{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Wastewater Treatment (WWT)"
   ]
  },
  {
   "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",
    "The WWT process models in the SAT framework are designed so that by changing default parameters, a variety of WWT technology components and configurations can be represented. A relatively small amount of the incoming PFAS may be released in initial screen rejects and grit. Volatilization is another potential pathway, and its importance is currently poorly understood. Most PFAS entering conventional WWTPs will exit in the effluent or with the solids. In an increasing number of cases, some fraction of the PFAS are removed in tertiary treatment through reverse osmosis (RO), ion exchange (IX) or granular activated carbon (GAC) adsorption systems prior to release. These systems then produce new waste streams (i.e., RO concentrate and spent GAC, respectively) that must be managed.\n",
    "\n",
    "The mass flow of PFAS through the WWT processes is modeled using a water and mass balance through the system. The incoming PFAS-waste is diluted with the rest of the influent wastewater. When PFAS is partitioned between liquids and solids, it is assumed that equilibrium is achieved. The model does not consider transformations of PFAS. A relatively small fraction of the influent water leaves in the screen rejects and grit. The water lost with the material is assumed to have the same PFAS concentration as the influent. The remainder of the water and PFAS enters primary settling (if the WWTP has primary settling), and a fraction of the water at the influent PFAS concentration is again lost. The rest of the PFAS-containing water enters biological treatment, where PFAS partitions between the solids and liquid based on the organic carbon-normalized partition coefficient for each PFAS. The effluent from biological treatment enters secondary settling, which acts in a similar manner to primary settling. The effluent from secondary settling can then either be released to surface water or continue to tertiary treatment. The primary and secondary solids can then be thickened, dewatered, dried, stabilized, anaerobically digested or composted. The effluent can be treated through tertiary treatment processes designed to remove PFAS, such as GAC, RO, or IX.\n",
    "\n",
    "<img src=\"../Images/ProcessModels/WWTP.png\" alt=\"Drawing\" style=\"width: 700px;\"/>\n",
    "\n",
    "\n",
    "<img src=\"../Images/ProcessModels/WWT_Settling_Solids_Diagram_v3.png\" alt=\"Drawing\" style=\"width: 700px;\"/>\n",
    "\n",
    "\n",
    "\n",
    "### Assumptions and Limitations\n",
    "\n",
    "1.\tThe model assumes that liquids lost in screen rejects, grit, and settled solids have the same PFAS concentrations as the liquid entering the process.\n",
    "2.\tVolatilization is assumed to be zero. However, the user may assign a fraction of the PFAS that volatilizes/aerosolizes.\n",
    "3.\tFuture work and additional data are required to include PFAS transformations during WWT processes. \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Input Parameters for WWT model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
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       "        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>Category</th>\n",
       "      <th>Parameter Name</th>\n",
       "      <th>Parameter Description</th>\n",
       "      <th>amount</th>\n",
       "      <th>unit</th>\n",
       "      <th>minimum</th>\n",
       "      <th>maximum</th>\n",
       "      <th>Reference</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>WWT Plant</td>\n",
       "      <td>Des_Cap</td>\n",
       "      <td>Design capacity of the WWT plant</td>\n",
       "      <td>7.6000</td>\n",
       "      <td>Million Liter/day</td>\n",
       "      <td>3.00</td>\n",
       "      <td>300.000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Screen Rejects</td>\n",
       "      <td>frac_sr-grit</td>\n",
       "      <td>Mass fraction influent into screen rejects and grit</td>\n",
       "      <td>0.0001</td>\n",
       "      <td>fraction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Screen Rejects</td>\n",
       "      <td>sol_cont_sr_grit</td>\n",
       "      <td>Solids content of the screen rejects and grit</td>\n",
       "      <td>0.6500</td>\n",
       "      <td>fraction</td>\n",
       "      <td>0.50</td>\n",
       "      <td>0.900</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Primary Settling</td>\n",
       "      <td>is_prim_set</td>\n",
       "      <td>Is there primary settling</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1:TRUE,0:FALSE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Primary Settling</td>\n",
       "      <td>frac_prim_solids</td>\n",
       "      <td>Mass fraction influent into settling that exits in the solids</td>\n",
       "      <td>0.0040</td>\n",
       "      <td>fraction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Primary Settling</td>\n",
