diff --git a/ConcordanceLibrary/EOL/EOL_RegionConcordance.xlsx b/ConcordanceLibrary/EOL/EOL_RegionConcordance.xlsx
index 43c8f80..68298b4 100644
Binary files a/ConcordanceLibrary/EOL/EOL_RegionConcordance.xlsx and b/ConcordanceLibrary/EOL/EOL_RegionConcordance.xlsx differ
diff --git a/ConcordanceLibrary/EXIOBASE/Source2Root_Region_EXIOBASE.csv b/ConcordanceLibrary/EXIOBASE/Source2Root_Region_EXIOBASE.csv
index 86f9b69..82b852d 100644
--- a/ConcordanceLibrary/EXIOBASE/Source2Root_Region_EXIOBASE.csv
+++ b/ConcordanceLibrary/EXIOBASE/Source2Root_Region_EXIOBASE.csv
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diff --git a/Rscripts/IEfeeds_code/IE_subroutines/IEDataProcessing_PIOLab_WasteMFAIOExtension.R b/Rscripts/IEfeeds_code/IE_subroutines/IEDataProcessing_PIOLab_WasteMFAIOExtension.R
index c222b5a..b802c98 100644
--- a/Rscripts/IEfeeds_code/IE_subroutines/IEDataProcessing_PIOLab_WasteMFAIOExtension.R
+++ b/Rscripts/IEfeeds_code/IE_subroutines/IEDataProcessing_PIOLab_WasteMFAIOExtension.R
@@ -72,8 +72,11 @@ IEDataProcessing_PIOLab_WasteMFAIOExtension <- function(year,path)
   # Load BACI trade flows 
   BACI <- read.csv(paste0(path$IE_Processed,"/BACI/BACI_",year,".csv"))
   
-  Flat_trade <- BACI %>% filter(Product == 8) %>% select(From,To,Quantity)
-  Long_trade <- BACI %>% filter(Product == 9) %>% select(From,To,Quantity)
+  Flat_trade <- BACI %>% filter(Product == base$product$Code[base$product$Name == "Flat rolled products"]) %>% 
+    select(From,To,Quantity)
+  
+  Long_trade <- BACI %>% filter(Product == base$product$Code[base$product$Name == "Long rolled products"]) %>% 
+    select(From,To,Quantity)
   
   # Estimate the net-use of products in countries
   Flat_import <- Flat_trade %>% group_by(To) %>% summarise(Quantity = sum(Quantity))
diff --git a/Rscripts/IEfeeds_code/IE_subroutines/IEFeed_PIOLab_EOL.R b/Rscripts/IEfeeds_code/IE_subroutines/IEFeed_PIOLab_EOL.R
index c51eba6..91338a2 100644
--- a/Rscripts/IEfeeds_code/IE_subroutines/IEFeed_PIOLab_EOL.R
+++ b/Rscripts/IEfeeds_code/IE_subroutines/IEFeed_PIOLab_EOL.R
@@ -29,6 +29,9 @@ IEFeed_PIOLab_EOL <- function(year,path)
   path_set <- paste0(path$IE_Processed,"/EOL")
   if(!dir.exists(path_set)) dir.create(path_set)
   
+  # Remove NaN (Bermudas & Kosovo for until we have a new root classification)
+  data_clean <- data_clean[!is.na(data_clean$base),]
+  
   write.csv(data_clean,
             file = paste0(path_set,"/EOL_",year,".csv"),
             row.names = FALSE)
diff --git a/Rscripts/IEfeeds_code/IE_subroutines/IEFeed_PIOLab_WSA.R b/Rscripts/IEfeeds_code/IE_subroutines/IEFeed_PIOLab_WSA.R
index f7fc862..a8a8fd1 100644
--- a/Rscripts/IEfeeds_code/IE_subroutines/IEFeed_PIOLab_WSA.R
+++ b/Rscripts/IEfeeds_code/IE_subroutines/IEFeed_PIOLab_WSA.R
@@ -16,6 +16,10 @@ IEFeed_PIOLab_WSA <- function(year,path)
   # Load function to align data with root classification
   source(paste0(path$Subroutines,"/Read_ProductionWSA.R"))
   
+  # Load region aggregator and look up base table codes
+  source(paste0(path$Subroutines,"/Root2Base_RegionAggregator.R"))
+  reg_agg <- Root2Base_RegionAggregator(RegionAggregator)
+  
   # Loop over selected items 
   for(i in 1:length(items))
   {
@@ -25,10 +29,6 @@ IEFeed_PIOLab_WSA <- function(year,path)
     # Read values and align with root classification
     data_clean <- Read_ProductionWSA(path,year,item_page,yb,concord)
       
-    # Load region aggregator and look up base table codes
-    source(paste0(path$Subroutines,"/Root2Base_RegionAggregator.R"))
-    reg_agg <- Root2Base_RegionAggregator(RegionAggregator)
-    
     data_clean <- left_join(data_clean,reg_agg,by = c("Code" = "root"),copy = FALSE) %>% select(base,Quantity)
     data_clean <- data_clean %>% group_by(base) %>% summarise(Quantity = sum(Quantity))
     
diff --git a/Rscripts/IEfeeds_code/Ind20Pro22v1_InitialEstimate.R b/Rscripts/IEfeeds_code/Ind20Pro22v1_InitialEstimate.R
index c3dea93..80fa928 100644
--- a/Rscripts/IEfeeds_code/Ind20Pro22v1_InitialEstimate.R
+++ b/Rscripts/IEfeeds_code/Ind20Pro22v1_InitialEstimate.R
@@ -170,4 +170,4 @@ if(file.exists(path$mother))
   write.table(ALANG,file = filename,row.names = FALSE, quote = F,sep = "\t") 
 }
   
