"""
Landuse LCA Generator
=====================
This module contains the LandUseLCAGenerator class, which is responsible for generating land-use footprints for climate change.
"""
from goblin_lite.impact_categories.climate_change import ClimateChangeLandUse
from goblin_lite.resource_manager.database_manager import DataManager
[docs]
class LandUseLCAGenerator:
"""
Manages the calculation of climate change footprints associated with various land use types.
Employs the ClimateChangeLandUse class for specific calculations.
Attributes
----------
data_manager_class : DataManager
An instance of the DataManager class for database interactions.
ef_country : str
Country code for emission factors.
calibration_year : int
Base year for model calibration.
target_year : int
Year of analysis.
landuse_data : pandas.DataFrame
Dataframe containing land use information.
transition_matrix : pandas.DataFrame
Dataframe representing transitions between land use types.
forest_data : pandas.DataFrame
Dataframe containing forest-related data.
DATABASE_PATH : str, optional
Path to the external database, if None, default internal database used.
AR_VALUE : str
IPCC Assessment Report version (e.g., 'AR4', 'AR5') for impact calculations.
Methods
-------
generate_landuse_footprint()
Calculates climate change footprints for various land use types.
Notes
-----
The wetlands category includes emissions from extraction and use of horticultural peat.
"""
def __init__(self, ef_country, calibration_year, target_year, landuse_data, transition_matrix, forest_data, DATABASE_PATH, AR_VALUE):
self.data_manager_class = DataManager(DATABASE_PATH)
self.ef_country = ef_country
self.calibration_year = calibration_year
self.target_year = target_year
self.landuse_data = landuse_data
self.transition_matrix = transition_matrix
self.forest_data = forest_data
self.AR_VALUE = AR_VALUE