Python scripts to download and preprocess air pollution concentration level data aquired from the Sentinel-5P mission

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This project aims to analyze and visualize Nitrogen Dioxide (NO₂) levels across various community districts using Python. Nitrogen Dioxide is a major air pollutant that can severely affect human health and the environment. Monitoring its levels at a local scale is crucial for understanding pollution patterns.

A data science project analyzing air pollution trends using Python libraries

Air Quality Index data analysis using Python for pollution trend identification and visualization.

Code Repository for Environmental Insights, a python package for the accessing and analytics of ambient air pollution concentration data.

A Python module to import data from the UK Automatic Urban Rural Network (air pollution monitoring network)

This project generates synthetic spatiotemporal PM2.5 and PM10 air quality data, visualizing pollution trends over time and space using Python. It demonstrates environmental data analysis techniques for urban air quality monitoring and modeling, aiding research, decision-making, and awareness in environmental health.

This project focuses on analyzing real-time air quality data from various Indian cities and states using Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn. It aims to provide insights into the pollution levels, identify the most affected regions, and visualize pollutant trends.

📊 Real-Time Air Quality Index (AQI) Analysis A Python project analyzing global air quality data using Pandas, Matplotlib, and Seaborn. It identifies pollution trends, high-risk areas, and time-based patterns for pollutants like PM2.5, NO₂, SO₂, and more.

air-pollution prediction using multivariate regression with python

Exploratory Data Analysis (EDA) project on air quality data using Python libraries such as NumPy, Pandas, Matplotlib, and Seaborn to uncover trends, distributions, correlations, and pollution patterns through statistical analysis and visualizations.

Web scraping of www.openaq.org for open source data to collect air pollution data. Tools used - Selenium Python.

Program to extract data from TROPOMI Satellite and creating a Heat Map using Python to detect and analyze the Hotspots(due to Air Pollution) in India.

Impact of Air Pollution on our Lives( Pre Corona [2016 to 2020] from Data available at kaggle ) analysis using python

Air Pollution Analysis and Prediction using Python and Machine Learning. Built an end-to-end pipeline including data preprocessing, exploratory data analysis, and multiple regression models (Linear Regression, KNN, Decision Tree, Random Forest) to predict average pollution levels and compare model performance.

Air pollution simulation written in Python

Python package for visualising future, historic and current air pollution data

Exploratory Data Analysis (EDA) and visualization of air pollution data across major Indian cities using Python. Includes data cleaning, outlier detection, time-series analysis, and visual insights using Seaborn and Matplotlib to reveal pollutant trends and seasonal variations.

Air Pollution Measuring Using IoT & Data Visualization Using Python ML

Air Quality Insight is a Python-based tool that retrieves real-time air quality data from the World Air Quality Index API and visualizes pollution levels for any specified city. By analyzing key pollutants such as PM2.5, PM10, NO2, SO2, O3, and Dew Point, this tool provides valuable insights into air quality trends

This project analyzes Air Quality Index (AQI) data to understand pollution trends. It includes data visualization, analysis of key pollutants, seasonal variations, and insights into air quality improvements or concerns. Built using Python, with libraries like Pandas and Matplotlib.

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Python script that reads air pollution data from api.luftdaten.info and sends email alerts.

Analyzed U.S. air quality data using Python and machine learning to identify pollution trends, predict air quality levels, and classify regions using regression, clustering, and PCA.

🌎 — EcoData: Environmental Analytics System is a unique Python + SQL Data Analytics project that uses environmental data (like air quality, temperature, and pollution) to generate insights and visualizations.

This project focuses on analyzing and visualizing Air Quality Index (AQI) data using Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn. The aim is to extract meaningful patterns, identify pollution trends, and generate insightful visualizations to better understand air quality dynamics over time.

End-to-end data engineering and analytics project for urban air pollution monitoring. Built a raw-to-clean-to-curated ETL pipeline using Python and Pandas, performed SQL-based analytics with SQLite, and developed an interactive Power BI dashboard to analyze PM2.5 trends, extremes, and time-based patterns.

Air Pollution Based Routing System developed using Python and Linear Regression.

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