Note: This Generation 1 Collection has been superseded by Generation 2 Simulation-level Collections

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This dataset provides surface-level particulate matter (PM2.5 and PM10) concentrations derived from in situ low-cost sensor (LCS) measurements, produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) in the context of the Horizon Europe All Data for Green Deal project. This dataset differs from existing air quality datasets by combining crowdsourced observations with a robust correction framework, producing high-resolution, reference-aligned gridded products.

calendar_today Interval/period: Mon, 01/01/2018 - Tue, 12/31/2024

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The nextGEMS data is aligned with the Climate Change Adaptation Digital Twin. The DestinE Digital Twin for Climate Change Adaptation (Climate DT) supports adaptation activities by providing innovative climate information on multi-decadal timescales, globally, at scales at which many impacts of climate change are observed.

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The nextGEMS data is aligned with the Climate Change Adaptation Digital Twin. The DestinE Digital Twin for Climate Change Adaptation (Climate DT) supports adaptation activities by providing innovative climate information on multi-decadal timescales, globally, at scales at which many impacts of climate change are observed.

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This dataset provides daily air quality analyses and forecasts for Europe.
CAMS produces specific daily air quality analyses and forecasts for the European
domain at significantly higher spatial resolution (0.1 degrees, approx. 10km)
than is available from the global analyses and forecasts. The production is
based on an ensemble of eleven air quality forecasting systems across Europe. A
median ensemble is calculated from individual outputs, since ensemble products

calendar_today Interval/period: Tue, 06/27/2023 - Wed, 07/01/2026

This dataset provides daily air quality forecasts at European observation
stations after optimisation using a statistical post-processing method called
Model Output Statistics (MOS). The unoptimised "raw" forecasts are also
provided in the same format.
The MOS method uses machine learning with predictive variables including
background air quality observation datasets, ECMWF meteorological forecasts and
the "raw" CAMS European air quality ensemble median forecast. The result is

calendar_today Interval/period: Wed, 01/17/2024 - Wed, 07/01/2026

CAMS produces global forecasts for atmospheric composition twice a day. The forecasts consist of more than 50 chemical species (e.g. ozone, nitrogen dioxide, carbon monoxide) and seven different types of aerosol (desert dust, sea salt, organic matter, black carbon, sulphate, nitrate and ammonium aerosol). In addition, several meteorological variables are available as well.

calendar_today Interval/period: Thu, 01/01/2015 - Wed, 07/01/2026

CAMS produces global forecasts for the two main long-lived greenhouse gases once a day. This dataset consists of 5-day high-resolution forecasts of carbon dioxide (CO2) and methane (CH4). Additionally, carbon monoxide (CO) and meteorological parameters relevant to the CAMS greenhouse gas forecast are included.

calendar_today Interval/period: Fri, 03/01/2024 - Wed, 07/01/2026