tutorial/westeros/westeros_carbon_removal.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3ce427fd",
   "metadata": {},
   "source": [
    "# Westeros tutorial - Adding DACCS in climate mitigation scenario\n",
    "In the previous tutorials, we have learnt how to create a baseline scenario (`westeros_baseline.ipynb`) and add emissions bounds (`westeros_emissions_bounds.ipynb`) to the baseline scenario. Here, we will show how to include an additional/new technology to a MESSAGE model. While the combination of currently existing technologies might be able to deliver the Paris targets, the deployment of some new technologies might improve the probability of meeting the targets and/or reducing the costs. These technologies include CO2 removal (CDR) technologies. Hence, in this tutorial, we will use direct air carbon capture and storage (DACCS) as an example of new technologies to be considered in climate mitigation pathways. \n",
    "\n",
    "In order to smoothly follow this tutorial, you have to alrady have the MESSAGEix framework installed and working. Additionally, you should have run the Westeros baseline and emissions bounds scenarios successfully as this tutorial is built on top of those scenarios.\n",
    "\n",
    "If all set, we can start by importing all the packages we need and connect to a database that store the scenario input and results. We can also name the model as `Westeros Electrified` here.\n",
    "\n",
    "In this tutorial, we will use add_dac tool which requires user to specify the location of the data, in yaml format. As such, we use os package to help us specifying the yaml file.\n",
    "\n",
    "## Requirements\n",
    "\n",
    "This tutorial requires that you have run `westeros_emissions_bounds.ipynb` and have [`message-ix-models`](https://github.com/iiasa/message-ix-models) installed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "239a17a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "import pandas as pd\n",
    "import ixmp\n",
    "import message_ix\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "\n",
    "from message_ix.utils import make_df\n",
    "import message_ix_models.model.dac as dac\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "%matplotlib inline\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "57257989",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "mp = ixmp.Platform()\n",
    "\n",
    "model = \"Westeros Electrified\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c82f18ff",
   "metadata": {},
   "source": [
    "After we are connected to the database, we can call the prevously run `\"emission_bound\"` scenario as our base model and clone the data before we start adding DACCS to the model. As prevoiusly mentioned, to run this tutorial, you have to have succesfully run the `\"emission_bound\"` scenario, which was built based on the `\"baseline\"` scenario."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9a868ad2",
   "metadata": {},
   "outputs": [],
   "source": [
    "base = message_ix.Scenario(mp, model=model, scenario=\"emission_bound\")\n",
    "\n",
    "scenario = base.clone(\n",
    "    model,\n",
    "    \"emission_bound_daccs\",\n",
    "    \"adding daccs using add_dac tool\",\n",