       "      <td>sol_cont_prim_solids</td>\n",
       "      <td>Solids content of primary solids - wet</td>\n",
       "      <td>0.0600</td>\n",
       "      <td>fraction</td>\n",
       "      <td>0.04</td>\n",
       "      <td>0.080</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Biological Treatmet</td>\n",
       "      <td>sol_cont</td>\n",
       "      <td>Mixed liquor suspended solids (MLSS)</td>\n",
       "      <td>3000.0000</td>\n",
       "      <td>mg/L</td>\n",
       "      <td>2000.00</td>\n",
       "      <td>4000.000</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Biological Treatmet</td>\n",
       "      <td>C_cont</td>\n",
       "      <td>Carbon content of the MLSS</td>\n",
       "      <td>0.5000</td>\n",
       "      <td>kg TS/kg</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Biological Treatmet</td>\n",
       "      <td>VS_cont</td>\n",
       "      <td>VS content of the MLSS - dry</td>\n",
       "      <td>0.8000</td>\n",
       "      <td>kg VSS/kg TS</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Thickening</td>\n",
       "      <td>is_prim_thick</td>\n",
       "      <td>Does primary sludge go to thickening</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1:TRUE,0:FALSE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Thickening</td>\n",
       "      <td>is_sec_thick</td>\n",
       "      <td>Does secondary sludge go to thickening</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1:TRUE,0:FALSE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Thickening</td>\n",
       "      <td>sol_cont_thick</td>\n",
       "      <td>Solids content after thickening</td>\n",
       "      <td>0.0500</td>\n",
       "      <td>fraction</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.100</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Dewatering</td>\n",
       "      <td>is_sol_dew</td>\n",
       "      <td>Are solids dewatered</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1:TRUE,0:FALSE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Dewatering</td>\n",
       "      <td>sol_cont_dewat</td>\n",
       "      <td>Solids content of dewatered solids</td>\n",
       "      <td>0.2200</td>\n",
       "      <td>kg TS/kg</td>\n",
       "      <td>0.15</td>\n",
       "      <td>0.300</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Secondary Settling</td>\n",
       "      <td>is_sec_set</td>\n",
       "      <td>Is there secondary settling</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1:TRUE,0:FALSE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Secondary Settling</td>\n",
       "      <td>frac_sec_solids</td>\n",
       "      <td>Mass fraction influent into settling that exits in the solids</td>\n",
       "      <td>0.0160</td>\n",
       "      <td>fraction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Drying</td>\n",
       "      <td>is_sol_dry</td>\n",
       "      <td>Are solids dried</td>\n",
       "      <td>1.0000</td>\n",
       "      <td>1:TRUE,0:FALSE</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Drying</td>\n",
       "      <td>sol_cont_dry</td>\n",
       "      <td>Solids content of dried solids</td>\n",
       "      <td>0.9000</td>\n",
       "      <td>kg TS/kg</td>\n",
       "      <td>0.65</td>\n",
       "      <td>0.950</td>\n",
       "      <td>[1]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Drying</td>\n",
       "      <td>frac_PFAS_to_Vol</td>\n",
       "      <td>Fraction of PFAS lost to volatilization</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>fraction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Volatilization</td>\n",
       "      <td>frac_vol_loss</td>\n",
       "      <td>Fraction of PFAS lost to volatilization</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>fraction</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>PFOA</td>\n",
       "      <td>PFOA Log Koc (WWT)</td>\n",
       "      <td>2.1900</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td>1.30</td>\n",
       "      <td>4.500</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>PFOS</td>\n",
       "      <td>PFOS Log Koc (WWT)</td>\n",
       "      <td>3.0400</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td>2.40</td>\n",
       "      <td>4.700</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>PFBA</td>\n",
       "      <td>PFBA Log Koc (WWT)</td>\n",
       "      <td>1.8800</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td>1.30</td>\n",
       "      <td>1.880</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>PFPeA</td>\n",
       "      <td>PFPeA Log Koc (WWT)</td>\n",
       "      <td>1.3700</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>PFHxA</td>\n",
       "      <td>PFHxA Log Koc (WWT)</td>\n",
       "      <td>1.7700</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td>1.31</td>\n",
       "      <td>2.100</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>PFHpA</td>\n",
       "      <td>PFHpA Log Koc (WWT)</td>\n",
