Fixes to KOR BUR4 reading

code/UNFCCC_reader/Republic_of_Korea/config_KOR_BUR4.py

@@ -315,7 +315,8 @@ remove_cats = [
     '5.B', '5.B.1', '5.B.2', '5.B.3', '5.B.4', '5.B.5',
     '5.C', '5.C.1', '5.C.2', '5.C.3', '5.C.4',
     '5.D', '5.D.1', '5.D.2', '5.D.3', '5.D.4',
-    '5.E', '5.F'
+    '5.E', '5.F',
+    '5.G', '5.B.6', # for 2021 NIR
 ]
 
 aggregate_before_mapping = {

code/UNFCCC_reader/Republic_of_Korea/read_KOR_2021-Inventory_from_xlsx.py

@@ -29,7 +29,7 @@ output_folder = extracted_data_path / 'non-UNFCCC' / 'Republic_of_Korea'
 if not output_folder.exists():
     output_folder.mkdir()
 
-output_filename = 'KOR_INV2021_2021_'
+output_filename = 'KOR_2021-Inventory_2021_'
 
 inventory_file = 'Republic_of_Korea_National_GHG_Inventory_(1990_2019).xlsx'
 years_to_read = range(1990, 2019 + 1)
@@ -303,11 +303,17 @@ for cat_to_agg in aggregate_after_mapping:
     else:
         print(f"no data to aggregate category {cat_to_agg}")
 
+
+#conversion to PRIMAP2 native format
+data_pm2_2006 = pm2.pm2io.from_interchange_format(data_if_2006)
+# convert back to IF to have units in the fixed format
+data_pm2_2006 = data_pm2_2006.reset_coords(["orig_cat_name", "cat_name_translation"],
+                                       drop=True)
+data_if_2006 = data_pm2_2006.pr.to_interchange_format()
 # save IPCC2006 data
 
 filter_data(data_if_2006, filter_remove=filter_remove_after_agg)
 pm2.pm2io.write_interchange_format(output_folder / (output_filename + coords_terminologies_2006["category"]), data_if_2006)
 
-data_pm2_2006 = pm2.pm2io.from_interchange_format(data_if)
 encoding = {var: compression for var in data_pm2_2006.data_vars}
 data_pm2_2006.pr.to_netcdf(output_folder / (output_filename + coords_terminologies_2006["category"] + ".nc"), encoding=encoding)