    "    keep_solution=False,)\n",
    "scenario.check_out()\n",
    "\n",
    "year_df = scenario.vintage_and_active_years()\n",
    "vintage_years, act_years = year_df[\"year_vtg\"], year_df[\"year_act\"]\n",
    "model_horizon = scenario.set(\"year\")\n",
    "country = \"Westeros\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b5db71ca",
   "metadata": {},
   "source": [
    "# Adding DACCS description\n",
    "First step of adding DACCS as a technology in the model is by including DACCS into the `\"technology\"` set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3b203192",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "mp.add_unit(\"USD/(tCO2/yr)\")\n",
    "mp.add_unit(\"USD/(tCO2/yr)/yr\")\n",
    "mp.add_unit(\"USD/tCO2\")\n",
    "mp.add_unit(\"tCO2/tCO2\")\n",
    "mp.add_unit(\"tCO2\")\n",
    "mp.add_unit(\"Mt CO2/yr\")\n",
    "\n",
    "\n",
    "filepath = os.path.join(os.getcwd(), \"data/westeros_carbon_removal_data.yaml\")\n",
    "dac.add_dac(scenario, filepath=filepath)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "017c5ca3",
   "metadata": {},
   "source": [
    "Similar to what we did when generating the `\"baseline\"` scenario, the first thing we need to do is defining the input and output comodities of each technology. "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "54cc0111",
   "metadata": {},
   "source": [
    "# Solve Statement\n",
    "Finally, this is the solve statement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3131e0dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Objective value:  196353.921875\n"
     ]
    }
   ],
   "source": [
    "scenario.commit(comment=\"Adding daccs using add_dac tool\")\n",
    "scenario.set_as_default()\n",
    "\n",
    "scenario.solve()\n",
    "scenario.var(\"OBJ\")[\"lvl\"]\n",
    "\n",
    "print('Objective value: ', scenario.var(\"OBJ\")[\"lvl\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dad6cedb",
   "metadata": {},
   "source": [
    "# Plotting Results and Compare\n",
    "Finally, this is the plotting results command to compare emissions bound scenarios with and without DACCS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "19e29174",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "# Create a Reporter object to describe and carry out reporting\n",
    "# calculations and operations (like plotting) based on `scenario`\n",
    "# Add keys like \"plot activity\" to describe reporting operations.\n",
    "# See tutorial/utils/plotting.py\n",
    "from message_ix.report import Reporter\n",
    "from message_ix.util.tutorial import prepare_plots\n",
    "\n",
    "rep_ori = Reporter.from_scenario(base)\n",
    "rep_new = Reporter.from_scenario(scenario)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb382f4d",
   "metadata": {},
   "source": [
    "## System acticity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ea31acff",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Without DACCS\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "With DACCS\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Without DACCS\")\n",
    "prepare_plots(rep_ori)\n",
    "rep_ori.set_filters(t=[\"coal_ppl\", \"wind_ppl\"])\n",
