Literature DB >> 28343863

Emerging role of Geographical Information System (GIS), Life Cycle Assessment (LCA) and spatial LCA (GIS-LCA) in sustainable bioenergy planning.

Moonmoon Hiloidhari1, D C Baruah2, Anoop Singh3, Sampriti Kataki4, Kristina Medhi5, Shilpi Kumari6, T V Ramachandra7, B M Jenkins8, Indu Shekhar Thakur9.   

Abstract

Sustainability of a bioenergy project depends on precise assessment of biomass resource, planning of cost-effective logistics and evaluation of possible environmental implications. In this context, this paper reviews the role and applications of geo-spatial tool such as Geographical Information System (GIS) for precise agro-residue resource assessment, biomass logistic and power plant design. Further, application of Life Cycle Assessment (LCA) in understanding the potential impact of agro-residue bioenergy generation on different ecosystem services has also been reviewed and limitations associated with LCA variability and uncertainty were discussed. Usefulness of integration of GIS into LCA (i.e. spatial LCA) to overcome the limitations of conventional LCA and to produce a holistic evaluation of the environmental benefits and concerns of bioenergy is also reviewed. Application of GIS, LCA and spatial LCA can help alleviate the challenges faced by ambitious bioenergy projects by addressing both economics and environmental goals.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Agro-residue biomass; Bioenergy; Geographical Information System; Life Cycle Assessment; Spatial LCA

Mesh:

Substances:

Year:  2017        PMID: 28343863     DOI: 10.1016/j.biortech.2017.03.079

Source DB:  PubMed          Journal:  Bioresour Technol        ISSN: 0960-8524            Impact factor:   9.642


  3 in total

1.  Comparative analysis on environmental and economic performance of agricultural cooperatives and smallholder farmers: The case of grape production in Hebei, China.

Authors:  Lei Deng; Lei Chen; Jingjie Zhao; Ruimei Wang
Journal:  PLoS One       Date:  2021-01-25       Impact factor: 3.240

2.  Prediction of global marginal land resources for Pistacia chinensis Bunge by a machine learning method.

Authors:  Shuai Chen; Mengmeng Hao; Yushu Qian; Fangyu Ding; Xiaolan Xie; Tian Ma
Journal:  Sci Rep       Date:  2022-04-07       Impact factor: 4.379

Review 3.  A consolidated review of commercial-scale high-value products from lignocellulosic biomass.

Authors:  Bo Zheng; Shengzhu Yu; Zhenya Chen; Yi-Xin Huo
Journal:  Front Microbiol       Date:  2022-08-23       Impact factor: 6.064

  3 in total

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