{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Anaerobic Digestion (AD)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import PFAS_SAT_ProcessModels as pspd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import Image\n",
    "import pandas as pd\n",
    "pd.set_option('display.max_colwidth', 0)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model document\n",
    "\n",
    "AD can accept food waste or wastewater treatment solids to stabilize them prior to aerobic curing and/or land application.\n",
    "The residual solids from AD can be further dewatered and the aerobically cured prior to land application. The liquid\n",
    "stream (digestate) may be returned to the AD process in some cases (e.g., a low solids food waste system) or sent to WWT.\n",
    "While it is possible that PFAS are volatilized/aerosolized during digestion and/or aerobic curing, as noted earlier,\n",
    "the default PFAS release to the air is zero.\n",
    "\n",
    "During digestion, the feedstocks (e.g., WWT solids, food waste) partially biodegrade with the conversion of solids to\n",
    "biogas. Model predictions of PFAS fate are based on achievement of equilibrium. The partition coefficient is used to\n",
    "estimate the concentration of PFAS in the liquid and solids. VS destruction during digestion changes the equilibrium\n",
    "PFAS distribution between the solid and aqueous phases. There are several different potential AD processes\n",
    "(e.g., thermophilic, mesophilic, single stage, multi-stages). The AD process model in the SAT framework is\n",
    "designed so that by changing default parameters, different AD systems can be represented.\n",
    "\n",
    "\n",
    "<img src=\"../Images/ProcessModels/AD_Diagram-v2.png\" alt=\"Drawing\" style=\"width: 700px;\"/>\n",
    "\n",
    "\n",
    "\n",
    "### Assumptions and Limitations:\n",
    "\n",
    "1. The model assumes that there is no water loss during anaerobic digestion, and that the C concentration in the solids\n",
    "   remains constant.\n",
    "2. Volatilization is assumed to be zero by default due to a lack of data. However, the user may assign a fraction of the PFAS\n",
    "   that volatilizes/aerosolizes.\n",
    "3. Future work is required to implement a dynamic model to account for changes in the organic C content over time as materials\n",
    "   decompose in the reactor and during aerobic curing. \n",
    "4. We do not consider the possible conversion of \"precursor\" compounds to commonly measured PFAAs.\n",
    "5. Anaerobic digestion processes are sometimes preceded by a thermal pre-treatment process for the purpose of enhancing\n",
    "   methane production. Thermal pretreatment can also enhance precursor conversion to PFAAs. This can lead to an increase\n",
    "   in aqueous PFAA concentrations across the process."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Input Parameters for AD model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Category</th>\n",
       "      <th>Dictonary_Name</th>\n",
       "      <th>Parameter Name</th>\n",
       "      <th>Parameter Description</th>\n",
       "      <th>amount</th>\n",
       "      <th>unit</th>\n",
       "      <th>Reference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AD parameters</td>\n",
       "      <td>AD</td>\n",
       "      <td>frac_PFAS_to_Vol</td>\n",
       "      <td>Fraction of PFAS lost to volatilization</td>\n",
       "      <td>0.00</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AD parameters</td>\n",
       "      <td>AD</td>\n",
       "      <td>frac_VS_loss</td>\n",
       "      <td>Fraction VS destruction during AD</td>\n",
       "      <td>0.55</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AD parameters</td>\n",
       "      <td>AD</td>\n",
       "      <td>frac_cured</td>\n",
       "      <td>Fraction of digestate cured</td>\n",
       "      <td>1.00</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AD parameters</td>\n",
       "      <td>AD</td>\n",
       "      <td>Reac_moist</td>\n",
       "      <td>Reactor moisture content _ wet</td>\n",
       "      <td>0.92</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Dewatering</td>\n",
       "      <td>Dew</td>\n",
       "      <td>Digestate_moist</td>\n",
       "      <td>Moisture Content of Solids Stream After Dewatering</td>\n",
       "      <td>0.76</td>\n",
       "      <td>fraction</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Curing Input</td>\n",
       "      <td>Curing</td>\n",
       "      <td>frac_C_lost</td>\n",
       "      <td>Fraction of organic C lost during curing</td>\n",
       "      <td>0.50</td>\n",
       "      <td>fraction C</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Curing Input</td>\n",
       "      <td>Curing</td>\n",
       "      <td>ts_end</td>\n",
       "      <td>Solids content at the end of curing</td>\n",
       "      <td>0.50</td>\n",
       "      <td>fraction ts</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Curing Input</td>\n",
       "      <td>Curing</td>\n",
       "      <td>bulk_dens</td>\n",
       "      <td>Bulk density of curing pile</td>\n",
       "      <td>400.00</td>\n",
       "      <td>kg/m3</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Curing Input</td>\n",
       "      <td>Curing</td>\n",
       "      <td>wind_ht</td>\n",
       "      <td>Curing windrow height</td>\n",
       "      <td>4.00</td>\n",
       "      <td>m</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Curing Input</td>\n",
       "      <td>Curing</td>\n",
       "      <td>wind_wid</td>\n",
       "      <td>Curing windrow width</td>\n",
       "      <td>6.00</td>\n",
       "      <td>m</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Curing Input</td>\n",
       "      <td>Curing</td>\n",
       "      <td>sol_loss_per_C_loss</td>\n",
       "      <td>Solids loss per C loss</td>\n",
       "      <td>2.00</td>\n",
       "      <td>kg/kg</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Curing Input</td>\n",
       "      <td>Curing</td>\n",
       "      <td>curing_time</td>\n",
       "      <td>Curing time</td>\n",
       "      <td>30.00</td>\n",
       "      <td>days</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Precipitation Data</td>\n",
       "      <td>Precip</td>\n",
       "      <td>ann_precip</td>\n",
       "      <td>Annual precipitation</td>\n",
       "      <td>1.00</td>\n",
       "      <td>m/yr</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>LogPartCoef</td>\n",
       "      <td>PFOA</td>\n",
       "      <td>PFOA Log Koc (AD)</td>\n",
       "      <td>2.19</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>LogPartCoef</td>\n",
       "      <td>PFOS</td>\n",
       "      <td>PFOS Log Koc (AD)</td>\n",
       "      <td>3.04</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>LogPartCoef</td>\n",
       "      <td>PFBA</td>\n",
       "      <td>PFBA Log Koc  (AD)</td>\n",
       "      <td>1.88</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>LogPartCoef</td>\n",
