The CMS is a multiscale stochastic Lagrangian framework developed by Paris' Lab at the Rosenstiel School of Marine, Atmospheric & Earth Science to study complex behaviors, giving probabilistic estimates of dispersion, connectivity, fate of pollutants, and other Lagrangian phenomena. This repository facilitates community contributions to CMS modules

I predict air quality index of a city in China using a Long Short Term Memory (LSTM) neural network. for a year. Executed time series analysis

The rebirth of IMPACT World+ in a fully automated and transparent fashion.

This is the repository file of HydroPol2D Model

Research Paper on the prediction of pollutants concentration in Lille using Machine Learning Methods

Ivan Ricart Borges - Pseudo real-time OPC service that reads 328 pollutant tags every minute from a remote OPC server, then implements the IT020 specification of the XEAC (Network Atmospheric Emissions of Catalonia) by creating some plain text files following the established pattern. Using Microsoft DCOM technology for the exchange of informatio…

Weatemp is a weather app that runs both as a website and as a app on a mobile or desktop device. Weatemp displays information about the current weather, the weather for the next 5 days, the current air pollution, and the air pollution for the next 4 days. Information is displayed for your exact location and any selected city in the world.

A project for handling the European Pollutant Release and Transfer Register (E-PRTR) data and publishing it as a national web service

Three AQ Mesh air quality measuring devices were installed for the EmBaLu research project at RWTH Aachen University on emission-based ventilation control in road tunnels. This API was created for automated retrieval of the measured pollutant concentrations.

Analysis of Air Pollutants in the years 2015-2020