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aeromaps.models.impacts.emissions.non_co2_emissions

non_co2_emissions

========================= Module to compute non-CO2 emissions from various aircraft types and energy origins.

NOxEmissionIndex 

NOxEmissionIndex(name='nox_emission_index', *args, **kwargs)

Bases: AeroMAPSModel

Class to compute NOx emission index.

Parameters:

Name Type Description Default
name str

Name of the model instance ('nox_emission_index' by default).

 'nox_emission_index'

Attributes:

Name Type Description
pathways_manager EnergyCarrierManager

EnergyCarrierManager instance to manage generic energy pathways and their data.
input_names dict

Dictionary of input variable names populated at model initialisation before MDA chain creation.
output_names dict

Dictionary of output variable names populated at model initialisation before MDA chain creation.
Warnings
  • Detailed i/o documentation is not yet provided for models defined wityh generic .yaml files?
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def __init__(self, name="nox_emission_index", *args, **kwargs):
    super().__init__(name=name, model_type="custom", *args, **kwargs)
    self.pathways_manager = None

custom_setup 

custom_setup()

Dynamically add all pathways variables to input_names and function outputs to output_names. Specific function for custom AeroMAPSModel instances.

Parameters:

Name Type Description Default
None
required

Returns:

Type Description
None
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def custom_setup(self):
    """
    Dynamically add all pathways variables to input_names and function outputs to output_names.
    Specific function for custom AeroMAPSModel instances.

    Parameters
    ----------
    None

    Returns
    -------
    None
    """

    # TODO caution aircraft types not generic there
    self.input_names = {
        "emission_index_nox_dropin_fuel_evolution": 0.0,
        "emission_index_nox_hydrogen_evolution": 0.0,
    }
    self.output_names = {}

    for aircraft_type in self.pathways_manager.get_all_types("aircraft_type"):
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            if self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            ):
                self.output_names.update(
                    {
                        f"{aircraft_type}_{energy_origin}_mean_emission_index_nox": pd.Series(
                            [0.0]
                        ),
                    }
                )

        for pathway in self.pathways_manager.get(aircraft_type=aircraft_type):
            self.input_names.update(
                {
                    f"{pathway.name}_emission_index_nox": 0.0,
                    f"{pathway.name}_massic_share_{aircraft_type}_{pathway.energy_origin}": pd.Series(
                        [0.0]
                    ),
                }
            )

compute 

compute(input_data)

NOx emission index calculation using simple method.

Parameters:

Name Type Description Default
input_data

Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

 required

Returns:

Type Description
output_data

Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def compute(self, input_data) -> dict:
    """
    NOx emission index calculation using simple method.

    Parameters
    ----------
    input_data
        Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

    Returns
    -------
    output_data
        Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.

    """

    output_data = {}

    for aircraft_type in self.pathways_manager.get_all_types("aircraft_type"):
        cagr_aircraft = input_data.get(f"emission_index_nox_{aircraft_type}_evolution", 0.0)
        growth_series = pd.Series(
            np.concatenate(
                (
                    np.ones(self.prospection_start_year - self.historic_start_year),
                    (1 + cagr_aircraft)
                    ** np.arange(0, self.end_year - self.prospection_start_year + 1),
                )
            ),
            index=range(self.historic_start_year, self.end_year + 1),
        )

        # intialize the mean values for the aircraft type
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            # Get the pathways for this aircraft type and energy origin
            pathways = self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            )
            if pathways:
                origin_mean_emission_index_nox = get_default_series(
                    self.historic_start_year, self.end_year
                )
                origin_cumulative_share = get_default_series(
                    self.historic_start_year, self.end_year
                )
                for pathway in pathways:
                    origin_share = input_data[
                        f"{pathway.name}_massic_share_{aircraft_type}_{energy_origin}"
                    ]
                    origin_cumulative_share = (
                        origin_cumulative_share + origin_share.fillna(0) / 100
                    )
                    pathway_emission_index_nox = input_data[
                        f"{pathway.name}_emission_index_nox"
                    ]

                    origin_mean_emission_index_nox += (
                        pathway_emission_index_nox * origin_share
                    ).fillna(0) / 100

                origin_valid_years = origin_cumulative_share.replace(0, np.nan)

                output_data[f"{aircraft_type}_{energy_origin}_mean_emission_index_nox"] = (
                    origin_mean_emission_index_nox * origin_valid_years * growth_series
                )

    self._store_outputs(output_data)

    return output_data

NOxEmissionIndexComplex 

NOxEmissionIndexComplex(name='nox_emission_index_complex', *args, **kwargs)

Bases: AeroMAPSModel

Class to compute NOx emission index using fleet renewal models.