       "      <td>PFPeA</td>\n",
       "      <td>PFPeA Log Koc (AD)</td>\n",
       "      <td>1.37</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>LogPartCoef</td>\n",
       "      <td>PFHxA</td>\n",
       "      <td>PFHxA Log Koc (AD)</td>\n",
       "      <td>1.77</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>LogPartCoef</td>\n",
       "      <td>PFHpA</td>\n",
       "      <td>PFHpA Log Koc (AD)</td>\n",
       "      <td>1.97</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>LogPartCoef</td>\n",
       "      <td>PFNA</td>\n",
       "      <td>PFNA Log Koc (AD)</td>\n",
       "      <td>2.63</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>LogPartCoef</td>\n",
       "      <td>PFDA</td>\n",
       "      <td>PFDA Log Koc (AD)</td>\n",
       "      <td>3.24</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>LogPartCoef</td>\n",
       "      <td>PFBS</td>\n",
       "      <td>PFBS Log Koc (AD)</td>\n",
       "      <td>1.51</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>LogPartCoef</td>\n",
       "      <td>PFHxS</td>\n",
       "      <td>PFHxS Log Koc (AD)</td>\n",
       "      <td>2.79</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td></td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Category Dictonary_Name       Parameter Name  \\\n",
       "0   AD parameters              AD             frac_PFAS_to_Vol      \n",
       "1   AD parameters              AD             frac_VS_loss          \n",
       "2   AD parameters              AD             frac_cured            \n",
       "3   AD parameters              AD             Reac_moist            \n",
       "4   Dewatering                 Dew            Digestate_moist       \n",
       "5   Curing Input               Curing         frac_C_lost           \n",
       "6   Curing Input               Curing         ts_end                \n",
       "7   Curing Input               Curing         bulk_dens             \n",
       "8   Curing Input               Curing         wind_ht               \n",
       "9   Curing Input               Curing         wind_wid              \n",
       "10  Curing Input               Curing         sol_loss_per_C_loss   \n",
       "11  Curing Input               Curing         curing_time           \n",
       "12  Precipitation Data         Precip         ann_precip            \n",
       "13  Log partition coefficient  LogPartCoef    PFOA                  \n",
       "14  Log partition coefficient  LogPartCoef    PFOS                  \n",
       "15  Log partition coefficient  LogPartCoef    PFBA                  \n",
       "16  Log partition coefficient  LogPartCoef    PFPeA                 \n",
       "17  Log partition coefficient  LogPartCoef    PFHxA                 \n",
       "18  Log partition coefficient  LogPartCoef    PFHpA                 \n",
       "19  Log partition coefficient  LogPartCoef    PFNA                  \n",
       "20  Log partition coefficient  LogPartCoef    PFDA                  \n",
       "21  Log partition coefficient  LogPartCoef    PFBS                  \n",
       "22  Log partition coefficient  LogPartCoef    PFHxS                 \n",
       "\n",
       "                                 Parameter Description  amount         unit  \\\n",
       "0   Fraction of PFAS lost to volatilization             0.00    fraction      \n",
       "1   Fraction VS destruction during AD                   0.55    fraction      \n",
       "2   Fraction of digestate cured                         1.00    fraction      \n",
       "3   Reactor moisture content _ wet                      0.92    fraction      \n",
       "4   Moisture Content of Solids Stream After Dewatering  0.76    fraction      \n",
       "5   Fraction of organic C lost during curing            0.50    fraction C    \n",
       "6   Solids content at the end of curing                 0.50    fraction ts   \n",
       "7   Bulk density of curing pile                         400.00  kg/m3         \n",
       "8   Curing windrow height                               4.00    m             \n",
       "9   Curing windrow width                                6.00    m             \n",
       "10  Solids loss per C loss                              2.00    kg/kg         \n",
       "11  Curing time                                         30.00   days          \n",
       "12  Annual precipitation                                1.00    m/yr          \n",
       "13  PFOA Log Koc (AD)                                   2.19    log L/kg OC   \n",
       "14  PFOS Log Koc (AD)                                   3.04    log L/kg OC   \n",
       "15  PFBA Log Koc  (AD)                                  1.88    log L/kg OC   \n",
       "16  PFPeA Log Koc (AD)                                  1.37    log L/kg OC   \n",
       "17  PFHxA Log Koc (AD)                                  1.77    log L/kg OC   \n",
       "18  PFHpA Log Koc (AD)                                  1.97    log L/kg OC   \n",
       "19  PFNA Log Koc (AD)                                   2.63    log L/kg OC   \n",
       "20  PFDA Log Koc (AD)                                   3.24    log L/kg OC   \n",
       "21  PFBS Log Koc (AD)                                   1.51    log L/kg OC   \n",
       "22  PFHxS Log Koc (AD)                                  2.79    log L/kg OC   \n",
       "\n",
       "   Reference  \n",
       "0             \n",
       "1             \n",
       "2             \n",
       "3             \n",
       "4             \n",
       "5             \n",
       "6             \n",
       "7             \n",
       "8             \n",
       "9             \n",
       "10            \n",
       "11            \n",
       "12            \n",
       "13            \n",
       "14            \n",
       "15            \n",
       "16            \n",
       "17            \n",
       "18            \n",
       "19            \n",
       "20            \n",
       "21            \n",
       "22            "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AD = pspd.AD()\n",
    "AD.InputData.Data[['Category','Dictonary_Name','Parameter Name', 'Parameter Description', 'amount', 'unit','Reference']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Incoming Dewatered WWT Solids to AD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Parameter</th>\n",
       "      <th>Unit</th>\n",
       "      <th>Amount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Mass flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Solids flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>200.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Moisture flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>800.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>VS flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>120.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Carbon flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>76.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>PFOA</td>\n",
