pudl.extract.epamats#

Retrieve data from EPA MATS hourly zipped CSVs.

The MATS data structure is similar to EPA CEMS but with different pollutants. Each year’s data is stored in a zip file (e.g., epamats-2015.zip) containing quarterly CSV files (e.g., epamats-2015q1.csv). The data tracks hourly Hg (mercury), HCl (hydrochloric acid), and HF (hydrogen fluoride) emissions from coal-fired power plants.

Similar to CEMS, the plant_id_epa field (Facility ID in raw data) needs to be mapped to plant_id_eia during transformation using the core_epa__assn_eia_epacamd crosswalk.

Attributes#

`logger`
`RENAME_DICT`	Mapping from raw EPA MATS column names to PUDL column names.
`DTYPE_DICT`	Data types for EPA MATS columns.

Classes#

`EpaMatsPartition`	Represents a MATS partition identifying a unique quarterly resource file.
`EpaMatsDatastore`	Helper class to extract MATS resources from datastore.

Functions#

raw_epamats__hourly_emissions(context) → pandas.DataFrame

Extract raw EPA MATS hourly emissions data and return as a pandas DataFrame.

Module Contents#

pudl.extract.epamats.logger[source]#

pudl.extract.epamats.RENAME_DICT[source]#

Mapping from raw EPA MATS column names to PUDL column names.

Type:: Dict

pudl.extract.epamats.DTYPE_DICT[source]#

Data types for EPA MATS columns.

Type:: Dict

class pudl.extract.epamats.EpaMatsPartition(/, **data: Any)[source]#

Bases: pudl.extract.epacems.EpaCemsPartition

Represents a MATS partition identifying a unique quarterly resource file.

Inherits the year_quarter validation, year/quarter properties, and datastore filters from EpaCemsPartition; only the CSV filename differs.

get_quarterly_file() → pathlib.Path[source]#: Return the name of the CSV file within the zip that holds quarterly data.

class pudl.extract.epamats.EpaMatsDatastore(datastore: pudl.workspace.datastore.Datastore)[source]#

Bases: pudl.extract.epacems.EpaCemsDatastore

Helper class to extract MATS resources from datastore.

MATS resources are identified by a year and a quarter. Each year’s data is in a zip file containing 4 quarterly CSV files. Inherits the zip-reading and column-renaming logic from EpaCemsDatastore; only the dataset name, column mapping, and dtypes differ.

dataset_name: str = 'epamats'[source]#: Name of the dataset used to fetch zipfile resources from the datastore.

rename_dict: dict[str, str][source]#: Mapping from raw column names to PUDL column names.

dtype_dict[source]#: Data types for the raw columns.

pudl.extract.epamats.raw_epamats__hourly_emissions(context) → pandas.DataFrame[source]#: Extract raw EPA MATS hourly emissions data and return as a pandas DataFrame.