull %>%
-        select(-"unit") %>%
-        quitte::factor.data.frame() %>%
-        as.quitte() %>%
-        interpolate_missing_periods(period = seq(1990, 2020)) %>%
-        group_by(across(all_of(c("region", "enduse")))) %>%
-        group_modify(~ extrapolateMissingPeriods(.x, key = "value")) %>%
-        ungroup() %>%
-        select("region", "period", "enduse", "value")
-
-
-      # NOTE: The linear regression might lead to negative values which will be
-      # filled up with small values and then re-normalized.
-      # (However, this is a very practical fix...)
-
-      dataETPfull <- dataETPfull %>%
-        mutate(value = ifelse(.data[["value"]] < 0, 1e-6, .data[["value"]]))
-
-      if (feOnly) {data  <- dataETPfull} #nolint
-      else        {regFE <- dataETPfull} #nolint
+    # Extrapolate ETP FE Data
+    evolutionFactor <- dataTCEP %>%
+      left_join(regmappingETP %>%
+                  select("CountryCode", "EEAReg") %>%
+                  rename(region = "CountryCode",
+                         regionAgg = "EEAReg"),
+                by = "region") %>%
+      group_by(across(all_of(c("regionAgg", "enduse", "period")))) %>%
+      reframe(value = sum(.data[["value"]], na.rm = TRUE)) %>%
+      group_by(across(all_of(c("regionAgg", "enduse")))) %>%
+      reframe(factor = .data[["value"]] / dplyr::lead(.data[["value"]])) %>%
+      filter(!is.na(.data[["factor"]])) %>%
+      left_join(regmappingETP %>%
+                  select("CountryCode", "EEAReg") %>%
+                  rename(region = "CountryCode",
+                         regionAgg = "EEAReg"),
+                by = "regionAgg") %>%
+      select(-"regionAgg")
+
+
+    dataETPstart <- feETP %>%
+      left_join(evolutionFactor, by = c("region", "enduse")) %>%
+      mutate(value = .data[["value"]] * .data[["factor"]],
+             period = 2000) %>%
+      select(-"factor") %>%
+      filter(!is.na(.data[["value"]]))
+
+
+    dataETPfull <- rbind(dataETPstart,
+                         feETP %>%
+                           filter(!is.na(.data[["value"]])))
+
+
+    dataETPfull <- dataETPfull %>%
+      select(-"unit") %>%
+      quitte::factor.data.frame() %>%
+      as.quitte() %>%
+      interpolate_missing_periods(period = seq(1990, 2020)) %>%
+      group_by(across(all_of(c("region", "enduse")))) %>%
+      group_modify(~ extrapolateMissingPeriods(.x, key = "value")) %>%
+      ungroup() %>%
+      select("region", "period", "enduse", "value")
+
+
+    # NOTE: The linear regression might lead to negative values which will be
+    # filled up with small values and then re-normalized.
+    # (However, this is a very practical fix...)
+
+    dataETPfull <- dataETPfull %>%
+      mutate(value = ifelse(.data[["value"]] < 0, 1e-6, .data[["value"]]))
+
+    if (feOnly) {
+      data  <- dataETPfull
+    } else {
+      regFE <- dataETPfull %>%
+        mutate(value = replace_na(.data[["value"]], 0))
     }
   }
 
@@ -383,7 +331,7 @@ calcShares <- function(subtype = c("carrier_nonthermal",
       interpolate_missing_periods(period = seq(1990, 2020), expand.values = TRUE)
 
 
-    if (carrierCorrection == TRUE) {
+    if (isTRUE(carrierCorrection)) {
       # The Carrier resolution will be extended by a further added resolution for
       # Enduses, which are however not disaggregated. This only serves the purpose
       # of facilitating specific corrections.
@@ -445,66 +393,36 @@ calcShares <- function(subtype = c("carrier_nonthermal",
 
 
       # Make more specific corrections
-      for (i in rownames(correction)) {
-        data <- data %>%
-          mutate(value = unlist(ifelse(
-            grepl(correction[i, "regex"],
-                  paste(.data[["RegionCode"]], .data[["enduse"]], .data[["carrier"]],
-                        sep = ".")),
-            correction[i, "value"],
-            .data[["value"]]
-          )))
-      }
-
-
-      # Remove Mapping Column
-      data <- select(data, -"RegionCode")
-
-      # Re-Normalize
-      data <- normalize(data, shareOf)
+      data <- data %>%
+        left_join(shareCorrections, by = c("RegionCode" = "region", "enduse", "carrier")) %>%
+        mutate(value = ifelse(is.na(.data[["correction"]]),
+                              .data[["value"]],
+                              .data[["correction"]])) %>%
+        select(-"correction", -"RegionCode") %>%
+        normalize(shareOf)
     }
   }
 
