diff --git a/cara/short_range_plots/results.py b/cara/short_range_plots/results.py
index 658ab820..efb1be4b 100644
--- a/cara/short_range_plots/results.py
+++ b/cara/short_range_plots/results.py
@@ -20,41 +20,42 @@ from cara.monte_carlo.data import symptomatic_vl_frequencies
 
 # print('\n<<<<<<<<<<< Peak viral concentration with short range interactions for baseline scenarios >>>>>>>>>>>')
 # concentration_curve(models=[exposure_module_with_short_range(
-#                                     activity='Seated', 
-#                                     expiration={"Speaking": 1, "Breathing": 2}, 
+#                                     activity='Light activity',
+#                                     expiration={"Speaking": 1, "Breathing": 2},
 #                                     mask='No mask',
-#                                     sr_presence=[(10.5, 11.0), (15.5, 16.0)],
-#                                     sr_activities=['Breathing', 'Shouting']),
+#                                     sr_presence=[(10.5, 11.0), (15.0, 16.0)],
+#                                     sr_activities=['Breathing', 'Speaking']),
 #                             exposure_module_without_short_range(
-#                                 activity='Seated', 
-#                                 expiration={"Speaking": 1, "Breathing": 2}, 
-#                                 mask='No mask',
-#                             )],
-#                             labels = ['Mean concentration with short range interactions', 'Mean concentration without short range interactions'],
-#                             colors = ['royalblue', 'darkviolet'],
-#                             linestyles = ['-', '-'],
-#                             thickness = [2, 2.5])
+#                                 activity='Light activity',
+#                                 expiration={"Speaking": 1, "Breathing": 2},
+#                                 mask='No mask',)
+#                             ],
+#                             labels = ['Concentration with short range interactions', 'Background (long-range) concentration'],
+#                             labelsDose = ['Dose (full)', 'Dose (long-range)'],
+#                             colors = ['salmon', 'royalblue'],
+#                             linestyles = ['-', '--'],
+#                             thickness = [2, 2])
 
-# print('\n<<<<<<<<<<< Probability of infections vs exposure time >>>>>>>>>>>')
-# Always assume 1h for the short range interactions.
-# Always assume that in each model there is only ONE short range interaction.
-# plot_pi_vs_exposure_time(exp_models = [
-#                             baseline_model(
-#                                 activity='Seated', 
-#                                 expiration={"Speaking": 2, "Breathing": 1}, 
-#                                 mask='No mask',
-#                                 sr_presence=[(10.0, 11.0)],
-#                                 sr_activities=['Breathing']),
-#                             baseline_model(
-#                                 activity='Seated', 
-#                                 expiration={"Shouting": 2, "Breathing": 1}, 
-#                                 mask='No mask',
-#                                 sr_presence=[(10.0, 11.0)],
-#                                 sr_activities=['Shouting'])],
-#                          labels = ['Baseline model breathing', 'Baseline model shouting'],
-#                          colors=['royalblue', 'darkviolet'],
-#                          linestyles=['solid', 'solid'],
-#                          points=20,
-#                          time_in_minutes=True,
-#                          normalize_y_axis=True)
+print('\n<<<<<<<<<<< Dose vs SR exposure time >>>>>>>>>>>')
+#Always assume 1h for the short range interactions.
+#Always assume that in each model there is only ONE short range interaction.
+plot_vD_vs_exposure_time(exp_models = [
+                            baseline_model(
+                                activity='Light activity',
+                                expiration={"Speaking": 2, "Breathing": 1},
+                                mask='No mask',
+                                sr_presence=[(8.5, 9.5)],
+                                sr_activities=['Breathing']),
+                            baseline_model(
+                                activity='Light activity',
+                                expiration={"Speaking": 2, "Breathing": 1},
+                                mask='No mask',
+                                sr_presence=[(8.5, 9.5)],
+                                sr_activities=['Speaking'])],
+                         labels = ['Baseline model breathing', 'Baseline model speaking'],
+                         colors=['royalblue', 'darkviolet'],
+                         linestyles=['solid', 'solid'],
+                         points=20,
+                         time_in_minutes=True,
+                         normalize_y_axis=True)
 
diff --git a/cara/short_range_plots/scripts.py b/cara/short_range_plots/scripts.py
index 72a54441..3e537d3c 100644
--- a/cara/short_range_plots/scripts.py
+++ b/cara/short_range_plots/scripts.py
@@ -149,18 +149,14 @@ def concentration_curve(models, labels, labelsDose, colors, linestyles, thicknes
     plt.legend(handles=labels_legend, loc='upper left')
     plt.show()
 
-def plot_pi_vs_exposure_time(exp_models: typing.List[mc.ExposureModel], 
-                            labels,
-                            colors,
-                            linestyles,
-                            points: int = 20, time_in_minutes: bool = False, normalize_y_axis: bool = False) -> None:
+def plot_vD_vs_exposure_time(exp_models: typing.List[mc.ExposureModel], labels, colors, linestyles, points: int = 20, time_in_minutes: bool = False, normalize_y_axis: bool = False) -> None:
     
-    TIMESTEP = 0.001
+    TIMESTEP = 0.01
 
     concentration_models = [model.concentration_model for model in exp_models]
     exposed_models = [model.exposed for model in exp_models]
     
-    pis: typing.List[typing.List[float]] = [[] for _ in exp_models]
+    vDs: typing.List[typing.List[float]] = [[] for _ in exp_models]
     
     presence_intervals = [model.short_range.presence[0].boundaries() for model in exp_models]
     start, final = presence_intervals[0]
@@ -177,20 +173,20 @@ def plot_pi_vs_exposure_time(exp_models: typing.List[mc.ExposureModel],
         ) for cm, exposed, em in zip(concentration_models, exposed_models, exp_models)]
 
         for i, m in enumerate(current_models):
-            pis[i].append(np.mean(m.build_model(SAMPLE_SIZE).infection_probability() / 100))
+            vDs[i].append(np.mean(m.build_model(SAMPLE_SIZE).deposited_exposure()))
 
     times = np.linspace(0, 60, points)
-    for i, pi in enumerate(pis):
-        plt.plot(times, pi, color=colors[i], label=labels[i])
+    for i, vD in enumerate(vDs):
+        plt.plot(times, vD, color=colors[i], label=labels[i])
 
     # plt.xlim((0, 60))
-    if normalize_y_axis:
-        plt.ylim((0, 1))
+    #if normalize_y_axis:
+    #    plt.ylim((0, 1))
         
     for m in exp_models:
-        print(np.mean(m.build_model(SAMPLE_SIZE).infection_probability() / 100))
+        print(np.mean(m.build_model(SAMPLE_SIZE).deposited_exposure()))
 
-    plt.xlabel(f'Exposure time (m)', fontsize=12)
-    plt.ylabel('Probability of infection\n$P(\,\mathtt{I}\,)$', fontsize=12)
+    plt.xlabel(f'Duration of close-proximity encounter\n(min)', fontsize=12)
+    plt.ylabel('Mean cumulative dose\n(infectious virus)', fontsize=12)
     plt.legend()
     plt.show()