Agro-ecosystem modeling can aid in the optimization of biomass feedstock supply. (November 2016)

• Record Type: Journal Article
• Authors: Dufossé, Karine; Drouet, Jean-Louis; Gabrielle, Benoît
• Is Part Of: Environmental modelling & software. Volume 85(2016:Nov.)
• Page Start: 139
• Page End: 155
• Publication Date: 2016-11
• Subjects: Lignocellusic biomass -- Miscanthus -- Agroecosystem modeling -- CERES-EGC -- Bioethanol; CAP common agricultural policy -- DM dry matter -- GCM general circulation model -- GHG greenhouse gas -- GIS geographical information system -- GWP global warming potential -- LCA life cycle assessment -- LUC land use change -- RED renewable energy directive -- SU simulation unit -- UAL utilized agricultural land; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2016.07.014
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Recent European Directives promoted the development of biofuels, requesting mandatory limits to their emissions ot greenhouse gases (GHG). Second-generation biofuels based on lignocellulosic biomass are prime candidates but their GHG emissions are variable and uncertain. Agro-ecosystem modeling can capture them and the performance of biofuel feedstocks. This study aimed at optimizing feedstock supply for a bioethanol unit in France, from agricultural residues, annual and perennial crops. Their productivity and environmental impacts were modelled on a regional scale using geo-referenced data on soil properties, crop management, land-use and future weather data. Several supply scenarios were tested. Cereal straw was the most efficient feedstock but had a low availability, and only miscanthus could meet the bioethanol plant's demand. Sorghum combined poor yields and high GHG emissions compared by miscanthus and triticale. A mix of three biomass sources used less than 3% of the regional agricultural land while abating GHG emissions by 60%. Highlights: The production of biomass and its environmental impacts can be mapped with agro-ecosystem models. Variability in soil and climate conditions can be used to optimize biomass supply mixes. Appropriate selection of feedstocks mitigates the carbon-intensity of biofuels. Perennial crops and agricultural residues out-perform annual crops, but their availability is limited. Relying on multiple biomass feedstock sources is recommended.