+  if (isFALSE(feOnly)) {
+    # replace NA's
+    data <- data %>%
+      mutate(value = replace_na(.data[["value"]], 0))
+  }
+
 
   #---Thermal Part
   if (thermVar == "thermal") {
     if (shareOf == "enduse") {
       data <- data %>%
-        addThermal(regmappingEDGE, fridgeShare)
+        toolAddThermal(regmappingEDGE, fridgeShare, feOnly = FALSE, shareOf)
 
-      if (feWeights) {
+      if (isFALSE(feOnly)) {
         regFE <- regFE %>%
-          addThermal(regmappingEDGE, fridgeShare)
+          toolAddThermal(regmappingEDGE, fridgeShare)
       }
     }
   }
 
-  #---Weights: Regional Shares of FE
-  # Weights consist of the share of each region's FE demand relative to global FE demand.
-  # FE data is taken from ieaIO.
-  regShare <- ieaIO %>%
-    mutate(carrier = .data[["variable"]]) %>%
-    select("region", "period", "carrier", "value") %>%
-    group_by(across(all_of(c("period", "region")))) %>%
-    filter(!all(.data[["value"]] == 0)) %>%
-    summarise(value = sum(.data[["value"]], na.rm = TRUE)) %>%
-    ungroup() %>%
-    group_by(across(all_of(c("region")))) %>%
-    complete(period = unique(data$period)) %>%
-    ungroup() %>%
-    interpolate_missing_periods(expand.values = TRUE) %>%
-    group_by(across(all_of(c("period")))) %>%
-    mutate(value = proportions(.data[["value"]]))
-
-  regFE <- regFE %>%
-    mutate(value = replace_na(.data[["value"]], 0))
-
-
-  if (feWeights) {
-    data <- data %>%
-      mutate(value = replace_na(.data[["value"]], 0))
-  }
-
 
 
 
@@ -516,30 +434,24 @@ calcShares <- function(subtype = c("carrier_nonthermal",
     as.magpie() %>%
     toolCountryFill(1, verbosity = 2)
 
-  regShare <- regShare %>%
-    as.magpie() %>%
-    collapseDim() %>%
-    time_interpolate(getItems(data, 2)) %>%
-    toolCountryFill(1, verbosity = 2)
-
-  regFE <- regFE %>%
-    as.magpie() %>%
-    collapseDim() %>%
-    time_interpolate(getItems(data, 2)) %>%
-    toolCountryFill(1, verbosity = 2)
-
-
 
   if (isTRUE(feOnly)) {
-    weight <- regShare
-    unit <- "EJ"
-    max <- NULL
+    weight <- NULL
+    unit   <- "EJ"
+    max    <- NULL
 
     description <- "Final energy demand of carrier or end use in buildings"
   } else {
+    regFE <- regFE %>%
+      as.magpie() %>%
+      collapseDim() %>%
+      time_interpolate(getItems(data, 2)) %>%
+      toolCountryFill(1, verbosity = 2)
+
     weight <- regFE
-    unit <- "1"
-    max <- 1
+    unit   <- "1"
+    max    <- 1
+
     description <- "Share of carrier or end use in buildings final energy demand"
   }
 