Parameters:

Name Type Description Default
name str

Name of the model instance ('nox_emission_index_complex' by default).

 'nox_emission_index_complex'

Attributes:

Name Type Description
fleet_model FleetModel(AeroMAPSModel)

AeroMAPSModel instance to provide fleet renewal data for NOx emission index calculation.
pathways_manager EnergyCarrierManager

EnergyCarrierManager instance to manage generic energy pathways and their data.
input_names dict

Dictionary of input variable names populated at model initialisation before MDA chain creation.
output_names dict

Dictionary of output variable names populated at model initialisation before MDA chain creation.
Warnings
  • Detailed i/o documentation is not yet provided for models defined wityh generic .yaml files?
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def __init__(self, name="nox_emission_index_complex", *args, **kwargs):
    super().__init__(name=name, model_type="custom", *args, **kwargs)
    self.fleet_model = None
    self.pathways_manager = None

custom_setup 

custom_setup()

Dynamically add all pathways variables to input_names and function outputs to output_names. Specific function for custom AeroMAPSModel instances.

Parameters:

Name Type Description Default
None
required

Returns:

Type Description
None
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def custom_setup(self):
    """
    Dynamically add all pathways variables to input_names and function outputs to output_names.
    Specific function for custom AeroMAPSModel instances.

    Parameters
    ----------
    None

    Returns
    -------
    None
    """
    # TODO caution aircraft types not generic there
    self.input_names = {
        "ask_long_range_dropin_fuel": pd.Series([0.0]),
        "ask_medium_range_dropin_fuel": pd.Series([0.0]),
        "ask_short_range_dropin_fuel": pd.Series([0.0]),
        "ask_long_range_hydrogen": pd.Series([0.0]),
        "ask_medium_range_hydrogen": pd.Series([0.0]),
        "ask_short_range_hydrogen": pd.Series([0.0]),
        "ask_long_range_electric": pd.Series([0.0]),
        "ask_medium_range_electric": pd.Series([0.0]),
        "ask_short_range_electric": pd.Series([0.0]),
    }

    self.output_names = {}

    aircraft_types = ["dropin_fuel", "hydrogen", "electric"]

    for aircraft_type in aircraft_types:
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            if self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            ):
                self.output_names.update(
                    {
                        f"{aircraft_type}_{energy_origin}_mean_emission_index_nox": pd.Series(
                            [0.0]
                        ),
                    }
                )

        for pathway in self.pathways_manager.get(aircraft_type=aircraft_type):
            self.input_names.update(
                {
                    f"{pathway.name}_emission_index_nox": 0.0,
                    f"{pathway.name}_massic_share_{aircraft_type}_{pathway.energy_origin}": pd.Series(
                        [0.0]
                    ),
                }
            )

compute 

compute(input_data)

NOx emission index calculation using fleet renewal models.

Parameters:

Name Type Description Default
input_data

Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

 required

Returns:

Type Description
output_data

Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def compute(
    self,
    input_data,
) -> dict:
    """
    NOx emission index calculation using fleet renewal models.

    Parameters
    ----------
    input_data
        Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

    Returns
    -------
    output_data
        Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.
    """
    output_data = {}
    # Getting fleet model data

    aircraft_types = ["dropin_fuel", "hydrogen", "electric"]

    for aircraft_type in aircraft_types:
        emission_index_nox_short_range = self.fleet_model.df[
            f"Short Range:emission_index_nox:{aircraft_type}"
        ]
        emission_index_nox_medium_range = self.fleet_model.df[
            f"Medium Range:emission_index_nox:{aircraft_type}"
        ]
        emission_index_nox_long_range = self.fleet_model.df[
            f"Long Range:emission_index_nox:{aircraft_type}"
        ]

        ask_short_range = input_data.get(
            f"ask_short_range_{aircraft_type}",
            get_default_series(self.historic_start_year, self.end_year),
        )
        ask_medium_range = input_data.get(
            f"ask_medium_range_{aircraft_type}",
            get_default_series(self.historic_start_year, self.end_year),
        )
        ask_long_range = input_data.get(
            f"ask_long_range_{aircraft_type}",
            get_default_series(self.historic_start_year, self.end_year),
        )

