The project started 01.01.2021 and will end 31.12.2023.

The SEEDS team is made of leading research institutions in air quality in Europe and applied-science SMEs. The project is coordinated by NILU, Norwegian Institute for Air Research. The consortium for SEEDS comprises six partners: two are private non-profit research and technological organizations, one is a SME and three are public research institutions who are bringing into the consortium considerable national resources and operational capabilities.

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The S5p-based biomass burning inventory is derived based on an inversion with the MAGRITTEv1.1 chemistry transport model (Müller et al. 2019) and its adjoint, and are constrained by TROPOMI HCHO vertical columns.

Biomass burning carbon flux

daily biomass burning flux

Basemap

NOx emissions have both strong anthropogenic and biogenic sources, while satellite observations see the total resulting NO2 concentrations. The inversion algorithm DECSO (Daily Emissions Constraint by Satellite Observations) is capable to derive the NOx emissions from the sources based on these satellite observations. In this task the DECSO algorithm is further developed to distinguish between anthropogenic and biogenic emissions.

Daily NOx emissions

Total NOx emissions derived from TROPOMI

Total NOx emissions derived from TROPOMI (alt)

Dry deposition of gases to the land surface is an important sink for reactive trace gases in the troposphere. Understanding dry deposition is of importance for understanding air quality and its impacts on human health and vegetation. SURFEX calculates dry deposition using a software scheme that was recently developed in the SEEDS project (deliverable D3.4). The dry deposition software scheme calculates dry deposition velocities, which can be used as an input to calculate dry deposition fluxes in an air quality model. The dry deposition velocities are provided for ozone, sulphur dioxide, and reactive nitrogen compounds (NOx, ammonia, nitric acid, organic nitrates, and per-nitric acid). All of the dry deposition data are output on an hourly time resolution.

Dry deposition velocities (assimilated data)

Dry deposition velocity of nitric acid

Dry deposition velocity of peroxynitric acid

Dry deposition velocity of nitrous acid

Dry deposition velocity of dinitrogen pentoxide

Dry deposition velocity of ammonia

Dry deposition velocity of nitrogen monoxide

Dry deposition velocity of nitrogen dioxide

Dry deposition velocity of nitrate

Dry deposition velocity of ozone

Dry deposition velocity of ONIT

Dry deposition velocity of PAN

Dry deposition velocity of sulfur dioxide

Dry deposition velocity of TPAN

Dry deposition velocities (open loop)

NOx emissions have both strong anthropogenic and biogenic sources, while satellite observations see the total resulting NO2 concentrations. The inversion algorithm DECSO (DAily Emissions Constraint by Satellite Observations) is capable to derive the NOx emissions from the sources based on these satellite observations. In this task the DECSO algorithm is further developed to distinguish between anthropogenic and biogenic emissions.

High resolution monthly NOx emissions

BVOC gas emissions from vegetation represent a hugely important contributor to the total emission of volatile organic compounds at the global scale. BVOCs in turn play a key role in tropospheric chemistry and impact both the formation of ozone photochemical smog and secondary organic aerosols, which both impact air quality. MEGAN is an open-sourced software package that has been adapted by researchers at NILU to operate with SURFEX model outputs and meteorological data from ECMWF. The MEGAN software calculates emissions of a wide range of BVOCs emitted by plants and aggregates these chemical components into representative chemical species defined in an external chemical mechanism. In our case, this done specifically is for the BVOCs defined (see Table 2 for full list) in the Regional Atmospheric Chemistry Mechanism (Stockwell et al., 1997) that is used in the MOCAGE (Guth et al., 2016) chemical transport model. MOCAGE is being used as the test model the SEEDS project since it is one of the CAMS regional atmospheric chemistry models.

Isoprene emissions (assimilated data)

Isoprene emissions

Isoprene emissions (open loop)

Leaf area index (LAI) is unitless measure of the total area of leaves per unit ground area (e.g., an LAI of 1 equates to 1 m2 of leaf area above 1 m2 of ground area), which can be a vital variable for predicting primary production of plants and evapotranspiration. The LAI data in SEEDS are calculated by the SURFEX land surface model. The seasonal changes in vegetation growth and senescence are simulated in a dynamic way by the model taking into account vegetation type, sunlight, and meteorological conditions that affect the growing season. The LAI is calculated over different vegetation types separately and are then spatially averaged to combine them into a single LAI for all natural surface types in the SURFEX model.

Leaf Area Index (assimilated data)

Leaf area index

Leaf Area Index (open loop)

Monthly emissions by the DECSO algorithm from CRIS observation.

Monthly NH3 emissions

NH3 emissions dervied from OMI

Monthly NOx emissions

Anthropogenic NOx emissions derived from TROPOMI

Anthropogenic NOx emissions derived from TROPOMI (alt)

Biogenic NOx emissions derived from TROPOMI

Biogenic NOx emissions derived from TROPOMI (alt)

Dry deposition of gases to the land surface is an important sink for reactive trace gases in the troposphere. Understanding dry deposition is of importance for understanding air quality and its impacts on human health and vegetation. SURFEX calculates dry deposition using a software scheme that was recently developed in the SEEDS project (deliverable D3.4). The dry deposition software scheme calculates dry deposition velocities, which can be used as an input to calculate dry deposition fluxes in an air quality model. The dry deposition velocities are provided for ozone, sulphur dioxide, and reactive nitrogen compounds (NOx, ammonia, nitric acid, organic nitrates, and per-nitric acid). In addition to the dry deposition velocities, SURFEX calculates various diagnostics to help understand the deposition of pollutants into the vegetation leaf canopy (in-canopy resistance) and into their stomata (stomatal resistance). All of the dry deposition data are output on an hourly time resolution.

Stomatal and in-canopy resistances (assmililated data)

Stomatal resistance (spatially averaged)

In-canopy resistance (spatially averaged)

Stomatal and in-canopy resistances (open loop)

The S5p-based top-down biogenic emission inventory is derived based on an inversion with the MAGRITTEv1.1 chemistry transport model (Müller et al. 2019) and its adjoint, and are constrained by TROPOMI HCHO vertical columns.

Top down isoprene emissions

daily isoprene emission fluxes

Soil moisture (assimilated data)

Soil liquid water content (surface)

Soil liquid water content (root zone)

Soil solid water content (surface)

Soil solid water content (root zone)

Total volumetric water content

Soil moisture (open loop)

We are a scientific partnership

Anthropogenic Emissions

Biogenic Emissions

Deposition Fluxes

Improved assimilation algorithm

The SEEDS team is made of leading research institutions in air quality in Europe and applied-science SMEs.

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Improved CAMS products

Stakeholder Engagement