diff --git a/R/toolAddThermal.R b/R/toolAddThermal.R
new file mode 100644
index 0000000..064d2ef
--- /dev/null
+++ b/R/toolAddThermal.R
@@ -0,0 +1,44 @@
+#' Introduce refrigerators as appliances
+#'
+#' @param df data.frame
+#' @param mapping original EDGE-B region mapping
+#' @param fridgeShare regional shares of refrigerators
+#' @param feOnly are absolute values (TRUE) or shares (FALSE) considered?
+#' @param shareOf column name to calculate share of - must be given if feOnly = FALSE
+#'
+#' @author Hagen Tockhorn
+#'
+#' @importFrom dplyr filter left_join select
+
+toolAddThermal <- function(df, mapping, fridgeShare, feOnly = TRUE, shareOf = NULL) {
+  df <- df %>%
+    filter(.data[["enduse"]] != "lighting") %>%
+    left_join(mapping %>%
+                select(-"RegionCodeEUR", -"RegionCodeEUR_ETP", -"X") %>%
+                rename(region = "CountryCode") %>%
+                left_join(fridgeShare, by = "RegionCode") %>%
+                select(-"RegionCode"),
+              by = "region") %>%
+    mutate(value = ifelse(.data[["enduse"]] != "appliances",
+                          .data[["value"]],
+                          .data[["value"]] * .data[["share"]]),
+           enduse = ifelse(.data[["enduse"]] == "appliances",
+                           "refrigerators",
+                           as.character(.data[["enduse"]]))) %>%
+    select(-"share")
+
+  if (!feOnly) {
+    if (is.character(shareOf) && (shareOf %in% colnames(df))) {
+      df <- df %>%
+        group_by(across(-all_of(c(shareOf, "value")))) %>%
+        mutate(value = .data[["value"]] / sum(.data[["value"]], na.rm = TRUE)) %>%
+        ungroup()
+    } else {
+      stop("Please give existing col name.")
+    }
+
+    return(df)
+  }
+
+  return(df)
+}
diff --git a/R/toolDisaggregate.R b/R/toolDisaggregate.R
index 1356561..43076f3 100644
--- a/R/toolDisaggregate.R
+++ b/R/toolDisaggregate.R
@@ -23,7 +23,7 @@
 #' @param dataDisagg data.frame similar to \code{data} but already disaggregated
 #'   by carriers and end uses. The average distribution of its disaggregation
 #'   will be used as the target distribution for the minisation.
-#' @param regionmapping data.frame with the columns \code{region} and
+#' @param regionMapping data.frame with the columns \code{region} and
 #'   \code{regionAgg} that maps the regions between \code{data} and
 #'   \code{enduseShares}.
 #' @param outliers list of regions where naive disaggregation estimate shall
@@ -238,7 +238,7 @@ toolDisaggregate <- function(data,
 
 
 
-#' Disaggregate energy demand within on aggregated region
+#' Disaggregate energy demand within an aggregated region
 #'
 #' Disaggregate regional energy demand per carrier by end use while meeting the
 #' end use shares in the aggregated region.
diff --git a/README.md b/README.md
index 2a9c56a..34d7dd6 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,6 @@
 # Prepare data to be used by the EDGE-Buildings model
 
-R package **mredgebuildings**, version **0.6.2**
+R package **mredgebuildings**, version **0.7.0**
 
 [![CRAN status](https://www.r-pkg.org/badges/version/mredgebuildings)](https://cran.r-project.org/package=mredgebuildings)  [![R build status](https://github.com/pik-piam/mredgebuildings/workflows/check/badge.svg)](https://github.com/pik-piam/mredgebuildings/actions) [![codecov](https://codecov.io/gh/pik-piam/mredgebuildings/branch/master/graph/badge.svg)](https://app.codecov.io/gh/pik-piam/mredgebuildings) [![r-universe](https://pik-piam.r-universe.dev/badges/mredgebuildings)](https://pik-piam.r-universe.dev/builds)
 
@@ -38,7 +38,7 @@ In case of questions / problems please contact Robin Hasse <robin.hasse@pik-pots
 
 To cite package **mredgebuildings** in publications use:
 
-Hasse R, Führlich P, Levesque A, Tockhorn H (2024). _mredgebuildings: Prepare data to be used by the EDGE-Buildings model_. R package version 0.6.2, <https://github.com/pik-piam/mredgebuildings>.
+Hasse R, Führlich P, Levesque A, Tockhorn H (2024). _mredgebuildings: Prepare data to be used by the EDGE-Buildings model_. R package version 0.7.0, <https://github.com/pik-piam/mredgebuildings>.
 