        emission_index_aircraft_type = (
            (
                emission_index_nox_short_range.loc[self.historic_start_year : self.end_year]
                * ask_short_range.loc[self.historic_start_year : self.end_year].fillna(0)
            )
            + (
                emission_index_nox_medium_range.loc[self.historic_start_year : self.end_year]
                * ask_medium_range.loc[self.historic_start_year : self.end_year].fillna(0)
            )
            + (
                emission_index_nox_long_range.loc[self.historic_start_year : self.end_year]
                * ask_long_range.loc[self.historic_start_year : self.end_year].fillna(0)
            )
        ) / (
            ask_short_range.loc[self.historic_start_year : self.end_year].fillna(0)
            + ask_medium_range.loc[self.historic_start_year : self.end_year].fillna(0)
            + ask_long_range.loc[self.historic_start_year : self.end_year].fillna(0)
        )

        relative_emission_index_aircraft_type = (
            emission_index_aircraft_type
            / emission_index_aircraft_type.loc[self.prospection_start_year - 1]
        )

        # intialize the mean values for the aircraft type
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            # Get the pathways for this aircraft type and energy origin
            pathways = self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            )
            if pathways:
                origin_mean_emission_index_nox = get_default_series(
                    self.historic_start_year, self.end_year
                )
                origin_cumulative_share = get_default_series(
                    self.historic_start_year, self.end_year
                )
                for pathway in pathways:
                    origin_share = input_data[
                        f"{pathway.name}_massic_share_{aircraft_type}_{energy_origin}"
                    ]
                    origin_cumulative_share = (
                        origin_cumulative_share + origin_share.fillna(0) / 100
                    )
                    pathway_emission_index_nox = input_data[
                        f"{pathway.name}_emission_index_nox"
                    ]

                    origin_mean_emission_index_nox += (
                        pathway_emission_index_nox * origin_share
                    ).fillna(0) / 100

                origin_valid_years = origin_cumulative_share.replace(0, np.nan)

                output_data[f"{aircraft_type}_{energy_origin}_mean_emission_index_nox"] = (
                    origin_mean_emission_index_nox
                    * origin_valid_years
                    * relative_emission_index_aircraft_type
                )

    # print(output_data)
    self._store_outputs(output_data)

    return output_data

SootEmissionIndex 

SootEmissionIndex(name='soot_emission_index', *args, **kwargs)

Bases: AeroMAPSModel

Class to compute Soot emission index.

Parameters:

Name Type Description Default
name str

Name of the model instance ('soot_emission_index' by default).

 'soot_emission_index'

Attributes:

Name Type Description
pathways_manager EnergyCarrierManager

EnergyCarrierManager instance to manage generic energy pathways and their data.
input_names dict

Dictionary of input variable names populated at model initialisation before MDA chain creation.
output_names dict

Dictionary of output variable names populated at model initialisation before MDA chain creation.
Warnings
  • Detailed i/o documentation is not yet provided for models defined wityh generic .yaml files?
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def __init__(self, name="soot_emission_index", *args, **kwargs):
    super().__init__(name=name, model_type="custom", *args, **kwargs)
    self.pathways_manager = None

custom_setup 

custom_setup()

Dynamically add all pathways variables to input_names and function outputs to output_names. Specific function for custom AeroMAPSModel instances.

Parameters:

Name Type Description Default
None
required

Returns:

Type Description
None
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def custom_setup(self):
    """
    Dynamically add all pathways variables to input_names and function outputs to output_names.
    Specific function for custom AeroMAPSModel instances.

    Parameters
    ----------
    None

    Returns
    -------
    None
    """
    # TODO caution aircraft types not generic there
    self.input_names = {"emission_index_soot_dropin_fuel_evolution": 0.0}

    self.output_names = {}

    for aircraft_type in self.pathways_manager.get_all_types("aircraft_type"):
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            if self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            ):
                self.output_names.update(
                    {
                        f"{aircraft_type}_{energy_origin}_mean_emission_index_soot": pd.Series(
                            [0.0]
                        ),
                    }
                )

        for pathway in self.pathways_manager.get(aircraft_type=aircraft_type):
            self.input_names.update(
                {
                    f"{pathway.name}_emission_index_soot": 0.0,
                    f"{pathway.name}_massic_share_{aircraft_type}_{pathway.energy_origin}": pd.Series(
                        [0.0]
                    ),
                }
            )

compute 

compute(input_data)

Execute Soot emission index calculation using simple method.

Parameters:

Name Type Description Default
input_data

Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

 required

Returns:

Type Description
output_data

Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def compute(self, input_data) -> dict:
    """
    Execute Soot emission index calculation using simple method.

    Parameters
    ----------
    input_data
        Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

    Returns
    -------
    output_data
        Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.

    """

    output_data = {}

    for aircraft_type in self.pathways_manager.get_all_types("aircraft_type"):
        cagr_aircraft = input_data.get(f"emission_index_soot_{aircraft_type}_evolution", 0.0)
        growth_series = pd.Series(
            np.concatenate(
                (
                    np.ones(self.prospection_start_year - self.historic_start_year),
                    (1 + cagr_aircraft)
                    ** np.arange(0, self.end_year - self.prospection_start_year + 1),
                )
            ),
            index=range(self.historic_start_year, self.end_year + 1),
        )

        # initialise the mean values for the aircraft type
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            # Get the pathways for this aircraft type and energy origin
            pathways = self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            )
            if pathways:
                origin_mean_emission_index_soot = get_default_series(
                    self.historic_start_year, self.end_year
                )
                origin_cumulative_share = get_default_series(
                    self.historic_start_year, self.end_year
                )
                for pathway in pathways:
                    origin_share = input_data[
                        f"{pathway.name}_massic_share_{aircraft_type}_{energy_origin}"
                    ]
                    origin_cumulative_share = (
                        origin_cumulative_share + origin_share.fillna(0) / 100
                    )
                    pathway_emission_index_soot = input_data[
                        f"{pathway.name}_emission_index_soot"
                    ]

                    origin_mean_emission_index_soot += (
                        pathway_emission_index_soot * origin_share
                    ).fillna(0) / 100

                origin_valid_years = origin_cumulative_share.replace(0, np.nan)

                output_data[f"{aircraft_type}_{energy_origin}_mean_emission_index_soot"] = (
                    origin_mean_emission_index_soot * origin_valid_years * growth_series
                )

    self._store_outputs(output_data)

    return output_data

SootEmissionIndexComplex 

SootEmissionIndexComplex(name='soot_emission_index_complex', *args, **kwargs)

Bases: AeroMAPSModel

Class to compute Soot emission index using fleet renewal models.

Parameters:

Name Type Description Default
name str

Name of the model instance ('soot_emission_index_complex' by default).

 'soot_emission_index_complex'

Attributes:

Name Type Description
fleet_model FleetModel(AeroMAPSModel)

AeroMAPSModel instance to provide fleet renewal data for Soot emission index calculation.
pathways_manager EnergyCarrierManager

EnergyCarrierManager instance to manage generic energy pathways and their data.
input_names dict

Dictionary of input variable names populated at model initialisation before MDA chain creation.
output_names dict

Dictionary of output variable names populated at model initialisation before MDA chain creation.
Warnings
  • Detailed i/o documentation is not yet provided for models defined wityh generic .yaml files?
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def __init__(self, name="soot_emission_index_complex", *args, **kwargs):
    super().__init__(name=name, model_type="custom", *args, **kwargs)
    self.fleet_model = None
    self.pathways_manager = None

custom_setup 

custom_setup()

Dynamically add all pathways variables to input_names and function outputs to output_names. Specific function for custom AeroMAPSModel instances.

Parameters:

Name Type Description Default
None
required

Returns:

Type Description
None
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def custom_setup(self):
    """
    Dynamically add all pathways variables to input_names and function outputs to output_names.
    Specific function for custom AeroMAPSModel instances.

    Parameters
    ----------
    None

    Returns
    -------
    None
    """
    # TODO caution aircraft types not generic there
    self.input_names = {
        "ask_long_range_dropin_fuel": pd.Series([0.0]),
        "ask_medium_range_dropin_fuel": pd.Series([0.0]),
        "ask_short_range_dropin_fuel": pd.Series([0.0]),
        "ask_long_range_hydrogen": pd.Series([0.0]),
        "ask_medium_range_hydrogen": pd.Series([0.0]),
        "ask_short_range_hydrogen": pd.Series([0.0]),
        "ask_long_range_electric": pd.Series([0.0]),
        "ask_medium_range_electric": pd.Series([0.0]),
        "ask_short_range_electric": pd.Series([0.0]),
    }

    self.output_names = {}

    aircraft_types = ["dropin_fuel", "hydrogen", "electric"]
    for aircraft_type in aircraft_types:
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            if self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            ):
                self.output_names.update(
                    {
                        f"{aircraft_type}_{energy_origin}_mean_emission_index_soot": pd.Series(
                            [0.0]
                        ),
                    }
                )

        for pathway in self.pathways_manager.get(aircraft_type=aircraft_type):
            self.input_names.update(
                {
                    f"{pathway.name}_emission_index_soot": 0.0,
                    f"{pathway.name}_massic_share_{aircraft_type}_{pathway.energy_origin}": pd.Series(
                        [0.0]
                    ),
                }
            )

compute 

compute(input_data)

Soot emission index calculation using fleet renewal models.

