Closed lindnemi closed 3 weeks ago
lindnemi
commented
4 weeks ago PyPSA does not model some sectors (but most) -> Assume homogeneous decrease across all sectors.
GB no longer part of EU -> Assume GB CO2 reduction follows EU27 trajectory
-> These simplifications justify the use of the common factor from the config file
lindnemi
commented
4 weeks ago
import pandas as pd
emissions = pd.Series({
# Net CO2 excl LULUCF, EEA statistics
1990: 3873588.21,
2019: 2913818.31,
2020: 2638542.76,# (-31.88%)
2021: 2814421.65,
"2020avg": (2913818.31 + 2638542.76 + 2814421.65)/3,
# # Projection WAM (with additional measures)
"2025WAM": 2508490.18184,
# 2030: 2000851.69936,
# Projection WEM (with existing measures)
2025: 2614272.70617,
2030: 2203144.0135,
2035: 1946301.91572575,
2040: 1750560.91992927,
2045: 1670385.17642877,
2050: 1621713.75770867,
})
(emissions / emissions[1990]).round(3)1990 1.000
2019 0.752
2020 0.681
2021 0.727
2020avg 0.720
2025WAM 0.648
2025 0.675
2030 0.569
2035 0.502
2040 0.452
2045 0.431
2050 0.419
dtype: float64
The CO2 emission targets for the EU have a considerable influence on the modeling outcome, especially in earlier years. The current pathway is based on an ad-hoc interpolation of official EU targets. However, these targets are for CO2 equivalent emissions, whereas PyPSA models only CO2 emissions.
Hence, we have to recompute the targets, based on date from the European Environmental Agency (EEA).
For the research i used the sources compiled by Climate Action Tracker: https://climateactiontracker.org/countries/eu/sources/
Most importantly: European Environment Agency. (2023a). Annual European Union greenhouse gas inventory 1990–2021 and inventory report 2023 - CRF Table. https://unfccc.int/documents/627830 - Table10s6 - CO2 emissions without net CO2 from LULUCF
European Environment Agency. (2023e). Member States’ greenhouse gas (GHG) emission projections 2023. https://www.eea.europa.eu/en/datahub/datahubitem-view/4b8d94a4-aed7-4e67-a54c-0623a50f48e8 - WAM Scenario (With Additional Measures)
For 2020:
Rely on the historical values from 2023a. Since 2020 was an atypical year due to Covid, take the mean of 2019-2021.
For 2025: Zielerreichungsszenarioen: Rely on projected values from 2023e. Optimistic scenario (WAM). CurrentPolicies Szenarien: Rely on projected values from 2023e. Existing policies scenario (WEM).
For 2030: Zielerreichung: Assume that all greenhouse gas shrink simultaneously (i.e., their ratio remains constant) -> use 55% Current Policies: Rely on projected values from 2023e. Optimistic scenario (WAM) or Existing policies scenario (WEM).