       "      <td>1.9700</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>2.190</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>PFNA</td>\n",
       "      <td>PFNA Log Koc (WWT)</td>\n",
       "      <td>2.6300</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td>2.30</td>\n",
       "      <td>3.180</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>PFDA</td>\n",
       "      <td>PFDA Log Koc (WWT)</td>\n",
       "      <td>3.2400</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td>2.65</td>\n",
       "      <td>3.780</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>PFBS</td>\n",
       "      <td>PFBS Log Koc (WWT)</td>\n",
       "      <td>1.5100</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.790</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Log partition coefficient</td>\n",
       "      <td>PFHxS</td>\n",
       "      <td>PFHxS Log Koc (WWT)</td>\n",
       "      <td>2.7900</td>\n",
       "      <td>log L/kg OC</td>\n",
       "      <td>2.05</td>\n",
       "      <td>2.875</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Category        Parameter Name  \\\n",
       "0   WWT Plant                  Des_Cap                \n",
       "1   Screen Rejects             frac_sr-grit           \n",
       "2   Screen Rejects             sol_cont_sr_grit       \n",
       "3   Primary Settling           is_prim_set            \n",
       "4   Primary Settling           frac_prim_solids       \n",
       "5   Primary Settling           sol_cont_prim_solids   \n",
       "6   Biological Treatmet        sol_cont               \n",
       "7   Biological Treatmet        C_cont                 \n",
       "8   Biological Treatmet        VS_cont                \n",
       "9   Thickening                 is_prim_thick          \n",
       "10  Thickening                 is_sec_thick           \n",
       "11  Thickening                 sol_cont_thick         \n",
       "12  Dewatering                 is_sol_dew             \n",
       "13  Dewatering                 sol_cont_dewat         \n",
       "14  Secondary Settling         is_sec_set             \n",
       "15  Secondary Settling         frac_sec_solids        \n",
       "16  Drying                     is_sol_dry             \n",
       "17  Drying                     sol_cont_dry           \n",
       "18  Drying                     frac_PFAS_to_Vol       \n",
       "19  Volatilization             frac_vol_loss          \n",
       "20  Log partition coefficient  PFOA                   \n",
       "21  Log partition coefficient  PFOS                   \n",
       "22  Log partition coefficient  PFBA                   \n",
       "23  Log partition coefficient  PFPeA                  \n",
       "24  Log partition coefficient  PFHxA                  \n",
       "25  Log partition coefficient  PFHpA                  \n",
       "26  Log partition coefficient  PFNA                   \n",
       "27  Log partition coefficient  PFDA                   \n",
       "28  Log partition coefficient  PFBS                   \n",
       "29  Log partition coefficient  PFHxS                  \n",
       "\n",
       "                                            Parameter Description     amount  \\\n",
       "0   Design capacity of the WWT plant                               7.6000      \n",
       "1   Mass fraction influent into screen rejects and grit            0.0001      \n",
       "2   Solids content of the screen rejects and grit                  0.6500      \n",
       "3   Is there primary settling                                      1.0000      \n",
       "4   Mass fraction influent into settling that exits in the solids  0.0040      \n",
       "5   Solids content of primary solids - wet                         0.0600      \n",
       "6   Mixed liquor suspended solids (MLSS)                           3000.0000   \n",
       "7   Carbon content of the MLSS                                     0.5000      \n",
       "8   VS content of the MLSS - dry                                   0.8000      \n",
       "9   Does primary sludge go to thickening                           1.0000      \n",
       "10  Does secondary sludge go to thickening                         1.0000      \n",
       "11  Solids content after thickening                                0.0500      \n",
       "12  Are solids dewatered                                           1.0000      \n",
       "13  Solids content of dewatered solids                             0.2200      \n",
       "14  Is there secondary settling                                    1.0000      \n",
       "15  Mass fraction influent into settling that exits in the solids  0.0160      \n",
       "16  Are solids dried                                               1.0000      \n",
       "17  Solids content of dried solids                                 0.9000      \n",
       "18  Fraction of PFAS lost to volatilization                        0.0000      \n",
       "19  Fraction of PFAS lost to volatilization                        0.0000      \n",