-print(paste0("End of ",IEdatafeed_name," InitialEstimate."))
\ No newline at end of file
+print(paste0("End of ",IEdatafeed_name," InitialEstimate."))
diff --git a/Rscripts/Subroutines/Read_ProductionWSA.R b/Rscripts/Subroutines/Read_ProductionWSA.R
index 47a5741..658e649 100644
--- a/Rscripts/Subroutines/Read_ProductionWSA.R
+++ b/Rscripts/Subroutines/Read_ProductionWSA.R
@@ -74,7 +74,8 @@ Read_ProductionWSA <- function(path,year,item_page,yb,concord)
     select(-countries,-index)
   colnames(data_clean)[2] <- "Quantity"
   # Look up root classification code and filter specific year
-  data_clean <- left_join(data_clean,root$region,by = c("ISO3digitCode"),copy = FALSE) %>% select(Code,Quantity)
+  data_clean <- left_join(data_clean,root$region,by = c("ISO3digitCode" = "RootCountryAbbreviation"),copy = FALSE) %>% 
+    select(Code,Quantity)
   # Translate quantities into metric tons
   data_clean$Quantity <- data_clean$Quantity * 1000
   
diff --git a/Rscripts/datafeeds_code/datafeed_PIOLab_IRPextraction.R b/Rscripts/datafeeds_code/datafeed_PIOLab_IRPextraction.R
index 912981b..445bf10 100644
--- a/Rscripts/datafeeds_code/datafeed_PIOLab_IRPextraction.R
+++ b/Rscripts/datafeeds_code/datafeed_PIOLab_IRPextraction.R
@@ -22,6 +22,9 @@ source(paste0(path$Subroutines,"/SE_LogRegression.R"))
 RSE <- filter(read.xlsx(path$RSE_settings),Item == datafeed_name)
 data <- SE_LogRegression(data,RSE$Minimum,RSE$Maximum)
 
+# Create identity matrix to be used as concordance when doing t command 
+Concord <- diag(length(root$region$Code))
+
 # Create empty ALANG table with header
 source(paste0(path$Subroutines,"/makeALANGheadline.R"))
 # Extend table with additional columns
@@ -32,31 +35,49 @@ for(i in 1:nrow(data))
   reg_num <- data$Code[i]
   reg_name <- as.character(root$region$Name[reg_num])
   reg_num <- as.character(reg_num)
+  
   # Read extraction value
-  value <- as.character(data$Quantity[i])
+  value <- paste0("[",data$Quantity[i],";","NaN","]")
   # Set SE
-  SE <- as.character(data$SE[i]) 
+  SE <-  paste0("[",as.character(data$SE[i]),";","NaN","]") 
   
   # Add command for domestic Use table
   ALANG <- add_row(ALANG,'1' = paste0("DataFeed IRP Extraction ",reg_name),
                    Value = value,'Row parent' = reg_num,'Column parent' = reg_num,S.E. = SE)
 }
+
+# Add NaN to all other regions
+for(i in setdiff(root$region$Code,data$Code))
+{ 
+  # Get root_code of region 
+  reg_num <- root$region$Code[i]
+  reg_name <- as.character(root$region$Name[reg_num])
+  reg_num <- as.character(reg_num)
+  
+  # Read extraction value
+  value <- SE <- paste0("[NaN;NaN]")
+  
+  # Add command for domestic Use table
+  ALANG <- add_row(ALANG,'1' = paste0("DataFeed IRP Extraction ",reg_name),
+                   Value = value,'Row parent' = reg_num,'Column parent' = reg_num,S.E. = SE)
+}
+
 # Add other variables
 
-# Create product concordance 
-Concord <-  matrix(0,nrow = 1, ncol = length(root$product$Code))
-Concord[1,1:5] <- 1
+# Create industry concordance 
+max_ind <- length(root$industry$Code)
+Concord <-  matrix(0,nrow = 2, ncol = max_ind)
+Concord[1,1:4] <- 1
+Concord[2,5:max_ind] <- 1
 
 # Write to folder
-Concord_path <- paste0(path$Concordance,"/IRPextraction_concordance.csv")
+Concord_path <- paste0(path$Concordance,"/IRPextraction_Sec_Concordance.csv")
 write.table(Concord,file = Concord_path,row.names = FALSE,col.names = FALSE,sep = ",")
 
-# Create extension conocrdane 
-
 ALANG$`Row child` <- "3"
 ALANG$`Row grandchild` <- "1"
 ALANG$`Column child` <- "1"
-ALANG$`Column grandchild` <- "1:e t2 CONCPATH/IRPextraction_concordance.csv"
+ALANG$`Column grandchild` <- "1:e t1 CONCPATH/IRPextraction_Sec_Concordance.csv"
 ALANG$`#` <- as.character(1:nrow(ALANG))
 ALANG$Incl <- "Y"
 ALANG$Parts <- "1"
@@ -72,4 +93,4 @@ ALANG$Coef1 <- "1"
 source(paste0(path$root,"Rscripts/datafeeds_code/datafeed_subroutines/WriteALANG2Folder.R"))
   
 print(paste0("datafeed_PIOLab_",datafeed_name," finished."))
-  
+