OmotoshoTaiwo/Exhaust-Emissions-Analysis-Ibadan-Nigeria-
Domaine:
environment and energyCréateur:
Omo
Hôte:
A data-driven environmental study on CO, CO₂, HC, O₂, and NOx emissions from generators in Ibadan using Python, PCA, regression models, and GIS tools.
# Exhaust-Emissions-Analysis-Ibadan-Nigeria-
A data-driven environmental study on CO, CO₂, HC, O₂, and NOx emissions from generators in Ibadan using Python, PCA, regression models, and GIS tools.
# 🌍 Emissions Analysis of Industrial Generators in Ibadan, Nigeria
## 🔬 Project Summary
This project presents a data-driven environmental study analyzing **exhaust emissions from industrial generators** across strategic locations in **Ibadan, Nigeria**. Leveraging **Python**, **GIS mapping**, and **regression modeling**, this research reveals the pollutant distribution (CO, CO₂, HC, O₂, and NOx) across major industrial zones — providing insight into **air quality trends** and potential environmental impacts.
This work is a fusion of **environmental science** and **data analytics** — a strong example of how data can power **sustainability decisions**.
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## 📍 Study Area
Ibadan is a major urban city in Southwest Nigeria, home to vibrant industrial activity. Emissions were measured from selected organizations and generator-powered industries across:
- Tollgate Area
- Oluyole Industrial Estate
- Soka Axis
- Ibadan-Lagos Expressway
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## ⚙️ Methodology & Tools
**🔧 Data Collection:**
A KANE Automotive 5-Gas Analyzer was used to measure:
- Carbon Monoxide (CO)
- Carbon Dioxide (CO₂)
- Hydrocarbons (HC in ppm)
- Oxygen (O₂)
- Nitrogen Oxides (NOx in ppm)
**🧪 Sampling Conditions:**
- Conducted in June 2023 (rainy season)
- Each measurement lasted 10 minutes while generators were “on load”
- All generators were tested in triplicate to ensure reliability
**📈 Data Analysis:**
- Python 3.9.12
- Libraries: `pandas`, `seaborn`, `matplotlib`, `scikit-learn`, `geopandas`, `QGIS`, `ArcGIS`
**📊 Statistical & Visual Techniques:**
- Descriptive statistics (mean, median, IQR, outliers)
- Pair plot of numerical features
- Correlation heatmap & regression models
- PCA (Principal Component Analysis)
- Duncan Multiple Range Test
- Spatial distribution maps using GIS
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## 🔍 Ke …
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