       "20  PFOA Log Koc (WWT)                                             2.1900      \n",
       "21  PFOS Log Koc (WWT)                                             3.0400      \n",
       "22  PFBA Log Koc (WWT)                                             1.8800      \n",
       "23  PFPeA Log Koc (WWT)                                            1.3700      \n",
       "24  PFHxA Log Koc (WWT)                                            1.7700      \n",
       "25  PFHpA Log Koc (WWT)                                            1.9700      \n",
       "26  PFNA Log Koc (WWT)                                             2.6300      \n",
       "27  PFDA Log Koc (WWT)                                             3.2400      \n",
       "28  PFBS Log Koc (WWT)                                             1.5100      \n",
       "29  PFHxS Log Koc (WWT)                                            2.7900      \n",
       "\n",
       "                 unit  minimum   maximum Reference  \n",
       "0   Million Liter/day  3.00     300.000   NaN       \n",
       "1   fraction          NaN      NaN        NaN       \n",
       "2   fraction           0.50     0.900     [1]       \n",
       "3   1:TRUE,0:FALSE    NaN      NaN        NaN       \n",
       "4   fraction          NaN      NaN        [1]       \n",
       "5   fraction           0.04     0.080     [1]       \n",
       "6   mg/L               2000.00  4000.000  [1]       \n",
       "7   kg TS/kg          NaN      NaN        NaN       \n",
       "8   kg VSS/kg TS      NaN      NaN        NaN       \n",
       "9   1:TRUE,0:FALSE    NaN      NaN        NaN       \n",
       "10  1:TRUE,0:FALSE    NaN      NaN        NaN       \n",
       "11  fraction           0.03     0.100     [1]       \n",
       "12  1:TRUE,0:FALSE    NaN      NaN        NaN       \n",
       "13  kg TS/kg           0.15     0.300     [1]       \n",
       "14  1:TRUE,0:FALSE    NaN      NaN        NaN       \n",
       "15  fraction          NaN      NaN        [1]       \n",
       "16  1:TRUE,0:FALSE    NaN      NaN        NaN       \n",
       "17  kg TS/kg           0.65     0.950     [1]       \n",
       "18  fraction          NaN      NaN        NaN       \n",
       "19  fraction          NaN      NaN        NaN       \n",
       "20  log L/kg OC        1.30     4.500     NaN       \n",
       "21  log L/kg OC        2.40     4.700     NaN       \n",
       "22  log L/kg OC        1.30     1.880     NaN       \n",
       "23  log L/kg OC       NaN      NaN        NaN       \n",
       "24  log L/kg OC        1.31     2.100     NaN       \n",
       "25  log L/kg OC       NaN       2.190     NaN       \n",
       "26  log L/kg OC        2.30     3.180     NaN       \n",
       "27  log L/kg OC        2.65     3.780     NaN       \n",
       "28  log L/kg OC       NaN       1.790     NaN       \n",
       "29  log L/kg OC        2.05     2.875     NaN       "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "WWT = ps.WWT()\n",
    "WWT.InputData.Data[['Category','Parameter Name', 'Parameter Description', 'amount', 'unit','minimum','maximum','Reference']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Incoming Landfill Leachte to WWT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>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>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Moisture flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Volume flow</td>\n",
       "      <td>L</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Carbon flow</td>\n",
       "      <td>kg</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>PFOA</td>\n",
       "      <td>μg</td>\n",
       "      <td>5700</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>PFOS</td>\n",
       "      <td>μg</td>\n",
       "      <td>90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>PFBA</td>\n",
       "      <td>μg</td>\n",
       "      <td>750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>PFPeA</td>\n",
       "      <td>μg</td>\n",
       "      <td>680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>PFHxA</td>\n",
       "      <td>μg</td>\n",
       "      <td>1650</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>PFHpA</td>\n",
       "      <td>μg</td>\n",
       "      <td>550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>PFNA</td>\n",
       "      <td>μg</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>PFDA</td>\n",
       "      <td>μg</td>\n",
       "      <td>30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>PFBS</td>\n",
       "      <td>μg</td>\n",
       "      <td>190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>PFHxS</td>\n",
       "      <td>μg</td>\n",
       "      <td>270</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   10   \n",
       "2   Moisture flow  kg   990  \n",
       "3   Volume flow    L    1000 \n",
       "4   Carbon flow    kg   5    \n",
       "5   PFOA           μg   5700 \n",
       "6   PFOS           μg   90   \n",
