diff --git a/caimira/docs/full_diameter_dependence.rst b/caimira/docs/full_diameter_dependence.rst
index 09561bee..626f21c2 100644
--- a/caimira/docs/full_diameter_dependence.rst
+++ b/caimira/docs/full_diameter_dependence.rst
@@ -317,6 +317,8 @@ The estimate of the concentration of CO\ :sub:`2` in a given room to indicate th
 Note that in order to calculate the CO\ :sub:`2` concentration one should use the concentration method defined in the superclass - :meth:`caimira.models._ConcentrationModelBase.concentration` - for a dedicated :class:`caimira.models.CO2ConcentrationModel` scenario.
 A fraction of 4.2% of the exhalation rate of the defined activity was considered as the  supplied to the room (:meth:`caimira.models.CO2ConcentrationModel.CO2_fraction_exhaled`).
 
+Note still that nothing depends on the aerosol diameter :math:`D` in this case (no particles are involved) - hence in this class all parameters are constant w.r.t :math:`D`.
+
 Since the CO\ :sub:`2` concentration differs from the virus concentration, the specific removal rate, CO\ :sub:`2` atmospheric concentration and normalization factors are respectively defined in :meth:`caimira.models.CO2ConcentrationModel.removal_rate`, 
 :meth:`caimira.models.CO2ConcentrationModel.min_background_concentration` and :meth:`caimira.models.CO2ConcentrationModel.normalization_factor`. 
 
diff --git a/caimira/models.py b/caimira/models.py
index 03602ca9..a9e5ae01 100644
--- a/caimira/models.py
+++ b/caimira/models.py
@@ -1085,7 +1085,12 @@ class _ConcentrationModelBase:
             return self.min_background_concentration()/self.normalization_factor()
         next_state_change_time = self._next_state_change(time)
         RR = self.removal_rate(next_state_change_time)
-        conc_limit = self._normed_concentration_limit(next_state_change_time)
+        # If RR is 0, conc_limit does not play a role but its computation 
+        # would raise an error -> we set it to zero.
+        try:
+            conc_limit = self._normed_concentration_limit(next_state_change_time)
+        except ZeroDivisionError:
+            conc_limit = 0.
 
         t_last_state_change = self.last_state_change(time)
         conc_at_last_state_change = self._normed_concentration_cached(t_last_state_change)