    "rep_ori.get(\"plot activity\")\n",
    "plt.show()\n",
    "\n",
    "print(\"With DACCS\")\n",
    "prepare_plots(rep_new)\n",
    "rep_new.set_filters(t=[\"coal_ppl\", \"wind_ppl\"])\n",
    "rep_new.get(\"plot activity\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f28be730",
   "metadata": {},
   "source": [
    "### DACCS Capacity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "803233f0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prepare_plots(rep_new)\n",
    "rep_new.set_filters(t=[\"daccs\"])\n",
    "rep_new.get(\"plot removal capacity\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d03f4f74",
   "metadata": {},
   "source": [
    "## Emissions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "76423c69",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Without DACCS\n"
     ]
    },
    {
     "data": {
      "image/png": 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tdenSReHh4Vq8eLF5NbFSpUq67777tHjxYo0ZM0affvqpsrKy7K7m2mw2ffrpp9q6dauWL1+uVatW6YknntCMGTO0devWyy6flX/chg0bpqioqELH/D3EF/WzKKzdKMUvYl1uO1c6P4pypfP3Wo7tte5TceoHUP4Irbiu/HW91s2bN9t9hNmkSRO5u7vr22+/VWJiojp37mz21apVS4ZhqGbNmqpdu/YVt9OgQQM1aNBAL730krZs2aKWLVvq7bff1qRJkyTJ7uPEfAEBAapYsaJyc3PVvn37Eu1fWFiYJOngwYMFrhoePHjQ7P/rfj3//PN6/vnndejQITVq1EgzZszQBx98UKLtl0T+l9B8fHyueb9/+eUXu6uwp06dKvSK17333quAgAAtXrxYzZo10/nz59W7d+8SbVu69AWvSpUq6Y8//rBr79Onj+6//35t375dixcvVuPGjVWvXr0Cr2/evLmaN2+ul19+WUuWLFGvXr300Ucf6cknnyz0XMnfpiS5urqW+Lhd74pz/l7u2P5dQECAvLy8dPDgwQJ9P/30k5ycnApclQZw/WB6AK4rTZs2Necz/v7773ZXWt3d3XX77bcrPj5emZmZduuzPvjgg3J2dtb48eMLXEExDEOnTp2SdGmtzpycHLv+Bg0ayMnJye5jSW9vb6WlpdmNc3Z2VnR0tJYtW6Yff/yxQO3FWUanadOmCgwM1Ntvv223vZUrV+rAgQPq0qWLpEsL1v/1W/XSpQBQsWLFYn00XZqaNGmiWrVq6dVXXy30jlLF2e927drJxcVFc+bMsWt/6623Ch3v4uKinj176pNPPtGCBQvUoEGDAlexC5OYmKjMzMwC7du2bdOpU6cKfKzcqVMnValSRdOmTdPGjRsLzJk9c+ZMgfMp/2pz/s/By8tLkgqcL4GBgWrTpo3eeeedAmFZKt5xu14V5/wtzrH9O2dnZ3Xs2FH/+c9/7JbOSklJ0ZIlS9SqVSv5+PiU3o4AKFdcacV1xc3NTXfccYe+//57ubu7q0mTJnb9LVq0MNeI/GtorVWrliZNmqRRo0bp6NGj6tatmypWrKgjR47o888/14ABAzRs2DCtX79egwYN0sMPP6zatWsrJydHixYtMgNpviZNmmjt2rV67bXXzBsfNGvWTFOnTtWGDRvUrFkz9e/fXxERETp9+rR27typtWvXFrrM1F+5urpq2rRp6tu3r1q3bq2ePXuaS17VqFHDXObp559/Vrt27dS9e3dFRETIxcVFn3/+uVJSUop9B7BPP/200I9YO3TooKCgoGK9hyQ5OTnpvffeU6dOnVSvXj317dtXN910k37//Xdt2LBBPj4+Wr58+WXfIygoSEOGDNGMGTP0//7f/9O9996rPXv2aOXKlapSpUqhVyv79OmjN954Qxs2bNC0adOKVeuiRYu0ePFiPfDAA2rSpInc3Nx04MABvf/++/Lw8NC//vUvu/Gurq7q0aOH3nrrLTk7O6tnz552/QsXLtTs2bP1wAMPqFatWjp79qzeffdd+fj4mFf6PT09FRERoY8//li1a9eWv7+/6tevr/r16ys+Pl6tWrVSgwYN1L9/f918881KSUlRQkKCfvvtN+3Zs6dY+3Ut0tPTi7wyX1Y3HSjO+VucY1uYSZMmac2aNWrVqpWeeeYZubi46J133lFWVpamT59eJvsDoJyU/4IFwLUZNWqUIclo0aJFgb78JYkqVqxo5OTkFOhftmyZ0apVK8Pb29vw9vY26tSpY8TGxhoHDx40DMMwfv31V+OJJ54watWqZXh4eBj+/v7GPffcY6xdu9bufX766Sfj7rvvNjw9PQssyZSSkmLExsYa1atXN1xdXY3g4GCjXbt2xty5c80x+ctJFbW01scff2w0btzYcHd3N/z9/Y1evXoZv/32m9l/8uRJIzY21qhTp47h7e1t+Pr6Gs2aNTM++eSTKx6/yy15pb8s51RUjX9fvijfrl27jAcffNCoXLmy4e7uboSFhRndu3c31q1bV2DbJ06cKFBXTk6OMXr0aCM4ONjw9PQ02rZtaxw4cMCoXLmy3ZJOf1WvXj3DycnJ7thczn//+19j+PDhxu233274+/sbLi4uRtWqVY2HH37Y2LlzZ6Gv2bZtmyHJ6NixY4G+nTt3Gj179jRCQ0MNd3d3IzAw0LjvvvuMH374wW7cli1bjCZNmhhubm4Flmg6fPiw0adPHyM4ONhwdXU1brrpJuO+++4zPv30U3NM/vJMf1/+qajjGRMTY3h7e1/xeFxuyau//vVwtdtp