       "7   PFBA           μg   750  \n",
       "8   PFPeA          μg   680  \n",
       "9   PFHxA          μg   1650 \n",
       "10  PFHpA          μg   550  \n",
       "11  PFNA           μg   50   \n",
       "12  PFDA           μg   30   \n",
       "13  PFBS           μg   190  \n",
       "14  PFHxS          μg   270  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "IncomingWaste = ps.IncomFlow()\n",
    "IncomingWaste.set_flow('LFLeachate', 1000)\n",
    "IncomingWaste.calc()\n",
    "LFLeachate = IncomingWaste.Inc_flow\n",
    "LFLeachate.report()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PFAS balance in WWT"
   ]
  },
  {
   "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>Volatilized</th>\n",
       "      <th>DryerExhaust</th>\n",
       "      <th>WWT Effluent</th>\n",
       "      <th>solids</th>\n",
       "      <th>Screen Rejects</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>80.21</td>\n",
       "      <td>19.78</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFOS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>37.37</td>\n",
       "      <td>62.62</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFBA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>88.74</td>\n",
       "      <td>11.25</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFPeA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>95.48</td>\n",
       "      <td>4.51</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHxA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>90.82</td>\n",
       "      <td>9.17</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHpA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>86.70</td>\n",
       "      <td>13.29</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFNA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>60.27</td>\n",
       "      <td>39.72</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFDA</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.40</td>\n",
       "      <td>72.59</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFBS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>94.26</td>\n",
       "      <td>5.73</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PFHxS</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>51.35</td>\n",
       "      <td>48.64</td>\n",
       "      <td>0.01</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Volatilized  DryerExhaust  WWT Effluent  solids  Screen Rejects\n",
       "PFOA   0.0          0.0           80.21         19.78   0.01          \n",
       "PFOS   0.0          0.0           37.37         62.62   0.01          \n",
       "PFBA   0.0          0.0           88.74         11.25   0.01          \n",
       "PFPeA  0.0          0.0           95.48         4.51    0.01          \n",
       "PFHxA  0.0          0.0           90.82         9.17    0.01          \n",
       "PFHpA  0.0          0.0           86.70         13.29   0.01          \n",
       "PFNA   0.0          0.0           60.27         39.72   0.01          \n",
       "PFDA   0.0          0.0           27.40         72.59   0.01          \n",
       "PFBS   0.0          0.0           94.26         5.73    0.01          \n",
       "PFHxS  0.0          0.0           51.35         48.64   0.01          "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "WWT.calc(Inc_flow=LFLeachate)\n",
    "WWT.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": [
    "WWT.plot_sankey()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x360 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "WWT.plot_sankey_report(margin=.6, gap=.6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "A=WWT.products()['WWTEffluent']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Effluent and solids mass flows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Effluent volume (Liter) : 988.4007936272117\n",
      "Screen Rejects mass (kg): 0.2857142857142857\n",
      "RawWWTSoilds mass (kg): 0.0\n",
      "DewateredWWTSolids mass (kg): 0\n",
      "DeriedWWTSolids mass (kg): 3.6033275744680844\n",
      "\n"
     ]
    }
   ],
   "source": [
    "products = WWT.products()\n",
    "print( \"\"\"\n",
    "Effluent volume (Liter) : {}\n",
    "Screen Rejects mass (kg): {}\n",
    "RawWWTSoilds mass (kg): {}\n",
    "DewateredWWTSolids mass (kg): {}\n",
    "DeriedWWTSolids mass (kg): {}\n",
    "\"\"\".format(products['WWTEffluent'].vol,\n",
    "           products['WWTScreenRejects'].mass,\n",
    "           products['RawWWTSolids'].mass,\n",
    "           products['DewateredWWTSolids'].mass,\n",