Parameters:

Name Type Description Default
input_data

Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

 required

Returns:

Type Description
output_data

Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def compute(
    self,
    input_data,
) -> dict:
    """Soot emission index calculation using fleet renewal models.

    Parameters
    ----------
    input_data
        Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

    Returns
    -------
    output_data
        Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.

    """
    output_data = {}
    # Getting fleet model data

    aircraft_types = ["dropin_fuel", "hydrogen", "electric"]

    for aircraft_type in aircraft_types:
        emission_index_soot_short_range = self.fleet_model.df[
            f"Short Range:emission_index_soot:{aircraft_type}"
        ]
        emission_index_soot_medium_range = self.fleet_model.df[
            f"Medium Range:emission_index_soot:{aircraft_type}"
        ]
        emission_index_soot_long_range = self.fleet_model.df[
            f"Long Range:emission_index_soot:{aircraft_type}"
        ]

        ask_short_range = input_data[f"ask_short_range_{aircraft_type}"]
        ask_medium_range = input_data[f"ask_medium_range_{aircraft_type}"]
        ask_long_range = input_data[f"ask_long_range_{aircraft_type}"]

        emission_index_aircraft_type = (
            (
                emission_index_soot_short_range.loc[self.historic_start_year : self.end_year]
                * ask_short_range.loc[self.historic_start_year : self.end_year].fillna(0)
            )
            + (
                emission_index_soot_medium_range.loc[self.historic_start_year : self.end_year]
                * ask_medium_range.loc[self.historic_start_year : self.end_year].fillna(0)
            )
            + (
                emission_index_soot_long_range.loc[self.historic_start_year : self.end_year]
                * ask_long_range.loc[self.historic_start_year : self.end_year].fillna(0)
            )
        ) / (
            ask_short_range.loc[self.historic_start_year : self.end_year].fillna(0)
            + ask_medium_range.loc[self.historic_start_year : self.end_year].fillna(0)
            + ask_long_range.loc[self.historic_start_year : self.end_year].fillna(0)
        )

        relative_emission_index_aircraft_type = (
            emission_index_aircraft_type
            / emission_index_aircraft_type.loc[self.prospection_start_year - 1]
        )

        # intialize the mean values for the aircraft type
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            # Get the pathways for this aircraft type and energy origin
            pathways = self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            )
            if pathways:
                origin_mean_emission_index_soot = get_default_series(
                    self.historic_start_year, self.end_year
                )
                origin_cumulative_share = get_default_series(
                    self.historic_start_year, self.end_year
                )
                for pathway in pathways:
                    origin_share = input_data[
                        f"{pathway.name}_massic_share_{aircraft_type}_{energy_origin}"
                    ]
                    origin_cumulative_share = (
                        origin_cumulative_share + origin_share.fillna(0) / 100
                    )
                    pathway_emission_index_soot = input_data[
                        f"{pathway.name}_emission_index_soot"
                    ]

                    origin_mean_emission_index_soot += (
                        pathway_emission_index_soot * origin_share
                    ).fillna(0) / 100

                origin_valid_years = origin_cumulative_share.replace(0, np.nan)

                output_data[f"{aircraft_type}_{energy_origin}_mean_emission_index_soot"] = (
                    origin_mean_emission_index_soot
                    * origin_valid_years
                    * relative_emission_index_aircraft_type
                )
    self._store_outputs(output_data)

    return output_data

H2OEmissionIndex 

H2OEmissionIndex(name='h2o_emission_index', *args, **kwargs)

Bases: AeroMAPSModel

Class to compute H2O emission index.

Parameters:

Name Type Description Default
name str

Name of the model instance ('h2o_emission_index' by default).