3bq1Ua9ePfP538+Z4py/xT22fz+e+a+NiooyKlSoYHh5eRn33HOPsWXLFrsxRR3T/PM+/88BAOuwGQazzQFYU1pamipVqqRJkybpxRdfLNDfuHFj+fv7a926dWVWw549e9SoUSP9+9//vqZ5swCAa8OcVgCW8Nfb8+Z7/fXXJcm8A9pf/fDDD9q9e3ex7vp0Ld59911VqFDBvJsVAMAxmNMKwBI+/vhjLViwQJ07d1aFChW0adMmffjhh+rYsaNatmxpjvvxxx+1Y8cOzZgxQ1WrVtUjjzxSJvUsX75c+/fv19y5czVo0KACtzQFAJQvQisAS2jYsKFcXFw0ffp0ZWRkmF/Oyl9mLN+nn36qCRMm6NZbb9WHH35od+ew0jR48GClpKSoc+fOGj9+fJlsAwBQfMxpBQAAgOUxpxUAAACWR2gFAACA5TGnVZfuAX78+HFVrFixyFsuAgAAazEMQ2fPnlVISIicnLgO909HaJV0/Phx7kcNAMB16tixY6pWrZqjy0AZI7RKqlixoqRLJz33pQYA4PqQkZGh6tWrm3+P45/N4aH1999/18iRI7Vy5UqdP39et9xyi+bPn6+mTZtKunTpf+zYsXr33XeVlpamli1bas6cOQoPDzff4/Tp0xo8eLCWL18uJycnRUdHa9asWYXeV70w+VMCfHx8CK0AAFxnmNp3Y3DoBJAzZ86oZcuWcnV11cqVK7V//37NmDFDlSpVMsdMnz5db7zxht5++20lJibK29tbUVFRunDhgjmmV69e2rdvn9asWaMVK1bou+++04ABAxyxSwAAACgDDl2n9YUXXtDmzZv1/fffF9pvGIZCQkL0/PPPa9iwYZKk9PR0BQUFacGCBerRo4cOHDigiIgIbd++3bw6+80336hz58767bffFBIScsU6MjIy5Ovrq/T0dK60AgBwneDv7xuLQ6+0fvnll2ratKkefvhhBQYGqnHjxnr33XfN/iNHjig5OVnt27c323x9fdWsWTMlJCRIkhISEuTn52cGVklq3769nJyclJiYWOh2s7KylJGRYfcAAACAdTk0tP7666/m/NRVq1Zp4MCBevbZZ7Vw4UJJUnJysiQpKCjI7nVBQUFmX3JysgIDA+36XVxc5O/vb475uylTpsjX19d8sHIAAACAtTk0tObl5en222/X5MmT1bhxYw0YMED9+/fX22+/XabbHTVqlNLT083HsWPHynR7AAAAuDYODa1Vq1ZVRESEXVvdunWVlJQkSQoODpYkpaSk2I1JSUkx+4KDg5WammrXn5OTo9OnT5tj/s7d3d1cKYAVAwAAAKzPoaG1ZcuWOnjwoF3bzz//rLCwMElSzZo1FRwcrHXr1pn9GRkZSkxMVGRkpCQpMjJSaWlp2rFjhzlm/fr1ysvLU7NmzcphLwAAAFDWHLpO69ChQ9WiRQtNnjxZ3bt317Zt2zR37lzNnTtX0qV115577jlNmjRJ4eHhqlmzpkaPHq2QkBB169ZN0qUrs/fee685reDixYsaNGiQevToUayVAwAAAGB9Dl3ySpJWrFihUaNG6dChQ6pZs6bi4uLUv39/sz//5gJz585VWlqaWrVqpdmzZ6t27drmmNOnT2vQoEF2Nxd44403in1zAZbMAADg+sPf3zcWh4dWK+CkBwDg+sPf3zcWh85pBQAAAIqD0AoAAADLI7QCAADA8gitAAAAsDyHLnkFAEBpq/HCV44u4R/h6NQuji4BsMOVVgAAAFgeoRUAAACWR2gFAACA5RFaAQAAYHmEVgAAAFgeoRUAAACWR2gFAACA5bFOK4ASYz3M0sOamABweVxpBQAAgOURWgEAAGB5hFYAAABYHqEVAAAAlkdoBQAAgOURWgEAAGB5hFYAAABYHqEVAAAAlkdoBQAAgOURWgEAAGB5hFYAAABYHqEVAAAAlkdoBQAAgOURWgEAAGB5hFYAAABYHqEVAAAAlkdoBQAAgOURWgEAAGB5hFYAAABYHqEVAAAAlkdoBQAAgOURWgEAAGB5hFYAAABYHqEVAAAAlkdoBQAAgOURWgEAAGB5hFYAAABYHqEVAAAAlkdoBQAAgOURWgEAAGB5hFYAAABYHqEVAAAAlkdoBQAAgOURWgEAAGB5hFYAAABYHqEVAAAAlufQ0Dpu3DjZbDa7R506dcz+CxcuKDY2VpUrV1aFChUUHR2tlJQUu/dISkpSly5d5OXlpcDAQA0fPlw5OTnlvSsAAAAoQy6OLqBevXpau3at+dzF5f9KGjp0qL766istXbpUvr6+GjRokB588EFt3rxZkpSbm6suXbooODhYW7Zs0R9//KE+ffrI1dVVkydPLvd9AQAAQNlweGh1cXFRcHBwgfb09HTNmzdPS5YsUdu2bSVJ8+fPV926dbV161Y1b95cq1ev1v79+7V27VoFBQWpUaNGmjhxokaOHKlx48bJzc2tvHcHAAAAZcDhc1oPHTqkkJAQ3XzzzerVq5eSkpIkSTt27NDFixfVvn17c2ydOnUUGhqqhIQESVJCQoIaNGigoKAgc0xUVJQyMjK0b9++IreZlZWljIwMuwcAAACsy6GhtVmzZlqwYIG++eYbzZkzR0eOHNFdd92ls2fPKjk5WW5ubvLz87N7TVBQkJKTkyVJycnJdoE1vz+/ryhTpkyRr6+v+ahevXrp7hgAAABKlUOnB3Tq1Mn8/4YNG6pZs2YKCwvTJ598Ik9PzzLb7qhRoxQXF2c+z8jIILgCAABYmMOnB/yVn5+fateurV9++UXBwcHKzs5WWlqa3ZiUlBRzDmxwcHCB1QTynxc2Tzafu7u7fHx87B4AAACwLkuF1nPnzunw4cOqWrWqmjRpIldXV61bt87sP3jwoJKSkhQZGSlJioyM1N69e5WammqOWbNmjXx8fBQREVHu9QMAAKBsOHR6wLBhw9S1a1eFhYXp+PHjGjt2rJydndWzZ0/5+vqqX79+iouLk7+/v3x8fDR48GBFRkaqefPmkqSOHTsqIiJCvXv31vTp05WcnKyXXnpJsbGxcnd3d+SuAQAAoBQ5NLT+9ttv6tmzp06dOqWAgAC1atVKW7duVUBAgCRp5syZcnJyUnR0tLKyshQVFaXZs2ebr3d2dtaKFSs0cOBARUZGytvbWzExMZowYYKjdgkAAABlwKGh9aOPPrpsv4eHh+Lj4xUfH1/kmLCwMH399delXRoAAAAsxFJzWgEAAIDCEFoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeZYJrVOnTpXNZtNzzz1ntl24cEGxsbGqXLmyKlSooOjoaKWkpNi9LikpSV26dJGXl5cCAwM1fPhw5eTklHP1AAAAKEuWCK3bt2/XO++8o4YNG9q1Dx06VMuXL9fSpUu1ceNGHT9+XA8++KDZn5ubqy5duig7O1tbtmzRwoULtWDBAo0ZM6a8dwEAAABlyOGh9dy5c+rVq5feffddVapUyWxPT0/XvHnz9Nprr6lt27Zq0qSJ5s+fry1btmjr1q2SpNWrV2v//v364IMP1KhRI3Xq1EkTJ05UfHy8srOzHbVLAAAAKGUOD62xsbHq0qWL2rdvb9e+Y8cOXbx40a69Tp06Cg0NVUJCgiQpISFBDRo0UFBQkDkmKipKGRkZ2rdvX5HbzMrKUkZGht0DAAAA1uXiyI1/9NFH2rlzp7Zv316gLzk5WW5ubvLz87NrDwoKUnJysjnmr4E1vz+/ryhTpkzR+PHjr7F6AAAAlBeHXWk9duyYhgwZosWLF8vDw6Nctz1q1Cilp6ebj2PHjpXr9gEAAHB1HBZad+zYodTUVN1+++1ycXGRi4uLNm7cqDfeeEMuLi4KCgpSdna20tLS7F6XkpKi4OBgSVJwcHCB1QTyn+ePKYy7u7t8fHzsHgAAALAuh4XWdu3aae/evdq9e7f5aNq0qXr16mX+v6urq9atW2e+5uDBg0pKSlJkZKQkKTIyUnv37lVqaqo5Zs2aNfLx8VFERES57xMAAADKhsPmtFasWFH169e3a/P29lblypXN9n79+ikuLk7+/v7y8fHR4MGDFRkZqebNm0uSOnbsqIiICPXu3VvTp09XcnKyXnrpJcXGxsrd3b3c9wkAAABlw6FfxLqSmTNnysnJSdHR0crKylJUVJRmz55t9js7O2vFihUaOHCgIiMj5e3trZiYGE2YMMGBVQMAAKC0WSq0fvvtt3bPPTw8FB8fr/j4+CJfExYWpq+//rqMKwMAAIAjOXydVgAAAOBKCK0AAACwPEIrAAAALI/QCgAAAMsjtAIAAMDyCK0AAACwPEIrAAAALI/QCgAAAMsjtAIAAMDyCK0AAACwPEIrAAAALI/QCgAAAMsjtAIAAMDyCK0AAACwPEIrAAAALI/QCgAAAMsjtAIAAMDyCK0AAACwPEIrAAAALI/QCgAAAMsjtAIAAMDyCK0AAACwPEIrAAAALM/F0QWg+Gq88JWjS/jHODq1i6NLAAAAV4ErrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8l6sZ/Mcff2jdunXy9/dX+/bt5ebmZvZlZmZqxowZGjNmTKkXCQAAUBJ5eXnKzs52dBkogqurq5ydnYs1ttihdfv27erYsaPy8vJ08eJF3XTTTfriiy9Ur149SdK5c+c0fvx4QisAALCE7OxsHTlyRHl5eY4uBZfh5+en4OBg2Wy2y44rdmj917/+pQceeEDvvfeeMjMzNXLkSLVu3Vpr1qxR48aNr7lgAACA0mIYhv744w85OzurevXqcnJiRqTVGIah8+fPKzU1VZJUtWrVy44vdmjdsWOH4uPj5eTkpIoVK2r27NkKDQ1Vu3bttGrVKoWGhl5b5QAAAKUkJydH58+fV0hIiLy8vBxdDorg6ekpSUpNTVVgYOBlpwpc1ZzWCxcu2D1/4YUX5OLioo4dO+r9998vQakAAAClLzc3V5Lsvn8Da8r/R8XFixdLJ7TWr19fW7ZsUcOGDe3ahw0bpry8PPXs2bOEpQIAAJSNK82ThOMV92dU7Akeffr00ebNmwvtGzFihMaPH88UAQAAAJSJYofWJ598UosWLSqyf+TIkTpy5EipFAUAAICyYbPZ9MUXX5Tb9hYsWCA/P79rfp+rmtOa77///a9+/vlnSVLt2rULTBkAAACwohovfFWu2zs6tUu5bu+f7KpC67Zt29SvXz/t379fhmFIupTW69Wrp3nz5umOO+4okyIBAABwYyv29ID9+/erXbt28vT01AcffKCdO3dq586dWrRokdzd3dWuXTvt37+/LGsFAAD4x8vLy9P06dN1yy23yN3dXaGhoXr55ZclSXv37lXbtm3l6empypUra8CAATp37pz52u3bt6tDhw6qUqWKfH191bp1a+3cubNEdRw9elQ2m00fffSRWrRoIQ8PD9WvX18bN240x3z77bey2Wz66quv1LBhQ3l4eKh58+b68ccfr+0gFKLYoXXcuHHq0KGDEhMT1bNnTzVq1EiNGjXSo48+qm3btqldu3YaN25cqRcIAABwIxk1apSmTp2q0aNHa//+/VqyZImCgoKUmZmpqKgoVapUSdu3b9fSpUu1du1aDRo0yHzt2bNnFRMTo02bNmnr1q0KDw9X586ddfbs2RLXM3z4cD3//PPatWuXIiMj1bVrV506darAmBkzZmj79u0KCAhQ165ddfHixRJvszDFnh6wYcMGrVy5stBlCWw2m/71r3+pc+fOpVocAADAjeTs2bOaNWuW3nrrLcXExEiSatWqpVatWundd9/VhQsX9O9//1ve3t6SpLfeektdu3bVtGnTFBQUpLZt29q939y5c+Xn56eNGzfqvvvuK1FNgwYNUnR0tCRpzpw5+uabbzRv3jyNGDHCHDN27Fh16NBBkrRw4UJVq1ZNn3/+ubp3716ibRam2Fdaz549q6CgoCL7g4ODrzrFz5kzRw0bNpSPj498fHwUGRmplStXmv0XLlxQbGysKleurAoVKig6OlopKSl275GUlKQuXbrIy8tLgYGBGj58uHJycq6qDgAAACs4cOCAsrKy1K5du0L7brvtNjOwSlLLli2Vl5engwcPSpJSUlLUv39/hYeHy9fXVz4+Pjp37pySkpJKXFNkZKT5/y4uLmratKkOHDhQ5Bh/f3/deuutBcZcq2KH1rCwMG3btq3I/sTERIWFhV3VxqtVq6apU6dqx44d+uGHH9S2bVvdf//92rdvnyRp6NChWr58uZYuXaqNGzfq+PHjevDBB83X5+bmqkuXLsrOztaWLVu0cOFCLViwQGPGjLmqOgAAAKwg/7amJRUTE6Pdu3dr1qxZ2rJli3bv3q3KlSsrOzu7lCp0nGKH1h49eiguLq7QibV79+7VsGHD9Mgjj1zVxrt27arOnTsrPDxctWvX1ssvv6wKFSpo69atSk