Publication Details

Category Text Publication
Reference Category Journals
DOI 10.3390/en13246488
Licence creative commons licence
Title (Primary) A method for assessing regional bioenergy potentials based on GIS data and a dynamic yield simulation model
Author Bao, K.; Padsala, R.; Coors, V.; Thrän, D.; Schröter, B.
Source Titel Energies
Year 2020
Department BIOENERGIE
Volume 13
Issue 24
Page From art. 6488
Language englisch
Keywords potential analysis; geographical information system (GIS); bioenergy; AquaCrop
Abstract The assessment of regional bioenergy potentials from different types of natural land cover is an integral part of simulation tools that aim to assess local renewable energy systems. This work introduces a new workflow, which evaluates regional bioenergy potentials and its impact on water demand based on geographical information system (GIS)-based land use data, satellite maps on local crop types and soil types, and conversion factors from biomass to bioenergy. The actual annual biomass yield of crops is assessed through an automated process considering the factors of local climate, crop type, soil, and irrigation. The crop biomass yields are validated with historic statistical data, with deviation less than 7% in most cases. Additionally, the resulting bioenergy potentials yield between 10.7 and 12.0 GWh/ha compared with 13.3 GWh/ha from other studies. The potential contribution from bioenergy on the energy demand were investigated in the two case studies, representing the agricultural-dominant rural area in North Germany and suburban region in South Germany: Simulation of the future bioenergy potential for 2050 shows only smaller effects from climate change (less than 4%) and irrigation (below 3%), but the potential to cover up to 21% of the transport fuels demand in scenario supporting biodiesel and bioethanol for transportation.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=24006
Bao, K., Padsala, R., Coors, V., Thrän, D., Schröter, B. (2020):
A method for assessing regional bioenergy potentials based on GIS data and a dynamic yield simulation model
Energies 13 (24), art. 6488 10.3390/en13246488