diff --git a/doc/source/whatsnew/v0.24.0.rst b/doc/source/whatsnew/v0.24.0.rst
index 44c467795d1ed..7dac2d03514a6 100644
--- a/doc/source/whatsnew/v0.24.0.rst
+++ b/doc/source/whatsnew/v0.24.0.rst
@@ -1372,6 +1372,7 @@ Reshaping
 - Bug in :func:`pandas.concat` when concatenating a multicolumn DataFrame with tz-aware data against a DataFrame with a different number of columns (:issue:`22796`)
 - Bug in :func:`merge_asof` where confusing error message raised when attempting to merge with missing values (:issue:`23189`)
 - Bug in :meth:`DataFrame.nsmallest` and :meth:`DataFrame.nlargest` for dataframes that have a :class:`MultiIndex` for columns (:issue:`23033`).
+- Bug in :meth:`DataFrame.append` with a :class:`Series` with a dateutil timezone would raise a ``TypeError`` (:issue:`23682`)
 
 .. _whatsnew_0240.bug_fixes.sparse:
 
diff --git a/pandas/_libs/lib.pyx b/pandas/_libs/lib.pyx
index cfc60256e97a3..0088a698f49e0 100644
--- a/pandas/_libs/lib.pyx
+++ b/pandas/_libs/lib.pyx
@@ -48,8 +48,7 @@ cdef extern from "src/parse_helper.h":
     int floatify(object, float64_t *result, int *maybe_int) except -1
 
 cimport util
-from util cimport (is_nan,
-                   UINT8_MAX, UINT64_MAX, INT64_MAX, INT64_MIN)
+from util cimport is_nan, UINT64_MAX, INT64_MAX, INT64_MIN
 
 from tslib import array_to_datetime
 from tslibs.nattype cimport NPY_NAT
@@ -1642,20 +1641,22 @@ def is_datetime_with_singletz_array(values: ndarray) -> bool:
 
     if n == 0:
         return False
-
+    # Get a reference timezone to compare with the rest of the tzs in the array
     for i in range(n):
         base_val = values[i]
         if base_val is not NaT:
             base_tz = get_timezone(getattr(base_val, 'tzinfo', None))
-
-            for j in range(i, n):
-                val = values[j]
-                if val is not NaT:
-                    tz = getattr(val, 'tzinfo', None)
-                    if not tz_compare(base_tz, tz):
-                        return False
             break
 
+    for j in range(i, n):
+        # Compare val's timezone with the reference timezone
+        # NaT can coexist with tz-aware datetimes, so skip if encountered
+        val = values[j]
+        if val is not NaT:
+            tz = getattr(val, 'tzinfo', None)
+            if not tz_compare(base_tz, tz):
+                return False
+
     return True
 
 
@@ -2045,7 +2046,7 @@ def maybe_convert_objects(ndarray[object] objects, bint try_float=0,
 
     # we try to coerce datetime w/tz but must all have the same tz
     if seen.datetimetz_:
-        if len({getattr(val, 'tzinfo', None) for val in objects}) == 1:
+        if is_datetime_with_singletz_array(objects):
             from pandas import DatetimeIndex
             return DatetimeIndex(objects)
         seen.object_ = 1
diff --git a/pandas/tests/reshape/test_concat.py b/pandas/tests/reshape/test_concat.py
index c7fba47a8f27c..07b00cef2669e 100644
--- a/pandas/tests/reshape/test_concat.py
+++ b/pandas/tests/reshape/test_concat.py
@@ -1010,6 +1010,21 @@ def test_append_missing_column_proper_upcast(self, sort):
         assert appended['A'].dtype == 'f8'
         assert appended['B'].dtype == 'O'
 
+    def test_append_empty_frame_to_series_with_dateutil_tz(self):
+        # GH 23682
+        date = Timestamp('2018-10-24 07:30:00', tz=dateutil.tz.tzutc())
+        s = Series({'date': date, 'a': 1.0, 'b': 2.0})
+        df = DataFrame(columns=['c', 'd'])
+        result = df.append(s, ignore_index=True)
+        expected = DataFrame([[np.nan, np.nan, 1., 2., date]],
+                             columns=['c', 'd', 'a', 'b', 'date'])
+        # These columns get cast to object after append
+        object_cols = ['c', 'd', 'date']
+        expected.loc[:, object_cols] = expected.loc[:, object_cols].astype(
+            object
+        )
+        assert_frame_equal(result, expected)
+
 
 class TestConcatenate(ConcatenateBase):