diff --git a/cara/models.py b/cara/models.py
index 0572c8f3..9195ef76 100644
--- a/cara/models.py
+++ b/cara/models.py
@@ -643,7 +643,21 @@ class ConcentrationModel:
         # Deposition rate (h^-1)
         k = (vg * 3600) / h
 
-        return k + self.virus.decay_constant + self.ventilation.air_exchange(self.room, time)
+        return k + self.virus.decay_constant + self.ventilation.air_exchange(
+            self.room, time
+        )
+
+    @cached()
+    def _concentration_limit(self, time: float) -> _VectorisedFloat:
+        """
+        Provides a constant that represents the theoretical asymptotic 
+        value reached by the concentration when time goes to infinity,
+        if all parameters were to stay time-independent.
+        """
+        V = self.room.volume
+        IVRR = self.infectious_virus_removal_rate(time)
+
+        return (self.infected.emission_rate(time)) / (IVRR * V)
 
     @cached()
     def state_change_times(self):
@@ -668,22 +682,42 @@ class ConcentrationModel:
                 return change_time
         return 0
 
+    def _next_state_change(self, time: float):
+        """
+        Find the nearest future state change.
+
+        """
+        for change_time in self.state_change_times():
+            if change_time >= time:
+                return change_time
+        raise ValueError(
+            f"The requested time ({time}) is greater than last available "
+            f"state change time ({change_time})"
+        )
+
     @cached()
     def concentration(self, time: float) -> _VectorisedFloat:
-        # Note that time is not vectorised. You can only pass a single float
-        # to this method.
+        """
+        Virus quanta concentration, as a function of time.
+        The formulas used here assume that all parameters (ventilation,
+        emission rate) are constant between two state changes - only
+        the value of these parameters at the next state change, are used.
+
+        Note that time is not vectorised. You can only pass a single float
+        to this method.
+        """
 
         if time == 0:
             return 0.0
-        IVRR = self.infectious_virus_removal_rate(time)
-        V = self.room.volume
+        next_state_change_time = self._next_state_change(time)
+        IVRR = self.infectious_virus_removal_rate(next_state_change_time)
+        concentration_limit = self._concentration_limit(next_state_change_time)
 
         t_last_state_change = self.last_state_change(time)
         concentration_at_last_state_change = self.concentration(t_last_state_change)
 
         delta_time = time - t_last_state_change
         fac = np.exp(-IVRR * delta_time)
-        concentration_limit = (self.infected.emission_rate(time)) / (IVRR * V)
         return concentration_limit * (1 - fac) + concentration_at_last_state_change * fac
 
 
diff --git a/cara/tests/models/test_concentration_model.py b/cara/tests/models/test_concentration_model.py
index 9be1cbbf..5f42a6d0 100644
--- a/cara/tests/models/test_concentration_model.py
+++ b/cara/tests/models/test_concentration_model.py
@@ -1,7 +1,9 @@
+import re
+
 import numpy as np
 import pytest
 
-import cara.models
+from cara import models
 
 
 @pytest.mark.parametrize(
@@ -27,28 +29,28 @@ def test_concentration_model_vectorisation(override_params):
     }
     defaults.update(override_params)
 
-    always = cara.models.PeriodicInterval(240, 240)  # TODO: This should be a thing on an interval.
-    c_model = cara.models.ConcentrationModel(
-        cara.models.Room(defaults['volume']),
-        cara.models.AirChange(always, defaults['air_change']),
-        cara.models.InfectedPopulation(
+    always = models.PeriodicInterval(240, 240)  # TODO: This should be a thing on an interval.
+    c_model = models.ConcentrationModel(
+        models.Room(defaults['volume']),
+        models.AirChange(always, defaults['air_change']),
+        models.InfectedPopulation(
             number=1,
             presence=always,
-            mask=cara.models.Mask(
+            mask=models.Mask(
                 η_exhale=defaults['η_exhale'],
                 η_leaks=defaults['η_leaks'],
                 η_inhale=0.3,
             ),
-            activity=cara.models.Activity(
+            activity=models.Activity(
                 0.51,
                 0.75,
             ),
-            virus=cara.models.Virus(
+            virus=models.Virus(
                 halflife=defaults['virus_halflife'],
                 viral_load_in_sputum=defaults['viral_load_in_sputum'],
                 coefficient_of_infectivity=defaults['coefficient_of_infectivity'],
             ),
-            expiration=cara.models.Expiration(
+            expiration=models.Expiration(
                 ejection_factor=(0.084, 0.009, 0.003, 0.002),
             ),
         )
@@ -56,3 +58,47 @@ def test_concentration_model_vectorisation(override_params):
     concentrations = c_model.concentration(10)
     assert isinstance(concentrations, np.ndarray)
     assert concentrations.shape == (2, )
+
+
+@pytest.fixture
+def simple_conc_model():
+    interesting_times = models.SpecificInterval(([0, 1], [1.1, 1.999], [2, 3]), )
+    return models.ConcentrationModel(
+        models.Room(75),
+        models.AirChange(interesting_times, 100),
+        models.InfectedPopulation(
+            number=1,
+            presence=interesting_times,
+            mask=models.Mask.types['Type I'],
+            activity=models.Activity.types['Seated'],
+            virus=models.Virus.types['SARS_CoV_2'],
+            expiration=models.Expiration.types['Breathing'],
+        )
+    )
+
+
+@pytest.mark.parametrize(
+    "time, expected_next_state_change", [
+        [0, 0],
+        [1, 1],
+        [1.1, 1.1],
+        [1.11, 1.999],
+        [2, 2],
+        [2.1, 3],
+        [3, 3],
+    ]
+)
+def test_next_state_change_time(
+        simple_conc_model: models.ConcentrationModel,
+        time,
+        expected_next_state_change,
+):
+    assert simple_conc_model._next_state_change(time) == expected_next_state_change
+
+
+def test_next_state_change_time_out_of_range(simple_conc_model: models.ConcentrationModel):
+    with pytest.raises(
+            ValueError,
+            match=re.escape("The requested time (3.1) is greater than last available state change time (3)")
+    ):
+        simple_conc_model._next_state_change(3.1)