INTRODUCTION

The  International  Renewable Energy Agency (IRENA) indicates that by  2030 biomass would comprise 20% of the global primary energy  supply,  doubling  its   share  from  10%  in   2010  (IRENA, 2015). The prospect of agro-residue as prominent global bioenergy provider is also  very  high in  the near future. Global agro-residue availability is  estimated to  be  3.6–17.2 billion tonnes with an equivalent energy potential of 13.1–122 EJ (WBA, 2015). Some  dis- tinct advantages of agro-residue as energy source are: (i) suitable feedstock for  heat and power and transportation fuel  production, (ii) generation of wide range of by-products with potential for fur- ther valorization through the biorefinery process, (iii)  a  carbon neutral or low carbon fuel that emits less carbon dioxide than fossil fuels in its life cycle,  (iv) scope for development of bioenergy based entrepreneurial  activities, (v)  feasibility of  generating decentral- ized  mode of energy to  empower remote areas.

Agro-residues are  geographically distributed with variation in spatio-temporal availability. For viable commissioning of biomass power plant, prior and precise database of  residue distribution, seasonal fluctuation (peak and lean period of  availability) is  a pre-requisite. Logistics such as residue harvest, collection, storage, transportation are  spatially interlinked and need meticulous plan- ning. Adequacy, precision, reliability of data collected through tra- ditional  methods   (survey  or    secondary   data   collection)  for bioenergy planning is  a  matter of  question, which often lead to over  or  under estimation of potentially accessible energy source. Therefore, energy and environmental  assessment  need decision support  system  (DSS)   for   effective  planning  (Sacchelli et  al.,2013). Spatial tools are  able   to  relate large scale environmental assessment with medium and small scale DSS, useful for  decision makers. Geographical Information  System (GIS)  is  an  important decision making spatial tool  which aids  precise assessment of dis- tributed  renewable  energy  resources  (Yue   and  Wang, 2006; Angelis-Dimakis et al.,  2011; Ramachandra et al.,  2005). Review of the potential applications of GIS in agro-residue bioenergy plan- ning is one  of the objectives of this paper.

The climate change mitigation benefit of bioenergy has  become a  much debatable issue in  recent times because of  the limited information  on   the  direct  and  indirect  environmental  conse- quences of bioenergy. It is  expressed that unsustainable produc- tion or  over-exploitation of  bioenergy feedstock may exacerbate greenhouse gas emissions and jeopardize many ecosystem services (Fargione et al.,  2008; Searchinger et al.,  2008; Danielsen et al.,2009; Lapola  et al., 2010; Liska et al., 2014). Large scale cultivation of  bioenergy crops can  lead to  the so-called food  vs. fuel  debate (Tilman et al., 2009). Loss of carbon pools and carbon sequestration dynamics may occur from the  conversion of  land to  bioenergy cropland, which can  only  be  balanced by  bioenergy crops in hun- dreds of years (Gibbs et al., 2008). In this regard, Life Cycle Assess- ment (LCA) based investigation of possible environmental implications of  bioenergy production is  critical to  avoid decline of existing carbon stocks (Cherubini et al., 2009). A review of the applications of LCA in agro-residue bioenergy is another objective of this paper. GIS and LCA differs from each other in the sense that, the former is used for spatial data acquisition, storage, processing and visual- ization, while LCA is not,  but they are complementary to each other(Gorniak-Zimroz and Pactwa, 2015). Certain impacts of bioenergy (e.g. impact on  biodiversity) are  spatially allocated due to  the dis- tributed nature of biomass feedstocks. Current LCA measures are inadequate to  spatially account such impacts. The  integrated use of GIS and LCA (hereafter termed as spatial LCA) could address such issues by allocating the impacts into spatial units (Bengtsson et al.,
1998; Geyer et al.,  2010; Gasol  et al.,  2011; Gorniak-Zimroz and Pactwa, 2015). Spatial LCA is  an  emerging research field  and the discussion of current development in  this field  is also  one  of the objectives of the paper.

In line  with the above discussion, the present paper reviews the potential applications of  GIS, LCA and spatial LCA in  sustainable planning of residue-based bioenergy program. The review includes a discussion on the role  of GIS in biomass resource assessment, bio- mass logistics planning and bioenergy power plant  design. The review also  highlights the application of LCA in evaluation of envi- ronmental performance of  agro-residue  bioenergy systems.  The uncertainties associated with LCA study and measures to  address them are also reviewed. Further, the importance and potential ben- efits  of integrating GIS into LCA platform (spatial LCA) for  bioen- ergy  planning are  also  reviewed.  It is  expected that, analysis of the aspects about the significance and practical relevance of GIS, LCA and spatial LCA tool  covered in  this study will  be  helpful in making informed decisions about future directions for  bioenergy planning, research and development.