BUG: to_datetime with multiple timezones does not coerce if invalid string in input
#### Code Sample

```python
import pandas as pd

se = pd.Series(["2019-01-01 03:00:00-0500", "abc", "2019-01-01 03:00:00-0100"])
assert type(pd.to_datetime(se, errors="coerce").iloc[0]) == str
```

Note that the type of the first element (`"2019-01-01 03:00:00-0500"`) is `str` *after* the "conversion".

```python
import pandas as pd

se1 = pd.Series(["2019-01-01 03:00:00-0500", "abc", "2019-01-01 03:00:00-0100"])
pd.to_datetime(se1, errors="coerce")
# 0    2019-01-01 03:00:00-0500
# 1                         abc
# 2    2019-01-01 03:00:00-0100
# dtype: object

se2 = pd.Series(["2019-01-01 03:00:00-0500", "2019-01-01 03:00:00-0100"]) 
pd.to_datetime(se2, errors="coerce")
# 0    2019-01-01 03:00:00-05:00
# 1    2019-01-01 03:00:00-01:00
# dtype: object
```

#### Problem description

If the input to `to_datetime` contains both dates with multiple timezones and invalid strings *no conversion* (the input strings will be returned) will happen when running with `errors="coerce"`. This is a problem as the (documented) expected output type is a date-like type. Note, that if the incorrect string is not present the dates will convert but the overall dtype will be object.

In previous versions (< 0.24) the function would convert the dates into timezone unaware timestamps which is a far more predictable behavior (the output can easily be converted into the desired timezone).

#### Expected Output

Output in 0.23

```python
import pandas as pd

se1 = pd.Series(["2019-01-01 03:00:00-0500", "abc", "2019-01-01 03:00:00-0100"])
pd.to_datetime(se1, errors="coerce")
# 0   2019-01-01 08:00:00
# 1                   NaT
# 2   2019-01-01 04:00:00
# dtype: datetime64[ns]

se2 = pd.Series(["2019-01-01 03:00:00-0500", "2019-01-01 03:00:00-0100"]) 
pd.to_datetime(se2, errors="coerce")
# 0   2019-01-01 08:00:00
# 1   2019-01-01 04:00:00
# dtype: datetime64[ns]
```

#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.4.final.0
python-bits: 64
OS: Darwin
OS-release: 18.6.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8

pandas: 0.24.2
pytest: 3.7.3
pip: 19.1.1
setuptools: 39.1.0
Cython: 0.29.7
numpy: 1.16.4
scipy: 1.0.0
pyarrow: 0.13.0
xarray: None
IPython: 6.2.1
sphinx: None
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.5
blosc: None
bottleneck: 1.2.1
tables: 3.5.2
numexpr: 2.6.9
feather: None
matplotlib: 2.2.0
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml.etree: 4.2.4
bs4: None
html5lib: 1.0.1
sqlalchemy: 1.3.0
pymysql: None
psycopg2: 2.7.4 (dt dec pq3 ext lo64)
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: None
gcsfs: None
</details>
