diff --git a/journal/logbook.md b/journal/logbook.md
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@@ -118,4 +118,24 @@ For this aim, I perfomed the following step:
 - Loaded the dataset from the Website Sentinelles 
 - Converted weekly data to dates and grouped it by epidemiological year (from September 1 to August 31)
 - Calculated the total incidence per epidemiological year
+ 
+Besides as part of *Mission 4*, I created a computational document by choosing **Subject 1: CO₂ concentration in the atmosphere since 1958**.
+
+In this project, I analyzed atmospheric CO₂ concentration data from the Mauna Loa Observatory, known as the **Keeling Curve**, covering the period from 1958 to the present.
+
+The analysis included:
+
+- Importing the dataset from the Scripps CO₂ Program
+
+- Visualizing the raw CO₂ time series to show seasonal oscillations and long-term trends
+
+- Performing seasonal decomposition to isolate and analyze monthly variations
+- 
+- Building a linear regression model to estimate the long-term trend
+-
+- Forecasting CO₂ levels up to the year 2025
+
+- Computing yearly statistics (minimum, maximum, mean CO₂ per year)
+
+All steps were carried out using Python 3 in a Jupyter notebook.