Estimation of Air Pollution with Remote Sensing Data: Revealing Greenhouse Gas Emissions from Space, presented at Tackling Climate Change with Machine Learning workshop at ICML 2021.
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Updated
Dec 3, 2021 - Python
Estimation of Air Pollution with Remote Sensing Data: Revealing Greenhouse Gas Emissions from Space, presented at Tackling Climate Change with Machine Learning workshop at ICML 2021.
Code repository for "Toward Global Estimation of Ground-Level NO2 Pollution With Deep Learning and Remote Sensing", IEEE TGSRS, 2022
Arduino project on a ESP32 for NO2 measurement sending the data with LoRaWan to TheThingsNetwork.
Python scripts and Jupyter Notebooks to download and preprocess Sentinel-5P NO2 data.
Python script downloading NO2 pollution datas from the European satellite Sentinel5 and aggregating by country, regions, states, cities. This work is carried out within the framework of the juanporrasl/AMSECovid19 project.
Website (startpage and map)
This Python script processes nitrogen dioxide (NO2) satellite data by extracting relevant information based on geographical conditions, interpolating values using a KD-tree algorithm, and aggregating monthly averages. The resulting data is stored in NetCDF files for further analysis.
air quality model benchmarking
MICS4514 Breakout board sensor for CO2 and NO2 only 3.3v
Some notebooks for [S5P-LNO2](https://github.com/zxdawn/S5P-LNO2).
This is a COVID-19 Air Pollution tracking program that looks at the correlation between COVID-19 Lockdowns and the overall pollution impact in certain European cities. The program utilses graphs and other visual stats to allow visual representations of significant or minimal difference in pollution levels with as a result to the on going pandemic.
Satellite observations showed a negligible reduction in NO2 pollution due to COVID-19 lockdown over Poland
Scripts for urban NO2 air quality analysis. Funded by the Air, Climate, and Health Lab at George Washington University
Australia SA3-level analysis of relationship between child mortality/morbidity and climate conditions/air pollution
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