OmotoshoTaiwo/Exhaust-Emissions-Analysis-Ibadan-Nigeria-

Domain:

environment and energy

Creator:

Omo

Host:

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**. --- ## 📍 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 --- ## ⚙️ 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 --- ## 🔍 Ke …

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MIT

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