       "      <td>μg</td>\n",
       "      <td>934.565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>PFOS</td>\n",
       "      <td>μg</td>\n",
       "      <td>3678.926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>PFBA</td>\n",
       "      <td>μg</td>\n",
       "      <td>146.226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>PFPeA</td>\n",
       "      <td>μg</td>\n",
       "      <td>365.103</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>PFHxA</td>\n",
       "      <td>μg</td>\n",
       "      <td>511.518</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>PFHpA</td>\n",
       "      <td>μg</td>\n",
       "      <td>88.188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>PFNA</td>\n",
       "      <td>μg</td>\n",
       "      <td>373.149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>PFDA</td>\n",
       "      <td>μg</td>\n",
       "      <td>1552.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>PFBS</td>\n",
       "      <td>μg</td>\n",
       "      <td>125.018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>PFHxS</td>\n",
       "      <td>μg</td>\n",
       "      <td>107.265</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Parameter Unit    Amount\n",
       "0   Mass flow      kg   1000    \n",
       "1   Solids flow    kg   200.0   \n",
       "2   Moisture flow  kg   800.0   \n",
       "3   VS flow        kg   120.0   \n",
       "4   Carbon flow    kg   76.0    \n",
       "5   PFOA           μg   934.565 \n",
       "6   PFOS           μg   3678.926\n",
       "7   PFBA           μg   146.226 \n",
       "8   PFPeA          μg   365.103 \n",
       "9   PFHxA          μg   511.518 \n",
       "10  PFHpA          μg   88.188  \n",
       "11  PFNA           μg   373.149 \n",
       "12  PFDA           μg   1552.18 \n",
       "13  PFBS           μg   125.018 \n",
       "14  PFHxS          μg   107.265 "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IncominWaste = pspd.IncomFlow()\n",
    "IncominWaste.set_flow('Dewatered WWT Solids', 1000)\n",
    "IncominWaste.calc()\n",
    "DewateredWWTSolids = IncominWaste.Inc_flow\n",
    "DewateredWWTSolids.report()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PFAS balance in AD (50% of the AD solids is Cured)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Volatilization</th>\n",
       "      <th>ADSolids</th>\n",
       "      <th>ADLiquids</th>\n",
       "      <th>Compost</th>\n",
       "      <th>Contact Water</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PFOA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>38.92</td>\n",
       "      <td>22.16</td>\n",
       "      <td>38.83</td>\n",
       "      <td>0.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFOS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>48.06</td>\n",
       "      <td>3.88</td>\n",
       "      <td>48.04</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFBA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>31.68</td>\n",
       "      <td>36.63</td>\n",
       "      <td>31.54</td>\n",
       "      <td>0.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFPeA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>17.69</td>\n",
       "      <td>64.62</td>\n",
       "      <td>17.43</td>\n",
       "      <td>0.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHxA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>28.69</td>\n",
       "      <td>42.61</td>\n",
       "      <td>28.52</td>\n",
       "      <td>0.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHpA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>33.99</td>\n",
       "      <td>32.01</td>\n",
       "      <td>33.86</td>\n",
       "      <td>0.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFNA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>45.30</td>\n",
       "      <td>9.40</td>\n",
       "      <td>45.26</td>\n",
       "      <td>0.04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFDA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>48.76</td>\n",
       "      <td>2.49</td>\n",
       "      <td>48.75</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFBS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>21.41</td>\n",
       "      <td>57.19</td>\n",
       "      <td>21.18</td>\n",
       "      <td>0.23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHxS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>46.65</td>\n",
       "      <td>6.70</td>\n",
       "      <td>46.62</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Volatilization  ADSolids  ADLiquids  Compost  Contact Water\n",
       "PFOA   0.0             38.92     22.16      38.83    0.09         \n",
       "PFOS   0.0             48.06     3.88       48.04    0.02         \n",
       "PFBA   0.0             31.68     36.63      31.54    0.15         \n",
       "PFPeA  0.0             17.69     64.62      17.43    0.26         \n",
       "PFHxA  0.0             28.69     42.61      28.52    0.17         \n",
       "PFHpA  0.0             33.99     32.01      33.86    0.13         \n",
       "PFNA   0.0             45.30     9.40       45.26    0.04         \n",
       "PFDA   0.0             48.76     2.49       48.75    0.01         \n",
       "PFBS   0.0             21.41     57.19      21.18    0.23         \n",
       "PFHxS  0.0             46.65     6.70       46.62    0.03         "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AD.InputData.AD['frac_cured']['amount'] = 0.5\n",
    "AD.calc(Inc_flow=DewateredWWTSolids)\n",
    "AD.report(normalized=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "AD.plot_sankey(gap=0.8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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xcXFh4sSJ6e7buXNnGjRogLOzM4sWLQJg0qRJREdH4+7uTu/evQGws7N7at9du3bRsWNHADp06IC7uzvu7u4ULVqUJUuWEBYWRvPmzalfvz7169fXJ8CTJk1i7969uLu789VXX6Up58GDB3Tu3Jm6devSqFEjTp48CcD06dMZNGgQ3t7eVK1aVZLdAkSSV5EvyC0sIYTIOyVKlMDLy4tNmzYBulbXl19+mYkTJ7Jjxw6Cg4M5evQoq1evfmrfn3/+maCgIAIDA1mwYAH3799n9uzZWFtbExwczO+//56pGDZu3EhwcDCLFy+mSpUqdO7cmTJlyrBt2zaOHTvG8uXL9fXq7Nmzad68OcHBwYwdOzZNOdOmTaNevXqcPHmSzz77jH79+unXnT17li1btnDkyBFmzJhBfHx8Nj8xkZ9I8iryBbmFJYQQeSt1vRsQEECVKlXw9vamdOnSmJmZ0bt3b/bs2fPUfgsWLMDNzY1GjRpx7do1zp8/n+0Y7t27R9++fVm2bBlFixYlPj6et99+G1dXV958801CQ0OfW8a+ffvo27cvAK1bt+b+/fs8efIEAF9fXywtLSlVqhRlypTh9u3b2Y5V5B+SvIp8QW5hCSFE3nrttdf4+++/OXbsGFFRUbi7uz93n127drF9+3YOHjzIiRMnqFevHjExMdk6fmJiIj169GDq1Kn6u2FfffUVZcuW5cSJEwQGBuq/E7LL0tJS/9rU1JSEhIQXKk/kD5K8inxBbmEJIUTesrOzo1WrVgwaNIiePXvi5eXF7t27uXfvHomJifj7+9OyZcs0+zx+/JjixYtjY2PD2bNnOXTokH6dubl5luq0SZMmUbduXXr06JGm/PLly2NiYsLSpUtJTEwEwN7envDw8HTLad68ub6e37VrF6VKlaJIkSKZjkMYH0leRb4ht7CEECJv9ezZkxMnTtCzZ0/Kly/P7NmzadWqFW5ubjRo0IDXXnstzfbt27cnISGB2rVrM2nSJBo1aqRf984771C3bl393a7nmTt3Llu3btXf8Vq7di3Dhg1jyZIluLm5cfbsWWxtbQGoW7cupqamuLm58dVXX6UpZ/r06QQFBVG3bl0mTZrEkiVLXvBTEfmdmaEDECLFa6+9xtixY9Pcwrp48eIz90l9C8vGxgZvb+9cu4WVlJSElZVVtspOIbewhBD5SefOndE0Tf++Z8+e6Y41CAsL079OuUP2X3PmzGHOnDn69xEREYBugG1ISAgA3t7eeHt7A6Q5bmopXa1SygRdq+6OHTvSbJdSTokSJdK9Kzd9+vQ071NiEMZPWl5FviG3sIQQQgjxPJK8inxFbmEJIYQQ4llURs326fHw8NACAwNzMRwhhMgdSqkgTdM8DB1HXpI6W+RHmzdvZvTo0SQmJjJ48GAmTZpk6JBEPvSsOltaXguo1atXo5Ti7NmzgK6/krW1NfXq1aN27dp4eXnh5+en397Pz48RI0Y8VU6HDh149OhRtmJ41sT9mXnIgBBCiIIlMTGR4cOHs2nTJkJDQ/H398/UQFghUpMBWwWUv78/zZo1w9/fnxkzZgBQrVo1jh8/DsClS5d4/fXX0TSNgQMHZljOxo0bsx2Dh4cHHh6FqqFLCCHEMxw5cgQnJyeqVq0KQI8ePVizZg116tQxcGTCmEjLawEUERHBvn37WLx48VNPrUpRtWpV5s2b99yJ8lO3kM6cOZMaNWrQrFkzevbsydy5cwHdiM+UW5P37t3D0dERSPsAgPv379OuXTucnZ0ZPHiwfpRpZGQkvr6+uLm54eLiwvLly1/4/IUQQuRPN27coFKlSvr3FStW5MaNGwaMSBgjSV4LoDVr1tC+fXtq1KhByZIlCQoKSne7+vXr67sVPE9QUBABAQEEBwezceNGjh49mqWYZsyYQbNmzTh9+jRdunTh6tWrgK7vU4UKFThx4gQhISG0b98+S+XmhM2bN1OzZk2cnJyYPXt2nh9fCCGEEJknyWsB5O/vr5/uqUePHvj7+6e7XVYG6+3du5cuXbpgY2NDkSJF6NSpU5Zi2rNnD3369AF0E/UXL14cAFdXV7Zt28bEiRPZu3cvRYsWzVK5L0r6XwkhRN5xcHDg2rVr+vfXr1/HwcHBgBEJYyR9XguYBw8esGPHDk6dOoVSisTERJRSDB8+/Kltjx8/Tu3atV/4mGZmZiQlJQFk+QEBNWrU4NixY2zcuJHJkyfTpk0bpk6d+sIxZZb0vxJCiLzj6enJ+fPnuXz5Mg4ODgQEBLBs2TJDhyWMjLS8FjCrVq2ib9++XLlyhbCwMK5du8ZLL72U5koXdLMPjB8/npEjR2aq3BYtWrB69Wqio6MJDw9n3bp1+nWOjo76rgmrVq3KcP+UCmrTpk08fPgQgJs3b2JjY0OfPn2YMGECx44dy/I5vwjpfyWEEHnHzMyMhQsX4uPjQ+3atenWrRvOzs6GDksYGWl5LWD8/f2ZOHFimmVvvPEGs2bN4uLFi9SrV4+YmBjs7e0ZNWoUAwYM0G/n5+eX5hF7qZ9WVb9+fbp3746bmxtlypTB09NTv278+PF069aNRYsW4evrm25c06ZNo2fPnjg7O9OkSRMqV64MwKlTp5gwYQImJiaYm5vz3Xff5cCnIIQQIr/q0KEDHTp0MHQYwojJQwpEtkyfPh07OzvGjx9v6FBeyMGDB5k+fTpbtmwBYNasWQB88MEHhgxL5AJ5SIEQQhgPeUiBEBlI3f8qLi6OgICALA9GE0IIIUTekW4DIlumT59u6BByROr+V4mJiQwaNEj6XwkhhBD5mCSvotCT/ldCCCGE8ZBuAyKN503YP2/ePOrUqUPdunVp06YNV65cASA4OJjGjRvj7OxM3bp15UlZQgghhMgVkrwKvcxM2F+vXj0CAwM5efIkXbt25f333wfAxsaGX3/9ldOnT7N582bGjBnDo0ePDHAWQgiRv6xevRqllP6JhmFhYVhbW1OvXj1q166Nl5cXfn5++u39/PwYMWLEU+V06NAh2/VqYGAgo0aNSndd6seA54Uff/qJSR9NISEhIc+OKQoW6TYg9DIzYX+rVq30rxs1asRvv/0G6B42kKJChQqUKVOGu3fvUqxYsbwJXggh8il/f3+aNWuGv78/M2bMAKBatWocP34cgEuXLvH666+jaRoDBw7MsJyNGzdmOwYPDw88PAw72UZiYiLDR47hl19/xcTChgMHD7Hur1V5/mRFYfyk5VXoZXXC/sWLF/PKK688tfzIkSPExcVRrVq1XIlTCCGMRUREBPv27WPx4sUEBASku03VqlWZN28eCxYseGZZqVtIZ86cSY0aNWjWrBk9e/Zk7ty5AHh7e5MyPdq9e/dwdHQEYNeuXXTs2BGA+/fv065dO5ydnRk8eLD+UeGRkZH4+vri5uaGi4tLjnf/0jSN/QcPEhf5hJiH/3LlyhUePHiQo8cQhYMkryJbfvvtNwIDA5kwYUKa5bdu3aJv37788ssvmJgYx59XQkJClh9rK4QQmbFmzRrat29PjRo1KFmypP5phP9Vv359fbeC5wkKCiIgIIDg4GA2btzI0aNHsxTTjBkzaNasGadPn6ZLly5cvXoV0I15qFChAidOnCAkJIT27dtnqdznMTMz49TxQBo0aADAlYvneOmll3L0GKJwMI7sQuQJBweHNI+RvX79Og4ODk9tt337dmbOnMnatWuxtLTUL3/y5Am+vr7MnDmTRo0a5UnML+rWrVvU82xEhcqOyGTuQoic5u/vT48ePQBdVyx/f/90t8vKA4P27t1Lly5dsLGxoUiRIlmem3rPnj306dMHAF9fX4oXLw6Aq6sr27ZtY+LEiezdu1du54t8S/q8Cr3UE/Y7ODgQEBDAsmXL0mxz/Phx3n33XTZv3kyZMmX0y+Pi4ujSpQv9+vWja9eueR16tkREROBW34O7/94EoEmz5hw6sJ/69esbODIhREHw4MEDduzYwalTp1BKkZiYiFKK4cOHP7Xt8ePHqV279gsf08zMjKSkJIAs31GqUaMGx44dY+PGjUyePJk2bdowderUF45JiJwmLa9CL/WE/bVr16Zbt244OzszdepU1q5dC8CECROIiIjgzTffxN3dXX/Fv2LFCvbs2YOfnx/u7u64u7sTHBxswLN5PltbW6Z8OEn//tOPZ+j7hwkhxItatWoVffv25cqVK4SFhXHt2jVeeumlNHe4QDf7wPjx4xk5cmSmym3RogWrV68mOjqa8PBw1q1bp1/n6Oio75qwatWqDPdPaZjYtGkTDx8+BODmzZvY2NjQp08fJkyYwLFjx7J8zkLkBWl5FWmkN2H/xx9/rH+9ffv2dPfr06eP/jaUsVBKMXLkSH7//XcOHz6sn/ZLCCFygr+/PxMnTkyz7I033mDWrFlcvHiRevXqERMTg729PaNGjWLAgAH67fz8/Fi9erX+/aFDh/Sv69evT/fu3XFzc6NMmTJ4enrq140fP55u3bqxaNEifH19041r2rRp9OzZE2dnZ5o0aULlypUBOHXqFBMmTMDExARzc3O+++67HPgUhMh5Kiv9bDw8PDTpFygKmkaNGnH48OEs9TkTxkcpFaRpmmHnCspjUmcXDtOnT8fOzo7x48cbOpRM8fDwICgoSOpc8UzPqrOl24AQQgghhDAa0m1ACCGEMGLTp083dAhC5ClpeRVCCCHyoc2bN1OzZk2cnJyYPXv2U+tjY2Pp3r07Tk5ONGzYkLCwsDTrr169ip2dnf4BBkIUFJK8iizRNC1Pn4EthBCFUWJiIsOHD2fTpk2Ehobi7+9PaGhomm0WL15M8eLFuXDhAmPHjn1qcNi4cePSfQqiEMZOkleRafHx8Qx8623KlC3LJ5/OlM72QgiRS44cOYKTkxNVq1bFwsKCHj16sGbNmjTbrFmzhv79+wPQtWtX/v77b329vHr1al566SWcnZ3zPHYhcpskryJTHjx4QItWL7P2YAjlB33Ll4uW0r1XH2JjYw0dmhBCFDg3btygUqVK+vcVK1bkxo0bGW5jZmZG0aJFuX//PhEREcyZM4dp06blacxC5BVJXsVznTt3Drf6npxPLIX9qx9iXrIiRd6cyd8h12nUrCV37twxdIhCCCGSTZ8+nbFjx2JnZ2foUITIFZK8imfavn07no2aEFPHF7uWg1AmpgCYmFth12E816yqUre+ByEhIQaOVAghCg4HB4c0T+K6fv06Dg4OGW6TkJDA48ePKVmypP6hK46OjsyfP5/PPvuMhQsX5mn8QuQmSV5Fhr797js6d+2Otc972Nb1eWq9UibYNe1NYv1uNG7ekg0bNhggSiGEKHg8PT05f/48ly9fJi4ujoCAAP3juFN06tSJJUuWALpHwbZu3RqlFHv37iUsLIywsDDGjBnDhx9+yIgRIwxxGkLkCpnnVTwlISGBkaPHsezPtRTtNgvzEg7P3N62TivMipaje9+BTPtwIuPfG4dSKo+iFUKIgsfMzIyFCxfi4+NDYmIigwYNwtnZmalTp+Lh4UGnTp1466236Nu3L05OTpQoUYKAgABDhy1EnpDHw4o0Hj9+zGtvdOPk1fvYdpiAqVXm+0wlPL5DxLqZdGrbksWLvsfc3DwXI8058njYwkEeDytE/iCPhxWZIY+HFZnWrGVr9u7ZjUWdl7OUuAKYFS2Dec2WLF3yC9169cmlCIUQQghRmEm3AZHGjKkfsW/fPpau3Qi1mmd5/6jAv/hs5ky8vLxyITohhBBCFHaSvIo0Xn/9dcqVK8fStduzXcbgwYMpXbp0DkYlhBBCCKEj3QaEEEIIIYTRkORVCCGEEEIYDUlehRBCCCMUGBhIyzbtOHz4sKFDESJPSfIqhBBCGJnly1fg/XI7TsSUpE27V1i2zN/QIQmRZyR5FUIIIYzItBkf07tvP2zbv0ex5n2w6ziR/gMH8eHkKYYOTYg8IcmrEEIIYUSCT52mXAUHkk6tByDx5AbKlC3HiZBQA0cmRN6Q5FUIIYQwImtWLWfpLz+hEuIAMEmM5ecfv2fD6j8MHJkQeUOSVyGEEEIIYTQkeRVCCCGEEEZDklchhBBCCGE0JHkVQgghhBBGQ5JXIYQQQghhNCR5FUIIIYQQRkOSVyGEEEIIYTQkeRVPiY2NBRPTbO2blJSIiYn8WQkhhBAid0iWIZ5y4cIFsC6WrX0T4mKxtrbO2YCEEEIIIZJJ8iqeMv+b71HVm2d5v6TYSExMTLCyssqFqIQQQgghJHkV/7F7926uXr+JdVWPLO8bd/siNeu4SLcBIYQQQuQayTKE3okTJ+j8xptYt3oXlY0+r3H/XqBxQ69ciEwIIYQQQkeSV8HFixcZPfY9mrZshVnTQdhU88xWOWYPw2jSMHv7CiGEEEJkhpmhA8hv4uPjafmyDw8fPcqR8s6ePJ4j5WTGSzXqZGl7TdOIiowgPCICG+c2FO3xBebFymXr2FpCPFFhJ2jWrFm29hdCCCGEyAxJXtORlJjI9UhT7Jr0fOGySjv5En35WQmslvyP9v/vtYzW6RLO9JjZlSCmVtMsx2dmbk1p+1IoM/Ms75ta1LkDuLq6Uq1atRcqRwghxPPFxMSAie4rXEuIx8LCwsARCZF3JHn9D3Nzczau/Qu3+p7E3LuCbd12L1ymTfVGORBZ/qaFbuH9L6YbOgwhhCgUQs+cIcm2BAAJ0U8oXry4gSMSIu9In9d0lChRgu1bNhJ36Hdirp40dDj5XtztSxBxl1dffdXQoQghRIGnaRrzF36HWU1v4h/cIDHyMbVr1zZ0WJmWmJho6BCEkZPkNQM1a9Zk1XJ/wjfOJf7hTUOHk29pSYlE7/qBqR99iJmZNOQLIURuCwgIIDw2CcuKzsSe2sLbbw3C0tLS0GFl2pUrVwwdgjBykrw+Q9u2bfn8s0+IWPspSTERhg4nX4o8to7q5YszYvgwQ4cihBAF3rp16xg8ZDjWbUehxccQdXoHI4YPNXRYWfLw4UP69Olj6DCEEZOmsucYPmwYp0LOsGLjXOw7T8nW/KcFVfz968QE/kHAsUB5MIEQIs9pmkZcXFyOlJWUlMSjbMwyo5TK0nIbG5ss3aXSNI2oqCgOHDjA3Pn/I+h4MEU6fYRFmZeI2DCH11/vgqOjY5bjNpQlS5YA8OOPPxo4EmHMJHnNhIULvuKsTwdCdv2EXet3DR1OvpAYHU7Exs+Z9eknVK1a1dDhCCEKofXr19OpUydMX3C2FIDEhPgciChzzCyydovf3NIKm9KVofbLlBw0FKUUEZu+pFYpS35e9H0uRZnzrl27xoABA6hRo0aBeIy4pmncuXOHsmXLGjqUQkeS10wwMzNjzZ8rcfdoSMSx9djW72jokAwqKSaC8DUf079b5wLRXSA+Pu++tIQQOcfb2xunWs48qtgE2wavGTqcXJcUG0nkya0khGyiVdOGBPz2q1FMkaVpGjNnzmTKlCkAnD171sAR5Qx/f3/eevsdDh88QN26dQ0dTqEiyWsmFS1alL+3bKS+ZyOii5XHumoDQ4dkEImRDwlf/TE9Xm3H1/PmZnhrzJicOXPG0CEIIbLB3t6e7Zs3UM+zIdHFKmCdzacD5mcJEQ+48U2/NMtatmyJa+2afPbZZwaKKnN2797Nnj170iybPHky06ZNM1BEOevkyZMkmVvT9hVfTh4LlBbYPCTJaxZUrVqVdav/4JVXO2Pa9VMsSlU2dEh5Kur8IaJ2/sCYEcP4ZMa0ApG4appGdHQ0EydONHQoQohsqFKlChvW/EXbVzpiWuRjLEo7GjqkHKVMTFHmVphY22NdtQGmtiUIToDgnZcMHdpzxd78/4HORZv0BKX4nxHEnXm2lOwyhbiLh/Hx7cShfbsLRHcIY6AyemJTejw8PLTAwMBcDMc4/PKLH6MnTqZoj88xtSlq6HByXWL0E6J2/YT1o8v4/7aE5s2bGzqkHDNz5kwmT55MQkICpqYyGK8gU0oFaZrmYeg48lJhqrOXLv2NYeMmUqzH55jaFjN0OKIQ0bQkIjZ9iXetcqxa7l8gGnbyg2fV2TJEPBsGDhzA4H49idzwOVpiwe0vmfD4DuF7f+XhkhF0b+7CuTMhBSpxDQ4OZvLkyfj6+uaLxDUmJoZr164ZOgwhjFLfvn0YNngAERtmoyXkzAwEQmSGUibYth3J34dPMOOTTw0dTqEgyWs2zf18Dl61KhP59/dkpfU6P9M0jYTHd4g8u4+IdZ/xaNk4utcvR9DhA3y78GtsbGwMHWKOiIuLY/DgwdSrV48iRYqwfv16Q4cEwCeffoqre32ZwFuIbJo18xOa1q1OxPZvC0y9LIyDibkVdq9+yJcLvmHFipWGDqfAk24DLyAiIoIGDZvwoJwntp6vGzqcLIu5