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aeromaps.models.air_transport.air_traffic.total_aircraft_distance

total_aircraft_distance

Module for computing total aircraft distance flown.

TotalAircraftDistance 

TotalAircraftDistance(name='total_aircraft_distance', *args, **kwargs)

Bases: AeroMAPSModel

Class to compute total aircraft distance flown for all commercial air transport.

Parameters:

Name Type Description Default
name str

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

 'total_aircraft_distance'
Source code in aeromaps/models/air_transport/air_traffic/total_aircraft_distance.py 
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def __init__(self, name="total_aircraft_distance", *args, **kwargs):
    super().__init__(name=name, *args, **kwargs)
    self.climate_historical_data = None

compute 

compute(rtk, ask, ask_dropin_fuel, ask_hydrogen, ask_electric, total_aircraft_distance_init)

Total aircraft distance calculation.

Parameters:

Name Type Description Default
rtk Series

Number of Revenue Tonne Kilometer (RTK) for freight air transport [RTK].

 required
ask Series

Number of (ASK) for all commercial air transport [ASK].

 required
ask_dropin_fuel Series

Number of (ASK) for drop-in fuel aircraft [ASK].

 required
ask_hydrogen Series

Number of (ASK) for hydrogen aircraft [ASK].

 required
ask_electric Series

Number of (ASK) for electric aircraft [ASK].

 required
total_aircraft_distance_init Series

Historical total distance travelled by aircraft over 2000-2019 [km].

 required

Returns:

Type Description
total_aircraft_distance

Total distance flown by all aircraft [km].
total_aircraft_distance_dropin_fuel

Total aircraft distance flown by drop-in fuel aircraft [km].
total_aircraft_distance_hydrogen

Total aircraft distance flown by hydrogen aircraft [km].
total_aircraft_distance_electric

Total aircraft distance flown by electric aircraft [km].
Source code in aeromaps/models/air_transport/air_traffic/total_aircraft_distance.py 
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def compute(
    self,
    rtk: pd.Series,
    ask: pd.Series,
    ask_dropin_fuel: pd.Series,
    ask_hydrogen: pd.Series,
    ask_electric: pd.Series,
    total_aircraft_distance_init: pd.Series,
) -> Tuple[pd.Series, pd.Series, pd.Series, pd.Series]:
    """
    Total aircraft distance calculation.

    Parameters
    ----------
    rtk
        Number of Revenue Tonne Kilometer (RTK) for freight air transport [RTK].
    ask
        Number of (ASK) for all commercial air transport [ASK].
    ask_dropin_fuel
        Number of (ASK) for drop-in fuel aircraft [ASK].
    ask_hydrogen
        Number of (ASK) for hydrogen aircraft [ASK].
    ask_electric
        Number of (ASK) for electric aircraft [ASK].
    total_aircraft_distance_init
        Historical total distance travelled by aircraft over 2000-2019 [km].

    Returns
    -------
    total_aircraft_distance
        Total distance flown by all aircraft [km].
    total_aircraft_distance_dropin_fuel
        Total aircraft distance flown by drop-in fuel aircraft [km].
    total_aircraft_distance_hydrogen
        Total aircraft distance flown by hydrogen aircraft [km].
    total_aircraft_distance_electric
        Total aircraft distance flown by electric aircraft [km].
    """

    historical_distance_for_temperature = self.climate_historical_data[:, 6]

    for k in range(self.climate_historic_start_year, self.historic_start_year):
        self.df_climate.loc[k, "total_aircraft_distance"] = historical_distance_for_temperature[
            k - self.climate_historic_start_year
        ]

    for k in range(self.historic_start_year, self.prospection_start_year):
        self.df_climate.loc[k, "total_aircraft_distance"] = total_aircraft_distance_init.loc[k]

    # Assumption: 1 RTK = 10 ASK
    for k in range(self.prospection_start_year, self.end_year + 1):
        self.df_climate.loc[k, "total_aircraft_distance"] = (
            (ask.loc[k] + 10 * rtk.loc[k])
            / (
                ask.loc[self.prospection_start_year - 1]
                + 10 * rtk.loc[self.prospection_start_year - 1]
            )
            * self.df_climate.loc[self.prospection_start_year - 1, "total_aircraft_distance"]
        )

    total_aircraft_distance = self.df_climate["total_aircraft_distance"]

    # Assumption: distribution proportional to ASK
    total_aircraft_distance_dropin_fuel = total_aircraft_distance * ask_dropin_fuel / ask
    total_aircraft_distance_hydrogen = total_aircraft_distance * ask_hydrogen / ask
    total_aircraft_distance_electric = total_aircraft_distance * ask_electric / ask
    self.df.loc[:, "total_aircraft_distance_dropin_fuel"] = total_aircraft_distance_dropin_fuel
    self.df.loc[:, "total_aircraft_distance_hydrogen"] = total_aircraft_distance_hydrogen
    self.df.loc[:, "total_aircraft_distance_electric"] = total_aircraft_distance_electric

    return (
        total_aircraft_distance,
        total_aircraft_distance_dropin_fuel,
        total_aircraft_distance_hydrogen,
        total_aircraft_distance_electric,
    )