{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Anaerobic Digestion (AD)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import PFAS_SAT as ps\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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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>NaN</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  NaN         \n",
       "1  NaN         \n",
       "2  NaN         \n",
       "3  NaN         \n",
       "4  NaN         \n",
       "5  NaN         \n",
       "6  NaN         \n",
       "7  NaN         \n",
       "8  NaN         \n",
       "9  NaN         \n",
       "10 NaN         \n",
       "11 NaN         \n",
       "12 NaN         \n",
       "13 NaN         \n",
       "14 NaN         \n",
       "15 NaN         \n",
       "16 NaN         \n",
       "17 NaN         \n",
       "18 NaN         \n",
       "19 NaN         \n",
       "20 NaN         \n",
       "21 NaN         \n",
       "22 NaN         "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "AD = ps.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</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Moisture flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>VS flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Carbon flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>76</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>3678.93</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    \n",
       "2   Moisture flow  kg   800    \n",
       "3   VS flow        kg   120    \n",
       "4   Carbon flow    kg   76     \n",
       "5   PFOA           μg   934.565\n",
       "6   PFOS           μg   3678.93\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 = ps.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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rEEIIIYSwGJK8CiGEEEIIiyHJqxBCCCGEsBiSvAohhBBCCIshyasQQgghhLAYkrwKIYQQQgiLIcmrEEIIIYSwGJK8CiGEEEIIiyHJqxBCCCGEsBiSvAohhBBCCIshyasQQgghhLAYkrwKIYQQQgiLIcmrEEIIIYSwGJK8CiGEECVMy5YtWb9+fbpls2fPZujQoZmWj46OxtPTM9t9RkdHs2zZMuPriIgIRo4cCcCiRYsYPnw4APPnz2fJkiW5jnnTpk3s2LHD+Dqv+xGWz8bcAQghhBCicAUFBRESEkL79u2Ny0JCQpg+fXqe95mWvD7//PMA+Pn54efnl6Hc4MGD87T/TZs24eTkRJMmTR5oP8LyScurEEIIUcL06NGD1atXc/fuXUBPPGNiYmjatCljxozB09MTLy8vQkNDM2wbHR1Ns2bN8PX1xdfX19ga+vbbb7N161a8vb2ZNWsWmzZtonPnzhm2nzRpEjNmzCAmJgZvb2/jj7W1NadPn2bVqlU8/vjj+Pj40KZNGy5evEh0dDTz589n1qxZeHt7s3XrVuN+APbv30/jxo1p0KABXbt25fr164Dewjx27FgCAgKoU6cOW7duLai3VBQiSV5FkSBdWEIIUXgqVKhAQEAA69atA/RW1169erF8+XL279/PgQMHCA8PZ8yYMVy4cCHdtpUrV2bDhg3s27eP0NBQY7368ccf06xZM/bv388bb7xx3xiqVavG/v372b9/Py+//DLdu3fn4YcfpmnTpuzcuZPIyEh69+7NtGnTcHd3Z/Dgwbzxxhvs37+fZs2apdtX3759mTp1KgcPHsTLy4vJkycb1yUnJ7N7925mz56dbrmwXDJsQBQJ0oUlhBCFK63effbZZwkJCeGbb75h6dKlBAUFYW1tTZUqVWjRogV79uyhQYMGxu2SkpIYPnw4+/fvx9rammPHjj1QHNu3b2fBggXGVtFz587Rq1cvLly4QGJiIjVr1sx2+5s3b3Ljxg1atGgBwEsvvcRzzz1nXN+tWzcAGjVqRHR09APFKooGaXkVRYJ0YQkhROHq0qULv//+O/v27ePOnTv4+vqiadp9t5s1axZVqlThwIEDREREkJiYmOcYLly4wMCBAwkNDcXJyQmAESNGMHz4cA4dOsSXX35JQkJCnvcPUKpUKQCsra1JTk5+oH2JokGSV1EkSBeWEEIULicnJ1q2bMmAAQMICgoCoHnz5oSGhpKSksLly5fZsmULAQEB6ba7efMmrq6uWFlZsXTpUlJSUgBwdnbm9u3bOT5+UlISPXv2ZOrUqdSpUyfd/qtXrw7A4sWLjcuz2r+LiwvlypUzNgYsXbrU2AoriidJXkWRkdaFBXryGhQUxLZt2zLtwjKVlJTEyy+/jJeXF8899xyHDx9+oDjSurC++eYbQO/Cat++PV5eXkyfPp2//vor2+0z68LasmWLcb10YQkhioqgoCAOHDhA7969AejatSsNGjSgYcOGtG7dmmnTplG1atV02wwdOpTFixfTuHFjjh07hqOjIwANGjTAxsaGhg0bMmvWrPsee8eOHezZs4eJEycae7xiYmKYNGkSzz33HM2aNaNixYrG8s888wxhYWHG3i5TixcvZsyYMTRo0ID9+/czYcKEB31rRBEmY15FkdGlSxdGjRqVrgsrJzdAmXZhpaamUrp06TzHkNaF9csvv6Trwho1ahSBgYFs2rSJSZMm5Xn/IF1YQoiio2vXrumGCiilmD59eob7Ddzd3YmKigLg0Ucf5eDBg8Z1H330EQC2trb8/vvv6bZr2bIlAP369aNfv34A6erQzIYEPPvsszz77LMZltepUyfdcU17vLy9vdm5c2eGbTZt2mT8f8WKFaXBoJiQlldRZEgXlhBCCCHuR5JXUaRIF5YQQgghsqNycmdhGj8/Py0iIqIAwxFCiIKhlNqraVrGudKKMamzRVG0bt06XnvtNVJSUhg0aBBvv/22uUMSRVB2dba0vBZTYWFhKKU4evQooE8nZW9vj4+PDx4eHgQEBKTrAjedtN9Ux44duXHjRp5iMH0owL3c3d25cuVKnvYrhBDCMqWkpDBs2DDWrl3L4cOHCQ4OfuCbbEXJIzdsFVPBwcE0bdqUkJAQ4+D4Rx55hMjISABOnjxJt27dSE1NpX///lnuZ82aNXmOIauHAgghhCiZdu/eTe3atalVqxYAvXv3ZuXKlTz22GNmjkxYEml5LYZiY2PZvn07CxcuNE49da9atWoxc+ZM5s6dm+2+TFtIp0yZQt26dWnTpg1BQUHGCflbtmxJWtfklStXcHd3B0j3UICrV6/Srl07fHx8ePXVV413t8bFxdGpUycaNmyIp6dnpg8hEEIIUTycP3+ehx56yPjazc2N8+fPmzEiYYkkeS2GVqxYQYcOHahTpw7ly5dn3759mZbz9fU1Diu4n7179xISEkJkZCTLly/PMNfq/UyePJmmTZsSGRlJYGAgZ86cAfSxT9WqVePAgQNERUXRoUOHXO03P6xbt466detSu3ZtPv7440I/vhBClBSZ3WejlDJDJMKSSfJaDAUHBxvv1u/duzfBwcGZlsvNzXpbt26la9euODg4UKZMGQIDA3MV05YtW+jTpw8AnTp1oly5cgB4eXkRHh7O2LFj2bp1Ky4uLrna74OS8VdCCFF43NzcOHv2rPH1uXPnqFatmhkjEpZIxrwWM1evXmXjxo1ERUWhlCIlJQWlFEOHDs1QNjIyEg8PjxzvO6urYxsbG1JTU4HMJ5zObvs6deqwd+9e1qxZw7hx42jXrl2hTisl46+EEKLw+Pv7c/z4cU6dOkX16tUJCQlh2bJl5g5LWBhpeS1mfvrpJ/r27cvp06eJjo7m7Nmz1KxZk3PnzqUrFx0dzejRoxkxYkSO9tu8eXPCwsK4c+cOt2/fZtWqVcZ17u7u7N2713j8rLb//vvvAVi7di3Xr18HICYmBgcHB/r06cPo0aOzHOJQUGT8lRBCFB4bGxvmzZtH+/bt8fDwoGfPntSvX9/cYQkLIy2vxUxwcHCGOfO6d+/Ohx9+yIkTJ/Dx8SEhIQFnZ2dGjBiRbqaBRYsWsWLFCuNr00ft+fr60qtXL7y9vXn44YfTPZZv9OjR9OzZk6VLl9K6detM45o4cSJBQUH4+vrSokULatSoAcChQ4cYM2YMVlZW2Nra8sUXX+TL+5BTMv5KCCEKV8eOHenYsaO5wxAWTB5SIPJk0qRJODk5MXr0aHOH8kD+/PNPJk2axPr164H/ntE9btw4c4YlCoA8pEAIISyHPKRAiCyYjr9KTEwkJCQk1zejCSGEEKLwyLABkSdpDz6wdKbjr1JSUhgwYICMvxJCCCGKMEleRYkn46+EEEIIyyHDBkQ695uw//vvv6dBgwY0aNCAJk2acODAAQDOnj1Lq1at8PDwoH79+syZM6ewQxdCCCFECSDJqzDKyYT9NWvWZPPmzRw8eJDx48fzyiuvAHr3+yeffMKRI0fYuXMnn332mUz2L4QQQFhYGEop4xMNo6Ojsbe3x8fHBw8PDwICAli8eLGx/KJFixg+fHiG/XTs2JEbN27kKYaIiAhGjhyZ6TrTx4AXhq8XLODtd8aTnJxcaMcUxYsMGxBGOZmwv0mTJsb/N27c2Dh/rKurK66urgA4Ozvj4eHB+fPnZbJ/IUSJFxwcTNOmTQkJCTHeL/DII48QGRkJwMmTJ+nWrRupqanppi+815o1a/Icg5+fH35+5p1sIyUlhWEjXufbJUuwsnNgx587WRX2U6E/WVFYPml5FUa5nbB/4cKFPP300xmWR0dHExkZyeOPP14gcQohhKWIjY1l+/btLFy4kJCQkEzL1KpVi5kzZzJ37txs92XaQjplyhTq1q1LmzZtCAoKYsaMGQC0bNmStOnRrly5gru7OwCbNm2ic+fOgP4kxnbt2uHj48Orr75qnO86Li6OTp060bBhQzw9PQkNDX3g8zelaRrb//yTxLhbJFz/l9OnT3Pt2rV8PYYoGSR5FUa5mbD/jz/+YOHChUydOjXd8tjYWLp3787s2bMpU6ZMgcSZ35KTk7N9rK0QQuTVihUr6NChA3Xq1KF8+fJZPkXQ19fXOKzgfvbu3UtISAiRkZEsX76cPXv25CqmyZMn07RpUyIjIwkMDOTMmTOAfs9DtWrVOHDgAFFRUXTo0CFX+70fGxsbDkVG0KhRIwBOnzhGzZo18/UYomSQ5FUYubm5cfbsWePrc+fOUa1atQzlDh48yKBBg1i5ciUVKlQwLk9KSqJ79+688MILdOvWrVBiflAXLlzAx78x1Wq4I5O5CyHyW3BwML179wb0oVjBwcGZlsvNA4O2bt1K165dcXBwoEyZMrmem3rLli306dMHgE6dOlGuXDkAvLy8CA8PZ+zYsWzdulW680WRJWNehZHphP3Vq1cnJCSEZcuWpStz5swZunXrxtKlS6lTp45xuaZpDBw4EA8PD0aNGlXYoedJbGwsDX39uPxvDABNmjZj547t+Pr6mjkyIURxcPXqVTZu3EhUVBRKKVJSUlBKMXTo0AxlIyMj8fDwyPG+s+oVs7GxITU1FSDbHqXMtq9Tpw579+5lzZo1jBs3jnbt2jFhwoQcxyREYZGWV2FkOmG/h4cHPXv2pH79+syfP5/58+cD8N5773H16lWGDh2Kt7e38QaA7du3s3TpUjZu3Ii3tzfe3t4PdHNBYXB0dGT8/942vv7gvcnG8WFCCPGgfvrpJ/r27cvp06eJjo7m7Nmz1KxZ03ija5ro6GhGjx7NiBEjcrTf5s2bExYWxp07d7h9+zarVq0yrnN3d2fv3r3G42e1/ffffw/A2rVruX79OgAxMTE4ODjQp08fRo8eneUQByHMTVpeRTqZTdg/ePBg4/8XLFjAggULMmzXtGnTXHV7FQVKKUaMGMH333/Prl27eOutt8wdkhCiGAkODubtt99Ot6x79+58+OGHnDhxAh8fHxISEnB2dmbEiBHpZhpYtGgRK1asML7euXOn8f++vr706tULb29vHn74YZo1a2ZcN3r0aHr27MnSpUtp3bp1pnFNnDiRoKAgfH19adGiBTVq1ADg0KFDjBkzBisrK2xtbfniiy/y5X0QIr+p3CQcfn5+mowLFMVN48aN2bVrl8Ul3yJ3lFJ7NU0z71xBhUzq7JJh0qRJODk5MXr0aHOHkiN+fn7s3btX6lyRrezqbBk2IIQQQgghLIYMGxBCCCEsWNqDD4QoKaTlVQghhCiC1q1bR926dalduzYff/xxhvWapjFy5Ehq165NgwYNMtxglZKSgo+Pj/HhBEIUF5K8ilzRNK1Qn4EthBAlUUpKCsOGDWPt2rUcPnyY4OBgDh8+nK7M2rVrOX78OMePH+err75iyJAh6dbPmTMnV9NvCWEpJHkVOZaUlET/gS9TuUoV3v9gigy2F0KIArJ7925q165NrVq1sLOzo3fv3qxcuTJdmZUrV9K3b1+UUjRu3JgbN25w4cIFQH/IzK+//sqgQYPMEb4QBUqSV5Ej165do3mrNvzyZxSuAz7nk6+W0uv5Pty9e9fcoQkhRLFz/vx5HnroIeNrNzc3zp8/n+Myr7/+OtOmTcPKSr7mRfEjv9Xivo4dO0ZDX3+Op1TE+Zn/YVvBjTLPTeH3qHM0btqCS5cumTtEIYQoVjLr2br3qVhZlVm9ejWVK1emUaNGBRafEOYkyavIVnh4OP6Nm5DwWCecWgxAWVkDYGVbGqeOozlbuhYNfP2Iiooyc6RCCFF8uLm5cfbsWePrc+fOUa1atRyV2b59O7/88gvu7u707t2bjRs30qdPn0KLXYiCJsmryNLnX3xBlx69sG//Jo4N2mdYr5QVTk++QIpvT55o1oJff/3VDFEKIUTx4+/vz/Hjxzl16hSJiYmEhIQQGBiYrkxgYCBLlixB0zR27tyJi4sLrq6ufPTRR5w7d47o6GhCQkJo3bo13333nZnORIj8J/O8igySk5MZ8dooli3/BZeeH2Fbvnq25R0fa4WNS1V6vdifif8by+g3R2Xo3hJCCJFzNjY2zJs3j/bt25OSksKAAQOoX78+8+fPB/THdnfs2JE1a9ZQu3ZtHBwc+Pbbb80ctRCFQx4PK9K5eZGHNhUAACAASURBVPMmz3bvycEzV3HsOAbr0k453jb55iViV00hsG0LFn41H1tb2wKMNP/I42FLBnk8rBBFgzweVuSEPB5W5FjTFq3ZumUzdo+1yVXiCmDjUhnbui1Yuvhbej4v46uEEEIIkf9k2IBIZ/KEd9i2bRtLf1kD9Zrlevv4iDA+nDKFgICAAohOCCGEECWdJK8inW7dulG1alWW/hKe530MGjSISpUq5WNUQgghhBA6GTYghBBCCCEshiSvQgghhBDCYkjyKoQQQligiIgIWjzVjl27dpk7FCEKlSSvQgghhIUJDf2Blm3acSChAk+1e5ply4LNHZIQhUaSVyGEEMKCTJz8Hi+82BfHDm9StlkfnDqP5aX+A/jfu+PNHZoQhUKSVyGEEMKC7D/0F1WrVSf10GoAUg7+SuUqVTkQddjMkQlROCR5FUIIISzIyp9CWfrtAlRyIgBWKXf55uv5/LriZzNHJkThkORVCCGEEEJYDElehRBCCCGExZDkVQghhBBCWAxJXoUQQgghhMWQ5FUIIYQQQlgMSV6FEEIIIYTFkORVCCGEEEJYDEleRQZ3794FK+s8bZuamoKVlfxaCSGEEKJgSJYhMvjnn3/Avmyetk1OvIu9vX0+RySEEEIIoZPkVWQw+7P5qEeb5Xq71LtxWFlZUbp06QKISgghhBBCkldxj82bN3PmXAz2tfxyvW3ixRPUfcxThg0IIYQQosBIliGMDhw4QJfuz2Hf6lVUHsa8Jv77D088HlAAkQkhhBBC6CR5FZw4cYLX3niTJ1u0wubJATg84p+n/dhcj6bJ43nbVgghhBAiJ2zMHUBRk5SURIs27bl+40a+7O/owch82U9O1KzzWK7Ka5pGfFwst2Njcaj/FC69p2Nbtmqejq0lJxEffYCmTZvmaXshhBBCiJyQ5DUTqSkpnIuzxqlJ0APvq1LtTtw5lV0Cqxn+0f57rWW1Tk84M2PjVJ6Eek/mOj4bW3sqOVdE2djmeltT8cd24OXlxSOPPPJA+xFCCHF/CQkJYKV/hWvJSdjZ2Zk5IiEKjySv97C1tWXNL2E09PUn4cppHBu0e+B9OjzaOB8iK9q0w+t5a/okc4chhBAlwuEjR0h1LA9A8p1blCtXzswRCVF4ZMxrJsqXL0/4+jUk7vyehDMHzR1OkZd48STEXuaZZ54xdyhCCFHsaZrG7HlfYFO3JUnXzpMSdxMPDw9zh5VjKSkp5g5BWDhJXrNQt25dfgoN5vaaGSRdjzF3OEWWlprCnU1fMuGd/2FjIw35QghR0EJCQrh9N5VSbvW5e2g9Lw8cQKlSpcwdVo6dPn3a3CEICyfJazbatm3LtA/fJ/aXD0hNiDV3OEVS3L5VPOpajuHDhpo7FCGEKPZWrVrFoMHDsG87Ei0pgfi/NjJ82BBzh5Ur169fp0+fPuYOQ1gwaSq7j2FDh3Io6gg/rJmBc5fxeZr/tLhKunqOhIifCdkXIQ8mEEIUOk3TSExMzJd9paamciMPs8wopXK13MHBIVe9VJqmER8fz44dO5gx+1P2Ru6nTOA72FWuSeyvU+nWrSvu7u65jttcFi9eDMDXX39t5kiEJZPkNQfmzZ3F0fYdidq0AKfWr5o7nCIh5c5tYtdM46MP3qdWrVrmDkcIUQKtXr2awMBArB9wthSAlOSkfIgoZ2zsctfFb1uqNA6VaoBHGyoMGIJSiti1n1CvYim++Wp+AUWZ/86ePUu/fv2oU6dOsXiMuKZpXLp0iSpVqpg7lBJHktccsLGxYeXyH/H2e5zYfatx9O1s7pDMKjUhltsr3+Olnl2KxXCBpKTC+9ISQuSfli1bUrtefW64NcGx0bPmDqfApd6NI+7gbyRHraXVk48T8t0Si5giS9M0pkyZwvjx4wE4evSomSPKH8HBwQx8+RV2/bmDBg0amDucEkWS1xxycXHh9/Vr8PVvzJ2yrtjXamTukMwiJe46t1e8R+9n2jFn5owsu8YsyZEjR8wdghAiD5ydnQlf9ys+/o9zp2w17PP4dMCiLDn2Guc/65tuWYsWLfDyqMuHH35opqhyZvPmzWzZsiXdsnfffZeJEyeaKaL8dfDgQVJt7Wn7dCcO7ouQFthCJMlrLtSqVYtVK37m6We6YN3jA+wq1jB3SIUq/vhO4v/4kteHD+X9yROLReKqaRp37txh7Nix5g5FCJEHDz/8ML+uDKPt052xLvMedpXczR1SvlJW1ijb0ljZO2NfqxHWjuXZnwz7/zhp7tDu627Mfzc6uzQJAqX41ALizjlHKnQdT+KJXbTvFMjObZuLxXAIS6CyemJTZvz8/LSIiIgCDMcyfPvtIl4b+y4uvadh7eBi7nAKXMqdW8RvWoD9jVMEf7eYZs2amTukfDNlyhTeffddkpOTsbaWm/GKM6XUXk3T/MwdR2EqSXX20qXfMXTUWMr2noa1Y1lzhyNKEE1LJXbtJ7SsV5WfQoOLRcNOUZBdnS23iOdB//79GNQ3iLhfp6GlFN/xksk3L3F76xKuLx5Or2aeHDsSVawS1/379/Puu+/SqVOnIpG4JiQkcPbsWXOHIYRFevHFPgwd1I/YXz9GS86fGQiEyAmlrHBsO4Lfdx1g8vsfmDucEkGS1zyaMW0qAfVqEPf7fHLTel2UaZpG8s1LxB3dRuyqD7mxbBS9fKuyd9cOPp83BwcHB3OHmC8SExMZNGgQPj4+lClThtWrV5s7JADe/+ADvLx9ZQJvIfLooynv82SDR4kN/7zY1MvCMljZlsbpmf/xydzP+OGHH80dTrEnwwYeQGxsLI0eb8K1qv44+nczdzi5lnA2iovL3s50naurK71798bR0bGQoyo4n332GdevX0+37N133zVTNBn98ccmdh8+wcOVy7Fvz06cnZ3NHVKxIsMGSob4+Hj8Gj/JpQoNcXr8OXOHI0qYxIsnuBU2iU3hv+HnV6Kqm3yXXZ0tN2w9ACcnJ8LX/Yp3I3/iy1bH4dHHzR1Srigra5RNKZSNLTZlXbGr+gjWThUAiAe+2XPJvAHmszhNn1vR2rkiTg3bA/DpplPmDCk99TCVew/g2q4f6NqjF+vXrCoSwxmEsCQODg5sWLuahmn1ct0m5g5JlCB2VR7BofUQOnR6hgP7IqhevToAYWFhdOvWjSNHjlCvXj2io6Px8PCgXr16JCQk4OzszLBhw3jppZcAuHjxIgMHDuTs2bMkJSXh7u7OmjVrsjxudHQ0nTt3JioqioiICJYsWcLcuXMzlHN3dyciIoKKFSsWzBtQSCR5fUAPPfQQa1f/Quu2HbApUwm7KpYzYX+p6h7UePNnc4dRaMo+GWTuEHLEqfWr7A2bzBuj32LurE/MHY4QFqd69eqs/3UVLZ5qi7VLZUpVrW3ukEQJ4lCnCbHXz9OmQycidm7H0dGR4OBgmjZtSkhICJMmTQLgkUceITIyEoCTJ0/SrVs3UlNT6d+/PxMmTKBt27a89tprgD4tV075+fkV+1ZfGfOaDwICAvh6/ufcXvUhKbHX77+BENlQ1rY4dRrLomU/8JU8QlGIPGnUqBGLFnzN7VUfkXz7qrnDESWMY0APLtlUpufzfbh16xbbt29n4cKFhISEZFq+Vq1azJw509haeuHCBdzc3Izr0x6CoGkaY8aMwdPTEy8vL0JDQzPsa9OmTXTurD9M6erVq7Rr1w4fHx9effVV41jwuLg4OnXqRMOGDfH09Mx0P0WZJK/5JCioN68NfYXY1R+RmnTX3OEIC2dt74xz4LuMGvM2mzdvNi4PCwtDKWV8Qk10dDT29vb4+Pjg4eFBQECA8dnhoHc9de7cmYYNG/LYY4/RsWPHbI8bHR2Np6cnABEREYwcOTLTcu7u7ly5cuVBT1OIAtWjR3feen04sas+JDUpwdzhiBJEKYXTU0PZcegEQS/0oUOHDtSpU4fy5cuzb9++TLfx9fU11u3Dhg1j4MCBtGrViilTphATEwPA8uXL2b9/PwcOHCA8PJwxY8Zw4cKFLOOYPHkyTZs2JTIyksDAQM6cOQPAunXrqFatGgcOHCAqKooOHTrk8ztQsCR5zUfvT55EC7/6xIXPkztdxQOzreCGY4dRPNutB//88w9Auq6nNGldT0eOHCEkJIRZs2bx7bffAhi7ng4cOMDhw4f5+OOPc3x8Pz+/TMdMCWFJxr/7Dm2b+BL321w0LdXc4YgSRNnY4tT5bdb/9hsVKuhjTHv37k1wcHCm5U3zhvbt23Py5Elefvlljh49io+PD5cvX2bbtm0EBQVhbW1NlSpVaNGiBXv27Mkyhi1bttCnTx8AOnXqRLly5QDw8vIiPDycsWPHsnXrVlxcLGvOekle85FSiuCli6lmdYu4nZbVBC+KJnt3b2z9e9GmfUfOnTsnXU9C5JJSiqWLvqFG6bvE7cg8aRCiwChFSkoqM2bMwNXVlenTpxMaGpppA1dkZCQeHh7G1+XLl+f5559n6dKl+Pv7s2XLljw1jGX20IQ6deqwd+9evLy8GDduHO+9916u92tOkrzmM3t7e35bswqr438Qd2SrucMRxYCj99PEVvTgqbbtadeunXQ9CZFLpUuXZv2vv2BzahtxhzeZOxxRgsT/vR0nz6eo1H08CUkpbN26lZo1a3Lu3Ll05aKjoxk9ejQjRowAYOPGjcTHxwNw+/ZtTpw4QY0aNWjevDmhoaGkpKRw+fJltmzZQkBAQJbHb968Od9//z0Aa9euNU4XGRMTg4ODA3369GH06NFZfp8UVZK8FgBXV1d+W7OaO5u/4m7M3+YORxQDji0GcvLsef69dBmQrichcqty5cpsWPsrCVu/4e75I+YOR5QQcYc341DnCewf8cfGpwtPte9Ip06d+PDDDzlx4oTxfoWePXsyYsQI+vfvD8DevXvx8/OjQYMGPPHEEwwaNAh/f3+6du1KgwYNaNiwIa1bt2batGlUrVo1y+NPnDiRLVu24Ovry2+//UaNGjUAOHToEAEBAXh7exsfk25JLG6qLCcnJ2JjYwv9uBMmTKB58+a0adMmR+W9vb35btE39BnwCta9p2NT5r851c59MQArO3tQCmvHclTsNAprp3L/LbfSrynKtx1KaTcPEi+f5lr4l6TcvgJoONZvjUuT3um6Ai79/D4p8TdwfVGmViqOUu/GkZIQz/r16yhfoQKODg4opRg6dGiGsll1PT3//PN07ty5QLqe1qxZw7hx42jXrh0TJkzI9b6FKAxeXl4EL11M7779se41DRuXyuYOSRRzVZ//7z4DB99Ablw/z/rwP/ht7eps5/EeM2YMY8aMybBcKcX06dOZPn16uuXu7u5ERUUB0LJlS1q2bAlAhQoV+O2334zlZs2aBegNG+3bt8/zeZmbtLzm0HvvvZfjxDVNly5dGDdmFLGrPyQ1Mf2drlWCPqTagHnYVa3NzZ0/pF/e/1Oq9f+U0m4epCbd5fLy93Fp3IPqr3yFa/9PuXv+KLGRvxq3SU2IJfHiCVIT4ki68e+DnagokuL/3o6j51O4DvqSxFQrFixYIF1PQuRB586dmTBuLLd/mULq3XhzhyNKEKUUTq1eIfLURV5/M2NiKnLOYpPXTZs20bJlS3r06EG9evV44YUXjK1Je/bsoUmTJjRs2JCAgABu375NQkIC/fv3x8vLCx8fH/744w8AFi1aRJcuXXjmmWeoWbMm8+bNY+bMmfj4+NC4cWOuXbsGQL9+/fjpp58A/Qpn4sSJ+Pr64uXlZRxfePnyZdq2bYuvry+vvvoqDz/8MK8MGsjTzR8ndv2sTO90Lf2QJ0nXY7I8z7jDmylV3QP7mr6A/vzk8m0Hc3PnT/+V+XsH9rUDcPRoTvyRLfnw7oqiJq3rybZsVZw6jua53s/z5JNPSteTEHkwZvSbBLZtTuy6mWipKeYOR5QgytoG9ZA327bvMHcoFs3ihg2YioyM5K+//qJatWo8+eSTbN++nYCAAHr16kVoaCj+/v7cunULe3t75syZA+hftkePHqVdu3YcO3YMgKioKCIjI0lISKB27dpMnTqVyMhI3njjDZYsWcLrr7+e4dgVK1Zk3759fP7558yYMYMFCxYwefJkWrduzbhx41i3bh1fffUVSikWLfyaJ1u0Jnrbdzg165tuP3dO7Maukrvx9cXg/4GVFcraFte+M0m6chq7e54OY1vOFS3xDql347Eq5UD8kc24PBmEtWM5Lq/4CJcneubzOy3MzbTrqfRDniQ36cvi74M5uC+CChUqZLmddD0JkZFSioVfzadZqzac2LYEp+b9zR2SKCHunIhAO/QrYXt2mTsUi2axLa+gP9nKzc0NKysrvL29iY6O5u+//8bV1RV/f38AypQpg42NDdu2bePFF18EoF69ejz88MPG5LVVq1Y4OztTqVIlXFxceOaZZwB9fFR0dHSmx+7WrRugP8Ulrcy2bdvo3bs3AB06dDDe1FKqVCnWrV6J3dldxEX9DuhJasy3I0i9G49L4+eM+00bNuDad6bJ0TKONUyTEnedpOsXKOVWH9vy1VFW1iRezjxmUXw4ebUhrtyjvDH6LXOHIoRFsrOzY80vYZSO2Ufcwd/uv4EQDyjx8mniNsxl1YrluLu7Z1lu3bp11K1bl9q1a2c7N/eePXuwtrY29gqD3rBQv359PD09CQoKIiGheD6cw6JbXkuVKmX8v7W1NcnJyWialumNJdndoGK6HysrK+NrKysrkpOTs90m7bj3O0bFihUJX7eGxk82Q0vRqBI0C2uH+9+ZbVuxBnfPRqVblnTjX5SdPValHLh1KJzUhFjOzx+ox5AYT9yRrelac0Xxk3TtPMnRexkw+3/mDkUIi1WhQgXC160h4ImmWJd1pXQNL3OHJIqplPib3F41hc/nzubJJ5/MulxKCsOGDWPDhg24ubnh7+9PYGAgjz32WIZyY8eOTdfzdf78eebOncvhw4ext7enZ8+ehISE0K9fv4I6LbOx6JbXzNSrV4+YmBjjtD+3b98mOTk53Q0nx44d48yZM9StWzdfj920aVN++EG/+eq3334z3tSS5rHHHiN02Xdo8TdJunkpR/t0fKwld88d5k70fgBSk+5yPfxLyjzeHYC4I5up0nMybkO+wW3IN1R9abaMey3mUu7c5vYvH/DJtI+M3fqZud/V+8qVK2nQoAHe3t74+fmxbds247o5c+bg6elJ/fr1mT17dkGchijmnJyczHLcCRMmEB4enuPy9erV4+cfgoldOyPD/QfnvhhAzMJhxHwznIuh40mJvZ5++bcjiPl2BAnn9Km3Ei+f5t/g/3H+q1c4/9XL3NgebGzUSIm7zqWfJhPzzXBiFgzh4o8T8+mMRVGnJScRu/pjBvfvS9++L2Zbdvfu3dSuXZtatWphZ2dH7969WblyZYZyn376Kd27d6dy5fQzZiQnJ3Pnzh2Sk5OJj4+nWrVq+XouRYVFt7xmxs7OjtDQUEaMGMGdO3ewt7cnPDycoUOHMnjwYLy8vLCxsWHRokXpWlzzw8SJEwkKCiI0NJQWLVrg6uqKs7NzujJPP/00ZcuWJW79LOyCZmBVyiHbfVrZlqJS9/Fc2zCfaxu+gNRUHOu3wtm3M8k3L5Jy6zJ21eoZy9uWrYpVKQfuxvxNqWr5m5wL89NSkolbM42+vbrz6iuvZFkuJ1fvTz31FIGBgSilOHjwID179uTo0aNERUXx9ddfs3v3buzs7OjQoQOdOnXi0UcfLYxTFOKB5OVJQW3btuXjDybzzgdTcOk1FavS/yXeVYI+xNrBheubF3Nz5w+Ub/NquuVp0maGKd9uKPY1fUlNSuBy2EfERv6Ks29nbmz9ntLu3pTxexaAxEunHvBMhSXQNI24jZ/zRP1aTP1oyn3Lnz9/noceesj42s3NjV27dmUoExYWxsaNG9PNz129enVGjx5NjRo1sLe3p127drRr1y7/TqYIsbjkNW2OV9ObSQDmzZtn/L+/vz87d+7MsO2iRYsyLOvXr1+6JnXTMa6m60y3NS3j5+fHpk2bAHBxcWH9+vXY2Njw559/8scff2SaIF+9eoVBrwwmbO0MnAPfQVnpc725Dfkm03O2q+Se7oadNDYuVXAbtiTDctd+czLdj7BsmqYR98dX+NaqypyZM7Ita3r1Dhiv3k2TV9OWsbi4OONwmyNHjtC4cWMcHPQLqxYtWhAWFsZbb8n4WpF7mzZtYtKkSVSsWJGoqCgaNWrEd999h1KKPXv28NprrxEXF0epUqX4/fffsbW1ZciQIURERGBjY8PMmTNp1aoVixYtYsWKFaSkpBAVFcWbb75JYmIiS5cupVSpUqxZs4by5cvTr18/OnfuTI8ePXB3d+ell15i1apVJCUl8eOPP1KvXj0uX77M888/z9WrV/H392fdunXs3buXQ38d5sc1M3DuMt5YL6cp/ZAnt/b+kuV5ZjUzzMXgcTj7diYl7hqla/oYy9tVrlkwb7goUuL2LKdS0iV+DNmOldX9O7szG35471DI119/nalTp2aYJ/b69eusXLmSU6dOUbZsWZ577jm+++474wNmipNiN2zAnM6cOYO/vz8NGzZk5MiRfP3115mWU0ox//N5eFR2IG7LosINUlis+H2rKHv7FGE/hWY7uTVkfvV+/vz5DOXCwsKoV68enTp14ptv9IsnT09PtmzZwtWrV4mPj2fNmjWcPXs2f09GlCiRkZHMnj2bw4cPc/LkSbZv305iYiK9evVizpw5xscU29vb89lnnwH6zDDBwcG89NJLxptOoqKiWLZsGbt37+add97BwcGByMhInnjiCZYsyXghD//NDDNkyBBmzNAv+tJmhtm3bx9du3Y1Pu74s7lz8HQrS+wfGevuzGaGifl2BBeWjAK478wwzj6duLp2Lv8Gj+PmjlCSb199sDdVFHnxx/6Ev9YSvu5XHB0dc7SNm5tbuvr23LlzGbr+IyIi6N27N+7u7vz0008MHTqUFStWEB4eTs2aNalUqRK2trZ069aNHTuK55RcFtfyWpQ9+uijREZG5qisra0tfYJ6Me6D6fcvLEq8OyciSNm/gvA9uzIMRclMTq7eAbp27UrXrl3ZsmUL48ePJzw8HA8PD8aOHUvbtm1xcnKiYcOG2NhIVSHyLm1mGMA4M4yLi0uGmWFAn7Ul7SEbWc0M4+zsnGFmmIMHD2Z6bNOZYZYvX248RlhYGJB+ZhgbGxtWhf2Ed6MAbhseBJM2faFdJXfKN/tvvOK9wwZ0Wc8MY1+rEdVfXUDCqb3cObmXC4teo9rAz3J0466wPIkXTxC/8XM2hf9G9erVc7ydv78/x48f59SpU1SvXp2QkBCWLVuWrsypU/8NOUnraejSpQu7du1i586dxMfHY29vz++//46fn1++nVNRIi2vZrJjxw7GjHsHhw5vmjsUUcQlXo4mbsNcVq8My3Z6FVM5uXo31bx5c06cOMGVK1cAGDhwIPv27WPLli2UL19exruKB2JJM8O4uLgQvn4NyRE/oiUnGqcvrNj5zXRjYe9lW7EGif8eT7fMdGYYAGt7Zxwfa0nFzm9SyvVREu6ZSUYUD8mx17i96kMWfjk/18mjjY0N8+bNo3379sYHz9SvX5/58+czf/78bLd9/PHH6dGjh/EBSqmpqbySzb0RlkyS1zwaMGAAlStXxtPTM9fbRkdH0/nZrji2HYldpYcLIDpRXKTE3eD2Lx/yxadzaNKkSY63M716T0xMJCQkhMDAwHRl/vnnH+OX+L59+0hMTDQ+8ODSJX02jDNnzrB8+XKCgoLy6YyE0BXlmWEeeeQRVq1YjnbnFknXsn4Coqn7zQxz5/QBUpP04Q+pd+NJun4BmzKV8uuURBGRmnSXuNUf8cbwIfTqlbcHBnXs2JFjx45x4sQJ3nnnHQAGDx7M4MGDM5RdtGgRPXr0ML6ePHmy8cbbtPHgxZH0BeZRv379GD58OH379r1/YRO3bt3iqfYdsfbugv0jxbM5X+QPLTmJ2F+nMmTgS7z4Yu4G3JtevaekpDBgwADj1TvoFeHPP//MkiVLsLW1xd7entDQUGNLWPfu3bl69Sq2trZ89tlnxm5VIfJLUZ8ZplmzZpQvX47YdZ9g+/wn9+3ez25mGIDEf//h+ob5YGUNWirODdtRyrVOvp6XMC9N04jb8CmtAxoweeIEc4dTrKnsuk/u5efnp0VERBRgOJYlOjqazp07Gx+neT8pKSm0e7ozB65b4dh6SKZdZkKAXgnG/jaXxjUcWRX2c47uUhXZU0rt1TStRF0xSp2dubt372JtbW2cGWbIkCHs378/07KvjXqTJSt/p0y3SShr20KOVFiS2B3LqB53nF3bt1C6dGlzh2PxsquzpeW1EL02ajSRpy7i3GWiJK4iW3F7fqZy8iV+WJaz6VWEEDl35swZevbsSWpqKnZ2dlnODAMwc/o0jhx5ln1/fIVTm2GFGKWwJHGHN2N9Ygu/7YuQxLUQSPJaSL786iuWhP6MS69pKGt52x9E4uVoUu/cRtnYoWxLoWzsMpRJunae5Bv/FsjxS1Wrm+2NGw/CxqUKd/7ZBYfXE753T46nVxFC5FxuZoaxtramcYAfe5dlfMqRyFzS1bNoKcl6HW1jS05vr9GSEki8HJ3/ASlFKdeCeWiPtaMLiRdPkrBlAdu3bKJKlSoFchyRnmRRheCPP/7gzbfG4dLzI6zt7z/NkcjehW+GZ7u+TNny3LpxrUBjqOqW/zfa3b55A9wD4EwEm3/fkKvpVYQQBePHH39i5rz5lO091dyhWIyYBUOyXW9rVwpnl4zj6K9dLpgGB4Dylarm+z7vJsRj+1ADki78zbIli2jQoEG+H0NkTpLXAnb8+HG6dH8Ox6ffxLa8JCP54eGxq43/11JTSLp6jsR//0G7cgKrq6e4df4fqj9ci34vvsCQwa9aTBL4zrvv8uGUKYSG/kCjRo3MHY4QxcaAAQNYvXo1lStXzvE9CqDPuqlbbgAAIABJREFUwtH/5Vdw7jIRG+eKBRhh8ZKujtZSSb5+gcR//yH1sl5H3z5/HCtra3x8fOnR5RleeOF5i+xlWrp0KX379uWjqVMzzOYiCpbcsJVHQUFBbNq0iStXrlClShUmT57MwIED05W5fv06DX39uVPvaRwbdjBTpCWPlppC4qVTJB3+nfgjm2nZqhWjXx9Jq1ativRY4927dxN54BCvvjzw/oVFrskNWyXXli1bcHJyom/fvjlOXmNiYmjg64fVE/1xqJvzaerE/f2X0B5HO7GDhHOHebHPi7w+cli+T4tWkE6ePMmKX1bxxmsji/R3i6XKrs6W5LWAJCUl0fKpdvydWBanloPMHU6JlXo3nri//iD1r/U4l7Zm7KjXGTz41fs+XlUUP5K8lmy5mR0mPj4ev8ZPcqlCQ5wef64QoivZkm9e5M7B9ST8FY6XlxdvvTGSwMBAebJfCZddnS23MRcATdMYPHQ4Ry7F49i8v7nDKdGsSjng7NuJMn3mkNh4IONnfY2Pf2OOHj1q7tCEEEVQamoqPZ/vw0WrCjgG9Lj/BuKB2bhUwblZXyoOWsiJcv68PGYSrm41jI/zFeJekrwWgNlzPuWnNRtweno0ykpa+IoCpRSlH/LEuft7xFTyp9HjT/DR1KmkpKSYOzQhRBEy7p3xbD94HKc2w6QruJApG1scH2uJ83MfYf3Ua/Qb8hpdevQ0PrZaiDSSvOaztWvXMn7y+zg9847xedai6FDKCiefTpQNmsH0BaHSCiuEMPruu+/5fMEinDq9nekUfKLwlH7Ik7J9ZrPtXDJ1POpLK6xIR5LXfHT48GF6Pd8Hp05jsC2b/9NyiPxjW7Yqzt0mc6FyAH6NmxAWFmbukIQQZvTnn38yePhInAP/h7VjWXOHIwAr29I4tRyIXfs3pRVWpCPJaz65fPkybTp0pNSTL1Harb65wxE5oJQVjt4dce4ykRcHvMKiRYvNHZIQogAEBQXxxBNP8Pfff+Pm5sbChQvTrT99+jSdArvg0HYEdpXczROkyFJpt/rpWmHlJkQht/Llg7t379Kh87MkPvQ4Tp5PmTsckUulqtbGqvv7jBg9ljsJdxgyeLC5QxJC5KPg4OAs192+fZun2nfE2jsQh0f8CzEqkRtprbDx1evTqm17Vq9YTosWLcwdljATaXl9QJqm0W/gy0THWePYtI+5wxF5ZFvxIcp0/4D/t3fncVXV+R/HX5dFNsXcwz0ENxZRwXHLNFISFccy0cw0M7fGpdK05tfqVLS6ZI2jZVZmopWR5q4o4w46uKGJqFlILiUqKiJwfn/4kEfkBsq9h3t5Px+PHs09nHO+70N1/My5n+/3jH/xZebNu/EfdCLiOPLy8ujVO5rTXnXxbNHT7DhSBJ7+rfF88Dm69XyIJUuW3PoAcUgqXu/QmzFvsyxhK15dxmKx6Ndpz1wr+eDd6xWGjvwHy5cvNzuOiFjZM+OeZ3taBuXvH6aVBeyIR71mVIj6J30fG8jq1avNjiMmULV1BxYtWsRb702mfPcXcSrnbnYcKQHlqtWnfLfneXTAQH7//Xez44iIlcycNYs58xZQvtsELM6uZseRYnKr2Yjy3Z6n1yPRbNmyxew4YmMqXm9TcnIyA554kgrdJ+LirXdeOxL3OoE4NWjHkGEjzY4iIlawfv16nh0/kQpR/4ezRwWz48htcq8TiOcDo4iI7M7BgwfNjiM2pOL1NmRkZNClazc87huKm09Ds+OIFXi268+aDZu1tqCIgzl48CA9H+qN14PP4lqlttlx5A55NAjDtcVDRPd/nPz8fLPjiI2oeC2mixcv0iWyB/kN78eryb1mxxErcXJ1x/OBUQwZNkLtAyIOIjMzk/CISFzDovGoH2J2HCkhXi17cOhkFpOnTDM7itiIitdiMAyDvo89zrF8b7xaR5sdR6zMvXZTnPzaq31AxAHk5ubS/e8Pc75qU7xCupodR0qQxeKE5wP/4JXXXiM1NdXsOGIDKl6L4aVXXiVhewpeD/xDM1PLCM+2/Vkdv46dO3eaHUVE7sCIp0eRknEOr/sGmx1FrMC1ci3cwx6h72MD1T5QBqh4LaKvv57P1I9nUr77Czi5upkdR2zEydWNcoFdmDxtutlRROQ2TZ02nQWLV1A+chwWJ2ez44iVqH2g7FDxWgTbtm3jqREjr7zzunwls+OIjXkEdWHBggWcOXPG7CgiUkwrVqzgn6+8Rvmof+Lk5mV2HLGiP7cPHD161Ow4YkUqXm/hl19+oWv3KDzD/0G56r5mxxETuJSvjKdvCz7/4guzo4hIMezbt49H+j5K+chxuN51t9lxxAZcK9fCvUknpn34kdlRxIpUvN5EVlYW4RGROAV1w9P/b2bHERO5BETw/tQPMQzD7CgiUgS///47D0RE4tZuIO51As2OIzbkFvwgsz6dzaVLl8yOIlai4vUG8vPzebhPP/5wr4VnaC+z44jJ3OoEcuZiLuvXrzc7iojcQk5ODg9278mlOmF4BYabHUdszLVyLVyr1WfhwoVmRxErUfF6A+Oen8C2n47iFT5cKwsIFosFp3v+xvIVK82OIiI3YRgGTwwZyqGzBl7tB5gdR0ziFPgg70750OwYYiUqXq9j9uzP+OSLr/XOaynEpYYfG7ZsMzuGiNxEzDvv8uPajXhFPIPFoj/iyiqPBmEcOnKU5ORks6OIFbiYHaC0uXDhAiOeHkk572pcWvH+HZ/v5IEdJZCqaKo3aVWs/U/sK1yIVfW1k74wixMW9wrk1w3Fs0kHmy1dVq6GH7vi/41hGHoaL1IKxcXF8cbb73FX33dwKudhdhwxkcXJmXKBnZk8bTqfz/7E7DhSwlS8/oWnpyf/Xb+e8+fPl8j5UlNT+eijG896vFoEFeXvNyuY6taty5AhQ4qV7ZdffmHKlCmkpKQAcOrQHubOnYuvb+leVSE3N5f09HRmfPIZ22Z9jlebfng172b1cZ0rVCHfuPJ7q1u3rtXHE5Gi27VrF48NGkyFHv/Exbua2XGkFPAM7MKCz0Ywe9Z/cHbW+r6ORMXrdbRqVbwnmDfTqVMnhg4dWmLnK2lPPfUUACdOnKBGjRo89thjpKam4ufnZ3KyW+vbty8HDhwgolsUWdnn8GrT16rjWSwWPGv6s337dhWvIqXI8ePH6dy1G+4dhuBWs5HZcaSUcC5fCbcKldi/fz8BAQFmx5ESpIYgAaB69eoFr9Tz9/c3OU3RNWzYkK0bE3BJS+Dioe1WHy+3Un22bku0+jgiUjTZ2dl0iexBnt99eDXpYHYcKWXK3e3H9u3W/7NBbEvFqxSwWCxkZmYC8OOPP5qcpuiqV69OzBuvk7fL+pmdKvpwIO2w1ccRkVszDINHBwzk11wvvFpb95sXsU+XK93DRk20dThqG5BCKlasCED37t3takH+6OhoRo19lsunM3Ct5GO1cSwu5bhwMdtq5xeRolu8eDGLvllAFf/mZC95447OdfH0Cc5lHCqhZDdXPaBNkfe9+MfxglxOruWo6t/cWrFKjsWZPHdvnP3a416vmakTXN3u9mPz1kWmjS/WoeJVrvHSSy8xadIks2MUi7u7Oy3DWrH35BHrFq+u5biQecFq5xeRogsPDy+xb4mysrIYN27cDX9+owKsuIXZmDFjitWadebMGYYPH05WVhb5l3M4kbKVyZMn06hR6e3tzcnJ4dChQ0z793/4Y/0sPDoNw71usClZyt3dgAPf7yUvL0+TthyIile5Rq1atcyOcFu8vb3Jv2Tdp6IWJxdycnKsOoaIFI2XlxeRkZEldr4+ffqU2LlKUv/+/QE4deoU1apV45lnnmHfvn00btzY5GQ3N3bsWH788UceHTAQ44HReDQItXkGJzcv3CtW0aQtB6OeV7mGk5N9/mthk6+mtL6riJikatWqBe1cTZo0MTnNrVksFrp3786KpUs4t2IKeeczTclRrsY97Nmzx5SxxTrss0oREREpo65OrF22bJnJSYqmTZs2/P3vPbmwe5U5AVw9yMrKMmdssQoVryIiInbk6sTakmyZsLbnxozi8t6VpkwENpzLkZ2tibaORMWriIiInRkxYoTZEYqlZcuWZJ/9AyP3ks3Hzndy5eLFizYfV6xHxauIiIidqV69utkRis3NwxPjsu2LV8PizOXLl20+rliPilcRERE7Y+baqbfLHjNL6aTiVURERETshopXEREREbEbKl5FRERExG6oeBURERERu6HiVURERETshopXEREREbEbKl5FRERExG6oeBURERERu6HiVeyeYRjk5eVh5OfbdjwT3tEtIiJS1ql4Fbu3atUqXFxcWPz9d7h4V7PqWM7lK7N962ZcXFyY+9VXVh1LREREruVidgCRO9WhQwce7tOXNVuScbnLx6pjOZevgne9AFr43s3fe/a06lgiIiJyLT15Fbvn7u7OwvnzeGZIfzLnP8+l3w5aZZzLf6RzJvZ5+nfryIqli6lQoYJVxhEREZEb05NXcQgWi4WXX/o/mjZpzKAhQ8nrNALPRm1L7PwXjyRzfvkHfPBuDEOfeqrEzisiIiLFo+JVHErv3r255557iOjWg6zMdLxa9cZisdzROc8nL+NyYixLvv+Wjh07lkxQEZEyYt36BL759juyL5ynognjG8APi5dw8vc/eO+dt3Fy0pfO9k7/BMXhtGzZkl07kqj++06yVkzFyL18W+cx8vPIip+FZ+pKkrZuVuEqInIb0tIO8dH0abgHdsbJw9vm43s1e5Ck3fv55ttFnD171ubjS8lT8SoOqWbNmiRt2Uib+hU4+91L5J3PLNbx+ZfOc+6HN2jscY6d27fh5+dnpaQiIo7tycGD+CEuDuPQJi7sS7Dp2PmXLnAh/j+0ah7Mzh2J3HXXXTYdX6xDxas4LE9PT3747huGRkeROf95ck4eKdJxlzN/40zsRB7q0Jx1q1foZicicod69OjBxvXxOG3/mqxN8zAM66/LfTnzN84smMDf7w1h3ZqVVKpUyepjim2oeBWH5uTkxNtvvcHHH7zN2W9f5mJa4k33z/5lD2diJ/L6xGf5ZOYMXFzUFi4iUhKCg4PZtSOJ2hcOkrXsffIvZ1ttrOxfUzgTO5FXx4