FsLtZZPSXVe+fHl69OiBra1tHkeVe7755hsePnyYZtnkyZMNFM3Tdu7cxZHQi1QpU5xjRw9hb29v6JAKFOk2UDhERUXh0agpd0q6YdfwTUOHIwqZuNsXefLXdHZt34qHR6GqbnLcs+psGbD1Auzs7Ni+eQPuDTyJKuaATfWGhg4pS5SJKcrMEmVmjlmx8liUq4apXUkAooCfj94xbIA5LFLTza1oal8KOzcfAP6367IhQ0pLVaFMj0E8OLyCLl27s2XjunzRnUEIY2JjY8O2TetxS6mXazYxdEiiELEoWw2b1kNp7/sqJ44F4uDgAMDq1avp0qULZ86coVatWoSFhVG7dm1q1apFTEwM9vb2DBs2jAEDBgBw+/Zt3nrrLa5du0Z8fDyOjo5s3Lgxw+OGhYXRsWNHQkJCCAwM5Ndff2XBggVPbefo6EhgYCClSpXKlfPPK5K8vqBKlSqxaf1aWrdtj1mR0liUNZ4J+y0dalP5vT8MHUaeKda0p6FDyBS71u8S9NcMxo5/nwVffWnocIQwOg4ODmzZsI6WbdpiWrQMluWcDB2SKERsajQh4uENXm7vS+Ch/dja2uLv70+zZs3w9/dnxowZAFSrVo3jx48DcOnSJV5//XU0TWPgwIFMnTqVtm3bMnr0aEA3LVdmeXh4FPhWX+nzmgO8vLz48ftvCV/3GYkRD5+/gxDPoEzNsfOdiN+yFSySRygKkS0NGjTA76cfCV83i4Tw+4YORxQytl5duWNWhm69+vDkyRP27dvH4sWLCQgISHf7qlWrMm/ePH1r6a1bt6hYsaJ+fcpDEDRNY8KECbi4uODq6sry5cufKmvXrl107Kh7mNL9+/dp164dzs7ODB48WN8XPDIyEl9fX9zc3HBxcUm3nPxMktcc0rNnD0YPe4eI9bNIio81dDjCyJla22PfaTLjJkxi9+7d+uWrV69GKaV/Qk1YWBjW1tbUq1eP2rVr4+XlhZ+fn37727dv07FjR9zc3KhTpw4dOnR45nHDwsJwcXEBIDAwkFGjRqW7naOjI/fu3XvBsxQid3Xt+gbvjxlBxLrPSIqPMXQ4ohBRSmHXZhgHTl2kV+8+tG/fnho1alCyZEmCgoLS3ad+/fr6un348OG89dZbtGrVipkzZ3Lz5k0A/vzzT4KDgzlx4gTbt29nwoQJ3Lp1K8M4ZsyYQbNmzTh9+jRdunTh6tWrAGzevJkKFSpw4sQJQkJCaN++fQ5/ArlLktcc9MmM6bT0cCZy+0IZ6SpemHnJiti2H8drr3flwoULAGluPaVIufV05swZAgICmD9/Pr/88guA/tbTiRMnCA0NZfbs2Zk+voeHR7p9poQwJlMmf0TbJvWJ3LoATUsydDiiEFFm5th1nMTmrVspWVLXx7RHjx5p6u/UUucNPj4+XLp0ibfffpuzZ89Sr1497t69y759++jZsyempqaULVuWli1bcvTo0Qxj2LNnD3369AHA19eX4sWLA+Dq6sq2bduYOHEie/fupWhR45qzXpLXHKSUwn/pEiqYPCHykHE1wYv8ydrRHXPP7rzs04Hr16/LrSchskgpxVK/n6lsFUvkgfSTBiFyjTIhMTGJuXPnUr58eb744gtWrFiRbgPX8ePHqV27tv59iRIl6NWrF0uXLsXT0/OpR+2+iBo1anDs2DFcXV2ZPHkyH3/8cY6VnRckec1h1tbWbN24DpPzO4k8s9fQ4YgCwNb9FSJK1aZNu/a0a9dObj0JkUVWVlZs2bAWs8v7iAzdZehwRCES9c9+7FzaUPqNKcTEJ7J3715eeumlpx5IExYWxvjx4xk5ciQAO3bsICoqCoDw8HAuXrxI5cqVad68OcuXLycxMZG7d++yZ88evLy8Mjx+ixYtWLZsGQCbNm3STxd58+ZNbGxs6NOnDxMmTODYsWO5cfq5RpLXXFC+fHm2blxP9O5FxN78x9DhiALAtuVbXL56nX/v3AXk1pMQWVWmTBm2bdpAzN6fib1xxtDhiEIi8sxubGo0xrqaJ2b1OtPGpwO+vr7MmjWLixcv6scrdOvWjVGjRjFw4EAAgoKC8PDwoG7dujRu3JjBgwfj6elJly5dqFu3Lm5ubrRu3ZrPP/+ccuXKZXj8adOmsWfPHpydnfnzzz+pXLkyAKdOncLLywt3d3dmzJiRr+Y8zwyjmyrLzs6OiIiIPD/u1KlTadGiBS+//HKmtnd3d+c3v5/pM+gdTHt8gVmR/59T7fp3gzCxsAalMLUtTinfcZjaFf//5Sa6a4oSbYdhVbE2cXev8GD7DyRG3ActCVvn1hRt0iPN85Nv/jIS8xIVKf3axJw9cZEvJMVGkRAbzZYtmylRsiS2NjYopRg+fPhT22Z066lXr1507NgxV249bdy4kcmTJ9OmTRumTp2aY+ULkZNcXV3xX7qEHv0GYtr9c8yKljF0SKKAK9dzlv61Tf1OPHp4gy3bd7J10/pnzuM9YcIEJkyY8NRypRRffPEFX3zxRZrljo6OhISEAODt7Y23tzcAJUuWZOvWrU+V4+Pjg4+PT3ZOKV+QltdM+vjjjzOduKbo3LkzH0wYR8T6z0iKSzvStWzPz6gwaCEW5Zx4fGhF2uUD/0eFgf/DqmJtkuJjufvnJxRt1BWHt3+g/MD/EXvjLBHHN+j3ib93DZKSiL1++qnjiIIh6p/92Dq3pvzgH4hLMuGnn36SW09CZEPHjh2Z+sFEwtfOJCk2ytDhiEJEKYVdq3c4fvk2Y957OjEVmWe0yeuuXbvw9vama9eu1KpVi969e+tvlx49epQmTZrg5uaGl5cX4eHhxMTEMHDgQFxdXalXrx47d+4EwM/Pj86dO9O2bVscHR1ZuHAh8+bNo169ejRq1IgHDx4AMGDAAFatWgXornCmTZtG/fr1cXV11fcvvHv3Lm3bttUPaqlSpQrvDH6LV1o0JGLLV+mOdLWq5EL8w5sZnmdk6G4sHWpj/VJ9QPf85BJth/D40Kr/3+bMbmxdWmHlWJ/oC4dy4NMV+U3KrSfzYuWw6zCeN3v0omnTpnLrSYhsmDD+PTq1bUHE5nloSYmGDkcUIsrUDFXJnX37Dxg6FKNmdN0GUjt+/DinT5+mQoUKNG3alP379+Pl5UX37t1Zvnw5np6ePHnyBGtra77++muUUpw6dYqzZ8/Srl07zp07B0BISAjHjx8nJiYGJycn5syZw/Hjxxk7diy//vorY8aMeerYpUqV4tixY3z77bfMnTuXn376iRkzZtC6dWs++OADNm/ezOLFi1FK4bf4R5q2bE3Yvt+wa94vTTnRF49gUdpR//62/4dgYoIyNad8v3nE37uCxX+eDmNevDxaXDRJsVGYWNoQeXYvZbt/Qvz964QHrcO2jndOf9TCwFLferKq5EJCk34s+d2fk8cCKVmyZIb7ya0nIZ6mlGLxou9p3uplLu77FbsWAw0dkigkoi8Gop3awF9HDxs6FKNmtC2voHuyVcWKFTExMcHd3Z2wsDD++ecfypcvj6enJwBFihTBzMyMffv26Qec1KpViypVquiT11atWmFvb0/p0qUpWrQor776KqDrHxUWFpbusV9//XVA9xSXlG327dtHjx49AGjfvr1+UIulpSWb16/B4tphIkP+BnRJ6s1fRpIUG0XRRm/qy03pNlC+37xMfQaxt85jal0EsyJlsKriRtztSyRGh2f2IxRGys71ZSKLV2fs+PcNHYoQRsnCwoKNa//C6uYxIk8+fWEmRE6Lu3uFyG0LWLf6TxwdHTPcbvPmzdSsWRMnJ6dnzs39xx9/oJQiMDAQgPj4ePr374+rqyu1a9dm1qxZGe5r7Iy65dXS0lL/2tTUlISEhBcux8TERP/exMQkwzJTtsnscUuVKsX2zRtp1LQ5WqJG2Z5fYWrz/JHZ5qUqE3stJM2y+Ef/oiysda2uZ3YTf/86178bBEBSXBRR/+zH3l2mLCrI4h/cICEsiEHzPzR0KEIYrZIlS7J980a8GjfDtFh5rCq7GjokUUAlRj0mfN1Mvl0wn6ZNm2a8XWIiw4cPZ9u2bVSsWBFPT086depEnTp10mwXHh7O119/TcOGDfXLVq5cSWxsLKdOnSIqKoo6derQs2fPZybKxsqoW17TU7NmTW7duqWf9ic8PJyEhASaN2/O77//DsC5c+e4evUqNWvWzNFjN23alBUrdIOvtm7dqh/UkqJOnTosX/YbWtRj4h/fyVSZtnW8ib0eSnRYMABJ8bE83P4DRRq+gaYlEXV2H+UHLaTi0J+pOPRnyrw+hcgzOTeaXOQ/idHhhK/9lC8/n6W/rZ+e5129f//997i6uuLu7k6zZs0IDQ0FIC4uTt8/3M3NjV27duXSmYiCzM7OziDHnTp1Ktu3b8/09rVq1eKPFf5EbJr71PiD698N4ubi4dz8eQS3l08hMeJh2uW/jOTmLyOJua6beivu7hX+9f+QGz++y41Fb/Nov79+LEZi5EPurJrBzZ9HcPOnodxeOS2Hzljkd1pCPBHrZzNkYD/69ev7zG2PHDmCk5MTVatWxcLCgh49erBmzZqntpsyZQoTJ07EyspKv0wpRWRkJAkJCURHR2NhYUGRIkVy/HzygwKXvFpYWLB8+XJGjhyJm5sbbdu2JSYmhmHDhpGUlISrqyvdu3fHz88vTYtrTpg2bRpbt27FxcWFlStXUq5cOezt7dNs88orr1CsWDEit3yVqZGuJuaWlH5jCo8PBHDjx3e59fMILMpVx75+R2KvncbUriRm9v/f59GykjPx96+SEPEgR89N5A9aYgKRGz+nX/c3ePeddzLcLuXqfdOmTYSGhuLv769PTlP06tWLU6dOERwczPvvv8+4ceMA+PHHHwHdYKxt27bx3nvvkZQkj9UUxiE7M8O0bduW2Z/OIGLtTJJi0k7FmFMzwzza+ztWju5UGLSQCoO/o3jLAS98riL/0zSNyB3f0ti5KnNmzXzu9jdu3KBSpUr69xUrVuTGjRtptjl27BjXrl3D19c3zfKuXbtia2tL+fLlqVy5MuPHj6dEiRI5cyL5jNF1G0iZ4zX1YBKAhQsX6l97enpy6NDTo+5Tnvee2oABAxgwYID+feo+rqnX+fn5pbuNh4eHvmWqaNGibNmyBTMzMw4ePMjRo0fTTZDv37/H4HeG8Nemudh3+ghlopvrreLQn9M9Z4vSjpTr9XTLmVVlV8r3+zLNMmViSqURv6VbjjBumqYRuXMR9auW4+t5c5+5beqrd0B/9Z761lPqK/LIyEj9vMGhoaG0bt0a0E3sXqxYMQIDA585lZYQGdm1axfTp0+nVKlShISE0KBBA3777TeUUhw9epTRo0cTGRmJpaUlf//9N+bm5gwdOpTAwEDMzMyYN28erVq1ws/Pj9WrVxMZGcn58+cZP348cXFxLF26FEtLSzZu3EiJEiUYMGAAHTt2pGvXrjg6OtK/f3/WrVtHfHw8K1eupFatWty9e5devXpx8+ZNGjduzLZt2wgKCuLU6VBWbpyLfecp+no5hVUlF54Erc3wPDOaGea2/wfY1+9IYuQDrF6qp9/eosxLufOBi3wl8uiflI6/w8qA/ZiYvHh7YVJSEuPGjUuTk6Q4cuQIpqam3Lx5k4cPH9K8eXNefvll/fdAQVLgWl4N6erVq3h6euLm5saoUaP0LVj/pZTi+28XUruMDZF7/PI2SGG0oo6to1j4Zf5atfyZk1tD5q7eAb755huqVavG+++/z4IFCwBwc3Nj7dq1JCQkcPnyZYKCgp6aT1aIrDh+/Djz588nNDSUS5cusX//fuLi4ujevTtff/21/jHF1tbWfPPNN/qZYfz9/enfvz8xMbr5q0NCQvjzzz85evQoH330ETY2Nhw/fpzGjRvz66+/pnvslJlhhg4dyty5uou+lJlhTp8+TdeuXfWPO/5mwde4VCxGxM6n6+70Zoa5+ctIbv2qu2PxvJlh7Ov5cn/TAv71/4DHB5aTEH7/hT9Xkb9FnTsIpzexffMGbG1tM7WPg4NDmvr2+vXrODg46N+Hh4cTEhKCt7c3jo6OHDp0iE6dOhEYGMiyZcto37495ubmlClThqZNm+oHcxU0krzmoOrVq3P8+HFOnDjB0aNH9TMepMfc3Jw+PbuTcO1EHkYojFX0xUASg1ezfcvGp7qivIjhw4dz8eJF5syZw6effgrAoEGDqFixIh4eHowZM4YmTZo8N1kW4lmMZWYYMzMz1v21iiIPz+lv9+fUzDDWVRvg8O5P2Lv5EP/gOrf8RpMY9TizH6EwMnG3LxK141s2b1iXJvl8Hk9PT86fP8/ly5eJi4sjICCATp066dcXLVqUe/fuERYWRlhYGI0aNWLt2rV4eHhQuXJlduzYAejuph06dIhatWrl+LnlB0bXbaCgOHDgABM++Igib3xi6FBEPhd3N4zIbQvYunFdpkeNPu/q/b969OjB0KFDAd0X+FdffaVf16RJE2rUqJG94IXAuGaGKVq0KNu3bKSBVyO0hATK9s+ZmWEATK3tsa3jjW0db+6smkHMtRBsa2Y88lwYp4SIB4Sv+4zFP3yPh4dHlvY1MzNj4cKF+Pj4kJiYyKBBg3B2dmbq1Kl4eHikSWT/a/jw4QwcOBBnZ2c0TWPgwIHUrVv3RU8nX5KW12waNGgQZcqUwcXFJcv7hoWF0fG1Lti2HYVF6Sq5EJ0oKBIjHxG+9jO++9/XNGnSJNP7Pe/qHeD8+fP61xs2bKB69eoAREVFERkZCcC2bdswMzN7apoWIV5Ufp4Zplq1aqxb/Sda9BPiH2T8BMTUnjUzDED0lRMkxeu6PyTFRhH/8BZmRUrn0BmJ/CIpPpbI9bMYO2Io3bt3y1YZHTp04Ny5c1y8eJGPPvoI0A1ETC9x3bVrlz5BtrOzY+XKlZw+fZrQ0NB0H1BTUEjLazYNGDCAESNG0K9fv+dvnMqTJ09o49MBU/fOWFfL2hWZKFy0hHgiNsxh6Fv96du3T5b2zczV+8KFC9m+fTvm5uYUL16cJUuWAHDnzh18fHwwMTHBwcGBpUuX5sbpiUIu9cww0dHRWFtbs337doYNG8bQoUNxdXXFzMws12aG6dmzJ0uXLqVx