diff --git a/caimira/apps/calculator/defaults.py b/caimira/apps/calculator/defaults.py
index a9e9d0f9..22b157aa 100644
--- a/caimira/apps/calculator/defaults.py
+++ b/caimira/apps/calculator/defaults.py
@@ -19,6 +19,7 @@ DEFAULTS = {
     'calculator_version': NO_DEFAULT,
     'ceiling_height': 0.,
     'conditional_probability_plot': False,
+    'conditional_probability_viral_loads': False,
     'exposed_coffee_break_option': 'coffee_break_0',
     'exposed_coffee_duration': 5,
     'exposed_finish': '17:30',
diff --git a/caimira/apps/calculator/model_generator.py b/caimira/apps/calculator/model_generator.py
index ae473ea5..664eef2b 100644
--- a/caimira/apps/calculator/model_generator.py
+++ b/caimira/apps/calculator/model_generator.py
@@ -35,6 +35,7 @@ class FormData:
     precise_activity: dict
     ceiling_height: float
     conditional_probability_plot: bool
+    conditional_probability_viral_loads: bool
     exposed_coffee_break_option: str
     exposed_coffee_duration: int
     exposed_finish: minutes_since_midnight
@@ -802,6 +803,7 @@ def baseline_raw_form_data() -> typing.Dict[str, typing.Union[str, float]]:
         'air_supply': '',
         'ceiling_height': '',
         'conditional_probability_plot': '0',
+        'conditional_probability_viral_loads': '0',
         'exposed_coffee_break_option': 'coffee_break_4',
         'exposed_coffee_duration': '10',
         'exposed_finish': '18:00',
diff --git a/caimira/apps/calculator/report_generator.py b/caimira/apps/calculator/report_generator.py
index 8297e132..6429729c 100644
--- a/caimira/apps/calculator/report_generator.py
+++ b/caimira/apps/calculator/report_generator.py
@@ -328,6 +328,18 @@ def non_zero_percentage(percentage: int) -> str:
         return "99.9%"
     else:
         return "{:0.1f}%".format(percentage)
+    
+
+def manufacture_viral_load_scenarios_percentiles(model: mc.ExposureModel) -> typing.Dict[str, mc.ExposureModel]:
+    viral_load = model.concentration_model.infected.virus.viral_load_in_sputum
+    scenarios = {}
+    for percentil in (0.01, 0.05, 0.25, 0.5, 0.75, 0.95, 0.99):
+        vl = np.quantile(viral_load, percentil)
+        specific_vl_scenario = dataclass_utils.nested_replace(model, 
+            {'concentration_model.infected.virus.viral_load_in_sputum': vl}
+        )
+        scenarios[round(np.log10(vl))] = np.mean(specific_vl_scenario.infection_probability())
+    return scenarios
 
 
 def manufacture_alternative_scenarios(form: FormData) -> typing.Dict[str, mc.ExposureModel]:
@@ -477,6 +489,7 @@ class ReportGenerator:
         context.update(report_data)
 
         alternative_scenarios = manufacture_alternative_scenarios(form)
+        context['alternative_viral_load'] = manufacture_viral_load_scenarios_percentiles(model) if form.conditional_probability_viral_loads else None
         context['alternative_scenarios'] = comparison_report(
             form, report_data, alternative_scenarios, scenario_sample_times, executor_factory=executor_factory,
         )