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Assessment of the GHG Reduction Potential from Energy Crops Using a Combined LCA and Biogeochemical Process Models: A Review SCI/SSCI论文
Authors:  Jiang D.;  Hao M. M.;  Fu J. Y.;  Wang Q.;  Huang Y. H.;  Fu X. Y.
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Long-term Experiments  Soil Organic-carbon  Greenhouse-gas Flux  Biome-bgc  Climate-change  Boreal Forest  Daycent Model  Marginal Land  Mineral Soils  Fuel Ethanol  
Assessment of the GHG Reduction Potential from Energy Crops Using a Combined LCA and Biogeochemical Process Models: A Review 期刊论文
Authors:  Jiang, Dong;  Hao, Mengmeng(郝蒙蒙);  Fu, Jingying;  Wang, Qiao;  Huang, Yaohuan;  Fu, Xinyu
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Assessment of bioenergy potential on marginal land in China 期刊论文
Bioenergy developed from energy plants will play a more and more important role in future energy supply. Much attention has been paid to energy plants in recent years. As China has fairly limited cultivated land resources, the bioenergy development may mainly rely on the exploitation of marginal land. This study focused on the assessment of marginal land resources and bio-fuel potential in China using newly acquired data and Geographic Information System (GIS) techniques. A multi-factor analysis method was adopted to identify marginal lands for bioenergy development in China, with data of several main types of energy plants on the eco-environmental requirements and natural habits employed. A combined planting zonation strategy was proposed, which was targeted for five species of energy plants including Helianthus tuberous L. Pistacia chinensis. Jatropha curcas L., Cassava and Vernicia fordii. The results indicated that total area of marginal land exploitable for development of energy plants on a large scale was about 43.75 million ha. If 10% of this marginal land was fully utilized for growing the energy plants, the production of bio-fuel would be 13.39 million tons. (C) 2010 Elsevier Ltd. All rights reserved., 2011, 卷号: 15, 期号: 2, 页码: 1050-1056
Authors:  Zhuang, Dafang(庄大方);  Jiang, Dong;  Liu, Lei;  Huang, Yaohuan
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Marginal Land  Bioenergy  Energy Plants  Gis  Remote Sensing