CASE STUDY
2023 Data Science
VEHICLE CO2 EMISSIONS ANALYSIS
Data Analysis Python Environmental Engineering Statistics
Challenge
Understanding the complex relationships between vehicle characteristics and CO2 emissions requires analysis of large datasets with many correlated variables.
Approach
Applied statistical analysis and data visualization techniques in Python to identify key correlations between vehicle parameters and emissions output.
Outcome
Identified significant predictors of vehicle emissions and developed data-driven policy recommendations for emissions reduction.
Duration
3 months
Tools
Python Pandas NumPy Matplotlib Scikit-learn
Overview
This project analyzed vehicle CO2 emissions data to understand the relationships between vehicle characteristics (engine size, fuel type, weight) and their environmental impact.
Methodology
- Statistical analysis of emissions datasets
- Correlation studies between vehicle parameters
- Visualization of emissions trends
- Policy recommendation development
Key Findings
The analysis revealed significant correlations between:
- Engine displacement and emissions
- Vehicle weight and fuel efficiency
- Manufacturing year and emissions standards compliance
Tools Used
- Python (Pandas, NumPy, Matplotlib)
- Statistical analysis libraries
- Data visualization frameworks