diff --git a/caimira/models.py b/caimira/models.py
index 2a766e6b..f43153fc 100644
--- a/caimira/models.py
+++ b/caimira/models.py
@@ -1417,23 +1417,23 @@ class ExposureModel:
 
     def _CO2_concentration(self, time: float) -> _VectorisedFloat:
         if time <= self.concentration_model._first_presence_time():
-            return 0.0
+            return 440.44e-6 # carbon dioxide concentration in the make up air (m3/m3 person) - 440ppm
         next_state_change_time = self.concentration_model._next_state_change(time)
         IVRR = self.concentration_model.air_exch_virus_removal_rate(next_state_change_time)
-        CO2_conc_limit = (self.concentration_model._CO2_concentration_limit(next_state_change_time) *
+        co2_conc_limit = (self.concentration_model._CO2_concentration_limit(next_state_change_time) *
                             (self.concentration_model.infected.activity.exhalation_rate * (self.exposed.number + self.concentration_model.infected.number)))
         
         t_last_state_change = self.concentration_model.last_state_change(time)
-        co2_conc_at_last_state_change = 0.00044
+        co2_conc_at_last_state_change = self._CO2_concentration_cached(t_last_state_change) # CO2 contribution in the room at start
 
         delta_time = time - t_last_state_change
         fac = np.exp(-IVRR * delta_time)
 
-        return (CO2_conc_limit * (1 - fac) + (co2_conc_at_last_state_change - 0.0004) * fac) + 0.0004
+        return co2_conc_limit * (1 - fac) + (co2_conc_at_last_state_change * fac)
 
     def CO2_concentration(self, time: float) -> _VectorisedFloat:
         # Correction due to the number of generated points.
-        return max(440, self._CO2_concentration(time) * 10**6)
+        return self._CO2_concentration(time) * 1e6
 
     def long_range_deposited_exposure_between_bounds(self, time1: float, time2: float) -> _VectorisedFloat:
         deposited_exposure = 0.