 'h2o_emission_index'

Attributes:

Name Type Description
pathways_manager EnergyCarrierManager

EnergyCarrierManager instance to manage generic energy pathways and their data.
input_names dict

Dictionary of input variable names populated at model initialisation before MDA chain creation.
output_names dict

Dictionary of output variable names populated at model initialisation before MDA chain creation.
Warnings
  • Detailed i/o documentation is not yet provided for models defined wityh generic .yaml files?
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def __init__(self, name="h2o_emission_index", *args, **kwargs):
    super().__init__(name=name, model_type="custom", *args, **kwargs)
    self.pathways_manager = None

custom_setup 

custom_setup()

Dynamically add all pathways variables to input_names and function outputs to output_names. Specific function for custom AeroMAPSModel instances.

Parameters:

Name Type Description Default
None
required

Returns:

Type Description
None
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def custom_setup(self):
    """
    Dynamically add all pathways variables to input_names and function outputs to output_names.
    Specific function for custom AeroMAPSModel instances.

    Parameters
    ----------
    None

    Returns
    -------
    None
    """
    self.input_names = {}
    self.output_names = {}

    for aircraft_type in self.pathways_manager.get_all_types("aircraft_type"):
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            if self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            ):
                self.output_names.update(
                    {
                        f"{aircraft_type}_{energy_origin}_mean_emission_index_h2o": pd.Series(
                            [0.0]
                        ),
                    }
                )

        for pathway in self.pathways_manager.get(aircraft_type=aircraft_type):
            self.input_names.update(
                {
                    f"{pathway.name}_emission_index_h2o": 0.0,
                    f"{pathway.name}_massic_share_{aircraft_type}_{pathway.energy_origin}": pd.Series(
                        [0.0]
                    ),
                }
            )

compute 

compute(input_data)

Average H20 emission index calculation

Parameters:

Name Type Description Default
input_data

Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

 required

Returns:

Type Description
output_data

Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def compute(self, input_data) -> dict:
    """Average H20 emission index calculation

    Parameters
    ----------
    input_data
        Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

    Returns
    -------
    output_data
        Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.

    """

    output_data = {}

    for aircraft_type in self.pathways_manager.get_all_types("aircraft_type"):
        # initialise the mean values for the aircraft type
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            # Get the pathways for this aircraft type and energy origin
            pathways = self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            )
            if pathways:
                origin_mean_emission_index_h2o = get_default_series(
                    self.historic_start_year, self.end_year
                )
                origin_cumulative_share = get_default_series(
                    self.historic_start_year, self.end_year
                )
                for pathway in pathways:
                    origin_share = input_data[
                        f"{pathway.name}_massic_share_{aircraft_type}_{energy_origin}"
                    ]
                    origin_cumulative_share = (
                        origin_cumulative_share + origin_share.fillna(0) / 100
                    )
                    pathway_emission_index_h2o = input_data[
                        f"{pathway.name}_emission_index_h2o"
                    ]

                    origin_mean_emission_index_h2o += (
                        pathway_emission_index_h2o * origin_share
                    ).fillna(0) / 100

                origin_valid_years = origin_cumulative_share.replace(0, np.nan)

                output_data[f"{aircraft_type}_{energy_origin}_mean_emission_index_h2o"] = (
                    origin_mean_emission_index_h2o * origin_valid_years
                )

    self._store_outputs(output_data)

    return output_data

SulfurEmissionIndex 

SulfurEmissionIndex(name='sulfur_emission_index', *args, **kwargs)

Bases: AeroMAPSModel

Class to compute Sulfur emission index.

Parameters:

Name Type Description Default
name str

Name of the model instance ('sulfur_emission_index' by default).

 'sulfur_emission_index'

Attributes:

Name Type Description
pathways_manager EnergyCarrierManager

EnergyCarrierManager instance to manage generic energy pathways and their data.
input_names dict

Dictionary of input variable names populated at model initialisation before MDA chain creation.
output_names dict

Dictionary of output variable names populated at model initialisation before MDA chain creation.
Warnings
  • Detailed i/o documentation is not yet provided for models defined wityh generic .yaml files?
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def __init__(self, name="sulfur_emission_index", *args, **kwargs):
    super().__init__(name=name, model_type="custom", *args, **kwargs)
    self.pathways_manager = None

custom_setup 

custom_setup()

Dynamically add all pathways variables to input_names and function outputs to output_names. Specific function for custom AeroMAPSModel instances.

Parameters:

Name Type Description Default
None
required

Returns:

Type Description
None
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def custom_setup(self):
    """
    Dynamically add all pathways variables to input_names and function outputs to output_names.
    Specific function for custom AeroMAPSModel instances.

