{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "\n# ChemicalDrift - Transport and fate of organic compounds\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "from opendrift.readers import reader_netCDF_CF_generic\nfrom opendrift.models.chemicaldrift import ChemicalDrift\nfrom opendrift.readers.reader_constant import Reader as ConstantReader\nfrom datetime import timedelta, datetime\nimport matplotlib.pyplot as plt\nimport numpy as np\n\n\no = ChemicalDrift(loglevel=0, seed=0)\n\n# Norkyst\nreader_norkyst = reader_netCDF_CF_generic.Reader('https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be')\nmixed_layer = ConstantReader({'ocean_mixed_layer_thickness': 40})\no.add_reader([reader_norkyst,mixed_layer])\n\no.set_config('drift:vertical_mixing', True)\no.set_config('vertical_mixing:diffusivitymodel', 'windspeed_Large1994')\no.set_config('chemical:particle_diameter',30.e-6)  # m\no.set_config('chemical:particle_diameter_uncertainty',5.e-6) # m\no.set_config('chemical:sediment:resuspension_critvel',0.15) # m/s\no.set_config('chemical:transformations:volatilization', True)\no.set_config('chemical:transformations:degradation', True)\no.set_config('chemical:transformations:degradation_mode', 'OverallRateConstants')\no.set_config('seed:LMM_fraction',.9)\no.set_config('seed:particle_fraction',.1)\no.set_config('general:coastline_action', 'previous')\n\no.init_chemical_compound(\"Phenanthrene\")\n\n# Modify half-life times with unrealistic values for this demo\no.set_config('chemical:transformations:t12_W_tot', 6.) # hours\no.set_config('chemical:transformations:t12_S_tot', 12.) # hours\n\no.list_configspec()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Seeding 500 lagrangian elements each representign 2mg og target chemical\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "td=datetime.today()\ntime = td - timedelta(days=10)\n\nlatseed= 57.6;   lonseed= 10.6 # Skagen\n\nntraj=500\niniz=np.random.rand(ntraj) * -10. # seeding the chemicals in the upper 10m\n\no.seed_elements(lonseed, latseed, z=iniz, radius=2000,number=ntraj,time=time, mass=2e3)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Running model\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "o.run(steps=48*2, time_step=1800, time_step_output=1800)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "Print and plot results\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "print('Final speciation:')\nfor isp,sp in enumerate(o.name_species):\n    print ('{:32}: {:>6}'.format(sp,sum(o.elements.specie==isp)))\n\nprint('Number of transformations:')\nfor isp in range(o.nspecies):\n    print('{}'.format(['{:>9}'.format(np.int32(item)) for item in o.ntransformations[isp,:]]) )\n\nmass = o.get_property('mass')\nmass_d = o.get_property('mass_degraded')\nmass_v = o.get_property('mass_volatilized')\n\nm_pre = sum(mass[0][-1])\nm_deg = sum(mass_d[0][-1])\nm_vol = sum(mass_v[0][-1])\nm_tot = m_pre + m_deg + m_vol\n\nprint('Mass budget for target chemical:')\nprint('mass preserved       : {:.3f}'.format(m_pre * 1e-6),' g   {:.3f}'.format(m_pre/m_tot*100),'%')\nprint('mass degraded        : {:.3f}'.format(m_deg * 1e-6),' g   {:.3f}'.format(m_deg/m_tot*100),'%')\nprint('mass volatilized     : {:.3f}'.format(m_vol * 1e-6),' g   {:.3f}'.format(m_vol/m_tot*100),'%')\n\nlegend=['dissolved', '', 'SPM', 'sediment', '']\n\no.animation_profile(color='specie',\n            markersize='mass',\n            markersize_scaling=30,\n            alpha=.5,\n            vmin=0,vmax=o.nspecies-1,\n            legend = legend,\n            legend_loc = 3,\n            fps = 10\n            )"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<img src=\"file://gallery/animations/example_chemicaldrift_0.gif\">\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "o.animation(color='specie',\n            markersize='mass',\n            markersize_scaling=100,\n            alpha=.5,\n            vmin=0,vmax=o.nspecies-1,\n            colorbar=False,\n            fast = True,\n            legend = legend,\n            legend_loc = 3,\n            fps=10\n            )"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "<img src=\"file://gallery/animations/example_chemicaldrift_1.gif\">\n\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": false
      },
      "outputs": [],
      "source": [
        "o.plot_mass(legend = legend,\n            time_unit = 'hours',\n            title = 'Chemical mass budget')"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
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    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
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      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
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