48bpzgzTvHlzSpQoTsTmLzHv9eVzW19TZoZ5sO17Hmz7DpKSsHVuhX39jgDE/XuBh9u+BxNT0JKwd2uHZXm5o1GQaJpG5Lb/0dqrLjOmTTV0OAWaSpmDLjM8PDy0gtr5NzvCwsLo2LGj/nGaz5OYmEi7Vzpy4qEJtq2H6kd3C/FfmqYRsXUBjSrbsu6vP3JklGphp5QK0jStUF0xSp2dvtjYWExNTfUzwwwdOpTg4OB0tx097j1+XfM3RV6fjjI1z9M4hXGJOLAMh8jzHN6/J838qyJ7nlVnS8trHho9bjzHL9/GvvM0SVzFM0Ue/YMyCXdYsSxnplcRQvy/q1ev0q1bN5KSkrCwsMhwZhiAeV98zpkzr3Fs5yLsXh6eh1EKYxIZuhvTi3vYeixQEtc8IMlrHvlh0SJ+Xf4HRbt/jjKVj/1FxN0NIyk6HGVmgTK3RJlZPLVN/IMbJDz6N1eOb1mhJiZWufP0ILOiZYm+cBhCt7A96Gimp1cRQmReyswwmWFqakojLw+Clj39lCORvvj719ASE3R1tJk5mR1eo8XHEHc3LOcDUgrL8jnbbzqFqW1R4m5fImbPT+zfs4uyZcvmynFEWpJF5YGdO3fy3vsfULTbLEytc26ao8Lq1s8jnrm+SLESPHmUu08YK1cx5wfahT9+BI5ecDWQ3X9vy9L0KkKI3LFy5SrmLfyeYj3mGDoUo3Hzp6HPXG9uYYl90eJPLX9wN3caHABKlC6X42XGxkRhXqku8bf+YdmvfgV2ZH9+JMlrLjt//jyd33gT21few7yEJCM5ocrE9frXWlIi8fevE/fvBbR7FzG5f5knNy7gUKUqA/r2ZuiQd40mCfxo8mQ+mzmT5ctX0KBBA0OHI0SBMWjQINavX0+ZMmUyPUYBdI/hHPj2O9h3noaZfalcjLBgSVNHa0kkPLxF3L8XSLqrq6PDb5zHxNSUevXq07Xzq/Tu3cso7zItXbqUfv36MWvOnGdOYSVyngzYyqaePXuya9cu7t27R9myZZkxYwZvvfVWmm0ePnyIW31Pomu9gq1bewNFWvhoSYnE3blMfOjfRJ3ZjXerVowfM4pWrVrl677GR44c4fiJU7z79lvP31hkmQzYKrz27NmDnZ0d/fr1y3TyevPmTerW98Ck8UBsamZ+mjrxfP+f0J5Hu3iAmOuh9O3TlzGjhuf4tGi56dKlS6xeu46xo0fl6+8WY/WsOluS11wSHx+Pd5t2/BNXDDvvwYYOp9BKio0i8vROkk5vwd7KlInjxjBkyLvyxKhCSJLXwi0rs8NERUXh0agpd0q6YdfwzeduL15MwuPbRJ/cQszp7bi6uvL+2FF06tQJMzO5OVyYPavOlmHMuUDTNIYMG8GZO1HYthho6HAKNRNLG+zr+1Kkz9fENXqLKV/9SD3PRpw9e9bQoQkh8qGkpCS69erDbZOS2Hp1NXQ4hYJZ0bLYN+9HqcGLuVjck7cnTKd8xcr8+eefhg5N5FOSvOaC+V//j1Ubt2H3yniUibTw5QdKKawquWD/xsfcLO1Jg4aNmTVnDomJiYYOTQiRj3zw0RT2nzyP3cvD5VZwHlNm5tjW8cb+zVmYthnNgKGj6dy1G/fu3TN0aCKfkeQ1h23atIkpMz7B7tWP9M+zFvmHUibY1fOlWM+5fPHTcmmFFULo/fbb73z7kx92vpPSnYJP5B2rSi4U6zOffdcTqFHbWVphRRqSvOag0NBQuvfqg53vBMyL5fy0HCLnmBcrh/3rM7hVxguPRk3466+/DB2SEMKADh48yJARo7Dv9CGmtsUMHY4ATMytsPN+Cwuf96QVVqQhyWsOuXv3Li+374Bl0/5YVXQ2dDgiE5Qywda9A/adp9F30Dv4+S0xdEhCiFzQs2dPGjduzD///EPFihVZvHhxmvVXrlzBt1NnbNqOxKK0o2GCFBmyquicphVWBiEKGcqXA2JjY2nf8TXiKjXEzqWNocMRWWRZzgmTNz5h5PiJRMdEM3TIEEOHJITIQf7+/hmuCw8Pp41PB0zdO2FTzTMPoxJZkdIKG+XgTKu2Pqxf/SctW7Y0dFjCQKTl9QVpmsaAt94mLNIU22Z9DB2OyCbzUpUo8sanTPhwKsuWZfxFJ4QoOBITE+nStTsPbStjU/81Q4cjMsGmeiNs2r+H72uvs379+ufvIAokSV5f0Gez57Bpz2Fs241BKfk4jZl58fIU6TKNd4aNYPPmzYYORwiRy8aOf5+gi7ewa/2uzCxgRKyruGHf6SN69OnP9u3bDR2OMADJtl7AX3/9xay5X2HX8UNMLKwMHY7IARalHbHzfZ9efftz//59Q4cjhMgli378Eb9lK7DznYgyNTd0OCKLLCvUxM73fbq82Z1Dhw4ZOhyRxyR5zabg4GD6DnwL+46TMCsiz7wuSKwquWBSrSmD3x1m6FCEELlg9+7djJswCftOkzG1tjd0OCKbrCq5YPPySHw6dOTChQuGDkfkIUles+HWrVu0e8UX65bvYFm+hqHDEbnApmlv/t53UOYWFKKAuXDhAq+93hXb9uMwL1nR0OGIF2RdzRPz+q/TvXc/kpKSDB2OyCOSvGZRdHQ07Tq8SlKN1tjWbm7ocEQuMTG3wublkQx+d6h0HxCigHj06BFtfDpg7tkda0d3Q4cjcohtg1e5dDeCr+YvMHQoIo9I8poFmqbRo08/biYVwbZRd0OHI3KZVcU6mDg1k+4DQhQACQkJdOz8BpGl6mDr/oqhwxE5SCkTbF4ewbQZMzh//ryhwxF5QJLXLJgybTp7gkKxfXmEjEwtJGya9Gb7zl2cOHHC0KEIIV7A0OEjCb0Vjm3LQYYOReQC8xIOWHm+SY8+/aX7QCEgyWsm+fsH8PW3i7Dr+AEm5paGDkfkERNzSyxc2vHVgoWGDkUIkU1fL1jIinVbsOswHmViauhwRC6R7gOFhySvmXDkyBHeHjpM98xru+KGDkfkMWvXdqxYsYLHjx8bOhQhRBZt2bKFj6bNwK7TR5hY2ho6HJGLUncfuHr1qqHDEblIktfnuHbtGq907IRNmxFYlKlq6HCEAZjZlcCman2W/PqroUMRQmTBmTNneLNHL+w6jMe8WDlDhyPygHkJB6xqt2LB/74xdCgiF0ny+gwRERG08emAiasvNtUbGjocYUBmzj58+fX/0DTN0KEIITLh/v37vOzTAcum/bGq5GLocEQesqzbnh8X/0xsbKyhQxG5RJLXDCQlJfFGt548sHLAxqOLocMRBmZZyYXH0Qns3r3b0KEIIZ4jLi6O9h1fI7aSJ7YubQwdjshj5iUcMC/tyMqVKw0disglkrxmYPz7Eznyz1Vs2wyRmQUESilMXmrI5i1bDR2KEOIZNE1j4OB3uPREw7ZZX0OHIwzExKU9X8z/n6HDELlEktd0/PzzL/z0q78881qkYVbWiX2Hjhg6DCHEM8z+/As27NiPrc9YlJKvuMLKuponl8KuEhwcbOhQRC4wM3QA+U1UVBRDhw/DokhpYrd8+cLl3T13LAeiypwytb2ytP2dM2kTsVJVjaRfmDJBWdmTVNkDm9ot8mzqMouyTpzc+R2apklrvBD50Jo1a5g5Zy7FenyOiYW1ocMRBqRMTLFwactXCxay5OefDB2OyGGSvP6HjY0Ne3fvJjIyMkfKO3/+PN98k/Gox5QkKDP/Pithqly5MoMHD85SbNeuXWP+/PmEhoYCcO9SCL/99htVq+bvWRUSEhK4ceMG3//0C0d+XIJt457Y1vPN9eOa2pckSdN9bpUrV8714wkhMu/kyZP0GTAI+1c/wqxIaUOHI/IBG5d2rPhlKD//+AOmpjK/b0EiyWs6vLyy1oL5LK1ateKdd97JsfJy2ttvvw3AnTt3KFu2LH369OH8+fM4OTkZOLLn69GjB+fOncPHtxMRMeHYNu6Rq8dTSmFToTpBQUGSvAqRj9y+fZu2r/hi1WIwlhVqGjockU+Y2hXH0r44Z8+exdnZ2dDhiBwkHYIEAGXKlNE/Uq969eoGjibzatSoweH9ezC7uIfoS0G5fryE4o4cPnI0148jhMicmJgY2nV4lUSnltjWbmHocEQ+Y1HOiaCg3P9uEHlLklehp5Ti0aNHAGzYsMGwwWRBmTJlmD3zYxJP5n7MJkXLc+7i5Vw/jhDi+TRNo1ff/lxPsMW2Ue7eeRHGKb74S+yXgbYFjnQbEGkULVoUgI4dOxrVhPzdu3dn5JhxxD+8hXnx8rl2HGVmQVR0TK6VL4TIvHXr1vHXqhWUrF6PmPUzX6is6Id3CL91KYcie7Yyzo0zvW30g9v6uEzMLShVvV5uhZVzlCmJVkUwdWqGVRU3gw5wtSznxMHDfxns+CJ3SPIqnjJlyhQ++eQTQ4eRJVZWVjTw9OL03bDcTV7NLYh6FJVr5QshMq9NmzY5dpcoIiKC8ePHZ7g+owQsq4nZ6NGjs9Q16/HjxwwZMoSIiAiS4uO4E3qYr776ipo182/f3ri4OC5dusSC737gwe4fsW71LlaV6xokFoty1Ti3+jSJiYkyaKsAkeRVPMXBwcHQIWRLkSJFSIrN3VZRZWJGXFxcrh5DCJE5tra2dOjQIcfK69atW46VlZN69+4NwL179yhdujRjx47lzJkz1KpVy8CRPduYMWPYsGEDvfr2R3t5FNbVPPI8BhNLW6yKlpRBWwWM9HkVTzExMc4/izy5NSXzuwohDKRUqVL67ly1a9c2cDTPp5SiY8eObNm4nvAt80mMfGSQOCzKvkRISIhBji1yh3FmKUIIIUQhlTKwdtOmTYYNJJMaN25M586vEXVqm2ECMLcmIiLCMMcWuUKSVyGEEMKIpAyszckuE7ntvdEjiT+91SADgTVTC2JiZKBtQSLJqxBCCGFkhg4daugQsqRBgwbEPHmAlhCb58dOMjEnOjo6z48rco8kr0IIIYSRKVOmjKFDyDJLaxu0+LxPXjVlSnx8fJ4fV+QeSV6FEEIII2PIuVOzyxhjFvmTJK9CCCGEEMJoSPIqhBBCCCGMhiSvQgghhBDCaEjyKoQQQgghjIYkr0IIIYQQwmhI8iqEEEIIIYyGJK9CCCGEEMJoSPIqhBBCCCGMhiSvwuhpmkZiYiJaUlLeHs8Az+gWQgghCjtJXoXR27ZtG2ZmZqxb/SdmRUrn6rFM7UoQdPggZmZm/Pb777l6LCGEEEI8zczQAQjxolq0aMEb3Xrw96FgzIqVz9VjmdqVpEgVZ+pXLUfn117L1WMJIYQQ4mnS8iqMnpWVFSsDljF2cG8eBbxP7L8XcuU48Q9u8Hj5+/T29WbLxnXY29vnynGEEEIIkTFpeRUFglKKqVMmU6d2LQYMfofEVkOxqdkkx8qPDgsmcvM85n0xm3fefjvHyhVCCCFE1kjyKgqUrl278tJLL+Hj+yoRj25g69UVpdQLlRkZvIn4o8tZv/oPvL29cyZQIYQoJHbt3sOqP/4kJiqSogY4vgasXbeeu/cfMPfzOZiYyE1nYye/QVHgNGjQgJPHAilz/wQRW75GS4jPVjlaUiIRO3/E5vxWAg8flMRVCCGy4eLFS3yzcAFWLm0xsS6S58e3dWtP4KmzrPrjL548eZLnxxc5T5JXUSBVqFCBwEP7aexoz5M/p5AY+ShL+yfFRhK+dia1rMM5EXQEJyen3AlUCCEKuLcGDWDtmjVolw4QdWZPnh47KTaKqJ0/4FWvLieOHaVYsWJ5enyROyR5FQWWjY0Na/9cxTvdO/Eo4H3i7oZlar/4R//yePkkXm9Rj13bt0hlJ4QQL+jVV19l/+6dmAT5E3FgGZqW+/Nyxz/6l8crJtK5uTu7/t5K8eLFc/2YIm9I8ioKNBMTE+bMmsm38+bw5I+pRF88+sztY66F8Hj5JD6eNI6fFn2PmZl0CxdCiJxQt25dTh4LpGLUBSI2fUlSfEyuHSvmeiiPl09i+oQxLF70Pebm5rl2LJH3JHkVhULfvn3Ytmk98bu+IzJodbpPx4o4tZ2ojZ/zR8BvjB41wgBRCiFEwVa2bFkO7dtNq9rlCV81hYSIBzl+jMjTO4jaMJuVy35l7JhRLzxoV+Q/kryKQqNx48YcDzxCsWsHiPz7W7RE3UAuTUsiYo8fliGrOXxgHz4+PgaOVAghCq6UublHv9WTxwETiLt9MUfK1bQkIvYtxfzEHxzav5dXXnklR8oV+Y8kr6JQqVKlCseOHsK9JDz5awYJT+4QsX42L2m3OHkskNq1axs6RCGEKPCUUkyfOoXF3/6PJ39NJ+rcgRcqLykuhoj1n1Ml/iongo5Sp06dHIpU5EeSvIpCx97eni0b19H31dbc+uFt2jeozv7dOyhZsqShQxNCiEKlW7c32bV9K0n7fybiyKp0u3Q9T8KTezxZ9SFt3R05sGcnpUuXzoVIRX4iyasolExNTVnw1ZdcunSR35b8goWFhaFDEkKIQsnDw4MTxwIpffc4EVuzNjd37K1zPFr+PhOGDsT/t1+xtLTMxUhFfiHJqyjUqlSpIp35hRDCwBwcHAg8tJ+GFW158udUEqMeP3efyLP7CF/zCUt/+p6PPpgkdXkhIsmrEEIIIQzO1taW9Wv+ZPCbvjwKmEDc3SvpbqdpGhEHA+Dwr+zbtYMuXbrkcaTC0GQSSyGEEELkCyYmJnwxZxauznUYNmoMtm1HYV3NQ79eS4gjYttCKpg8ZuuxQMqXL2/AaIWhSMurEEIIIfKVfv36snXjOuJ3fUtE0Fo0TSMx4iFPVk2mmVMJjhzYK4lrISYtr0IIIYTId5o0acKxo4dp49OBh3cuEn8zlFFDBvPpxzOkf2shJy2vwqj8+++/9OjRg2rVqtGgQQM6dOjAuXPnDB0Wjx494ttvvzV0GEIIUaA4Ojpy/OghOnlUZdGCecz85GNJXIUkr8J4aJpGly5d8Pb25uLFiwQFBTFr1ixu375t6NAkeRVCiFxSpEgR/BYvomfPHoYOReQTkrwKo7Fz507Mzc0ZMmSIfpmbmxvNmjVjwoQJuLi44OrqyvLlywHYtWsXLVu25LXXXqNq1apMmjSJ33//HS8vL1xdXbl4UfdIwgEDBjBkyBA8PDyoUaMG69evByAmJoaBAwfi6upKvXr12LlzJwCnT5/Gy8sLd3d36taty/nz55k0aRIXL17E3d2dCRMm5PEnI4QQQhQe0udVGI2QkBAaNGjw1PI///yT4OBgTpw4wb179/D09KRFixYAnDhxgjNnzlCiRAmqVq3K4MGDOXLkCF9//TX/+9//mD9/PgBhYWEcOXKEixcv0qpVKy5cuMA333yDUopTp05x9uxZ2rVrx7lz5/j+++8ZPXo0vXv3Ji4ujsTERGbPnk1ISAjBwcF5+IkIIYQQhY+0vAqjt2/fPnr27ImpqSlly5alZcuWHD16FABPT0/Kly+PpaUl1apVo127dgC4uroSFhamL6Nbt26YmJhQvXp1qlatytmzZ9m3bx99+vQBoFatWlSpUoVz587RuHFjPvvsM+bMmcOVK1ewtrbO83MWQgghCitJXoXRcHZ2JigoKEv7pH5UoImJif69iYkJCQkJ+nX/HQDwrAEBvXr1Yu3atVhbW9OhQwd27NiRpZiEEEIIkX2SvAqj0bp1a2JjY1m0aJF+2cmTJylWrBjLly8nMTGRu3fvsmfPHry8vLJU9sqVK0lKSuLixYtcunSJmjVr0rx5c37//XcAzp07x9WrV6lZsyaXLl2iatWqjBo1itdee42TJ09ib29PeHh4jp6vEEIYK5kZRuQmSV6F0VBK8ddff7F9+3aqVauGs7MzH3zwAb169aJu3bq4ubnRunVrPv/8c8qVK5elsitXroyXlxevvPIK33//PVZWVgwbNoykpCRcXV3p3r07fn5+WFpasmLFClxcXHB3dyckJIR+/fpRsmRJmjZtiouLiwzYEkIUajIzjMh1mqZl+qdBgwaaKPgWLVqk6f40Cof+/ftrK1euNHQYIpcBgVoW6ruC8CN1dsE1ffr0fFtP//3331rz5s2fWp6UlKSNHz9ec3Z21lxcXLSAgABN0zRt586dWosWLbROnTppL730kjZx4kTtt99+0zw9PTUXFxftwoULmqbp6up3331Xa9CggVa9enVt3bp1mqZpWnR0tDZgwADNxcVFc3d313bs2KFpmqaFhIRonp6empubm+bq6qqdO3dO6969u2ZlZaW5ublp48ePz6NPRGTHs+psmW1ACCGEEDlGZoYRuU26DYg03h0+ikkffgRAm/a+rF2/wcAR5T4/Pz+6du1q6DCEEKJAk5lhRE6R5FWkERkRzqPHjzEvU5X9e3ZjbWlh6JCEEEIYEZkZRuQ2SV5FGkv9fuaTjz+mamk7jh4+SNu2bQ0dUrZt3ryZmjVr4uTkxOzZs59a//333+Pq6oq7uzvNmjUjNDQUgLi4OP2Ttdzc3Ni1a1ceRy6EEMZLZoYRuU2S1wLmRacnUUrx4aSJDBk8kGrVqmUrhuDgYDZu3JitfXNKYmIiw4cPZ9OmTYSGhuLv769PTlP06tWLU6dOERwczPvvv8+4ceMA+PHHHwE4deoU27Zt47333iMpKSnPz0EIIdITExNDdHQ0ABEREfmufpKZYUSuy2gkV3o/MnI1f0tKStIaNWqkfffdd/plwcHB2p49e7JcVpUqVbS7d+9mK45ffvlFGz58eLb2zSkHDhzQ2rVrp3//2WefaZ999lmG2y9btkxr3769pmmaNmzYMO3XX3/Vr2vdurV2+PDh3AtW5AlktgFRQFStXlMD9D/+/gGGDilPyMwwhcuz6mxpeS1Adu7cibm5OUOGDNEvc3Nzo1mzZkyYMAEXFxdcXV1Zvnw5ALt27cLb25uuXbtSq1YtevfujaZpLFiwgJs3b9KqVStatWoFwNChQ/Hw8MDZ2Zlp06bpyz969ChNmjTBzc0NLy8vHj9+zNSpU1m+fDnu7u76Y+W1GzduUKlSJf37ihUrcuPGjae2++abb6hWrRrvv/8+CxYsAHSf2dq1a0lISODy5csEBQVx7dq1PItdCCGe5cfvv6VI8ZLYlXOkS9duvPZaJ0OHJESekqmyCpDsTE9y/PhxTp8+TYUKFWjatCn79+9n1KhRzJs3j507d1KqVCkAZs6cSYkSJUhMTKRNmzacPHmSWrVq0b17d5YvX46npydPnjzBxsaGjz/+mMDAQBYuXJin558dw4cPZ/jw4SxbtoxPP/2UJUuWMGjQIM6cOYOHhwdVqlShSZMmmJqaGjpUIUQB8e+//zJmzBiOHj1KsWLFKFu2LPPnz6dGjRqZ2r9169YEHj7I9OnTWbRoUbZG0QcHB3Pz5k06dOiQ5X0Nxc/Pz9AhiHxCWl4LgWdNT+Ll5UXFihUxMTHB3d09zZQkqa1YsYL69etTr149Tp8+TWhoKP/88w/ly5fH09MTgCJFimBmlj+uhxwcHNK0ll6/fh0HB4cMt+/RowerV68GwMzMjK+++org4GDWrFnDo0ePMv2lIoQQz6JpOfP0qerVq7N//35939esyg9jE4TILkleC5AXnZ7E1NQ0zZQkKS5fvszcuXP5+++/OXnyJL6+vsTExLxwvLnJ09OT8+fPc/nyZeLi4ggICKBTp7S31s6fP69/vWHDBqpXrw5AVFQUkZGRAGzbtg0zMzPq1KmTd8ELIQos6d71tOfNDJPijz/+QClFYGAgAPHx8fTv3x9XV1dq167NrFmz8ipkYWCSvBYgOTk9SerpRJ48eYKtrS1Fixbl9u3bbNq0CYCaNWty69YtfStueHg4CQkJ+WIqEjMzMxYuXIiPjw+1a9emW7duODs7M3XqVNauXQvAwoULcXZ2xt3dnXnz5rFkyRIA7ty5Q/369alduzZz5sxh6dKlhjwVIUQBkpnuXdu3b2fChAncunUL0HXvmj9/PqGhoVy6dEnfvatChQrs3LmTnTt3ArruXYGBgZw8eZLdu3dz8uRJ4uLi6N69O19//bW+bFtbWz7++GO6d+9OcHAw3bt3z9PPILXMzAwDuu+Xr7/+moYNG+qXrVy5ktjYWE6dOkVQUBA//PBDhncPRcGSP+7xihyRMj3JmDFjmDNnDlZWVjg6OjJ//nwiIiJwc3NDKaWfnuTs2bMZlvXOO+/Qvn17feVYr149atWqRaVKlWjatCkAFhYWLF++nJEjRxIdHY21tTXbt2+nVatWzJ49G3d3dz744AODVYwdOnR4qj/Xxx9/rH/99ddfp7ufo6Mj//zzT67GJoQQqWXUvatIkSL67l2AvntXs2bNnipjxYoVLFq0iISEBG7dukVoaChKqae6d+UnR44cwcnJiapVqwK6Llxr1qx56m7XlClTmDhxIl988YV+mVKKyMhIEhISiI6OxsLCIt+dn8gdkrwWMBUqVGDFihVPLf/iiy/S/KcH8Pb2xtvbW/8+9QCrkSNHMnLkSP37jDrKe3p6cujQoaeWp7TGCiGE+H/Ozs6sWrUqS/tkpXvX0aNHKV68OAMGDMj33bsg/ZlhDh8+nGabY8eOce3aNXx9fdN8j3Xt2pU1a9ZQvnx5oqKi+OqrryhRokSexS4MR7oNCCGEEHlEundlTVJSEuPGjePLL798at2RI0cwNTXl5s2bXL58mS+//JJLly4ZIEqR1yR5FUIIIfJITj59KqV7V6tWrXBzc9N37+rVq1e63bvc3Nxo27YtMTExtGrVitDQUIMP2HrezDDh4eGEhITg7e2No6Mjhw4dolOnTgQGBrJs2TLat2+Pubk5ZcqUoWnTpvrBXKJgU7qHGGSOh4eHJn8YxmXs2LFUqVKFMWPGAODj40OlSpX46aefAHjvvfdwcHDQPxo1NT8/P9q1a0eFChXyMmQhcoVSKkjTNA9Dx5GXpM4W+V1CQgI1atTg77//xsHBAU9PT5YtW4azs3O623t7ezN37lw8PDyYM2cOZ8+e5ZdffiEyMhJPT08CAgKoW7duHp+FyA3PqrOl5bWAa9q0KQcOHAB0t1/u3bvH6dOn9esPHDhAkyZN0t3Xz8+PmzdvZul46fXFEkIIIdKTmZlhMjJ8+HAiIiJwdnbG09OTgQMHSuJaSEjLawF38+ZNGjZsyLVr1zh16hRz587l1q1bLF++HBsbG8qWLcu4ceNYt24d0dHRNGnShB9++IE//viDAQMG4ODggLW1NQcPHiQ0NJRx48YRERFBqVKl8PPzo3z58nh7e+Pu7q4fLfvee+8Z+rSFeIq0vAohhPGQltdCrEKFCpiZmXH16lUOHDhA48aNadiwIQcPHiQwMBBXV1dGjBjB0aNHCQkJITo6mvXr19O1a1c8PDz4/fffCQ4OxszMjJEjR7Jq1SqCgoIYNGgQH330kf44cXFxBAYGSuIqhBBCiFwlyWsh0KRJEw4cOKBPXhs3bqx/37RpU3bu3EnDhg1xdXVlx44daboVpPjnn38ICQmhbdu2uLu78+mnn3L9+nX9ekNOci2EEMZs7NixzJ8/X//ex8eHwYMH69+/9957zJs3L919s9O9SwhjJ8lrIZDS7/XUqVO4uLjQqFEjDh48qO/vOmzYMFatWsWpU6d4++23050bUNM0nJ2dCQ4OJjg4mFOnTrF161b9eltb27w8JSGEKDBkbIIQWSPJayHQpEkT1q9fT4kSJTA1NaVEiRI8evSIgwcP6ivEUqVKERERkWby7NTzANasWZO7d+9y8OBBQPdM6fRaaIUQQmRNkyZN9HXr6dOncXFxwd7enocPHxIbG8uZM2fYunUrnp6euLi48M4776BpGqtWrSIwMJDevXvj7u5OdHQ0QUFBtGzZkgYNGuDj46N/xKy3tzdjxozBw8Mjw6cLCmEsJHktBFxdXbl37x6NGjVKs6xo0aKUKlWKt99+GxcXF3x8fPSPEAQYMGAAQ4YMwd3dncTERFatWsXEiRNxc3PD3d1d31IghBAi+2RsghBZI4+HLQRMTU158uRJmmWpH/f66aef8umnnz613xtvvMEbb7yhf+/u7s6ePXue2m7Xrl05FqsQQhRGqccmjBs3jhs3bnDgwAGKFi2qH5vw+eefExUVxYMHD3B2dubVV19NU0bqsQkAiYmJlC9fXr9exiaIgkKSVyGEEMLA/js2oVKlSnz55ZcUKVKEgQMH8vbbbxMYGEilSpWYPn36M8cmpHRB+C8ZmyAKCuk2IIQQQhiYjE0QIvMkeRVCCCEMTMYmCJF58oStAmzz5s2MHj2axMREBg8ezKRJk9Ksj42NpV+/fgQFBVGyZEmWL1+Oo6MjALNmzWLx4sWYmpqyYMECfHx8nlnmjh07GD9+PHFxcTRo0IDFixdjZia9UkT+IU/YEkII4yFP2CqEEhMTGT58OJs2bSI0NBR/f39CQ0PTbLN48WKKFy/OhQsXGDt2LBMnTgQgNDSUgIAATp8+zebNmxk2bBiJiYkZlpmUlET//v0JCAggJCSEKlWqsGTJEkOcthBCCCEKOEleC6gjR47g5ORE1apVsbCwoEePHqxZsybNNmvWrKF///4AdO3alb///htN01izZg09evTA0tKSl156CScnJ44cOZJhmffv38fCwoIaNWoA0LZtW/744488P2chhBBCFHySvBZQN27coFKlSvr3FStW5MaNGxluY2ZmRtGiRbl//36G+2a0vFSpUiQkJJBye3LVqlVcu3YtN09PCCEKhM2bN1OzZk2cnJyYPXv2U+tjY2Pp3r07Tk5ONGzYkLCwMP26WbNm4eTkRM2aNdmyZctzy+zduzc1a9bExcWFQYMGER8fn6vnJkRukeRVvDClFAEBAYwdOxYvLy/s7e0xNTU1dFhCCJGv5WX3LtAlr2fPnuXUqVNER0fz008/5fk5C5ETJHktoBwcHNK0fl6/fh0HB4cMt0lISODx48eULFkyw32fVWbjxo3Zu3cvR44coUWLFvouBEIIIdKXl927ADp06IBSCqUUXl5eXL9+Pc/PWYicIMlrAeXp6cn58+e5fPkycXFxBAQE0KlTpzTbdOrUST+watWqVbRu3RqlFJ06dSIgIIDY2FguX77M+fPn8fLyemaZd+7cAXS3uObMmcOQIUPy9oSFEMLI5GX3rtTi4+NZunQp7du3z43TEiLXyVxGBZSZmRkLFy7Ex8eHxMREBg0ahLOzM1OnTsXDw4NOnTrx1ltv0bdvX5ycnChRogQBAQEAODs7061bN+rUqYOZmRnffPONvhtAemUCfPHFF6xfv56kpCSGDh1K69atDXbuQgghMjZs2DBatGhB8+bNDR2KENkiyWsB1qFDBzp06JBm2ccff6x/bWVlxcqVK9Pd96OPPuKjjz7KVJmgS16/+OKLF4xYCCEKj6x076pYsWKmuncBzyxzxowZ3L17lx9++CG3TkuIXCfdBoQQQggDyOvuXT/99BNbtmzB398fExP5+hfGS1pehRBCCAPI6+5dQ4YMoUqVKjRu3BiA119/nalTpxrm5IV4AfJ4WCFEoSCPhxVCCOMhj4cVQgghhBAFgiSvQgghhBDCaEjyKoQQQgghjIYkr0IIIYQQwmhI8iqEEEIIIYyGJK9CCCGEEMJoSPIqhBBCCCGMhiSvQgghhBDCaEjyKoQQQgghjIYkr0IIIYQQwmhI8iqEEEIIIYyGJK9CCCGEEMJoSPIqhBBCCCGMhiSvQgghhBDCaEjyKoQQQgghjIYkr0IIIYQQwmhI8iqEEEIIIYyGJK9CCCGEEMJoSPIqhBBCCCGMhiSvQgghhBDCaEjyKoQQQgghjIbSNC3zGyt1F7iSe+EIIUSuqaJpWmlDB5GXpM4WQhixDOvsLCWvQgghhBBCGJJ0GxBCCCGEEEZDklchhBBCCGE0JHkVQgghhBBGQ5JXIYQQQghhNCR5FUIIIYQQRkOSVyGEEEIIYTQkeRVCCCGEEEZDklchhBBCCGE0JHkVQgghhBBG4/8ASto0xUy82r8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "AD.plot_sankey_report(margin=0.9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PFAS balance in AD (AD solids are not Cured)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Volatilization</th>\n",