    Parameters
    ----------
    None

    Returns
    -------
    None
    """
    self.input_names = {}
    self.output_names = {}

    for aircraft_type in self.pathways_manager.get_all_types("aircraft_type"):
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            if self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            ):
                self.output_names.update(
                    {
                        f"{aircraft_type}_{energy_origin}_mean_emission_index_sulfur": pd.Series(
                            [0.0]
                        ),
                    }
                )

        for pathway in self.pathways_manager.get(aircraft_type=aircraft_type):
            self.input_names.update(
                {
                    f"{pathway.name}_emission_index_sulfur": 0.0,
                    f"{pathway.name}_massic_share_{aircraft_type}_{pathway.energy_origin}": pd.Series(
                        [0.0]
                    ),
                }
            )

compute 

compute(input_data)

Average H20 emission index calculation

Parameters:

Name Type Description Default
input_data

Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

 required

Returns:

Type Description
output_data

Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def compute(self, input_data) -> dict:
    """Average H20 emission index calculation

    Parameters
    ----------
    input_data
        Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

    Returns
    -------
    output_data
        Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.

    """

    output_data = {}

    for aircraft_type in self.pathways_manager.get_all_types("aircraft_type"):
        # initialise the mean values for the aircraft type
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            # Get the pathways for this aircraft type and energy origin
            pathways = self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            )
            if pathways:
                origin_mean_emission_index_sulfur = get_default_series(
                    self.historic_start_year, self.end_year
                )
                origin_cumulative_share = get_default_series(
                    self.historic_start_year, self.end_year
                )
                for pathway in pathways:
                    origin_share = input_data[
                        f"{pathway.name}_massic_share_{aircraft_type}_{energy_origin}"
                    ]
                    origin_cumulative_share = (
                        origin_cumulative_share + origin_share.fillna(0) / 100
                    )
                    pathway_emission_index_sulfur = input_data[
                        f"{pathway.name}_emission_index_sulfur"
                    ]

                    origin_mean_emission_index_sulfur += (
                        pathway_emission_index_sulfur * origin_share
                    ).fillna(0) / 100

                origin_valid_years = origin_cumulative_share.replace(0, np.nan)

                output_data[f"{aircraft_type}_{energy_origin}_mean_emission_index_sulfur"] = (
                    origin_mean_emission_index_sulfur * origin_valid_years
                )

    self._store_outputs(output_data)

    return output_data

NonCO2Emissions 

NonCO2Emissions(name='non_co2_emissions', *args, **kwargs)

Bases: AeroMAPSModel

Class to compute non-CO2 emissions.

Parameters:

Name Type Description Default
name str

Name of the model instance ('non_co2_emissions' by default).

 'non_co2_emissions'

Attributes:

Name Type Description
pathways_manager EnergyCarrierManager

EnergyCarrierManager instance to manage generic energy pathways and their data.
input_names dict

Dictionary of input variable names populated at model initialisation before MDA chain creation.
output_names dict

Dictionary of output variable names populated at model initialisation before MDA chain creation.
Warnings
  • Detailed i/o documentation is not yet provided for models defined wityh generic .yaml files?
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def __init__(self, name="non_co2_emissions", *args, **kwargs):
    super().__init__(name=name, model_type="custom", *args, **kwargs)
    self.climate_historical_data = None
    self.pathways_manager = None

custom_setup 

custom_setup()

Dynamically add all pathways variables to input_names and function outputs to output_names. Specific function for custom AeroMAPSModel instances.

Parameters:

Name Type Description Default
None
required

Returns:

Type Description
None
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def custom_setup(self):
    """
    Dynamically add all pathways variables to input_names and function outputs to output_names.
    Specific function for custom AeroMAPSModel instances.

    Parameters
    ----------
    None

    Returns
    -------
    None
    """
    aircraft_type = ["dropin_fuel", "hydrogen"]

    for aircraft_type in aircraft_type:
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            if self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            ):
                self.input_names.update(
                    {
                        f"{aircraft_type}_{energy_origin}_mean_emission_index_nox": pd.Series(
                            [0.0]
                        ),
                        f"{aircraft_type}_{energy_origin}_mean_emission_index_soot": pd.Series(
                            [0.0]
                        ),
                        f"{aircraft_type}_{energy_origin}_mean_emission_index_h2o": pd.Series(
                            [0.0]
                        ),
                        f"{aircraft_type}_{energy_origin}_mean_emission_index_sulfur": pd.Series(
                            [0.0]
                        ),
                        f"{aircraft_type}_{energy_origin}_mean_lhv": pd.Series([0.0]),
                        f"{aircraft_type}_{energy_origin}_energy_consumption": pd.Series([0.0]),
                    }
                )

    self.output_names.update(
        {
            "soot_emissions": pd.Series([0.0]),
            "h2o_emissions": pd.Series([0.0]),
            "nox_emissions": pd.Series([0.0]),
            "sulfur_emissions": pd.Series([0.0]),
        }
    )

compute 

compute(input_data)

Non-CO2 emissions calculation.

