Source code for message_ix_models.model.emissions

import logging
from typing import Optional

import pandas as pd
from iam_units import convert_gwp
from message_ix import Scenario, make_df

from message_ix_models import ScenarioInfo

log = logging.getLogger(__name__)


[docs]def add_tax_emission( scen: Scenario, price: float, conversion_factor: Optional[float] = None, drate_parameter="drate", ) -> None: """Add a global CO₂ price to `scen`. A carbon price is implemented on node=“World” by populating the :ref:`MESSAGEix parameter <message-ix:section_parameter_emissions>` ``tax_emission``, starting from the first model year and covering the entire model horizon. The tax has an annual growth rate equal to the discount rate. The other dimensions of ``tax_emission`` are filled with type_emission=“TCE” and type_tec=“all”. Parameters ---------- scen : :class:`message_ix.Scenario` price : float Price in the first model year, in USD / tonne CO₂. conversion_factor : float, optional Factor for converting `price` into the model's internal emissions units, currently USD / tonne carbon. Optional: a default value is retrieved from :mod:`iam_units`. drate_parameter : str; one of "drate" or "interestrate" Name of the parameter to use for the growth rate of the carbon price. """ years = ScenarioInfo(scen).Y filters = dict(year=years) # Default: since the mass of the species is in the denominator, take the inverse conversion_factor = conversion_factor or 1.0 / convert_gwp( "AR5GWP100", "1 t", "CO2", "C" ) # Duration of periods dp = scen.par("duration_period", filters=filters).set_index("year")["value"] # Retrieve the discount rate if drate_parameter == "interestrate": # MESSAGE parameter with "year" dimension r = scen.par(drate_parameter, filters=filters).set_index("year")["value"] else: # MACRO parameter with "node" dimension drates = scen.par(drate_parameter).value.unique() if len(drates) > 1: log.warning(f"Using the first of multiple discount rates: drate={drates}") r = pd.Series([drates[0]] * len(years), index=pd.Index(years, name="year")) # Compute cumulative growth versus the first period r_cumulative = (r + 1).pow(dp.shift(-1)).cumprod().shift(1, fill_value=1.0) # Assemble the parameter data name = "tax_emission" data = make_df( name, value=(price * conversion_factor * r_cumulative), type_year=r_cumulative.index, node="World", type_emission="TCE", type_tec="all", unit="USD/tC", ) with scen.transact("Added carbon price"): scen.add_par(name, data)