       "      <th>ADSolids</th>\n",
       "      <th>ADLiquids</th>\n",
       "      <th>Compost</th>\n",
       "      <th>Contact Water</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PFOA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>727.434261</td>\n",
       "      <td>207.130739</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFOS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>3536.048455</td>\n",
       "      <td>142.877545</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFBA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>92.656402</td>\n",
       "      <td>53.569598</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFPeA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>129.166403</td>\n",
       "      <td>235.936597</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHxA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>293.556374</td>\n",
       "      <td>217.961626</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHpA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>59.955306</td>\n",
       "      <td>28.232694</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFNA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>338.078122</td>\n",
       "      <td>35.070878</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFDA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1513.581279</td>\n",
       "      <td>38.598721</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFBS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>53.521082</td>\n",
       "      <td>71.496918</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHxS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>100.078296</td>\n",
       "      <td>7.186704</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Volatilization     ADSolids   ADLiquids  Compost  Contact Water\n",
       "PFOA   0.0             727.434261   207.130739  0.0      0.0          \n",
       "PFOS   0.0             3536.048455  142.877545  0.0      0.0          \n",
       "PFBA   0.0             92.656402    53.569598   0.0      0.0          \n",
       "PFPeA  0.0             129.166403   235.936597  0.0      0.0          \n",
       "PFHxA  0.0             293.556374   217.961626  0.0      0.0          \n",
       "PFHpA  0.0             59.955306    28.232694   0.0      0.0          \n",
       "PFNA   0.0             338.078122   35.070878   0.0      0.0          \n",
       "PFDA   0.0             1513.581279  38.598721   0.0      0.0          \n",
       "PFBS   0.0             53.521082    71.496918   0.0      0.0          \n",
       "PFHxS  0.0             100.078296   7.186704    0.0      0.0          "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AD.InputData.AD['frac_cured']['amount'] = 0\n",
    "AD.calc(Inc_flow=DewateredWWTSolids)\n",
    "AD.report()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "AD.plot_sankey()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "AD.plot_sankey_report()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PFAS balance in AD (All AD solids are Cured)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Volatilization</th>\n",
       "      <th>ADSolids</th>\n",
       "      <th>ADLiquids</th>\n",
       "      <th>Compost</th>\n",
       "      <th>Contact Water</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PFOA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.16</td>\n",
       "      <td>77.66</td>\n",
       "      <td>0.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFOS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.88</td>\n",
       "      <td>96.09</td>\n",
       "      <td>0.03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFBA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36.63</td>\n",
       "      <td>63.07</td>\n",
       "      <td>0.29</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFPeA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>64.62</td>\n",
       "      <td>34.86</td>\n",
       "      <td>0.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHxA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.61</td>\n",
       "      <td>57.05</td>\n",
       "      <td>0.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHpA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32.01</td>\n",
       "      <td>67.73</td>\n",
       "      <td>0.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFNA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.40</td>\n",
       "      <td>90.53</td>\n",
       "      <td>0.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFDA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.49</td>\n",
       "      <td>97.49</td>\n",
       "      <td>0.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFBS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>57.19</td>\n",
       "      <td>42.35</td>\n",
       "      <td>0.46</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHxS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.70</td>\n",
       "      <td>93.25</td>\n",
       "      <td>0.05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Volatilization  ADSolids  ADLiquids  Compost  Contact Water\n",
       "PFOA   0.0             0.0       22.16      77.66    0.18         \n",
       "PFOS   0.0             0.0       3.88       96.09    0.03         \n",
       "PFBA   0.0             0.0       36.63      63.07    0.29         \n",
       "PFPeA  0.0             0.0       64.62      34.86    0.51         \n",
       "PFHxA  0.0             0.0       42.61      57.05    0.34         \n",
       "PFHpA  0.0             0.0       32.01      67.73    0.26         \n",
       "PFNA   0.0             0.0       9.40       90.53    0.08         \n",
       "PFDA   0.0             0.0       2.49       97.49    0.02         \n",
       "PFBS   0.0             0.0       57.19      42.35    0.46         \n",
       "PFHxS  0.0             0.0       6.70       93.25    0.05         "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AD.InputData.AD['frac_cured']['amount'] = 1\n",
    "AD.calc(Inc_flow=DewateredWWTSolids)\n",
    "AD.report(normalized=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "AD.plot_sankey()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "AD.plot_sankey_report(margin=0.9)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sensitivity to precipitation (Curing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Percent of Incoming PFAS that \\n remains in the Compost (%)')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "precip = np.linspace(0,10,30)\n",
    "frac_remain = []\n",
    "for i in precip:\n",
    "    AD.InputData.Precip['ann_precip']['amount'] = i\n",
    "    AD.calc(Inc_flow=DewateredWWTSolids)\n",
    "    frac_remain.append(sum(AD.report()['Compost'])/sum(DewateredWWTSolids.PFAS))\n",
    "\n",
    "plt.plot(precip,frac_remain)\n",
    "plt.xlabel('Annual precipitation rate (m)')\n",
    "plt.ylabel('Percent of Incoming PFAS that \\n remains in the Compost (%)')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