Parameters:

Name Type Description Default
input_data

Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

 required

Returns:

Type Description
output_data

Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.
Source code in aeromaps/models/impacts/emissions/non_co2_emissions.py 
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def compute(self, input_data) -> dict:
    """Non-CO2 emissions calculation.

    Parameters
    ----------
    input_data
        Dictionary containing all input data required for the computation, completed at model instantiation with information from yaml files and outputs of other models.

    Returns
    -------
    output_data
        Dictionary containing all output data resulting from the computation. Contains outputs defined during model instantiation.
    """

    soot_emissions = get_default_series(self.climate_historic_start_year, self.end_year)
    h2o_emissions = get_default_series(self.climate_historic_start_year, self.end_year)
    nox_emissions = get_default_series(self.climate_historic_start_year, self.end_year)
    sulfur_emissions = get_default_series(self.climate_historic_start_year, self.end_year)

    ## Initialization
    historical_nox_emissions_for_temperature = self.climate_historical_data[:, 2]
    historical_h2o_emissions_for_temperature = self.climate_historical_data[:, 3]
    historical_soot_emissions_for_temperature = self.climate_historical_data[:, 4]
    historical_sulfur_emissions_for_temperature = self.climate_historical_data[:, 5]

    soot_emissions.loc[self.climate_historic_start_year : self.historic_start_year] = (
        historical_soot_emissions_for_temperature
    )
    h2o_emissions.loc[self.climate_historic_start_year : self.historic_start_year] = (
        historical_h2o_emissions_for_temperature
    )
    nox_emissions.loc[self.climate_historic_start_year : self.historic_start_year] = (
        historical_nox_emissions_for_temperature
    )
    sulfur_emissions.loc[self.climate_historic_start_year : self.historic_start_year] = (
        historical_sulfur_emissions_for_temperature
    )

    for aircraft_type in ["dropin_fuel", "hydrogen"]:
        for energy_origin in self.pathways_manager.get_all_types("energy_origin"):
            if self.pathways_manager.get(
                aircraft_type=aircraft_type, energy_origin=energy_origin
            ):
                mass_consumption = (
                    input_data[f"{aircraft_type}_{energy_origin}_energy_consumption"]
                    / input_data[f"{aircraft_type}_{energy_origin}_mean_lhv"]
                    / 10**9  # convert MJ to Mt
                )
                soot_emissions.loc[self.historic_start_year + 1 : self.end_year] += (
                    input_data[f"{aircraft_type}_{energy_origin}_mean_emission_index_soot"]
                    * mass_consumption
                ).fillna(0.0)
                h2o_emissions.loc[self.historic_start_year + 1 : self.end_year] += (
                    input_data[f"{aircraft_type}_{energy_origin}_mean_emission_index_h2o"]
                    * mass_consumption
                ).fillna(0.0)
                nox_emissions.loc[self.historic_start_year + 1 : self.end_year] += (
                    input_data[f"{aircraft_type}_{energy_origin}_mean_emission_index_nox"]
                    * mass_consumption
                ).fillna(0.0)
                sulfur_emissions.loc[self.historic_start_year + 1 : self.end_year] += (
                    input_data[f"{aircraft_type}_{energy_origin}_mean_emission_index_sulfur"]
                    * mass_consumption
                ).fillna(0.0)

    output_data = {
        "soot_emissions": soot_emissions,
        "h2o_emissions": h2o_emissions,
        "nox_emissions": nox_emissions,
        "sulfur_emissions": sulfur_emissions,
    }

    self.df_climate.loc[:, "soot_emissions"] = soot_emissions
    self.df_climate.loc[:, "h2o_emissions"] = h2o_emissions
    self.df_climate.loc[:, "nox_emissions"] = nox_emissions
    self.df_climate.loc[:, "sulfur_emissions"] = sulfur_emissions

    return output_data