DOC: DatetimeTZDtype astype behavior with Series.astype
#### Code Sample

```python
import pandas as pd

typ = pd.DatetimeTZDtype(tz = 'EST')
s = pd.Series([pd.Timestamp('2020-01-01 15:00')])
print(s.astype(typ))

```

```
0   2020-01-01 10:00:00-05:00
dtype: datetime64[ns, EST] 
```

#### Problem description
Hello,

I noticed a strange behavior using `DatetimeTZDtype` , when specifying a timezone as argument. When the type is applied to a tz-naive datetime column using `astype`, it will first localize the timestamps to `UTC` and then convert the timezone, whereas I was expecting it would just localize my tz-naive timestamps. 

My situation is I am getting data from a database and need to convert the columns to the desired types. Using  `DatetimeTZDtype` and `astype` is a nice way to convert and localize in just one line, but I encountered this unexpected behavior (though it is easy to work around that).

I tracked the issue to these lines [https://github.com/pandas-dev/pandas/blob/master/pandas/core/internals/blocks.py#L2090](url)

Thanks
#### Expected Output
```
0   2020-01-01 15:00:00-05:00
dtype: datetime64[ns, EST]
```

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

<details>

INSTALLED VERSIONS
------------------
commit           : None
python           : 3.7.6.final.0
python-bits      : 64
OS               : Windows
OS-release       : 10
machine          : AMD64
processor        : Intel64 Family 6 Model 158 Stepping 13, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : None.None
pandas           : 1.0.3
numpy            : 1.18.2
pytz             : 2019.3
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 45.2.0
Cython           : 0.29.16
pytest           : 5.4.1
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : 0.9.3
psycopg2         : None
jinja2           : 2.11.1
IPython          : 7.13.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fastparquet      : None
gcsfs            : None
lxml.etree       : None
matplotlib       : 3.2.1
numexpr          : 2.7.1
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 0.16.0
pytables         : None
pytest           : 5.4.1
pyxlsb           : None
s3fs             : None
scipy            : 1.4.1
sqlalchemy       : 1.3.15
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
xlsxwriter       : None
numba            : 0.48.0


[paste the output of ``pd.show_versions()`` here leaving a blank line after the details tag]

</details>
