:py:mod:`gnome.utilities.weathering.huibers_lehr`
=================================================

.. py:module:: gnome.utilities.weathering.huibers_lehr


Module Contents
---------------

Classes
~~~~~~~

.. autoapisummary::

   gnome.utilities.weathering.huibers_lehr.HuibersLehr




.. py:class:: HuibersLehr


   Bases: :py:obj:`object`

   Using Huibers & Katrisky for solubility.
   Using EPA report (2012), and tweaking by Bill so that results
   better match measured values, to estimate the correlation between
   a specific aromatic hydrocarbon's density and molecular weight
   with its partition coefficient.

       rho_arom = density of aromatic
       mol_wt = molecular weight
       S_w = solubility

       S_w = Huibers(rho_arom, mol_wt)
       k_ow = 5.45 * s**(-.89)  (EPA)
       k_ow = 10 * s**(-.95)  (Lehr)


   .. py:method:: partition_coeff(mol_wt, density)
      :classmethod:

      :param mol_wt: Molecular weight in kg/kmole
      :param density: Density in kg/m^3