Forecast Emission Reduction Pathways
Model emission reduction pathways to net-zero — forecast future emissions under different intervention scenarios and identify optimal decarbonization strategies.
Forecast Emission Reduction Pathways
python • Step 3
Model emission reduction pathways to net-zero — forecast future emissions under different intervention scenarios and identify optimal decarbonization strategies.
Learning Objectives
- →Forecast baseline emissions trajectory
- →Model reduction scenarios (renewable energy, efficiency, offsets)
- →Calculate net-zero target year under each scenario
Dataset
View on KaggleUNFCCC GHG inventory 1990-2017 — country_or_area, year, value, category.
*bleep* Load the dataset in the browser terminal:
from pyodide.http import open_url
import pandas as pd
df = pd.read_csv(open_url("/datasets/greenhouse_gas_inventory_data_data.csv"))
print(df.shape)
print(df.columns.tolist()) Running locally? The file inside the Kaggle download is already named greenhouse_gas_inventory_data_data.csv — drop it into the notebook's working directory and the code above runs unchanged (swap open_url(...) for "greenhouse_gas_inventory_data_data.csv").
Dataset Columns
country_or_areayearvaluecategory- Write your solution in the Try It Yourself editor below — matplotlib/seaborn figures and pandas tables render inline.
- Stuck? Expand a section and click ↑ Send to editor to stack its snippet into the editor, notebook-style.
- Hit ▶ Run (or ⌘↵) — once your output matches the expected result, the step is marked solved.
- Use ↺ Reset to restore the starter code at any time.
Try It Yourself
Aggressive (7%/yr): Net-zero ~ Moderate (4%/yr): Net-zero ~ Conservative (2%/yr): Net-zero ~
Cross-verse learning
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