Skip to main content
Dryad logo

Input data to model multiple effects of large-scale deployment of grass in crop-rotations at European scale

Citation

Englund, Oskar (2022), Input data to model multiple effects of large-scale deployment of grass in crop-rotations at European scale, Dryad, Dataset, https://doi.org/10.5061/dryad.18931zd1m

Abstract

This is the input dataset to a Python script (https://github.com/oskeng/MF-bio-grass) used to model the effects of widespread deployment of grass in rotations with annual crops to provide biomass while remediating soil organic carbon (SOC) losses and other environmental impacts.

For more information about the dataset and the study, see the original article:

Englund, O., Mola-Yudego, B., Börjesson, P., Cederberg, C., Dimitriou, I., Scarlat, N., Berndes, G. Large-scale deployment of grass in crop rotations as a multifunctional climate mitigation strategy. GCB Bioenergy

Methods

See original article:

Englund, O., Mola-Yudego, B., Börjesson, P., Cederberg, C., Dimitriou, I., Scarlat, N., Berndes, G. Large-scale deployment of grass in crop rotations as a multifunctional climate mitigation strategy. GCB Bioenergy

Preprint:

Englund, O., Mola-Yudego, B., Börjesson, P., Cederberg, C., Dimitriou, I., Scarlat, N., Berndes, G., (2022). Large-scale deployment of grass in crop rotations as a multifunctional climate mitigation strategy. EarthArXiv. Sept. 23. https://doi.org/10.31223/X5KW5J

Usage Notes

The data file (Geopackage) can be opened using standard GIS software, preferably GRASS GIS or QGIS (both open source).

This dataset is intended as input to a Python script (https://github.com/oskeng/MF-bio-grass) that must be run from within a GRASS GIS session.

Funding

Swedish Energy Agency, Award: P48364-1

f3 Swedish Knowledge Centre for Renewable Transportation Fuels, Award: P48364-1

IEA Bioenergy