diff --git a/conf/hermes.conf b/conf/hermes.conf
index c79b872dc0b632bd232b66bf8dce848408cd7f66..0a85af5d194f0a134b92e1997a433a046661a126 100755
--- a/conf/hermes.conf
+++ b/conf/hermes.conf
@@ -3,7 +3,7 @@ log_level = 3
 input_dir = /home/Earth/ctena/Models/hermesv3_bu_data
 data_path = /esarchive/recon
 output_dir = /scratch/Earth/HERMESv3_BU_OUT
-output_name = HERMESv3_<date>_aviation.nc
+output_name = HERMESv3_<date>_TRATRA_old_1_1.nc
 emission_summary = 0
 start_date = 2016/11/29 00:00:00
 # ----- end_date = start_date [DEFAULT] -----
@@ -130,7 +130,7 @@ writing_processors = 1
 # traffic_processors = 256
 # traffic_area_processors = 1
 
-aviation_processors = 1
+aviation_processors = 0
 shipping_port_processors = 0
 livestock_processors = 0
 crop_operations_processors = 0
@@ -140,7 +140,7 @@ residential_processors = 0
 recreational_boats_processors = 0
 point_sources_processors = 0
 traffic_processors = 0
-traffic_area_processors = 0
+traffic_area_processors = 1
 
 
 [SHAPEFILES]
diff --git a/hermesv3_bu/io_server/io_netcdf.py b/hermesv3_bu/io_server/io_netcdf.py
index a102d83ea3938d9fe0abc8af95cf3f4885beb751..ed44f4a42ef08af429eeadb28a0e2816b5b58269 100755
--- a/hermesv3_bu/io_server/io_netcdf.py
+++ b/hermesv3_bu/io_server/io_netcdf.py
@@ -122,6 +122,7 @@ class IoNetcdf(IoServer):
         try:
             lat_o = nc.variables['latitude'][:]
             lon_o = nc.variables['longitude'][:]
+            n_lat = len(lat_o)
             time = nc.variables['time']
         except KeyError as e:
             error_exit("{0} variable not found in {1} file.".format(str(e), path))
@@ -143,7 +144,7 @@ class IoNetcdf(IoServer):
         # From 1D to 2D
         lat = np.array([lat_o[:]] * len(lon_o[:])).T.flatten()
         lon = np.array([lon_o[:]] * len(lat_o[:])).flatten()
-        del lat_o, lon_o
+        # del lat_o, lon_o
 
         # Reads the var variable of the xone and the times needed.
         try:
@@ -173,7 +174,7 @@ class IoNetcdf(IoServer):
         var = var.reshape((var.shape[0], var.shape[1] * var.shape[2]))
         df = gpd.GeoDataFrame(var.T, geometry=[Point(xy) for xy in zip(lon, lat)])
         # df.columns = ['t_{0}'.format(x) for x in df.columns.values[:-1]] + ['geometry']
-        df.loc[:, 'REC'] = df.index
+        df.loc[:, 'REC'] = (((df.index // len(lon_o)) + j_min) * n_lat) + ((df.index % len(lon_o)) + i_min)
 
         return df