diff --git a/tests/conftest.py b/tests/conftest.py
index 92cf76a..f33e098 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,3 +1,4 @@
 from .fixtures.nonunitary_db_fixture import nonunitary_db
 from .fixtures.substitution_db_fixture import substitution_db
 from .fixtures.vehicle_db_fixture import vehicle_db
+from .fixtures.dynamic_biomatrix_db_fixture import dynamic_biomatrix_db
diff --git a/tests/fixtures/dynamic_biomatrix_db_fixture.py b/tests/fixtures/dynamic_biomatrix_db_fixture.py
new file mode 100644
index 0000000..0218c71
--- /dev/null
+++ b/tests/fixtures/dynamic_biomatrix_db_fixture.py
@@ -0,0 +1,120 @@
+import pytest
+import bw2data as bd
+import numpy as np
+
+from bw2data.tests import bw2test
+from bw_temporalis import TemporalDistribution
+
+
+@pytest.fixture
+@bw2test
+def dynamic_biomatrix_db():
+    bd.projects.set_current("__test_dynamic_biomatrix__")
+    bd.Database("bio").write(
+        {
+            ("bio", "CO2"): {
+                "type": "emission",
+                "name": "carbon dioxide",
+            },
+        },
+    )
+
+    bd.Database("db_2020").write(
+        {
+            ("db_2020", "C"): {
+                "name": "node c",
+                "location": "somewhere",
+                "reference product": "C",
+                "exchanges": [
+                    {
+                        "amount": 1,
+                        "type": "production",
+                        "input": ("db_2020", "C"),
+                    },
+                    {
+                        "amount": 1.5,
+                        "type": "biosphere",
+                        "input": ("bio", "CO2"),
+                    },
+                ],
+            },
+        }
+    )
+
+    bd.Database("foreground").write(
+        {
+            ("foreground", "A"): {
+                "name": "node a",
+                "location": "somewhere",
+                "reference product": "A",
+                "exchanges": [
+                    {
+                        "amount": 1,
+                        "type": "production",
+                        "input": ("foreground", "A"),
+                    },
+                    {
+                        "amount": 8,
+                        "type": "technosphere",
+                        "input": ("foreground", "B"),
+                        "temporal_distribution": TemporalDistribution(
+                            date=np.array([4], dtype="timedelta64[Y]"),
+                            amount=np.array([1]),
+                        ),
+                    },
+                    {
+                        "amount": 8,
+                        "type": "technosphere",
+                        "input": (
+                            "foreground",
+                            "B_1",
+                        ),  # occuring at exactly the same time as B
+                        "temporal_distribution": TemporalDistribution(
+                            date=np.array([4], dtype="timedelta64[Y]"),
+                            amount=np.array([1]),
+                        ),
+                    },
+                ],
+            },
+            ("foreground", "B"): {
+                "name": "node b",
+                "location": "somewhere",
+                "reference product": "B",
+                "exchanges": [
+                    {
+                        "amount": 1,
+                        "type": "production",
+                        "input": ("foreground", "B"),
+                    },
+                    {
+                        "amount": 2,
+                        "type": "technosphere",
+                        "input": ("db_2020", "C"),
+                    },
+                ],
+            },
+            ("foreground", "B_1"): {  # identical to B
+                "name": "node b_1",
+                "location": "somewhere",
+                "reference product": "B_1",
+                "exchanges": [
+                    {
+                        "amount": 1,
+                        "type": "production",
+                        "input": ("foreground", "B_1"),
+                    },
+                    {
+                        "amount": 2,
+                        "type": "technosphere",
+                        "input": ("db_2020", "C"),
+                    },
+                ],
+            },
+        }
+    )
+
+    bd.Method(("GWP", "example")).write(
+        [
+            (("bio", "CO2"), 1),
+        ]
+    )
diff --git a/tests/test_dynamic_biomatrix_construction.py b/tests/test_dynamic_biomatrix_construction.py
new file mode 100644
index 0000000..847498b
--- /dev/null
+++ b/tests/test_dynamic_biomatrix_construction.py
@@ -0,0 +1,46 @@
+from datetime import datetime
+import numpy as np
+import pandas as pd
+import bw2data as bd
+import pytest
+
+from bw_timex import TimexLCA
+
+# make sure the test db is loaded
+def test_dynamic_biomatrix_fixture(dynamic_biomatrix_db):
+    assert len(bd.databases) == 3
+
+
+@pytest.mark.usefixtures("dynamic_biomatrix_db")
+class TestClass_dynamic_biomatrix:
+
+    @pytest.fixture(autouse=True)
+    def setup_method(self):
+        self.node_a = bd.get_node(database="foreground", code="A")
+
+        database_date_dict = { 
+            "db_2020": datetime.strptime("2020", "%Y"),
+            "foreground": "dynamic",
+        }
+
+        self.tlca = TimexLCA(
+            demand={self.node_a: 1},
+            method=("GWP", "example"),
+            database_date_dict=database_date_dict,
+        )
+
+        self.tlca.build_timeline()
+        self.tlca.lci(expand_technosphere=True, build_dynamic_biosphere=True)
+        self.tlca.static_lcia()
+
+    def test_identical_time_mapped_producers_exist_in_timeline(self):
+        
+        duplicates = self.tlca.timeline["time_mapped_producer"].duplicated().any()
+        assert duplicates, f"No duplicates found in column {"time_mapped_producer"}"
+      
+    def test_dynamic_biomatrix_for_multiple_identical_time_mapped_producers_in_timeline(self):
+
+        expected_dynamic_biomatrix_as_array = np.array([[0. , 0. , 0. , 0. , 0. , 0. , 0. , 1.5]]) #1.5 CO2 is only added once for the time_mapped producer, depsite it occuring twice in the timeline! Before #78, it was added twice , resulting in 3.0                        
+
+        assert np.array_equal(self.tlca.dynamic_biomatrix.toarray(), expected_dynamic_biomatrix_as_array),  "Arrays are not equal"
+