Bottom up isoprene emissions (open loop)

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Data type
Horizontal coverage
Europe (west=25.0° W, east=45.0° E, south=30.0° N, north=70.0° N)
Horizontal resolution
0.1° x 0.1°
Temporal resolution
Temporal coverage
MEGANv3 coupled with the SURFEX land surface model
File format

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Isoprene 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.


NILU - CNRM. (2024). Bottom up isoprene emissions (open loop) [Data set]. Zenodo.

Download instructions


This sample Python code shows how to download this dataset, create subsets of it and save them as NetCDF, using the Xarray library.

import xarray as xr import fsspec # Open remote dataset ds = xr.open_zarr( store=fsspec.get_mapper("") ) # Subset a time range, save as NetCDF time_subset = ds.emiss.sel(time=slice('2019-06-01', '2019-07-01')) time_subset.to_netcdf('./') # Subset a time and geographical range, save as NetCDF time_geo_subset = ds.emiss.sel(time=slice('2019-06-01', '2019-07-01'), latitude=slice(40, 43), longitude=slice(0,3.5)) time_geo_subset.to_netcdf('./')