diff --git a/dev/Untitled1.ipynb b/dev/Untitled1.ipynb
index ad7f18a3..57671bf9 100644
--- a/dev/Untitled1.ipynb
+++ b/dev/Untitled1.ipynb
@@ -91,6 +91,7 @@
     "        #{\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2010},\n",
     "        #{\"model\":\"image\", \"pathway\":\"SSP2-Base\", \"year\":2020},\n",
     "        #{\"model\":\"image\", \"pathway\":\"SSP2-Base\", \"year\":2050},\n",
+    "        {\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2048},\n",
     "        {\"model\":\"remind\", \"pathway\":\"SSP2-Base\", \"year\":2050},\n",
     "        #{\"model\":\"image\", \"pathway\":\"SSP2-Base\", \"year\":2060},\n",
     "        #{\"model\":\"image\", \"pathway\":\"SSP2-Base\", \"year\":2050},\n",
@@ -110,7 +111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "a324c189-26bd-4a65-885c-bba4683e9ed1",
    "metadata": {},
    "outputs": [
@@ -118,15 +119,34 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Processing scenarios: 100%|█████████████| 2/2 [00:16<00:00,  8.10s/it]"
+      "Processing scenarios:   0%|                     | 0/2 [00:00<?, ?it/s]"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Done!\n",
-      "\n"
+      "{2020: {'min': 160, 'max': 383, 'mean': 272}, 2030: {'min': 134, 'max': 300, 'mean': 217}, 2040: {'min': 120, 'max': 267, 'mean': 194}, 2050: {'min': 108, 'max': 236, 'mean': 172}}\n",
+      "{2020: {'min': 272, 'max': 639, 'mean': 456}, 2030: {'min': 203, 'max': 479, 'mean': 341}, 2040: {'min': 182, 'max': 479, 'mean': 330}, 2050: {'min': 168, 'max': 370, 'mean': 269}}\n",
+      "{2020: {'min': 394, 'max': 1110, 'mean': 752}, 2030: {'min': 323, 'max': 802, 'mean': 562}, 2040: {'min': 296, 'max': 726, 'mean': 511}, 2050: {'min': 273, 'max': 666, 'mean': 470}}\n",
+      "{2020: {'min': 509, 'max': 1291, 'mean': 900}, 2030: {'min': 390, 'max': 978, 'mean': 684}, 2040: {'min': 362, 'max': 906, 'mean': 634}, 2050: {'min': 360, 'max': 845, 'mean': 603}}\n",
+      "{2020: {'min': 660, 'max': 1515, 'mean': 1088}, 2030: {'min': 550, 'max': 1207, 'mean': 879}, 2040: {'min': 530, 'max': 1124, 'mean': 827}, 2050: {'min': 490, 'max': 1038, 'mean': 764}}\n",
+      "{2020: {'min': 665, 'max': 1542, 'mean': 1104}, 2030: {'min': 550, 'max': 1200, 'mean': 875}, 2040: {'min': 530, 'max': 1123, 'mean': 826}, 2050: {'min': 490, 'max': 1067, 'mean': 779}}\n",
+      "{2020: {'min': 835, 'max': 1804, 'mean': 1320}, 2030: {'min': 670, 'max': 1349, 'mean': 1010}, 2040: {'min': 630, 'max': 1255, 'mean': 942}, 2050: {'min': 603, 'max': 1188, 'mean': 896}}\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Processing scenarios:  50%|██████▌      | 1/2 [00:13<00:13, 13.59s/it]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{2020: {'min': 160, 'max': 383, 'mean': 272}, 2030: {'min': 134, 'max': 300, 'mean': 217}, 2040: {'min': 120, 'max': 267, 'mean': 194}, 2050: {'min': 108, 'max': 236, 'mean': 172}}\n"
      ]
     },
     {
@@ -135,10 +155,26 @@
      "text": [
       "\n"
      ]
+    },
+    {
+     "ename": "KeyError",
+     "evalue": "'min'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[5], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mndb\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupdate\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtrucks\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/Github/premise/premise/new_database.py:963\u001b[0m, in \u001b[0;36mNewDatabase.update\u001b[0;34m(self, sectors)\u001b[0m\n\u001b[1;32m    961\u001b[0m update_func \u001b[38;5;241m=\u001b[39m sector_update_methods[sector][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfunc\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m    962\u001b[0m fixed_args \u001b[38;5;241m=\u001b[39m sector_update_methods[sector][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124margs\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[0;32m--> 963\u001b[0m scenario \u001b[38;5;241m=\u001b[39m \u001b[43mupdate_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mscenario\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mfixed_args\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    965\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mapplied functions\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m scenario:\n\u001b[1;32m    966\u001b[0m     scenario[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mapplied functions\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m []\n",
+      "File \u001b[0;32m~/Github/premise/premise/transport.py:52\u001b[0m, in \u001b[0;36m_update_vehicles\u001b[0;34m(scenario, vehicle_type, version, system_model)\u001b[0m\n\u001b[1;32m     49\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m     50\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mUnknown vehicle type.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m---> 52\u001b[0m trspt \u001b[38;5;241m=\u001b[39m \u001b[43mTransport\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     53\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdatabase\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mscenario\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mdatabase\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     54\u001b[0m \u001b[43m    \u001b[49m\u001b[43myear\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mscenario\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43myear\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     55\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmodel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mscenario\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmodel\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     