 A BibTeX entry for LaTeX users is
 
@@ -47,11 +47,7 @@ A BibTeX entry for LaTeX users is
   title = {mredgebuildings: Prepare data to be used by the EDGE-Buildings model},
   author = {Robin Hasse and Pascal Führlich and Antoine Levesque and Hagen Tockhorn},
   year = {2024},
-<<<<<<< HEAD
   note = {R package version 0.7.0},
-=======
-  note = {R package version 0.6.2},
->>>>>>> 8aff157d9945bce34154e6bab672c915009a6bf7
   url = {https://github.com/pik-piam/mredgebuildings},
 }
 ```
diff --git a/inst/extdata/sectoral/correction_carrierShares.csv b/inst/extdata/sectoral/correction_carrierShares.csv
new file mode 100644
index 0000000..5c4793b
--- /dev/null
+++ b/inst/extdata/sectoral/correction_carrierShares.csv
@@ -0,0 +1,76 @@
+region,enduse,carrier,correction
+NCD,water_heating,heat,0.0
+OAS,water_heating,heat,0.0
+AFR,water_heating,heat,0.0
+FIN,water_heating,heat,0.0
+MIE,water_heating,heat,0.0
+OCD,water_heating,heat,0.0
+AUT,water_heating,heat,0.0
+BEL,water_heating,heat,0.0
+BGR,water_heating,heat,0.0
+BRA,water_heating,heat,0.0
+CHN,water_heating,heat,0.0
+CYP,water_heating,heat,0.0
+CZE,water_heating,heat,0.0
+DEU,water_heating,heat,0.0
+DNK,water_heating,heat,0.0
+ESP,water_heating,heat,0.0
+EST,water_heating,heat,0.0
+FRA,water_heating,heat,0.0
+GBR,water_heating,heat,0.0
+GRC,water_heating,heat,0.0
+HRV,water_heating,heat,0.0
+HUN,water_heating,heat,0.0
+IND,water_heating,heat,0.0
+IRL,water_heating,heat,0.0
+ITA,water_heating,heat,0.0
+JPN,water_heating,heat,0.0
+LTU,water_heating,heat,0.0
+LUX,water_heating,heat,0.0
+LVA,water_heating,heat,0.0
+MEX,water_heating,heat,0.0
+MLT,water_heating,heat,0.0
+NLD,water_heating,heat,0.0
+POL,water_heating,heat,0.0
+USA,water_heating,heat,0.0
+PRT,water_heating,heat,0.0
+ROU,water_heating,heat,0.0
+RUS,water_heating,heat,0.0
+SVK,water_heating,heat,0.0
+SVN,water_heating,heat,0.0
+SWE,water_heating,heat,0.0
+ZAF,water_heating,heat,0.0
+OCD,water_heating,biomod,0.0
+OCD,cooking,biomod,0.0
+EUR,water_heating,biomod,0.0
+EUR,cooking,biomod,0.0
+USA,water_heating,biomod,0.0
+USA,cooking,biomod,0.0
+EUR,water_heating,biotrad,0.0
+EUR,cooking,biotrad,0.0
+RUS,space_heating,heat,0.6
+RUS,water_heating,natgas,0.7
+RUS,cooking,natgas,0.7
+RUS,water_heating,elec,0.07
+RUS,cooking,elec,0.07
+RUS,space_heating,elec,0.03
+RUS,space_heating,coal,0.04
+RUS,water_heating,coal,0.04
+RUS,cooking,coal,0.04
+RUS,space_heating,petrol,0.1
+RUS,water_heating,petrol,0.1
+RUS,cooking,petrol,0.1
+IND,space_heating,biotrad,0.8
+IND,water_heating,biotrad,0.8
+IND,space_heating,coal,0.1
+IND,water_heating,coal,0.1
+IND,cooking,coal,0.1
+IND,space_heating,petrol,0.12
+IND,water_heating,petrol,0.12
+IND,space_heating,natgas,0.0
+IND,water_heating,natgas,0.0
+IND,space_heating,elec,0.02
+IND,water_heating,elec,0.02
+IND,cooking,natgas,0.04
+IND,cooking,biotrad,0.5
+IND,cooking,petrol,0.5
diff --git a/inst/extdata/sectoral/fridgeShare.csv b/inst/extdata/sectoral/fridgeShare.csv
new file mode 100644
index 0000000..5e6899f
--- /dev/null
+++ b/inst/extdata/sectoral/fridgeShare.csv
@@ -0,0 +1,12 @@
+RegionCode,share
+USA,0.12
+EUR,0.17
+OCD,0.17
+RUS,0.17
+JPN,0.17
+CHN,0.3
+IND,0.3
+NCD,0.3
+AFR,0.3
+MIE,0.3
+OAS,0.3
diff --git a/man/calcShares.Rd b/man/calcShares.Rd
index 7aa0fa9..bd93642 100644
--- a/man/calcShares.Rd
+++ b/man/calcShares.Rd
@@ -8,8 +8,7 @@ calcShares(
   subtype = c("carrier_nonthermal", "carrier_thermal", "enduse_nonthermal",
     "enduse_thermal"),
   carrierCorrection = FALSE,
-  feOnly = FALSE,
-  feWeights = TRUE
+  feOnly = FALSE
 )
 }
 \arguments{
@@ -18,8 +17,6 @@ calcShares(
 \item{carrierCorrection}{allows additional corrections}
 
