From 656eddaf8f11e34a791d814e4fdd973b00b9bf88 Mon Sep 17 00:00:00 2001 From: TimoDiepers Date: Wed, 17 Jul 2024 18:29:37 +0200 Subject: [PATCH] update dynamic_lcia docstring --- bw_timex/timex_lca.py | 13 +++++++------ 1 file changed, 7 insertions(+), 6 deletions(-) diff --git a/bw_timex/timex_lca.py b/bw_timex/timex_lca.py index 6e85dfb..32be4c1 100644 --- a/bw_timex/timex_lca.py +++ b/bw_timex/timex_lca.py @@ -335,19 +335,20 @@ def dynamic_lcia( ) -> pd.DataFrame: """ Calculates dynamic LCIA with the `DynamicCharacterization` class using the dynamic inventory and dynamic - characterization functions. + characterization functions. Dynamic characterization is handled by the separate package + `dynamic_characterization` (https://dynamic-characterization.readthedocs.io/en/latest/). Dynamic characterization functions in the form of a dictionary {biosphere_flow_database_id: characterization_function} can be given by the user. - If none are given, a set of default dynamic characterization functions based on IPCC AR6 are provided. - These are mapped to the biosphere3 flows of the chosen static climate change impact category. - If there is no characterization function for a biosphere flow, it will be ignored. + If none are given, a set of default dynamic characterization functions based on IPCC AR6 are provided from + `dynamic_characterization` package. These are mapped to the biosphere3 flows of the chosen static climate + change impact category. If there is no characterization function for a biosphere flow, it will be ignored. Two dynamic climate change metrics are provided: "GWP" and "radiative_forcing". The time horizon for the impact assessment can be set with the `time_horizon` parameter, defaulting to 100 years. The `fixed_time_horizon` parameter determines whether the emission time horizon for all emissions is calculated from the functional unit (`fixed_time_horizon=True`) or from the time of the emission (`fixed_time_horizon=False`). - The former is the implementation of the Levasseur approach(https://doi.org/10.1021/es9030003), while the latter is how conventional LCA is done. + The former is the implementation of the Levasseur approach (see https://doi.org/10.1021/es9030003), while the latter is how conventional LCA is done. Parameters ---------- @@ -372,7 +373,7 @@ def dynamic_lcia( See also -------- - bw_timex.dynamic_characterization.DynamicCharacterization: Class that characterizes the dynamic inventory. + dynamic_charaterization: Package handling the dynamic characterization: https://dynamic-characterization.readthedocs.io/en/latest/ """ if not hasattr(self, "dynamic_inventory"):