/l05kzcHV1tdpYYnsqXqVMGDDgMVYtW8Lldf/m/Pbvr/t2rKzdq7mw9B2+nT+XMaP/YUJKERHHVqNGDbZsWE+nJj6c++YlcrP+KPExzu9dy4UfY1g47wueGTv6jiftSumj4lXKjDZt2vC/pG3c9csmzq/5GCPvykQuw8gnK2EObnu+Z+umDURERJicVETEcV1dm3vMk/04M388OcfTSuS8hpFP1oYvcd35LVs2/peuXbuWyHml9FHxKmVKvXr12JG4hZAqcHbRa+SePUHWkhjuMTLYtSOJJk2amB1RRMThWSwWXn35JT79+EPOLnqVCwc23dH58nOyyVryDvUuH2Xn9kSaNm1aQkmlNFLxKmVOhQoVWLF0MQN63E/Gf57iwZb+bFy/lipVqpgdTUSkTOnT5xHWrV5J/sbZZG375rotXbeSe/YUZ795kc4h9dmUEE+1atWskFRKExWvUiY5OzszbfL7HDqUxtzPP6NcuXJmRxIRKZNCQ0PZuSOJaif/R9bK4q3NfSnjAJmxzzN+xBN8PfcL3NzcrJhUSgsVr1Km1atXT838IiImq1WrFklbNvK32l6c/e5l8i6cueUx5/dv4FzcJL78ZAb/fGGi7uVliIpXERERMZ2XlxdL4r5jyCPdyJw/npyTP193P8MwyNo8H7Z+wYZ1a+nVq5eNk4rZtIiliIiIlApOTk68+/ZbBAU0ZeTosXh1Ho1Hg9CCnxu5OWStmk5NpzOs3JGEj4+PiWnFLHryKiIiIqXK448PYOXSxVxe9zFZ23/AMAzysk5z9pv/o71fZbZt+q8K1zJMT15FRESk1Gnbti07ErcSHhHJ6RNpXD6WwujhQ/jX66+pv7WM05NXsSu//fYbffv2pUGDBjRt2pTIyEgOHDhgdiwyMzP5+OOPzY4hIuJQ6tevz/8StxAV6svMaR/wxqTXVbiKilexH4Zh0KtXLzp27EhaWhopKSm8+eabHD9+3OxoKl5FRKzE29ubOZ/OpF+/vmZHkVJCxavYjfj4eFxdXRk+fHjBtpCQENq3b8/48eMJDAwkKCiI2NhYANatW8d9991Hnz59aNiwIRMnTuSrr76iVatWBAUFkZZ25ZWEgwYNYvjw4dx77700bNiQJUuWAJCdnc0TTzxBUFAQzZs3Jz4+HoC9e/fSqlUrQkJCCA4OJjU1lYkTJ5KWlkZISAjjx4+38W9GRESk7FDPq9iNPXv20LJly2u2f/fddyQnJ7Nz505OnTpFWFgYHTp0AGDnzp3s27ePypUr4+vry5AhQ9i2bRtTp07lww8/ZMqUKQAcOXKE9evXk5aWRqdOnTh48CAfffQRALt372b//v106dKFAwcOMGPGDMaMGUP//v3JyckhLy+PmJgY9uzZQ3Jysu1+ISIiImWQnryK3duwYQP9+vXD2dmZGjVqcN9995GYmAhAWFgYPj4+uLm50aBBA7p06QJAUFAQR44cKThHnz59cHJywt/fH19fX/bv38+GDRsYMGAAAI0bN6ZevXocOHCANm3a8Oabb/L222/z888/4+HhYfNrFhERKatUvIrdCAgIYPv27ddsv9m7sP/8qkAnJ6eCz05OTuTm5hb87K8TACwWyw3P++ijj/LDDz/g4eFBREQEa9euLdZ1iIiIyO1T8Sp24/777+fSpUvMmjWrYFtiYiKVKlUiNjaWvLw8Tp48SUJCAq1atSrWuRcuXEh+fj5paWkcOnSIRo0a0aFDB7766isADhw4wNGjR2nUqBGHDh3C19eX0aNHExUVxa5du6hQoQLnzp0r0esVEbFXWhlGrEnFq9gNi8XCokWLWLVqFQ0aNCAgIIBXX32VRx99lODgYJo1a8b999/PO++8w913312sczdq1Ij77ruPrl27MmPGDNzd3Rk5ciR5eXkEBQURHR3NnDlzcHNzIzY2lsDAQEJCQti/fz+PP/44VapUoV27dgQGBmrCloiUaVoZRqzOMIwi/9WyZUtDHN/MmTONK/9qlA0DBw40Fi5caHYMsTIgySjG/c4R/tI923G9+uqrpfY+vWbNGuPee++9Znt+fr4xbtw4IyAgwAgMDDTmz59vGIZhxMfHGx06dDAeeeQRw9/f35gwYYIxd+5cIywszAgMDDQOHjxoGMaVe/WwYcOM9u3bG/7+/sbixYsNwzCMixcvGoMGDTICAwONkJAQY+3atYZhGMaePXuMsLAwo1mzZkZQUJBx4MABIzo62nB3dzeaNWtmjBs3zka/EbkdN7tna7UBERERKTFaGUasTW0DUsiwp0cz8cV/AhD+YDd+WPKjyYmsb86cOfTu3dvsGCIiDk0rw0hJUfEqhZzPOkfmmTO4VvdlY8J6PNzKmR1JRETsiFaGEWtT8SqFfDlnNpNefx3fauVJ3LqZzp07mx3pti1fvpxGjRrh5+dHTEzMNT+Pi4sjODiYkJAQQkND2bBhQ8HPpk6dSmBgIAEBAQVfV4mIyK1pZRixNhWvDuZOlyexWCy8OHECw4c8QYMGDW4rQ3JyMkuXLr2tY0tKXl4eTz/9NMuWLSMlJYWvv/6alJSUQvuEh4ezc+dOkpOTmT17NkOGDAGu9GvNmjWLbdu2sXPnTpYsWUJqaqoZlyEico3s7GwuXrwIQFZWFvn5+SYnKkwrw4i1WW72GP+vQkNDjaSkJCvGkTthGAZt27Zl4MCBDB8+HLhSSJ47d4577723WOeqX78+SUlJVK1atdg55syZQ1JSEtOnTy/2sSVl8+bNvPrqq6xYsQKAt956C4AXXnjhhvsPHjyYffv2sXDhQlasWMEnn3wCwKRJk3Bzc+P555+3TXixCovFst0wjFCzc9iS7tmOqUHDxhxK/ang89dfz6dv32gTE9nGoEGD6N69u+YolBE3u2fryasDiY+Px9XVtaBwBQgJCaF9+/aMHz+ewMBAgoKCiI2NBWDdunV07NiR3r1707hxY/r3749hGEybNo1jx47RqVMnOnXqBMCIESMIDQ0lICCAV155peD8iYmJtG3blmbNmtGqVSvOnDnDyy+/TGxsLCEhIQVj2Vp6ejp16tQp+Fy7dm3S09Ov2W/RokU0btyYbt26MXv2bAACAwNJSEjg999/58KFCyxdupRffvnFZtlFRG5m1oyP8a5UhfJ316dX7z707BlldiQRm9JSWQ7kdpYn+d///sfevXupWbMm7dq1Y+PGjYwePZoPPviA+Pj4gievb7zxBpUrVyYvL4/w8HB27dpF48aNiY6OJjY2lrCwMM6ePYunpyevv/666U9er/eNwl8b/QF69epFr169SEhI4KWXXmL16tU0adKECRMm0LlzZ8qXL0+zZs1wcdF/KiJSMn777TfGjh1LYmIibm5u1K9fnylTptCwYcMiHX///feTtPXKt0szZ868rVn0ycnJHDt2jMjIyGIfa5Y5c+aYHUFKCT15LQNutjxJq1atqF27Nk5OToSEhBRakuTPFixYQIsWLWjevDl79+4lJSWFn376CR8fH8LCwgDw9vYuNUVe7dq1Cz0t/fXXX6lZs+YN9+/QoQNpaWmcOnUKgCeffJIdO3aQkJBA5cqV8ff3t3pmEXF8Rgm9fcrf35+NGzcW9L4WV2mYmyByu1S8OpA7XZ7E2dm50JIkVx0+fJj33nuPNWvWsGvXLrp160Z2djaGYVz3aWZpEBYWRmpqKocPHyYnJ4f58+cTFVX4q7WDBw8W/G527NhBTk4OVapUAeDEiRMAHD16lO+++45+/frZ9gJExCGpvetat1oZ5qrExEScnZ355ptvCrZNnjyZgIAAAgMD6devH9nZ2baILCZT8epASnJ5kj8vJ3L27Fm8vLyoWLEix48fZ9myZcCVxaCPHTtW8BT33Llz5ObmloqlSFxcXJg+fToRERE0adKEPn36EBAQwIwZM5gxYwYA3377bcFM1KeffprY2NiCYvzhhx+madOm9OjRg48++ohKlSqZeTki4iCK0t61evVqxo8fT0ZGBnClvWvKlCmkpKRw6NChgvaumjVrEh8fT3x8PHClvSspKYldu3axfv16du3aRU5ODtHR0UydOrXg3F5eXrz++utER0eTnJxMdLR5k72KsjLM1f0mTJhAREREwbb09HSmTZtGUlISe/bsIS8vj/nz59syvpikdHzHKyXi6vIkY8eOJSYmBnd394JeqqysLJo1a4bFYilYnmT//v03PNfQoUPp2rUrPj4+xMfH07x5cwICAvD19aVdu3YAlCtXjtjYWEaNGsXFixfx8PBg9erVdOrUiZiYGEJCQnjhhRdMuzFGRkZe08/156cdEyZMYMKECdc99r///a9Vs4mI/NmN2ru8vb0L2ruAgvau9u3bX3OOBQsWMHPmTHJzc8nIyCAlJQWLxXJNe1dpsm3bNvz8/PD19QWgb9++xMXF0bRp00L7ffjhhzz88MMFD0uuys3N5eLFi7i6unLhwoWbtoeJ41Dx6mBq1qzJggULrtn+7rvv8u677xba1rFjRzp27Fjw+c8TrEaNGsWoUaMKPt+oUT4sLIwtW7Zcs/2vNxgREbnS3vXnr72vKqn2rqvftg0aNKjUt3fB9VeG2bp16zX7LFq0iLVr1xb6s6VWrVqMGzeOunXr4uHhQZcuXQpeKyuOTW0DIiIiNqL2rsKKsjLM2LFjefvtt3F2di60/fTp08TFxXH48GGOHTvG+fPnmTt3rlXzSumgJ68iIiI2ovauwoqyMkxSUhJ9+/YF4NSpUyxduhQXFxcuX77MPffcQ7Vq1QB46KGH2LRpE4899pjtLkBMoTdsObhnnnmGevXqMXbsWAAiIiKoU6dOwdujnnvuOWrVqsWzzz57zbGZmZnMmzePkSNH2jSziDXoDVsipU9ubi4NGzZkzZo11KpVi7CwMObNm0dAQMB19//zW7a2bt3K4MGDSUxMxMPDg0GDBhEaGlqo5U3sl96wVYa1bduWTZs2AZCfn8+pU6fYu3dvwc83bdpU8P/Q/yozM5OPP/64WOMZhlHq3rMtIiKlU1FWhrmRv/3tb/Tu3ZsWLVoQFBREfn4+Q4cOtVFyMZOevDq4Y8eO0apVK3799Vd2797Ne++9R0ZGBrGxsXh6elKjRg2OHj1Kr169OH36NJcvX+Zf//oXPXv2LJj12ahRIzp37lww6WvBggVcunSJXr168dprr3HkyBG6du1Kp06d2Lx5M99//z316tUz+9JFCtGTVxER+3Gze7Z6Xh1czZo1cXFx4ejRo2zatIk2bdqQnp7O5s2bqVixIsHBwXh6erJo0SK8vb05deoUrVu3JioqipiYGPbs2UNycjIAK1euJDU1lW3btmEYBlFRUSQkJFC3bl1++uknPvvss2I/qRUREREpDrUNlAHt2rVj06ZNBcVrmzZtCj63bdsWwzB48cUXCQ4O5oEHHiA9Pf26rypcuXIlK1eupHnz5rRo0YL9+/eTmpoKQL169WjdurWtL01ExO4988wzTJkypeBzREQEQ4YMKfj83HPP8cEHH1z32Ntp7xKxdypey4Crfa+7d+8mMDCQ1q1bs3nz5oJ+16+++oqTJ0+yfft2kpOTqVGjxnVfsWcYBi+88ALJyckkJydz8OBBnnzySQC8vLxsfVkiIg5BcxNEikfFaxnQrl07lixZQuXKlXF2dqZy5cpkZmayefNm2rRpw5kzZ6hevTqurq7Ex8fz888/A1yzDmBERASzZ88mKysLuLJw9IkTJ0y5JhERR3H12zGAvXv3EhgYSIUKFTh9+jSXLl1i3759NGnShPDw8ILJSXFxcQBMnDiRtLQ0QkJCGD9+PHDlpTRhYWEEBwfzyiuvAHDkyBGaNGnCyJEjadGiRaHlqUTNq5zlAAAF9klEQVTsjXpey4CgoCBOnTrFo48+WmhbVlYWVatWpX///vTo0YPQ0FBCQkJo3LgxAFWqVKFdu3YEBgbStWtX3n33Xfbt20ebNm0AKF++PHPnzr1m4WgRESk6zU0QKR4Vr2WAs7MzZ8+eLbTtz697rVq1Kps3b77usfPmzSv0ecyYMYwZM+aa/fbs2XPnQUVEyqg/z0149tlnSU9PZ9OmTVSsWLHQ3ISEhAScnJyKNDcBICsri9TUVOrWrau5CeIwVLyKiIiY7K9zE+rUqcP777+Pt7c3gwcPLjQ3wdXVlfr16990bsKwYcMKbT9y5IjmJojDUM+riIiIyTQ3QaTo9ORVRETEZJqbIFJ0esOWg1q+fDljxowhLy+PIUOGMHHixEI/NwyDMWPGsHTpUjw9PZkzZw4tWrS46bF//PEH0dHRHDlyhPr167NgwQIqVapETk4Ow4YNIykpCScnJ6ZOnUrHjh1tfckiN6U3bImI2I+b3bPVNuCA8vLyePrpp1m2bBkpKSl8/fXXpKSkFNpn2bJlpKamkpqaysyZMxkxYsQtj42JiSE8PJzU1FTCw8OJiYkBYNasWQDs3r2bVatW8dxzz2kNQREREbEKFa8OaNu2bfj5+eHr60u5cuXo27dvwZqAV8XFxfH4449jsVho3bo1mZmZZGRk3PTYuLg4Bg4cCMDAgQP5/vvvAUhJSSE8PByA6tWrc9ddd6GnPSIiImINKl4dUHp6OnXq1Cn4XLt2bdLT04u0z82OPX78OD4+PgD4+PgUTAJo1qwZcXFx5ObmcvjwYbZv364FsEVEbmH58uU0atQIPz+/gm+y/swwDEaPHo2fnx/BwcHs2LHjlsf+8ccfdO7cGX9/fzp37szp06cBWLVqFS1btiQoKIiWLVuydu1a61+giJWoeHVA1+tjtlgsRdqnKMf+1eDBg6lduzahoaGMHTuWtm3b4uKiuYAiIjdi6/auqlWrsnjxYnbv3s3nn3/OgAEDbHvBIiVIxasDql27dqEnn7/++is1a9Ys0j43O7ZGjRpkZGQAkJGRQfXq1QFwcXFh8uTJJCcnExcXR2ZmJv7+/la7PhERe2fr9q7mzZsX3MsDAgLIzs7m0qVLNrxikZKj4tUBhYWFkZqayuHDh8nJyWH+/PlERUUV2icqKoovvvgCwzDYsmULFStWxMfH56bHRkVF8fnnnwPw+eef07NnTwAuXLjA+fPngStfTbm4uNC0aVMbXrGIiH2xdXvXn3377bc0b94cNze3Er0mEVvRd7sOyMXFhenTpxMREUFeXh6DBw8mICCAGTNmADB8+HAiIyNZunQpfn5+eHp68tlnn930WICJEyfSp08fPv30U+rWrcvChQsBOHHiBBERETg5OVGrVi2+/PJLcy5cRMRO2Lq966q9e/cyYcIEVq5cWcSkIqWPilcHFRkZSWRkZKFtw4cPL/jfFouFjz76qMjHwpXFsNesWXPN9vr16/PTTz/dYWIRkbLjTtq7cnJybtne5ePjU6i96+p+vXr14osvvqBBgwbWujQRq1PbgIiIiI3Zur0rMzOTbt268dZbb9GuXTvbXqxICdOTVxERERuzdXvX9OnTOXjwIJMmTWLSpEkArFy5stCTWRF7odfDikiZoNfDiojYD70eVkREREQcgopXEREREbEbKl5FRERExG6oeBURERERu6HiVURERETshopXEREREbEbKl5FRERExG6oeBURERERu6HiVURERETshopXEREREbEbKl5FRERExG6oeBURERERu6HiVURERETshopXEREREbEbKl5FRERExG6oeBURERERu6HiVURERETshopXEREREbEbKl5FRERExG6oeBURERERu6HiVURERETshsUwjKLvbLGcBH62XhwREaupZxhGNbND2JLu2SJix254zy5W8SoiIiIiYia1DYiIiIiI3VDxKiIiIiJ2Q8WriIiIiNgNFa8iIiIiYjdUvIqIiIiI3VDxKiIiIiJ2Q8WriIiIiNgNFa8iIiIiYjdUvIqIiIiI3fh/yt4dm7bESoAAAAAASUVORK5CYII=\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": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