9P17x58/Taa6+pbdu2atKkiebPn68tW7Zo69atkqTVq1dr//79+uCDD9SoUSN16tRJEydOVHx8/D/ihwMAAG4s4eHh8vT01Lp16wr01a1bV3v27FFmZqbZtnnzZjk5OenWW281nz/77LPq3Lmz6tWrJ3d3d508efKaasrPXZKUk5OjHTt2qG7dukWOOXPmjH7++ecCY65Vsee0jho1SmvXrlWjRo3UoUMH1a1bV4Zh6MCBA1q7dq3uvPNO/etf/ypxIbm5uVq6dKkyMzMVGRmpHTt26OLFi2rfvr05pk6dOgoNDVVCQoKaN2+uhIQENWjQwG7aQlRUlAYOHKh9+/apcePGhW4rKytLWVlZ5vOMjIwS1w0AAFBaPDw8NHLkSI0YMUJubm5q2bKlTpw4oX379qlXr14aO3asYmJiNG7cOJ04cUKDBw9W7969zSwUHh6uRYsWqWnTpsrIyNDw4cOv+eptfHy8wsPDVbduXc2cOVNnzpzRE088YTdmwoQJqly5soKCgvTiiy+qSpUq6tat2zVt9++KHVo9PDy0YcMGzZw5Ux9++KG53EHt2rU1adIkDR06VO7u7lddwN69exUZGakLFy6oQoUK+vzzzxUREaHdu3fLzc2twB0UgoKClJycLElKTk4uMM82/3n+mMJMmTJF48ePv+paAQDA9e16WOx/9OjRcnFx0ZgxY3T8+HFVrVpVTz/9tLy8vLRq1SoNGTJEd9xxh7y8vBQdHa3XXnvNfO28efM0YMAA3X777apevbomT56sYcOGXVM9U6dO1dSpU7V7927dcsst+vLLL1WlSpUCY4YMGaJDhw6pUaNGWr58udzc3K5pu393VTcXcHNz08iRIzVy5MhSK+DWW2/V7t27lZ6erk8//VQxMTF263+VhVGjRikuLs58npGRoerVq5fpNgEAAIrDyclJL774ol588cUCfQ0aNND69euLfG3jxo21fft2u7aHHnrI7nn+DaKKq27dukpMTLzsmFatWhW5Nuvjjz+uxx9//Kq2WZhiz2k9c+aM3nzzzUI/Sk9PTy+y70rc3Nx0yy23qEmTJpoyZYpuu+02zZo1S8HBwcrOzlZaWprd+JSUFAUHB0u6tGLB31cTyH+eP6Yw7u7u5ooF+Q8AAABYV7FD61tvvaXvvvuu0IDn6+ur77//Xm+++eY1F5SXl6esrCw1adJErq6udhORDx48qKSkJHNZhcjISO3du1epqanmmDVr1sjHx0cRERHXXAsAAMA/1eTJk1WhQoVCH506dXJ0eQUUe3rAsmXLNGPGjCL7n3rqKQ0bNqzQS9lFGTVqlDp16qTQ0FCdPXtWS5Ys0bfffqtVq1bJ19dX/fr1U1xcnPz9/eXj46PBgwcrMjJSzZs3lyR17NhRERER6t27t6ZPn67k5GS99NJLio2NLdH8WgAAgBvF008/XeTi/56enrrpppuuOJWgTZs2Vz3doKSKHVoPHz6s8PDwIvvDw8N1+PDhq9p4amqq+vTpoz/++EO+vr5q2LChVq1aZd5RYebMmXJyclJ0dLSysrIUFRWl2bNnm693dnbWihUrNHDgQEVGRsrb21sxMTGaMGHCVdUBAABwo/H395e/v7+jyyi2YodWZ2dnHT9+XKGhoYX2Hz9+XE5OxZ5tIOnSN9wux8PDQ/Hx8YqPjy9yTFhYmL7++uur2i4AALgxlNdVQJRccX9GxU6ZjRs31hdffFFk/+eff17kuqgAAADlydnZWZK42dB14Pz585IkV1fXy44r9pXWQYMGqUePHqpWrZoGDhxongy5ubmaPXu2Zs6cqSVLllxDyQAAAKXDxcVFXl5eOnHihFxdXa/602CUPcMwdP78eaWmpsrPz8/MlkUpdmiNjo7WiBEj9Oyzz+rFF1/UzTffLEn69ddfde7cOQ0fPrzAOmAAAACOYLPZVLVqVR05ckT/+9//HF0OLsPPz++yS5Xmu6qbC7z88svq1q2bFi1apMOHD8swDLVu3VqPPvqo7rjjDiUlJRU55xUAAKA8ubm5KTw8nCkCFubq6nrFK6z5riq0SlLz5s31xx9/KDAw0K791KlTqlmzpnJzc6/2LQEAAMqEk5OTPDw8HF0GSsFVT/AwDEM2m61A+7lz5zgpAAAAUCaKfaU1Li5O0qU5IqNHj5aXl5fZl5ubq8TERDVq1KjUCwQAAACKHVp37dol6dKV1r1798rNzc3sc3Nz02233aZhw4aVfoUAAAC44RU7tG7YsEGS1LdvX82aNUs+Pj5lVhQAAADwV1f9Raz58+eXRR0AAABAkVhpFwAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeYRWAAAAWB6hFQAAAJZHaAUAAIDlEVoBAABgeQ4NrVOmTNEdd9yhihUrKjAwUN26ddPBgwftxly4cEGxsbGqXLmyKlSooOjoaKWkpNiNSUpKUpcuXeTl5aXAwEANHz5cOTk55bkrAAAAKEMODa0bN25UbGystm7dqjVr1ujixYvq2LGjMjMzzTFDhw7V8uXLtXTpUm3cuFHHjx/Xgw8+aPbn5uaqS5cuys7O1pYtW7Rw4UItWLBAY8aMccQuAQAAoAy4OHLj33zzjd3zBQsWKDAwUDt27NDdd9+t9PR0zZs3T0uWLFHbtm0lSfPnz1fdunW1detWNW/eXKtXr9b+/fu1du1aBQUFqVGjRpo4caJGjhypcePGyc3NzRG7BgAAgFJkqTmt6enpkiR/f39J0o4dO3Tx4kW1b9/eHFOnTh2FhoYqISFBkpSQkKAGDRooKCjIHBMVFaWMjAzt27ev0O1kZWUpIyPD7gEAAADrskxozcvL03PPPaeWLVuqfv36kqTk5GS5ubnJz8/PbmxQUJCSk5PNMX8NrPn9+X2FmTJlinx9fc1H9erVS3lvAAAAUJosE1pjY2P1448/6qOPPirzbY0aNUrp6enm49ixY2W+TQAAAJScQ+e05hs0aJBWrFih7777TtWqVTPbg4ODlZ2drbS0NLurrSkpKQoODjbHbNu2ze798lcXyB/zd+7u7nJ3dy/lvQAAAEBZceiVVsMwNGjQIH3++edav369atasadffpEkTubq6at26dWbbwYMHlZSUpMjISElSZGSk9u7dq9TUVHPMmjVr5OPjo4iIiPLZEQAAAJQph15pjY2N1ZIlS/Sf//xHFStWNOeg+vr6ytPTU76+vurXr5/i4uLk7+8vHx8fDR48WJGRkWrevLkkqWPHjoqIiFDv3r01ffp0JScn66WXXlJsbCxXUwEAAP4hHBpa58yZI0lq06aNXfv8+fP1+OOPS5JmzpwpJycnRUdHKysrS1FRUZo9e7Y51tnZWStWrNDAgQMVGRkpb29vxcTEaMKECeW1GwAAAChjDg2thmFccYyHh4fi4+MVHx9f5JiwsDB9/fXXpVkaAAAALMQyqwcAAAAARSG0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIcGlq/++47de3aVSEhIbLZbPriiy/s+g3D0JgxY1S1alV5enqqffv2OnTokN2Y06dPq1evXvLx8ZGfn5/69eunc+fOleNeAAAAoKw5NLRmZmbqtttuU3x8fKH906dP1xtvvKG3335biYmJ8vb2VlRUlC5cuGCO6dWrl/bt26c1a9ZoxYoV+u677zRgwIDy2gUAAACUAxdHbrxTp07q1KlToX2GYej111/XSy+9pPvvv1+S9O9//1tBQUH64osv1KNHDx04cEDffPONtm/frqZNm0qS3nzzTXXu3FmvvvqqQkJCym1fAAAAUHYsO6f1yJEjSk5OVvv27c02X19fNWvWTAkJCZKkhIQE+fn5mYFVktq3by8nJyclJiYW+d5ZWVnKyMiwewAAAMC6LBtak5OTJUlBQUF27UFBQWZfcnKyAgMD7fpdXFzk7+9vjinMlClT5Ovraz6qV69eytUDAACgNFk2tJalUaNGKT093XwcO3bM0SUBAADgMiwbWoODgyVJKSkpdu0pKSlmX3BwsFJTU+36c3JydPr0aXNMYdzd3eXj42P3AAAAgHVZNrTWrFlTwcHBWrdundmWkZGhxMRERUZGSpIiIyOVlpamHTt2mGPWr1+vvLw8NWvWrNxrBgAAQNlw6OoB586d0y+//GI+P3LkiHbv3i1/f3+Fhobqueee06RJkxQeHq6aNWtq9OjRCgkJUbdu3SRJdevW1b333qv+/fvr7bff1sWLFzVo0CD16NGDlQMAAAD+QRwaWn/44Qfdc8895vO4uDhJUkxMjBYsWKARI0YoMzNTAwYMUFpamlq1aqVvvvlGHh4e5msWL16sQYMGqV27dnJyclJ0dLTeeOONct8XAAAAlB2HhtY2bdrIMIwi+202myZMmKAJEyYUOcbf319Lliwpi/IAAABgEZad0woAAADkI7QCAADA8gitAAAAsDxCKwAAACyP0AoAAADLI7QCAADA8gitAAAAsDxCKwAAACyP0AoAAADLI7QCAADA8gitAAAAsDxCKwAAACyP0AoAAADLI7QCAADA8gitAAAAsDxCKwAAACyP0AoAAADLI7QCAADA8gitAAAAsDxCKwAAACyP0AoAAADLI7QCAADA8gitAAAAsDxCKwAAACyP0AoAAADLI7QCAADA8gitAAAAsDxCKwAAACyP0AoAAADLI7QCAADA8gitAAAAsDxCKwAAACyP0AoAAADLI7QCAADA8gitAAAAsDxCKwAAACyP0AoAAADLI7QCAADA8gitAAAAsDxCKwAAACyP0AoAAADLI7QCAADA8gitAAAAsDxCKwAAACyP0AoAAADLI7QCAADA8gitAAAAsDxCKwAAACyP0AoAAADL+8eE1vj4eNWoUUMeHh5q1qyZtm3b5uiSAAAAUEr+EaH1448/VlxcnMaOHaudO3fqtttuU1RUlFJTUx1dGgAAAErBPyK0vvbaa+rfv7/69u2riIgIvf322/Ly8tL777/v6NIAAABQClwcXcC1ys7O1o4dOzRq1CizzcnJSe3bt1dCQkKhr8nKylJWVpb5PD09XZKUkZFRtsVeo7ys844u4R/D6j/r6wXnZOnhnCw9nJel43o4J/NrNAzDwZWgPFz3ofXkyZPKzc1VUFCQXXtQUJB++umnQl8zZcoUjR8/vkB79erVy6RGWI/v646uALDHOQmruZ7OybNnz8rX19fRZaCMXfehtSRGjRqluLg483leXp5Onz6typUry2azObCy61tGRoaqV6+uY8eOycfHx9HlAJI4L2E9nJOlxzAMnT17ViEhIY4uBeXgug+tVapUkbOzs1JSUuzaU1JSFBwcXOhr3N3d5e7ubtfm5+dXViXecHx8fPhFDMvhvITVcE6WDq6w3jiu+y9iubm5qUmTJlq3bp3ZlpeXp3Xr1ikyMtKBlQEAAKC0XPdXWiUpLi5OMTExatq0qe688069/vrryszMVN++fR1dGgAAAErBPyK0PvLIIzpx4oTGjBmj5ORkNWrUSN98802BL2ehbLm7u2vs2LEFpl4AjsR5CavhnARKxmawTgQAAAAs7rqf0woAAIB/PkIrAAAALI/QCgAAAMsjtAIAAMDyCK0AAACwPEIrAAAALI/QCgAAAMv7R9xcAI6Tk5Ojffv2KTk5WZIUHBysiIgIubq6Orgy3MiSk5OVmJhod142a9ZMwcHBDq4MNyp+VwLXjtCKEsnLy9OYMWMUHx+v9PR0uz5fX18NGjRI48ePl5MTF/NRfjIzM/XUU0/po48+ks1mk7+/vyTp9OnTMgxDPXv21DvvvCMvLy8HV4obBb8rgdLDnxKUyAsvvKC5c+dq6tSp+vXXX5WZmanMzEz9+uuvmjZtmubOnatRo0Y5ukzcYIYMGaJt27bpq6++0oULF5SSkqKUlBRduHBBX3/9tbZt26YhQ4Y4ukzcQPhdCZQebuOKEgkODtbChQsVFRVVaP+qVavUp08fpaSklHNluJFVqlRJX331lVq0aFFo/+bNm3XffffpzJkz5VwZblT8rgRKD1daUSJnz55VSEhIkf1Vq1ZVZmZmOVYEXPoo1s3Nrch+Nzc35eXllWNFuNHxuxIoPYRWlEibNm00bNgwnTx5skDfyZMnNXLkSLVp06b8C8MN7b777tOAAQO0a9euAn27du3SwIED1bVrVwdUhhsVvyuB0sP0AJTIsWPH1LlzZ/30009q0KCBgoKCJEkpKSnau3evIiIitGLFClWvXt3BleJGcubMGT366KNatWqVKlWqpMDAQElSamqq0tLSFBUVpSVLlsjPz8+xheKGwe9KoPQQWlFieXl5WrVqlbZu3Wq3jEtkZKQ6duzIt2HhMD/99JMSEhIKnJd16tRxcGW4EfG7EigdhFYAAABYHuu04pps27atwBWtFi1a6I477nBwZUBBZ86c0fLly9WnTx9Hl4IbTF5eXqFXVPPy8vTbb78pNDTUAVUB1xeutKJEUlNTFR0drc2bNys0NNRunlZSUpJatmypZcuWmXMKASvYs2ePbr/9duXm5jq6FNwgMjIy9OSTT2r58uXy8fHRU089pbFjx8rZ2VnSpd+ZISEhnJNAMXClFSXyzDPPKDc3VwcOHNCtt95q13fw4EE98cQTio2N1dKlSx1UIW5EGRkZl+0/e/ZsOVUCXDJ69Gjt2bNHixYtUlpamiZNmqSdO3fqs88+M5dn49oRUDxcaUWJVKxYUd99950aN25caP+OHTvUpk0bQgLKlZOTk2w2W5H9hmHIZrNxVQvlJiwsTAsXLjSXtTp58qS6dOkiPz8/ffnll0pLS+NKK1BMXGlFibi7u1/2qtbZs2fl7u5ejhUBl/4x9eKLL6pZs2aF9h86dEhPPfVUOVeFG9mJEycUFhZmPq9SpYrWrl2rqKgode7cWe+9954DqwOuL4RWlMgjjzyimJgYzZw5U+3atZOPj4+kSx/Prlu3TnFxcerZs6eDq8SN5vbbb5cktW7dutB+Pz8/PopFuQoNDdWBAwdUs2ZNs61ixYpavXq1OnbsqAceeMCB1QHXF0IrSuS1115TXl6eevTooZycHHNuVnZ2tlxcXNSvXz+9+uqrDq4SN5pHH31U58+fL7I/ODhYY8eOLceKcKPr0KGD5s+fr86dO9u1V6hQQatWrVKHDh0cVBlw/WFOK65JRkaGfvjhB6WkpEi6FAqaNGliXnkFgBvZmTNndPz4cdWrV6/Q/rNnz2rnzp1FfjoA4P8QWlEigwcPVvfu3XXXXXc5uhTAxHkJq+GcBEoPoRUlkv8t7Vq1aqlfv36KiYlRcHCwo8vCDY7zElbDOQmUHm54jBJbvXq1OnfurFdffVWhoaG6//77tWLFCuXl5Tm6NNzAOC9hNZyTQOkgtKLEGjRooNdff13Hjx/XBx98oKysLHXr1k3Vq1fXiy++qF9++cXRJeIGxHkJq+GcBEoH0wNQIk5OTkpOTi5wm9akpCS9//77WrBggY4dO8aC2ShXnJewGs5JoPQQWlEiRf0izmcYhtauXctyLihXnJewGs5JoPQwPQAlEhYWJmdn5yL7bTYbv4RR7jgvYTWck0Dp4UorAAAALI8rrQAAALA8QisAAAAsj9AKAAAAyyO0AgAAwPIIrQAAALA8QiuA64JhGGrfvr2ioqIK9M2ePVt+fn767bffHFAZAKA8EFoBXBdsNpvmz5+vxMREvfPOO2b7kSNHNGLECL355puqVq1aqW7z4sWLpfp+AICSI7QCuG5Ur15ds2bN0rBhw3TkyBEZhqF+/fqpY8eOaty4sTp16qQKFSooKChIvXv31smTJ83XfvPNN2rVqpX8/PxUuXJl3XfffTp8+LDZf/ToUdlsNn388cdq3bq1PDw8tHjxYkfsJgCgENxcAMB1p1u3bkpPT9eDDz6oiRMnat++fapXr56efPJJ9enTR3/++adGjhypnJwcrV+/XpK0bNky2Ww2NWzYUOfOndOYMWN09OhR7d69W05OTjp69Khq1qypGjVqaMaMGWrcuLE8PDxUtWpVB+8tAEAitAK4DqWmpqpevXo6ffq0li1bph9//FHff/+9Vq1aZY757bffVL16dR08eFC1a9cu8B4nT55UQECA9u7dq/r165uh9fXXX9eQIUPKc3cAAMXA9AAA153AwEA99dRTqlu3rrp166Y9e/Zow4YNqlChgvmoU6eOJJlTAA4dOqSePXvq5ptvlo+Pj2rUqCFJSkpKsnvvpk2bluu+AACKx8XRBQBASbi4uMjF5dKvsHPnzqlr166aNm1agXH5H+937dpVYWFhevfddxUSEqK8vDzVr19f2dnZduO9vb3LvngAwFUjtAK47t1+++1atmyZatSoYQbZvzp16pQOHjyod999V3fddZckadOmTeVdJgDgGjA9AMB1LzY2VqdPn1bPnj21fft2HT58WKtWrVLfvn2Vm5urSpUqqXLlypo7d65++eUXrV+/XnFxcY4uGwBwFQitAK57ISEh2rx5s3Jzc9WxY0c1aNBAzz33nPz8/OTk5CQnJyd99NFH2rFjh+rXr6+hQ4fqlVdecXTZAICrwOoBAAAAsDyutAIAAMDyCK0AAACwPEIrAAAALI/QCgAAAMsjtAIAAMDyCK0AAACwPEIrAAAALI/QCgAAAMsjtAIAAMDyCK0AAACwPEIrAAAALO//A9ZEVPK5DJH4AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "With DACCS\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "emission_factor: mixed units ['tCO2/kWa', 'tCO2/tCO2'] discarded\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Without DACCS\")\n",
    "prepare_plots(rep_ori)\n",
    "rep_ori.set_filters(t=[\"coal_ppl\", \"wind_ppl\"])\n",
    "rep_ori.get(\"plot emission\")\n",
    "plt.show()\n",
    "\n",
    "print(\"With DACCS\")\n",
    "prepare_plots(rep_new)\n",
    "rep_new.set_filters(t=[\"coal_ppl\", \"wind_ppl\",\"daccs\"])\n",
    "rep_new.get(\"plot emission\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "436e75d0",
   "metadata": {},
   "source": [
    "## Close the connection with the database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "ff03f487",
   "metadata": {},
   "outputs": [],
   "source": [
    "mp.close_db()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c907fa13",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}