56\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpathway\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mscenario\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mpathway\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     57\u001b[0m \u001b[43m    \u001b[49m\u001b[43miam_data\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mscenario\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43miam data\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     58\u001b[0m \u001b[43m    \u001b[49m\u001b[43mversion\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mversion\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     59\u001b[0m \u001b[43m    \u001b[49m\u001b[43msystem_model\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msystem_model\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     60\u001b[0m \u001b[43m    \u001b[49m\u001b[43mvehicle_type\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mvehicle_type\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     61\u001b[0m \u001b[43m    \u001b[49m\u001b[43mrelink\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m     62\u001b[0m \u001b[43m    \u001b[49m\u001b[43mhas_fleet\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mhas_fleet\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     63\u001b[0m \u001b[43m    \u001b[49m\u001b[43mindex\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mscenario\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mindex\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     64\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     66\u001b[0m scenario[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdatabase\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m trspt\u001b[38;5;241m.\u001b[39mdatabase\n\u001b[1;32m     67\u001b[0m scenario[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcache\u001b[39m\u001b[38;5;124m\"\u001b[39m] \u001b[38;5;241m=\u001b[39m trspt\u001b[38;5;241m.\u001b[39mcache\n",
+      "File \u001b[0;32m~/Github/premise/premise/transport.py:397\u001b[0m, in \u001b[0;36mTransport.__init__\u001b[0;34m(self, database, iam_data, model, pathway, year, version, system_model, relink, vehicle_type, has_fleet, index)\u001b[0m\n\u001b[1;32m    394\u001b[0m         \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mVehicle map is empty for \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mvehicle_type\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    396\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhas_fleet:\n\u001b[0;32m--> 397\u001b[0m     fleet_datasets \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate_vehicle_markets\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    398\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdatabase\u001b[38;5;241m.\u001b[39mextend(fleet_datasets)\n\u001b[1;32m    399\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39madd_to_index(fleet_datasets)\n",
+      "File \u001b[0;32m~/Github/premise/premise/transport.py:485\u001b[0m, in \u001b[0;36mTransport.create_vehicle_markets\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    478\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mvehicle_type \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtruck\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    479\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m ds \u001b[38;5;129;01min\u001b[39;00m ws\u001b[38;5;241m.\u001b[39mget_many(\n\u001b[1;32m    480\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdatabase,\n\u001b[1;32m    481\u001b[0m         ws\u001b[38;5;241m.\u001b[39mcontains(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mname\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mbattery electric\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m    482\u001b[0m         ws\u001b[38;5;241m.\u001b[39mcontains(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mname\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtruck\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m    483\u001b[0m         ws\u001b[38;5;241m.\u001b[39mequals(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124munit\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124munit\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m    484\u001b[0m     ):\n\u001b[0;32m--> 485\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43madjust_battery_size\u001b[49m\u001b[43m(\u001b[49m\u001b[43mds\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    487\u001b[0m \u001b[38;5;66;03m# if trucks, need to reconnect everything\u001b[39;00m\n\u001b[1;32m    488\u001b[0m \u001b[38;5;66;03m# loop through datasets that use truck transport\u001b[39;00m\n\u001b[1;32m    489\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mvehicle_type \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtruck\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n",
