Reprint
Renewable Energy Production from Energy Crops and Agricultural Residues
Edited by
August 2021
336 pages
- ISBN978-3-0365-0106-2 (Hardback)
- ISBN978-3-0365-0107-9 (PDF)
This book is a reprint of the Special Issue Renewable Energy Production from Energy Crops and Agricultural Residues that was published in
Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary
Energies is open to submissions for a Special Issue on “Renewable Energy Production from Energy Crops and Agricultural Residues”. Biomass represents an important source of renewable and sustainable energy production. Its increasing consumption is mainly related to the increase in global energy demand and fossil fuel prices, but also to a lower environmental impact compared to non-renewable fuels. These factors take RED II directives into consideration. In the past, forestry interventions were the main supply source of biomass, but in recent decades two others sources have entered the international scene. These are dedicated energy crops and agricultural residues, which are important sources of biomass for biofuel and bioenergy. Below, we consider four main value chains: • Oil crops: Oil production from non-food oilseed crops (such as camelina, Crambe, safflower, castor, cuphea, cardoon, etc.), oil extraction, and oil utilization for fuel production. • Lignocellulosic crops: Biomass production from perennial grasses (miscanthus, giant reed, switchgrass, reed canary grass, etc.), woody crops (willow, poplar, Robinia, eucalyptus, etc.), and agricultural residues (pruning, maize cob, maize stalks, wheat chaff, sugar cane straw, etc.), considering two main transformation systems: 1. Electricity/heat production 2. Second-generation ethanol production • Carbohydrate crops (cereals, sweet sorghum, sugar beets, sugar cane, etc.) for ethanol production. • Fermentable crops (maize, barley, triticale, Sudan grass, sorghum, etc.) and agricultural residues (chaff, maize stalks and cob, fruit and vegetable waste, etc.) for production of biogas and/or biomethane.
Format
- Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
bioenergy; crop by-products; harvesting methods; maize cob; wheat chaff; combine harvesting; olive groves; pruning; stationary chipper; harvesting system; hog fuel; pruning supply chain; populus; biomass; yield energy value; lower heating value; ash content; sulphur; biomass; bioenergy; circular bioeconomy; oil crops; agricultural residues; thermophysical and chemical features; wheat; straw; weed seed; biocommodity; threshing; bioenergy; pruning harvesting; olive groves; biomass quality; slope; work productivity; bioresource; cereals; commodity; harvest index; staple foods; triticum; wheat; Miscanthus x giganteus; bioenergy; environmental impact; agricultural production; circular bioeconomy; digestate; eucalyptus; woody biomass; storage of fine wood chips; moisture content; calorific value; ash content; dry matter loss; Eucalyptus; tree whole stem; firewood logs; storage system; moisture content; dry matter loss; renewable energy; pruning; harvesting; slope; suitable areas; Central Italy; Corine Land Cover; short rotation coppice; Salix; genotype × site interaction; ash content; lower heating value; nitrogen content; sulphur content; willow biomass; soil organic carbon; life cycle assessment; spatial analysis; greenhouse gas emissions; energy return on investment; lignocellulosic biomass; hydrothermal pretreatment; enzymatic hydrolysis; sugar yield; high-performance liquid chromatography (HPLC) analysis; externalities; economic analysis; willow biomass production; new varieties; sustainable production; renewable energy sources; straw; biofuels; agriculture residues; forecasting; modelling; Poland; bioenergy; oil crops; work performance; harvesting loss; fuelwood; cable yarder; CO2 emission; pine plantations; time study; energy efficiency; agroenvironmental mapping; energy crop; Jatropha curcas L.; land suitability; bio-based supply chains; integrated biomass logistical center; mixed integer programming model