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Integrated spatiotemporal modelling of bioenergy production potentials, agricultural land use, and related GHG balances; demonstrated for Ukraine
Author(s) -
van der Hilst Floor,
Verstegen Judith A.,
Zheliezna Tetiana,
Drozdova Olga,
Faaij André P.C.
Publication year - 2014
Publication title -
biofuels, bioproducts and biorefining
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.931
H-Index - 83
eISSN - 1932-1031
pISSN - 1932-104X
DOI - 10.1002/bbb.1471
Subject(s) - greenhouse gas , bioenergy , environmental science , agricultural land , agriculture , land use, land use change and forestry , land use , scenario analysis , biofuel , production (economics) , agricultural productivity , fossil fuel , natural resource economics , environmental engineering , agricultural economics , economics , waste management , engineering , geography , ecology , civil engineering , macroeconomics , archaeology , finance , biology
This study shows how bioenergy potential and total greenhouse gas ( GHG ) balances of land‐use change and agricultural intensification can be modeled in an integrated way. The modeling framework is demonstrated for first‐ and second‐generation ethanol production in Ukraine for the timeframe 2010–2030 for two scenarios: a business as usual ( BAU ) scenario in which current trends in agricultural productivity are continued; and a progressive scenario, which projects a convergence of yield levels in Ukraine with Western Europe. The spatiotemporal development in land for food production is analyzed making use of the PCRaster Land Use Change ( PLUC ) model. The land‐use projections serve as input for the analysis of the CO 2 , N 2 O , and CH 4 emissions related to changes in land use and agricultural management, as well as the abatement of GHG emissions by replacing fossil fuels with bioethanol production from wheat and switchgrass. This results in annual maps (1 km 2 resolution) of the different GHG emissions for the modeled timeframe. In the BAU scenario, the GHG emissions increase over time, whereas in the progressive scenario, a total cumulative GHG emission reduction of 0.8 Gt CO 2 ‐eq for wheat and 3.8 Gt CO 2 ‐eq for switchgrass could be achieved in 2030. When the available land is used for the re‐growth of natural vegetation, 3.5 Gt CO 2 ‐eq could be accumulated. These emission reductions could increase when appropriate measures are taken. The spatiotemporal PLUC model + GHG module allows for spatiotemporal and integrated modeling of total GHG emissions of bioenergy production and intensification of the agricultural sector. © 2014 Society of Chemical Industry and John Wiley & Sons, Ltd