+      "File \u001b[0;32m~/Github/premise/premise/transport.py:646\u001b[0m, in \u001b[0;36mTransport.adjust_battery_size\u001b[0;34m(self, ds)\u001b[0m\n\u001b[1;32m    642\u001b[0m     max_battery_size \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbattery_size[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtruck\u001b[39m\u001b[38;5;124m\"\u001b[39m][size][\n\u001b[1;32m    643\u001b[0m         \u001b[38;5;28mmin\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbattery_size[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtruck\u001b[39m\u001b[38;5;124m\"\u001b[39m][size][\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39myear]\u001b[38;5;241m.\u001b[39mkeys())\n\u001b[1;32m    644\u001b[0m     ][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmax\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m    645\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39myear \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;28mmax\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbattery_size[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtruck\u001b[39m\u001b[38;5;124m\"\u001b[39m][size]\u001b[38;5;241m.\u001b[39mkeys()):\n\u001b[0;32m--> 646\u001b[0m     mean_battery_size \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbattery_size\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtruck\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[43msize\u001b[49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\n\u001b[1;32m    647\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mmax\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbattery_size\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtruck\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[43msize\u001b[49m\u001b[43m]\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43myear\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkeys\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    648\u001b[0m \u001b[43m    \u001b[49m\u001b[43m]\u001b[49m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmean\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m    649\u001b[0m     min_battery_size \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbattery_size[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtruck\u001b[39m\u001b[38;5;124m\"\u001b[39m][size][\n\u001b[1;32m    650\u001b[0m         \u001b[38;5;28mmax\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbattery_size[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtruck\u001b[39m\u001b[38;5;124m\"\u001b[39m][size][\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39myear]\u001b[38;5;241m.\u001b[39mkeys())\n\u001b[1;32m    651\u001b[0m     ][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmin\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n\u001b[1;32m    652\u001b[0m     max_battery_size \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbattery_size[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtruck\u001b[39m\u001b[38;5;124m\"\u001b[39m][size][\n\u001b[1;32m    653\u001b[0m         \u001b[38;5;28mmax\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbattery_size[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtruck\u001b[39m\u001b[38;5;124m\"\u001b[39m][size][\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39myear][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmax\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mkeys())\n\u001b[1;32m    654\u001b[0m     ][\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmax\u001b[39m\u001b[38;5;124m\"\u001b[39m]\n",
+      "\u001b[0;31mKeyError\u001b[0m: 'min'"
+     ]
     }
    ],
    "source": [
-    "ndb.update()"
+    "ndb.update(\"trucks\")"
    ]
   },
   {
diff --git a/premise/data/additional_inventories/lci-trucks.xlsx b/premise/data/additional_inventories/lci-trucks.xlsx
index a6148b1f..c1f86834 100644
Binary files a/premise/data/additional_inventories/lci-trucks.xlsx and b/premise/data/additional_inventories/lci-trucks.xlsx differ
diff --git a/premise/electricity.py b/premise/electricity.py
index 4aca29db..c57cb6ee 100644
--- a/premise/electricity.py
+++ b/premise/electricity.py
@@ -1442,69 +1442,81 @@ def update_efficiency_of_solar_pv(self) -> None:
             if len(pv_tech) > 0:
                 pv_tech = pv_tech[0]
 
-            for exc in ws.technosphere(
-                dataset,
-                ws.contains("name", "photovoltaic"),
-                ws.equals("unit", "square meter"),
-            ):
-                surface = float(exc["amount"])
-                max_power = surface  # in kW, since we assume a constant 1,000W/m^2
-                current_eff = power / max_power
-
-                if self.year in module_eff.coords["year"].values:
-                    new_mean_eff = module_eff.sel(
-                        technology=pv_tech, year=self.year, efficiency_type="mean"
-                    ).values
-                    new_min_eff = module_eff.sel(
-                        technology=pv_tech, year=self.year, efficiency_type="min"
-                    ).values
-                    new_max_eff = module_eff.sel(
-                        technology=pv_tech, year=self.year, efficiency_type="max"
-                    ).values
-                else:
-                    new_mean_eff = (
-                        module_eff.sel(technology=pv_tech, efficiency_type="mean")
-                        .interp(year=self.year, kwargs={"fill_value": "extrapolate"})
-                        .values
-                    )
-                    new_min_eff = (
-                        module_eff.sel(technology=pv_tech, efficiency_type="min")
-                        .interp(year=self.year, kwargs={"fill_value": "extrapolate"})
-                        .values
-                    )
-                    new_max_eff = (
-                        module_eff.sel(technology=pv_tech, efficiency_type="max")
-                        .interp(year=self.year, kwargs={"fill_value": "extrapolate"})
-                        .values
-                    )
+            if pv_tech:
 
-                # in case self.year <10 or >2050
-                new_mean_eff = np.clip(new_mean_eff, 0.1, 0.30)
-                new_min_eff = np.clip(new_min_eff, 0.1, 0.30)
-                new_max_eff = np.clip(new_max_eff, 0.1, 0.30)
-
-                # We only update the efficiency if it is higher than the current one.