    "           products['DriedWWTSolids'].mass))        "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sensitivity to the Mixed liquor suspended solids (MLSS)  (Default: 1000 mg/L)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Percent of Incoming PFAS that \\n remains in the Effluent (%)')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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IJOHctNkBp/ryX1W13JplIvJQqdcAqOrDJxWpCYv4mEj+NaI3XZMb8sSHq1i74wDjrs0gpXG816EZY2qJQNdoXgUOAv8CGgBPB7nPgz6PIpwZOdtUPkQTbiLC7T/pwAvXZrB+xyF++vRXPPnhKjbvOex1aMaYWiDQNZqFqtrL5/V8Ve1T4QOIxAIzVPX8yodZMdZ1VnnfbtvPn99dweertyPA2V2SyMpM54yOzYmMsOs3xtRWnnSdOceVJpwYDBDp+1pVdwV5jHqA34EDpQ52D3ATzmi1JcAN7raTcVpE64GrVHV3kMc1ldAhqQEv39CfDbsOMWlOPpPnbODjFdto3SSeEf3TuCojleYNYr0O0xhTg4Rj1NkS3KHNQCTQHHhYVceWGYRIK+Br4BRVPSwirwPv4czmuUtV/yoi9wNNVPW+8j6UtWhC51hhMR8u30J2Tj6z1u4kOlI4v1tLRmWmM6BtUxulZkwt4UmLRlXbVHKfvgU0C3GmDQjmhs0oIF5EjuO0ZDbjVBg4y33/FZxJ18pNNCZ0YqIiuLhHChf3SOHbbQeYkJvP1HkbeGdxAe2bJ5A1IJ0rM1rTIC7a61CNMdVUyIY3l3MTZ7ldbSJyN87cN4eBD1U1S0T2qGpjn3V2q2qT8mKxFk14HT5WxDuLN5Odm8/CDXtIbRrPC6Mz6NLS5rczpqaqEffRiMg6nC6zCnW1uds2Ad4Argb2AFOAqcDYYBONiNwC3AKQlpbWNy8vr7IfxVTA7HW7uGPCfA4cLeTJq3pxQfeWXodkjKkET6o3V8K1bjLpqqptSz3KGwxwDrBOVber6nHgTZzKAltFJBnA/VlmrRRVHaeqGaqa0bx58xB9JFOe/m2b8vadg+nYogFjxs/jnx+vodgqQxtjfJSbaHzrm/k8/HXI/9P9ObMSceQDmSJST5yry0OAFcAM4Dp3neuA6ZXYtwmzFg3jmHxLJpf3acU/Pl7N7RPmc/Co1VE1xjgCDW8uMR9IxalbJkBjoEBEtgE3q+o8d73jIvIy0FpEfnRzp6reVdYBVDVXRKa6xyoEFuDUS6sPvC4iN+IkoyuD/mSmSsVFR/L3K3tySnJDHn1vBet2HOSF0RmkNq3ndWjGGI+Ve41GRP4NTFPVD9zX5wEXAK8D/3Sne0ZEEnG6wB4DHiq9H1V9JbShl80GA3jry9XbuWPCfCIjhGey+jCwfaLXIRljyuH1NZqMkiQDoKofAmeoag7ge+fevao6CXhGVV8p/Qhx3KYaO6NTc6bfMZhm9WO59qXZvDprPeEq3mqMqf6CSTS7ROQ+EUl3H78BdotIJM4NnSUucq/d2GyahraJCUy7bSBndWrOQ9OX8eC0JRwrLC5/Q2NMrRNMohkJtAbewrkYn+YuiwSu8lnvfWAH0ENE9vk89otIuVWfTe3TIC6acaMzuO2s9kycvYGRL+Swff9Rr8MyxlSxkM9HIyLTVXVYSHdaQXaNpvp5e9Fm7p26iKb1Yhg3OoPurRp5HZIxxoen12hEpJOIjBORD0Xk05KHn/W6AKjqMLdis+97maEL2dREl/RMYeqYgQAM//dMZiza7HFExpiqEkzX2RSc4ca/A+71eZQ2wef5rFLvPVup6Eyt0r1VI6bfMZhTWzXirokLeOz9lRTZzZ3G1HrB3EdTqKrPBbGelPHc32tTRzVvEEv2TZn8fsYynvv8O1Zt2c9T1/SioRXlNKbWCqZF87aI3CYiyb7VAfysp2U89/fa1GExURE8ell3/jSsG1+u3s5lz3zDuh0HvQ7LGBMmwdywuc7P4h8VyXQrBUzCab1c7T7HfX2VqrY4+XCDY4MBao5Z3+3ktux5FBUr/xrZhzM7WZ06Y7xQU6o3XxfofasMYMqyYdchbn51Lqu37ueBC7ty0+ltbUI1Y6qYJxOficjZqvqpiFzu731VfbPUa7v731RKatN6vHHrQH49ZRF/fm8FKwr28ejlpxIXHel1aMaYEAg0GOBM4FPgEj/vKU4pf2NCIiE2imdG9mHsZ9/y5Eer+W77AZ6/NoOWjeK8Ds0Yc5JCfsNmdWBdZzXbB8u28MvJC0mIjeLJq3oxqEMz60ozJsw8vUYjIo2B0UAbfFpAgcr+e80STc23ast+bn51Lvm7DtG5RQOyMtO4tHcrGwZtTJh4nWhmAjnAEnyKaJZ1TUZEOgHPAS1UtbuI9ACGquojIYu6HJZoaofDx4qYsWgT2bn5LN64l3oxkQzrlULWgHQrYWNMiHmdaOarap+gdyjyBU7lgOdVtbe7bKmqdj+pSCvAEk3ts3jjHrJz8pm+aBNHjhfTs3UjsjLTuaRHCvExNmjAmJPldaK5BzgAvAN8X3pXVXeVsf4cVe0nIgt8Es1CVe0VurADs0RTe+09fJxp8zeSnZvPmm0HaBAXxRV9WjMqM40OSQ28Ds+YGsuT4c0+jgGPA7/lxB3+CrQrY/0dItK+ZF0RGQ4UnGScxgDQKD6a6we15bqBbZizfjfjc/LIzs3jvzPXk9muKX8a1p2OLSzhGFOdBNOi+Q4YoKo7gtqhSDtgHDAQ2A2sA0ap6vqTCzV41qKpW3YcOMrUeRt58au1HDlezFNX9+KcU6qsEIUxtYLXUzkvAw4Fu0NVXauq5wDNgS6qOrgqk4ypexLrxzLmzPa8fedg2iYmcPNrc3nms29t+mhjqolgus6KgIUi8hk/vEbjd3izOxfNFbjDoUvuf1DVh082WGMCSW4Uz5Qxp3HfG4t5/INVLC/Yx+PDe1AvJphfc2NMuATzP/At9xGs6cBeYB4+icmYqhAXHclTV/filOSG/PX9lazbfpAXrsugVeN4r0Mzps4KqjKAiMQAndyXq1T1eIB1q3Qosz92jcYAfLZqG3dNXEBMZATPjepL/7b+ZrcwxoD3UzmfBawBnsGZKXO1iJwRYJOZInJqaMIzpvJ+0jmJt24fRKP4aEa+kEN2bp7XIRlTJwXTdfZ34DxVXQXf3/k/Eejru5KILMEZ0hwF3CAia3G6zgRn/poeoQzcmGC0b16fabcP4u5JC/jttKWsKNjHQxd3IyYqmHEwxphQCCbRRJckGQBVXS0i/gpOXRy6sIwJnUbx0bx0XT/+9sFKnv9iLau3HuC5rD40qx/rdWjG1AnBfK2bKyIvichZ7uMFnAv9P6CqeaqaBzxS8tx3WagDN6YiIiOEBy7sylNX92LRhj0MHfsNizfu8TosY+qEYBLNrTj30twF3A0sB8YEWL+b7wsRiaRUN5sxXrm0dyumjDmNomJl6NhvuGbcLN5ZvJljhcXlb2yMqZRgKgMkAEdUtch9HQnEquqhUus9ADwIxHPiBk/BKWEzTlUfCHHsZbJRZ6Y8uw8eY+KcfCbk5rNx92ES68dwVUYqI/qnkdq0ntfhGVPlvC6qmQOco6oH3Nf1gQ9VdWAZ6/+lKpOKP5ZoTLCKipUv12wnOyefT1duRYGzOjVnVGY6Z3VOIjLCJlwzdYPXieZHlZeruhpzRVmiMZWxac9hJs/OZ9KcDWzbf5RWjeMZ0T+Vq/qlktTAppQ2tZvXtc4Oisj389GISF/gcDiCMcZLrRrH88vzOvPN/WfzXFYf2iYm8MSHqxn4l0+5LXseeTsPeh2iMTVSMC2afsAkYLO7KBm4WlV/NPKsurAWjQmVtdsPMHF2PpNmbyAiQnhmZB8Gd0z0OixjQs7TrjM3gGigM87F/ZWBStC460cCLfC5T0dV808u1OBZojGhlrfzIDe/Opfvth/ktxd15YZBbSgpGGtMbeD1xGcA/XCrMQO9RQRVfdXfiiJyJ/B7YCtQMmZUAasMYGqs9GYJvHnbIO6ZvJCH31nOioJ9PHJZd2KjbBppY8pTbqIRkdeA9sBCnCkDwEkcfhMNzr02nVV1Z0giNKaaqB8bxfOj+vLUJ2t4+pM1fLv9AM+P6ktSQxsoYEwgwbRoMoBTNPhZpDbgTBNgTK0TESH88txOdGnZgF+9voihY7/h+Wv70jO1sdehGVNtBTPqbCnQsgL7XAt8LiIPiMgvSx6VC8+Y6umiU5N549aBREYIVz4/i2kLNnodkjHVVjCJJhFYLiIfiMiMkkeA9fOBj4AYoIHPIyAR6SwiC30e+0TkFyLSVEQ+EpE17s8mwXwwY8LtlJSGzLhjEL1TG3PP5EU8+t4Kiopt+mhjSgtmePOZ/par6hdhiYjvR61tAgYAtwO7VPWvInI/0ERV7wu0vY06M1XpeFExf3x7GeNz8jmzU3OeHtGbRvH+CpwbU315Prw5qB2JPKWqvxCRt3EGC/yAqg6twL7OA36vqoNEZBVwlqoWiEgy8Lmqdg60vSUa44Xs3Dx+P30ZqU3r8cLoDDok1fc6JGOC5snwZhHZj5+EwYmJzBqWWv6a+/OJEMR1Dc7kagAtVLUA56AFIpIUgv0bE3JZA9LpmNSAW8fP44KnvuT87i3JGpDGae2a2T03pk4LWYsmVEQkBqcKQTdV3Soie1S1sc/7u1X1R9dpROQW4BaAtLS0vnl5Nm2v8UbB3sO8+NU6ps7byN7Dx2nXPIGsAekM79OaRvWsS81UTzWi6yxURGQYcLuqnue+tq4zUyMdOV7EO4sLyM7NY0H+HmKjIrikZwpZA9LoldrYWjmmWqkOlQGq0ghOdJsBzACuA/7q/pzuRVDGVFRcdCTD+7ZmeN/WLNu8lwm5+by1YBNT522kW0pDsgakM6xXCgmx1fG/oTGhU2aLRkRiVfXoSe1cJAKor6r7gly/Hs4Nn+1Uda+7rBnwOpCGM3T6SlXdFWg/1qIx1dWBo4W8tWAT43PyWLllP/Vjo7isdyuyMtPo0rL0ZU9jqo4nXWciMl9V+4jIa6p6bdA7FJmAM9VzETAPaAQ8qaqPhyLgYFiiMdWdqjI/fw/ZuXm8s7iAY4XFZKQ3ISszjQu7JxMXbTXUTNXyKtEsBR4HHgLuLf2+qr5ZxnYLVbWXiGQBfYH7gHmqWmVFNS3RmJpk98FjvDF/I9m5+azbcZAm9aK50p1Wum1igtfhmTrCq2s0Y4AsoDFwSan3FPCbaIBod1qBS4GxqnpcRKrXiANjqpEmCTHcdHo7bhzclpnf7SQ7N4//fL2OcV+uZXCHREZlpjGkawuiI4Mp5GFM9VNmolHVr4GvRWSuqr5UgX0+D6wHFgFfikg6ENQ1GmPqMhFhUIdEBnVIZNu+I0yes4GJs/MZM34+SQ1iuaZ/Gtf0SyWlcbzXoRpTIcGUoInBad2c4S76Avh3eZOfldpHlKoWVjrKCrKuM1NbFBUrn6/axvicPD5fvR0BLuyezCOXdqdJQozX4ZlaxOvhzc8C0e5PgGuB54Cb/K0sIrHAFZyYKK3Ew5WO0pg6KjJCGNK1BUO6tmDDrkNMmJ3PS1+tY/GmPbwwOsNGqpkaIZhO336qep2qfuo+bsCZcbMs04FhQCFw0OdhjDkJqU3rcd8FXZj880yOHi/m8mdn8v7SLV6HZUy5gmnRFIlIe1X9DkBE2nFipk1/WqvqBSGJzhjzI73TmvD2nYO55bV5jBk/j3vO6cSdZ3cgIsIqDZjqKZgWzb3AZyLyuYh8AXwK/CrA+jNF5NSQRGeM8atFwzgm35LJ5b1b8Y+PV3P7hPkcPFpll0GNqZByWzSq+omIdAQ641RuXllOxYDBwPUisg44yolqz1V2H40xdUFcdCR/v6onp6Q05NH3VrBux0FeGJ1BatN6XodmzA+EvKimO5z5R1S1ysop26gzU9d8sXo7d06YT2SE8ExWHwa2T/Q6JFPDhHPUWcjuABORkuEv+8t4GGPC5MxOzZl+x2Ca1Y/l2pdm8+qs9VS3yuym7grlrcYT3J/zgLnuz3k+r40xYdQ2MYFptw3krE7NeWj6Mh6ctoRjhcVeh2VM+YlGRD4JZpmqXuz+bKuq7dyfJY92oQnXGBNIg7hoxo3O4Laz2jNx9gZGvpDDpj2HvQ7L1HGBpnKOA+oBiSLSBOeiPkBDICXQTt31OwJxJctU9cuTjtYYU67ICOE3F3Sha3JD7p26iNMf+5QhXVswKjOd0zsk2jBoU+UCjTr7OfALnKQyjxOJZh/wTFkbichNwN1Aa2AhkAnMAs4OQbzGmCBd0jOFXqmNmTA7n9fnbOCj5VtJa1qPkQPSuB+k01cAABiRSURBVLJva5rVj/U6RFNHBFPr7E5V/VfQOxRZglM5IMedLqAL8EdVvfrkQg2ejToz5oeOFhbxwbKtZOfkkbtuFzGREVzQvSWjMtPp16aJTSttvK11pqr/EpGBlKpdpqqvlrHJEVU9IiIls3SuFJHOoQnXGFMZsVGRDO2ZwtCeKazZup/s3HzemL+RGYs20zGpPlkD0ri8b2saxkV7HaqphYJp0bwGtMfpBispPaOqelcZ608DbsDpdjsb2A1Eq+pFoQq6PNaiMaZ8h44V8s6iArJz81i0cS/x0U4yyspMo0frxl6HZ6qYJzNs+hx8BXCKVmJQvoiciTOV8/uqeqxyIVacJRpjKmbJxr1k5+YxfeFmDh8vokfrRmQNSOOSninUiwmmJKKp6bxONFOAu1S1IOidOqPOUvlhV9v8ygZZUZZojKmcfUeOM23+JrJz81i99QAN4qK4ok9rRg5Io1OLBl6HZ8LI60TzGdALmI1TuwwAVR1axvp/Aq4H1gLFJ1bXKht1ZonGmJOjqszN2834nDz+t2QLx4qK6d+2KVkD0rige0tioyK9DtGEmNeJ5kx/y1X1izLWXwWcWpVdZaVZojEmdHYeOMqUeRuZkJtP/q5DNEuI4cqMVEb2TyOtmRXwrC08TTRuAOlAR1X9WETqAZGq6rd+mYi8AdyqqttCG2rwLNEYE3rFxcpX3+4gOyePj1dsRYHTOzZn1IA0zu6SRFRkKCtamarmdYvmZuAWoKmqtnenDPi3qg4pY/0MnFk2lxJEV1s4WKIxJrwK9h5m0uwNTJqTz9Z9R0luFMc1/dK4ul8qLRvFlb8DU+14nWgWAv2BXFXt7S5boqp+JzcTkWXA88ASTlyjKbOrLRws0RhTNQqLivlk5TbG5+Tx1ZodREYI53RNYlRmOoPaW7mbmsTTGzaBo6p6rOTOYRGJAgJlpx2q+nQogjPGVG9RkRGc360l53drSd7Og0yYnc+UuRv5YNlW2jRzyt0M75tK04QYr0M1HgqmRfM3YA8wGrgTuA1Yrqq/LWP9J3G6zGbww64zG95sTB1wtLCI95duYXxOHnPW7yYmMoKLTm1JVmY6GelW7qa68rrrLAK4ETgPp7DmB8CLZd3A6Q6HLs2GNxtTB63asp8JuXm8OX8T+48W0rlFA7Iy07isdysaWLmbasXrRJOAU7+syH0dCcSq6qFwBBQKlmiMqV4OHStkxsLNjM/NY+mmfdSLiWRYrxSyBqTTvVUjr8MzeJ9ocoBzVPWA+7o+8KGqDixj/RbAo0CKql4oIqcAp6nqS6ENvWyWaIypvhZt2EN2bh4zFm3myPFieqY2dsrd9EghPsZuBPWK14lmoar2Km+Zz3v/A14GfquqPd3BAwvKGqUWDpZojKn+9h4+zrT5Gxmfm8+32w7QMC6KK/q2JmtAGh2SrNxNVQtnognmDquDItLHJ5i+QKC5YRNV9XXcoc2qWsiJqs/GGANAo/horh/Ulo/uOYPJt2RyVuckxufkcc6TX3LNuFm8vWgzxwqLy9+RqfaCGd58NzBFRDa7r5OBQJOYHRSRZrhDoEUkE9h7UlEaY2otEWFAu2YMaNeMHQdOYcrcjUyYncedExeQWD+GqzJSGdE/jdSmVu6mpgrYdeaOOMsE5gCdcUadrVTV4wG26QP8C+iOUx2gOTBcVReHMO6ArOvMmJqtuFj5cs12snPz+cQtd3NWp+ZkDUjnJ12SiLQbQUPO62s0s1T1tKB2diIxzeZEYloVKDGFgyUaY2qPzXsOM2nOBibNzmfb/qOkNIpjRH+n3E1SQyt3EypeJ5o/AouBN4OZ/KwiiSlcLNEYU/scLyrmkxVbyc7N56s1O4iKEM7r1oKsAemc1q6Zlbs5SV4nmv1AAs4F/cM4rRRV1YZlrF+hxBQOlmiMqd3W7ygpd7OB3YeO0zYxgZH90xjetzVNrNxNpXg+TUCFdngiMRUCRygnMYWDJRpj6oYjx0+Uu5mbt5uYqAguPjWZrMx0+qQ1tnI3FeB1i0aALKCtqv5JRFKBZFWdHY6AQsESjTF1z8ot+5iQm8+b8zdx4GghXVo2ICsznct6t6J+bDADbOs2rxPNczj3xJytql1FpAlOZYB+IQ9GpDHwIs6INQV+BqwCJgNtgPXAVaq6O9B+LNEYU3cdPFrIjEWbGZ+Tx7LN+0iIiWRY71ZkDUijW4qVuymL14lmvqr2EZEFPvPRLFLVniEPRuQV4CtVfVFEYoB6wIPALlX9q4jcDzRR1fsC7ccSjTFGVVm0cS/ZOU65m6OFxfROa0zWgHQu7pFMXLSVu/HldaLJBQYCc9yE0xynRdM7pIGINAQWAe18BxGIyCrgLFUtEJFk4HNV7RxoX5ZojDG+9h46zhvzN5Kdm8d32w/SKD6a4X1bM3JAGu2b1/c6vGrB60SThVMJoA/wCjAc+J2qTglpICK9gHHAcqAnMA+nKsEmVW3ss95uVW3iZ/tbcKacJi0trW9eXl4owzPG1AKqSs7aXWTn5vHBsi0cL1IGtm9G1oB0zj2lBTFRwVTlqp08H3UmIl2AITgjyD5R1RUhD0QkA8gBBqlqroj8E9gH3BlMovFlLRpjTHm27z/K63M3MCE3n017DpNYP5Zr+qVyTf9UWjepe+VuPEk0IhIHjAE6AEuAl9wCmWEhIi2BHFVt474+HbjfPb51nRljwqKoWPly9Xayc/P4dOU2FPhJ5ySyBqRxVue6U+4mnIkm0Ji/V4DjwFfAhUBX4BfhCAJAVbeIyAYR6ayqq3BaUMvdx3XAX92f08MVgzGm7omMEH7SJYmfdEli057DTJqdz6Q5G7jxlbm0ahzPiP6pXNUvlaQGVu6msgK1aJaUzCHjzikzW1X7+F05VME412leBGKAtcANOFMZvA6kAfnAlaq6K9B+rEVjjDkZx4uK+Wj5VrJz8/jm253fl7sZNSCd09o3q5U3gnrVovm+EKaqFlbFiVXVhYC/Dzok7Ac3xhhXdGQEF52azEWnJrN2+wEm5OYzZd5G3luyhXaJCYwc4JS7aVzPyt0EI1CLpgg4WPISiAcO4UFJmYqyFo0xJtSOHC/ivSUFjM/JY37+HmKjIri4RwpZmWn0Tq355W48H3VW01iiMcaE0/LN+8jOzeOtBZs4eKyIrskNGZWZxrBeNbfcjSWaCrJEY4ypCgeOFjJ94SbG5+SzosApd3Np71aMykyna3K17fTxyxJNBVmiMcZUJVVlwYY9jM/J493FBRwtLKaPW+7mpzWk3I0lmgqyRGOM8cqeQ8eYOm8jE3LzWbvjII3rRTO8j1Pupl01LndjiaaCLNEYY7ymqsz6bifZufl8sGwLhcXKoA4nyt1ER1avcjeWaCrIEo0xpjrZtu8Ir8/dwMTZG9i05zDNG5SUu0mjVeN4r8MDLNFUmCUaY0x1VFSsfL5qG9m5+Xy2ahsCnN0liawB6ZzRqbmn5W68umHTGGNMCEVGCEO6tmBI1xZs2HWISXPymTxnAx+v2EbrJvGM6J/GVRmpNG8Q63WoIWUtGmOM8dCxwmI+XL6F7Jx8Zq3dSXSkcH63lmQNSCezXdMquxHUus4qyBKNMaYm+nabU+5m6rwN7DtSSPvmCWQNSOeKPq1pVC86rMe2RFNBlmiMMTXZkeNFvLPYKXezcMMe4qIjuKRHClmZ6fRs3SgsrRxLNBVkicYYU1ss3bSX7Nx8pi/cxKFjRXRLaciozHSG9kwhIYTlbizRVJAlGmNMbbP/yHHeWriZ7Jw8Vm7ZT/3YKC7r3YqszDS6tDz5cjeWaCrIEo0xprZSVebn72Z8Tj7vLingWGExGelNyMpM48LulS93Y4mmgizRGGPqgl0Hj/HGvI1k5+axfuchmtSL5sqMVEb2T6NNYkKF9mWJpoIs0Rhj6pLiYmXmdzsZn5PHRyu2UlSsnN4xkawBaQzpGly5G0s0FWSJxhhTV23dd4TJczYwcXY+BXuP0KJhLFf3S2NE/1SSG5Vd7sYSTQVZojHG1HWFRcV8tmo72bl5fLF6OwIM6dqCrAFpnNGxORGlyt1YCRpjjDEVEhUZwbmntODcU5xyNxNm5/P6nA18tHwrqU3jGdk/nSszWpNYP/zlbqxFY4wxdcSxwmI+WLaF8Tl55K7bRXSkcGH3ZLIGpJHZPtFaNMYYY05OTFQEl/RM4ZKeKXy7bT/Zufm8MW8jMxZtDutxrUVjjDF12OFjRby9eDNX90sLW4umek3xZowxpkrFx0RyVUZqWI9hicYYY0xYWaIxxhgTVpZojDHGhJUlGmOMMWFlicYYY0xYWaIxxhgTVpZojDHGhJUlGmOMMWFVKysDiMh2IM/rOEIoEdjhdRDVlJ0b/+y8lM3OjX+dVbVBOHZcK2udqWpzr2MIJRGZG67SEDWdnRv/7LyUzc6NfyIStrpd1nVmjDEmrCzRGGOMCStLNDXDOK8DqMbs3Phn56Vsdm78C9t5qZWDAYwxxlQf1qIxxhgTVpZojDHGhJUlGg+ISKqIfCYiK0RkmYjc7S5vKiIficga92cTn20eEJFvRWSViJzvs7yviCxx33taRMSLzxRqIhIpIgtE5B33dZ0/NyLSWESmishK93fnNDsvDhG5x/2/tFREJopIXF09NyLyHxHZJiJLfZaF7FyISKyITHaX54pIm3KDUlV7VPEDSAb6uM8bAKuBU4C/Afe7y+8HHnOfnwIsAmKBtsB3QKT73mzgNECA/wEXev35QnSOfglMAN5xX9f5cwO8AtzkPo8BGtt5UYBWwDog3n39OnB9XT03wBlAH2Cpz7KQnQvgNuDf7vNrgMnlxuT1SbGHAkwHzgVWAcnusmRglfv8AeABn/U/cH8BkoGVPstHAM97/XlCcD5aA58AZ/skmjp9boCG7h9TKbW8Tp8X9zO0AjYATXFuQn8HOK8unxugTalEE7JzUbKO+zwKp8qCBIrHus485jY7ewO5QAtVLQBwfya5q5X8Ryqx0V3Wyn1eenlN9xTwG6DYZ1ldPzftgO3Ay26X4osikoCdF1R1E/AEkA8UAHtV9UPs3PgK5bn4fhtVLQT2As0CHdwSjYdEpD7wBvALVd0XaFU/yzTA8hpLRC4GtqnqvGA38bOsNp6bKJzukOdUtTdwEKcLpCx15bzgXm8YhtP1kwIkiMioQJv4WVYrz00QKnMuKnyeLNF4RESicZJMtqq+6S7eKiLJ7vvJwDZ3+UYg1Wfz1sBmd3lrP8trskHAUBFZD0wCzhaR8di52QhsVNVc9/VUnMRT188LwDnAOlXdrqrHgTeBgdi58RXKc/H9NiISBTQCdgU6uCUaD7ijN14CVqjqkz5vzQCuc59fh3PtpmT5Ne5oj7ZAR2C22wTeLyKZ7j5H+2xTI6nqA6raWlXb4Fxo/FRVR1HHz42qbgE2iEhnd9EQYDl1/Ly48oFMEannfqYhwArs3PgK5bnw3ddwnP+jgVt+Xl+0qosPYDBOU3MxsNB9XITTz/kJsMb92dRnm9/ijAhZhc9IGCADWOq+N5ZyLsrVpAdwFicGA9T5cwP0Aua6vzdvAU3svHz/mf4IrHQ/12s4o6jq5LkBJuJcqzqO0/q4MZTnAogDpgDf4oxMa1deTFaCxhhjTFhZ15kxxpiwskRjjDEmrCzRGGOMCStLNMYYY8LKEo0xxpiwskRTA4mIishrPq+jRGS7nKh0PFREAt01XpFjHQi0XERSRGRqKI5VG4hIG9+quUFu818RGX6Sx71eRMa6z8eIyOiTjU0cn4pIQ/d1eb9338dQaj8/c6sALxanuvIwd3mmW/13oTjVqP/gLr9YRP4YIK5LReShYD9HEJ8zWUQ+LOv8iMgTInJ2qI5XF0V5HYCplINAdxGJV9XDOAU5N5W8qaozcG6qCjtV3Yxz01bYiEiUOjWVTBBU9d8h2tVFwCI9UR4p4O+dPyLSGuc+jT6qutctu9TcffsV4CpVXSQikUDJzajvAn8SkcdU9ZCf3f4GGHpSn+yHLsApFFmWfwEvAJ+G8Jh1irVoaq7/AT91n4/AuUkL+NG32+kl325F5Ociku0+by8i74vIPBH5SkS6uMvbisgsEZkjIn8qLwjfb4EiEi8ik9xvrpPdb6sZ7nsHfLYZLiL/dZ+ni8gn7jafiEiau/y/IvKkiHwGPFbqmN1EZLb7TXixiHQs/W1URH7t8w35LhFZ7q47yV32BxF5zf3GvkZEbvbZ9l738y8u+Wbt7n+FiLwgzrwnH4pIvPteXxFZJCKzgNt99hMpIo/77Ovn7nIRkbFuTO9yosBh6XPrL+6mIvKWuyxHRHr42e4PIvLrcmL70Tn0E0IWP74zvszfuzIkAfuBAwCqekBV1/m8V1LosUhVl7vPFfgcuNjPZ+sEHFXVHe7r/4rIc+LM77RWRM4UZz6WFSW/Y+56N4rIahH53P039G15XeB+Lr9UNQ9oJiIty/mspgyWaGquSTilI+KAHjjVn/25BXhIRE4HfgXc6S4fB9ypqn2BXwPPusv/iVO4sR+wpYIx3QocUtUewJ+BvkFsMxZ41d0mG3ja571OwDmq+qtS24wB/qmqvXDuXt5IYPcDvd1jjPFZ3gPnj+ZpOOcoRUTOwynD0R/nTvy+InKGu35H4BlV7QbsAa5wl78M3KWqp5U67o04lYT7Af2Am8Up83EZzrf3U4GbcepyBRv3H4EF7rIHgVfL+exlxRbMORwElC5uGuzvXYlFwFZgnYi8LCKX+Lz3D2CViExzvwTF+bw3Fzi9jJjml1rWBGdKiXuAt939dgNOFZFeIpIC/B+QidMK61KyYUlLqiTJBTDfPbapBEs0NZSqLsaZc2IE8F6A9bYCDwGfAb9S1V3idF8MBKaIyELgeZz5J8D5z1TyLfW10vsrxxnAeJ/4FgexzWk4E5yVHG+wz3tTVLXIzzazgAdF5D4g3e3GCWQxkC1ORV/fLrjpqnrY/Xb8GU5yOc99LMD549IFJ8GAU7hxoft8HtBGRBoBjVX1C5/PUOI8YLR7jnNxyoB0xDlPE91v8Zspu0vGX9yDS46hqp/ifNNu5G/jcmIL5hw2VdX9vguC/b3zWb8Ip8UwHGeCv3+UtDRV9WGcJPchMBJ432fTbTiVmEtLxpkuwdfbbitoCbBVVZeoajGwzI21P/CFqu5Sp+jmFJ9tB1B+sgwUjwmCJZqabQbOPBzldV+cCuzkxH+UCGCPqvbyeXT1Wf9k6hKVta3v8rgy1im93kG/K6hOwOmjPwx8IM6F2kJ++Pvse4yfAs/gtLDmiVNx1l+sJeXR/+JzXjqo6kvu+0d91i3CucYpfvZTQnBajSX7aqvOPCn+ju2Pv7grUqK9zNjKOIelFYqIv78Rwf7elRxLVXW2qv4Fp1DqFT7vfaeqz+EUwuwpIiXzmsS5sZV2mB///pT8uxTzw3+jYk78G5XlQn6Y4MpSVjwmCJZoarb/AA+r6pKyVhCR/jj/mXoDvxaRtu7F3XUicqW7johIT3eTb3D+GIDTR18RX5ZsIyLdcbpWSmwVka7uH67LfJbPLHW8r8s7iIi0A9aq6tM4f/R64HTPJIlIMxGJxe3fd4+Xqqqf4VxEbgzUd3c1TJy55ZvhFPCcg3NR+Gduqw8RaSUifq+hAKjqHmCviJS0xHzP2QfAreJMCYGIdBJnsrIvcbqfIsUp2f4TP5+xrLh9z/FZwA4tYy6jQLGVcQ5LW4Uz4Vpp5f7e+RwnRUT6+CzqBeS57/1UREqSQEec5L3Hfd0Jp6BjaSuADuUdt5TZwJki0sRN1lf4vDcEp8hkecqKxwTBRp3VYKq6Eeeail/uH9wXgBtUdbOI/Ar4j/vtNQt4TkR+B0Tj9L0vAu4GJojI3Tjz5VTEczgzQJZUpZ7t8979OFPsbsD5D1vyx/4uN6Z7cbpEbgjiOFcDo0TkOM51pIdV9biIPIzTDbIOp5IvQCQw3u1GEuAfqrrH/fs2G2eEUxrwJ7cba7OIdAVmuescAEbh/BEsyw3uZzjED0cvvYjTdTPf/YO6HbgUmIZzTWEJTnfSF/xYWXH/gRPn+BAnyrVXNLYfnUM/276Lk4C/9V1Yzu/d9SJyqc/rQcAT7nWSIzjnoOR607U4XWmHcFqkWT5dpT/BmWa4tC+Bv4uIaJAVgVV1k4g8ivO7sRlneoW9ItIcOFIqUXcWEd/rVffgVMrugHPdyFSCVW82YSMinwO/VtVq9x/U/YN9QFWf8DqW6sptbb2qqudW8XFbABNUdUgZ7/8T57rMxxXYZ31VPeC2aKbhtMoSgNaq+tdytr0MZ3j2/wX9IcwPWIvGGOOXqha4Q4EbltU9FyZpOCMky/IozkX8iviDiJyDc63lQ+CtYFtEOH8n/17B4xkf1qIxxhgTVjYYwBhjTFhZojHGGBNWlmiMMcaElSUaY4wxYWWJxhhjTFj9P14tX4pMUHliAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "MLSS = np.linspace(500,10000,30)\n",
    "PFAS_inEffluent = []\n",
    "IncomingWaste.set_flow('LFLeachate', 1000)\n",
    "IncomingWaste.calc()\n",
    "for i in MLSS:\n",
    "    WWT.InputData.BioTrtmnt['sol_cont']['amount'] = i\n",
    "    WWT.calc(IncomingWaste.Inc_flow)\n",
    "    PFAS_inEffluent.append(round(WWT.report(normalized=True)['WWT Effluent']['PFOA']))\n",
    "plt.plot(MLSS,PFAS_inEffluent)\n",
    "plt.xlim(500,10000)\n",
    "plt.xlabel('Mixed liquor suspended solids (MLSS) (mg/L)')\n",
    "plt.ylabel('Percent of Incoming PFAS that \\n remains in the Effluent (%)')"
   ]
  }
 ],
 "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
}
