BUG: pd.concat inconsistent behaviour with empty and tz-aware Series

```python
df = pd.concat([
    pd.Series(dtype=float), 
    pd.Series(index=[pd.Timestamp('2020-01-01T00:00:00+00:00')], data=0, dtype=float)], 
axis=1)
>>> df
                            0    1
2020-01-01 00:00:00+00:00 NaN  0.0
```

```python
df = pd.concat([
    pd.Series(index=[pd.Timestamp('2020-01-01T00:00:00')], data=0, dtype=float)], 
    pd.Series(dtype=float),    
axis=1)
>>> df
              0   1
2020-01-01  0.0 NaN
```

```python
df = pd.concat([
    pd.Series(index=[pd.Timestamp('2020-01-01T00:00:00+00:00')], data=0, dtype=float), 
    pd.Series(dtype=float)], 
axis=1)

Traceback (most recent call last):
  File "<input>", line 1, in <module>
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\reshape\concat.py", line 281, in concat
    sort=sort,
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\reshape\concat.py", line 452, in __init__
    self.new_axes = self._get_new_axes()
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\reshape\concat.py", line 517, in _get_new_axes
    for i in range(ndim)
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\reshape\concat.py", line 517, in <listcomp>
    for i in range(ndim)
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\reshape\concat.py", line 523, in _get_comb_axis
    self.objs, axis=data_axis, intersect=self.intersect, sort=self.sort
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\indexes\api.py", line 90, in get_objs_combined_axis
    return _get_combined_index(obs_idxes, intersect=intersect, sort=sort)
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\indexes\api.py", line 138, in _get_combined_index
    index = union_indexes(indexes, sort=sort)
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\indexes\api.py", line 202, in union_indexes
    return result.union_many(indexes[1:])
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\indexes\datetimes.py", line 363, in union_many
    this, other = this._maybe_utc_convert(other)
  File "C:\Users\user\AppData\Local\Programs\Python\Python37\lib\site-packages\pandas\core\indexes\datetimelike.py", line 832, in _maybe_utc_convert
    raise TypeError("Cannot join tz-naive with tz-aware DatetimeIndex")
TypeError: Cannot join tz-naive with tz-aware DatetimeIndex
```

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.4.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None
pandas           : 1.0.3
numpy            : 1.16.4
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 46.1.3
Cython           : 0.29.14
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.3.4
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : 2.10.3
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : 4.3.4
matplotlib       : 3.1.1
numexpr          : 2.7.0
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pytables         : None
pytest           : None
pyxlsb           : None
s3fs             : None
scipy            : 1.3.0
sqlalchemy       : 1.3.16
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : 1.2.0
xlwt             : None
xlsxwriter       : None
numba            : 0.45.1

</details>