 \item{feOnly}{specifies if shares or quantities are returned}
-
-\item{feWeights}{calculate additional FE weights for share aggregation}
 }
 \value{
 data.frame with historic energy demands
diff --git a/man/dot-disaggregate.Rd b/man/dot-disaggregate.Rd
index 1e509d3..db38679 100644
--- a/man/dot-disaggregate.Rd
+++ b/man/dot-disaggregate.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/toolDisaggregate.R
 \name{.disaggregate}
 \alias{.disaggregate}
-\title{Disaggregate energy demand within on aggregated region}
+\title{Disaggregate energy demand within an aggregated region}
 \usage{
 .disaggregate(subset, key)
 }
diff --git a/man/makeFloorspaceProjection.Rd b/man/makeFloorspaceProjection.Rd
deleted file mode 100644
index f3660ec..0000000
--- a/man/makeFloorspaceProjection.Rd
+++ /dev/null
@@ -1,28 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/calcFloorspacePast.R
-\name{makeFloorspaceProjection}
-\alias{makeFloorspaceProjection}
-\title{Predict missing historic floorspace data}
-\usage{
-makeFloorspaceProjection(df, gdppop, dens, endOfHistory, periodBegin)
-}
-\arguments{
-\item{df}{data.frame containing floorspace per capita}
-
-\item{gdppop}{data.frame containing gdp per capita}
-
-\item{dens}{data.frame containing population density}
-
-\item{endOfHistory}{upper temporal boundary of historic data}
-
-\item{periodBegin}{lower temporal boundary of historic data}
-}
-\value{
-floorspace per capita with filled missing entries
-}
-\description{
-A linear regression is performed to establish a general relationship between
-floorspace per capita and gdp per capita and population density.
-Predicted values are corrected w.r.t. to historical data where available,
-otherwise the prediction is chosen.
-}
diff --git a/man/toolAddThermal.Rd b/man/toolAddThermal.Rd
new file mode 100644
index 0000000..d02535d
--- /dev/null
+++ b/man/toolAddThermal.Rd
@@ -0,0 +1,25 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/toolAddThermal.R
+\name{toolAddThermal}
+\alias{toolAddThermal}
+\title{Introduce refrigerators as appliances}
+\usage{
+toolAddThermal(df, mapping, fridgeShare, feOnly = TRUE, shareOf = NULL)
+}
+\arguments{
+\item{df}{data.frame}
+
+\item{mapping}{original EDGE-B region mapping}
+
+\item{fridgeShare}{regional shares of refrigerators}
+
+\item{feOnly}{are absolute values (TRUE) or shares (FALSE) considered?}
+
+\item{shareOf}{column name to calculate share of - must be given if feOnly = FALSE}
+}
+\description{
+Introduce refrigerators as appliances
+}
+\author{
+Hagen Tockhorn
+}
diff --git a/man/toolCalcShares.Rd b/man/toolCalcShares.Rd
new file mode 100644
index 0000000..98d7012
--- /dev/null
+++ b/man/toolCalcShares.Rd
@@ -0,0 +1,22 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/toolCalcShares.R
+\name{toolCalcShares}
+\alias{toolCalcShares}
+\title{Calculate Shares}
+\usage{
+toolCalcShares(df, colShare)
+}
+\arguments{
+\item{df}{data.frame}
+
+\item{colShare}{column to be grouped over}
+}
+\value{
+data.frame with calculated shares for colShare
+}
+\description{
+Calculate Shares
+}
+\author{
+Hagen Tockhorn
+}
diff --git a/man/toolDisaggregate.Rd b/man/toolDisaggregate.Rd
index 1db3798..24e0e1e 100644
--- a/man/toolDisaggregate.Rd
+++ b/man/toolDisaggregate.Rd
@@ -33,7 +33,7 @@ end uses in \code{enduseShares} are considered.}
 by carriers and end uses. The average distribution of its disaggregation
 will be used as the target distribution for the minisation.}
 
-\item{regionmapping}{data.frame with the columns \code{region} and
+\item{regionMapping}{data.frame with the columns \code{region} and
 \code{regionAgg} that maps the regions between \code{data} and
 \code{enduseShares}.}
 }