-                if new_mean_eff.sum() > current_eff:
-                    exc["amount"] *= float(current_eff / new_mean_eff)
-                    exc["uncertainty type"] = 5
-                    exc["loc"] = exc["amount"]
-                    exc["minimum"] = exc["amount"] * (new_min_eff / new_mean_eff)
-                    exc["maximum"] = exc["amount"] * (new_max_eff / new_mean_eff)
-
-                    dataset["comment"] = (
-                        f"`premise` has changed the efficiency "
-                        f"of this photovoltaic installation "
-                        f"from {int(current_eff * 100)} pct. to {int(new_mean_eff * 100)} pt."
-                    )
+                for exc in ws.technosphere(
+                    dataset,
+                    ws.contains("name", "photovoltaic"),
+                    ws.equals("unit", "square meter"),
+                ):
+                    surface = float(exc["amount"])
+                    max_power = surface  # in kW, since we assume a constant 1,000W/m^2
+                    current_eff = power / max_power
+
+                    if self.year in module_eff.coords["year"].values:
+                        new_mean_eff = module_eff.sel(
+                            technology=pv_tech, year=self.year, efficiency_type="mean"
+                        ).values
+                        new_min_eff = module_eff.sel(
+                            technology=pv_tech, year=self.year, efficiency_type="min"
+                        ).values
+                        new_max_eff = module_eff.sel(
+                            technology=pv_tech, year=self.year, efficiency_type="max"
+                        ).values
+                    else:
+                        new_mean_eff = (
+                            module_eff.sel(technology=pv_tech, efficiency_type="mean")
+                            .interp(
+                                year=self.year, kwargs={"fill_value": "extrapolate"}
+                            )
+                            .values
+                        )
+                        new_min_eff = (
+                            module_eff.sel(technology=pv_tech, efficiency_type="min")
+                            .interp(
+                                year=self.year, kwargs={"fill_value": "extrapolate"}
+                            )
+                            .values
+                        )
+                        new_max_eff = (
+                            module_eff.sel(technology=pv_tech, efficiency_type="max")
+                            .interp(
+                                year=self.year, kwargs={"fill_value": "extrapolate"}
+                            )
+                            .values
+                        )
 
-                    if "log parameters" not in dataset:
-                        dataset["log parameters"] = {}
+                    # in case self.year <10 or >2050
+                    new_mean_eff = np.clip(new_mean_eff, 0.1, 0.30)
+                    new_min_eff = np.clip(new_min_eff, 0.1, 0.30)
+                    new_max_eff = np.clip(new_max_eff, 0.1, 0.30)
+
+                    # We only update the efficiency if it is higher than the current one.
+                    if new_mean_eff.sum() >= current_eff:
+                        exc["amount"] *= float(current_eff / new_mean_eff)
+                        exc["uncertainty type"] = 5
+                        exc["loc"] = exc["amount"]
+                        exc["minimum"] = exc["amount"] * (new_min_eff / new_mean_eff)
+                        exc["maximum"] = exc["amount"] * (new_max_eff / new_mean_eff)
+
+                        dataset["comment"] = (
+                            f"`premise` has changed the efficiency "
+                            f"of this photovoltaic installation "
+                            f"from {int(current_eff * 100)} pct. to {int(new_mean_eff * 100)} pt."
+                        )
 
-                    dataset["log parameters"].update({"old efficiency": current_eff})
-                    dataset["log parameters"].update({"new efficiency": new_mean_eff})
+                        if "log parameters" not in dataset:
+                            dataset["log parameters"] = {}
 
-                    # add to log
-                    self.write_log(dataset=dataset, status="updated")
+                        dataset["log parameters"].update(
+                            {"old efficiency": current_eff}
+                        )
+                        dataset["log parameters"].update(
+                            {"new efficiency": new_mean_eff}
+                        )
+
+                        # add to log
+                        self.write_log(dataset=dataset, status="updated")
 
     def create_region_specific_power_plants(self):
         """